Quantitative Database Research Articles

Sci-ModoM: a quantitative database of transcriptome-wide high-throughput RNA modification sites.

We present Sci-ModoM, the first next-generation RNome database offering a holistic view of the epitranscriptomic landscape. Sci-ModoM has a simple yet powerful interface, underpinned by FAIR data principles, a standardized nomenclature, and interoperable formats, fostering the use of common standards within the epitranscriptomics community. Sci-ModoM provides quantitative measurements per site and dataset, enabling users to assess confidence levels based on score, coverage, and stoichiometry. Data in Sci-ModoM is directly traceable to its sources. Users can Search and Compare over six million modifications across 156 datasets, Browse or download datasets, and retrieve metadata. A comparison tool offers a novel and unique opportunity to compare modifications site-wise across datasets, with the ability to securely upload and compare user data against latest published research. Sci-ModoM empowers researchers, including non-experts, to access a broad spectrum of recent quantitative RNA modification data, thereby enhancing the utility and impact of latest discoveries, and opening new avenues in biological and medical research.

Causal relationship between key genes and metabolic dysfunction-associated fatty liver disease risk mediated by immune cells: A Mendelian randomization and mediation analysis.

Non-invasive diagnostics for metabolic dysfunction-associated fatty liver disease (MAFLD) remain challenging. We aimed to identify novel key genes as non-invasive biomarkers for MAFLD, elucidate causal relationships between biomarkers and MAFLD and determine the role of immune cells as potential mediators. Utilizing published transcriptome data of patients with biopsy-proven MAFLD, we applied linear models for microarray data, least absolute shrinkage and selector operation (LASSO) regressions and receiver operating characteristic (ROC) curve analyses to identify and validate biomarkers for MAFLD. Using the expression quantitative trait loci database and a cohort of 778 614 Europeans, we used Mendelian randomization to analyse the causal relationships between key biomarkers and MAFLD. Additionally, mediation analysis was performed to examine the involvement of 731 immunophenotypes in these relationships. We identified 31 differentially expressed genes, and LASSO regression showed three hub genes, IGFBP2, PEG10, and P4HA1, with area under the receiver operating characteristic (AUROC) curve of 0.807, 0.772 and 0.791, respectively, for identifying MAFLD. The model of these three genes had an AUROC of 0.959 and 0.800 in the development and validation data sets, respectively. This model was also validated using serum-based enzyme-linked immunosorbent assay data from MAFLD patients and control subjects (AUROC: 0.819, 95% confidence interval: 0.736-0.902). PEG10 was associated with an increased MAFLD risk (odds ratio = 1.106, p = 0.032) via inverse variance-weighted analysis, and about 30% of this risk was mediated by the percentage of CD11c + CD62L- monocytes. The MAFLD panels have good diagnostic accuracy, and the causal link between PEG10 and MAFLD was mediated by the percentage of CD11c + CD62L- monocytes.

Continuous briefing for the future university campus: an evidence-based approach to match spatial supply and demand

PurposeTo plan the future university campus, campus executives need decision-making support from theory and practice. Matching the static campus (supply) with the dynamic (demand) - while safeguarding spatial quality and sustainability - requires management information from similar organizations. This study presents an evidence-based briefing approach to support decision-makers of individual universities with management information when making decisions for their future campus.Design/methodology/approachFor the proposed evidence-based briefing approach, the continuous Designing an Accommodation Strategy (DAS) framework is used in a mixed-method research design to evaluate the past to plan for the future. Five campus themes and three campus models (solid, liquid, and gas) are introduced to describe the development and diversification of university campuses and their impact across different university building types. Based on this theoretical framework, first, qualitative interview data are analyzed to understand which standards campus managers expect; second, a quantitative project database is used to demonstrate what is actually realized.FindingsThe findings demonstrate that remote working and online education will become more common. Academic workplaces and learning environments are more adaptive to changes than laboratory spaces. The analyses reveal different effective space use strategies to meet the current demand: they include space-efficient mixed-use buildings, and mono-functional generic educational and office spaces. These results show that operationalized evidence-based briefing can help design the future campus.Originality/valueThe study adds knowledge during a critical (post-COVID) period when decision-makers need evidence from others to adapt their campus management strategies to hybrid and sustainable ambitions.

