Reactive capture and electrochemical conversion of CO2 with ionic liquids and deep eutectic solvents.

Ionic liquids (ILs) and deep eutectic solvents (DESs) have tremendous potential for reactive capture and conversion (RCC) of CO2 due to their wide electrochemical stability window, low volatility, and high CO2 solubility. There is environmental and economic interest in the direct utilization of the captured CO2 using electrified and modular processes that forgo the thermal- or pressure-swing regeneration steps to concentrate CO2, eliminating the need to compress, transport, or store the gas. The conventional electrochemical conversion of CO2 with aqueous electrolytes presents limited CO2 solubility and high energy requirement to achieve industrially relevant products. Additionally, aqueous systems have competitive hydrogen evolution. In the past decade, there has been significant progress toward the design of ILs and DESs, and their composites to separate CO2 from dilute streams. In parallel, but not necessarily in synergy, there have been studies focused on a few select ILs and DESs for electrochemical reduction of CO2, often diluting them with aqueous or non-aqueous solvents. The resulting electrode-electrolyte interfaces present a complex speciation for RCC. In this review, we describe how the ILs and DESs are tuned for RCC and specifically address the CO2 chemisorption and electroreduction mechanisms. Critical bulk and interfacial properties of ILs and DESs are discussed in the context of RCC, and the potential of these electrolytes are presented through a techno-economic evaluation.

Promoting longevity in aged liver through NLRP3 inflammasome inhibition using tauroursodeoxycholic acid (TUDCA) and SCD probiotics.

This investigation explores the combined influence of SCD Probiotics and tauroursodeoxycholic acid (TUDCA) on liver health in elderly male Sprague-Dawley rats. Through the administration of intravenous TUDCA (300 mg/kg) and oral SCD Probiotics (3 mL at 1 × 10^8 CFU) daily for one week, this study evaluates the biomolecular composition, histopathological alterations, and inflammasome activity in the liver. Analytical methods encompassed ATR-FTIR spectroscopy integrated with machine learning for the assessment of biomolecular structures, RT-qPCR for quantifying inflammasome markers (NLRP3, ASC, Caspase-1, IL18, IL1ß), and histological examinations to assess liver pathology. The findings reveal that TUDCA prominently enhanced lipid metabolism by reducing cholesterol esters, while SCD Probiotics modulated both lipid and protein profiles, notably affecting fatty acid chain lengths and protein configurations. Histological analysis showed significant reductions in cellular degeneration, lymphatic infiltration, and hepatic fibrosis. Furthermore, the study noted a decrease in the immunoreactivity for NLRP3 and ASC, suggesting suppressed inflammasome activity. While SCD Probiotics reduced the expression of certain inflammasome-related genes, they also paradoxically increased AST and LDH levels. Conversely, an exclusive elevation in albumin levels was observed in the group treated with SCD Probiotics, implying a protective role against liver damage. These results underscore the therapeutic potential of TUDCA and SCD Probiotics for managing age-associated liver disorders, illustrating their individual and synergistic effects on liver health and pathology. This study provides insights into the complex interactions of these agents, advocating for customized therapeutic approaches to combat liver fibrosis, enhance liver functionality, and decrease inflammation in aging populations.

Rapid and Accurate Screening of the COF Space for Natural Gas Purification: COFInformatics.

In this work, we introduced COFInformatics, a computational approach merging molecular simulations and machine learning (ML) algorithms, to evaluate all synthesized and hypothetical covalent organic frameworks (COFs) for the CO2/CH4 mixture separation under four different adsorption-based processes: pressure swing adsorption (PSA), vacuum swing adsorption (VSA), temperature swing adsorption (TSA), and pressure-temperature swing adsorption (PTSA). We first extracted structural, chemical, energy-based, and graph-based molecular fingerprint features of every single COF structure in the very large COF space, consisting of nearly 70,000 materials, and then performed grand canonical Monte Carlo simulations to calculate the CO2/CH4 mixture adsorption properties of 7540 COFs. These features and simulation results were used to develop ML models that accurately and rapidly predict CO2/CH4 mixture adsorption and separation properties of all 68,614 COFs. The most efficient separation process and the best adsorbent candidates among the entire COF spectrum were identified and analyzed in detail to reveal the most important molecular features that lead to high-performance adsorbents. Our results showed that (i) many hypoCOFs outperform synthesized COFs by achieving higher CO2/CH4 selectivities; (ii) the top COF adsorbents consist of narrow pores and linkers comprising aromatic, triazine, and halogen groups; and (iii) PTSA is the most efficient process to use COF adsorbents for natural gas purification. We believe that COFInformatics promises to expedite the evaluation of COF adsorbents for CO2/CH4 separation, thereby circumventing the extensive, time- and resource-intensive molecular simulations.

