Unlocking The Mysteries of DNA Adducts with Artificial Intelligence.

Cellular genome is considered a dynamic blueprint of a cell since it encodes genetic information that gets temporally altered due to various endogenous and exogenous insults. Largely, the extent of genomic dynamicity is controlled by the trade-off between DNA repair processes and the genotoxic potential of the causative agent (genotoxins or potential carcinogens). A subset of genotoxins form DNA adducts by covalently binding to the cellular DNA, triggering structural or functional changes that lead to significant alterations in cellular processes via genetic (e. g., mutations) or non-genetic (e. g., epigenome) routes. Identification, quantification, and characterization of DNA adducts are indispensable for their comprehensive understanding and could expedite the ongoing efforts in predicting carcinogenicity and their mode of action. In this review, we elaborate on using Artificial Intelligence (AI)-based modeling in adducts biology and present multiple computational strategies to gain advancements in decoding DNA adducts. The proposed AI-based strategies encompass predictive modeling for adduct formation via metabolic activation, novel adducts' identification, prediction of biochemical routes for adduct formation, adducts' half-life predictions within biological ecosystems, and, establishing methods to predict the link between adducts chemistry and its location within the genomic DNA. In summary, we discuss some futuristic AI-based approaches in DNA adduct biology.

deepGraphh: AI-driven web service for graph-based quantitative structure-activity relationship analysis.

Artificial intelligence (AI)-based computational techniques allow rapid exploration of the chemical space. However, representation of the compounds into computational-compatible and detailed features is one of the crucial steps for quantitative structure-activity relationship (QSAR) analysis. Recently, graph-based methods are emerging as a powerful alternative to chemistry-restricted fingerprints or descriptors for modeling. Although graph-based modeling offers multiple advantages, its implementation demands in-depth domain knowledge and programming skills. Here we introduce deepGraphh, an end-to-end web service featuring a conglomerate of established graph-based methods for model generation for classification or regression tasks. The graphical user interface of deepGraphh supports highly configurable parameter support for model parameter tuning, model generation, cross-validation and testing of the user-supplied query molecules. deepGraphh supports four widely adopted methods for QSAR analysis, namely, graph convolution network, graph attention network, directed acyclic graph and Attentive FP. Comparative analysis revealed that deepGraphh supported methods are comparable to the descriptors-based machine learning techniques. Finally, we used deepGraphh models to predict the blood-brain barrier permeability of human and microbiome-generated metabolites. In summary, deepGraphh offers a one-stop web service for graph-based methods for chemoinformatics.

Artificial intelligence uncovers carcinogenic human metabolites.

The genome of a eukaryotic cell is often vulnerable to both intrinsic and extrinsic threats owing to its constant exposure to a myriad of heterogeneous compounds. Despite the availability of innate DNA damage responses, some genomic lesions trigger malignant transformation of cells. Accurate prediction of carcinogens is an ever-challenging task owing to the limited information about bona fide (non-)carcinogens. We developed Metabokiller, an ensemble classifier that accurately recognizes carcinogens by quantitatively assessing their electrophilicity, their potential to induce proliferation, oxidative stress, genomic instability, epigenome alterations, and anti-apoptotic response. Concomitant with the carcinogenicity prediction, Metabokiller is fully interpretable and outperforms existing best-practice methods for carcinogenicity prediction. Metabokiller unraveled potential carcinogenic human metabolites. To cross-validate Metabokiller predictions, we performed multiple functional assays using Saccharomyces cerevisiae and human cells with two Metabokiller-flagged human metabolites, namely 4-nitrocatechol and 3,4-dihydroxyphenylacetic acid, and observed high synergy between Metabokiller predictions and experimental validations.

Coordination of floral and fiber development in cotton (Gossypium) by hormone- and flavonoid-signalling associated regulatory miRNAs.

