Miracle-dz/UniFAR-FTUs huggingface dataset:
Imaging features and prognostic factors in fetal and postnatal torcular dural sinus malformations, part II: synthesis of the literature and patient management

Background Torcular dural sinus malformations (tDSMs) are described as slow flow dural arteriovenous fistulae with frequently poor outcomes in the neuroangiographic literature, but other etiologies have been proposed in the obstetric literature, where outcomes have been more favorable. Objective To review tDSMs reported in the literature of multiple specialties for features that support a common etiology, and to identify key prognostic factors, with an emphasis on tDSM trajectory highlighted in part I. Methods Analysis of imaging features and clinical outcome for 77 prenatal and 22 postnatal tDSMs reported in 37 papers from the literature. Results In addition to large venous lakes, 36% of prenatal and 96% of postnatal tDSMs had evidence of arterialization, where specifically assessed. For fetal cases, where there was an observable natural history, 97% underwent a spontaneous decrease—13% after an initial increase and only 1 case with subsequent enlargement after a decrease. Prenatal cases had 83% survival (62% with a favorable outcome) whereas postnatal cases had 59% survival (29% favorable). In addition to a postnatal diagnosis, unfavorable features included ventriculomegaly, parenchymal injury, arterialization, and need for intervention. Favorable features included decreasing tDSM size, presence of clot, and increasing clot percentage. Conclusions Neonatal and fetal tDSMs have overlapping imaging appearances, suggesting a common etiology, where neonatal tDSMs represent those rare fetal tDSMs that do not undergo spontaneous regression and have a propensity for worse outcomes. Decrease in tDSM size is a critical observation when managing a tDSM because it is generally irreversible and associated with a favorable outcome.
Renal Effects and Underlying Molecular Mechanisms of Long-Term Salt Content Diets in Spontaneously Hypertensive Rats

Several evidences have shown that salt excess is an important determinant of cardiovascular and renal derangement in hypertension. The present study aimed to investigate the renal effects of chronic high or low salt intake in the context of hypertension and to elucidate the molecular mechanisms underlying such effects. To this end, newly weaned male SHR were fed with diets only differing in NaCl content: normal salt (NS: 0.3%), low salt (LS: 0.03%), and high salt diet (HS: 3%) until 7 months of age. Analysis of renal function, morphology, and evaluation of the expression of the main molecular components involved in the renal handling of albumin, including podocyte slit-diaphragm proteins and proximal tubule endocytic receptors were performed. The relationship between diets and the balance of the renal angiotensin-converting enzyme (ACE) and ACE2 enzymes was also examined. HS produced glomerular hypertrophy and decreased ACE2 and nephrin expressions, loss of morphological integrity of the podocyte processes, and increased proteinuria, characterized by loss of albumin and high molecular weight proteins. Conversely, severe hypertension was attenuated and renal dysfunction was prevented by LS since proteinuria was much lower than in the NS SHRs. This was associated with a decrease in kidney ACE/ACE2 protein and activity ratio and increased cubilin renal expression. Taken together, these results suggest that LS attenuates hypertension progression in SHRs and preserves renal function. The mechanisms partially explaining these findings include modulation of the intrarenal ACE/ACE2 balance and the increased cubilin expression. Importantly, HS worsens hypertensive kidney injury and decreases the expression nephrin, a key component of the slit diaphragm.
Determination of air pollution-related biomarkers of exposure in urine of travellers between Germany and China using liquid chromatographic and liquid chromatographic-mass spectrometric methods: a pilot study

