ObjectiveTo dynamically observe and evaluate the damage to the pulmonary air-blood barrier in mice during the inflammatory cancer transformation process of ulcerative colitis （UC） based on the "lung-intestine correlation" theory. MethodsSixty-five C57BL/6 mice were divided into a normal group （n=25） and a model group （n=40） using a random number table. Azoxymethane/dextran sodium sulfate （DSS） method was used to establish a mouse model of UC inflammation cancer transformation in the modeling group. According to the tissue collection time points at 5， 8， 11， 13， and 15 weeks， the normal group mice were randomly divided into the normal 5w， 8w， 11w， 13w， and 15w groups. The model group mice， 10 mice of which died after the first cycle of DSS administration， were randomly divided into model 5w， 8w， 11w， 13w， and 15w groups. During the experiment， the general condition of the mice was observed daily， and their body weight was measured weekly. At the corresponding tissue collection time points， the colon length of each group was measured. Histopathology of mouse lung and colon tissues was examined using HE staining. Immunofluorescence was used to detect changes in the positive expression of tight junction protein （ZO-1）， vascular endothelial cadherin （VE-cadherin）， and cytoskeletal protein （F-actin） in lung and colon tissues. RT-PCR was used to detect the mRNA expression of apoptosis regulatory proteins B-cell lymphoma-2 （Bcl-2）， BCL2-associated X protein （Bax）， and Cysteine aspartic acid protease-3 （Caspase-3） in lung tissues. Western Blot was employed to measure protein levels of ZO-1， VE-cadherin， and F-actin in lung tissues. ResultsCompared to the normal group at the same time point， the mice in the model group at each time point generally had poorer conditions， with weight loss and shortened colon length （P＜0.05 or P＜0.01）. In the model 5w group， there was significant inflammatory cell infiltration in the colon tissue； in the model 8w group， there was mild atypical hyperplasia； in the model 11w group， the crypt structure was disordered， and moderate to severe atypical hyperplasia occurred； in the model 13w and 15w groups， tumors appeared. Pulmonary interstitial lesions， inflammation， vasculitis， and fibrosis were observed at all stages of UC inflammation cancer transformation. The protein levels of ZO-1， VE-cadherin， and F-actin， as well as Bcl-2 mRNA expression in lung tissue decreased during the acute inflammatory recovery period， atypical hyperplasia period， and canceration period， while the expressions of Bax and Caspase-3 mRNA increased； the expressions of ZO-1， VE-cadherin， and F-actin proteins in colon tissue decreased during the acute inflammatory recovery period， atypical hyperplasia period， and canceration period （P＜0.01 or P＜0.05）. Compared to the model 5w group， the ZO-1 and F-actin protein levels and Bcl-2 mRNA expression in lung tissue in the other model groups increased in the atypical hyperplasia period and canceration period， while the expressions of Bax and Caspase-3 mRNA decreased； the expression of ZO-1 protein in colon tissue increased in the canceration period， and the expression of VE-cadherin protein decreased in the atypical hyperplasia period （P＜0.01 or P＜0.05）. ConclusionIn the process of "inflammatory response-atypical hyperplasia-carcinogenesis" in UC inflammatory cancer transformation mice， there were damage to air-blood barrier.

OBJECTIVE To establish population pharmacokinetic model of levetiracetam （Lev） for Chinese patients with post- stroke epilepsy （PSE）， and provide reference for formulating individualized dosing regimens for Lev therapy in this specific population. METHODS Blood concentration data and clinical diagnosis and treatment information of PSE patients meeting the inclusion criteria were retrospectively collected and divided into model group and validation group at an 8∶2 ratio using a random number method. Based on the model group data， a population pharmacokinetic model was developed using nonlinear mixed-effects modeling. Internal evaluation was performed through goodness-of-fit tests and bootstrap analysis， while external validation was conducted using the validation group data. RESULTS A total of 75 blood concentration measurements from 70 PSE patients were collected， with 60 measurements from 55 patients used for model development and 15 measurements from 15 patients reserved for external validation. The final model estimated a population typical value of clearance at 2.98 L/h. Estimated glomerular filtration rate， daily dose， and homocysteine level significantly influenced clearance of Lev （P＜0.01）. The model demonstrated satisfactory predictive performance， as evidenced by goodness-of-fit tests， bootstrap analysis， and external validation results. CONCLUSIONS Daily dose， estimated glomerular filtration rate， and homocysteine level are identified as significant covariates influencing Lev clearance in Chinese PSE patients. When making clinical decisions， comprehensive consideration should be given to the patient’s treatment response， physiological and pathological conditions， and the occurrence of adverse reactions， etc. The dosage of Lev should be adjusted based on the results of population pharmacokinetic model.

