FastBiCmrMLM: a fast and powerful compressed variance component mixed logistic model for big genomic case-control genome-wide association study.

Large sample datasets have been regarded as the primary basis for innovative discoveries and the solution to missing heritability in genome-wide association studies. However, their computational complexity cannot consider all comprehensive effects and all polygenic backgrounds, which reduces the effectiveness of large datasets. To address these challenges, we included all effects and polygenic backgrounds in a mixed logistic model for binary traits and compressed four variance components into two. The compressed model combined three computational algorithms to develop an innovative method, called FastBiCmrMLM, for large data analysis. These algorithms were tailored to sample size, computational speed, and reduced memory requirements. To mine additional genes, linkage disequilibrium markers were replaced by bin-based haplotypes, which are analyzed by FastBiCmrMLM, named FastBiCmrMLM-Hap. Simulation studies highlighted the superiority of FastBiCmrMLM over GMMAT, SAIGE and fastGWA-GLMM in identifying dominant, small α (allele substitution effect), and rare variants. In the UK Biobank-scale dataset, we demonstrated that FastBiCmrMLM could detect variants as small as 0.03% and with α ≈ 0. In re-analyses of seven diseases in the WTCCC datasets, 29 candidate genes, with both functional and TWAS evidence, around 36 variants identified only by the new methods, strongly validated the new methods. These methods offer a new way to decipher the genetic architecture of binary traits and address the challenges outlined above.

Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review.

BACKGROUND: A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identify, describe, and appraise AI-Ms of CVD prediction in the general and special populations and develop a new independent validation score (IVS) for AI-Ms replicability evaluation. METHODS: PubMed, Web of Science, Embase, and IEEE library were searched up to July 2021. Data extraction and analysis were performed for the populations, distribution, predictors, algorithms, etc. The risk of bias was evaluated with the prediction risk of bias assessment tool (PROBAST). Subsequently, we designed IVS for model replicability evaluation with five steps in five items, including transparency of algorithms, performance of models, feasibility of reproduction, risk of reproduction, and clinical implication, respectively. The review is registered in PROSPERO (No. CRD42021271789). RESULTS: In 20,887 screened references, 79 articles (82.5% in 2017-2021) were included, which contained 114 datasets (67 in Europe and North America, but 0 in Africa). We identified 486 AI-Ms, of which the majority were in development (n = 380), but none of them had undergone independent external validation. A total of 66 idiographic algorithms were found; however, 36.4% were used only once and only 39.4% over three times. A large number of different predictors (range 5-52,000, median 21) and large-span sample size (range 80-3,660,000, median 4466) were observed. All models were at high risk of bias according to PROBAST, primarily due to the incorrect use of statistical methods. IVS analysis confirmed only 10 models as "recommended"; however, 281 and 187 were "not recommended" and "warning," respectively. CONCLUSION: AI has led the digital revolution in the field of CVD prediction, but is still in the early stage of development as the defects of research design, report, and evaluation systems. The IVS we developed may contribute to independent external validation and the development of this field.

Pitfalls in Developing Machine Learning Models for Predicting Cardiovascular Diseases: Challenge and Solutions.

In recent years, there has been explosive development in artificial intelligence (AI), which has been widely applied in the health care field. As a typical AI technology, machine learning models have emerged with great potential in predicting cardiovascular diseases by leveraging large amounts of medical data for training and optimization, which are expected to play a crucial role in reducing the incidence and mortality rates of cardiovascular diseases. Although the field has become a research hot spot, there are still many pitfalls that researchers need to pay close attention to. These pitfalls may affect the predictive performance, credibility, reliability, and reproducibility of the studied models, ultimately reducing the value of the research and affecting the prospects for clinical application. Therefore, identifying and avoiding these pitfalls is a crucial task before implementing the research. However, there is currently a lack of a comprehensive summary on this topic. This viewpoint aims to analyze the existing problems in terms of data quality, data set characteristics, model design, and statistical methods, as well as clinical implications, and provide possible solutions to these problems, such as gathering objective data, improving training, repeating measurements, increasing sample size, preventing overfitting using statistical methods, using specific AI algorithms to address targeted issues, standardizing outcomes and evaluation criteria, and enhancing fairness and replicability, with the goal of offering reference and assistance to researchers, algorithm developers, policy makers, and clinical practitioners.

[Identification and functional analysis of jasmonic acid signaling repressor McJAZ8 gene in Mentha canadensis].

