Objective:To assess the status of undernutrition and appropriate catch-up growth in extremely preterm infants within 24 months of corrected age (CA).Methods:A retrospective cohort study was conducted. A total of 422 extremely preterm infants born at Shenzhen Maternity and Child Healthcare Hospital, Women and Children's Medical Center, Southern Medical University from January 2017 to December 2022 and followed up until 24 months of CA were enrolled. The extremely preterm infants were grouped by gestational age at birth (<25, 25-26, 27 weeks), birth weight (<500, 500-749, 750-999,≥1 000 g), weight for gestational age (large for gestational age (LGA), appropriate for gestational age (AGA), small for gestational age (SGA)) and sex. Weight data within 24 months of CA were collected every 3 months. Nutritional insufficiency, growth rate, and achievement of adequate catch-up growth were analyzed during the period from 0 to 24 months of CA. Z-score method was used to analyze data. Fenton 2013 preterm growth charts (Fenton 2013) were used before 40 weeks of corrected gestational age, and World Health Organization child growth standards (2009) fitted Z-scores were applied from 40 weeks of CA. Changes in weight Z-scores of extremely preterm infants from 0 to 24 months of CA were observed and compared, the occurrence of moderate to severe malnutrition and growth retardation was determined, nutritional insufficiency was assessed, and growth rate as well as the achievement of appropriate catch-up growth were analyzed. The Lambda-mu-sigma method combined with the Z-score fitting model was used to fit and analyze the distribution characteristics of weight percentiles in extremely preterm infants. The Chi-square test was used to compare differences among groups.Results:A total of 422 extremely preterm infants were included, with a gestational age at birth of 26.3(25.4, 27.2) weeks and a birth weight of (880±177) g. Among them, 238 were males and 184 were females; 36 cases (8.5%) were LGA, and 16 cases (3.8%) were SGA. During follow-up within 24 month of CA, 89 cases (21.1%) developed moderate to severe malnutrition. When compared separately among different birth weight and gestational age at birth groups, there had both statistically differences in the incidence of moderate to severe malnutrition ( χ2=42.94 and 9.17, both P<0.05). The incidence was the highest in the birth weight of CA<500 g group and the <25 weeks gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks gestational age at birth group in their respective groups. Growth retardation occurred in 5.2% (22/422). However, there had statistically differences in the incidence of growth retardation among different birth weight and gestational age at birth groups, in each grouped time interval ( χ2=21.61 and 4.30, both P<0.05). The proportions of rapid growth were relatively high in the 0-3 months and 3-6 months of CA groups, which were 96 cases (27.4%) and 98 cases (26.6%), respectively. Overall, appropriate catch-up growth was achieved in 341 cases (80.8%) from 0 to 24 months of CA. There had statistically differences in the completion rate of appropriate catch-up growth among different birth weight and gestational age at birth groups ( χ2=23.65 and 7.08, both P<0.05). The completion rate was the highest in the birth weight of CA<500 g group and the <25 weeks of gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks of gestational age at birth group. Conclusions:The lower the birth weight and gestational age of extremely preterm infants, the higher the incidence of moderate to severe malnutrition and the lower the achievement rate of adequate catch-up growth within 24 months of CA. The period of 0-6 months of CA is the critical window for catch-up in extremely preterm infants.

