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AIM: To investigate the molecular mechanisms underlying memory impairment induced by high-altitude (HA) hypoxia, specifically focusing on the role of cold-inducible RNA-binding protein (CIRP) in regulating the AMPA receptor subunit GluR1 and its potential as a therapeutic target. METHODS: A mouse model was exposed to 14 days of hypobaric hypoxia (HH), simulating conditions at an altitude of 6000 m. Behavioral tests were conducted to evaluate memory function. The expression, distribution, and interaction of CIRP with GluR1 in neuronal cells were analyzed. The binding of CIRP to GluR1 mRNA and its impact on GluR1 protein expression were examined. Additionally, the role of CIRP in GluR1 regulation was assessed using Cirp knockout mice. The efficacy of the Tat-C16 peptide, which consists of the Tat sequence combined with the CIRP 110-125 amino acid sequence, was also tested for its ability to mitigate HH-induced memory decline. RESULTS: CIRP was primarily localized in neurons, with its expression significantly reduced following HH exposure. This reduction was associated with decreased GluR1 protein expression on the cell membrane and increased localization in the cytoplasm. The interaction between CIRP and GluR1 was diminished under HH conditions, leading to reduced GluR1 stability on the cell membrane and increased cytoplasmic relocation. These changes resulted in a decreased number of synapses and dendritic spines, impairing learning and memory functions. Administration of the Tat-C16 peptide effectively ameliorated these impairments by modulating GluR1 expression and distribution in HH-exposed mice. CONCLUSION: CIRP plays a critical role in maintaining synaptic integrity under hypoxic conditions by regulating GluR1 expression and distribution. The Tat-C16 peptide shows promise as a therapeutic strategy for alleviating cognitive decline associated with HA hypoxia.
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Hipóxia , Transtornos da Memória , Camundongos Knockout , Neurônios , Proteínas de Ligação a RNA , Receptores de AMPA , Animais , Receptores de AMPA/metabolismo , Proteínas de Ligação a RNA/metabolismo , Transtornos da Memória/metabolismo , Transtornos da Memória/etiologia , Camundongos , Neurônios/metabolismo , Neurônios/efeitos dos fármacos , Hipóxia/metabolismo , Masculino , Camundongos Endogâmicos C57BL , Membrana Celular/metabolismo , Membrana Celular/efeitos dos fármacosRESUMO
Owing to sluggish reaction kinetics and high potential, oxygen evolution reaction (OER) electrocatalysts face a trade-off between activity and stability. Herein, an innovative topological strategy is presented for preparing 2D multimetallic (oxy)hydroxide, including ternary CoFeZn, quaternary CoFeMnZn, and high-entropy CoFeMnCuZn. The key to the synthesis lies in using Ca-rich brownmillerite oxide as a precursor, which possesses inherent structural flexibility enabling tailored elemental adjustments and topologically transforms from a point-shared structure of metal-oxygen octahedrons into an edge-shared structure under alkaline conditions. The presence of Zn in the catalysts causes a shift in the center of the O2p band toward the Fermi level, resulting in more Co4+ species, which drive holes into oxygen ligands to promote intramolecular oxygen coupling. The triggered lattice oxidation mechanism is identified by detecting peroxo-like (O2 2-) negative species using tetramethylammonium chemical probe, along with 18O isotope labeling experiments. As a result, the catalyst demonstrates an overpotential of 267 mV at 10 mA cm-2, ranking it among the top-performing non-Ni-based catalysts. Importantly, the catalysts also show high Fe-leaching resistance during OER compared to conventional NiFe and CoFe hydroxides/(oxy)hydroxides. The assembled zinc-air battery enables stable operation for over 225 h at a low charging voltage of 1.93 V.
