cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/y8g5pyk9px.1
title: Oral administration of Proteus mirabilis mutilates the dendritic morphology of striatal dopaminergic neurons leading to cognitive dysfunction

description: Parkinson’s disease (PD) is an age-related disorder now the most common neurodegenerative disorder after Alzheimer’s disease which is identified by the motor symptoms occurring due to abnormalities in cortical region. A distinguished feature of the progressive loss of dopaminergic neurons in the basal ganglia region of the brain leads to motor and non-motor symptoms. The potential that gut microbial dysbiosis is linked to PD pathogenesis is indicated by prior research on pathological alterations in the intestines of PD patients and PD animal models. This study aims to target the gut bacteria that could be involved in the degeneration of striatal dopaminergic neurons and consequently progressing the symptoms of PD. The study explores the effect of Proteus in causing cognitive and behavioral changes in animal models and it further goes to the neuronal level to investigate how it affects the structural profile of striatal dopaminergic neurons.
This study provides compelling evidence that intestinal colonization by *Proteus mirabilis* can trigger Parkinson’s disease (PD)-like neuropathological features in mice. Using a combination of fecal cultures, behavioral assays, histological analyses, and molecular techniques, the authors demonstrated a strong association between gut infection and neurodegeneration. Mice orally administered *P. mirabilis* exhibited significant bacterial colonization in feces, confirming successful gut infection. Behavioral testing revealed marked impairments in motor coordination and cognitive functions, resembling clinical symptoms of PD.

Histopathological evaluation through Golgi-Cox staining and Sholl analysis revealed pronounced dendritic degeneration and reduced arborization in medium spiny neurons of the striatum, indicating synaptic dysfunction. Furthermore, immunofluorescence staining showed enhanced accumulation of α-synuclein aggregates in both the colon and various brain regions (notably the substantia nigra and striatum), consistent with Braak’s hypothesis that misfolded α-synuclein may propagate from the gut to the brain via the vagus nerve.

Molecular analysis supported these pathological findings, showing decreased expression of tyrosine hydroxylase (TH), a marker for dopaminergic neurons, suggesting significant dopaminergic cell loss. Additionally, elevated levels of glial fibrillary acidic protein (GFAP) pointed to astroglial activation and neuroinflammation. Notably, these PD-like changes were similar to those seen in rotenone-induced models, a well-established toxin-based model of PD.

Together, the findings support the notion that gut microbiota, specifically *P. mirabilis*, may play a causal role in PD by initiating synucleinopathy, neuroinflammation, and dopaminergic neurodegeneration. This highlights a novel potential mechanism in PD pathogenesis and suggests the gut-brain axis as a promising therapeutic target.
DOI: 10.17632/jypsd478f6.1
title: Berwickshire Marine Reserve 2023-2024 horse mussel (Modiolus modiolus) data with survey details, summary data, and location data

description: With the help of Scottish Marine Environmental Enhancement Fund (SMEEF), Blue Marine Foundation, Project Baseline, Berwickshire Marine Reserve (BMR) and St Abbs Marine Station gathered horse mussel (Modiolus modiolus) data in the Berwickshire Marine Reserve off the SE coast of Scotland. These datasets include a summary of the different transects conducted and approximate GPS locations of recorded horse mussel individuals (live) and shells. Data were collected in 2023 and 2024. Details on the survey methodology and data processing can be found in the report submitted to SMEEF (details to follow). The data highlight five locations that may meet Priority Marine Feature (PMF) requirements for semi-infaunal horse mussel beds.
DOI: 10.17632/wvp9tksn72.1
title: SDNCampus Dataset

description: The SDNCampus dataset provides a collection of flow statistics data across thirty applications available in a campus and other enterprise networks. It serves as a valuable resource for developing and evaluating deep learning models intended for precisely classifying applications generating traffic in a network.
Key Features:
The dataset precisely documents and labels thirty applications organized in single file for each application. To ensure inclusivity, a range of applications which are found on conventional computers, smart phones and Internet of Things (IoT) gadgets is represented. Efforts have been made to maintain a balanced distribution of samples across applications classes to enhance model training efficacy and generalization.
DOI: 10.17632/mw5ntyrc82.1
title: Supplemental Material for Personalized UVA1 Phototherapy Strategies for Steroid-Refractory Hand-Foot Eczema: A Prospective Study

description: Supplemental Material for: Personalized UVA1 Phototherapy Strategies for Steroid-Refractory Hand-Foot Eczema: A Prospective Study

This supplemental file provides additional figures and a table supporting the main findings of the study.

