Miracle-dz/UniFAR-FTUs huggingface dataset:
Gimbal: enabling multi-tenant storage disaggregation on SmartNIC JBOFs

Emerging SmartNIC-based disaggregated NVMe storage has become a promising storage infrastructure due to its competitive IO performance and low cost. These SmartNIC JBOFs are shared among multiple co-resident applications, and there is a need for the platform to ensure fairness, QoS, and high utilization. Unfortunately, given the limited computing capability of the SmartNICs and the non-deterministic nature of NVMe drives, it is challenging to provide such support on today's SmartNIC JBOFs. This paper presents Gimbal, a software storage switch that orchestrates IO traffic between Ethernet ports and NVMe drives for co-located tenants. It enables efficient multi-tenancy on SmartNIC JBOFs using the following techniques: a delay-based SSD congestion control algorithm, dynamic estimation of SSD write costs, a fair scheduler that operates at the granularity of a virtual slot, and an end-to-end credit-based flow control channel. Our prototyped system not only achieves up to x6.6 better utilization and 62.6% less tail latency but also improves the fairness for complex workloads. It also improves a commercial key-value store performance in a multi-tenant environment with x1.7 better throughput and 35.0% less tail latency on average.
Network planning with deep reinforcement learning

Network planning is critical to the performance, reliability and cost of web services. This problem is typically formulated as an Integer Linear Programming (ILP) problem. Today's practice relies on hand-tuned heuristics from human experts to address the scalability challenge of ILP solvers. In this paper, we propose NeuroPlan, a deep reinforcement learning (RL) approach to solve the network planning problem. This problem involves multi-step decision making and cost minimization, which can be naturally cast as a deep RL problem. We develop two important domain-specific techniques. First, we use a graph neural network (GNN) and a novel domain-specific node-link transformation for state encoding, in order to handle the dynamic nature of the evolving network topology during planning decision making. Second, we leverage a two-stage hybrid approach that first uses deep RL to prune the search space and then uses an ILP solver to find the optimal solution. This approach resembles today's practice, but avoids human experts with an RL agent in the first stage. Evaluation on real topologies and setups from large production networks demonstrates that NeuroPlan scales to large topologies beyond the capability of ILP solvers, and reduces the cost by up to 17% compared to hand-tuned heuristics.
SYNTHESIS, ANTIBACTERIAL, AND ANTIFUNGAL EVALUATION OF NOVEL MANNICH BASES COMPOUNDS CONTAINING OXADIAZOLE AND PYRAZOLE MOIETIES

Purpose: To synthesize novel series of compounds containing 1,3,4-oxadiazole and pyrazole-3- one moieties in good yields and to evaluate the antimicrobial activity of title compounds. Methods: Title compounds were characterized by IR, 1H NMR and mass spectra and evaluated for their antimicrobial activities against certain selected gram-positive bacteria, gram-negative bacteria and fungi by disk diffusion method and broth dilution method. Results: Fluoro, chloro, bromo, nitro, morphonilyl, piperizynyl, N-methylpiperizine substituted compounds (VII c, d, e, f, i, j and k) showed more antimicrobial activity against than other compounds of the series. Conclusion: Antimicrobial activity was expressed as the corresponding minimum inhibitory concentration (MIC). The compounds have demonstrated considerable antibacterial and antifungal activities.
Differential mechanisms of cold sensitivity in mouse trigeminal and vagal ganglion neurons

