European Journal of Molecular & Clinical Medicine

Despite of decades of research in conventional drug delivery systems many challenges are unconfronted in treatment of chronic diseases at a personalized medicine level. So there is a need for development of targeted and efficient drug delivery systems at such levels of treatment. Microelectromechanical systems have some unique characteristics like analyte sensitivity, electrical responsiveness, temporal control and sizes similar to cells and organelles that has led to engineering of implants for drug delivery in various chronic diseases.Targeting can be achieved through the use of this technology as the drugs are released at the site of action as well as in minimal effective concentrations, thus avoiding side-effects also. This review gives a general overview about the Bio Microelectromechanical systems used in targeting with some relevant examples. Hence Microelectromechanical systems prove to be a promising contender for development of drug delivery systems and targeting in pharmaceutical field.

Background
The Bone Morphogenetic Protein 4 (BMP4) is identified to play a significant role in cardiac remodelling; gene polymorphism and its resulting associations with Left Ventricular Hypertrophy (LVH) in diabetic Chronic Kidney Disease (CKD) patients of this protein are yet to be established. Aim To analyse the association between BMP4 gene polymorphism and LVH in diabetic CKD patients. Materials and methods Isolation of DNA from whole blood samples of 50 patients each; patients diagnosed LVH with diabetic CKD and also from LVH patients without diabetic CKD, diabetic CKD without LVH and also normal patients as control were extracted. The gene of interest (BMP4 gene) purified from various samples digested using zero-cutter restriction endonucleases (Hind III and Bam HI) by employing the Restriction Fragment Length Polymorphism (RFLP) technique. The restriction has been analysed using 1% agarose gel Electrophoresis.
Results
The gene from patient having LVH without diabetic CKD when digested with Hind III showed fragmentation, more specifically, it presented three/four fragments which were at a comparable distance corresponding with the following size reference markers at 2000 bp(few cases), 1500 bp, between 700–600 bp and the last one near 100 bp. This fragmentation pattern was repeated identically for the gene from blood sample of patient having LVH with diabetic CKD which was also digested with Hind III. A similar fragmentation was not visualized for sample from patient having diabetic CKD without LVH when digested with Hind III. But no such fragments were noted for the samples from the same patients when digested with Bam HI.
Conclusion
BMP4 gene polymorphism has been confirmed in patients having LVH regardless of the presence or absence of diabetic CKD along with it. Focal points • Benchside: Left ventricular (LV) hypertrophy is a strong autonomous predictor of increased cardiovascular morbidity and mortality in clinical and population-based samples. Thus understanding the correlation of LVH with BMP4 gene is necessitated to provide alternate therapeutics strategy at genome level. Eventually, genetic investigations provide high assurance for future prevention, early intervention and treatment of this major public health issue. • Bedside: Determination of BMP4 Polymorphism would raise a new drug development target using single nucleotide polymorphism. They also serve as molecular marker for next generation therapeutics of personalized medicine at genome level. • Community: The patient's therapeutic quality would be high due target specific approach with the understanding of personalized medicine. This can prevent unwanted treatment that can guide way to side-effects in the system. • Governments: Funding bodies should continue to acknowledge the importance that the BMP4 gene plays a role in LVH, which can be a causative agent for many other cardio-disorders. Overtime, this will help in benefiting patients and healthcare institutions.

Latest advances in genetics have prompted swift progress towards the efficient identification of genes tangled in complex diseases. Still, the comprehensive understanding of the relation between the physiological and molecular mechanism of genes and how they affect disease phenotypes remains a challenge for researchers and clinicians. Here, we wish to identify the osteoporosis disease module, i.e. the indigenous neighborhood of the interactome whose agitation is associated with osteoporosis, and endorse it for functional and pathophysiological application, using both computational and experimental methodologies. Recent studies in osteoporosis suggest that against certain genetic variations, the expression level of genes were different in both diseased and normal conditions. The osteoporosis disease module supplemented with uncertain GWAS p-values may also contain mechanisms that are collective with other disease modules. We, therefore, constructed the gene-gene and protein-protein interaction network for 104 genes with 173 reported SNPs accompanied by GO functional enrichment and KEGG pathway enrichment analysis and recognized the substantial genes of osteoporosis along with their molecular functions. Our analyses exposed polymorphism in SOST and LRP5 as significantly conservative SNPs. Focal points: • Benchside: Robust and concise curation of raw data for osteoporosis will help to make the presymptomatic data more valuable to perform wet lab studies. • Bedside: Bioinformatics network studies are crucial in finding drug targets so it becomes necessary to process the huge data for osteoporosis to curate and produce significance targets. Further, unpredicted pathways and genes could be explored to support clinical studies. • Industry: Data from disease network studies is essential for predicting clinical and non-clinical follow-ups for better drug development. • Community: Ratification and standardization of redundant osteoporosis and gene polymorphism data helps to improvise clinical validation of drug targets. It is important that the data is upto the proper stringency level. • Government: As for the ultimate purpose of drug development, refined gene expression data is the key in developing clinical products. Financial support from government to produce and validate such products is important as with time these will help both the patients and clinicians as well.

