Significant Clusters Research Articles

Subjectively salient faces differ from emotional faces: ERP evidence

The self-face is processed differently than emotional faces. A question arises whether other highly familiar and subjectively significant non-self faces (e.g. partner’s face) are also differentiated from emotional faces. The aim of this event-related potential (ERP) study was to investigate the neural correlates of personally-relevant faces (the self and a close-other’s) as well as emotionally positive (happy) and neutral faces. Participants were tasked with the simple detection of faces. Amplitudes of N170 were more negative in the right than in the left hemisphere and were not modulated by type of face. A similar pattern of N2 and P3 results for the self-face and close-other’s face was observed: they were associated with decreased N2 and increased P3 relative to happy and neutral faces. However, the self-face was preferentially processed also when compared to a close-other’s face as revealed by lower N2 and higher P3 amplitudes. Nonparametric cluster-based permutation tests showed an analogous pattern of results: significant clusters for the self-face compared with all other faces (close-other’s, happy, neutral) and for close-other’s face compared to happy and neutral faces. In summary, the self-face prioritization was observed, as indicated by significant differences between one’s own face and all other faces. Crucially, both types of personally-relevant faces differed from happy faces. These findings point to the pivotal role of subjective evaluation of the saliency factor.

Spatial distribution and source identification of metal contaminants in soil and rice grain samples: a study on exploration of soil quality and risk assessment.

The present study aims to assess soil quality and potential health risks associated with soil pollution of the Batala region of Punjab, India. Physico-chemical parameters such as pH (6.69-7.43), electrical conductivity (0.17-0.33 mS/cm), and total organic carbon (1.01-5.94%) were observed to be within permissible limits. The maximum mean content (mg/kg) of heavy metals in soil was found as Fe (4060.93), Zn (444.33), Mn (278.5), Pb (23.16), Cu (21.78), Ni (20.16), Co (7.14), and Cd (1.85) which were below the prescribed limits but beyond the geochemical background limits of world soil. For rice grain samples, metal content (mg/kg) was seen as Fe (307.01) > Zn (12.41) > Mn (7.43) > Cu (4.57) and was below the permissible limits. The mean bioaccumulation factor for various metals was in the order as Zn > Cu > Fe > Mn. Single and integrated soil pollution indices revealed that among 18 sites, six were highly contaminated. The ecological risk index (Er) has shown that contamination of soil with Cd, Zn, and Ni was higher than that of other metals studied. The estimated daily intake of metal (EDI), hazard quotient (HQ), and hazard index (HI) were higher for children than those for adults. Spatial variability based on metal pollution load and soil quality was also determined using cluster analysis (CA) and principal component analysis (PCA). During CA, soil samples from 18 sites formed three statistically significant clusters based on the level of metal pollution at the specific site. PCA showed that all variables were reduced into two main components 1 and 2 with eigenvalues as 3.82 (47% variance) and 1.53 (19.7% variance), respectively.

Applying Geostatistics to Understand Seismic Activity Patterns in the Northern Red Sea Boundary Zone

A comprehensive geostatistical analysis was conducted on a dataset comprising 24,321 seismic events in the Red Sea region, spanning from 1997 to 2020. This analysis involved the creation of a new seismic activity database, incorporating data from both Egyptian and Saudi Seismic Networks. This enriched database provided a robust foundation for a detailed examination of the seismic patterns and activities in the region. Utilizing geographic information systems and various spatial analytic methods, it identifies seismic patterns and tectonic influences. The findings reveal significant seismic clustering along the Central Red Sea axis, indicative of active rifting between the Nubian and Arabian plates. The study demonstrates spatial autocorrelation in seismic activities, with high-high clusters marking zones of elevated seismicity. Kernel Density Estimator analyses highlight concentrated seismic activity in the Gulfs of Aqaba and Suez. Higher magnitude events are shown to localize in areas of greater tectonic stress, aligning with known geological features. This research provides critical insights into the seismic dynamics of the Red Sea, showcasing the effectiveness of geostatistical techniques in analyzing seismic data in tectonically active regions.

