bluuebunny/crossref_metadata_2025_split huggingface dataset:
Opportunities for Improving Motor Assessment and Rehabilitation After Stroke by Leveraging Video-Based Pose Estimation
Authors: Cherry-Allen Kendra M. , French Margaret A. , Stenum Jan , Xu Jing , Roemmich Ryan T. 
Published: January 2023

Abstract
Stroke is a leading cause of long-term disability in adults in the United States. As the healthcare system moves further into an era of digital medicine and remote monitoring, technology continues to play an increasingly important role in post-stroke care. In this Analysis and Perspective article, opportunities for using human pose estimation—an emerging technology that uses artificial intelligence to track human movement kinematics from simple videos recorded using household devices (e.g., smartphones, tablets)—to improve motor assessment and rehabilitation after stroke are discussed. The focus is on the potential of two key applications: (1) improving access to quantitative, objective motor assessment and (2) advancing telerehabilitation for persons post-stroke.
Factors Associated With Diagnostic Error: An Analysis of Closed Medical Malpractice Claims
Authors: Grenon Véronique , Szymonifka Jackie , Adler-Milstein Julia , Ross Jacqueline , Sarkar Urmimala 
Published: January 2023

Introduction
Missed and delayed diagnoses have received substantial attention as a quality and patient safety priority. To the extent that electronic health records, team-based care, and other mitigation strategies have been successful in improving diagnosis since the last large-scale study, we would expect that the contributing factors to diagnostic claims may have changed.

Methods
This study sought to examine paid medical malpractice claims as a proxy to identify contributing factors that reflect a clear diagnostic error. Diagnostic error cases with indemnity payments (2009–2020) were identified using the Candello (formerly known as CRICO) proprietary taxonomy. Factors associated with indemnity payments were analyzed using a multivariable logistic regression model.

Results
Of 5367 included claims, 2161 (40%) had indemnity payments. A majority of claims had multiple contributing factors on the diagnostic pathway. In multivariable analysis, factors independently associated with an indemnity payment included the insurer (odds ratio and 95% confidence interval, 2.8 [2.4–3.3]), high injury severity (1.9 [1.3–2.8]) or death (1.5 [0.99–2.1]), and case setting (inpatient (0.77 [0.65–0.91]) or emergency department (0.67 [0.49–0.92])). Importantly, cases with contributing factors outside of Candello’s diagnostic pathway were more likely to lead to indemnity payment.

Conclusions
The digital transformation and acceleration of team-based care in medicine have not mitigated the malpractice risks of complex cases with severe injuries and multiple missteps.
Acute Care Surgery and Surgical Rescue: Expanding the Definition
Authors: Diaz Jose J , Barnes Stephen , O’Meara Lindsay , Sawyer Robert , May Addison , Cullinane Daniel , Schroeppel Thomas , Chipman Amanda , Kufera Joseph , Vesselinov Roumen , Zielinski Martin ,   for the Meridian Study Group
Published: January 2023

Background:
Surgical Rescue (SR) is the recovery of patients with surgical complications. Patients transferred (TP) for surgical diagnoses to higher-level care or inpatients (IP) admitted to nonsurgical services may develop intra-abdominal infection (IAI) and require emergency surgery (ES). The aims were to characterize the SR population by the site of ES consultation, open abdomen (OA), and risk of mortality.

Study Design:
Secondary analysis of an international, multi-institutional prospective observational study of patients requiring ES for IAI. Laparotomy before the transfer was an exclusion criterion. Patients were divided into groups: Clinic/ED (C/ED), IP, or TP. Data collected included demographics, the severity of illness (SOI), procedures, OA, and # of laparotomies. The primary outcome was mortality. Multivariable logistic regression models were constructed.

