Miracle-dz/UniFAR-FTUs huggingface dataset:
Cold Pulsatile Machine Perfusion versus Static Cold Storage in Kidney Transplantation: A Single Centre Experience

Introduction We present our experience with hypothermic machine perfusion (HMP) versus cold storage (CS) in relation to kidney transplant outcomes. Methods Retrospective analysis of 33 consecutive HMP kidney transplant outcomes matched with those of 33 cold stored: delayed graft function (DGF), length of hospital stay (LOS), estimated glomerular filtration rate (eGFR), and patient and graft survival were compared. Renal Resistive Indexes (RIs) during HMP in relation to DGF were also analysed. Results In the HMP group, mean HMP time was 5.7 ± 3.9 hours with a mean cold ischaemic time (CIT) of 15 ± 5.6 versus 15.1 ± 5.3 hours in the CS group. DGF was lower in the HMP group (p=0.041), and donation after Circulatory Death (DCD) was a predictor for DGF (p<0.01). HMP decreased DGF in DCD grafts (p=0.036). Patient and graft survival were similar, but eGFR at 365 days was higher in the HMP cohort (p<0.001). RIs decreased during HMP (p<0.01); 2-hours RI ≥ 0.45 mmHg/mL/min predicted DGF in DCD kidneys (75% sensitivity, 80% specificity; area under the curve 0.78); 2-hours RI ≥ 0.2 mmHg/ml/min predicted DGF in DBD grafts (sensitivity 100%, specificity 91%; area under the curve 0.87). Conclusion HMP decreased DGF compared to CS, offering viability assessment pretransplant and improving one-year renal function of the grafts.
Salmonella and Enterohemorrhagic Escherichia coli Serogroups O45, O121, O145 in Wheat Flour: Effects of Long-Term Storage and Thermal Treatments

Salmonella and enterohemorrhagic Escherichia coli (EHEC) are of serious concern in wheat flour and its related products but little is known on their survival and thermal death kinetics. This study was undertaken to determine their long-term viability and thermal inactivation kinetics in flour. Inoculation was performed using mixtures of EHEC serogroups O45, O121, O145 and Salmonella followed by storage at room temperature (23°C) or 35°C (for Salmonella). Plate counting on tryptic soy agar (TSA) and enrichment were used to assess long-term survival. For thermal studies, wheat flour samples were heated at 55, 60, 65, and 70°C and cell counts of EHEC and Salmonella were determined by plating. The δ-values were calculated using the Weibull model. At room temperature, EHEC serovars and Salmonella were quantifiable for 84 and 112 days, and were detectable for the duration of the experiment after 168 and 365 days, respectively. The δ-values were 2.0, 5.54, and 9.3 days, for EHEC O121, O45, and O145, respectively, and 9.7 days for Salmonella. However, the only significant difference among all values was the δ-value for Salmonella and serogroup O121 (p ≤ 0.05). At 35°C, Salmonella counts declined to unquantifiable levels after a week and were not detected upon enrichment after 98 days. Heat treatment of inoculated wheat flour at 55, 60, 65, and 70°C resulted in δ-value ranges of 20.0–42.9, 4.9–10.0, 2.4–3.2, and 0.2–1.6 min, respectively, for EHEC. The δ-values for Salmonella at those temperatures were 152.2, 40.8, 17.9, and 17.4 min, respectively. The δ-values obtained for Salmonella at each temperature were significantly longer than for EHEC (p ≤ 0.05). Weibull model was a good fit to describe the thermal death kinetics of Salmonella and EHEC O45, O121 and O145 in wheat flour. HIGHLIGHTS - EHEC and Salmonella can survive for extended periods of time in wheat flour. - Long-term storage inactivation curves of EHEC and Salmonella were similar. - EHEC was more sensitive to heat than Salmonella. - Weibull model was a good fit to describe thermal death kinetics of EHEC and Salmonella. - Flour storage at 35°C may be a feasible method for microbial reduction.
Topology of Learning in Artificial Neural Networks