Spatial variation and determinants of delayed breastfeeding initiation in Ethiopia: spatial and multilevel analysis of recent evidence from EDHS 2019

BackgroundDespite the World Health Organization’s firm recommendation to start breastfeeding during the first hour after delivery, nearly 54% of children in low- and middle-income countries are unable to initiate breastfeeding within the recommended time frame. Understanding the initiation of breastfeeding is essential for optimal child health and maternal well-being.MethodsThis study was conducted using the recent Ethiopian Demographic and Health Survey (EDHS) data (2019) on a weighted sample of 1982 Ethiopian mothers of children aged under 24 months. The data extraction was conducted between August 1 and 30, 2023. Delayed’ initiation of breastfeeding is defined as failure to initiate breastfeeding within one hour after birth. STATA version 17 was used for non-spatial analysis. ArcGIS Pro and Sat Scan version 9.6 were used to map the visual presentation of delayed breastfeeding initiation. Global Moran’s I was computed to determine whether delayed breastfeeding initiation is randomly distributed, clustered, or dispersed. Getis-Ord Gi* Spatial Statistics was done to identify significant spatial clusters of cold and hot spot areas. Multilevel mixed-effect logistic regression analysis was computed to identify determinants of delayed breastfeeding initiation.ResultsThe prevalence of delayed breastfeeding initiation is 26.4% (95% CI 24.4, 28.3). Significant clustering of delayed initiation of breastfeeding practice was found in the Somali region. Less clustering was identified in Northern Amhara, Addis Ababa and Dire Dawa. Being a young mother (15–24 years) (AOR 1.66; 95% CI 1.06, 2.62), no antenatal care (AOR 1.45; 95% CI 1.04, 2.02), cesarean section (AOR 4.79; 95% CI 3.19, 7.21) and home birth (AOR 1.53; 95% CI 1.14, 2.06) were found to be determinants of delayed initiation of breastfeeding.ConclusionsIn Ethiopia, delayed breastfeeding initiation is distributed non-randomly. Significant hotspot areas were identified in the eastern part of Ethiopia. Thus, deploying additional resources in high hotspot regions is recommended. Programs should focus on promoting health facility birth and increasing antenatal care visits. Further emphasis should be considered on supporting young mothers and those giving birth via cesarean section to improve timely breastfeeding initiation.

487 - Adult atopic dermatitis is associated with impaired oral health and oral dysbiosis - a case-control study

Abstract Background Previous studies linked chronic oral diseases to skin disorders such as psoriasis. However, data about oral health and oral microbiota in atopic dermatitis (AD) is sparse. Objectives To compare the oral health status and oral microbiota of AD patients and healthy controls. Methods This was a prospective sex and age- matched case-control study comparing adult participants with and without dermatologist-verified AD. Exclusion criteria included recent use of oral, topical, or systemic medication that could affect oral health or microbiome assessment. Oral health indices including Gingival Index, Plaque Index, Oral Hygiene Index, Caries Severity Index and prosthodontics status, were assessed by a dentist. Samples of oral flora were collected and subjected to high-throughput 16S rRNA gene sequencing analysis for microbiome analysis. Results Forty-five AD participants and 41 non-AD controls were recruited. The two groups had no significant differences in terms of their demographic and clinical characteristics, except for the higher rate of atopic co-morbidities in the AD group (p<.001). Compared to the control group, participants with AD had significantly poorer plaque (p=0.04) and oral hygiene indices (p=0.04) and a trend towards higher gingival index (p=0.05). The results of the Faith phylogenetic diversity (FDR) test indicated that the oral microbial diversity in the AD group was significantly higher (α-diversity, FDR-adjusted p=0.0007) when compared with the control group. Characterization of the similarities and differences in the composition of the microbial communities between the samples (β-diversity) from the AD patients and controls indicated that they clustered separately. The groups showed significant dissimilarity and distinct clustering of microbial abundance (FDR-adjusted p=0.001). Importantly, higher community diversity was previously linked to periodontitis and gingival disease. Furthermore, AD patients had a significantly increased abundance of taxa correlated with oral diseases and decreased abundance of oral health-associated bacteria. Conclusion AD appears to be associated with poorer oral health and oral dysbiosis, and thus, there is a need to increase the awareness of both patients and physicians about oral health.