Results:
There were 752 study patients [C/ED (63.8%), vs. TP (23.4%), & IP (12.8%)], with mean age of 59 and 43.6% female. IP had worse SOI scores (CCI, ASA, and SOFA). The most common procedures were small and large bowel (77.3%). IP and TP had similar rates of OA (IP 52.1% & TP 52.3 %) vs. C/ED (37.7%) (p<0.001) and IP had more relaparotomies (3-4). The unadjusted mortality rate was as highest in IP (n=24,25.0%) vs TP (n=29, 16.5%), and C/ED (n=68, 14.2%) (p=0.03). Adjusting for age and SOI, only SOI had an impact on the risk of mortality. [AUC of 86%]

Conclusions:
IP had the highest unadjusted mortality after ES for IAI and was followed by the TP; SOI drove the risk of mortality. SR must be extended to IP for timely recognition of the IAI.
Reactivity and mechanism in chemical and synthetic biology
Authors: Richards Nigel G. J. , Bearne Stephen L. , Goto Yuki , Parker Emily J. 
Published: January 2023

Physical organic chemistry and mechanistic thinking provide a strong intellectual framework for understanding the chemical logic of evolvable informational macromolecules and metabolic transformations in living organisms. These concepts have also led to numerous successes in designing and applying tools to delineate biological function in health and disease, chemical ecology and possible alternative chemistries employed by extraterrestrial life. A symposium at the 2020 Pacifichem meeting was scheduled in December 2020 to discuss designing and exploiting expanded genetic alphabets, methods to understand the biosynthesis of natural products and re-engineering primary metabolism in bacteria. The COVID-19 pandemic led to postponement of in-person discussions, with the symposium eventually being held on 20–21 December 2021 as an online event. This issue is a written record of work presented on biosynthetic pathways and enzyme catalysis, engineering microorganisms with new metabolic capabilities, and the synthesis of non-canonical, nucleobases for medical applications and for studies of alternate chemistries for living organisms. The variety of opinion pieces, reviews and original research articles provide a starting point for innovations that clarify how complex biological systems emerge from the rules of chemical reactivity and mechanism.This article is part of the themed issue ‘Reactivity and mechanism in chemical and synthetic biology’.
Success probability of high-affinity DNA aptamer generation by genetic alphabet expansion
Authors: Kimoto Michiko , Tan Hui Pen , Tan Yaw Sing , Mislan Nur Afiqah Binte Mohd , Hirao Ichiro 
Published: January 2023

Nucleic acid aptamers as antibody alternatives bind specifically to target molecules. These aptamers are generated by isolating candidates from libraries with random sequence fragments, through an evolutionary engineering system. We recently reported a high-affinity DNA aptamer generation method that introduces unnatural bases (UBs) as a fifth letter into the library, by genetic alphabet expansion. By incorporating hydrophobic UBs, the affinities of DNA aptamers to target proteins are increased over 100-fold, as compared with those of conventional aptamers with only the natural four letters. However, there is still plenty of room for improvement of the methods for routinely generating high-affinity UB-containing DNA (UB-DNA) aptamers. The success probabilities of the high-affinity aptamer generation depend on the existence of the aptamer candidate sequences in the initial library. We estimated the success probabilities by analysing several UB-DNA aptamers that we generated, as examples. In addition, we investigated the possible improvement of conventional aptamer affinities by introducing one UB at specific positions. Our data revealed that UB-DNA aptamers adopt specific tertiary structures, in which many bases including UBs interact with target proteins for high affinity, suggesting the importance of the UB-DNA library design.
This article is part of the theme issue ‘Reactivity and mechanism in chemical and synthetic biology’.
MVMRmode: Introducing an R package for plurality valid estimators for multivariable Mendelian randomisation
Authors: Woolf Benjamin , Gill Dipender , Grant Andrew J , Burgess Stephen 
Published: January 2023

