cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/754r78nmbm.3
title: A novel narrow band ultraviolet B (NB-UVB) perilesional irradiation for treating vitiligo with complete leukotrichia: A 12-week, open-label, double-arm, multicenter, randomized clinical trial

description: Background: Vitiligo is a prevalent dermatological condition wherein the loss of melanocytes leads to skin depigmentation with or without leukotrichia. Existing phototherapies can be ineffective for treating vitiligo patients with complete leukotrichia. Our modified approach of ‘NB-UVB Perilesional Irradiation’ offers a new clinical alternative for treating vitiligo patients with complete leukotrichia.
Objective: This study aimed to compare the efficacy of NB-UVB Perilesional irradiation with conventional NB-UVB therapy for repigmentation in vitiligo patients with complete leukotrichia. 
Methods: This is a 12-week, open-label, double-arm, multicenter clinical trial, with a total of 121 vitiligo patients included in the study protocol. All patients were required to have a patch of 100% white vellus hair on their body, with an area less than 1% of their body surface area. The subjects were randomly divided into two groups: one group received conventional NB-UVB irradiation (CI), while the other group received perilesional NB-UVB irradiation (PI). Both groups of patients received topical tacrolimus. The primary outcome was the mean percentage reduction in vitiligo area from baseline to week 12.
Findings: A statistically significant difference in improvement from baseline was observed in the PI group compared to the CI group (-30·8%±11·8%, -25·5%±11·05%, p=0·01) (pair-wise comparison p=0·900 at week 4, p=0·104 at week 8, p=0·01 at week 12). After subgroup analysis, patients older than 18 years old (p=0·014), with lesions on their limbs and trunk (p=0·003), or with a disease duration less than four years (p=0·029), obtained a superior efficacy of repigmentation with PI compared to CI. Meanwhile, at week 12, the average percentage change from baseline of leukotrichia in the irradiation area significantly decreased from 100% to 82·2±13·65% in the PI group, and from 100% to 88·7±9·64% in the CI group (p=0·027). Additionally, the lesions exhibited enhanced marginal repigmentation in the PI group (45/62 [72·58%]) compared to the CI group (p=0·008). Adverse events were minor, including desquamation and dryness, erythema, and blisters. No severe or lasting side effects were observed during the study.
Interpretation: PI has a better effect on the repigmentation of vitiligo with complete leukotrichia than CI and offers a valuable new therapeutic option for vitiligo patients with complete leukotrichia.
DOI: 10.17632/knbkckx9dx.1
title: LDHU3_17.1050

description: Mitoribosomal protein mL73; Leishmania donovani (HU3 strain)
DOI: 10.17632/xv25b8y65h.1
title: Morphological trait database of bark and woodboring beetles

description: This dataset comprises a single csv file containing data on morphological traits for bark beetles and woodboring beetles, with an accompanying metadata file.
DOI: 10.17632/xv25b8y65h.2
title: Morphological trait database of bark and woodboring beetles

description: This dataset comprises a single csv file containing data on morphological traits for bark beetles and woodboring beetles, with an accompanying metadata file.
DOI: 10.17632/63y42ssnt4.1
title: LDHU3_17.1030

description: Acyl CoA binding protein; Leishmania donovani (HU3 strain)
DOI: 10.17632/b7m43jyhcs.1
title: LDHU3_17.1010

description: Hypothetical protein - conserved; Leishmania donovani (HU3 strain)
DOI: 10.17632/n6dzrd3kzd.1
title: Does Country of Origin Matter? Investigating Olive Oil Preferences among Japanese Consumers Using Best-Worst Scaling

description: Questionnaire data and program code for the paper, "Does Country of Origin Matter? Investigating Olive Oil Preferences among Japanese Consumers Using Best-Worst Scaling."
DOI: 10.17632/kcrjt8tysz.1
title: LDHU3_17.1090

description: GRAM domain containing protein; Leishmania donovani (HU3 strain)
DOI: 10.17632/vw2m9w8b2c.1
title: Pilot Data of Instrument Validation for Factor Affecting Indonesian Preservice Mathematics Teachers' Technology Integration

