Perspectives on label-free microscopy of heterogeneous and dynamic biological systems.

Significance: Advancements in label-free microscopy could provide real-time, non-invasive imaging with unique sources of contrast and automated standardized analysis to characterize heterogeneous and dynamic biological processes. These tools would overcome challenges with widely used methods that are destructive (e.g., histology, flow cytometry) or lack cellular resolution (e.g., plate-based assays, whole animal bioluminescence imaging). Aim: This perspective aims to (1) justify the need for label-free microscopy to track heterogeneous cellular functions over time and space within unperturbed systems and (2) recommend improvements regarding instrumentation, image analysis, and image interpretation to address these needs. Approach: Three key research areas (cancer research, autoimmune disease, and tissue and cell engineering) are considered to support the need for label-free microscopy to characterize heterogeneity and dynamics within biological systems. Based on the strengths (e.g., multiple sources of molecular contrast, non-invasive monitoring) and weaknesses (e.g., imaging depth, image interpretation) of several label-free microscopy modalities, improvements for future imaging systems are recommended. Conclusion: Improvements in instrumentation including strategies that increase resolution and imaging speed, standardization and centralization of image analysis tools, and robust data validation and interpretation will expand the applications of label-free microscopy to study heterogeneous and dynamic biological systems.

Adaptive multi-source domain collaborative fine-tuning for transfer learning.

Fine-tuning is an important technique in transfer learning that has achieved significant success in tasks that lack training data. However, as it is difficult to extract effective features for single-source domain fine-tuning when the data distribution difference between the source and the target domain is large, we propose a transfer learning framework based on multi-source domain called adaptive multi-source domain collaborative fine-tuning (AMCF) to address this issue. AMCF utilizes multiple source domain models for collaborative fine-tuning, thereby improving the feature extraction capability of model in the target task. Specifically, AMCF employs an adaptive multi-source domain layer selection strategy to customize appropriate layer fine-tuning schemes for the target task among multiple source domain models, aiming to extract more efficient features. Furthermore, a novel multi-source domain collaborative loss function is designed to facilitate the precise extraction of target data features by each source domain model. Simultaneously, it works towards minimizing the output difference among various source domain models, thereby enhancing the adaptability of the source domain model to the target data. In order to validate the effectiveness of AMCF, it is applied to seven public visual classification datasets commonly used in transfer learning, and compared with the most widely used single-source domain fine-tuning methods. Experimental results demonstrate that, in comparison with the existing fine-tuning methods, our method not only enhances the accuracy of feature extraction in the model but also provides precise layer fine-tuning schemes for the target task, thereby significantly improving the fine-tuning performance.

Analytical code sharing practices in biomedical research.

Data-driven computational analysis is becoming increasingly important in biomedical research, as the amount of data being generated continues to grow. However, the lack of practices of sharing research outputs, such as data, source code and methods, affects transparency and reproducibility of studies, which are critical to the advancement of science. Many published studies are not reproducible due to insufficient documentation, code, and data being shared. We conducted a comprehensive analysis of 453 manuscripts published between 2016-2021 and found that 50.1% of them fail to share the analytical code. Even among those that did disclose their code, a vast majority failed to offer additional research outputs, such as data. Furthermore, only one in ten articles organized their code in a structured and reproducible manner. We discovered a significant association between the presence of code availability statements and increased code availability. Additionally, a greater proportion of studies conducting secondary analyses were inclined to share their code compared to those conducting primary analyses. In light of our findings, we propose raising awareness of code sharing practices and taking immediate steps to enhance code availability to improve reproducibility in biomedical research. By increasing transparency and reproducibility, we can promote scientific rigor, encourage collaboration, and accelerate scientific discoveries. We must prioritize open science practices, including sharing code, data, and other research products, to ensure that biomedical research can be replicated and built upon by others in the scientific community.

Importance of Source Control in the Subgroup of Intra-Abdominal Infections for Septic Shock Patients: Analysis of 390 Cases.

