Clustering by fast search and find of Density Peaks (referred to as DPC) was introduced by Alex Rodríguez and Alessandro Laio. The DPC algorithm is based on the idea that cluster centers are ...characterized by having a higher density than their neighbors and by being at a relatively large distance from points with higher densities. The power of DPC was demonstrated on several test cases. It can intuitively find the number of clusters and can detect and exclude the outliers automatically, while recognizing the clusters regardless of their shape and the dimensions of the space containing them. However, DPC does have some drawbacks to be addressed before it may be widely applied. First, the local density ρi of point i is affected by the cutoff distance dc, and is computed in different ways depending on the size of datasets, which can influence the clustering, especially for small real-world cases. Second, the assignment strategy for the remaining points, after the density peaks (that is the cluster centers) have been found, can create a “Domino Effect”, whereby once one point is assigned erroneously, then there may be many more points subsequently mis-assigned. This is especially the case in real-word datasets where there could exist several clusters of arbitrary shape overlapping each other. To overcome these deficiencies, a robust clustering algorithm is proposed in this paper. To find the density peaks, this algorithm computes the local density ρi of point i relative to its K-nearest neighbors for any size dataset independent of the cutoff distance dc, and assigns the remaining points to the most probable clusters using two new point assignment strategies. The first strategy assigns non-outliers by undertaking a breadth first search of the K-nearest neighbors of a point starting from cluster centers. The second strategy assigns outliers and the points unassigned by the first assignment procedure using the technique of fuzzy weighted K-nearest neighbors. The proposed clustering algorithm is benchmarked on publicly available synthetic and real-world datasets which are commonly used for testing the performance of clustering algorithms. The clustering results of the proposed algorithm are compared not only with that of DPC but also with that of several well known clustering algorithms including Affinity Propagation (AP), Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and K-means. The benchmarks used are: clustering accuracy (Acc), Adjusted Mutual Information (AMI) and Adjusted Rand Index (ARI). The experimental results demonstrate that our proposed clustering algorithm can find cluster centers, recognize clusters regardless of their shape and dimension of the space in which they are embedded, be unaffected by outliers, and can often outperform DPC, AP, DBSCAN and K-means.
Abstract
Background
Characterizing the mutations selected by the integrase strand transfer inhibitor (INSTI) dolutegravir and their effects on susceptibility is essential for identifying viruses less ...likely to respond to dolutegravir therapy and for monitoring persons with virological failure (VF) on dolutegravir therapy.
Methods
We systematically reviewed dolutegravir resistance studies to identify mutations emerging under dolutegravir selection pressure, the effect of INSTI resistance mutations on in vitro dolutegravir susceptibility, and the virological efficacy of dolutegravir in antiretroviral-experienced persons.
Results and conclusions
We analysed 14 studies describing 84 in vitro passage experiments, 26 studies describing 63 persons developing VF plus INSTI resistance mutations on a dolutegravir-containing regimen, 41 studies describing dolutegravir susceptibility results, and 22 clinical trials and 16 cohort studies of dolutegravir-containing regimens. The most common INSTI resistance mutations in persons with VF on a dolutegravir-containing regimen were R263K, G118R, N155H and Q148H/R, with R263K and G118R predominating in previously INSTI-naive persons. R263K reduced dolutegravir susceptibility ∼2-fold. G118R generally reduced dolutegravir susceptibility >5-fold. The highest levels of reduced susceptibility occurred in viruses containing Q148 mutations in combination with G140 and/or E138 mutations. Dolutegravir two-drug regimens were highly effective for first-line therapy and for virologically suppressed persons provided dolutegravir’s companion drug was fully active. Dolutegravir three-drug regimens were highly effective for salvage therapy in INSTI-naive persons provided one or more of dolutegravir’s companion drugs was fully active. However, dolutegravir monotherapy in virologically suppressed persons and functional dolutegravir monotherapy in persons with active viral replication were associated with a non-trivial risk of VF plus INSTI resistance mutations.
