Version Of Database Research Articles

PolylexFLE

Abstract MWE knowledge is key in the process of learning a foreign language, but its teaching remains hindered by the lack of list of expressions connected to pedagogical aims. In this paper, we present an extended version of the PolylexFLE database, containing 4,525 French multiword expressions (MWE) of three types: idioms, collocations or fixed expressions. In order to propose exercises following the difficulty scale of the European Framework of Reference for Languages (CEFR), we used a mixed approach (manual and automatic) to annotate 1,186 expressions according to the CEFR levels. The paper focuses mostly on the automatic procedure that first identifies the expressions from the PolylexFLE database (and their variants) in a corpus of pedagogical texts (with CEFR labels) using a pattern-based system. In a second step, their distribution in this corpus is estimated and transformed into a single CEFR level. The automatic approach proposed is finally evaluated by 52 French as foreign language learners.

Study of the impact of organic minerals on spermatozoal gene expression in Osmanabadi bucks

Sperm transcripts aside from providing genetic material have an eminent role in post-fertilization events and embryonic development. The current study was carried out to study the gene expression in Osmanabadi buck (Capra hircus) supplemented with organic minerals. Organic minerals alone or in combination with different concentrations were fed to the treatment groups (T2- Zn 20 mg, T3- Zn 40 mg, T4- Zn 60 mg, T5- Cu 12.5 mg, T6- Cu 25 mg, T7- Cu 37.5 mg, T8- Zn 20 mg + Cu 12.5 mg, T9- Zn 40 mg + Cu 25 mg, T10- Zn 60 mg + Cu 37.5 mg) along with the concentration mixture and roughages; whereas control (T1) group was fed concentrate mixture and roughages. The sperm samples were processed for gene expression studies of Ras Homolog Family Member A (RHOA), Mesoderm Specific Transcript (MEST), Nucleoside diphosphate-linked moiety X motif 6 (NUDT6), Protamine 1 (PRM1), Protamine 2 (PRM2) and Heat shock protein 90 alpha family class A member 1 (HSP90AA) using qRT-PCR and the protein-protein interaction analysis was carried out through String database version 11.0. Supplementation of trace minerals has enhanced the gene expression at a significant level (P<0.05) in the supplemented groups. The expression of MEST, RHOA, and PRM1 was higher in Cu 25-supplemented groups; whereas, NUDT6 in Zn 20, PRM2 and HSP90AA in Zn 40 showed higher expressions. Osmanabadi bucks supplemented with Cu 25 mg have shown promising results in the present and earlier studies so it can be concluded that the field-level application of Cu 25 mg would lead to promising results.

Potential shared pathogenic mechanisms between endometriosis and inflammatory bowel disease indicate a strong initial effect of immune factors.

Over the past decades, immune dysregulation has been consistently demonstrated being common charactoristics of endometriosis (EM) and Inflammatory Bowel Disease (IBD) in numerous studies. However, the underlying pathological mechanisms remain unknown. In this study, bioinformatics techniques were used to screen large-scale gene expression data for plausible correlations at the molecular level in order to identify common pathogenic pathways between EM and IBD. Based on the EM transcriptomic datasets GSE7305 and GSE23339, as well as the IBD transcriptomic datasets GSE87466 and GSE126124, differential gene analysis was performed using the limma package in the R environment. Co-expressed differentially expressed genes were identified, and a protein-protein interaction (PPI) network for the differentially expressed genes was constructed using the 11.5 version of the STRING database. The MCODE tool in Cytoscape facilitated filtering out protein interaction subnetworks. Key genes in the PPI network were identified through two topological analysis algorithms (MCC and Degree) from the CytoHubba plugin. Upset was used for visualization of these key genes. The diagnostic value of gene expression levels for these key genes was assessed using the Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) The CIBERSORT algorithm determined the infiltration status of 22 immune cell subtypes, exploring differences between EM and IBD patients in both control and disease groups. Finally, different gene expression trends shared by EM and IBD were input into CMap to identify small molecule compounds with potential therapeutic effects. 113 differentially expressed genes (DEGs) that were co-expressed in EM and IBD have been identified, comprising 28 down-regulated genes and 86 up-regulated genes. The co-expression differential gene of EM and IBD in the functional enrichment analyses focused on immune response activation, circulating immunoglobulin-mediated humoral immune response and humoral immune response. Five hub genes (SERPING1、VCAM1、CLU、C3、CD55) were identified through the Protein-protein Interaction network and MCODE.High Area Under the Curve (AUC) values of Receiver Operating Characteristic (ROC) curves for 5hub genes indicate the predictive ability for disease occurrence.These hub genes could be used as potential biomarkers for the development of EM and IBD. Furthermore, the CMap database identified a total of 9 small molecule compounds (TTNPB、CAY-10577、PD-0325901 etc.) targeting therapeutic genes for EM and IBD. Our research revealed common pathogenic mechanisms between EM and IBD, particularly emphasizing immune regulation and cell signalling, indicating the significance of immune factors in the occurence and progression of both diseases. By elucidating shared mechanisms, our study provides novel avenues for the prevention and treatment of EM and IBD.

