Anastomotic Leakage and Gastroparesis Syndrome Following Laparoscopic Radical Gastrectomy: A Retrospective Cohort Study Involving 3779 Patients.

Background And Objectives: The occurrence of anastomotic leakage (AL) and gastroparesis syndrome (GS), common and severe complications after laparoscopic radical gastrectomy, significantly impacts the prognosis of patients. The objective of this study was to investigate the risk factors associated with AL after laparoscopic radical gastrectomy and GS after laparoscopic distal gastrectomy.

Methods: In this retrospective cohort study, 3779 patients who underwent laparoscopic radical gastrectomy and met the inclusion criteria were included.

Collectin-11 promotes fibroblast proliferation and modulates their activation status and extracellular matrix synthesis.

Introduction: Collectin-11 (CL-11), a recently described soluble C-type lectin, has been shown to stimulate cell proliferation in fibroblasts and melanoma cells. However, its broader influence on fibroblast functions and the specific receptors mediating CL-11's effects remain to be elucidated.

Methods: The EDU proliferation assay and WB detection of PCNA protein levels were used to evaluate the fibroblast proliferative effect after CL-11 stimulated.

AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations.

Recent applications of artificial intelligence (AI) and machine learning in medicine, psychology, and social sciences have led to common terminological confusions. In this paper, we review emerging evidence from systematic reviews documenting widespread misuse of key terms, particularly "prediction" being applied to studies merely demonstrating association or retrospective analysis. We clarify when "prediction" should be used and recommend using "prospective prediction" for future prediction; explain validation procedures essential for model generalizability; discuss overfitting and generalization in machine learning and traditional regression methods; clarify relationships between features, independent variables, predictors, risk factors, and causal factors; and clarify the hierarchical relationship between AI, machine learning, deep learning, large language models, and generative AI.

Programmable conformal transluminal ablation device for irregular remote small lesions.

Development of micro-surgical robotic and high-resolution navigation techniques has enabled reach of micro-lesions . However, the small size, special shape, and location of these lesions make conformal treatment a challenge, especially for atherosclerotic lesion. A programmable conformal transluminal ablation device, including multi-channel and multi-level (MCML) radiofrequency (RF) system and RF balloon with circulating low-temperature flow inside, was designed to realize treatment for irregular remote lesions automatically.

Leveraging large language models for automated depression screening.

Mental health diagnoses possess unique challenges that often lead to nuanced difficulties in managing an individual's well-being and daily functioning. Self-report questionnaires are a common practice in clinical settings to help mitigate the challenges involved in mental health disorder screening. However, these questionnaires rely on an individual's subjective response which can be influenced by various factors.

Correction: Using Wearable Devices and Speech Data for Personalized Machine Learning in Early Detection of Mental Disorders: Protocol for a Participatory Research Study.

[This corrects the article DOI: 10.2196/48210.].

Synergistic roles of NFATc1 and c-Jun in immunomodulation.

The immune system relies on precise regulatory mechanisms, with transcription factors being central to modulating immune responses. NFATc1 and c-Jun are key transcription factors that influence both adaptive and innate immunity. This review provides a comprehensive examination of the individual and synergistic roles of NFATc1 and c-Jun in immune regulation.

The combination of nitrogen fertilizers and EDDS enhances remediation efficiency of Bidens pilosa L. in Cd-contaminated soils.

Biodegradable chelating agents and nitrogen (N) fertilizers are widely used for the remediation of heavy metal-contaminated soils due to their ability to promote plant growth, enhance metal mobility and facilitate plant uptake. In this study, a pot experiment was conducted to investigate the effects of nitrate nitrogen (N-NO), ammonium nitrogen (N-NH) and amide nitrogen (N-amide) with different concentrations of 25, 50 and 75 mg N·kg combined with (S,S)-ethylenediaminedisuccinic acid (EDDS) (1 mmol·L) on growth, biomass and phytoextraction efficiency of Bidens. pilosa L.

