Evaluating the Efficacy of CortexID Quantitative Analysis in Localization of the Epileptogenic Zone in Patients with Temporal Lobe Epilepsy.

INTRODUCTION: There remains a critical need for precise localization of the epileptogenic foci in individuals with drug-resistant epilepsy (DRE). 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) imaging can reveal hypometabolic regions during the interval between seizures in patients with epilepsy. However, visual-based qualitative analysis is time-consuming and strongly influenced by physician experience. CortexID Suite is a quantitative analysis software that helps to evaluate PET imaging of the human brain. Therefore, we aimed to evaluate the efficacy of CortexID quantitative analysis in the localization of the epileptogenic zone in patients with temporal lobe epilepsy (TLE). METHODS: A total of 102 patients with epilepsy who underwent 18F-FDG-PET examinations were included in this retrospective study. The PET visual analysis was interpreted by two nuclear medicine physicians, and the quantitative analysis was performed automatically using CortexID analysis software. The assumed epileptogenic zone was evaluated comprehensively by two skilled neurologists in the preoperative assessment of epilepsy. The accuracy of epileptogenic zone localization in PET visual analysis was compared with that in CortexID quantitative analysis. RESULTS: The diagnostic threshold for the difference in the metabolic Z-score between the right and left sides of medial temporal lobe epilepsy (MTLE) was calculated as 0.87, and that for lateral temporal lobe epilepsy (LTLE) was 2.175. In patients with MTLE, the area under the curve (AUC) was 0.922 for PET visual analysis, 0.853 for CortexID quantitative analysis, and 0.971 for the combined diagnosis. In patients with LTLE, the AUC was 0.842 for PET visual analysis, 0.831 for CortexID quantitative analysis, and 0.897 for the combined diagnosis. These results indicate that the diagnostic efficacy of CortexID quantitative analysis is not inferior to PET visual analysis (p > 0.05), while combined analysis significantly increases diagnostic efficacy (p < 0.05). Among the 23 patients who underwent surgery, the sensitivity and specificity of PET visual analysis for localization were 95.4% and 66.7%, and the sensitivity and specificity of CortexID quantitative analysis were 100% and 50%. CONCLUSION: The diagnostic efficacy of CortexID quantitative analysis is comparable to PET visual analysis in the localization of the epileptogenic zone in patients with TLE. CortexID quantitative analysis combined with visual analysis can further improve the accuracy of epileptogenic zone localization.

Coping Tendency as a Mediator in the Relationship Between Psychological Resilience and Health Problems Among College Students.

Purpose: The study aimed to explore the status of four common health problems (ie, smoking, internet addiction, physical inactivity, psychological disorder) among college students and analyze the relationship between psychological resilience, coping tendency and health problems. Participants and Methods: The convenience sampling method was used to recruit 500 college students from four universities. The General Information Questionnaire, Adolescent Psychological Resilience Scale, Simplified Coping Style Questionnaire and Health Risk Behavior Questionnaire were used for survey. Results: Among the students, there were 71 smokers (15.4%) and 61 internet addicts (13.2%). Over a third of the students reported physical inactivity (35.9%) and a minority had psychological disorder (6.3%). The psychological resilience score differed between students who smoked, had internet addiction, physical inactivity, psychological disorder and those without these health-risk behaviors. Logistic regression analysis showed that negative coping tendency was the common contributing factor of physical inactivity, internet addiction and psychological disorder. Coping tendency played a partial mediating effect in the relationship between psychological resilience and health problems, with a mediating effect of 37.93%. Conclusion: Psychological resilience can not only affect health problems directly but also influence health problems indirectly through coping tendency. Educators and administrators in universities can apply effective measures to improve psychological resilience and positive coping to prevent or reduce health problems among undergraduates.

Effects of dietary ginger (Zingiber officinale) polysaccharide on the growth, antioxidant, immunity response, intestinal microbiota, and disease resistance to Aeromonas hydrophila in crucian carp (Carassius auratus).