Contents:

Supplemental Figure 1: Representative cases of hand eczema patients undergoing UVA1 phototherapy in both low and high-frequency treatment cohorts. The figure illustrates the progression of skin lesions in patients with fissured and hyperkeratotic conditions, as well as those with dyshidrotic or recurrent vesicular eczema, at various treatment timepoints.
Supplemental Figure 2: UVA1 phototherapy outcomes in hand-foot eczema patients with different lesion types across low and high-frequency regimens after 15 sessions. The figure shows the proportions of patients achieving HECSI-75 and HECSI-90 response rates.
Supplemental Figure 3: Additional UVA1 phototherapy outcomes, including changes in HF-Peak Pruritus NRS and HF-Peak Pain NRS scores, recurrence times, and the correlation between initial palmar epidermal thickness and the number of treatments needed to reach IGA 0/1.
Supplemental Table 1: Baseline demographics and clinical characteristics of the study participants, comparing the low-frequency and high-frequency treatment groups.
These supplemental materials provide detailed clinical data and visual documentation to enhance the interpretation of the study results.
DOI: 10.17632/x5fkgwtmhz.1
title: Optimorph Simulation Dataset

description: This dataset provides detailed urban building energy modeling (UBEM) simulation data for various urban block configurations in Tehran, Iran. The data was generated using a parametric modeling workflow in Grasshopper, incorporating multiple urban morphological parameters.
DOI: 10.17632/2n9b33xfry
title: Personal Data Protection System and Capital Market Pricing Efficiency

description: Our analysis draws upon data from A-share listed companies on the Shanghai and Shenzhen Stock Exchanges between 2016 and 2023—a period that coincides with China’s progressive data governance reforms, triggered by the enactment of the Cybersecurity Law in 2016. Firm-level data is obtained from the China Stock Market and Accounting Research (CSMAR) database. To ensure sample quality, financial sector entities are excluded due to their distinct regulatory environment, followed by the removal of firms with special treatment (ST) or particular transfer (PT) status, which signal abnormal financial conditions. Observations with incomplete variable coverage are also excluded. Continuous variables are winsorized at the 1st and 99th percentiles to mitigate the influence of outliers, yielding a final sample of 27,449 firm-year observations.
DOI: 10.17632/2n9b33xfry.1
title: Personal Data Protection System and Capital Market Pricing Efficiency

description: Our analysis draws upon data from A-share listed companies on the Shanghai and Shenzhen Stock Exchanges between 2016 and 2023—a period that coincides with China’s progressive data governance reforms, triggered by the enactment of the Cybersecurity Law in 2016. Firm-level data is obtained from the China Stock Market and Accounting Research (CSMAR) database. To ensure sample quality, financial sector entities are excluded due to their distinct regulatory environment, followed by the removal of firms with special treatment (ST) or particular transfer (PT) status, which signal abnormal financial conditions. Observations with incomplete variable coverage are also excluded. Continuous variables are winsorized at the 1st and 99th percentiles to mitigate the influence of outliers, yielding a final sample of 27,449 firm-year observations.
DOI: 10.17632/9hgnbmxtpf.1
title: Bibliometric Dataset (Geography in Educational Technology)

description: Scopus database as of 18 October 2024 (Geography in Educational Technology)
DOI: 10.17632/hx662zxrbr.1
title: An Exact Empirical Model of Adsorption Equilibria of Mesoporous Materials as Adsorbents for Performance Prediction of Solar-Powered Integrated Refrigeration Systems

description: This data set contains all the spline coefficients obtained via cubic spline interpolation (in the same order as shared) including:

