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PLoS Computational Biology Jun 2024Therapeutic interventions are designed to perturb the function of a biological system. However, there are many types of proteins that cannot be targeted with...
Therapeutic interventions are designed to perturb the function of a biological system. However, there are many types of proteins that cannot be targeted with conventional small molecule drugs. Accordingly, many identified gene-regulatory drivers and downstream effectors are currently undruggable. Drivers and effectors are often connected by druggable signaling and regulatory intermediates. Methods to identify druggable intermediates therefore have general value in expanding the set of targets available for hypothesis-driven validation. Here we identify and prioritize potential druggable intermediates by developing a network perturbation theory, termed NetPert, for response functions of biological networks. Dynamics are defined by a network structure in which vertices represent genes and proteins, and edges represent gene-regulatory interactions and protein-protein interactions. Perturbation theory for network dynamics prioritizes targets that interfere with signaling from driver to response genes. Applications to organoid models for metastatic breast cancer demonstrate the ability of this mathematical framework to identify and prioritize druggable intermediates. While the short-time limit of the perturbation theory resembles betweenness centrality, NetPert is superior in generating target rankings that correlate with previous wet-lab assays and are more robust to incomplete or noisy network data. NetPert also performs better than a related graph diffusion approach. Wet-lab assays demonstrate that drugs for targets identified by NetPert, including targets that are not themselves differentially expressed, are active in suppressing additional metastatic phenotypes.
PubMed: 38935814
DOI: 10.1371/journal.pcbi.1012195 -
PloS One 2024When the costs of the inputs and outputs of the units under evaluation are known, the evaluation of the profit efficiency of the units is one of the most significant...
When the costs of the inputs and outputs of the units under evaluation are known, the evaluation of the profit efficiency of the units is one of the most significant evaluations that can provide valuable information about them. In this research, first, a new definition of the optimal scale size based on the maximization of the average measure of profit efficiency is presented. The average measure of profit efficiency develops the concept of economic efficiency measure by introducing a more accurate measure of efficiency compared to the measure of comparative and profit efficiency. It has been shown that the average measure of profit efficiency in a convex space is equivalent to the measure of profit efficiency in constant returns to scale technology, and then, some models are presented to calculate profit efficiency in a stochastic environment, to increase the ability of profit models in real examples by considering the calculation errors of inputs and outputs. Finally, the proposed method is used in an empirical example to calculate the average profit efficiency of a set of postal areas in Iran.
Topics: Uncertainty; Models, Economic; Iran; Stochastic Processes
PubMed: 38935791
DOI: 10.1371/journal.pone.0295241 -
PLoS Computational Biology Jun 2024As the spatial arrangement of trees planted along streets in cities makes their bases potential ecological corridors for the flora, urban tree bases may be a key...
As the spatial arrangement of trees planted along streets in cities makes their bases potential ecological corridors for the flora, urban tree bases may be a key contributor to the overall connectivity of the urban ecosystem. However, these tree bases are also a highly fragmented environment in which extinctions are frequent. The goal of this study was to assess the plant species' ability to survive and spread through urban tree bases. To do so, we developed a Bayesian framework to assess the extinction risk of a plant metapopulation using presence/absence data, assuming that the occupancy dynamics was described by a Hidden Markov Model. The novelty of our approach is to take into account the combined effect of low-distance dispersal and the potential presence of a seed bank on the extinction risk. We introduced a metric of the extinction risk and examined its performance over a wide range of metapopulation parameters. We applied our framework to yearly floristic inventories carried out in 1324 tree bases in Paris, France. While local extinction risks were generally high, extinction risks at the street scale varied greatly from one species to another. We identified 10 plant species that could survive and spread through urban tree bases, and three plant traits correlated with the extinction risk at the metapopulation scale: the maximal height, and the beginning and end of the flowering period. Our results suggest that some plant species can use urban tree bases as ecological corridors despite high local extinction risks by forming a seed bank. We also identified other plant traits correlated with the ability to survive in tree bases, related to the action of gardeners. Moreover, our findings demonstrate that our Bayesian estimation framework based on percolation theory has the potential to be extended to more general metapopulations.
