Objective: To reveal the molecular biological mechanism of a rare Dc-variant individual using PacBio third-generation sequencing technology. Methods: ABO and Rh blood type identification, DAT, unexpected antibody screening and D antigen enhancement test were conducted by serological testing. The absorption-elution test was used to detect the e antigen. RHCE gene typing was performed by PCR-SSP, and the 1-10 exons of RHCE were sequenced by Sanger sequencing. The full-length sequences of RHCE, RHD and RHAG were detected by PacBio third-generation sequencing technology. Results: Serological findings: Blood type O, Dc-phenotype, DAT negative, unexpected antibody screening negative; enhanced D antigen expression; no detection of e antigen in the absorption-elution test. PCR-SSP genotyping indicated the presence of only the RHCE c allele. Sanger sequencing results: Exons 5-9 of RHCE were deleted, exon 1 had a heterozygous mutation at c. 48G/C, and exon 2 had five heterozygous mutations at c. 150C/T, c. 178C/A, c. 201A/G, c. 203A/G and c. 307C/T. Third-generation sequencing results: RHCE genotype was RHCE 02N. 08/RHCE-D(5-9)-CE; RHD genotype was RHD 01/RHD 01; RHAG genotype was RHAG 01/RHAG 01 (c. 808G>A and c. 861G>A). Conclusion: This Dc-individual carries the allele RHCE 02N. 08 and the novel allele RHCE-D(5-9)-CE. The findings of this study provide data support and a theoretical basis for elucidating the molecular mechanisms underlying RhCE deficiency phenotypes.

Objective: To assess the awareness and associated factors of wild mushroom poisoning among students in Guizhou Province, so as to provide a scientific foundation for wild mushroom poisoning prevention and control among students. Methods: By a multi stage stratified cluster random sampling method, 1 162 students from Guizhou Province were selected in May 2024. The questionnaire survey was administered to evaluate knowledge regarding wild mushroom poisoning. Data were analyzed employing the χ 2 test and Logistic regression model. Results: Among the nine questions assessing awareness of wild mushroom poisoning, only three had the awareness rate exceeding 70%. Binary Logistic regression analysis revealed that students who "actively learn about the prevention of wild mushroom poisoning" ( OR=0.48, 95%CI =0.26-0.92) and "spread knowledge about wild mushroom poisoning to others" ( OR=0.47, 95%CI =0.33-0.69) scored higher on the wild mushroom poisoning knowledge questions ( P <0.05). Conversely, students with a habit of consuming wild mushrooms ( OR=1.52, 95%CI =1.15-2.02) scored lower ( P < 0.05 ). 42.3% of the students suggested that scientific dissemination and publicity about wild mushrooms should be intensified. Conclusions The awareness rate of wild mushroom poisoning knowledge among students in Guizhou Province requires further attention. Comprehensive knowledge should be disseminated systematically through various channels to further improve students awareness of the prevention and control of wild mushroom poisoning.

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

Objective To analyze the caregiver presence needs and their influencing factors among hospitalized elderly non-surgical patients and provide a basis for formulating relevant policies.Methods A descriptive qualitative study method was adopted.Through purposive sampling,semi-structured interviews were conducted on elderly non-surgical patients and their families and medical staff in Peking Union Medical College Hospital from September to October 2023.MAXQDA 2020 and the 7-step phenomenological analysis method of Colaizzi were used to classify and code the interview contents and identify themes.Results The categories of caregiver presence needs of elderly non-surgical patients included basic living assistance needs,disease monitoring needs,psychological support needs,as well as the needs for family members to provide economic support and participate in treatment decision-making.The influencing factors included advanced age,frailty,the lack of self-care ability in patients with comorbidities,the susceptibility of patients to sudden situations during the disease exacerbation period,the increased risk of unexpected events in patients with psychological distress,and patients' concerns about social support and medical decision-making.Conclusion The caregiver presence needs of elderly non-surgical patients during hospitalization are high and influenced by multiple factors.
Humans ; Caregivers/psychology* ; Aged ; Hospitalization ; Social Support ; Male ; Qualitative Research ; Female