Ginger polysaccharides (GP) promote growth and development in fish. However, the effects of GP on crucian carp remain unclear. The present study investigated the effects of GP on the growth performance, immunity, intestinal microbiota, and disease resistance in crucian carp. Four treatment groups were established with different concentrations of GP (0.1 %, 0.2 %, 0.4 %, and 0.8 %). GP was not added as the control group, and the feeding period lasted for 56 d, followed by a 96-h anti-infection treatment using Aeromonas hydrophila. The results showed that dietary GP significantly improved growth performance, especially in the 0.4 % GP group. Furthermore, GP administration notably increased serum lysozyme (LMZ) activity, digestive enzyme performance, and antioxidant capacity of crucian carp. Moreover, dietary inclusion of GP up-regulated the expression of tumour necrosis factor-α (TNF-α), interleukin-8 (IL-8), interferon-γ (IFN-γ), and nuclear factor kappa-B (NF-κB) genes while down-regulating IL-10 and transforming growth factor-ß (TGF-ß) gene expressions, thus promoting liver health in crucian carp. Additionally, incorporating GP into the diet regulated both the diversity and composition of the intestinal microbiota in crucian carp, explicitly enhancing the relative abundance of beneficial bacteria, such as Fusobacteriota and Firmicutes. Therefore, GP reduces the mortality of crucian carp infected with A. hydrophila. In conclusion, this study provides novel insights into the application of dietary GP in cultured fish and evaluates the value of traditional Chinese medicinal polysaccharides against pathogenic bacteria.

Sub-regional CT Radiomics for the Prediction of Ki-67 Proliferation Index in Gastrointestinal Stromal Tumors: A Multi-center Study.

RATIONALE AND OBJECTIVES: The objective was to assess and examine radiomics models derived from contrast-enhanced CT for their predictive capacity using the sub-regional radiomics regarding the Ki-67 proliferation index (PI) in patients with pathologically confirmed gastrointestinal stromal tumors (GIST). METHODS: In this retrospective study, a total of 412 GIST patients across three institutions (223 from center 1, 106 from center 2, and 83 from center 3) was enrolled. Radiomic features were derived from various sub-regions of the tumor region of interest employing the K-means approach. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed to identify features correlated with Ki-67 PI level in GIST patients. A support vector machine (SVM) model was then constructed to predict the high level of Ki-67 (Ki-67 index >8%), drawing on the radiomics features from each sub-region within the training cohort. RESULTS: After features selection process, 6, 9, 9, 7 features were obtained to construct SVM models based on sub-region 1, 2, 3 and the entire tumor, respectively. Among different models, the model developed by the sub-region 1 achieved an area under the receiver operating characteristic curve (AUC) of 0.880 (95% confidence interval [CI]: 0.830 to 0.919), 0.852 (95% CI: 0.770-0.914), 0.799 (95% CI: 0.697-0.879) in the training, external test set 1, and 2, respectively. CONCLUSION: The results of the present study suggested that SVM model based on the sub-regional radiomics features had the potential of predicting Ki-67 PI level in patients with GIST.

Compact high-power 320-nm continuous-wave single-frequency laser based on power scaling of a diode-pumped Pr:LiYF4 ring laser at red.

Single-frequency (SF) lasers in the visible spectral region are usually obtained through an indirect method, i.e., frequency doubling of near-infrared SF lasers. In this work, we report on the direct generation of a high-power continuous-wave (CW) SF laser in red based on a diode-pumped Pr:LiYF4 (YLF) ring cavity technology. A maximum output power is scaled to 3.98 W at 640 nm with a linewidth of about 17.2 MHz and a power stability of 0.6%. Moreover, by inserting a LBO crystal into the ring cavity for intracavity frequency doubling of the 640 nm SF laser, we have also successfully demonstrated an ultraviolet (UV) SF laser at 320 nm, for the first time to the best of our knowledge, with a maximum power of 670 mW. This work provides a promising route for the development of simple, compact, and high-power SF lasers operating in visible and UV spectral regions.

Validation and Evaluation of a Vendor-Provided Head Motion Correction Algorithm on the uMI Panorama PET/CT System.

