Optical spectra and conformation pool of tyrosine kinase inhibitor PD153035 using robust quantum mechanical conformation search

Tyrosine kinase inhibitors (TKIs) based on the quinazoline-aniline scaffold represent a significant class of small molecule drugs for diseases such as cancer. The present study applies the recently developed robust...

Differentiated approach to pancreatic-enteroanastomosis in pancreaticoduodenal resection: a clinical experimental controlled trial

Background. Despite decreasing mortality in pancreaticoduodenal resection, the incidence of postoperative complications in such patients remains high. The choice and formation of “reliable” pancreatic-enteroanastomosis remain relevant.Objectives. The improvement of immediate surgery outcomes in pancreaticoduodenal resection via development of a differentiated algorithm for pancreatic-enteroanastomosis formation.Methods. A prospective non-randomised controlled trial enrolled 90 patients with a pancreaticoduodenal resection surgery. The patients were divided in three cohorts, A (n = 30), B (n = 30) and control C (n = 30). Pancreatic shear wave ultrasound elastography was conducted pre-surgery in main cohorts A and B. Average parenchymal stiffness and intraoperative data decided between the two pancreatico-enteric anastomosis techniques, end-to-side or the original pancreatic-enteroanastomosis. Control cohort C had pancreatico-enteric anastomosis without taking into account the pancreas stiffness and macrocondition.Results. Class A postoperative pancreatic fistula was registered in 2 (6.7%) of 30 patients in cohort B; it was transient, asymptomatic, not requiring additional treatment or a longer postoperative period. No class B and C pancreatic-enteroanastomosis failures or stump pancreonecroses were observed in main cohorts A and B. Clinically significant class B and C postoperative pancreatic fistulae were registered in 5 (16.7%) of 30 patients in control cohort C (inter-cohort comparison statistically significant).Conclusion. The proposed differentiated approach to pancreatic-enteroanastomosis formation associates with a reliably low postoperative complication frequency and lack of clinically significant class B and C postoperative pancreatic fistulae.

An Approach for Movie Review Classification in Turkish

Web 2.0 has given to all people the right to become a representative of a huge cast of informal media. The importance of this power is getting more evident everyday. Every social media actor can influence the rest of the world by one’s own opinions, feelings, and thoughts generously shared on multiple media. This information belonging to various fields of life can be very handy and be used to one’s advantage, gaining precious experience. One of the greatest problems that this poses is the huge number of data spread everywhere, which are difficult to process as row data per se. Social media and general sentiment text analysis is of much valuable use, accomplishing the task extracting pure gold out of raw mineral. The key point of this investigation is to characterize new reviews automatically. To start with, features selected out of all the word roots appearing in the comments were used to train the system according to known machine learning algorithms. Next, critical words determining positive or negative sense were extracted. Another strategy was attempted eliminating common terms and dealing only with the significant class-determining words to build vocabulary with them. Aparts from linear approach, vector based feature sets were prepared out all or some of the features. The outcomes acquired were analyzed and compared leading to important conclusions, emphasizing the importance of feature selection in text classification.

Antibacterial Activity of Thiazole and its Derivatives: A Review

Thiazoles are one of the most intensively scrutinized classes of 5-membered aromatic heterocycles. Many natural and synthesized thiazole and its derivatives showed significant biological activity. Due to its unique properties, thiazole derivatives show significant antibacterial activity against various bacteria and pathogens. Thus, the present review ascribes the antibacterial activity of various thiazole and its derivatives. From using various databases, all the relevant literature has been reviewed. The review was deliberated based on the significant papers on the antibacterial activity of thiazole derivatives. Thiazole and its derivatives, a significant class of heterocyclic derivatives, have played an important role in chemical sciences. Due to their unique properties, they play an important role in the pharmaceutical industry. Thiazole and its derivatives show significant anticancer, anti-tuberculous, antioxidant, and anti-inflammatory activities. Due to their tremendous biological significance, scientists are actively engaged in designing new biological active thiazole derivatives. This review emphasized the antibacterial properties of various thiazole and its derivatives. The present study will help researchers design and synthesize various biological active molecular probes and study their antibacterial properties using various processes against various bacteria and pathogens.

