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Abstract Pathogenic germline mutations in the P-type copper-transporting ATPase (ATP7B) gene cause Wilson’s disease (WD), a hereditary disorder characterized by disrupted copper metabolism. The Arg778Leu (R778L) mutation in exon 8 is prevalent among individuals with WD in East Asia and is associated with more severe phenotypes. In this study, we generated a WD mouse model harboring R778L mutation (R778L mice) using CRISPR/Cas9. R778L mice exhibit a range of pathological characteristics resembling those of patients with WD and the same point mutations, including aberrant copper metabolism, pathological cellular injury, inflammation, and severe hepatic fibrosis. At 3–5 months of age, these mice started to display neurological deficits in motor coordination and cognitive dysfunction, accompanied by increased expression of inflammatory cytokines in the central nervous system. Microglia in the striatum and cortex exhibit significant activation, shorter processes, and decreased branch points. However, the Cu2+ levels in the brain tissue of R778L mice did not differ significantly from those of wild-type mice. Notably, inhibition of hepatic inflammation with PJ34 or siNfkb markedly alleviated the deficiencies in cognitive performance and improved locomotor activity in R778L mice. Thus, this study establishes a novel murine model to investigate the pathophysiology of WD, highlights the liver-brain crosstalk responsible for neurological manifestations in individuals with WD caused by the R778L point mutation, and demonstrates the potential of modulating liver inflammation as a therapeutic strategy for alleviating the neurological manifestations of WD.

Abstract Au@Pt nanozyme, a bimetallic core–shell structure Au and Pt nanoparticle, has attracted significant attention due to its excellent catalytic activity and stability. Here, we propose that Au@Pt improves glucose tolerance and reduces TG after four weeks administration. The transcriptomic analysis of mouse liver tissues treated with Au@Pt nanozyme showed changes in genes related to glucose and lipid metabolism signaling pathways, including glycolysis/gluconeogenesis, pyruvate metabolism, PPAR signaling, and insulin signaling. Moreover, analysis of fecal samples from mice treated with Au@Pt nanozyme showed significant changes in the abundance of beneficial gut microbiota such as Dubosiella, Parvibacter, Enterorhabdus, Monoglobus, Lachnospiraceae_UCG-008, Lachnospiraceae_UCG-006, Lachnospiraceae_UCG-001, and Christensenellaceae_R-7_group. Combined multi-omics correlation analyses revealed that the modulation of glucose and lipid metabolism by Au@Pt was strongly correlated with changes in hepatic gene expression profiles as well as changes in gut microbial profiles. Overall, our integrated multi-omics analysis demonstrated that Au@Pt nanozyme could modulate glucose and lipid metabolism by regulating the expression of key genes in the liver and altering the composition of gut microbiota, providing new insights into the potential applications of Au@Pt nanozyme in the treatment of metabolic disorder. Graphical Abstract

Abstract Aortic valve replacement (AVR) is a critical procedure for patients with aortic valve diseases. This study compares the effectiveness of three minimally-invasive surgical approaches for AVR: totally thoracoscopic (TT), right anterior mini-thoracotomy, and upper mini-sternotomy. We analyzed retrospective data from 130 patients who underwent one of these surgeries, focusing on various factors such as duration of hospital stay, operation time, times for cardiopulmonary bypass and aortic cross-clamping, postoperative complications, levels of cardiac biomarkers, pain intensity using the Visual Analog Scale, and mid-term survival rates. Results show that while the TT method had the longest operation times, it also had the shortest hospital stays and faster pain reduction post-surgery. Although the TT group initially showed higher cardiac biomarker levels after surgery, these levels normalized by the third day, similar to the other groups. There were no significant differences in mid-term survival and major adverse cardiac and cerebrovascular event (MACCE) rates among the groups. These findings suggest that the TT method, despite longer surgical times, offers a quicker initial recovery, making it a viable option for AVR.

Abstract Objective Inflammation, malnutrition, and cancer are intricately interconnected. Despite this, only a few studies have delved into the relationship between inflammatory malnutrition and the risk of death among cancer survivors. This study aimed to specifically investigate the association between the categorically defined Naples prognostic score (NPS) and the prognosis of cancer survivors. Methods Data from 42,582 participants in the National Health and Nutrition Examination Survey (NHANES, 1999–2018) were subjected to analysis. Naples prognostic scores (NPS) were computed based on serum albumin (ALB), total cholesterol (TC), neutrophil to lymphocyte ratio (NLR), and lymphocyte to monocyte ratio (LMR), and participants were stratified into three groups accordingly. Cancer status was ascertained through a self-administered questionnaire, while mortality data were sourced from the National Death Index up to December 31, 2019. Multiple logistic regression was employed to estimate the odds ratio (OR) with a 95% confidence interval (CI) between NPS and cancer prevalence within the U.S. community population. Kaplan-Meier survival analysis and the Log-rank test were utilized to compare survival disparities among the three groups. Additionally, Cox proportional regression was utilized to estimate the hazard ratio (HR) with a 95% CI. Results The incidence of cancers was 9.86%. Among the participants, 8140 individuals (19.1%) were classified into Group 0 (NPS 0), 29,433 participants (69.1%) into Group 1 (NPS 1 or 2), and 5009 participants (11.8%) into Group 2 (NPS 3 or 4). After adjusting for confounding factors, the cancer prevalence for the highest NPS score yielded an odds ratio (OR) of 1.64 (95% CI: 1.36, 1.97) (P(for trend)

ABSTRACT The COVID-19 pandemic caused by SARS-CoV-2 has had a persistent and significant impact on global public health for 4 years. Recently, there has been a resurgence of seasonal influenza transmission worldwide. The co-circulation of SARS-CoV-2 and seasonal influenza viruses results in a dual burden on communities. Additionally, the pandemic potential of zoonotic influenza viruses, such as avian Influenza A/H5N1 and A/H7N9, remains a concern. Therefore, a combined vaccine against all these respiratory diseases is in urgent need. mRNA vaccines, with their superior efficacy, speed in development, flexibility, and cost-effectiveness, offer a promising solution for such infectious diseases and potential future pandemics. In this study, we present FLUCOV-10, a novel 10-valent mRNA vaccine created from our proven platform. This vaccine encodes hemagglutinin (HA) proteins from four seasonal influenza viruses and two avian influenza viruses with pandemic potential, as well as spike proteins from four SARS-CoV-2 variants. A two-dose immunization with the FLUCOV-10 elicited robust immune responses in mice, producing IgG antibodies, neutralizing antibodies, and antigen-specific cellular immune responses against all the vaccine-matched viruses of influenza and SARS-CoV-2. Remarkably, the FLUCOV-10 immunization provided complete protection in mouse models against both homologous and heterologous strains of influenza and SARS-CoV-2. These results highlight the potential of FLUCOV-10 as an effective vaccine candidate for the prevention of influenza and COVID-19.IMPORTANCEAmidst the ongoing and emerging respiratory viral threats, particularly the concurrent and sequential spread of SARS-CoV-2 and influenza, our research introduces FLUCOV-10. This novel mRNA-based combination vaccine, designed to counteract both influenza and COVID-19, by incorporating genes for surface glycoproteins from various influenza viruses and SARS-CoV-2 variants. This combination vaccine was highly effective in preclinical trials, generating strong immune responses and ensuring protection against both matching and heterologous strains of influenza viruses and SARS-CoV-2. FLUCOV-10 represents a significant step forward in our ability to address respiratory viral threats, showcasing potential as a singular, adaptable vaccine solution for global health challenges.

