Age-related macular degeneration(ARMD)is a progressive visual impairment fundus disease that frequently occurs in individuals aged >55 years. The main risk factors are aging, long-term smoking, genetics, and racial differences. Pathogenesis includes abnormal function of the retinal pigment epithelium, damaged blood-retinal barrier, and abnormal immune function. Currently, intravitreal injection(IVI)of anti-vascular endothelial growth factor(VEGF)drugs is the preferred treatment option for ARMD in clinical practice. However, it also faces challenges such as repeated treatments, high medical costs, and poor patient compliance. The predicament in the treatment of ARMD has given rise to several new treatment options. This article aims to review the treatment methods and progress of dry ARMD and wet ARMD, providing new ideas for addressing the limitations of the current clinical anti-VEGF treatment.

Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.

OBJECTIVE To confirm trigger items for adverse drug reaction （ADR） induced by bevacizumab， to identify and analyze the occurrence of related ADR， and to establish a predictive model for severe adverse reaction （SAR） caused by this drug. METHODS Based on the global trigger tool （GTT） theory， and referencing the GTT White Paper， drug package inserts and relevant literature， trigger items for bevacizumab-related ADR were confirmed using a single-round Delphi method. Utilizing these established items， electronic medical records of relevant patients at Guilin People’s Hospital from January 2020 to September 2024 were actively screened via the China Hospital Pharmacovigilance System. Pharmacists then identified and tallied the occurrence of bevacizumab-induced ADR. Data from patients with any positive trigger item served as the study subjects （divided into training and test sets at a ratio of 7∶3）， candidate feature variables were selected from 39 related variables using the Boruta algorithm， and the multivariable Logistic regression analysis was performed with the occurrence of SAR as the dependent variable. Based on these candidate features， Logistic Regression， Extreme Gradient Boosting， Light Gradient Boosting Machine， Random Forest， and Categorical Boosting models were constructed. Model performance was evaluated using metrics including the area under the curve （AUC） of receiver operating characteristic curve and recall rate. The Shapley Additive exPlanations （SHAP） method was applied to analyze and interpret the contribution of each variable. A nomogram was constructed based on the optimal model. RESULTS A total of 38 trigger items for active monitoring of bevacizumab-related ADR were determined， comprising 17 laboratory indicators， 13 clinical manifestations， and 8 intervention measures. In total， 483 patients with positive trigger items were included， and 318 patients with bevacizumab-induced ADR were identified， including 83 SARs. The positive predictive values for the trigger items and cases were 43.57% （708/1 625） and 63.84% （318/483）， respectively. Bevacizumab-induced ADR involved 7 systems/organs， with the hematological system being the most frequently involved （64.15%）. The Boruta algorithm selected 7 vari ables： serum potassium， hematocrit， albumin-to-globulin ratio， prealbumin， hypertension history， age and red blood cell count. Multivariable Logistic regression showed that elevated serum potassium levels were associated with a decreased risk of bevacizumab-induced SAR （OR＝0.234， P ＝0.002）， while a history of hypertension （OR＝2.642， P ＝0.006） and increased age （OR＝1.040， P ＝0.025） were associated with an increased risk. The Logistic Regression model demonstrated superior performance with higher AUC， F1 score and recall rate （0.761， 0.447， 0.607）， compared to other models. SHAP evaluation results indicated that variables such as serum potassium， hematocrit， and age ranked highest in importance. CONCLUSIONS Totally 38 trigger entries have been successfully identified for active screening of bevacizumab-related ADR. Elevated serum potassium levels are a protective factor against bevacizumab-induced SAR， whereas the hypertension history and increased age are risk factors. The Logistic Regression model is the optimal predictive model.

