Control of Halogen Atom in Inorganic Metal-Halide Perovskites Enables Large Piezoelectricity for Electromechanical Energy Generation.

Regulating the strain of inorganic perovskites has emerged as a critical approach to control their electronic and optical properties. Here, an alternative strategy to further control the piezoelectric properties by substituting the halogen atom (I/Br) in the CsPbX3 perovskite (X = Cl, Br) structure is adopted. A series of piezoelectric materials with excellent piezoelectric coefficients (d33 ) are unveiled. Iodine-incorporated CsPbBr2 I demonstrates the record intrinsic piezoelectric response (d33 ≈47 pC N-1 ) among all inorganic metal halide perovskites. This leads to an excellent electrical output power of ≈ 0.375 mW (24.8 µW cm-2 N-1 ) in the piezoelectric energy generator (PEG) which is higher than those of the pristine/mixed perovskite references with CsPbX3 (X = I, Br, Cl). With its structural phase remaining unchanged, the strained CsPbBr2 I retains its superior piezoelectricity in both thin film and nanocrystal powder forms, further demonstrating its repeatability and versatility of applications. The origin of high piezoelectricity is found to be due to halogen-induced anisotropic lattice strain in the unit-cell along the c-axis, and octahedral distortion. This study reveals an avenue to design new piezoelectric materials by modifying their halide constituents and paves the way to design efficient PEGs for improved electromechanical energy conversion.

Factors affecting depression among married adults: a gender-based household cross-sectional study.

BACKGROUND: Depression is a common mental health problem all over the world including Bangladesh. World Health Organization included it in the Mental Health Gap Action Programme as one of its priority conditions. Research on this issue is scanty in Bangladesh. Therefore, we designed to a gender-based household study on associated factors of depression among married adults in Rajshahi City of Bangladesh. METHODS: We conducted this household cross-sectional study from August 01 to October 31, 2019. A total of 708 married adults currently living together in Rajshahi City were recruited for this study. We applied a multi-stage random sampling technique for selecting samples and used a semi-structured questionnaire to collect necessary information from them. The Patient Health Questionnaire-9 was used for measuring depression and frequency distribution and binary logistic regression model were used for data analysis. RESULTS: The prevalence of depression (moderate to severe) was 14.4% (95% CI: 11.9-16.9) among married adults, and females (21.2%, 95% CI: 17.2-25.4) suffered more than males (7.6%, 95% CI: 4.8-10.5). A multiple binary logistic regression model established four main factors of depression among married females: (i) multiple marriage [AOR = 19.982; 95% CI: 10.081-39.610; p < 0.01]; (ii) poor relationship with spouse [AOR = 2.175; 95%CI: 1.068-4.428; p < 0.05]; (iii) chronic medical comorbidity [AOR = 1.876; 95%CI: 1.009-2.626; p < 0.05]; and (iv) 7-12 years duration of conjugal life [AOR = 2.091, 1.009-4.334; p < 0.05]. Two main factors of depression among married males were (i) multiple marriage [AOR = 24.605; 95% CI: 20.228-40.402; p < 0.01] and hard work [AOR = 4.358; 95%CI: 1.109-7.132; p < 0.05]. CONCLUSION: The prevalence of depression was significantly high among the study population, and females were the most vulnerable group. The concerned authorities and stakeholders should take appropriate measures to manage the problem with special focus on the risk factors and the vulnerable groups.

Occurrences, sources, fate and impacts of plastic on aquatic organisms and human health in global perspectives: What Bangladesh can do in future?

Bangladesh is not an exception to the growing global environmental problem of plastic pollution. Plastics have been deemed a blessing for today's world thanks to their inexpensive production costs, low weight, toughness, and flexibility, but poor biodegradability and massive misuse of plastics are to blame for widespread contamination of the environmental components. Plastic as well as microplastic pollution and its adverse consequences have attracted significant investigative attention all over the world. Plastic pollution is a rising concern in Bangladesh, but scientific studies, data, and related information are very scarce in numerous areas of the plastic pollution problem. The current study examined the effects of plastic and microplastic pollution on the environment and human health, and it examined Bangladesh's existing knowledge of plastic pollution in aquatic ecosystems in light of the rapidly expanding international research in this field. We also made an effort to investigate the current shortcomings in Bangladesh's assessment of plastic pollution. This study proposed several management approaches to the persistent plastic pollution problem by analyzing studies from industrialized and emerging countries. Finally, this work pushed investigators to investigate Bangladesh's plastic contamination thoroughly and develop guidelines and policies to address the issue.

