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PubMed2026

Retrosigmoid craniotomy surgical guide: The way forward for precise exposure of the transverse-sigmoid sinuses.

INTRODUCTION: The retrosigmoid craniotomy is the workhorse approach to the cerebellopontine angle. Accurate localisation of the transverse-sigmoid junction (TSJ) is key for optimised exposure and cerebellar retraction. Various methods, both anatomical and navigational, have been used but with suboptimal results. We utilised a 3D-printed retrosigmoid surgical guide in an attempt to overcome this and report our early outcomes and experiences in the design, production and utilisation of the guide. METHODS: This is a prospective cohort study of the patients with retrosigmoid craniotomies performed using the surgical guides. Patient demographics and diagnoses, along with the accuracy of the planned burrhole and craniotomy, need for craniotomy extension, presence of venous sinus injury, set-up time, and cost were reported. RESULTS: There were ten cerebellopontine angle cases in which the surgical guides were utilised, three petrous meningiomas, two trigeminal neuralgias, two metastasis, and three other tumours. The planned burrhole and craniotomy were precise in all cases with accurate exposure of the TSJ and no requirement for craniotomy extension. The mean set up time was 3.9 min, and the mean cost of the surgical guides was USD 470.90. One elderly patient had an intraoperative transverse sinus injury related to adherent dura that was planned for exposure. CONCLUSION: The 3D-printed surgical guide is a potential solution to the rapid, precise and consistent identification of the TSJ when performing a retrosigmoid craniotomy. We present our early experience and discuss nuances in the designing, production, and intraoperative phases to optimise the precision of this guide. We suggest two methods to avoid sinus injury in elderly patients: either to plan the craniotomy to the edge of the sinus, or to plan sinus exposure but to use burr drills rather than the osteotome, as in our case, to expose the sinus.

Humans↗
PubMed2026

Mitigating pH-induced instability in deruxtecan-based ADCs: an onboard-mixing icIEF approach for robust charge heterogeneity characterization.

Accurate charge variant analysis of antibody-drug conjugates (ADCs) is essential for understanding product heterogeneity and ensuring quality control. However, Deruxtecan (DXd)-based ADCs present a unique analytical challenge due to the intrinsic instability of the payload, where the lactone ring readily undergoes hydrolysis under alkaline conditions, resulting in time-dependent shifts in charge distribution during imaged capillary isoelectric focusing (icIEF). In this study, we describe the development of an onboard-mixing icIEF method designed to minimize pH-induced degradation during sample preparation. By separating ADC samples from carrier ampholytes (CAs) prior to injection and enabling real-time mixing within the instrument, this approach effectively suppresses premature lactone ring opening and stabilizes charge variant profiles. Comparative studies between conventional premixing and onboard-mixing approach demonstrated that the latter significantly enhances reproducibility, particularly for acidic variants that are highly sensitive to structural conversion. Comprehensive method validation confirmed excellent precision, linearity, and sensitivity, with consistent performance across run-to-run and intra-day analyses. The results underscore the importance of controlling microenvironmental pH exposure in the analysis of chemically instable ADCs. The proposed onboard-mixing strategy provides a robust and efficient solution for icIEF-based characterization, reducing analytical artifacts while simplifying method development. This approach is broadly applicable to ADCs and other biotherapeutics containing pH-sensitive functional groups.

Hydrogen-Ion Concentration↗
PubMed2026

Approaches to observational study designs and analytical options to evaluate the safety of multi-dose vaccines: a systematic review.

