bluuebunny/crossref_metadata_2025 huggingface dataset:
The American Cancer Society National Lung Cancer Roundtable strategic plan: Implementation of high‐quality lung cancer screening
Authors: Fathi Joelle T. , Barry Angela M. , Greenberg Grant M. , Henschke Claudia I. , Kazerooni Ella A. , Kim Jane J. , Mazzone Peter J. , Mulshine James L. , Pyenson Bruce S. , Shockney Lillie D. , Smith Robert A. , Wiener Renda Soylemez , White Charles S. , Thomson Carey C. ,   for the ACS NLCRT Implementation Strategies Task Group
Published: September 2024

More than a decade has passed since researchers in the Early Lung Cancer Action Project and the National Lung Screening Trial demonstrated the ability to save lives of high‐risk individuals from lung cancer through regular screening by low dose computed tomography scan. The emergence of the most recent findings in the Dutch–Belgian lung‐cancer screening trial (Nederlands–Leuvens Longkanker Screenings Onderzoek [NELSON]) further strengthens and expands on this evidence. These studies demonstrate the benefit of integrating lung cancer screening into clinical practice, yet lung cancer continues to lead cancer mortality rates in the United States. Fewer than 20% of screen eligible individuals are enrolled in lung cancer screening, leaving millions of qualified individuals without the standard of care and benefit they deserve. This article, part of the American Cancer Society National Lung Cancer Roundtable (ACS NLCRT) strategic plan, examines the impediments to successful adoption, dissemination, and implementation of lung cancer screening. Proposed solutions identified by the ACS NLCRT Implementation Strategies Task Group and work currently underway to address these challenges to improve uptake of lung cancer screening are discussed.

Plain language summary

The evidence supporting the benefit of lung cancer screening in adults who previously or currently smoke has led to widespread endorsement and coverage by health plans. Lung cancer screening programs should be designed to promote high uptake rates of screening among eligible adults, and to deliver high‐quality screening and follow‐up care.
The American Cancer Society National Lung Cancer Roundtable strategic plan: Current challenges and future directions for shared decision making for lung cancer screening
Authors: Volk Robert J. , Myers Ronald E. , Arenberg Douglas , Caverly Tanner J. , Hoffman Richard M. , Katki Hormuzd A. , Mazzone Peter J. , Moulton Benjamin W. , Reuland Daniel S. , Tanner Nichole T. , Smith Robert A. , Wiener Renda Soylemez
Published: September 2024

Shared decision making (SDM) between health care professionals and patients is essential to help patients make well informed choices about lung cancer screening (LCS). Patients who participate in SDM have greater LCS knowledge, reduced decisional conflict, and improved adherence to annual screening compared with patients who do not participate in SDM. SDM tools are acceptable to patients and clinicians. The importance of SDM in LCS is emphasized in recommendations from professional organizations and highlighted as a priority in the 2022 President's Cancer Panel Report. The updated 2022 national coverage determination from the Centers for Medicare & Medicaid Services reaffirms the value of SDM in offering LCS to eligible beneficiaries. The Shared Decision‐Making Task Group of the American Cancer Society National Lung Cancer Roundtable undertook a group consensus process to identify priorities for research and implementation related to SDM for LCS and then evaluated current knowledge in these areas. Priority areas included: (1) developing feasible, adaptable SDM training programs for health care professionals; (2) understanding the impact of alternative health system LCS models on SDM practice and outcomes; (3) developing and evaluating new patient decision aids for use with diverse populations and in varied settings; (4) offering conceptual clarity about what constitutes a high‐quality decision and developing appropriate quality measures; and (5) studying the use of prediction‐augmented screening to support SDM in practice. Gaps in current research in all areas were observed. The authors conclude with a research and implementation agenda to advance the quality and implementation of SDM for persons who might benefit from LCS.
Evaluating Quinolines: Molecular Dynamics Approach to Assess Their Potential as Acetylcholinesterase Inhibitors for Alzheimer's Disease.
Authors: Prejanò Mario , Romeo Isabella , Felipe Hernández‐Ayala Luis , Gabriel Guzmán‐López Eduardo , Alcaro Stefano , Galano Annia , Marino Tiziana
Published: September 2024

Quinoline represents a promising scaffold for developing potential drugs because of the wide range of biological and pharmacological activities that it exhibits. In the present study, quinoline derivatives obtained from CADMA‐Chem docking protocol were investigated in the mean of molecular dynamics simulations as potential inhibitors of acetylcholinesterase enzyme. The examined species can be partitioned between neutral, dq815 (2,3 dihydroxyl‐quinoline‐4‐carbaldehyde), dq829 (2,3 dihydroxyl‐quinoline‐8‐carboxylic acid methane ester), dq1356 (3,4 dihydroxyl‐quinoline‐6‐carbaldehyde), dq1368 (3,4 dihydroxyl‐quinoline‐8‐carboxylic acid methane ester) and dq2357 (5,6 dihydroxyl‐quinoline‐8‐carboxylic acid methane ester), and deprotonated, dq815_dep, dq829_dep, dq1356_dep and dq2357_dep. Twelve molecular dynamics simulations were performed including those of natural acetylcholine, of the well‐known donepezil inhibitor and of the founder quinoline chosen as reference. Key intermolecular interactions were detected and discussed to describe the different dynamic behavior of all the considered species. Binding energies calculation from MMPBSA well accounts for the dynamic behavior observed in the simulation time proposing dq1368 as promising candidate for the inhibition of acetylcholinesterase. Retrosynthetic route for the production of the investigated compounds is also proposed.
Photoinduced Anisotropy in Thin Films of Azobenzene‐Containing Liquid Crystalline Supramolecular Complexes of Various Polymer Architecture
Authors: Bugakov Miron , Shibaev Valery , Boiko Natalia
Published: September 2024

