A comprehensive AI model development framework for consistent Gleason grading.

BACKGROUND: Artificial Intelligence(AI)-based solutions for Gleason grading hold promise for pathologists, while image quality inconsistency, continuous data integration needs, and limited generalizability hinder their adoption and scalability. METHODS: We present a comprehensive digital pathology workflow for AI-assisted Gleason grading. It incorporates A!MagQC (image quality control), A!HistoClouds (cloud-based annotation), Pathologist-AI Interaction (PAI) for continuous model improvement, Trained on Akoya-scanned images only, the model utilizes color augmentation and image appearance migration to address scanner variations. We evaluate it on Whole Slide Images (WSI) from another five scanners and conduct validations with pathologists to assess AI efficacy and PAI. RESULTS: Our model achieves an average F1 score of 0.80 on annotations and 0.71 Quadratic Weighted Kappa on WSIs for Akoya-scanned images. Applying our generalization solution increases the average F1 score for Gleason pattern detection from 0.73 to 0.88 on images from other scanners. The model accelerates Gleason scoring time by 43% while maintaining accuracy. Additionally, PAI improve annotation efficiency by 2.5 times and led to further improvements in model performance. CONCLUSIONS: This pipeline represents a notable advancement in AI-assisted Gleason grading for improved consistency, accuracy, and efficiency. Unlike previous methods limited by scanner specificity, our model achieves outstanding performance across diverse scanners. This improvement paves the way for its seamless integration into clinical workflows.

Gleason grading is a well-accepted diagnostic standard to assess the severity of prostate cancer in patients' tissue samples, based on how abnormal the cells in their prostate tumor look under a microscope. This process can be complex and time-consuming. We explore how artificial intelligence (AI) can help pathologists perform Gleason grading more efficiently and consistently. We build an AI-based system which automatically checks image quality, standardizes the appearance of images from different equipment, learns from pathologists' feedback, and constantly improves model performance. Testing shows that our approach achieves consistent results across different equipment and improves efficiency of the grading process. With further testing and implementation in the clinic, our approach could potentially improve prostate cancer diagnosis and management.

Medical image foundation models in assisting diagnosis of brain tumors: a pilot study.

OBJECTIVES: To build self-supervised foundation models for multicontrast MRI of the whole brain and evaluate their efficacy in assisting diagnosis of brain tumors. METHODS: In this retrospective study, foundation models were developed using 57,621 enhanced head MRI scans through self-supervised learning with a pretext task of cross-contrast context restoration with two different content dropout schemes. Downstream classifiers were constructed based on the pretrained foundation models and fine-tuned for brain tumor detection, discrimination, and molecular status prediction. Metrics including accuracy, sensitivity, specificity, and area under the ROC curve (AUC) were used to evaluate the performance. Convolutional neural networks trained exclusively on downstream task data were employed for comparative analysis. RESULTS: The pretrained foundation models demonstrated their ability to extract effective representations from multicontrast whole-brain volumes. The best classifiers, endowed with pretrained weights, showed remarkable performance with accuracies of 94.9, 92.3, and 80.4%, and corresponding AUC values of 0.981, 0.972, and 0.852 on independent test datasets in brain tumor detection, discrimination, and molecular status prediction, respectively. The classifiers with pretrained weights outperformed the convolutional classifiers trained from scratch by approximately 10% in terms of accuracy and AUC across all tasks. The saliency regions in the correctly predicted cases are mainly clustered around the tumors. Classifiers derived from the two dropout schemes differed significantly only in the detection of brain tumors. CONCLUSIONS: Foundation models obtained from self-supervised learning have demonstrated encouraging potential for scalability and interpretability in downstream brain tumor-related tasks and hold promise for extension to neurological diseases with diffusely distributed lesions. CLINICAL RELEVANCE STATEMENT: The application of our proposed method to the prediction of key molecular status in gliomas is expected to improve treatment planning and patient outcomes. Additionally, the foundation model we developed could serve as a cornerstone for advancing AI applications in the diagnosis of brain-related diseases.

Impact of duck astrovirus on susceptibility to infection across duck ages.

