Advancing Open Science

Transition metal sulfides and oxides are attractive for supercapacitor electrodes due to rich redox sites and high theoretical capacitances. Yet single-phase materials suffer from poor structural stability and slow charge transfer, restricting practical applications. Herein, a facile microwave route is developed to prepare Cu₂S/CoO composite electrodes. Experimental results demonstrate that the heterogeneous interface between Cu₂S and CoO induces a prominent synergistic effect, which greatly boosts the redox activity of the electrode. The optimized Cu₂S/CoO composite exhibits a specific capacitance of 2898 F g⁻¹ at 1 A g⁻¹, and maintains 84.1% of its initial capacitance after 30,000 continuous cycles, revealing remarkable cycling durability. The asymmetric supercapacitor fabricated with the Cu₂S/CoO negative electrode delivers an energy density of 186.45 Wh kg⁻¹ at a power density of 800.02 W kg⁻¹, and this performance outperforms most recently reported analogous electrode systems. This research offers a practical route for the fast fabrication of high-performance bimetallic composite electrodes through microwave treatment, and supplies useful references for the structural engineering and performance optimization of advanced electrochemical energy storage materials.

Digital transformation is a strategic priority across care-intensive service sectors, yet many organisations struggle to realise its intended benefits. Existing research often examines technological, organisational, and environmental barriers separately, offering limited insight into their interconnections within organisational systems. Drawing on Systems Theory and Sociotechnical Systems (STS) Theory, this study investigates digital transformation among small and medium providers within Australia’s National Disability Insurance Scheme (NDIS). Using an interpretive qualitative design, semi-structured interviews were conducted with 15 participants from 15 distinct NDIS provider organisations in Sydney, Australia, followed by reflexive thematic analysis and systems-oriented interpretation. Participants described recurring associations among technological misalignment, fragmented software, adaptive workarounds, increased administrative demands, and constraints on organisational capacity for digital improvement, with regulatory and resource pressures interacting with these technological and organisational conditions. Building on these cross-sectional patterns, this study develops Recursive Capability Constriction (RCC), a systems-based conceptual framework that proposes how technological misalignment, compensatory adaptation, administrative expansion, and constrained organisational capability for digital improvement may become interconnected through reinforcing relationships. Rather than representing an inevitable or empirically established causal sequence, RCC provides a conditional explanation of how local adaptations may become associated with constraints on subsequent digital improvement. By shifting attention from isolated implementation barriers to interconnected sociotechnical relationships, RCC extends digital transformation research and provides practical guidance for managing digital change in regulated care environments.

Efficient generation of tumor-specific cytotoxic T lymphocytes (CTLs) remains challenging. Although mRNA-based approaches enable the delivery and expression of diverse tumor-specific antigens, unmodified mRNA can trigger innate immune responses that suppress translation. Here, we investigated whether 1-methyl-pseudouridine (m¹Ψ)-modified mRNA enhances antigen expression in human dendritic cells (DCs) and promotes the induction of antigen-specific CTLs, using survivin and MART-1 as model tumor-associated antigens. Remarkably, m¹Ψ modification increased protein production in DCs by up to 20-fold compared with unmodified mRNA. DCs transfected with m¹Ψ-modified mRNAs efficiently primed survivin- and MART-1-specific CD8⁺ T cells from autologous peripheral blood mononuclear cells of healthy donors, as demonstrated by HLA class I peptide–MHC dextramer staining. Expanded CTL lines exhibited potent effector functions, including IFN-γ production, CD107a mobilization, and robust cytotoxicity against peptide-pulsed T2 cells and tumor cell lines expressing survivin or MART-1. Translation of the engineered mRNA variants in human HeLa cells and DCs is strongly dependent on the poly(A) tail. Together, these findings demonstrate that m¹Ψ modification substantially enhances antigen expression and supports the efficient generation of functional, antigen-specific CTLs, providing a promising platform for next-generation mRNA-based cancer vaccines and adoptive T-cell therapies.