1. Functional dependence of specific heat capacity of MIL-101(Cr) on adsorption/desorption bed temperature
2. Functional dependence of heat of adsorption of MIL-101(Cr) on adsorption/desorption bed temperature
3. Functional dependence of specific heat capacity of silica-gel on adsorption/desorption bed uptake
4. Functional dependence of heat of adsorption of silica-gel on adsorption/desorption bed uptake
5. Adsorption Isotherm (uptake v.s. relative pressure) of silica-gel
6. Adsorption Isotherm (uptake v.s. relative pressure) of MIL-101(Cr) 
7.Desorption Isotherm (uptake v.s. relative pressure) of MIL-101(Cr) 
8. Functional dependence of diffusion coefficient of water molecules in LiBr/water solution upon concentration and temperature
9. Functional dependence of specific heat capacity of Aluminum heat exchanger on temperature
10. Functional dependence of specific heat capacity of Copper heat exchanger on temperature
11. Functional dependence of specific heat capacity of water on temperature
12. Functional dependence of specific heat capacity of saturated water vapor on temperature
13. Functional dependence of specific heat capacity of latent heat of vaporization of water on temperature

Finally, the entire zipped code for simulation of stand-alone silica-gel/water adsorption chiller has also been shared here with the name: stand_alonesilica_gel_ads_chiller.zip. It runs by first unzipping this file in a folder, opening this folder in MATLAB command window, and typing "adsorption_chiller_test" at the command prompt. After this code runs successfully, it will save a number of .dat files in the folder out of which only two are important namely "Perfor.dat" and "DATA.dat". Perfor.dat consists of the same number of rows as the total number of cycles, its first column represents the COP values for each cycle, while the second and the third one represents the solar COP and SCP values for each cycle, respectively. The "DATA.dat" file has 21 columns and more than 9000,000 rows each of which represents a time-step in simulation. The columns can be represented as follows: 1. adsorption bed temp, 2. desorption bed temp, 3. evaporator temperature, 4. adsorption bed pressure, 5. desorption bed pressure, 6. adsorption bed uptake, 7. desorption bed uptake, 8. hot water storage tank temp, 9. Mass of liquid water in evaporator, 10. refrigeration power, 11. heating power, 12. driving temp, 13. incremental COP values, 14. relative pressure in adsorption bed, 15. relative pressure in desorption bed, 16. chilled water inlet temp, 17. cooling water inlet temp, 18. heating water inlet temp, 19. heating water outlet temp, 20. chilled water outlet temp, 21. cooling water outlet temp
DOI: 10.17632/hx662zxrbr.2
title: A Novel Design Based on Experimentally Exact Adsorption Equilibrium of Integrated Absorption-Adsorption Refrigeration System with Mass Recovery Cycle

description: This data set contains all the spline coefficients obtained via cubic spline interpolation (in the same order as shared) including:

1. Functional dependence of specific heat capacity of MIL-101(Cr) on adsorption/desorption bed temperature
2. Functional dependence of heat of adsorption of MIL-101(Cr) on adsorption/desorption bed temperature
3. Functional dependence of specific heat capacity of silica-gel on adsorption/desorption bed uptake
4. Functional dependence of heat of adsorption of silica-gel on adsorption/desorption bed uptake
5. Adsorption Isotherm (uptake v.s. relative pressure) of silica-gel
6. Adsorption Isotherm (uptake v.s. relative pressure) of MIL-101(Cr) 
7.Desorption Isotherm (uptake v.s. relative pressure) of MIL-101(Cr) 
8. Functional dependence of diffusion coefficient of water molecules in LiBr/water solution upon concentration and temperature
9. Functional dependence of specific heat capacity of Aluminum heat exchanger on temperature
10. Functional dependence of specific heat capacity of Copper heat exchanger on temperature
11. Functional dependence of specific heat capacity of water on temperature
12. Functional dependence of specific heat capacity of saturated water vapor on temperature
13. Functional dependence of specific heat capacity of latent heat of vaporization of water on temperature

Finally, the entire zipped code for simulation of stand-alone silica-gel/water adsorption chiller has also been shared here with the name: stand_alonesilica_gel_ads_chiller.zip. It runs by first unzipping this file in a folder, opening this folder in MATLAB command window, and typing "adsorption_chiller_test" at the command prompt. After this code runs successfully, it will save a number of .dat files in the folder out of which only two are important namely "Perfor.dat" and "DATA.dat". Perfor.dat consists of the same number of rows as the total number of cycles, its first column represents the COP values for each cycle, while the second and the third one represents the solar COP and SCP values for each cycle, respectively. The "DATA.dat" file has 21 columns and more than 9000,000 rows each of which represents a time-step in simulation. The columns can be represented as follows: 1. adsorption bed temp, 2. desorption bed temp, 3. evaporator temperature, 4. adsorption bed pressure, 5. desorption bed pressure, 6. adsorption bed uptake, 7. desorption bed uptake, 8. hot water storage tank temp, 9. Mass of liquid water in evaporator, 10. refrigeration power, 11. heating power, 12. driving temp, 13. incremental COP values, 14. relative pressure in adsorption bed, 15. relative pressure in desorption bed, 16. chilled water inlet temp, 17. cooling water inlet temp, 18. heating water inlet temp, 19. heating water outlet temp, 20. chilled water outlet temp, 21. cooling water outlet temp
DOI: 10.17632/72zgvbbbsd
title: Data: The impact of currency market shocks on global bond fund returns and volatility

