JCcirc: circRNA full-length sequence assembly through integrated junction contigs.

Recent studies have shed light on the potential of circular RNA (circRNA) as a biomarker for disease diagnosis and as a nucleic acid vaccine. The exploration of these functionalities requires correct circRNA full-length sequences; however, existing assembly tools can only correctly assemble some circRNAs, and their performance can be further improved. Here, we introduce a novel feature known as the junction contig (JC), which is an extension of the back-splice junction (BSJ). Leveraging the strengths of both BSJ and JC, we present a novel method called JCcirc (https://github.com/cbbzhang/JCcirc). It enables efficient reconstruction of all types of circRNA full-length sequences and their alternative isoforms using splice graphs and fragment coverage. Our findings demonstrate the superiority of JCcirc over existing methods on human simulation datasets, and its average F1 score surpasses CircAST by 0.40 and outperforms both CIRI-full and circRNAfull by 0.13. For circRNAs below 400 bp, 400-800 bp, 800 bp-1200 bp and above 1200 bp, the correct assembly rates are 0.13, 0.09, 0.04 and 0.03 higher, respectively, than those achieved by existing methods. Moreover, JCcirc also outperforms existing assembly tools on other five model species datasets and real sequencing datasets. These results show that JCcirc is a robust tool for accurately assembling circRNA full-length sequences, laying the foundation for the functional analysis of circRNAs.

RevGraphVAMP: A protein molecular simulation analysis model combining graph convolutional neural networks and physical constraints.

Molecular dynamics simulation is a crucial research domain within the life sciences, focusing on comprehending the mechanisms of biomolecular interactions at atomic scales. Protein simulation, as a critical subfield, often utilizes MD for implementation, with trajectory data play a pivotal role in drug discovery. The advancement of high-performance computing and deep learning technology becomes popular and critical to predict protein properties from vast trajectory data, posing challenges regarding data features extraction from the complicated simulation data and dimensionality reduction. Simultaneously, it is essential to provide a meaningful explanation of the biological mechanism behind dimensionality. To tackle this challenge, we propose a new unsupervised model named RevGraphVAMP to intelligently analyze the simulation trajectory. This model is based on the variational approach for Markov processes (VAMP) and integrates graph convolutional neural networks and physical constraint optimization to enhance the learning performance. Additionally, we introduce attention mechanism to assess the importance of key interaction region, facilitating the interpretation of molecular mechanism. In comparison to other VAMPNets models, our model showcases competitive performance, improved accuracy in state transition prediction, as demonstrated through its application to two public datasets and the Shank3-Rap1 complex, which is associated with autism spectrum disorder. Moreover, it enhanced dimensionality reduction discrimination across different substates and provides interpretable results for protein structural characterization.

Transcriptome analysis of sexual dimorphism in dorsal down coloration in goslings.

BACKGROUND: In day-old Hungarian white goose goslings, there is a noticeable difference in dorsal down coloration between males and females, with females having darker dorsal plumage and males having lighter plumage. The ability to autosex day-old goslings based on their dorsal down coloration is important for managing them efficiently and planning their nutrition in the poultry industry. The aim of this study was to determine the biological and genetic factors underlying this difference in dorsal down colorationthrough histological analysis, biochemical assays, transcriptomic profiling, and q‒PCR analysis. RESULTS: Tissue analysis and biochemical assays revealed that compared with males, 17-day-old embryos and day-old goslings of female geese exhibited a greater density of melanin-containing feather follicles and a greater melanin concentration in these follicles during development. Both female and male goslings had lower melanin concentrations in their dorsal skin compared to 17-day-old embryos. Transcriptome analysis identified a set of differentially expressed genes (DEGs) (MC1R, TYR, TYRP1, DCT and MITF) associated with melanogenesis pathways that were downregulated or silenced specifically in the dorsal skin of day-old goslings compared to 17-day-old embryos, affecting melanin synthesis in feather follicles. Additionally, two key genes (MC1R and MITF) associated with feather coloration showed differences between males and females, with females having higher expression levels correlated with increased melanin synthesis and darker plumage. CONCLUSION: The expression of multiple melanogenesis genes determines melanin synthesis in goose feather follicles. The dorsal down coloration of day-old Hungarian white goose goslings shows sexual dimorphism, likely due to differences in the expression of the MC1R and MITF genes between males and females. These results could help us better understand why male and female goslings exhibit different plumage patterns.