Brain PET imaging often faces challenges from head motion (HM), which can introduce artifacts and reduce image resolution, crucial in clinical settings for accurate treatment planning, diagnosis, and monitoring. United Imaging Healthcare has developed NeuroFocus, an HM correction (HMC) algorithm for the uMI Panorama PET/CT system, using a data-driven, statistics-based approach. The HMC algorithm automatically detects HM using a centroid-of-distribution technique, requiring no parameter adjustments. This study aimed to validate NeuroFocus and assess the prevalence of HM in clinical short-duration 18F-FDG scans. Methods: The study involved 317 patients undergoing brain PET scans, divided into 2 groups: 15 for HMC validation and 302 for evaluation. Validation involved patients undergoing 2 consecutive 3-min single-bed-position brain 18F-FDG scans-one with instructions to remain still and another with instructions to move substantially. The evaluation examined 302 clinical single-bed-position brain scans for patients with various neurologic diagnoses. Motion was categorized as small or large on the basis of a 5% SUV change in the frontal lobe after HMC. Percentage differences in SUVmean were reported across 11 brain regions. Results: The validation group displayed a large negative difference (-10.1%), with variation of 5.2% between no-HM and HM scans. After HMC, this difference decreased dramatically (-0.8%), with less variation (3.2%), indicating effective HMC application. In the evaluation group, 38 of 302 patients experienced large HM, showing a 10.9% ± 8.9% SUV increase after HMC, whereas most exhibited minimal uptake changes (0.1% ± 1.3%). The HMC algorithm not only enhanced the image resolution and contrast but also aided in disease identification and reduced the need for repeat scans, potentially optimizing clinical workflows. Conclusion: The study confirmed the effectiveness of NeuroFocus in managing HM in short clinical 18F-FDG studies on the uMI Panorama PET/CT system. It found that approximately 12% of scans required HMC, establishing HMC as a reliable tool for clinical brain 18F-FDG studies.

ST3GAL1 promotes malignant phenotypes in intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) has poor prognosis and elucidation of the molecular mechanisms underlying iCCA malignancy is of great significance. Glycosylation, an important post-translational modification, is closely associated with tumor progression. Altered glycosylation, including aberrant sialylation resulting from abnormal expression of sialyltransferases (STs) and neuraminidases (NEUs), is a significant feature of cancer cells. However, there is limited information on the roles of STs and NEUs in iCCA malignancy. Here, utilizing our proteogenomic resources from a cohort of 262 iCCA patients, we identified ST3GAL1 as a prognostically relevant molecule in iCCA. Moreover, overexpression of ST3GAL1 promoted proliferation, migration and invasion and inhibited apoptosis of iCCA cells in vitro. Through proteomic analyses, we identified the downstream pathway potentially regulated by ST3GAL1, which was the NF-κB signaling pathway and further demonstrated that this pathway was positively correlated with malignancy in iCCA cells. Notably, glycoproteomics showed that O-glycosylation was changed in iCCA cells with high ST3GAL1 expression. Importantly, the altered O-glycopeptides underscored the potential utility of O-glycosylation profiling as a discriminatory marker for iCCA cells with ST3GAL1 overexpression. Additionally, miR-320b was identified as a post-transcriptional regulator of ST3GAL1, capable of suppressing ST3GAL1 expression and then reducing the proliferation, migration and invasion abilities of iCCA cell lines. Taken together, these results suggest ST3GAL1 could serve as a promising therapeutic target for iCCA.

BNIP3-mediated mitophagy boosts the competitive growth of Lenvatinib-resistant cells via energy metabolism reprogramming in HCC.

An increasing evidence supports that cell competition, a vital selection and quality control mechanism in multicellular organisms, is involved in tumorigenesis and development; however, the mechanistic contributions to the association between cell competition and tumor drug resistance remain ill-defined. In our study, based on a contructed lenvitinib-resistant hepatocellular carcinoma (HCC) cells display obvious competitive growth dominance over sensitive cells through reprogramming energy metabolism. Mechanistically, the hyperactivation of BCL2 interacting protein3 (BNIP3) -mediated mitophagy in lenvatinib-resistant HCC cells promotes glycolytic flux via shifting energy production from mitochondrial oxidative phosphorylation to glycolysis, by regulating AMP-activated protein kinase (AMPK) -enolase 2 (ENO2) signaling, which perpetually maintaining lenvatinib-resistant HCC cells' competitive advantage over sensitive HCC cells. Of note, BNIP3 inhibition significantly sensitized the anti-tumor efficacy of lenvatinib in HCC. Our findings emphasize a vital role for BNIP3-AMPK-ENO2 signaling in maintaining the competitive outcome of lenvitinib-resistant HCC cells via regulating energy metabolism reprogramming; meanwhile, this work recognizes BNIP3 as a promising target to overcome HCC drug resistance.

