Deviation Values Research Articles

Advanced Amperometric Microsensors for the Electrochemical Quantification of Quercetin in Ginkgo biloba Essential Oil from Regenerative Farming Practices.

In this study, we present a novel approach using amperometric microsensors to detect quercetin in cosmetic formulations and track its metabolic behavior after topical application. This method offers a sensitive, real-time alternative to conventional techniques, enabling the detection of quercetin's bioavailability, its transformation into active metabolites, and its potential therapeutic effects when applied to the skin. Quercetin (Q) is a bioactive flavonoid known for its potent antioxidant properties, naturally present in numerous plants, particularly those with applications in cosmetic formulations. In response to the growing interest in developing novel plant-based dermo-cosmetic solutions, this study investigates the electrochemical detection of quercetin, a ketone-type flavonoid, extracted from Gingko biloba essential oil. Three newly designed amperometric microsensors were developed to assess their efficacy in detecting quercetin in botanical samples. The sensor configurations utilized two forms of carbon material as a foundation: graphite (G) and carbon nanoparticles (CNs). These base materials were modified with paraffin oil, chitosan (CHIT), and cobalt(II) tetraphenylporphyrin (Co(II)TPP) to enhance sensitivity. Differential pulse voltammetry (DPV) served as the analytical method for this investigation. Among the sensors, the CHIT/G-CN microsensor exhibited the highest sensitivity, with a detection limit of 1.22 × 10-7 mol L-1, followed by the G-CN (5.64 × 10-8 mol L-1) and Co(II)TPP/G-CN (9.80 × 10-8 mol L-1) microsensors. The minimum detectable concentration was observed with the G-CN and CoP/G-CN microsensors, achieving a threshold as low as 0.0001 μmol L-1. Recovery rates and relative standard deviation (RSD) values averaged 97.4% ± 0.43, underscoring the sensors' reliability for quercetin detection in botanical matrices.

Quantification of diclofenac in natural waters by the photo-induced fluorescence (PIF) method

A photo-induced fluorescence (PIF) method was developed for the quantification of diclofenac sodium, sodium 2-[2-(2,6-dichloroanilino)phenyl]acetate (NaDCF), in natural waters. Since diclofenac is not naturally fluorescent, its photoconversion under UV irradiation was carried out to produce highly fluorescent photoproduct(s) in various media (water, methanol, isopropanol, acetonitrile, ethyl acetate, dimethyl sulfoxide (DMSO), and a water-isopropanol mixture). The photoproduct responsible for the intense fluorescence of NaDCF in aqueous media was identified as chloro-carbazole by gas chromatography-mass spectrometry (GC-MS). Several PIF parameters were optimized. Using the PIF method, a highly fluorescent diclofenac photoproduct was obtained at λex/λem = 235/360 nm, with optimum fluorescence achieved after 10 min irradiation in a water-isopropanol mixture (90:10 v/v). The limit of detection (LOD) and quantification (LOQ) for diclofenac sodium in this medium were 0.11 ng ml–1 and 0.37 ng ml–1, respectively, with low relative standard deviation (RSD) values. The PIF calibration curves demonstrated good linearity, extending over one to three orders of magnitude, with correlation coefficients (R2) near unity, indicating good reproducibility. Analytical applications of this method to natural water samples yielded satisfactory results, with average recovery rates ranging from 84.77 to 101.72 %.

Determination of Emtricitabine from Pharmaceutical Dosage Form By extractive ion pair complex colorimetric method

Simple sensitive and accurate extractive colorimetric method was developed for the estimation of emtricitabine in pharmaceutical dosage forms. The method was based on the formation of colored ion pair complexes by the drugs with thiocynate ions. These ion pair complexes were quantitatively extracted under the experimental condition in chloroform. The absorbance values were measured at 620 nm respectively. The proposed method was validated statistically. A recovery of method was carried out by standard addition methods. The Beer’s law ranges were found to be 2-16 μg/ml, respectively. The low values of standard deviation and percentage RSD indicate high precision of method. Hence the method is useful for routine estimation of Emtricitabine in tablets respectively.

