Small Residues Research Articles

Coarse-Grained Simulation Study of the Association of Selected Dipeptides.

The association of 55 dipeptides extracted from aggregation-prone regions of selected proteins was studied by means of multiplexed replica-exchange molecular dynamics simulations with the coarse-grained UNRES model of polypeptide chains. Each simulation was carried out with 320 dipeptide molecules in a periodic box at 0.24 mol/dm3 concentration, in the 260-370 K temperature range. The temperature profiles of the degree of association, distributions of dipeptide cluster size, and structures of clusters were examined. It has been found that the dipeptides composed of strongly nonpolar (aromatic or aliphatic) residues associate nearly completely at all temperatures to form tight clusters, while those composed of charged or polar residues exhibited no or residual association. The dipeptides composed of nonpolar and small polar residues and those composed of less hydrophobic residues formed single clusters, gradually dissolving with increasing temperature, while those composed of phenylalanine or tryptophan and polar or charged residues formed multiple irregular clusters with room to accommodate water inside, suggesting the formation of liquid droplets or gels. The logarithms of the average degree of association and the free energy of aggregation per monomer were found to correlate with the dipeptide hydrophobicity.

Triplet Order Adaptive Seventh-Order WENO Scheme for Compressible Flows

Abstract Accurately determining shock structures is crucial for assessing the loads on supersonic flights. Achieving precision in aero-thermal load estimation for high Mach number flows demands the use of higher-order high-resolution algorithms. This study introduces a specific higher-order high-resolution scheme renowned for its exceptional shock-resolving capabilities. While many seventh-order schemes typically achieve only fourth or seventh-order accuracy, the presented scheme can attain accuracy levels of fourth-, sixth-, or seventh-order. Notably, it precisely satisfies the Taylor series with zero residues, unlike many existing schemes that yield small non-zero residues. This accomplishment is attributed to a novel weighting function that breaks the direct connection between the smoothness indicator and the weighting function. The scheme’s effectiveness is validated using gas dynamics Euler equations, particularly in scenarios involving step-like discontinuities such as shock tube problems and double Mach reflection test cases. Across various test cases, the proposed scheme consistently demonstrates minimal errors and exhibits outstanding shock-resolving properties.

Cascade adaptive optics with a second stage based on a Zernike wavefront sensor for exoplanet observations

Context. Over the past decade, the high-contrast observation of disks and gas giant planets around nearby stars has been made possible with ground-based instruments using extreme adaptive optics (XAO). These facilities produce images with a Strehl ratio higher than 90% in the H band, in median observing conditions and high-flux regime. However, the correction leaves behind adaptive optics (AO) residuals, which impede studies of fainter or less massive exoplanets. Aims. Cascade AO systems with a fast second stage based on a Pyramid wavefront sensor (PWFS) have recently emerged as an appealing solution to reduce the atmospheric wavefront errors. Since these phase aberrations are expected to be small, they can also be accurately measured by a Zernike wavefront sensor (ZWFS), a well-known concept for its high sensitivity and moderate linear capture range. We propose an alternative second stage that relies on the ZWFS to correct for the AO residuals. Methods. We implemented the cascade AO with a ZWFS-based control loop on the ESO’s GPU-based High-order adaptive OpticS Testbench (GHOST) to validate the scheme in monochromatic light. We emulated the XAO first stage in different observing conditions (wind speed, seeing) and determined the corresponding operation parameters (e.g., number of controlled modes, integrator gain, loop calibration) that lead to stable loop operation and good correction performance. Our strategy was assessed in terms of corrected wavefront errors and contrast gain in the images with a Lyot coronagraph to probe its efficiency. Results. In median wind speed and seeing, our second-stage AO with a ZWFS and a basic integrator was able to reduce the atmospheric residuals by a factor of 6 and increase the wavefront error stability with a gain of 2 between open and closed loop. In the presence of non-common path aberrations, we also achieved a contrast gain of a factor of 2 in the coronagraphic images at short separations from the source, proving the ability of our scheme to work in cascade with an XAO loop. In addition, it may prove useful for imaging fainter or lighter close-in companions. In more challenging conditions, contrast improvements are also achieved by adjusting the control loop features. Conclusions. Our study validates the ZWFS-based second-stage AO loop as an effective solution to address small residuals left over from a single-stage XAO system for the coronagraphic observations of circumstellar environments. Our first in-lab demonstration paves the way for more advanced versions of our approach with different temporal control laws, non-linear reconstructors, and spectral widths. This would allow our approach to operate in high-contrast facilities on the current 8–10 m class telescopes and Extremely Large Telescopes to observe exoplanets, all the way down to Earth analogs around M dwarfs.

