Scalable Probabilistic Model Selection for Network Representation Learning in Biological Network Inference

A biological system is a complex network of heterogeneous molecular entities and their interactions contributing to various biological characteristics of the system. Although the biological networks not only provide an elegant theoretical framework but also offer a mathematical foundation to analyze, understand, and learn from complex biological systems, the reconstruction of biological networks is an important and unsolved problem. Current biological networks are noisy, sparse and incomplete, limiting the ability to create a holistic view of the biological reconstructions and thus fail to provide a system-level understanding of the biological phenomena. Experimental identification of missing interactions is both time-consuming and expensive. Recent advancements in high-throughput data generation and significant improvement in computational power have led to novel computational methods to predict missing interactions. However, these methods still suffer from several unresolved challenges. It is challenging to extract information about interactions and incorporate that information into the computational model. Furthermore, the biological data are not only heterogeneous but also high-dimensional and sparse presenting the difficulty of modeling from indirect measurements. The heterogeneous nature and sparsity of biological data pose significant challenges to the design of deep neural network structures which use essentially either empirical or heuristic model selection methods. These unscalable methods heavily rely on expertise and experimentation, which is a time-consuming and error-prone process and are prone to overfitting. Furthermore, the complex deep networks tend to be poorly calibrated with high confidence on incorrect predictions. In this dissertation, we describe novel algorithms that address these challenges. In Part I, we design novel neural network structures to learn representation for biological entities and further expand the model to integrate heterogeneous biological data for biological interaction prediction. In part II, we develop a novel Bayesian model selection method to infer the most plausible network structures warranted by data. We demonstrate that our methods achieve the state-of-the-art performance on the tasks across various domains including interaction prediction. Experimental studies on various interaction networks show that our method makes accurate and calibrated predictions. Our novel probabilistic model selection approach enables the network structures to dynamically evolve to accommodate incrementally available data. In conclusion, we discuss the limitations and future directions for proposed works

Anomalous Thermoelectric power of over-doped Bi2Sr2CaCu2O8 superconductor

Temperature dependence of thermoelectric power S(T) of three differently processed Bi2Sr2CaCu2O8 (Bi2212) samples, viz. as-processed melt quenched (Bi2212-MQ), 6000C N2-annealed (Bi2212-N2) and 6000C O2-annealed (Bi2212-O2) is reported here. All the samples possess single-phase character and their superconducting transition temperatures (TcR=0) are 85 K, 90 K and 72 K respectively for Bi2212-MQ, Bi2212-N2 and Bi2212-O2. While Bi2212-MQ and Bi2212-N2 samples are in near optimum doping regime, Bi2212-O2 is an over-doped sample. TcS=0 values obtained through S(T) data are also in line with those deduced from the temperature dependence of resistance and DC magnetization. Interestingly, S(T) behaviour of the optimally-doped Bi2212-MQ and Bi2212-N2 samples is seen to be positive in whole temperature range, it is found negative for the over-doped Bi2212-O2 sample above TcS=0. These results have been seen in the light of the recent band structure calculations and the ensuing split Fermi surface as determined by angle-resolved photoelectron spectroscopy (ARPES).Comment: 11 Pages Text + Figs: comments welcome ([email protected]

Prediction Criteria for Successful Weaning from Respiratory Support: Statistical and Connectionist Analyses

Objective: To develop predictive criteria for successful weaning from mechanical assistance to ventilation based upon simple clinical tests using discriminant analyses and neural network systems. Design: Retrospective development of predictive criteria and subsequent prospective testing of the same. Setting: Medical intensive care unit of a 300-bed teaching veterans administration hospital. Patients: Twenty-five ventilator-dependent elderly patients with acute respiratory failure. Interventions: Routine measurements of negative inspiratory force (NIF), tidal values (VT), minute ventilation (VE), respiratory rate (RR), vital capacity (FVC), and maximum voluntary ventilation (MVV), followed by weaning trial. Success or failure in 21 efforts analyzed by linear and quadratic discriminant model and neural network formulas to develop prediction criteria. The criteria so developed were tested for predictive power prospectively in nine trials in six patients. The analyses thus obtained predicted the success or failure of weaning within 9O-lOO% accuracy. Conclusion: Use of quadratic discriminant and neural network analyses could be useful in developing accurate predictive criteria for successful weaning based upon simple bedside measurements