Supplementing probiotics during intermittent fasting proves more effective in restoring ileum and colon tissues in aged rats.

This study aimed to explore the impact of SCD Probiotics supplementation on biomolecule profiles and histopathology of ileum and colon tissues during a 30-day intermittent fasting (IF) program. Male Sprague-Dawley rats, aged 24 months, underwent 18-h daily fasting and received 3 mL (1 × 108 CFU) of SCD Probiotics. The differences in biomolecule profiles were determined using FTIR Spectroscopy and two machine learning techniques, Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), which showed significant differences with high accuracy rates. Spectrochemical bands indicating alterations in lipid, protein and nucleic acid profiles in both tissues. The most notable changes were observed in the group subjected to both IF and SCD Probiotics, particularly in the colon. Both interventions, individually and in combination, decreased protein carbonylation levels. SCD Probiotics exerted a more substantial impact on membrane dynamics than IF alone. Additionally, both IF and SCD Probiotics were found to have protective effects on intestinal structure and stability by reducing mast cell density and levels of TNF-α and NF-κB expression in ileum and colon tissues, thus potentially mitigating age-related intestinal damage and inflammation. Furthermore, our results illustrated that while IF and SCD Probiotics individually instigate unique changes in ileum and colon tissues, their combined application yielded more substantial benefits. This study provides evidence for the synergistic potential of IF and SCD Probiotics in combating age-related intestinal alterations.

High-throughput computational screening of MOF adsorbents for efficient propane capture from air and natural gas mixtures.

In this study, we used a high-throughput computational screening approach to examine the potential of metal-organic frameworks (MOFs) for capturing propane (C3H8) from different gas mixtures. We focused on Quantum MOF (QMOF) database composed of both synthesized and hypothetical MOFs and performed Grand Canonical Monte Carlo (GCMC) simulations to compute C3H8/N2/O2/Ar and C3H8/C2H6/CH4 mixture adsorption properties of MOFs. The separation of C3H8 from air mixture and the simultaneous separation of C3H8 and C2H6 from CH4 were studied for six different adsorption-based processes at various temperatures and pressures, including vacuum-swing adsorption (VSA), pressure-swing adsorption (PSA), vacuum-temperature swing adsorption (VTSA), and pressure-temperature swing adsorption (PTSA). The results of molecular simulations were used to evaluate the MOF adsorbents and the type of separation processes based on selectivity, working capacity, adsorbent performance score, and regenerability. Our results showed that VTSA is the most effective process since many MOFs offer high regenerability (>90%) combined with high C3H8 selectivity (>7 × 103) and high C2H6 + C3H8 selectivity (>100) for C3H8 capture from air and natural gas mixtures, respectively. Analysis of the top MOFs revealed that materials with narrow pores (<10 Å) and low porosities (<0.7), having aromatic ring linkers, alumina or zinc metal nodes, typically exhibit a superior C3H8 separation performance. The top MOFs were shown to outperform commercial zeolite, MFI for C3H8 capture from air, and several well-known MOFs for C3H8 capture from natural gas stream. These results will direct the experimental efforts to the most efficient C3H8 capture processes by providing key molecular insights into selecting the most useful adsorbents.

Accelerated Discovery of Metal-Organic Frameworks for CO2 Capture by Artificial Intelligence.

The existence of a very large number of porous materials is a great opportunity to develop innovative technologies for carbon dioxide (CO2) capture to address the climate change problem. On the other hand, identifying the most promising adsorbent and membrane candidates using iterative experimental testing and brute-force computer simulations is very challenging due to the enormous number and variety of porous materials. Artificial intelligence (AI) has recently been integrated into molecular modeling of porous materials, specifically metal-organic frameworks (MOFs), to accelerate the design and discovery of high-performing adsorbents and membranes for CO2 adsorption and separation. In this perspective, we highlight the pioneering works in which AI, molecular simulations, and experiments have been combined to produce exceptional MOFs and MOF-based composites that outperform traditional porous materials in CO2 capture. We outline the future directions by discussing the current opportunities and challenges in the field of harnessing experiments, theory, and AI for accelerated discovery of porous materials for CO2 capture.

