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Jiun-Ling Wang,1,* Chih-Feng Kuo,2,* Che-Ming Yeh,3 Jung-Ren Chen,4 Ming-Fang Cheng,5–7 Chih-Hsin Hung3 1Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan, ROC; 2Department of Nursing, I-Shou University, Kaohsiung, Taiwan, ROC; 3Department of Chemical Engineering and Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan, ROC; 4Department of Biological Science and Technology, I-Shou University, Kaohsiung, Taiwan, ROC; 5Department of Pediatrics, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan, ROC; 6School of Medicine, Faculty of Medicine, National Yang-Ming University, Taipei, Taiwan, ROC; 7Department of Nursing, Fooyin University, Kaohsiung, Taiwan, ROC *These authors contributed equally to this work Purpose: Few effective antibiotics are available for treating extensively drug-resistant Acinetobacter baumannii (XDRAB) sepsis. Phage therapy may show potential in treating XDRAB infections. Materials and methods: We studied ϕkm18p phage therapy in BALB/c and C57BL/6 mice models of XDRAB bacteremia. Results: We observed survival rates of nearly 100% in groups given phage therapy concurrent with XDRAB at different multiplicities of infection. In mice that received phage therapy after a 1-hour delay, the survival rate decreased to about 50%. The bacterial load in the blood decreased from 108 to 102 and 103 colony-forming units (CFU)/mL in the concurrent treatment group. In the phage therapy group, the levels of the cytokines, such as tumor necrosis factor alpha (TNF-α) and interleukin-6 (IL-6), were low at 3 hours after infection. Although some phage-resistant mutants were isolated after phage therapy, a cytotoxicity study showed that they had reduced fitness. Conclusion: Phage therapy in XDRAB bacteremia increased the animal survival rates, decreased the bacteremia loads, and decreased the levels of inflammatory markers TNF-α and IL-6. However, the reduced therapeutic effect with delayed administrations may be a concern in developing a successful phage therapy for treating acute infections of multidrug-resistant pathogens. Keywords: Acinetobacter baumannii, survival rates, bacteria, multiple antimicrobial drug resistance, phage therapy

Chang-Fu Kuo,1,2,* I-Jun Chou,3,4,* Matthew J Grainge,5 Shue-Fen Luo,2 Lai-Chu See,2,6,7 Kuang-Hui Yu,2 Weiya Zhang,1 Michael Doherty,1 Ana M Valdes1 1Division or Rheumatology, Orthopaedics and Dermatology, School of Medicine, University of Nottingham, Nottingham, UK; 2Division of Rheumatology, Allergy and Immunology, Chang Gung Memorial Hospital, Taoyuan, Taiwan; 3Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK; 4Division of Paediatric Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan; 5Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, Nottingham, UK; 6Biostatistics Core Laboratory, Molecular Medicine Research Centre, Chang Gung University, Taoyuan, Taiwan; 7Department of Public Health, College of Medicine, Chang Gung University, Taoyuan, Taiwan *These authors contributed equally to this work Purpose: To estimate the extent of familial aggregation of type 1 diabetes (T1D) and coaggregation of related chronic diseases and assess the relative contribution of environmental and genetic factors on the risks.Patients and methods: This population-based study used the Taiwan National Health Insurance database to reconstruct family structure and identify people with T1D and other chronic diseases between 1999 and 2015. Relative risks (RRs) for T1D and other chronic diseases and heritability of T1D were estimated. Heritability was estimated using the polygenic liability model.Results: Validation of family structure found the positive predictive value to be 98.7% for maternal links and 98.6% for paternal links. Having an affected twin, first-degree relative, or spouse was associated with an adjusted RR (95% CI) of 553.66 (427.59–716.89), 32.49 (28.66–36.84), and 2.17 (0.31–15.40) for T1D, respectively. Based on the polygenic liability model, heritability, shared and non-shared contributions to T1D, and variances were 66.50%, 10.86%, and 22.64%, respectively. A family history of T1D was associated with an RR (95% CI) of 1.51 (1.20–1.89) for rheumatoid arthritis, 1.66 (1.21–2.26) for Sjögren’s syndrome, 1.48 (1.09–2.01) for systemic lupus erythematosus, 1.24 (1.14–1.35) for simple goiter, 1.16 (1.04–1.31) for non-toxic nodular goiter, 1.61 (1.49–1.74) for thyrotoxicosis, 1.78 (1.57–2.01) for acquired hypothyroidism, 1.66 (1.40–1.98) for thyroiditis, and 1.15 (0.97–1.37) for epilepsy.Conclusion: These data highlight the importance of the genetic contribution to T1D and confirm the coaggregation of autoimmune and metabolic diseases with T1D. Keywords: type 1 diabetes mellitus, familial aggregation, co-aggregation, autoimmune diseases, endocrine diseases

Yung-Fong Tsai,1,2,* Fu-Chao Liu,1,2,* Chang-Fu Kuo,3,4 Ting-Ting Chung,3 Huang-Ping Yu1,2,5 1Department of Anesthesiology, Chang Gung Memorial Hospital, Taoyuan, Taiwan; 2College of Medicine, Chang Gung University, Taoyuan, Taiwan; 3Division of Rheumatology, Allergy and Immunology, Chang Gung Memorial Hospital, Taoyuan, Taiwan; 4Office for Big Data Research, Chang Gung Memorial Hospital, Taoyuan, Taiwan; 5Department of Anesthesiology, Xiamen Chang Gung Hospital, Xiamen, China *These authors contributed equally to this work Background: Immunosuppression plays an essential role to overcome immune-related allograft rejection, but it also causes some nephrotoxicity. This study aimed to investigate how the immunosuppressant combinations affect graft outcomes in kidney transplant recipients. Methods: A nationwide population-based cohort study using the Taiwan National Health Insurance Database was conducted. A total of 3,441 kidney transplant recipients who underwent kidney transplantation during the targeted period were included. The effects on graft outcomes contributed by conventional immunosuppressants, including corticosteroid, calcineurin inhibitors, antimetabolite purine antagonists, and mammalian target of rapamycin inhibitors, were compared. Results: A total of 423 graft failures developed after the index date. Therapy regimens incorporated with purine antagonists had a comparable reduction of graft failure among four main drug groups regardless of whether they were given as monotherapy or in combination (adjusted hazard ratio: 0.52, 95% confidence interval: 0.42–0.63). Corticosteroid was found to have inferior effects among four groups (adjusted hazard ratio: 1.67, 95% confidence interval: 1.28–2.21). Furthermore, all 15 arrangements of mutually exclusive treatment combinations were analyzed by referencing with corticosteroid monotherapy. As referenced with steroid-based treatment, regimens incorporated with purine antagonists all have superior advantage on graft survival regardless of whether given in monotherapy (65% of graft failure reduced), dual therapy (48%–67% reduced), or quadruple therapy (43% reduced). In all triple therapies, only corticosteroid combined with calcineurin inhibitor and purine antagonist demonstrated superior protection on graft survival (52% of graft failure reduced). Conclusion: The results may recommend several superior regimens for contributing to graft survival, and for supporting a steroid-minimizing strategy in immunosuppression maintenance. Keywords: chronic rejection, corticosteroid, graft survival, purine antagonist, steroid-minimizing strategy

Fu-Chao Liu,1,2 Chang-Fu Kuo,2–5 Lai-Chu See,4,6 Hsin-I Tsai,1,2,7 Huang-Ping Yu1,2 1Department of Anesthesiology, Chang Gung Memorial Hospital, 2College of Medicine, Chang Gung University, 3Division of Rheumatology, Allergy and Immunology, Chang Gung Memorial Hospital, 4Department of Public Health, College of Medicine, Chang Gung University, 5Office for Big Data Research, Chang Gung Memorial Hospital, 6Biostatistics Core Laboratory, Molecular Medicine Research Center, 7Graduate Institute of Clinical Medical Sciences, Chang Gung University, Taoyuan, Taiwan, Republic of China Introduction: Myasthenia gravis (MG) is clinically heterogeneous and can be life-threatening if bulbar or respiratory muscles are involved. However, relative contributions of genetic, shared, and nonshared environmental factors to MG susceptibility remain unclear. The aim of this study was to examine the familial aggregation and heritability of MG and the relative risks (RRs) of other autoimmune diseases in the relatives of patients with MG.Methods: A population-based family study using the Taiwan National Health Insurance (NHI) Database was conducted. Participants included all individuals (N=23,422,955) who were actively registered in the NHI Database in 2013, 15,066 of whom had at least one first-degree relative with MG. We identified 8,638 parent–child relationships, 3,279 with an affected offspring, 3,134 with affected siblings, and 26 with affected twins. Prevalence and RRs of MG and other autoimmune diseases in the relatives of patients as well as the relative contributions of heritability, shared, and nonshared environmental factors to MG susceptibility were measured.Results: RRs (95% confidence intervals [CIs]) for MG were 17.85 (8.71–36.56) for patients’ siblings, 5.33 (2.79–10.18) for parents, 5.82 (3.03–11.16) for offspring, and 1.42 (0.20–10.10) for spouses without genetic similarities. RRs (95% CIs) in individuals with a first-degree relative with MG were 2.18 (1.53–3.12) for systemic lupus erythematosus, 1.73 (1.09–2.74) for primary Sjögren’s syndrome, 1.90 (1.66–2.18) for autoimmune thyroid disease, and 1.68 (1.22–2.30) for rheumatoid arthritis. Accountability for the phenotypic variance of MG was 82.1% for familial transmission and 17.9% for nonshared environmental factors.Conclusion: Individual risks of MG and other autoimmune diseases are increased in the relatives of patients with MG. Familial transmission of MG was estimated to be 82.1%. Keywords: myasthenia gravis, familial risk, population based family study