Prostaglandin E2 (PGE₂) signalling influences amyloid-β (Aβ) processing, myeloid function, and neuronal injury in Alzheimer’s disease (AD). Although EP2 and EP4 share Gs–cyclic adenosine monophosphate (cAMP) signalling, their cellular effects differ. This review integrates genetic, pharmacological, ageing, and AD-model evidence to assess receptor-selective targeting. EP2 deletion enhances myeloid Aβ handling and reduces microglia-mediated neuronal injury in experimental systems, providing a rationale for selective EP2 inhibition. In aged mice, PGE₂–EP2 signalling redirects glucose towards glycogen storage and restricts myeloid mitochondrial respiration; benefits from a predominantly peripheral antagonist suggest that some age-related outcomes may improve without high brain exposure. Chronic antagonist studies in AD models, however, show variable effects on inflammation, amyloid burden, and behaviour. EP4 exhibits contrasting cell-dependent actions: activation supports microglial Aβ uptake and inflammatory control, whereas signalling in some amyloid precursor protein (APP)-expressing cells promotes APP internalisation and Aβ production. Human AD evidence remains mainly tissue-based; EP2 antagonist testing has involved healthy volunteers, not patients with AD. These findings indicate that receptor selectivity alone is insufficient to predict therapeutic outcomes. Further studies should combine cell-specific receptor manipulation, measurements of central and peripheral exposure, and separate assessments of Aβ production, clearance, tissue injury, and functional outcomes.

Ultraviolet radiation is increasingly used as a controllable physical technology for crop disease management, but inconsistencies in parameter reporting, the validation scale, and engineering evidence hinder cross-study comparisons and practical translation. Following the PRISMA 2020 statement, this systematic review searched the Web of Science Core Collection and IEEE Xplore, screened eligible studies, and conducted full-text data extraction and structured coding. A total of 80 studies were evaluated across four domains: UV treatment parameter reporting, highest validation level, translational maturity, and engineering characteristics of application equipment. The treatment frequency or number of applications and wavelength were explicitly reported in 83.8% and 76.3% of studies, respectively, whereas irradiance and post-treatment light or dark conditions were reported in only 36.3% and 35.0%. In 57.5% of studies, the highest validation level remained limited to in vitro pathogen assays, detached-material experiments, or controlled-environment whole-plant experiments; low and low-medium translational maturity together accounted for 62.5%. Among the 11 equipment-related studies included in this review, the operating speed and target-surface dose calibration were reported more frequently than within-canopy dose uniformity, shading effects, and operational control. UV-based crop disease control is progressing toward field and equipment applications, but incomplete parameter reporting, discontinuities in the production-scale evidence chain, and unstable dose delivery still constrain reproducibility and scale-up. Future research should establish minimum reporting standards, strengthen multi-site and multi-season validation, translate biologically effective doses into equipment operating parameters, and develop closed-loop control based on actual target-surface dose monitoring.

The IFNAR2 gene encodes an essential component of the type I interferon receptor, which is essential for antiviral defense. It has been proven that the severity of COVID-19 may be influenced by the genetic variants in IFNAR2; however, the results are inconclusive in the African cohorts. Thus, in this study, we investigate the association between three IFNAR2 SNPs and the critical form of COVID-19 in the Tunisian population. A total of 413 COVID-19 patients classified as hospitalized with critical illness (ICU) (n = 46) and non-hospitalized (n = 367) are included. Genotyping of three IFNAR2 polymorphisms (rs1051393, rs2236757, rs9984273) was performed using Taq Man RT-PCR assays. rs2236757 (OR = 0.31, 95% CI: 0.16–0.60), p = 4 × 10⁻⁴) and rs9984273 (OR = 0.41, 95% CI: 0.22–0.76, p = 0.0055) were associated with COVID-19 severity with a potential protective effect. However, rs1051393 did not show a significant association with disease severity. Additionally, exploratory haplotype analysis suggested a possible protective association for the TAC haplotype (OR = 0.11, 95% CI: 0.02–0.86, p = 0.036), based on a very small number of carriers and not significant after correction for multiple testing. The GAC haplotype, absent from ICU patients, yielded a continuity-corrected OR of 0.03 (95% CI [0.002–0.53]); this estimate rests on a zero cell and is hypothesis-generating only. These preliminary findings, obtained from a single-center cohort with a limited number of critically ill patients, warrant replication in larger, independent, and multicentric populations.

