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Current evidence supports the use of intravenous thrombolysis with alteplase in patients with wake-up stroke selected with MRI or perfusion imaging and is recommended in clinical guidelines. However, access to advanced imaging techniques is often scarce. We aimed to determine whether thrombolytic treatment with intravenous tenecteplase given within 4·5 h of awakening improves functional outcome in patients with ischaemic wake-up stroke selected using non-contrast CT.TWIST was an investigator-initiated, multicentre, open-label, randomised controlled trial with blinded endpoint assessment, conducted at 77 hospitals in ten countries. We included patients aged 18 years or older with acute ischaemic stroke symptoms upon awakening, limb weakness, a National Institutes of Health Stroke Scale (NIHSS) score of 3 or higher or aphasia, a non-contrast CT examination of the head, and the ability to receive tenecteplase within 4·5 h of awakening. Patients were randomly assigned (1:1) to either a single intravenous bolus of tenecteplase 0·25 mg per kg of bodyweight (maximum 25 mg) or control (no thrombolysis) using a central, web-based, computer-generated randomisation schedule. Trained research personnel, who conducted telephone interviews at 90 days (follow-up), were masked to treatment allocation. Clinical assessments were performed on day 1 (at baseline) and day 7 of hospital admission (or at discharge, whichever occurred first). The primary outcome was functional outcome assessed by the modified Rankin Scale (mRS) at 90 days and analysed using ordinal logistic regression in the intention-to-treat population. This trial is registered with EudraCT (2014-000096-80), ClinicalTrials.gov (NCT03181360), and ISRCTN (10601890).From June 12, 2017, to Sept 30, 2021, 578 of the required 600 patients were enrolled (288 randomly assigned to the tenecteplase group and 290 to the control group [intention-to-treat population]). The median age of participants was 73·7 years (IQR 65·9-81·1). 332 (57%) of 578 participants were male and 246 (43%) were female. Treatment with tenecteplase was not associated with better functional outcome, according to mRS score at 90 days (adjusted OR 1·18, 95% CI 0·88-1·58; p=0·27). Mortality at 90 days did not significantly differ between treatment groups (28 [10%] patients in the tenecteplase group and 23 [8%] in the control group; adjusted HR 1·29, 95% CI 0·74-2·26; p=0·37). Symptomatic intracranial haemorrhage occurred in six (2%) patients in the tenecteplase group versus three (1%) in the control group (adjusted OR 2·17, 95% CI 0·53-8·87; p=0·28), whereas any intracranial haemorrhage occurred in 33 (11%) versus 30 (10%) patients (adjusted OR 1·14, 0·67-1·94; p=0·64).In patients with wake-up stroke selected with non-contrast CT, treatment with tenecteplase was not associated with better functional outcome at 90 days. The number of symptomatic haemorrhages and any intracranial haemorrhages in both treatment groups was similar to findings from previous trials of wake-up stroke patients selected using advanced imaging. Current evidence does not support treatment with tenecteplase in patients selected with non-contrast CT.Norwegian Clinical Research Therapy in the Specialist Health Services Programme, the Swiss Heart Foundation, the British Heart Foundation, and the Norwegian National Association for Public Health.

Serology and molecular tests are the two most commonly used methods for rapid COVID-19 infection testing. The two types of tests have different mechanisms to detect infection, by measuring the presence of viral SARS-CoV-2 RNA (molecular test) or detecting the presence of antibodies triggered by the SARS-CoV-2 virus (serology test). A handful of studies have shown that symptoms, combined with demographic and/or diagnosis features, can be helpful for the prediction of COVID-19 test outcomes. However, due to nature of the test, serology and molecular tests vary significantly. There is no existing study on the correlation between serology and molecular tests, and what type of symptoms are the key factors indicating the COVID-19 positive tests. In this study, we propose a machine learning based approach to study serology and molecular tests, and use features to predict test outcomes. A total of 2,467 donors, each tested using one or multiple types of COVID-19 tests, are collected as our testbed. By cross checking test types and results, we study correlation between serology and molecular tests. For test outcome prediction, we label 2,467 donors as positive or negative, by using their serology or molecular test results, and create symptom features to represent each donor for learning. Because COVID-19 produces a wide range of symptoms and the data collection process is essentially error prone, we group similar symptoms into bins. This decreases the feature space and sparsity. Using binned symptoms, combined with demographic features, we train five classification algorithms to predict COVID-19 test results. Experiments show that XGBoost achieves the best performance with 76.85% accuracy and 81.4% AUC scores, demonstrating that symptoms are indeed helpful for predicting COVID-19 test outcomes. Our study investigates the relationship between serology and molecular tests, identifies meaningful symptom features associated with COVID-19 infection, and also provides a way for rapid screening and cost effective detection of COVID-19 infection.

