cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/yv26pkh4pd.2
title: Acute cold exposure in rats leading to malignant arrhythmias: Is it tissue damage or functional remodeling?

description: Here are the priginal data of the experiment " Acute cold exposure in rats leading to malignant arrhythmias: Is it tissue damage or functional remodeling?"
DOI: 10.17632/w72shkvs2c
title: Gut microbiota-driven IL-17A production by hepatic γδ T cells enhances neutrophil defense against systemic Staphylococcus aureus infection

description: Staphylococcus aureus (S. aureus) bloodstream infections pose a significant clinical threat, exacerbated by increasing antibiotic resistance and high mortality. While the gut microbiota is recognized as a key modulator of systemic immunity, the mechanisms underlying its protective role against invasive bacterial infections remain incompletely understood. Here, we investigated how gut microbiota influences hepatic immune responses during early S. aureus bloodstream infection using animal models. Our findings demonstrate that the gut microbiota exerts a protective effect against systemic S. aureus infection. Specifically, commensal microbiota-derived signals prime hepatic γδ T cells for rapid IL-17A production upon bacterial challenge. This microbiota-dependent IL-17A response subsequently promotes neutrophil recruitment to the liver, facilitating bacterial clearance and limiting systemic dissemination. Disruption of the gut microbiota impaired hepatic γδ T cell IL-17A production, reduced neutrophil mobilization, and compromised host resistance to infection. Notably, we found that colonization with the commensal Limosilactobacillus reuteri (L. reureri) activates this hepatic γδT17-neutrophil axis, enhancing host defense against S. aureus. This study reveals a novel gut-liver axis whereby intestinal microbiota orchestrates hepatic γδ T cell function to establish an early immunological barrier against invasive bacterial pathogens, offering potential therapeutic avenues for enhancing host defense against life-threatening S. aureus infections.
DOI: 10.17632/w72shkvs2c.2
title: Gut microbiota-driven IL-17A production by hepatic γδ T cells enhances neutrophil defense against systemic Staphylococcus aureus infection

description: Staphylococcus aureus (S. aureus) bloodstream infections pose a significant clinical threat, exacerbated by increasing antibiotic resistance and high mortality. While the gut microbiota is recognized as a key modulator of systemic immunity, the mechanisms underlying its protective role against invasive bacterial infections remain incompletely understood. Here, we investigated how gut microbiota influences hepatic immune responses during early S. aureus bloodstream infection using animal models. Our findings demonstrate that the gut microbiota exerts a protective effect against systemic S. aureus infection. Specifically, commensal microbiota-derived signals prime hepatic γδ T cells for rapid IL-17A production upon bacterial challenge. This microbiota-dependent IL-17A response subsequently promotes neutrophil recruitment to the liver, facilitating bacterial clearance and limiting systemic dissemination. Disruption of the gut microbiota impaired hepatic γδ T cell IL-17A production, reduced neutrophil mobilization, and compromised host resistance to infection. Notably, we found that colonization with the commensal Limosilactobacillus reuteri (L. reureri) activates this hepatic γδT17-neutrophil axis, enhancing host defense against S. aureus. This study reveals a novel gut-liver axis whereby intestinal microbiota orchestrates hepatic γδ T cell function to establish an early immunological barrier against invasive bacterial pathogens, offering potential therapeutic avenues for enhancing host defense against life-threatening S. aureus infections.
DOI: 10.17632/vtn9p9g2kf
title: GASTRIC RESIDUAL VOLUME BEFORE ELECTIVE SURGERY IN CHILDREN DEPENDING ON PREOPERATIVE FASTING DURATION: SINGLE-CENTER PROSPECTIVE RANDOMIZED CLINICAL TRIAL

