With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

Rhegmatogenous retinal detachment(RRD)is a vision-threatening ocular emergency with the potential risk of blindness. Pars plana vitrectomy(PPV)is the treatment of choice for RRD, especially for complex retinal detachments such as posterior pole retinal tears, grade B or higher proliferative vitreoretinopathy, and concomitant choroidal detachment. Although most patients achieve good anatomical restoration after surgery, some patients may still experience postoperative symptoms such as distorted vision, abnormal color perception, and lack of improvement in corrected visual acuity. Epiretinal membranes(ERM), as one of the most common complications after RRD, occur in 4% to 13% of cases, which not only affect the recovery of patients' postoperative vision, but also are frequently associated with visual distortion. In severe cases, a second surgical intervention may be required. In recent years, internal limiting membrane peeling(ILMP)has been introduced as an adjunctive procedure in the treatment of RRD, to facilitate retinal reorientation, reduce postoperative complications, and improve patients' postoperative visual quality and quality of life. However, previous studies on the effects of combined intraoperative ILMP on retinal anatomy and visual function recovery are limited. Therefore, this article reviews the mechanism, clinical application, challenges and research progress of ILMP in RRD, providing a reference for surgical decision making, disease assessment, and prognosis evaluation.

To investigate the impact of mild-to-moderate frailty on the long-term prognosis of hospitalized elderly patients with type 2 diabetes mellitus(T2DM).

A complete plant body consists of elements on different scales, including microscopic molecules, mesoscopic multicellular structures, and macroscopic tissues and organs, which are interconnected to form complex biological networks. The growth and development of plants involve the regulation of elements on different scales and their biological networks, which requires the coordinated operation of multiple molecules, cells, tissues, and organs. It is difficult to reveal the essence of multi-level life activities by a single method or technology. In recent years, the development of various novel imaging technologies has provided new approaches for revealing the complex life activities in plants. Using multi-modal imaging technologies to study the cross-scale network connections of plants from the microscopic, mesoscopic, and macroscopic levels is crucial for understanding the complex internal connections behind biological functions. This paper first summarizes multi-modal cross-scale imaging technologies, three-dimensional reconstruction, and image processing methods, outlines the basic framework of cross-scale network connection properties, and then summarizes the applications of multi-modal imaging technologies in elucidating plant multi-scale networks. Finally, this review systematically integrates the combined analysis of cross-scale 3D spatial structural data and single-cell omics, laying a theoretical foundation for the innovation of novel plant imaging technologies. Furthermore, it provides a new research paradigm for in-depth exploration of the interaction mechanisms among cross-scale elements and the principles of biological network connectivity in plant life activities.
Plants/metabolism* ; Imaging, Three-Dimensional/methods* ; Image Processing, Computer-Assisted/methods* ; Multimodal Imaging/methods* ; Plant Physiological Phenomena

Large language models (LLMs), represented by ChatGPT, have garnered significant attention due to their powerful capabilities in understanding and generating human language. Research on the application of LLMs across various medical tasks has shown a vigorous development trend. This review aims to outline the development and clinical applications of LLMs, with a focus on the primary tasks of medical intelligent assistants, including their associated opportunities and challenges. At the technical level, we provide a detailed explanation of the architecture and training processes of existing medical LLMs, and summarize the general technical steps for adapting large models to the healthcare domain. At the application level, we introduce the main tasks of medical intelligent assistants from both healthcare provider- and patient-oriented perspectives, andcompare the performance of different LLMs across various medical tasks to illustrate their unique advantages and limitations in medical applications.

Objective To explore the clinical effect of applying an improved"outside-in"technique in hip arthroscopic surgery.Methods Totally 136 patients undergoing hip arthroscopic surgery between June 2021 and July 2023 were selected and studied retrospectively.According to their different surgi-cal approach,they were divided into a modified approach group(n=75,including 30 males and 45 fe-males,with an average age of 36±14)and a classic approach group(n=61,including 33 males and 28 females,with an average age of 31±11).Before as well as 4 weeks,3 months and 6 months after the surgery,both groups were evaluated using the visual analog scale(VAS)and Harris hip score,and observed their surgical complications.Moreover,the surgical outcomes and time of sur-gical approach establishment were compared between the two groups.Results There was no significant difference between the two groups in general information,preoperative VAS and Harris scores.More-over,no significant difference was found between the two groups in the Harris score after surgery.Compared with the classic approach group,the improved group had significantly less surgical time(49.0±16.9 min vs.66.0±13.3 min,P<0.05),without using the C-arm fluoroscopy during surgery.Moreover,in the modified approach group,the time for establishing the mid-anteriorapproach was sig-nificantly shortened(10.4±5.9 min vs.25.9±15.1 min,P<0.05),along with the traction time during surgery(66.0±13.3 min vs.49.0±16.9 min,P<0.05).Conclusion The modified"outside-in"hip ar-throscopy technique is a safe and effective surgical method,easier to operate,with shorter surgical time.

Alzheimer's disease (AD) is characterized by cognitive and functional deterioration, with pathological features such as amyloid-beta (Aβ) aggregates in the extracellular spaces of parenchymal neurons and intracellular neurofibrillary tangles formed by the hyperphosphorylation of tau protein. Despite a thorough investigation, current treatments targeting the reduction of Aβ production, promotion of its clearance, and inhibition of tau protein phosphorylation and aggregation have not met clinical expectations, posing a substantial obstacle in the development of drugs for AD. Recently, artificial intelligence (AI), computational biology (CB), and systems biology (SB) have emerged as promising methodologies in AD research. Their capacity to analyze extensive and varied datasets facilitates the identification of intricate patterns, thereby enriching our comprehension of AD pathology. This paper provides a comprehensive examination of the utilization of AI, CB, and SB in the diagnosis of AD, including the use of imaging omics for early detection, drug discovery methods such as lecanemab, and complementary therapies like phototherapy. This review offers novel perspectives and potential avenues for further research in the realm of translational AD studies.

