Miracle-dz/UniFAR-FTUs huggingface dataset:
Finding the optimal tube current and iterative reconstruction strength in liver imaging; two needles in one haystack

Objectives The aim of the study was to find the lowest possible tube current and the optimal iterative reconstruction (IR) strength in abdominal imaging. Material and methods Reconstruction software was used to insert noise, simulating the use of a lower tube current. A semi-anthropomorphic abdominal phantom (Quality Assurance in Radiology and Medicine, QSA-543, Moehrendorf, Germany) was used to validate the performance of the ReconCT software (S1 Appendix). Thirty abdominal CT scans performed with a standard protocol (120 kVref, 150 mAsref) scanned at 90 kV, with dedicated contrast media (CM) injection software were selected. There were no other in- or exclusion criteria. The software was used to insert noise as if the scans were performed with 90, 80, 70 and 60% of the full dose. Consequently, the different scans were reconstructed with filtered back projection (FBP) and IR strength 2, 3 and 4. Both objective (e.g. Hounsfield units [HU], signal to noise ratio [SNR] and contrast to noise ratio [CNR]) and subjective image quality were evaluated. In addition, lesion detection was graded by two radiologists in consensus in another 30 scans (identical scan protocol) with various liver lesions, reconstructed with IR 3, 4 and 5. Results A tube current of 60% still led to diagnostic objective image quality (e.g. SNR and CNR) when IR strength 3 or 4 were used. IR strength 4 was preferred for lesion detection. The subjective image quality was rated highest for the scans performed at 90% with IR 4. Conclusion A tube current reduction of 10–40% is possible in case IR 4 is used, leading to the highest image quality (10%) or still diagnostic image quality (40%), shown by a pairwise comparison in the same patients.
A Framework for Biomarkers of COVID-19 Based on Coordination of Speech-Production Subsystems

Goal: We propose a speech modeling and signal-processing framework to detect and track COVID-19 through asymptomatic and symptomatic stages. Methods: The approach is based on complexity of neuromotor coordination across speech subsystems involved in respiration, phonation and articulation, motivated by the distinct nature of COVID-19 involving lower (i.e., bronchial, diaphragm, lower tracheal) versus upper (i.e., laryngeal, pharyngeal, oral and nasal) respiratory tract inflammation, as well as by the growing evidence of the virus’ neurological manifestations. Preliminary results: An exploratory study with audio interviews of five subjects provides Cohen's d effect sizes between pre-COVID-19 (pre-exposure) and post-COVID-19 (after positive diagnosis but presumed asymptomatic) using: coordination of respiration (as measured through acoustic waveform amplitude) and laryngeal motion (fundamental frequency and cepstral peak prominence), and coordination of laryngeal and articulatory (formant center frequencies) motion. Conclusions: While there is a strong subject-dependence, the group-level morphology of effect sizes indicates a reduced complexity of subsystem coordination. Validation is needed with larger more controlled datasets and to address confounding influences such as different recording conditions, unbalanced data quantities, and changes in underlying vocal status from pre-to-post time recordings.
Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome

Artificial intelligence and machine learning (AI/ML) is becoming increasingly more accessible to biomedical researchers with significant potential to transform biomedicine through optimization of highly-accurate predictive models and enabling better understanding of disease biology. Automated machine learning (AutoML) in particular is positioned to democratize artificial intelligence (AI) by reducing the amount of human input and ML expertise needed. However, successful translation of AI/ML in biomedicine requires moving beyond optimizing only for prediction accuracy and towards establishing reproducible clinical and biological inferences. This is especially challenging for clinical studies on rare disorders where the smaller patient cohorts and corresponding sample size is an obstacle for reproducible modeling results. Here, we present a model-agnostic framework to reinforce AutoML using strategies and tools of explainable and reproducible AI, including novel metrics to assess model reproducibility. The framework enables clinicians to interpret AutoML-generated models for clinical and biological verifiability and consequently integrate domain expertise during model development. We applied the framework towards spinal cord injury prognostication to optimize the intraoperative hemodynamic range during injury-related surgery and additionally identified a strong detrimental relationship between intraoperative hypertension and patient outcome. Furthermore, our analysis captured how evolving clinical practices such as faster time-to-surgery and blood pressure management affect clinical model development. Altogether, we illustrate how expert-augmented AutoML improves inferential reproducibility for biomedical discovery and can ultimately build trust in AI processes towards effective clinical integration.
Akaby—Cell-free protein expression system for linear templates

