The aim of this study is to describe a research protocol of a multi-country randomized controlled trial to investigate the effect of a smartphone CBT stress management program on improving depression and other health- and work-related outcomes among hospital nurses in Vietnam and Thailand during the COVID-19 epidemic as a part of the COCONATS project. The study is a two-arm, parallel randomized control trial. Hospital nurses (N = 1,500) will be recruited in Vietnam and Thailand, and those who meet the criteria will be randomly allocated to the intervention or control (treatment as usual) group. A seven-week, seven-module smartphone-based stress management program will be developed to teach CBT skills. The intervention group will participate in the program for 10 weeks. Depression as the primary outcome will be measured using the DASS21 at baseline and in 3- and 6-month follow-up surveys. A mixed model repeated measures analysis will be used to test the intervention effect in the total combined sample, on an intention-to-treat basis. This is the first study to investigate the effectiveness of a self-guided smartphone CBT program on improving depression among hospital nurses using a RCT design in South-East Asian middle-income countries during the COVID-19 pandemic.

Care coordination (CC) for children with special healthcare needs and medical complexity (CSHCN-CMC) is challenging, and medication management is especially difficult for providers, parents/caregivers, and patients alike. While numerous strategies for CC have been suggested and implemented, barriers to medication optimization remain. The report describes the creation of a pediatric clinical pharmacotherapy practice, related standard operating procedures to assure consistent application of screening tools and care provision through comprehensive medication management (CMM), and establishment of a collaborative practice agreement (CPA) to guide drug therapy delegation, monitoring, and modification. The methodology of a prospective case series is also presented to highlight drug therapy problems and their resolution in CSHCN-CMC. Future opportunities to expand the practice for engagement in population health management as well as prior authorization activities on behalf of physicians will be discussed.

At present, there are no hardware or biochemical systems allow to assess the severity of post-COVID syndrome in vivo. The hardware of the proposed biotechnical system is based on routine transthoracic electrical impedance rheography, which makes it possible to register the frequency characteristics of the patient's bioimpedance response to controlled stress stimulation, thereby simultaneously fixing the characteristics of his productive heart, the state of the hemomicrocirculatory bed, the efficiency of the gas transport function of his blood, and also reliably assess personal reactivity and adaptive potential. Subsequent mathematical approximation of the obtained biometric data by an original neural network makes it possible to rank the results obtained and automatically generate a program of medical rehabilitation for a particular patient, depending on the severity of his post-COVID syndrome. The study results proved two reliable physiological signs confirming the presence of latent post-COVID complications: a decrease in the base impedance value for light exercise and an increase in the length of the systolic arc of the rheocardiogram.

This report is a narrative of a certified nurse working on a long-term rehabilitation ward for patients with dementia in Japan during the early phase of the COVID-19 pandemic. During this time visitation restrictions had been implemented to prevent the spread of COVID-19 causing psychological distress for patients and their families which nurses had to cope with . The nurse was interviewed twice September–October 2020. The recordings were transcribed verbatim and analysed thematically. Three themes were identified relating to changes in care in response to the pandemic which nurses had to adapt to: the risk of collapse of family members’ roles, anxiety caused by patients forgetting family members and family memories and increased disorientation. During the pandemic, nursing care needs to adapt, ensuring that family attachments and ties continue and minimizing the disruption caused by the pandemic, while ensuring that everyone remains Covid-safe.

Improving access to sexual health services is critical in light of rising sexually transmitted infections (STIs). We evaluated a Hub and Spoke model for improving access to sexual health services in three general practices in Victoria, Australia. The primary outcome was the impact on HIV and STI (chlamydia, gonorrhoea, syphilis) testing. Segmented linear regression analysis was conducted to examine the trends in the total HIV/STI tests before (from January 2019 to June 2020) and post-implementation (from July 2020 to July 2021). We evaluated the feasibility and acceptability of integrating this model into the general practices using semi-structured individual interviews. There was a statistically significant rise in testing for HIV and STIs in all general practices: post-implementation, there was an increase of an average of 11.2 chlamydia tests per month (p=0.026), 10.5 gonorrhoea tests per month (p=0.001), 4.3 syphilis tests per month (p=0.010), and 5.6 HIV tests per month (p=0.010). Participants reported increases in knowledge level and confidence in offering STI testing and managing more variety of sexual health cases. This study demonstrated the feasibility of implementing a hub and spoke model to enable GPs to deliver sexual health care with support from a sexual health specialist service.

This paper addresses crashes involving heavy goods vehicles (HGV) in Europe focusing on long-haul trucks weighing 16 tons or more (16t+). The identification of the most critical scenarios and their characteristics is based on a three-level analysis: general crash statistics from CARE addressing all HGVs, results about 16t+ trucks from national crash databases and a detailed study of in-depth crash data from GIDAS, including a crash causation analysis. Most European HGV crashes occur in clear weather, during daylight, on dry roads, outside city limits, and on non-highway roads. Three main scenarios for 16t+ trucks are characterized in-depth: (1) rear-end crashes in which the truck is the striking partner, (2) conflicts during right turn maneuvers of the truck and a cyclist riding alongside and (3) pedestrians crossing the road in front of the truck. Among truck-related crash causes, information admission failures (e.g. distraction) were the main causing factors in 72% of cases in scenario (1) while information access problems (e.g. blind spots) were present for 72% of cases in scenario (2) and 75% of cases in scenario (3). The results provide both a global overview and sufficient depth of analysis in the most relevant cases and thereby aid safety system development.

Artificial Intelligence are creating a paradigm shift in health care, being phenotyping patients through clustering techniques one of the areas of interest. Objective: To develop a predictive model to classify heart failure (HF) patients according to their left ventricular ejection fraction (LVEF), by using available data in Electronic Health Records (EHR). Subjects and methods: 2854 subjects more than 25 years old with diagnose of HF and LVEF measured by echocardiography were selected to develop an algorithm to predict patients with reduced EF using supervised analysis. Performance of the algorithm developed were tested in heart failure patients from Primary Care. To select the most influencing variables, LASSO algorithm setting was used and to tackle the issue of one class exceed the other one by a large proportion we used the Synthetic Minority Oversampling Technique (SMOTE). Finally, Random Forest (RF) and XGBoost models were constructed. Results: Full XGBoost model obtained the maximized accuracy, a high negative predictive value and the highest positive predictive value. Gender, age, unstable angina, atrial fibrillation and acute myocardial infarct are the variables that most influence FE value. Applied in the EHR data set with a total 25594 patients with an ICD-code of HF and no regular follow-up in Cardiology clinics, 6170 (21.1%) were identified as those pertaining to the reduced EF group. Conclusion: The algorithm obtained is able to rescue a number of HF patients with reduced ejection fraction that can be take benefit for a protocol with strong recommendation to succeed. Furthermore, the methodology can be used for studies with data extracted from the Electronic Health Records.

COVID-19 pandemic has the potential to adversely affect the mental health of healthcare workers (HCWs). The public healthcare system in Greece was already facing serious challenges at the outset of the outbreak following years of austerity and an escalating refugee crisis. The multi-center, cross-sectional study aims to assess the levels and associated risk factors of anxiety, depression, traumatic stress and burnout of frontline staff in Greece. A total of 464 HCWs in six reference hospitals completed a self-administered questionnaire comprising of sociodemographic and work-related information and psychometric scales. The proportion of HCWs with symptoms of moderate/severe depression, anxiety and traumatic stress were 30%, 25% and 33% respectively. Burnout levels were particularly high with 65% of respondents scoring moderate/severe in Emotional Exhaustion, 92% severe in Depersonalization and 51% low/moderate in Personal Accomplishment. Predictive factors of adverse psychological outcomes included fear, perceived stress, risk of infection, lack of protective equipment and low social support. The psychological burden associated with Covid-19 in healthcare professionals in Greece is considerable with more than half experiencing at least mild mental health difficulties. Findings signal the need for immediate organizational and individually tailored interventions to enhance resilience and support wellbeing under pandemic conditions.

Levels of synthetic musk fragrances (SMFs) and various personal care products (PCPs) were measured in the Han River and its tributaries in Seoul, Korea. The most abundant SMF in all river and PCP samples was 4,6,6,7,8,8-hexamethyl-1,3,4,7-tetrahydrocyclopenta[g]isochromene (HHCB), followed by 1-(3,5,5,6,8,8-hexamethyl-6,7-dihydronaphthalen-2-yl)ethanone (AHTN), musk ketone (MK), and 1,1,2,3,3-pentamethyl-2,5,6,7-tetrahydroinden-4-one (DPMI). There was a significant correlation between the SMF concentration in the PCPs and the Han River samples. Moving from upstream to downstream in the Han River, the median SMF concentration was 6.756, 2.945, 0.304, and 0.141 μg/L in the sewage treatment plant (STP) influent, effluent, tributaries, and mainstream, respectively, implying that effective SMF removal was achieved during the sewage treatment process, followed by dilution in the receiving water. Four STPs using advanced biological treatment processes had removal efficiencies of 55.8%, 50.6%, 43.3% for HHCB, AHTN, and MK, respectively. The highest SMF concentrations in the tributaries were observed at locations close to the STPs. Our study confirmed that the main source of SMFs in the receiving water were sewage effluent containing untreated SMFs, which are largely originated from household PCPs, especially hair care products (e.g., shampoo) and perfumes.

Background and Objectives The socioeconomics working group of the European ME/CFS Research Network (EUROMENE) has conducted a review of the literature pertaining to GPs’ knowledge and understanding of ME/CFS. Materials and Methods A MEDLINE search was carried out. The papers identified were reviewed following the Synthesis Without Meta-analysis (SWiM) methodology, and were classified according to the focus of the enquiry (patients, GPs, database and medical record studies, evaluation of a training programme, and overview papers), and whether they were quantitative or qualitative in nature. Results 33 papers were identified in the MEDLINE search. The quantitative surveys of GPs demonstrated that a third to a half of all GPs did not accept ME/CFS as a genuine clinical entity and, even when they did, they lacked confidence in diagnosing or managing it. Patient surveys indicated that a similar proportion of patients was dissatisfied with the primary medical care they had received. These findings were consistent with the findings of the qualitative studies that were examined, and have changed little over several decades. Conclusions Lack of knowledge and understanding of ME/CFS among GPs is widespread, and the resultant diagnostic delays constitute a risk factor for severe and prolonged disease. Failure to diagnose ME/CFS renders problematic attempts to determine its prevalence, and hence its economic impact.

On March 2020 strict measures took place in Finland to limit the COVID -19 pandemic. A majority of the Finnish COVID -19 –patients have been located in the southern Finland and consequently cared for in the HUS Helsinki University Hospital. During the ongoing pandemic, HUS personnel’s psychological symptoms are followed via an electronic survey, which also delivers information on psychosocial support services. The baseline survey in June 2020 was sent to 25494 HUS employees out of whom 4804 (19%) answered; altogether 62.4% of the respondents were nursing staff and 8.9% medical doctors. While the follow-up continues for a year and a half, this report shares the sociodemographic characteristics of the respondents and the first results of psychological symptoms from the baseline survey. Out of those who were directly involved in pandemic patients` care, 43.4% reported potentially traumatic COVID-19 pandemic-related experiences vs. 21.8% among the other (p < 0.001). While over a half of the personnel was symptomless, a group of respondents reported pandemic work –related traumatic events and concurrent depressive, insomnia and anxiety symptoms. This highlights the need to ensure appropriate psychosocial support services to all traumatized personnel and PTEs were present especially among nursing staff.

The research objectives was to determine the plants vegetation profile in forest revegetation and Mount Arjuna springs. The method used was descriptive method. While based on the techniques and tools used to research, the author uses the survey method to obtain facts that occur in the research area, namely in the area around the springs of Arjuna mount, Pasuruan, East Java, Indonesia. Data obtained in the field are then processed and analyzed using GIS, ArcView 3.3 and Google Earth programs. The results of the study explain the profile of plant vegetation, namely plant stratification, bird wealth, taxonomic wealth and plant density have a significant effect on forest revegetation and springs in Arjuna mount. The forest vegetation profile has a positive and significant effect on the preservation of springs. The better the profile of forest vegetation, the preservation of springs will be better, and vice versa.

The Affordable Care Act (ACA) is at the crossroads. It is important to evaluate the effectiveness of the ACA in order to make rational decisions about the ongoing healthcare reform, but existing research into its effect on health insurance status in the United States is insufficient and descriptive. Using data from the National Health Interview Surveys from 2009 to 2015, this study examines changes in health insurance status and its determinants before the ACA in 2009, during its partial implementation in 2010–2013, and after its full implementation in 2014 and 2015. The results of trend analysis indicate a significant increase in national health insurance rate from 82.2% in 2009 to 89.4% in 2015. Logistic regression analyses confirm the similar impact of age, gender, race, marital status, nativity, citizenship, education, and poverty on health insurance status before and after the ACA. Despite similar effects across years, controlling for other variables, youth aged 26 or below, the foreign-born, Asians, and other races had a greater probability of gaining health insurance after the ACA than before the ACA; however, the odds of obtaining health insurance for Hispanics and the impoverished rose slightly during the partial implementation of the ACA but somewhat declined after the full implementation of the ACA starting in 2014. These findings should be taken into account by the U.S. government in deciding the fate of the ACA.

