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Anomaly detection on attributed graphs is a crucial topic for practical applications. Existing methods suffer from semantic mixture and imbalance issue because they commonly optimize the model based on the loss function for anomaly discrimination, mainly focusing on anomaly discrimination and ignoring representation learning. Graph Neural networks based techniques usually tend to map adjacent nodes into close semantic space. However, anomalous nodes commonly connect with numerous normal nodes directly, conflicting with the assortativity assumption. Additionally, there are far fewer anomalous nodes than normal nodes, leading to the imbalance problem. To address these challenges, a unique algorithm, decoupled self-supervised learning for anomaly detection (DSLAD), is proposed in this paper. DSLAD is a self-supervised method with anomaly discrimination and representation learning decoupled for anomaly detection. DSLAD employs bilinear pooling and masked autoencoder as the anomaly discriminators. By decoupling anomaly discrimination and representation learning, a balanced feature space is constructed, in which nodes are more semantically discriminative, as well as imbalance issue can be resolved. Experiments conducted on various six benchmark datasets reveal the effectiveness of DSLAD. [ABSTRACT FROM AUTHOR]

We present a psycholinguistic study investigating lexical effects on simplified Chinese character recognition by deaf readers. Prior research suggests that deaf readers exhibit efficient orthographic processing and decreased reliance on speech-based phonology in word recognition compared to hearing readers. In this large-scale character decision study (25 participants, each evaluating 2500 real characters and 2500 pseudo-characters), we analyzed various factors influencing character recognition accuracy and speed in deaf readers. Deaf participants demonstrated greater accuracy and faster recognition when characters were more frequent, were acquired earlier, had more strokes, displayed higher orthographic complexity, were more imageable in reference, or were less concrete in reference. Comparison with a previous study of hearing readers revealed that the facilitative effect of frequency on character decision accuracy was stronger for deaf readers than hearing readers. The effect of orthographic-phonological regularity differed significantly for the two groups, indicating that deaf readers rely more on orthographic structure and less on phonological information during character recognition. Notably, increased stroke counts (i.e., higher orthographic complexity) hindered hearing readers but facilitated recognition processes in deaf readers, suggesting that deaf readers excel at recognizing characters based on orthographic structure. The database generated from this large-scale character decision study offers a valuable resource for further research and practical applications in deaf education and literacy. [ABSTRACT FROM AUTHOR]

Clostridium butyricum (CB) has received much attention as a probiotic; however, few studies have focused on its effects on liver health. Here, we studied the influence of CB on the liver health of spotted sea bass through transcriptomics and metabolomics studies and preliminarily explored its molecular mechanisms. This study showed that CB significantly reduced hepatic aspartate aminotransferase (AST) activity and increased alkaline phosphatase (AKP) and acid phosphatase (ACP) activity (P < 0.05). CB has demonstrated significant effects in strengthening liver immunity and can increase hepatic amylase and trypsin activities and promote hepatic catabolism of carbohydrates and amino acids. Integration of the liver transcriptomics and metabolomics showed altered transcript levels of mainly gluconeogenic, lipogenic, and amino acid metabolic pathways. It regulated the abundance of metabolic biomarkers such as arachidonate, crotonyl-CoA, and D-glucose 1-phosphate. Our findings support that CB can reduce liver damage in spotted sea bass, enhance liver immunity, and improve liver metabolism. [ABSTRACT FROM AUTHOR]

This study explored the effects of chlorogenic acid (CGA) on antioxidant capacity, immunity, and intestinal health of spotted sea bass Lateolabrax maculatus. Spotted sea bass were fed six diets: a normal-fat diet (NFD) with 11.9% lipid; HFD with 17% lipid (HFD); and HFD supplemented with 100, 200, 300, and 400 mg/kg CGA (HFD1, HFD2, HFD3, and HFD4 respectively) for 7 weeks. Results showed that HFD-feeding significantly decreased CAT and T-SOD activity compared to the containing-CGA groups. Dietary supplementation with 300 mg/kg CGA significantly reduced MDA content and increased T-AOC compared to the HFD group. HFD supplemented with 100 and 200 mg/kg CGA significantly enhanced GSH activity compared to the HFD group. The activity of ACP and AKP significantly increased with 200 mg/kg CGA treatment compared to the HFD group. Compared to the HFD group, dietary CGA significantly increased the levels of LZM. CGA supplementation at 100, 200, and 300 mg/kg CGA significantly increased the levels of complement C3 compared to that in the HFD group. Supplementation of 300 and 400 mg/kg CGA significantly improved the lipase activity in the foregut compared with the HFD group. For histological analysis, HFD-feeding led to a reduction in muscular thickness, villi length, and density of the midgut compared to the NFD group, while the addition of CGA can improve the negative effects induced by HFD. Additionally, HFD-feeding increased both the diversity and abundance of intestinal bacteria in the midgut compared to the NFD diet, while contrasting results were observed in the hindgut. Furthermore, the addition of CGA mitigated the reduction in hindgut bacterial diversity induced by HFD. Overall, the present study indicated that dietary CGA plays a positive role in antioxidant capacity, immunity, and intestinal health of fed HFD. [ABSTRACT FROM AUTHOR]

Helwingia, a shrub of the monotypic cosmopolitan family Helwingiaceae, is distinguished by its inflorescence, in which flowers are borne on the midrib of the leaf—a trait not commonly observed in related plant families. Previous studies have investigated the development of this unusual structure using comparative anatomical methods. However, the scarcity of genomic data has hindered our understanding of the origins and evolutionary history of this uncommon trait at the molecular level. Here, we report the first high-quality genome of the family Helwingiaceae. Assembled using HiFi sequencing and Hi-C technologies, the genome of H. omeiensis is anchored to 19 chromosomes, with a total length of 2.75 Gb and a contig N50 length of 6.78 Mb. The BUSCO completeness score of the assembled genome was 98.2%. 53,951 genes were identified, of which 99.7% were annotated in at least one protein database. The high-quality reference genome of H. omeiensis provides an essential genetic resource and sheds light on the phylogeny and evolution of specific traits in the family Helwingiaceae. [ABSTRACT FROM AUTHOR]

Two Gram-staining-negative, facultative anaerobic, rod-shaped and phosphate-solubilizing strains designated SG2303T and SG2305, were isolated from paddy soil in China. Phylogenetic analysis based on 16 S rRNA gene sequences indicated that SG2303T and SG2305 represented a member of the genus Crenobacter within the family Neisseriaceae of the phylum Pseudomonadota. Strain SG2303T displayed higher 16 S rRNA gene sequence similarities with members of the genus Crenobacter ranging from 93.5 to 94.0%. Strains C. luteus YIM 78141T and C. cavernae K1W11S-77T were closest related to the isolated strains and were considered as type strains. Growth of strain SG2303T occurred at 10–55 °C (optimum 37 °C), pH 5.0–9.0 (optimum pH 6.0–7.0) and 0–1% (w/v) NaCl (optimum 0%). The average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values between strain SG2303T and its closely related taxa were 76.1–78.2% and 20.5–22.1%, respectively. The genomic DNA G + C content was 62.2%. The quinone of strain SG2303T was Q-8. The major fatty acids (> 10%) of strain SG2303T were C16:0 (30.6%), summed feature 3 (C16:1ω7c and/or C16:1ω6c) (26.0%) and C12:0 3OH (12.1%). The polar lipids were phosphatidylglycerol (PG), diphosphatidylglycerol (DPG), phosphatidylethanolamine (PE), phospholipids (PL), glycolipid (GL) and unidentified lipids (UL). Based on the results of the phylogenetic, physiological, biochemical, and morphological analysis, strain SG2303T is recognized as a novel species of the genus Crenobacter, for which the name Crenobacter oryzisoli sp. nov. is proposed. The type strain is SG2303T (= GDMCC 1.3970T = JCM 36468T). In addition, SG2303T was also able of phosphorus solubilization and promoting the growth of rice seeds. Strain SG2303T exhibited a relatively high dissolvable phosphorus content of 2.52 µg·mL− 1. [ABSTRACT FROM AUTHOR]