Development and validation of genome-wide SSR molecular markers of Tapes dorsatus.

BACKGROUND: Tapes dorsatus is an economically important benthic animal in the Beibu Gulf of China. However, the deficiency of microsatellite markers has hindered the study of its genetics. The development of microsatellite markers will provide useful tools for genetic improvement, variety identification, phylogenetic analysis and resource conservation. METHODS AND RESULTS: Within the genome sequence, 145,008 simple sequence repeats (SSRs) were identified, and 29,691 primer pairs were designed successfully. A total of 100 primer pairs were randomly synthesized for testing, and 93 primers yielded products. Sixty highly polymorphic primers were used to reveal the genetic diversity of 50 T. dorsatus individuals. The average number of alleles (Na) of the population was 10.40; the average number of effective alleles was 6.16, the average expected heterozygosity (He) was 0.82, and the average polymorphic information content was 0.80. The genetic structure of the population was detected, by which the population could be divided into three subpopulations. CONCLUSION: We identified 145,008 SSRs in the genome of T. dorsatus and designed 29,691 primer pairs in this study. Of 100 synthesized primers, 60 were highly polymorphic and used to reveal the genetic diversity and structure of the population. The SSR markers identified here will provide useful tools and a foundation for genetic diversity, linkage mapping and molecular marker-aided breeding in T. dorsatus.

A meta-analysis for prevalence of infectious laryngotracheitis in chickens in mainland China in 1981-2022.

BACKGROUND: Infectious laryngotracheitis (ILT) is a highly infectious upper respiratory tract disease of chickens caused by infectious laryngotracheitis virus or Gallid herpesvirus 1 (GaHV-1). ILT is an important respiratory disease of chickens and annually causes significant economic losses in the chicken industry. Although numerous relevant studies have been published, the overall prevalence of ILT infection among chicken in mainland China is still unknown, and associated risk factors need to be evaluated to establish preventive measures. RESULTS: The present study reviewed the literature on the prevalence of ILT in chickens in China as of December 20, 2022, retrieved from six databases-CNKI, Wanfang, VIP, PubMed, Web of Science, and ScienceDirect-were used to retrieve relevant studies published between January 1, 1981 and December 20, 2022. The literature quality of studies was assessed, and 20 studies with a total of 108,587 samples were included in the meta-analysis. Results of the meta-analysis showed that the overall prevalence of ILT was 10% (95% confidence interval: 8 -12%) through the random-effects model, which showed high heterogeneity, I2 = 99.4%. Further subgroup analyses showed that the prevalence of ILT decreased over time; furthermore, the prevalence in Northwest China was slightly lower than that in North China and South China, and the prevalence estimated using the diagnostic technique AGP was higher than that reported using other diagnostic techniques. CONCLUSIONS: ILT is prevalent to some extent in mainland China. Given that the ILT attenuated live vaccine has a certain level of virulence and the prevalence differences between regions, we recommend controlling breeding density, improving immunization programs and continuously monitoring viruses and to prevent ILT prevailing in mainland China.

Nrf2, gp91phox and IL-17 are associated with severity and clinical outcomes of patients with subclinical hypothyroidism: a comparative study.

