To investigate the protective effects and underlying mechanisms of Qin-Zhu-Liang-Xue decoction (QZLX) in atopic dermatitis (AD) and glucocorticoid resistance, we conducted a single-blinded, randomized controlled clinical trial to evaluate the efficacy and safety of this concoction. Network pharmacology analysis was performed and validated through clinical studies. The efficacy, safety, and mechanism of action of QZLX and glucocorticoid receptor (GR) α recombinant protein were assessed in AD mice induced by 2,4-dinitrofluorobenzene (DNFB). Correlation analysis was performed to determine the clinical relevance of GRα. The trial demonstrated that patients who received QZLX showed considerable improvements in their Scoring Atopic Dermatitis (SCORAD) and Dermatology Life Quality Index (DLQI) scores compared with those who received mizolastine at week 4. Network pharmacological analysis identified GRα as a key target for QZLX in AD treatment. QZLX administration increased the serum GRα expression in AD patients, alleviated AD symptoms in mice, decreased inflammatory cytokine expression, and increased GRα expression without affecting liver or kidney function. In addition, GRα recombinant protein improved AD-like skin lesions in DNFB-induced mice. A negative correlation was observed between GRα expression and clinical parameters, including SCORAD, DLQI, and serum IgE levels. QZLX alleviates AD symptoms through the upregulation of GRα and thus presents a novel therapeutic strategy for the prevention of glucocorticoid resistance in AD management.
Dermatitis, Atopic/drug therapy* ; Animals ; Drugs, Chinese Herbal/administration & dosage* ; Humans ; Mice ; Network Pharmacology ; Male ; Female ; Adult ; Receptors, Glucocorticoid/metabolism* ; Disease Models, Animal ; Single-Blind Method ; Middle Aged ; Young Adult

Objective:To construct univariate and multivariate relapse free survival (RFS) prediction models for breast cancer patients with diabetes mellitus type 2 (T2DM) and to compare and select the model with higher predictive performance.Methods:A total of 912 breast cancer patients treated at the First Affiliated Hospital of Dalian Medical University from January 2010 to December 2016 were included, of which 202 patients had T2DM and 710 patients did not. Kaplan-Meier survival curve was drawn based on whether patients had T2DM, and log-rank test was performed based on whether patients had T2DM. All patients were randomly divided into a training set ( n=640) and a validation set ( n=272) at a ratio of 7∶3. Univariate and multivariate Cox proportional risk regression models were used to analyze RFS in breast cancer patients with the survival package. The "rms" package was employed to construct univariate and multivariate RFS prediction models for breast cancer patients with T2DM. Clinical decision curves and calibration curves were used to validate the models. The receiver operator characteristic (ROC) curve was used to compare and analyze the prediction performance of the two models. Results:There were no statistically significant differences between the training set and the validation set patients in terms of age, T2DM, surgical approach, axillary management methods, T stage, N stage, molecular sub-type, estrogen receptor (ER) 1, ER2, progesterone receptor (PR) , ER and PR consistency, Ki67, human epidermal growth factor receptor 2 (HER2) (all P>0.05) . There was a statistically significant difference in histological grade ( χ2=7.59, P=0.022) . Survival analysis showed that the 5-year RFS rate was 83.7% in patients with T2DM and 92.3% in patients without T2DM ( χ2=16.61, P<0.001) . Univariate analysis revealed that age ( HR=1.04, 95% CI: 1.03-1.06, P<0.001) , T2DM ( HR=2.31, 95% CI: 1.49-3.55, P<0.001) , surgical approach ( HR=2.39, 95% CI: 1.20-4.77, P=0.013) , axillary management methods ( HR=2.62, 95% CI: 1.72-3.98, P<0.001) , T stage (T 2: HR=2.13, 95% CI: 1.36-3.31, P<0.001; T 3: HR=6.90, 95% CI: 3.35-14.22, P<0.001) , N stage (N 2: HR=3.87, 95% CI: 2.12-7.07, P<0.001; N 3: HR=8.61, 95% CI: 4.71-15.75, P<0.001) , molecular sub-type (Luminal B: HR=2.74, 95% CI: 1.17-6.36, P=0.019; HER2 +: HR=3.64, 95% CI: 1.38-9.58, P=0.009; TNBC: HR=4.40, 95% CI: 1.71-11.34, P=0.002) , ER1 (>10%: HR=0.57, 95% CI: 0.37-0.90, P=0.016) , ER2 ( HR=0.57, 95% CI: 0.37-0.89, P=0.015) , and PR ( HR=0.56, 95% CI: 0.37-0.86, P=0.008) were all factors influencing RFS in breast cancer patients. Multivariate analysis demonstrated that age ( HR=1.04, 95% CI: 1.02-1.06, P<0.001) , T2DM ( HR=1.82, 95% CI: 1.16-2.85, P=0.009) , T stage (T 2: HR=1.60, 95% CI: 1.01-2.54, P=0.046; T 3: HR=2.64, 95% CI: 1.22-5.72, P=0.014) , N stage (N 2: HR=3.72, 95% CI: 2.01-6.88, P<0.001; N 3: HR=5.34, 95% CI: 2.78-10.25, P<0.001) , and ER1 (>10%: HR=0.63, 95% CI: 0.39-0.99, P=0.046) were independent factors influencing RFS in breast cancer patients. Based on the 10 and 5 variables with P<0.05 in the univariate and multivariate analyses respectively, the nomograms of the univariate and multivariate prediction models were constructed to evaluate the influence of factors such as T2DM on the postoperative RFS of breast cancer patients. Clinical decision curves and calibration curves indicated that both models had high predictive value for RFS in breast cancer patients, and the predictive results were highly consistent with the actual observed results. ROC curve analysis showed that there was no statistically significant difference in the area under the curve (AUC) of the two models for predicting the RFS rates of breast cancer patients in the training set and validation set at 36, 60, and 84 months (all P>0.05) , indicating that the predictive efficacy of the two models was comparable. The multivariate model is more suitable for clinical application because it uses fewer variables. Conclusions:Breast cancer patients with T2DM have poorer prognosis. Age, T2DM, T stage, N stage, and ER1 are independent factors influencing postoperative RFS in breast cancer patients. The multi-factor prediction model of RFS in breast cancer patients based on T2DM is more suitable for clinical application due to its higher predictive efficacy and fewer variables.