The good management of the building maintenance should be based on the regular maintenance work. Repair works are often not carried out or there are shifts in time, which causes degradation of the building. The article presents a method of planning renovation works of a MUBAR (maintenance Management in an Un-renovated Building with Abandoning Renovation) based on the consequences in case of their lack. No renovation work on individual elements in a building can cause a threat to the stability of the building structure, risking the lives of users, continuing damage to the building by damaging further elements, or even a building disaster. The method can also be applied to historic buildings. Often, due to abandonment of repairs caused most often by lack of the owner, improper manager or irresponsible users, degradation of these objects occurs. The consequences of neglected renovation of buildings lead to irreversible processes of their destruction. The aim of the article is to present the developed method of planning renovation works based on the consequences of lack of renovation works.

The theory says that the first things to exist in the universe and the current moment were driven by an imperative need; that is, the intensities of the physical concept specify influence the existence of elements and facts based on the countless observations in physical spaces in relation to elements and facts. The existence of mandatory elements in space is motivated by the characteristics of the spaces that offer conditions for such an obligation. The theory states that the universe did not arise by chance; that is, the universe emerged through determination influenced by its surroundings. The objective of the study is to help explain the elements and facts of the universe from its origins to the present.

In this paper, existence and stability results of non-local integro-differential equation with Hilfer derivative of order ω∈(1,2) have been investigated. In this derivative is applied in RLC circuit equation of various fractional order. To proposed problem the existence solutions are derived using Schaefer’s fixed point theorem and the Banach contraction principle is using for uniqueness results. To demonstrate the effectiveness and applicability of our theoretical conclusions and two-step Lagrange polynomial interpolation were used to solve four numerical results.

Little is known about how differences in water availability within the “super humid” tropics can influence the distribution of understory plant species and the composition of understory plant communities. We investigated variation in the physiological drought tolerances of understory plants and plant communities across a large elevation and precipitation gradient. We established 58 understory plots along a gradient of 400 – 3600 m asl elevation and 1000 – 6000 mm yr-1 rainfall in and around Manu National Park in southeastern Peru. Within the plots, we sampled all understory woody plants and measured three metrics of physiological leaf drought tolerance - turgor loss point (TLP), cuticular conductance (Gmin), and solute leakage (SL) - and assessed how the community-level means of these traits related to mean annual precipitation (MAP) and elevation (in the study gradient temperature decreases linearly and vapor pressure deficit increases monotonically with elevation). We did not find any correlations between the three metrics of leaf drought tolerance, suggesting that they represent independent strategies for coping with low water availability. Despite being widely used metrics of leaf drought tolerance, neither TLP nor Gmin showed any significant relationships with elevation or MAP. In contrast, SL, which has only recently been developed for use in ecological field studies, increased significantly at higher precipitations and at lower elevations (i.e., plants in colder and drier habitats have lower SL, indicating greater drought tolerances). Our results illustrate that differences in water availability may play a strong role in structuring plant communities even in in the wet tropics and highlight the potential for SL assays to be an efficient and effective tool for measuring drought tolerances in the field.

This study presents the solution of the second type of a two-dimensional nonlinear integral equation in Banach space. Also, the existence and uniqueness of this equation’s solution are discussed. We utilize a numerical approach involving hybrid and block-pulse functions to obtain the approximate solution of a two-dimensional nonlinear integral equation. Nonlinear integral equation in two dimensions is reduced numerically to a system of nonlinear algebraic equations that can be solved using numerical methods. This study focuses on showing the convergence analysis for the numerical approach and obtaining an error estimate. Some numerical examples have been provided to demonstrate the approach’s viability and efficacy

The rapid development of three-dimensional (3D) acquisition technology based on 3D sensors provides a large volume of data, which is often represented in the form of point clouds. Point cloud representation can preserve the original geometric information along with associated attributes in a 3D space. Therefore, it has been widely adopted in many scene-understanding-related applications such as virtual reality (VR) and autonomous driving. However, the massive amount of point cloud data aggregated from distributed 3D sensors also poses challenges for secure data collection, management, storage, and sharing. Thanks to the characteristics of decentralization and security nature, Blockchain has a great potential to improve point cloud services and enhance security and privacy preservation. Inspired by the rationales behind Software Defined Network (SDN) technology, this paper envisions SAUSA, a blockchain-based authentication network that is capable of recording, tracking, and auditing the access, usage, and storage of 3D point cloud data sets in their life-cycle in a decentralized manner. SAUSA adopts an SDN-enabled point cloud service architecture which allows for efficient data processing and delivery to satisfy diverse Quality-of-Service (QoS) requirements. A blockchain-based authentication framework is proposed to ensure security and privacy preservation in point cloud data acquisition, storage, and analytics. Leveraging smart contracts for digitizing access control policies and point cloud data on the blockchain, data owners have full control of their 3D sensors and point clouds. In addition, anyone can verify the authenticity and integrity of point clouds in use without relying on a third party. Moreover, SAUSA integrates a decentralized storage platform to store encrypted point clouds while recording references of raw data on the distributed ledger. Such a hybrid on-chain and off-chain storage strategy not only improves robustness and availability but also ensures privacy preservation for sensitive information in point cloud applications. A proof-of-concept prototype is implemented and tested on a physical network. The experimental evaluation validates the feasibility and effectiveness of the proposed SAUSA solution.

The task of determining the distance from one object to another is one of the important tasks solved in robotics systems. Conventional algorithms rely on an iterative process of predicting distance estimates, which results in an increased computational burden. Algorithms used in robotic systems should require minimal time costs, as well as be resistant to the presence of noise. To solve these problems, the paper proposes an algorithm for Kalman combination filtering with a Goldschmidt divisor and a median filter. Software simulation showed an increase in the accuracy of predicting the estimate of the developed algorithm in comparison with the traditional filtering algorithm, as well as an increase in the speed of the algorithm. The results obtained can be effectively applied in various computer vision systems.

This work presents a control scheme to control the grid-connected single-phase photovoltaic (PV) system. The considered system has four 250W solar panels, a non-inverting buck-boost DC-DC converter, and DC-AC inverter with LCL filter. The control system aims to track and operate at the maximum power point (MPP) of PV panels, regulate the voltage of DC link, and supply the grid with a unity power factor. To well achieve these goals, the proposed control system consists of three parts, that are MPP tracking controller module with a fuzzy-based modified incremental conductance (INC) algorithm, a DC-link voltage regulator with a hybrid fuzzy proportional-integral (PI) controller, and a Current Controller module using the linear quadratic regulator (LQR) for grid-connected power. Based on fuzzy control and LQR, this work introduces a full control solution for grid-connected single-phase PV systems. The key novelty of this research is to analyze and prove that the newly proposed method is more successful in numerous aspects by comparing and evaluating the previous and present control methods. The designed control system settles quickly, which is critical for output stability. In addition, as compared to backstepping approach used in our past study, the LQR technique is more resistant to sudden changes and disturbances. Furthermore, backstepping method produces the larger overshoot, which has a detrimental impact on efficiency. Simulation findings under various weather conditions were compared to theoretical ones to indicate that the system can deal with variations in weather parameters.

This Paper intends to introduce the notion of prime ideals of Intuitionistic fuzzy normed Rings and to establish basic properties related to it. It investigates these notions and shown anew Result using intuinistic fuzzy points and non membership function incorparating with t-norm and s-norm to show aome results of fuzzy prime ideal.

It has now known that at least 10% of samples with pancreatic cancers (PC) contain a causative mutation in the known susceptibility genes, suggesting the importance of identifying cancer-associated genes that carry the causative mutations in high-risk individuals for early detection of PC. In this study, we develop a statistical pipeline using a new concept, called gene-motif, that utilizes both mutated genes and mutational processes to identify 4,211 3-nucleotide PC-associated gene-motifs within 203 significantly mutated genes in PC. Using these gene-motifs as distinguishable features for pancreatic cancer subtyping results in identifying five PC subtypes with distinguishable phenotypes and genotypes. Our comprehensive biological characterization reveals that these PC subtypes are associated with different molecular mechanisms including unique cancer related signaling pathways, in which for most of the subtypes targeted treatment options are currently available. Some of the pathways we identified in all five PC subtypes, including cell cycle and the Axon guidance pathway are frequently seen and mutated in cancer. We also identified Protein kinase C, EGFR (epidermal growth factor receptor) signaling pathway and P53 signaling pathways as potential targets for treatment of the PC subtypes. Altogether, our results uncover the importance of considering both the mutation type and mutated genes in the identification of cancer subtypes and biomarkers.

C-C Chemokine receptor type 5 (CCR5) is expressed on the CD4 T cell surface where CXCR4 and CCR5 expressions are controlled differently during the activation of T cells and with the binding of interleukin type-2 (IL-2). IL-2 can upregulate CCR1 and CCR2 in CD45R01 T cells and increase the T lymphocyte chemotaxis toward CC-chemokines. CD4+ T cells are either apart of the T helper 1 or Th1 lymphocytes that release interferon gamma (IFNγ) and lymphotoxin that provide cellular immunity to internal pathogens and T helper cells type 2 (Th2), which secrete interleukins 4 and 5 (IL-4 and IL-5). IL-4 and IL-5 cause an allergic and humoral immune response to parasites. Th2 lymphocytes use CCR3 chemokine receptors. CCR5 and CXCR3 chemokine receptors are specific for CD4+ Th1 and Th2 lymphocytes. CCR5Δ32 is a 32-base-pair deletion of the CCR5 gene. CCR5 is a co-receptor for the entrance of the human immunodeficiency virus-1 (HIV-1). CCR5Δ32 creates a malfunction of the CCR5 protein that can prevent HIV-1 infection. However, the CCR5Δ32 32-base-pair deletion is not prevalent and predominant in many populations worldwide and there also exist more genetic variations of CCR5 known as CCR5-SNPs. An alternative polymorphism was identified based on the CCR5 gene that was identified as a A to G (A/G) point mutation. This point mutation is located at the 59029 locus on the promoter that lowers the expression rate of CCR5. Gurdol et al. found activity at the promoter of CCR5/590029G was 45% lesser than the CCR5/59029A. The genetic variations of CCR5 SNPs also include: 2459G>SNP of CCR5, C101X, CCR5 gene position at -2273, and the A to G SNP mutation found in two South African blacks. Therefore, more studies are needed to find more and varied chemokine polymorphisms that are present in many diverse populations in the world. The aim of this literature review is to describe the immense impact of CCR5 SNP mutations on viral infection susceptibility, on the pathogenesis of chronic conditions, to endorse the increased discovery of more novel CCR5 SNPs, and to show the significant potential of anti-CCR5 therapies to treat multiple diseased conditions.

Current pharmacological treatments of Fibromyalgia (FM) are merely symptom palliative, as clinical trials have so far failed to provide overall benefits without associated harms. Polypharmacy often leads to patient´s health deterioration and chronic drug use to an eventual lack of patient´s response. Emerging evidence support that physiotherapy treatments based on mechanical triggers improve FM symptoms and therefore could be used for therapeutic purposes by themselves, or in combination with current pharmacological treatments, as part of integrative medicine programs. However, a paucity of studies rigorously and systematically evaluating this possibility exists. This study uses scores from validated standardized questionnaires, algometer pressure point threshold (PPT) readings and responses from a custom self-developed questionnaire to determine the impact of a pressure-controlled manual protocol on FM hyperalgesia/allodynia, fatigue and patient´s quality of life. The results show that patient´s baseline sensitivity to pain inversely correlates with treatment response in FM. Moreover, patients presenting comorbid ME/CFS do not seem to respond to the applied therapy as those presenting FM only. Thus, pre-treatment PPTs and ME/CFS comorbidity may serve as indicators to predict patient´s response to physiotherapy programs based on mechanical triggers, as the one evaluated here. These unexpected findings grant further explorations including the study of gene expression profiles associating to patient´s treatment response in the blood collection of samples generated by this study.

Single-molecule fluorescence detection (SMFD) experiments are useful in distinguishing sub-populations of molecular species when measuring heterogeneous samples. One experimental platform for SMFD is based on a confocal microscope, where molecules randomly traverse an effective detection volume. The non-uniformity of the excitation profile and the random nature of Brownian motion, produce fluctuating fluorescence signals. For these signals to be distinguished from the background, burst analysis is frequently used. Yet, the relation between the results of burst analyses and the underlying information of the diffusing molecules is still obscure and requires systematic assessment. In this work we performed three-dimensional Brownian motion simulations of SMFD, and tested the positions at which molecules emitted photons that passed the burst analysis criteria for different values of burst analysis parameters. The results of this work verify which of the burst analysis parameters and experimental conditions influence both the position of molecules in space when fluorescence is detected and taken into account, and whether these bursts of photons arise purely from single molecules, or not entirely. Finally, we show, as an example, the effect of bursts that are not purely from a single molecule on the accuracy in single-molecule Förster resonance energy transfer measurements.

We analyze the modular geometry of the variable exponent Lebesgue space L^p(.). We show that L^p(.) possesses a modular uniform convexity property. Part of the novelty is that the property holds even in the case supp(x) = ∞ . We present specific applications to fixed point theory. xÆΩ

Based on the Expected Utility Theory and Regret Theory, the Extended Regret Theory (ERT) is proposed in this paper to study the optimal pricing strategy of retailers in e-commerce environment. Taking the diversity of sales channels and the uncertainty of consumers in e-commerce environment into consideration, author of the paper designs an extended regret utility function which comprehensively considers both pessimistic and optimistic attitudes of decision makers in retailing industry to describe their regret-avoidance behavior. According to the sensitivity analysis, it is found that the optimal retail price decreases as the consumer price sensitivity coefficient increases, yet does not show variation with changes of the consumers pessimism degree. Moreover, the optimal retail price(s) obtained under EUT, ERT and combination of EUT and ERT represent the same.

