Objective: To investigate the hematological characteristics of the rare McLeod phenotype associated with X-linked chronic granulomatous disease, KEL and XK gene analysis, identification of unexpected antibodies, serological characteristics of high-frequency antigen antibodies, and transfusion strategies. Methods: Serological methods were employed to determine the ABO, Rh, and other blood group system antigen phenotypes of the child, along with screening and identification of unexpected antibodies. The titers of high-frequency antigen antibodies were measured using tube antihuman globulin and microcolumn gel card techniques. Kell blood group typing was performed using serological and genotyping methods, while XK gene sequencing was conducted via next-generation sequencing. Peripheral blood smears from the child's mother were examined for erythrocyte morphology. Results: The child's serological results were as follows: blood group O, ccDEE, MM, Le(a-b+), JK(a+b+), Fy(a+b-), and Kell phenotype K-k+, Kp(a-b+). Plasma analysis revealed alloantibodies anti-C、e, as well as a high-frequency antigen antibody anti-KL, with titers of 512 (tube method) and 2 048 (microcolumn gel method). Genotyping results showed KEL genotype K-k+, Kp(a-b+), Js(a-b+), while XK gene NGS identified a hemizygous deletion of exons 1-3 (XK N. 01), consistent with XK: -1 or Kx-(McLeod). The mother's peripheral blood smear exhibited prominent acanthocytes. Conclusion: The hematological features of this rare McLeod phenotype with X-CGD include weakened Kell antigen expression and a complete exon deletion in the XK gene. Early clinical attention should be given to the symptoms and laboratory diagnosis of X-linked chronic granulomatous disease in pediatric patients. XK genotyping for McLeod phenotype should be prioritized to guide cautious transfusion strategies, preventing life-threatening complications due to incompatible blood products.

Metastasis is the leading cause of death from cutaneous melanoma. Identifying metastasis-related targets and developing corresponding therapeutic strategies are major areas of focus. While functional genomics strategies provide powerful tools for target discovery, investigations at the protein level can directly decode the bioactive epitopes on functional proteins. Aptamers present a promising avenue as they can explore membrane proteomes and have the potential to interfere with cell function. Herein, we developed a target and epitope discovery platform, termed functional aptamer evolution-enabled target identification (FAETI), by integrating affinity aptamer acquisition with phenotype screening and target protein identification. Utilizing the aptamer XH3C, which was screened for its migration-inhibitory function, we identified the Chondroitin Sulfate Proteoglycan 4 (CSPG4), as a potential target involved in melanoma migration. Further evidence demonstrated that XH3C induces cytoskeletal rearrangement by blocking the interaction between the bioactive epitope of CSPG4 and integrin α4. Taken together, our study demonstrates the robustness of aptamer-based molecular tools for target and epitope discovery. Additionally, XH3C is an affinity and functional molecule that selectively binds to a unique epitope on CSPG4, enabling the development of innovative therapeutic strategies.

Objective To observe the value of machine learning(ML)models based on ultrasound radiomics for preoperatively distinguishing atypical parathyroid tumor(APT)/parathyroid carcinoma(PC)and parathyroid adenoma(PA).Methods Totally 330 primary hyperparathyroidism patients who underwent surgical treatments were retrospectively enrolled and categorized into APT/PC group(n=78)and PA group(n=252)according to surgical pathology and clinical follow-up results,also divided into training set(n=231)and test set(n=99)at the ratio of 7∶3.Based on preoperative ultrasound,545 radiomics features were extracted,and recursive feature elimination(RFE),Kruskal-Wallis or analysis of variance methods were used to screen the features,respectively.Support vector machine(SVM),linear discriminant analysis(LDA),least absolute shrinkage and selection operator logistic regression(LRLASSO),also random forest(RF)and decision tree(DT)algorithms were adopted to construct ML models for differentiating APT/PC and PA,respectively.Then the models were trained in training set,their performance were verified in test set,and a 5-fold cross-validation was adopted to screen out the better combinations.Results Compared with Kruskal-Wallis and analysis of variance methods,the distinguishing efficacy of SVM,LDA,LRLASSO,RF and DT models constructed based on features screened out using RFE method in training set(area under the curve[AUC]=0.870,0.878,0.850,0.847,1.000)and test set(AUC=0.856,0.842,0.827,0.847 and 0.704)were all relatively higher.In test set,the AUC of SVM,LDA,LRLASSO and RF models constructed based on the features screened out using RFE method(included 25,23,17 and 23 features)were all higher than that of DT model(8 features)(all P＜0.001).No significant difference of AUC was found between SVM,LRLASSO or RF models and LDA model(all P＞0.05).The AUC of SVM and RF models were higher than that of LRLASSO model(both P＜0.05),while of SVM and RF models were not significantly different(P＞0.05),indicating that SVM,LDA and RF models were better ones.Conclusion SVM,LDA,LRLASSO,RF and DT models based on ultrasound radiomics could effectively distinguish APT/PC and PA preoperatively,among which SVM,LDA and RF models had better diagnostic efficacy.

