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BackgroundSubstance Use Disorder (SUD) persists as a significant public health challenge worldwide, with an estimated prevalence of approximately 10-15% across the global populace. This condition is characterized by a notably high risk of lapses and relapses, even subsequent to treatment interventions. Mobile health interventions, owing to their widespread accessibility, emerge as a promising approach to diminish the risk of relapse post-treatment and to broaden the scope of care, especially in regions with a scarcity of trained medical professionals.MethodThis study is designed to assess the effectiveness of mobile interventions in mitigating cravings and preventing lapses among individuals diagnosed with SUD. Employing a two-armed, randomized controlled trial framework, the study will evaluate a self-administered psychological intervention delivered through a mobile application, Nałogometr 2.0. Over a period of three months, participants will engage with intervention modules that primarily incorporate mindfulness techniques and Cognitive Behavioral Therapy (CBT) principles. Ecological Momentary Assessment (EMA) will be utilized to gather longitudinal data on a range of variables that are indicative of craving intensity and the risk of lapse. In addition to this, a monthly-administered battery of questionnaires will be employed to gauge the severity of substance dependence, as well as to measure levels of anxiety, depression, and overall life satisfaction.ResultsResults will be submitted for publication in peer-reviewed journals.Clinical trial registrationhttps://clinicaltrials.gov/, identifier [NCT05730504].

Background: The prevalence of substance and behavioral addiction is estimated between 10 and 15% of the global population and remains a severe public health concern. Moreover, addiction treatment has several barriers, such as a lack of access to professional treatment or stigmatization. Mobile health interventions emerge as a promising solution. Methods: This two-armed randomized controlled trial (RCT) aims to assess the efficacy of a mobile app-based self-guided psychological intervention delivered via a smartphone app (Nałogometr) in reducing craving and lapse risk in problematic behaviors and substance use compared to a control condition. Participant recruitment and data collection will start in June 2022 and end in September 2022. Due to the nature of the study, i.e., a nationwide study of problematic substance use and behaviors, we will aim to recruit all individuals willing to participate. The four-week intervention condition includes short-term and long-term modules based mainly on mindfulness and cognitive behavioral therapy. Longitudinal data on several variables related to craving and lapse risk are collected daily using ecological momentary assessment (EMA). The primary outcomes of interest will be the self-reported number of lapses and craving level in daily EMA. Moreover, a questionnaire battery assessment is administered at baseline in the first week following onboarding, after five weeks, and after six months. The secondary outcome measures will include the severity of problematic substance use or behaviors, anxiety and depression, and life satisfaction. Results: Results will be submitted for publication in peer-reviewed journals. Clinical trial registration: [https://clinicaltrials.gov/], identifier [NCT054 34,429].

Background. Dexmedetomidine (DEX) is a widely used sedative agent for treating post-surgery patients. It also acts on hemodynamic parameters like heart rate or cardiac output. This study aimed to develop a pharmacokinetic-pharmacodynamic (PK/PD) model of DEX using bispectral index (BIS) and cardiac output (CO) as a response. Methodology and results. 21 mechanically ventilated elderly cardiac patients undergoing abdominal aortic surgery were enrolled in the study. DEX was given to maintain moderate or deep sedation. Genotypes of ADR2A*55 were identified using real-time PCR-HRM. Data were analyzed using nonlinear mixed-effect modelling. A two-compartment model described DEX pharmacokinetics. The sigmoid Emax and linear models were used to describe BIS and CO measurements. The typical value of EC50 for DEX effects on BIS was 3.62 ng/ml, and the slope between CO and DEX concentrations was 0.819 (L/min)/(ng/ml). We were unable to show the effects of considered covariates on DEX pharmacodynamics. Conclusions. WE proposed the PK/PD model of DEX to understand better the BIS and CO changes observed after surgery. The measured CI values were in the reference range showing that the used doses of DEX ensured stable cardiac function in the studied patients.

BackgroundThe prevalence of alcohol consumption in Poland is estimated to be as high as 80% of the adult population. The use of stimulants is the second most common reason for seeking addiction treatment. However, treatment outcomes remain unsatisfactory, as 40–85% of individuals who complete various treatment programs relapse and fall back into addiction within 2 years following program completion.MethodsThe 13-armed randomized controlled trial aimed to assess the effectiveness of a mobile app-based self-guided psychological intervention delivered via a smartphone app (Nałogometr) in reducing craving and lapse risk in problematic alcohol or stimulants use. Participant recruitment and data collection will be performed from June 2022 to September 2022. The 4-week mobile intervention program will include short-term and long-term intervention modules based mainly on mindfulness and cognitive-behavioral therapy. Intervention effectiveness assessment will include Ecological Momentary Assessment. That is, we will collect longitudinal data on a set of characteristics of day-to-day functioning. The primary outcomes will include a self-reported number of lapses and addiction craving level. In contrast, the secondary outcomes will be the severity of problematic substance use, anxiety and depression scores, and life satisfaction scores.ConclusionThis study will establish how mobile app-based self-guided psychological interventions can help reduce craving and lapse risk in alcohol and stimulant dependence. If successful, this randomized controlled trial (RCT) may provide an innovative, easily available, and cost-effective mHealth approach for craving and lapse risk in substance addictions.Clinical trial registration[https://clinicaltrials.gov/], identifier [NCT054 34429].

