Biliary atresia （BA） is characterized by progressive inflammation and fibrous obstruction of bile ducts， ultimately leading to cholestatic liver cirrhosis. Kasai surgery is the standard procedure for the treatment of BA， and early diagnosis is a key influencing factor for the prognosis of BA. Indocyanine green （ICG） is a near-infrared photosensitive dye that is efficiently and selectively absorbed by hepatocytes after intravenous injection， and it enters the intestine via bile and is excreted with the feces in the free form， with a favorable safety profile. In addition， ICG can emit fluorescence under near-infrared light， which can be captured by camera instruments and converted into visual images， and ICG fluorescence imaging technology can reflect the intraoperative situation in real time and significantly improve the success rate of the surgical procedure. This article reviews the advances in the application of ICG in early preoperative diagnosis， intraoperative imaging， and postoperative liver function assessment in recent years.

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

Ursodeoxycholic acid (UDCA) is a naturally occurring, low-toxicity, and hydrophilic bile acid (BA) in the human body that is converted by intestinal flora using primary BA. Solute carrier family 7 member 11 (SLC7A11) functions to uptake extracellular cystine in exchange for glutamate, and is highly expressed in a variety of human cancers. Retroperitoneal liposarcoma (RLPS) refers to liposarcoma originating from the retroperitoneal area. Lipidomics analysis revealed that UDCA was one of the most significantly downregulated metabolites in sera of RLPS patients compared with healthy subjects. The augmentation of UDCA concentration (≥25 μg/mL) demonstrated a suppressive effect on the proliferation of liposarcoma cells. [¹⁵N₂]-cystine and [¹³C₅]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione (GSH) synthesis. Mechanistically, UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis, leading to reactive oxygen species (ROS) accumulation and mitochondrial oxidative damage. Furthermore, UDCA can promote the anti-cancer effects of ferroptosis inducers (Erastin, RSL3), the murine double minute 2 (MDM2) inhibitors (Nutlin 3a, RG7112), cyclin dependent kinase 4 (CDK4) inhibitor (Abemaciclib), and glutaminase inhibitor (CB839). Together, UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity, and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA. More importantly, in combination with other antitumor chemotherapy or physiotherapy treatments, UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.

Organoids,recognized as invaluable models in tumor and stem cell research,assume a pivotal role in the meticulous analysis of diverse datasets pertaining to their growth dynamics,drug screening processes and related phenomena.However,the manual scrutiny and conventional statistical methodologies employed in handling organoid data often grapple with challenges such as diminished precision and efficiency,heightened complexity,escalated human resource requirements,and a degree of subjectivity.Acknowledging the remarkable efficacy of artificial intelligence(AI)in the realms of biology and medicine,the incorporation of AI into organoid research stands poised to enhance the objectivity,precision and expediency of analyses.This integration empowers organoids to more effectively fulfill objectives such as disease modeling,drug screening and precision medicine.Notably,significant strides have been made in AI-driven analyses of organoid image data.The amalgamation of deep learning into image analysis facilitates a more meticulous delineation of the microstructural intricacies and nuanced changes within organoids,achieving a level of accuracy akin to that of experts.This not only elevates the precision of organoid morphology and growth recognition,but also contributes to substantial time and cost savings in research endeavors.Furthermore,the infusion of AI technology has yielded breakthroughs in the processing of organoid omics data,resulting in heightened efficiency in data processing and the identification of latent gene expression patterns.This furnishes novel tools for comprehending cellular development and unraveling the intricate mechanisms underlying various diseases.In addition to image data,AI techniques applied to diverse organoid datasets,encompassing electrical signals and spectra,have realized an unbiased classification of organoid types and states,embarking on a comprehensive journey towards characterizing organoids holistically.In the pivotal domain of drug screening for organoids,AI emerges as a stalwart companion,providing robust support for real-time process monitoring and result prediction.Leveraging high-content microscopy images and sophisticated deep learning models,researchers can dynamically monitor organoid responses to drugs,effecting non-invasive detection of drug impacts and amplifying the precision and efficiency of drug screening processes.Despite the significant strides made by AI in organoid research,challenges persist,encompassing hurdles in data acquisition,constraints in sample quality and quantity,and quandaries associated with model interpretability.Overcoming these challenges necessitates dedicated future research efforts aimed at enhancing data consistency,fortifying model interpretability,and exploring methodologies for the seamless fusion of multimodal data.Such endeavors are poised to usher in a more comprehensive and dependable application of AI in organoid research.In summation,the integration of AI technology introduces unparalleled opportunities to organoid research,resulting in noteworthy advancements.Nevertheless,interdisciplinary research and collaborative efforts remain imperative to navigate challenges and propel the more profound integration of AI into organoid research.The future holds promise for AI to assume an even more prominent role in advancing organoid research toward clinical translation and precision medicine.

Dysbiosis can cause microenvironmental dysregulation, which can further lead to local or systemic diseases, such as caries, inflammatory bowel disease, obesity, and diabetes. Dysbiosis is primarily manifested as the disturbance of metabolic processes and products. Arginine plays an important role in various metabolic processes and homeostasis of the microbial flora and the host. This study aims to explore the potential therapeutic value of arginine and its metabolism and homeostasis regulation in diseases associated with oral-intestinal dysbiosis. Host and microbial homeostasis can be restored by regulating the composition or function of host microbiota, and arginine has been found to exhibit significant clinical potential in restoring host microbiota composition and function. For example, arginine can reduce the risk of caries by regulating the relative abundance of Streptococcus mutans and Streptococcus sanguineus. Additionally, arginine metabolism may play a therapeutic role in inflammatory bowel disease and obesity by regulating the relative abundance of Firmicutes and Bacteroidetes. In addition, supplementation of arginine and its metabolite polyamine has clinical prospects in the treatment of diabetic patients with ketoacidosis. Although studies have demonstrated the therapeutic role of arginine in oral, intestinal, and metabolism-related diseases, the specific mechanism is yet to be explored. In addition, further research is required to determine the optimal clinical dosage of arginine that can maintain microbiota homeostasis without causing any side effects.

