Variety Of Metrics Research Articles

Integration of ESG Data in the Financial Sector (Essential for Sustainable Investment and Risk Management)

The financial industry, Environmental, Social, and Governance data have lately become an important factor for responsible investment and good risk management. ESG data is a broad array of measures that include climate risk, corporate governance, labor practices, and environmental stewardship that financial institutions may use to assess the sustainability and ethical impact of their various investments. The article addresses the importance of ESG data in underlining climate risks, informing decision- making, and keeping pace with global sustainability norms. It looks at the types of data collected, such as carbon emissions, diversity metrics, and board structure, and the methodologies of collection, including surveys, third-party databases, and IoT-driven monitoring systems. This article further reviews portfolio optimization, credit risk, and the regulatory use of ESG data. Functional comparisons between some of the popular ESG tools prevalent in the market, which include Bloomberg Terminal, MSCI ESG Manager, and Sustainalytics, are made to give perception into how these different tools function. With this trend, based on ESG data insights, financial institutions will show better alignment with SDG goals, become more transparent, and minimize long-run risks for the development of a more sustainable financial ecosystem. Keywords: ESG data, sustainable investment, risk management, climate risk, financial sector, ESG tools, methods of data collection, portfolio optimization,

Estimating the impact of 2D urban landscape patterns on extreme precipitation based on non-stationary models in the Guangdong-Hong Kong-Macao Greater Bay Area, China.

Rapid urbanization has significantly altered surface landscape configurations, leading to complex urban climates. While much attention has been focused on impervious surfaces' impact on extreme precipitation, a critical gap remains in understanding how various 2D urban landscape components influence extreme precipitation across different durations. Through an analysis of the non-stationarity and spatiotemporal variations in extreme precipitation across the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 1990 to 2020, we constructed the non-stationary Generalized Additive Models for Location Scale and Shape (GAMLSS) model by introducing six urban landscape structural metrics as explanatory variables for each of the 27 meteorological stations in the GBA. Additionally. we assessed the frequency of these metrics in the best-fitting models and predicted design values across different interannual periods. Our findings reveal that aggregation metrics (patch density: PD) and diversity metrics (Shannon's Diversity Index: SHDI) appeared more frequently in the best-fitting models than other metrics within all extreme precipitation indices. For short-duration extreme precipitation indices (≤ 3h), the area matrix (Impervious Surface Percentage: ISP), PD, and SHDI were selected more often than other metrics, whereas for long-duration (> 3h), PD and SHDI had a higher relative frequency as ISP's impact decreased. Design values peaked in the 2010s across all return periods (100, 50, and 20years), highlighting the importance of integrating urban landscape features into non-stationary models of extreme precipitation. This research provides valuable insights for improving the management of urbanization-induced heavy precipitation and flood risks.

Facilitating bootstrapped and rarefaction-based microbiome diversity analysis with q2-boots

Background We present q2-boots, a QIIME 2 plugin that facilitates bootstrapped and rarefaction-based microbiome diversity analysis. This plugin provides eight new actions that allow users to apply any of thirty different alpha diversity metrics and twenty-two beta diversity metrics to bootstrapped or rarefied feature tables, using a single QIIME 2 Pipeline command, or more granular QIIME 2 Action commands. Results Given a feature table, an even sampling depth, and the number of iterations to perform (n), the command qiime boots core-metrics will resample the feature table n times and compute alpha and beta diversity metrics on each resampled table. The results will be integrated in summary data artifacts that are identical in structure and type to results that would be generated by applying diversity metrics to a single table. This enables all the same downstream analytic tools to be applied to these tables and ensures that all collected data is considered when computing microbiome diversity metrics. Conclusions A challenge of this work was deciding how to integrate distance matrices that were computed on n resampled feature tables, as a simple average of pairwise distances (median or mean) does not account for the structure of distance matrices. q2-boots provides three options, and we show here that the results of these approaches are highly correlated. q2-boots is free and open source. Source code can be found at https://github.com/caporaso-lab/q2-boots; installation instructions and a tutorial can be found in the project’s documentation at https://q2-boots.readthedocs.io.

