Integrative Analysis of scRNA-Seq and Bulk RNA-Seq Identifies Plasma Cell Related Genes and Constructs a Prognostic Model for Hepatocellular Carcinoma.

Purpose: The complexity and heterogeneity of the tumor immune microenvironment (TIME) are linked to the development and poor prognosis of hepatocellular carcinoma (HCC). However, the cell type within the TIME that is most closely associated with HCC development remains unclear. Herein, we aimed to identify cell clusters that significantly contribute to HCC development and their underlying mechanisms.

Application of TransUnet Deep Learning Model for Automatic Segmentation of Cervical Cancer in Small-Field T2WI Images.

Effective segmentation of cervical cancer tissue from magnetic resonance (MR) images is crucial for automatic detection, staging, and treatment planning of cervical cancer. This study develops an innovative deep learning model to enhance the automatic segmentation of cervical cancer lesions. We obtained 4063 T2WI small-field sagittal, coronal, and oblique axial images from 222 patients with pathologically confirmed cervical cancer.

Syringin protects high glucose-induced BMSC injury, cell senescence, and osteoporosis by inhibiting JAK2/STAT3 signaling.

Background: Acanthopanax senticosus (Rupr. et Maxim.) is commonly used in Traditional Chinese Medicine.

High-Efficiency Cell-Type Proteomics Strategy Deciphers Cholangiocarcinoma Fibrosis-Associated Pathological Heterogeneity.

Cholangiocarcinoma (CCA) is the second most common primary liver cancer and is characterized by huge heterogeneity, difficult diagnosis, and poor prognosis. Fibrosis-associated heterogeneity in CCA serves as an indicator of the malignant progression of cancer; however, a precise approach to deciphering fibrosis heterogeneity is still lacking. Typically, the tissue proteome is profiled by analyzing bulk tissues, which gives average results of different cell types, especially for CCA tissues in which cancer cells occupy a very small proportion.

PM concentration prediction using a whale optimization algorithm based hybrid deep learning model in Beijing, China.

PM is a significant global atmospheric pollutant impacting visibility, climate, and public health. Accurate prediction of PM concentrations is critical for assessing air pollution risks and providing early warnings for effective management. This study proposes a novel hybrid machine learning model that combines the whale optimization algorithm (WOA) with a convolutional neural network (CNN), long short-term memory (LSTM), and an attention mechanism (AM) to predict daily PM concentrations.

GGN repeat length of the androgen receptor gene is associated with antral follicle count in Chinese women undergoing controlled ovarian stimulation.

Objectives: To evaluate the association of GGN repeat polymorphism of androgen receptor (AR) with ovarian reserve and ovarian response in controlled ovarian stimulation (COS).

Methods: This genetic association study was conducted among a total of 361 women aged ≤40 years with basal FSH≤12 U/L undergoing the GnRH-agonist long protocol for COS in a university-affiliated IVF center. GGN repeat in the AR gene was analyzed with Sanger sequencing.

Nanophotonic Zero-Index-Material-Enabled Optical Coherent Interferometry with High Signal-to-Noise Ratio.

Optical interferometry enables distance measurement with record-high precision. However, the conventional interference intensity shows fast spatial variations, limiting photodetection to a single spot. The light intensity at this spot is affected by various noises, restricting the signal-to-noise ratio (SNR) of a coherent system.

BSRF1 modulates IFN-β-mediated antiviral responses by inhibiting NF-κB activity via an IKK-dependent mechanism in Epstein-Barr virus infection.

The Epstein-Barr virus (EBV) encoded tegument protein BSRF1 plays a significant role in the processes of viral maturation and release, however, it's not clear whether BSRF1 is involved in the modulation of host innate immunity. In this study, we demonstrated that BSRF1 can inhibit interferon β (IFN-β) production by downregulating nuclear factor kappa B (NF-κB) activity and subsequently reducing the yield of inflammatory cytokines, thereby facilitating viral replication. Dual luciferase reporter assays indicated that BSRF1 may inhibit NF-κB signaling at the level of IKK or between IKK and p65, while co-immunoprecipitation experiments revealed its association with multiple critical host adaptor proteins.

