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Cell Painting PLUS: expanding the multiplexing capacity of Cell Painting-based phenotypic profiling using iterative staining-elution cycles
Abstract Phenotypic changes in the morphology and internal organization of cells can indicate perturbations in cell functions. Therefore, imaging-based high-throughput phenotypic profiling (HTPP) applications such as Cell Painting (CP) play an important role in basic and translational research, drug discovery, and regulatory toxicology. Here we present the Cell Painting PLUS (CPP) assay, an efficient, robust and broadly applicable approach that further expands the versatility of available HTPP methods and offers additional options for addressing mode-of-action specific research questions. An iterative staining-elution cycle allows multiplexing of at least seven fluorescent dyes that label nine different subcellular compartments and organelles including the plasma membrane, actin cytoskeleton, cytoplasmic RNA, nucleoli, lysosomes, nuclear DNA, endoplasmic reticulum, mitochondria, and Golgi apparatus. In this way, CPP significantly expands the flexibility, customizability, and multiplexing capacity of the original CP method and, importantly, also improves the organelle-specificity and diversity of the phenotypic profiles due to the separate imaging and analysis of single dyes in individual channels.
Synaptic plasticity-based regularizer for artificial neural networks
Abstract Regularization is an important tool for the generalization of ANN models. Due to the lack of constraints, it cannot guarantee that the model will work in a real environment with input data distribution changes. Inspired by neuroplasticity, this paper introduces a bounded regularization method that can be safely applied during the deployment phase. First, the reliability of neuron outputs is improved by extending our recent neuronal masking method to generate new supporting neurons. The model is then regularized by incorporating a synaptic connection module containing conenctions of the generated neurons to their previous layer. These connections are optimized online by introducing a synaptic rewiring process triggered by the information about the input distribution. This process is formulated as bilevel mixed-integer nonlinear programming (MINLP) with an objective to minimize the outer risk of the output by identifying the connections that minimize the inner risk of the neuron output. To address this optimization problem, a single-wave scheme is introduced to decompose the problem into smaller, parallel sub-problems that minimize the inner cost function while ensuring the aggregated solution to minimize the outer one. In addition, a storage/recovery memory module is proposed to memorize these connections and their corresponding risks, enabling the model to retrieve previous knowledge when encountering similar situations. Experimental results from classification and regression tasks show around 8% improvement in accuracy over state-of-the-art techniques. As a result, the proposed regularization method enhances the adaptability and robustness of ANN models in a variable environment.
Linking vector favourable environmental conditions with serological evidence of widespread bluetongue virus exposure in livestock in Ecuador
Abstract Despite existing knowledge of bluetongue disease (BT) in Latin America, little information is available on its actual spread and overall burden. As a vector-borne disease, high-risk areas for BT coincide with environmental conditions favourable for the prevailing vector. In Ecuador, information on the presence of BT is limited to singled out virological findings. In this study, we obtained serological evidence for BT virus exposure from the passive surveillance system of the National Veterinary Service, which monitors reproductive-vesicular diseases, including FMD and BT, as part of differential diagnosis. Bioclimatic factors relevant to Culicoides development as the main vector and host abundance at the parish level were considered as risk factors and analysed using a logistic regression model. The results reveal widespread evidence of bluetongue virus exposure, geographically aligning with favourable vector ecosystems within a temperature range of 12–32 °C. Key variables for predicting high-risk BT areas include cattle population, maximum temperature of the warmest month, minimum temperature of the coldest month, temperature seasonality, and precipitation of the driest month. This analysis, the first of its kind for an Andean country with diverse ecosystems, provides a foundation for initial strategic approaches for targeted surveillance and control measures, considering a One Health approach.
Detection of a sympatric cryptic species mimicking Aedes albopictus (Diptera: Culicidae) in dengue and Chikungunya endemic forest villages of Tripura, India, posing a daunting challenge for vector research
Abstract The Aedes ( Stegomyia ) albopictus (Skuse, 1895) (Diptera: Culicidae) is one of the major vectors for Dengue and Chikungunya. However, our study uncovered another mosquito species morphologically similar to Ae. albopictus but is genetically different. The male genitalia of this species possess minute differences in the IX tergum with Ae. albopictus . Nucleotide diversity and mean genetic distance analysis confirmed the genetic difference from Ae. albopictus and other Aedes species. However, this species has a significant degree of genetic similarity with the cryptic species of Ae. albopictus earlier reported from Vietnam and China. The time tree revealed the median divergence time of this species and Ae. albopictus species to be approximately 36.13 million years ago. This study marks the discovery of an Aedes nr. Albopictus species resembling Ae. albopictus in India and third in the world, also reports the distinct morphological feature of the male genitalia for the first time. Our study indicates the sympatric behavior of this species as it shares the breeding habitat of Ae. albopictus . The absence of endosymbiont Wolbachia in this species raises the possibility of reproductive isolation with Ae. albopictus leading to sympatric speciation and increasing virus-carrying capability for this species, having significant implications for vector-borne disease control.