AbstractBackgroundMendelian randomisation (MR) is the use of genetic variants as instrumental variables. Mode-based estimators (MBE) are one of the most popular types of estimators used in univariable-MR studies. However, because there are no plurality valid regression estimators, there are no existent modal estimators for multivariable-MR.MethodsWe use the residual method for multivariable-MR to introduce two multivariable modal estimators: multivariable-MBE, which uses IVW to create residuals fed into a traditional plurality valid estimator, and multivariable-CM which instead has the residuals fed into the contamination mixture method. We then use Monte-Carlo simulations to explore the performance of these estimators when compared to existing ones and re-analyse the data used by Grant and Burgess (2021) looking at the causal effect of intelligence, education, and household income on Alzheimer’s disease as an applied example.ResultsIn our simulation, we found that multivariable-MBE was generally too variable to be much use. Multivariable-CM produced more precise estimates on the other hand. Multivariable-CM performed better than MR-Egger in almost all settings, and Weighted Median under balanced pleiotropy. However, it underperformed Weighted Median when there was a moderate amount of directional pleiotropy. Our re-analysis supported the conclusion of Grant and Burgess (2021), that intelligence had a protective effect on Alzheimer’s disease, while education, and household income do not have a causal effect.ConclusionsHere we introduced two, non-regression-based, plurality valid estimators for multivariable MR. Of these, “multivariable-CM” which uses IVW to create residuals fed into a contamination-mixture model, performed the best. This method uses a plurality of variants valid assumption, and appears to provided precise and unbiased estimates in the presence of balanced pleiotropy and small amounts of directional pleiotropy. We developed the MVMRmode R package (available fromhttps://github.com/bar-woolf/MVMRmode/wiki) to facilitate the use of this estimator. We hope this will further enable the future triangulation of univariable MR studies which have used plurality valid estimators with multivariable MR designs.
The genetic architecture of changes in adiposity during adulthood
Authors: Venkatesh Samvida S. , Ganjgahi Habib , Palmer Duncan S. , Coley Kayesha , Wittemans Laura B. L. , Nellaker Christoffer , Holmes Chris , Lindgren Cecilia M. , Nicholson George 
Published: January 2023

AbstractObesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 1.5 million primary-care health records in over 177,000 individuals in UK Biobank to study the genetic architecture of weight-change. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (a missense variant inAPOE). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI, and higher in women than in men. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology driving quantitative trait values in adulthood.
Dermal microdialysis: a method to determine drug levels in the skin of patients with Post Kala-azar Dermal Leishmaniasis (PKDL)
Authors: Wijnant Gert-Jan , Moulik Srija , Chatterjee Kingshuk , Das Nilay K , de la Flor Raúl , Van Bocxlaer Katrien , Croft Simon L. , Chatterjee Mitali 
Published: January 2023

AbstractObjectivesPost-kala-azar-dermal leishmaniasis (PKDL) is an infectious skin disease that occurs after apparent cure from visceral leishmaniasis (VL) and causes stigmatizing lesions on the face and other exposed body parts. While the first-line drug miltefosine is typically used for 28 days to treat VL, 12 weeks of therapy is required for PKDL, highlighting the need to evaluate the extent of drug penetration at the dermal site of infection. In this proof-of-concept study, we demonstrate the use of a minimally invasive sampling technique called microdialysis to measure dermal drug exposure in a PKDL patient, providing a tool for the optimisation of treatment regimens.Methods and MaterialsThree PKDL patients receiving miltefosine (50 mg twice daily for 12 weeks) were recruited to the study. Conventional blood samples and skin biopsies were collected to determine drug content. One patient consented to undergo dermal microdialysis. Briefly, a µDialysis Linear Catheter 66 for skin and muscle, a probe with a semi-permeable membrane, was inserted in the dermis. A perfusate (a drug-free physiological solution) was pumped through the probe at a low flow rate, allowing miltefosine present in the dermis to cross the membrane and be collected in the dialysates over time. Protein-free (dialysates) and total (blood and skin biopsies) drug concentrations were analysed using LC-MS/MS.Results and conclusionsAfter confirming the presence of miltefosine in skin lesions of PKDL patients via traditional biopsy sampling, protein-free drug concentrations over time (Cmax≈ 1 µg/ml) could be detected in the infected dermis via microdialysis. This clinical proof-of-concept study thus illustrates the potential of dermal microdialysis as a minimally invasive alternative to invasive skin biopsies to quantify drug concentrations directly at the pharmacological site of action in PKDL.
Mechanistic modeling of brain metastases in NSCLC provides computational markers for personalized prediction of outcome
Authors: Benzekry Sébastien , Schlicke Pirmin , Tomasini Pascale , Simon Eléonore 
Published: January 2023