Mentha canadensis, as a plant with medicinal and culinary uses, holds significant economic value. Jasmonic acid signaling repressor JAZ protein has a crucial role in regulating plant response to adversity stresses. The M. canadensis McJAZ8 gene is cloned and analyzed for protein characterization, protein interactions, and expression patterns, so as to provide genetic resources for molecular breeding of M. canadensis for stress tolerance. This experiment will analyze the protein structural characteristics, subcellular localization, protein interactions, and gene expression of McJAZ8 using bioinformatics, yeast two-hybrid(Y2H), transient expression in tobacco leaves, qRT-PCR, and other technologies. The results show that:(1)The full length of the McJAZ8 gene is 543 bp, encoding 180 amino acids. The McJAZ8 protein contains conserved TIFY and Jas domains and exhibits high homology with Arabidopsis thaliana AtJAZ1 and AtJAZ2.(2)The McJAZ8 protein is localized in the nucleus and cytoplasm.(3)The Y2H results show that McJAZ8 interacts with itself or McJAZ1/3/4/5 proteins to form homologous or heterologous dimers.(4)McJAZ8 is expressed in different tissue, with the highest expression level in young leaves. In terms of leaf sequence, McJAZ8 shows the highest expression level in the fourth leaf and the lowest expression level in the second leaf.(5) In leaves and roots, the expression of McJAZ8 is upregulated to varying degrees under methyl jasmonate(MeJA), drought, and NaCl treatments. The expression of McJAZ8 shows an initial upregulation followed by a downregulation pattern under CdCl_2 treatment. In leaves, the expression of McJAZ8 tends to gradually decrease under CuCl_2 treatment, while in roots, it initially decreases and then increases before decreasing again. In both leaves and roots, the expression of McJAZ8 is downregulated to varying degrees under AlCl_(3 )treatment. This study has enriched the research on jasmonic acid signaling repressor JAZ genes in M. canadensis and provided genetic resources for the molecular breeding of M. canadensis.

Overexpression of an Integument Esterase Gene LbEST-inte4 Infers the Malathion Detoxification in Liposcelis bostrychophila (Psocoptera: Liposcelididae).

Liposcelis bostrychophila, commonly known as booklouse, is an important stored-product pest worldwide. Studies have demonstrated that booklices have developed resistance to several insecticides. In this study, an integument esterase gene, LbEST-inte4, with upregulated expression, was characterized in L. bostrychophila. Knockdown of LbEST-inte4 resulted in a substantial increase in the booklice susceptibility to malathion. Overexpression of LbEST-inte4 in Drosophila melanogaster significantly enhanced its malathion tolerance. Molecular modeling and docking analysis suggested potential interactions between LbEST-inte4 and malathion. When overexpressed LbEST-inte4 in Sf9 cells, a notable elevation in esterase activity and malathion tolerance was observed. HPLC analysis indicated that the LbEST-inte4 enzyme could effectively degrade malathion. Taken together, the upregulated LbEST-inte4 appears to contribute to malathion tolerance in L. bostrychophila by facilitating the depletion of malathion. This study elucidates the molecular mechanism underlying malathion detoxification and provides the foundations for the development of effective prevention and control measures against psocids.

Candidatus Liberibacter asiaticus influences the emergence of the Asian citrus psyllid Diaphorina citri by regulating key cuticular proteins.

The Asian citrus psyllid, Diaphorina citri, is the primary vector of the HLB pathogen, Candidatus Liberibacter asiaticus (CLas). The acquisition of CLas shortens the developmental period of nymphs, accelerating the emergence into adulthood and thereby facilitating the spread of CLas. Cuticular proteins (CPs) are involved in insect emergence. In this study, we investigated the molecular mechanisms underlying CLas-promoted emergence in D. citri via CP mediation. Here, a total of 159 CP genes were first identified in the D. citri genome. Chromosomal location analysis revealed an uneven distribution of these CP genes across the 13 D. citri chromosomes. Proteomic analysis identified 54 differentially expressed CPs during D. citri emergence, with 14 CPs exhibiting significant differential expression after CLas acquisition. Five key genes, Dc18aa-1, Dc18aa-2, DcCPR-24, DcCPR-38 and DcCPR-58, were screened from the proteome and CLas acquisition. The silencing of these 5 genes through a modified feeding method significantly reduced the emergence rate and caused various abnormal phenotypes, indicating the crucial role that these genes play in D. citri emergence. This study provides a comprehensive overview of the role of CPs in D. citri and reveals that CLas can influence the emergence process of D. citri by regulating the expression of CPs. These key CPs may serve as potential targets for future research on controlling huanglongbing (HLB) transmission.