Understanding how neural networks learn remains one of the central challenges in machine learning research. From random at the start of training, the weights of a neural network evolve in such a way as to be able to perform a variety of tasks, like classifying images. Here we study the emergence of structure in the weights by applying methods from topological data analysis. We train simple feedforward neural networks on the MNIST dataset and monitor the evolution of the weights. When initialized to zero, the weights follow trajectories that branch off recurrently, thus generating trees that describe the growth of the effective capacity of each layer. When initialized to tiny random values, the weights evolve smoothly along two-dimensional surfaces. We show that natural coordinates on these learning surfaces correspond to important factors of variation.
Substance Use, Demographic and Socioeconomic Factors Are Independently Associated With Postpartum HIV Care Engagement in the Southern United States, 1999–2016

Abstract Background Retention in care (RIC) and viral suppression (VS) are associated with reduced HIV transmission and mortality. Studies addressing postpartum engagement in HIV care have been limited by small sample size, short follow-up, and a lack of data from the Southeast United States. Methods HIV-positive adult women with ≥1 prenatal visit at the Vanderbilt Obstetrics Comprehensive Care Clinic from 1999 to 2015 were included. Poor RIC was defined as not having ≥2 encounters per year, ≥90 days apart; poor VS was a viral load >200 copies/mL. Modified Poisson regression was used to estimate adjusted relative risks (aRRs) of poor postpartum RIC and VS. Results Among 248 women over 2070 person-years of follow-up, 37.6% person-years had poor RIC and 50.4% lacked VS. Prenatal substance use was independently associated with poor RIC (aRR, 1.40; 95% confidence interval [CI], 1.08–1.80) and poor VS (aRR, 1.20; 95% CI, 1.04–1.38), and lack of VS at enrollment was associated with poor RIC (aRR, 1.64; 95% CI, 1.15–2.35) and poor VS (aRR, 1.59; 95% CI, 1.30–1.94). Hispanic women were less likely and women with lower educational attainment were more likely to have poor RIC. Women >30 years of age and married women were less likely to have poor VS. Conclusions In this population of women in prenatal care at an HIV primary medical home in Tennessee, women with prenatal substance use and a lack of VS at enrollment into prenatal care were at greater risk of poor RIC and lack of VS postpartum. Interventions aimed at improving postpartum engagement in HIV care among these high-risk groups are needed.
Amyloid β Induces Early Changes in the Ribosomal Machinery, Cytoskeletal Organization and Oxidative Phosphorylation in Retinal Photoreceptor Cells

Amyloid β (Aβ) accumulation and its aggregation is characteristic molecular feature of the development of Alzheimer’s disease (AD). More recently, Aβ has been suggested to be associated with retinal pathology associated with AD, glaucoma and drusen deposits in age related macular degeneration (AMD). In this study, we investigated the proteins and biochemical networks that are affected by Aβ in the 661 W photoreceptor cells in culture. Time and dose dependent effects of Aβ on the photoreceptor cells were determined utilizing tandem mass tag (TMT) labeling-based quantitative mass-spectrometric approach. Bioinformatic analysis of the data revealed concentration and time dependent effects of the Aβ peptide stimulation on various key biochemical pathways that might be involved in mediating the toxicity effects of the peptide. We identified increased Tau phosphorylation, GSK3β dysregulation and reduced cell viability in cells treated with Aβ in a dose and time dependent manner. This study has delineated for the first-time molecular networks in photoreceptor cells that are impacted early upon Aβ treatment and contrasted the findings with a longer-term treatment effect. Proteins associated with ribosomal machinery homeostasis, mitochondrial function and cytoskeletal organization were affected in the initial stages of Aβ exposure, which may provide key insights into AD effects on the photoreceptors and specific molecular changes induced by Aβ peptide.
Evaluating the Search Phase of Neural Architecture Search