EISA-Score: Element Interactive Surface Area Score for Protein-Ligand Binding Affinity Prediction.

Molecular surface representations have been advertised as a great tool to study protein structure and functions, including protein-ligand binding affinity modeling. However, the conventional surface-area-based methods fail to deliver a competitive performance on the energy scoring tasks. The main reason is the lack of crucial physical and chemical interactions encoded in the molecular surface generations. We present novel molecular surface representations embedded in different scales of the element interactive manifolds featuring the dramatically dimensional reduction and accurately physical and biological properties encoders. Those low-dimensional surface-based descriptors are ready to be paired with any advanced machine learning algorithms to explore the essential structure-activity relationships that give rise to the element interactive surface area-based scoring functions (EISA-score). The newly developed EISA-score has outperformed many state-of-the-art models, including various well-established surface-related representations, in standard PDBbind benchmarks.

Investigation of the New Inhibitors by Sulfadiazine and Modified Derivatives of α-D-glucopyranoside for White Spot Syndrome Virus Disease of Shrimp by In Silico: Quantum Calculations, Molecular Docking, ADMET and Molecular Dynamics Study.

The α-D-glucopyranoside and its derivatives were as the cardinal investigation for developing an effective medication to treat the highest deadly white spot syndrome virus (WSSV) diseases in Shrimp. In our forthcoming work, both computational tools, such as molecular docking, quantum calculations, pharmaceutical kinetics, ADMET, and their molecular dynamics, as well as the experimental trial against WSSV, were executed to develop novel inhibitors. In the beginning, molecular docking was carried out to determine inhibitors of the four targeted proteins of WSSV (PDB ID: 2ED6, 2GJ2, 2GJI, and 2EDM), and to determine the binding energies and interactions of ligands and proteins after docking. The range of binding affinity was found to be between -5.40 and -7.00 kcal/mol for the protein 2DEM, from -5.10 to 6.90 kcal/mol for the protein 2GJ2, from -4.70 to -6.2 kcal/mol against 2GJI, and from -5.5 kcal/mol to -6.6 kcal/mol for the evolved protein 2ED6 whereas the L01 and L03 display the highest binding energy in the protein 2EDM. After that, the top-ranked compounds (L01, L02, L03, L04, and L05), based on their high binding energies, were tested for molecular dynamics (MD) simulations of 100 ns to verify the docking validation and stability of the docked complex by calculating the root mean square deviation (RMSD) and root mean square fluctuation (RMSF). The molecules with the highest binding energy were then picked and compared to the standard drugs that were been applied to fish experimentally to evaluate the treatment at various doses. Consequently, approximately 40-45% cure rate was obtained by applying the dose of oxytetracycline (OTC) 50% with vitamin C with the 10.0 g/kg feed for 10 days. These drugs (L09 to L12) have also been executed for molecular docking to compare with α-D-glucopyranoside and its derivatives (L01 to L08). Next, the evaluation of pharmacokinetic parameters, such as drug-likeness and Lipinski's principles; absorption; distribution; metabolism; excretion; and toxicity (ADMET) factors, were employed gradually to further evaluate their suitability as inhibitors. It was discovered that all ligands (L01 to L12) were devoid of hepatotoxicity, and the AMES toxicity excluded L05. Additionally, all of the compounds convey a significant aqueous solubility and cannot permeate the blood-brain barrier. Moreover, quantum calculations based on density functional theory (DFT) provide the most solid evidence and testimony regarding their chemical stability, chemical reactivity, biological relevance, reactive nature and specific part of reactivity. The computational and virtual screenings for in silico study reveals that these chosen compounds (L01 to L08) have conducted the inhibitory effect to convey as a possible medication against the WSSV than existing drugs (L09, L10, L11 and L12) in the market. Next the drugs (L09, L10, L11 and L12) have been used in trials.