Investigating Thermal Stability in Hyderabad City, India

Abstract Thermal environment and land use status are the two controlling factors for determining the ecological health of any urban area. The study aims to investigates the stability of the relationship between land surface temperature with normalized difference built-up index in Hyderabad City, India using eight Landsat 8 data of the summer season in 2023. The study applies Pearson’s method for determining the correlation coefficient of this relationship. The results represent a consistent nature of land surface temperature and normalized difference built-up index values in this summer season as the range of the mean (0.08 for normalized difference built-up index and 6.78 oC for land surface temperature) and standard deviation (0.02 for normalized difference built-up index and 0.79 for land surface temperature) values of land surface temperature and normalized difference built-up index are significantly low. Land surface temperature and normalized difference built-up index values are very stable (correlation coefficient = > 0.63 for eight land surface temperature images and correlation coefficient = > 0.50 for eight normalized difference built-up index images). Moreover, normalized difference built-up index also built a stable strong positive relationship (average correlation coefficient =0.64) with land surface temperature. The summer season affects the vegetation life of the city and influences the relationship between land surface temperature and normalized difference built-up index. Built-up surface leads to an increase in the value of land surface temperature and also regulates the values of normalized difference built-up index. The study is useful for stable urban environmental planning.

Parallel Bayesian Optimization of Thermophysical Properties of Low Thermal Conductivity Materials Using the Transient Plane Source Method in the Body-Fitted Coordinate.

The transient plane source (TPS) method heat transfer model was established. A body-fitted coordinate system is proposed to transform the unstructured grid structure to improve the speed of solving the heat transfer direct problem of the winding probe. A parallel Bayesian optimization algorithm based on a multi-objective hybrid strategy (MHS) is proposed based on an inverse problem. The efficiency of the thermophysical properties inversion was improved. The results show that the meshing method of 30° is the best. The transformation of body-fitted mesh is related to the orthogonality and density of the mesh. Compared with parameter inversion the computational fluid dynamics (CFD) software, the absolute values of the relative deviations of different materials are less than 0.03%. The calculation speeds of the body-fitted grid program are more than 36% and 91% higher than those of the CFD and self-developed unstructured mesh programs, respectively. The application of body-fitted coordinate system effectively improves the calculation speed of the TPS method. The MHS is more competitive than other algorithms in parallel mode, both in terms of accuracy and speed. The accuracy of the inversion is less affected by the number of initial samples, time range, and parallel points. The number of parallel points increased from 2 to 6, reducing the computation time by 66.6%. Adding parallel points effectively accelerates the convergence of algorithms.

Development of the skill of dosed pressure in doctors in the process of professional retraining in the speciality «Osteopathy»