Light patternable colorless liquid crystalline (LC) polymers are promising materials for functional photonic devices with broad applications in optical communication, diffractive optics, and displays. This work reports photoinduced optical anisotropy in thin films of azobenzene‐containing (Azo) LC block copolymer supramolecular complexes, which can be decolorized after light patterning providing colorless patterned birefringent polymer films. The supramolecular complexes are prepared via intermolecular pyridine–phenol hydrogen bonding between a low‐molecular‐weight Azo phenol and host LC AB diblock and ABA triblock copolymers consisted of LC phenylbenzoate (PhM) blocks and poly(vinylpyridine) units. The molecular architecture of the host polymers and the morphological pattern formed by the complexes can affect orientational behavior of Azo groups under irradiation with linearly polarized light. Photoorientation of hydrogen‐bonded Azo groups is accompanied by the cooperative orientation of non‐photochromic PhM units, which form individual microphases and stabilize the orientation of Azo groups. This effect is specific for block copolymer complexes and it is absent for random copolymer complex, which is used as a reference sample. Optical anisotropy induced in films of the block copolymer complexes can be amplified by heating above the glass transition temperature and subsequent rinsing with diethyl ether allows colorless birefringent polymer films to be prepared.
Quantitative Characterization of Fluorine‐Centered Noncovalent Interactions in Crystalline Benzanilides
Authors: Kumar Mondal Pradip , Shukla Rahul , Khandelwal Saurish , Sharma Kartikay , Gonde Shivani , Biswas Subha , Som Shubham , Chopra Deepak
Published: September 2024

Six isomeric molecules, featuring a minimum of three fluorine atoms on either the benzoyl or aniline side, have been synthesized, crystallized and characterized through single crystal X‐ray diffraction (SCXRD). In addition, two other compounds, containing six fluorine atoms, three on each of the benzoyl and aniline side of the benzanilide scaffold have also been characterized through SCXRD. This current study aims to augment the capacity for hydrogen bond formation, specifically involving organic fluorine, by elevating the acidity of the involved hydrogens through the incorporation of highly electronegative fluorine atoms, in the presence of strong N−H⋅⋅⋅O=C H‐bonds. Lattice energy calculations and assessment of intermolecular interaction energies elucidate the contributions of electrostatics and dispersion forces in crystal packing. The topological analysis of the electron density is characterized by the presence of bond critical points (BCPs) involving C−H⋅⋅⋅F and F⋅⋅⋅F contacts, thus establishing the bonding nature of these interactions which play a crucial role in the crystal packing in addition to the presence of traditional N−H⋅⋅⋅O=C H‐bonds.
A QSPR Model for Henry's Law Constants of Organic Compounds in Water and Ethanol for Distilled Spirits
Authors: White John , Graf Johnathan , Haines Samuel , Sathitsuksanoh Noppadon , Eric Berson R. , Jaeger Vance W.
Published: September 2024

Henry's law describes the vapor‐liquid equilibrium for dilute gases dissolved in a liquid solvent phase. Descriptions of vapor‐liquid equilibrium allow the design of improved separations in the food and beverage industry. The consumer experience of taste and odor are greatly affected by the liquid and vapor phase behavior of organic compounds. This study presents a machine learning (ML) based model that allows quick, accurate predictions of Henry's law constants (kH) for many common organic compounds. Users input only a Simplified Molecular‐Input Line‐Entry System (SMILES) string or a common English name, and the model returns Henry's law estimates for compounds in water and ethanol. Training was performed on 5,690 compounds. Training data were gathered from an existing database and were supplemented with quantum mechanical (QM) calculations. An extra trees regression model was generated that predicts kH with a mean absolute error of 1.3 in log space and an R2 of 0.98. The model is applied to common flavor and odor compounds in bourbon whiskey as a test case for food and beverage applications.
Platelet Ceria Catalysts from Solution Combustion and Effect of Iron Doping for Synthesis of Dimethyl Carbonate from CO2
Authors: Rusta Nicoletta , Mameli Valentina , Ricci Pier Carlo , Porcu Stefania , Seeharaj Panpailin , Marciniak Aryane A. , Santos Evelyn C. S. , Alves Odivaldo Cambraia , Mota Claudio J. A. , Rombi Elisabetta , Cannas Carla
Published: September 2024