Thermal signals are critical elements in the operation of interoceptive and exteroceptive neural circuits, essential for triggering thermally-driven reflexes and conscious behaviors. A fraction of cutaneous and visceral sensory endings are activated by cold temperatures. Compared to somatic (DRG and TG) neurons, little is known about the mechanisms underlying cold sensitivity of visceral vagal neurons. We used pharmacological and genetic tools for a side-by-side characterization of cold-sensitive (CS) neurons in adult mouse trigeminal (TG) and vagal ganglia (VG). We found that CS neurons are more abundant in VG than in TG. In both ganglia, sensitivity to cold varied widely and was enhanced by the potassium channel blocker 4-AP. The majority of CS neurons in VG co-express TRPA1 markers and cold-evoked responses are severely blunted in Trpa1 KO mice, with little impact of TRPM8 deletion or pharmacological TRPM8 blockade. Consistent with these findings, the expression of TRPM8-positive neurons was low in VG and restricted to the rostral jugular ganglion. In vivo retrograde labelling of airway-innervating vagal neurons demonstrated their enhanced cold sensitivity and a higher expression of TRPA1 compared to neurons innervating the stomach wall. In contrast, the majority of CS TG neurons co-express TRPM8 markers and their cold sensitivity is reduced after TRPM8 deletion or blockade. However, pharmacological or genetic reduction of TRPA1 showed that these channels contribute significantly to their cold sensitivity in TG. In both ganglia, a fraction of CS neuron respond to cooling by a mechanism independent of TRPA1 or TRPM8 yet to be characterized.
Identification of biomarkers, pathways and potential therapeutic targets for heart failure using bioinformatics analysis

Heart failure (HF) is a complex cardiovascular diseases associated with high mortality. To discover key molecular changes in HF, we analyzed next-generation sequencing (NGS) data of HF. In this investigation, differentially expressed genes (DEGs) were analyzed using limma in R package from GSE161472 of the Gene Expression Omnibus (GEO). Then, gene enrichment analysis, protein-protein interaction (PPI) network, miRNA-hub gene regulatory network and TF-hub gene regulatory network construction, and topological analysis were performed on the DEGs by the Gene Ontology (GO), REACTOME pathway, STRING, HiPPIE, miRNet, NetworkAnalyst and Cytoscape. Finally, we performed receiver operating characteristic curve (ROC) analysis of hub genes. A total of 930 DEGs 9464 up regulated genes and 466 down regulated genes) were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections and the citric acid (TCA) cycle and respiratory electron transport. Subsequently, the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed, and 10 hub genes in these network were focused on by centrality analysis and module analysis. Furthermore, data showed that HSP90AA1, ARRB2, MYH9, HSP90AB1, FLNA, EGFR, PIK3R1, CUL4A, YEATS4 and KAT2B were good diagnostic values. In summary, this study suggests that HSP90AA1, ARRB2, MYH9, HSP90AB1, FLNA, EGFR, PIK3R1, CUL4A, YEATS4 and KAT2B may act as the key genes in HF.
DBpred: A deep learning method for the prediction of DNA interacting residues in protein sequences

DNA-protein interaction is one of the most crucial interactions in the biological system, which decide the fate of many processes such as transcription, regulation of gene expression, splicing, and many more. Though many computational approaches exist that can predict the DNA interacting residues from the protein sequences, there is still a significant opportunity for improvement in terms of performance and accessibility. In this study, we have downloaded the benchmark dataset from method hybridNAP and recently published method ProNA2020, for training and validation purposes, that comprise 864 and 308 proteins, respectively. We have implemented CD-HIT software to handle the redundancy with 30% identity, and left with 646 proteins for training and 46 proteins for validation purposes, in which the validation dataset do not share more than 30% of sequence identity with the training dataset. We have generated amino acid binary profiles, physicochemical-properties based binary profiles, PSSM profiles, and a combination of all profiles described as hybrid feature. 1D-CNN based model performed best as compared to other models for each set of features. The model developed using amino acid binary profile achieved AUROC of 0.83 and 0.74 for training and validation dataset. Using physicochemical properties based binary profile, model attained AUROC of 0.86 and 0.73 for training and validation dataset. Model generated using PSSM profile resulted in the better performance with AUROC 0.91 and 0.74 for training and validation dataset. And, model developed using hybrid of all features performed best with AUROC of 0.91, and 0.79 for training and validation dataset, respectively. We have compared our method’s performance with the current approach and shown improvements. We have included the best-performing models in the standalone and web server accessible at https://webs.iiitd. edu.in/raghava/dbpred. DBPred is an effective approach to predict the DNA interacting residues in the protein using its primary structure.
Rotavirus pre-symptomatically downregulates ileum-innervating sympathetic nerves concomitant with increased intestinal transit and altered brain activity

