Miracle-dz/UniFAR-FTUs huggingface dataset:
Umbilical Cord Blood Transplants: Current Status and Evolving Therapies

Hematopoietic cell transplants using stem cells from umbilical cord blood are used worldwide for the treatment of malignant and non-malignant disorders. Transplant procedures from this stem cell source have shown promising outcomes in successfully treating various hematologic, immunologic, malignant, and inherited metabolic disorders. Rapid availability of these stem cells is an important advantage over other unrelated donor transplants, especially in situations where waiting can adversely affect the prognosis. The umbilical cord blood is rich in CD34+ stem cells, though with a limited cell dose and usually takes longer to engraft. Limitations around this have been addressed by in vivo and ex vivo expansion techniques as well as enhanced engraftment kinetics. Development of adoptive immunotherapy using other components of umbilical cord blood such as regulatory T cells, virus-specific T cells, and natural killer cells has further transformed the field and enhanced the utility of umbilical cord blood unit.
Contribution of Vocabulary Knowledge to Reading Comprehension Among Chinese Students: A Meta-Analysis

This study investigated the correlation between vocabulary knowledge and reading comprehension. To address the correlation picture under Chinese logographical scripts, the researchers investigated the potential explanation for the correlation via Reading Stage, Information Gap, Content-based Approach, and Cognition and Creativity Theory approaches. This study undertook a meta-analysis to synthesize 89 independent samples from primary school stage to Master's degree stage. Results showed the correlation picture as an inverted U-shape, supporting the idea that vocabulary knowledge contributed a large proportion of variance on text comprehension and might also support the independent hypothesis of the impact of vocabulary knowledge on reading comprehension. In each education stage, the correlation between vocabulary knowledge and reading comprehension was independent in that it did not interact with any significant moderators. This study informed that the vocabulary knowledge not only determined text comprehension progress through facial semantic meaning identification but also suggested that the coordinate development of vocabulary knowledge, grammatical knowledge, and inference would be better in complexity comprehension task performance.
Gene Signatures and Prognostic Values of m6A Regulators in Hepatocellular Carcinoma

N6-methyladenosine (m6A) is the most abundant mRNA modification in mammals and has been implicated in various biological processes. However, its role in hepatocellular carcinoma (HCC) remains largely unknown. In this study, we investigated the alterations of 19 main m6A regulatory genes in HCC and their association with clinicopathological features, including survival. The mutation, copy number variation (CNV) and clinical data of HCC patients were retrieved from The Cancer Genome Atlas (TCGA) database. We found that the m6A regulators had high frequent alterations in HCC. The alterations of m6A regulators were significantly associated with clinicopathological features as well as TP53 alteration. Patients with any mutation of the m6A regulatory genes had worse overall survival (OS) and disease free survival (DFS). Deletion of METTL16 or ALKBH5 predicted poor OS and DFS of HCC patients. Moreover, deletion of METTL16 was an independent risk factor for DFS. Low METT16 expression was association with activation of multiple metabolic pathways in HCC. Finally, by RT-PCR, we confirmed that METTL16 was downregulated in HCC, and that lower METTL16 expression was associated with poor OS. In conclusion, we reported a significant association between alterations of m6A regulators and clinicopathological features, and highlighted the importance of METTL16 among the 19 m6A regulators in HCC pathogenesis. These findings will provide new insights into the role of m6A modification in HCC.
Prospective Teachers' Development of Meta-Cognitive Functions in Solving Mathematical-Based Programming Problems with Scratch

Transformations, including symmetry and rotations, are important in solving mathematical problems. Meta-cognitive functions are considered critical in solving mathematical problems. In the current study, we examined prospective teachers’ use of meta-cognitive functions while solving mathematical-based programming problems in the Scratch environment. The study was conducted among 18 prospective teachers, who engaged in a sequence of mathematical problems that utilize Scratch. The data sources included video recordings and solution reports while they performed mathematical problems. The findings indicated that the participants developed their meta-cognitive functions as problem solvers related to both mathematics and programming aspects. The findings also indicated that the participants developed regulation meta-cognitive functions more than awareness and evaluation ones in mathematical and programming aspects.
The Discovery of SWI/SNF Chromatin Remodeling Activity as a Novel and Targetable Dependency in Uveal Melanoma

