Impact of Latency Variations on the Predictive Value of Facial Nerve Proximal-to-Distal Amplitude Ratio during Vestibular Schwannoma Surgery.

Introduction This study highlights the relation between compound muscle action potential (CMAP) latency variations and the predictive value of facial nerve (FN) proximal-to-distal (P/D) amplitude ratio measured at the end of vestibular schwannoma resection. Methods Forty-eight patients underwent FN stimulation at the brainstem (proximal) and internal acoustic meatus (distal) using a current intensity of 2 mA. The proximal latency and the P/D amplitude ratio were assessed. House-Brackmann grades I & II indicated good FN function, and grades III to VI were considered fair/poor function. A P/D amplitude ratio > 0.6 was used as a cutoff to indicate a good FN function, while a ratio of ≤ 0.6 indicated a fair/poor FN function. Results The P/D amplitude ratio was measured for all patients, and the calculated sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) were 85.2, 85.7, 88.5, and 81.8%, respectively. The CMAPs from the mentalis muscle were then classified based on their proximal latency into group I (< 6 ms), group II (6-8 ms), and group III (> 8 ms). The SE, SP, PPV, and NPV became 90.5, 90.9, 95, and 83.3%, respectively, in group II. In group I, SE and NPV increased, whereas SP and PPV decreased. While in group III, SP and PPV increased, whereas SE and NPV decreased. Conclusion At a latency between 6 and 8 ms, the P/D amplitude ratio was predictive of outcomes with high SE and SP. When latency was < 6 ms or > 8 ms, the same predictive ability was not observed. Knowing the strengths and limitations is important for understanding the predictive value of the P/D amplitude ratio.

NoC simulation steered by NEST: McAERsim and a Noxim patch.

Introduction: Great knowledge was gained about the computational substrate of the brain, but the way in which components and entities interact to perform information processing still remains a secret. Complex and large-scale network models have been developed to unveil processes at the ensemble level taking place over a large range of timescales. They challenge any kind of simulation platform, so that efficient implementations need to be developed that gain from focusing on a set of relevant models. With increasing network sizes imposed by these models, low latency inter-node communication becomes a critical aspect. This situation is even accentuated, if slow processes like learning should be covered, that require faster than real-time simulation. Methods: Therefore, this article presents two simulation frameworks, in which network-on-chip simulators are interfaced with the neuroscientific development environment NEST. This combination yields network traffic that is directly defined by the relevant neural network models and used to steer the network-on-chip simulations. As one of the outcomes, instructive statistics on network latencies are obtained. Since time stamps of different granularity are used by the simulators, a conversion is required that can be exploited to emulate an intended acceleration factor. Results: By application of the frameworks to scaled versions of the cortical microcircuit model-selected because of its unique properties as well as challenging demands-performance curves, latency, and traffic distributions could be determined. Discussion: The distinct characteristic of the second framework is its tree-based source-address driven multicast support, which, in connection with the torus topology, always led to the best results. Although currently biased by some inherent assumptions of the network-on-chip simulators, the results suit well to those of previous work dealing with node internals and suggesting accelerated simulations to be in reach.

Advancing Toward a Human Immunodeficiency Virus Cure: Initial Progress on a Difficult Path.

Therapies to eradicate human immunodeficiency virus (HIV) infection, sparing lifelong antiviral therapy, are a still-distant goal. But significant advances have been made to reverse HIV latency while antiretroviral therapy (ART) is maintained to allow targeting of the persistent viral reservoir, to test interventions that could clear cells emerging from latent infection, and to improve HIV cure research assays and infrastructure. Steady progress gives hope that future therapies to clear HIV infection may relieve individuals and society of the burden of HIV.

Incremental RBF-based cross-tier interference mitigation for resource-constrained dense IoT networks in 5G communication system.

