Bennettwalther7600

Computer-aided design of new drugs is an exponentially growing field, especially in the last decade. The support of theoretical tools may accelerate the drug discovery process, which is a long and very expensive journey. Tools as QSAR and docking calculations are on the top of the list for helping medicinal chemists to find more potent and selective molecules as potential leads for facing challenging diseases. Coumarins have been an important source of inspiration for the design of new drugs. Due to their chemical properties and their affinity to some targets, special attention has been paid to their role against neurodegenerative diseases. Therefore, the authors provide an overview of the scientific reports describing the research and development of new drug design tools supporting the discovery of coumarins as enzymatic inhibitors or receptor ligands involved in these diseases. This review emphasizes the rationale behind the design of new drug candidates, and particular attention is paid to the search for new leads over the last 10 years. QSAR and docking studies are discussed, as well as new technologies applied for the research in this field. The manuscripts discussed in this review have been collected from multiple electronic databases, including Pubmed, SciFinder, and Mendeley.Heat shock protein 90 (HSP90) is a multichaperone complex that mediates the maturation and stability of a variety of oncogenic signaling proteins. HSP90 has emerged as a promising target for the development of anticancer agents. Heterocyclic chemical moieties with HSP90 inhibitory activity were studied continuously during the last decades, and resulting data were applied by medicinal chemists to design and develop new drugs. Their structure-activity relationship (SAR) studies and QSAR models have been derived to assist the current drug development process. The QSAR models are obtained via multiple linear regression (MLR) and non-linear approaches. Interpretation of the reported model highlights the core template required to design novel, potent HSP90 inhibitors to be used as anticancer agents.For many years, natural products have played a crucial role in drug discovery and drug design as a source of active agents or as inspiration. Lactoferrin (Lf), a glycoprotein found in milk and mammalian secretions, has been extensively studied in recent years, and numerous antimicrobial, anti-inflammatory, and anticancer properties of Lf have been demonstrated in the literature. The use of lactoferrin as a co-agent or supplement to enhance the beneficial effect of drugs, or to reduce their side effects, arouses the interest of many researchers, especially since Lf is a well-studied, biocompatible, cheap, and easily accessible protein. In this mini-review, we focus on the elucidation of the role of Lf in antimicrobial or anticancer therapies, pointing to the possible mechanism underlying the determined synergism between Lf and commonly used drugs.Colorectal cancer is the third most common cancer globally. Despite extensive preclinical and clinical studies, it is still among the leading causes of cancer-related death, and a need for new therapeutic options is required. The renin-angiotensin system plays an important role in regulating blood pressure and cell growth. In addition to their hemodynamic effects, some of the renin-angiotensin system components, such as angiotensin, are also growth factors that promote cell proliferation and angiogenesis, and its dysregulation is reported to be associated with poor prognosis in colorectal cancer. Here we describe the critical role of the renin-angiotensin system pathway in colorectal cancer as well as the preclinical and clinical investigations renin-angiotensin system inhibitors angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers as a potential therapeutic target in the treatment of colorectal cancer. Several studies have been shown that the inhibition of these pathways can reduce tumor growth and metastasis; however, some of the data remain inconsistent. There is accumulating evidence of the therapeutic potential of some inhibitors, such as Losartan which are now in clinical phases in the treatment of several malignancies using Nivolumab in combination with FOLFIRINOX in pancreatic cancer. Further investigations are warranted to improve the efficacy and selectivity of current and future anticancer strategies targeting renin-angiotensin systems.

The clinical features and treatment approaches, outcomes, and mortality predictors of COVID-19 in solid-organ transplant recipients have not been well defined. This study investigated the clinical features of COVID-19 infection in solid-organ transplant recipients at our center in Turkey.

Our study included 23 solidorgan transplant recipients and 336 nontransplant individuals (143 previously healthy and 193 patients with at least 1 comorbidity) who were hospitalized due to COVID-19 disease in our hospital between March 2020 and January 2021. Demographic, clinical, and laboratory data of patients were compared. We used SPSS version 20.0 for statistical analysis. L-Kynurenine in vivo All groups were compared using chi-square and Mann-Whitney U tests. P < .05 was considered statistically significant.

