BACKGROUND: The mechanisms distinguishing metabolically healthy from unhealthy phenotypes within the same BMI categories remain unclear. This study aimed to investigate the associations between regional fat distribution and metabolically unhealthy phenotypes in Chinese adults across different BMI categories. METHODS: This cross-sectional study involving 11833 Chinese adults aged 20 years and older. Covariance analysis, adjusted for age, compared the percentage of regional fat (trunk, leg, or arm fat divided by whole-body fat) between metabolically healthy and unhealthy participants. Trends in regional fat percentage with the number of metabolic abnormalities were assessed by the Jonckheere-Terpstra test. Odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated by logistic regression models. All analyses were performed separately by sex. RESULTS: In non-obese individuals, metabolically unhealthy participants exhibited higher percent trunk fat and lower percent leg fat compared to healthy participants. Additionally, percent trunk fat increased and percent leg fat decreased with the number of metabolic abnormalities. After adjustment for demographic and lifestyle factors, as well as BMI, higher percent trunk fat was associated with increased odds of being metabolically unhealthy [highest vs. lowest quartile: ORs (95%CI) of 1.64 (1.35, 2.00) for men and 2.00 (1.63, 2.46) for women]. Conversely, compared with the lowest quartile, the ORs (95%CI) of metabolically unhealthy phenotype in the highest quartile for percent arm and leg fat were 0.64 (0.53, 0.78) and 0.60 (0.49, 0.74) for men, and 0.72 (0.56, 0.93) and 0.46 (0.36, 0.59) for women, respectively. Significant interactions between BMI and percentage of trunk and leg fat were observed in both sexes, with stronger associations found in individuals with normal weight and overweight. CONCLUSIONS Trunk fat is associated with a higher risk of metabolically unhealthy phenotype, while leg and arm fat are protective factors. Regional fat distribution assessments are crucial for identifying metabolically unhealthy phenotypes, particularly in non-obese individuals.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Young Adult ; Adipose Tissue ; Body Fat Distribution ; Body Mass Index ; China/epidemiology* ; Cross-Sectional Studies ; Health Surveys ; Phenotype

Objective:To investigate the differences in electrophysiological brain development of neonates in Tibet and Beijing.Methods:This prospective cohort study included neonates with gestational ages of 28 to 40 weeks and 6 days, without asphyxia, hypoxia, or brain injury, who were born between January 2022 and June 2024 at the Tibet Autonomous Region People's Hospital and Peking University First Hospital. The first electroencephalographic (EEG) monitoring was completed within 48 hours to 7 days after birth, which included a 4-channel amplitude-integrated EEG (aEEG) and a 12-channel continuous EEG (cEEG). Two electrophysiology experts scored the EEG results according to a rating scale, and the intraclass correlation coefficient (ICC) was used to explore the consistency between different evaluators. Preterm infants with gestational ages of 32 to 36 weeks and 6 days and post-menstrual age (PMA) less than full-term at the first EEG monitoring were re-examined with aEEG and cEEG at PMA of 37 to 40 weeks and 6 days. Infants were grouped based on PMA at the first EEG monitoring. Spearman rank correlation was used to analyze the correlations between total aEEG+cEEG scores, individual aEEG and cEEG scores, and PMA, gestational age, birth weight, and head circumference at the first EEG monitoring. Mann-Whitney U test, Kruskal-Wallis H test, and Bonferroni correction were used to compare the differences in total aEEG+cEEG scores, individual aEEG and cEEG scores between Tibet and Beijing, among adjacent PMA groups, and for premature infants at full-term PMA. Results:(1) A total of 341 neonates were included in this study, including 154 cases from Tibet (nine cases in the PMA of 28-29 weeks and 6 days group, 13 cases in the PMA of 30-31 weeks and 6 days group, 28 cases in the PMA of 32-33 weeks and 6 days group, 38 cases in the PMA of 34-36 weeks and 6 days group, and 66 cases in the PMA of 37-40 weeks and 6 days group) and 187 cases from Beijing (10 cases in the PMA of 28-29 weeks and 6 days group, 10 cases in the PMA of 30-31 weeks and 6 days group, 16 cases in the PMA of 32-33 weeks and 6 days group, 91 cases in the PMA of 34-36 weeks and 6 days group, and 60 cases in the PMA of 37-40 weeks and 6 days group). (2) Inter-rater consistency:the consistency of PMA inferred based on the total aEEC+CEEC score and actual PMA was high in two raters ( ICCrater one=0.96, ICCrater two=0.94, both P<0.01). (3) The correlation between total aEEG+cEEG score and PMA ( r=0.80) was stronger than that between the aEEG alone or cEEG scores and PMA ( r were 0.79 and 0.66, respectively). The total aEEG+cEEG score also correlated with gestational age at birth ( r=0.74), birth weight ( r=0.69), and head circumference at first EEG monitoring ( r=0.69) (all P<0.01). (4) Regardless of whether in Tibet or Beijing, the total aEEG+cEEG score increased sequentially in the PMA of 30- 31 weeks and 6 days, 32-33 weeks and 6 days, 34-36 weeks and 6 days, and 37-40 weeks and 6 days groups; the cEEG score increased sequentially in the PMA of 32-33 weeks and 6 days group, 34-36 weeks and 6 days group, and 37-40 weeks and 6 days groups; the aEEG score in the PMA 32- 33 weeks and 6 days group was higher than that in the 30-31 weeks and 6 days group, and the score in the PMA 37-40 weeks and 6 days group was higher than that in the 34-36 weeks and 6 days group (Bonferroni correction, all P<0.05). (5) At PMA of 34-36 weeks and 6 days, the total aEEG+cEEG score [25 points (22-26 points) vs. 26 points (24-28 points), Z=－2.62, P=0.009] and cEEG score [12 points (12-14 points) vs. 15 points (13-16 points), Z=－4.77, P<0.001] of newborns in Tibet were lower than those in Beijing, while the aEEG score was higher than those in Beijing [12 points (10-13 points) vs. 11 points (10-12 points), Z=2.17, P=0.030]; at PMA of 37-40 weeks and 6 days, the cEEG score of newborns in Tibet was lower than those in Beijing [16 points (15-17 points) vs. 17 points (15-18 points), Z=－2.27, P=0.023]. (6) The total aEEG+cEEG score of preterm infants born at 32 to 33 weeks and 6 days in Tibet was lower at PMA full-term compared to those in Beijing [27 points (26-28 points) vs. 29 points (28 -30 points), Z=－2.94], and also lower compared to the total aEEG+cEEG score of full-term gestational age newborns in Tibet during their first EEG monitoring [29 points (27-30 points)] (both P<0.05). Conclusions:In the high-altitude hypobaric hypoxic environment, the electroencephalographic development of newborns, especially premature infants, maybe lag behind of plain areas. The combined use of aEEG+cEEG may provide a better evaluation of neonatal brain development than using cEEG or aEEG alone.