The deployment of resource-constrained and densely distributed Internet of Things (IoT) devices poses significant challenges for 5G communication systems due to the increased likelihood of inter-tier interference. This interference can degrade network performance and hinder the transmission of data in a reliable and efficient manner. Using an incremental Radial Basis Function (RBF) technique, this paper proposes a novel approach for cross-tier interference mitigation in 5G communication among resource-constrained dense IoT networks. Utilizing the incremental RBF method to model and optimize interference patterns in resource-constrained dense IoT networks is the primary innovation of our approach. In contrast to conventional interference mitigation techniques, which view interference as a static phenomenon, our method adapts to the dynamic nature of IoT networks by incrementally updating the RBF model. This enables precise modeling of the various interference scenarios and real-time modification of interference mitigation parameters. Utilizing the spatial distribution of IoT devices, this approach improves interference mitigation. The proposed method intelligently allocates resources and optimizes interference mitigation parameters based on the location and density of IoT devices. This adaptive resource allocation improves network capacity, reliability, and overall system performance by maximizing the utilization of available resources while minimizing interference. We demonstrate the effectiveness of the incremental RBF-based approach in mitigating cross-tier interference in resource-constrained dense IoT networks within the 5G ecosystem through extensive experiments and simulations. Our findings indicate substantial improvements in communication performance, including increased throughput, decreased packet loss, and decreased latency.

Aging and sex are associated with multiple sleep latency test findings and their relationship with self-reported sleepiness.

The aim of this study was to assess age- and sex-related differences in multiple sleep latency test (MSLT) results and in the performance of the Epworth Sleepiness Scale (ESS) at classifying objective hypersomnia (mean sleep latency (MSL) ≤ 8 min). We studied 480 consecutive adults (39.3 ± 15.3 years old [18-93], 67.7% female) who underwent hypersomnia evaluation. We fit linear regression models to investigate associations between age and sex and sleep latencies (mean and for every nap), after adjusting for total sleep time and sleep efficiency (on polysomnography), and REM-suppressing antidepressant effect. A logistic regression was performed to assess whether age and sex were associated with sleep-onset REM period (SOREMP) occurrence. ROC analysis assessed the diagnostic performance of ESS scores to identify a MSL ≤ 8 min in different age/sex groups. For every 10 years of age, there was 0.41 (95% CI 0.11-0.72, p = 0.008) min reduction in MSL. Objectively (MSL ≤ 8 min) sleepy patients had shortening of latencies in naps 4 and 5 with aging. Female sex was associated with a higher MSL only in patients with MSL > 8 min. A 2.4% reduction in the odds of SOREMP occurrence was observed for every year of age in objectively sleepy patients (p = 0.045). ESS scores had a better diagnostic performance in older (≥ 50 years old) men than younger (< 50 years old) women (p < 0.05). Older patients with objectively confirmed hypersomnia may be sleepier in later naps, possibly due to less restorative naps and/or circadian rhythm factors. Self-reported sleepiness is more predictive of objective sleepiness in older men than younger women.

5G-enabled UAVs for energy-efficient opportunistic networking.

The article explores the potential of 5G-enabled Unmanned Aerial Vehicles (UAVs) in establishing opportunistic networks to improve network resource management, reduce energy use, and boost operational efficiency. The proposed framework utilizes 5G-enabled drones and edge command and control software to provide energy-efficient network topologies. As a result, UAVs operate edge computing for efficient data collecting and processing. This invention enhances network performance using modern Artificial Intelligence (AI) algorithms to improve UAV networking capabilities while conserving energy. An empirical investigation shows a significant improvement in network performance measures when using 5G technology compared to older 2.4 GHz systems. The communication failure rate decreased by 50 %, from 12 % to 6 %. The round-trip time was lowered by 58.3 %, from 120 Ms to 50 Ms. The payload efficiency improved by 13.3 %, dropping from 15 % to 13 %. The data transmission rate increased significantly from 1 Gbps to 5 Gbps, representing a 400 % boost. The numerical findings highlight the significant impact that 5G technology may have on UAV operations. Testing on a 5G-enabled UAV confirms the effectiveness of our technique in several domains, including precision agriculture, disaster response, and environmental monitoring. The solution seriously improves UAV network performance by reducing energy consumption and using peripheral network command-and-control software. Our results emphasize the versatile networking capacities of 5G-enabled drones, which provide new opportunities for UAV applications.

