Regulation of 3β-Hydroxysteroid Dehydrogenase/∆5-∆4 Isomerase: A Review

This review focuses on the expression and regulation of 3β-hydroxysteroi ddehydrogenase/Δ5-Δ4 isomerase (3β-HSD), with emphasis on the porcine version. 3β-HSD is often associated with steroidogenesis, but its function in the metabolism of both steroids and xenobiotics is more obscure. Based on currently available literature covering humans,rodents and pigs, this review provides an overview of the present knowledge concerning the regulatory mechanisms for 3β-HSD at all omic levels. The HSD isoenzymes are essential in steroid hormone metabolism, both in the synthesis and degradation of steroids. They display tissue-specific expression and factors influencing their activity, which therefore indicates their tissue-specific responses. 3β-HSD is involved in the synthesis of a number of natural steroid hormones, including progesterone and testosterone, and the hepatic degradation of the pheromone androstenone. In general, a number of signaling and regulatory pathways have been demonstrated to influence 3β-HSD transcription and activity, e.g., JAK-STAT, LH/hCG, ERα, AR, SF-1 and PPARα. The expression and enzymic activity of 3β-HSD are also influenced by external factors, such as dietary composition. Much of the research conducted on porcine 3β-HSD is motivated by its importance for the occurrence of the boar taint phenomenon that results from high concentrations of steroids such as androstenone. This topic is also examined in this review

The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin motifs) family

The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin motifs) enzymes are secreted, multi-domain matrix-associated zinc metalloendopeptidases that have diverse roles in tissue morphogenesis and patho-physiological remodeling, in inflammation and in vascular biology. The human family includes 19 members that can be sub-grouped on the basis of their known substrates, namely the aggrecanases or proteoglycanases (ADAMTS1, 4, 5, 8, 9, 15 and 20), the procollagen N-propeptidases (ADAMTS2, 3 and 14), the cartilage oligomeric matrix protein-cleaving enzymes (ADAMTS7 and 12), the von-Willebrand Factor proteinase (ADAMTS13) and a group of orphan enzymes (ADAMTS6, 10, 16, 17, 18 and 19). Control of the structure and function of the extracellular matrix (ECM) is a central theme of the biology of the ADAMTS, as exemplified by the actions of the procollagen-N-propeptidases in collagen fibril assembly and of the aggrecanases in the cleavage or modification of ECM proteoglycans. Defects in certain family members give rise to inherited genetic disorders, while the aberrant expression or function of others is associated with arthritis, cancer and cardiovascular disease. In particular, ADAMTS4 and 5 have emerged as therapeutic targets in arthritis. Multiple ADAMTSs from different sub-groupings exert either positive or negative effects on tumorigenesis and metastasis, with both metalloproteinase-dependent and -independent actions known to occur. The basic ADAMTS structure comprises a metalloproteinase catalytic domain and a carboxy-terminal ancillary domain, the latter determining substrate specificity and the localization of the protease and its interaction partners; ancillary domains probably also have independent biological functions. Focusing primarily on the aggrecanases and proteoglycanases, this review provides a perspective on the evolution of the ADAMTS family, their links with developmental and disease mechanisms, and key questions for the future

Gene expression and matrix turnover in overused and damaged tendons

Chronic, painful conditions affecting tendons, frequently known as tendinopathy, are very common types of sporting injury. The tendon extracellular matrix is substantially altered in tendinopathy, and these changes are thought to precede and underlie the clinical condition. The tendon cell response to repeated minor injuries or “overuse” is thought to be a major factor in the development of tendinopathy. Changes in matrix turnover may also be effected by the cellular response to physical load, altering the balance of matrix turnover and changing the structure and composition of the tendon. Matrix turnover is relatively high in tendons exposed to high mechanical demands, such as the supraspinatus and Achilles, and this is thought to represent either a repair or tissue maintenance function. Metalloproteinases are a large family of enzymes capable of degrading all of the tendon matrix components, and these are thought to play a major role in the degradation of matrix during development, adaptation and repair. It is proposed that some metalloproteinase enzymes are required for the health of the tendon, and others may be damaging, leading to degeneration of the tissue. Further research is required to investigate how these enzyme activities are regulated in tendon and altered in tendinopathy. A profile of all the metalloproteinases expressed and active in healthy and degenerate tendon is required and may lead to the development of new drug therapies for these common and debilitating sports injuries

An Optimizing Method for Performance and Resource Utilization in Quantum Machine Learning Circuits

