Proteomic Landscape Associated with Cognitive Impairment in Individuals with Long-term Methamphetamine Dependence.

BACKGROUND: Methamphetamine (METH) is a highly addictive drug that directly affects the central nervous system. METH use not only harms the user's health but also poses risks and costs to society. Prolonged METH dependence has been shown to impair cognition, which may be the primary factor in impulsive drug-seeking behaviors and high relapse rates. However, the molecular mechanisms underlying METH addiction and METH-induced cognitive decline remain poorly understood. METHODS: To illuminate the potential molecular mechanisms underpinning METH addiction, we compared serum protein expression levels between 12 long-term METH users and 12 healthy controls using label-free quantitative proteomics. Bioinformatic analyses were conducted to determine functional networks and protein-protein interactions. RESULTS: In total, 23 differentially expressed proteins were identified between the two groups. The differentially expressed proteins were related to cognitive dysfunction, neuroinflammation, immune impairment, metabolic disturbances, and calcium binding and regulation. CONCLUSIONS: These 23 proteins may underpin the multi-system damage induced by chronic METH exposure. Our findings provide novel insights into the molecular basis of METH addiction and inform potential prevention and treatment strategies for individuals with METH dependence.

Hierarchical superstructure aerogels for in situ biofluid metabolomics.

High-throughput biofluid metabolomics analysis for screening life-threatening diseases is urgently needed. However, the high salt content of biofluid samples, which introduces severe interference, can greatly limit the analysis throughput. Here, a new 3-D interconnected hierarchical superstructure, namely a "plasmonic gold-on-silica (Au/SiO2) double-layered aerogel", integrating distinctive features of an upper plasmonic gold aerogel with a lower inert silica aerogel was successfully developed to achieve in situ separation and storage of inorganic salts in the silica aerogel, parallel enrichment of metabolites on the surface of the functionalized gold aerogel, and direct desorption/ionization of enriched metabolites by the photo-excited gold aerogel for rapid, sensitive, and comprehensive metabolomics analysis of human serum/urine samples. By integrating all these unique advantages into the hierarchical aerogel, multifunctional properties were introduced in the SALDI substrate to enable its effective utilization in clinical metabolomics for the discovery of reliable metabolic biomarkers to achieve unambiguous differentiation of early and advanced-stage lung cancer patients from healthy individuals. This study provides insight into the design and application of superstructured nanomaterials for in situ separation, storage, and photoexcitation of multi-components in complex biofluid samples for sensitive analysis.

Neural correlates of breath work, mental imagery of yoga postures, and meditation in yoga practitioners: a functional near-infrared spectroscopy study.

Objective: Previous research has shown numerous health benefits of yoga, a multicomponent physical and mental activity. The three important aspects of both traditional and modern yoga are breath work, postures, and meditation. However, the neural mechanisms associated with these three aspects of yoga remain largely unknown. The present study investigated the neural underpinnings associated with each of these three yoga components in long- and short-term yoga practitioners to clarify the neural advantages of yoga experience, aiming to provide a more comprehensive understanding of yoga's health-promoting effects. Methods: Participants were 40 Chinese women, 20 with a long-term yoga practice and 20 with a short-term yoga practice. Functional near-infrared spectroscopy was conducted while participants performed abdominal breathing, mental imagery of yoga postures, and mindfulness meditation. The oxygenated hemoglobin concentrations activated in the brain during these three tasks were used to assess the neural responses to the different aspects of yoga practice. The self-reported mastery of each yoga posture was used to assess the advantages of practicing yoga postures. Results: Blood oxygen levels in the dorsolateral prefrontal cortex during breath work were significantly higher in long-term yoga practitioners than in short-term yoga practitioners. In the mental imagery of yoga postures task, self-reported data showed that long-term yoga practitioners had better mastery than short-term practitioners. Long-term yoga practitioners demonstrated lower activation in the ventrolateral prefrontal cortex, with lower blood oxygen levels associated with performing this task, than short-term yoga practitioners. In the mindfulness meditation task, blood oxygen levels in the orbitofrontal cortex and the ventrolateral prefrontal cortex were significantly higher in long-term yoga practitioners than in short-term yoga practitioners. Conclusion: The three core yoga components, namely, yogic breathing, postures, and meditation, showed differences and similarities in the activation levels of the prefrontal cortex. Long-term practice of each component led to the neural benefits of efficient activation in the prefrontal cortex, especially in the dorsolateral prefrontal cortex, orbitofrontal cortex, and ventrolateral prefrontal cortex.

