BackgroundDementia seriously affects the quality of life and lifespan of elderly people， with Alzheimer's disease （AD） being the most common type of dementia. Previous studies have suggested that gout may reduce the risk of developing AD， but the causal relationship between the two still requires further research. ObjectiveTo investigate the potential causal relationship between gout and AD through a two-sample Mendelian randomization （MR） analysis， so as to provide references for the prevention and treatment of AD. MethodsData from Genome-Wide Association Studies （GWAS） extracted in 2024 were analyzed， using pooled data on gout （6 810 cases in the case group and 477 788 cases in the control group） published by UK Biobank in 2021 as the exposure variable， and data on AD （3 899 cases in the case group and 214 893 cases in the control group） published by FinnGen in the same year as the outcome variable. The inverse-variance weighted， MR-Egger regression， weighted median estimation， simple model and weighted model were used to analyze the potential causal relationship between gout and AD. Pleiotropic effects were assessed using MR-Egger regression. Heterogeneity assessment was conducted using Cochran's Q test. The leave-one-out analysis was carried out for sensitivity analysis. And a funnel plot was drawn to detect potential publication bias. ResultsThe inverse-variance weighted analysis demonstrated a negative causal relationship between gout and AD （OR=0.004， 95% CI： 0~0.700， P<0.05）. The plot resembled a symmetrical inversed funnel， indicating the absence of publication bias. No heterogeneity was detected by Cochran's Q test. The MR-Egger regression indicated no significant horizontal pleiotropy. Concerning the reverse directions， no significant associations between AD and gout were noted. ConclusionThere is a negative causal relationship between gout and AD， with gout potentially reducing the risk of developing AD. ［Funded by The Third Batch of Social Welfare and Basic Research Projects （Medical and Health） of Zhongshan City in 2022 （number， 2022B3017）］

Background Environmental metal exposure is closely associated with the onset and progression of mild cognitive impairment (MCI) in the elderly. Effectively identifying hazardous metal exposure and assessing their interaction effects have significant public health implications. Objective To explore the relationship between urinary single metal and metal mixture exposure and MCI in elderly compound residents. Methods This study included 391 elderly individuals aged 60 and above from residential compounds in Zhongshan City, Guangdong Province. Concentrations of iron (Fe), copper (Cu), selenium (Se), arsenic (As), cadmium (Cd), manganese (Mn), chromium (Cr), nickel (Ni), vanadium (V), cobalt (Co), antimony (Sb), thallium (Tl), zinc (Zn), calcium (Ca), and magnesium (Mg) in urine were measured using inductively coupled plasma mass spectrometry. Cognitive function in the elderly was assessed using the Chinese version of the Mini-Mental State Examination (MMSE). Logistic regression was used to explore the relationship between single metal exposure level and MCI. LASSO regression and multi-metal logistic regression models were used to identify key metal ions associated with MCI. Bayesian kernel machine regression (BKMR) was employed to analyze the relationship between key metal ion mixtures and MCI, as well as the interactions between metals. Age, gender, education level, occupation, and body mass index were adjusted as covariates. Results A total of 78 among the 391 elderly individuals surveyed (19.94%) were diagnosed with MCI (MCI group), and the other 313 individuals were controls. The levels of Se, Cd, Mn, and As in the urine of the MCI group were significantly higher than those in the control group (P < 0.05). In the single-metal model, after adjusting for covariates and using the first quartile (Q₁) of each metal concentration as the reference, the OR for MCI in the elderly in the Q₄ group of Se was 2.190 (95%CI: 1.017, 4.716); for Cd, the OR was 2.345 (95%CI: 1.041, 5.283) in the Q₃ group and 2.371 (95%CI: 1.043, 5.393) in the Q₄ group; for Mn, the OR was 2.355 (95%CI: 1.038, 5.344) in the Q₂ group; for As, the OR was 3.377 (95%CI: 1.442, 7.908) in the Q₃ group and 2.886 (95%CI: 1.227, 6.788) in the Q₄ group; for Sb, the OR was 2.779 (95%CI: 1.234, 6.257) in the Q₂ group. When urinary metal concentrations were ln-transformed and included as continuous variables in the single-metal model, Cd concentration was positively correlated with MCI (OR=1.377; 95%CI: 1.008, 1.882; P=0.044). Cd, Se, Mg, Ca, Mn, As, Cr, Co, Tl, and Sb were selected by the LASSO regression model and included in the multi-metal model. In the multi-metal model, compared with Q₁, the OR for MCI in the elderly was 0.395 (95%CI: 0.164, 0.953) in the Q₂ group of Co and 0.390(95%CI: 0.167，0.911) in the Q₃ group of Co; for Mn, the OR in the Q₂ group was 2.636 (95%CI: 1.053, 6.596); for Sb, the OR in the Q₂ group was 2.640 (95%CI: 1.047, 6.658). As continuous variables, Mg (OR=0.472; 95%CI: 0.248, 0.899; P=0.022) and Co (OR=0.857; 95%CI: 0.737, 0.996; P=0.044) concentrations were negatively correlated with MCI. The BKMR mixture analysis suggested that Mg and Co exhibited a synergistic negative correlation with MCI, while Mn and Sb exhibited a synergistic positive correlation with MCI. Mg and Co attenuated the positive correlation of Mn and Sb with MCI, whereas Mn weakened the protective effects of Mg and Co. Conclusion Elevated levels of Se, Cd, As, Mn, and Sb in urine may increase the risk of MCI in the elderly, while Mg and Co have protective effects. Potential synergistic or antagonistic interactions may be found among Mn, Sb, Mg, and Co, which should not be overlooked in terms of their impact on the cognitive function of the elderly.