Abstract Nanozyme, characterized by outstanding and inherent enzyme-mimicking properties, have emerged as highly promising alternatives to natural enzymes owning to their exceptional attributes such as regulation of oxidative stress, convenient storage, adjustable catalytic activities, remarkable stability, and effortless scalability for large-scale production. Given the potent regulatory function of nanozymes on oxidative stress and coupled with the fact that reactive oxygen species (ROS) play a vital role in the occurrence and exacerbation of metabolic diseases, nanozyme offer a unique perspective for therapy through multifunctional activities, achieving essential results in the treatment of metabolic diseases by directly scavenging excess ROS or regulating pathologically related molecules. The rational design strategies, nanozyme-enabled therapeutic mechanisms at the cellular level, and the therapies of nanozyme for several typical metabolic diseases and underlying mechanisms are discussed, mainly including obesity, diabetes, cardiovascular disease, diabetic wound healing, and others. Finally, the pharmacokinetics, safety analysis, challenges, and outlooks for the application of nanozyme are also presented. This review will provide some instructive perspectives on nanozyme and promote the development of enzyme-mimicking strategies in metabolic disease therapy. Graphical Abstract

Abstract Aims This study aimed to explore the relationship between workplace bullying among nurses and their professional quality of life, as well as the mediating role of coping styles between the two factors. Background In China, the overall status of nurses' professional quality of life is not optimistic, and the problems of low compassion satisfaction and high compassion fatigue persist. Workplace bullying, which is a serious global issue, can negatively impact the mental health and professional quality of nurses. However, it has still not attracted enough attention from managers. Methods The study used a cross-sectional research design and surveyed 297 clinical nurses from two tertiary grade A hospitals in Wuhan, China. Data were collected through an online questionnaire survey from March to May 2022. The data were analyzed using descriptive statistical methods, including Pearson correlation analysis and structural equation modeling. Results The score for nurses' workplace bullying was 38.72 ± 12.30. The scores for the three dimensions of professional quality of life were 27.56 ± 4.79 for compassion satisfaction, 30.51 ± 4.33 for burnout, and 28.47 ± 4.65 for secondary trauma stress. The scores for positive coping style and negative coping style were 34.59 ± 5.72 and 20.34 ± 5.08 points, respectively. Workplace bullying had a direct negative effect on compassion satisfaction, as well as positive direct effects on burnout and secondary traumatic stress. Coping styles played a mediating effect between workplace bullying and the pairwise relationships of compassion satisfaction, burnout, and secondary trauma stress. Conclusion Workplace bullying hurts nurses' professional quality of life while coping styles plays an mediating role between workplace bullying and professional quality of life. Nursing managers can improve nurses' professional quality of life by reducing workplace bullying and enhancing positive coping style. Implications for nursing management Nursing managers can employ management wisdom and techniques to mitigate the presence and detrimental effects of workplace bullying. This, in turn, promotes a positive work environment and enhances the professional quality of life for nurses.

Type 2 diabetes mellitus (T2DM) as a chronic metabolic disease has become a global public health problem. Insulin resistance (IR) is the main pathogenesis of T2DM. Oxidative stress refers to an imbalance between free radical production and the antioxidant system, causing insulin resistance and contributing to the development of T2DM via several molecular mechanisms. Besides, the reduction in hepatic glycogen synthesis also leads to a decrease in peripheral insulin sensitivity. Thus, reducing oxidative stress and promoting glycogen synthesis are both targets for improving insulin resistance and treating T2DM. The current study aims to investigate the pharmacological effects of single-atom Ce-N-C nanozyme (SACe-N-C) on the improvement of insulin resistance and to elucidate its underlying mechanisms using HFD/STZ-induced C57BL/6J mice and insulin-resistant HepG2 cells. The results indicate that SACe-N-C significantly improves hepatic glycogen synthesis and reduces oxidative stress, as well as pancreatic and liver injury. Specifically, compared to the T2DM model group, fasting blood glucose decreased by 29%, hepatic glycogen synthesis increased by 17.13%, and insulin secretion increased by 18.87%. The sod and GPx in the liver increased by 17.80% and 25.28%, respectively. In terms of mechanism, SACe-N-C modulated glycogen synthesis through the PI3K/AKT/GSK3β signaling pathway and activated the Keap1/Nrf2 pathway to alleviate oxidative stress. Collectively, this study suggests that SACe-N-C has the potential to treat T2DM.

This work provides a new multimodal fusion generative adversarial net (GAN) model, Multiple Conditions Transform W-net (MCSTransWnet), which primarily uses femtosecond laser arcuate keratotomy surgical parameters and preoperative corneal topography to predict postoperative corneal topography in astigmatism-corrected patients. The MCSTransWnet model comprises a generator and a discriminator, and the generator is composed of two sub-generators. The first sub-generator extracts features using the U-net model, vision transform (ViT) and a multi-parameter conditional module branch. ​The second sub-generator uses a U-net network for further image denoising. The discriminator uses the pixel discriminator in Pix2Pix. Currently, most GAN models are convolutional neural networks; however, due to their feature extraction locality, it is difficult to comprehend the relationships among global features. Thus, we added a vision Transform network as the model branch to extract the global features. It is normally difficult to train the transformer, and image noise and geometric information loss are likely. Hence, we adopted the standard U-net fusion scheme and transform network as the generator, so that global features, local features, and rich image details could be obtained simultaneously. Our experimental results clearly demonstrate that MCSTransWnet successfully predicts postoperative corneal topographies (structural similarity ​= ​0.765, peak signal-to-noise ratio ​= ​16.012, and Fréchet inception distance ​= ​9.264). Using this technique to obtain the rough shape of the postoperative corneal topography in advance gives clinicians more references and guides changes to surgical planning and improves the success rate of surgery.

Abstract Background Vertebral compression fractures (VCFs) are common clinical problems that arise from various reasons. The differential diagnosis of benign and malignant VCFs is challenging. This study was designed to develop and validate a radiomics model to predict benign and malignant VCFs with 18F-fluorodeoxyglucose-positron emission tomography/computed tomography (18F-FDG-PET/CT). Results Twenty-six features (9 PET features and 17 CT features) and eight clinical variables (age, SUVmax, SUVpeak, SULmax, SULpeak, osteolytic destruction, fracture line, and appendices/posterior vertebrae involvement) were ultimately selected. The area under the curve (AUCs) of the radiomics and clinical–radiomics models were significantly different from that of the clinical model in both the training group (0.986, 0.987 vs. 0.884, p 0.05). The accuracies of the radiomics and clinical–radiomics models were 94.0% and 95.0% in the training group and 93.2% and 93.2% in the test group, respectively. The three models all showed good calibration (Hosmer–Lemeshow test, p > 0.05). According to the decision curve analysis (DCA), the radiomics model and clinical–radiomics model exhibited higher overall net benefit than the clinical model. Conclusions The PET/CT-based radiomics and clinical–radiomics models showed good performance in distinguishing between malignant and benign VCFs. The radiomics method may be valuable for treatment decision-making.

At present, the concepts related to 6G have not been unified, and there is an urgent need for consistent cognition and definition.Academics and industries lack a clear understanding of the overall development of 6G and the research progress in related fields.Therefore, the 6G knowledge base and knowledge system was constructed.Firstly, the existing 6G academic documents were automatically screened and stored in a structured way.Secondly, a 6G knowledge base was constructed on the basis of labeling and standardizing text data.In addition, a comprehensive statistical analysis was conducted across all domains of 6G based on the knowledge base and the technologies such as natural language processing, deep neural network and latent tree model were used to realize the extraction and generation of 6G knowledge.Finally, on the basis of large-scale model training, the on-demand knowledge application was realized for diversified service requirements.

