Genetic and pathogenic characteristics of a novel recombinant GI-19 infectious bronchitis virus strain isolated from northeastern China.

Since the 1980s, despite vaccination, the infectious bronchitis virus (IBV) infection rate in commercial broilers and layers in China has continued to rise significantly, causing substantial economic losses to the poultry industry. In this study, an IBV strain was isolated from a layer farm in northeast China and named CK/CH/LN/2302. The whole genome sequence analysis revealed that CK/CH/LN/2302 shared a high level of homology (96.

MF-06 alleviates intestinal mucosal barrier from damage in chicks infected with via activating the Wnt/-catenin pathway.

Introduction: This study aimed to assess the protective efficacy of MF-06 as a potential alternative to antibiotics in mitigating intestinal mucosal damage in chicks infected with .

Methods: A total of 150 one-day-old SPF chicks were selected and randomly divided into five groups: control group (CK), probiotics group (EM), probiotics treatment group (PT), antibiotic treatment group (AT), group (SI), CK, AT and SI groups were fed a basal diet, EM and PT groups were fed a basal diet supplemented with 1.0 × 10 CFU/g ; PT, AT and SI groups were gavaged with 1.

Research Notes: Evaluation of recombinant Newcastle disease virus expressing gB protein of infectious laryngotracheitis virus as bivalent in ovo vaccine.

Infectious laryngotracheitis (ILT) and Newcastle disease (ND) are 2 highly infectious avian respiratory diseases that have caused significant economic losses in the poultry industry worldwide. In ovo vaccination is administered during the late stage of incubation and is an attractive immunization method for poultry industry. However, most of the avian live vaccine strains that are safe for use after hatching are highly pathogenic to chicken embryos and therefore unsafe for in ovo vaccination.

Deep learning-based diagnosis and survival prediction of patients with renal cell carcinoma from primary whole slide images.

There is an urgent clinical demand to explore novel diagnostic and prognostic biomarkers for renal cell carcinoma (RCC). We proposed deep learning-based artificial intelligence strategies. The study included 1752 whole slide images from multiple centres.

Deep learning-based pathological prediction of lymph node metastasis for patient with renal cell carcinoma from primary whole slide images.

Background: Metastasis renal cell carcinoma (RCC) patients have extremely high mortality rate. A predictive model for RCC micrometastasis based on pathomics could be beneficial for clinicians to make treatment decisions.

Methods: A total of 895 formalin-fixed and paraffin-embedded whole slide images (WSIs) derived from three cohorts, including Shanghai General Hospital (SGH), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and Cancer Genome Atlas (TCGA) cohorts, and another 588 frozen section WSIs from TCGA dataset were involved in the study.

Deep learning-based multi-model prediction for disease-free survival status of patients with clear cell renal cell carcinoma after surgery: a multicenter cohort study.

Background: Although separate analysis of individual factor can somewhat improve the prognostic performance, integration of multimodal information into a single signature is necessary to stratify patients with clear cell renal cell carcinoma (ccRCC) for adjuvant therapy after surgery.

Methods: A total of 414 patients with whole slide images, computed tomography images, and clinical data from three patient cohorts were retrospectively analyzed. The authors performed deep learning and machine learning algorithm to construct three single-modality prediction models for disease-free survival of ccRCC based on whole slide images, cell segmentation, and computed tomography images, respectively.

A bi-allelic REC114 loss-of-function variant causes meiotic arrest and nonobstructive azoospermia.

Nonobstructive azoospermia (NOA), the most severe manifestation of male infertility, lacks a comprehensive understanding of its genetic etiology. Here, a bi-allelic loss-of-function variant in REC114 (c.568C > T: p.

Association of the m A reader IGF2BP3 with tumor progression and brain-specific metastasis in breast cancer.

Background: This study aimed to determine the role of insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3), an N -methyladinosine reader, in the progression and distant metastasis of breast cancer.

Methods: IGF2BP3 expression was assessed in 152 pairs of breast cancer and adjacent normal tissue (ANT) by real-time quantitative polymerase chain reaction and in 561 cases of breast cancer and 163 cases of ANT by immunohistochemistry. Survival curves were estimated using the Kaplan-Meier method and then compared statistically using the log-rank test.