BACKGROUND: Molecular subtyping is an essential complementarity after pathological analyses for targeted therapy. This study aimed to investigate the consistency of next-generation sequencing (NGS) results between circulating tumor DNA (ctDNA)-based and tissue-based in non-small cell lung cancer (NSCLC) and identify the patient characteristics that favor ctDNA testing. METHODS: Patients who diagnosed with NSCLC and received both ctDNA- and cancer tissue-based NGS before surgery or systemic treatment in Lung Cancer Center, Sichuan University West China Hospital between December 2017 and August 2022 were enrolled. A 425-cancer panel with a HiSeq 4000 NGS platform was used for NGS. The unweighted Cohen's kappa coefficient was employed to discriminate the high-concordance group from the low-concordance group with a cutoff value of 0.6. Six machine learning models were used to identify patient characteristics that relate to high concordance between ctDNA-based and tissue-based NGS. RESULTS: A total of 85 patients were enrolled, of which 22.4% (19/85) had stage III disease and 56.5% (48/85) had stage IV disease. Forty-four patients (51.8%) showed consistent gene mutation types between ctDNA-based and tissue-based NGS, while one patient (1.2%) tested negative in both approaches. Patients with advanced diseases and metastases to other organs would be suitable for the ctDNA-based NGS, and the generalized linear model showed that T stage, M stage, and tumor mutation burden were the critical discriminators to predict the consistency of results between ctDNA-based and tissue-based NGS. CONCLUSION ctDNA-based NGS showed comparable detection performance in the targeted gene mutations compared with tissue-based NGS, and it could be considered in advanced or metastatic NSCLC.
Humans ; Carcinoma, Non-Small-Cell Lung/pathology* ; Circulating Tumor DNA/blood* ; High-Throughput Nucleotide Sequencing/methods* ; Female ; Male ; Lung Neoplasms/pathology* ; Middle Aged ; Mutation/genetics* ; Aged ; Adult ; Aged, 80 and over

Natural components serve the survival instincts of cells that are obtained through long-term evolution, while they often fail to meet the demands of engineered cells for efficiently performing biological functions in special industrial environments. Enzymes, as biological catalysts, play a key role in biosynthetic pathways, significantly enhancing the rate and selectivity of biochemical reactions. However, the catalytic efficiency, stability, substrate specificity, and tolerance of natural enzymes often fall short of industrial production requirements. Therefore, exploring and modifying enzymes to suit specific biomanufacturing processes has become crucial. In recent years, artificial intelligence (AI) has played an increasingly important role in the discovery, evaluation, engineering, and de novo design of proteins. AI can accelerate the discovery and optimization of proteins by analyzing large amounts of bioinformatics data and predicting protein functions and characteristics by machine learning and deep learning algorithms. Moreover, AI can assist researchers in designing new protein structures by simulating and predicting their performance under different conditions, providing guidance for protein design. This paper reviews the latest research advances in protein discovery, evaluation, engineering, and de novo design for biomanufacturing and explores the hot topics, challenges, and emerging technical methods in this field, aiming to provide guidance and inspiration for researchers in related fields.
Protein Engineering/methods* ; Artificial Intelligence ; Proteins/genetics* ; Computational Biology ; Machine Learning ; Data Mining ; Algorithms ; Deep Learning

