bluuebunny/crossref_metadata_2025 huggingface dataset:
Differential contribution of direct and indirect pathways from dorsolateral and dorsomedial striatum to motor symptoms in Huntington’s disease mice
Authors: Conde-Berriozabal Sara , Sitjà-Roqueta Laia , García-García Esther , García-Gilabert Lia , Sancho-Balsells Anna , Fernández-García Sara , Rodriguez-Urgellés Ened , Giralt Albert , López-Gil Javier , Muñoz-Moreno Emma , Castañé Anna , Soria Guadalupe , Rodríguez Manuel J , Alberch Jordi , Masana Mercè
Published: June 2024

The alterations in the basal ganglia circuitry associated with motor symptoms in Huntington’s Disease (HD) have been extensively investigated. Yet, the specific contribution of the direct and indirect striatal output pathways from the dorsolateral (DLS) and dorsomedial striatum (DMS) to the motor dysfunction is still not fully understood. Here, using the symptomatic R6/1 male mouse model of HD, strong functional connectivity alterations between DMS and DLS regions with the rest of brain were observed by fMRI, particularly pronounced in the DLS. Then, we systematically evaluated how the selective optogenetic stimulation of the direct and indirect pathways from DLS and DMS influences locomotion, exploratory behavior, and motor learning. In wild type (WT) mice, optogenetic stimulation of the direct pathway from DLS and the indirect pathway from DMS elicited subtle locomotor enhancements, while exploratory behavior remained unaltered. Additionally, stimulation of the indirect pathway from DLS improved the performance in the accelerated rotarod task. In contrast, in HD mice, optogenetic stimulation of the distinct striatal pathways did not modulate these behaviors. Overall, this study points to deficits in the integration of neuronal activity in HD mice, while it contributes to deeper understanding of the complexity of motor control by the diverse striatal subcircuits.
Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language
Authors: Hong Zhuoqiao , Wang Haocheng , Zada Zaid , Gazula Harshvardhan , Turner David , Aubrey Bobbi , Niekerken Leonard , Doyle Werner , Devore Sasha , Dugan Patricia , Friedman Daniel , Devinsky Orrin , Flinker Adeen , Hasson Uri , Nastase Samuel A. , Goldstein Ariel
Published: June 2024

Recent research has used large language models (LLMs) to study the neural basis of naturalistic language processing in the human brain. LLMs have rapidly grown in complexity, leading to improved language processing capabilities. However, neuroscience researchers haven’t kept up with the quick progress in LLM development. Here, we utilized several families of transformer-based LLMs to investigate the relationship between model size and their ability to capture linguistic information in the human brain. Crucially, a subset of LLMs were trained on a fixed training set, enabling us to dissociate model size from architecture and training set size. We used electrocorticography (ECoG) to measure neural activity in epilepsy patients while they listened to a 30-minute naturalistic audio story. We fit electrode-wise encoding models using contextual embeddings extracted from each hidden layer of the LLMs to predict word-level neural signals. In line with prior work, we found that larger LLMs better capture the structure of natural language and better predict neural activity. We also found a log-linear relationship where the encoding performance peaks in relatively earlier layers as model size increases. We also observed variations in the best-performing layer across different brain regions, corresponding to an organized language processing hierarchy.
Interactively Integrating Reach and Grasp Information in Macaque Premotor Cortex
Authors: Chen Junjun , Sun Guanghao , Zhang Yiwei , Chen Weidong , Zheng Xiaoxiang , Zhang Shaomin , Hao Yaoyao
Published: June 2024

Successful reach-to-grasp movements necessitate the integration of both object location and grip type information. However, how these two types of information are encoded in a single brain region and to what extend they interact with each other, remain largely unknown. We designed a novel experimental paradigm that sequentially prompted reach and grasp cues to monkeys and recorded neural activity in the dorsal premotor cortex (PMd) to investigate how the encoding structures change and interact during arm reaching and hand grasping movements. This paradigm required monkeys to retain the first prompted cue when the second one arrived, and integrate both to accomplish a final goal movement. PMd neurons represented both reach and grasp to similar extend, yet the encodings were not independent. Upon the arrival of second cue, PMd continued to encode the first cue, albeit with a significantly altered structure, as evidenced by more than half of the neurons displaying incongruent modulation. At a population level, the encoding structure formed a distinct subspace that differed from, but was not entirely orthogonal to, the original one. Employing canonical correlation analysis, we identified a subspace that consistently preserved the encoding of the initial cue, potentially serving as a mechanism for downstream brain regions to extract coherent information. Furthermore, this shared subspace comprised a diverse population of neurons, including both congruent and incongruent units. these findings support the argument that reach and grasp information are interactively integrated within PMd, with a shared subspace likely underpinning a consistent encoding framework.
Transcriptomics and proteomics of projection neurons in a circuit linking hippocampus with dorsolateral prefrontal cortex in human brain
Authors: Bharadwaj Rahul A. , Borcuk Christopher , Kikidis Gianluca C. , Sportelli Leonardo , Bertolino Alessandro , Cole Robert N. , DeVine Lauren , Kleinman Joel E. , Maher Brady , Sripathy Srinidhi R. , Mallepalli Vamshi , Parihar Madhur , Shin Joo Heon , Lee Yong Kyu , Montoya Carly , Deep-Soboslay Amy , Hyde Thomas M. , Weinberger Daniel R. , Pergola Giulio
Published: June 2024

