Bilateral pulmonary metastases of papillary thyroid carcinoma in a 12-year-old child-A case report and review of the literature.

Metastatic disease of the lung has been extensively documented in the adult patient population. The most common primary sources for pulmonary metastases include breast, colon gastrointestinal including pancreas and urinary bladder. Malignant lung tumors in pediatric population is extremely rare. However, like in adult patient population, metastases are more common than primary tumors in lung in pediatric patients. Metastatic spread of tumors can occur both by way of hematogenous spread and lymphatic pathways. We present a rare case of biopsy proven metastatic thyroid carcinoma in the lung in a 12-year-old male child masquerading as bilateral miliary nodules on imaging studies. The importance of recognition of this entity in terms of prognosis and treatment is discussed

Optimal rate of freezing biological systems

This thesis addresses optimization techniques for cryopreservation of biological systems. A part of the thesis (Chapter 2) reports a simplified procedure to predict the optimal rate of freezing biological systems once the cell level parameters are known a priori. The key cell level parameters investigated were, reference permeability of the membrane to water (Lpg), apparent activation energy (ELp), inactive cell volume (Vb), diameter (D), and the ratio of the available surface area for water transport to the initial volume of intracellular water (SA/WV). The simplified procedure was developed by performing a thorough analysis of the water transport model over a physiologically relevant range for the various cell level parameters. The results from the parametric analysis are analyzed and used to develop a Generic Optimal Cooling Rate Chart (GOCRC) and a Generic Optimal Cooling Rate Equation (GOCRE). The use of GOCRC and GOCRE greatly simplifies the prediction of the optimal rate of freezing of biological systems without resorting to complex numerical simulations. The second and last part of the thesis (Chapter 3) reports the membrane permeability parameters (Lpg and ELp) of canine sperm cells during freezing using a differential scanning calorimeter (DSC) technique. In this study a well established shape independent Differential Scanning Calorimeter (DSC) technique was used to measure the dehydration response during freezing of ejaculated canine sperm cells. Volumetric shrinkage during freezing of canine sperm cell suspensions was obtained at cooling rates of 5 and 10 oC/min in the presence of extracellular ice and with or without cryoprotective agents (CPAs). By fitting a model of water transport to the experimentally obtained volumetric shrinkage data the best fit membrane permeability parameters (Lpg and ELp) were determined. Numerical simulations of water transport in canine sperm cells were then performed under a variety of cooling rates (5 to 100 oC/min) using the experimentally determined membrane permeability parameters (Lpg and ELp). The simulation results were analyzed to predict the amount of water left in the cell after dehydration ceased, in the absence of IIF and the optimal cooling rates for canine sperm cryopreservation

Cryopreservation of Adipose Derived Adult Stem Cells and Multidimensional Cell Sheets

Human adipose tissue provides a uniquely abundant and accessible source of adult stem cells. In response to chemical, hormonal or structural stimuli, these human adipose-derived adult stem (ASCs) cells can differentiate along multiple lineage pathways, including adipocytes, chondrocytes, myocytes, neurons and osteoblasts. Successful cryopreservation of scientifically and commercially important ASCs would revolutionize the tissue engineering and regenerative medicine industry. In this research, we have investigated the water transport phenomenon during freezing of several passages of adipose derived adult stem cells and generated the membrane permeability parameters in the presence and absence of cryoprotective agents. These measured permeability parameters were then used to find the optimal cooling rates for freezing ASCs. We have also analyzed the individual and interaction effects of four important thermal parameters (cooling rate, hold time, thawing rate and end temperature) on the post-thaw viability of all passages (passage 0 to passage 4) of ASCs. We have then studied the effect of nanoparticles on the water transport response and apoptotic behavior of biological systems during a cryopreservation process. Further, we have investigated the maintenance of differentiation potential of post-freeze huASCs through histochemical staining. In an attempt to eliminate the usage of chemical CPAs (DMSO/glycerol) during cryopreservation, studies were conducted to investigate the possibility of using non toxic polymers, such as PVP, as cryoprotective agents. Flow cytometry analysis was employed to assess the post-thaw viability and apoptotic response of P1 ASCs frozen stored for more than two weeks in different concentrations of PVP. The results suggest that PVP in fact posses excellent cryoprotective properties and produced acceptable viability when compared to the most routinely used cryopreservation media involving DMSO and serum. In another study, cell sheet engineering approach has been applied to generate multi-dimensional cell sheets for tissue engineering using ASCs

Clickbait Classification and Spoiling Using Natural Language Processing

Clickbait is the practice of engineering titles to incentivize readers to click through to articles. Such titles with sensationalized language reveal as little information as possible. Occasionally, clickbait will be intentionally misleading, so natural language processing (NLP) can scan the article and answer the question posed by the clickbait title, or spoil it. We tackle two tasks: classifying the clickbait into one of 3 types (Task 1), and spoiling the clickbait (Task 2). For Task 1, we propose two binary classifiers to determine the final spoiler type. For Task 2, we experiment with two approaches: using a question-answering model to identify the span of text of the spoiler, and using a large language model (LLM) to generate the spoiler. Because the spoiler is contained in the article, we frame the second task as a question-answering approach for identifying the starting and ending positions of the spoiler. We created models for Task 1 that were better than the baselines proposed by the dataset authors and engineered prompts for Task 2 that did not perform as well as the baselines proposed by the dataset authors due to the evaluation metric performing worse when the output text is from a generative model as opposed to an extractive model.Comment: 7 pages, 2 figures, 3 tables, 1 Appendix (3 Sections

Mutual query data sharing protocol for public key encryption through chosen-ciphertext attack in cloud environment

In this paper, we are proposing a mutual query data sharing protocol (MQDS) to overcome the encryption or decryption time limitations of exiting protocols like Boneh, rivest shamir adleman (RSA), Multi-bit transposed ring learning parity with noise (TRLPN), ring learning parity with noise (Ring-LPN) cryptosystem, key-Ordered decisional learning parity with noise (kO-DLPN), and KD_CS protocol’s. Titled scheme is to provide the security for the authenticated user data among the distributed physical users and devices. The proposed data sharing protocol is designed to resist the chosen-ciphertext attack (CCA) under the hardness solution for the query shared-strong diffie-hellman (SDH) problem. The evaluation of proposed work with the existing data sharing protocols in computational and communication overhead through their response time is evaluated

Migration of Virtual Machine to improve the Security of Cloud Computing

Cloud services help individuals and organization to use data that are managed by third parties or another person at remote locations. With the increase in the development of cloud computing environment, the security has become the major concern that has been raised more consistently in order to move data and applications to the cloud as individuals do not trust the third party cloud computing providers with their private and most sensitive data and information. This paper presents, the migration of virtual machine to improve the security in cloud computing. Virtual machine (VM) is an emulation of a particular computer system. In cloud computing, virtual machine migration is a useful tool for migrating operating system instances across multiple physical machines. It is used to load balancing, fault management, low-level system maintenance and reduce energy consumption. Virtual machine (VM) migration is a powerful management technique that gives data center operators the ability to adapt the placement of VMs in order to better satisfy performance objectives, improve resource utilization and communication locality, achieve fault tolerance, reduce energy consumption, and facilitate system maintenance activities. In the migration based security approach, proposed the placement of VMs can make enormous difference in terms of security levels. On the bases of survivability analysis of VMs and Discrete Time Markov Chain (DTMC) analysis, we design an algorithm that generates a secure placement arrangement that the guest VMs can moves before succeeds the attack