While diarrhea, the hallmark symptom of rotavirus infection, has been considered to occur only due to intrinsic intestinal effects, we show evidence for central control underlying the symptomology. With large-scale 3D volumetric tissue imaging a mouse model, we show that rotavirus infection disrupts the autonomic balance by downregulating the noradrenergic sympathetic nervous system in ileum, concomitant with increased intestinal transit. A most interesting observation was that nervous response from CNS occurs pre-symptomatically, an observation that bring new understanding to how virus give raise to clinical symptoms. In the CNS of infected animals, we found increased pS6 immunoreactivity in the area postrema and decreased phosphorylated STAT5-immunoreactive neurons in the bed nucleus of the stria terminalis, which are associated with autonomic control including stress response. Our observations bring new and important knowledge of how rotavirus virus infection induce gut-nerve-brain crosstalk giving raise to sickness symptoms.
Oral Fc-Coupled Preproinsulin Achieves Systemic and Thymic Delivery Through the Neonatal Fc Receptor and Partially Delays Autoimmune Diabetes

Tolerogenic vaccinations using beta-cell antigens are attractive for type 1 diabetes prevention, but clinical trials have been disappointing. This is probably due to the late timing of intervention, when multiple auto-antibodies are already present. We therefore devised a strategy to introduce the initiating antigen preproinsulin (PPI) during neonatal life, when autoimmunity is still silent and central tolerance mechanisms, which remain therapeutically unexploited, are more active. This strategy employs an oral administration of PPI-Fc, i.e. PPI fused with an IgG Fc to bind the intestinal neonatal Fc receptor (FcRn) that physiologically delivers maternal antibodies to the offspring during breastfeeding. Neonatal oral PPI-Fc vaccination did not prevent diabetes development in PPI T-cell receptor-transgenic G9C8.NOD mice. However, PPI-Fc was efficiently transferred through the intestinal epithelium in an Fc- and FcRn-dependent manner, was taken up by antigen presenting cells, and reached the spleen and thymus. Although not statistically significant, neonatal oral PPI-Fc vaccination delayed diabetes onset in polyclonal Ins2 -/-. NOD mice that spontaneously develop accelerated diabetes. Thus, this strategy shows promise in terms of systemic and thymic antigen delivery via the intestinal FcRn pathway, but the current PPI-Fc formulation/regimen requires further improvements to achieve diabetes prevention.
Tight Adherence (Tad) Pilus Genes Indicate Putative Niche Differentiation in Phytoplankton Bloom Associated Rhodobacterales

The multiple interactions of phytoplankton and bacterioplankton are central for our understanding of aquatic environments. A prominent example of those is the consistent association of diatoms with Alphaproteobacteria of the order Rhodobacterales. These photoheterotrophic bacteria have traditionally been described as generalists that scavenge dissolved organic matter. Many observations suggest that members of this clade are specialized in colonizing the microenvironment of diatom cells, known as the phycosphere. However, the molecular mechanisms that differentiate Rhodobacterales generalists and phycosphere colonizers are poorly understood. We investigated Rhodobacterales in the North Sea during the 2010–2012 spring blooms using a time series of 38 deeply sequenced metagenomes and 10 metaproteomes collected throughout these events. Rhodobacterales metagenome assembled genomes (MAGs) were recurrently abundant. They exhibited the highest gene enrichment and protein expression of small-molecule transporters, such as monosaccharides, thiamine and polyamine transporters, and anaplerotic pathways, such as ethylmalonyl and propanoyl-CoA metabolic pathways, all suggestive of a generalist lifestyle. Metaproteomes indicated that the species represented by these MAGs were the dominant suppliers of vitamin B12 during the blooms, concomitant with a significant enrichment of genes related to vitamin B12 biosynthesis suggestive of association with diatom phycospheres. A closer examination of putative generalists and colonizers showed that putative generalists had persistently higher relative abundance throughout the blooms and thus produced more than 80% of Rhodobacterales transport proteins, suggesting rapid growth. In contrast, putative phycosphere colonizers exhibited large fluctuation in relative abundance across the different blooms and correlated strongly with particular diatom species that were dominant during the blooms each year. The defining feature of putative phycosphere colonizers is the presence of the tight adherence (tad) gene cluster, which is responsible for the assembly of adhesive pili that presumably enable attachment to diatom hosts. In addition, putative phycosphere colonizers possessed higher prevalence of secondary metabolite biosynthetic gene clusters, particularly homoserine lactones, which can regulate bacterial attachment through quorum sensing. Altogether, these findings suggest that while many members of Rhodobacterales are competitive during diatom blooms, only a subset form close associations with diatoms by colonizing their phycospheres.
LEAP2 Impairs the Capability of the Growth Hormone Secretagogue Receptor to Regulate the Dopamine 2 Receptor Signaling

