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Foundational neuroscience is crucial to locating lesions, understanding current functional limitations, making correct prognoses, and designing holistic and realistic treatment plans for stroke patients. A model bridging neuroscience knowledge and clinical practice was assessed through a rare pontine infarction case. A 76-year-old patient suffered two consecutive right-sided pontine ischemic strokes, leading to significant motor and sensory abnormalities on the left side. After the strokes stabilized, the patient was admitted to Knoxville Rehabilitation Hospital on August 10, 2023, under an intensive rehabilitation program grounded in neuroscience-based principles of plasticity. Remarkably, the patient fully recovered sensation by August 17. The clinical presentations, which included no ipsilateral cranial nerve dysfunction but the contralateral compromise of cranial nerves V and VII, indicated lesions in the right middle to caudal basilar pons. Employing available brainstem motor control systems, including reticulospinal and vestibulospinal tracts, the rehabilitation team designed a task-oriented, realistic neuroplasticity program to focus on gross motor skills such as postural control, bed mobility, transfers, walking, and stair negotiation, dynamically adjusted daily according to the patient's progress, while waiting for the recovery of corticospinal tract. The patient successfully improved from varied levels of assistance to independently performing all tasks except stair negotiation, which required supervision due to safety concerns, possibly resulting from past silent cerebrovascular problems. The patient was discharged home on August 29 after demonstrating significant functional recovery. This study highlights leveraging foundational neuroscience knowledge to accelerate recovery and quickly improve stroke rehabilitation outcomes.

PURPOSE: Dry needling (DN) is increasingly included in Doctor of Physical Therapy (DPT) curricula, yet standardized education integrating functional anatomy and clinical reasoning is limited. This study evaluated the impact of an intensive, anatomy-based DN elective on students' perceived knowledge, confidence, clinical skills, and pain relief. METHODS: Thirteen third-year DPT students completed a pre-post study involving a DN course that combined functional anatomy instruction, hands-on practice, and case-based learning. Outcomes included self-reported knowledge and confidence (via Likert-scale surveys), clinical competence (Objective Structured Clinical Examination, OSCE), and open-ended feedback. Quantitative data were analyzed using paired t-tests and effect sizes. RESULTS: Students reported significant gains in knowledge and confidence post-course (p < 0.01; Cohen's d = 1.4-2.8). Among those with pre-existing pain, DN reduced symptoms by an average of 65%. Qualitative feedback highlighted strong satisfaction with course content and clinical applicability. All students passed the OSCE, though one demonstrated lower anatomy knowledge and confidence. CONCLUSION: A focused, anatomy-integrated DN course enhanced DPT students' perceived clinical preparedness and skill. Embedding functional anatomy and clinical reasoning into DN education may support skill development and inform multimodal strategies in physical therapy training.

The c-Myb, A-Myb and B-Myb transcription factors have nearly identical DNA-binding domains, activate the same reporter gene constructs in animal cells, but have different biological roles. The Myb proteins are often coexpressed in the same cells, raising questions about whether they activate similar or distinct gene expression profiles, and whether they cooperate or compete in regulating the same promoters. Here, recombinant adenoviruses were used to express each protein in human mammary cells, and then microarray assays were used to assess global changes in gene expression. Each Myb protein induced a unique and specific set of changes, displaying activities far more complex than revealed by standard reporter gene assays. These results have important implications for the roles of various Myb proteins in normal and transformed human cells, for regulatory pathways that might modify their activities and for the importance of acquired mutations that may qualitatively alter their functions in tumors.

Abstract Macrophages are the primary lung phagocyte and are instrumental in maintenance of a sterile, noninflamed microenvironment. IFNs are produced in response to bacterial and viral infection, and activate the macrophage to efficiently counteract and remove pathogenic invaders. Respiratory syncytial virus (RSV) inhibits IFN-mediated signaling mechanisms in epithelial cells; however, the effects on IFN signaling in the macrophage are currently unknown. We investigated the effect of RSV infection on IFN-mediated signaling in macrophages. RSV infection inhibited IFN-β– and IFN-γ–activated transcriptional mechanisms in primary alveolar macrophages and macrophage cell lines, including the transactivation of important Nod-like receptor family genes, Nod1 and class II transactivator. RSV inhibited IFN-β– and IFN-γ–mediated transcriptional activation by two distinct mechanisms. RSV impaired IFN-β–mediated signal transducer and activator of transcription (STAT)-1 phosphorylation through a mechanism that involves inhibition of tyrosine kinase 2 phosphorylation. In contrast, RSV-impaired transcriptional activation after IFN-γ stimulation resulted from a reduction in the nuclear STAT1 interaction with the transcriptional coactivator, CBP, and was correlated with increased phosphorylation of STAT1β, a dominant-negative STAT1 splice variant, in response to IFN-γ. In support of this concept, overexpression of STAT1β was sufficient to repress the IFN-γ–mediated expression of class II transactivator. These results demonstrate that RSV inhibits IFN-mediated transcriptional activation in macrophages, and suggests that paramyxoviruses modulate an important regulatory mechanism that is critical in linking innate and adaptive immune mechanisms after infection.

