Lower Values Research Articles

Numerical investigation of combustion characteristics of hydrogen-enriched low calorific value landfill gas for energy applications

Landfill gas is regarded as a promising renewable energy resource. However, Low calorific value landfill gases with less than 40 vol% CH4 are not well suited for energy applications and therefore disposed by flaring or direct emission to atmosphere causing environmental problems. In the present work, the potential of using hydrogen-enriched low calorific value landfill gas for energy applications has been explored through numerical investigation of combustion characteristics of different blends of fuels. The ignition delay of fuel mixtures decreased with the increase of hydrogen fraction (H2 enrichment from 0 to 50 vol%) at stoichiometric conditions. At high initial pressure conditions, ignition delay showed a weak relationship with the pressure. The laminar burning velocity increased with the increment of hydrogen fraction for the range of equivalence ratios considered (φ = 0.7 – 1.4) and also with the increase of initial temperature. However, the laminar burning velocity decreased significantly with the increasing initial pressure and hydrogen enrichment has insignificant effect at high initial pressures. The sensitivity analysis shows that the main elementary reactions inhibit the laminar burning velocity more with increasing initial pressure. The combustion performance of low calorific value landfill gas with 30 vol% CH4 enriched with 30 vol% hydrogen shows comparable performance to biogas with 60 vol% CH4 for a range of operating conditions. The numerical investigation results show that hydrogen-enriched low calorific value landfill gas could be used for thermal applications with the use of suitably designed combustion systems operating at low initial pressures and relatively high initial temperatures.

Constraints on the continental weathering intensity through the Permian using lithium isotopes of well-preserved brachiopod shells

Lithium isotopic compositions (δ7Li) in marine carbonates provide a powerful means to track continental weathering intensity through geological history and promote our understanding of how and why Earth remained habitable. However, δ7Li values in ancient carbonates can be affected by factors such as primary carbonate mineralogy (e.g., aragonite, high-Mg calcite, low-Mg-calcite) and post-depositional diagenesis, which may alter their primary signals. Modern articulate brachiopod shells have shown a constant δ7Li offset compared to contemporary seawater, suggesting that fossil brachiopod shells could serve as robust archives for this geochemical proxy due to their diagenetically resistant low-Mg calcite composition. Despite this potential, few studies have explored this topic.In this study, we analyze and compare the geochemical compositions of fossil brachiopod shells and their enclosing carbonate rocks from Permian strata in South China to investigate whether brachiopod shells can reliably preserve the δ7Li values of ancient seawater and, if they do, to obtain new constraints on changes in the continental weathering regimes through the Permian. We used several diagenetic screening methods, including scanning electron microscopy, cathodoluminescence microscopy, and elemental concentrations to detect potential diagenetic alteration. Our results indicate that 32 out of 49 shells preserve primary δ7Li values. Notably, we observed that δ7Li offsets between brachiopod shells and their enclosing carbonate rocks vary across the studied sections, likely due to diagenetic alteration of the bulk carbonates. Using the δ7Li values from well-preserved brachiopod shells, we reconstructed δ7Li variations of Permian seawater. We identified three distinct intervals: (1) extremely low δ7Lisw values (as low as 6.7 ± 2.9, n = 12, 1sd) during the Asselian and Sakmarian stages, (2) high δ7Lisw values (32.6 ± 4.5, n = 3, 1sd) similar to modern seawater during the Kungurian stage, and (3) relatively low δ7Lisw values (13.6 ± 3.9‰, n = 14, 1sd) from the Capitanian to the Changhsingian stages. These significant changes in δ7Li values of Permian seawater indicate dramatic changes in continental weathering regimes during the Permian, possibly linked to major climate changes, such as the termination of the Late Paleozoic Ice Age and warming associated with the emplacement of the large igneous provinces.