Background: This study aimed to evaluate the epidemiology of septic shock (SS) associated with intraabdominal infections (IAI) as well as associated mortality and efficacy of early source control in a tertiary-care educational hospital. Methods: Patients who had SS with IAI and consulted by Infectious Diseases consultants between December 2013 and October 2022 during night shifts in our centre were analyzed retrospectively. Results: A total number of 390 patients were included. Overall, 30-day mortality was 42.5% on day 3, while day 14 and 30 mortality rates were 63.3% and 71.3%, respectively. Source control by surgical or percutaneous operation was performed in 123 of 390 cases (31.5%), and the mortality rate was significantly lower in cases that were performed source control at any time during SS (65/123-52.8% vs 213/267-79.8%, p<0.001). In 44 of 123 cases (35.7%), source control was performed during the first 12 hours, and mortality was significantly lower in this group versus others (24/44-54.5% vs 254/346-73.4%, p=0.009). On the other hand, female gender (p<0.001, odds ratio(OR)= 2.943, 95%CI=1.714-5.054), diabetes mellitus (p= 0.014, OR=2.284, 95%CI=1.179-4.424), carbapenem-resistant Gram-negative etiology (p=0.011, OR=4.386, 95%CI=1.398-13.759), SOFA≥10 (p<0.001, OR=3.036, 95%CI=1.802-5.114), lactate >3 mg/dl (p<0.001, OR=2.764, 95%CI=1.562-4.891) and lack of source control (p=0.001, OR=2.796, 95%CI=1.523-5.133) were significantly associated with 30-day mortality in logistic regression analysis. Conclusion: Source control has a vital importance in terms of mortality rates for IAI-related septic shock patients. Our study underscores the need for additional research, as the present analysis indicates that early source control does not manifest as a protective factor in logistic regression.

Investigation of rock genesis and geodynamic significance based on Sr-Yb granite classification and geochemical characteristics: A case study from Guangxi, China.

The intrusive bodies in the study area are categorized into two intrusive units, γπK2 and ηoπK2, based on rock structure characteristics and intrusive contact relationships. The primary lithologies are granite porphyry and quartz monzonite porphyry. Through LA-ICP-MS zircon U-Pb dating, the weighted mean ages of zircon ^206Pb/^238U for these two units were determined to be 84.09 ± 0.86 Ma and 86.10 ± 0.76 Ma, respectively. According to geochemical characteristics and Sr-Yb granite classification, the quartz monzonite porphyry is classified as Zhejiang-Fujian type granite, and the granite porphyry as Nanling type granite. The study explores the geodynamic significance of granites in the area based on Sr-Yb granite classification, identifying the lower crust metamorphic facies as amphibolite facies. The source rocks are primarily basic granulites and felsic granulites, reflecting a thermally active lower crust with poorly developed fluids. Additionally, Sr-Yb granite classification aids in determining the crustal thickness of the lower crust, which is crucial for understanding continental geological evolution. This paper discusses the optimal locations and conditions for mineralizing fluid precipitation, noting that tungsten-tin mineralization is associated with Nanling type granites and that the mineralization process generally occurs later than the diagenetic process under conditions of low pressure and low oxygen fugacity. Tungsten-tin prospecting should focus on areas where the surrounding rock temperature ranges from 300 to 500 °C, with particular attention to the contact zones of sedimentary rocks or near structural fault zones.

Characteristics of China's coal mine methane emission sources at national and provincial levels.

