bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ionic surfactants of different dipole moments as anti-solvent additives for air-processing MAPbI3−xClx perovskite thin films
Authors: Camacho-Cáceres Jaquelina , Millán-Franco Mario A. , Mejía-Vázquez Melvia Carinne , Arias-Ramos Carlos Fabián , Corpus-Mendoza Asiel N. , Rodríguez-Rivera Mario A. , Nicho María Elena , Sotelo-Lerma Mérida , Hu Hailin 
Published: December 2023

AbstractThree ionic surfactants, didodecyldimethylammonium bromide (DDABr), sodium lauryl ether sulfate (NaLES) and sodium lauryl sulfate (NaLS), with different dipole moment values: 0.907, 17 and 212 Debye, respectively, have been used as anti-solvent additives to remove the moisture from perovskite precursor solutions. The three additives impact in different ways on the crystallinity, wettability and morphology of perovskite thin films, as well as on the stability and efficiency of air-processed perovskite solar cells (PSCs). The hydrophobic groups of the additives at the surface of perovskite thin films help to increase the stability of PSCs, especially DDABr of the lowest dipole moment. On the other hand, NaLES, of the highest dipole moment, is the most efficient to extract moisture from the perovskite precursor coatings, increasing the average power conversion efficiency (PCE) of NaLES-based PSCs from 16.16 ± 0.94% to 17.21 ± 0.32% in comparison with that of the reference. Furthermore, the synergy between NaLES and the perovskite precursor additive, KI, achieves the best photovoltaic performance of the PSCs, leading to an average PCE of 17.42% and the best PCE of 18.75%. It is concluded that ionic surfactants of different dipole moments are good candidates as anti-solvent additives to improve the efficiency and stability of air-processed PSCs.
Polymorphisms and expressions of ADSL, MC4R and CAPN1 genes and their effects on economic traits in Egyptian chicken breeds
Authors: Aboelhassan Dalia M. , Darwish Hassan R. , Mansour Hayam , Abozaid Hesham , Ghaly Inas S. , Radwan Hasnaa A. , Hassan Eman R. , Farag Ibrahim M. 
Published: December 2023

Abstract
In recent years, strategic plans for poultry production have emphasized quantitative traits, particularly body weight and carcass traits (meat yield), in response to overpopulation challenges. Candidate genes such as adenylosuccinate lyase (ADSL), melanocortin-4-receptor (MC4R), and calpain 1 (CAPN1) have played vital roles in this context due to their associations with muscle growth and body composition. This study aims to investigate the influence of polymorphisms and gene expressions of the aforementioned genes on body weight (BW), growth rate (GR), breast weight (BrW), and thigh weight (TW) across four distinct chicken breeds: Fayoumi, Matrouh, Mamourah, and Leghorn. The use of PCR-SSCP analysis revealed genetic polymorphisms through the identification of various patterns (genotypes) within the three examined genes. The ADSL, MC4R, and CAPN1 genes exhibited five, three, and two different genotypes, respectively. These polymorphisms displayed promising connections with enhancing economically significant production traits, particularly BW, BrW and TW. Furthermore, gene expression analyses were conducted on breast and thigh tissues obtained from the chicken breeds at 60 days of age, where ADSL and MC4R exhibited a noteworthy up-regulation in Fayoumi and Matrouh breeds, and down-regulation in Mamourah and Leghorn. In contrast, CAPN1 expression decreased across most breeds with a slight increase noted in Fayoumi breed. In conclusion, this investigation underscores the substantial impact of ADSL, MC4R, and CAPN1 genes on economically important production traits within Egyptian domestic chicken breeds. Consequently, these genes emerge as significant molecular markers, holding potential utility in avian selection and breeding programs aimed at enhancing productive performance.
Pathological complete response of hepatocellular carcinoma confirmed by conversion hepatectomy following atezolizumab plus bevacizumab therapy: a case report and literature review
Authors: Sato Shun , Aoki Taku , Matsumoto Takatsugu , Shiraki Takayuki , Mori Shozo , Iso Yukihiro , Nemoto Takehiko , Onishi Toshihiko , Iijima Makoto , Ishida Kazuyuki 
Published: December 2023

