bluuebunny/crossref_metadata_2025_split huggingface dataset:
The CARING study: Examining biological, behavioral, and genetic mechanisms in the intergenerational transmission of toxic stress
Authors: Condon Eileen M. , Scheibner Hannah R. , Kuzel Meredith , Howard Mackenzie , Cisse Mouhamadou , O'Connell Meghan , Conley Yvette , Jeon Sangchoon , Sadler Lois S. , Redeker Nancy S. 
Published: May 2024

AbstractWhen children experience extreme or persistent stressors (e.g., maltreatment, housing insecurity, intimate partner violence), prolonged elevation of the stress‐response system can lead to disrupted development of multiple physiological systems. This response, known as toxic stress, is associated with poor physical and mental health across the life course. Emerging evidence suggests that the effects of toxic stress may be transmitted through generations, but the biological and behavioral mechanisms that link caregivers’ childhood history with the health of the children they care for remain poorly understood. The purpose of this report is to describe the research protocol for The CARING (Childhood Adversity and Resilience In the Next Generation) Study, a cross‐sectional study of caregivers with children aged 3–5 years designed to (1) examine the intergenerational transmission of toxic stress and protective factors; (2) explore three hypothesized pathways of transmission: parenting, daily routines, stressors, and supports; and (3) explore the extent to which genotypic variation in candidate genes related to caregiving and stress contribute to caregivers’ and children's susceptibility to the effects of early childhood experiences (i.e., gene × environment interactions). We expect that findings from this study will provide critical data needed to identify targets for precision health interventions, reduce health disparities related to toxic stress, and prevent cycles of adversity among families at risk.
PCDHGC3 hypermethylation as a potential biomarker of intestinal neuroendocrine carcinomas
Authors: Cubiella Tamara , Celada Lucía , San‐Juan‐Guardado Jaime , Rodríguez‐Aguilar Raúl , Suárez‐Priede Álvaro , Poch María , Dominguez Francisco , Fernández‐Vega Iván , Montero‐Pavón Pedro , Fraga Mario F , Nakatani Yoichiro , Takata So , Yachida Shinichi , Valdés Nuria , Chiara María‐Dolores 
Published: May 2024

AbstractNeuroendocrine neoplasms (NENs) encompass tumors arising from neuroendocrine cells in various organs, including the gastrointestinal tract, pancreas, adrenal gland, and paraganglia. Despite advancements, accurately predicting the aggressiveness of gastroenteropancreatic (GEP) NENs based solely on pathological data remains challenging, thereby limiting optimal clinical management. Our previous research unveiled a crucial link between hypermethylation of the protocadherin PCDHGC3 gene and neuroendocrine tumors originating from the paraganglia and adrenal medulla. This epigenetic alteration was associated with increased metastatic potential and succinate dehydrogenase complex (SDH) dysfunction. Expanding upon this discovery, the current study explored PCDHGC3 gene methylation within the context of GEP‐NENs in a cohort comprising 34 cases. We uncovered promoter hypermethylation of PCDHGC3 in 29% of GEP‐NENs, with a significantly higher prevalence in gastrointestinal (GI) neuroendocrine carcinomas (NECs) compared with both pancreatic (Pan) NECs and neuroendocrine tumors (NETs) of GI and Pan origin. Importantly, these findings were validated in one of the largest multi‐center GEP‐NEN cohorts. Mechanistic analysis revealed that PCDHGC3 hypermethylation was not associated with SDH mutations or protein loss, indicating an SDH‐independent epigenetic mechanism. Clinically, PCDHGC3 hypermethylation emerged as a significant prognostic factor, correlating with reduced overall survival rates in both patient cohorts. Significantly, whereas PCDHGC3 hypermethylation exhibited a strong correlation with TP53 somatic mutations, a hallmark of NEC, its predictive value surpassed that of TP53 mutations, with an area under the curve (AUC) of 0.95 (95% CI 0.83–1.0) for discriminating GI‐NECs from GI‐NETs, highlighting its superior predictive performance. In conclusion, our findings position PCDHGC3 methylation status as a promising molecular biomarker for effectively stratifying patients with GI‐NENs. This discovery has the potential to advance patient care by enabling more precise risk assessments and tailored treatment strategies. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Vancomycin: An analysis and evaluation of eight population pharmacokinetic models for clinical application in general adult population
Authors: Duong Alexandre , El Gamal Ahmed , Bilodeau Véronique , Huot Justine , Delorme Carole , Poudrette Johanne , Crevier Benoît , Marsot Amélie 
Published: May 2024

