Prognostic significance of ß2-microglobulin decline index in multiple myeloma.

Purpose: To assess the prognostic significance of ß2-microglobulin decline index (ß2M DI) in multiple myeloma (MM). Methods: 150 MM patients diagnosed with MM were enrolled in this study. Cox proportional hazards model was used to analyze the uni- and multivariate prognosis in training cohort (n=105). A new combined prognostic model containing ß2M DI was built up based on the data in training cohort. The validation group was used to verify the model. Results: ß2M DI showed significant correlation with prognosis in both uni- and multivariate analyses and had a good correlation with complete response (CR) rate and deep remission rate. The ROC and calibration curves in validation cohort (n=45) indicated a good predictive performance of the new model. Based on the median risk score of the training group, we classified patients into high- and low- risk groups. In both training and validation groups, patients in the low-risk group had longer overall survival (OS) time than that in the high-risk group (p<0.05). Conclusion: ß2M DI is a good predictive index for predicting treatment response and survival time in MM patients. The prognostic model added with ß2M DI showed a better correlation with OS.

Application of DNA barcodes in the genetic diversity of hard ticks (Acari: Ixodidae) in Kazakhstan.

Forty-five tick species have been recorded in Kazakhstan. However, their genetic diversity and evolutionary relationships, particularly when compared to ticks in neighbouring countries, remain unclear. In the present study, 148 mitochondrial cytochrome c oxidase subunit I (COI) sequence data from our laboratory and NCBI (National Center for Biotechnology Information; https://www.ncbi.nlm.nih.gov/ ) data were used to address this knowledge gap. Phylogenetic analyses showed that i) Hyalomma anatolicum anatolicum (Koch, 1844) ticks from Jambyl Oblast (southeastern Kazakhstan) and Gansu Province (northwestern China) constituted a newly deviated clade; and ii) Dermacentor reticulatus (Fabricius, 1974) ticks from South Kazakhstan Oblast were closer to those in Romania and Turkey. The network diagram of haplotypes showed that i) the H-1 and H-2 haplotypes of Dermacentor marginatus (Sulzer, 1776) ticks from Zhetisu and Almaty were all newly evolved; and ii) the H-3 haplotypes of Haemaphysalis erinacei (Pavesi, 1884) from Almaty Oblast and Xinjiang Uygur Autonomous Region (northwestern China) were evolved from the H-1 haplotype from Italy. In the future, more COI data from different tick species, especially from Kazakhstan and neighbouring countries, should be employed in the field of tick DNA barcoding.

Knowledge, Attitudes, and Practices Among Middle-Aged and Elderly Population Towards Ultrasound Screening for Strokes.

Purpose: This study aimed to assess the knowledge, attitudes and practices (KAP) among middle-aged and elderly population towards ultrasound screening for strokes. Patients and Methods: This web-based cross-sectional study was conducted between March, 2023, and May, 2023 at Shanghai Eighth People's Hospital. A self-designed questionnaire was developed to collect demographic information of middle-aged and elderly population and assess their knowledge, attitudes and practices toward ultrasound screening for strokes. Results: A total of 552 participants enrolled in this study, among them 151 (27.36%) aged above 60 years old, 306 (55.43%) resided in rural area, 239 (43.30%) possessed educational attainment at the level of junior college, college or above. The mean knowledge, attitudes and practice scores were 5.53 ± 2.56, 40.22 ± 5.60 and 38.30 ± 7.38, respectively. Pearson's analysis was performed to assess the relationship between knowledge, attitudes, and practices. It was shown that knowledge and attitudes were positively correlated (r = 0.544, P < 0.001), and knowledge and practices were also positively correlated (r = 0.404, P < 0.001). Additionally, there was a positive correlation between attitude and practice scores (r = 0.566, P < 0.001). Conclusion: The results of this study demonstrate that the middle-aged and elderly population exhibited insufficient knowledge, positive attitudes, and moderate practices towards ultrasound screening for strokes. There is a need to improve the understanding of stroke risk factors, symptoms, and emergency measures among this population.