An outbreak of duck astrovirus (DAstV) has occurred in duck farming regions of China, causing substantial economic setbacks in the duck industry. This investigation aimed to examine the variations in DAstV pathogenicity among ducks at different age intervals. Infections were induced in ducks at distinct age groups (1, 7, 14, 21, and 28 d) utilizing the DAstv-1-GDB-2022 strain. The results indicate increased pathogenicity of the DAstv-1-GDB-2022 strain in ducklings aged 21 to 28 d, manifesting as liver and kidney enlargement, severe bleeding, and potential fatalities. Conversely, ducklings aged 1 and 14 d displayed milder symptoms postinfection. Notably, viral shedding continued in ducks of diverse age groups even 21 d postinfection (Dpi). Moreover, DAstV replicates in various tissues, predominantly affecting the liver. Immunohistochemical tests using rabbit anti-DAstV antibodies revealed robust positive signals in both the liver and kidneys, which correlated with the clinical symptom severity observed through macroscopic and microscopic examinations. Serum biochemical assays and indirect ELISA demonstrated a consistent response to DAstV infection across different age groups, with older ducklings exhibiting increased sensitivity. In conclusion, this study successfully replicated clinical symptoms similar to those of natural DAstV infection using the DAstv-1-GDB-2022 strain. Importantly, we systematically delineated the differences in susceptibility to DAstV among ducks at various ages, laying the foundation for further research into the pathogenic mechanisms of DAstV and potential vaccine development.

Stromal-derived MAOB promotes prostate cancer growth and progression.

Prostate cancer (PC) develops in a microenvironment where the stromal cells modulate adjacent tumor growth and progression. Here, we demonstrated elevated levels of monoamine oxidase B (MAOB), a mitochondrial enzyme that degrades biogenic and dietary monoamines, in human PC stroma, which was associated with poor clinical outcomes of PC patients. Knockdown or overexpression of MAOB in human prostate stromal fibroblasts indicated that MAOB promotes cocultured PC cell proliferation, migration, and invasion and co-inoculated prostate tumor growth in mice. Mechanistically, MAOB induces a reactive stroma with activated marker expression, increased extracellular matrix remodeling, and acquisition of a protumorigenic phenotype through enhanced production of reactive oxygen species. Moreover, MAOB transcriptionally activates CXCL12 through Twist1 synergizing with TGFß1-dependent Smads in prostate stroma, which stimulates tumor-expressed CXCR4-Src/JNK signaling in a paracrine manner. Pharmacological inhibition of stromal MAOB restricted PC xenograft growth in mice. Collectively, these findings characterize the contribution of MAOB to PC and suggest MAOB as a potential stroma-based therapeutic target.

A novel bivalent inactivated vaccine for ducks against Riemerella anatipestifer based on serotype distribution in southern China.

Riemerella anatipestifer (RA) causes epizootic infectious polyserositis in ducks with high mortality and leads to huge economic losses worldwide. Bacterial resistance poses a challenge for the control of the disease, vaccines failed to provide ideal cross-protection. Thus, the preparation of vaccines based on popular serotypes is important. In this study, we collected 700 brain and liver tissues of dead ducks from 8 provinces in southern China from 2016 to 2022 and obtained 195 RA isolates with serotypes 1, 2, 7, and 10. Serotypes 1 and 2 were the most prevalent (82%). A novel bivalent inactivated vaccine WZX-XT5 containing propolis adjuvant was prepared, we chose XT5 (serotype 1) and WZX (serotype 2) as vaccine strains and evaluated WZX-XT5-induced immune response and protective efficacy in ducks. Results showed that the XT5 (LD50, 3.5 × 103 CFU) exhibited high virulence and provided better protection against RA compared with ZXP, DCR and LCF1 (LD50, 108 CFU). Notably, the dose of 109 CFU provided ideal protection compared with 108 CFU, propolis and oil emulsion adjuvants induced stronger protective efficacy compared with aluminum hydroxide adjuvant. Importantly, WZX-XT5 immunization induced high levels of RA-specific IgY, IFN-γ, IL-2, and IL-4 in serum and offered over 90% protection against RA with ultra-high lethal dose in ducks. Additionally, no clinical signs of RA infection or obvious pathological damage in tissues were observed in protected ducks. Overall, this study first reports the identification, serotyping and virulence of RA in ducks of southern China and the preparation of a novel bivalent inactivated vaccine, providing useful scientific information to prevent and control RA infection.

Chromosome-level genome of Ambrosia trifida provides insights into adaptation and the evolution of pollen allergens.