QLTI-02. THE ROLE OF REOPERATION IN PAEDIATRIC PILOCYTIC ASTROCYTOMA

Abstract INTRO Cerebellar pilocytic astrocytomas (cPAs) in childhood have long been recognized to have a good prognosis after total resection, but the outcome after incomplete resective surgery remains largely unpredictable, with the incidence of radiological progressive disease ranging from 18-100%. It has been traditionally thought that gross-total resection was required for long-term survival, and small residuals were classically resected in a subsequent operation. OBJECTIVE To determine the role of reoperation in residual or recurrent cerebellar pilocytic astrocytoma. METHODS The authors analyzed their pediatric low-grade clioma (PLGG) database for cases treated between 1985-2020 and filtered for intracranial PAs, to determine what clinical or radiological factors precipitated revisional resective surgery in their single quaternary care center cohort. RESULTS Using the PLGG database, 283 patients <18 years of age were identified to have a histopathological diagnosis or intracranial PA between 1985-2020, of which, 200 were within the cerebellum (70.7%). The majority of patients with cPA were between 1 and 10 years of age (n=145, 72.5%) without gender preponderance (M/F=99:101) usually presenting with 1 lesion (n=197, 98.5%). Gross total resection was achieved in 74.5% (n=149) of initial surgeries for cPA. In patients with subtotal resection, the mean largest diameter of the postoperative residual tumor was 1.06cm (range 0-2.95cm). Seven patients with subtotal resection did not require a second resective intervention. In 31 patients the neuro-oncology multi-disciplinary team recommended a second resection at a mean time interval of 22.9 months (range 0.13-81.6 months) from the initial surgery. Proportionally, the children who underwent multiple resections were also more likely to receive adjuvant chemo/radiotherapy. Functionally, the children in the multiple operation cohort experienced more complications of therapy including ongoing endocrinopathy, treatment-associated hearing deficit, and neuro-cognitive deficits. CONCLUSION Residual disease in cPA should be maintained under clinico-radiological surveillance postoperatively with adoption of a more conservative approach when residual disease is not significantly changing over time.

How to evaluate local fit (residuals) in large structural equation models.

Consistent with reporting standards for structural equation modelling (SEM), model fit should be evaluated at two different levels, global and local. Global fit concerns the overall or average correspondence between the entire data matrix and the model, given the parameter estimates for the model. Local fit is evaluated at the level of the residuals, or differences between observed and predicted associations for every pair of measured variables in the model. It can happen that models with apparently satisfactory global fit can nevertheless have problematic local fit. This may be especially true for relatively large models with many variables, where serious misspecification is indicated by some larger residuals, but their contribution to global fit is diluted when averaged together with all the other smaller residuals. It can be challenging to evaluate local fit in large models with dozens or even hundreds of variables and corresponding residuals. Thus, the main goal of this tutorial is to offer suggestions about how to efficiently evaluate and describe local fit for large structural equation models. An empirical example is described where all data, syntaxand output files are freely available to readers.

Clinician's Guide to Epitranscriptomics: An Example of N1-Methyladenosine (m1A) RNA Modification and Cancer.

Epitranscriptomics is the study of modifications of RNA molecules by small molecular residues, such as the methyl (-CH3) group. These modifications are inheritable and reversible. A specific group of enzymes called "writers" introduces the change to the RNA; "erasers" delete it, while "readers" stimulate a downstream effect. Epitranscriptomic changes are present in every type of organism from single-celled ones to plants and animals and are a key to normal development as well as pathologic processes. Oncology is a fast-paced field, where a better understanding of tumor biology and (epi)genetics is necessary to provide new therapeutic targets and better clinical outcomes. Recently, changes to the epitranscriptome have been shown to be drivers of tumorigenesis, biomarkers, and means of predicting outcomes, as well as potential therapeutic targets. In this review, we aimed to give a concise overview of epitranscriptomics in the context of neoplastic disease with a focus on N1-methyladenosine (m1A) modification, in layman's terms, to bring closer this omics to clinicians and their future clinical practice.