PubMed: 38935782
DOI: 10.1371/journal.pcbi.1012191 -
PloS One 2024Hepatitis B virus (HBV) infection is a global public health issue. We offer a comprehensive analysis of the dynamics of HBV, which can be successfully controlled with...
Hepatitis B virus (HBV) infection is a global public health issue. We offer a comprehensive analysis of the dynamics of HBV, which can be successfully controlled with vaccine and treatment. Hepatitis B virus (HBV) causes a significantly more severe and protracted disease compared to hepatitis A. While it initially presents as an acute disease, in approximately 5 to 10% of cases, it can develop into a chronic disease that causes permanent damage to the liver. The hepatitis B virus can remain active outside the body for at least seven days. If the virus penetrates an individual's body without immunization, it may still result in infection. Upon exposure to HBV, the symptoms often last for a duration ranging from 10 days to 6 months. In this study, we developed a new model for Hepatitis B Virus (HBV) that includes asymptomatic carriers, vaccination, and treatment classes to gain a comprehensive knowledge of HBV dynamics. The basic reproduction number [Formula: see text] is calculated to identify future recurrence. The local and global stabilities of the proposed model are evaluated for values of [Formula: see text] that are both below and above 1. The Lyapunov function is employed to ensure the global stability of the HBV model. Further, the existence and uniqueness of the proposed model are demonstrated. To look at the solution of the proposed model graphically, we used a useful numerical strategy, such as the non-standard finite difference method, to obtain more thorough numerical findings for the parameters that have a significant impact on disease elimination. In addition, the study of treatment class in the population, we may assess the effectiveness of alternative medicines to treat infected populations can be determined. Numerical simulations and graphical representations are employed to illustrate the implications of our theoretical conclusions.
Topics: Humans; Hepatitis B; Hepatitis B virus; Computer Simulation; Epidemics; Hepatitis B Vaccines; Basic Reproduction Number; Vaccination
PubMed: 38935766
DOI: 10.1371/journal.pone.0304375 -
JMIR Mental Health Jun 2024Text-based digital media platforms have revolutionized communication and information sharing, providing valuable access to knowledge and understanding in the fields of... (Review)
Review
BACKGROUND
Text-based digital media platforms have revolutionized communication and information sharing, providing valuable access to knowledge and understanding in the fields of mental health and suicide prevention.
OBJECTIVE
This systematic review aimed to determine how machine learning and data analysis can be applied to text-based digital media data to understand mental health and aid suicide prevention.
METHODS
A systematic review of research papers from the following major electronic databases was conducted: Web of Science, MEDLINE, Embase (via MEDLINE), and PsycINFO (via MEDLINE). The database search was supplemented by a hand search using Google Scholar.
RESULTS
Overall, 19 studies were included, with five major themes as to how data analysis and machine learning techniques could be applied: (1) as predictors of personal mental health, (2) to understand how personal mental health and suicidal behavior are communicated, (3) to detect mental disorders and suicidal risk, (4) to identify help seeking for mental health difficulties, and (5) to determine the efficacy of interventions to support mental well-being.
CONCLUSIONS
Our findings show that data analysis and machine learning can be used to gain valuable insights, such as the following: web-based conversations relating to depression vary among different ethnic groups, teenagers engage in a web-based conversation about suicide more often than adults, and people seeking support in web-based mental health communities feel better after receiving online support. Digital tools and mental health apps are being used successfully to manage mental health, particularly through the COVID-19 epidemic, during which analysis has revealed that there was increased anxiety and depression, and web-based communities played a part in reducing isolation during the pandemic. Predictive analytics were also shown to have potential, and virtual reality shows promising results in the delivery of preventive or curative care. Future research efforts could center on optimizing algorithms to enhance the potential of text-based digital media analysis in mental health and suicide prevention. In addressing depression, a crucial step involves identifying the factors that contribute to happiness and using machine learning to forecast these sources of happiness. This could extend to understanding how various activities result in improved happiness across different socioeconomic groups. Using insights gathered from such data analysis and machine learning, there is an opportunity to craft digital interventions, such as chatbots, designed to provide support and address mental health challenges and suicide prevention.
