To investigate the correlation between vitamin D nutritional status and insulin resistance in pubertal adolescents.

Background Diesel engines are widely used in transportation, agriculture, construction, industry, and other fields. Diesel exhaust, classified as a Group 1 carcinogen, emits particles (DEP) that can penetrate deep into the respiratory tract, posing significant health risks. DEP pollution is particularly severe in confined environments, necessitating effective control measures. Objective Under laboratory simulation conditions, to explore the spatiotemporal distribution characteristics of the mass and number concentrations of DEP as it diffuses indoors and to reveal the effects of ventilation and additional airflow on indoor DEP pollution levels. Methods A diesel engine was placed in a laboratory (length 3.39 m × width 2.85 m × height 2.4 m) with its exhaust emitted from east to west. An air purifier was installed 1 m south of the engine. Eight measurement points (1 m horizontal distance from the exhaust outlet, height: 1 m/1.5 m) were setup to monitor DEP concentrations using portable laser particle sizers. The effects of engine power (4.05 kW vs. 5.15 kW), ventilation (maximum airflow: 600 m³·h⁻¹), additional airflow intensity (low and high), and direction (forward/reverse) on DEP pollution were analyzed. DEP levels of 5 diesel vehicle models were also compared. Results The mass and number concentrations of DEP indoors increased immediately after the diesel engine started. The peak mass concentration time at the eastern measurement point (−1, 0) m opposite to the exhaust direction (17.70 min) was significantly longer than that at the western (1, 0) m (16.20 min), southern (0, -1) m (14.45 min), and northern (0, 1) m (12.70 min) points (P<0.05), with no significant differences between the other points (western, southern, and northern) (P>0.05). The northern point (0, 1) m exhibited the highest DEP mass and number concentration peaks (174.62 μg·m⁻³, 1319.85 p·cm⁻³), significantly exceeding those at the southern (0, −1) m (129.89 μg·m⁻³, 1175.24 p·cm⁻³), eastern (−1, 0) m (140.12 μg·m⁻³, 1120.53 p·cm⁻³), and western (1, 0) m (147.60 μg·m⁻³, 818.62 p·cm⁻³) points (P<0.05), and no significant differences were observed among other points (P>0.05). There were no significant differences in peak DEP mass and number concentrations by measurement heights (P>0.05). Diesel engine power, ventilation, airflow intensity, and airflow direction had no significant effect on the time of peak DEP concentration (P>0.05). However, higher engine power (5.15 kW) produced greater DEP peaks [(186.66±19.29) μg·m⁻³, (1382.79±122.56) p·cm⁻³] than the 4.05 kW engine power [(168.41±12.65) μg·m⁻³, (1284.45±71.30) p·cm⁻³] (P<0.05). The peak mass concentration [(342.04±35.03) μg·m⁻³] and number concentration [(1886.87±57.91) p·cm⁻³] of DEP in the non-ventilated group were significantly higher than those in the ventilated group [(186.66±19.29) μg·m⁻³, (1382.79±122.56) p·cm⁻³] (P<0.001). Forward airflow elevated DEP mass concentrations compared to reverse airflow (287.71 μg·m⁻³ vs. 243.74 μg·m⁻³, t=−2.592, P=0.009), but no effects on DEP number concentration (P>0.05). Significant differences in mass concentration were observed among selected 5 vehicle models (Z=38.109, P<0.001). Conclusion The operation of diesel engines will emit a large amount of particulate matter, causing pollution in enclosed spaces. Diesel engines with greater power have higher levels of DEP pollution emissions. Based on the spatiotemporal distribution characteristics, it is recommended to set the operation position in the reverse direction of exhaust emissions and close to air purifiers, while avoiding the use of additional air flow equipment.

Dendritic cells (DCs) serve as the primary antigen-presenting cells in autoimmune diseases, like rheumatoid arthritis (RA), and exhibit distinct signaling profiles due to antigenic diversity. Type II collagen (CII) has been recognized as an RA-specific antigen; however, little is known about CII-stimulated DCs, limiting the development of RA-specific therapeutic interventions. In this study, we show that CII-stimulated DCs display a preferential gene expression profile associated with migration, offering a new perspective for targeting DC migration in RA treatment. Then, saikosaponin D (SSD) was identified as a compound capable of blocking CII-induced DC migration and effectively ameliorating arthritis. Optineurin (OPTN) is further revealed as a potential SSD target, with Optn deletion impairing CII-pulsed DC migration without affecting maturation. Function analyses uncover that OPTN prevents the proteasomal transport and ubiquitin-dependent degradation of C-C chemokine receptor 7 (CCR7), a pivotal chemokine receptor in DC migration. Optn-deficient DCs exhibit reduced CCR7 expression, leading to slower migration in CII-surrounded environment, thus alleviating arthritis progression. Our findings underscore the significance of antigen-specific DC activation in RA and suggest OPTN is a crucial regulator of CII-specific DC migration. OPTN emerges as a promising drug target for RA, potentially offering significant value for the therapeutic management of RA.