Therapeutic Potential, Synthesis, Patent evaluation and SAR studies of thieno[3,2-d]pyrimidine derivatives: Recent updates.

: Thieno[3,2-d]pyrimidine ring framework comprises a significant class of heterocyclics that serve as a promising platform showing different pharmacological activities. The interest in thieno[3,2-d]pyrimidine cores for pharmaceutical products makes this scaffold an exceptionally helpful building block for organic chemistry. This review presents current research on thieno[3,2-d]pyrimidines and elucidates their biological importance in anti-cancer, anti-infectious, anti-convulsant, anti-diabetic, CNS, and osteoporosis drug discoveries. Patents on the thieno[3,2-d]pyrimidines are also elaborated as a piece of useful information. Here we additionally focus on the synthesis of this vital ring and the discovery of new thieno[3,2-d]pyrimidines.

Selecting lifestyle entrepreneurship recovery strategies: A response to the COVID-19 pandemic

The devastating context of the Covid-19 pandemic has created a new reality in which tourism has practically come to a standstill, a situation that must be reversed. This study focuses on the revitalization of businesses run by lifestyle entrepreneurs, a very significant class, of pivotal importance in innovation in the tourism sector. Specifically, this study aims to identify the most relevant indicators to select the recovery strategies of these entrepreneurs. Using the Delphi method combined with the Q-sort technique, a ranking of the indicators was produced on the basis of input from a panel of 26 senior managers and academics. The top five indicators were: creativity and innovation, level of innovation, qualification, startups number, and turnover volume. Findings reveal that the priority is on innovation and the qualification of the entrepreneurs. Only afterward do the traditional indicators of competitiveness of tourist destinations emerge.

ON CONFORMALLY BERWALD M-TH ROOT (α, β)-METRICS

In this paper, we study the class of $m$-th root (α, β)-metrics which is a significant class mixed of two classes of metrics: $m$-th root metrics and (α, β)-metrics. First, we find the necessary and sufficient condition under which the quartic (α, β)-metrics are conformally Berwald. Then, we find the necessary and sufficient condition under which the cubic (α, β)-metrics are conformally Berwald. Finally, we construct some conformal Finslerian invariants.

Artificial Bee Colony-Based Associative Classifier for Healthcare Data Diagnosis

Data mining is likely to explore hidden patterns from the huge quantity of data and provides a way of analyzing and categorizing the data. Associative classification (AC) is an integration of two data mining tasks, association rule mining, and classification which is used to classify the unknown data. Though association rule mining techniques are successfully utilized to construct classifiers, it lacks in generating a small set of significant class association rules (CARs) to build an accurate associative classifier. In this work, an attempt is made to generate significant CARs using Artificial Bee Colony (ABC) algorithm, an optimization technique to construct an efficient associative classifier. Associative classifier, thus built using ABC discovered CARs achieve high prognostic accurateness and interestingness value. Promising results were provided by the ABC based AC when experiments were conducted using health care datasets from the UCI machine learning repository.

Preparation of Composite Metal-Organic Frameworks

In recent years, metal-organic frameworks (MOFs)-derived composites have emanated as a significant class of substantial materials with specific functional characteristics such as flexibility, high porosity, and diverse composition. Specific chemical modifications can also endow MOFs with specific functionality by offering the possibility of manufacturing all new generation of sensing devices. As on comparison with pure MOFs, the mix up of MOFs with matrix materials(e.g., metal nanoparticles, quantum dots, molecular species, enzymes, silica, and polymers) or functional species not only exhibits enhanced properties, but also widens its applications to modern field of heterogeneous catalysis, gas separation, potential hydrogen storage material and many others due to its high adsorption nature and excellent reversibility kinetics as in result reveals its various undefined attributes, such as reproducible syntheses, amenability to scale-up and chemical modification due to interactions of the functional matrix or species with the MOFs structures.

Diverse synthetic approaches towards C1′-branched acyclic nucleoside phosphonates

Acyclic nucleoside phosphonates (ANPs) represent a significant class of antiviral, anticancer, and antiprotozoal compounds. It is therefore highly desirable to have diverse synthetic routes leading towards these molecules. In the...