Are National Breast and Cervical Cancer Early Detection Program Recipients Providing Services in Counties Heavily Burdened by Breast and Cervical Cancer?

Alignment of National Breast and Cervical Cancer Early Detection Program (NBCCEDP) clinical services with the spatial distribution of breast and cervical cancer burden is essential to maximizing programmatic impact and addressing cancer disparities. This study identified spatial clustering of breast and cervical cancer burden scores and assessed whether and to what extent NBCCEDP clinical services were associated with clusters for the 5-year period, 2015-2019. We examined burden scores for spatial clustering using Local Indicators of Spatial Association (LISA) tests in GeoDA. We then used t-tests to compare the NBCCEDP 5-year average percentage of eligible women served clinical breast and cervical cancer services between hotspot (high burden) and coolspot clusters. There was statistically significant spatial clustering in the pattern of breast and cervical cancer burden scores across counties, with hotspot clusters mostly observed in the Southern region, Idaho and Nevada. For both breast and cervical cancer, higher percentages of eligible women received breast and cervical cancer clinical services in coolspot clusters compared to hotspot clusters during each year from 2015-2019. NBCCEDP clinical services can help reduce breast and cervical cancer burden. Yet, during 2015-2019, increased service delivery was not aligned with the spatial distribution of counties with greater breast and cervical cancer burdens. NBCCEDP recipients may improve their impact on breast and cervical cancer burden by prioritizing and consistently increasing service delivery in cancer burden hotspot clusters if they have not already maximized their resources in these areas.

Serum metabolism characteristics of patients with myocardial injury after noncardiac surgery explored by the untargeted metabolomics approach

BackgroundMyocardial injury after noncardiac surgery (MINS) is one of the most common complications associated with postoperative adverse cardiovascular outcomes and mortality. However, MINS often fails to be timely diagnosed due to the absence of clinical symptoms and limited diagnostic methods. The metabolomic analysis might be an efficient way to discover new biomarkers of MINS. Characterizing the metabolomic features of MINS patients may provide new insight into the diagnosis of MINS.MethodsIn this study, serum samples from 20 matched patients with or without MINS (n = 10 per group) were subjected to untargeted metabolomics analysis to investigate comprehensive metabolic information. Differential metabolites were identified, and the enriched metabolic pathway was determined based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.ResultsA comprehensive analysis revealed 124 distinct metabolites, predominantly encompassing lipids, amino acids and other compounds. The observed modifications in metabolic pathways in patients with or without MINS showed significant clustering in cholesterol metabolism, aldosterone synthesis and secretion, primary bile acid biosynthesis, as well as cysteine and methionine metabolism. Four specific metabolites (taurocholic acid, L-pyroglutamic acid, taurochenodeoxycholic acid, and pyridoxamine) exhibited promising potential as biomarkers for prognosticating MINS.ConclusionsThis study contributes valuable insights into the metabolomic features of MINS and the discovery of potential biomarkers which may help the early diagnosis of MINS. The identified metabolites and altered pathways offer valuable insights into the molecular underpinnings of MINS, paving the way for improved diagnostic approaches and potential intervention strategies.

Spatial distribution and determinants of unmet need for family planning among all reproductive‑age women in Uganda: a multi‑level logistic regression modeling approach and spatial analysis