In this paper, we prove some random fixed point theorems for generalized random $\alpha-\psi-$contractive mappings in a Polish space and, as some applications, we show the existence of random solutions of second order random differential equation.

The Colebrook equation ζ is implicitly given in respect to the unknown flow friction factor λ ; λ=ζ(Re,ε*,λ) which cannot be expressed explicitly in exact way without simplifications and use of approximate calculus. Common approach to solve it is through the Newton-Raphson iterative procedure or through the fixed-point iterative procedure. Both requires in some case even eight iterations. On the other hand numerous more powerful iterative methods such as three-or two-point methods, etc. are available. The purpose is to choose optimal iterative method in order to solve the implicit Colebrook equation for flow friction accurately using the least possible number of iterations. The methods are thoroughly tested and those which require the least possible number of iterations to reach the accurate solution are identified. The most powerful three-point methods require in worst case only two iterations to reach final solution. The recommended representatives are Sharma-Guha-Gupta, Sharma-Sharma, Sharma-Arora, Džunić-Petković-Petković; Bi-Ren-Wu, Chun-Neta based on Kung-Traub, Neta, and Jain method based on Steffensen scheme. The recommended iterative methods can reach the final accurate solution with the least possible number of iterations. The approach is hybrid between iterative procedure and one-step explicit approximations and can be used in engineering design for initial rough, but also for final fine calculations.

Surface area and pore size distribution of Eucalyptus samples pretreated by different methods were determined by the Brunauer-Emmett-Teller (BET) technique. Three methods were applied to prepare cellulosic biomass samples for BET measurements: air, freeze, and critical point drying (CPD). Air and freeze drying caused severe collapse of biomass pore structures, but CPD effectively preserved biomass morphology. Surface area of CPD prepared Eucalyptus samples was determined to be 58–161 m2/g, whereas air and freeze dried samples were 0.5–1.3 and 1.0–2.4 m2/g, respectively. Average pore diameter of CPD prepared Eucalyptus samples were 61–70Å. CPD preserved Eucalyptus sample morphology by replacing water with a non-polar solvent, CO2 fluid, which prevented hydrogen bond reformation in the cellulose.

The research is devoted to the acute problem of cinema influence on the young audience. With the continuous development of mass media, cinema is still one of the most popular leisure activities, remaining an influential tool on the picture of the world, values, stereotypes, the behavior of viewers, etc. The paper studies the effects of the cinema on young viewers in relation to their ideas about the elderly. Using a psychosemantic technique that includes 25 scales designed specifically to identify the content of representation of older people, respondents evaluated their various characteristics before and after watching the film. It should be noted that after watching a film about the elderly, the respondents changed their representations of motivational and regulatory, cognitive and emotional characteristics of the older people. However, the changes were not similar in different groups of young people: students seemed to have more negative representation, graduate students’ assessment, on the contrary, changed for a better one. The discovered opposite effects of the cinema influence can be explained by a number of reasons starting from age, personal experience of the respondents, the formation of ideas to the special features of the film itself. In this regard, the contribution of individual factors to the efficiency of the cinema impact and the prediction of its specific effects requires further study.

The study of the emission, propagation, and reflection of balls in Newtonian mechanics, applying the laws of conservation of momentum and energy when the mass of the balls converges to zero, concludes that the kinematics of light are like those of massless balls. The kinematics of light explain why the speed of light is the constant c in each inertial frame in which the light source and reflective mirror are at rest, why the laws of physics have the same form in each inertial frame, and why any light experiment in an inertial frame cannot prove the motion of that inertial frame. The following law of mechanics governs the kinematics of balls and electromagnetic radiation: Each inertial frame drags at its velocity the balls and electromagnetic radiation emitted by bodies at rest in that inertial frame. The theory of special relativity misapplies the symmetry observed in phenomena to two inertial frames; therefore, it duplicates a physical phenomenon from one inertial frame, which is considered stationary, into another. There are multiple issues rooted in Lorentz's and Einstein's transformations. For example, transformations offer the speed of light at the constant c in the moving and opposite directions of the inertial frame. At the same time, it is variable in any other direction, converging to infinity. Time contraction in the moving direction of the inertial frame is different from time dilation in the opposite direction. It requires a ruler and time synchronization in each direction. There are no length contractions in Lorentz's and Einstein's transformations to support the fundamental concept of length contraction in special relativity. With these unacceptable conclusions, the theory of special relativity is self-negating.

The origin of life was a cosmic event happened on primitive Earth. A critical problem to better understand the origins of life in Earth is to glimpse in which chemical scenarios the basic building blocks of biological molecules could be produced. Classic works in pre-biotic chemistry frequently considered early Earth as a homogeneous atmosphere constituted by chemical elements such as methane (CH₄), ammonia (NH₃), water (H₂O), hydrogen (H₂) and hydrogen sulfide (H₂S). Under that scenario, Stanley Miller was capable to produce amino acids and solved the question about the origin of proteins. Conversely, the origin of nucleic acids has tricked scientists for decades as nucleotides are complex though necessary molecules to allow the existence of life. Here we review possible chemical scenarios that allowed not only the formation of nucleotides but also other significant biomolecules. We aim to provide a theoretical solution for the origin of biomolecules at specific sites named “Prebiotic Chemical Refugia”. A prebiotic chemical refugium should therefore be understood as a geographic site in prebiotic Earth on which certain chemical elements were accumulated in higher proportion than expected, facilitating the production of basic biomolecules. Plus, this higher proportion should not be understood as static, but dynamic; once the physicochemical conditions of our planet changed periodically. This different concentration of elements, together with geochemical and astronomical changes along days, synodic months and years provided somewhat periodic changes in temperature, pressure, electromagnetic fields, and conditions of humidity; among other features. Recent and classic works suggesting most likely prebiotic refugia on which the main building blocks of biological molecules might be accumulated are reviewed and discussed.

Liposomal amphotericin B (L-AmB) has become the cornerstone for the treatment of severe invasive fungal infections. However, renal toxicity may be an associated risk. Our aim was to evaluate the incidence of acute kidney injury (AKI) in critically ill patients receiving L-AmB for more than 48 hours. Clinical, demographic and laboratory variables were obtained retrospectively from electronic health record. Follow-up of the patients was for 7 days after L-AmB infusion. Patients were analyzed globally and differentiated between patients with "low" and "high" risk of developing AKI with machine learning techniques. Sixty-seven patients were included: 61 years, 67% male, with mean SOFA score of 4 (3-6.5) and a crude intensive care unit mortality of 34.3%. No significant variations in serum creatinine were observed during the observation period, except for the decrease in the high-risk subgroup. Overall, 26.8% of patients developed AKI-I, while 25% and 13% of patients at low and high risk of AKI developed AKI-I, respectively. The random forest models performed in overall and low-risk subgroup identified several major contributor’s factors to the development of AKI other than L-AmB administration. The development of AKI is multifactorial and the administration of L-AmB appears to be safe in this group of patients.

Introduction: Despite its high prevalence and impact on health, metabolic dysfunction-associated steatotic liver disease (MASLD) is inadequately addressed in European primary care (PC), with a large proportion of cases going undiagnosed or diagnosed too late. A multi-country European re-search consortium led a project to design and evaluate a patient-centered, integrated model for MASLD screening, diagnosis and linkage to specialty care for European PC settings. Aim: Based on the lessons from this project, the latest research evidence and existing guidelines for the management of MASLD, we sought to develop a set of practice recommendations for screening, referral and management of MASLD in PC. Methods: The Rand/UCLA modified Delphi panel method, with two rounds, was used to reach consensus on practice recommendations. The international panel consisted of experts from six countries, representing family medicine, gastroenterology, hepatology, cardiology and public health. Initially, fifteen statements were drafted based on a synthesis of evidence from the literature and earlier findings from our consortium. Prior to the consensus meeting, the statements were rated by the experts in a first round. Then, in a hybrid meeting, the experts discussed findings of round one, adjusted the statements and reassessed the updated recommendations in a second round. Results: In round one, there was already a high level of consensus on 10 out of 15 statements. After round 2, there were fourteen statements with a high agreement (>90%). One statement was not endorsed. The approved recommendations addressed the following practice areas: risk screening and diagnosis, management of MASLD – Lifestyle interventions, pharmacological treatment of MASLD/MASH, pharmacological treatment for co-morbidity, integrated care, surgical management and other referrals to specialists. Conclusion: The final set of 14 recommendations focuses on increasing comprehensive care for MASLD in PC. The recommendations provide practical evidence-based guidance tailored to PC practitioners. We expect that these recommendations will contribute to the ongoing discussion on systematic approaches to tackle MASLD and support European PC providers by integrating the latest evidence into practice.

In Taiwan, remote healthcare was initially limited to telemedicine services, and the systematic development of remote care was relatively delayed. It was not until 2007 that the Department of Health of the Executive Yuan first initiated the 'Remote Care Pilot Program,' followed by the 'Remote Care Service Improvement and Quality Enhancement Plan' in the subsequent year. In 2010, Taiwan officially launched the 'Remote Health Care Services Development Plan' and established a dedicated project office, marking the comprehensive start-up of remote care services. This stage saw significant contributions from artificial intelligence aids and ICT remote transmission technologies, greatly promoting the application of smart healthcare in home care. This study aims to explore the strategic gaps in the application of smart healthcare in home remote care. By analyzing gaps in 'legal regulations,' 'economic factors,' 'user behavior habits,' 'policy and culture,' and 'environment and technology,' this study employs a mixed-methods approach. Particularly, it uses the Analytic Hierarchy Process (AHP) to construct a weighted ranking of these strategic gaps. Through in-depth interviews with doctors and smart healthcare experts and the collection of 16 valid AHP questionnaire samples, which cover both industry and academia with a balanced distribution, the survey results are ensured to be representative and reliable. The findings indicate that 'legal regulations' are considered the most critical strategic gap that needs to be addressed first, followed by 'user behavior habits.' This suggests that when designing smart healthcare applications, greater consideration needs to be given to user acceptance and habits. By systematically analyzing and addressing these strategic gaps, this study not only provides solutions to issues in the application of smart healthcare in home remote care but also offers valuable references for future research and practice, aiming to make home remote care services more comprehensive and efficient.

Background/Objectives: The aim of this study was to investigate feasibility and safety of neuromuscular electrical stimulation (NMES) in patients on extracorporeal membrane oxygenation (ECMO) and assess thoroughly any potential adverse events. Methods: We conducted a safety and feasibility study including 16 ICU patients on ECMO support who were admitted to the cardiac surgery ICU from January 2022 to December 2023. Patients underwent a 45-minute NMES session, still on ECMO support, that included a warm up phase of 5 minutes, a main phase of 35 minutes and a recovery phase of 5 minutes. NMES was implemented on vastus lateralis, vastus medialis, gastrocnemius and peroneus longus muscle of both lower extremities. Two stimulators delivered biphasic, symmetric impulses of 75 Hz, with 400 μsec pulse duration, 5 sec on (1,6 sec ramp up and 0,8 sec ramp down) and 21 sec off. The intensity levels aimed to cause visible contractions and be well tolerated. Primary outcomes of the study were feasibility and safety, evaluated by whether the NMES sessions were successfully achieved, and by any adverse events and complications. Secondary outcomes included indices of rhabdomyolysis from biochemical blood test, 24 hours after the application of NMES. Results: All patients successfully completed their 45-minute NMES session, without presenting hemodynamic deterioration, adverse events or signs of rhabdomyolysis. The majority of patients achieved type 4 and 5 quality of muscle contraction. Conclusions: NMES is a safe and feasible exercise methodology in patients supported with ECMO.

.Bacground: Sepsis remains a major health challenge worldwide, characterized by a dysre-gulated host response to infection, leading to high mortality and morbidity in intensive care units (ICUs). The Fibrosis 4 (FIB-4) index, originally developed to assess liver fibrosis in hepatitis C patients, has recently been explored for its potential prognostic value in sepsis patients. Method: This study retrospectively analyzed 309 sepsis patients admitted to the Internal Me-dicine and Anaesthesia ICUs between December 12, 2021, and December 15, 2023, to inves-tigate the relationship between FIB-4 levels, Acute Physiology and Chronic Health Evaluation (APACHE), and Sequential Organ Failure Assessment (SOFA) and clinical outcomes. Results: The study found that higher FIB-4 measurements were statistically significantly asso-ciated with increased 28-day mortality, with a cut-off value of 4.9 providing a sensitivity of 54.92% and specificity of 74.25%. Logistic regression analysis indicated that elevated Conclusion:FIB-4 levels were a significant predictor of early mortality, suggesting that the FIB-4 index could serve as a valuable prognostic tool in assessing the severity and prognosis of sepsis patients.