In order to study the feasibility ofCucumber mosaic virus (CMV) as an expression vector, the full-length cDNA of RNA 3 from strain SD was cloned and the sequence around the start codon of the coat protein (CP) gene was modified to create anNsi I site for insertion of foreign genes. The CP gene was replaced by the green fluorescent protein (GFP) gene. The cDNAs of Fny RNAs 1 and 2 and the chimeric SD RNA 3 were cloned between the modified 35S promoter and terminator. Tobacco protoplasts were transfected with a mixture of the viral cDNAs containing 35S promoter and terminator as a replacement vector and expressed GFP. A complementation system was established when the replacement vector was inoculated onto the transgenic tobacco plants expressing SD-CMV CP. GFP was detected in the inoculated leaves in 5 of 18 tested plants and in the first upper systemic leaf of one of the 5 plants ten days after inoculation. However, no GFP could be detected in all the plants one month after inoculation. Recombination between the CMV vector and the CP transgene was proved by retro-transcriptional polymerase chain reaction (RT-PCR) and verified by DNA sequencing. Our results argue against the feasibility of the CMV-based replacement vector trans-complemented by the CP transgene, and at the same time, enlighten ways to improve the CMV-based expression vector and the biosafety of CMV CP-mediated virus resistant transgenic plants.

Macrophages are the primary lung phagocyte and are instrumental in maintenance of a sterile, noninflamed microenvironment. IFNs are produced in response to bacterial and viral infection, and activate the macrophage to efficiently counteract and remove pathogenic invaders. Respiratory syncytial virus (RSV) inhibits IFN-mediated signaling mechanisms in epithelial cells; however, the effects on IFN signaling in the macrophage are currently unknown. We investigated the effect of RSV infection on IFN-mediated signaling in macrophages. RSV infection inhibited IFN-beta- and IFN-gamma-activated transcriptional mechanisms in primary alveolar macrophages and macrophage cell lines, including the transactivation of important Nod-like receptor family genes, Nod1 and class II transactivator. RSV inhibited IFN-beta- and IFN-gamma-mediated transcriptional activation by two distinct mechanisms. RSV impaired IFN-beta-mediated signal transducer and activator of transcription (STAT)-1 phosphorylation through a mechanism that involves inhibition of tyrosine kinase 2 phosphorylation. In contrast, RSV-impaired transcriptional activation after IFN-gamma stimulation resulted from a reduction in the nuclear STAT1 interaction with the transcriptional coactivator, CBP, and was correlated with increased phosphorylation of STAT1beta, a dominant-negative STAT1 splice variant, in response to IFN-gamma. In support of this concept, overexpression of STAT1beta was sufficient to repress the IFN-gamma-mediated expression of class II transactivator. These results demonstrate that RSV inhibits IFN-mediated transcriptional activation in macrophages, and suggests that paramyxoviruses modulate an important regulatory mechanism that is critical in linking innate and adaptive immune mechanisms after infection.

Using eight maize varieties （Tiannuo 888, Yunnuo 6, Yunrui 999, Yunrui 6, Yunrui 47, Yunrui 88, Yunyou 105, Yuntianyun 2） as the research ma- terials, this paper aimed to figure out the possible influence caused by repeated drought treatment. A pot experiment was conducted to investigate the changes in 13 phenotypic characters and physiological and biochemical indexes （plant height, fresh mass, root shoot ratio, POD activity, SOD activity） related to drought resist- ante, under two levels of water supply （repeated drought treatment and CK） at seedling stage of maize varieties, and evaluated drought resistanee comprehensively by standard deviation coefficient allocation weighed method. The results showed that the survival rate, leaf area, plant height, shoot fresh mass, root fresh mass, shoot dry mass and root dry mass of seedling maize decreased at varying degrees after repeated drought stress. However, the MDA molality, root shoot ratio, Pro content and soluble protein content increased under repeated drought stress. There were significant difference in morphological, physiological and biochemical inde- xes among different maize varieties. The drought resistances of different maize varieties successively were Yunrui 47 〉 Yuntianyu 2 〉 Yunyou 105 〉 Yunnuo 6 〉 Tianuo 888 〉 Yunrui 6 〉 Yunrui 999 〉 Yunrui 88. These results provide references for maize drought-resistant breeding and maize production.