ABSTRACTBackgroundIntracranial progression after curative treatment of early-stage non-small cell lung cancer (NSCLC) occurs from 10 to 50% and is difficult to manage, given the heterogeneity of clinical presentations and the variability of treatments available.The objective of this study was to develop a mechanistic model of intracranial progression to predict survival following a first brain metastasis (BM) event.MethodsData included early-stage NSCLC patients treated with a curative intent who had a BM as the first and single relapse site (N=31).We propose a mechanistic mathematical model to estimate the amount and sizes of (visible and invisible) BMs. The two key parameters of the model areα, the proliferation rate of a single tumor cell; andμ, the per day, per cell, probability to metastasize. The predictive value of these individual computational biomarkers was evaluated.FindingsThe model was able to correctly describe the number and size of metastases at the time of first BM relapse for 20 patients. Parametersαandμwere significantly associated with overall survival (OS) (HR 1.65 (1.07-2.53) p=0.0029 and HR 1.95 (1.31-2.91) p=0.0109, respectively). Adding the computational markers to the clinical ones significantly improved the predictive value of OS (c-index increased from 0.585 (95% CI 0.569-0.602) to 0.713 (95% CI 0.700-0.726), p<0.0001).InterpretationWe demonstrated that our model was applicable to brain oligoprogressive patients in NSCLC and that the resulting computational markers had predictive potential. This may help lung cancer physicians to guide and personalize the management of NSCLC patients with intracranial oligoprogression.SIGNIFICANCE STATEMENTNon-small cell lung cancer is difficult to manage when brain metastases are present. This study presents a mathematical model that can be calibrated on individual patients’ data early in the treatment course to explain the growth dynamics of brain metastases and demonstrates that the mathematically derived parameters can serve as predictive tool in clinical routine care.Highlights-Mechanistic mathematical modeling allows individualized prognosis for lung cancer patients at first brain metastatic relapse-Individual model-derived computational parameters identifies high-risk patients in terms of brain metastasis progression and survival-Prognostic features include quantification of the number and sizes of both clinically visible and invisible brain metastases
The challenge of controlling an auditory BCI in the case of severe motor disability
Authors: Séguin Perrine , Maby Emmanuel , Fouillen Mélodie , Otman Anatole , Luauté Jacques , Giraux Pascal , Morlet Dominique , Mattout Jérémie 
Published: January 2023

AbstractBackgroundThe locked-in syndrome (LIS), due to a lesion in the pons, impedes communication. This situation can also be met after some severe brain injury or in advanced Amyotrophic Lateral Sclerosis (ALS). In the most severe condition, the persons cannot communicate at all because of a complete oculomotor paralysis (Complete LIS or CLIS). This even prevents the detection of consciousness. Some studies suggest that auditory brain-computer interface (BCI) could restore a communication through a « yes-no » code.MethodsWe developed an auditory EEG-based interface which makes use of voluntary modulations of attention, to restore a yes-no communication code in non-responding persons. This binary BCI uses repeated speech sounds (alternating “yes” on the right ear and “no” on the left ear) corresponding to either frequent (short) or rare (long) stimuli. Users are instructed to pay attention to the relevant stimuli only. We tested this BCI with 18 healthy subjects, and 7 people with severe motor disability (3 “classical” persons with locked-in syndrome and 4 persons with ALS).ResultsWe report online BCI performance and offline event-related potential analysis. On average in healthy subjects, online BCI accuracy reached 86% based on 50 questions. Only one out of 18 subjects could not perform above chance level. Ten subjects had an accuracy above 90%. However, most patients could not produce online performance above chance level, except for two people with ALS who obtained 100% accuracy. We report individual event-related potentials and their modulation by attention. In addition to the classical P3b, we observed a signature of sustained attention on responses to frequent sounds, but in healthy subjects and patients with good BCI control only.ConclusionsAuditory BCI can be very well controlled by healthy subjects, but it is not a guarantee that it can be readily used by the target population of persons in LIS or CLIS. A conclusion that is supported by a few previous findings in BCI and should now trigger research to assess the reasons of such a gap in order to propose new and efficient solutions.Clinical trial registrationsN°NCT02567201(2015) andNCT03233282(2013)
Bayesian sequential approach to monitor COVID-19 variants through positivity rate from wastewater
Authors: Montesinos-López J. Cricelio , Daza–Torres Maria L. , García Yury E. , Herrera César , Bess C. Winston , Bischel Heather N. , Nuño Miriam 
Published: January 2023

