Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1％of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9％)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5％)was lower than that in inpatient children(31.5％).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1％)than in inpatient children(59.4％).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14％,11.7％,47.8％in outpatients,but 24.2％,20.6％,and 52.8％in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.

Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)％.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0％vs 29.5％).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7％vs 7.8％,0.8％vs 0.1％,both P＜0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)％with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9％and 1.8％,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1％).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10％.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P＜0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.

The aim of this updated guideline is to provide comprehensive recommendations for the management of gout in patients with common comorbidities, such as chronic kidney disease(CKD), cardiovascular disease(CVD), diabetes, osteoarthritis(OA), and gastrointestinal disorders. This guideline was developed by a multidisciplinary expert panel consisting of specialists in endocrinology, rheumatology, nephrology, cardiology, gastroenterology, and methodology. The development process adhered to standard methodologies, including PICO(population, intervention, comparator, and outcomes) question deconstruction, systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation(GRADE) for evidence and recommendation evaluation, Delphi voting, and expert consensus. The guideline presents 26 evidence-based recommendations addressing 7 clinical questions for patients with hyperuricemia and gout in the context of comorbidities. Key recommendations include the maintenance of strict serum urate targets, particularly for patients with CKD stage≥3, chronic gouty arthritis, and OA, in order to prevent disease progression. In patients with CVD or diabetes, intra-articular triamcinolone is preferred over systemic glucocorticoids. Prioritized anti-inflammatory treatments for patients with CKD, gastrointestinal diseases and OA are recommended. The guideline also introduces emerging therapies, such as interleukin-1 inhibitors and selective urate transport inhibitors, as potential treatment options for refractory cases. The update offers a comprehensive, patient-centered approach to managing gout, particularly in individuals with associated comorbidities. Multidisciplinary collaboration and emerging new treatments and evidence ensure the optimization of the recommendations.

Objective:To summarize the clinical characteristics of focal cerebral arteriopathy (FCA) in children, and to analyze its influencing factor of prognosis.Methods:A retrospective cohort study was conducted. Clinical data from 40 children with FCA who were hospitalized at the Department of Neurology, Beijing Children′s Hospital, Capital Medical University, from September 2015 to August 2024 were collected. A centralized follow-up was conducted in October 2024 via outpatient clinics or the internet. The pediatric stroke outcome measure (PSOM) was used to evaluate their outcomes. Based on the PSOM, the children were further divided into a group with normal neurological function and another group with abnormal neurological function. Differences between groups were analyzed using the Mann-Whitney U test and Fisher exact test. Univariate Logistic regression analysis was performed to identify the influencing factors for neurological outcomes in children with FCA. Results:A total of 40 children were included, with 20 males and 20 females, and the onset age of 9.2 (6.8, 12.5) years. Among them, 12 cases (30%) had a history of varicella within 1 year before onset. There were 23 cases (58%) presenting with transient ischemic attack (TIA) or recurrent fluctuating symptoms of onset, while 3 cases (8%) developed progressive stroke within the first month of onset. The M1 segment of the middle cerebral artery was the most commonly affected vascular site, with a total of 16 cases (40%). Arterial occlusion occurred in 8 cases (20%). Lumbar puncture was completed in 36 children, and white blood cell counts in cerebrospinal fluid was increased in 6 cases. All 23 patients who completed magnetic resonance vessel wall imaging (VWI) showed circular enhancement of the arterial wall. A total of 28 patients (70%) received antiplatelet or anticoagulation therapy, and 16 patients (40%) received hormone therapy. At admission, the pediatric National Institute of Health Stroke Scale (PedNIHSS) score was 6.0 (2.0, 8.8) points, which decreased to 0.5 (0, 3.0) points at discharge. The follow-up duration was 1.6 (0.8, 4.9) years, with 1 case lost to follow-up. There was 1 case presenting with recurrence course manifesting as TIA. Among the 39 cases who completed the follow-up, 23 cases (59%) were assessed as neurologically normal by PSOM, while 16 cases (41%) were assessed as neurologically abnormal. Among the 29 cases who completed the imaging review, magnetic resonance angiography (MRA) review in 23 cases indicated stability or improvement in the original arterial stenosis, with 6 cases experiencing transient worsening of arterial stenosis early in the disease course (within 2 months), which later improved. Arterial stenosis progression occurred in 6 cases at the final review of 29 cases who completed the imaging review, with 1 case developing progressive cerebral arteriopathy. The proportion of patients with headache, altered consciousness, and aphasia in the abnormal neurological function group, as well as the PedNISS scores at admission and discharge, were all higher than those in the normal neurological function group (all P<0.05). Univariate Logistic regression analysis revealed that only a PedNISS score>6 points at onset was an influencing factor for abnormal neurological function ( OR=20.58, 95% CI 3.93-107.70, P<0.001). Conclusions:Childhood FCA often presents with fluctuating onset, and the proximal segment of the middle cerebral artery is frequently affected. Progression of arterial stenosis is common within 2 months of the disease course, but clinical progression and new ischemic lesions are uncommon. Most patients have a favorable long-term prognosis. PedNIHSS score>6 points at admission is related to abnormal neurological function outcomes.