The mechanism of high mobility group box-1 in the proliferation and macrophage polarization in esophageal squamous cell carcinoma cells.

Background: Previous studies showed that high mobility group box-1 (HMGB1) facilitates the initiation and progression of esophageal squamous cell carcinoma (ESCC), and the current research investigated the detailed mechanisms implicated.

Methods: The impact of HMGB1 and IGFBP3 levels on the survival of ESCC was examined by plotting Kaplan-Meier (KM) curves based on the data collected from The Cancer Genome Atlas (TCGA). Quantitative real-time PCR (qRT-PCR) was performed to detect the expressions of HMGB1 in both human esophageal epithelial cells (HEEC) and ESCC cells.

Nivolumab combined with induction chemotherapy and radiotherapy in nasopharyngeal carcinoma: A multicenter phase 2 PLATINUM trial.

Severe toxicities caused by concurrent cisplatin are a critical problem in nasopharyngeal carcinoma (NPC) treatment. In this phase 2 multicenter PLATINUM trial (NCT03984357), we recruited 152 NPC patients who received 12-cycle nivolumab plus induction chemotherapy and radiotherapy without concurrent cisplatin. After a median follow-up of 43 months, the 3-year failure-free survival (FFS) was 88.

In silico modeling of targeted protein degradation.

Targeted protein degradation (TPD) techniques, particularly proteolysis-targeting chimeras (PROTAC) and molecular glue degraders (MGD), have offered novel strategies in drug discovery. With rapid advancement of computer-aided drug design (CADD) and artificial intelligence-driven drug discovery (AIDD) in the biomedical field, a major focus has become how to effectively integrate these technologies into the TPD drug discovery pipeline to accelerate development, shorten timelines, and reduce costs. Currently, the main research directions for applying CADD and AIDD in TPD include: 1) ternary complex modeling; 2) linker generation; 3) strategies to predict degrader targets, activities and ADME/T properties; 4) In silico degrader design and discovery.

A comprehensive metabolomic and lipidomic study of olanzapine in the treatment of first-episode schizophrenia.

Background: Despite advances in research, critical gaps remain in understanding the molecular mechanisms of antipsychotic medications such as olanzapine. This study investigated the molecular pathways by which olanzapine exerts its therapeutic effects and causes metabolic side effects by analyzing changes in the serum metabolic and lipid profiles of patients with first-episode schizophrenia.

Methods: Clinical symptoms were assessed using the Positive and Negative Symptom Scale (PANSS) in 43 patients with first-episode schizophrenia.

Personalized contrast agent dosing to prevent contrast induced nephropathy in high risk populations in Guangdong, China.

Contrast-induced nephropathy (CIN) is an acute kidney injury manifests within 72 h post-administration of contrast media, excluding other kidney-damage etiologies. Despite the recognition of CIN, the complex interplay among high-risk factors remains poorly understood, and precision in the existing risk stratification models is lacking. This retrospective, observational cohort study included patients who underwent percutaneous coronary intervention (PCI) or computed tomography angiography (CTA) at four hospitals in Guangdong, China, between 2010 and 2018.

A study of benthic habitat classification schemes in the northern equatorial Pacific based on a Gaussian mixture model.

Due to the complexity and extreme environment of the deep sea, related research is limited by the level of detection technology, and the overall understanding of this topic is limited. At present, the increasing number of disturbances in the deep sea, such as those caused by deep-sea mining, necessitates the urgent formulation of scientifically informed deep-sea environmental management decisions. In response to this challenge, a data-driven, large-scale, and probability-based benthic habitat classification scheme is proposed for the northern equatorial Pacific.

Determination of circulating tumor cells by surface-enhanced Raman scattering based on molecularly imprinted polymers doped with silver nanoparticles.

The rapid and simple detection of circulating tumor cells (CTCs) can help with early diagnosis of tumor diseases and assist clinical judgment of tumor disease development status and prognosis. An important alteration in cancer progression is a significant increase in sialic acid (SA) levels, making sialic acid one of an interesting biomarker for cancer type diversity. Here, novel SERS nano-biosensors were fabricated employing molecularly imprinted polymers (MIPs) particles loaded with Ag nanoparticles (AgNPs) to form high affinity toward sialic acid on CTCs.