ObjectiveTo determine the optimal combination of the effective monomer components "quercetin-kaempferol-abietic acid-boswellic acid" in Fujin Shengjisan for promoting diabetic ulcer （DU） wound healing through uniform design， thereby achieving the modern application of the ancient formula. MethodsFollowing the principle of "uniform design-pharmacodynamic experiment-mathematical modeling and model verification"， the U₁₄（14⁵） uniform design table was adopted.The four monomer components of Chinese medicine were considered as the independent variables， and the proliferation rate of human umbilical vein endothelial cells （HUVECs） induced by glucose was used as the pharmacodynamic indicator. A mathematical model was constructed using DPS software to correlate the effective monomer components with the pharmacodynamic indicator. The results of uniform design were verified through CCK-8 assay， cell scratch healing， tube formation， Western blot， and Real-time PCR. ResultsAmong the 14 compatibility groups， compared with the high-glucose model group， compound compatibility group 6 showed the strongest proliferation effect and statistical significance （P<0.05）. Four quadratic polynomial regression equations （Y₁-Y₄） were obtained through DPS modeling. Considering the model's fit， stability， and practical application， equations Y₁-Y₃ were selected for the follow-up verification. To ensure experiment reproducibility， group 6 was used for validation. Group 6 and equations Y₁-Y₃ were renamed as compound prescription ① to compound prescription④， respectively， to represent the modern application of the ancient FJSJ Powder through compatibility of monomer components. Verification experiments showed that in the CCK-8， scratch healing， and tube formation assays， the cell viability， wound healing rate， and tube formation number of HUVECs stimulated with 50 mmol·L^-1 glucose were significantly reduced compared with the blank group. Moreover， the expression levels of angiogenesis-related cytokines， vascular endothelial growth factor （VEGF） and fibroblast growth factor 2 （FGF2）， and CD31 secretion were significantly down-regulated. However， after intervention with compound prescriptions ① to ④， compound prescriptions ① and ③ significantly improved the biological functions of HUVECs induced by 50 mmol·L^-1 glucose. Further analysis of the regression coefficients of compound prescriptions ① and ③， and the relative dose ratios of each monomer component， indicated that abietic acid， quercetin， and boswellic acid promoted angiogenesis of HUVECs in the high glucose environment， with a major effect （positive partial correlation coefficients， all > 0.9）. Abietic acid and boswellic acid， as well as kaempferol and boswellic acid， promoted angiogenesis in HUVECs through interaction （positive partial correlation coefficients）. ConclusionCompound prescriptions ① and ③ are the optimal combinations. They can reverse the inhibitory effects of high glucose， stimulate the proliferation， migration， and tube formation abilities of HUVECs in a high glucose environment， and promote the expression of vascular endothelial growth factorA（VEGFA）， FGF2， and CD31， thereby promoting angiogenesis and facilitating DU wound healing. This finding not only confirms the good reproducibility and feasibility of compound prescriptions ① and ③ but also provides new insights and methods for the rational construction of mathematical models to further study the compatibility theory of Chinese medicine.