Diabetic foot ulcers (DFUs) significantly affect the lives of patients and increase the risk of hospital stay and amputation. We suggest a remote-monitoring platform for better DFU care. This system uses digital health metrics (scaled from 0 to 10, where higher scores indicate a greater risk of slow healing) to provide a comprehensive overview through a visual interface. The platform features smart offloading devices that capture behavioral metrics such as offloading adherence, daily steps, and cadence. Coupled with remotely measurable frailty and phenotypic metrics, it offers an in-depth patient profile. Additional demographic data, wound characteristics, and clinical parameters, such as cognitive function, were integrated, contributing to a comprehensive risk factor profile. We evaluated the feasibility of this platform with 124 DFU patients over 12 weeks; 39% experienced unfavorable outcomes such as dropout, adverse events, or non-healing. Digital biomarkers were benchmarked (0-10), categorized into low, medium, and high risk for unfavorable outcomes, and visually represented using color-coded radar plots. The initial results of case reports illustrate the value of this holistic visualization to pinpoint the underlying risk factors for unfavorable outcomes, including a high number of steps, poor adherence, and cognitive impairment. Although future studies are needed to validate the effectiveness of this visualization in personalizing care and improving wound outcomes, early results in identifying risk factors for unfavorable outcomes are promising.

This study explores the multifaceted influence of litter size, maternal care, exercise, and aging on rats' neurobehavioral plasticity and dentate gyrus microglia dynamics. Body weight evolution revealed a progressive increase until maturity, followed by a decline during aging, with larger litters exhibiting lower weights initially. Notably, exercised rats from smaller litters displayed higher body weights during mature and aged stages. Dentate gyrus volumes showed no significant differences among groups, except for aged sedentary rats from smaller litters, which exhibited a reduction. Maternal care varied significantly based on litter size, with large litter dams showing lower frequencies of caregiving behaviors. Behavioral assays highlighted the detrimental impact of a sedentary lifestyle and reduced maternal care/large litters on spatial memory, mitigated by exercise in aged rats from smaller litters. Microglial dynamics in the layers of dentate gyrus revealed age-related changes modulated by litter size and exercise. Exercise interventions mitigated microgliosis associated with aging, particularly in aged rats. These findings underscore the complex interplay between early-life experiences, exercise, microglial dynamics, and neurobehavioral outcomes during aging.

This study aims to explore the associations between pediatric adverse events (PAEs) and hospital and patient characteristics within the inpatient hospital setting, focusing solely on the framework of pediatric quality indicators (PDIs) from the Agency for Healthcare Research and Quality (AHRQ). Specifically, the study focuses on NQI 03 Neonatal Blood Stream Infection (NBSI). The analysis utilizes discharge data from the Healthcare Cost and Utilization Project (HCUP) Kids’ Inpatient Databases (KID) for the year 2019. Through this analysis, the study seeks to answer research questions regarding associations between hospital characteristics and patient characteristics with NQI 03. The methodology employs bivariate and multivariate logistic regression models to analyze patient-level encounters of NBSI. The results indicate that smaller, rural, and non-teaching hospitals exhibit significantly lower odds of NQI 03 compared to large hospitals. Various individual factors such as gender, age, race, service lines, payment sources, and major operating room procedures also demonstrate differing levels of significance in relation to NQI 03, warranting further investigation. This study provides contextual expansion on the findings and offers valuable insights into PAEs in the inpatient hospital setting, specifically focusing on NBSI within the PDIs framework. It highlights areas for developing evidence-based interventions and guidelines for clinicians and policymakers. Ultimately, the findings contribute to the growing understanding of factors influencing NBSI and emphasize the importance of targeted strategies for improving pediatric patient safety.

Efficient triaging and referral assessment are critical in ensuring prompt medical intervention in the Community Health Care (CHC) system. However, the existing triaging systems in many Community Health Services are an intensive, time-consuming process and often lack accuracy, particularly for various symptoms that might represent heart failure or other health-threatening conditions. There is a noticeable limit of research papers describing AI technologies for triaging patients. This paper proposes a novel quantitative data-driven approach using machine learning (ML) modelling to improve the community clinical triaging process. Furthermore, this study aims to employ the feature selection process and machine learning power to reduce the triaging process’s waiting time and increase accuracy in clinical decision-making. The model was trained on medical records of “Heart Failure” patients’ dataset, which included demographics, past medical history, vital signs, medications, and clinical symptoms. A comparative study was conducted using the list of machine learning algorithms where XGBoost demonstrated the best performance among other ML models. The triage levels of 2,35,982 patients achieved an accuracy of 99.94%, precision of 0.9986, recall of 0.9958, and f1-score of 0.9972 within 0.059 seconds. The proposed diagnostic model can be implemented for the CHC decision system and be developed further for other medical conditions.

In this study, we propose an augmentation method for machine learning based on relabeling data in caregiving and nursing staff indoor localization with Bluetooth Low Energy (BLE) technology. Indoor localization is used to monitor staff to patient assistance in caregiving and to gain insights into workload management. However, improving accuracy is challenging when there is a limited amount of sensor data available for training. In this paper, we propose a data augmentation method to reuse the Received Signal Strength (RSS) from different sensors by relabeling to the sensors with less samples resolving data imbalance. Standard deviation and Kullback-Leibler divergence between minority and majority class are used to measure signal pattern to find matching sensors to relabel. By matching sensors between classes, two variation of relabeling are implemented specifically full and partial matching. The performance is evaluated using real world dataset we collected for five days in a nursing care facility installed with 25 BLE beacons. Random Forest model is utilized for location recognition, and performance is compared using the weighted F1-score to account for class imbalance. By increasing the sensor data with our proposed relabeling method for data augmentation, we achieved higher minority class F1-score as compared to augmentation with Random Sampling, Synthetic Minority Oversampling Technique (SMOTE) and Adaptive Synthetic Sampling (ADASYN). Our proposed method utilizes collected sensor data by leveraging majority class samples. Full matching demonstrated a 6 to 8% improvement from the original baseline overall weighted F1-score.

Background Acute kidney injury (AKI) is a common comorbidity in the intensive care unit (ICU), with higher mortality rate among those who receive continuous renal replacement therapy (CRRT). This study aimed to investigate the association of white blood cell (WBC) levels with all-cause mortality in AKI patients undergoing CRRT. Method We conducted a post hoc analysis of ICU patient data from multiple centers in Korea. First, the levels of WBCs were classified into four groups based on quartiles. Second, the relationship between different WBC levels and mortality was investigated with the Kaplan-Meier (K-M) survival curves, Cox proportional hazards model, and generalized additivity model (GAM). Finally, we used multiple imputation to avoid bias caused by non-randomized missing data. The endpoints were short-term (28 days) and long-term (90 days) mortality. Result In our analysis, a total of 1,100 ICU patients were included. Among them, 670 (60.90%) and 781 (71.00%) died within 28 and 90 days, respectively. K-M survival curves showed that patients with the lowest WBC levels had the highest risk of mortality for both outcomes. Adjusted multivariate Cox regression analysis confirmed that compared with the reference level (quartile 2), low WBC levels increased the risk of both 28-day mortality (quartile 1, HR = 1.43, 95% CI: 1.13–1.83, P = 0.004) and 90-day mortality (quartile 1: HR = 1.32; 95% CI: 1.05-1.66, P = 0.016). GAM analysis showed a non-linear, U-shaped relationship between pre-CRRT WBC levels and all-cause mortality (non-linear P < 0.05). Conclusion The baseline WBC level is an independent predictor of prognosis for ICU patients receiving CRRT. Patients in the lowest WBC quartile had the highest risk of all-cause mortality. These results provide further evidence that early observation and intervention may have a prognostic value for these high-risk patients.

Background: This study delves into the examination of racial and ethnic disparities in the distribution of the Monkeypox (MPOX) virus vaccine within the United States, offering a critical healthcare perspective on an emerging public health concern. It particularly focuses on the demographic patterns associated with MPOX transmission and the allocation of vaccines. Methods: A comprehensive analysis was conducted, drawing on a wide array of data sources to understand the vaccine distribution and demographic trends in the United States. The study scrutinized three main aspects: MPOX cases by race and ethnicity, vaccine administration across different racial and gender categories, and the potential disparities therein. Results: The findings reveal significant disparities in the distribution of vaccine doses, with males, particularly gay, bisexual, and other Men who have sex with men (MSM), receiving the majority of doses. Moreover, substantial variations in MPOX cases are observed among different racial and ethnic groups, emphasizing the need for culturally sensitive public health strategies. Conclusions: The study underscores the urgent need for targeted public health interventions to address disparities and safeguard the well-being of those at higher risk, particularly MSM. It highlights the importance of equity in vaccine distribution and culturally sensitive approaches, and serves as a foundation for shaping effective public health policies and strategies to mitigate the spread of MPOX. This research advances our understanding of healthcare disparities in the context of an emerging viral infection, providing valuable insights for future public health initiatives.

Machine learning (ML) techniques can help predict survival among cancer patients and might help with a timely integration in palliative care. We aim to explore the importance of subjective variables self-reported and collected via electronic patient reported outcome measure (ePROM) for survival prediction. A total of 256 advanced cancer patients met the eligible criteria. We analyzed objective variables collected from electronic health records, subjective variables collected via ePROM and all clinical variables combined. We used logistic regression (LR), decision trees, and random forests to predict 1-year mortality. Receiver operating characteristic (ROC) curve - area under the curve (AUC) and the ML models feature importance were analyzed. The performance of all variables for predictions (LR reaches 0.80 [ROC AUC] and 0.72 [F1 Score]) does not improve over the performance of only clinical non-patient reported outcome (non-PRO) variables (LR reaches 0.81 [ROC AUC] and 0.72 [F1 Score]). Our study indicates that patient-reported outcome (PRO) variables, which measure subjective burden, cannot be reliably used to predict survival. Further research in this area is needed to clarify the role of self-reported patient's burden and mortality prediction via ML.

The Coronavirus Disease 2019 (COVID-19) pandemic has had a major impact on the mental and physical health of hospitalized patients. In our study we focused on the onset of symptoms correlated with Post-traumatic stress disorder (PTSD), depression and physical disabilities in patients admitted to the Intensive Care Unit (ICU) because of a severe respiratory distress related to COVID-19 (COVID Group) compared with patients admitted to the same ICU for trauma and other medical conditions than COVID-19 (No-COVID Group). The physical symptoms and the level of disability were evaluated with the Glasgow Outcome Scale-Extended (GOS-E), the Quality of Life after Brain Injury (QOLIBRI) and the 3 levels version of EQ-5D (EQ-5D-3L) questionnaire; psychiatric symptoms were investigated using the Impact of Event Scale-Revised 22-item (IES-R), the Patient Health Questionnaire, 9-Item Version (PHQ-9) and the Generalized Anxiety Disorder Assessment, 7-items version (GAD-7). These questionnaires were administered 6 months after discharge. Patients in the No-COVID Group showed statistically significant more severe scores in all the physical assessments while similar relevant PTSD and depressive symptoms were reported in both groups. The results of the present study underline the psychopathological impact of being hospitalized in ICU because of COVID-19 even after 6 months from discharge ,suggesting the importance of assessing the psychiatric effects of COVID-19 in the long term in order to create supportive measures.

Background: Skin and soft tissue infections (SSTI) are common presentations to the emergency department. However, this is less common after contact with contaminated water, both salt or fresh. This review presents the diagnosis and the management of water-related soft tissue sepsis in this vulnerable and difficult to treat subgroup of necrotizing soft tissue sepsis. Methods: A summative literature overview regarding bacterial and fungal SSTI after contact with contaminated water, with practical diagnostic and management aspects addressed. Results: The literature indicates that these remain difficult to treat wounds and organisms. An approach using appropriate diagnostic tools with both medical and surgical management strategies is provided. Conclusion: SSTI due to water contamination of wounds involve unusual organisms with unusual resistance patterns and require a nuanced and directed diagnostic approach with adaptation of the normal antibiotic or antifungal selection to achieve cure, along with aggressive debridement and wound care.

The objective of this study was to compare the pathogens and susceptibilities of the current automated rule-based technology (RBT) antibiogram with one manually collected through chart review with additional rules applied. This study was a 2-year, retrospective cohort study and included all bacterial cultures within the first 30 days from patients admitted to a single Burn Center. The current RBT antibiogram served as the control and new antibiogram versions were created using additional rules and compared to the control. Six-hundred fifty-seven patients were admitted (61% excluded for lack of cultures). Fifty-nine percent had at least one hospital acquired risk factor with over one-third having recent illicit drug use and one-third having a recent hospitalization. Of the 410 cultures included, 57% were Gram-negative and half were from wound infections. Sensitivities were significantly different when comparing manual and the RBT version after including factors, such as days since admission, presence of hospital acquired risk factors, or previous antibiotic courses. Recommended empiric Gram-negative antibiotics changed from double coverage to a single β-lactam with > 90% susceptibility. The susceptibilities between first and subsequent courses were dramatically different. Before developing an antibiogram or interpreting the output, it is important to consider which automated criteria are utilized, especially for units with extended lengths of stay.

: Background: Vaccine-related death is one of the leading causes of death among African Children. Vaccine coverage is a very important measure to decrease infant mortality. Covid-19 Pandemic has affected the healthcare system and may have disrupted vaccine coverage. Methods: DTP third doses (DTP3) Vaccine Coverage was extracted from UNICEF databases from 2012 to 2021( the last available date). Joinpoint regression was performed to detect the point where the trend changed. The annual percentage change (APC) with 95% confidence intervals (95% CI) was calculated for Africa and the regions. We compared DTP3 vaccination coverage in 2019 with 2021 in each country to verify compliance with WHO targets. Result: During the whole period, the vaccine coverage in Africa has increased with an Annual Percent change of 1.2% (IC 95% 0.9-1.5): We detected one Joint point in 2019. In 2019-2021, there was a decrease in DTP3 coverage with an APC of -3.5(95% -6.0;-0,9). (P< 0.001). Vaccination rates have decreased in many regions and countries during the last two years. Conclusions. COVID-19 has disrupted vaccine coverage, decreasing it all over Africa.