AbstractThe combination regimen of atezolizumab plus bevacizumab (Atezo/Bev) is currently used as first-line treatment in patients with unresectable hepatocellular carcinoma. Herein, we report a rare case of curative hepatic resection performed as conversion surgery in a patient with intermediate-stage hepatocellular carcinoma following preoperative Atezo/Bev therapy. After five treatment cycles of Atezo/Bev therapy, followed by four cycles of atezolizumab monotherapy, the tumor marker levels decreased to baseline levels and 22 small daughter nodules disappeared, leaving only the primary tumor. Therefore, we performed resection of the primary tumor as conversion surgery, and postoperative histopathology confirmed complete tumor necrosis. No cancer recurrence has been observed until the 5-month postoperative follow-up, and the patient remains drug free. Consistent with the findings in this case, a review of previously reported cases revealed that in cases of successful conversion surgery, neoadjuvant Atezo/Bev therapy was associated with intra-tumoral bleeding, immune-related adverse events, and normalization of the tumor marker levels.
Spin glass theory and its new challenge: structured disorder
Authors: Mézard Marc 
Published: December 2023

AbstractThis paper first describes, from a high-level viewpoint, the main challenges that had to be solved in order to develop a theory of spin glasses in the last fifty years. It then explains how important inference problems, notably those occurring in machine learning, can be formulated as problems in statistical physics of disordered systems. However, the main questions that we face in the analysis of deep networks require to develop a new chapter of spin glass theory, which will address the challenge of structured data.
Forecasting volatility by using wavelet transform, ARIMA and GARCH models
Authors: Rubio Lihki , Palacio Pinedo Adriana , Mejía Castaño Adriana , Ramos Filipe 
Published: December 2023

AbstractForecasting volatility of certain stocks plays an important role for investors as it allows to quantify associated trading risk and thus make right decisions. This work explores econometric alternatives for time series forecasting, such as the ARIMA and GARCH models, which have been widely used in the financial industry. These techniques have the advantage that training the models does not require high computational cost. To improve predictions obtained from ARIMA, the discrete Fourier transform is used as ARIMA pre-processing, resulting in the wavelet ARIMA strategy. Due to the linear nature of ARIMA, non-linear patterns in the volatility time series cannot be captured. To solve this problem, two hybridisation techniques are proposed, combining wavelet ARIMA and GARCH. The advantage of applying this methodology is associated with the ability of each to capture linear and non-linear patterns present in a time series. These two hybridisation techniques are evaluated to verify which provides better prediction. The volatility time series is associated with Tesla stock, which has a highly volatile nature and it is of major interest to many investors today.
Interpolation of missing swaption volatility data using variational autoencoders
Authors: Richert Ivo , Buch Robert 
Published: December 2023

AbstractAlbeit of crucial interest for financial researchers, market-implied volatility data of European swaptions often exhibit large portions of missing quotes due to illiquidity of the underlying swaption instruments. In this case, standard stochastic interpolation tools like the common SABR model cannot be calibrated to observed volatility smiles, due to data being only available for the at-the-money quote of the respective underlying swaption. Here, we propose to infer the geometry of the full unknown implied volatility cube by learning stochastic latent representations of implied volatility cubes via variational autoencoders, enabling inference about the missing volatility data conditional on the observed data by an approximate Gibbs sampling approach. Up to our knowledge, our studies constitute the first-ever completely nonparametric approach to modeling swaption volatility using unsupervised learning methods while simultaneously tackling the issue of missing data. Since training data for the employed variational autoencoder model is usually sparsely available, we propose a novel method to generate synthetic swaption volatility data for training and afterwards test the robustness of our approach on real market quotes. In particular, we show that SABR interpolated volatilities calibrated to reconstructed volatility cubes with artificially imputed missing values differ by not much more than two basis points compared to SABR fits calibrated to the complete cube. Moreover, we demonstrate how the imputation can be used to successfully set up delta-neutral portfolios for hedging purposes.
Existence and Stability of Ulam–Hyers for Neutral Stochastic Functional Differential Equations
Authors: Selvam Arunachalam , Sabarinathan Sriramulu , Pinelas Sandra , Suvitha Vaidhiyanathan 
Published: December 2023