Cell-free protein expression is increasingly becoming popular for biotechnology, biomedical and research applications. Among cell-free systems, the most popular one is based on Escherichia coli (E. coli). Endogenous nucleases in E. coli cell-free transcription-translation (TXTL) degrade the free ends of DNA, resulting in inefficient protein expression from linear DNA templates. RecBCD is a nuclease complex that plays a major role in nuclease activity in E. coli, with the RecB subunit possessing the actual nuclease activity. We created a RecB knockout of an E. coli strain optimized for cell-free expression. We named this new strain Akaby. We demonstrated that Akaby TXTL successfully reduced linear DNA degradations, rescuing the protein expression efficiency from the linear DNA templates. The practicality of Akaby for TXTL is an efficient, simple alternative for linear template expression in cell-free reactions. We also use this work as a model protocol for modifying the TXTL source E. coli strain, enabling the creation of TXTL systems with other custom modifications.
Estimating the differences in Caesarean section (C-section) rates between public and privately insured mothers in Florida: A decomposition approach

Background Caesarean section (C-sections) is a medically critical and often life-saving procedure for prevention of childbirth complications. However, there are reports of its overuse, especially in women covered by private insurance as compared to public insurance. This study evaluates the difference in C-Section rates among nulliparous women in Florida hospitals across insurance groups and quantifies the contribution of maternal and hospital factors in explaining the difference in rates. Methods We used Florida’s inpatient data provided by the Florida Agency for HealthCare Administration (FLAHCA) and focused on low-risk births that occurred between January 1, 2010, and September 30, 2015. A Fairlie decomposition method was performed on cross-sectional data to decompose the difference in C-Section rates between insurance groups into the proportion explained versus unexplained by the differences in observable maternal and hospital factors. Results Of the 386,612 NTSV low-risk births, 72,984 were delivered via C-Section (18.87%). Higher prevalence of C-section at maternal level was associated with diabetes, hypertension, and the expectant mother being over 35 years old. Higher prevalence of C-section at the hospital level was associated with lower occupancy rate, presence of neonatal ICU (NICU) unit and higher obstetrics care level in the hospital. Private insurance coverage in expectant mothers is associated with C-section rates that were 4.4 percentage points higher as compared to that of public insurance. Just over 33.7% of the 4.4 percentage point difference in C-section rates between the two insurance groups can be accounted for by maternal and hospital factors. Conclusions The study identifies that the prevalence of C-sections in expectant mothers covered by private insurance is higher compared to mothers covered by public insurance. Although, majority of the difference in C-Section rates across insurance groups remains unexplained (around 66.3%), the main contributor that explains the other 33.7% is advancing maternal age and socioeconomic status of the expectant mother. Further investigation to explore additional factors that explain the difference needs to be done if United States wants to target specific policies to lower overall C-Section rate.
Heart-Lung Interactions During Mechanical Ventilation: Analysis via a Cardiopulmonary Simulation Model

Heart-lung interaction mechanisms are generally not well understood. Mechanical ventilation, for example, accentuates such interactions and could compromise cardiac activity. Thereby, assessment of ventilation-induced changes in cardiac function is considered an unmet clinical need. We believe that mathematical models of the human cardiopulmonary system can provide invaluable insights into such cardiorespiratory interactions. In this article, we aim to use a mathematical model to explain heart-lung interaction phenomena and provide physiologic hypotheses to certain contradictory experimental observations during mechanical ventilation. To accomplish this task, we highlight three model components that play a crucial role in heart-lung interactions: 1) pericardial membrane, 2) interventricular septum, and 3) pulmonary circulation that enables pulmonary capillary compression due to lung inflation. Evaluation of the model’s response under simulated ventilation scenarios shows good agreement with experimental data from the literature. A sensitivity analysis is also presented to evaluate the relative impact of the model’s highlighted components on the cyclic ventilation-induced changes in cardiac function.
Relationships between executive functions and sensory patterns among adults with specific learning disabilities as reflected in their daily functioning