OBJECTIVE: To explore the application value of infrared thermography in the design and harvesting of ultrathin anterolateral thigh perforator flaps. METHODS: Between June 2024 and December 2024, 9 cases of ultrathin anterolateral thigh perforator flaps were designed and harvested with the assistance of infrared thermography. There were 7 males and 2 females, aged 21-61 years (mean, 39.8 years). The body mass index ranged from 19.49 to 26.45 kg/m² (mean, 23.85 kg/m²). Causes of injury included 5 cases of traffic accident injuries and 4 cases of machine crush injuries. There were 3 cases of leg wounds, 2 cases of foot wounds, and 4 cases of hand wounds. After debridement, the size of wound ranged from 7 cm×4 cm to 13 cm×11 cm. The time from admission to flap repair surgery was 5-12 days (mean, 7 days). Preoperatively, perforator localization was performed using a traditional Doppler flow detector and infrared thermography, respectively. The results were compared with the actual intraoperative locations; a discrepancy ≤10 mm was considered as consistent localization (positive), and the positive predictive value was calculated. All 9 cases were repaired with ultrathin anterolateral thigh perforator flaps designed and harvested based on thermographic images. The size of flap ranged from 8 cm×5 cm to 14 cm×8 cm, with a thickness of 3-6 mm (mean, 5.2 mm). One donor site was repaired with a full-thickness skin graft, and the others were sutured directly. Postoperatively, anti-inflammatory, anticoagulant, and anti-vascular spasm treatments were administered, and follow-up was conducted. RESULTS: The Doppler flow detector identified 22 perforating vessels within the set range, among which 16 were confirmed as superficial fascia layer perforators intraoperatively, with a positive predictive value of 72.7%. The infrared thermograph detected 23 superficial fascia layer perforating vessels, and 21 were verified intraoperatively, with a positive predictive value of 91.3%. There was no significant difference between the two methods [OR (95%CI)=3.93 (0.70, 22.15), P=0.100]. The perforator localization time of the infrared thermograph was (5.1±1.3) minutes, which was significantly shorter than that of the Doppler flow detector [(10.1±2.6) minutes; MD (95%CI)=-5.00 (-7.08, -2.91), P<0.001]. Postoperatively, 1 case of distal flap necrosis healed after dressing change; all other flaps survived successfully. The skin grafts at donor site survived, and all incisions healed by first intention. All patients were followed up 3-6 months (mean, 4.7 months). No pain or other discomfort occurred at the donor or recipient sites. All patients with foot wounds could walk with shoes, and no secondary flap revision was required. Flaps in 3 hand wound cases, 2 foot wound cases, and 3 leg wound cases recovered light touch and pressure sensation, but not pain or temperature sensation; the remaining 2 cases had no sensory recovery. CONCLUSION Preoperative localization using infrared thermography for repairing ultrathin anterolateral thigh perforator flaps can help evaluate the blood supply status of perforators, reduce complications, and improve surgical safety and flap survival rate.
Humans ; Perforator Flap/blood supply* ; Adult ; Male ; Thermography/methods* ; Female ; Thigh/blood supply* ; Middle Aged ; Plastic Surgery Procedures/methods* ; Tissue and Organ Harvesting/methods* ; Infrared Rays ; Skin Transplantation/methods* ; Soft Tissue Injuries/surgery* ; Young Adult

Sonodynamic therapy (SDT) can potentially induce immunogenic cell death in tumor cells, leading to the release of ATP, and facilitating the initiation of an immune response. Nevertheless, the enzymes CD39 and CD73 can swiftly convert ATP into immunosuppressive adenosine (ADO), resulting in an immunosuppressive tumor microenvironment (TME). This study introduced a nanomedicine (QD/POM1@NP@M) engineered to reprogram TME by modulating the CD39/CD73/ADO pathway. The nanomedicine encapsulated sonosensitizers silver sulfide quantum dots, and the CD39 inhibitor POM1, while also incorporating homologous tumor cell membranes to enhance targeting capabilities. This integrated approach, on the one hand, stimulates the release of ATP via SDT, thereby initiating the immune response. In addition, it reduced the accumulation of ADO by inhibiting CD39 activity, which ameliorated the immunosuppressive TME. Upon administration, the nanomedicine demonstrated substantial anti-tumor efficacy by facilitating the infiltration of anti-tumor immune cells, while reducing the immunosuppressive cells. This modulation effectively transformed the TME from an immunologically "cold" state to a "hot" state. Furthermore, combined with the checkpoint inhibitor α-PDL1, the nanomedicine augmented systemic anti-tumor immunity and promoted the establishment of long-term immune memory. This study provides an innovative strategy for combining non-invasive SDT and ATP-driven immunotherapy, offering new ideas for future cancer treatment.

[This corrects the article DOI: 10.1016/j.apsb.2018.08.009.].

