Level Of Complexity Research Articles

A new technique for handling non-probability samples based on model-assisted kernel weighting

Surveys are going through massive changes, and the most important innovation is the use of non-probability samples. Non-probability samples are increasingly used for their low research costs and the speed of the attainment of results, but these surveys are expected to have strong selection bias caused by several mechanisms that can eventually lead to unreliable estimates of the population parameters of interest. Thus, the classical methods of statistical inference do not apply because the probabilities of inclusion in the sample for individual members of the population are not known. Therefore, in the last few decades, new possibilities of inference from non-probability sources have appeared.Statistical theory offers different methods for addressing selection bias based on the availability of auxiliary information about other variables related to the main variable, which must have been measured in the non-probability sample. Two important approaches are inverse probability weighting and mass imputation. Other methods can be regarded as combinations of these two approaches.This study proposes a new estimation technique for non-probability samples. We call this technique model-assisted kernel weighting, which is combined with some machine learning techniques. The proposed technique is evaluated in a simulation study using data from a population and drawing samples using designs with varying levels of complexity for, a study on the relative bias and mean squared error in this estimator under certain conditions. After analyzing the results, we see that the proposed estimator has the smallest value of both the relative bias and the mean squared error when considering different sample sizes, and in general, the kernel weighting methods reduced more bias compared to based on inverse weighting. We also studied the behavior of the estimators using different techniques such us generalized linear regression versus machine learning algorithms, but we have not been able to find a method that is the best in all cases. Finally, we study the influence of the density function used, triangular or standard normal functions, and conclude that they work similarly.A case study involving a non-probability sample that took place during the COVID-19 lockdown was conducted to verify the real performance of the proposed methodology, obtain a better estimate, and control the value of the variance.

Electrolytes at Uncharged Liquid Interfaces: Adsorption, Potentials, Surface Tension, and the Role of the Surfactant Monolayer.

The article summarizes the results of our research on the behavior of ions at uncharged fluid interfaces, with a focus on moderately to highly concentrated aqueous electrolytes. The ion-specific properties of such interfaces have been analyzed. The ion-specificity series are different for water|air and water|oil; different for surface tension σ, surface Δχ potential and electrolyte adsorption, and they change with concentration. A methodology has been developed that allows to disentangle the multiple factors controlling the ion order. The direct ion-surface interactions are not always the most significant factor behind the observed ion sequences: indirect effects stemming from conjugate bulk properties are often more important. For example, the order of the surface tension with the nature of the anion (σKOH > σKCl > σKNO3 for potassium salts) is often the result of bulk nonideality and follows the order of the bulk activity coefficients (γKOH > γKCl > γKNO3) rather than that of a specific ion-surface interaction potential. The surface Δχ potential of aqueous solutions is, in many cases, insensitive to the ion distribution in the electric double layer but reflects the orientation of water at the surface, through the ion-specific dielectric permittivity ε of the solution. Even the sign of Δχ is often the result of the decrement of ε in the presence of electrolyte. A whole new level of complexity appears when the ions interact with an uncharged surfactant monolayer. A method has been developed to measure the electrolyte adsorption isotherms on monolayers of varying area per surfactant molecule via a combination of experiments-compression isotherms and surface pressure of equilibrium spread monolayers. The obtained isotherms demonstrate that the ions exhibit a maximum in their adsorption on monolayers of intermediate density. The maximum is explained with the interplay between ion-surfactant complexation, volume exclusion and osmotic effects.

Regimen on Dnaja3 haploinsufficiency mediated sarcopenic obesity with imbalanced mitochondrial homeostasis and lipid metabolism.

