Mechanistic insight on water dissociation on pristine low-index TiO2 surfaces from machine learning molecular dynamics simulations

Water adsorption and dissociation processes on pristine low-index TiO$_{2}$ interfaces are important but poorly understood outside the well-studied anatase (101) and rutile (110). To understand these, we construct three sets of machine learning potentials that are simultaneously applicable to various TiO$_{2}$ surfaces, based on three density-functional-theory approximations. Here we show the water dissociation free energies on seven pristine TiO$_{2}$ surfaces, and predict that anatase (100), anatase (110), rutile (001), and rutile (011) favor water dissociation, anatase (101) and rutile (100) have mostly molecular adsorption, while the simulations of rutile (110) sensitively depend on the slab thickness and molecular adsorption is preferred with thick slabs. Moreover, using an automated algorithm, we reveal that these surfaces follow different types of atomistic mechanisms for proton transfer and water dissociation: one-step, two-step, or both. These mechanisms can be rationalized based on the arrangements of water molecules on the different surfaces. Our finding thus demonstrates that the different pristine TiO$_{2}$ surfaces react with water in distinct ways, and cannot be represented using just the low-energy anatase (101) and rutile (110) surfaces

Elucidating the molecular mechanisms of ozone therapy for neuropathic pain management by integrated transcriptomic and metabolomic approach

Introduction: Neuropathic pain remains a prevalent and challenging condition to treat, with current therapies often providing inadequate relief. Ozone therapy has emerged as a promising treatment option; however, its mechanisms of action in neuropathic pain remain poorly understood.Methods: In this study, we investigated the effects of ozone treatment on gene expression and metabolite levels in the brainstem and hypothalamus of a rat model, using a combined transcriptomic and metabolomic approach.Results: Our findings revealed significant alterations in key genes, including DCST1 and AIF1L, and metabolites such as Aconitic acid, L-Glutamic acid, UDP-glucose, and Tyrosine. These changes suggest a complex interplay of molecular pathways and region-specific mechanisms underlying the analgesic effects of ozone therapy.Discussion: Our study provides insights into the molecular targets of ozone treatment for neuropathic pain, laying the groundwork for future research on validating these targets and developing novel therapeutic strategies

Up-regulation of interferon-a/APOBEC3G signal pathway potently inactivates HIV-1 infectivity in resting CD4-T cells

Poster Presentation

Multi-tissue integrative analysis of personal epigenomes

Evaluating the impact of genetic variants on transcriptional regulation is a central goal in biological science that has been constrained by reliance on a single reference genome. To address this, we constructed phased, diploid genomes for four cadaveric donors (using long-read sequencing) and systematically charted noncoding regulatory elements and transcriptional activity across more than 25 tissues from these donors. Integrative analysis revealed over a million variants with allele-specific activity, coordinated, locus-scale allelic imbalances, and structural variants impacting proximal chromatin structure. We relate the personal genome analysis to the ENCODE encyclopedia, annotating allele- and tissue-specific elements that are strongly enriched for variants impacting expression and disease phenotypes. These experimental and statistical approaches, and the corresponding EN-TEx resource, provide a framework for personalized functional genomics

Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big data

Under the development pattern of the “double cycle”, optimizing urban economic resilience is tremendously meaningful to improving a city’s affordability and the adaptability of the economy and to promoting the Chinese economy to develop with high quality. Based on Baidu migration big data perspective, exploratory spatial data analysis (ESDA) and multi-scale geographical weighted regression (MGWR) model were used to analyze the spatial characteristics and driving factors of economic resilience in 287 Chinese cities in 2019. The results show that (1) the number of low-level economically resilient cities is the largest and distributed continuously, while the number of high-level economically resilient cities is the lowest and distributed in clusters and blocks; (2) compared with the Pearl River Delta and Yangtze River Delta, the population accumulation characteristic of the Beijing- Tianjin-Hebei region is relatively slow; (3) Both net inflow of population after spring festival and daily flow scale are significantly correlated with urban economic resilience, and the former will affect urban economic resilience; and (4) the spatial heterogeneity of each factor driving is significant, and they have different impact scales. The impact intensity is as follows: net population inflow > innovation ability > public financial expenditure > financial efficiency > urban size. First published online 07 February 202