Abstract Objective: The influence of different exposures to PM2.5 (particulate matter with an aerodynamic diameter below 2.5 μm) on the concentrations of biomarkers of exposure and oxidative stress should be investigated. For this purpose, urine samples from individuals travelling from Germany to China were collected and analysed. Materials: Robust LC and LC-MS/MS methods were established for the determination of biomarkers including 8-hydroxy-2′-deoxyguanosine, malondialdehyde, F2α-isoprostanes and hydroxylated polycyclic aromatic hydrocarbons. As a pilot study, nine volunteers travelled from Germany (mean daily concentration of PM2.5: 21 μg/m3) to China (mean daily concentration of PM2.5: 108 μg/m3). Urine samples were collected before and after the trip. Results: In samples collected after return to Germany, the median concentrations of oxidative stress biomarkers were observed to be higher than in samples collected before leaving Germany. Decreasing trends were observed in the sequences of samples collected after return in the following weeks. Correlations were found between exposure and oxidative stress biomarkers. Conclusion: Travellers are ideal models for PM pollution-induced acute health effects study. Exposure to PM pollution can cause oxidative stress and damage.
Policy transfer using Value Function as Prior Information

This work proposes an approach based on reward shaping techniques in a reinforcement learning setting to approximate the optimal decision-making process (also called the optimal policy) in a desired task with a limited amount of data. We extract prior information from an existing family of policies have been used as a heuristic to help the construction of the new one under this challenging condition. We use this approach to study the relationship between the similarity of two tasks and the minimal amount of data needed to compute a near-optimal policy for the second one using the prior information of the existing policy. Preliminary results show that for the least similar existing task considered compared to the desired one, only 10% of the dataset was needed to compute the corresponding near-optimal policy.
Discounted near-optimal control of general continuous-action nonlinear systems using optimistic planning

We propose an optimistic planning method to search for near-optimal sequences of actions in discrete-time, infinite-horizon optimal control problems with discounted rewards. The dynamics are general nonlinear, while the action (input) is scalar and compact. The method works by iteratively splitting the infinite-dimensional search space into hyperboxes. Under appropriate conditions on the dynamics and rewards, we analyze the shrinking rate of the range of possible values in each box. When coupled with a measure of problem complexity, this leads to an overall convergence rate of the algorithm to the infinite-horizon optimum, as a function of computation invested. We provide simulation results showing that the algorithm is useful in practice, and comparing it with two alternative planning methods.
Rank-based Molecular Prognosis and Network-guided Biomarker Discovery for Breast Cancer. (Pronostic moléculaire basé sur l'ordre des gènes et découverte de biomarqueurs guidé par des réseaux pour le cancer du sein)

Breast cancer is the second most common cancer worldwide and the leading cause of women's death from cancer. Improving cancer prognosis has been one of the problems of primary interest towards better clinical management and treatment decision making for cancer patients. With the rapid advancement of genomic profiling technologies in the past decades, easy availability of a substantial amount of genomic data for medical research has been motivating the currently popular trend of using computational tools, especially machine learning in the era of data science, to discover molecular biomarkers regarding prognosis improvement. This thesis is conceived following two lines of approaches intended to address two major challenges arising in genomic data analysis for breast cancer prognosis from a methodological standpoint of machine learning: rank-based approaches for improved molecular prognosis and network-guided approaches for enhanced biomarker discovery. Furthermore, the methodologies developed and investigated in this thesis, pertaining respectively to learning with rank data and learning on graphs, have a significant contribution to several branches of machine learning, concerning applications across but not limited to cancer biology and social choice theory.
National survey of paediatric audiological services for diagnosis and intervention in the South African private health care sector.

OBJECTIVE A national survey of early hearing detection and intervention services was undertaken to describe the current status of diagnostic and intervention services in the South African private health care sector. METHODS All private hospitals with obstetric units (n = 166) were surveyed telephonically. The data was integrated with data collected from self-administered questionnaires subsequently distributed nationally to private audiology practices providing hearing screening at the respective hospitals reporting hearing screening services (n = 87). Data was analysed descriptively to yield national percentages and frequency distributions. RESULTS Average reported age at diagnosis was 11 months. Most participants (74%) indicated that less than 20% of infants fitted with hearing aids received amplification before the age of 6 months. Most (64%) participants indicated that the average period between confirmed diagnosis and hearing aid fitting was 1 month, on par with international benchmarks. Only 16%-23% of participants included all diagnostic procedures recommended by the Health Professions Council of South Africa's 2007 position statement for minimum diagnostic test batteries for infants and young children. CONCLUSIONS Diagnosis of hearing loss, hearing aid fitting and audiological intervention is delayed significantly in the South African private health care sector. Improved services should include integrated systematic hospital-based screening as part of birthing packages with diagnostic referral to specialist paediatric audiologists for accurate assessment and management of patients in a timely manner.
Dietary Natural Products for Prevention and Treatment of Breast Cancer

