bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Review on Torilis japonica: Ethnomedicinal, Phytochemical, and Biological Features
Authors: Rahimpour Yahya , Doorandishan Mina , Dehsheikh Anahita Boveiri , Sourestani Mohammad Mahmoodi , Mottaghipisheh Javad 
Published: April 2023

AbstractThe present study was aimed at comprehensive overviewing a phytochemically and biologically important species namely Torilis japonica (Apiaceae family). Treatment of dysentery, fever, haemorrhoids, spasm, uterine tumors, lymphadenitis, rheumatism, impotence, infertility, women's diseases, and chronic diarrhea are reported as the main folk medicinal applications of the T. japonica fruits. So far, the plant is phytochemically characterized for its diverse terpene derivatives, predominantly sesquiterpenes. The plant's fruit is a rich source of torlin, a guaiane‐type sesquiterpene, possessing various potent bioactivities. To date, anticancer, anti‐inflammatory, antimicrobial, antioxidant, skin photoaging activities of the plant extracts and its constituents have been evaluated. Further investigation of the plant, specifically bioassay‐guided isolation and identification of its major bioactive constituents can lead to discover potential phytopharmaceutical candidates.
An inguinal enigma: Myxoid liposarcoma in a female
Authors: Agarwal Shantanu , Bains Lovenish , Makthala Sripooja , Lal Pawan , Singh Meeta 
Published: April 2023

AbstractMyxoid liposarcoma of the inguinal region is rare, can mimics an inguinal hernia. Any swelling in the inguinal region, that is partially reducible, fluctuant, soft, and without any signs of bowel obstruction should be evaluated further.
Intermolecular Dearomative 1,2‐Amination/Carbonylation via Nucleophilic Addition of Simple Amines to Arene π‐Bonds
Authors: Li Zheng‐Jian , Wang Ming‐Yang , Li Chu‐Qiao , Zeng Wei‐Long , Li Wei 
Published: April 2023

AbstractThe incorporation of the privileged amino functionality is of paramount importance in organic synthesis. In contrast to the well‐developed amination methods for alkenes, the dearomative amination of arenes is largely underexplored due to the inherently inert reactivity of arene π‐bonds and selectivity challenges. Herein, we report an intermolecular dearomative aminofunctionalization via direct nucleophilic addition of simple amines to chromium‐bound arenes. This multicomponent 1,2‐amination/carbonylation reaction enables rapid access to complicated alicyclic compounds containing amino and amide functionalities from benzene derivatives under CO‐gas‐free conditions, which also represents the first application of nitrogen‐based nucleophiles in η6‐coordination‐induced arene dearomatizations.
d‐Amino acids in biological systems
Authors: Du Siqi , Wey Michael , Armstrong Daniel W. 
Published: April 2023

AbstractInvestigations on the occurrence and biochemical roles of free D‐amino acids and D‐amino acid‐containing peptides and proteins in living systems have increased in frequency and significance. Their occurrence and roles may vary substantially with progression from microbiotic to evermore advanced macrobiotic systems. We now understand many of the biosynthetic and regulatory pathways, which are outlined herein. Important uses for D‐amino acids in plants, invertebrates, and vertebrates are reviewed. Given its importance, a separate section on the occurrence and role of D‐amino acids in human disease is presented.
Bayesian instrumental variable estimation in linear measurement error models
Authors: Wang Qi , Wang Lichun , Wang Liqun 
Published: April 2023

AbstractIn this article, we study the problem of parameter estimation for measurement error models by combining the Bayes method with the instrumental variable approach, deriving the posterior distribution of parameters under different priors with known and unknown variance parameters, respectively, and calculating the Bayes estimator (BE) of the parameters under quadratic loss. However, it is difficult to obtain an explicit expression for BE because of the complex multiple integrals involved. Therefore, we adopt the linear Bayes method, which does not specify the form of the prior and avoids these complicated integral calculations, to obtain an expression for the linear Bayes estimator (LBE) for different priors. We prove that this LBE is superior to the two‐stage least squares estimator under the mean squared error matrix criterion. Numerical simulations show that our LBE is very close to the real parameter whether the variance parameters are known or unknown, and it gradually approaches BE as the sample size increases. Our results indicate that this instrumental variable approach is valid for measurement error models.
Derivation of human retinal cell densities using high‐density, spatially localized optical coherence tomography data from the human retina
Authors: Tong Janelle , Khou Vincent , Trinh Matt , Alonso‐Caneiro David , Zangerl Barbara , Kalloniatis Michael 
Published: April 2023