Validation of the PL-C Quest in China: understanding the pictorial physical literacy self-report scale.

Introduction: The notion of physical literacy is gaining interest from several countries as a potential mechanism for understanding the development of the physical self. This research endeavor represents an inaugural attempt to translate the Australian Physical Literacy Questionnaire for Children (PL-C Quest) into Chinese to evaluate the reliability and validity of the Chinese version of the PL-C Quest to assess physical literacy among children in mainland China. Methods: The Beaton translation paradigm was used to carry out language translation, back-translation, cultural adaptation, and presurveys. Data were collected from 642 children aged 6-12 years, with a mean age of 9.71 years (SD 1.816), to test the reliability of the Chinese version of the PL-C Quest. Results: The PL-C Quest items translated well (6.187 ~ 15.499) and correlated well (0.441 ~ 0.622). The Chinese version of the PL-C Quest had good reliability, with retest reliability values ranging from 0.91 to 0.74, Cronbach's alpha from 0.65 to 0.894, and McDonald's ω from the Spearman-Brown Coefficient was 0.84. The validity results are acceptable because the CFI, IFI, and TLI values are above 0.8 and close to 0.9, but the model fit's chi-square degrees-of-freedom ratio of 2.299, the RMSEA of 0.05, which was less than 0.08. Discussion: After translation and cultural adaptation, the Chinese version of the PL-C Quest is a reliable measurement tool and can be used in the Chinese region.

Identification of Tumor Antigens and Immune Subtypes of High-grade Serous Ovarian Cancer for mRNA Vaccine Development.

High-grade serous ovarian cancer (HGSC) is the most common pathology of ovarian cancer and has aggressive characteristics and poor prognosis. mRNA vaccines are a novel tool for cancer immune treatment and may play an important role in HGSC therapy. Our study aimed to explore tumour antigens for vaccine development and identify potential populations amenable to vaccine treatment. Based on transcription data from The Cancer Genome Atlas (TCGA), we identified four tumour-specific antigens for vaccine production: ARPC1B, ELF3, VSTM2L, and IL27RA. In addition to being associated with HGSC patient prognosis, the expression of these antigens was positively correlated with the abundances of antigen-presenting cells (APCs). Furthermore, we stratified HGSC samples into three immune subtypes (IS1-IS3) with different immune characteristics. A corhort from ICGC (International Cancer Genome Consortium) was used to validate. Patients of IS3 had the best prognosis, while patients of IS1 were most likely to benefit from vaccination. There was substantial heterogeneity in immune signatures and immune-associated molecule expression in HGSC. Finally, weighted gene coexpression network analysis (WGCNA) was employed to cluster immune-related genes and explore potential biomarkers related to vaccination. In conclusion, we identified four potential tumour antigens for mRNA vaccine production for HGSC treatment, and the immune subtype could be an important indicator to select suitable HGSC patients to receive vaccination.

The combined analysis of urine and blood metabolomics profiles provides an accurate prediction of the training and competitive status of Chinese professional swimmers.