Extensive epigenetic reprogramming involves in memory CD8+ T-cell differentiation. The elaborate epigenetic rewiring underlying the heterogeneous functional states of CD8+ T cells remains hidden. Here, we profile single-cell chromatin accessibility and map enhancer-promoter interactomes to characterize the differentiation trajectory of memory CD8+ T cells. We reveal that under distinct epigenetic regulations, the early activated CD8+ T cells divergently originated for short-lived effector and memory precursor effector cells. We also uncover a defined epigenetic rewiring leading to the conversion from effector memory to central memory cells during memory formation. Additionally, we illustrate chromatin regulatory mechanisms underlying long-lasting versus transient transcription regulation during memory differentiation. Finally, we confirm the essential roles of Sox4 and Nrf2 in developing memory precursor effector and effector memory cells, respectively, and validate cell state-specific enhancers in regulating Il7r using CRISPR-Cas9. Our data pave the way for understanding the mechanism underlying epigenetic memory formation in CD8+ T-cell differentiation.
CD8-Positive T-Lymphocytes/metabolism* ; Cell Differentiation ; Chromatin/immunology* ; Animals ; Mice ; Immunologic Memory ; Epigenesis, Genetic ; SOXC Transcription Factors/immunology* ; NF-E2-Related Factor 2/immunology* ; Mice, Inbred C57BL ; Gene Regulatory Networks ; Enhancer Elements, Genetic

Objective Based on the assumption of spatial heterogeneity,the distribution pattern and risk characteristics of health poverty in middle-aged and elderly people with chronic diseases are described from the perspective of spatial differentiation.In order to providing a theoretical basis for the optimization of subsequent poverty reduction policies and a model policy for other countries.Methods It used factor detector and interaction detector to capture the role of single-factor and multi-factor interactions on the spatial differentiation of health poverty,and risk detectors were utilized to explore the high-risk factors in risky areas Results The single factor explanation of medical assistance and health education activities is prominent,and the factors such as PM2.5,old-age dependency ratio and urban unemployment rate have strong interaction.Furthermore,it identified high-risk factor characteristics in areas at high risk of health poverty.Conclusion The spatial differentiation pattern of health poverty among the middle-aged and elderly chronic disease population in China is the result of the synergistic driving effect of multidimensional factors,and there is variability in the risk characteristics among regions.The government should establish a contextual optimization strategy and pay attention to the joint effect of multiple factors to establish a synergistic management system.

Objective:To investigate the influence of prealbumin on cerebral infarction severity, hemorrhage transformation and 1-year prognosis.Methods:A retrospective study was conducted to select 752 patients with cerebral infarction who were treated in Beijing Tiantan Hospital,Capital Medical University from December 2018 to December 2019 as the study objects. Personal information and laboratory indicators of the patients were collected including prealbumin, hemoglobin, white blood cell count, etc.Patients were divided into group B1 (<238 mg/L) and group B2 (≥238 mg/L) based on median prealbumin. By inquiry patient's case, NIHSS score (<16 was classified as mild, ≥16 as moderate and severe)and cerebral infarction volume (<20 cm 3 as small infarct, >20 cm 3 as large infarct) were recorded to evaluate the severity of the disease, and whether hemorrhage transformation occurred during hospitalization was recorded. Patients were followed up 1 year after discharge, and prognostic information of patients was recorded, including neurological function recovery (mRS score <3 was classified as good recovery, ≥3 as poor recovery),all-cause case fatality rate, and recurrence of cardio-cerebrovascular events. Normally distributed measurement data were expressed as xˉ±s, non-normally distributed measurement data were expressed as median and quartiles[ M( Q1, Q3)], categorical variable were expressed as ratio and percent(%). Comparison between groups of measurement data were performed by independent sample t test and Mann-Whitney U test. Chi-square test were used on comparison between groups of categorical variable. Single-factor comparison, Spearman correlation analysis and multiple Logistic regression were used to analyze the correlation between prealbumin and other laboratory indicators, cerebral infarction severity, hemorrhage transformation and 1-year prognosis, respectively. Results:The NIHSS score and infarct volume of patients in group B1 were 5(2,10) and 3.18(0.72,18.00) cm 3, and those in group B2 were 3(2,7) and 2.0(0.5,10.0) cm 3, respectively, which were higher in group B1 than in group B2, the differences were statistically significant ( Z=3.85, P<0.001, Z=2.81, P=0.005). The proportion of mRS Score ≥3 in group B1 was 28.8%(107/371), and the all-cause case fatality rate was 7.5%(28/371), both higher than 20.5%(78/381) and 3.1%(12/381) in group B2, with statistical significance ( χ2=7.10, P=0.008, χ2=7.22, P=0.007). Hemorrhage transformation and recurrence of cardio-cerebrovascular events were 13.5%(50/371) and 11.6%(43/371) in group B1 and 9.2% (35/381) and 8.7%(33/381) in group B2, respectively, with no significant difference between the two groups ( χ2=3.45, P=0.063, χ2=1.78, P=0.183). Multivariate logistic regression analysis showed that, after adjusted for potential confounding factors, prealbumin was protective factor of NIHSS ( OR and 95% CI: 0.990(0.984-0.997), P=0.035), poor neurological recovery(mRS≥3) ( OR and 95% CI:0.992(0.988-0.997), P<0.001) and all-cause case fatality rate ( OR and 95% CI:0.991(0.983-0.999), while prealbumin had no significant influence on cardiocerebrovascular recurrence events ( OR and 95% CI: 0.999(0.993-1.005), P=0.729). Conclusion:Prealbumin is significantly associated with the severity of cerebral infarction and poor prognosis 1 year after discharge, and low prealbumin was an independent risk factor for NIHSS score(≥16), poor neurological recovery (mRS≥3) and all-cause case fatality rate.