Objective To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.Methods The GSE95065 and GSE59785 datasets of scleroderma from GEO database were used for analyzing expressions of mitochondria-related genes,and the differential genes were identified by Random forest,LASSO regression and SVM algorithms.Based on these differential genes,an artificial neural network model was constructed,and its diagnostic accuracy was evaluated by 10-fold crossover verification and ROC curve analysis using the verification dataset GSE76807.The mRNA expressions of the key genes were verified by RT-qPCR in a mouse model of scleroderma.The CIBERSORT algorithm was used to estimate the bioinformatic association between scleroderma and the screened biomarkers.Results A total of 24 differential genes were obtained,including 11 up-regulated and 13 down-regulated genes.Seven most relevant mitochondria-related genes(POLB,GSR,KRAS,NT5DC2,NOX4,IGF1,and TGM2)were screened using 3 machine learning algorithms,and the artificial neural network diagnostic model was constructed.The model showed an area under the ROC curves of 0.984 for scleroderma diagnosis(0.740 for the verification dataset and 0.980 for cross-over validation).RT-qPCR detected significant up-regulation of POLB,GSR,KRAS,NOX4,IGF1 and TGM2 mRNAs and significant down-regulation of NT5DC2 in the mouse models of scleroderma.Immune cell infiltration analysis showed that the differential genes in scleroderma were associated with follicular helper T cells,immature B cells,resting dendritic cells,memory activated CD4+T cells,M0 macrophages,monocytes,resting memory CD4+T cells and mast cell activation.Conclusion The artificial neural network diagnostic model for scleroderma established in this study provides a new perspective for exploring the pathogenesis of scleroderma.

Objective to establish a combined diagnosis model of scleroderma related genes based on gene expression comprehensive database(GEO)and artificial neural network(ANN)and to evaluate its effect and to predict and analyze targeted traditional Chinese medicine.Methods two scleroderma chips GSE23741 and GSE95065 were obtained from the GEO database as the training group data set.Random forest and lasso regression algorithms were used to screen the key genes of scleroderma and construct the ANN model for the diagnosis of scleroderma.The validation data sets GSE76807,GSE32413 and GSE59785 were used to verify the model,and the area under curve(AUC)analysis was used to evaluate the clinical application value of ANN model.The relative expression of key gene mRNA was verified by RT-qPCR experiment.The CIBERSORT algorithm was used to estimate the bioinformatics association between scleroderma and the screened biomarkers.Finally,the key genes were used to screen the targeted traditional Chinese medicine.Results A total of 167 differential genes were obtained.Furthermore,the five most relevant key genes(SERPINE2,SFRP4,SUGCT,FBLN5,NRXN2)were screened by machine learning,and the artificial neural network diagnosis model was constructed.The model was used to draw the subject operating characteristic(ROC)curves diagnosed by the training group and the verification group,and the AUC value of the training group was 1.000.The AUC of verification group were 0.770,0.795 and 0.872 respectively.The result of RT-qPCR experiment is consistent with that of machine learning algorithm.Immune cell infiltration analysis showed that the relative content of memory CD4+T cells was significantly increased in scleroderma group,while the relative content of γ δ T cells in normal group was significantly increased.Key genes are associated with macrophage M1,T cells,memory activated CD4+T cells,resting mast cells,CD8+T cells and so on.According to the key genes,12 traditional Chinese medicines were screened.Most of the four qi and five flavors belong to warm,cold,flat,sweet,pungent and bitter,and most of them belong to the meridians of liver,spleen and lung.Conclusion the artificial neural network diagnosis model of key genes of scleroderma is constructed,which can be used in clinical diagnosis of scleroderma,and the potential targeted traditional Chinese medicine for the treatment of scleroderma is predicted,which provides a new perspective for exploring the pathogenesis of scleroderma.

