bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictive model for a second hip fracture occurrence using natural language processing and machine learning on electronic health records
Authors: Larrainzar-Garijo Ricardo , Fernández-Tormos Esther , Collado-Escudero Carlos Alberto , Alcantud Ibáñez María , Oñorbe-San Francisco Fernando , Marin-Corral Judith , Casadevall David , Donaire-Gonzalez David , Martínez-Sanchez Luisa , Cabal-Hierro Lucia , Benavent Diego , Brañas Fátima
Published: January 2024

Hip fractures (HFx) are associated with a higher morbidity and mortality rates, leading to a significant reduction in life quality and in limitation of patient´s mobility. The present study aimed to obtain real-world evidence on the clinical characteristics of patients with an initial and a second hip fracture (HFx) and develop a predictive model for second HFx using artificial intelligence. Electronic health records from one hospital centre in Spain from January 2011 to December 2019 were analysed using EHRead® technology, based on natural language processing and machine learning. A total of 1,960 patients with HFx were finally included during the study period after meeting all inclusion and exclusion criteria. From this total, 1835 (93.6%) patients were included in the HFx subgroup, while 124 (6.4%) were admitted to the second HFx (2HFx) subgroup. The mean age of the participants was 84 years and 75.5% were female. Most of comorbidities were more frequently identified in the HFx group, including hypertension (72.0% vs. 67.2%), cognitive impairment (33.0% vs. 31.2%), diabetes mellitus (28.7% vs. 24.8%), heart failure (27.6% vs. 22.4%) and chronic kidney disease (26.9% vs. 16.0%). Based on clinical criteria, 26 features were selected as potential prediction factors. From there, 16 demographics and clinical characteristics such as comorbidities, medications, measures of disabilities for ambulation and type of refracture were selected for development of a competitive risk model. Specifically, those predictors with different associated risk ratios, sorted from higher to lower risk relevance were visual deficit, malnutrition, walking assistance, hypothyroidism, female sex, osteoporosis treatment, pertrochanteric fracture, dementia, age at index, osteoporosis, renal failure, stroke, COPD, heart disease, anaemia, and asthma. This model showed good performance (dependent AUC: 0.69; apparent performance: 0.75) and could help the identification of patients with higher risk of developing a second HFx, allowing preventive measures. This study expands the current available information of HFx patients in Spain and identifies factors that exhibit potential in predicting a second HFx among older patients.
Development of deoxidation process for off-grade titanium sponge using magnesium metal with wire mesh strainer type of crucible
Authors: Park Sung-Hun , Jeoung Hyeong-Jun , Lee Tae-Hyuk , Sohn Ho-Sang , Kang Jungshin
Published: January 2024

In this study, the deoxidation process for off-grade titanium (Ti) sponge using magnesium (Mg) metal with a wire mesh strainer type of crucible was developed. Ti hydride (TiH2) feedstock, which was prepared by hydrogenating off-grade Ti sponge, was deoxidized using Mg in a molten magnesium chloride–potassium chloride salt at 933 K under an argon and 20% hydrogen (H2) mixed gas atmosphere. After deoxidation, the residual Mg-containing salt was separated in situ from the crucible to investigate the feasibility of minimizing salt loss during the leaching and production of pure TiH2. The results showed that the presence of residual Mg-containing salt inside the crucible strongly influenced whether a mixture of Ti and TiH2 or pure TiH2 was produced. When the salt was not sufficiently separated, a mixture of Ti and TiH2 was obtained and its oxygen (O) concentration was 0.121 mass% under certain conditions. Meanwhile, pure TiH2 was obtained by increasing the H2 gas flow rate during deoxidation. Therefore, these results demonstrate that the decrease of O concentration to below 0.180 mass% and the minimal loss of the salt are feasible.
Renal denervation restores biomechanics of carotid arteries in a rat model of hypertension
Authors: Gkousioudi Anastasia , Razzoli Margherita , Moreira Jesse D. , Wainford Richard D. , Zhang Yanhang
Published: January 2024

The prevalence of hypertension increases with aging and is associated with increased arterial stiffness. Resistant hypertension is presented when drug treatments fail to regulate a sustained increased blood pressure. Given that the mechanisms between the sympathetic nervous system and the kidney play an important role in blood regulation, renal denervation (RDN) has emerged as a therapeutic potential in resistant hypertension. In this study, we investigated the effects of RDN on the biomechanical response and microstructure of elastic arteries. Common carotid arteries (CCA) excised from 3-month, 8-month, and 8-month denervated rats were subjected to biaxial extension-inflation test. Our results showed that hypertension developed in the 8-month-old rats. The sustained elevated blood pressure resulted in arterial remodeling which was manifested as a significant stress increase in both axial and circumferential directions after 8 months. RDN had a favorable impact on CCAs with a restoration of stresses in values similar to control arteries at 3 months. After biomechanical testing, arteries were imaged under a multi-photon microscope to identify microstructural changes in extracellular matrix (ECM). Quantification of multi-photon images showed no significant alterations of the main ECM components, elastic and collagen fibers, indicating that arteries remained intact after RDN. Regardless of the experimental group, our microstructural analysis of the multi-photon images revealed that reorientation of the collagen fibers might be the main microstructural mechanism taking place during pressurization with their straightening happening during axial stretching.
LDL cholesterol target attainment in cardiovascular high- and very-high-risk patients with statin intolerance: a simulation study
Authors: Katzmann Julius L. , Stürzebecher Paulina E. , Kruppert Silvia , Laufs Ulrich
Published: January 2024