Objective: The purpose of this study was to employ metabolomics for the analysis of urine metabolites in swimmers, with the aim of establishing models for assessing their athletic status and competitive potential. Furthermore, the study sought to compare the identification efficacy of multi-component (urine and blood) model versus single-component (urine or blood) models, in order to determine the optimal approach for evaluating training and competitive status. Methods: A total of 187 Chinese professional swimmers, comprising 103 elite and 84 sub-elite level athletes, were selected as subjects for this study. Urine samples were obtained from each participant and subjected to nuclear magnetic resonance (NMR) metabolomics analysis. Significant urine metabolites were screened through multivariable logistic regression analysis, and an identification model was established. Based on the previously established model of blood metabolites, this study compared the discriminative and predictive performance of three models: either urine or blood metabolites model and urine + blood metabolites model. Results: Among 39 urine metabolites, 10 were found to be significantly associated with the athletic status of swimmers (p < 0.05). Of these, levels of 2-KC, cis-aconitate, formate, and LAC were higher in elite swimmers compared to sub-elite athletes, while levels of 3-HIV, creatinine, 3-HIB, hippurate, pseudouridine, and trigonelline were lower in elite swimmers. Notably, 2-KC and 3-HIB exhibited the most substantial differences. An identification model was developed to estimate physical performance and athletic level of swimmers while adjusting for different covariates and including 2-KC and 3-HIB. The urine metabolites model showed an area under the curve (AUC) of 0.852 (95% CI: 0.793-0.912) for discrimination. Among the three identification models tested, the combination of urine and blood metabolites showed the highest performance than either urine or blood metabolites, with an AUC of 0.925 (95% CI: 0.888-0.963). Conclusion: The two urine metabolites, 2-KC and 3-HIV, can serve as significant urine metabolic markers to establish a discrimination model for identifying the athletic status and competitive potential of Chinese elite swimmers. Combining two screened urine metabolites with four metabolites reported exhibiting significant differences in blood resulted in improved predictive performance compared to using urine metabolites alone. These findings indicate that combining blood and urine metabolites has a greater potential for identifying and predicting the athletic status and competitive potential of Chinese professional swimmers.

Application of action observation therapy in stroke rehabilitation: A systematic review.

BACKGROUND: Numerous studies have described the positive effects of action observation therapy (AOT) on motor recovery among patients with stroke. However, there is no standardized procedure for when and how to intervene with AOT. OBJECTIVES: Thus, we reviewed and analyzed previous studies to provide a guideline for the application of AOT in stroke rehabilitation. METHOD: We searched PubMed, Cochrane Library, and EMBASE from inception to October 31 2022, using title and abstract search terms of "action observation" and "stroke" or "hemiplegia." Of 4108 potential articles, 29 articles (sample size = 429 in AOT groups; sample size = 423 in control groups) that met inclusion criteria were included in final analyses. RESULTS: The results suggested starting adjuvant AOT > 23 days after stroke onset and conducting 30-40 min/session, 3-5 times/week for at least 4 weeks. CONCLUSION: Based on our results, many factors will impact the effect of AOT on stroke rehabilitation, when to apply (timing) and how to apply (frequency, single, and total duration) should be fully considered when applying AOT as adjuvant therapy in stroke rehabilitation.

Clinical characteristics, treatment patterns, and survival outcomes of pulmonary mucosa-associated lymphoid tissue lymphoma in the United States.

BACKGROUND: Pulmonary mucosa-associated lymphoid tissue (MALT) lymphoma is a relatively rare disease. We aimed to perform a large-scale study of clinical characteristics and optimal treatment for pulmonary MALT lymphoma patients. METHOD: Our study extracted data from the Surveillance, Epidemiology, and End Results (SEER) Program. The chi-square test was utilized to compare clinical factors. Overall survival (OS) was compared using the Kaplan-Meier (KM) method and Cox regression analysis. Cancer-specific survival (CSS) was compared by the Fine-Gray test. Propensity score matching (PSM) was used to balance confounders. RESULTS: Females and elderly individuals are more likely to suffer from pulmonary MALT lymphoma. The incidence rate is increasing, and most patients are diagnosed in the early stage without specific symptoms. Patients usually suffer from a favorable survival period, especially patients in the early stage. Patients in stage I-II can obtain a survival advantage from surgery, especially for patients older than 60 years, with unilateral lesions, with single-lung-lobe lesions, in stage I, and without B symptoms. Chemotherapy decreases the risk of death for advanced-stage patients, and males, caucasians, patients with stage IV disease, or patients with only unilateral lung involvement were especially recommended for chemotherapy. CONCLUSION: Pulmonary MALT lymphoma is an indolent tumor. Patients in different stages had different prognoses, and different treatments were recommended. We will conduct prospective research in the future.

Molecular Biomarker Exploration of Rituximab plus CHOP Therapy in Real-World Diffuse Large B-Cell Lymphoma Patients.

