ObjectiveTo observe the clinical efficacy of Gandou Fumu Granules （GDFMG） combined with sodium dimercaptosulphonate （DMPS） on liver fibrosis in Wilson disease （WD） patients with the syndrome of phlegm and blood stasis， evaluate its effect on cuproptosis-related indicators， and explore the possible mechanisms of cuproptosis in WD-related liver fibrosis. MethodsSixty WD patients diagnosed with the syndrome of phlegm and blood stasis between January 2023 and December 2023 were randomly divided into a control group and an observation group， with 30 patients in each group. The control group received the copper chelator DMPS for the first 6 days， followed by calcium gluconate injection for the next 2 days， completing an 8-day treatment cycle. The observation group received GDFMG in addition to the treatment regimen of the control group， with both groups treated for 21 cycles. A Beckman fully automated biochemical analyzer was used to detect levels of type Ⅳ collagen （CⅣ）， hyaluronic acid （HA）， laminin （LN）， N-terminal propeptide of type Ⅲ procollagen （PⅢ-NP）， and serum copper （SCu） before and after treatment in both groups. Enzyme-linked immunosorbent assay （ELISA） was used to measure levels of ferredoxin 1 （FDX1）， lipoic acid synthetase （LIAS）， and dihydrolipoamide S-acetyltransferase （DLAT）. Atomic absorption spectroscopy measured 24-hour urine copper levels before treatment and after the 7， 14， and 21 treatment cycles in both groups. An Fibro Touch （FT） non-invasive liver fibrosis diagnostic device was used to measure liver stiffness （LSM） in both groups before and after treatment. Traditional Chinese medicine syndrome score （TCMSS） was evaluated at the same intervals. Clinical efficacy， adverse events， and safety indicators were also compared. ResultsAfter treatment， levels of CⅣ， HA， LN， and PⅢNP significantly decreased in both groups compared to pre-treatment levels （P<0.01）. The observation group showed a more pronounced reduction compared to the control group （P<0.05）. There were no statistically significant differences in SCu levels in both groups before and after treatment. After treatment， levels of FDX1，LIAS and DLAT significantly increased in both groups（P<0.01）. The observation group showed more notable improvements in these indicators than the control group （P<0.05）. After the 7， 14， 21 treatment cycles， 24-hour urine copper levels significantly increased in both groups compared to pre-treatment levels （P<0.01）. The observation group had a greater increase in 24-hour urine copper levels than the control group after treatment （P<0.05，P<0.01）， and although 24-hour urine copper levels increased after 7 cycles， a gradual decline was observed in subsequent cycles. After treatment， LSM levels significantly decreased in both groups compared to pre-treatment levels （P<0.01）， with the observation group showing a greater reduction than the control group （P<0.05）. Clinical efficacy was significantly better in the observation group than the control group （P<0.05）. No significant differences in the incidence of adverse events or safety indicators were observed between the two groups after treatment. ConclusionGDFMG combined with DMPS can reduce LSM in WD patients with liver fibrosis and the syndrome of phlegm and blood stasis， inhibit cuproptosis， and improve clinical efficacy.