Various plant development activities and stress responses are tightly regulated by various microRNAs (miRNA) and their target genes, or transcription factors in a spatiotemporal manner. Here, to exemplify how flowering-associated regulatory miRNAs synchronize their expression dynamics during floral and fiber development in cotton, constitutive expression diminution transgenic lines of auxin-signaling regulatory Gh-miR167 (35S-MIM167) were developed through target mimicry approach. 'Moderate' (58% to 80%)- and 'high' (> 80%)-Gh-miR167 diminution mimic lines showed dosage-dependent developmental deformities in anther development, pollen maturation, and fruit (= boll) formation. Cross pollination of 'moderate' 35S-MIM167 mimic lines with wild type (WT) plant partially restored boll formation and emergence of fiber initials on the ovule surface. Gh-miR167 diminution favored organ-specific transcription biases in miR159, miR166 as well as miR160, miR164, and miR172 along with their target genes during anther and petal development, respectively. Similarly, accumulative effect of percent Gh-miR167 diminution, cross regulation of its target ARF6/8 genes, and temporal mis-expression of hormone signaling- and flavonoid biosynthesis-associated regulatory miRNAs at early fiber initiation stage caused irregular fiber formation. Spatial and temporal transcription proportions of regulatory miRNAs were also found crucial for the execution of hormone- and flavonoid-dependent progression of floral and fiber development. These observations discover how assorted regulatory genetic circuits get organized in response to Gh-miR167 diminution and converge upon ensuing episodes of floral and fiber development in cotton.

Performance analysis of U-Net with hybrid loss for foreground detection.

With the latest developments in deep neural networks, the convolutional neural network (CNN) has made considerable progress in the area of foreground detection. However, the top-rank background subtraction algorithms for foreground detection still have many shortcomings. It is challenging to extract the true foreground against complex background. To tackle the bottleneck, we propose a hybrid loss-assisted U-Net framework for foreground detection. A proposed deep learning model integrates transfer learning and hybrid loss for better feature representation and faster model convergence. The core idea is to incorporate reference background image and change detection mask in the learning network. Furthermore, we empirically investigate the potential of hybrid loss over single loss function. The advantages of two significant loss functions are combined to tackle the class imbalance problem in foreground detection. The proposed technique demonstrates its effectiveness on standard datasets and performs better than the top-rank methods in challenging environment. Moreover, experiments on unseen videos also confirm the efficacy of proposed method.

A systematic survey of advances in retinal imaging modalities for Alzheimer's disease diagnosis.

Recent advances in retinal imaging pathophysiology have shown a new function for biomarkers in Alzheimer's disease diagnosis and prognosis. The significant improvements in Optical coherence tomography (OCT) retinal imaging have led to significant clinical translation, particularly in Alzheimer's disease detection. This systematic review will provide a comprehensive overview of retinal imaging in clinical applications, with a special focus on biomarker analysis for use in Alzheimer's disease detection. Articles on OCT retinal imaging in Alzheimer's disease diagnosis were identified in PubMed, Google Scholar, IEEE Xplore, and Research Gate databases until March 2021. Those studies using simultaneous retinal imaging acquisition were chosen, while those using sequential techniques were rejected. "Alzheimer's disease" and "Dementia" were searched alone and in combination with "OCT" and "retinal imaging". Approximately 1000 publications were searched, and after deleting duplicate articles, 145 relevant studies focused on the diagnosis of Alzheimer's disease utilizing retinal imaging were chosen for study. OCT has recently been demonstrated to be a valuable technique in clinical practice as according to this survey, 57% of the researchers employed optical coherence tomography, 19% used ocular fundus imaging, 13% used scanning laser ophthalmoscopy, and 11% have used multimodal imaging to diagnose Alzheimer disease. Retinal imaging has become an important diagnostic technique for Alzheimer's disease. Given the scarcity of available literature, it is clear that future prospective trials involving larger and more homogeneous groups are necessary, and the work can be expanded by evaluating its significance utilizing a machine-learning platform rather than simply using statistical methodologies.

Global expression dynamics and miRNA evolution profile govern floral/fiber architecture in the modern cotton (Gossypium).