Heart Murmur Classification Using a Capsule Neural Network.

The healthcare industry has made significant progress in the diagnosis of heart conditions due to the use of intelligent detection systems such as electrocardiograms, cardiac ultrasounds, and abnormal sound diagnostics that use artificial intelligence (AI) technology, such as convolutional neural networks (CNNs). Over the past few decades, methods for automated segmentation and classification of heart sounds have been widely studied. In many cases, both experimental and clinical data require electrocardiography (ECG)-labeled phonocardiograms (PCGs) or several feature extraction techniques from the mel-scale frequency cepstral coefficient (MFCC) spectrum of heart sounds to achieve better identification results with AI methods. Without good feature extraction techniques, the CNN may face challenges in classifying the MFCC spectrum of heart sounds. To overcome these limitations, we propose a capsule neural network (CapsNet), which can utilize iterative dynamic routing methods to obtain good combinations for layers in the translational equivariance of MFCC spectrum features, thereby improving the prediction accuracy of heart murmur classification. The 2016 PhysioNet heart sound database was used for training and validating the prediction performance of CapsNet and other CNNs. Then, we collected our own dataset of clinical auscultation scenarios for fine-tuning hyperparameters and testing results. CapsNet demonstrated its feasibility by achieving validation accuracies of 90.29% and 91.67% on the test dataset.

Polymorphisms in the promoter regions of RHD and RHCE genes in the Chinese Han population.

BACKGROUND AND OBJECTIVES: The Rh blood group system is the most polymorphic human blood group system. Previous studies have investigated variants in the RHD and RHCE promoter. The relevance of these variants to the Chinese Han population is further clarified in this study. MATERIALS AND METHODS: In total, 317 donors (223 Rh D-positive [D+], including 20 Del and 94 Rh D-negative [D-]) were randomly selected. The promoter regions and exon 1 of RHD and RHCE were amplified through polymerase chain reaction (PCR) whose products were directly sequenced using forward and reverse primers. RESULTS: Expected PCR products of the RHD promoter and exon 1 were amplified in 223 D+ individuals, including 20 Del individuals, and were absent in 81 of 94 D- individuals. Expected PCR products of RHCE were observed in all donors. Two single nucleotide variants (SNVs) were observed in the RHD promoter region. Moreover, 11 SNVs were observed in the promoter and exon 1 of RHCE. rs4649082, rs2375313, rs2281179, rs2072933, rs2072932, rs2072931 and rs586178 with strong linkage disequilibria were significantly different between the D+ and D- groups. [A;C] was the most common haplotype in the RHD promoter (NC_000001.11:g.[-1033A>G;-831C>T]). [G;T;T;A;T;A;C;G;A;C;G] was the most predominant haplotype in both total and D- groups. In D+ individuals, [A;C;T;G;C;G;C;G;C;C;C] was the most frequent haplotype in the RHCE promoter (NC_000001.11:g.[-1080A>G;-958C>T;-390T>C;-378G>A;-369C>T;-296G>A;-144C>G;-132G>A;-122C>A;28C>T;48C>G]). CONCLUSION: We speculate that the SNVs/haplotypes found in this article cannot significantly affect gene expression. The present study findings should help elucidate the molecular basis of the polymorphic expression of RHD and RHCE promoter regions.

Multisequence MRI-based radiomics nomogram for early prediction of osimertinib resistance in patients with non-small cell lung cancer brain metastases.