Purpose: To retrospectively evaluate the tislelizumab-based chemoimmunotherapy combined with gemcitabine/cisplatin for bladder-sparing in patients with muscle-invasive bladder cancer (MIBC). Methods: Forty-five patients who received bladder-sparing treatment or radical cystectomy (RC) for MIBC (cT2-T4a, NxM0) were retrospectively enrolled. All patients received maximal transurethral resection of bladder tumor (mTURBT), followed by four cycles of chemo-immunotherapy with tislelizumab (PD-L1 inhibitor), gemcitabine, and cisplatin. Clinical efficacy was evaluated to compare the benefit of bladder-sparing treatment on clinical CR (cCR) and RC for non-cCR patients. The primary outcomes were bladder intact disease-free survival (BIDFS) and overall survival (OS), and the secondary outcomes were adverse effects. The PD-L1 status and molecular subtypes of tumors were analyzed. Results: The overall survival rate was 88.8% (95%CI: 79.6%, 98.0%) at 12 months, 85.7% (95%CI: 74.9%, 96.5%) at 18 months, and 66.6% (95%CI: 45.2%, 88.0%) at 24 months. Twenty-nine patients (64.4%) achieved cCR and their OS rate was 96.6% (95%CI: 89.9%, 100%). Sixteen patients were in the non-cCR group, and their OS rate was 75.0% (95%CI: 53.8%, 96.2%) at 12 months, 65.6% (95%CI: 40.3%, 90.9%) at 18 months, and 52.5% (95%CI: 21.9%, 83.1%) at 24 months. The BIDFS rate for patients who received bladder-sparing treatment was 96.0% (95%CI: 88.4%, 100%) from 12 to 24 months. Four patients (8.8%) were PD-L1 positive and 41 patients (91.2%) were PD-L1 negative. Conclusions: Our retrospective study of patients with MIBC suggests that tislelizumab-based neoadjuvant therapy was a safe and effective bladder-sparing treatment. [ABSTRACT FROM AUTHOR]

Veratramine and cyclopamine, two of the most representative members of the isosteroidal alkaloids, are valuable molecules in agricultural and medicinal chemistry. While plant extraction of these compounds suffers from uncertain supply, efficient chemical synthesis approaches are in high demand. Here, we present concise, divergent, and scalable syntheses of veratramine and cyclopamine with 11% and 6.2% overall yield, respectively, from inexpensive dehydro-epi-androsterone. Our synthesis readily provides gram quantities of both target natural products by utilizing a biomimetic rearrangement to form the C-nor-D-homo steroid core and a stereoselective reductive coupling/(bis-)cyclization sequence to establish the (E)/F-ring moiety. Veratramine and cyclopamine are valuable molecules in agricultural and medicinal chemistry, but the efficient chemical synthesis approaches are in high demand. Here, the authors report the concise, divergent, and scalable syntheses of veratramine and cyclopamine with 11% and 6.2% overall yield, respectively. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is a prevalent malignancy with high mortality and morbidity rates. Although the significant efficacy of immunotherapy is well established, it is only beneficial for a limited number of individuals with CRC. Methods: Differentially expressed immune-related genes (DE-IRGs) were retrieved from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and ImmPort databases. A prognostic signature comprising DE-IRGs was developed using univariate, LASSO, and multivariate Cox regression analyses. A nomogram integrating the independent prognostic factors was also developed. CIBERSORT was used to assess immune cell infiltration (ICI). Furthermore, wound-healing, colony formation, migration, and invasion assays were performed to study the involvement of ACTG1 in CRC. Results: A signature including six DE-IRGs was developed. The overall survival (OS) rate was accurately estimated for TCGA and GSE38832 cohorts. The risk score (RS) of the signature was an independent factor for OS. Moreover, a nomogram encompassing age, RS, and pathological T stage accurately predicted the long-term OS probability of individuals with CRC. The high-risk group had an elevated proportion of patients treated with ICIs, including native B cells, relative to the low-risk group. Additionally, ACTG1 expression was upregulated, which supported the proliferation, migration, and invasion abilities of CRC cells. Conclusions: An immune-related prognostic signature was developed for predicting OS and for determining the immune status of individuals with CRC. The present study provides new insights into accurate immunotherapy for individuals with CRC. Moreover, ACTG1 may serve as a new immune biomarker. [ABSTRACT FROM AUTHOR]

Pulmonary tuberculosis (TB) can result in irreversible damage and lead to tuberculous destructive lung (TDL), a severe chronic lung disease that is associated with a high mortality rate. Additionally, pulmonary hypertension (PH) is a hemodynamic disorder that can be caused by lung diseases. The objective of this study is to investigate the risk factors associated with PH in active TB patients diagnosed with TDL. We conducted a retrospective review of the medical records of 237 patients who were diagnosed with TDL, active pulmonary tuberculosis, and underwent echocardiography at the Third People’ Hospital of Shenzhen from January 1, 2016, to June 30, 2023. Univariate and multivariate logistic regression analyses were performed to identify factors that correlated with the development of pulmonary hypertension. Univariate and multivariate logistic regression analyses revealed that several factors were associated with an increased risk of pulmonary hypertension (PH) in individuals with tuberculosis destroyed lung (TDL). These factors included age (OR = 1.055), dyspnea (OR = 10.728), D-dimer (OR = 1.27), PaCO2 (OR = 1.040), number of destroyed lung lobes (OR = 5.584), bronchiectasis (OR = 3.205), and chronic pleuritis (OR = 2.841). When age, D-dimer, PaCO2, and number of destroyed lung lobes were combined, the predictive value for PH in patients with TDL was found to be 80.6% (95% CI 0.739–0.873),with a sensitivity of 76.6% and specificity of 73.2%. Advanced age, elevated D-dimer levels, hypercapnia, and severe lung damage were strongly correlated with the onset of PH in individuals with active pulmonary tuberculosis (PTB) and TDL. Furthermore, a model incorporating age, D-dimer, PaCO2, and the number of destroyed lung lobes might be valuable in predicting the occurrence of PH in patients with active PTB and TDL. [ABSTRACT FROM AUTHOR]

Text-based personality detection aims to identify the personality traits implied in subject-supplied textual data. However, over-reliance on pre-trained language models and neglect of psycholinguistic features has become a bottleneck in personality detection. In this work, we conduct extensive feature-level ablation experiments using multiple psycholinguistic features to verify the importance of psycholinguistic features for personality detection. Furthermore, we propose a novel personality detection framework, DLP-Personality Detection, which fuses multiple psycholinguistic features and pre-trained language features. With the DLP-Personality Detection, we achieve state-of-the-art performance for the Big Five personality traits (Big 5) and Myers-Briggs Type Indicator (MBTI) personality traits on the Essays and Kaggle MBTI datasets. Finally, we provide some suggestions for psycholinguistic features and discuss future work for personality detection. [ABSTRACT FROM AUTHOR]