The inability to tolerate sufficient doses of statins, statin intolerance (SI), contributes to the non-achievement of guideline-recommended low-density lipoprotein cholesterol (LDL-C) treatment targets. Patients with SI require alternative lipid-lowering therapies (LLT). We conducted a simulation study on LDL-C target achievement with oral LLT (ezetimibe, bempedoic acid) in patients with SI, using representative data of 2.06 million German outpatients. SI was defined using literature-informed definitions based on electronic medical records (EMR). Among n = 130,778 patients with hypercholesterolaemia, available LDL-C measurement, and high or very-high cardiovascular risk, 8.6% met the definition of SI. Among patients with SI, 7.7% achieved the LDL-C target at baseline. After simulation of the stepwise addition of treatment with ezetimibe and bempedoic acid, 22.6 and 52.0% achieved the LDL-C target, respectively. The median achieved LDL-C was 80 and 62 mg/dL, the corresponding reductions from baseline were 20.0 and 38.0%, respectively. A higher proportion of patients classified as high risk achieved the target compared to those at very-high risk (58.1 vs. 49.9%). In conclusion, in patients with increased cardiovascular risk meeting the definition of SI based on EMR, combination LLT with ezetimibe and bempedoic acid has the potential to substantially increase the proportion of patients achieving clinically relevant LDL-C reductions.
Cell migration, DNA fragmentation and antibacterial properties of novel silver doped calcium polyphosphate nanoparticles
Authors: Ekram Basma , Tolba Emad , El-Sayed Ahmed F. , Müller Werner E. G. , Schröder Heinz C. , Wang Xiaohong , Abdel-Hady Bothaina M.
Published: January 2024

To combat infections, silver was used extensively in biomedical field but there was a need for a capping agent to eliminate its cytotoxic effects. In this study, polymeric calcium polyphosphate was doped by silver with three concentrations 1, 3 or 5 mol.% and were characterized by TEM, XRD, FTIR, TGA. Moreover, cytotoxicity, antibacterial, cell migration and DNA fragmentation assays were done to assure its safety. The results showed that the increase in silver percentage caused an increase in particle size. XRD showed the silver peaks, which indicated that it is present in its metallic form. The TGA showed that thermal stability was increased by increasing silver content. The antibacterial tests showed that the prepared nanoparticles have an antibacterial activity against tested pathogens. In addition, the cytotoxicity results showed that the samples exhibited non-cytotoxic behavior even with the highest doping concentration (5% Ag-CaPp). The cell migration assay showed that the increase in the silver concentration enhances cell migration up to 3% Ag-CaPp. The DNA fragmentation test revealed that all the prepared nanoparticles caused no fragmentation. From the results we can deduce that 3% Ag-CaPp was the optimum silver doped calcium polyphosphate concentration that could be used safely for medical applications.
High-performance spinel NiMn2O4 supported carbon felt for effective electrochemical conversion of ethylene glycol and hydrogen evolution applications
Authors: Medany Shymaa S. , Hefnawy Mahmoud A. , Kamal Soha M.
Published: January 2024

One of the most effective electrocatalysts for electrochemical oxidation reactions is NiMn2O4 spinel oxide. Here, a 3-D porous substrate with good conductivity called carbon felt (CF) is utilized. The composite of NiMn2O4-supported carbon felt was prepared using the facile hydrothermal method. The prepared electrode was characterized by various surface and bulk analyses like powder X-ray diffraction, X-ray photon spectroscopy (XPS), Scanning and transmitted electron microscopy, thermal analysis (DTA), energy dispersive X-ray (EDX), and Brunauer–Emmett–Teller (BET). The activity of NiMn2O4 toward the electrochemical conversion of ethylene glycol at a wide range of concentrations was investigated. The electrode showed a current density of 24 mA cm−2 at a potential of 0.5 V (vs. Ag/AgCl). Furthermore, the ability of the electrode toward hydrogen evaluation in an alkaline medium was performed. Thus, the electrode achieved a current density equal 10 mA cm−2 at an overpotential of 210 mV (vs. RHE), and the provided Tafel slope was 98 mV dec−1.
Recombination-aware phylogenetic analysis sheds light on the evolutionary origin of SARS-CoV-2
Authors: Esquivel Gomez Luis Roger , Weber Ariane , Kocher Arthur , Kühnert Denise
Published: January 2024

SARS-CoV-2 can infect human cells through the recognition of the human angiotensin-converting enzyme 2 receptor. This affinity is given by six amino acid residues located in the variable loop of the receptor binding domain (RBD) within the Spike protein. Genetic recombination involving bat and pangolin Sarbecoviruses, and natural selection have been proposed as possible explanations for the acquisition of the variable loop and these amino acid residues. In this study we employed Bayesian phylogenetics to jointly reconstruct the phylogeny of the RBD among human, bat and pangolin Sarbecoviruses and detect recombination events affecting this region of the genome. A recombination event involving RaTG13, the closest relative of SARS-CoV-2 that lacks five of the six residues, and an unsampled Sarbecovirus lineage was detected. This result suggests that the variable loop of the RBD didn’t have a recombinant origin and the key amino acid residues were likely present in the common ancestor of SARS-CoV-2 and RaTG13, with the latter losing five of them probably as the result of recombination.
An N-glycome tissue atlas of 15 human normal and cancer tissue types determined by MALDI-imaging mass spectrometry
Authors: Wallace Elizabeth N. , West Connor A. , McDowell Colin T. , Lu Xiaowei , Bruner Evelyn , Mehta Anand S. , Aoki-Kinoshita Kiyoko F. , Angel Peggi M. , Drake Richard R.
Published: January 2024