Sarcopenic obesity is characterized by excess fat mass and diminished muscular mass/function. DNAJA3, a mitochondrial co-chaperone protein, plays a crucial role in skeletal muscle development. GMI, an immunomodulatory protein, promotes myogenic differentiation through DNAJA3 activation. This study aims to elucidate the physiological effects of muscular Dnaja3 haploinsufficiency on mitochondrial dysfunction and dysregulated lipid metabolism and to assess the efficacy of GMI in rescuing sarcopenic obesity both in vitro and in vivo. We generated mouse strain with Dnaja3 heterozygosity (HSA-Dnaja3f/+) specifically in skeletal muscle. The body weight, body composition, and locomotor activity of WT and HSA-Dnaja3f/+ mice were examined. The isolated skeletal muscles and primary myoblasts from the WT and HSA-Dnaja3f/+ mice, at young or old age, were utilized to study the molecular mechanisms, mitochondrial respiration and ROS level, mitochondrial proteomes, and serological analyses, respectively. To evaluate the therapeutic efficacy of GMI, both short-term and long-term GMI treatment were administrated intraperitoneally to the HSA-Dnaja3f/+ young (4weeks old) or adult (3months old) mice for a duration of either 1 or 6months, respectively. Muscular Dnaja3 heterozygosity resulted in impaired locomotor activity (P<0.05), reduced muscular cross-sectional area (P<0.0001), and up-regulation of lipogenesis (ACC2) and pro-inflammation (STAT3) in skeletal muscles (P<0.05). Primary myoblasts from the HSA-Dnaja3f/+ mice displayed impaired mitochondrial respiration (P<0.01) and imbalanced mitochondrial ROS levels. A systemic proteomic analysis of the purified mitochondria from the primary myoblasts was conducted to show the abnormalities in mitochondrial function and fatty acid metabolism (P<0.0001). At age of 13 to 14months, the HSA-Dnaja3f/+ mice displayed increased body fat mass (P<0.001), reduced fat-free mass (P<0.01), and impaired glucose and insulin tolerance (P<0.01). The short-term GMI treatment improved locomotor activity (P<0.01) and down-regulated the protein levels of STAT3 (P<0.05), ACC2, and mitochondrial respiratory complex III (UQCRC2) (P<0.01) via DNAJA3 activation. The long-term GMI treatment ameliorated fat mass accumulation, glucose intolerance, and systemic inflammation (AST) (P<0.05) in skeletal muscle, while enhancing thermogenesis (UCP1) (P<0.01) in eWAT. GMI treatment promoted myogenesis, enhanced oxygen consumption, and ameliorated STAT3 (P<0.01) through DNAJA3 activation (P<0.05) in vitro. Muscular Dnaja3 haploinsufficiency dysregulates mitochondrial function and lipid metabolism then leads to sarcopenic obesity. GMI emerges as a therapeutic regimen for sarcopenic obesity treatment through DNAJA3 activation.

3D chromatin-based variant-to-gene maps across 57 human cell types reveal the cellular and genetic architecture of autoimmune disease susceptibility.

A portion of the genetic basis for many common autoimmune disorders has been uncovered by genome-wide association studies (GWAS), but GWAS do not reveal causal variants, effector genes, or the cell types impacted by disease-associated variation. We have generated 3D genomic datasets consisting of promoter-focused Capture-C, Hi-C, ATAC-seq, and RNA-seq and integrated these data with GWAS of 16 autoimmune traits to physically map disease-associated variants to the effector genes they likely regulate in 57 human cell types. These 3D maps of gene cis-regulatory architecture are highly powered to identify the cell types most likely impacted by disease-associated genetic variation compared to 1D genomic features, and tend to implicate different effector genes than eQTL approaches in the same cell types. Most of the variants implicated by these cis-regulatory architectures are highly trait-specific, but nearly half of the target genes connected to these variants are shared across multiple autoimmune disorders in multiple cell types, suggesting a high level of genetic diversity and complexity among autoimmune diseases that nonetheless converge at the level of target gene and cell type. Substantial effector gene sharing led to the common enrichment of similar biological networks across disease and cell types. However, trait-specific pathways representing potential areas for disease-specific intervention were identified. To test this, we pharmacologically validated squalene synthase, a cholesterol biosynthetic enzyme encoded by the FDFT1 gene implicated by our approach in MS and SLE, as a novel immunomodulatory drug target controlling inflammatory cytokine production by human T cells. These data represent a comprehensive resource for basic discovery of gene cis-regulatory mechanisms, and the analyses reported reveal mechanisms by which autoimmune-associated variants act to regulate gene expression, function, and pathology across multiple, distinct tissues and cell types.