A proteome-wide quantitative platform for nanoscale spatially resolved extraction of membrane proteins into native nanodiscs.

The intricate molecular environment of the native membrane profoundly influences every aspect of membrane protein (MP) biology. Despite this, the most prevalent method of studying MPs uses detergent-like molecules that disrupt and remove this vital local membrane context. This severely impedes our ability to quantitatively decipher the local molecular context and comprehend its regulatory role in the structure, function, and biogenesis of MPs. Using a library of membrane-active polymers we have developed a platform for the high-throughput analysis of the membrane proteome. The platform enables near-complete spatially resolved extraction of target MPs directly from their endogenous membranes into native nanodiscs that maintain the local membrane context. We accompany this advancement with an open-access database that quantifies the polymer-specific extraction variability for 2065 unique mammalian MPs and provides the most optimized condition for each of them. Our method enables rapid and near-complete extraction and purification of target MPs directly from their endogenous organellar membranes at physiological expression levels while maintaining the nanoscale local membrane environment. Going beyond the plasma membrane proteome, our platform enables extraction from any target organellar membrane including the endoplasmic reticulum, mitochondria, lysosome, Golgi, and even transient organelles such as the autophagosome. To further validate this platform, we took several independent MPs and demonstrated how our resource can enable rapid extraction and purification of target MPs from different organellar membranes with high efficiency and purity. Further, taking two synaptic vesicle MPs, we show how the database can be extended to capture multiprotein complexes between overexpressed MPs. We expect these publicly available resources to empower researchers across disciplines to efficiently capture membrane 'nano-scoops' containing a target MP and interface with structural, functional, and other bioanalytical approaches. We demonstrate an example of this by combining our extraction platform with single-molecule TIRF imaging to demonstrate how it can enable rapid determination of homo-oligomeric states of target MPs in native cell membranes.

Predict progression free survival and overall survival using objective response rate for anti—PD1/PDL1 therapy development

In oncology anti—PD1 / PDL1 therapy development for solid tumors, objective response rate (ORR) is commonly used clinical endpoint for early phase study decision making, while progression free survival (PFS) and overall survival (OS) are widely used for late phase study decision making. Developing predictive models to late phase outcomes such as median PFS (mPFS) and median OS (mOS) based on early phase clinical outcome ORR could inform late phase study design optimization and probability of success (POS) evaluation. In existing literature, there are ORR / mPFS / mOS association and surrogacy investigations with limited number of included clinical trials. In this paper, without establishing surrogacy, we attempt to predict late phase survival (mPFS and mOS) based on early efficacy ORR and optimize late phase trial design for anti—PD1 / PDL1 therapy development. In order to include adequate number of eligible clinical trials, we built a comprehensive quantitative clinical trial landscape database (QLD) by combining information from different sources such as clinicaltrial.gov, publications, company press releases for relevant indications and therapies. We developed a generalizable algorithm to systematically extract structured data for scientific accuracy and completeness. Finally, more than 150 late phase clinical trials were identified for ORR / mPFS (ORR / mOS) predictive model development while existing literature included at most 50 trials. A tree-based machine learning regression model has been derived to account for ORR / mPFS (ORR / mOS) relationship heterogeneity across tumor type, stage, line of therapy, treatment class and borrow strength simultaneously when homogeneity persists. The proposed method ensures that the predictive model is robust and have explicit structure for clinical interpretation. Through cross validation, the average predictive mean square error of the proposed model is competitive to random forest and extreme gradient boosting methods and outperforms commonly used additive or interaction linear regression models. An example application of the proposed ORR / mPFS (ORR / mOS) predictive model on late phase trial POS evaluation for anti—PD1 / PDL1 combination therapy was illustrated.