N-glycosylation is an abundant post-translational modification of most cell-surface proteins. N-glycans play a crucial role in cellular functions like protein folding, protein localization, cell–cell signaling, and immune detection. As different tissue types display different N-glycan profiles, changes in N-glycan compositions occur in tissue-specific ways with development of disease, like cancer. However, no comparative atlas resource exists for documenting N-glycome alterations across various human tissue types, particularly comparing normal and cancerous tissues. In order to study a broad range of human tissue N-glycomes, N-glycan targeted MALDI imaging mass spectrometry was applied to custom formalin-fixed paraffin-embedded tissue microarrays. These encompassed fifteen human tissue types including bladder, breast, cervix, colon, esophagus, gastric, kidney, liver, lung, pancreas, prostate, sarcoma, skin, thyroid, and uterus. Each array contained both normal and tumor cores from the same pathology block, selected by a pathologist, allowing more in-depth comparisons of the N-glycome differences between tumor and normal and across tissue types. Using established MALDI-IMS workflows and existing N-glycan databases, the N-glycans present in each tissue core were spatially profiled and peak intensity data compiled for comparative analyses. Further structural information was determined for core fucosylation using endoglycosidase F3, and differentiation of sialic acid linkages through stabilization chemistry. Glycan structural differences across the tissue types were compared for oligomannose levels, branching complexity, presence of bisecting N-acetylglucosamine, fucosylation, and sialylation. Collectively, our research identified the N-glycans that were significantly increased and/or decreased in relative abundance in cancer for each tissue type. This study offers valuable information on a wide scale for both normal and cancerous tissues, serving as a reference for future studies and potential diagnostic applications of MALDI-IMS.
ADAMTS13 regulates angiogenic markers via Ephrin/Eph signaling in human mesenchymal stem cells under serum-deprivation stress
Authors: Dutta Gupta Srishti , Ta Malancha
Published: January 2024

Mesenchymal stem cells (MSCs) are known to facilitate angiogenesis and promote neo-vascularization via secretion of trophic factors. Here, we explored the molecular mechanism adopted by ADAMTS13 in modulating the expression of some key angiogenic markers in human umbilical cord-derived MSCs under serum-deprivation stress. Wharton’s jelly MSCs (WJ-MSCs) were isolated from the perivascular region of human umbilical cords by explant culture. ADAMTS13 was upregulated at both mRNA and protein levels in WJ-MSCs under serum-deprivation stress. Correspondingly, some key angiogenic markers were also seen to be upregulated. By screening signaling pathways, p38 and JNK pathways were identified as negative and positive regulators for expression of ADAMTS13, and the angiogenic markers, respectively. Our results also indicated the Notch pathway and p53 as other probable partners modulating the expression of ADAMTS13 and the angiogenic markers. Knockdown of ADAMTS13 using siRNA led to reversal in the expression of these angiogenic markers. Further, ADAMTS13 was shown to act via the EphrinB2/EphB4 axis followed by ERK signaling to control expression of the angiogenic markers. Interestingly, stronger expression levels were noted for ADAMTS13, VEGF and PDGF under a more stringent nutrient stress condition. Thus, we highlight a novel role of ADAMTS13 in WJ-MSCs under nutrient stress condition.
Research on fire early warning index system of coal mine goaf based on multi-parameter fusion
Authors: Wang Beifang , Lv Yuanhao , Liu Chunbao
Published: January 2024

In order to improve the precision of goaf fire early warning outcomes, this paper obtains the temperature characteristic index of goaf fire early warning by using a coal spontaneous combustion thermogravimetric test and a coal spontaneous combustion programmed heating test. The major gas index and auxiliary gas index for early warning are derived using the integration of the Graham coefficient and grey correlation approach. The D-S evidence theory, which involves optimizing weight allocation, is utilized to integrate the early warning temperature index and various gas indexes. Based on the fusion results, a coal mine goaf fire early warning index system is developed through multi-parameter fusion. The early warning index system is then validated through a programmed heating experiment. The results show that the process of coal spontaneous combustion can be categorized into six distinct stages: latent stage, oxidation stage, critical stage, pyrolysis stage, fission stage, and combustion stage. These stages are determined by the characteristic temperatures of coal spontaneous combustion, which are 31.7 °C, 54.8 °C, 153.7 °C, 204.5 °C, and 241.6 °C. The major gas index for early warning of goaf fires can be determined by 100∆(CO)/∆O2(%). Additionally, auxiliary gas indexes such as C3H8/CH4, C3H8/C2H6, C2H4/C2H6, and C2H2 can be used for goaf fire early warning. The programmed heating experiment shows that the early warning system software is designed by the multi-parameter fusion goaf fire early warning index system is accurate and effective. The selection of the goaf fire early warning index is more rational and precise when using the multi-parameter fusion goaf fire early warning index system based on the D-S evidence theory of weight allocation. It offers robust support for enhancing the goaf fire early warning index system and predicting coal mine goaf fires.
Extensive antibody search with whole spectrum black-box optimization
Authors: Tučs Andrejs , Ito Tomoyuki , Kurumida Yoichi , Kawada Sakiya , Nakazawa Hikaru , Saito Yutaka , Umetsu Mitsuo , Tsuda Koji
Published: January 2024