Objective:To explore the effects of the intervention of ginger baixiao moxibustion combined with probiotics on immune function, liver and kidney function of colorectal cancer patients after surgery, so as to provide a theoretical basis for clinical intervention methods to promote postoperative rehabilitation of patients.Methods:This study was a randomized controlled trial, and 180 patients with colorectal cancer radical resection from the Cancer Hospital of Guangxi Medical University were randomly divided into 4 groups, namely control group, probiotic group, ginger baixiao moxibustion group, and combination group, with 45 cases in each group. The control group was given routine nursing before and after surgery. In the probiotic group, probiotics were used for 3 d in routine preoperative care and 4 d from the first day after surgery. The preoperative routine care of the ginger baixiao moxibustion group was supplemented by ginger baixiao moxibustion for 3 d, and the intervention was carried out on the first day after surgery for 4 d. The combined group was treated with probiotics before and after surgery, and the specific intervention methods were the same as those of the probiotics group and the ginger baixiao moxibustion group. The differences in postoperative immune function, liver and kidney function and and other indexes among the four groups were compared.Results:Forty-five cases were ultimately selected from each of the 4 groups. There were 31 males and 14 females, aged (56.67 ± 10.13) years old in the control group. There were 27 males and 18 females, aged (55.33 ± 13.02) years old in the probiotic group. There were 20 males and 25 females, aged (57.87 ± 12.43) years old in the ginger baixiao moxibustion group. There were 26 males and 19 females, aged (57.67 ± 11.63) years old in the combination group. The IgA at 5 d after the operation in the control group, the probiotic group, the ginger baixiao moxibustion group and the combined group were (1.46 ± 0.42), (1.71 ± 0.49), (1.72 ± 0.58), (1.97 ± 0.72) g/L, and the IgM were (0.96 ± 0.20), (1.13 ± 0.33), (1.11 ± 0.35), (1.18 ± 0.52) g/L, and the IgG were (8.45 ± 1.68), (9.57 ± 1.71), (9.41 ± 2.14), (10.40 ± 2.16) g/L, and the differences among the four groups were statistically significant ( F=6.20, 10.64, 7.69, all P<0.05). The CD3 + values at 5 d after the operation in the control group, the probiotic group, the ginger baixiao moxibustion group and the combined group were 0.616 ± 0.094, 0.671 ± 0.101, 0.653 ± 0.119, 0.723 ± 0.091, and CD4 + were 0.408 ± 0.060, 0.444 ± 0.063, 0.441 ± 0.103, 0.483 ± 0.069, and CD4 +/CD8 + were 2.173 ± 0.715, 2.367 ± 0.963, 2.204 ± 1.137, 2.803 ± 1.064, and the differences among the four groups were statistically significant ( F=8.58, 7.43, 3.93, all P<0.05). The alanine aminotransferases at 5 d after the operation in the control group, the probiotic group, the ginger baixiao moxibustion group and the combined group were (16.22 ± 11.56), (15.87 ± 10.69), (12.91 ± 7.45), (11.31 ± 8.31) U/L, and the aspartate aminotransferases were (26.13 ± 7.97), (25.84 ± 7.89), (25.67 ± 10.85), (21.84 ± 5.51) U/L, and the differences among the four groups were statistically significant ( F=2.71, 2.70, both P<0.05). Conclusions:The combination of ginger baixiao moxibustion and probiotics intervention can effectively improve the immune function of colorectal cancer patients after surgery, and improve the liver function and other indexes of patients to a certain extent, so as to benefit patients.

