Background:To compare the efficacy and safety of monthly administrations of gonadotropin releasing hormone (GnRH) agonists LY01005 and Zoladex ? in Chinese patients with premenopausal breast cancer. Methods:From October 2020 to November 2021, 188 premenopausal breast cancer patients were enrolled in 34 hospitals and randomized 1:1 to receive either LY01005 or Zoladex ? every 28 days for a total of three injections. All patients concomitantly received oral tamoxifen (TAM). The primary efficacy endpoint was cumulative probability of maintaining menopausal level [oestradiol (E2) ≤30 pg/ml] from day 29 to day 85. The second efficacy endpoint included changes in E2, luteinizing hormone (LH), and follicle-stimulating hormone (FSH) compared with the baseline. Pharmacokinetics (PK), pharmacodynamics (PD), and safety were analyzed. The study also evaluated the pharmacokinetic and pharmacodynamic characteristics of LY01005. Results:A total of 188 patients were randomised and 187 patients received either LY01005 or Zoladex ?. Cumulative probabilities of maintaining menopausal level (E2≤30 pg/ml) from day 29 to day 85 were 93.1% for LY01005 and 86.3% for Zoladex ?. The between-group difference was 6.8% (95% CI: -2.3%, 15.9%) and primary efficacy in the LY01005 group was not inferior to that in the Zoladex ? group. Changes in E2, LH, and FSH levels compared with the baseline were equivalent between the two groups (E2: 89.34% to 90.23% vs. 82.11% to 85.02%; LH: 88.89% to 95.52% vs. 89.70% to 97.02%; FSH: 75.36% to 80.85% vs.73.07% to 80.24%, respectively). After three consecutive doses of LY01005, the LH and FSH levels of the subjects showed a transient increase after the first dose, reached a peak on the second day and then started to decrease. The LH and FSH reached a lower level and remained at or below that level until the 85th day. Both treatments were well-tolerated. Conclusion:LY01005 is as effective as Zoladex ? in suppressing E2 to menopausal levels in Chinese patients with premenopausal breast cancer, with a similar safety profile.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To examine the postoperative morphological changes in outer retinal wave-like changes (ORC) in eyes with rhegmatogenous retinal detachment (RRD).Methods:A retrospective clinical study. From March 2020 to March 2024, 64 eyes of 64 RRD patients diagnosed at The Second Affiliated Hospital of Zunyi Medical University were included. The cohort included 39 males (39 eyes) and 25 females (25 eyes), with a mean age of (45.3±15.7) years and a mean retinal detachment duration of (16.6±13.5) days. Macular involvement was observed in 51 eyes. Scleral buckling surgery (SB), pars plana vitrectomy (PPV), and SB+PPV were performed in 17, 44, and 3 eyes respectively. Best corrected visual acuity (BCVA) and spectral domain optical coherence tomography examinations were performed in all affected eyes. BCVA examination was performed using the standard logarithmic visual acuity chart, and the visual acuity was converted to logarithm of the minimum angle of resolution (logMAR) during statistics. Combined with the ORC situation before the operation, the morphological repositioning of outer retinal folds (ORF) after the operation was classified into types Ⅰ, Ⅱ and Ⅲ. One week and one and three months after the operation, relevant examinations were performed using the same equipment and methods as before the operation. The structural characteristics of ORC and the morphology of ORF after surgery were observed. The comparison between groups was conducted using the independent sample t test or the Mann-Whitney U test. Results:Among the 64 eyes, preoperative ORC was present in 46 eyes (71.9%, 46/64) and absent in 18 eyes (28.1%, 18/64). The 18 eyes without ORC had retinal detachment durations of either ≤4 days or ≥42 days. Postoperatively, ORF was observed in 51 eyes (79.7%, 51/64) and absent in 13 eyes (20.3%, 13/64). Among the 51 eyes with macular holes involved, 24 eyes (47.1%, 24/51) had ORF after the operation and 27 eyes (52.9%, 27/51) had no ORF. Among the 46 and 18 eyes with and without ORC, the ORF after surgery was 28 (60.9%, 28/46) and 1 (5.6%, 1/18) eyes, respectively. There was a statistically significant difference in the reduction rate of ORF after surgery between eyes with and without ORC ( χ2=15.974, P<0.001). Among the 46 eyes with ORC, the proportions of ORF to types Ⅰ, Ⅱ and Ⅲ after surgery were 24 (52.2%, 24/46), 20 (43.5%, 20/46), and 2 (4.3%, 2/46) eyes, respectively. There was no statistically significant difference in the incidence of ORF after different surgical methods in eyes with ORC ( P>0.05). One week and one month after the surgery, the logMAR BCVA of the affected eyes with and without ORF was 0.97±0.47, 0.69±0.34 and 0.85±0.32, 0.54±0.21, respectively. The BCVA of those without ORF was better than that of those with ORF, but the differences were not statistically significant ( t=0.237, 0.408; P>0.05). Conclusions:The occurrence of ORC in RRD eyes has a certain relationship with the time of retinal detachment. For RRD eyes with ORC before the operation, the repositioning morphology after the operation is more likely to show changes in ORF. The transformation from ORC to ORF after ORC surgery has no correlation with the surgical method.