Recent imaging studies with the stop-signal task in healthy individuals indicate that the subthalamic nucleus, the pre-supplementary motor area and the inferior frontal gyrus are key components of the right hemisphere “inhibitory network”. Limited information is available regarding neural substrates of inhibitory processing in patients with asymmetric Parkinson’s disease. The aim of the current fMRI study was to identify the neural changes underlying deficient inhibitory processing on the stop-signal task in patients with predominantly left-sided Parkinson’s disease. Fourteen patients and 23 healthy controls performed a stop-signal task with the left and right hands. Behaviorally, patients showed delayed response inhibition with either hand compared to controls. We found small imaging differences for the right hand, however for the more affected left hand when behavior was successfully inhibited we found reduced activation of the inferior frontal gyrus bilaterally and the insula. Using the stop-signal delay as regressor, contralateral underactivation in the right dorsolateral prefrontal cortex, inferior frontal and anterior putamen were found in patients. This finding indicates dysfunction of the right inhibitory network in left-sided Parkinson’s disease. Functional connectivity analysis of the left subthalamic nucleus showed a significant increase of connectivity with bilateral insula. In contrast, the right subthalamic nucleus showed increased connectivity with visuomotor and sensorimotor regions of the cerebellum. We conclude that altered inhibitory control in left-sided Parkinson’s disease is associated with reduced activation in regions dedicated to inhibition in healthy controls, which requires engagement of additional regions, not observed in controls, to successfully stop ongoing actions.

Clinical trials are crucial for the advancement of treatment and knowledge within the medical community. Although the ClinicalTrials.gov initiative has resulted in a rich source of information for clinical trial research, only a handful of analytic studies have been carried out to understand this valuable data source. Analysis of this database provides insight for emerging trends of clinical research. In this study, we propose to use network analysis to understand infectious disease clinical trial research. Our goal is to understand two important issues related to the clinical trials: (1) the concentrations and characteristics of infectious disease clinical trial research, and (2) recommendation of clinical trials to a sponsor (or an investigator). The first issue helps summarize clinical trial research related to a particular disease(s), and the second issue helps match clinical trial sponsors and investigators for information recommendation. By using 4228 clinical trials as the test bed, our study investigates 4864 sponsors and 1879 research areas characterized by Medical Subject Heading (MeSH) keywords. We use a network to characterize infectious disease clinical trials, and design a new community-topic-based link prediction approach to predict sponsors’ interests. Our design relies on network modeling of both clinical trial sponsors and keywords. For sponsors, we extract communities with each community consisting of sponsors with coherent interests. For keywords, we extract topics with each topic containing semantic consistent keywords. The communities and topics are combined for accurate clinical trial recommendation. This transformative study concludes that using network analysis can tremendously help the understanding of clinical trial research for effective summarization, characterization, and prediction.