Forecast of Foreground Cleaning Strategies for AliCPT-1

We report the test results of several independent foreground cleaning pipelines used in the Ali CMB Polarization Telescope experiment (AliCPT-1), a high-altitude cosmic microwave background (CMB) imager in the Northern Hemisphere with thousands of detectors dedicated to the search for a primordial CMB polarization B-mode signature. Based on simulated data from four detector modules and a single season of observation, which we refer to as Data Challenge 1 (DC1), we employ different and independent pipelines to examine the robustness and effectiveness of estimates on foreground parameters and primordial B-mode detection. The foreground cleaning strategies used in the pipelines include the parametric method of template fitting (TF) and the nonparametric methods of constrained internal linear combination (cILC), analytical blind separation (ABS), and generalized least squares (GLS). We examine the impact of possible foreground residuals on the estimate of the CMB tensor-to-scalar ratio (r) for each pipeline by changing the contamination components in the simulated maps and varying the foreground models and sky patches for various tests. According to the DC1 data with the simulation input value r true = 0.023, the foreground residual contamination levels in the TF/ABS/cILC/GLS pipelines are well within the corresponding statistical errors at the 2σ level. Furthermore, by utilizing the tension estimator, which helps identify significant residual foreground contamination in the detection of the primordial B-mode signal by quantifying the discrepancy between various r measurements, we conclude that the presence of small foreground residuals does not lead to any significant inconsistency in the estimation of r.

Deep neural networks-prescribed performance optimal control for stochastic nonlinear strict-feedback systems

This article explores the application of deep neural networks (DNNs) for optimized backstepping control design in a category of stochastic nonlinear strict-feedback systems with unknown dynamics, focusing on prescribed performance. DNNs, distinguished by their ability to handle high-complexity functions and enhance function approximation, are employed to estimate unknown nonlinear functions. The weight updating strategy for each layer of DNNs is determined through a Lyapunov function analysis. Tomitigate potential issues such as the tracking error exploding at uncertain moments, prescribed performance control (PPC) is introduced to constrain the tracking error within a predetermined range. Subsequently, a novel optimal tracking control scheme, integrating the backstepping method and Hamilton–Jacobi–Bellman (HJB) equation, is presented. The results indicate that all signals in the closed-loop system are bounded in probability, and the tracking error is maintained within a set of predefined arbitrarily small residuals. Simulation outcomes affirm the efficacy of the proposed control scheme.

Copper leaching behaviour during oxygen pressure leaching of zinc sulfide concentrate

ABSTRACT To optimise copper (Cu) leaching, this study investigated Cu behaviour during a two-stage oxygen pressure leaching process of zinc sulfide concentrate (ZnS). The results indicated that maintaining low temperature, low sulfuric acid (H2SO4) concentration, and low oxygen partial pressure during the first stage of leaching the reduction of ferric iron (Fe3+) by ZnS and the weak leaching of Cu. In the second stage, increasing the temperature, H2SO4 concentration, and oxygen partial pressure enabled efficient Cu leaching while converting iron (Fe) back to Fe3+ and returning it to the first stage. This two-stage process effectively mitigated Fe hydrolysis precipitation, resulting in a small residue yield and preventing Cu incorporation into jarosite. Cyclic validation experiments were conducted under optimum experimental conditions with a residue yield of 36.1%, the dissolution rates of Zn, Cu, and Fe impurity of 98.76%, 91.65%, and 81.05%, and the Zn, Cu, and silver (Ag) contents of leaching residue were 1.61%, 0.17%, and 0.524%, respectively. The primary phases in the leach residue included lead (Pb) sulfate, sulfur, and pyrite. This approach allowed for deep leaching of Zn and Cu as well as achieving efficient Pb and Ag enrichment.

