Chemical Factors Research Articles

Association Between Non-spinal Comorbid Medical Conditions and Neuropathic Low Back Pain. - A Further Unravelling of Pain Complexities in the Context of Back Pain.

Prospective cohort study. Understanding the complex nature of low back pain (LBP) is crucial for effective management. The PainDETECT questionnaire is a tool that distinguishes between neuropathic (NeP) and nociceptive (NoP) low back pain. Traditionally NeP and NoP have been primarily attributed to patho-anatomical abnormalities within the lumbar spine. However, increasing evidence points to multifaceted involvement, encompassing a range of physical, biomechanical, chemical, and psychosocial factors. The study aimed to determine the independent relationship between NeP as assessed by the PainDETECT questionnaire and non-spinal comorbid medical conditions. A prospective cohort study was conducted involving 400 patients suffering from chronic LBP (>6months), aged >18years, who complete the PainDETECT questionnaire and provided responses regarding the presence of any comorbid conditions. A binary logistic regression model was used to analyse the confounding status of comorbid medical conditions and pain severity measured by NRS to determine independent relationships between specific conditions and neuropathic pain. The study included 143 and 257 patients suffering from NeP and NoP, respectively. The NeP group had a 38% higher mean numerical rating scale score compared to the NoP group (8.10 1.55 vs 5.86 2.26, P < 0.001). The odds of developing NeP were 2.9 Exp(B) = 2.844, 95%C.I. [1.426-5.670], P < 0.01), 2.7 (Exp(B) = 2.726, 95%C.I. [1.183-6.283], P < 0.05) and 2.8 (Exp(B) = 2.847, 95%C.I. [1.473-5.503], P < 0.05) times higher in patients suffering from gastrointestinal conditions, rheumatoid arthritis, and depression, respectively. NeP as determined by the PainDETECT questionnaire, is associated with gastrointestinal conditions, rheumatoid arthritis, and depression. This pioneering study has shed light on the potential involvement of the gut microbiome as a common factor connecting non-spinal comorbidities and NeP. These findings underscore the importance of formulating personalized management plans tailored to individual pain and medical profiles, rather than relying on a blanket approach to pain management.

Assessment of the hematologic factors as a prognostic factor in COVID-19 patients

Introduction: Identifying laboratory predictors of disease progression should be a priority in current COVID-19 studies, which leads to an appropriate treatment for patients and reduce the risk of severe or critical illness. In this study we tend to analyze the hematologic and biochemical findings of COVID-19 patients as an easy-to-get diagnostic factor that can become the first choice for disease monitoring and the evaluation of general conditions. Methods: In this retrospective study, all patients with positive COVID-19 diagnosis that admitted to the emergency department, from 1st of April 2020, to 30th June, 2020 were included. For all patients, CBC, differential, urea, serum creatinine, and CRP were collected. Data analysis was performed using IBM® SPSS® Statistics 19.0 software. Pearson correlation and spearman correlation were used to analyze quantitative and qualitative data correlations respectively. Diagnostic ability of the variables was identified by their ROC curves. Results: A total number of 977 patients were included in this study. The median and mode of the age of the population are 50 and 29 respectively. ROC curves for diagnostic ability indicated that, Urea and creatinine have the highest diagnostic values with its optimum sensitivity and specificity for urea=62.5 mg/dL and creatinine=2.05 mg/dL, with sensitivities of 87.5% and 81.3%, and specificities of 80.6% and 82.1% respectively. Conclusion: The results from the current study show that no chemical or hematologic factor can properly detect COVID-19 in patients. Also, hematologic factors cannot determine patients’ prognosis; however creatinine and urea are able to estimate patients’ prognosis. Therefore, it is recommended to focus on the kidney injuries in COVID-10 patients for predicting their prognosis.