Magnesium isotope constraints on the role of recycled carbonate-rich sediments in the formation of ultrapotassic magmatic rocks at a continental arc setting

The formation of orogenic ultrapotassic magmatism in a subduction setting is still unclear as it requires various co-processing mechanisms. To address this problem, especially to investigate the role of carbonate metasomatism in the mantle source, whole-rock Mg-Sr-Nd isotopic compositions have been measured for ultrapotassic magmatic rocks from the Central Pontides arc, northern Turkey, one of the rare examples of subduction-related ultrapotassic magmatism. These ultrapotassic rocks have relatively low (87Sr/86Sr)i (0.70461–0.70687) and εNd(t) (0.3 to 2.6) values and display much lower δ26Mg values (−0.73 ‰ to −0.19 ‰) than the normal mantle. The petrological and geochemical characteristics of the Pontide Ultrapotassic rocks (PUR) indicate that the low δ26Mg values do not result from surficial weathering, diffusion, or magmatic differentiation, but rather reflect the presence of distinct metasomatizing agent in their mantle source. The low Hf/Hf*, Ti/Ti*, Fe/Mn and Ti/Eu ratios, high Ca/Al and (Na2O + K2O)/TiO2 ratios, and lack of significant correlations between δ26Mg and Fe/Mn or (Gd/Yb)N suggest that the low δ26Mg values cannot be reconciled with the contribution of recycled carbonated eclogites, but are induced by the addition of carbonate-rich sediments to their mantle source. This interpretation is also supported by the significant (La/Yb)N vs. Ti/Eu and Hf/Sm vs. CaO/Al2O3 correlations for the ultrapotassic rocks. Using two end-member mixing calculations of MgSr isotopic compositions, the mantle source of PUR is constrained to contain varying proportions of carbonates, mostly of dolomite composition. The addition of carbonate-rich sediments to the mantle may have occurred at depths of 100–150 km as indicated by the trace element compositions of PUR. In this regard, the enrichment of K and other large ion lithophile elements in the ultrapotassic rocks can be induced by the contribution of silicic sediments. Meanwhile, carbonatitic melts can be formed through the partial melting of carbonate-rich sediments in the subducting oceanic slab, which then reacts with the overlying mantle to form carbonated peridotite that serves as the source of ultrapotassic rocks with low-δ26Mg, low-silica, and high LREEs. This study reports for the first time the Mg isotope data of ultrapotassic rocks formed in a continental arc setting and documents that carbonate-rich sediments play an important role in creating such rocks. Future work is needed to test whether this process is common in both oceanic arc and continental arc settings.

Unveiling the organic chemical composition and sources of organic carbon in PM2.5 at an urban site in Greater Cairo (Egypt): A comprehensive analysis of primary and secondary compounds

This work presents an exhaustive chemical characterization of the organic fraction of fine particulate matter (PM2.5) collected at an urban site in the Greater Cairo Area, Egypt, one of the most polluted megacities in the world. An intensive 2-month sampling campaign was conducted at an urban site in Giza (Dokki), from November 26, 2019, to January 28, 2020. Daily (24-h integrated) PM2.5 filter samples were then analyzed for their carbonaceous (OC, EC) and organic fractions including primary (n-alkanes, phthalates, fatty acids, polycyclic aromatic hydrocarbons, hopanes, sugars, and sugar alcohols) and secondary (isoprene and β-caryophyllene oxidation products, and dicarboxylic acids) compounds. Average organic (OC) and elemental carbon (EC) concentrations were 17.8 ± 6.6 μg/m3 and 4.4 ± 1.5 μg/m3, respectively. Biomass burning was confirmed by high daily concentration levels of levoglucosan, mannosan, and galactosan (sum equals to 288 ng/m3). Road traffic was also highlighted by the relative abundance of tetracosane and a carbon preference index close to unity as well as by the concentration ratios of PAHs and hopanes. Moreover, phthalates were identified for the first time in Cairo with high concentrations (654 ng/m3) that might be attributable to open waste burning activities. Fatty acids and sugars were also investigated and assigned to cooking activities and primary biogenic sources, respectively. The average concentration of isoprene and β-caryophyllene oxidation products were 0.89 ± 0.83 ng/m3, and 0.01 ± 0.02 ng/m3, respectively. These low values are expected since no pine trees or even forests exist in Egypt. The macrotracer approach was employed alongside Monte Carlo simulation to identify sources of primary OC and evaluate the uncertainties associated with source attribution and OC reconstruction. The findings revealed a strong contribution from cooking (31% of observed OC) and biomass burning (18%), with median reconstructed OC levels showing significant uncertainty (64%) as expected.