Objective:To analyze mortality risk factors in patients with severe pneumonia and investigate their varying influences across different time periods.Methods:A total of 134 patients with severe pneumonia admitted to the Emergency Department of Xiang’an Hospital, Xiamen University, between June 2019 and February 2020 were enrolled. All patients were treated in the EICU and followed up for four years. Based on outcomes, they were categorized into a death group ( n=77) and a survival group ( n=57). COX regression analysis was employed to identify mortality risk factors at different time points, while logistic regression analysis was used to assess risk factors influencing mortality during hospitalization, ICU stay, 1-month, and 1-year follow-up periods. Results:Mortality rates were 11.9% ( n=16) during ICU admission, 20.8% ( n=28) during hospitalization, 16.4% ( n=22) within 1 month, and 31.3% ( n=42) within 1 year. By the end of the follow-up, 57.4% ( n=77) of patients had died. Ten mortality risk factors were identified, with the number increasing over time. During ICU admission and hospitalization, significant risk factors included total bilirubin levels, APACHE-II score, invasive ventilation, ARDS, and vasopressor use in the ICU. One-month mortality risk additionally involved bacterial infection. One-year mortality risk further incorporated advanced age and chronic heart failure. By the end of follow-up, acute kidney injury (AKI) during ICU admission also emerged as a contributing factor, while higher body weight was identified as a protective factor. Conclusions:The number of mortality risk factors in severe pneumonia patients increases progressively over time. Early-stage factors during hospitalization and ICU admission exert a stronger impact on short-term mortality, whereas bacterial infection, advanced age, and chronic heart failure become increasingly significant in later stages. These findings highlight the dynamic nature of risk factors and underscore the importance of tailored monitoring and intervention strategies at different disease phases.

Bone formation and deposition are initiated by sensory nerve infiltration in adaptive bone remodeling. Here, we focused on the role of Semaphorin 3A (Sema3A), expressed by sensory nerves, in mechanical loads-induced bone formation and nerve withdrawal using orthodontic tooth movement (OTM) model. Firstly, bone formation was activated after the 3rd day of OTM, coinciding with a decrease in sensory nerves and an increase in pain threshold. Sema3A, rather than nerve growth factor (NGF), highly expressed in both trigeminal ganglion and the axons of periodontal ligament following the 3rd day of OTM. Moreover, in vitro mechanical loads upregulated Sema3A in neurons instead of in human periodontal ligament cells (hPDLCs) within 24 hours. Furthermore, exogenous Sema3A restored the suppressed alveolar bone formation and the osteogenic differentiation of hPDLCs induced by mechanical overload. Mechanistically, Sema3A prevented overstretching of F-actin induced by mechanical overload through ROCK2 pathway, maintaining mitochondrial dynamics as mitochondrial fusion. Therefore, Sema3A exhibits dual therapeutic effects in mechanical loads-induced bone formation, both as a pain-sensitive analgesic and a positive regulator for bone formation.
Humans ; Bone Remodeling ; Cell Differentiation ; Osteogenesis ; Semaphorin-3A/pharmacology* ; Trigeminal Ganglion/metabolism*