Cell-intrinsic platinum response and associated genetic and gene expression signatures in ovarian cancer cell lines and isogenic models.

Ovarian cancers are still largely treated with platinum-based chemotherapy as the standard of care, yet few biomarkers of clinical response have had an impact on clinical decision making as of yet. Two particular challenges faced in mechanistically deciphering platinum responsiveness in ovarian cancer have been the suitability of cell line models for ovarian cancer subtypes and the availability of information on comparatively how sensitive ovarian cancer cell lines are to platinum. We performed one of the most comprehensive profiles to date on 36 ovarian cancer cell lines across over seven subtypes and integrated drug response and multiomic data to improve on our understanding of the best cell line models for platinum responsiveness in ovarian cancer. RNA-seq analysis of the 36 cell lines in a single batch experiment largely conforms with the currently accepted subtyping of ovarian cancers, further supporting other studies that have reclassified cell lines and demonstrate that commonly used cell lines are poor models of high-grade serous ovarian carcinoma. We performed drug dose response assays in the 32 of these cell lines for cisplatin and carboplatin, providing a quantitative database of IC 50 s for these drugs. Our results demonstrate that cell lines largely fall either well above or below the equivalent dose of the clinical maximally achievable dose (C max ) of each compound, allowing designation of cell lines as sensitive or resistant. We performed differential expression analysis for high-grade serous ovarian carcinoma cell lines to identify gene expression correlating with platinum-response. Further, we generated two platinum-resistant derivatives each for OVCAR3 and OVCAR4, as well as leveraged clinically-resistant PEO1/PEO4/PEO6 and PEA1/PEA2 isogenic models to perform differential expression analysis for seven total isogenic pairs of platinum resistant cell lines. While gene expression changes overall were heterogeneous and vast, common themes were innate immunity/STAT activation, epithelial to mesenchymal transition and stemness, and platinum influx/efflux regulators. In addition to gene expression analyses, we performed copy number signature analysis and orthogonal measures of homologous recombination deficiency (HRD) scar scores and copy number burden, which is the first report to our knowledge applying field-standard copy number signatures to ovarian cancer cell lines. We also examined markers and functional readouts of stemness that revealed that cell lines are poor models for examination of stemness contributions to platinum resistance, likely pointing to the fact that this is a transient state. Overall this study serves as a resource to determine the best cell lines to utilize for ovarian cancer research on certain subtypes and platinum response studies, as well as sparks new hypotheses for future study in ovarian cancer.

Identification of candidate genes associated with growth and development of sheep from a crossbred population using genome-wide association studies

The article presents the results of a search for genome-wide associations with phenotypic traits characterizing the growth and development of sheep from a crossbred population obtained from crossing Romanov sheep and F1 hybrid rams (Romanov sheep x Katahdin). The phenotype database included ten body measurements (withers height, sacral height, back height, chest depth, chest width, ischial tuberosity width, body length, oblique body length, chest girth, pastern girth) recorded at the age of 6 days, 3, 6 and 9 months. Genotyping of sheep was carried out using high-density DNA chips containing about 600,000 SNP markers. Genome-wide association studies (GWAS) were performed using regression analysis in the STATISTICA 10 program. The search for candidate genes localized in the SNP region was performed using Ensembl genome browser 110. There was carried out an analysis of the matches of the identified SNPs with known quantitative trait loci (QTLs) described in the Sheep Quantitative Trait Locus Database. There were found SNPs that were significantly associated with the studied phenotypic traits overlapped with the QTLs, among which the most common categories were “Body weight (slaughter)”, “Muscle weight in carcass”, “Body weight (live)” and “Bone weight in carcass”. There has been established that SNPs significantly associated with exterior traits were localized within or in the immediate vicinity of 64 genes. There were found potential candidates regulating the growth of muscle (FOXO3, PRKAG3, MYOZ2, and ANKRD1) and cartilage tissues FGF12) and involved in metabolic processes, which were critical for the growth of lambs (CLDN, ALB, and MRC1). Along with the known in sheep functional candidates (CAST and SCD5) , there were identified genes that were not previously described in sheep, but regulated growth and development processes in other livestock species including genes RAB28, PRKAG3 and FOXO3. The identified SNPs can be recommended for inclusion in marker-guided selection programs in sheep breeding.

