Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of Early Increase in Complement Activation Marker sC5b-9 as a Predictive Biomarker for the Development of Thrombotic Microangiopathy After Stem Cell Transplantation

Hematopoietic stem cell transplantation (HSCT)-associated thrombotic microangiopathy (TA-TMA) is a multifactorial complication. Complement dysregulation may play an important role in the pathogenesis of TA-TMA. Our previous observations suggested that early increase of soluble C5b-9 (sC5b-9), before the development of other complications, can predict the development of later TA-TMA. The present study aims to validate our earlier findings in an independent cohort enrolling 67 pediatric patients who underwent allogeneic HSCT during the study period (October 2015–January 2019). Five different TA-TMA diagnostic criteria were applied, and all important clinical and laboratory parameters of TA-TMA activity were registered. Complement pathway activities, components and sC5b-9 levels were systematically measured before transplantation and on days 28, 56, and 100 after HSCT. A strong and remarkable association still have been found between early increase of sC5b-9 (10 of 10 patients with TA-TMA vs. 27 of 57 without TA-TMA; P = 0.002) and the development of TA-TMA during 100 days post-transplantation. An increase in sC5b-9 concentration had 100% sensitivity and 53% specificity for TA-TMA in the cohort. All TA-TMA cases have been observed during cyclosporine immunosuppression, no TA-TMA was diagnosed during tacrolimus or mycophenolat mofetil therapy. In the majority of patients TA-TMA was mild and self-limiting, without any signs of organ damage. No additional complement parameters were closely associated with the development of TA-TMA. Early raise of the sC5b-9 activation marker was predictive for later development of TA-TMA throughout the whole study period. In patients with a marked increase, early and frequent monitoring of TA-TMA activity markers should be attempted, to facilitate subsequent therapy decisions in time. However, patients with TA-TMA were only identified during or after cyclosporine immunosuppression. Further studies enrolling higher number of patients are necessary to determine the role of immunosuppression in the pathogenesis of TA-TMA.
Adaptation, Versatility, and Evolution

Vermeij, G. J. (Dept. of Zoology, University of Maryland, College Park, Maryland 20742) 1974. Adaptation, Versatility, and Evolution. Syst. Zool. 22:466-477. -The potential versatility of form and potential adaptive zone of a higher taxon or body plan depend on the number and range of independent morphogenetic parameters. The actual versatility and adaptive zone of a given higher taxon are determined by interactions of members of that taxon with species belonging to groups with a different body plan. More recently evolved higher taxa tend to exhibit a greater potential versatility of form than related more ancient taxa. In the course of earth history, more potentially versatile taxa have tended to replace less versatile groups in the same or similar adaptive zone. This increase in potential versatility is not the inevitable consequence of the decrease in number of higher taxa through geologic time, but is the result of strong selection favoring some plans of organization over others which may or may not have become extinct. Increasing potential versatility allows for greater homeostasis, efficiency, and exploitation of continuously available resources, and integration of structures and functions. New body plans may arise either from stocks of small adult body size and with relatively simple integration patterns, or else by a process of correlative progression of structures and functions from a relatively specialized ancestral stock.
Dif-MAML: Decentralized Multi-Agent Meta-Learning

The objective of meta-learning is to exploit knowledge obtained from observed tasks to improve adaptation to unseen tasks. Meta-learners are able to generalize better when they are trained with a larger number of observed tasks and with a larger amount of data per task. Given the amount of resources that are needed, it is generally difficult to expect the tasks, their respective data, and the necessary computational capacity to be available at a single central location. It is more natural to encounter situations where these resources are spread across several agents connected by some graph topology. The formalism of meta-learning is actually well-suited for this decentralized setting, where the learner benefits from information and computational power spread across the agents. Motivated by this observation, we propose a cooperative fully-decentralized multi-agent meta-learning algorithm, referred to as Diffusion-based MAML or Dif-MAML. Decentralized optimization algorithms are superior to centralized implementations in terms of scalability, robustness, avoidance of communication bottlenecks, and privacy guarantees. The work provides a detailed theoretical analysis to show that the proposed strategy allows a collection of agents to attain agreement at a linear rate and to converge to a stationary point of the aggregate MAML objective even in non-convex environments. Simulation results illustrate the theoretical findings and the superior performance relative to the traditional non-cooperative setting.
Systems Thinking: A Review and Bibliometric Analysis