INTRODUCTION: Observational studies require careful considerations when evaluating the safety of multidose vaccines. We reviewed design and analytical approaches in observational studies evaluating the safety of multidose vaccines in the post-licensure phase. METHODS: EMBASE, MEDLINE, Web of Science, and Scopus (2018-2022) were searched for hypothesis-testing studies evaluating the safety of multidose vaccines. Key features from frequently used designs were extracted. RESULTS: Among 123 eligible studies, cohort (46%) and self-controlled case series (SCCS)/self-controlled risk interval (SCRI) (40%) followed by case-control (12%) were the most common designs, and 15% of studies used multiple designs. Among cohort studies evaluating multiple doses, vaccination date (36%) and cohort entry with time-updated exposure status (32%) were frequent approaches used to define time zero. Twenty-eight percent of cohort studies did not report time zero; all but one evaluated COVID-19 vaccine effect on post-delivery and fertility-related outcomes. For SCCS/SCRI, 64% of studies accounted for event-dependent exposures, mainly by including pre-exposure periods (53%) and modified SCCS model (48%), while 20% employed multiple correction strategies. Among studies using multiple designs, 68% reached consistent conclusions. CONCLUSIONS: SCCS/SCRI and cohort designs dominate multidose vaccine safety studies. Clear reporting on time zero in pregnancy and fertility-related cohort studies, and on addressing event-dependent exposures in SCCS/SCRI studies is needed, along with guidance on interpreting results from multiple designs.

Humans↗
PubMed2026

Therapeutic approaches for the treatment of bovine metritis: a systematic review of clinical, reproductive and productive outcomes.

Bovine metritis is a complex multifactorial disease associated with substantial clinical and economic impact due to reduced milk production, subfertility, and increased culling rates. Considerable uncertainty remains regarding the comparative efficacy of the many therapeutic strategies used to manage it. This systematic review aimed to summarize and critically evaluate the available evidence on therapeutic approaches for bovine metritis, with respect to clinical cure, reproductive performance, productive performance, and culling. A literature search conducted in PubMed, Web of Science and CABI Digital Library (2010-2025) identified 18 randomized controlled clinical trials eligible for inclusion. Risk of bias was assessed independently by two reviewers using the Cochrane RoB 2 tool. Given substantial clinical and methodological heterogeneity across studies, findings were synthesized narratively by outcome, without meta-analytic pooling, and the certainty of evidence was assessed using GRADE for the comparisons supported by more than one study. Overall, systemic antimicrobial therapies consistently improved short-term clinical cure rates, although their effects on long-term reproductive and productive performance remained inconsistent. In selected cases, nonsteroidal anti-inflammatory drugs (NSAIDs) showed clinical outcomes comparable to antimicrobial treatments, allowing reductions in antimicrobial use ranging from 50% to 92%. Alternative approaches, such as intrauterine flavonoid, chitosan or dextrose-based therapies, produced inconsistent results that appeared to correlate with disease severity and treatment protocol. The evidence base is limited by substantial heterogeneity in disease definitions, postpartum timing of diagnosis, and cure criteria across studies, and by the near-universal absence of allocation concealment in the primary literature; these limitations restrict the certainty of most conclusions to low or moderate. Therefore, effective metritis control should move beyond symptom resolution and incorporate integrated and preventive strategies targeting inflammatory and metabolic dysregulation during the transition period.

Animals↗
PubMed2026

Biomass burning contributions to Mexico City's atmospheric CO2 estimated using a multi-isotope approach.

Fossil fuel combustion dominates anthropogenic emissions worldwide; however, special attention should be addressed to biomass burning, since it is an increasingly important contributor under warmer, drier fire-weather conditions exacerbated by climate change. These emissions could impact the atmospheric composition of heavily urbanized environments. To assess the influence of biomass burning, along with fossil fuels combustion and soil and plant respiration on Mexico City's atmospheric composition, we conducted a year-long (December 2023-December 2024) isotopic monitoring of atmospheric CO2, combining radiocarbon (&#x394;14C), CO2 stable isotopes (&#x3b4;13C, &#x3b4;18O), and CO/CO2 ratios. Once defined the isotopic signatures and the characteristic CO/CO2 that describe the sources, we performed Monte Carlo simulations under two tracer modalities (&#x394;14C + CO/CO2 and &#x394;14C + CO2 stable isotopes) for source apportionment. Results show that during the dry season, particularly in March-April, atmospheric &#x394;14C values approached and overlapped background levels despite Mexico City's fossil-fuel dominance, indicating enhanced non-fossil inputs. Moreover, backward HYSPLIT trajectories supported that these elevated &#x394;14C values coincided with regional wildfire activity. Monte Carlo results attributed up to &#x223c;34 %-60 % of local CO2 to biomass burning in April, followed by March with contributions of &#x223c;31 %-49 %. Since these biomass burning figures contrast with the official emissions inventory of Mexico City metropolitan area, which assigns <1 % of total CO2 emissions to biomass burning, this study could exhibit the emissions inventory underestimation of this source, and thus, the need to reassess and incorporate top-down isotopic constraints in fire-affected urban regions.