BACKGROUND: Presently, several classification methods are based on diffuse large B-cell lymphoma (DLBCL), but its clinical application has not yet been testified in Asian populations. METHODS: Twenty-five DLBCL patients were subjected to second-generation gene sequencing (NGS), and retrospective analysis of clinical features of the patients was to explore genotyping and survival prognosis biomarkers. RESULTS: The prevalent mutant genes in DLBCL patients cover myeloid differentiation factor 88 (MyD88) (40%), TP53 (32%), B-cell translocation gene 2 (BTG2) (28%), PIM1 (28%), and CREB-binding protein (CREBBP) (24%) in this study. The classical International Prognostic Index (IPI) scores were associated with progression-free survival (PFS) (HR: 7.52, 95% CI 1.51 - 37.6, p = 0.00393) via univariate analysis. Furthermore, patients with ETS-variant gene 6 (ETV6) (HR: 5.1, 95% CI 0.927 - 28.1, p = 0.0371), platelet-derived growth factor receptor A (PDGFRA) (HR: 4.29, 95% CI 0.824 - 22.3, p = 0.0594), platelet-derived growth factor receptor B (PDGFRB) (HR: 10.8, 95% CI 0.979 - 119, p = 0.0149) was distinctively correlated with poor PFS except for the IPI score. Nevertheless, the mutation of PDGFRA/B gene was not distinct in further multivariate analysis (PFS: HR: 2.72, 95% CI 0.52 - 14.23, p = 0.2369). Additionally, better survival prognosis was in DLBCL patients who did not progress within 12 months (POD12). Ultimately, caspase recruitment domain 11 (CARD11) gene mutations were enriched in patients with primary intranodal tumors, but the prognostic relevance was not discovered. CONCLUSIONS: ETV6 and platelet-derived growth factor receptor (PDGFR)A/B gene mutations are supposed to be potential biomarkers for the prognosis of DLBCL patients via the statistical analysis of this small sample, and POD12 is also expected to be an effective endpoint for efficacy assessment.

Bibliometric analysis study on cognitive function in developmental coordination disorder from 2010 to 2022.

Objective: To identify the research hotspots on cognitive function in developmental coordination disorder (DCD) in recent years, predict the research frontier and development trend, and provide more perspectives for the study of the DCD population. Methods: Using CiteSpace and VOSviewer software to draw charts, 1,082 pieces of literature about DCD and cognitive function in the Web of Science core collection database from 2010 to 2022 were visually analyzed. Results and conclusion: Interest in the cognitive function of DCD has been on the rise in the past 10 years. Over 40 countries and regions, 117 institutions and 200 researchers have participated in the corresponding research, mainly in the United States, and their institutions have published more highly influential results. The hot keywords are DCD, children, attention, working memory, performance, and attention-deficit/hyperactivity disorder (ADHD), and the main research hot topics include functional performance, population, cognitive psychology. The research directions include "DCD," "Asperger syndrome," "memory," "infant," "clumsiness," "neurodevelopmental disorder," "occupational therapy," "preschool children," "motor competence," "model," and "online control." Future research should focus on motor imagery and intrinsic models and use more neurophysiological techniques to reveal the cognitive characteristics of children with DCD and develop intervention programs.

Has COVID-19 accelerated the E-commerce of agricultural products? Evidence from sales data of E-stores in China.

We investigated the operation of e-stores specializing in food and agricultural products before and after the occurrence of COVID-19. A difference-in-difference (DID) method was employed to estimate the relationship between COVID-19 and the online sales of agricultural products using data from 164,002 food and agricultural product e-commerce stores (in short, e-stores) of two major Chinese e-commerce platforms in 120 prefectural-level or above cities. The results demonstrated that while COVID-19 and its control measures were associated with a substantial growth in the monthly sales of food and agricultural product e-stores, the growth varies considerably across store scales and with the type of food and agricultural product in which an e-store is specialized. Micro stores experienced much larger growth and played a more important role in maintaining the resilience of the supply chain of food and agricultural products than larger-scale stores; stores selling more essential food items experienced larger growth than those selling leisure food items. A mechanism analysis further revealed that the growth of online sales of agricultural products was mainly driven by changes in consumers' food purchase behaviors from offline channels to online channels (i.e., an increase in the number of online customer orders and price per online order) starting with the onset of COVID-19. The results of this paper underscore the importance of e-commerce in maintaining the resilience of the agri-food supply chain and call for public support of the development of micro- and small-scale e-stores to meet consumers' increasing demand for food supply from those types of stores during the pandemic period.

