The evolution of HIV-1 entry phenotypes as a guide to changing target cells

Through a twist of fate the most common form of HIV-1, as defined by entry phenotype, was not appreciated until recently. The entry phenotype is closely linked to the target cell and thus to virus–host interactions and pathogenesis. The most abundant form of HIV-1 uses CCR5 as the coreceptor and requires a high density of CD4 for efficient entry, defining its target cell as the CD4+ memory T cell. This is the transmitted form of the virus, the form that is found in the blood, and the form that rebounds from the latent reservoir. When CD4+/CCR5+ T cells become limiting the virus evolves to use alternative target cells to support viral replication. In the CNS, the virus can evolve to use a cell that displays only a low density of CD4, while maintaining the use of CCR5 as the coreceptor. When this evolutionary variant evolves, it must be sustaining its replication in either macrophages or microglial cells, which display only a low density of CD4 relative to that on T cells. In the blood and lymphoid system, the major switch late in disease is from T cells expressing CD4 and CCR5 to T cells expressing CD4 and CXCR4, with a change in coreceptor specificity. Thus the virus responds in two different ways to different environments when its preferred target cell becomes limiting. ©2018 The Authors. Society for Leukocyte Biology Published by Wiley Periodicals, Inc

Understanding the functions of kinesin-II

AbstractSpecies ranging from Chlamydomonas to humans possess the heterotrimeric kinesin-II holoenzyme composed of two different motor subunits and one non-motor accessory subunit. An important function of kinesin-II is that it transports the components needed for the construction and maintenance of cilia and flagella from the site of synthesis in the cell body to the site of growth at the distal tip. Recent work suggests that kinesin-II does not directly interact with these components, but rather via a large protein complex, which has been termed a raft (intraflagellar transport (IFT)). While ciliary transport is the best-established function for kinesin-II, evidence has been reported for possible roles in neuronal transport, melanosome transport, the secretory pathway and during mitosis

Ensemble machine learning for Monkeypox transmission time series forecasting

Public health is now in danger because of the current monkeypox outbreak, which has spread rapidly to more than 40 countries outside of Africa. The growing monkeypox epidemic has been classified as a “public health emergency of international concern” (PHEIC) by the World Health Organization (WHO). Infection outcomes, risk factors, clinical presentation, and transmission are all poorly understood. Computer- and machine-learning-assisted prediction and forecasting will be useful for controlling its spread. The objective of this research is to use the historical data of all reported human monkey pox cases to predict the transmission rate of the disease. This paper proposed stacking ensemble learning and machine learning techniques to forecast the rate of transmission of monkeypox. In this work, adaptive boosting regression (Adaboost), gradient boosting regression (GBOOST), random forest regression (RFR), ordinary least square regression (OLS), least absolute shrinkage selection operator regression (LASSO), and ridge regression (RIDGE) were applied for time series forecasting of monkeypox transmission. Performance metrics considered in this study are root mean square (RMSE), mean absolute error (MAE), and mean square error (MSE), which were used to evaluate the performance of the machine learning and the proposed Stacking Ensemble Learning (SEL) technique. Additionally, the monkey pox dataset was used as test data for this investigation. Experimental results revealed that SEL outperformed other machine learning approaches considered in this work with an RMSE of 33.1075; a MSE of 1096.1068; and a MAE of 22.4214. This is an indication that SEL is a better predictor than all the other models used in this study. It is hoped that this research will help government officials understand the threat of monkey pox and take the necessary mitigation actions

Maximum thick paths in static and dynamic environments

AbstractWe consider the problem of finding a large number of disjoint paths for unit disks moving amidst static or dynamic obstacles. The problem is motivated by the capacity estimation problem in air traffic management, in which one must determine how many aircraft can safely move through a domain while avoiding each other and avoiding “no-fly zones” and predicted weather hazards. For the static case we give efficient exact algorithms, based on adapting the “continuous uppermost path” paradigm. As a by-product, we establish a continuous analogue of Menger's Theorem.Next we study the dynamic problem in which the obstacles may move, appear and disappear, and otherwise change with time in a known manner; in addition, the disks are required to enter/exit the domain during prescribed time intervals. Deciding the existence of just one path, even for a 0-radius disk, moving with bounded speed is NP-hard, as shown by Canny and Reif [J. Canny, J.H. Reif, New lower bound techniques for robot motion planning problems, in: Proc. 28th Annu. IEEE Sympos. Found. Comput. Sci., 1987, pp. 49–60]. Moreover, we observe that determining the existence of a given number of paths is hard even if the obstacles are static, and only the entry/exit time intervals are specified for the disks. This motivates studying “dual” approximations, compromising on the radius of the disks and on the maximum speed of motion.Our main result is a pseudopolynomial-time dual-approximation algorithm. If K unit disks, each moving with speed at most 1, can be routed through an environment, our algorithm finds (at least) K paths for disks of radius somewhat smaller than 1 moving with speed somewhat larger than 1