Determining the Relationships Between Genotype and Phenotype Using Molecular Genetic Tools in Chickens

Context: Chicken meat is one of the rich sources of protein and is considered one of the most commonly consumed meats in the world. Enhancing poultry production and its products is achievable through chicken breeding. Effective breeding projects for future genetic improvement require an understanding of the genetic potential of a given population. Evidence Acquisition: Articles were selected based on novel molecular markers related to economic traits of chicken in Animal quantitative trait loci (QTL) database, Ensemble genome browser, CorrDB, ChickVD, Galbase, and Google Scholar. These databases contain QTLs, markers, and reference genomes of chicken. Galbase provides research communities with updated possibilities to conduct thorough functional genomics research on chickens. ChickVD manages high-quality sequence variation data, variation analysis in relation to chicken genes, cDNAs, genetic markers, and QTLs. CorrDB compiles all available chicken genetic and phenotypic trait correlation data to aid in the analysis of genetic networks and facilitate systems biology research. Animal Quantitative Trait Loci Database (Animal QTLdb) gathers and compiles all existing data on trait mapping, including QTL (phenotype/expression, eQTL), candidate gene, association data (GWAS), and copy number variations (CNV) for livestock animal genomes. This comprehensive database facilitates the easier identification and comparison of discoveries within and across species. Ensemble genome browser is a powerful tool for analyzing vertebrate genomes, offering valuable insights into comparative genomics, evolutionary processes, sequence variations, and transcriptional regulation. Results: Valuating the relatedness of the studied broilers and layers is important for maintaining and improving the genetic reserves of the same population. Candidate genes (CGs) are used to determine genes related to economic traits in chickens. Molecular genetic techniques such as whole-genome re-sequencing (WGRS) can identify single nucleotide polymorphisms (SNPs), insertion/deletion polymorphisms (indels), structural variations (SV), CNV, and simple sequence repeats (SSRs) and their chromosomal regions in terms of QTL. Recently, the pan-genome (PG) has become one of the most important tools to study genome variation and changes in important traits. The use of molecular markers and CGs can aid in evaluating the genetic relationships between phenotype and genotype of broilers and layers. Conclusions: This review introduces molecular genetic methods and new approaches to identify novel genes related to important biological pathways and significant production and reproductive traits.

Quality of Life and Treatment Modalities in Patients with Interstitial Cystitis: The Patients' Perspective.

Quality of life (QoL)-based outcomes are hardly incorporated into interstitial cystitis/bladder pain syndrome (IC/BPS) guidelines, because studies are limited and outdated. Therefore, guidelines might not reflect the current clinical situation accurately. Secondly, guidelines suggest using a multimodal approach for BPS/IC management, but data on the patient-perceived efficacy of these therapies are limited. The aim of this study is to investigate the perception of IC/BPS patients of their QoL, to determine which treatments they have received, and to examine how they evaluate the efficacy of these various (alternative) therapies. A quantitative retrospective database evaluation was performed, with data from an existing IC/BPS patient survey (n = 217) that was conducted in 2021. This survey contained QoL data based on validated questionnaires such as EQ-5D 5L. The QoL of patients is affected significantly by IC/BPS. This is evident from the various affected domains on the EQ-5D 5L. The symptom severity was negatively affected by a delay in diagnosis, and there were clear differences in QoL domains between females and males. Secondly, coagulation therapy and intravesical glycosaminoglycan (GAG) therapy were most appreciated by patients. Other (alternative) treatments were commonly utilized, although some had doubtful results and high discontinuation rates. QoL is considerably impaired in IC/BPS patients. The diverse responses and adherence to various treatments warrant a personalized approach (phenotype-oriented therapy). To achieve QoL improvement, it is important to incorporate the patient's perspective in treatment guidelines.