Reduced liver damage and fibrosis with combined SCD Probiotics and intermittent fasting in aged rat.

This study aimed to examine the impact of SCD Probiotics supplementation on liver biomolecule content and histological changes during a 30-day intermittent fasting (IF) program in 24-month-old male Sprague-Dawley rats. Rats underwent 18-h daily fasting and received 1 × 108 CFU of SCD Probiotics daily. Liver tissue biomolecules were analysed using FTIR Spectroscopy, LDA, and SVM techniques, while histopathological evaluations used Haematoxylin and eosin and Masson trichrome-stained tissues. Blood samples were collected for biochemical analysis. Gross alterations in the quantity of biomolecules were observed with individual or combined treatments. LDA and SVM analyses demonstrated a high accuracy in differentiating control and treated groups. The combination treatments led to the most significant reduction in cholesterol ester (1740 cm-1 ) and improved protein phosphorylation (A1239 /A2955 and A1080 /A1545 ) and carbonylation (A1740 /A1545 ). Individually, IF and SCD Probiotics were more effective in enhancing membrane dynamics (Bw2922 /Bw2955 ). In treated groups, histological evaluations showed decreased hepatocyte degeneration, lymphocyticinfiltration, steatosis and fibrosis. Serum ALP, LDH and albumin levels significantly increased in the SCD Probiotics and combined treatment groups. This study offers valuable insights into the potential mechanisms behind the beneficial effects of IF and SCD Probiotics on liver biomolecule content, contributing to the development of personalized nutrition and health strategies.

Evaluating CH4/N2 Separation Performances of Hundreds of Thousands of Real and Hypothetical MOFs by Harnessing Molecular Modeling and Machine Learning.

Considering the large abundance and diversity of metal-organic frameworks (MOFs), evaluating the gas adsorption and separation performance of the entire MOF material space using solely experimental techniques or brute-force computer simulations is impractical. In this study, we integrated high-throughput molecular simulations with machine learning (ML) to explore the potential of both synthesized, the real MOFs, and computer-generated, the hypothetical MOFs (hypoMOFs), for adsorption-based CH4/N2 separation. CH4/N2 mixture adsorption data obtained from molecular simulations were used to train the ML models that could accurately predict gas uptakes of 4612 real MOFs. These models were then transferred to two distinct databases consisting of 98 601 hypoMOFs and 587 anion-pillared hypoMOFs to examine their CH4/N2 mixture separation performances using various adsorbent evaluation metrics. The top adsorbents were identified for vacuum swing adsorption (VSA) and pressure swing adsorption (PSA) conditions and examined in detail to gain molecular insights into their structural and chemical properties. Results revealed that the hypoMOFs offered high CH4 selectivities, up to 14.8 and 13.6, and high working capacities, up to 3.1 and 5.8 mol/kg, at VSA and PSA conditions, respectively, and many of the hypoMOFs could outperform the real MOFs. Our approach offers a rapid and accurate assessment of the mixture adsorption and separation properties of MOFs without the need for computationally demanding simulations. Our results for the best adsorbents will be useful in accelerating the experimental efforts for the design of novel MOFs that can achieve high-performance CH4/N2 separation.

Hierarchical Computational Screening of Quantum Metal-Organic Framework Database to Identify Metal-Organic Frameworks for Volatile Organic-Compound Capture from Air.

The design and discovery of novel porous materials that can efficiently capture volatile organic compounds (VOCs) from air are critical to address one of the most important challenges of our world, air pollution. In this work, we studied a recently introduced metal-organic framework (MOF) database, namely, quantum MOF (QMOF) database, to unlock the potential of both experimentally synthesized and hypothetically generated structures for adsorption-based n-butane (C4H10) capture from air. Configurational Bias Monte Carlo (CBMC) simulations were used to study the adsorption of a quaternary gas mixture of N2, O2, Ar, and C4H10 in QMOFs for two different processes, pressure swing adsorption (PSA) and vacuum-swing adsorption (VSA). Several adsorbent performance evaluation metrics, such as C4H10 selectivity, working capacity, the adsorbent performance score, and percent regenerability, were used to identify the best adsorbent candidates, which were then further studied by molecular simulations for C4H10 capture from a more realistic seven-component air mixture consisting of N2, O2, Ar, C4H10, C3H8, C3H6, and C2H6. Results showed that the top five QMOFs have C4H10 selectivities between 6.3 × 103 and 9 × 103 (3.8 × 103 and 5 × 103) at 1 bar (10 bar). Detailed analysis of the structure-performance relations showed that low/mediocre porosity (0.4-0.6) and narrow pore sizes (6-9 Å) of QMOFs lead to high C4H10 selectivities. Radial distribution function analyses of the top materials revealed that C4H10 molecules tend to confine close to the organic parts of MOFs. Our results provided the first information in the literature about the VOC capture potential of a large variety and number of MOFs, which will be useful to direct the experimental efforts to the most promising adsorbent materials for C4H10 capture from air.