Background: Osimertinib resistance is a major problem in the course of targeted therapy for non-small cell lung cancer (NSCLC) patients. To develop and validate a multisequence MRI-based radiomics nomogram for early prediction of osimertinib resistance in NSCLC with brain metastases (BM). Methods: Pretreatment brain MRI of 251 NSCLC patients proven with BM were retrospectively enrolled from two centers (training cohort: 196 patients; testing cohort: 55 patients). According to the gene test result of osimertinib resistance, patients were labeled as resistance and non-resistance groups (training cohort: 65 versus 131 patients; testing cohort: 25 versus 30 patients). Radiomics features were extracted from T2WI, T2 fluid-attenuated inversion recovery (T2-FLAIR), diffusion weighted imaging (DWI) and contrast-enhanced T1-weighted imaging (T1-CE) sequences separately and radiomics score (rad-score) were built from the four sequences. Then a multisequence MRI-based nomogram was developed and the predictive ability was evaluated by ROC curves and calibration curves. Results: The rad-scores of the four sequences has significant differences between resistance and non-resistance groups in both training and testing cohorts. The nomogram achieved the highest predictive ability with area under the curve (AUC) of 0.989 (95 % confidence interval, 0.976-1.000) and 0.923 (95 % confidence interval, 0.851-0.995) in the training and testing cohort respectively. The calibration curves showed excellent concordance between the predicted and actual probability of osimertinib resistance using the radiomics nomogram. Conclusions: The multisequence MRI-based radiomics nomogram can be used as a noninvasive auxiliary tool to identify candidates who were resistant to osimertinib, which could guide clinical therapy for NSCLC patients with BM.

Extracellular Vesicles: Techniques and Biomedical Applications Related to Single Vesicle Analysis.

Extracellular vesicles (EVs) are extensively dispersed lipid bilayer membrane vesicles involved in the delivery and transportation of molecular payloads to certain cell types to facilitate intercellular interactions. Their significant roles in physiological and pathological processes make EVs outstanding biomarkers for disease diagnosis and treatment monitoring as well as ideal candidates for drug delivery. Nevertheless, differences in the biogenesis processes among EV subpopulations have led to a diversity of biophysical characteristics and molecular cargos. Additionally, the prevalent heterogeneity of EVs has been found to substantially hamper the sensitivity and accuracy of disease diagnosis and therapeutic monitoring, thus impeding the advancement of clinical applications. In recent years, the evolution of single EV (SEV) analysis has enabled an in-depth comprehension of the physical properties, molecular composition, and biological roles of EVs at the individual vesicle level. This review examines the sample acquisition tactics prior to SEV analysis, i.e., EV isolation techniques, and outlines the current state-of-the-art label-free and label-based technologies for SEV identification. Furthermore, the challenges and prospects of biomedical applications based on SEV analysis are systematically discussed.

Comprehensive analysis of ferroptosis-related genes in immune infiltration and prognosis in multiple myeloma.

Background: One particular type of cellular death that is known as ferroptosis is caused by the excessive lipid peroxidation. It is a regulated form of cell death that can affect the response of the tumor cells. Currently, it is not known if the presence of this condition can affect the prognosis of patients with multiple myeloma (MM). Methods: In this study, we studied the expression differences and prognostic value of ferroptosis-related genes (FRGs) in MM, and established a ferroptosis risk scoring model. In order to improve the prediction accuracy and clinical applicability, a nomogram was also established. Through gene enrichment analysis, pathways closely related to high-risk groups were identified. We then explored the differences in risk stratification in drug sensitivity and immune patterns, and evaluated their value in prognostic prediction and treatment response. Lastly, we gathered MM cell lines and samples from patients to confirm the expression of marker FRGs using quantitative real-time PCR (qRT-PCR). Results: The ability to predict the survival of MM patients is a challenging issue. Through the use of a risk model derived from ferroptosis, we were able to develop a more accurate prediction of the disease's prognosis. They were then validated by a statistical analysis, which showed that the model is an independent factor in the prognosis of MM. Patients of high ferroptosis risk scores had a much worse chance of survival than those in the low-risk groups. The calibration and power of the nomogram were also strong. We noted that the link between the ferroptosis risk score and the clinical treatment was suggested by the FRG's significant correlation with the immune checkpoint genes and the medication sensitivity. We validated the predictive model using qRT-PCR. Conclusion: We demonstrated the association between FRGs and MM, and developed a new risk model for prognosis in MM patients. Our study sheds light on the potential clinical relevance of ferroptosis in MM and highlights its potential as a therapeutic target for patients with this disease.