AbstractThis study sought to identify demographic variations in retinal thickness measurements from optical coherence tomography (OCT), to enable the calculation of cell density parameters across the neural layers of the healthy human macula. From macular OCTs (n = 247), ganglion cell (GCL), inner nuclear (INL), and inner segment–outer segment (ISOS) layer measurements were extracted using a customized high‐density grid. Variations with age, sex, ethnicity, and refractive error were assessed with multiple linear regression analyses, with age‐related distributions further assessed using hierarchical cluster analysis and regression models. Models were tested on a naïve healthy cohort (n = 40) with Mann–Whitney tests to determine generalizability. Quantitative cell density data were calculated from histological data from previous human studies. Eccentricity‐dependent variations in OCT retinal thickness closely resemble topographic cell density maps from human histological studies. Age was consistently identified as significantly impacting retinal thickness (p = .0006, .0007, and .003 for GCL, INL and ISOS), with gender affecting ISOS only (p < .0001). Regression models demonstrated that age‐related changes in the GCL and INL begin in the 30th decade and were linear for the ISOS. Model testing revealed significant differences in INL and ISOS thickness (p = .0008 and .0001; however, differences fell within the OCT's axial resolution. Qualitative comparisons show close alignment between OCT and histological cell densities when using unique, high‐resolution OCT data, and correction for demographics‐related variability. Overall, this study describes a process to calculate in vivo cell density from OCT for all neural layers of the human retina, providing a framework for basic science and clinical investigations.
Elucidating the Effect of Ion Exchange Protocol on the Copper Exchange Efficacy, Copper Siting, and SCR activity in Cu‐SSZ‐13
Authors: Koishybay Aibolat , Umhey Charles , Kuo Chun‐Te , Groden Kyle , McEwen Jean‐Sabin , Karim Ayman M. , Shantz Daniel F. 
Published: April 2023

AbstractThe influence of the copper ion exchange protocol on SCR activity of SSZ‐13 is quantified. Using the same parent SSZ‐13 zeolite, four exchange protocols are used to assess how exchange protocol impacts metal uptake and SCR activity. Large differences in the SCR activity, nearly 30 percentage points at 160 °C at constant copper content, are observed for different exchange protocols implying that different exchange protocols lead to different copper species. Hydrogen temperature programmed reduction on selected samples and infrared spectroscopy of CO binding corroborates this conclusion as the reactivity at 160 °C correlates with the intensity of the IR band at 2162 cm−1. DFT‐based calculations show that such an IR assignment is consistent with CO adsorbed on a Cu(I) cation within an eight‐membered ring. This work shows that SCR activity can be influenced by the ion exchange process even when different protocols lead to the same metal loading. Perhaps most interesting, a protocol used to generate Cu‐MOR for methane to methanol studies led to the most active catalyst both on a unit mass or unit mole copper basis. This points to a yet not recognized means to tailor catalyst activity as the open literature is silent on this issue.
Growing Cu2ZnSnS4 Thin Film at Low Temperature Using a New Improved Configuration of Close‐Distance CVD Technique
Authors: Belaqziz Mohamed , Medjnoun Kahina , Chehouani Hassan , Sagna Alphousseyni , Lahlali Sanaa , Djessas Kamal 
Published: April 2023