SCD Probiotics mitigate cafeteria diet-induced liver damage in Wistar rats during development.

BACKGROUND AND AIM: The liver plays a critical role in metabolic homeostasis, and its health is often compromised by poor dietary habits. This study aimed to investigate the therapeutic potential of SCD Probiotics in mitigating adverse liver effects induced by a cafeteria diet in male Wistar rats during their developmental period. METHODS: Four groups of seven male Wistar rats each were subjected to different dietary regimens from day 21 (weaning) to day 56. The groups were as follows: a control group on normal feed; a probiotic-supplemented group on normal feed; a group on a cafeteria diet mixed with normal feed; and a group on a cafeteria diet mixed with normal feed, supplemented with SCD Probiotics. Liver health was assessed using Fourier transform infrared spectroscopy and histopathological evaluations. RESULTS: Rats on the cafeteria diet exhibited significant disruptions in lipid, protein, cholesterol, triglyceride levels, and glycogen/phosphate content. Histopathological abnormalities such as lymphocytic infiltration, steatosis, and necrosis were also observed. However, SCD Probiotics supplementation led to notable improvements in the liver's biomolecular composition and mitigated histopathological abnormalities. Serum liver enzyme levels (AST, ALT, ALP, and LDH) also showed beneficial effects, while serum albumin levels remained stable. CONCLUSIONS: SCD Probiotics demonstrated a promising potential to counteract the adverse liver effects induced by a cafeteria diet in male Wistar rats. The study revealed significant improvements in biomolecular composition, histopathology, and serum enzyme levels. However, these findings are preliminary and necessitate further in vivo studies and clinical trials for validation.

The rejuvenating influence of young plasma on aged intestine.

This study aims to investigate the effects of plasma exchange on the biomolecular profiles and histology of ileum and colon tissues in young and aged Sprague-Dawley male rats. Fourier transform infrared (FTIR) spectroscopy, linear discriminant analysis and support vector machine (SVM) techniques were employed to analyse the lipid, protein, and nucleic acid indices in young and aged rats. Following the application of young plasma, aged rats demonstrated biomolecular profiles similar to those of their younger counterparts. Histopathological and immunohistochemical assessments showed that young plasma had a protective effect on the intestinal tissues of aged rats, increasing cell density and reducing inflammation. Additionally, the expression levels of key inflammatory mediators tumour necrosis factor-alpha and cyclooxygenase-2 significantly decreased after young plasma administration. These findings underscore the therapeutic potential of young plasma for mitigating age-related changes and inflammation in the intestinal tract. They highlight the critical role of plasma composition in the ageing process and suggest the need for further research to explore how different regions of the intestines respond to plasma exchange. Such understanding could facilitate the development of innovative therapies targeting the gastrointestinal system, enhancing overall health during ageing.

Advancing CH4/H2 separation with covalent organic frameworks by combining molecular simulations and machine learning.

A high-throughput computational screening approach combined with machine learning (ML) was introduced to unlock the potential of both synthesized and hypothetical COFs (hypoCOFs) for adsorption-based CH4/H2 separation. We studied 597 synthesized COFs for adsorption of a CH4/H2 mixture using Grand Canonical Monte Carlo (GCMC) simulations under pressure-swing adsorption (PSA) and vacuum-swing adsorption (VSA) conditions. Based on the simulation results, the CH4/H2 selectivities, CH4 working capacities, adsorbent performance scores, and regenerabilities of the synthesized COFs were assessed and the structural properties of the top-performing COFs were identified. The hypoCOF database composed of 69 840 materials was then filtered to identify 7737 hypothetical materials having similar structural properties to the top synthesized COFs. These hypothetical COFs were then examined for CH4/H2 separation using molecular simulations and the results showed that the top hypoCOFs have CH4 selectivities and working capacities in the ranges of 21.9-28.7 (64.7-128.6) and 5.8-7.6 (1.3-3.1) mol kg-1 under PSA (VSA) conditions, respectively, outperforming the synthesized COFs and metal-organic frameworks (MOFs). ML models were then developed based on the hypoCOF simulation results to accurately predict the CH4/H2 mixture adsorption properties of all remaining hypothetical materials when their structural and chemical properties are fed into the models. These models accurately assessed the CH4/H2 mixture separation performances of any hypoCOF within seconds without performing computationally demanding molecular simulations. The computational approach that we have proposed in this study will provide an accurate and efficient assessment of COF materials for CH4/H2 separation and significantly accelerate the experimental efforts towards the design and discovery of new high-performing COF adsorbents.