Uveal melanoma is a rare and aggressive cancer that originates in the eye. Currently, there are no approved targeted therapies and very few effective treatments for this cancer. Although activating mutations in the G protein alpha subunits, GNAQ and GNA11, are key genetic drivers of the disease, few additional drug targets have been identified. Recently, studies have identified context-specific roles for the mammalian SWI/SNF chromatin remodeling complexes (also known as BAF/PBAF) in various cancer lineages. Here, we find evidence that the SWI/SNF complex is essential through analysis of functional genomics screens and further validation in a panel of uveal melanoma cell lines using both genetic tools and small-molecule inhibitors of SWI/SNF. In addition, we describe a functional relationship between the SWI/SNF complex and the melanocyte lineage–specific transcription factor Microphthalmia-associated Transcription Factor, suggesting that these two factors cooperate to drive a transcriptional program essential for uveal melanoma cell survival. These studies highlight a critical role for SWI/SNF in uveal melanoma, and demonstrate a novel path toward the treatment of this cancer.
The Current Status of COVID-19 Vaccines

The current COVID-19 pandemic has substantially accelerated the demands for efficient vaccines. A wide spectrum of approaches includes live attenuated and inactivated viruses, protein subunits and peptides, viral vector-based delivery, DNA plasmids, and synthetic mRNA. Preclinical studies have demonstrated robust immune responses, reduced viral loads and protection against challenges with SARS-CoV-2 in rodents and primates. Vaccine candidates based on all delivery systems mentioned above have been subjected to clinical trials in healthy volunteers. Phase I clinical trials have demonstrated in preliminary findings good safety and tolerability. Evaluation of immune responses in a small number of individuals has demonstrated similar or superior levels of neutralizing antibodies in comparison to immunogenicity detected in COVID-19 patients. Both adenovirus- and mRNA-based vaccines have entered phase II and study protocols for phase III trials with 30,000 participants have been finalized.
Efficient Latency Control in Fog Deployments via Hardware-Accelerated Popularity Estimation

Introduced as an extension of the Cloud at the network edge for computing and storage purposes, the Fog is increasingly considered a key enabler for Internet-of-Things applications whose latency requirements are not compatible with a Cloud-only approach. Unlike Cloud platforms, which can elastically accommodate large numbers of requests, Fog deployments are usually dimensioned for an average traffic load and, thus, unable to handle sudden bursts of requests without violating latency guarantees. In this article, we address the problem of efficiently controlling Fog admission to guarantee application response time. We propose request-aware admission control (AC) strategies maximizing the number of Fog-handled requests by means of dynamic popularity estimation. In particular, the LRU-AC, an AC strategy based on online learning of the request popularity distribution via a Least Recently Used (LRU) filter, is introduced. We contribute an analytical model for assessing LRU-AC performance and quantifying the incurred reduction of Cloud offload cost, w.r. t. both an ideal oracle-based and a request-oblivious AC strategy. Further, we propose a feasible implementation design of LRU-AC on FPGA hardware using Aging Bloom Filters (ABF) to mimic the function of the LRU-AC, while providing a compact memory representation. The use of ABFs for LRU-AC is theoretically validated and verified through simulation. The current implementation shows a throughput of 16.7 Mpps and a processing latency of less than 3μ s while multiplying the Fog acceptance-rate by 10 in the evaluated scenario.
New Identities Dealing with Gauss Sums

