Nano‐encapsulated Tinospora cordifolia (Willd.) using poly (D,L‐lactide) nanoparticles educe effective control in streptozotocin‐induced type 2 diabetic rats

The therapeutics for type 2 diabetes mellitus has emerged in the current century towards nanomedicine incorporated with plant active compounds. In this study, Tinospora cordifolia loaded poly (D, L‐lactide) (PLA) nanoparticles (NPs) were evaluated in vivo for their anti‐hyperglycemic potency towards streptozotocin‐induced type 2 diabetic rats. T. cordifolia loaded PLA NPs were synthesised by the double solvent evaporation method using PLA polymer. The NPs were then characterised and administrated orally for 28 successive days to streptozotocin‐induced diabetic rats. The PLA NPs had significant anti‐diabetic effects which were equal to the existing anti‐diabetic drug glibenclamide. The antidiabetic activity is due to the synergism of compounds present in stem extract of the plant which reduced the side effects and anti‐diabetic.Inspec keywords: blood, nanofabrication, drug delivery systems, biochemistry, evaporation, nanoparticles, nanomedicine, drugs, diseases, polymers, biomedical materialsOther keywords: PLA nanoparticles, antidiabetic effects, nanoencapsulated Tinospora cordifolia, streptozotocin‐induced type 2 diabetic rats, type 2 diabetes mellitus, poly(d, l‐lactide) nanoparticles, diabetic drug glibenclamide, nanomedicine, antihyperglycemic potency, double‐solvent evaporation     

The Aceh Besar midwives with mobile phones project: Design and evaluation perspectives using the information and communication technologies for healthcare development model

The introduction of information and communication technologies (ICT) such as mobile phones to basic health service providers in rural areas can help bridge lacunae in their work environment, resulting from under‐capacitated resources, constrained access to information and delayed interventions. The midwife mobile phone project was implemented in 15 health centres in Aceh Besar, Indonesia involving 223 midwives. The study group (121 participants) used project cell phones to transmit health statistics to a central database, contact coordinators and peers for health advice and information, and communicate with doctors and patients. The ICT for healthcare development model (Author, Lwin, Ang, Lin, & Santoso, 2008) was used a heuristic to determine project effectiveness. Findings from the project indicate that the mobile phone has proven to be an effective and efficient device for facilitating smoother communication, and allowing speedier emergency response. The system also aids in gathering and disseminating health‐related information to midwives, who in turn convey this knowledge to the patient community. The Technology‐Community‐Management model (Author & Zhao, 2009; Lee & Author, 2008) was used as a conceptual framework for probing the design of ICT for development projects. In particular, infrastructural, economic, technological, and socio‐cultural barriers were examined to highlight the tension between a top‐down hierarchical model of technology diffusion versus a more participatory bottom‐up approach.     

Molecular Characterization of a Rare Case of Bilateral Vitreoretinal T Cell Lymphoma through Vitreous Liquid Biopsy

Vitreoretinal lymphoma (VRL) is an uncommon eye malignancy, and VRLs of T cell origin are rare. They are difficult to treat, and their molecular underpinnings, including actionable genomic alterations, remain to be elucidated. At present, vitreous fluid liquid biopsies represent a valuable VRL sample for molecular analysis to study VRLs. In this study, we report the molecular diagnostic workup of a rare case of bilateral T cell VRL and characterize its genomic landscape, including identification of potentially targetable alterations. Using next-generation sequencing of vitreous-derived DNA with a pan-cancer 126-gene panel, we found a copy number gain of BRAF and copy number loss of tumor suppressor DNMT3A. To the best of our knowledge, this represents the first exploration of the T cell VRL cancer genome and supports vitreous liquid biopsy as a suitable approach for precision oncology treatments.     

A prediction model for the loading-wetting volumetric behavior of unsaturated granular materials

Geotechnical structures made of granular material tend to be unsaturated during their service life. However, there is presently a lack of sufficient research and studies on their volumetric behavior under unsaturated conditions. In this study, loading and wetting induced volumetric behavior of granular materials in the unsaturated state was studied within a moisture content-based framework. Recycled crushed brick (CB) and excavation waste rock (WR) were the granular materials used in this research to promote sustainable construction. Several loading, unloading, and wetting state paths were investigated with respect to virgin compaction surfaces (VCS) developed using groups of compaction curves. The obtained experimental data was utilized to develop a constitutive model capable of predicting wetting-induced volume changes of granular materials in a net stress range of 100–4000 kPa and gravimetric moisture content range of 3.6% for WR, and 7.5% for CB to saturation. The model was verified by undertaking several independent state paths on independent materials and comparing the experimental responses with those predicted using the model. The proposed model is featured with simplicity in acquiring the model input parameters with the aim of filling the existing gap between the theoretical and real-life application of unsaturated soil mechanics. An application of the model can be the basis for the prediction of the settlement of a granular geotechnical structure that is being externally loaded and is subject to changes in moisture content due to climatic effects.     

