Miracle-dz/UniFAR-FTUs huggingface dataset:
Repetitive Erythropoietin Treatment Improves Long-Term Neurocognitive Outcome by Attenuating Hyperoxia-Induced Hypomyelination in the Developing Brain

Introduction: Preterm infants born before 28 weeks of gestation are at high risk of neurodevelopmental impairment in later life. Cerebral white and gray matter injury is associated with adverse outcomes. High oxygen levels, often unavoidable in neonatal intensive care, have been identified as one of the main contributing factors to preterm brain injury. Thus, preventive and therapeutic strategies against hyperoxia-induced brain injury are needed. Erythropoietin (Epo) is a promising and also neuroprotective candidate due to its clinical use in infants as erythropoiesis-stimulating agent. Objective: The objective of this study was to investigate the effects of repetitive Epo treatment on the cerebral white matter and long-term motor-cognitive outcome in a neonatal rodent model of hyperoxia-induced brain injury. Methods: Three-day old Wistar rats were exposed to hyperoxia (48 h, 80% oxygen). Four doses of Epo (5,000 IU/kg body weight per day) were applied intraperitoneally from P3-P6 with the first dose at the onset of hyperoxia. Oligodendrocyte maturation and myelination were evaluated via immunohistochemistry and Western blot on P11. Motor-cognitive deficits were assessed in a battery of complex behavior tests (Open Field, Novel Object Recognition, Barnes maze) in adolescent and fully adult animals. Following behavior tests animals underwent post-mortem diffusion tensor imaging to investigate long-lasting microstructural alterations of the white matter. Results: Repetitive treatment with Epo significantly improved myelination deficits following neonatal hyperoxia at P11. Behavioral testing revealed attenuated hyperoxia-induced cognitive deficits in Epo-treated adolescent and adult rats. Conclusion: A multiple Epo dosage regimen protects the developing brain against hyperoxia-induced brain injury by improving myelination and long-term cognitive outcome. Though current clinical studies on short-term outcome of Epo-treated prematurely born children contradict our findings, long-term effects up to adulthood are still lacking. Our data support the essential need for long-term follow-up of preterm infants in current clinical trials.
Dietary Glucose Consumption Promotes RALDH Activity in Small Intestinal CD103+CD11b+ Dendritic Cells

Retinal dehydrogenase (RALDH) enzymatic activities catalyze the conversion of vitamin A to its metabolite Retinoic acid (RA) in intestinal dendritic cells (DCs) and promote immunological tolerance. However, precise understanding of the exogenous factors that act as initial trigger of RALDH activity in these cells is still evolving. By using germ-free (GF) mice raised on an antigen free (AF) elemental diet, we find that certain components in diet are critically required to establish optimal RALDH expression and activity, most prominently in small intestinal CD103+CD11b+ DCs (siLP-DCs) right from the beginning of their lives. Surprisingly, systematic screens using modified diets devoid of individual dietary components indicate that proteins, starch and minerals are dispensable for this activity. On the other hand, in depth comparison between subtle differences in dietary composition among different dietary regimes reveal that adequate glucose concentration in diet is a critical determinant for establishing RALDH activity specifically in siLP-DCs. Consequently, pre-treatment of siLP-DCs, and not mesenteric lymph node derived MLNDCs with glucose, results in significant enhancement in the in vitro generation of induced Regulatory T (iTreg) cells. Our findings reveal previously underappreciated role of dietary glucose concentration in establishing regulatory properties in intestinal DCs, thereby extending a potential therapeutic module against intestinal inflammation.
Type IV Coupling Proteins as Potential Targets to Control the Dissemination of Antibiotic Resistance