In this paper, we propose to use imbalanced learning for hospital readmission prediction. The goal is to predict whether a patient, based on his/her current hospital visit records, is likely going to be re-admitted or not within 30-days after being discharged from the current hospital visit. The main challenge of hospital readmission prediction is twofold: (1) the readmission visits (i.e., the positive class) are a small portion of the total hospital visits, representing a severe class imbalance problem for learning; (2) due to privacy and health regulation, the information available for patient characterization is limited; and is often only limited to the payment level information. However, there are over 80,000 procedures code, representing a high dimensionality and high sparsity problem for learning. Motivated by the above challenges, in this paper, we design an imbalanced learning strategy to create features from patient hospital visit, by combining patient demographic information, ICD-10 clinical modification (CM) and procedure codes (PCS), and Clinical Classification Software Refined (CCSR) conversion. Instead of directly using ICD-10-CM/PCS code to characterize patients, we convert each patient’s visit to CCSR code space with a smaller feature space. By using random sampling approach to balance the sample distributions in the training set, our method achieves good performance to predict patient readmission.

The author considers the tendencies and dynamics of the development of bilateral relations between the USSR and Japan between 1980 and 1985. The main purpose of this study is to analyse the events taking place in Japan and in the world, which resulted in a drastic change in the foreign policy of the Japanese government as regarded the Soviet Union from mutually beneficial cooperation to open confrontation replete with unconcealed anti-Sovietism. The article carefully examines the actions of the go­vernments of both states directly or indirectly affecting the Japan-Soviet Union relations of the period. The author notes that the positive tendencies in the Japan-Soviet Union relations at the turn of the 1970s did not suit the representatives of the political circles in Japan who believed that the country should increase its role in the world by means of solidarity with the US global policy and a return to the Cold War. Referring to the analysis, the author concludes that despite the constant demonstration by the Soviet Union of a desire to establish good neighbourly relations with Japan, the Japan-Soviet Union relations had reached their lowest level to the point of open confrontation by the end of the first half of the 1980s. According to the author, the main reasons for such negative dynamics were the change in the foreign policy of the Japanese government for consistency with the military strategy of the United States, the unsolved territorial issue, and the military strengthening of the Far East as a direct threat to the national security of Japan.

As of March 30 2021, over 5,193 COVID-19 clinical trials have been registered through Clinicaltrial.gov. Among them, 191 trials were terminated, suspended, or withdrawn (indicating the cessation of the study). On the other hand, 909 trials have been completed (indicating the completion of the study). In this study, we propose to study underlying factors of COVID-19 trial completion vs. cessation, and design predictive models to accurately predict whether a COVID-19 trial may complete or cease in the future. We collect 4,441 COVID-19 trials from ClinicalTrial.gov to build a testbed, and design four types of features to characterize clinical trial administration, eligibility, study information, criteria, drug types, study keywords, as well as embedding features commonly used in the state-of-the-art machine learning. Our study shows that drug features and study keywords are most informative features, but all four types of features are essential for accurate trial prediction. By using predictive models, our approach achieves more than 0.87 AUC (Area Under the Curve) score and 0.81 balanced accuracy to correctly predict COVID-19 clinical trial completion vs. cessation. Our research shows that computational methods can deliver effective features to understand difference between completed vs. ceased COVID-19 trials. In addition, such models can also predict COVID-19 trial status with satisfactory accuracy, and help stakeholders better plan trials and minimize costs.

Clinical trials are crucial for the advancement of treatment and knowledge within the medical community. Since 2007, US federal government took the initiative and requires organizations sponsoring clinical trials with at least one site in the United States to submit information on these clinical trials to the ClinicalTrials.gov database, resulting in a rich source of information for clinical trial research. Nevertheless, only a handful of analytic studies have been carried out to understand this valuable data source. In this study, we propose to use network analysis to understand infectious disease clinical trial research. Our goal is to answer two important questions: (1) what are the concentrations and characteristics of infectious disease clinical trial research? and (2) how to accurately predict what type of clinical trials a sponsor (or an investigator) are interested in? The answers to the first question provide effective ways to summarize clinical trial research related to particular disease(s), and the answers to the second question help match clinical trial sponsors and investigators for information recommendation. By using 4,228 clinical trials as the test bed, our study involves 4,864 sponsors and 1,879 research areas characterized by Medical Subject Heading (MeSH) keywords. We extract a set of network measures to show patterns of infectious disease clinical trials, and design a new community based link prediction approach to predict sponsors' interests, with significant improvement compared to baselines. This trans-formative study concludes that using network analysis can tremendously help the understanding of clinical trial research for effective summarization, characterization, and prediction.