Acute malnutrition and its determinants of preschool children in Bangladesh: gender differentiation.

BACKGROUND: Children acute malnutrition (AM) is a global public health concern, especially in low and middle income countries. AM is associated with multiple physiological vulnerabilities, including immune dysfunction, enteric barrier disruption, gut microbiome dysbiosis, and essential nutrient deficits. This study aimed to determine the prevalence of AM and its associated factors among preschool children in Rajshahi district, Bangladesh. METHODS: This cross-sectional study was conducted from October to December, 2016. Children acute malnutrition was assessed using mid-upper arm circumference. Multiple binary logistic regression analyses were employed to determine the associated factors after adjusting the effect of independent factors of children AM. RESULT: The prevalence of AM amongst preschool children was 8.7%, among them 2.2 and 6.5% were severe acute malnutrition and moderate acute malnutrition, respectively. Z-proportional test demonstrated that the difference in AM between girls (11.6) and boys (5.9%) was significant (p < 0.05). Children AM was associated with being: (i) children aged 6-23 months (aOR = 2.29, 95% CI: 1.20-4.37; p < 0.05), (ii) early childbearing mothers' (age < 20 years) children (aOR = 3.06, 95% CI: 1.08-8.66; p < 0.05), (iii) children living in poor family (aOR = 3.08, 95% CI: 1.11-8.12; p < 0.05), (iv) children living in unhygienic latrine households (aOR = 2.81, 95% CI: 1.52-5.09; p < 0.01), (v) Hindu or other religion children (aOR = 0.42, 95% CI: 0.19-0.92; p < 0.05). CONCLUSION: The prevalence of AM was high among these preschool children. Some modifiable factors were associated with AM of preschool children. Interventions addressing social mobilization and food security could be an effective way to prevent acute malnutrition among children in Bangladesh.

Design and Numerical Analysis of a Graphene-Coated SPR Biosensor for Rapid Detection of the Novel Coronavirus.

In this paper, a highly sensitive graphene-based multiple-layer (BK7/Au/PtSe2/Graphene) coated surface plasmon resonance (SPR) biosensor is proposed for the rapid detection of the novel Coronavirus (COVID-19). The proposed sensor was modeled on the basis of the total internal reflection (TIR) technique for real-time detection of ligand-analyte immobilization in the sensing region. The refractive index (RI) of the sensing region is changed due to the interaction of different concentrations of the ligand-analyte, thus impacting surface plasmon polaritons (SPPs) excitation of the multi-layer sensor interface. The performance of the proposed sensor was numerically investigated by using the transfer matrix method (TMM) and the finite-difference time-domain (FDTD) method. The proposed SPR biosensor provides fast and accurate early-stage diagnosis of the COVID-19 virus, which is crucial in limiting the spread of the pandemic. In addition, the performance of the proposed sensor was investigated numerically with different ligand-analytes: (i) the monoclonal antibodies (mAbs) as ligand and the COVID-19 virus spike receptor-binding domain (RBD) as analyte, (ii) the virus spike RBD as ligand and the virus anti-spike protein (IgM, IgG) as analyte and (iii) the specific probe as ligand and the COVID-19 virus single-standard ribonucleic acid (RNA) as analyte. After the investigation, the sensitivity of the proposed sensor was found to provide 183.33°/refractive index unit (RIU) in SPR angle (θSPR) and 833.33THz/RIU in SPR frequency (SPRF) for detection of the COVID-19 virus spike RBD; the sensitivity obtained 153.85°/RIU in SPR angle and 726.50THz/RIU in SPRF for detection of the anti-spike protein, and finally, the sensitivity obtained 140.35°/RIU in SPR angle and 500THz/RIU in SPRF for detection of viral RNA. It was observed that whole virus spike RBD detection sensitivity is higher than that of the other two detection processes. Highly sensitive two-dimensional (2D) materials were used to achieve significant enhancement in the Goos-Hänchen (GH) shift detection sensitivity and plasmonic properties of the conventional SPR sensor. The proposed sensor successfully senses the COVID-19 virus and offers additional (1 + 0.55) × L times sensitivity owing to the added graphene layers. Besides, the performance of the proposed sensor was analyzed based on detection accuracy (DA), the figure of merit (FOM), signal-noise ratio (SNR), and quality factor (QF). Based on its performance analysis, it is expected that the proposed sensor may reduce lengthy procedures, false positive results, and clinical costs, compared to traditional sensors. The performance of the proposed sensor model was checked using the TMM algorithm and validated by the FDTD technique.

