The association between serum S100ß levels and prognosis in acute stroke patients after intravenous thrombolysis: a multicenter prospective cohort study.

BACKGROUND: S100ß is a biomarker of astroglial damage, the level of which is significantly increased following brain injury. However, the characteristics of S100ß and its association with prognosis in patients with acute ischemic stroke following intravenous thrombolysis (IVT) remain unclear. METHODS: Patients in this multicenter prospective cohort study were prospectively and consecutively recruited from 16 centers. Serum S100ß levels were measured 24 h after IVT. National Institutes of Health Stroke Scale (NIHSS) and hemorrhagic transformation (HT) were measured simultaneously. NIHSS at 7 days after stroke, final infarct volume, and modified Rankin Scale (mRS) scores at 90 days were also collected. An mRS score ≥ 2 at 90 days was defined as an unfavorable outcome. RESULTS: A total of 1072 patients were included in the analysis. The highest S100ß levels (> 0.20 ng/mL) correlated independently with HT and higher NIHSS at 24 h, higher NIHSS at 7 days, larger final infarct volume, and unfavorable outcome at 3 months. The patients were divided into two groups based on dominant and non-dominant stroke hemispheres. The highest S100ß level was similarly associated with the infarct volume in patients with stroke in either hemisphere (dominant: ß 36.853, 95% confidence interval (CI) 22.659-51.048, P < 0.001; non-dominant: ß 23.645, 95% CI 10.774-36.516, P = 0.007). However, serum S100ß levels at 24 h were more strongly associated with NIHSS scores at 24 h and 3-month unfavorable outcome in patients with dominant hemisphere stroke (NIHSS: ß 3.470, 95% CI 2.392-4.548, P < 0.001; 3-month outcome: odds ratio (OR) 5.436, 95% CI 2.936-10.064, P < 0.001) than in those with non-dominant hemisphere stroke (NIHSS: ß 0.326, 95% CI  - 0.735-1.387, P = 0.547; 3-month outcome: OR 0.882, 95% CI 0.538-1.445, P = 0.619). The association of S100ß levels and HT was not significant in either stroke lateralization group. CONCLUSIONS: Serum S100ß levels 24 h after IVT were independently associated with HT, infarct volume, and prognosis in patients with IVT, which suggests the application value of serum S100ß in judging the degree of disease and predicting prognosis.

HNRNPC mediates lymphatic metastasis of cervical cancer through m6A-dependent alternative splicing of FOXM1.

Cervical cancer (CCa) patients with lymph node (LN) metastasis face poor prognoses and have limited treatment options. Aberrant N6-methyladenosine (m6A) modification of RNAs are known to promote tumor metastasis, but their role in CCa remains unclear. Our study reveals that HNRNPC, an alternative splicing (AS) factor and m6A reader, increases tumor-related variants through m6A-dependent manner, thereby promoting lymphatic metastasis in CCa. We found that HNRNPC overexpression correlates with lymphatic metastasis and poorer prognoses in CCa patients. Functionally, knocking down HNRNPC markedly inhibited the migration and invasion of several CCa cell lines, while supplementing HNRNPC restored the malignant phenotypes of these cells. Mechanistically, HNRNPC regulates exon skipping of FOXM1 by binding to its m6A-modified motif. Mutating the m6A site on FOXM1 weakened the interaction between HNRNPC and FOXM1 pre-RNA, leading to a reduction in the metastasis-related FOXM1-S variant. In conclusion, our findings demonstrate that m6A-dependent alternative splicing mediated by HNRNPC is essential for lymphatic metastasis in CCa, potentially providing novel clinical markers and therapeutic strategies for patients with advanced CCa.

Increased peripheral leukocyte aggravates brain injury and leads to poor outcome in stroke patients receiving intravenous thrombolysis: A study based on clinical evidence.

