bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evolution of Service Metrics and Utilisation of Evidence-Based Outcome Measures in Anterior Cruciate Ligament Reconstruction Rehabilitation: An Observational Review of Two Cohorts in a Public Hospital Physiotherapy Department
Authors: Tuckerman Kirby , Potts Wendy , Ebrahimi Milad , Scholes Corey , Nelson Mark 
Published: March 2020

AbstractObjectiveDetermine in patients undergoing supervised rehabilitation post ACL reconstruction in a public hospital, whether a new model of care incorporating a phase-based program, compared to standard care, increased physiotherapist utilisation of outcome measures, improved service metrics such as attendance and rehabilitation completion rates, as well as increased self-reported knee function and activity levels.MethodsPatients attending outpatient physiotherapy after ACL reconstruction at a metropolitan public hospital (N = 132) were included in retrospective chart review to assess utilisation of outcomes such as quadriceps and hamstrings strength assessment, patient attendance and rehabilitation completion. Phone followup (minimum one year) was conducted to retrieve patient-reported measures of knee function (IKDC) and activity (Tegner Activity Scale). Patients were categorised by rehabilitation model of care (contemporary - time based [N = 93] vs new - phase based [N = 39]) and logistic regression used to assess the influence of patient factors and model of care on outcomes.ResultsPatients included for analysis were aged 25 years at surgery (IQR 20.3 - 30.8), with 42.4% of non-Australia country of origin. Compliance was equivalent between models of care and completion rates (formally discharged by therapist) were low (30-38%). The probability of a patient receiving strength assessment was significantly associated with model of care, sex, BMI and the number of sessions attended. The probability of a patient being recorded as discharged from the program was significantly associated with the model of care, as well as the duration and number of sessions.ConclusionThe transition to a new model of care incorporating a phase-based rehabilitation program increased physiotherapist utilisation of certain evidence-based outcome measures, increased total duration of rehabilitation and increased the total number of sessions attended. Despite this, rehabilitation completion rates remained low, and no change was demonstrated with respect to self-reported knee function and activity levels.Level of evidenceIII, retrospective case-control study
Negligible Risk of the COVID-19 Resurgence Caused by Work Resuming in China (outside Hubei): a Statistical Probability Study
Authors: Zhao Kedong , Long Cheng , Wang Yan , Zeng Tieyong , Fu Xinmiao 
Published: March 2020

AbstractThe COVID-19 outbreak in China appears to reach the late stage since late February 2020, and a stepwise restoration of economic operations is implemented. Risk assessment for such economic restoration is of significance. Here we estimated the probability of COVID-19 resurgence caused by work resuming in typical provinces/cities, and found that such probability is very limited (<5% for all the regions except Beijing). Our work may inform provincial governments to make risk level-based, differentiated control measures.
Forecasting the Worldwide Spread of COVID-19 based on Logistic Model and SEIR Model
Authors: Zhou Xiang , Ma Xudong , Hong Na , Su Longxiang , Ma Yingying , He Jie , Jiang Huizhen , Liu Chun , Shan Guangliang , Zhu Weiguo , Zhang Shuyang , Long Yun 
Published: March 2020