Objective:To investigate the differences in electrophysiological brain development of neonates in Tibet and Beijing.Methods:This prospective cohort study included neonates with gestational ages of 28 to 40 weeks and 6 days, without asphyxia, hypoxia, or brain injury, who were born between January 2022 and June 2024 at the Tibet Autonomous Region People's Hospital and Peking University First Hospital. The first electroencephalographic (EEG) monitoring was completed within 48 hours to 7 days after birth, which included a 4-channel amplitude-integrated EEG (aEEG) and a 12-channel continuous EEG (cEEG). Two electrophysiology experts scored the EEG results according to a rating scale, and the intraclass correlation coefficient (ICC) was used to explore the consistency between different evaluators. Preterm infants with gestational ages of 32 to 36 weeks and 6 days and post-menstrual age (PMA) less than full-term at the first EEG monitoring were re-examined with aEEG and cEEG at PMA of 37 to 40 weeks and 6 days. Infants were grouped based on PMA at the first EEG monitoring. Spearman rank correlation was used to analyze the correlations between total aEEG+cEEG scores, individual aEEG and cEEG scores, and PMA, gestational age, birth weight, and head circumference at the first EEG monitoring. Mann-Whitney U test, Kruskal-Wallis H test, and Bonferroni correction were used to compare the differences in total aEEG+cEEG scores, individual aEEG and cEEG scores between Tibet and Beijing, among adjacent PMA groups, and for premature infants at full-term PMA. Results:(1) A total of 341 neonates were included in this study, including 154 cases from Tibet (nine cases in the PMA of 28-29 weeks and 6 days group, 13 cases in the PMA of 30-31 weeks and 6 days group, 28 cases in the PMA of 32-33 weeks and 6 days group, 38 cases in the PMA of 34-36 weeks and 6 days group, and 66 cases in the PMA of 37-40 weeks and 6 days group) and 187 cases from Beijing (10 cases in the PMA of 28-29 weeks and 6 days group, 10 cases in the PMA of 30-31 weeks and 6 days group, 16 cases in the PMA of 32-33 weeks and 6 days group, 91 cases in the PMA of 34-36 weeks and 6 days group, and 60 cases in the PMA of 37-40 weeks and 6 days group). (2) Inter-rater consistency:the consistency of PMA inferred based on the total aEEC+CEEC score and actual PMA was high in two raters ( ICCrater one=0.96, ICCrater two=0.94, both P<0.01). (3) The correlation between total aEEG+cEEG score and PMA ( r=0.80) was stronger than that between the aEEG alone or cEEG scores and PMA ( r were 0.79 and 0.66, respectively). The total aEEG+cEEG score also correlated with gestational age at birth ( r=0.74), birth weight ( r=0.69), and head circumference at first EEG monitoring ( r=0.69) (all P<0.01). (4) Regardless of whether in Tibet or Beijing, the total aEEG+cEEG score increased sequentially in the PMA of 30- 31 weeks and 6 days, 32-33 weeks and 6 days, 34-36 weeks and 6 days, and 37-40 weeks and 6 days groups; the cEEG score increased sequentially in the PMA of 32-33 weeks and 6 days group, 34-36 weeks and 6 days group, and 37-40 weeks and 6 days groups; the aEEG score in the PMA 32- 33 weeks and 6 days group was higher than that in the 30-31 weeks and 6 days group, and the score in the PMA 37-40 weeks and 6 days group was higher than that in the 34-36 weeks and 6 days group (Bonferroni correction, all P<0.05). (5) At PMA of 34-36 weeks and 6 days, the total aEEG+cEEG score [25 points (22-26 points) vs. 26 points (24-28 points), Z=－2.62, P=0.009] and cEEG score [12 points (12-14 points) vs. 15 points (13-16 points), Z=－4.77, P<0.001] of newborns in Tibet were lower than those in Beijing, while the aEEG score was higher than those in Beijing [12 points (10-13 points) vs. 11 points (10-12 points), Z=2.17, P=0.030]; at PMA of 37-40 weeks and 6 days, the cEEG score of newborns in Tibet was lower than those in Beijing [16 points (15-17 points) vs. 17 points (15-18 points), Z=－2.27, P=0.023]. (6) The total aEEG+cEEG score of preterm infants born at 32 to 33 weeks and 6 days in Tibet was lower at PMA full-term compared to those in Beijing [27 points (26-28 points) vs. 29 points (28 -30 points), Z=－2.94], and also lower compared to the total aEEG+cEEG score of full-term gestational age newborns in Tibet during their first EEG monitoring [29 points (27-30 points)] (both P<0.05). Conclusions:In the high-altitude hypobaric hypoxic environment, the electroencephalographic development of newborns, especially premature infants, maybe lag behind of plain areas. The combined use of aEEG+cEEG may provide a better evaluation of neonatal brain development than using cEEG or aEEG alone.

