Miracle-dz/UniFAR-FTUs huggingface dataset:
Serinc5 restricts HIV membrane fusion by altering lipid order and heterogeneity in the viral membrane

The host restriction factor, Serinc5, incorporates into budding HIV particles and inhibits their infection by an incompletely understood mechanism. We have previously reported that Serinc5 but not its paralogue, Serinc2, blocks HIV cell entry by membrane fusion, specifically by inhibiting fusion pore formation and dilation. A compelling body of work also suggests Serinc5 may alter the conformation and clustering of the HIV fusion protein, Env. To contribute an additional perspective to the developing model of Serinc5 restriction, we assessed Serinc2 and Serinc5’s effects on HIV pseudoviral membranes. Using fluorescence lifetime imaging with an order sensitive dye, FLIPPER-TR, and by measuring pseudoviral membrane thickness via cryo electron microscopy (cryoEM), Serinc5 was found to increase membrane heterogeneity, skewing the distribution towards a larger fraction of the viral membrane in an ordered phase. We also directly observed for the first time the coexistence of membrane domains within individual viral membrane envelopes. Using a TIRF-based single particle fusion assay, we found that incorporation of exogenous phosphatidylethanolamine (PE) into the viral membrane rescued HIV pseudovirus fusion from restriction by Serinc5, which was accompanied by decreased membrane heterogeneity and order. This effect was specific for PE and did not depend on acyl chain length or saturation. Together, these data suggest that Serinc5 alters multiple interrelated properties of the viral membrane—lipid chain order, rigidity, line tension, and lateral pressure—which decrease accessibility of fusion intermediates and disfavor completion of fusion. These biophysical insights into Serinc5 restriction of HIV infectivity could contribute to the development of novel antivirals that exploit the same weaknesses of HIV and potentially other enveloped viruses.
Subclinical Atherosclerosis Is Associated with Discrepancies in BAFF and APRIL Levels and Altered Breg Potential of Precursor-like Marginal Zone B-Cells in Long-Term HIV Treated Individuals

Chronic inflammation persists in people living with HIV (PLHIV) despite antiretrovial therapy (ART), and is involved in their premature development of cardiovascular diseases (CVD) such as atherosclerosis. We have previously reported that an excess of “B-cell activating factor” (BAFF), an important molecule for the selection and activation of first line Marginal Zone (MZ) B-cell populations, is associated with deregulations of precursor-like MZ (MZp), whose potent B-cell regulatory (Breg) capacities are altered in PLHIV, early on and despite 1-2 years of ART. Based on these observations, and growing evidence that MZ populations are involved in atherosclerosis control, we designed a cross sectional study to explore the associations between BAFF and its analogue “A proliferation-inducing ligand” (APRIL) with subclinical CVD in long time treated individuals of the Canadian HIV and Aging Cohort Study (CHACS) imaging sub-study group. We also characterized the Breg profile of MZp from the blood of these individuals. Results were correlated with the total volume of atherosclerotic plaques (TPV) and with CVD risk factors and biomarkers. TPV was measured using cardiac computerised tomography angiography, and presence of CVD was defined as TPV > 0. We report that blood levels of BAFF are elevated and correlate positively with CVD and its risk factors in PLHIV from the CHACS, in contrast to APRIL levels, which correlate negatively with these factors. Expression levels of Breg markers such as NR4A3, CD39, CD73 and CD83 are significantly lower in PLHIV when compared to those of HIV-uninfected controls. In vitro experiments show that APRIL upregulates the expression of Breg markers by blood MZp from HIV-uninfected individuals, while this modulation is dampened by the addition of recombinant BAFF. Altogether, our observations suggest that strategies viewed to modulate levels of BAFF and/or APRIL could eventually represent a potential treatment target for CVD in PLHIV.
Learning-dependent evolution of odor mixture representations in piriform cortex

