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Inflammatory bowel disease (IBD) is a chronic autoimmune disorder stemming from unrestrained immune activation and subsequent destruction of colon tissue. Genetic susceptibility, microbiota remodeling, and environmental cues are involved in IBD pathogenesis. Up to now, there are limited treatment options for IBD, so better therapies for IBD are eagerly needed. The therapeutic effects of naturally occurring compounds have been extensively investigated, among which quercetin becomes an attractive candidate owing to its unique biochemical properties. To facilitate the clinical translation of quercetin, we aimed to get a comprehensive understanding of the cellular and molecular mechanisms underlying the anti-IBD role of quercetin. We summarized that quercetin exerts the anti-IBD effect through consolidating the intestinal mucosal barrier, enhancing the diversity of colonic microbiota, restoring local immune homeostasis, and restraining the oxidative stress response. We also delineated the effect of quercetin on gut microbiome and discussed the potential side effects of quercetin administration. Besides, quercetin could serve as a prodrug, and the bioavailability of quercetin is improved through chemical modifications or the utilization of effective drug delivery systems. Altogether, these lines of evidence hint the feasibility of quercetin as a candidate compound for IBD treatment.

Four hundred myopic children randomly received atropine 0.02% (n = 138) or 0.01% (n = 142) in both eyes once-nightly or only wore single-vision spectacles (control group) (n = 120) for 2 years. Spherical equivalent refractive error (SER), axial length (AL), pupil diameter (PD), and amplitude of accommodation (AMP) were measured every 4 months. After 2 years, the SER changes were − 0.80 (0.52) D, − 0.93 (0.59) D and − 1.33 (0.72) D and the AL changes were 0.62 (0.29) mm, 0.72 (0.31) mm and 0.88 (0.35) mm in the 0.02% and 0.01% atropine groups and control group, respectively. There were significant differences between changes in SER and AL in the three groups (all P  < 0.001). The changes in SER and AL in the 2nd year were similar to the changes in the 1st year in the three groups (all P  > 0.05). From baseline to 2 years, the overall decrease in AMP and increase in PD were not significantly different in the two atropine groups, whereas the AMP and PD in the control group remained stable (all P  > 0.05). 0.02% atropine had a better effect on myopia control than 0.01% atropine, and its effects on PD and AMP were similar to 0.01% atropine. 0.02% or 0.01% atropine controlled myopia progression and AL elongation synchronously and had similar effects on myopia control each year.

Abstract Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. With their exceptional long-context reasoning capabilities, LLMs are proficient in clinically relevant tasks, particularly in medical text analysis and interactive dialogue. They can enhance diagnostic accuracy by processing vast amounts of patient data and medical literature and have demonstrated their utility in diagnosing common diseases and facilitating the identification of rare diseases by recognizing subtle patterns in symptoms and test results. Building on their image-recognition abilities, multimodal LLMs (MLLMs) show promising potential for diagnosis based on radiography, chest computed tomography (CT), electrocardiography (ECG), and common pathological images. These models can also assist in treatment planning by suggesting evidence-based interventions and improving clinical decision support systems through integrated analysis of patient records. Despite these promising developments, significant challenges persist regarding the use of LLMs in medicine, including concerns regarding algorithmic bias, the potential for hallucinations, and the need for rigorous clinical validation. Ethical considerations also underscore the importance of maintaining the function of supervision in clinical practice. This paper highlights the rapid advancements in research on the diagnostic and therapeutic applications of LLMs across different medical disciplines and emphasizes the importance of policymaking, ethical supervision, and multidisciplinary collaboration in promoting more effective and safer clinical applications of LLMs. Future directions include the integration of proprietary clinical knowledge, the investigation of open-source and customized models, and the evaluation of real-time effects in clinical diagnosis and treatment practices.

Three hundred and twenty-eight myopic children, randomized to use either 0.01% (N = 166) or 0.02% (N = 162) atropine were enrolled in this study. Gender, age, body mass index(BMI), parental myopia status, atropine concentration used, pupil diameter, amplitude of accommodation, spherical equivalent refractive error (SER), anterior chamber depth (ACD) and axial length (AL) were collected at baseline and 1 year after using atropine. Rapid AL elongation was defined as > 0.36 mm growth per year. Univariate analyses showed that children with rapid AL elongation tend to be younger, have a smaller BMI, use of 0.01% atropine, narrow ACD, lower SER, shorter AL, smaller change in pupil diameter between 1 year and baseline (all P < 0.05). Multivariate logistic regression analyses confirmed that rapid AL elongation was associated with children that were younger at baseline ( P  < 0.0001), use of 0.01% atropine (P = 0.04), a shorter baseline AL (P = 0.03) and a smaller change in pupil diameter between 1 year and baseline ( P  = 0.04). Younger children with shorter AL at baseline, less change in their pupil diameter with atropine treatment and using the lower of the two atropine concentrations may undergo rapid AL elongation over a 12 months myopia control treatment period.