description: INTRODUCTION. Ensuring patient comfort and eliminating excess limitations before elective surgeries is the foundation of the modern concept of rapid patient recovery after surgeries.
STUDY OBJECTIVE: Based on ultrasound examination, evaluate the residual volume of the stomach depending on the duration of preoperative fasting and intake of clear fluid.
MATERIALS AND METHODS. Design – a single-center prospective randomized clinical trial. Examined 38 children aged 6 to 17 years before elective surgeries, who were randomly assigned to the main (I) and control (II) groups. In group I (n = 18), as early as 12 hours before the operation, children did not receive any food and fluid by mouth, in group II (n = 17), fresh water consumption in the amount of 4 ml/kg was allowed 2 hours before the operation. Inclusion criteria: a) healthy children under the age of 18; b) ASA I-II functional status assessment; c) planned surgical intervention; d) informed voluntary consent to participate in the study. Ultrasound examination was carried out in the supine position and on the right side with measurement of the cross-sectional area of the antrum of the stomach and subsequent calculation of the volume of gastric contents. To assess the severity of thirst, a visual analog scale was used, three levels were distinguished: 0-3 - light; 4-6 points - moderate; 7-10 points - strong thirst.
RESULTS. No complications of anesthesia and surgery, including aspiration of gastric contents, were reported in any child included in the study. In children of group 1, the median glucose level was 4.5 (4.2-4.6) mmol/L, which was significantly higher than in patients of group II 4.1 (3.9-4.5) (p = 0.014). The median residual gastric volume in patients who did not receive solid food and clear fluid in the 12 hours before surgery was 0.34 (0.28 - 0.39) mL/kg, which was not statistically significantly different from the group of children who were allowed to drink fluid in the volume of 4 mL/kg in the 2 hours before surgery: 0.36 (0.31 - 0.4) mL/kg (p = 0,766). Thirst intensity in children of the first group was 3 (3-4.75) points, versus 1 (0-1.5) points in children of the second group (p = 0.000). 
CONCLUSIONS. Drinking 4 ml/kg of fresh water two hours before surgery is a safe alternative to prolonged fasting, providing patient comfort without increasing the risk of aspiration of gastric contents.
DOI: 10.17632/vtn9p9g2kf.1
title: GASTRIC RESIDUAL VOLUME BEFORE ELECTIVE SURGERY IN CHILDREN DEPENDING ON PREOPERATIVE FASTING DURATION: SINGLE-CENTER PROSPECTIVE RANDOMIZED CLINICAL TRIAL

description: INTRODUCTION. Ensuring patient comfort and eliminating excess limitations before elective surgeries is the foundation of the modern concept of rapid patient recovery after surgeries.
STUDY OBJECTIVE: Based on ultrasound examination, evaluate the residual volume of the stomach depending on the duration of preoperative fasting and intake of clear fluid.
MATERIALS AND METHODS. Design – a single-center prospective randomized clinical trial. Examined 38 children aged 6 to 17 years before elective surgeries, who were randomly assigned to the main (I) and control (II) groups. In group I (n = 18), as early as 12 hours before the operation, children did not receive any food and fluid by mouth, in group II (n = 17), fresh water consumption in the amount of 4 ml/kg was allowed 2 hours before the operation. Inclusion criteria: a) healthy children under the age of 18; b) ASA I-II functional status assessment; c) planned surgical intervention; d) informed voluntary consent to participate in the study. Ultrasound examination was carried out in the supine position and on the right side with measurement of the cross-sectional area of the antrum of the stomach and subsequent calculation of the volume of gastric contents. To assess the severity of thirst, a visual analog scale was used, three levels were distinguished: 0-3 - light; 4-6 points - moderate; 7-10 points - strong thirst.
RESULTS. No complications of anesthesia and surgery, including aspiration of gastric contents, were reported in any child included in the study. In children of group 1, the median glucose level was 4.5 (4.2-4.6) mmol/L, which was significantly higher than in patients of group II 4.1 (3.9-4.5) (p = 0.014). The median residual gastric volume in patients who did not receive solid food and clear fluid in the 12 hours before surgery was 0.34 (0.28 - 0.39) mL/kg, which was not statistically significantly different from the group of children who were allowed to drink fluid in the volume of 4 mL/kg in the 2 hours before surgery: 0.36 (0.31 - 0.4) mL/kg (p = 0,766). Thirst intensity in children of the first group was 3 (3-4.75) points, versus 1 (0-1.5) points in children of the second group (p = 0.000). 
CONCLUSIONS. Drinking 4 ml/kg of fresh water two hours before surgery is a safe alternative to prolonged fasting, providing patient comfort without increasing the risk of aspiration of gastric contents.
DOI: 10.15468/dl.uw99wg
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ovis aries",
 "Country is Slovenia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 9 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015087-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2hnjmzpxyd
title: MedSeek_userBehavior