Battery Remaining Useful Life Estimation based on Particle Swarm Optimization-Neural Network

Determining the Remaining Useful Life (RUL) of a battery is essential for several purposes, including proactive maintenance planning, optimizing resource allocation, preventing unforeseen failures, improving safety, extending battery lifespan, and achieving accurate cost savings. Concerning that matter, this study proposed hybrid Particle Swarm Optimization–Neural Network (PSO-NN) for estimating battery RUL. In the evaluation of the proposed method, the effectiveness is assessed using the metrics of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The dataset employed for this investigation comprises eight input parameters and one output variable, representing the battery RUL. In conducting an analysis, the performance of the PSO-NN model is compared with hybrid NN with Cultural Algorithm (CA-NN) and Harmony Search Algorithm (HSA-NN), as well as the standalone Autoregressive Integrated Moving Average (ARIMA). Upon examination of the findings, it becomes evident that the PSO-NN model outperforms the alternatives with an MAE of 2.7708 and an RMSE of 4.3468, significantly lower than HSA-NN (MAE: 22.0583, RMSE: 34.5154), CA-NN (MAE: 9.1189, RMSE: 22.4646), and ARIMA (MAE: 494.6275, RMSE: 584.3098). The PSO-NN also achieves the lowest maximum error of 104.7381 compared to 490.3125 for HSA-NN, 827.0163 for CA-NN, and 1,160.0000 for ARIMA. Additionally, the low two-tail probability values (P(T≤t)), all below the significance level of 0.05, indicate that the differences between PSO-NN and the other methods (HSA-NN, CA-NN, and ARIMA) are statistically significant. These results highlight the superior accuracy and robustness of the PSO-NN model in predicting battery RUL. This study contributes to the field by presenting the PSO-NN as a highly effective tool for accurate battery RUL estimation, as evidenced by its superior performance over alternative methods.

Ilha de calor de superfície e indicadores geoespaciais: avaliação decadal comparativa por sensoriamento remoto

Abstract Surface Urban Heat Islands (SUHI) are formed through processes that include decreasing vegetation and increasing materials that are more conductive to heat. To investigate this phenomenon, the objective of this work is to comparatively verify the surface temperature and geospatial indicators to analyze environmental variation in the city of São Paulo, Brazil. The study method is remote sensing, with data from the Landsat 8 satellite over a ten-year timeframe. The variables include land cover, the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built-up Index (NDBI), and land surface temperature (LST), thereby obtaining the Urban Thermal Field Variation Index (UTFVI) and estimating SUHI formation. The results allowed for the presentation of a progression of variables, highlighting the recurrent formation of SUHI in the central and eastern regions of the city of São Paulo, Brazil. Conversely, the southern and extreme northern districts exhibited the best NDVI indices and low LST values.

Machine Learning Prediction of Quality of Life: Insight from Property Crime and Tropical Climate Analysis

<p align="center">This study delves into predicting the quality of life, a widely researched concept spanning various domains, employing mixed methodologies and indicators. Common predictors of overall quality of life encompass health status, socioeconomic factors, subjective well-being, and environmental conditions. Consequently, this research investigates the potential of utilizing machine learning prediction models for quality-of-life prediction, focusing on two key indicators.Five machine learning algorithms—Generalized Linear Model, Random Forest, Decision Tree, Gradient Boosted Tree, and Support Vector Machine—are empirically compared. Their performance in predicting quality of life is assessed based on property crime and tropical climate (temperature) attributes. Despite an initially low correlation value, temperature yields valuable insights for specific algorithms, enhancing predictive accuracy. This underscores the intricate and nuanced impact of seemingly unrelated factors in machine learning. The Support Vector Machine emerges as the top-performing algorithm, followed by Random Forest and Decision Tree. This paper offers a foundational research framework to aid educators and researchers in exploring quality of life prediction in-depth, utilizing property crime and temperature as key factors.</p>

Quantum mechanical approaches and Molecular Docking studies of Platinum based anticancer drugs Satraplatin and Picoplatin structures.

The structures of the anticancer drug compounds satraplatin and picoplatin are optimized, and theoretical studies done by Density Functional Theory (DFT) to investigate the optical properties, global chemical descriptors, and band gap were calculated using the obtained Frontier molecular orbital values. The theoretically obtained data of the platinum drugs found to possess low energy gap values and low chemical hardness with high chemical softness describe that the compounds are chemically stable and most reactive. Using the molecular docking process, the binding mechanisms of the satraplatin and picoplatin drugs with cancer DNA structures were studied, and the results were analyzed. For the two drug compounds examined, satraplatin has shown the least binding energies at -5.06 kcal/mol compared to picoplatin at -2.69 kcal/mol, and conformations with root mean square deviation (RMSD) values by DNA structures are less than or equal to 2.00Å in targeting the specific DNA target residues of the reference bound ligand. The grid box was generated using the selective grid parameters using the Autodock 4.2 program. The drug molecules found to have the least binding energy value with the lowest inhibition constant implicate the good docking score towards the DNA structure by the docking studies. DFT studies also show good structural properties and chemical reactivity. From the obtained results, satraplatin and picoplatin were found to have good chemical descriptors and good binding affinity and are best suited for biological molecular targets.