Exome-Wide Sequencing Study Identified Genetic Variants Associated With Sarcopenic Obesity.

Sarcopenic obesity (SO) is an age-related disease characterized by the coexistence of excessive adiposity and low muscle mass or function. Although obesity and sarcopenia are heritable conditions, the genetic determinants of SO have not been fully understood. We conducted a large-scale exome-wide association analysis of SO in a sequenced sample of 2887 cases and 113284 controls and an imputed sample of 4003 cases and 161990 controls in the UK Biobank cohort. Single-variant association analysis identified one locus 1q41 (lead SNP rs1417066, LYPLAL1-AS1, odds ratio [OR] = 1.15, 95% confidence interval [CI] = [1.11-1.19], p = 1.75 × 10-14) that was significantly associated with SO at the exome-wide significance level (p < 1 × 10-8). Colocalization analysis in the Genotype-Tissue Expression expression quantitative trait locus database showed that LYPLAL1-AS1 was colocalized with SO in multiple musculoskeletal-related tissues. Gene-based burden test of rare loss-of-function variants identified 5 genes at the gene-wise significance level (p < 4.3 × 10-6): PDE3B (OR = 2.48, p = 1.10 × 10-6), MYOZ3 (OR = 25.49, p = 1.41 × 10-7), SLC15A3 (OR = 4.75, p = 6.82 × 10-7), RNF130 (OR = 25.83, p = 4.07 × 10-6), and TNK2 (OR = 4.25, p = 8.75 × 10-8). Overall, our study uncovered the genetic effects of both common and rare variants on SO susceptibility, expanded existing knowledge of the genetic architecture of SO, and improved understanding of the genetic mechanisms underlying SO.

Associations of MMP9 polymorphism with the risk of severe pneumonia in a Southern Chinese children population

BackgroundSevere pneumonia frequently causes irreversible sequelae and represents a major health burden for children under the age of 5. Matrix Metallopeptidase 9 (MMP9) is a zinc-dependent endopeptidase that is involved in various cellular processes. The correlation between MMP9 and the risk of severe childhood pneumonia remains unclear.MethodsHere we assemble a case–control cohort to study the association of genetic variants in MMP9 gene with severe childhood pneumonia susceptibility in a Southern Chinese population (1034 cases and 8426 controls).ResultsOur results indicate that the allele G in rs3918262 SNP was significantly associated with an increased risk of severe pneumonia. Bioinformatic analyses by expression quantitative trait loci (eQTL), RegulomeDB and FORGEdb database analysis showed that rs3918262 SNP has potential regulatory effect on translational efficiency and protein level of MMP9 gene. Furthermore, MMP9 concentrations were significantly up-regulated in the bronchoalveolar lavages (BALs) of children with severe pneumonia.ConclusionIn summary, our findings suggest that MMP9 is a novel predisposing gene for childhood pneumonia.

Monitoring of Labor Protests: Results and Directions of Analysis

The article describes the methodology and analytical capabilities of the “Monitoring of labor protests in Russia”. The information base is Internet messages about labor protests, which contain the necessary information and are first entered into a textual and then into a quantitative database. The monitoring has been functioning for 15 years and has accumulated information about 4.5 thousand protests. The structure of the Monitoring is briefly described, the main concepts and variables that allow analyzing the protest movement in several directions at once.The first direction is linear data analysis, which allows obtaining the most general data on the number of protests and their most important characteristics. Another direction is the calculation of indices, which make it possible to obtain comparable and relative indicators, which make it possible to overcome the heterogeneity of the compared objects.Another important type of analysis is the long-term dynamics of protests based on the identification of trends and the development of criteria for its assessment: determining the turning points of trends from growth to decline and vice versa, as well as the intensity of trends at each stage.An actor-transactional analysis launched in 2016, which determines the number of actors involved in labor protests (35 types of actors are identified) and types of interactions (transactions) between them, both outgoing (actor activity) and incoming (actor authority). Based on these indicators, the index of significance of each actor is calculated, which is monitored in dynamics. This makes it possible to understand the role institutional and non-institutional actors play in the settlement of protests.

