Nodal Yield From Neck Dissection Predicts the Anti-Tumor Immune Response in Head and Neck Cancers.

Background: Lymph node count (LNC) from neck dissection has been associated with undernutrition and survival in head and neck squamous cell carcinoma (HNSCC). As local components of the immune system, cervical lymph nodes may reflect anti-tumor immune status. This study investigates the relationship between decreased LNC, formation of tertiary lymphoid structures (TLS), and primary tumor infiltration by lymphocytes in undernourished patients.

Cell Segmentation With Globally Optimized Boundaries (CSGO): A Deep Learning Pipeline for Whole-Cell Segmentation in Hematoxylin-and-Eosin-Stained Tissues.

Accurate whole-cell segmentation is essential in various biomedical applications, particularly in studying the tumor microenvironment. Despite advancements in machine learning for nuclei segmentation in hematoxylin and eosin (H&E)-stained images, there remains a need for effective whole-cell segmentation methods. This study aimed to develop a deep learning-based pipeline to automatically segment cells in H&E-stained tissues, thereby advancing the capabilities of pathological image analysis.

Efficient and simultaneous immobilization of fluoride and lead in water and tea garden soil by bayberry tannin foam loaded zirconium.

Nowadays, human activities intensified the combined pollution of fluoride and lead in acidic tea garden soil. The key to eliminating this combined pollution is to immobilize pollutants simultaneously, thus preventing their migration from tea garden soil to tea trees. In this paper, the natural product bayberry tannin was employed as raw material to fabricate functional materials (TF-Zr) for simultaneous adsorption of fluorine (F) and lead (Pb) in water and soil by the reactivity of tannin with Pb and the affinity of Zr with F.

Enhancing Medical Imaging Segmentation with GB-SAM: A Novel Approach to Tissue Segmentation Using Granular Box Prompts.

Recent advances in foundation models have revolutionized model development in digital pathology, reducing dependence on extensive manual annotations required by traditional methods. The ability of foundation models to generalize well with few-shot learning addresses critical barriers in adapting models to diverse medical imaging tasks. This work presents the Granular Box Prompt Segment Anything Model (GB-SAM), an improved version of the Segment Anything Model (SAM) fine-tuned using granular box prompts with limited training data.

iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis.

Current clustering analysis of spatial transcriptomics data primarily relies on molecular information and fails to fully exploit the morphological features present in histology images, leading to compromised accuracy and interpretability. To overcome these limitations, we have developed a multi-stage statistical method called iIMPACT. It identifies and defines histology-based spatial domains based on AI-reconstructed histology images and spatial context of gene expression measurements, and detects domain-specific differentially expressed genes.

Reconstructing Spatial Transcriptomics at the Single-cell Resolution with BayesDeep.

Spatially resolved transcriptomics (SRT) techniques have revolutionized the characterization of molecular profiles while preserving spatial and morphological context. However, most next-generation sequencing-based SRT techniques are limited to measuring gene expression in a confined array of spots, capturing only a fraction of the spatial domain. Typically, these spots encompass gene expression from a few to hundreds of cells, underscoring a critical need for more detailed, single-cell resolution SRT data to enhance our understanding of biological functions within the tissue context.

Deep Learning-Based H-Score Quantification of Immunohistochemistry-Stained Images.

Immunohistochemistry (IHC) is a well-established and commonly used staining method for clinical diagnosis and biomedical research. In most IHC images, the target protein is conjugated with a specific antibody and stained using diaminobenzidine (DAB), resulting in a brown coloration, whereas hematoxylin serves as a blue counterstain for cell nuclei. The protein expression level is quantified through the H-score, calculated from DAB staining intensity within the target cell region.

Thermodynamic and Mechanistic Analyses of Direct CO Methylation with Toluene to -Xylene.

Direct CO methylation with toluene, as one of the CO hydrogenation technologies, exhibits great potential for the CO utilization to produce the valuable -xylene (PX), but the tandem catalysis remains a challenge for low conversion and selectivity due to the competitive side reactions. The thermodynamic analyses and the comparation with two series of catalytic results of direct CO methylation are conducted to investigate the product distribution and possible mechanism in adjusting the feasibility of higher conversion and selectivity. Based on the Gibbs energy minimization method, the optimal thermodynamic conditions for direct CO methylation are 360-420 °C, 3 MPa with middle CO/CH ratio (1:1 to 1:4) and high H feed (CO/H = 1:3 to 1:6).