Parenting During the Student Period: the Possibilities of Combining Life Strategies

The demographic challenges that Russia is facing today require more and more new measures aimed at increasing the birth rate. In the context of an increase in the age of first childbearing, modern youth have stable ideas that the age of 18-24 is not “suitable” for childbearing. The authors’ review of existing and proposed measures to support student families suggests the active development of this area. The key areas of implemented and planned support are highlighted: assistance to student families in solving housing issues; financial support for student parents; organizational measures aimed at combining parental and educational responsibilities. Our analysis focused on the problem of creating the necessary conditions for the implementation of the parental life strategy by young people during their student years. The aim of the study was to develop potential tools to minimize the difficulties of parenthood that arise during parental leave for student families. To achieve this goal, two tasks were set: to identify the totality of difficulties and contradictions experienced by parents during parental leave, and to develop proposals based on the results obtained aimed at increasing the birth rate of students during their higher education. The research method was semi-formalized interviews with 40 parents whose families use the right to parental leave. According to the results of the analysis, two levels of complexity have been identified: institutional (difficulties related to government regulation, infrastructure, labor market) and personal (social attitudes, relationships with the environment, health status). For student parents, the situation during parental leave is even more difficult, and support is more in demand. Based on this, recommendations have been developed that are aimed at mitigating the difficulties of student families on parental leave and can be implemented in the Russian higher education system.

Upstream alternative polyadenylation in SCN5A produces a short transcript isoform encoding a mitochondria-localized NaV1.5 N-terminal fragment that influences cardiomyocyte respiration.

SCN5A encodes the cardiac voltage-gated Na+ channel, NaV1.5, that initiates action potentials. SCN5A gene variants cause arrhythmias and increased heart failure risk. Mechanisms controlling NaV1.5 expression and activity are not fully understood. We recently found a well-conserved alternative polyadenylation (APA) signal downstream of the first SCN5A coding exon. This yields a SCN5A-short transcript isoform expressed in several species (e.g. human, pig, and cat), though rodents lack this upstream APA. Reanalysis of transcriptome-wide cardiac APA-seq and mRNA-seq data shows reductions in both upstream APA usage and short/full-length SCN5A mRNA ratios in failing hearts. Knock-in of the human SCN5A APA sequence into mice is sufficient to enable expression of SCN5A -short transcript, while significantly decreasing expression of full-length SCN5A mRNA. Notably, SCN5A -short transcript encodes a novel protein (NaV1.5-NT), composed of an N-terminus identical to NaV1.5 and a unique C-terminus derived from intronic sequence. AAV9 constructs were able to achieve stable NaV1.5-NT expression in mouse hearts, and western blot of human heart tissues showed bands co-migrating with NaV1.5-NT transgene-derived bands. NaV1.5-NT is predicted to contain a mitochondrial targeting sequence and localizes to mitochondria in cultured cardiomyocytes and in mouse hearts. NaV1.5-NT expression in cardiomyocytes led to elevations in basal oxygen consumption rate, ATP production, and mitochondrial ROS, while depleting NADH supply. Native PAGE analyses of mitochondria lysates revealed that NaV1.5-NT expression resulted in increased levels of disassembled complex V subunits and accumulation of complex I-containing supercomplexes. Overall, we discovered that APA-mediated regulation of SCN5A produces a short transcript encoding NaV1.5-NT. Our data support that NaV1.5-NT plays a multifaceted role in influencing mitochondrial physiology: 1) by increasing basal respiration likely through promoting complex V conformations that enhance proton leak, and 2) by increasing overall respiratory efficiency and NADH consumption by enhancing formation and/or stability of complex I-containing respiratory supercomplexes, though the specific molecular mechanisms underlying each of these remain unresolved.