Background
Tobacco smoking is a major established risk factor for pancreatic cancer (PC), increasing the incidence up to six fold depending on the duration and intensity of smoking. Nicotine is a key toxin in tobacco and cigarette, which may contribute to development of pancreatitis and PC. Our previous studies revealed an aberrant expression of Pak1 in PC as compared to normal pancreas and its association with cancer progression, tumor angiogenesis, drug resistance and metastasis. Here, we explore a potential link between Pak1 expression and smoking-mediated PC pathogenesis and the use of Pak1 inhibitors to curtail this association. Methods Mia Pa Ca 2 cell line was obtained from NCCS, Pune and grown in the presence and absence of 0.5 μM (0.112 μg/ml) nicotine hemisulphate salt (5 h) and further nicotine exposed cells were treated with Pak1 inhibitor, IPA-3 (1 h). Protein, mRNA and kinase activity of Pak1 were evaluated. Using human pancreatic cancer tissue, mRNA from smokers (n = 10) and non –smokers (n = 10) were assessed for Pak1 expression.
Results
Nicotine significantly enhanced the expression and kinase activity of Pak1, with subsequent activation of NF-κB signalling cascade in cooperation with other pathways, this effect was blocked by IPA-3. Also, it was observed that pharmacological blockage or silencing of α7-nAChR abrogated nicotine mediated activation of Pak1/NF-κB. Additionally, we demonstrated up-regulated Pak1 mRNA expression in tissue sample from smokers compared to non-smokers.
Conclusion
Our findings suggest probable mechanism of action of nicotine through Pak1 signalling on PC pathogenesis and this could be targeted using Pak1 inhibitors for PC treatment.

Background
Sepsis is a medical emergency and a major public health concern for society. It is estimated that there are 18 million cases of sepsis annually, and in developing countries over 6 million neonates and children die each year[1]. Data from the US supports the fact that the incidence and mortality from sepsis is rising, which reflects a global trend[2–4]. Reasons for this increasing incidence is likely due to a combination of ageing populations with multiple co-morbidities, improved life expectancy from other diseases, rising prevalence of people taking immunosuppressants and escalating antibiotic resistance[5]. Analysis of sepsis in a worldwide audit of intensive care units found that mortality was as high as 30%[6]. Within the UK, sepsis costs the NHS £830 million a year directly and between 36,000-64,0000 deaths. When sensitivity analyses are applied the estimated annual cost of sepsis to the UK is over £10 billion. [7]

Current clinical practices focus on a small number of biochemical directly related to the pathophysiology with patients and thus only describe a very limited metabolome of a patient and fail to consider the interations of these small molecules. This lack of extended information may prevent clinicians from making the best possible therapeutic interventions in sufficient time to improve patient care. Various post-genomics ‘(’omic)’ approaches have been used for therapeutic interventions previously. Metabolomics now a well-established’omics approach, has been widely adopted as a novel approach for biomarker discovery and in tandem with genomics (especially SNPs and GWAS) has the potential for providing systemic understanding of the underlying causes of pathology. In this review, we discuss the relevance of metabolomics approaches in clinical sciences and its potential for biomarker discovery which may help guide clinical interventions. Although a powerful and potentially high throughput approach for biomarker discovery at the molecular level, true translation of metabolomics into clinics is an extremely slow process. Quicker adaptation of biomarkers discovered using metabolomics can be possible with novel portable and wearable technologies aided by clever data mining, as well as deep learning and artificial intelligence; we shall also discuss this with an eye to the future of precision medicine where metabolomics can be delivered to the masses.

HSA, IHS, and BBO algorithms are compared in this work for handling restricted economic load
dispatch issues in a power system with a limited number of available resources. New solution vectors
are generated using the IHS algorithm, which makes use of numerous harmony memory consideration
rates and dynamic pitch adjustment rates. They were tested in a test system with twenty producing units
with ramp rate restrictions and valve point loading constraints, and the algorithms worked well. IHS
approach outperforms both Harmony search and Biogeography-based optimization algorithm in terms
of total fuel cost and convergence characteristics, as shown by the simulation results.

Data sharing is a significant usefulness in distributed storage. In this article, we tell the best way to safely, proficiently, and deftly share information with others in distributed storage. We depict new open key cryptosystems which produce steady size ciphertexts with the end goal that effective appointment of decoding rights for any arrangement of ciphertexts are conceivable. The curiosity is that one can total any arrangement of mystery keys and make them as minimized as a solitary key, however including the intensity of the considerable number of keys being totaled. At the end of the day, the mystery key holder can discharge a consistent size total key for adaptable decisions of ciphertext set in distributed storage, however the other scrambled documents outside the set remain confidential. This minimized total key can be helpfully sent to others or be put away in a brilliant card with constrained secure stockpiling. We give formal security examination of our plans in the standard model. We additionally portray other utilization of our plans. Specifically, our plans give the main open key patient-controlled encryption for adaptable chain of importance, which was at this point to be known. In our cryptosystem, ciphertexts are labeled with sets of attributes and private keys are associated with access structures that control which ciphertexts a user is able to decrypt. We demonstrate the applicability of our construction to sharing of audit-log information and broadcast encryption