bluuebunny/crossref_metadata_2025_split huggingface dataset:
Learning to Kitesurf Using an Adapted Prosthesis: A Case Report
Authors: De Castro-Maqueda Guillermo , Gutiérrez-Manzanedo José V. , Minghelli Beatriz 
Published: September 2021

Case description:
Kitesurfing is a sliding water sport whose popularity and number of practitioners are growing around the world. We describe an athlete of this sport who has undergone a transfemoral amputation (right leg, at the distal third), who uses a knee prosthesis that requires flexion and extension to absorb the shocks encountered. Kitesurfing under these circumstances calls for a proper prosthesis that accommodates the various strenuous maneuvers of the sport. Mr. M, 36 years old, nonprofessional athlete, uses a special prosthesis of this type.

Objective:
We report on Mr. M, a person with a transfemoral amputation, who wanted to learn to kitesurf.

Study design:
This was a case report study.

Treatment:
A prosthesis consisting of a thigh socket interface (Iceross Seal-In X TF, Iceland), knee (SymBiotechs XT9), and a foot (MotionFoot MX), which in addition to being saltwater-resistant, combines low weight and resistance to the shocks inherent to the sport.

Outcomes:
Mr. M uses this prosthesis for kitesurfing with good results in both learning and improving. During the waterstart, he must be sitting on the beach and cannot shorten his left leg. This prosthesis adjusts its tension depending on the weather and water conditions and if the subject changes sports in such a way that it should be tensioned or relaxed depending on the needs of the new sport.

Conclusions:
This prosthesis is adapted for kitesurfing and allows precise adjustments to kitesurfing maneuvers. It has allowed the user to perform the movements of the sport with success.
Predicting, Diagnosing, and Treating Acute and Early HIV Infection in a Public Sector Facility in Eswatini
Authors: Kerschberger Bernhard , Aung Aung , Mpala Qhubekani , Ntshalintshali Nombuso , Mamba Charlie , Schomaker Michael , Tombo Marie Luce , Maphalala Gugu , Sibandze Dumile , Dube Lenhle , Kashangura Rufaro , Mthethwa-Hleza Simangele , Telnov Alex , Tour Roberto de la , Gonzalez Alan , Calmy Alexandra , Ciglenecki Iza 
Published: September 2021

Background:
The lack of acute and early HIV infection (AEHI) diagnosis and care contributes to high HIV incidence in resource-limited settings. We aimed to assess the yield of AEHI, predict and diagnose AEHI, and describe AEHI care outcomes in a public sector setting in Eswatini.

Setting:
This study was conducted in Nhlangano outpatient department from March 2019 to March 2020.

Methods:
Adults at risk of AEHI underwent diagnostic testing for AEHI with the quantitative Xpert HIV-1 viral load (VL) assay. AEHI was defined as the detection of HIV-1 VL on Xpert and either an HIV-seronegative or HIV-serodiscordant third-generation antibody-based rapid diagnostic test (RDT) result. First, the cross-sectional analysis obtained the yield of AEHI and established a predictor risk score for the prediction of AEHI using Lasso logistic regression. Second, diagnostic accuracy statistics described the ability of the fourth-generation antibody/p24 antigen–based Alere HIV-Combo RDT to diagnose AEHI (vs Xpert VL testing). Third, we described acute HIV infection care outcomes of AEHI-positive patients using survival analysis.

Results:
Of 795 HIV-seronegative/HIV-serodiscordant outpatients recruited, 30 (3.8%, 95% confidence interval: 2.6% to 5.3%) had AEHI. The predictor risk score contained several factors (HIV-serodiscordant RDT, women, feeling at risk of HIV, swollen glands, and fatigue) and had sensitivity and specificity of 83.3% and 65.8%, respectively, to predict AEHI. The HIV-Combo RDT had sensitivity and specificity of 86.2% and 99.9%, respectively, to diagnose AEHI. Of 30 AEHI-positive patients, the 1-month cumulative treatment initiation was 74% (95% confidence interval: 57% to 88%), and the 3-month viral suppression (<1000 copies/mL) was 87% (67% to 98%).