Recent studies have found that the items retained in visual working memory (VWM) regulate the time required to access visual consciousness. However, this finding obtained from manmade stimuli may not applicable to real-world objects, as objects in real life are typically connected meaningfully. We used breaking continuous flash suppression ( b-CFS) and intermixed a delayed match-to-sample task to determine whether manmade and real-world representations in VWM differentially regulate priority for accessing visual consciousness, to determine whether VWM retains manmade and real-world objects at different representational levels. The results found that when the stimulus was congruent with manmade items in VWM, the stimulus was detected faster than the memory-incongruent stimulus, whereas the memory-incongruent stimulus was detected faster than the memory-congruent stimulus for the real-world objects. These findings suggest that VWM regulates conscious perception at the feature level for manmade stimuli and at the object-identity level for real-world stimuli, highlighting the hierarchical nature of representational processing in conscious access.

Background The prenatal test of cell-free fetal DNA (cffDNA) is also known as noninvasive prenatal testing (NIPT) with high sensitivity and specificity. This study is to evaluate the performance of NIPT and its clinical relevance with various clinical indications. Methods A retrospective analysis was conducted on 14,316 pregnant women with prenatal indications, including advanced maternal age (≥35 years), maternal serum screening abnormalities, the thickened nuchal translucency (≥2.5 mm) and other ultrasound abnormalities, twin pregnancy/IVF-ET pregnancy, etc. The whole-genome sequencing (WGS) of maternal plasma cffDNA was employed in this study. Results A total of 189 (1.32%) positive NIPT cases were identified, and 113/189 (59.79%)cases were confirmed by invasive prenatal testing. Abnormal serological screening (53.14%) was the most common indication, followed by elderly pregnancy (23.02%). The positive prediction value for T21, T18, T13, sex chromosome abnormalities, other autosomal aneuploidy abnormalities, and CNV abnormalities were 91.84, 68.75,37.50, 66.67, 14.29, and 6.45%, respectively. The positive rate and the true positive rate of nuchal translucency (NT) thickening were the highest (4.17 and 3.33%), followed by the voluntary requirement group (3.49 and 1.90%) in the various prenatal screening indications. The cffDNA concentration was linearly correlated with gestational age (≥10 weeks) and the positive NIPT group’s Z-score values. Conclusions whole-genome sequencing of cffDNA has extremely high sensitivity and specificity for T21, high sensitivity for T18, sex chromosome abnormalities, and T13. It also provides evidence for other abnormal chromosomal karyotypes (CNV and non-21/18/13 autosomal aneuploidy abnormalities). The cffDNA concentration is closely related to the gestational age and determines the specificity of NIPT. Our results highlight NIPT’s clinical significance, which is an effective prenatal screening tool for high-quality care of pregnancy. Highlights The whole-genome sequencing of cell-free fetal DNA from maternal plasma is an effective prenatal screening tool for pregnancies with various prenatal indications. The concentration of cffDNA was linear with gestational age and the Z-score values of the positive NIPT group. NIPT has a significant positive predictive value for pregnancies with prenatal indications.

The charging policy of pharmacy intravenous admixture service (PIVAS) is not merely a minor \"billing issue\" confined to individual hospitals, but rather a critical component that impacts the safety, efficiency, equity, and long-term sustainability of the national healthcare system. Its implications extend across patients, medical institutions, the pharmaceutical industry, and even the broader public health landscape. To establish a foundation for the national charging standard of intravenous admixture service, this study comprehensively investigated and analyzed the operational costs and current charging policies of PIVAS across 30 provinces in China. Questionnaires were distributed through the \"Wenjuan Xing\" platform from May 6th to 1 July 2022. After data generation and export by the platform, statistical and descriptive analyses of the questionnaire results were conducted using statistical software, including EXCEL, SPSS. A total of 761 PIVAS surveyed, 91.59% were affiliated with the pharmacy department, while 6.70% belonged to the hospital independent department. Most PIVAS strongly agreed with imposing fees, while most tertiary hospitals agreed that dispensing fees should be categorized based on hospital levels; however, most secondary hospitals disagreed. Approximately 60.58% of PIVAS have implemented a charging system which allows charges after inspection and evaluation. Regarding changes for different drugs nationwide, common drugs had an average charge standard of 4.39 yuan per bag while antibacterial drugs averaged 5.01 yuan per bag. Hazardous drugs had an average charge of 23.17 yuan per bag, whereas parenteral nutrition solutions averaged 38.75 yuan per bag. The annual operating cost of PIVAS in China was approximately RMB 2,098,100, with the integrated operating cost comprising 89.36% of the total, while dispensing cost accounted for only 10.64%. Human costs emerged as the highest annual consumption (74.20%), followed by facility maintenance (4.77%) and equipment acquisition costs (3.44%). The lack of a unified inspection and evaluation standard as well as charging standard in China is currently an urgent issue that needs to be addressed. The existing charging standard falls below the recommended level, thus it is necessary to develop a more reasonable and equitable charging standard that takes into account operational costs. This study can serve as an empirical reference for national medical insurance and health administration authorities in establishing unified regulatory standards and dynamic pricing adjustment mechanisms for PIVAS. It contributes to the transition of PIVAS from \"regionally fragmented management\" to \"nationally standardized operations,\" thereby supporting the dual objectives of enhancing healthcare service quality and optimizing the utilization efficiency of medical insurance funds.