Ambrosia trifida (giant ragweed) is an invasive plant that can cause serious damage to natural ecosystems and severe respiratory allergies. However, the genomic basis of invasive adaptation and pollen allergens in Ambrosia species remain largely unknown. Here, we present a 1.66 Gb chromosome-scale reference genome for giant ragweed and identified multiple types of genome duplications, which are responsible for its rapid environmental adaptation and pollen development. The largest copies number and species-specific expansions of resistance-related gene families compared to Heliantheae alliance might contribute to resist stresses, pathogens and rapid adaptation. To extend the knowledge of evolutionary process of allergic pollen proteins, we predicted 26 and 168 potential pollen allergen candidates for giant ragweed and other Asteraceae plant species by combining machine learning and identity screening. Interestingly, we observed a specific tandemly repeated array for potential allergenic pectate lyases among Ambrosia species. Rapid evolutionary rates on putative pectate lyase allergens may imply a crucial role of nonsynonymous mutations on amino acid residues for plant biological function and allergenicity. Altogether, this study provides insight into the molecular ecological adaptation and putative pollen allergens prediction that will be helpful in promoting invasion genomic research and evolution of putative pollen allergy in giant ragweed.

Neutrophil heterogeneity and aging: implications for COVID-19 and wound healing.

Neutrophils play a critical role in the immune response to infection and tissue injury. However, recent studies have shown that neutrophils are a heterogeneous population with distinct subtypes that differ in their functional properties. Moreover, aging can alter neutrophil function and exacerbate immune dysregulation. In this review, we discuss the concept of neutrophil heterogeneity and how it may be affected by aging. We then examine the implications of neutrophil heterogeneity and aging for COVID-19 pathogenesis and wound healing. Specifically, we summarize the evidence for neutrophil involvement in COVID-19 and the potential mechanisms underlying neutrophil recruitment and activation in this disease. We also review the literature on the role of neutrophils in the wound healing process and how aging and neutrophil heterogeneity may impact wound healing outcomes. Finally, we discuss the potential for neutrophil-targeted therapies to improve clinical outcomes in COVID-19 and wound healing.

Mpox (formerly monkeypox): pathogenesis, prevention, and treatment.

In 2022, a global outbreak of Mpox (formerly monkeypox) occurred in various countries across Europe and America and rapidly spread to more than 100 countries and regions. The World Health Organization declared the outbreak to be a public health emergency of international concern due to the rapid spread of the Mpox virus. Consequently, nations intensified their efforts to explore treatment strategies aimed at combating the infection and its dissemination. Nevertheless, the available therapeutic options for Mpox virus infection remain limited. So far, only a few numbers of antiviral compounds have been approved by regulatory authorities. Given the high mutability of the Mpox virus, certain mutant strains have shown resistance to existing pharmaceutical interventions. This highlights the urgent need to develop novel antiviral drugs that can combat both drug resistance and the potential threat of bioterrorism. Currently, there is a lack of comprehensive literature on the pathophysiology and treatment of Mpox. To address this issue, we conducted a review covering the physiological and pathological processes of Mpox infection, summarizing the latest progress of anti-Mpox drugs. Our analysis encompasses approved drugs currently employed in clinical settings, as well as newly identified small-molecule compounds and antibody drugs displaying potential antiviral efficacy against Mpox. Furthermore, we have gained valuable insights from the process of Mpox drug development, including strategies for repurposing drugs, the discovery of drug targets driven by artificial intelligence, and preclinical drug development. The purpose of this review is to provide readers with a comprehensive overview of the current knowledge on Mpox.

Molecular characterization of chicken astrovirus and pathogenicity of a novel isolate in China.

As an enteric virus, chicken astrovirus has been related to various kinds of diseases in chickens, including white chick syndrome, runting-stunting syndrome, severe kidney disease, urate deposits and visceral gout, generating economic losses in the poultry industry globally. The complete ORF2 gene of 31 CAstV isolates in six provinces of China during 2020-2022 was characterized and analyzed with the purpose of better understanding the molecular epidemiology and genetic diversity of CAstV field isolates. Phylogenetic analysis which was based on the complete ORF2 (capsid) amino acid sequence of 31 CAstV isolates and 57 reference strains indicated that 2 isolates belonged to subgroup Ai, 10 isolates belonged to subgroup Bi, 3 isolates belonged to subgroup Bii, 5 isolates belonged to subgroup Biii, 7 isolates belonged to subgroup Biv, 3 isolates belonged to subgroup Bv, and one isolate (JS202103) belonged to a new B subgroup. In addition, the novel CAstV strain JS202103 was successfully isolated in vitro, and its whole genome shared 76.9-94.3% identity with the 29 CAstV reference strains. JS202103 caused hatchability reduction, dead embryos, kidney disease and visceral gout in chicken embryos. Moreover, this is the also the initial study focusing on diverse CAstV strains including subgroups Biii, Biv, and Bv circulate in China. The current work contributes to improving our understanding of CAstV isolates in China, and it will also provide references for developing efficient measures to control this virus.

