Objective To explore the biological characteristics associated with different subtypes and the response to immunotherapy by integrating multiomics analysis and artificial neural networks(ANN)to delineate the precise molecular subtypes of adrenocortical carcinoma(ACC)and establish a prognostic prediction model,in order to provide reference for the accurate prognosis assessment and individualized treatment of ACC.Methods The multiomics data of 44 Chinese ACC patients admitted to the Department of Urology,West China Hospital of Sichuan University during Jan.1,2012 and Dec.31,2022 were integrated,including genomic,transcriptomic and clinical features.Ten different clustering algorithms were employed for consensus clustering to identify robust molecular subtypes.The results were then incorporated into an ANN model to construct an ANN-driven prognostic index(ANPI)for patient stratification and survival prediction.Results Three distinct molecular subtypes(cancer subtypes,CS1-3)with significantly different prognoses were identified,among which CS1 exhibited the poorest survival outcomes.A set of 20 core genes was selected to form the basis of the ANPI model.ANPI effectively stratified patients into high-and low-risk groups:patients in the low-ANPI group had significantly better overall survival and exhibited"hot tumor"immune phenotypes,suggesting greater benefits from immunotherapy.In contrast,high-ANPI patients had worse prognoses and displayed"cold tumor"characteristics with weaker immunotherapy responses.Conclusion Our integrative multiomics analysis illustrated the molecular landscape of ACC in the Chinese population and uncovered the key immune-related features linked to clinical outcomes.The ANPI model demonstrated strong performance in prognostic prediction and immunotherapy response assessment,offering a valuable tool for precision oncology and clinical decision-making.

Objective:To analyze the epidemiological characteristics of drug resistance genes of carbapenemase-producing Escherichia coli (CPECO) in Henan Province Hospital of Traditional Chinese Medicine from 2021 to 2023, providing data support and theoretical basis for controlling nosocomial infections of CPECO.Methods:Using a cross-sectional study, 30 carbapenem-resistant Escherichia coli (CRECO) strains confirmed by VITEK-2 Compact identification and drug sensitivity test in the Clinical Microbiology Laboratory of Henan Province Hospital of Traditional Chinese Medicine from 2021 to 2023 were tested, using carbapenemase inhibitor enhancement test to conduct preliminary screening of carbapenemases, and colloidal gold immunochromatography and polymerase chain reaction (PCR) were used to determine the phenotypes and genotypes of common carbapenemases ( blaKPC, blaNDM, blaVIM, blaIMP, blaOXA) respectively, and the genotypes ( blaSHV, blaTEM, blaCTX) of common extended Spectrum beta-lactamases (ESBL) were confirmed using PCR. The PCR amplification products of carbapenemase and ESBL positive strains were Sanger-sequenced, and the sequencing products were compared on the Blast website to determine the exact carbapenemase and ESBL genotypes. Sequence typing (ST) was performed on CPECO using the Achtman multi-locus sequence typing scheme to determine the cloning relationship between different strains. Results:A total of 21 CPECO strains were screened. Drug sensitivity test results showed that CPECO strains showed widespread drug resistance, with the resistance rate to monocyclic (aztreonam) and trimethoprim/sulfamethoxazole being over 60%(16/21, 14/21), and the resistance rate to other antibacterial drugs being 100%. Only the sensitivity to aminoglycosides and fosfomycin remained relatively high, and no strains resistant to tigecycline and colistin were found. Colloidal gold immunochromatography detected 18 blaNDM types, 2 blaKPC types, and 1 blaIMP type. Sequencing of drug resistance gene PCR products classified 17 blaNDM-5 strains, 1 blaNDM-4 strain, 2 blaKPC-2 strain, and 1 blaIMP-4 strain, which were completely consistent with the results of screening test and colloidal gold immunochromatography. ESBL resistance gene testing showed that the detection rate of blaTEM was 42.9%(9/21), blaCTX-M was 33.3%(7/21), and blaSHV was 4.8%(1/21). The rate of blaNDM producing CPECO carrying both ESBL resistance genes was 27.8%(5/18). The MLST typing results revealed 11 sequence types (STs), including one ST155 clonal complex and nine singleton STs. Among these, there were seven strains of ST167, five strains of ST410, and one strain each of ST58, ST68, ST69, ST93, ST131, ST155, ST648, ST1114, and ST3268. Conclusion:The main resistance mechanism identified in this study for CPECO was the production of blaNDM-5 carbapenemase, with a high proportion of strains also carrying blaTEM-1D and/or blaCTX-M-15 ESBLs. MLST typing found that the epidemic strain of CPECO showed certain polymorphism, but there were clonal transmission of multiple clonal complexes between ST167 and ST410.