Solution combustion (SC) remains among the most promising synthetic strategies for the production of crystalline nanopowders from an aqueous medium, due to its easiness, time and cost‐effectiveness, scalability and eco‐friendliness. In this work, this method was selected to obtain anisometric ceria‐based nanoparticles applied as catalysts for the direct synthesis of dimethyl carbonate. The catalytic performances were studied for the ceria and Fe‐doped ceria from SC (CeO2‐SC, Ce0.9Fe0.1O2‐SC) in comparison with the ceria nanorods (CeO2‐HT, Ce0.9Fe0.1O2‐HT) obtained by hydrothermal (HT) method, one of the most studied systems in the literature. Indeed, the ceria nanoparticles obtained by SC were found to be highly crystalline, platelet‐shaped, arranged in a mosaic‐like assembly and with smaller crystallite size (≈6 nm vs. ≈17 nm) and higher surface area (80 m2 g−1 vs. 26 m2 g−1) for the undoped sample with respect to the Fe‐doped counterpart. Although all samples exhibit an anisometric morphology that should favor the exposition of specific crystalline planes, HT‐samples showed better performances due to higher oxygen vacancies concentration and lower amount of strong basic and acid sites.
Interplay Between the N→C Dative Bond, Intramolecular Chalcogen Bond and π Conjugation in the Complexes Formed by Cyclo[18]carbon and C14 Polyyne with 1,2,5‐Chalcogenadiazoles
Authors: Zhang Yu , Wang Weizhou
Published: September 2024

The N→C dative bond (DB), intramolecular chalcogen bond and π conjugation play important roles in determining the structures and properties of some molecular carbon materials and organic/polymeric photovoltaic materials. In this work, the interplay between the N→C DB, intramolecular chalcogen bond and π conjugation in the complexes formed by cyclo[18]carbon and C14 polyyne with 1,2,5‐chalcogenadiazoles has been investigated in detail by using reliable quantum chemical calculations. This study has made four main findings. First, only the Te‐containing complexes bound by N→C DBs are much more stable than their corresponding van der Waals (vdW) complexes. Second, in addition to through‐bond π conjugations, through‐space π conjugations also exist in some Se/Te‐containing complexes bound by N→C DBs. Third, the cooperativity between intramolecular chalcogen bond, π conjugation between two monomers and N→C DB is not very strong and can be ignored. Fourth, compared to π conjugations, intramolecular Ch⋅⋅⋅C (Ch=O, S, Se, Te) chalcogen bonds play a secondary role in stabilizing the complexes bound by N→C DBs. These findings clearly indicate that the role of “conformational lock”, popular in the field of organic optoelectronic materials, may have been greatly overestimated.
Spectroscopic Response of Chiral Proteophenes Binding to Two Chiral Insulin Amyloids
Authors: Watanabe Takahiro , Swaminathan Priyanka , Björk Linnea , Nakanishi Ayaka , Sato Hisako , Zako Tamotsu , Nilsson K. P. R. , Lindgren Mikael
Published: September 2024

We recently reported on 8 different pentameric oligothiophenes, denoted proteophenes, with different amino acid substitution patterns along the conjugated thiophene backbone. The proteophenes were forming chiral both molecular (solvent dissolved) and self‐assembled nano‐architectonic structures, the latter having approximately 5–6 times greater ICD responses. Herein, two proteophenes, HS‐84‐E−E and HS‐84‐K−K, were further investigated in terms of binding to two chiral variants of insulin amyloid fibrils. Binding curves based on fluorescence revealed strong primary binding sites for both proteophenes and more unspecific secondary binding for especially the latter. Interestingly, their induced circular dichroism (ICD) responses were similar to or stronger than for their solvent form and showed a complicated alteration upon binding suggesting that the microstructure at the binding site governs the helical structure of the ligand. Hyperspectral fluorescence microscopy and FLIM revealed more details on the molecular binding in terms of proteophene emission decay‐times. Vibrational circular dichroism (VCD) analysis showed that VCD signal of amyloid fibrils was enhanced upon binding of proteophenes, suggesting changes in the amyloid microstructures.
Validation of regression‐based change formulae for mild cognitive impairment and Alzheimer's disease
Authors: Duff Kevin , Sevigny‐Resetco Deborah
Published: September 2024

INTRODUCTION

Identification of cognitive decline is critical in older adults at risk for dementia. In a 2020 study reported in Archives of Clinical Neuropsychology, Kiselica and colleagues developed standardized regression‐based (SRB) change formulae for the Uniform Data Set 3.0 Neuropsychological Battery in cognitively unimpaired older adults. However, validation of their applicability in impaired individuals is needed.

METHODS

Using longitudinal data on 5974 participants (cognitively unimpaired, mild cognitive impairment, dementia) from the National Alzheimer's Coordinating Center, SRB change scores were calculated for each individual and compared across groups.

RESULTS

Across 6 to 24 months, minimal cognitive change was observed in cognitively unimpaired participants. Modest declines were seen in those with mild cognitive impairment and substantial declines in those with dementia. Change scores were negatively correlated with the Clinical Dementia Rating scale. In impaired individuals, SRB scores indicated more decline in those with positive amyloid scans.

DISCUSSION

Validation of SRB scores affords greater confidence in employing them in clinical and research settings.

Highlights

Validation of regression‐based cognitive change scores in impaired samples.

Clear differences on change scores across three groups (intact, MCI, dementia).

Largely stable scores in intact participants, but notable decline in MCI and dementia.

Moderate to strong relationship between change scores and the Clinical Dementia Rating scale sum of boxes.
Q&A: 5 questions with Lisa Weinberger
Authors: Talarico Donna
Published: September 2024

In our recurring “5 questions with” series, the Recruiting and Retaining Adult Learners marketing column profiles a communications professional through a brief Q&A. This month, we introduce you to Lisa Weinberger, search engine optimization (SEO) manager at University of Maryland Global Campus (UMGC).
Explainable machine learning and online calculators to predict heart failure mortality in intensive care units
Authors: Chen An‐Tian , Zhang Yuhui , Zhang Jian
Published: September 2024

Aims

This study aims to develop explainable machine learning models and clinical tools for predicting mortality in patients in the intensive care unit (ICU) with heart failure (HF).