In designing functional biological sequences with machine learning, the activity predictor tends to be inaccurate due to shortage of data. Top ranked sequences are thus unlikely to contain effective ones. This paper proposes to take prediction stability into account to provide domain experts with a reasonable list of sequences to choose from. In our approach, multiple prediction models are trained by subsampling the training set and the multi-objective optimization problem, where one objective is the average activity and the other is the standard deviation, is solved. The Pareto front represents a list of sequences with the whole spectrum of activity and stability. Using this method, we designed VHH (Variable domain of Heavy chain of Heavy chain) antibodies based on the dataset obtained from deep mutational screening. To solve multi-objective optimization, we employed our sequence design software MOQA that uses quantum annealing. By applying several selection criteria to 19,778 designed sequences, five sequences were selected for wet-lab validation. One sequence, 16 mutations away from the closest training sequence, was successfully expressed and found to possess desired binding specificity. Our whole spectrum approach provides a balanced way of dealing with the prediction uncertainty, and can possibly be applied to extensive search of functional sequences.
Immune, metabolic landscapes of prognostic signatures for lung adenocarcinoma based on a novel deep learning framework
Authors: Qin Shimei , Sun Shibin , Wang Yahui , Li Chao , Fu Lei , Wu Ming , Yan Jinxing , Li Wan , Lv Junjie , Chen Lina
Published: January 2024

Lung adenocarcinoma (LUAD) is a malignant tumor with high lethality, and the aim of this study was to identify promising biomarkers for LUAD. Using the TCGA-LUAD dataset as a discovery cohort, a novel joint framework VAEjMLP based on variational autoencoder (VAE) and multilayer perceptron (MLP) was proposed. And the Shapley Additive Explanations (SHAP) method was introduced to evaluate the contribution of feature genes to the classification decision, which helped us to develop a biologically meaningful biomarker potential scoring algorithm. Nineteen potential biomarkers for LUAD were identified, which were involved in the regulation of immune and metabolic functions in LUAD. A prognostic risk model for LUAD was constructed by the biomarkers HLA-DRB1, SCGB1A1, and HLA-DRB5 screened by Cox regression analysis, dividing the patients into high-risk and low-risk groups. The prognostic risk model was validated with external datasets. The low-risk group was characterized by enrichment of immune pathways and higher immune infiltration compared to the high-risk group. While, the high-risk group was accompanied by an increase in metabolic pathway activity. There were significant differences between the high- and low-risk groups in metabolic reprogramming of aerobic glycolysis, amino acids, and lipids, as well as in angiogenic activity, epithelial-mesenchymal transition, tumorigenic cytokines, and inflammatory response. Furthermore, high-risk patients were more sensitive to Afatinib, Gefitinib, and Gemcitabine as predicted by the pRRophetic algorithm. This study provides prognostic signatures capable of revealing the immune and metabolic landscapes for LUAD, and may shed light on the identification of other cancer biomarkers.
Improving counseling effectiveness with virtual counselors through nonverbal compassion involving eye contact, facial mimicry, and head-nodding
Authors: Choi Doo Sung , Park Jongyoul , Loeser Martin , Seo Kyoungwon
Published: January 2024

An effective way to reduce emotional distress is by sharing negative emotions with others. This is why counseling with a virtual counselor is an emerging methodology, where the sharer can consult freely anytime and anywhere without having to fear being judged. To improve counseling effectiveness, most studies so far have focused on designing verbal compassion for virtual counselors. However, recent studies showed that virtual counselors’ nonverbal compassion through eye contact, facial mimicry, and head-nodding also have significant impact on the overall counseling experience. To verify this, we designed the virtual counselor’s nonverbal compassion and examined its effects on counseling effectiveness (i.e., reduce the intensity of anger and improve general affect). A total of 40 participants were recruited from the university community. Participants were then randomly assigned to one of two virtual counselor conditions: a neutral virtual counselor condition without nonverbal compassion and a compassionate virtual counselor condition with nonverbal compassion (i.e., eye contact, facial mimicry, and head-nodding). Participants shared their anger-inducing episodes with the virtual counselor for an average of 16.30 min. Note that the virtual counselor was operated by the Wizard-of-Oz method without actually being technically implemented. Results showed that counseling with a compassionate virtual counselor reduced the intensity of anger significantly more than counseling with a neutral virtual counselor (F(1, 37) = 30.822, p < 0.001, ηp2 = 0.454). In addition, participants who counseled with a compassionate virtual counselor responded that they experienced higher empathy than those who counseled with a neutral virtual counselor (p < 0.001). These findings suggest that nonverbal compassion through eye contact, facial mimicry, and head-nodding of the virtual counselor makes the participants feel more empathy, which contributes to improving the counseling effectiveness by reducing the intensity of anger.
Intensionality is more cognitively demanding than false belief in adults: evidence from a non-inferential sentence-reading task
Authors: Yeung Elaine Kit Ling , Cheung Him
Published: January 2024

Children are said to understand false belief if they can appreciate an agent’s wrong description of an object as a result of misinformation, and intensionality if they can appreciate and switch between alternative descriptions from different epistemic viewpoints. Most previous studies have investigated the developmental trajectories of these capacities in the age range from 3 to 10 years aiming to discern their conceptual nature. The present research examines whether intensionality incurs lower performance accuracies and longer response times than false belief in adults, using a task in which participants read sentences that explicitly state an agent’s beliefs. Experiment 1 showed that participants were less accurate in rejecting verbal probes that contradicted an agent’s alternative than false thoughts about objects. Experiments 2 and 3 replicated this finding using thoughts about object identities but not properties. These results suggest that compared to false belief, intensionality is cognitively demanding for adults to process because of the availability of more than one identity candidate under the agent’s perspective.
Identification and prognostic biomarkers among ZDHHC4/12/18/24, and APT2 in lung adenocarcinoma
Authors: Bian Jing , Xiong Wenji , Yang Zhiguang , Li Minzhe , Song Demei , Zhang Yanli , Liu Chaoying
Published: January 2024