Rodents can learn from exposure to rewarding odors to make better and quicker decisions. The piriform cortex is thought to be important for learning complex odor associations, however it is not understood exactly how it learns to remember discriminations between many, sometimes overlapping, odor mixtures. We investigated how odor mixtures are represented in the posterior piriform cortex (pPC) of mice while they learn to discriminate a unique target odor mixture against hundreds of nontarget mixtures. We find that a significant proportion of pPC neurons discriminate between the target and all other nontarget odor mixtures. Neurons that prefer the target odor mixture tend to respond with brief increases in firing rate at odor onset compared to other neurons, which exhibit sustained and/or decreased firing. We allowed mice to continue training after they had reached high levels of performance and find that pPC neurons become more selective for target odor mixtures as well as for randomly chosen repeated nontarget odor mixtures that mice did not have to discriminate from other nontargets. These single unit changes during overtraining are accompanied by better categorization decoding at the population level, even though behavioral metrics of mice such as reward rate and latency to respond do not change. However, when difficult ambiguous trial types are introduced, the robustness of the target selectivity is correlated with better performance on the difficult trials. Taken together, these data reveal pPC as a dynamic and robust system that can optimize for both current and possible future task demands at once.
Model Choice Metrics to Optimize Profile-QSAR Performance

Background Predicting molecular activity against protein targets is difficult because of the paucity of experimental data. Approaches like multitask modeling and collaborative filtering seek to improve model accuracy by leveraging results from multiple targets, but are limited because different compounds are measured with different assays, leading to sparse data matrices. Profile-QSAR (pQSAR) 2.0 addresses this problem by fitting a series of partial least squares models for each target, using as features the predictions from single-task models on the remaining targets. This method has been shown to produce better results than single task and multitask models. However, the factors determining the success of pQSAR 2.0 have as yet not been characterized. In this paper we examine the experimental conditions that lead to better pQSAR models. We limit the amount of data available to the method by retraining with decreasing amounts of data and explore the model’s ability to generalize to compounds that have never been assayed. Finally, we look at the properties of training data needed to demonstrate pQSAR improvement. Results We apply pQSAR 2.0 on a collection of GPCR and safety targets collected from Drug Target Commons, ExcapeDB, and ChEMBL. We found that pQSAR improved models on 34 of the 149 assays selected. In the other 115 assays, single task random forests offered better performance. There are many factors that contribute to an increase in performance, but the main factor is compound assay coverage. The pQSAR model improves when more compounds are measured in multiple assays. Conclusion It is necessary to consider the available data before applying pQSAR. Successful pQSAR models require a profile made of correlated targets that share compounds with other assays. This technique is best used when experimental data is available as random forest regressors often do not generalize well enough for virtual drug search applications.
Targeted IS-element sequencing uncovers transposition dynamics during selective pressure in enterococci

