Miracle-dz/UniFAR-FTUs huggingface dataset:
Splenic Autotransplantation after Blunt Spleen Injury in Children

Non-operative management has been preferred in blunt spleen injury. Moreover children are more susceptible to post-splenectomy infection, spleen should be preserved if possible. However, splenectomy is inevitable to patients with severe splenic injury. Therefore splenic autotransplantation could be the last chance for preserving splenic function in these patients although efficacy has not proven. Here we reported four cases of children who were underwent splenic autotransplantation successfully after blunt trauma.
Changes of secondary structure and surface tension of whey protein isolate dispersions upon pH and temperature.

Tomczynska-Mleko M. , Kamysz E. , Sikorska E. , Puchalski C. , Mleko S. , Ozimek L. , Kowaluk G. , Gustaw W. , Wesolowska-Trojanowska M. (2014): Changes of secondary structure and surface tension of whey protein isolate dispersions upon pH and temperature. Czech J. Food Sci., 32: 82–89. The secondary structure of proteins in unheated and heated whey protein isolate dispersions and the surface tension of the solutions were investigated at different pH. Heating protein solutions at 80°C results in an increase of unordered structure. Nevertheless, the difference between the contents of unordered structure in the unheated and heated samples increases with increasing pH of the solution. At low protein concentrations the surface tension decreased with increasing protein concentration to about 5 mg/ml. For the heated solution, a similar trend was observed in the decrease in the surface tension with increasing concentrations of protein. In both cases, the curves depicting the surface tension as a function of protein concentration could be fitted to the exponential function with a negative exponent, but with the heated solutions lower values of surface tension were observed. Studies on the surface tension of whey protein isolate solutions prove that the unfolding of whey proteins, revealed by changes in the secondary structure, causes a decrease in the surface tension.
Supplementary Information

Here, we reported water masses as approximated by water depth to influence the prokaryotic community composition and holobiont metabolome in three deep-sea sponge species, Geodia barretti, Stryphnus fortis and Weberella bursa. By 16S rRNA gene sequencing and computational statistical analyses, we assessed and analysed the operational taxonomic units (ASVs) that increased or decreased with depth and found distinct groups of ASVs in samples associated with two water masses (Labrador Sea Water and Irminger Current) in the Davis Strait, North Atlantic. In parallel, by Ultra-high Performance Liquid Chromatography coupled with High-Resolution Mass Spectrometry (UPLC-HRMS) we acquired and analysed the metabolome of these sponge holobionts. Using computational analyses, we found that the metabolomes changed with depth. We extracted and identified metabolite signals driving the depth-dependent changes as well as signals of known bioactive compounds. Finally, we combined microbiota and metabolome data to generate a hypothesis about the producer of the antibiofounling compound barettin. This multi-omics data acquisition and analysis approach relied on the use of several instruments and methods that are detailed in the experimental section. The supplementary methods described herein apply to the wet lab procedures. The code and comments for the subsequent computational analyses were deposited at the Paamiut GitHub repository.
Assisted Peritoneal Dialysis

The number of patients depending on dialysis therapies increases worldwide. The home- based dialysis modalities offer some advantages especially for elderly patients. In the case of peritoneal dialysis (PD), the life quality is superior compared to in-center hemodialysis (HD), and other advantages are existent. Due to the effect that a lot of elderly PD patients are frail, a concept covering the different modalities of PD must include the assistance at home or the living environment (assisted PD) for the bag exchanges that often cannot be performed reliably by elderly and frail patients by themselves. Nowadays, we have enough data to safely offer assisted peritoneal dialysis (aPD) in a cost-saving manner. Putting all these aspects together, aPD is a safe and in some countries widely used modality. The issue of reimbursement and education of home nurse staff must be solved. However, for elderly and frail patients, aPD offers a change to use the advantages of PD for these population, and on a local level, the provider should seek ways to establish aPD programs.
Efficacy and safety of nivolumab (NIVO) plus ipilimumab (IPI) in patients with melanoma (MEL) metastatic to the brain: Results of the phase II study CheckMate 204.