The correlation between red cell distribution width to albumin ratio and all-cause mortality in critically ill patients with rheumatic diseases: a population-based retrospective study.

Background: Patients with rheumatic diseases have an increased likelihood of being admitted to the intensive care unit (ICU), highlighting the importance of promptly identifying high-risk individuals to enhance prognosis. This study aimed to assess the correlation of red blood cell distribution width to albumin ratio (RAR) with the 90-days and 360-days survival rates among critically ill rheumatic patients. Methods: Adult rheumatic patients admitted to the ICU from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were included. The participants were categorized into two groups, survivors (n = 436) and non-survivors (n = 192), based on their 90-days survival outcome. The population was further classified into tertiles using RAR values, with RAR < 4.63 (n = 208), 4.63-6.07 (n = 211), and > 6.07 (n = 209). Kaplan-Meier curves were utilized to evaluate the cumulative survival rates at 90-days and 360-days. The association between RAR and mortality was assessed using restricted cubic splines (RCS) and multivariate Cox regression analysis. Additional subgroup analyses and sensitivity analyses were conducted to further explore the findings. Receiver operating characteristic (ROC) curves were generated to evaluate the predictive performance of RAR. Results: This study involved 628 critically ill patients with rheumatic diseases, and they had an all-cause mortality of 30.57% at 90-days and 38.69% at 360-days. Kaplan-Meier analysis showed a gradual decrease in both 90-days and 360-days cumulative survival with increasing RAR (χ2 = 24.400, p < 0.001; χ2 = 35.360, p < 0.001). RCS revealed that RAR was linearly related to 90-days and 360-days all-cause mortality risk for critically ill patients with rheumatic diseases (χ2 = 4.360, p = 0.225; χ2 = 1.900, p = 0.594). Cox regression analysis indicated that elevated RAR (> 6.07) was significantly correlated with mortality. The ROC curves demonstrated that an optimal cut-off value of RAR for predicting 90-days mortality was determined to be 5.453, yielding a sensitivity of 61.5% and specificity of 60.3%. Conclusion: Elevated RAR (> 6.07) was associated with all-cause mortality at 90-days and 360-days among critically ill patients with rheumatic diseases, serving as an independent risk factor for unfavorable prognosis.

Assessing Motor Function in Frail Older Adults in Their Home Settings: Challenges, Strategies and Recommendations.

Assessing motor competence is essential for evaluating the effectiveness of physical activity interventions that aim to maintain or improve older adults' function. However, assessing motor competence in older adults who have difficulties walking or standing is challenging, because few instruments or guidelines are appropriate for these frail older adults. This article aims to describe challenges in evaluating motor function among frail older adults, discuss strategies for adapting motor function assessments to their home settings, and provide recommendations for future clinical trials so that older adults with ambulatory difficulties can benefit from motor function assessment and physical activity programs. Data came from the baseline assessment of 116 participants of an ongoing clinical trial, "Promoting Seniors' Health with Home Care Aides (Pro-Home)". Our results demonstrated that the Pro-Home study involved participants who would be typically excluded from clinical trials and that the two instruments selected or developed for Pro-Home (Short Physical Performance Battery, Pro-Home Ankle Range of Motion Measure) captured a wide range of lower extremity motor competence with no or few missing data. Recommendations for future studies include knowing the target population thoroughly, developing trust and rapport with all parties involved, and continuously collaborating with interviewers who conduct assessments.