Cooperative Learning for Distributed In-Network Traffic Classification

Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative  learning  algorithm  for  propagation and  synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification

The HIV/SIV Envelope Protein: From Structure To Function To Host Evasion

It is a pleasure to write an introduction for this collection of five short reviews of primate lentivirus Env proteins. These are very timely reviews, each designed to cover a different aspect of the biology of these proteins. This is a remarkable time to organize what we know about this family of proteins. There has been a long-standing interest in these proteins for their role in viral entry. The Env protein is the only viral protein on the surface of the virion making it the sole protein involved in entry. The synthesis of the Env protein is somewhat unremarkable, being a typical type 1 transmembrane protein synthesized as a large precursor on the rough ER. There is the co-translational addition of carbohydrate within the ER and trimerization of the Env protein precursor. Then in the golgi, a host protease cleaves the larger precursor into an extracellular surface protein (SU subunit) and a transmembrane protein (TM subunit), creating a new N terminus of the TM protein that functions as the fusion peptide in the fusion event. Despite this cleavage event, the SU and TM proteins remain together, with three of each subunit comprising an Env trimer

The Lazy Bureaucrat Scheduling Problem

We introduce a new class of scheduling problems in which the optimization is performed by the worker (single ``machine'') who performs the tasks. A typical worker's objective is to minimize the amount of work he does (he is ``lazy''), or more generally, to schedule as inefficiently (in some sense) as possible. The worker is subject to the constraint that he must be busy when there is work that he can do; we make this notion precise both in the preemptive and nonpreemptive settings. The resulting class of ``perverse'' scheduling problems, which we denote ``Lazy Bureaucrat Problems,'' gives rise to a rich set of new questions that explore the distinction between maximization and minimization in computing optimal schedules.Comment: 19 pages, 2 figures, Latex. To appear, Information and Computatio

Blocking formation of the stable HIV reservoir: A new perspective for HIV-1 cure

Recent studies demonstrate that the stable HIV-1 reservoir in resting CD4+ T cells is mostly formed from viruses circulating when combination antiretroviral therapy (ART) is initiated. Here we explore the immunological basis for these observations. Untreated HIV-1 infection is characterized by a progressive depletion of memory CD4+ T cells which mostly express CD127, the α chain of the IL-7 receptor (IL-7R). Depletion results from both direct infection and bystander loss of memory CD4+ T cells in part attributed to dysregulated IL-7/IL-7R signaling. While IL-7/IL7R signaling is not essential for the generation of effector CD4+ T cells from naïve cells, it is essential for the further transition of effectors to memory CD4+ T cells and their subsequent homeostatic maintenance. HIV-1 infection therefore limits the transition of CD4+ T cells from an effector to long-lived memory state. With the onset of ART, virus load (VL) levels rapidly decrease and the frequency of CD127+ CD4+ memory T cells increases, indicating restoration of effector to memory transition in CD4+ T cells. Collectively these data suggest that following ART initiation, HIV-1 infected effector CD4+ T cells transition to long-lived, CD127+ CD4+ T cells forming the majority of the stable HIV-1 reservoir. We propose that combining ART initiation with inhibition of IL-7/IL-7R signaling to block CD4+ T cell memory formation will limit the generation of long-lived HIV-infected CD4+ T cells and reduce the overall size of the stable HIV-1 reservoir. © 2019 Goonetilleke, Clutton, Swanstrom and Joseph

Genetic Evidence for Selective Transport of Opsin and Arrestin by Kinesin-II in Mammalian Photoreceptors

AbstractTo test whether kinesin-II is important for transport in the mammalian photoreceptor cilium, and to identify its potential cargoes, we used Cre-loxP mutagenesis to remove the kinesin-II subunit, KIF3A, specifically from photoreceptors. Complete loss of KIF3A caused large accumulations of opsin, arrestin, and membranes within the photoreceptor inner segment, while the localization of α-transducin was unaffected. Other membrane, organelle, and transport markers, as well as opsin processing appeared normal. Loss of KIF3A ultimately caused apoptotic photoreceptor cell death similar to a known opsin transport mutant. The data suggest that kinesin-II is required to transport opsin and arrestin from the inner to the outer segment and that blocks in this transport pathway lead to photoreceptor cell death as found in retinitis pigmentosa