WATER BODIES EXTRACTION USING MATHEMATICAL MORPHOLOGY

The management of water resources is vital for maintaining the world’s ecosystems. Conventional methods of extracting water bodies remain very limited due to the complexity of the implementation. This leads to a reduction in the extraction precision. Our main objec- tive is to improve the detection of water bodies. We tested the accuracy of our method on the Sentinel-2 Dataset that contains images with different complexity levels and heterogeneous structures like shadows, roads, buildings, etc. This article presents an original method that implements the idea of separating the three-component RGB image matrices and then processing only the green matrix because it contains all water bodies with high precision. Our method is based mainly on the mathematical morphology. Firstly, we propose a simple and fast binary algorithm to detect the maximum of water bodies existing in the images. This step was carried out using the Hit-or-Miss Transform. The second step exploits applying the Top-Hat Transform to refine the segmentation result. By comparing our method with several currently used methods, we notice that our method improves the quality of segmentation and gives excellent results, which exceed 95% for all the metrics used to calculate the classification quality in the purview of remote sensing. The error obtained with our method remains less than 1 %. We can affirm that our method is very suitable for detecting bodies of water compared to all current methods.

(Invited) Point-of-Care Biomembrane-Based Electronic Sensors

The development of medical devices that comply with the soft mechanics of biological systems at different length and complexity levels is highly desirable. With the emergence of conducting polymers exciting directions opened up in bioelectronics research, bridging the gap between traditional electronics and biology. With the ultimate goal of fully integrated devices, organic bioelectronic technologies have been heavily explored the past decade resulting in novel materials/device configurations. Multiplexing capability, ability to adopt to complex performance requirements in biological fluids, sensitivity, stability, literal flexibility and compatibility with large-area processes are only some of the merits of this technology for biomedical applications. A recent example of a bio-integrated electronic device, the BiOET, is based on polymeric semiconductor technology and is fabricated using nano/micro-fabrication methods in conjunction with synthetic biology approaches to incorporate hierarchically organized biological models of the cell membrane. Despite their significance, cell membranes are still an underexplored target for studying the mechanisms of diseases or drug therapies. Cell-free commercially available technologies for cell membrane studies have been limited to synthetic membranes that lack the inherent complexity found in the membrane of the cell. In this talk I will describe a method to create native cell membranes, using vesicles derived from live cells, on top of conducting polymer- based microfabricated electrodes and transistors. The activity of transmembrane proteins in response to different stimuli can be electrically monitored, offering a direct means to characterize drug toxicity or potency at the critical first contact point: membrane interaction.

In-situ valve opening response of eastern oysters to estuarine conditions

High-frequency recordings of valve opening behavior (VOB) in bivalves are often used to detect changes in environmental conditions. However, generally a single variable such as temperature or the presence of toxicants in the water is the focus. A description of routine VOB under non-stressful conditions is also important for interpreting responses to environmental changes. Here we present the first detailed quantitative investigation of the in-situ VOB of eastern oysters (Crassostrea virginica) to environmental variables typically not considered stressful. The VOB of eight individuals was monitored for seven weeks in a Louisiana estuary. We examined the relationships between VOB metrics (variance in mean % max opening among oysters, the probability of an oyster being closed, and the rate of valve closure), and temperature, salinity, chlorophyll-a (chl-a) concentration, the rate of change in those environmental variables, and the rate of change in water depth. Relationships were analyzed through statistical models including rates of change over 0, 0.25, 1-, 6-, 12-, and 24-hours. All the responses were best explained by the 12-hour time step model. The interaction effect between salinity and the rate of change of salinity had the greatest impact on variance in oysters’ behavior. Oysters closed faster at higher salinities and were more likely to be closed at lower chl-a concentrations. Significant interactions were found between many environmental variables, indicating a high level of complexity of oyster behavior in the natural environment. This study contributes to a better understanding of the impact of environmental conditions on oyster behavior and can help inform predictive tools for restoration initiatives and fisheries practices.

The effect of a combined cooling intervention on cognitive function in the heat during an intermittent running protocol.