RNA-sequencing studies of brain tissue homogenates have shed light on the molecular processes underlying schizophrenia (SCZ) but lack biological granularity at the cell type level. Laser capture microdissection (LCM) can isolate selective cell populations with intact cell bodies to allow complementary gene expression analyses of mRNA and protein. We used LCM to collect excitatory neuron-enriched samples from CA1 and subiculum (SUB) of the hippocampus and layer III of the dorsolateral prefrontal cortex (DLPFC), from which we generated gene, transcript, and peptide level data. In a machine learning framework, LCM-derived expression achieved superior regional identity predictions as compared to bulk tissue, with further improvements when using isoform-level transcript and protein quantifications. LCM-derived co-expression also had increased co-expression strength of neuronal gene sets compared to tissue homogenates. SCZ risk co-expression pathways were identified and replicated across transcript and protein networks and were consistently enriched for glutamate receptor complex and post-synaptic functions. Finally, through inter-regional co-expression analyses, we show that CA1 to SUB transcriptomic connectivity may be altered in SCZ.
Mitochondrial damage triggers concerted degradation of negative regulators of neuronal autophagy
Authors: Basak Bishal , Holzbaur Erika L.F.
Published: June 2024

Mutations in genes that regulate mitophagy, a key mitochondrial quality control pathway, are causative for neurological disorders including Parkinson’s. Here, we identify a novel stress response pathway activated by mitochondrial damage that regulates mitophagy in neurons. We find that increasing levels of mitochondrial stress triggers a graded, concerted response that induces proteasomal degradation of negative regulators of autophagy. These include Myotubularin-related phosphatase 5 (MTMR5), MTMR2 and Rubicon. This ‘MitophagicStressResponse’ (MitoSR) pathway is neuron-specific and acts in parallel to the classical Pink1/Parkin-mediated mitophagy pathway. While MTMR5/MTMR2 inhibits autophagosome biogenesis, we find that Rubicon inhibits lysosomal function and thus blocks autophagosome maturation. Targeted depletion of these negative regulators is sufficient to enhance mitophagy, promoting autophagosome biogenesis and facilitating the fusion of mitophagosomes with lysosomes. Our work suggests that therapeutic activation of the MitoSR pathway to induce degradation of negative regulators of autophagy may enhance mitochondrial quality control in stressed neurons.
Studying time-resolved functional connectivity via communication theory: on the complementary nature of phase synchronization and sliding window Pearson correlation.
Authors: Wiafe Sir-Lord , Asante Nana , Calhoun Vince , Faghiri Ashkan
Published: June 2024

Time-resolved functional connectivity (trFC) assesses the time-resolved coupling between brain regions using functional magnetic resonance imaging (fMRI) data. This study aims to compare two techniques used to estimate trFC, to investigate their similarities and differences when applied to fMRI data. These techniques are the sliding window Pearson correlation (SWPC), an amplitude-based approach, and phase synchronization (PS), a phase-based technique. To accomplish our objective, we used resting-state fMRI data from the Human Connectome Project (HCP) with 827 subjects (repetition time: 0.7s) and the Function Biomedical Informatics Research Network (fBIRN) with 311 subjects (repetition time: 2s), which included 151 schizophrenia patients and 160 controls. Our simulations reveal distinct strengths in two connectivity methods: SWPC captures high-magnitude, low-frequency connectivity, while PS detects low-magnitude, high-frequency connectivity. Stronger correlations between SWPC and PS align with pronounced fMRI oscillations. For fMRI data, higher correlations between SWPC and PS occur with matched frequencies and smaller SWPC window sizes (~30s), but larger windows (~88s) sacrifice clinically relevant information. Both methods identify a schizophrenia-associated brain network state but show different patterns: SWPC highlights low anti-correlations between visual, subcortical, auditory, and sensory-motor networks, while PS shows reduced positive synchronization among these networks. Our findings underscore the complementary nature of SWPC and PS, elucidating their respective strengths and limitations without implying the superiority of one over the other.
Valine and Inflammation Drive Epilepsy in a Mouse Model of ECHS1 Deficiency
Authors: Eller Meghan M. , Zuberi Aamir R. , Fu Xiaorong , Burgess Shawn C. , Lutz Cathleen M. , Bailey Rachel M.
Published: June 2024

ECHS1 Deficiency (ECHS1D) is a rare and devastating pediatric disease that currently has no defined treatments. This disorder results from missense loss-of-function mutations in theECHS1gene that result in severe developmental delays, encephalopathy, hypotonia, and early death. ECHS1 enzymatic activity is necessary for the beta-oxidation of fatty acids and the oxidation of branched-chain amino acids within the inner mitochondrial matrix. The pathogenesis of disease remains unknown, however it is hypothesized that disease is driven by an accumulation of toxic metabolites from impaired valine oxidation.