S-palmitoylases and S-depalmitoylases are differentially expressed in various cancers and several malignant tumors and show a strong prognostic ability. Notwithstanding, the potential clinical impact of S-palmitoylases and S-depalmitoylases, particularly in the prognosis and progression of lung adenocarcinoma (LUAD), has not been clarified. Expression levels of S-palmitoylases and S-depalmitoylases in LUAD were investigated using TCGA. GEPIA was used to evaluate the mRNA levels of S-palmitoylases and S-depalmitoylases at different pathological stages. Metascape was used to investigate the biological significance of S-palmitoylases and S-depalmitoylases. The Kaplan–Meier plotter was used to analyze the prognostic value of S-palmitoylases and S-depalmitoylases. CBioportal was used to analyze gene alterations in S-palmitoylases and S-depalmitoylases. UALCAN was used to examine DNA promoter methylation levels of S-palmitoylases and S-depalmitoylases. Finally, we investigated the relationship between S-palmitoylases, S-depalmitoylases, and tumor-infiltrating immune cells using TIMER. Correlations with immune checkpoint-related genes were determined using the R packages reshape2, ggpubr, ggplot2, and corrplot. PCR was also performed to assess the degree of ZDHHC4/12/18/24 and APT2 transcript expression in lung adenocarcinoma and adjacent normal lung tissues. HPA was utilized to investigate protein levels of S-palmitoylases and S-depalmitoylases in LUAD and normal lung tissue. Our study found that ZDHHC2/3/4/5/6/7/9/12/13/16/18/20/21/23/24, APT1/2, PPT1, LYPLAL1, ABHD4/10/11/12/13 and ABHD17C mRNA expression was significantly upregulated in LUAD, whereas ZDHHC1/8/11/11B/14/15/17/19/22, ABHD6/16A and ABHD17A mRNA expression was significantly downregulated. The functions of the differentially expressed S-palmitoylases and S-depalmitoylases were mainly associated with protein-cysteine S-palmitoyltransferase and protein-cysteine S-acyltransferase activities. Patients with high expression of ZDHHC4/12/18/24, APT2, ABHD4, ABHD11 and ABHD12 had a shorter overall survival. Infiltration of six immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells) was closely associated with the expression of ZDHHC4/12/18/24 and APT2. ZDHHC4/12/18/24 and APT2 positively correlated with the immune checkpoint-related gene CD276. We assessed the mRNA levels of ZDHHC4/12/18/24 and APT2 using qRT-PCR and found increased expression of ZDHHC4/12/18/24 in LUAD compared with healty control lung tissues. ZDHHC4/12/18/24, and APT2 are potential prognostic biomarkers of LUAD. Their expression levels could be related to the tumor microenvironment in LUAD.
Differential temporal utility of passively sensed smartphone features for depression and anxiety symptom prediction: a longitudinal cohort study
Authors: Stamatis Caitlin A. , Meyerhoff Jonah , Meng Yixuan , Lin Zhi Chong Chris , Cho Young Min , Liu Tony , Karr Chris J. , Liu Tingting , Curtis Brenda L. , Ungar Lyle H. , Mohr David C.
Published: January 2024

While studies show links between smartphone data and affective symptoms, we lack clarity on the temporal scale, specificity (e.g., to depression vs. anxiety), and person-specific (vs. group-level) nature of these associations. We conducted a large-scale (n = 1013) smartphone-based passive sensing study to identify within- and between-person digital markers of depression and anxiety symptoms over time. Participants (74.6% female; M age = 40.9) downloaded the LifeSense app, which facilitated continuous passive data collection (e.g., GPS, app and device use, communication) across 16 weeks. Hierarchical linear regression models tested the within- and between-person associations of 2-week windows of passively sensed data with depression (PHQ-8) or generalized anxiety (GAD-7). We used a shifting window to understand the time scale at which sensed features relate to mental health symptoms, predicting symptoms 2 weeks in the future (distal prediction), 1 week in the future (medial prediction), and 0 weeks in the future (proximal prediction). Spending more time at home relative to one’s average was an early signal of PHQ-8 severity (distal β = 0.219, p = 0.012) and continued to relate to PHQ-8 at medial (β = 0.198, p = 0.022) and proximal (β = 0.183, p = 0.045) windows. In contrast, circadian movement was proximally related to (β = −0.131, p = 0.035) but did not predict (distal β = 0.034, p = 0.577; medial β = −0.089, p = 0.138) PHQ-8. Distinct communication features (i.e., call/text or app-based messaging) related to PHQ-8 and GAD-7. Findings have implications for identifying novel treatment targets, personalizing digital mental health interventions, and enhancing traditional patient-provider interactions. Certain features (e.g., circadian movement) may represent correlates but not true prospective indicators of affective symptoms. Conversely, other features like home duration may be such early signals of intra-individual symptom change, indicating the potential utility of prophylactic intervention (e.g., behavioral activation) in response to person-specific increases in these signals.
Interpretable Machine Learning for Kinetic Rate Model Discovery
Authors: Ángel de Carvalho Servia Miguel , Antonio del Rio Chanona Ehecatl
Published: January 2024