Abstract Background Concomitant diseases often occur in cancer patients and are important in decision-making regarding treatments. However, information regarding the prognostic relevance of comorbidities for mortality risk is still limited among Chinese gastric cancer (GC) patients. This study aimed to investigate the association between comorbidities and 3-year mortality risk. Methods This retrospective study enrolled 376 GC patients undergoing radical gastrectomy at the Affiliated Zhongshan Hospital of Dalian University from January 2011 to December 2019. Demographic and clinicopathological information and treatment outcomes were collected. Patients were divided into low-, moderate- and high-risk comorbidity groups based on their Charlson Comorbidity Index (CCI) and age-adjusted CCI (ACCI) scores. Kaplan-Meier survival and Cox regression analyses were used to examine 3-year overall survival (OS) and mortality risk for each group. Results The median follow-up time was 43.5 months, and 40.2% (151/376) of GC patients had died at the last follow-up. There were significant differences in OS rates between ACCI-based comorbidity groups (76.56; 64.51; 54.55%, log-rank P = 0.011) but not between CCI-based comorbidity groups (log-rank P = 0.16). The high-risk comorbidity group based on the ACCI remained a significant prognostic factor for 3-year OS in multivariate analysis, with an increased mortality risk (hazard ratio [HR], 1.99; 95% CI, 1.15–3.44). Subgroup analysis revealed that this pattern only held for male GC patients but not for female patients. Conclusion The present study suggested that high-risk comorbidities were significantly associated with a higher mortality risk, particularly in Chinese male GC patients. Moreover, the ACCI score was an independent prognostic factor of long-term mortality.

Abnormal glucose homeostasis is associated with metabolic syndromes including cardiovascular diseases, hypertension, type 2 diabetes mellitus, and obesity, highlighting the significance of maintaining a balanced glucose level for optimal biological function. This highlights the importance of maintaining normal glucose levels for proper biological functioning. Sulforaphane (SFN), the primary bioactive compound in broccoli from the Cruciferae or Brassicaceae family, has been shown to enhance glucose homeostasis effectively while exhibiting low cytotoxicity. This paper assesses the impact of SFN on glucose homeostasis in vitro, in vivo, and human trials, as well as the molecular mechanisms that drive its regulatory effects. New strategies have been proposed to enhance the bioavailability and targeted delivery of SFN in order to overcome inherent instability. The manuscript also covers the safety evaluations of SFN that have been documented for its production and utilization. Hence, a deeper understanding of the favorable influence and mechanism of SFN on glucose homeostasis, coupled with the fact that SFN is abundant in the human daily diet, may ultimately offer theoretical evidence to support its potential use in the food and pharmaceutical industries.

Vibrio parahaemolyticus (V. parahaemolyticus) is one of the important seafood-borne pathogens that cause a serious gastrointestinal disorder in humans. Recently, biosensors have attracted serious attention for precisely detecting and tracking risk factors in foods. However, a major consideration when fabricating biosensors is to match the low cost of portable devices to broaden its application. In this study, a 3D-printed integrated handheld biosensor (IHB) that combines RPA-CRISPR/Cas12a, a lateral flow strip (LFS), and a handheld device was developed for the ultrasensitive detection of V. parahaemolyticus. Using the preamplification of RPA on tlh gene of V. parahaemolyticus, a specific duplex DNA product was obtained to activate the trans-cleavage activity of CRISPR/Cas12a, which was then utilized to cleave the ssDNA probe. The ssDNA probe was then detected by the LFS, which was negatively correlated with the content of amplified RPA products of the tlh gene. The IHB showed high selectivity and excellent sensitivity for V. parahaemolyticus detection, and the limit of detection was 4.9 CFU/mL. The IHB also demonstrated great promise for the screening of V. parahaemolyticus in samples and had the potential to be applied to the rapid screening of other pathogen risks for seafood and marine environmental safety.

Abstract Background Peripheral nerve damage causes neuroinflammation, which plays a critical role in establishing and maintaining neuropathic pain (NeP). The mechanisms contributing to neuroinflammation remain poorly elucidated, and pharmacological strategies for NeP are limited. Thus, in this study, we planned to explore the possible link between astrocyte senescence and NeP disorders following chronic sciatic nerve injury. Methods An NeP animal model was established by inducing chronic constrictive injury (CCI) to the sciatic nerve in adult rats. A senolytic drug combination of dasatinib and quercetin was gavaged daily from the first postoperative day until the end of the study. Paw mechanical withdrawal threshold (PMWT) and paw thermal withdrawal latency (PTWL) were evaluated to assess behaviors in response to pain in the experimental rats. Senescence-associated β-galactosidase staining, western blot analysis, and immunofluorescence were applied to examine the levels of proinflammatory factors and severity of the senescence-like response in the spinal cord. Lipopolysaccharide (LPS) was administered to induce senescence of spinal astrocytes in primary cultures in vitro, to explore the potential impacts of senescence on the secretion of proinflammatory factors. Furthermore, single-cell RNA sequencing (scRNA-seq) was conducted to identify senescence-related molecular responses in spinal astrocytes under neuropathic pain. Results Following sciatic nerve CCI, rats exhibited reduced PMWT and PTWL, increased levels of spinal proinflammatory factors, and an enhanced degree of senescence in spinal astrocytes. Treatment with dasatinib and quercetin effectively attenuated spinal neuroinflammation and mitigated the hypersensitivities of the rats subjected to sciatic nerve CCI. Mechanistically, the dasatinib-quercetin combination reversed senescence in LPS-stimulated primary cultured astrocytes and decreased the levels of proinflammatory factors. The scRNA-seq data revealed four potential senescence-related genes in the spinal astrocyte population, and the expression of clusterin (CLU) protein was validated via in vitro experiments. Conclusion The findings indicate the potential role of astrocyte senescence in neuroinflammation following peripheral nerve injury, and suggest that targeting CLU activation in astrocytes might provide a novel therapeutic strategy to treat NeP. Graphical abstract

Abstract Background Existing evidence shows that there is an independent correlation between nephrolithiasis and gout, and hyperuricemia is the most important risk factor for gout. However, hyperuricemia was often used as an accompanying symptom of gout to explore its association with nephrolithiasis, there were few studies to explore whether hyperuricemia itself or serum uric acid (SUA) is related to the risk of nephrolithiasis. Evidence on the relationship between hyperuricemia and nephrolithiasis is still insufficient. Methods A total of 22,303 participants aged 30 to 79 years who participated in the China Multi-Ethnic Cohort (CMEC) study in Yunnan Province from May 2018 to September 2019 were included in the study. All participants received standardized face-to-face interviews, medical examinations, and biochemical examinations. Logistic regression was used to estimate the association between hyperuricemia and nephrolithiasis, and a restricted cubic spline (RCS) model was used to explore the dose–response relationship between SUA and the risk of nephrolithiasis. Results 14.5% of all participants were diagnosed with hyperuricemia, and 12.1% were diagnosed with nephrolithiasis. After adjusting for all potential confounders, the OR (95%CI) for nephrolithiasis in participants with hyperuricemia compared with participants without hyperuricemia was 1.464 (1.312,1.633), p

Abstract Background Cutaneous melanoma (CM) has an overall poor prognosis due to a high rate of metastasis. This study aimed to explore the role of hypoxia-related genes (HRGs) in CM. Methods We first used on-negative matrix factorization consensus clustering (NMF) to cluster CM samples and preliminarily analyzed the relationship of HRGs to CM prognosis and immune cell infiltration. Subsequently, we identified prognostic-related hub genes by univariate COX regression analysis and the least absolute shrinkage and selection operator (LASSO) and constructed a prognostic model. Finally, we calculated a risk score for patients with CM and investigated the relationship between the risk score and potential surrogate markers of response to immune checkpoint inhibitors (ICIs), such as TMB, IPS values, and TIDE scores. Results Through NMF clustering, we identified high expression of HRGs as a risk factor for the prognosis of CM patients, and at the same time, increased expression of HRGs also indicated a poorer immune microenvironment. Subsequently, we identified eight gene signatures (FBP1, NDRG1, GPI, IER3, B4GALNT2, BGN, PKP1, and EDN2) by LASSO regression analysis and constructed a prognostic model. Conclusion Our study identifies the prognostic significance of hypoxia-related genes in melanoma and shows a novel eight-gene signature to predict the potential efficacy of ICIs.