The growth hormone secretagogue receptor (GHSR) signals in response to ghrelin, but also acts via ligand-independent mechanisms that include either constitutive activation or interaction with other G protein-coupled receptors, such as the dopamine 2 receptor (D2R). A key target of GHSR in neurons is voltage-gated calcium channels type 2.2 (CaV2.2). Recently, the liver-expressed antimicrobial peptide 2 (LEAP2) was recognized as a novel GHSR ligand, but the mechanism of action of LEAP2 on GHSR is not well understood. Here, we investigated the role of LEAP2 on the canonical and non-canonical modes of action of GHSR on CaV2.2 function. Using a heterologous expression system and patch-clamp recordings, we found that LEAP2 impairs the reduction of CaV2.2 currents induced by ghrelin-evoked and constitutive GHSR activities, acting as a GHSR antagonist and inverse agonist, respectively. We also found that LEAP2 prevents GHSR from modulating the effects of D2R signaling on CaV2.2 currents, and that the GHSR-binding N-terminal region LEAP2 underlies these effects. Using purified labeled receptors assembled into lipid nanodiscs and Forster Resonance Energy Transfer (FRET) assessments, we found that the N-terminal region of LEAP2 stabilizes an inactive conformation of GHSR that is dissociated from Gq protein and, consequently, reverses the effect of GHSR on D2R-dependent Gi activation. Thus, our results provide critical molecular insights into the mechanism mediating LEAP2 modulation of GHSR.
Diversity and Versatility in Small RNA-Mediated Regulation in Bacterial Pathogens

Bacterial gene expression is under the control of a large set of molecules acting at multiple levels. In addition to the transcription factors (TFs) already known to be involved in global regulation of gene expression, small regulatory RNAs (sRNAs) are emerging as major players in gene regulatory networks, where they allow environmental adaptation and fitness. Developments in high-throughput screening have enabled their detection in the entire bacterial kingdom. These sRNAs influence a plethora of biological processes, including but not limited to outer membrane synthesis, metabolism, TF regulation, transcription termination, virulence, and antibiotic resistance and persistence. Almost always noncoding, they regulate target genes at the post-transcriptional level, usually through base-pair interactions with mRNAs, alone or with the help of dedicated chaperones. There is growing evidence that sRNA-mediated mechanisms of actions are far more diverse than initially thought, and that they go beyond the so-called cis- and trans-encoded classifications. These molecules can be derived and processed from 5' untranslated regions (UTRs), coding or non-coding sequences, and even from 3' UTRs. They usually act within the bacterial cytoplasm, but recent studies showed sRNAs in extracellular vesicles, where they influence host cell interactions. In this review, we highlight the various functions of sRNAs in bacterial pathogens, and focus on the increasing examples of widely diverse regulatory mechanisms that might compel us to reconsider what constitute the sRNA.
Modulatory Effect of 4-(methylthio)butyl Isothiocyanate Isolated From Eruca Sativa Thell. on DMBA Induced Overexpression of Hypoxia and Glycolytic Pathway in Sprague-Dawley Female Rats

4-(methylthio)butyl isothiocyanate (4-MTBITC) is a hydrolytic product from the plant Eruca sativa Thell. In the present study, we explored the anti-cancer effect of 4-MTBITC against 7,12-dimethylbenz [a] anthracene (DMBA) induced breast cancer. Hypoxic conditions were developed using a single dose of 60 mg/kg DMBA. Hepatic and renal parameters were increased along with antioxidants in cancer-bearing rats which were lowered with the treatment of 4-MTBITC. Further, it inhibited the up-regulation of glycolytic enzymes caused by DMBA. The hypoxia pathway was evaluated using RT-PCR and it was found that the 40 mg/kg doses of 4-MTBITC statistically lowered the expression of HIF-1α. Akt/mTOR signaling pathway was one of the major pathways involved in 4-MTBITC-induced cell growth arrest by western blotting. Amino acid profiling serum-free plasma revealed the downregulation of specific amino acids required for vital components of fast-growing cancer cells. 4-MTBITC reduced the levels of serine, arginine, alanine, asparagines, and glutamic acid. Histological examination also showed neoplastic growth following DMBA doses. 4-MTBITC treated rats showed less infiltration and normal physiology. Our findings for the first time demonstrated the potential therapeutic significance of 4-MTBITC on modulation of glycolytic enzymes and hypoxia pathway in female rats.
Genome-Wide Identification of the ARF Gene Family and ARF3 Target Genes Regulating Ovary Initiation in Hazel via ChIP Sequencing