ObjectiveTo investigate the mechanisms by which the combination of berberine （BBR） and baicalin （BAI） ameliorates type 2 diabetes mellitus （T2DM） due to internal accumulation of dampness-heat from the perspectives of gut microbiota and metabolomics. MethodsAntibiotics were used to induce pseudo-sterile mice. Thirty pseudo-sterile mice were randomized into a normal fecal microbiota transplantation group （n=10） and a T2DM （syndrome of internal accumulation of dampness-heat） fecal microbiota transplantation group （n=20）. The mice were then administrated with suspensions of fecal microbiota from healthy volunteers and a patient with T2DM due to internal accumulation of dampness-heat by gavage， respectively. Each mouse received 200 µL suspension every other day for a total of 15 times to reshape the gut microbiota. The T2DM model mice were then assigned into a model group （n=8） and a BBR-BAI group （n=11）. BBR was administrated at a dose of 200 mg·kg^-1， and BAI was administrated in a ratio of BBR-BAI 10∶1 based on preliminary research findings. The administration lasted for 8 consecutive weeks. Fasting blood glucose （FBG）， glycated hemoglobin （HbA1c）， insulin （INS）， triglycerides （TG）， total cholesterol （CHOL）， low-density lipoprotein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， aspartate aminotransferase （AST）， and alanine aminotransferase （ALT） levels were measured to evaluate the effects of the BBR-BAI combination on glucose and lipid metabolism and liver function in T2DM mice. Hematoxylin-eosin staining was employed to observe pathological changes in the colon tissue. The expression of claudin-1， zonula occludens-1 （ZO-1）， and occludin in the colon tissue was determined by Western blot. Real-time quantitative polymerase chain reaction（Real-time PCR） was employed to assess the levels of tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6） in the colon tissue. The fecal microbiota composition and differential metabolites were analyzed by 16S rRNA sequencing and ultra-high performance liquid chromatography-quadrupole-time of flight tandem mass spectrometry （UPLC-Q-TOF-MS）， respectively. ResultsThe BBR-BAI combination lowered the FBG， HbA1c， and INS levels （P<0.05， P<0.01） and alleviated insulin resistance （P<0.01） in T2DM mice. Additionally， BBR-BAI elevated the levels of ZO-1， occludin， and claudin-1 （P<0.05， P<0.01） and down-regulated the expression levels of TNF-α， IL-1β， and IL-6 in the colon （P<0.05， P<0.01）. The results of 16S rRNA sequencing showed that BBR-BAI increased the relative abundance of Ligilactobacillus， Phascolarctobacterium， and Akkermansia （P<0.05）， while significantly decreasing the relative abundance of Alistipes， Odoribacter， and Colidextribacter （P<0.05）. UPLC-Q-TOF-MS identified 28 differential metabolites， which were primarily involved in arachidonic acid metabolism and α-linolenic acid metabolism. ConclusionBBR-BAI can ameliorate T2DM due to internal accumulation of dampness-heat by modulating the relative abundance of various bacterial genera in the gut microbiota and the expression of fecal metabolites.

Toxoplasma gondii is a single-celled parasite that infects nearly all warm-blooded animals, including humans (Montoya and Liesenfeld, 2004). It occurs worldwide and can persist for a lifetime in mammals. Humans get infected by eating undercooked meat of animals containing the tissue cysts of this parasite. In immune-competent individuals, T. gondii infection usually does not cause significant clinical symptoms, whereas in pregnant or immunocompromised individuals, T. gondii infection (toxoplasmosis) can cause more serious problems like abortion and even death (Dunn et al., 1999; Wang et al., 2017). A combination of pyrimethamine and sulfadiazine is usually used to treat toxoplasmosis, although it is generally inefficient and causes side effects (Alday and Doggett, 2017). Worse still, there is a lack of vaccines to prevent T. gondii infection in humans or animals.
Toxoplasma/enzymology* ; Animals ; Humans ; Toxoplasmosis ; Mitochondria/enzymology* ; Protozoan Proteins/metabolism*

