106 research outputs found

    Molecular Evolution of the Deuterolysin (M35) Family Genes in Coccidioides

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    Coccidioides is a primary fungal pathogen of humans, causing life-threatening respiratory disease known as coccidioidomycosis (Valley fever) in immunocompromised individuals. Recently, Sharpton et al (2009) found that the deuterolysin (M35) family genes were significantly expanded in both the Coccidioides genus and in U. reesii, and that Coccidioides has acquired three more M35 family genes than U. reesii. In the present work, phylogenetic analyses based on a total of 28 M35 family genes using different alignments and tree-building methods consistently revealed five clades with high nodal supports. Interestingly, likelihood ratio tests suggested significant differences in selective pressure on the ancestral lineage of three additional duplicated M35 family genes from Coccidioides species compared to the other lineages in the phylogeny, which may be associated with novel functional adaptations of M35 family genes in the Coccidioides species, e.g., recent pathogenesis acquisition. Our study adds to the expanding view of M35 family gene evolution and functions as well as establishes a theoretical foundation for future experimental investigations

    Anisotropic scattering characteristics of nanoparticles in different morphologies: improving the temperature uniformity of tumors during thermal therapy using forward scattering

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    Precise control of the thermal damage area is the key issue during thermal therapy, which can be achieved by manipulating the light propagation in biological tissue. In the present work, a method is proposed to increase the uniformity of the specific absorption rate (SAR) distribution in tumors during laser-induced thermal therapy, which is proved to be effective in reducing the thermal damage of healthy tissue. In addition, a better way of manipulating light propagation in biological tissue is explored. It is found that the anisotropic scattering characteristics of nanoparticles are strongly dependent on their shapes, sizes, orientations, and incident wavelengths, which will strongly affect the light propagation in nanoparticle embedded biological tissue. Therefore, to obtain a better outcome from photothermal therapy, the scattering properties of nanoparticles are very important factors that need to be taken into consideration, along with the absorption efficiency. Further investigation finds that nanoparticles that predominantly scatter to the forward direction are favorable in obtaining a larger penetration depth of light, which will improve the uniformity of SAR and temperature distributions. This paper is meaningful for the application of nanoparticle-assisted laser-induced thermal therapy

    Ultrafast-and-Ultralight ConvNet-Based Intelligent Monitoring System for Diagnosing Early-Stage Mpox Anytime and Anywhere

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    Due to the lack of more efficient diagnostic tools for monkeypox, its spread remains unchecked, presenting a formidable challenge to global health. While the high efficacy of deep learning models for monkeypox diagnosis has been demonstrated in related studies, the overlook of inference speed, the parameter size and diagnosis performance for early-stage monkeypox renders the models inapplicable in real-world settings. To address these challenges, we proposed an ultrafast and ultralight network named Fast-MpoxNet. Fast-MpoxNet possesses only 0.27M parameters and can process input images at 68 frames per second (FPS) on the CPU. To counteract the diagnostic performance limitation brought about by the small model capacity, it integrates the attention-based feature fusion module and the multiple auxiliary losses enhancement strategy for better detecting subtle image changes and optimizing weights. Using transfer learning and five-fold cross-validation, Fast-MpoxNet achieves 94.26% Accuracy on the Mpox dataset. Notably, its recall for early-stage monkeypox achieves 93.65%. By adopting data augmentation, our model's Accuracy rises to 98.40% and attains a Practicality Score (A new metric for measuring model practicality in real-time diagnosis application) of 0.80. We also developed an application system named Mpox-AISM V2 for both personal computers and mobile phones. Mpox-AISM V2 features ultrafast responses, offline functionality, and easy deployment, enabling accurate and real-time diagnosis for both the public and individuals in various real-world settings, especially in populous settings during the outbreak. Our work could potentially mitigate future monkeypox outbreak and illuminate a fresh paradigm for developing real-time diagnostic tools in the healthcare field