Covalent Bonding and Coulomb Repulsion-Guided AuNP Array: A Tunable and Reusable Substrate for Metabolomic Characterization of Lung Cancer Patient Sera.

Surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS) has gained increased attention in the metabolic characterization of human biofluids. However, the stability and reproducibility of nanoparticle-based substrates remain two of the biggest challenges in high-salt environments. Here, by controlling the extent of Coulomb repulsion of 26 nm positively charged AuNPs, a homogeneous layer of covalently bonded AuNPs on a coverslip with tunable interparticle distances down to 16 nm has been successfully fabricated to analyze small biomolecules in human serum. Compared with the self-assembled AuNP array, the covalently bonded AuNP array showed superior performances on stability, reproducibility, and sensitivity in high-salt environments. The stable attachment of AuNPs maintained a detection reproducibility with a RSD less than 12% and enabled the reusability of the array for 10 experiments without significant signal deterioration (<15%) and carryover effects. Moreover, the closely positioned AuNPs allowed the coupling of photoinduced plasmons to generate an enhanced electric field, which promotes the generation of excited electrons to facilitate the desorption/ionization processes instead of the heat dissipation, thus enhancing the detection sensitivity with detection limits down to the femtomole level. Combined with machine learning methods, the AuNP array has been successfully applied to discover seven biomarkers for differentiating early-stage lung cancer patients from healthy controls. It is anticipated that this simple approach of developing robust AuNP arrays can also be extended to other types of NP arrays for wider applications of SALDI-MS technology.

Comprehensive analyses of genomic features and mutational signatures in adenosquamous carcinoma of the lung.

Adenosquamous carcinoma (ASC) of the lung is a relatively rare tumor with strong aggressiveness and poor prognosis. The analysis of mutational signatures is becoming routine in cancer genomics and has implications for pathogenesis, classification, and prognosis. However, the distribution of mutational signatures in ASC patients has not been evaluated. In this study, we sought to reveal the landscape of genomic mutations and mutational signatures in ASC. Next-generation sequencing (NGS) technology was used to retrieve genomic information for 124 ASC patients. TP53 and EGFR were the most prevalent somatic mutations observed, and were present in 66.9% and 54.8% of patients, respectively. CDKN2A (21%), TERT (21%), and LRP1B (18.5%) mutations were also observed. An analysis of gene fusion/rearrangement characteristics revealed a total of 64 gene fusions. The highest frequency of variants was determined for ALK fusions, with six ALK-EML4 classical and two intergenic ALK fusions, followed by three CD74-ROS1 fusions and one ROS1-SYN3 fusion. EGFR 19del (45.6%), and EGFR L858R (38.2%) and its amplification (29.4%) were the top three EGFR mutations. We extracted mutational signatures from NGS data and then performed a statistical analysis in order to search for genomic and clinical features that could be linked to mutation signatures. Amongst signatures cataloged at COSMIC, the most prevalent, high-frequency base changes were for C > T; and the five most frequent signatures, from highest to lowest, were 2, 3, 1, 30, and 13. Signatures 1 and 6 were determined to be associated with age and tumor stage, respectively, and Signatures 22 and 30 were significantly related to smoking. We additionally evaluated the correlation between tumor mutational burden (TMB) and genomic variations. We found that mutations ARID2, BRCA1, and KEAP1 were associated with high TMB. The homologous recombination repair (HRR) pathway-related gene mutation displayed a slightly higher TMB than those without mutations. Our study is the first to report comprehensive genomic features and mutational signatures in Chinese ASC patients. Results obtained from our study will help the scientific community better understand signature-related mutational processes in ASC.

Corrigendum: Behavioral and brain reactivity associated with drug-related and non-drug-related emotional stimuli in methamphetamine addicts.

[This corrects the article DOI: 10.3389/fnhum.2022.894911.].

