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Pre-analytical errors in a high-volume Bangladeshi diagnostic centre: Prevalence, workload impact, and mitigation strategies
Background Pre-analytical errors are the most frequent cause of laboratory mistakes, accounting for nearly half of all diagnostic inaccuracies worldwide. These errors can invalidate test results, delay clinical decisions, and waste valuable healthcare resources, particularly in resource-limited, high-volume diagnostic laboratories. This study aimed to assess the prevalence, contributing factors, and severity of pre-analytical errors in a large diagnostic centre in Bangladesh. Methods An observational, cross-sectional study was conducted over two months in the Biochemistry and Immunology Laboratories of a high-volume diagnostic centre in Dhaka, Bangladesh. Data from 195 documented pre-analytical errors and a structured survey of 27 laboratory staff were analysed. Errors were classified into minor, moderate, or major using definitions adapted from ISO 15189:2022 and WHO guidelines. Descriptive statistics and Chi-square tests were performed to explore associations between workload level (≥ 931 samples/day) and error frequency, with p < 0.05 considered statistically significant. Results The most frequent errors were sample misplacement (38.5%) and incorrect labelling (17.9%). The sample collection (42.6%) and pick-and-drop (38.5%) units contributed the majority of errors. Morning shifts (65.1%) and high-workload days (70.8%) showed higher error frequencies, with a statistically significant association between workload and error occurrence (χ² = 121.093, p < 0.001). Major errors accounted for 37.4% of incidents. Conclusion Pre-analytical errors remain a critical threat to diagnostic accuracy in resource-limited laboratories. Improving workflow organization, implementing barcoding and automation, and strengthening staff training and workload management can substantially reduce error rates and enhance patient safety in high-throughput clinical settings.
Bimodal versus Unimodal Pore Architectures in Diimine-Linked Two-Dimensional Covalent Organic Frameworks
Near Neutral Selectionist Theories (NNST) for SARS-CoV-2 suggested by the substitution-mutation ratio (c/µ) analysis
A definitive test to measure genome-wide fitness effects of any nucleotide mutation, including translated regions ( TRs ) and untranslated regions ( UTRs ), is essential to help resolve the decades-long neutralist–selectionist debate regarding mutation-mediated species evolution. The precise boundary, composition, and abundance of nearly neutral mutations remain disputed, highlighting the need for a rigorous framework supported by empirical sequence data. Our substitution–mutation rate ratio test ( c/μ ) might provide such a framework. c/μ compares the ratio of how often mutations fix into the population (substitution rate, c ) with their expected arrival (mutation rate, µ ), which classifies each mutation type ( c/µ > 1: adaptive; c/µ = 1: neutral; c/µ < 1: deleterious). We previously showed that SARS-CoV-2 exhibits L-shaped distributions of fitness effects ( DFEs ) and a strict molecular clock, and mutation type proportions consistent only with the Near-Neutral Balanced Selectionist Theory ( NNBST ) and not with conventional molecular evolution theories. However, a theoretical explanation for incidences of non-strict clock behavior in several SARS-CoV-2 segments are not formalized. Here, we extended c/μ analysis to 49 segments of SARS-CoV-2 (26 TRs, 12 UTRs, and 10 transcriptional regulatory sequences ( TRSs )) and provide formal, mathematical frameworks for our NNBST and Near-Neutral Unbalanced Selectionist Theory ( NNUST ) to explain non-strict clock behavior. All 49 segments displayed L-shaped DFEs : 24 segments (mostly TRs ) supported molecular clocks and balanced effects of near neutral mutations, consistent with NNBST ; meanwhile, 25 segments (mostly UTRs / TRSs ) did not support molecular clocks or balancing of near neutral mutations, consistent with NNUST . Numerous violations of Selectionist Theory ( ST) , Kimura’s Neutral Theory ( KNT) , and Ohta’s Nearly Neutral Theory ( ONNT) were observed, but none for NNBST or NNUST. Together, these results support a unified Near-Neutral Selectionist Theory ( NNST ), combining neutral and selectionist perspectives to better explain the molecular evolution of SARS-CoV-2.
