Objective To understand and grasp the status quo of resistance of Culex pipiens pallens to four commonly used insecticides in Hefei City, and to provide a scientific basis for the chemical control of mosquito larvae. Methods From June to July 2023, Cx. pipiens pallens larvae were collected from 9 counties (cities and districts) in Hefei City. The LC50 of late third-instar to early fourth-instar larvae of Cx. pipiens pallens to commonly used insecticides was determined by larval immersion method (sensitive baseline method). Results Cx.pipiens pallens larvae in Hefei City exhibited different degrees of resistance to four insecticides: permethrin, beta-cypermethrin, temephos, and propoxur. The relative resistance coefficients to permethrin and beta-cypermethrin were 26.96 and 21.17, respectively, indicating the moderate resistance level. The relative resistance coefficients to propoxur were 6.70, indicating a low resistance level. The relative resistance coefficient to temephos was 2.43, indicating a sensitivity level. Culex pipiens pallens against pyrethroids such as 0.25% permethrin, 0.025% deltamethrin and 0.025% cypermethrin in 1 h knockout rate and 24 h mortality rates were 3.25% (4/123) and 46.34% (57/123), 3.60% (5/139) and 35.97% (50/139), 3.85% (6/156) and 40.38% (63/156), respectively. For 5% malathion and 0.1% propoxur, the 1 h knockdown rate and 24 h mortality rate were 97.69% (127/130) and 99.23% (129/130), 94.48% (137/145) and 100.00% (145/145), respectively. It showed resistance to 0.25% permethrin, 0.025% deltamethrin and 0.025% cypermethrin, and sensitivity to 5% malathion and 0.1% propoxur. Conclusions Culex pipiens pallens in Hefei City have developed varying degrees of resistance to parathyroid and carbamate insecticides. In the control of mosquito vectors, it is essential to strengthen the scientific and rational use of chemical control in combination with environmental and physical control measures to form an integrated control strategy. This approach will improve the control efficiency while delaying the occurrence and development of insecticide resistance.

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:To evaluate long-term outcomes of endoscopic papillectomy (EP) for duodenal papillary adenomas and to identify risk factors for incomplete resection.Methods:Clinical data of 180 patients diagnosed as having duodenal papillary adenoma via postoperative pathology after EP in Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School from January 2010 to December 2022 were retrospectively analyzed. Patients were divided into two groups based on their postoperative margin status: the complete resection group (negative resection margins) and the incomplete resection group (positive/uncertain resection margins). Recurrence rates were compared between the two groups, and logistic regression analysis was performed to identify risk factors for incomplete resection.Results:Among the 180 patients included in the study, 137 underwent complete resection, and 43 had incomplete resections. Recurrence rate was significantly higher in the incomplete resection group than that in the complete resection group (30.2% VS 15.3%, χ2=4.75, P=0.029). logistic regression analysis indicated that high-grade intraepithelial neoplasia was an independent risk factor for incomplete resection ( OR=2.43, 95% CI:1.12-5.26, P=0.024). Conclusion:Patients with incomplete resection after EP have a higher recurrence rate in the long-term follow-up. High-grade intraepithelial neoplasia is an independent risk factor for incomplete resection. Close surveillance and aggressive management are warranted for patients with positive or uncertain resection margins to mitigate the recurrence risk.

Objective To analyze the imaging features of cerebral small vessel disease in patients with type 2 diabetes mellitus by multimodal MRI.Methods The clinical data of 160 patients with cerebral small vessel disease admitted to our hospital from January to December 2020 were retrospectively analyzed.According to whether they were complicated with type 2 diabetes mellitus,they were divided into the diabetic group and the non-diabetic group,with 80 cases in each group.Both groups underwent multimodal MRI scans.And the severity of lacunar infarction,the severity of subcortical and periventricular white matter lesions,white matter integral and cerebral microbleeds of patients in the two groups were compared.Results The severity of lacunar infarction(χ2=34.076,P=0.001),subcortical white matter lesions(χ2=25.000,P=0.001),periventricular white matter lesions(χ2=22.895,P=0.001)and white matter integral(t=12.370,P=0.001)of patients in the diabetic group were significantly higher than those in the non-diabetic group.No cerebral microbleeds were detected in either group of patients.Conclusion Patients with cerebral small vessel disease and type 2 diabetes mellitus show characteristic multimodal MRI changes.The increase in the number of lacunar infarction lesions and the aggravation of white matter lesions can be used as the characteristic imaging basis for the diagnosis of type 2 diabetes mellitus related cerebral small vessel disease.