Methane (CH4) is the second most abundant greenhouse gas. China is the largest CH4 emitter in the world, with coal mine methane (CMM) being one of the main anthropogenic contributions. Thus, there is an urgent need for comprehensive estimates and strategies for reducing CMM emissions in China. However, the development of effective strategies is currently challenged by a lack of information on temporal variations in the contributions of different CMM sources and the absence of provincial spatial analysis. Here, considering five sources and utilization, we build a comprehensive inventory of China's CMM emissions from 1980 to 2022 and quantify the contributions of individual sources to the overall CMM emissions at the national and provincial levels. Our results highlight a significant shift in the source contributions of CMM emissions, with the largest contributor, underground mining, decreasing from 89% in 1980 to 69% in 2022. Underground abandoned coal mines, which were ignored or underestimated in past inventories, have become the second source of CMM emissions since 1999. From 2011 to 2022, we identified Shanxi, Guizhou, and Shaanxi as the three largest CMM-emitting provinces, while the Emissions Database for Global Atmospheric Research (EDGAR) v8 overestimated emissions from Inner Mongolia, ranking it third. Notably, we observed a substantial decrease (exceeding 1 Mt) in CMM emissions in Sichuan, Henan, Liaoning, and Hunan between 2011 and 2022, which was not captured by EDGAR v8. To develop targeted CMM emission reduction strategies at the provincial level, we classified 31 provinces into four groups based on their CMM emission structures. In 2022, the number of provinces with CMM emissions mainly from abandoned coal mines has exceeded that of provinces with mainly underground mines, which requires attention. This study reveals the characteristics of the source of CMM emissions in China and provides emission reduction directions for four groups of provinces.

Source and level of dietary iron influence semen quality by affecting inflammation, oxidative stress and iron utilization levels in boars.

BACKGROUND: Boars fed a mixed form of inorganic and organic iron in excess of the NRC recommended levels still develop anemia, which suggested that the current level and form of iron supplementation in boar diets may be inappropriate. Therefore, 56 healthy Topeka E line boars aged 15-21 months were randomly divided into 5 groups: basal diet supplemented with 96 mg/kg ferrous sulfate (FeSO4) and 54 mg/kg glycine chelated iron (Gly-Fe, control); 80 mg/kg or 115 mg/kg Gly-Fe; 80 mg/kg or 115 mg/kg methionine hydroxyl analogue chelated iron (MHA-Fe, from Calimet-Fe) for 16 weeks. The effects of dietary iron supplementation with different sources and levels on semen quality in boars were investigated. RESULTS: 1) Serum Fe and hemoglobin concentrations were not affected by reduced dietary iron levels in the 80 mg/kg or 115 mg/kg Gly-Fe and MHA-Fe groups compared with the control group (P > 0.05). 2) Serum interleukin-6 (IL-6) and sperm malondialdehyde (MDA) levels in the 80 mg/kg or 115 mg/kg MHA-Fe groups were lower than those in the control group (P < 0.05), and higher serum superoxide dismutase levels and lower MDA levels in the 115 mg/kg MHA-Fe group (P < 0.05). 3) Boars in the 80 mg/kg or 115 mg/kg Gly-Fe and MHA-Fe groups had lower serum hepcidin (P < 0.01), ferritin (P < 0.05), and transferrin receptor (P < 0.01) concentrations, and boars in the 115 mg/kg MHA-Fe group had higher seminal plasma Fe concentrations compared with the control group. 4) Boars in the 80 mg/kg and 115 mg/kg MHA-Fe groups had lower abnormal sperm rate and in situ oscillating sperm ratio compared to the control group at weeks 12 and/or 16 of the trial. However, the effect of Gly-Fe on improving semen quality in boars was not evident. 5) Serum IL-6 level was positively correlated with hepcidin concentration (P < 0.05), which in turn was significantly positively correlated with abnormal sperm rate (P < 0.05). Furthermore, significant correlations were also found between indicators of iron status and oxidative stress and semen quality parameters. CONCLUSIONS: Dietary supplementation with 80 mg/kg or 115 mg/kg MHA-Fe did not induce iron deficiency, but rather reduced serum inflammatory levels and hepcidin concentration, alleviated oxidative stress, increased body iron utilization, and improved semen quality in adult boars.

Machine learning-driven source identification and ecological risk prediction of heavy metal pollution in cultivated soils.