Removal of dioxins from municipal solid waste incineration fly ash by low-temperature thermal treatment: Laboratory simulation of degradation and ash discharge stages.

Dioxins in municipal solid waste incineration fly ash (MSWIFA) can cause significant risks to the environment and human health. In this study, the low-temperature thermal treatment of MSWIFA under industrial conditions was simulated in the laboratory to investigate the process parameters for dioxin degradation and ash discharge stages. Correlation analysis and dioxin fingerprint characterization were used to analyze the degradation and ash discharge processes.

Deep-Learning-Based Hepatic Ploidy Quantification Using H&E Histopathology Images.

Polyploidy, the duplication of the entire genome within a single cell, is a significant characteristic of cells in many tissues, including the liver. The quantification of hepatic ploidy typically relies on flow cytometry and immunofluorescence (IF) imaging, which are not widely available in clinical settings due to high financial and time costs. To improve accessibility for clinical samples, we developed a computational algorithm to quantify hepatic ploidy using hematoxylin-eosin (H&E) histopathology images, which are commonly obtained during routine clinical practice.

A Deep Learning Approach for Histology-Based Nucleus Segmentation and Tumor Microenvironment Characterization.

Microscopic examination of pathology slides is essential to disease diagnosis and biomedical research. However, traditional manual examination of tissue slides is laborious and subjective. Tumor whole-slide image (WSI) scanning is becoming part of routine clinical procedures and produces massive data that capture tumor histologic details at high resolution.

Deep learning in digital pathology for personalized treatment plans of cancer patients.

Over the past decade, many new cancer treatments have been developed and made available to patients. However, in most cases, these treatments only benefit a specific subgroup of patients, making the selection of treatment for a specific patient an essential but challenging task for oncologists. Although some biomarkers were found to associate with treatment response, manual assessment is time-consuming and subjective.

Review of thermal treatments for the degradation of dioxins in municipal solid waste incineration fly ash: Proposing a suitable method for large-scale processing.

Dioxin degradation is considered essential for the environmentally sound management of municipal solid waste incineration fly ash (MSWIFA). Among the many degradation techniques, thermal treatment has shown good prospects owing to its high efficiency and wide range of applications. Thermal treatment is divided into high-temperature thermal, microwave thermal, hydrothermal, and low-temperature thermal treatments.

Enhanced Pathology Image Quality with Restore-Generative Adversarial Network.

Whole slide imaging is becoming a routine procedure in clinical diagnosis. Advanced image analysis techniques have been developed to assist pathologists in disease diagnosis, staging, subtype classification, and risk stratification. Recently, deep learning algorithms have achieved state-of-the-art performances in various imaging analysis tasks, including tumor region segmentation, nuclei detection, and disease classification.

Multisystem Langerhans Cell Histiocytosis in Younger Infants First Presenting in Skin: A Case Series.

Objectives-To investigate the clinical characteristics, managements, outcome, and evaluate the risk factors of Multisystem (MS) Langerhans Cell Histiocytosis (LCH) with diverse skin lesions as the first sign in four young infants. Methods-Their clinical features, disease progression, therapy, and outcomes were reviewed and analyzed retrospectively. Results-The average onset age of skin lesions was about 2 months.

In vivo CD8 T cell CRISPR screening reveals control by Fli1 in infection and cancer.

Improving effector activity of antigen-specific T cells is a major goal in cancer immunotherapy. Despite the identification of several effector T cell (T)-driving transcription factors (TFs), the transcriptional coordination of T biology remains poorly understood. We developed an in vivo T cell CRISPR screening platform and identified a key mechanism restraining T biology through the ETS family TF, Fli1.

The expression and clinical significance of murine double minute 2, lysosome-associated membrane protein 1, and P-glycoprotein in pediatric acute lymphoblastic leukemia.

Background: To analyze the expression and clinical significance of murine double minute 2 (), lysosome-associated membrane protein () and P-glycoprotein () in children with acute lymphoblastic leukemia (ALL).