    Case report: A case of ocular infection caused by Corynespora cassiicola

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    ObjectiveThe aim of this study is to identify the pathogen causing ocular infection in a Chinese patient and to describe its morphological characteristics.MethodsSamples from the patient’s intraoperative pus were collected for microscopic examination and culture. Morphology and drug sensitivities of the isolated fungus were analyzed. Ribosomal DNA (rDNA) sequencing was performed and blasted in GenBank.ResultsA strain of fungi was repeatedly isolated from pus samples in different types of medium. No conidia were shown when the isolate cultured on normal PDA medium, whereas pseudoseptate thick-walled conidia were shown when cultured on medium containing leaf leachate. The results of BLAST and phylogenetic trees based on internal transcribed spacer, beta-tubulin, translation elongation factor 1-alpha, and RNA polymerase II gene demonstrated that the isolated fungus was Corynespora cassiicola. Minimum inhibitory concentration results of this organism were as follows: anidulafungin, 0.06 μg/ml; amphotericin B, 0.12 μg/ml; micafungin, 0.06 μg/ml; caspofungin, 0.5 μg/ml; 5-fluorocytosine, >64 μg/ml; posaconazole, 2 μg/ml; voriconazole, 0.25 μg/ml; itraconazole, 0.5 μg/ml; fluconazole, 64 μg/ml.ConclusionThe case was infected with Corynespora cassiicola and led to eye suppurative endophthalmitis and blindness. Combined applications of morphological and molecular biology techniques facilitate accurate diagnosis of fungal infections

    PRIMA-1Met suppresses colorectal cancer independent of p53 by targeting MEK

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    This work was supported by Grant No. 81201779 (Hua Xiong) from the National Natural Science Youth Foundation; Grant No. 81502118 (Yanmei Zou) from the National Natural Science Youth Foundation; Grant No. 2014CFB250 (Yanmei Zou) from the Natural Science Foundation of Hubei Province; Grant No. 81372434 (Huihua Xiong) from the National Natural Science Foundation.PRIMA-1Met is the methylated PRIMA-1 (p53 reactivation and induction of massive apoptosis) and could restore tumor suppressor function of mutant p53 and induce p53 dependent apoptosis in cancer cells harboring mutant p53. However, p53 independent activity of PRIMA-1Met remains elusive. Here we reported that PRIMA-1Met attenuated colorectal cancer cell growth irrespective of p53 status. Kinase profiling revealed that mitogen-activated or extracellular signal-related protein kinase (MEK) might be a potential target of PRIMA-1Met. Pull-down binding and ATP competitive assay showed that PRIMA-1Met directly bound MEK in vitro and in cells. Furthermore, the direct binding sites of PRIMA-1Met were explored by using a computational docking model. Treatment of colorectal cancer cells with PRIMA-1Met inhibited p53-independent phosphorylation of MEK, which in turn impaired anchorage-independent cell growth in vitro. Moreover, PRIMA-1Met suppressed colorectal cancer growth in xenograft mouse model by inhibiting MEK1 activity. Taken together, our findings demonstrate a novel p53-independent activity of PRIMA-1Met to inhibit MEK and suppress colorectal cancer growth.Publisher PDFPeer reviewe

    Metabolomic analysis reveals spermatozoa and seminal plasma differences between Duroc and Liang guang Small-spotted pig

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    The Liang guang Small-spotted pig is a well-known Chinese indigenous pig that is valued for its exceptional meat quality. However, the Liang guang Small-spotted pig has a lower semen storage capacity, shorter storage time and worse semen quality compared to Duroc. Pig sperm used for artificial insemination (AI) loses part of vitality and quality when being stored in commercial solutions. Serious vitality losses and short shelf life of the semen are particularly prominent in Liang guang Small-spotted pig. In this study, the metabolites in seminal plasma and spermatozoa of Duroc and Liang guang Small-spotted pigs were identified using UHPLC–Q-TOF/MS technology. The findings indicated forty distinct metabolites concentrating on energy metabolic substrates and antioxidant capacity in Liang guang Small-spotted pig and Duroc seminal plasma, including D-Fructose, succinate, 2-dehydro-3-deoxy-d-gluconate, alanine betaine, citrate, carnitine, acetylcarnitine and so on. Seventeen different metabolites were explored, with a focus on glycerophospholipid metabolism in Liang guang Small-spotted pig and Duroc spermatozoa, primarily including glycerol 3-phosphate, acetylcarnitine, phosphatidylcholine (PC) 16:0/16:0, palmitoyl sphingomyelin, acetylcholine, choline, glycerophosphocholine, betaine, L-carnitine, creatinine and others. This study reveals the metabolite profile of spermatozoa and seminal plasma among different pig breeds and might be valuable for understanding the mechanisms that lead to sperm storage capacity. Metabolites involved in energy metabolism, antioxidant capacity and glycerophospholipid metabolism might be key to the poor sperm storage capacity in Liang guang Small-spotted pig

    AI is a viable alternative to high throughput screening: a 318-target study

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    : High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

    Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

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    While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)—present in some but not all cells—remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e−4), with recurrent somatic deletions of exons 1–5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5′ deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk
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