AIM:To explore the use of attention mechanism and Pix2Pix generative adversarial network to predict the postoperative corneal topography of age-related cataract patients undergone femtosecond laser arcuate keratotomy.METHODS:In this retrospective case series study, the 210 preoperative and postoperative corneal topographies from 87 age-related cataract patients(105 eyes)undergoing femtosecond laser arcuate keratotomy at Shanxi Eye Hospital between March 2018 and March 2020 were selected and divided into a training set(180)and a test set(30)for model training and testing. The peak signal-to-noise ratio(PSNR), structural similarity(SSIM)and Alpins astigmatism vector analysis were used to compare the accuracy of postoperative corneal topography prediction under different attention mechanisms.RESULTS:The model based on attention mechanism and Pix2Pix network can predict postoperative corneal topography, among which the model based on Self-Attention mechanism has the best prediction effect, with PSNR and SSIM reaching 16.048 and 0.7661, respectively. There were no statistically significant differences in the difference vector, difference vector axis position, surgically induced astigmatism, and correction index between real and generated corneal topography on the 3mm and 5mm rings(all P>0.05).CONCLUSION:Based on the Self-Attention mechanism and Pix2Pix network, the postoperative corneal topography can be well predicted, which can provide reference for the surgical planning and postoperative effects of ophthalmic clinicians.

Objective Sedentary behaviour is associated with a variety of adverse health outcomes, including obesity, oestrogen metabolism and chronic inflammation, all of which are related to the pathogenesis of uterine fibroids (UFs). This study aimed to explore the relationship between leisure sedentary time (LST) and UFs.Design Cross-sectional.Setting We conducted a cross-sectional analysis of data from patients from the Yunnan region in the China Multi-Ethnic Cohort Study.Participants A total of 6623 non-menopausal women aged 30–55 years old were recruited. Menstrual status was self-reported. Participants who lacked a unique national identity card, suffered from serious mental illness, did not have a clear diagnosis of UFs, or provided incomplete information were excluded.Primary and secondary outcome UFs were diagnosed by abdominal B-ultrasound. Leisure sedentary behaviour was assessed by using a face-to-face questionnaire interview. Logistic regression and restricted cubic spline were employed to explore the relationship between LST and UFs.Results A total of 562 participants had UFs, with a prevalence rate of 8.5% (7.8%, 9.2%). Multivariate adjusted logistic regression analysis showed that the risk of UFs in women with LST≥6 hour/day was 2.008 times that in women with LST0.05). According to the results of the stratified analysis for menstrual status and body mass index (BMI), there was a correlation between LST and the prevalence of UFs only in women with a BMI

AbstractBackground An increasing number of studies show that the intestinal flora is closely related to spinal cord injury. Many researchers are exploring the changes in the richness, diversity, and evenness of intestinal flora in spinal cord injury animal models to identify the characteristic bacteria.Methods A comprehensive literature search was conducted using three databases: PubMed, Embase, and Web of Science. A meta-analysis was performed using R 4.3.1 to evaluate the comparison of microbiota diversity, richness, and evenness and the relative abundance of intestinal microbiota in animals with spinal cord injury and blank controls.Results Fifteen studies were included in the meta-analysis, of which 12 involved gut microbiota distribution indicators and 11 included intestinal microflora relative abundance indicators. Meta-analysis of high-dimensional indicators describing the distribution of the gut microbiota identified a substantial decline in the evenness and richness of the intestinal flora. In addition, the Actinobacteria phylum and Erysipelotrichales and Clostridiales orders were significantly different between the spinal cord injury and sham groups; therefore, they may be the characteristic bacteria in spinal cord injury models.Conclusion Our meta-analysis suggested that the gut microbiota in the spinal cord injury animal model group was altered compared with that in the control group, with varying degrees of changes in richness and evenness and potentially pathogenic characteristic flora. More rigorous methodological studies are needed because of the high heterogeneity and limited sample size. Further research is needed to clinically apply intestinal microbiota and potentially guide fecal microbiota transplantation therapy.

BackgroundClinical trials are a crucial element in advancing medical knowledge and developing new treatments by establishing the evidence base for safety and therapeutic efficacy. However, the success of these trials depends on various factors, including trial design, project planning, research staff training, and adequate sample size. It is also crucial to recruit participants efficiently and retain them throughout the trial to ensure timely completion. ObjectiveThere is an increasing interest in using electronic health records (EHRs)—a widely adopted tool in clinical practice—for clinical trials. This scoping review aims to understand the use of EHR in supporting the conduct of clinical trials in low- and middle-income countries (LMICs) and to identify its strengths and limitations. MethodsA comprehensive search was performed using 5 databases: MEDLINE, Embase, Scopus, Cochrane Library, and the Cumulative Index to Nursing and Allied Health Literature. We followed the latest version of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guideline to conduct this review. We included clinical trials that used EHR at any step, conducted a narrative synthesis of the included studies, and mapped the roles of EHRs into the life cycle of a clinical trial. ResultsA total of 30 studies met the inclusion criteria: 13 were randomized controlled trials, 3 were cluster randomized controlled trials, 12 were quasi-experimental studies, and 2 were feasibility pilot studies. Most of the studies addressed infectious diseases (15/30, 50%), with 80% (12/15) of them about HIV or AIDS and another 40% (12/30) focused on noncommunicable diseases. Our synthesis divided the roles of EHRs into 7 major categories: participant identification and recruitment (12/30, 40%), baseline information collection (6/30, 20%), intervention (8/30, 27%), fidelity assessment (2/30, 7%), primary outcome assessment (24/30, 80%), nonprimary outcome assessment (13/30, 43%), and extended follow-up (2/30, 7%). None of the studies used EHR for participant consent and randomization. ConclusionsDespite the enormous potential of EHRs to increase the effectiveness and efficiency of conducting clinical trials in LMICs, challenges remain. Continued exploration of the appropriate uses of EHRs by navigating their strengths and limitations to ensure fitness for use is necessary to better understand the most optimal uses of EHRs for conducting clinical trials in LMICs.

An increasing number of connected vehicles (CVs) driving together with regular vehicles (RVs) on the road is an inevitable stage of future traffic development. As accurate traffic flow state detection is essential for ensuring safe and efficient traffic, the level of road intelligence is being enhanced by the mass deployment of roadside perception devices, which is capable of sensing the mixed traffic flow consisting of RVs and CVs. In this background, we propose a roadside radar and camera data fusion framework to improve the accuracy of traffic flow state detection, which utilizes relatively more accurate traffic parameters obtained from real-time communication between CVs and roadside unit (RSU) as calibration values for training the back propagation (BP) neural network. Then, with the perception data collected by roadside sensors, the BP neural network-based data fusion model is applied to all vehicles including RVs. Furthermore, considering the changes of road environments, a dynamic BP fusion method is proposed, which adopts dynamic training by updating samples conditionally, and are applied to fuse traffic flow, occupancy and RVs speed data. Simulation results demonstrate that for CVs data and all vehicles (including RVs) data, the proposed dynamic BP fusion method is more accurate than single sensor detection, entropy based Bayesian fusion method and traditional BP fusion without training by CVs. It can achieve smaller error, and the accuracies of vehicle speed, traffic flow, and occupancy are all above 95%.

LATS1/2 kinases are reported to be tumour suppressors in many cancers. Here the authors show that conditional deletion of LATS1/2 in the mature mouse luminal mammary epithelium leads to luminal-basal plasticity and development of basal-like carcinomas.

