Objective:To construct and validate a depression risk prediction model for middle-aged and elderly patients with diabetes.Methods:Data were extracted from the fifth wave (2020) of the China Health and Retirement Longitudinal Study (CHARLS). A total of 900 diabetic patients were identified, and after excluding those with missing data or invalid questionnaires, 769 patients were included in the analysis. Patients were randomly divided into a training set and a validation set in a 7∶3 ratio. Univariate analysis and logistic regression analysis were performed to screen the optimal predictors of depression in diabetic patients, and a nomogram model was developed. The predictive performance of the model was assessed by the area under the receiver operating characteristic curve ( AUC). Model calibration and accuracy were evaluated using bootstrap resampling, calibration plots, and the Hosmer-Lemeshow test. The clinical utility was further assessed by decision curve analysis (DCA) and clinical impact curves (CIC) . Results:Among the 769 patients, 366 (47.59%) had depression. Logistic regression analysis showed that place of residence, pain, difficulty in toileting, difficulty in bathing, sleep duration, physical exercise, life satisfaction, and children's satisfaction were independent predictors of depression in diabetic patients. A nomogram was constructed based on these variables, yielding an AUC of 0.775. At the optimal cutoff value of 0.557, the model demonstrated a sensitivity of 59.1% and a specificity of 84.8%, indicating good discriminative ability. The Hosmer-Lemeshow test showed (χ 2=15.821, P=0.105), suggesting good agreement between predicted and observed outcomes. In the validation set, the AUC was 0.778, with Hosmer-Lemeshow (χ 2=8.557, P=0.575). DCA and CIC indicated favorable clinical applicability of the model. Conclusions:The depression risk prediction model constructed in this study demonstrated good predictive performance. It can assist clinicians in early identification of high-risk individuals with diabetes and provide a theoretical basis for targeted interventions.

Tuberculosis is still the second leading cause of death from a single source of infection in the world.There is a two-way relationship between tuberculosis and the nutritional status of the body,which affects and causes each other.Vitamin D is an essential micronutrient,most research results show that vitamin D deficiency is common in tuberculosis patients,which is related to lack of sunlight,decreased dietary intake of vitamin D and anti-tuberculosis drug treatment.Low level vitamin D can increase tuberculosis susceptibility to some extent,but the research results are not completely consistent.This paper reviews the nutritional status of vitamin D in tuberculosis patients in recent years,the causes of vitamin D deficiency in tuberculosis patients and the relationship between vitamin D deficiency and susceptibility of tuberculosis,so as to provide references for further study on the role of vitamin D in tuberculosis prevention and treatment.

Image 1.

Objective To evaluate the relationship between systemic inflammation makers and bone mineral density(BMD)in male patients with type 2 diabetes(T2DM).Methods A total of 261 male patients with T2DM were selected and divided into three groups based on diagnostic criteria:the normal bone mass group(96 cases),the reduced bone mass group(111 cases)and the osteoporosis group(54 cases).Differences in systemic inflammation markers and bone metabolic markers were compared between the three groups.Multivariate ordered Logistic regression analysis was used to investigate factors influencing the progression from normal bone mass to osteoporosis in male patients with T2DM.Receiver operating characteristic(ROC)curves were used to evaluate the predictive value of inflammatory markers for osteoporosis in male patients with T2DM.Correlation analysis was conducted to investigate the correlation between inflammatory markers and BMD and bone turnover markers(BTM)in male patients with T2DM.Results Platelet count(PLT),platelet-to-lymphocyte ratio(PLR),systemic inflammatory index(SII)and neutrophil-to-lymphocyte ratio(NLR)were significantly higher in the osteoporosis group than those in the normal bone mass group(P＜0.05).Multivariate ordered Logistic regression analysis showed that PLR and SII were risk factors for the progression from normal bone mass to osteoporosis in male patients with T2DM(P＜0.05).The area under the ROC curve of PLR was 0.590,and the cut-off value was 96.67.The area under the curve of SII was 0.613,with a cut-off value of 307.9,and the area under the combined curve of the above two indicators was 0.612.In patients with osteoporosis and osteopenia,SII,PLR and PLT were negatively correlated with L1-4 BMD and left hip BMD(P＜0.05).SII was also negatively correlated with left femoral neck BMD(P＜0.05).Conclusion Inflammatory markers PLR and SII have predictive values for the progression from normal bone mass to bone loss and osteoporosis in male patients with T2DM.