Breast cancer is the most common cancer among females worldwide. Several epidemiological studies suggested the inverse correlation between the intake of vegetables and fruits and the incidence of breast cancer. Substantial experimental studies indicated that many dietary natural products could affect the development and progression of breast cancer, such as soy, pomegranate, mangosteen, citrus fruits, apple, grape, mango, cruciferous vegetables, ginger, garlic, black cumin, edible macro-fungi, and cereals. Their anti-breast cancer effects involve various mechanisms of action, such as downregulating ER-α expression and activity, inhibiting proliferation, migration, metastasis and angiogenesis of breast tumor cells, inducing apoptosis and cell cycle arrest, and sensitizing breast tumor cells to radiotherapy and chemotherapy. This review summarizes the potential role of dietary natural products and their major bioactive components in prevention and treatment of breast cancer, and special attention was paid to the mechanisms of action.
Handbook of Microbiological Quality Control in Pharmaceuticals and Medical Devices

Contents 1. Safe microbiological practices / Anthony W. Smith -- 2. Culture media used in pharmaceutical microbiology / Rosamund M. Baird -- 3. Sampling : principles and practice / Rosamund M. Baird -- 4. Enumeration of micro-organisms / Ronnie Millar -- 5. Identification of micro-organisms / Norman Hodges -- 6. Pharmacopoeial methods for the detection of specified micro-organisms / Norman Hodges -- 7. Rapid methods for enumeration and identification in microbiology / Paul Newby -- 8. Microbiology laboratory methods in support of the sterility assurance system / Andrew Bill -- 9. Endotoxin testing / Alan Baines -- 10. Antimicrobial preservative efficacy testing / Norman Hodges and Geoffrey Hanlon -- 11. Microbiological assay of antibiotics in pharmaceutical preparations / Colin Thompson -- 12. Disinfection and cleansing / Norman Hodges and Rosamund M. Baird -- 13. Microbiological hazard analysis and audit : the practice / Martin Lush -- 14. Case studies and worked examples. Abstract This book is a practical guide to techniques used in microbial quality assurance in the pharmaceutical industry. It aims to fill the gap in the literature between food and medical microbiology techniques books.
Risk factors for impaired pulmonary function and cardiorespiratory fitness in very long-term adult survivors of childhood acute lymphoblastic leukemia after treatment with chemotherapy only*

Abstract Background: Survivors of childhood acute lymphoblastic leukemia (ALL) are at risk of late treatment-related side-effects. Data regarding prevalence and risk factors for impairments in pulmonary function and cardiorespiratory fitness are limited, and reported findings are inconsistent and inconclusive. Material and methods: In a cross-sectional study, 116 ALL survivors (median 5 years at diagnosis, 29 years at follow-up, 53% females) were examined, median 23 years after treatment with chemotherapy only. Individual cumulative doses of cytostatic agents were calculated. Methods included blood tests, echocardiography, pulmonary function tests and cardiorespiratory exercise test. Results: Females had lower % predicted gas diffusing capacity (DLCO) than males (mean [SD] 84 [13] versus 97 [14], p < .001). Impairment in DLCO was found in 34% females versus 7% males, p < . 001. In a multiple linear regression model, female gender, body mass index (BMI) and smoking were risk factors for reduced % predicted DLCO, with a borderline significant effect of left ventricular ejection fraction (LVEF). Impaired cardiorespiratory fitness was found in 42% of the survivors, with a borderline increased risk in females, p = . 06. Smoking and BMI were risk factors for reduced % predicted VO2peak. Subjects exposed to anthracyclines had lower LVEF% and % predicted VO2peak than those not exposed, (mean [SD] 56.2 [4.3] versus 59.2 [5.2], p = .01 and 86.9 [18.4] versus 92.8 [18.4], p = .03, respectively). Conclusions: Impairments in pulmonary function and cardiorespiratory fitness are common in very long-term survivors of childhood ALL. Risk factors are female gender, BMI and smoking. In order to preserve pulmonary function and cardiorespiratory fitness, we suggest increased attention and targeted advice on modifiable lifestyle factors such as smoking, inactivity and overweight.
High precision real-time FMCW-radar signal processing performed on a levitating sphere control loop system