Despite optimal cognitive function being essential for performance, there is a lack of research on the effectiveness of combined cooling interventions on team sport athlete's cognitive function when exercising in the heat. In a randomised, crossover design, 12 unacclimatised men (age: 22.3±3.0years, body mass: 73.4±5.1kg, height: 181.0±5.3cm and max: 51.2±9.5mL/kg/min) participated in a control (CON) and combined cooling trial (ice slurry and ice collar; COOL). A battery of cognitive tests were completed prior to, during (at half-time) and following a 90-min intermittent running protocol in the heat (33°C, 50% relative humidity (RH)). Perceptual and physiological measures were taken throughout the protocol. In CON, response times were quicker on the Stroop task complex level (p=0.002) and the visual search test complex level at full-time (p=0.014) compared to COOL. During COOL, response times were quicker at half-time on the Stroop task complex level (p=0.024) compared to CON. Lower rectal temperatures were seen during COOL (CON: 37.44±0.65°C and COOL: 37.28±0.68°C) as well as lower skin, neck and forehead temperatures (main effect of trial, all p<0.05). Lower ratings of thermal sensation and perceived exertion and enhanced thermal comfort were recorded during COOL (main effect of trial, all p<0.05). Whilst minimal differences in cognitive function were found when using the combined cooling intervention, the findings highlight a practical and effective strategy to improving many physiological and perceptual responses to intermittent exercise in the heat.

Robustness of highly complex radial carpet beams in turbulent atmospheres

In this study, we report observations of propagating radial carpet beams (RCBs) through a turbulent atmosphere at ground level with a 120 m path length. RCBs are a class of nondiffracting, accelerating, self-healing, and self-amplifying beams, and generated in the diffraction of a plane wave from amplitude/phase radial gratings having different spoke numbers. Observations were made at different times of the day. The intensity profile of an RCB becomes complicated when the number of grating spokes used to generate the beam is large, and includes high intensity spots, called main intensity spots (MISs), which are symmetrically placed at the central area around the beam axis and whose number is equal to (twice) the number of spokes of the amplitude (phase) grating used to generate the beam. With the aid of a telescope and a CCD camera, successive frames of the intensity pattern of the RCBs having different levels of structural complexity are recorded at the end of the path. For the data recorded at different times of the day, we calculate the variance of displacements of MISs along the radial direction. We observe that displacements of the MISs increase with increasing mean temperature of the air; on the other hand, as the complexity of the beam intensity pattern increases, the displacements of the MISs decrease. In order to compare the resilience of different RCBs and a well-known structured beam against atmospheric turbulence, we investigate deformation of the intensity profiles of a Laguerre–Gaussian (LG) beam having a topological charge 20 and different RCBs at the end of the path. It is shown that under the same turbulence condition, highly complex RCBs are more resilient to the destructive effects of the atmospheric turbulence. In particular, for the RCBs generated with gratings having 30 spokes and more, the number of MISs of the received intensity patterns is changed by less than 1% even when the turbulence strength is high. But for the LG beam, its intensity ring is clearly broken in different places, which makes it impossible to follow its maximum intensity in the radial direction

Associations of luteal phase changes in vagally mediated heart rate variability with premenstrual emotional changes

BackgroundA recent meta-analysis revealed that vagally mediated heart rate variability (vmHRV; a biomarker of emotion regulation capacity) significantly decreases in the luteal phase of the menstrual cycle. As two follow-up studies suggest, these vmHRV decreases are driven primarily by increased luteal progesterone (P4). However, analyses also revealed significant interindividual differences in vmHRV reactivity to the cycle, which is in line with longstanding evidence for interindividual differences in mood sensitivity to the cycle. The present study begins to investigate whether these interindividual differences in vmHRV cyclicity can explain who is at higher risk of showing premenstrual emotional changes. We expected a greater degree of midluteal vmHRV decrease to be predictive of a greater premenstrual increase in negative affect.MethodsWe conducted an observational study with a naturally cycling community sample (N = 31, M = 26.03 years). Over a span of six weeks, participants completed (a) daily ratings of negative affect and (b) counterbalanced lab visits in their ovulatory, midluteal, and perimenstrual phases. Lab visits were scheduled based on positive ovulation tests and included assessments of baseline vmHRV and salivary ovarian steroid levels.ResultsIn line with previous research, multilevel models suggest that most of the sample shows ovulatory-to-midluteal vmHRV decreases which, however, were not associated with premenstrual emotional changes. Interestingly, it was only the subgroup with luteal increases in vmHRV whose negative affect markedly worsened premenstrually and improved postmenstrually.ConclusionThe present study begins to investigate cyclical changes in vmHRV as a potential biomarker of mood sensitivity to the menstrual cycle. The results demonstrate a higher level of complexity in these associations than initially expected, given that only atypical midluteal increases in vmHRV are associated with greater premenstrual negative affect. Potential underlying mechanisms are discussed, among those the possibility that luteal vmHRV increases index compensatory efforts to regulate emotion in those with greater premenstrual negative affect. However, future studies with larger and clinical samples and more granular vmHRV assessments should build on these findings and further explore associations between vmHRV cyclicity and menstrually related mood changes.

