Semi-Supervised Medical Hyperspectral Image Segmentation Using Adversarial Consistency Constraint Learning and Cross Indication Network.

Hyperspectral imaging technology is considered a new paradigm for high-precision pathological image segmentation due to its ability to obtain spatial and spectral information of the detected object simultaneously. However, due to the time-consuming and laborious manual annotation, precise annotation of medical hyperspectral images is difficult to obtain. Therefore, there is an urgent need for a semi-supervised learning framework that can fully utilize unlabeled data for medical hyperspectral image segmentation.

UFPF: A Universal Feature Perception Framework for Microscopic Hyperspectral Images.

In recent years, deep learning has shown immense promise in advancing medical hyperspectral imaging diagnostics at the microscopic level. Despite this progress, most existing research models remain constrained to single-task or single-scene applications, lacking robust collaborative interpretation of microscopic hyperspectral features and spatial information, thereby failing to fully explore the clinical value of hyperspectral data. In this paper, we propose a microscopic hyperspectral universal feature perception framework (UFPF), which extracts high-quality spatial-spectral features of hyperspectral data, providing a robust feature foundation for downstream tasks.

Safety contributing factors analysis of older vulnerable road users: General and local perspectives.

Increasing attention to older people's traffic safety is necessary to understand the relationship between their traffic safety and contributing factors on a spatial scale. However, zero crashes exist at the analysis unit for some specific types of crashes, and few studies have considered the spatial heterogeneity between older people's crash frequency and the influencing variables. To fill these gaps, this study developed an analytic approach to explore the effects of contributing factors for older vulnerable road users' (VRUs) crashes, with particular attention to the integration of general and local analysis.

Inversion of Biological Strategies in Engineering Technology: A Case Study of the Underwater Soft Robot.

Bio-inspired design, a paradigm-shifting methodology that translates evolutionary mechanisms into engineering solutions, has established itself as a cornerstone for pioneering innovation in multifaceted technological systems. Despite its promise, the inherent complexity of biological systems and interdisciplinary knowledge gaps hinder the effective translation of biological principles into practical engineering solutions. This study introduces a structured framework integrating large language models (LLMs) with a function-behavior-characteristic-environment (F-B-C-E) paradigm to systematize biomimetic design processes.

Formyl peptide receptor 1 and its antagonist T0080 in atherosclerosis.

Focal inflammation and arterial damage driven by macrophages are key pathogenic processes in atherosclerosis. However, the mechanisms that regulate these processes remain poorly understood. In this study, we demonstrate that formyl peptide receptor 1 (FPR1) agonist, a mitochondrial N-formyl peptide, is elevated in the blood of patients with atherosclerosis and correlates with carotid stenosis.

Serum levels of galanin-like peptide and alarin are highly correlated with polycystic ovary syndrome.

To compare the levels of galanin-like peptide (GALP) and alarin between patients with polycystic ovary syndrome (PCOS) and a control group, and to explore the correlations between GALP/alarin and PCOS. We selected a total of 103 PCOS patients and 89 non-PCOS control patients who visited the hospital during the same period. The PCOS patients and the controls were assigned by body mass index (BMI) into PCOS subgroup 1 and control subgroup 1 (18.

Cost Shifting in Lung Cancer Inpatient Care Under Diagnosis-Intervention Packet Reform: A Pilot Study in China.

Purpose: China has developed and widely implemented an innovative case-based payment method for inpatient services under a regional global budget, termed the "Diagnosis-Intervention Packet" (DIP). This study aims to examine cost-shifting behaviour in lung cancer inpatient care under the DIP reform.

Methods: This study examines the impact of the DIP reform in Zunyi, a national pilot city, using double machine learning (DML).

Optimal conditions for sampling of blood cytokine tests using AimPlex flow cytometry.

Objectives: Quantification of cytokine is indispensable to elucidate the mechanism of immune regulation at the molecular level, thereby contributing to the diagnosis and treatment of several diseases. Here, we aimed to determine the effect of detection method and storage conditions of specimens on the quantification of cytokine levels.

Methods: We used four vacuum blood collection tubes containing EDTA, heparin, clot activator, gel and compared the changes in the expression levels of 14 cytokines in serum and plasma samples at different temperatures and durations of storage using AimPlex flow cytometry-based immunoassay.

Labor epidural analgesia among Han and Uyghur parturients: a prospective observational study in China.

Background: Disparities in pain sensitivity and tolerance have been described, however little is known about variability in the experience of labor pain and childbirth in China.

Methods: This prospective observational study was conducted at a tertiary hospital in Xinjiang, China with two major ethnic groups: Han and Uyghur women. Women with a vaginal delivery with labor epidural analgesia were enrolled.

Does vertical integration increase the costs for primary care inpatients? Evidence from a national pilot programme in China.

Objective: To assess the impact of vertical integration (VI) within County-Level Integrated Health Organisations (CIHOs) on the costs of primary care inpatients.

Methods: This study assessed Xishui, a national pilot county for CIHOs, using inpatient claims data. The treatment group comprised 10,118 inpatients from 5 vertically integrated township health centres (THCs), while the control group consisted of 21,165 inpatients from 19 non-vertically integrated THCs.

Proteomics analysis of immune response-related proteins in Guillain-Barré Syndrome (GBS) and Chronic Inflammatory Demyelinating Polyneuropathy (CIDP).

