Miracle-dz/UniFAR-FTUs huggingface dataset:
Presymptomatic Treatment With Andrographolide Improves Brain Metabolic Markers and Cognitive Behavior in a Model of Early-Onset Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common type of dementia. The onset and progression of this pathology are correlated with several changes in the brain, including the formation of extracellular aggregates of amyloid-beta (Aβ) peptide and the intracellular accumulation of hyperphosphorylated tau protein. In addition, dysregulated neuronal plasticity, synapse loss, and a reduction in cellular energy metabolism have also been described. Canonical Wnt signaling has also been shown to be downregulated in AD. Remarkably, we showed previously that the in vivo inhibition of Wnt signaling accelerates the appearance of AD markers in transgenic (Tg) and wild-type (WT) mice. Additionally, we found that Wnt signaling stimulates energy metabolism, which is critical for the ability of Wnt to promote the recovery of cognitive function in AD. Therefore, we hypothesized that activation of canonical Wnt signaling in a presymptomatic transgenic animal model of AD would improve some symptoms. To explore the latter, we used a transgenic mouse model (J20 Tg) with mild AD phenotype expression (high levels of amyloid aggregates) and studied the effect of andrographolide (ANDRO), an activator of canonical Wnt signaling. We found that presymptomatic administration of ANDRO in J20 Tg mice prevented the reduction in cellular energy metabolism markers. Moreover, treated animals showed improvement in cognitive performance. At the synaptic level, J20 Tg animals showed severe deficiencies in presynaptic function as determined by electrophysiological parameters, all of which were completely restored to normal by ANDRO administration. Finally, an analysis of hippocampal synaptosomes by electron microscopy revealed that the length of synapses was restored with ANDRO treatment. Altogether, these data support the idea that the activation of canonical Wnt signaling during presymptomatic stages could represent an interesting pharmacological strategy to delay the onset of AD.
Discordant attributes of structural and functional connectivity in a two-layer multiplex network

Several studies have suggested that functional connectivity (FC) is constrained by the underlying structural connectivity (SC) and mutually correlated. However, not many studies have focused on differences in the network organization of SC and FC, and on how these differences may inform us about their mutual interaction. To explore this issue, we adopt a multi-layer framework, with SC and FC, constructed using Magnetic Resonance Imaging (MRI) data from the Human Connectome Project, forming a two-layer multiplex network. In particular, we examine whether node strength assortativity within and between the SC and FC layer may confer increased robustness against structural failure. We find that, in general, SC is organized assortatively, indicating brain regions are on average connected to other brain regions with similar node strengths. On the other hand, FC shows disassortative mixing. This discrepancy is apparent also among individual resting-state networks within SC and FC. In addition, these patterns show lateralization, with disassortative mixing within FC subnetworks mainly driven from the left hemisphere. We discuss our findings in the context of robustness to structural failure, and we suggest that discordant and lateralized patterns of associativity in SC and FC may explain laterality of some neurological dysfunctions and recovery.
Impact of the pulvinar on the ventral pathway of the cat visual cortex

iii Table of contents . v List of Tables . vii List of Figures . viii Abbreviations . xi Acknowledgements . xiv Introduction . 1 1 The organization of the visual system . 2 2 Visual cortex . 5 2.1 The primary visual cortex . 6 2.2 The neuron receptive field . 7 2.2.1 The reverse correlation method . 10 2.3 The response to contrast. 14 3 The cortical hierarchy . 17 3.1 The dorsal visual stream . 20 3.2 The ventral visual stream . 21 3.2.1 The cat area 21a . 22 3.3 Perception and action . 24 4 The visual thalamus . 25 4.1 Drivers and modulators . 26 4.2 First and higher order thalamic nuclei . 29 4.2.1 Higher order nuclei and the transthalamic pathway . 30 4.3 The pulvinar . 32 4.3.1 The primate pulvinar . 33 4.3.2 The cat pulvinar . 37
Immunological Study of Responses to a Meningococcal Antigen Using a Multiplex Antibody Binding Assay