Heterogeneous cellular networks (HCNs) are envisioned as a promising architecture to provide seamless wireless coverage and increase network capacity. However, the densified multi-tier network architecture introduces excessive intra- and cross-tier interference and makes HCNs vulnerable to eavesdropping attacks. In this article, a dynamic spectrum control (DSC)-assisted transmission scheme is proposed for HCNs to strengthen network security and increase the network capacity. Specifically, the proposed DSC-assisted transmission scheme leverages the idea of block cryptography to generate sequence families, which represent the transmission decisions, by performing iterative and orthogonal sequence transformations. Based on the sequence families, multiple users can dynamically occupy different frequency slots for data transmission simultaneously. In addition, the collision probability of the data transmission is analyzed, which results in closed-form expressions of the reliable transmission probability and the secrecy probability. Then, the upper and lower bounds of network capacity are further derived with given requirements on the reliable and secure transmission probabilities. Simulation results demonstrate that the proposed DSC-assisted scheme can outperform the benchmark scheme in terms of security performance. Finally, the impacts of key factors in the proposed DSC-assisted scheme on the network capacity and security are evaluated and discussed.

Climate change and the growing world population leading to agriculture and food safety are global challenges facing humanity, while biosensors have long been regarded as one of the powerful tools for providing solutions. Biosensors can aid in sustainable agriculture by providing continuous monitoring or early detection of disease outbreaks that can be averted. It also plays an important role in monitoring food risk factors such as pesticides, veterinary medications, heavy metals, pathogens, poisons, and illegal additions. Currently, this field includes a series of reviews covering the topic, but surprisingly, there tend to focus more on a single level and ignore the role across the food value chain. In this Perspective, we emphasized on the importance of all sectors from farm to fork for developing better biosensors.

ObjectivesCranial magnetic resonance imaging (MRI) could be a crucial tool for the assessment for neurological symptoms in patients with Wilson’s disease (WD). Diffusion-weighted imaging (DWI) hyperintensity reflects the acute brain injuries, which mainly occur in specific brain regions. Therefore, this study aimed to develop a weighted cranial DWI scale for patients with WD, with special focus on specific brain regions.Materials and methodsIn total, 123 patients with WD were enrolled, 118 of whom underwent 1.5 T-MRI on admission. The imaging score was calculated as described previously and depended on the following sequences: one point was acquired when abnormal intensity occurred in the T1, T2, and fluid-attenuation inversion recovery sequences, and two points were acquired when DWI hyperintensity were found. Consensus weighting was conducted based on the symptoms and response to treatment.ResultsIntra-rater agreement were good (r = 0.855 [0.798–0.897], p < 0.0001). DWI hyperintensity in the putamen was a high-risk factor for deterioration during de-copper therapy (OR = 8.656, p < 0.05). The high-risk factors for readmission for intravenous de-copper therapies were DWI hyperintensity in the midbrain (OR = 3.818, p < 0.05) and the corpus callosum (OR = 2.654, p < 0.05). Both scoring systems had positive correlation with UWDRS scale (original semi-quantitative scoring system, r = 0.35, p < 0.001; consensus semi-quantitative scoring system, r = 0.351, p < 0.001.). Compared to the original scoring system, the consensus scoring system had higher correlations with the occurrence of deterioration (OR = 1.052, 95%CI [1.003, 1.0103], p < 0.05) and readmission for intravenous de-copper therapy (OR = 1.043, 95%CI [1.001, 1.086], p < 0.05).ConclusionThe predictive performance of the consensus semi-quantitative scoring system for cranial MRI was improved to guide medication, healthcare management, and prognosis prediction in patients with WD. For every point increase in the neuroimaging score, the risk of exacerbations during treatment increased by 5.2%, and the risk of readmission to the hospital within 6 months increased by 4.3%.

Food safety is closely related to human health. However, the regulation and testing processes for food safety are intricate and resource-intensive. Therefore, it is necessary to address food safety risks using a combination of deep learning, the Internet of Things, smartphones, quick response codes, smart packaging, and other smart technologies. Intelligent designs that combine digital systems and advanced functionalities with biosensors hold great promise for revolutionizing current food safety practices. This review introduces the concept of Food Safety 4.0, and discusses the impact of intelligent biosensors, which offer attractive smarter solutions, including real-time monitoring, predictive analytics, enhanced traceability, and consumer empowerment, helping improve risk management and ensure the highest standards of food safety.

Food safety has emerged as a significant concern for global public health and sustainable development. The development of analytical tools capable of rapidly, conveniently, and sensitively detecting food safety hazards is imperative. Over the past few decades, personal glucose meters (PGMs), characterized by their rapid response, low cost, and high degree of commercialization, have served as portable signal output devices extensively utilized in the construction of biosensors. This paper provides a comprehensive overview of the mechanism underlying the construction of PGM-based biosensors, which consists of three fundamental components: recognition, signal transduction, and signal output. It also detailedly enumerates available recognition and signal transduction elements, and their modes of integration. Then, a multitude of instances is examined to present the latest advancements in the application of PGMs in food safety detection, including targets such as pathogenic bacteria, mycotoxins, agricultural and veterinary drug residues, heavy metal ions, and illegal additives. Finally, the challenges and prospects of PGM-based biosensors are highlighted, aiming to offer valuable references for the iterative refinement of detection techniques and provide a comprehensive framework and inspiration for further investigations.

In modern agricultural practices, organophosphorus pesticides or insecticides (OPs) are regularly used to restrain pests. Their limits are closely monitored since their residual hinders the capability of acetylcholinesterase (AChE) and brings out a threatening accumulation of the neurotransmitter acetylcholine (ACh), which affects human well-being. Therefore, spotting OPs in food and the environment is compulsory to prevent human health. Several techniques are available to identify OPs but encounter shortcomings like time-consuming, operating costs, and slow results achievement, which calls for further solutions. Herein, we present a rapid colorimetric sensor for quantifying OPs in foods using TMB as a substrate, a multi-enzyme cascade system, and the synergistic property of core-shell Palladinum@Platinum (Pd@Pt) nanoparticles. The multi-enzyme cascade response framework is a straightforward and effective strategy for OPs recognition and can resolve the previously mentioned concerns. Numerous OPs, including Carbofuran, Malathion, Parathion, Phoxim, Rojor, and Phosmet, were successfully quantified at different concentrations. The cascade method established using Pd@Pt had a simple and easy operation, a lower detection limit range of (1–2.5 ng/mL), and a short detection time of about 50 min. With an R2 value of over 0.93, OPs showed a linear range of 10–200 ng/mL, portraying its achievement in quantifying pesticide residue. Lastly, the approach was utilized in food samples and recovered more than 80% of the residual OPs.

We propose and demonstrate a new simultaneous optical and radio frequency (RF) transmission scheme using optical phase stabilization combined with phase conjugate technology. The acousto-optical modulator (AOM) is used as a frequency actuator to compensate the optical frequency phase noise introduced by the optical fiber link, and the electro-optical modulator (EOM) is used to modulate two optical carrier sidebands simultaneously to stabilize the RF phase by phase conjugate technology. The novelty is that forward and backward RFs are distinguished by the AOMs used in standard optical carrier transfer to avoid the backscattering without WDM, so that the optical link is more symmetric, reducing the degradation of frequency stability due to polarization fluctuation and chromatic dispersion thermal sensitivity. We experimentally demonstrate 193.4 THz optical frequency transfer with a frequency stability of 1.2 $ \times $ 10−17 at the integral time of 1 s and 3.3 $ \times $ 10−19 at 10000 s, 1 GHz RF with a frequency stability of 7 $ \times $ 10−13 at 1 s and 3 $ \times $ 10−16 at 10000 s over a 50.4 km fiber spools. This novel scheme demonstrates the compatibility of two contrasting fiber noise cancellation techniques, and is superior to the current optical frequency and RF simultaneous transmission schemes in terms of cost and complexity.

