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Weakly Interacting Massive Particles (WIMPs) are among the best-motivated dark matter candidates. No conclusive signal, despite an extensive search program that combines, often in a complementary way, direct, indirect, and collider probes, has been detected so far. This situation might change in near future due to the advent of one/multi-TON Direct Detection experiments. We thus, find it timely to provide a review of the WIMP paradigm with focus on a few models which can be probed at best by these facilities. Collider and Indirect Detection, nevertheless, will not be neglected when they represent a complementary probe.

Cells are richly equipped with nuclear receptors, which act as ligand-regulated transcription factors. Peroxisome proliferator activated receptors (PPARs), members of the nuclear receptor family, have been extensively studied for their roles in development, differentiation, and homeostatic processes. In the recent past, there has been substantial interest in understanding and defining the functions of PPARs and their agonists in regulating innate and adaptive immune responses as well as their pharmacologic potential in combating acute and chronic inflammatory disease. In this review, we focus on emerging evidence of the potential roles of the PPAR subtypes in macrophage biology. We also discuss the roles of dual and pan PPAR agonists as modulators of immune cell function, microbial infection, and inflammatory diseases.

We give a fresh look at the WIMP paradigm by considering updated limits and prospects for direct and indirect dark matter detection and covering realistic dark matter models, beyond the so-called simplified models, which have been the target of experimental scrutiny. In particular, we investigate dark matter scenarios featuring dwindled direct detection signals, due to loop or momentum suppression. Therefore, this review extends previous reviews in different aspects and motivates the search for WIMP dark matter in light of the present and near-future detectors.

Modeling human diseases as networks simplify complex multi-cellular processes, helps understand patterns in noisy data that humans cannot find, and thereby improves precision in prediction. Using Inflammatory Bowel Disease (IBD) as an example, here we outline an unbiased AI-assisted approach for target identification and validation. A network was built in which clusters of genes are connected by directed edges that highlight asymmetric Boolean relationships. Using machine-learning, a path of continuum states was pinpointed, which most effectively predicted disease outcome. This path was enriched in gene-clusters that maintain the integrity of the gut epithelial barrier. We exploit this insight to prioritize one target, choose appropriate pre-clinical murine models for target validation and design patient-derived organoid models. Potential for treatment efficacy is confirmed in patient-derived organoids using multivariate analyses. This AI-assisted approach identifies a first-in-class gut barrier-protective agent in IBD and predicted Phase-III success of candidate agents. Traditional drug discovery process use differential, Bayesian and other network based approaches. We developed a Boolean approach for building disease maps and prioritizing pre-clinical models to discover a first-in-class therapy to restore and protect the leaky gut barrier in inflammatory bowel disease.

SARS-CoV-2, the virus responsible for COVID-19, causes widespread damage in the lungs in the setting of an overzealous immune response whose origin remains unclear. We present a scalable, propagable, personalized, cost-effective adult stem cell-derived human lung organoid model that is complete with both proximal and distal airway epithelia. Monolayers derived from adult lung organoids (ALOs), primary airway cells, or hiPSC-derived alveolar type II (AT2) pneumocytes were infected with SARS-CoV-2 to create in vitro lung models of COVID-19. Infected ALO monolayers best recapitulated the transcriptomic signatures in diverse cohorts of COVID-19 patient-derived respiratory samples. The airway (proximal) cells were critical for sustained viral infection, whereas distal alveolar differentiation (AT2→AT1) was critical for mounting the overzealous host immune response in fatal disease; ALO monolayers with well-mixed proximodistal airway components recapitulated both. Findings validate a human lung model of COVID-19, which can be immediately utilized to investigate COVID-19 pathogenesis and vet new therapies and vaccines. This work was supported by the National Institutes for Health (NIH) grants 1R01DK107585-01A1, 3R01DK107585-05S1 (to SD); R01-AI141630, CA100768 and CA160911 (to PG) and R01-AI 155696 (to PG, DS and SD); R00-CA151673 and R01-GM138385 (to DS), R01- HL32225 (to PT), UCOP-R00RG2642 (to SD and PG), UCOP-R01RG3780 (to P.G. and D.S) and a pilot award from the Sanford Stem Cell Clinical Center at UC San Diego Health (P.G, S.D, D.S). GDK was supported through The American Association of Immunologists Intersect Fellowship Program for Computational Scientists and Immunologists. L.C.A's salary was supported in part by the VA San Diego Healthcare System. This manuscript includes data generated at the UC San Diego Institute of Genomic Medicine (IGC) using an Illumina NovaSeq 6000 that was purchased with funding from a National Institutes of Health SIG grant (#S10 OD026929).

A bstract Supersymmetric models with singlet extensions can accommodate single- or multi-step first-order phase transitions (FOPT) along the various constituent field directions. Such a framework can also produce Gravitational Waves, detectable at the upcoming space-based interferometers, e.g., U-DECIGO. We explore the dynamics of electroweak phase transition and the production of Gravitational Waves in an extended set-up of the Next-to-Minimal Supersymmetric Standard Model (NMSSM) with a Standard Model singlet right-handed neutrino superfield. We examine the role of the new parameters compared to NMSSM on the phase transition dynamics and observe that the occurrence of a FOPT, an essential requirement for Electroweak Baryogenesis, typically favours a right-handed sneutrino state below 125 GeV. Our investigation shows how the analysis can offer complementary probes for physics beyond the Standard Model besides the collider searches.