description: The dataset is a pilot study data as part of instrument validation for determining the factors of Mathematics-Technological Pedagogical Content Knowledge (Math-TPACK), Beliefs in Digital Mathematics Learning Media (DMLM), and Beliefs in online learning (OL) had a significant influence on Indonesian PSMTs' use of DMLM (UDMLM) in online teaching practices. In theory, yes. Schmidt et al. [1] defines TPACK as a useful framework for thinking about what knowledge teachers must have to integrate TPACK as a framework for measuring teaching knowledge may have an impact on the type of training and professional development experiences designed for both pre-service and in-service teachers. As a result, Math-TPACK can be defined as a TPACK framework based on mathematical knowledge and mathematical software. The TPACK framework is made up of three types of knowledge: technological knowledge (TK), pedagogical knowledge (PK), and content knowledge (CK). In addition, TPACK also consists of a combination of the three basic knowledge, namely pedagogical-content knowledge (PCK), technological-content knowledge (TCK), technological-pedagogical knowledge (TPK), and technological-pedagogical-content knowledge (TPACK).
Beliefs in DMLM and Beliefs in OL were also examined using the Theory of Planned Behavior (TPB). TPB was first introduced by Ajzen in 1980 as an academic framework aimed at understanding someone's belief in things, objects, or ways [2]. TPB is made up of three basic components: attitude (AT), which is a factor that motivates someone to do something; subjective norm (SN), which is associated with how other influential and important people accept and understand the specific behaviors that are suggested to be performed; and perceived behavioral control (PBC), which is a set that deals with the presence or absence of necessary resources and opportunities. AT refers to factors that influence PSMTs' views on DMLM in the context of beliefs on DMLM. Next, SN discusses how the environment around PSMTs helps them integrate DMLM during teaching practice. Finally, PBC refers to the condition in which PSMTs have complete control over their desire to use DMLM. In the context of online learning beliefs, AT refers to factors that influence PSMTs to use online learning mode. Furthermore, the SN component refers to how the PMSTs' surroundings assist them in using the online learning model. Finally, the PBC component refers to how PSMTs can exercise complete control over their desire to use online learning mode.
DOI: 10.17632/82wryk8hw8.1
title: LINF_290020000

description: RNA-binding protein | DRBD11; Leishmania infantum (strain JPCM5)
DOI: 10.17632/6jp64ht2rr.1
title: LINF_290020300

description: RNA binding protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/jbczpg94cm.1
title: LDHU3_17.1170

description: VID27 cytoplasmic protein; Leishmania donovani (HU3 strain)
DOI: 10.17632/kr33n9799k.1
title: LDHU3_17.1150

description: PKL | Polo-like protein kinase; Leishmania donovani (HU3 strain)
DOI: 10.17632/jz726skp6d.1
title: Data for: Chapter 4 (Properties of and Charged Defects in ThO2) of the PhD Thesis - Large-Scale Density Functional Theory (DFT) Simulations of Lanthanide and Actinide Oxide Materials

description: This repository hosts computational data supporting the findings in Chapter 4 (Properties and Charged Defects) of the PhD thesis: Large-Scale Density Functional Theory (DFT) Simulations of Lanthanide and Actinide Oxide Materials in ThO2 by Nabeel Anwar. Supervised by Robert M. Harker, Mark T. Storr, Marco Molinari and Chris-Kriton Skylaris.

UK Ministry of Defence © Crown owned copyright 2024/AWE
DOI: 10.17632/96pm8h9cgn.1
title: LINF_290022100

description: protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/62mg8s54yd.1
title: LINF_290021900

description: protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/nzkckrc2bf.1
title: Small intestine as a glucose reservoir contributes to glucose homeostasis

description: The small intestine acts as a glucose reservoir to harness glucose homeostasis, which dysfunction is associated with type 2 diabetes.
DOI: 10.17632/f5fprf2xrj.1
title: LDHU3_07.0790

description: Sel1-like protein; Leishmania donovani (HU3 strain)
DOI: 10.17632/ts8ws9w52y.1
title: Code and Data for Predicting Large-Scale Systematic Missing Pipe Attributes in Water Distribution Networks