Utility of Visual Evoked Potentials (VEPs) study in the evaluation of visual pathway dysfunction in diabetics without retinopathy: correlations with diabetic peripheral neuropathy and other clinical findings.

Aim and objectives: Visual dysfunction in diabetes mellitus (DM) is multifactorial and can be due to vascular disease, and metabolic abnormalities that can affect the retina, optic nerve, and visual pathways. Visual evoked potential (VEP) is an electrophysiological test that can quantify the functional integrity of the visual pathways from the retina via the optic nerves, and optic tracts to the visual cortices. In this study, we aimed to investigate the visual pathway dysfunction among diabetics without retinopathy compared with healthy controls and to look for any correlation with diabetic neuropathy, duration of diabetes, or HbA1c level. Methods: The study included 75 diabetic patients and 75 age and sex-matched controls. VEPs were recorded using the pattern reversal stimulation method on the Medtronic EMG EP machine, and P100 latency and N75-P100 amplitude were recorded in both diabetic patients and healthy controls. Results: Mean P100 latency was significantly prolonged and N75-P100 amplitude significantly reduced among diabetic cases compared to healthy controls (p < 0.001). Among diabetics with peripheral neuropathy, P100 latency was significantly prolonged and N75-P100 amplitude was significantly reduced compared to diabetics without peripheral neuropathy. A significant positive correlation of VEP P100 latency (p < 0.001) and a negative correlation with N75-P100 amplitude (p < 0.001) with duration of disease were also found. Conclusion: VEP changes are observed in diabetics before the development of retinopathy or peripheral neuropathy indicating optic pathway dysfunction, which precedes the development of these complications. Early preclinical visual pathway dysfunction can warrant taking the necessary measures to reduce diabetic complications. Abbreviations: DM = Diabetes Mellitus, VEP = Visual Evoked Potential, HbA1c = Hemoglobin A1 c, MRI = Magnetic Resonance Imaging, EEG = Electroencephalography, P100 = Positive wave peak at latency 100 ms (millisecond), N75 = Negative wave peak at latency 75 ms (millisecond), N145 = Negative wave peak at latency 145 ms (millisecond), OCT = Optical coherence tomography, PRVEP = Pattern Reversal Visual Evoked Potential, NCS = Nerve Conduction Study, SSR = Sympathetic Skin Response, IL1 = Interleukin-1, LIF = Leukemia inhibitory factor, CNTF = Ciliary neurotrophic factor, TNF alpha = Tumor necrosis factor-alpha, TGF-beta = Transforming growth factor-beta.

Advances in the immunoescape mechanisms exploited by alphaherpesviruses.

Alphaherpesviruses, categorized as viruses with linear DNA composed of two complementary strands, can potentially to induce diseases in both humans and animals as pathogens. Mature viral particles comprise of a core, capsid, tegument, and envelope. While herpesvirus infection can elicit robust immune and inflammatory reactions in the host, its persistence stems from its prolonged interaction with the host, fostering a diverse array of immunoescape mechanisms. In recent years, significant advancements have been achieved in comprehending the immunoescape tactics employed by alphaherpesviruses, including pseudorabies virus (PRV), herpes simplex virus (HSV), varicella-zoster virus (VZV), feline herpesvirus (FeHV), equine herpesvirus (EHV), and caprine herpesvirus type I (CpHV-1). Researchers have unveiled the intricate adaptive mechanisms existing between viruses and their natural hosts. This review endeavors to illuminate the research advancements concerning the immunoescape mechanisms of alphaherpesviruses by delineating the pertinent proteins and genes involved in virus immunity. It aims to furnish valuable insights for further research on related mechanisms and vaccine development, ultimately contributing to virus control and containment efforts.