Basal cell carcinoma (BCC) is the most common malignancy diagnosed in the USA and its incidence continues to increase. While BCC is still most prevalent in the older segments of the population, it is becoming ever more frequent in younger individuals. The costs of treatment and morbidity associated with BCCs place a heavy public health and economic burden on patients, their families and the American healthcare system and underscore the importance of efficient management and prevention efforts directed toward this malignancy. In this article, we address economic aspects of BCC using evidence from large-scale epidemiological studies. This information may help clinicians in developing better and more cost-effective methods for dealing with the most common cancer in America and in the world.

We found a new type of spiral wave behavior in a homogeneous two-dimensional autowave medium. In this regime, the spiral wave tip motion transforms from a two-periodic meander into one-periodic circular rotation due to spontaneous deceleration of spiral wave drift. This discovery might be useful for insight into the nature of various phenomena and, in particular, some potentially life-threatening cardiac arrhythmias.

Dynamic and chromatographic processes of isolation and purification of antibiotics and amino acids on surface-layer ion exchangers have been investigated. It was shown that the optimum conditions of sorption and desorption on these exchangers can be determined by using a criterion for the regularity of the dynamic process. Theoretical predictions are in agreement with experimental data on the sorption and desorption of slowly diffusing organic ions.

A two-phase convective flow with convection caused by a nonuniform distribution of solid particles is considered. The use of the mathematical model proposed is illustrated by an example of a two-phase flow in a shutter sedimentation reservoir.

The process of the industrial waste water purification from solid admixtures is considered. The possibilities are shown for using the two-phase convective flow model in the hydraulic construction design.

A rate-limiting factor in the ontogeny of auditory eyeblink conditioning (EBC) is the development of sensory inputs to the pontine nucleus. One possible way to facilitate the emergence of EBC would be to use a conditioned stimulus (CS) that activates an earlier-developing sensory system. The goal of the current study was to investigate whether using a vibration CS would facilitate the ontogeny of delay EBC relative to an auditory CS. Rat pups received six sessions of delay EBC or unpaired training using either a tone or vibration CS on postnatal day (P)14-15, 17-18, 21-22, or 24-25. Conditioning with a vibration CS resulted in rapid learning as early as P17-18, whereas conditioning with a tone CS did not result in rapid conditioning until after P17-18. Control experiments verified that the differences in EBC were due to CS-specific sensory properties. The results suggest that the ontogeny of EBC depends on sensory system development.

In the present paper a mathematical model of sedimentation of a rarefied cloud of particles with account of the feedback effect of particles on the fluid is suggested. The calculations have shown that this effect changes significantly the pattern of particle motion. The results of model calculations agree fairly well with the experimental data on the sedimentation of coal dust particles in a settler.

Weak periodic external perturbations of an autowave medium can cause large-distance directed motion of the spiral wave. This happens when the period of the perturbation coincides with, or is close to the rotation period of a spiral wave, or its multiple. Such motion is called resonant or parametric drift. It may be used for low-voltage defibrillation of heart tissue. Theory of the resonant drift exists, but so far was used only qualitatively. In this paper, we show good quantitative agreement of the theory with direct numerical simulations. This is done for Complex Ginzburg-Landau Equation, one of the simplest autowave models.

Spiral waves in excitable media may drift due to interaction with medium inhomogeneities. We describe this drift asymptotically, within the kinematic (eikonal) approximation.

A free-ranging, adult male Canada-lynx (Lynx canadensis) experienced a closed, complete, non-comminuted transverse fracture of the left radius and ulna when captured in a leg snare. A dynamic compression plate (DCP) attached to the anterior surface of the radius was used to stabilize the fracture. Radiographs 44 days post-surgery indicated advanced primary bone healing. The lynx was released 46 days post-surgery near the site of capture. Radiotelemetry indicated long-term survival and movements similar to other males monitored during the same period.