To expand our knowledge on disease mechanisms, a novel mouse model of ECHS1D was generated that possesses a disease-associated knock-in (KI) allele and a knock-out (KO) allele. To investigate the behavioral phenotype, a battery of testing was performed at multiple time points, which included assessments of learning, motor function, endurance, sensory responses, and anxiety. Neurological abnormalities were assessed using wireless telemetry EEG recordings, pentylenetetrazol (PTZ) seizure induction, and immunohistochemistry. Metabolic perturbations were measured within the liver, serum, and brain using mass spectrometry and magnetic resonance spectroscopy. To test disease mechanisms, mice were subjected to disease pathway stressors and then survival, body weight gain, and epilepsy were assessed.

Mice containing KI/KI or KI/KO alleles were viable with normal development and survival, and the presence of KI and KO alleles resulted in a significant reduction in ECHS1 protein. ECHS1D mice displayed reduced exercise capacity and pain sensation. EEG analysis revealed increased slow wave power that was associated with perturbations in sleep. ECHS1D mice had significantly increased epileptiform EEG discharges, and were sensitive to seizure induction, which resulted in death of 60% of ECHS1D mice. Under basal conditions, brain structure was grossly normal, although histological analysis revealed increased microglial activation in aged ECHS1D mice. Increased dietary valine only affected ECHS1D mice, which significantly exacerbated seizure susceptibility and resulted in death. Lastly, acute inflammatory challenge drove regression and early lethality in ECHS1D mice.

In conclusion, we developed a novel model of ECHS1D that may be used to further knowledge on disease mechanisms and to develop therapeutics. Our data suggests altered metabolic signaling and inflammation may contribute to epilepsy in ECHS1D, and these alterations may be attributed to impaired valine metabolism.
Effective Abelian lattice gauge field theories for scalar-matter-monopole interactions
Authors: Farakos K. , Koutsoumbas G. , Mavromatos Nick E.
Published: June 2024

We present a gauge and Lorentz invariant effective field theory model for the interaction of a charged scalar matter field with a magnetic monopole source, described by an external magnetic current. The quantum fluctuations of the monopole field are described effectively by a strongly coupled “dual” Ud(1) gauge field, which is independent of the electromagnetic Uem(1) gauge field. The effective interactions of the charged matter with the monopole source are described by a gauge invariant mixed Chern-Simons-like (Pontryagin-density) term between the two U(1) gauge fields. The latter interaction coupling is left free, and a lattice study of the system is performed with the aim of determining the phase structure of this effective theory. Our study shows that, in the spontaneously broken-symmetry phase, the monopole source triggers, via the mixed Chern-Simons term, which is nontrivial in its presence, the generation of a dynamical singular configuration (magnetic-monopolelike) for the respective gauge fields. The scalar field also behaves in the broken phase in a way similar to that of the scalar sector of the ’t Hooft-Polyakov monopole. Moreover, we show that the modest size of the lattices involved does not have significant effects on the main conclusions of our analysis.

Published by the American Physical Society
2024
Efficient Quantum Algorithms for Stabilizer Entropies
Authors: Haug Tobias , Lee Soovin , Kim M. S.
Published: June 2024

Stabilizer entropies (SEs) are measures of nonstabilizerness or “magic” that quantify the degree to which a state is described by stabilizers. SEs are especially interesting due to their connections to scrambling, localization and property testing. However, applications have been limited so far as previously known measurement protocols for SEs scale exponentially with the number of qubits. Here, we efficiently measure SEs for integer Rényi index n>1 via Bell measurements. The SE of N-qubit quantum states can be measured with O(n) copies and O(nN) classical computational time, where for even n we additionally require the complex conjugate of the state. We provide efficient bounds of various nonstabilizerness monotones that are intractable to compute beyond a few qubits. Using the IonQ quantum computer, we measure SEs of random Clifford circuits doped with non-Clifford gates and give bounds for the stabilizer fidelity, stabilizer extent, and robustness of magic. We provide efficient algorithms to measure Clifford-averaged 4n-point out-of-time-order correlators and multifractal flatness. With these measures we study the scrambling time of doped Clifford circuits and random Hamiltonian evolution depending on nonstabilizerness. Counterintuitively, random Hamiltonian evolution becomes less scrambled at long times, which we reveal with the multifractal flatness. Our results open up the exploration of nonstabilizerness with quantum computers.

Published by the American Physical Society
2024
Exploring generative AI assisted feedback writing for students’ written responses to a physics conceptual question with prompt engineering and few-shot learning
Authors: Wan Tong , Chen Zhongzhou
Published: June 2024

Instructor’s feedback plays a critical role in students’ development of conceptual understanding and reasoning skills. However, grading student written responses and providing personalized feedback can take a substantial amount of time, especially in large enrollment courses. In this study, we explore using GPT-3.5 to write feedback on students’ written responses to conceptual questions with prompt engineering and few-shot learning techniques. In stage I, we used a small portion (n=20) of the student responses on one conceptual question to iteratively train GPT to generate feedback. Four of the responses paired with human-written feedback were included in the prompt as examples for GPT. We tasked GPT to generate feedback for another 16 responses and refined the prompt through several iterations. In stage II, we gave four student researchers (one graduate and three undergraduate researchers) the 16 responses as well as two versions of feedback, one written by the authors and the other by GPT. Students were asked to rate the correctness and usefulness of each feedback and to indicate which one was generated by GPT. The results showed that students tended to rate the feedback by human and GPT equally on correctness, but they all rated the feedback by GPT as more useful. Additionally, the success rates of identifying GPT’s feedback were low, ranging from 0.1 to 0.6. In stage III, we tasked GPT to generate feedback for the rest of the students’ responses (n=65). The feedback messages were rated by four instructors based on the extent of modification needed if they were to give the feedback to students. All four instructors rated approximately 70% (ranging from 68% to 78%) of the feedback statements needing only minor or no modification. This study demonstrated the feasibility of using generative artificial intelligence (AI) as an assistant to generate feedback for student written responses with only a relatively small number of examples in the prompt. An AI assistant can be one of the solutions to substantially reduce time spent on grading student written responses.