9507Background: Brain metastases (BMts) are a major cause of morbidity/death in MEL. We report the first efficacy data in MEL patients (pts) with BMts who received NIVO+IPI in study CheckMate 204. Methods: In this multicenter US trial (NCT02320058), MEL pts with ≥1 measurable BMt 0.5-3.0 cm and no neurologic symptoms or steroid Rx received NIVO 1 mg/kg + IPI 3 mg/kg Q3W x 4, then NIVO 3 mg/kg Q2W until progression or toxicity. Pts with severe adverse events (AEs) during NIVO+IPI could receive NIVO when toxicity resolved; stereotactic radiotherapy (SRT) was allowed for brain oligo-progression if an assessable BMt remained. The primary endpoint was intracranial (IC) clinical benefit rate (complete response [CR] + partial response [PR] + stable disease [SD] > 6 months). The planned 90-pt accrual is complete; we report efficacy and updated safety for 75 pts with disease assessment before the Nov 2016 database lock. Results: Median age was 59 yrs (range 22–79). Median number of induction doses was 3; 26 pts (3.
Régulation de la métalloprotéase ADAM10/Kuzbanian par les tétraspanines à 8 cystéines et conséquences sur l’activation de la voie Notch chez les mammifères et la Drosophile

L’importance des activites proteolytiques associees a la membrane plasmique dans divers processus biologiques fondamentaux est de mieux en mieux definie. Les proteases de la famille ADAM (A Disintegrin and Metalloprotease), et ADAM10 en particulier, ont suscite un interet tout particulier du fait de l’importance de leurs substrats (recepteur de l’EGF, TNFα, Notch, APP…). Neanmoins, peu d’etudes se sont interessees aux mecanismes regulant le trafic d’ADAM10.Les tetraspanines sont une super-famille de proteines de surface impliquees dans de nombreux processus biologiques fondamentaux parmi lesquels la migration, les interactions intercellulaires, la reponse immunitaire, la fusion des gametes… L’une des caracteristiques majeure des tetraspanines est leur capacite a organiser un reseau d’interactions moleculaires appele le « tetraspanin web ». De precedentes etudes menees dans le laboratoire ont montre qu’ADAM10 est associe au « tetraspanin web ». Neanmoins, la tetraspanine en interaction directe avec ADAM10 permettant son association au reseau n’est pas encore connue. Dans cette etude nous nous sommes interesses a la regulation d’ADAM10 par les tetraspanines. Nous avons ainsi pu identifier une sous-famille de tetraspanines a 8 cysteines, les TspanC8 (Tspan5, Tspan10, Tspan14, Tspan15, Tspan17 et Tspan33), comme etant capables d’interagir directement avec ADAM10 et de reguler sa sortie du reticulum endoplasmique. Nous avons montre que Tspan5, Tspan14, Tspan15 et Tspan33 sont capables de reguler l’expression de surface d’ADAM10 et que Tspan10 et Tspan17 entrainent l’accumulation d’ADAM10 dans un compartiment endosomal tardif. Les TspanC8 pourraient egalement contribuer a la regulation de la specificite de substrat d’ADAM10 puisque nous avons montre que l’expression des TspanC8 humaines Tspan5 et Tspan14 augmente l’activation de la voie Notch alors que Tspan15 n’a pas d’effet. Par ailleurs, les TspanC8 de Drosophile sont capables d’interagir directement avec Kuzbanian (l’orthologue d’ADAM10), permettent son accumulation a la surface cellulaire et regulent l’activation de la voie Notch dans differents contextes developpementaux. Nous proposons que les TspanC8 soient une nouvelle famille de proteines ayant une fonction tres conservee dans la regulation de l’activite et du trafic d’ADAM10, capables de reguler l’activation de la voie Notch.
Issues in the Pharmacokinetics of Trichloroethylene and Its Metabolites