Whether the dynamic development of peripheral inflammation aggravates brain injury and leads to poor outcome in stroke patients receiving intravenous thrombolysis (IVT), remains unclear and warrants further study. In this study, total of 1034 patients with acute ischemic stroke who underwent IVT were enrolled. Serum leukocyte variation (whether increase from baseline to 24 h after IVT), National Institutes of Health Stroke Scale (NIHSS), infarct volume, early neurologic deterioration (END), the unfavorable outcome at 3-month (modified Rankin Scale [mRS] score ≥3) and mortality were recorded. Serum brain injury biomarkers, including Glial fibrillary acidic protein (GFAP), ubiquitin c-terminal hydrolase L1 (UCH-L1), S100ß, neuron-specific enolase (NSE), were measured to reflect the extent of brain injury. We found that patients with increased serum leukocytes had elevated brain injury biomarkers (GFAP, UCH-L1, and S100ß), larger infarct volume, higher 24 h NIHSS, higher proportion of END, unfavorable outcome and mortality. Furthermore, an increase in serum leukocytes was independently associated with infarct volume, 24 h NIHSS, END, and unfavorable outcome at 3 months, and serum UCH-L1, S100ß, and NSE levels. These results suggest that an increase in serum leukocytes indicates severe brain injury and may be used to predict the outcome of patients with ischemic stroke who undergo IVT.

Butylphthalide mitigates traumatic brain injury by activating anti-ferroptotic AHR-CYP1B1 pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Increasing evidence suggests that ferroptosis, an iron-dependent form of cell death characterized by lipid peroxidation, may play a substantial role in the traumatic brain injury (TBI) pathophysiology. 3-n-butylphthalide (NBP), a compound extracted from the seeds of Apium graveolens Linn (Chinese celery) and used in China to treat ischemic stroke, has demonstrated encouraging anti-reactive oxygen species (ROS) effects. Ascertaining whether NBP can inhibit ferroptosis and its mechanism could potentially expand its use in models of neurological injury and neurodegenerative diseases. METHODS AND RESULTS: In this study, we used erastin-induced in vitro ferroptosis models (HT22 cells, hippocampal slices, and primary neurons) and an in vivo controlled cortical impact mouse model. Our study revealed that NBP administration mitigated erastin-induced death in HT-22 cells and decreased ROS levels, lipid peroxidation, and mitochondrial superoxide indicators, resulting in mitochondrial protection. Moreover, the ability of NBP to inhibit ferroptosis was confirmed in organotypic hippocampal slice cultures and a TBI mouse model. NBP rescued neurons, inhibited microglial activation, and reduced iron levels in the brain tissue. The protective effect of NBP can be partly attributed to the inhibition of the AHR-CYP1B1 axis, as evidenced by RNA-seq and CYP1B1 overexpression/inhibition experiments in HT22 cells and primary neurons. CONCLUSIONS: Our study underscores that NBP inhibition of the AHR-CYP1B1 axis reduces ferroptosis in neuronal damage and ameliorates brain injury.

Detecting emerald ash borer boring vibrations using an encoder-decoder and improved DenseNet model.

BACKGROUND: Forest ecosystems are under constant threat from wood-boring pests such as the Emerald ash borer (EAB), which remain elusive owing to their hidden life cycles within tree trunks. Early detection is vital to mitigate economic and ecological damage. The main current monitoring method is manual detection which is ineffective at early stages of infestation. This study introduces VibroEABNet, a deep learning-based joint recognition network designed to enhance the detection of EAB boring vibration signals, with a novel approach integrating denoising and recognition modules. RESULTS: The proposed VibroEABNet model demonstrated exceptional performance, achieving an average accuracy of 98.98% across multiple signal-to-noise ratios (SNRs) in test datasets and a remarkable 97.5% accuracy in real forest datasets, surpassing traditional models and other deep learning networks evaluated in this study. These findings were supported by rigorous noise resistance analysis and real dataset evaluation, indicating the model's robustness and reliability in practical applications. Furthermore, the model's efficiency was highlighted by its inference time of 26 ms and a compact model size of 8.43 MB, underscoring its suitability for deployment in resource-limited environments. CONCLUSION: The development of VibroEABNet marks a significant advancement in pest detection methodologies, offering a scalable, accurate and efficient solution for early monitoring of wood-boring pests. The integration of a denoising module within the network structure addresses the challenge of environmental noise, one of the primary limitations in acoustic monitoring of pests. Currently, this research is limited to a specific pest. Future work will focus on the applicability of this network to other wood-boring pests. © 2024 Society of Chemical Industry.

