ObjectiveTo identify the pathogen species responsible for the wilt disease of Tetradium ruticarpum in Chongqing， investigate there biological characteristics， and screen effective fungicides， so as to provide a theoretical basis for disease control in production. MethodsThe pathogen was isolated via the tissue culture method. Pathogenicity was verified according to Koch's postulates. The pathogen was identified based on morphological characteristics and multi-gene phylogenetic analysis. The mycelial growth rate method was used for biological characterization of the pathogen and fungicide screening. ResultsThe pathogen colonies were nearly circular with irregular edges， white， short， velvety aerial hyphae， and pale purple undersides. Macroconidia were colorless， sickle-shaped， with 3-5 septa， while microconidia were transparent， elliptical， aseptate or with 1-2 septa. Multi-gene phylogenetic analysis showed that the pathogen clustered in the same clade as Fusarium fujikuroi with 100% support， which， combined with morphological characteristics， identified the pathogen causing wilt of T. ruticarpum in Chongqing as F. fujikuroi. The optimal conditions for the mycelial growth of F. fujikuroi were mung bean agar （MBA） with glucose as the carbon source， beef extract and yeast powder as nitrogen sources， 28 ℃， pH 7.0， and alternating light/dark conditions. The optimal conditions for sporulation were potato dextrose agar （PDA） with glucose as the carbon source， beef extract as the nitrogen source， 28 ℃， pH 7.0， and complete darkness. Among chemical fungicides， phenazine-1-carboxylic acid exhibited the strongest inhibitory effect on F. fujikuroi. Shenqinmycin and tetramycin were the most effective bio-fungicides. ConclusionThis study is the first to report F. fujikuroi as the causal agent of wilt disease in T. rutaecarpa. The chemical fungicide phenazine-1-carboxylic acid and the bio-fungicides shenqinmycin and tetramycin showed strong inhibitory effects against F. fujikuroi.

Objectives: . The prognostic value of the pretreatment albumin-to-alkaline phosphatase ratio (AAPR) in head and neck cancer (HNC) remains uncertain. This meta-analysis aimed to evaluate the predictive role of AAPR for survival outcomes in patients with HNC. Methods: . A comprehensive search of the Cochrane Library, PubMed, and Embase databases was conducted to identify relevant studies published up to July 30, 2024. We included studies on AAPR and survival outcomes in HNC patients. Results: . Eight studies comprising 1,737 HNC patients were analyzed using random-effects models. Lower AAPR values were significantly correlated with worse overall survival (hazard ratio [HR], 2.08), progression-free survival (HR, 2.00), and disease-free survival (HR, 2.18). Sensitivity analyses confirmed the robustness of these results, with no significant publication bias detected. Conclusion . Our findings suggest that pretreatment AAPR could serve as a valuable and cost-effective prognostic indicator in HNC, potentially aiding clinicians in risk stratification and treatment decision-making. However, additional validation studies are warranted to confirm its clinical applicability.

Objectives: . This study aimed to investigate the regulatory functions of gamma-aminobutyric acid (GABA)ergic neural circuits from the inferior colliculus (IC) to the medial geniculate body (MGB) in salicylate-induced tinnitus. Methods: . Mice were treated with salicylate to induce tinnitus, and tinnitus-like behaviors were evaluated via gap prepulse inhibition of acoustic startle. Using combined viral tracing methodologies, we identified and mapped the pathways and connections from the IC to the MGB. Furthermore, we employed Gq-coupled human M3 designer receptors exclusively activated by designer drugs (DREADDs) and Gi-coupled human M4 DREADDs to achieve targeted excitation or suppression of GABAergic neurons in the IC and MGB. Following the administration of clozapine N-oxide, which binds to these receptors, we modulated these neural circuits to assess their impact on tinnitus severity in a mouse model. Results: . Our findings demonstrated that mice exposed to salicylate exhibited tinnitus-like behaviors. GABAergic neurons projecting retrogradely from the MGB to the IC were primarily concentrated in the external nucleus of the IC. After clozapine N-oxide administration, chemogenetic activation of IC-MGB GABAergic neurons aggravated salicylate-induced tinnitus. Additionally, activation of GABAergic neurons between the IC and MGB induced the perception of tinnitus even without salicylate. However, chemogenetic inhibition of the IC-MGB GABAergic circuit did not reverse salicylate-induced tinnitus. Conclusion . These findings suggest that activation of the IC-MGB GABAergic neural circuit may contribute to tinnitus generation through a mechanism distinct from that of salicylate-induced tinnitus. This study provides novel insights into the mechanisms underlying tinnitus.