AbstractThe primary aim of this paper is to focus on the stability analysis of an advanced neural stochastic functional differential equation with finite delay driven by a fractional Brownian motion in a Hilbert space. We examine the existence and uniqueness of mild solution of $$ {\textrm{d}}\left[ {x}_{a}(s) + {\mathfrak {g}}(s, {x}_{a}(s - \omega (s)))\right] =\left[ {\mathfrak {I}}{x}_a(s) + {\mathfrak {f}}(s, {x}_a(s -\varrho (s)))\right] {\textrm{d}}s + \varsigma (s){\textrm{d}}\varpi ^{{\mathbb {H}}}(s),$$

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The main goal of this paper is to investigate the Ulam–Hyers stability of the considered equation. We have also provided numerical examples to illustrate the obtained results. This article also discusses the Euler–Maruyama numerical method through two examples.
Targeting epigenetic and posttranslational modifications regulating ferroptosis for the treatment of diseases
Authors: Wang Yumin , Hu Jing , Wu Shuang , Fleishman Joshua S. , Li Yulin , Xu Yinshi , Zou Wailong , Wang Jinhua , Feng Yukuan , Chen Jichao , Wang Hongquan 
Published: December 2023

AbstractFerroptosis, a unique modality of cell death with mechanistic and morphological differences from other cell death modes, plays a pivotal role in regulating tumorigenesis and offers a new opportunity for modulating anticancer drug resistance. Aberrant epigenetic modifications and posttranslational modifications (PTMs) promote anticancer drug resistance, cancer progression, and metastasis. Accumulating studies indicate that epigenetic modifications can transcriptionally and translationally determine cancer cell vulnerability to ferroptosis and that ferroptosis functions as a driver in nervous system diseases (NSDs), cardiovascular diseases (CVDs), liver diseases, lung diseases, and kidney diseases. In this review, we first summarize the core molecular mechanisms of ferroptosis. Then, the roles of epigenetic processes, including histone PTMs, DNA methylation, and noncoding RNA regulation and PTMs, such as phosphorylation, ubiquitination, SUMOylation, acetylation, methylation, and ADP-ribosylation, are concisely discussed. The roles of epigenetic modifications and PTMs in ferroptosis regulation in the genesis of diseases, including cancers, NSD, CVDs, liver diseases, lung diseases, and kidney diseases, as well as the application of epigenetic and PTM modulators in the therapy of these diseases, are then discussed in detail. Elucidating the mechanisms of ferroptosis regulation mediated by epigenetic modifications and PTMs in cancer and other diseases will facilitate the development of promising combination therapeutic regimens containing epigenetic or PTM-targeting agents and ferroptosis inducers that can be used to overcome chemotherapeutic resistance in cancer and could be used to prevent other diseases. In addition, these mechanisms highlight potential therapeutic approaches to overcome chemoresistance in cancer or halt the genesis of other diseases.
Effective hybrid search technique based constraint mixed-integer programming for smart home residential load scheduling
Authors: Abdelhameed Esam H. , Abdelraheem Samah , Mohamed Yehia Sayed , Diab Ahmed A. Zaki 
Published: December 2023

AbstractIn this paper, the problem of scheduling smart homes (SHs) residential loads is considered aiming to minimize electricity bills and enhance the user comfort. The problem is addressed as a multi-objective constraint mixed-integer optimization problem (CP-MIP) to model the constrained load operation. As the CP-MIP optimization problem is non-convex, a novel hybrid search technique, that combines the Relaxation and Rounding (RnR) approach and metaheuristic algorithms to enhance the accuracy and relevance of decision variables, is proposed. This search technique is implemented through two stages: the relaxation stage in which a metaheuristic technique is applied to get the optimal rational solution of the problem. Whereas, the second stage is the rounding process which is applied via stochastic rounding approach to provide a good-enough feasible solution. The scheduling process has been done under time-of-use (ToU) dynamic electricity pricing scheme and two powering modes (i.e., powering from the main grid only or powering from a grid-tied photovoltaic (PV) residential power system), in addition, four metaheuristics [i.e., Binary Particle Swarm Optimization (BPSO), Self-Organizing Hierarchical PSO (SOH-PSO), JAYA algorithm, and Comprehensive Learning JAYA algorithm (CL-JAYA)] have been utilized. The results reported in this study verify the effectiveness of the proposed technique. In the 1st powering mode, the electricity bill reduction reaches 19.4% and 20.0% when applying the modified metaheuristics, i.e. SOH-PSO and CL-JAYA, respectively, while reaches 56.1%, and 54.7% respectively in the 2nd powering scenario. In addition, CL-JAYA superiority is also observed with regard to the user comfort.
Selenium nanoparticles coated bacterial polysaccharide with potent antimicrobial and anti-lung cancer activities
Authors: Shehata Nourhan S. , Elwakil Bassma H. , Elshewemi Salma S. , Ghareeb Doaa A. , Olama Zakia A. 
Published: December 2023