Background. DNA methylation patterns have been found to be distinct between tumor and normal patients. However, the effect of DNA demethylation enzymes, ten eleven translocation (TET) proteins, has not been comprehensively characterized in liver cancer. In this research, we sought to unravel the linkage of TET proteins with prognosis, immune characteristics and biological pathways in hepatocellular carcinoma (HCC). Materials and Methods. Four independent datasets with gene expression data and clinical data of HCC samples were downloaded from public databases. CIBERSORT, single sample Gene Set Enrichment Analysis (ssGSEA), MCP-counter, and TIMER were implemented to evaluate immune cell infiltration. limma was employed to screen differentially expressed genes (DEGs) between two groups. The demethylation-related risk model was established by using univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO), and stepwise Akaike information criterion (stepAIC). Results. TET1 was significantly higher expressed in tumor samples than that in normal samples. HCC patients with advanced stages (III+IV) and grades (G3+G4) had higher TET1 expression compared to early stages (I+II) and grades (G1+G2). HCC samples with high TET1 expression had worse prognosis than that with low expression. High and low TET1 expression groups had distinct immune cell infiltration and response to immunotherapy and chemotherapy. We identified 90 DEGs related to DNA demethylation in high vs. low TET1 expression groups. Furthermore, we established a risk model based on 90 DEGs containing seven key prognostic genes (SERPINH1, CDC20, HACD2, SPHK1, UGT2B15, SLC1A5, and CYP2C9) with effectiveness and robustness in predicting HCC prognosis. Conclusions. Our study suggested TET1 as a potential indicator in HCC progression. TET1 was closely involved in immune infiltration and activation of oncogenic pathways. The DNA demethylation-related risk model was potential to be applied for predicting HCC prognosis in clinics.

The enzyme-mimicking catalytic activity of single-atom nanozymes has been widely used in tumor treatment. However, research on alleviating metabolic diseases, such as hyperglycemia, has not been reported. Herein, we found that the single-atom Ce-N4-C-(OH)2 (SACe-N4-C-(OH)2) nanozyme promoted glucose absorption in lysosomes, resulting in increased reactive oxygen species production in HepG2 cells. Furthermore, the SACe-N4-C-(OH)2 nanozyme initiated a cascade reaction involving superoxide dismutase-, oxidase-, catalase-, and peroxidase-like activity to overcome the limitations associated with the substrate and produce •OH, thus improving glucose intolerance and insulin resistance by increasing the phosphorylation of protein kinase B and glycogen synthase kinase 3β, and the expression of glycogen synthase, promoting glycogen synthesis to improve glucose intolerance and insulin resistance in high-fat diet-induced hyperglycemic mice. Altogether, these results demonstrated that the novel nanozyme SACe-N4-C-(OH)2 alleviated the effects of hyperglycemia without evident toxicity, demonstrating its excellent clinical application potential.

With the rapid development of Internet of things and artificial intelligence technology, accurate analysis and prediction of traffic data have become the primary target of intelligent transportations.In recent years, the method of traffic forecasting has gradually changed from the classical model-driven type to the data-driven type.However, how to effectively analyze the spatial-temporal characteristics of road networks through big data is one of the key issues in the traffic prediction process.Spatiotemporal big data analysis is a powerful tool for the traffic prediction.The traffic network can be modeled as a graph network, while the deep learning method can be extended on the graph network.Utilizing graph neural networks, we can build the spatiotemporal prediction model, and obtain the spatial-temporal correlation between the sensor nodes in road networks effectively by using graph convolution, which can significantly improve the accuracy of traffic prediction models.The traffic forecasting technology driven by graph neural networks was explored, and two kinds of traffic prediction models based on the analysis of deep spatial-temporal characteristics were extracted.The actual cases were analyzed and evaluated to discuss the technical advantages and key challenges of graph neural networks in the traffic prediction.The potential issues of graph neural network driven prediction mechanisms were also excavated.

The active forces exerted from the extracellular matrix (ECM) to mechanoreceptors have crucial impact on many cell functions and disease development. However, our understanding of the underlying mechanisms is held back due to the lack of ECM mimicking platform able to apply molecularly resolved forces to cells. Herein, we present novel hydrogel platform capable of generate pN range forces to specific cellular receptors, at molecular scale. This capability was achieved through near-infrared (NIR) light regulated macromolecular actuators functionalized within the platform. This platform enables us to reveal cell responses to molecularly resolved forces under controlled magnitude (150–400 ​pN) and frequency (up to 100 ​Hz) on matrix with varied stiffness. We find the stiffness of the matrix has a large influence on the applied force transduction to cells. This versatile platform holds the potential for establishing correlation between receptor signaling pathways and cellular responses closer to physiological conditions.

Abstract Background Opioids have been identified by the World Health Organization to be ‘indispensable for the relief of pain and suffering’. Side-effects, such as nausea, vomiting, postoperative delirium, and effects on breathing, of opioids have been well investigated; however, the influence of opioids on monocyte-endothelial adherence has never been reported. Therefore, we explored the effects of representative opioids, fentanyl, sufentanil, and remifentanil, on monocyte-endothelial adherence and the underlying mechanisms. Methods We built a cell adhesion model with U937 monocytes and human umbilical vein endothelial cells (HUVECs). Two kinds of connexin43 (Cx43) channel inhibitors, 18-α-GA and Gap 27, were used to alter Cx43 channel function in U937 monocytes and HUVECs, respectively, to determine the effects of Cx43 channels on U937-HUVEC adhesion. Subsequently, the effects of fentanyl, sufentanil and remifentanil on Cx43 channel function and U937-HUVEC adhesion were explored. Results When fentanyl, sufentanil and remifentanil acted on monocytes or endothelial cells, their effects on monocyte-endothelial adherence differed. When acting on U937 monocytes, sufentanil significantly increased U937-HUVEC adhesion which was associated with reduced release of ATP from Cx43 channels, while fentanyl and remifentanil did not have these influences. Although sufentanil could also inhibit Cx43 channel function in HUVECs, it had no effect on ATP release from HUVECs or U937-HUVECs adhesion. Conclusions We demonstrated that sufentanil application increases monocyte-endothelial adherence which was associated with reduced release of ATP from Cx43 channels in monocytes. This side-effect of sufentanil should be considered seriously by clinicians.

Abstract Background Uvulopalatopharyngoplasty(UPPP) is the most prevalent surgical treatment of obstructive sleep apnea, but postoperative pharyngeal pain may affect patient comfort. The enhanced recovery after surgery pathway has been proved beneficial to many types of surgery but not to UPPP yet. The aim of this pilot study was to preliminarily standrize an enhanced recovery after surgery protocol for UPPP, to assess whether it has positive effects on reducing postoperative pharyngeal pain and improving patient comfort, and to test its feasibility for an international multicentre study. Methods This randomised controlled study analysed 116 patients with obstructive sleep apnoea (OSA) who were undergoing UPPP in a single tertiary care hospital. They were randomly divided according to treatment: the ERAS group (those who received ERAS treatment) and the control group (those who received traditional treatment). Ninety-five patients completed the assessment (ERAS group, 59 patients; control group, 36 patients). Pharyngeal pain and patient comfort were evaluated using a visual analogue scale (VAS) at 30 min and at 6, 12, 24 and 48 h after UPPP. Complications, hospitalisation duration, and hospital cost were recorded. Results The VAS scores for resting pain and swallowing pain were significantly lower in the ERAS group than those in the control group at 30 min and at 6, 12, 24 and 48 h after surgery. Patient comfort was improved in the ERAS group. The hospitalisation duration and cost were comparable between the groups. The incidence of complications showed an increasing trend in the ERAS group. Conclusion The ERAS protocol significantly relieved pharyngeal pain after UPPP and improved comfort in patients with OSA, which showed the prospect for an larger study. Meanwhile a potential increase of post-operative complications in the ERAS group should be noticed. Trial registration Chinese Clinical Trial Registry (23/09/2018, ChiCTR1800018537 )