The COVID-19 pandemic has profoundly changed the world and human society in various ways. Infection-related figures are key indicators of the direct impact of the pandemic. In addition to the virus, many vulnerable populations (e.g. patients with complex health conditions) have suffered direct or indirect health impacts, such as delayed treatment or diagnosis of cancer and severe mental illness due to stay-at-home restrictions, or financial issues. Studying these kinds of impacts can provide the community with insights and understanding of how the pandemic has affected patients with health conditions and help inform decision-makers design policies that support various vulnerable populations. This paper surveys analytical work conducted on how COVID-19 has impacted patients with complex health conditions. We categorise vulnerable populations into three specific cohorts: patients with chronic disease, patients with cancer and patients with end-of-life care. We then investigate how each of these cohorts has been impacted by the pandemic. We also identify each cohort from an analytics perspective by leveraging various data collection strategies and analytical methods. The goals of this paper are to provide evidence on how to improve the quality of life for vulnerable populations and to inform a national response strategy for future pandemics, which seems inevitable in a highly globalised economy.

The past several decades have seen a shift in patient care towards digitalisation, which has ushered in a new era of health care delivery and improved sustainability and resilience of health systems, with positive impacts on both internal and external stakeholders. This study’s aim was to understand the role of digital virtual consultations in improving internal and external stakeholders’ health, as well as wellbeing among hospital doctors. A qualitative research approach was used with semi-structured online interviews administered to hospital doctors. The interviews showed that the doctors viewed digital virtual consultations as supplementary to in-person consultations, and as tools to reduce obstacles related to distance and time. If the necessary infrastructure and technology were in place, doctors would be willing to use these options. Implementing these technologies would improve the medical profession’s flexibility on the one hand; but it might affect doctors’ work–life balance if consultations extended beyond standard working hours.

The WHO European Region defined the role of a new central professional for primary care, the Family and Community Nurse (FCN). The introduction of FCN in the framework of health policies highlight a key role of nurses in addressing the families’ and communities’ needs. A scoping review was conducted in order to identify and describe the available tools which has been adopted for the assessment of the community health needs by FNC. A comprehensive literature review on Embase, Cochrane Library, PubMed, CINAHL, Scopus and PsycInfo databases was conducted including all studies up to May 2021. A total of 1563 studies were identified and 36 of them were included. The literature review had made possible to identify studies employing twelve different community assessment's tools or modalities. Referring the WHO framework proposed in 2001 some common themes have been identified with an uneven distribution, as profiling the population, deciding on priorities for action and public healthcare programmes, implementing the planned activities, evaluation of health outcomes, multidisciplinary activity, flexibility and involving the community. To the best of our knowledge, this work is the first attempt to provide an overview of community assessment tools, keeping the guidance provided by the WHO as a reference.

Systemic hypertension has been recognized as a modifiable traditional cardiovascular risk factor and influenced by many factors such as eating habits, physical activity, diabetes and obesity. The objective of this study was to identify cardiometabolic factors that predict changes in blood pressure induced by a one-year lifestyle intervention in primary care settings involving a collaboration between family physicians, dietitians, and exercise specialists. Patients with metabolic syndrome diagnosis were recruited by family physicians participating in primary care lifestyle intervention among several family care clinics across Canada. Participants for whom all cardiometabolic data at the beginning (T0) and the end (T12) of the intervention were available were included in the present analysis (n=101). Patients visited the dietitian and the exercise specialist weekly for the first three months and monthly for the last nine months. Diet quality, exercise capacity, anthropometric indicators, and cardiometabolic variables were evaluated at T0 and at T12. The intervention induced a significant decrease in waist circumference (WC), systolic (SBP) and diastolic (DBP) blood pressure, and plasma triglycerides and an increase in cardiorespiratory fitness (estimated VO2max). Body weight (p<0.001), body mass index (BMI) (p<0.001), and plasma glucose (p=0.006) reduction and VO2max increase (p=0.048) were all related to changes in SBP. WC was the only variable for which changes were significantly correlated with those in both SBP (p<0.0001) and DBP (p=0.0004). Variations in DBP were not associated with changes in other cardiometabolic variables to a statistically significant extent. Twelve participants were identified as adverse responders in both SBP and DBP and displayed less favorable changes in WC. The beneficial effects of a lifestyle intervention on blood pressure were significantly associated with cardiometabolic variables, especially WC. These findings suggest that a structured lifestyle intervention in primary care can help improve cardiometabolic risk factors in patients with metabolic syndrome.

Background: Although, negative repercussions of inadequate health service use on the health outcomes has been presumably exacerbated by COVID-19, the impact of the pandemic measures has been not evaluated properly yet. Objective: Our study aimed to quantify the COVID-19 pandemic measures’ effect on the general practitioner (GP) visit, specialist care, hospitalization and cost-related prescription nonredemption (CRPNR) among adults in Hungary, and to identify the social strata susceptible to the pandemic effect. Methods: This community-based cross-sectional study based on nationally representative data of 6,611 (Nprepandemic=5,603 and Npandemic=1,008) subjects aged 18 years and above. Data were obtained from the European Health Interview Survey 2019 (EHIS) and International Social Survey Program 2021 (ISSP) for prepandemic and pandemic, respectively. Multivariable logistic regression models were applied to determine the sociodemographic and clinical factors influencing the health care use by odds ratios (OR) along with the corresponding 95% confidence intervals (CI). To identify the social strata susceptible to pandemic effect, the interaction of the time of data collection with level of education, marital status, and ethnicity, was also tested. Results: While, the CRPNR did not changed, the frequency of GP visit, specialist care and hospitalization rate were remarkably reduced by 22.2%, 26.4%, and 6.7%, respectively, during the pandemic in Hungary. Roma proved to be not specifically affected by the pandemic in any studied respect. The pandemic restructuring of health care impacted the social subgroups evenly with respect to hospital care. However, the pandemic effect was weaker among primary educated adults (ORhigh-school vs primary-education =0.434; 95% CI 0.243-0.776, ORhigh-school vs primary-education =0.598; 95% CI 0.364-0.985), and among widows (ORwidowed vs married =2.284; 95% CI 1.043-4.998, ORwidowed vs married=1.915; 95% CI 1.157-3.168) on the frequency of GP visit and specialist visit; and the prepandemic CRPNR inequality by level of education was increased (ORhigh-school vs primary-education =0.236; 95% CI 0.075-0.743). Conclusion: Primary educated and widowed did not follow the general trend, and their prepandemic limited health care use was not reduced further during pandemic, resulting in an inequality reduction. The vulnerability of primary educated to CRPNR was the only gap widened in the pandemic period. This shows that although the management of pandemic health care use restrictions was implemented by increasing the social inequality in Hungary, the prevention of inequity in drug availability for primary educated individuals could require more support.

The study reports about a case of a lung cancer patient with increasing difficulties in falling asleep and frequent periods of wakefulness. Severe dyspnea related to pneumonitis caused as a side effect of immunotherapy worsened the situation. Eventually, fear of falling asleep developed, including panic attacks and anxiety of choking, which was shown to lead to nights of complete wakefulness. The patient did not only sleep poorly; he did not sleep at all at night for several days, as evidenced by the notes he made during the night. Polygraphy showed no evidence of sleep-disordered breathing, but frequent periods of wakefulness and reduced basal saturation around 90% during sleep due to lung changes such as extensive functional failure of the left upper lobe with position-dependent shunts. The authors hypothesized that the symptoms described were causally related to a drop in oxygen saturation in the patient's blood. Therefore, they pursued the goal of finding a measurement technique that is as inexpensive as possible and that the patient can operate without outside assistance and great effort. So the patient started using a low-cost wearable device that allows simultaneous measurements of blood oxygen content, pulse rate and movement intensity. It consists of a finger ring with pulse oximetry sensor and a wristband with the control unit containing a vibration motor. The described device reliably warned of disturbances in oxygen concentration in the blood during the night with its vibration alarm. By use of that device during the whole night at home, the events of reduced oxygen saturation and the anxiety symptoms were reduced. Sleep disturbances with sudden awakenings did not occur when using the device. The patient benefited from the security gained in this way and slept much more peacefully, and he could spend nights without waking up again. In conclusion, wearable oximeters with vibration alarm can be recommended for patients’ home care in lung cancer patients.

Titin is a giant protein that functions as a molecular spring in sarcomeres. Titin interplays the contraction of actin-containing thin filaments and myosin-containing thick filaments. The breakdown product of titin has been measurable in urine as urinary titin N-fragments. Urinary titin N-fragment was originally reported to be a useful biomarker in the diagnosis of muscle dystrophy. Recently, the urinary titin N-fragment has been increasingly gaining attention as a novel biomarker of muscle atrophy and intensive care unit-acquired weakness in critically ill patients, in whom titin loss is a possible pathophysiology. Furthermore, several studies reported that the urinary titin N-fragment also reflected muscle atrophy and weakness in patients with chronic illnesses. It may be used to predict the risk of post-intensive care syndrome or to monitor patients’ condition after hospital discharge for better nutritional and rehabilitation management. We provide several tips on the use of this promising biomarker in post-intensive care syndrome.

While nursing is an ethical profession, unethical behavior among nurses is increasing worldwide. This study examined the effects of an ethics seminar on nurses' moral sensitivity and ethical behavior. A total of 37 nurses (17 experimental, 20 control) were recruited. The ethics seminar was held over a 6-month period from May to October, 2018, and comprised six sessions held once a month for two hours. Moral sensitivity and unethical behavior were measured at the start and end of the seminar. Moral sensitivity and unethical behavior showed a negative correlation (r= -.455, p&lt;0.01). After the ethics seminar, the experimental group's moral sensitivity was significantly increased (t = -1.039, p = 0.314). The mean scores of unethical behavior at pre and post-test in the experimental group were 12.59 and 9.47, respectively. This was a statistically significant difference (t = 3.118, p = 0.004). There was no statistically significant difference in the mean score in both moral sensitivity and unethical behavior in the control group. We conclude that ethics seminars can enhance moral sensitivity and reduce the risk of unethical behavior among nurses. Regular ethics seminars and training must be provided to nurses as a matter of policy.

In recent years, the management of health systems is a main concern of governments and decision makers. Home health care is one of the newest methods of providing services to patients in developed societies that can respond to the individual lifestyle of modern age and the increase of life expectancy. The home health care routing and scheduling problem is a generalized version of the vehicle routing problem, which is extended to a complex problem by adding special features and constraints of health care problems. In this problem, there are multiple stakeholders such as nurses for which an increase of their satisfaction level is very important. In this study, a mathematical model is developed to expand traditional home health care routing and scheduling models to downgrading cost aspects by adding the objective of minimizing the difference between the actual and potential skills of the nurses. Downgrading can lead to a dissatisfaction of the nurses. In addition, skillful nurses have higher salaries and high-level services increase equipment costs and need more expensive trainings and nursing certificates. Therefore, downgrading can enforce hidden huge costs to the managers of a company. To solve the bi-objective model, an -constraint based approach is suggested and the model applicability and its ability to solve the problem in various sizes are discussed. A sensitivity analysis on the Epsilon parameter is conducted to analyze the effect of this parameter on the problem. Finally, some managerial insights are presented to help the managers in this field, and some directions for future studies are mentioned as well.

Background: Given the increasing request for natural pharmacological molecules, this study assessed the antimicrobial capacity of Pistacia lentiscus L. essential oil (PLL-EO) obtained from the leaves of wild plants growing in North Sardinia (Italy), toward a wide range of periodontal bacteria and Candida including laboratory and clinical isolates sp., together with its anti-inflammatory activity and safety; Methods: PLL-EO was screened by gas chromatography / mass spectrometry. The minimal inhibitory concentration (MIC) was determined. The anti-inflammatory activity was measured by cyclooxygenase (COX 1/2) and lipoxygenase (LOX) inhibition while the antioxidant capacity was determined electro-chemically and by the MTT assay. The WST-1 assay was used to ascertain cytotoxicity toward four line of oral cells; Results: According to the concentrations of terpens, PLL-EO is a pharmacologically active phytocomplex. MICs against periodontal bacteria ranged between 3.13 and 12.5 µg/ml, while against Candida sp. were between 6.25 and 12.5 µg/ml. Oxidation by COX 1/2 and LOX was inhibited by 80% and 20% µg/mL of the oil respectively. Antioxidant activity seemed negligible, and no cytotoxicity arose; Conclusions: PLL-EO exhibits a broad-spectrum activity against periodontal bacteria and Candida, with an interesting dual inhibitory capacity toward COX2 and LOX inflammatory enzymes and without side effects against oral cells.

