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Formation of spatial vegetation patterns in heterogeneous environments
Functioning of many resource-limited ecosystems is facilitated through spatial patterns. Patterns can indicate ecosystems productivity and resilience, but the interpretation of a pattern requires good understanding of its structure and underlying biophysical processes. Regular patterns are understood to form autogenously through self-organization, for which exogenous heterogeneities are negligible. This has been corroborated by reaction-diffusion models which generate highly regular patterns in idealized homogeneous environments. However, such model-generated patterns are considerably more regular than natural patterns, which indicates that the concept of autogenous pattern formation is incomplete. Models can generate patterns which appear more natural when they incorporate exogenous random spatial heterogeneities (noise), such as microtopography or spatially varying soil properties. However, the mechanism through which noise influences the pattern formation has not been explained so far. Recalling that irregular patterns can form through stochastic processes, we propose that regular patterns can form through stochastic processes as well, where spatial noise is filtered through scale-dependent biophysical feedbacks. First, we demonstrate that the pattern formation in nonlinear reaction-diffusion models is highly sensitive to noise. We then propose simple stochastic processes which can explain why and how random exogenous heterogeneity influences the formation of regular and irregular patterns. Finally, we derive linear filters which reproduce the spatial structure and visual appearance of natural patterns well. Our work contributes to a more holistic understanding of spatial pattern formation in self-organizing ecosystems.
Personalized prediction of gait freezing using dynamic mode decomposition
The role of gut leakage and immune cell miss-homing on gut dysbiosis-induced lung inflammation in a DSS mice model
Background Inflammatory Bowel Disease (IBD), encompassing Crohn’s disease and ulcerative colitis, affects millions globally, with extraintestinal manifestations (EIMs) occurring in 25–40% of patients. Among these, respiratory complications are of particular concern, yet the immunologic and physiologic mechanisms underlying gut-lung interactions remain poorly understood. The gut-lung axis (GLA) describes bi-directional communication between the gut and lungs, where microbial dysbiosis in the gut can drive lung inflammation and immune dysregulation. Methods Mice were treated with 4% DSS for 7 days to induce colitis. Gut permeability, tight junction protein expression, lung inflammation, immune cell trafficking, and microbial translocation were assessed through histology, qPCR, flow cytometry, and GFP-tagged fecal microbiome experiments. Results DSS treatment led to significant disruption of the gut barrier, with upregulation of gut leakage markers and downregulation of tight junction proteins. Lung inflammation was characterized by elevated IL-17, neutrophil infiltration, and airway hyperresponsiveness. Flow cytometry revealed mis-homing of gut-primed immune cells (α4β7+ and CCR9 + CD4+) to the lungs and tracking bacteria via GFP- tagged fecal microbiome confirmed microbial translocation from the gut to the lungs which may contribute to lung inflammation. Conclusion Disrupted gut integrity facilitates microbial translocation and immune cell mis-homing, contributing to lung inflammation. These results provide new insights into how gut dysbiosis influences respiratory inflammation.
Index case testing uptake and determinants among HIV clients attending Shashemene town public health facilities, Southern Ethiopia
Knowledge, attitude, and practice of vasoactive agents infusions: Development and psychometric properties of a questionnaire with chinese clinical nurses
Background Inconsistencies with guidelines or standards regarding nurses’ practice of vasoactive agent infusion have been documented. Adequate knowledge and positive attitudes are critical for compliance. However, there are currently no validated tools specifically designed to measure the knowledge and attitudes related to vasoactive agent infusions among nurses. Objective The aim of this study was to develop and test the validity and reliability of the Chinese mainland version of Knowledge, Attitude, and Practice of Vasoactive Agents Infusions Questionnaire among nurses. Methods The initial questionnaire items were developed through a comprehensive literature review, expert consultation, and pilot study. From February to June 2024, cross-sectional data were collected using convenience sampling from 538 nurses across 9 hospitals in Sichuan Province, China. The reliability and validity of the scale were evaluated through internal consistency reliability, inter-rater reliability, exploratory factor analysis, and confirmatory factor analysis. Results The final version of the questionnaire included 33 items across 3 dimensions, explaining 78.04% of the variance, with item loadings ranging from 0.56 to 0.89. The content validity index ranged from 0.91 to 1.00, and the scale-level content validity index was 0.98.The overall Cronbach’s α for the questionnaire was 0.96, with Cronbach’s α for each dimension ranging from 0.96 to 0.98. The test-retest reliability for the entire questionnaire was 0.90, and for each dimension, it ranged from 0.90 to 0.94 (p < 0.05). The confirmatory factor analysis demonstrated acceptable fit indices for the three-dimensional model: χ²/(df) = 1.135, p = 0.200, RMSEA = 0.024, CFI = 0.986, TLI = 0.985, GFI = 0.884, and NFI = 0.895. Conclusion The Knowledge, Attitude, and Practice of Vasoactive Agents Infusions Questionnaire demonstrates good reliability and validity, making it a reliable measurement tool for assessing nurses’ attitudes and knowledge related to vasoactive agents’ infusions. This version will facilitate further research and advancements in this specific field of study.