The increase of infections caused by multidrug-resistant bacteria, together with the loss of effectiveness of currently available antibiotics, represents one of the most serious threats to public health worldwide. The loss of human lives and the economic costs associated to the problem of the dissemination of antibiotic resistance require immediate action. Bacteria, known by their great genetic plasticity, are capable not only of mutating their genes to adapt to disturbances and environmental changes but also of acquiring new genes that allow them to survive in hostile environments, such as in the presence of antibiotics. One of the major mechanisms responsible for the horizontal acquisition of new genes (e.g., antibiotic resistance genes) is bacterial conjugation, a process mediated by mobile genetic elements such as conjugative plasmids and integrative conjugative elements. Conjugative plasmids harboring antibiotic resistance genes can be transferred from a donor to a recipient bacterium in a process that requires physical contact. After conjugation, the recipient bacterium not only harbors the antibiotic resistance genes but it can also transfer the acquired plasmid to other bacteria, thus contributing to the spread of antibiotic resistance. Conjugative plasmids have genes that encode all the proteins necessary for the conjugation to take place, such as the type IV coupling proteins (T4CPs) present in all conjugative plasmids. Type VI coupling proteins constitute a heterogeneous family of hexameric ATPases that use energy from the ATP hydrolysis for plasmid transfer. Taking into account their essential role in bacterial conjugation, T4CPs are attractive targets for the inhibition of bacterial conjugation and, concomitantly, the limitation of antibiotic resistance dissemination. This review aims to compile present knowledge on T4CPs as a starting point for delving into their molecular structure and functioning in future studies. Likewise, the scientific literature on bacterial conjugation inhibitors has been reviewed here, in an attempt to elucidate the possibility of designing T4CP-inhibitors as a potential solution to the dissemination of multidrug-resistant bacteria.
Bolder and Brighter? Exploring Correlations Between Personality and Cognitive Abilities Among Individuals Within a Population of Wild Zebrafish, Danio rerio

Within populations, individual differences in behavioral and cognitive traits are dependent on the habitat and specific contexts, such as the presence of a predator or other risks. The ability to show variable responses to changing conditions can be of immense survival advantage to organisms. We studied individual differences in specific personality traits, such as boldness, exploration, and spatial ability, and the effect of these traits on learning ability and memory in the presence of a predatory threat, among wild caught zebrafish (Danio rerio). Under laboratory conditions, individuals were trained to perform a simple navigation task, and their performance, exploration, boldness traits were measured, along with learning and memory abilities under two contexts (i.e., in the presence and absence of a predator). Our results revealed that fish showed a clear decline in emergence time, exploration time, and feeding latency over trials, indicative of learning, and further tests for memory also showed memory retention. While the presence of a predator increased emergence time and latencies for navigating, indicating declines in boldness and exploration, these were found to be correlated to different personalities among the individuals and dependent on their sex. While females tended to be bolder and learned the spatial task faster, they showed lower memory retention abilities than males. Personality traits were also found to affect cognitive abilities among individuals. In general, the presence of a predator decreased performance latencies. However, bolder individuals were less affected and emerged more quickly from the refuge chamber than shy individuals. Our results point to the complex interplay of ecological context along with inherent correlations across personality traits that decide the overall personality and cognitive responses among individuals even within populations. These findings thus highlight the importance of an inclusive approach that combines personality and cognition studies for understanding variations within populations.
Performance Analysis of Fair Medium Access Control Protocol for Asymmetric Full Duplex in WLAN

Full-duplex (FD) communication is capable of simultaneously transmitting and receiving data on the same frequency band. To effectively utilize FD in a wireless local area network (WLAN), one must use medium access control (MAC) protocols that consider the characteristics of FD. Many researchers have proposed and analyzed FD MAC protocols for WLANs. Most of this work revealed that as the number of nodes increases, the overall throughput decreases due to collisions. We have found, however, that with a smart MAC protocol, the throughput actually improves as the number of nodes increases. In this paper, we propose an asymmetric FD MAC protocol and then design an FD WLAN analytical model to evaluate saturation throughput. In our analytical model, we consider FD pair probability—the probability that a node capable of FD communication exists. To validate our model, we calculate FD pair probability values based on the modulation and coding scheme (MCS) levels and self-interference cancellation (SIC). We then analyze the effect of the FD pair probability on throughput. Simulation results verify the accuracy of our analytical model. Moreover, we compare the fairness of the proposed and conventional FD MAC protocols. As demonstrated through extensive evaluations, the fairness of the proposed FD MAC protocol is improved.
Local Bases for Model‐reduced Smoke Simulations

We present a flexible model reduction method for simulating incompressible fluids. We derive a novel vector field basis composed of localized basis flows which have simple analytic forms and can be tiled on regular lattices, avoiding the use of complicated data structures or neighborhood queries. Local basis flow interactions can be precomputed and reused to simulate fluid dynamics on any simulation domain without additional overhead. We introduce heuristic simulation dynamics tailored to our basis and derived from a projection of the Navier‐Stokes equations to produce physically plausible motion, exposing intuitive parameters to control energy distribution across scales. Our basis can adapt to curved simulation boundaries, can be coupled with dynamic obstacles, and offers simple adjustable trade‐offs between speed and visual resolution.
SWITCHES: Searchable Web Interface for Topologies of CHEmical Switches