Sex differences in depression, anxiety and health-promoting lifestyles among community residents: A network approach.

BACKGROUND: Researchers have studied sex differences in typical depressive and anxiety symptoms and their cooccurrence. The World Health Organization (WHO) proposed a mental health promotion objective that suggests considering protective health-promoting factors when developing strategies for preventing mental disorders between sexes. From a network perspective, psychopathology is viewed as a result of interacting symptoms and influential factors. This study adopted network approach to investigate sex differences in health-promoting lifestyles (HPL) and the cooccurrence symptoms of communities in Shanghai. The aim is to provide health-promoting suggestions on better enhancing the life quality for community members. METHODS: Depression, anxiety symptoms, and HPL were assessed with PHQ-9, GAD-7 and HPLP-II scales in 2420 adults (1411 females). Networks were constructed by Gaussian Graphical Models and the networks of two sexes using the Network Comparison Test. RESULTS: Females scored significantly higher on PHQ-9 (p < 0.001) and GAD-7 (p < 0.001), and no differences were found between the two sexes in HPL scores. Restlessness and low energy yielded the highest strength centrality in the female network, while suicide ideation and restlessness were central in male network. Regarding protective HPL, physical activity and stress management were identified as the central mental health-promoting behaviours in female and male network, respectively. However, stress management was positively related to suicide ideation in the male network. CONCLUSION: Communities should be aware of suicide ideation in males because of its high relationships with other symptoms and also provide stress management courses, especially for males. As for women, chronic energy deficiency deserves more attention for its high probability of cooccurrence with other symptoms in the network. Also, advocating physical activities may be particularly beneficial for the overall mental health among women. Future study should collect time-series data and analyze intraindividual networks to specify personalized health promoting strategies for each individual.

Dynamic dual-functional optical wave plate based on phase-change meta-molecules.

Optical metasurfaces have shown great potential for revolutionizing wave plates by enabling compact footprints and diversified functionalities. However, most metasurface wave plates (meta-WPs) are typically passive, featuring defined responses after fabrication, whereas dynamic meta-WPs have so far often been limited to ON and OFF states. Here, we design a dynamic dual-functional meta-WP based on judiciously designed low-loss Sb2Se3 meta-molecules at the telecom wavelength of 1.55 µm which enables reconfigurable linear-to-circular and linear-to-linear polarization conversion for orthogonal linear polarizations when Sb2Se3 transits between amorphous and crystalline states. In addition, a comprehensive electro-thermal simulation is carried out to verify the phase change process for realistic implementation. The designed dynamic dual-functional wave plate may open new avenues for developing integrated adaptive photonics with dynamic and multiplexed functionalities.

A novel glycolysis-related gene signature for predicting the prognosis of multiple myeloma.

Background: Metabolic reprogramming is an important hallmark of cancer. Glycolysis provides the conditions on which multiple myeloma (MM) thrives. Due to MM's great heterogeneity and incurability, risk assessment and treatment choices are still difficult. Method: We constructed a glycolysis-related prognostic model by Least absolute shrinkage and selection operator (LASSO) Cox regression analysis. It was validated in two independent external cohorts, cell lines, and our clinical specimens. The model was also explored for its biological properties, immune microenvironment, and therapeutic response including immunotherapy. Finally, multiple metrics were combined to construct a nomogram to assist in personalized prediction of survival outcomes. Results: A wide range of variants and heterogeneous expression profiles of glycolysis-related genes were observed in MM. The prognostic model behaved well in differentiating between populations with various prognoses and proved to be an independent prognostic factor. This prognostic signature closely coordinated with multiple malignant features such as high-risk clinical features, immune dysfunction, stem cell-like features, cancer-related pathways, which was associated with the survival outcomes of MM. In terms of treatment, the high-risk group showed resistance to conventional drugs such as bortezomib, doxorubicin and immunotherapy. The joint scores generated by the nomogram showed higher clinical benefit than other clinical indicators. The in vitro experiments with cell lines and clinical subjects further provided convincing evidence for our study. Conclusion: We developed and validated the utility of the MM glycolysis-related prognostic model, which provides a new direction for prognosis assessment, treatment options for MM patients.

Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma.

Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown. Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR). Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p < 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro. Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients.

Efficacy of dynamic interpersonal therapy for major depressive disorder in China: results of a multicentered, three-arm, randomized, controlled trial.

BACKGROUND: Dynamic interpersonal therapy (DIT) is a brief, structured psychodynamic psychotherapy with demonstrated efficacy in treating major depressive disorder (MDD). The aim of the study was to determine whether DIT is an acceptable and efficacious treatment for MDD patients in China. METHOD: Patients were randomized to 16-week treatments with either DIT plus antidepressant medication (DIT + ADM; n = 66), general supportive therapy plus antidepressant medication (GST + ADM; n = 75) or antidepressant medication alone (ADM; n = 70). The Hamilton Depression Rating Scale (HAMD) administered by blind raters was the primary efficacy measure. Assessments were completed during the acute 16-week treatment and up to 12-month posttreatment. RESULTS: The group × time interaction was significant for the primary outcome HAMD (F = 2.900, df1 = 10, df2 = 774.72, p = 0.001) in the acute treatment phase. Pairwise comparisons showed a benefit of DIT + ADM over ADM at weeks 12 [least-squares (LS) mean difference = -3.161, p = 0.007] and 16 (LS mean difference = -3.237, p = 0.004). Because of the unexpected high attrition during the posttreatment follow-up phase, analyses of follow-up data were considered exploratory. Differences between DIT + ADM and ADM remained significant at the 1-, 6-, and 12-month follow-up (ps range from 0.001 to 0.027). DIT + ADM had no advantage over GST + ADM during the acute treatment phase. However, at the 12-month follow-up, patients who received DIT remained less depressed. CONCLUSIONS: Acute treatment with DIT or GST in combination with ADM was similarly efficacious in reducing depressive symptoms and yielded a better outcome than ADM alone. DIT may provide MDD patients with long-term benefits in symptom improvement but results must be viewed with caution.

Structures of the human Wilson disease copper transporter ATP7B.

The P-type ATPase ATP7B exports cytosolic copper and plays an essential role in the regulation of cellular copper homeostasis. Mutants of ATP7B cause Wilson disease (WD), an autosomal recessive disorder of copper metabolism. Here, we present cryoelectron microscopy (cryo-EM) structures of human ATP7B in the E1 state in the apo, the putative copper-bound, and the putative cisplatin-bound forms. In ATP7B, the N-terminal sixth metal-binding domain (MBD6) binds at the cytosolic copper entry site of the transmembrane domain (TMD), facilitating the delivery of copper from the MBD6 to the TMD. The sulfur-containing residues in the TMD of ATP7B mark the copper transport pathway. By comparing structures of the E1 state human ATP7B and E2-Pi state frog ATP7B, we propose the ATP-driving copper transport model of ATP7B. These structures not only advance our understanding of the mechanisms of ATP7B-mediated copper export but can also guide the development of therapeutics for the treatment of WD.

Electrophysiological evidence for the characteristics of implicit self-schema and other-schema in patients with major depressive disorder: An event-related potential study.