A COMPREHENSIVE REVIEW ON PHARMACEUTICAL AND NUTRITIONAL APPLICATIONS OF INULIN

Inulin is a versatile, water-soluble polysaccharide that is commonly available in nature. In the pharmaceutical industry, the non-digestible function of inulin has made it attractive. Inulin is granted with GRAS status by the FDA and more than 30,000 plants in nature store inulin as a carbohydrate. The chicory is the key plant source of inulin out of all sources. It can be used as the sugar or fat replacer in the processed foods to influence the desirable characteristics. Good biocompatibility, essential chemical properties, and a wide variety of bioactivities have rendered inulin an outstanding natural nutrient. Regulating blood sugar, antioxidant, anticancer is some of the biological activities of inulin. Inulin can also be a carrier for colon/tumor targeting, as only specific enzymes in the colon zhydrolyze the inulin. It allows the growth of micro-flora, the good bacteria in the gut. Inulin is considered as a prebiotic as it is fermented by bacteria that normalize the colon. This review offers an in-depth insight into its novel Pharmaceutical applications as well as sources, processing, physicochemical properties, and nutritional and physiological activities. The chemically modified inulin is gaining a specific interest in the pharmaceutical field with its outstanding properties which are discussed in this review

Correlation between endothelial dysfunction, inflammatory status, oxidative stress and total (nitrite/ nitrate) in subjects with diabetes mellitus type 2

Background: Diabetes Mellitus is a systemic metabolic disorder associated with Endothelial dysfunction and increased systemic inflammatory state with oxidative stress leading to increased Cardiovascular risk. This study planned to correlate the level of Endothelial dysfunction with oxidative stress and inflammatory status.Methods: Study was conducted in 60 Diabetes Mellitus subjects of both genders with duration of more than two years. Endothelial dysfunction assessed as Augmentation Pressure and Augmentation Index generated from Radial artery waveforms by tonometer using Spygmocor PWA system. Plasma Total Nitrite/ Nitrate, High sensitive C - Reactive Protein, Malondialdehyde and Glutathione were measured.Results: Out of total 60 Diabetes Mellitus subjects 16 subjects were with Coronary Artery Disease. There was no significant difference in High sensitive C - Reactive Protein, Glutathione, Malondialdehyde and Total Nitrite/ Nitrate between Diabetes Mellitus with Coronary Artery Disease and without Coronary Artery Disease, however significant difference (p=0.02) was observed Augmentation Pressure between Diabetic alone (12.8±5.19 mm of Mercury) and diabetics with Coronary Artery Disease (16.13±33.47 mm of Mercury) and Augmentation Index (p=0.04) between Diabetic alone (29.8±5.68 mm of Mercury) and diabetics with Coronary Artery Disease (40.01±5.74). As endothelial function is age dependent the subjects were divided into three age groups (20-40 years, 40-60 years and more than 60 years). High sensitive C - Reactive Protein, Glutathione, Malondialdehyde, Total Nitrite/ Nitrate and Augmentation Index did not differ in the three age groups while Augmentation Pressure (p=0.0096) showed significant difference between age group 20-40 years (10.59±3.24) and age group more than 60 years (15.83±3.92).Conclusions: There is significant endothelial dysfunction observed in Diabetes Mellitus subjects and Diabetes Mellitus with coronary artery disease showed greater endothelial dyfunction. Thereby concluding that Diabetes Mellitus subjects were at higher risk for development of coronary artery disease and as endothelial dysfunction is an early event, it may have some prognostic value

Enhanced Room Temperature Coefficient of Resistance and Magneto-resistance of Ag-added La0.7Ca0.3-xBaxMnO3 Composites

In this paper we report an enhanced temperature coefficient of resistance (TCR) close to room temperature in La0.7Ca0.3-xBaxMnO3 + Agy (x = 0.10, 0.15 and y = 0.0 to 0.40) (LCBMO+Ag) composite manganites. The observed enhancement of TCR is attributed to the grain growth and opening of new conducting channels in the composites. Ag addition has also been found to enhance intra-granular magneto-resistance. Inter-granular MR, however, is seen to decrease with Ag addition. The enhanced TCR and MR at / near room temperature open up the possibility of the use of such materials as infrared bolometric and magnetic field sensors respectively.Comment: 22 pages of Text + Figs:comments/suggestions([email protected]

Structural and Magnetic Properties of MrSr₂Y₁.₅Ce₀.₅Cu₂Oz (M-1222) Compounds with M = Fe and Co

The MSr2Y1.5Ce0.5Cu2Oz (M-1222) compounds, with M = Fe and Co, have been synthesized through a solid-state reaction route. Both compounds crystallize in a tetragonal structure (space group 14/mmm). A Rietveld structural refinement of the room-temperature neutron diffraction data for Fe-1222 reveals that nearly half the Fe remains at the M site, while the other half goes to the Cu site in the CuO2 planes. Existence of Fe at two different lattice sites is also confirmed by 57Fe Mössbauer spectroscopy from which it is inferred that ~50% of the total Fe occupies the Cu site in the CuO2 planes as Fe3+, whereas the other ~50% is located at the M site with ~40% as Fe4+ and ~10% as Fe3+. For the M[Double Bond]Co compound, nearly 84% of Co remains at its designated M site, while the rest occupies the Cu site in the CuO2 planes