A cisplatin conjugate with tumor cell specificity exhibits antitumor effects in renal cancer models.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer and is notorious for its resistance to both chemotherapy and small-molecule inhibitor targeted therapies. Subcellular targeted cancer therapy may thwart the resistance to produce a substantial effect. METHODS: We tested whether the resistance can be circumvented by subcellular targeted cancer therapy with DZ-CIS, which is a chemical conjugate of the tumor-cell specific heptamethine carbocyanine dye (HMCD) with cisplatin (CIS), a chemotherapeutic drug with limited use in ccRCC treatment because of frequent renal toxicity. RESULTS: DZ-CIS displayed cytocidal effects on Caki-1, 786-O, ACHN, and SN12C human ccRCC cell lines and mouse Renca cells in a dose-dependent manner and inhibited ACHN and Renca tumor formation in experimental mouse models. Noticeably, in tumor-bearing mice, repeated DZ-CIS use did not cause renal toxicity, in contrast to the CIS-treated control animals. In ccRCC tumors, DZ-CIS treatment inhibited proliferation markers but induced cell death marker levels. In addition, DZ-CIS at half maximal inhibitory concentration (IC50) sensitized Caki-1 cells to small-molecule mTOR inhibitors. Mechanistically, DZ-CIS selectively accumulated in ccRCC cells' subcellular organelles, where it damages the structure and function of mitochondria, leading to cytochrome C release, caspase activation, and apoptotic cancer cell death. CONCLUSIONS: Results from this study strongly suggest DZ-CIS be tested as a safe and effective subcellular targeted cancer therapy.

Glucocorticoids promote lung metastasis of pancreatic cancer cells through enhancing cell adhesion, migration and invasion.

Glucocorticoids (GCs) are the important stress hormones and widely prescribed as drugs. Although stress has been suggested as a promoter of tumor progression, the direct influence of GCs on metastasis of tumor is not fully understood. Metastasis is a major cause of death in pancreatic cancer patients. In the present study, we investigated the effect of GCs on progression of pancreatic cancer and elucidated the underlying mechanism. It was found that GCs significantly promote cell adhesion, migration, and invasion of pancreatic cancer cells in vitro and their lung metastasis in vivo. Further mechanistic studies showed that GCs notably up-regulate the expression of a trans-membrane glycoprotein, mucin 1 (MUC1) and increase the activation of AKT. Inhibiting MUC1 expression not only attenuates the activation of AKT, but also significantly reduces the promoting effects of GCs on cell adhesion, migration, invasion, and lung metastasis of pancreatic cancer cells. Moreover, GCs not only significantly up-regulate expression of Rho-associated kinase 1/2 (ROCK1/2) and matrix metalloproteinase 3 and 7 (MMP3/7), but also activate ROCK2, which are also involved in the pro-migratory and pro-invasive effects of GCs in pancreatic cancer cells. Taken together, our findings reveal that GCs promote metastasis of pancreatic cancer cells through complex mechanism. MUC1-PI3K/AKT pathway, ROCK1/2 and MMP3/7 are involved in the promoting effect of GCs on cell migration, invasion and metastasis in pancreatic cancer cells. These results suggest the importance of reducing stress and GCs administration in patients with pancreatic cancer to avoid an increased risk of cancer metastasis.

Artificial Intelligence Applications in Glioma With 1p/19q Co-Deletion: A Systematic Review.

As an important genomic marker for oligodendrogliomas, early determination of 1p/19q co-deletion status is critical for guiding therapy and predicting prognosis in patients with glioma. The purpose of this study is to systematically review the literature concerning the magnetic resonance imaging (MRI) with artificial intelligence (AI) methods for predicting 1p/19q co-deletion status in glioma. PubMed, Scopus, Embase, and IEEE Xplore were searched in accordance with the Preferred Reporting Items for systematic reviews and meta-analyses guidelines. Methodological quality of studies was assessed according to the Quality Assessment of Diagnostic Accuracy Studies-2. Finally, 28 studies were included in the quantitative analysis. Diagnostic test accuracy reached an area under the ROC curve of 0.71-0.98 were reported in 24 studies. The remaining four studies with no available AUC provided an accuracy of 0.75-0. 89. The included studies varied widely in terms of imaging sequences, input features, and modeling methods. The current review highlighted that integrating MRI with AI technology is a potential tool for determination 1p/19q status pre-operatively and noninvasively, which can possibly help clinical decision-making. However, the reliability and feasibility of this approach still need to be further validated and improved in a real clinical setting. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: 2.

Whole-transcriptome analyses identify key differentially expressed mRNAs, lncRNAs, and miRNAs associated with male sterility in watermelon.