Effects of environmental microplastic exposure on Chlorella sp. biofilm characteristics and its interaction with nitric oxide signaling.

Microalgal biofilm is promising in simultaneous pollutants removal, CO2 fixation, and biomass resource transformation when wastewater is used as culturing medium. Nitric oxide (NO) often accumulates in microalgal cells under wastewater treatment relevant abiotic stresses such as nitrogen deficiency, heavy metals, and antibiotics. However, the influence of emerging contaminants such as microplastics (MPs) on microalgal intracellular NO is still unknown. Moreover, the investigated MPs concentrations among existing studies were mostly several magnitudes higher than in real wastewaters, which could offer limited guidance for the effects of MPs on microalgae at environment-relevant concentrations. Therefore, this study investigated three commonly observed MPs in wastewater at environment-relevant concentrations (10-10,000 µg/L) and explored their impacts on attached Chlorella sp. growth characteristics, nutrients removal, and anti-oxidative responses (including intracellular NO content). The nitrogen source NO3--N at 49 mg/L being 20 % of the nitrogen strength in classic BG-11 medium was selected for MPs exposure experiments because of least intracellular NO accumulation, so that disturbance of intracellular NO by nitrogen availability could be avoided. Under such condition, 10 µg/L polyethylene (PE) MPs displayed most significant microalgal growth inhibition comparing with polyvinyl chloride (PVC) and polyamide (PA) MPs, showing extraordinarily low chlorophyll a/b ratios, and highest superoxide dismutase (SOD) activity and intracellular NO content after 12 days of MPs exposure. PVC MPs exposed cultures displayed highest malonaldehyde (MDA) content because of the toxic characteristics of organochlorines, and most significant correlations of intracellular NO content with conventional anti-oxidative parameters of SOD, CAT (catalase), and MDA. MPs accelerated phosphorus removal, and the type rather than concentration of MPs displayed higher influences, following the trend of PE > PA > PVC. This study expanded the knowledge of microalgal biofilm under environment-relevant concentrations of MPs, and innovatively discovered the significance of intracellular NO as a more sensitive indicator than conventional anti-oxidative parameters under MPs exposure.

Do autistic adults spontaneously reason about belief? A detailed exploration of alternative explanations.

Southgate et al.'s (Southgate 2007 Psychol. Sci. 18, 587-92 (doi:10.1111/j.1467-9280.2007.01944.x)) anticipatory-looking paradigm has presented exciting yet inconclusive evidence surrounding spontaneous mentalizing in autism. The present study aimed to develop this paradigm to address alternative explanations for the lack of predictive eye movements on false-belief tasks by autistic adults. This was achieved through implementing a multi-trial design with matched true-belief conditions, and both high and low inhibitory demand false-belief conditions. We also sought to inspect if any group differences were related to group-specific patterns of attention on key events. Autistic adults were compared with non-autistic adults on this adapted implicit mentalizing task and an established explicit task. The two groups performed equally well in the explicit task; however, autistic adults did not show anticipatory-looking behaviour in the false-belief trials of the implicit task. Critically, both groups showed the same attentional distribution in the implicit task prior to action prediction, indicating that autistic adults process information from social cues in the same way as non-autistic adults, but this information is not then used to update mental representations. Our findings further document that many autistic people struggle to spontaneously mentalize others' beliefs, and this non-verbal paradigm holds promise for use with a wide range of ages and abilities.

Blockage of L2HGDH-mediated S-2HG catabolism orchestrates macrophage polarization to elicit antitumor immunity.

The high infiltration of tumor-associated macrophages (TAMs) in the immunosuppressive tumor microenvironment prominently attenuates the efficacy of immune checkpoint blockade (ICB) therapies, yet the underlying mechanisms are not fully understood. Here, we investigate the metabolic profile of TAMs and identify S-2-hydroxyglutarate (S-2HG) as a potential immunometabolite that shapes macrophages into an antitumoral phenotype. Blockage of L-2-hydroxyglutarate dehydrogenase (L2HGDH)-mediated S-2HG catabolism in macrophages promotes tumor regression. Mechanistically, based on its structural similarity to α-ketoglutarate (α-KG), S-2HG has the potential to block the enzymatic activity of 2-oxoglutarate-dependent dioxygenases (2-OGDDs), consequently reshaping chromatin accessibility. Moreover, S-2HG-treated macrophages enhance CD8+ T cell-mediated antitumor activity and sensitivity to anti-PD-1 therapy. Overall, our study uncovers the role of blockage of L2HGDH-mediated S-2HG catabolism in orchestrating macrophage antitumoral polarization and, further, provides the potential of repolarizing macrophages by S-2HG to overcome resistance to anti-PD-1 therapy.