Preliminary exploration of the effects of environmental factors on the microsatellite status of BRAF-mutated colorectal cancer.

Background: To investigate the expression of EBV products and frequency of gallstone disease (GD) among different microsatellite status in colorectal cancer (CRC) with BRAF mutation.

Methods: We collected 30 CRC patients with BRAF mutation and 10 BRAF ( -) CRC patients as well as 54 healthy subjects. Tumor tissue samples were collected to detect the mutation of BRAF, KRAS, and TP53.

Quantitative proteomics profiling reveals the inhibition of trastuzumab antitumor efficacy by phosphorylated RPS6 in gastric carcinoma.

Background: The anti-HER2 antibody trastuzumab is a standard treatment for gastric carcinoma with HER2 overexpression, but not all patients benefit from treatment with HER2-targeted therapies due to intrinsic and acquired resistance. Thus, more precise predictors for selecting patients to receive trastuzumab therapy are urgently needed.

Methods: We applied mass spectrometry-based proteomic analysis to 38 HER2-positive gastric tumor biopsies from 19 patients pretreated with trastuzumab (responders n = 10; nonresponders, n = 9) to identify factors that may influence innate sensitivity or resistance to trastuzumab therapy and validated the results in tumor cells and patient samples.

Screening and identification of prognostic genes associated with eosinophilic features of clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma, which is characterized by transparent cytoplasm. However, some ccRCC also show eosinophilic cytoplasm, and the molecular difference between eosinophilic and clear subtypes is unclear. In this study, we uncovered that under an optical microscope ccRCC with eosinophilic features has a poor prognosis.

Identification of Embryonic Chicken Proteases Activating Newcastle Disease Virus and Their Roles in the Pathogenicity of Virus Used as Vaccine.

vaccination is an attractive immunization approach for chickens. However, most live Newcastle disease virus (NDV) vaccine strains used safely after hatching are unsafe as vaccines due to their high pathogenicity for chicken embryos. The mechanism for viral pathogenicity in chicken embryos is poorly understood.

Ultrasonographic evaluation of the rete testis thickness: a promising approach to differentiate obstructive from nonobstructive azoospermia.

This study aimed to evaluate the ability of rete testis thickness (RTT) and testicular shear wave elastography (SWE) to differentiate obstructive azoospermia (OA) from nonobstructive azoospermia (NOA). We assessed 290 testes of 145 infertile males with azoospermia and 94 testes of 47 healthy volunteers at Shanghai General Hospital (Shanghai, China) between August 2019 and October 2021. The testicular volume (TV), SWE, and RTT were compared among patients with OA and NOA and healthy controls.

The feasibility of proteomics sequencing based immune-related prognostic signature for predicting clinical outcomes of bladder cancer patients.

Background: Bladder cancer (BCa) shows its potential immunogenity in current immune-checkpoint inhibitor related immunotherapies. However, its therapeutic effects are improvable and could be affected by tumor immune microenvironment. Hence it is interesting to find some more prognostic indicators for BCa patients concerning immunotherapies.

Robust Prediction of Prognosis and Immunotherapeutic Response for Clear Cell Renal Cell Carcinoma Through Deep Learning Algorithm.

It is of great urgency to explore useful prognostic markers and develop a robust prognostic model for patients with clear-cell renal cell carcinoma (ccRCC). Three independent patient cohorts were included in this study. We applied a high-level neural network based on TensorFlow to construct the robust model by using the deep learning algorithm.

Predicting Clear Cell Renal Cell Carcinoma Survival Using Kurtosis of Cytoplasm in the Hematoxylin Channel from Histology Slides.

Purpose: Grade-dependent decrease of lipid storage in clear cell renal cell carcinoma (ccRCC) leads to morphology changes in HE sections. This study investigated the role of cytoplasmic features in frozen sections of ccRCC on prognosis using the digital pathology approach.

Methods: We established an automatic pipeline that performed tumor region selection, stain vector normalization, nuclei segmentation, and feature extraction based on the pathologic data from Shanghai General Hospital and The Cancer Genome Atlas database.

Machine learning-based pathomics signature could act as a novel prognostic marker for patients with clear cell renal cell carcinoma.