Chung-Feng Jeffrey Kuo,1 Chun-Shu Lin,2 Cheng-Hsien Chuang,1 Chung-Shen Lin,3 Feng-Shiang Chiu,3 Shao-Cheng Liu3 1Department of Material Science & Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, Republic of China; 2Department of Radiation Oncology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of China; 3Department of Otolaryngology-Head and Neck Surgery Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of ChinaCorrespondence: Shao-Cheng LiuDepartment of Otolaryngology-Head and Neck Surgery, Tri-Service General Hospital, National Defense Medical Center, No. 325, Sec. 2, Cheng-Gong Road, Neihu District, Taipei, Taiwan 114, Republic of ChinaTel +886-2-8792-7192Fax +886-2-8792-7193Email m871435@ndmctsgh.edu.twIntroduction: Current diagnostic routines in obstructive sleep apnea syndrome (OSAS), including drug-induced sleep endoscopy (DISE), provide qualitative data. Quantitative morphometric measurements of oropharyngeal structures remain challenging. This study aims to introduce a special linear laser projection device that can facilitate computer-assisted digitalized analysis and provide important quantitative information for OSAS prediction.Materials and Methods: We used a single-wavelength green three-linear laser to provide the scaling reference, with one at an angle of 8.5 degrees with the other two which were parallel. The oropharyngeal images were divided into two groups: the non-OSAS and OSAS group, after polysomnography. A minimum of three evaluations were carried out to determine the maximum cross-sectional area of the oropharyngeal inlet (CSAOI) and the retropalatal depth.Results: A total of 132 subjects were enrolled in this study, with 76 subjects in the non-OSAS group and 56 cases in the OSAS group. In the non-OSAS group, the CSAOI was significantly larger in males than in females. There was a trend toward deeper retropalatal region in men than in women (14.25 vs 11.76 mm). Correlation analysis revealed that retropalatal depth is significantly related to body height and the CSAOI. The body weight and BMI of patients with OSAS were significantly higher than those of participants without OSAS. The retropalatal depth and CSAOI were significantly decreased in OSAS patients as compared to those without OSAS. Our new parameter, the oropharyngeal index, showed the most outstanding discrimination by ROC analysis to predict OSAS.Conclusion: Our innovative module can provide reference parameters, which make it possible to directly estimate the objective absolute values of relevant oropharyngeal structures. Our non-invasive approach can be used for outpatient screening, since it allows the identification of potential OSAS patients who should be referred for polysomnography, as many patients do not require DISE early in their evaluation.Keywords: obstructive sleep apnea syndrome, quantitative endoscope, computer-aided diagnostic system, retropalatal depth, cross-sectional area, oropharyngeal inlet

The aim of the present study was to train a natural language processing model to recognize key text elements from research abstracts related to hand surgery, enhancing the efficiency of systematic review screening. A sample of 1600 abstracts from a systematic review of distal radial fracture treatment outcomes was annotated to train the natural language processing model. To assess time-saving potential, 200 abstracts were processed by the trained models in two experiments, where reviewers accessed natural language processing predictions to include or exclude articles. The natural language processing model achieved an overall accuracy of 0.91 in recognizing key text elements, excelling in identifying study interventions. Use of the natural language processing reduced mean screening time by 31% without compromising accuracy. Precision varied, improving in the second experiment, indicating context-dependent performance. These findings suggest that natural language processing models can streamline abstract screening in systematic reviews by effectively identifying original research and extracting relevant text elements. Level of evidence: IV., Competing Interests: Declaration of conflicting interestsThe authors disclosed the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: KCC receives funding from the National Institutes of Health, book royalties from Wolters Kluwer and Elsevier, and has received grant support from Sonex.

Objectives: Elizabethkingia spp. are resistant to multiple antibiotics. This study aimed to determine in vitro and in vivo activities of cefiderocol against Elizabethkingia spp. and to investigate resistance mechanisms., Methods: Bloodstream isolates were collected from four hospitals. In vitro and in vivo activities were determined using broth microdilution and the wax moth model, respectively. Genome comparison and gene editing were used to confirm the contribution of target genes. Conjugation experiments and serial passage were used to determine transferability and stability, respectively. A MIC of ≤ 4 mg/L was designated as the susceptibility breakpoint., Results: Among 228 non-duplicated isolates, 226 exhibited a MIC of ≤ 4 mg/L with MIC 50/90 of 1/2 mg/L. Two isolates had a MIC of 128 mg/L; both source patients had multiple comorbidities, were ventilator-dependent, and had not received cefiderocol previously. Resistance was attributable to acquisition of bla CfxA-3 , carried by a conjugative transposon from Prevotella jejuni, and duplication of intrinsic bla CME-3 , which led to its overexpression. tetQ coexisted with bla CfxA-3 in this conjugative transposon and minocycline facilitated its transfer among E. anophelis. Antibiotics prescribed for source patients did not induce bla CME-3 duplication. The stabilities of bla CfxA-3 and double bla CME-3 were 100% and > 90%, respectively, after 10-day serial passage. Cefiderocol failed to rescue moth larvae infected with resistant strains, but removal of resistance mechanisms restored in vivo efficacy., Conclusions: Cefiderocol was in vitro and in vivo active against Elizabethkingia spp. but resistance may emerge due to the availability, transferability, and/or stability of resistance mechanisms., Competing Interests: Competing Interests All authors declare that they have no competing interests., (Copyright © 2024. Published by Elsevier Ltd.)

Background: This study investigated drug-drug interactions in patients with atrial fibrillation taking both a direct oral anticoagulant (DOAC) and an antiarrhythmic drug., Methods and Results: Using data from the National Health Insurance database (2012-2018), we identified 78 805 patients with atrial fibrillation on DOACs, with 24 142 taking amiodarone, 8631 taking propafenone, 2784 taking dronedarone, 297 taking flecainide, 177 taking sotalol, and 42 772 on DOACs alone. Patients with bradycardia, heart block, heart failure, mitral stenosis, prosthetic valves, or incomplete data were excluded. Propensity score matching compared those taking both DOACs and antiarrhythmic drugs with those on DOACs alone. There was an increased risk of major bleeding in patients concomitantly taking DOACs with amiodarone when compared with matched patients taking DOACs alone (hazard ratio [HR],1.13 [95% CI, 1.04-1.23]; P =0.0044), particularly in patients taking dabigatran (HR, 1.19 [95% CI, 1.03-1.38]; P =0.0175). No significant difference in bleeding risk was found for propafenone, dronedarone, flecainide, or sotalol. The small sample sizes in the flecainide and sotalol groups limit interpretation. Notably, intracranial bleeding risk was higher in patients on DOACs and amiodarone, regardless of age. Additionally, patients <80 years old taking dabigatran with amiodarone or propafenone had a higher risk of gastrointestinal bleeding., Conclusions: Concomitant use of DOACs with amiodarone, but not dronedarone or propafenone, increases the risk of major bleeding, particularly intracranial bleeding. This study provides new evidence to guide clinicians to tailor concomitant anticoagulation and antiarrhythmic therapy for patients with atrial fibrillation.

Purpose: Osteoporosis, affecting over 200 million individuals, often remains unrecognized and untreated, increasing the risk of fractures in older adults. Osteoporosis is typically diagnosed with bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA). This study aims to develop DeepDXA-Hand, a deep learning model using the efficient CNN-based deep learning architecture, for opportunistic osteoporosis screening from hand radiographs., Methods: DeepDXA-Hand utilizes a CNN-based, HarDNet, approach to predict BMD non-invasively. A total of 10,351 hand radiographs and DXA pairs were used for model training and validation. The model's interpretability was enhanced using GradCAM for hotspot analysis to determine the model's attention areas., Results: The predicted and ground truth BMD were significantly correlated with a correlation coefficient of 0.745. For binary classification of osteoporosis, DeepDXA-Hand demonstrated a sensitivity of 0.73, specificity of 0.83, and accuracy of 0.80, indicating its clinical potential. The model mainly focused on the carpal bones, such as the capitate, trapezoid, hamate, triquetrum, and the head of the second metacarpal bone, suggesting these areas provide radiological features for inferring BMD., Conclusion: DeepDXA-Hand shows potential for the early detection of osteoporosis with high sensitivity and specificity. Further studies should explore its utility in predicting fracture risks., Mini Abstract: Osteoporosis affects millions and often goes undetected and untreated. DeepDXA-Hand, a HarDNet-based deep learning model, predicted bone mineral density with a correlation of 0.745 and classified osteoporosis with 0.80 accuracy. This model enhances early detection and has significant clinical potential as osteoporosis opportunistic screening tool., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yueh-Peng Chen reports financial support was provided by National Science and Technology Council, Taiwan. Yueh-Peng Chen has patent licensed to Yueh-Peng Chen. Chan-Shien Ho has patent issued to Chan-Shien Ho. Tzuo-Yau Fan has patent issued to Tzuo-Yau Fan. Yu-Cheng Pei has patent issued to Yu-Cheng Pei. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Objectives: Biological disease-modifying antirheumatic drugs have been the primary treatment option for moderate to severe rheumatoid arthritis (RA) in Taiwan since 2010. Tocilizumab is an interleukin-6 receptor inhibitor, whereas tofacitinib is a Janus kinase inhibitor. The two medications were indicated to treat RA by direct and indirect inhibition of interleukin-6 cytokine. We compared the safety outcomes of tocilizumab and tofacitinib in patients with RA in real-world clinical settings, following the 7 key components of target trial emulation (TTE)., Methods: The data source was the Taiwan National Health Insurance Research Database. Patients with RA between 2010 and 2018 were eligible and assigned to either tocilizumab or tofacitinib based on their first prescription of these two medications. The index date was set as the first prescription date of either study medication. Propensity score stabilized weighting (PSSW) was used to balance the characteristics between the two medication groups. The incidences of safety outcomes were all-cause mortality, cancer, coronary heart disease, stroke, venous thrombosis events, tuberculosis, joint replacement events, and herpes zoster infection. The intention-to-treat (ITT) effect was commenced from the index date until the study outcomes, independently, 3 years, withdrawal, or December 31, 2021, whichever occurred first. For the per-protocol (PP) effect, patients were required to maintain the same medical group during the entire follow-up period., Results: A total of 2125 patients with RA who were prescribed tocilizumab (n = 844) or tofacitinib (n = 1281) were included in this study. The mean follow-up duration was 2.78 years in the tocilizumab group and 2.83 years in the tofacitinib group. For ITT, the sample sizes were 721 and 1196 for the tocilizumab and tofacitinib, respectively, after PSSW. A substantially lower incidence rate of herpes zoster infection (per 100 patient-years) was observed in the tocilizumab group (3.67) than in the tofacitinib group (7.61), with a hazard ratio of 0.48 (95%CI =0.37-0.63; p < .0001). All-cause mortality, cancer, coronary heart disease, stroke, total hip replacement, and tuberculosis were similar between the two medication groups. For PP, the sample sizes were 619 and 1085 for the tocilizumab and tofacitinib, respectively, after PSSW. The results of the PP analysis were similar to those of the ITT analysis., Conclusions: Tocilizumab and tofacitinib act along the same inflammatory pathway. A lower herpes zoster incident rate was observed in the tocilizumab group than in the tofacitinib group. The incidence rates of other safety concerns and mortality rates were comparable in both groups of patients with RA treated in real-world settings., (© 2024 The Author(s). International Journal of Rheumatic Diseases published by Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.)