[Response of Relationship Between Microplastic Abundance and Nitrogen Metabolism Function Microorganisms and Genes in Water].

The impact of microplastics (MPs) as a new type of pollutant on water pollution has become a research hotspot. To explore the response relationship between the abundance of MPs and nitrogen metabolism function in a freshwater environment, Lake Ulansuhai was used as the research object; the abundance of MPs in the water was detected using a Zeiss microscope, and the distribution characteristics of nitrogen metabolism functional bacteria and functional genes in the water were analyzed using metagenomics sequencing. The correlation analysis method was used to explore the relationship between the abundance of MPs and nitrogen metabolism functional microorganisms and nitrogen metabolism functional genes. The results showed that the presence of MPs in freshwater environments had a higher impact on Cyanobacteria and Firmicutes as the dominant phyla, and the presence of MPs promoted their enrichment and growth. Among the dominant bacterial genera, MPs promoted the growth of Mycobacterium and inhibited Candidatus_Planktopila more significantly, further indicating that in freshwater environments, MPs affected normal nitrogen metabolism by affecting microbial communities, and pathways such as carbon and nitrogen fixation and denitrification were important pathways for MPs to affect nitrogen metabolism. From the perspective of nitrogen metabolism functional genes, it was found that the abundance of MPs significantly affected some functional genes during nitrification (pmoA-amoA, pmoB-amoB, and pmoC-amoC), denitrification (nirK and napA), and dissimilatory nitrate reduction (nrfA) processes (P < 0.05). Moreover, the influence of MPs abundance on different functional genes in the same pathway of nitrogen metabolism varied, making the impact of MPs on aquatic environments very complex; thus, its harm to the water environment cannot be underestimated.

Platycodin D Ameliorates Type 2 Diabetes-Induced Myocardial Injury by Activating the AMPK Signaling Pathway.

The current study aimed to assess the effectiveness of pharmacological intervention with Platycodin D (PD), a critically active compound isolated from the roots of Platycodon grandiflorum, in mitigating cardiotoxicity in a murine model of type 2 diabetes-induced cardiac injury and in H9c2 cells in vitro. Following oral administration for 4 weeks, PD (2.5 mg/kg) significantly suppressed the elevation of fasting blood glucose (FBG) levels, improved dyslipidemia, and effectively inhibited the rise of the cardiac injury markers creatine kinase isoenzyme MB (CK-MB) and cardiac troponin T (cTnT). PD treatment could ameliorate energy metabolism disorders induced by impaired glucose uptake by activating AMPK protein expression in the DCM mouse model, thereby promoting the GLUT4 transporter and further activating autophagy-related proteins. Furthermore, in vitro experiments demonstrated that PD exerted a concentration-dependent increase in cell viability while also inhibiting palmitic acid and glucose (HG-PA)-stimulated H9c2 cytotoxicity and activating AMPK protein expression. Notably, the AMPK activator AICAR (1 mM) was observed to upregulate the expression of AMPK in H9c2 cells after high-glucose and -fat exposure. Meanwhile, we used AMPK inhibitor Compound C (20 µM) to investigate the effect of PD activation of AMPK on cells. In addition, the molecular docking approach was employed to dock PD with AMPK, revealing a binding energy of -8.2 kcal/mol and indicating a tight interaction between the components and the target. PD could reduce the expression of autophagy-related protein p62, reduce the accumulation of autophagy products, promote the flow of autophagy, and improve myocardial cell injury. In conclusion, it has been demonstrated that PD effectively inhibits cardiac injury-induced type 2 diabetes in mice and enhances energy metabolism in HG-PA-stimulated H9c2 cells by activating the AMPK signaling pathway. These findings collectively unveil the potential cardioprotective effects of PD via modulation of the AMPK signaling pathway.

Clinical research progress on acupuncture for the treatment of otogenic vertigo.