A Rare Case Report of an Adult With Intraspinal Gouty Stones and Concurrent Knee Joint Involvement.

This case highlights the importance of considering spinal gout in patients with hyperuricemia presenting with atypical back pain or neurological symptoms. Multidisciplinary surgical management, including decompression and joint arthroscopy, combined with urate-lowering therapy and lifestyle modifications, can achieve significant symptom relief and prevent disease recurrence.

Drought-activated BZR1 reprograms flavonoid metabolism via transcriptional cascades to amplify baicalin biosynthesis in Scutellaria baicalensis.

Environmental stress triggers a dual response in medicinal plants by inhibiting growth while enhancing secondary metabolite production. However, the regulatory mechanism of this trade-off remains unclear. Here, we identified SbBZR1 as a brassinosteroid (BR)-responsive transcription factor that orchestrates drought resilience and baicalin biosynthesis in Scutellaria baicalensis through integrated multi-omics and metabolic flux analysis.

Mo-P bond-induced MoS fast electron transfer improves the lithium storage performance of MoS-MoP heterojunction.

Mo-based hybrids, including molybdenum oxide, molybdenum sulfide, and molybdenum carbide, have been extensively investigated as anode materials for lithium-ion batteries (LIBs) due to their high theoretical electrochemical capacities compared to conventional carbon materials. However, molybdenum phosphide, which shows great promise as an anode material for LIBs, has been scarcely investigated to date. In this paper, two-dimensional (2D) mesoporous ultrasmall MoS-MoP heterostructured nanosheets/graphene hybrids (meso-MoS-MoP/G) were synthesized using a "nanocasting" method followed by a phosphidation treatment.

[One case of eustachian tube hairy polyp was removed by microscope combined with endoscope].

This paper reports the diagnosis and treatment of a child with eustachian hairy polyp. The patient was a female, aged 1 year and 4 months, and visited our clinic due to "intermittent purulent discharge of the left ear, nasal congestion and sleep snoring for 1 year". Preoperative endoscopic examination found white masses at the posterior part of the nasal cavity on both sides.

Suffering in silence: Accessing mental health care and repetitive transcranial magnetic stimulation (rTMS) for peripartum depression - A qualitative study.

Peripartum depression (PPD) is a prevalent and serious mental health disorder that is often underdiagnosed and undertreated due to limited effective and safe treatment options. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a non-invasive treatment for PPD, yet awareness among patients is low. This study aims to identify barriers and facilitators to accessing mental health treatment, particularly rTMS, for PPD.

An air target intention data extension and recognition model based on deep learning.

As the core part of battlefield situational awareness, air target intention recognition plays an important role in modern air operations. Aiming at the problems of data scarcity and insufficient temporal feature extraction in the process of air target intention recognition, an air target intention data extension and recognition model based on Deep Learning named IDERDL is proposed, where ID denotes intention data, E denotes data extension, R denotes intention recognition, and DL denotes deep learning. The model mainly consists of two parts: intention data generation and intention recognition.

Population-level individualized prospective prediction of opioid overdose using machine learning.

The opioid overdose epidemic has rapidly expanded in North America, with rates accelerating during the COVID-19 pandemic. No existing study has demonstrated prospective opioid overdose at a population level. This study aimed to develop and validate a population-level individualized prospective prediction model of opioid overdose (OpOD) using machine learning (ML) and de-identified provincial administrative health data.

MZT1 protects gastric cancer against glucose starvation through targeting NEDD1.

A fasting mimic diet (FMD) has been proven to be a potential therapeutic regimen for gastric cancer (GC) patients. However, the intolerance of energy restriction and limited efficacies hinder wide application of FMD. To identify critical targets mediating resistance against glucose starvation and explore novel approaches to GC therapy, proteomics profiling was performed to depict the landscape of protein expression changes in cells under glucose deprivation.

Brassinosteroid-related transcription factor BZR1 regulates vegetative development and flavonoids biosynthesis in Scutellaria baicalensis.