Bistable biochemical switches are key motifs in cellular state decisions and long-term storage of cellular ‘memory’. There are a few known biological switches that have been well characterized, however these examples are insufficient for systematic surveys of properties of these important systems. Here we present a resource of all possible bistable biochemical reaction networks with up to 6 reactions between 3 molecules, and 3 reactions between 4 molecules. Over 35,000 reaction topologies were constructed by identifying unique combinations of reactions between a fixed number of molecules. Then, these topologies were populated with rates within a biologically realistic range. The Searchable Web Interface for Topologies of CHEmical Switches (SWITCHES, https://switches.ncbs.res.in) provides a bistability and parameter analysis of over 7 million models from this systematic survey of chemical reaction space. This database will be useful for theoreticians interested in analyzing stability in chemical systems and also experimentalists for creating robust synthetic biological switches. Availability and Implementation Freely available on the web at https://switches.ncbs. res.in. Website implemented in PHP, MariaDB, Graphviz, and Apache, with all major browsers supported. Supplementary Information Not applicable.
Antisense oligonucleotides against monoacylglycerol acyltransferase 1 (Mogat1) improve glucose metabolism independently of Mogat1

Objective Monoacylglycerol acyltransferase (MGAT) enzymes catalyze the synthesis of diacylglycerol from monoacylglycerol. Previous work has suggested the importance of MGAT activity in the development of obesity-related hepatic insulin resistance. Indeed, antisense oligonucleotide (ASO)-mediated knockdown of the gene encoding MGAT1, Mogat1, reduced hepatic MGAT activity and improved glucose tolerance and insulin resistance in high fat diet (HFD) fed mice. However, recent work has suggested that some ASOs may have off-target effects on body weight and metabolic parameters via activation of the interferon alpha/beta receptor 1 (IFNAR-1) pathway. Methods Mice with whole-body Mogat1 knockout or a floxed allele for Mogat1 to allow for liver-specific Mogat1-knockout (by either a liver-specific transgenic or adeno-associated virus-driven Cre recombinase) were generated. These mice were placed on a high fat diet and glucose metabolism and insulin sensitivity was assessed after 16 weeks on diet. In some experiments, mice were treated with control or Mogat1 or control ASOs in the presence or absence of IFNAR-1 neutralizing antibody. Results Genetic deletion of hepatic Mogat1, either acutely or chronically, did not improve hepatic steatosis, glucose tolerance, or insulin sensitivity in HFD-fed mice. Furthermore, constitutive Mogat1 knockout in all tissues actually exacerbated HFD-induced weight gain, insulin resistance, and glucose intolerance on a HFD. Despite markedly reduced Mogat1 expression, liver MGAT activity was unaffected in all knockout mouse models. Mogat1 overexpression hepatocytes increased liver MGAT activity and TAG content in low-fat fed mice, but did not cause insulin resistance. Interestingly, Mogat1 ASO treatment improved glucose tolerance in both wild-type and Mogat1 null mice, suggesting an off target effect. Inhibition of IFNAR-1 did not block the effect of Mogat1 ASO on glucose homeostasis. Conclusion These results indicate that genetic loss of Mogat1 does not affect hepatic MGAT activity or metabolic homeostasis on HFD and show that Mogat1 ASOs improve glucose metabolism through effects independent of targeting Mogat1 or activation of IFNAR-1 signaling. Highlights Mogat1 liver-specific KO or KD does not improve metabolism in HFD fed mice. Whole-body Mogat1-deletion impairs insulin tolerance in HFD fed mice. Mogat1 ASOs improves whole body metabolism independently of gene knockdown. Blockade of the INFR response does not prevent off-target effects of Mogat1 ASOs.
Treatment of human cells with 5-aza-dC induces formation of PARP1-DNA covalent adducts at genomic regions targeted by DNMT1

The nucleoside analog 5-aza-2’-deoxycytidine (5-aza-dC) is used to treat some hematopoietic malignancies. The mechanism of cell killing depends upon DNMT1, but is otherwise not clearly defined. Here we show that PARP1 forms covalent DNA adducts in human lymphoblast or fibroblasts treated with 5-aza-dC. Some adducts recovered from 5-aza-dC-treated cells have undergone cleavage by apoptotic caspases 3/7. Mapping of PARP1-DNA adducts, by a new method, “Adduct-Seq”, demonstrates adduct enrichment at CpG-dense genomic locations that are targets of maintenance methylation by DNMT1. Covalent protein-DNA adducts can arrest replication and induce apoptosis, and these results raise the possibility that induction of PARP1-DNA adducts may contribute to cell killing in response to treatment with 5-aza-dC.
Distributed Adaptive Sliding Mode Control for Vehicle Platoon with Uncertain Driving Resistance and Actuator Saturation