Neural Architecture Search (NAS) aims to facilitate the design of deep networks for new tasks. Existing techniques rely on two stages: searching over the architecture space and validating the best architecture. NAS algorithms are currently compared solely based on their results on the downstream task. While intuitive, this fails to explicitly evaluate the effectiveness of their search strategies. In this paper, we propose to evaluate the NAS search phase. To this end, we compare the quality of the solutions obtained by NAS search policies with that of random architecture selection. We find that: (i) On average, the state-of-the-art NAS algorithms perform similarly to the random policy; (ii) the widely-used weight sharing strategy degrades the ranking of the NAS candidates to the point of not reflecting their true performance, thus reducing the effectiveness of the search process. We believe that our evaluation framework will be key to designing NAS strategies that consistently discover architectures superior to random ones.
Development and Survival of Lygus hesperus (Hemiptera: Miridae) Nymphs Under Constant and Variable Temperatures

Abstract Thermal environments of the arid western United States are often harsh compared with the ranges of temperatures favorable for development and survival of crop insect pests. In cotton [Gossypium spp. (Malvales: Malvaceae)], new irrigation practices such as deficit irrigation may impact populations of pest and beneficial arthropods by temporarily altering temperature profiles within the plant canopy. Most information regarding the temperature-dependent development and survival of an important cotton pest, the western tarnished plant bug (Lygus hesperus Knight), is derived from constant temperature studies. We examined the development and survival of L. hesperus nymphs under constant (±0.2°C) and variable (±8°C) temperature regimes at daily mean temperatures of 15, 22, and 29°C. Under the low temperature (15°C), stadium lengths and duration of the nymphal stage were shorter when temperatures were variable compared with a constant temperature. No differences in development times were observed between regimes at the medium temperature (22°C). Except for the first stadium, development times under the high variable temperature regime were longer compared with the high constant regime (29°C). Nymph survival was unaffected by temperature regime except at the lowest temperature, where daily thermal fluctuations substantially improved survival compared with the constant conditions. These results suggest that temporarily increased crop canopy temperatures caused by altered irrigation schemes are unlikely to substantially reduce the growth of L. hesperus populations. However, enhanced nymphal development and survival under low variable temperatures likely contribute to the survival of overwintering L. hesperus in the absence of acute, low-temperature mortality.
Serotonergic Contributions to Human Brain Aggression Networks

Aggressive behavior is associated with dysfunctional frontolimbic emotion regulation circuits. Recent findings suggest serotonin as a primary transmitter for prefrontal amygdala control. However, the association between serotonin levels, amygdala regulation, and aggression is still a matter of debate. Neurobehavioral models furthermore suggest a possible mediating influence of the monoamine oxidase A gene (MAOA) on this brain-behavior relationship, with carriers of low expressing allele varieties being a risk group for aggression. In the present study, we investigated the influence of brain serotonin modulation and MAOA genotype on functional amygdala connectivity during aggressive behavior. Modulation of serotonergic neurotransmission with acute tryptophan depletion (ATD) and placebo were administered in a double-blind, cross-over design in 38 healthy male participants. Aggressive behavior was modeled in a violent video game during simultaneous assessment of brain activation with functional magnetic resonance imaging (fMRI). Trait aggression was measured with the Buss-Perry Aggression Questionnaire (BP-AQ), and MAOA genotypes were assessed from blood samples. Voxel-wise functional connectivity with anatomically defined amygdala was calculated from the functional data. Tryptophan depletion with ATD reduced aggression-specific amygdala connectivity with bilateral supramarginal gyrus. Moreover, ATD impact was associated with trait aggression and MAOA genotype in prefrontal cortex regions. In summary, serotonergic corticolimbic projections contribute to aggressive behavior. Genotype-specific vulnerability of frontolimbic projections may underlie the elevated risk in low expressing allele carriers.
A Growth Mixture Modeling Study of Learning Trajectories in an Extended Computerized Working Memory Training Programme Developed for Young Children Diagnosed With Attention-Deficit/Hyperactivity Disorder