IntroductionUnmet need for family planning is defined as the percentage of sexually active and fecund women who want to delay the next birth (birth spacing) or who want to stop childbirth (birth limiting) beyond two years but who are not using any modern or traditional method of contraception. Despite the provision of family planning services, the unmet need of family planning remains a challenge in low- and middle-income countries (LMICs). Thus, this study aimed to assess the spatial distribution and determinant factors of unmet need for family planning among all reproductive‑age women in Uganda.MethodsA secondary data analysis was done based on 2016 Ugandan Demographic and Health Surveys (UDHS). Total weighted samples of 18,506 women were included. Data processing and analysis were performed using SPSS Version 26, STATA 14.2, ArcGIS 10.8, and SaTScan 10.1.2 software. Spatial autocorrelation and hotspot analysis was made using Global Moran’s index (Moran’s I) and Gettis-OrdGi*statistics, respectively. Determinants of unmet needs for family planning were identified by multi-level logistic regression analysis. Variables with a p-value < 0.05 were declared statistically significant predictors.ResultsThe spatial distribution of unmet need for family planning among women of reproductive age in Uganda was found to be clustered (Global Moran’s I = 0.27, Z-score of 12.71, and p-value < 0.0001). In the multivariable multilevel logistic regression analysis; women in West Nile (AOR = 1.86, 95% CI: 1.39, 2.47), aged 25–49 years old (AOR = .84; 95% CI .72, .99), highly educated (AOR = .69; 95% CI .54, .88), Muslim (AOR = 1.20, 95% CI: 1.03, 1.39), high wealth status (AOR = .73, 95% CI: .64, .82), and had five or more living child (AOR = 1.69, 95% CI: 1.51, 1.88) were significant predictors of unmet need for family planning. Significant hotspot areas were identified in West Nile, Acholi, Teso, and Busoga regions.ConclusionA significant clustering of unmet need for family planning were found in Uganda. Moreover, age, educational status, religion, wealth status, number of alive children, and region were significant predictors of unmet need for family planning. Therefore, in order to minimize the burdens associated with unmet need, an interventions focusing on promotion of sexual and reproductive health service should be addressed to the identified hotspot areas.

Research trend on dyscalculia by bibliometric analysis during 2017-2022

&lt;span lang="EN-US"&gt;Dyscalculia is the inability to perform simple numerical calculations in everyday life. However, no one has researched this topic worldwide in about two years. This study aimed to investigate the research trends on dyscalculia through bibliometric studies and research issues related to dyscalculia in the Scopus database starting 2017 to October 2022. The sample consisted of 536 total documents. The results showed that scientific publications on dyscalculia fluctuated. In the next five years, its movements cannot be predicted. The highest number of document types is articles, which is 369. The number of cross-border documents from 2017 to 2022 is in the United States, as many as 75 papers, and in Italy, 74 copies. These two countries are more dominant on the topic of dyscalculia. Furthermore, 536 documents comprising 94.4% of articles were used in English. In general, in research on dyscalculia, researchers produce four out of five significant clusters: patient, approach, task, and grade. However, topics related to dyscalculia and mathematics often studied are deficit students, deficit addition and subtraction, mathematics difficulty, instruction, and primary school. The results can be used to shed light on developing tendencies in dyscalculia investigations and suggest directions for future studies.&lt;/span&gt;

ESG sustainable technologies literature review using cluster-based methods

Purpose- This study aims to address the existing gaps in the body of knowledge on sustainable technologies in the Environmental, Social, and Governance (ESG) field. It achieves this by employing a rigorous systematic review methodology and using VOSviewer and Biblioshiny software to analyze a comprehensive dataset of 1,603 papers from the ABS 2023 journal list, covering various knowledge domains. Methodology- This research undertakes a systematic analysis of the multifaceted ESG domain using a cluster-based approach rooted in bibliographic coupling analysis. This methodology reveals intricate network associations within distinct clusters of ESG literature. The study identifies four significant literature clusters: sustainable financial technology (FinTech), sustainable artificial intelligence (AI), sustainable big data, and sustainable cryptocurrency. Findings- The analysis conducted in this study reveals four distinct clusters of literature within the ESG field, shedding light on the interconnectedness of these areas. The identified clusters are sustainable financial technology (FinTech), sustainable artificial intelligence (AI), sustainable big data, and sustainable cryptocurrency. Each cluster represents a specific facet of ESG and provides valuable insights into its individual development and interrelationships. Conclusion- This research offers valuable insights into the state of knowledge in the ESG field, providing a well-structured understanding of the ESG landscape. It not only highlights the key clusters of literature but also offers a qualitative analysis, providing researchers with a roadmap for exploring research opportunities and specific areas within the ESG literature. By identifying these clusters and their relationships, this study contributes to the advancement of sustainable technologies within the ESG domain and sets the stage for future research in this evolving field. Keywords: ESG, sustainability, financial technology, artificial intelligence, big data, cryptocurrency, Cluster analysis. JEL Codes: G34, G38, G39