Scutellaria baicalensis Georgi is a traditional Chinese medicine known for its flavonoid and polysaccharide content, which offers significant pharmacological effects. However, the molecular mechanisms governing the biosynthesis of these phytochemicals are not fully understood. Here, we first identified the transcription factor BZR1 (~36 kDa) within the brassinosteroid (BR) pathway as a key regulator of active compound biosynthesis in S.

Exploring Mechanisms of Ephx2 in Treating Atherosclerosis Using Independent Cascade Model and Adverse Outcome Pathways.

Background: Atherosclerosis (AS) is a leading cause of cardiovascular diseases, characterized by lipid accumulation in arterial walls. The enzyme Ephx2 (soluble epoxide hydrolase, sEH) is implicated in AS development, but its precise mechanisms and therapeutic potential are not fully understood.

Objectives: This study aimed to analyze gene expression data from low-density lipoprotein receptor knockout (LDLR⁸/⁸) and LDLR⁸/⁸sEH⁸/⁸ mice to identify significant genes associated with AS.

Validating the effectiveness of a classroom-setting form of early clinical exposure with direct physician involvement in gastrointestinal physiology education.

Background: Early clinical exposure (ECE) represents one form of vertical integration that bridges the gap between the early theoretical years and the clinical practicing years in undergraduate medical education. In most medical colleges in China, the complex healthcare system and large-enrollment classes pose significant challenges for implementing ECE in a hospital setting. However, there is a paucity of data comprehensively demonstrating the effectiveness of a classroom-setting form of ECE with direct physician involvement in physiology education.

[Effects of Exogenous NO Combined with EDDS on Growth and Cd Accumulation of under Soil Cd Stress Conditions].

Under 40 mg·kg Cd stress, pot experiments were conducted to investigate the effects of 0.05, 0.10, 0.

Small molecule carbon sources drivers increase in heavy metal passivation during chicken manure composting by regulating microbial functional and metabolic pattern.

The application of compost products to the soil impacts the soil microenvironment. Optimize the composting process is essential to minimize potential harm to the soil. This research aims to explore the effects of small molecular carbon source (SMCS) additives on the transformation of heavy metal (HM) fractions, bacterial community structure and metabolism functions to better comprehend the degradation of organic compounds and HM passivation during composting.

Cross-population tongue image features and tongue coating microbiome changes in the evolution of colorectal cancer.

Introduction: Tongue diagnosis, a cornerstone of Traditional Chinese Medicine (TCM), relies significantly on the assessment of tongue coating, which is used to evaluate Zang-fu organ functions, qi and blood dynamics, and the influence of pathogenic factors. This diagnostic method is integral to disease diagnosis and treatment in TCM. Recent research suggests a strong correlation between the characteristics of tongue coating and its microbial composition.

Preoperative prediction of the Lauren classification in gastric cancer using automated nnU-Net and radiomics: a multicenter study.

Objectives: To develop and validate a deep learning model based on nnU-Net combined with radiomics to achieve autosegmentation of gastric cancer (GC) and preoperative prediction via the Lauren classification.

Methods: Patients with a pathological diagnosis of GC were retrospectively enrolled in three medical centers. The nnU-Net autosegmentation model was developed using manually segmented datasets and evaluated by the Dice similarity coefficient (DSC).

A rare case of unexplained recurrent intracerebral haemorrhage.

Recurrent intracerebral haemorrhage (ICH) presents a complex clinical challenge that eludes traditional diagnostic and treatment approaches. We report a rare and unexplained case of a middle-aged patient with recurrent ICH, for which extensive multidisciplinary investigations have yet to provide a definitive diagnosis or an effective long-term treatment strategy. Intraoperative pathology, genetic testing, cerebral angiography, inflammatory markers (erythrocyte sedimentation rate, C-reactive protein), specific antibodies (ANCA, anti-nuclear antibodies), and immunoglobulin levels showed no specific positive findings.