The mechanisms underlying subclinical hypothyroidism (SCH) remain unclear, making timely and accurate differentiation between hypothyroidism and SCH, as well as severity assessment, challenging. This study aimed to investigate the role of NFE2 like bZIP transcription factor 2 (Nrf2), gp91phox, and interleukin-17 (IL-17) in the pathogenesis of SCH. In this prospective comparative study, 105 SCH patients, 105 hypothyroidism patients, and 105 healthy individuals were enrolled from January 2022 to August 2023. SCH patients were categorized into mild-moderate and severe groups based on thyroid-stimulating hormone (TSH) levels. Levels of TSH, free T4 (FT4), free T3 (FT3), thyroglobulin antibodies (TG-Ab), thyroid peroxidase antibodies (TPO-Ab), cholesterol (TC), triglycerides (TG), high-density lipoprotein-cholesterol (HDL-ch), and low-density lipoprotein-cholesterol (LDL-ch) were measured. Nrf2, IL-1ß, IL-6, IL-17, and gp91phox levels were tested using ELISA. Nrf2, IL-17 and gp91phox were significantly higher in SCH and hypothyroidism patients compared to the healthy controls, with hypothyroidism patients showing the highest levels. Nrf2 levels were negatively correlated with TSH, TG-Ab and IL-17, but not gp91phox. Nrf2, IL-17 and gp91phox could be used for diagnosis of SCH and severe SCH. Only TG-Ab, IL-17 and gp91phox were independent risk factors for severe SCH. This study demonstrates a negative correlation between serum Nrf2 levels and SCH severity. TG-Ab, IL-17, and gp91phox are independent risk factors, and their associations with SCH pathology suggest their potential roles in the disease mechanism. These findings provide insights into SCH pathogenesis and highlight the need for further research to elucidate their diagnostic or prognostic significance.

Placental T2WI MRI-based radiomics-clinical nomogram predicts suspicious placenta accreta spectrum in patients with placenta previa.

BACKGROUND: The incidence of placenta accreta spectrum (PAS) increases in women with placenta previa (PP). Many radiologists sometimes cannot completely and accurately diagnose PAS through the simple visual feature analysis of images, which can affect later treatment decisions. The study is to develop a T2WI MRI-based radiomics-clinical nomogram and evaluate its performance for non-invasive prediction of suspicious PAS in patients with PP. METHODS: The preoperative MR images and related clinical data of 371 patients with PP were retrospectively collected from our hospital, and the intraoperative examination results were used as the reference standard of the PAS. Radiomics features were extracted from sagittal T2WI MR images and further selected by LASSO regression analysis. The radiomics score (Radscore) was calculated with logistic regression (LR) classifier. A nomogram integrating Radscore and selected clinical factors was also developed. The model performance was assessed with respect to discrimination, calibration and clinical usefulness. RESULTS: A total of 6 radiomics features and 1 clinical factor were selected for model construction. The Radscore was significantly associated with suspicious PAS in both the training (p < 0.001) and validation (p < 0.001) datasets. The AUC of the nomogram was also higher than that of the Radscore in the training dataset (0.891 vs. 0.803, p < 0.001) and validation dataset (0.897 vs. 0.780, p < 0.001), respectively. The calibration was good, and the decision curve analysis demonstrated the nomogram had higher net benefit than the Radscore. CONCLUSIONS: The T2WI MRI-based radiomics-clinical nomogram showed favorable diagnostic performance for predicting PAS in patients with PP, which could potentially facilitate the obstetricians for making clinical decisions.

Meta-analysis of clinical efficacy of thoracoscopy and robotic surgery in the treatment of mediastinal tumors.