Due to global scale problems (e.g. exponential population growth), catalytic processes are of more importance today than they have ever been before. The industrialisation of these processes requires kinetic models. Mechanistic models are difficult to construct; data-driven and hybrid models, although easier to construct, lack interpretability and physical knowledge. Recently, a new approach called automated knowledge discovery has been popularised, but existing methods in the literature suffer from important drawbacks: necessitating assumptions about model structures and a lack of model selection routine (both being directly linked to kinetic model building). As such, this motivated the presented work to construct a generalisable methodological framework for the automated discovery of catalytic kinetic models. The methodological framework proposed utilises symbolic regression for model generation, a hybrid optimisation algorithm for parameter estimation, and the Akaike information criterion (AIC) and the Hunter–Reiner criterion for model selection and discrimination, respectively. The methodology was applied to an illustrative isomerisation case study, where concentration versus time data were provided for three different experiments (i.e. each experiment has different initial conditions). The framework was able to retrieve the correct kinetic model with realistic (i.e. noisy) data from the catalytic system. This exemplifies how the presented methodology can be harnessed to efficiently provide important and interpretable insights of catalytical systems that have not yet been researched.
Graph Neural Networks for the Prediction of Molecular Structure–Property Relationships
Authors: Rittig Jan G. , Gao Qinghe , Dahmen Manuel , Mitsos Alexander , Schweidtmann Artur M.
Published: January 2024

Molecular property prediction is of crucial importance in many disciplines such as drug discovery, molecular biology, or materials and process design. The frequently employed quantitative structure–property/activity relationships (QSPRs/QSARs) characterize molecules by descriptors which are then mapped to the properties of interest via a linear or nonlinear model. In contrast, graph neural networks, a novel machine learning method, directly work on the molecular graph, i.e., a graph representation where atoms correspond to nodes and bonds correspond to edges. GNNs allow learning of properties in an end-to-end fashion, thereby avoiding the need for informative descriptors as in QSPRs/QSARs. GNNs have been shown to achieve state-of-the-art prediction performance on various property prediction tasks and represent an active field of research. We describe the fundamentals of GNNs and demonstrate the application of GNNs via two examples for molecular property prediction.
Hybrid Modelling Under Uncertainty: Effects of Model Greyness, Data Quality and Data Quantity
Authors: Rogers Alexander W. , Song Ziqi , Vega Ramon Fernando , Jing Keju , Zhang Dongda
Published: January 2024

Previous chapters have demonstrated how, by combining data-driven and mechanistic methods, hybrid modelling provides a cost-effective solution to modelling complex (bio)chemical reaction kinetics when the underlying mechanisms are not fully understood. However, the question of how much kinetic information to incorporate into a hybrid model (i.e., the ‘greyness’ of a hybrid model) remains to be systematically addressed. Therefore, to illustrate the effect of model greyness on accuracy and reliability, in this chapter, we built three hybrid models for predicting the kinetics of a complex biochemical system: γ-linolenic acid production via fermentation of the fungus Cunninghamella echinulata. Each hybrid model incorporated different amounts of kinetic information, representing three levels of hybrid model ‘greyness’, then embedded a Gaussian process (GP) to simulate the unknown kinetics inferred from experimental observation. Hybrid model parameter estimation is also revisited to introduce time-varying parameter regularisation to mitigate the risk of overfitting real process data with missing or uncertain measurements. Although all three hybrid models could fit well, we demonstrate how incorporating more specific kinetic information increases the risk of incorrect inductive bias, while too little renders the hybrid model prone to overfitting. By balancing the regularisation penalty weight and the amount of kinetic information provided, it is possible to build a high-fidelity hybrid model for predicting reaction system performance for new operating conditions and reactor scales. This extends the hybrid modelling theory presented in earlier chapters to meet the challenges encountered in practice.
Industrial Data Science for Batch Reactor Monitoring and Fault Detection
Authors: Arzac I. Imanol , Vallerio Mattia , Perez-Galvan Carlos , Navarro-Brull Francisco J.
Published: January 2024

Batch processes show several sources of variability, from raw materials’ properties to initial and evolving conditions that change during the different events in the manufacturing process. In this chapter, we will illustrate with an industrial example how to use machine learning to reduce this apparent excess of data while maintaining the relevant information for process engineers. Two common use cases will be presented: (1) AutoML analysis to quickly find correlations in batch process data and (2) trajectory analysis to monitor and identify anomalous batches leading to process control improvements.
Boron nitride nanoplate-based strand exchange amplification with enhanced sensitivity and rapidity for quantitative detection of Staphylococcus aureus in food samples
Authors: Lin Shuo , Zhang Xin , Tian Anning , Wang Pengyu , Li Yong , Shi Chao , Ma Cuiping , Fan Yaofang
Published: January 2024

Staphylococcus aureus is one of the most common foodborne pathogens that can cause serious food poisoning and infectious diseases in humans.
Wound microenvironment regulatory poly(l-glutamic acid) composite hydrogels containing metal ion-coordinated nanoparticles for effective hemostasis and wound healing
Authors: Chen Yanzheng , Zhang Xueliang , Wang Qing , Du Chang , Dong Chang-Ming
Published: January 2024

A wound microenvironment regulatory poly(l-glutamic acid) composite hydrogel can promote cell proliferation, migration, and angiogenesis, alleviate inflammation and polarize pro-inflammatory M1 macrophages into pro-healing M2 macrophages, thus accelerating wound healing.
Iridium-catalysed hydroamination of internal homoallylic amines
Authors: Ho An T. , Vanable Evan P. , Miguel Chelsea San , Hull Kami L.
Published: January 2024