Bulk Photovoltaic Effect in High-Temperature Lead-Halide Molecular Ferroelectric [C4N2H14][PbI4].

Hybrid organic-inorganic molecular ferroelectrics (HOIMFs) have garnered significant attention owing to their potential applications in optoelectronic and spintronic devices. However, HOIMFs with high Curie temperature (Tc), narrow bandgap (Eg), excellent stability, and high breakdown voltage are still very rare. Herein, we present a novel lead-halide molecular ferroelectric, (1,4-butanediammonium)PbI4 (1), synthesized hydrothermally. 1 exhibits a ferroelectric-to-paraelectric phase transition with a high Curie temperature of 485 K, a room temperature ferroelectric hysteresis loop with a robust saturation polarization of 3.9 µC/cm2 and strong coercivity of 33 kV/cm, and a typical semiconductor behavior with a direct bandgap of 2.28 eV. Switchable photovoltaic effect was observed in 1-based device with a fast response time of ∼2 ms and high breakdown electric field of 80 kV/cm. Dramatically enhanced photovoltaic performance has been achieved by manipulating the ferroelectric polarization, resulting in a maximum photovoltage of Voc ∼ 0.84 V and a photocurrent of Jsc ∼ 33.31 nA/cm2 under standard AM 1.5 G illumination. This study offers a bright avenue for advancing high-Tc lead-halide molecular ferroelectrics with promising potentials in photodetectors, data storage, and logical switching devices.

Accelerated hydrolytic degradation of poly(l-lactide) by blending with poly(ether-block-amide).

A continuing challenge in the most common biodegradable polyester of poly(l-lactide) (PLLA) is to improve the degradation rate in the environment, though it has been widely used in packaging and medical applications. In this study, PLLA/poly(ether-block-amide) (PEBA) blends are prepared by melt blending to investigate the effect of PEBA component on the phase morphology, thermal behavior, mechanical properties, and hydrolytic degradation of the blends. The incorporation of PEBA component is beneficial to the improved toughness and increased water absorption of the blends, and accelerated hydrolytic degradation of PLLA. The blend exhibits the optimal mechanical and hydrolytic degradation properties when the blend mass ratio of PLLA/PEBA is 80/20. The toughness of the blend is increased by 390 % compared to that of pure PLLA. After being hydrolyzed at 58 °C for 240 h, the water absorption, the mass loss and the decrease of molecular weight of the blend is increased by 138 %, 160 % and 40 %, respectively, indicating faster hydrolytic degradation rate of the blend than that of pure PLLA. Furthermore, the accelerated hydrolytic degradation mechanism of PLLA in the blend is revealed. The amorphous region of PLLA is hydrolyzed initially at the phase interface of the blend, and subsequently the crystalline structure of PLLA is degraded. The hydrolysis process causes a change in the relative content of crystalline regions in the system, resulting in an increase in crystallinity of PLLA first and then decrease. These findings provide a new strategy for the design of novel degradable PLLA materials for practical applications.

Semantic-Aware Message Broadcasting for Efficient Unsupervised Domain Adaptation.