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.
Humans ; Large Language Models ; Tomography, X-Ray Computed

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

ObjectiveTo observe the clinical efficacy and safety of Modified Guomin Decoction （加味过敏煎， MGD） in patients with mild to moderate atopic dermatitis （AD） of the traditional Chinese medicine （TCM） pattern of heart fire and spleen deficiency， and to explore its possible mechanisms. MethodsIn this randomized， double-blind， placebo-controlled study， 72 patients with mild to moderate AD and the TCM pattern of heart fire and spleen deficiency were randomly divided into a treatment group and a control group， with 36 cases in each group. The treatment group received oral MGD granules combined with topical vitamin E emulsion， while the control group received oral placebo granules combined with topical vitamin E treatment. Both groups were treated twice daily for 4 weeks. Clinical efficacy， TCM syndrome scores， Visual Analogue Scale （VAS） for pruritus， Dermatology Life Quality Index （DLQI） scores， Scoring Atopic Dermatitis （SCORAD） and serum biomarkers， including interleukin-33 （IL-33）， interleukin-1β （IL-1β）， immunoglobulin E （IgE）， and tumor necrosis factor-α （TNF-α） were compared before and after treatment. Safety indexes was also assessed. ResultsThe total clinical effective rates were 77.78% （28/36） in the treatment group and 38.89% （14/36） in the control group， with cure rates of 19.44% （7/36） and 2.78% （1/36）， respectively. The treatment group showed significantly better clinical outcomes compared to the control group （P＜0.05）. The treatment group exhibited significant reductions in total TCM syndrome scores， including erythema， edema， papules， scaling， lichenification， pruritus， irritability， insomnia， abdominal distension， and fatigue scores， as well as reductions in VAS， DLQI， SCORAD， and serum IgE and IL-33 levels （P＜0.05 or P＜0.01）. Compared to the control group， the treatment group had significantly better improvements in all indicators except for insomnia （P＜0.05）. No adverse events occurred in either group. ConclusionMGD is effective and safe in treating mild to moderate AD patients with heart fire and spleen deficiency pattern. It significantly alleviates pruritus， improves TCM syndromes and quality of life， and enhances clinical efficacy， possibly through modulation of immune responses.

Under the background of climate change, the escalating air pollution and extreme weather events have been identified as risk factors for chronic respiratory diseases (CRD), causing serious public health burden worldwide. This review aims to summarize the effects of changed atmospheric environment caused by climate change on CRD. Results indicated an increased risk of CRD (mainly COPD, asthma) associated with environmental factors, such as air pollutants, adverse meteorological conditions, extreme temperatures, sandstorms, wildfire, and atmospheric allergens. Furthermore, this association can be modified by factors such as socioeconomic status, adaptability, individual behavior, medical services. Potential pathophysiological mechanisms linking climate change and increased risk of CRD involved pulmonary inflammation, immune disorders, oxidative stress. Notably, the elderly, children, impoverished groups and people in regions with limited adaptability are more sensitive to respiratory health risks caused by climate change. This review provides a reference for understanding risk factors of CRD in the context of climate change, and calls for the necessity of adaptive strategies. Further interdisciplinary research and global collaboration are needed in the future to enhance adaptability and address climate health inequality.
Climate Change ; Humans ; Air Pollution/adverse effects* ; Risk Factors ; Respiratory Tract Diseases/etiology* ; Chronic Disease ; Air Pollutants/adverse effects* ; Environmental Exposure/adverse effects*

Objective To compare the distribution characteristics and drug resistance of mucous and non-mucous Streptococcus pneumoniae(SP).Methods SP isolated from clinical specimens of the Second Affiliated Hospital of Xiamen Medical College from January 2023 to June 2024 were collected.They were isolated,cultured and identified,and their susceptibility to antibacterial drugs was determined.Results A total of 291 SP strains were isolated,of which 20 strains were mucous SP and 271 strains were non-mucous SP.Children played a dominant role of non-mucous SP infection,but mucous SP mainly infected adults and the children above 5 years old.Both phenotypes of SP were mainly characterized by pulmonary infection.Non-mucous SP had a relatively high sensitivity rate to vancomycin,linezolid,penicillin,ertapenem,chloramphenicol,levofloxacin,moxifloxacin and ofloxacin.It had a high resistance rate to compound sulfamethoxazole,clindamycin,erythromycin and tetracycline.Mucous SP was completely sensitive to penicillin,amoxicillin,cefotaxime,ceftriaxone,ertapenem,vancomycin,linezolid,levofloxacin and moxifloxacin,and had a relatively high resistance rate to clindamycin,erythromycin and tetracycline.Conclusion The laboratory should enhance the detection capacity of mucous SP.Mucous SP is highly sensitive to common antibiotics.Clinicians should select antibiotics based on drug sensitivity results to delay the occurrence of drug resistance.