ABSTRACTBackgroundWith the outbreak of coronavirus disease 2019 (COVID-19), a sudden case increase in late February 2020 led to deep concern globally. Italy, South Korea, Iran, France, Germany, Spain, the US and Japan are probably the countries with the most severe outbreaks. Collecting epidemiological data and predicting epidemic trends are important for the development and measurement of public intervention strategies. Epidemic prediction results yielded by different mathematical models are inconsistent; therefore, we sought to compare different models and their prediction results to generate objective conclusions.MethodsWe used the number of cases reported from January 23 to March 20, 2020, to estimate the possible spread size and peak time of COVID-19, especially in 8 high-risk countries. The logistic growth model, basic SEIR model and adjusted SEIR model were adopted for prediction. Given that different model inputs may infer different model outputs, we implemented three model predictions with three scenarios of epidemic development.ResultsWhen comparing all 8 countries’ short-term prediction results and peak predictions, the differences among the models were relatively large. The logistic growth model estimated a smaller epidemic size than the basic SERI model did; however, once we added parameters that considered the effects of public health interventions and control measures, the adjusted SERI model results demonstrated a considerably rapid deceleration of epidemic development. Our results demonstrated that contact rate, quarantine scale, and the initial quarantine time and length are important factors in controlling epidemic size and length.ConclusionsWe demonstrated a comparative assessment of the predictions of the COVID-19 outbreak in eight high-risk countries using multiple methods. By forecasting epidemic size and peak time as well as simulating the effects of public health interventions, the intent of this paper is to help clarify the transmission dynamics of COVID-19 and recommend operation suggestions to slow down the epidemic. It is suggested that the quick detection of cases, sufficient implementation of quarantine and public self-protection behaviors are critical to slow down the epidemic.
Vitamin B12 and Risk of Diabetes: New insight from Cross-Sectional and Longitudinal Analyses of the China Stroke Primary Prevention Trial (CSPPT)
Authors: Liu Lishun , Huang Xiao , Wang Binyan , Song Yun , Lin Tengfei , Zhou Ziyi , Wang Zhuo , Wei Yaping , Guo Huiyuan , Chen Ping , Yang Yan , Ling Wenhua , Li Youbao , Qin Xianhui , Tang Genfu , Liu Chengzhang , Li Jianping , Zhang Yan , Zalloua Pierre , Wang Xiaobin , Huo Yong , Zhang Hao , Xu Xiping 
Published: March 2020

AbstractIntroductionPrevious studies in mostly Western populations, have yielded conflicting findings on the association of vitamin B12 with diabetes risk, in part, due to differences in study design and population characteristics. This study sought to examine the vitamin B12 – diabetes association in Chinese hypertensive adults by both cross-sectional and longitudinal analyses.Research Design and MethodsThis report included a total of 16699 participants from the China Stroke Primary Prevention Trial (CSPPT), with pertinent baseline and follow-up data. Diabetes mellitus (DM) was defined as either physician-diagnosed diabetes, the use of glucose-lowering drugs, or fasting blood glucose (FBG) ≥7.0 mmol/L. New-onset diabetes was defined as any new case of onset diabetes during the follow-up period or fasting blood glucose (FBG) ≥7.0 mmol/L at the exit visit.ResultsAt baseline, there were 1872 (11.2%) diabetic patients; less than 1.5% had clinical B12 deficiency (<148.0 pmol/L). Over a median follow-up period of 4.5 years, there were 1589 (10.7%) cases of new-onset diabetes. Cross-sectional analyses showed a positive association between baseline vitamin B12 levels and FBG levels (β=0.18, 95%CI 0.15-0.21) and diabetes (OR=1.42, 95%CI 1.33-1.51). However, longitudinal analyses showed no association between baseline vitamin B12 and new-onset diabetes or changes in FBG levels. Among a subset of the sample (N=4366) with both baseline and exit B12 measurements, we found a positive association between an increase in B12 and an increase in FBG.ConclusionsIn this large Chinese hypertensive population mostly sufficient with vitamin B12, parallel cross-sectional and longitudinal analyses provided new insight into the conflicting findings of previous studies, and these results underscore the need for future studies to consider both baseline vitamin B12 and its longitudinal trajectory in order to better elucidate the role of vitamin B12 in the development of diabetes. Such findings, would have important clinical and public health implications.
“The more I fear about COVID-19, the more I wear medical masks”: A survey on risk perception and medical masks’ uses
Authors: Duc Huynh Toan Luu 
Published: March 2020

AbstractThe legal behaviors in using medical masks in public have been finally promulgated by the Vietnamese Government after 47 days since the WHO declared the Public Health Emergency of International Concern (PHEIC) due to the COVID-19 pandemic. From a sample of 345 Vietnamese respondents aged from 15 to 47 years, this brief note found that the risk perception of COVID-19 danger significantly increases the likelihood of wearing the medical masks. In addition, there is a weak evidence about the differences in age under the COVID-19 outbreaks. More noticeably, those who use masks before COVID-19 pandemic tend to maintain their behaviors. Our results offer the insightful into Vietnamese citizens’ responses in terms of using medical masks; even the uses of this method are still controversial. Our results are robust by performing Exploratory Factor Analysis for five features and further regressions.
Temperature dependence of COVID-19 transmission
Authors: Notari Alessio 
Published: March 2020