Mexico↗
PubMed2026

A flipped classroom approach compared with low-interactive online learning for pediatric pain management knowledge and instructional motivation in nursing students: A randomized controlled study.

AIM: This study aimed to compare a flipped classroom approach with low-interactive online learning in terms of nursing students' questionnaire-assessed pediatric pain management knowledge and instructional motivation. BACKGROUND: Pain management in children is a critical and multidimensional nursing responsibility. However, limited curricular time and opportunities for applied learning may restrict nursing students' preparedness in this area. Structured and interactive instructional formats, such as the flipped classroom, may support knowledge acquisition and motivation in pediatric nursing education. METHODS: This study employed a parallel-group randomized controlled trial design with a 1:1 allocation ratio. Eighty-eight third-year prelicensure nursing students were randomized to either the flipped classroom group (n&#xa0;=&#xa0;44) or the low-interactive online learning group (n&#xa0;=&#xa0;44). Due to attrition (2 intervention, 2 control), analyses included 42 participants per group (n&#xa0;=&#xa0;84 in total). Data were collected between February and July 2022 using the Pediatric Pain Management Knowledge Scale for Nursing Students and the Instructional Materials Motivation Survey. This study was prospectively registered at ClinicalTrials.gov (Identifier: NCT07129044). RESULTS: At baseline, the groups were comparable in terms of knowledge and learning motivation. Following the intervention, the flipped classroom group demonstrated greater improvements in questionnaire-assessed pediatric pain management knowledge and instructional motivation than the low-interactive online learning group. Although scores declined from post-test to the three-month follow-up, they remained above baseline in the flipped classroom group. CONCLUSIONS: Within the context of this course, the flipped classroom approach was associated with greater improvement in questionnaire-assessed pediatric pain management knowledge and instructional motivation than low-interactive online learning. The findings should be interpreted as proximal educational outcomes rather than evidence of improved clinical competence or durable long-term effectiveness. Further studies using objective performance-based outcomes and longer follow-up periods are needed.

Humans↗
PubMed2026

Efficacy of current approaches to non-invasive diagnosis of skin cancer and the potential impact of artificial intelligence: A systematic review and meta-analysis.

BACKGROUND: Skin cancer is one of the most prevalent malignancies worldwide, particularly within Caucasian populations. This systematic review and meta-analysis aimed to quantitatively review the current literature on non-invasive diagnosis of skin cancer and evaluate the current evidence to support the use of tools in addition to, or in replacement of clinician face-to-face assessment. METHODS: A literature search was conducted for publications in PubMed, Medline and Embase databases. Articles describing accuracy, sensitivity, specificity and outcomes of their mode of assessment were included. A total of 208 articles met the inclusion criteria. RESULTS AND CONCLUSION: This systematic review and meta-analysis showed that the diagnostic performance of artificial intelligence (AI) in the interpretation of dermatoscopic images was high for melanoma diagnosis, basal cell carcinoma or malignancy, in comparison to dermatoscopic assessment alone by clinicians and experts. Although AI interpretation of images demonstrated higher sensitivity for melanoma diagnosis in comparison to clinical assessment combined with dermatoscopic assessment, it is unclear if this is also the case for basal cell carcinoma and squamous cell carcinoma diagnosis. Reflectance confocal microscopy, a non-invasive high resolution imaging technique, is known to have a high sensitivity for diagnosing cutaneous malignancy, and this may have applications within secondary care. Therefore, AI could help reduce resource burden and aid in clinical assessment, particularly within primary care settings.

Humans↗
PubMed2026

Integration of ear and hearing care services in low- and middle-income health systems: a systematic review and qualitative synthesis.