STUDY OF THE EFFECT OF SUPERCRITICAL WATER ON SOLID PRODUCTS OBTAINED AFTER CRACKING

One of the possible applications of supercritical water is the conversion of heavy hydrocarbon feedstocks with a high content of resins and asphaltenes. The use of supercritical water makes it possible to reduce the yield of solid products and increase the yield of light fractions. In this work, a comparative analysis of the cracking processes of petroleum residue, asphaltenes and resins isolated from it was carried out in an environment of supercritical water and without water. The experiments were carried out in an autoclave at a temperature of 450 °С and a pressure of up to 47 MPa. Cracking duration – 60 min. Cracking of petroleum residue, as well as its individual components - resins and asphaltenes, in a supercritical water environment - showed a positive effect on conversion; in all experiments, the yield of solid products decreased and the yield of maltenes increased. Solid products were studied using X-ray diffraction and thermogravimetric analysis and scanning electron microscopy. Using X-ray diffraction analysis, the influence of supercritical water on the parameters of the macrostructure was studied. It was determined that cracking with water affects the increase in the distance between saturated fragments of molecules (dr) in the structure of solid cracking products in comparison with products obtained without water. Using scanning electron microscopy, the surface of particles of insoluble cracking products was characterized. Solid products obtained in a supercritical water environment have a porous surface. According to thermal analysis data, it is shown that solid products obtained by cracking in water are characterized by more intense dynamics of sample weight loss and a smaller residue at the final temperature. For citation: Nalgieva Kh.V., Kopytov M.A. Study of the effect of supercritical water on solid products obtained after cracking. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2024. V. 67. N 8. P. 113-120. DOI: 10.6060/ivkkt.20246708.14t.

Peptides En Route from Prebiotic to Biotic Catalysis.

ConspectusIn the quest to understand prebiotic catalysis, different molecular entities, mainly minerals, metal ions, organic cofactors, and ribozymes, have been implied as key players. Of these, inorganic and organic cofactors have gained attention for their ability to catalyze a wide array of reactions central to modern metabolism and frequently participate in these reactions within modern enzymes. Nevertheless, bridging the gap between prebiotic and modern metabolism remains a fundamental question in the origins of life.In this Account, peptides are investigated as a potential bridge linking prebiotic catalysis by minerals/cofactors to enzymes that dominate modern life's chemical reactions. Before ribosomal synthesis emerged, peptides of random sequences were plausible on early Earth. This was made possible by different sources of amino acid delivery and synthesis, as well as their condensation under a variety of conditions. Early peptides and proteins probably exhibited distinct compositions, enriched in small aliphatic and acidic residues. An increase in abundance of amino acids with larger side chains and canonical basic groups was most likely dependent on the emergence of their more challenging (bio)synthesis. Pressing questions thus arise: how did this composition influence the early peptide properties, and to what extent could they contribute to early metabolism?Recent research from our group and colleagues shows that highly acidic peptides/proteins comprising only the presumably "early" amino acids are in fact competent at secondary structure formation and even possess adaptive folding characteristics such as spontaneous refoldability and chaperone independence to achieve soluble structures. Moreover, we showed that highly acidic proteins of presumably "early" composition can still bind RNA by utilizing metal ions as cofactors to bridge carboxylate and phosphoester functional groups. And finally, ancient organic cofactors were shown to be capable of binding to sequences from amino acids considered prebiotically plausible, supporting their folding properties and providing functional groups, which would nominate them as catalytic hubs of great prebiotic relevance.These findings underscore the biochemical plausibility of an early peptide/protein world devoid of more complex amino acids yet collaborating with other catalytic species. Drawing from the mechanistic properties of protein-cofactor catalysis, it is speculated here that the early peptide/protein-cofactor ensemble could facilitate a similar range of chemical reactions, albeit with lower catalytic rates. This hypothesis invites a systematic experimental test.Nonetheless, this Account does not exclude other scenarios of prebiotic-to-biotic catalysis or prioritize any specific pathways of prebiotic syntheses. The objective is to examine peptide availability, composition, and functional potential among the various factors involved in the emergence of early life.