MAIN CONCLUSION: Majority of differentially expressed miRNAs with functional attributes have been recruited independently and parallelly during allopolyploidy followed by the millennia of human selection of both domesticated G. hirsutum and G. barbadense. The genus Gossypium is a marvelous evolutionary model for studying allopolyploidy and morpho-evolution of long-spinnable fibers from the ancestral wild-fuzz. Many genes, transcription factors, and notably, the regulatory miRNAs essentially govern such remarkable modern fiber phenotypes. To comprehend the impact of allopolyploidy on the evolutionary selection of transcriptional dynamicity of key miRNAs, comparative transcriptome profiling of vegetative and fiber tissues of domesticated diploid G. arboreum (A2) and allopolyploid cotton species G. hirsutum (AD1), and G. barbadense (AD2) identified > 300 differentially expressed miRNAs (DEmiRs) within or between corresponding tissues of A2, AD1 and AD2 species. Up to 49% and 32% DEmiRs were up- and down-regulated at fiber initiation stage of AD1 and AD2 species, respectively, whereas 50% and 18% DEmiRs were up- and down-regulated at fiber elongation stage of both the allopolyploid species. Interestingly, A-subgenome-specific DEmiRs exhibit expression dominance in the allopolyploid genetic backgrounds. Comparative spatio-temporal expression analyses of AD1 and AD2 species discovered that a majority of DEmiRs were recruited independently under millennia of human selection during domestication. Functional annotations of these DEmiRs revealed selection of associated molecular functions such as hormone-signaling, calcium-signaling and reactive oxygen species (ROS) signaling during fiber initiation and elongation. To validate the functional attributes of annotated DEmiRs, we demonstrated for the first time that the target-mimicry-based constitutive diminution of auxin-signaling associated miR167 directly affected the differentiation of floral and fiber tissues of transgenic cotton. These results strongly suggested that the evolutionarily favored DEmiRs including miR167 were involved in the transcriptional regulation of numerous genes during cotton evolution for enhanced fiber-associated agronomic traits.

HIV-1 Nef Disrupts CD4+ T Lymphocyte Polarity, Extravasation, and Homing to Lymph Nodes via Its Nef-Associated Kinase Complex Interface.

HIV-1 Nef is a multifunctional protein that optimizes virus spread and promotes immune evasion of infected cells to accelerate disease progression in AIDS patients. As one of its activities, Nef reduces the motility of infected CD4+ T lymphocytes in confined space. In vivo, Nef restricts T lymphocyte homing to lymph nodes as it reduces the ability for extravasation at the diapedesis step. Effects of Nef on T lymphocyte motility are typically mediated by its ability to reduce actin remodeling. However, interference with diapedesis does not depend on residues in Nef required for inhibition of host cell actin dynamics. In search for an alternative mechanism by which Nef could alter T lymphocyte extravasation, we noted that the viral protein interferes with the polarization of primary human CD4+ T lymphocytes upon infection with HIV-1. Expression of Nef alone is sufficient to disrupt T cell polarization, and this effect is conserved among lentiviral Nef proteins. Nef acts by arresting the oscillation of CD4+ T cells between polarized and nonpolarized morphologies. Mapping studies identified the binding site for the Nef-associated kinase complex (NAKC) as critical determinant of this Nef activity and a NAKC-binding-deficient Nef variant fails to impair CD4+ T lymphocyte extravasation and homing to lymph nodes. These results thus imply the disruption of T lymphocyte polarity via its NAKC binding site as a novel mechanism by which lentiviral Nef proteins alter T lymphocyte migration in vivo.

Hyperactivation of mammalian target of rapamycin complex 1 by HIV-1 is necessary for virion production and latent viral reactivation.

Generation of new HIV-1 virions requires the constant supply of proteins, nucleotides, and energy; however, it is not known which cellular pathways are perturbed and what molecular mechanisms are employed. We hypothesized that HIV-1 may regulate pathways that control synthesis of biomolecules in the cell. In this study, we provide evidence that HIV-1 hyperactivates mammalian target of rapamycin complex 1 (mTORC1), the central regulator of biosynthesis. Mechanistically, we identify the viral regulatory gene tat (transactivator) as being responsible for increasing mTORC1 activity in a PI3K-dependent manner. Furthermore, we show that hyperactivation of mTORC1 leads to activation of the enzyme, carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, dihydroorotase, and repression of initiation factor 4E-binding protein 1 activity. These are regulators of nucleotide biogenesis and protein translation, respectively. Moreover, we are able to replicate these results in HIV-1 latent cell line models. Finally, we show that inhibition of mTORC1 or PI3K inhibits viral replication and viral reactivation as a result of a decrease in biosynthesis. Overall, our study identifies a new avenue in HIV-1 biology that can lead to development of novel therapeutic targets.-Kumar, B., Arora, S., Ahmed, S., Banerjea, A. C. Hyperactivation of mammalian target of rapamycin complex 1 by HIV-1 is necessary for virion production and latent viral reactivation.