Published by the American Physical Society
2024
Counterexample to the Lévy flight foraging hypothesis in the narrow capture framework
Authors: Tzou Justin C. , Tzou Leo
Published: June 2024

The Lévy flight foraging hypothesis asserts that biological organisms have evolved to employ (truncated) Lévy flight searches due to such strategies being more efficient than those based on Brownian motion. However, we provide here a concrete two-dimensional counterexample in which Brownian search is more efficient. In fact, we show that the efficiency of Lévy searches worsens the farther the Lévy flight tail index deviates from the Brownian limit. Our counterexample is based on the framework of the classic narrow capture problem in which a random search is performed for a small target within a confined search domain. Our results are obtained via three avenues: Monte Carlo simulations of the discrete search processes, finite-difference solutions, and a matched asymptotic analysis of the elliptic (pseudo)differential equations of the corresponding continuum limits. Asymptotic analysis of the Lévy search yields an expression for the average search time accurate to O(1), providing insights into how the latter is impacted by various features of the target and search domain.

Published by the American Physical Society
2024
Saturating the Maximum Success Probability Bound for Noiseless Linear Amplification Using Linear Optics
Authors: Guanzon Joshua J. , Winnel Matthew S. , Singh Deepesh , Lund Austin P. , Ralph Timothy C.
Published: June 2024

A noiseless linear amplifier (NLA) performs the highest-quality amplification allowable under the rules of quantum physics. Unfortunately, these same rules conspire against us via the no-cloning theorem, which constrains NLA operations to the domain of probabilistic processes. Nevertheless, they are useful for a wide variety of quantum protocols, with numerous proposals assuming access to an optimal NLA device that performs with the maximum possible success probability. Here we propose the first linear-optics NLA protocol that asymptotically achieves this success probability bound by modifying the Knill-Laflamme-Milburn near-deterministic teleporter into an amplifier.

Published by the American Physical Society
2024
Multi-feature fusion stock prediction based on knowledge graph
Authors: Liu Zhenghao , Qian Yuxing , Lv Wenlong , Fang Yanbin , Liu Shenglan
Published: June 2024

Purpose

Stock prices are subject to the influence of news and social media, and a discernible co-movement pattern exists among multiple stocks. Using a knowledge graph to represent news semantics and establish connections between stocks is deemed essential and viable.

Design/methodology/approach

This study presents a knowledge-driven framework for predicting stock prices. The framework integrates relevant stocks with the semantic and emotional characteristics of textual data. The authors construct a stock knowledge graph (SKG) to extract pertinent stock information and use a knowledge graph representation model to capture both the relevant stock features and the semantic features of news articles. Additionally, the authors consider the emotional characteristics of news and investor comments, drawing insights from behavioral finance theory. The authors examined the effectiveness of these features using the combined deep learning model CNN+LSTM+Attention.

Findings

Experimental results demonstrate that the knowledge-driven combined feature model exhibits significantly improved predictive accuracy compared to single-feature models.

Originality/value

The study highlights the value of the SKG in uncovering potential correlations among stocks. Moreover, the knowledge-driven multi-feature fusion stock forecasting model enhances the prediction of stock trends for well-known enterprises, providing valuable guidance for investor decision-making.
Do learners exhibit a willingness to use ChatGPT? An advanced two-stage SEM-neural network approach for forecasting factors influencing ChatGPT adoption
Authors: Thongsri Nattaporn , Tripak Orawan , Bao Yukun
Published: June 2024

Purpose

This study aims to examine the variables that influence learners’ acceptance of chat generative pre-trained transformer (ChatGPT) through the theoretical synthesis of variables in the field of behavioral science. It uses the use and gratifications theory in conjunction with variables related to the information system (IS), as proposed by the Delone and McLean IS success model.

Design/methodology/approach

This quantitative research collected data from 679 undergraduate students using stratified random sampling. A two-staged structural equation modeling (SEM)-neural network approach was used to analyze the data, with SEM used to study the factors influencing the intention to use ChatGPT. Additionally, an artificial neural network approach was used to confirm the results obtained through SEM.

Findings

The two-staged SEM-neural network approach yielded robust and consistent analysis results, indicating that the variable “System quality (SYQ)” has the highest influence, followed by “Cognitive need (CN),” “Information Quality (INQ),” “Social need (SN)” and “Affective need (AN)” in descending order of importance.

Practical implications

The results obtained from integrating the behavioral variables with IS variables will provide guidance to various organizations, such as the Ministry of Education, universities and educators, in the application of artificial intelligence technology in learning. They should prioritize the quality aspect of the system and the technological infrastructure that supports the use of ChatGPT for learning. Additionally, they should prepare learners to be ready in various dimensions, including knowledge, emotions and social aspects.