Insertion sequences (IS) are simple transposons implicated in the genome evolution of diverse pathogenic bacterial species. Enterococci have emerged as important human intestinal pathogens with newly adapted virulence potential and antibiotic resistance. These genetic features arose in tandem with large-scale genome evolution mediated by mobile elements. Pathoadaptation in enterococci is thought to be mediated in part by the IS element IS256 through gene inactivation and recombination events. However, the regulation of IS256 and the mechanisms controlling its activation are not well understood. Here, we adapt an IS256-specfic deep sequencing method to describe how chronic lytic phage infection drives widespread diversification of IS256 in E. faecalis and how antibiotic exposure is associated with IS256 diversification in both E. faecalis and E. faecium during a clinical human infection. We show through comparative genomics that IS256 is primarily found in hospital-adapted enterococcal isolates. Analyses of IS256 transposase gene levels reveal that IS256 mobility is regulated at the transcriptional level by multiple mechanisms in E. faecalis, indicating tight control of IS256 activation in the absence of selective pressure. Our findings reveal that stressors such as phages and antibiotic exposure drives rapid genome-scale transposition in the enterococci. IS256 diversification can therefore explain how selective pressures mediate evolution of the enterococcal genome, ultimately leading to the emergence of dominant nosocomial lineages that threaten human health. Author Summary Insertion sequence (IS) elements are simple transposons that are ubiquitous in bacteria. In the enterococci, which includes medically relevant species such as Enterococcus faecalis and Enterococcus faecium, the IS element IS256 is widespread and has been implicated in pathogenesis and antibiotic resistance. Despite the importance of IS256 to the biology of the enterococci, we know very about how this element is regulated and diversifies enterococcal genomes. Here, we show that IS256 is preferentially found in hospital-adapted and virulent strains of the enterococci. In E. faecalis V583, a vancomycin resistant blood isolate, IS256 is regulated by multiple transcriptional mechanisms. To understand how IS256 is mobilized, we adapted an Illumina-based deep sequencing method called IS-Seq to find novel IS256 insertions when applying the selective pressure of bacteriophage (phage) predation. Using this method, we found that chronic phage infection drives IS256 diversification of the E. faecalis V583 genome. Additionally, we tracked IS256 insertional activity during a human E. faecium infection and found that increased IS256 diversity was associated with specific antibiotic usage. Together, our results demonstrate that the enterococci control IS256 activity to diversify their genomes which may lead to the emergence of hospital-adapted strains that threaten human health.
1,000 ancient genomes uncover 10,000 years of natural selection in Europe

Ancient DNA has revolutionized our understanding of human population history. However, its potential to examine how rapid cultural evolution to new lifestyles may have driven biological adaptation has not been met, largely due to limited sample sizes. We assembled genome-wide data from 1,291 individuals from Europe over 10,000 years, providing a dataset that is large enough to resolve the timing of selection into the Neolithic, Bronze Age, and Historical periods. We identified 25 genetic loci with rapid changes in frequency during these periods, a majority of which were previously undetected. Signals specific to the Neolithic transition are associated with body weight, diet, and lipid metabolism-related phenotypes. They also include immune phenotypes, most notably a locus that confers immunity to Salmonella infection at a time when ancient Salmonella genomes have been shown to adapt to human hosts, thus providing a possible example of human-pathogen co-evolution. In the Bronze Age, selection signals are enriched near genes involved in pigmentation and immune-related traits, including at a key human protein interactor of SARS-CoV-2. Only in the Historical period do the selection candidates we detect largely mirror previously-reported signals, highlighting how the statistical power of previous studies was limited to the last few millennia. The Historical period also has multiple signals associated with vitamin D binding, providing evidence that lactase persistence may have been part of an oligogenic adaptation for efficient calcium uptake and challenging the theory that its adaptive value lies only in facilitating caloric supplementation during times of scarcity. Finally, we detect selection on complex traits in all three periods, including selection favoring variants that reduce body weight in the Neolithic. In the Historical period, we detect selection favoring variants that increase risk for cardiovascular disease plausibly reflecting selection for a more active inflammatory response that would have been adaptive in the face of increased infectious disease exposure. Our results provide an evolutionary rationale for the high prevalence of these deadly diseases in modern societies today and highlight the unique power of ancient DNA in elucidating biological change that accompanied the profound cultural transformations of recent human history.
Subcellular Localization of Glycogen Synthase Kinase 3 (cid:2) Controls Embryonic Stem Cell Self-Renewal (cid:1)

Phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT1), and c-myc have well-established roles in promoting the maintenance of murine embryonic stem cells (mESCs). In contrast, the activity of glycogen synthase kinase 3 (cid:1) (GSK3 (cid:1) ), a negatively regulated target of AKT1 signaling, antagonizes self-renewal. Here, we show that PI3K/AKT1 signaling promotes self-renewal by suppressing GSK3 (cid:1) activity and restricting its access to nuclear substrates such as c-myc. GSK3 (cid:1) shuttles between the cytoplasm and nucleus in mESCs but accumulates in the cytoplasm in an inactive form due to AKT1-dependent nuclear export and inhibitory phosphorylation. When PI3K/AKT1 signaling declines following leukemia inhibitory factor withdrawal, active GSK3 (cid:1) accumulates in the nucleus, where it targets c-myc through phosphorylation on threonine 58 (T58), promoting its degradation. Ectopic nuclear localization of active GSK3 (cid:1) promotes differentiation, but this process is blocked by a mutant form of c-myc (T58A) that evades phosphorylation by GSK3 (cid:1) . for cell cycle control, apoptosis, replicative senescence,
MRI anatomy of schizophrenia The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters

Structural magnetic resonance imaging (MRI) data have provided much evidence in support of our current view that schizophrenia is a brain disorder with altered brain structure, and consequently involving more than a simple disturbance in neurotransmission. This review surveys 118 peer– reviewed studies with control group from 1987 to May 1998. Most studies (81%) do not find abnormalities of whole brain/intracranial contents, while lateral ventricle enlargement is reported in 77%, and third ventricle enlargement in 67%. The temporal lobe was the brain parenchymal region with the most consistently documented abnormalities. Volume decreases were found in 62% of 37 studies of whole temporal lobe, and in 81% of 16 studies of the superior temporal gyrus (and in 100% with gray matter separately evaluated). Fully 77% of the 30 studies of the medial temporal lobe reported volume reduction in one or more of its constituent structures (hippocampus, amygdala, parahippocampal gyrus). volume lobes studied; the studies positive findings. Most studies cortical gray matter (86%) found volume reductions were in certain areas. discussed. The relationship of clinical symptoms to MRI findings is reviewed, as is the growing evidence suggesting structural abnormalities differ in affective (bipolar) psychosis and schizophrenia.
Transferring biodiversity-ecosystem function research to the 1 management of ‘ real-world ’ ecosystems 2 Running title : Transferring BEF research 3

50 51 Biodiversity-ecosystem functioning (BEF) research grew rapidly following concerns that biodiversity 52 loss would negatively affect ecosystem functions and the ecosystem services they underpin. However, 53 despite evidence that biodiversity strongly affects ecosystem function, the influence of BEF research 54 upon policy and the management of ‘real-world’ ecosystems, i.e. semi-natural habitats and 55 agroecosystems, has been limited. Here, we address this issue by classifying BEF research into three 56 clusters based on the degree of human control over species composition and the spatial scale, in terms 57 of grain, of the investigation, and discussing how the research of each cluster is best suited to inform 58 particular fields of ecosystem management. Research in the first cluster, small-grain highly controlled 59 studies, is best able to provide general insights into mechanisms and to inform the management of 60 species-poor and highly managed systems such as croplands, plantations, and the restoration of 61 heavily degraded ecosystems. Research from the second cluster, small-grain observational studies, and 62 species removal and addition studies, may allow for direct predictions of the impacts of species loss in 63 specific semi-natural ecosystems. Research in the third cluster, large-grain uncontrolled studies, may 64 best inform landscape scale management and national-scale policy. We discuss barriers to transfer 65 within each cluster and suggest how new research and knowledge exchange mechanisms may 66 overcome these challenges. To meet the potential for BEF research to address global challenges, we 67 recommend transdisciplinary research that goes beyond these current clusters and considers the social68 ecological context of the ecosystems in which BEF knowledge is generated. This requires recognizing 69 the social and economic value of biodiversity for ecosystem services at scales, and in units, that matter 70 to land managers and policy makers. 71
The Challenge of Iron Stress in Cyanobacteria The Challenge of Iron Stress in Cyanobacteria

Iron is an essential nutrient for most living organisms. Due to the low solubility of ferric iron at physiological pH, the transition from an anaerobic atmosphere to the actual oxi-dant environment caused a dramatical decrease of iron bioavailability. Therefore, most organisms had to adapt their lifestyle to survive under an iron-depleted environment. In cyanobacteria, the electron transport chains involved in photosynthesis and respiration, as well as the enzymes involved in nitrogen metabolism have a high content of iron. Hence, cyanobacterial iron requirements are much higher than those of heterotrophic organisms. In this chapter, we revise different strategies developed by this important group of microorganisms to cope with iron deficiency, as well as the regulatory networks involved in the homeostasis of this indispensable element.
Initial Investigation of Position Determination of Various Sound Sources in a Room