Tenofovir and bone health Grant, Philip M; Cotter, Aoife G
Current opinion in HIV & AIDS
11, Številka:
3
Journal Article
Odprti dostop
With continued improvements to the antiviral efficacy and tolerability of antiretroviral therapy, long-term safety of antiretroviral therapy has become paramount. Low bone mineral density and ...fragility fractures are more common in HIV-infected individuals than in the general population. The aims of this review are to describe potential mechanisms underlying the adverse effects of tenofovir on bone, clinical studies of tenofovir disoproxil fumarate (TDF) and bone, and more recent bone data on tenofovir alafenamide.
Several studies have demonstrated an approximately 1-3% greater bone mineral density loss with TDF compared with other agents. Recent studies with tenofovir alafenamide have shown improved bone (and renal) safety with similar virologic efficacy when compared to TDF.
Given these findings, TDF-containing regimens may be gradually replaced with non-TDF containing regimens for the treatment of HIV infection, especially in those at higher risk for fragility fracture.
To tackle the challenges in genomic data analysis caused by their tens of thousands of dimensions while having a small number of examples and unbalanced examples between classes, the technique of ...unsupervised feature selection based on standard deviation and cosine similarity is proposed in this paper. We refer to this idea as SCFS (Standard deviation and Cosine similarity based Feature Selection). It defines the discernibility and independence of a feature to value its distinguishable capability between classes and its redundancy to other features, respectively. A 2-dimensional space is constructed using discernibility as x-axis and independence as y-axis to represent all features where the upper right corner features have both comparatively high discernibility and independence. The importance of a feature is defined as the product of its discernibility and its independence (i.e., the area of the rectangular enclosed by the feature’s coordinate lines and axes). The upper right corner features are by far the most important, comprising the optimal feature subset. Based on different definitions of independence using cosine similarity, there are three feature selection algorithms derived from SCFS. These are SCEFS (Standard deviation and Exponent Cosine similarity based Feature Selection), SCRFS (Standard deviation and Reciprocal Cosine similarity based Feature Selection) and SCAFS (Standard deviation and Anti-Cosine similarity based Feature Selection), respectively. The KNN and SVM classifiers are built based on the optimal feature subsets detected by these feature selection algorithms, respectively. The experimental results on 18 genomic datasets of cancers demonstrate that the proposed unsupervised feature selection algorithms SCEFS, SCRFS and SCAFS can detect the stable biomarkers with strong classification capability. This shows that the idea proposed in this paper is powerful. The functional analysis of these biomarkers show that the occurrence of the cancer is closely related to the biomarker gene regulation level. This fact will benefit cancer pathology research, drug development, early diagnosis, treatment and prevention.
BACKGROUNDElevated levels of inflammatory cytokines have been associated with poor outcomes among COVID-19 patients. It is unknown, however, how these levels compare with those observed in critically ...ill patients with acute respiratory distress syndrome (ARDS) or sepsis due to other causes.METHODSWe used a Luminex assay to determine expression of 76 cytokines from plasma of hospitalized COVID-19 patients and banked plasma samples from ARDS and sepsis patients. Our analysis focused on detecting statistical differences in levels of 6 cytokines associated with cytokine storm (IL-1β, IL-1RA, IL-6, IL-8, IL-18, and TNF-α) between patients with moderate COVID-19, severe COVID-19, and ARDS or sepsis.RESULTSFifteen hospitalized COVID-19 patients, 9 of whom were critically ill, were compared with critically ill patients with ARDS (n = 12) or sepsis (n = 16). There were no statistically significant differences in baseline levels of IL-1β, IL-1RA, IL-6, IL-8, IL-18, and TNF-α between patients with COVID-19 and critically ill controls with ARDS or sepsis.CONCLUSIONLevels of inflammatory cytokines were not higher in severe COVID-19 patients than in moderate COVID-19 or critically ill patients with ARDS or sepsis in this small cohort. Broad use of immunosuppressive therapies in ARDS has failed in numerous Phase 3 studies; use of these therapies in unselected patients with COVID-19 may be unwarranted.FUNDINGFunding was received from NHLBI K23 HL125663 (AJR); The Bill and Melinda Gates Foundation OPP1113682 (AJR and CAB); Burroughs Wellcome Fund Investigators in the Pathogenesis of Infectious Diseases #1016687 NIH/NIAID U19AI057229-16; Stanford Maternal Child Health Research Institute; and Chan Zuckerberg Biohub (CAB).