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Deep graph neural networks are extensively utilized to predict chemical reactivity and molecular properties. However, because of the complexity of chemical space, such models often have difficulty extrapolating beyond the chemistry contained in the training set. Augmenting the model with quantum mechanical (QM) descriptors is anticipated to improve its generalizability. However, obtaining QM descriptors often requires CPU-intensive computational chemistry calculations. To identify when QM descriptors help graph neural networks predict chemical properties, we conduct a systematic investigation of the impact of atom, bond, and molecular QM descriptors on the performance of directed message passing neural networks (D-MPNNs) for predicting 16 molecular properties. The analysis surveys computational and experimental targets, as well as classification and regression tasks, and varied data set sizes from several hundred to hundreds of thousands of data points. Our results indicate that QM descriptors are mostly beneficial for D-MPNN performance on small data sets, provided that the descriptors correlate well with the targets and can be readily computed with high accuracy. Otherwise, using QM descriptors can add cost without benefit or even introduce unwanted noise that can degrade model performance. Strategic integration of QM descriptors with D-MPNN unlocks potential for physics-informed, data-efficient modeling with some interpretability that can streamline de novo drug and material designs. To facilitate the use of QM descriptors in machine learning workflows for chemistry, we provide a set of guidelines regarding when and how to best leverage QM descriptors, a high-throughput workflow to compute them, and an enhancement to Chemprop, a widely adopted open-source D-MPNN implementation for chemical property prediction.
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Single-atom catalysts (SACs) with unitary active sites hold great promise for realizing high selectivity toward a single product in the CO2 electroreduction reaction (CO2RR). However, achieving high Faradaic efficiency (FE) of multielectron products like methane on SACs is still challenging. Herein, we report a pressure-regulating strategy that achieves 83.5 ± 4% FE for the CO2-to-CH4 conversion on the asymmetric Cu-N2 sites, representing one of the best CO2-to-CH4 performances. Elevated CO2 pressure was demonstrated as an efficient way to inhibit the hydrogen evolution reaction via promoting the competing adsorption of reactant CO2, regardless of the nature of the active sites. Meanwhile, the asymmetric Cu-N2 structure could endow the Cu sites with stronger electronic coupling with *CO, thus suppressing the desorption of *CO and facilitating the following hydrogenation of *CO to *CHO. This work provides a synergetic strategy of the pressure-induced reaction environment regulating and the electronic structure modulating for selective CO2RR toward targeted products.
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OBJECTIVE: To compare the saccule-to-utricle ratio in early- versus late-stage Meniere's disease (MD) patients based on magnetic resonance imaging (MRI) images. METHODS: In this retrospective study, we performed 3-dimensional real inversion recovery (3D-real IR) MRI 24 h after intratympanic gadolinium administration in unilateral MD patients at early-stage (n = 56) and late-stage (n = 70). Two radiologists independently graded endolymphatic hydrops (EH) and the saccule-to-utricle ratio inversion (SURI) was compared between the two groups. Furthermore, early-stage MD patients were further divided into two subgroups based on disease duration: ≤6 months (n = 20) and >6 months (n = 36) and the SURI was compared. RESULTS: Among the 56 patients in the early-stage group, 26 cases (46.43%) exhibited an enlarged saccule that is larger than the utricle, showing SURI. In contrast, among the late-stage MD, only four cases (5.71%) showed SURI (p < 0.001). In the early-stage MD subgroup with a disease duration of ≤6 months, the proportion of SURI was 70% (14/20), which was higher than that in the subgroup with a disease duration of >6 months (33.33%, 12/36, p = 0.02). CONCLUSION: SURI may serve as an effective imaging marker for diagnosis of early-stage MD. Our finding suggests that endolymphatic hydrops in MD may primarily originate from the saccule. LEVEL OF EVIDENCE: Level 3 Laryngoscope, 2024.