Objective: To investigate the influencing factors of depressive symptoms and to construct and verify the prediction model of depressive symptoms in middle school students, so as to provide risk assessment tools for effectively screening depressive symptom. Methods: Physical examination and questionnaire survey were conducted among middle school students in one city in Guangdong Province from September to October in 2021 ( n =2 376) and from September to October in 2022 ( n =4 344) by a multistage cluster sampling method, and a nomographic prediction model of depressive symptoms in middle school student was constructed. The questionnaire survey was conducted using the student health status and influencing factors questionnaire (secondary school version) and the Center for Epidemiological Studies Depression Scale (CES-D) to measure the lifestyle and depressive symptom of middle school students. Results: The detection rate of depressive symptoms in 2021 was 23.3%. Multivariate Logistic regression analysis showed that irregular breakfast ( OR =2.64), school bullying ( OR =4.28), being beaten by parents ( OR =2.86), using mobile devices for a long time ( OR =1.08) and sitting for a long time ( OR =1.05) were positively related to depressive symptoms in middle school students ( P <0.05). Long sleep duration ( OR =0.78) and outdoor activity durations of 1-<2, 2-<3 and ≥3 h/d (compared with <1 h/d, OR =0.63, 0.61, 0.49) were negatively related to depressive symptoms in middle school students ( P < 0.05 ). Multivariate Logistic regression analysis showed that 7 statistically signifucant predictive factors constructed a nomogram, and the AUC of the nomogram was 0.77, which had been verified internally and externally with good differentiation and reliability. Conclusions The nomogram prediction model of depressive symptoms provides a convenient and effective risk assessment tool for depressive symptoms among middle school students. The life behavior, diet behavior and injury behavior of middle school students play an important role in the formation of depressive symptoms. It should pay attention to the impact of the behavioral factors on the mental health of middle school students.

Objective By comprehensively applying the integrated technology acceptance model,we explore the accept-ability of"6S management work"among members within the medical group and analyze important influencing factors.This pro-vides theoretical support and practical guidance for promoting work progress and sustainable development.Methods In order to determine the specific items for the questionnaire,a combination of literature review and expert consultation methods was used.The entire hospital staff was stratified sampled proportionally,and an online survey was conducted to collect feedback on the ac-ceptability from 354 employees who had been employed and stably served in the hospital before 2024.The questionnaire results were statistically described using SPSS 27.0 to clarify the current satisfaction with management work and the relevant factors.Results The community influence was the highest in the independent variable with a score of(2.11±0.91),followed by per-formance expectation with a score of(2.11±0.75),and giving expectation scored the lowest with a score of only(1.99±0.46).The dependent variables of behavioural intention and satisfaction scored(1.96±0.75)and(1.97±0.85)respectively.Conclusion Using the key factors influencing the behavioural intentions and satisfaction of medical group members,such as co-operation,community influence,performance expectations,and payment expectations,recommendations are made for the contin-uous optimization of the"6S management"process.

Objective:To explore the surgical intervention strategy for metastatic cervical lymph nodes surrounding the carotid artery in head and neck squamous cell carcinoma.Methods:A total of 62 patients with advanced head and neck tumors and carotid wrap by disease treated in Department of Otorhinolaryngology and Head and Neck Surgery, the Affiliated BenQ Hospital of Nanjing Medical University between June 2019 and December 2023 were reviewed, of whom 9 patients presented with metastatic squamous cell carcinoma in cervical lymph nodes of unknown primary or with no recurrence of primary lesion and all the 9 patients were males, aged from 48 to 79 years old, with≤level 2 of Eastern Cooperative Oncology Group-Performance Status (ECOG-PS). Radiographically common carotid artery (CCA) and/or internal carotid artery (ICA) were surrounded by≥270° with tumor. All the 9 patients received implantation of covered stent in carotid artery and radical resection of metastatic cervical lymph nodes. The success rate, complications, surgery-related complications, local recurrence rate, quality of life (QOL) and overall survival (OS) were analyzed. The QOL of patients was compared by paired rank sum test, and P<0.05 indicated statistically significant difference. The OS was analyzed by Kaplan-Meier. Results:The success rate of stent implantation was 100%, with no implantation-related complications. R0 resection was performed in 8 cases and R1 resection in 1 case. The QOL of patients after surgery was improved, and the improvements in "pain", "mood" and "anxiety" were statistically significant( Z values were -2.236, -2.460 and -2.200, respectively, and all P values were<0.05). Follow-up was 1-18 months, with a median of 7 months, and 1 case was lost to follow-up. Local recurrence occurred in 3 patients with an incidence of 37.5% (3/8). OS was 59.9% at 12 months after surgery. Conclusion:Implantation of covered stent in carotid artery combined with radical resection is an effective method for the treatment of cervical lymph node metastasis.