Special sounds, such as ultrasonic waves and diffused sound sources used to perform high precision indoor positioning. If the positioning of various ordinary sound sources in a room becomes possible, it is thought that numerous applications are likely. This paper proposes a new method to estimate with high accuracy the position of various ordinary indoor sound sources, rather than using any special sound source. We constructed an environment where positioning experiments can be performed by knowing the size of the actual sonic environment. Positioning experiments were conducted using the sound of an operating microwave oven, the ringing tone of a telephone, and a diffused sound source. Highly accurate positioning about +/20 cm could be realized for the diffused sound and the microwave oven. In contrast, it was confirmed that the ringtone had a positioning error exceeding 1 m. Keywords-Positioning; Sound Source; TDOA; CSP Analysis; Real Environment.
In Vitro Evaluation of the Efficacy of Two Different At-home Bleaching Agents: Solo or Combined

Background: Combining at-home and in-office vital teeth bleaching techniques has proven to be effective; however, the efficacy of combining at-home bleaching agents is still unclear. Objective: To compare the effectiveness of 10% and 35% carbamide peroxide at-home bleaching agents solo or in combination. Materials and Methods: Forty enamel samples from human premolars were divided into four groups (n=10) to receive different at-home bleaching protocols. The samples were bleached for two weeks as follow: G1 bleached with 10%CP for 8h/day; G2 bleached with 35%CP for 30 minutes/day; G3 starting with 35%CP for three days and continue with 10%CP for the last 11 days; and G4 bleached with 10%CP for the first 11 days and with 35%CP for the last three days. Teeth color measurements were recorded by a colorimeter in reference to the CIE L*a*b* at different periods. Student's t-test was used to compare between the groups at each measuring period. Results : No significant differences were seen among the four groups neither in ΔE*1& ΔE*2 nor in ΔE*6 (p>0.05). Conclusion : Both 10% and 35%CP, used for two weeks, were effective in teeth whitening. Compared with 10% CP, combination treatments whether starting with 35% CP or ending with it produced no significant difference in teeth whitening during the treatment or one month post operatively.
Inﬂuence on the Temperature Estimation by the Planetary Boundary Layer Scheme with Different Minimum Eddy Diffusivity in WRF v3.9.1.1

The minimum eddy diffusivity (Kzmin) in the planetary boundary layer (PBL) scheme can inﬂuence the model performance in simulating meteorological parameters such as temperature. However, detailed studies on the sensitivities of the simulated temperature to the settings of Kzmin are still lacking. Thus, in this study, we evaluated the performance of the ACM2 (Asymmetrical Convective Model, version 2) scheme in the WRF (Weather Research and Forecasting) model with different settings of Kzmin, in simulating the spatiotemporal distribution of the temperature in the region of Beijing, China. Five constant 5 values and a function were implemented in the model to calculate Kzmin, and the simulation results with different settings of Kzmin were compared and analyzed. The results show that the increase of Kzmin leads to an elevation of the 2-m temperature, especially in the nighttime. We ﬁgured out that the deviation in the 2-m temperature at night is mainly caused by the different estimations of the turbulent mixing under stable conditions in simulation scenarios with different Kzmin settings. Moreover, the spatial distribution of the temperature deviation indicates that under various underlying surface categories, the change in Kzmin 10 exerts a distinct inﬂuence on the prediction of the 2-m temperature. This inﬂuence was found stronger during the nighttime than during the daytime, in plain areas than in mountain areas, in urban areas than in non-urban areas. In the nighttime of the urban areas, the inﬂuence on the simulated by the change is the addition, the model performance using a functional type Kzmin in the ACM2 scheme in capturing the spatiotemporal distribution of the temperature in this region was also compared with that using a constant Kzmin.