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CRISPR/Cas and Argonaute (Ago) proteins, which target specific nucleic acid sequences, can be applied as diagnostic tools. Despite high specificity and efficiency, achieving sensitive detection often necessitates a preamplification step that involves opening the lid and multistep operation, which may elevate the risk of contamination and prove inadequate for point-of-care testing. Hence, various one-pot detection strategies have been developed that enable preamplification and sensing in a single operation. We outline the challenges of one-pot detection with Cas and Ago proteins, present several main implementation strategies, and discuss future prospects. This review offers comprehensive insights into this vital field and explores potential improvements to detection methods that will be beneficial for human health.
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BACKGROUND: Alzheimer's disease (AD) is a recognized complex and severe neurodegenerative disorder, presenting a significant challenge to global health. Its hallmark pathological features include the deposition of ß-amyloid plaques and the formation of neurofibrillary tangles. Given this context, it becomes imperative to develop an early and accurate biomarker model for AD diagnosis, employing machine learning and bioinformatics analysis. METHODS: In this study, single-cell data analysis was employed to identify cellular subtypes that exhibited significant differences between the diseased and control groups. Following the identification of NK cells, hdWGCNA analysis and cellular communication analysis were conducted to pinpoint NK cell subset with the most robust communication effects. Subsequently, three machine learning algorithms-LASSO, Random Forest, and SVM-RFE-were employed to jointly screen for NK cell subset modular genes highly associated with AD. A logistic regression diagnostic model was then designed based on these characterized genes. Additionally, a protein-protein interaction (PPI) networks of model genes was established. Furthermore, unsupervised cluster analysis was conducted to classify AD subtypes based on the model genes, followed by the analysis of immune infiltration in the different subtypes. Finally, Spearman correlation coefficient analysis was utilized to explore the correlation between model genes and immune cells, as well as inflammatory factors. RESULTS: We have successfully identified three genes (RPLP2, RPSA, and RPL18A) that exhibit a high association with AD. The nomogram based on these genes provides practical assistance in diagnosing and predicting patients' outcomes. The interconnected genes screened through PPI are intricately linked to ribosome metabolism and the COVID-19 pathway. Utilizing the expression of modular genes, unsupervised cluster analysis unveiled three distinct AD subtypes. Particularly noteworthy is subtype C3, characterized by high expression, which correlates with immune cell infiltration and elevated levels of inflammatory factors. Hence, it can be inferred that the establishment of an immune environment in AD patients is closely intertwined with the heightened expression of model genes. CONCLUSION: This study has not only established a valuable diagnostic model for AD patients but has also delved deeply into the pivotal role of model genes in shaping the immune environment of individuals with AD. These findings offer crucial insights into early AD diagnosis and patient management strategies.
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Doença de Alzheimer , Biomarcadores , Comunicação Celular , Células Matadoras Naturais , Aprendizado de Máquina , Doença de Alzheimer/diagnóstico , Doença de Alzheimer/imunologia , Humanos , Biomarcadores/metabolismo , Mapas de Interação de Proteínas , Biologia Computacional , Feminino , MasculinoRESUMO
BACKGROUND: Recent insights suggest that lipids and statin medication play a role in the development of sensorineural hearing loss (SNHL), yet the exact role remains controversial. This research applied Mendelian randomization (MR) to assess whether lipids and statin medication are associated with an increased risk of SNHL. METHODS: A two-sample MR was used in this study. Genetic instruments were constructed from variants associated with risk factors. Data for lipids and statin medication were obtained from the IEU OpenGWAS project, and for SNHL from the Finngen research project, which comprises 32,487 individuals with SNHL and 331,736 control individuals. RESULTS: Genetically predicted higher levels of triglycerides were associated with an increased risk of SNHL. The use of genetically predicted atorvastatin was associated with a lower risk of SNHL. Rosuvastatin has demonstrated potential in treating SNHL, yet further investigations are warranted to elucidate its relationship with SNHL. Insufficient evidence was available to suggest that the genetically predicted level of high-density lipoprotein cholesterol or low-density lipoprotein cholesterol or the use of simvastatin were associated with SNHL. CONCLUSIONS: The study provides genetic evidence suggesting that increased levels of triglycerides in the blood could be a risk factor for SNHL and that the use of certain statin medications, including atorvastatin and rosuvastatin, could reduce the risk of SNHL. These results align with findings from previous observational studies that have linked hyperlipidemia with the risk of SNHL. LEVEL OF EVIDENCE: According to the Oxford Centre for Evidence-Based Medicine 2011 levels of Evidence, the study has a third level of Evidence Laryngoscope, 2024.