PROTAC-Mediated Degradation of mHTT Aggregates Attenuates Neurotoxicity in Cellular and R6/2 Mouse Models of Huntington’s Disease
Social media analysis reflects the negative sentiments experienced at both time changes with somewhat more depressive impact in early fall
We quantify the effect of biannual time changes on sentiment using US online and social media posts from periods around changes to Daylight Saving Time (DST) in the spring and Standard Time (ST) in the fall over the period 2019–2023. We compare sentiment—a measure of individuals overall mood or emotions towards an event—in cities on either side of US time zones the day before and after the societal time change. We find negative shocks to sentiment following both time changes. This effect seems stronger in the fall. Given the amount of daylight relative to a fixed work schedule should be the same in each group of cities on these days, these differences suggest strong negative ceteris paribus reactions to societal time changes, which may indicate preference to abolish these adjustments, although we do not measure preference for DST versus ST. We also use regression analysis to estimate how sentiment changes over time. We find persistent negative impacts from the change to Standard Time in the fall. In contrast, individuals experience a noisy shock to sentiment that attenuates over time. These findings provide evidence that individuals have a more negative reaction to the societal time change to Standard Time in the fall than they do to DST in the Spring. This work highlights the potential that the reaction to societal time changes varies depending on whether moving to or away from DST or Standard Time.
Combating Phase Segregation in Earth-Abundant Pyrite Cathodes for High-Energy-Density Lithium–Metal Batteries
Tailored job coaching for people with severe mental illness living in supported housing settings: A realist approach
Background For people with severe mental illness (SMI) residing in supported housing settings, finding and maintaining paid or unpaid work is challenging. This study was initiated to examine how professionals tailor job coaching trajectories to effectively address the specific needs of clients. The aim was to unravel the complexity of these trajectories, providing a deeper understanding of how and under what circumstances people with SMI in supported housing can obtain and sustain meaningful daily activities, including paid or unpaid work, as part of their recovery journey. Methods Interviews were conducted with 24 clients with severe mental illness (SMI) and their job coaches (N = 15) in dyads. Additionally, two mixed focus group discussions were held with job coaches (n = 16) and their supervisors (n = 2). A realist evaluation approach was used to determine what works for whom, how, and under which conditions. Self-Determination Theory (SDT) served as the analytical framework to explore the motivational factors that drive clients to seek and retain paid or unpaid work. Results Our findings are structured in three sections, each focusing on context-intervention-mechanism-outcome (CIMO) configurations. These configurations illustrate how job coaches address clients’ needs for relatedness, competence and autonomy. The findings provide a deeper understanding of the inner workings of job coaching trajectories, showing how job coaches foster autonomous motivation and thereby enable clients to obtain and retain both paid and unpaid work. Conclusions This study highlights that there is no universal approach to job coaching. Job coaching requires a tailored approach with a strong emphasis on building personal-professional relationships and adapting interventions to individual circumstances.