Comparison of the Ionospheric Dynamo Current of Mars Above InSight and Zhurong Landing Sites: A Modeling Study

AbstractPrevious observational studies suggest that the surface time‐varying magnetic field of Mars originates in large part from the dynamo currents in the Martian ionosphere. However, whether there are significant differences in the strength, configuration, diurnal, and seasonal variations of the dynamo currents above different regions need to be further studied. In this study, using the ionospheric parameters from Mars Climate Database version 5.3 (MCD v5.3) and 7 years of MAVEN magnetic field measurements, we compare the ionospheric dynamo currents above the landing sites of InSight (4.50°N, 135.62°E) and Zhurong (25.07°N, 109.90°E) and the resulting surface magnetic variations at the two landing sites by conducting a modeling study. We find that the average dynamo current as well as its diurnal magnetic field amplitude on the Martian surface is significantly stronger at InSight than that at Zhurong due to the stronger background magnetic field strength and more perpendicular angle between magnetic field and neutral wind vectors in the dynamo region, though the conductivities is always weaker over InSight landing site. The seasonal variation of the current intensity (represented by differences between northern winter and summer solstices) is prominent over InSight than that over Zhurong because the heliospheric distance effect‐resulted conductivity difference is the dominate factor for the seasonal variations over InSight while both the heliospheric distance and solar zenith angle (SZA) contribute to the current intensity at different Ls over Zhurong. The two factors partially offset each other and lead to a smaller seasonal variation. The role of crustal field, as well as the latitude effects on dynamo currents is also discussed. This study provides an attempt to promote the understanding of the solar wind‐induced magnetosphere‐ionosphere‐surface coupling process.

PENERAPAN SISTEM INFORMASI MANAJEMEN INVENTORY PADA CV MADJU DJAJA BANJARMASIN

Abstract, The purpose of this research is to determine the application of the inventory management information system at the CV Madju Djaja Banjarmasin company. The type of research used is descriptive qualitative. The data sources in this research are interviews. Data analysis uses Web-based programming, namely PHP Version 5.1.1 and MySQL database Version 5.0.18. The results of research using an inventory management information system, it can make it easier for company employees to process goods data such as inputting incoming and outgoing goods via computer and by using this system it can make it easier for the warehouse stock section to make monthly stock reports. Control and supervision of inventory can be carried out directly by the director because the information system can be accessed on the internet by entering a username and password which are only known by the company director and the warehouse stock section. So that there is no interference from other unrelated parties and can minimize the risks that occur.

Decarbonizing the cement industry: Findings from coupling prospective life cycle assessment of clinker with integrated assessment model scenarios

In the race to achieve global climate neutrality, carbon intensive industries like the clinker and cement industry are required to decarbonize rapidly. The environmental impacts related to potential transition pathways to low-carbon systems can be evaluated using prospective life cycle assessment (pLCA). This study conducts a pLCA for future global clinker production, integrating long-term transition pathways from the IMAGE integrated assessment model (IAM) to maintain global consistency. It systematically modifies the ecoinvent v3.9.1 database using the Python library premise to create future database versions representing future clinker production embedded in a future economy according to a 3.5°C-baseline, a 2°C-compliant and a 1.5°C-compliant scenario. Our study indicates that climate change impacts of clinker production may decrease from about 1.03 kg CO2-eq/kg clinker in 2020 to 0.94 (3.5°C-baseline), 0.20 (2°C-compliant), and 0.16 (1.5°C-compliant) kg CO2-eq/kg clinker in 2060 for the global average. This corresponds to a 10% (3.5°C-baseline), 81% (2°C-compliant) and 84% (1.5°C-compliant) decrease by 2060 compared to 2020. Under these scenarios, global clinker production alone would require 5%–11% of the remaining end-of-century carbon budget for the 2 °C and 1.5 °C-target, respectively. While the climate change impacts are substantially reduced, our study also indicates that the transition pathways shift the burden towards other impact categories, such as ionizing radiation, ozone depletion, material resources and land use. Developing IAM-compatible scenarios for more product groups helps to increase the coherence of pLCA studies. As this study is based on an IAM heavily reliant on carbon capture and storage and bioenergy, future research should explore the effects of different technology pathways and alternative mitigation strategies.