Composite of MIL-101(Cr) with a Pyrrolidinium-Based Ionic Liquid Providing High CO2 Selectivity.

Capturing CO2 selectively from flue gas and natural gas addresses the criteria of a sustainable society. In this work, we incorporated an ionic liquid (IL) (1-methyl-1-propyl pyrrolidinium dicyanamide, [MPPyr][DCA]) into a metal organic framework (MOF), MIL-101(Cr), by wet impregnation and characterized the resulting [MPPyr][DCA]/MIL-101(Cr) composite in deep detail to identify the interactions between [MPPyr][DCA] molecules and MIL-101(Cr). Consequences of these interactions on the CO2/N2, CO2/CH4, and CH4/N2 separation performance of the composite were examined by volumetric gas adsorption measurements complemented by the density functional theory (DFT) calculations. Results showed that the composite offers remarkably high CO2/N2 and CH4/N2 selectivities of 19,180 and 1915 at 0.1 bar and 15 °C corresponding to 1144- and 510-times improvements, respectively, as compared to the corresponding selectivities of pristine MIL-101(Cr). At low pressures, these selectivities reached practically infinity, making the composite completely CO2-selective over CH4 and N2. The CO2/CH4 selectivity was improved from 4.6 to 11.7 at 15 °C and 0.001 bar, yielding a 2.5-times improvement, attributed to the high affinity of [MPPyr][DCA] toward CO2, validated by the DFT calculations. These results offer broad opportunities for the design of composites where ILs are incorporated into the pores of MOFs for high performance gas separation applications to address the environmental challenges.

Age-related differences in response to plasma exchange in male rat liver tissues: insights from histopathological and machine-learning assisted spectrochemical analyses.

This study aimed to examine the biological effects of blood plasma exchange in liver tissues of aged and young rats using machine learning methods and spectrochemical and histopathological approaches. Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) were the machine learning algorithms employed. Young plasma was given to old male rats (24 months), while old plasma was given to young male rats (5 weeks) for thirty days. LDA (95.83-100%) and SVM (87.5-91.67%) detected significant qualitative changes in liver biomolecules. In old rats, young plasma infusion increased the length of fatty acids, triglyceride, lipid carbonyl, and glycogen levels. Nucleic acid concentration, phosphorylation, and carbonylation rates of proteins were also increased, whereas a decrease in protein concentration was measured. Aged plasma decreased protein carbonylation, triglyceride, and lipid carbonyl levels. Young plasma infusion improved hepatic fibrosis and cellular degeneration and reduced hepatic microvesicular steatosis in aged rats. Otherwise, old plasma infusion in young rats caused disrupted cellular organization, steatosis, and increased fibrosis. Young plasma administration increased liver glycogen accumulation and serum albumin levels. Aged plasma infusion raised serum ALT levels while diminished ALP concentrations in young rats, suggesting possible liver dysfunction. Young plasma increased serum albumin levels in old rats. The study concluded that young plasma infusion might be associated with declined liver damage and fibrosis in aged rats, while aged plasma infusion negatively impacted liver health in young rats. These results imply that young blood plasma holds potential as a rejuvenation therapy for liver health and function.

Integrating Molecular Simulations with Machine Learning Guides in the Design and Synthesis of [BMIM][BF4]/MOF Composites for CO2/N2 Separation.