The Ir-catalyzed amine-directed hydroamination of internal alkenes is developed. Mechanistic investigations support that a trans-aminoiridation is occurring.
Palladium-catalysed fragmentary esterification-induced allylic alkylation of allyl carbonates and cyclic vinylogous anhydrides
Authors: Wu Shu-Yi , Li Yang , Shen Peng , Yang Xin-Han , Ran Guang-Yao
Published: January 2024

A palladium-catalysed fragmental esterification-induced allylic alkylation of allylic carbonates with cyclic vinylogous anhydrides was disclosed, providing an efficient approach for the synthesis of 1,6/1,7-dicarbonyls and medium-sized rings.
Novel superhard semiconducting structures of C8B2N2 predicted using the first-principles approach
Authors: Sun Xiao-Wei , Chen Meng-Ru , Song Ting , Tian Jun-Hong , Liu Zi-Jiang , Huang Wen-Chao
Published: January 2024

We predicted three novel superhard semiconducting structures of C8B2N2 with a space group P3m1 that have hardness values up to 82.4, 83.1, and 82.0 GPa and indirect band gaps of 4.164, 4.692, and 3.582 eV, respectively.
Computational investigation of copper-mediated conformational changes in α-synuclein dimer
Authors: Savva Loizos , Platts James A.
Published: January 2024

MD simulations are used to examine the effect of bridging Cu(ii) ions on dimerization of α-synuclein.
Elucidating the mechanism and origin of stereoselectivity in the activation/transformation of an acetic ester catalyzed by an N-heterocyclic carbene
Authors: Liang Pingxin , Yang Haoran , Wang Yang
Published: January 2024

The detailed mechanism, origin of stereoselectivity and substrate and catalyst effects are extensively investigated using DFT methods.
A mesoionic carbene stabilized nickel(ii) hydroxide complex: a facile precursor for C–H activation chemistry
Authors: Pavun Anna , Niess Raffael , Scheibel Lucas A. , Seidl Michael , Hohloch Stephan
Published: January 2024

We report the synthesis of a nickel(ii) hydroxide complex 2 supported by a rigid, tridentate triazolylidene-carbazolid ligand, acting as a versatile precursor to perform E–H (E = O, S, N) and C–H activation reactions.
Laboratory measurements underestimate persistence of the aquatic herbicide fluridone in lakes
Authors: Van Frost Sydney R. , White Amber M. , Jauquet Josie M. , Magness Angela M. , McMahon Katherine D. , Remucal Christina K.
Published: January 2024

Laboratory measurements overpredict the susceptibility of the herbicide fluridone to bio- and photodegradation compared to measurements in lakes.
Surpassing water-splitting potential in aqueous redox flow batteries: insights from kinetics and thermodynamics
Authors: Muralidharan Vithiya , Jayasubramaniyan S. , Lee Hyun-Wook
Published: January 2024

Aqueous redox flow batteries (AQRFBs) employing non-flammable electrolytes are recognized for their inherent safety and eco-friendliness, making them promising candidates for large-scale energy storage systems.
Lactic acid fermentation of goji berries (Lycium barbarum) prevents acute alcohol liver injury and modulates gut microbiota and metabolites in mice
Authors: Duan Wenhui , Zhou Lingxi , Ren Yilin , Liu Fei , Xue Yuzheng , Wang Fang-Zhou , Lu Ran , Zhang Xiao-Juan , Shi Jin-Song , Xu Zheng-Hong , Geng Yan
Published: January 2024

Lactic acid bacteria (LAB) fermented goji juice prevented alcohol-induced liver and gut dysfunction through the gut–liver crosstalk.
Multifunctional droplet handling on surface-charge-graphic-decorated porous papers
Authors: Wu Jiayao , Fang Duokui , Zhou Yifan , Gao Ge , Zeng Ji , Zeng Yubin , Zheng Huai
Published: January 2024

Surface charge graphics endow unspecific porous papers with multifunctional droplet manipulation, which shows great potential for applications in flexible droplet pick-up robots and dynamically controllable fluidic networks.
Py-2NO ligand enabled Ni(ii)-catalyzed asymmetric Michael addition reaction of indoles with β,γ-unsaturated α-keto esters
Authors: Chen Zi-Yue , Wang Xi-Rui , Xu Ke-Lan , Hu Pan , Tian You-Ping , Wang Hui-Juan , Zhou Ying , Liu Xiong-Li
Published: January 2024

This work diversified the Py-2NO ligand library recently developed by our group and further expanded the application of chiral Py-2NO ligands in asymmetric catalysis.
Facile preparation of physically crosslinked hydrogel based on the glassy state with high strength
Authors: Lin Qiurui , Rao Tao , Ma Xinyu , Du Pan , Liu Yuhan , Luo Die , He Xianru
Published: January 2024

Hydrogels are promising materials, but because of their weak mechanical performance, further applications are limited.
An A′–A–DA′D–A–A′-type acceptor enables organic solar cells with high VOC and low nonradiative voltage loss
Authors: Zhou Bingjie , Wang Helin , He Zehua , Zheng Guoqiang , Tang Ailing , Zhou Erjun
Published: January 2024

A novel A′–A–DA′D–A–A′ typed acceptor was developed, where the benzotriazole unit was used as the A′ unit both on the central core and terminal groups, to reduce the voltage loss and to increase the open-circuit voltage in efficient organic solar cells.
Synthesis of platinum-containing oligomers utilizing ADMET chemistry and polycondensation of a bisimide with α,ω-dibromoalkanes: examination of triplet–triplet annihilation upconversion
Authors: Sotani Taichi , Shimada Naoki , Mizokuro Toshiko , Sogawa Hiromitsu , Wagener Kenneth. B. , Sanda Fumio
Published: January 2024