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Obtaining accurate enthalpies of formation of chemical species, ΔHf, often requires empirical corrections that connect the results of quantum mechanical (QM) calculations with the experimental enthalpies of elements in their standard state. One approach is to use atomization energy corrections followed by bond additivity corrections (BACs), such as those defined by Petersson et al. or Anantharaman and Melius. Another approach is to utilize isodesmic reactions (IDRs) as shown by Buerger et al. We implement both approaches in Arkane, an open-source software that can calculate species thermochemistry using results from various QM software packages. In this work, we collect 421 reference species from the literature to derive ΔHf corrections and fit atomization energy corrections and BACs for 15 commonly used model chemistries. We find that both types of BACs yield similar accuracy, although Anantharaman- and Melius-type BACs appear to generalize better. Furthermore, BACs tend to achieve better accuracy than IDRs for commonly used model chemistries, and IDRs can be less robust because of the sensitivity to the chosen reference species and reactions. Overall, Anantharaman- and Melius-type BACs are our recommended approach for achieving accurate QM corrections for enthalpies.
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Background: Frostbite is a chemia resulting from cold-induced skin damage. The process of frostbite is often accompanied by inflammation, and the therapeutic strategies focusing on anti-inflammation are the main direction to data. Tat-CIRP is a 15 amino acid peptide containing HIV protein and cold-inducible RNA-binding protein (CIRP), which is believed to compete with endogenous CIRP for myeloid differentiation 2 (MD2) binding. This study aims to investigate the efficacy of Tat-CIRP in the treatment of frostbite. Methods: A mouse model of frostbite was established, and on the first day after frostbite occurrence, Tat-CIRP peptide was administered intravenously via the tail with a dosage interval of one day for a total of three doses. Frozen mouse skin sections were subjected to histological analysis, including hematoxylin-eosin (HE) staining, Masson staining, and immunohistochemical examination. Western blotting was performed to detect the expression level of Ki-67 in mouse skin tissue. Results: One day after frostbite, mice exhibited skin swelling and a solid appearance. From day 1 to 5 after frostbite, MD2 expression was significantly upregulated, while CIRP expression was downregulated. Compared to the frostbite group, mice treated with Tat-CIRP showed accelerated frostbite recovery, reduced levels of inflammatory factors and MD2. Furthermore, the expression of cell proliferation-associated protein Ki-67 and angiogenesis-related protein CD31 was upregulated. Conclusion: Tat-CIRP promotes frozen wound healing via inhibiting inflammation and promoting angiogenesis in frostbitten mice.
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The extremely poor solution stability and massive carrier recombination have seriously prevented III-V semiconductor nanomaterials from efficient and stable hydrogen production. In this work, an anodic reconstruction strategy based on group III-V active semiconductors is proposed for the first time, resulting in 19-times photo-gain. What matters most is that the device after anodic reconstruction shows very superior stability under the protracted photoelectrochemical (PEC) test over 8100 s, while the final photocurrent density does not decrease but rather increases by 63.15%. Using the experiment and DFT theoretical calculation, the anodic reconstruction mechanism is elucidated: through the oxidation of indium clusters and the migration of arsenic atoms, the reconstruction formed p+-GaAs/a-InAsN. The hole concentration of the former is increased by 10 times (5.64 × 1018 cm-1 increases up to 5.95 × 1019 cm-1) and the band gap of the latter one is reduced to a semi-metallic state, greatly strengthening the driving force of PEC water splitting. This work turns waste into treasure, transferring the solution instability into better efficiency.
