Objective To determine the prognostic biomarkers and new therapeutic targets of the lung adenocarcinoma (LUAD), based on which to establish a prediction model for the survival of LUAD patients. Methods An integrative analysis was conducted on gene expression and clinicopathologic data of LUAD, which were obtained from the UCSC database. Subsequently, various methods, including screening of differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA), were employed to analyze the data. Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to establish an assessment model. Based on this model, we constructed a nomogram to predict the probable survival of LUAD patients at different time points (1-year, 2-year, 3-year, 5-year, and 10-year). Finally, we evaluated the predictive ability of our model using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves. The validation group further verified the prognostic value of the model. Results The different-grade pathological subtypes' DEGs were mainly enriched in biological processes such as metabolism of xenobiotics by cytochrome P450, natural killer cell-mediated cytotoxicity, antigen processing and presentation, and regulation of enzyme activity, which were closely related to tumor development. Through Cox regression and LASSO regression, we constructed a reliable prediction model consisting of a five-gene panel (MELTF, MAGEA1, FGF19, DKK4, C14ORF105). The model demonstrated excellent specificity and sensitivity in ROC curves, with an area under the curve (AUC) of 0.675. The time-dependent ROC analysis revealed AUC values of 0.893, 0.713, and 0.632 for 1-year, 3-year, and 5-year survival, respectively. The advantage of the model was also verified in the validation group. Additionally, we developed a nomogram that accurately predicted survival, as demonstrated by calibration curves and C-index. Conclusion We have developed a prognostic prediction model for LUAD consisting of five genes. This novel approach offers clinical practitioners a personalized tool for making informed decisions regarding the prognosis of their patients.

Objective: To investigate the impact of disposable plastic food container usage on the executive function among primary school students, so as to provide the evidence for the formulation of relevant health policies. Methods: From November 2023 to May 2024, a convenience sampling method was employed to select 1 118 grade 1-3 students from three primary schools in a central district of Chongqing. A self developed questionnaire was used to collect demographic characteristics and data on disposable plastic food container usage. Executive function of primary school students was assessed using the Childhood Executive Functioning Inventory (CHEXI). Multivariate linear regression analysis was conducted to explore the associations between disposable plastic food container usage and heating with executive function among primary school students. Results: Median scores for working memory, inhibition and total executive function among primary school students were 32 (26, 39), 33 (28, 38), and 66 (54, 75), respectively. Multivariate linear regression analysis showed that among girls, higher frequencies of eating meals from plastic lunchboxes were associated with higher CHEXI working memory scores ( β =1.29), inhibition scores ( β =1.57), and total executive function scores ( β =2.85) ( P <0.05). Compared to girls who did not use plastic cups or drank bottled water, those who used plastic cups for drinking or drank bottled water had higher scores in working memory ( β =2.63), inhibition ( β =2.10), and total executive function ( β =4.73); compared to girls who did not eat canned food from metal cans, those who ate such food had higher scores in working memory ( β =3.62), inhibition ( β =1.89), and total executive function ( β =5.50) ( P <0.05).Among boys, higher frequencies of eating meals from plastic lunchboxes were associated with higher inhibition scores ( β =1.13) ( P <0.05). Compared to girls who ate with a plastic lunch box and did not heat it when they ate,girls who more frequent heating plastic lunchboxes with food inside had higher working memory scores ( β = 5.39), inhibition scores ( β =4.29), and total executive function scores ( β = 9.68) ( P <0.05). Conclusions The use of disposable plastic food containers may adversely affect executive function of primary school students, with a more pronounced effect observed in girls. Strengthened regulation of disposable plastic products and health education are urgently needed.

Salvia miltiorrhiza is a perennial herb of the genus Salvia(Lamiaceae). As one of the earliest medicinal plants to undergo molecular biology research, it has gradually become a model plant for molecular biology of medicinal plants. With the gradual analysis of the genome of S. miltiorrhiza and the biosynthetic pathways of its main active components tanshinone and salvianolic acids, the transcriptional regulation mediated by transcription factors and related regulatory proteins has gradually become a new research focus. Due to the lack of scientific and unified naming of transcription factors and different research indexes in different literature, this paper systematically sorted out the transcription factors in different literature with the genomes of DSS3 from selfing for three generations and bh2-7 from selfing for six generations as reference. In total, 73 transcription factors and related regulatory proteins belonging to 13 gene families were identified. The effects of overexpression or gene silencing experiments on tanshinone and salvianolic acids were also analyzed. This study unified the identified transcription factors, which laid a foundation for further constructing the regulatory networks of secondary metabolites and insect or stress resistance and improving the quality of medicinal materials by using global transcriptional regulation engineering.
Salvia miltiorrhiza/chemistry* ; Plant Proteins/metabolism* ; Gene Expression Regulation, Plant ; Transcription Factors/metabolism* ; Abietanes/metabolism*