Mean age of solid-organ transplant recipients was 49.8 ± 13.7 years (78.3% men, 21.7% women). Among the 23 recipients, 17 (73.9%) were kidney and 6 (26.1%) were liver transplant recipients. Among nontransplant individuals, 88.7sus that shown in healthy patients. More attention on secondary infections is needed in transplant recipients to reduce mortality.Physicians are increasingly becoming employed by hospitals and health systems. While associated with less professional autonomy, such employment offers physicians the opportunity to become leaders within a vertically integrated healthcare environment. Multidisciplinary care teams, led by physician champions, can impact care for a large swath of patients and establish clinical excellence. Successful teams can improve outcomes, increase professional satisfaction, and potentially set physicians on a path to becoming leaders within their health system.Humans obtain characteristic information such as texture and weight of external objects, relying on the brain's integration and classification of tactile information; however, the decoding mechanism of multi-level tactile information is relatively elusive from the temporal sequence. In this paper, nonvariant frequency, along with the variant pulse width of electrotactile stimulus, was performed to generate multi-level pressure sensation. Event-related potentials (ERPs) were measured to investigate the mechanism of whole temporal tactile processing. Five ERP components, containing P100-N140-P200-N200-P300, were observed. By establishing the relationship between stimulation parameters and ERP component amplitudes, we found the following (1) P200 is the most significant component for distinguishing multi-level tactile sensations; (2) P300 is correlated well with the subjective judgment of tactile sensation. The temporal sequence of brain topographies was implemented to clarify the spatiotemporal characteristics of the tactile process, which conformed to the serial processing model in neurophysiology and cortical network response area described by fMRI. Our results can help further clarify the mechanism of tactile sequential processing, which can be applied to improve the tactile BCI performance, sensory enhancement, and clinical diagnosis for doctors to evaluate the tactile process disorders by examining the temporal ERP components.Seizure prediction using intracranial electroencephalogram (iEEG) has attracted an increasing attention during recent years. iEEG signals are commonly recorded in the form of multiple channels. Many previous studies generally used the iEEG signals of all channels to predict seizures, ignoring the consideration of channel selection. In this study, a method of one-dimensional convolutional neural networks (1D-CNN) combined with channel selection strategy was proposed for seizure prediction. First, we used 30-s sliding windows to segment the raw iEEG signals. Then, the 30-s iEEG segments, which were in three channel forms (single channel, channels only from seizure onset or free zone and all channels from seizure onset and free zones), were used as the inputs of 1D-CNN for classification, and the patient-specific model was trained. Finally, the channel form with the best classification was selected for each patient. The proposed method was evaluated on the Freiburg Hospital iEEG dataset. In the situation of seizure occurrence period (SOP) of 30[Formula see text]min and seizure prediction horizon (SPH) of 5[Formula see text]min, 98.60[Formula see text] accuracy, 98.85[Formula see text] sensitivity and 0.01/h false prediction rate (FPR) were achieved. In the situation of SOP of 60[Formula see text]min and SPH of 5[Formula see text]min, 98.32[Formula see text] accuracy, 98.48[Formula see text] sensitivity and 0.01/h FPR were attained. Compared with the many existing methods using the same iEEG dataset, our method showed a better performance.

Elderly patients frequently experience poor sleep quality. We aimed to determine its prevalence and risk factors in diabetic elderly patients from Turkey.

An observational cross-sectional study of 220 diabetic elderly patients with a mean age of 70.4±5.9 was conducted between June 2019 and December 2019. Pittsburgh Sleep Quality Index (PSQI) questionnaire was used. Patients were divided based on sleep quality into poor (PSQI> 5) and good (PSQI≤ 5) sleep quality groups. Geriatric Depression Scale, Beck Anxiety Inventory, and Hendrich II Fall Risk Model were adopted. The prevalence of poor sleep quality and risk factors were evaluated.

Prevalence of poor sleep quality was 58.6%. Poor sleepers were significantly older, were more likely to be divorced, had more comorbidities, and used more medicines (ps<0.05). Longer duration of diabetes, higher incidence of hypoglycemic events, and diabetic complications were significantly associated with poor sleep quality (ps<0.05). Poor sleepers had higher levels of blood glucose and HbA1c levels (ps<0.05). PSQI was significantly correlated with age, HbA1c, duration of diabetes, higher depression, anxiety, and falling risk (ps<0.05). Severe depression, anxiety, and higher falling risk were independent risk factors.

Most patients experienced poor sleep quality. It was associated with a longer duration of diabetes, chronic diabetes-related complications, and higher HbA1c levels. Severe depression, anxiety, and higher falling risk were risk factors for poor sleep quality.

Most patients experienced poor sleep quality. It was associated with a longer duration of diabetes, chronic diabetes-related complications, and higher HbA1c levels. Severe depression, anxiety, and higher falling risk were risk factors for poor sleep quality.Health professions programs lack sufficient exposure to geriatric education in curricula. The Seniors Assisting in Geriatric Education (SAGE) Program exposes interprofessional (IP) teams of health professions students to older adults. To determine the impact of an interprofessional geriatric educational experience on student perceptions of team collaboration and older adults. IP teams of three or four students (n = 662) representing eight disciplines from two institutions were paired with an older adult to promote person-centered care over three semesters. Students completed two online questionnaires (pre- and post-SAGE Program, ~10 min). 136 students completed both questionnaires. Three IP collaborative practice sub-competencies under the Roles & Responsibilities and Interprofessional Communication Core Competencies increased significantly from pre- to post-SAGE Program (p ≤ 0.002). Comparison of the means for attitudes toward geriatric patients revealed statistically significant improvement in one item, Compassion (p less then .