In this article, we used the elementary methods and the properties of the classical Gauss sums to study the problem of calculating some Gauss sums. In particular, we obtain some interesting calculating formulas for the Gauss sums corresponding to the eight-order and twelve-order characters modulo p, where p be an odd prime with p=8k+1 or p=12k+1.
MEG

Emerging three-dimensional (3D) memory technologies, such as the Hybrid Memory Cube (HMC) and High Bandwidth Memory (HBM), provide high-bandwidth and massive memory-level parallelism. With the growing heterogeneity and complexity of computer systems (CPU cores and accelerators, etc.), efficiently integrating emerging memories into existing systems poses new challenges and requires detailed evaluation in a realistic computing environment. In this article, we propose MEG, an open source, configurable, cycle-exact, and RISC-V-based full-system emulation infrastructure using FPGA and HBM. MEG provides a highly modular hardware design and includes a bootable Linux image for a realistic software flow, so that users can perform cross-layer software-hardware co-optimization in a full-system environment. To improve the observability and debuggability of the system, MEG also provides a flexible performance monitoring scheme to guide the performance optimization. The proposed MEG infrastructure can potentially benefit broad communities across computer architecture, system software, and application software. Leveraging MEG, we present two cross-layer system optimizations as illustrative cases to demonstrate the usability of MEG. In the first case study, we present a reconfigurable memory controller to improve the address mapping of standard memory controller. This reconfigurable memory controller along with its OS support allows us to optimize the address mapping scheme to fully exploit the massive parallelism provided by the emerging three-dimensional (3D) memories. In the second case study, we present a lightweight IOMMU design to tackle the unique challenges brought by 3D memory in providing virtual memory support for near-memory accelerators. We provide a prototype implementation of MEG on a Xilinx VU37P FPGA and demonstrate its capability, fidelity, and flexibility on real-world benchmark applications. We hope MEG fills a gap in the space of publicly available FPGA-based full-system emulation infrastructures, specifically targeting memory systems, and inspires further collaborative software/hardware innovations.
Symmetry Breaking of Phospholipids

Either stereo reactants or stereo catalysis from achiral or chiral molecules are a prerequisite to obtain pure enantiomeric lipid derivatives. We reviewed a few plausibly organic syntheses of phospholipids under prebiotic conditions with special attention paid to the starting materials as pro-chiral dihydroxyacetone and dihydroxyacetone phosphate (DHAP), which are the key molecules to break symmetry in phospholipids. The advantages of homochiral membranes compared to those of heterochiral membranes were analysed in terms of specific recognition, optimal functions of enzymes, membrane fluidity and topological packing. All biological membranes contain enantiomerically pure lipids in modern bacteria, eukarya and archaea. The contemporary archaea, comprising of methanogens, halobacteria and thermoacidophiles, are living under extreme conditions reminiscent of primitive environment and may indicate the origin of one ancient evolution path of lipid biosynthesis. The analysis of the known lipid metabolism reveals that all modern cells including archaea synthetize enantiomerically pure lipid precursors from prochiral DHAP. Sn-glycerol-1-phosphate dehydrogenase (G1PDH), usually found in archaea, catalyses the formation of sn-glycerol-1-phosphate (G1P), while sn-glycerol-3-phosphate dehydrogenase (G3PDH) catalyses the formation of sn-glycerol-3-phosphate (G3P) in bacteria and eukarya. The selective enzymatic activity seems to be the main strategy that evolution retained to obtain enantiomerically pure lipids. The occurrence of two genes encoding for G1PDH and G3PDH served to build up an evolutionary tree being the basis of our hypothesis article focusing on the evolution of these two genes. Gene encoding for G3PDH in eukarya may originate from G3PDH gene found in rare archaea indicating that archaea appeared earlier in the evolutionary tree than eukarya. Archaea and bacteria evolved probably separately, due to their distinct respective genes coding for G1PDH and G3PDH. We propose that prochiral DHAP is an essential molecule since it provides a convergent link between G1DPH and G3PDH. The synthesis of enantiopure phospholipids from DHAP appeared probably firstly in the presence of chemical catalysts, before being catalysed by enzymes which were the products of later Darwinian selection. The enzymes were probably selected for their efficient catalytic activities during evolution from large libraries of vesicles containing amino acids, carbohydrates, nucleic acids, lipids, and meteorite components that induced symmetry imbalance.
Integrating Disturbance, Seasonality, Multi-Year Temporal Dynamics, and Dormancy Into the Dynamics and Conservation of Metacommunities