Adults with specific learning disabilities (e.g., dyslexia, dysgraphia, and dyscalculia) reveal limitations in daily functioning in various life domains. Following previous evidence of deficient executive functions and unique sensory patterns in this population, this study examined how relationships between these two domains are expressed in daily functioning. Participants included 55 adults with specific learning disabilities and 55 controls matched by age, gender, socioeconomic status, and education. Participants completed a sociodemographic questionnaire, the Behavioral Rating Inventory of Executive Functions–adult version, and the Adolescent/Adult Sensory Profile. Results indicated significant relationships between executive functions (per the Behavioral Rating Inventory of Executive Functions–adult version) and sensory patterns (per the Adolescent/Adult Sensory Profile) as reflected in daily functioning. The low sensory registration pattern predicted 12% to 16% of the variance in the behavioral regulation index, metacognitive index, and general executive composite scores and was a significant predictor of specific executive function abilities. Results indicated that the difficulties of adults with specific learning disabilities in using executive function abilities efficiently might be tied to a high sensory threshold and passive self-regulation strategies. A deeper understanding of this population’s sensory–executive mechanisms may improve evaluation and intervention processes. This understanding can consequently increase executive abilities for improved daily functioning and life satisfaction.
CHARM: COVID-19 Health Action Response for Marines–Association of antigen-specific interferon-gamma and IL2 responses with asymptomatic and symptomatic infections after a positive qPCR SARS-CoV-2 test

SARS-CoV-2 T cell responses are associated with COVID-19 recovery, and Class I- and Class II-restricted epitopes have been identified in the spike (S), nucleocapsid (N) and membrane (M) proteins and others. This prospective COVID-19 Health Action Response for Marines (CHARM) study enabled assessment of T cell responses in symptomatic and asymptomatic SARS-CoV-2 infected participants. At enrollment all participants were negative by qPCR; follow-up occurred biweekly and then bimonthly for the next 6 weeks. Study participants who tested positive by qPCR SARS-CoV-2 test were asked to enroll in an immune response sub-study. FluoroSpot interferon-gamma (IFN-γ) and IL2 responses following qPCR-confirmed infection at enrollment (day 0), day 7 and 14 and more than 28 days later were measured using pools of 17mer peptides covering S, N, and M proteins, or CD4+CD8 peptide pools containing predicted epitopes from multiple SARS-CoV-2 antigens. Among 124 asymptomatic and 105 symptomatic participants, SARS-CoV-2 infection generated IFN-γ responses to the S, N and M proteins that persisted longer in asymptomatic cases. IFN-γ responses were significantly (p=0.001) more frequent to the N pool (51.4%) than the M pool (18.9%) among asymptomatic subjects; however, the difference was not statistically significant (p=0.06) for symptomatic subjects (N pool: 44.4%; M pool: 25.9%). In asymptomatic participants IFN-γ responders to the CD4+CD8 pool responded more frequently to the S pool (55.6%) and N pool (57.1%), than the M pool (7.1%), but symptomatic participants, IFN-γ responses were more frequent to the S pool (75.0%) than N pool (33.3%) and M pool (33.3%). The frequencies of IFN-γ responses to the S and N+M pools peaked 7 days after the positive qPCR test among asymptomatic (S pool: 22.2%; N+M pool: 28.7%) and symptomatic (S pool: 15.3%; N+M pool 21.9%) participants and dropped by >28 days. Magnitudes of post-infection IFN-γ and IL2 responses to the N+M pool were significantly correlated with IFN-γ and IL2 responses to the N and M pools. These data further support the central role of Th1-biased cell mediated immunity IFN-γ and IL2 responses, particularly to the N protein, in controlling COVID-19 symptoms, and justify T cell-based COVID-19 vaccines that include the N and S proteins.
Chronic kidney disease and atrial fibrillation: A dangerous combination