Methods

Patients diagnosed with HF who experienced their first ICU stay lasting between 24 h and 28 days were selected from the Medical Information Mart for Intensive Care IV (MIMIC‐IV) database. The primary outcome was all‐cause mortality within 28 days. Data analysis was performed using Python and R, with feature selection conducted via least absolute shrinkage and selection operator (LASSO) regression. Fifteen models were evaluated, and the most effective model was rendered explainable through the Shapley additive explanations (SHAP) approach. A nomogram was developed based on logistic regression to facilitate interpretation. For external validation, the eICU database was utilized.

Results

After selection, the study included 2343 records, with 1808 surviving and 535 deceased patients. The median age of the study population was 70.00, with ~3/5 males (60.31%). The median length of stay in the ICU was 6.00 days. The median age of the survival group was younger than the non‐survival group (69.00 vs. 73.00), and non‐survival patients spent longer time in the ICU. Seventy‐five features were initially selected, including basic information, vital signs, laboratory tests, haemodynamics and oxygen status. LASSO regression determined the shrinkage parameter α = 0.020, and 44 features were chosen for model construction. The linear discriminant analysis (LDA) model showed the best performance, and the accuracy reached 0.8354 in the training cohort and 0.8563 in the testing cohort. It showed satisfying area under the curve (AUC), recall, precision, F1 score, Cohen's kappa score and Matthew's correlation coefficient. The concordance index (c‐index) reached 0.7972 in the training cohort and 0.8125 in the testing cohort. In external validation, the LDA model achieved approximately 0.9 in accuracy, precision, recall and F1 score, with an AUC of 0.79. Univariable analysis was performed in the training cohort. Features that differed significantly between the survival and non‐survival groups were subjected to multiple logistic regression. The nomogram built on multiple logistic regression included 14 features and demonstrated excellent performance. The AUC of the nomogram is 0.852 in the training cohort, 0.855 in the internal validation cohort and 0.770 in the external validation cohort. The calibration curve showed good consistency.

Conclusions

The study developed an LDA and a nomogram model for predicting mortality in HF patients in the ICU. The SHAP approach was employed to elucidate the LDA model, enhancing its utility for clinicians. These models were made accessible online for clinical application.
An energy consumption rectification method based on Bayesian linear regression and heating degree‐days
Authors: Sun Shouchen , Wang Jiandong , Sun Qingdian , Zhao Changsheng
Published: September 2024

The time‐varying external environment is one of the main variables influencing heating energy consumptions, so that its influence should be rectified when energy savings of different heating modes are calculated. This paper proposes an energy consumption rectification method based on Bayesian linear regression and heating degree‐days, to obtain heating energy consumptions without the influence of different outdoor temperatures. The proposed method consists of three main steps. First, a physical model of heating houses is used to prove a relationship between energy consumptions and heating degree‐days. Second, Bayesian linear regression is exploited to estimate uncertainty ranges of heating energy consumptions. Finally, heating energy consumptions are rectified, and energy savings with their uncertainty ranges for different heating modes under the same outdoor temperature are obtained. The proposed method does not require the physical parameters of heating houses to facilitate practical implementation. Additionally, it provides uncertainty ranges of heating energy consumptions to measure the estimation accuracy. Numerical and experimental examples show that the proposed method provides more accurate estimates of heating energy consumptions than existing methods.
Potential of natural stimulants and spirulina algae extracts on Cape gooseberry plant: A study on functional properties and enzymatic activity
Authors: Heydarnajad Giglou Rasoul , Torabi Giglou Mousa , Hatami Mehrnaz , Ghorbanpour Mansour
Published: September 2024

The need to discover new strategy to enhance agricultural productivity while minimizing negative effects on cultivation system is the driving force behind much novel research. Little is known about the use of natural growth promoters, in combination with Spirulina algae extract (Sae), on plants' quality and quantity characteristics. This can be an effective strategy to reduce the impact of environmental stress on plants. The aim of this study was to investigate the effects of natural growth promoters in combination with Sae on the functional properties and enzymatic activity of Cape gooseberry plants. For this purpose, natural growth stimulants, Kitoplus® and Azotobacter, were foliar applied to plants in a completely randomized factorial design under greenhouse conditions, with varying concentrations of Sae. Results indicated that the use of Sae in conjunction with natural growth promoters had a significant impact on increasing the yield of Cape gooseberry plants. The study found that using Kitoplus® and Spirulina extract at a concentration of 0.5% increased the yield of Cape gooseberry plants by 35.82% compared to control plants, with a yield of 310.43 g per plant. The leaves of Physalis plants treated with 0.5% Kitoplus®, Azotobacter biofertilizer, and Sae had the highest amount of chlorophyll, which was observed to be 46.2%, 40.1%, and 32.3% higher than that of control, respectively. Exposure to Kitoplus® (0.5%) and Azotobacter biofertilizer (0.5%) resulted in the highest percentage (25.49%) of dry to fresh weight ratio (DF) per fruit in the plant. Additionally, plants treated with Kitoplus® at 0.5% in combination with Azotobacter (0.5%) and Sae (0.5%) showed a 14.83% increase in vitamin C (VITC) levels compared to control plants. The highest levels of total antioxidant content (73.8%) and total carbohydrate content were obtained from plants treated with Spirulina algae extract spray at a concentration of 0.5% in the presence of Kitoplus® and Azotobacter. Results also showed that the highest activity of peroxidase (POD) (by 43.5% and 38.8%) and ascorbate peroxidase (APX) (by 29.1% and 28.4%) enzymes was observed in plants sprayed with natural growth promoters in the presence of Spirulina algae extract at concentrations of 0.25% and 0.5%, respectively. Overall, this research opens the possibility of utilizing foliar spray of effective biostimulants in combination with Sae to improve the quantity and quality of Cape gooseberry plants. Implementing this simple, safe, eco‐friendly, and low‐cost management tool can result in nutritionally rich fruit that benefits the consumer at little or no additional cost.
Kinetic Insights into Methanol Synthesis from CO2 Hydrogenation at Atmospheric Pressure over Intermetallic Pd2Ga Catalyst
Authors: Ahmad Kaisar , Dabbawala Aasif Asharafbhai , Polychronopoulou Kyriaki , Anjum Dalaver , Gacesa Marko , Abi Jaoude Maguy
Published: September 2024