Objective:To establish a graded method to avoid mean fluorescence intensity(MFI)threshold of HLA Class I antibodies corresponding antigen,and the HLAMatchmaker program has been used to select the minimum mismatch value of donor-patient epitopes.Evaluate the application value of combining both methods in selecting HLA compatible platelets(PTL)for patients with immune platelet transfusion failure(IPTR)in improving platelet the corrected count increment(CCI).Methods:A total 7 807 PLT cross-matching compatible were performed by the solid-phase red cell adherence(SPRCA)method for 51 IPTR patients.The Luminex single antigen flow cytometry was used to detect HLA Class I antibodies in patients,and detected the MFI value for different specificity antigens of HLA Class I antibodies,was graded into strong positive group(MFI＞4 000,level 1),medium positive group(1 000＜MFI 4 000,2),weak positive group(500＜MFI≤1 000,3),and one negative control group(MFI≤500).The results of 7 807 SPRCA their negative/positive reaction wells were enrolled and statistically analyzed in different grades and the four groups,the statistical differences between the four groups were compared.Multiple applications for the select HLA Class I compatible donor events were made for patients in two cases,and HLAMatchmaker program was used to calculate the number of HLA Class I epitopes mismatches between the donors and patients.The donor with the minimum number of epitopes mismatches was selected,while avoiding the corresponding antigens of HLA Class I antibodies in levels 1 and 2,the provision of HLA compatible platelets for IPTR.After the transfusions,the CCI value of the platelet transfusion efficacy evaluation index was calculated,and the clinical evaluation of the transfusion effect was obtained through statistical analysis.Results:There were statistically significant differences in the positive results of SPRCA immunoassay among the strong positive group,medium positive group,and weak positive group of 51 IPTR patients with different specific of HLA-I class antibodies and corresponding antigens(all P＜0.001).The positive results showed a range from high to low,with strong positive group＞medium positive group＞weak positive group.There were a statistical difference among between the strongly positive or moderately positive groups and the negative control group(P＜0.001).There was no statistical difference between the weakly positive group and the negative control group(P＞0.05).The strong positive group was set as the corresponding specific HLA Class I site corresponding antigen grade 1 avoidance threshold,the medium positive group as the grade 2 avoidance thresholds,and the weak positive group as the grade 3 avoidance threshold.In the case of donor platelet shortage,it is not necessary to avoid the weak positive group.Avoiding the strategy of donor antigens and HLAMatchmaker program scores≤7 corresponding to HLA Class I antibodies of levels 1 and 2,with CCI values＞4.5 × 109/L within 24 hours,can obtain effective clinical platelet transfusion conclusions.Conclusion:When selecting HLA Class I compatible donors for IPTR patients,the grading avoids HLA Class I antibodies corresponding to donor antigens,and the donor selection strategy with the minimum scores of HLAMatchmaker program is comprehensively selected.The negative result confirmed by platelet cross-matching experiments has certain practical application value for improving platelet count in IPTR patients.