Low-stakes Scientist Spotlight Assignment Demonstrates High Value and Multiple Effects for Introductory Biology Students.

Scientist Spotlights are homework assignments that highlight the personal and scientific stories of counterstereotypical scientists. Previous research has focused on whether these assignments promote possible selves in STEM (science, technology, engineering, mathematics). We sought to understand the value students themselves placed on the assignment using expectancy-value theory complemented by further analysis of the assignment's self-reported impacts on students. Therefore, at the end of an introductory biology course with several Scientist Spotlights, we asked students to reflect on how the course would influence them for years to come. We found that although the assignments had low instrumental value, 49% of students mentioned Scientist Spotlights or a highlighted scientist. Thematic analysis on the Scientist Spotlight-related parts of the reflections found novel emergent themes including diversity in science, humanizing scientists, and self-efficacy. Most students mentioned multiple themes, with few differences between students from minoritized and nonminoritized groups. We interpreted our results through the lens of the "mirrors, windows, and sliding glass doors" framework, as Scientist Spotlights appeared to function as "windows" into the diverse scientific world, "mirrors" for seeing human traits in scientists, and "sliding glass doors" inviting students further into science. Our study expands our understanding of the broad, multiple, and intersecting impacts of Scientist Spotlights.

Enhanced conversion of rosin to polymerized rosin with reusable Brønsted acid deep eutectic solvent

With the depletion of non-renewable resources and the increasingly serious environmental problems, the production of high value-added polymer materials using renewable resources as raw materials had aroused great interest. Deep eutectic solvent (DES)-[ChCl][TfOH]2 (prepared by choline chloride (ChCl) and trifluoromethanesulfonic acid (TfOH)), with suitable acid strength (H0=0.98) and active hydrogen, had been successfully used for enhanced conversion of rosin to polymerized rosin efficiently, under the conditions of rosin =15 g, mDES: mrosin=30 %, T=110℃ and t=9 h, polymerized rosin with high softening point (150.40℃) and low acid value (124.21 mg KOH/g) could be produced efficiently. [ChCl][TfOH]2 required no special treatment then could be reused for 5 times without significant loss of catalytic performance, on this basis, the green synthesis technology of polymerized rosin under DES system was given, not only promoted the further application of polymerized rosin, but also realized the high value-added utilization of renewable resource rosin. In addition, the formation mechanism of DES was systematically explained through DFT calculation, the reaction mechanism of rosin polymerization over [ChCl][TfOH]2 was explored, which could provide theoretical basis for further research.

Ensemble versus deterministic lightning forecast performance at a convective scale over Indian region

The present study quantifies the improvement achieved in lightning forecast skill of the NCMRWF regional ensemble prediction system (NEPS-R) compared to its deterministic counterpart (CNTL). The lightning forecasts over study regions of East and Northeast India (ENEI) and Peninsular India (PI) during the pre-monsoon season and Central-East and Northeast India (CENEI) during the monsoon season have been verified using lightning observations from the Indian Institute of Tropical Meteorology (IITM) Lightning Detection Network (LDN). The persisting systematic negative bias in deterministic and EPS-based forecasts of the ensemble mean (EnsMean) and ensemble maximum (EnsMax) indicate the lack of spread among the members, supported by the low values of ensemble spread over all the study regions. EnsMean has the lowest RMSE, with a decrease in error ranging from 0.8 % to 2.18 % compared to CNTL. Categorical skill scores indicate that the EPS-based forecasts (EnsMean and EnsMax) are more skillful than the deterministic forecast at all thresholds and lead times. Further, Fractions Skill Score (FSS) establishes the superiority of the ensemble forecasts over the deterministic forecasts, where for threshold >1, EnsMean is skillful at comparatively smaller neighborhood sizes (ENEI and PI ~68 km; CENEI ~36 km for day-1) than CNTL (ENEI-116 km; PI-196 km; CENEI-68 km). EnsMax at higher thresholds (>5 and > 10) is skillful at lesser neighborhood sizes ranging from 116 to 276 km compared to CNTL (>401 km) for day-1. Hence, skillful re-scaled EPS forecasts based on FSS could provide better guidance for the forecasters. The Continuous Ranked Probability Score of EPS forecasts is lower by around 9 % than the Mean Absolute Error of CNTL forecasts, and the ROC of EPS shows better discrimination of events and non-events compared to CNTL. These highlight the merits of using an EPS over a deterministic system for forecasting a field of high spatial variability, like lightning, and thereby, the use of vast computational resources to run a convective scale EPS is justified.