Objectives:To explore the effects of infarct volume, infarct type, inflammation, and coagulation indicators on hemorrhagic transformation in patients with acute cerebral infarction.Methods:711 patients with cerebral infarction admitted to Beijing Tiantan Hospital were retrospectively included as the study objects from December 2018 to December 2019 [535 males and 176 females, age 22-95 years, mean age (59.6±12.1) years]. Clinical data, laboratory indicators such as inflammation and coagulation function of patients were collected, and information such as location, volume and type of infarction were recorded. The patients were divided into hemorrhage transformation group and non-hemorrhage transformation group according to whether hemorrhage transformation occurred during hospitalization. Normally distributed measurement data were expressed as xˉ± s, non-normally distributed measurement data were expressed as median and quartiles [ M( Q1, Q3)], categorical variable were expressed as ratio and percent (%). Comparison between groups of measurement data were performed by independent sample t test and Mann-Whitney U test. χ2 test were used on comparison between groups of categorical variable. Univariate comparison and multivariate Logistic regression were used to analyze the correlation between hemorrhage transformation and infarct volume, infarction type and laboratory indicators, respectively, to explore the risk factors of hemorrhage transformation. ROC curve analysis was used to evaluate the diagnostic value of indicators. Results:The rates of coronary heart disease and atrial fibrillation history in the hemorrhage transformation group were 23.5% (20/85) and 22.4% (19/85), respectively, which were significantly higher than those in the non-hemorrhage transformation group (13.9% (87/626) and 5.8% (36/626), respectively), and the difference between the two groups was statistically significant ( χ2=5.43, χ2=28.90, P=0.020, P<0.001, respectively). The NIHSS score [10(4,17) points] and infarct volume [46.50 (14.21,118.42) mL] in the hemorrhage transformation group were significantly higher than those in the non-hemorrhage transformation group [4(2,7) points, 2.00(0.51,8.94) mL]. The difference between the two groups was statistically significant ( Z values were 6.69 and 10.69, respectively, P<0.001). The results of multivariate Logistic regression analysis showed that atrial fibrillation (OR=2.604, 95% CI: 1.186-5.716, P=0.107), infarct volume (OR=1.009, 95% CI: 1.004-1.015, P=0.001), infarct type of Chinese ischemic stroke subclassfication (OR=1.371, 95% CI: 1.085-1.731, P=0.008) and neutrophil/lymphocyte ratio (OR=1.047, 95% CI: 1.006-1.090, P=0.023) were independent risk factors for hemorrhage transformation. ROC curve analysis showed that the area under curve (AUC) of infarct volume and neutrophil/lymphocyte ratio were 0.861 (0.821-0.901) and 0.684 (0.626-0.741), respectively, which were effective in predicting hemorrhage transformation after cerebral infarction. The prediction of infarct volume was more efficient. Conclusion:History of atrial fibrillation, classification of cardioembolic stroke, infarct volume, and neutrophil/lymphocyte ratio are all risk factors for hemorrhagic transformation after acute cerebral infarction.