OBJECTIVE: Comparing the clinical efficacy of thoracoscopy and robotic surgery in the treatment of mediastinal tumors using meta-analysis. METHODS: Computer retrieval of PubMed, Embase, The Cochrane Library, and Web of Science databases for literature comparing the clinical effects of video-assisted thoracic surgery (VATS) and robot-assisted thoracic surgery (RATS) in treating mediastinal tumors, with the retrieval time limit from the establishment of the database to September 2023. Two evaluators independently screened the literature, extracted data, and assessed the risk of bias. Meta-analysis was performed using RevMan 5.4. RESULTS: A total of 19 articles were included, with a total of 3517 patients. The results of the Meta-analysis showed that the RATS group had less intraoperative bleeding [MD = - 5.20, 95%CI (- 9.28, - 1.12), P = 0.01], lower rate of conversion to thoracotomy [OR = 0.41, 95%CI (0.23, 0.72), P = 0.002], lower rate of total postoperative complications [OR = 0.57, 95%CI (0.34, 0.95), P = 0.03], shorter postoperative drainage time [MD = - 0.72, 95%CI (- 1.13, - 0.32), P = 0.0004], and shorter postoperative hospital stay [MD = - 0.90, 95%CI (- 1.16, - 0.65), P < 0.001], in comparison with the VATS group. There was an insignificant difference between the two groups in terms of tumor size [MD = - 0.02, 95%CI (- 0.33, 0.30), P = 0.91] and operation time [MD = 0.17, 95%CI (- 7.61, 7.94), P = 0.97]. However, in regards to hospitalization costs [MD = 2634.75, 95%CI (991.62, 4277.88), P = 0.002], the RATS group was more expensive than the VATS group. CONCLUSION: Robot-assisted mediastinal tumor resection surgery has more advantages in terms of intraoperative bleeding, conversion to thoracotomy rate, total postoperative complication rate, postoperative drainage time, and postoperative hospital stay, in comparison with thoracoscopic-assisted mediastinal tumor resection surgery. There is an insignificant difference in tumor size and operation time between the two surgeries. However, robot-assisted mediastinal tumor resection surgery increases hospitalization costs.

Development and Validation of a Computed Tomography-Based Model for Noninvasive Prediction of the T Stage in Gastric Cancer: Multicenter Retrospective Study.

BACKGROUND: As part of the TNM (tumor-node-metastasis) staging system, T staging based on tumor depth is crucial for developing treatment plans. Previous studies have constructed a deep learning model based on computed tomographic (CT) radiomic signatures to predict the number of lymph node metastases and survival in patients with resected gastric cancer (GC). However, few studies have reported the combination of deep learning and radiomics in predicting T staging in GC. OBJECTIVE: This study aimed to develop a CT-based model for automatic prediction of the T stage of GC via radiomics and deep learning. METHODS: A total of 771 GC patients from 3 centers were retrospectively enrolled and divided into training, validation, and testing cohorts. Patients with GC were classified into mild (stage T1 and T2), moderate (stage T3), and severe (stage T4) groups. Three predictive models based on the labeled CT images were constructed using the radiomics features (radiomics model), deep features (deep learning model), and a combination of both (hybrid model). RESULTS: The overall classification accuracy of the radiomics model was 64.3% in the internal testing data set. The deep learning model and hybrid model showed better performance than the radiomics model, with overall classification accuracies of 75.7% (P=.04) and 81.4% (P=.001), respectively. On the subtasks of binary classification of tumor severity, the areas under the curve of the radiomics, deep learning, and hybrid models were 0.875, 0.866, and 0.886 in the internal testing data set and 0.820, 0.818, and 0.972 in the external testing data set, respectively, for differentiating mild (stage T1~T2) from nonmild (stage T3~T4) patients, and were 0.815, 0.892, and 0.894 in the internal testing data set and 0.685, 0.808, and 0.897 in the external testing data set, respectively, for differentiating nonsevere (stage T1~T3) from severe (stage T4) patients. CONCLUSIONS: The hybrid model integrating radiomics features and deep features showed favorable performance in diagnosing the pathological stage of GC.

Potential toxicity of microplastics on vertebrate liver: A systematic review and meta-analysis.