AbstractIntroductionBased on the recent guidelines for vancomycin therapeutic drug monitoring (TDM), the area under the curve to minimum inhibitory concentration ratio was to be employed combined with the usage of population pharmacokinetic (popPK) model for dosing adaptation. Yet, deploying these models in a clinical setting requires an external evaluation of their performance.ObjectivesThis study aimed to evaluate existing vancomycin popPK models from the literature for the use in TDM within the general patient population in a clinical setting.MethodsThe models under external evaluation were chosen based on a review of literature covering vancomycin popPK models developed in general adult populations. Patients' data were collected from Charles‐Le Moyne Hospital (CLMH). The external evaluation was performed with NONMEM® (v7.5). Additional analyses such as evaluating the impact of number of samples on external evaluation, Bayesian forecasting, and a priori dosing regimen simulations were performed on the best performing model.ResultsEight popPK models were evaluated with an independent dataset that included 40 patients and 252 samples. The model developed by Goti and colleagues demonstrated superior performance in diagnostic plots and population predictive performance, with bias and inaccuracy values of 0.251% and 22.7%, respectively, and for individual predictive performance, bias and inaccuracy were −4.90% and 12.1%, respectively. When limiting the independent dataset to one or two samples per patient, the Goti model exhibited inadequate predictive performance for inaccuracy, with values exceeding 30%. Moreover, the Goti model is suitable for Bayesian forecasting with at least two samples as prior for the prediction of the next trough concentration. Furthermore, the vancomycin dosing regimen that would maximize therapeutic targets of area under the curve to minimum inhibitory concentration ratio (AUC24/MIC) and trough concentrations (Ctrough) for the Goti model was 20 mg/kg/dose twice daily.ConclusionConsidering the superior predictive performance and potential for Bayesian forecasting in the Goti model, future research aims to test its applicability in clinical settings at CLMH, both in a priori and a posteriori scenario.
Prediction of peptide hormones using an ensemble of machine learning and similarity‐based methods
Authors: Kaur Dashleen , Arora Akanksha , Vigneshwar Palani , Raghava Gajendra P. S. 
Published: May 2024

AbstractPeptide hormones serve as genome‐encoded signal transduction molecules that play essential roles in multicellular organisms, and their dysregulation can lead to various health problems. In this study, we propose a method for predicting hormonal peptides with high accuracy. The dataset used for training, testing, and evaluating our models consisted of 1174 hormonal and 1174 non‐hormonal peptide sequences. Initially, we developed similarity‐based methods utilizing BLAST and MERCI software. Although these similarity‐based methods provided a high probability of correct prediction, they had limitations, such as no hits or prediction of limited sequences. To overcome these limitations, we further developed machine and deep learning‐based models. Our logistic regression‐based model achieved a maximum AUROC of 0.93 with an accuracy of 86% on an independent/validation dataset. To harness the power of similarity‐based and machine learning‐based models, we developed an ensemble method that achieved an AUROC of 0.96 with an accuracy of 89.79% and a Matthews correlation coefficient (MCC) of 0.8 on the validation set. To facilitate researchers in predicting and designing hormone peptides, we developed a web‐based server called HOPPred. This server offers a unique feature that allows the identification of hormone‐associated motifs within hormone peptides. The server can be accessed at: https://webs.iiitd.edu.in/raghava/hoppred/.
Comparison of home‐based spirometry and oscillometry measurements in school‐age children with bronchopulmonary dysplasia
Authors: Lee Julia X. , Ryan Morgan , Mukharesh Lana , Dahlberg Suzanne E. , Sun Bob Z. , Hayden Lystra , Phipatanakul Wanda , Gaffin Jonathan 
Published: May 2024