In this paper a brief overview of a cyber-physical demonstration system for high precision real-time FMCW-radar signal processing is presented. This system is an example for the benefits of hardware acceleration in special use cases such as FMCW-radar signal processing. To highlight the real-time capabilities a highly unstable and nonlinear control loop system, called the levitating sphere, is chosen, where the signal processing affects the stability by delaying positional information through the feedback path. A signal processing chain with real-time capabilities and a processing time of 416.9 fis for 1024 16-bit FMCW-radar IF-data samples on a Xilinx Zynq-7030 platform is presented.
Heterodimers of serotonin receptor subtypes 2 are driven by 5-HT2C protomers

The serotonin receptor subtypes 2 comprise 5-HT2A, 5-HT2B, and 5-HT2C, which are Gαq-coupled receptors and display distinct pharmacological properties. Although co-expressed in some brain regions and involved in various neurological disorders, their functional interactions have not yet been studied. We report that 5-HT2 receptors can form homo- and heterodimers when expressed alone or co-expressed in transfected cells. Co-immunoprecipitation and bioluminescence resonance energy transfer studies confirmed that 5-HT2C receptors interact with either 5-HT2A or 5-HT2B receptors. Although heterodimerization with 5-HT2C receptors does not alter 5-HT2C Gαq-dependent inositol phosphate signaling, 5-HT2A or 5-HT2B receptor-mediated signaling was totally blunted. This feature can be explained by a dominance of 5-HT2C on 5-HT2A and 5-HT2B receptor binding; in 5-HT2C-containing heterodimers, ligands bind and activate the 5-HT2C protomer exclusively. This dominant effect on the associated protomer was also observed in neurons, supporting the physiological relevance of 5-HT2 receptor heterodimerization in vivo. Accordingly, exogenous expression of an inactive form of the 5-HT2C receptor in the locus ceruleus is associated with decreased 5-HT2A-dependent noradrenergic transmission. These data demonstrate that 5-HT2 receptors can form functionally asymmetric heterodimers in vitro and in vivo that must be considered when analyzing the physiological or pathophysiological roles of serotonin in tissues where 5-HT2 receptors are co-expressed.
Distributed Collaborative Hashing and Its Applications in Ant Financial

Collaborative filtering, especially latent factor model, has been popularly used in personalized recommendation. Latent factor model aims to learn user and item latent factors from user-item historic behaviors. To apply it into real big data scenarios, efficiency becomes the first concern, including offline model training efficiency and online recommendation efficiency. In this paper, we propose a D istributed C ollaborative H ashing ( DCH ) model which can significantly improve both efficiencies. Specifically, we first propose a distributed learning framework, following the state-of-the-art parameter server paradigm, to learn the offline collaborative model. Our model can be learnt efficiently by distributedly computing subgradients in minibatches on workers and updating model parameters on servers asynchronously. We then adopt hashing technique to speedup the online recommendation procedure. Recommendation can be quickly made through exploiting lookup hash tables. We conduct thorough experiments on two real large-scale datasets. The experimental results demonstrate that, comparing with the classic and state-of-the-art (distributed) latent factor models, DCH has comparable performance in terms of recommendation accuracy but has both fast convergence speed in offline model training procedure and realtime efficiency in online recommendation procedure. Furthermore, the encouraging performance of DCH is also shown for several real-world applications in Ant Financial.
Second- and Third-line Antiretroviral Therapy for Children and Adolescents: A Scoping Review.