Knowledge and practices of healthcare professionals regarding antibiotic use in a district hospital, Southern Mozambique: a cross-sectional study
Quantitative determination of the mineral content of settleable particulate matter samples
Decentralized active fault tolerant control of direct current microgrids under actuator and source disturbances using proportional integral unknown input observer
Doxorubicin loaded polylactide nanoparticles functionalized histamine promote apoptosis of human gastric cancer cells AGS
A novel water quality risk assessment framework for reservoir water bodies coupling key parameter selection and dynamic warning threshold determination
Scientific naming conventions should keep in step with contemporary science
Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN)
Abstract The ambulance dispatch system plays a crucial role in emergency medical care by ensuring efficient communication, reducing response times, and ultimately saving lives. Delays in ambulance arrival can have serious consequences for patient health and survival. To enhance emergency preparedness, decision trees are used to analyze historical data and predict ambulance demand in specific locations over time. This helps in planning the necessary number of ambulances in advance. In situations where ambulance resources are limited, a support vector machine (SVM) evaluates patient data to optimize the distribution of available ambulances, ensuring that the most critical patients receive timely medical attention. For real-time route optimization, a convolutional neural network (CNN)-based deep learning model is used to adjust ambulance routes based on current traffic and road conditions, achieving an accuracy of 99.15%. By improving dispatch efficiency and communication, the proposed machine learning-based ambulance system reduces the burden on emergency services, enhancing overall effectiveness, particularly during peak demand periods.
Calcium modulates growth and biofilm formation of Lactobacillus acidophilus ATCC 4356 and Lactiplantibacillus plantarum ATCC 14917
Coping with five mismatches between policy and practice in hemiboreal forest stands and landscapes
Abstract Maintenance of forest ecosystems revolves around the long-term persistence and resilience of their components, structures and functions. Focusing on Europe’s hemiboreal forests, we evaluate mismatches between naturally dynamic forest ecosystems and current forest management systems forming obstacles for developing closer-to-nature forest management. Using Lithuania as a case study, we (i) quantify the main forest vegetation community types using soil types, ground layer flora, and tree and shrub species, (ii) review the relationships among these vegetation communities and their predicted natural disturbance regimes, (iii) analyse changes in tree species composition, (iv) compare the life expectancy of trees with harvest age, and (v) compare the contemporary stand age distributions with predicted natural disturbance regimes stand age distributions. Results show five mismatches between current practices and policy visions. Despite identifying 17 natural hemiboreal forest vegetation communities only eight dominant stand tree species were reported in current forestry reporting. The areal extents of three different natural disturbance regimes were: gap dynamics - mixed broadleaved forests on wet-mesic very fertile sites (22%), succession - mixed spruce forests on fertile sites (49%), and cohort dynamics - Scots pine forest on poor fertility sites (30%). Changes in tree species composition showed declines of primary tree species of 12–71% for the three disturbance regimes. The ratio of natural expected life expectancy to harvest age varied from two-fold to eight-fold across different tree species. Stand age distributions in naturally dynamic forests and managed forests revealed a current dramatic deficit of old-growth stands. Coping with the five identified mismatches between natural forests and current forest management requires multiple solutions: (1) closer-to-nature forest management that emulate natural disturbance regimes at tree and stand scales, (2) landscape planning, and (3) multi-level governance approaches.