Objective:To assess the status of undernutrition and appropriate catch-up growth in extremely preterm infants within 24 months of corrected age (CA).Methods:A retrospective cohort study was conducted. A total of 422 extremely preterm infants born at Shenzhen Maternity and Child Healthcare Hospital, Women and Children's Medical Center, Southern Medical University from January 2017 to December 2022 and followed up until 24 months of CA were enrolled. The extremely preterm infants were grouped by gestational age at birth (<25, 25-26, 27 weeks), birth weight (<500, 500-749, 750-999,≥1 000 g), weight for gestational age (large for gestational age (LGA), appropriate for gestational age (AGA), small for gestational age (SGA)) and sex. Weight data within 24 months of CA were collected every 3 months. Nutritional insufficiency, growth rate, and achievement of adequate catch-up growth were analyzed during the period from 0 to 24 months of CA. Z-score method was used to analyze data. Fenton 2013 preterm growth charts (Fenton 2013) were used before 40 weeks of corrected gestational age, and World Health Organization child growth standards (2009) fitted Z-scores were applied from 40 weeks of CA. Changes in weight Z-scores of extremely preterm infants from 0 to 24 months of CA were observed and compared, the occurrence of moderate to severe malnutrition and growth retardation was determined, nutritional insufficiency was assessed, and growth rate as well as the achievement of appropriate catch-up growth were analyzed. The Lambda-mu-sigma method combined with the Z-score fitting model was used to fit and analyze the distribution characteristics of weight percentiles in extremely preterm infants. The Chi-square test was used to compare differences among groups.Results:A total of 422 extremely preterm infants were included, with a gestational age at birth of 26.3(25.4, 27.2) weeks and a birth weight of (880±177) g. Among them, 238 were males and 184 were females; 36 cases (8.5%) were LGA, and 16 cases (3.8%) were SGA. During follow-up within 24 month of CA, 89 cases (21.1%) developed moderate to severe malnutrition. When compared separately among different birth weight and gestational age at birth groups, there had both statistically differences in the incidence of moderate to severe malnutrition ( χ2=42.94 and 9.17, both P<0.05). The incidence was the highest in the birth weight of CA<500 g group and the <25 weeks gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks gestational age at birth group in their respective groups. Growth retardation occurred in 5.2% (22/422). However, there had statistically differences in the incidence of growth retardation among different birth weight and gestational age at birth groups, in each grouped time interval ( χ2=21.61 and 4.30, both P<0.05). The proportions of rapid growth were relatively high in the 0-3 months and 3-6 months of CA groups, which were 96 cases (27.4%) and 98 cases (26.6%), respectively. Overall, appropriate catch-up growth was achieved in 341 cases (80.8%) from 0 to 24 months of CA. There had statistically differences in the completion rate of appropriate catch-up growth among different birth weight and gestational age at birth groups ( χ2=23.65 and 7.08, both P<0.05). The completion rate was the highest in the birth weight of CA<500 g group and the <25 weeks of gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks of gestational age at birth group. Conclusions:The lower the birth weight and gestational age of extremely preterm infants, the higher the incidence of moderate to severe malnutrition and the lower the achievement rate of adequate catch-up growth within 24 months of CA. The period of 0-6 months of CA is the critical window for catch-up in extremely preterm infants.

BACKGROUND: Recent studies have provided compelling evidence that exposure to brominated flame retardants (BFRs) can adversely affect human health. We aim to explore the potential impact of BFRs on adiposity and central obesity. METHODS: Data from the National Health and Nutrition Examination Surveys (NHANES) cycles conducted between 2009 and 2014 was used to study the connections between variables. After filtering, we analyzed a sample of 4,110 adults aged 20 years and above. Our goal was to examine the potential association between BFRs and consequences and investigate the part played by oxidative stress and inflammatory markers as intermediaries. To achieve this, we used advanced statistical methods such as weighted quantile sum (WQS) regression, quantile-based g-computation (QGC), and the Bayesian kernel machine regression (BKMR). RESULTS: The findings showed that among the examined chemicals, exposure to PBDE85 (weight: 41%), PBDE100 (24%), and PBB153 (23%) may be the dominant contributors to general obesity risk. Upon controlling for all variables that could impact the results, it was found that the QGC outcomes indicated a positive correlation between exposure to mixtures of brominated flame retardants and the occurrence of abdominal obesity (OR = 1.187, 95% CI: 1.056-1.334, p = 0.004). Significant contributions were made by PBDE85 (52%), PBB153 (27%), and PBDE100 (21%). Mediation analysis shows that lymphatic cells (LC) and albumin (ALB) partially mediate the link between brominated flame retardants and obesity. The results of BKMR are generally consistent with those of WQS and QGC. CONCLUSION At a population level, our research has revealed a noteworthy correlation between BFRs and obesity. However, further investigation is required through prospective cohort studies and in-depth mechanistic exploratory studies.