Hazel (Corylus spp.) is an economically important nut species with a unique biological characteristic of ovary differentiation and development initiating from the ovary primordium after pollination. Auxin participates in ovary initiation and has an essential impact on hazel fruit yield and quality. The regulation of auxin in ovary development is thought to be related to auxin response factors (ARFs); however, its detailed regulatory mechanism remains unclear. The spatiotemporal expression pattern of C. heterophylla ARF3 (ChARF3) was accessed via ARF gene family member identification and expression abundance analysis as well as immunohistochemistry. ChARF3 target genes were identified via chromatin immunoprecipitation followed by next-generation sequencing (ChIP-Seq). In total, 14 ChARF members containing at least B3 and Auxin_resp domains were found to be distributed on 9 of 11 chromosomes, and the protein molecular weights were predicted to range from 70.93–139.22 kD. Among eight differentially expressed ChARFs, ChARF3 showed the most significant differences over four ovary developmental stages. Immunohistochemical analysis revealed that ChARF3 was expressed in the ovary primordium and funiculus, integument, endosperm, radicle, and cotyledon indicating its potential regulatory roles in ovary differentiation and development. In total, 3,167 ChARF3 target genes were identified through ChIP-Seq in four ovary developmental stages and were significantly enriched in the biosynthesis of secondary metabolites (ko01110), phenylpropanoid biosynthesis (ko00940), and phytohormone signal transduction (ko04075). ChARF3 was hypothesized to be involved in the regulation of auxin-induced genes and the transcription factors MADS, AP2/ERF, TCP, FT, and LFY. These results suggest that ChARF3 may regulate ovary initiation and ovule development by mediating genes related to auxin biosynthesis and transport, cell division and proliferation, and flower and fruit development. This study provides new insights into the molecular mechanism of hazel yield formation.
Emergence of Dengue 4 as Dominant Serotype During 2017 Outbreak in South India and Associated Cytokine Expression Profile

Dengue virus (DENV) infection is prevalent in tropical and subtropical regions of the world, which is fatal if untreated symptomatically. Emergence of new genotype within serotypes led to enhanced severity. The objective of the study is to identify the molecular characteristics of the DENV circulated during 2017 outbreak in Tamil Nadu, India, and to investigate the role of inflammatory cytokines in different “serotypes” and in “dengue severity”. A total of 135 suspected samples were tested for DENV infection using IgM, IgG, and qPCR assay; where 76 samples were positive for DENV and analyzed for 12 inflammatory cytokines using ELISA. Serotyping shows 14 DENV-1, 22 DENV-2, 7 DENV-3, and 33 DENV-4, where DENV-4 was predominant. Among 76, 42 isolates were successfully sequenced for C-prM region and grouped. A lineage shift was observed in DENV-4 genotype. Irrespective of serotypes, IFNγ was significantly elevated in all serotypes than control as well as in primary infection than secondary, indicating its role in immune response. GM-CSF and IP-10 were significantly elevated in secondary infection and could be used as prognostic biomarkers for secondary infection. Our observation shows differential cytokine expression profile varied with each serotype, indicating serotype/genotype-specific viral proteins might play a major role in dengue severity. DENV-4 as dominant serotype was reported in Tamil Nadu for the first time during an outbreak with a mixed Th1/Th17 cytokine expression profile that correlated with disease severity. We conclude it is essential to identify circulating viral genotype and their fitness by mutational analysis to correlate with disease severity and immune status, as this correlation will be helpful in diagnostics and therapeutics applications.