Examining Psychological Factors in Peripheral Artery Disease: Affective Temperament, Anxiety, and Depression in Patients Undergoing Revascularization Procedures.

Purpose: This study aimed to assess the prevalence of depressive and anxiety symptoms in peripheral artery disease (PAD) patients, correlating these symptoms with clinical parameters and examining affective temperaments within the study group. Material and Methods: A total of 159 PAD patients, predominantly male, admitted for vascular surgery due to lower limb atherosclerosis, participated in this cross-sectional study. Various assessments were conducted, including the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-Autoquestionnaire (TEMPS-A) for affective temperaments, the Hospital Anxiety and Depression Scale (HADS) for anxiety and depression symptoms, and the Numerical Rating Scale (NRS) for pain intensity. Additionally, the Ankle-Brachial Index (ABI) was measured to assess circulation in the legs. Results: The findings revealed a higher prevalence of depressive and anxiety symptoms in the PAD patient group compared to the control group. Notably, depressive and anxiety symptoms correlated with the severity of PAD, as indicated by lower ABI values in the operated leg. Patients undergoing surgical revascularizations exhibited higher depressive symptoms than those undergoing endovascular procedures. Furthermore, correlations were observed between depressive symptoms and the number of previous vascular procedures and amputations, alongside increased pain levels at admission. Clinical factors such as diabetes, hypertension, heart failure, ischemic heart disease, previous revascularization procedures, amputations, and the intensity of affective temperaments did not correlate with HADS scores. Discussion: The study highlighted the intricate relationship between mood disorders and PAD severity, emphasizing the potential prognostic implications of untreated depression and anxiety in PAD patients. These findings suggest the importance of closely monitoring and addressing psychological well-being in PAD management. However, the study encountered limitations such as varying assessment timing and sample size discrepancies among comorbidities, impacting the observation of associations between mood disorders and certain conditions. Conclusion: In conclusion, depressive and anxiety symptoms are often in PAD. Further research is needed to explore therapeutic interventions targeting mental health and pain management to improve the course and outcomes of PAD.

Prostate-Specific Antigen and Testosterone Levels as Biochemical Indicators of Cognitive Function in Prostate Cancer Survivors and the Role of Diabetes.

Prostate cancer (PC) is one of the most common malignancies in men. The increase in the number of PC survivors is associated with many problems including cognitive impairment. Early detection of such problems facilitates timely protective intervention. This study examined the association between prostate-specific antigen (PSA) or testosterone (T) levels and cognitive function in patients undergoing radical prostatectomy. Such a correlation could help identify patient groups at risk of cognitive impairment. Participants underwent clinical (demographic data, medical history, physical examination, and blood analyses) and neuropsychological assessment (cognitive test battery). Preoperative PSA or T levels were not associated with cognitive function. However, long-term follow-up after prostatectomy showed a strong correlation between PSA levels and the results of verbal memory and executive function tests. A trend toward significance was also observed for visuospatial memory. The levels of free T and total T were not correlated with cognitive function. Only the levels of free T after hormonal treatment were significantly correlated with executive functions. Comorbid diabetes affected these correlations. In conclusion, PSA levels at a distant postoperative time and free T level after hormonal treatment may be biomarkers of cognitive function.

Biochemical Parameters in Cognitive Functions.

Cognitive impairment is a common disease. Many studies attempt to explain the mechanisms of these dysfunctions formation, including correlations between cognitive functions and biochemical parameters. Scientists search for substances that would be indicators of cognitive functions and which could be determined in the cerebrospinal fluid or blood of the subjects. To date, they have isolated a few of such substances; however, research on their specificity, validity and the possibility of their use in diagnostics and prognostic assessment is still ongoing. However, there have been only few reports in the literature systematizing the existing knowledge on this subject, and they are mostly related to Alzheimer's disease, not cognition in general, or referring only to a specific group of substances. This article discusses the most important biochemical exponents of cognitive functions.

Multiplex Eukaryotic Transcription (In)activation: Timing, Bursting and Cycling of a Ratchet Clock Mechanism.

Activation of eukaryotic transcription is an intricate process that relies on a multitude of regulatory proteins forming complexes on chromatin. Chromatin modifications appear to play a guiding role in protein-complex assembly on chromatin. Together, these processes give rise to stochastic, often bursting, transcriptional activity. Here we present a model of eukaryotic transcription that aims to integrate those mechanisms. We use stochastic and ordinary-differential-equation modeling frameworks to examine various possible mechanisms of gene regulation by multiple transcription factors. We find that the assembly of large transcription factor complexes on chromatin via equilibrium-binding mechanisms is highly inefficient and insensitive to concentration changes of single regulatory proteins. An alternative model that lacks these limitations is a cyclic ratchet mechanism. In this mechanism, small protein complexes assemble sequentially on the promoter. Chromatin modifications mark the completion of a protein complex assembly, and sensitize the local chromatin for the assembly of the next protein complex. In this manner, a strict order of protein complex assemblies is attained. Even though the individual assembly steps are highly stochastic in duration, a sequence of them gives rise to a remarkable precision of the transcription cycle duration. This mechanism explains how transcription activation cycles, lasting for tens of minutes, derive from regulatory proteins residing on chromatin for only tens of seconds. Transcriptional bursts are an inherent feature of such transcription activation cycles. Bursting transcription can cause individual cells to remain in synchrony transiently, offering an explanation of transcriptional cycling as observed in cell populations, both on promoter chromatin status and mRNA levels.

Tracing the molecular basis of transcriptional dynamics in noisy data by using an experiment-based mathematical model.

Changes in transcription factor levels, epigenetic status, splicing kinetics and mRNA degradation can each contribute to changes in the mRNA dynamics of a gene. We present a novel method to identify which of these processes is changed in cells in response to external signals or as a result of a diseased state. The method employs a mathematical model, for which the kinetics of gene regulation, splicing, elongation and mRNA degradation were estimated from experimental data of transcriptional dynamics. The time-dependent dynamics of several species of adipose differentiation-related protein (ADRP) mRNA were measured in response to ligand activation of the transcription factor peroxisome proliferator-activated receptor δ (PPARδ). We validated the method by monitoring the mRNA dynamics upon gene activation in the presence of a splicing inhibitor. Our mathematical model correctly identifies splicing as the inhibitor target, despite the noise in the data.

Population-level transcription cycles derive from stochastic timing of single-cell transcription.

Eukaryotic transcription is a dynamic process relying on a large number of proteins. By measuring the cycling expression of the pyruvate dehydrogenase kinase 4 gene in human cells, we constructed a detailed stochastic model for single-gene transcription at the molecular level using realistic kinetics for diffusion and protein complex dynamics. We observed that gene induction caused an approximate 60 min periodicity of several transcription related processes: first, the covalent histone modifications and presence of many regulatory proteins at the transcription start site; second, RNA polymerase II activity; third, chromatin loop formation; and fourth, mRNA accumulation. Our model can predict the precise timing of single-gene activity leading to transcriptional cycling on the cell population level when we take into account the sequential and irreversible multistep nature of transcriptional initiation. We propose that the cyclic nature of population gene expression is primarily based on the intrinsic periodicity of the transcription process itself.