Outpatient versus inpatient management of preterm prelabor rupture of membranes: A systematic review and meta-analysis.

INTRODUCTION: To compare neonatal, obstetrical, and maternal outcomes associated with outpatient versus inpatient management of pregnancies with preterm prelabor rupture of membranes (PPROM). MATERIAL AND METHODS: A search of MEDLINE, EMBASE, the Cochrane Database and Central Register from January 1, 1990 to July 31, 2023 identified randomized controlled trials (RCTs) and cohort studies comparing outpatient with inpatient management for pregnant persons diagnosed with PPROM before 37 weeks' gestation. No language restriction was applied. We applied a random effects model for meta-analysis. Trustworthiness was assessed using recently published guidance and Risk of bias using the RoB 2.0 tool for RCTs and ROBINS-I tool for cohort studies. The Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach was used to assess the certainty of evidence (COE). Outcomes of interest included perinatal mortality, neonatal morbidities, latency and gestational age at delivery, and maternal morbidities. RCTs and cohort studies were analyzed separately. This study was registered in the International Prospective Register of Systematic Reviewsr: CRD42022295275. RESULTS: From 2825 records, two RCTs and 10 cohort studies involving 1876 patients were included in the review and meta-analysis. Outpatient management protocols varied but generally included brief initial hospitalization, strict eligibility criteria, and surveillance with laboratory and ultrasound investigations. Outpatient management showed lower rates of neonatal respiratory distress syndrome (cohort: RR 0.63 [0.52-0.77, very low COE]), longer latency to delivery (RCT: MD 7.43 days [1.14-13.72 days, moderate COE], cohort: MD 8.78 days [2.29-15.26 days, low COE]), higher gestational age at birth (cohort: MD 7.70 days [2.02-13.38 days, low COE]), lower rates of Apgar scores <7 at 5 min of life (cohort: RR 0.66 [0.50-0.89, very low COE]), and lower rates of histological chorioamnionitis (cohort: RR 0.74 [0.62-0.89, low COE]) without increased risks of adverse neonatal, obstetrical, or maternal outcomes. CONCLUSIONS: Meta-analysis of data from RCTs and cohort studies with very low-to-moderate certainty of evidence indicates that further high-quality research is needed to evaluate the safety and potential benefits of outpatient management for selected PPROM cases, given the moderate-to-high risk of bias in the included studies.

Novel biomarkers derived from the Maintenance of Wakefulness Test as predictors of sleepiness and response to treatment.

The Maintenance of Wakefulness Test (MWT) is a widely accepted objective test used to evaluate daytime somnolence and is commonly used in clinical studies evaluating novel therapeutics for excessive daytime sleepiness. In the latter, sleep onset latency (SOL) is typically the sole MWT endpoint. Here, we explored microsleeps, sleep probability measures derived from automated sleep scoring, and quantitative electroencephalography (qEEG) features as additional MWT biomarkers of daytime sleepiness, using data from a phase 1B trial of the selective orexin receptor 2 agonist danavorexton (TAK-925) in people with narcolepsy type 1 (NT1) or type 2 (NT2). Danavorexton treatment reduced the rate and duration of microsleeps during the MWT in NT1 (days 1 and 7; p ≤ 0.005) and microsleep rate in NT2 (days 1 and 7; p < 0.0001). Use of an EEG-sleep-staging-derived measure to determine the probability of wakefulness for each minute revealed a novel metric to track changes in daytime sleepiness, which were consistent with the θ/α ratio, a known biomarker of drowsiness. The slopes of line-fits to both the log-transformed sleepiness score or log-transformed θ/α ratio correlated well to (inverse) MWT SOL for NT1 (R = 0.93 and R = 0.83, respectively) and NT2 (R = 0.97 and R = 0.84, respectively), suggesting that individuals with narcolepsy have increased sleepiness immediately after lights-off. These analyses demonstrate that novel EEG-based biomarkers can augment SOL as predictors of sleepiness and its response to treatment and provide a novel framework for the analysis of wake EEG in hypersomnia disorders.