Bone formation and deposition are initiated by sensory nerve infiltration in adaptive bone remodeling.Here,we focused on the role of Semaphorin 3A(Sema3A),expressed by sensory nerves,in mechanical loads-induced bone formation and nerve withdrawal using orthodontic tooth movement(OTM)model.Firstly,bone formation was activated after the 3rd day of OTM,coinciding with a decrease in sensory nerves and an increase in pain threshold.Sema3A,rather than nerve growth factor(NGF),highly expressed in both trigeminal ganglion and the axons of periodontal ligament following the 3rd day of OTM.Moreover,in vitro mechanical loads upregulated Sema3A in neurons instead of in human periodontal ligament cells(hPDLCs)within 24 hours.Furthermore,exogenous Sema3A restored the suppressed alveolar bone formation and the osteogenic differentiation of hPDLCs induced by mechanical overload.Mechanistically,Sema3A prevented overstretching of F-actin induced by mechanical overload through ROCK2 pathway,maintaining mitochondrial dynamics as mitochondrial fusion.Therefore,Sema3A exhibits dual therapeutic effects in mechanical loads-induced bone formation,both as a pain-sensitive analgesic and a positive regulator for bone formation.

Bone formation and deposition are initiated by sensory nerve infiltration in adaptive bone remodeling.Here,we focused on the role of Semaphorin 3A(Sema3A),expressed by sensory nerves,in mechanical loads-induced bone formation and nerve withdrawal using orthodontic tooth movement(OTM)model.Firstly,bone formation was activated after the 3rd day of OTM,coinciding with a decrease in sensory nerves and an increase in pain threshold.Sema3A,rather than nerve growth factor(NGF),highly expressed in both trigeminal ganglion and the axons of periodontal ligament following the 3rd day of OTM.Moreover,in vitro mechanical loads upregulated Sema3A in neurons instead of in human periodontal ligament cells(hPDLCs)within 24 hours.Furthermore,exogenous Sema3A restored the suppressed alveolar bone formation and the osteogenic differentiation of hPDLCs induced by mechanical overload.Mechanistically,Sema3A prevented overstretching of F-actin induced by mechanical overload through ROCK2 pathway,maintaining mitochondrial dynamics as mitochondrial fusion.Therefore,Sema3A exhibits dual therapeutic effects in mechanical loads-induced bone formation,both as a pain-sensitive analgesic and a positive regulator for bone formation.

Bone formation and deposition are initiated by sensory nerve infiltration in adaptive bone remodeling.Here,we focused on the role of Semaphorin 3A(Sema3A),expressed by sensory nerves,in mechanical loads-induced bone formation and nerve withdrawal using orthodontic tooth movement(OTM)model.Firstly,bone formation was activated after the 3rd day of OTM,coinciding with a decrease in sensory nerves and an increase in pain threshold.Sema3A,rather than nerve growth factor(NGF),highly expressed in both trigeminal ganglion and the axons of periodontal ligament following the 3rd day of OTM.Moreover,in vitro mechanical loads upregulated Sema3A in neurons instead of in human periodontal ligament cells(hPDLCs)within 24 hours.Furthermore,exogenous Sema3A restored the suppressed alveolar bone formation and the osteogenic differentiation of hPDLCs induced by mechanical overload.Mechanistically,Sema3A prevented overstretching of F-actin induced by mechanical overload through ROCK2 pathway,maintaining mitochondrial dynamics as mitochondrial fusion.Therefore,Sema3A exhibits dual therapeutic effects in mechanical loads-induced bone formation,both as a pain-sensitive analgesic and a positive regulator for bone formation.

Bone formation and deposition are initiated by sensory nerve infiltration in adaptive bone remodeling.Here,we focused on the role of Semaphorin 3A(Sema3A),expressed by sensory nerves,in mechanical loads-induced bone formation and nerve withdrawal using orthodontic tooth movement(OTM)model.Firstly,bone formation was activated after the 3rd day of OTM,coinciding with a decrease in sensory nerves and an increase in pain threshold.Sema3A,rather than nerve growth factor(NGF),highly expressed in both trigeminal ganglion and the axons of periodontal ligament following the 3rd day of OTM.Moreover,in vitro mechanical loads upregulated Sema3A in neurons instead of in human periodontal ligament cells(hPDLCs)within 24 hours.Furthermore,exogenous Sema3A restored the suppressed alveolar bone formation and the osteogenic differentiation of hPDLCs induced by mechanical overload.Mechanistically,Sema3A prevented overstretching of F-actin induced by mechanical overload through ROCK2 pathway,maintaining mitochondrial dynamics as mitochondrial fusion.Therefore,Sema3A exhibits dual therapeutic effects in mechanical loads-induced bone formation,both as a pain-sensitive analgesic and a positive regulator for bone formation.