This study presents a single‐site microkinetic model for methanol synthesis by CO2 hydrogenation over intermetallic Pd2Ga/SiO2. A reaction path analysis (RPA) combining theoretical results and realistic catalyst surface reaction data is established to elucidate the reaction mechanism and kinetic models of CO2 hydrogenation to methanol and CO. The RPA leads to the derivation of rate expressions for both reactions without presumptions about the most abundant reactive intermediate (MARI) and rate‐determining step (rds). The formation of H2COOH* is found to be the rds (step 19) for methanol synthesis via the formate pathway, with CO2 and H‐atoms adsorbed on intermetallic sites as the MARIs. The derived kinetic model is corroborated with experimental data acquired under different reaction conditions, using a lab‐scale fixed‐bed reactor and Pd2Ga/SiO2 nanoparticles prepared by incipient wetness impregnation. The excellent agreement between the experimental data and the kinetic model (R2 = 0.99) substantiates the proposed mechanism with an activation energy of 61.52 kJ mol‐1 for methanol synthesis. The reported catalyst exhibits high selectivity to methanol (96%) at 1 bar, 150 °C, and H2/CO2 ratio of 3:1. These findings provide critical insights to optimize catalysts and processes targeting CO2 hydrogenation at atmospheric pressure and low temperatures for on‐demand energy production.
Microglial morphology aligns with vigilance stage‐specific neuronal oscillations in a brain region‐dependent manner
Authors: Steffens Sarah , Mäkinen Hilla , Stenberg Tarja , Wigren Henna‐Kaisa
Published: September 2024

Microglia, the resident immune cells in the brain, dynamically adapt their morphology based on their functional state. This study explored the relationship between microglial morphology and sleep–wake cycles in mice. Using Iba1 immunostaining to identify microglia, we quantified morphological changes in microglia at different timepoints in multiple brain regions (cortex, hippocampus, basal forebrain, hindbrain, and cerebellum) in B6 male mice using semi‐automated 3D structural analysis. Simultaneously, in a separate group, we monitored wake and sleep stage‐specific brain activity using EEG/EMG recordings. During natural sleep–wake cycles, we observed increased microglial complexity (enlarged volume, territorial coverage, and ramification) during wakefulness, characterized by high‐frequency theta (8–12 Hz) and gamma activity (30–80 Hz). Conversely, during NREM sleep, which is dominated by delta activity (0.5–4 Hz), microglia displayed reduced complexity. Notably, this pattern was absent in brain regions lacking direct functional connections to areas generating vigilance stage‐dependent thalamocortical oscillations. We then extended wakefulness to decouple circadian influence from sleep–wake‐specific neuronal activity. This procedure attenuated the decrease in microglial complexity observed during natural sleep, suggesting a crucial role for neuronal activity. Subsequent recovery sleep restored microglial features, independent of the time of day (zeitgeber time). These findings reveal a dynamic interplay between vigilance stage‐specific thalamocortical activity and microglial morphology across various brain regions. This suggests a potential role for microglia in sleep regulation and warrants further investigation to understand the underlying mechanisms.
Individual‐specific metabolic network based on 18F‐FDG PET revealing multi‐level aberrant metabolisms in Parkinson's disease
Authors: Lu Weizhao , Song Tianbin , Li Jiping , Zhang Yuqing , Lu Jie
Published: September 2024