Conclusion:
AEHI diagnosis and care seem possible in resource-limited settings.
Multicenter Study of Outcomes Among Persons With HIV Who Presented to US Emergency Departments With Suspected SARS-CoV-2
Authors: Bennett Christopher L. , Ogele Emmanuel , Pettit Nicholas R. , Bischof Jason J. , Meng Tong , Govindarajan Prasanthi , Camargo Carlos A. , Nordenholz Kristen , Kline Jeffrey A. ,   on behalf of the RECOVER Investigators
Published: September 2021

Background:
There is a need to characterize patients with HIV with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Setting:
Multicenter registry of patients from 116 emergency departments in 27 US states.

Methods:
Planned secondary analysis of patients with suspected SARS-CoV-2, with (n = 415) and without (n = 25,306) HIV. Descriptive statistics were used to compare patient information and clinical characteristics by SARS-CoV-2 and HIV status. Unadjusted and multivariable models were used to explore factors associated with death, intubation, and hospital length of stay. Kaplan–Meier curves were used to estimate survival by SARS-CoV-2 and HIV infection status.

Results:
Patients with both SARS-CoV-2 and HIV and patients with SARS-CoV-2 but without HIV had similar admission rates (62.7% versus 58.6%, P = 0.24), hospitalization characteristics [eg, rates of admission to the intensive care unit from the emergency department (5.0% versus 6.3%, P = 0.45) and intubation (10% versus 13.3%, P = 0.17)], and rates of death (13.9% versus 15.1%, P = 0.65). They also had a similar cumulative risk of death (log-rank P = 0.72). However, patients with both HIV and SARS-CoV-2 infections compared with patients with HIV but without SAR-CoV-2 had worsened outcomes, including increased mortality (13.9% versus 5.1%, P < 0.01, log-rank P < 0.0001) and their deaths occurred sooner (median 11.5 versus 34 days, P < 0.01).

Conclusions:
Among emergency department patients with HIV, clinical outcomes associated with SARS-CoV-2 infection are not worse when compared with patients without HIV, but SARS-CoV-2 infection increased the risk of death in patients with HIV.
Pilot-Testing a Blended Learning Package for Health Care Workers to Improve Index Testing Services in Southern Malawi: An Implementation Science Study
Authors: Tembo Tapiwa A. , Simon Katherine R. , Kim Maria H. , Chikoti Chrissy , Huffstetler Hanna E. , Ahmed Saeed , Mang'anda Chimwemwe , Chu Stephen Q. , Manyeki Rachael , Kavuta Elijah , Majoni Robert , Phiri Duncan , Kalanga Alinafe , Rosenberg Nora E. 
Published: September 2021

Background:
HIV index testing, an intervention in which HIV-positive “indexes” (persons diagnosed with HIV) are supported to recruit their “contacts” (sexual partners and children) efficiently identifies HIV-infected persons in need of treatment and HIV-uninfected persons in need of prevention. However, index testing implementation in sub-Saharan African health care settings has been suboptimal. The objective of this study was to develop and pilot test a blended learning capacity-building package to improve index testing implementation in Malawi.

Methods:
In 2019, a blended learning package combining digital and face-to-face training modalities was field tested at 6 health facilities in Mulanje, Malawi using a pre-/post- type II hybrid design with implementation and effectiveness outcomes. Health care worker (HCW) fidelity to the intervention was assessed via observed encounters before and after the training. Preliminary effectiveness was examined by comparing index testing program indicators in the 2 months before and 4 months after the training. Indicators included the mean number of indexes screened, contacts elicited, and contacts who received HIV testing per facility per month.

Results:
On a 30-point scale, HCW fidelity to index testing protocols improved from 6.0 pre- to 25.5 post-package implementation (P = 0.002). Index testing effectiveness indicators also increased: indexes screened (pre = 63, post = 101, P < 0.001); contacts elicited (pre = 75, post = 131, P < 0.001); and contacts who received HIV testing (pre = 27, post = 41, P = 0.014).

Conclusions:
The blended learning package improved fidelity to index testing protocols and preliminary effectiveness outcomes. This package has the potential to enhance implementation of HIV index testing approaches, a necessary step for ending the HIV epidemic.
Metal Artifact Reduction With Tin Prefiltration in Computed Tomography
Authors: Hackenbroch Carsten , Schüle Simone , Halt Daniel , Zengerle Laura , Beer Meinrad 
Published: September 2021

Objectives
With the aging population and thus rising numbers of orthopedic implants (OIs), metal artifacts (MAs) increasingly pose a problem for computed tomography (CT) examinations. In the study presented here, different MA reduction techniques (iterative metal artifact reduction software [iMAR], tin prefilter technique, and dual-energy CT [DECT]) were compared.