Objective To develop a risk prediction model for ischemic stroke in symptomatic intracranial atherosclerotic stenosis(ICAS)patients based on high-resolution magnetic resonance imaging(HR-MRI)and arterial spin labeling(ASL)imaging.Methods A total of 142 patients were included and divided into acute ischemic stroke(AIS)and transient ischemic attack(TIA)groups based on stroke occurrence.Clinical risk factors,plaque characteristics,and arterial transit artifact(ATA)presence on ASL images were compared between the two groups.Multivariate logistic regression analysis was performed,incorporating clinical risk factors,plaque characteristics,and double post labeling delay(PLD)ATA presence.The predictive value of different models was compared using receiver operating characteristic(ROC)curve and DeLong tests.Results Hypertension,positive lumen remodeling,plaque enhance-ment rate,1.5 s-ATA presence,and 2.5 s-ATA presence were independent risk factors for AIS(P＜0.05).The combination of HR-MRI and ASL imaging predicted AIS most effectively[area under the curve(AUC)=0.908;95％ confidence interval(CI)0.862-0.954].No significant difference was found between the prediction performances of HR-MRI and ASL(95％CI-0.041-0.082,Z=0.659,P=0.509).Conclusion ASL is more convenient than HR-MRI for predicting ischemic stroke in ICAS patients.A model combining plaque characteristics and ATA presence effectively predicts AIS occurrence.

Objective To explore the risk factors for noncontiguous spinal fractures(NSFs)in the elderly.Methods The clinical data of 614 elderly patients with spinal fracture from January 2013 to December 2019 were analyzed retrospectively.Patients were divided into the NSFs group and the Non-NSFs group according to whether NSFs occurred or not.Univariate analysis and multivariate Logistic regression analysis were used to screen the risk factors of NSFs.Results Univariate analysis showed that female(P=0.003),high-energy violent injury(P=0.032),osteoporosis(P=0.004),fracture in spring(P=0.020),and previous spinal fracture history(P<0.001)were associated with the occurrence of NSFs.Multivariate Logistic regression analysis showed that fracture in spring(P=0.024),previous spinal fracture history(P<0.001)and high-energy violent injury(P=0.038)were the independent risk factors for the occurrence of NSFs in the elderly.Conclusion High-energy violent injury,fracture in spring and previous spinal fracture history are the independent risk factors for the occurrence of NSFs in the elderly.Therefore,elderly patients with the above risk factors should be examined more carefully and comprehensively to avoid missed diagnosis and delayed diagnosis.In order to reduce the incidence of this disease,corresponding measures should be taken according to the preventable risk factors.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Objective To analyze the imaging features of cerebral small vessel disease in patients with type 2 diabetes mellitus by multimodal MRI.Methods The clinical data of 160 patients with cerebral small vessel disease admitted to our hospital from January to December 2020 were retrospectively analyzed.According to whether they were complicated with type 2 diabetes mellitus,they were divided into the diabetic group and the non-diabetic group,with 80 cases in each group.Both groups underwent multimodal MRI scans.And the severity of lacunar infarction,the severity of subcortical and periventricular white matter lesions,white matter integral and cerebral microbleeds of patients in the two groups were compared.Results The severity of lacunar infarction(χ2=34.076,P=0.001),subcortical white matter lesions(χ2=25.000,P=0.001),periventricular white matter lesions(χ2=22.895,P=0.001)and white matter integral(t=12.370,P=0.001)of patients in the diabetic group were significantly higher than those in the non-diabetic group.No cerebral microbleeds were detected in either group of patients.Conclusion Patients with cerebral small vessel disease and type 2 diabetes mellitus show characteristic multimodal MRI changes.The increase in the number of lacunar infarction lesions and the aggravation of white matter lesions can be used as the characteristic imaging basis for the diagnosis of type 2 diabetes mellitus related cerebral small vessel disease.

Objective To develop a risk prediction model for ischemic stroke in symptomatic intracranial atherosclerotic stenosis(ICAS)patients based on high-resolution magnetic resonance imaging(HR-MRI)and arterial spin labeling(ASL)imaging.Methods A total of 142 patients were included and divided into acute ischemic stroke(AIS)and transient ischemic attack(TIA)groups based on stroke occurrence.Clinical risk factors,plaque characteristics,and arterial transit artifact(ATA)presence on ASL images were compared between the two groups.Multivariate logistic regression analysis was performed,incorporating clinical risk factors,plaque characteristics,and double post labeling delay(PLD)ATA presence.The predictive value of different models was compared using receiver operating characteristic(ROC)curve and DeLong tests.Results Hypertension,positive lumen remodeling,plaque enhance-ment rate,1.5 s-ATA presence,and 2.5 s-ATA presence were independent risk factors for AIS(P＜0.05).The combination of HR-MRI and ASL imaging predicted AIS most effectively[area under the curve(AUC)=0.908;95％ confidence interval(CI)0.862-0.954].No significant difference was found between the prediction performances of HR-MRI and ASL(95％CI-0.041-0.082,Z=0.659,P=0.509).Conclusion ASL is more convenient than HR-MRI for predicting ischemic stroke in ICAS patients.A model combining plaque characteristics and ATA presence effectively predicts AIS occurrence.