Purpose: The aim of this study is to determine the impact of solute carrier family 3 member 2 (SLC3A2) on the malignant phenotype of gliomas and its role in regulating ferroptosis sensitivity. Materials and Methods: The malignant phenotype of glioma was assessed by cell proliferation assay, colony formation assay, EdU assay, wound healing, and Transwell experiments. We further validated the impact of reduced SLC3A2 expression on the sensitivity to ferroptosis in glioma cells through Cell Counting Kit-8 assays, flow cytometry, western blotting, and transmission electron microscopy. Western blot was used to explore how SLC3A2 affects glioma sensitivity to ferroptosis through the AKT/NF-E2-related factor 2 (NRF2)/glutathione peroxidase 4 (GPX4) axis. By establishing a subcutaneous xenograft tumor model in BALB/c-nude mice, we investigated the growth of tumors following the knockout of SLC3A2 in glioma cells. Results: Downregulation of SLC3A2 suppressed the malignant phenotype of glioma by blocking the cell cycle and epithelial-mesenchymal transition processes. On the other hand, loss of SLC3A2 not only downregulated SLC7A11 but also prevented the activation of the AKT/NRF2/GPX4 axis. These lead to increased accumulation of reactive oxygen species and lipid peroxides, ultimately enhancing the susceptibility of glioma to ferroptosis. Conclusion Our findings suggest that SLC3A2 is an oncogene in gliomas, promoting their occurrence and development. It plays a critical role in ferroptosis resistance through the AKT/NRF2/GPX4 axis.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

ObjectiveTo investigate the novel post-translational modifications (PTMs) of SnRK2.6, a central component in the abscisic acid (ABA) signaling pathway, such as SUMOylation, and to establish a foundation for revealing the physiological functions and molecular mechanisms of SnRK2.6 regulated by these new modifications. MethodsThe interaction between SnRK2.6 and the SUMO E3 ligase SIZ1, as well as members of the SUMO protease family, was examined using yeast two-hybrid and in vitro pull-down assays. An in vitro SUMOylation system in Escherichia coli was utilized to determine whether SnRK2.6 undergoes SUMOylation. Mass spectrometry, combined with site-directed mutagenesis of candidate lysine residues, was employed to identify potential SUMOylation sites on SnRK2.6. In vitro de-SUMOylation assays were performed to assess whether SUMO proteases interacting with SnRK2.6 could catalyze the removal of SUMO moieties from modified SnRK2.6. The protein stability of SnRK2.6 was assessed in a cell-free degradation assay using bacterial-purified SnRK2.6 incubated with total protein extracts from Col and siz1 mutant seedlings. To dissect the genetic relationship between SnRK2.6 and SIZ1, stomatal aperture assays were performed under ABA treatment using snrk2.6, siz1, and snrk2.6 siz1 double mutant plants. ResultsSnRK2.6 physically interacts with SIZ1 and the SUMO protease ESD4, with the binding domains localized to the C-terminal region of SIZ1 and the N-terminal region of ESD4, respectively. SnRK2.6 was found to be SUMOylated, exhibiting two distinct high-molecular-mass bands ranging from 70 to 100 ku, indicative of modified forms. Bioinformatics analysis predicted four putative SUMOylation sites on lysine residues K57, K63, K142, and K190. Mass spectrometry identified three SUMOylation sites on K63, K142, and K174. However, individual or combinatorial point mutations on these sites had minimal impact on the pattern or intensity of SUMOylation signals, suggesting that these residues may not be responsible for the SUMOylation on SnRK2.6. Instead, such mutations only weaken the protein stability or accelerate the protein mobility of SnRK2.6. Therefore, the exact SUMOylation sites on SnRK2.6 remain unidentified. In de-SUMOylation experiments, incubation of GST-ESD4 with SUMOylated SnRK2.6 for 1-2 h led to the near-complete disappearance of both SUMOylated bands. In contrast, neither the GST control nor the catalytically inactive mutant GST-ESD4^C448S exhibited any de-SUMOylation activity. In protein turnover experiments, SnRK2.6 exhibited markedly enhanced half-life in siz1 compared with Col, indicating that SIZ1-dependent SUMOylation promotes SnRK2.6 turnover. Phenotypically, snrk2.6 mutants were completely insensitive to ABA-induced stomatal closure; siz1 mutants displayed pronounced hypersensitivity; and the snrk2.6 siz1 double mutant phenocopied snrk2.6—showing no significant response to ABA beyond that of the snrk2.6 mutant. These data indicate that SIZ1 acts as a negative regulator of ABA-triggered stomatal closure and SnRK2.6 functions as a positive regulator, and the inhibitory activity of SIZ1 is strictly dependent on SnRK2.6, placing SnRK2.6 genetically upstream of SIZ1 in the ABA signaling pathway. ConclusionSnRK2.6 undergoes SUMOylation, although the specific SUMOylation sites have not been defined. SnRK2.6 is dynamically regulated by reversible SUMOylation—catalyzed by SIZ1 and reversed by ESD4—which controls its protein stability. SUMOylation acts as a destabilizing signal for SnRK2.6, and SIZ1 exerts its negative effect on ABA-triggered stomatal closure probably through promoting SnRK2.6 degradation via SUMOylation. These findings uncover SUMOylation as a critical regulatory layer fine-tuning SnRK2.6 abundance in ABA signaling.

