A framework for generalized group testing with inhibitors and its potential application in neuroscience

The main goal of group testing with inhibitors (GTI) is to efficiently identify a small number of defective items and inhibitor items in a large set of items. A test on a subset of items is positive if the subset satisfies some specific properties. Inhibitor items cancel the effects of defective items, which often make the outcome of a test containing defective items negative. Different GTI models can be formulated by considering how specific properties have different cancellation effects. This work introduces generalized GTI (GGTI) in which a new type of items is added, i.e., hybrid items. A hybrid item plays the roles of both defectives items and inhibitor items. Since the number of instances of GGTI is large (more than 7 million), we introduce a framework for classifying all types of items non-adaptively, i.e., all tests are designed in advance. We then explain how GGTI can be used to classify neurons in neuroscience. Finally, we show how to realize our proposed scheme in practice

Learning Immune-Defectives Graph through Group Tests

This paper deals with an abstraction of a unified problem of drug discovery and pathogen identification. Pathogen identification involves identification of disease-causing biomolecules. Drug discovery involves finding chemical compounds, called lead compounds, that bind to pathogenic proteins and eventually inhibit the function of the protein. In this paper, the lead compounds are abstracted as inhibitors, pathogenic proteins as defectives, and the mixture of "ineffective" chemical compounds and non-pathogenic proteins as normal items. A defective could be immune to the presence of an inhibitor in a test. So, a test containing a defective is positive iff it does not contain its "associated" inhibitor. The goal of this paper is to identify the defectives, inhibitors, and their "associations" with high probability, or in other words, learn the Immune Defectives Graph (IDG) efficiently through group tests. We propose a probabilistic non-adaptive pooling design, a probabilistic two-stage adaptive pooling design and decoding algorithms for learning the IDG. For the two-stage adaptive-pooling design, we show that the sample complexity of the number of tests required to guarantee recovery of the inhibitors, defectives, and their associations with high probability, i.e., the upper bound, exceeds the proposed lower bound by a logarithmic multiplicative factor in the number of items. For the non-adaptive pooling design too, we show that the upper bound exceeds the proposed lower bound by at most a logarithmic multiplicative factor in the number of items.Comment: Double column, 17 pages. Updated with tighter lower bounds and other minor edit

Low lopinavir plasma or hair concentrations explain second-line protease inhibitor failures in a resource-limited setting.

In resource-limited settings, many patients, with no prior protease inhibitor (PI) treatment on a second-line, high genetic barrier, ritonavir-boosted PI-containing regimen have virologic failure

Diagnosis and management of antiretroviral-therapy failure in resource-limited settings in sub-Saharan Africa: challenges and perspectives.

Despite the enormous progress made in scaling up antiretroviral therapy (ART) in sub-Saharan Africa, many challenges remain, not least of which are the identification and management of patients who have failed first-line therapy. Less than 3% of patients are receiving second-line treatment at present, whereas 15-25% of patients have detectable viral loads 12 months or more into treatment, of whom a substantial proportion might have virological failure. We discuss the reasons why virological ART failure is likely to be under-diagnosed in the routine health system, and address the current difficulties with standard recommended second-line ART regimens. The development of new diagnostic tools for ART failure, in particular a point-of-care HIV viral-load test, combined with simple and inexpensive second-line therapy, such as boosted protease-inhibitor monotherapy, could revolutionise the management of ART failure in resource-limited settings

A rodent model of HIV protease inhibitor indinavir induced peripheral neuropathy

The research leading to these results is part of the EUROPAIN Collaboration, which has received support from the Innovative Medicines Initiative Joint Undertaking, under grant agreement no 115007, resources of which are composed of financial contribution from the European Union's Seventh Framework Program (FP7/2007‐2013) and EFPIA companies’ in kind contribution. We thank Pfizer for providing indinavir and gabapentin. MC received Conicyt grant (Folio 82130016),to complete this work.Peer reviewedPostprin