Razvoj i vrednovanje plutajućih tableta norfloksacina s produljenim zadržavanjem u želucu

Floating matrix tablets of norfloxacin were developed to prolong gastric residence time, leading to an increase in drug bioavailability. Tablets were prepared by the wet granulation technique, using polymers such as hydroxy propyl methylcellulose (HPMCK4M, HPMCK100M) and xanthan gum. Tablets were evaluated for their physical characteristics viz., hardness, thickness, friability, and mass variation, drug content and floating properties. Further, tablets were studied for in vitro drug release characteristics for 9 hours. The tablets exhibited controlled and prolonged drug release profiles while floating over the dissolution medium. Non-Fickian diffusion was confirmed as the drug release mechanism from these tablets, indicating that water diffusion and the polymer rearrangement played an essential role in drug release. The best formulation (F4) was selected based on in vitro characteristics and was used in vivo radiographic studies by incorporating BaSO4. These studies revealed that the tablets remained in the stomach for 180 ± 30 min in fasting human volunteers and indicated that gastric retention time was increased by the floating principle, which was considered desirable for absorption window drugs.Razvijene su plutajuće tablete norfloksacina koje se produljeno zadržavaju u želucu i time povećavaju bioraspoloživost. Tablete su pripravljene metodom vlažne granulacije, koristeći hidroksipropil metilcelulozu (HPMCK4M, HPMCK100M) i ksantan gumu. Tabletama su određena fizikalna svojstva (čvrstoća, debljina, lomljivost i varijacija mase) te sadržaj ljekovite tvari i plutajuća svojstva. Nadalje, praćeno je oslobađanje ljekovite tvari in vitro tijekom 9 h. Uočeno je da je oslobađanje kontrolirano i produljeno te da tablete plutaju u ispitivanom mediju. Mehanizam oslobađanja nije slijedio Fickov zakon, što ukazuje da difuzija vode i promjene u strukturi polimera imaju bitnu ulogu u oslobađanju ljekovite tvari. Najbolja formulacija (F4) in vitro uporabljena je s dodatkom barijevog sulfata za radiografska ispitivanja in vivo. Ispitivanja na volonterima koji su apstinirali od hrane pokazala su da primjena plutajućih tableta produljuje vrijeme zadržavanja u želucu na 180 ± 30 min

PI3-kinase mutation linked to insulin and growth factor resistance in vivo

The phosphatidylinositol 3-kinase (PI3K) signaling pathway is central to the action of insulin and many growth factors. Heterozygous mutations in the gene encoding the p85alpha regulatory subunit of PI3K (PIK3R1) have been identified in patients with SHORT syndrome - a disorder characterized by short stature, partial lipodystrophy, and insulin resistance. Here, we evaluated whether SHORT syndrome-associated PIK3R1 mutations account for the pathophysiology that underlies the abnormalities by generating knockin mice that are heterozygous for the Pik3r1Arg649Trp mutation, which is homologous to the mutation found in the majority of affected individuals. Similar to the patients, mutant mice exhibited a reduction in body weight and length, partial lipodystrophy, and systemic insulin resistance. These derangements were associated with a reduced capacity of insulin and other growth factors to activate PI3K in liver, muscle, and fat; marked insulin resistance in liver and fat of mutation-harboring animals; and insulin resistance in vitro in cells derived from these mice. In addition, mutant mice displayed defective insulin secretion and GLP-1 action on islets in vivo and in vitro. These data demonstrate the ability of this heterozygous mutation to alter PI3K activity in vivo and the central role of PI3K in insulin/growth factor action, adipocyte function, and glucose metabolism

Fecal microbiota transplant rescues mice from human pathogen mediated sepsis by restoring systemic immunity.

Death due to sepsis remains a persistent threat to critically ill patients confined to the intensive care unit and is characterized by colonization with multi-drug-resistant healthcare-associated pathogens. Here we report that sepsis in mice caused by a defined four-member pathogen community isolated from a patient with lethal sepsis is associated with the systemic suppression of key elements of the host transcriptome required for pathogen clearance and decreased butyrate expression. More specifically, these pathogens directly suppress interferon regulatory factor 3. Fecal microbiota transplant (FMT) reverses the course of otherwise lethal sepsis by enhancing pathogen clearance via the restoration of host immunity in an interferon regulatory factor 3-dependent manner. This protective effect is linked to the expansion of butyrate-producing Bacteroidetes. Taken together these results suggest that fecal microbiota transplantation may be a treatment option in sepsis associated with immunosuppression