Understanding the vaginal microbiome among women with different genotypes of human papillomavirus infection in remote Andaman islands

BackgroundHuman papillomavirus (HPV) is a viral infection, and its acquisition and persistence are significantly influenced by the vaginal microbiota. Understanding and comparing the vaginal microbiome of HPV infected women in Andaman and Nicobar Islands is crucial.MethodsThe study involved collecting vaginal swabs and extracting DNA using the QIAamp DNA Minikit. The DNA was then subjected to PCR amplification to confirm HPV infection. illumina NovaSeq 6000 platform was utilized to perform sequencing utilizing 2 x 250 paired end chemistry. Taxonomic analysis was performed and Bacterial abundance plots were generated and samples were grouped based on demographic parameters, pap test diagnosis, and genotypes. To assess diversity, samples were rarefied to 49,000 sequence reads per sample, and alpha and beta diversity metrics were calculated.ResultsThe study analyzed the presence of 21 assigned phyla, with Firmicutes, Actinobacteria, Bacteriodetes, and Proteobacteria emerging as the predominant taxa. At the genus level, Lactobacillus and Gardnerella dominated across all samples. Gardnerella was significantly more abundant in HPV-positive (22.40%) compared to HPV-negative samples (10.04%). Symptomatic group of HPV-positive samples had Gardnerella, and unclassified Coriobacteriaceae being dominant. In terms of bacterial diversity, the study found statistically significant association when comprising individuals aged 21 to 30 years to those aged 31 to 40 years.ConclusionMost research concluded that exposure to HPV can boost bacterial diversity in vagina compared to healthy women, increasing the risk of cervical cancer development. Current study highlights the importance of vaginal microbiome associated with high and low risk HPV, various age group as well as the symptomatic and asymptomatic cases of HPV infected women in South Andaman.

Methods for Evaluating the Effectiveness of Social Media Marketing Campaigns

This article examines the methodological aspects of evaluating the effectiveness of marketing campaigns on social media. It highlights the significance of such evaluations, emphasizing their role in optimizing processes, identifying areas for improvement, enhancing decision-making, ensuring alignment with objectives, and enabling iterative progress. The study identifies the unique characteristics of assessing social media marketing campaigns, contrasting them with traditional, non-digital methods commonly used in internal business marketing. The article reviews widely used methods for evaluating social media marketing performance and argues for the development of a customized approach that integrates multiple evaluation techniques with diverse origins, principles, and metrics. Particular attention is given to customer journey mapping as a tool for identifying and resolving potential "bottlenecks" in social media marketing efforts. The article describes the main stages of journey mapping and suggests key metrics for evaluation. It also discusses data sources and provides structured recommendations for creating a company-specific methodology for assessing social media marketing effectiveness. The study emphasizes the importance of setting clear goals, defining specific metrics and key performance indicators, incorporating diverse measures, and automating analytics for long-term use. Finally, it advocates for focusing on creative development as part of the optimization process. This research is intended for marketers working in social media, offering insights into comprehensive evaluation and strategies for improving campaign effectiveness.

Optimization Study of a High-Efficiency Preservative for Ammonia-Free Concentrated Natural Rubber Latex