A green and simple method for enrichment of major diterpenoids from the buds of Wikstroemia chamaedaphne with macroporous resins and their activation of latent human immunodeficiency virus activity.

In this study, a green and efficient enrichment method for the four majors active diterpenoid components: pimelotide C, pimelotide A, simplexin, and 6α,7α-epoxy-5ß-hydroxy-12-deoxyphorbol-13-decanoate in the buds of Wikstroemia chamaedaphne was established using macroporous resin chromatography. The adsorption and desorption rates of seven macroporous resins were compared using static tests. The D101 macroporous resin exhibited the best performance. Static and dynamic adsorption tests were performed to determine the enrichment and purification of important bioactive diterpenoids in the buds of W. chamaedaphne. Diterpenoid extracts were obtained by using D101 macroporous resin from the crude extracts of W. chamaedaphne. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis demonstrated that most of the diterpenoids were enriched in diterpenoid extracts. These results confirmed that diterpenoids in the buds of W. chamaedaphne could be enriched using macroporous resin technology, and the enriched diterpenoid extracts showed more efficient activation of the latent human immunodeficiency virus. This study provides a novel strategy for discovering efficient and low-toxicity latency-reversing agents and a potential basis for the comprehensive development and clinical application of the buds of W. chamaedaphne.

Mice learn to identify and discriminate sugar solutions based on odor cues.

This study examined how olfaction impacts ingestive responses of mice to sugar solutions. Experiment 1 asked whether naïve C57BL/6 (B6) mice could identify 1 M glucose, fructose, or sucrose solutions based on odor cues, during a 30-min 2-bottle acceptability test. We tested mice both before and after they were rendered anosmic with ZnSO4 treatment. We used 2 indirect measures of odor-mediated response: number of trials initiated and latency to initiate licking. Before ZnSO4 treatment, the mice learned how to identify 1 M glucose and fructose (but not sucrose) solutions based on odor cues. ZnSO4 treatment eliminated their ability to identify the glucose and fructose solutions. Experiment 2 asked whether 2 d of exposure to a 1 M glucose, fructose, or sucrose solution improved the identification of the same sugar solution. Following exposure, the B6 mice identified all 3 sugar solutions based on odor cues. Experiment 3 asked whether T1R3 knockout mice (i.e. mice lacking the T1R3 subunit of the T1R2 + R3 sweet taste receptor) could learn to discriminate 0.44 M glucose and fructose solutions based on odor cues. All mice were subjected to a 1-h preference test, both before and after exposure to the 0.44 M glucose and fructose solutions. During exposure, the experimental mice received ZnSO4 treatment, whereas the control mice received saline treatment. Before exposure, neither type of mouse preferred the glucose solution. After exposure, the control mice preferred the glucose solution, whereas the experimental mice did not. Our results reveal that mice can learn to use odor cues to identify and discriminate between sugar solutions.

cGAS-STING-TBK1 Signaling Promotes Valproic Acid-Responsive Human Cytomegalovirus Immediate-Early Transcription during Infection of Incompletely Differentiated Myeloid Cells.