Effect of mowing versus abandonment of mesic grasslands in Central Europe on biomass use for biogas production: Implications for semi-natural ecosystem conservation

The economic management of lignocellulosic biomass from semi-natural grasslands is now a challenge across Europe. The abandonment of mowing these grasslands leads to the gradual degradation of these ecosystems. This study investigates how chemical and biological factors affect the suitability of biomass from abandoned grasslands for biogas production. We sampled 30 mown and 30 abandoned grassland sites in the Sudetes Mountains (Poland and Czechia). The cover contribution of short herbs was found to be significantly higher in mown grasslands (p < 0.001), while that of tall herbs was more prevalent in abandoned grasslands (p < 0.01). The specific biogas yield (SBY, NL kg−1 volatile solids) is negatively affected by an increased percentage of herbs in the biomass of mown and abandoned grasslands. This is due to the inhibitory effect of herbs on biodegradation, the increase in lignin content and the decrease in cellulose. This study highlights the importance of individual plant species in assessing grassland biomass for area biogas yield (ABY, m3 ha−1) and provides new insights into a field that has not yet been extensively investigated. In mown grasslands, ABY was most positively correlated with grass species (Arrhenatherum elatius, Trisetum flavescens and Festuca pratensis). In abandoned grasslands, the ABY was most correlated with herbaceous species (Galium aparine, Urtica dioica and Chaerophyllum aromaticum) and grasses (A. elatius and Elymus repens). Mown grasslands had significantly higher species richness (p < 0.001) compared to abandoned grasslands, but the number of species sampled did not correlate with SBY and ABY. This study contributes to the development of a sustainable bio-economy by highlighting the need for efficient use of grassland biomass. This approach helps protect semi-natural ecosystems and facilitates sustainable management of renewable resources.

Developing Online ICP-MS Methodology for Examining Catalyst Degradation Dynamics during Electrochemical CO2 Reduction

The electrochemical CO2 reduction reaction (CO2RR) provides a path towards sustainable production of carbon-based fuels and chemicals, using renewable electricity to drive the conversion of CO2 into products such as ethylene, ethanol, and methane. A challenge limiting the implementation of CO2RR is catalyst stability during operation, and greater fundamental understanding is needed to uncover the governing physical, chemical, and electrochemical factors, as well as degradation mechanisms, operative under reducing conditions. One tool that can be used for conducting such fundamental studies is online inductively coupled plasma mass spectrometry (ICP-MS). In this study, an experimental framework was developed for using online ICP-MS for time-resolved degradation studies during CO2RR conditions. Using a customized flow cell setup, we coupled an ICP-MS to a potentiostat to simultaneously apply a potential or current while evaluating dynamics and degradation for both Au and Cu catalysts. Both ionic dissolution and degradation in the form of nanoparticle detachment can be detected and analyzed. The presence of nanoparticles is indicated by spikes in ICP-MS data. The intensity of the spikes is directly related to particle size. We used ICP-MS to determine particle mass, size distribution, and cumulative mass loss over time. We found the use of ICP-MS to obtain particle size distribution gave comparable results to transmission electron microscopy (TEM) determination of particle size distribution.Au foil as the CO2 reduction catalyst was used as a model system for detecting and quantifying degradation in situ using ICP-MS. We found Au degradation to occur in the form of nanoparticle detachment, with increasingly negative applied potential (0 V vs RHE to -1 V vs. RHE) in the presence of CO2 leading to increased number of nanoparticles in the electrolyte; however, no ionic dissolution was observed. In comparison, when the electrolyte was saturated with N2, nanoparticles detached from the electrode at a lower rate than in CO2-saturated conditions. We also examined Cu degradation under the same conditions as the Au system. Cu degradation occurs as both ionic dissolution and nanoparticle detachment, but under all conditions, Cu has less nanoparticle detachment and cumulative mass loss due to nanoparticles than Au. The developed experimental framework in this study would be translatable to a variety of electrocatalytic reactions and environments. Examination of catalyst degradation behavior in situ, including non-traditional degradation mechanisms such as nanoparticle detachment from bulk materials, can be used to obtain greater fundamental understanding of degradation mechanisms and rational design of materials with improved stability.