Hearing loss is a global public health burden and mostly affects those living in low- and middle-income countries (LMICs). One approach to address ongoing challenges is the World Health Organization's recommendation for the integration of ear and hearing care (EHC) services into healthcare packages. However, little is known about EHC integration approaches, particularly in LMICs additionally, these approaches have not been investigated through a health systems lens. This qualitative review aimed to describe the various approaches to the EHC service integration in LMICs and to identify enabling and constraining factors. We reviewed 17 studies, with a focus on LMICs, using adaptations of the Valentijn integration and World Health Organization EHC frameworks, following the PRISMA guidelines. Our investigation showed that most integration approaches were at micro or individual level. Enabling factors for integration of EHC services were training, mentorship, collaboration, technology, inclusion of EHC in healthcare packages and investment in EHC services. Barriers were challenges with training, facilities and equipment, policy implementation and resourcing of EHC services. We further described factors influencing healthcare seeking behaviour and the use of integrated EHC services, such as access and ability to pay, referral systems and communication and awareness. This study describes the complex nature of EHC integration and ways to support integration. Key considerations are the level of integration, training to address workforce issues and factors influencing service utilisation as we work towards health system strengthening.

Humans↗
PubMed2026

Effectiveness of the DASH diet versus alternative dietary interventions for hypertension management: A systematic review and meta-analysis.

BACKGROUND: The Dietary Approaches to Stop Hypertension (DASH) diet is widely recommended for blood pressure control; however, its comparative effectiveness relative to other structured dietary interventions remains uncertain. OBJECTIVE: To evaluate the comparative effectiveness of the DASH diet versus alternative dietary interventions on blood pressure and cardiometabolic outcomes in adults. METHODS: A systematic review and meta-analysis of randomized controlled trials was conducted in accordance with PRISMA guidelines. Multiple databases were searched from inception to February 2026. Eligible studies included adults with elevated blood pressure or hypertension comparing the DASH diet with other dietary interventions or usual care. Continuous outcomes were pooled using random-effects models and expressed as mean differences (MD) or standardized mean differences (SMD). Risk of bias was assessed using the Cochrane RoB 2 tool, and certainty of evidence was evaluated using the GRADE approach. RESULTS: A total of 22 randomized controlled trials were included in the qualitative synthesis, of which 10 were included in the meta-analysis. The DASH diet did not demonstrate a statistically significant advantage over comparator diets in reducing systolic blood pressure (MD = 1.30; 95% CI: -1.54 to 4.14) or diastolic blood pressure (MD = 0.21; 95% CI: -3.72 to 4.14), with substantial heterogeneity observed across studies. Significant effects were identified for selected cardiometabolic outcomes, including reductions in urinary sodium excretion (MD = -32.89; 95% CI: -62.76 to -3.01), LDL cholesterol (MD = -8.59; 95% CI: -14.64 to -2.54), and glycated hemoglobin (HbA1c) (MD = -0.49; 95% CI: -0.52 to -0.46), as well as an increase in urinary potassium excretion (MD = 11.76; 95% CI: 4.08 to 19.44). The certainty of evidence ranged from moderate to very low across outcomes. CONCLUSIONS: The DASH diet was not superior to other dietary interventions in reducing blood pressure; however, it demonstrated consistent benefits in selected cardiometabolic parameters. Given the overall low certainty of evidence and substantial heterogeneity, these findings should be interpreted cautiously. Future research should focus on well-designed trials with standardized outcomes and longer follow-up to clarify comparative effectiveness.

Humans↗
PubMed2026

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans↗
PubMed2026

Comparison of paralog identification methods and their impact on species tree topologies in target capture phylogenomics within the Sindora clade (Detarioideae: Leguminosae).