AbstractThe recent coronavirus pandemic follows in its early stages an almost exponential expansion, with the number of cases as a function of time reasonably well fit byN(t) ∝eαt, in many countries. We analyze the rateαin different countries, choosing as a starting point in each country the first day with 30 cases and fitting for the following 12 days, capturing thus the early exponential growth in a rather homogeneous way. We look for a link between the rateαand the average temperatureTof each country, in the month of the epidemic growth. We analyze abaseset of 42 countries, which developed the epidemic at an earlier stage, anintermediateset of 88 countries and anextendedset of 125 countries, which developed the epidemic more recently. Fitting with a linear behaviorα(T), we find increasing evidence in the three datasets for a decreasing growth rate as a function ofT, at 99.66%C.L., 99.86%C.L. and 99.99995% C.L. (p-value 5 10−7, or 5σdetection) in thebase, intermediateandextendeddataset, respectively. The doubling time is expected to increase by 40% 50%, going from 5° C to 25° C. In thebaseset, going beyond a linear model, a peak at about (7.7 ± 3.6)°Cseems to be present in the data, but such evidence disappears for the larger datasets. Moreover we have analyzed the possible existence of a bias: poor countries, typically−located in warm regions, might have less intense testing. By excluding countries below a given GDP per capita from the dataset, we find that this affects our conclusions only slightly and only for theextendeddataset. The significance always remains high, with ap-value of about 10−310−4or less. Our findings give hope that, for northern hemisphere countries, the growth rate should significantly decrease as a result of both warmer weather and lockdown policies. In general the propagation should be hopefully stopped by strong lockdown, testing and tracking policies, before the arrival of the next cold season.
A deductive approach to modeling the spread of COVID-19
Authors: Mishra Pranav , Mishra Shekhar 
Published: March 2020

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-COV-2), previously known as 2019-nCoV, is responsible for the atypical pneumonia pandemic designated as Coronavirus Disease 2019 (COVID-19). The number of cases continues to grow exponentially reaching 492,000 people in 175 countries as of March 25, 2020. 22,169 people (∼4.5%) infected with SARS-COV-2 virus have died. We have developed an exponential regression model using the COVID-19 case data (Jan 22 – Mar 22, 2020). Our primary model uses designated Phase 1 countries, who exceed 2500 cases on Mar 22. The model is then applied to Phase 2 countries: those that escaped the initial Phase 1 global expansion of COVID-19. With the exception of stabilizing countries (South Korea, Japan, and Iran) all Phase 1 countries are growing exponentially, as per I2500(t) = 120.4 × e0.238t, with a rate, r = 0.238 ± 0.068. Excluding China, the BRICS developing nations and Australia are in Phase 2. Case data from Phase 2 countries are following the model derived from Phase 1 countries. In the absence of measures employed to flatten the curve including social distancing, quarantine, and healthcare expansion, our model projects over 274,000 cases and 12,300 deaths in the US by Mar 31. India can expect 123,000 cases by April 16. By flattening the curve to the growth rate of stabilizing countries (r = 0.044 ± 0.062), the US would prevent 8,500 deaths by Mar 31, and India would prevent 5,500 deaths by April 16.
A model to forecast regional demand for COVID-19 related hospital beds
Authors: Ferstad Johannes O. , Gu Angela , Lee Raymond Y. , Thapa Isha , Shin Andrew Y. , Salomon Joshua A. , Glynn Peter , Shah Nigam H. , Milstein Arnold , Schulman Kevin , Scheinker David 
Published: March 2020

ABSTRACTCOVID-19 threatens to overwhelm hospital facilities throughout the United States. We created an interactive, quantitative model that forecasts demand for COVID-19 related hospitalization based on county-level population characteristics, data from the literature on COVID-19, and data from online repositories. Using this information as well as user inputs, the model estimates a time series of demand for intensive care beds and acute care beds as well as the availability of those beds. The online model is designed to be intuitive and interactive so that local leaders with limited technical or epidemiological expertise may make decisions based on a variety of scenarios. This complements high-level models designed for public consumption and technically sophisticated models designed for use by epidemiologists. The model is actively being used by several academic medical centers and policy makers, and we believe that broader access will continue to aid community and hospital leaders in their response to COVID-19.LINK TO ONLINE MODELhttps://surf.stanford.edu/covid-19-tools/covid-19/
Telomere length and chromosomal instability for predicting individual radiosensitivity and risk via machine learning
Authors: Luxton Jared J. , McKenna Miles J. , Lewis Aidan M. , Taylor Lynn E. , Jhavar Sameer G. , Swanson Gregory P. , Bailey Susan M. 
Published: March 2020