Systems thinking (ST) is an interdisciplinary domain that offers different ways to better understand the behavior and structure of a complex system. Over the past decades, several publications can be identified in academic literature, focusing on different aspects of systems thinking. However, two critical questions are not properly addressed in the extant body of ST literature: (i) How to conduct the content analysis exclusively to derive the prominent statistics (i.e., influential journals, authors, affiliated organizations and countries) pertaining to the domain of ST? (ii) How to get better insights regarding the current and emerging trends that may evolve over time based on the existing body of ST literature? To address these gaps, the aim of this research study is to provide a comprehensive insight into the domain of systems thinking through bibliometric and network analysis. Beginning with over 6000 accumulated publications, the analysis narrowed down to 626 prominent articles with proven influence published over the past three decades. Leveraging rigorous bibliometric tools analysis, this research unveils the influential authors, leading journals and top contributing organizations and countries germane to the domain of systems thinking. In addition, citation, co-citation and page rank analysis used to rank top influential articles in the area of systems thinking. Finally, with the aid of the network analysis, key clusters in the existing literature are identified based on the research areas of systems thinking. The findings of this research will serve as a bluebook for practitioners and scholars to conduct future research within systems thinking context.
Disentangle-based Continual Graph Representation Learning

Graph embedding (GE) methods embed nodes (and/or edges) in graph into a low-dimensional semantic space, and have shown its effectiveness in modeling multi-relational data. However, existing GE models are not practical in real-world applications since it overlooked the streaming nature of incoming data. To address this issue, we study the problem of continual graph representation learning which aims to continually train a GE model on new data to learn incessantly emerging multi-relational data while avoiding catastrophically forgetting old learned knowledge. Moreover, we propose a disentangle-based continual graph representation learning (DiCGRL) framework inspired by the human's ability to learn procedural knowledge. The experimental results show that DiCGRL could effectively alleviate the catastrophic forgetting problem and outperform state-of-the-art continual learning models.
Effect of Selenium on Expression of Apoptosis-Related Genes in Cryomedia of Mice Ovary after Vitrification

Introduction Freezing of ovarian tissue is used for preservation of fertility. The freezing-thawing process is accompanied by oxidative stress and induction of apoptosis. Apoptosis is a complex process that has been studied in animal models. The present study was aimed at investigating the effect of selenium on suppression of apoptosis during vitrification-thawing process of mice ovary via studying expression of apoptosis-related genes, and also, we aimed to design statistical models for the roles of single genes and gene-gene interactions in suppression of apoptosis. Methods A total of 10 right ovary samples from 10 mice were randomly divided into two groups of selenium treatment (at dose 5 μg/ml sodium selenite, through adding to the media) and control group. Vitrification-thawing process was done according to the existed protocols. Real-time PCR was used for gene expression study. The apoptosis gene profile included P53, Bax, Fas, and Bcl-2. General linear model was applied to study single gene associations and gene-gene interactions. Results From the studied genes, P53 showed a significant downregulation in the selenium group in comparison to the control group (∆∆CT = 1.96; P = 0.013; relative expression (RE) = 0.28). Bcl-2 showed a significant upregulation in the selenium group in comparison to the control group (∆∆CT = −2.49; P < 0.001; RE = 3.49). No significant result was found for other genes. According to the multiple models, Bcl-2 showed a protective single gene association (beta = −0.33; P = 0.032), and Fas∗Bcl-2 interaction was significantly positive (beta = 0.19; P = 0.036). Conclusion Addition of selenium to cryomedia of vitrification-thawing process could reduce the apoptosis induced by freezing-thawing stress in mice ovary via downregulation of P53 and upregulation of Bcl-2 at transcription level. Multivariable statistical models should be performed in future researches to study biological systems.
On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network

This research work aims to develop a deep learning-based crop classification framework for remotely sensed time series data. Tobacco is a major revenue generating crop of Khyber Pakhtunkhwa (KP) province of Pakistan, with over 90% of the country’s Tobacco production. In order to analyze the performance of the developed classification framework, a pilot sub-region named Yar Hussain is selected for experimentation work. Yar Hussain is a tehsil of district Swabi, within KP province of Pakistan, having highest contribution to the gross production of the KP Tobacco crop. KP generally consists of a diverse crop land with different varieties of vegetation, having similar phenology which makes crop classification a challenging task. In this study, a temporal convolutional neural network (TempCNNs) model is implemented for crop classification, while considering remotely sensed imagery of the selected pilot region with specific focus on the Tobacco crop. In order to improve the performance of the proposed classification framework, instead of using the prevailing concept of utilizing a single satellite imagery, both Sentinel-2 and Planet-Scope imageries are stacked together to assist in providing more diverse features to the proposed classification framework. Furthermore, instead of using a single date satellite imagery, multiple satellite imageries with respect to the phenological cycle of Tobacco crop are temporally stacked together which resulted in a higher temporal resolution of the employed satellite imagery. The developed framework is trained using the ground truth data. The final output is obtained as an outcome of the SoftMax function of the developed model in the form of probabilistic values, for the classification of the selected classes. The proposed deep learning-based crop classification framework, while utilizing multi-satellite temporally stacked imagery resulted in an overall classification accuracy of 98.15%. Furthermore, as the developed classification framework evolved with specific focus on Tobacco crop, it resulted in best Tobacco crop classification accuracy of 99%.
Molecular Phylogenetics and Conservation of Tupinambis (Sauria: Teiidae)