Leveraging Advanced Analytical Chemistry Techniques to Probe Thermo-Electrochemical Aging Effects in Lithium-Ion Battery Electrolytes

As lithium-ion and other battery chemistries gain market traction for grid and industrial-scale applications, pressure is mounting to develop more robust, longer lasting cells that can operate for hundreds of cycles at variable temperatures without sacrificing performance or safety. Electrolyte design is crucial to this effort and requires deep understanding of the correlated physical, chemical, and electrochemical factors that dictate long-term electrolyte performance. In this presentation, I will discuss the value of combined analytical chemistry techniques (solid- and liquid- state NMR, GCMS, and ICPMS) to resolve molecular-level impacts of thermally- and electrochemically- induced aging of lithium-ion electrolytes. In a model electrolyte, High Resolution (HR)-GCMS enables identification of subtle changes in solvent and additive chemistry while NMR reveals the formation of lithium-salt breakdown products. These findings are instructive for battery cycling as demonstrated by full chemical analysis of electrolyte extracted from aged lithium-ion cells, including evolved gas analysis, electrolyte deformulation, and SEI characterization. These cutting-edge analytical chemistry techniques are powerful and underutilized tools for detecting and mitigating failure modes in liquid electrolytes.

A Guide to Chemical Considerations for the Pre-Clinical Development of Oligonucleotides.

Oligonucleotide therapeutics, a pioneering category of modern medicinal drugs, are at the forefront of utilizing innate mechanisms to modulate gene expression. With 18 oligonucleotide-based FDA-approved medicines currently available for treating various clinical conditions, this field showcases an innovative potential yet to be fully explored. Factors such as purity, formulation, and endotoxin levels profoundly influence the efficacy and safety of these therapeutics. Therefore, a thorough understanding of the chemical factors essential for producing high-quality oligonucleotides for preclinical studies is crucial in their development for further clinical application. This paper serves as a concise guide to these chemical considerations, aiming to inspire and equip researchers with the necessary knowledge to advance in this exciting and innovative field.

An In Silico-Guided Approach for Assessing Herb-Drug Interaction Potential: A Case Study with Cudrania tricuspidata Leaf Extracts.

Cudrania tricuspidata leaf extracts have long been utilized as traditional oriental medicines across Asian countries like Korea, China, and Japan. These extracts are renowned for their therapeutic benefits in addressing inflammation, tumors, obesity, and diabetes, maintaining their status as a pivotal folk remedy. Given the rising trend of combining medicinal herbs with conventional medications, it is imperative to explore the potential herb-drug interactions. However, there is a dearth of research on evaluating the herb-drug interactions of C. tricuspidata leaf extracts. Also, the intricate chemical composition of medicinal herbs presents methodological hurdles in establishing causal relationships between their constituents and herb-drug interactions. To overcome these challenges, a combined in silico and in vitro workflow was developed and effectively applied to evaluate the potential herb-drug interaction of C. tricuspidata leaf extracts along with the associated chemical factors. In in vitro CYP inhibition assays, C. tricuspidata leaf extracts exhibited potent inhibition of CYP1A2 and CYP2C8, with quercetin, kaempferol, and their glycosides identified as the major constituents. In silico analysis based on the prediction tools (ADMETlab 2.0 and pkCSM) identified key contributors to CYP inhibition, quercetin and kaempferol. Additionally, molecular docking analysis validated the binding of ligands (quercetin and kaempferol) to proteins (CYP1A2 and CYP2C8). These findings suggest that C. tricuspidata leaf extracts could inhibit CYP1A2 and CYP2C8, aiding in understanding the herb-drug interaction potential of C. tricuspidata leaf extracts for safe clinical application. Furthermore, this approach can be broadly applied to study herb-drug interactions of various medicinal herbs, enhancing their therapeutic benefits and reducing adverse reactions by considering chemical profiles relevant to herb-drug interaction potential in herbal preparations.

Biological Pollution of Indoor Air, Its Assessment and Control Methods

The aim of the entry was to write a substantial contribution that analyses and compares the biological pollution of indoor air, the possibilities of its assessment and the control methods. In addition, the aim of our entry was to review journals covering both commercial and residential buildings. By analysing the above topics from the existing articles, one can have the impression that air pollution is one of the most important problems that need to be solved in the modern world. Adequate air quality is important for maintaining human health, affects the health of ecosystems, including animals, and determines crop production. With the development of civilisation, the quality of air in the atmosphere and indoors is constantly deteriorating. Indoor air pollution can be divided into physical (e.g., noise, inadequate lighting, ionising radiation), chemical (e.g., tobacco smoke, household products) and microbiological (bacteria, viruses, fungi and products of their metabolism) factors. Each of these factors can have a negative impact on a person’s health or cause premature death. The entry deals with indoor air pollution, focussing on biological pollutants. It compares different methods available and describes the method of sampling to analyse indoor air pollution and ways to reduce it.