Arctium lappa L. polysaccharide (ALP) is a prominent bioactive compound renowned for its multifaceted functional properties, including anti-inflammatory, antioxidant, antifibrotic, immunomodulatory, and pro-apoptotic effects. This study evaluated the aging-delaying effect of ALP and its mechanisms using a D-galactose (D-gal)-induced aging model. After an 8-week treatment, ALP significantly ameliorated D-gal-induced inflammation and oxidative stress in the liver, kidneys, and intestines. Notably, ALP administration led to a marked reduction of the pathogenic bacterium Desulfovibrio and a substantial increase in the beneficial bacterium Muribaculum. These microbial shifts were associated with upregulated expression of intestinal tight junction proteins and intestinal mucins, leading to enhanced intestinal barrier integrity. Consequently, the leakage of enterotoxins and inflammatory mediators was effectively reduced. The findings indicate that ALP alleviates tissue inflammation and oxidative stress, while also delaying aging in mice. This effect is achieved through the regulation of intestinal ecological homeostasis and the repair of the intestinal immune barrier., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objectives: The usefulness of methotrexate-polyglutamates (MTX-PGs) concentration for management of rheumatoid arthritis has been debated. We aimed to clarify the association of MTX-PGs concentration with efficacy and safety in MTX-naïve patients initiating MTX in a prospective interventional clinical trial., Methods: The MIRACLE trial enrolled 300 MTX-naïve patients. Oral MTX was initiated and increased to the maximum tolerated dose by week 12. Patients who did not achieve remission according to the Simplified Disease Activity Index at week 24 were randomised to either the continued dose or reduced dose group and were started on subcutaneous adalimumab. We measured the concentrations of MTX-PGs in erythrocytes using liquid chromatography-tandem mass spectrometry and analysed the association of these concentrations with efficacy and safety., Results: The mean concentration of total MTX-PGs increased with an increasing dose of MTX and continued to elevate for another 12 weeks after the dose was fixed. At week 24, the total MTX-PGs concentration was 110.5 (SD 43.8) nmol/L with MTX dose of 12.6 (3.0) mg/week (0.23 (0.07) mg/kg/week). During MTX monotherapy, the higher MTX-PGs concentration was an independent factor for lower disease activity; however, this association disappeared after adalimumab initiation in patients with continued MTX dose. Hepatotoxicity was related to the higher MTX-PGs concentration regardless of adalimumab use. The total MTX-PGs concentration was significantly elevated by lower estimated glomerular filtration rate, serum albumin and body mass index., Conclusions: The MIRACLE trial demonstrated that higher total MTX-PGs concentration in erythrocytes is related to the higher efficacy and lower safety of MTX., Trial Registration Number: NCT03505008., Competing Interests: Competing interests: HTam received honoraria from AbbVie, Eisai; support for attending meetings from PhRMA. KI received grants from Mitsubishi-Tanabe, Eli Lilly; honoraria from AbbVie, Eisai, Pfizer, Mitsubishi-Tanabe, Janssen, Novartis, UCB, Daiichi-Sankyo, Eli Lilly, Gilead Sciences, AstraZeneca, Asahi Kasei, Chugai, Bristol-Myers Squibb. TM received consulting fees from Eisai, Gilead Sciences; honoraria from Eisai, AbbVie, Eli Lilly, Gilead Sciences, Asahi Kasei. KS received grants/research support from Novartis, Astellas, AbbVie, Bristol-Myers Squibb, Yuhan; consulting fees from KD Bio. SH received grants from AbbVie, Asahi Kasei, Chugai, Eisai, Eli Lily, Otsuka, Taisho, UCB; honoraria from AbbVie, Asahi-Kasei, Astellas, AstraZeneca, Ayumi, Bristol-Myers Squibb, Boehringer Ingelheim, Chugai, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead Sciences, Glaxo SmithKline, Janssen, Nihon-Shinyaku, Novartis, Otsuka Pharmaceutical, Pfizer, Taisho, Tanabe-Mitsubishi, UCB; participated on advisory boards of AbbVie, Astellas, Bristol Myers Squibb, Eisai, Eli Lilly, Gilead Sciences, Janssen, Taisho, UCB. SS received honoraria from AbbVie, Pfizer. HY received grants from AbbVie, Boehringer Ingelheim, Gilead Sciences, Nippon Shinyaku, Asahi Kasei, Chugai, Eisai, Mitsubishi-Tanabe, Taisho; honoraria from AbbVie, Asahi Kasei, Astellas, Daiichi Sankyo, Eisai, Eli Lilly, Pfizer, Janssen, Sanofi, Teijin, Boehringer Ingelheim, Bayer, Viatris, Kissei, Takeda, Mitsubishi-Tanabe, Chugai, Novartis. MK received grants and royalties from MBL; consulting fees from Boehringer Ingelheim, Mochida, Kissei, GSK, AstraZeneca, Mitsubishi-Tanabe, Janssen, Biogen; received honoraria from Boehringer Ingelheim, Chugai, Asahi Kasei; participated on advisory board of Argenx. TI received honoraria from Asahi Kasei, GSK, Chugai, Pfizer, Eli Lilly, Boehringer-Ingelheim, AstraZeneca. HK received a grant from Pfizer, AbbVie, Asahi Kasei, Boehringer Ingelheim, Chugai, Eisai, Mitsubishi-Tanabe, Taisho; consulting fees from Sanofi; honoraria from AbbVie, Asahi Kasei, AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Chugai, Eisai, Eli Lilly, Janssen, Mitsubishi-Tanabe, Novartis, Pfizer. TK received grant/research support from AbbVie, Astellas, Chugai; honoraria from AbbVie, Astellas, Bristol-Myers Squibb, Chugai, Daiichi-Sankyo, Eli Lilly, Pfizer, Eisai, Taisho, UCB; participated on board of JCR subcommittee on Guidelines for RA Therapeutics. YN is a shareholder and employee of Eisai. MM is a shareholder and employee of Eisai. HM is an employee of Eisai. YS received honoraria from Mochida. WT received consulting fees and honoraria from Eli Lilly, Eisai; honoraria from Pfizer. TT received consulting fees from AbbVie, Eli Lilly, Gilead Sciences, Mitsubishi-Tanabe, Taisho; honoraria from AbbVie, Astellas, AstraZeneca, Chugai, Eisai, Eli Lilly, Gilead Sciences, Janssen, Mitsubishi-Tanabe, Pfizer, Taisho. YK received grants from AbbVie, Asahi Kasei, Ayumi, Boehringer Ingelheim, Chugai, Eisai, Gilead Sciences, Mitsubishi-Tanabe, Taisho, UCB; consulting fees from AbbVie, Asahi Kasei, Bristol-Myers Squibb, Eli Lilly, Gilead Sciences, Pfizer, Taisho, UCB; honoraria from AbbVie, Asahi Kasei, Astellas, AstraZeneca, Ayumi, Bristol-Myers Squibb, Chugai, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead, Glaxo SmithKline, Janssen, Mitsubishi-Tanabe, Novartis, Pfizer, Sanofi, Taisho, UCB. The other coauthors declare no relevant conflicts of interest., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ on behalf of EULAR.)

Older age is associated with reduced social networks while social skill abilities are important assets for older people to cope with these situations. To better understand older people's social skill ability and important demographic correlates, the present cross-sectional survey research interviewed 1000 Taiwanese older volunteers from 73 community care centers. Findings of a mixed model indicated that education and serving area outweighed other demographic factors significantly correlated with older volunteers' social skill ability. Latent class analyses further identified different latent ability groups for different education (high vs. low) or serving-area (urban vs. suburban) older volunteers. Specifically, low-education or suburban volunteers were correlated with disadvantageous social skill profiles. Notably, the suburban eclectic ability group exhibited a skill pattern signifying the risk of loneliness. Overall, the findings called for further investigation into the relationship between older people's socioeconomic factors (e.g., education and serving area) and their social skill ability., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: Diagnosing and treating tonsillitis pose no significant challenge for otolaryngologists; however, it can increase the infection risk for healthcare professionals amidst the coronavirus pandemic. In recent years, with the advancement of artificial intelligence (AI), its application in medical imaging has also thrived. This research is to identify the optimal convolutional neural network (CNN) algorithm for accurate diagnosis of tonsillitis and early precision treatment., Methods: Semi-supervised learning with pseudo-labels used for self-training was adopted to train our CNN, with the algorithm including UNet, PSPNet, and FPN. A total of 485 pharyngoscopic images from 485 participants were included, comprising healthy individuals (133 cases), patients with the common cold (295 cases), and patients with tonsillitis (57 cases). Both color and texture features from 485 images are extracted for analysis., Results: UNet outperformed PSPNet and FPN in accurately segmenting oropharyngeal anatomy automatically, with average Dice coefficient of 97.74% and a pixel accuracy of 98.12%, making it suitable for enhancing the diagnosis of tonsillitis. The normal tonsils generally have more uniform and smooth textures and have pinkish color, similar to the surrounding mucosal tissues, while tonsillitis, particularly the antibiotic-required type, shows white or yellowish pus-filled spots or patches, and shows more granular or lumpy texture in contrast, indicating inflammation and changes in tissue structure. After training with 485 cases, our algorithm with UNet achieved accuracy rates of 93.75%, 97.1%, and 91.67% in differentiating the three tonsil groups, demonstrating excellent results., Conclusion: Our research highlights the potential of using UNet for fully automated semantic segmentation of oropharyngeal structures, which aids in subsequent feature extraction, machine learning, and enables accurate AI diagnosis of tonsillitis. This innovation shows promise for enhancing both the accuracy and speed of tonsillitis assessments., Competing Interests: Declarations Ethics approval and consent to participate The research protocol (NO: 1-108-05-132) has been reviewed and approved by the Institutional Review Board of our Hospital. Consent for publication Consent to publish has been obtained from all participants. Conflict of interest The authors declare that there are no financial or non-financial competing interests directly or indirectly related to the work submitted for publication., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study aims to estimate the familial risks of pterygium and assess its relative contributions to environmental and genetic factors using the 2000-2017 Taiwan National Health Insurance Research Database. The marginal Cox's model and the polygenic liability model were made. In Taiwan, the prevalence rate of pterygium in 2017 was 1.64% for individuals with affected first-degree relatives, higher than the general population (1.34%). The adjusted relative risk (RR) for pterygium was highest for twins of the same sex (15.54), followed by siblings of the same sex (4.69), offsprings (3.39), siblings of the different sex (2.88), spouse (2.12), parents (1.86), twins of the different sex (1.57), respectively. The phenotypic variance of pterygium was 21.6% from additive genetic variance, 24.3% from common environmental factors shared by family members, and 54.1% from non-shared environmental factors, respectively. Sensitivity analysis by restricting those with surgical pterygium reveals that aRRs and the three components were similar to those of the overall pterygium. In summary, the prevalence rate of pterygium was higher for individuals with affected first-degree relatives than for the general population. The non-shared environmental factors account for half of the phenotypic variance of pterygium; genetic and shared environmental factors explain the rest., (© 2024. The Author(s).)