Ammonia is commonly used as a preservative in the production of concentrated natural rubber latex (CNRL) and latex products; however, it poses a serious risk to human health and the environment. In this study, we investigated a thioacetamide derivative (TD) as a preservative of ammonia-free CNRL and the optimization of a stabilization system comprising potassium hydroxide (KOH), lauric acid (LA), and sodium dodecyl sulfate (SDS) to enhance its preservation effect. The results revealed that an optimal amount of TD (0.03%) can effectively maintain the stability of CNRL, inhibit the increase in volatile fatty acid number (VFA number), maintain stable viscosity values, and improve the mechanical stability time (MST). However, increasing the TD dosage results in an increase in both the viscosity and VFA number and a decrease in MST. KOH was used to regulate the pH value of CNRL. It was also found that it can enhance considerably the mechanical properties of CNRL dry films and accelerates the vulcanization of vulcanized film; however, an excessive amount causes latex thickening. LA proved essential for improving the MST and reducing latex viscosity, thereby substantially enhancing the stability and processability of pre-vulcanized latex, but an excessive amount is detrimental to the curing speed and final mechanical strength. SDS can rapidly improve the MST and reduce the viscosity, but it negatively affects the surface molding of dry rubber films. In conclusion, KOH, LA, and SDS at appropriate dosages play a balancing and complementary role in the preparation of ammonia-free CNRL. Upon analyzing diverse performance metrics of CNRL, it has been determined that the optimal TD dosage ranges from 0.02 to 0.03% for maximum efficacy. The KOH dosage should be maintained within 0.1–0.15% to achieve the most favorable outcome, while the LA dosage is advisable to be kept between 0.06 and 0.1%.

Machine Learning Assessment of Dredging Impacts on the Phytoplankton Community on the Brazilian Equatorial Margin: A Multivariate Analysis.

Dredging in estuarine systems significantly impacts phytoplankton communities, with suspended particulate matter (SPM) and dissolved aluminum (Al) serving as indicators of disturbance intensity. This study assessed the effects of dredging in the São Marcos Estuarine Complex (SMEC), Brazil, over three distinct events (2015, 2017, 2020), involving varying sediment volumes and climatic influences. Prolonged dredging operations and increased sediment volumes led to a pronounced 43.81% reduction in species diversity, with diatoms and dinoflagellates being the most affected. Climatic variability, particularly El Niño events, exacerbated environmental dispersion, amplifying the complexity of ecosystem responses. Despite these losses, certain centric diatoms persisted, reflecting resilience mechanisms within this tropical macrotidal estuary. Machine learning approaches, specifically Random Forest (RF) models, revealed SPM and dissolved Al as critical stressors influencing species diversity. Additionally, river discharge and salinity were identified as key predictors of phytoplankton biomass. Generalized Additive Models (GAMs) confirmed that chlorophyll-a concentrations responded negatively to elevated SPM and Al levels but were less sensitive to dredging than diversity metrics. This study provides novel insights into the compounded effects of dredging and climatic variability, emphasizing the utility of RF and GAM models for predicting ecosystem responses and guiding management strategies. Recommendations include optimizing operations to reduce biodiversity impacts, minimizing sediment resuspension, and integrating predictive tools to mitigate long-term disturbances. These findings offer a data-driven framework for sustainable dredging in sensitive estuarine ecosystems.

Bacterial, Archaeal, and Eukaryotic Life of Volcanic Cave Features from Lava Beds National Monument, California, USA

Volcanic caves present a variety of surfaces that host unique life, but most microbiology studies of these environments to date have focused on colorful and sometimes abundant biofilms, while largely ignoring ooze and hard secondary mineral deposits. In this study, we conducted 16S/18S rRNA gene sequencing with bacterial, archaeal, and eukaryotic domain-specific primer sets, focusing on a broad spectrum of volcanic cave features in Lava Beds National Monument grouped into ‘microbial-dominant’ (biofilms and ooze) and ‘mineral-dominant’ (secondary mineral deposits). While there are differences between individual mineral-dominant features, collectively, microbial communities associated with these features are distinct from those of microbial-dominant based on prokaryotic beta diversity metrics. Mineral-dominant features are not merely a subset of the microbial-dominant owing to their similar alpha diversity scores and unique ASVs. Ooze is distinct from all other categories due to the near absence of otherwise abundant Actinobacteriota and abundance of taxa associated with roles in ammonia and nitrite oxidation. Differences in eukaryotic communities were associated with the sampling year rather than feature type, suggesting that cave eukaryotes have a more transient lifestyle than prokaryotes. Overall, these results provide evidence that mineral-dominant features and ooze are microbiologically distinct from more-often-studied cave biofilms.