S-allyl Cysteine Enhances Testosterone Production in Mice and Mouse Testis-Derived I-10 Cells.

Hypogonadism, associated with low levels of testosterone synthesis, has been implicated in several diseases. Recently, the quest for natural alternatives to prevent and treat hypogonadism has gained increasing research interest. To this end, the present study explored the effect of S-allyl cysteine (SAC), a characteristic organosulfur compound in aged-garlic extract, on testosterone production. SAC was administered at 50 mg/kg body weight intraperitoneally into 7-week-old BALB/c male mice in a single-dose experiment. Plasma levels of testosterone and luteinizing hormone (LH) and testis levels of proteins involved in steroidogenesis were measured by enzymatic immunoassay and Western blot, respectively. In addition, mouse testis-derived I-10 cells were also used to investigate the effect of SAC on steroidogenesis. In the animal experiment, SAC significantly elevated testosterone levels in both the plasma and the testis without changing the LH level in plasma and increased phosphorylated protein kinase A (p-PKA) levels. Similar results were also observed in I-10 cells. The findings demonstrating the increasing effect of SAC on p-PKA and mRNA levels of Cyp11a suggest that SAC increases the testosterone level by activating the PKA pathway and could be a potential target for hypogonadism therapeutics.

Knowledge of tuberculosis among female sex workers in Rajshahi city, Bangladesh: a cross sectional study.

BACKGROUND: Tuberculosis (TB) is a major public health problem in developing countries like Bangladesh. Female sex workers (FSWs) and their clients are active sources for spreading TB. The purpose of this study was to assess the knowledge of TB among FSWs in Rajshahi city, Bangladesh. METHODS: It was a cross-sectional study with a sample size of 225 FSWs. The knowledge on TB was measured by six different questions. Chi-square test and multinomial logistic regression model were used in this study to find the associated factors of lack of general knowledge on TB among FSWs. RESULTS: Out of 225 FSWs, 43.1, 34.7 and 22.2% came from urban, rural and slum areas respectively. More than 41% FSWs perceived that TB is a non-communicable disease. A large number of FSWs (76.4%) did not know the spread of TB. It was found that more than 90% FSWs did not have knowledge on latent TB. The χ2-test demonstrated that FSWs' education, monthly family income, age, currently marital status and sex trading place were significantly associated with their knowledge on TB. A remarkable number of FWSs (42.2%) had poor knowledge on TB. It was found that comparatively higher educated FWSs were more likely to have good or fair knowledge on TB than lower educated ones (p < 0.01). CONCLUSIONS: This study revealed that near to half of FSWs in Rajshahi city, Bangladesh had poor knowledge on TB. Public health authorities should pay due attention and adopt policy for increasing the knowledge on TB among FSWs to reduce the incidence of TB in Bangladesh. Subsequently, advocacy, communication for social mobilization program is very urgent.

Genotypic Selection in Spatially Heterogeneous Producer-Grazer Systems Subject to Stoichiometric Constraints.

Various environmental conditions may exert selection pressures leading to adaptation of stoichiometrically important traits, such as organismal nutritional content or growth rate. We use theoretical approaches to explore the connections between genotypic selection and ecological stoichiometry in spatially heterogeneous environments. We present models of a producer and two grazing genotypes with different stoichiometric phosphorus/carbon ratios under spatially homogenous and heterogeneous conditions. Numerical experiments predict that selection of a single genotype, co-persistence of both genotypes, and extinction are possible outcomes depending on environmental conditions. Our results indicated that in spatially homogenous settings, co-persistence of both genotypes can occur when population dynamics oscillate on limit cycles near a key stoichiometric threshold on food quality. Under spatially heterogeneous settings, dynamics are more complex, where co-persistence is observed on limit cycles, as well as stable equilibria.