Introduction. The main instrument of diagnosis and treatment for an osteopathic physician is the hands. In the process of professional retraining in the speciality of osteopathy, doctors master various types of palpation and hundreds of osteopathic correction techniques, which require various strictly dosed pressure forces on tissues.The goal of the study is to research the development of pressure force dosing skill in primary retraining trainees in osteopathy during training.Materials and methods. The cohort prospective study was conducted during 2022–2024. The object of the study was the students of the professional retraining cycle in the speciality «Osteopathy» at the Institute of Osteopathy (Saint-Petersburg) — 15 people aged 32–65 years (median — 51 years), 8 men and 7 women. The survey was conducted 4 times: at the end of the 2nd course, in the fi rst and second half of the 3rd course and in the 4th course. Also during 2023, a cohort one-time survey of 16 doctors working in various specialities in the Lipetsk State Institution of Health Care № 4 «Lipetsk-Med» was conducted. This control group included doctors with work experience of at least 3 years, there were 10 men and 6 women aged 30 to 60 years (median 49 years), and according to these indicators, as well as work experience, there were no statistically signifi cant differences from the main group of osteopathy trainees (p>0,05). The subjects pressed their hand on the electronic scales and achieved weights of 30; 250; 800 g. They pressed the scales once with open eyes and saw the result, then tried to repeat it three times with closed eyes. The arithmetic mean was calculated from the three values and then the target weight was subtracted from it and the deviation from it was obtained in absolute numbers (g) and in %. Results. The survey of the cadets of primary retraining in the speciality «Osteopathy» at the end of the 2nd year of training, and doctors from the control group, showed that the future osteopaths demonstrated statistically significantly (p<0,05) smaller error (p<0,05) when trying to reproduce the weight of 30 g (from 0 to 220 g, median 50 g) and 250 g (from –190 to 350 g, median 41 g) from the doctors of the control group (respectively from 20 to 200 g, median 90 g and from –70 to 260 g, median 75 g). At the same time, physicians of both groups were more often mistaken in the larger direction. Calculating the % deviations from the target weight showed that for both groups of physicians, the minimum weight of 30 g was the most difficult to reproduce and the maximum weight of 800 g was the easiest. The relative values of deviations from the target weight were statistically significantly lower in the group of future osteopaths (p<0,05). In the process of training doctors on the course of professional retraining in osteopathy, the absolute values of deviations from the target weight systematically decreased, for the weights of 30 g (p=0,001) and 800 g (p=0,041) these changes were statistically significant. The most pronounced dynamics was observed for the improvement of the 30 g weight set. Men were more accurate in 800 g weight set, women were more accurate in 250 g weight set. The dynamics of the skill of dosing the 30 g pressure force showed similar results regardless of gender. In the experimental group, 9 people had been using manual therapy techniques in their medical practice for 3 to 17 years before the training. Calculation of correlations between the number of years of chiropractic practice and absolute deviations from the target weight showed low values of correlation coefficients in all courses of training (p>0,05).Conclusion. The skill of dosed pressure is better developed in the trainees of the 2nd year of the professional retraining course in osteopathy than in doctors who are not trained in osteopathy. In the process of osteopathic training, the skill of dosed pressure improves. Its development was independent of years of chiropractic practice, and little influenced by gender. The most pronounced progress occurred on the small (p=0,001) and large scales (p=0,041) in the 4th year of training.

Docking‑based virtual screening of BRD4 (BD1) inhibitors: assessment of docking methods, scoring functions and in silico molecular properties

To enhance the accuracy of virtual screening for bromodomain-containing protein 4 (BRD4) inhibitors, two docking protocols and seven scoring functions were compared. A total of 73 crystal structures of BRD4 (BD1) complexes were selected for analysis. Firstly, docking was carried out using both the LibDock and CDOCKER methods. The CDOCKER protocol was shown to be more effective based on the root mean square deviation (RMSD) values (in Å) between the docking positions and the co-crystal structures, achieving a docking accuracy rate of 86.3%. Then, among the various scoring functions (LigScore1, LigScore2, PLP1, PLP2, PMF, PMF04 and Ludi3), PMF showed the highest correlation with inhibition constants (r2 = 0.614), while Ludi3 scored lowest (r2 = 0.266). Finally, using ligand descriptors from PubChem, a strong correlation (r2 > 0.5) with inhibition constants for heavy atom count was found. Based on these comprehensive evaluations, the PMF scoring function emerged as the best tool for docking-based virtual screening of potential BRD4 (BD1) inhibitors. And the correlation between molecular properties and BRD4 (BD1) ligands also provided information for future design strategies.

Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube voltage and tube current