description: Global bond funds and currency markets
DOI: 10.17632/72zgvbbbsd.1
title: Data: The impact of currency market shocks on global bond fund returns and volatility

description: Global bond funds and currency markets
DOI: 10.17632/hp5ksdrgz5.1
title: LINF_170014300

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/y9mxzcrbbw.1
title: LINF_170014400

description: Methyltransferase-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/7vhwvrg855.1
title: LINF_170014500

description: Myb-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/dvv5grdsj9.1
title: LINF_170015300

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/mxzh4dxybb.1
title: KAP Questionnaire on MTS 2022 triage_raw data

description: Hypothesis: There is a strong correlation between triage knowledge and the execution of triage skills, as well as between triage knowledge and attitudes toward the revised MTS version.
Results: The median MTS scores for knowledge, attitudes, and practice were 69.6% (IQR = 60.9% - 73.9%), 40 (IQR = 34-42), and 70.0% (IQR = 60% - 80%), respectively. Significant differences in knowledge scores observed across socio-demographic variables, including age groups (p = 0.005), designation (p = 0.001), educational levels (p = 0.001), types of hospital (p = 0.008), awareness of MTS (p = 0.002), and participation in triage training (p = 0.018). Practice scores varied significantly with gender (p = 0.003), designation (p = 0.001), educational levels (p = 0.001), hospital type (p = 0.001), usage of MTS (p = 0.008), and MyTriage application (p = 0.02) . Post-Bonferroni correction analysis revealed significant knowledge, and practices score differences between nurses and EPs, as well as between AMO and EPs. Furthermore, respondents with doctoral degrees (91.3%, IQR = 91.3) and master's degrees (78.3%, IQR = 69.6 – 82.6) achieved higher median knowledge scores than those with lower qualifications.
DOI: 10.17632/mdgfsf4c4p.1
title: LINF_170015400

description: Lariat debranching enzyme-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/xhxkwzyvhn.1
title: LINF_170015600

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/gpg5s6g8s7.1
title: Talabat

description: Talabat reviews, annotated to 3 class classification (pos,neg,nue) by native arabic speekers
DOI: 10.17632/gpg5s6g8s7.2
title: Talabat

description: Talabat reviews, annotated to 3 class classification (pos, neg, nue) by native arabic speekers
related publications:

- Arabic Sentiment Analysis of Food Delivery Services Reviews
D Mustafa, SM Khabour, AS Shatnawi, E Taqieddin, 2023 International Symposium on Networks, Computers and Communications (ISNCC)

- Customers' sentiment on food delivery services: An Arabic text mining approach, D Mustafa, SM Khabour, AS Shatnawi , International Journal of Information Management Data Insights 4 (2), 100299

- Leveraging sentiment analysis of food delivery services reviews using deep learning and word embedding, D Mustafa, SM Khabour, M Al-Kfairy, A Shatnawi, PeerJ Computer Science 11, e2669
DOI: 10.17632/6tddv74p8k.1
title: [Dataset] Physiochemical characterization of fabricated starch-based nanoscaffolds incorporated with Pocockiella variegata extract-mediated green synthesised copper oxide nanoparticles