Much progress has been made in understanding the complex pharmacokinetics of trichloroethylene (TCE). Qualitatively, it is clear that TCE is metabolized to multiple metabolites either locally or into systemic circulation. Many of these metabolites are thought to have toxicologic importance. In addition, efforts to develop physiologically based pharmacokinetic (PBPK) models have led to a better quantitative assessment of the dosimetry of TCE and several of its metabolites. As part of a mini-monograph on key issues in the health risk assessment of TCE, this article is a review of a number of the current scientific issues in TCE pharmacokinetics and recent PBPK modeling efforts with a focus on literature published since 2000. Particular attention is paid to factors affecting PBPK modeling for application to risk assessment. Recent TCE PBPK modeling efforts, coupled with methodologic advances in characterizing uncertainty and variability, suggest that rigorous application of PBPK modeling to TCE risk assessment appears feasible at least for TCE and its major oxidative metabolites trichloroacetic acid and trichloroethanol. However, a number of basic structural hypotheses such as enterohepatic recirculation, plasma binding, and flow- or diffusion-limited treatment of tissue distribution require additional evaluation and analysis. Moreover, there are a number of metabolites of potential toxicologic interest, such as chloral, dichloroacetic acid, and those derived from glutathione conjugation, for which reliable pharmacokinetic data is sparse because of analytical difficulties or low concentrations in systemic circulation. It will be a challenge to develop reliable dosimetry for such cases.
Cloning of partial glycoprotein B gene and molecular epidemiological studies of bovine herpes virus -1 isolates

The study describes genetic grouping and molecular epidemiology of bovine herpes virus-1 (BoHV-1) through cloning of partial glycoprotein B gene of BoHV-1 isolates, with special reference to isolates recovered from cattle breeding stations. Samples were collected from 212 animals (91 bulls and 121 female cattle). Avidin-biotin ELISA employed on serum samples found 74 animals as seropositive for BoHV-1. On inoculation of 212 semen/swab samples to MDBK cell line for virus isolation, samples of 4 seropositive and 5 seronegative animals yielded cytopathic changes characteristic of BoHV-1. Partial gB gene of these isolates were cloned in pGEM T vector, nucleotide sequences were deduced and phylogenetic tree was constructed. Sequence analysis grouped 5 of these isolates under BoHV-1.1 cluster having highest sequence identities with previously described Indian, European and Brazilian isolates of BoHV-1.1. The other 4 isolates were clustered as BoHV-1.2 subtypes having 100% sequence identity with European strain of BoHV-1.2. We found that, apparently healthy, seronegative animals can be sources of BoHV-1, attributable to the unique pathogenesis/ latency of BoHV-1. This finding necessitates mandatory culling of breeding animals which are positive either in antigen detection or by serology, especially in countries which do not practice vaccination but report high seroprevalance of BoHV-1.
The Conservation Value of Peripheral Populations: the Supporting Science

Traditionally, populations at the periphery of the geographic range of a species have been regarded as having little value in conserving biodiversity. This view developed from the expectation that populations at the edge of their geographic range are more vulnerable to extinction than populations in the central portion of the range. Conservation biologists have also assumed that the genetic diversity of a species is greatest near the center of its geographic range. This low regard for peripheral populations has been incorporated into guidelines for conserving biodiversity. Conservation practitioners are told to direct limited conservation resources to conserving central populations because peripheral populations have little chance of survival and are genetically impoverished. These expectations and their related guidelines have caused officials at many governmental levels to question including species at the periphery of their distribution in lists of protected species. Despite the often uncritical acceptance of the low conservation value of peripheral populations, recent research suggests that peripheral populations may play an important role in conserving declining species. Contrary to expectations, in species that have undergone large range contractions, peripheral populations persist significantly more often than do the central populations. In addition, examinations of the genetic diversity of populations across the geographic range of a species are beginning to call in to question the assumption of higher central diversity. Furthermore, studies on both persistence and genetics suggest that the distinction between central and peripheral populations may not be an important distinction for conserving biodiversity. Thus, conservation plans should include populations found both near the center and the periphery of a species' distribution.
Concerns and Returns to Work in Patients with Breast Cancer Receiving Outpatient Chemotherapy: a Pilot Study