Study of microRNAs-21/221 as potential breast cancer biomarkers in Egyptian women

microRNAs (miRNAs) play an important role in cancer prognosis. They are small molecules, approximately 17–25 nucleotides in length, and their high stability in human serum supports their use as novel diagnostic biomarkers of cancer and other pathological conditions. In this study, we analyzed the expression patterns of miR-21 and miR-221 in the serum from a total of 100 Egyptian female subjects with breast cancer, fibroadenoma, and healthy control subjects. Using microarray-based expression profiling followed by real-time polymerase chain reaction validation, we compared the levels of the two circulating miRNAs in the serum of patients with breast cancer (n = 50), fibroadenoma (n = 25), and healthy controls (n = 25). The miRNA SNORD68 was chosen as the housekeeping endogenous control. We found that the serum levels of miR-21 and miR-221 were significantly overexpressed in breast cancer patients compared to normal controls and fibroadenoma patients. Receiver Operating Characteristic (ROC) curve analysis revealed that miR-21 has greater potential in discriminating between breast cancer patients and the control group, while miR-221 has greater potential in discriminating between breast cancer and fibroadenoma patients. Classification models using k-Nearest Neighbor (kNN), Naïve Bayes (NB), and Random Forests (RF) were developed using expression levels of both miR-21 and miR-221. Best classification performance was achieved by NB Classification models, reaching 91% of correct classification. Furthermore, relative miR-221 expression was associated with histological tumor grades. Therefore, it may be concluded that both miR-21 and miR-221 can be used to differentiate between breast cancer patients and healthy controls, but that the diagnostic accuracy of serum miR-21 is superior to miR-221 for breast cancer prediction. miR-221 has more diagnostic power in discriminating between breast cancer and fibroadenoma patients. The overexpression of miR-221 has been associated with the breast cancer grade. We also demonstrated that the combined expression of miR-21 and miR-221can be successfully applied as breast cancer biomarkers

ΔFosB Regulates Gene Expression and Cognitive Dysfunction in a Mouse Model of Alzheimer\u27s Disease.

Alzheimer\u27s disease (AD) is characterized by cognitive decline and 5- to 10-fold increased seizure incidence. How seizures contribute to cognitive decline in AD or other disorders is unclear. We show that spontaneous seizures increase expression of ΔFosB, a highly stable Fos-family transcription factor, in the hippocampus of an AD mouse model. ΔFosB suppressed expression of the immediate early gene c-Fos, which is critical for plasticity and cognition, by binding its promoter and triggering histone deacetylation. Acute histone deacetylase (HDAC) inhibition or inhibition of ΔFosB activity restored c-Fos induction and improved cognition in AD mice. Administration of seizure-inducing agents to nontransgenic mice also resulted in ΔFosB-mediated suppression of c-Fos, suggesting that this mechanism is not confined to AD mice. These results explain observations that c-Fos expression increases after acute neuronal activity but decreases with chronic activity. Moreover, these results indicate a general mechanism by which seizures contribute to persistent cognitive deficits, even during seizure-free periods

Niraparib in ovarian cancer. results to date and clinical potential

Ovarian cancer is the first cause of death from gynaecological malignancy. Germline mutation in BRCA1 and 2, two genes involved in the mechanisms of reparation of DNA damage, are showed to be related with the incidence of breast and ovarian cancer, both sporadic and familiar. PARP is a family of enzymes involved in the base excision repair (BER) system. The introduction of inhibitors of PARP in patients with BRCA-mutated ovarian cancer is correlated with the concept of synthetic lethality. Among the PARP inhibitors introduced in clinical practice, niraparib showed interesting results in a phase III trial in the setting of maintenance treatment in ovarian cancer, after platinum-based chemotherapy. Interestingly, was niraparib showed to be efficacious not only in BRCA-mutated patients, but also in patients with other alterations of the homologous recombination (HR) system and in patients with unknown alterations. These results position niraparib as the first PARP-inhibitor with clinically and statistically significant results also in patients with no alterations in BRCA 1/2 and other genes involved in the DNA repair system. Even if the results are potentially practice-changing, the action of niraparib must be further studied and deepened