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Global warming modulates soil respiration (RS) via microbial decomposition, which is seasonally dependent. Yet, the magnitude and direction of this modulation remain unclear, partly owing to the lack of knowledge on how microorganisms respond to seasonal changes. Here, we investigated the temporal dynamics of soil microbial communities over 12 consecutive months under experimental warming in a tallgrass prairie ecosystem. The interplay between warming and time altered (P

The aims of this narrative review were to summarize the current literature on the beneficial effects of exercise interventions on individuals with comorbid depression and cardiovascular disease, and to review the current evidence that advances our understanding of the pathophysiological mechanisms underlying these effects. Ninety relevant articles were included and analyzed through a systematic search of PubMed and Web of Science. The analyses indicated that exercise interventions could modulate regulatory pathways to prevent depressive symptoms and reduce adverse cardiovascular events through five mechanisms: promoting immunosuppression, improving mitochondrial function, balancing the autonomic nervous system, up-regulating serum brain-derived neurotrophic factor, and improving vascular endothelial function; and the critical role of integrating the key principles of exercise prescription (frequency, intensity, type, time, volume, and progression) to identify novel therapeutic targets and optimize interventions. In conclusion, this study emphasizes not only the significance of exercise interventions but also the critical role of optimizing exercise prescriptions in managing comorbid depression and cardiovascular disorders. The approach holds important theoretical and clinical practice implications for enhancing both mental and cardiovascular health.

Abstract Background In an aging society, depression has become a public health challenge that can lead to many adverse health outcomes; evidence addressing the link between depression and motor cognitive risk syndrome (MCR, a novel syndrome that effectively predicts dementia) is still lacking. Methods A PRISMA checklist was used to systematically review the relevant peer-reviewed literature for the primary data analysis. A computer search of CNKI, Wan Fang Data, CBM, VIP, PubMed, Web of Science, Embase, Cochrane Library, Scopus, and Ovid databases, all from creation to March 15, 2023. A meta-analysis was conducted using Stata 17.0, the Newcastle-Ottawa Scale instrument (NOS), and the Agency for Healthcare Research and Quality (AHRQ) for quality appraisal. We used Q and I2 statistics to assess heterogeneity and random effects models to pool estimates. Egger’s regression tests and adjustments were made using the trim and fill test. Result Thirteen studies were included, including seven cross-sectional studies and six cohort studies, and data on the association between depression and MCR in the elderly were extracted. Moreover, the results of the meta-analysis showed that there was a significant correlation between depression and MCR in the cross-sectional study [OR = 2.43, 95% CI(1.31 ~ 3.54), P

Abstract The mitochondrial malic enzyme 2 (ME2), which is frequently elevated during carcinogenesis and may be a target for cancer therapy, catalyzes the conversion of malate to pyruvate. The processes controlling ME2 activity, however, remain largely unclear. In this work, we show that human hepatocellular carcinoma (HCC) tissues contain high levels of ME2 and that the methylation of ME2 stimulates the growth and migration of HCC cells. Furthermore, we observed that ME2 interacts with protein arginine methyltransferase 1 (PRMT1) and that ME2 enzymatic activity is activated by mutation of ME2 at lysine 67. Mitochondrial respiration was markedly increased by activated ME2, which promoted cell division and carcinogenesis. Furthermore, a negative prognosis for patients was strongly linked with the expression levels of PRMT1 and ME2 R67K in HCC tissues. These findings imply that hepatocellular carcinoma growth is aided by PRMT1-mediated ME2 methylation, that is an essential signaling event that cancer cells need to continue mitochondrial respiration.

Abstract The leaf beetle Ophraella communa LeSage (Coleoptera: Chrysomelidae) is an effective biological control agent of the common ragweed. Here, we assembled a chromosome-level genome of the O. communa by combining Illumina, Nanopore, and Hi-C sequencing technologies. The genome size of the final genome assembly is 733.1 Mb, encompassing 17 chromosomes, with an improved contig N50 of 7.05 Mb compared to the original version. Genome annotation reveals 25,873 protein-coding genes, with functional annotations available for 22,084 genes (85.35%). Non-coding sequence annotation identified 204 rRNAs, 626 tRNAs, and 1791 small RNAs. Repetitive elements occupy 414.41 Mb, constituting 57.76% of the genome. This high-quality genome is fundamental for advancing biological control strategies employing O. communa.