LGG-28. THE ROLE OF REOPERATION IN PEDIATRIC CEREBELLAR PILOCYTIC ASTROCYTOMA

Abstract BACKGROUND Cerebellar pilocytic astrocytomas (cPAs) in childhood have long been recognized to have a good prognosis after total resection but the outcome after incomplete resective surgery remains largely unpredictable with the incidence of radiological progressive disease ranging from 18-100%. Traditionally thought that GTR was required for long-term survival, small residuals were classically resected in a subsequent operation. METHODS We analyzed our Pediatric Low-Grade Glioma (PLGG) database, between 1985 and 2020, and filtered for intracranial pilocytic astrocytomas to determine what clinical or radiological factors precipitated revisional resective surgery in our single quaternary center cohort. RESULTS Using our Pediatric Low-Grade Glioma (PLGG) database, 283 patients were identified to have a histopathological diagnosis of intracranial pilocytic astrocytoma between 1985-2020 of which 202 were within the cerebellum (68.2%). The majority of patients with cerebellar PA were between 1-10 years of age (n=147, 73.5%) without gender predominance (M:F=99:101), usually presenting with 1 lesion (n=197, 98.5%). Gross total resection (GTR) was achieved in 74.5% (n=149) of initial surgeries for cerebellar PA. In patients with NTR or STR, the mean largest diameter of the post-operative residual was 1.1cm (0.2-3.7cm). Seven patients with STR did not require a second resective intervention. In 31 patients the neuro-oncology multidisciplinary team (MDT) recommended a second surgical resection at a mean time interval of 22.9 months (0.13-81.6 months) from the initial surgery. Proportionally, the children who underwent multiple resections were also more likely to receive adjuvant chemo/radiotherapy. Functionally, the children in the multiple operation cohort experienced more complications of therapy including ongoing endocrinopathy, treatment-associated hearing deficit, and neurocognitive deficits. CONCLUSION Residual disease in cPA should be maintained under clinocoradiological surveillance post-operatively with adoption of a more conservative approach when residual disease is not significantly changing over time.

Cigarette butts as a source of phenolic compounds for the environment.

Cigarette butts (CBs) are small residues with mixed composition. Produced in large amounts, their accumulation in the environment has become alarming. It is possible to classify more than 7000 chemical components generated either in the burning process or when distilled from the tobacco. The aim of this work was to describe the rate of release of phenolic compounds from CBs, to determine the content of these compounds in freshly smoked CBs and to monitor the release of phenols from CBs into fresh natural waters. The kinetics of release of selected phenolic compounds (hydroquinone, resorcinol, pyrocatechol, phenol, guaiacol, o-cresol, m-cresol, p-cresol) into water was monitored for 48h. More than 90% of the content was extracted within 10h for all analytes. The phenolic content was determined in the CBs of five different brands. The total content of phenols determined for each sample of freshly smoked CB was 215-861µg/CB. For all CBs analysed, phenol, pyrocatechol and hydroquinone were the most abundant analytes, accounting for up to 75% of the content of all phenols determined. Phenol was the most abundant analyte (64.6-267.8µg/CB) in all analysed samples. The content of pyrocatechol, the second most abundant analyte, was 45.6-221.2µg/CB and the third most abundant analyte was hydroquinone (41.71-157.5µg/CB). Monitoring the release of phenols from CBs into fresh natural waters (river, stream, pond) under steady and slight moving conditions showed that the kinetics of release is not influenced by the type of water. On the contrary, the process of decomposition of the released compounds is influenced by the type of water. The maximum concentrations of individual phenols in CBs extracts were comparable to those determined via laboratory extraction, thus indicating that within 72h, most of the phenolic compounds are released from CBs into natural water. This research provides missing information on the phenolic content in CBs and the rate of release into water. It thus complements previously published information on CBs as a source of environmental contamination.

Combinatorial Optimization Strategies for 3-Fucosyllactose Hyperproduction in Escherichia coli.