OBJECTIVES: To develop a risk prediction model for left ventricular adverse remodeling (LVAR) based on cardiac magnetic resonance (CMR) parameters in patients undergoing percutaneous coronary intervention (PCI) for acute ST-segment elevation myocardial infarction (STEMI). METHODS: A total of 329 acute STEMI patients undergoing primary PCI at 8 medical centers from January, 2018 to December, 2021 were prospectively enrolled. The parameters of CMR, performed at 7±2 days and 6 months post-PCI, were analyzed using CVI42 software. LVAR was defined as an increase >20% in left ventricular end-diastolic volume or >15% in left ventricular end-systolic volume at 6 months compared to baseline. The patients were randomized into training (n=230) and validation (n=99) sets in a 7∶3 ratio. In the training set, potential predictors were selected using LASSO regression, followed by univariate and multivariate logistic regression to construct a nomogram. Model performance was evaluated using receiver-operating characteristic (ROC) curves, area under the curve (AUC), calibration curves, and decision curve analysis. RESULTS: LVAR occurred in 100 patients (30.40%), who had a higher incidence of major adverse cardiovascular events than those without LVAR (58.00% vs 16.16%, P<0.001). Left ventricular global longitudinal strain (LVGLS; OR=0.76, 95% CI: 0.61-0.95, P=0.015) and left atrial active strain (LAAS; OR=0.78, 95% CI: 0.67-0.92, P=0.003) were protective factors for LVAR, while infarct size (IS; OR=1.05, 95% CI: 1.01-1.10, P=0.017) and microvascular obstruction (MVO; OR=1.26, 95% CI: 1.01-1.59, P=0.048) were risk factors for LVAR. The nomogram had an AUC of 0.90 (95% CI: 0.86-0.94) in the training set and an AUC of 0.88 (95% CI: 0.81-0.94) in the validation set. CONCLUSIONS LVGLS, LAAS, IS, and MVO are independent predictors of LVAR in STEMI patients following PCI. The constructed nomogram has a strong predictive ability to provide assistance for management and early intervention of LVAR.
Humans ; Percutaneous Coronary Intervention ; Prospective Studies ; ST Elevation Myocardial Infarction/diagnostic imaging* ; Ventricular Remodeling ; Magnetic Resonance Imaging ; Male ; Female ; Middle Aged ; Risk Factors ; Aged ; Risk Assessment

OBJECTIVES: To investigate the inhibitory effect of pirfenidone (PFD) on growth of bladder cancer xenograft and its regulatory effect on Treg cells in tumor-bearing mice. METHODS: Thirty-two C57BL/6 mice bearing ectopic bladder tumors were randomized into control and PFD groups (n=16). In PFD group, PFD was administered orally at the daily dose of 500 mg/kg, and tumor growth and survival of the mice were monitored. After treatment for 21 days, the tumors and vital organs were harvested for analysis. Immunohistochemistry was used to assess CD3, CD4, CD8, and FOXP3 expressions in the tumors. Flow cytometry and RT-qPCR were used to analyze the percentage of CD4⁺CD25⁺FOXP3⁺ Treg cells and IL-2, IL-10, and IL-35 expressions in the tumors and spleens; organ damage of the mice was examined with HE staining. RESULTS: Compared with the control group, the PFD-treated mice exhibited significantly lower tumor growth rate with smaller tumor volumes at day 21, along with improved survival at day 28. Immunohistochemistry revealed no significant differences in the infiltration of CD3⁺ and CD8⁺ cells between the two groups, but the percentages of CD4⁺ and FOXP3⁺ cells were significantly lower in the tumors of PFD-treated mice. Flow cytometric analysis confirmed a decrease in CD4⁺CD25⁺FOXP3⁺ Treg cells in the tumors from PFD-treated mice, which also had reduced expression levels of IL-2, IL-10 and IL-35 mRNAs in the tumors. No significant differences were found in Treg cell populations or cytokine expressions in the spleen tissues between the two groups. HE staining showed obvious organ damage in neither of the groups. CONCLUSIONS PFD inhibits bladder cancer growth and enhances survival of tumor-bearing mice possibly by suppressing Treg cells in the tumor microenvironment.
Animals ; Urinary Bladder Neoplasms/drug therapy* ; Mice ; T-Lymphocytes, Regulatory/metabolism* ; Mice, Inbred C57BL ; Interleukins/metabolism* ; Interleukin-10/metabolism* ; Cell Line, Tumor ; Interleukin-2/metabolism* ; Xenograft Model Antitumor Assays ; Female