Modern clinical diagnosis relies heavily on medical imaging. Unimodal images contain limited information, whereas image fusion techniques can combine functional and structural information of images, thus speeding up the diagnostic and therapeutic process. However, existing methods lack global dependency and incomplete retention of image information. Therefore, we provide an end-to-end unsupervised training model called TCGFusion: a network for PET-MRI fusion based on GAN and transformer. We set the generator to a dual-path layout to ensure the gathering of both global semantic and detailed image information. The T-Path guarantees the coarse scale picture extraction and prevents the high computational cost. The C-Path's multi-cascade structure captures image details well. Additionally, we create a dual discriminator to determine the distribution of structural similarity between the fused result and the source image and use patch-SSIM to reinforce the semantic constraints between them and promote the image details. Through thorough investigation using public datasets, our TCGFusion possesses the capability to effectively combine the structural and functional information of an image, thus guaranteeing the integrity of the fused image. On objective measures, our method is about 3% higher overall than EMFusion. QG reached 0.7862 and SSIM reached 0.901. [ABSTRACT FROM AUTHOR]

Personality assessment plays a crucial role in various domains, such as clinical diagnosis, organizational settings, and academic achievement. While most existing assessment models rely on questionnaires or scales, this manuscript proposes an AI-based assessment application that utilizes physiological signals as input. The underlying model is developed in our previous research work and was built upon the big five personality model, encompassing extraversion, agreeableness, conscientiousness, emotional stability, and openness to experience. The manuscript presents the development of a user-friendly GUI application that simplifies the usage of this assessment model. The application supports real-time personality assessment by automatically connecting to physiological sensors and providing real-time signal visualization. It also generates comprehensive reports for offline analysis. The manuscript further discusses the related works on personality trait models and assessment methods, as well as the system analysis, design, and implementation. The proposed tool shows promise in simplifying the assessment process and enabling real-time personality assessment. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel energy minimization approach (called R-NCG) that combines a random batch idea with a nonlinear conjugate gradient method to accelerate the dynamics pre-equilibrium simulation of charged polymers in different systems. By using small but random batches, R-NCG can efficiently approximate the collective dynamics numerically while maintaining the numerical behaviours of standard NCG algorithm, and further improving its performance. Our simulation results suggest that the R-NCG can significantly reduce the computational cost of the minimization process for system with N-body interactions, thus reducing the time complexity to O(N). In other words, R-NCG method improves the problem of the dependence of CPU simulation time on the number of charged particles, and achieves acceptable accuracy in most cases. Our work can be helpful for accelerating the pre-equilibrium simulations of systems with N-body interactions, and confer new insights into the optimization of energy minimization algorithms in large electrostatic systems. In this work, we apply the random batch idea to the nonlinear conjugate gradient (NCG) method for improving the dependence of the CPU time on the number of charged particles in the energy minimization of the standard NCG method. Furthermore, we use the local iteration algorithm proposed in previous work to compute the spatial electrostatic potential distribution, which effectively improves the efficiency of the most time-consuming parts of calculating the electrostatic energy and its gradient values. Numerical results show that for different dielectric systems with N-body interactions, the NCG method based on random batch idea is computationally more efficient than the standard NCG method with acceptable accuracy in most cases (time complexity is reduced to O(N)). [ABSTRACT FROM AUTHOR]

Public key encryption with equality test (PKEET) can test if two ciphertexts generated from different public keys contain the same message without decryption. In the application of cloud storage, PKEET could be used to search on encrypted data. Currently, there have been many researches about security, efficiency, and function of PKEET. After analyzing the ciphertext sizes in the existing proposals, we find that the ciphertext sizes in PKEET schemes are usually large. In this case, it will bring storage burden for the cloud server. To address the problem, in this paper, we introduce a new notion of lightweight public key encryption with equality test (L-PKEET). Then we present a concrete construction of L-PKEET. Furthermore, we demonstrate that L-PKEET can reduce ciphertext sizes efficiently. In terms of the computation cost and ciphertext size, we compare L-PKEET with related schemes which also achieve four kinds of authorization. The comparison results show that L-PKEET is more efficient in terms of encryption, decryption, and test algorithms. Regarding the adversaries with/without trapdoor, we theoretically prove that L-PKEET can meet OW-CCA security and IND-CCA security, respectively. [ABSTRACT FROM AUTHOR]

The Health Action Process Approach (HAPA) is a two-stage (pre-intentional and post-intentional) behavioral change model that distinguishes between motivation and volition in behavior change process. This study aims to develop HAPA-based assessments for smoking cessation among current smokers. The HAPA-based measures were developed and the draft measures included nine constructs, namely, risk perception in smoking-induced cancer, risk perception in smoking-induced systemic disease, positive outcome expectancy, negative outcome expectancy, self-efficacy in quitting smoking, self-efficacy in maintaining, self-efficacy in re-initiating, quitting planning and coping planning in smoking cessation, with a total of 26 items. A cross-sectional survey was conducted in China in 2022. Principal Component Analysis was used for Exploratory Factor Analysis (EFA). Cronbach's α coefficient was calculated to evaluate the internal consistency. Variables such as severity of smoking addiction were selected to evaluate the correlation between the HAPA scale and these variables. Of the 928 participants, 76.4% (709/928) were male and the median age was 35 years. Five factors were extracted by EFA. The factor loadings of each item were all greater than 0.60, and the cumulative variance contribution rate was 90.15%. The Cronbach's α coefficient of each HAPA-based subscales was 0.929–0.986. The HAPA-based measurements are comprehensive, reliable and valid in the assessment of smokers' smoking cessation cognition, which can be used to guide the design and implementation of intervention and the development of theory. [ABSTRACT FROM AUTHOR]

Pork backfat (PB) contains excessive saturated fatty acids (SFAs), but lacks polyunsaturated fatty acids (PUFAs). Excessive SFAs can be used as a substrate for the growth of certain microorganisms that convert them into PUFAs and monounsaturated fatty acids (MUFAs), and the added value of PB can be enhanced. In this study, Mucor circinelloides CBS 277.49 and Lactiplantacillus plantarum CGMCC 24189 were co-cultured for conversion of PB into fermented pork backfat (FPB) with high level of PUFAs. Our results showed that the content of γ-linolenic acid (GLA) and linoleic acid (LA) in the surface of FPB reached 9.04 ± 0.14 mg/g and 107.31 ± 5.16 mg/g for 7-day fermentation, respectively. To convert the internal SFAs of PB, ultrasound combined with papain was used to promote the penetrative growth of M. circinelloides into the internal PB, and the GLA level in the third layer of fat reached 2.58 ± 0.31 mg/g FPB. The internal growth of M. circinelloides in PB was promoted by adjusting the oxygen rate and ventilation rate through the wind velocity sensor. When the oxygen rate is 2 m/s and the ventilation rate is 18 m3/h, the GLA level in the third layer of fat reached 4.13 ± 1.01 mg/g FPB. To further improve the level of PUFAs in PB, FPB was produced by M. circinelloides at 18 °C. The GLA content on the surface of FPB reached 15.73 ± 1.13 mg/g FPB, and the GLA yield in the second and third layers of fat reached 8.68 ± 1.77 mg/g FPB and 6.13 ± 1.28 mg/g FPB, the LA yield in the second and third layers of fat reached 105.45 ± 5.01 mg/g FPB and 98.46 ± 4.14 mg/g FPB, respectively. These results suggested that excessive SFAs in PB can be converted into PUFAs and provided a new technique for improving PUFAs in FPB. Key points: • This article achieved the conversion of PUFAs in pork backfat by Mucor circinelloides CBS 277.49 and Lactiplantacillus plantarum CGMCC 24189. • This article solved the internal growth of M. circinelloides CBS277.49 in pork backfat by ultrasound combined with papain. • This article proposed an innovative of promoting the internal growth of M. circinelloides and increasing the PUFAs production by oxygen ventilation in pork backfat. [ABSTRACT FROM AUTHOR]