description: This collection of geospatial data, water network models, and Python code were developed for a pending journal paper with the following abstract: "Water distribution network (WDN) models are an essential tool used by water utilities for hydraulic analysis. Unfortunately, missing data and insufficient resources often make creating and maintaining these models unfeasible. Existing methods for missing pipe properties like sequential imputation for missing values and reconstruction using graph metrics are designed to accommodate random patterns of missing information and require at least 50% of the values to be known. However, these assumptions about data completeness do not always align with real-world scenarios where large sections of the WDN model have missing data. To address this challenge, this study proposes a data-driven approach for estimating the properties (e.g., diameter) of pipes in a WDN when considering different spatial patterns and degrees of data completeness (i.e., 0% - 90%). Using data from 16 WDNs in Kentucky, this study compares the use of machine learning (ML) to predict pipe diameter using topological, geospatial, and hydraulic features against an existing deterministic approach. Results demonstrate that WDN models completed by the proposed ML approach had comparable hydraulic performance to the true models. Moreover, results suggest that WDN system classification and percentage of missing data significantly influence the ML model and its parametrization. Insights from this study help advance the ability to leverage partial data to create WDN models that can be used for resilience analysis, a capability particularly important for communities without adequate resources."
DOI: 10.17632/pdgwsywvhj.1
title: LDHU3_07.0750

description: Hypothetical protein - conserved; Leishmania donovani (HU3 strain)
DOI: 10.17632/3gbgj6ww6f.1
title: Response of chicken litter microbiota to the invasion of Salmonella Infantis throughout the Broiler Production Cycle

description: The microbiota of chicken manure is complex and dynamic and has a direct effect on the welfare and development of diseases in poultry. Leaf litter is composed of fungi, protozoa, archaea and bacteria. Communities can vary depending on the stage of the production cycle and the use of antimicrobial growth promoters.
Our hypothesis was that the litter microbiota changed according to the age of the birds and that the addition of microorganisms altered the litter microbiota and the interaction of the microbial communities.
DOI: 10.17632/59mwtzvnks.1
title: COVID-19 GCA

description: Data used to find an association between COVID-19 and GCA in Bath, UK.
DOI: 10.17632/gzhfdtmhcm.1
title: School Leavers Study for Latent Code Identification Replication

description: Essay database for replication purposes for the study: Latent Code Identification [LACOID]: A Machine Learning-Based Integrative Framework [and Open-Source Software] to Classify Big Textual Data, Rebuild Contextualized/Unaltered Meanings, and Avoid Aggregation Bias
Manuel S. González Canché
Accepted version available here: https://drive.google.com/file/d/17uADm0_7ygT2FhYp_2krRrXS-Kj3sjXh/view?usp=sharing
Accepted version available here: https://drive.google.com/file/d/17uADm0_7ygT2FhYp_2krRrXS-Kj3sjXh/view?usp=sharing

Labeling or classifying textual data and qualitative evidence is an expensive and consequential challenge. The rigor and consistency behind the construction of these labels ultimately shape research findings and conclusions. A multifaceted methodological conundrum to address this challenge is the need for human reasoning for classification that leads to deeper and more nuanced understandings; however, this same manual human classification comes with the well-documented increase in classification inconsistencies and errors, particularly when dealing with vast amounts of documents and teams of coders. An alternative to human coding consists of machine learning-assisted techniques. These data science and visualization techniques offer tools for data classification that are cost-effective and consistent but are prone to losing participants’ meanings or voices for two main reasons: (a) these classifications typically aggregate all text inputs into a single topic or code and (b) these words configuring texts are analyzed outside of their original contexts. To address this challenge and analytic conundrum, we present an analytic framework and software tool, that addresses the following question: How to classify vast amounts of qualitative evidence effectively and efficiently without losing context or the original voices of our research participants and while leveraging the nuances that human reasoning bring to the qualitative and mixed methods analytic tables? This framework mirrors the line-by-line coding employed in human/manual code identification but relying on machine learning to classify texts in minutes rather than months. The resulting outputs provide complete transparency of the classification process and aid to recreate the contextualized, original, and unaltered meanings embedded in the input documents, as provided by our participants. We offer access to the textual database required to replicate all the analyses. We hope this opportunity to become familiar with the analytic framework and software, may result in expanded access of data science tools to analyze qualitative evidence.