Vehicle platoon has been demonstrated to be a promising driving pattern for its prominent advantages in enhancing traffic safety, improving highway capacity, and increasing fuel economy as well as reducing carbon emissions. However, the uncertain driving resistance and saturated actuator output decay the control performance and may even lead to the instability of a vehicle platoon. Therefore, a distributed adaptive sliding mode control algorithm for vehicle platoon with uncertain driving resistance and actuator saturation is proposed in this paper. First of all, sliding mode control technique, together with the coupled sliding surface (CSS) method, is adopted to design the vehicle platoon control algorithm and an adaptive updating law is proposed to estimate the unknown driving resistance coefficients. Then, for the problem of actuator saturation, an antiwindup compensation-based approach is utilized to attenuate the integral windup of the adaptive platoon control laws in the case of actuator saturation. In addition, considering the chattering problem inherent in sliding mode control, a sigmoid-like function sgn⋅ is deployed to weaken the influence of chattering, which is expected to enhance the driving comfortableness. Both theoretical analysis and numerical simulation verify the feasibility and effectiveness of the proposed vehicle platoon algorithm.
A valid protective immune response elicited in rhesus macaques by an inactivated vaccine is capable of defending against SARS-CoV-2 infection

With the relatively serious global epidemic outbreak of SARS-CoV-2 infection, public concerns focus on not only clinical therapeutic measures and public quarantine for this disease but also the development of vaccines. The technical design of our SARS-CoV-2 inactivated vaccine provides a viral antigen that enables the exposure of more than one structural protein based upon the antibody composition of COVID-19 patients’ convalescent serum. This design led to valid immunity with increasing neutralizing antibody titers and a CTL response detected post-immunization of this vaccine by two injections in rhesus macaques. Further, this elicited immunoprotection in macaques enables not only to restrain completely viral replication in tissues of immunized animals, compared to the adjuvant control and those immunized by an RBD peptide vaccine, but also to significantly alleviate inflammatory lesion in lung tissues in histo-pathologic detection, compared to the adjuvant control with developed interstitial pneumonia. The data obtained from these macaques immunized with the inactivated vaccine or RBD peptide vaccine suggest that immunity with a clinically protective effect against SARS-CoV-2 infection should include not only specific neutralizing antibodies but also specific CTL responses against at least the S and N antigens.
Multiple Morphological Constraints-Based Complex Gland Segmentation in Colorectal Cancer Pathology Image Analysis

Histological assessment of glands is one of the major concerns in colon cancer grading. Considering that poorly differentiated colorectal glands cannot be accurately segmented, we propose an approach for segmentation of glands in colon cancer images, based on the characteristics of lumens and rough gland boundaries. First, we use a U-net for stain separation to obtain H-stain, E-stain, and background stain intensity maps. Subsequently, epithelial nucleus is identified on the histopathology images, and the lumen segmentation is performed on the background intensity map. Then, we use the axis of least inertia-based similar triangles as the spatial characteristics of lumens and epithelial nucleus, and a triangle membership is used to select glandular contour candidates from epithelial nucleus. By connecting lumens and epithelial nucleus, more accurate gland segmentation is performed based on the rough gland boundary. The proposed stain separation approach is unsupervised, and the stain separation makes the category information contained in the H&E image easy to identify and deal with the uneven stain intensity and the inconspicuous stain difference. In this project, we use deep learning to achieve stain separation by predicting the stain coefficient. Under the deep learning framework, we design a stain coefficient interval model to improve the stain generalization performance. Another innovation is that we propose the combination of the internal lumen contour of adenoma and the outer contour of epithelial cells to obtain a precise gland contour. We compare the performance of the proposed algorithm against that of several state-of-the-art technologies on publicly available datasets. The results show that the segmentation approach combining the characteristics of lumens and rough gland boundary has better segmentation accuracy.
State of the Art in Time‐Dependent Flow Topology: Interpreting Physical Meaningfulness Through Mathematical Properties

We present a state‐of‐the‐art report on time‐dependent flow topology. We survey representative papers in visualization and provide a taxonomy of existing approaches that generalize flow topology from time‐independent to time‐dependent settings. The approaches are classified based upon four categories: tracking of steady topology, reference frame adaption, pathline classification or clustering, and generalization of critical points. Our unique contributions include introducing a set of desirable mathematical properties to interpret physical meaningfulness for time‐dependent flow visualization, inferring mathematical properties associated with selective research papers, and utilizing such properties for classification. The five most important properties identified in the existing literature include coincidence with the steady case, induction of a partition within the domain, Lagrangian invariance, objectivity, and Galilean invariance.