Desalination plays a crucial role in addressing water scarcity and promoting sustainable development. However, the presence of high boron content in seawater poses a significant challenge. This study introduces a progressive freezing-melting method that effectively removes boron while desalinating seawater. The experimental results indicated that salinity and boron rate of removal increased with freezing temperature and decreased with freezing duration. Among the experimental melting methods, ultrasonic melting (UM) and oscillatory melting (OM) were superior to natural melting (NM) for boron removal and desalination, with oscillatory melting proving to be the most effective. Specifically, when seawater was frozen at − 20 °C for 44 h followed by OM of 55% of the ice, salinity and boron removal rates reached 96.79% and 97.60%, respectively. The concentrations of boron and salinity in the treated seawater were only 0.777‰ and 0.149 mg/L. Moreover, the estimated theoretical energy consumption for treating 1 m3 of seawater was calculated to be 5.95 kWh. This study not only contributes to environmental sustainability but also holds significant potential due to its high efficiency in desalination and boron removal. [ABSTRACT FROM AUTHOR]

Objective: The study addresses the long-standing challenge of insufficient length in vascularized fibular flaps when reconstructing large mandibular defects that require dual-barrel grafts. Employing personalized 3D-printed osteotomy guides, the study aims to optimize fibular utilization and minimize the required graft length. Material and methods: Two reconstruction methods for distal bone defects were compared: a fold-down (FD) group that employed a specialized osteotomy guide for folding down a triangular bone segment, and a traditional double-barrel (DB) group. Metrics for comparison included defect and graft lengths, as well as the graft-to-defect length ratio. Postoperative quality of life was assessed using the University of Washington Quality of Life questionnaire (UW-QoL). Result: Both FD and DB groups achieved successful mandibular reconstruction. Despite larger defects in the FD group (117 ± 31.35 mm vs 84 ± 35.34 mm, p = 0.028), the used fibula length was not statistically longer in the FD group. The median ratio of graft-to-defect length was also lower in the FD group (1.327 vs 1.629, p = 0.024), suggesting that FD required only 82.47% of the graft length needed in the DB approach. Quality of life scores post-surgery were comparable between the groups. Conclusion: Personalized 3D-printed osteotomy guides enhance fibula graft efficacy for reconstructing larger mandibular defects, necessitating shorter graft lengths while preserving postoperative quality of life. Clinical relevance: This study confirms the utility of 3D printing technology as an effective and precise tool in orthopedic surgery, particularly for complex reconstructions like large mandibular defects. It suggests a viable alternative that could potentially revolutionize current practices in bone grafting. [ABSTRACT FROM AUTHOR]

A novel non-intrusive and computer vision-based framework for driver fatigue detection from video is proposed in this paper. To improve the judging accuracy of the driver's facial expressions, the personalized threshold is proposed based on the driver's eye aspect ratio and mouth aspect ratio instead of the traditional average threshold, as individual drivers have different eye and mouth sizes. In order to alleviate the impact of the lack of relevant public data on model training, transfer learning is employed to train the eye and mouth state classifier. Furthermore, to address the low universality and accuracy of driver fatigue detection caused by using only one type of facial features, multiple features, including appearance-based features and deep learning-based features, are utilized. The experiment results indicate that our method achieves a 92.21% F1 score and 29 fps, outperforming traditional methods on the public NTHU-DDD dataset. [ABSTRACT FROM AUTHOR]

The behavior of fluid flow through rock fractures in the form of radial flow is a critical issue in various subsurface geological engineering projects. Previous work has considered to couple the radial seepage flow and the normal stress on the fracture surface, while ignored the influence of the fracture surface morphology on the seepage. Therefore, to quantitatively assess the fracture morphology influences on radial permeability, we conducted research adopting seepage testing and fracture surface scanning experiments and the tests results were present in this paper. The difference about fracture surface morphology of each sample can be quantitatively described by fractal dimension. Compared with natural fractures, artificial fractures had larger fractal dimension, rougher surface, and lower radial permeability. And the average radial seepage flow of natural fractures was about 1.57 times that of artificial fractures. In the same sample, the single hole permeability of different outlet holes was also different, which was related to the fracture surface morphology and its fractal dimension of the section line in this direction. The magnitude of fracture radial seepage flow increased with decreasing fractal dimension, and the change law of both followed a negative exponential function. A similar change tendency appeared in both artificial fracture samples and natural fracture samples. [ABSTRACT FROM AUTHOR]

This study has documented the structural and stratigraphic investigations of the Darwaza, Tajwal, Masot, Bhurban, Dewal, and Malkot areas of Murree and KPK, Pakistan. The proposed territory is positioned along the western limb of the Hazara Kashmir syntaxis (HKS). The HKS is an anti-formal hairpin-like architecture, which is seismically an active folded-and-thrust belt in the sub-Himalayas of Pakistan. It was studied using the Kink method (stratigraphic and structural analysis) combined with detailed field observations. The results reveal that the sedimentary rock sequence is fully exposed to the area from the Middle Jurassic (Samana Suk Formation) to date (Quaternary alluvium). Structurally, the study area is highly deformed. Two main deformational episodes (D1 and D2) were recognized. D1 deformation is characterized by tight to isoclinal folds with penetrative axial plane cleavage, axes plunging N43°E/80°NW, and interlimb angle 03–05°, whereas D2 deformation is categorized by open to gentle-style folds with an axial plane ranging from N28°E/68° SE to N50°E/86°NW and an interlimb angle of 95–122°. Moreover, faults and folds are present in the area. Sandh overturned syncline, Sandh anticline, Sandh syncline, Daryagali anticline, Tandoi syncline, Bhurban anticline, and Potha syncline are the major folds. These folds are northwest verging and southeast or southwest plunging. These are isoclinal to gentle folds. The Darwaza fault, Masot fault, and Main Boundary Thrust (MBT) are the major faults in the study area. These faults are northeast–southwest trending and dip to the northwest, thus forming thrust-fault–related folds. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is an age-related neurodegenerative disorder that poses a significant burden on socio-economic and healthcare systems worldwide. However, the currently available therapy of AD is limited, and new strategies are needed to enhance the clearance of β-amyloid (Aβ) protein and improve cognitive function. Photobiomodulation (PBM) is a non-invasive and effective therapeutic method that has shown promise in treating various brain diseases. Here, we demonstrate that 1267-nm PBM significantly alleviates cognitive decline in the 5xFAD mouse model of AD and is safe as it does not induce a significant increase in cortical temperature. Moreover, with the combination of 3D tissue optical clearing imaging and automatic brain region segmentation, we show that PBM-mediated reductions of Aβ plaques in different subregions of prefrontal cortex and the hippocampus are different. The PBM-induced lymphatic clearance of Aβ from the brain is associated with improvement of memory and cognitive functions in 5xFAD mice. Our results suggest that the modulation of meningeal lymphatic vessels (MLVs) should play an important role in promoting Aβ clearance. Collectively, this pilot study demonstrates that PBM can safely accelerate lymphatic clearance of Aβ from the brain of 5xFAD mice, promoting improvement of neurocognitive status of AD animals suggesting that PBM can be an effective and bedside therapy for AD. [ABSTRACT FROM AUTHOR]