Male sterility is a valuable trait for watermelon breeding, as watermelon hybrids exhibit obvious heterosis. However, the underlying regulatory mechanism is still largely unknown, especially regarding the related non-coding genes. In the present study, approximately 1035 differentially expressed genes (DEGs), as well as 80 DE-lncRNAs and 10 DE-miRNAs, were identified, with the overwhelming majority down-regulated in male-sterile floral buds. Enrichment analyses revealed that the general phenylpropanoid pathway as well as its related metabolisms was predicted to be altered in a mutant compared to its fertile progenitor. Meanwhile, the conserved genetic pathway DYT1-TDF1-AMS-MS188-MS1, as well as the causal gene ClAMT1 for the male-sterile mutant Se18, was substantially disrupted during male reproductive development. In addition, some targets of the key regulators AMS and MS188 in tapetum development were also down-regulated at a transcriptional level, such as ABCG26 (Cla004479), ACOS5 (Cla022956), CYP703A2 (Cla021151), PKSA (Cla021099), and TKPR1 (Cla002563). Considering lncRNAs may act as functional endogenous target mimics of miRNAs, competitive endogenous RNA networks were subsequently constructed, with the most complex one containing three DE-miRNAs, two DE-lncRNAs, and 21 DEGs. Collectively, these findings not only contribute to a better understanding of genetic regulatory networks underlying male sterility in watermelon, but also provide valuable candidates for future research.

A SERS-signalled, CRISPR/Cas-powered bioassay for amplification-free and anti-interference detection of SARS-CoV-2 in foods and environmental samples using a single tube-in-tube vessel.

The pandemic of COVID-19 creates an imperative need for sensitive and portable detection of SARS-CoV-2. We devised a SERS-read, CRISPR/Cas-powered nanobioassay, termed as OVER-SARS-CoV-2 (One-Vessel Enhanced RNA test on SARS-CoV-2), which enabled supersensitive, ultrafast, accurate and portable detection of SARS-CoV-2 in a single vessel in an amplification-free and anti-interference manner. The SERS nanoprobes were constructed by conjugating gold nanoparticles with Raman reporting molecular and single-stranded DNA (ssDNA) probes, whose aggregation-to-dispersion changes can be finely tuned by target-activated Cas12a though trans-cleavage of linker ssDNA. As such, the nucleic acid signals could be dexterously converted and amplified to SERS signals. By customizing an ingenious vessel, the steps of RNA reverse transcription, Cas12a trans-cleavage and SERS nanoprobes crosslinking can be integrated into a single and disposal vessel. It was proved that our proposed nanobioassay was able to detect SARS-CoV-2 as low as 200 copies/mL without any pre-amplification within 45 min. In addition, the proposed nanobioassay was confirmed by clinical swab samples and challenged for SARS-CoV-2 detection in simulated complex environmental and food samples. This work enriches the arsenal of CRISPR-based diagnostics (CRISPR-Dx) and provides a novel and robust platform for SARS-CoV-2 decentralized detection, which can be put into practice in the near future.

Isolation, identification, and pathogenicity analysis of newly emerging gosling astrovirus in South China.

Goose astroviruses (GoAstV) cause fatal gout and decrease product performance in the waterfowl industry across the world. Since no effective vaccines are available, studies on the epidemiology of the virus are necessary for vaccine development. In this study, we collected 94 gout samples from goose farms in the Guangdong Province of South China. Among them, 87 samples (92.6%) tested positive for GoAstV, out of which five GoAstV strains were isolated after four generations of blind transmission through healthy 13-day-old goose embryos. The whole genome of the isolates was sequenced and further analyzed by comparing the sequences with published sequences from China and other parts of the world. The results of the alignment analysis showed that nucleotide sequence similarities among the five GoAstV isolates were around 97.4-98.8%, 98.6-100%, 98.1-99.8%, and 96.7-100% for the whole genome, ORF1a, ORF1b, and ORF2, respectively. These results showed that the GoAstV isolates were highly similar to each other, although they were prevalent in five different regions of the Guangdong Province. The results of the phylogenetic analysis showed that the whole genome, along with the ORF1a, ORF1b, and ORF2 genes of the isolates, were clustered on a single branch, along with the recently published GoAstV-2, and were very distinct from the DNA sequences of the GoAstV-1 virus. In this study, we also reproduced the clinical symptoms of natural infection using the GoAstV-GD2101 isolates, confirming that the gout-causing pathogen in goslings was the goose astrovirus. These findings provided new insights into the pathogenicity and genetic evolution of GoAstV and laid the foundation for effectively controlling the disease.

NTRK-rearranged spindle cell neoplasms: a clinicopathological and molecular study of 13 cases with peculiar characteristics at one of the largest institutions in China.