Direct Distillation: A Novel Approach for Efficient Diffusion Model Inference.

Diffusion models are among the most common techniques used for image generation, having achieved state-of-the-art performance by implementing auto-regressive algorithms. However, multi-step inference processes are typically slow and require extensive computational resources. To address this issue, we propose the use of an information bottleneck to reschedule inference using a new sampling strategy, which employs a lightweight distilled neural network to map intermediate stages to the final output.

Molecular mechanism of pancreatic ductal adenocarcinoma: The heterogeneity of cancer-associated fibroblasts and key signaling pathways.

Pancreatic ductal adenocarcinoma stands out as an exceptionally fatal cancer owing to the complexities associated with its treatment and diagnosis, leading to a notably low five-year survival rate. This study offers a detailed exploration of epidemiological trends in pancreatic cancer and key molecular drivers, such as mutations in , , , and , along with the influence of cancer-associated fibroblasts (CAFs) on disease progression. In particular, we focused on the pivotal roles of signaling pathways such as the transforming growth factor-β and Wnt/β-catenin pathways in the development of pancreatic cancer and investigated their application in emerging therapeutic strategies.

Development and evaluation of a novel rapid fungal nucleic acid extraction kit.

Fungal infections can cause different diseases, and nucleic acid extraction is a crucial step in assisting the diagnosis of fungal infections. Traditional methods and current commercial fungal nucleic acid extraction kits are often time-consuming and involve hazardous chemicals. We developed a nucleic acid extraction kit that is safe, rapid, and efficient, designated as FNA-REK (Fungal Nucleic Acid Extraction Kit), which facilitates the simultaneous extraction of DNA and RNA without the necessity for hazardous chemicals, liquid nitrogen, or glass beads.

Effectiveness of biologics for endoscopic healing in patients with isolated proximal small bowel Crohn's disease.

Background: Endoscopic healing (EH) is a key therapeutic target in Crohn's disease (CD). Proximal small bowel (SB) lesions in patients with CD are associated with a significant risk of strictures and bowel resection. Assessing SB in patients with CD is necessary because of its significant therapeutic implications.

Association between weekend catch-up sleep and the systemic immune-inflammation index in adults: Evidence from the NHANES 2017-2020.

Background: Chronic sleep deprivation is widespread and associated with detrimental health outcomes, including inflammation. A common strategy to address weekday sleep deficits is weekend catch-up sleep (WCS). However, the relevance of the WCS on systemic inflammation, as quantified by the systemic immune-inflammation index (SII), remains inadequately understood.

Determination of tetracycline antibiotics in food using covalent organic frameworks composites-based on magnetic solid phase extraction coupled to HPLC.

Tetracycline antibiotics (TCs) has been widely applied as animal and human medicine for the prevention and treatment of diseases. The unsafe residues of TCs pose serious risks to human health. Development of a rapid and sensitive method for determining TCs residues in environment and food samples is still challenging.

Multi-scale modelling of battery cooling systems for grid frequency regulation with high C-rate amplitude and non-uniform cell heat generation.

The introduction of battery energy storage systems is crucial for addressing the challenges associated with reduced grid stability that arise from the large-scale integration of renewable energy sources into the grid. However, operating the energy storage system in scenarios such as frequency regulation and fluctuation mitigation can result in high C-rates, leading to increased heat load and significant thermal gradients within the cells. This study investigates the electro-thermal characteristics and non-uniform heat generation of a 100 Ah lithium-ion battery.

Spatiotemporal analysis of carbon emission efficiency across economic development stages and synergistic emission reduction in the Beijing-Tianjin-Hebei region.

Exploring regional carbon emission efficiency and its patterns is crucial for promoting a sustainable economy. This study investigated the spatiotemporal variations of carbon emissions and emission efficiency in the Beijing-Tianjin-Hebei region. Night light data was used to estimate carbon emissions, and the Super-EBM model was employed to calculate carbon emission efficiency.