Background Meteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the impact of ambient temperature and atmospheric pressure on CVD, especially on pre-hospital CVD emergent events, has become imperative for evidence-based prevention and emergency preparedness. Objective To quantify the temporal trends of daily mean temperature and atmospheric pressure and their associations with pre-hospital CVD emergent events in Yantai, and to explore effect modification by demographic subgroups and geographic areas, thereby providing an empirical basis for the rational allocation of emergency medical resources. Methods Pre-hospital CVD emergency data from January 1, 2016 to December 31, 2022 were selected from the Yantai 120 Emergency Medical Command System. Synchronous meteorological factors and environmental pollutant data were obtained from the websites of the National Oceanic and Atmospheric Administration and the National Centers for Environmental Information of the United States. Time-series analysis combined with distributed lag non-linear model was used to analyze the association between daily temperature, atmospheric pressure, and pre-hospital CVD emergencies. Average annual percentage changes (AAPC) were calculated using Joinpoint (version 5.2.0.0) to reflect temporal trends. Spearman correlation analysis was employed to screen variables with low collinearity for inclusion in the multi-pollutant adjusted models. Results From 2016 to 2022, a total of 268275 pre-hospital CVD emergency cases were recorded in Yantai City, showing an increasing annual trend (AAPC=7.16%, P=0.002). Emergency volume, daily temperature, atmospheric pressure, and PM₁₀ displayed marked seasonal patterns, with summer bottoms and winter peaks for emergencies, daily temperature higher in summer and lower in winter, and the inverse for atmospheric pressure. Correlation analysis showed that both daily temperature and atmospheric pressure were positively correlated with O₃, with correlation coefficients of 0.745 and 0.723, respectively; negatively correlated with PM_2.5, with correlation coefficients of −0.246 and −0.235, respectively; and negatively correlated with PM₁₀, with correlation coefficients of −0.241 and −0.229, respectively (P < 0.05). A U-shaped correlation was revealed between daily temperature and pre-hospital CVD emergency risk. Using 24 °C as the reference, risk was elevated at both low and high daily temperatures, with the strongest cold effect at –11 ℃ (RR=1.53, 95%CI: 1.35, 1.73) and strongest heat effect at 30 ℃ (RR=1.06, 95%CI: 1.01, 1.11); cold effects were prolonged (lag0–14d) compared to heat effects. Atmospheric pressure exhibited a positive association with emergencies; using a median of 1012.2 hPa as the reference, the maximum risk occurred at 1037 hPa (RR=1.25, 95%CI: 1.03, 1.52), with a 0–5 d lag. In the subgroup analysis, the impact of low temperature was more pronounced among females (RR_{−9 ℃}=1.66), people over 60 years (RR_{−9 ℃}=1.91), and rural residents (RR_{−9 ℃}=1.76). High atmospheric pressure significantly increased the risk of pre-hospital CVD emergency among females (RR_{1035 hPa}=1.54), people under 18 years (RR_{1035 hPa}=3.62), and rural residents (RR_{1035 hPa}=1.46). The sensitivity analysis results indicated that, after excluding the impact of pandemic and the degrees of freedom for time variations, the effects of daily average temperature and atmospheric pressure on pre-hospital CVD emergency volume were consistent with the primary analysis findings. Conclusion Both non-optimal temperature and atmospheric pressure significantly increase the pre-hospital CVD emergency volume; therefore, emergency medical services should develop targeted response protocols, optimize resource allocation, and intensify public health education to mitigate the pre-hospital burden attributable to temperature and pressure fluctuations.