AbstractThis study presents a new possibility to deposit the polycrystalline Cu2ZnSnS4 (CZTS) thin film at low temperature using an improved close‐distance chemical vapor deposition reactor. Firstly, a theoretical study is conducted to predict the iodine pressure (PI2) and the substrate temperature (Ts) as the optimal conditions for the deposition of CZTS. The theoretical model is based on the minimization of the Gibbs energy of the Cu‐Zn‐Sn‐S‐I chemical system. An experimental study is realized, and the predicted optimal conditions to obtain quasi‐stoichiometric depositions are tested. The X‐ray diffraction, Raman spectroscopy, energy dispersive spectroscopy, scanning electron microscopy, and UV–vis–NIR spectroscopy are used to analyze the thin films elaborated at substrate temperatures of Ts = 400 and 550 °C for iodine pressure PI2 = 0.03 × 105 Pa. With the help of the thermodynamical calculations, the results show that it is possible to grow a good quality CZTS thin film at a low substrate temperature of 400 °C.
Establishing standards for Yonsei point in a White South African population for the treatment of gummy smile
Authors: Booysen Brandon , Baron René H. , Uys André 
Published: April 2023

AbstractIntroductionThe purpose of this study is to establish the efficacy of Yonsei point in the treatment of a gummy smile in a White South African population. The accurate surface anatomy criteria in relation to the underlying musculature for the administration of Botulinum toxin injections in the treatment of gummy smile was determined.Materials and MethodsNineteen (10 males and 9 females) cadavers were selected for facial dissection. Facial profile photographs were taken before and after dissection. The before and after photographs were overlayed to determine where the pin positions should be on the dissected cadaver to determine the Yonsei point. The levator labii superioris (LLS), LLS alaeque nasi (LLSAN), zygomaticus minor, and zygomaticus major muscles were measured using a protractor and ruler, which accounted for the manual measurements. Digital measurements were measured by importing dissected images into ImageJ. Circles with a 2 cm diameter (1 cm radius) were constructed to determine whether the Yonsei point could successfully influence muscles fibers.ResultsDigital and manual measurements show comparable results with high correlation and reliability. Results showed that the White South African population had narrower facial musculature angles as compared with the Korean population.ConclusionBased on the selected sample, the Yonsei point is an ineffective injection site for the successful treatment of gummy smile in a White South African population.
Corpus analysis of evaluative language and framework implementation for pharmaceutical industryCSRreports
Authors: Cai Siying , Zhu Wenzhong , Wang Yuting 
Published: April 2023

AbstractCorporate social responsibility (CSR) is a concept, where organizations can store and maintain environmental, economic and social issues by including social or environmental concerns. This research intends to map out the features of evaluative language used by pharmaceutical industry CSR reports and figure out how evaluative meaning assists companies in communicating with stakeholders and narrowing the legitimacy gap, to be in a status congruent with societal expectation. An integrated analytical framework and the Three‐Domain Model of CSR is created to fulfill the research objectives. This study primarily examines the characteristics of evaluative language with the use of two sets of self‐built corpora that include CSR reports from pharmaceutical companies that must maintain and repair their legitimacy; the study reveals that report authors usually use more resources with a positive attitude to evaluate themselves whereas negative resources are only adopted to characterize others. Statistics demonstrate a considerable difference in the utilization of affect resources, although CSR reports in both organizations embrace appreciation resources as the primary means of maintaining or repairing their legitimacy. Finally, by borrowing the Three‐Domain Model of CSR, the results also show “ethical” responsibility as the focused area in pharmaceutical industry CSR reports.
Rate Response of Poly(Ethylene Terephthalate)‐Hydrolases to Substrate Crystallinity: Basis for Understanding the Lag Phase
Authors: Thomsen Thore B. , Schubert Sune , Hunt Cameron J. , Borch Kim , Jensen Kenneth , Brask Jesper , Westh Peter , Meyer Anne S. 
Published: April 2023