The Internet of Things applications are diverse in nature, and a key aspect of it is multimedia sensors and devices. These IoT multimedia devices form the Internet of Multimedia Things (IoMT). Compared with the Internet of Things, it generates a large amount of text data with different characteristics and requirements. Aiming at the problems that machine learning and single structure deep learning model cannot effectively grasp the text emotional information in text processing, resulting in poor classification effect, this paper proposes a text classification method of tourism questions based on deep learning model. First, the corpus is trained with word2vec tool based on continuous word bag model to obtain the text word vector representation. Then, the attention mechanism is introduced into the long-short term network (LSTM), and the attention-based LSTM model is constructed for text feature extraction, which highlights the impact of different words in the input text on the text emotion category. Finally, the text features are input into the Softmax classifier to obtain the probability distribution of text categories, and the model is trained combined with the cross entropy loss function. The experimental results show that the average accuracy, recall, and F value are 0.943, 0.867, and 0.903, respectively, which has better classification effect than other methods.

Background Social-emotional competence (SEC) is a critical protective factor for mental health among female graduate students. While cross-sectional research suggests potential associations between physical activity (PA) and SEC development, longitudinal evidence specifically targeting highly educated adult females remains scarce, hindering the design of tailored interventions. This study investigated the longitudinal effects of PA on SEC among Chinese female graduate students and elucidated the underlying mechanisms. Methods A three-wave longitudinal panel design with a 9-month follow-up was employed. Using cluster random sampling, female graduate students (master’s or doctoral level; ≥18 years) from 68 “Double First-Class” universities were recruited. The final sample consisted of 860 participants who completed all three waves. Assessment tools included the International Physical Activity Questionnaire-Short Form (IPAQ-SF), the Body Esteem Scale for Adolescents and Adults (BESAA), and the Delaware Social-Emotional Competency Scale-Short (DSECS-S). Cross-lagged panel modeling (CLPM) with bootstrapping was utilized to examine longitudinal relationships, mediation, and moderated mediation effects. Results PA exerted sustained positive predictive effects on SEC. Specifically, PA at T1 predicted SEC at T2 (β = 0.264, p  < 0.001), and PA at T2 predicted SEC at T3 (β = 0.229, p  < 0.001). Body esteem significantly mediated this relationship (indirect effect β = 0.074, 95% CI: 0.055–0.096). Furthermore, the upbringing environment (urban vs. rural) significantly moderated the mediation pathway; specifically, the beneficial effects were more pronounced for rural participants(β = 0.103) than for their urban counterparts(β = 0.057), with a moderated mediation index of 0.045 (95% CI: 0.005–0.087). Conclusions Regular PA consistently promotes SEC development in female graduate students by enhancing body esteem, with stronger effects observed among those from rural backgrounds. These findings offer a scientific basis for designing differentiated campus-based PA interventions. Specifically, programs should integrate PA with body-esteem enhancement and implement stratified strategies tailored to upbringing environments to optimize mental health outcomes for this population.

As one of the most predominant interannual variabilities, the Indian Ocean Dipole (IOD) exerts great socio-economic impacts globally, especially on Asia, Africa, and Australia. While enormous efforts have been made since its discovery to improve both climate models and statistical methods for better prediction, current skills in IOD predictions are mostly limited up to three months ahead. Here, we challenge this long-standing problem using a multi-task deep learning model that we name MTL-NET. Hindcasts of the IOD events during the past four decades indicate that the MTL-NET can predict the IOD well up to 7-month ahead, outperforming most of world-class dynamical models used for comparison in this study. Moreover, the MTL-NET can help assess the importance of different predictors and correctly capture the nonlinear relationships between the IOD and predictors. Given its merits, the MTL-NET is demonstrated to be an efficient model for improved IOD prediction. A multi-task learning model is proposed to improve seasonal-to-annual prediction of the Indian Ocean Dipole (IOD). This model captures the inter-basin interactions between ENSO and IOD and distinctive precursors of positive and negative IOD events.