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Code and results for "Non-exonic read content reorganises lncRNA networks and masks tumour cell programmes in renal cancer". Bulk and single-cell RNA-seq pipelines in R.

2.0.0-alpha.3 (2026-10-06) 🐞 Bug Fixes particle centres include shifts; skip filament objects (v2.0) (#168) (dbf73ef)

The study examined the relationship between oxidative stress markers (SOD, CAT, GPX, AND MDA) and anthropometric parameters (BMI, WC, WHR, WHTR, BRI, AND VAI) among patients with type 2 diabetes melli…

The study examined the relationship between oxidative stress markers (SOD, CAT, GPX, AND MDA) and anthropometric parameters (BMI, WC, WHR, WHTR, BRI, AND VAI) among patients with type 2 diabetes mellitus. In carrying out this study, comparative cross-sectional study was adopted. The study population consisted of one hundred (100) diagnosed type 2 diabetic patients and one hundred (100) apparently healthy, age- and sex-matched non-diabetic individuals who served as controls. All participants were aged between 30 and 70 years. Ten (10) mL of venous blood samples were collected from each participant after overnight fast using standard aseptic procedures and distributed into appropriate “...for the determination of lipid profile parameters, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Serum and plasma were prepared by centrifugation at 3000 rpm for 10 minutes, while whole blood was used for selected analyses. The samples were analyzed using standard laboratory methods. Data obtained were analyzed using Statistical Package for Social Sciences (SPSS) version 25.0. Results were expressed as Mean ± Standard Deviation. The test of significance was determined using independent samples t-test, while Pearson correlation analysis was used to assess relationships between variables, with p < 0.05 considered statistically significant. the results showed a significant negative correlation between SOD and BRI (r = −0.207, p = 0.039). CAT showed significant negative correlations with BMI (r = −0.402, p < 0.001), WC (r = −0.329, p = 0.001), and WHtR (r = −0.211, p = 0.035), but xsignificant positive correlations with WHR (r = 0.287, p = 0.004) and BRI (r = 0.359, p < 0.001). MDA showed significant positive correlations with BMI (r = 0.337, p = 0.001), WC (r = 0.222, p = 0.027), and BRI (r = 0.265, p = 0.008). No statistically significant relationships were observed between GPx and the anthropometric parameters, or between VAI and the oxidative stress markers.

Circuits, simulation results and scripts for the numerical results of E. Weilandt, T. Peham, R. Wille, "Synthesis of Fault-tolerant State Preparation Circuits using Steane-type Error Detection", Phys.…

Circuits, simulation results and scripts for the numerical results of E. Weilandt, T. Peham, R. Wille, "Synthesis of Fault-tolerant State Preparation Circuits using Steane-type Error Detection", Phys. Rev. A (2026), doi:10.1103/y9ln-b4t9.The record contains the following:- the four state-preparation circuits per code synthesized with fault-set-guided synthesis, for the [[17,1,5]], [[19,1,5]], [[25,1,5]], [[20,2,6]], [[31,1,7]] and [[37,1,7]] codes (OpenQASM 2);- the flag-at-origin baseline circuits used for comparison;- the logical error and acceptance rates from circuit-level Stim simulations;- the lookup-table decoder used for the [[31,1,7]] code;- the numbers of the results table;- scripts to check the table against the files, to regenerate the results figure, and to run the simulations.See README.md for the mapping between files and the paper.The implementation is part of MQT QECC (https://github.com/munich-quantum-toolkit/qecc). Version 2 of this record will add a frozen snapshot of the source code and the circuit-synthesis notebooks.

The endothelial protein C receptor (EPCR) has emerged as a clinically significant biomarker for a distinct subgroup of triple-negative breast cancers (TNBC), where its overexpression is associated wit…

The endothelial protein C receptor (EPCR) has emerged as a clinically significant biomarker for a distinct subgroup of triple-negative breast cancers (TNBC), where its overexpression is associated with stem-like tumour phenotypes and poor prognosis. Rapid and accessible detection of EPCR is therefore important for future diagnostic stratification. In this study, we present a new electrochemical immunosensor for EPCR detection based on a graphene–arginine (G-Arg) nanointerface synthesised via fluorographene chemistry. The G-Arg layer provides abundant carboxyl groups, enabling efficient EDC/Sulfo-NHS-mediated covalent immobilisation of anti-EPCR antibodies and formation of a stable electrochemically active biointerface. The resulting immunosensor exhibited a linear impedimetric response to EPCR over the 49.6–496 ng mL−1 range, with a calculated detection limit of 10.48 ng mL−1, together with good selectivity against non-specific proteins. In addition, the analytical signal remained stable after 30 days of ambient storage, indicating good operational stability. Preliminary experiments further confirmed sensor functionality in human plasma, where a distinguishable response was observed between non-spiked and EPCR-spiked samples. Overall, this work introduces a new G-Arg-based electrochemical platform for EPCR detection and provides a basis for further development of biosensing strategies targeting aggressive breast cancer biomarkers.