Objective: Breast cancer survivors are increasing in number among survivors of all types of cancer, and survivors returning to work are extremely important. The development of outpatient chemotherapy has increased the working population of patients undergoing cancer therapy. Consequently, a significant number of breast cancer survivors experience physical, psychological, and social problems. This study aimed to clarify differences in concerns among patients with breast cancer receiving outpatient chemotherapy according to their employment status. Methods: Twenty-eight patients with breast cancer undergoing outpatient chemotherapy were recruited. A questionnaire was used to survey the attributes, employment status, and levels of concern in these patients based on the Cancer-chemotherapy Concerns Rating Scale (CCRS). Data from three groups (employed full time, employed part-time, and unemployed) were analyzed using multiple comparison tests. Results: The patients' mean age was (55.1 ± 9.9) years. According to the CCRS findings, the following three parameters differed between the three groups: scores for the items “I always think about my disease” (employed vs. unemployed, P = 0.005) and “I can't work (housework/schoolwork)” (employed full time vs. part time, P = 0.045), and scores for the “self-existence” subscale (employed vs. unemployed, P = 0.024). Conclusions: This study revealed the characteristics of concerns in patients with breast cancer according to their employment status. Being able to continue working is considered to enhance the social health of these patients. Predicting concerns in employed patients will help gain perspective in early nursing interventions.
NodeSLAM: Neural Object Descriptors for Multi-View Shape Reconstruction

The choice of scene representation is crucial in both the shape inference algorithms it requires and the smart applications it enables. We present efficient and optimisable multi-class learned object descriptors together with a novel probabilistic and differential rendering engine, for principled full object shape inference from one or more RGB-D images. Our framework allows for accurate and robust 3D object reconstruction which enables multiple applications including robot grasping and placing, augmented reality, and the first object-level SLAM system capable of optimising object poses and shapes jointly with camera trajectory.
Fast digital methods for adiabatic state preparation

We present quantum algorithms for adiabatic state preparation on a gate-based quantum computer, with complexity polylogarithmic in the inverse error. This constitutes an exponential improvement over existing methods, which achieve subpolynomial error dependence. Our first algorithm digitally simulates the adiabatic evolution between two self-adjoint operators $H_0$ and $H_1$, exponentially suppressing the diabatic error by harnessing the theoretical concept of quasi-adiabatic continuation as an algorithmic tool. Given an upper bound $\alpha$ on $\|H_0\|$ and $\|H_1\|$ along with the promise that the $k$th eigenstate $|\psi_k(s)\rangle$ of $H(s) \equiv (1-s)H_0 + sH_1$ is separated from the rest of the spectrum by a gap of at least $\gamma > 0$ for all $s \in [0,1]$, this algorithm implements an operator $\widetilde{U}$ such that $\| |\psi_k(1)\rangle - \widetilde{U}|\psi_k(s)\rangle\| \leq \epsilon$ using $\mathcal{O}(({\alpha^2}/{\gamma^2})\mathrm{polylog}(\alpha/\gamma\epsilon))$ queries to block-encodings of $H_0$ and $H_1$. Our second algorithm is applicable only to ground states and requires multiple queries to an oracle that prepares $|\psi_0(0)\rangle$, but has slightly better scaling in all parameters. We also show that the costs of both algorithms can be further reduced under certain reasonable conditions, such as when $\|H_1 - H_0\|$ is small compared to $\alpha$, or when more information about the gap of $H(s)$ is available. For certain problems, the scaling can even be improved to linear in $\|H_1 - H_0\|/\gamma$ up to polylogarithmic factors.
A Survey on Coarse-Grained Reconfigurable Architectures From a Performance Perspective

With the end of both Dennard’s scaling and Moore’s law, computer users and researchers are aggressively exploring alternative forms of computing in order to continue the performance scaling that we have come to enjoy. Among the more salient and practical of the post-Moore alternatives are reconfigurable systems, with Coarse-Grained Reconfigurable Architectures (CGRAs) seemingly capable of striking a balance between performance and programmability. In this paper, we survey the landscape of CGRAs. We summarize nearly three decades of literature on the subject, with a particular focus on the premise behind the different CGRAs and how they have evolved. Next, we compile metrics of available CGRAs and analyze their performance properties in order to understand and discover knowledge gaps and opportunities for future CGRA research specialized towards High-Performance Computing (HPC). We find that there are ample opportunities for future research on CGRAs, in particular with respect to size, functionality, support for parallel programming models, and to evaluate more complex applications.
GGA-MG: Generative Genetic Algorithm for Music Generation