Marein from Coreopsis tinctoria Nutt. alleviates oxidative stress and lipid accumulation via SIRT1/Nrf2 signaling
Verification of the chromosome number using cytogenetics and estimation of genome size via flow cytometry and k-mer analyses for representative Anoectochilus roxburghii accessions
Anoectochilus roxburghii (Wall.) Lindl. is a perennial herb of orchidaceae. Because of its functions of heat-clearing and blood-cooling, removing dampness, detoxification and enhancing immunity, it is considered as a nutritious medicinal plant with high economic value. Originating from Guangdong province, China, chromosome number and genome size of A. roxburghii (“Luofushan-1”) were determined through cytogenetics, flow cytometry, and k-mer analysis. We analyzed the karyotype of A. roxburghii using different cytogenetic markers, and the results showed a chromosome number of 2n = 80, but no sex-linked chromosome heterotropy was observed. For flow cytometry analysis, tomato and maize were used as internal standard, and the 2C DNA amount among sixteen Anoectochilus accessions ranged from 6.57 to 8.26 pg (including Luofushan-1). Additionally, a genome survey of “Luofushan-1” was performed using Illumina HiSeq 2000 DNA sequencing, k-mer analysis revealed that the genome size of “Luofushan-1” was approximately 5.68 Gbp. This comprehensive study establishes a foundation for subsequent whole-genome sequencing of A. roxburghii, contributing valuable insights into its genetic characteristics and paving the way for further research on this medicinal plant.
Toxicological assessment of omethoate insecticide in Allium cepa L.
AMD-FV: Adaptive margin loss and dual path network+ for deep face verification
Face verification is important in a variety of applications, for instance, access control, surveillance, and identification. Existing methods often struggle with the challenges of dataset imbalance and manual hyperparameter tuning. To address this, we propose the Adaptive Margin Loss and Dual Path Network+ (AMD-FV) for deep face verification. Two innovations are introduced, namely, Adaptive Margin Loss (AML) and Dual Path Network+ (DPN+). AML aims at automating the selection of margin and scale hyperparameters in large margin loss functions, thus, eliminating the need for manual tuning. Input dissimilarity information is used to estimate the margin, while the scale parameter is computed using the number of classes and AML’s range. Next, DPN+ enhances the original Dual Path Network by redesigning the first block with a series of 3x3 convolutions, batch normalization, and ReLU activations, leveraging shared connections across layers, leading to increases in spatial resolution and computational cost efficiency, while maximizing the use of discriminative features. We present comprehensive experiments on five diverse face verification datasets (LFW, Megaface, IJB-B, CALFW, and CPLFW) to demonstrate the effectiveness of the proposed approach. The results show that AMD-FV outperforms state-of-the-art methods, achieving a verification accuracy of 99.75% on LFW, improving the True Acceptance Rate by 6% on IJB-B at a False Acceptance Rate of 0.001, compared to VGGFace2, and attaining a Rank-1 identification score of 92.16% on Megaface, surpassing the CosFace model by 9.44%.