Characterization of burn wound healing gel prepared from human amniotic membrane and Aloe vera extract.

BACKGROUND: Skin burn wound is a notable medical burden worldwide. Rapid and effective treatment of burnt skin is vital to fasten wound closure and healing properly. Amniotic graft and Aloe vera are widely used as wound managing biomaterials. Sophisticated processing, high cost, availability, and the requirement of medics for transplantation limit the application of amnion grafts. We aim to prepare a novel gel from amnion combined with the Aloe vera extract for burn wound healing which overcome the limitations of graft. METHODS: Two percent human amniotic membrane (AM), Aloe vera (AV) and AM+AV gels were prepared. In vitro cytotoxicity, biocompatibility, cell attachment, proliferation, wound healing scratch assays were performed in presence of the distinct gels. After skin irritation study, second-degree burns were induced on dorsal region of Wistar rats; and gels were applied to observe the healing potential in vivo. Besides, macroscopical measurement of wound contraction and re-epithelialization; gel treated skin was histologically investigated by Hematoxylin and eosin (H&E) staining. Finally, quantitative assessment of angiogenesis, inflammation, and epithelialization was done. RESULTS: The gels were tested to be non-cytotoxic to nauplii and compatible with human blood and skin cells. Media containing 500 µg/mL AM+AV gel were observed to promote HaCaT and HFF1 cells attachment and proliferation. In vitro scratch assay demonstrated that AM+AV significantly accelerated wound closure through migration of HaCaT cells. No erythema and edema were observed in skin irritation experiments confirming the applicability of the gels. AV and AM+AV groups showed significantly accelerated wound closure through re-epithelialization and wound contraction with P < 0.01. Macroscopically, AM and AM+AV treated wound recovery rates were 87 and 90% respectively with P < 0.05. Histology analysis revealed significant epitheliazation and angiogenesis in AM+AV treated rats compared to control (P < 0.05). AM+AV treated wounds had thicker regenerated epidermis, increased number of blood vessels, and greater number of proliferating keratinocytes within the epidermis. CONCLUSION: We demonstrated that a gel consisting of a combination of amnion and Aloe vera extract has high efficacy as a burn wound healing product. Amniotic membrane combined with the carrier Aloe vera in gel format is easy to produce and to apply.

Salt Tolerance Improvement in Rice through Efficient SNP Marker-Assisted Selection Coupled with Speed-Breeding.

Salinity critically limits rice metabolism, growth, and productivity worldwide. Improvement of the salt resistance of locally grown high-yielding cultivars is a slow process. The objective of this study was to develop a new salt-tolerant rice germplasm using speed-breeding. Here, we precisely introgressed the hst1 gene, transferring salinity tolerance from "Kaijin" into high-yielding "Yukinko-mai" (WT) rice through single nucleotide polymorphism (SNP) marker-assisted selection. Using a biotron speed-breeding technique, we developed a BC3F3 population, named "YNU31-2-4", in six generations and 17 months. High-resolution genotyping by whole-genome sequencing revealed that the BC3F2 genome had 93.5% similarity to the WT and fixed only 2.7% of donor parent alleles. Functional annotation of BC3F2 variants along with field assessment data indicated that "YNU31-2-4" plants carrying the hst1 gene had similar agronomic traits to the WT under normal growth condition. "YNU31-2-4" seedlings subjected to salt stress (125 mM NaCl) had a significantly higher survival rate and increased shoot and root biomasses than the WT. At the tissue level, quantitative and electron probe microanalyzer studies indicated that "YNU31-2-4" seedlings avoided Na+ accumulation in shoots under salt stress. The "YNU31-2-4" plants showed an improved phenotype with significantly higher net CO2 assimilation and lower yield decline than WT under salt stress at the reproductive stage. "YNU31-2-4" is a potential candidate for a new rice cultivar that is highly tolerant to salt stress at the seedling and reproductive stages, and which might maintain yields under a changing global climate.

An overview of distributed microgrid state estimation and control for smart grids.