Bacillus subtilis is an extensively characterized Gram-positive bacterium with broad applications in agriculture, biotechnology, and biocontrol. Strain SNUY1, known for its antifungal properties and use as an edible coating, has been completely sequenced and deposited in NCBI (accession: CP199918), making it an important model for genomic and functional characterization. Here, we present the MAYA pipeline, a fully automated, rule-based Snakemake workflow that integrates eighteen bioinformatic tools into a single end-to-end framework. MAYA accepts either raw Illumina paired-end FASTQ reads or pre-assembled FASTA sequences, utilizing per-rule Conda environment isolation to ensure strict version control and reproducibility across all constituent tools from quality control and assembly through functional annotation, plasmid typing, and detection of biosynthetic and antimicrobial resistance gene clusters. To benchmark pipeline accuracy across both input modes, MAYA was evaluated using Bacillus subtilis subsp. subtilis str. 168(AL009126 OZ025638). The FASTA assembly yielded a circularized 4,215,606 bp chromosome (N50: 4.21 Mb, 43.51% GC) with 98.28% CheckM completeness and 100.0% BUSCO ortholog recovery. Prokka annotation predicted 4214 CDSs (86 tRNAs, 30 rRNAs) in FASTA mode compared to 4313 CDSs (106 tRNAs, 25 rRNAs) in FASTQ mode, reflecting expected read fragmentation in unassembled data. DIAMOND mapping against SwissProt yielded 4135 hits (99.90% mean identity) in FASTA mode and 4170 hits (99.75% mean identity) in FASTQ mode. Both modes identified identical ST1 Multilocus Sequence Typing (MLST) profiles and six core AMR determinants (mphK, vmlR, rphC, aadK, satA_Bsub, and tet(L)), while antiSMASH detected 15 biosynthetic gene cluster (BGC) regions (22 protoclusters) in FASTA mode versus 16 regions (23 protoclusters) in FASTQ mode. MOB-suite resolved two non-mobilizable plasmids in the FASTQ assembly (bioproject: PRJNA76): pAC670 and a novel 1666 bp plasmid. Furthermore, nucleotide BLASTN analysis resolved a 76-CDS discrepancy between published NCBI annotations and MAYA/Prokka, demonstrating 95.5% (4081/4272) stringent sequence match and confirming that differences stem from gene-model predictions rather than omitted loci. To demonstrate the FASTA-mode application workflow, the complete SNUY1 (NZ_CP199918) genome assembly was processed through MAYA, yielding a single, contiguous chromosome of 4,196,931 base pairs with a GC content of 43.69% (98.28% CheckM, 100% BUSCO completeness). Annotation identified 4196 coding sequences, while antiSMASH profiling revealed 13 candidate biosynthetic gene cluster (BGC) regions comprising 20 protoclusters (including NRPS, lanthipeptides, terpenes, and sactipeptides), aligning with the strain’s biocontrol capabilities. AMR profiling identified six chromosomally encoded resistance genes (mphK, vmlR, rphC, aadK, satA_Bsub, and tet(L)). In silico mobility analysis via MOB-suite demonstrated that these sequences lack functional conjugation machinery and are classified as non-mobilizable. Executing in 3–4 h on an Intel Xeon server (128 GB RAM, 29 CPU cores), MAYA delivers an efficient, audit-ready framework for end-to-end bacterial genomic profiling.

Background: Portal venous phase (PVP) contrast-enhanced CT is a cornerstone for response assessment in early-phase oncology trials, yet contrast-enhancement phase timing remains insufficiently monitored across sites. We assessed PVP timing using a validated artificial intelligence (AI) quality control tool (CECT-QC). Methods: In this retrospective multicenter study, 402 CT examinations from 402 patients enrolled in phase I oncology trials across three European institutions were analyzed using CECT-QC, which quantifies aortic and portal venous enhancement to classify contrast-enhancement phase. The primary analysis included 335 standard CT examinations. Optimal PVP classification was compared (i) across institutions, (ii) before vs. after French regulatory changes impacting contrast delivery, and (iii) across scanner technologies (photon-counting CT [PCCT] vs. standard CT). Results: Among the 335 standard CT examinations included in the primary analysis, 53.1% (178/335) were classified by CECT-QC as optimal PVP. Optimal PVP rates were 39.0% (32/82) at Institution A, 56.9% (87/153) at Institution B, and 59.0% (59/100) at Institution C, with a significant adjusted institutional association (p = 0.039). No significant temporal association was observed before versus after the legislative change (p = 0.716). At Institution A, standard CT was associated with higher odds of optimal PVP classification than PCCT (OR 2.24, 95% CI 1.07–4.68; p = 0.031), while PCCT showed higher aortic and portal venous attenuation (both p < 0.001). Conclusions: Approximately half of standard CT examinations in phase I oncology trials were classified as optimal PVP. Classification varied significantly across institutions and by scanner technology, whereas no significant temporal association was observed before versus after the legislative change. These findings support continued quality-control monitoring, protocol harmonization, and adaptation of classification tools to emerging CT platforms.