To overcome challenges in assessing the impact of environmental factors on heavy metal accumulation in soil due to limited comprehensive data, our study in Yangxin County, Hubei Province, China, analyzed 577 soil samples in combination with extensive big data. We used machine learning techniques, the potential ecological risk index, and the bivariate local Moran's index (BLMI) to predict Cr, Pb, Cd, As, and Hg concentrations in cultivated soil to assess ecological risks and identify pollution sources. The random forest model was selected for its superior performance among various machine learning models, and results indicated that heavy metal accumulation was substantially influenced by environmental factors such as climate, elevation, industrial activities, soil properties, railways, and population. Our ecological risk assessment highlighted areas of concern, where Cd and Hg were identified as the primary threats. BLMI was used to analyze spatial clustering and autocorrelation patterns between ecological risk and environmental factors, pinpointing areas that require targeted interventions. Additionally, redundancy analysis revealed the dynamics of heavy metal transfer to crops. This detailed approach mapped the spatial distribution of heavy metals, highlighted the ecological risks, identified their sources, and provided essential data for effective land management and pollution mitigation.

Mercury sources, transport, and transformation in rainfall-runoff processes: Mercury isotope approach.

Mercury (Hg) in runoff water poses significant ecological risks to aquatic ecosystems that can affect organisms. However, accurately identifying the sources and transformation processes of Hg in runoff water is challenging due to complex natural conditions. This study provides a comprehensive investigation of Hg dynamics in water from rainfall to runoff. The Hg isotope fractionation in water was characterized, which allows accurate quantification of Hg sources, transport, and transformations in rainfall-runoff processes. Δ200Hg and corrected Δ199Hg values can serve as reliable tracers for identifying Hg sources in the runoff water and the variation of δ202Hg can be explained by Hg transformation processes. During runoff migration processes, Hg from rainfall is rapidly absorbed on the land surface, while terrestrial Hg entering the water by the dissolution process becomes the primary component of dissolved mercury (DHg). Besides the dissolution and adsorption, microbial Hg(II) reduction and demethylation of MeHg were dominant processes for DHg in the runoff water that flows through the rice paddies, while photochemical Hg(II) reduction was the dominant process for DHg in the runoff water with low water exchange rates. Particulate Hg (PHg) in runoff water is dominantly originated by the terrestrial material and derived from the dissolution and adsorption process. Tracking sources and transformations of Hg in runoff water during the rainfall-runoff process provides a basis for studying Hg pollution in larger water bodies under complex environmental factors.

Beyond carrots: evaluation of gelling agents as wet feeds for Tenebrio molitor L. (Coleoptera: Tenebrionidae) larvae.

Previous studies have shown that larvae of the yellow mealworm, Tenebrio molitor L. (Coleoptera: Tenebrionidae), need a source of moisture to grow and perform well. Currently, much research has been oriented towards the effect of dry feed on larval growth and performance. The effect of different wet feeds as moisture source on the performance traits of T. molitor larvae has not been thoroughly investigated yet. This study aims to investigate in laboratory trials the effect of various gelling agents (agar, carrageenans, guar gum, xanthan gum, sodium alginate, modified starch, and pectin) on the growth and performance of T. molitor larvae. A number of 50 newly emerged larvae obtained from the rearings of the LEAZ were inserted in plastic vials together with 4 g of wheat bran as dry feed. Additionally, 1g of gelling agents was provided 3 times per week as moisture sources. Carrot slices served as control. Larval survival and weight were recorded weekly until the appearance of the first pupa. Dry feed was replenished when depleted. Our data showed that gelling agents efficiently supported the growth of T. molitor larvae, in terms of larval survival and weight, as well as feed utilization expressed as FCR. Interestingly, carrageenans seem to be the most appropriate gelling agent for T. molitor larvae rearing as it can enhance their weight and is also able to reduce their development time and their specific growth rate.