Neisseria meningitidis is an important human pathogen and a major cause of septicaemia and meningitis worldwide. The immunodominant antigen of N. meningitidis is the highly variable OMP, PorA and detection of serum anti-PorA antibodies (IgG) is classically performed through use of the enzyme-linked immunosorbent assay (ELISA). Whilst sensitive and reliable, these methods are labour and reagent intensive particularly for detection of multiple anti-PorA antibodies within a single serum sample. This thesis describes the development and evaluation of an assay for simultaneous detection of antibodies directed to eight serosubtypes of PorA. A panel of purified meningococcal proteins were developed including seven serosubtypes of PorA along with a variable regions 1 and 2 deleted mutant; three serotypes of PorB and five variants of FetA. PorA proteins were conjugated to fluorescent microsphere sets and assessed using serum from a range of sources including preclinical and clinical trials and carriage and seroepidemiology studies. No evidence of microsphere interference was observed between monoplex and multiplex assays over a range of dilutions. The multiplex assay was specific; sensitive, with low limits of detection (<176.88 pg/ml); and reproducible for the measurement of serotype specific anti-PorA antibodies, with low intra- and inter-assay variability. Increases in serum IgG against specific PorA serosubtypes were detected using the assay in serum from a range of sources. However with the complexity of adult serum, it is difficult to distinguish between pre-existing and induced responses and may result in what appear to be non-specific responses. Lack of a suitable human standard has hindered the quantification of antibodies and an arbitrary concentration was assigned for each PorA serosubtype. However, advantages of small sera volumes, high throughput of sera, simplicity of the assay, and the ability to extend the assay, make the PorA multiplex assay a viable alternative to the standard ELISA.
Subjective contours are useful for extracting contours with very weak contrasts

Certain figures cause one to perceive clearly visible contours (subjective contours) in the region where there are no physical contrasts in brightness or color. An algorithm is proposed for generating subjective contours automatically from given figures. The algorithm is based on the following idea: 'L' or 'I' type vertices are produced on physical contours because they are occluded by a subjectively perceived plane. And these vertices are candidate points where subjective contours will pass. Then pairs of points to be filled in with subjective contours are determined according to factors of proximity and similarity in Gestalt's rules. The algorithm was implemented as a procedure reflecting neurophysiological and perceptual findings and applied to typical figures successfully. Furthermore, the algorithm was applied to real images where leaves overlapped one another with extremely feeble inner contours. The algorithm could extract the inner contours and separate each leaf.
Single Cell Pluripotency Regulatory Networks

Embryonic stem (ES) cells represent a popular model system for investigating development, tissue regeneration and repair. Although much is known about the molecular mechanisms that regulate the balance between self-renewal and lineage commitment in ES cells, the spatiotemporal integration of responsive signalling pathways with core transcriptional regulatory networks are complex and only partially understood. Moreover, measurements made on populations of cells reveal only average properties of the underlying regulatory networks, obscuring their fine detail. Here, we discuss the reconstruction of regulatory networks in individual cells using novel single cell transcriptomics and proteomics, in order to expand our understanding of the molecular basis of pluripotency, including the role of cell-cell variability within ES cell populations, and ways in which networks may be controlled in order to reliably manipulate cell behaviour.
Purification and characterization of a-amylase from Paenibacillus sp. D9 and Escherichia coli recombinants