The application of continuous natural fibers as reinforcement in composite thin-walled structures offers a feasible approach to achieve light weight and high strength while remaining environmentally friendly. In addition, additive manufacturing technology provides a favorable process foundation for its realization. In this study, the printability and energy absorption properties of 3D printed continuous fiber reinforced thin-walled structures with different configurations were investigated. The results suggested that a low printing speed and a proper layer thickness would mitigate the printing defects within the structures. The printing geometry accuracy of the structures could be further improved by rounding the sharp corners with appropriate radii. This study successfully fabricated structures with various configurations characterized by high geometric accuracy through printing parameters optimization and path smoothing. Moreover, the compressive property and energy absorption characteristics of the structures under quasi-static axial compression were evaluated and compared. It was found that all studied thin-walled structures exhibited progressive folding deformation patterns during compression. In particular, energy absorption process was achieved through the combined damage modes of plastic deformation, fiber pullout and delamination. Furthermore, the comparison results showed that the hexagonal structure exhibited the best energy absorption performance. The study revealed the structure-mechanical property relationship of 3D printed continuous fiber reinforced composite thin-walled structures through the analysis of multiscale failure characteristics and load response, which is valuable for broadening their applications. [ABSTRACT FROM AUTHOR]

One-dimensional (1D) one-way waveguides based on topological edge states of two-dimensional (2D) gyromagnetic photonic crystals have been studied extensively. Here, we theoretically propose a three-dimensional (3D) all-dielectric gyromagnetic photonic crystal with type-II Weyl points. Based on the inclined band properties of the type-II Weyl surface states, we design a 2D one-way interface transmission channel on the Weyl crystal. Light waves in such 2D waveguides can be transmitted robustly over metal obstacles almost without any back-reflection, topologically protected by the type-II Weyl points. By manipulating the magnetic field or structural parameters, we also achieve the topological phase transition between Weyl phase and 3D Chern insulator phase and obtain the corresponding phase diagram, which provides more possibilities for topological regulation of the surface states. This work suggests a new way to construct unidirectional 2D waveguides with larger area of energy transmission in 3D space, which is a promising platform for developing 3D topological photonic devices. [ABSTRACT FROM AUTHOR]

We report on the structural properties of Bi thin films grown on (111) Si substrates with a thickness of 22–30 BL. HRXRD and EBSD measurements show that these Bi films are mainly composed of twinning grains in the (0003) direction. The grain size can be as large as tens of microns. From a double-peak (01 1 ¯ 4) φ-scan, we found two pairs of twinning phases coexisting with a rotation angle of ~ 3.6°. We proposed a coincidence site lattice model based on preferential close-packed sites for Bi atoms on Si (111) surface to explain the coexistence of the rotation phases in the quasi-van der Waals epitaxy. From the measured lattice constants c and a of our samples, along with the data from the literature, we derived a c–a relation: (c–c0) = − 2.038(a–a0), where c0 and a0 are the values of bulk Bi. The normalized position of the second basis atom in the unit cell x, in these strained Bi films is found very close to that of bulk Bi, indicating that the strain does not disturb the Peierls distortion of the lattice. The fixed ratio of bilayer thickness to lattice constant c, reveals that the elastic properties of covalent-bonded bilayer dominate those of Bi crystal. [ABSTRACT FROM AUTHOR]

Purpose: To investigate whether the cost-effective, pretreatment tumor markers carcinoembryonic antigen (CEA) and carbohydrate antigen-125 (CA-125) can be used to predict lymph node metastasis (LNM) in endometrioid-type endometrial cancer (EC) and to develop a predictive model. Methods: This was a single-center retrospective study of patients with endometrioid-type EC who underwent complete staging surgery between January 2015 and June 2022. We identified the optimal cut-off values of CEA and CA-125 for predicting LNM using receiver operating characteristic (ROC) curves. Stepwise multivariate logistic regression analysis was used to identify independent predictors. A nomogram for predicting LNM was constructed and validated by bootstrap resampling. Results: The optimal cut-off values of CEA and CA-125 were 1.4 ng/mL (area under the ROC curve (AUC) 0.62) and 40 U/mL (AUC 0.75), respectively. Multivariate analysis showed that CEA (odds ratio (OR) 1.94; 95% confidence interval (CI) 1.01–3.74) and CA-125 (OR 8.75; 95% CI 4.42–17.31) were independent predictors of LNM. Our nomogram showed adequate discrimination with a concordance index of 0.78. Calibration curves for the probability of LNM showed optimal agreement between the predicted and actual probabilities. The risk of LNM for markers below the cut-offs was 3.6%. The negative predictive value and negative likelihood ratio were 96.6% and 0.26, respectively, with moderate ability to rule out the possibility of LNM. Conclusion: We report a cost-effective method of using pretreatment CEA and CA-125 levels to identify patients with endometrioid-type EC who are at a low risk for LNM, which may guide decision-making regarding aborting lymphadenectomy. [ABSTRACT FROM AUTHOR]

Background and Objective: Glioblastoma is a cranial malignant tumor with a high recurrence rate after surgery and a poor response to chemoradiotherapy. Bevacizumab has demonstrated efficacy in the treatment of glioblastoma by inhibiting vascular endothelial growth factor, but the efficacy of vascular endothelial growth factor receptor tyrosine kinase inhibitors varies in treating glioblastoma. This single-arm prospective study aimed to explore the efficacy and safety of the vascular endothelial growth factor receptor tyrosine kinase inhibitor apatinib in treating recurrent glioblastoma after chemoradiotherapy. Methods: A total of 15 patients with recurrent glioblastoma (2016 World Health Organization grade IV) after chemoradiotherapy were enrolled in this study from September 2017 to September 2019 and treated with apatinib 500 mg once daily. Responses were evaluated according to the Response Assessment in Neuro-Oncology criteria, and adverse events were recorded according to the National Cancer Institute Common Terminology Criteria for Adverse Events Version 4.0. Results: The overall response rate was 33.3%, and the disease control rate was 66.6%. The median progression-free survival was 2 months, and the median overall survival was 6.5 months. The apatinib dose was adjusted in seven patients because of adverse events (46.6%). The most common adverse events were thrombocytopenia (53.3%), asthenia (40%), and hand-foot syndrome (33.3%). Conclusions: Apatinib might be effective in treating recurrent glioblastoma after chemoradiotherapy in terms of the overall response rate, but the efficacy is not durable and the clinical benefit is limited. The adverse effects of apatinib were acceptable. Clinical Trial Registration: ChiCTR-ONC-17013098, date of registration: 24 October, 2017. [ABSTRACT FROM AUTHOR]

