OBJECTIVE: To explore the clinical phenotype and genetic characteristics of four patients with Phelan-McDermid syndrome (PMS) due to variants of SHANK3 gene. METHODS: Four patients diagnosed with PMS at Guangzhou Women and Children's Medical Center Liuzhou Hospital from January 2020 to January 2025 were selected as the study subjects. Clinical data of the patients were collected. Peripheral venous blood samples were collected from each patient for the extraction of genomic DNA, followed by whole-exome sequencing (WES) and validation by Sanger sequencing. Pathogenicity of candidate variants was rated based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), and multiple bioinformatic tools were used to assess the pathogenic effects of the variants. The study was approved by the Ethics Committee of the Hospital (Ethics No. 2025-007). RESULTS: All four patients had exhibited language delay and intellectual disability (IQ 35 ~ 65). Some also presented with autism spectrum disorder and schizophrenia, albeit with significant phenotypic heterogeneity. All patients were found to harbor deletions of 22q13.33 region, ranging from 55.46 Kb to 112.64 Kb, primarily involving the SHANK3 gene. CONCLUSION PMS is typically caused by deletions or mutations of the SHANK3 gene. The clinical manifestations are diverse, with developmental delay and intellectual disability being the most common. Accurate diagnosis requires integration of genetic testing and standardized clinical assessment. Genetic screening for suspected patients and at-risk pregnant women is recommended to facilitate their genetic counseling.
Child ; Humans ; Chromosome Deletion ; Chromosome Disorders/genetics* ; Chromosomes, Human, Pair 22/genetics* ; Exome Sequencing ; Nerve Tissue Proteins/genetics* ; Phenotype

OBJECTIVE To explore the intervention mechanism of Shangke Lengtongtie on cold hyperalgesia in KOA mice based on the HMGB1/CXCL12/CXCR4 signaling axis.METHODS Monosodium iodoacetate(MIA)was used for the intra-articular injec-tion into the knee joint to establish mice model of knee osteoarthritis(KOA).Peripheral blood monocytes were extracted from mice,cultured,and then reinfused into the tail vein of the mice.Subsequently,in vivo animal imaging was used to observe the recruitment sites of these monocytes.The cold hyperalgesia threshold was measured at various time points in each group of mice.Hematoxylin and eosin(HE)staining was used to evaluate the level of synovial pathological changes.ELISA was employed to detect the expression of in-flammatory factors IL-1β,TNF-α,and pain mediators CGRP and Substance P in mouse serum.Western blot and qPCR methods were used to detect the protein and gene expression of cold hyperalgesia-related indicators such as TRPA1,TRPM8,HMGB1,CXCL12,CXCR4,Collagen Ⅰ,and Netrin-1 in synovial tissue,as well as DCC in dorsal root ganglia(DRG)tissue.RESULTS In vivo ima-ging showed that after the monocytes were reinfused into KOA mice,they were recruited to the knee joint area,with the HMGB1 group exhibiting a greater recruitment of circulating monocytes at the knee joint.Additionally,compared to the control group,the KOA group and HMGB1 group showed inflammatory pathological changes in the synovium,increased expression of serum inflammatory factors and pain mediators,reduced cold hyperalgesia threshold,and upregulated protein and gene expression of cold hyperalgesia-related indica-tors in synovial and DRG tissues.The changes were more significant in the HMGB1 group compared to the KOA group(P<0.05).Af-ter treatment with Shangke Lengtongtie or GL intervention,synovial inflammation was alleviated,serum inflammatory factors and pain mediators decreased,cold hyperalgesia threshold increased,and the upregulation of cold hyperalgesia-related indicator protein and gene expression levels was significantly reversed(P<0.05).CONCLUSION Shangke Lengtongtie exerts a beneficial effect on the mitigation of synovitis and cold hyperalgesia in KOA mice,a therapeutic mechanism that possibly mediated through the inhibition of the HMGB1/CXCL12/CXCR4 signaling axis.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Tegoprazan is a novel potassium-competitive acid blocker with long-lasting and potent acid-suppressing effects,showing favorable efficacy in many acid-related diseases.In eradicating Helicobacter pylori(Hp)infections,tegoprazan-based regimens are noninferior to proton pump inhibitor(PPI)regimens in terms of efficacy,and are well tolerated and safe.In this article,we review the pharmacological mechanism,clinical studies on Hp eradication regimens,and safety of tegoprazan to provide a reference for the selection of Hp e-radication regimens.