Topics: Humans; Machine Learning; Suicide Prevention; Mental Health; Social Media; Data Analysis
PubMed: 38935419
DOI: 10.2196/55747 -
Journal of the American Heart... Jun 2024Experimental preeclampsia (ePE) has been shown to have worsened outcome from stroke. We investigated the effect of low-dose aspirin, known to prevent preeclampsia, on...
BACKGROUND
Experimental preeclampsia (ePE) has been shown to have worsened outcome from stroke. We investigated the effect of low-dose aspirin, known to prevent preeclampsia, on stroke hemodynamics and outcome, and the association between the vasoconstrictor and vasodilator cyclooxygenase products thromboxane A and prostacyclin.
METHODS AND RESULTS
Middle cerebral artery occlusion was performed for 3 hours with 1 hour of reperfusion in normal pregnant rats on day 20 of gestation and compared with ePE treated with vehicle or low-dose aspirin (1.5 mg/kg per day). Multisite laser Doppler was used to measure changes in cerebral blood flow to the core middle cerebral artery and collateral vascular territories. After 30 minutes occlusion, phenylephrine was infused to increase blood pressure and assess cerebral blood flow autoregulation. Infarct and edema were measured using 2,3,5-triphenyltetrazolium chloride staining. Plasma levels of thromboxane A, prostacyclin, and inflammatory markers in plasma and cyclooxygenase levels in cerebral arteries were measured. ePE had increased infarction compared with normal pregnant rats (<0.05) that was reduced by aspirin (<0.001). ePE also had intact cerebral blood flow autoregulation and reduced collateral perfusion during induced hypertension that was also prevented by aspirin. Aspirin increased prostacyclin in ePE (<0.05) without reducing thromboxane B, metabolite of thromboxane A, or 8-isoprostane-prostaglandin-2α, a marker of lipid peroxidation. There were no differences in cyclooxygenase levels in cerebral arteries between groups.
CONCLUSIONS
Low-dose aspirin in ePE reduced infarction that was associated with increased vasodilator prostacyclin and improved collateral perfusion during induced hypertension. The beneficial effect of aspirin on the brain and cerebral circulation is likely multifactorial and worth further study.
PubMed: 38934871
DOI: 10.1161/JAHA.124.035990 -
Indian Journal of Public Health Oct 2023Cancer incidence rates are rising at an alarming rate in India and are expected to rise by 12% in the next 5 years. Hence, a thorough knowledge of the existing scope of...
BACKGROUND
Cancer incidence rates are rising at an alarming rate in India and are expected to rise by 12% in the next 5 years. Hence, a thorough knowledge of the existing scope of the cancer problem is required to provide an approach for analyzing and regulating the impact of cancer across the country.
OBJECTIVES
This study aimed to determine whether the cancer incidence rates of all the states and union territories across the six geographical regions of India are statistically different from each other or not and also to identify the highly cancer-affected states.
MATERIALS AND METHODS
The data have been obtained from the website www.indiastat.com from 2009 to 2020. The one-way analysis of variance, followed by Tukey's test and t-test, is used for the statistical evaluation.
RESULTS
The multiple comparison tests revealed that the difference between the cancer incidence rates is significant in all the states and union territories in every region of India. The highly affected states in the six geographical regions of India are Uttar Pradesh (UP), Tamil Nadu, Bihar, Maharashtra, Assam, and Madhya Pradesh. The most highly affected state among them is UP. These states contributed to nearly half of India's cancer burden in 2020.
CONCLUSION
This study offers significant information on the current status of cancer incidence rates in India for 12 years. As India is observing an increase in cancer incidence, therefore, additional efforts are required to strengthen cancer prevention and control strategies, particularly in India's most cancer-affected states.
Topics: India; Humans; Incidence; Neoplasms
PubMed: 38934824
DOI: 10.4103/ijph.ijph_1587_22 -
Heliyon Jun 2024The remediation of dye pollutants remains a concern in contemporary water management practices. Hence, the need for efficient and cost-effective techniques for dye...