Pt-containing oligomers synthesized by ADMET oligomerization and polycondensation phosphoresced under N2, while did not under air. They served as sensitizers of triplet–triplet annihilation upconversion with 9,10-diphenylanthracene as an emitter.
Calcium ferrites for phosphate adsorption and recovery from wastewater
Authors: Araújo Matheus Henrique Pimentel , Ardisson José Domingos , Krohling Alisson Carlos , Lago Rochel Montero , Guimarães Júnior Walber , Tristão Juliana Cristina
Published: January 2024

In this study, calcium ferrites with different Ca : Fe atomic ratios (1 : 1, 1 : 2, 1 : 3 and 2 : 1) were prepared from Ca and Fe nitrates treated at 300, 700 and 900 °C and evaluated for phosphate adsorption and recovery from wastewater.
Morphological, structural, optical and dielectric analysis of Cs2TiBr6 perovskite nanoparticles
Authors: Ben Bechir Mohamed , Alresheedi Faisal
Published: January 2024

In the pursuit of lead-free perovskite materials suitable for harnessing solar energy, a recent discovery has emerged regarding Cs2TiBr6.
Retraction: Novel fatty chain-modified GLP-1R G-protein biased agonist exerts prolonged anti-diabetic effects through targeting receptor binding sites
Authors: Wang Maorong , Yao Ping , Gao Minpeng , Jin Jian , Yu Yerong
Published: January 2024

Retraction of ‘Novel fatty chain-modified GLP-1R G-protein biased agonist exerts prolonged anti-diabetic effects through targeting receptor binding sites’ by Maorong Wang et al., RSC Adv., 2020, 10, 8044–8053, DOI: https://doi.org/10.1039/C9RA10593J.
Efficient construction of functionalized pyrroloindolines through cascade radical cyclization/intermolecular coupling
Authors: Jiang Yonggang , Liu Dongxiang , Zhang Lening , Qin Cuirong , Li Hui , Yang Haitao , Walsh Patrick J. , Yang Xiaodong
Published: January 2024

A novel tandem radical cyclization/intermolecular coupling between 2-azaallyl anions and indole N-aryloxy acetamides is developed, which enables the synthesis of C3a-substituted pyrroloindolines under mild conditions.
Ultrafast charge transfer of stiboviologens for electrochromism and visible light-induced α-amino C(sp3)–H functionalization
Authors: Xu Liang , Zhang Lei , Qiao Yi , Zheng Haifeng , Li Guoping , Rao Bin , Zhang Mingming , Ma Wenqiang , He Gang
Published: January 2024

Four stiboviologens (SbV2+) with tunable optoelectronic properties were synthesized. Stiboviologens exhibited ultrafast MLCT (metal-to-ligand charge transfer) processes and had great visible light catalytic performance.
Synchronous achievement of ultra-wideband microwave absorption and high thermal conduction in spongy TiO2-based magnetic composites via constructing magnetic/dielectric double loss and phonon/electron co-transmission
Authors: Yao Qibin , Fu Kang , Ji Ran , Ying Meiwan , Yang Yijun , Yang Kaixia , Tong Guoxiu , Wu Wenhua , Chen Dabo
Published: January 2024

Spongy TiO2-based magnetic composites were synthesized as high-performance fillers with excellent EMW absorption and high thermal conduction via a hydrothermal-soaking-annealing route for the first time.
Rationalizing the carborane versus phenyl-driven luminescence in related dicarboxylic ligands and their antenna effect for their Eu3+ and Tb3+ metal–organic frameworks: a combined experimental and computational study
Authors: Li Zhen , Roscini Claudio , Núñez Rosario , Teixidor Francesc , Viñas Clara , Ruiz Eliseo , Planas José Giner
Published: January 2024

Replacement of a phenyl moiety with a 3D-carborane cluster induces a more effective energy transfer on lanthanide ions.
Flexible and multifunctional composite films based on rare earth phosphors as broadband thermal emitters for high-performance passive radiative cooling
Authors: Tan Ruiming , Hu Wangyang , Yao Xin , Lin Nan , Xue Peng , Xu Shiqing , Bai Gongxun
Published: January 2024

Flexible composite films based on rare earth phosphors can be used as broadband thermal emitters for passive radiative cooling and energy conservation.
A promise for neuronal repair: reprogramming astrocytes into neurons in vivo
Authors: Huang Lijuan , Lai Xinyu , Liang Xiaojun , Chen Jiafeng , Yang Yue , Xu Wei , Qin Qingchun , Qin Rongxing , Huang Xiaoying , Xie Minshan , Chen Li
Published: January 2024

Massive loss of neurons following brain injury or disease is the primary cause of central nervous system dysfunction. Recently, much research has been conducted on how to compensate for neuronal loss in damaged parts of the nervous system and thus restore functional connectivity among neurons. Direct somatic cell differentiation into neurons using pro-neural transcription factors, small molecules, or microRNAs, individually or in association, is the most promising form of neural cell replacement therapy available. This method provides a potential remedy for cell loss in a variety of neurodegenerative illnesses, and the development of reprogramming technology has made this method feasible. This article provides a comprehensive review of reprogramming, including the selection and methods of reprogramming starting cell populations as well as the signaling methods involved in this process. Additionally, we thoroughly examine how reprogramming astrocytes into neurons can be applied to treat stroke and other neurodegenerative diseases. Finally, we discuss the challenges of neuronal reprogramming and offer insights about the field.