Objective To analyze the overall characteristics, research hotspots, and development trends of immune cell-related studies in radiotherapy for rectal cancer. Methods A systematic search was conducted by using Web of Science Core Collection to retrieve articles related to radiation therapy and immune cells in rectal cancer published from 1991 to 2024. Advanced bibliometric tools, such as VOSviewer and CiteSpace, were utilized to facilitate analysis and describe publication trends, geographic contributions, institutional affiliations, journal prominence, author collaboration, and prominent keywords. Results The annual number of relevant publications has increased steadily, showing remarkable growth over the past five years. Studies focusing on adaptive immune cells (T and B cells) account for the largest proportion of works and form the most extensive collaboration networks, reflecting the central role of T cell–mediated antitumor immunity in radiotherapy. Meanwhile, innate immune cells, including myeloid-derived suppressor cells, macrophages, monocytes, and neutrophils, are increasingly investigated for their regulatory roles in shaping the tumor immune microenvironment and influencing therapeutic responses. Among countries, China and the United States have contributed the highest number of publications and demonstrated strong academic influence. While several stable research groups have been formed, intergroup collaboration remains limited. Keyword analysis revealed that radiotherapy-induced immune modulation, tumor immune microenvironment remodeling, and treatment response have emerged as major research hotspots. Conclusion Research on immune cells in rectal cancer radiotherapy has progressed rapidly in recent years. The emphasis of this field has gradually shifted from single-treatment approaches to mechanistic studies investigating the interaction between radiotherapy and the tumor immune microenvironment. The field still demonstrates considerable potential for future research and clinical translational applications.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

ObjectiveTo develop an emotion management course and evaluate its effectiveness in improving emotion regulation, coping strategies, and anxiety and depression among first-year university students, so as to provide a basis for colleges to optimize mental health education courses. MethodsUsing a multi-stage cluster random sampling method, five classes of first-year students (n=169) from a university were randomly selected as participants, with three classes assigned to the experimental group (n=102) and two classes to the control group (n=67). The experimental group attended both the standard mental health education course and the emotion management course developed in this study, while the control group only attended the standard mental health education course. Pre- and post-intervention assessments were conducted using the Emotion Regulation Questionnaire (ERQ), Simplified Coping Style Questionnaire (SCSQ), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS). ResultsBefore the intervention, there were no significant differences between the experimental group and the control group in ERQ, SCSQ, SDS, and SAS scores (P>0.05). After the intervention, the experimental group demonstrated greater improvements than the control group in the ERQ expression inhibition subscale (14.42±5.05, 16.12±5.65), SCSQ positive coping tendency (1.97±0.51, 1.80±0.49) and negative coping tendency (1.26±0.55, 1.47±0.50), as well as in SDS (50.26±11.48, 53.86±8.21) and SAS (43.96±11.97, 47.59±9.50) scores (t value: 2.039, 2.144, 2.572; Z value: -2.214, -2.486; P<0.05). Compared with pre-intervention scores, the experimental group also showed improvements in the ERQ cognitive reappraisal subscale (32.19±5.76, 30.92±6.18), SCSQ positive coping tendency (1.97±0.51, 1.83±0.48), and SDS scores (50.26±11.48, 50.75±11.59) (t value: -2.654, -3.027; Z value: -2.100, P<0.05). ConclusionThe emotion management course effectively enhances students’ use of cognitive reappraisal strategies while reducing reliance on expressive suppression. It also contributes to improvements in coping strategies for life events and alleviates symptoms of depression and anxiety. Universities should consider integrating emotion management education into their curricula to enhance the mental well-being of first-year students.

Invasive fungal infections (IFIs) have become prominent global health threats, escalating the burden on public health systems. The increasing occurrence of invasive fungal infections is due primarily to the extensive application of chemotherapy, immunosuppressive therapies, and broad-spectrum antifungal agents. At present, therapeutic practices utilize multiple categories of antifungal agents, such as azoles, polyenes, echinocandins, and pyrimidine analogs. Nevertheless, the clinical effectiveness of these treatments is progressively weakened by the emergence of drug resistance, thereby substantially restricting their therapeutic utility. Consequently, there is an imperative need to expedite the discovery of novel antifungal agents. This review seeks to present an exhaustive synthesis of novel antifungal drugs and candidate agents that are either under current clinical investigation or anticipated to progress into clinical evaluation. These emerging compounds exhibit unique benefits concerning their modes of action, antimicrobial spectra, and pharmacokinetic characteristics, potentially leading to improved therapeutic outcomes relative to conventional antifungal regimens. It is anticipated that these novel therapeutic agents will furnish innovative treatment modalities and enhance clinical outcomes in managing invasive fungal infections.