Background: Chronic fatigue syndrome (CFS) has been linked to several conditions, including infections, immune system changes, or emotional stress. Our study aimed to assess the risk of CFS after a pneumonia diagnosis using data from National Health Insurance Research Database of Taiwan., Methods: In this nested case-control study, we identified 2,000,000 adult patients from a nationwide population-based health insurance claims database spanning from January 1, 2000, to December 31, 2017. Each case diagnosed with a pathogenic infection was matched with a corresponding control using propensity scores. We excluded individuals under 20 years of age, those with a history of pathogenic infections before the index date, or those with more than one potential pathogen. To estimate hazard ratios (HR) and the adjusted hazard ratio (aHR) with their respective 95 % confidence intervals (CI), we applied univariable and multivariable Cox proportional hazard models. The multivariable analysis incorporated adjustments for age, sex, and comorbidity-related confounders., Results: The relationship between infection and the subsequent risk of CFS was assessed using Cox proportional hazards regression analysis. The incidence density rates were 6.13 and 8.70 per 1000 person-years among the non-pulmonary infection and pulmonary infection populations, respectively (adjusted hazard ratio [HR] = 1.4, 95 % confidence interval [CI] 1.32-1.5). Patients infected with Pseudomonas, Klebsiella pneumoniae, Haemophilus influenzae, Streptococcus pneumoniae, and influenza virus exhibited a significantly higher risk of CFS than those without these pathogens (p < 0.05). Additionally, patients with pneumonia had a significantly increased risk of thromboembolism compare with control group (p < 0.05)., Competing Interests: Declaration of Competing Interest The authors declare that there is no conflict of interest regarding the publication of this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Although elevated heart rate is a risk factor for cardiovascular morbidity and mortality in healthy people, the association between resting heart rate and major cardiovascular risk in patients after acute ischemic stroke remains debated. This study evaluated the association between heart rate and major adverse cardiovascular events after ischemic stroke., Methods: We conducted a retrospective cohort study analyzing data from the Chang Gung Research Database for 21,655 patients with recent ischemic stroke enrolled between January 1, 2010, and September 30, 2018. Initial in-hospital heart rates were averaged and categorized into 10-beats per minute (bpm) increments. The primary outcome was the composite of hospitalization for recurrent ischemic stroke, myocardial infarction, or all-cause mortality. Secondary outcomes were hospitalization for recurrent ischemic stroke, myocardial infarction, and heart failure. Hazard ratios and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models, using the heart rate < 60 bpm subgroup as the reference., Results: After a median follow-up of 3.2 years, the adjusted hazard ratios for the primary outcome were 1.13 (95% CI: 1.01 to 1.26) for heart rate 60-69 bpm, 1.35 (95% CI: 1.22 to 1.50) for heart rate 70-79 bpm, 1.64 (95% CI: 1.47 to 1.83) for heart rate 80-89 bpm, and 2.08 (95% CI: 1.85 to 2.34) for heart rate ≥ 90 bpm compared with the reference group. Heart rate ≥ 70 bpm was associated with increased risk of all secondary outcomes compared with the reference group except heart failure.  CONCLUSIONS: Heart rate is a simple measurement with important prognostic implications. In patients with ischemic stroke, initial in-hospital heart rate was associated with major adverse cardiovascular events., (© 2024. The Author(s).)

Osteoporosis is a common condition that can lead to fractures, mobility issues, and death. Although dual-energy X-ray absorptiometry (DXA) is the gold standard for osteoporosis, it is expensive and not widely available. In contrast, kidney-ureter-bladder (KUB) radiographs are inexpensive and frequently ordered in clinical practice. Thus, it is a potential screening tool for osteoporosis. In this study, we explored the possibility of predicting the bone mineral density (BMD) and classifying high-risk patient groups using KUB radiographs. We proposed DeepDXA-KUB, a deep learning model that predicts the BMD values of the left hip and lumbar vertebrae from an input KUB image. The datasets were obtained from Taiwanese medical centers between 2006 and 2019, using 8913 pairs of KUB radiographs and DXA examinations performed within 6 months. The images were randomly divided into training and validation sets in a 4:1 ratio. To evaluate the model's performance, we computed a confusion matrix and evaluated the sensitivity, specificity, accuracy, precision, positive predictive value, negative predictive value, F1 score, and area under the receiver operating curve (AUROC). Moderate correlations were observed between the predicted and DXA-measured BMD values, with a correlation coefficient of 0.858 for the lumbar vertebrae and 0.87 for the left hip. The model demonstrated an osteoporosis detection accuracy, sensitivity, and specificity of 84.7 %, 81.6 %, and 86.6 % for the lumbar vertebrae and 84.2 %, 91.2 %, and 81 % for the left hip, respectively. The AUROC was 0.939 for the lumbar vertebrae and 0.947 for the left hip, indicating a satisfactory performance in osteoporosis screening. The present study is the first to develop a deep learning model based on KUB radiographs to predict lumbar spine and femoral BMD. Our model demonstrated a promising correlation between the predicted and DXA-measured BMD in both the lumbar vertebrae and hip, showing great potential for the opportunistic screening of osteoporosis., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Recent advancements in deep learning models have demonstrated their potential in the field of medical imaging, achieving remarkable performance surpassing human capabilities in tasks such as classification and segmentation. However, these modern state-of-the-art network architectures often demand substantial computational resources, which limits their practical application in resource-constrained settings. This study aims to propose an efficient diagnostic deep learning model specifically designed for the classification of intracranial hemorrhage in brain CT scans., Method: Our proposed model utilizes a combination of depthwise separable convolutions and a multi-receptive field mechanism to achieve a trade-off between performance and computational efficiency. The model was trained on RSNA datasets and validated on CQ500 dataset and PhysioNet dataset., Result: Through a comprehensive comparison with state-of-the-art models, our model achieves an average AUROC score of 0.952 on RSNA datasets and exhibits robust generalization capabilities, comparable to SE-ResNeXt, across other open datasets. Furthermore, the parameter count of our model is just 3 % of that of MobileNet V3., Conclusion: This study presents a diagnostic deep-learning model that is optimized for classifying intracranial hemorrhages in brain CT scans. The efficient characteristics make our proposed model highly promising for broader applications in medical settings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that may have influenced the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: One in five patients with rheumatoid arthritis (RA) rely on surgery to restore joint function. However, variable response to disease-modifying antirheumatic drugs (DMARDs) complicates surgical planning, and it is difficult to predict which patients may ultimately require surgery. We used machine learning to develop predictive models for the likelihood of undergoing an operation related to RA and which type of operation patients who require surgery undergo., Methods: We used electronic health record data to train two extreme gradient boosting machine learning models. The first model predicted patients' probabilities of undergoing surgery ≥5 years after their initial clinic visit. The second model predicted whether patients who underwent surgery would undergo a major joint replacement versus a less intensive procedure. Predictors included demographics, comorbidities, and medication data. The primary outcome was model discrimination, measured by area under the receiver operating characteristic curve (AUC)., Results: We identified 5,481 patients, of whom 278 (5.1%) underwent surgery. There was no significant difference in the frequency of DMARD or steroid prescriptions between patients who did and did not have surgery, though nonsteroidal anti-inflammatory drug prescriptions were more common among patients who did have surgery (P = 0.03). The model predicting use of surgery had an AUC of 0.90 ± 0.02. The model predicting type of surgery had an AUC of 0.58 ± 0.10., Conclusions: Predictive models using clinical data have the potential to facilitate identification of patients who may undergo rheumatoid-related surgery, but not what type of procedure they will need. Integrating similar models into practice has the potential to improve surgical planning., (© 2023 American College of Rheumatology.)

Background: Electrocardiogram (ECG) abnormalities have demonstrated potential as prognostic indicators of patient survival. However, the traditional statistical approach is constrained by structured data input, limiting its ability to fully leverage the predictive value of ECG data in prognostic modeling., Methods: This study aims to introduce and evaluate a deep-learning model to simultaneously handle censored data and unstructured ECG data for survival analysis. We herein introduce a novel deep neural network called ECG-surv, which includes a feature extraction neural network and a time-to-event analysis neural network. The proposed model is specifically designed to predict the time to 1-year mortality by extracting and analyzing unique features from 12-lead ECG data. ECG-surv was evaluated using both an independent test set and an external set, which were collected using different ECG devices., Results: The performance of ECG-surv surpassed that of the Cox proportional model, which included demographics and ECG waveform parameters, in predicting 1-year all-cause mortality, with a significantly higher concordance index (C-index) in ECG-surv than in the Cox model using both the independent test set (0.860 [95% CI: 0.859- 0.861] vs. 0.796 [95% CI: 0.791- 0.800]) and the external test set (0.813 [95% CI: 0.807- 0.814] vs. 0.764 [95% CI: 0.755- 0.770]). ECG-surv also demonstrated exceptional predictive ability for cardiovascular death (C-index of 0.891 [95% CI: 0.890- 0.893]), outperforming the Framingham risk Cox model (C-index of 0.734 [95% CI: 0.715-0.752])., Conclusion: ECG-surv effectively utilized unstructured ECG data in a survival analysis. It outperformed traditional statistical approaches in predicting 1-year all-cause mortality and cardiovascular death, which makes it a valuable tool for predicting patient survival., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that may have influenced the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Endoscopic submucosal dissection (ESD) is a widely accepted treatment for patients with mucosa (T1a) disease without lymph node metastasis. However, the inconsistency of inspection quality of tumor staging under the standard tool combining endoscopic ultrasound (EUS) with computed tomography (CT) scanning makes it restrictive. Methods: We conducted a study using data augmentation and artificial intelligence (AI) to address the early gastric cancer (EGC) staging problem. The proposed AI model simplifies early cancer treatment by eliminating the need for ultrasound or other staging methods. We developed an AI model utilizing data augmentation and the You-Only-Look-Once (YOLO) approach. We collected a white-light image dataset of 351 stage T1a and 542 T1b images to build, test, and validate the model. An external white-light images dataset that consists of 47 T1a and 9 T1b images was then collected to validate our AI model. The result of the external dataset validation indicated that our model also applies to other peer health institutes. Results: The results of k -fold cross-validation using the original dataset demonstrated that the proposed model had a sensitivity of 85.08% and an average specificity of 87.17%. Additionally, the k -fold cross-validation model had an average accuracy rate of 86.18%; the external data set demonstrated similar validation results with a sensitivity of 82.98%, a specificity of 77.78%, and an overall accuracy of 82.14%. Conclusions: Our findings suggest that the AI model can effectively replace EUS and CT in early GC staging, with an average validation accuracy rate of 86.18% for the original dataset from Linkou Cheng Gun Memorial Hospital and 82.14% for the external validation dataset from Kaohsiung Cheng Gun Memorial Hospital. Moreover, our AI model's accuracy rate outperformed the average EUS and CT rates in previous literature (around 70%)., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Background: Developmental dysplasia of the hip (DDH) is a common congenital disorder that may lead to hip dislocation and requires surgical intervention if left untreated. Ultrasonography is the preferred method for DDH screening; however, the lack of experienced operators impedes its application in universal neonatal screening., Methods: We developed a deep neural network tool to automatically register the five keypoints that mark important anatomical structures of the hip and provide a reference for measuring alpha and beta angles following Graf's guidelines, which is an ultrasound classification system for DDH in infants. Two-dimensional (2D) ultrasonography images were obtained from 986 neonates aged 0-6 months. A total of 2406 images from 921 patients were labeled with ground truth keypoints by senior orthopedists., Results: Our model demonstrated precise keypoint localization. The mean absolute error was approximately 1 mm, and the derived alpha angle measurement had a correlation coefficient of R = 0.89 between the model and ground truth. The model achieved an area under the receiver operating characteristic curve of 0.937 and 0.974 for classifying alpha <60° (abnormal hip) and <50° (dysplastic hip), respectively. On average, the experts agreed with 96% of the inferenced images, and the model could generalize its prediction on newly collected images with a correlation coefficient higher than 0.85., Conclusions: Precise localization and highly correlated performance metrics suggest that the model can be an efficient tool for assisting DDH diagnosis in clinical settings., Competing Interests: Conflicts of interest No Conflicts of interest., (© 2023 The Authors. Published by Elsevier B.V. on behalf of Chang Gung University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Background: The role of P-wave in identifying left atrial enlargement (LAE) with the use of artificial intelligence (AI)-enabled electrocardiography (ECG) models is unclear. It is also unknown if AI-enabled single-lead ECG could be used as a diagnostic tool for LAE surveillance. We aimed to build AI-enabled P-wave and single-lead ECG models to identify LAE using sinus rhythm (SR) and non-SR ECGs, and compare the prognostic ability of severe LAE, defined as left atrial diameter ≥ 50 mm, assessed by AI-enabled ECG models vs echocardiography., Methods: This retrospective study used data from 382,594 consecutive adults with paired 12-lead ECG and echocardiography performed within 2 weeks of each other at Chang Gung Memorial Hospital. UNet++ was used for P-wave segmentation. ResNet-18 was used to develop deep convolutional neural network-enabled ECG models for discriminating LAE. External validation was performed with the use of data from 11,753 patients from another hospital., Results: The AI-enabled 12-lead ECG model outperformed other ECG models for classifying LAE, but the single-lead ECG models also showed excellent performance at a left atrial diameter cutoff of 50 mm. AI-enabled ECG models had excellent and fair discrimination on LAE using the SR and the non-SR data set, respectively. Severe LAE identified by AI-enabled ECG models was more predictive of future cardiovascular disease than echocardiography; however, the cumulative incidence of new-onset atrial fibrillation and heart failure was higher in patients with echocardiography-severe LAE than with AI-enabled ECG-severe LAE., Conclusions: P-Wave plays a crucial role in discriminating LAE in AI-enabled ECG models. AI-enabled ECG models outperform echocardiography in predicting new-onset cardiovascular diseases associated with severe LAE., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