Kidney disease is a worldwide killer. Treat it that way
Differential expression and functional analysis of circular RNAs and m6A modifications in children with Philadelphia chromosome-positive acute lymphoblastic leukemia
Abstract Philadelphia chromosome-positive (Ph+) acute lymphoblastic leukaemia (ALL) in childhood is associated with dismal outcomes, in large part due to challenges in diagnosis and monitoring therapeutic efficacy. Recent studies suggest that circular RNAs (circRNAs) are potential diagnostic and prognostic biomarkers for various tumours. to indicate the potential role of circRNAs in identifying or serving as novel targets for treatments. Here, we analysed CircRNA expression profiles in samples from three Ph+ ALL patients at diagnosis (CK1 group), on day 19 after treatment (T1 group) and in first complete remission (day 46 after treatment, T2 group), as well as one Ph− ALL patient at diagnosis (CK2 group). A total of 922 differentially expressed circRNAs (DECs) potentially associated with RNA degradation, microRNAs in cancer, propanoate metabolism and ubiquitin-mediated proteolysis were found (626 upregulated and 296 downregulated) between the CK1 and CK2 groups. In addition, we identified 224 DECs (129 upregulated and 95 downregulated) between the CK1 and T1 groups and 225 DECs (136 upregulated and 89 downregulated) between the CK1 and T2 groups, including 136 for which their expression was upregulated and 89 for which their expression was downregulated. The levels of hsa_circ_0012152 and hsa_circ_0009024 were significantly increased in Ph+ ALL patients, the changes in the levels of these circRNAs were confirmed by qRT‒PCR, indicating their potential as diagnostic biomarkers. Most upregulated DECs underwent N6-methyladenosine (m6A) modification noting the specific roles that are now better understood based on the circRNAs and DECs identified, and ideally suggesting how the findings could impact the diagnosis and treatment of Ph+ ALL The findings of this study increase our understanding of the roles of m6A-modified circRNAs in the pathogenesis of Ph+ ALL.
Pathogenesis of bovine H5N1 clade 2.3.4.4b infection in macaques
An agent-based model of COVID- 19 in the food industry for assessing public health and economic impacts of infection control strategies
Abstract The COVID- 19 pandemic exposed challenges of balancing public health and economic goals of infection control in essential industries like food production. To enhance decision-making during future outbreaks, we developed a customizable agent-based model (FInd CoV Control) that predicts and counterfactually compares COVID- 19 transmission in a food production operation under various interventions. The model tracks the number of infections as well as economic outcomes (e.g., number of unavailable workers, direct expenses, production losses). The results revealed strong tradeoffs between public health and economic impacts of interventions. Temperature screening and virus testing protect public health but have substantial economic downsides. Vaccination, while inexpensive, is too slow as a reactive strategy. Intensive physical distancing and biosafety interventions prove cost-effective. The variability and bimodality in predicted impacts of counterfactual interventions, explained by the chance effects and early stochastic infection die-off, caution against relying on single-operation real-world data for decision-making. These findings underscore the need for a proactive infrastructure capable of rapidly developing integrated infection-economic mechanistic models for the essential industries to guide infection control, policy-making, and socially acceptable decisions.
Astaxanthin alleviates fipronil-induced neuronal damages in male rats through modulating oxidative stress, apoptosis, and inflammatory markers
Abstract Fipronil (FPN) is an effective pesticide for veterinary and agricultural use; however, it can induce neurotoxic effects on non-target organisms after accidental exposure. Astaxanthin (AST) is a dark red carotenoid with antioxidant, anti-inflammatory, neuroprotective, and antiapoptotic effects. This study investigated the ameliorative impact of AST against FPN-induced brain damage in rats. Thirty-two adult Wistar rats were allocated into four groups (n = 8): Control, AST (20 mg/kg bwt/day), fipronil (FPN) (20 mg/kg bwt/day), and AST + FPN group. Acetylcholine (ACh), dopamine, malondialdehyde (MDA), and proinflammatory cytokines, including tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6), and inflammatory cytokine cyclooxygenase-2 (COX2) levels were enhanced in the FPN-administered group relative to the control group. In addition, a substantial reduction of acetylcholine esterase (AchE), gamma-aminobutyric acid (GABA), serotonin, reduced glutathione (GSH) levels, catalase (CAT), and total superoxide dismutase (T-SOD) enzyme activities were determined. FPN induced histopathological alterations in the cerebral and cerebellar tissues. Likewise, the histomorphometric image analysis of H and E-stained tissue sections was constant with FPN-induced neurotoxicity. Immunohistochemically, an intense positive immunohistochemical staining of apoptotic marker caspase-3 and astrocytes activation marker glial fibrillary acidic protein (GFAP) in the examined tissues was noticed. Inversely, the simultaneous administration of AST partially attenuated FPN impacts, ameliorating the severity of FPN-induced neuronal damage. These results were also established with the molecular docking findings. It could be suggested that AST has antioxidant, anti-inflammatory, and anti-apoptotic capabilities against FPN-induced neuronal damage via suppression of oxidative stress and pro-inflammatory cytokines, preservation of the neurotransmitters, and the cerebral and cerebellar histoarchitectures.