302 Military Hospital of China

Autophagy exerts an important effect on preserving homeostasis of cellular metabolism through degrading superfluous intracellular components. In addition, it serves as the defense mechanism for eliminating invading pathogens, such as viruses, by the host. The onset of a viral infection triggers autophagy, thereby initiating the innate immunity via the pattern recognition receptor pathways. As a result, interferons and other proinflammatory factors are produced. Furthermore, autophagy specifically targets immune components linked to viral particles for degradation. Through presenting virus-derived antigens to T lymphocytes, this process supports adaptive immunity. Nonetheless, certain viruses evolve mechanisms for inhibiting autophagy, enabling evasion of degradation and immune detection, since autophagy is frequently related to inflammatory diseases, including infections, autoimmune disorders, cancer, metabolic syndromes, neurodegenerative conditions, and cardiovascular and liver diseases. This review aims to summarize the current knowledge regarding the key molecules and specific molecular mechanisms that underlie the pattern recognition receptor signaling where autophagy is implicated during viral infections.

Tropospheric scattering is a critical propagation mechanism for Over-the-Horizon wireless communications, where radio propagation characteristics are significantly influenced by nonuniform and spatiotemporally dynamic atmospheric refraction and turbulence. This paper proposes a weather forecast-enabled parabolic equation-based tropospheric scattering path loss channel model, referred to as the WPE model. First, atmospheric parameters extracted from the Weather Research and Forecasting (WRF) scheme are used to compute atmospheric refractivity profiles, enabling the WPE model to enhance temporal and spatial resolution while integrating meteorological factors specific to the marine environment, thus overcoming the limitations of traditional scattering parabolic equation (PE) model. Then, the atmospheric refractivity structure constant is used to obtain the stochastic turbulence perturbation component, which is incorporated into the two-dimensional PE to reflect the impact of turbulence on tropospheric scatter radio wave propagation. More importantly, a cross-sea shore-to-shore experiment is conducted in the South China Sea with a 300 km link distance for both C-band and Ku-band. Finally, the results from the validation of the proposed WPE model and measurement, demonstrate that the average root mean square error and mean error of the WPE model can be reduced to below 3 dB and 1.5 dB at C-band and below 5 dB and 1 dB at Ku-band, respectively. These findings suggest that the WPE model effectively predicts path loss and provides a more realistic characterization of turbulence effects compared to the traditional PE model. This research establishes a theoretical foundation for troposcatter channel modeling and propagation analysis, offering valuable insights for the design of Over-the-Horizon maritime communication systems.

Recent studies have illuminated a significant relationship between the gut microbiota and the development and progression of autism spectrum disorder (ASD), mediated through the complex gut–brain axis, where metabolic pathways are crucial. Nevertheless, the exact causal link remains to be elucidated. This study aims to assess the potential causal relationship between the gut microbiota, metabolites, and ASD, utilizing Mendelian randomization methodology. The exposure variable of gut microbiota was ascertained using instrumental variables derived from a genome-wide association study that included a cohort of 18,340 individuals. The outcome variable comprised genome-wide association study data from 14,759 individuals diagnosed with ASD and 1,55,327 controls. The primary method of analysis was the inverse-variance weighted method. Multivariable multiple regression analysis was conducted to examine the impact of gut microbial metabolites on the established correlations. Inverse-variance weighted analyses revealed that Methanobacteria[c] (odds ratio [OR] = 1.17 [1.03–1.33]), Methanobacteriaceae[f] (OR = 1.17 [1.03–1.33]), Prevotellaceae[f] (OR = 1.29 [1.04–1.60]), Holdemania[g] (OR = 1.23 [1.03–1.45]), Lachnospiraceae[g] (OR = 1.29 [1.06–1.57]), Ruminiclostridium[g] (OR = 1.63 [1.27–2.10]), Terrisporobacter[g] (OR = 1.28 [1.00–1.63]), Methanobacteriales[o] (OR = 1.17 [1.03–1.33]), and Euryarchaeota[p] (OR = 1.16 [1.02–1.32]) serve as risk factors for ASD, while Eisenbergiella[g] (OR = 0.80 [0.68–0.94]) and Ruminococcaceae[g] (OR = 0.79 [0.63–1.00]) exhibit protective roles against ASD. Adjustments for neurotransmitter and amino acid metabolites effects diminished these associations. However, Prevotellaceae and Lachnospiraceae remained significantly associated with increased ASD risk. Reverse Mendelian randomization analyses did not establish a causal relationship between ASD and gut microbiota composition. Sensitivity tests showed no evidence of heterogeneity or pleiotropy. Alterations in metabolites induced by the gut microbiota may contribute to ASD susceptibility. Prevotellaceae and Lachnospiraceae are implicated as potential risk factors. Investigating these associations further could unveil novel therapeutic targets and provide deeper insights into ASD’s etiological mechanisms.

