Neurodegenerative conditions significantly impact patient quality of life. Many conditions do not have a cure, but with appropriate and timely treatment the advance of the disease could be diminished. However, many patients only seek a diagnosis once the condition progresses to a point at which the quality of life is significantly impacted. Effective non-invasive and readily accessible methods for early diagnosis can considerably enhance the quality of life of patients affected by neurodegenerative conditions. This work explores the potential of convolutional neural networks (CNNs) for patient gain freezing associated with Parkinson’s disease. Sensor data collected from wearable gyroscopes located at the sole of the patient’s shoe record walking patterns. These patterns are further analyzed using convolutional networks to accurately detect abnormal walking patterns. The suggested method is assessed on a public real-world dataset collected from parents affected by Parkinson’s as well as individuals from a control group. To improve the accuracy of the classification, an altered variant of the recent crayfish optimization algorithm is introduced and compared to contemporary optimization metaheuristics. Our findings reveal that the modified algorithm (MSCHO) significantly outperforms other methods in accuracy, demonstrated by low error rates and high Cohen’s Kappa, precision, sensitivity, and F1-measures across three datasets. These results suggest the potential of CNNs, combined with advanced optimization techniques, for early, non-invasive diagnosis of neurodegenerative conditions, offering a path to improve patient quality of life.

Systemic arterial hypertension (HTN) is the main cause of morbidity and mortality, and HTN crises contribute significantly to an unfavourable clinical course. For decades, HTN crises have been dichotomized into hypertensive emergency (HTN-E) and hypertensive urgency (HTN-U). The main difference between the two is the presence of acute hypertension-mediated organ damage (HMOD) - if HMOD is present, HTN crisis is HTN-E; if not, it is HTN-U. Patients with HTN-E are in a life-threatening situation. They are hospitalized and receive antihypertensive drugs intravenously (IV). On the other hand, patients with HTN-U are usually not hospitalized and receive their antihypertensives orally. We suggest a modification of the current risk stratification scheme for patients with HTN crises. The new category would be the intermediate risk group, more precisely the 'impending HTN-E' group, with a higher risk in comparison to HTN-U and a lower risk than HTN-E. 'Impending HMOD' means that HMOD has not occurred (yet), and the prognosis is, therefore, better than in patients with ongoing HMOD. There are three main reasons to classify patients as having impending HTN-E: excessively elevated BP, high-risk comorbidities, and ongoing bleeding/high bleeding risk. Their combinations are probable. This approach may enable us to prevent some HTNEs by avoiding acute HMOD using a timely blood pressure treatment. This treatment should be prompt but controlled.

The goal of this study was to examine the effects of group art therapy on different measures of both therapeutic processes (group cohesion and art therapy-related emotional regulation) and therapeutic outcomes (self-esteem, social state self-esteem, and distress) in a clinically heterogenous sample. This is a pretest-posttest control group design with a random allocation of participants, i.e., randomized control trial. The sample consisted of 160 patients (68.75% female) aged 14 to 73 years (M = 43.19, SD = 14.06; nART = 87, nTAU=73). Participants completed self-report measures of distress (depression, anxiety, and stress), self-esteem, social state self-esteem, group cohesion (GCQ), and self-expression and emotion regulation in art therapy (SERATS). The group art therapy lasted for six once-a-week sessions were 90 min long. GCQ and SERATS have unidimensional factor structures. The results showed that art therapy has statistically significant positive effects on group cohesion, self-esteem, and social state self-esteem, and lowering effects on anxiety as compared to active treatment-as-usual. Moreover, self-expression and emotional regulation during art therapy increased in the art therapy group. The measures of mental health outcomes and psychotherapeutic processes are meaningfully related in the art therapy group. In conclusion, this study presents some novel evidence for the benefits of art therapy.

Horakova, Lenka , Susi Kriemler, Vladimír Študent, Jacqueline Pichler Hefti, David Hillebrandt, Dominique Jean, Kastė Mateikaitė-Pipirienė, Peter Paal, Alison Rosier, Marija Andjelkovic, Beth Beidlemann, Mia Derstine, and Linda E. Keyes. Hormonal contraception and menstrual cycle control at high altitude: a scoping review-UIAA Medical Commission recommendations. High Alt Med Biol. 00:00-00, 2024. Background: Women who use hormonal contraception (HC) may have questions about their use during travel to high altitude. This scoping review summarizes current evidence on the efficacy and safety of HC and cycle control during high-altitude travel. Methods: We performed a scoping review for the International Climbing and Mountaineering Federation (UIAA) Medical Commission series on Women's Health in the Mountains. Pertinent literature from PubMed and Cochrane was identified by keyword search combinations (including contraception) with additional publications found by hand search. Results: We identified 17 studies from 7,165 potentially eligible articles. No articles assessed the efficacy of contraception during a short-term high-altitude sojourn. Current data show no advantage or disadvantage in HC users for acclimatization or acute mountain sickness (AMS). Use of HC during high-altitude travel is common and safe for menses suppression. A potential concern of estrogen-containing HC is the increased thrombotic risk, which theoretically could be compounded in hypobaric hypoxia. Conclusions: Evidence is limited for the interaction of HC and high altitude on performance, thrombosis, and contraceptive efficacy. HC does not affect the risk of AMS. The most efficacious and safest method at high altitude is generally the one women are most familiar with and already using.