Coefficient of spatial variance of choroidal thickness on swept-source optical coherence tomography in healthy eyes.

PURPOSE: This study aims to introduce the coefficient of spatial variance of choroidal thickness to describe the choroidal variation and investigate its associated factors in healthy eyes. METHODS: This retrospective cross-sectional study included 1031 eyes from 1031 subjects who received a swept-source optical coherence tomography examination. The mean choroidal thickness in the macular 6 × 6 mm region and 900 subregions of 0.2 × 0.2 mm were computed using the embedded algorithm. Before analysis, potential segmentation and magnification errors were corrected. The coefficient of spatial variance was defined as the standard deviation divided by the mean (multiplied by 100%) of the choroidal thicknesses across 900 grids. Potential factors associated with the coefficient of spatial variance were assessed using multiple linear regression. RESULTS: The mean choroidal thickness of the entire 6 × 6 mm macular region was 204.50 ± 72.88 µm. The mean coefficient of spatial variance was 26.58 ± 8.24%, ranging from 11.00 to 61.58%. Statistical analysis revealed that the means choroidal thickness (ß = - 0.08, R2 = 0.42, p < 0.001) and anterior chamber depth (ß = - 2.39, R2 = 0.05, p = 0.06) were associated with the coefficient of spatial variance. CONCLUSION: Our study first incorporated the coefficient of spatial variance to represent the spatial variation of the choroidal thickness and observed that the greater thinning of the choroid is correlated with a more pronounced spatial variation.

Coherently and Incoherently Pumped Telecom C-Band Single-Photon Source with High Brightness and Indistinguishability.

Long-range, terrestrial quantum networks require high-brightness single-photon sources emitting in the telecom C-band for maximum transmission rates. For solid-state quantum emitters, the underlying pumping process, i.e., coherent or incoherent excitation schemes, impacts several photon properties such as photon indistinguishability, single-photon purity, and photon number coherence. These properties play a major role in quantum communication applications, the latter in particular for quantum cryptography. Here, we present a versatile telecom C-band single-photon source that is operated coherently and incoherently using two complementary pumping schemes. The source is based on a quantum dot coupled to a circular Bragg grating cavity, whereas coherent (incoherent) operation is performed via the novel SUPER scheme (phonon-assisted excitation). In this way, high end-to-end-efficiencies (ηend) of 5.36% (6.09%) are achieved simultaneously with a small multiphoton contribution g(2)(0) of 0.076 ± 0.001 [g(2)(0) of 0.069 ± 0.001] for coherent (incoherent) operation.

Accelerating the continuous community sharing of digital neuromorphology data.

The tree-like morphology of neurons and glia is a key cellular determinant of circuit connectivity and metabolic function in the nervous system of essentially all animals. To elucidate the contribution of specific cell types to both physiological and pathological brain states, it is important to access detailed neuroanatomy data for quantitative analysis and computational modeling. NeuroMorpho.Org is the largest online collection of freely available digital neural reconstructions and related metadata and is continuously updated with new uploads. Earlier in the project, we released multiple datasets together yearly, but this process caused an average delay of several months in making the data public. Moreover, in the past 5 years, >80% of invited authors agreed to share their data with the community via NeuroMorpho.Org, up from <20% in the first 5 years of the project. In the same period, the average number of reconstructions per publication increased 600%, creating the need for automatic processing to release more reconstructions in less time. The progressive automation of our pipeline enabled the transition to agile releases of individual datasets as soon as they are ready. The overall time from data identification to public sharing decreased by 63.7%; 78% of the datasets are now released in less than 3 months with an average workflow duration below 40 days. Furthermore, the mean processing time per reconstruction dropped from 3 h to 2 min. With these continuous improvements, NeuroMorpho.Org strives to forge a positive culture of open data. Most importantly, the new, original research enabled through reuse of datasets across the world has a multiplicative effect on science discovery, benefiting both authors and users.

A multi-source heterogeneous medical data enhancement framework based on lakehouse.