The quantity, size, and distribution of non-metallic inclusions in High-Strength Low-Alloy (HSLA) steel critically influence its service performance. Conventional detection methods often fail to adequately characterize extreme inclusion distributions in large-section components. This study developed an integrated full-process inclusion analysis system combining high-precision motion control, parallel optical imaging, and laser spectral analysis technologies to achieve rapid and automated identification and compositional analysis of inclusions in meter-scale samples. Through systematic investigation across the industrial process chain—from a dia. 740 mm consumable electrode to a dia. 810 mm electroslag remelting (ESR) ingot and finally to a dia. 400 mm forged billet—key process-specific insights were obtained. The results revealed the effective removal of Type D (globular oxides) inclusions during ESR, with their counts reducing from over 8000 in the electrode to approximately 4000–7000 in the ingot. Concurrently, the mechanism underlying the pronounced enrichment of Type C (silicates) in the ingot tail was elucidated, showing a nearly fourfold increase to 1767 compared to the ingot head, attributed to terminal solidification segregation and flotation dynamics. Subsequent forging further demonstrated exceptional refinement and dispersion of all inclusion types. The billet tail achieved exceptionally high purity, with counts of all inclusion types dropping to extremely low levels (e.g., Types A, B, and C were nearly eliminated), representing a reduction of approximately one order of magnitude. Based on these findings, enhanced process strategies were proposed, including shallow molten pool control, slag system optimization, and multi-dimensional quality monitoring. An intelligent analysis framework integrating a YOLOv11 detection model with spectral feedback was also established. This work provides crucial process knowledge and technological support for achieving the quality control objective of “known and controllable defects” in HSLA steel.

We aimed to assess long-term disease progression in patients with severe keratoconus (KC). Clinical records of 125 patients (201 eyes) with severe KC followed-up for > 12 months were retrospectively analyzed. From these, 28 patients (31 eyes) were included. Corneal topography parameters evaluated included thinnest corneal thickness (TCT), maximum keratometry (Kmax), anterior and posterior mean corneal radii of 3 mm (aKM, pKM), steep keratometry, and KC screening indices. All patients wore rigid gas permeable contact lenses (RGPCLs) for an extended period. The median patient age and follow-up period were 20 (interquartile range [IQR] 17–22) years and 25 (15–38) months, respectively. Compared to baseline, the aKM, Kmax, and KC screening indices on the anterior corneal surface were reduced at the final follow-up ( P  < 0.05). No changes were observed in RGP-corrected visual acuity, TCT, pKM, or KC screening indices on the posterior corneal surface. The higher the baseline value, the greater the reduction in aKM and Kmax. Five patients (16%) experienced disease progression during follow-up. Patients with severe KC showed reduced anterior corneal surface curvature and no change in corneal thickness during an average follow-up period of 2–3 years while wearing RGPCLs.

Early diagnosis of Alzheimer’s disease (AD) and its precursor, mild cognitive impairment (MCI), is critical for effective prevention and treatment. Computer-aided diagnosis using magnetic resonance imaging (MRI) provides a cost-effective and objective approach. However, existing methods often segment 3D MRI images into 2D slices, leading to spatial information loss and reduced diagnostic accuracy. To overcome this limitation, we propose TA-SSM Net, a deep learning model that leverages tri-directional attention and structured state-space model (SSM) for improved MRI-based diagnosis of AD and MCI. The tri-directional attention mechanism captures spatial and contextual information from forward, backward, and vertical directions in 3D MRI images, enabling effective feature fusion. Additionally, gradient checkpointing is applied within the SSM to enhance processing efficiency, allowing the model to handle whole-brain scans while preserving spatial correlations. To evaluate our method, we construct a dataset from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), consisting of 300 AD patients, 400 MCI patients, and 400 normal controls. TA-SSM Net achieved an accuracy of 90.24% for MCI detection and 95.83% for AD detection. The results demonstrate that our approach not only improves classification accuracy but also enhances processing efficiency and maintains spatial correlations, offering a promising solution for the diagnosis of Alzheimer’s disease.