Lithocarpus litseifolius is rich in the chalcones phloridzin and trilobatin, the biosynthesis pathways of which have not been fully demonstrated. Chalcone synthase(CHS) is the first key rate-limiting enzyme in the biosynthesis of flavonoids in plants. To explore the functions of CHS gene family in chalcone synthesis of L. litseifolius, this study screened out two CHS genes(LlCHS1 and LlCHS2) from the transcriptome data of this plant, and then bioinformatics analysis and functional characterization were performed for the two genes. The bioinformatics analysis showed that LlCHS1 and LlCHS2 were acidic hydrophilic stable proteins with no transmembrane domain, composed of 395 and 390 amino acid residues, respectively. Both of them contained the characteristic amino acid sequence "WGVLFGFGPGL" and highly conserved active sites(Cys-164, Phe-215, His-303, and Asn-336) of the CHS family. The phylogenetic tree showed that LlCHS1 shared the same clade with similar genes in Aquilaria sinensis, and LlCHS2 was closely related to similar genes in Malus domestica. Under exogenous addition of phloretic acid, co-expression of LlCHS1 or LlCHS2 with Aa4CL from Aromatoleum aromaticum in Escherichia coli catalyzed the production of phloretin from phloretic acid. This study laid a theoretical foundation for revealing the functions of CHS in plants and provided new enzymatic modules for producing phloretin by synthetic biology.
Acyltransferases/chemistry* ; Phylogeny ; Plant Proteins/chemistry* ; Cloning, Molecular ; Amino Acid Sequence

Objective To evaluate the immunogenicity of inactivated quadrivalent influenza vaccine (QIV) in people over 60 years old. Methods Databases including PubMed, EMBASE, Cochrane Library, China Biology Medicine disc, Wangfang Database and China National for Biotechnology Information were searched for random control studies comparing and analyzing the immunogenicity and safety between QIV and inactivated trivalent influenza vaccine (TIV) in people over 60 years old. Meta-analysis of the included literature data was performed using Stata11.0 software. Results A total of 9 articles were included in this study. There was no difference in seroconversion rates (SCR) and seroprotection rates (SPR) for the same vaccine strain after inoculation between QIV and TIV, while for the B vaccine strain (B/Victoria or B/Yamagata) not included in TIV, the SCR and SPR of QIV were significantly higher: SCR RR of 2.04 (95%CI:1.48~2.83) and SPR RR of 1.21 (95%CI:1.11~1.31) for B/Victoria; SCR RR of 2.35 (95%CI:2.04~2.69) and SPR RR of 1.12 (95%CI:1.02~1.23) for B/Yamagata. Conclusion For people over 60 years old, QIV has good immunogenicity, and produces better immunogenicity against influenza B vaccine strains not included in TIV.

Intestinal flora and its metabolites are closely related to the progression of type 2 diabetes mellitus(T2DM). Eubacterium is one of the dominant intestinal flora, and its metabolites short-chain fatty acids (SCFAs) play a leading role in regulating intestinal metabolic balance. It has been reported that SCFAs can regulate the secretion of glucagon-like peptide-1, improve the function of pancreatic β cells, participate in bile acids metabolism and regulate the production of inflammatory factors in T2DM. Based on the above research background, this article mainly reviews the relationship between Eubacterium and its metabolite SCFAs and T2DM and its regulatory mechanism.
Humans ; Diabetes Mellitus, Type 2 ; Eubacterium/metabolism* ; Fatty Acids, Volatile/metabolism* ; Gastrointestinal Microbiome