Obtaining high-quality data sets from raw data is a key step before data exploration and analysis. Nowadays, in the medical domain, a large amount of data is in need of quality improvement before being used to analyze the health condition of patients. There have been many researches in data extraction, data cleaning and data imputation, respectively. However, there are seldom frameworks integrating with these three techniques, making the dataset suffer in accuracy, consistency and integrity. In this paper, a multi-source heterogeneous data enhancement framework based on a lakehouse MHDP is proposed, which includes three steps of data extraction, data cleaning and data imputation. In the data extraction step, a data fusion technique is offered to handle multi-modal and multi-source heterogeneous data. In the data cleaning step, we propose HoloCleanX, which provides a convenient interactive procedure. In the data imputation step, multiple imputation (MI) and the SOTA algorithm SAITS, are applied for different situations. We evaluate our framework via three tasks: clustering, classification and strategy prediction. The experimental results prove the effectiveness of our data enhancement framework.

Contamination source identification for the prompt management of a gastroenteritis outbreak caused by norovirus in drinking water in Northern Italy.

In June 2022, a gastroenteritis outbreak occurred in a town in Northern Italy, possibly associated with the ingestion of norovirus from public drinking water. Noroviruses are highly infectious RNA viruses, with high stability in the environment. They are the primary cause of non-bacterial gastroenteritis worldwide, and despite the fact that the disease is mainly self-limiting, norovirus infection can lead to severe illness in the immunocompromised, the elderly and children. Immediately after the notification of the suspected norovirus outbreak, faecal specimens were collected from hospitalised patients, and water samples were collected from public drinking fountains in the affected area, to confirm the presence of norovirus. Norovirus was detected in 80 % (95 % CI 0.58-0.91) of the faecal specimens, and in 50 % (95 % CI 0.28-0.72) of the water samples using RT (reverse transcription) Real-time PCR. The identification of GII genotype in all samples confirmed public drinking water as the source of norovirus contamination. In addition, in one faeces and one water sample, the co-presence of genotypes GI and GII was detected. The strains were typed by sequencing, with most of them belonging to the genotype GII.3. Immediately after the confirmation of norovirus contamination in public drinking water, the local competent authorities applied safety measures, resulting in a decline in number of cases. Moreover, after the application of disinfection protocols in the water plant, the sampling was repeated with negative results for norovirus in the affected area. However, positive samples were found in the neighbouring area (prevalence 10.00 %, 95 % CI 0.02-0.40) and in the water spring (prevalence 50.00 %, 95 % CI 0.21-0.78), suggesting norovirus persistence and spread from the water source. The prompt identification of the source of contamination, and collaboration with the local authorities guided the implementation of proper procedures to control viral spread, resulting in the successful control of the outbreak.

Sources of Human Immunodeficiency Virus Infections Among Men Who Have Sex With Men With a Migration Background: A Viral Phylogenetic Case Study in Amsterdam, The Netherlands.

BACKGROUND: Men and women with a migration background comprise an increasing proportion of incident human immunodeficiency virus (HIV) cases across Western Europe. METHODS: To characterize sources of transmission in local transmission chains, we used partial HIV consensus sequences with linked demographic and clinical data from the opt-out AIDS Therapy Evaluation in the Netherlands (ATHENA) cohort of people with HIV in the Netherlands and identified phylogenetically and epidemiologically possible HIV transmission pairs in Amsterdam. We interpreted these in the context of estimated infection dates, and quantified population-level sources of transmission to foreign-born and Dutch-born Amsterdam men who have sex with men (MSM) within Amsterdam transmission chains. RESULTS: We estimate that Dutch-born MSM were the predominant sources of infections among all Amsterdam MSM who acquired their infection locally in 2010-2021, and among almost all foreign-born Amsterdam MSM subpopulations. Stratifying by 2-year intervals indicated time trends in transmission dynamics, with a majority of infections originating from foreign-born MSM since 2016, although uncertainty ranges remained wide. CONCLUSIONS: Native-born MSM have predominantly driven HIV transmissions in Amsterdam in 2010-2021. However, in the context of rapidly declining incidence in Amsterdam, the contribution from foreign-born MSM living in Amsterdam is increasing, with some evidence that most local transmissions have been from foreign-born Amsterdam MSM since 2016.