AbstractTrends in COVID-19 infection have changed throughout the pandemic due to myriad factors, including changes in transmission driven by social behavior, vaccine development and uptake, mutations in the virus genome, and public health policies. Mass testing was an essential control measure for curtailing the burden of COVID-19 and monitoring the magnitude of the pandemic during its multiple phases. However, as the pandemic progressed, new preventive and surveillance mechanisms emerged. Implementing vaccine programs, wastewater (WW) surveillance, and at-home COVID-19 tests reduced the demand for mass severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. This paper proposes a sequential Bayesian approach to estimate the COVID-19 positivity rate (PR) using SARS-CoV-2 RNA concentrations measured in WW through an adaptive scheme incorporating changes in virus dynamics. PR estimates are used to compute thresholds for WW data using the CDC thresholds for low, substantial, and high transmission. The effective reproductive number estimates are calculated using PR estimates from the WW data. This approach provides insights into the dynamics of the virus evolution and an analytical framework that combines different data sources to continue monitoring the COVID-19 trends. These results can provide public health guidance to reduce the burden of future outbreaks as new variants continue to emerge. The proposed modeling framework was applied to the City of Davis and the campus of the University of California Davis.
Covariates of success in quitting smoking in the community and secondary acute or mental health care services: a rapid systematic review
Authors: Hock Emma S. , Franklin Matthew , Baxter Susan , Clowes Mark , Chilcott Jim , Gillespie Duncan 
Published: January 2023

ABSTRACTObjectivesTo identify a comprehensive set of variables associated with quitting success among tobacco smokers contacting secondary healthcare services in the United Kingdom (UK) who are offered support to quit smoking and subsequently set a quit date.DesignRapid systematic literature review of five electronic databases.SettingStudies eligible for inclusion investigated quitting success in one of three contexts: (a) the general population in the UK; (b) people with a mental health condition; (c) quit attempts initiated within a secondary care setting.InterventionsSmoking cessation intervention in a secondary care setting.Primary and secondary outcome measuresParameters from statistical analysis showing the effects of covariates on quitting success with a statistically significant (i.e., p-value <0.05) association.ResultsThe review identified 29 relevant studies and 14 covariates of quitting success, which we grouped into four categories: demographics (age; sex; ethnicity; socio-economic conditions; relationship status, cohabitation and social network), individual health status and healthcare setting (physical health, mental health), tobacco smoking variables (current tobacco consumption, smoking history, nicotine dependence; motivation to quit; quitting history), and intervention characteristics (reduction in amount smoked prior to quitting, the nature of behavioural support, tobacco dependence treatment duration, pharmacological aids).ConclusionsFourteen data fields were identified that should be considered for inclusion in datasets and statistical analysis plans for evaluating the quitting outcomes of smoking cessation interventions initiated in secondary care contexts in the UK.Trial registrationPROSPERO CRD42021254551STRENGTHS AND LIMITATIONS OF THIS STUDYThe strengths of this review lie in the rapid but systematic approach taken and in the design of the research question and population restrictions to identify data fields important to consider in plans for the statistical analysis of the quitting outcomes of smoking cessation interventions initiated in secondary care contexts in the UK.The limitations lie in the compromises made as part of the rapid review approach, for example, our focus only on studies published in English, not searching grey literature, limited critical appraisal of the studies found.