Multiscale partitioning effects of livestock grazing management on plant community composition and diversity in arid rangelands.

Arid steppe rangelands in North Africa are highly significant ecosystems that are exceedingly sensitive to global warming and are also influenced by severe grazing and heavy utilization practices. Consequently, it is imperative to conduct extensive investigations regarding the impact of overgrazing due to increased sheep populations on plant diversity in these regions. The objective of this study is to examine the effect of two grazing managements (grazing-excluded vs. free-grazing) on floristic diversity in the arid steppe rangelands of North Africa. Sampling encompassed 10 sites, with 5 freely accessible to livestock and 5 protected from grazing. Within each site, three 200-m transects were established to survey and quantify plant species abundance. Alpha (species richness and diversity) and beta (qualitative and quantitative similarity analysis) biodiversity parameters were evaluated at both small and large spatial scales. The findings demonstrated a substantial disparity in plant diversity between grazing-excluded rangelands and free-grazed rangelands. Plant community diversity and stability parameters were notably higher in grazing-excluded areas. The taxonomic structure of plant communities also exhibited greater stability in grazing-excluded steppe areas. Specifically, the grazing-excluded sites displayed superior diversity metrics, including species richness (93), Shannon index (3.2), and Simpson reciprocal index (5.5), in comparison to severely grazed sites (61, 2.6, and 4.4), respectively). The influence of severe grazing had a more pronounced effect on ephemeral species rather than perennials, emphasizing the heightened vulnerability of these plants to overgrazing effect or inadequate grassland management practices. This effect coincided with heterogeneity in floristic composition between sites with free continuous livestock access and those protected from grazing. Furthermore, analysis of similarity at different spatial scales revealed an increase in diversity at small scales contrasted with a decrease at larger scales. Grazing exerted discernible effects on floristic composition, particularly affecting ephemeral species, albeit primarily at small scales. At larger scales, the impact of grazing was not detected. These findings underscore the complex relationship between grazing practices and plant diversity dynamics in arid steppe ecosystems, emphasizing the importance of sustainable management strategies to preserve biodiversity in these vulnerable habitats.

Long-term physical and biological recovery of disturbed intertidal beach habitat from simulated oil spill cleanup in Prince William Sound, Alaska.

Following the Exxon Valdez oil spill, hydraulic techniques using combinations of high-pressure and heated water were used to mobilize weathered oil from impacted shorelines. During treatment, concerns were raised over the ecological impacts of these treatment methods. We report on a long-term study comparing grain size and infaunal communities in washed and unwashed plots at unoiled beaches treated using these methods. Despite the long-term (nine-year) disruption of grain size structure, total infaunal abundance showed no significant differences between washed and unwashed plots after only one year and species diversity metrics had recovered by the third year post-treatment. Similarly, community structure appeared to have recovered by year three. Reasons for this apparent physical/biological disconnect may be related to the native lack of fine-grained sediments in the Prince William Sound system, and inherently robust infaunal reproductive and recolonizing strategies. This work has practical implications for spill response, damage assessment, and restoration.

Utilizing a novel fecal sampling method to examine resistance of the honey bee (Apis mellifera) gut microbiome to a low dose of tetracycline.