In this study, we implemented a combination of data augmentation and artificial intelligence (AI) model-Convolutional Neural Network (CNN)-to help physicians classify colonic polyps into traditional adenoma (TA), sessile serrated adenoma (SSA), and hyperplastic polyp (HP). We collected ordinary endoscopy images under both white and NBI lights. Under white light, we collected 257 images of HP, 423 images of SSA, and 60 images of TA. Under NBI light, were collected 238 images of HP, 284 images of SSA, and 71 images of TA. We implemented the CNN-based artificial intelligence model, Inception V4, to build a classification model for the types of colon polyps. Our final AI classification model with data augmentation process is constructed only with white light images. Our classification prediction accuracy of colon polyp type is 94%, and the discriminability of the model (area under the curve) was 98%. Thus, we can conclude that our model can help physicians distinguish between TA, SSA, and HPs and correctly identify precancerous lesions such as TA and SSA., (© 2024. The Author(s).)

People wear clothes for warmth, survival and necessity in modern life, but in the modern era, eco-friendliness, shortened production times, design and intelligence also matter. To determine the relationship between data series and verify the proximity of each data series, a gray relational analysis, or GRA, is applied to textiles, where seamless bonding technology enhances the bond between components. In this study, a polyurethane prepolymer, 2-hydroxyethyl acrylate (2-HEA) as an end-capping agent and n-octyl acrylate (ODA) as a photoinitiator were used to synthesize a dual-curing polyurethane hot-melt adhesive. Taguchi quality engineering and a gray relational analysis were used to discuss the influence of different mole ratios of NCO:OH and the effect of the molar ratio of the addition of octyl decyl acrylate on the mechanical strength. The Fourier transform infrared spectroscopy (FTIR) results showed the termination of the prepolymer's polymerization reaction and the C=O peak intensity at 1730 cm -1 , indicating efficient bonding to the main chain. Advanced Polymer Chromatography (APC) was used to investigate the high-molecular-weight (20,000-30,000) polyurethane polymer bonded with octyl decyl acrylate to achieve a photothermosetting effect. The thermogravimetric analysis (TGA) results showed that the thermal decomposition temperature of the polyurethane hot-melt adhesive also increased, and they showed the highest pyrolysis temperature (349.89 °C) for the polyhydric alcohols. Furthermore, high peel strength (1.68 kg/cm) and shear strength (34.94 kg/cm 2 ) values were detected with the dual-cure photothermosetting polyurethane hot-melt adhesive. The signal-to-noise ratio was also used to generate the gray relational degree. It was observed that the best parameter ratio of NCO:OH was 4:1 with five moles of monomer. The Taguchi quality engineering method was used to find the parameters of single-quality optimization, and then the gray relation calculation was used to obtain the parameter combination of multi-quality optimization for thermosetting the polyurethane hot-melt adhesive. The study aims to meet the requirements of seamless bonding in textile factories and optimize experimental parameter design by setting target values that can effectively increase production speed and reduce processing time and costs as well.

Purpose: To estimate the familial risks of primary angle-closure glaucoma (PACG) and primary open-angle glaucoma (POAG) and assess the relative contributions of environmental and genetic factors to these risks., Design: Retrospective, population-based cohort study., Methods: We used the 2000-2017 Taiwan National Health Insurance Program database to construct 4,144,508 families for the 2017 population (N = 23,373,209). We used the polygenic liability model to estimate glaucoma's heritability and familial transmission. The degree of familial aggregation of glaucoma was obtained from the adjusted relative risk for individuals whose first-degree relatives had glaucoma using Cox's model., Results: PACG and POAG prevalence rates for individuals whose first-degree relatives had PACG or POAG were 0.95% and 2.40%, higher than those of the general population (0.61% and 0.40%, respectively). The relative risk of PACG in individuals whose first-degree relatives had PACG was 2.44 (95% CI = 2.31-2.58). The relative risk of POAG in individuals whose first-degree relatives had POAG was 6.66 (95% CI = 6.38-6.94). The estimated contributions to PACG and POAG phenotypic variances were 19.4% and 59.6% for additive genetic variance, 19.1% and 23.2% for common environmental factors shared by family members, and 61.5% and 17.2% for nonshared environmental factors, respectively., Conclusions: These data highlight the relative importance of genetic contribution to POAG and environmental contribution to PACG. Therefore, future work may need to focus on finding more novel environmental determinants of PACG., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Purpose: Our objective was to assess the adverse outcomes during pregnancy, as well as for the fetus and neonates, in women with epilepsy, both with and without the use of antiseizure medications (ASMs)., Methods: A cohort of singleton pregnancies between January 1, 2004 and December 31, 2014 was identified using the Taiwan National Health Database. The pregnancies were categorized into ASM exposure, ASM nonexposure, and control (consisting of women without an epilepsy diagnosis) groups. We recorded adverse outcomes in neonates and documented pregnancy complications. The generalized estimating equation with logit link was used to estimate adjusted odds ratios., Results: There were 629 singleton pregnancies in the group exposed to ASMs, 771 in the epilepsy group without ASM exposure, and 2,004,479 in the control group. Women with epilepsy had a significantly higher risk of puerperal cerebrovascular diseases (adjusted odds ratios in the exposure and nonexposure groups = 54.46 and 20.37, respectively), respiratory distress syndrome (5.1 and 2.99), mortality (3.15 and 3.22), sepsis (2.67 and 2.54), pregnancy-related hypertension (1.71 and 1.8), preeclampsia (1.87 and 1.79), cesarean delivery (1.72 and 2.15), and preterm labor (1.38 and 1.56). The use of ASMs may increase the risk of eclampsia (adjusted odds ratio = 12.27). Compared to controls, fetuses/neonates born to women with epilepsy had a higher risk of unexplained stillbirth (adjusted odds ratios in the exposure and nonexposure groups = 2.51 and 2.37, respectively), congenital anomaly (1.37 and 1.33), central nervous system malformation (3.57 and 2.25), low birth weight (1.90 and 1.97), and a low Apgar score at 5 min (2.63 and 1.3). The use of ASMs may introduce an additional risk of small for gestational age; the adjusted odds ratio was 1.51., Conclusion: Women with epilepsy, irrespective of their exposure to ASMs, had a slightly elevated risk of pregnancy and perinatal complications. Puerperal cerebrovascular diseases may be a hidden risk for women with epilepsy., (© 2023 The Authors. Brain and Behavior published by Wiley Periodicals LLC.)

Background: Previous serological studies have indicated an association between viruses and atypical pathogens and Chronic Fatigue Syndrome (CFS). This study aims to investigate the correlation between infections from common pathogens, including typical bacteria, and the subsequent risk of developing CFS. The analysis is based on data from Taiwan's National Health Insurance Research Database., Methods: From 2000 to 2017, we included a total of 395,811 cases aged 20 years or older newly diagnosed with infection. The cases were matched 1:1 with controls using a propensity score and were followed up until diagnoses of CFS were made., Results: The Cox proportional hazards regression analysis was used to estimate the relationship between infection and the subsequent risk of CFS. The incidence density rates among non-infection and infection population were 3.67 and 5.40 per 1000 person-years, respectively (adjusted hazard ratio [HR] = 1.5, with a 95% confidence interval [CI] 1.47-1.54). Patients infected with Varicella-zoster virus, Mycobacterium tuberculosis, Escherichia coli, Candida, Salmonella, Staphylococcus aureus and influenza virus had a significantly higher risk of CFS than those without these pathogens (p < 0.05). Patients taking doxycycline, azithromycin, moxifloxacin, levofloxacin, or ciprofloxacin had a significantly lower risk of CFS than patients in the corresponding control group (p < 0.05)., Conclusion: Our population-based retrospective cohort study found that infection with common pathogens, including bacteria, viruses, is associated with an increased risk of developing CFS., (© 2023. The Author(s).)