Given the significant concerns regarding carbon emission from the fossil fuels, global warming and energy crisis, the renewable distributed energy resources (DERs) are going to be integrated in the smart grid. This grid can spread the intelligence of the energy distribution and control system from the central unit to the long-distance remote areas, thus enabling accurate state estimation (SE) and wide-area real-time monitoring of these intermittent energy sources. In contrast to the traditional methods of SE, this paper proposes a novel accuracy dependent Kalman filter (KF) based microgrid SE for the smart grid that uses typical communication systems. Then this article proposes a discrete-time linear quadratic regulation to control the state deviations of the microgrid incorporating multiple DERs. Therefore, integrating these two approaches with application to the smart grid forms a novel contributions in green energy and control research communities. Finally, the simulation results show that the proposed KF based microgrid SE and control algorithm provides an accurate SE and control compared with the existing method.

Research and application of polypropylene: a review.

Polypropylene (PP) is a versatile polymer with numerous applications that has undergone substantial changes in recent years, focusing on the demand for next-generation polymers. This article provides a comprehensive review of recent research in PP and its advanced functional applications. The chronological development and fundamentals of PP are mentioned. Notably, the incorporation of nanomaterial like graphene, MXene, nano-clay, borophane, silver nanoparticles, etc., with PP for advanced applications has been tabulated with their key features and challenges. The article also conducts a detailed analysis of advancements and research gaps within three key forms of PP: fiber, membrane, and matrix. The versatile applications of PP across sectors like biomedical, automotive, aerospace, and air/water filtration are highlighted. However, challenges such as limited UV resistance, bonding issues, and flammability are noted. The study emphasizes the promising potential of PP while addressing unresolved concerns, with the goal of guiding future research and promoting innovation in polymer applications.

Identification of most representative hub-genes for diagnosis, prognosis, and therapies of hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths globally. To reduce HCC-related mortality, early diagnosis and therapeutic improvement are essential. Hub differentially expressed genes (HubGs) may serve as potential diagnostic and prognostic biomarkers, also offering therapeutic targets for precise therapies. Therefore, we aimed to identify top-ranked hub genes for the diagnosis, prognosis, and therapy of HCC. METHODS: Through a systematic literature review, 202 HCC-related HubGs were derived from 59 studies, yet consistent detection across these was lacking. Then, we identified top-ranked HubGs (tHubGs) by integrated bioinformatics analysis, highlighting their functions, pathways, and regulators that might be more representative of the diagnosis, prognosis, and therapies of HCC. RESULTS: In this study, eight HubGs (CDK1, AURKA, CDC20, CCNB2, TOP2A, PLK1, BUB1B, and BIRC5) were identified as the tHubGs through the protein-protein interaction (PPI) network and survival analysis. Their differential expression in different stages of HCC, validated using The Cancer Genome Atlas (TCGA) Program database, suggests their potential as early HCC markers. The enrichment analyses revealed some important roles in HCC-related biological processes (BPs), molecular functions (MFs), cellular components (CCs), and signaling pathways. Moreover, the gene regulatory network analysis highlighted key transcription factors (TFs) and microRNAs (miRNAs) that regulate these tHubGs at transcriptional and post-transcriptional. Finally, we selected three drugs (CD437, avrainvillamide, and LRRK2-IN-1) as candidate drugs for HCC treatment as they showed strong binding with all of our proposed and published protein receptors. CONCLUSIONS: The findings of this study may provide valuable resources for early diagnosis, prognosis, and therapies for HCC.

Comprehensive Assessment of the Genotype-Environment Interaction and Yield Stability of Boro Rice Genotypes under Four Environments in Bangladesh Using AMMI Analysis.