4-Octyl itaconate blocks GSDMB-mediated pyroptosis and restricts inflammation by inactivating granzyme A.

GSDMB-mediated pyroptosis facilitates a pro-inflammatory immune microenvironment and needs to be tightly regulated to avoid excessive inflammation. Here, we provide evidence that itaconate and its cell-permeable derivative 4-octyl itaconate (4-OI) can significantly inhibit GSDMB-rendered pyroptotic activity independent of Nrf2. 4-OI interferes proteolytic process of GSDMB by directly modifying Cys54, Cys148 and Ser212 on granzyme A (GrzA), a serine protease that site-specifically cleaves the inter-domain linker of GSDMB, instead of interaction with GSDMB, thereby blocking pyroptosis and exerts anti-inflammatory effects. Moreover, 4-OI alleviates inflammation by suppressing GSDMB-induced pyroptotic cell death during acute colitis models in intestinal epithelial GSDMB conditional transgenic mice. Our data expand the role of 4-OI as a crucial immunometabolic derivative that regulates innate immunity and inflammation through a newly identified posttranslational modification, and targeting of pyroptosis by 4-OI therefore holds potent therapeutic potential for primarily inflammatory and/or autoimmune diseases.

Regulations of m6A and other RNA modifications and their roles in cancer.

RNA modification is an essential component of the epitranscriptome, regulating RNA metabolism and cellular functions. Several types of RNA modifications have been identified to date; they include N6-methyladenosine (m6A), N1-methyladenosine (m1A), 5-methylcytosine (m5C), N7-methylguanosine (m7G), N6,2'-O-dimethyladenosine (m6Am), N4-acetylcytidine (ac4C), etc. RNA modifications, mediated by regulators including writers, erasers, and readers, are associated with carcinogenesis, tumor microenvironment, metabolic reprogramming, immunosuppression, immunotherapy, chemotherapy, etc. A novel perspective indicates that regulatory subunits and post-translational modifications (PTMs) are involved in the regulation of writer, eraser, and reader functions in mediating RNA modifications, tumorigenesis, and anticancer therapy. In this review, we summarize the advances made in the knowledge of different RNA modifications (especially m6A) and focus on RNA modification regulators with functions modulated by a series of factors in cancer, including regulatory subunits (proteins, noncoding RNA or peptides encoded by long noncoding RNA) and PTMs (acetylation, SUMOylation, lactylation, phosphorylation, etc.). We also delineate the relationship between RNA modification regulator functions and carcinogenesis or cancer progression. Additionally, inhibitors that target RNA modification regulators for anticancer therapy and their synergistic effect combined with immunotherapy or chemotherapy are discussed.

Machine learning-based nomogram: integrating MRI radiomics and clinical indicators for prognostic assessment in acute ischemic stroke.