Electrospray deposition (ESD) is a promising technique for depositing micro-/nano-scale droplets and particles with high quality and repeatability. It is particularly attractive for surface coating of costly and delicate biomaterials and bioactive compounds. While high efficiency of ESD has only been successfully demonstrated for spraying surfaces larger than the spray plume, this work extends its utility to smaller surfaces. It is shown that by architecting the local "charge landscape", ESD coatings of surfaces smaller than plume size can be achieved. Efficiency approaching 100% is demonstrated with multiple model materials, including biocompatible polymers, proteins, and bioactive small molecules, on both flat and microneedle array targets. UV-visible spectroscopy and high-performance liquid chromatography measurements validate the high efficiency and quality of the sprayed material. Here, we show how this process is an efficient and more competitive alternative to other conformal coating mechanisms, such as dip coating or inkjet printing, for micro-engineered applications. Electrospray deposition is a promising technique for depositing functional coatings at the micro-/nano-scale. Here, the authors establish the necessary conditions for high efficiency electrospray deposition of small targets, establishing promise as an alternative to other conformal coating methods. [ABSTRACT FROM AUTHOR]

Background and aims: The use of sutures to strengthen the anastomosis after rectal cancer surgery to reduce the possibility of anastomotic leakage has been debated. The aim of this systematic review and meta-analysis was to investigate the influence of intraoperative anastomotic reinforcing sutures on anastomotic leakage of double-stapling anastomosis for laparoscopic rectal cancer surgery. Methods: A systematic search of PubMed, Embase, Web of Science, and Cochrane databases was performed to identify literature examining anastomotic leak as the primary outcome to compare studies of laparoscopic surgery for rectal cancer using the double-stapling anastomosis technique with or without intraoperative anastomotic reinforcement with sutures. Results: A total of 1122 rectal cancer patients from 5 nonrandomized studies were included in the research. In the combined trial, intraoperative anastomotic reinforcement sutures significantly reduced the incidence of anastomotic leakage in patients who underwent laparoscopic rectal cancer surgery (OR, 0.32; 95% CI, 0.19–0.55; p < 0.0001). With or without intraoperative anastomotic reinforcing sutures, the incidence of postoperative reoperation for anastomotic leak did not differ substantially (OR, 0.32; 95% CI, 0.08–1.21, p = 0.09). Moreover, the surgery was prolonged due to anastomotic reinforcement with sutures (OR, 6.64; 95% CI, − 6.18 to 19.47, p = 0.31). Conclusions: Intraoperative anastomotic reinforcement with sutures may be associated with a lower incidence of anastomotic leakage. The amount of research evidence is limited because most of the studies analyzed did not include patients with factors such as neoadjuvant therapy or prophylactic stomas. Therefore, additional multicenter randomized controlled studies with larger size samples are needed to support the validity of the approach. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has led to a global surge in Sinophobia. We examine how Chinese language users responded to COVID-19 on Western social media by compiling a unique database (CNTweets) with over 25 million Chinese tweets mentioning any Chinese characters related to China, the Chinese Communist Party (CCP), Chinese, and Asians from December 2019 to April 2021. Our analysis of Twitter users' self-reported geographic information shows that most Chinese language users on Twitter originated from Mainland China, Hong Kong, Taiwan, and the United States. We then adopt the Robustly Optimized Bidirectional Encoder Representations from Transformers (RoBERTa) and structural topic modeling to further analyze the sentiments, content, and topics of Chinese tweets during the COVID-19 pandemic. Our results suggest that 61.8% of tweets in our database were contributed by only 1% of Twitter users and 62.2% of tweets were negative toward China. Despite the prevalence of anti-China sentiments, the target entity analysis shows that these negative sentiments were more likely to target the Chinese government and CCP than the Chinese people. Our findings also show that the most popular topics were politics (e.g., Hong Kong protests and Taiwan issues), COVID-19, and the United States (e.g., the US-China relations and domestic issues). Anti-China users focused relatively more on political issues such as democracy and freedom, while pro-China users mentioned cultural and economic topics more. Our social network analysis reveals that these pro-China and anti-China Twitter users lacked in-depth engagement in China-related conversations and were highly segregated from each other. We conclude by discussing our contributions to China and social media studies and possible policy implications. [ABSTRACT FROM AUTHOR]

Circadian disruption is involved in the progress of sepsis-induced cardiomyopathy (SICM), one of the leading causes of death in sepsis. The molecular mechanism remains ambiguous. In this study, LPS was used to build SICM model in H9c2 cell. The results suggested that LPS induced cytotoxicity via increasing ferroptosis over the time of course. After screening the expressions of six circadian genes, the circadian swing of Bmal1 was dramatically restrained by LPS in H9c2 cell of SIMC vitro model. PcDNA and siRNA were used to upregulate and downregulate Bmal1 and confirmed that Bmal1 inhibited LPS-triggered ferroptosis in H9c2 cells. Then, the results suggested that AKT/p53 pathway was restrained by LPS in H9c2 cell. Rescue test indicated that Bmal1 inhibited LPS-triggered ferroptosis via AKT/p53 pathway in H9c2 cells. In summary, our findings demonstrated that LPS induced cytotoxicity via increasing ferroptosis over the time of course in H9c2 cells and Bmal1 inhibited this toxicity of LPS via AKT/p53 pathway. Although further studies are needed, our findings may contribute to a new insight to mechanism of SICM. [ABSTRACT FROM AUTHOR]

Large-scale screening for the risk of coronary heart disease (CHD) is crucial for its prevention and management. Physical examination data has the advantages of wide coverage, large capacity, and easy collection. Therefore, here we report a gender-specific cascading system for risk assessment of CHD based on physical examination data. The dataset consists of 39,538 CHD patients and 640,465 healthy individuals from the Luzhou Health Commission in Sichuan, China. Fifty physical examination characteristics were considered, and after feature screening, ten risk factors were identified. To facilitate large-scale CHD risk screening, a CHD risk model was developed using a fully connected network (FCN). For males, the model achieves AUCs of 0.8671 and 0.8659, respectively on the independent test set and the external validation set. For females, the AUCs of the model are 0.8991 and 0.9006, respectively on the independent test set and the external validation set. Furthermore, to enhance the convenience and flexibility of the model in clinical and real-life scenarios, we established a CHD risk scorecard base on logistic regression (LR). The results show that, for both males and females, the AUCs of the scorecard on the independent test set and the external verification set are only slightly lower (<0.05) than those of the corresponding prediction model, indicating that the scorecard construction does not result in a significant loss of information. To promote CHD personal lifestyle management, an online CHD risk assessment system has been established, which can be freely accessed at http://lin-group.cn/server/CHD/index.html. [ABSTRACT FROM AUTHOR]

Labor mobility is an inherent component of economic development and labor market changes. With globalization and urbanization, labor mobility is on the rise in many developing countries, and it is of great significance to study the economic outcomes and poverty alleviation effects of this phenomenon. This paper explores the impact of labor mobility on the wages of rural migrants when they move out with their fellow townsmen (folks from the same county). The study uses the China Migrants Dynamic Survey (CMDS) data and applies the Propensity Score Matching (PSM) method for empirical analysis. Our results suggest that labor mobility with fellow townsmen significantly increases the wages of rural migrants. The paper shows two promotion mechanisms: mobility with fellow townsmen affects the wages of rural migrants by improving their ability to search for information and negotiate wages. Heterogeneity analysis indicates that mobility with fellow townsmen significantly increases the wages of rural migrants engaged in producer service, consumer service, blue-collar occupations, and working in state-owned and private enterprises. Furthermore, it has a more positive impact on the wages of older rural migrants from an intergenerational perspective. Interestingly, rural migrants may "give up" part of their wages to care for their families when they move with their spouses, parents, or children. Therefore, the government needs to take effective policy measures to promote the employment service system and improve the labor rights and interests protection mechanism for rural migrants. [ABSTRACT FROM AUTHOR]