The miRNA miR-34a enhances HIV-1 replication by targeting PNUTS/PPP1R10, which negatively regulates HIV-1 transcriptional complex formation.

HIV-1 relies heavily on the host cellular machinery for its replication. During infection, HIV-1 is known to modulate the host-cell miRNA profile. One of the miRNAs, miR-34a, is up-regulated by HIV-1 in T-cells as suggested by miRNA microarray studies. However, the functional consequences and the mechanism behind this phenomenon were not explored. The present study shows that HIV-1 enhances miR-34a in a time-dependent manner in T-cells. Our overexpression and knockdown-based experimental results suggest that miR-34a promotes HIV-1 replication in T-cells. Hence, there is a positive feedback loop between miR-34a and HIV-1 replication. We show that the mechanism of action of miR-34a in HIV-1 replication involves a cellular protein, the phosphatase 1 nuclear-targeting subunit (PNUTS). PNUTS expression levels decrease with the progression of HIV-1 infection in T-cells. Also, the overexpression of PNUTS potently inhibits HIV-1 replication in a dose-dependent manner. We report for the first time that PNUTS negatively regulates HIV-1 transcription by inhibiting the assembly of core components of the transcription elongation factor P-TEFb, i.e. cyclin T1 and CDK9. Thus, HIV-1 increases miR-34a expression in cells to overcome the inhibitory effect of PNUTS on HIV-1 transcription. So, the present study provides new mechanistic details with regard to our understanding of a complex interplay between miR-34a and the HIV-1 transcription machinery involving PNUTS.

HIV-1 Vpr redirects host ubiquitination pathway.

UNLABELLED: HIV-1 modulates key host cellular pathways for successful replication and pathogenesis through viral proteins. By evaluating the hijacking of the host ubiquitination pathway by HIV-1 at the whole-cell level, we now show major perturbations in the ubiquitinated pool of the host proteins post-HIV-1 infection. Our overexpression- and infection-based studies of T cells with wild-type and mutant HIV-1 proviral constructs showed that Vpr is necessary and sufficient for reducing whole-cell ubiquitination. Mutagenic analysis revealed that the three leucine-rich helical regions of Vpr are critical for this novel function of Vpr, which was independent of its other known cellular functions. We also validated that this effect of Vpr was conserved among different subtypes (subtypes B and C) and circulating recombinants from Northern India. Finally, we establish that this phenomenon is involved in HIV-1-mediated diversion of host ubiquitination machinery specifically toward the degradation of various restriction factors during viral pathogenesis. IMPORTANCE: HIV-1 is known to rely heavily on modulation of the host ubiquitin pathway, particularly for counteraction of antiretroviral restriction factors, i.e., APOBEC3G, UNG2, and BST-2, etc.; viral assembly; and release. Reports to date have focused on the molecular hijacking of the ubiquitin machinery by HIV-1 at the level of E3 ligases. Interaction of a viral protein with an E3 ligase alters its specificity to bring about selective protein ubiquitination. However, in the case of infection, multiple viral proteins can interact with this multienzyme pathway at various levels, making it much more complicated. Here, we have addressed the manipulation of ubiquitination at the whole-cell level post-HIV-1 infection. Our results show that HIV-1 Vpr is necessary and sufficient to bring about the redirection of the host ubiquitin pathway toward HIV-1-specific outcomes. We also show that the three leucine-rich helical regions of Vpr are critical for this effect and that this ability of Vpr is conserved across circulating recombinants. Our work, the first of its kind, provides novel insight into the regulation of the ubiquitin system at the whole-cell level by HIV-1.