Proteome-wide Mendelian randomization identifies therapeutic targets for ankylosing spondylitis.

Ankylosing Spondylitis (AS) is a chronic inflammatory disorder which can lead to considerable pain and disability. Mendelian randomization (MR) has been extensively applied for repurposing licensed drugs and uncovering new therapeutic targets. Our objective is to pinpoint innovative therapeutic protein targets for AS and assess the potential adverse effects of druggable proteins. We conducted a comprehensive proteome-wide MR study to assess the causal relationships between plasma proteins and the risk of AS. The plasma proteins were sourced from the UK Biobank Pharma Proteomics Project (UKB-PPP) database, encompassing GWAS data for 2,940 plasma proteins. Additionally, GWAS data for AS were extracted from the R9 version of the Finnish database, including 2,860 patients and 270,964 controls. The colocalization analysis was executed to identify shared causal variants between plasma proteins and AS. Finally, we examined the potential adverse effects of druggable proteins for AS therapy by conducting a phenome-wide association study (PheWAS) utilizing the extensive Finnish database in version R9, encompassing 2,272 phenotypes categorized into 46 groups. The findings revealed a positive genetic association between the predicted plasma levels of six proteins and an elevated risk of AS, while two proteins exhibited an inverse association with AS risk (P fdr < 0.05). Among these eight plasma proteins, colocalization analysis identified AIF1, TNF, FKBPL, AGER, ALDH5A1, and ACOT13 as shared variation with AS(PPH3+PPH4>0.8), suggesting that they represent potential direct targets for AS intervention. Further phenotype-wide association studies have shown some potential side effects of these six targets (P fdr < 0.05). Our investigation examined the causal connections between six plasma proteins and AS, providing a comprehensive understanding of potential therapeutic targets.

Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models

Model development in the Next Generation Attenuation-East (NGA-East) project included two components developed concurrently and independently: (1) earthquake ground-motion models (GMMs) that predict the median and aleatory variability of various intensity measures conditioned on magnitude and distance, derived for a reference hard-rock site condition with an average shear-wave velocity in the upper 30 m ( VS30) = 3000 m/s; and (2) a site amplification model that modifies intensity measures for softer site conditions. We investigate whether these models, when used in tandem, are compatible with ground-motion recordings in central and eastern North America (CENA) using an expanded version of the NGA-East database that includes new events from November 2011 (end date of NGA-East data curation) to April 2022. Following this expansion, the data set has 187 events, 2096 sites, and 16,272 three-component recordings, although the magnitude range remains limited (∼4 to 5.8). We compute residuals using 17 NGA-East GMMs and three data selection criteria that reflect within-CENA regional variations in ground-motion attributes. Mixed-effects regression of the residuals reveals a persistent pattern in which ground motions are overpredicted at short periods (0.01–0.6 s, including peak ground acceleration (PGA)) and underpredicted at longer periods. These misfits are regionally variable, with the Texas–Oklahoma–Kansas region having larger absolute misfits than other parts of CENA. Two factors potentially influencing these misfits are (1) differences in the site amplification models used to adjust the data to the reference condition during NGA-East GMM development relative to CENA amplification models applied since the 2018 National Seismic Hazard Model (NSHM), and (2) potential bias in simulation-based factors used to adjust ground motions from the hard-rock reference condition to a VS30 = 760 m/s condition. We provide adjustment factors and their epistemic uncertainties and discuss implications for applications.