Vision transformer has demonstrated great potential in abundant vision tasks. However, it also inevitably suffers from poor generalization capability when the distribution shift occurs in testing (i.e., out-of-distribution data). To mitigate this issue, we propose a novel method, Semantic-aware Message Broadcasting (SAMB), which enables more informative and flexible feature alignment for unsupervised domain adaptation (UDA). Particularly, we study the attention module in the vision transformer and notice that the alignment space using one global class token lacks enough flexibility, where it interacts information with all image tokens in the same manner but ignores the rich semantics of different regions. In this paper, we aim to improve the richness of the alignment features by enabling semantic-aware adaptive message broadcasting. Particularly, we introduce a group of learned group tokens as nodes to aggregate the global information from all image tokens, but encourage different group tokens to adaptively focus on the message broadcasting to different semantic regions. In this way, our message broadcasting encourages the group tokens to learn more informative and diverse information for effective domain alignment. Moreover, we systematically study the effects of adversarial-based feature alignment (ADA) and pseudo-label based self-training (PST) on UDA. We find that one simple two-stage training strategy with the cooperation of ADA and PST can further improve the adaptation capability of the vision transformer. Extensive experiments on DomainNet, OfficeHome, and VisDA-2017 demonstrate the effectiveness of our methods for UDA.

METTL3/IGF2BP1 influences the development of non-small-cell lung cancer by mediating m6A methylation modification of TRPV1.

BACKGROUND: Methyltransferase 3 (METTL3) accelerates N6-methyladenosine (m6A) modifications and affects cancer progression, including non-small-cell lung cancer (NSCLC). In this study, we aimed to explore the regulatory mechanisms of METTL3 underling NSCLC. METHODS: Immunohistochemical assay, quantitative real-time polymerase chain reaction (qRT-PCR) assay, and western blot assay were conducted for gene expression. MTT assay and colony formation assay were performed to explore cell proliferation capacity. Cell apoptosis and THP-1 cell polarization were estimated by flow cytometry analysis. Cell migration and invasion capacities were evaluated by transwell assay. Methylated RNA immunoprecipitation assay, dual-luciferase reporter assay, actinomycin D treatment and RIP assay were performed to analyze the relationships of METTL3, insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1), and transient receptor potential cation channel subfamily V member 1 (TRPV1). The functions of METTL3 and TRPV1 in vivo were investigated through establishing the murine xenograft model. RESULTS: TRPV1 expression was upregulated in NSCLC and related poor prognosis. TRPV1 silencing inhibited NSCLC cell growth and metastasis, induced NSCLC cell apoptosis, and repressed M2 macrophage polarization. The results showed that METTL3 and IGF2BP1 could regulate TRPV1 expression through m6A methylation modification. Moreover, METTL3 deficiency inhibited NSCLC cell growth, metastasis, and M2 macrophage polarization and facilitated NSCLC cell apoptosis, while TRPV1 overexpression restored the impacts. In addition, METTL3 knockdown restrained tumor growth in vivo via regulating TRPV1 expression. CONCLUSION: METTL3 bound to IGF2BP1 and enhanced IGF2BP1's m6A recognition of TRPV1 mRNA, thereby promoting NSCLC cell growth and metastasis, and inhibiting M2 macrophage polarization.

The association between ferritin levels and all-cause mortality in stroke patients.

Purpose: The purpose of study was to describe the association between ferritin and all-cause mortality of cases with stroke. Methods: Clinical data derived from Multiparameter Intelligent Monitoring in Intensive Care were analyzed. The primary endpoint was 30-day mortality. The potential prognostic roles of Ferritin L were analyzed by Cox proportional hazard models. The independent prognostic roles of Ferritin L in the cases were analyzed by smooth curve fitting. Results: Concerning 30-day mortality, the HR (95% CI) for a high Ferritin (≥373) was 1.925 (1.298, 2.854; p = 0.00113), compared to a low ferritin (< 373). After adjusting for multiple confounders, the HR (95% CI) for a high Ferritin (≥373) was 1.782 (1.126, 2.820; p = 0.01367), compared to a low Ferritin (< 373). A non-linear association between Ferritin and 30-day mortality was found. Using recursive algorithm and two-piecewise linear regression model, inflection point (IP) was calculated, which was 2,204. On the left side of the IP, there was a positive relationship between Ferritin and 30-day mortality, and the effect size, 95% CI and p value were 1.0006 (1.0004, 1.0009) p < 0.0001, respectively. On the right of the IP, the effect size, 95% CI and p value were 1.0000 (1.0000, 1.0000) and 0.3107, respectively. Conclusion: Ferritin was associated with increased risk of stroke; it is important to further examine the association if the increased uric acid would increase the outcome of stroke in a longitudinal study. The non-linear relationship between Ferritin and all-cause mortality of stroke was observed. Ferritin was a risk factor for the outcome of stroke when ferritin was <2204.