At present,the drug substitutes represented by new psychoactive substances are gradually be-coming popular,leading to an increasing demand for identifying novel drugs with unknown structures in drug investigation.Nuclear magnetic resonance(NMR)spectroscopy is an important tool for ana-lyzing molecular structures.In the absence of standard substances,quantitative NMR(qNMR)can un-dertake the quantitative analysis of target substances in complex mixtures and has unique advantages in the research of new drugs and their precursor drugs.Due to the limitations of the site and mainte-nance costs,as well as relatively complex operation,high-field superconducting NMR is less com-monly applied in drug research.The desktop low-field NMR developed in recent years provides a new alternative solution.Due to the use of permanent magnets,its size is reduced,and the operation and maintenance costs are lowered.It has been widely used in various research fields.This article reviews the development of low-field NMR technology,summarizes the application of desktop low-field NMR in screening and identification of suspicious substances,rapid content determination,analysis of drug manufacturing processes and synthetic routes,and correlation traceability.It also looks forward to the prospects and development directions of this technology in drug research,aiming to provide a reference for researchers who work in analytical chemistry and drug research.

Objective To explore the real experiences of nutrition impact symptoms in esophageal cancer patients during diagnosis and treatment,and to provide references for developing nutritional management strategies.Methods Using purposive sampling,15 esophageal cancer patients admitted to the thoracic surgery department of a tertiary grade A hospital in Guangzhou from October to December 2024 were selected for semi-structured interviews.Thematic analysis was used for data analysis.Results 4 themes and 12 sub-themes were identified:①Multiple symptom perceptions:esophageal obstruction-dysphagia,appetite-affecting symptoms,multiple symptom over-lap,and individual differences in symptom perception.② Insufficient symptom cognition:overestimation of symptom controllability and biased symptom attribution.③ Negative emotional reactions:anxiety and fear about eating,frustration with declining eating function,and helplessness and guilt about losing control over eating.④ Di-verse symptom coping strategies:avoidance coping,adaptive coping,and active nutritional management.Conclusion The nutrition impact symptom experiences of esophageal cancer patients are complex and diverse.Healthcare professionals should promptly identify and assess nutrition impact symptoms,provide nutrition health education,strengthen psychological guidance,and develop culturally distinctive individualized nutritional management strategies.

Objective:To develop an artificial intelligence-based model for automated recognition of serum indices using machine vision and deep learning.Methods:This study was a cross-sectional study.Serum sample images were collected fromWest China Hospital of Sichuan University from September 21, 2020 to January 20, 2023 using the imaging device of the fully automated sample pre-processing system. A computer random number generator was used to randomly select one whole hour each day, and all serum sample images processed within that hour were included. After excluding samples with unqualified images and missing serum index results, a total of 5, 534 samples were included. These were divided into a training set and a test set in an 8∶2 ratio using Python random shuffle function, and 4, 458 samples were in the training set and 1, 076 samples were in the test set. After manual inspection, the serum regions were annotated using the MATLAB Image Labeler tool and converted into YOLO format, and a YOLO v5-based model was constructed for automatic serum region extraction. The actual values of lipemia index (L-index), hemolysis index (H-index), and icterus index (I-index) were measured using the automatic biochemical analyzerwith matched reagent kits. A serum index regression model was constructed based on the MobileNet v2 network using the PyTorch 1.10.0 framework. The grading performance of the model was evaluated using accuracy, Kappa coefficient, sensitivity, specificity, positive predictive value, and negative predictive value. Regression performance was assessed using root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and Bland-Altman analysis.Results:The overall accuracy rates for grading L-index, H-index, and I-index were 98.88%, 95.26%, and 92.47%, respectively, with Kappa coefficients of 0.72, 0.72, and 0.59. For L-index, MAE was 5.11, RMSE was 9.77, and R2 was 0.78. For H-index, MAE was 5.18, RMSE was 8.99, and R2 was 0.89. For I-index, MAE was 1.13, RMSE was 3.01, and R2 was 0.71. Bland-Altman analysis showed that 95.5%, 95.1%, and 95.7% of the data points fell within the consistency intervals for L-index, H-index, and I-index, respectively.Conclusion:The study developed an artificial intelligence-based serum index regression modelto estimate serum indices with high efficiency and accuracy. It shows great potential for reducing laboratory costs, improving clinical testing efficiency, and promoting intelligent development in laboratory medicine.