The aim of this study was to purify and characterize a-amylase of Paenibacillus species D9 and cloned a-amylase in Escherichia coli transformants. Optimal growth and production of D9 a-amylase were obtained after the 24-h incubation period, at pH 7, 30 C and 200 rpm, using starch as the sole carbon source. Sodium nitrate stimulated a-amylase production by 3 folds while urea had an inhibitory effect comparing with yeast extract as the control. Characterization results of the crude and purified enzyme were similar. Purified D9 a-amylase possessed 97% residual activity after incubation at 30 C for 120min while 50% at 45 C and 27% at 60 C, respectively, under the same condition. The presence of Ca2þ ions enhanced the activity, while EDTA and Fe3þ had an inhibitory effect. Kinetic parameters were obtained having values of 37.3mM, 19.8U/mg and 4.84 s 1 for Km, Vmax and kcat, respectively. The a-amylase gene (amyS) of Paenibacillus sp. D9 was amplified using polymerase chain reaction (1482bp), cloned into PSF-OXB20 vector and expressed in E. coli BL21 DE3 (pLysS) after transformation. The a-amylase purified from the transformant using a Hispur Cobalt column possessed 1.4 folds (450.8U/mg) higher specific activity than the purified a-amylase from the wild type. Cloned a-amylase was more thermostable at 45 C and at 60 C, but less pH stable at pH 5 and 6. All other biochemical properties of the native and recombinant a-amylase show no significant differences. In conclusion, a-amylase of Paenibacillus sp. D9 was purified, cloned and characterized. The potential biotechnological application(s) of a-amylase may be explored. ARTICLE HISTORY Received 17 February 2019 Revised 24 May 2019 Accepted 3 June 2019
Consumption of cranberry powder shifts urinary protein profile in healthy human subjects

We hypothesize that consumption of cranberry products containing A‐type proanthocyanidins (PAC) modulates expression of endogenous proteins by cells of the urinary tract. Urine samples at baseline and post 7 day consumption of cranberry powder (36mg PAC equivalent/day) were collected from ten human subjects. We performed liquid chromatography mass spectrometry (LC‐MS/MS) analysis on an LTQ Orbitrap to monitor changes in urinary proteome in response to cranberry powder consumption. This new method has advantages over the classical proteomic approach in that it allows for the detection and determination of relative ratios of a large number of proteins. Supplementation of cranberry powder resulted in statistically significant lowering of eight proteins/peptides in the urine. The identification of these proteins in context of cranberry powder supplementation serves as a novel discovery using a unique LD‐MS/MS methodological approach to assess shifts in urinary proteome. Many of these proteins seem to play regulatory role in immune processes and tumorigenesis. Additionally, the methodology utilized in this discovery phase only provides a semi‐quantitative assessment of the shifts in the urinary proteome that occurred. Support for this research was provided by Ocean Spray Cranberries, Inc. and Complete Phytochemical Solutions, LLC.
DPPA2 and DPPA4 are necessary to establish a totipotent state in mouse embryonic stem cells

After fertilization of the transcriptionally silent oocyte, expression from both parental chromosomes is launched through so-called zygotic genome activation (ZGA), occurring in the mouse at the 2-cell stage. Amongst the first elements to be transcribed are the Dux gene, the product of which secondarily induces a wide array of ZGA genes, and a subset of evolutionary recent LINE-1 retrotransposons, which regulate chromatin accessibility in the early embryo. The maternally-inherited factors that activate Dux and LINE-1 transcription have so far remained unknown. Here we identify the paralog proteins DPPA2 and DPPA4 as responsible for this process.
A case study of an expert mathematics teacher's interactive decision-making system using physiological and behavioral time series data

A Case Study of an Expert Mathematics Teacher’s Interactive Decision-Making System Using Physiological and Behavioral Time Series Data. (December 2004) Deborah Larkey Jensen, B.A., University of California at Los Angeles; M.A., University of Hartford Chair of Advisory Committee: Dr. Carol Stuessy The purpose of this exploratory case study was to describe an expert teacher’s decisionmaking system during interactive instruction using teacher self-report information, classroom observation data, and physiological recordings. Timed recordings of instructional interaction variables using an adapted Stallings Observation System were combined with simultaneous skin voltage measurements in time series analyses to describe observable and physiological elements of an expert teacher’s decision-making process. The mean and standard deviation of observable decision-action rates on teacheridentified “teaching days” were higher than the rates on “guiding” days. Bivariate time series analysis of decision-action rates and physiological response rates showed a significant positive relationship between the teacher’s decision-action rate and her physiological response rate on one teaching day. The positive relationship between the teacher’s decision-action rate and her physiological response rate was found to be context-dependent and related to the teaching strategy being used. High decision-action rates during direct instruction were associated with high physiological response rates compared to lower decision-action rates and physiological response rates while monitoring independent seatwork during a test. Correlation analysis of physiological
DNA shape complements sequence-based representations of transcription factor binding sites