Attenuation of hemodynamic response to laryngoscopy and orotracheal intubation using intravenous clonidine.

BACKGROUND AND AIMS: Alpha-2 agonists are being increasingly used as adjuncts in general anesthesia and the present study was carried out to study the effect of clonidine as an adjuvant to low dose fentanyl in attenuating the hemodynamic response to laryngoscopy and orotracheal intubation. MATERIALS AND METHODS: Ninety female patients belonging to American Society of Anesthesiologists (ASA) physical status I, II, and III in age group 25-65 years, body mass index (BMI) 21-26 kg/m(2), and diagnosed as carcinoma breast scheduled for breast surgery were included in this Prospective, randomized, placebo-controlled study. One-way analysis of variance (ANOVA), paired t-test, and chi-square test was applied where deemed appropriate. P-value at or below the level of 0.05 was considered as statistically significant. RESULTS: Intravenous (IV) clonidine 1.0 µg kg(-1) and clonidine 2.0 µg kg(-1) significantly attenuated the hyperdynamic response to laryngoscopy and intubation. Clonidine 2.0 µg kg(-1) was associated with adverse effects like hypotension at the time of induction and postoperative sedation which was not observed with clonidine 1.0 µg kg(-1). CONCLUSIONS: A single intravenous low dose clonidine (1.0 µg kg(-1)) when combined with low dose fentanyl (2 µg kg(-1)) is a practical, pharmacological and safe method with minimal side effects to attenuate the hyperdynamic response to laryngoscopy and intubation.

Association of sleep quality with physical and psychological health indicators in overweight and obese rural Indians.

Objective: To measure the association of sleep quality with physical (i.e., grip strength, functional mobility, balance) and psychological (depression, anxiety) health indicators in an overweight/obese population. Methods: Baseline data of 2337 participants (1382 overweight/obese and 955 normal weight) from an aging cohort in rural southern India (CBR-SANSCOG) was analyzed retrospectively. Assessment tools included the Pittsburgh Sleep Quality Index (PSQI) for sleep quality, dynamometry for Hand Grip Strength (HGS), Timed Up-and-Go (TUG) for functional mobility, Chair Stand Test (CST) for lower limb strength, Geriatric Depression scale (GDS-30) for depressive symptoms and Generalized Anxiety Disorder scale (GAD-7) for anxiety symptoms. Linear regression models, adjusted for known confounders, were used to examine the association of sleep quality with the health parameters in overweight/obese and normal-weight groups. Results: In the fully adjusted model, higher global PSQI score was associated with higher TUG time (ß = 0.06, 95 % CI: 0.004,0.12), higher scores on GDS (ß = 1.08, 95 % CI: 0.96,1.20) and GAD (ß = 0.71, 95 % CI: 0.62,0.79), and lower scores on CST (ß = -0.12, 95 % CI: -0.19,-0.06) in overweight/obese individuals. The sleep disturbance sub-component of PSQI was associated with most of the physical (TUG, CST) and psychological (GDS and GAD) health indicators. Sleep duration and use of sleep medication showed no significant association with any of the health indicators. Conclusion: The concurrent presence of poor sleep quality and overweight/obesity could worsen physical and psychological health in middle-aged and older adults. We highlight the importance of early detection and timely management of sleep problems in this population to reduce physical and psychological morbidities.

CRISPR screen for rAAV production implicates genes associated with infection.

Recombinant adeno-associated virus (rAAV) vectors are an effective and well-established tool in the growing gene therapy field, with five FDA-approved AAV-mediated gene therapies already on the market and numerous more in clinical trials. However, manufacturing rAAV vectors is an expensive, timely, and labor-intensive process that limits the commercial use of AAV-mediated gene therapies. To address this limitation, we screened producer cells for genes that could be targeted to increase rAAV yield. Specifically, we performed a CRISPR-based genome-wide knockout screen in HEK 293 cells using an antibody specific to intact AAV2 capsids coupled with flow cytometry to identify genes that modulate rAAV production. We discovered that the knockout of a group of heparan sulfate biosynthesis genes previously implicated in rAAV infectivity decreased rAAV production. Additionally, we identified several vesicular trafficking proteins for which knockout in HEK 293 cells increased rAAV yields. Our findings provide evidence that host proteins associated with viral infection may have also been co-opted for viral assembly and that the genetic makeup of viral producer cells can be manipulated to increase particle yield.