OBJECTIVES: To summarize the clinical and genetic characteristics of epilepsy with intellectual disability caused by SETD1B gene variants in children. METHODS: A retrospective analysis was conducted on the clinical data of three children with SETD1B gene variants diagnosed and treated at the Department of Pediatric Neurology of Xiangya Hospital of Central South University. Relevant literature was reviewed to summarize the clinical characteristics of this condition. RESULTS: All three children presented with symptoms during infancy or early childhood, including mild intellectual disability and myoclonic seizures, with two cases exhibiting eyelid myoclonia. After treatment with three or more antiepileptic drugs, two cases achieved seizure control or partial control, while one case remained refractory. Each of the three children was found to have a heterozygous variant in the SETD1B gene (one deletion, one frameshift, and one missense variant). To date, 54 cases with SETD1B gene variants have been reported, involving a total of 56 variants, predominantly missense variants (64%, 36/56). The main clinical manifestations included varying degrees of developmental delay (96%, 52/54) and seizures (81%, 44/54). Among the 44 patients with seizures, myoclonic (20%, 9/44) and absence seizures (34%, 15/44) were common, with eyelid myoclonia reported in six cases. Approximately one-fifth of these patients had poorly controlled seizures. CONCLUSIONS The primary phenotypes associated with SETD1B gene variants are intellectual disability and seizures, and seizures exhibit distinct characteristics. Eyelid myoclonia is not uncommon.
Humans ; Intellectual Disability/complications* ; Epilepsy/complications* ; Male ; Female ; Histone-Lysine N-Methyltransferase/genetics* ; Child, Preschool ; Child ; Retrospective Studies

Myocardial fibrosis is a serious cause of heart failure and even sudden cardiac death. However, the mechanisms underlying myocardial ischemia-induced cardiac fibrosis remain unclear. Here, we identified that the expression of sterile alpha and TIR motif containing 1 (SARM1), was increased significantly in the ischemic cardiomyopathy patients, dilated cardiomyopathy patients (GSE116250) and fibrotic heart tissues of mice. Additionally, inhibition or knockdown of SARM1 can improve myocardial fibrosis and cardiac function of myocardial infarction (MI) mice. Moreover, SARM1 fibroblasts-specific knock-in mice had increased deposition of extracellular matrix and impaired cardiac function. Mechanically, elevated expression of SARM1 promotes the deposition of extracellular matrix by directly modulating P4HA1. Notably, by using the Click-iT reaction, we identified that the increased expression of ZDHHC17 promotes the palmitoylation levels of SARM1, thereby accelerating the fibrosis process. Based on the fibrosis-promoting effect of SARM1, we screened several drugs with anti-myocardial fibrosis activity. In conclusion, we have unveiled that palmitoylated SARM1 targeting P4HA1 promotes collagen deposition and myocardial fibrosis. Inhibition of SARM1 is a potential strategy for the treatment of myocardial fibrosis. The sites where SARM1 interacts with P4HA1 and the palmitoylation modification sites of SARM1 may be the active targets for anti-fibrosis drugs.