Influence of pre-processing methods on the automatic priority prediction of native-language end-users’ maintenance requests through machine learning methods

Feedback and requests by occupants are relevant sources of data to improve building management, and building maintenance. Indeed, most predictable faults can be directly identified by occupants and communicated to facility managers through communications written in the end-users’ native language. In this sense, natural language processing methods can support the request identification and attribution process if they are robust enough to extract useful information from these unstructured textual sources. Machine learning (ML) can support assessing and managing these data, especially in the case of many simultaneous communications. In this field, the application of pre-processing and ML methods to English-written databases has been widely provided, while efforts in other native languages are still limited, impacting the real applicability. Moreover, the performance of combinations of methods for pre-processing, ML and classification classes attribution, has been limitedly investigated while comparing different languages. To fill this gap, this work hence explores the performance of automatic priority assignment of maintenance end-users’ requests depending on the combined influence of: (a) different natural language pre-processing methods, (b) several supervised ML algorithms, (c) two priority classification rules (2-class versus 4-class), (d) the database language (i.e. the original database written in Italian, the native end-users’ language; a translated database version in English, as standard reference). Analyses are performed on a database of about 12000 maintenance requests written in Italian concerning a stock of 23 buildings open to the public. A random sample of the sentences is supervised and labelled by 20 expert annotators following the best-worst method to attribute a priority score. Labelled sentences are then pre-processed using four different approaches to progressively reduce the number of unique words (potential predictors). Five different consolidated ML methods are applied, and comparisons involve accuracy, precision, recall and F1-score for each combination of pre-processing action, ML method and the number of priority classes. Results show that, within each ML algorithm, different pre-processing methods limitedly impact the final accuracy and average F1-score. In both Italian and English conditions, the best performance is obtained by NN, LR, SVM methods, while NB generally fails, and by considering the 2-class priority classification scale. In this sense, results confirm that facility managers can be effectively supported by ML methods for preliminary priority assessments in building maintenance processes, even when the requests database is written in end-users’ native language.

Analysis of the public HARPS/ESO spectroscopic archive

Context. Magnetic activity is currently the primary limiting factor in radial velocity (RV) exoplanet searches. Even inactive stars, such as the Sun, exhibit RV jitter of the order of a few m s−1 due to active regions on their surfaces. Time series of chromospheric activity indicators, such as the Ca II H&amp;K lines, can be utilized to reduce the impact of such activity phenomena on exoplanet search programmes. In addition, the identification and correction of instrumental effects can improve the precision of RV exoplanet surveys. Aims. We aim to update the HARPS -RVBANK RV database and include an additional 3.5 yr of time series and Ca II H&amp;K lines (R′HK) chromospheric activity indicators. This additional data will aid in the analysis of the impact of stellar magnetic activity on the RV time series obtained with the HARPS instrument. Our updated database aims to provide a valuable resource for the exoplanet community in understanding and mitigating the effects of such stellar magnetic activity on RV measurements. Methods. The new HARPS-RVBANK database includes all stellar spectra obtained with the HARPS instrument prior to January 2022. The RVs corrected for small but significant nightly zero-point variations were calculated using an established method. The R′HK estimates were determined from both individual spectra and co-added template spectra with the use of model atmospheres. As input for our derivation of R′HK, we derived stellar parameters from co-added, high signal-to-noise ratio templates for a total of 3230 stars using the stellar parameter code SPECIES. Results. The new version of the HARPS RV database has a total of 252 615 RVs of 5239 stars. Of these, 195 387 have R′HK values, which corresponds to 77% of all publicly available HARPS spectra. Currently, this is the largest public database of high-precision (down to ~1 m s−1) RVs, and the largest compilation of R′HK measurements. We also derived lower limits for the RV jitter of F-, G-, and K-type stars as a function of R′HK.

Psychometric evaluation and linking of the PHQ-9, QIDS-C, and VQIDS-C in a real-world population with major depressive disorder.