Objective:To construct and validate a depression risk prediction model for middle-aged and elderly patients with diabetes.Methods:Data were extracted from the fifth wave (2020) of the China Health and Retirement Longitudinal Study (CHARLS). A total of 900 diabetic patients were identified, and after excluding those with missing data or invalid questionnaires, 769 patients were included in the analysis. Patients were randomly divided into a training set and a validation set in a 7∶3 ratio. Univariate analysis and logistic regression analysis were performed to screen the optimal predictors of depression in diabetic patients, and a nomogram model was developed. The predictive performance of the model was assessed by the area under the receiver operating characteristic curve ( AUC). Model calibration and accuracy were evaluated using bootstrap resampling, calibration plots, and the Hosmer-Lemeshow test. The clinical utility was further assessed by decision curve analysis (DCA) and clinical impact curves (CIC) . Results:Among the 769 patients, 366 (47.59%) had depression. Logistic regression analysis showed that place of residence, pain, difficulty in toileting, difficulty in bathing, sleep duration, physical exercise, life satisfaction, and children's satisfaction were independent predictors of depression in diabetic patients. A nomogram was constructed based on these variables, yielding an AUC of 0.775. At the optimal cutoff value of 0.557, the model demonstrated a sensitivity of 59.1% and a specificity of 84.8%, indicating good discriminative ability. The Hosmer-Lemeshow test showed (χ 2=15.821, P=0.105), suggesting good agreement between predicted and observed outcomes. In the validation set, the AUC was 0.778, with Hosmer-Lemeshow (χ 2=8.557, P=0.575). DCA and CIC indicated favorable clinical applicability of the model. Conclusions:The depression risk prediction model constructed in this study demonstrated good predictive performance. It can assist clinicians in early identification of high-risk individuals with diabetes and provide a theoretical basis for targeted interventions.

Thyrotoxic periodic paralysis(TPP) is a rare but potentially life-threatening complication of thyrotoxicosis. TPP secondary to thyrotoxicosis factitia(TF) is exceptionally uncommon. Here, we report the case of a 31-year-old female who developed TF and subsequent TPP after taking laxatives containing unknown ingredients. The patient presented with acute onset of quadriplegia. Laboratory investigations revealed severe hypokalemia(serum potassium 1.47mmol/L), thyrotoxicosis[thyroid stimulating hormone(TSH)<0.005 mIU/L, free thyroxine(FT 4) 30.84 pmol/L, free triiodothyronine(FT 3) 7.71 pmol/L], and a decreased thyroglobulin level(3.08 ng/mL). The patient′s symptoms resolved rapidly following potassium supplementation, and thyroid function gradually normalized after discontinuation of the suspected medication. This case highlights the importance of considering TF in the differential diagnosis of TPP, particularly in patients with a history of unknown medication use. It also underscores the diagnostic value of thyroglobulin measurement in identifying TF and outlines clinical strategies for the management of TF-induced TPP.

Thyrotoxic periodic paralysis(TPP) is a rare but potentially life-threatening complication of thyrotoxicosis. TPP secondary to thyrotoxicosis factitia(TF) is exceptionally uncommon. Here, we report the case of a 31-year-old female who developed TF and subsequent TPP after taking laxatives containing unknown ingredients. The patient presented with acute onset of quadriplegia. Laboratory investigations revealed severe hypokalemia(serum potassium 1.47mmol/L), thyrotoxicosis[thyroid stimulating hormone(TSH)<0.005 mIU/L, free thyroxine(FT 4) 30.84 pmol/L, free triiodothyronine(FT 3) 7.71 pmol/L], and a decreased thyroglobulin level(3.08 ng/mL). The patient′s symptoms resolved rapidly following potassium supplementation, and thyroid function gradually normalized after discontinuation of the suspected medication. This case highlights the importance of considering TF in the differential diagnosis of TPP, particularly in patients with a history of unknown medication use. It also underscores the diagnostic value of thyroglobulin measurement in identifying TF and outlines clinical strategies for the management of TF-induced TPP.