Chlamydia pneumoniae (C. pneumoniae) is a specialized intracellular parasitic pathogen capable of causing pneumonia, sinusitis, bronchitis, and other respiratory diseases, which pose significant public health challenges. Therefore, rapid, accurate, and sensitive diagnosis is crucial for the prevention and treatment of respiratory diseases caused by C. pneumoniae. In this study, we combined enzymatic recombination amplification (ERA) with the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) 12a system (CRISPR/Cas12a) to develop a dual detection platform termed the Cpn-ERA-CRISPR/Cas12a dual system. This system integrates both the ERA-CRISPR/Cas12a fluorescence system and the ERA-CRISPR/Cas12a lateral flow system. Detection results can be measured using a fluorescence detector or observed with the naked eye on lateral flow strips. The fluorescence system and the lateral flow system detect C. pneumoniae in 30 minutes and 15 minutes, respectively. This dual system exhibits no cross-reactivity with the other seven pathogens, demonstrating high specificity, and achieves a sensitivity of 100 copies/µL. Additionally, the Cpn-ERA-CRISPR/Cas12a dual system was employed to analyze 39 clinical samples, comprising 19 positive and 20 negative samples. The detection rate for positive samples was 100%, with no positive results in the negative samples, indicating a high level of concordance with qPCR results. In summary, the Cpn-ERA-CRISPR/Cas12a dual system represents a novel tool for diagnosing C. pneumoniae and holds promising application potential in grassroots community hospitals.

BackgroundAs individuals age, they commonly experience reduced physical activity and cognitive decline. While evidence, there is limited trajectory research on their concurrent progression and interrelation in individuals over 55 years old.MethodsThe data was collected from 5,765 individuals aged over 55 years who participated in the China Health and Retirement Longitudinal Study (CHARLS) between 2011 and 2020. Physical activity was measured by IPAQ, cognitive function by episodic memory, and mental intactness score. Separate sets of group-based trajectory models were fitted to identify physical activity trajectories and cognitive function trajectories. Multivariate logistic regression was used to estimate the association between baseline characteristics and each set of trajectories. Group-based dual trajectory modeling (GBDTM) was applied to quantify these associations.ResultsGBDTM identified three distinct trajectory groups for physical activity and cognitive outcomes. The physical activity trajectories were classified as “Persistently low physical activity” (74.2%), “Decreasing physical activity” (13.7%), and “Rising physical activity” (12.1%). Similarly, cognitive function trajectories were categorized as “Persistently low cognitive function” (22.2%), “Persistently moderate cognitive function” (37.9%), and “Persistently high cognitive function” (39.9%). Notably, 15.6% of participants followed the trajectories of “Persistently low physical activity” and “Persistently low cognitive function.” The presence of a severe decline in physical activity was associated with an increased likelihood of poor cognitive function and vice versa. Age, sex, education, residential status, BMI, and visual impairment were identified as significant predictors for physical activity and cognitive decline.ConclusionThis study found that the GBDTM can determine the consistent trajectories of physical activity and cognitive function trajectories that persistently decline in individuals over 55 years. Analyses of predictive factors can be instrumental in promoting physical activity and delaying cognitive decline.

BackgroundOlder adults with cognitive impairment can experience poor oral health due to reduced self-care ability, yet the impact of various oral health indicators on the cognitive ability remains unclear. We investigated the relationship between oral health indicators and mild cognitive impairment (MCI) in older adults.MethodsA cross-sectional study of 234 older adults aged 65 years or over was performed form January to March 2023 at health screening departments of hospitals. This study used the Mini-mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Activities of Daily Living (ADL), Clinical Dementia Rating (CDR), and Hachinski Ischemic Score (HIS) to measure MCI. Two qualified dentists performed clinical oral examinations (number of teeth lost, dental caries, removable dentures, periodontitis). The other oral health status was measured by subjective assessment questionnaires, and the oral health-related quality of life (OHRQoL) was assessed by Geriatric Oral Health Assessment Index (GOHAI).ResultsOf the 234 older adults, 166 had MCI and 68 had normal cognitive ability. The univariate analyses revealed that older adults with poor oral health indicators of dental caries, mastication ability, oral and maxillofacial pain, self-perceived oral health status and OHRQoL had lower cognitive levels. The stepwise logistic regression analysis observed that higher education level (OR = 0.06, 95%CI = 0.007, 0.567) and OHRQoL score (OR = 0.92, 95%CI = 0.878, 0.963) were negatively associated with the presence of MCI. The area under the ROC curve (AUC) of MCI was 0.675 (95% CI: 0.600, 0.749) with a low sensitivity of 41.6% and a moderate specificity of 86.8%.ConclusionOHRQoL was found to be associated with MCI, implying that OHRQoL may be important in cognitive decline. The GOHAI scale can be used to more easily assess the oral health of older adults, which is important for the timely detection of poor oral status to delay cognitive decline.