Objective To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.Methods The GSE95065 and GSE59785 datasets of scleroderma from GEO database were used for analyzing expressions of mitochondria-related genes,and the differential genes were identified by Random forest,LASSO regression and SVM algorithms.Based on these differential genes,an artificial neural network model was constructed,and its diagnostic accuracy was evaluated by 10-fold crossover verification and ROC curve analysis using the verification dataset GSE76807.The mRNA expressions of the key genes were verified by RT-qPCR in a mouse model of scleroderma.The CIBERSORT algorithm was used to estimate the bioinformatic association between scleroderma and the screened biomarkers.Results A total of 24 differential genes were obtained,including 11 up-regulated and 13 down-regulated genes.Seven most relevant mitochondria-related genes(POLB,GSR,KRAS,NT5DC2,NOX4,IGF1,and TGM2)were screened using 3 machine learning algorithms,and the artificial neural network diagnostic model was constructed.The model showed an area under the ROC curves of 0.984 for scleroderma diagnosis(0.740 for the verification dataset and 0.980 for cross-over validation).RT-qPCR detected significant up-regulation of POLB,GSR,KRAS,NOX4,IGF1 and TGM2 mRNAs and significant down-regulation of NT5DC2 in the mouse models of scleroderma.Immune cell infiltration analysis showed that the differential genes in scleroderma were associated with follicular helper T cells,immature B cells,resting dendritic cells,memory activated CD4+T cells,M0 macrophages,monocytes,resting memory CD4+T cells and mast cell activation.Conclusion The artificial neural network diagnostic model for scleroderma established in this study provides a new perspective for exploring the pathogenesis of scleroderma.

Research on inflammatory response,liver injury,and immune regulation has demonstrated that the intricate interactions among immune cells constitute a critical regulatory network.Alcohol consumption alters the liver microenvironment,triggering inflammation and immune responses.Elucidating the inhibitory,cooperative,and synergistic effects among lymphocytes and myeloid cells may reveal the core mechanisms of alcohol-associated liver disease(ALD)pathogenesis and identify promising therapeutic targets.This review seeks to elucidate the intricate and multifaceted interactions among immune cells,encompassing both direct cellular interactions and the secretion of various effector molecules.It is essential to underscore that these interactions have broader and more complex roles in ALD than the activities of individual immune cell types.These interactions play a crucial role in mutually regulating one another,thereby preserving the homeostasis of the inflammatory and immune response in the liver environment.Targeting these immune cell interactions is anticipated to offer a novel approach to the prevention and treatment of ALD.

Objective To investigate the environmental contamination related to first patient with carbapenem-re-sistant Acinetobacter baumannii(CRAB)infection and the infection status of relevant patients in a newly established intensive care unit(ICU)of a hospital in Tibetan area,and analyze the transmission risk.Methods From the ad-mission in ICU of a patients who was first detected CRAB on November 15,2021 to the 60th day of hospitalization,all patients who stayed in ICU for＞48 hours were performed active screening on CRAB.On the 30th day and 60th day of the admission to the ICU of the first CRAB-infected patient,environment specimens were taken respectively 2 hours after high-frequency diagnostic and therapeutic activities but before disinfection,and after disinfection but before medical activities.CRAB was cultured with chromogenic culture medium.Results Among the 13 patients who were actively screened,1 case was CRAB positive,he was transferred from the ICU of a tertiary hospital to the ICU of this hospital on November 19th.On the 40th day of admission to the ICU,he had fever,increased frequency for sputum suction,and CRAB was detected.The drug sensitivity spectrum was similar to that of the first case,and he also stayed in the adjacent bed of the first case.64 environmental specimens were taken,and 9 were positive for CRAB,with a positive rate of 14.06％,8 sampling points such as the washbasin,door handle and bed rail were positive for CRAB after high-frequency diagnostic and therapeutic activities.After routine disinfection,CRAB was detected from the sink of the washbasin.Conclusion For the prevention and control of CRAB in the basic-level ICU in ethnic areas,it is feasible to conduct risk assessment on admitted patients and adopt bundled prevention and con-trol measures for high-risk patients upon admission.Attention should be paid to the contaminated areas(such as washbasin,door handle,and bed rail)as well as the effectiveness of disinfection of sink of washbasin.