Repression of human cytomegalovirus (HCMV) immediate-early (IE) gene expression is a key regulatory step in the establishment and maintenance of latent reservoirs. Viral IE transcription and protein accumulation can be elevated during latency by treatment with histone deacetylase inhibitors such as valproic acid (VPA), rendering infected cells visible to adaptive immune responses. However, the latency-associated viral protein UL138 inhibits the ability of VPA to enhance IE gene expression during infection of incompletely differentiated myeloid cells that support latency. UL138 also limits the accumulation of IFNß transcripts by inhibiting the cGAS-STING-TBK1 DNA-sensing pathway. Here, we show that, in the absence of UL138, the cGAS-STING-TBK1 pathway promotes both IFNß accumulation and VPA-responsive IE gene expression in incompletely differentiated myeloid cells. Inactivation of this pathway by either genetic or pharmacological inhibition phenocopied UL138 expression and reduced VPA-responsive IE transcript and protein accumulation. This work reveals a link between cytoplasmic pathogen sensing and epigenetic control of viral lytic phase transcription and suggests that manipulation of pattern recognition receptor signaling pathways could aid in the refinement of MIEP regulatory strategies to target latent viral reservoirs.

The HIV-1 Transcriptional Program: From Initiation to Elongation Control.

A large body of work in the last four decades has revealed the key pillars of HIV-1 transcription control at the initiation and elongation steps. Here, I provide a recount of this collective knowledge starting with the genomic elements (DNA and nascent TAR RNA stem-loop) and transcription factors (cellular and the viral transactivator Tat), and later transitioning to the assembly and regulation of transcription initiation and elongation complexes, and the role of chromatin structure. Compelling evidence support a core HIV-1 transcriptional program regulated by the sequential and concerted action of cellular transcription factors and Tat to promote initiation and sustain elongation, highlighting the efficiency of a small virus to take over its host to produce the high levels of transcription required for viral replication. I summarize new advances including the use of CRISPR-Cas9, genetic tools for acute factor depletion, and imaging to study transcriptional dynamics, bursting and the progression through the multiple phases of the transcriptional cycle. Finally, I describe current challenges to future major advances and discuss areas that deserve more attention to both bolster our basic knowledge of the core HIV-1 transcriptional program and open up new therapeutic opportunities.

KDM5A/B contribute to HIV-1 latent infection and survival of HIV-1 infected cells.

Combinational antiretroviral therapy (cART) suppresses human immunodeficiency virus type 1 (HIV-1) viral replication and pathogenesis in acquired immunodeficiency syndrome (AIDS) patients. However, HIV-1 remains in the latent stage of infection by suppressing viral transcription, which hinders an HIV-1 cure. One approach for an HIV-1 cure is the "shock and kill" strategy. The strategy focuses on reactivating latent HIV-1, inducing the viral cytopathic effect and facilitating the immune clearance for the elimination of latent HIV-1 reservoirs. Here, we reported that the H3K4 trimethylation (H3K4me3)-specific demethylase KDM5A/B play a role in suppressing HIV-1 Tat/LTR-mediated viral transcription in HIV-1 latent cells. Furthermore, we evaluated the potential of KDM5-specific inhibitor JQKD82 as an HIV-1 "shock and kill" agent. Our results showed that JQKD82 increases the H3K4me3 level at HIV-1 5' LTR promoter regions, HIV-1 reactivation, and the cytopathic effects in an HIV-1-latent T cell model. In addition, we identified that the combination of JQKD82 and AZD5582, a non-canonical NF-κB activator, generates a synergistic impact on inducing HIV-1 lytic reactivation and cell death in the T cell. The latency-reversing potency of the JQKD82 and AZD5582 pair was also confirmed in peripheral blood mononuclear cells (PBMCs) isolated from HIV-1 aviremic patients and in an HIV-1 latent monocyte. In latently infected microglia (HC69) of the brain, either deletion or inhibition of KDM5A/B results in a reversal of the HIV-1 latency. Overall, we concluded that KDM5A/B function as a host repressor of the HIV-1 lytic reactivation and thus promote the latency and the survival of HIV-1 infected reservoirs.

Network Latency in Teleoperation of Connected and Autonomous Vehicles: A Review of Trends, Challenges, and Mitigation Strategies.