Humans ; Flame Retardants/adverse effects* ; Oxidative Stress/drug effects* ; Adult ; Male ; Female ; Middle Aged ; Inflammation/epidemiology* ; Obesity/chemically induced* ; Biomarkers/blood* ; Nutrition Surveys ; Mediation Analysis ; Young Adult ; United States/epidemiology* ; Environmental Exposure/adverse effects* ; Aged ; Environmental Pollutants/adverse effects* ; Halogenated Diphenyl Ethers/adverse effects*

Objective To screen the targets related to the metabolic enzymes involved in the cholesterol synthesis pathway that inhibits the polarization of macrophages towards M1 phenotype,and verify the intervention effects and underlying mechanisms in colorectal cancer cells.Methods Mouse colorectal cancer MC38 cells were divided into control group(si-NC)and experimental groups(the expression of enzymes in cholesterol synthesis pathway was interfered with siRNA for corresponding targets).RT-qPCR was used to detect the mRNA levels of corresponding targets in MC38 cells after transfection.After peritoneal macrophages were extracted from male C57BL/6 mice(6 weeks old,weighing 13～18 g),the macrophages were then treated with the conditioned media of MC38 cells transfected with different siRNAs for 48 h.RT-qPCR was employed to detect the mRNA levels of IL-1β,IL-6 and TNF-α in the macrophages so as to evaluate the effect of the culture media on the M1 polarization.MC38 cells were divided into control groups(OE-NC and sh-NC),farnesyl-diphosphate farnesyltransferase 1(FDFT1)overexpression group(OE-FDFT1)and FDFT1 knockdown group(sh-FDFT1).RT-qPCR was applied to detect the mRNA expression of FDFT1,and Western blotting was conducted to measure the protein level of FDFT1.C57BL/6 mice were subjected randomly to construct a subcutaneous tumor-bearing model and a model of intraperitoneal metastatic tumor(n=5)respectively.The growth of tumor mass was then measured.Flow cytometry was used to observe the proliferation and apoptosis of MC38 cells,and Trans well assay to detect migration ability of MC38 cells.Five C57BL/6 macrophage-depleted mice(established with injection of clodronate liposome suspension through tail vein)received intraperitoneal implantation to construct a metastasis model,and then the obtained tumor masses were then weighted.Results Compared with MC38 cells after si-NC transfection,the mRNA levels of corresponding targets in MC38 cells in the experimental groups were significantly reduced(P＜0.05).Significant increases were found in the mRNA levels of IL-1β,IL-6 and TNF-α of the macrophages with FDFT1 interference than the control cells(P＜0.05).There were no statistical differences in the proliferation,apoptosis and migration of MC38 cells in the control group(OE-NC and sh-NC)and the cells of the FDFT1 overexpression group and FDFT1 knockdown group(P＞0.05).In both the subcutaneous tumor-bearing model and the model of intraperitoneal metastatic tumor,the mass weight was significantly heavier in the OE-FDFT1 group than the OE-NC group(P＜0.01),and was notably smaller in the sh-FDFT1 group than the sh-NC group(P＜0.01).For the macrophage-depleted mouse tumor model,no remarkable change was observed in the tumor weight between the OE-FDFT1 group and the OE-NC group as well as the sh-FDFT1 group and the sh-NC group.Conclusion FDFT1,the metabolic enzyme in the cholesterol synthesis pathway of colorectal cancer tumor cells,is a potential target for tumor immunotherapy targeting macrophages,which promotes tumor progression by regulating macrophages.