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Epigenetic regulators present novel opportunities for both ischemic stroke research and therapeutic interventions. While previous work has implicated that they may provide neuroprotection by potentially influencing coordinated sets of genes and pathways, most of them remain largely uncharacterized in ischemic conditions. In this study, we used the oxygen-glucose deprivation (OGD) model in the immortalized mouse hippocampal neuronal cell line HT-22 and carried out an RNAi screen on epigenetic regulators. PRMT5 was identified as a novel negative regulator of neuronal cell survival after OGD, which presented a phenotype of translocation from the cytosol to the nucleus upon oxygen and energy depletion both in vitro and in vivo. PRMT5 bound to the chromatin and a large number of promoter regions to repress downstream gene expression. Silencing Prmt5 significantly dampened the OGD-induced changes for a large-scale of genes, and gene ontology analysis showed that PRMT5-target genes were highly enriched for Hedgehog signaling. Encouraged by the above observation, mice were treated with middle cerebral artery occlusion with the PRMT5 inhibitor EPZ015666 and found that PRMT5 inhibition sustains protection against neuronal death in vivo. Together, these findings revealed a novel epigenetic mechanism of PRMT5 in cerebral ischemia and uncovered a potential target for neuroprotection.
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Isquemia Encefálica , Proteínas Hedgehog , Proteína-Arginina N-Metiltransferases , Animais , Camundongos , Isquemia Encefálica/genética , Glucose , Neuroproteção/genética , Oxigênio , Fenótipo , Proteína-Arginina N-Metiltransferases/genéticaRESUMO
Electrocatalytic CO2 reduction (ECR) to high value-added chemicals is an excellent method to attenuate the impact of greenhouse effect caused by CO2. At the same time, multicarbon products (C2+) get extensive attention in view of their relatively high energy density and market price. At present, Cu is an important metal electrocatalyst to convert CO2 into multicarbon products (e.g. ethylene, ethanol, and n-propanol); however, its poor selectivity impedes its practical application. It is well-known that the Cu(100) crystal facet can enhance the selectivity toward multicarbon products among different Cu crystal facets. Herein, the Cu nanoparticles were firstly prepared using the inductive effect of different gases (CO2, CO, Ar, N2, and air) during the Cu electrodeposition processes, in which the CO2-induced Cu catalyst (Cu-CO2) showed the largest normalized content of the Cu(100) crystal facet and the highest C2+ faradaic efficiency of 69% at a current density of 80 mA cm-2 in ECR. Subsequently, the different CO2 pressures during the Cu electrodepositions were studied to reveal the optimal CO2 pressure in the CO2-induced Cu synthesis for improved Cu(100) content as well as C2+ faradaic efficiency. Finally, density functional theory (DFT) calculations confirmed that CO2 molecules preferred to get adsorbed on the Cu(100) crystal facet, which resulted in not only the presence of dominant Cu(100) during the CO2-induced Cu synthesis but also the good electrocatalytic performance in ECR.
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STUDY OBJECTIVES: Growing evidences have documented various abnormalities of the white matter bundles in people with narcolepsy. We sought to evaluate topological properties of brain structural networks, and their association with symptoms and neuropathophysiological features in people with narcolepsy. METHODS: Diffusion tensor imaging was conducted for people with narcolepsy (nâ =â 30) and matched healthy controls as well as symptoms assessment. Structural connectivity for each participant was generated to analyze global and regional topological properties and their correlations with narcoleptic features. Further human brain transcriptome was extracted and spatially registered for connectivity vulnerability. Genetic functional enrichment analysis was performed and further clarified using in vivo emission computed tomography data. RESULTS: A wide and dramatic decrease in structural connectivities was observed in people with narcolepsy, with descending network degree and global efficiency. These metrics were not only correlated with sleep latency and awakening features, but also reflected alterations of sleep macrostructure in people with narcolepsy. Network-based statistics identified a small hyperenhanced subnetwork of cingulate gyrus that was closely related to rapid eye movement sleep behavior disorder (RBD) in narcolepsy. Further imaging genetics analysis suggested glutamatergic signatures were responsible for the preferential vulnerability of connectivity alterations in people with narcolepsy, while additional PET/SPECT data verified that structural alteration was significantly correlated with metabotropic glutamate receptor 5 (mGlutR5) and N-methyl-D-aspartate receptor (NMDA). CONCLUSIONS: People with narcolepsy endured a remarkable decrease in the structural architecture, which was not only closely related to narcolepsy symptoms but also glutamatergic signatures.