Objective To develop a scientific and reliable sensitive index system of nursing quality in enteral nutrition for neurocritical patients to ensure the effective implementation of enteral nutrition.Methods Literature on enteral nutrition for neurocritical patients were systematically retrieved from databases,such as BMJ Best Practice,UpToDate,Joanna Briggs Institute(JBI)Evidence-Based Healthcare Database,American Society for Parenteral and Enteral Nutrition(ASPEN),European Society for Clinical Nutrition and Metabolism(ESPEN),National Guideline Clearinghouse(NGC),Guidelines International Network(GIN),Medlive,the Cochrane Library,PubMed,Cumulative Index to Nursing and Allied Health Literature(CINAHL),SinoMed,and China National Knowledge Infrastructure(CNKI)and Wanfang Data.The initial questionnaire was formulated by using the quality evaluation model of"structure-process-outcome".The index system was established by using the Delphi method,and the index weight was determined by the analytic hierarchy process.Results A total of 11 papers were included,of which 5 were graded in A and 6 in B.The effective recovery rates of the two rounds of correspondence questionnaires were 100%(19/19),the expert authority coefficients was 0.864,and the Kendall harmony coefficients were 0.328 and 0.392(P<0.01),respectively.Consequently,a sensitive index system of nursing quality in enteral nutrition for neurocritical patients was established,which encompassed 3 primary indexes,10 secondary indexes and 28 tertiary indexes.Conclusion The index system developed in this study is scientific,reliable and clinically applicable.It conforms to the characteristics of clinical management and nursing,thereby it provides a reference for assessment of the nursing quality in enteral nutrition for neurocritical patients.

Objective:To investigate the prevalence and risk factors of overweight and obesity among Chinese children aged 3-18 years from 11 provinces, antonomous regions, or municipalities.Methods:This national cross-sectional community health survey utilized a multistage stratified cluster-random sampling method to recruit 193 997 nationally representative participants from 11 provinces, autonomous regions, or municipalities between January 2017 and December 2019. All participants underwent physical examinations, and their caregivers completed questionnaires assessing participants′ dietary, lifestyle, familial, and perinatal information. Multilevel multinomial logistic regression models were employed to identify the potential risk factors.Results:The cohort comprised 193 997 children (102 178 boys, 91 819 girls),aged (10±4) years. Overall prevalence rates were 30 574(15.8%)overweight children and 17 217(8.9%) obesity children. Boys exhibited higher overweight and obesity rates than girls (17.0% (17 368/102 178) vs. 14.4% (13 206/102 178), 11.3% (11 553/91 819) vs. 6.2% (5 664/91 819), χ2=249.12,1 578.69,both P<0.001). The detection rates of obesity in Tanner stage 2 and 3 were the highest in boys and girls, with 13.4%(2 231/16 665) and 8.6%(880/10 221) respectively. Risk factors for obesity included parental overweight (paternal OR=2.34 and maternal OR=2.29), annual household income of 100 000-200 000 yuan (compared with<100 000 yuan, OR=1.04), higher paternal education (compared with below high school,high school and a college education OR=1.09,1.14), birth weight >4.0 kg (≤5 and>5 years old OR=1.74, 1.44,respectively), and western food consumption≥1 time/month (compared with<1, 1-2, 3-4,>4 times/month OR=1.36, 1.30, 1.67(≤5 years), 1.19, 1.16, 1.15 (>5 years), respectively) (all P<0.05). Conversely, coarse grain intake≥1 times/week (compared with<1 times/week, every day, 3-4, 1-2 times/week OR=0.74, 0.80, 0.71 (≤5 years), 0.75, 0.87, 0.90(>5 years), respectively, all P<0.05) was associated with reduced obesity risk. Conclusions:Obesity epidemiology in children demonstrates significant heterogeneity across age, gender, geographic regions, and pubertal stages. It is necessary to establish a personalized prevention and control strategy.