A rate-limiting factor in the ontogeny of auditory eyeblink conditioning (EBC) is the development of sensory inputs to the pontine nucleus. One possible way to facilitate the emergence of EBC would be to use a conditioned stimulus (CS) that activates an earlier-developing sensory system. The goal of the current study was to investigate whether using a vibration CS would facilitate the ontogeny of delay EBC relative to an auditory CS. Rat pups received six sessions of delay EBC or unpaired training using either a tone or vibration CS on postnatal day (P)14-15, 17-18, 21-22, or 24-25. Conditioning with a vibration CS resulted in rapid learning as early as P17-18, whereas conditioning with a tone CS did not result in rapid conditioning until after P17-18. Control experiments verified that the differences in EBC were due to CS-specific sensory properties. The results suggest that the ontogeny of EBC depends on sensory system development.

Spiral waves in excitable media may drift due to interaction with medium inhomogeneities. We describe this drift asymptotically, within the kinematic (eikonal) approximation.

Experimental methods for determining the physicomechanical characteristics of powder, polymer, and composite materials under thermal-force static and dynamic loads are presented. The results of the experimental investigations are used in numerical methods for calculating the stress — strain state and the stability and for describing the supercritical behavior as well as in methods for efficient design of strong machine-building structures made from new constructional materials.

We describe an asymptotic approach to gated ionic models of single-cell cardiac excitability. It has a form essentially different from the Tikhonov fast-slow form assumed in standard asymptotic reductions of excitable systems. This is of interest since the standard approaches have been previously found inadequate to describe phenomena such as the dissipation of cardiac wave fronts and the shape of action potential at repolarization. The proposed asymptotic description overcomes these deficiencies by allowing, among other non-Tikhonov features, that a dynamical variable may change its character from fast to slow within a single solution. The general asymptotic approach is best demonstrated on an example which should be both simple and generic. The classical model of Purkinje fibers (Noble, 1962) has the simplest functional form of all cardiac models but according to the current understanding it assigns a physiologically incorrect role to the Na current. This leads us to suggest an ``Archetypal Model'' with the simplicity of the Noble model but with a structure more typical to contemporary cardiac models. We demonstrate that the Archetypal Model admits a complete asymptotic solution in quadratures. To validate our asymptotic approach, we proceed to consider an exactly solvable ``caricature'' of the Archetypal Model and demonstrate that the asymptotic of its exact solution coincides with the solutions obtained by substituting the ``caricature'' right-hand sides into the asymptotic solution of the generic Archetypal Model. This is necessary, because, unlike in standard asymptotic descriptions, no general results exist which can guarantee the proximity of the non-Tikhonov asymptotic solutions to the solutions of the corresponding detailed ionic model., 43 pages, 10 figures, submitted to Bull Math Biol 2007/04/04

Traditional means of assessing the problem of teen pregnancy have relied on national or state statistics. By using large geographic areas, usually comprised of a heterogeneous population, it is impossible to tell which subareas have more of a problem than others. This study focused on trends in teen birth rates at the health district level in New York City over a 25-year period to illustrate variations among ethnic groups. Teen birth rates were calculated based on vital statistics published by the New York City Department of Health. They were calculated as the number of births per 1,000 females in each of three age groups: under age 15, 15-17, and 18-19. Rates were calculated for the entire City, for four boroughs, and for selected health center districts. The decline in the birth rate among New York City teens is most significant in health districts populated by blacks. An exception is the noted increases in birth rates in districts populated predominantly by Hispanics. Data show substantial decreases among older teens compared to younger teens. Birth trends in small areas of New York City mirror trends seen nationwide. As migration changes the ethnic composition of small areas, it is important to monitor trends so that policies and programs can be targeted to those in need.

The effects of feedback, reinforcement, and increased food presentation on caloric intake were sequentially examined in an experimental single-case design with an anorexia nervosa patient. Although feedback on weight and a point-reinforcement system for weight gains led to increased consumption, augmenting the amount of food presented in combination with feedback and reinforcement resulted in the most dramatic change in caloric intake.