Bridging, Mapping, and Addressing Research Gaps in Health Sciences: The Naqvi-Gabr Research Gap Framework.

Innovations pertaining to the ever-evolving needs of the medical and healthcare sciences remain constant. This creates a gap between the rationalized needs of the study and the proposed research question. However, classifying, identifying, and addressing these research gaps require a systematic and precise structured map. Using the Medical Subject Heading (MeSH) terms "Research Gaps" AND "Healthcare" AND "Framework" in MEDLINE, Scopus, and CINAHL databases with the filters yielded no relevant literature. Therefore, this review aims to fill this practical and clinical knowledge gap by developing the Naqvi-Gabr Research Gap Framework through critical synthesis based on extensive research on medical and healthcare research gaps. Fourteen research gaps are distributed for allocation as per the healthcare delivery system approach: developing new treatments or prevention strategies, improving diagnostic tools and techniques, addressing health disparities, and improving access to healthcare services. This structured framework determines the strategic mapping of research gaps corresponding to the nature of the research. The identification and classification of the appropriate research gap led to precise and concise conclusions corresponding to the research process proposed in this study. Hence, the Naqvi-Gabr Research Gap Framework is a valuable tool for determining the potential application of gaps by researchers, policymakers, and other stakeholders with a productive address.

Arginine rich short linear motif of HIV-1 regulatory proteins inhibits dicer dependent RNA interference.

BACKGROUND: Arginine Rich Motif (ARM) of HIV-1 Tat and Rev are extensively studied linear motifs (LMs). They are already established as an inefficient bipartite nuclear localisation signal (NLS). The unusual passive diffusion of HIV-1 NLS tagged reporter proteins across the nucleus is due to an unknown competing functionality of ARM. Recent findings about the role of retroviral proteins as a suppressor of RNA interference (RNAi) involving their basic residues hint an interesting answer to this alternate functionality. The present work explores the role of HIV-1 ARM as a uniquely evolved viral motif to combat Dicer dependent RNAi. RESULTS: We show that RNA binding ARM of both HIV-1 Tat and Rev is a LM with a pattern RXXRRXRRR unique to viruses. Extending the in silico results to wet lab, we proved both HIV-1 Tat and Rev can suppress Dicer dependent RNA silencing process involving ARM. We show, HIV-1 Tat and Rev and their corresponding ARM can bind the RISC loading complex (RLC) components TRBP and PACT confirming ARM as an independent RNAi suppression motif. Enhancement of RNAi in infection scenario through enoxacin increases HIV-1 replication as indicated by p24 levels. Except Dicer, all other cytoplasmic RNAi components enhance HIV-1 replication, indicating crucial role of Dicer independent (Ago2 dependent) RNAi pathway in HIV-1 infection. Sequence and structural analysis of endo/exo-microRNA precursors known to be regulated in HIV-1 infection highlights differential features of microRNA biogenesis. One such set of miRNA is viral TAR encoded HIV-1-miR-TAR-5p (Tar1) and HIV-1-miR-TAR-3p (Tar2) that are known to be present throughout the HIV-1 life cycle. Our qPCR results showed that enoxacin increases Tar2 miRNA level which is interesting as Tar2 precursor shows Ago2 dependent processing features. CONCLUSIONS: We establish HIV-1 ARM as a novel viral motif evolved to target the Dicer dependent RNAi pathway. The conservation of such motif in other viral proteins possibly explains the potent suppression of Dicer dependent RNAi. Our model argues that HIV-1 suppress the processing of siRNAs through inhibition of Dicer while at the same time manipulates the RNAi machinery to process miRNA involved in HIV-1 replication from Dicer independent pathways.

Inhibition of ß-TrcP-dependent ubiquitination of p53 by HIV-1 Vpu promotes p53-mediated apoptosis in human T cells.