Lung adenocarcinoma with EGFR 19Del and an ALK rearrangement benefits from alectinib instead of an EGFR-TKI: A case report.

RATIONALE: A remarkable concurrence of an EGFR mutation and an EML4-ALK fusion (double positive) occasionally occurs within a narrow number of patients. Previous studies using targeted therapy on EGFR/ALK co-mutated patients have commonly focused on single tyrosine kinase inhibitors (TKIs) or on the sequential use of EGFR-TKIs and ALK-TKIs. At present, no consensus exists regarding the treatment of patients with double positive mutations. The effectiveness of precision therapy also remains unknown. PATIENT CONCERNS: A 53-year-old female non-smoker who described recurrent coughing and blood in her sputum over a month-long interval was examined at a local hospital. DIAGNOSIS: Using computed tomography (CT) and positron emission tomography CT (PET-CT), the patient was diagnosed with Stage IVb lung adenocarcinoma (T4N3M1). INTERVENTIONS: The patient had a novel ALK-RAB10 rearrangement identified using DNA sequencing, which, at the transcript level, was actually a canonical ALK fusion that caused a response to alectinib therapy. OUTCOMES: The patient has achieved partial remission (PR), with a progression free survival (PFS) of 16 months, and continues to benefit. LESSONS: Our results may indicate differential sensitivities to TKIs in patients harboring an EGFR mutation and an ALK rearrangement. Our patient's response to alectinib, instead of to EGFR-TKIs, may lead to an expanded list of alectinib beneficiaries who have rare gene co-alterations in lung adenocarcinoma.

Behavioral and Brain Reactivity Associated With Drug-Related and Non-Drug-Related Emotional Stimuli in Methamphetamine Addicts.

Background: Methamphetamine addicts can experience severe emotional processing disorders, with abnormal responses to emotional and drug-related stimuli. These aberrant behaviors are one of the key factors leading to relapse. Nevertheless, the characteristics of addicts' responses to drug-related stimuli and their responses to emotional stimuli remain controversial. Methods: 52 methamphetamine addicts from China passively viewed three different categories of images: Drug-related; positive emotional; and negative emotional. In the first task, participants completed a 9-point Self-Assessment Manikin (SAM) scale, rating the valence of each image. In the second, they performed a cued-action task while electroencephalography (EEG) data were recorded. Result: Drug-related images were rated negatively, with an average rating of 3.57. However, reaction times to drug-related stimuli were significantly faster than for negative stimuli (p = 0.030), and were indistinguishable from positive stimuli (p > 0.99). Similarly, EPN amplitudes evoked by drug-related images were significantly larger than those evoked by negative stimuli (p < 0.001), but no different than positive stimuli (p > 0.99). LPP amplitudes evoked by drug-related stimuli were significantly smaller than those evoked by negative (p < 0.001) and positive stimuli (p = 0.004). Conclusion: Despite negative self-assessments of drug-related imagery, MA-addicts reaction times were no slower than positive reactions. Similarly, drug-related and positive imagery EPN amplitudes were indistinguishable. Together, these results suggest increased attentional resources were allocated to the processing of drug-related stimuli and the pathways responsible partially overlap with the those recruited in processing positive emotional imagery in addicts. Moreover, in the late stage of visual processing, MA-addicts showed reduced brain activity in response to drug-related stimuli, suggesting reverse inhibition in response preparation and emotional appraisal. These findings may provide a reference for clinicians treating drug-taking behavior and for the development of new models of rehabilitation therapy.

Lactate Is Answerable for Brain Function and Treating Brain Diseases: Energy Substrates and Signal Molecule.

Research to date has provided novel insights into lactate's positive role in multiple brain functions and several brain diseases. Although notable controversies and discrepancies remain, the neurobiological role and the metabolic mechanisms of brain lactate have now been described. A theoretical framework on the relevance between lactate and brain function and brain diseases is presented. This review begins with the source and route of lactate formation in the brain and food; goes on to uncover the regulatory effect of lactate on brain function; and progresses to gathering the application and concentration variation of lactate in several brain diseases (diabetic encephalopathy, Alzheimer's disease, stroke, traumatic brain injury, and epilepsy) treatment. Finally, the dual role of lactate in the brain is discussed. This review highlights the biological effect of lactate, especially L-lactate, in brain function and disease studies and amplifies our understanding of past research.