In the application recommendation field, collaborative filtering (CF) method is often considered to be one of the most effective methods. As the basis of CF-based recommendation methods, representation learning needs to learn two types of factors: attribute factors revealed by independent individuals (e.g., user attributes, application types) and interaction factors contained in collaborative signals (e.g., interactions influenced by others). However, existing CF-based methods fail to learn these two factors separately; therefore, it is difficult to understand the deeper motivation behind user behaviors, resulting in suboptimal performance. From this point of view, we propose a multi-granularity coupled graph neural network recommendation method based on implicit relationships (IMGC-GNN). Specifically, we introduce contextual information (time and space) into user-application interactions and construct a three-layer coupled graph. Then, the graph neural network approach is used to learn the attribute and interaction factors separately. For attribute representation learning, we decompose the coupled graph into three homogeneous graphs with users, applications, and contexts as nodes. Next, we use multilayer aggregation operations to learn features between users, between contexts, and between applications. For interaction representation learning, we construct a homogeneous graph with user-context-application interactions as nodes. Next, we use node similarity and structural similarity to learn the deep interaction features. Finally, according to the learned representations, IMGC-GNN makes accurate application recommendations to users in different contexts. To verify the validity of the proposed method, we conduct experiments on real-world interaction data from three cities and compare our model with seven baseline methods. The experimental results show that our method has the best performance in the top-k recommendation. [ABSTRACT FROM AUTHOR]

Background: This study aimed to assess whether postoperative adjuvant chemoimmunotherapy could lead to better clinical outcomes for high-risk patients with perihilar cholangiocarcinoma (pCCA). Methods: In the cohort study, we retrospectively reviewed patients who received surgical resection for pCCA with curative intent from January 2018 to December 2021 at the Sun Yat-sen Memorial Hospital. The patients at high risk for relapse were further analyzed. Among them, 20 patients received adjuvant chemoimmunotherapy, 28 patients received adjuvant chemotherapy, and 33 patients received surgery alone. The oncological outcomes and drug-associated adverse events were evaluated. Results: The 2-year overall survival (OS) rates in patients treated with adjuvant chemoimmunotherapy, adjuvant chemotherapy, and surgery alone were 80.0%, 49.4% and 22.6%, respectively. Univariable and multivariable Cox analyses showed that the treatment regimen and TNM stage were associated with adverse OS. Adjuvant chemoimmunotherapy led to an increase in OS compared with adjuvant chemotherapy [hazard ratio (HR) = 3.253; 95% confidence interval (CI) 1.072–9.870; P = 0.037] or surgery alone (HR = 7.560; 95% CI 2.508–22.785; P < 0.001). The median recurrence-free survival was 22.0 months for the adjuvant chemoimmunotherapy group, 17.0 months for the adjuvant chemotherapy group, and 13.2 months for the surgery alone group (P = 0.177); these differences were not significant. The chemoimmunotherapy group was associated with more frequent hematological side effects than the chemotherapy group, but the difference was not statistically significant. Conclusion: Postoperative adjuvant chemoimmunotherapy for resected pCCA patients showed improved OS compared with adjuvant chemotherapy or surgery alone, and further prospectively randomized controlled trials are necessary to validate these results. [ABSTRACT FROM AUTHOR]

Neutralizing antibodies exert a potent inhibitory effect on viral entry; however, they are less effective in therapeutic models than in prophylactic models, presumably because of their limited efficacy in eliminating virus-producing cells via Fc-mediated cytotoxicity. Herein, we present a SARS-CoV-2 spike-targeting bispecific T-cell engager (S-BiTE) strategy for controlling SARS-CoV-2 infection. This approach blocks the entry of free virus into permissive cells by competing with membrane receptors and eliminates virus-infected cells via powerful T cell-mediated cytotoxicity. S-BiTE is effective against both the original and Delta variant of SARS-CoV2 with similar efficacy, suggesting its potential application against immune-escaping variants. In addition, in humanized mouse model with live SARS-COV-2 infection, S-BiTE treated mice showed significantly less viral load than neutralization only treated group. The S-BiTE strategy may have broad applications in combating other coronavirus infections. A SARS-CoV-2 spike-targeting bispecific T-cell engager (S-BiTE) strategy is presented that effectively reduces SARS-CoV-2 viral load in a humanized mouse model. [ABSTRACT FROM AUTHOR]

Objectives: Lymph node (LN) metastasis is a common cause of recurrence in oral cancer; however, the accuracy of distinguishing positive and negative LNs is not ideal. Here, we aimed to develop a deep learning model that can identify, locate, and distinguish LNs in contrast-enhanced CT (CECT) images with a higher accuracy. Methods: The preoperative CECT images and corresponding postoperative pathological diagnoses of 1466 patients with oral cancer from our hospital were retrospectively collected. In stage I, full-layer images (five common anatomical structures) were labeled; in stage II, negative and positive LNs were separately labeled. The stage I model was innovatively employed for stage II training to improve accuracy with the idea of transfer learning (TL). The Mask R-CNN instance segmentation framework was selected for model construction and training. The accuracy of the model was compared with that of human observers. Results: A total of 5412 images and 5601 images were labeled in stage I and II, respectively. The stage I model achieved an excellent segmentation effect in the test set (AP50-0.7249). The positive LN accuracy of the stage II TL model was similar to that of the radiologist and much higher than that of the surgeons and students (0.7042 vs. 0.7647 (p = 0.243), 0.4216 (p < 0.001), and 0.3629 (p < 0.001)). The clinical accuracy of the model was highest (0.8509 vs. 0.8000, 0.5500, 0.4500, and 0.6658 of the Radiology Department). Conclusions: The model was constructed using a deep neural network and had high accuracy in LN localization and metastasis discrimination, which could contribute to accurate diagnosis and customized treatment planning. Key Points: • Lymph node metastasis is not well recognized with modern medical imaging tools. • Transfer learning can improve the accuracy of deep learning model prediction. • Deep learning can aid the accurate identification of lymph node metastasis. [ABSTRACT FROM AUTHOR]

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Although medical imaging is frequently used to diagnose diseases, in complex diagnostic situations, specialists typically need to look at different modalities of image information. Creating a composite multimodal medical image can aid professionals in making quick and accurate diagnoses of diseases. The fused images of many medical image fusion algorithms, however, are frequently unable to precisely retain the functional and structural information of the source image. This work develops an end-to-end model based on GAN (U-Patch GAN) to implement the self-supervised fusion of multimodal brain images in order to enhance the fusion quality. The model uses the classical network U-net as the generator, and it uses the dual adversarial mechanism based on the Markovian discriminator (PatchGAN) to enhance the generator's attention to high-frequency information. To ensure that the network satisfies the Lipschitz continuity, we apply the spectral norm to each layer of the network. We also propose better adversarial loss and feature loss (feature matching loss and VGG-16 perceptual loss) based on the F-norm, which significantly enhance the quality of fused images. On public data sets, we performed a lot of tests. First, we studied how clinically useful the fused image was. The model's performance in single-slice images and continuous-slice images was then confirmed by comparison with other six most popular mainstream fusion approaches. Finally, we verify the effectiveness of the adversarial loss and feature loss. [ABSTRACT FROM AUTHOR]