Objective To evaluate the quality of treatment planning(TP)and re-optimization planning(RP)of radiotherapy for rectal cancer using PlanIQ software,thereby providing methods and tools for the screening and optimization of radiotherapy plans.Methods Twenty patients with rectal cancer who received radiotherapy were selected retrospectively,with 10 cases of intensity-modulated radiotherapy(IMRT)and 10 of volumetric modulated arc therapy(VMAT).(1)TP:IMRT plan involved 5-field irradiation,and VMAT plan involved two 360°arcs.The prescription doses were 50 Gy/25 f for PTV1 and 45 Gy/25 f for PTV2.All plans underwent direct machine parameter optimization and required 95%isodose lines to cover 100%of the target volume.Organs-at-risk(OAR)were limited by reference to tolerated dose standards.After the planning was completed,the plans were reviewed and confirmed by a physician,and the treatment was implemented after dose verification.(2)RP:a physicist with 10 years of experience re-optimized the 20 TP plans,with the irradiation technique and field setting unchanged.The re-optimization involved adjusting planning conditions and parameters based on individual experience until the dose to OAR was minimized while without affecting PTV coverage.The quality of TP plans and RP plans were quantitatively evaluated using PlanIQ software.Non-parametric Wilcoxon signed rank test was performed for dose-volume histogram parameters and plan quality index between two groups.Results The dose-volume histogram parameters in RP plans were superior to those in TP plans,and the differences in the Dmax of PTV1,the V45 Gy and Dmax of small intestine,and the V45 Gy of colon were statistically significant(P<0.05).The quality scores of RP plans for IMRT group,VMAT group and all patients were significantly higher than those of TP plans(P<0.05),with plan quality index of 88.55±3.35 vs 86.61±4.63(P=0.005),89.72±3.15 vs 87.21±3.04(P=0.028),and 89.14±3.22 vs 86.91±3.22(P=0.001),respectively.Conclusion RP can further improve the quality of radiotherapy plan for rectal cancer.PlanIQ software serves as an effective tool for quality control and screening of radiotherapy planning.

Objective To assess inter-observer variations(IOV)in the delineation of target volumes and organs-at-risk(OAR)for intensity-modulated radiotherapy(IMRT)of nasopharyngeal carcinoma(NPC)among physicians from different levels of cancer centers,thereby providing a reference for quality control in multi-center clinical trials.Methods Twelve patients with NPC of different TMN stages were randomly selected.Three physicians from the same municipal cancer center manually delineated the target volume(GTVnx)and OAR for each patient.The manually modified and confirmed target volume(GTVnx)and OAR delineation structures by radiotherapy experts from the regional cancer center were used as the standard delineation.The absolute volume difference ratio(△V_diff),maximum/minimum volume ratio(MMR),coefficient of variation(CV),and Dice similarity coefficient(DSC)were used to compare the differences in organ delineation among physicians from different levels of cancer centers and among the 3 physicians from the same municipal cancer center.Furthermore,the IOV of GTVnx and OAR among physicians from different levels cancer centers were compared across different TMN stages.Results Significant differences in the delineation of GTVnx were observed among physicians from different levels of cancer centers.Among the 3 physicians,the maximum values of △V_diff,MMR,and CV were 97.23%±83.45%,2.19±0.75,and 0.31±0.14,respectively,with an average DSC of less than 0.7.Additionally,there were considerable differences in the delineation of small-volume OAR such as the left and right optic nerves,chiasm,and pituitary,with average MMR>2.8,CV>0.37,and DSC<0.51.However,relatively smaller differences were observed in the delineation of large-volume OAR such as the brainstem,spinal cord,left and right eyeballs,and left and right mandible,with average△V_diff<42%,MMR<1.55,and DSC>0.7.Compared with the differences among physicians from different levels cancer centers,the differences among the 3 physicians from the municipal cancer center were slightly reduced.Furthermore,there were also differences in the delineation of target volumes for NPC among physicians from different levels cancer centers,depending on the staging of the disease.Compared with the delineation of target volumes for earlier stage patients(stages I or II),the differences among physicians in the delineation of target volumes for advanced stage patients(stages III or IV)were smaller,with average △V_diff and DSC of 98.31%±67.36%vs 69.38%±72.61%(P<0.05)and 0.55±0.08 vs 0.72±0.12(P<0.05),respectively.Conclusion There are differences in the delineation of GTVnx and OAR in radiation therapy for NPC among physicians from different levels of cancer centers,especially in the delineation of target volume(GTVnx)and small-volume OAR for early-stage patients.To ensure the accuracy of multicenter clinical trials,it is recommended to provide unified training to physicians from different levels of cancer centers and review their delineation results to reduce the effect of differences on treatment outcomes.