OBJECTIVE: Based on the PTEN-induced hypothetical kinase 1 (PINK1)/Parkin pathway, the effect of acupuncture pretreatment on the expression of mitochondrial autophagy-related proteins in gastrocnemius muscle tissue of rats with exercise-induced muscle damage (EIMD) was observed, and the underlying mechanism of acupuncture pretreatment for the prevention and treatment of EIMD was explored. METHODS: Of 88 SD male rats, aged 6 weeks, 8 rats were randomly selected as a blank group, and the remaining 80 rats were randomized into a model group and an acupuncture pretreatment group, with 40 rats in each group. Either the model group or the acupuncture pretreatment group was subdivided randomly into 5 subgroups with 8 rats in each one according to the time points of sample collection, 0 h, 12 h, 24 h, 48 h and 72 h after modeling. An intermittent downhill running centrifugal exercise was carried out on an animal experimental treadmill to establish the EIMD model in the model group and the acupuncture pretreatment group. The rats in the acupuncture pretreatment group received acupuncture at "Guanyuan" (CV6) and bilateral "Zusanli" (ST36), once a day for 20 min each time, for 7 consecutive days before EIMD model preparation. Transmission electron microscopy was used to observe the ultrastructure of gastrocnemius muscle tissue in each group. The contents of malondialdehyde (MDA), superoxide dismutase (SOD) and catalase (CAT) in serum were detected by ELISA. Western blot was used to detect the protein expression of PINK1, Parkin, sequestosome 1 (p62) and microtubule-associated protein light chain 3B (LC3B) in rat gastrocnemius muscle tissue. Real-time PCR was adopted to detect the mRNA expression of PINK1, Parkin, p62 and LC3B in rat gastrocnemius muscle tissue. RESULTS: Compared with the blank group, the mitochondria of gastrocnemius muscles showed obvious swelling in the 0 h, 12 h, 24 h, and 48 h model subgroups , autophagosomes were formed in the 12 h and 24 h model subgroups, and the mitochondrial morphology returned to normal gradually in the 72 h model subgroup. The serum MDA contents of rats in 5 model subgroups increased (P<0.01, P<0.05). The contents of SOD and CAT in the subgroups of 0 h, 12 h, 24 h and 48 h decreased (P<0.05, P<0.01). The protein and mRNA expression levels of PINK1, Parkin and LC3B in gastrocnemius muscle tissue of rats in 0 h, 12 h and 24 h subgroups were elevated (P<0.01); and the protein and mRNA expression levels of p62 in the 0 h, 12 h, 24 h and 48 h subgroups were reduced (P<0.01, P<0.05). Compared with the model subgroup at the same time point, the myofibril damage and the degree of mitochondrial swelling were mild in each acupuncture pretreatment subgroup, and the numbers of autophagosomes were fewer. The contents of MDA in the acupuncture pretreatment subgroups decreased at 0 h, 12 h, 24 h, and 48 h (P<0.05, P<0.01). The contents of SOD and CAT in the 12 h acupuncture pretreatment subgroup increased (P<0.05, P<0.01). The protein and mRNA expression levels of PINK1 and Parkin in the 0 h, 12 h, and 24 h acupuncture pretreatment subgroups decreased (P<0.01, P<0.05). The protein and mRNA expression levels of LC3B in the 12 h acupuncture pretreatment subgroup decreased (P<0.01), and that of p62 in the 0 h and 24 h acupuncture pretreatment subgroups increased (P<0.01, P<0.05). CONCLUSION The intermittent downhill running centrifugal exercise induces the excessive mitochondrial autophagy. Acupuncture pretreatment may attenuate EIMD, and the underlying mechanism is related to the regulation of PINK1/Parkin signaling pathway expression, reducing oxidative stress damage in skeletal muscle cells, and inhibiting mitochondrial autophagy overactivation.
Animals ; Ubiquitin-Protein Ligases/genetics* ; Male ; Rats ; Acupuncture Therapy ; Protein Kinases/genetics* ; Rats, Sprague-Dawley ; Mitophagy ; Humans ; Muscle, Skeletal/metabolism* ; Physical Conditioning, Animal ; Muscular Diseases/physiopathology* ; Signal Transduction