BackgroundThe low tube-voltage technique (e.g., 80 kV) can efficiently reduce the radiation dose and increase the contrast enhancement of vascular and parenchymal structures in abdominal CT. However, a high tube current is always required in this setting and limits the dose reduction potential. This study investigated the feasibility of a deep learning iterative reconstruction algorithm (Deep IR) in reducing the radiation dose while improving the image quality for abdominal computed tomography (CT) with low tube voltage and current.MethodsSixty patients (male/female, 36/24; Age, 57.72 ± 10.19 years) undergoing the abdominal portal venous phase CT were randomly divided into groups A (100 kV, automatic exposure control [AEC] with reference tube-current of 213 mAs) and B (80 kV, AEC with reference of 130 mAs). Images were reconstructed via hybrid iterative reconstruction (HIR) and Deep IR (levels 1–5). The mean CT and standard deviation (SD) values of four regions of interest (ROI), i.e. liver, spleen, main portal vein and erector spinae at the porta hepatis level in each image serial were measured, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The image quality was subjectively scored by two radiologists using a 5-point criterion.ResultsA significant reduction in the radiation dose of 69.94% (5.09 ± 0.91 mSv vs. 1.53 ± 0.37 mSv) was detected in Group B compared with Group A. After application of the Deep IR, there was no significant change in the CT value, but the SD gradually increased. Group B had higher CT values than group A, and the portal vein CT values significantly differed between the groups (P < 0.003). The SNR and CNR in Group B with Deep IR at levels 1–5 were greater than those in Group A and significantly differed when HIR and Deep IR were applied at levels 1–3 of HIR and Deep IR (P < 0.003). The subjective scores (distortion, clarity of the portal vein, visibility of small structures and overall image quality) with Deep IR at levels 4–5 in Group B were significantly higher than those in group A with HIR (P < 0.003).ConclusionDeep IR algorithm can meet the clinical requirements and reduce the radiation dose by 69.94% in portal venous phase abdominal CT with a low tube voltage of 80 kV and a low tube current. Deep IR at levels 4–5 can significantly improve the image quality of the abdominal parenchymal organs and the clarity of the portal vein.

Determining the most suitable empirical model for global solar radiation prediction in the lakes region

In this study, it was aimed to determine the most suitable model for predicting global solar radiation in the Lakes Region (Isparta, Burdur, Antalya). Through ATATEK-Solar software, a total of 15 models were tested, including 14 empirical models from the literature and a new artificial intelligence-supported model. Each model was analyzed with three different optimization algorithms (Nelder-Mead Simplex, Pattern Search, Simulated Annealing). In province-based evaluations, the Model 9 (RMSE: 0.1507, R²: 0.9990) for Isparta, and the Model 14 for Burdur and Antalya (RMSE: 0.1940, R²: 0.9992 and RMSE: 0.2218, R²: 0.9987, respectively) provided the most successful results. In regional analysis results, while the Model 5 (RMSE: 0.2626, R²: 0.9980) gave the lowest average error, the Model 13 (RMSE: 0.2649, R²: 0.9979, standard deviation: 0.0122) showed the highest consistency. These models were followed by the Model 6 (RMSE: 0.2646, R²: 0.9979, standard deviation: 0.0444). Although the Model 15 gave the best results in Burdur and Antalya, it had a high standard deviation value (0.2201) due to its low performance in Isparta. The characteristic features of the Lakes Region, including the presence of lake ecosystems, elevation differences, and the resulting microclimatic diversity, necessitate a regional approach in predicting global solar radiation. In this context, the Model 13 has been determined as the most suitable model that can be used throughout the region with its low error rate and high consistency. The obtained results can provide reliable predictions in evaluating the solar energy potential of the region and designing solar energy systems.

The Impact of Previous Accidents on The Probability of Repeat Accidents to Motorcyclists

According to 2019 statistics in Indonesia, the number of motorcycle accidents is relatively high, at 84.4 percent. Other data show that 16.13 percent of accidents include drivers who have previously been in an accident. The purpose of this study is to obtain a model of the probability of an accident for motorcycle riders who have previously experienced an accident as well as for motorcycle riders who have never experienced an accident before. Data were collected by interviewing motorcycle riders who had only been in one traffic accident and those who had been in more than one. The results of the analysis suggest that a driver who has had a previous accident has a 16 percent probability of having an accident, but a driver who has never had an accident has an 84 percent probability of having an accident. Furthermore, validation is carried out by calculating the Mean Absolute Deviation (MAD) value. The MAD value calculated from the results is 11.16 percent. Following that, numerous scenarios were run, with scenario 1 demonstrating that female drivers who have previously been in an accident have a higher accident probability than male drivers who have previously been in an accident. Meanwhile, scenario 2 shows that drivers above the age of 20 who have had a previous accident are more likely to be involved in an accident than drivers under the age of 20. Scenario 3 reveals that drivers who are on varied roadside variable roads and driving on bends can reduce their monotone level from 45% to 22%, but this condition has no effect on the level of fatigue and the probability of accidents. The final scenario shows that a driver who drives between 24:00 and 06:00 will have probability of fatigue by 73% and will have accident probability by 17%. Finding of this study is the drivers who have previously been involved in an accident are less likely to be involved in another accident compared to the drivers who have never been involved in an accident before.