Originality/value

This study presents challenges in implementing artificial intelligence technology in learning, which educational institutions must embrace to keep up with the global technological trends. The educational sector should integrate artificial intelligence into the curriculum planning, teaching methods and learner assessment processes from the outset.
Development of a population pharmacokinetic model for the novel long‐acting injectable antipsychotic risperidone ISM®
Authors: Laveille Christian , Snoeck Eric , Ochoa Díaz de Monasterioguren Lourdes , Martínez‐González Javier , Llaudó Jordi , Anta Lourdes , Gutierro Ibon
Published: June 2024

Aims

The aims of this study were to develop a population pharmacokinetic (PK) model for risperidone ISM® and to investigate the relationships between active moiety exposure, as described by apparent clearance (CL40), and several covariates using all data from five clinical studies.

Methods

A population PK model was developed using active moiety concentrations from a study in healthy volunteers and two studies in patients with schizophrenia. Data from a comparative bioavailability study in medically stable patients and a Phase III study in patients with acute exacerbation of schizophrenia were then incorporated, using empirical Bayesian feedback and model refinement in NONMEM. Finally, covariate analysis was performed on CL40.

Results

The final model adequately described the pharmacokinetics of 6288 active moiety concentrations in 17 healthy volunteers and 430 patients with schizophrenia. This one‐compartment disposition model had a complex absorption process, combining a small amount immediately entering the central active moiety compartment, two first‐order absorption processes and a combined zero‐order and first order process, with first‐order elimination from the central compartment. Significant covariates on CL40 were BMI and sex. Goodness‐of‐fit (GOF) plots and visual predictive checks (VPC) confirmed acceptable description of the data.

Conclusions

The population PK model adequately described active moiety concentrations from five clinical studies after risperidone ISM® administration. Relationships between active moiety exposure and covariates were defined in order to facilitate simulations for future studies. The model showed that risperidone ISM® rapidly achieves therapeutic plasma levels within the first hours after the first injection that are maintained sustainedly throughout the whole dosing interval following once‐monthly gluteal injections of 100 mg and 75 mg.
Immunogenicity of COVID‐19 vaccines in patients with follicular lymphoma receiving frontline chemoimmunotherapy
Authors: Lim Yeong Jer , Ward Victoria , Brown Anthony , Phillips Eloise , Kronsteiner Barbara , Malone Tom , Jennings Daisy , Healy Saoirse , Longet Stephanie , James Timothy , Thomson Paul , Farrell Liam , Oates Melanie , Jackson Richard , Morrison Andrew , Burns Matthew , Carroll Miles , Klenerman Paul , Turtle Lance , Naisbitt Dean , Rhodes Malcolm , Robinson Kate , Gatto Simona , Young Moya , Linton Kim , Eyre Toby A. , Eyre David W. , Dunachie Susanna , Barnes Eleanor , Pettitt Andrew
Published: June 2024

Immune responses to primary COVID‐19 vaccination were investigated in 58 patients with follicular lymphoma (FL) as part of the PETReA trial of frontline therapy (EudraCT 2016–004010‐10). COVID‐19 vaccines (BNT162b2 or ChAdOx1) were administered before, during or after cytoreductive treatment comprising rituximab (depletes B cells) and either bendamustine (depletes CD4+ T cells) or cyclophosphamide‐based chemotherapy. Blood samples obtained after vaccine doses 1 and 2 (V1, V2) were analysed for antibodies and T cells reactive to the SARS‐CoV‐2 spike protein using the Abbott Architect and interferon‐gamma ELISpot assays respectively. Compared to 149 healthy controls, patients with FL exhibited lower antibody but preserved T‐cell responses. Within the FL cohort, multivariable analysis identified low pre‐treatment serum IgA levels and V2 administration during induction or maintenance treatment as independent determinants of lower antibody and higher T‐cell responses, and bendamustine and high/intermediate FLIPI‐2 score as additional determinants of a lower antibody response. Several clinical scenarios were identified where dichotomous immune responses were estimated with >95% confidence based on combinations of predictive variables. In conclusion, the immunogenicity of COVID‐19 vaccines in FL patients is influenced by multiple disease‐ and treatment‐related factors, among which B‐cell depletion showed differential effects on antibody and T‐cell responses.
Controversies in the pathophysiology of leg ulcers in sickle cell disease
Authors: Catella Judith , Guillot Nicolas , Nader Elie , Skinner Sarah , Poutrel Solène , Hot Arnaud , Connes Philippe , Fromy Berengère
Published: June 2024