Background Chronic kidney disease (CKD) and atrial fibrillation (AF) are both risk factors for bleeding, stroke and mortality. The aim of our study was to investigate the interaction between CKD and atrial fibrillation and outcomes. Methods We included 12,394 subjects referred to the University Medical Center Utrecht (the Netherlands) from September 1996 to February 2018 for an out-patient visit (Utrecht Cardiovascular Cohort Second Manifestation of Arterial disease cohort). Hazard ratios (HRs) with 95% confidence intervals (CIs) for bleeding, ischemic stroke or mortality were calculated with Cox proportional hazard analyses. Presence of interaction between AF and CKD was examined by calculating the relative excess risk due to interaction (RERI), the attributable proportion (AP) due to interaction and the synergy index (S). Results Of the 12,394 patients, 699 patients had AF, 2,752 patients had CKD and 325 patients had both AF and CKD. Patients with both CKD and AF had a 3.0-fold (95% CI 2.0–4.4) increased risk for bleeding, a 4.2-fold (95% CI 3.0–6.0) increased ischemic stroke risk and a 2.2-fold (95% CI 1.9–2.6) increased mortality risk after adjustment as compared with subjects without atrial fibrillation and CKD. We did not find interaction between AF and CKD for bleeding and mortality. However, we found interaction between AF and CKD for ischemic stroke risk (RERI 1.88 (95% CI 0.31–3.46), AP 0.45 (95% CI 0.17–0.72) and S 2.40 (95% CI 1.08–5.32)). Conclusion AF and CKD are both associated with bleeding, ischemic stroke and mortality. There is a positive interaction between AF and CKD for ischemic stroke risk, but not for bleeding or mortality.
Alpha-band power increases in posterior brain regions in attention deficit hyperactivity disorder after digital cognitive stimulation treatment: randomized controlled study

Abstract The changes triggered by pharmacological treatments in resting-state alpha-band (8–14 Hz) oscillations have been widely studied in attention deficit hyperactivity disorder. However, to date, there has been no evidence regarding the possible changes in cognitive stimulation treatments on these oscillations. This paper sets out to verify whether cognitive stimulation treatments based on progressive increases in cognitive load can be effective in triggering changes in alpha-band power in attention deficit hyperactivity disorder. With this objective, we compared a cognitive stimulation treatment (n = 12) to a placebo treatment (n = 14) for 12 weeks (36 sessions of 15 min) in child patients (8–11 years old) with attention deficit hyperactivity disorder. Two magnetoencephalographic recordings were acquired for all participants. In order to extract the areas with changes in alpha power between both magnetoencephalographic recordings, the differences in the power ratio (pre/post-condition) were calculated using an analysis of covariance test adjusted for the age variable. The results show an increase in the post-treatment alpha power in the experimental group versus the placebo group (P < 0.01) in posterior regions. In addition, these changes were related to measures of attention, working memory and flexibility. The results seem to indicate that cognitive stimulation treatment based on progressive increases in cognitive load triggers alpha-band power changes in children diagnosed with attention deficit hyperactivity disorder in the direction of their peers without this disorder.
Long: Influence of water masses on the summer structure of the seabird community in the northeastern Chukchi Sea