Sensing of pathogens by Toll-like receptor 4 (TLR4) induces an inflammatory response; controlled responses confer immunity but uncontrolled responses cause harm. Here we define how a multimodular scaffold, GIV (a.k.a. Girdin), titrates such inflammatory response in macrophages. Upon challenge with either live microbes or microbe-derived lipopolysaccharides (a ligand for TLR4), macrophages with GIV mount a more tolerant (hypo-reactive) transcriptional response and suppress proinflammatory cytokines and signaling pathways (i.e., NFkB and CREB) downstream of TLR4 compared to their GIV-depleted counterparts. Myeloid-specific gene-depletion studies confirmed that the presence of GIV ameliorates dextran sodium sulfate-induced colitis and sepsis-induced death. The antiinflammatory actions of GIV are mediated via its C-terminally located TIR-like BB-loop (TILL) motif which binds the cytoplasmic TIR modules of TLR4 in a manner that precludes receptor dimerization; such dimerization is a prerequisite for proinflammatory signaling. Binding of GIV’s TILL motif to TIR modules inhibits proinflammatory signaling via other TLRs, suggesting a convergent paradigm for fine-tuning macrophage inflammatory responses.

In adult tissue, stem and progenitor cells must tightly regulate the balance between proliferation and differentiation to sustain homeostasis. How this exquisite balance is achieved is an area of active investigation. Here, we show that epidermal genes, including ~30% of induced differentiation genes already contain stalled Pol II at the promoters in epidermal stem and progenitor cells which is then released into productive transcription elongation upon differentiation. Central to this process are SPT6 and PAF1 which are necessary for the elongation of these differentiation genes. Upon SPT6 or PAF1 depletion there is a loss of human skin differentiation and stratification. Unexpectedly, loss of SPT6 also causes the spontaneous transdifferentiation of epidermal cells into an intestinal-like phenotype due to the stalled transcription of the master regulator of epidermal fate P63. Our findings suggest that control of transcription elongation through SPT6 plays a prominent role in adult somatic tissue differentiation and the inhibition of alternative cell fate choices. The role of RNA polymerase II (Pol II) recruitment during adult stem cell differentiation is well understood, but not that of Pol II elongation. Here, the authors show that 30% of epidermal stem cell differentiation genes depend on SPT6 and PAF1 for Pol II elongation, and SPT6 loss leads to an intestine-like phenotype.

Accumulating evidence suggests that dysregulation of transcriptional enhancers plays a significant role in cancer pathogenesis. Herein, we performed a genome-wide discovery of enhancer elements in colorectal cancer (CRC). We identified PVT1 locus as a previously unrecognized transcriptional regulator in CRC with a significantly high enhancer activity, which ultimately was responsible for regulating the expression of MYC oncogene. High expression of the PVT1 long-non-coding RNA (lncRNA) transcribed from the PVT1 locus was associated with poor survival among patients with stage II and III CRCs ( p  < 0.05). Aberrant methylation of the PVT1 locus inversely correlated with the reduced expression of the corresponding the PVT1 lncRNA, as well as MYC gene expression. Bioinformatic analyses of CRC-transcriptomes revealed that the PVT1 locus may also broadly impact the expression and function of other key genes within two key CRC-associated signaling pathways – the TGFβ/SMAD and Wnt/β-Catenin pathways. We conclude that the PVT1 is a novel oncogenic enhancer of MYC and its activity is controlled through epigenetic regulation mediated through aberrant methylation in CRC. Our findings also suggest that the PVT1 lncRNA expression is a promising prognostic biomarker and a potential therapeutic target in CRC.

The ongoing pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), necessitates strategies to identify prophylactic and therapeutic drug candidates for rapid clinical deployment. Here, we describe a screening pipeline for the discovery of efficacious SARS-CoV-2 inhibitors. We screen a best-in-class drug repurposing library, ReFRAME, against two high-throughput, high-content imaging infection assays: one using HeLa cells expressing SARS-CoV-2 receptor ACE2 and the other using lung epithelial Calu-3 cells. From nearly 12,000 compounds, we identify 49 (in HeLa-ACE2) and 41 (in Calu-3) compounds capable of selectively inhibiting SARS-CoV-2 replication. Notably, most screen hits are cell-line specific, likely due to different virus entry mechanisms or host cell-specific sensitivities to modulators. Among these promising hits, the antivirals nelfinavir and the parent of prodrug MK-4482 possess desirable in vitro activity, pharmacokinetic and human safety profiles, and both reduce SARS-CoV-2 replication in an orthogonal human differentiated primary cell model. Furthermore, MK-4482 effectively blocks SARS-CoV-2 infection in a hamster model. Overall, we identify direct-acting antivirals as the most promising compounds for drug repurposing, additional compounds that may have value in combination therapies, and tool compounds for identification of viral host cell targets. Here, the authors perform repurposing screens of the ReFRAME drug library in two cell lines and identify inhibitors of SARS-CoV-2 infection. Antiviral activity of prodrug MK-4482 is confirmed in hamsters.