Objective To evaluate the relationship between systemic inflammation makers and bone mineral density(BMD)in male patients with type 2 diabetes(T2DM).Methods A total of 261 male patients with T2DM were selected and divided into three groups based on diagnostic criteria:the normal bone mass group(96 cases),the reduced bone mass group(111 cases)and the osteoporosis group(54 cases).Differences in systemic inflammation markers and bone metabolic markers were compared between the three groups.Multivariate ordered Logistic regression analysis was used to investigate factors influencing the progression from normal bone mass to osteoporosis in male patients with T2DM.Receiver operating characteristic(ROC)curves were used to evaluate the predictive value of inflammatory markers for osteoporosis in male patients with T2DM.Correlation analysis was conducted to investigate the correlation between inflammatory markers and BMD and bone turnover markers(BTM)in male patients with T2DM.Results Platelet count(PLT),platelet-to-lymphocyte ratio(PLR),systemic inflammatory index(SII)and neutrophil-to-lymphocyte ratio(NLR)were significantly higher in the osteoporosis group than those in the normal bone mass group(P＜0.05).Multivariate ordered Logistic regression analysis showed that PLR and SII were risk factors for the progression from normal bone mass to osteoporosis in male patients with T2DM(P＜0.05).The area under the ROC curve of PLR was 0.590,and the cut-off value was 96.67.The area under the curve of SII was 0.613,with a cut-off value of 307.9,and the area under the combined curve of the above two indicators was 0.612.In patients with osteoporosis and osteopenia,SII,PLR and PLT were negatively correlated with L1-4 BMD and left hip BMD(P＜0.05).SII was also negatively correlated with left femoral neck BMD(P＜0.05).Conclusion Inflammatory markers PLR and SII have predictive values for the progression from normal bone mass to bone loss and osteoporosis in male patients with T2DM.

The seventy-two grid palm technique is an important theoretical source of traditional Chinese medicine hand diagnosis. Starting from the ecological medical model， we analyse the seventy-two grid palm technique， and believe that its diagnosis of human body integrates biological， ecological， psychological， social and other factors， and each factor is based on physiological and pathological theories， and its external social interpretation of the nature of the human body is inseparable from health state. It is proposed that the seventy-two grid palm technique should be integrated with the ecological and natural viewpoints based on the biomedical models or bio-psycho-social medical models， and the research should be conducted from the perspective of the ecological medical model， in order to promote the development of hand diagnosis.

BACKGROUND: The new emerging avian influenza A H7N9 virus, causing severe human infection with a mortality rate of around 41%. This study aims to provide a novel treatment option for the prevention and control of H7N9. METHODS: H7 hemagglutinin (HA)-specific B cells were isolated from peripheral blood plasma cells of the patients previously infected by H7N9 in Jiangsu Province, China. The human monoclonal antibodies (mAbs) were generated by amplification and cloning of these HA-specific B cells. First, all human mAbs were screened for binding activity by enzyme-linked immunosorbent assay. Then, those mAbs, exhibiting potent affinity to recognize H7 HAs were further evaluated by hemagglutination-inhibiting (HAI) and microneutralization in vitro assays. Finally, the lead mAb candidate was selected and tested against the lethal challenge of the H7N9 virus using murine models. RESULTS: The mAb 6-137 was able to recognize a panel of H7 HAs with high affinity but not HA of other subtypes, including H1N1 and H3N2. The mAb 6-137 can efficiently inhibit the HA activity in the inactivated H7N9 virus and neutralize 100 tissue culture infectious dose 50 (TCID50) of H7N9 virus (influenza A/Nanjing/1/2013) in vitro, with neutralizing activity as low as 78 ng/mL. In addition, the mAb 6-137 protected the mice against the lethal challenge of H7N9 prophylactically and therapeutically. CONCLUSION The mAb 6-137 could be an effective antibody as a prophylactic or therapeutic biological treatment for the H7N9 exposure or infection.
Animals ; Antibodies, Monoclonal/therapeutic use* ; Antibodies, Neutralizing/therapeutic use* ; Antibodies, Viral ; Hemagglutinins ; Humans ; Influenza A Virus, H1N1 Subtype ; Influenza A Virus, H3N2 Subtype ; Influenza A Virus, H7N9 Subtype ; Influenza Vaccines ; Influenza in Birds ; Influenza, Human/prevention & control* ; Mice