Objective:To investigate the predictive efficacy of Delta radiomics for the patholo-gical complete remission (pCR) of pancreatic cancer after total neoadjuvant therapy (TNT).Methods:The retrospective cohort study was conducted. The clinicopathological data of 263 patients with pancreatic cancer who were admitted to Henan Provincial People′s Hospital (Zhengzhou University People's Hspital) from January 2019 to September 2024 were collected. There were 166 males and 97 females, aged (56±12)years. All patients underwent TNT. The 263 patients were randomly divided into a training set of 184 cases and a test set of 79 cases using a 7∶3 random seed count. The training set was used to construct the prediction model, and the test set was used to validate the performance of the prediction model. Observation indicators: (1) postoperative and follow-up condi-tions; (2) imaging feature selection and model construction; (3) evaluation of predictive efficacy of different radiomic models. Comparison of measurement data with normal distribution between groups was conducted using the t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. The Kaplan-Meier method was used to calculate the survival rate and draw survival curve. The Log-rank test was used for survival analysis. The perfor-mance of the prediction model for pCR after TNT was evaluated using the receiver operator charac-teristic (ROC) curve, precision-recall (P-R) curve and Bootstrap method, along with the calculation of area under the curve (AUC), precision rate, recall rate, F1-score. Results:(1) Postoperative and follow-up conditions. All 263 patients underwent surgery after TNT, with pathological examination revealing 124 cases of pCR (86 cases in the training set, 38 cases in the test set) and 139 cases of non-pCR (98 cases in the training set, 41 cases in the test set), respectively. All 263 patients were followed up for 6(range, 3-12) months after surgery, of which 15 cases (4 cases of pCR and 11 cases of non-pCR) were lost to follow-up or died due to non-tumor reasons within 6 months after surgery. The postoperative 6-month recurrence-free survival rate of 124 pCR patients and 139 non-pCR patients were 80% and 50%, respectively, showing a significant difference between the two groups of patients ( χ2=22.84, P<0.05). (2) Imaging feature selection and model construction. Construction of the traditional radiology model: based on the response evaluation criteria in solid tumors 1.1, the Logistic regression model was constructed using the relative shrinkage (D%) as a predictive variable. The AUC of traditional radiology model was 0.72 [95% confidence interval ( CI) as 0.63?0.81] in the training set and 0.75 (95% CI as 0.66?0.84) in the test set, respectively. Construction of the Delta radiomics model: 10 non-zero coefficient features were selected. The Delta radiomics models were constructed by using the regularized Logistic regression, random forest, gradient boosting machine, and support vector machine algorithms through using selected features as input variables. (3) Evaluation of predictive efficacy of different radiomic models. The AUC of Delta radiomics model constructed by regularized Logistic regression algorithm in the test set for predicting pCR in pancreatic cancer after TNT was 0.90, higher than that of the random forest algorithm, gradient boosting machine algorithm, support vector machine algorithm (AUC as 0.81, 0.81, 0.83), and higher than that of the traditional radiology model (AUC as 0.72). Results of Bootstrap method revealed significant differences in the predictive efficacy of Delta radiomics model constructed by regularized Logistic regression algorithm compared to the Delta radiomics model constructed by random forest algorithm, gradient boosting machine algorithm, support vector machine algorithm and the tradi-tional radiology model (95% CI as 0.03?0.16, 0.03?0.16, 0.03?0.13, 0.08?0.29, P<0.05). The regularized Logistic regression algorithm within the Delta radiomics model demonstrated the best overall performance among the above models evaluated. Conclusion:Compared to the traditional radiology model, the Delta radiomics model offers superior efficacy in predicting pCR of pancreatic cancer after TNT, in which the regularized Logistic regression algorithm demonstrates the best overall performance metrics.