examined genetic or morphological variation in these lizards. We sequenced parts of the mitochondrial cytochrome b (300bp) and ND4 (375bp) genes and examined this variation in light of morphological characters traditionally used to identify these species. DNA sequences provided a preliminary view of intraspecific and interspecific variation and were used to explore evolutionary relationships among 17 individuals representing T. merianae, T. rufescens, and T. duseni from Paraguay, and T. longilineus and T. teguixin from Roraima, Brazil, and Cuyabeno, Ecuador. Kentropyx viridistriga, Ameiva ameiva, and Cnemidophorus ocellifer were included as outgroups. Maximum-parsimony and neighbor-joining analyses revealed two distinctive groups within Tupinambis; a northern South American and Amazonian clade (T. teguixin, T. longilineus) and a clade (T. duseni, T. rufescens, and T. merianae) that is distributed primarily south of Amazonia. Although genetically similar and previously considered synonymous with T. rufescens, T. duseni is morphologically distinct based on squamation, coloration, and morphometrics. This incongruence between the molecular data and morphology suggests that T. duseni and T. rufescens may have undergone extensive and recent morphological evolution or there has been introgression of mitochondrial DNA between these species. Sequence divergence between T. teguixin from Brazil and Ecuador was similar to that found between T. rufescens and T. merianae and may indicate these T. teguixin populations are not conspecific. The T. teguixin clade was sister to T. longilineus. These findings, combined with the largescale commercial exploitation of the genus, suggest an urgent need to address geographic variation and the systematics of species of Tupinambis.
Resting TcPO2 levels decrease during liner wear in persons with a transtibial amputation

Background In our clinic, a substantial number of patients present with transtibial residual limb pain of no specific somatic origin. Silicone liner induced tissue compression may reduce blood flow, possibly causing residual limb pain. Thus, as a first step we investigated if the liner itself has an effect on transcutaneous oxygen pressure (TcPO2). Methods Persons with unilateral transtibial amputation and residual limb pain of unknown origin were included. Medical history, including residual limb pain, was recorded, and the SF-36 administered. Resting TcPO2 levels were measured in the supine position and without a liner at 0, 10, 20 and 30 minutes using two sensors: one placed in the Transverse plane over the tip of the Tibia End (= TTE), the other placed in the Sagittal plane, distally over the Peroneal Compartment (= SPC). Measurements were repeated with specially prepared liners avoiding additional pressure due to sensor placement. Statistical analyses were performed using SPSS. Results Twenty persons (9 women, 11 men) with a mean age of 68.65 years (range 47–86 years) participated. The transtibial amputation occurred on average 43 months prior to study entry (range 3–119 months). With liner wear, both sensors measured TcPO2 levels that were significantly lower than those measured without a liner (TTE: p < 0.001; SPC: p = 0.002) after 10, 20 and 30 minutes. No significant differences were found between TcPO2 levels over time between the sensors. There were no significant associations between TcPO2 levels and pain, smoking status, age, duration of daily liner use, mobility level, and revision history. Conclusion Resting TcPO2 levels decreased significantly while wearing a liner alone, without a prosthetic socket. Further studies are required to investigate the effect of liner wear on exercise TcPO2 levels.
Grain Fe and Zn contents linked SSR markers based genetic diversity in rice

Rice is critical for sustainable food and nutritional security; however, nominal micronutrient quantities in grains aggravate malnutrition in rice-eating poor populations. Here, we assessed genetic diversity in grain iron (Fe) and zinc (Zn) contents using trait-linked simple sequence repeat (SSR) markers in 56 fine and coarse grain rice accessions of different geographical origin. Aromatic fine gain accessions contained relatively higher Fe and Zn contents in brown rice (BR) than coarse grain accessions. Genotyping with 24 SSR markers identified 21 polymorphic markers, among which seventeen demonstrated higher gene diversity and polymorphism information content (PIC) values, strongly indicating that markers used in current research were moderate to highly informative for evaluating genetic diversity. Population structure, principal coordinate and phylogenetic analyses classified studied rice accessions into two fine grain specific and one fine and coarse grain admixture subpopulations. Single marker analysis recognized four ZnBR and single FeBR significant marker-trait associations (MTAs), contributing 15.41–39.72% in total observed phenotypic variance. Furthermore, high grain Fe and Zn contents linked marker alleles from significant MTAs were also identified. Collectively, these results indicate availability of wide genetic diversity in rice germplasm and perspective for marker-assisted biofortification breeding.
Targeted Engagement of the Action Selection Network during Task-Oriented Arm Training after Stroke