description: This dataset presents a comprehensive physicochemical characterization of starch-based nanoscaffolds integrated with copper oxide nanoparticles (CuO NPs) synthesized via a green approach using Pocockiella variegata algal extract. The study focuses on evaluating the structural, morphological, and functional properties of these nanocomposite scaffolds, which combine biodegradable starch polymers with eco-friendly CuO NPs for potential biomedical applications. Key analytical techniques include scanning (SEM) for assessing nanoscaffold porosity and nanoparticle dispersion, X-ray diffraction (XRD) for crystallinity analysis of CuO NPs, and Fourier-transform infrared spectroscopy (FTIR) to identify chemical interactions between starch matrices and nanoparticles. Additional data on thermal stability (via TGA) are provided to assess scaffold durability. By merging natural polymer scaffolds with green-synthesized nanoparticles, this work highlights sustainable strategies for developing advanced biomaterials. The findings are relevant to tissue engineering, wound dressings, or drug delivery systems, emphasizing eco-friendly alternatives to conventional synthetic nanomaterials. Researchers can leverage this dataset to optimize nanoparticle loading, scaffold architecture, and functional performance for targeted biomedical uses.
DOI: 10.17632/spt9yn3p97.1
title: "TÜRK MÜZİĞİ BESTE ve AĞIR SEMÂÎLERİNDE NAKIŞ TERTİPLERİ" MAKALE DATA

description: Data Dosyaları
DOI: 10.17632/spt9yn3p97.2
title: "TÜRK MÜZİĞİ BESTE ve AĞIR SEMÂÎLERİNDE NAKIŞ TERTİPLERİ" MAKALE DATA

description: Data Dosyaları
DOI: 10.21227/vmm8-3269
title: "XCH\u2084 Measurements for High-Resolution Methane Concentration Mapping"

description: "The dataset utilized in this study corresponds to the year 2019 (all months) and covers an extensive region within the Mediterranean Basin. This particular year was selected to investigate seasonal variations in column-averaged dry-air mole fraction of methane (XCH\u2084), providing insights into methane dynamics over different climatic periods.Furthermore, to assess long-term trends in methane emissions in the world, data from four distinct years\u20142019 and 2021\u2014were analyzed, and they cover 4 months (January, April, July, and October). By comparing these periods, we aimed to identify potential increases in atmospheric XCH\u2084 concentrations and detect emerging emission patterns. Specific intervals within these years were carefully selected based on data quality, spatial coverage, and relevance to the research objectives, ensuring robust and reliable methane estimations.For the purposes of this study, two different geographical domains were defined:A global study area, encompassing longitudes from 180\u00b0W to 180\u00b0E and latitudes from 90\u00b0S to 90\u00b0N.A regional study area, focused on longitudes between 1\u00b0E and 40\u00b0E and latitudes between 20\u00b0N and 50\u00b0N, covering a substantial portion of the Mediterranean region.This approach allowed for a comprehensive analysis, integrating both broad-scale atmospheric observations and more localized assessments to enhance the understanding of methane distribution and its temporal evolution."
DOI: 10.17632/m7jzmb7mr9.1
title: [Dataset] Structural and functional profiling of starch-polymer nanoscaffolds enhanced with Ectocarpales-derived biogenic copper oxide nanoparticles

description: This dataset provides a detailed physicochemical and functional evaluation of starch-polymer nanoscaffolds integrated with biogenic copper oxide nanoparticles (CuO NPs) synthesized using Ectocarpales sp., a brown algal extract, as a sustainable reducing agent. The work employs UV-visible spectroscopy (UV-Vis) to confirm CuO NP synthesis and assess optical properties, while Fourier-transform infrared spectroscopy (FT-IR) identifies functional groups and interactions between the starch matrix and nanoparticles. X-ray diffraction (XRD) reveals the crystalline structure and phase purity of CuO NPs, complemented by scanning electron microscopy (SEM) imaging to visualize nanoscaffold morphology, porosity, and nanoparticle distribution. Thermal gravimetric analysis (TGA) evaluates the thermal stability and degradation profiles of the nanocomposite, and dynamic light scattering (DLS) characterizes nanoparticle hydrodynamic size and colloidal stability in suspension. The dataset highlights how Ectocarpales-mediated CuO NPs influence scaffold properties, including enhanced structural integrity, thermal resistance, and controlled particle dispersion. By merging eco-friendly synthesis with advanced material characterization, this resource underscores the potential of algal-derived nanoparticles in reinforcing biodegradable starch scaffolds for biomedical applications, such as tissue engineering or controlled drug delivery. Researchers can leverage this multidisciplinary dataset to correlate synthesis parameters with material performance, optimize nanoparticle loading, and design sustainable nanohybrid systems with tailored structural and functional attributes. The integration of green chemistry principles with robust analytical workflows offers a template for developing eco-conscious biomaterials.