bluuebunny/crossref_metadata_2025 huggingface dataset:
Pulmonary valve replacement in tetralogy of Fallot – who and how?
Authors: Costa Catarina M. , Cruz Cristina , Pinho Teresa , Torres Sofia , Silva João C. , Madureira José A. , Salgueiro Elson , Casanova Jorge , Pinho Paulo , Macedo Filipe
Published: November 2023

Background and Aim:

Pulmonary regurgitation is the most common complication in repaired tetralogy of Fallot patients. Severe chronic pulmonary regurgitation can be tolerated for decades, but if not treated, it can progress to symptomatic, irreversible right ventricular dilatation and dysfunction. We investigated clinical associations with pulmonary valve replacement among patients with significative pulmonary regurgitation and how interventional developments can change their management.

Methods:

All adult patients with repaired tetralogy of Fallot who were followed at an adult CHD Clinic at a single centre from 1980 to 2022 were included on their first outpatient visit. Follow-up was estimated from the time of correction surgery until one of the following events occurred first: pulmonary valve replacement, death, loss to follow-up or conclusion of the study.

Results:

We included 221 patients (116 males) with a median age of 19 (18–25). At a median age of 33 (10) years old, 114 (51%) patients presented significant pulmonary regurgitation. Among patients with significant pulmonary regurgitation, pulmonary valve replacement was associated with male gender, older age at surgical repair, and longer QRS duration in adulthood. Pulmonary valve replacement was performed in 50 patients, including four transcatheter pulmonary valve implantations, at a median age of 34 (14) years.

Conclusion:

Pulmonary regurgitation affects a large percentage of tetralogy of Fallot adult patients, requiring a long-term clinical and imaging follow-up. Sex, age at surgical repair and longer QRS are associated with the need of PVR among patients with significative pulmonary regurgitation. Clinical practice and current literature support TPVI as the future gold standard intervention.
Global economic freedom during the second year of the pandemic
Authors: Miozzi Vincent J. , Powell Benjamin
Published: November 2023

This note updates a measure oflockdown regulatory freedomfor 2021 and then uses it to adjust countries' 2021 economic freedom scores to account for pandemic regulations that impact economic freedom but otherwise would go unmeasured. We directly follow Miozzi and Powell's (2023a,Journal of Institutional Economics19(2), 229–250) methods to measure lockdown regulations and adjust 2020 economic freedom scores. Thus, when paired with those findings we provide a data set that consistently measures coronavirus disease 2019 regulations and economic freedom over the course of the pandemic that can be used in other research. We find thatlockdown regulatory freedomincreased as countries scaled back pandemic regulations, while other areas of economic freedom continued declining. We also find that adjusting forlockdown regulatory freedomcontinues to significantly impact countries' relative ranking in economic freedom.
It's Not Easy Being Green: Kinetic Modeling of the Emission Spectrum Observed in STEVE's Picket Fence
Authors: Gasque L. Claire , Janalizadeh Reza , Harding Brian J. , Yonker Justin D. , Gillies D. Megan
Published: November 2023

Recent studies suggest that, despite its aurora‐like appearance, the picket fence may not be driven by magnetospheric particle precipitation but instead by local electric fields parallel to Earth's magnetic field. Here, we evaluate the parallel electric fields hypothesis by quantitatively comparing picket fence spectra with the emissions generated in a kinetic model driven by local parallel electric fields energizing ambient electrons in a realistic neutral atmosphere. We find that, at a typical picket fence altitude of 110 km, parallel electric fields between 40 and 70 Td (∼80–150 mV/m at 110 km) energize ambient electrons sufficiently so that, when they collide with neutrals, they reproduce the observed ratio of N2 first positive to atomic oxygen green line emissions, without producing first negative emissions. These findings establish a quantitative connection between ionospheric electrodynamics and observable picket fence emissions, offering verifiable targets for future models and experiments.
Inhibition of LSD1 induces ferroptosis through the ATF4-xCT pathway and shows enhanced anti-tumor effects with ferroptosis inducers in NSCLC
Authors: Du Linna , Yang Han , Ren Yufei , Ding Yanli , Xu Yichao , Zi Xiaolin , Liu Hongmin , He Pengxing
Published: November 2023

Lysine-specific demethylase 1 (LSD1) has been identified as an important epigenetic target, and recent advances in lung cancer therapy have highlighted the importance of targeting ferroptosis. However, the precise mechanisms by which LSD1 regulates ferroptosis remain elusive. In this study, we report that the inhibition of LSD1 induces ferroptosis by enhancing lipid peroxidation and reactive oxygen species (ROS) accumulation. Mechanistically, LSD1 inhibition downregulates the expression of activating transcription factor 4 (ATF4) through epigenetic modification of histone H3 lysine 9 dimethyl (H3K9me2), which sequentially inhibits the expression of the cystine–glutamate antiporter (xCT) and decreases glutathione (GSH) production. Furthermore, LSD1 inhibition transcriptionally upregulates the expression of transferrin receptor (TFRC) and acyl-CoA synthetase long chain family member 4 (ACSL4) by enhancing the binding of histone H3 lysine 4 dimethyl (H3K4me2) to their promoter sequences. Importantly, the combination of an LSD1 inhibitor and a ferroptosis inducer demonstrates an enhanced anti-tumor effect in a xenograft model of non-small cell lung cancer (NSCLC), surpassing the efficacy of either agent alone. These findings reveal new insights into the mechanisms by which LSD1 inhibition induces ferroptosis, offering potential guidance for the development of new strategies in the treatment of NSCLC.
Deep learning at the edge enables real-time streaming ptychographic imaging
Authors: Babu Anakha V. , Zhou Tao , Kandel Saugat , Bicer Tekin , Liu Zhengchun , Judge William , Ching Daniel J. , Jiang Yi , Veseli Sinisa , Henke Steven , Chard Ryan , Yao Yudong , Sirazitdinova Ekaterina , Gupta Geetika , Holt Martin V. , Foster Ian T. , Miceli Antonino , Cherukara Mathew J.
Published: November 2023