A model for inversion of hyperspectral characteristics of phosphate content in mural plaster based on fractional-order differential algorithm

The Dunhuang murals, a significant part of Chinese heritage, have suffered deterioration primarily due to environmental and chemical factors, notably salt damage. This study proposes a sophisticated method that synergizes Fractional Order Differentiation (FOD) and Partial Least Squares Regression (PLSR) to accurately invert the phosphate content in the mural plaster of the Dunhuang paintings. The focal points of the research include: (1) To address the issue of information loss and reduced modeling precision caused by integer-order differentiation algorithms, the FOD method is employed for preprocessing spectral data. This approach ensures the fine spectral differences in the phosphate content of the mural plaster are precisely captured, (2) Utilizing PLSR, the study models the spectral bands identified at a significance level of 0.01 with measured conductivity values, thereby enabling the precise prediction of the phosphate content in the murals. The research outcomes reveal: (1) The FOD method can elucidate the nonlinear characteristics and variation patterns of the mural samples in the spectral data. As the order increases from zero to two, the number of spectral bands meeting the 0.01 significance test initially decreases and then increases. The highest absolute value of the positive correlation coefficient is observed at the 1.9 order, corresponding to the 2077 nm band, (2) For predicting the phosphate content in the murals, the model at the 1.9 order is most suitable for inversion. This model, after cross-validation, achieves a maximum R2 value of 0.861. This study created an efficient FOD-based model for estimating phosphate in mural plaster.

Exploring the Exposome Spectrum: Unveiling Endogenous and Exogenous Factors in Non-Communicable Chronic Diseases.

The exposome encompasses all endogenous and exogenous exposure individuals encounter throughout their lives, including biological, chemical, physical, psychological, relational, and socioeconomic factors. It examines the duration and intensity of these types of exposure and their complex interactions over time. This interdisciplinary approach involves various scientific disciplines, particularly toxicology, to understand the long-term effects of toxic exposure on health. Factors like air pollution, racial background, and socioeconomic status significantly contribute to diseases such as metabolic, cardiovascular, neurodegenerative diseases, infertility, and cancer. Advanced analytical methods measure contaminants in biofluids, food, air, water, and soil, but often overlook the cumulative risk of multiple chemicals. An exposome analysis necessitates sophisticated tools and methodologies to understand health interactions and integrate findings into precision medicine for better disease diagnosis and treatment. Chronic exposure to environmental and biological stimuli can lead to persistent low-grade inflammation, which is a key factor in chronic non-communicable diseases (NCDs), such as obesity, cardiometabolic disorders, cancer, respiratory diseases, autoimmune conditions, and depression. These NCDs are influenced by smoking, unhealthy diets, physical inactivity, and alcohol abuse, all shaped by genetic, environmental, and social factors. Dietary patterns, especially ultra-processed foods, can exacerbate inflammation and alter gut microbiota. This study investigates the exposome's role in the prevention, development, and progression of NCDs, focusing on endogenous and exogenous factors.

Chemically reactive and mixed convective hybrid nanofluid flow between two parallel rotating disks with Joule heating: A thermal computational study

An electrically conducting and magnetically influenced three-dimensional flow of modified nanofluid between two rotating disks is investigated in this study. Nanometer-size particles of two distinct materials (Al2O3, Ag) suspended in water in the hybrid nanofluid are considered. The Joule heating effects, mixed convection, chemical factor, and exponential heating are considered in this study. The physical problem under these assumptions is transformed into a system of equations. To convert partial differential equations (PDEs) into systems of ordinary differential equations (ODEs), the suitable similarity variables are introduced. The reduced system is numerically solved using bvp4c, a well-known higher-order algorithm. The effects of significant variables on the profiles of velocity, temperature, and concentration are depicted graphically. We have chosen the pertinent parameters in the specific intervals; [Formula: see text][Formula: see text][Formula: see text][Formula: see text][Formula: see text], [Formula: see text][Formula: see text][Formula: see text] and [Formula: see text]. The interactions between a number of significant factors, including skin friction and Nusselt and Sherwood numbers at the higher and lower disks, are shown in tables. The results demonstrate that the local skin fraction decreases as the mixed convection factor is increased, which physically increases the heat transmission rate between the two discs. Furthermore, as the magnetic field and radiation number rise, the rate of heat transfer at the lower and top discs decreases. The numerical results in the form of a table are compared with the available literature, and our results beat the previously published work. The results described here are desirable choices for thermal uses such as automotive cooling systems, solar thermal systems, engineering, medical areas, heat sinks, or current energy storage since they have demonstrated higher thermal characteristics and stability than simple nanofluids (NFs). In Table 6, a comparative numerical study is presented for the various of state variables with the available literature, where the present study is validated.