The metacommunity framework has rapidly become a dominant concept used by ecologists to understand community assembly. By emphasizing extinction-colonization dynamics, dispersal, and species’ niche requirements in determining community structure, metacommunity theory unifies local and regional processes as integral to species distributions across landscapes. Metacommunity structure has traditionally been treated as static. However, habitat characteristics and community composition can shift through time because of factors like seasonal dynamics, ecosystem disturbance, multi-year climate variation (e.g., El Niño Southern Oscillation), and production and emergence of dormant propagules. In most systems, the relevance of such temporal variation for the structure and persistence of metacommunities is an open question that is of potential importance for conservation and management. We evaluate and synthesize the theory and concepts relevant to four major forms of temporal dynamics that are pertinent to metacommunities: disturbance, seasonality, multi-year climate variation, and dormancy. For each type of dynamic we review the theoretical underpinnings and empirical evidence to evaluate how the dynamic drives temporal variation in metacommunity structure. We also consider how major forms of anthropogenic change further influence these patterns. Our survey highlights that seasonal climatic differences can modify the distribution and availability of resources and connectivity, with consequences for species’ use of the landscape and species interactions. Disturbance and multi-year climate cycles can increase the importance of dispersal, but implications for environmental filtering and species interactions remain unresolved. Dormant life stages serve to anchor habitat patches and species pools in space and highlight the importance of dispersal-dormancy tradeoffs and environmental variation for metacommunity structure. Temporal variability in biotic and abiotic conditions associated with these drivers can modify the relative strengths of dispersal, environmental filtering, and species interactions, three biological processes that drive metacommunity structure. Inclusion of spatiotemporal drivers creates patterns of species diversity that differ from traditional metacommunity ideas. We use these insights to highlight research needs, suggest a reconceptualization of metacommunities as undergoing continuous change, and discuss the implications of temporal dynamism for the conservation and management of metacommunities.
On a Semigroup Problem II

We consider the following semigroup problem: is the closure of a semigroup S in a topological vector space X a group when S does not lie on “one side” of any closed hyperplane of X? Whereas for finite dimensional spaces, the answer is positive, we give a new example of infinite dimensional spaces where the answer is negative.
Are MCDA Methods Benchmarkable? A Comparative Study of TOPSIS, VIKOR, COPRAS, and PROMETHEE II Methods

Multi-Criteria Decision-Analysis (MCDA) methods are successfully applied in different fields and disciplines. However, in many studies, the problem of selecting the proper methods and parameters for the decision problems is raised. The paper undertakes an attempt to benchmark selected Multi-Criteria Decision Analysis (MCDA) methods. To achieve that, a set of feasible MCDA methods was identified. Based on reference literature guidelines, a simulation experiment was planned. The formal foundations of the authors’ approach provide a reference set of MCDA methods ( Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Complex Proportional Assessment (COPRAS), and PROMETHEE II: Preference Ranking Organization Method for Enrichment of Evaluations) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). This allowed the generation of a set of models differentiated by the number of attributes and decision variants, as well as similarity research for the obtained rankings sets. As the authors aim to build a complex benchmarking model, additional dimensions were taken into account during the simulation experiments. The aspects of the performed analysis and benchmarking methods include various weighing methods (results obtained using entropy and standard deviation methods) and varied techniques of normalization of MCDA model input data. Comparative analyses showed the detailed influence of values of particular parameters on the final form and a similarity of the final rankings obtained by different MCDA methods.
Organ-Specific Effects of Low Dose Radiation Exposure: A Comprehensive Review