This study explored (1) whether growth mixture modelling (GMM) could identify different trajectories of learning efficiency during a working memory (WM) training programme for young children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD), compared with a typically developing (TD) control group, and (2) if learning trajectories and outcomes were different for simple and complex training tasks. Children completed simple visuospatial short-term memory (VSSTM) and complex visuospatial WM (VSWM) tasks for 15 minutes a day, 5 days a week and for 8 weeks. Parent-reported executive functioning, and children’s WM and attention control, educational achievement, and IQ were measured prior to (T1), immediately following (T2) and three months after training (T3). GMM analysis showed that WM training was represented as one learning curve, and there was no difference for the trajectories of the ADHD and TD groups. The learning trajectory for the VSSTM tasks across groups was represented as one learning curve and for the VSWM tasks there were three learning curves. Learning for the VSSTM tasks and for most children in the VSWM tasks was characterized by an inverted-U shape, indicating that training was effective for up to 15 sessions, was stable and declined thereafter, highlighting an optimal training timeframe. For the VSWM tasks, the two remaining groups showed either a U-shaped or a high inverted U-shaped trajectory, with the latter group achieving the highest T1T2 change score (i.e., children showed a lower starting point and the most gain in terms of learning and post-training performance). There were no broader benefits of training at post-test or follow-up. Further research should explore who would benefit most from intensive cognitive training, as well as the potential benefits for mental health and well-being. Keywords. WM training, learning trajectories, young children, Attention-Deficit/Hyperactivity Disorder (ADHD), Growth Mixture Modelling (GMM).
Statistics and Samples in Distributional Reinforcement Learning

We present a unifying framework for designing and analysing distributional reinforcement learning (DRL) algorithms in terms of recursively estimating statistics of the return distribution. Our key insight is that DRL algorithms can be decomposed as the combination of some statistical estimator and a method for imputing a return distribution consistent with that set of statistics. With this new understanding, we are able to provide improved analyses of existing DRL algorithms as well as construct a new algorithm (EDRL) based upon estimation of the expectiles of the return distribution. We compare EDRL with existing methods on a variety of MDPs to illustrate concrete aspects of our analysis, and develop a deep RL variant of the algorithm, ER-DQN, which we evaluate on the Atari-57 suite of games.
Effect of in vivo Hydroxychloroquine and ex vivo Anti-BDCA2 mAb Treatment on pDC IFNα Production From Patients Affected With Cutaneous Lupus Erythematosus

Objective: Plasmacytoid dendritic cells (pDCs) are a major source of Type-I Interferon (IFN-I), a key driver in cutaneous lupus erythematosus (CLE). Currently evaluated in Phase II clinical trial, 24F4A (BIIB059) is an antibody targeting BDCA2, an inhibitory receptor expressed on pDCs. Given that Hydroxychloroquine (HCQ), a widely-used CLE therapy, and 24F4A are both able to inhibit pDC-derived IFN-I production; this study aimed to determine whether 24F4A would show an additional inhibitory effect on pDC response after ex vivo or in vivo treatment with HCQ. Methods: The effect of 24F4A on pDC-derived IFNα was measured from peripheral blood mononuclear cells (PBMC) either from healthy donors in presence or absence of HCQ or from CLE patients clinically exposed to various levels of HCQ. TLR7, TLR7/8, and TLR9 agonists (ssRNA, R848, and CpG-A) were used for pDC stimulation. Results: PDCs were the only producers of IFNα in response to CpG-A, R848, and ssRNA stimulation in PBMC cultures. CLE patients with higher levels of blood HCQ showed lower ex vivo pDC responses to CpG-A, but not R848 or ssRNA. In contrast, 24F4A reduced the amount of IFNα produced by pDCs from CLE patients in response to all TLR agonists, irrespective of the blood HCQ level. Conclusion: Our findings reveal that clinically-relevant HCQ concentrations partially inhibit the pDC response to TLR9 and weakly affect the response to TLR7/8 stimulation. 24F4A robustly inhibits pDC responses even in the presence of HCQ, highlighting its unique potential to disrupt pDC disease relevant biology, which could provide additional therapeutic benefit for CLE patients.
Mixture Models for Diverse Machine Translation: Tricks of the Trade