NTRK-rearranged spindle cell neoplasms (NTRK-RSCNs) represent an emerging group of rare tumours defined using molecular means. To the best of our knowledge, there have been no large series of reports about this tumour in the Chinese population in English full-text articles. Herein, we present 13 NTRK-RSCNs with peculiar characteristics. Ten of the 13 (77%) patients were children without sex differences. The tumour locations included six trunks, four extremities, two recta, and one small bowel. The histological morphology included four lipofibromatosis-like neural tumour (LPF-NT)-like, eight malignant peripheral nerve sheath tumours (MPNST)/fibrosarcoma-like, and one extremely rare myxofibrosarcoma-like pattern. Immunohistochemically, all cases were CD34, pan-TRK and TRK-A positive, SOX-10 negative, and H3K27me3 intact. S-100 protein expression was identified in 11 of 13 (85%) cases. Genetically, NTRK1 rearrangements were considered positive (7/13, 54%) or suspicious for positivity (6/13, 46%) by fluorescence in situ hybridisation. Next-generation sequencing and Sanger sequencing confirmed NTRK1 fusions with a variety of partner genes, including five LMNA, three TPM3, one SQSTM1, three novel CPSF6, IGR (downstream PMVK), and GAS2L1 genes. Interestingly, the last tumour concurrently harboured a second EWSR1-PBX1 fusion, which has never been reported. Four patients developed local recurrence and two of them suffered metastasis. In our study, NTRK-RSCNs had peculiar fusions that displayed unusual or complicated clinicopathological features. Histological clues and IHC helped streamline a small subset of potential candidates. Although FISH is a powerful technology for identifying NTRK rearrangements, RNA-/DNA-based NGS is recommended for highly suspected cases in which FISH signal patterns are not discernible as classic positive patterns, particularly if targeted therapy is considered.

Uncovering potential diagnostic biomarkers of acute myocardial infarction based on machine learning and analyzing its relationship with immune cells.

BACKGROUND: Acute myocardial infarction (AMI) is a common cardiovascular disease. This study aimed to mine biomarkers associated with AMI to aid in clinical diagnosis and management. METHODS: All mRNA and miRNA data were downloaded from public database. Differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNAs (DEmiRNAs) were identified using the metaMA and limma packages, respectively. Functional analysis of the DEmRNAs was performed. In order to explore the relationship between miRNA and mRNA, we construct miRNA-mRNA negative regulatory network. Potential biomarkers were identified based on machine learning. Subsequently, ROC and immune correlation analysis were performed on the identified key DEmRNA biomarkers. RESULTS: According to the false discovery rate < 0.05, 92 DEmRNAs and 272 DEmiRNAs were identified. GSEA analysis found that kegg_peroxisome was up-regulated in AMI and kegg_steroid_hormone_biosynthesis was down-regulated in AMI compared to normal controls. 5 key DEmRNA biomarkers were identified based on machine learning, and classification diagnostic models were constructed. The random forests (RF) model has the highest accuracy. This indicates that RF model has high diagnostic value and may contribute to the early diagnosis of AMI. ROC analysis found that the area under curve of 5 key DEmRNA biomarkers were all greater than 0.7. Pearson correlation analysis showed that 5 key DEmRNA biomarkers were correlated with most of the differential infiltrating immune cells. CONCLUSION: The identification of new molecular biomarkers provides potential research directions for exploring the molecular mechanism of AMI. Furthermore, it is important to explore new diagnostic genetic biomarkers for the diagnosis and treatment of AMI.

Detection Methods for Foodborne Viruses: Current State-of-Art and Future Perspectives.

Foodborne viruses have been recognized as important threats to food safety and human health. Rapid and accurate detection is one of the most crucial measures for food safety control. With the development of biology, chemistry, nanoscience, and related interdisciplines, detection strategies have been devised and advanced continuously. This review mainly focuses on the progress of detection methods for foodborne viruses. The current detection methods for foodborne viruses are summarized, including traditional electron microscopy and cultural isolation, immunoassay, molecular technology, biosensors, and newly emerging CRISPR/Cas-based detection technology. Furthermore, a comparison of the detection methods was objectively discussed. This review provides a comprehensive account of foodborne virus detection methods from fundamentals to state-of-the-art and illustrates the advantages and disadvantages of the current methods and proposes the future trends and directions for foodborne virus detection. It is hoped that this review can update current knowledge and present blueprints in order to accelerate futuristic development.