A machine-learning based approach to predict facies associations and improve local and regional stratigraphic correlations

The geological record has challenged stratigraphers through time. Many depositional, tectonic and paleobiological events require stratigraphic positioning to determine temporal relationships among such events. This task is complicated and challenging, especially in sedimentary succession with scarcity or lack of paleontological content bearing biostratigraphic value and radiometric ages. Therefore, subjective personal criteria adopted during correlations and field mapping activities make stratigraphic correlations more complex and confusing. New methodological approaches are necessary to test human expertise in recognizing stratigraphic units with environmental significance and to contribute to stratigraphic correlations based on quantitative data. We used cores obtained by coal drilling campaigns during the 1970s and 1980s on the southern border of the Paraná Basin, southern Brazil, to generate a quantitative database. Data obtained from gamma spectrometry in the cores of Carboniferous to Permian age measured total count (cps), potassium (K), uranium (U) and thorium (Th). We used machine learning (ML) to predict facies associations and to confront the quantitative database with the three facies associations mapped through time based on qualitative geological mapping criteria. The k-nearest neighbors (KNN) algorithm reached maximum accuracy values of 86.0%% and f1-score of 90.0%, 73.0% and 91.0% for facies associations 1, 2 and 3, respectively, using exponential moving average and normalized data. This KNN-based method using gamma spectrometric data opened new possibilities to perform local and regional stratigraphic correlations using quantified data. New tests must be performed to improve this promising correlation method in other regional settings and related basins.

Characterization of cranial growth patterns using craniometric parameters and best-fit logarithmic growth curves

Few studies have reported a complete quantitative database of cranial growth, from infancy to adulthood, as a reference through three-dimensional analysis. Our study aimed to characterize cranial growth patterns using craniometric parameters by establishing sex- and age-specific norms.In total, 1009 Korean patients (male-to-female ratio, 2:1; age range, 0–18 years) who underwent thin-slice computed tomography (CT) scans for head trauma were divided into 20 age groups, with a 6-month interval for those under 2 years and a 1-year interval for those over 2 years. After four reference planes [Frankfurt horizontal (FH), midsagittal, and two coronal planes passing the sella (S) and basion (B)] had been established, intracranial volume (ICV), anteroposterior diameter (APD), biparietal diameter (BPD), cranial heights (CHs), cephalic index (CI, BPD/APD), and height index (HI, CH–B/APD) were measured using Mimics software. Best-fit logarithmic curves were derived using a linear regression model.The best-fit curves for ICV (cm3) were y = 785.6 + 157*ln(age) for males (R2 = 0.5752) and y = 702 + 150.5*ln(age) for females (R2 = 0.6517). After adjustment for age, males had higher values of ICV, APD, BPD, and CHs than females (all p < 0.0001). ICV, APD, BPD, and CHs demonstrated a rapid increase during the first few months of life, reaching 90–95% of the adult size by 5–6 years of age, while CI and HI showed a continuous decline by 4%, regardless of sex.This study presented cranial growth references for more than 1000 of the Korean population aged up to 18 years. This might help to provide guidelines for diagnosis and treatment (including timing, amount, and direction) for cranial reconstruction in pediatric patients with craniosynostosis.