Mixture models trained via EM are among the simplest, most widely used and well understood latent variable models in the machine learning literature. Surprisingly, these models have been hardly explored in text generation applications such as machine translation. In principle, they provide a latent variable to control generation and produce a diverse set of hypotheses. In practice, however, mixture models are prone to degeneracies---often only one component gets trained or the latent variable is simply ignored. We find that disabling dropout noise in responsibility computation is critical to successful training. In addition, the design choices of parameterization, prior distribution, hard versus soft EM and online versus offline assignment can dramatically affect model performance. We develop an evaluation protocol to assess both quality and diversity of generations against multiple references, and provide an extensive empirical study of several mixture model variants. Our analysis shows that certain types of mixture models are more robust and offer the best trade-off between translation quality and diversity compared to variational models and diverse decoding approaches. \footnote{Code to reproduce the results in this paper is available at \url{this https URL}}
Cross-Sensor Periocular Biometrics: A Comparative Benchmark including Smartphone Authentication

The massive availability of cameras and personal devices results in a wide variability between imaging conditions, producing large intra-class variations and performance drop if such images are compared for person recognition. However, as biometric solutions are extensively deployed, it will be common to replace acquisition hardware as it is damaged or newer designs appear, or to exchange information between agencies or applications in heterogeneous environments. Furthermore, variations in imaging bands can also occur. For example, faces are typically acquired in the visible (VW) spectrum, while iris images are captured in the near-infrared (NIR) spectrum. However, cross-spectrum comparison may be needed if for example a face from a surveillance camera needs to be compared against a legacy iris database. Here, we propose a multialgorithmic approach to cope with cross-sensor periocular recognition. We integrate different systems using a fusion scheme based on linear logistic regression, in which fused scores tend to be log-likelihood ratios. This allows easy combination by just summing scores of available systems. We evaluate our approach in the context of the 1st Cross-Spectral Iris/Periocular Competition, whose aim was to compare person recognition approaches when periocular data from VW and NIR images is matched. The proposed fusion approach achieves reductions in error rates of up to 20-30% in cross-spectral NIR-VW comparison, leading to an EER of 0.22% and a FRR of just 0.62% for FAR=0.01%, representing the best overall approach of the mentioned competition. Experiments are also reported with a database of VW images from two different smartphones, achieving even higher relative improvements in performance. We also discuss our approach from the point of view of template size and computation times, with the most computationally heavy system playing an important role in the results.
Impact of old age on resectable colorectal cancer outcomes

Objective This study was performed to identify a reasonable cutoff age for defining older patients with colorectal cancer (CRC) and to examine whether old age was related with increased colorectal cancer-specific death (CSD) and poor colorectal cancer-specific survival (CSS). Methods A total of 76,858 eligible patients from the surveillance, epidemiology, and end results (SEER) database were included in this study. The Cox proportional hazard regression model and the Chow test were used to determine a suitable cutoff age for defining the older group. Furthermore, a propensity score matching analysis was performed to adjust for heterogeneity between groups. A competing risk regression model was used to explore the impact of age on CSD and non-colorectal cancer-specific death (non-CSD). Kaplan–Meier survival curves were plotted to compare CSS between groups. Also, a Cox regression model was used to validate the results. External validation was performed on data from 1998 to 2003 retrieved from the SEER database. Results Based on a cutoff age of 70 years, the examined cohort of patients was classified into a younger group (n = 51,915, <70 years of old) and an older group (n = 24,943, ≥70 years of old). Compared with younger patients, older patients were more likely to have fewer lymph nodes sampled and were less likely to receive chemotherapy and radiotherapy. When adjusted for other covariates, age-dependent differences of 5-year CSD and 5-year non-CSD were significant in the younger and older groups (15.84% and 22.42%, P < 0.001; 5.21% and 14.21%, P < 0.001). Also an age of ≥70 years remained associated with worse CSS comparing with younger group (subdistribution hazard ratio, 1.51 95% confidence interval (CI) [1.45–1.57], P < 0.001). The Cox regression model as a sensitivity analysis had a similar result. External validation also supported an age of 70 years as a suitable cutoff, and this older group was associated with having reduced CSS and increased CSD. Conclusions A total of 70 is a suitable cutoff age to define those considered as having elderly CRC. Elderly CRC was associated with not only increased non-CSD but also with increased CSD. Further research is needed to provide evidence of whether cases of elderly CRC should receive stronger treatment if possible.