The position weight matrix (PWM) has long been a useful tool for describing variation in the composition of regions of DNA such as transcription factor (TF) binding sites. It is difficult, however, to relate the sequence-based representation of a DNA motif to the biological features of the interaction of a TF with its binding site. Here we present an alternative strategy for representing DNA motifs – called Structural Motif (StruM) – that can easily represent different sets of structural features. Structural features are inferred from dinucleotide properties listed in the Dinucleotide Property Database. StruMs are able to specifically model TF binding sites, using an encoding strategy that is distinct from sequence-based models. This difference in encoding strategies makes StruMs complementary to sequence-based methods of TF binding site identification.
Molecular Docking Studies of Phenolic Compounds from Syzygium cumini with Multiple Targets of Type 2 Diabetes

Diabetes mellitus (or simply diabetes) is a long-lasting disorder of food metabolism characterized by hyperglycemia, originating due to defect in insulin secretion, insulin function or both leading to tissue and vascular damage and resulting in a variety of complications (Bastaki, 2005; Cade, 2008; Grewal et al., 2014; Grewal et al., 2016). It is currently one of the largest global health emergencies; according to the International Diabetes Federation, in 2017 there were 425 million adults estimated to have diabetes, and the number is likely to reach 629 million by 2045 (IDF). Type 2 diabetes (T2D) affecting more than 90% of all the diabetic patients, is a long-term disordered food metabolism caused by declined insulin action (Kohei, 2010; Olokoba et al., 2012). Although a variety of medicines are available for T2D therapeutics, no single drug is useful for achieving long-term control of normal blood glucose levels in majority of patients. Due to this reason, general practitioners prescribe combination of antidiabetic agents for T2D therapy and overdose of antidiabetic medicines could lead to severe hypoglycemia resulting in brutal toxic and side effects. This caused the scientific community to search for new antidiabetic drugs (Olokoba et al., 2012; Osadebe et al., 2014). Large numbers of plants and parts of plants were reported with their antidiabetic properties. Various types of plant-derived active principles representing several bioactive compounds have established their beneficial role for possible use in T2D therapeutics (Patil et al., 2011; Ibrahim et al., 2013; Kumar et al., 2012). Syzygium cumini (Linn.) is an economically important tropical fruit tree belonging to the family Myrtaceae largely grown in Indian subcontinent along with some other parts of South Asia including Bangladesh, Sri Lanka, Nepal, Pakistan, Burma and Indonesia. It is also cultivated in some parts of Africa and South America (Swami et al., 2012; Srivastava and Chandra, 2013). It is commonly known as jamun in India, black plum in Europe, jambolan in Spanish spoken countries, and Jambolac in Brazil. It is also known as java plum, Indian blackberry, Portuguese plum, Malabar plum, purple plum, Jamaica and damson plum (Ayyanar and Subash-Babu, 2012; Chagas et al., 2015). Various types of secondary metabolites like flavonoids (quercetin, rutin, catechin, kaempferol, myricetin, isoquercetin, Molecular Docking Studies of Phenolic Compounds from Syzygium cumini with Multiple Targets of Type 2 Diabetes
Characterization of Bioinformatics Applications on Multimedia Processor