Active ingredient identification and purification of organosilicon spray adjuvant and its uptake and translocation in rice (Oryza sativa L.).

The assessment of residue, absorption, conduction, and degradation of agricultural organosilicon surfactants in the environment is hindered by the lack of information on active ingredients and corresponding quantitative standards for organosilicon spray adjuvants. The spray adjuvant 'Jiexiaoli,' a primary organosilicon spray agent in China, was identified as hydroxy (polyethylene) propyl-heptamethyl trisiloxane (TSS-H) with 3-15 ethoxy (EO) groups. Purification of TSS-H was achieved through semi-preparative separation using high-performance liquid chromatography (HPLC), resulting in TSS-H purity exceeding 96%. An accurate residual detection method for nine oligomers (4-12 EO) of TSS-H in rice roots, stems, leaves, and culture solution samples was developed using HPLC tandem high-resolution mass spectrometry (HPLC-HRMS). Recoveries for nine oligomers of TSS-H in the four matrices ranged from 80.22% to 104.01%. Foliar application experiments demonstrated that TSS-H did not transfer from the upper to the lower parts of the rice plant. The half-lives of each oligomer (4-12 EO) in leaves were less than 3.21 days. Root application experiments revealed a root concentration factor (RCF) ranging from 0.20 to 0.56, a biological enrichment factor (BCF) ranging from 0.36 to 0.68, a transpiration factor (TSCF) ranging from 0.069 to 0.086, and a transport factor (TF) ranging from 0.08 to 0.43. These results indicated that TSS-H could be absorbed by rice roots and conducted to the above-ground parts of rice plants. This study fills the data gap in the environmental risk and food safety assessment of agricultural silicone spray adjuvants. © 2024 Society of Chemical Industry.

A Time-Frequency Domain Mixed Attention-Based Approach for Classifying Wood-Boring Insect Feeding Vibration Signals Using a Deep Learning Model.

Wood borers, such as the emerald ash borer and holcocerus insularis staudinger, pose a significant threat to forest ecosystems, causing damage to trees and impacting biodiversity. This paper proposes a neural network for detecting and classifying wood borers based on their feeding vibration signals. We utilize piezoelectric ceramic sensors to collect drilling vibration signals and introduce a novel convolutional neural network (CNN) architecture named Residual Mixed Domain Attention Module Network (RMAMNet).The RMAMNet employs both channel-domain attention and time-domain attention mechanisms to enhance the network's capability to learn meaningful features. The proposed system outperforms established networks, such as ResNet and VGG, achieving a recognition accuracy of 95.34% and an F1 score of 0.95. Our findings demonstrate that RMAMNet significantly improves the accuracy of wood borer classification, indicating its potential for effective pest monitoring and classification tasks. This study provides a new perspective and technical support for the automatic detection, classification, and early warning of wood-boring pests in forestry.

Microbiota-microglia crosstalk between Blautia producta and neuroinflammation of Parkinson's disease: A bench-to-bedside translational approach.