AbstractIntroductionThis study compares home‐based oscillometry and spirometry for characterizing respiratory system disease in school‐aged children with bronchopulmonary dysplasia (BPD) in clinical research. We hypothesized higher rates of successful completion and abnormal cases identified through oscillometry, with correlations between device measurements.MethodsParticipants 6–12 years old with BPD in the ongoing Air Quality, Environment and Respiratory Outcomes in BPD (AERO‐BPD) study performed oscillometry followed by spirometry at two separate home visits. Parameters measured included airway resistance at 5 Hz(R5), resistance from 5 to 19 Hz(R5‐19), resonance frequency(Fres), reactance at 5 Hz(X5), area under the curve between Fres and X5(AX), forced expiratory volume in 1 second(FEV1), forced vital capacity(FVC), and FEV1/FVC. Descriptive statistics identified the proportion of successful tests, correlation in measurements, and rate of lung disease for each device.ResultsAmong 76 subjects with 120 paired observations, 95% and 71% of participants successfully performed oscillometry and spirometry, respectively, at home visit one. 98% and 77% successfully performed oscillometry and spirometry, respectively, at home visit two. Odds ratios favored oscillometry (range 5.31–10.13, p < 0.01). FEV1 correlated with AX (correlation coefficient r = −0.27, p = 0.03); FEV1/FVC with AX (r = −0.32, p = 0.02); and FEV1/FVC with R5 (r = −0.37, p = 0.01). AX exhibited the highest prevalence of abnormality at 25%; other oscillometry parameters ranged from 5%–22%. Forty‐five to sixty‐four percent of participants had abnormal spirometry. Oscillometry assessments had significantly lower odds of capturing lung disease (odds ratios 0.07–0.24, p < 0.0001).ConclusionsSchool‐aged children with BPD demonstrated higher success rates in field‐based oscillometry than spirometry. Spirometry exhibited higher rates of abnormality than oscillometry. Moderate correlation exists between device measurements.
Invariant point message passing for protein side chain packing
Authors: Randolph Nicholas Z. , Kuhlman Brian 
Published: May 2024

AbstractProtein side chain packing (PSCP) is a fundamental problem in the field of protein engineering, as high‐confidence and low‐energy conformations of amino acid side chains are crucial for understanding (and designing) protein folding, protein–protein interactions, and protein‐ligand interactions. Traditional PSCP methods (such as the Rosetta Packer) often rely on a library of discrete side chain conformations, or rotamers, and a forcefield to guide the structure to low‐energy conformations. Recently, deep learning (DL) based methods (such as DLPacker, AttnPacker, and DiffPack) have demonstrated state‐of‐the‐art predictions and speed in the PSCP task. Building off the success of geometric graph neural networks for protein modeling, we present the Protein Invariant Point Packer (PIPPack) which effectively processes local structural and sequence information to produce realistic, idealized side chain coordinates using ‐angle distribution predictions and geometry‐aware invariant point message passing (IPMP). On a test set of ∼1400 high‐quality protein chains, PIPPack is highly competitive with other state‐of‐the‐art PSCP methods in rotamer recovery and per‐residue RMSD but is significantly faster.
ERegPose: An explicit regression based 6D pose estimation for snake‐like wrist‐type surgical instruments
Authors: Li Jinhua , Ma Zhengyang , Sun Xinan , Su He 
Published: May 2024

AbstractBackgroundAccurately estimating the 6D pose of snake‐like wrist‐type surgical instruments is challenging due to their complex kinematics and flexible design.MethodsWe propose ERegPose, a comprehensive strategy for precise 6D pose estimation. The strategy consists of two components: ERegPoseNet, an original deep neural network model designed for explicit regression of the instrument's 6D pose, and an annotated in‐house dataset of simulated surgical operations. To capture rotational features, we employ an Single Shot multibox Detector (SSD)‐like detector to generate bounding boxes of the instrument tip.ResultsERegPoseNet achieves an error of 1.056 mm in 3D translation, 0.073 rad in 3D rotation, and an average distance (ADD) metric of 3.974 mm, indicating an overall spatial transformation error. The necessity of the SSD‐like detector and L1 loss is validated through experiments.ConclusionsERegPose outperforms existing approaches, providing accurate 6D pose estimation for snake‐like wrist‐type surgical instruments. Its practical applications in various surgical tasks hold great promise.
Challenges and opportunities in piezoelectric polymers: Effect of oriented amorphous fraction in ferroelectric semicrystalline polymers
Authors: Rui Guanchun , Allahyarov Elshad , Zhu Zhiwen , Huang Yanfei , Wongwirat Thumawadee , Zou Qin , Taylor Philip L. , Zhu Lei 
Published: May 2024