Metabolic network analysis in Parkinson's disease (PD) based on 18F‐FDG PET has revealed PD‐related metabolic patterns. However, alterations at the systemic metabolic network level and at the connection level between different brain regions still remain unknown. This study aimed to explore metabolic network alterations at multiple network levels among PD patients using an individual‐specific metabolic network (ISMN) approach. 18F‐FDG‐PET images of patients with PD (n = 34) and healthy subjects (n = 47) were collected. Healthy subjects were further separated into reference group (n = 28) and control group (n = 19) randomly. Standardized uptake value normalized by lean body mass ratio (SULr) maps was calculated from the PET images. ISMNs were constructed based on SULr maps for PD patients and controls with reference to the reference group. Comparisons of nodal and edge features were performed between PD and control groups. Correlation analysis was conducted between multilevel network properties and clinical scales in PD group. A linear classifier was trained based on nodal or edge features to distinguish PD from controls. The distance from each patient's ISMN to the group‐level difference network showed a negative correlation with Hoehn and Yahr stage (r = −0.390, p = .023). Eight nodes from ISMN were identified which exhibited significantly increased nodal degree in PD patients compared to controls (p < .05). Eleven edges were observed which demonstrated significant distinctions in Z‐score values in comparisons to the control group (p < .05). Furthermore, the nodal and edge features showed comparable performances in PD diagnosis compared to the traditional SULr values, with area under the receiver operating characteristic curve larger than 0.91. The proposed ISMN approach revealed systemic metabolic deviations, as well as nodal and edge distinctions in PD, which might be supplementary to the existing findings on PD‐related metabolic patterns.
Changes in the structure of spontaneous speech predict the disruption of hierarchical brain organization in first‐episode psychosis
Authors: He Rui , Alonso‐Sánchez Maria Francisca , Sepulcre Jorge , Palaniyappan Lena , Hinzen Wolfram
Published: September 2024

Psychosis implicates changes across a broad range of cognitive functions. These functions are cortically organized in the form of a hierarchy ranging from primary sensorimotor (unimodal) to higher‐order association cortices, which involve functions such as language (transmodal). Language has long been documented as undergoing structural changes in psychosis. We hypothesized that these changes as revealed in spontaneous speech patterns may act as readouts of alterations in the configuration of this unimodal‐to‐transmodal axis of cortical organization in psychosis. Results from 29 patients with first‐episodic psychosis (FEP) and 29 controls scanned with 7 T resting‐state fMRI confirmed a compression of the cortical hierarchy in FEP, which affected metrics of the hierarchical distance between the sensorimotor and default mode networks, and of the hierarchical organization within the semantic network. These organizational changes were predicted by graphs representing semantic and syntactic associations between meaningful units in speech produced during picture descriptions. These findings unite psychosis, language, and the cortical hierarchy in a single conceptual scheme, which helps to situate language within the neurocognition of psychosis and opens the clinical prospect for mental dysfunction to become computationally measurable in spontaneous speech.
Evaluating a process‐guided deep learning approach for predicting dissolved oxygen in streams
Authors: Sadler Jeffrey M. , Koenig Lauren E. , Gorski Galen , Carter Alice M. , Hall Robert O.
Published: September 2024

Dissolved oxygen (DO) is a critical water quality constituent that governs habitat suitability for aquatic biota, biogeochemical reactions and solubility of metals in streams. Recently introduced high‐frequency sensors have increased our ability to measure DO, but we still lack the capacity to understand and predict DO concentrations at high spatial resolutions or in unmonitored locations. Machine learning (ML) has been a commonly used approach for modelling DO, however, conventional ML models have no representation of the limnological processes governing DO dynamics. Here we implement and evaluate two process‐guided deep learning (PGDL) approaches for predicting daily minimum, mean and maximum DO concentrations in rivers from the Delaware River Basin, USA. In both cases, a multi‐task approach was taken in which the PGDL models predicted stream metabolism and gas exchange rates in addition to the DO concentrations themselves. Our results showed that for these sites, the PGDL approaches did not improve upon baseline predictions in temporal and spatially similar holdout experiments. One of the approaches did, however, improve predictions when applied to spatially dissimilar sites. Although this particular PGDL approach did not improve predictive accuracy in most cases, our results suggest that process guidance, perhaps a more constrained approach, could benefit a data‐driven DO model.
Malignant salivary gland tumors of the tongue: A multicenter REFCOR study
Authors: Poissonnet Valentine , Uro‐Coste Emmanuelle , Chabrillac Emilien , Modesto Anouchka , Even Caroline , Fakhry Nicolas , Garrel Renaud , Malard Olivier , Chatelet Florian , Dupin Charles , Jegoux Franck , Schultz Philippe , Culié Dorian , Baudouin Robin , Evrard Diane , Ransy Pierre , Morinière Sylvain , Mirghani Haitham , Mouawad François , Righini Christian , Duflo Suzy , Marie Jean‐Paul , Jourdan‐Soulier Florence , Atallah Sarah , Brenet Esteban , Bertolus Chloé , Ceruse Philippe , Ramin Lionel , Dufour Xavier , Nguyen Duc Trung , Bastit Vianney , Segier Bertille , Vergez Sébastien
Published: September 2024

Salivary carcinomas of minor salivary glands are very infrequent tumors. When located in the tongue, the therapeutic strategy may comprise upfront surgery, which may be debilitating, and/or (chemo‐)radiotherapy. The aim of this study was to identify the prognostic factors of salivary carcinomas of the tongue in a population‐based cohort. This retrospective multicentric study, based on the “Réseau d'Expertise Français sur les Cancers ORL Rares” (REFCOR), included all the patients with a salivary carcinoma of the tongue, diagnosed between January 2009 and December 2018. Dubious slides were reviewed by REFCOR expert pathologists to ensure diagnostic accuracy. Treatment was performed in accordance with national REFCOR recommendations. From 28 centers, 103 patients were included in this study. Median age at diagnosis was 63 years, and 60.2% were female. Tumors were adenoid cystic carcinomas (41.7%), mucoepidermoid carcinomas (30.1%), and other adenocarcinomas (28.2%). Primary treatment was surgical for 61.2% of them. Five‐year overall survival (OS) and event‐free survival (EFS) rates were 84.7% and 38.6%, respectively. In multivariable analysis, EFS was significantly worse in case of nonsurgical treatment, alcohol consumption, and glossotonsillar sulcus involvement. N‐positive status was the only significant prognostic factor for OS in multivariable analysis. Salivary carcinomas of the tongue represent a heterogeneous group of rare tumors, with a high risk of recurrence. In this national cohort, surgery was associated with better EFS and N‐status was the main independent prognostic factor for OS.
Data simulations for advancing psychological research: Insights, preparations and investigations
Authors: Auger Victor , Normand Alice
Published: September 2024