HIV-1 genotypic resistance test (GRT) interpretation systems (IS) require updates as new studies on HIV-1 drug resistance are published and as treatment guidelines evolve.
An expert panel was created ...to provide recommendations for the update of the Stanford HIV Drug Resistance Database (HIVDB) GRT-IS. The panel was polled on the ARVs to be included in a GRT report, and the drug-resistance interpretations associated with 160 drug-resistance mutation (DRM) pattern-ARV combinations. The DRM pattern-ARV combinations included 52 nucleoside RT inhibitor (NRTI) DRM pattern-ARV combinations (13 patterns x 4 NRTIs), 27 nonnucleoside RT inhibitor (NNRTI) DRM pattern-ARV combinations (9 patterns x 3 NNRTIs), 39 protease inhibitor (PI) DRM pattern-ARV combinations (13 patterns x 3 PIs) and 42 integrase strand transfer inhibitor (INSTI) DRM pattern-ARV combinations (14 patterns x 3 INSTIs).
There was universal agreement that a GRT report should include the NRTIs lamivudine, abacavir, zidovudine, emtricitabine, and tenofovir disoproxil fumarate; the NNRTIs efavirenz, etravirine, nevirapine, and rilpivirine; the PIs atazanavir/r, darunavir/r, and lopinavir/r (with "/r" indicating pharmacological boosting with ritonavir or cobicistat); and the INSTIs dolutegravir, elvitegravir, and raltegravir. There was a range of opinion as to whether the NRTIs stavudine and didanosine and the PIs nelfinavir, indinavir/r, saquinavir/r, fosamprenavir/r, and tipranavir/r should be included. The expert panel members provided highly concordant DRM pattern-ARV interpretations with only 6% of NRTI, 6% of NNRTI, 5% of PI, and 3% of INSTI individual expert interpretations differing from the expert panel median by more than one resistance level. The expert panel median differed from the HIVDB 7.0 GRT-IS for 20 (12.5%) of the 160 DRM pattern-ARV combinations including 12 NRTI, two NNRTI, and six INSTI pattern-ARV combinations. Eighteen of these differences were updated in HIVDB 8.1 GRT-IS to reflect the expert panel median. Additionally, HIVDB users are now provided with the option to exclude those ARVs not considered to be universally required.
The HIVDB GRT-IS was updated through a collaborative process to reflect changes in HIV drug resistance knowledge, treatment guidelines, and expert opinion. Such a process broadens consensus among experts and identifies areas requiring further study.
Immune reconstitution inflammatory syndrome (IRIS) is reported widely in patients initiating antiretroviral therapy (ART). However, few studies are prospective, and no study has evaluated the impact ...of the timing of ART when allocated randomly during an acute opportunistic infection (OI).
A5164 randomized 282 subjects with AIDS-related OIs (tuberculosis excluded), to early or deferred ART. IRIS was identified prospectively using pre-defined criteria. We evaluated associations between IRIS and baseline variables in subjects with follow-up on ART using Wilcoxon and Fisher's exact tests, logistic regression, and Cox models with time-varying covariates. Twenty of 262 (7.6%) subjects developed IRIS after a median of 33 days on ART. Subjects with fungal infections (other than pneumocystis) developed IRIS somewhat more frequently (OR = 2.7; 95% CI: 1.02, 7.2; p-value = 0.06 (using Fisher's exact test)). In Cox models, lower baseline and higher on-treatment CD4+ T-cell counts and percentage were associated with IRIS. Additionally, higher baseline and lower on-treatment HIV RNA levels were associated with IRIS. Corticosteroids during OI management and the timing of ART were not associated with the development of IRIS.
In patients with advanced immunosuppression and non-tuberculous OIs, the presence of a fungal infection, lower CD4+ T-cell counts and higher HIV RNA levels at baseline, and higher CD4+ T-cell counts and lower HIV RNA levels on treatment are associated with IRIS. Early initiation of ART does not increase the incidence of IRIS, and concern about IRIS should not prompt deferral of ART.
ClinicalTrials.gov NCT00055120.
•Self-tuning cutoff distance is proposed to extend DPC.•Optimal initial seeds and number of clusters determined simultaneously.•New dissimilarity measure is proposed calculating dissimilarities ...between objects.•Self-tuning k-modes clustering algorithm, referred to as DP-k-modes, is proposed.•DP-k-modes is superior to the compared ones and is significant different to them.