AbstractThe ability to predict a cancer patient’s response to radiotherapy and risk of developing adverse late health effects would greatly improve personalized treatment regimens and individual outcomes. Telomeres represent a compelling biomarker of individual radiosensitivity and risk, as exposure can result in dysfunctional telomere pathologies that coincidentally overlap with many radiation-induced late effects, ranging from degenerative conditions like fibrosis and cardiovascular disease to proliferative pathologies like cancer. Here, telomere length was longitudinally assessed in a cohort of fifteen prostate cancer patients undergoing Intensity Modulated Radiation Therapy (IMRT) utilizing Telomere Fluorescencein situHybridization (Telo-FISH). To evaluate genome instability and enhance predictions for individual patient risk of secondary malignancy, chromosome aberrations were also assessed utilizing directional Genomic Hybridization (dGH) for high-resolution inversion detection. We present the first implementation of individual telomere length data in a machine learning model, XGBoost, trained on pre-radiotherapy (baseline) andin vitroexposed (4 Gy γ-rays) telomere length measures, to predict post-radiotherapy telomeric outcomes, which together with chromosomal instability provide insight into individual radiosensitivity and risk for radiation-induced late effects.
Longitudinal assessment of mycotoxin co-exposures in exclusively breastfed infants
Authors: Braun Dominik , Schernhammer Eva , Marko Doris , Warth Benedikt 
Published: March 2020

ABSTRACTEarly-life development of infants may be critically affected by man-made or natural contaminants including mycotoxins. However, data on the occurrence of food contaminants in breast milk is scarce and prohibits a comprehensive exposure and risk assessment for mothers and their infants.Here, we present a longitudinal exposure assessment over the first 211 days of a single newborn girl (study A) by measuring multiple mycotoxins in milk. Eighty-seven consecutive breast milk samples were obtained from the newborn’s mother living in Austria and following a regular mixed diet. Mycotoxins were analyzed by utilizing a highly sensitive LC-MS/MS approach covering 29 mycotoxins and key metabolites. In addition to this longitudinal study, three mothers provided breast milk samples each on five consecutive days, for a preliminary comparison of inter-day and inter-individual variation in exposures (study B). Study A revealed that mycotoxin occurrence in breast milk was limited to the emerging mycotoxins alternariol monomethyl ether (AME), beauvericin (BEA), enniatins (A, A1, B, B1) and to ochratoxin A (OTA), which is regulated in commercial infant food. These mycotoxins were, if present, mostly detected at very low concentrations (<10 ng/L), except AME which exceeded this concentration on two distinct days by a factor of 3x and 5x. Overall, longitudinal results indicated chronic low-dose exposure to the detected mycotoxins. Other regulated mycotoxins including the carcinogenic aflatoxins or the estrogenic zearalenone and their biotransformation products were absent in all tested samples. Study B confirmed the results of study A, with minimal inter-day and inter-individual variation. In addition, a preliminary correlation of OTA levels occurring in breast milk and matched urine samples was found (r=0.64, p=0.034) in study B. Based on the data set obtained in study A, exposure of the infant was estimated. Exposure estimates of individual mycotoxins were on average below 1 ng/kg body weight per day.Our preliminary findings suggest that recommended maximum daily intake levels might not be exceeded in the Austrian population. However, exposure is likely to be higher in populations with lower food safety standards. In the light of co-occurrence of several emerging mycotoxins in breast milk, future studies should address low-dose mixture effects. This also includes other environmental contaminants which may be present in this bio-fluid and should involve an exposome-scale risk assessment. All these efforts must be intended to minimize exposure of mothers and infants in a window of high susceptibility.
The Stochastic Resonance model of auditory perception: A unified explanation of tinnitus development, Zwicker tone illusion, and residual inhibition
Authors: Schilling Achim , Tziridis Konstantin , Schulze Holger , Krauss Patrick 
Published: March 2020