Target capture is a common method of generating high throughput DNA sequencing data for phylogenetic reconstruction of species relationships, for which single copy genes are usually most informative. However, a pervasive problem with target capture is that putatively single copy genes may in fact be paralogs resulting from gene duplication, which are problematic for phylogenetic inference because their evolutionary history may differ from the divergence history of species. Here, we use as a case study a target enrichment dataset of 88 species of Detarioideae (Leguminosae) with a focus on the Sindora clade to examine approaches for handling paralogs, including the built-in paralog handling functions in HybPiper and CAPTUS, plus subsequent steps using Putative Paralog Detection and the tree-based Yang & Smith orthology inference approach. We compare the paralogs flagged using these methods and verify their performance with BLAST mapping against a reference genome sequence of Sindora glabra, and then subsequently compare the species tree topologies produced across these methods. Our comparisons of paralogs flagged across the Sindora clade show that the Putative Paralog Detection pipeline was the most accurate in identifying paralogs in terms of its similarity to the BLAST mapping, followed by the built-in paralog identification function of CAPTUS. However, the results we recovered for the Detarioideae subfamily suggest that the largest differences in species tree topology resulted from the use of paralog-filtered alignments (such as with the Putative Paralog Detection pipeline and the Yang & Smith orthology inference approaches) rather than just by removing the sequences of identified paralogous genes. This was the true for HybPiper-assembled datasets but was not seen in CAPTUS-assembled datasets. In all comparisons, the topological differences caused by different paralog handling methods tended to be confined to clades where processes such as hybridisation and introgression are prevalent. Our study provides a roadmap to establish the best approach to identify, eliminate or separate paralogs in the absence of a chromosomally contiguous reference genome for a study group, and highlights the importance of careful data inspection and processing in addition to understanding the extent of paralogy and paralog characteristics (e.g. sequence divergence between copies) for their study group.

Phylogeny↗
PubMed2026

Integration of Clinical Case Scenarios With Anatomical Dissection Teaching-Is Recall Improved Among Medical Students?

BACKGROUND: There is ongoing debate about how best to deliver anatomy teaching in a modern medical curriculum. Some studies suggest that the separation of basic sciences and clinical teaching can impact students' confidence in anatomy, which has potential long-term implications on their medical career. This suggests new pedagogic approaches to improve anatomy teaching may be beneficial. This study aimed to establish if integrating a clinical case into anatomy practical classes would improve students' anatomy recall compared to anatomy teaching alone. APPROACH: A ten minute clinical scenario was developed, which focused on the typical history, examination, investigations and management of a hip fracture patient. Medical students (n&#x2009;=&#x2009;220) currently studying lower limb anatomy were randomised by pre-assigned anatomy groups to become intervention or control. In the intervention group, students received the clinical case teaching, followed by their anatomy session. In the control group, students attended the anatomy session. Students in both groups were then assessed on hip anatomy. The intervention group also gave their perception of the clinical case. EVALUATION: This study showed that participants who received integrated teaching performed significantly better in the anatomy recall test (3.64 SD &#xb1; 0.574) than whose who had anatomy teaching only (1.95 SD &#xb1; 0.994) (chi2&#x2009;=&#x2009;185.51, p&#x2009;<&#x2009;0.00001). Most participants (93.5%; 101/108) strongly agreed/agreed that integrating clinical cases into anatomy teaching benefited their learning. IMPLICATIONS: These results suggest that students' anatomy recall may be improved by integrating clinical cases and anatomy teaching. It also suggests that students found this approach beneficial for their learning.

Humans↗
PubMed2026

Dissociating behavioral, neural and experiential effects of prefrontal HD-tDCS during conflict resolution.

Inconsistent evidence regarding the cognitive effects of transcranial direct current stimulation (tDCS) highlights the need for more comprehensive approaches to assess its impact. This study aimed to investigate the effects of high-definition tDCS (HD-tDCS) on conflict resolution by combining behavioral, neural, and subjective experience measures. Sixty participants were randomly assigned to anodal, cathodal, or sham HD-tDCS groups and completed a 30-min flanker task. EEG was recorded during the first and last blocks (without stimulation), while stimulation was applied during the intermediate blocks of the task. Using a multidimensional methodological approach including Drift-Diffusion Modeling (DDM), EEG spectral analysis, Lempel-Ziv complexity, and Temporal Experience Tracing (TET), we assessed the cognitive, neural, and phenomenological effects of stimulation. Behavioral results indicated no significant improvements in reaction times or accuracy across the stimulation groups. Similarly, DDM parameters showed no effect of HD-tDCS on latent cognitive processes. However, EEG data revealed a significant reduction in neural complexity in the anodal group during resting-state, suggesting a stabilization or reorganization of neural dynamics. Subjective experience analysis identified two distinct clusters of task-related feelings, though time spent in these experiential states did not differ between groups. Interestingly, sensation of stimulation was significantly higher for anodal stimulation than sham when analyzed as a single dimension. Despite null behavioral effects, this study provides important insights into the neural and subjective responses to HD-tDCS and highlights the value of integrating complementary multidimensional approaches to better characterize brain stimulation effects. These findings contribute to the ongoing debate about the efficacy of tDCS in cognitive enhancement.