Source-specific ecological risk analysis and critical source identification of heavy metal(loid)s in the soil of typical abandoned coal mining area.

Long-term coal mining activities in abandoned coal mining areas have resulted in the migration of large quantities of heavy metals into the surrounding soil environment, posing a threat to the regional ecological environment. This study focuses on the surface soil collected from a typical abandoned coal mining area. Methods such as the pollution index (PI) and potential ecological risk index (RI) were used to comprehensively evaluate the pollution levels and ecological risks of soil heavy metals. Geostatistical analysis and the APCS-MLR model were used to quantify the sources of soil heavy metals, and Nemerow integrated ecological risk (NIRI) model was coupled to apportion the ecological risks from different pollution sources. The results indicate that the average concentrations of Cd, As, and Zn are 4.58, 2.44, and 1.67 times the soil background values, respectively, while the concentrations of other heavy metals are below the soil background values. The soil of study area is strongly polluted by heavy metals, with the pollution level and ecological risk of Cd being significantly higher than those of other heavy metals. The NIRI calculation results show that the overall comprehensive ecological risk level is considerable, with sample points classified as relatively considerable, moderate, and low at 60.53 %, 36.84 %, and 2.63 %, respectively. The sources of soil heavy metals can be categorized into four types: traffic activities, natural sources, coal gangue accumulation, and a combined source of coal mining and agricultural activities, with contribution rates of 35.3 %, 36.1 %, 19.5 %, and 9.1 %, respectively. The specific source ecological risk assessment results indicate that coal gangue accumulation contributes the most to ecological risk (36.4 %) and should be prioritized for pollution control, with Cd being the priority control element for ecological risk. The findings provide theoretical support for the refined management of soil heavy metal pollution in abandoned coal mining areas.

Data Flow Construction and Quality Evaluation of Electronic Source Data in Clinical Trials: Pilot Study Based on Hospital Electronic Medical Records in China.

Background: The traditional clinical trial data collection process requires a clinical research coordinator who is authorized by the investigators to read from the hospital's electronic medical record. Using electronic source data opens a new path to extract patients' data from electronic health records (EHRs) and transfer them directly to an electronic data capture (EDC) system; this method is often referred to as eSource. eSource technology in a clinical trial data flow can improve data quality without compromising timeliness. At the same time, improved data collection efficiency reduces clinical trial costs. Objective: This study aims to explore how to extract clinical trial-related data from hospital EHR systems, transform the data into a format required by the EDC system, and transfer it into sponsors' environments, and to evaluate the transferred data sets to validate the availability, completeness, and accuracy of building an eSource dataflow. Methods: A prospective clinical trial study registered on the Drug Clinical Trial Registration and Information Disclosure Platform was selected, and the following data modules were extracted from the structured data of 4 case report forms: demographics, vital signs, local laboratory data, and concomitant medications. The extracted data was mapped and transformed, deidentified, and transferred to the sponsor's environment. Data validation was performed based on availability, completeness, and accuracy. Results: In a secure and controlled data environment, clinical trial data was successfully transferred from a hospital EHR to the sponsor's environment with 100% transcriptional accuracy, but the availability and completeness of the data could be improved. Conclusions: Data availability was low due to some required fields in the EDC system not being available directly in the EHR. Some data is also still in an unstructured or paper-based format. The top-level design of the eSource technology and the construction of hospital electronic data standards should help lay a foundation for a full electronic data flow from EHRs to EDC systems in the future.

Benchmarking short and long read polishing tools for nanopore assemblies: achieving near-perfect genomes for outbreak isolates.