Abstract Background Adverse remodeling is significantly associated with heart failure, and strains derived from Cardiovascular magnetic resonance (CMR) serves as a sensitive detector in predicting this pathophysiological process after acute myocardial infarction (MI). However, strategies to identify individuals at risk of adverse remodeling focusing on segmental strains, especially strains of remote myocardium are lacking, we therefore aimed to investigate the predictive value of functional early change in infarcted, viable and remote myocardium after acute MI. Method We derived data from a cohort of 271 STEMI patients with serial CMR collected at one week and six months after. Adverse remodeling is defined as 20% increase in end-diastolic volume after 6 months of MI. According to whether the adverse remodeling occurred, stratified random sampling was used to divide 271 patients into training and testing set in 8:2 ratio. A total of 53 features (38 clinical parameters, 3 CMR traditional parameters and 12 CMR feature-tracking derived strain parameters) have been used to predict the risk of adverse remodeling. To evaluate the predictive accuracy of various machine learning techniques and feature combinations, we calculate the areas under the receiver operating characteristic curve (AUC)s, in which 1) ML with clinical features (ML-clinic), 2) ML with traditional CMR parameters (ML-LGE), and 3) ML with strain data (ML-strain), 4) ML combining clinical and traditional CMR parameters (ML-combined LGE), 5) ML combining clinical and strain data (ML-combined strain) was used as an input of five ML techniques. The SHAP (SHapley Additive exPlanations) value was used to quantity the feature importance. Results Multilayer perceptron (MLP) with residual framework perform best in ML techniques. Using MLP, addition of segmental and global strain measures to clinical data increased the AUC from 0.55 (ML-selected clinic) and 0.42 (ML-strain) to 0.83 (ML-combined strain), which is comparable to 0.73 (LGE combined model). We also found that LS in adjacent regions may serve as a more sensitive detector for adverse remodeling after a SHAP value-based comparison of global versus regional stains. Conclusion ML combined both clinical and strains were found to have high predictive accuracy for adverse remodeling, which could serve as alternative to traditional CMR parameters. Besides, we illustrated a framework for comparing the prognostic value of multiple CMR-feature tracking parameters in the context of clinical parameters.The Study Workflow SHAP feature importance from MLP model

Abstract Multi‐species occupancy models for estimating the effects of environmental covariates on species occurrences while accounting for the effects of false‐negative errors in detection were developed more than 20 years ago. Only recently have these models been extended to include correlations in occurrence between species. Tobler et al. (2019) proposed two of these models wherein species occurrences are specified using a probit‐regression model of correlated multivariate binary outcomes. In one model, correlations in occurrence between species are formal parameters. In the other model, a factor‐analytic approximation of these correlations is used. After conducting extensive simulation studies to compare the performance of these models, Tobler et al. (2019) recommended the latter model in favour of the former owing to difficulties in fitting the former to simulated or real data. The same software (JAGS) was used to fit both models. Since the former model specifies the actual process used to generate species occurrences, we hypothesized that shortcomings in the software were responsible for the difficulties reported by Tobler et al. (2019). We therefore devised an efficient Markov chain Monte Carlo algorithm for fitting the data‐generating, multi‐species occupancy model using parameter‐expanded data augmentation. Using this algorithm, we conducted analyses of simulated data sets to re‐evaluate and compare the performance of the two multi‐species occupancy models. We also compared the results of fitting these models to a real dataset collected in camera‐trap surveys of mammalian species on the Tibetan Plateau. Our analyses of simulated data revealed that estimators of species occurrence, correlation and detection parameters had similar performance in terms of average bias, average root‐mean‐squared error and average coverage of 95% credible intervals regardless of whether the data‐generating model or its factor‐analytic approximation was used to analyse the data. However, our analyses also revealed the presence of systematic bias in the correlation estimates of both models, wherein strongly negative correlations were overestimated and strongly positive correlations were underestimated. Systematic bias was not evident in correlations estimated by fitting a multivariate probit regression model to latent species occurrences; therefore, the systematic bias in correlation estimates of the two occupancy models must have been produced by the failure of these models to estimate latent species occurrences accurately.