Mining Top-k High Average-Utility Sequential Patterns for Resource Transformation

High-utility sequential pattern mining (HUSPM) helps researchers find all subsequences that have high utility in a quantitative sequential database. The HUSPM approach appears to be well suited for resource transformation in DIKWP graphs. However, all the extensions of a high-utility sequential pattern (HUSP) also have a high utility that increases with its length. Therefore, it is difficult to obtain diverse patterns of resources. The patterns that consist of many low-utility items can also be a HUSP. In practice, such a long pattern is difficult to analyze. In addition, the low-utility items do not always reflect the interestingness of association rules. High average-utility pattern mining is considered a solution to extract more significant patterns by considering the lengths of patterns. In this paper, we formulate the problem of top-k high average-utility sequential pattern mining (HAUSPM) and propose a novel algorithm for resource transformation. We adopt a projection mechanism to improve efficiency. We also adopt the sequence average-utility-raising strategy to increase thresholds. We design the prefix extension average utility and the reduced sequence average utility by incorporating the average utility into the utility upper bounds. The results of our comparative experiments demonstrate that the proposed algorithm can achieve sufficiently good performance.

Transcriptome analysis of the Bactrian camel (Camelus bactrianus) reveals candidate genes affecting milk production traits

BackgroundMilk production traits are complex traits with vital economic importance in the camel industry. However, the genetic mechanisms regulating milk production traits in camels remain poorly understood. Therefore, we aimed to identify candidate genes and metabolic pathways that affect milk production traits in Bactrian camels.MethodsWe classified camels (fourth parity) as low- or high-yield, examined pregnant camels using B-mode ultrasonography, observed the microscopic changes in the mammary gland using hematoxylin and eosin (HE) staining, and used RNA sequencing to identify differentially expressed genes (DEGs) and pathways.ResultsThe average standard milk yield over the 300 days during parity was recorded as 470.18 ± 9.75 and 978.34 ± 3.80 kg in low- and high-performance camels, respectively. Nine female Junggar Bactrian camels were subjected to transcriptome sequencing, and 609 and 393 DEGs were identified in the low-yield vs. high-yield (WDL vs. WGH) and pregnancy versus colostrum period (RSQ vs. CRQ) comparison groups, respectively. The DEGs were compared with genes associated with milk production traits in the Animal Quantitative Trait Loci database and in Alashan Bactrian camels, and 65 and 46 overlapping candidate genes were obtained, respectively. Functional enrichment and protein–protein interaction network analyses of the DEGs and candidate genes were conducted. After comparing our results with those of other livestock studies, we identified 16 signaling pathways and 27 core candidate genes associated with maternal parturition, estrogen regulation, initiation of lactation, and milk production traits. The pathways suggest that emerged milk production involves the regulation of multiple complex metabolic and cellular developmental processes in camels. Finally, the RNA sequencing results were validated using quantitative real-time PCR; the 15 selected genes exhibited consistent expression changes.ConclusionsThis study identified DEGs and metabolic pathways affecting maternal parturition and milk production traits. The results provides a theoretical foundation for further research on the molecular mechanism of genes related to milk production traits in camels. Furthermore, these findings will help improve breeding strategies to achieve the desired milk yield in camels.Graphical

The Burden of Urinary Tract Infections on Quality of Life and Healthcare in Patients with Interstitial Cystitis.

Interstitial cystitis/bladder pain syndrome (IC/BPS) patients are more susceptible to urinary tract infections (UTIs), likely worsening pre-existing symptoms. However, this receives limited attention in guidelines. This study aimed to explore the burden of UTIs on IC/BPS patients' quality of life and their healthcare. Two quantitative retrospective database studies were conducted in cystoscopically proven IC/BPS patients: one compiled existing patient survey data (n = 217) from July 2021 to examine physical and emotional UTI burden, and the other used a patient file database (n = 100) from January 2020 to May 2022, focusing on UTI prevalence, healthcare use, urine cultures and antibiotic resistance. A delay in diagnosis was seen in 70% of patients, due to doctors confusing IC/BPS symptoms with UTIs. The UTI prevalence was over 50%; these patients also report anxiety for new UTIs (70%) and worsening of IC/BPS symptoms (60%). Additionally, for UTI+ patients, healthcare consumption was significantly increased in both studies. Antibiotic resistance (80% of cultures) and prophylactic antibiotic use were common. These findings highlight the burden of UTIs on quality of life in IC/BPS patients and the healthcare system. These results emphasize the need for improved UTI guidelines concerning diagnosis, management and prevention for IC/BPS patients to improve quality of life and care.