X-ray is usually used to determine anatomy and localization during conventional permanent pacemaker implantation.But X-ray exposure might induce radiation injury to fetus.In this paper,we reported 2 cases successful double cavity permanent pacemaker implantation in pregnant women woman at 13 weeks of gestation under the guidance of transthoracic echocardiography.The postoperative pacing parameters were good,the whole process was finished with zero radiation,and there were complications during pregnancy.Both cases resulted in full-term pregnancies and the natural delivery of healthy newborns.Pacemaker electrodes were in normal position as confirmed by post-delivery X-ray examinations.

Objective To evaluate the efficacy of the manual cyclotorsion compensation method based on the obser-vation screen in the correction of with-the-rule astigmatism during small incision lenticule extraction(SMILE).Methods This prospective study enrolled 40 patients who underwent SMILE and another 40 patients who underwent Q-value-guided femtosecond laser-assisted laser in situ keratomileusis(FS-LASIK)at the Ophthalmology Center of the Second Affiliated Hospital of Nanchang University from April to September 2024.Through the random number method,one eye of each pa-tient who underwent SMILE was assigned to the manual cyclotorsion compensation group(the cyclotorsion group,40 eyes),while the contralateral eye was assigned to the non-cyclotorsion group(the non-cyclotorsion group,40 eyes).Meanwhile,one eye of each patient who underwent FS-LASIK was randomly selected for the FS-LASIK group(40 eyes).The age,uncorrected distance visual acuity(UDVA),spherical power,cylindrical power,spherical equivalent(SE),and corrected distance visual acuity(CDVA)were recorded before surgery and 3 months after surgery,respectively.Astigma-tism was subjected to Alpins vector analysis,and the indicators for assessing astigmatism included target-induced astigma-tism(TIA),surgically-induced astigmatism(SIA),difference vector(DV),correction index(CI),success index(IOS),angle of error(AE),and absolute value of angle of error(|AE|).Results Before surgery,there was no significant difference in age,spherical power,cylindrical power,SE,and CDVA among the cyclotorsion group,the non-cyclotorsion group,and the FS-LASIK group(all P＞0.05).At 3 months after surgery,the cyclotorsion group showed better UDVA and lower cylindrical power than the non-cyclotorsion group,with statistically significant differences(both P＜0.05);howev-er,there was no significant difference in CDVA,spherical power,and SE between the two groups(all P＞0.05).Besides,there was no significant difference in UDVA,CDVA,or refractive parameters between the cyclotorsion and FS-LASIK groups(all P＞0.05).The Alpins vector analysis of astigmatism 3 months after surgery revealed better SIA,CI,IOS,and|AE|in the cyclotorsion group compared with the non-cyclotorsion group,with statistically significant differences(all P＜0.05);however,there was no significant difference in TIA,DV,and AE between the two groups(all P＞0.05).No signifi-cant differences were found between the cyclotorsion and FS-LASIK groups in any astigmatism vector parameter(all P＞0.05).The linear regression analysis results indicated a high linear correlation between TIA and SIA in all groups.Conclu-sion The manual cyclotorsion compensation method based on the observation screen in the correction of with-the-rule astigmatism during SMILE is comparable to Q-value-guided FS-LASIK and superior to the conventional central tear film marking method in SMILE.