During hospitalization 97 years old patient had blood transfusion. This procedure lead to overload of cardiovascular system. Pharmacotherapy gradually improved the general condition of the patient. The patient was discharged in a stable state. Doubts arise; when blood should be transfused, in which cases should a blood transfusion be discontinued, what should be the recommendation for a blood transfusion for older people over the age of 90. There is a need for further research in geriatrics regarding the transfusion of blood and its components.

Klebsiella variicola is a bacterial species that was originally identified as a mild endosymbiont in plants, it occurs in humans and cattle. It is a bacterium that has been discovered relatively recently and research on the broader understanding of the pathogen is still underway. Vascular catheters are very often used to receive chemotherapy by patients. The purpose of this work was to present the management of blood infection caused by colonization of the vascular port with klebsiella varicola. The material described can be used to conduct patient pharmacotherapy. Care for a patient with a vascular port should be developed. There is a need to conduct staff training on: proper care and use of the vascular port and Huber needle for pharmacotherapy. Huber needles could be standard material in the list of required equipment in hospital wards to improve patient care with a vascular port.

Aim. This study aimed to evaluate the pharmacodynamics of dexmedetomidine in elderly cardiac patients. Material and Methods. Twelve patients of 60 years or older and need for analgesia after surgery or as a result of critical health conditions were included into our study. Dexmedetomidine was administered intravenously as a continuous infusion without the initial dose. At the beginning the infusion was started at the rate of 0.7 µg/kg/h and then it was continued in the range of 0.17–1.39 µg/kg/h according to desired level of sedation. Information about heart rate, systolic, diastolic and mean arterial blood pressure, bispectral index and cardiac index were collected a few minutes before, during and in 12 hours after infusion of dexmedetomidine. Results. The hemodynamic data as well as BIS level were collected from 12 patients. The duration of dexmedetomidine infusion was less than 9 hours. For each patient the reduction in blood pressure and heart rate compared to the value before dexmedetomidine infusion was observed. We did not observe bradycardia in any patient. Appropriate sedation level was achieved using only dexmedetomidine and ranged from 60 to 80. In only 2 cases it was necessary to give a single dose of another sedative. Conclusions. To conclude, in the patients’ population involved in the study, which included older cardiac patients dexmedetomidne has been shown as a sedative agent which enabled to achieve desire level of sedation in the recommended ranges without episodes of bradycardia, however hypotension events were noted.

High-dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high-throughput interrogation and characterization of cell populations. Here, we present an updated R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signalling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models or linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g., multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g., plots of aggregated signals).

High-dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high-throughput interrogation and characterization of cell populations. Here, we present an updated R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signalling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models or linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g., multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g., plots of aggregated signals).

High dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high throughput interrogation and characterization of cell populations.Here, we present an R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signaling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g. multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g. plots of aggregated signals).

Numerous data indicate that polymorphism of estrogen receptor alpha (ERalpha) may predict lipid levels, lipid response to hormone replacement therapy (HRT), myocardial infarction risk, bone fracture risk, bone mineral density (BMD) and changes in BMD over time. In this study we aimed to evaluate distribution of ERalpha PvuII and XbaI genotypes in population of Polish postmenopausal women qualified to different protocols of HRT. Subject of the study were 64 consecutive postmenopausal women aged from 45 to 65 years (mean 56.6) assigned to HRT. ERalpha PvuII and XbaI polymorphism was determined by PCR-restriction fragment length polymorphism (RFLP). The absence of PvuII and XbaI restriction sites were indicated by "P" and "X" and presence by "p" and "x", respectively. PvuII genotype was distributed as follows: PP 17.2% (n=11), Pp 50% (n=32), pp 32.83% (n=21). Frequency of XbaI genotype was: XX 6.25% (n=4), Xx 34.4% (n=22), xx 59.4% (n=38). Four haplotypes with following frequencies were recognized: PX 17.3%, px 47.4%, Px 24.4% and pX 10.9%. Prevalence of estrogen receptor alpha PvuII and XbaI polymorphisms in Polish women is similar to previously studied population.

Abstract Steady-state visual evoked potentials (SSVEP) are electroencephalographic signals elicited when the brain is exposed to a visual stimulus with a steady frequency. We analyzed the temporal dynamics of SSVEP during sustained flicker stimulation at 5, 10, 15, 20 and 40 Hz. We found that the amplitudes of the responses were not stable over time. For a 5 Hz stimulus, the responses progressively increased, while, for higher flicker frequencies, the amplitude increased during the first few seconds and often showed a continuous decline afterward. We hypothesize that these two distinct sets of frequency-dependent SSVEP signal properties reflect the contribution of parvocellular and magnocellular visual pathways generating sustained and transient responses, respectively. These results may have important applications for SSVEP signals used in research and brain-computer interface technology and may contribute to a better understanding of the frequency-dependent temporal mechanisms involved in the processing of prolonged periodic visual stimuli.