Variable reference alignment: an improved peak alignment protocol for NMR spectral data with large intersample variation

In an effort to address the variable correspondence problem across large sample cohorts common in metabolomic/metabonomic studies, we have developed a prealignment protocol that aims to generate spectral segments sharing a common target spectrum. Under the assumption that a single reference spectrum will not correctly represent all spectra of a data set, the goal of this approach is to perform local alignment corrections on spectral regions which share a common "most similar" spectrum. A natural beneficial outcome of this procedure is the automatic definition of spectral segments, a feature that is not common to all alignment methods. This protocol is shown to specifically improve the quality of alignment in (1)H NMR data sets exhibiting large intersample compositional variation (e.g., pH, ionic strength). As a proof-of-principle demonstration, we have utilized two recently developed alignment algorithms specific to NMR data, recursive segment-wise peak alignment and interval correlated shifting, and applied them to two data sets composed of 15 aqueous cell line extract and 20 human urine (1)H NMR profiles. Application of this protocol represents a fundamental shift from current alignment methodologies that seek to correct misalignments utilizing a single representative spectrum, with the added benefit that it can be appended to any alignment algorithm.     

Protective role of biosynthesised zinc oxide nanoparticles on pancreatic beta cells: an in vitro and in vivo approach

Sulphonylureas are extensively used in the treatment of type II diabetes; however, these drugs have complications of hypoglycaemia and weight gain. The current study aims at developing a potent antidiabetic drug that has lesser side effects and better management of its associated conditions. Zinc oxide nanoparticles (ZnO NPs) were synthesised using Syzygium cumini seed extract with an average size of 18.92 nm. In vitro studies on rat insulinoma (RIN‐5F) cells revealed that cells treated with synthesised ZnO NPs showed a dose‐dependent increase in insulin secretion. Streptozotocin‐fructose‐induced type II diabetic rats treated with ZnO NPS exhibited a significant reduction (p  < 0.01) in the blood glucose levels, total cholesterol, triglycerides, and low‐density lipoprotein levels and increase (p  < 0.01) in serum insulin and liver antioxidant enzyme levels proclaiming its role as a hypoglycaemic and hypolipidaemic drug. Treatment of ZnO NPs in diabetic rats exhibited an increased number of beta cells which was responsible for its increased insulin levels and reduced glucose levels. From the overall observations, biosynthesised ZnO NPs exhibited an efficacious hypoglycaemic effect in diabetic rats, so it can be suggested as a potent antidiabetic drug.Inspec keywords: biochemistry, II‐VI semiconductors, drug delivery systems, drugs, patient treatment, blood, enzymes, zinc compounds, molecular biophysics, sugar, cellular biophysics, nanofabrication, liver, nanoparticles, diseases, biomedical materials, nanomedicineOther keywords: protective role, biosynthesised zinc oxide nanoparticles, pancreatic beta cells, vivo approach, type II diabetes, drugs, hypoglycaemia, weight gain, potent antidiabetic drug, lesser side effects, associated conditions, Syzygium cumini seed, rat insulinoma, synthesised ZnO NPs, dose‐dependent increase, insulin secretion, streptozotocin‐fructose‐induced type II diabetic rats, blood glucose levels, low‐density lipoprotein levels, serum insulin, liver antioxidant enzyme levels, hypoglycaemic drug, hypolipidaemic drug, increased insulin levels, reduced glucose levels, biosynthesised ZnO NPs, efficacious hypoglycaemic effect, size 18.92 nm, temperature 5.0 F, ZnO     

Data-driven construction of Convex Region Surrogate models

With the increasing trend of solving more complex and integrated optimization problems, there is a need for developing process models that are sufficiently accurate as well as computationally efficient. In this work, we develop an algorithm for the data-driven construction of a type of surrogate model that can be formulated as a set of mixed-integer linear constraints, yet still provide good approximations of nonlinearities and nonconvexities. In such a surrogate model, which we refer to as Convex Region Surrogate (CRS), the feasible region is given by the union of convex regions in the form of polytopes, and for each region, the corresponding cost function can be approximated by a linear function. The general problem is as follows: given a set of data points in the parameter space and a scalar cost value associated with each data point, find a CRS model that approximates the feasible region and cost function indicated by the given data points. We present a two-phase algorithm to solve this problem and demonstrate its effectiveness with an extensive computational study as well as a real-world case study.