Major depressive disorder (MDD) is a leading cause of disability worldwide. An accurate assessment of depressive symptomology is crucial for clinical management and research. This study assessed the convergent validity, reliability, and total scale score interconversion across the 9-item Patient Health Questionnaire (PHQ-9) self-report, the 16-item Quick Inventory of Depressive Symptomatology-clinician report (QIDS-C) (two widely used clinical ratings) and the 5-item Very Brief Quick Inventory of Depressive Symptoms-clinician report (VQIDS-C), which evaluate the core features of MDD. This study leveraged electronic health record (EHR)-derived, de-identified data from the NeuroBlu Database (Version 23R1), a longitudinal behavioural health real-world platform. Classical Test Theory (CTT) and Item Response Theory (IRT) analyses were used to evaluate the reliability, validity of, and conversions between the scales. The Test Information Function (TIF) was calculated for each scale, with greater test information reflecting higher precision and reliability in measuring depressive symptomology. IRT was also used to generate conversion tables so that total scores on each scale could be compared to the other. The study sample (n = 2,156) had an average age of 36.4 years (standard deviation [SD] = 13.0) and 59.7% were female. The mean depression scores for the PHQ-9, QIDS-C, and VQIDS-C were 12.9 (SD = 6.6), 12.0 (SD = 4.9), and 6.18 (SD = 3.2), respectively. The Cronbach's alpha coefficients for PHQ-9, QIDS-C, and VQIDS-C were 0.9, 0.8, and 0.7, respectively, suggesting acceptable internal consistency. PHQ-9 (TIF = 30.3) demonstrated the best assessment of depressive symptomology, followed by QIDS-C (TIF = 25.8) and VQIDS-C (TIF = 17.7). Overall, PHQ-9, QIDS-C, and VQIDS-C appear to be reliable and convertible measures of MDD symptomology within a US-based adult population in a real-world clinical setting.

Analysis of Meteorological Drought Changes in Afghanistan Using SPI Index

Meteorological drought, as a natural and significant phenomenon in the field of hydrometeorology, refers to the scarcity of precipitation and moisture in a specific region. This research was conducted with the objectives of understanding the intensity and duration of weather droughts in Afghanistan, categorizing the extent of weather droughts in Afghanistan, and detecting the trend of weather droughts across the country. To investigate the droughts in Afghanistan, daily precipitation data from the Afrodite database version V1101 was utilized, which covered the statistical precipitation records during the period of 1950-2015. Using the Standardized Precipitation Index (SPI) as a measure of drought severity, duration, and frequency, the status of droughts was examined. Based on the analysis, significant trends of droughts were observed in the northern, northeastern, southwestern, and northwestern regions of Afghanistan. Furthermore, the results indicated the occurrence of three periods: wet, normal, and drought, during the study period. The climatic conditions classification during our study period demonstrated that mild moist conditions occurred repeatedly in certain regions of Afghanistan, especially in provinces such as Khost, Paktia, Logar, Kabul, eastern Ghazni, Parwan, Panjshir, Bamyan, Kunduz, southern Takhar, Balkh, Jawzjan, Faryab, Badghis, and northern Herat. On the contrary, severe droughts were more prevalent in the eastern, northeastern, central, and southern regions of Afghanistan. Additionally, mild and moderate droughts were observed in many areas.

Simultaneous assessment of stress hyperglycemia ratio and glycemic variability to predict mortality in patients with coronary artery disease: a retrospective cohort study from the MIMIC-IV database

BackgroundStress hyperglycemia and glycemic variability (GV) can reflect dramatic increases and acute fluctuations in blood glucose, which are associated with adverse cardiovascular events. This study aimed to explore whether the combined assessment of the stress hyperglycemia ratio (SHR) and GV provides additional information for prognostic prediction in patients with coronary artery disease (CAD) hospitalized in the intensive care unit (ICU).MethodsPatients diagnosed with CAD from the Medical Information Mart for Intensive Care-IV database (version 2.2) between 2008 and 2019 were retrospectively included in the analysis. The primary endpoint was 1-year mortality, and the secondary endpoint was in-hospital mortality. Levels of SHR and GV were stratified into tertiles, with the highest tertile classified as high and the lower two tertiles classified as low. The associations of SHR, GV, and their combination with mortality were determined by logistic and Cox regression analyses.ResultsA total of 2789 patients were included, with a mean age of 69.6 years, and 30.1% were female. Overall, 138 (4.9%) patients died in the hospital, and 404 (14.5%) patients died at 1 year. The combination of SHR and GV was superior to SHR (in-hospital mortality: 0.710 vs. 0.689, p = 0.012; 1-year mortality: 0.644 vs. 0.615, p = 0.007) and GV (in-hospital mortality: 0.710 vs. 0.632, p = 0.004; 1-year mortality: 0.644 vs. 0.603, p < 0.001) alone for predicting mortality in the receiver operating characteristic analysis. In addition, nondiabetic patients with high SHR levels and high GV were associated with the greatest risk of both in-hospital mortality (odds ratio [OR] = 10.831, 95% confidence interval [CI] 4.494–26.105) and 1-year mortality (hazard ratio [HR] = 5.830, 95% CI 3.175–10.702). However, in the diabetic population, the highest risk of in-hospital mortality (OR = 4.221, 95% CI 1.542–11.558) and 1-year mortality (HR = 2.013, 95% CI 1.224–3.311) was observed in patients with high SHR levels but low GV.ConclusionsThe simultaneous evaluation of SHR and GV provides more information for risk stratification and prognostic prediction than SHR and GV alone, contributing to developing individualized strategies for glucose management in patients with CAD admitted to the ICU.

