Atorvastatin enhances LDL receptor-mediated LDL-C uptake and modulates PCSK9 protein expression in pancreatic β-cells.

Statins are widely used to treat hyperlipidemia and atherosclerotic cardiovascular diseases (ACVD) by significantly lowering low-density lipoprotein cholesterol (LDL-C) levels. However, their use has been associated with an increased risk of type 2 diabetes (T2D), a paradox given their lipid-lowering benefits. This study investigates the role of LDL receptors (LDLR) and proprotein convertase subtilisin/kexin type 9 (PCSK9) in the diabetogenic effects of atorvastatin on pancreatic β-cells.

Rapid detection of frogeye leaf spot pathogen in seeds by LAMP assays to protect soybean production.

Frogeye leaf spot (FLS), caused by Cercospora sojina, is a significant disease affecting soybean crops economically. Seed inspection plays a vital role in reducing the incidence of this disease. However, limited research has been conducted on the fast and accurate identification of C.

Genetic and epigenetic mechanisms of GPRC5D loss after anti-GPRC5D CAR T-cell therapy in multiple myeloma.

G protein-coupled receptor, class C, group 5, member D (GPRC5D) has emerged as a novel target for chimeric antigen receptor (CAR) T-cell therapy, demonstrating promising efficacy in multiple myeloma (MM). However, disease relapse is still common, and the mechanism of resistance remains poorly understood. In this study, we conducted whole-genome sequencing (WGS) and whole-genome bisulfite sequencing (WGBS) on MM samples from 10 patients who relapsed after GPRC5D CAR T-cell therapy.

Safety and efficacy of rilzabrutinib vs placebo in adults with immune thrombocytopenia: the phase 3 LUNA3 study.

Rilzabrutinib is a covalent, reversible BTK inhibitor with multiple mechanisms targeting key immune thrombocytopenia (ITP) disease pathophysiology. The phase 3 LUNA3 study in previously treated adults with persistent/chronic ITP evaluated oral rilzabrutinib 400 mg bid (n=133) vs placebo (n=69) for 24 weeks. At baseline overall, median age was 47 years (range, 18-80), 63% female, 7.

Potential Adverse Events of Fluoxetine: A Real-world Study Based on FAERS Database.

Objective: This study aimed to mine and analyze adverse event signals of fluoxetine using the FAERS database.

Methods: This study focused on suspected drug adverse reaction reports from the first quarter of 2004 to the second quarter of 2023, with fluoxetine as the primary suspected drug. Four signal mining and analysis methods were employed to comprehensively assess adverse event signals.

The neutrophil antigen 3a/b polymorphism in SLC44A2 unexpectedly encodes Csa/Csb red cell antigens.

The Csa blood group antigen was identified more than 50 years ago but its genetic basis has yet to be elucidated. All our recent genomic investigation has failed to resolve the genetic basis of this enigmatic antigen. By investigating the association of the HNA-3a/b polymorphism (rs2288904-G/A) in SLC44A2 with clinical features of Sickle Cell Disease (SCD), we incidentally discovered that rare subjects with the homozygous HNA-3b/b genotype also carry the uncommon Cs(a-) phenotype.

Ruxolitinib combined with dexamethasone for adult patients with newly diagnosed hemophagocytic lymphohistiocytosis in China.

Hemophagocytic lymphohistiocytosis (HLH) is a severe hyperinflammatory syndrome, and the overall survival of adult patients is poor. Ruxolitinib, a Janus kinase (JAK) 1/2 inhibitor, has shown promise in treating HLH and exerts synergistic effects when combined with dexamethasone. Our pilot study preliminarily demonstrated that the combination of ruxolitinib and dexamethasone (the Ru-D regimen) had a high response rate and led to favorable short-term survival outcomes in adult HLH patients.

Single-cell panleukemia signatures of HSPC-like blasts predict drug response and clinical outcome.

The critical role of leukemic initiating cells as a therapy-resistant population in myeloid leukemia is well established, however, the molecular signatures of such cells in acute lymphoblastic leukemia remain underexplored. Moreover, their role in therapy response and patient prognosis is yet to be systematically investigated across various types of acute leukemia. We employed single-cell multiomics to analyze diagnostic specimens from 96 pediatric patients with acute lymphoblastic, myeloid, and lineage ambiguous leukemias.

An MR-only deep learning inference model-based dose estimation algorithm for MR-guided adaptive radiation therapy.