Materials and Methods
Four human cadaver pelvises with OIs were scanned on a third-generation DECT scanner using tin prefilter (Sn), dual-energy (DE), and conventional protocols. Virtual monoenergetic CT images were generated from DE data sets. Postprocessing of CT images was performed using iMAR. Qualitative (bony structures, MA, image noise) image analysis using a 6-point Likert scale and quantitative image analysis (contrast-to-noise ratio, standard deviation of background noise) were performed by 2 observers. Statistical testing was performed using Friedman test with Nemenyi test as a post hoc test.

Results
The iMAR Sn 150 kV protocol provided the best overall assessability of bony structures and the lowest subjective image noise. The iMAR DE protocol and virtual monochromatic image (VMI) ± iMAR achieved the most effective metal artifact reduction (MAR) (P < 0.05 compared with conventional protocols). Bony structures were rated worse in VMI ± iMAR (P < 0.05) than in tin prefilter protocols ± iMAR. The DE protocol ± iMAR had the lowest contrast-to-noise ratio (P < 0.05 compared with iMAR standard) and the highest image noise (P < 0.05 compared with iMAR VMI). The iMAR reduced MA very efficiently.

Conclusions
When considering MAR and image quality, the iMAR Sn 150 kV protocol performed best overall in CT images with OI. The iMAR generated new artifacts that impaired image quality. The DECT/VMI reduced MA best, but experienced from a lack of resolution of bony fine structures.
Biomarker Analysis for Combination Therapy of Vitamin C and Thiamine in Septic Shock: A Post-Hoc Study of the ATESS Trial
Authors: Park Jong Eun , Jo You Hwan , Hwang Sung Yeon , Kim Won Young , Ryoo Seung Mok , Jang Dong-Hyun , Kim Taegyun , Kim Youn-Jung , Kim Seonwoo , Cho Hyun , Lee Gun Tak , Chung Sung Phil , Choi Sung-Hyuk , Shin Tae Gun , Suh Gil Joon 
Published: September 2021

ABSTRACT

Introduction:
We evaluated the effects of vitamin C and thiamine administration on biomarkers in patients with septic shock.

Methods:
This was a post-hoc analysis of the Ascorbic Acid and Thiamine Effect in Septic Shock (ATESS) trial, a multicenter, double-blind, randomized controlled trial. Patients were randomized to either a treatment group (intravenous vitamin C and thiamine for 48 h) or a control group. Interleukin (IL)-6, IL-10, angiopoietin-II (AP2), and S100β were assessed at baseline and at 72 h. The primary outcomes were the biomarker levels at 72 h, and the secondary outcome was reduction rate.

Results:
Forty-five patients were assigned to the treatment group and 52 were assigned to the control group. Baseline biomarker levels and at 72 h were not significantly different between the treatment and the placebo groups. The reduction rates were not significantly different between the two groups. These outcome variables showed fair diagnostic accuracy for predicting 28-day mortality according to the area under the receiver operating characteristic curve.

Conclusion:
Vitamin C and thiamine administration during the early phase of septic shock did not significantly change prognostic biomarker levels of IL-6, IL-10, AP2, and S100β.

Trial registration:
NCT, ClinicalTrials.gov NCT03756220, ATESS. Registered 28 November 2018, https://clinicaltrials.gov/ct2/show/NCT03756220.
Ideology, policy decision-making and environmental impact in the face of the Coronavirus pandemic in the US
Authors: Prieto-Rodríguez Juan , Salas Rafael , Noonan Douglas , Cabeza-Martinez Francisco , Ramos-Gutiérrez Javier 
Published: September 2021

AbstractCovid-19 pandemic was a challenge for the health systems of many countries. It altered people’s way of life and shocked the world economy. In the United States, political ideology has clashed with the fight against the pandemic. President Trump’s denial prevailed despite the warnings from the WHO and scientists who alerted of the seriousness of the situation. Despite this, some state governments did not remain passive in the absence of federal government measures, and passed laws restricting mobility (lockdowns). Consequently, the political polarity was accentuated. On the one hand, the defenders of more severe public health measures and, on the other, the advocates of individual rights and freedom above any other consideration. In this study, we analyze whether political partisanship and the political ideology has influenced the way Covid-19 was handled at the outbreak. Specifically, we analyze by using a Diff-in-Diff model, whether the ideology of each state, measure at three levels, affected the decrease in the NO2 levels observed after the pandemic outbreak in the US. We distinguish three alternative post-Covid periods and results show that the State ideology has a robust negative impact on the NO2 levels. There is an important difference between Democratic and Republican states, not just in the scope and following-up of the mobility and activity restrictions, but also in the speed they implemented them.
Neural circuit dynamics of drug-context associative learning in the hippocampus
Authors: Sun Yanjun , Giocomo Lisa M 
Published: September 2021