Evaluation of cone beam computed tomography videos on Youtube

Purpose: Cone beam computed tomography (CBCT) is an imaging modality that plays an important role in dental practice. However, it is unclear whether videos with adequate and accurate information are available on a platform such as YouTube. The aim of this study was to determine whether CBCT videos posted on YouTube are indeed a valuable source of information. Methods: During the data collection process, we analyzed Google Trends searches using the keywords "cone beam computed tomography (in Turkish)", "dental tomography (in Turkish)", and "tooh tomography (in Turkish)" over the last 5 years. Then, 168 videos were analyzed as a result of searches on YouTube with these keywords. Among these videos, 48 were included in the study according to certain criteria. The number of view, viewing times, number of like, interaction index and viewing rate of the included videos were calculated. The upload source of the videos was categorized as clinic, dentist, educational channel, commercial, professional organization and TV channel. According to the upload source of the videos, the image quality, sound quality, narrator, purpose of the video, usefulness scoring and Global Quality Scale were evaluated. Results: The average number of views of the analyzed videos was determined as 1559.95, while the standard deviation value was determined as 2435.30. The average interaction index was 1.58, and the standard deviation value was 1.77. The average view rate was 377.55, and the standard deviation value was 956.88. Significant relationships were found between the upload source of the videos and the duration of the video, the number of subscribers of the channel that uploaded the video, and the number of likes (p=0.016, p=0.021, p=0.030, respectively). In addition, when the videos were evaluated in terms of their usability levels, significant relationships were found between the duration of the video, the number of likes, and the interaction index (p=0.001, p=0.009, p=0.015, respectively). Conclusion: This study reveals that CBCT videos posted on YouTube are generally of low quality and not informative. This highlights the need for reliable sources of information for dentists, patients, and future dentists.

Nonenzymatic Sensor Based on Glassy Carbon Electrode Modified by Platinum Nanoparticles Decorated Reduced Graphene Oxide for Glucose Detection in Human Urine

This research aims to develop a sensitive and selective nonenzymatic electrochemical sensor for glucose detection using a glassy carbon electrode modified with platinum nanoparticles (PtNPs) decorated on reduced graphene oxide (RGO). The structural properties and surface morphology of PtNPs/RGO composite were characterized using Raman spectroscopy and scanning electron microscopy (SEM). In addition, cyclic voltammetry (CV) and differential pulse voltammetry (DPV) techniques were employed to investigate glucose measurements in human urine samples. The developed sensor shows an increasing anodic peak of glucose with a linear response at a concentration range from 10 to 1000 µM, with a detection limit of 5 µM. The proposed sensor also demonstrated good reproducibility, indicated by the value of relative standard deviation (%RSD) of 3.9%, and maintained its current response over seven consecutive measurements. Moreover, the proposed sensor exhibited high selectivity for glucose detection against several potential interferences, such as potassium (K+), chloride (Cl−), magnesium (Mg2+), ascorbic acid, dopamine, and urea, with recovery values of 96-102%, which are acceptable within the analytical range. Furthermore, this proposed sensor successfully detected glucose in human urine samples, and their concentrations were not significantly different when measured with a commercial glucose sensor.

The value of dual-energy computed tomography angiography-based virtual monoenergetic imaging for evaluations after cerebral aneurysm clipping.