Background: Magnetic resonance-guided adaptive radiation therapy (MRgART) systems combine Magnetic resonance imaging (MRI) technology with linear accelerators (LINAC) to enhance the precision and efficacy of cancer treatment. These systems enable real-time adjustments of treatment plans based on the latest patient anatomy, creating an urgent need for accurate and rapid dose calculation algorithms. Traditional CT-based dose calculations and ray-tracing (RT) processes are time-consuming and may not be feasible for the online adaptive workflow required in MRgART.

Sunlight-sensitive carbon dots for plant immunity priming and pathogen defence.

Global food production faces persistent threats from environmental challenges and pathogenic attacks, leading to significant yield losses. Conventional strategies to combat pathogens, such as fungicides and disease-resistant breeding, are limited by environmental contamination and emergence of pathogen resistance. Herein, we engineered sunlight-sensitive and biodegradable carbon dots (CDs) capable of generating reactive oxygen species (ROS), offering a novel and sustainable approach for plant protection.

Quantitative susceptibility mapping via deep neural networks with iterative reverse concatenations and recurrent modules.

Background: Quantitative susceptibility mapping (QSM) is a post-processing magnetic resonance imaging (MRI) technique that extracts the distribution of tissue susceptibilities and holds significant promise in the study of neurological diseases. However, the ill-conditioned nature of dipole inversion often results in noise and artifacts during QSM reconstruction from the tissue field. Deep learning methods have shown great potential in addressing these issues; however, most existing approaches rely on basic U-net structures, leading to limited performances and reconstruction artifacts sometimes.

SNet: Self-adaptive weighted fusion and self-adaptive aligned network for multi-modal MRI segmentation.

Background: Accurate segmentation of lesions is beneficial for quantitative analysis and precision medicine in multimodal magnetic resonance imaging (MRI).

Purpose: Currently, multimodal MRI fusion segmentation networks still face two main issues. On one hand, simple feature concatenation fails to fully capture the complex relationships between different modalities, as it overlooks the importance of dynamically changing feature weights across modalities.

Exploring miR-577 and miR-494-3p as Emerging Biomarkers in Sepsis-Associated Acute Kidney Injury: Diagnostic and Prognostic Perspectives.

Sepsis-associated acute kidney injury (AKI) poses a severe threat to patients' lives and health, making early predictions, intervention, and treatment crucial. This study aims to preliminarily explore the clinical role of miR-577 and miR-494-3p in sepsis-associated AKI. The study included 70 sepsis patients with AKI, 65 sepsis patients without AKI, and a healthy control group (HC, n = 67) to set baseline miRNA levels.

Decentralized learning for medical image classification with prototypical contrastive network.

Background: Recently, deep convolutional neural networks (CNNs) have shown great potential in medical image classification tasks. However, the practical usage of the methods is constrained by two challenges: 1) the challenge of using nonindependent and identically distributed (non-IID) datasets from various medical institutions while ensuring privacy, and 2) the data imbalance problem due to the frequency of different diseases.

Purpose: The objective of this paper is to present a novel approach for addressing these challenges through a decentralized learning method using a prototypical contrastive network to achieve precise medical image classification while mitigating the non-IID problem across different clients.

Diagnostic image-based treatment planning for online adaptive ultra-hypofractionated prostate cancer radiotherapy with MR-Linac.

Purpose: A new workflow was investigated for Elekta Unity MR-Linac by removing the computed tomography (CT)-simulation step and using diagnostic CT (DCT) for reference plan generation.

Materials And Methods: Ten patients with ultra-hypofractionated prostate cancer treated with magnetic resonance imaging (MRI)-guided adaptive radiotherapy were retrospectively enrolled. Targets and organs at risk (OARs) were recontoured on DCT, and Hounsfield unit conversions to relative electron density were calibrated for DCT.

A practical synthesis of YZD-7082B, a novel orally bioavailable selective estrogen receptor degrader (SERD) for the treatment of ER+ breast cancer.

In previous studies, we discovered YZD-7082B, a selective estrogen receptor degrader (SERD) with excellent comprehensive properties. Here, we reported the development of an efficient multigram-scale synthetic process for YZD-7082 in 13 steps. The route featured a chiral resolution of a thiochroman intermediate with a unique cis-1,2-diaryl motif using a chiral amine and a mild reduction of amide using ZnEt/LiCl/(EtO)SiH system.

The 5-HT Descending Facilitation System Contributes to the Disinhibition of Spinal PKCγ Neurons and Neuropathic Allodynia via 5-HT Receptors.