Abstract Background Mild cognitive impairment has received widespread attention as a high-risk population for Alzheimer’s disease, and many studies have developed or validated predictive models to assess it. However, the performance of the model development remains unknown. Objective The objective of this review was to provide an overview of prediction models for the risk of Alzheimer’s disease dementia in older adults with mild cognitive impairment. Method PubMed, EMBASE, Web of Science, and MEDLINE were systematically searched up to October 19, 2023. We included cohort studies in which risk prediction models for Alzheimer’s disease dementia in older adults with mild cognitive impairment were developed or validated. The Predictive Model Risk of Bias Assessment Tool (PROBAST) was employed to assess model bias and applicability. Random-effects models combined model AUCs and calculated (approximate) 95% prediction intervals for estimations. Heterogeneity across studies was evaluated using the I 2 statistic, and subgroup analyses were conducted to investigate sources of heterogeneity. Additionally, funnel plot analysis was utilized to identify publication bias. Results The analysis included 16 studies involving 9290 participants. Frequency analysis of predictors showed that 14 appeared at least twice and more, with age, functional activities questionnaire, and Mini-mental State Examination scores of cognitive functioning being the most common predictors. From the studies, only two models were externally validated. Eleven studies ultimately used machine learning, and four used traditional modelling methods. However, we found that in many of the studies, there were problems with insufficient sample sizes, missing important methodological information, lack of model presentation, and all of the models were rated as having a high or unclear risk of bias. The average AUC of the 15 best-developed predictive models was 0.87 (95% CI: 0.83, 0.90). Discussion Most published predictive modelling studies are deficient in rigour, resulting in a high risk of bias. Upcoming research should concentrate on enhancing methodological rigour and conducting external validation of models predicting Alzheimer’s disease dementia. We also emphasize the importance of following the scientific method and transparent reporting to improve the accuracy, generalizability and reproducibility of study results. Registration This systematic review was registered in PROSPERO (Registration ID: CRD42023468780).

Genotyping single-nucleotide polymorphisms (SNPs) in microbiomes enables strain-level quantification. In this protocol, we describe a computational pipeline that performs fast and accurate SNP genotyping using metagenomic data. We first demonstrate how to use Maast to catalog SNPs from microbial genomes. Then we use GT-Pro to extract unique SNP-covering k-mers, optimize a data structure for storing these k-mers, and finally perform metagenotyping. For proof of concept, the protocol leverages public whole-genome sequences to metagenotype a synthetic community. For complete details on the use and execution of this protocol, please refer to Shi et al. (2022a)1 and Shi et al. (2022b).2.

Detecting genetic variants in metagenomic data is a priority for understanding the evolution, ecology, and functional characteristics of microbial communities. Many tools that perform this metagenotyping rely on aligning reads of unknown origin to a database of sequences from many species before calling variants. In this synthesis, we investigate how databases of increasingly diverse and closely related species have pushed the limits of current alignment algorithms, thereby degrading the performance of metagenotyping tools. We identify multi-mapping reads as a prevalent source of errors and illustrate a trade-off between retaining correct alignments versus limiting incorrect alignments, many of which map reads to the wrong species. Then we evaluate several actionable mitigation strategies and review emerging methods showing promise to further improve metagenotyping in response to the rapid growth in genome collections. Our results have implications beyond metagenotyping to the many tools in microbial genomics that depend upon accurate read mapping.