Objective:To identify risk factors influencing the incidence of hypertension among steelworkers (Homo sapiens) and establish an effective and easily implementable hypertension prediction model.Methods:In September 2023, 2214 steelworkers (Homo sapiens) were selected as study subjects. Basic demographic information, lifestyle, and occupational exposure data were collected, along with physiological measurements such as height, weight, and blood pressure. Multivariate unconditional logistic regression analysis was employed based on relevant literature to determine influencing factors for hypertension among steelworkers (Homo sapiens). Python 3.9 software was used to construct and compare logistic regression, support vector machine (SVM), random forest, extreme gradient boosting tree (XGBoost), and LGBM models. Model performance was evaluated using metrics such as receiver operating characteristic (ROC) curves, accuracy, calibration curves, and F1 scores. The Shapley Additive Explanations (SHAP) model was introduced for feature importance analysis to enhance the interpretability of the prediction model.Results:A total of 432 cases of hypertension were detected among 2214 study subjects, with a detection rate of 19.51%. Age, smoking status, salt intake, use of cooling equipment, carbon monoxide exposure, family history of hypertension, fasting blood glucose, triglycerides, and hemoglobin were identified as independent risk factors for hypertension ( P<0.05). A comparison of the five models revealed the following performance metrics: logistic regression achieved an accuracy of 0.853, F1 score of 0.680, Brier score of 0.108, and AUC of 0.907; SVM demonstrated an accuracy of 0.863, F1 score of 0.687, Brier score of 0.081, and AUC of 0.910; random forest showed an accuracy of 0.857, F1 score of 0.603, Brier score of 0.105, and AUC of 0.861; XGBoost yielded an accuracy of 0.850, F1 score of 0.684, Brier score of 0.117, and AUC of 0.899; and the LGBM model exhibited an accuracy of 0.838, F1 score of 0.625, Brier score of 0.112, and AUC of 0.870. Conclusion:The SVM model demonstrated strong predictive performance, effectively assessing the risk of hypertension among steelworkers (Homo sapiens) and facilitating targeted health management interventions.

Objective:To compare the effects of using cone beam CT (CBCT) and oral scanning registration on implant positional accuracy during robot-assisted implant surgery, and to provide a basis for selecting the appropriate registration for robot-assisted implant surgical options.Methods:One patient with dentition defect, specifically missing teeth at positions 21 and 26 and having natural teeth adjacent mesially and distally to the edentulous area, who visited the Department of Oral Implantology, School of Hospital of Stomatology Wuhan University in 2024 were selected. Based on reconstructed imaging data, 30 identical jaw models were printed. These models were divided into a CBCT registration group and an intra-oral scanning registration group (15 models per group). An associate chief physician with extensive experience in implant surgery performed preoperative registration using the implant robot and completed the implant surgeries. Postoperative CBCT scans were used to determine the three-dimensional position of the implants. The deviations between the planned implant position and the actual position were evaluated, including deviations at the implantation point, apical point, and angular deviation. The differences between the two groups were compared.Results:The implantation deviation was 0.675 (0.490) mm, apical deviation was (0.680±0.272) mm, and the angular deviation was 0.566°±0.147° in the CBCT registration group, and in the intra-oral scanning registration group, implantation deviation was 0.695 (0.313) mm, apical deviation was (0.667±0.217) mm, and the angular deviation was 0.523°±0.168°. There was no statistically significant error in implant precision between the two groups ( P>0.05). Conclusions:This in vitro experiment found that the use of intra-oral scanning registration in robot-assisted implant surgery can achieve similar implant placement accuracy as CBCT registration.

Objective:To identify risk factors influencing the incidence of hypertension among steelworkers (Homo sapiens) and establish an effective and easily implementable hypertension prediction model.Methods:In September 2023, 2214 steelworkers (Homo sapiens) were selected as study subjects. Basic demographic information, lifestyle, and occupational exposure data were collected, along with physiological measurements such as height, weight, and blood pressure. Multivariate unconditional logistic regression analysis was employed based on relevant literature to determine influencing factors for hypertension among steelworkers (Homo sapiens). Python 3.9 software was used to construct and compare logistic regression, support vector machine (SVM), random forest, extreme gradient boosting tree (XGBoost), and LGBM models. Model performance was evaluated using metrics such as receiver operating characteristic (ROC) curves, accuracy, calibration curves, and F1 scores. The Shapley Additive Explanations (SHAP) model was introduced for feature importance analysis to enhance the interpretability of the prediction model.Results:A total of 432 cases of hypertension were detected among 2214 study subjects, with a detection rate of 19.51%. Age, smoking status, salt intake, use of cooling equipment, carbon monoxide exposure, family history of hypertension, fasting blood glucose, triglycerides, and hemoglobin were identified as independent risk factors for hypertension ( P<0.05). A comparison of the five models revealed the following performance metrics: logistic regression achieved an accuracy of 0.853, F1 score of 0.680, Brier score of 0.108, and AUC of 0.907; SVM demonstrated an accuracy of 0.863, F1 score of 0.687, Brier score of 0.081, and AUC of 0.910; random forest showed an accuracy of 0.857, F1 score of 0.603, Brier score of 0.105, and AUC of 0.861; XGBoost yielded an accuracy of 0.850, F1 score of 0.684, Brier score of 0.117, and AUC of 0.899; and the LGBM model exhibited an accuracy of 0.838, F1 score of 0.625, Brier score of 0.112, and AUC of 0.870. Conclusion:The SVM model demonstrated strong predictive performance, effectively assessing the risk of hypertension among steelworkers (Homo sapiens) and facilitating targeted health management interventions.