Objective:To apply statistical process control (SPC) techniques to the quality assurance of non-normal radiotherapy plans through Johnson transformation, establishing patient-specific tolerance and action limits based on treatment sites and dose/distance assessment criteria, thereby enhancing the intensity-modulated radiation therapy (IMRT) verification accuracy and dose delivery precision.Methods:In this study, 951 gamma analysis data of patient-specific quality assurance (PSQA) executed on the Halcyon accelerator platform were selected and categorized into six groups based on treatment sites, including brain (102 cases), head and neck (100 cases), breast (229 cases), lung (154 cases), esophagus (223 cases), and pelvic (143 cases) groups. The six groups of data were statistically analyzed through Anderson-Darling normality tests ( α = 0.05) using Minitab 21 software. Non-normal data were transformed into normal data through Johnson transformation and then were used to establish treatment site-specific tolerance and action limits, which were compared with the Shewhart control charts based on normal distributions. Results:The PSQA result of the six groups all exhibited non-normal distributions ( P < 0.05). Through Johnson transformation, the tolerance and action limits for the head and neck, breast, lung, esophagus, and pelvic areas under the 3%/2 mm criterion ranged from 95.13% to 96.16% and 94.19% to 95.91%, respectively. In contrast, the tolerance and action limits ranged from 91.15% to 94.86% and 89.94% to 94.78% under the 2%/2 mm criterion. Directly applying Shewhart control charts without normality assumptions yielded higher tolerance limits compared to the application of Johnson transformation, increasing the false positive rate in the non-normal PSQA process. Conclusions:Applying the SPC techniques directly to a non-normal process can lead to an increased false alarm rate and wrong process interpretation. The SPC techniques combined with Johnson transformation enable more effective monitoring of a non-normal PSQA process, facilitating timely identification of potential factors that may lead to an out-of-control process based on the treatment site-specific limits.

Objective To observe the effects of Yitangkang on brown fat thermogenesis and mitochondrial biogenesis of PGC1α-NRF1/2-TFAM pathway in db/db mice;To explore its mechanism of regulating glucose and lipid metabolism.Methods Totally 27 six-week-old db/db mice were randomly divided into model group,Yitangkang group(30 g/kg)and liraglutide group(200 μg/kg),another 9 db/m mice of the same age were set as normal group.All groups received intervention with drugs or saline for 6 weeks.The body mass and FBG were measured weekly.After intervention,oral glucose tolerance test(OGTT)was carried out,the contents of serum TC,TG,LDL-C and HDL-C were detected by biochemical analyzer,HE staining was used to observe the morphology of brown adipose tissue(BAT)in scapular region,RT-qPCR and Western blot were used to detect the expressions of UCP1,PRDM16,PGC1α related to BAT thermogenesis and NRF1,Nrf2,TFAM related to mitochondrial biogenesis.Results Compared with the normal group,the body mass,FBG,area under the curve of OGTT and serum TG,TC,LDL-C content of model group significantly increased(P<0.01),the content of HDL-C significantly decreased(P<0.01);the diameter of BAT cells in scapular region was larger,white vacuoles appeared,lipid droplets increased,and the mRNA and protein expressions of UCP1,PRDM16,PGC-1α,NRF1,NRF2 and TFAM in BAT decreased significantly(P<0.01).Compared with the model group,the body mass,FBG,area under the curve of OGTT and serum TG,TC,LDL-C contents of Yitangkang group and liraglutide group significantly decreased(P<0.01),the content of HDL-C increased(P<0.01);BAT cells were smaller in diameter,more closely arranged,more regular in shape,and more abundant in capillary,the mRNA and protein expressions of UCP1,PRDM16,PGC-1α,NRF1,NRF2 and TFAM in BAT increased significantly(P<0.01).Conclusion Yitangkang can regulate mitochondrial biogenesis through PGC1α-NRF1/2-TFAM pathway to activate brown fat in db/db mice and improve glucose and lipid metabolism in db/db mice.