Association between alkaline phosphatase to albumin ratio and mortality among patients with sepsis

The alkaline phosphatase-to-albumin ratio (APAR) is correlated to worse prognosis in coronary artery disease, cancer, and acute renal failure. However, the relationship between APAR and sepsis prognosis has received little research. The content of this research was to investigate the prognostic relationship between APAR and sepsis. And validate the stability of the correlation in 90-days and 1-year mortality. Retrospective cohort research was conducted basing MIMIC-IV database (version 2.0). The hazard ratio (HR) and 95% confidence interval (Cl) were computed using multivariate Cox regression analysis. In addition, plots of survival curves and subgroup analyzes were conducted. Receiver operating characteristic (ROC) curves were also used. 9741 participants were included in this investigation. The 90-days mortality was 32.8%, and the 1-year mortality was 42.0%. After controlling for confounders, the adjusted HRs (95% CI) for tertile 2 (2.2–3.8) and tertile 3 (> 3.8) were 1.37 (1.25–1.51) and 1.74 (1.58–1.91), respectively. The Kaplan–Meier curve analysis showed a higher probability of 90-days death in the higher APAR group. The area under the curve (AUC) of APAR was 0.674 and could reach 0.709 after combining the Oxford Acute Severity of Illness Score (OASIS). This study demonstrates that APAR is significantly related to bad clinical outcomes in sepsis.

HCCDB v2.0: Decompose Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC.

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). Integrated 15 transcriptomic datasets of HCC clinical samples, the first version of HCC database (HCCDB v1.0) was released in 2018. Through the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets, it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. With four years having passed, the database now needs integration of recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric is proposed as well to summarize cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

Plant macrofossil data for 48-0 ka in the USGS North American Packrat Midden Database, version 5.0

Plant macrofossils from packrat (Neotoma spp.) middens provide direct evidence of past vegetation changes in arid regions of North America. Here we describe the newest version (version 5.0) of the U.S. Geological Survey (USGS) North American Packrat Midden Database. The database contains published and contributed data from 3,331 midden samples collected in southwest Canada, the western United States, and northern Mexico, with samples ranging in age from 48 ka to the present. The database includes original midden-sample macrofossil counts and relative-abundance data along with a standardized relative-abundance scheme that makes it easier to compare macrofossil data across midden-sample sites. In addition to the midden-sample data, this version of the midden database includes calibrated radiocarbon (14C) ages for the midden samples and plant functional type (PFT) assignments for the midden taxa. We also provide World Wildlife Fund ecoregion assignments and climate and bioclimate data for each midden-sample site location. The data are provided in tabular (.xlsx), comma-separated values (.csv), and relational database (.mdb) files.

MOODLE MANUAL UPGRADE METHODOLOGY

This abstract outlines a systematic four-step methodology for upgrading Moodle from version 3.6.5 to 3.9.9. The process begins with comprehensive backup and preparation, followed by the replacement of the Moodle codebase and execution of the upgrade script. Post-upgrade checks are performed to ensure the smooth functioning of core and third-party components. Additionally, the abstract explores the actions and functions of the cron script, emphasizing its role in executing scheduled tasks critical for Moodle's operation.&#x0D; Furthermore, the document sheds light on common reasons behind slow Moodle operation and provides practical tips for enhancing system speed. Recommendations include optimizing server resources, database maintenance, strategic caching implementation, and the judicious use of content delivery networks (CDNs). The importance of upgrading PHP and database versions is highlighted, alongside the benefits of disabling unused features and employing server monitoring tools. The abstract emphasizes the significance of staying abreast of Moodle updates for continued performance improvements and bug fixes, offering a holistic guide for upgrading and optimizing Moodle systems.

Dietary polyphenol intake in the Canadian population: Findings from the 2015 Canadian Community Health Survey-Nutrition.