With remarkable advancements in the development of connected and autonomous vehicles (CAVs), the integration of teleoperation has become crucial for improving safety and operational efficiency. However, teleoperation faces substantial challenges, with network latency being a critical factor influencing its performance. This survey paper explores the impact of network latency along with state-of-the-art mitigation/compensation approaches. It examines cascading effects on teleoperation communication links (i.e., uplink and downlink) and how delays in data transmission affect the real-time perception and decision-making of operators. By elucidating the challenges and available mitigation strategies, the paper offers valuable insights for researchers, engineers, and practitioners working towards the seamless integration of teleoperation in the evolving landscape of CAVs.

Navigating latency hurdles: an in-depth examination of a cloud-powered GNSS real-time positioning application on mobile devices.

A growing dependence on real-time positioning apps for navigation, safety, and location-based services necessitates a deep understanding of latency challenges within cloud-based Global Navigation Satellite System (GNSS) solutions. This study analyses a GNSS real-time positioning app on smartphones that utilizes cloud computing for positioning data delivery. The study investigates and quantifies diverse latency contributors throughout the system architecture, including GNSS signal acquisition, data transmission, cloud processing, and result dissemination. Controlled experiments and real-world scenarios are employed to assess the influence of network conditions, device capabilities, and cloud server load on overall positioning latency. Findings highlight system bottlenecks and their relative contributions to latency. Additionally, practical recommendations are presented for developers and cloud service providers to mitigate these challenges and guarantee an optimal user experience for real-time positioning applications. This study not only elucidates the complex interplay of factors affecting GNSS app latency, but also paves the way for future advancements in cloud-based positioning solutions, ensuring the accuracy and timeliness critical for safety-critical and emerging applications.

[Latent Macrophage and Immature B Cell Lines Generated with Hygromycin-Resistant Murine Gammaherpesvirus 68 Genome Expresses Modest Levels of Viral miRNAs].

Murine gammaherpesvirus 68 (MHV68) establishes latency mainly in B cells and causes lymphomas reminiscent of human gammaherpesvirus diseases in laboratory mice. To study the molecular mechanism of virus infection and how the viral determinants control cell and eventually cause tumorigenesis, readily available latently infected cell lines are essential. For in vitro MHV68 latency studies, only two cell culture systems have been available. Gammaherpesviruses are known to infect developing B cells and macrophages, therefore we aimed to expand the MHV68 latently infected cell line repertoire. Here, several latently infected immature B cell and macrophage-like cell line clones were generated. Hygromycin-resistant recombinant MHV68 was isolated from a laboratory-made latent cell line, HE2.1, and propagated to develop stable cell lines that carry the viral genome under hygromycin selection. Subclones of these cells lines were analyzed for viral miRNA expression by TaqMan qPCR and assessed for expression of a lytic viral transcript M3. The cell lines maintain the viral genome as an episome shown by the digestion-circularization PCR assay. Latently infected cell lines generated here do not express viral miRNAs higher than the parental cell line. However, these cell lines may provide an alternative tool to study latency mechanisms and miRNA target identification studies.

Integrated Single-cell Multiomic Analysis of HIV Latency Reversal Reveals Novel Regulators of Viral Reactivation.

Despite the success of antiretroviral therapy, human immunodeficiency virus (HIV) cannot be cured because of a reservoir of latently infected cells that evades therapy. To understand the mechanisms of HIV latency, we employed an integrated single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq) approach to simultaneously profile the transcriptomic and epigenomic characteristics of ∼ 125,000 latently infected primary CD4+ T cells after reactivation using three different latency reversing agents. Differentially expressed genes and differentially accessible motifs were used to examine transcriptional pathways and transcription factor (TF) activities across the cell population. We identified cellular transcripts and TFs whose expression/activity was correlated with viral reactivation and demonstrated that a machine learning model trained on these data was 75%-79% accurate at predicting viral reactivation. Finally, we validated the role of two candidate HIV-regulating factors, FOXP1 and GATA3, in viral transcription. These data demonstrate the power of integrated multimodal single-cell analysis to uncover novel relationships between host cell factors and HIV latency.