description: The target dataset contains de-identified, high-resolution interaction information from MedSeek, a large-language-model (LLM) platform optimised for medical education. Built on the DeepSeek architecture and fine-tuned with &gt;200 M clinically curated instruction–response pairs, MedSeek achieves state-of-the-art accuracy on multiple medical NLP benchmarks, including MedQA (78.6 %), PubMedQA (83.9 %), MedMCQA (67.4 %), MedBullets (72.1 %), MMLU (81.2 %), MMLU-Pro (79.5 %) and CARE-QA (74.8 %). This dataset captures usage patterns from a medical education large language model (LLM) platform, representing interaction behaviors during Q2 2025. It contains anonymized observational records of platform engagement across diverse medical education contexts.

#### Dataset Components:

1. **User Profiles** (`medical_llm_users.csv`)
 * 1,454 anonymized participant records
 * Role distribution: Educators (2.2%), Medical students (97.8%)
 * Discipline representation: Clinical Medicine (39%), Pharmacy (18%), Public Health (11%), Basic Medicine (26%), Nursing (4%), Medical Humanities (2%)
 * Engagement tiers: High-engagement (15%), Regular (25%), Low-frequency (40%), Dormant (20%)
2. **Session Records** (`medical_llm_sessions.csv`)
 * Platform access sessions with temporal metadata
 * Device access patterns (mobile/desktop/tablet)
 * Duration metrics and temporal distribution
 * Special annotation for examination period (May 10-24, 2025)
3. **Interaction Logs** (`medical_llm_interactions.csv`)
 * Question-Answer exchanges across medical domains
 * Six knowledge domains with topic classifications
 * Interaction types: Initial queries (35%), Follow-ups (25%), Answer review (20%), Clarifications (10%), Content saving (5%), Feedback (5%)
 * Complexity engagement metrics

#### Data Harness:

Data was harnessed through parameterized behavioral modeling based on established medical education frameworks. The process incorporates:

* Professionally validated medical education taxonomies
* Temporal usage distributions reflecting academic calendars
* Device access patterns aligned with mobility studies
* Knowledge domain representations mirroring standard curricula

#### Potential Research Applications:

* Medical education technology adoption studies
* Temporal analysis of learning behaviors
* Domain-specific knowledge retrieval patterns
* Adaptive learning system development
* Educational data mining methodology validation

#### Ethical Compliance:

All identifiers represent anonymized entities. Content follows medical education standards without including real patient information or personally identifiable data. Generated text reflects generalized medical education scenarios without specific case references.
DOI: 10.17632/2hnjmzpxyd.3
title: MedSeek_userBehavior

description: The target dataset contains de-identified, high-resolution interaction information from MedSeek, a large-language-model (LLM) platform optimised for medical education. Built on the DeepSeek architecture and fine-tuned with &gt;200 M clinically curated instruction–response pairs, MedSeek achieves state-of-the-art accuracy on multiple medical NLP benchmarks, including MedQA (78.6 %), PubMedQA (83.9 %), MedMCQA (67.4 %), MedBullets (72.1 %), MMLU (81.2 %), MMLU-Pro (79.5 %) and CARE-QA (74.8 %). This dataset captures usage patterns from a medical education large language model (LLM) platform, representing interaction behaviors during Q2 2025. It contains anonymized observational records of platform engagement across diverse medical education contexts.