Humans↗
PubMed2026

Cooperative anaerobic catabolism of chlorinated organic compounds: implications for sustainable bioremediation.

Biodegradation research historically followed a reductionist approach focused on axenic (pure) cultures capable of catabolizing the specific contaminant(s) of interest. While this approach has substantially advanced our understanding of the microbiology, physiology, biochemistry, and genetics of contaminant degradation under laboratory conditions, it does not capture the complexity of natural and engineered environments. During in situ bioremediation, microbiomes are exposed to mixtures of contaminants, and microbial interactions profoundly influence contaminant transformation and fate. In anoxic environments, degradation of chlorinated compounds is often sustained by metabolic cooperation among taxonomically and physiologically distinct microorganisms. Through the exchange of metabolites such as hydrogen, formate, acetate, and other nutrients, microbial populations establish interdependent networks that overcome thermodynamic and physiological constraints, enabling self-sustaining systems of contaminant transformations that would be inefficient or impossible with individual organisms. We highlight examples of microbial interactions that underpin anaerobic catabolism of chlorinated contaminants, including systems resulting in self-sustained anaerobic bioremediation.

Biodegradation, Environmental↗
PubMed2026

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence↗
PubMed2026

Exploring the perceptions, experiences, and behaviours that nurses and midwives face in relation to sleep: A systematic review of qualitative evidence.

BACKGROUND: The importance of sleep for nurses and midwives is increasingly being recognised. Poor sleep is known to have negative impacts on physical health, mental wellbeing, and work performance. This has prompted efforts to promote and support staff sleep. However, further efforts are needed to understand how nurses and midwives consider and manage sleep to ensure that meaningful and effective interventions are adopted and sustained. AIMS: This review of qualitative evidence aims to examine nurses' and midwives' perceptions, experiences, and behaviours around sleep. METHODS: This review followed JBI's systematic meta-aggregative approach including development of an a priori protocol. A systematic search of six electronic databases (MEDLINE, Embase, Emcare, PsycINFO, CINAHL, and Scopus) was undertaken to identify qualitative studies that examine nurses' and midwives' perceptions, experiences, and behaviours related to sleep. The search was conducted on the 10th of October 2024. Study selection, quality appraisal, data extraction, and synthesis followed JBI approaches and the ConQual approach was used to report assessment of synthesised findings. RESULTS: Thirty-three studies were included for review, and 245 findings were aggregated into 24 categories and nine synthesised findings related to the perceptions, behaviours, and experiences. While sleep was perceived as important, poor sleep was often understood as an expected and inevitable part of the job and that there was a need to always be awake to provide continual care. Experiences influencing sleep related to personal circumstances and work-related factors, as well as professional training and institutional practices. A range of behaviours, including planning time to sleep, using sleep aids, modifying the sleep environment, and altering daytime behaviours were also described. CONCLUSION: This review identified a range of perceptions, behaviours, and experiences that may influence the sleep of nurses and midwives which are vital to supporting individual and workforce wellbeing and safe, effective clinical practice. Insights from this review can be used to better understand nurses' and midwives' relationship with sleep and to develop and enhance targeted sleep interventions and programs that aim to promote and support healthy sleep among nurses and midwives. Open Science Framework Registration: 10.17605/OSF.IO/F32UM.

Humans↗
PubMed2026

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics↗