Highly Conductive Fiberboards Made with Carbon and Wood Fibers

Carbon fibers (CFs) were mixed with wood fibers using the solution blend method to make highly conductive fiberboards. The microstructure, conductivity, shielding effectiveness (SE), and mechanical properties of fiberboards filled with CFs of various lengths and contents were investigated. The uniform distribution of CFs formed an excellent, three-dimensional conductive network. The CF-filled fiberboards exhibited evidence of percolation and piezoresistivity. A greater content of shorter CFs was necessary to realize the effects of percolation. The corresponding thresholds of fiberboards containing CFs of 2, 5, and 10 mm in length were 1.5%, 0.75%, and 0.5%, respectively. The volume resistance of fiberboards tended to be stable as the external pressure increased to 1.4 MPa. The volume resistivity of fiberboards reached equilibrium when the CF content was 10%. The fiberboards with greater than 10% CF content exhibited a SE of 30 dB above the average, yet they met the requirements for commercial application. The mechanical properties of fiberboards were investigated, and CFs were found to enhance the modulus of rupture (MOR) and modulus of elasticity (MOE). Therefore, it was concluded that fiberboards containing CF of 5 mm in length exhibited the best performance between percolation threshold and steady CF content

Clinical Analysis of Sphenoid Sinus Mucocele With Initial Neurological Symptoms

Background and Objectives: Neurological manifestations associated with sphenoid sinus mucocele (SSM) are easily misdiagnosed due to nonspecific symptoms. The objective is to analyze and report the clinical features of SSM presenting with neurological manifestations, to allow an earlier diagnosis and more timely intervention for this disease. Methods: This was a retrospective cross-sectional study including 19 patients. The detailed clinical information of 19 patients with the initial symptom of neurological manifestations caused by SSM presenting at the Second Affiliated Hospital of Wenzhou Medical University between January 2000 and May 2018 were retrospectively analyzed. Collected data including symptoms, signs, neuroimaging, and pathologic diagnoses. Results: There were eleven males and 8 females, and their ages ranged from 23 to 71 years. Headache was the most frequent symptom, in 12 of the 19 patients presenting as the initial symptom. The visual disturbance included visual loss (4/19), diplopia (3/19), and another patient had both visual loss and diplopia. Neurophysical examination found that 4 patients presented with oculomotor nerve palsy, 4 patients had optic nerve or abducens nerve palsy, and 1 patient had optic neuropathy, oculomotor nerve palsy and abducens nerve palsy simultaneously. All patients underwent endoscopic surgery and had postoperative clinical symptom improvement. Conclusions: Headache is the most common symptom of SSM and should be on the differential diagnosis of patients presenting with headache, even if in isolation. The results suggest that CT and MRI are the best tools in diagnosis of SSM and endoscopic sphenoidotomy is a safe and effective method in the treatment of SSM.</p

A state of art review on time series forecasting with machine learning for environmental parameters in agricultural greenhouses

Agricultural greenhouse production has to require a stable and acceptable environment, it is therefore essential for future greenhouse production to obtain full and precisely internal dynamic environment parameters. Dynamic modeling based on machine learning methods, e.g., intelligent time series prediction modeling, is a popular and suitable way to solve the above issue. In this article, a systematic literature review on applying advanced time series models has been systematically conducted via a detailed analysis and evaluation of 61 pieces selected from 221 articles. The historical process of time series model application from the use of data and information strategies was first discussed. Subsequently, the accuracy and generalization of the model from the selection of model parameters and time steps, providing a new perspective for model development in this field, were compared and analyzed. Finally, the systematic review results demonstrate that, compared with traditional models, deep neural networks could increase data structure mining capabilities and overall information simulation capabilities through innovative and effective structures, thereby it could also broaden the selection range of environmental parameters for agricultural facilities and achieve environmental prediction end-to-end optimization via intelligent time series model based on deep neural networks