New perspectives on the genetic structure of dotted gizzard shad (Konosirus punctatus) based on RAD-seq

To maintain, develop and rationally utilize marine organisms, understanding their genetic structure and habitat adaptation pattern is necessary. Konosirus punctatus, which is a commercial fish species inhabiting the Indo-west Pacific Ocean, has shown an obvious annual global capture and aquaculture production decline due to climate changes and human activities. In the present study, restriction-site associated DNA sequencing (RAD-seq) was used to describe its genome-wide single nucleotide polymorphisms panel (SNPs). Among 146 individuals collected at nine locations scattered in China, Korea and Japan, a set of 632,090 SNPs were identified. Population genetic analysis showed that K. punctatus individuals were divided into two significant genetic clusters. Meanwhile, potential genetic differentiation between northern and southern population of K. punctatus was found. Treemix results indicated that gene flow existed among sampling locations of K. punctatus, especially from southern Japan to others. Moreover, candidate genes associated with habitat adaptations of K. punctatus were identified, which are involved in diverse physiological processes of K. punctatus including growth and development (e.g., KIDINS220, PAN3), substance metabolism (e.g., PGM5) and immune response (e.g., VAV3, CCT7, HSPA12B). Our findings may aid in understanding the possible mechanisms for the population genetic structure and local adaptation of K. punctatus, which is beneficial to establish the management and conservation units of K. punctatus, guiding the rational use of resources, with reference significance for a profound understanding of the adaptative mechanisms of other marine organisms to the environment.

Spatial analysis of the tumor immune microenvironment in papillary renal cell carcinoma.

471 Background: Spatial analysis of the tumor immune microenvironment (TIME) has yet to be explored in papillary renal cell carcinoma (pRCC). We utilized multiplex immunofluorescence (mIF) and spatial transcriptomics using spatial molecular imaging (SMI) to evaluate TIME properties in pRCC and contrasted these results with clear cell RCC (ccRCC). Methods: Tumor specimens were obtained from localized RCC tumors. mIF was performed on regions of interest (ROIs) selected from matched compartments from tumor, stroma, and tumor/stromal subsets of the interface. Two antibody panels were used for markers against T cells and B cells/macrophages. Marker abundance and clustering differences between pRCC and ccRCC were evaluated across ROIs. Select markers were also explored across pathologic tumor staging in pRCC. The SMI platform used for validation utilized probes against 959 transcripts. Cells were phenotyped using InSituType using the Kidney Cell Atlas as a reference. Cell clustering was quantified by univariate and bivariate Ripley’s K using the spatialTIME package in R. Results: mIF was performed on 1178 ROIs from 16 pRCC tumors and 70 ccRCC tumors. Compared to ccRCC, pRCC immune cell abundance was statistically lower amongst many T cell types and M2-like macrophages (Figure). M1-like macrophages were the only cell line seen at higher levels in interface compartments only. Increased macrophage clustering was observed in pRCC, including doubly positive M2-like macrophages in interface compartments (p=0.001 and 0.007). Higher abundance of CD8+ and FOXP3+ T cells in pRCC was associated with worse clinical stage, but no trend was seen with marker clustering. Four ROIs from 2 pRCC patients underwent SMI validation. On SMI of the tumor compartment, T cells were clustered with other T cells, B cells, and M1 macrophages. Conclusions: Compared to ccRCC, pRCC has fewer T cells and macrophages but more macrophage clustering. Using spatial transcriptomics, we found significant clustering between T cells, macrophages, and B cells in pRCC.

Cortical changes in the brain of patients with hemifacial spasm.