Disruption of host-associated microbial communities can have detrimental impacts on host health. However, the capacity of individual host-associated microbial communities to resist disturbance has not been well defined. Using a novel fecal sampling method for honey bees (Apis mellifera), we examined the resistance of the honey bee gut microbiome to disruption from a low dose of the antibiotic, tetracycline (4.5 μg). Prior to the experiment, bacterial communities from fecal samples were compared to communities from dissected whole guts of the same individuals to ensure fecal samples accurately represented the gut microbiome. Fecal samples were collected from lab-caged honey bees prior to, and five days after, tetracycline exposure to assess how antibiotic disturbance affected the communities of individuals. We used metrics of alpha and beta diversity calculated from 16S rRNA gene amplicon sequences to compare gut community structure. Low dose tetracycline exposure did not consistently change honey bee gut microbiome structure, but there was individual variation in response to exposure and specific taxa (one ASV assigned to Lactobacillus kunkeei and one ASV in the genus Bombella) were differentially abundant following tetracycline treatment. To assess whether individual variation could be influenced by the presence of tetracycline resistance genes, we quantified the abundance of tet(B) and tet(M) with qPCR. The abundance of tet(M) prior to tetracycline treatment was negatively correlated with change in community membership, assessed by difference in Jaccard dissimilarity over the five-day experiment. Our results suggest that the honey bee gut microbiome has some ability to resist or recover from antibiotic-induced change, specific taxa may vary in their susceptibility to tetracycline exposure, and antibiotic resistance genes may contribute to gut microbiome resistance.

Niche-related processes explain phylogenetic structure of acoustic bird communities in Mexico.

Acoustic communities are acoustically active species aggregations within a habitat, where vocal interactions between species can interfere their communication. The acoustic adaptation hypothesis (AAH) explains how the habitat favors the transmission of acoustic signals. To understand how bird acoustic communities are structured, we tested the effect of habitat structure on the phylogenetic structure, and on the phylogenetic and vocal diversity of acoustic communities in a semi-arid zone of Mexico. From autonomous recordings in three types of vegetation (crop fields, tetecheras, and mesquiteras), which differ in terms of complexity and canopy openness, we evaluated sound attenuation, and estimated metrics of phylogenetic structure and diversity as well as acoustic diversity with the use of two indices. Mesquiteras showed greater vegetation density, more attenuation, more vocal diversity, as well as a phylogenetic structure that tended towards overdispersion, in contrast to crop fields that showed less vegetation density, less attenuation, less vocal diversity and more phylogenetic relatedness, while tetecheras showed intermediate patterns. Phylogenetic structure was explained by vegetation density and excess attenuation. The higher vocal diversity, phylogenetic structure tended towards overdispersion. These results suggest a role for environmental filters in the crop fields, where more closely related species with similar vocal characteristics coexist (supporting AAH), and probably competitive exclusion in the mesquiteras, where more distantly related species coexist, promoting vocal diversity. This study offers information about the influence of habitat on the acoustic community structure, which could inform our understanding of the distribution of species from acoustic perspective.

Temporal changes in Plasmodium falciparum genetic diversity and multiplicity of infection across three areas of varying malaria transmission intensities in Uganda

BackgroundMalaria is a significant public health challenge in Uganda, with Plasmodium falciparum (P. falciparum) responsible for most of malaria infections. The high genetic diversity and multiplicity of infection (MOI) associated with P. falciparum complicate treatment and prevention efforts. This study investigated temporal changes in P. falciparum genetic diversity and MOI across three sites with varying malaria transmission intensities. Understanding these changes is essential for informing effective malaria control strategies for the different malaria transmission settings.MethodsA total of 220 P. falciparum-positive dried blood spot (DBS) filter paper samples from participants in a study conducted during 2011–2012 and 2015–2016 were analyzed. Genotyping utilized seven polymorphic markers: Poly-α, TA1, TA109, PfPK2, 2490, C2M34–313, and C3M69–383. Genetic diversity metrics, including the number of alleles and expected heterozygosity, were calculated using GENALEX and ARLEQUIN software. MOI was assessed by counting distinct genotypes. Multi-locus linkage disequilibrium (LD) and genetic differentiation were evaluated using the standardized index of association (IAS) and Wright's fixation index (FST), respectively. Statistical comparisons were made using the Kruskal–Wallis test, and temporal trends were analyzed using the Jonckheere–Terpstra test, with statistical significance set at p < 0.05.ResultsOf the 220 samples, 180 were successfully amplified. The majority of participants were males (50.6%) and children aged 5–11 years (46.7%). Genetic diversity remained high, with mean expected heterozygosity (He) showing a slight decrease over time (range: 0.73–0.82). Polyclonal infections exceeded 50% at all sites, and mean MOI ranged from 1.7 to 2.2, with a significant reduction in Tororo (from 2.2 to 2.0, p = 0.03). Linkage disequilibrium showed a slight increase, with Kanungu exhibiting the lowest IAS in 2011–2012 (0.0085) and Jinja the highest (0.0239) in 2015–2016. Overall genetic differentiation remained low, with slight increases in pairwise FST values over time, notably between Jinja and Tororo (from 0.0145 to 0.0353).ConclusionsThis study highlights the genetic diversity and MOI of P. falciparum in Uganda's malaria transmission settings, noting a slight decrease in both genetic diversity and MOI overtime. Continued surveillance and targeted control strategies are essential for monitoring the impact of malaria control efforts in Uganda.