Objective:To compare the effects of using cone beam CT (CBCT) and oral scanning registration on implant positional accuracy during robot-assisted implant surgery, and to provide a basis for selecting the appropriate registration for robot-assisted implant surgical options.Methods:One patient with dentition defect, specifically missing teeth at positions 21 and 26 and having natural teeth adjacent mesially and distally to the edentulous area, who visited the Department of Oral Implantology, School of Hospital of Stomatology Wuhan University in 2024 were selected. Based on reconstructed imaging data, 30 identical jaw models were printed. These models were divided into a CBCT registration group and an intra-oral scanning registration group (15 models per group). An associate chief physician with extensive experience in implant surgery performed preoperative registration using the implant robot and completed the implant surgeries. Postoperative CBCT scans were used to determine the three-dimensional position of the implants. The deviations between the planned implant position and the actual position were evaluated, including deviations at the implantation point, apical point, and angular deviation. The differences between the two groups were compared.Results:The implantation deviation was 0.675 (0.490) mm, apical deviation was (0.680±0.272) mm, and the angular deviation was 0.566°±0.147° in the CBCT registration group, and in the intra-oral scanning registration group, implantation deviation was 0.695 (0.313) mm, apical deviation was (0.667±0.217) mm, and the angular deviation was 0.523°±0.168°. There was no statistically significant error in implant precision between the two groups ( P>0.05). Conclusions:This in vitro experiment found that the use of intra-oral scanning registration in robot-assisted implant surgery can achieve similar implant placement accuracy as CBCT registration.

Objective:To construct a nomogram model for predicting frailty in elderly hypertensive patients, and to evaluate the discrimination and consistency of the model.Methods:A total of 317 patients with essential hypertension who were admitted to Hebei Eighth People′s Hospital from February 2021 to June 2022 were taken, they were divided into modeling group (190 cases) and verification group (127 cases) according to the proportion of 6∶4, the patients in the modeling group were divided into the asthenic group (45 cases) and the non asthenic group (145 cases) according to whether the patients in the modeling group had asthenia. The nomograph model was constructed based on the results of Logistic analysis.Results:The age, obesity or overweight ratio, diabetes ratio and systolic blood pressure in the frail group were significantly higher than those in the non-frail group: (76.25 ± 3.64)years vs.(70.44 ± 3.82) years, 51.11%(23/45) vs. 24.83%(36/145), 46.67%(21/45) vs. 17.24%(25/145), (156.46 ± 18.64) mmHg (1 mmHg = 0.133 kPa) vs. (143.25 ± 12.38) mmHg, and the mini-nutrition assessment summary form (MNA-SF) score was significantly lower than that in the non-frail group: (11.45 ± 2.06) scores vs. (13.12 ± 1.22) scores, there were statistical differences ( P<0.05). Logistic results showed that age, body mass index, diabetes, and systolic blood pressure were the risk factors for frailty ( P<0.05). The receiver operating characteristic (ROC) curve evaluation showed that the area under the curve (AUC) in the modeling group was 0.998, and AUC in the validation group was 0.954. The Hosmer-Lemeshow goodness of fit test showed: modeling group χ2 = 6.18, P = 0.627; validation group χ2 = 6.58, P = 0.582. Conclusions:The nomogram prediction model of frailty risk in elderly hypertensive patients has good consistency and differentiation