Parkinson's disease (PD) is intricately linked to abnormal gut microbiota, yet the specific microbiota influencing clinical outcomes remain poorly understood. Our study identified a deficiency in the microbiota genus Blautia and a reduction in fecal short-chain fatty acid (SCFA) butyrate level in PD patients compared to healthy controls. The abundance of Blautia correlated with the clinical severity of PD. Supplementation with butyrate-producing bacterium B. producta demonstrated neuroprotective effects, attenuating neuroinflammation and dopaminergic neuronal death in mice, consequently ameliorating motor dysfunction. A pivotal inflammatory signaling pathway, the RAS-related pathway, modulated by butyrate, emerged as a key mechanism inhibiting microglial activation in PD. The change of RAS-NF-κB pathway in PD patients was observed. Furthermore, B. producta-derived butyrate demonstrated the inhibition of microglial activation in PD through regulation of the RAS-NF-κB pathway. These findings elucidate the causal relationship between specific gut microbiota and PD, presenting a novel microbiota-based treatment perspective for PD.

Protein structuromics: A new method for protein structure-function crosstalk in glioma.

Glioma is a type of tumor that starts in the glial cells of the brain or spine. Since the 1800s, when the disease was first named, its survival rates have always been unsatisfactory. Despite great advances in molecular biology and traditional treatment methods, many questions regarding cancer occurrence and the underlying mechanism remain to be answered. In this study, we assessed the protein structural features of 20 oncogenes and 20 anti-oncogenes via protein structure and dynamic analysis methods and 3D structural and systematic analyses of the structure-function relationships of proteins. All of these results directly indicate that unfavorable group proteins show more complex structures than favorable group proteins. As the tumor cell microenvironment changes, the balance of oncogene-related and anti-oncogene-related proteins is disrupted, and most of the structures of the two groups of proteins will be disrupted. However, more unfavorable group proteins will maintain and refold to achieve their correct shape faster and perform their functions more quickly than favorable group proteins, and the former thus support cancer development. We hope that these analyses will help promote mechanistic research and the development of new treatments for glioma.

Malnutrition and cerebral intraparenchymal damage in patients with thrombosis of dural sinuses and/or cerebral veins.

BACKGROUNDS: Thrombosis of dural sinuses and/or cerebral veins (CVT) is an uncommon form of cerebrovascular disease. Malnutrition is common in patients with cerebrovascular disease, and early assessment of malnutrition and individualized nutritional treatment have been reported to improve functional outcomes of these patients. As for CVT patients, little is known about whether these patients would suffer from malnutrition. Also, the correlation between malnutrition and cerebral intraparenchymal damage (CID) in CVT patients was rarely studied. METHODS: Patients with CVT were retrospectively included in this observational study. Multivariate logistic regressions were used to investigate the effects of nutritional indexes on the risk of CID. Subsequently, we used the independent risk factors to construct the nomogram model, and the consistency index (C-index), calibration curve and decision curve analysis (DCA) to assess the reliability and applicability of the model. RESULTS: A total of 165 patients were included in the final analysis. Approximately 72.7% of CVT patients were regarded as malnourished by our malnutrition screening tools, and malnutrition is associated with an increased risk of CID. Prognostic Nutritional Index (PNI) (OR = 0.873; CI: 0.791, 0.963, p = 0.007) remained as an independent predictor for CID after adjustment for other risk factors. The nomogram model showed that PNI and gender have a great contribution to prediction. Besides, the nomogram model was consistent with the actual observations of CID risk (C-index = 0.65) and was of clinical significance. CONCLUSIONS: We reported that malnutrition, as indicated by PNI, was associated with a higher incidence of CID in CVT patients. Also, we have constructed a nomogram for predicting the risk of CID in these patients.

The impact of perceived school climate on exercise behavior engagement among obese adolescents: a dual mediation effect test of exercise benefits and perseverance qualities.