AbstractThe rate response of poly(ethylene terephthalate) (PET)‐hydrolases to increased substrate crystallinity (XC) of PET manifests as a rate‐lowering effect that varies significantly for different enzymes. Herein, we report the influence ofXCon the product release rate of six thermostable PET‐hydrolases. All enzyme reactions displayed a distinctive lag phase until measurable product formation occurred. The duration of the lag phase increased withXC. The recently discovered PET‐hydrolase PHL7 worked efficiently on “amorphous” PET disks (XC≈10 %), but this enzyme was extremely sensitive to increasedXC, whereas the enzymes LCCICCG, LCC, and DuraPETase had higher tolerance to increases inXCand had activity on PET disks havingXCof 24.4 %. Microscopy revealed that theXC‐tolerant hydrolases generated smooth and more uniform substrate surface erosion than PHL7 during reaction. Structural and molecular dynamics analysis of the PET‐hydrolyzing enzymes disclosed that surface electrostatics and enzyme flexibility may account for the observed differences.
Cognitive function in individuals with and without painful and painless diabetic polyneuropathy—A cross‐sectional study in type 1 diabetes
Authors: Croosu Suganthiya S. , Gjela Mimoza , Røikjer Johan , Hansen Tine M. , Mørch Carsten D. , Frøkjær Jens B. , Ejskjaer Niels 
Published: April 2023

AbstractIntroductionPrevious studies suggest that cognitive impairment is more prevalent in individuals with painful and painless diabetic peripheral neuropathy (DPN). However, the current evidence is not well described. This study investigated cognitive function in adults with type 1 diabetes mellitus (T1DM) and the association to painful/painless DPN and clinical parameters.MethodsThis cross‐sectional, observational, case–control study included 58 participants with T1DM, sub‐grouped into 20 participants with T1DM and painful DPN, 19 participants with T1DM and painless DPN, 19 participants with T1DM without DPN, and 20 healthy controls were included. The groups were matched for sex and age. The participants performed Addenbrooke's examination III (ACE‐III), which assesses attention, memory, verbal fluency, language and visuospatial skills. Working memory was evaluated using an N‐back task. Cognitive scores were compared between the groups and correlated to age, diabetes duration, HbA1c and nerve conduction measurements.ResultsCompared to healthy controls, T1DM participants showed lower total ACE‐III (p = .028), memory (p = .013) and language scores (p = .028), together with longer reaction times in the N‐back task (p = .041). Subgroup analyses demonstrated lower memory scores in those with painless DPN compared with healthy controls (p = .013). No differences were observed between the three T1DM subgroups. Cognitive scores and clinical parameters were not associated.ConclusionsThis study supports the notion of cognitive alterations in T1DM and indicates that cognitive function is altered in T1DM regardless of underlying neuropathic complications. The memory domain appears altered in T1DM, particularly in those with painless DPN. Further studies are needed to verify the findings.
A year in heart failure: updates of clinical and preclinical findings
Authors: Bäck Magnus , von Haehling Stephan , Papp Zoltán , Piepoli Massimo F. 
Published: April 2023

AbstractWe witnessed major advances in the management of heart failure (HF) in 2022. Results of recent clinical and preclinical investigations aid preventive strategies, diagnostic efforts, and therapeutic interventions, and collectively, they hold promises for a more effective HF care for the near future. Accordingly, currently available information extends the 2021 European Society of Cardiology guidelines and provides a solid background for the introduction of improved clinical approaches in the number of HF‐related cases. Elaboration on the relationships between epidemiological data and risk factors lead to better understanding of the pathophysiology of HF with reduced ejection fraction and HF with preserved ejection fraction. The clinical consequences of valvular dysfunctions are increasingly interpreted not only in their haemodynamic consequences but also in association with their pathogenetic factors and modern corrective treatment possibilities. The influence of coronavirus disease 2019 pandemic on the clinical care of HF appeared to be less intense in 2022 than before; hence, this period allowed to refine coronavirus disease 2019 management options for HF patients. Moreover, cardio‐oncology emerges as a new subdiscipline providing significant improvements in clinical outcomes for oncology patients. Furthermore, the introduction of state‐of‐the‐art molecular biologic methods, multi‐omic approaches forecast improved phenotyping and precision medicine for HF. All above aspects are addressed in this article that highlights a selection of papers published in ESC Heart Failure in 2022.
The goal of explaining black boxes in EEG seizure prediction is not to explain models' decisions
Authors: Pinto Mauro F. , Batista Joana , Leal Adriana , Lopes Fábio , Oliveira Ana , Dourado António , Abuhaiba Sulaiman I. , Sales Francisco , Martins Pedro , Teixeira César A. 
Published: April 2023