Effects of taurine on the growth performance, diarrhea, oxidative stress and intestinal barrier function of weanling piglets.

Oxidative damage resulting from weaning stress significantly impacts the growth performance and health status of piglets. Taurine, a dietary antioxidant with diverse functions, was investigated in this study for its protective role against weaning stress-induced oxidative damage and its underlying mechanism. Forty 28-day-old male castrated weaned piglets were randomly assigned to four groups. The control group received the basal diet, while the experimental groups were fed the basal diet supplemented with 0.1, 0.2%, or 0.3% taurine over a 28-day period. In vitro, H2O2 was utilized to induce oxidative damage to the jejunal mucosa of piglets via IPEC-J2 cells. The results demonstrated that taurine supplementation reduced the incidence of diarrhea in piglets compared to that in the control group (p < 0.05); the addition of 0.2 and 0.3% taurine led to increased average daily gain and improved feed conversion efficiency in weaned piglets, showing a linear dose-response correlation (p < 0.05). Taurine supplementation at 0.2 and 0.3% enhanced the activities of serum CAT and GSH-Px while decreasing the levels of serum NO, XOD, GSSG, and MDA (p < 0.05). Moreover, it significantly elevated the levels of GSS, Trx, POD, complex I, mt-nd5, and mt-nd6, enhancing superoxide anion scavenging capacity and the hydroxyl-free scavenging rate in the livers of weaned piglets while reducing NO levels in the liver (p < 0.05). Additionally, 0.2 and 0.3% taurine supplementation decreased serum IL-6 levels and elevated the concentrations of IgA, IgG, and IL-10 in weaned piglets (p < 0.05). The levels of occludin, claudin, and ZO-1 in the jejunum mucosa of weaned piglets increased with 0.2 and 0.3% taurine supplementation (p < 0.05). In IPEC-J2 cells, pretreatment with 25 mM taurine for 24 h enhanced the activities of SOD and CAT; reduced the MDA content; upregulated the mRNA expression of various genes, including ZO-1, occludin, claudin-1, Nrf2, and HO-1; and reversed the oxidative damage induced by H2O2 exposure (p < 0.05). Overall, the findings suggest that the inclusion of 2 and 3% taurine in the diet can enhance growth performance, reduce diarrhea rates, ameliorate oxidative stress and inflammation, and promote intestinal barrier function in weaned piglets.

The authenticity dilemma: towards a theory on the conditions and effects of authentic learning

A highly authentic learning setting is likely to trigger positive motivational and emotional reactions due to its emphasis on promoting the acquisition of knowledge that is connected and transferable to real-world phenomena outside the learning environment. However, a high level of authenticity is usually accompanied by a high level of complexity due to the complexity inherent in the real world. This complexity can be overwhelming for learners and can hamper or even prevent cognitive learning outcomes. Consequently, to help learners cope with this complexity, they need some kind of instructional support. By building a high level of support into the learning setting in order to promote cognitive learning outcomes, the level of authenticity and thereby the effects of authenticity on motivational outcomes may, however, in turn be reduced. In the present conceptual paper, we refer to this tension between authenticity and complexity, on the one hand, and instructional support, on the other hand, as the “authenticity dilemma”. Based on existing empirical evidence from previous studies, we (1) outline this dilemma, (2) discuss ways to reconceptualize it, and (3) derive implications regarding the conditions and effects of authentic learning. Finally, we discuss the findings of the studies included in the special issue “Perspectives on Authentic Learning” through the lens of the authenticity dilemma.