Microplastics (MPs) pollution is emerging as a significant environmental concern, threatening human and animal health. Liver, as an important organ, plays an important role in the metabolism and detoxification of pollutants. Many studies have suggested that the liver is a potential target organ for MPs. However, the extent and consequences of the impacts of MPs on the liver reported in studies remain inconsistent. We categorized vertebrates into fish, mammals, and birds and performed a meta-analysis to comprehensively examine the effects of MPs on the liver. Hedges' g values were calculated to evaluate effect sizes. To further explore the sources of heterogeneity among the studies, we conducted subgroup analyses focusing on life stage, MPs type, MPs size, and exposure duration. Additionally, we normalized the MPs concentrations and conducted meta-regression analyses to explore the relationship between MPs concentrations and their hepatotoxic effects. A total of 118 studies were included in this meta-analysis. By quantifying 19 indicators, the results showed that MPs could damage the liver by altering liver morphology, inducing oxidative stress, producing intracellular toxicity, altering biotransformation processes, and disturbing lipid metabolism. Intracellular toxicity, followed by oxidative stress, had the greatest impact. Organisms are more sensitive to MPs under the following conditions: longer exposure duration, smaller MPs sizes, and earlier life stages. As the concentration of MPs increases, the levels of several liver indicators, including catalase, glutathione S-transferase, reactive oxygen species, and alkaline phosphatase, progressively increase. This study provides a comprehensive understanding of the effects of MPs on the liver and suggests the underlying mechanisms of MPs hepatotoxicity.

Recent Progress in Photothermal, Photodynamic and Sonodynamic Cancer Therapy: Through the cGAS-STING Pathway to Efficacy-Enhancing Strategies.

Photothermal, photodynamic and sonodynamic cancer therapies offer opportunities for precise tumor ablation and reduce side effects. The cyclic guanylate adenylate synthase-stimulator of interferon genes (cGAS-STING) pathway has been considered a potential target to stimulate the immune system in patients and achieve a sustained immune response. Combining photothermal, photodynamic and sonodynamic therapies with cGAS-STING agonists represents a newly developed cancer treatment demonstrating noticeable innovation in its impact on the immune system. Recent reviews have concentrated on diverse materials and their function in cancer therapy. In this review, we focus on the molecular mechanism of photothermal, photodynamic and sonodynamic cancer therapies and the connected role of cGAS-STING agonists in treating cancer.

CCE and EODF as two distinct non-shivering thermogenesis models inducing weight loss.

Increasing energy expenditure and reducing energy intake are considered two classical methods to induce weight loss. Weight loss through physical methods instead of drugs has been a popular research topic nowadays, but how these methods function in adipose and cause weight loss in body remains unclear. In this study, we set up chronic cold exposure (CCE) and every-other-day fasting (EODF) as two distinct models in long-term treatment to induce weight loss, recording their own characteristics in changes of body temperature and metabolism. We investigated the different types of non-shivering thermogenesis induced by CCE and EODF in white and brown adipose tissue through sympathetic nervous system (SNS), creatine-driven pathway, and fibroblast growth factor 21 (FGF21)-adiponectin axis. CCE and EODF could reduce body weight, lipid composition, increase insulin sensitivity, promote the browning of white fat, and increase the expression of endogenous FGF21 in adipose tissue. CCE stimulated the SNS and increased the thermogenic function of brown fat, and EODF increased the activity of protein kinase in white fat. In this study, we further explained the thermogenic mechanism function in adipose and metabolic benefits of the stable phenotype through physical treatments used for weight loss, providing more details for the literature on weight loss models. The influence on metabolism, non-shivering thermogenesis, endogenous FGF21, and ADPN changes in the long-term treatment of distinct methods (increasing energy expenditure and decreasing energy intake) to induce weight loss.

Key Roles of Interfacial OH- ion Distribution on Proton Coupled Electron Transfer Kinetics Toward Urea Oxidation Reaction.