Introduction: This study explores the relationship between perceived school climate and exercise behavior among obese adolescents, as well as the multiple mediating effects of perseverance qualities and exercise benefits. Methods: A survey was conducted on 586 obese adolescents in Beijing, with an age range of 13-18 years old and an average age of 15.40 ± 1.824, among who 337 were male, 249 were female, 303 were high school students and 238 were middle school students. A standard scale was used to evaluate perceived school climate, exercise benefits, perseverance qualities, and exercise behaviors. The data was analyzed by independent samples t-test, bivariate correlation analysis, descriptive statistical analysis, and structural equation model (SEM). Results: (1) Perceived school climate among obese adolescents positively predicted exercise behavior (Z = 2.870, p < 0.01), perseverance qualities (Z = 3.107, p < 0.01) and exercise benefits (Z = 4.290, p < 0.001); perseverance qualities positively predicted exercise behavior in obese adolescents (Z = 4.431, p < 0.001); exercise benefits positively predicted the obese adolescents' exercise behavior (Z = 4.267, p < 0.001). (2) Perseverance qualities (Z = 2.282, 95% CI [0.032, 0.191], [0.028, 0.179]) and exercise benefits (Z = 2.518, 95% CI [0.060, 0.287], [0.053, 0.271]) play a mediating role in the obese adolescents' perceived school climate and exercise behavior, respectively. These two factors have parallel multiple mediating effects between obese adolescents' perceived school climate and exercise behavior, with mediating effects accounting for 16 and 25%, respectively. The mediating effect of exercise benefits is greater than that of perseverance qualities. (3) There is no difference in the specific indirect effects of perseverance qualities and exercise benefits (Z = -0.800, 95% CI [- 0.198, 0.064], [-0.190, 0.068]). Conclusion: Obese adolescents' perception of school climate can effectively enhance their motivation to participate in exercise behavior and indirectly influence exercise behavior through exercise benefits and perseverance qualities, cultivate good physical exercise behavior among obese adolescents, and effectively prevent and intervene in the occurrence of obesity.

Fecal microbiota transplantation inhibited neuroinflammation of traumatic brain injury in mice via regulating the gut-brain axis.

Introduction: Recent studies have highlighted the vital role of gut microbiota in traumatic brain injury (TBI). Fecal microbiota transplantation (FMT) is an effective means of regulating the microbiota-gut-brain axis, while the beneficial effect and potential mechanisms of FMT against TBI remain unclear. Here, we elucidated the anti-neuroinflammatory effect and possible mechanism of FMT against TBI in mice via regulating the microbiota-gut-brain axis. Methods: The TBI mouse model was established by heavy object falling impact and then treated with FMT. The neurological deficits, neuropathological change, synaptic damage, microglia activation, and neuroinflammatory cytokine production were assessed, and the intestinal pathological change and gut microbiota composition were also evaluated. Moreover, the population of Treg cells in the spleen was measured. Results: Our results showed that FMT treatment significantly alleviated neurological deficits and neuropathological changes and improved synaptic damage by increasing the levels of the synaptic plasticity-related protein such as postsynaptic density protein 95 (PSD-95) and synapsin I in the TBI mice model. Moreover, FMT could inhibit the activation of microglia and reduce the production of the inflammatory cytokine TNF-α, alleviating the inflammatory response of TBI mice. Meanwhile, FMT treatment could attenuate intestinal histopathologic changes and gut microbiota dysbiosis and increase the Treg cell population in TBI mice. Conclusion: These findings elucidated that FMT treatment effectively suppressed the TBI-induced neuroinflammation via regulating the gut microbiota-gut-brain axis, and its mechanism was involved in the regulation of peripheral immune cells, which implied a novel strategy against TBI.

SPAG5 Expression Predicts Poor Prognosis and is Associated With Adverse Immune Infiltration in Lung Adenocarcinomas.