Hemifacial spasm (HFS) is a movement disorder characterized by involuntary muscle contractions on one side of the face. It is associated with disturbances in the brain's functional architecture. Despite this, the structural alterations in the brain related to HFS remain poorly understood. In this study, we investigated the cortical morphology changes in patients with HFS compared to healthy controls (HCs). We analyzed 3D T1-weighted MRI images from 33 patients with left-sided primary HFS and 33 age- and sex-matched HCs. Measurements of cortical thickness (CTh), sulcal depth, local gyrification index (lGI), and fractal dimension were taken using a computational anatomy toolbox. A general linear model, accounting for age, gender, and total brain volume, was applied for statistical analyses. Significant clusters were then assessed for correlations with clinical parameters. The HFS patients displayed several cortical abnormalities when compared to HCs, including reduced CTh in the contralateral precentral gyrus and left orbitofrontal cortex, decreased sulcal depth in the left orbitofrontal cortex, and increased lGI in the right insula and superior temporal cortex. However, fractal dimension did not differ significantly between the groups. Additionally, in HFS patients, a notable negative correlation was found between the sulcal depth in the left orbitofrontal cortex and the Beck Depression Inventory-II scores. Our findings reveal that HFS is associated with specific surface-based morphological changes in the brain. These alterations contribute to a deeper understanding of the neurophysiological mechanisms involved in HFS and may have implications for future research and treatment strategies.

Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and Biological Insight.

Human tear fluid contains numerous compounds, which are present in highly variable amounts owing to the dynamic and multipurpose functions of tears. A better understanding of the level and sources of variance is essential for determining the functions of the different tear components and the limitations of tear samples as a potential biomarker source. In this study, a quantitative proteomic method was used to analyze variations in the tear protein profiles of healthy volunteers. High day-to-day and inter-eye personal variances were observed in the tear volumes, protein content, and composition of the tear samples. Several normalization and outlier exclusion approaches were evaluated to decrease variances. Despite the intrapersonal variances, statistically significant differences and cluster analysis revealed that proteome profile and immunoglobulin composition of tear fluid present personal characteristics. Using correlation analysis, we could identify several correlating protein clusters, mainly related to the source of the proteins. Our study is the first attempt to achieve more insight into the biochemical background of human tears by statistical evaluation of the experimentally observed dynamic behavior of the tear proteome. As a pilot study for determination of personal protein profiles of the tear fluids of individual patients, it contributes to the application of this noninvasively collectible body fluid in personal medicine.

Functional antagonism and insights into the biosynthetic potential of human gut-derived microbes

The specialised small molecules encoded by commensal microbes mediate distinct functional interactions. However, there is a landscape of antagonistic interactions mediated by specialised strains and their small molecules. Herein, the antagonistic landscape within a collection of 330 human gut-derived commensal microbial strains was elucidated to evaluate antimicrobial interactions as a defensive contributor, and gain new insights into structure-related functions. The potential antagonistic gut-derived strains displayed strain-specific selective inhibition. This is in contrast to common antimicrobial drugs, which typically wipe out a broad range of species and are usually found in environmental microbes. Genome sequencing of representative gut strains revealed the presence of significant biosynthetic gene clusters (BGCs) encoding compound families that contribute to antagonistic activities, and are important in host defence and maintaining gut homeostasis. Subsets of these BGCs were abundant in metagenomic sequencing data from healthy individuals. Furthermore, the cell culture secretome of these strains revealed potential biomarkers linked to hallmark pathways. These microorganisms have biosynthetic novelty and are a source of biologically significant natural products. Such natural products are essential in the development of new antimicrobial agents to reduce the usage of broad-spectrum antibiotics and combat antimicrobial resistance.