The objective is to characterize differentially expressed proteins (DEPs) in Guillain-Barré Syndrome (GBS) and Chronic Inflammatory Demyelinating Polyneuropathy (CIDP) through high-throughput analysis. Sera from 11 healthy controls (HCs), 21 GBS and 19 CIDP patients were subjected to Olink Proteomics Analysis. In the comparison between CIDP and GBS groups, up-regulation of ITM2A and down-regulation of NTF4 were observed.

Deep learning-based hyperspectral technique identifies metastatic lymph nodes in oral squamous cell carcinoma-A pilot study.

Aims: To establish a system based on hyperspectral imaging and deep learning for the detection of cancer cells in metastatic lymph nodes.

Main Methods: The continuous sections of metastatic lymph nodes from 45 oral squamous cell carcinoma (OSCC) patients were collected. An improved ResUNet algorithm was established for deep learning to analyze the spectral curve differences between cancer cells and lymphocytes, and that between tumor tissue and normal tissue.

miR-34b-5p suppresses the epithelial-mesenchymal transition and metastasis in endometrial cancer AN3CA cells by targeting .

Objectives: Tumor metastasis is a primary cause of recurrence and mortality in endometrial cancer. miR-34b-5p is abnormally expressed in various cancers and participates in tumor cell progression and metastasis. The objective of this study was to elucidate the biological functions and molecular mechanisms of miR-34b-5p in regulating the epithelial-mesenchymal transition (EMT) and metastasis in AN3CA endometrial cancer cells.

Interferon-induced transmembrane protein-1 competitively blocks Ephrin receptor A2-mediated Epstein-Barr virus entry into epithelial cells.

Epstein-Barr virus (EBV) can infect both B cells and epithelial cells (ECs), causing diseases such as mononucleosis and cancer. It enters ECs via Ephrin receptor A2 (EphA2). The function of interferon-induced transmembrane protein-1 (IFITM1) in EBV infection of ECs remains elusive.

FD-Net: Feature Distillation Network for Oral Squamous Cell Carcinoma Lymph Node Segmentation in Hyperspectral Imagery.

Oral squamous cell carcinoma (OSCC) has the characteristics of early regional lymph node metastasis. OSCC patients often have poor prognoses and low survival rates due to cervical lymph metastases. Therefore, it is necessary to rely on a reasonable screening method to quickly judge the cervical lymph metastastic condition of OSCC patients and develop appropriate treatment plans.

Analysis of cellular response to drugs with a microfluidic single-cell platform based on hyperspectral imaging.

Background: Cellular response to pharmacological action of drugs is significant for drug development. Traditional detection method for cellular response to drugs normally rely on cell proliferation assay and metabolomics examination. In principle, these analytical methods often required cell labeling, invasion analysis, and hours of co-culture with drugs, which are relatively complex and time-consuming.

Study on spatiotemporal dynamic characteristics of precipitation and causes of waterlogging based on a data-driven framework.

The discernible alterations in regional precipitation patterns, influenced by the intersecting factors of urbanization and climate change, exert a substantial impact on urban flood disasters. Based on multi-source precipitation data, a data-driven model fusion framework was constructed to analyze the spatial and temporal dynamic distribution characteristics of precipitation in Beijing. Wavelet analysis method was used to reveal the periodic variation characteristics and multi-scale effects of precipitation, and the machine learning method was used to characterize the spatiotemporal dynamic change pattern of precipitation.

Multi-omics analysis of small RNA, transcriptome, and degradome to identify putative miRNAs linked to MeJA regulated and oridonin biosynthesis in Isodon rubescens.

Isodon rubescens has garnered much attention due to its anti-tumor or anti-cancer properties. However, little is known about the molecular mechanism of oridonin biosynthesis leveraging the regulatory network between small RNAs and mRNAs. In this study, the regulatory networks of miRNAs and targets were examined by combining mRNA, miRNA, and degradome.

A Diamond/Graphene/Diamond Electrode for Waste Water Treatment.

Boron-doped diamond (BDD) thin film electrodes have great application potential in water treatment. However, the high electrode energy consumption due to high resistance directly limits the application range of existing BDD electrodes. In this paper, the BDD/graphene/BDD (DGD) sandwich structure electrode was prepared, which effectively improved the conductivity of the electrode.

Genome resequencing reveals the evolutionary history of garlic reproduction traits.

The propagation of cultivated garlic relies on vegetative cloves, thus flowers become non-essential for reproduction in this species, driving the evolution of reproductive feature-derived traits. To obtain insights into the evolutionary alteration of reproductive traits in the clonally propagated garlic, the evolutionary histories of two main reproduction-related traits, bolting and flower differentiation, were explored by genome analyses using 134 accessions displaying wide diversity in these two traits. Resequencing identified 272.

A systematic approach to macro-level safety assessment and contributing factors analysis considering traffic crashes and violations.

During rapid urbanization and increase in motorization, it becomes particularly important to understand the relationships between traffic safety and risk factors in order to provide targeted improvements and policy recommendations. Violations and police enforcement are key variables, but the endogenous relationship between crashes and violations has made these variables unreliable and has limited their use. To manage this problem, this study developed a systematic approach for the joint modeling of crashes and violations to identify crash and violation hotspots and examine the mechanisms underlying macro-level contributing factors.