We used data collected during a variety of research cruises in the northeastern Chukchi Sea and contributed to the Distributed Biological Observatory to explore the influence of the seasonal change in water masses on the development of the seabird community during the summer. Surveys that included seabird observations and hydrographic sampling were conducted from Alaska’s northwestern coast to ~220 km offshore during 2008–2018. Species composition varied geographically, shifting from a nearshore community that included short-tailed shearwaters, loons, and seaducks to an offshore community dominated by crested auklets. Crested auklets were remarkably consistent in their occupation of Hanna Shoal among years and remained in the area throughout the summer. Short-tailed shearwaters exhibited the greatest seasonal and interannual variation in abundance and distribution of the 35 species recorded. They were concentrated south of 71°N and within 50 km of shore in August and tended to spread throughout the region in September. Surface-feeding species like gulls, fulmars, and phalaropes were 1–2 orders of magnitude less abundant and had wider distributions than birds that feed by diving. Including information about hydrography improved the fit of models of seabird density. Seabirds, especially those that breed in the Bering Sea, generally were more abundant in areas dominated by moderate-salinity Bering Sea Water than nearshore in low-salinity Alaska Coastal Water. The distribution of seabirds across the northeastern Chukchi Sea reflected the heterogeneity of oceanic habitats and prey availability over the shallow shelf. Our results will inform efforts to develop ecosystem models that incorporate oceanographic conditions to predict ongoing consequences of climate change.
Feasibility Validation on Healthy Adults of a Novel Active Vibrational Sensing Based Ankle Band for Ankle Flexion Angle Estimation

Goal: In this paper, we introduced a novel ankle band with a vibrational sensor that can achieve low-cost ankle flexion angle estimation, which can be potentially used for automated ankle flexion angle estimation in home-based foot drop rehabilitation scenarios. Methods: Previous ankle flexion angle estimation methods require either professional knowledge or specific equipment and lab environment, which is not feasible for foot drop patients to achieve accurate measurement by themselves in a home-based scenario. To solve the above problems, a prototype was developed based on the assumption that the echo of a vibration signal on the tibialis anterior had different acoustic impedance distribution. By analyzing the frequency spectrum of the echo, the ankle flexion angle can be estimated. Therefore, a surface transducer was utilized to generate frequency-varying active vibration, and a contact microphone was utilized to capture the echo. A portable analog signal processing hub drove the transducer, and was used for echo signal collection from the microphone. Finally, a Random Forest regression model was applied to estimate the ankle flexion angle based on the spectrum amplitude of the echo. Results: Five healthy subjects were recruited in the experiment. The regression estimation error is 4.16 degrees, and the R2 is 0.81. Conclusions: These results demonstrate the feasibility of the proposed ankle band for accurate ankle flexion angle estimation.
Maternal occupational exposures and fetal growth in a Spanish birth cohort

While the epidemiologic literature suggests certain maternal occupational exposures may be associated with reduced measures of size at birth, the occupational literature employing fetal biometry data to assess fetal growth is sparse. The present study examines associations between maternal occupational exposures and ultrasound-measured fetal growth. We included 1,739 singleton pregnancies from the INfancia y Medio Ambiente (INMA) project (2003-2008). At 32 weeks of pregnancy, interviewers ascertained mothers’ employment status and assessed job-related physical loads, work schedules, and job strain during pregnancy. Job titles were linked to a job-exposure matrix to estimate exposure to 10 endocrine disrupting chemical (EDC) groups. We calculated z-scores from longitudinal growth curves representing trajectories from 0-12, 12-20 and 20-34 gestational weeks for abdominal circumference (AC), biparietal diameter (BPD), femur length (FL), and estimated fetal weight (EFW). Linear mixed models clustered by IMNA region (i.e., Gipuzkoa, Sabadell, Valencia) were used to examine associations between occupational exposures and fetal growth. Effect estimates are presented as percentage change in fetal growth. There was limited evidence of associations between work-related non-chemical stressors and fetal growth. We observed associations of similar magnitude between multiple EDC groups and decreased EFW trajectories during 20-34 gestational weeks (phthalates: -1.4% [-3.5, 0.6%]; alkylphenolic compounds (APCs): -1.1% [-2.3, 0.1%]; miscellaneous chemicals: -1.5% [-3.7, 0.8%]), while miscellaneous chemicals were associated with increased BPD from 12-20 weeks (2.1% [0.8, 3.5%]). Notably, 67% of women exposed to phthalates were hairdressers; 68% of women exposed to APCs worked as domestic cleaners. In conclusion, we found limited evidence that maternal occupational exposures impact fetal growth. Further research should consider the combined impact of multiple workplace exposures.