Bibliometric Analysis and Predictors of Citations for Publications of a Higher Institution

Purpose: This study aims to depict the productivity and impact of publications affiliated with Jordan University of Science and Technology (JUST), and to identify bibliometric factors associated with the number of citations. Methods: Using keywords and identification numbers, Scopus and Web of Science were searched for all publications affiliated with JUST from 1987-2022. The retrieved data was imported, cleaned, visualized, and analyzed using stataIC 16, Excel 395 software, and VOSviewer software. The bibliometric analyses were conducted for types of publications, year of publications, type of journals, faculties, departments, faculty members, and most cited publications. Networking analyses were also conducted for international collaboration and keyword analysis using VOSviewer. Univariable and multivariable Poisson regression models were conducted to estimate the impact of several bibliometric factors on citation numbers. Results: A total of 16,830 publications were affiliated with JUST and published between 1986 and 2022. The total number of citations was 330,046. The average citation per publication was 19.6 and the institutional h-index was 165. Most publications were original articles (81.8%) and 71.7% were published in traditional (non-open) journals. Publication and citation numbers increased steadily, until 2013, and then exponentially, afterward. ? The Faculty of Engineering had the highest number of total publications (4,593), while the Faculty of Medicine had the highest number of total citations (148,384). Professor Yousef S. Khader ranks first as JUST's influential faculty? with 640 publications and 110,777 citations. Factors contributing to higher incidence rate for citations include years since publication, indexing in Scopus and WoS, reviews, publication in open-access journals, and collaboration. Network analysis revealed significant clusters of authors and keywords, with strong connections to the United States and Saudi Arabia. Conclusion: The productivity nd impact of JUST publications have improved annually for all faculties and departments. ?However, this improvement seems to be limited and can be explained by several factors. Further improvements in research productivity and impact are needed by implementing relevant strategies such as collaboration and interdisciplinary research, publishing in high-impact journals, considering open-access publishing, considering the potential societal impact of research, increasing visibility and reputation through appropriate affiliations, publishing review articles, and monitoring research output over time.

The corticofugal oscillatory modulation of the cochlear receptor during auditory and visual attention is preserved in tinnitus.

The mechanisms underlying tinnitus perception are still under research. One of the proposed hypotheses involves an alteration in top-down processing of auditory activity. Low-frequency oscillations in the delta and theta bands have been recently described in brain and cochlear infrasonic signals during selective attention paradigms in normal hearing controls. Here, we propose that the top-down oscillatory activity observed in brain and cochlear signals during auditory and visual selective attention in normal subjects, is altered in tinnitus patients, reflecting an abnormal functioning of the corticofugal pathways that connect brain circuits with the cochlear receptor. To test this hypothesis, we used a behavioral task that alternates between auditory and visual top-down attention while we simultaneously measured electroencephalogram (EEG) and distortion-product otoacoustic emissions (DPOAE) signals in 14 tinnitus and 14 control subjects. We found oscillatory activity in the delta and theta bands in cortical and cochlear channels in control and tinnitus patients. There were significant decreases in the DPOAE oscillatory amplitude during the visual attention period as compared to the auditory attention period in tinnitus and control groups. We did not find significant differences when using a between-subjects statistical approach comparing tinnitus and control groups. On the other hand, we found a significant cluster in the delta band in tinnitus when using within-group statistics to compare the difference between auditory and visual DPOAE oscillatory power. These results confirm the presence of top-down infrasonic low-frequency cochlear oscillatory activity in the delta and theta bands in tinnitus patients, showing that the corticofugal suppression of cochlear oscillations during visual and auditory attention in tinnitus patients is preserved.

Characterization and structural study of a novel β-N-acetylgalactosaminidase from Niabella aurantiaca.

We report here the identification, characterization and three-dimensional (3D) structure determination of NaNga, a newly identified β-N-acetylgalactosaminidase from the Gram-negative soil bacterium Niabella aurantiaca DSM 17617. Whenrecombinantly expressed in Escherichia coli, the enzyme selectively cleaved 4-nitrophenyl-N-acetyl-β-d-galactosamine (pNP-β-d-GalpNAc). The X-ray crystal structure of the protein was refined to 2.5 Å and consists of an N-terminal β-sandwich domain and a (β/α)8 barrel catalytic domain. Despite a mere 22% sequence identity, the 3D structure of NaNga is similar to those previously determined for family GH123 members, suggesting it also employs the same substrate-assisted catalytic mechanism. Inhibition by N-acetyl-galactosamine thiazoline (GalNAc-thiazoline) supports the suggested mechanism. A phylogenetic analysis of its proximal sequence space shows significant clustering ofunknown sequences around NaNga with sufficient divergence with previously identified GH123 members to subdivide this family into distinctsubfamilies. Although the actual biological substrate of our enzyme remains unknown, examination of the active site pocket suggests that it may bea β-N-acetylgalactosaminide substituted by a monosaccharide at O-3. Analysis of the genomic context suggests, in turn, that this substituted β-N-acetylgalactosaminide may be appended to a d-arabinan from an environmental Actinomycete.