Comparing subsampling strategies for metagenomic analysis in microbial studies using amplicon sequence variants versus operational taxonomic units.

The microbiome is increasingly regarded as a key component of human health, and analysis of microbiome data can aid in the development of precision medicine. Due to the high cost of shotgun metagenomic sequencing (SM-seq), microbiome analyses can be done cost-effectively in two phases: Phase 1-sequencing of 16S ribosomal RNA, and Phase 2-SM-seq of an informative subsample. Existing research suggests strategies to select the subsample based on biological diversity and dissimilarity metrics calculated using operational taxonomic units (OTUs). However, the microbiome field has progressed towards amplicon sequencing variants (ASVs), as they provide more precise microbe identification and sample diversity information. The aim of this work is to compare the subsampling strategies for two-phase metagenomic studies when using ASVs instead of OTUs, and to propose data driven strategies for subsample selection through dimension reduction techniques. We used 199 samples of infant-gut microbiome data from the DIABIMMUNE project to generate ASVs and OTUs, then generated subsamples based on five existing biologically driven subsampling methods and two data driven methods. Linear discriminant analysis Effect Size (LEfSe) was used to assess differential representation of taxa between the subsamples and the overall sample. The use of ASVs showed a 50-93% agreement in the subsample selection with the use of OTUs for the subsampling methods evaluated, and showed a similar bacterial representation across all methods. Although sampling using ASVs and OTUs typically lead to similar results for each subsample, ASVs had more clades that differed in expression levels between allergic and non-allergic individuals across all sample sizes compared to OTUs, and led to more biomarkers discovered at Phase 2-SM-seq level.

OligoDistiller: A Platform Agnostic Software Tool for MS and MS2 Data Analysis of Complex Oligonucleotides and Their Impurities.

Oligonucleotides are currently one of the most rapidly advancing classes of therapeutic modalities. Understanding critical quality attributes, such as the impurity profile, stability, potential metabolites, and sequence conformity, is the key to their ultimate success. To obtain the information presented above, liquid chromatography-mass spectrometry (LC-MS) is often employed. However, data interpretation can be challenging due to multiple charge states, unknown species, chemical noises, and overlapping isotope envelopes (OIEs) of distinct but unresolved species. To address these challenges, we have developed an MS-platform agnostic, multifunctional R package and a web-tool for automated and interactive MS and MS2 data analysis, OligoDistiller. From the MS spectrum of a complex mixture of two synthetic strands, our tool OligoDistiller annotated and quantified 45 oligonucleotide-related features including 13 unknown impurities and 6 OIEs, which all together explained 90.8% of the detected peaks. Also, major product ions were assigned from the MS2 spectrum of a 47-mer DNA strand, covering 80.3% of the oligonucleotide sequence. We provide not only diverse isotope quality metrics for each annotated feature but also an interactive data review module allowing for direct inspection of the part of raw spectrum linked to a selected feature. This tool OligoDistiller is freely available at https://github.com/daniellyz/OligoDistiller.