There is much discussion among clinicians, epidemiologists, and public health experts about why case fatality rate from COVID-19 in Italy (at 13.3% as of April 20, 2020, versus a global case fatality rate of 6.9%) is considerably higher than estimates from other countries (especially China, South Korea, and Germany). In this article, we propose several potential explanations for these differences. We suggest that Italy’s overall and relative case fatality rate, as reported by public health authorities, is likely to be inflated by such factors as heterogeneous reporting of coronavirus-related fatalities across countries and the iceberg effect of under-testing, yielding a distorted view of the global severity of the COVID-19 pandemic. We also acknowledge that deaths from COVID-19 in Italy are still likely to be higher than in other equally affected nations due to its unique demographic and socio-economic profile. Lastly, we discuss the important role of the stress imparted by the epidemic on the Italian healthcare system, which weakened its capacity to adequately respond to the sudden influx of COVID-19 patients in the most affected areas of the country, especially in the Lombardy region.

Aim: this scoping review was designed to identify studies that assess the adverse drug reactions (ADRs) for older people in Australian aged-care facilities. This review critically evaluated each published study to identify the risk of, or actual adverse drug events in older people. Inclusion criteria: This review considered any clinical studies that examined the adverse effects of medications in older people who were living in aged-care facilities. This review considered qualitative studies, analytical studies, RCTs, descriptive cross-sectional studies, and analytic observational studies that explored the use of medications and their adverse effects on older people in clinical settings (including aged care facilities). Methods: An initial search of the PubMed, OvidSP, EBSCOHost, MEDLINE, ScienceDirect, Wiley Online, SAGE, and SCOPUS databases, with full text was performed, followed by an analysis of the article’s title and abstract. Additionally, MeSH was used to describe the article. The initial round of the database search was based on inclusion criteria from studies that assessed tools or protocols aiming to identify the adverse effects of medications on the elderly population suffering chronic conditions or multiple co-morbidities. Two reviewers screened the retrieved papers for inclusion. The data presented in this review are in tabular forms and a narrative summary which aligns with the review’s objectives. Results: Seven studies were identified, and the extracted data from these studies were grouped according their characteristics and the auditing results of each study. Conclusion: There was no comprehensive or broadly adverse drug reaction assessment tool derived from Australian data that has been used on the elderly in an Australian healthcare setting.

This paper evaluates the effect of China’s New Rural Pension Scheme (NRPS) on the retirement sustainability in forms of both formal labor supply and informal labor supply, using data from China Health and Retirement Longitudinal Study (CHARLS). We explore the regional differences of the NRPS effect on labor supply between the Western regions and the other regions of China. Our analysis shows that western rural China has a more severe problem of “ceaseless toil” compared to the rest of the country. We find that NRPS improves the “ceaseless toil” situation of the Chinese rural elderly, and the results show a very different pattern between western China and other parts of the country.

The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (K_d), can be considered as one of the most important characteristics for any antibody-antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC₅₀ approaches the K_d value in the case of infinitely small concentrations of the reagent concentrations. A two-dimensional dilution of the reagents leads to an asymptotic convergence to K_d. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.

The data from the extended system was recorded on-going basis in the archives of the monitoring system, and the multipoint system was directly stored in the methane-anemometers, which allows one to perform a comparative analysis of the obtained records from many methane detectors. An important element of the analyses was the simultaneous registration of the methane concentration in the longwall, together with information on operating time, direction of shearer operation and type of work: mining/cleaning. Mining practice shows that in methane coal mines, methane is often the basic limitation for modern and high-efficiency longwall complexes. The paper reports on selected observations and tests carried out in the Cw-4 longwall in seam 364/2 of the Budryk mine belonging to JSW SA. In observation of the methane level in the Cw-4 longwall, additional sensors installed in the end part of the longwall from the side of the gobs and registration of air velocity and methane concentration in the multipoint system built in the selected longwall cross-section were used, regardless of the air parameters recorded in the monitoring system.

Individuals with Parkinson’s Disease (PD) are at an increased risk of falls due to associated motor symptoms and impaired postural control. Gait dysfunction, observed soon after diagnosis, leads to disability with disease progression. The purpose of this study was to determine if there were differences in dynamic postural control during self-paced walking and obstacle-crossing between persons with mild to moderate PD and healthy controls. Participants included nine individuals with mild to moderate PD (PD cohort) and nine age- and gender-matched controls (CON cohort). Anatomical marker trajectories and ground reaction forces were collected as participants walked along the pathway. Three successful representative right and left gait cycles were analyzed using Visual3D biomechanical software. Analyses, involving a mixed model ANOVA using R Statistical Software, examined spatiotemporal (ST) gait parameters for strides involving the leading and trailing limbs and dynamic balance variables, including COM - COP inclination angle, and the COP - COM M/L, COP - XCOM M/L, UMAX - XCOM M/L distances, at distinct points from the stance limb related to the leading and trailing legs. There were no differences between CON and PD for all ST gait parameters during obstacle crossing, except for a significantly reduced step length (p = 0.00489) for the PD group related to the trailing limb. However, there were significant main effects of Step and Condition interacting with Step for swing time, stance time, and step length. For both CON and PD groups the COP - COM , COP - XCOM , UMAX - XCOM metrics demonstrated that the COM was medial to the BOS from first double support, generally moving more medially through second double support for the stance limb during motion of the leading and trailing limbs. Event and Event interacting with Condition were significant for the COP - COM and COP - XCOM variables, while UMAX – XCOM was significant only for Event (p < 0.001). The PD group demonstrated significantly larger mean values for COP – COM M/L at first double support (p = 0.00435) and COP - XCOM M/L at second double support (p = 0.0158) for the second step. Our results suggest that the margin of stability may be useful in discerning dynamic postural control adaptations during walking and obstacle negotiation in persons with mild PD.

Hepatitis is the eighth highest cause of mortality globally and second-highest in Pakistan. The purpose of this study was to determine frequency of Hepatitis B and C and related lifestyle and socio-demographic risk factors among adults. The data were collected though questionnaire from Hepatitis B and C patients from Mayo and Jinnah hospital Lahore. The data was analyzed using SPSS version 18. There were 5095 patients with Hepatitis B and C out of which 146 patients (67 males and 79 females) filled questionnaire. The frequency of hepatitis C was higher than hepatitis B. The significant risk factors associated with hepatitis B and C were education, marital status, family history, household income, and type of food consumed. Therefore, socio-demographic and lifestyle risk factors related interventions are needed to reduce frequency of Hepatitis B and C.

Antimicrobial resistance (AMR) is a global threat associated with high morbidity and mortality, particularly in low- and middle-income countries. Inappropriate use of antimicrobials is one of the major drivers of the AMR pandemic. This study aims to evaluate the rate and quality of antimicrobial prescription and use at the University Teaching Hospital of Kigali, a tertiary referral and teaching hospital. A point prevalence survey (PPS) of antimicrobial prescription was conducted using the Global PPS tool, including the healthcare-acquired infections (HAI)-module. On the day of PPS, 39.3% (145/369) of the patients were prescribed at least one antimicrobial. Out of 259 prescribed antimicrobials, 232 (89.6%) were antibacterials of which 151 (65.1%) belonged to the Watch-group of the WHO AWaRe classification. Top three antibiotics prescribed were cefotaxime (87; 37.5%), parenteral metronidazole (31; 13.4%); and meropenem (23; 9.9%). Stop/review of the prescribed antimicrobials was documented in 27/259 prescriptions (10.4%). Surgical prophylaxis (SP) was prescribed for more than one day in 83.3% of 61. Samples for culture were sent for 27.1% (63/232) of all prescribed antibiotics. This PPS showed a high usage of Watch antibiotics, prolonged surgical prophylaxis and other poor-quality indicators. Therefore, there is an urgent need for antimicrobial stewardship interventions.

Leveraging the open-world understanding capacity of large-scale visual-language pre-trained models has become a hot-spot in point cloud classification. Recent approaches rely on transferable visual-language pre-trained models, classifying point clouds by projecting them into 2D images and evaluating consistency with textual prompts. These methods benefit from the robust open-world understanding capabilities of visual-language pre-trained models and require no additional training. However, they face several challenges summarized as prompt ambiguity, image domain gap, view weights confusion, and feature deviation. In response to these challenges, we propose PointBLIP, a zero-training point cloud classification network based on the recently introduced BLIP-2 visual-language model. PointBLIP is adept at processing similarities between multi-images and multi-prompts. We separately introduce a novel method for point cloud zero-shot and few-shot classification, which involves comparing multiple features to achieve effective classification. Simultaneously, we enhance the input data quality for both the image and text sides of PointBLIP. In point cloud zero-shot classification tasks, we outperform state-of-the-art methods on three benchmark datasets. For few-shot classification tasks, to the best of our knowledge, we present the first zero-training few-shot point cloud method, surpassing previous works under the same conditions and showcasing comparable performance to full-training methods.

The paper discusses the classification of fuzzy metrics based on their continuity conditions, dividing them into Erceg, Deng, Yang-Shi, and Chen metrics. It explores the relationships between these types of fuzzy metrics, concluding that a Deng metric in [0,1]-topology must also be Erceg, Chen, and Yang-Shi metrics. The paper also proves that the product of countably many Deng pseudo-metric spaces remains a Deng pseudo-metric space, and demonstrates some σ-locally finite properties of Deng metric space. Additionally, the paper constructs two interrelated mappings based on normal space and concludes that if a [0,1]-topological space is T1 and regular, and its topology has a σ-locally finite base, then it is Deng metrizable, and thus Erceg, Yang-Shi, and Chen metrizable as well.

3D measurement is a high-throughput method that can record a large amount of information. In this study, we have developed new methods that could be used for morphological analysis of plants from the information contained in 3D data. Specifically, we investigated characteristics that can be measured by scale (dimension) and/or visual assessment by humans. The characteristics that can be measured on a scale-related dimension were tested based on the bounding box, convex hull, column solid, and voxel. Furthermore, for characteristics that can be evaluated by visual assessment, we propose a new method using normal vectors and local curvature (LC) data. For these examinations, we used our highly accurate all-around 3D plant modelling system. The correlation coefficients between manual measurements and the scale-related methods were all above 0.9. In particular, the differences in LC calculated from the normal vector data allowed us to visualize and quantify the concavity and convexity of leaves. Furthermore, we also found a difference in the time point at which leaf blistering began to develop among the cultivars. The precise 3D model made it possible to perform quantitative measurements of lettuce size and morphological characteristics. In addition, the newly proposed LC-based analysis method made it possible to quantify the characteristics that rely on visual assessment.

Previous studies demonstrate the critical importance of non-coding RNAs interfacing with chromatin-modifying machinery resulting in promoter-enhancer-based gene regulation and raise the possibility that many other enhancer-like RNAs may operate via similar mechanisms. Critically, more than 80% of the disease-linked variations identified in genome-wide studies are located in the non-coding regions of genomes, especially non-coding RNA, suggesting non-coding RNAs are relevant to disease. Thus, a critical path forward for understanding non-coding RNAs' role, especially long non-coding RNAs, is to understand the genomic regions' transcriptional regulation, especially non-coding regions. Here, we developed a user-friendly R package called SomaGene for studying and identifying enhancer-like non-coding RNAs with enriched somatic mutations in the cancer genome. SomaGene accepts different genomic variants (whole genome/exome somatic point mutations, structural variations, copy number variations) to identify those RNAs that significantly mutated in diseases (e.g., cancer). It then uses multiple publicly available genomics and epigenetics datasets including ENCODE epigenomics annotations, FANTOM5 tissue-specific expression profiles, disease-associated genome-wide association SNPs, and tissue-specific eQTL pairs to identify those RNAs with potentially enhancer function. SomaGene, as a powerful R package, can provide the opportunity to cancer scientists to study the roles of non-coding RNAs in different cancer genomes.

The advent of high throughput sequencing has enabled researchers to systematically evaluate the genetic variations in cancer, resulting in identifying many cancer-associated genes. Although cancers in the same tissue are widely categorized in the same group, they demonstrate many differences concerning their mutational profiles. Hence there is no “silver bullet” for the treatment of a cancer type. This reveals the importance of developing a pipeline to identify cancer-associated genes accurately and re-classify patients with similar mutational profiles. Classification of cancer patients with similar mutational profiles may help discover subtypes of cancer patients who might benefit from specific treatment types. In this study, we propose a new machine learning pipeline to identify protein-coding genes mutated in a significant portion of samples to identify cancer subtypes. We applied our pipeline to 12270 samples collected from the International Cancer Genome Consortium (ICGC), covering 19 cancer types. Here we identified 17 different cancer subtypes. Comprehensive phenotypic and genotypic analysis indicates distinguishable properties, including unique cancer-related signaling pathways, in which, for most of them, targeted treatment options are currently available. This new subtyping approach offers a novel opportunity for cancer drug development based on the mutational profile of patients. We also comprehensive study the causes of mutations among samples in each subtype by mining the mutational signatures, which provides important insight into their active molecular mechanisms. Some of the pathways we identified in most subtypes, including the cell cycle and the Axon guidance pathways, are frequently observed in cancer disease. Interestingly, we also identified several mutated genes and different rates of mutation in multiple cancer subtypes. In addition, our study on “gene-motif” suggests the importance of considering both the context of the mutations and mutational processes in identifying cancer-associated genes. The source codes for our proposed clustering pipeline and analysis are publicly available at: https://github.com/bcb-sut/Pan-Cancer.

The purpose of this paper is to prove strong convergent theorems for Browder's type iterations and Halpern's type iterations of a family of nonexpansive mappings in a complete geodesic space with curvature bounded above by a positive number. Moudafi's viscosity type methods are also discussed without the nice projection property.