Objective:To investigate the clinical characteristics and independent risk factors of severe disease in patients with anti-nuclear matrix protein (NXP) 2 antibody-positive juvenile dermatomyositis (JDM).Methods:A retrospective cohort study was conducted, including 219 anti-NXP2 antibody-positive JDM patients admitted to 23 children′s hospitals across China from July 2011 to July 2023. Patients were classified into severe and non-severe groups based on classification criteria for severe dermatomyositis. Demographic characteristics, clinical manifestations, and laboratory parameters were compared between the 2 groups using independent sample t-test, Mann-Whitney U test, or χ2 test. Univariate and multivariate Logistic regression analyses were performed to identify risk factors for severe disease. The receiver operating characteristic curve was employed to calculate optimal cut-off values. Results:Among the 219 patients, 108 were male and 111 were female, with an age at onset of 6.3 (3.5, 9.4) years. The severe group comprised 69 patients, and the non-severe group 150 patients. The severe group had significantly higher rates of fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, as well as elevated levels of ferritin-to-albumin ratio (FAR), creatine kinase (CK), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH) (all P<0.05). Multivariate analysis identified anti-Ro52 antibody positivity ( OR=13.26, 95% CI 1.37-128.29) and elevated FAR ( OR=1.90, 95% CI 1.09-2.31) as independent risk factors for severe anti-NXP2 antibody-positive JDM (both P<0.05). Receiver operating characteristic curve analysis revealed that a FAR cutoff value of 6.82 predicted severe disease with an area under the curve of 0.87 (95% CI 0.81-0.94, P<0.001), sensitivity of 0.85, and specificity of 0.70. All patients received glucocorticoid therapy, and the severe group received higher proportions of steroid pulse therapy, cyclophosphamide, mycophenolate mofetil, intravenous immunoglobulin, biologics, and adjuvant treatments compared to the non-severe group (all P<0.05). In terms of outcomes, 2 patients (2.9%) in the severe group died (due to neurological involvement and intestinal perforation, respectively), while the remaining patients achieved complete clinical response or remission. All patients in the non-severe group achieved remission. Conclusions:The primary clinical features of anti-NXP2 antibody-positive JDM included fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, and elevated levels of CK, AST, LDH, and FAR. Furthermore, anti-Ro52 antibody positivity and a FAR>6.82 were identified as independent risk factors.

Objective:To evaluate the effectiveness of nursing interventions based on Maslow's hierarchy of needs combined with cognitive behavioral intervention in patients undergoing cataract surgery.Methods:A convenience sampling method was used to select 107 cataract surgery patients admitted to the Department of Ophthalmology of Shangqiu First People's Hospital from January 2022 to June 2023. Among them, 49 patients admitted from January to September 2022 formed the control group and received routine nursing care, while 58 patients admitted from October 2022 to June 2023 formed the intervention group and received psychological nursing based on Maslow's hierarchy of needs combined with cognitive behavioral intervention. The intervention lasted for two weeks. Before and after the intervention, the patients' anxiety (using the State-Anxiety Inventory of the State-Trait Anxiety Inventory, S-AI), and illness perception (using the Chinese version of Brief Illness Perception Questionnaire, BIPQ) were evaluated.Results:After the intervention, the intervention group showed significantly lower scores on the S-AI and Chinese version of BIPQ, compared to the control group ( P<0.05) . Conclusions:Psychological nursing based on Maslow's hierarchy of needs combined with cognitive behavioral intervention can effectively reduce anxiety and illness perception in patients undergoing cataract surgery.

Objective:To understand the changes in the experience of dietary behavior compliance management in middle-aged and young adults with newly diagnosed type 2 diabetes (T2DM) and provide strategies for healthcare professionals to manage patients' long-term dietary compliance.Methods:A longitudinal qualitative study design was used. Purposeful sampling was conducted to select 16 middle-aged and young adult patients diagnosed with T2DM at the Department of Endocrinology, the Affiliated Huaian No. 1 Hospital of Nanjing Medical University, from January to May 2024. Semi-structured interviews were conducted, and data was analyzed cross-sectionally and longitudinally.Results:A total of 3 main themes and nine sub-themes were identified: emotional changes in dietary compliance (negative emotional experiences, positive emotional coping, and emotional fluctuations transformation) ; management experience of dietary compliance (gradual adaptation to dietary management, disruption of daily eating routine, and lack of family decision-making support) ; diverse support needs for dietary compliance (needs for knowledge and information support, peer and decision-making support, and continuity of care management system) .Conclusions:The experience of dietary behavior compliance management in middle-aged and young adults with T2DM is a continuous, dynamic, and fluctuating process. Healthcare professionals can develop targeted interventions based on patients' real situations and management experiences to improve their compliance levels.