Objective:Using resting-state functional magnetic resonance imaging (rs-fMRI), we explored the changes in dynamic functional network connections (dFNC) in the brains of patients with first-episode schizophrenia (SZ) and evaluated the potential clinical value of dFNC changes in combination with a machine learning model.Methods:Clinical data of 50 patients with schizophrenia (schizophrenia group), 29 males and 21 females, aged 18-47 (28.3±7.2) years, who attended the psychiatric department of the Second Affiliated Hospital of Xinxiang Medical College from January 2022 to August 2023, were retrospectively included. In the same period, 50 healthy controls matched for age and education (healthy control group) were recruited, of which 24 were male and 26 were female, aged 18-48 (28.0±6.9) years. The rs-fMRI imaging data were acquired for each subject. The dFNC cluster analysis was performed based on independent component analysis, and the differences between groups with different state FNC matrices were statistically analyzed. The dataset samples were divided into a training set (35 SZ patients and 35 healthy controls) and a validation set (15 SZ patients and 15 healthy controls) in a 7∶3 ratio. A machine learning classification model was constructed based on the dFNC matri. The performance of the model for distinguishing between schizophrenia and healthy controls was assessed by five-fold cross-validation using accuracy (ACC), recall (REC), F1 score, and area under curve (AUC) metrics of the working characteristics of the subjects.Results:Five network functional connectivity states were obtained by dFNC cluster analysis. Patients with first SZ showed a wide range of high connectivity and low connectivity changes on the neural dynamic functional networks, as shown by increased dynamic connectivity within the visual network (VIS) in state 1 (weak connectivity); The dynamic connectivity between executive control network (ECN) and VIS, frontal parietal network (FPN) and VIS decreases at state 3 (strong connectivity); The dynamic connectivity between default mode network (DMN) and FPN, DMN and ventral attention network (VAN) decreases at state 4 (weak connectivity). The machine learning results show that the classification model constructed by the dFNC matrix combined with SVM in state 3 (strongly connected) in the validation set obtains the best classification results (ACC=0.938; REC=0.938; F1=0.937; AUC=0.984), and the overall average classification ACC of the five states reaches 0.751, and AUC reaches 0.784.Conclusion:Patients with first-episode SZ have some brain functional network connectivity abnormalities, and a machine learning model based on dFNC features has high classification performance in distinguishing first-episode SZ from HC.