AbstractDespite extensive research on piezoelectric polymers since the discovery of piezoelectric poly(vinylidene fluoride) (PVDF) in 1969, the fundamental physics of polymer piezoelectricity has remained elusive. Based on the classic principle of piezoelectricity, polymer piezoelectricity should originate from the polar crystalline phase. Surprisingly, the crystal contribution to the piezoelectric strain coefficient d31 is determined to be less than 10%, primarily owing to the difficulty in changing the molecular bond lengths and bond angles. Instead, >85% contribution is from Poisson's ratio, which is closely related to the oriented amorphous fraction (OAF) in uniaxially stretched films of semicrystalline ferroelectric (FE) polymers. In this perspective, the semicrystalline structure–piezoelectric property relationship is revealed using PVDF‐based FE polymers as a model system. In melt‐processed FE polymers, the OAF is often present and links the crystalline lamellae to the isotropic amorphous fraction. Molecular dynamics simulations demonstrate that the electrostrictive conformation transformation of the OAF chains induces a polarization change upon the application of either a stress (the direct piezoelectric effect) or an electric field (the converse piezoelectric effect). Meanwhile, relaxor‐like secondary crystals in OAF (SCOAF), which are favored to grow in the extended‐chain crystal (ECC) structure, can further enhance the piezoelectricity. However, the ECC structure is difficult to achieve in PVDF homopolymers without high‐pressure crystallization. We have discovered that high‐power ultrasonication can effectively induce SCOAF in PVDF homopolymers to improve its piezoelectric performance. Finally, we envision that the electrostrictive OAF mechanism should also be applicable for other FE polymers such as odd‐numbered nylons and piezoelectric biopolymers.
Modulating Ionic Linkages in the Heterocyclic Sulfated Polysaccharide Carrageenan for Enhanced Selectivity Against Amelanotic Melanoma Cells
Authors: Bhatt Akanksha , Kailkhura Shashank , Shukla Aman , Kumar Sachin , Purohit Priyank , Abdellattif Magda H. 
Published: May 2024

AbstractThe present research is the use of Heterocyclic sulfated polysaccharides, exemplified by carrageenan, with the high selective anti‐cancer against melanoma cancer. This study focuses on optimizing the ionic linkage of carrageenan to enhance its selectivity and activity against skin cancer cells with the help of cell line assays and in‐silico studies. The cytotoxicity and selectivity of the optimized derivatives were assessed in‐vitro against skin cancer cells and normal skin cells. The barium‐linked carrageenan demonstrated significantly increased selectivity against skin cancer cells with a selectivity index of 45, however, the reference drug was found with a selectivity index of 23. The selectivity of the compound 3 (Ba ion linked) was analysed through the ion dissociation energy and found that the more energy is require to dissoxiate in the ion, which signifiacnlty absorbs inside the cell because of non‐ionic form. The selectivity sequence of K+<Ca2+<Ba2+ as a targeted anti‐cancer agent. The present research unfold the importance of ion linkage of chromophore, to get the more active and selective compounds, which will be a path to get the ion activity relationship of various drugs without interfering the chromophore. The findings suggest a promising avenue for the development of targeted therapies with the change of ions, emphasizing the potential of heterocyclic sulfated polysaccharides in the field of cancer treatment with enhanced tuning of selectivity. The further scope is the gel formation of the Ba2+ carrageenan which will be the first API (Active Pharmaceuitical Ingredients) based formulation for skin cancer.
G‐Quadruplex‐Programmed Versatile Nanorobot Combined with Chemotherapy and Gene Therapy for Synergistic Targeted Therapy
Authors: Wang Qiwei , Du Yi , Zheng Jiao , Shi Lili , Li Tao 
Published: May 2024