Enhancing alkaline urea oxidation reaction (UOR) activity is essential to upgrade renewable electrolysis systems. As a core step of UOR, proton-coupled electron transfer (PCET) determines the overall performance, and accelerating its kinetic remains a challenge. In this work, a newly raised electrocatalyst of NiCoMoCuOx Hy with derived multi-metal co-doping (oxy)hydroxide species during electrochemical oxidation states is reported, which ensures considerable alkaline UOR activity (10/500 mA cm-2 at 1.32/1.52 V vs RHE, respectively). Impressively, comprehensive studies elucidate the correlation between the electrode-electrolyte interfacial microenvironment and the electrocatalytic urea oxidation behavior. Specifically, NiCoMoCuOx Hy featured with dendritic nanostructure creates a strengthened electric field distribution. This structural factor prompts the local OH- enrichment in electrical double layer (EDL), so that the dehydrogenative oxidation of the catalyst is directly reinforced to facilitate the subsequent PCET kinetics of nucleophilic urea, resulting in high UOR performance. In practical utilization, NiCoMoCuOx Hy -driven UOR coupled cathodic hydrogen evolution reaction (HER) and carbon dioxide reduction reaction (CO2 RR), and harvested high value-added products of H2 and C2 H4 , respectively. This work clarifies a novel mechanism to improve electrocatalytic UOR performance through structure-induced interfacial microenvironment modulation.

Manual correction of genome annotation improved alternative splicing identification of Artemisia annua.

Gene annotation is essential for genome-based studies. However, algorithm-based genome annotation is difficult to fully and correctly reveal genomic information, especially for species with complex genomes. Artemisia annua L. is the only commercial resource of artemisinin production though the content of artemisinin is still to be improved. Genome-based genetic modification and breeding are useful strategies to boost artemisinin content and therefore, ensure the supply of artemisinin and reduce costs, but better gene annotation is urgently needed. In this study, we manually corrected the newly released genome annotation of A. annua using second- and third-generation transcriptome data. We found that incorrect gene information may lead to differences in structural, functional, and expression levels compared to the original expectations. We also identified alternative splicing events and found that genome annotation information impacted identifying alternative splicing genes. We further demonstrated that genome annotation information and alternative splicing could affect gene expression estimation and gene function prediction. Finally, we provided a valuable version of A. annua genome annotation and demonstrated the importance of gene annotation in future research.

Comparison of MRI and CT-Based Radiomics and Their Combination for Early Identification of Pathological Response to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer.

BACKGROUND: Current radiomics for treatment response assessment in gastric cancer (GC) have focused solely on Computed tomography (CT). The importance of multi-parametric magnetic resonance imaging (mp-MRI) radiomics in GC is less clear. PURPOSE: To compare and combine CT and mp-MRI radiomics for pretreatment identification of pathological response to neoadjuvant chemotherapy in GC. STUDY TYPE: Retrospective. POPULATION: Two hundred twenty-five GC patients were recruited and split into training (157) and validation dataset (68) in the ratio of 7:3 randomly. FIELD/SEQUENCE: T2-weighted fast spin echo (fat suppressed T2-weighted imaging [fs-T2WI]), diffusion weighted echo planar imaging (DWI), and fast gradient echo (dynamic contrast enhanced [DCE]) sequences at 3.0T. ASSESSMENT: Apparent diffusion coefficient (ADC) maps were generated from DWI. CT, fs-T2WI, ADC, DCE, and mp-MRI Radiomics score (Radscores) were compared between responders and non-responders. A multimodal nomogram combining CT and mp-MRI Radscores was developed. Patients were followed up for 3-65 months (median 19) after surgery, the overall survival (OS) and progression free survival (PFS) were calculated. STATISTICAL TESTS: A logistic regression classifier was applied to construct the five models. Each model's performance was evaluated using a receiver operating characteristic curve. The association of the nomogram with OS/PFS was evaluated by Kaplan-Meier survival analysis and C-index. A P value <0.05 was considered statistically significant. RESULTS: CT Radscore, mp-MRI Radscore and nomogram were significantly associated with tumor regression grading. The nomogram achieved the highest area under the curves (AUCs) of 0.893 (0.834-0.937) and 0.871 (0.767-0.940) in training and validation datasets, respectively. The C-index was 0.589 for OS and 0.601 for PFS. The AUCs of the mp-MRI model were not significantly different to that of the CT model in training (0.831 vs. 0.770, P = 0.267) and validation dataset (0.797 vs. 0.746, P = 0.137). DATA CONCLUSIONS: mp-MRI radiomics provides similar results to CT radiomics for early identification of pathologic response to neoadjuvant chemotherapy. The multimodal radiomics nomogram further improved the capability. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: 2.