Objective:To construct an internal quality evaluation system based on the structure-process-outcome(SPO)model,and to analyze its applied effect in the quality management for equipment in the ward of neurology of third-level grade-A hospital.Methods:The internal quality evaluation system for medical equipment based on SPO model realized comprehensive management for medical equipment in the ward of neurology of third-level grade-A hospital through structural design,platform management and outcome feedback.Thirty using medical equipment in the wards of the neurology of Shenzhen Longhua District Central Hospital from May,2022 to April,2024 were selected.The equipment that were used from May,2022 to April,2023 were managed by using conventional management method,and the equipment that were used from May 2023 to April 2024 were managed by using internal quality evaluation system(SPO model management method)based on SPO model.A self-made questionnaire was adopted to investigate and research the satisfaction degree of 35 equipment-related managers,and the operating quality of equipment,error rate of clinical operation and increased degree of equipment benefit of the two management methods were compared.Results:The execution rate of equipment,standard rate of disinfection,timely rate of failure treatment and pass rate of quality detection of adopting SPO model management method were respectively(94.15±4.63)%,(92.69±3.36)%,(93.65±4.36)%and(90.62±3.14)%,which were higher all than these of conventional management method,and the differences of them between two methods were statistically significant(t=14.218,14.582,11.813,14.859,P<0.05).The occurrences of misuse,operation error and human error were respectively one,one and two equipment in 30 equipment by using SPO model management method,and the incidence rates of them were respectively 3.333%,3.333%and 6.667%,which were lower all than those of conventional management method,and the differences of them between two methods were statistically significant(x2=11.882,13.416,12.272,P<0.05).The average scores of 35 managers for convenience,used effect,emergency use and automatic warning efficiency of adopting SPO model management method to use equipment were respectively(92.36±3.14)points,(93.21±4.36)points,(91.25±3.36)points and(94.23±4.36)points,all of which were higher than those of conventional management method,and the differences of them between two methods were statistically significant(t=12.849,11.894,11.417,11.401,P<0.05).The average values of the increased degrees of cost-benefit and social-benefit of equipment of using SPO model management method were respectively(4.36±0.96)%and(3.25±0.65)%,which were higher than these of conventional management method,while the average value of the increased degree of maintenance management expenditure of using SPO model management method was(1.56±0.69)%,which was lower than that of conventional management method,and the differences of them between two methods were statistically significant(t=11.754,14.438,16.320,P<0.05).Conclusion:The application of the internal quality evaluation system based on SPO model for medical equipment in the management for medical equipment in neurology wards of third-level grade-A hospital can improve the operation quality of equipment,and reduce the error rate of operating equipment,and enhance the satisfaction of relevant managers in using equipment.

Rice is the world's largest food crop, and its yield and quality are directly related to food security and human health. Grain size, as one of the important factors determining the rice yield, has been widely concerned by breeders and researchers for a long time. To decipher the regulatory mechanism of rice grain size, we obtained a multi-tiller, dwarf, and small-grain mutant htd1 by ethyl methanesulfonate (EMS) mutation from the Japonica rice cultivar 'Zhonghua 11' ('ZH11'). Genetic analysis indicated that the phenotype of htd1 was controlled by a single recessive gene. Using the mutation site map (Mutmap) method, we identified the candidate gene OsHTD1, which encoded a carotenoid cleavage dioxygenase involved in the biosynthesis of strigolactone (SL). The SL content in htd1 was significantly lower than that in 'ZH11'. Cytological analysis showed that the grain size of the mutant decreased due to the reductions in the length and width of glume cells. The function of htd1 was further verified by the CRISPR/cas9 gene editing technology. The plants with the gene knockout exhibited similar grain size to the mutant. In addition, gene expression analysis showed that the expression levels of multiple grain size-related genes in the mutant changed significantly, suggesting that HTD1 may interact with other genes regulating grain size. This study provides a new theoretical basis for research on the regulatory mechanism of rice grain size and potential genetic resources for breeding the rice cultivars with high yields.
Oryza/growth & development* ; Mutation ; Edible Grain/growth & development* ; Alleles ; Plant Proteins/genetics* ; Dioxygenases/genetics* ; Lactones/metabolism* ; Gene Expression Regulation, Plant ; Genes, Plant ; Gene Editing ; CRISPR-Cas Systems ; Phenotype