Objective To investigate the potential of one-stop multi-modality CT in the assessment of collateral circulation and prognosis in acute ischemic stroke(AIS).Methods From February 2022 to May 2024,115 patients diagnosed with AIS at Wuzhou Red Cross Hospital were enrolled in the study.All subjects were examined with one-stop multi-modality CT at admission and received endovascular therapy.According to the collateral circulation score derived from multi-phase CT angiography(mCTA)and the modified Rankin scale score at 90 days,these patients were divided into different groups:good(n=59)vs poor(n=56)collateral circulation groups,and favorable(n=48)vs unfavorable(n=67)outcome groups.Clinical and imaging parameters were compared between these groups.Independent risk factors for collateral circulation and prognosis of AIS patients were identified through multivariate Logistic regression analysis.A prediction model for unfavorable AIS prognosis was developed based on the results of multivariate Logistic analysis,and its predictive value was assessed using receiver operating characteristic(ROC)curve analysis.Results Poor collateral circulation group exhibited higher proportions of insular ribbon and gray-white matter junction blurring as compared with good collateral circulation group(P<0.05),while the ratio of hypoperfusion intensity ratio(HIR)<0.3 was lower in poor collateral circulation group(P<0.05).Relative cerebral blood volume(rCBV)<40%,relative cerebral blood flow(rCBF)<30%,peak time(Tmax)>8 s,and Tmax>10 s volume were all significantly higher in poor collateral circulation group(P<0.05),whereas the Alberta stroke program early CT score(ASPECTS)was lower(P<0.05).Multivariate Logistic regression analysis identified ASPECTS,rCBV<40%,rCBF<30%,and Tmax>10 s as independent risk factors for poor collateral circulation(P<0.05).Unfavorable outcome group had higher rates of hemorrhage following endovascular thrombectomy and mismatch ratio<1.8 than favorable outcome group(P<0.05),with a lower HIR<0.3 ratio(P<0.05).Compared with favorable outcome group,unfavorable outcome group also showed higher admission NIHSS scores,higher percentages of rCBV<40%,rCBF<30%,Tmax>4 s,Tmax>6 s,and Tmax>10 s volumes(P<0.05),but lower mCTA collateral circulation score(P<0.05).Multivariate Logistic regression analysis indicated that admission NIHSS score,mCTA collateral circulation score,rCBV<40%,rCBF<30%,and Tmax>10 s were independent risk factors for unfavorable outcomes(P<0.05).The regression equation was formulated as:Logit(P)=-0.184+(admission NIHSS score×0.134)+(mCTA collateral circulation score×-0.415)+(rCBV<40%×0.107)+(rCBF<30%×0.089)+(Tmax>10 s×0.028).ROC curve analysis demonstrated an area under the curve of 0.775(95 CI:0.689-0.860,P<0.001)for the prediction model in assessing unfavorable AIS prognosis.Conclusion One-stop multi-modality CT has significant application value in assessing collateral circulation and predicting prognosis in AIS patients.

Objective:To investigate the application and effectiveness of the scaffolding teaching method in improving the teaching effect of septic shock and cultivating learning interest among medical students.Methods:A total of 52 medical students participating in intensive care internship were randomly divided into traditional teaching group and scaffolding teaching group,with 26 students in each group. The students in the traditional teaching group received traditional teaching,while those in the scaffolding teaching group received scaffolding teaching; assessments were performed in both groups. The two groups were compared in terms of theoretical assessment score,case assessment score,and degree of satisfaction with teaching. SPSS 25.0 was used to perform the t-test and the chi-square test. Results:There was no significant difference in theoretical assessment score at the time of department enrollment between the two groups [(5.31±1.05) vs. (5.35±0.94), P=0.890]. Compared with the traditional teaching group,the scaffolding teaching group had significantly higher scores in theoretical assessment [(7.19±1.17) vs. (6.39±1.20), P=0.017],specialized physical examination in case assessment [(7.15±0.66) vs. (6.29±0.59), P<0.001],and diagnosis and treatment regimen [(7.58±0.66) vs. (6.83±0.60), P<0.001],as well as significantly more interest in critical care medicine ( χ2=4.59, P=0.032). Conclusions:In the teaching process of the diagnosis and treatment of septic shock,building various types of scaffolds based on the basic knowledge of students can stimulate their interest and improve teaching effectiveness,which holds promise for further application in critical care medicine teaching.