Surgical consideration in posterior C1-2 instrumentation in case of vertebral artery anomaly

Anatomical variations in the course of the vertebral artery have been previously described in the literature. Generally, these predictable patterns of variations commonly observed in lower cervical vertebral artery anatomy and less commonly described for upper cervical vertebral artery anatomy. Due to presence of these variations, treatment options for upper cervical spine pathology may be influenced and sometimes prevent commonly performed stabilization procedures.  Herein author presented a case of vertebral artery anatomic variation at the craniovertebral junction and management option for such variations

Biological Approaches to Bone Regeneration: Innovations and Clinical Implications

In orthopaedics, bone regeneration is still a major difficulty that calls for creative solutions for efficient tissue repair. Modern biological techniques, such as scaffolds, growth factors, tissue engineering, and their therapeutic applications in bone regeneration, are examined in this study. Growth factors—in particular, platelet-derived growth factors (PDGFs) and bone morphogenetic proteins (BMPs)—are essential for promoting osteogenesis and improving bone regeneration. Clinical settings have shown their therapeutic potential; nonetheless, there are ideal doses, administration modalities, and safety profiles to take into account. With their exact designs and variety of biomaterials, scaffolds provide structural support and foster the cellular activity that is essential for bone repair. The functioning and interactions between cells and scaffolds are improved by a variety of manufacturing approaches, including 3D bioprinting and surface changes. Tissue engineering techniques combine scaffolds, cells, and signalling molecules to create useful tissue constructions for bone mending. In tissue-engineered structures, the integration of growth factors and mesenchymal stem cells (MSCs) exhibit potential for augmenting osteogenesis. Clinical applications provide a variety of settings for regenerative therapies, including fracture healing, non-unions, and significant bone defects. However, obstacles to their wider clinical application include safety assurance, scalability, regulatory compliance, effectiveness validation, and personalised therapy. By tackling these obstacles with thorough investigation and translational work, novel biological strategies to improve bone regeneration treatments will become possible

DETERMINATION OF RESIDUAL DIMETHYL SULFATE IN METHOXSALEN DRUG SUBSTANCE BY PRE-COLUMN DERIVATIZATION WITH STATIC HEADSPACE GAS CHROMATOGRAPHY

Objective: Dimethyl sulfate has been highlighted as potential genotoxic and carcinogenic impurity. A sensitive Headspace gas chromatography (HS-GC) method with pre-column derivatization was developed and validated for the determination of dimethyl sulfate impurity in methoxsalen active pharmaceutical ingredient.Methods: HS-GC method on the column Agilent DB-5, 30m X 0.53 mm, film thickness 1.5 µm, with flame ionization detector (FID) was used. Derivatization reagent concentration, time of reaction and pH of the solution were optimized during method development. This analytical method was evaluated by performing method validation as per ICH guideline.Results: The proposed method was specific, linear, accurate, rugged and precise. The calibration curves showed good linearity over the concentration range of 0.5 μg/ml to 3.0 μg/ml and the correlation coefficient was 0.999. Method had very low limit of detection (LOD) and limit of quantification (LOQ) 2.0 μg/g and 5.0 μg/g respectively. Accuracy was observed within 98.1%–104.5%.Conclusion: The developed method was demonstrated to be accurate, robust and sensitive for the determination of dimethyl sulfate impurity in methoxsalen drug substance

An efficient stacking based NSGA-II approach for predicting type 2 diabetes

Diabetes has been acknowledged as a well-known risk factor for renal and cardiovascular disorders, cardiac stroke and leads to a lot of morbidity in the society. Reducing the disease prevalence in the community will provide substantial benefits to the community and lessen the burden on the public health care system. So far, to detect the disease innumerable data mining approaches have been used. These days, incorporation of machine learning is conducive for the construction of a faster, accurate and reliable model. Several methods based on ensemble classifiers are being used by researchers for the prediction of diabetes. The proposed framework of prediction of diabetes mellitus employs an approach called stacking based ensemble using non-dominated sorting genetic algorithm (NSGA-II) scheme. The primary objective of the work is to develop a more accurate prediction model that reduces the lead time i.e., the time between the onset of diabetes and clinical diagnosis. Proposed NSGA-II stacking approach has been compared with Boosting, Bagging, Random Forest and Random Subspace method. The performance of Stacking approach has eclipsed the other conventional ensemble methods. It has been noted that k-nearest neighbors (KNN) gives a better performance over decision tree as a stacking combiner

Self-assembled polymer nanocomposites and their networks

This dissertation describes new routes to synthesize polymer nanocomposite networks via self-assembly. Polymerizable structure directing agents (referred to as surfmers) obtained by end-group functionalization preserves the structure-directing capabilities of the surfactant for templating ordered mesoporous silica particle growth, while simultaneously generating a reactive matrix for polymer network formation through reactive end groups in the presence of intimately mixed mesoporous silicates. A combination of small angle X-ray scattering, surface area, and microscopy experiments on mesoporous silica indicated the structure directing capabilities of surfmers. Free-radical polymerization of the surfmer leads to novel crosslinked nanocomposites networks. Multiple experiments, including gel permeation chromatography, swelling, and solid state NMR experiments on polymer nanocomposites gave evidence of the polymerization of surfmer leading to formation of crosslink networks. Polymer nanocomposites with varied silica content were prepared. Effects of silica content on polymer nanocomposites were studied on rheometer. Results obtained from rheological experiments indicate that the storage (G') and loss modulus (G") increases with increase in the content of mesoporous silica. In this way, the nanocomposites networks obtained via self-assembly shows independent behavior with respect to frequency in rheological experiments. Additionally, this self-assembled route was extended to synthesize biodegradable and biocompatible polymer nanocomposites networks. The nanocomposite networks obtained with 15% of silica content showed the increase in storage modulus by two orders of magnitude in rheological experiments

Study of preoperative GnRh agonist in cutaneous scar endometriosis

Background: Cutaneous scar endometriosis is an uncommon pathology, it is rare and difficult to diagnose, mostly follows obstetrical and gynaecological surgeries. Surgical wide excision is the mainstay of treatment. The objective of this study was to evaluate efficacy of preoperative GnRh agonist in scar endometriosis.Methods: This is prospective randomized case control study performed on all cutaneous scar endometriosis cases reporting to our institute as well as consultants from Dhule obstetrics and gynaecology society. All cases were operated and follow up in our institute by same surgeon.Results: Surgical excision accompanied by preoperative GnRh agonist therapy is helpful for easy excision and reduce recurrence of scar endometriosis.Conclusions: Abdominal scar endometriosis is rare gynecological pathology, should be suspected in any women of child bearing age group complaining of cyclical painful nodule in scar following a previous obstetric and gynaecological procedure