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Encéfalo , Imagem de Tensor de Difusão , Narcolepsia , Humanos , Narcolepsia/fisiopatologia , Narcolepsia/genética , Narcolepsia/diagnóstico por imagem , Masculino , Adulto , Feminino , Encéfalo/diagnóstico por imagem , Encéfalo/fisiopatologia , Encéfalo/patologia , Rede Nervosa/fisiopatologia , Rede Nervosa/diagnóstico por imagem , Substância Branca/diagnóstico por imagem , Substância Branca/fisiopatologia , Substância Branca/patologia , Transtorno do Comportamento do Sono REM/fisiopatologia , Transtorno do Comportamento do Sono REM/diagnóstico por imagem , Transtorno do Comportamento do Sono REM/genética , Estudos de Casos e Controles , Pessoa de Meia-IdadeRESUMO
Background: Plantar fasciitis (PF) is the most common cause of chronic heel pain among adults. Extracorporeal shock wave therapy (ESWT) is the recommended in the current guidelines, and the small needle-knife yields acceptable clinical effects for musculoskeletal pain. Objective: To systematically compare the efficacy of the small needle-knife versus ESWT for the treatment of PF. Methods: The present review was registered in the International Prospective Register of Systematic Reviews (i.e., "PROSPERO", CRD42023448813). Two of the authors searched electronic databases for randomized controlled trials (RCTs) comparing the small needle-knife versus ESWT for the treatment of PF, and collected outcomes including curative effect, pain intensity, and function. Risk of bias was assessed using the Cochrane Handbook Risk of Bias tool and the quality of the RCTs was evaluated according to the Jadad Scale. The same authors independently performed data extraction from the included studies, which were imported into Review Manager version 5.4.1(Copenhagen: Nordic Cochrane Centre, The Cochrane Collaboration, 2020) for meta-analysis. Results: The initial literature search retrieved 886 studies, of which 6 were eventually included in this study. Meta-analysis revealed no significant difference in curative effect (OR = 1.87; 95 % CI [0.80, 4.37], p = .15) nor short-term pain improvement (MD = 2.20; 95 % CI [-2.77, 7.16], p = .39) between the small needle-knife and ESWT. However, the small needle-knife may be more effective than ESWT for pain improvement in mid-term (MD = 9.11; 95 % CI [5.08, 13.15], pï¼ .00001) and long-term follow-ups (MD = 10.71; 95 % CI [2.18, 19.25], pï¼ .00001). Subgroup analysis revealed that the small needle-knife combined with a corticosteroid injection yielded a statistically significant difference in reduction of pain intensity at all follow-ups (MD = 4.84; 95 % CI [1.33, 8.36], p = .007; MD = 10.99; 95 % CI [8.30, 13.69], pï¼ .00001; MD = 17.87; 95 % CI [15.26, 20.48], pï¼ .00001). Meta-analysis revealed no statistical differences in short-term (MD = 1.34; 95 % CI [-3.19, 5.86], p = .56) and mid-term (MD = 2.75; 95 % CI [-1.21, 6.72], p = . 17) functional improvement between the needle-knife and ESWT groups. In a subgroup analysis of moderate-quality studies, the small needle-knife demonstrated a favorable effect on mid-term functional improvement (MD = 1.58; 95 % CI [0.52, 2.65], p = .004), with low heterogeneity (χ2 = 0.77, p = .038, I2 = 0 %). Conclusion: Pain reduction and functional improvement are essential for the treatment of PF. Therefore, treatment using the small needle-knife may be superior to ESWT. Results of this systematic review and meta-analysis may provide alternative treatment options for patients with PF as well as more reliable, evidence-based recommendations supporting use of the small needle-knife.