Objective To propose and validate a decomposition method based on half-projection reconstruction for dual-energy cone beam CT(DE CBCT),thereby providing a potentially feasible low-dose imaging solution for anatomical monitoring and dose reconstruction optimization in adaptive radiotherapy.Methods Dual-energy scans were performed on a Gammex phantom using the on-board kilovoltage CBCT system of a VitalBeam accelerator at acquisition frame rates of 15 and 7 frames per second(f/s).Images were reconstructed from the projection data,and dual-energy decomposition was applied to the 7 f/s dual-energy images to derive relative electron density(RED)and stopping power ratio(SPR)using weighted formulas and empirical functions,followed by accuracy evaluation.Additionally,the weighted CT dose index was calculated for different scanning parameters.Results Dual-energy decomposition effectively suppressed image artifacts,with RED and SPR errors remaining below 2.82%and 2.56%,respectively.Compared with the traditional dual-scan method which required high-and low-energy acquisitions,the weighted CT dose index of the half-projection DE CBCT was reduced by 11.60 mGy(a 52.90%reduction).Furthermore,it was 2.58 mGy lower than the dose of the full-projection high-energy CBCT alone(a 19.98%reduction)and only 1.31 mGy higher than that of the low-energy CBCT(a 14.52%increase).Conclusion The proposed method effectively suppresses image artifacts while maintaining high accuracy in RED and SPR under low radiation dose conditions,demonstrating its potential value for scenarios requiring frequent image guidance,such as adaptive radiotherapy.

Objective:To investigate the clinical characteristics and independent risk factors of severe disease in patients with anti-nuclear matrix protein (NXP) 2 antibody-positive juvenile dermatomyositis (JDM).Methods:A retrospective cohort study was conducted, including 219 anti-NXP2 antibody-positive JDM patients admitted to 23 children′s hospitals across China from July 2011 to July 2023. Patients were classified into severe and non-severe groups based on classification criteria for severe dermatomyositis. Demographic characteristics, clinical manifestations, and laboratory parameters were compared between the 2 groups using independent sample t-test, Mann-Whitney U test, or χ2 test. Univariate and multivariate Logistic regression analyses were performed to identify risk factors for severe disease. The receiver operating characteristic curve was employed to calculate optimal cut-off values. Results:Among the 219 patients, 108 were male and 111 were female, with an age at onset of 6.3 (3.5, 9.4) years. The severe group comprised 69 patients, and the non-severe group 150 patients. The severe group had significantly higher rates of fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, as well as elevated levels of ferritin-to-albumin ratio (FAR), creatine kinase (CK), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH) (all P<0.05). Multivariate analysis identified anti-Ro52 antibody positivity ( OR=13.26, 95% CI 1.37-128.29) and elevated FAR ( OR=1.90, 95% CI 1.09-2.31) as independent risk factors for severe anti-NXP2 antibody-positive JDM (both P<0.05). Receiver operating characteristic curve analysis revealed that a FAR cutoff value of 6.82 predicted severe disease with an area under the curve of 0.87 (95% CI 0.81-0.94, P<0.001), sensitivity of 0.85, and specificity of 0.70. All patients received glucocorticoid therapy, and the severe group received higher proportions of steroid pulse therapy, cyclophosphamide, mycophenolate mofetil, intravenous immunoglobulin, biologics, and adjuvant treatments compared to the non-severe group (all P<0.05). In terms of outcomes, 2 patients (2.9%) in the severe group died (due to neurological involvement and intestinal perforation, respectively), while the remaining patients achieved complete clinical response or remission. All patients in the non-severe group achieved remission. Conclusions:The primary clinical features of anti-NXP2 antibody-positive JDM included fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, and elevated levels of CK, AST, LDH, and FAR. Furthermore, anti-Ro52 antibody positivity and a FAR>6.82 were identified as independent risk factors.