OBJECTIVE: To explore the clinical and genetic characteristics of four patients with medium-chain acyl-CoA dehydrogenase deficiency (MCADD). METHODS: Four children who had presented at the Children's Hospital Affiliated to Zhengzhou University between August 2019 and August 2021 were selected as the study subjects. Clinical data of the children were collected. The children were subjected to whole exome sequencing (WES). RESULTS: All of the four children were diagnosed with MCADD. Blood amino acid and ester acyl carnitine spectrum test showed that the concentration of octanoyl carnitine (C8) was significantly increased. The main clinical manifestations included poor mental response (3 cases), intermittent diarrhea with abdominal pain (1 case), vomiting (1 case), increased transaminase (3 cases), and metabolic acidosis (2 cases). Five variants were identified by genetic testing, among which c.341A>G (p.Y114C) was unreported previously. Three were missense variants, one was frameshift variant and one was splicing variant. CONCLUSION The clinical heterogeneity of MCADD is obvious, and the severity of the disease may vary. WES can assist with the diagnosis. Delineation of the clinical symptoms and genetic characteristics of the disease can facilitate early diagnosis and treatment of the disease.
Child ; Humans ; Acyl-CoA Dehydrogenase/genetics* ; Carnitine ; Genetic Testing ; Lipid Metabolism, Inborn Errors/genetics* ; Neonatal Screening

OBJECTIVE: To explore the clinical features and genetic basis of a child with Galactosemia. METHODS: A child who had presented at the Children's Hospital Affiliated to Zhengzhou University on November 20, 2019 was selected as the study subject. Clinical data of the child was collected. Whole exome sequencing was carried out for the child. Candidate variants were validated by Sanger sequencing. RESULTS: Clinical manifestations of the child have included anemia, feeding difficulty, jaundice, hypomyotonia, abnormal liver function and coagulation abnormality. Tandem mass spectrometry showed increased citrulline, methionine, ornithine and tyrosine. Urine organic acid analysis showed increased phenyllactic acid, 4-hydroxyphenylacetic acid, 4-hydroxyphenyllactic acid, 4-hydroxyphenylpyruvate and N-acetyltyrosine. Genetic testing revealed that the child has harbored compound heterozygous variants of the GALT gene, namely c.627T>A (p.Y209*) and c.370G>C (p.G124R), which were respectively inherited from her healthy parents. Among these, c.627T>A (p.Y209*) was known as a likely pathogenic variant, while c.370G>C (p. G124R) was unreported previously and also predicted as a likely pathogenic variant(PM1+PM2_Supporting+PP3_Moderate+PPR). CONCLUSION Above discovery has expanded the spectrum of the GALT gene variants underlying Galactosemia. Patients with thrombocytopenia, feeding difficulties, jaundice, abnormal liver function and coagulation abnormality without obvious causes should be analyzed by screening of metabolic diseases in combination with genetic testing.
Child ; Female ; Humans ; Galactosemias/genetics* ; Genetic Testing ; Health Status ; Methionine ; Muscle Hypotonia ; Mutation

Cognitive impairment caused by chronic cerebral hypoperfusion (CCH) is associated with white matter injury (WMI), possibly through the alteration of autophagy. Here, the autophagy-lysosomal pathway (ALP) dysfunction in white matter (WM) and its relationship with cognitive impairment were investigated in rats subjected to two vessel occlusion (2VO). The results showed that cognitive impairment occurred by the 28th day after 2VO. Injury and autophagy activation of mature oligodendrocytes and neuronal axons sequentially occurred in WM by the 3rd day. By the 14th day, abnormal accumulation of autophagy substrate, lysosomal dysfunction, and the activation of mechanistic target of rapamycin (MTOR) pathway were observed in WM, paralleled with mature oligodendrocyte death. This indicates autophagy activation was followed by ALP dysfunction caused by autophagy inhibition or lysosomal dysfunction. To target the ALP dysfunction, enhanced autophagy by systemic rapamycin treatment or overexpression of Beclin1 (BECN1) in oligodendrocytes reduced mature oligodendrocyte death, and subsequently alleviated the WMI and cognitive impairment after CCH. These results reveal that early autophagy activation was followed by ALP dysfunction in WM after 2VO, which was associated with the aggravation of WMI and cognitive impairment. This study highlights that alleviating ALP dysfunction by enhancing oligodendrocyte autophagy has benefits for cognitive recovery after CCH.