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Deep learning has become a powerful and frequently employed tool for the prediction of molecular properties, thus creating a need for open-source and versatile software solutions that can be operated by nonexperts. Among the current approaches, directed message-passing neural networks (D-MPNNs) have proven to perform well on a variety of property prediction tasks. The software package Chemprop implements the D-MPNN architecture and offers simple, easy, and fast access to machine-learned molecular properties. Compared to its initial version, we present a multitude of new Chemprop functionalities such as the support of multimolecule properties, reactions, atom/bond-level properties, and spectra. Further, we incorporate various uncertainty quantification and calibration methods along with related metrics as well as pretraining and transfer learning workflows, improved hyperparameter optimization, and other customization options concerning loss functions or atom/bond features. We benchmark D-MPNN models trained using Chemprop with the new reaction, atom-level, and spectra functionality on a variety of property prediction data sets, including MoleculeNet and SAMPL, and observe state-of-the-art performance on the prediction of water-octanol partition coefficients, reaction barrier heights, atomic partial charges, and absorption spectra. Chemprop enables out-of-the-box training of D-MPNN models for a variety of problem settings in fast, user-friendly, and open-source software.
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Aprendizado de Máquina , Software , Redes Neurais de Computação , Fenômenos Químicos , ÁguaRESUMO
Limited information on the virome and bacterial community hampers our ability to discern systemic ecological risk factors that cause cattle diarrhea, which has become a pressing issue in the control of disease. A total of 110 viruses, 1,011 bacterial genera, and 322 complete viral genomes were identified from 70 sequencing samples mixed with 1,120 fecal samples from 58 farms in northeast China. For the diarrheic samples, the identified virome and bacterial community varied in terms of composition, abundance, diversity, and geographic distribution in relation to different disease-associated ecological factors; the abundance of identified viruses and bacteria was significantly correlated with the host factors of clinical status, cattle type, and age, and with environmental factors such as aquaculture model and geographical location (P < 0.05); a significant interaction occurred between viruses and viruses, bacteria and bacteria, as well as between bacteria and viruses (P < 0.05). The abundance of SMB53, Butyrivibrio, Facklamia, Trichococcus, and Turicibacter was significantly correlated with the health status of cattle (P < 0.05). The proportion of BRV, BCoV, BKV, BToV, BoNoV, BoNeV, BoAstV, BEV, BoPV, and BVDV in 1,120 fecal samples varied from 1.61% to 12.05%. A series of significant correlations were observed between the prevalence of individual viruses and the disease-associated ecological factors. A genome-based phylogenetic analysis revealed high variability of 10 bovine enteric viruses. The bovine hungarovirus was initially identified in both dairy and beef cattle in China. This study elucidates the fecal virome and bacterial community signatures of cattle affected by diarrhea, and reveals novel disease-associated ecological risk factors, including cattle type, cattle age, aquaculture model, and geographical location.IMPORTANCEThe lack of data on the virome and bacterial community restricts our capability to recognize ecological risk factors for bovine diarrhea disease, thereby hindering our overall comprehension of the disease's cause. In this study, we found that, for the diarrheal samples, the identified virome and bacterial community varied in terms of composition, abundance, diversity, configuration, and geographic distribution in relation to different disease-associated ecological factors. A series of significant correlations were observed between the prevalence of individual viruses and the disease-associated ecological factors. Our study aims to uncover novel ecological risk factors of bovine diarrheal disease by examining the pathogenic microorganism-host-environment disease ecology, thereby providing a new perspective on the control of bovine diarrheal diseases.