Rice (Oryza sativa L.) is an important food crop. The appearance of lesion mimics in rice leads to phytohormone disorders, which affects rice adaptation to environmental stresses and ultimately reduces the yield and quality. To explore whether the changes in the adaptability of rice lesion-mimic mutants to stressful environments are caused by the disorder of phytohormone metabolism in plants. In this study, we screened an ethyl methane sulfonate-treated population of the japonica cultivar 'Taipei 309' for a mutant with rust-like spots on leaves at the early tillering stage and brown-red spots at maturity and named it rsl1 (rust spotted leaf 1). Compared with the wild type, rsl1 showed decreases in plant height, panicle length, primary branch number, secondary branch number, filled grains per panicle, seed-setting rate, and 1 000-grain weight, and an increase in number of effective panicles. Genetic analysis indicated that rsl1 was controlled by a single recessive nuclear gene. RSL1 was localized between two molecular markers, B7-7 and B7-9, on rice chromosome 7 by map-based cloning. PCR sequencing of the annotated genes in this interval revealed a mutation of C1683A on the eighth exon of SPL5 (LOC_Os07g10390) in rsl1, which resulted in premature termination of protein translation. Exogenous phytohormone treatments showed that rsl1 was less sensitive to salicylic acid (SA), abscisic acid (ABA), and indo-3-acetic acid (IAA) and more sensitive to methyl jasmonate (MeJA) and gibberellin acid (GA) than the wild type. In addition, the survival rate of rsl1 was lower than that of the wild type under salt, alkali, drought, and high temperature stresses, and it was higher than that of the wild type under cold stress. Quantitative real-time polymerase chain reaction (qRT-PCR) results showed that RSL1 was involved in the regulation of ABA, SA, MeJA, IAA, and GA-related genes under abiotic stresses. The present study showed that the RSL1 mutation led to the appearance of lesion mimics and affected the growth, development, and stress resistance of rsl1 under abiotic stresses. The study of the functional mechanism of this gene can provide theoretical guidance for the research on rice stress resistance.
Oryza/microbiology* ; Stress, Physiological/genetics* ; Plant Diseases/genetics* ; Cloning, Molecular ; Chromosome Mapping ; Plant Growth Regulators/metabolism* ; Plant Proteins/genetics* ; Mutation ; Cyclopentanes ; Genes, Plant ; Plant Leaves/genetics* ; Oxylipins

Rice (Oryza sativa L.), as a thermophilic crop, is highly susceptible to cold stress during its growth process. Chilling injury at the plumule stage and seedling stage often affects the morphological development and leads to yield reduction of rice. The exploration and utilization of cold tolerance genes are among the most direct and effective approaches to address cold stress in rice. To identify quantitative trait loci (QTLs) associated with cold tolerance at plumule and seedling stages, in this study, we measured the seedling rates and survived seedling rates of the indica rice cultivar 'HZ', the japonica cultivar 'Nekken2', and their 120 recombinant inbred lines (RILs) under cold stress. A previously constructed high-density genetic linkage map was used for the mapping of the QTLs conferring cold tolerance at the plumule and seedling stages. A total of 4 QTLs for plumule-stage cold tolerance and 9 QTLs for seedling-stage cold tolerance were detected, with the maximum limit of detection reaching 5.20. Notably, a genetically overlapping QTL for both plumule and seedling stages was identified on chromosome 8, spanning a physical interval of 24 432 953-25 295 129 bp. Candidate genes within the detected QTL intervals were screened, and quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to analyze the gene expression during the plumule and seedling stages. The results revealed that LOC_Os03g06570, LOC_Os03g07100, LOC_Os06g08280, LOC_Os08g38440, LOC_Os08g39100, and LOC_Os08g39540 exhibited significantly differential expression between the parental lines. These genes were either significantly downregulated or upregulated under cold stress. Among them, the first three gene (LOC_Os03g06570, LOC_Os03g07100, and LOC_Os06g08280) were hypothesized to be key candidates regulating the cold tolerance of rice seedlings, while the latter three genes (LOC_Os08g38440, LOC_Os08g39100, and LOC_Os08g39540) were identified as comprehensive regulators of cold tolerance during both plumule and seedling stages. These findings lay a foundation for the fine mapping and cloning of cold tolerance genes at the plumule and seedling stages, providing valuable insights for breeding cold-tolerant rice varieties.
Quantitative Trait Loci/genetics* ; Oryza/growth & development* ; Seedlings/growth & development* ; Cold Temperature ; Chromosome Mapping ; Gene Expression Regulation, Plant