AbstractStochastic Resonance (SR) has been proposed to play a major role in auditory perception, and to maintain optimal information transmission from the cochlea to the auditory system. By this, the auditory system could adapt to changes of the auditory input at second or even sub-second timescales. In case of reduced auditory input, somatosensory projections to the dorsal cochlear nucleus would be disinhibited in order to improve hearing thresholds by means of SR. As a side effect, the increased somatosensory input corresponding to the observed tinnitus-associated neuronal hyperactivity is then perceived as tinnitus. In addition, the model can also explain transient phantom tone perceptions occurring after ear plugging, or the Zwicker tone illusion. Vice versa, the model predicts that via stimulation with acoustic noise, SR would not be needed to optimize information transmission, and hence somatosensory noise would be tuned down, resulting in a transient vanishing of tinnitus, an effect referred to as residual inhibition.
Brain structures associated with reading and their abnormalities in dyslexia: a whole-brain analysis
Authors: Kujala T. , Thiede A. , Palo-oja P. , Virtala P. , Laasonen M. , Numminen J. , Sihvonen A. J. 
Published: March 2020

AbstractDevelopmental dyslexia (DD) is a highly prevalent neurodevelopmental disorder, which often has a devastating influence on the individual’s academic achievement and career. Research on the neural origins of DD has continued for half a century, yielding, however, inconsistent results. The current study was set out to determine abnormalities of grey and white matter volumes in adults with DD and to shed light on neural architectures associated with reading and related skills. To this end, we conducted a whole-brain voxel based morphometry following current recommendations on analysis approaches, coupled with rigorous neuropsychological testing, to characterize the associations between neuroanatomy and skills vital for reading in DD. We found decreased volumes of grey matter in DD, comprising a left-hemispheric network including superior temporal and inferior frontal gyri, insula, the limbic system, and basal ganglia, and white matter, including the right middle temporal gyrus and hippocampus, as well as the right precuneus. These results are both consistent with the most robust previous findings on cortical abnormalities in DD and yield novel insight to the role of subcortical structures in DD, scarcely studied so far. Crucially, areas with decreased grey matter in DD overlapped with brain areas associated with technical reading skills. This supports the conclusion that the grey matter regions that we identified to have a low volume in DD are associated with the core areas vital for reading.
Durable Changes to Airway Mucus and Fluid Secretion Following Cholinergic Challenge
Authors: Liao Yan Shin J. , Collins Emily N. , Guevara Maria Valentina , Schurmann Veronica , Atanasova Kalina R. , Bravo Laura , Sponchiado Mariana , Hoegger Mark J. , Reznikov Leah R. 
Published: March 2020

AbstractPurposeMucus abnormalities are central to the pathophysiology of several chronic airway diseases. Mucus secretion and clearance are regulated, in part, by cholinergic innervation. Prolonged cholinergic stimulation may contribute to mucus abnormalities in disease. Thus, we tested the hypothesis that prolonged cholinergic stimulation gives rise to lasting mucus abnormalities in airways.MethodsWe delivered aerosolized bethanechol, a cholinergic agonist, to pig airways. Forty-eight hours later, we measured mucus secretion and mucociliary transport in tracheal segmentsex vivo. Tracheal and bronchoalveolar lavage concentrations of the major secreted mucus glycoproteins, mucin5B (MUC5B) or mucin5AC (MUC5AC), were measured with ELISA and antibody labeling. Pig airway epithelia were cultured at the air-liquid interface and treated with bethanechol for forty-eight hours. Stimulated fluid secretion was measured with reflected microscopy and Ussing chambers were used to measure ion transport.ResultsAirways from bethanechol-challenged pigs exhibited sheet-like mucus films, which were not associated with a greater abundance of MUC5AC or MUC5B. Epithelia treated with bethanechol had diminished fluid secretion and decreased Cl-transport. However, mucus and fluid alterations were not associated with impaired mucociliary transport.ConclusionsThese data suggest that cholinergic transmission induces sustained alterations in airway mucus properties. Such defects might compound and/or contribute to persistent mucus phenotypes found after the resolution of airway inflammation.