Nut fruits likely played a significant role before and during the origin of agriculture; however, relatively little research conducted on the morphological characteristics and statistical comparisons of nut fruit starch granule hinders the progress of paleodietary analysis of prehistorical society. For better species identification of starch granule remaining on tools discovered at archaeological sites, it is desirable to develop a more abundant morphology database of modern nut fruit starch granules as well as the establishment of relevant identification standards. Therefore, nuts from 40 species in four genera (Quercus, Lithocarpus, Castanea, and Castanopsis) of Fagaceae were collected from South China for statistical measurement and comparative analysis. Starch granules are highly accumulated in 34 species except for 6 species, whose shapes involve oval, subcircular, drop-shaped, rounded triangle, polygonal, spherical caps, and bell-shaped types, or a combination of several types, and the average length is between 10 and 20 μm. According to research on Quercus phylogeny relationships, it was found that the species in the same infragenious section produce similar morphological characteristics of starch granules. The result was applied in the identification of starch granules extracted from stone tools from the 20 to 10 ka cultural layer of Xiaodong Rockshelter, and some starch granules can be recognized to species level, revealing that nuts from Quercus and Lithocarpus were gathered and exploited by ancient people. This expansion of modern starch presentation and comparison of nuts helps to improve the accuracy of the identification of ancient starch and deepen the understanding of plant utilization of ancient humans.

PurposeThis study aimed to develop a deep learning model to generate a postoperative corneal axial curvature map of femtosecond laser arcuate keratotomy (FLAK) based on corneal tomography using a pix2pix conditional generative adversarial network (pix2pix cGAN) for surgical planning.MethodsA total of 451 eyes of 318 nonconsecutive patients were subjected to FLAK for corneal astigmatism correction during cataract surgery. Paired or single anterior penetrating FLAKs were performed at an 8.0-mm optical zone with a depth of 90% using a femtosecond laser (LenSx laser, Alcon Laboratories, Inc.). Corneal tomography images were acquired from Oculus Pentacam HR (Optikgeräte GmbH, Wetzlar, Germany) before and 3 months after the surgery. The raw data required for analysis consisted of the anterior corneal curvature for a range of ± 3.5 mm around the corneal apex in 0.1-mm steps, which the pseudo-color corneal curvature map synthesized was based on. The deep learning model used was a pix2pix conditional generative adversarial network. The prediction accuracy of synthetic postoperative corneal astigmatism in zones of different diameters centered on the corneal apex was assessed using vector analysis. The synthetic postoperative corneal axial curvature maps were compared with the real postoperative corneal axial curvature maps using the structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR).ResultsA total of 386 pairs of preoperative and postoperative corneal tomography data were included in the training set, whereas 65 preoperative data were retrospectively included in the test set. The correlation coefficient between synthetic and real postoperative astigmatism (difference vector) in the 3-mm zone was 0.89, and that between surgically induced astigmatism (SIA) was 0.93. The mean absolute errors of SIA for real and synthetic postoperative corneal axial curvature maps in the 1-, 3-, and 5-mm zone were 0.20 ± 0.25, 0.12 ± 0.17, and 0.09 ± 0.13 diopters, respectively. The average SSIM and PSNR of the 3-mm zone were 0.86 ± 0.04 and 18.24 ± 5.78, respectively.ConclusionOur results showed that the application of pix2pix cGAN can synthesize plausible postoperative corneal tomography for FLAK, showing the possibility of using GAN to predict corneal tomography, with the potential of applying artificial intelligence to construct surgical planning models.

ObjectiveTo evaluate whether social capital played a mediating role in the relationship between negative life events (NLE) and quality of life (QoL) among adults in China after proposed a conceptual model based on stress buffering theory.MethodsA cross-sectional study was conducted based on baseline survey from the Chinese Multi-ethnic Cohort (CMEC) in Yunnan province. A total of 22,866 adults were recruited by multistage stratified cluster sampling. A structured questionnaire was used to collect the general demographic characteristics and the occurrence of NLE. A self-developed brief social capital scale was utilized to assess the social capital and the EQ-5D-5L scale was used to measure the QoL. The relationships among NLE, social capital and QoL were analyzed using multiple linear regression analyses. Structural equation models were used to evaluate whether social capital had a mediating effect on the relationship between NLE and QoL. The standardize coefficient (β) and it's 95% confidence intervals (CI) were calculated in this process.ResultsThe mean age of participants was 52.70 years old. The mean of EQ-5D index value was 0.92 (SD = 0.12) and the mean of EQ-VAS score was 71.77 (SD = 13.80). NLE not only directly affected EQ-5D index value [β = −0.127, 95% CI (−0.144, −0.110)] but also indirectly negatively affected EQ-5D index value through social capital [β = −0.019, 95% CI (−0.023, −0.015)]. Social capital had a direct positive effect on EQ-5D index value [β = 0.114, 95% CI (0.097, 0.133)]. A similar pattern was identified for the association between NLE and EQ-VAS score. The direct effect of NLE on EQ-VAS score was negatively significant [β = −0.132, 95% CI (−0.146, −0.118)]. Moreover, the indirect effect through social capital was also negatively significant [β = −0.022, 95% CI (−0.026, −0.019)]. There was a positive direct effect of social capital on EQ-VAS score [β = 0.135, 95% CI (0.117, 0.151)].ConclusionSocial capital played an important mediating role in the relationship between NLE and QoL, and it alleviated the negative effects of NLE on the QoL of the community residents in China. Providing reliable social capital for community residents experiencing NLE could effectively improve their quality of life.

A comprehensive study in selenium (Se) biofortification of staple food is vital for the prevention of Se-deficiency-related diseases in human beings. Thus, the roles of exogenous Se species, application methods and rates, and wheat growth stages were investigated on Se accumulation in different parts of wheat plant, and on Se speciation and bioaccessibility in whole wheat and white all-purpose flours. Soil Se application at 2 mg kg–1 increased grains yield by 6% compared to control (no Se), while no significant effects on yield were observed with foliar Se treatments. Foliar and soil Se application of either selenate or selenite significantly increased the Se content in different parts of wheat, while selenate had higher bioavailability than selenite in the soil. Regardless of Se application methods, the Se content of the first node was always higher than the first internode. Selenomethionine (SeMet; 87–96%) and selenocystine (SeCys2; 4–13%) were the main Se species identified in grains of wheat. The percentage of SeMet increased by 6% in soil with applied selenite and selenate treatments at 0.5 mg kg–1 and decreased by 12% compared with soil applied selenite and selenate at 2 mg kg–1, respectively. In addition, flour processing resulted in losses of Se; the losses were 12–68% in white all-purpose flour compared with whole wheat flour. The Se bioaccessibility in whole wheat and white all-purpose flours for all Se treatments ranged from 6 to 38%. In summary, foliar application of 5 mg L–1 Se(IV) produced wheat grains that when grounds into whole wheat flour, was the most efficient strategy in producing Se-biofortified wheat. This study provides an important reference for the future development of high-quality and efficient Se-enriched wheat and wheat flour processing.

Pathogen detection and control have long presented formidable challenges in the domains of medicine and public health. This review paper underscores the potential of nanozymes as emerging bio-mimetic enzymes that hold promise in effectively tackling these challenges. The key features and advantages of nanozymes are introduced, encompassing their comparable catalytic activity to natural enzymes, enhanced stability and reliability, cost effectiveness, and straightforward preparation methods. Subsequently, the paper delves into the detailed utilization of nanozymes for pathogen detection. This includes their application as biosensors, facilitating rapid and sensitive identification of diverse pathogens, including bacteria, viruses, and plasmodium. Furthermore, the paper explores strategies employing nanozymes for pathogen control, such as the regulation of reactive oxygen species (ROS), HOBr/Cl regulation, and clearance of extracellular DNA to impede pathogen growth and transmission. The review underscores the vast potential of nanozymes in pathogen detection and control through numerous specific examples and case studies. The authors highlight the efficiency, rapidity, and specificity of pathogen detection achieved with nanozymes, employing various strategies. They also demonstrate the feasibility of nanozymes in hindering pathogen growth and transmission. These innovative approaches employing nanozymes are projected to provide novel options for early disease diagnoses, treatment, and prevention. Through a comprehensive discourse on the characteristics and advantages of nanozymes, as well as diverse application approaches, this paper serves as a crucial reference and guide for further research and development in nanozyme technology. The expectation is that such advancements will significantly contribute to enhancing disease control measures and improving public health outcomes.