The k-modes clustering algorithm was proposed by Huang for handling datasets with categorical attributes, however, the dissimilarity measure used limits its applicability. Ng et al. improved on Huang’s k-modes algorithm by proposing a new dissimilarity measure between objects. Moreover, both k-modes algorithms require the initial seeds to be randomly chosen and the number of clusters be specified manually. To overcome the limitations of Huang’s and Ng’s k-modes clustering algorithms, we first extend the clustering algorithm published in Science in 2014 (“clustering by fast search and find of density peaks”). The optimal initial seeds and the number of clusters of a dataset are determined simultaneously by taking the standard deviation as the self-tuning cutoff distance and the simple match dissimilarity as the distance measurement in the definition of the density of a point. A new dissimilarity measure is proposed to calculate the dissimilarities between objects to improve on that of Ng’s k-modes algorithm. The performance of our resulting self-tuning k-modes clustering algorithm was tested on nine datasets (three being relatively large) from the UCI (University of California in Irvine) machine learning repository. The clustering results were compared to those produced by Huang’s and Ng’s algorithms. Statistical tests of three k-modes algorithms were undertaken to determine whether or not there is significant difference between our self-tuning k-modes algorithm and Huang’s and Ng’s k-modes algorithms. All these experimental results demonstrate that our proposed k-modes clustering algorithm is superior to Hang’s and Ng’s k-modes algorithms in terms of clustering accuracy (ACC) and the well-known Adjusted Rand Index (ARI) metric. Our self-tuning k-modes algorithm is significantly different from both Huang’s and Ng’s k-modes algorithms, and there is no statistically significant difference between Ng’s and Huang’s k-modes algorithms.
Antiretroviral therapy (ART) and oral pre-exposure prophylaxis (PrEP) are effective in reducing HIV transmission in heterosexual adults. The epidemiologic impact and cost-effectiveness of combined ...prevention approaches in resource-limited settings remain unclear.
We develop a dynamic mathematical model of the HIV epidemic in South Africa's adult population. We assume ART reduces HIV transmission by 95% and PrEP by 60%. We model two ART strategies: scaling up access for those with CD4 counts ≤ 350 cells/μL (Guidelines) and for all identified HIV-infected individuals (Universal). PrEP strategies include use in the general population (General) and in high-risk individuals (Focused). We consider strategies where ART, PrEP, or both are scaled up to 100% of remaining eligible individuals yearly. We measure infections averted, quality-adjusted life-years (QALYs) gained and incremental cost-effectiveness ratios over 20 years.
Scaling up ART to 50% of eligible individuals averts 1,513,000 infections over 20 years (Guidelines) and 3,591,000 infections (Universal). Universal ART is the most cost-effective strategy at any scale ($160-$220/QALY versus comparable scale Guidelines ART expansion). General PrEP is costly and provides limited benefits beyond ART scale-up ($7,680/QALY to add 100% PrEP to 50% Universal ART). Cost-effectiveness of General PrEP becomes less favorable when ART is widely given ($12,640/QALY gained when added to 100% Universal ART). If feasible, Focused PrEP is cost saving or highly cost effective versus status quo and when added to ART strategies.
Expanded ART coverage to individuals in early disease stages may be more cost-effective than current guidelines. PrEP can be cost-saving if delivered to individuals at increased risk of infection.
Fostemsavir is a recently Food and Drug Administration-approved HIV-1 attachment inhibitor that binds to HIV-1 gp120 and prevents viral attachment to the cellular CD4 receptor. Here, we review the ...pharmacology, efficacy, tolerability, and resistance profile of fostemsavir.
Fostemsavir is well tolerated and maintains virologic activity in individuals harboring multidrug-resistant HIV-1. In conjunction with optimal background therapy, a majority of heavily treatment-experienced clinical trial participants treated with fostemsavir achieved virologic suppression.
The approval of fostemsavir represents an important advance for individuals harboring multidrug resistant HIV-1 due to its novel mechanism of action and lack of cross-resistance to other antiretrovirals. Further study will better define the role of resistance testing for fostemsavir and fostemsavir's potential role outside of salvage therapy in heavily treatment-experienced individuals.
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