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This Comment provides methodological insights and clinical perspectives on real-world outcomes of device-aided therapies in Parkinson's disease.This Comment provides methodological insights and clinical perspectives on real-world outcomes of device-aided therapies in Parkinson's disease.

The elephant herding optimization (EHO) algorithm is a novel metaheuristic optimizer inspired by the clan renewal and separation behaviors of elephant populations. Although it has few parameters and is easy to implement, it suffers from a lack of exploitation, leading to slow convergence. This paper proposes an improved EHO algorithm called manta ray foraging and Gaussian mutation-based EHO for global optimization (MGEHO). The clan updating operator in the original EHO algorithm is replaced by the somersault foraging strategy of manta rays, which aims to optimally adjust patriarch positions. Additionally, a dynamic convergence factor is set to balance exploration and exploitation. The gaussian mutation is adopted to enhance the population diversity, enabling MGEHO to maintain a strong local search capability. To evaluate the performances of different algorithms, 33 classical benchmark functions are chosen to verify the superiority of MGEHO. Also, the enhanced paradigm is compared with other advanced metaheuristic algorithms on 32 benchmark functions from IEEE CEC2014 and CEC2017. Furthermore, a scalability test, convergence analysis, statistical analysis, diversity analysis, and running time analysis demonstrate the effectiveness of MGEHO from various aspects. The results illustrate that MGEHO is superior to other algorithms in terms of solution accuracy and stability. Finally, MGEHO is applied to solve three real engineering problems. The comparison results show that this method is a powerful auxiliary tool for handling complex problems.

Objective To analyze factors for cognitive impairment in epileptic patients. Methods A total of 257 epileptic patients completed clinical memory scale (CMS) and 70 of them were further surveyed with mini‐mental state examination (MMSE), Montreal cognitive assessment (MoCA), digital symbol test (DSy), verbal fluency test, digit span test (DSp), Hamilton anxiety scale (HAMA) and Hamilton depression scale (HAMD). Monadic linear related analysis and multiple stepwise regression analysis were performed to evaluate the potential factors for cognitive impairment. Results Educational level was correlated with scores of cognitive tests (p < .01), with a difference between the junior high school group and senior high school group (p < .01 or p < .05). Seizure frequency was negatively correlated with CMS scores (p < .01), with a difference between the group with a seizure frequency of less than once a year and other groups (p < .01). The kind of antiepileptic drugs (AEDs) was negatively correlated with CMS scores (p < .01), with a difference between the single‐drug group and the group taking more than two kinds of AEDs (p < .01). Depression scores were negatively correlated with MMSE, MoCA, DSy, DSp (p < .01 or p < .05), disease duration negatively with DSy (p < .01), and age negatively with MoCA (p < .05). Seizure type was correlated with DSy, and general seizure fared worse in the tests than other seizure types (p < .05). Conclusion Educational level, seizure frequency, kinds of AEDs and depression can affect the cognitive function of epileptic patients. High educational level, good seizure control, single‐drug treatment and healthy psychological state are protective factors for cognitive function of epileptic patients. Educational level, seizure frequency, kinds of antiepileptic drugs, and depression can affect the cognitive function of epileptic patients. High educational level, good seizure control, single‐drug treatment, and healthy psychological state are protective factors for cognitive function of epileptic patients. These findings provide a new strategy for avoiding cognitive impairment in epileptic patients.

Asparagine synthetase B (AS-B) is essential for nitrogen metabolism, but its broader physiological functions remain poorly understood. Here we show that the evolutionarily conserved Nicotiana benthamiana NbAS-B confers expression-dependent antiviral resistance and promotes plant growth. Multi-omics analyses indicate that NbAS-B-mediated antiviral immunity relies on glutamate-induced activation of Ca²⁺ signaling through the receptor GLR3.3, whereas its growth-promoting effect results from photosynthetic reprogramming. Building on these insights, we develop polyglutamate-loaded chitosan nanogels (PGANPs) to artificially manipulate this pathway. These nanogels efficiently enter plant tissues and enable sustained in situ release of glutamate, thereby mimicking and amplifying NbAS-B signaling outputs. PGANPs provide long-lasting systemic antiviral immunity while concurrently enhancing plant growth, without incurring metabolic costs. Our work identifies NbAS-B as a dual-function regulator linking metabolic status to immune activation and establishes PGANPs as an eco-friendly, controllable, and durable nanobiotechnology for managing viral diseases in crops. Controlling plant metabolism to improve growth and disease resistance has huge potential. Here, the authors find a conserved pathway which promotes antiviral resistance and promotes plant growth and develop polyglutamate-loaded chitosan nanogels to manipulate this pathway.