Ionizing radiation (IR) is a high-energy radiation whose biological effects depend on the irradiation doses. Low-dose radiation (LDR) is delivered during medical diagnoses or by an exposure to radioactive elements and has been linked to the occurrence of chronic diseases, such as leukemia and cardiovascular diseases. Though epidemiological research is indispensable for predicting and dealing with LDR-induced abnormalities in individuals exposed to LDR, little is known about epidemiological markers of LDR exposure. Moreover, difference in the LDR-induced molecular events in each organ has been an obstacle to a thorough investigation of the LDR effects and a validation of the experimental results in in vivo models. In this review, we summarized the recent reports on LDR-induced risk of organ-specifically arranged the alterations for a comprehensive understanding of the biological effects of LDR. We suggested that LDR basically caused the accumulation of DNA damages, controlled systemic immune systems, induced oxidative damages on peripheral organs, and even benefited the viability in some organs. Furthermore, we concluded that understanding of organ-specific responses and the biological markers involved in the responses is needed to investigate the precise biological effects of LDR.
Information technology-enabled explorative learning and competitive performance in industrial service SMEs: a configurational analysis

As purveyors of knowledge-based and high value-added services to the manufacturing sector, industrial service small- and medium-sized enterprises (SMEs) must develop the information technology (IT) capabilities that, in combination with other non-IT capabilities, enable their capacity for organizational learning (OL) and for explorative learning in particular. In this context, this study aims to identify the different causal configurations that account for the nonlinear complex interplay of IT capabilities for exploration and strategic capabilities for explorative learning as they affect these firms’ competitive performance. ,Survey data obtained from 92 industrial service SMEs were analyzed with a configurational approach, using fuzzy set qualitative comparative analysis (fsQCA). ,As it allows for equifinality, the fsQCA analysis identified two sets of causal configurations that characterize the sampled firms’ explorative learning capability as it relates to competitive performance. In the first set, two configurations were equally associated with high innovation performance, whereas in the second set, four configurations were equally associated with high productivity. ,By viewing explorative learning as a dynamic capability that is enabled by the firm’s IT and strategic capabilities, the study contributes to OL theory by providing a more concrete or “operational” grounding, which allows for a greater practical applicability of this theory. By taking both the configurational and capability-based views of the OL-IT-performance causal framework, the authors provide an empirical basis for unraveling, explaining and understanding the complex non-linear relationships embedded within this framework.
Interlimb Asymmetries and Ipsilateral Associations of Plantar Flexors and Knee Extensors Rate-of-Force Development Scaling Factor

Rate of force/torque development scaling factor (RFD-SF/RTD-SF) was recently introduced as a tool to quantify the neuromuscular quickness, and it could have potential for interlimb asymmetry identification. Moreover, positive relationships in RFD-SF ability among different muscle groups were shown, but not in the lower extremity. The first aim of our study was to use RTD-SF for interlimb asymmetry identification. The second aim was to determine associations between plantar flexors (PF) and knee extensors (KE). Forty young healthy athletes (14.8 ± 1.2 years) performed explosive isometric contractions to a span of torque levels for PF and KE. From rapid isometric contractions, the RTD-SF and linearity (r2) of the regression line were calculated. Using RTD-SF we identified 10% (PF) and 15% (KE) of subjects with contralateral asymmetries (>15% criterion). The results revealed significant positive moderate correlation in RTD-SF between PF and KE (r = 0.401, p < 0.05). We supported that RTD-SF can be a useful tool for interlimb asymmetry identification. Future research about observed asymmetry in rapid submaximal contractions deserves more attention, as most of the functional sport specific activities put high demands on rapid force production. Our study as first confirmed positive associations in RTD-SF ability between muscle groups in lower limbs.