AbstractThe environmental context associated with previous drug consumption serves as a potent trigger for relapse to drug use. The mechanism by which existing neural representations of context are modified to incorporate information associated with a given drug however, remains unknown. Using longitudinal calcium imaging in freely behaving mice, we reveal that drug-context associations for psychostimulants and opioids are encoded in a subset of hippocampal neurons. In these neurons, drug context pairing in a conditioned place preference task weakened their spatial coding for the nondrug-paired context, with drug-induced changes to spatial coding predictive of drug-seeking behavior. Furthermore, the dissociative drug ketamine blocked both the drug-induced changes to hippocampal coding and corresponding drug-seeking behavior. Together, this work reveals how drugs of abuse can alter the hippocampal circuit to encode drug-context associations and points to the hippocampus as a key node in the cognitive process of drug addiction and context-induced drug relapse.
Intersectional, anterograde transsynaptic targeting of the neurons receiving monosynaptic inputs from two upstream regions
Authors: Kitanishi Takuma , Tashiro Mariko , Kitanishi Naomi , Mizuseki Kenji 
Published: September 2021

AbstractA brain region typically receives inputs from multiple upstream areas. However, currently, no method is available to selectively access neurons that receive monosynaptic inputs from two upstream regions. Here, we devised a method to genetically label such neurons in mice by combining the anterograde transsynaptic spread of adeno-associated virus serotype 1 (AAV1) with intersectional gene expression. Injections of AAV1s expressing either Cre or Flpo recombinases and the Cre/Flpo double-dependent AAV into two upstream regions and the downstream region, respectively, were used to label the postsynaptic neurons receiving inputs from the two upstream regions. We demonstrated this labelling in two distinct circuits: the retina/primary visual cortex to the superior colliculus and the bilateral motor cortex to the dorsal striatum. Systemic delivery of the intersectional AAV allowed for unbiased detection of the labelled neurons throughout the brain. This strategy may help analyse the interregional integration of information in the brain.
Rapid dynamic naturalistic monitoring of bradykinesia in Parkinson’s disease using a wrist-worn accelerometer
Authors: Habets Jeroen G.V. , Herff Christian , Kubben Pieter L. , Kuijf Mark L. , Temel Yasin , Evers Luc J.W. , Bloem Bastiaan R. , Starr Philip A. , Gilron Ro’ee , Little Simon 
Published: September 2021

AbstractIntroductionMotor fluctuations in Parkinson’s disease are characterized by unpredictability in the timing and duration of dopaminergic therapeutic benefit on symptoms including bradykinesia and rigidity. These fluctuations significantly impair the quality of life of many Parkinson’s patients. However, current clinical evaluation tools are not designed for the continuous, naturalistic (real-world) symptom monitoring needed to optimize clinical therapy to treat fluctuations. Although commercially available wearable motor monitoring, used over multiple days, can augment neurological decision making, the feasibility of rapid and dynamic detection of motor fluctuations is unclear. So far, applied wearable monitoring algorithms are trained on group data. Here, we investigate the influence of individual model training on short timescale classification of naturalistic bradykinesia fluctuations in Parkinson’s patients using a single wrist-accelerometer.MethodsAs part of the Parkinson@Home study protocol, 20 Parkinson patients were recorded with bilateral wrist-accelerometers for a one hour OFF medication session and a one hour ON medication session during unconstrained activities in their own homes. Kinematic metrics were extracted from the accelerometer data from the bodyside with the largest unilateral bradykinesia fluctuations across medication states. The kinematic accelerometer features were compared over the whole one-hour recordings, and medication-state classification analyses were performed on one-minute segments of data. The influence of individual versus group model training, data window length, and total amount of training patients included in group model training on classification was analyzed.ResultsStatistically significant areas under the curves (AUCs) for medication induced bradykinesia fluctuation classification were seen in 85% of the Parkinson patients at the single minute timescale using the group models. Individually trained models performed at the same level as the group trained models (mean AUC both 0.70, +/− respectively 0.18 and 0.10) despite the small individual training dataset. AUCs of the group models improved as the length of the feature windows was increased to 300 seconds, and with additional training patient datasets.ConclusionMedication induced fluctuations in bradykinesia can be classified using wrist worn accelerometery at the time scale of a single minute. Rapid, naturalistic Parkinson motor monitoring has important clinical potential to evaluate dynamic symptomatic and therapeutic fluctuations and help tailor treatments on a fast timescale.
Mosaic and non-mosaic protocadherin 19 mutation leads to neuronal hyperexcitability in zebrafish
Authors: Robens Barbara K. , Yang Xinzhu , McGraw Christopher M. , Turner Laura H. , Robens Carsten , Thyme Summer , Rotenberg Alexander , Poduri Annapurna 
Published: September 2021