This study aimed to estimate usual polyphenol intake among Canadians using the nationally representative 2015 Canadian Community Health Survey-Nutrition and to explore the main dietary contributors to polyphenol intake and the sociodemographic and lifestyle factors that may impact polyphenol intake. Dietary information was collected from 19,409 respondents using 24-h dietary recalls. The polyphenol content of foods was estimated using the Phenol-Explorer Database (version 3.6). Daily intake values for total polyphenols (adjusted to energy intake), main classes, and subclasses were calculated for each respondent and dietary recall. Usual intake was estimated by age/sex groups and by sociodemographic and lifestyle characteristics independently for adults and children using the National Cancer Institute method. Given-day arithmetic mean polyphenol intakes and mean proportions of main classes contributing to sum total polyphenol intakes were explored. Population proportions were used to determine dietary contributors. Usual total polyphenol intake was 1119.3mg/1000kcal/day (95% CI: 1090.5, 1148.1) for adults ≥ 19years and 473.0mg/1000kcal/day (95% CI: 454.9, 491.0) for children 2‒18years. Generally, total polyphenol intakes differed by age, sex, ethnicity, and household education status and were higher among coffee and tea consumers. Most polyphenols came from flavonoids (40.0%) and phenolic acids (49.8%), with children consuming more flavonoids and other polyphenols and adults more phenolic acids. The top food contributors to polyphenol intake were coffee (26.8%), tea (8.9%), fruit juice (4.2%), banana (4.1%), and apple (3.8%). Usual intake of total polyphenols among Canadians differed primarily by age. Non-alcoholic beverages were top contributors to total polyphenol intake.

Ligand-based virtual screening and biological evaluation of inhibitors of Mycobacterium tuberculosis H37Rv

ABSTRACT Novel antimycobacterial compounds are needed to expand the existing toolbox of therapeutic agents, which sometimes fail to be effective. In our study we extracted, filtered, and aggregated the diverse data on antimycobacterial activity of chemical compounds from the ChEMBL database version 24.1. These training sets were used to create the classification and regression models with PASS and GUSAR software. The IOC chemical library consisting of approximately 200,000 chemical compounds was screened using these (Q)SAR models to select novel compounds potentially having antimycobacterial activity. The QikProp tool (Schrödinger) was used to predict ADME properties and find compounds with acceptable ADME profiles. As a result, 20 chemical compounds were selected for further biological evaluation, of which 13 were the Schiff bases of isoniazid. To diversify the set of selected compounds we applied substructure filtering and selected an additional 10 compounds, none of which were Schiff bases of isoniazid. Thirty compounds selected using virtual screening were biologically evaluated in a REMA assay against the M. tuberculosis strain H37Rv. Twelve compounds demonstrated MIC below 20 µM (ranging from 2.17 to 16.67 µM) and 18 compounds demonstrated substantially higher MIC values. The discovered antimycobacterial agents represent different chemical classes.

Identification of Hub Genes and Pathways of Middle Cerebral Artery Occlusion in Aged Rats Using the Gene Expression Omnibus Database.

Stroke remained the leading cause of disability in the world, and the most important non-modifiable risk factor was age. The treatment of stroke for elder patients faced multiple difficulties due to its complicated pathogenesis and mechanism. Therefore, we aimed to identify the potential differentially expressed genes (DEGs) and singnalling pathways for aged people of stroke. To compare the DEGs in the aged rats with or without middle cerebral artery occlusion (MCAO) and to analyse the important genes and the key signaling pathways involved in the development of cerebral ischaemia in aged rats. The Gene Expression Omnibus (GEO) analysis tool was used to analyse the DEGs in the GSE166162 dataset of aged MCAO rats compared with aged sham rats. Differential expression analysis was performed in aged MCAO rats and sham rats using limma. In addition, the 74 DEGs (such as Fam111a, Lcn2, Spp1, Lgals3 and Gpnmb were up-regulated; Egr2, Nr4a3, Arc, Klf4 and Nr4a1 were down-regulated) and potential compounds corresponding to the top 20 core genes in the Protein-Protein Interaction (PPI) network was constructed using the STRING database (version 12.0). Among these 30 compounds, resveratrol, cannabidiol, honokiol, fucoxanthin, oleandrin and tyrosol were significantly enriched. These DEGs were subjected to Gene Ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to determine the most significantly enriched pathway in aged MCAO rats. Moreover, innate immune response, the complement and coagulation cascades signaling pathway, the IL-17 and other signaling pathways were significantly correlated with the aged MCAO rats. Our study indicates that multiple genes and pathological processes involved in the aged people of stroke. The immune response might be the key pathway in the intervention of cerebral infarction in aged people.