Computational analysis of missense mutations in squalene epoxidase associated with terbinafine resistance in clinically reported dermatophytes
Deep learning-based classification of speech disorder in stroke and hearing impairment
Background and objective Speech disorders can arise from various causes, including congenital conditions, neurological damage, diseases, and other disorders. Traditionally, medical professionals have used changes in voice to diagnose the underlying causes of these disorders. With the advancement of artificial intelligence (AI), new possibilities have emerged in this field. However, most existing studies primarily focus on comparing voice data between normal individuals and those with speech disorders. Research that classifies the causes of these disorders within the abnormal voice data, attributing them to specific etiologies, remains limited. Therefore, our objective was to classify the specific causes of speech disorders from voice data resulting from various conditions, such as stroke and hearing impairments (HI). Methods We experimentally developed a deep learning model to analyze Korean speech disorder voice data caused by stroke and HI. Our goal was to classify the disorders caused by these specific conditions. To achieve effective classification, we employed the ResNet-18, Inception V3, and SEResNeXt-18 models for feature extraction and training processes. Results The models demonstrated promising results, with area under the curve (AUC) values of 0.839 for ResNet-18, 0.913 for Inception V3, and 0.906 for SEResNeXt-18, respectively. Conclusions These outcomes suggest the feasibility of using AI to efficiently classify the origins of speech disorders through the analysis of voice data.
Null-image effect of planar coils over a grounded ferrite slab
On the coincidence of weather extremes and geopolitical conflicts: Risk analysis in regional food markets
Given the recent increase in geopolitical tensions between major agricultural producers and weather extremes, there is a likelihood that geopolitical conflict will occur simultaneously with weather extremes, leading to devastating production losses between the conflicting parties. These losses can affect the entire food supply chain, leading to food shortages and price increases in regional markets. This paper models the impact of these concurrent events on the global food market, using the Russian-Ukrainian war and the extreme heatwaves of summer 2022 as a case study. The model considers four war scenarios: the start of the invasion, the peak of the war, Ukraine’s resistance, sanctions against Russia, and refugee crises in Europe. Using data from the US Department of Agriculture (USDA), Statista, WITS, and Acclimate production value losses, the results show that the agricultural sectors of southern European countries such as France, Italy, and Spain were the most affected by the extreme events, although the direct impact of refugees was smaller compared to their northern counterparts. Strict sanctions against Russia coupled with Ukraine’s resistance will benefit EU food markets, but at the same time the agricultural sectors of smaller countries and weaker economies, particularly those of Russia’s allies, will be highly vulnerable. This study suggests that when developing and adopting conflict resolution strategies, their impact on weak economies should not be overlooked. An example of this policy recommendation is the continuous renewal of the Black Sea Grain Initiative to stabilize global food prices.
Siglec6 CAR T cells suppressed progression of AML via inhibiting Siglec6 and SHP2 induced Src and ERK signaling activation
Genomic insights into the role of Salmonella Typhi carriers in antimicrobial resistance and typhoid transmission in Urban Kenya
Typhoid fever cases and carriers can transmit Salmonella enterica serovar Typhi (S. Typhi) through fecal shedding. It remains unclear whether the S. Typhi shedding by carriers exhibits similar phenotypic and genotypic characteristics to those from acute cases. We investigated multidrug resistance in S. Typhi from individuals residing in urban informal settlements in Nairobi, Kenya. We recruited participants ≤ 65 years from six health facilities and tested for typhoid infection through blood and stool cultures. The S. Typhi culture-positive cases were treated and followed up after treatment, where index cases and their household contacts provided stool samples for culture. The susceptibility of all S. Typhi isolates was tested against 14 antibiotics using Kirby Bauer disc diffusion. Total deoxyribonucleic acid (DNA) was extracted from selected multi-drug resistant (MDR) S. Typhi for whole genome sequencing using Illumina Nextseq2000, and their genomes were analyzed on Pathogen-watch. Of the 115 S. Typhi isolates, 81/115 (70%) were from cases, while 34/115 (30%) were from carriers. S. Typhi resistance against ampicillin was observed in 32/81 (40%) and 11/34 (32%) of isolates from cases and carriers, respectively, while resistance against co-trimoxazole was observed in 34/81 (42%) and 10/34 (29%) of isolates from cases and carriers, respectively. In addition, resistance against chloramphenicol was observed in 30/81(37%) and 10/34 (29%) in isolates from cases and carriers, respectively. Multidrug resistance was observed in 33% (38/115) of the S. Typhi isolates, with majority, 28/38 (74%) recovered from cases. A subset (22/38, 15 from cases and 7 from carriers) of the MDR isolates was randomly selected for sequencing. All the 22 S. Typhi belonged to genotype 4.3.1, with the majority 15/22 (68%) from genotype 4.3.1.2EA3. All these isolates carried the blaTEM-1D, catA1, dfrA7; sul1, and sul2 AMR genes. GyrA point mutations conferring reduced susceptibility to quinolones and fluoroquinolones were detected in 19/22 (86%) isolates, with the majority 15/22 (79%) occurring on codon 83. This study’s findings highlight the plausibility of typhoid transmission within communities in disease endemic settings. Consequently, the study demonstrates the need for surveillance of antimicrobial resistance, antimicrobial stewardship, deployment of typhoid vaccine and improvement of water, hygiene and sanitation infrastructure in disease endemic settings.