Supramolecular Polymers Controlled by Glycan Geometry
Impact of demographic factors and HIV status on Hepatitis B vaccination adherence and completion rate among high-risk populations in Lagos State, Nigeria
Hepatitis-B-Virus (HBV) remains an important global public health concern, as well as a primary cause of both acute and chronic liver diseases, with over 18 million people infected by the virus in Nigeria. This study evaluated the impact of HIV status, age, and gender of high-risk populations on HBV vaccination adherence and completion rate in Lagos state, Nigeria. A retrospective study design was utilized to access the clinic data of 641 study participants who participated in the HBV program at the one-stop-shop clinic between June 2021 to June 2024. Data on age, HIV status, gender, population type, and the date of each dose of administered vaccine were recorded. To estimate the odds-ratios (ORs) and adjusted-ORs at 95% confidence intervals (CIs), bivariate/multivariate logistic regression models were utilized, and the association between age, gender, HIV status, and HBV vaccination adherence and the completion rate was examined. The study participants had a mean age of 21.7 ± 8.8 years and were composed of 510 (79.6%) males, 131 (20.4%) females; 162 (25.3%) participants living with HIV, 423 (66.0%) HIV-negative participants, 500 (78.0%) MSM, and 115 (17.9%) FSW. The overall vaccination completion rate was 45.4%, with significant variation by age group (p = 0.004). The highest completion rates were observed among participants aged 30–34 years (58.4%) and 35–39 years (57.8%), while younger participants aged 15–29 had lower adherence. Gender and HIV status were not independently associated with vaccination completion (p > 0.05). Age was the only factor significantly affecting completion (AOR: 1.92, 95% CI: 1.23, 3.03). HBV vaccination coverage in high-risk populations is low in Lagos State. This suggests that the HBV vaccination program in the state is still facing significant challenges. Creating awareness about HBV infection and strengthening the availability, accessibility, and cost effectiveness of HBV service uptake will enhance the program's success.
Amphiphile Confined Water Electrolyte Enables Facilitated Cation Transport through Nanometric Water Channels
Beyond Ubiquity: Scale-dependent patterns of tardigrade diversity on the Iztaccíhuatl volcano
The diversity of tardigrade communities has been related with variables, such as habitat type, litter type, elevation, among others. However, the integration of variables in a multiscale context has been little explored, so this study analyzed tardigrade diversity and community composition across multiple ecological scales—moss substrates (rock, soil, bark), landscapes, and elevation zones—in a montane ecosystem. Mosses on tree bark harbor the highest species richness, including several substrate-specific taxa, while mosses on soil hosts unique species not found elsewhere. Mosses on rocks share species with soil mosses but lacks exclusive taxa. Among landscapes, the coniferous forests (mixed, Abies religiosa , and Pinus hartwegii ) exhibit high species richness and community similarity, with distinct local assemblages characterized by exclusive species within each forest type. Three generalist species were ubiquitous across all landscapes. Elevation analysis reveals maximal tardigrade richness and abundance in the alpine zone, with the nival zone supporting fewer species, mostly a subset of alpine taxa, and hosting a few unique species likely adapted to harsher conditions. Beta diversity analyses indicated that species turnover rather than nestedness predominantly drives community dissimilarities across substrates and habitats. These findings highlight the importance of considering scale-dependent patterns in understanding tardigrade distribution in complex montane environments.
Electrochemomics Profiling Metabolic Dynamics in Biofluids
Integrated miRNA-mRNA transcriptomic analysis of hepatopancreas reveals molecular mechanisms in Macrobrachium rosenbergii under graded nitrite stress
Nitrite accumulation poses a significant threat to aquatic organisms in intensive aquaculture systems. Macrobrachium rosenbergii , a commercially vital freshwater prawn, exhibits adaptive responses to environmental stressors, yet the molecular mechanisms underlying nitrite tolerance remain poorly understood. This study employed integrated mRNA and miRNA transcriptomics to dissect the regulatory networks activated in M. rosenbergii hepatopancreas under acute nitrite stress (0, 40, and 87.25 mg/L nitrite-N over 48 h). High-throughput sequencing revealed 640 and 912 differentially expressed genes (DEGs) in low-concentration (LC) and high-concentration (HC) groups, respectively, compared to controls (CK). In the LC group, enrichment was predominantly observed in ribosome biogenesis (96 genes, p < 0.001). Conversely, the HC group was characterized by the significant modulation of the PPAR signaling (11 genes), glycerophospholipid metabolism, and the citrate cycle ( p < 0.005). Calcium signaling and MAPK pathways may be central to stress adaptation across both groups. miRNA profiling revealed 17 downregulated and 2 upregulated miRNAs within the HC group relative to the CK group, with miR-193-y, miR-263-x, and miR-145-x implicated in metabolic regulation. Notably, novel miRNAs (e.g., novel-m0087-3p) showed concentration-dependent expression. qPCR validated the consistency of sequencing data, confirming stress-responsive genes ( P53 , HORMA , SLC25a28 ) and miRNAs. This study is the first to integrate the mRNA-miRNA regulatory network in Macrobrachium rosenbergii to elucidate the response mechanism to nitrite stress, emphasizing the role of metabolic reprogramming and signal pathway regulation as key survival strategies. It provides a foundation and novel perspectives for the molecular evolution of nitrite adaptability in aquatic animals and breeding programs.