This study was conducted to evaluate the yield potential, yield components and some agronomic traits of 8 natural color cotton elite lines, which were improved by the National Corn and Sorghum Research Center [NCSRC], tested with 2 check varieties; Dora11, and Srisumrong60 in the early rainy season of 2022 at the NCSRC, Faculty of Agriculture, Kasetsart University, Nakhon Ratchasima Province, Thailand. The randomized complete block design [RCBD] with 3 replications was used with 25 plants/row, 4 rows/experimental unit, and data were recorded from middle row. It was found that 9 of 11 recorded traits of the tested cotton varieties/lines were significantly different. It comprised no. of days to 50% boll opening (107-114 days), plant ht (135-164 cm), no. of vegetative branch (1.2-3.4 branches/plant), no. of fruiting branch (12.3-14.6 branches/plant), seed wt (8.2-13.4 g/100 seeds), boll wt (4.28-5.71 g/boll), seed cotton yield (194-262 kg/rai), cotton lint yield (70-108 kg/rai), and ginning outturn (30.9-41.9%). While no. of days to 50% flowering (53-55 days) and no. of boll/plant (51.7-58.3 balls/plant) had a non-significant difference. The result of this study indicated that natural color cotton lines W535, W537 and W536 had a trend for higher lint yield than Dora11, Srisumrong60. The lint yields were 108, 105, 103, 93 and 80 kg/rai, respectively. While other 5 natural color lines had lint yield of 70-94 kg/rai.

Мета роботи - виокремити роль пацієнта/відвідувача аптеки, лікаря/фармацевта в реалізації фармацевтичної опіки при лікуванні мігрені. Матеріали і методи. Методологічну основу дослідження складають принципи об’єктивності і системності. У роботі використано комплекс загальнонаукових та спеціальних методів: теоретичний, метод узагальнення, систематизації даних, порівняння, аналізу, анкетування. Проведено анкетне опитування 20 відвідувачів аптеки, які зверталися до аптеки з метою придбання лікарського засобу для лікування мігрені. Результати й обговорення. При нападах легкого та помірного ступеня тяжкості наші респонденти застосовували прості анальгетики та нестероїдні протизапальні засоби (ібупрофен, парацетамол, напроксен та ацетилсаліцилова кислота). Вибір лікарського засобу для симптоматичного лікування здійснювався на засадах відповідального самолікування за консультативної участі фармацевта. При тяжких нападах застосовували триптани: суматриптан, золмітриптан та ризатриптан, які були призначені лікарем. 15 % респондентів застосовували засоби рецептурного відпуску для превентивного лікування мігрені: пропранолол (таблетки, 10 мг); метопролол (таблетки, вкриті плівковою оболонкою, з уповільненим вивільненням, 25 мг) та топірамат (таблетки, вкриті плівковою оболонкою, 25 мг). Найбільш затребуваними були таблетки і капсули (90 % респондентів надавала їм перевагу при виборі лікарської форми і 10 % – віддали перевагу спрею назальному. Стосовно правил прийому лікарських засобів для лікування/профілактики мігрені: 80 % респондентів дотримуються правил прийому і лише 20 % не надавали належного значення умовам раціонального застосування лікарських засобів. Серед факторів, що впливають на прихильність до лікування, респондентами було зазначено: зручна форма випуску лікарського засобу, швидкий початок його дії, стійкість ефекту, мінімальна потреба в повторній дозі, можливість самолікування. Висновки. Фармацевтична опіка (на усіх етапах її реалізації) відіграє важливу роль у підвищенні ефективності та безпеки терапії мігрені. Саме взаємодія фахівців медицини та фармації і високий ступінь залученості до процесу осіб із мігренню буде сприяти профілактиці нападів, зменшенню частоти та тяжкості перебігу болю голови, підвищенню якості життя. Удосконалення фармацевтичної опіки при лікуванні мігрені має відбуватися безперервно з урахуванням новітніх медичних технологій та розвитку знань в неврології.