As the need for antibody production rises, there is an urgent need to lower the costs and enhance the efficiency of the separation process. Currently, the chromatographic media used for antibody separation and purification often focus on individual properties of antibodies, such as affinity, hydrophobicity, and charge, leading to issues like low purification efficiency or inadequate adsorption capacity. To address this, an electrostatically coupled polypeptide affinity medium (FD7-3, 5-diaminobenzoic acid n-sepharose, FD7-DA-Sepharose) was developed for rapid purification of antibodies from cell culture supernatant. This medium utilized 3, 5-diaminobenzoic acid as a spacer to attach the heptapeptide-affinity ligand (FYEILHD, FD7) to agarose microspheres. Antibodies could be adsorbed through charge interactions with the carboxyl functional group of the FD7-DA-Sepharose spacer, while FD7 enhanced electrostatic coupling and affinity adsorption through synergistic effects, significantly increasing the adsorption capacity while maintaining the affinity and specificity. The influences of pH and ionic strength on adsorption capacity were investigated with human immunoglobulin as a model protein. The static adsorption capacity (Q_m) of FD7-DA-Sepharose in the solution of pH 6.0 reached 67.73 mg/mL, representing a 52.68% increase compared with that (44.36 mg/mL) of the commercial Protein A affinity medium. Furthermore, the elution conditions for FD7-DA- Sepharose were mild (20 mmol/L PB, 0.5 mol/L NaCl, pH 6.0), in contrast to the harsh acidic elution (pH 2.7-3.6) typically associated with Protein A, which can damage antibody integrity. The FD7-DA-Sepharose medium was then employed to purify antibodies from cell culture supernatant, achieving the yield of 94.8% and the purity of 98.4%. The secondary structure of the purified antibody was determined by circular dichroism spectroscopy. The results demonstrated that FD7-DA-Sepharose enabled efficient purification of antibodies from cell culture supernatant, which provided a cost-effective solution (approximately one-third the price of commercial Protein A affinity medium) with gentle elution conditions that preserve the natural conformation of antibodies. This approach paves a novel, economical, and efficient way for the separation and purification of antibodies from cell culture supernatant.
Chromatography, Affinity/methods* ; Static Electricity ; Humans ; Sepharose/analogs & derivatives* ; Peptides/chemistry* ; Adsorption ; Antibodies/isolation & purification*

Objective:To analyze the use of medicare antiviral drugs (ART) and related factors among HIV-infected people in Ningbo City.Methods:The retrospective data was collected related to infection and treatment of HIV-infected people in ART in Ningbo up to February 2023 through the National Infectious Disease Surveillance System. Binary logistic regression was used to analyze the factors related to medicare antiviral drug use in HIV-infected people. R 4.2.2 software was used for statistical analysis.Results:A total of 6 433 HIV-infected people with ART records were collected, among which 5 783 were in ART. The prevalence of medicare drugs use among people in ART was 24.8% (1 435/5 783, 95% CI: 23.7%-25.9%). Beilun District (8.7%, 43/497) and Fenghua District (5.7%, 14/247) had the lowest level in medicare drugs use. Among people in ART using medicare or out‐of‐pocket drugs, the prevalence of those who had at least one viral load test in the last year (84.9%, 1 352/1 593) was significantly lower than that of those using free drugs (91.4%, 3 829/4 190) ( χ2=52.50, P<0.001). The results of multivariate logistic analysis showed that the factors influencing medicare drug use included low educational level (junior high school and below: a OR=0.24, 95% CI:0.17-0.34), farmer or worker (farmer: a OR=0.60, 95% CI: 0.39-0.91; worker: a OR=0.42, 95% CI: 0.27-0.64), low monthly income (<3 000 Yuan: a OR=0.29, 95% CI: 0.18-0.45), the longer interval time between diagnosis and treatment (≥21 days: a OR=0.47, 95% CI: 0.30-0.74). Conclusions:Significant regional differences on the prevalence of medicare antiviral drugs use in HIV-infected people exist in Ningbo City. Follow-up management program of patients should be improved to strengthen patient compliance to mobilize medicare drug promotion. Meanwhile, publicity of medicare drugs should be strengthened for farmers or workers with low education level and patients with delayed treatment.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.

Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.