3-Fucosyllactose (3-FL), an important fucosylated human milk oligosaccharide in breast milk, offers numerous health benefits to infants. Previously, we metabolically engineered Escherichia coli BL21(DE3) for the in vivo biosynthesis of 3-FL. In this study, we initially optimized culture conditions to double 3-FL production. Competing pathway genes involved in in vivo guanosine 5'-diphosphate-fucose biosynthesis were subsequently inactivated to redirect fluxes toward 3-FL biosynthesis. Next, three promising transporters were evaluated using plasmid-based or chromosomally integrated expression to maximize extracellular 3-FL production. Additionally, through analysis of α1,3-fucosyltransferase (FutM2) structure, we identified Q126 residues as a highly mutable residue in the active site. After site-saturation mutation, the best-performing mutant, FutM2-Q126A, was obtained. Structural analysis and molecular dynamics simulations revealed that small residue replacement positively influenced helical structure generation. Finally, the best strain BD3-A produced 6.91 and 52.1 g/L of 3-FL in a shake-flask and fed-batch cultivations, respectively, highlighting its potential for large-scale industrial applications.

Urban environmental monitoring and health risk assessment introducing a fuzzy intelligent computing model.

To enhance the precision of evaluating the impact of urban environments on resident health, this study introduces a novel fuzzy intelligent computing model designed to address health risk concerns using multi-media environmental monitoring data. Three cities were selected for the study: Beijing (B City), Kunming (K City), and Wuxi (W City), representing high, low, and moderate pollution levels, respectively. The study employs a Fuzzy Inference System (FIS) as the chosen fuzzy intelligent computing model, synthesizing multi-media environmental monitoring data for the purpose of urban health risk assessment. (1) The model reliably estimates health risks across diverse cities and environmental conditions. (2) There is a positive correlation between PM2.5 concentrations and health risks, though the impact of noise levels varies by city. In cities B, K, and W, the respective correlation coefficients are 0.65, 0.55, and 0.7. (3) The Root Mean Square Error (RMSE) values for cities B, K, and W, are 0.0132, 0.0125, and 0.0118, respectively, indicating that the model has high accuracy. The R2 values for the three cities are 0.8963, 0.9127, and 0.9254, respectively, demonstrating the model's high explanatory power. The residual values for the three cities are 0.0087, 0.0075, and 0.0069, respectively, indicating small residuals and demonstrating robustness and adaptability. (4) The model's p-values for the Indoor Air Quality Index (IAQI), Thermal Comfort Index (TCI), and Noise Pollution Index (NPI) all satisfy p < 0.05 for the three cities, affirming the model's credibility in estimating health risks under varied urban environments. These results showcase the model's ability to adapt to diverse geographical conditions and aid in the accurate assessment of existing risks in urban settings. This study significantly advances environmental health risk assessment by integrating multidimensional data, enhancing the formulation of comprehensive environmental protection and health management strategies, and providing scientific support for sustainable urban planning.

QSAR Reveals Decreased Lipophilicity of Polar Residues Determines the Selectivity of Antimicrobial Peptide Activity.

Antimicrobial resistance has increased rapidly, causing daunting morbidity and mortality rates worldwide. Antimicrobial peptides (AMPs) have emerged as promising alternatives to traditional antibiotics due to their broad range of targets and low tendency to elicit resistance. However, potent antimicrobial activity is often accompanied by excessive cytotoxicity toward host cells, leading to a halt in AMP therapeutic development. Here, we present multivariate analyses that correlate 28 peptide properties to the activity and toxicity of 46 diverse African-derived AMPs and identify the negative lipophilicity of polar residues as an essential physiochemical property for selective antimicrobial activity. Twenty-seven active AMPs are identified, of which the majority are of scorpion or frog origin. Of these, thirteen are novel with no previously reported activities. Principal component analysis and quantitative structure-activity relationships (QSAR) reveal that overall hydrophobicity, lipophilicity, and residue side chain surface area affect the antimicrobial and cytotoxic activity of an AMP. This has been well documented previously, but the present QSAR analysis additionally reveals that a decrease in the lipophilicity, contributed by those amino acids classified as polar, confers selectivity for a peptide to pathogen over mammalian cells. Furthermore, an increase in overall peptide charge aids selectivity toward Gram-negative bacteria and fungi, while selectivity toward Gram-positive bacteria is obtained through an increased number of small lipophilic residues. Finally, a conservative increase in peptide size in terms of sequence length and molecular weight also contributes to improved activity without affecting toxicity. Our findings suggest a novel approach for the rational design or modification of existing AMPs to increase pathogen selectivity and enhance therapeutic potential.