Background: Traditional histopathology performed by pathologists through naked eyes is insufficient for accurate survival prediction of clear cell renal cell carcinoma (ccRCC).

Methods: A total of 483 whole slide images (WSIs) data from three patient cohorts were retrospectively analyzed. We performed machine learning algorithm to identify optimal digital pathological features and constructed machine learning-based pathomics signature (MLPS) for ccRCC patients.

A Novel Nomogram Based on Machine Learning-Pathomics Signature and Neutrophil to Lymphocyte Ratio for Survival Prediction of Bladder Cancer Patients.

Traditional histopathology performed by pathologists through naked eyes is insufficient for accurate survival prediction of bladder cancer (BCa). In addition, how neutrophil to lymphocyte ratio (NLR) could be used for prognosis prediction of BCa patients has not been fully understood. In this study, we collected 508 whole slide images (WSIs) of hematoxylin-eosin strained BCa slices and NLR value from the Shanghai General Hospital and The Cancer Genome Atlas (TCGA), which were further processed for nuclear segmentation.

PD-1-Positive Tumor-Associated Macrophages Define Poor Clinical Outcomes in Patients With Muscle Invasive Bladder Cancer Through Potential CD68/PD-1 Complex Interactions.

Tumor-associated macrophages (TAMs) regulate tumor immunity. Previous studies have shown that the programmed cell death protein 1 (PD-1)-positive TAMs have an M2 macrophage phenotype. CD68 is a biomarker of TAMs and is considered to be a poor prognostic marker of several malignancies.

Clinical use of machine learning-based pathomics signature for diagnosis and survival prediction of bladder cancer.

Traditional histopathology performed by pathologists by the naked eye is insufficient for accurate and efficient diagnosis of bladder cancer (BCa). We collected 643 H&E-stained BCa images from Shanghai General Hospital and The Cancer Genome Atlas (TCGA). We constructed and cross-verified automatic diagnosis and prognosis models by performing a machine learning algorithm based on pathomics data.

A Novel mA Gene Signature Associated With Regulatory Immune Function for Prognosis Prediction in Clear-Cell Renal Cell Carcinoma.

The important role of N-methyladenosine (mA) RNA methylation regulator in carcinogenesis and progression of clear-cell renal cell carcinoma (ccRCC) is poorly understood by now. In this study, we performed comprehensive analyses of mA RNA methylation regulators in 975 ccRCC samples and 332 adjacent normal tissues and identified ccRCC-related mA regulators. Moreover, the mA diagnostic score based on ccRCC-related mA regulators could accurately distinguish ccRCC from normal tissue in the Meta-cohort, which was further validated in the independent GSE-cohort and The Cancer Genome Atlas-cohort, with an area under the curve of 0.

Clinical use of a machine learning histopathological image signature in diagnosis and survival prediction of clear cell renal cell carcinoma.

Due to the complicated histopathological characteristics of renal neoplasms, traditional distinguishing of clear cell renal cell carcinoma (ccRCC) by naked eyes of experienced pathologist remains labor intensive and time consuming. Here, we extracted quantitative features of hematoxylin-eosin-stained images using CellProfiler and performed machine learning method to develop and verify a novel computational recognition of digital pathology for diagnosis and prognosis of ccRCC patients in the training, test and external validation cohort. The diagnostic model based on digital pathology could accurately distinguish ccRCC from normal renal tissues, with area under the curve (AUC) of 96.

Protoporphyrin IX is a dual inhibitor of p53/MDM2 and p53/MDM4 interactions and induces apoptosis in B-cell chronic lymphocytic leukemia cells.

p53 is a tumor suppressor, which belongs to the p53 family of proteins. The family consists of p53, p63 and p73 proteins, which share similar structure and function. Activation of wild-type p53 or TAp73 in tumors leads to tumor regression, and small molecules restoring the p53 pathway are in clinical development.

Differential expressions of integrin-linked kinase, β-parvin and cofilin 1 in high-fat diet induced prostate cancer progression in a transgenic mouse model.

High-fat diet induced obesity was associated with more aggressive prostate cancer. Recent research has demonstrated that integrin-linked kinase (ILK), β-parvin and downstream cofilin 1 jointly affected cancer progression. Meanwhile, these proteins were also involved in energy metabolism.