OBJECTIVES: To investigate the causal associations between autoimmune diseases and aplastic anemia (AA) using Mendelian randomization analysis. METHODS: Publicly available genome-wide association study (GWAS) data were utilized to obtain single nucleotide polymorphisms (SNPs) associated with autoimmune diseases and AA for analysis. The inverse variance weighted (IVW) method was employed as the primary analytical approach, with MR Egger, Weighted Mode, Weighted Median, and Simple Mode methods serving as complementary analyses. Heterogeneity and pleiotropy analyses were conducted using designated functions, and the robustness of Mendelian randomization results was assessed using leave-one-out analysis. RESULTS: The two-sample Mendelian randomization analysis using the IVW method revealed significant positive causal associations of rheumatoid arthritis (OR=1.094, 95% CI: 1.023-1.170, P=0.009, adjusted P=0.042), systemic lupus erythematosus (OR=1.111, 95% CI: 1.021-1.208, P=0.015, adjusted P=0.036), Hashimoto thyroiditis (OR=1.206, 95% CI: 1.049-1.387, P=0.009, adjusted P=0.029), and Sicca syndrome (OR=1.173, 95% CI: 1.054-1.306, P=0.004, adjusted P=0.035) with AA, which was supported by the results from the Weighted Median method. Sensitivity analyses indicated no evidence of pleiotropy or heterogeneity, and leave-one-out analysis confirmed the robustness of the causal relationships. No direct evidence was found linking Graves' disease, ulcerative colitis, Crohn's disease, autoimmune hepatitis, primary biliary cholangitis, or primary sclerosing cholangitis with AA (P>0.05, adjusted P>0.05), indicating a lack of causal association. Reverse Mendelian randomization results and multiple corrections indicated that AA was not an influencing factor for autoimmune diseases (adjusted P>0.05). CONCLUSIONS Our findings support at the genetic level that rheumatoid arthritis, systemic lupus erythematosus, Hashimoto thyroiditis, and Sicca syndrome are risk factors for AA, and confirm a causal association of the these 4 autoimmune diseases with an increased risk of AA.
Humans ; Mendelian Randomization Analysis ; Anemia, Aplastic/genetics* ; Autoimmune Diseases/complications* ; Polymorphism, Single Nucleotide ; Genome-Wide Association Study ; Arthritis, Rheumatoid/genetics* ; Lupus Erythematosus, Systemic/genetics* ; Genetic Predisposition to Disease

Deactivation of the mitochondrial pyruvate dehydrogenase complex (PDC) is important for the metabolic switching of cancer cell from oxidative phosphorylation to aerobic glycolysis. Studies examining PDC activity regulation have mainly focused on the phosphorylation of pyruvate dehydrogenase (E1), leaving other post-translational modifications largely unexplored. Here, we demonstrate that the acetylation of Lys 488 of pyruvate dehydrogenase complex component X (PDHX) commonly occurs in hepatocellular carcinoma, disrupting PDC assembly and contributing to lactate-driven epigenetic control of gene expression. PDHX, an E3-binding protein in the PDC, is acetylated by the p300 at Lys 488, impeding the interaction between PDHX and dihydrolipoyl transacetylase (E2), thereby disrupting PDC assembly to inhibit its activation. PDC disruption results in the conversion of most glucose to lactate, contributing to the aerobic glycolysis and H3K56 lactylation-mediated gene expression, facilitating tumor progression. These findings highlight a previously unrecognized role of PDHX acetylation in regulating PDC assembly and activity, linking PDHX Lys 488 acetylation and histone lactylation during hepatocellular carcinoma progression and providing a potential biomarker and therapeutic target for further development.
Humans ; Acetylation ; Carcinoma, Hepatocellular/genetics* ; Liver Neoplasms/genetics* ; Pyruvate Dehydrogenase Complex/genetics* ; Gene Expression Regulation, Neoplastic ; Animals ; Mice ; Cell Line, Tumor ; Protein Processing, Post-Translational ; Histones/metabolism* ; Disease Progression

ObjectiveTo investigate the whole genomic characteristics and phylogenetic relationships of clinical isolates of enteroaggregative Escherichia coli (EAEC) in diarrhea outpatients in Pudong New Area, Shanghai. MethodsBased on the diarrheal disease surveillance network in Pudong New Area, Shanghai, whole-genome sequencing was performed on a total of 55 EAEC strains isolated from fecal samples of the diarrhea outpatients from January 2015 to December 2019. The genome analyses based on raw sequencing data encompassed genome size, coding genes, dispersed repeat sequences, genomic islands, and protein coding regions, and pan-genome analyses were conducted simultaneously. Contigs sequences assays were performed to analyze molecular characteristics including serotypes, antibiotic resistance genes, and virulence factors. The phylogenetic clusters and multilocus sequence typing (MLST) were identified, and a phylogenetic tree was constructed. ResultsEAEC exhibited an open pan-genome. The predominant serotype of EAEC in diarrhea outpatients in Pudong New Area was O130:H27, and the carriage rate of β-lactam resistance genes was the highest (67.27%, 37/55). A total of 29 virulence factors and 106 virulence genes were identified, phylogenic group B1 was the predominant group, and clonal group CC31 was the dominant clonal group. The strain distribution was highly heterogeneous. ConclusionThe genomic characteristics of EAEC displayed significant strain polymorphism. It is necessary to develop effective strategies for differential diagnosis and improve detection capabilities for infection with EAEC of different serotypes and genotypes.