This study aimed to research the optimal energy range of dual-energy computed tomography angiography (DECTA)-based virtual monoenergetic imaging (VMI) for evaluations after cerebral aneurysm clipping. Sixty patients who underwent DECTA after cerebral aneurysm clipping were analyzed retrospectively. Conventional computed tomography angiography (CTA) was compared with VMIs at 60, 70, 80, 90, and 100 keV. The mean attenuation and standard deviation values within the regions of interest placed in the brain parenchyma and arteries with the worst artifact were measured, respectively. The ΔCT and artifact index (AI) values were calculated to assess the artifact severity. The contrast-to-noise ratio (CNR) was calculated to assess vascular contrast. Two radiologists assessed brain parenchyma and cerebrovascular scores qualitatively using a five-point Likert scale. Quantitative analysis showed that the artifacts of VMIs were significantly reduced compared with conventional CTA (P ≤ 0.014), except for the ΔCT and AI of 60 keV and the ΔCT of 70 keV. However, there was no significant difference in the vascular contrast on VMIs compared with conventional CTA, except for the CNR of 60 keV (P = 0.008). In qualitative analysis, the proportions of brain parenchyma scores and cerebrovascular scores ≥4 on the VMIs of 70 and 80 keV were higher than those of conventional CTA and other VMIs. For the patients who underwent DECTA after cerebral aneurysm clipping, the 70-80 keV VMIs are expected to be the optimal energy range for balancing clip artifacts and visibility of adjacent vessels. Studying the optimal energy range of DECTA-based VMI for post-operative assessment of aneurysm clipping can reduce metal artifacts in images and increase vascular contrast. This facilitates the follow-up of patients after aneurysm clipping, offers timely and accurate detection of postoperative complications, provides assistance to clinicians in diagnosis and treatment, and improves patient prognosis.

An LC‐MS/MS Method Development and Validation for the Quantification of Abametapir in Plasma Samples

ABSTRACTThe major goal of the current research study was to establish a sensitive tandem mass spectrometric method using electrospray ionization and liquid chromatography for quantifying abametapir in biological matrices. An Inertsil ODS chromatographic column with dimensions of 50 × 4.60 mm and 5.0 µm particles size was used to achieve chromatographic elution. Injection volume was set to 10.0 µL. Flow rate and stationary phase oven temperature were retained at 0.70 mL/min and 25.0°C. Isocratic elution was executed with acetonitrile, 0.10% v/v HCOOH, and methanol in a fraction of 20:10:70 (v/v/v) as the mobile phase. On multiple reaction monitoring, precursor‐product ion transitions were monitored at m/z 185.1→106.06 for abametapir and 287.16→269.15 for the abacavir internal standard. The drug's linearity graph had an r2 value of 0.9998 and was rectilinear at concentrations between 2.6 and 104 ng/mL. The inter‐ and intrabatch precision % relative standard deviation values ranged from 2.57 to 4.53. In short, the method that was made has been proven to work and validated as per the regulatory guidelines.

Spectral Data-Driven Prediction of Soil Properties Using LSTM-CNN-Attention Model

Accurate prediction of soil properties is essential for sustainable land management and precision agriculture. This study presents an LSTM-CNN-Attention model that integrates temporal and spatial feature extraction with attention mechanisms to improve predictive accuracy. Utilizing the LUCAS soil dataset, the model analyzes spectral data to estimate key soil properties, including organic carbon (OC), nitrogen (N), calcium carbonate (CaCO3), and pH (in H2O). The Long Short-Term Memory (LSTM) component captures temporal dependencies, the Convolutional Neural Network (CNN) extracts spatial features, and the attention mechanism highlights critical information within the data. Experimental results show that the proposed model achieves excellent prediction performance, with coefficient of determination (R2) values of 0.949 (OC), 0.916 (N), 0.943 (CaCO3), and 0.926 (pH), along with corresponding ratio of percent deviation (RPD) values of 3.940, 3.737, 5.377, and 3.352. Both R2 and RPD values exceed those of traditional machine learning models, such as partial least squares regression (PLSR), support vector machine regression (SVR), and random forest (RF), as well as deep learning models like CNN-LSTM and Gated Recurrent Unit (GRU). Additionally, the proposed model outperforms S-AlexNet in effectively capturing temporal and spatial patterns. These findings emphasize the potential of the proposed model to significantly enhance the accuracy and reliability of soil property predictions by capturing both temporal and spatial patterns effectively.