AbstractEpilepsy is one of the most common neurological disorders. The X-linked gene PCDH19 is associated with sporadic and familial epilepsy in humans, typically with early-onset clustering seizures and intellectual disability in females but not in so-called ‘carrier’ males, suggesting that mosaic PCDH19 expression is required to produce epilepsy. To characterize the role of loss of PCDH19 function in epilepsy, we generated zebrafish with truncating pcdh19 variants. Evaluating zebrafish larvae for electrophysiological abnormalities, we observed hyperexcitability phenotypes in both mosaic and non-mosaic pcdh19+/- and pcdh19-/- mutant larvae. Thus, we demonstrate that the key feature of epilepsy—network hyperexcitability—can be modeled effectively in zebrafish, even though overt spontaneous seizure-like swim patterns were not observed. Further, zebrafish with non-mosaic pcdh19 mutation displayed reduced numbers of inhibitory interneurons suggesting a potential cellular basis for the observed hyperexcitability. Our findings in both mosaic and non-mosaic pcdh19 mutant zebrafish challenge the prevailing theory that mosaicism governs all PCDH19-related phenotypes and point to interneuron-mediated mechanisms underlying these phenotypes.
Defining the extent of gene function using ROC curvature
Authors: Fischer Stephan , Gillis Jesse 
Published: September 2021

AbstractMachine learning in genomics plays a key role in leveraging high-throughput data, but assessing the generalizability of performance has been a persistent challenge. Here, we propose to evaluate the generalizability of gene characterizations through the shape of performance curves. We identify Functional Equivalence Classes (FECs), uniform subsets of annotated and unannotated genes that jointly drive performance, by assessing the presence of straight lines in ROC curves. FECs are widespread across modalities and methods, and can be used to evaluate the extent and context-specificity of functional annotations in a data-driven manner. For example, FECs suggest that B cell markers can be decomposed into shared primary markers (10 to 50 genes), and tissue-specific secondary markers (100 to 500□genes). In addition, FECs are compatible with a wide range of functional encodings, with marker sets spanning at most 5% of the genome and data-driven extensions of Gene Ontology sets spanning up to 40% of the genome. Simple to assess visually and statistically, the identification of FECs in performance curves paves the way for novel functional characterization and increased robustness in analysis.
Mathematical modelling of autoimmune myocarditis and the effects of immune checkpoint inhibitors
Authors: van der Vegt Solveig A. , Polonchuk Liudmila , Wang Ken , Waters Sarah L. , Baker Ruth E. 
Published: September 2021

AbstractAutoimmune myocarditis is a rare, but frequently fatal, side effect of immune checkpoint inhibitors (ICIs), a class of cancer therapies. Despite extensive experimental work on the causes, development and progression of this disease, much still remains unknown about the importance of the different immunological pathways involved. We present a mathematical model of autoimmune myocarditis and the effects of ICIs on its development and progression to either resolution or chronic inflammation. From this, we gain a better understanding of the role of immune cells, cytokines and other components of the immune system in driving the cardiotoxicity of ICIs. We parameterise the model using existing data from the literature, and show that qualitative model behaviour is consistent with disease characteristics seen in patients in an ICI-free context. The bifurcation structures of the model show how the presence of ICIs increases the risk of developing autoimmune myocarditis. This predictive modelling approach is a first step towards determining treatment regimens that balance the benefits of treating cancer with the risk of developing autoimmune myocarditis.