Action selection (AS), or selection of an action from a set of alternatives, is an important movement preparation process that engages a frontal-parietal network. The addition of AS demands to arm training after stroke could be used to engage this motor planning process and the neural network that supports it. The purpose of this case series is to describe the feasibility and outcomes associated with task-oriented arm training aimed at engaging the AS behavioral process and the related neural network in three individuals with chronic stroke. Three participants with mild to moderate motor deficits completed 13 to 15 sessions of task-oriented arm training that included AS cues for each movement repetition; cues dictated movement direction, height, or distance. Before and after training, individuals completed an AS brain-behavior probe during functional MRI. AS behavioral performance improved after training (increased accuracy, decreased reaction time) in all participants while brain activation in the AS network (dorsal premotor, parietal, dorsolateral prefrontal cortices) decreased in two participants. Gains in motor function were also found in all three participants, especially on patient-reported measures of perceived difficulty and confidence to complete upper extremity functional tasks. It was feasible to target the AS behavioral process and the related neural network through the addition of AS demands to functional, task-oriented arm training in three individuals with mild to moderate motor dysfunction poststroke.
Assessment of the functional efficacy of root canal treatment with high-frequency waves in rats

The purpose of this study was to develop a high-frequency wave therapy model in rats and to investigate the influence of high-frequency waves on root canal treatment, which may provide a novel strategy for treating apical periodontitis. Root canal treatments with and without high-frequency wave irradiation were performed on the mandibular first molars of 10-week-old male Wistar rats. The mesial roots were evaluated radiologically, bacteriologically, and immunohistochemically. At 3 weeks after root canal treatment, lesion volume had decreased significantly more in the irradiated group than in the non-irradiated group, indicating successful development of the high-frequency therapy model. The use of high-frequency waves provided no additional bactericidal effect after root canal treatment. However, high-frequency wave irradiation was found to promote healing of periapical lesions on the host side through increased expression of fibroblast growth factor 2 and transforming growth factor-β1 and could therefore be useful as an adjuvant nonsurgical treatment for apical periodontitis.
Conceptual and Technical Challenges for High Performance Computing

High Performance Computing (HPC) aims at providing reasonably fast computing solutions to scientific and real life problems. Many efforts have been made on the way to powerful supercomputers, including generic and customized configurations. The advent of multicore architectures is noticeable in the HPC history, because it has brought the underlying parallel programming concept into common considerations. At a larger scale, there is a keen interest in building or hosting frontline supercomputers; the Top500 ranking is a nice illustration of this (implicit) racing. Supercomputers, as well as ordinary computers, have fallen in price for years while gaining processing power. We clearly see that, what commonly springs up in mind when it comes to HPC is computer capability. However, when going deeper into the topic, especially on large-scale problems, it appears that the processing speed by itself is no longer sufficient. Indeed, the real concern of HPC users is the time-to-output. Thus, we need to study each important aspect in the critical path between inputs and outputs. The first step is clearly the method, which is a conjunction of modelling with specific considerations (hypothesis, simplifications, constraints, to name a few) and a corresponding algorithm, which could be numerical and/or non numerical. Then comes the topic of programming, which should yield a skillful mapping of the algorithm onto HPC machines. Based on multicore processors, probably enhanced with acceleration units, current generation of supercomputers is rated to deliver an increasing peak performance, the Exascale era being the current horizon. However, getting a high fraction of the available peak performance is more and more difficult. The Design of an efficient code that scales well on a supercomputer is a non-trivial task. Manycore processors are now common, and the scalability issue in this context is crucial. Code optimization requires advanced programming techniques, taking into account the specificities and constraints of the target architecture. Many challenges are to be considered from the standpoint of efficiency and expected performances. The present chapter will discuss the aforementioned points, interleaved with commented contributions from the literature and our personal views.
Diverse Exploration via InfoMax Options

In this paper, we study the problem of autonomously discovering temporally abstracted actions, or options, for exploration in reinforcement learning. For learning diverse options suitable for exploration, we introduce the infomax termination objective defined as the mutual information between options and their corresponding state transitions. We derive a scalable optimization scheme for maximizing this objective via the termination condition of options, yielding the InfoMax Option Critic (IMOC) algorithm. Through illustrative experiments, we empirically show that IMOC learns diverse options and utilizes them for exploration. Moreover, we show that IMOC scales well to continuous control tasks.