Existing single nucleotide polymorphism (SNP) genotyping algorithms do not scale for species with thousands of sequenced strains, nor do they account for conspecific redundancy. Here we present a bioinformatics tool, Maast, which empowers population genetic meta-analysis of microbes at an unrivaled scale. Maast implements a novel algorithm to heuristically identify a minimal set of diverse conspecific genomes, then constructs a reliable SNP panel for each species, and enables rapid and accurate genotyping using a hybrid of whole-genome alignment and k-mer exact matching. We demonstrate Maast's utility by genotyping thousands of Helicobacter pylori strains and tracking SARS-CoV-2 diversification.

This study presented a narrative review of the six latest sets of guidelines on physical activity for children and adolescents from Australia, Canada, China, the United Kingdom, the United States and WHO, and analysed the history of the development of the guidelines; the policy context in which the guidelines were developed; and the main subjects of the guidelines. The core elements of the latest guidelines were identified and compared, including frequency, intensity, duration (time), and type of physical activity, assessment intensity of physical activity, and risk prevention for physical activity participation. There is an urgent need for obtaining the latest scientific evidence to support and update the contents of the Chinese guidelines. We therefore make the following recommendations for future revisions of the Chinese guidelines based on the findings of this study: (1) to update the recommended frequency, intensity, duration, and type of physical activities that meet the needs for Chinese children and adolescents; (2) to update the methods for assessing physical activity intensity, and identifying and managing the risk factors in participating in physical activity; and (3) to incorporate analyses and reviews of school physical education curriculum for effectively achieving the adequate levels of physical activity.

BackgroundThe tumor growth rate and tumor volume doubling time are crucial parameters in diagnosing and managing lung lesions. Pulmonary sarcomatoid carcinoma (PSC) is a unique and highly malignant subtype of lung cancer, with limited documentation on its growth feature. This article aims to address the gap in knowledge regarding a PSC’s growth patterns by describing the characteristics of a confirmed case using computed tomography, thereby enhancing the understanding of this rare disease.Case presentationA 79-year-old man was transferred to our center presenting with a mild cough, blood-tinged sputum, and a malignant nodule in the left upper lobe. Chest CT revealed a solid nodule in the left upper lobe. A follow-up CT ten days later showed a significant increase in the size of the nodule, accompanied by ground-glass opacity in the surrounding lung. The rapid preoperative growth of the nodule suggested a non-neoplastic lesion, and intraoperative frozen pathology also considered the possibility of tuberculosis. Subsequently, a left upper apical-posterior segment (S1 + 2) resection was performed. Postoperative tumor pathology confirmed the diagnosis of pulmonary sarcomatoid carcinoma with extensive giant cell carcinoma and necrosis. Immunohistochemistry indicated approximately 60% PD-L1 positive and genetic testing revealed a MET mutation. The patient was discharged with oral crizotinib targeted therapy, and his condition remained stable postoperatively. The patient is currently undergoing regular follow-up at our hospital, with no evidence of distant metastasis or recurrence.ConclusionPulmonary sarcomatoid carcinoma can exhibit rapid tumor growth on imaging, and PSC should be considered in the differential diagnosis for lesions that present with a fast growth rate. Timely and appropriate treatment for PSC may lead to a good prognosis.

In the realm of speech emotion recognition, researchers strive to refine representation methods for improved emotional information capture. Traditional one-dimensional time series classification falls short in expressing intricate emotional patterns present in speech signals, posing challenges in accuracy and robustness. This study introduces an innovative algorithm leveraging Hilbert curves to transform one-dimensional speech data into two-dimensional form, enhancing feature extraction accuracy. A tiling module based on Hilbert curve maximizes Hilbert curve arrangements for improved emotional information capture. Results reveal spatial efficiency gains up to 23,195 times pixel units, enhancing data storage. With an exceptional 98.73% accuracy, the proposed approach traditional methods, affirming its superior emotion classification performance on the same dataset. These empirical findings underscore the effectiveness of our proposed method in advancing speech emotion recognition.

Soil microbial communitys responses to climate warming alter the global carbon cycle. In temperate ecosystems, soil microbial communities function along seasonal cycles. However, little is known about how the responses of soil microbial communities to warming vary when the season changes. In this study, we investigated the seasonal dynamics of soil bacterial community under experimental warming in a temperate tall-grass prairie ecosystem. Our results showed that warming significantly (p = 0.001) shifted community structure, such that the differences of microbial communities between warming and control plots increased nonlinearly (R 2 = 0.578, p = 0.021) from spring to winter. Also, warming significantly (p