Osteoarthritis (OA) is a chronic degenerative joint disease whose main characteristic is the destruction of articular cartilage, causing pain and disability in patients and seriously affecting their quality of life. OA can be induced by a variety of causes, and pathological changes in articular cartilage are considered to be one of the key driving factors for the occurrence of OA. High mobility group box-1 protein (HMGB1), as a non-histone protein in eukaryotic cells, can participate in regulating the inflammation and apoptosis process of OA chondrocytes, thus leading to the occurrence of OA. This article reviews the research on the mechanism of HMGB1 in OA chondrocytes, with a view to providing new ideas for the clinical prevention and treatment of OA.

Objective To explore the value of MR diffusion tensor imaging(DTI)in evaluating the effect of march training on the thigh muscles of recruits.Methods DTI scans of the right thigh were performed three times in forty recruits:before and after the march training and one month after the rest.Fractional anisotropy(FA)was measured on the cross-sectional images of the thigh muscles,including rectus femoris(RF),vastus medialis(VM),vastus lateralis(VL),vastus intermedius(VI),gracilis muscle(GM),sartorius muscle(SM),semitendinosus muscle(STM),semimembranosus muscle(SMM),long head of biceps femoris(LHBF)and short head of biceps femoris(SHBF).The percentage changes in FA values of each muscle after the training and rest were calculated.Paired samplet-tests were used to analyze the differences in FA among the thigh muscles at different time points,and one-way ANOVA was used to analyze the differences in the percentage changes of FA among the thigh muscles after the training and rest.Results Compared to pre-training,the FA values of all thigh muscles significantly decreased after the training,with statistical differences(P＜0.05).After the rest,the FA values of all thigh muscles recovered,but statistical differences remained in RF(P＜0.001),VM(P＜0.001),VL(P=0.001),STM(P=0.046),and LHBF(P=0.013).After the training and rest,the FA values of the recruits'thigh muscles showed a"decreasing first and then increasing"trend.There were statistical differences in the percentage changes of FA after the training and the recovery percentages of FA after the rest among the thigh muscles(P＜0.001,P＜0.001).Conclusion DTI may reflect the ultra-structure changes in the thigh muscles of recruits after the march training and provide a quantitative and noninvasive assessment of muscle micro-injuries.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective: To explore the relationship between myopia and nutritional status among upper elementary students in Shanghai. Methods: A stratified cluster sampling method was used to select 5 576 fourth and fifth grade students from 16 districts in Shanghai, vision test, physical examination and questionnaire survey were administered. Two level multivariate Logistic regression and mixed linear models were used to analyze the relationship between myopia, spherical equivalent (SE) and nutritional status. Results: The detection rates of overweight and obesity were 17.0%(949) and 18.7%(1 042), respectively. There was a statistical difference in the proportion of the nutritional status in boys and girls( χ 2=210.94, P <0.01), with overweight and obesity in boys higher than those of girls. The overweight boys were more likely to have myopia (univariate analysis: OR=1.23, P =0.04; multivariate analysis: OR=1.21, P =0.06) than the normal weight boy. Overweight students tended to had more negative refractive than those with normal weight in both boys and girls(multivariate analysis, boys: β =-0.19, girls: β=-0.24, P <0.05). Myopia risk and refractive power in obese students showed no statistical difference with normal weight students( P >0.05). Conclusion Overweight students have lower SE than the normal weight among upper elementary students of Shanghai, more researches are needed to confirm this finding and to provide theoretical bases for myopia prevention and control.

Objective To evaluate the effect of applying sitting posture corrector on improving reading and writing posture of elementary school students， and provide scientific evidence for prevention and control of myopia in children and adolescents. Methods One elementary school each in urban and suburban areas of Shanghai was selected using a convenience sampling strategy. Furthermore， two classes each in Grade 3 and 4 were selected as the intervention group （282 students were included in the study）， and the other two classes each in Grades 3 and 4 were selected as the control group （294 students were included in the study）. Students in the intervention group used the sitting posture corrector in the classrooms for 4 months （from September 2020 to January 2021）， while those in the control group did not use the sitting posture corrector. Relevant data were collected before and after the intervention through a self-administered questionnaire and visual examination. Statistical analysis was performed using chi-square test and generalized estimating equation. Results Before the intervention， 13.5% （38/282） of students in the intervention group and 12.2% （36/294） in the control group had good reading and writing posture （ χ ² = 0.195， P >0.659）. After the intervention， 18.4% （52/282） of students in the intervention group had good reading and writing posture， which was higher than that （11.2%， 33/294） in the control group （ χ ²=5.957， P =0.015）. Before and after the intervention， there was no significant differences in the prevalence of myopia between students in the intervention and control groups （all P >0.05）. Generalized estimating equation analysis showed that students in the intervention group were 1.502 times more likely to have good reading and writing posture than those in the control group after the intervention （ P =0.043）. Conclusion Applying sitting posture corrector in schools could improve students' reading and writing posture.