Miracle-dz/UniFAR-FTUs huggingface dataset:
E6/E7 and E6* From HPV16 and HPV18 Upregulate IL-6 Expression Independently of p53 in Keratinocytes

Keratinocyte infection with high-risk human papillomavirus genotypes has been linked to cancer development. In cervix, the alpha HPV16 and HPV18 have been reported as the mayor causative agents of cervical cancer. Oncogenic progression and chronic inflammation are closely related processes, with IL-6 as one of the main pro-inflammatory cytokines involved. However, there are limited studies about the regulation of IL-6 by low and high risk HPVs and the HPV proteins implicated in this modulation. In this work, we report the overexpression of IL-6 in HPV infected cervical cancer derived cell lines (HeLa and SiHa) compared to non-tumorigenic keratinocytes (HaCaT), and in Cervical Intraepithelial Neoplasia grade 1 HPV16 and HPV18 positive cervical samples compared to HPV negative samples without lesions. Moreover, we generated HaCaT keratinocytes that express E5, E6, and E7 from high risk (16 or 18) or low risk (62 and 84) HPVs. E5 proteins do not modify IL-6 expression, while E7 modestly increase it. Interestingly, E6 proteins in HaCaT cells upregulate IL-6 mRNA expression and protein secretion. Indeed, in HaCaT cells that express high risk HPV16E6 or HPV18E6 proteins, only the truncated E6* isoforms were expressed, showing the stronger IL-6 overexpression, while in HaCaT cells that express low risk HPV62 and HPV84 full length E6 proteins, IL-6 was also upregulated but not so drastically. Since HaCaT cells have a mutated p53 form that is not degraded by the introduction of E6 or E6/E7, it seems that E6/E7 regulate IL-6 by an additional mechanism independent of p53. In addition, basal keratinocytes showed a strong expression of IL-6R using immunohistochemistry, suggesting an autocrine mechanism over proliferative cells. Altogether, IL-6 cytokine expression in keratinocytes is upregulated by E6 and E7 proteins from HPVs 16, 18, 62, and 84, especially by high risk HPV16 and HPV18 E6*, which may contribute to promote a pro-inflammatory and highly proliferative microenvironment that can persist over time and lead to cervical tumorigenesis.
Antimicrobial Activity and Action Approach of the Olive Oil Polyphenol Extract Against Listeria monocytogenes

Olive oil polyphenol extract (OOPE) has been reported to have antibacterial activity; however, its effect on Listeria monocytogenes is less studied so far. This study, thus, aimed to reveal its antimicrobial activity and action approach against L. monocytogenes via evaluating the minimum inhibitory concentration (MIC) as well as the changes of intracellular adenosine 5′-triphosphate (ATP) concentration, cell membrane potential, bacterial protein, DNA, and cell morphology. The results showed that OOPE could inhibit the growth of L. monocytogenes with a measured MIC of 1.25 mg/ml. L. monocytogenes cells treated by OOPE showed significant reduction in intracellular ATP concentrations, bacterial protein, or DNA (p < 0.05), in comparison with those without any treatment. In addition, OOPE was observed to depolarize strain cells and alter cell morphology, resulting in damaged cell membrane and, thereby, leakage of cell fluid. These findings demonstrated that OOPE had inhibition on L. monocytogenes via its action on cells, suggesting its potential as a natural preservative.
Risperidone Reverses the Downregulation of BDNF in Hippocampal Neurons and MK801-Induced Cognitive Impairment in Rats

MK-801, also known as dizocilpine, is a non-competitive N-methyl-D-aspartic acid (NMDA) receptor antagonist that induces schizophrenia-like symptoms. Our previous study showed that brain-derived neurotrophic factor (BDNF) signaling was upregulated in cultured hippocampal astrocytes in response to MK-801. However, dysfunctional NMDA receptors are mainly expressed in neurons. The effects of MK-801 on neuron-derived BDNF expression and of risperidone on MK-801-induced cognitive impairment and changes in BDNF expression are unclear. To address this issue, we examined BDNF expression in the hippocampus of rats that received repeated injections of MK-801 (0.5 mg/kg body weight for 6 days) and in primary cultured hippocampal neurons incubated with 20 μM MK-801 for 24 h. BDNF expression and cognitive function were also evaluated in rats receiving intraperitoneal injections of risperidone (1 mg/kg body weight) once daily for 7 days and in hippocampal neurons incubated with 10 μM risperidone following MK801 treatment. MK-801 treatment decreased BDNF expression in the rat hippocampus as well as the expression and secretion of BDNF in hippocampal neurons in vitro. However, risperidone reversed the effects of MK801 on BDNF level and improved cognitive function in rats treated with MK801. These findings suggest that risperidone may alleviate cognitive impairment caused by MK801 via upregulation of BNDF signaling in the hippocampus.
MicroRNA Expression Profiling in Newcastle Disease Virus-Infected DF-1 Cells by Deep Sequencing