INTRODUCTION: The diagnosis of sarcopenia relies on key indicators such as handgrip strength, walking speed and muscle mass. Developing a composite index that integrates these measures could enhance clinical evaluation in older adults. This study aimed to standardise and combine these metrics to establish a z score for the sarcopenia composite index (ZoSCI) tailored for the ageing population. Additionally, we explore the risk factors associated with ZoSCI to provide insights into early prevention and intervention strategies. METHOD: This retrospective study analysed data between January 2017 and December 2021 from an elderly health programme in Taiwan, applying the Asian Working Group for Sarcopenia criteria to assess sarcopenia. ZoSCI was developed by standardising handgrip strength, walking speed and muscle mass into z scores and integrating them into a composite index. Receiver operating characteristic (ROC) curve analysis was used to determine optimal cut-off values, and multiple regression analysis identified factors influencing ZoSCI. RESULTS: Among the 5047 participants, the prevalence of sarcopenia was 3.7%, lower than the reported global prevalence of 3.9-15.4%. ROC curve analysis established optimal cut-off points for distinguishing sarcopenia in ZoSCI: -1.85 (sensitivity 0.91, specificity 0.88) for males and -1.97 (sensitivity 0.93, specificity 0.88) for females. Factors associated with lower ZoSCI included advanced age, lower education levels, reduced exercise frequency, lower body mass index and creatinine levels. CONCLUSION This study introduces ZoSCI, a new compo-site quantitative indicator for identifying sarcopenia in older adults. The findings highlight specific risk factors that can inform early intervention. Future studies should validate ZoSCI globally, with international collaborations to ensure broader applicability.
Humans ; Sarcopenia/physiopathology* ; Male ; Aged ; Female ; Retrospective Studies ; Hand Strength ; Taiwan/epidemiology* ; ROC Curve ; Aged, 80 and over ; Risk Factors ; Walking Speed ; Geriatric Assessment/methods* ; Prevalence ; Muscle, Skeletal ; Middle Aged

BACKGROUND: Severe stroke has high rates of mortality and morbidity. This study aimed to investigate the clinical course, causes of worsening, and outcomes of severe ischemic stroke. METHODS: This prospective, multicenter cohort study enrolled adult patients admitted ≤30 days after ischemic stroke from nine hospitals in China between September 2017 and December 2019. Severe stroke was defined as a score of ≥15 on the National Institutes of Health Stroke Scale (NIHSS). Clinical worsening was defined as an increase of 4 in the NIHSS score from baseline. Unfavorable functional outcome was defined as a modified Rankin scale score ≥3 at 3 months and 1 year after stroke onset, respectively. We performed Logistic regression to explore baseline features and reperfusion therapies associated with clinical worsening and functional outcomes. RESULTS: Among 4201 patients enrolled, 854 patients (20.33%) had severe stroke on admission. Of 3347 patients without severe stroke on admission, 142 (4.24%) patients developed severe stroke in hospital. Of 854 patients with severe stroke on admission, 33.95% (290/854) experienced clinical worsening (median time from stroke onset: 43 h, Q1-Q3: 20-88 h), with brain edema (54.83% [159/290]) as the leading cause; 24.59% (210/854) of these patients died by 30 days, and 81.47% (677/831) and 78.44% (633/807) had unfavorable functional outcomes at 3 months and 1 year respectively. Reperfusion reduced the risk of worsening (adjusted odds ratio [OR]: 0.24, 95% confidence interval [CI]: 0.12-0.49, P  <0.01), 30-day death (adjusted OR: 0.22, 95% CI: 0.11-0.41, P  <0.01), and unfavorable functional outcomes at 3 months (adjusted OR: 0.24, 95% CI: 0.08-0.68, P <0.01) and 1 year (adjusted OR: 0.17, 95% CI: 0.06-0.50, P  <0.01). CONCLUSIONS: Approximately one-fifth of patients with ischemic stroke had severe neurological deficits on admission. Clinical worsening mainly occurred in the first 3 to 4 days after stroke onset, with brain edema as the leading cause of worsening. Reperfusion reduced the risk of clinical worsening and improved functional outcomes. REGISTRATION ClinicalTrials.gov , NCT03222024.
Humans ; Male ; Female ; Prospective Studies ; Ischemic Stroke/mortality* ; Aged ; Middle Aged ; Aged, 80 and over ; Stroke ; Brain Ischemia