Background: The risk of mortality is relatively high among patients who visit the emergency department (ED), and stratifying patients at high risk can help improve medical care. This study aimed to create a machine-learning model that utilizes the standard 12-lead ECG to forecast acute mortality risk in ED patients., Methods: The database included patients who visited the EDs and underwent standard 12-lead ECG between October 2007 and December 2017. A convolutional neural network (CNN) ECG model was developed to classify survival and mortality using 12-lead ECG tracings acquired from 345,593 ED patients. For machine learning model development, the patients were randomly divided into training, validation and testing datasets. The performance of the mortality risk prediction in this model was evaluated for various causes of death., Results: Patients who visited the ED and underwent one or more ECG examinations experienced a high incidence of 30-day mortality [18,734 (5.42%)]. The developed CNN model demonstrated high accuracy in predicting acute mortality (hazard ratio 8.50, 95% confidence interval 8.20-8.80) with areas under the receiver operating characteristic (ROC) curve of 0.84 for the 30-day mortality risk prediction models. This CNN model also demonstrated good performance in predicting one-year mortality (hazard ratio 3.34, 95% confidence interval 3.30-3.39). This model exhibited good predictive performance for 30-day mortality not only for cardiovascular diseases but also across various diseases., Conclusions: The machine learning-based ECG model utilizing CNN screens the risks for 30-day mortality. This model can complement traditional early warning scoring indexes as a useful screening tool for mortality prediction., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Chang, Liu, Huang, Hsu, Chen, Lin, Tsai, Chou, Wen, Wo, Lee, Liu, Wang and Kuo.)

Objective: Obstructive sleep apnea is a global health concern, and several tools have been developed to screen its severity. However, most tools focus on respiratory events instead of sleep arousal, which can also affect sleep efficiency. This study employed easy-to-measure parameters-namely heart rate variability, oxygen saturation, and body profiles-to predict arousal occurrence., Methods: Body profiles and polysomnography recordings were collected from 659 patients. Continuous heart rate variability and oximetry measurements were performed and then labeled based on the presence of sleep arousal. The dataset, comprising five body profiles, mean heart rate, six heart rate variability, and five oximetry variables, was then split into 80% training/validation and 20% testing datasets. Eight machine learning approaches were employed. The model with the highest accuracy, area under the receiver operating characteristic curve, and area under the precision recall curve values in the training/validation dataset was applied to the testing dataset and to determine feature importance., Results: InceptionTime, which exhibited superior performance in predicting sleep arousal in the training dataset, was used to classify the testing dataset and explore feature importance. In the testing dataset, InceptionTime achieved an accuracy of 76.21%, an area under the receiver operating characteristic curve of 84.33%, and an area under the precision recall curve of 86.28%. The standard deviations of time intervals between successive normal heartbeats and the square roots of the means of the squares of successive differences between normal heartbeats were predominant predictors of arousal occurrence., Conclusions: The established models can be considered for screening sleep arousal occurrence or integrated in wearable devices for home-based sleep examination., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Background: Blood shortage is a persistent problem affecting Taiwan's health-care system. The theory of planned behavior (TPB) has been commonly used in studies of health advocacy. The purpose of this study was to develop a questionnaire measuring clinicians' intention to prescribe transfusion based on the TPB., Method: A questionnaire comprising 15 items for assessing clinicians' intention to prescribe blood transfusion was developed, and it collected demographic characteristics, tested patient blood management (PBM) and perceived knowledge of PBM. Furthermore, the questionnaire contained four subscales related to the TPB. A total of 129 clinicians participated in this pilot study between July and December2020. Item analysis and exploratory factor analysis were conducted to examine the validity and reliability of this measurement instrument., Results: The results indicated no statistically significant correlations between the demographic characteristics and PBM test scores. Regarding perceived knowledge, the results of a one-way analysis of variance revealed that the effect of age, hierarchy of doctors, and education level were significant. In terms of subjective norms, a significant effect on education level was noted [t (129) = 2.28, p < 0.05], with graduate school graduates receiving higher scores than college graduates. An analysis of variance demonstrated the effects of hierarchy, education level, and medical specialty on perceived behavioral control. The results of the regression analyses revealed that perceived knowledge (β = 0.32, p < 0.01) and subjective norms (β = 0.22, p < 0.05) were significantly related to clinicians' behavioral intentions., Conclusions: This study revealed that factors affecting clinicians' blood transfusion management can be explained using the TPB-based questionnaire. This study demonstrated that physicians' perceptions of whether most people approve of PBM and their self-assessment of their PBM knowledge affect their intentions to proceed with PBM. According to this finding, a support system among physicians must be established and maintained to increase physicians' confidence in promoting PBM., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Occult scaphoid fractures on initial radiographs of an injury are a diagnostic challenge to physicians. Although artificial intelligence models based on the principles of deep convolutional neural networks (CNN) offer a potential method of detection, it is unknown how such models perform in the clinical setting., Questions/purposes: (1) Does CNN-assisted image interpretation improve interobserver agreement for scaphoid fractures? (2) What is the sensitivity and specificity of image interpretation performed with and without CNN assistance (as stratified by type: normal scaphoid, occult fracture, and apparent fracture)? (3) Does CNN assistance improve time to diagnosis and physician confidence level?, Methods: This survey-based experiment presented 15 scaphoid radiographs (five normal, five apparent fractures, and five occult fractures) with and without CNN assistance to physicians in a variety of practice settings across the United States and Taiwan. Occult fractures were identified by follow-up CT scans or MRI. Participants met the following criteria: Postgraduate Year 3 or above resident physician in plastic surgery, orthopaedic surgery, or emergency medicine; hand fellows; and attending physicians. Among the 176 invited participants, 120 completed the survey and met the inclusion criteria. Of the participants, 31% (37 of 120) were fellowship-trained hand surgeons, 43% (52 of 120) were plastic surgeons, and 69% (83 of 120) were attending physicians. Most participants (73% [88 of 120]) worked in academic centers, whereas the remainder worked in large, urban private practice hospitals. Recruitment occurred between February 2022 and March 2022. Radiographs with CNN assistance were accompanied by predictions of fracture presence and gradient-weighted class activation mapping of the predicted fracture site. Sensitivity and specificity of the CNN-assisted physician diagnoses were calculated to assess diagnostic performance. We calculated interobserver agreement with the Gwet agreement coefficient (AC1). Physician diagnostic confidence was estimated using a self-assessment Likert scale, and the time to arrive at a diagnosis for each case was measured., Results: Interobserver agreement among physicians for occult scaphoid radiographs was higher with CNN assistance than without (AC1 0.42 [95% CI 0.17 to 0.68] versus 0.06 [95% CI 0.00 to 0.17], respectively). No clinically relevant differences were observed in time to arrive at a diagnosis (18 ± 12 seconds versus 30 ± 27 seconds, mean difference 12 seconds [95% CI 6 to 17]; p < 0.001) or diagnostic confidence levels (7.2 ± 1.7 seconds versus 6.2 ± 1.6 seconds; mean difference 1 second [95% CI 0.5 to 1.3]; p < 0.001) for occult fractures., Conclusion: CNN assistance improves physician diagnostic sensitivity and specificity as well as interobserver agreement for the diagnosis of occult scaphoid fractures. The differences observed in diagnostic speed and confidence is likely not clinically relevant. Despite these improvements in clinical diagnoses of scaphoid fractures with the CNN, it is unknown whether development and implementation of such models is cost effective., Level of Evidence: Level II, diagnostic study., Competing Interests: All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research® editors and board members are on file with the publication and can be viewed on request., (Copyright © 2023 by the Association of Bone and Joint Surgeons.)

Objective: To provide better preconceptional and prenatal counselling to patients with sjögren syndrome (SS)., Methods: In total, 2 100 143 pregnancies between 2004 and 2014 were identified in the Taiwan National Health Insurance database and birth registry. The maternal history of SS was ascertained, and data were compared between pregnant women with and without SS. We assessed the odds ratios and 95% CIs of fetal-neonatal and maternal outcomes., Results: There were 449 pregnancies in women with SS and 2 099 694 pregnancies in women without SS. The risks of still birth [odds ratio (OR) = 2.14, 95% CI = 1.01, 4.55], low birth weight (<2500 g, OR = 2.53, 95% CI = 1.92, 3.33), small for gestational age (OR = 2.03, 95% CI = 1.57, 2.03) and fetal distress (OR = 1.72, 95% CI = 1.2, 2.45) as well as maternal risks of pulmonary oedema (OR = 11.64, 95% CI = 1.62, 83.48), shock (OR = 6.07, 95% CI = 1.51, 24.3) and respiratory distress (OR = 5.61, 95% CI = 1.39, 22.6) were higher in the SS group than in the non-SS group., Conclusion: Women with SS have significant risks of adverse fetal-neonatal and maternal outcomes and must undergo prenatal counselling to understand the risks involved before conception., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Cancer treatment in female adolescent and young adult (AYA) cancer survivors (i.e., those diagnosed between 15 and 39 years of age) may adversely affect multiple bodily functions, including the reproductive system., Methods: We initially assembled a retrospective, nationwide population-based cohort study by linking data from two nationwide Taiwanese data sets. We subsequently identified first pregnancies and singleton births to AYA cancer survivors (2004-2018) and select AYA without a previous cancer diagnosis matched to AYA cancer survivors for maternal age and infant birth year., Results: The study cohort consisted of 5151 and 51,503 births to AYA cancer survivors and matched AYA without a previous cancer diagnosis, respectively. The odds for overall pregnancy complications (odds ratio [OR], 1.09; 95% confidence interval [CI], 1.01-1.18) and overall adverse obstetric outcomes (OR, 1.07; 95% CI, 1.01-1.13) were significantly increased in survivors compared with matched AYA without a previous cancer diagnosis. Specifically, cancer survivorship was associated with an increased risk of preterm labour, labour induction, and threatened abortion or threatened labour requiring hospitalisation., Conclusions: AYA cancer survivors are at increased risk for pregnancy complications and adverse obstetric outcomes. Efforts to integrate individualised care into clinical guidelines for preconception and prenatal care should be thoroughly explored., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: Family disease history plays a vital role in type 2 diabetes mellitus (T2DM) risk. However, the familial aggregation of T2DM among different kinship relatives warrants further investigation., Methods: This nationwide kinship relationship study collected 2000-2016 data of two to five generations of the Taiwanese population from the National Health Insurance Research Database. Approximately 4 million family trees were constructed from the records of 20, 890, 264 Taiwanese residents during the study period. T2DM was diagnosed on the basis of ICD-9-CM codes 250.x0 or 250.x2, with three consecutive related prescriptions. The Cox proportional hazard model was used for statistical analysis., Results: Compared with their counterparts, individuals who had first-degree relatives with T2DM were more likely to develop T2DM during the follow-up period (hazard ratio [HR], 2.37-27.75), followed by individuals who had second-degree relatives with T2DM (HR, 1.29-1.88). T2DM relative risk was higher in those with an affected mother than in those with affected father. The HR for T2DM was 20.32 (95%CI = 15.64-26.42) among male individuals with an affected twin brother, whereas among female individuals with an affected twin sister, it was 60.07 (95%CI = 40.83-88.36). The HRs presented a dose-response relationship with the number of affected family members., Conclusion: The study suggests a significant familial aggregation of T2DM occurrence; these findings could aid in identifying the high-risk group for T2DM and designing early intervention strategies and treatment plans., Competing Interests: Conflicts of interest The authors declare no competing interests., (Copyright © 2022 Chang Gung University. Published by Elsevier B.V. All rights reserved.)