Newcastle disease virus (NDV), causative agent of Newcastle disease (ND), is one of the most devastating pathogens for poultry industry worldwide. MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by regulating mRNA translation efficiency or mRNA abundance through binding to mRNA directly. Accumulating evidence has revealed that cellular miRNAs can also affect virus replication by controlling host-virus interaction. To identify miRNA expression profile and explore the roles of miRNA during NDV replication, in this study, small RNA deep sequencing was performed of non-inoculated DF-1 cells (chicken embryo fibroblast cell line) and JS 5/05-infected cells collected at 6 and 12 h post infection (hereafter called mock‚ NDV-6 h, and NDV-12 h groups respectively). A total of 73 miRNAs of NDV-6 h group and 64miRNAs of NDV-12 h group were significantly differentially expressed (SDE) when compared with those in mock group. Meanwhile, 50 SDE miRNAs, including 48 up- and 2 down-regulated, showed the same expression patterns in NDV-6 h and NDV-12 h groups. qRT-PCR validation of 15 selected miRNAs’ expression patterns was consistent with deep sequencing. To investigate the role of these SDE miRNAs in NDV replication, miRNA mimics and inhibitors were transfected into DF-1 cells followed by NDV infection. The results revealed that gga-miR-451 and gga-miR-199-5p promoted NDV replication while gga-miR-19b-3p and gga-miR-29a-3p inhibited NDV replication. Further function research demonstrated gga-miR-451 suppressed NDV-induced inflammatory response via targeting YWHAZ (tyrosine3-monooxygenase/tryptophan5-monooxygenase activation protein zeta). Overall, our study presented a global miRNA expression profile in DF-1 cells in response to NDV infection and verified the roles of some SDE miRNAs in NDV replication which will underpin further studies of miRNAs’ roles between the host and the virus.
Method Validation for Simultaneous Quantification of Olmesartan and Hydrochlorothiazide in Human Plasma Using LC-MS/MS and Its Application Through Bioequivalence Study in Healthy Volunteers

A new, simple, sensitive, selective, rapid, and high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS) method has been developed and validated for simultaneous quantification of Olmesartan and hydrochlorothiazide in human plasma. Simple liquid–liquid extraction procedure was applied for plasma sample pretreatment using a mixture of diethyl ether and dichloromethane, as an extraction solution. Analytes were separated on UNISOL C18 150*4.6 mm, 5 µm column using methanol, and 2 mM ammonium acetate pH 5.5 (80:20, v/v) as a mobile phase and detected by electrospray ionization in the multiple reaction monitoring (MRM) mode. The mass transition ion pairs were followed in negative ion mode as m/z 445.20 → 148.90 for Olmesartan; m/z 451.40 → 154.30 for Olmesartan D6 and m/z 295.80 → 205.10 for hydrochlorothiazide; m/z 298.90 → 206.30 for hydrochlorothiazide 13C D2. The method showed excellent linearity (r 2 > 0.99) over the concentration range of 5.002–2,599.934 ng/ml for Olmesartan and from 3.005 to 499.994 ng/ml for hydrochlorothiazide. Precision (% CV) and accuracy (% bias) for Olmesartan were found in the range of 3.07–9.02% and −5.00–0.00%, respectively. Precision (% CV) and accuracy (% bias) for hydrochlorothiazide were found in the range of 3.32–8.21% and 1.99–3.80%, respectively. This as developed novel and high-throughput liquid–liquid extraction bioanalytical method has substantial innovative value with the benefits of cost effectiveness, good extraction efficiency, shorter analysis run time, low organic solvent consumption, and simpler procedure over the previously reported solid-phase extraction method. The application of this method in pharmacokinetic studies was further demonstrated successfully through a bioequivalence study conducted on healthy human subjects, following oral administration of combined formulation of Olmesartan medoxomil and hydrochlorothiazide in fixed-dose tablet.
Convolutional Neural Networks for the Automatic Identification of Plant Diseases