In this paper we describe a nonparametric maximum likelihood (NPML) method for estimating multivariate mixing distributions. Given $N$ independent observations, convexity theory shows that the NPML estimator is discrete with at most $N$ support points. The original infinite NPML problem then becomes the finite dimensional problem of finding the location and probability of the support points. The probability of the support points is found by a Primal-Dual Interior-Point method; the location of the support points is found by an Adaptive Grid method. Our method is able to handle high-dimensional and complex multivariate mixture models.An important application is discussed for the problem of population pharmacokinetics and a non-trivial example is treated.Our algorithm has been successfully applied in hundreds of published pharmacometric studies. In addition to population pharmacokinetics, this research also applies to empirical Bayes estimation and many other areas of applied mathematics.

The study focused on two climatic variables i.e. precipitation and stream flow for analysing change in trend of rainfall for the River Ssezibwa Catchment area and stream flow of River Ssezibwa. This Catchment is found in the districts of Mukono and Buikwe in Uganda. In this area agriculture is majorly dependent on rainfall and irrigation on a small scale. However, rainfall occurrence has become unpredictable over the past few years as result of the changes in patterns of weather. This has caused severe effects on the agricultural cropping system as well as caused negative effects on the natural water resources. Stream flow data of 57 years (1960 – 2017) and rainfall data for 35 years (1982 – 2017) on a daily basis was analysed to find out the trend and detect change point. Trend analysis was done by using the non-parametric analysis while the change point detection was carried out by using the Pettit test (1979).Magnitude of trend for the time series data was carried out using Sen’s Slope estimator and Mann – Kendall test was done to determine the trend. Results from the statistical analysis highlighted that; for stream flow the trend was generally positive and change point detected to be in the year 2000 while for rainfall data analysis indicated that the trend was predominantly negative and change point was in the year 1998.

Causal relationships lie at the very core of our scientific description of biophysical phenomena. Nevertheless, observable facts such as chaotic dynamics, symmetry breaks, long-range collisionless neural interactions, zero-value energy singularities, particle/wave duality, ecological approaches to visual perception elude cause effect inductive explanations. We illustrate how simple topological claims, seemingly useless and far away from scientific inquiry (e.g., “given at least some wind on Earth, there must at all times be a cyclone or anticyclone somewhere”; “if one stirs to dissolve a lump of sugar in a cup of coffee, it appears there is always a point without motion”; “at any moment, there is always a pair of antipodal points on the Earth’s surface with equal temperatures and barometric pressures”) describe a real world, made of projections and mappings unsupplied with causality. Unavoidable, necessary, passive, spontaneous changes in systems’ shapes, dimensions and symmetries incarnate biophysical quantifiable counterparts of abstract mathematical concepts. Real features arising from topological mechanisms do not require causal powers to be produced, because are independent of exerted physical forces, energetic fields’ actions and thermodynamic constraints. Providing examples that shed novel interpretative light on phenomena such as double slit experiments, cellular mechanisms and brain function, we conclude as follows: countless scientific matters can be accessed through methodological weapons which not just break causality, replace temporal correlations and probabilistic a priori knowledge of previous cases, but also permit augments in available information devoid of entropy increases and energy losses.

TThe number of supermarkets offering a grocery delivery has been increasing during the last years. Many studies deduce CO₂ emission savings using this concept. Since the delivery of groceries also consumes energy and produces emissions, break-even points can be calculated, from where the delivery has environmental advantages compared to the customer pickup. In this paper, influences of differing vehicle use on break-even points for savings of energy and CO₂ emissions are analyzed for the case of Haidhausen Süd, a city district of Munich in Germany. Internal combustion engine and electric vehicles are investigated to depict current as well as future trends. After an introduction to the used methodology, the potential to save energy and CO₂ emissions related to the delivery of groceries in the chosen district of Munich is evaluated. Afterwards, influences on the break even points are presented and discussed. As the results show, a delivery of groceries leads to energy and carbon dioxide savings in a wide range of private vehicle use for grocery shopping trips. Nevertheless, if the complete customer vehicle fleet is electrified, the use of delivery vehicles with an internal combustion engine can cause an additional environmental impact at the current modal split for shopping trips in Germany.

In this paper we present the measurement of charged pion two-particle femtoscopic correlation functions in $\sqrt{S_{NN}}$= 200 GeV Au+Au collisions, in 31 average transverse mass bins, separately for positive and negative pion pairs. Lévy-shaped source distributions yield a statistically acceptable description of the measured correlation functions, with three physical parameters: correlation strength parameter λ , Lévy index α and Lévy scale parameter R. The transverse mass dependence of these Lévy parameters is then investigated. Their physical interpretation is also discussed, and the appearance of a new scaling variable is observed.

After a local pollution control plant significantly reduced phosphorus loading into a phytoplankton-dominated tributary of the Potomac River in the early 1980’s, water quality and biological communities were monitored bi-weekly from April-September. After a 10-year time-lag, submerged aquatic vegetation (SAV), once abundant in this freshwater tidal embayment, returned to the area in 1993. After additional reductions in nitrogen load starting in 2000, the system completely switched to a SAV-dominated state in 2005. Fish abundance didn’t change during these distinct phase changes, but the fish community structure did. Increases in SAV provided refuge and additional spawning substrate for species with adhesive eggs such as Banded Killifish (Fundulus diaphanus), which is now the most abundant species in the embayment. Other changes seen were a decrease in the relative contribution of open water dwelling species such as White Perch (Morone americana), and an increase of visual predators such as Largemouth Bass (Micropterus salmoides). The 30-year record of data from this Potomac River tributary has revealed many important long-term trends that validate the effectiveness of initiatives to improve water treatment, and will aid in the continued management of the watershed and point source inputs.

This article integrates existing theory from distributed computing and cryptology with anecdotal material from the cryptocurrency industry, to provide a comprehensive description of the minimum requirements of the hypothetical academic blockchain. The paper argues that such a community could significantly reduce the biases and misconduct that now exist in the academic peer review process. Theory suggests such a system could operate effectively as a distributed encrypted telecommunications network where nodes are anonymous, do not trust each other, and there is minimal central authority. To incentivize the academic community to join such a proposed community, the paper proposes a pseudo-cryptocurrency called litcoin (literature coin). This litcoin-based system would create economic scarcity based on proof of knowledge (POK), which is a synthesis of the proof of work (POW) mechanism used in bitcoin, and the proof of stake (POS) mechanism used in various altcoin communities. The paper argues that the proposed POK system would enable the academic community to more effectively develop the research it finds valuable.

Velvet worms, or onychophorans, include placental species and, as a phylum, have survived all mass extinctions since the Cambrian. They capture prey with an extraordinary adhesive net that appears in an instant. The first naturalist to formally mention them was Lansdown Guilding (1797-1831), a British priest from the Caribbean island of Saint Vincent. His life is as little known as the history of the field he initiated, onychophorology. This is the first general history of onychophorology, and I have divided it into half century periods. The beginning, 1826-1879, was defined by former students of great names in the history of biology, like Cuvier and von Baer. This generation included Milne-Edwars and Blanchard, and the greatest advances came from France, with smaller but still important contributions from England and Germany. In the 1880-1929 period, work concentrated in anatomy, behavior, biogeography and ecology, but of course the most important work was Bouvier’s mammoth monograph. The next half century, 1930-1979, was important for the discovery of Cambrian species; Vachon’s explanation of how ancient distribution defined the existence of two families; Pioneer DNA and electron microscopy from Brazil; and primitive attempts at systematics using embryology or isolated anatomical characteristics. Finally, the 1980-2020 period, with research centered in Australia, Brazil, Costa Rica and Germany, is marked by an evolutionary approach to everything, from body and behavior to distribution; for the solution of the old problem of how they form their adhesive net and how the glue works; the reconstruction of Cambrian onychophoran communities, the first experimental taphonomy; the first country-wide map of conservation status (from Costa Rica); the first model of why they survive in cities; the discovery of new phenomena like food hiding, parental feeding investment and ontogenetic diet shift; and for the birth of a new research branch, Onychophoran Ethnobiology, founded in 2015. While a few names appear often in the literature, most knowledge was produced by a mass of researchers who entered the field only briefly.

The COVID-19 pandemic profoundly impacted older people in residential aged care facilities (RACFs), especially those with dementia. This retrospective cohort study investigates the impact of the pandemic on agitation incidents within this population in 40 Australian RACFs. We compared pre-pandemic data (January-October 2019) with during-pandemic data (same months in 2020 and 2021) from electronic health records (EHRs) using Python to extract information from nursing notes. Various statistical analyses, including descriptive statistics to summarize the data, and a chi-square test to examine any significant association between the COVID-19 pandemic and the prevalence of dementia and agitation in dementia. Dementia prevalence dropped by 1.98% in 2021 compared to 2019, and by 4.09% compared to 2020 (p < 0.05). Overall agitation symptoms decreased by 20.1% from 2019 to 2021 (p < 0.05), but six specific symptoms increased: resisting (28.98%), wandering (11.78%), restlessness (3.19%), complaining (10.1%), arguing (2.36%), and outbursts (1.74%) (p < 0.05). Conversely, pacing decreased by 15.88% and speaking loudly de-creased by 10.9% (p < 0.05). Over half of the care recipients experienced agitation symptoms 2-5 times each year, increasing from 50.56% in 2019 to 58.28% in 2021 (p < 0.05). It is important to exercise caution regarding the accuracy of these findings due to the reduced opportunity for busy care staff to record behavioral changes caused by the isolation of individuals in their rooms during the pandemic.

(1) Context: Cancer triggers significant changes in family dynamics. It is noteworthy that coping and problem-solving skills, particularly in situations involving cancer in children and adolescents, have not been adequately explored in the context of family adaptation. This study aims to analyze the effectiveness of family interventions in coping to improve problem-solving skills in parents and/or caregivers of children and adolescents during and after oncological treatment. (2) Methods: This is a scoping review following the recommendations of the Joanna Briggs Institute and the Systematic Reviews and Meta-Analyses Extension for Scoping Review (PRISMA-ScR), from 2014 to 2024, in the databases LILACS, CINAHL, SCOPUS, Web of Science, and PUBMED. (3) Results: Forty-five studies were eligible. Coping strategies were categorized as follows: (1) positive attitudes (including a sense of courage and hope, family support to enhance resilience, and future planning), (2) caregiver empowerment (involving acceptance of diagnosis, emotional distancing, and coping through religiosity), and (3) communication skills (encompassing professional communication, horizontal dialogue with healthcare teams, and sincere communication with friends and family). (4) Conclusions: Over time, families develop coping and problem-solving strategies that influence changes in family functioning patterns, aiding them in accepting, reinterpreting, and reframing ideas and feelings associated with neoplasia.

We report the case of a 44-year-old woman who suffered gastric perforation after receiving bag-valve-mask (BVM) ventilation in the setting of alcohol intoxication. She had a markedly distended abdomen and cold, dusky lower extremities upon arrival to the emergency department. Imaging revealed a large volume intraabdominal accumulation of air with compression of the aorta. Needle decompression relieved symptoms of lower extremity arterial insufficiency. However, the patient quickly decompensated and subsequent exploratory laparotomy confirmed gastric rupture. A subtotal gastrectomy was performed but the patient ultimately passed on post-operative day two due to multi-organ dysfunction. Although BVM ventilation is commonplace in both the hospital and field, there is a lack of awareness of the serious complications of abdominal air accumulation due to their rareness in the adult population. Checking for abdominal distention during resuscitation ought to be routine in all patients. Signs of arterial insufficiency accompanying abdominal distention, once confirmed by diagnostic imaging that shows extensive pneumoperitoneum, are indicators of having reached a life-threatening level of air accumulation, calling for immediate needle decompression and exploratory laparotomy.

Non-pharmaceutical interventions (NPIs), including social distancing, wearing personal protective equipment, and lockdown measures, have been at the forefront of outbreak control in nursing homes. We used a mixed methodology to assess which NPIs nursing homes in the canton of Geneva, Switzerland, followed for their staff and residents during the first wave of the pandemic, between March 1, 2020 and June 1, 2020. For the qualitative component, we interviewed the attending physicians and/or director of each nursing home. Based on in-vivo codes, NPIs for nursing home workers and residents in each nursing home were thematically classified as: maximally restrictive, moderately restrictive, and minimally restrictive. In the quantitative component, we calculated incident rate ratios (IRR) for infection between the three levels of COVID-19-related measures taken in these nursing homes. We found an equal distribution of maximally (n=4), moderately (n=4), and minimally (n=4) restrictive NPIs. The extent of restriction did not show to be significantly associated with the cumulative incidence of COVID-19 cases among residents (maximally restrictive IRR = 3.90, 95%CI 0.82-45.54, p = 0.184; moderately restrictive IRR = 3.55, 95%CI 0.75-41.42, p = 0.212 ; minimally restrictive IRR = reference). Variabilities in NPIs adopted by nursing homes, and the number of COVID-19 cases appear to be randomly affected.