Quantum computing is a new and advanced topic that refers to calculations based on the principles of quantum mechanics. Itmakes certain kinds of problems be solved easier compared to classical computers. This advantage of quantum computingcan be used to implement many existing problems in different fields incredibly effectively. One important field that quantumcomputing has shown great results in machine learning. Until now, many different quantum algorithms have been presented toperform different machine learning approaches. In some special cases, the execution time of these quantum algorithms will bereduced exponentially compared to the classical ones. But at the same time, with increasing data volume and computationtime, taking care of systems to prevent unwanted interactions with the environment can be a daunting task and since thesealgorithms work on machine learning problems, which usually includes big data, their implementation is very costly in terms ofquantum resources. Here, in this paper, we have proposed an approach to reduce the cost of quantum circuits and to optimizequantum machine learning circuits in particular. To reduce the number of resources used, in this paper an approach includingdifferent optimization algorithms is considered. Our approach is used to optimize quantum machine learning algorithms forbig data. In this case, the optimized circuits run quantum machine learning algorithms in less time than the original onesand by preserving the original functionality. Our approach improves the number of quantum gates by 10.7% and 14.9% indifferent circuits and the number of time steps is reduced by three and 15 units, respectively. This is the amount of reduction forone iteration of a given sub-circuit U in the main circuit. For cases where this sub-circuit is repeated more times in the maincircuit, the optimization rate is increased. Therefore, by applying the proposed method to circuits with big data, both cost andperformance are improved

Application of Quantum Natural Language Processing for Language Translation

In this paper, we develop compositional vector-based semantics of positive transitive sentences using quantum natural language processing (Q-NLP) to compare the parametrized quantum circuits of two synonymous simple sentences in English and Persian. We propose a protocol based on quantum long short-term memory (Q-LSTM) for Q-NLP to perform various tasks in general but specifically for translating a sentence from English to Persian. Then, we generalize our method to use quantum circuits of sentences as an input for the Q-LSTM cell. This enables us to translate sentences in different languages. Our work paves the way toward representing quantum neural machine translation, which may demonstrate quadratic speedup and converge faster or reaches a better accuracy over classical methods

Unilateral vs. bilateral DLPFC rTMS: comparative effects on depression, visual-spatial memory, inhibitory control and cognitive flexibility in major depressive disorder

BackgroundExciting left DLPFC activity with high frequency and inhibiting right DLPFC with low frequency repetitive transcranial magnetic stimulation (rTMS) has shown antidepressant effects in major depressive disorder (MDD) and executive functions. However, few studies have directly compared unilateral and bilateral protocols.MethodsForty-seven individuals with treatment-resistant MDD underwent 10 sessions of rTMS over left DLPFC (20 Hz), bilateral DLPFC (left 20 Hz, right 1 Hz), or sham stimulation. Outcomes were depression (Beck Depression Inventory-II), visual-spatial memory (Corsi Block Test), response inhibition (Go/No-Go task), and cognitive flexibility (Wisconsin Card Sorting Test) assessed before and after treatment.ResultsBoth unilateral and bilateral rTMS significantly reduced depression levels versus sham controls based on BDI-II scores. While bilateral stimulation did not improve Corsi Test performance, unilateral protocol enhanced visual-spatial memory. On the Go/No-Go task, accuracy was higher in both active stimulation groups compared to sham, with no response time differences. Neither unilateral nor bilateral rTMS had significant effects on cognitive flexibility per the WCST.ConclusionsDespite comparable antidepressant effects, unilateral stimulation had some cognitive advantages over bilateral rTMS, potentially due to greater left dorsolateral prefrontal cortex excitation. Further research on parameter optimization is warranted

A systematic review on the impact of empowerment in improving self-care behaviors and some other factors in diabetic patients

Introduction: Traditional education seems to be sufficient in meeting the needs related to knowledge of patients, However, by recognizing the impact of psychosocial issues and the environment on patients 'behavior, educational techniques were used to change patients' behavior. And the education approach to diabetic patients has changed, as well as the theory and research on diabetes was introduced. And the focus of the capacity building approach to adapt treatment to self-efficacy and empowerment was changed. Empowerment is a collaborative approach to diabetes care and patient education. This systematic review was conducted with the aim of empowerment in improving self-care behaviors in diabetic patients. Materials and Methods: In order to achieve the aim of the study and to improve the accuracy of the study and its comprehensive understanding, this review study was conducted based on the Broome method. This method is carried out in three steps: searching for texts, evaluating data and analyzing data. So, in the search phase, postretrospective study texts are examined in four stages in terms of inclusion criteria. After obtaining the conditions for entry into the study, the content of the study is evaluated and at the end of the analysis of the data. Results: In this study, 12 articles were reviewed that showed that the empowerment approach of diabetic patients improves self-efficacy and self-care scores and reduces hemoglobin A1C, Improvement of general self-care behaviors, reduction of mean glycosylated hemoglobin and improvement of quality of life, blood glucose control, and so on. Conclusion: In researches done on the empowerment approach of diabetic patients, the importance of empowerment approach is confirmed by increasing control and self-care and improving some other factors in diabetic patients. Therefore, considering the importance of the concept of empowerment as an effective approach to supporting patients with diabetes, it is necessary to consider this approach in furtherresearch