OBJECTIVE To systematically analyze the functional system and construction requirements for infection prevention and control('infection control system'in short)in medical institutions so as to facilitate the effective,standardized and practical construction of the infection control system.METHODS The questionnaires were de-signed based on the relevant criteria and literatures that were released in China with the combination of expect con-sultant and were distributed to experts or professionals involving multiple fields such as hospital infection manage-ment,clinical medical treatment and information technology.The questionnaires were recycled,summarized and analyzed.RESULTS The list of functions of the infection control system(consultative draft)was formulated after review of literatures and expert consultation,including fundamental functions such as data management,case sur-veillance and intervention feedback as well as the advanced functions like target surveillance,occupational protec-tion and interconnection.The surveyed subjects agreed unanimously after the questionnaire survey that all of the function modules and elements enlisted were important,the average score of importance was more than 4 points,the score of coefficient of variable(CV)for importance of the function modules was less than 0.25,indicating that there was high consistency in the opinions among the surveyed subjects.The element of tracing and epidemiologi-cal survey function was adopted and added according to the feedback suggestions from some of the subjects;two function elements including data query and clinical interaction were revised,and the list of function requirements for the infection control systems was finally defined.CONCLUSION The requirements for functions of the infection control system that are determined in the study can provide important bases and data support for the research and standardized development of future infection control system.

Objective To compare the node strength in white matter networks between depressive disorder and bipolar depression patients,analyze structural connectivity impairments across brain regions,and assess their diagnostic utility.Methods This longitudinal study initially enrolled 91 patients with a baseline diagnosis of depressive episode.All subjects underwent diffusion tensor imaging at recruitment and white matter structural weighted networks were constructed using deterministic fiber tracking.After≥9 years of naturalistic follow-up,23 patients who maintained a diagnosis of major depressive disorder(MDD group)and 18 patients who maintained a diagnosis of bipolar disorder(BD group),while 30 demographically matched healthy controls(HC group)were included for comparison.The differences in nodal connection strength within the brain white matter networks among the three groups were compared.Furthermore,the receiver operator characteristic(ROC)curve was utilized to evaluate the diagnostic value of the differential brain regions in distinguishing between MDD and BD.Results In the left anterior cingulate gyrus,the node strength was lower in the BD than in the MDD group(3.89±0.76 vs.4.74±0.60).However,the node strength in the right caudate nucleus(4.94±1.26 vs.3.46±0.99)and right globus pallidus(1.98±0.67 vs.1.25±0.29)was higher in the BD than in the MDD group(P<0.01,FWE-corrected).The combined connectivity strengths of three brain regions—the left anterior cingulate gyrus,right caudate nucleus and right globus pallidus—were used to differentiate between MDD and BD,and an ROC curve was plotted,with an area under the curve(AUC)of 0.95(95%CI:0.91～0.99;P<0.001).The sensitivity and the specificity were 0.89 and 0.87,respectively.Conclusion The differences in node strength between patient groups may serve as a potential neuroimaging biomarker.Integration of node connectivity strengths from these differential brain regions can achieve superior discrimination accuracy.

Nanopore sequencing,as a representative of third-generation sequencing technology,is widely used in molecular biology research.It offers several advantages,including high throughput,ultra-long read lengths,real-time sequencing,and the absence of amplification and labeling requirements.This technology has been applied for the detection of various pathogens,genomic typing,structural variation analysis,and personalized treatment guidance,making it valuable for pathogen monitoring and medical research.This article focuses on the principles of nanopore sequencing technology,its advantages,and its applications in molecular biology and molecular medicine.The limitations of nanopore sequencing and its future development directions are also summarized,providing new perspectives for further research in this field.

Objective:To investigate the effect of childhood trauma on non-suicidal self-injury (NSSI) behavior in patients with depression.Method:Embase, PubMed, Cochrane Library, PsycINFO, China National Knowledge Infrastructure, Wanfang Data and China Biology Medicine dis were searched from inception to March 2024 for cross-sectional, case-control and cohort studies on childhood trauma and NSSI in patients with depression. Two researchers independently screened studies, extracted data, and assessed quality. The effect indicators were the odds ratio ( OR) of childhood trauma and school bullying to NSSI in the depressed population and the mean difference ( MD) of the childhood trauma subscale scores between the depressed population with and without NSSI. Meta-analysis was performed using Review Manager 5.3 and Stata17 software. Results:A total of 29 articles with 5 095 depressed patients were included. Childhood trauma was significantly associated with NSSI in patients with depression ( OR=2.91, 95% CI=2.01-4.21). Various forms of childhood trauma were related to NSSI behaviors in depressive patients: physical abuse ( MD=0.77, 95% CI=0.47-1.06), emotional abuse ( MD=2.99, 95% CI=2.10-3.88), physical neglect ( MD=1.17, 95% CI=0.47-1.87), emotional neglect ( MD=2.59, 95% CI=1.82-3.36), and sexual abuse ( MD=0.35, 95% CI=0.19-0.51). Additionally, school bullying among extra-family factors was identified as a risk factor for NSSI ( OR=2.16, 95% CI=1.46-3.18). Conclusion:Childhood trauma is a risk factor for NSSI behaviors in patients with depression. Different types of childhood trauma within the family, including various forms of abuse and neglect, and school bullying outside the family are related to NSSI behaviors in this population.