Physical interpretation of entropy, Boltzmann constant, and temperature

Through the previously reported the quantum-identity, the light-model, and the T(temperature)·\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\cdot$$\\end{document}S(entropy) energy, the implied meaning of temperature and entropy, respectively, which it was difficult to intuitively recognize, was clearly defined. In order to minimize possible errors at this time, the interrelationship of the SI base unit, which is the smallest unit, and the T(temperature)·\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\cdot$$\\end{document}S(entropy) unit integration was used. In the process of converting to Planck units, each unit (criterion) for entropy and temperature was calculated, and their physical and chemical meanings were compared and reinterpreted. Thus, the unit of entropy is related to the Boltzmann constant, and the temperature is the oscillation of pure mass units. Therefore, the intuitive recognition of physical and chemical factors based on the unit of meter(m)-time(s) is considered sufficient as an initiator to move closer to new science beyond the current limited application.

Advance in the Thermoinhibition of Lettuce (Lactuca sativa L.) Seed Germination.

Thermoinhibition refers to the inability of seeds to germinate when inhibited by high temperatures, but when environmental conditions return to normal, the seeds are able to germinate rapidly again, which is different from thermodormancy. Meanwhile, with global warming, the effect of the thermoinhibition phenomenon on the yield and quality of crops in agricultural production is becoming common. Lettuce, as a horticultural crop sensitive to high temperature, is particularly susceptible to the effects of thermoinhibition, resulting in yield reduction. Therefore, it is crucial to elucidate the intrinsic mechanism of action of thermoinhibition in lettuce seeds. This review mainly outlines several factors affecting thermoinhibition of lettuce seed germination, including endosperm hardening, alteration of endogenous or exogenous phytohormone concentrations, action of photosensitizing pigments, production and inhibition of metabolites, maternal effects, genetic expression, and other physical and chemical factors. Finally, we also discuss the challenges and potential of lettuce seed germination thermoinhibition research. The purpose of this study is to provide theoretical support for future research on lettuce seed germination thermoinhibition, and with the aim of revealing the mechanisms and effects behind lettuce seed thermoinhibition. This will enable the identification of more methods to alleviate seed thermoinhibition or the development of superior heat-tolerant lettuce seeds.

PH-induced changes in IgE molecules measured by atomic force microscopy.

The environment surrounding proteins is tightly linked to its dynamics, which can significantly influence the conformation of proteins. This study focused on the effect of pH conditions on the ultrastructure of Immunoglobulin E (IgE) molecules. Herein, the morphology, height, and area of IgE molecules incubated at different pH were imaged by atomic force microscopy (AFM), and the law of IgE changes induced by pH value was explored. The experiment results indicated that the morphology, height and area of IgE molecules are pH dependent and highly sensitive. In particular, IgE molecules were more likely to present small-sized ellipsoids under acidic conditions, while IgE molecules tend to aggregate into large-sized flower-like structures under alkaline conditions. In addition, it was found that the height of IgE first decreased and then increased with the increase of pH, while the area of IgE increased with the increase of pH. This work provides valuable information for further study of IgE, and the methodological approach used in this study is expected to developed into AFM to investigate the changes of IgE molecules mediated by other physical and chemical factors. RESEARCH HIGHLIGHTS: The ultrastructure of IgE molecules is pH dependent and highly sensitive. IgE molecules were tend to present small-sized ellipsoids under acidic pH. Alkaline pH drives IgE self-assembly into flower-like aggregates.