AbstractMany state‐of‐the‐art methods for seizure prediction, using the electroencephalogram, are based on machine learning models that are black boxes, weakening the trust of clinicians in them for high‐risk decisions. Seizure prediction concerns a multidimensional time‐series problem that performs continuous sliding window analysis and classification. In this work, we make a critical review of which explanations increase trust in models' decisions for predicting seizures. We developed three machine learning methodologies to explore their explainability potential. These contain different levels of model transparency: a logistic regression, an ensemble of 15 support vector machines, and an ensemble of three convolutional neural networks. For each methodology, we evaluated quasi‐prospectively the performance in 40 patients (testing data comprised 2055 hours and 104 seizures). We selected patients with good and poor performance to explain the models' decisions. Then, with grounded theory, we evaluated how these explanations helped specialists (data scientists and clinicians working in epilepsy) to understand the obtained model dynamics. We obtained four lessons for better communication between data scientists and clinicians. We found that the goal of explainability is not to explain the system's decisions but to improve the system itself. Model transparency is not the most significant factor in explaining a model decision for seizure prediction. Even when using intuitive and state‐of‐the‐art features, it is hard to understand brain dynamics and their relationship with the developed models. We achieve an increase in understanding by developing, in parallel, several systems that explicitly deal with signal dynamics changes that help develop a complete problem formulation.
Increasing saltiness of salts (NaCl) using mid‐infrared radiation to reduce the health hazards
Authors: Umakanthan Thangaraju , Mathi Madhu 
Published: April 2023

AbstractTable salt, rock salt, and iodized salts (composed principally of NaCl) are commonly used in many areas, such as medicine, cooking, industry, or personal care. Common fried, salty, and spicy foods contain an excess of added salt, which has detrimental health effects, especially on the kidneys. Our research aims to enhance the inherent saltiness of these three salts, which would reduce intake and thereby minimize salt's health hazards. We invented a water‐based 2–6 μm of Mid‐Infrared Generating Atomizer (MIRGA), which, when applied to salts, caused changes in the salts' chemistry and enhanced saltiness, thus allowing the reduction of salt intake by 25%–30%. This easy‐to‐use technology did not show any side effects. MIRGA was found to have enhanced the saltiness, thus allowing the reduction of salt intake by 25%–30%. MIRGA is safe, portable, highly economical, unique in the mid‐IR laser technology, and possesses vast research scope in other areas of food science.
Can decision field theory enhance our understanding of health‐based choices? Evidence from risky health behaviors
Authors: Meester David A. J. , Hess Stephane , Buckell John , Hancock Thomas O. 
Published: April 2023

AbstractDiscrete choice models are almost exclusively estimated assuming random utility maximization (RUM) is the decision rule applied by individuals. Recent studies indicate alternative behavioral assumptions may be more appropriate in health. Decision field theory (DFT) is a psychological theory of decision‐making, which has shown promise in transport research. This study introduces DFT to health economics, empirically comparing it to RUM and random regret minimization (RRM) in risky health settings, namely tobacco and vaccine choices. Model fit, parameter ratios, choice shares, and elasticities are compared between RUM, RRM and DFT. Test statistics for model differences are derived using bootstrap methods. Decision rule heterogeneity is investigated using latent class models, including novel latent class DFT models. Tobacco and vaccine choice data are better explained with DFT than with RUM or RRM. Parameter ratios, choice shares and elasticities differ significantly between models. Mixed results are found for the presence of decision rule heterogeneity. We conclude that DFT shows promise as a behavioral assumption that underpins the estimation of discrete choice models in health economics. The significant differences demonstrate that care should be taken when choosing a decision rule, but further evidence is needed for generalizability beyond risky health choices.