OBJECTIVE: To compare the registration accuracy of cone beam computed tomography (CBCT) images while registering to virtual craniodentofacial patients based on soft tissue and the dentition registration method. METHODS: Virtual dentofacial patients out of 13 selected participants who needed CBCT scanning were established by impression with a registered-block impression (RBI) based on digital dental images, three-dimensional (3D) facial images and maxillofacial CBCT images. CBCT images were processed in the Mimics software program, establishing the craniofacial virtual patients based on CBCT images (CCTs). Registration between virtual patients from RBI and CCT, using the soft tissue in lower half face (STE) and dentition (DTN) as the reference area, respectively, forming two kinds of virtual craniofacial patients based on digital dental images, 3D facial images and skeletal images of CBCT (hiding the soft tissue and dental casts from CBCT). Three-dimensional deviation analysis was performed in the upper half face and lower half face of facial images from CBCT between two kinds of virtual craniodentofacial patients and compared with 3D facial images from RBI and recorded as root mean square error (RMSE). Paired-t test was used to compare the deviations of RMSEs between the upper and lower half of the face and the upper half of the face of facial images from CCT, respectively, between the two kinds of virtual craniodentofacial patients based on STE and DTN methods. RESULTS: Paired-t tests showed that there was no statistically significant difference between the upper and lower half faces of facial images from CCT between STE and DTN (P>0.05), but the deviation of RMSEs of the upper half face of facial images from CCT in STE was smaller than those in DTN [(1.696±0.420) mm vs. (1.752±0.424) mm, P < 0.01]. CONCLUSION The registration accuracy of CBCT registered in virtual craniodentofacial patients using soft tissue as the reference area was higher.
Humans ; Cone-Beam Computed Tomography/methods* ; Imaging, Three-Dimensional/methods* ; Male ; Face/anatomy & histology* ; Female ; Adult ; Image Processing, Computer-Assisted/methods* ; Young Adult ; User-Computer Interface

Objective:To explore the impact of the fear of disease progression on the return-to-work readiness of patients after percutaneous coronary intervention (PCI) , and the chain mediating effect of psychological consistency and disease acceptance between the two factors.Methods:A convenience sampling method was used to select 198 PCI patients at the Affiliated Hospital of Jining Medical University from February 2023 to May 2024. The General Information Survey, Return-To-Work Readiness Scale, Fear of Progression Questionnaire-Short Form, Acceptance Illness Scale, and Sense of Coherence-13 were used to investigate the patients.Results:A total of 198 questionnaires were distributed, with 178 valid questionnaires returned, yielding an effective response rate of 89.90%. Among the patients' return-to-work readiness, 42 patients were in the pre-intention stage, 60 patients in the intention stage, 36 patients in the action preparation-self-assessment stage, and 40 patients in the action preparation-behavior stage. The fear of disease progression significantly influenced the patients' return-to-work readiness. Psychological consistency and disease acceptance played significant chain mediation roles between the fear of disease progression and return-to-work readiness, with a total mediation effect value of -0.072, accounting for 41.38% of the total effect.Conclusions:Return-to-work readiness in PCI patients needs improvement. Psychological consistency and disease acceptance play a chain mediation role between the fear of disease progression and return-to-work readiness. Healthcare providers should develop personalized care strategies based on patients' specific conditions, improve their psychological state, and enhance their readiness to return to work.

Objective:To investigate the current status of medication discrepancy in patients after emergency percutaneous coronary intervention (PCI) and its influencing factors.Methods:Convenience sampling was used to select 260 patients with acute myocardial infarction who underwent emergency PCI in the Affiliated Hospital of Jining Medical University from July 2023 to February 2024 for the study. Patients were surveyed using the General Information Questionnaire, Medication Discrepancy Tools, Brief Illness Perception Questionnaire, Drug Literacy Questionnaire for Discharged Patients, and Sense of Coherence-13 Scale. Binomial Logistic regression was used to analyze the influencing factors of medication discrepancy.Results:A total of 260 questionnaires were distributed, 247 valid questionnaires were recovered, and the effective recovery rate was 95.00%. There were 166 cases without medication discrepancy and 81 cases with medication discrepancy. Binomial Logistic regression showed that age, occupational status, disease perception, medication literacy, and sense of coherence were the influencing factors of medication discrepancy in patients after emergency PCI ( P<0.05) . Conclusions:There is an urgent need to improve the medication discrepancy in patients after emergency PCI. Healthcare professionals can provide target interventions to patients to reduce the incidence of medication discrepancy by looking at the influencing factors and taking into account the individualized needs of the patients.