Simulation has become an essential tool in psychological research, offering unique insights into statistical concepts, optimising research project planning and modelling human behaviour and cognition. This tutorial navigates simulations' diverse applications across various research stages. This tutorial begins by demonstrating simulations' impact on understanding statistical concepts. Amidst growing demands for effect size reporting and interpretation, simulations can help clarify the relationship between data and effect sizes, benefiting both educational purposes and advanced research. Simulations play a crucial role in planning psychological research. They provide flexible solutions for power, helping to determine necessary sample sizes and aiding in robust research planning, providing evidence of planned procedures. Simulations are pivotal in exploring human behaviour and cognition, as well as statistical method properties. By forcing researchers to translate verbal theory into formal models, simulation can help specify the assumptions. The paper also discusses improving simulation efficiency, such as using calculation clusters, optimising simulation practices and recognises simulations' limitations. This paper emphasises simulations' versatile role in psychological research. They enable deep insights into complex datasets, streamline project preparation and uncover subtleties in human behaviour, cognition and statistical methodologies.
Network Pharmacology, Molecular Docking, and Molecular Dynamics Study to Explore the Effect of Resveratrol on Type 2 Diabetes
Authors: Martínez‐Esquivias Fernando , Guzmán‐Flores Juan Manuel , Reyes‐Chaparro Andrés , Sánchez‐Enríquez Sergio , Anaya‐Esparza Luis Miguel
Published: September 2024

This network pharmacology study represents a significant step in understanding the potential of Resveratrol as an antidiabetic agent and its molecular targets. Targets for Type 2 diabetes were obtained from the MalaCards and DisGeNET databases, while targets for Resveratrol were sourced from the STP and CTD databases. Subsequently, we performed matching to identify common disease‐compound targets. The identified genes were analyzed using the ShinGO‐0.76.3 database for functional enrichment analysis and KEGG pathway mapping. A protein−protein interaction network was then constructed using Cytoscape software, and hub genes were identified. These hub genes were subjected to molecular docking and dynamic simulations using AutoDock Vina and Gromacs software. According to functional enrichment and KEGG pathway analysis, Resveratrol influences insulin receptors, endoplasmic reticulum functions, and oxidoreductase activity and is involved in the estrogen and HIF‐1 pathways. Ten hub genes were identified, including ESR1, PTGS2, SRC, NOS3, MMP9, IGF1R, CYP19A1, MTOR, MMP2, and PIK3CA. The proteins associated with these genes exhibited high interaction with Resveratrol in the molecular docking analysis, and molecular dynamics showed a stable interaction of Resveratrol with ESR1, MMP9, PIK3CA, and PTGS2. In conclusion, our work enhances the understanding of the antidiabetic activity of Resveratrol, which future studies should experimentally corroborate.
Prenatal and postnatal imaging for early detection of sirenomelia: A case study
Authors: Yao Mengxia , Wang Yin , Liu Yanying
Published: September 2024

Sirenomelia is a rare congenital caudal abnormality. We applied two‐dimensional, three‐dimensional, and color Doppler ultrasound to diagnose a fetus with sirenomelia at 12 + 6 weeks. The fetus exhibited on ultrasound fused lower limbs, two tibiae in lower legs, no fibulae, knees in retroflexion, pelvic hypoplasia, hypoplasia of the lower lumbar vertebrae and coccyx, bilateral renal agenesis, no bladder, and a single umbilical artery. The postnatal X‐ray revealed a fetus with two femurs, two tibiae, and no fibula. The results of chorionic villus aspiration indicated that the fetus was male with a normal karyotype (46, XY), and the microarray results were normal.
Arylation of 2‐Chloro‐3‐(4,6‐Diaryl‐1,3,5‐Triazin‐2‐yl) Quinolines: Formal Synthesis of 3‐(4,6‐Diaryl‐1,3,5‐Triazin‐2‐yl)‐2‐Substituted Quinolines by Suzuki–Miyaura Reaction
Authors: Jeon Joo‐Hyun , Lee Han‐Joo , Kim Jin‐Hee , Hawsawi Mohammed B. , Jalani Hitesh B. , Jeong Jin‐Hyun
Published: September 2024

We have described herein a simple and formal two‐step synthesis of 3‐(4,6‐diaryl‐1,3,5‐triazin‐2‐yl)‐2‐aryl quinolines from 2‐chloro‐3‐(4,6‐diaryl‐1,3,5‐triazin‐2‐yl) quinolines and boronic acids under the Suzuki–Miyaura conditions. This protocol provides the C‐2 arylation of 2‐chloro‐3‐(4,6‐diaryl‐1,3,5‐triazin‐2‐yl) quinolines under the mild reaction conditions. These newly formed chemo‐types may be useful in drug discovery programs or in material chemistry.
How bureaucratic competition shapes foreign aid allocation: The case of South Korea's aid agencies
Authors: Whang Taehee , McLean Elena V. , Yu Chamseul
Published: September 2024