Music Generation (MG) is an interesting research topic that links the art of music and Artificial Intelligence (AI). The goal is to train an artificial composer to generate infinite, fresh, and pleasurable musical pieces. Music has different parts such as melody, harmony, and rhythm. In this paper, we propose a Generative Genetic Algorithm (GGA) to produce a melody automatically. The main GGA uses a Long Short-Term Memory (LSTM) recurrent neural network as the objective function, which should be trained by a spectrum of bad-to-good melodies. These melodies have to be provided by another GGA with a different objective function. Good melodies have been provided by CAMPINs collection. We have considered the rhythm in this work, too. The experimental results clearly show that the proposed GGA method is able to generate eligible melodies with natural transitions and without rhythm error.
The Spotify Podcasts Dataset

Podcasts are a relatively new form of audio media. Episodes appear on a regular cadence, and come in many different formats and levels of formality. They can be formal news journalism or conversational chat; fiction or non-fiction. They are rapidly growing in popularity and yet have been relatively little studied. As an audio format, podcasts are more varied in style and production types than, say, broadcast news, and contain many more genres than typically studied in video research. The medium is therefore a rich domain with many research avenues for the IR and NLP communities. We present the Spotify Podcasts Dataset, a set of approximately 100K podcast episodes comprised of raw audio files along with accompanying ASR transcripts. This represents over 47,000 hours of transcribed audio, and is an order of magnitude larger than previous speech-to-text corpora.
LightConvPoint: convolution for points

Recent state-of-the-art methods for point cloud semantic segmentation are based on convolution defined for point clouds. In this paper, we propose a formulation of the convolution for point cloud directly designed from the discrete convolution in image processing. The resulting formulation underlines the separation between the discrete kernel space and the geometric space where the points lies. The link between the two space is done by a change space matrix $\mathbf{A}$ which distributes the input features on the convolution kernel. Several existing methods fall under this formulation. We show that the matrix $\mathbf{A}$ can be easily estimated with neural networks. Finally, we show competitive results on several semantic segmentation benchmarks while being efficient both in computation time and memory.
Global Public Health Surveillance using Media Reports: Redesigning GPHIN

Global public health surveillance relies on reporting structures and transmission of trustworthy health reports. But in practice, these processes may not always be fast enough, or are hindered by procedural, technical, or political barriers. GPHIN, the Global Public Health Intelligence Network, was designed in the late 1990s to scour mainstream news for health events, as that travels faster and more freely. This paper outlines the next generation of GPHIN, which went live in 2017, and reports on design decisions underpinning its new functions and innovations.
CovidSens: A Vision on Reliable Social Sensing based Risk Alerting Systems for COVID-19 Spread

With the spiraling pandemic of the Coronavirus Disease 2019 (COVID-19), it has becoming inherently important to disseminate accurate and timely information about the disease. Due to the ubiquity of Internet connectivity and smart devices, social sensing is emerging as a dynamic sensing paradigm to collect real-time observations from online users. In this vision paper we propose CovidSens, the concept of social-sensing-based risk alerting systems to notify the general public about the COVID-19 spread. The CovidSens concept is motivated by two recent observations: 1) people have been actively sharing their state of health and experience of the COVID-19 via online social media, and 2) official warning channels and news agencies are relatively slower than people reporting their observations and experiences about COVID-19 on social media. We anticipate an unprecedented opportunity to leverage the posts generated by the social media users to build a real-time analytic system for gathering and circulating vital information of the COVID-19 propagation. Specifically, the vision of CovidSens attempts to answer the questions of: how to track the spread of the COVID-19? How to distill reliable information about the disease with the coexistence of prevailing rumors and misinformation in the social media? How to inform the general public about the latest state of the spread timely and effectively and alert them to remain prepared? In this vision paper, we discuss the roles of CovidSens and identify the potential challenges in implementing reliable social-sensing-based risk alerting systems. We envision that approaches originating from multiple disciplines (e.g. estimation theory, machine learning, constrained optimization) can be effective in addressing the challenges. Finally, we outline a few research directions for future work in CovidSens.