Background: Sperm-associated antigen 5 (SPAG5) has been identified as a novel driver oncogene involved in multiple cancers; however, its role in lung adenocarcinoma (LUAD) needs further investigation. Our study aims to elucidate the potential significance of SPAG5 in LUAD prognosis and its implications for the efficacy of immunotherapy. Methods: In this study, we used bioinformatics analysis and tissue microarray (TMA) staining to examine the potential role of SPAG5 in LUAD survival and response to immunotherapy. We used the Oncomine, TIMER2.0, Gene Expression Profiling Interactive Analysis (GEPIA), Sangerbox, PredicScan, and Kaplan-Meier Plotter databases to examine the expression and prognostic role of SPAG5 in the LUAD of The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and other databases. We also used Cancer Single-cell State Atlas (CancerSEA) and Tumor Immune Estimation Resource (TIMER2.0) to analyze the association of SPAG5 with malignant phenotype and tumor immune microenvironment. Furthermore, Immune Cell Abundance Identifier (ImmuCellAI) analysis of TCGA sequencing data was used to predict the role of SPAG5 in determining the response to immune checkpoint blockade (ICB) treatment in LUAD. Co-expression analysis of programmed death-ligand 1 (PD-L1) and SPAG5 was performed using LUAD TMA immunohistochemistry (IHC) analysis. Results: Our findings indicate that SPAG5 is overexpressed in LUAD and is positively correlated with advanced clinical stage, poor overall survival, relapse-free survival, and progression-free survival outcomes. SPAG5 may be involved in regulating the cell cycle, proliferation, invasion, DNA damage and repair, and tumor immunosuppression. Furthermore, TMA IHC analysis showed a positive correlation between PD-L1 expression in LUAD and SPAG5 which suggests that SPAG5 may serve as a potential predictor of response to ICB therapy in LUAD. Conclusions: Our results highlight the role of SAPG5 in promoting a tumor malignancy phenotype and immunosuppression in LUAD and suggest that SPAG5 may serve as a potential response marker for ICB therapy.

The Influence of Patent Foramen Ovale on the Clinical Features of Migraine without Aura: A Cross-Sectional Study.

Objective: To investigate the influence of patent foramen ovale (PFO) on the clinical features of migraine without aura (MoA). Methods: We consecutively enrolled 390 MoA patients and compared the frequency of headache, episode duration, and the Visual Analogue Scale (VAS), Headache Impact Test 6 (HIT-6), and European Health Interview Survey-Quality of Life 8-item index (EUROHIS-QOL8) scores of patients with and without PFO, those with the mild right-to-left shunt (RLS) and moderate to large RLS, and those with permanent RLS and latent RLS using a nonparametric Mann-Whitney U-test. In addition, we analyzed the clinical features of migraine in 39 MoA patients before and after PFO closure treatment using the paired Wilcoxon test. Results: The prevalence of PFO in the 390 MoA patients was 44.4%. Patients with PFO had significantly higher frequency of headaches, VAS scores, HIT-6 scores, and incidence of white matter lesions than those without PFO (all p< 0.05). Patients with moderate to large RLS had significantly higher VAS scores than those with mild RLS (p = 0.002). Additionally, 39 MoA patients underwent PFO closure, which remarkably decreased their frequency of headache, episode duration, VAS scores, and HIT-6 scores, and increased their EUROHIS-QOL8 scores. Conclusion: The migraine features in MoA patients could be influenced by PFO, especially in patients with moderate to large shunt, in whom PFO closure improved the symptoms.

Classification of Camellia oleifera Diseases in Complex Environments by Attention and Multi-Dimensional Feature Fusion Neural Network.

The use of neural networks for plant disease identification is a hot topic of current research. However, unlike the classification of ordinary objects, the features of plant diseases frequently vary, resulting in substantial intra-class variation; in addition, the complex environmental noise makes it more challenging for the model to categorize the diseases. In this paper, an attention and multidimensional feature fusion neural network (AMDFNet) is proposed for Camellia oleifera disease classification network based on multidimensional feature fusion and attentional mechanism, which improves the classification ability of the model by fusing features to each layer of the Inception structure and enhancing the fused features with attentional enhancement. The model was compared with the classical convolutional neural networks GoogLeNet, Inception V3, ResNet50, and DenseNet121 and the latest disease image classification network DICNN in a self-built camellia disease dataset. The experimental results show that the recognition accuracy of the new model reaches 86.78% under the same experimental conditions, which is 2.3% higher than that of GoogLeNet with a simple Inception structure, and the number of parameters is reduced to one-fourth compared to large models such as ResNet50. The method proposed in this paper can be run on mobile with higher identification accuracy and a smaller model parameter number.