BACKGROUND: Oxford Nanopore provides high throughput sequencing platforms able to reconstruct complete bacterial genomes with 99.95% accuracy. However, even small levels of error can obscure the phylogenetic relationships between closely related isolates. Polishing tools have been developed to correct these errors, but it is uncertain if they obtain the accuracy needed for the high-resolution source tracking of foodborne illness outbreaks. RESULTS: We tested 132 combinations of assembly and short- and long-read polishing tools to assess their accuracy for reconstructing the genome sequences of 15 highly similar Salmonella enterica serovar Newport isolates from a 2020 onion outbreak. While long-read polishing alone improved accuracy, near perfect accuracy (99.9999% accuracy or ~ 5 nucleotide errors across the 4.8 Mbp genome, excluding low confidence regions) was only obtained by pipelines that combined both long- and short-read polishing tools. Notably, medaka was a more accurate and efficient long-read polisher than Racon. Among short-read polishers, NextPolish showed the highest accuracy, but Pilon, Polypolish, and POLCA performed similarly. Among the 5 best performing pipelines, polishing with medaka followed by NextPolish was the most common combination. Importantly, the order of polishing tools mattered i.e., using less accurate tools after more accurate ones introduced errors. Indels in homopolymers and repetitive regions, where the short reads could not be uniquely mapped, remained the most challenging errors to correct. CONCLUSIONS: Short reads are still needed to correct errors in nanopore sequenced assemblies to obtain the accuracy required for source tracking investigations. Our granular assessment of the performance of the polishing pipelines allowed us to suggest best practices for tool users and areas for improvement for tool developers.

Analysis of physical activity in psoriatic arthritis: relationship with clinical and analytical parameters and comorbidity-description of the sedentary patient.

Objective: This study aimed to relate physical activity and a sedentary lifestyle to clinical, biological, functional, and comorbid parameters in a cohort of patients with psoriatic arthritis (PsA). Methods: A cross-sectional study was conducted with 232 PsA patients. Physical activity and sedentary lifestyle were obtained using the International Physical Activity Questionnaire (IPAQ) questionnaire. The demographic, clinical, and biological variables measured were age, time since PsA diagnosis, smoking, type of treatment used, clinical form, presence of enthesitis, dactylitis (present or past), fatigue, tumor necrosis factor (TNF)-alpha, and interleukin 6 (IL-6). Activity and functionality were measured using the Disease Activity Index for Psoriatic Arthritis (DAPSA) and Health Assessment Questionnaire (HAQ) in peripheral forms, while the Ankylosing Spondylitis Disease Activity Score (ASDAS-PCR) and Bath Ankylosing Spondylitis Functional Index (BASFI) were measured in axial forms. Disease impact was assessed using the Psoriatic Arthritis Impact of Disease (PsAID) questionnaire. Alongside comorbidities, obesity, anxiety, depression [Hospital Anxiety and Depression Scale (HADS)], and sleep quality [Insomnia Severity Index (ISI)] were assessed. Results: The mean age was 54.6 (SD: 11.4) years, with 54.3% being male. A total of 25.6% of patients were sedentary. Physical activity and sedentary lifestyle were inversely correlated with fatigue, activity, functionality, and disease impact. Within comorbidities, they correlated with anxiety, depression, and insomnia. In addition, physical activity was inversely correlated with obesity. In linear regression analysis, physical activity was found to be related to body mass index (BMI) with a ß coefficient of -0.1 (p < 0.04; 95%CI: -194.1--4.5), and an R2 value of 0.11. In logistic regression analysis, a sedentary lifestyle was found to be related to pain, with an odds ratio (OR) of 1.5 (p < 0.001; 95%CI:1.1-1.8) and an R2 Nagelkerke value of 0.36. Conclusion: A quarter of the patients were sedentary. Lack of physical activity correlated with worse parameters of clinical activity, functionality, disease impact, and the presence of comorbidities.