Complexity of hydrometeorological variables: false nearest neighbour algorithm

ABSTRACT This study examines the complexity of hydrometeorological variables in the Savitri River basin in India. Specifically, the study estimates the dimensionality of daily rainfall, runoff, maximum temperature, minimum temperature, pan evaporation, relative humidity, sunshine duration, and wind speed observed during 2000–2010 at two stations (Kangule and Birwadi). The false nearest neighbour (FNN) algorithm is employed to estimate the dimensionality of each variable. The dimensionality represents the number of variables dominantly governing the system. The FNN dimension values of the eight daily hydrometeorological time series from each station range between 4 and 7, which may be considered as exhibiting a medium level of complexity. Among the eight series, wind speed is found to be the least complex, whereas minimum temperature and sunshine duration are the most complex. An attempt is also made to examine the effect of temporal scale on the complexity of the hydrometeorological variables, by analysing the hourly rainfall and runoff series from the two stations. The results indicate that, for both rainfall and runoff, hourly data (finer scale) exhibits greater complexity, with two to three additional influential variables. The present results have important implications for hydrometeorological modelling, prediction, and disaster management in the small and flood-prone Savitri River basin.

Role of the polyamine transporter PotABCD during biofilm formation by Streptococcus pneumoniae.

Streptococcus pneumoniae is a bacterium of great global importance, responsible for more than one million deaths per year. This bacterium is commonly acquired in the first years of life and colonizes the upper respiratory tract asymptomatically by forming biofilms that persist for extended times in the nasopharynx. However, under conditions that alter the bacterial environment, such as viral infections, pneumococci can escape from the biofilm and invade other niches, causing local and systemic disease of varying severity. The polyamine transporter PotABCD is required for optimal survival of the organism in the host. Immunization of mice with recombinant PotD can reduce subsequent bacterial colonization. PotD has also been suggested to be involved in pneumococcal biofilm development. Therefore, in this study we aimed to elucidate the role of PotABCD and polyamines in pneumococcal biofilm formation. First, the formation of biofilms was evaluated in the presence of exogenous polyamines-the substrate transported by PotABCD-added to culture medium. Next, a potABCD-negative strain was used to determine biofilm formation in different model systems using diverse levels of complexity from abiotic surface to cell substrate to in vivo animal models and was compared with its wild-type strain. The results showed that adding more polyamines to the medium stimulated biofilm formation, suggesting a direct correlation between polyamines and biofilm formation. Also, deletion of potABCD operon impaired biofilm formation in all models tested. Interestingly, more differences between wild-type and mutant strains were observed in the more complex model, which emphasizes the significance of employing more physiological models in studying biofilm formation.

Enhancing Photosynthesis and Plant Productivity through Genetic Modification.

Enhancing crop photosynthesis through genetic engineering technologies offers numerous opportunities to increase plant productivity. Key approaches include optimizing light utilization, increasing cytochrome b6f complex levels, and improving carbon fixation. Modifications to Rubisco and the photosynthetic electron transport chain are central to these strategies. Introducing alternative photorespiratory pathways and enhancing carbonic anhydrase activity can further increase the internal CO2 concentration, thereby improving photosynthetic efficiency. The efficient translocation of photosynthetically produced sugars, which are managed by sucrose transporters, is also critical for plant growth. Additionally, incorporating genes from C4 plants, such as phosphoenolpyruvate carboxylase and NADP-malic enzymes, enhances the CO2 concentration around Rubisco, reducing photorespiration. Targeting microRNAs and transcription factors is vital for increasing photosynthesis and plant productivity, especially under stress conditions. This review highlights potential biological targets, the genetic modifications of which are aimed at improving photosynthesis and increasing plant productivity, thereby determining key areas for future research and development.

