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Hidradenitis suppurativa (HS) is a chronic skin condition affecting approximately 1% of the US population. HS skin lesions are highly inflammatory and characterized by a large immune infiltrate. While B cells and plasma cells comprise a major component of this immune milieu, the biology and the contribution of these cells in HS pathogenesis are unclear. We aimed to investigate the dynamics and microenvironmental interactions of B cells within cutaneous HS lesions. Combining histological analysis, single-cell RNA sequencing, and spatial transcriptomics profiling of HS lesions, we defined the tissue microenvironment relative to B cell activity within this disease. Our findings identified tertiary lymphoid structures (TLSs) within HS lesions and described organized interactions among T cells, B cells, antigen-presenting cells, and skin stroma. We found evidence that B cells within HS TLSs actively underwent maturation, including participation in germinal center reactions and class switch recombination. Moreover, skin stroma and accumulating T cells were primed to support the formation of TLSs and facilitate B cell recruitment during HS. Our data definitively demonstrated the presence of TLSs in lesional HS skin and point to ongoing cutaneous B cell maturation through class switch recombination and affinity maturation during disease progression in this inflamed nonlymphoid tissue.

Record linkage is the task of combining records from multiple files which refer to overlapping sets of entities when there is no unique identifying field. In streaming record linkage, files arrive sequentially in time and estimates of links are updated after the arrival of each file. This problem arises in settings such as longitudinal surveys, electronic health records, and online events databases, among others. The challenge in streaming record linkage is to efficiently update parameter estimates as new data arrive. We approach the problem from a Bayesian perspective with estimates calculated from posterior samples of parameters and present methods for updating link estimates after the arrival of a new file that are faster than fitting a joint model with each new data file. In this article, we generalize a two-file Bayesian Fellegi-Sunter model to the multi-file case and propose two methods to perform streaming updates. We examine the effect of prior distribution on the resulting linkage accuracy as well as the computational tradeoffs between the methods when compared to a Gibbs sampler through simulated and real-world survey panel data. We achieve near-equivalent posterior inference at a small fraction of the compute time. for this article are available online. [ABSTRACT FROM AUTHOR]

Existing robotic systems have a tension between generality and precision. Deployed solutions for robotic manipulation tend to fall into the paradigm of one robot solving a single task, lacking "precise generalization," or the ability to solve many tasks without compromising on precision. This paper explores solutions for precise and general pick and place. In precise pick and place, or kitting, the robot transforms an unstructured arrangement of objects into an organized arrangement, which can facilitate further manipulation. We propose SimPLE (Simulation to Pick Localize and placE) as a solution to precise pick and place. SimPLE learns to pick, regrasp, and place objects given the object's computer-aided design model and no prior experience. We developed three main components: task-aware grasping, visuotactile perception, and regrasp planning. Task-aware grasping computes affordances of grasps that are stable, observable, and favorable to placing. The visuotactile perception model relies on matching real observations against a set of simulated ones through supervised learning to estimate a distribution of likely object poses. Last, we computed a multistep pick-and-place plan by solving a shortest-path problem on a graph of hand-to-hand regrasps. On a dual-arm robot equipped with visuotactile sensing, SimPLE demonstrated pick and place of 15 diverse objects. The objects spanned a wide range of shapes, and SimPLE achieved successful placements into structured arrangements with 1-mm clearance more than 90% of the time for six objects and more than 80% of the time for 11 objects. Editor's summary: In robotic manipulation, there is often a trade-off between high accuracy for a repetitive motion and reliability in an unstructured environment. To teach a robot to move objects into an organized arrangement, Bauza et al. have developed a framework called SimPLE, which stands for Simulation to Pick, Localize, and placE. Given only a model of the object, the framework generates training data by sampling grasps in simulation. The SimPLE framework was tested with a set of 15 objects of different geometries on a dual-arm robot equipped with tactile sensors and an external depth camera. Using hand-to-hand regrasps, the robot successfully relocated the objects into structured arrangements, demonstrating the possibility of transferring a model learned in simulation to a real robot. —Melisa Yashinski [ABSTRACT FROM AUTHOR]

Prior self-control exertion is consistently reported to cause decrements in subsequent physical performance. However, research into the explanatory mechanisms underpinning the effect is limited and has not been assessed under a meta-analytical lens. Therefore, the present study reports a meta-analysis examining the effects of self-control exertion on subsequent physical performance, as well as the mechanisms underpinning the effect. A systematic search of relevant databases was conducted to identify studies that utilized the sequential task paradigm, involving self-control manipulations lasting 30 minutes or less, and examined an aspect of physical performance. Random effects meta-analysis demonstrated that the prior exertion of self-control resulted in a statistically significant medium sized negative effect of prior self-control exertion on subsequent physical performance (g = −0.55). Further analysis revealed a small increase in initial perceptions of pain (g = 0.18) and a medium sized reduction in self-efficacy (g = −0.48), while motivation and RPE were unaffected following the exertion of self-control. The present study provides a novel insight into the mechanisms underpinning the effects of prior self-control exertion on subsequent physical performance. Initial perceptions of pain and self-efficacy appear important mechanisms and thus could be targeted in future interventions aimed at attenuating the effects of self-control exertion to enhance subsequent physical performance. [ABSTRACT FROM AUTHOR]