Augmented glycerosomes as a promising approach against fungal ear infection: Optimization and microbiological, ex vivo and in vivo assessments

In the current study, voriconazole (VCZ) augmented glycerosomes were optimized for topical otomycosis management according to a 23 factorial design, employing a thin film hydration method. By optimizing Glycerol volume, limonene: VCZ ratio and Span® 60: soybean phosphatidyl choline (PC) ratio, glycerosomes with maximum percentage entrapment efficiency (%EE) and zeta potential (ZP) and minimum vesicle size (VS) and polydispersity index (PDI) were to be obtained. An optimal augmented glycerosomal formula (OAG) that contained 10 mg VCZ, 150 mg PC, and 3 mL glycerol, comprising 2.5: and 0.92:1 ratios of the latter two independent variables, was proposed via numerical optimization. OAG exhibited high %EE and ZP values and acceptable low values for VS and PDI (84.3 ± 2.0 %, −38.8 ± 1.8 mV, 191.0 ± 1.1 nm, and 0.192 ± 0.01, respectively). Extensive in vitro testing of OAG revealed the entrapment of VCZ within OAG, biphasic in vitro release profile, stability for up to 3 months at 2–8 °C and spherical morphology of OAG with VS like that obtained via zetasizer. OAG demonstrated higher permeated amounts of VCZ and flux values than VCZ suspension, leading to an enhancement ratio of 2.56 in the ex vivo permeation study. The deeper penetration ability of OAG demonstrated by Confocal Laser Scanning Microscopy and its superior in vitro antifungal activity confirmed the validity of the ex vivo study. Also, the histopathological study confirmed the safety of OAG for topical use, suggesting that VCZ OAG was a promising topical antimycotic formula.

Numerical and experimental investigation on mixed convection heat transfer inside cavity heated from below with reciprocating moving upper surface

This investigation involves a numerical and experimental work on mixed convective heat transfer inside cavity heated from below and reciprocating moving upper surface. For the experimental work, the smoke method is used for the air flow visualization. The experiments include the measurements of air temperature inside the cavity and upper and lower surfaces of duct. For the numerical work, the velocity boundary condition of the upper surface is defined asu=umaxsinωt with low constant temperature (Tc), whereas the lower surface of duct is kept at constant wall temperature (Th) and the vertical walls are well insulted. The mathematical model adopted in the calculations are solved by building an own code using finite difference method in MATLAB software The influences of Richardson number (Ri), Aspect Ratio (AR) and dimensionless period (dp) on the flow behavior and average Nusselt number (Nu) are investigated. The experimental and numerical outcomes are compared under identical conditions, where the comparison gives a good matching between them. The numerical outcomes demonstrated that the rising in AR with constant Ri leads to increase the Nu values. For AR=1 and Ri=0.01, the average Nu increases with dp. The experimental results show that the Nu value increases to 3.2 with increasing AR to 2 under constant Ri=10. The dp decreases to 33 s when AR is increased under constant Ri value. The data indicated that Nu rises with reducing in Ri for all AR values. The value of Nu depends on dp, AR and Ri. The multi-cells flow is observed when Ri is raised under constant AR value. The maximum Nu value is obtained for low values of AR and Ri. The profiles of Nu reveal that AR, Ri and dp have considerable influences on the heat transfer.

Efficacy of Autofluorescence in Detection of Tobacco-associated Oral Mucosal Lesions - A Systematic Review

Abstract Background: This study was conducted with the aim to systematically review the efficacy of autofluorescence in the detection of tobacco-associated oral mucosal lesions. Objectives and Data Sources: Clinical studies with patients that focused on the autofluorescence method in the detection, visualisation, or management of tobacco-associated oral mucosal lesions were included in the literature search across bibliographic databases. Results: Autofluorescence visualisation showed positive results, with high sensitivity scores when compared with the gold standard of histopathology in the clinical evaluation of common tobacco-associated oral mucosal lesions. However, the low specificity values indicate its limited ability to distinguish between dysplasia and other benign conditions. Conclusions and Implications: This review provides promising evidence for the application of autofluorescence in the detection of tobacco-associated oral mucosal lesions where autofluorescence is used in conjunction with conventional examination with the gold standard of histopathological examination. Registration number: PROSPERO 2023 CRD42023442292.