Analysis of Cytological Misdiagnosis and Oversight of Adenoid Cystic Carcinoma of Salivary Gland.

OBJECTIVE: In this article on adenoid cystic carcinoma (ACC) of salivary gland, we intend to summarize the causes of misdiagnosis and oversight of ACC hoping to improve cytological diagnostic accuracy, clinical management and patient treatment. METHODS: The study retrospectively reviewed 32 patients with ACC of salivary gland, registered at the Affiliated Hospital of Southwest Medical University from July 2014 to June 2021. These cases were diagnosed by FNA and surgical excision biopsy. All cytopathological results were retrospectively categorized according to Milan system for reporting salivary gland cytopathology (MSRSGC). The accuracy of FNA was verified by surgical excision biopsy. RESULTS: Of these 32 patients, 16 (50.0%) cases were male, and 16 (50.0%) were female. Their age ranged from 21 to 79 years, with an average age of 50.32 years. The highest incidence (15/32, 46.9%) of ACC was observed in patients between 41 and 50 years of age. 10 cases (31.3%) occurred in the parotid gland, 9 cases (28.1%) in the submandibular gland, 9 cases (28.1%) in the sublingual gland, 3 cases (9.4%) in the palate, and 1 case (3.1%) in the lip. Among the 32 cases of ACC, 23 cases (71.9%) were classified to VI, 4 cases (12.5%) to IVa, and 5 cases (15.6%) to II by MSRSGC. A comparison of the FNA results with biopsy showed that the accuracy of FNA in ACC of salivary gland is 71.9%. Being able to identify the cytomorphological features is the key factor for accurate diagnosis of ACC of the salivary gland. CONCLUSION: Our results confirm that FNA is an important initial screening in the diagnosis of ACC of salivary gland. Increased study of the cytomorphology of ACC is beneficial for more accurate diagnosis of ACC, to reduce misdiagnosis and oversight.

EpiHNet: Detecting epistasis by heterogeneous molecule network.

Epistasis between single nucleotide polymorphisms (SNPs) plays an important role in elucidating the missing heritability of complex diseases. Diverse approaches have been invented for detecting SNP interactions, but they canonically neglect the important and useful connections between SNPs and other bio-molecules (i.e., miRNAs and lncRNAs). To comprehensively model these disease related molecules, a heterogeneous bio-molecular network based solution EpiHNet is introduced for high-order SNP interactions detection. EpiHNet firstly uses case/control data to construct an SNP statistical network, and meta-path based similarity on the heterogeneous network composed with SNPs, genes, lncRNAs, miRNAs and diseases to define another SNP relational network. The SNP relational network can explore and exploit different associations between molecules and diseases to complement the SNP statistical network and search the significantly associated SNPs. Next, EpiHNet integrates these two networks into a composite network, applies the modularity based clustering with fast search strategy to divide SNP nodes into different clusters. After that, it detects SNP interactions based on SNP combinations derived from each cluster. Synthetic experiments on diverse two-locus and three-locus disease models manifest that EpiHNet outperforms competitive baselines, even without the heterogeneous network. For real WTCCC breast cancer data, EpiHNet also demonstrates expressive results on detecting high-order SNP interactions.

Genetic characteristics and pathogenicity of avian pox virus for a new host, Cherry Valley breeder ducks in China.