Genetically modified (GM) maize is one of the earliest GM crops to have achieved large-scale commercial cultivation globally, and it is of great significance to excel in the development and implementation of safety policy regarding GM, and in its technical oversight. This article describes the general situation regarding genetically modified maize, including its varieties, applications, relevant laws and regulations, and so on. From a technical point of view, we summarize and critically analyze the existing methods for detecting nucleic acid levels in genetically modified maize. The nucleic acid extraction technology used for maize is explained, and the introduction of traditional detection techniques, which cover variable-temperature and isothermal amplification detection technology and gene chip technology, applications in maize are described. Moreover, new technologies are proposed, with special attention paid to nucleic acid detection methods using sensors. Finally, we review the current limitations and challenges of GM maize nucleic acid testing and share our vision for the future direction of this field.

Abstract. Background:. Diabetes mellitus (DM) is an important risk factor in the long-term outcomes of surgical revascularization. However, few studies have focused on patients with ischemic heart failure (IHF) and DM, and the results are controversial. This study aimed to evaluate the effect of DM on the long-term outcomes of IHF patients undergoing coronary artery bypass grafting (CABG). Methods:. In this propensity-matched study, data of IHF patients who underwent CABG in our hospital from January 2007 to December 2017 were analyzed. With a mean 73-month follow-up time, the patients were divided into two groups according to whether they had DM. The primary endpoint was all-cause death, and the secondary endpoint was a composite of all-cause death, stroke, recurrent myocardial infarction, and revascularization. Results:. There was no significant difference in all-cause mortality between the two groups (5.8% vs. 4.1%, P = 0.216). The incidence of main adverse cardiovascular and cerebrovascular events (MACCE) in the secondary endpoint was significantly higher in the DM group than that in the non-DM group (10.4% vs. 8.1%, P = 0.023). Conclusions:. DM can negatively affect the long-term outcomes of IHF patients undergoing CABG by significantly increasing the overall incidence of MACCE, though the long-term survival does not show a significant difference between the DM and non-DM patients.

Abstract Paroxysmal dyskinesias are a group of neurological diseases characterized by intermittent episodes of involuntary movements with different causes. Paroxysmal kinesigenic dyskinesia (PKD) is the most common type of paroxysmal dyskinesia and can be divided into primary and secondary types based on the etiology. Clinically, PKD is characterized by recurrent and transient attacks of involuntary movements precipitated by a sudden voluntary action. The major cause of primary PKD is genetic abnormalities, and the inheritance pattern of PKD is mainly autosomal-dominant with incomplete penetrance. The proline-rich transmembrane protein 2 (PRRT2) was the first identified causative gene of PKD, accounting for the majority of PKD cases worldwide. An increasing number of studies has revealed the clinical and genetic characteristics, as well as the underlying mechanisms of PKD. By seeking the views of domestic experts, we propose an expert consensus regarding the diagnosis and treatment of PKD to help establish standardized clinical evaluation and therapies for PKD. In this consensus, we review the clinical manifestations, etiology, clinical diagnostic criteria and therapeutic recommendations for PKD, and results of genetic analyses in PKD patients performed in domestic hospitals.

Abstract Wilson’s disease (WD) is an inherited disorder characterized by excessive accumulation of copper in the body, particularly in the liver and brain. In the central nervous system (CNS), extracellular copper accumulation triggers pathological microglial activation and subsequent neurotoxicity. Growing evidence suggests that levels of inflammatory cytokines are elevated in the brain of murine WD models. However, the mechanisms associated with copper deposition to neuroinflammation have not been completely elucidated. In this study, we investigated how the activation of NLR family pyrin domain containing 3 (NLRP3) inflammasome contributes to copper-mediated neuroinflammation in an animal model of WD. Elevated levels of interleukin-1β, interleukin-18, interleukin-6, and tumor necrosis factor-α were observed in the sera of WD patients and toxic milk (TX) mice. The protein levels of inflammasome adaptor molecule apoptosis-associated speck-like protein containing a C-terminal caspase recruitment domain (ASC), cleaved caspase-1, and interleukin-1β were upregulated in the brain regions of the TX mice. The NLRP3 inflammasome was activated in the TX mice brains. Furthermore, the activation of NLRP3 inflammasome was noted in primary microglia treated with CuCl2, accompanied by the increased levels of cleaved caspase-1, ASC, and interleukin-1β. Blocking NLRP3 inflammasome activation with siNlrp3 or MCC950 reduced interleukin-1β and interleukin-18 production, thereby effectively mitigating cognitive decline, locomotor behavior impairment, and neurodegeneration in TX mice. Overall, our study demonstrates the contribution of copper overload-mediated activation of NLRP3 inflammasome to progressive neuropathology in the CNS of a murine model of WD. Therefore, blockade of the NLRP3 inflammasome activation could be a potential therapeutic strategy for WD.

We demonstrate a hybrid solution for simultaneous transfer of ultra-stable optical frequency, RF frequency and time signal on a 100 km fiber spool with the same wavelength based on coherent demodulation and optical phase-lock-loop (OPLL). The one pulse per second (1PPS) is encoded by phase and RF frequency is encoded with an intensity modulator. The noise caused by fiber link is compensated by the round-trip method. And the bad effect on optical frequency caused by optical phase modulation (PM) can be cleaned using OPLL. When the fiber link is stabilized, the transferred time deviation (TDEV) can be 2.4E-11@1s and 1.9E-12@104s, RF frequency stability can achieve 8.0E-14@1s and 2.5E-17@104s, the modified Allan deviation (MDEV) of cleaned optical frequency can be 1.4E-16@1s and 1.6E-19@104s.

With the advance of the information technologies,the scale of the information services gradually expands,from ground services,to aerial,maritime,and spatial services,with the soaring requirements on multi-dimensional comprehensive information resources.The space-air-ground integrated networks (SAGINs) are envisioned to provide seamless network services to spatial,aerial,maritime,and ground users,satisfying the future network requirements on all-time,all-domain,and all-space communications and interconnected networking.Firstly,we reviewed the current research development of SAGINs,discussing the research trends on the low-earth orbiting (LEO) satellite constellation and space-ground network integration.Then,the reinforcement learning (RL) framework was proposed in SAGINs to address the problems of complex architecture,high dynamics,and resource constraints in SAGINs,which facilitated efficient and fast network design,analysis,optimization,and management.As a case study,the method of applying deep RL (DRL) was showed for the intelligent access network selection in SAGINs.To improve the RL training efficiency,a comprehensive SAGINs simulation platform was established,through which the agent-environments interaction was accelerated and training samples could be obtained more cost-effectively.Finally,some open research directions were presented.

Inpatient early mobility initiatives are effective therapeutic interventions for improving patient outcomes and decreasing use of hospital resources among adult ICU and general medicine patients. To establish and demonstrate guidelines for early patient ambulation, we developed and implemented a novel multidisciplinary mobility bundle utilizing the JH-HLM (Johns Hopkins Highest Level of Mobility) scale for mobility classification, on a single adult general medicine unit of a community hospital. Our results show that patients admitted to the unit after implementation of the mobility bundle had improved mobility scores, reduced rates of 30-day hospital readmission, and a shortened length of hospital stay. This study emphasizes the importance of measuring mobility using a systematic method, easing workflow among unit practitioners, and allowing mobility initiatives to be jointly driven by nursing, physical therapy, and physicians.