AbstractBacterial exopolysaccharides are homopolymeric or heteropolymeric polysaccharides with large molecular weights (10–1000 kDa). Exopolysaccharides' functional uses and potential have revolutionized the industrial and medicinal industries. Hence, the aim of the present study was to optimize the production of bacterial exopolysaccharide and apply it as a capping agent for selenium nanoparticles synthesis. Exopolysaccharide (EPS) producing Lactic acid bacteria (LAB) were isolated from dairy products then biochemically characterized and assessed for their potential antimicrobial effect. The most potent EPS producer was identified as Lactiplantibacillus plantarum strain A2 with accession number OP218384 using 16S rRNA sequencing. Overall, FTIR data of the extracted EPS revealed similarity with amylopectin spectrum. 1H NMR spectrum revealed an α-anomeric configuration of the glycosidic linkage pattern in the polysaccharides while the 13C NMR spectrum can also be separated into two main portions, the anomeric carbons region (δ 98–102 ppm) and the non-anomeric carbons region (δ 60–81 ppm). Antimicrobial activity of the produced EPS showed maximum activity against Staphylococcus aureus, MRSA, Enterobacter aerogenes, Klebsiella pneumoniae and Candida albicans respectively. The EPS capsule layer surrounding the bacterial cells was detected by TEM study. Optimization of EPS production was evaluated using Taguchi design, trial 23 reported the highest biomass yield and EPS output (6.5 and 27.12 g/L respectively) with 2.4 and 3.3 folds increase (from the basal media) respectively. The optimized exopolysaccharide was used as a capping and stabilizing agent for selenium nanoparticles (EPS-SeNPs) synthesis. Zeta potential, size and PDI of the synthesized nanoparticles were − 19.7 mV, 45–65 nm and 0.446 respectively with strong bactericidal and fungicidal effect against the tested pathogens. Complete microbial growth eradication was recorded after 6, 8 and 10 h against Staphylococcus aureus, Candida albicans and Klebsiella pneumoniae respectively. EPS-SeNPs showed a potent antioxidant effect reached 97.4% and anticancer effect against A549 lung cancer cell line (IC50 reached 5.324 µg/mL). EPS-SeNPs inhibited cancerous cell growth at S phase. Moreover, molecular studies revealed the anti-apoptotic activity of Bcl2's was inhibited and Bax was activated. The present investigation successfully synthesized selenium nanoparticles through bacterial EPS with significantly high antimicrobial and anticancer activity.
Caspase inhibition improves viability and efficiency of liposomal transfection
Authors: Yoshida Tatsushi , Yamasaki Kenta , Tadagaki Kenjiro 
Published: December 2023

AbstractHigh transfection efficiency is the most important point for experiments of DNA and RNA introduction into cells. Decrease of cell viability during the transfection procedure is a crucial issue, resulting in transfection failure. However, the mechanism underlying cell growth inhibition has not been fully elucidated. Lipofection is frequently used for transfection experiments, whereases, depending on cell type, it causes a decrease in cell viability. The present study demonstrates here that a potent pan-caspase inhibitor Q-VD-OPh blocked cell death during the lipofection, indicating apoptosis was induced in lipofection. Moreover, Q-VD-OPh drastically increased transfected cells. This method provides easier and more effective transfection system of lipofection and may be useful for transfection of not only cell lines but also clinical uses such as gene therapy and nucleic acids vaccine.
Uncovering myocardial infarction genetic signatures using GWAS exploration in Saudi and European cohorts
Authors: Al-Ali Amein K. , Al-Rubaish Abdullah M. , Alali Rudaynah A. , Almansori Mohammed S. , Al-Jumaan Mohammed A. , Alshehri Abdullah M. , Al-Madan Mohammed S. , Vatte ChittiBabu , Cherlin Tess , Young Sylvia , Verma Shefali S. , Morahan Grant , Koeleman Bobby P. C. , Keating Brendan J. 
Published: December 2023