Ischemic stroke is a leading cause of mortality and disability worldwide, with limited therapeutic options and high rates of recurrence. Mitochondrial dysfunction plays a critical role in neuronal injury during ischemia-reperfusion, making mitochondrial autophagy a potential therapeutic target. Gypenoside XLIX, a major active metabolite of Gynostemma pentaphyllum, exhibits antioxidant and organ-protective properties, but its effects on neuronal mitochondrial damage in stroke remain unclear. This study aimed to explore the neuroprotective mechanisms of Gypenoside XLIX in ischemic stroke, focusing on the PI3K/AKT/FOXO1 signaling pathway. Neuroprotective effects were evaluated in oxygen-glucose deprivation (OGD) neuronal cells and middle cerebral artery occlusion (MCAO) rat models. Cell viability, apoptosis, ROS production, mitochondrial membrane potential, and autophagic flux were assessed by CCK-8, flow cytometry, ELISA, TMRE staining, immunofluorescence, and Western blotting. Signaling pathway involvement was examined using PI3K inhibitor LY294002, AKT activator SC79, and FOXO1 knockdown. Gypenoside XLIX significantly improved neuronal viability (p < 0.01), reduced apoptosis (p < 0.01), and decreased ROS levels (p < 0.001) in OGD cells. It enhanced p-PI3K and p-AKT expression while suppressing FOXO1 (p < 0.05), promoted Beclin-1, LC3, PINK1, and Parkin expression (p < 0.001), and reduced p62 (p < 0 .01). In MCAO rats, Gypenoside XLIX decreased infarct volume (p < 0.001), brain edema (p < 0.01), and TUNEL-positive cells (p < 0.001), while elevating mitochondrial membrane potential and antioxidant enzyme levels (SOD, GSH-Px, CAT; all p < 0.001). Gypenoside XLIX alleviates ischemic stroke injury by activating the PI3K/AKT/FOXO1 pathway, enhancing mitochondrial autophagy, and reducing oxidative stress, supporting its potential as a novel neuroprotective agent in stroke management.

Danshen ( Salvia miltiorrhiza Bunge), a member of the genus Salvia within the Lamiaceae family, holds significant economic and medicinal value. Regrettably, the emergence of a novel leaf anthracnose in 2020 has significantly impacted its cultivation, leading to decreased yield and compromised quality. This newly identified pathogen was meticulously isolated from affected leaves, employing meticulous single conidia isolation techniques. Subsequent confirmation of pathogenicity was achieved through strict adherence of Koch’s postulates. To ensure precise identification, morphological characteristics were supplemented with tandem sequence analysis targeting the rDNA internal transcribed spacer ( ITS ), β-tubulin ( TUB ), and histone ( His3 ) regions. Combining molecular biology techniques with morphological observation and Koch’s postulates, the pathogen was conclusively identified as Colletotrichum karstii . Further investigations focused on understanding the environmental factors influencing the mycelial growth and sporulation of the pathogen. The optimum temperature for the growth of C.karstii is 25°C, the suitable light conditions are 12h light/12h dark or 24h dark, and the suitable pH is 5 to 9. Utilizing BIOLOG phenotypic analysis technique, the metabolic utilization of carbon and nitrogen sources by the pathogen was assessed across different temperatures (20°C, 25°C, and 30°C). Results indicated the highest utilization rates at 25°C, particularly for arbutin and L-tryptophan. Lastly, the efficacy of 15 chemical fungicides and six botanical fungiticide against C. karstii was evaluated in vitro, revealing fluazinam as the most potent inhibitor against mycelial growth with EC 50 of 0.0725 mg/mL for mycelium and 0.0378 mg/mL for spore germination, respectively. The 1 % osthole emulsion in water was found to have the strongest inhibitory effect on the growth of mycelium, with an EC50 value of 4.8984 µg/mL. Spore germination was most strongly inhibited by the 80 % ethylicin EC, which had an EC50 value of 0.5541 µg/mL. This study represents the first documentation of C. karstii as a causative agent of anthrax in Danshen, underscoring the significance of these findings for agricultural management and disease control strategies.

Background Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, the stroke care systems have been seriously affected because of social restrictions and other reasons. As the pandemic continues to spread globally, it is of great significance to understand how COVID-19 affects the stroke care systems in mainland China. Methods We retrospectively studied the real-world data of one comprehensive stroke center in mainland China from January to February 2020 and compared it with the data collected during the same period in 2019. We analyzed DTN time, onset-to-door time, severity, effects after treatment, the hospital length of stays, costs of hospitalization, etc., and the correlation between medical burden and prognosis of acute ischemic stroke (AIS) patients. Results The COVID-19 pandemic was most severe in mainland China in January and February 2020. During the pandemic, there were no differences in pre-hospital or in-hospital workflow metrics (all p >0.05), while the degree of neurological deficit on admission and at discharge, the effects after treatment, and the long-term prognosis were all worse (all p <0.05). The severity and prognosis of AIS patients were positively correlated with the hospital length of stays and total costs of hospitalization (all p <0.05). Conclusions COVID-19 pandemic is threatening the stroke care systems. Measures must be taken to minimize the collateral damage caused by COVID-19.