Possibility and quality assessment in seafloor modeling relative to the sea surface using hybrid data

Possibility and quality assessment in seafloor modeling relative to the sea surface using hybrid data

A hybrid approach combining mechanism-guided data augmentation and machine learning for biomass pyrolysis

Process accuracy modelling requires comprehensive thermodynamics and kinetic knowledge, which is not feasible for complex biomass pyrolysis. Here, we propose a hybrid modelling strategy that combines mechanism-guided modelling (Aspen Plus) with data-driven machine learning (ML) models to accurately predict biomass pyrolysis products. Specifically, we establish the pyrolysis equilibrium model based on the first principles and Gibbs free energy minimization approach; then, the equilibrium model is leveraged to augment data by selecting points with smaller residuals; finally, the augmented data and experimental data serve as input for the ML models training. The results revealed that the hybrid model exhibited superior performance, with average R2 and MAPE values of 0.981 and 0.266, respectively, for predicting biochar yield and heating value. Conclusively, this work introduces new insight and strategy to accelerate the engineered application of bioenergy via modelling biomass pyrolysis and screening biomass.

Exploring Impact of Protein Sequence Local Information to Predict Enzyme-Ligand Binding Residues Using Machine Learning

Enzymes are important for various biochemical reactions in living cells. In drug discovery and drug design, identifying small molecule binding residues in enzymes is a crucial step. Although, identifying ligand-binding residues using computational techniques are improving, accurate prediction remains difficult. Therefore, to address this problem, we used the sequence local information, i.e., sequence neighbors around the target residue, and transformed it into two ways. First, into a Chaos Game Representation (CGR) to form a feature vector and train with an Extreme Gradient Boosting classifier (XGB) and second into a non-numeric feature space and apply the conditional probabilistic based approach. Our results suggest that local protein sequence information along with global information can help to develop precise predictors for small molecule binding residues. We hope our observations could facilitate the researchers to investigate more into enzyme-ligand interaction and drug discovery.

The role of reoperation in pediatric cerebellar pilocytic astrocytoma.

Cerebellar pilocytic astrocytomas (cPAs) in childhood have long been recognized to have a good prognosis after total resection, but the outcome after incomplete resective surgery remains largely unpredictable, with the incidence of radiological progressive disease ranging from 18% to 100%. It has been traditionally thought that gross-total resection was required for long-term survival, and small residuals were classically resected in a subsequent operation. The authors analyzed their pediatric low-grade glioma (PLGG) database for cases treated between 1985 and 2020 and filtered for intracranial PAs, to determine what clinical or radiological factors precipitated revisional resective surgery in their single quaternary care center cohort. Using the pediatric low-grade glioma database, 283 patients were identified to have a histopathological diagnosis of intracranial PA between 1985 and 2020, of which 200 lesions were within the cerebellum (70.7%). The majority of patients with cPA were between 1 and 10 years of age (n = 145, 72.5%) without gender predominance (M/F = 99:101), usually presenting with 1 lesion (n = 197, 98.5%). Gross-total resection was achieved in 74.5% (n = 149) of initial surgeries for cPA. In patients with subtotal resection, the mean largest diameter of the postoperative residual tumor was 1.06 cm (range 0-2.95 cm). Seven patients with subtotal resection did not require a second resective intervention. In 31 patients the neuro-oncology multidisciplinary team recommended a second resection at a mean time interval of 22.9 months (range 0.13-81.6 months) from the initial surgery. Proportionally, the children who underwent multiple resections were also more likely to receive adjuvant chemo/radiotherapy. Functionally, the children in the multiple operation cohort experienced more complications of therapy including ongoing endocrinopathy, treatment-associated hearing deficit, and neurocognitive deficits. Residual disease in cPA should be maintained under clinicocoradiological surveillance postoperatively with adoption of a more conservative approach when residual disease is not significantly changing over time.