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*

Giant extralobar pulmonary sequestration in newborns is still relatively rare in pulmonary diseases, and there are few relevant studies published. A neonate with the giant extralobar pulmonary sequestration accompanied by severe pleural effusion was reported here. After 12 days of birth, the diseased lung tissue was surgically extracted. The patient had an uneventful postoperative recovery and was discharged from the hospital. The case shows the advantage of early surgical treatment to extralobar pulmonary sequestration with severe pleural effusion in neonatal period.

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.

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.

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.