The COVID-19 pandemic has led to a substantial revolution in the incorporation of digital solutions in healthcare. This systematic review investigates the enduring physical and psychological consequences individuals experience up to two years post-recovery. Additionally, it focuses on examining the influence of mHealth interventions on these effects. Significantly, 41.7% of survivors experience lingering symptoms that have not been addressed, while 14.1% encounter difficulties in returning to work. The presence of anxiety, compromised respiratory functioning, and persistent symptoms highlight the immediate requirement for specific therapies. Telehealth, particularly telerehabilitation, presents itself as a possible way to address these difficulties. The study thoroughly examines 10 studies encompassing 749 COVID-19 patients, investigating the efficacy of telerehabilitation therapies in addressing various health markers. Telerehabilitation-based breathing exercises yield substantial enhancements in functional performance, dyspnea, and overall well-being. The results emphasize the potential of telerehabilitation to have a favorable effect on patient outcomes, however more research is needed to strengthen the existing evidence basis as one of the most important limitation is the limited number of trials and the evaluation of varied therapies. The analysis highlights the significance of digital solutions in post-COVID care and calls for ongoing research to improve comprehension and implementation of telehealth interventions in a swiftly changing healthcare environment.

Background and Aims: Late diagnosis of sepsis is associated with adverse consequences and high mortality rate. The aim of this study was to evaluate the diagnostic value of hematologic research parameters, that reflect the cell morphology of blood cells, available on the BC 6800 plus automated analyzer (Mindray) for the early detection of sepsis. Materials and Methods: A complete blood count (CBC) was performed by Mindray BC 6800 Plus Analyzer in 327 patients (223 with a confirmed diagnosis of sepsis following sepsis-3 criteria, 104 without sepsis), admitted at the Intensive Care Unit of the Novara’s Hospital (Italy) and in 56 patients with localized infection. Results: In univariate logistic regression, age, Hb, RDW, MO#, NMR, NeuX, NeuY, NeuZ, LymX, MonX, MonY, MonZ were associated with sepsis (p<0.005). In multivariate analysis, only RDW, NeuX, NeuY, NeuZ, MonX and MonZ were found to be independent predictors of sepsis (p<0.005). Morphological research parameters are confirmed to be predictors of sepsis even when analyzing the group with localized infection. Conclusions: In addition to already established biomarkers and basic CBC parameters, new morphological cell parameters can be a valuable aid in the early diagnosis of sepsis at no additional cost.

Process mining offers significant services in the development of digital threads and digital twin applications for healthcare. One of the sub-emerging case studies is the use of patients’ location data in process mining analyses. While the streamlining of published works is focused on introducing process discovery algorithms, there is a necessity to address challenges beyond that. Literature analysis indicates that explainability, reasoning, and characterizing the root causes of process drifts in healthcare processes is an important but overlooked challenge. In addition, incorporating domain-specific knowledge into process discovery could be a significant contribution to process mining literature. To address this, we present the DIAG approach that consists of a meta-model and an algorithm that enables diagnosing in process mining through an ontology-driven approach. With DIAG, we modeled the healthcare semantics in a process mining application and diagnosed the causes of drifts in patients’ pathways. We performed an experiment in a hospital living lab to examine the effectiveness of the DIAG approach.

Accountable Care Organizations (ACOs) are healthcare delivery systems that aim to coordinate and improve the quality of care for patients while reducing costs. ACOs bring together doctors, hospitals, and other healthcare providers to work as a team to care for a defined population of patients. The idea behind ACOs is to shift the focus from paying for each individual service provided to patients, known as fee-for-service, to paying for the overall care and well-being of patients.ACOs typically operate under a shared savings model and also encourages providers to use data and technology to better coordinate care and improve patient outcomes.ACOs can be physician-led organizations, hospital-led organizations, and collaborations between healthcare providers. The success of ACOs depends on many factors, including the level of cooperation and collaboration among healthcare providers, the quality of care provided, and the ability to effectively manage costs.Despite their potential benefits, ACOs also face challenges, including the difficulty of coordinating care across multiple healthcare providers, the need to invest in technology and data management systems, and the challenge of changing provider behavior.This study assessed a number of systemic reviews and journals to assess the impact of ACO’s on population health. ACO’s have shifted away from costly care patterns and thus helped many countries.

Chest trauma is one of the most serious and difficult injuries, with various complications that can lead to ventilation - perfusion (V/Q) mismatch and systemic hypoxia. We are presenting a case of 53 – year - old male with no comorbidities or chronic therapy, who was admitted to the Intensive Care Unit due to severe respiratory failure after chest trauma. He developed right - sided pneumothorax and then thoracic drain was placed. On admission, the patient was hemodynamically unstable and tachypneic. The patient was intubated and mechanically ventilated, febrile (38.9°C) and unconscious. A lung CT showed massive non-ventilated areas predominantly in the right lung. He was ventilated with PEEP of 10 cmH2O with a FiO2 of 0.6 – 0.8. Empirical broad-spectrum antimicrobial therapy was immediately initiated. Both high FiO2 and moderate PEEP were maintained and adjusted according to the current blood gas values and oxygen saturation. After Stenotrophomonas maltophilia was identified and treated with sulfamethoxazole/trimethoprim his general condition gradually improved, and he was weaned from mechanical ventilation. In conclusion, both ventilatory and antibiotic therapy were needed to improve oxygenation and outcome of the patient with pneumonia due to the resistant S. maltophilia with V/Q mismatch.

BACKGROUNDː The so-called Low Cardiac Output Syndrome (LCOS) is one of the most common complications in pediatric patients with congenital heart disease undergoing corrective surgery. LCOS requires high concentrations of inotropes to support cardiac contractility and improve cardiac output, allowing for a better systemic perfusion. To date, serum lactate concentrations and central venous oxygen saturation (ScVO2) are the most commonly used perfusion markers, but they are not completely reliable to identify a state of global tissue hypoxia. The study aims to evaluate whether the venoarterial carbon dioxide difference/arterial-venous oxygen difference ratio [P(v-a)CO2/C(a-v)O2] can be a good index to predict the development of LCOS in the aforemen-tioned patients, so as to treat it promptly. METHODSː This study followed a population of 98 children undergoing corrective cardiac surgery from June 2018 to October 2020 at the Department of Cardiac Surgery of University Hospital Inte-grated Trust and their subsequent admission at the Postoperative Cardiothoracic Surgery Intensive Care Unit. During the study, central arterial and venous blood gas analysis were carried out before and after cardiopulmonary bypass (CPB) (pre-CPB and post-CPB), at admission to intensive care unit, before and after extubation and at any time of instability or modification of the patient’s clinical and therapeutic conditions. RESULTSː The data analysis shows that 46.9% of the children developed a LCOS (in line with the current literature) but that there is no statistically significant association between the P(v-a)CO2/C(a-v)O2 ratio and LCOS onset. Despite the limits of statistical significance, however, a 31% increase in the ratio emerged from the pre-CPB phase to the post-CPB phase when LCOS is present. CONCLUSIONSː This study confirms a statistically significant association between the most used markers in adult patients (serum lactate concentration, ScVO2 and oxygen extraction ratio-ERO2) measured in the pre-CPB phase and the incidence of LCOS onset, especially in patients with he-modynamic instability before surgery.

Semantic interoperability facilitates exchange and access of health data that is being documented in EHRs with various semantic features. In the EU, the regulation proposal of European health data space requires development of semantic interoperability. To achieve a fully integrated EHDS ecosystem leveraging the value of health data, stakeholders need to overcome challenges of implementing common standards and other semantic interoperability features. We aimed to research what scientific evidence is available on developing semantic interoperability. Our research questions focused specifically on key features and approaches for semantic interoperability and on possible benefits of these choices. For that purpose, we performed a systematic literature review by defining our study framework based on previous research. Our results consisted of 10 studies where data models, ontologies, terminologies, classifications, and standards were applied for building interoperability. Through increased access to interoperable patient information, a better quality and outcomes in care can be achieved. Better communication based on easily accessible data is facilitated between health professionals and between clinicians and the patients. When heading towards semantic harmonization as outlined in the EHDS proposal, more experiences and analyses are needed to assess how applicable the chosen solutions are for semantic interoperability of European health care data.

Abstract: Background: To determine the impact of a patient's ethnicity on the seeking preventive dental services at the Community Health Centers (CHCs) in South-Central Texas. Methods: Pri-mary electronic health records (HER) data were collected regarding each patient's medical and dental history, and comprehensive treatment planning. The researchers retrieved EHR from Jan-uary 2016 to 2022. Bivariate analysis was completed to test outcome with predicator and covariates using appropriate statistical tests. A multiple linear regression model was used to understand the association between the predictor and outcome variable while controlling for confounders. Results: The study findings revealed significantly higher dental visits (2.26 ± 2.88) for Hispanic patients. The results from the multiple regression model indicated that non-Hispanic patients had a 8% fewer chance of visiting the CHCs for preventive dental services compared to the Hispanic population (p-value<0.001) when all other variables are held constant. However, the study results were not significant as the effect size was small to conclude the effect of ethnicity on the patients visiting the dental clinic at the CHCs for preventive services. Conclusion: The study concluded that there is no difference in the preventive dental services completed by Hispanics and Non-Hispanics when all other variables are controlled.

Methods to handle uncertainty in economic evaluation have gained much attention in the literature and the cost-effectiveness acceptability curve (CEAC) is the most widely used method to summarize and present uncertainty associated with program costs and effects in cost-effectiveness analysis. Some researchers have emphasized the limitations of the CEAC for informing decision and policy makers as the CEAC is insensitive to radial shifts of the joint distribution of incremental costs and effects in the North-East and South-West quadrants of the cost-effective plane (CEP). Furthermore, it has been pointed out that the CEAC does not incorporate risk-aversion in valuing uncertain costs and effects. In the present article we show that the cost-effectiveness affordability curve (CEAFC) captures both dimensions of the joint distribution of incremental costs and effects on the CEP and is therefore sensitive to radial shifts of the joint distribution on the CEP. Furthermore, the CEAFC also informs about the budget impact of a new intervention as it estimates the joint probability an intervention is both affordable and cost-effective. Moreover, we show that the cost-effectiveness risk-aversion curve (CERAC) allows to incorporate risk-aversion into the analysis and can therefore be used to inform decision-makers who are risk-averse. We use data from a published cost-effectiveness model of palbociclib in addition to letrozole versus letrozole alone for the treatment of oestrogen-receptor positive, HER-2 negative, advanced breast cancer to demonstrate the differences between CEAC, CEAFC and CERAC and show how these can jointly be used to inform decision and policy makers.

In recent years, Lassa fever has been announced as an infectious disease in the world, a few imported cases have been accounted for in various pieces of the world and there are developing worries of the possibilities of Lassa fever Virus as an organic weapon. Regardless of its assaulting impact, no substantial arrangement has been created to reduce the hazard of the ailment, about a large portion of 10 years after identifying it. A Review based on the documents from the literature search on PubMed, Scopus, Goggle Scholar and Science direct. Out of these, the final 16 articles that met the criteria were selected. Relevant information on epidemiology, the burden of management and control were obtained. Timely and effective containment of the Lassa fever disease in Lassa village four decades ago could have minimized the devastating effect and threats posed by this illness in the West African sub-region and indeed the entire globe. That was a hard lesson calling for much more proactive measures towards the eradication of the illness at primary, secondary, and tertiary levels of health care. Hence, the paper is aimed at appraising the threats associated with Lassa fever disease; its demands on curtailing the menace of the epidemic, and recommendations on important focal points.

A significant part of the literature on innovative practice in medicine relates to seizing opportunities and curbing harms for patients in desperate situations. Unfortunately, the term innovation has multiple meanings and a rich rhetorical flourish that adds confusion and misunderstanding to an already difficult debate. This paper aims to enhance the current definition of innovative practice for medicine. First, we replace the term innovation with the more literal of new non-validated practice. To identify this meaning, we analyse the traditional research ethics’ distinction between research, validated practice, and innovation in the Belmont Report. Second, we propose the following explicit definition of new non-validated practice: the first or recent use of diagnostic, therapeutic or preventive interventions that introduce a significant change, with an insufficient level of evidence of safety or efficacy for regular healthcare, and with the main aim to benefit individual patients. This definition is a promising conceptual tool to inform empirical research, ethicists, and the harmonization of its regulation and legislation (e.g. right-to-try laws).

Translation of the genetic code into proteins is the main process across all life and ribosomes are ancient cellular machines uniquely enabling this information transformation. We provide a brief overview of the recent advances in linking the ribosomal structure and evolution. Based on these insights into ribosomal organisation across time, we propose that early replication and protein biosynthesis functions were inseparable and in fact were performed by the same ancient RNA molecule, the riboreplisome. Riboreplisome hypothesis helps to address issues of non-Darwinian evolution and complicated starting point that are characteristic to the RNA world, protein world and RNA:protein mixed co-development theories. We suggest that the riboreplisome is the missing link and a molecular machine connecting chemical and biological evolution paths, by being capable of basic genetic and feature selection functions in a cell- or cell-free setting. The riboreplisome hypothesis allows ease of sequential, genetically uninterrupted emergence and sophistication of the genetic code and its decoding machinery, and provides plausible explanations to the origins of the three main RNA types involved in the decoding: the ribosomal, transfer and messenger RNA. Furthermore, riboreplisome can help explaining the co-evolution of aminoacylation machinery, the driving force behind selective gene transcription and expression, and the cell-like compartmentalisation. While we may never find the original riboreplisome again, we might continue to discover different molecular remnants of its prior existence across the existing biological RNA, which, once identified or resurrected, can be useful in synthetic biology applications.

An axiomatic theory is proposed that reconciles the existence of an absolute scale for time (Planck time) and special relativity. According to this theory speed of light c becomes a variable which is proposed to be taken as the fifth dimension.