What explains aid allocation–donor interests or recipient needs? This research debate has generated a number of studies, which generally conclude that both motivations matter. One limitation of this literature is that donor governments are conceptualized as unitary actors with coherent preferences. In this study, we relax this assumption and focus on the interests and interactions of bureaucratic agencies within a donor government. We argue that these agencies compete as they seek to control a larger share of the foreign aid budget because foreign aid is a valuable policy instrument for bureaucratic agencies. This competition results in emulation: the agency that leads the government's development cooperation policy emulates other agencies' provision of domestic benefits, while the lead agency's competitors mimic its aid allocation patterns. We test our expectations using data on bilateral aid disbursed by four bureaucratic agencies of the South Korean government and find evidence of both types of emulation strategies. Our results point to the role played by a mostly overlooked group of domestic‐level actors in donor countries and the importance of bureaucratic politics and competition.
Win‐win or tradeoff? Investigating the hybridity of impact investing in Cambodia's microfinance industry
Authors: Park Kyungmin , Jun Hannah
Published: September 2024

Impact investing plays a critical role in financing enterprises that have the potential to tackle social problems through business means, particularly in developing countries. However, concerns about over‐indebtedness of microfinance institutions have fueled questions regarding potential trade‐offs between financial and social efficiency of impact investing and demand further investigation. Using the case of Cambodia's microfinance industry, this paper first examines whether the microfinance industry outperforms from the perspective of both social and financial returns. In addition, as impact investments by Development Finance Institutions (DFIs) form the backbone of the microfinance sector, a related objective is to investigate whether social or financial returns are more important for DFIs when making impact investment decisions. Using Data Envelopment Analysis (DEA) and Tobit regression, our research finds that while Cambodian MFIs excel in financial efficiency, social efficiency is considerably lower. The analysis also finds that DFIs' investments are predominantly driven by financial efficiency rather than an approach that considers both social and financial outcomes. Our analysis suggests the need for enhanced impact measurement frameworks and a reevaluation of DFIs impact investing strategies to ensure a more equitable focus on both financial and social impacts.
Amino Acid Composition Determination From the Fractional Mass of Peptides
Authors: Downard Kevin M. , Cody Robert B.
Published: September 2024

A peptide's fractional mass is directly associated with its elemental composition and thus amino acid composition. Here it is demonstrated that a peptide's fractional mass alone can be a useful identifier or indicator of that composition for small to mid‐sized peptides (5–7 amino acids) and can significantly reduce the number of viable amino acid compositions for larger peptides (> 8 residues) to include or exclude certain possibilities. Separate consideration of the integer portion of the peptide's mass helps to reduce the number of possibilities where many duplicate fractional mass values are found. Adoption of this fractional mass strategy should aid approaches that are presently employed for peptide identification, including in the use of mass map data to search protein databases for proteomics applications.
Research on microbial diversity and nutritional flavor formation of Xianju wheat paste
Authors: Xiao Yao , Feng Wu , Chen Jiaping , Li Yuanyuan , Liu Yating
Published: September 2024

BACKGROUND

Xianju wheat paste, a traditional condiment in Hubei Province, China, possesses nutritional value and a distinctive taste profile. Nevertheless, there remains a dearth of comprehensive comprehension regarding the intricate interplay between the microbial population and its nutritional profile in Xianju wheat paste.

RESULTS

It was determined that Xianju wheat paste harbors predominant microbial genera such as Bacillus, Staphylococcus and Aspergillus. The findings from high‐throughput sequencing analysis revealed the presence of 11 bacterial genera in Xianju wheat paste, with relative abundances exceeding 1%. These genera included Bacillus, Staphylococcus, Brevibacterium, Lactobacillus, Allorhizobium‐Neorhizobium‐Pararhizobium‐Rhizobium, Enterobacteriaceae, Pantoea, Brachybacterium, Klebsiella, Escherichia‐Shigella and Ochrobactrum. Furthermore, six fungal genera were identified with relative abundances greater than 1%, specifically Aspergillus, Zygosaccharomyces, Cutaneotrichosporon, Candida, Millerozyma and Rhizopus. The correlation analysis indicated a significant impact of the microbial community and nutritional flavor on the second phase of fermentation in Xianju wheat paste. The predominant bacterium Bacillus in Xianju wheat paste facilitated the production of free amino acids, whereas Staphylococcus exhibited a negative correlation with free amino acid levels. The quantity of volatile compounds in Xianju wheat paste progressively increased during fermentation, with the presence of typical aroma compounds 4‐vinyl‐2‐methoxyphenol significantly associated with Bacillus. This indicated Bacillus notably enhanced the production of aromatic substances. Furthermore, a strong correlation was observed between Staphylococcus and the 18 volatile organic compounds, highlighting their substantial contribution to these aroma compounds.

CONCLUSION

This research indicates that the presence of microbial communities significantly contributes to the development of the nutritional flavor profile in Xianju wheat paste. © 2024 Society of Chemical Industry.