Patients with sickle cell disease (SCD) often experience painful vaso‐occlusive crises and chronic haemolytic anaemia, as well as various acute and chronic complications, such as leg ulcers. Leg ulcers are characterized by their unpredictability, debilitating pain and prolonged healing process. The pathophysiology of SCD leg ulcers is not well defined. Known risk factors include male gender, poor social conditions, malnutrition and a lack of compression therapy when oedema occurs. Leg ulcers typically start with spontaneous pain, followed by induration, hyperpigmentation, blister formation and destruction of the epidermis. SCD is characterized by chronic haemolysis, increased oxidative stress and decreased nitric oxide bioavailability, which promote ischaemia and inflammation and consequently impair vascular function in the skin. This cutaneous vasculopathy, coupled with venostasis around the ankle, creates an ideal environment for local vaso‐occlusive crises, which can result in the development of leg ulcers that resemble arterial ulcers. Following the development of the ulcer, healing is hindered as a result of factors commonly observed in venous ulceration, including venous insufficiency, oedema and impaired angiogenesis. All of these factors are modulated by genetic factors. However, our current understanding of these genetic factors remains limited and does not yet enable us to accurately predict ulceration susceptibility.
Spatiotemporal cell landscape of human embryonic tooth development
Authors: Shi Yueqi , Yu Yejia , Li Jutang , Sun Shoufu , Han Li , Wang Shaoyi , Guo Ke , Yang Jingang , Qiu Jin , Wei Wenjia
Published: June 2024

Understanding the cellular composition and trajectory of human tooth development is valuable for dentistry and stem cell engineering research. Previous single‐cell studies have focused on mature human teeth and developing mouse teeth, but the cell landscape of human embryonic dental development is still unknown. In this study, tooth germ tissues were collected from aborted foetus (17–24 weeks) for single‐cell RNA sequence and spatial transcriptome analysis. The cells were classified into seven subclusters of epithelium, and seven clusters of mesenchyme, as well as other cell types such as Schwann cell precursor and pericyte. For epithelium, the stratum intermedium branch and the ameloblast branch diverged from the same set of outer enamel‐inner enamel‐ALCAM+ epithelial cell lineage, but their spatial distribution of two branches was not clearly distinct. This trajectory received spatially adjacent regulation signals from mesenchyme and pericyte, including JAG1 and APP. The differentiation of pulp cell and pre‐odontoblast showed four waves of temporally distinct gene expression, which involved regulation networks of LHX9, DLX5 and SP7, and these genes were regulated by upstream ligands such as the BMP family. This provides a reference landscape for the research on early human tooth development, covering different spatial structures and developmental periods.
From the little divergence to the little divide: Real wages in the Kingdom of Sicily (1540‒1850)
Authors: Buscemi Tancredi
Published: June 2024

This paper challenges the commonly held belief that Southern Italy was a homogeneous, backwards region by reconstructing real wages in the kingdom of Sicily over three centuries. The findings suggest more than one divide in pre‐unitarian regions, with Sicilian living standards being structurally higher than the Italian average. This study has important implications for traditional debates in European and Italian economic history, such as the timing of the little divergence and the Italian economic downturn. Additionally, it raises new questions regarding the origins of the regional divide, highlighting a heterogeneous picture of regional trends and the need for broader spatial coverage in wage studies to avoid the potential bias of single‐city analysis.
Fabrication, microstructure, and properties of Dy‐doped (Y1−xDyx)3Si2C2 ceramics fabricated by in situ reactive spark plasma sintering
Authors: Chen Lianghao , Cui Pengxing , Yang Guangyong , Tatarko Peter , Dai Jian‐Qing , Wang Canglong , Zhou Xiaobing
Published: June 2024

Dysprosium (Dy)‐doped (Y1−xDyx)3Si2C2 (x = 0, 0.1, 0.3, 0.5) solid solution ceramics were successfully fabricated using an in situ reaction spark plasma sintering technology, for the first time. The effect of various Dy doping contents (x) on the microstructure, mechanical, and thermal properties of (Y1−xDyx)3Si2C2 ceramics was investigated. The (0 2 0) crystal plane spacing of (Y0.5Dy0.5)3Si2C2 was 7.813 Å, which was smaller than that of Y3Si2C2, due to the fact that the atomic radius of Dy is smaller than that of Y. The Dy doping facilitated the consolidation of (Y1−xDyx)3Si2C2, thus a highly dense (Y0.5Dy0.5)3Si2C2 ceramic material with a low open porosity of 0.14% was successfully obtained at a relatively low temperature of 1 200°C. As the content of Dy doping (x) increased from 0 to 0.5, the purity of (Y1−xDyx)3Si2C2 ceramics increased from 88.3 to 90.7 wt.%, while the grain size of (Y1−xDyx)3Si2C2 ceramics decreased from 0.59 to 0.46 µm. As a result, the Vickers hardness and thermal conductivity of the (Y0.5Dy0.5)3Si2C2 material was 7.1 GPa and 9.8 W·m−1·K−1, respectively.
Synergetic engineering of ZnS/In2Te3 heterostructure for efficient oxygen evolution reaction
Authors: Alothman Asma A. , Kumar Ome Parkash , Madni Muhammad , Ahmad Imran , Mohammad Saikh , Saleem Shahroz , Abid Abdul Ghafoor
Published: June 2024