Methods: Thirty-three children with ALL who were admitted to our hospital between January 2017 and January 2018 were enrolled as the ALL group. The expression of , and was compared between the two groups, as well as between ALL patients with different clinical characteristics.

eIF5B drives integrated stress response-dependent translation of PD-L1 in lung cancer.

Cancer cells express high levels of PD-L1, a ligand of the PD-1 receptor on T cells, allowing tumors to suppress T cell activity. Clinical trials utilizing antibodies that disrupt the PD-1/PD-L1 checkpoint have yielded remarkable results, with anti-PD-1 immunotherapy approved as first-line therapy for lung cancer patients. We used CRISPR-based screening to identify regulators of PD-L1 in human lung cancer cells, revealing potent induction of PD-L1 upon disruption of heme biosynthesis.

Mice With Increased Numbers of Polyploid Hepatocytes Maintain Regenerative Capacity But Develop Fewer Hepatocellular Carcinomas Following Chronic Liver Injury.

Background & Aims: Thirty to 90% of hepatocytes contain whole-genome duplications, but little is known about the fates or functions of these polyploid cells or how they affect development of liver disease. We investigated the effects of continuous proliferative pressure, observed in chronically damaged liver tissues, on polyploid cells.

Methods: We studied Rosa-rtTa mice (controls) and Rosa-rtTa;TRE-short hairpin RNA mice, which have reversible knockdown of anillin, actin binding protein (ANLN).

The effect of anterior communicating artery flow on neurovascular injury and neurobehavioral outcomes in mice with recurrent stroke.

Background: Previous studies have estimated that the risk of recurrent stroke was nearly 20% shortly after a transient ischemic attack (TIA) or minor stroke. A missing or hypoplastic (<0.5 mm) anterior communicating artery can have deleterious effects on the brain.

Lipocalin-2 may produce damaging effect after cerebral ischemia by inducing astrocytes classical activation.

Background: Functions of astrocytes in the rehabilitation after ischemic stroke, especially their impacts on inflammatory processes, remain controversial. This study uncovered two phenotypes of astrocytes, of which one was helpful, and the other harmful to anoxic neurons after brain ischemia.

Methods: We tested the levels of inflammatory factors including TNF-a, IL-6, IL-10, iNOS, IL-1beta, and CXCL10 in primary astrocytes at 0 h, 6 h, 12 h, 24 h, and 48 h after OGD, grouped the hypoxia astrocytes into iNOS-positive (iNOS(+)) and iNOS-negative (iNOS(-)) by magnetic bead sorting, and then co-cultured the two groups of cells with OGD-treated neurons for 24 h.

Phosphatase PP2A is essential for T17 differentiation.

Phosphatase PP2A expression levels are positively correlated to the clinical severity of systemic lupus erythematosus (SLE) and IL17A cytokine overproduction, indicating a potential role of PP2A in controlling T17 differentiation and inflammation. By generating a mouse strain with ablation of the catalytic subunit α of PP2A in peripheral mature T cells (PP2A cKO), we demonstrate that the PP2A complex is essential for T17 differentiation. These PP2A cKO mice had reduced T17 cell numbers and less severe disease in an experimental autoimmune encephalomyelitis (EAE) model.

MicroRNA-1906, a Novel Regulator of Toll-Like Receptor 4, Ameliorates Ischemic Injury after Experimental Stroke in Mice.

Toll-like receptor 4 (TLR4) is a proinflammatory cascade initiator in poststroke inflammation. In this study, miR-1906, a novel regulator of TLR4, was identified via analysis and microRNA profiling in male adult mice and its expression was then quantitated in the ischemic hemisphere. We found miR-1906 to be significantly brain enriched in the ischemic hemisphere and even more drastically enriched in the peri-infarct regions.

Optimization of behavioural tests for the prediction of outcomes in mouse models of focal middle cerebral artery occlusion.

Intraluminal middle cerebral artery occlusion (MCAO) is the most widely used model of stroke. We aimed to predict the outcome of MCAO using a combination of fine behavioural tests for the prediction of unsuccessful surgery in mice leading to no infarction, haemorrhage and unexpected death. MCAO was performed on adult mice under the guidance of laser-Doppler flowmetry (LDF) to warrant a decrease in regional cerebral blood flow (rCBF) in the MCA territory.