Combining MALDI-MS with machine learning for metabolomic characterization of lung cancer patient sera.

An increasing amount of evidence has proven that serum metabolites can instantly reflect disease states. Therefore, sensitive and reproducible detection of serum metabolites in a high-throughput manner is urgently needed for clinical diagnosis. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is a high-throughput platform for metabolite detection, but it is hindered by significant signal fluctuations because of the "sweet spot" effect of organic matrices. Here, by screening two transformation methods and four normalization techniques to reduce the significant signal fluctuations of the DHB matrix, an integrated MALDI-MS data processing approach combined with machine learning methods was established to reveal metabolic biomarkers of lung cancer. In our study, 13 distinctive features with statistically significant differences (p < 0.001) between 34 lung cancer patients and 26 healthy controls were selected as significant potential biomarkers of lung cancer. 6 out of the 13 distinctive features were identified as intact metabolites. Our results demonstrate the potential for clinical application of MALDI-MS in serum metabolomics for biomarker screening in lung cancer.

WSVAS: A YOLOv4 -based phenotyping platform for automatically detecting the salt tolerance of wheat based on seed germination vigour.

Salt stress is one of the major environmental stress factors that affect and limit wheat production worldwide. Therefore, properly evaluating wheat genotypes during the germination stage could be one of the effective ways to improve yield. Currently, phenotypic identification platforms are widely used in the seed breeding process, which can improve the speed of detection compared with traditional methods. We developed the Wheat Seed Vigour Assessment System (WSVAS), which enables rapid and accurate detection of wheat seed germination using the lightweight convolutional neural network YOLOv4. The WSVAS system can automatically acquire, process and analyse image data of wheat varieties to evaluate the response of wheat seeds to salt stress under controlled environments. The WSVAS image acquisition system was set up to continuously acquire images of seeds of four wheat varieties under three types of salt stress. In this paper, we verified the accuracy of WSVAS by comparing manual scoring. The cumulative germination curves of wheat seeds of four genotypes under three salt stresses were also investigated. In this study, we compared three models, VGG16 + Faster R-CNN, ResNet50 + Faster R-CNN and YOLOv4. We found that YOLOv4 was the best model for wheat seed germination target detection, and the results showed that the model achieved an average detection accuracy (mAP) of 97.59%, a recall rate (Recall) of 97.35% and the detection speed was up to 6.82 FPS. This proved that the model could effectively detect the number of germinating seeds in wheat. In addition, the germination rate and germination index of the two indicators were highly correlated with germination vigour, indicating significant differences in salt tolerance amongst wheat varieties. WSVAS can quantify plant stress caused by salt stress and provides a powerful tool for salt-tolerant wheat breeding.

Bibliometric analysis of the effects of mental fatigue on athletic performance from 2001 to 2021.

Aims: To explore the research hot topics and main contents in the field of the influence of mental fatigue on athletic performance, and to provide new ideas and directions for future research in this field. Methods: Using CiteSpace and VOSviewer visualization tool software core collection of Web of Science database to TS = ("mental fatigue" OR "mental exertion" OR "cognitive fatigue" OR "Cognitive exertion" OR "mental exhaustion" OR "mental tiredness") AND ("athletic performance" OR "technical skill*" OR "Skill*" OR "technique" OR "decision making" OR "performance") AND ("Humans") searched for the influence of mental fatigue on athletic performance from 2001 to 2021 to conduct visual analysis. Research hot topics were analyzed from the aspects of high-impact countries/regions, institutions, authors, high-frequency keywords, and mutation terms. Results: A total of 658 publications were identified finally, and there has been an increasing trend in the annual number of publications, with the United States ranking first in the number of publications and influence. Future research will focus on promoting the application of EEG technology as an objective indicator for assessing mental fatigue, exploring effective methods and measures for pharmacological or non-pharmacological interventions against fatigue, and focusing on the effects of mental fatigue on endurance performance, technical skills, and sports-related decision-making. Conclusion: The results of the present study help us understand the status of the mental fatigue and athletic performance field and its recent developments.