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

OBJECTIVES: To investigate the clinical characteristics and prognosis of acute erythroleukemia (AEL) in children. METHODS: A retrospective analysis was conducted on the clinical data, treatment, and prognosis of 8 children with AEL treated at the First Affiliated Hospital of Zhengzhou University from January 2013 to December 2023. RESULTS: Among the 7 patients with complete bone marrow morphological analysis, 4 exhibited trilineage dysplasia, with a 100% incidence of erythroid dysplasia (7/7), a 71% incidence of myeloid dysplasia (5/7), and a 57% incidence of megakaryocytic dysplasia (4/7). Immunophenotyping revealed that myeloid antigens were primarily expressed as CD13, CD33, CD117, CD38, and CD123, with 4 cases expressing erythroid antigens CD71 and 2 cases expressing CD235a. Chromosomal analysis indicated that 2 cases presented with abnormal karyotypes, including +8 in one case and +4 accompanied by +6 in another; no complex karyotypes were observed. Genetic abnormalities were detected in 4 cases, with fusion genes including one case each of dup MLL positive and EVI1 positive, as well as mutations involving KRAS, NRAS, WT1, and UBTF. Seven patients received chemotherapy, with 6 achieving remission after one course of treatment; 2 underwent hematopoietic stem cell transplantation, and all had disease-free survival. Follow-up (median follow-up time of 6 months) showed that only 3 patients survived (2 cases after hematopoietic stem cell transplantation and 1 case during treatment). CONCLUSIONS Children with AEL have unique clinical and biological characteristics, exhibit poor treatment response, and have a poor prognosis; however, hematopoietic stem cell transplantation may improve overall survival rates.
Humans ; Male ; Female ; Prognosis ; Child, Preschool ; Retrospective Studies ; Child ; Leukemia, Erythroblastic, Acute/diagnosis* ; Infant ; Adolescent

OBJECTIVES: To investigate the clinical features and prognosis of children with non-Down-syndrome-related acute megakaryoblastic leukemia (non-DS-AMKL). METHODS: A retrospective analysis was conducted on the medical data of 17 children with non-DS-AMKL who were admitted to Children's Hospital of The First Affiliated Hospital of Zhengzhou University from January 2013 to December 2023, and their clinical features, treatment, and prognosis were summarized. RESULTS: Among the 17 children with non-DS-AMKL, there were 8 boys and 9 girls. Fourteen patients had an onset age of less than 36 months, with a median age of 21 months (range:13-145 months). Immunophenotyping results showed that 16 children were positive for CD61 and 13 were positive for CD41. The karyotype analysis was performed on 16 children, with normal karyotype in 6 children and abnormal karyotype in 9 children, among whom 5 had complex karyotype and 1 had no mitotic figure. Detected fusion genes included EVI1, NUP98-KDM5A, KDM5A-MIS18BP1, C22orf34-BRD1, WT1, and MLL-AF9. Genetic alterations included TET2, D7S486 deletion (suggesting 7q-), CSF1R deletion, and PIM1. All 17 children received chemotherapy, among whom 16 (94%) achieved complete remission after one course of induction therapy, and 1 child underwent hematopoietic stem cell transplantation (HSCT) and remained alive and disease-free. Of all children, 7 experienced recurrence, among whom 1 child received HSCT and died of graft-versus-host disease. At the last follow-up, six patients remained alive and disease-free. CONCLUSIONS Non-DS-AMKL primarily occurs in children between 1 and 3 years of age. The patients with this disorder have a high incidence rate of chromosomal abnormalities, with complex karyotypes in most patients. Some patients harbor fusion genes or gene mutations. Although the initial remission rate is high, the long-term survival rate remains low.
Humans ; Male ; Female ; Leukemia, Megakaryoblastic, Acute/etiology* ; Child, Preschool ; Infant ; Child ; Retrospective Studies ; Prognosis ; Down Syndrome/complications*