Genetic diversity of Colletotrichum kahawae populations in Burundi

AbstractMicrosatellite markers were used to assess genetic diversity of Colletotrichum kahawae isolates from Burundi. Sampling was carried out through all coffee growing areas in Burundi. The indices of genetic diversity such as the number of different alleles (Na), the number of effective alleles (Ne) revealed low genetic diversity with an average of 1.900 and 1.196 respectively. Higher than expected heterozygosity and significant linkage disequilibrium are consistent with clonal reproduction. The results showed a weak genetic diversity between the populations from different region and the low value of Fst indicated that the C. kahawae populations of Burundi were weakly differentiated. Our results confirm the clonality of C. kahawae and its low dispersion ability. The weak differentiation between the populations and the occurrence of one clonal lineage in Burundi are consistent with previous study suggesting that the East African populations of C. kahawae are the most recently populations derived from the ancestral Angolan population.

Abstract B010: Improving pancreatic cancer image classification with transfer learning: CD45 vs. PANCK

Abstract Pancreatic ductal adenocarcinoma (PDAC) is known for its high aggressiveness and is the fourth most common cause of death of cancer-related death in the United States. It is highly malignant and often goes undiagnosed until advanced stages due to its late-onset symptoms, resulting in poor prognosis. Using quantitative analyses of histological features, such as the expression of prognostic biomarker, can provide valuable insight to guide treatment decisions, monitor disease progression and predict outcomes. Previous researchers have found that CD45 and PANCK play a huge role in characterizing the tumor microenvironment of PDAC. One study using single-cell RNA sequencing compared the microenvironments of healthy pancreata and pancreatic tumors, revealing differences in cellular composition. Tumor samples showed a higher proportion of immune cells, including CD45+ cells, compared to heathy samples and utilized PANCK to differentiate between epithelial and non-epithelial cells. This study aims to enhance the accuracy of classifying pancreatic cancer pathological images based on prognostic markers using transfer learning techniques. We curated and pre-processed a dataset of pancreatic cancer pathological images with different prognostic markers. Using the pre-trained convolutional neural network (CNN) model VGG16, we fine-tuned it with our dataset to better differentiate between two prognostic markers, CD45 and PANCK. The model's performance was evaluated using a similarity matrix to illustrate distinctions among the two prognostic markers. Our results demonstrate that the transfer learning approach significantly improves classification accuracy, achieving confusion matrix validation results of 90% between CD45 and PANCK prognostic markers. SSIM values were relatively low, highlighting the ability of our model to differentiate between the two prognostic markers. The low SSIM value also shows variability within the two prognostic markers, indicating heterogeneity in structural changes due to pancreatic cancer. These findings indicate that transfer learning can be a powerful tool for improving the classification of pathological images and that there is notable variability in the structural features associated with different prognostic markers in pancreatic cancer. Citation Format: Miracle Thomas. Improving pancreatic cancer image classification with transfer learning: CD45 vs. PANCK [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B010.

Early Monitoring of Donor-Derived Cell-Free DNA in Kidney Allograft Recipients Followed-Up for Two Years: Experience of One Center

(1) Background: donor-derived circulating free DNA (dd-cfDNA), an innovative biomarker with great potential for the early identification and prevention of graft damage. (2) Methods: Samples were collected prospectively and the study was performed retrospectively to analyze dd-cfDNA plasma levels in 30 kidney transplant patients during their post-transplant follow-up (15 days, 3, 6, and 9 months), to determine if the result could be of interest in the identification of possible adverse events, especially rejection. The aim was to verify whether the data on sensitivity, specificity, NPV, and PPV compare with reference values and creatinine values. (3) Results: We observed levels of dd cfDNA > 1% in six of nine patients with active rejection (ABMR or TCMR) and elevated values (>0.5%) in two other patients in this rejection group. Our results show low values of sensitivity = 50%, specificity = 61.11%, rejection NPV = 64.71%, and rejection PPV = 46.13% of the technique compared to reference values previously published. With respect to creatinine, only for TCRM, we observed better results for dd-cfDNA in these parameters than in creatinine. Also, our data suggest that dd-cfDNA could help to differentiate those patients with dnDSAs that are going to through rejection better than creatinine, specially at 15 d post transplant. In this study, this appears to have no positive predictive value for borderline rejection (BR) or TCMR IA. (4) Conclusions: plasma levels of dd-cfDNA could be considered an additional or alternative biomarker for graft rejection monitoring in early post-kidney transplant up to several months before its clinical presentation, especially for patients with suspected TCMR or ABMR.