Research on the fine-scale spatial-temporal evolution characteristics of carbon emissions based on nighttime light data: A case study of Xi'an city

Carbon emissions have resulted in severe ecological damage, jeopardizing the very existence of humanity. In China, carbon emissions from urban areas contribute to 80% of the total carbon emissions, this significant contribution underscores the importance of addressing urban emissions. To gain insights into the spatial patterns of carbon emissions in urban areas at the fine-scale regional level, this study utilizes Xi'an as a case study, constructs a fine-scale regional carbon emission estimation model based on energy consumption and NPP-VIIRS-like NTL data, and quantifies multiscale carbon emissions from 2000 to 2021. Furthermore, global spatial autocorrelation, cold and hot spot analysis, and standard deviation ellipse analysis were used to investigate the spatial characteristics of carbon emissions at the street (township) level in Xi'an. This study revealed a sixfold increase in carbon emissions in Xi'an, rising from 51.35 million tons in 2000 to 281.95 million tons in 2021.The area affected by carbon emissions has expanded, with the centre of gravity of emission consistently shifting towards the south. The average street-level carbon emission density fluctuated and doubled compared to that in 2000. The total number of streets with low-carbon-emission-density decreased by 23%, indicating a shift away from low-carbon-emission-density streets. Furthermore, the global Moran's I index consistently remained within the range of 0.85–0.95, indicating significant spatial clustering, with cold spots expanding into surrounding districts and counties. Additionally, this study accurately identified carbon emissions within the city, offering the potential for the development of more precise carbon reduction strategies. Moreover, this approach can provide valuable support for the dynamic monitoring of carbon emissions in developing cities worldwide.

Impacts of compounding drought and heatwave events on child mental health: insights from a spatial clustering analysis

BackgroundConcurrent heatwave and drought events may have larger health impacts than each event separately; however, no US-based studies have examined differential mental health impacts of compound drought and heatwave events in pediatric populations.ObjectiveTo examine the spatial patterns of mood disorders and suicide-related emergency department (ED) visits in children during heatwave, drought, and compound heatwave and drought events. We tested whether the occurrence of compound heatwave and drought events have a synergistic (multiplicative) effect on the risk of mental health related outcomes in children as compared to the additive effect of each individual climate hazard. Lastly, we identified household and community-level determinants of geographic variability of high psychiatric burden.MethodsDaily counts of psychiatric ED visits in North Carolina from 2016 to 2019 (May to Sept) for pediatric populations were aggregated at the county scale. Bernoulli cluster analyses identified high-risk spatial clusters of psychiatric morbidity during heatwave, drought, or compound heatwave and drought periods. Multivariate adaptive regression models examined the individual importance of household and community-level determinants in predicting high-risk clustering of mood disorders or suicidality across the three climate threats.ResultsResults showed significant spatial clustering of suicide and mood disorder risks in children during heatwave, drought, and compound event periods. Periods of drought were associated with the highest likelihood of spatial clustering for suicide and mood disorders, where the risk of an ED visit was 4.48 and 6.32 times higher, respectively, compared to non-drought periods. Compounding events were associated with a threefold increase in both suicide and mood disorder-related ED visits. Community and household vulnerability factors that most contributed to spatial clustering varied across climate hazards, but consistent determinants included residential segregation, green space availability, low English proficiency, overcrowding, no broadband access, no vehicle access, housing vacancy, and availability of housing units.ConclusionFindings advance understanding on the locations of vulnerable pediatric populations who are disproportionately exposed to compounding climate stressors and identify community resilience factors to target in public health adaptation strategies.