AbstractDeveloping synergistic targeted therapeutics to improve treatment efficacy while reducing side effects has proven promising for anticancer therapies, but how to conveniently modulate multidrug cooperation remains a challenge. Here, a novel synergistic strategy using a G‐quadruplex‐programmed versatile nanorobot (G4VN) containing two subunits of DNAzyme (DzG4) and ligand‐drug conjugates (LDCs) is proposed to precisely target tumors and then execute both gene silencing and chemotherapy. As the core module of this nanorobot, a well‐designed G4 responding to a high level of K+ in tumor microenvironment smartly kills three birds with one stone, which makes two TfR aptamers proximate to improve their efficiency of targeting tumor cells, and in situ activates a split 10–23 DNAzyme to downregulate target mRNA expression, meanwhile promotes the cell uptake of a GSH‐responsive LDCs to enhance drug efficacy. Such a design enables a potently synergistic anticancer therapy with low side effects in vivo, showing great promise for broad applications in precision disease treatment.
Regulation of Peptide Liquid–Liquid Phase Separation by Aromatic Amino Acid Composition
Authors: Netzer Amit , Baruch Leshem Avigail , Veretnik Shirel , Edelstein Ilan , Lampel Ayala 
Published: May 2024

AbstractMembraneless organelles are cellular biomolecular condensates that are formed by liquid–liquid phase separation (LLPS) of proteins and nucleic acids. LLPS is driven by multiple weak attractive forces, including intermolecular interactions mediated by aromatic amino acids. Considering the contribution of π‐electron bearing side chains to protein‐RNA LLPS, systematically study sought to how the composition of aromatic amino acids affects the formation of heterotypic condensates and their physical properties. For this, a library of minimalistic peptide building blocks is designed containing varying number and compositions of aromatic amino acids. It is shown that the number of aromatics in the peptide sequence affect LLPS propensity, material properties and (bio)chemical stability of peptide/RNA heterotypic condensates. The findings shed light on the contribution of aromatics’ composition to the formation of heterotypic condensates. These insights can be applied for regulation of condensate material properties and improvement of their (bio)chemical stability, for various biomedical and biotechnological applications.
Chemical analysis and antibacterial susceptibility of some brands of amoxicillin suspension marketed in Sagamu, Ogun, Nigeria
Authors: Oresanya Ayooluwa Omobolanle , Ayodele Adekunle Olatunde , Awotuya Oluwafemi Iyanu , Fagbohun Babasola Ayodele , Olufolabo Olabanjo Katherine , Daodu Olabanji John , Olaitan James Olatunde , Kasim Lateef Saka 
Published: May 2024

AbstractPoor quality medicines present a serious public health concern and have a significant impact on national clinical and economic burden. This study was carried out for comparative quality assessment of different brands of amoxicillin suspension in Sagamu community in Nigeria to determine their suitability for the therapeutic purpose. Ten brands of 125 mg/5 mL amoxicillin suspension, marketed in Sagamu community pharmacies were procured and subjected to chemical analysis using the high‐performance liquid chromatography method according to the official procedures in United State Pharmacopoeia (USP) and the microbiological analysis on different clinical isolates which include Pseudomonas aeruginosa, Escherichia coli, Streptococcus pyogene, and Staphylococcus aureus using agar disc diffusion antimicrobial susceptibility testing. The results of the high‐performance liquid chromatography revealed the percentage content of the brands A, B, C, D, E, F, G, H, I, and J to be 97.39%, 57.078%, 91.565%, 98.137%, 61.694%, 103.337%, 91.454%, 106.683%, 75.109%, and 96.895% w/v, respectively. The result of the high‐performance liquid chromatography reveals the brands (A, C, D, F, G, H, and J) had a percentage within the required range and were deemed unsuitable for therapeutic use. In the microbiological analysis, all the brands passed the antibacterial susceptibility testing except for brand (B, E, and I) which were not susceptible to S. aureus due to their zone of inhibition being less than 15 mm. Overall, this study emphasizes the importance of quality assurance in the pharmaceutical industry to ensure that only high‐quality drugs are made available to the population for optimal therapeutic benefit.