Deep learning techniques, and in particular Convolutional Neural Networks (CNNs), have led to significant progress in image processing. Since 2016, many applications for the automatic identification of crop diseases have been developed. These applications could serve as a basis for the development of expertise assistance or automatic screening tools. Such tools could contribute to more sustainable agricultural practices and greater food production security. To assess the potential of these networks for such applications, we survey 19 studies that relied on CNNs to automatically identify crop diseases. We describe their profiles, their main implementation aspects and their performance. Our survey allows us to identify the major issues and shortcomings of works in this research area. We also provide guidelines to improve the use of CNNs in operational contexts as well as some directions for future research.
Non-canonical Targets Mediating the Action of Drugs of Abuse: Cocaine at the Sigma-1 Receptor as an Example

In addition to acting on traditionally recognized receptors or transporters on the plasma membrane, several drugs of abuse, including amphetamine, methamphetamine, nicotine, opioid, cocaine, ketamine, and cannabinoid, have been shown to exert their effects by acting on additional molecular targets either on the plasma membrane or inside a cell. These targets are usually nascent receptors or proteins that can cause downstream signaling or molecular events, leading to altered physiological outcomes favoring addictive processes. However, those “non-canonical” targets of drugs of abuse, in general, have not been widely recognized in drug abuse research. This perspective diverts attention to those underrecognized targets, in the hope of promoting a more complete understanding of the action of drugs of abuse.
Evolved but Not Fixed: A Life History Account of Gender Roles and Gender Inequality

The rift between evolutionary psychology and the biosocial model of gender relations impedes a fuller understanding of gender roles and gender inequality. In a novel evolutionary account that complements both existing theories, we highlight life history strategies as intermediate mechanism linking distal environmental forces to variations in gender relations. Specifically, traditional versus modernized gender roles are seen as shaped by present-oriented versus future-oriented reproductive strategies, which are sensitive to uncontrollable morbidity-mortality risks. Gender inequality stems from a combination of present-oriented reproductive strategies adapted to high-risk environments and dominance hierarchies resulting from societal competition (i.e., the probability of obtaining resources desired by others through personal efforts). By contrast, gender egalitarian values develop as people increasingly enact future-oriented reproductive strategies in a competitive but orderly and controllable environment, which is conducive to prestige hierarchies. The current account provides novel interpretations of phenomena ranging from sex differences in mate preference, sociosexuality, and sexism to cross-cultural variability in marital systems and cultural practices. All of these serve to support the view that gender relations are evolved, changeable, and influenced by the interaction between ecological and social environments in ways predicted by the life history mechanism.
Molecular Epidemiology of Multidrug-Resistant Klebsiella pneumoniae Isolates in a Brazilian Tertiary Hospital

Multidrug-resistant (MDR) Klebsiella pneumoniae (Kp) is a major bacterial pathogen responsible for hospital outbreaks worldwide, mainly via the spread of high-risk clones and epidemic resistance plasmids. In this study, we evaluated the molecular epidemiology and β-lactam resistance mechanisms of MDR-Kp strains isolated in a Brazilian academic care hospital. We used whole-genome sequencing to study drug resistance mechanisms and their relationships with a K. pneumoniae carbapenemase-producing (KPC) Kp outbreak. Forty-three Kp strains were collected between 2003 and 2012. Antimicrobial susceptibility testing was performed for 15 antimicrobial agents, and polymerase chain reaction (PCR) was used to detect 32 resistance genes. Mutations in ompk35, ompk36, and ompk37 were evaluated by PCR and DNA sequencing. Pulsed field gel electrophoresis (PFGE) and multilocus sequence typing (MLST) were carried out to differentiate the strains. Based on distinct epidemiological periods, six Kp strains were subjected to whole-genome sequencing. β-lactamase coding genes were widely distributed among isolates. Almost all isolates had mutations in porin genes, particularly ompk35. The presence of blaKPC promoted a very high increase in carbapenem minimum inhibitory concentration only when ompk35 and ompk36 were interrupted by insertion sequences. A major cluster was identified by PFGE analysis and all isolates from this cluster belonged to clonal group (CG) 258. We have also identified a large repertoire of resistance genes in the sequenced isolates. A blaKPC–2-bearing plasmid (pUFPRA2) was also identified, which was very similar to a plasmid previously described in the first Brazilian KPC-Kp (2005). We found high-risk clones (CG258) and an epidemic resistance plasmid throughout the duration of the study (2003 to 2012), emphasizing a persistent presence of MDR-Kp strains in the hospital setting. Finally, we found that horizontal transfer of resistance genes between clones may have played a key role in the evolution of the outbreak.
Increasing Local Excitability of Brainstem Respiratory Nuclei Reveals a Distributed Network Underlying Respiratory Motor Pattern Formation