OBJECTIVE: To investigate the clinical characteristics, diagnosis, and treatment of one patient with primary adrenal natural killer/T-cell lymphoma (PANKTCL), and to strengthen the understanding of this rare type of lymphoma. METHODS: The clinical manifestations, diagnosis and treatment process, and prognosis of the patient admitted in our hospital were retrospectively analyzed. RESULTS: Combined with pathology, imaging, bone marrow examination， etc, the patient was diagnosed with PANKTCL (CA stage, stage II; PINK-E score 3, high-risk group). Six cycles of "P-GemOx+VP-16" regimen（gemcitabine 1 g/m² d1 + oxaliplatin 100 mg/m² d 1 + etoposide 60 mg/m² d 2-4 + polyethylene glycol conjugated asparaginase 3 750 IU d 5） was performed, and complete response was assessed in 4 cycles. Maintenance therapy with sintilimab was administered after the completion of chemotherapy. Eight months after the complete response, the patient experienced disease recurrence and underwent a total of four courses of chemotherapy, during which hemophagocytic syndrome occurred. The patient died of disease progression 1 month later. CONCLUSION PANKTCL is rare, relapses easily, and has a worse prognosis. The choice of the "P-GemOx+VP-16" regimen combined with sintilimab help to improve the survival prognosis of patient with non-upper aerodigestive tract natural killer /T-cell lymphoma.
Humans ; Treatment Outcome ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Retrospective Studies ; Etoposide ; Neoplasm Recurrence, Local/drug therapy* ; Asparaginase ; Deoxycytidine ; Lymphoma, T-Cell, Peripheral/drug therapy* ; Lymphoma, Extranodal NK-T-Cell/therapy* ; Oxaliplatin/therapeutic use*

Objective: To analyze the expression levels of the F9 gene and F9 protein in hepatocellular carcinoma by combining multiple gene chip data, real-time fluorescence quantitative PCR (RT qPCR), and immunohistochemistry. Additionally, explore their correlation with the occurrence and development of hepatocellular carcinoma, as well as with various clinical indicators and prognosis. Methods: The mRNA microarray dataset from the GEO database was analyzed to identify the F9 gene with significant expression differences associated with hepatocellular carcinoma. Liver cancer and adjacent tissues were collected from 18 cases of hepatocellular carcinoma. RT-qPCR method was used to detect the F9 gene expression level. Immunohistochemistry was used to detect the F9 protein level. Combined with the TCGA database information, the correlation between F9 gene expression level and prognostic and clinicopathological parameters was analyzed. The biological function of F9 co-expressed genes associated with hepatocellular carcinoma was analyzed by the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Statistical analysis was performed using Graphpad Prism software. Results: Meta-analysis results showed that the expression of the F9 gene was lower in HCC tissues than in non-cancerous tissues. Immunohistochemistry results were basically consistent with those of RT-qPCR. The data obtained from TCGA showed that the F9 gene had lower expression values in stages III-IV, T3-T4, and patients with vascular invasion. A total of 127 genes were selected for bioinformatics analysis as co-expressed genes of F9, which were highly enriched in redox processes and metabolic pathways. Conclusion: This study validates that the F9 gene and F9 protein are lower in HCC. The down-regulation of the F9 gene predicts adverse outcomes, which may provide a new therapeutic target for HCC.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Down-Regulation ; Prognosis ; Gene Expression ; Gene Expression Regulation, Neoplastic

OBJECTIVES: To investigate the efficacy and required indicators of Children Neuropsychological and Behavioral Scale-Revision 2016 (CNBS-R2016) in the differential diagnosis of autism spectrum disorder (ASD) and global developmental delay (GDD). METHODS: A total of 277 children with ASD and 415 children with GDD, aged 18-48 months, were enrolled as subjects. CNBS-R2016 was used to assess the developmental levels of six domains, i.e., gross motor, fine motor, adaptive ability, language, social behavior, and warning behavior, and a total of 13 indicators on intelligence age and developmental quotient (DQ) were obtained as the input features. Five commonly used machine learning classifiers were used for training to calculate the classification accuracy, sensitivity, and specificity of each classifier. RESULTS: DQ of warning behavior was selected as the first feature in all five classifiers, and the use of this indicator alone had a classification accuracy of 78.90%. When the DQ of warning behavior was used in combination with the intelligence age of warning behavior, gross motor, and language, it had the highest classification accuracy of 86.71%. CONCLUSIONS Machine learning combined with CNBS-R2016 can effectively distinguish children with ASD from those with GDD. The DQ of warning behavior plays an important role in machine learning, and its combination with other features can improve classification accuracy, providing a basis for the efficient and accurate differential diagnosis of ASD and GDD in clinical practice.
Child ; Humans ; Autism Spectrum Disorder/psychology* ; Diagnosis, Differential ; Machine Learning ; Social Behavior