Neuropathic pain, often featuring allodynia, imposes significant physical and psychological burdens on patients, with limited treatments due to unclear central mechanisms. Addressing this challenge remains a crucial unsolved issue in pain medicine. Our previous study, using protein kinase C gamma (PKCγ)-tdTomato mice, highlights the spinal feedforward inhibitory circuit involving PKCγ neurons in gating neuropathic allodynia.

Explainable attention-enhanced heuristic paradigm for multi-view prognostic risk score development in hepatocellular carcinoma.

Purpose: Existing prognostic staging systems depend on expensive manual extraction by pathologists, potentially overlooking latent patterns critical for prognosis, or use black-box deep learning models, limiting clinical acceptance. This study introduces a novel deep learning-assisted paradigm that complements existing approaches by generating interpretable, multi-view risk scores to stratify prognostic risk in hepatocellular carcinoma (HCC) patients.

Methods: 510 HCC patients were enrolled in an internal dataset (SYSUCC) as training and validation cohorts to develop the Hybrid Deep Score (HDS).

ESM1 suppresses LncRNA GAS5/miR-23a-3p/PTEN axis to promote the cisplatin-chemotherapy resistance of ovarian cancer cells via activating the PI3K/AKT pathway.

Background: Cisplatin chemotherapy is an important treatment for advanced ovarian cancer (OC). However, the development of cisplatin resistance greatly limits the survival time of OC patients. Endothelial cell-specific molecule 1 (ESM1) has been found to be an important proto-oncogene promoting OC, but its mediating OC cisplatin resistance remains unknown.

Is Multiwavelength Photobiomodulation Effective and Safe for Age-Related Macular Degeneration? A Systematic Review and Meta-Analysis.

Introduction: This systematic review and meta-analysis compares the complications and effects of photobiomodulation (PBM) therapy with sham treatment in patients with age-related macular degeneration (AMD). AMD is a leading cause of visual impairment in older adults, with current treatments primarily focusing on symptom management. PBM therapy is emerging as a potential intervention to improve clinical and anatomical outcomes in patients with AMD, necessitating a comparative analysis with sham treatment to determine its efficacy and safety.

Identification of DIO2 as a Molecular Therapeutic Target for Depression in Chronic Rhinosinusitis: A Comprehensive Bioinformatics and Experimental Study.

Chronic rhinosinusitis (CRS) and depression are both common conditions with significant socioeconomic impact. The high co-occurrence of depression in CRS patients suggests a common pathophysiology, but the mechanisms are unclear. This study aimed to identify potential molecular links between the two conditions.

Population transcriptome reveals genetic divergence and expression diversity of medicinally effective ingredients-related genes for Rheum palmatum complex derived from the top-geoherb area.

The study revealed genetic diversity and moderate differentiation among the R. palmatum complex within the top-geoherb area. RNA-seq-derived SNP datasets hold the potential to trace geographic origins of the core germplasm.

Molecular docking and molecular dynamics simulations revealed interaction mechanism of acetylcholinesterase with organophosphorus pesticides and their alternatives.

Organophosphate pesticides (OPs) are widely used in agricultural fields and can inhibit the activity of human acetylcholinesterase (hAChE) by covalently binding to serine at the enzyme's active site. However, the molecular recognition mechanisms beyond their covalent binding remain unclear. This study employed molecular docking along with molecular dynamics simulations (MD) to investigate four representative OPs, Phosphamidon, Monocrotophos, Dichlorvos, and Trichlorfon, as well as two potential alternatives Magnolol (MAG) and Honokiol (HON), to understand the conformational change of hAChE and its molecular recognition mechanism.

Single-center clinical efficacy analysis of 16 cases of primary light chain cardiac amyloidosis including stage IIIb patients.

Objective: To investigate the clinical efficacy of daratumumab versus bortezomib in patients with systemic light chain amyloidosis (pAL) with cardiac involvement, particularly those at stage IIIb.

Methods: Retrospective analysis of 16 AL patients with cardiac involvement, two groups of patients received treatment primarily with bortezomib and daratumumab, respectively. The hematologic remission rate, cardiac response rate, survival and adverse reactions of the two groups were analyzed.

LncRNA CCAT1 decreases the sensitivity to doxorubicin in lung cancer cells by regulating miR-181a/CPEB2 axis.

Recently, long non-coding RNAs have gained an increasing amount of attention in treating lung cancer. However, a full understanding of how CCAT1 lncRNA works against proliferation is not yet available. Therefore, we assess the impact of CCAT1 on the lung cancer cell proliferation, apoptosis, and doxorubicin (DOX) sensitivity, and the involvement of miR-181a/CPEB2 pathway.