SAMHD1 regulates cellular nucleotide homeostasis, controlling dNTP levels by catalysing their hydrolysis into 2'-deoxynucleosides and triphosphate. In differentiated CD4+ macrophage and resting T-cells SAMHD1 activity results in the inhibition of HIV-1 infection through a dNTP blockade. In cancer, SAMHD1 desensitizes cells to nucleoside-analogue chemotherapies. Here we employ time-resolved cryogenic-EM imaging and single-particle analysis to visualise assembly, allostery and catalysis by this multi-subunit enzyme. Our observations reveal how dynamic conformational changes in the SAMHD1 quaternary structure drive the catalytic cycle. We capture five states at high-resolution in a live catalytic reaction, revealing how allosteric activators support assembly of a stable SAMHD1 tetrameric core and how catalysis is driven by the opening and closing of active sites through pairwise coupling of active sites and order-disorder transitions in regulatory domains. This direct visualisation of enzyme catalysis dynamics within an allostery-stabilised platform sets a precedent for mechanistic studies into the regulation of multi-subunit enzymes. SAMHD1 is a regulator of dNTP homeostasis and an HIV restriction factor. The authors use time-resolved cryo-EM to visualise dynamic conformational changes that drive the catalytic cycle and allosteric regulation of this multi-subunit enzyme. [ABSTRACT FROM AUTHOR]

Purpose: The conflict between the desire to reduce effort during exercise and the performance goal of the exercise task contributes to explaining endurance exercise performance. However, whether the trajectories of these two motivational responses systematically differ across individuals with different characteristics is poorly understood. The present study examined whether changes in desire to reduce effort and performance goal value across moderate, heavy, and severe exercise intensity domains differed between cyclists and untrained, but active participants., Methods: Fifty participants (14 cyclists and 36 untrained) completed an incremental step test on a cycle ergometer, in which work rate was increased by 25 W every 4 min until voluntary exhaustion. Desire to reduce effort, performance goal value, and blood lactate concentration (for determination of exercise intensity domains) were measured every 4 min and the data were analysed using multilevel modelling., Results: Desire to reduce effort increased quicker for untrained participants in the moderate exercise intensity domain (b = 1.66, p < .001) and across the whole trial (b = 1.64, p < .001), compared to cyclists (b = .69, and b = 1.14, respectively, both p < .001). Untrained participants reported similar performance goal value at the beginning of the trial (b = 16.02, p < .001), compared to cyclists (b = 17.25, p < .001). Beyond moderate intensities, the performance goal value decreased significantly for the untrained participants (b = -.70, p < .001) but significantly increased for cyclists (b = .45, p = .01). This pattern was also observed when focusing solely on the severe intensity domain (cyclists: b = .90, p < .001; untrained: b = -.84, p < .001)., Conclusion: There are distinct differences in the desire to reduce effort and performance goal value between cyclists and untrained athletes. Identifying these systematic differences enhances the credibility of the desire-goal conflict framework in explaining endurance performance and provides insight into the type and timing of interventions that might be successful in improving performance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: Estrogen receptor (ER) alpha signaling is a known driver of ER-positive (ER+)/human epidermal growth factor receptor 2 negative (HER2-) breast cancer. Combining endocrine therapy (ET) such as fulvestrant with CDK4/6, mTOR, or PI3K inhibitors has become a central strategy in the treatment of ER+ advanced breast cancer. However, suboptimal ER inhibition and resistance resulting from the ESR1 mutation dictates that new therapies are needed., Experimental Design: A medicinal chemistry campaign identified vepdegestrant (ARV-471), a selective, orally bioavailable, and potent small molecule PROteolysis-TArgeting Chimera (PROTAC) degrader of ER. We used biochemical and intracellular target engagement assays to demonstrate the mechanism of action of vepdegestrant, and ESR1 wild-type (WT) and mutant ER+ preclinical breast cancer models to demonstrate ER degradation-mediated tumor growth inhibition (TGI)., Results: Vepdegestrant induced ≥90% degradation of wild-type and mutant ER, inhibited ER-dependent breast cancer cell line proliferation in vitro, and achieved substantial TGI (87%-123%) in MCF7 orthotopic xenograft models, better than those of the ET agent fulvestrant (31%-80% TGI). In the hormone independent (HI) mutant ER Y537S patient-derived xenograft (PDX) breast cancer model ST941/HI, vepdegestrant achieved tumor regression and was similarly efficacious in the ST941/HI/PBR palbociclib-resistant model (102% TGI). Vepdegestrant-induced robust tumor regressions in combination with each of the CDK4/6 inhibitors palbociclib, abemaciclib, and ribociclib; the mTOR inhibitor everolimus; and the PI3K inhibitors alpelisib and inavolisib., Conclusions: Vepdegestrant achieved greater ER degradation in vivo compared with fulvestrant, which correlated with improved TGI, suggesting vepdegestrant could be a more effective backbone ET for patients with ER+/HER2- breast cancer., (©2024 The Authors; Published by the American Association for Cancer Research.)

Lenacapavir, targeting the human immunodeficiency virus type-1 (HIV-1) capsid, is the first-in-class antiretroviral drug recently approved for clinical use. The development of Lenacapavir is attributed to the remarkable progress in our understanding of the capsid protein made during the last few years. Considered little more than a component of the virus shell to be shed early during infection, the capsid has been found to be a key player in the HIV-1 life cycle by interacting with multiple host factors, entering the nucleus, and directing integration. Here, we describe the key advances that led to this 'capsid revolution'., (© The Author(s) (2023). Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, CEMCS, CAS.)