OBJECTIVE: To investigate the frequency and related factors of ineffective triggering (IT) and double triggering (DT) in patients with acute brain injury undergoing invasive mechanical ventilation. METHODS: A retrospective cohort study was conducted using data from a single-center observational trial. Patients with acute brain injury [traumatic brain injury, stroke, and post-craniotomy for brain tumors] undergoing mechanical ventilation in the intensive care unit (ICU) of Beijing Tiantan Hospital, Capital Medical University between June 2017 and July 2019 were retrospectively analyzed. Demographic and clinical data were collected. Respiratory parameters and waveforms during the first 3 days of mechanical ventilation were recorded, with 15-minute waveform segments collected 4 times daily. Airway occlusion pressure (P_0.1) was measured via end-expiratory hold at the end of each recording. IT and DT were identified based on airway pressure, flow, and esophageal pressure waveforms, and the ineffective triggering index (ITI) and DT incidence were calculated. Multivariate Logistic regression was used to identify factors associated with IT and DT. RESULTS: A total of 94 patients with acute brain injury were ultimately enrolled, including 19 cases of traumatic brain injury (20.2%), 39 cases of stroke (41.5%), and 36 cases of post-craniotomy for brain tumor (38.3%). Supratentorial injury was observed in 49 patients (52.1%), while infratentorial injury was identified in 45 patients (47.9%). A total of 94 patients with 1 018 datasets were analyzed; 684 (67.2%) datasets were on pressure support ventilation (PSV), and 334 (32.8%) were on mandatory ventilation. IT was detected in 810 (79.6%) datasets, with a median incidence of 2.1% (0.3%, 12.0%). Datasets demonstrating IT were characterized by lower P_0.1, higher tidal volume (VT), reduced respiratory rate (RR), and decreased minute ventilation (MV) compared to those without IT. The proportion of datasets exhibiting IT was higher during PSV than in mandatory ventilation [83.8% (573/684) vs. 71.0% (237/334), P < 0.05], while, the prevalence of ITI ≥ 10% was lower [23.8% (163/684) vs. 33.5% (112/334), P < 0.05]. DT was detected in 305 datasets (30%), with a median incidence of 0.6% (0.4%, 1.3%). Datasets exhibiting DT were characterized by higher VT, reduced RR, and lower pressure support levels. The incidence of DT was lower in PSV compared to mandatory ventilation modes [0% (0%, 0.3%) vs. 0% (0%, 0.5%), P < 0.05]. The post-craniotomy for brain tumors group exhibited higher ITI, lower RR, reduced MV, and a greater proportion of infratentorial lesions, compared to the TBI group. The infratentorial lesion group demonstrated higher ITI and incidence of DT compared to the supratentorial lesion group [ITI: 3.1% (0.7%, 17.8%) vs. 1.5% (0%, 8.3%), incidence of DT: 0% (0%, 0.5%) vs. 0% (0%, 0%), both P < 0.05]. After adjusting for confounding factors through multivariate logistic regression analysis, infratentorial lesion [odds ratio (OR) = 2.029, 95% confidence interval (95%CI) was 1.465-2.811, P < 0.001], lower P_0.1 (OR = 0.714, 95%CI was 0.616-0.827, P < 0.001), and mandatory ventilation (OR = 1.613, 95%CI was 1.164-2.236, P = 0.004) were independently associated with IT. Additionally, infratentorial lesion (OR = 1.618, 95%CI was 1.213-2.157, P = 0.001), large tidal volume (OR = 1.222, 95%CI was 1.137-1.314, P < 0.001), lower pressure support levels (OR = 0.876, 95%CI was 0.829-0.925, P < 0.001), and mandatory ventilation (OR = 2.750, 95%CI was 1.983-3.814, P < 0.001) were independently associated with DT. CONCLUSION IT and DT were common in patients with acute brain injury. Infratentorial lesions and mandatory ventilation were independently associated with both IT and DT.
Humans ; Respiration, Artificial/methods* ; Retrospective Studies ; Brain Injuries/therapy* ; Intensive Care Units ; Male ; Female ; Middle Aged ; Brain Injuries, Traumatic/therapy* ; Logistic Models ; Aged ; Adult

Objective To investigate the population density and seasonal fluctuations of Aedes albopictus in Guangzhou City, Guangdong Province, from 2021 to 2023, so as to provide insights into A. albopictus control and management of dengue fever. Methods The surveillance of A. albopictus density was performed in all surveillance sites assigned across all streets (townships) in Guangzhou City during the period from January to December from 2021 to 2023. The surveillance frequency was twice every half month from May to September, and once every month for the rest of a year. In each surveillance period, A. albopictus mosquito larvae were captured from indoor and outdoor small water containers in residential areas, parks, medical facilities, schools, other government sectors and social organizations, construction sites, special industries and others for mosquito species identification. Adult mosquitoes were captured using electric mosquito suction apparatus for species identification and gender classification. Adult mosquitoes and mosquito eggs were collected with mosquito and egg traps at the breeding and dwelling places of Aedes mosquitoes for identification. The mosquito oviposition index (MOI), Breteau index (BI), adult mosquito density index (ADI) and standard space index (SSI) were calculated. The A. albopictus density was classified into grades 0, 1, 2 and 3 in each surveillance site, with Grade 0 density defined eligible, and the eligible rate of A. albopictus density was calculated at all surveillance sites each year from 2021 to 2023. In addition, the changing trends in MOI, SSI, BI and ADI of A. albopictus were analyzed in Guangzhou City from 2021 to 2023. Results The eligible rates of A. albopictus density were 61.69%, 68.75% and 55.15% in surveillance sites of Guangzhou City from 2021 to 2023 (χ² = 297.712, P < 0.001), and appeared a tendency towards a reduction followed by a rise each year, which gradually reduced since January, maintained at a low level during the period between May and October, and gradually increased from November to December. The MOI, SSI, BI and ADI of A. albopictus all appeared a tendency towards a rise followed by a reduction in Guangzhou City during the period between January and December from 2021 to 2023. The BI of A. albopictus peaked in the first half of June in 2021 (4.03), the first half of July in 2022 (3.89) and the last half of August in 2023 (5.02), and the SSI of A. albopictus peaked in the last half of June in 2021 (0.93), the last half of May in 2022 (0.59), and the last half of June (0.94) and the first half of September in 2023 (1.12). In addition, the MOI of A. albopictus peaked in the first half of May in 2021 (8.64), the first half of June in 2022 (8.96), and the last half of May (10.21) and the last half of June in 2023 (10.89), and the ADI of A. albopictus peaked in the first half of June in 2021 (3.41), the last half of June in 2022 (4.06), and the first half of July in 2023 (3.61). Conclusions The density of A. albopictus is high in Guangzhou City during the period from May to October, and the risk of local outbreak caused by imported dengue fever is high. Persistent intensified surveillance of the density and seasonal fluctuation of A. albopictus is recommended and timely mosquito prevention and control is required according to the fluctuation in the A. albopictus density.