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Doenças dos Bovinos , Vírus , Animais , Bovinos , Viroma , Filogenia , Vírus/genética , Bactérias/genética , Diarreia/epidemiologia , Doenças dos Bovinos/epidemiologia , Fatores de RiscoRESUMO
A closed-loop, autonomous molecular discovery platform driven by integrated machine learning tools was developed to accelerate the design of molecules with desired properties. We demonstrated two case studies on dye-like molecules, targeting absorption wavelength, lipophilicity, and photooxidative stability. In the first study, the platform experimentally realized 294 unreported molecules across three automatic iterations of molecular design-make-test-analyze cycles while exploring the structure-function space of four rarely reported scaffolds. In each iteration, the property prediction models that guided exploration learned the structure-property space of diverse scaffold derivatives, which were realized with multistep syntheses and a variety of reactions. The second study exploited property models trained on the explored chemical space and previously reported molecules to discover nine top-performing molecules within a lightly explored structure-property space.
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Noise-induced hearing loss (NIHL) is one of the most prevalent acquired sensorineural hearing loss etiologies and is characterized by the loss of cochlear hair cells, synapses, and nerve terminals. Currently, there are no agents available for the treatment of NIHL because drug delivery to the inner ear is greatly limited by the blood-labyrinth barrier. In this study, we used mesenchymal stem cell-derived small extracellular vesicles (MSC-sEVs) as nanoscale vehicles to deliver brain-derived neurotrophic factor (BDNF) and evaluated their protective effects in a mouse model of NIHL. Following intravenous administration, BDNF-loaded sEVs (BDNF-sEVs) efficiently increased the expression of BDNF protein in the cochlea. Systemic application of sEVs and BDNF-sEVs significantly attenuated noise-induced cochlear hair cell loss and NIHL in CBA/J mice. BDNF-sEVs also alleviated noise-induced loss of inner hair cell ribbon synapses and cochlear nerve terminals. In cochlear explants, sEVs and BDNF-sEVs effectively protected hair cells against H2O2-induced cell loss. Additionally, BDNF-sEVs remarkably ameliorated H2O2-induced oxidative stress, cell apoptosis, and cochlear nerve terminal degeneration. Transcriptomic analysis revealed that many mRNAs and miRNAs were involved in the protective actions of BDNF-sEVs against oxidative stress. Collectively, our findings reveal a novel therapeutic strategy of MSC-sEVs-mediated BDNF delivery for the treatment of NIHL.
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Vesículas Extracelulares , Perda Auditiva Provocada por Ruído , Animais , Camundongos , Fator Neurotrófico Derivado do Encéfalo , Cóclea/metabolismo , Vesículas Extracelulares/metabolismo , Perda Auditiva Provocada por Ruído/tratamento farmacológico , Perda Auditiva Provocada por Ruído/prevenção & controle , Peróxido de Hidrogênio/metabolismo , Camundongos Endogâmicos CBARESUMO
The plasma membrane Na+/H+ exchanger Salt Overly Sensitive 1 (SOS1) is crucial for plant salt tolerance. Unlike typical sodium/proton exchangers, SOS1 contains a large cytoplasmic domain (CPD) that regulates Na+/H+ exchange activity. However, the underlying modulation mechanism remains unclear. Here we report the structures of SOS1 from Arabidopsis thaliana in two conformations, primarily differing in CPD flexibility. The CPD comprises an interfacial domain, a cyclic nucleotide-binding domain-like domain (CNBD-like domain) and an autoinhibition domain. Through yeast cell-based Na+ tolerance test, we reveal the regulatory role of the interfacial domain and the activation role of the CNBD-like domain. The CPD forms a negatively charged cavity that is connected to the ion binding site. The transport of Na+ may be coupled with the conformational change of CPD. These findings provide structural and functional insight into SOS1 activity regulation.