Traditional and Contemporary Measures of Recreational Fishing Activity to Inform Sustainable Management of Blue Swimmer Crab (Portunus armatus) Fisheries in Western Australia

ABSTRACTRecreational fishing is a popular activity that has many social and economic benefits. Monitoring has traditionally centred around measuring fishing effort and catch. However, contemporary measures, such as fisher demographics and behaviours, which may be linked to social and economic objectives, are now recognised as necessary to meet expectations that all aspects of resource use are considered for fisheries management. The challenge for recreational fisheries is how to regularly provide information across a growing diversity of metrics, and at a scale relevant to specific fisheries, with limited resources. The Blue Swimmer Crab (Portunus armatus) is one of the most commonly recreationally harvested species in Western Australia. This species served as a case study to explore if data from five broad‐scale phone‐diary surveys between 2011–2012 and 2020–2021 could be adapted to meet expanded information needs. Twelve discrete fisheries represented small spatial‐scale areas for fisheries management, with some variation in management arrangements (i.e., bag limits). Robust estimates of traditional and contemporary measures could be produced for three fisheries: Peel‐Harvey Estuary, Swan‐Canning Estuary and Geographe Bay. Traditional measures of participation, fishing effort, total catch and harvest from 2011–2012 to 2020–2021 were generally consistent for Swan‐Canning Estuary but decreased for Peel‐Harvey Estuary and Geographe Bay. The proportion of harvest from recreational and commercial fishing varied from mixed use (Swan‐Canning Estuary, Peel‐Harvey Estuary) to recreational only (Geographe Bay). Variation in contemporary measures was also evident, with recreational fishing largely undertaken by local residents in Swan‐Canning Estuary, while participation was more uniform between local and non‐local residents in Peel‐Harvey Estuary and Geographe Bay. We found that broad‐scale surveys could be successfully adapted to meet the growing need for information on contemporary measures to support a holistic approach to sustainable fisheries management for small spatial‐scale recreational fisheries.

Interrelationships of the Intestinal Microbiome, Trimethylamine N-Oxide and Lipopolysaccharide-Binding Protein with Crohn’s Disease Activity

Crohn’s disease (CD) is a multifactorial inflammatory bowel disease whose pathogenetic mechanisms are a field of ongoing study. Changes in the intestinal microbiome in CD may influence metabolite production and reflect the disease’s severity. We investigate the relationship between trimethylamine N-oxide (TMAO) and lipopolysaccharide-binding protein (LPS) levels and changes in the gut microbiome in patients with CD of various degrees of activity. Methods: In total, 29 CD patients and 15 healthy individuals were investigated for their levels of TMAO by HPLC-MS, and LPS protein by ELISA and metagenomic 16 s-sequencing of feces was performed. Results: We found significant differences in TMAO levels in patients in the remission/mild and moderate/severe groups compared to the control group (p = 0.02 and p = 0.014), changes in alpha diversity with the Shannon index (p = 0. 0151 and p = 0.0018) and in beta diversity (ANOSIM p = 0.009 and PERMANOVA p = 0.005) in both groups compared to controls. Strongly positive correlations in TMAO levels and mixed correlations of LPS with alpha diversity metrics were found, as well as significant correlations with microbiota species. Conclusions: Changes in the level of metabolites may reflect specific disturbances in the composition of the intestinal microbiome at different degrees of severity of CD.

Empirical Insights into Eye-Tracking for Design Evaluation: Applications in Visual Communication and New Media Design.