Replication steps and outcomes (pages 12 and 13 in the paper)
First download and extract the data from this repository
DOI: 10.17632/f234tpmp4y.2
title: Features of acute COVID-19 associated with Post-Acute Sequelae of SARS-CoV-2 phenotypes: results from the IMPACC study

description: Post-acute sequelae of SARS-CoV-2 (PASC) is a significant public health concern. We describe Patient Reported Outcomes (PROs) on 590 participants prospectively assessed from hospital admission for COVID-19 through one year after discharge. Modeling identified 4 PRO clusters based on reported deficits (minimal, physical, mental/cognitive, and multidomain), supporting heterogenous clinical presentations in PASC, with sub-phenotypes associated with female sex and distinctive comorbidities. During the acute phase of disease, a higher respiratory SARS-CoV-2 viral burden and lower Receptor Binding Domain and Spike antibody titers were associated with both the physical predominant and the multidomain deficit clusters. A lower frequency of circulating B lymphocytes by mass cytometry (CyTOF) was observed in the multidomain deficit cluster. Circulating fibroblast growth factor 21 (FGF21) was significantly elevated in the mental/cognitive predominant and the multidomain clusters. Future efforts to link PASC to acute anti-viral host responses may help to better target treatment and prevention of PASC.
DOI: 10.17632/2nmr2cz9yy.3
title: Datasets for "Multiscalar 3D-temporal structural characterisation of Smøla Island, Mid-Norwegian passive margin" Authored by Hodge et al.

description: A repository of support datasets for "Multiscalar 3D-temporal structural characterisation of Smøla Island, Mid-Norwegian passive margin: an analogue for unravelling the tectonic history of offshore basement highs", authored by: Hodge et al. originally submitted 2023, resubmitted 2024 - Solid Earth
DOI: 10.17632/zk5s7vwwxp.2
title: Sustainable Infrastructure

description: Data of systematic review on sustainable infrastructure for disaster resilience
DOI: 10.17632/x3tzxg38wj.1
title: 2D Data Arrangement to Habituate ANN for Depression Levels Measurement

description: This dataset focuses on optimizing input structures for Artificial Neural Networks (ANN) by arranging data in two-dimensional (2D) parameters. The approach involves collecting and organizing a combination of physical parameters (body temperature, heart rate, oxygen saturation, and sleep duration) and psychological parameters (Perceived Stress Scale) from individuals to create 2D matrices. These matrices serve as input for the ANN, which is trained to predict depression levels based on patterns detected in the data. By structuring the data in this manner, the model becomes more adaptive and effective in identifying the severity of depression, leading to improved accuracy in mental health assessments.
DOI: 10.17632/5zpbzdb8vn.1
title: Supplemental data to Schmid et al. "PGC-1β modulates catabolism and fiber atrophy in the fasting-response of specific skeletal muscle beds", https://doi.org/10.1016/j.molmet.2022.101643

description: The paper Schmid et al. "PGC-1β modulates catabolism and fiber atrophy in the fasting-response of specific skeletal muscle beds", https://doi.org/10.1016/j.molmet.2022.101643, describes the study of the effect of skeletal muscle-specific ablation of the peroxisome proliferator-activated receptor gamma coactivator 1beta on the fasting response. This dataset includes supplemental experimental procedures, Supplementary Table 1 (acclimatization protocol for the treadmill running), Supplementary Table 2 (the primer sequences for the qPCR-based gene expression analysis), Supplementary Table 3 (gene ontology analysis of the differentially expressed genes in the comparison of fasted wild-type and fasted PGC-1beta muscle-specific knockouts), Supplementary Figure S1 (muscle fiber size analysis of the Gastrocnemius muscles of the different experimental cohorts), Supplemental dataset 1 (the complete list of annotation clusters of all comparisons of the gene expression profiles of wild-type and PGC-1beta muscle-specific knockouts in the fasted and fed state), Supplemental dataset 2 (Integrated System for Motif Activity Response Analysis [ISMARA] analysis all comparisons of the gene expression profiles of wild-type and PGC-1beta muscle-specific knockouts in the fasted and fed state). All of these data complement the results in Schmid et al. "PGC-1β modulates catabolism and fiber atrophy in the fasting-response of specific skeletal muscle beds", https://doi.org/10.1016/j.molmet.2022.101643. Moreover, the complete gene expression dataset, including raw and analyzed data, is available at the Gene Expression Omnibus (GEO), accession number GSE210904.
DOI: 10.17632/y4znm8mgz3.3
title: Raw dataset Predation of Asian weaver ant on Metisa plana bagworms

