There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

A survey on deep learning in medical image analysis

Chitin is the most abundant natural amino polysaccharide and is estimated to be produced annually almost as much as cellulose. It has become of great interest not only as an underutilized resource, but also as a new functional material of high potential in various fields, and recent progress in chitin chemistry is quite noteworthy. The purpose of this review is to take a closer look at chitin and chitosan applications. Based on current research and existing products, some new and futuristic approaches in this fascinating area are thoroughly discussed.

A review of chitin and chitosan applications

https://yunus.hacettepe.edu.tr/~damlacetin/kmu407/index_dosyalar/4.%20makale.pdf

Biodegradable polymers as biomaterials

Hydrogel: Preparation, characterization, and applications: A review

Nuclear segmentation in digital microscopic tissue images can enable extraction of high-quality features for nuclear morphometrics and other analysis in computational pathology. Conventional image processing techniques, such as Otsu thresholding and watershed segmentation, do not work effectively on challenging cases, such as chromatin-sparse and crowded nuclei. In contrast, machine learning-based segmentation can generalize across various nuclear appearances. However, training machine learning algorithms requires data sets of images, in which a vast number of nuclei have been annotated. Publicly accessible and annotated data sets, along with widely agreed upon metrics to compare techniques, have catalyzed tremendous innovation and progress on other image classification problems, particularly in object recognition. Inspired by their success, we introduce a large publicly accessible data set of hematoxylin and eosin (H&E)-stained tissue images with more than 21000 painstakingly annotated nuclear boundaries, whose quality was validated by a medical doctor. Because our data set is taken from multiple hospitals and includes a diversity of nuclear appearances from several patients, disease states, and organs, techniques trained on it are likely to generalize well and work right out-of-the-box on other H&E-stained images. We also propose a new metric to evaluate nuclear segmentation results that penalizes object- and pixel-level errors in a unified manner, unlike previous metrics that penalize only one type of error. We also propose a segmentation technique based on deep learning that lays a special emphasis on identifying the nuclear boundaries, including those between the touching or overlapping nuclei, and works well on a diverse set of test images.

A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology

Polyanhydrides: an overview

Hydrogels are crosslinked hydrophilic polymer structures that can imbibe large amounts of water or biological fluids. Hydrogels are one of the upcoming classes of polymer-based systems that embrace numerous biomedical and pharmaceutical applications. This review discusses various parameters of hydrogels such as surface properties, water content and swelling behavior, effect of nature of polymer, ionic content, and thermodynamics, all of which can influence the biomedical usage of hydrogels. Meanwhile, intelligent or environment-sensitive hydrogels and bioadhesive hydrogels continue to be important materials for medical applications; therefore, a part of this review is devoted to some of their important classes. Hydrogels are extensively used for various biomedical applications--tissue engineering, molecular imprinting, wound dressings materials, immunoisolation, drug delivery, etc. Thus, this review aims to throw light on the numerous applications that hydrogels have in the biomedical arena.

Hydrogels for pharmaceutical and biomedical applications.

Recent progresses in the field of Induced Pluripotent Stem Cells (iPSCs) have opened up many gateways for the research in therapeutics. iPSCs are the cells which are reprogrammed from somatic cells using different transcription factors. iPSCs possess unique properties of self renewal and differentiation to many types of cell lineage. Hence could replace the use of embryonic stem cells (ESC), and may overcome the various ethical issues regarding the use of embryos in research and clinics. Overwhelming responses prompted worldwide by a large number of researchers about the use of iPSCs evoked a large number of peple to establish more authentic methods for iPSC generation. This would require understanding the underlying mechanism in a detailed manner. There have been a large number of reports showing potential role of different molecules as putative regulators of iPSC generating methods. The molecular mechanisms that play role in reprogramming to generate iPSCs from different types of somatic cell sources involves a plethora of molecules including miRNAs, DNA modifying agents (viz. DNA methyl transferases), NANOG, etc. While promising a number of important roles in various clinical/research studies, iPSCs could also be of great use in studying molecular mechanism of many diseases. There are various diseases that have been modeled by uing iPSCs for better understanding of their etiology which maybe further utilized for developing putative treatments for these diseases. In addition, iPSCs are used for the production of patient-specific cells which can be transplanted to the site of injury or the site of tissue degeneration due to various disease conditions. The use of iPSCs may eliminate the chances of immune rejection as patient specific cells may be used for transplantation in various engraftment processes. Moreover, iPSC technology has been employed in various diseases for disease modeling and gene therapy. The technique offers benefits over other similar techniques such as animal models. Many toxic compounds (different chemical compounds, pharmaceutical drugs, other hazardous chemicals, or environmental conditions) which are encountered by humans and newly designed drugs may be evaluated for toxicity and effects by using iPSCs. Thus, the applications of iPSCs in regenerative medicine, disease modeling, and drug discovery are enormous and should be explored in a more comprehensive manner.

/pdf/induced-pluripotent-stem-cells-applications-in-regenerative-4jc4rvqncz.pdf

Neeraj Kumar

Papers

A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology

Polyanhydrides: an overview

Hydrogels for pharmaceutical and biomedical applications.

Induced pluripotent stem cells: applications in regenerative medicine, disease modeling, and drug discovery

Biodegradable block copolymers