Precomputed promoter-background score distributions for the PscanR transcription factor binding motif enrichment package, for the JASPAR 2024 CORE motif collection. The record holds 35 backgrounds: se…

Precomputed promoter-background score distributions for the PscanR transcription factor binding motif enrichment package, for the JASPAR 2024 CORE motif collection. The record holds 35 backgrounds: seven genome assemblies (hg38, hs1, mm10, mm39, dm6, sacCer3, TAIR9) times five promoter windows (200u_50d, 450u_50d, 500u_0d, 950u_50d, 1000u_0d, i.e. bp upstream/downstream of the TSS). Files are named <collection>_<assembly>_<window>_<annotation>.psbg2.txt and are tab-separated tables of per-motif background statistics. SHA256SUMS_J2024.txt lists the SHA-256 checksums.The files are served individually to R users through Bioconductor's ExperimentHub by the PscanRBackgrounds package (https://github.com/Federico77z/PscanRBackgrounds) and read by PscanR (https://github.com/Federico77z/PscanR). The same files, together with the other JASPAR releases, are archived as a single ZIP in record 10.5281/zenodo.21821764.

Precomputed promoter-background score distributions for the PscanR transcription factor binding motif enrichment package, for the JASPAR 2022 CORE motif collection. The record holds 35 backgrounds: se…

Precomputed promoter-background score distributions for the PscanR transcription factor binding motif enrichment package, for the JASPAR 2022 CORE motif collection. The record holds 35 backgrounds: seven genome assemblies (hg38, hs1, mm10, mm39, dm6, sacCer3, TAIR9) times five promoter windows (200u_50d, 450u_50d, 500u_0d, 950u_50d, 1000u_0d, i.e. bp upstream/downstream of the TSS). Files are named <collection>_<assembly>_<window>_<annotation>.psbg2.txt and are tab-separated tables of per-motif background statistics. SHA256SUMS_J2022.txt lists the SHA-256 checksums.The files are served individually to R users through Bioconductor's ExperimentHub by the PscanRBackgrounds package (https://github.com/Federico77z/PscanRBackgrounds) and read by PscanR (https://github.com/Federico77z/PscanR). The same files, together with the other JASPAR releases, are archived as a single ZIP in record 10.5281/zenodo.21821764.

Abstract: The increasing use of online shopping and social media has contributed to a rise in impulsive buying behaviour among teenagers, with peer influence playing a significant role in shaping pur…

Abstract: The increasing use of online shopping and social media has contributed to a rise in impulsive buying behaviour among teenagers, with peer influence playing a significant role in shaping purchasing decisions. This study examined the relationship between peer influence and impulsive buying behaviour among Maldivian teenagers and determined whether peer influence significantly predicts impulsive buying behaviour. A quantitative cross-sectional research design was employed, and data were collected from 255 teenagers using a structured questionnaire. Data were analysed using descriptive statistics, Pearson's correlation, and simple linear regression. The findings revealed a significant moderate positive relationship between peer influence and impulsive buying behaviour (r = 0.523, p < 0.001). Regression analysis showed that peer influence significantly predicted impulsive buying behaviour (β = 0.523, p < 0.001), explaining 27.4% of the variance (R² = 0.274). These results indicate that teenagers who experience greater peer influence are more likely to make spontaneous and unplanned purchasing decisions. The findings support the Stimulus–Organism–Response (S-O-R) Theory and contribute to the limited literature on adolescent consumer behaviour in the Maldives. The study highlights the importance of promoting financial literacy and awareness of peer influence to encourage responsible purchasing behaviour among teenagers.

Precomputed promoter-background score distributions for the PscanR transcription factor binding motif enrichment package, for the JASPAR 2020 CORE motif collection. The record holds 35 backgrounds: se…

Precomputed promoter-background score distributions for the PscanR transcription factor binding motif enrichment package, for the JASPAR 2020 CORE motif collection. The record holds 35 backgrounds: seven genome assemblies (hg38, hs1, mm10, mm39, dm6, sacCer3, TAIR9) times five promoter windows (200u_50d, 450u_50d, 500u_0d, 950u_50d, 1000u_0d, i.e. bp upstream/downstream of the TSS). Files are named <collection>_<assembly>_<window>_<annotation>.psbg2.txt and are tab-separated tables of per-motif background statistics. SHA256SUMS_J2020.txt lists the SHA-256 checksums.The files are served individually to R users through Bioconductor's ExperimentHub by the PscanRBackgrounds package (https://github.com/Federico77z/PscanRBackgrounds) and read by PscanR (https://github.com/Federico77z/PscanR). The same files, together with the other JASPAR releases, are archived as a single ZIP in record 10.5281/zenodo.21821764.