Background Ischemic heart failure (IHF) is one of the leading causes of death in the world. Plasma apolipoprotein C3 (ApoC3) levels are significantly elevated in patients with heart failure and positively associated with the incidence of ischemic heart disease (IHD). However, the causal association between ApoC3 and IHD development is unclear. Methods ApoC3 expression changes were assessed in plasma from IHF patients/healthy donors and cardiac tissue from rodent models. 10-week-old male human ApoC3 transgenic (ApoC3 Tg ) mice, ApoC3 knockout (ApoC3 −/− ) mice, ApoC3 −/− hamsters, and wild-type (WT) controls underwent left anterior descending coronary artery (LAD) ligation to establish IHF models 4 weeks post-MI. Echocardiography, biochemical assays, and histopathology were employed to investigate ApoC3’s role and regulatory mechanisms in MI-induced IHF. Results Overexpression of human ApoC3 in ApoC3 Tg mice exacerbated IHF after MI surgery, characterized by cardiac hypertrophy with thinned ventricular wall thickness and decreased contractile function. Mechanistically, ApoC3 overexpression markedly upregulated its receptor TLR2 at the myocardial ischemic site, and activated the NF-κB pathway resulting in significant increases in inflammation, oxidative stress and apoptosis. Unfortunately, ApoC3 deficiency did not show an overt protective effect in mouse MI model. We subsequently introduced ApoC3 −/− hamsters and found that unlike mouse model, plasma HDL levels were markedly higher in ApoC3 −/− hamsters 4 weeks after surgery compared with WT hamsters cardiac remodeling and contractile function were significantly ameliorated with a reduction in TLR2 gene expression, eventually inhibiting inflammation, oxidative stress, and apoptosis in MI heart. Conclusions ApoC3 overexpression could activate cardiac TLR2/NF-κB to trigger the inflammation, oxidation, and apoptosis pathways, finally aggravating IHF in mice. Inactivation of ApoC3 could significantly alleviate IHF in hamsters. Graphical Abstract

At present, the management of Phytophthora capsici (P. capsici) mainly relies on chemical pesticides. However, along with the resistance generated by P. capsici to these chemical pesticides, the toxicity and non-degradability of this chemical molecule may also cause serious environmental problems. Herein, a new bio-based nano-antifungal material (CNC@CTAB) was made with coating hexadecyl trimethyl ammonium bromide (CTAB) on the surface of a cellulose nanocrystal (CNC). This material was then applied to the prevention of P. capcisi. This particle was facilely fabricated by mixing CTAB and sulfuric group modified CNC in an aqueous solvent. Compared to pure CTAB, the enrichment of CTAB on the CNC surface showed a better anti-oomycete activity both in vitro and in vivo. When CNC@CTAB was applied on P. capsici in vitro, the inhibition rate reached as high as 100%, while on the pepper leaf, the particle could also efficiently prevent the infection of P. capsici, and achieve a disease index as low as zero Thus, considering the high safety of CNC@CTAB in agricultural applications, and its high anti-oomycete activity against P. capsici, we believe that this CNC@CTAB has great application potential as a new green nano-fungicide in P. capsici management during the production of peppers or other vegetables.

Objective This study aims to investigate the differences in electroencephalogram (EEG) microstates and power spectrum between patients with epilepsy (PWE) comorbid with (without) mild cognitive impairment (MCI) and to develop a machine learning model to predict the risk of MCI comorbidity in PWE. Method Participants were classified into PWE comorbid with MCI (EPMCI) and PWE comorbid without MCI (EPNMCI). The microstate parameters and power spectral density (PSD) of both groups were compared. We combined different types of variables and constructed models using Support Vector Machine (SVM), Neural Network (NNET), Random Forest (RF), K-Nearest Neighbors (KNN), and Naive Bayes (NB). An ideal predictive model was selected to evaluate the risk of MCI comorbidity in PWE. Result A total of 627 PWE were included in this study, of whom 106 had MCI and 521 did not. Significant differences were observed between the two groups of patients in microstates A, B, C, D, and PSD. Among various machine learning models and multiple variable groups, we selected the NNET model based on microstate variables as the optimal model. It demonstrated the second-highest ROCAUC value (0.93), the highest accuracy (0.89), the lowest standard error (0.11), and superior calibration metrics, including the highest discrimination index (D = 0.724), the lowest Brier score (0.084), and the smallest unreliability index (U = 0.006). Finally, we compared this model with the traditional MMSE decision curve analysis (DCA) and found that it exhibited a wider range of applicable thresholds and a greater overall net benefit, demonstrating enhanced clinical utility. Conclusion Differences in EEG microstates analysis and spectral analysis provide evidence for the mechanisms and dynamic changes associated with epilepsy comorbid with MCI. The development of a predictive model offers guidance for the assessment of MCI in specific populations with epilepsy.