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

OBJECTIVE: To investigate the association of various polycyclic aromatic hydrocarbon (PAH) metabolites with diverse subtypes of cardiovascular disease (CVD) risk. METHODS: A novel predicting risk of cardiovascular disease EVENTs PREVENT equation was used to estimate the 10-year diverse subtypes of CVD risk, and their associations with PAH metabolites were analyzed using multiple logistic regression models, the weighted quantile sum (WQS) model, the quantile g-computation (qgcomp) model, and a stratified analysis of subgroups. RESULTS: For this study, six thousand seven hundred and forty-five participants were selected, and significant positive associations were observed between PAHs, naphthalene (NAP), and fluorene (FLU), and the risks of total CVD, atherosclerotic cardiovascular disease (ASCVD), and heart failure (HF). NAP and FLU were the primary contributors to the effects of PAH mixtures, and their associations with total CVD, ASCVD, and HF risk were significant in younger participants (30 ≤ age < 50 years); however, the associations of phenanthrene (PHEN) with ASCVD, HF, coronary heart disease (CHD), and stroke were dominant in aging participants (age ≥ 50 years). Notably, pyrene (PYR) was negatively associated with the risk of ASCVD, HF, CHD, and stroke. Similarly, negative associations of PYR with the four CVD subtypes were noticeable in aging participants. CONCLUSION Different PAHs metabolites had different impacts on each CVD subtype among different age groups. Notably, the protective effects of PYR on ASCVD, HF, CHD, and stroke were noticeable in aging individuals.
Humans ; Cardiovascular Diseases/chemically induced* ; Middle Aged ; Polycyclic Aromatic Hydrocarbons/metabolism* ; Male ; Female ; Adult ; Aged ; Risk Factors ; China/epidemiology*

Objective:To analyze the mutant spectrum of clonal hematopoiesis of indeterminate potential(CHIP)related mutations and clinical characteristics and to explore the correlation and the possible mechanism between CHIP-related mutations and cardio-cerebrovasculars events(CCEs)in patients with myeloproliferative neoplasms(MPNs).Methods:The clinical data and next-generation sequencing results of 73 MPN patients in Beijing Anzhen Hospital from August 2019 to July 2022 were retrospectively analyzed.Statistical analyses were conducted by multivariate logistic regression for the effects of CHIP-related mutations and inflammatory cytokines on CCEs for MPNs patients.Results:Fifty-five cases of MPN(75.3％)showed positive in CHIP-related genes.There was no significant difference in variant allele frequency of CHIP-related gene between essential thrombocythemia(ET)and polycythemia vera(PV).CHIP-related gene mutations were mainly single gene mutations,with mutation rate from high to low as JAK2V617F(63.0％,46/73),ASXL1(16.4％,12/73),TET2(11.0％,8/73),DNMT3A(9.6％,7/73),SRSF2(6.9％,5/73),SF3B1(4.1％,3/73),TP53(1.4％,1/73)and PPM1D(1.4％,1/73).The mutation rate of CHIP-related genes in MPN patients＞60 years old was significantly higher than that in the patients ≤ 60 years old[91.7％(33/36)vs 59.5％(22/37)].CCEs occurred in 27 MPNs patients(37.0％,MPNs/CCEs),and 5 had recurrent CCEs,all of which were arterial events.Age(62.8±12.8 years vs 53.9±15.8 years,P=0.015),IL-1β level(17.7±26.0 vs 4.3±8.6,P=0.012),IL-8 level(360.7±598.6 vs 108.3±317.0,P=0.045),the proportion of the patients with thrombosis history(29.6％vs 2.2％,P=0.020),and the detection rate of CHIP-related mutations(88.9％vs 67.4％,P=0.040)in the group with CCEs were higher than those in the group without CCEs.Multivariate Logistic regression analysis showed that age(OR=0.917,95％CI:0.843-0.999,P=0.047),thrombosis history(OR=34.148,95％CI·2.392-487.535,P=0.009),any CHIP-related mutations(OR=16.065,95％CI·1.217-212.024,P=0.035),and elevated levelofIL-1β(OR=0.929,95％CI:0.870-0.992,P=0.027)were independent risk factors for MPNs/CCEs.CHIP-related gene mutations were not associated with CCEs in MPN patients,but DNMT3A(OR=88.717,95％CI:2.690-292.482,P=0.012)and ASXL1(OR=7.941,95％CI:1.045-60.353,P=0.045)were independent risk factors for CCEs in PV.Conclusion:There is a higher mutation rate of CHIP-related genes in MPN patients,especially those over 60 years old.Older age,thrombosis history,CHIP-related mutations and IL-1βelevated levels are independent risk factors for CCEs in MPN.DNMT3A and ASXL1 mutations are independent risk factors for CCEs in PV patients.CHIP-related gene mutations and inflammatory cytokine IL-1 β elevated levels may be the novel risk factors for CCEs in MPN.