Objective:To evaluate the accuracy of the oral healthcare information provided by different large language models (LLM) to explore their feasibility and limitations in the application of oral auxiliary, treatment and health consultation.Methods:This study designed eight items comprising 47 questions in total related to the diagnosis and treatment of oral diseases [to assess the performance of LLM as an artificial intelligence (AI) medical assistant], and five items comprising 35 questions in total about oral health consultations (to assess the performance of LLM as a simulated doctor). These questions were answered individually by the five LLM models (Erine Bot, HuatuoGPT, Tongyi Qianwen, iFlytek Spark, ChatGPT). Two attending physicians with more than 5 years of experience independently rated the responses using the 3C criteria (correct, clear, concise), and the consistency between the raters was assessed using the Spearman rank correlation coefficient, and the Kruskal-Wallis test and Dunn post hoc test were used to assess the statistical differences between the models. Additionally, this study used 600 questions from the 2023 dental licensing examination to evaluate the time taken to answer, scores, and accuracy of each model.Results:As an AI medical assistant, LLM can assist doctors in diagnosis and treatment decision-making, with an inter-evaluator Spearman coefficient of 0.505 ( P<0.01). As a simulated doctor, LLM can carry out patient popularization, with an inter-evaluator Spearman coefficient of 0.533 ( P<0.01). The 3C scores of each model as an AI medical assistant and a simulated doctor were respectively: 2.00 (1.00, 3.00) and 2.00 (2.00, 3.00) points of Erine Bot, 1.00 (1.00, 2.00) and 2.00 (1.00, 2.00) points of HuatuoGPT, 2.00 (1.00, 2.00) and 2.00 (1.00, 3.00) points of Tongyi Qianwen, 2.00 (1.00, 2.00) and 2.00 (1.75, 2.25) points of iFlytek Spark, 3.00 (2.00, 3.00) and 3.00 (2.00, 3.00) points of ChatGPT (full score of 4 points). The Kruskal-Wallis test results showed that, as an AI medical assistant or a simulated doctor, there were statistically differences in the 3C scores among the five large language models (all P<0.001). The average score of the 5 LLMs on the dental licensing examination was 370.2, with an accuracy rate of 61.7% (370.2/600) and a time consumption of 94.6 min. Specifically, Erine Bot took 115 min, scored 363 points with an accuracy rate of 60.5% (363/600), HuatuoGPT took 224 min and scored 305 points with an accuracy rate of 50.8% (305/600), Tongyi Qianwen took 43 min, scored 438 points with an accuracy rate of 73.0% (438/600), iFlytek Spark took 32 min, scored 364 points with an accuracy rate of 60.7% (364/600), and ChatGPT took 59 min, scored 381 points with an accuracy rate of 63.5% (381/600). Conclusions:Based on the evaluation of LLM′s dual roles as an AI medical assistant and a simulated doctor, ChatGPT performes the best, with basically correct, clear and concise answers, followed by Erine Bot, Tongyi Qianwen and iFlytek Spark, with HuatuoGPT lagging behind significantly. In the dental licensing examination, all the 4 LLM, except for HuatuoGPT, reach the passing level, and the time consumpution for answering is significantly reduced compared to the 8 h required for the exam regulations in all of the five models. LLM has the feasibility of application in oral auxiliary, treatment and health consultation, and it can help both doctors and patients obtain medical information quickly. Howere, their outputs carry a risk of errors (since the 3C scoring results do not reach the full marks), so prudent judgment should be exercised when using them.