BACKGROUND The World Health Organization identified a need for evidence to inform revision of second- and third-line antiretroviral therapy (ART) options in children failing ART. We performed an in-depth scoping review of all available literature on second-line and subsequent ART regimens in children younger than 18 years. METHODS We comprehensively searched, without language or date limitations, the Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, the World Health Organization's International Clinical Trials Registry Platform and ClinicalTrials.gov. RESULTS The search retrieved 1982 records. Eighteen studies provided efficacy data: 1 randomized controlled trial, 7 phase II trials, 5 prospective and 5 retrospective cohorts. Five studies evaluated regimens in children failing first-line ART, 4 in children with multidrug resistance and 9 in children with variable treatment experience. Only 10/18 studies reported week 48 or month 12 outcomes. The overall proportion of children with virologic suppression defined by study at week 48 was 61.8%. Although the randomized controlled trial had low risk of bias, outcomes were similar between groups because of highly active optimized background regimens. All phase II and prospective studies were judged to have moderate to high risk of bias. No study compared currently recommended lopinavir-based second-line regimens for nonnucleoside reverse transcriptase inhibitor failures to other non-nonnucleoside reverse transcriptase inhibitor regimens head-to-head. CONCLUSIONS We found no evidence comparing current World Health Organization-recommended second- and third-line ART regimens with regimens including drugs of interest: raltegravir, darunavir, etravirine and atazanavir. Randomized controlled trials or prospective cohort studies with comparator arms, and bridging studies, ideally conducted in resource-limited settings, are required to guide future recommendations.
Fingerprint Liveness Detection Using CNN Features of Random Sample Patches

As a result of the growing use of commercial fingerprint authentication systems in mobile devices, detection of fingerprint spoofing has become increasingly important and widely used. This study proposes a fingerprint liveness- detection method based on convolutional neural network (CNN) features extracted from fingerprint patches. Firstly, fingerprints are segmented, and then data augmentation is performed to increase the size of training data. Secondly, on the augmented fingerprint, locations of patches are determined through normal distributions of segmented areas of the fingerprint image. Finally, a voting strategy is applied on all patches to make a decision of live or fake fingerprints. Experimental results show that the proposed method can be applied to fingerprint liveness detection with a 3.42% average classification error rate on a LivDet2009 Identix sensor dataset.
Fuzzy Nonlinear Dynamic Evaporator Model in Supercritical Organic Rankine Cycle Waste Heat Recovery Systems

The organic Rankine cycle (ORC)-based waste heat recovery (WHR) system operating under a supercritical condition has a higher potential of thermal efficiency and work output than a traditional subcritical cycle. However, the operation of supercritical cycles is more challenging due to the high pressure in the system and transient behavior of waste heat sources from industrial and automotive engines that affect the performance of the system and the evaporator, which is the most crucial component of the ORC. To take the transient behavior into account, the dynamic model of the evaporator using renowned finite volume (FV) technique is developed in this paper. Although the FV model can capture the transient effects accurately, the model has a limitation for real-time control applications due to its time-intensive computation. To capture the transient effects and reduce the simulation time, a novel fuzzy-based nonlinear dynamic evaporator model is also developed and presented in this paper. The results show that the fuzzy-based model was able to capture the transient effects at a data fitness of over 90%, while it has potential to complete the simulation 700 times faster than the FV model. By integrating with other subcomponent models of the system, such as pump, expander, and condenser, the predicted system output and pressure have a mean average percentage error of 3.11% and 0.001%, respectively. These results suggest that the developed fuzzy-based evaporator and the overall ORC-WHR system can be used for transient simulations and to develop control strategies for real-time applications.