Cellular response to plasma-generated electrical and chemical stimulation of equal electricity

Plasma medicine is a novel field of research that has the potential in life sciences, including cancer treatment. It has been believed that all of these potential applications depend on the chemical factor of the plasma. However, the electrical factors that are produced simultaneously with the chemical factors have not been researched thoroughly. To assess the effect of plasma on the response of cells, a system that enables simultaneous comparison of the effects of chemical and electrical factors of plasma with equal electricity was invented. This system separates the polarity of plasma and isolates the chemical species from the electric stimulation. Using this system, HT-1080 cells were exposed to plasma for 10 min, 1 h, and 24 h. The 10 min plasma treatment showed a clear difference in the polarity of plasma, where cells under exposure to positive plasma died while cells in other conditions survived. An hour of plasma treatment affected the cells under the negative plasma, where the cell viability was reduced to half. Meanwhile, the electric stimulation did not affect the cell viability but did alter the cell membrane. Collectively, this study demonstrates the differential effects of three factors (electric factor, positive plasma, negative plasma) under the same condition: both the electrical and chemical effects of plasma-generated stimuli with equal amounts of electricity were successfully observed.

Research progress on formation mechanism of pearl

Pearls are deeply cherished for their rich color and gorgeous luster, and their quality directly affects their value. Currently, the evaluation of pearl quality is mainly based on four aspects: color, shape, size and smoothness. The quality of pearls is influenced by a variety of factors, categorized into internal factors, such as the structural composition of the nacreous layer and genetic factors of the mussels, and external factors, including the aquaculture environment. Existing research results indicates that genetic factors are the dominant factor controlling the pearl quality. However, the macromolecules such as metal ions, organic pigments and various physical and chemical factors in the aquaculture water environment will also significantly impact pearl quality. Among these, matrix proteins are organic macromolecules found in the nacreous layer that play an important role in pearl quality. They participate in the deposition of calcium carbonate and the construction of the organic framework, affecting the pearls’ size and shape. The color of pearls is influenced by the deposition of metal ions, the transport of organic pigments and the regulation of microstructure.

Environmental and chemical determinants of contamination and survival of Vibrio cholerae in water sources in Bukavu in the Democratic Republic of the Congo

Introduction: Cholera is endemo-epidemic in Bukavu. The aim of the study was to assess the environmental determinants of permanent contamination of spring and well water and to evaluate some of the chemical factors responsible for the persistence of Vibrio cholerae in water consumed by cholera patients.Methods: Conducted in the Bukavu health district from September 2020 to September 2021, this was a cross-sectional. The potential of hydrogen (pH) of the water was evaluated before comparing it with the survival of Vibrio cholerae. A total of 641 latrines, 92 water sources, and wells were surveyed, with 298 samples analyzed in the laboratory.Results: Out of the 641 latrines surveyed, 367 (57%) were found to be unsanitary; 54 (59%) of the water sources and wells were also deemed unsanitary. In total, 57% of the water samples were found to contain Vibrio cholerae, with 90% exhibiting an alkaline pH, of which 54% tested positive for the bacteria. Conversely, 10% of the samples had an acidic pH, with 80% of those containing Vibrio cholerae. The pH levels of the water remained alkaline both during the epidemic (95%) and post-epidemic (84%), thereby favoring the survival of Vibrio cholerae serotypes Ogawa and Inaba in these water sources. An acidic pH was observed to increase the likelihood of Vibrio cholerae survival in these waters by a factor of 3.39.Conclusion: Spring and well water are consistently contaminated with Vibrio cholerae due to the unsanitary conditions of nearby latrines. The presence of Vibrio cholerae serotypes Inaba and Ogawa in these water sources is further influenced by the alkaline and acidic pH levels.