The explosive growth in size of genomic data and increase in computational complexity of bioinformatics applications has fueled the issue of appropriate underlying hardware architecture choice. Another impediment is the latest trend towards handheld/mobile bio-computational devices. One of the most critical factors holding back mobile computing is the perfect match between hardware architecture and application expression profile (AEP). This paper analyzes AEP for several bioinformatics application on a high end processor. We found that the synergy of bio-applications and hardware architecture is hampered by many debilitating factors, such as application algorithm, input sequences, architecture constraints, to name just a few. The result of the proposed approach are measured at our profile monitor framework that characterize static and dynamic behavior of bioinformatics applications based on instruction profile, scheduling factor, slot utilization, and on-chip/off-chip memory usage. Experimental results show very high applicationarchitecture correlation between our target platform (Nexperia PNX1302) and well known applications such as NetPlanGene (87%), Manfinder (92%), Fgene (82%), GlimmerHMM (68%) and Mummer (75%). Impact of different bio-computing algorithms on cache performance is also studied. The result is important for developing general methodology for highly efficient handheld bioinformatics devices.
Control of Generalized Energy Storage Networks

The integration of intermittent and volatile renewable energy resources requires increased flexibility in the operation of the electric grid. Storage, broadly speaking, provides the flexibility of shifting energy over time; network, on the other hand, provides the flexibility of shifting energy over geographical locations. The optimal control of general storage networks in uncertain environments is an important open problem. The key challenge is that, even in small networks, the corresponding constrained stochastic control problems with continuous spaces suffer from curses of dimensionality, and are intractable in general settings. For large networks, no efficient algorithmis known to give optimal or near-optimal performance. This paper provides an efficient and provably near-optimal algorithm to solve this problem in a very general setting. We study the optimal control of generalized storage networks, i.e., electric networks connected to distributed generalized storages. Here generalized storage is a unifying dynamic model for many components of the grid that provide the functionality of shifting energy over time, ranging from standard energy storage devices to deferrable or thermostatically controlled loads. An online algorithm is devised for the corresponding constrained stochastic control problem based on the theory of Lyapunov optimization. We prove that the algorithm is near-optimal, and construct a semidefinite program to minimize the sub-optimality bound. The resulting bound is a constant that depends only on the parameters of the storage network and cost functions, and is independent of uncertainty realizations. Numerical examples are given to demonstrate the effectiveness of the algorithm.
Diagnostic Assessment of Osteosarcoma Chemoresistance Based on Virtual Clinical Trials

Osteosarcoma is the most common primary bone tumor in pediatric and young adult patients. Successful treatment of osteosarcomas requires a combination of surgical resection and systemic chemotherapy, both neoadjuvant (prior to surgery) and adjuvant (after surgery). The degree of necrosis following neoadjuvant chemotherapy correlates with the subsequent probability of disease-free survival. Tumors with less than 10% of viable cells after treatment represent patients with a more favorable prognosis. However, being able to predict early, such as at the time of the pre-treatment tumor biopsy, how the patient will respond to the standard chemotherapy would provide an opportunity for more personalized patient care. Patients with unfavorable predictions could be studied in a protocol, rather than a standard setting, towards improving therapeutic success. The onset of necrotic cells in osteosarcomas treated with chemotherapeutic agents is a measure of tumor sensitivity to the drugs. We hypothesize that the remaining viable cells, i.e., cells that have not responded to the treatment, are chemoresistant, and that the pathological characteristics of these chemoresistant tumor cells within the osteosarcoma pre-treatment biopsy can predict tumor response to the standard-of-care chemotherapeutic treatment. This hypothesis can be tested by comparing patient histopathology samples before, as well as after treatment to identify both morphological and immunochemical cellular features that are characteristic of chemoresistant cells, i.e., cells that survived treatment. Consequently, using computational simulations of dynamic changes in tumor pathology under the simulated standard of care chemotherapeutic treatment, one can couple the pre- and post-treatment morphological and spatial patterns of chemoresistant cells, and correlate them with patient clinical diagnoses. This procedure, that we named ‘Virtual Clinical Trials’, can serve as a potential predictive biomarker providing a novel value added decision support tool for oncologists.