Research indicates that microbe activity within the human body significantly influences health by being closely linked to various diseases. Accurately predicting microbe-disease interactions (MDIs) offers critical insights for disease intervention and pharmaceutical research. Current advanced AI-based technologies automatically generate robust representations of microbes and diseases, enabling effective MDI predictions. However, these models continue to face significant challenges. A major issue is their reliance on complex feature extractors and classifiers, which substantially diminishes the models' generalizability. To address this, we introduce a novel graph autoencoder framework that utilizes decoupled representation learning and multi-scale information fusion strategies to efficiently infer potential MDIs. Initially, we randomly mask portions of the input microbe-disease graph based on Bernoulli distribution to boost self-supervised training and minimize noise-related performance degradation. Secondly, we employ decoupled representation learning technology, compelling the graph neural network (GNN) to independently learn the weights for each feature subspace, thus enhancing its expressive power. Finally, we implement multi-scale information fusion technology to amalgamate the multi-layer outputs of GNN, reducing information loss due to occlusion. Extensive experiments on public datasets demonstrate that our model significantly surpasses existing top MDI prediction models. This indicates that our model can accurately predict unknown MDIs and is likely to aid in disease discovery and precision pharmaceutical research. Code and data are accessible at: https://github.com/shmildsj/MDI-IFDRL.

Objective To investigate the five-circuit and six-qi features at conception and at birth in the patients with endometrial cancer.Methods From June 2020 to August 2024,the information about the conception time and birth time of 1 099 patients with endometrial cancer admitted to Guang'anmen Hospital of China Academy of Chinese Medical Sciences was collected from the electronic medical record system.The circuit-qi information at conception and at birth of the patients was statistically analyzed,and then the congenital endowment characteristics of the patients were explored.Results The results showed that most of the patients suffering endometrial cancer were born in winter,and the dominant qi at birth of the patients was predominated by taiyang cold-water,and the differences of the distribution of dominant qi at birth were statistically significant(P＜0.05).There were no significant differences in the distribution of yearly circuit,guest qi,and sitian-zaiquan at birth,and in the distribution of seasons,yearly circuit,dominant qi,guest qi,and sitian-zaiquan at conception(P＞0.05),and only an obvious trend of differences was presented.Conclusion There is a certain correlation between the prevalence of endometrial cancer and the five-circuit and six-qi features at conception and at birth.The congenital endowment of patients with endometrial cancer is characterized by yang deficiency with predominant coldness,and the prevalence is related to jueyin wind wood.

Research indicates that microbe activity within the human body significantly influences health by being closely linked to various diseases.Accurately predicting microbe-disease interactions(MDIs)offers critical insights for disease intervention and pharmaceutical research.Current advanced AI-based technologies automatically generate robust representations of microbes and diseases,enabling effec-tive MDI predictions.However,these models continue to face significant challenges.A major issue is their reliance on complex feature extractors and classifiers,which substantially diminishes the models' generalizability.To address this,we introduce a novel graph autoencoder framework that utilizes decoupled representation learning and multi-scale information fusion strategies to efficiently infer po-tential MDIs.Initially,we randomly mask portions of the input microbe-disease graph based on Bernoulli distribution to boost self-supervised training and minimize noise-related performance degradation.Secondly,we employ decoupled representation learning technology,compelling the graph neural network(GNN)to independently learn the weights for each feature subspace,thus enhancing its expressive power.Finally,we implement multi-scale information fusion technology to amalgamate the multi-layer outputs of GNN,reducing information loss due to occlusion.Extensive experiments on public datasets demonstrate that our model significantly surpasses existing top MDI prediction models.This indicates that our model can accurately predict unknown MDIs and is likely to aid in disease discovery and precision pharmaceutical research.Code and data are accessible at:https://github.com/shmildsj/MDI-IFDRL.