A new thermodynamic model for predicting the 3-D phase equilibrium surface of gas hydrates considering the effect of salt concentration

An accurate understanding of the thermodynamic stability of gas hydrates in salt-bearing systems is of great significance for predicting the extent of hydrate accumulation and determining the hydrate decomposition domain. Therefore, this study proposes a thermodynamic model for predicting the temperature–pressure-salt concentration three-dimensional phase-equilibrium surface. The model considered the interaction of the electrolyte in a mixed salt solution system and non-spherical shaped hydrate crystal cavity. The modified van der Waals-Platteeuw (vdW-P) model and Benedict-Webb-Rubin-Starling (BWRS) equation of state were used to describe the hydrate phase. The Pitzer-Debye-Hückel equation and nonelectrolyte non random two liquid non random factor (N-NRTL-NRF) activity coefficient model were used to describe the fluid phase. The prediction results of the model agreed with the experimental data, and the absolute average relative deviation in temperature (AARD-T) under pure water conditions was only 0.08, and the AARD-T under electrolyte conditions did not exceed 0.15, which proved the accuracy and reliability of the model. The calculation results showed that when the mole fraction of chloride salt was greater than 0.02 and the pressure was higher than 20 MPa, chemical factors caused the p-T curves to translate. When the pressure was low, the temperature gradient along the direction of the salt concentration changed drastically, and the p-T curves no longer had translation characteristics. In comparison, under the same mole fraction, AlCl3 had a stronger inhibitory effect on the CH4 hydrate than the other chloride salts. The lnp-X-1/T three-dimensional surface of the CH4 hydrate exhibited good Clausius-Clapeyron linear behavior locally, and the surface had certain nonlinear characteristics. The degree of nonlinearity of the lnp-X-1/T three-dimensional surfaces of different types of chloride salts was different. A better inhibitory effect of the chloride salt electrolyte on the CH4 hydrate was associated with stronger nonlinearity between 1/T and lnp.

A Saturation Artifacts Inpainting Method Based on Two-Stage GAN for Fluorescence Microscope Images.

Fluorescence microscopic images of cells contain a large number of morphological features that are used as an unbiased source of quantitative information about cell status, through which researchers can extract quantitative information about cells and study the biological phenomena of cells through statistical and analytical analysis. As an important research object of phenotypic analysis, images have a great influence on the research results. Saturation artifacts present in the image result in a loss of grayscale information that does not reveal the true value of fluorescence intensity. From the perspective of data post-processing, we propose a two-stage cell image recovery model based on a generative adversarial network to solve the problem of phenotypic feature loss caused by saturation artifacts. The model is capable of restoring large areas of missing phenotypic features. In the experiment, we adopt the strategy of progressive restoration to improve the robustness of the training effect and add the contextual attention structure to enhance the stability of the restoration effect. We hope to use deep learning methods to mitigate the effects of saturation artifacts to reveal how chemical, genetic, and environmental factors affect cell state, providing an effective tool for studying the field of biological variability and improving image quality in analysis.

Priorities of ensuring hygiene and occupational safety of medical personnel and the resilience of healthcare facilities in emergency situations

Aim. To evaluate the influence of biological and socio-political emergencies on the safety of healthcare staff members. Materials and methods. The study used bibliosemantic, statistical, and mathematical methods, analyzing official statistical data on the healthcare system state in Ukraine. Results. While performing their functions in healthcare facilities, medical workers are exposed to the risk of negative effects from biological, psychophysiological, chemical, physical, and social harmful and hazardous factors. Adverse occupational factors in hospital environments exert a complex, combined, or concurrent effect, and its impact intensity can be enormously increased in various types of emergency situations. During the COVID-19 pandemic, a steep increase in occupational injuries in the national healthcare (in fact, by 30 times) has been documented, including due to the registration of acute infectious diseases among medical personnel at the workplace. Similar trends are also evidenced in indicators of lethal injuries, professional and occupationally induced morbidity. Furthermore, Ukraine has faced overlapping emergency situations of socio-political terms, caused by the full-scale aggression of the Russian Federation, and medical-biological problems caused by the COVID-19 pandemic, significantly complicating the state of affairs. According to official data, only in the first year of the full-scale invasion of Ukraine, about 1500 healthcare facilities were damaged, 106 medical workers died, including 33 at their workplace. Conclusions. The resilience of healthcare facilities to various types of emergency situations is an extremely important component of ensuring the hospital environment safety and, as practice shows, requires improvement. There is an urgent need to develop clear response algorithms for healthcare facilities to cope with emergency situations that could influence them. Reinforcing a safety culture in the national medical sector could become the goal and foundation for future strategies to create a safe hospital environment by improving and enhancing the safety culture.