Background: The significance of implicit self-schema and other-schema in major depressive disorder (MDD) is highlighted by both cognitive theory and attachment theory. The purpose of the current study was to investigate the behavioral and event-related potential (ERP) characteristics of implicit schemas in MDD patients. Methods: The current study recruited 40 patients with MDD and 33 healthy controls (HCs). The participants were screened for mental disorders using the Mini-International Neuropsychiatric Interview. Hamilton Depression Rating Scale-17 and Hamilton Anxiety Rating Scale-14 were employed to assess the clinical symptoms. Extrinsic Affective Simon Task (EAST) was conducted to measure the characteristics of implicit schemas. Meanwhile, reaction time and electroencephalogram data were recorded. Results: Behavioral indexes showed that HCs responded faster to positive self and positive others than negative self (t = -3.304, p = 0.002, Cohen's d = 0.575) and negative others (t = -3.155, p = 0.003, Cohen's d = 0.549), respectively. However, MDD did not show this pattern (p > 0.05). The difference in other-EAST effect between HCs and MDD was significant (t = 2.937, p = 0.004, Cohen's d = 0.691). The ERP indicators of self-schema showed that under the condition of positive self, the mean amplitude of LPP in MDD was significantly smaller than that in HCs (t = -2.180, p = 0.034, Cohen's d = 0.902). The ERP indexes of other-schema showed that HCs had a larger absolute value of N200 peak amplitude for negative others (t = 2.950, p = 0.005, Cohen's d = 0.584) and a larger P300 peak amplitude for positive others (t = 2.185, p = 0.033, Cohen's d = 0.433). The above patterns were not shown in MDD (p > 0.05). The comparison between groups found that under the condition of negative others, the absolute value of N200 peak amplitude in HCs was larger than that in MDD (t = 2.833, p = 0.006, Cohen's d = 1.404); under the condition of positive others, the P300 peak amplitude (t = -2.906, p = 0.005, Cohen's d = 1.602) and LPP amplitude (t = -2.367, p = 0.022, Cohen's d = 1.100) in MDD were smaller than that in HCs. Conclusion: Patients with MDD lack positive self-schema and positive other-schema. Implicit other-schema might be related to abnormalities in both the early automatic processing stage and the late elaborate processing stage, while the implicit self-schema might be related only to the abnormality in the late elaborate processing stage.

Association of Chinese Visceral Adiposity Index and Carotid Atherosclerosis in Steelworkers: A Cross-Sectional Study.

The Chinese Visceral Adiposity Index (CVAI) is an indicator of visceral adiposity dysfunction used to evaluate the metabolic health of the Chinese population. Steelworkers are more likely to be obese due to their exposure to special occupational factors, and have a higher prevalence of carotid atherosclerosis (CAS). This study aimed to analyze the special relationship between CVAI and CAS among steelworkers. A total of 4075 subjects from a northern steel company were involved in the cross-sectional study. Four logistic regression models were developed to analyze the correlation between CVAI and CAS. In addition, the restricted cubic spline was applied to fit the dose-response association between CVAI and CAS risk. In the study, the prevalence of CAS was approximately 25.94%. After adjustment for potential confounders, we observed a positive correlation between CVAI and CAS risk. Compared to the first CVAI quartile, the effect value odds ratio (OR) and 95% CI in the second, third, and fourth CVAI quartile were 1.523 (1.159-2.000), 2.708 (2.076-3.533), and 4.101 (3.131-5.372), respectively. Additionally, this positive correlation was stable in all subgroups except for female. Furthermore, we also found a non-linear relationship between CVAI and CAS risk (p nonlinear < 0.05). Notably, CVAI could increase the risk of CAS when higher than 106. In conclusion, our study showed that CVAI might be a reliable indicator to identify high-risk populations of CAS among steelworkers.

A case control study on the relationship between occupational stress and genetic polymorphism and dyslipidemia in coal miners.