The potential of electrochemical water splitting to tackle energy and environmental issues has garnered substantial interest. In the present work, an effective ZnS/In2Te3 has been constructed by hydrothermal support on a stainless‐steel strip and explored for oxygen evolution. The addition of ZnS modifies the band structure of In2Te3 and enhances its specific conductivity and capacitance on an intrinsic level, making rapid ion transportation. The optimized ZnS/In2Te3 displayed efficient oxygen evolution reaction (OER) performance with an overpotential of 228 mV and a Tafel slope of 111 mV dec−1 with cyclic activity up to 1000 cycles in 1 M KOH solution. ZnS/In2Te3 has a large surface area (28 m3g−1) and a charge capacitance of (.037 mF), according to studies using Brunauer–Emmett–Teller and double‐layer capacitance. Combining several strategies improves overall electrochemical performance of ZnS/In2Te3, making it a promising option for use in state‐of‐the‐art OER.
Unemployment volatility: When workers pay costs upon accepting jobs
Authors: Ryan Rich
Published: June 2024

Hiring workers is costly. Firms' costs reduce resources that can go to recruitment and amplify how unemployment responds to changes in productivity. Workers also incur up‐front costs. Examples include moving expenses and regulatory fees. Workers' costs lessen unemployment volatility and leave resources available for recruitment unchanged. Their influence is bounded by the properties of a matching function. Using adjusted data on job finding, I estimate a bound that ascribes limited influence. The results demonstrate that workers' costs affect outcomes (firms threaten workers with paying the fixed costs again if negotiations fail), but their influence on volatility is less than firms' costs.
Effect of sheeting pressure on the viability of Escherichia coli during noodle processing
Authors: Xu Yingying , Lv Na , Yang Xudong , He Xiaohua , Li Ke , Liu Bin
Published: June 2024

Escherichia coli is known to easily contaminate noodles and form biofilms during noodle processing. Sheeting was a key step in the processing. The objective of our study was to investigate the influence of sheeting pressure on the viability of E. coli. Our findings revealed a significant reduction in the E. coli count (by 1.46 log CFU g−1), as well as their swimming diameter (by 46.7%) and biofilm formation (by 25.7%) following an additional 20 sheeting treatments. The expression of genes (flhC, flhD, rpoS, csgD and adrA) validated the weakening of E. coli survival due to sheeting pressure. Moreover, the alterations in dough texture properties had adverse effects on the survival of E. coli. These results highlight that sheeting pressure can effectively reduce E. coli viability in dough. The implications of our findings provide valuable insights for minimising microbial contamination in noodle production.
Do cash transfer programs have different effects on children based on household disability status? Evidence from Malawi and Zambia
Authors: Silverstein Hannah , Angeles Gustavo , Handa Sudhanshu , Singh Kavita , Shanahan Meghan , Thissen David
Published: June 2024

Globally, about 1 billion people have disabilities. Cash transfers (CTs) are social protection programs often explicitly including people with disabilities. There is little research differentiating CT impacts by disability status. We used a triple difference estimation strategy with three‐way interaction terms to estimate disability‐differential impacts of CTs in Malawi and Zambia on material needs, physical health, and nutritional status among children. Results show CTs reduced the prevalence of illness more among children in households of members experiencing the greatest functional difficulties compared to those in households without disability. The CTs similarly improved access to material needs for all children. This research suggests CTs in Malawi and Zambia affected children in households with disabilities more in terms of health outcomes, despite experiencing similar impacts on material inputs.
Evaluating the carbon footprint of sedation practices in intensive care
Authors: Soong Jie Lin , Ho Pei Lin , Neo Valerie Ser Hwee , Lie Sui An
Published: June 2024

Background

Healthcare's carbon footprint contributes to 4.4% of global net emissions and intensive care units (ICUs) are very resource intensive. Existing studies on environmental sustainability in ICUs focused on carbon footprint generated from energy and electricity consumption, use of medical consumables and equipment, but few studies quantified carbon footprint generated from pharmaceuticals used in ICUs.

Aim

To evaluate carbon footprint arising from sedation practices in the ICUs.

Study Design

A pilot, prospective observational study was conducted in two ICUs from 1 August to 22 September 2022 in Singapore General Hospital. Adult patients who were consecutively sedated, intubated and expected to be mechanically ventilated for at least 24 h were included. Total amount of analgesia and sedatives used and wasted in eligible patients were collected. Carbon emission from ICU sedation practices were then quantified using available life cycle assessment data.

Results

A total of 31 patients were recruited. Top analgesia and sedative used in both ICUs were fentanyl and propofol, respectively. Carbon footprint from sedative usage and wastage across 7 weeks in both ICUs were 2.206 kg CO2‐e and 0.286 g CO2‐e, respectively. In total, this equates to driving 15.8 km by car. Proportion of drug wasted ranged from 5.1% to 25.0%, with the top reason for wastage being the drug was no longer clinically indicated. Recommendations to reduce carbon footprint include choosing sedatives with lower carbon emissions where possible and having effective communication among doctors and nurses regarding management plans to minimize unnecessary wastage.

Conclusion

Our study quantified carbon footprint arising from sedation practices, mainly drug usage and wastage in two ICUs in Singpore General Hospital.