Considering the existence of a large number and variety of metal-organic frameworks (MOFs) and ionic liquids (ILs), assessing the gas separation potential of all possible IL/MOF composites by purely experimental methods is not practical. In this work, we combined molecular simulations and machine learning (ML) algorithms to computationally design an IL/MOF composite. Molecular simulations were first performed to screen approximately 1000 different composites of 1-n-butyl-3-methylimidazolium tetrafluoroborate ([BMIM][BF4]) with a large variety of MOFs for CO2 and N2 adsorption. The results of simulations were used to develop ML models that can accurately predict the adsorption and separation performances of [BMIM][BF4]/MOF composites. The most important features that affect the CO2/N2 selectivity of composites were extracted from ML and utilized to computationally generate an IL/MOF composite, [BMIM][BF4]/UiO-66, which was not present in the original material data set. This composite was finally synthesized, characterized, and tested for CO2/N2 separation. Experimentally measured CO2/N2 selectivity of the [BMIM][BF4]/UiO-66 composite matched well with the selectivity predicted by the ML model, and it was found to be comparable, if not higher than that of all previously synthesized [BMIM][BF4]/MOF composites reported in the literature. Our proposed approach of combining molecular simulations with ML models will be highly useful to accurately predict the CO2/N2 separation performances of any [BMIM][BF4]/MOF composite within seconds compared to the extensive time and effort requirements of purely experimental methods.

Prediction of gestational diabetes using deep learning and Bayesian optimization and traditional machine learning techniques.

The study aimed to develop a clinical diagnosis system to identify patients in the GD risk group and reduce unnecessary oral glucose tolerance test (OGTT) applications for pregnant women who are not in the GD risk group using deep learning algorithms. With this aim, a prospective study was designed and the data was taken from 489 patients between the years 2019 and 2021, and informed consent was obtained. The clinical decision support system for the diagnosis of GD was developed using the generated dataset with deep learning algorithms and Bayesian optimization. As a result, a novel successful decision support model was developed using RNN-LSTM with Bayesian optimization that gave 95% sensitivity and 99% specificity on the dataset for the diagnosis of patients in the GD risk group by obtaining 98% AUC (95% CI (0.95-1.00) and p < 0.001). Thus, with the clinical diagnosis system developed to assist physicians, it is planned to save both cost and time, and reduce possible adverse effects by preventing unnecessary OGTT for patients who are not in the GD risk group.

Computational Investigation of Dual Filler-Incorporated Polymer Membranes for Efficient CO2 and H2 Separation: MOF/COF/Polymer Mixed Matrix Membranes.

Mixed matrix membranes (MMMs) composed of two different fillers such as metal-organic frameworks (MOFs) and covalent-organic frameworks (COFs) embedded into polymers provide enhanced gas separation performance. Since it is not possible to experimentally consider all possible combinations of MOFs, COFs, and polymers, developing computational methods is urgent to identify the best performing MOF-COF pairs to be used as dual fillers in polymer membranes for target gas separations. With this motivation, we combined molecular simulations of gas adsorption and diffusion in MOFs and COFs with theoretical permeation models to calculate H2, N2, CH4, and CO2 permeabilities of almost a million types of MOF/COF/polymer MMMs. We focused on COF/polymer MMMs located below the upper bound due to their low gas selectivity for five industrially important gas separations, CO2/N2, CO2/CH4, H2/N2, H2/CH4, and H2/CO2. We further investigated whether these MMMs could exceed the upper bound when a second type of filler, a MOF, was introduced into the polymer. Many MOF/COF/polymer MMMs were found to exceed the upper bounds showing the promise of using two different fillers in polymers. Results showed that for polymers having a relatively high gas permeability (≥104 barrer) but low selectivity (≤2.5) such as PTMSP, addition of the MOF as the second filler can have a dramatic effect on the final gas permeability and selectivity of the MMM. Property-performance relations were analyzed to understand how the structural and chemical properties of the fillers affect the permeability of the resulting MMMs, and MOFs having Zn, Cu, and Cd metals were found to lead to the highest increase in gas permeability of MMMs. This work highlights the significant potential of using COF and MOF fillers in MMMs to achieve better gas separation performances than MMMs with one type of filler, especially for H2 purification and CO2 capture applications.

Le Fort Partial Colpocleisis: An Early and Feasible Option in Pelvic Organ Prolapse.