Background: The burden of osteoarthritis (OA) in UK primary care has not been investigated thoroughly., Aim: To estimate healthcare use and mortality in people with OA (overall and joint specific)., Design and Setting: A matched cohort study of adults with an incident diagnosis of OA in primary care were selected for the study using UK national Clinical Practice Research Datalink (CPRD) electronic records., Method: Healthcare utilisation was measured as the annual average number of primary care consultations and admissions to hospital after the index date for any cause and all-cause mortality data in 221 807 people with OA and an equal number of controls (with no OA diagnosis) who were matched to the case patients by age (standard deviation 2 years), sex, practice, and year of registration. The associations between OA and healthcare utilisation and all-cause mortality were estimated using multinomial logistic regression and Cox regression, respectively, adjusting for covariates., Results: The mean age of the study population was 61 years and 58% were female. In the OA group, the median number of primary care consultations per year after the index date was 10.91 compared with 9.43 in the non-OA control group ( P = 0.001) OA was associated with an increased risk of GP consultation and admission to hospital. The adjusted hazard ratio for all-cause mortality was 1.89 (95% confidence interval [CI] = 1.85 to 1.93) for any OA, 2.09 (95% CI = 2.01 to 2.19) for knee OA, 2.08 (95% CI = 1.95 to 2.21) for hip OA, and 1.80 (95% CI = 1.58 to 2.06) for wrist/hand OA, compared with the respective non-OA control group., Conclusion: People with OA had increased rates of GP consultations, admissions to hospital, and all-cause mortality that varied across joint sites., (© The Authors.)

Background: Lung cancer, especially non-small cell lung cancer (NSCLC), is one of the leading causes of cancer-related deaths worldwide. Vincristine (VCR) is a chemotherapeutic agent for lung cancers; however, its effectiveness is limited by side effects and the development of drug resistance. Patchouli alcohol (PA), from Pogostemon cablin extract, is known to possess anti-inflammatory and anticancer properties. In this study, we investigated the role of PA in inducing reactive oxygen species (ROS)-mediated DNA damage in A549 and VCR-resistant A549/V16 NSCLC cells., Methods: The anticancer potential of PA was studied using the MTT assay, colony formation, flow cytometry analysis, western blotting, DCFDA staining, immunofluorescence staining, and TUNEL assay techniques., Results: The intracellular ROS levels were enhanced in PA-treated cells, activating the CHK1 and CHK2 signaling pathways. PA further inhibited proliferation and colony-forming abilities and induced cell cycle arrest at the G 0 /G 1 phase by regulating p53/p21 and CDK2/cyclin E1 expression. Moreover, PA increased the percentage of cells in the subG 1 phase and induced apoptosis by activating the Bax/caspase-9/caspase-3 intrinsic pathway. In addition, drug resistance (p-glycoprotein) and cancer stem cell (CD44 and CD133) markers were downregulated after PA treatment. Furthermore, combining PA and cisplatin exhibited synergistic inhibitory activity in A549 and A549/V16 cells., Conclusions: PA induced ROS-mediated DNA damage, triggered cell cycle arrest and apoptosis, attenuated drug resistance and cancer stem cell phenotypes, and synergistically inhibited proliferation in combination with cisplatin. These findings suggest that PA has the potential to be used for the treatment of NSCLC with or without VCR resistance., (© 2023 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.)

COVID-19-associated mold infection (CAMI) is defined as development of mold infections in COVID-19 patients. Co-pathogenesis of viral and fungal infections include the disruption of tissue barrier following SARS CoV-2 infection with the damage in the alveolar space, respiratory epithelium and endothelium injury and overwhelming inflammation and immune dysregulation during severe COVID-19. Other predisposing risk factors permissive to fungal infections during COVID-19 include the administration of immune modulators such as corticosteroids and IL-6 antagonist. COVID-19-associated pulmonary aspergillosis (CAPA) and COVID-19-associated mucormycosis (CAM) is increasingly reported during the COVID-19 pandemic. CAPA usually developed within the first month of COVID infection, and CAM frequently arose 10-15 days post diagnosis of COVID-19. Diagnosis is challenging and often indistinguishable during the cytokine storm in COVID-19, and several diagnostic criteria have been proposed. Development of CAPA and CAM is associated with a high mortality despiteappropriate anti-mold therapy. Both isavuconazole and amphotericin B can be used for treatment of CAPA and CAM; voriconazole is the primary agent for CAPA and posaconazole is an alternative for CAM. Aggressive surgery is recommended for CAM to improve patient survival. A high index of suspicion and timely and appropriate treatment is crucial to improve patient outcome., (Copyright © 2022. Published by Elsevier B.V.)

Aims: Limited data compared antiarrhythmic drugs (AADs) with concomitant non-vitamin K antagonist oral anticoagulants in atrial fibrillation patients, hence the aim of the study., Methods and Results: National health insurance database were retrieved during 2012-17 for study. We excluded patients not taking AADs, bradycardia, heart block, heart failure admission, mitral stenosis, prosthetic valve, incomplete demographic data, and follow-up <3 months. Outcomes were compared in Protocol 1, dronedarone vs. non-dronedarone; Protocol 2, dronedarone vs. amiodarone; and Protocol 3, dronedarone vs. propafenone. Outcomes were acute myocardial infarction (AMI), ischaemic stroke/systemic embolism, intracranial haemorrhage (ICH), major bleeding, cardiovascular death, all-cause mortality, and major adverse cardiovascular event (MACE) (including AMI, ischaemic stroke, and cardiovascular death). In Protocol 1, 2298 dronedarone users and 6984 non-dronedarone users (amiodarone = 4844; propafenone = 1914; flecainide = 75; sotalol = 61) were analysed. Dronedarone was associated with lower ICH (HR = 0.61, 95% CI = 0.38-0.99, P = 0.0436), cardiovascular death (HR = 0.24, 95% CI = 0.16-0.37, P < 0.0001), all-cause mortality (HR = 0.33, 95% CI = 0.27-0.42, P < 0.0001), and MACE (HR = 0.56, 95% CI = 0.45-0.70, P < 0.0001). In Protocol 2, 2231 dronedarone users and 6693 amiodarone users were analysed. Dronedarone was associated with significantly lower ICH (HR = 0.53, 95%=CI 0.33-0.84, P = 0.0078), cardiovascular death (HR = 0.20, 95% CI = 0.13-0.31, P < 0.0001), all-cause mortality (HR 0.27, 95% CI 0.22-0.34, P < 0.0001), and MACE (HR = 0.53, 95% CI = 0.43-0.66, P < 0.0001), compared with amiodarone. In Protocol 3, 812 dronedarone users and 2436 propafenone users were analysed. There were no differences between two drugs for primary and secondary outcomes., Conclusion: The use of dronedarone with NOACs was associated with cardiovascular benefits in an Asian population, compared with non-dronedarone AADs and amiodarone., Competing Interests: Conflict of interest: This investigator-sponsored study received funding from Sanofi. Victor Chien-Chia Wu, Chun-Li Wang, and Shang-Hung Chang received grants and support from Sanofi. The remaining authors have nothing to disclose., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Alzheimer's disease (AD) is generally diagnosed using advanced imaging, but recent research suggests early screening using biomarkers in peripheral blood is feasible; among them, plasma tau proteins phosphorylated at threonine 231, threonine 181, and threonine 217 (p-tau217) are potential targets. A recent study indicates that the p-tau217 protein is the most efficacious biomarker. However, a clinical study found a pg/ml threshold for AD screening beyond standard detection methods. A biosensor with high sensitivity and specificity p-tau217 detection has not yet been reported. In this study, we developed a label-free solution-gated field effect transistor (SGFET)-based biosensor featuring a graphene oxide/graphene (GO/G) layered composite. The top layer of bilayer graphene grown using chemical vapor deposition was functionalized with oxidative groups serving as active sites for forming covalent bonds with the biorecognition element (antibodies); the bottom G could act as a transducer to respond to the attachment of the target analytes onto the top GO conjugated with the biorecognition element via π-π interactions between the GO and G layers. With this unique atomically layered G composite, we obtained a good linear electrical response in the Dirac point shift to p-tau217 protein concentrations in the range of 10 fg/ml to 100 pg/ml. The biosensor exhibited a high sensitivity of 18.6 mV/decade with a high linearity of 0.991 in phosphate-buffered saline (PBS); in human serum albumin, it showed approximately 90% of the sensitivity (16.7 mV/decade) in PBS, demonstrating high specificity. High stability of the biosensor was also displayed in this study., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

This study tested the effectiveness of a 6-month vitality acupunch (VA) exercise program on muscle mass, hand grip strength, and sleep quality in institutional older adults with probable sarcopenia. A cluster randomized controlled trial was conducted. A total of 103 older adults were assigned to the experimental group ( n = 52) and control group ( n = 51) according to the institution they inhabited. After the 6-month VA exercise intervention, the experimental group showed significant increases in muscle mass ( F = 5.93, p = .017), hand grip strength ( F = 56.73, p < .001), and improved sleep quality ( F = 23.20, p < .001) compared to the control group. Based on the meridian theory that promotes qi and blood circulation, VA exercise has positive effects on muscle mass, hand grip strength, and sleep quality in older adults with probable sarcopenia.