Group Counseling for Fostering Resident at UPTD Social Welfare Centre (UPTD-PSRAMPK) Ogan Ilir

Social Rehabilitation is spread across several cities in Indonesia and one of them is in South Sumatra which is located in Ogan Ilir. Children included in the UPTD Children's Rehabilitation Social Home Need Special Protection (UPTD – RAMPK) from various problems. Based on the results of observations, it show that the inmates also experience psychological issues, one of which is self-esteem. The subjects showed that they had negative feelings within themselves. They consider that they cannot do something even though they have been given various activities to improve their hard skills. The problem of low self-esteem can be overcome through a group counseling approach. Group counseling can also be a therapeutic medium for individuals to improve self-understanding and behavior change. The counseling session consists of 5 stages, namely: (a) the initial stage; (b) the transition stage; (c) the working stage; (d) the termination stage; and (e) follow-up. Subjects are also given a pretest and posttest. Based on the results of statistical data analysis using the paired sample t-test, it was found that there was a difference in scores before and after the provision of group counseling. This is shown by the mean value before group counseling of 25.10 and the mean value after group counseling of 26.60. The standard deviation value before group counseling was 1.28 and the standard deviation after group counseling was 1.95. In addition, the results of the data analysis conducted a test of the difference in a p-value of 0.048 &lt; 0.05. This shows that there is a significant difference before and after the provision of group counseling to Assisted Residents at the UPTD Social Rehabilitation Home for Children in Need of Special Protection (RAMPK).

Heart Rate Variability in Relation to Cardiovascular Autonomic Neuropathy Among Patients at an Urban Hospital in Kazakhstan.

In clinical practice, heart rate variability (HRV) has not been considered an indicator for the preventive assessment of cardiovascular autonomic neuropathy (CAN). The paper studies HRV in a large, randomly selected group. A cross-sectional study included a representative sample of 5707 Kazakhs aged 20 years and older from a total population of 25,454 attached to an urban clinic in the capital of Kazakhstan. The sample was drawn from individuals who visited the clinic for a preventive examination. CAN diagnosis was confirmed using data from questionnaires, electronic medical records, HRV, and heart rate measurements. Mean values of the standard deviation of normal sinus RR intervals (SDNN) and the root mean square of successive RR interval differences (RMSSDs) from a 24 h electrocardiogram recording were assessed. CAN was identified in 17.19% of the study participants, with a ratio of the subclinical to clinical phase of 1:0.24. Diabetes mellitus was present in 30.99% of patients with CAN. The prevalence of CAN varied by sex and age, aligning with the prevalence trajectory of diabetes. It was concluded that the SDNN and RMSSD parameters in electrocardiographic studies can be used for preventive measures in the context of limited healthcare resources.

Assessment of the Relationship Between Amino Acid Status and Parkinson's Disease: A Comprehensive Review and Meta-analysis.

Parkinson's disease (PD) is characterized by the inability of dopamine production from amino acids. Therefore, changes in amino acid profile in PD patients are very critical for understanding disease development. Determination of amino acid levels in PD patients with a cumulative approach may enlighten the disease pathophysiology. A systematic search was performed until February 2023, resulting in 733 articles in PubMed, Web of Science and Scopus databases to evaluate the serum amino acid profile of PD patients. Relevant articles in English with mean/standard deviation values of serum amino acid levels of patients and their healthy controls were included in the meta-analysis. Our results suggest that valine, proline, ornithine and homocysteine levels were increased, while aspartate, citrulline, lysine and serine levels were significantly decreased in PD patients compared to healthy controls. Homocysteine showed positive correlations with glutamate and ornithine levels. We also analyzed the disease stage parameters: Unified Parkinson's Disease Rating Scale III (UPDRS III) score, Hoehn-Yahr Stage Score, disease duration and levodopa equivalent daily dose (LEDD) of patients. It was observed that LEDD has a negative correlation with arginine levels in patients. UPDRS III score is negatively correlated with phenylalanine levels, and it also tends to show a negative correlation with tyrosine levels. Disease duration tends to be negatively correlated with citrulline levels in PD patients. This cumulative analysis shows evidence of the relation between the mechanisms underlying amino acid metabolism in PD, which may have a great impact on disease development and new therapeutic strategies.