#### Dataset Components:

1. **User Profiles** (`medical_llm_users.csv`)
 * 1,454 anonymized participant records
 * Role distribution: Educators (2.2%), Medical students (97.8%)
 * Discipline representation: Clinical Medicine (39%), Pharmacy (18%), Public Health (11%), Basic Medicine (26%), Nursing (4%), Medical Humanities (2%)
 * Engagement tiers: High-engagement (15%), Regular (25%), Low-frequency (40%), Dormant (20%)
2. **Session Records** (`medical_llm_sessions.csv`)
 * Platform access sessions with temporal metadata
 * Device access patterns (mobile/desktop/tablet)
 * Duration metrics and temporal distribution
 * Special annotation for examination period (May 10-24, 2025)
3. **Interaction Logs** (`medical_llm_interactions.csv`)
 * Question-Answer exchanges across medical domains
 * Six knowledge domains with topic classifications
 * Interaction types: Initial queries (35%), Follow-ups (25%), Answer review (20%), Clarifications (10%), Content saving (5%), Feedback (5%)
 * Complexity engagement metrics

#### Data Harness:

Data was harnessed through parameterized behavioral modeling based on established medical education frameworks. The process incorporates:

* Professionally validated medical education taxonomies
* Temporal usage distributions reflecting academic calendars
* Device access patterns aligned with mobility studies
* Knowledge domain representations mirroring standard curricula

#### Potential Research Applications:

* Medical education technology adoption studies
* Temporal analysis of learning behaviors
* Domain-specific knowledge retrieval patterns
* Adaptive learning system development
* Educational data mining methodology validation

#### Ethical Compliance:

All identifiers represent anonymized entities. Content follows medical education standards without including real patient information or personally identifiable data. Generated text reflects generalized medical education scenarios without specific case references.
DOI: 10.17632/s426xsf99b.2
title: ZhangJiaKouQinghe

description: This study investigates how agricultural and urban land use affect microbial communities in river water and sediments along the Qingshui River, China. Using 16S rRNA sequencing, co-occurrence networks, and iCAMP modeling, we found distinct microbial structures and assembly processes: agricultural runoff increased nitrate in water, while urban areas elevated sediment nutrients, driving bacterial changes. Water communities were more responsive to land use and shaped by heterogeneous selection, whereas sediment communities were dominated by dispersal limitation. Network analysis revealed stronger synergistic interactions in agricultural zones and higher competition and robustness in urban areas. Key microbial co-dependencies suggest watershed-scale ecological connectivity, offering insights for science-based river management and conservation.
DOI: 10.5517/ccdc.csd.cc20w8v1
title: CCDC 1873263: Experimental Crystal Structure Determination

description: Related Article: yogesh O. Bhola|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.ck3832
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is BOLD:ACC5171"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015088-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/tzvttww89z.1
title: Persistence of Wild Cycles of Trypanosoma cruzi in Attalea butyracea Palms Infested by Rhodnius in a Region Certified as Free of Domiciliary Vector-Borne Transmission in Colombia.

description: Infestación de Attalea butyracea con vectores de la enfermedad de Chagas e infección natural con Trypanpsoma spp. en el municipio de El Zulia, Norte de Santander, Colombia
DOI: 10.17632/ftghc7dph6
title: The Impact of AI on Korean Language Learning Performance: An Empirical Study from the Perspective of Technological Mediation