AbstractGenome-wide association studies (GWAS) have yielded significant insights into the genetic architecture of myocardial infarction (MI), although studies in non-European populations are still lacking. Saudi Arabian cohorts offer an opportunity to discover novel genetic variants impacting disease risk due to a high rate of consanguinity. Genome-wide genotyping (GWG), imputation and GWAS followed by meta-analysis were performed based on two independent Saudi Arabian studies comprising 3950 MI patients and 2324 non-MI controls. Meta-analyses were then performed with these two Saudi MI studies and the CardioGRAMplusC4D and UK BioBank GWAS as controls. Meta-analyses of the two Saudi MI studies resulted in 17 SNPs with genome-wide significance. Meta-analyses of all 4 studies revealed 66 loci with genome-wide significance levels of p < 5 × 10–8. All of these variants, except rs2764203, have previously been reported as MI-associated loci or to have high linkage disequilibrium with known loci. One SNP association in Shisa family member 5 (SHISA5) (rs11707229) was evident at a much higher frequency in the Saudi MI populations (> 12% MAF). In conclusion, our results replicated many MI associations, whereas in Saudi-only GWAS (meta-analyses), several new loci were implicated that require future validation and functional analyses.
Identification of ITPR1 gene as a novel target for hsa-miR-34b-5p in non-obstructive azoospermia: a Ca2+/apoptosis pathway cross-talk
Authors: Maleki Bahareh , Modarres Parastoo , Salehi Peyman , Vallian Sadeq 
Published: December 2023

AbstractMiR-34b-5p has been reported as a non-invasive diagnostic biomarker for infertility. However, no gene targets regulating the mechanism of cation of this miRNA are known. In this study, using gene set enrichment analysis the Inositol 1,4,5-Trisphosphate Receptor Type 1 (ITPR1)gene was identified as the sole target for hsa-miR-34b-5p, and found significantly overexpressed in non-obstructive azoospermia (NOA) patients. This finding was confirmed by qRT-PCR on fresh testicular tissues from NOA patients. Then, pathway enrichment analysis as well as the diagnostic value analysis of hsa-miR-34b-5p/ITPR1indicatedITPR1as a hub gene in the calcium (Ca2+)-apoptosis pathway, and a valuable predictive biomarker for NOA. Moreover, gene expression and histological assays showed the association of the effects of ITPR1’s increased expression on spermatogenesis failure through induction of apoptosis in NOA patients. These data suggested that the hsa-miR-34b-5p/ITPR1 axis could serve as a potential regulatory predictive biomarker for human spermatogenesis through the Ca2+-apoptosis pathway cross-talk.
Influence of pneumatic transportation on the stability of monoclonal antibodies
Authors: Coliat Pierre , Erb Stéphane , Diemer Hélène , Karouby Dan , Martin Tristan , Banerjee Mainak , Zhu Chen , Demarchi Martin , Cianférani Sarah , Detappe Alexandre , Pivot Xavier 
Published: December 2023

AbstractPneumatic transportation systems (PTS) were recently proposed as a method to carry ready-for-injection diluted monoclonal antibodies (mAbs) from the pharmacy to the bedside of patients. This method reduces transportation time and improves the efficiency of drug distribution process. However, mAbs are highly sensitive molecules for which subtle alterations may lead to deleterious clinical effects. These alterations can be caused by various external factors such as temperature, pH, pressure, and mechanical forces that may occur during transportation. Hence, it is essential to ensure that the mAbs transported by PTS remain stable and active throughout the transportation process. This study aims to determine the safety profile of PTS to transport 11 routinely used mAbs in a clinical setting through assessment of critical quality attributes (CQA) and orthogonal analysis. Hence, we performed aggregation/degradation profiling, post-translational modifications identification using complementary mass spectrometry-based methods, along with visible and subvisible particle formation determination by light absorbance and light obscuration analysis. Altogether, these results highlight that PTS can be safely used for this purpose when air is removed from the bags during preparation.