HIV-1 viral protein U (Vpu) is involved in ubiquitination and degradation of BM stromal cell Ag 2 and surface receptor CD4 through their recruitment to SCF(ß-TrcP) (Skp1/Cul1/F-box) ubiquitin ligase (SCF) complex. Here, we show that specific interaction of wild-type Vpu protein with SCF complex leads to inhibition of ubiquitination and proteasomal degradation of p53 protein in a ß-TrcP-dependent manner. Successful interaction of SCF(ß-TrcP) complex with ß-TrcP binding motif (DS(52)GNES(56)) present in Vpu is essential because mutant Vpu possessing specific alanine substitutions (DA(52)GNEA(56)) in the ß-TrcP binding motif not only failed to stabilize p53 protein but was also unable to inhibit ubiquitination of p53 protein. Furthermore, Vpu competes efficiently with the interaction of p53 protein with the ß-TrcP subunit of the SCF complex and inhibits subsequent ubiquitination of p53 proteins in a dose-dependent manner. We also observed potent apoptotic activity in a p53 null cell line (H-1299) that was cotransfected with p53 and Vpu-expressing plasmids. Furthermore, MOLT-3 (human T-lymphoblast) cells when infected with vesicular stomatitis virus glycoprotein-pseudotypic HIV-1 possessing wild-type vpu gene exhibited maximum activation of p53/Bax proteins and p53-mediated cell death. These findings establish a novel function of Vpu in modulating the stability of p53 protein that correlates positively with apoptosis during late stages of HIV-1 infection.

Osteoporosis diagnosis in knee X-rays by transfer learning based on convolution neural network.

Osteoporosis degrades the quality of bones and is the primary cause of fractures in the elderly and women after menopause. The high diagnostic and treatment costs urge the researchers to find a cost-effective diagnostic system to diagnose osteoporosis in the early stages. X-ray imaging is the cheapest and most common imaging technique to detect bone pathologies butmanual interpretation of x-rays for osteoporosis is difficult and extraction of required features and selection of high-performance classifiers is a very challenging task. Deep learning systems have gained the popularity in image analysis field over the last few decades. This paper proposes a convolution neural network (CNN) based approach to detect osteoporosis from x-rays. In our study, we have used the transfer learning of deep learning-based CNNs namely AlexNet, VggNet-16, ResNet, and VggNet -19 to classify the x-ray images of knee joints into normal, osteopenia, and osteoporosis disease groups. The main objectives of the current study are: (i) to present a dataset of 381 knee x-rays medically validated by the T-scores obtained from the Quantitative Ultrasound System, and (ii) to propose a deep learning approach using transfer learning to classify different stages of the disease. The performance of these classifiers is compared and the best accuracy of 91.1% is achieved by pretrained Alexnet architecture on the presented dataset with an error rate of 0.09 and validation loss of 0.54 as compared to the accuracy of 79%, an error rate of 0.21, and validation loss of 0.544 when pretrained network was not used.. The results of the study suggest that a deep learning system with transfer learning can help clinicians to detect osteoporosis in its early stages hence reducing the risk of fractures.

Eph Receptors in Cancer.

Eph receptor tyrosine kinases play critical functions during development, in the formation of tissue and organ borders, and the vascular and neural systems. Uniquely among tyrosine kinases, their activities are controlled by binding to membrane-bound ligands, called ephrins. Ephs and ephrins generally have a low expression in adults, functioning mainly in tissue homeostasis and plasticity, but are often overexpressed in cancers, where they are especially associated with undifferentiated or progenitor cells, and with tumour development, vasculature, and invasion. Mutations in Eph receptors also occur in various tumour types and are suspected to promote tumourigenesis. Ephs and ephrins have the capacity to operate as both tumour promoters and tumour suppressors, depending on the circumstances. They have been demonstrated to impact tumour cell proliferation, migration, and invasion in vitro, as well as tumour development, angiogenesis, and metastases in vivo, making them potential therapeutic targets. However, successful development of therapies will require detailed understanding of the opposing roles of Ephs in various cancers. In this review, we discuss the variations in Eph expression and functions in a variety of malignancies. We also describe the multiple strategies that are currently available to target them in tumours, including preclinical and clinical development.