Background: Acute Ischemic Stroke (AIS) remains a leading cause of mortality and disability worldwide. Rapid and precise prognostication of AIS is crucial for optimizing treatment strategies and improving patient outcomes. This study explores the integration of machine learning-derived radiomics signatures from multi-parametric MRI with clinical factors to forecast AIS prognosis. Objective: To develop and validate a nomogram that combines a multi-MRI radiomics signature with clinical factors for predicting the prognosis of AIS. Methods: This retrospective study involved 506 AIS patients from two centers, divided into training (n = 277) and validation (n = 229) cohorts. 4,682 radiomic features were extracted from T1-weighted, T2-weighted, and diffusion-weighted imaging. Logistic regression analysis identified significant clinical risk factors, which, alongside radiomics features, were used to construct a predictive clinical-radiomics nomogram. The model's predictive accuracy was evaluated using calibration and ROC curves, focusing on distinguishing between favorable (mRS ≤ 2) and unfavorable (mRS > 2) outcomes. Results: Key findings highlight coronary heart disease, platelet-to-lymphocyte ratio, uric acid, glucose levels, homocysteine, and radiomics features as independent predictors of AIS outcomes. The clinical-radiomics model achieved a ROC-AUC of 0.940 (95% CI: 0.912-0.969) in the training set and 0.854 (95% CI: 0.781-0.926) in the validation set, underscoring its predictive reliability and clinical utility. Conclusion: The study underscores the efficacy of the clinical-radiomics model in forecasting AIS prognosis, showcasing the pivotal role of artificial intelligence in fostering personalized treatment plans and enhancing patient care. This innovative approach promises to revolutionize AIS management, offering a significant leap toward more individualized and effective healthcare solutions.

Research on the preparation and performance of Ni2P@MOF composite nanomaterials.

The present study employed a solvothermal method utilizing triphenylphosphine and nickel acetylacetonate as precursors for phosphide preparation, followed by analysis and characterization. The Ni-MOF precursor was prepared using benzene diacid, triethylenediamine, and nickel sulfate as raw materials. Ni2P was introduced into the Ni-MOF precursor during its preparation while maintaining the synthesis conditions, allowing for the adsorption of Ni2P nanoparticles during Ni-MOF synthesis to produce Ni2P@MOF composite materials. The materials underwent individual testing for UV, magnetic, and microwave absorption properties. Magnetic testing results demonstrated that the incorporation of Ni2P led to an increase in the saturation magnetization (Ms) of Ni2P@MOFs compared to the Ni-MOF, thereby enhancing its electromagnetic loss capability. Microwave absorption property testing indicated that the Ni2P@MOFs exhibited enhanced dielectric and electromagnetic loss capabilities compared to the Ni-MOF, optimizing impedance matching properties and increasing effective absorption bandwidth compared to pure Ni2P materials.

Integration of deep learning and habitat radiomics for predicting the response to immunotherapy in NSCLC patients.

BACKGROUND: The non-invasive biomarkers for predicting immunotherapy response are urgently needed to prevent both premature cessation of treatment and ineffective extension. This study aimed to construct a non-invasive model for predicting immunotherapy response, based on the integration of deep learning and habitat radiomics in patients with advanced non-small cell lung cancer (NSCLC). METHODS: Independent patient cohorts from three medical centers were enrolled for training (n = 164) and test (n = 82). Habitat imaging radiomics features were derived from sub-regions clustered from individual's tumor by K-means method. The deep learning features were extracted based on 3D ResNet algorithm. Pearson correlation coefficient, T test and least absolute shrinkage and selection operator regression were used to select features. Support vector machine was applied to implement deep learning and habitat radiomics, respectively. Then, a combination model was developed integrating both sources of data. RESULTS: The combination model obtained a strong well-performance, achieving area under receiver operating characteristics curve of 0.865 (95% CI 0.772-0.931). The model significantly discerned high and low-risk patients, and exhibited a significant benefit in the clinical use. CONCLUSION: The integration of deep-leaning and habitat radiomics contributed to predicting response to immunotherapy in patients with NSCLC. The developed integration model may be used as potential tool for individual immunotherapy management.

Prediction of Potential Distribution of Carposina coreana in China under the Current and Future Climate Change.