Rare diseases are a collective term for diseases with extremely low prevalence and incidence rates.Up to now,China has released two lists identifying a total of 207 rare diseases.Given that most rare diseases do not have drugs with corresponding indications,physicians frequently resort to using off-label drugs when treating patients with rare diseases.However,there is currently no systematic guideline or expert consensus for the use of off-label medications in China.To comprehensively collect existing evidence of off-label drug use for rare diseases,fully analyze and evaluate the rationality of off-label drug use for rare diseases,and standardize the management of off-label drug use for rare diseases,the Rare Disease Branch of Beijing Medical Association,Chinese Pharmaceutical Association,Beijing Pharmaceutical Association,and the School of Public Health,Peking University have jointly initiated the drafting of the Expert Consensus on Off-label Use of Drugs for Rare Diseases.This consensus refer to the WHO Handbook for Guideline Development,the Guidelines for Developing/Revising Clinical Diagnostic and Treatment Guidelines in China(2022 Edition),the AGREE Ⅱ and the STAR tools.This protocol outlines the background and purpose of consensus,as well as the comprehensive framework for consensus development,encompassing panel formation,clinical issue identification,evidence retrieval,data extraction,and evidence-based recommendation formulation.

In recent years,with the constant rise in the number of infertility patients,the rapid and accurate assessment of sperm quality has become a key challenge in reproductive medicine.Currently,traditional methods for sperm classification suffer from limitations in efficiency,subjectivity,and cost-effectiveness,and hence fail to meet clinical needs.With the introduction of artificial intelligence(AI),innovative approaches have been offered to address these issues.Herein,we systematically reviewed the latest progress in AI applications in the field of male infertility,focusing on the role of AI in the assessment of sperm concentration,motility,morphology,DNA fragmentation index,and the treatment of non-obstructive azoospermia.It has been reported that AI technologies,such as convolutional neural networks,demonstrate high accuracy and efficiency in assessing sperm concentration and motility.Particularly in morphological analysis,the performance of AI has been validated in multiple studies,significantly enhancing objectivity and clinical utility.However,the assessment of DNA fragmentation index remains underexplored due to the lack of support in advanced imaging technology,with only a few models showing promise.Additionally,AI significantly improves sperm detection rates in modified testicular sperm extraction through AI-driven image recognition,offering a breakthrough in the treatment of patients with non-obstructive azoospermia.We also discussed the application of natural language processing technology in patient pre-consultation and follow-up,such as automated data collection and intelligent tracking systems,which demonstrate AI's potential to optimize medical workflows.In the future,with the accumulation of high-quality datasets,algorithm optimization,and advances in imaging technology,the application of artificial intelligence is expected to enable multi-dimensional comprehensive screening and play a greater role in the diagnosis and treatment of male infertility.

This review aimed to provide a comprehensive analysis of the etiology, epidemiology, pathology, and conventional treatment of heterotopic ossification (HO), especially emerging potential therapies. HO is the process of ectopic bone formation at non-skeletal sites. HO can be subdivided into two major forms, acquired and hereditary, with acquired HO predominating. Hereditary HO is a rare and life-threatening genetic disorder, but both acquired and hereditary form can cause severe complications, such as peripheral nerve entrapment, pressure ulcers, and disability if joint ankylosis develops, which heavily contributes to a reduced quality of life. Modalities have been proposed to treat HO, but none have emerged as the gold standard. Surgical excision remains the only effective modality; however, the optimal timing is controversial and may cause HO recurrence. Recently, potential therapeutic strategies have emerged that focus on the signaling pathways involved in HO, and small molecule inhibitors have been shown to be promising. Moreover, additional specific targets, such as small interfering RNAs (siRNAs) and non-coding RNAs, could be used to effectively block HO or develop combinatorial therapies for HO.
Humans ; Ossification, Heterotopic/genetics*

Rare diseases are a collective term for diseases with extremely low prevalence and incidence rates.Up to now,China has released two lists identifying a total of 207 rare diseases.Given that most rare diseases do not have drugs with corresponding indications,physicians frequently resort to using off-label drugs when treating patients with rare diseases.However,there is currently no systematic guideline or expert consensus for the use of off-label medications in China.To comprehensively collect existing evidence of off-label drug use for rare diseases,fully analyze and evaluate the rationality of off-label drug use for rare diseases,and standardize the management of off-label drug use for rare diseases,the Rare Disease Branch of Beijing Medical Association,Chinese Pharmaceutical Association,Beijing Pharmaceutical Association,and the School of Public Health,Peking University have jointly initiated the drafting of the Expert Consensus on Off-label Use of Drugs for Rare Diseases.This consensus refer to the WHO Handbook for Guideline Development,the Guidelines for Developing/Revising Clinical Diagnostic and Treatment Guidelines in China(2022 Edition),the AGREE Ⅱ and the STAR tools.This protocol outlines the background and purpose of consensus,as well as the comprehensive framework for consensus development,encompassing panel formation,clinical issue identification,evidence retrieval,data extraction,and evidence-based recommendation formulation.