Inventing with bacteriology: controversy over anti-cholera therapeutic serum and tensions between transnational science and local practice in Tokyo and Berlin (1890-1902).

The present article examines the material, epistemological, and social dimensions of late nineteenth-century anti-cholera serum controversies that unfolded in Tokyo and Berlin. It seeks to shed light on the conflicting values embedded in the construction of scientific evidence during the transnational exploration of bacteriology as an effective response to controlling epidemics. Driven by Japanese health authorities' initiatives, Japanese bacteriologist Kitasato Shibasaburo participated in the elaboration of bacteriological research oriented toward therapeutic application during his stay in Berlin. This work coincided with the rise of a controversy over anti-cholera serum in relation to the animal experiments conducted by Richard Pfeiffer, a German bacteriologist. After presenting a series of animal experiments and certain clinical cases conducted in Germany, France, and Egypt in the context of the controversies, the article analyzes a therapeutic trial conducted by Kitasato in Japan during an 1895 cholera epidemic. His strategy, bringing new data to the transnational debate through an intensive investment of resources in the trial, provoked criticism from his Japanese and German colleagues. These critics questioned Kitasato's method and pointed out the low social value of this experimental serum therapy, performed in highly equipped conditions. Through this case study, the present article highlights: a) a strong tension between transnational research interactions among bacteriologists and local medical practices during public health campaigns against epidemics at the turn of the twentieth century; b) the importance of analyzing the interconnected effects of local, national and transnational frameworks of medical science when examining the increasingly intertwined relationships between laboratory science and clinical medicine.

Experimental Investigation of Ammonia/Oxygen/Argon Combustion: The Role of Equivalence Ratio and Nozzle Shape in a Constant Volume Combustion Chamber with Sub-chamber

The global rise in carbon emissions presents a rising challenge for current and future generations. In the pursuit of zero carbon emissions, ammonia (NH3) has emerged as an attractive alternative energy source. Ammonia offers a carbon-free fuel option with a higher energy density than liquid hydrogen while maintaining ease of transport and storage. However, ammonia still has its drawbacks, such as a high autoignition temperature, slow burning velocity, and low heating value, that demand further investigation of its combustion characteristics. This experiment was done to study the effect of nozzle shape and equivalence ratio (ɸ) on the combustion of an ammonia/oxygen/argon mixture using a constant volume combustor equipped with a sub-chamber. The fuels were premixed for 10 minutes and conditioned to an initial pressure of 0.2 MPa and an initial mixture temperature of 423 K. The results show that the different nozzle shapes each have their advantages in terms of pressure and jet speed. Overall, the lean mixtures (ɸ0.6 and ɸ0.8) consistently performed better compared to the stoichiometric mixtures (ɸ1.0) in all categories investigated in this study. The round nozzle generates higher pressure, while the special shape nozzle enhances jet speed, highlighting trade-offs between the two.

Acid Resistance Engineering of Endoglucanase for the Degradation of Wine Lees.

Wine lees is a low value biomass resource rich in cellulose, with great potential for producing organic fertilizers and chemicals. However, the high acidity of wine lees limits the catalytic efficiency of the conversion tool endoglucanase. Here, we expressed endoglucanase tCel5A from Trichoderma reesei in Pichia pastoris, and the combination of promoter AOX1 and signal peptide SUC2 resulted in a highly active expression of 4632.81 U/mg. Subsequently, the catalytic center design and surface charge modification strategy resulted in mutants T88H/W255H and S45D/T55D/T59D exhibiting catalytic activity twice and three times higher than WT at pH 3.0, respectively. Finally, when the solid-liquid ratio was 1:15 (w/v), the degradation rate of wine lees was nearly double that of WT. The degradation products contained a variety of industrial and pharmaceutical raw components, including the antioxidant and anticonvulsant isopiperolein B. This study accelerates the green and sustainable management of wine lees.