OBJECTIVE: To evaluate the safety and effectiveness of Le Fort Partial Colpocleisis (LFPC) in the surgical treatment of pelvic organ prolapse (POP) and to determine the incidence of pop recurrence in postoperative follow-up. STUDY DESIGN: Cross-sectional study. PLACE AND DURATION OF STUDY: Ordu University Medical Faculty Training and Research Hospital, Ordu, Turkey, from June 2013 to November 2020. METHODOLOGY: Sixty-four women (82.8% had uterine prolapsed) who had been operated as LFPC operations were included in the study. Patient's characteristics, medical comorbidities, postoperative outcomes, and operation complications were analysed. POP recurrence was evaluated during the postoperative follow-up period reaching 80 months. RESULTS: Eight patients (12.5%) had anti-incontinence surgery. Concomitant vaginal hysterectomy was performed in six patients (9.4%) and concomitant anti-incontinence surgery was performed in eight patients (12.5%). There were no serious intraoperative complications such as hematoma formation, and bladder / bowel injury. Postoperative complications were seen in a quarter of the patients (16/64) and most of them resolved spontaneously. Three of sixty-four patients (4.7%) were complicated with de novo urinary incontinence and all cases were healed without the need for treatment. In the current study, none of the patients reported POP recurrence on average over three years of follow-up. CONCLUSION: There was a low frequency of intraoperative and postoperative complications in LFPC surgery. In addition, no POP recurrence was observed in any patient during long-term follow-up. Therefore, the LFPC procedure was described as a good surgical option in the selected elderly population with POP. KEY WORDS: Colpocleisis, Le fort partial colpocleisis, Pelvic organ prolapse.

An Evaluation of Cesarean Delivery Rates According to Robson Classification in the Black Sea Region of Turkey.

OBJECTIVE: To analyse cesarean deliveries (CD) using the Ten Group Classification System (TGCS) for reducing cesarean rates. STUDY DESIGN: Cross-sectional study. PLACE AND DURATION OF STUDY: Ordu University Medical Faculty Training and Research Hospital, Ordu, Turkey, from 1st January 2008 to 31st December 2020. METHODOLOGY: A total of 29,885 deliveries during the 13-year study period were analysed. Group sizes and annual, overall, absolute, and relative CD rates were calculated to analyse the effect of the Robson groups (RGs)/TGCS. The data were analysed using the two-way Chi-square test and two-proportion Z-test with Bonferroni correction. RESULTS: The overall CD rate was 59.22% (17,697). The principal contributors to the overall CD rate were RG5 (54.48%), RG1 (12.52%), and RG2 (10.06%). The relative CD rate in preterm pregnancies (RG10) increased approximately five-fold over the 13-year study period due to the increase in both group size and absolute CD rate (p<0.001). CONCLUSION: TGCS shows the cesarean delivery trends in terms of cesarean rates and identifies those groups requiring special precautions. The target groups (RG5, RG1, RG2 and RG10) need more in-depth research to reduce CD rates. Various approaches need to be implemented including individualised cesarean indication, encouragement of vaginal delivery after cesarean delivery, expectant management in nulliparous women, and spontaneous labor for preterms labor. KEY WORDS: Cesarean section, Elective cesarean section, Induction of labor, Vaginal birth after cesarean section, Robson classification, Preterm deliveries.

Histopathological Changes in Liver and Heart Tissue Associated with Experimental Ultraviolet Radiation A and B Exposure on Wistar Albino Rats.

This study aims to evaluate the influences of ultraviolet radiation A and B (UVA + B) exposure on the liver and heart organs of albino rats. Female Wistar Albino rats, whose hair of the dorsal skin was shaved, were exposed to a combined UVA + B radiation for 2 h/day, for 4 weeks in order to be compared with the control group. Histopathological findings in vital organs (liver and heart) were evaluated. Tissues were fixed in 10% buffered formalin (pH = 7.2) and embedded in paraffin. The histopathological findings were examined on the H&E stained sections with light microscopy. The results show that the liver and the heart were injured in the UVA + B group. Liver tissue in the UVA + B group showed minimal vacuolation, enlargement of hepatocytes and bile duct proliferation, and the heart tissue showed hibernomas; uniform large cells resembling brown fat with coarsely granular to multivacuolated cytoplasm that is eosinophilic or pale with a small central nucleus. The number of hibernoma cases was significantly higher in the UVA + B group compared with the control group (P = 0.021). The control group showed normal liver and heart histology with normal adipose tissue in the pericardium. As a result, UVA + B exposure has toxic effects, especially on the liver and the heart of Wistar albino rats. UV radiation may cause such adverse effects in humans. Therefore, protection against the harmful effects of UV radiation is of significant importance for skin and organs.