Yield stability, alongside high yield potential and broad adaptation to various agroclimatic environments, is a key objective for rice breeders aiming to ensure food security. This study aimed to explore the most suitable and stable Boro rice genotypes for Bangladesh. Ten Boro rice genotypes underwent testing in four environments during the 2022 Boro season to investigate genotype-environment interaction (GEI) and yield stability performance. The experiment utilized three replications of a completely randomized block design. Yield stability performance was assessed through combined analysis and the additive main effects and multiplicative interaction (AMMI) model. The combined ANOVA revealed that the environment explained 10.23%, while GEI accounted for 9.17%, and the genotypes captured 80.60% of the variance, significantly impacting grain yield. Significance was observed in the environment, genotype main effects, and GEI. Analysis indicated that BRRI dhan 68 yielded the highest (6,754 kg·ha-1) and BRRI dhan 88 the lowest (5,620 kg·ha-1) among the investigated genotypes. In addition, genotypes BRRI dhan 84, BRRI dhan 81, and BRRI dhan 67 exhibited the highest grain yields. The Rangpur environment demonstrated considerable stability across the four environments with a high mean value of grain yield (7,206 kg·ha-1). Therefore, the AMMI model emerges as a valuable tool for identifying the most suitable and stable Boro rice genotypes with high-yielding potential across various regions in Bangladesh, as well as under diverse conditions.

Geometric graph learning with extended atom-types features for protein-ligand binding affinity prediction.

Understanding and accurately predicting protein-ligand binding affinity are essential in the drug design and discovery process. At present, machine learning-based methodologies are gaining popularity as a means of predicting binding affinity due to their efficiency and accuracy, as well as the increasing availability of structural and binding affinity data for protein-ligand complexes. In biomolecular studies, graph theory has been widely applied since graphs can be used to model molecules or molecular complexes in a natural manner. In the present work, we upgrade the graph-based learners for the study of protein-ligand interactions by integrating extensive atom types such as SYBYL and extended connectivity interactive features (ECIF) into multiscale weighted colored graphs (MWCG). By pairing with the gradient boosting decision tree (GBDT) machine learning algorithm, our approach results in two different methods, namely sybylGGL-Score and ecifGGL-Score. Both of our models are extensively validated in their scoring power using three commonly used benchmark datasets in the drug design area, namely CASF-2007, CASF-2013, and CASF-2016. The performance of our best model sybylGGL-Score is compared with other state-of-the-art models in the binding affinity prediction for each benchmark. While both of our models achieve state-of-the-art results, the SYBYL atom-type model sybylGGL-Score outperforms other methods by a wide margin in all benchmarks. Finally, the best-performing SYBYL atom-type model is evaluated on two test sets that are independent of CASF benchmarks.

Geometric Graph Learning to Predict Changes in Binding Free Energy and Protein Thermodynamic Stability upon Mutation.

Accurate prediction of binding free energy changes upon mutations is vital for optimizing drugs, designing proteins, understanding genetic diseases, and cost-effective virtual screening. While machine learning methods show promise in this domain, achieving accuracy and generalization across diverse data sets remains a challenge. This study introduces Geometric Graph Learning for Protein-Protein Interactions (GGL-PPI), a novel approach integrating geometric graph representation and machine learning to forecast mutation-induced binding free energy changes. GGL-PPI leverages atom-level graph coloring and multiscale weighted colored geometric subgraphs to capture structural features of biomolecules, demonstrating superior performance on three standard data sets, namely, AB-Bind, SKEMPI 1.0, and SKEMPI 2.0 data sets. The model's efficacy extends to predicting protein thermodynamic stability in a blind test set, providing unbiased predictions for both direct and reverse mutations and showcasing notable generalization. GGL-PPI's precision in predicting changes in binding free energy and stability due to mutations enhances our comprehension of protein complexes, offering valuable insights for drug design endeavors.

Development and characterization of natural sourced bioplastic for food packaging applications.

Climate change and increased pollution caused by traditional petrochemical plastics made the biodegradable environment-friendly plastic (bioplastic) research more popular. Bioplastics can be manufactured from natural renewable ingredients and used as food packaging material without harming the environment. This research work focuses on developing bioplastic films from natural ingredients such as starch of tamarind seeds, and berry seeds, with licorice root. Attention has been paid to characterizing the material by biodegradability, mechanical testing, Fourier Transformed Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), antimicrobial analysis tests. Phenolic compounds present in the berry seeds starch increased the soil biodegradability as well as the mechanical and thermal properties of the bioplastic films. The FTIR spectra confirmed the presence of various bio-molecules. Improved antimicrobial performance is also obtained. The results of this research confirm that the prepared bioplastic samples can be used in packaging applications.