The remediation of dye pollutants remains a concern in contemporary water management practices. Hence, the need for efficient and cost-effective techniques for dye removal from wastewater. In this study, the epicarp of fruits was treated with orthophosphoric acid for enhanced porosity and efficiency in the uptake of Indigo carmine dye (ICD). Treated fruit waste (RHPW) presented morphologically distributed pores as well as high porosity with Branneur-Emmet-Teller (BET) surface area of 945.43 m/g. RHPW displayed functional groups suitable for adsorption. The maximum ICD uptake was observed at pH 5 while the maximum uptake (q) was 20.41 mg/g in the concentration range of 2-10 mg/L. Freundlich isotherm and Pseudo-second order kinetics well-described equilibrium and kinetics data respectively. This indicated a multilayered adsorption. The Dubinin-Radushkecich model energy value was 40.82 kJ/mol, indicating chemical adsorption. The ridge regression, the Lasso and the Elastic net statistical models were used to establish a positive relationship between the various adsorption operational parameters studied. Lasso provided the best result based on the estimated mean squared error. The RHPW-ICD adsorption system was more favorable at room temperature, as the removal efficiency decreased with temperature rise. The findings established fruit epicarp as an economical and sustainable precursor for the preparation of potent adsorbent for Indigo carmine dye removal. This can find possible application in wastewater treatment.
PubMed: 38933985
DOI: 10.1016/j.heliyon.2024.e32121 -
Heliyon Jun 2024In this research, the behavior of an electric field caused by the mechanism of electrostatic painting has been investigated using the finite element method and FLEXPDE...
In this research, the behavior of an electric field caused by the mechanism of electrostatic painting has been investigated using the finite element method and FLEXPDE software. The aim of this study is to optimize the electrostatic spraying performance of the paint sprayer by investigating the potential field in the paint nozzle. The results show that the potential and the electric field can be solved at any given point and displayed graphically. Additionally, changing the 2D rectangular covering surface to a circular one increased the potential value reached on the covering surface by 10 percent. The amount of electric potential and electrostatic field in the direction perpendicular to the x-axis is shown to be symmetrical and equal for y > 0 and y < 0. The size of the spray opening/hole is a significant factor in reaching paint particles to the coating surface. Doubling the size of the spray opening increased the potential value on the coating surface by 54.3 percent, while halving it decreased the potential value by 75 percent.
PubMed: 38933942
DOI: 10.1016/j.heliyon.2024.e32191 -
PNAS Nexus Jun 2024The unfolded protein response (UPR) is a widespread signal transduction pathway triggered by endoplasmic reticulum (ER) stress. Because calcium (Ca) is a key factor in...
The unfolded protein response (UPR) is a widespread signal transduction pathway triggered by endoplasmic reticulum (ER) stress. Because calcium (Ca) is a key factor in the maintenance of ER homeostasis, massive Ca depletion of the ER is a potent inducer of ER stress. Although moderate changes in ER Ca drive the ubiquitous Ca signaling pathways, a possible incremental relationship between UPR activation and Ca changes has yet to be described. Here, we determine the sensitivity and time-dependency of activation of the three ER stress sensors, inositol-requiring protein 1 alpha (IRE1α), protein kinase R-like ER kinase (PERK), and activating transcription factor 6 alpha (ATF6α) in response to controlled changes in the concentration of ER Ca in human cultured cells. Combining Ca imaging, fluorescence recovery after photobleaching experiments, biochemical analyses, and mathematical modeling, we uncover a nonlinear rate of activation of the IRE1α branch of UPR, as compared to the PERK and ATF6α branches that become activated gradually with time and are sensitive to more important ER Ca depletions. However, the three arms are all activated within a 1 h timescale. The model predicted the deactivation of PERK and IRE1α upon refilling the ER with Ca. Accordingly, we showed that ER Ca replenishment leads to the complete reversion of IRE1α and PERK phosphorylation in less than 15 min, thus revealing the highly plastic character of the activation of the upstream UPR sensors. In conclusion, our results reveal a dynamic and dose-sensitive Ca-dependent activation/deactivation cycle of UPR induction, which could tightly control cell fate upon acute and/or chronic stress.
PubMed: 38933930
DOI: 10.1093/pnasnexus/pgae229