Heterojunction engineering in catalyst structures is a promising approach for solving the main restriction of the narrow photoabsorption range and quick recombination of photogenerated charge carriers in the photocatalysts. Herein, a simple, eco-friendly, non-toxic, and novel Z-scheme heterojunction of nanoflower-like NiS/BiOI was systematically designed using the low-temperature solvothermal and precipitation methods. The physicochemical and photo-electrochemical properties of the as-synthesized nanomaterials were characterized using XRD, FESEM, FT-IR, XPS, BET, UV-vis, PL, and EIS. NiS/BiOI nanomaterials exhibited a wide photoabsorption range (200-1000 nm), a narrow bandgap energy (1.76 eV), a large surface area (35.82 m 2  g -1 ), and a low charge carrier recombination rate because of the synergistic effects of the NiS and BiOI photocatalysts, which could be the basis for superior photocatalytic efficiency. Particularly, the optimal 40% NiS/BiOI nanocomposite exhibited better stability and efficiency than the pure NiS and BiOI. The maximum degradation efficiency of rhodamine B (RhB) was 99.8% after 200 min, tetracycline (TC) was 96.3% after 140 min, and the photoreduction of Cr(VI) was 92.8% after 180 min rather than the pure NiS and BiOI under visible light irradiation. The constant rate (k) of RhB was approximately 10 and 4, TC was 12 and 4, and Cr(VI) was 10 and 8 times that of pristine NiS and BiOI, respectively. Radical trapping experiments and Tauc plot analysis proposed the design of the plausible Z-scheme reaction mechanism between NiS and BiOI, which has a crucial role in the rate of transportation and separation of electron/hole pairs. This investigation provides a venue for the design of a photoactive NiS-based nanocomposite for environmental remediation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Background: Psoriasis is a chronic autoimmune disease involving both environmental and genetic risk factors. Maternal psoriasis often results in poor pregnancies that influence both mothers and newborns. However, the influence of paternal psoriasis on the newborn remains unknown. The aim of this study was to investigate whether paternal psoriasis is associated with increased risk of adverse neonatal outcomes, within a nationwide population-based data setting., Methods: Singleton pregnancies were identified in the Taiwan National Health Insurance database and National Birth Registry between 2004-2011 and classified into four study groups according to whether mothers and spouses had psoriasis (paternal(-)/maternal(-), paternal(+)/maternal(-), paternal(-)/maternal(+), and paternal(+)/maternal(+)). Data were analyzed retrospectively. Adjusted odds ratios (aOR) or hazard ratios (aHR) were calculated to evaluate the risk of neonatal outcomes between groups., Results: A total of 1,498,892 singleton pregnancies were recruited. Newborns of fathers with psoriasis but not of mothers with psoriasis were associated with an aHR (95% CI) of 3.69 (1.65-8.26) for psoriasis, 1.13 (1.06-1.21) for atopic dermatitis and 1.05 (1.01-1.10) for allergic rhinitis. Newborns of mothers with psoriasis but not of fathers with psoriasis were associated with an aOR (95% CI) of 1.26 (1.12-1.43) for low birth weight (<2500 g) and 1.64 (1.10-2.43) for low Apgar scores, and an aHR of 5.70 (2.71-11.99) for psoriasis., Conclusion: Newborns of fathers with psoriasis are associated with significantly higher risk of developing atopic dermatitis, allergic rhinitis and psoriasis. Caution is advised for adverse neonatal outcomes when either or both parents have psoriasis., Competing Interests: Author Y-HH has conducted clinical trials or received honoraria as a consultant for Abbvie, Celgene, Janssen-Cilag Pharmaceuticals, Novartis, Pfizer Pharmaceuticals. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Huang, Chiou, Yang and Kuo.)

Background: Efficacy of combination therapy with methotrexate and biological disease-modifying antirheumatic drugs is well established in the management of patients with rheumatoid arthritis; however, the optimal dose of methotrexate to administer with a tumour necrosis factor inhibitor remains unclear. We aimed to clarify the efficacy and safety of adalimumab combined with reduced methotrexate dose compared with the maximum tolerated methotrexate dose in patients with rheumatoid arthritis and an inadequate response to methotrexate monotherapy., Methods: In this open-label, randomised controlled trial, we recruited methotrexate-naive patients with rheumatoid arthritis and a disease duration of less than 2 years across 24 secondary or tertiary care hospitals across Japan, South Korea, and Taiwan. At initiation, methotrexate was given orally and increased to the maximum tolerated dose by week 12. Patients who did not achieve remission on the basis of the Simplified Disease Activity Index (SDAI) at week 24 were randomly assigned (1:1) to receive adalimumab (40 mg biweekly) combined with a continued maximum tolerated dose of methotrexate or adalimumab combined with a reduced dose of methotrexate. The primary endpoint was non-inferiority of adalimumab plus reduced-dose methotrexate to adalimumab plus maximal-dose methotrexate based on SDAI remission at week 48, assessed in the modified full-analysis set with a pre-specified non-inferiority margin of -15%, based on a two-sided 90% CI. Adverse events were assessed in the safety analysis set. This trial is registered with ClinicalTrials.gov, NCT03505008 and has been completed., Findings: From April 18, 2018, to June 2, 2020, from 323 patients screened, 300 were enrolled, and 291 patients were included in the full analysis set. The mean age was 57·7 years (SD 15·2), 217 (75%) were female, 74 (25%) were male, and all patients were of Asian ethnicity. The mean SDAI at study enrolment was 26·5 (SD 12·4). 52 patients discontinued the study before week 24 or at week 24 before randomisation. At week 24, 105 (36%) of 291 patients achieved remission and continued methotrexate monotherapy through week 48. 134 (46%) did not achieve remission at week 24 and were randomly assigned to receive adalimumab plus the maximum tolerated dose of methotrexate (n=68) or adalimumab plus reduced-dose methotrexate (n=66). Remission at week 48 was achieved in 25 (38%) of 66 and 27 (44%) of 61 patients, respectively, with an adjusted risk difference of 6·4% (90% CI -7·0 to 19·8), which met the non-inferiority margin of -15%. Adverse events after week 24 tended to be more frequent in the maximum tolerated dose group than in the reduced-dose group (24 [35%] vs 13 [20%], p=0·054). Between week 24 and 48, there were 14 serious adverse events (6 in the methotrexate monotherapy group, 5 in the adalimumab plus maximal-dose methotrexate, and 3 in the adalimumab plus reduced-dose methotrexate group), and no deaths., Interpretation: The MIRACLE study showed that the efficacy of adalimumab combined with reduced methotrexate dose was not inferior to that with the maximum tolerated methotrexate dose, with a tendency to a better safety profile., Funding: Eisai., Competing Interests: Declaration of interests HTam has received speaker honoraria from AbbVie and Eisai. KI has received grants from Mitsubishi-Tanabe Pharma, speaker honoraria from AbbVie, Eisai, Mitsubishi-Tanabe Pharma, Astellas Pharma, UCB, Daiichi-Sankyo, Eli Lilly, Gilead Sciences, Asahi Kasei Pharma, Chugai Pharma, and Bristol-Myers Squibb. TM received grants, research support, or speaker fees from AbbVie, Astellas Pharma, AstraZeneca, Bristol-Myers Squibb, Chugai Pharma, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead Sciences, Kirin, Pfizer, and UCB. KS has received grants, research support from Novartis, Astellas Pharma, AbbVie, Bristol-Myers Squibb, and Yuhan Corporation, and consulting fees from KD Bio. SH has received grants from AbbVie, Asahi Kasei Pharma, Eisai, Otsuka, Sanofi, Shionogi, Chugai, Pfizer, Mitsubishi-Tanabe Pharma, Eli Lilly, and UCB; speaker honoraria from AbbVie, Asahi Kasei Pharma, Astellas Pharma, Ayumi Pharma, Bristol-Myers Squibb, Celgene Corporation, Chugai Pharma, Eisai, Gilead Sciences, GlaxoSmithKline, Eli Lilly, Janssen, Kyorin Pharmaceutical, Novartis, Pfizer, Sanofi, Mitsubishi-Tanabe Pharma, and UCB; paid instructor fees from AbbVie and Mitsubishi-Tanabe Pharma; and consulting fees from AbbVie, Astellas Pharma, Bristol-Myers Squibb, Eisai, Gilead Sciences, and Eli Lilly. SS has received grants from Asahi Kasei Pharma, AbbVie, Chugai Pharma, Eli Lilly, Eisai, Teijin, Pfizer, Ayumi Pharma, and Daiichi Sankyo. HY has received research grants from Asahi Kasei Pharma, Mitsubishi-Tanabe Pharma, Chugai Pharma, Eisai, and Taisho Pharma; speaker fees from AbbVie, Janssen, Gilead Sciences, Nippon Boehringer Ingelheim, and Nippon Shinyaku. MK has received grants from Nippon Boehringer Ingelheim, Ono Pharma, and MBL; royalties from MBL; consulting fees from Nippon Boehringer Ingelheim, Mochida Pharmaceutical, and Kissei Pharmaceutical; speaker honoraria from AbbVie, Asahi Kasei Pharma, Astellas Pharma, Chugai Pharma, Nippon Shinyaku, Mitsubishi-Tanabe Pharma, and Nippon Boehringer Ingelheim. TI has received payment or honoraria from AbbVie, Asahi Kasei Pharma, Astellas Pharma, Bristol-Myers Squibb, Chugai Pharma, Eisai, Eli Lilly, Gilead Sciences, Janssen, Pfizer, Boehringer Ingelheim, Novartis, and GlaxoSmithKline. HK has received a research grant from AbbVie, Asahi Kasei Pharma, Boehringer, Chugai Pharma, Eisai, Mitsubishi-Tanabe Pharma, and Taisho; speaker honoraria fees from AbbVie, Asahi Kasei Pharma, Astellas Pharma, Boehringer, Bristol-Myers Squibb, Chugai Pharma, Eisai, Eli Lilly, Gilead Sciences, Janssen, Mitsubishi-Tanabe Pharma, Novartis, Pfizer, and UCB. TK has received grants or research support and speaker fees from AbbVie, Astellas Pharma, Bristol-Myers Squibb, Chugai Pharma, Daiichi-Sankyo, Eli Lilly, Pfizer, Eisai, UCB, and Taisho. TTan, MM, and HM are shareholders and employees of Eisai. YS has received speaker honoraria from Eisai and Kowa Pharmaceuticals; and consulting fees from Mochida Pharmaceutical. TTak received grants from AbbVie, Asahi Kasei Pharma, Ayumi Pharma, Chugai Pharma, Eisai, Eli Lilly, Mitsubishi-Tanabe Pharma, and Ono Pharma; consulting fees from AbbVie, Chugai Pharma, Eli Lilly, and Gilead Sciences, and Mitsubishi-Tanabe Pharma; and payment or honoraria from AbbVie, Asahi Kasei Pharma, Astellas Pharma, Bristol-Myers Squibb, Chugai Pharma, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead Sciences, Janssen, Mitsubishi-Tanabe Pharma, and Pfizer. YK has received grants from AbbVie, Asahi Kasei Pharma, Ayumi Pharma, Chugai Pharma, Eisai, Mitsubishi-Tanabe Pharma, Boehringer Ingelheim, and Asahi Kasei Pharma; payment or honoraria from AbbVie, Asahi Kasei Pharma, Astellas Pharma, Bristol-Myers Squibb, Chugai Pharma, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead Sciences, Janssen, Mitsubishi-Tanabe Pharma, Pfizer, Boehringer Ingelheim, Asahi Kasei Pharma, and Novartis. All other authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)