The core circuit of the respiratory central pattern generator (rCPG) is located in the ventrolateral medulla, especially in the pre-Bötzinger complex (pre-BötC) and the neighboring Bötzinger complex (BötC). To test the hypothesis that this core circuit is embedded within an anatomically distributed pattern-generating network, we investigated whether local disinhibition of the nucleus tractus solitarius (NTS), the Kölliker-Fuse nuclei (KFn), or the midbrain periaqueductal gray area (PAG) can similarly affect the respiratory pattern compared to disinhibition of the pre-BötC/BötC core. In arterially-perfused brainstem preparations of rats, we recorded the three-phase respiratory pattern (inspiration, post-inspiration and late-expiration) from phrenic and vagal nerves before and after bilateral microinjections of the GABA(A)R antagonist bicuculline (50 nl, 10 mM). Local disinhibition of either NTS, pre-BötC/BötC, or KFn, but not PAG, triggered qualitatively similar disruptions of the respiratory pattern resulting in a highly significant increase in the variability of the respiratory cycle length, including inspiratory and expiratory phase durations. To quantitatively analyze these motor pattern perturbations, we measured the strength of phase synchronization between phrenic and vagal motor outputs. This analysis showed that local disinhibition of all brainstem target nuclei, but not the midbrain PAG, significantly decreased the strength of phase synchronization. The convergent perturbations of the respiratory pattern suggest that the rCPG expands rostrally and dorsally from the designated core but does not include higher mid-brain structures. Our data also suggest that excitation-inhibition balance of respiratory network synaptic interactions critically determines the network dynamics that underlie vital respiratory rhythm and pattern formation.
Ictal Epileptic Headache: When Terminology Is Not a Moot Question

The relationship between headache and epilepsy is complex and despite the nature of this association is not yet clear. In the last few years, it has been progressively introduced the concept of the “ictal epileptic headache” that was included in the recently revised International Classification of Headaches Disorders 3rd edition (ICHD-3-revised). The diagnostic criteria for ictal epileptic headache (IEH) suggested in 2012 were quite restrictive thus leading to the underestimation of this phenomenon. However, these criteria have not yet been included into the ICHD-3 revision published in 2018, thus creating confusion among both, physicians and experts in this field. Here, we highlight the importance to strictly apply the original IEH criteria explaining the reasons through the analysis of the clinical, historical, epidemiological and pathophysiological characteristics of the IEH itself. In addition, we discuss the issues related to the neurophysiopathological link between headache and epilepsy as well as to the classification of these epileptic events as “autonomic seizure. ”
Dopamine Receptor Blockade Attenuates Purinergic P2X4 Receptor-Mediated Prepulse Inhibition Deficits and Underlying Molecular Mechanisms