Cherry Valley breeder ducks in Shandong province in northern China have experienced swollen eyes, lachrymation, pox scabs on glabrous or glabrous skin, depression and dysentery since 2021. The spread of this infectious disease has seriously affected the breeder ducks in major Cherry Valley duck farms in China. The virus causing clinical signs in Cherry Valley breeder ducks was isolated by chicken embryo inoculation. We successfully isolated a strain of duck pox virus from diseased breeder ducks by virus replication. We have also successfully conducted experiments for duck pox disease using the isolated strains to infect ducklings. By comparison with 22 pox viruses already published in GenBank, the virus strain obtained in this study was most homologous (about 99.7%) to the strain isolated from infected domestic ducks in Guangxi, China in 2014 (KJ192189), and belonged to the same A5 subtype. Since there were no previous cases of avian pox virus infecting white or Cherry Valley duck breeds, this study identified a new host for avian pox virus infection and provided theoretical support and data for the development of avian pox virus research.RESEARCH HIGHLIGHTS Avian pox virus can infect a new host type - Cherry Valley breeder ducks.The avian pox virus isolated from Cherry Valley breeder ducks showed highest identity with Guangxi hemp duck-derived avian pox virus.Cherry Valley breeder ducks were infected with avian pox virus of subtype A5.

DeepBindBC: A practical deep learning method for identifying native-like protein-ligand complexes in virtual screening.

Identifying native-like protein-ligand complexes (PLCs) from an abundance of docking decoys is critical for large-scale virtual drug screening in early-stage drug discovery lead searching efforts. Providing reliable prediction is still a challenge for most current affinity predicting models because of a lack of non-binding data during model training, lost critical physical-chemical features, and difficulties in learning abstract information with limited neural layers. In this work, we proposed a deep learning model, DeepBindBC, for classifying putative ligands as binding or non-binding. Our model incorporates information on non-binding interactions, making it more suitable for real applications. ResNet model architecture and more detailed atom type representation guarantee implicit features can be learned more accurately. Here, we show that DeepBindBC outperforms Autodock Vina, Pafnucy, and DLSCORE for three DUD.E testing sets. Moreover, DeepBindBC identified a novel human pancreatic α-amylase binder validated by a fluorescence spectral experiment (Ka = 1.0 × 105 M). Furthermore, DeepBindBC can be used as a core component of a hybrid virtual screening pipeline that incorporating many other complementary methods, such as DFCNN, Autodock Vina docking, and pocket molecular dynamics simulation. Additionally, an online web server based on the model is available at http://cbblab.siat.ac.cn/DeepBindBC/index.php for the user's convenience. Our model and the web server provide alternative tools in the early steps of drug discovery by providing accurate identification of native-like PLCs.

Giant cell tumor of tendon sheath: A report of 216 cases.

BACKGROUND: In this article on giant cell tumor of tendon sheath (GCTTS), we intend to summarize and analyze the clinical and pathological features of GCTTS hoping to improve clinical management and patient treatment. METHODS: The study retrospectively reviewed 216 patients of GCTTS, registered at the Affiliated Hospital of Southwest Medical University from January 2010 to December 2020. These cases were diagnosed by surgical excision. The clinicopathological features and the prognosis were reviewed in the light of the current literature. RESULTS: Of these 216 GCTTS patients, 72 were males (33.3%) and 144 females (66.7%), with a ratio male-to-female of 1:2. The patients' age ranged from 5 to 82, the average being 41.5 years at diagnosis. A total of 96 cases (44.4%) occurred in the hand region, followed by 35 cases (16.2%) in the knee, 32 cases (14.8%) in the foot, 25 cases (11.6%) in the ankle, 12 cases (5.6%) in the wrist, 12 cases (5.6%) in the leg, 2 cases (0.9%) in the head, 1 case (0.5%) in the forearm, and 1 case (0.5%) inside and outside the spinal channel. Histopathology mainly revealed large synovial-like monocytes, small monocytes, and osteoclast-like giant cells. CONCLUSION: Our results confirm that GCTTS predominantly occurs in the hands of young women. Complete surgical resection with long-term follow-up is the preferred management.