Otogenic vertigo is a common disorder that affects the vestibular system, which often results in considerable discomfort and impaired daily functioning. Traditional Chinese medicine (TCM), including acupuncture and moxibustion, has been historically utilized to manage the symptoms of vertigo. However, the effectiveness and methodology of these treatments have rarely been investigated in the medical literature. This study reviews the existing literature on the point selection, method, and therapeutic effect of acupuncture and moxibustion to provide a reference for the TCM treatment of otogenic vertigo. A literature search was performed using the PubMed search engine. The terms used included otogenic vertigo, acupuncture treatment, and acupuncture point selection. A total of 34 relevant articles were retrieved from PubMed. These suggest that the clinical treatment of otogenic vertigo should consider the functions of zang-fu organs and meridians and select different acupuncture treatment methods according to syndrome differentiation based on the difference between deficiency and excess. Acupuncture and moxibustion therapy should be based on acupoint selection, considering the syndrome differentiation, supplemented with experience. The treatment of otogenic vertigo with acupuncture and moxibustion refers to the selection of appropriate acupuncture methods under the guidance of TCM theory and following the principles of syndrome, disease, and meridian differentiation. Common acupuncture methods include body acupuncture, auricular acupuncture, scalp acupuncture, acupoint injection, electroacupuncture, and moxibustion. There are many acupuncture and moxibustion acupoints selected for the treatment of otogenic vertigo. Individualized treatment according to the patient's specific condition is effective and safe, which can help to improve the patient's vertigo symptoms and cerebral blood perfusion.

Platycodin D Ameliorates Cognitive Impairment in Type 2 Diabetes Mellitus Mice via Regulating PI3K/Akt/GSK3ß Signaling Pathway.

Objectives: The aim of this study was to investigate the ameliorative effect of platycodin D (PD) on cognitive dysfunction in type 2 diabetes mellitus (T2DM) and its potential molecular mechanisms of action in vivo and in vitro. Materials and methods: An animal model of cognitive impairment in T2DM was established using a single intraperitoneal injection of streptozotocin (100 mg/kg) after 8 weeks of feeding a high-fat diet to C57BL/6 mice. In vitro, immunofluorescence staining and Western blot were employed to analyze the effects of PD on glucose-induced neurotoxicity in mouse hippocampal neuronal cells (HT22). Results: PD (2.5 mg/kg) treatment for 4 weeks significantly suppressed the rise in fasting blood glucose in T2DM mice, improved insulin secretion deficiency, and reversed abnormalities in serum triglyceride, cholesterol, low-density lipoprotein, and high-density lipoprotein levels. Meanwhile, PD ameliorated choline dysfunction in T2DM mice and inhibited the production of oxidative stress and apoptosis-related proteins of the caspase family. Notably, PD dose-dependently prevents the loss of mitochondrial membrane potential, promotes phosphorylation of phosphatidylinositol 3 kinase and protein kinase B (Akt) in vitro, activates glycogen synthase kinase 3ß (GSK3ß) expression at the Ser9 site, and inhibits Tau protein hyperphosphorylation. Conclusions: These findings clearly indicated that PD could alleviate the neurological damage caused by T2DM, and the phosphorylation of Akt at Ser473 may be the key to its effect.

Biocontrol of plant parasitic nematodes by bacteria and fungi: a multi-omics approach for the exploration of novel nematicides in sustainable agriculture.

Plant parasitic nematodes (PPNs) pose a significant threat to global crop productivity, causing an estimated annual loss of US $157 billion in the agriculture industry. While synthetic chemical nematicides can effectively control PPNs, their overuse has detrimental effects on human health and the environment. Biocontrol agents (BCAs), such as bacteria and fungi in the rhizosphere, are safe and promising alternatives for PPNs control. These BCAs interact with plant roots and produce extracellular enzymes, secondary metabolites, toxins, and volatile organic compounds (VOCs) to suppress nematodes. Plant root exudates also play a crucial role in attracting beneficial microbes toward infested roots. The complex interaction between plants and microbes in the rhizosphere against PPNs is mostly untapped which opens new avenues for discovering novel nematicides through multi-omics techniques. Advanced omics approaches, including metagenomics, transcriptomics, proteomics, and metabolomics, have led to the discovery of nematicidal compounds. This review summarizes the status of bacterial and fungal biocontrol strategies and their mechanisms for PPNs control. The importance of omics-based approaches for the exploration of novel nematicides and future directions in the biocontrol of PPNs are also addressed. The review highlighted the potential significance of multi-omics techniques in biocontrol of PPNs to ensure sustainable agriculture.