Increased MPO concentration but decreased peroxidase activity in saliva of obese women
The impact of COVID-19 stress on nurses’ organizational deviance: A moderated mediation model
The outbreak and rapid spread of the COVID-19 in December 2019 (Iqbal Z, Aslam MZ, Aslam T, Ashraf R, Kashif M, Nasir H, Register J, 2020, 13, 208–30) has brought great work pressure to nurses on the frontline of the fight against the virus, which is very likely to lead to work deviant behaviors, therefore, how to effectively manage nurses to inhibit their organizational deviance in the context of an emergency public health crisis has a high research value. A questionnaire was administered to 319 Chinese in-service nurses, and SPSS and AMOS software were used to conduct correlation analysis, confirmatory factor analysis, and hierarchical regression analysis to statistically test the hypotheses of the developed model. COVID-19 stress can significantly positively predict nurses’ organizational deviance. The relationship between the two variables is mediated by job satisfaction. Furthermore, perceived organizational support(POS) demonstrates a dual moderating function in our framework: it not only influences the relationship between CST and employee job satisfaction, but also affects the extent to which satisfaction mediates subsequent organizational outcomes. COVID-19 stress is an important psychological factor influencing nurses’ organizational deviance. The government and relevant organizations are supposed to take the psychological stress of such primary medical staff seriously, provide more supportive resources and take various measures to reduce COVID-19 stress to help individuals cope with the COVID-19 crisis.
A retrospective study on the association of ambient air pollutants and temperature co-exposure with female infertility risk in Chengdu, China
Geriatric ocular trauma and mortality: A retrospective cohort study
Purpose The objective of this investigation is to evaluate the 5-year mortality of geriatric patients who have sustained eye injuries. Design This retrospective cohort study included patients aged 65 years or older who had histories of either ocular trauma or age-related nuclear cataracts. Subjects and controls: Patients with ocular trauma constituted the study group, while those with a history of cataracts served as controls. Methods Data from the I2B2 Carolina Data Warehouse were analyzed. Patient demographics were collected, and the outcomes of interest were the overall mortality rate and annual mortality rates over a 5-year period. Chi-squared tests were utilized for the comparison of mortality data. Main outcomes and measures The primary outcomes were overall mortality rates and annual mortality rates expressed as percentages. Results The study group consisted of 602 patients who had suffered ocular trauma. The control group included 1066 patients of similar age who had been diagnosed with age-related nuclear cataracts at some point in their lives. Among the study group, 74 patients died within 5 years, while 69 patients in the control group died within the same timeframe, resulting in a study group mortality rate of 11.30% and a control group mortality rate of 6.47%. For patients with ocular trauma, the annual mortality rates were 4.15%, 2.60%, 1.96%, 2.54%, and 0.56%, respectively. For the control group, the annual mortality rates were 1.03%, 1.70%, 1.64%, 0.88%, and 1.38% respectively. Conclusion The study suggests that geriatric patients who have experienced ocular trauma are at a higher risk of mortality compared to age-matched controls without such injuries. These findings highlight the necessity of identifying the causes of geriatric periorbital trauma and underscore the importance of close patient follow-up to improve outcomes.