Dyslipidemia is one of the known risk factors for cardiovascular disease, and its prevalence is increasing worldwide. At present, the study of dyslipidemia has gradually shifted from simple environmental or genetic factors to environment-gene interactions. In order to further explore the etiology and mechanism of dyslipidemia, we used occupational stress(OS) and LYPLAL1, APOC3 and SOD2 gene as research variables to explore their association with dyslipidemia.Here we used a case-control study to include Han workers from a coal mining enterprise in China to determine the association between study variables and dyslipidemia. Monofactor analysis showed that smoking, drinking, physical activity level, DASH diet score, sleep quality, BMI, hypertension, hyperuricemia, shift work, OS were significantly different between the two groups (P < 0.05). In the APOC3 rs2854116 dominant model, patients with CT/CC genotype had a higher risk of dyslipidemia than those with TT genotype. In SOD2 rs4880 recessive model, patients with GG genotype had a lower risk of dyslipidemia than those with AA/AG genotype, and the difference was statistically significant. We found that rs12137855 and OS, rs2854116 and OS, rs4880 and OS had joint effects, but no interaction based on the multiplication and addition model was found (Pinteraction > 0.05). GMDR model showed that the rs12137855-rs2854116-rs4880-OS four-factor model had the highest cross-validation consistency and training-validation accuracy (P < 0.05), suggesting that there was a high-order interaction between them associated with dyslipidemia. We found that dyslipidemia in coal miners was related to OS and genetic factors. Through this study, we revealed the dual regulation of environmental factors and genetic factors on dyslipidemia. At the same time, this study provides clues for understanding the etiology and mechanism of dyslipidemia.

Risk Prediction for the Development of Hyperuricemia: Model Development Using an Occupational Health Examination Dataset.

OBJECTIVE: Hyperuricemia has become the second most common metabolic disease in China after diabetes, and the disease burden is not optimistic. METHODS: We used the method of retrospective cohort studies, a baseline survey completed from January to September 2017, and a follow-up survey completed from March to September 2019. A group of 2992 steelworkers was used as the study population. Three models of Logistic regression, CNN, and XG Boost were established to predict HUA incidence in steelworkers, respectively. The predictive effects of the three models were evaluated in terms of discrimination, calibration, and clinical applicability. RESULTS: The training set results show that the accuracy of the Logistic regression, CNN, and XG Boost models was 84.4, 86.8, and 86.6, sensitivity was 68.4, 72.3, and 81.5, specificity was 82.0, 85.7, and 86.8, the area under the ROC curve was 0.734, 0.724, and 0.806, and Brier score was 0.121, 0.194, and 0.095, respectively. The XG Boost model effect evaluation index was better than the other two models, and similar results were obtained in the validation set. In terms of clinical applicability, the XG Boost model had higher clinical applicability than the Logistic regression and CNN models. CONCLUSION: The prediction effect of the XG Boost model was better than the CNN and Logistic regression models and was suitable for the prediction of HUA onset risk in steelworkers.

Development and Internal Validation of Risk Assessment Models for Chronic Obstructive Pulmonary Disease in Coal Workers.

Coal workers are more likely to develop chronic obstructive pulmonary disease due to exposure to occupational hazards such as dust. In this study, a risk scoring system is constructed according to the optimal model to provide feasible suggestions for the prevention of chronic obstructive pulmonary disease in coal workers. Using 3955 coal workers who participated in occupational health check-ups at Gequan mine and Dongpang mine of Hebei Jizhong Energy from July 2018 to August 2018 as the study subjects, random forest, logistic regression, and convolutional neural network models are established, and model performance is evaluated to select the optimal model, and finally a risk scoring system is constructed according to the optimal model to achieve model visualization. The training set results show that the logistic, random forest, and CNN models have sensitivities of 78.55%, 86.89%, and 77.18%; specificities of 85.23%, 92.32%, and 87.61%; accuracies of 81.21%, 85.40%, and 83.02%; Brier scores of 0.14, 0.10, and 0.14; and AUCs of 0.76, 0.88, and 0.78, respectively, and similar results are obtained for the test set and validation set, with the random forest model outperforming the other two models. The risk scoring system constructed according to the importance ranking of random forest predictor variables has an AUC of 0.842; the evaluation results of the risk scoring system shows that its accuracy rate is 83.7% and the AUC is 0.827, and the established risk scoring system has good discriminatory ability. The random forest model outperforms the CNN and logistic regression models. The chronic obstructive pulmonary disease risk scoring system constructed based on the random forest model has good discriminatory power.