Relevance to Clinical Practice

Adopting a holistic approach to environmental sustainability in the ICU, sedation practices also contribute to generating greenhouse gases, albeit small, and can be targeted to reduce unnecessary carbon footprint.
Innovations and prospectives of multidimensional trait integration
Authors: Li Ying , He Nianpeng
Published: June 2024

This article is a Commentary on Ye et al. (2024), 244: 436–450.
Practical Applications of the Material Modeling Approach in the Aerospace Industry
Authors: Chengalva Mahesh , Dang Vivian
Published: June 2024

As the aerospace industry steadily increases the use of Model-Based Engineering, digital twins are rapidly preceding physical counterparts in all types of applications. Virtual testing, which involves the use of digital twins to accurately replicate the results of physical tests, provides a significant competitive advantage. A powerful analytical methodology that enables virtual testing to failure is referred to in academia and industry as the material modeling approach. In this approach, basic material characterization data from simple and inexpensive coupon-level tests are utilized to develop generalized 3D material constitutive equations using continuum mechanics. These in turn are condensed into code referred to as ‘material subroutines’ that can then be interfaced with commercial Finite Element software for general purpose structural modeling of failure. The main advantage of this approach is in their capability to model structural failure based on material characterization data from simple easy-to-perform tests. Moreover, the independence of the material model from structural considerations enables applications to structures of all forms and sizes. Production applications of this approach at Boeing for strength and stability prediction are covered in this paper along with pathfinder applications in the areas of ballistic impact, illustrating the broad scope and potential of this powerful analytical approach.
Aeroservoelasticity’s Digital Simulation Using PLC
Authors: Deepthi K. Sudha , B. Rammohan
Published: June 2024

The objective of the “Digital Twin for “Aeroservoelasticity” is to generate an intricate virtual model of aeroelastic systems that closely resembles their real attributes and behaviors. Ladder logic programming on a programmable logic controller (PLC) is a powerful tool for handling such changes. Consistent with the principles of Industry 4.0, this study creates a ladder logic to explain the digital twin idea inside the aeroservoelastic model. Ladder logic programming and the digital twin idea enable the monitoring, optimization, and predictive maintenance of aerospace systems. which enables more accurate and timely results. This method works especially well in aeroservoelastic situations when there is a complicated interaction between forces and reactions and quick and precise decision-making is needed. Additionally, ladder logic programming’s adaptability meets Industry 4.0 requirements. In order to address aeroservoelasticity this research work presents a novel methodology and the creative integration of ladder logic programming within the digital twin concept. Additionally, it focuses on enhancing the capabilities of the digital twin by incorporating ladder logic programming, a type of Programmable Logic Controller (PLC) programming. Industry 4.0, Building a complex virtual model that accurately captures the dynamic interactions between structural elasticity, aerodynamic forces, and aircraft control systems is required for its application in aeroelasticity.
Predicting Fracture Toughness in Polymers Using a Novel Atomistic-Continuum Concurrent Coupling Technique
Authors: Aditya Sankha , Roy Samit
Published: June 2024

The objective of this paper is to predict fracture properties of soft materials such as polymer using molecular dynamics (MD) coupled with finite element method (FEM). A novel method for concurrent coupling of atomistic and continuum domains is applied to achieve the length scales required to fully capture the fracture process zone (FPZ). Outside of the FPZ, linear elastic fracture mechanics (LEFM) concepts are valid and used to prescribe K-field boundary conditions. The nonlinear stress-strain behavior of an epoxy polymer MD model is approximated using the Ramberg-Osgood model, which is used to define the FEM domain. The coupled system is validated and then used for simulating fracture. FPZ size and J-integral variation with increasing stress intensity factor are then studied and compared with LEFM solutions.
Incline Firing Analysis Using ANSYS to Determine Directional Barrel Deformations
Authors: Huang Ce , Dhainaut Jean-Michel , Talley Jefferson , Du Phil
Published: June 2024

In this paper, the directional deformations of a 120mm smoothbore tank gun were analyzed during several initial firing angles. This analysis sets up the barrel as a cantilever beam and accelerates the projectile with a given pressure time load history. This study aims to understand the deformation patterns associated with various firing angles with a Finite Element Analysis (FEA) approach and seeks to obtain valuable initial conditions to improve long-range firing accuracy at a relatively large firing angle. The primary objective of the paper was to uncover a physical rationale behind the “rifle rule”, which suggests that when shooting at an inclined surface, the projectile tends to strike higher. The findings are intended to inform the development of a 3D trajectory analysis simulator. The axial, vertical, and horizontal deformation of the barrel at 0, ±15, ±30, and ±45 degrees are compared, as well as validating the results with the projectile’s exit velocity. Lastly, the results show that the vertical deformation of the barrel is significant enough to vary the trajectory of the projectile and should be considered during an inclined/declined firing scenario. While the axial and horizontal deformations are small enough to be considered trivial and unlikely to have a significant effect on the accuracy.
Structural and Aerodynamic Characteristics of Micro-Perforated Porous Sheets for Laminar Flow Control
Authors: Traub Hendrik , Kube Jan , Jose Siby , Prasannakumar Adarsh , Hühne Christian
Published: June 2024

Laminar flow control shows an unparalleled potential to increase the energy efficiency of state-of-the-art transport aircraft. However, active boundary layer suction requires micro-metre precision and is associated with extensive manufacturing effort. This study investigates new manufacturing technologies, such as additive manufacturing and laminating of porous sheets for boundary layer suction. The new porous sheets extend the design space of porous skins for laminar flow control and aim to reduce their manufacturing effort. This research shows the feasibility of additively manufactured and laminated porous sheets with perforation diameters below 250 μm and pressure drop characteristics comparable to available etched and laser-drilled sheets.