description: Field observations and monitoring of the foraging-predation of Oecophylla smaragdina major workers on pupae-larvae of the invasive bagworms species Metisa plana in oil palm plantations in Malaysia. The relationship between foraging-predation behaviors with air temperature AT and relative humidity RH was examined as well. 
A large plantation comparative biological control strategy trial with trunk systemic chemical injection to monitor the monthly, yearly yield productivity of Fresh Fruit Bunches FFB, the quality of fruit by the Oil Extraction Rate OER and the monthly, yearly incomes-profit: assessment of the effectiveness between both treatment methods. 
The Biological control strategy by weaver ants BC ant was significantly much higher, hence more effective than chemical trunk injection for all the variables of the study: Monthly-yearly yield; OER and Incomes. This is the first study ever conducted using the Asian weaver ants colonies towards the control of M. plana in a critically affected-infested large oil palm plantations in Asia.
DOI: 10.17632/m7whnv4gdf.1
title: supplement material to Le Houedec et al., Assessing atmospheric and oceanic teleconnections between the eastern and western Mediterranean over the past 8,000 years

description: Data Tables of recomputed age model and interpolated stable isotopic data set used for the computation - Le Houedec et al., Assessing atmospheric and oceanic teleconnections between the eastern and western Mediterranean over the past 8,000 years.
DOI: 10.17632/tw2bjh857f.1
title: Synonymous codon usage regulates translation initiation; Barrington et al.

description: Abstract: Nonoptimal synonymous codon usage represses gene expression, but the underlying mechanisms are poorly understood. We and others have shown that nonoptimal codons slow translation elongation speeds and thereby trigger mRNA degradation. Nevertheless, transcript levels are often insufficient to explain protein levels, suggesting there are additional mechanisms by which codon usage regulates gene expression. Using reporter assays in human and Drosophila cells, we found that transcript levels account for less than half of the variation in protein abundance. This discrepancy is explained by translational differences whereby nonoptimal codons repress translation initiation. Nonoptimal transcripts are also less bound by the key translation initiation factors eIF4E and eIF4G, providing a mechanistic explanation for their reduced initiation rates. Importantly, translational repression can occur in the absence of mRNA decay and deadenylation, and it does not depend on the known nonoptimality sensor, CNOT3. Our results reveal a potent new mechanism of regulation by codon usage, where nonoptimal codons repress further rounds of translation.

Raw images are included here, i.e. Western blots and microscopy images. They are organized by Figure.
DOI: 10.17632/tw2bjh857f.2
title: Synonymous codon usage regulates translation initiation; Barrington et al.

description: Abstract: Nonoptimal synonymous codon usage represses gene expression, but the underlying mechanisms are poorly understood. We and others have shown that nonoptimal codons slow translation elongation speeds and thereby trigger mRNA degradation. Nevertheless, transcript levels are often insufficient to explain protein levels, suggesting there are additional mechanisms by which codon usage regulates gene expression. Using reporter assays in human and Drosophila cells, we found that transcript levels account for less than half of the variation in protein abundance. This discrepancy is explained by translational differences whereby nonoptimal codons repress translation initiation. Nonoptimal transcripts are also less bound by the key translation initiation factors eIF4E and eIF4G, providing a mechanistic explanation for their reduced initiation rates. Importantly, translational repression can occur in the absence of mRNA decay and deadenylation, and it does not depend on the known nonoptimality sensor, CNOT3. Our results reveal a potent new mechanism of regulation by codon usage, where nonoptimal codons repress further rounds of translation.

Raw images are included here, i.e. Western blots and microscopy images. They are organized by Figure.