(1) Background: As digital technology continues to reshape visual landscapes, understanding how design elements influence customer experience has become essential. Eye-tracking technology offers a powerful, quantitative approach to assessing visibility, aesthetics, and design components, providing unique insights into visual engagement. (2) Methods: This paper presents a systematic review of eye-tracking methodologies applied in design research. Thirty studies were selected for analysis from recognized academic databases using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. Employing the Population, Intervention, Comparison, and Outcomes (PICO) framework, this review focused on experimental studies in visual communication and new media design that utilized visual symbols for communication and leveraged new media technologies. (3) Results: The findings corroborated that eye-tracking technology offers in-depth insights into gaze patterns, visual perception, and attention, which can inform design strategies. This review shows that assessing visual designs based on eye-tracking data can enhance consumer-centered interfaces, better align with user preferences, and foster more engaged behaviors in both digital and physical environments. (4) Conclusions: This review deepens our understanding of the cognitive and emotional processes underlying visual engagement. It also suggests new avenues for integrating diverse eye-tracking metrics into design evaluation, offering practical applications for improving design strategies and advancing the field of design research.

Alterations in Gut Microbiota Composition Are Associated with Changes in Emotional Distress in Children with Obstructive Sleep Apnea.

Emerging evidence underscores the pivotal role of the gut microbiota in regulating emotional and behavioral responses via the microbiota-gut-brain axis. This study explores associations between pediatric obstructive sleep apnea (OSA), emotional distress (ED), and gut microbiome alterations before and after OSA treatment. Sixty-six children diagnosed with OSA via polysomnography participated, undergoing adenotonsillectomy alongside routine educational sessions. ED was assessed using the OSA-18 questionnaire, categorizing participants into high ED (scores ≥ 11, 52%) and low ED (scores < 11, 48%) groups. Gut microbiome analysis revealed significant diversity differences, with high ED linked to a reduced Shannon index (p = 0.03) and increased beta diversity (p = 0.01). Three months post-treatment, significant improvements were observed in OSA symptoms, ED scores, and gut microbiome alpha diversity metrics among 55 participants (all p < 0.04). Moreover, changes in the relative abundances of Veillonella, Bifidobacterium, Flavonifractor, and Agathobacter, as well as ultra-low frequency power and low frequency power of sleep heart rate variability, were independently associated with ED score alterations. These findings underscore the gut microbiome's critical role in the emotional and behavioral symptoms associated with pediatric OSA, suggesting that microbiome-targeted interventions could complement traditional treatments for ED reduction and emphasizing the need for further research.

Optimal Combination of Different Selection and Mating Strategies on Exploiting Genetic Diversity and Genetic Gain in Small Pig Conservation Populations.

Both selection and mating systems are essential tools for breeders to conserve the genetic variance and improve the performance of livestock animals. How to effectively balance the genetic gain and inbreeding has always been an important issue in quantitative genetics research. In this study, a total of 11 selection methods, including random and truncation selection, six conventional selection methods, three different optimal contribution selection (OCS) methods and three mating strategies including random mating, minimum-coancestry mating based on pedigree (MCPed) and genomic information (MCmarker), were performed using stochastic simulations. The long-term effects of different combinations of selection and mating strategies on the genetic gain, the rate of inbreeding and genetic diversity in the small-scale pig conservation populations were investigated. The results showed that different strategies of selection and mating methods had different effects on genetic gain and inbreeding rate. For maintaining additive genetic variance, the optimal strategy was random selection with random mating, followed by SIREhalf-DAMfullRandom selection (which means selecting dams randomly from each full-sib family) and random mating. For mainting the number of common ancestors, the optimal strategy was SIREhalf-DAMfull selection (which means selecting dams with the highest estimated breeding value within each full-sib family) and random mating, followed by SIREhalf-DAMfullRandom selection and random mating, OCS and MCPed mating. For genetic diversity metrics, taking He and Ho as an example, the optimal strategy was GOCS (optimal contribution selection based on genomic information) with MCmarker mating. For genetic gain, the optimal strategy was truncation selection and MCmarker mating, followed by POCS (optimal contribution selection based on pedigree information) and MCmarker mating, truncation selection and MCPed mating. For the rate of inbreeding, the optimal strategy was SIREhalf-DAMfull selection and MCPed mating. Our findings can help breeding managers and farmers choose a more suitable and sustainable strategy for maintaining the genetic diversity and improving the genetic gain of local pig breeds.