Carposina coreana is an important pest of Cornus officinalis, distributed in China, Korea, and Japan. In recent years, its damage to C. officinalis has become increasingly serious, causing enormous economic losses in China. This study and prediction of current and future suitable habitats for C. coreana in China can provide an important reference for the monitoring, early warning, prevention, and control of the pest. In this study, the potential distributions of C. coreana in China under current climate and future climate models were predicted using the maximum entropy (MaxEnt) model with ArcGIS software. The distribution point data of C. coreana were screened using the buffer screening method. Nineteen environmental variables were screened using the knife-cut method and variable correlation analysis. The parameters of the MaxEnt model were optimized using the kuenm package in R software. The MaxEnt model, combined with key environmental variables, was used to predict the distribution range of the suitable area for C. coreana under the current (1971-2000) and four future scenarios. The buffer screening method screened data from 41 distribution points that could be used for modeling. The main factors affecting the distribution of C. coreana were precipitation in the driest month (Bio14), precipitation in the warmest quarter (Bio18), precipitation in the coldest quarter (Bio19), the standard deviation of seasonal variation of temperature (Bio4), minimum temperature in the coldest month (Bio6), and average temperature in the coldest quarter (Bio11). The feature class (FC) after the kuenm package optimization was a Q-quadratic T-threshold combination, and the regularization multiplier (RM) was 0.8. The suitable areas for C. coreana under the current climate model were mainly distributed in central China, and the highly suitable areas were distributed in southern Shaanxi, southwestern Henan, and northwestern Hubei. The lowest temperature in the coldest month (Bio6), the average temperature in the coldest quarter (Bio11), and the precipitation in the warmest quarter (Bio18) all had good predictive ability. In future climate scenarios, the boundary of the suitable area for C. coreana in China is expected to shift northward, and thus, most of the future climate scenarios would shift northward.

Whole-brain glucose metabolic pattern differentiates minimally conscious state from unresponsive wakefulness syndrome.

AIMS: The patient being minimally conscious state (MCS) may benefit from wake-up interventions aimed at improving quality of life and have a higher probability of recovering higher level of consciousness compared to patients with the unresponsive wakefulness syndrome (UWS). However, differentiation of the MCS and UWS poses challenge in clinical practice. This study aimed to explore glucose metabolic pattern (GMP) obtained from 18F-labeled-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) in distinguishing between UWS and MCS. METHODS: Fifty-seven patients with disorders of consciousness (21 cases of UWS and 36 cases of MCS) who had undergone repeated standardized Coma Recovery Scale-Revised (CRS-R) evaluations were enrolled in this prospective study. 18F-FDG-PET was carried out in all patients and healthy controls (HCs). Voxel-based scaled subprofile model/principal component analysis (SSM/PCA) was used to generate GMPs. The expression score of whole-brain GMP was obtained, and its diagnostic accuracy was compared with the standardized uptake value ratio (SUVR). The diagnostic efficiency was validated by one-year later clinical outcomes. RESULTS: UWS-MCS GMP exhibited hypometabolism in the frontal-parietal cortex, along with hypermetabolism in the unilateral lentiform nucleus, putamen, and anterior cingulate gyrus. The UWS-MCS-GMP expression score was significantly higher in UWS compared to MCS patients (0.90 ± 0.85 vs. 0 ± 0.93, p < 0.001). UWS-MCS-GMP expression score achieved an area under the curve (AUC) of 0.77 to distinguish MCS from UWS, surpassing that of SUVR based on the frontoparietal cortex (AUC = 0.623). UWS-MCS-GMP expression score was significantly correlated with the CRS-R score (r = -0.45, p = 0.004) and accurately predicted the one-year outcome in 73.7% of patients. CONCLUSION: UWS and MCS exhibit specific glucose metabolism patterns, the UWS-MCS-GMP expression score significantly distinguishes MCS from UWS, making SSM/PCA a potential diagnostic methods in clinical practice for individual patients.

Gastrodin regulates the expression of renin-angiotensin system-SIRT3 and proinflammatory mediators in reactive astrocytes via activated microglia.