description: AI technology is reshaping language learning by enhancing personalization and feedback, yet its impact on Korean language learning and underlying mechanisms remains insufficiently studied. This research adopts the perspective of technological mediation and constructs a model of AI application, intelligent recommendation system, and learning performance. Using questionnaire and academic data from Korean-major undergraduates, multiple regression and mediation analyses reveal that AI significantly improves performance (β=4.684, p&lt;0.01). The intelligent recommendation system partially mediates this effect as AI usage increases recommendation system engagement (β=3.127, p&lt;0.01), which further enhances learning outcomes (β=2.827, p&lt;0.01). Marginal effect analysis shows optimal improvement at moderate AI use (β=5.127), with diminishing returns at higher levels. These results demonstrate that AI not only directly boosts academic performance but also indirectly enhances it by improving learning resource alignment. The study confirms the mediating role of intelligent systems and offers theoretical and empirical insights for optimizing AI-assisted language learning and curriculum design.
DOI: 10.17632/ftghc7dph6.1
title: The Impact of AI on Korean Language Learning Performance: An Empirical Study from the Perspective of Technological Mediation

description: AI technology is reshaping language learning by enhancing personalization and feedback, yet its impact on Korean language learning and underlying mechanisms remains insufficiently studied. This research adopts the perspective of technological mediation and constructs a model of AI application, intelligent recommendation system, and learning performance. Using questionnaire and academic data from Korean-major undergraduates, multiple regression and mediation analyses reveal that AI significantly improves performance (β=4.684, p&lt;0.01). The intelligent recommendation system partially mediates this effect as AI usage increases recommendation system engagement (β=3.127, p&lt;0.01), which further enhances learning outcomes (β=2.827, p&lt;0.01). Marginal effect analysis shows optimal improvement at moderate AI use (β=5.127), with diminishing returns at higher levels. These results demonstrate that AI not only directly boosts academic performance but also indirectly enhances it by improving learning resource alignment. The study confirms the mediating role of intelligent systems and offers theoretical and empirical insights for optimizing AI-assisted language learning and curriculum design.
DOI: 10.17632/4ck4psxbgd
title: yz_data

description: For research paper of yz
DOI: 10.17632/4ck4psxbgd.1
title: yz_data

description: For research paper of yz
DOI: 10.15468/dl.rnqjsg
title: Occurrence Download

description: A dataset containing 77 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ovis aries",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 77 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015089-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/xsh685p3xj.2
title: Therapy of allergic rhinitis using ribavirin spray to clear nasal commensal viruses

description: Much attention has focused on commensal bacteria in health and disease, but the role of commensal viruses is largely unexplored, especially in the nose that directly contacts outer environment. Here, we focused on nasal commensal viruses in the development of allergic rhinitis (AR), and found that clearance of nasal commensal viruses using ribavirin alleviated AR symptoms, suggesting that nasal commensal viruses promote AR etiology. Mechanistically, nasal commensal viruses, recognized by innate sensors, initiated the production of type I interferon, generating interferon-induced neutrophils and releasing NETs to promote AR. We then performed a randomized, double-blind, placebo-controlled, phase 2 clinical trial (www.chictr.org.cn ChiCTR2400082642) to explore the efficacy and safety of ribavirin spray in treating AR patients, and found that the patients of ribavirin group experienced significantly reduced nasal commensal viruses and alleviated symptoms as compared to placebo. Thus, we suggest a new mechanism for AR and a new approach for the treatment.
DOI: 10.15468/dl.yarm3p
title: Occurrence Download

description: A dataset containing 4452 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Myrmia micrura)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 4452 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015093-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w6usmj
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Clusia havetioides"
 ]
}

 The dataset includes 90 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015091-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.8414136
title: Early Slavic word embeddings

description: Word embeddings trained on the lemmatised TOROT Treebank, using Word2Vec and the following parameters:


sg = True
min_count = <1,3,5>
window = <3,5>
vector_size = <100,200,300>
epochs = 5


One model was trained for each combination of the parameters enclosed in angled brackets (< >). 


The release contains both the full models (.model) and the plain vector files (_vectors.txt). The models are named according to the parameters they were trained with.


Note that these are the result of very preliminary experiments and no systematic evaluation of their quality was carried out, so use with caution.