Objective:To apply statistical process control (SPC) techniques to the quality assurance of non-normal radiotherapy plans through Johnson transformation, establishing patient-specific tolerance and action limits based on treatment sites and dose/distance assessment criteria, thereby enhancing the intensity-modulated radiation therapy (IMRT) verification accuracy and dose delivery precision.Methods:In this study, 951 gamma analysis data of patient-specific quality assurance (PSQA) executed on the Halcyon accelerator platform were selected and categorized into six groups based on treatment sites, including brain (102 cases), head and neck (100 cases), breast (229 cases), lung (154 cases), esophagus (223 cases), and pelvic (143 cases) groups. The six groups of data were statistically analyzed through Anderson-Darling normality tests ( α = 0.05) using Minitab 21 software. Non-normal data were transformed into normal data through Johnson transformation and then were used to establish treatment site-specific tolerance and action limits, which were compared with the Shewhart control charts based on normal distributions. Results:The PSQA result of the six groups all exhibited non-normal distributions ( P < 0.05). Through Johnson transformation, the tolerance and action limits for the head and neck, breast, lung, esophagus, and pelvic areas under the 3%/2 mm criterion ranged from 95.13% to 96.16% and 94.19% to 95.91%, respectively. In contrast, the tolerance and action limits ranged from 91.15% to 94.86% and 89.94% to 94.78% under the 2%/2 mm criterion. Directly applying Shewhart control charts without normality assumptions yielded higher tolerance limits compared to the application of Johnson transformation, increasing the false positive rate in the non-normal PSQA process. Conclusions:Applying the SPC techniques directly to a non-normal process can lead to an increased false alarm rate and wrong process interpretation. The SPC techniques combined with Johnson transformation enable more effective monitoring of a non-normal PSQA process, facilitating timely identification of potential factors that may lead to an out-of-control process based on the treatment site-specific limits.

Objective To explore the factors affecting the prognosis of patients with symptomatic severe intracranial artery stenosis after interventional therapy,and to construct a nomogram prediction model accordingly.Methods The clinical data of 121 patients with symptomatic severe intracranial artery stenosis,who received interventional treatment at the First People's Hospital of Zhengzhou from June 1,2021 to October 31,2024,were retrospectively analyzed.The general data,characteristics of vascular lesions,treatment-related factors and prognosis of patients were collected.According to the modified Rankin scale(mRS)score,the patients were divided into good prognosis group(mRS score ≤2 points)and poor prognosis group(mRS score＞2 points).The clinical data were compared between the two groups.Multivariate logistic regression analysis was used to identify and determine independent factors affecting patient's outcomes,to construct a nomogram prediction model and to validate this model.Results Among the 121 patients,31(25.61％)had poor prognosis and 90(74.38％)had good prognosis.The postoperative 3-month mRS score was lower than preoperative mRS score value(P＞0.05).There were significant differences in hypertension history,stenosis site,stenosis degree,collateral circulation state,interventional therapeutic mode,cholesterol level,platelet count,lesion length and preoperative NIHSS score(P＜0.05)between the poor prognosis group and the good prognosis group.Multivariate analysis showed that hypertension history,stenosis degree,collateral circulation status,cholesterol level,platelet count,lesion's length and preoperative NIHSS score were the independent influencing factors for the prognosis of patients with symptomatic severe intracranial artery stenosis.The predicted AUC of the nomogram model was 0.931(95％ CI=0.873-0.989),and the calibration curve showed that the predicted value was in good agreement with the actual value.Conclusion Hypertension history,stenosis degree,collateral circulation status,cholesterol level,platelet count,lesion length and preoperative NIHSS score are the important influencing factors for the prognosis of patients with symptomatic severe intracranial artery stenosis.The nomogram prediction model constructed in this study shows a high accuracy in predicting the prognosis of patients,and it can provide important reference for clinical decision-making.