Atolls of the world: A reappraisal from an optical remote sensing and global mapping perspective

The Millennium Coral Reef Mapping Project (MCRMP) aimed to map coral reefs worldwide at geomorphological thematic scales using Landsat satellite images at 30 m spatial resolution. The 5-level hierarchical classification scheme implemented by MCRMP identified at Level 2 ‘Atolls’ as one of the main types of coral reef complexes. In this review, the qualitative criteria used by MCRMP to identify atolls are presented. Then, we report on the global census of atolls, from which a consistent geomorphologic GIS database is provided. A total of 598 atolls are identified and mapped. The quantitative database provides surface areas for all geomorphologic units at Level 4 and 5 of the MCRMP classification scheme. It allows further work on atoll and coral reef classifications, regionally and globally, in order to identify geomorphic trends and outliers. It is also a convenient database to use in multivariate analyses with ancillary biodiversity, fishery, socio-economic or climate data.

Where Do Social Support and Epistemic Centrality Come From? The Case of Innovators in the French Biotech Industry

The link between entrepreneur’s network centrality and innovation performance has been broadly studied in knowledge-intensive industries such as biotechnology. However, little research has been focused on the social mechanisms that allow innovators to reach such a central position. We contribute to the existing literature by exploring the factors that may lead or prevent entrepreneurs from reaching a central position in their professional networks of knowledge exchange and social support in French biotech milieu. We use a unique quantitative and qualitative database of 138 and 126 biotech entrepreneurs observed, respectively, in 2008 and 2013. When accounting for entrepreneurs’ position in the social (friendship) and knowledge (advice) domain, we draw on three dimensions through which entrepreneurs build their position: their professional experience, their inter-organizational (or political) engagement, and the financial and geographical situation of their company. Results from a regression analysis showed that the specific individual and organizational aspects of the trajectory of the entrepreneurs explain their position in the observed networks. Factors such as the previous experience in the health industry, the training expertise, the international experience, the political engagement, and the geographical and financial situation of the company help entrepreneurs to build up their centrality. The two observations allow us to describe indirectly the evolution of norms that are considered legitimated to carry out innovation in the biotech field.

High-Throughput in Situ Characterization of Polymer Crystallization under an Intense Flow, High Pressure, and Cooling Gradient during Injection Molding

Injection molding is a polymer-processing method widely used, which consumes about one-third of global plastics and produces 80% of plastic parts. However, it is still challenging to in situ reveal the structural evolution of polymers during injection molding, which is a long-standing obstacle to understand the relationship of processing–structure–property. This work has first built an in situ investigation system with the aid of a highly brilliant synchrotron X-ray and large experimental space with a length of 30 m, width of 8 m, and height of 6 m, allowing the installation of an industrial-scale injection molding machine. Based on the characterization system, the fast millisecond-resolved structural evolution of general semicrystalline polymers is identified. Various structural types of information including crystallization kinetics, polymorphism, and the growth and orientation of their lamellar crystals under an actual environment of non-isothermal crystallization with a cooling gradient, intense flow, and high pressure during injection molding have been revealed for the first time. The high-throughput feature of the system provides a vital prerequisite for the subsequent establishment of a quantitative database of processing parameter–structure–performance and the precise regulation of polymer aggregation structures, which is valuable for the digitalization and intelligence of the development of the injection molding industry and integration into the Industrial Internet.