G-Net: Implementing an enhanced brain tumor segmentation framework using semantic segmentation design.

A fundamental computer vision task called semantic segmentation has significant uses in the understanding of medical pictures, including the segmentation of tumors in the brain. The G-Shaped Net architecture appears in this context as an innovative and promising design that combines components from many models to attain improved accuracy and efficiency. In order to improve efficiency, the G-Shaped Net architecture synergistically incorporates four fundamental components: the Self-Attention, Squeeze Excitation, Fusion, and Spatial Pyramid Pooling block structures. These factors work together to improve the precision and effectiveness of brain tumor segmentation. Self-Attention, a crucial component of G-Shaped architecture, gives the model the ability to concentrate on the image's most informative areas, enabling accurate localization of tumor boundaries. By adjusting channel-wise feature maps, Squeeze Excitation completes this by improving the model's capacity to capture fine-grained information in the medical pictures. Since the G-Shaped model's Spatial Pyramid Pooling component provides multi-scale contextual information, the model is capable of handling tumors of various sizes and complexity levels. Additionally, the Fusion block architectures combine characteristics from many sources, enabling a thorough comprehension of the image and improving the segmentation outcomes. The G-Shaped Net architecture is an asset for medical imaging and diagnostics and represents a substantial development in semantic segmentation, which is needed more and more for accurate brain tumor segmentation.

Bacterial Communities Associated with the Leaves and the Roots of Salt Marsh Plants of Bayfront Beach, Mobile, Alabama, USA.

Salt marshes are highly dynamic and biologically diverse ecosystems that serve as natural habitats for numerous salt-tolerant plants (halophytes). We investigated the bacterial communities associated with the roots and leaves of plants growing in the coastal salt marshes of the Bayfront Beach, located in Mobile, Alabama, United States. We compared external (epiphytic) and internal (endophytic) communities of both leaf and root plant organs. Using 16S rDNA amplicon sequencing methods, we identified 10 bacterial phyla and 59 different amplicon sequence variants (ASVs) at the genus level. Bacterial strains belonging to the phyla Proteobacteria, Bacteroidetes, and Firmicutes were highly abundant in both leaf and root samples. At the genus level, sequences of the genus Pseudomonas were common across all four sample types, with the highest abundance found in the leaf endophytic community. Additionally, Pantoea was found to be dominant in leaf tissue compared to roots. Our study revealed that plant habitat (internal vs. external for leaves and roots) was a determinant of the bacterial community structure. Co-occurrence network analyses enabled us to discern the intricate characteristics of bacterial taxa. Our network analysis revealed varied levels of ASV complexity in the epiphytic networks of roots and leaves compared to the endophytic networks. Overall, this study advances our understanding of the intricate composition of the bacterial microbiota in habitats (epiphytic and endophytic) and organs (leaf and root) of coastal salt marsh plants and suggests that plants might recruit habitat- and organ-specific bacteria to enhance their tolerance to salt stress.

The effect of nonlinear environmental feedback on the outcomes of evolutionary dynamics

In this paper, we construct a nonlinear evolutionary game model to analyze the cooperation mechanisms of the population based on a nonlinear relationship among environment and strategies. In the model, replicator dynamics and aspiration dynamics are used to explore the evolutionary outcomes of collective decision, respectively. The results suggest that the environment tends to become progressively more affluent as the number of cooperators increases, if there is a smaller intensity of environmental destruction of defectors. Interestingly, the enriched environments may attract more defectors. Hence, the population requires a higher level of vigilance against plentiful environments in response to the emergence of defectors. As opposed to replicator dynamics, aspiration dynamics can avoid the persistent oscillatory loops due to the level of aspiration. Further, we investigate the effect of complexity between the population strategy and the environment on the evolutionary outcomes. It is found that higher level of complexity can drive the environment closer to a state of affluence, but the population's strategy structure will not be modified. These insights into the relationship between environment and strategies further our understanding of the evolutionary mechanism of population and society.