Sensorimotor gating refers to the ability to filter incoming sensory information in a stimulus-laden environment and disruption of this physiological process has been documented in psychiatric disorders characterized by cognitive aberrations. The effectiveness of current pharmacotherapies for treatment of sensorimotor gating deficits in the patient population still remains controversial. These challenges emphasize the need to better understand the biological underpinnings of sensorimotor gating which could lead to discovery of novel drug targets for therapeutic intervention. Notably, we recently reported a role for purinergic P2X4 receptors (P2X4Rs) in regulation of sensorimotor gating using prepulse inhibition (PPI) of acoustic startle reflex. P2X4Rs are ion channels gated by adenosine-5′-triphosphate (ATP). Ivermectin (IVM) induced PPI deficits in C57BL/6J mice in a P2X4R-specific manner. Furthermore, mice deficient in P2X4Rs [P2X4R knockout (KO)] exhibited PPI deficits that were alleviated by dopamine (DA) receptor antagonists demonstrating an interaction between P2X4Rs and DA receptors in PPI regulation. On the basis of these findings, we hypothesized that increased DA neurotransmission underlies IVM-mediated PPI deficits. To test this hypothesis, we measured the effects of D1 and D2 receptor antagonists, SCH 23390 and raclopride respectively and D1 agonist, SKF 82958 on IVM-mediated PPI deficits. To gain mechanistic insights, we investigated the interaction between IVM and dopaminergic drugs on signaling molecules linked to PPI regulation in the ventral striatum. SCH 23390 significantly attenuated the PPI disruptive effects of IVM to a much greater degree than that of raclopride. SKF 82958 failed to potentiate IVM-mediated PPI disruption. At the molecular level, modulation of D1 receptors altered IVM’s effects on dopamine and cyclic-AMP regulated phosphoprotein of 32 kDa (DARPP-32) phosphorylation. Additionally, IVM interacted with the DA receptors antagonists and SKF 82958 in phosphorylation of Ca2+/calmodulin kinase IIα (CaMKIIα) and its downstream target, neuronal nitric oxide synthase (nNOS). Current findings suggest an involvement for D1 and D2 receptors in IVM-mediated PPI disruption via modulation of DARPP-32, CaMKIIα and nNOS. Taken together, the findings suggest that stimulation of P2X4Rs can lead to DA hyperactivity and disruption of information processing, implicating P2X4Rs as a novel drug target for treatment of psychiatric disorders characterized by sensorimotor gating deficits.
Deep learning and structured data

In the recent years deep learning has witnessed successful applications in many different domains such as visual object recognition, detection and segmentation, automatic speech recognition, natural language processing, and reinforcement learning. In this thesis, we will investigate deep learning from a spectrum of different perspectives. First of all, we will study the question of generalization, which is one of the most fundamental notion in machine learning theory. We will show how, in the regime of deep learning, the characterization of generalization becomes different from the conventional way, and propose alternative ways to approach it. Moving from theory to more practical perspectives, we will show two different applications of deep learning. One is originated from a real world problem of automatic geophysical feature detection from seismic recordings to help oil & gas exploration; the other is motivated from a computational neuroscientific modeling and studying of human auditory system. More specifically, we will show how deep learning could be adapted to play nicely with the unique structures associated with the problems from different domains. Lastly, we move to the computer system design perspective, and present our efforts in building better deep learning systems to allow efficient and flexible computation in both academic and industrial worlds. Thesis Supervisor: Tomaso Poggio Title: Eugene McDermott Professor of Brain and Cognitive Sciences
Modeling of natural stimulus representation in the human brain using canonical correlation analysis

Author(s): Bilenko, Natalia Yurievna | Advisor(s): Gallant, Jack L | Abstract: Understanding the representation of natural stimuli in the human brain is one of the fundamental goals of neuroscience. In this dissertation, I describe an unsupervised learning approach for investigating BOLD (blood oxygen level dependent) responses throughout the cortex to natural movies and speech. This approach for data-driven learning of representational features is particularly useful for regions of the brain where the features aren't well understood.First, I describe Python software for canonical correlation analysis called Pyrcca, developed for implementing this approach. Then, I introduce a method called FISCA (functional inter-subject component analysis). FISCA uses canonical correlation analysis to estimate components of BOLD responses based on cross-subject similarity. FISCA can be used for combining data across subjects according to functional and not anatomical similarity. FISCA predictively models BOLD responses to novel stimuli across subjects and allows accurate identification of stimulus timepoints based on these predictions.FISCA components are interpretable. For both natural movie and natural story experiments, I visualize the components on the cortical surface to characterize the role of each component in explaining representation in different brain areas. I also compute the tuning of each component for low-level visual and semantic features. FISCA components are stimulus-agnostic. I demonstrate how FISCA can be used to identify amodal regions by combining data between natural movie and speech experiments.FISCA is an accurate, flexible, and extensible unsupervised method for modeling brain responses to natural stimuli. Using this approach, I uncover representation of natural visual and speech stimuli throughout the cortex. I hope that in the future, this approach will be used for creating more accurate models and improving our understanding of cortical processing.