Gastrodin, an anti-inflammatory herbal agent, is known to suppress microglia activation. Here, we investigated whether it would exert a similar effect in reactive astrocytes and whether it might act through the renin-angiotensin system (RAS) and sirtuin 3 (SIRT3). Angiotensinogen (ATO), angiotensin-converting enzyme (ACE), angiotensin II type 1 (AT1) and type 2 (AT2) receptor and SIRT3 expression was detected in TNC-1 astrocytes treated with BV-2 microglia conditioned medium (CM) with or without gastrodin and lipopolysaccharide (LPS) pre-treatment by RT-PCR, immunofluorescence and western blotting analysis. Expression of C3 (A1 astrocyte marker), S100A10 (A2 astrocyte marker), proinflammatory cytokines and neurotrophic factors was then evaluated. The results showed a significant increase of ATO, ACE, AT1, SIRT3, C3, proinflammatory cytokines and neurotrophic factors expression in TNC-1 astrocytes incubated in CM + LPS when compared with cells incubated in the CM, but AT2 and S100A10 expression was reduced. TNC-1 astrocytes responded vigorously to BV-2 CM treated with gastrodin + LPS as compared with the control. This was evident by the decreased expression of the abovementioned protein markers, except for AT2 and S100A10. Interestingly, SIRT3, IGF-1 and BDNF expression was enhanced, suggesting that gastrodin inhibited the expression of RAS and proinflammatory mediators but promoted the expression of neurotrophic factors. And gastrodin regulated the phenotypic changes of astrocytes through AT1. Additionally, azilsartan (a specific inhibitor of AT1) inhibited the expression of C3 and S100A10, which remained unaffected in gastrodin and azilsartan combination treatment. These findings provide evidence that gastrodin may have a therapeutic effect via regulating RAS-SIRT3.

A dataset to measure global climate physical risk.

Extreme climate events have become more frequent and have had serious impacts on the global community. Consequently, the risk associated with climate change has gained increasing attention and has been considered as a new source of risk factors. To understand the socio-economic impacts of this new risk, systematically measuring risk around the world is critical for researchers and policymakers. Building on daily observations from meteorological stations, a Climate Physical Risk Index (CPRI) dataset is constructed for 170 countries, paying special attention to four extreme climate events: extreme low temperature (LTD), extreme high temperature (HTD), extreme rainfall (ERD), and extreme drought (EDD). A comprehensive index of climate physical risk for each country has also been constructed, covering the period from 1993 to 2023. The dataset will be updated regularly. Subnational indices or more detailed regional indices are available upon request.

A New Species of the Genus Takydromus (Squamata: Lacertidae) from Northeastern Guangxi, China.

During our collecting trip to Guangxi in 2016, we collected ten specimens of the genus Takydromus from the suburb of Guilin, northeastern Guangxi, South China, and found that they did not belong to any currently known species. Here, we described this new species, Takydromus guilinensis sp. nov., based on morphological and mitochondrial DNA (CO1 and cyt b) data. This new species is a sister taxon to T. intermedius with a p-distance of 0.070 in CO1 and 0.080 in cyt b. These two p-distances exceed not only the minimum value (0.067) between T. septentrionalis and T. stejnegeri but also the minimum value (0.079) between T. intermedius and T. yunkaiensis. Morphologically, this new species differs from other currently recognized Takydromus species from the same clade, more evidently in the longitudinal rows of dorsal scales, transverse rows of scales at the mid-body and mensural variables. The description of Takydromus guilinensis sp. nov. increases the total number of Takydromus species to 25, of which 16 can be found in China. Takydromus guilinensis sp. nov. is currently known only from Guilin, Guangxi, South China, where it is sympatric with the other four Takydromus species (T. septentrionalis, T. kuehnei, T. sexlineatus and T. intermedius).

Coherent beam combining of two all-PM thulium-doped fiber chirped pulse amplifiers.

In this paper, we report a coherent beam combining (CBC) system that involves two thulium-doped all-polarization maintaining (PM) fiber chirped pulse amplifiers. Through phase-locking the two channels via a fiber stretcher by using the stochastic parallel gradient descent (SPGD) algorithm, a maximum average power of 265 W is obtained, with a CBC efficiency of 81% and a residual phase error of λ/17. After de-chirping by a pair of diffraction gratings, the duration of the combined laser pulse is compressed to 690 fs. Taking into account the compression efficiency of 90% and the main peak energy proportion of 91%, the corresponding peak power is calculated to be 4 MW. The laser noise characteristics before and after CBC are examined, and the results indicate that the CBC would degrade the low frequency relative intensity noise (RIN), of which the integration is 1.74% in [100 Hz, 2 MHz] at the maximum combined output power. In addition, the effects of the nonlinear spectrum broadening during chirped pulse amplification on the CBC efficiency are also investigated, showing that a higher extent of pulse stretching is effective in alleviating the spectrum broadening and realizing a higher output power with decent combining efficiency.