Unraveling Sulfur Tolerance Mechanisms in Samarium-Doped Ceria-NiRh Catalysts for Solid Oxide Fuel Cells
Correction: Perspectives of multidisciplinary healthcare providers in elderly daycare centres: Challenges, opportunities and impacts on geriatric care in Chiangrai Municipality, Thailand
Proximate determinants of the frequency of mosquito sounds: separating species-specific effects from environmentally driven variations - Implications for AI species recognition
In recent years, several technologies have been developed for the monitoring and control of insect vector species. Many of them aim to use mosquito wingbeat frequency in the form of sound or opto-acoustic measurements to identify mosquito species, often through the training of AI classification models. However, these models often struggle to be accurate in real-life conditions, as the training data rarely captures the variability range of different species across many individual and environmental conditions, or does not explicitly control for it. Here, we use lab recordings of mosquito sounds to evaluate the impact of several environmental and life history factors on the mean frequency of the first harmonic of mosquito sounds. We recorded 475 individuals of 15 species in several environmental conditions, varying in temperature and humidity, while we also characterized the effect of body size (wing length), sex and age on the frequency of wingbeat sound at the among-individual level. Only species that comprised at least 2 recorded individuals were included in the analysis (N = 10 species). Variances at the within-individual and within-species level varied consistently, as the repeatability of the trait was 0.411 and 0.466, respectively. However, when we controlled for morphological and environmental effects, the proportion of between-individual variance decreased, while the between-species component increased (repeatabilities: 0.267 and 0.630). This suggests that species-specific signals in the sound are more robust once factors introducing variances due to real life conditions are involved in the models. Sex and temperature both had a significant effect on mosquito sound: an increase in temperature led to an increase in wingbeat frequency. In addition, the random slope analysis showed that response to temperature differ between species, with strong between-species differences, especially for males. Therefore, advancing AI species recognition requires that biotic and environmental variables be either explicitly integrated into classification models or sufficiently represented in training data to reflect real-life variability.
Can Intermediate Temperatures be a “Goldilocks Zone” for Green Hydrogen Production?
Dynamic response of Blue Honeysuckle fruit-stem system based on mathematical model
To investigate the motion and detachment behavior of Blue Honeysuckle fruit during vibratory harvesting, the fruit-bearing branch was modeled as a constant strength beam, and an analytical series solution for its dynamic response was derived. This solution shows that the branch undergoes approximately simple harmonic motion under low frequency excitation. Subsequently, a dynamic model of the fruit-stem system subject to branch oscillation with the fruit stem at an angle to the excitation direction was developed. When the fruit stem is perpendicular to the excitation direction, the stress within it can exceed its allowable limit under low frequency excitation, leading to fruit detachment. Conversely, when the fruit stem is aligned parallel to the excitation direction, fruit detachment results from the vibrational instability of the fruit-stem system. For the case where a small angle exists between the stem and the excitation direction, the criterion for vibrational instability remains consistent with that of the parallel scenario. Modal analysis and frequency sweep analysis were performed using the finite element method (FEM) to study the vibration response characteristics of the fruit-stem system. The finite element simulation results are in close agreement with theoretical calculations. Field vibration experiments were carried out in an experimental plot. The experimental data confirmed that the simplified dynamic model can accurately predict the fruit detachment patterns. The findings of this study can serve as a theoretical foundation for the design, selection, and optimization of mechanical harvesting equipment for berry crops.