Many methods exist for solving the problem of evaluating efficiency in different processes. They are divided into two basic groups, parametric and non-parametric methods, which can have significant differences in the results. In this study, the authors consider the process of assessing the business climate depending on realized foreign investments. Due to the expected difference in efficiency assessment using different approaches, the goal of this paper is to create an optimization model of an ensemble for efficiency assessment that uses both types of methods with the aim of creating a symmetrical approach that achieves better results than each type of method individually. The proposed solution simultaneously analyzes the impact of different factors on foreign investments in order to determine the most important factors and thus enable each local government to ensure the best possible efficiency in this process. The innovative idea of this study is in the inclusion of classification and feature selection methods of machine learning to fulfill the set goal. Our research, focused on a specific case study in various cities across the Republic of Serbia, evaluated the effectiveness of that process. This study extends previous research and confirms the published results, highlighting the advantages of the newly proposed model.

The aim of this review is to provide a summary of the botany, phytochemistry and dermatological effects of Punica granatum (PG), with special emphasis on therapeutic mechanisms in various skin conditions. PG peel contains the highest levels of chemical compounds. Due to the high abundance of polyphenolic compounds, including phenolic acids, anthocyanins and flavonoids, exhibiting strong antioxidant properties, PG peel possesses significant health-promoting effects. Up until now, different parts of PG in the form of various extracts, fixed seed oil or individual active compounds have been investigated for various effects on skin conditions in in vitro and in vivo studies, such as antioxidant, anti-inflammatory, antimicrobial, chemoprotective and antiaging effects, as well as positive effects on striae distensae, skin repair mechanisms, erythema, pigmentation and psoriasis. Therefore, formulations containing PG active compounds have been used for skincare of diseased and healthy skin. Only a few effects have been confirmed on human subjects. Based on encouraging results obtained in in vitro and animal studies about the numerous substantial dermatological effects of PG active compounds, future perspectives should incorporate more in vivo investigations in human volunteers. This approach can aid in identifying the optimal concentrations and formulations that would be most efficacious in addressing specific skin conditions.

Purpose: This study explores corporate news communication about intangible assets during the COVID-19 crisis in the largest global pharmaceutical companies. Methodology/approach: Computerised lexical content analysis was performed on 297 articles (texts) from 34 companies, amounting to 280,246 words. We generated a bottom-up clustering of the keywords, titles and abstracts. The qualitative data were obtained from the ProQuest textual database by Clarivate. Findings: The research demonstrates that the biggest global pharmaceutical companies focused intensively on intangible assets during the crisis. They disclosed information on three main intangibles: (1) brand, (2) patent and (3) license, covering 78.17% of the entire corpus text. Research limitations: The study limitations include the fact that the sample concerns only the biggest pharmaceutical companies that met our criteria. Further research could cover small and medium-sized companies and other industries. Finally, further analysis could combine quantitative and qualitative methods within the same research. Originality/value: The research article contributes to the current literature on intangible asset narratives, showing how the biggest pharmaceutical companies tend to achieve a competitive advantage, stay successful during a crisis and address messages to their key stakeholders. Considering the high risks and existing uncertainties, these messages could be of the utmost importance.

Recent advances in computing power triggered the use of artificial intelligence in image analysis in life sciences. To train these algorithms, a large enough set of certified labeled data is required. The trained neural network is then capable of producing accurate instance segmentation results that will then need to be re-assembled into the original dataset: the entire process requires substantial expertise and time to achieve quantifiable results. To speed-up the process, from cell organelle detection to quantification across electron microscopy modalities, we propose a deep-learning based approach for fast automatic outline segmentation (FAMOUS), that involves organelle detection combined with image morphology, and 3D meshing to automatically segment, visualize and quantify cell organelles within volume electron microscopy datasets. From start to finish, FAMOUS provides full segmentation results within a week on previously unseen datasets. FAMOUS was showcased on a HeLa cell dataset acquired using a focused ion beam scanning electron microscope, and on yeast cells acquired by transmission electron tomography. RESEARCH HIGHLIGHTS: Introducing a rapid, multimodal machine-learning workflow for the automatic segmentation of 3D cell organelles. Successfully applied to a variety of volume electron microscopy datasets and cell lines. Outperforming manual segmentation methods in time and accuracy. Enabling high-throughput quantitative cell biology.

This review summarises our two decades of polychlorinated biphenyl (PCB) monitoring in different marine organisms along the eastern Adriatic Sea. The aim was to gain an insight into the trends of PCB distribution in order to evaluate the effectiveness of past and current legislation and suggest further action. Here we mainly focus on PCB levels in wild and farmed Mediterranean mussels, wild and farmed bluefin tuna, loggerhead sea turtles, common bottlenose dolphins, and small pelagic fish. The use of artificial intelligence and advanced statistics enabled an insight into the influence of various variables on the uptake of PCBs in the investigated organisms as well as into their mutual dependence. Our findings suggest that PCBs in small pelagic fish and mussels reflect global pollution and that high levels in dolphins and wild tuna tissues raise particular concern, as they confirm their biomagnification up the food chain. Therefore, the ongoing PCB monitoring should focus on predatory species in particular to help us better understand PCB contamination in marine ecosystems in our efforts to protect the environment and human health.