Fish suffer from starvation due to environmental risks such as extreme weather in the wild and due to insufficient feedings in farms. Nutrient problems from short-term or long-term starvation conditions can result in stress-related health problems for fish. Yellowfin seabream (Acanthopagrus latus) is an important marine economic fish in China. Understanding the molecular responses to starvation stress is vital for propagation and culturing yellowfin seabream. In this study, the transcriptome and genome-wide DNA methylation levels in the livers of yellowfin seabream under 14-days starvation stress were analyzed. One hundred sixty differentially expressed genes (DEGs) by RNA-Seq analysis and 737 differentially methylated-related genes by whole genome bisulfite sequencing analysis were identified. GO and KEGG pathway enrichment analysis found that energy metabolism–related pathways such as glucose metabolism and lipid metabolism were in response to starvation. Using bisulfite sequencing PCR, we confirmed the presence of CpG methylation differences within the regulatory region of a DEG ppargc1a in response to 14-days starvation stress. This study revealed the molecular responses of livers in response to starvation stress at the transcriptomic and whole genome DNA methylation levels in yellowfin seabream. [ABSTRACT FROM AUTHOR]

The main objective of this study was to examine the use of protection motivation theory (PMT) in explaining smokers' quitting intentions among Chinese adults with the goal of providing valuable evidence to promote theory-guided and culturally appropriate cessation interventions. This cross-sectional study included 613 participants randomly selected from 26 provinces in Mainland China. Cronbach's alpha and interclass correlation coefficients (ICC) were used to assess the reliability of individual PMT constructs. A multiple linear regression was used for the multivariable analysis. Cronbach's alpha coefficient of the 23 items was 0.74. Cronbach's alpha coefficient of all the subscales varied from 0.71 to 0.74. Stronger quitting intentions were significantly associated with higher perceived vulnerability (Coef. = 0.13, P < 0.01), self-efficacy (Coef. = 0.28, P < 0.01), and response efficacy (Coef. = 0.23, P < 0.01) but inversely associated with intrinsic rewards (Coef. = −0.15, P < 0.01). Greater quitting intentions were significantly associated with higher threat (Coef. = 0.19, P < 0.01) and coping appraisals (Coef. = 0.25, P < 0.01). Regarding behaviour, longer quitting attempts were significantly associated only with self-efficacy (Coef. = 0.13, P < 0.01) and response cost (Coef. = −0.18, P < 0.01) Our results confirmed the applicability of PMT for predicting the quitting intention in Chinese adults. Self-efficacy is the only factor that has a predictive effect on both the intention and behaviour. To improve the effectiveness of smoking-cessation interventions, specific attention should be directed during their design to the more influential PMT constructs. [ABSTRACT FROM AUTHOR]

PET-MRI fusion images are of great significance in improving diagnostic accuracy and nursing quality. However, existing fusion methods usually subjectively define fusion rules to retain specific fusion regions, which will lead to information distortion. Complex processes or network design can also significantly slow down fusion speed. The fusion results of unsupervised models without artificially setting fusion rules are usually poor. To address these limitations, we designed an unsupervised model to accomplish the fusion of MRI-PET brain images. We use the attention modules CBAM (convolutional block attention module) and AG (attention gate) to dynamically highlight the salient features, and the ASPP (arous spatial pyramid pooling) module and residual structure are used to maximize the preservation of source image information. The unique design of each module saves us a lot of computational costs. In addition, we designed a fusion strategy for separating the bone density information and the fusion region, which solves the problem of MRI bone density information retention during image fusion. We have done lots of experiments to verify the superiority of the model. In comparison with the state-of-the-art methods, our model has a higher QG than FusionDN at 68.9% and a Qs than U2Fusion at 120.49%, and the fusion efficiency has also reached a high level. [ABSTRACT FROM AUTHOR]

The purpose of this study was the design of a vibrator that would be suitable for the ultrasonic tool holder using the "coolant through spindle structure," as well as to investigate the effects of the shape, material and design of the vibrator on the performance of the tool holder assembly. The COMSOL Engineering simulation program was used for cross verification of resonance frequency and amplitude as well as to analyze the node position of the vibrator using the frequency analysis feature. Comparison of the measured and simulated values of the vibrator resonance frequency showed the error rate to be 2.97% and 2.76% for 2 cells and 4 cells of piezoelectric ceramic respectively. Next, during the experiment measuring by installing varied types of piezoelectric ceramics in the vibrator, it showed that a higher amplitude response could be achieved with PZT-8 piezoelectric ceramics material than was possible with PZT-4 material. The third experiment being conducted by locking the vibrator with varied bolt pretension forces indicated that an increase in bolt pretension force caused a sudden steep drop in initial equivalent impedance which gradually stabilized. During the final experiment, the performance response of the vibrator was also measured using tools of different size and the results showed that there was a difference of 600 Hz in resonance frequency between tools of 10 mm and 8 mm in diameter. Longer tools also resonated at lower frequency, but with higher amplitude. The maximum offset was expressed as 1000 Hz and 11.5 μm. [ABSTRACT FROM AUTHOR]

Background and Objective: In clinical practice, injectable drug combination (IDC) usually provides good therapeutic effects for patients. Numerous clinical studies have directly indicated that inappropriate IDC generates adverse drug events (ADEs). The clinical application of injections is increasing, and many injections lack relevant combination information. It is still a significant need for experienced clinical pharmacists to participate in evidence-based drug decision making, monitor medication safety, and manage drug interactions. Meanwhile, a large number of injection pairs and dosage combinations limit exhaustive screening. Here, we present a prediction framework, called DeepIDC, that can expediently screen the feasibility of IDCs using heterogeneous information with deep learning. This is the first specific prediction framework to identify IDCs. Methods: Since the interaction between the injected drugs may occur in the direct physical and chemical reactions at the time of mixing or may be the indirect interaction of their drug targets and pathways, we used molecular fingerprints, drug-target associations, and drug-pathway associations to convert injections into a string of digital vectors. Then, based on these injection vectors, we combined a bidirectional long short-term memory and a feed-forward neural network to build a prediction model for accurate and instructive prediction of IDC. Results: In three realistic evaluation scenarios, DeepIDC has achieved ideal prediction results. Furthermore, compared with the other five machine-learning methods, the proposed predictor is more efficient and robust. Among the top 30 potential IDCs of each IDC class predicted by DeepIDC, we found that 9 cases were experimentally verified in the literature or available on Drug.com. Conclusion: The information we extracted in vivo and in vitro can effectively characterize injectable drugs. DeepIDC developed based on deep learning algorithm provides a valuable unified framework for new IDC discovery, which can make up for the lack of IDC information and predict potential IDC events. [ABSTRACT FROM AUTHOR]

Due to centralized storage, centralization problems are common in machine learning model training and invocation, which makes train data and trained models extremely vulnerable to tampering and stealing. A safe framework for training and invoking models called ISC-MTI (IPFS (InterPlanetary File System) and Smart Contract-Based Method for Storage and Invocation of Machine Learning Mobel) is proposed in this paper. The framework uses IPFS as the storage solution, EOS (Enterprise Operation System) blockchain as the smart contract platform, RSA and AES as the implementation of encrypted communication. The Action responsible for invoking the training data and trained models in the smart contract and the model training, uploading, and invoking methods are designed. The experimental results demonstrate that ISC-MTI can improve the safety of model training and invocation with losing a little efficiency. Simultaneously, ISC-MTI can provide anti-theft model capabilities, traceability, tamper resistance, reliability, and privacy for the process. [ABSTRACT FROM AUTHOR]