DETAILED ELECTROCHEMICAL BEHAVIOR INVESTIGATION AND DETERMINATION OF ANTIPSYCHOTIC DRUG PALIPERIDONE ON A GLASSY CARBON ELECTRODE

Objective: A sensitive and cost-effective electrochemical method was developed on a bare glassy carbon electrode (GCE) for the determination of paliperidone (PAL), an antipsychotic drug used in the primary schizophrenia treatment affecting the whole world. Material and Method: The oxidation studies carried out in pH 8 phosphate buffer solution (PBS) by cyclic voltammetry (CV) showed that the oxidation reaction of PAL is a process including the same number of electrons and protons. The electrochemical detection of PAL was carried out by differential pulse voltammetry (DPV). Result and Discussion: The linearity range was between 1 µM and 100 µM. The limit of detection (LOD) and quantification (LOQ) values were calculated as 2.41x10-7 M and 8.033x10-7 M, respectively. The applicability of the developed method was confirmed by using it on synthetic human serum. The relative standard deviation (RSD) values were less than 2%. The selectivity of the analysis was demonstrated over against interfering substances such as ascorbic acid, KNO3, MgCl2, paracetamol, dopamine, Na2SO4, and uric acid with recovery% and RSD% values in the range 98.32%-101.56% and 0.15%-1.99%, respectively. The proposed method provided high sensitivity for PAL and is the first reported method for the electroanalysis of PAL.

Automated Assessment of Pelvic Longitudinal Rotation Using Computer Vision in Canine Hip Dysplasia Screening.

Canine hip dysplasia (CHD) screening relies on accurate positioning in the ventrodorsal hip extended (VDHE) view, as even mild pelvic rotation can affect CHD scoring and impact breeding decisions. This study aimed to assess the association between pelvic rotation and asymmetry in obturator foramina areas (AOFAs) and to develop a computer vision model for automated AOFA measurement. In the first part, 203 radiographs were analyzed to examine the relationship between pelvic rotation, assessed through asymmetry in iliac wing and obturator foramina widths (AOFWs), and AOFAs. A significant association was found between pelvic rotation and AOFA, with AOFW showing a stronger correlation (R2 = 0.92, p < 0.01). AOFW rotation values were categorized into minimal (n = 71), moderate (n = 41), marked (n = 37), and extreme (n = 54) groups, corresponding to mean AOFA ± standard deviation values of 33.28 ± 27.25, 54.73 ± 27.98, 85.85 ± 41.31, and 160.68 ± 64.20 mm2, respectively. ANOVA and post hoc testing confirmed significant differences in AOFA across these groups (p < 0.01). In part two, the dataset was expanded to 312 images to develop the automated AOFA model, with 80% allocated for training, 10% for validation, and 10% for testing. On the 32 test images, the model achieved high segmentation accuracy (Dice score = 0.96; Intersection over Union = 0.93), closely aligning with examiner measurements. Paired t-tests indicated no significant differences between the examiner and model's outputs (p > 0.05), though the Bland-Altman analysis identified occasional discrepancies. The model demonstrated excellent reliability (ICC = 0.99) with a standard error of 17.18 mm2. A threshold of 50.46 mm2 enabled effective differentiation between acceptable and excessive pelvic rotation. With additional training data, further improvements in precision are expected, enhancing the model's clinical utility.