Coherent imaging techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells. Driven by the construction of brighter sources and high-rate detectors, coherent imaging methods like ptychography are poised to revolutionize nanoscale materials characterization. However, these advancements are accompanied by significant increase in data and compute needs, which precludes real-time imaging, feedback and decision-making capabilities with conventional approaches. Here, we demonstrate a workflow that leverages artificial intelligence at the edge and high-performance computing to enable real-time inversion on X-ray ptychography data streamed directly from a detector at up to 2 kHz. The proposed AI-enabled workflow eliminates the oversampling constraints, allowing low-dose imaging using orders of magnitude less data than required by traditional methods.
Specific heterozygous variants in MGP lead to endoplasmic reticulum stress and cause spondyloepiphyseal dysplasia
Authors: Gourgas Ophélie , Lemire Gabrielle , Eaton Alison J. , Alshahrani Sultanah , Duker Angela L. , Li Jingjing , Carroll Ricki S. , Mackenzie Stuart , Nikkel Sarah M. ,   Care4Rare Canada Consortium, Bober Michael B. , Boycott Kym M. , Murshed Monzur
Published: November 2023

Matrix Gla protein (MGP) is a vitamin K-dependent post-translationally modified protein, highly expressed in vascular and cartilaginous tissues. It is a potent inhibitor of extracellular matrix mineralization. Biallelic loss-of-function variants in the MGP gene cause Keutel syndrome, an autosomal recessive disorder characterized by widespread calcification of various cartilaginous tissues and skeletal and vascular anomalies. In this study, we report four individuals from two unrelated families with two heterozygous variants in MGP, both altering the cysteine 19 residue to phenylalanine or tyrosine. These individuals present with a spondyloepiphyseal skeletal dysplasia characterized by short stature with a short trunk, diffuse platyspondyly, midface retrusion, progressive epiphyseal anomalies and brachytelephalangism. We investigated the cellular and molecular effects of one of the heterozygous deleterious variants (C19F) using both cell and genetically modified mouse models. Heterozygous ‘knock-in’ mice expressing C19F MGP recapitulate most of the skeletal anomalies observed in the affected individuals. Our results suggest that the main underlying mechanism leading to the observed skeletal dysplasia is endoplasmic reticulum stress-induced apoptosis of the growth plate chondrocytes. Overall, our findings support that heterozygous variants in MGP altering the Cys19 residue cause autosomal dominant spondyloepiphyseal dysplasia, a condition distinct from Keutel syndrome both clinically and molecularly.
DNA strand breaks and gaps target retroviral intasome binding and integration
Authors: Senavirathne Gayan , London James , Gardner Anne , Fishel Richard , Yoder Kristine E.
Published: November 2023

Retrovirus integration into a host genome is essential for productive infections. The integration strand transfer reaction is catalyzed by a nucleoprotein complex (Intasome) containing the viral integrase (IN) and the reverse transcribed (RT) copy DNA (cDNA). Previous studies suggested that DNA target-site recognition limits intasome integration. Using single molecule Förster resonance energy transfer (smFRET), we show prototype foamy virus (PFV) intasomes specifically bind to DNA strand breaks and gaps. These break and gap DNA discontinuities mimic oxidative base excision repair (BER) lesion-processing intermediates that have been shown to affect retrovirus integration in vivo. The increased DNA binding events targeted strand transfer to the break/gap site without inducing substantial intasome conformational changes. The major oxidative BER substrate 8-oxo-guanine as well as a G/T mismatch or +T nucleotide insertion that typically introduce a bend or localized flexibility into the DNA, did not increase intasome binding or targeted integration. These results identify DNA breaks or gaps as modulators of dynamic intasome-target DNA interactions that encourage site-directed integration.
Rapid threat assessment in the Drosophila thermosensory system
Authors: Jouandet Genevieve C. , Alpert Michael H. , Simões José Miguel , Suhendra Richard , Frank Dominic D. , Levy Joshua I. , Para Alessia , Kath William L. , Gallio Marco
Published: November 2023

Neurons that participate in sensory processing often display “ON” responses, i.e., fire transiently at the onset of a stimulus. ON transients are widespread, perhaps universal to sensory coding, yet their function is not always well-understood. Here, we show that ON responses in the Drosophila thermosensory system extrapolate the trajectory of temperature change, priming escape behavior if unsafe thermal conditions are imminent. First, we show that second-order thermosensory projection neurons (TPN-IIIs) and their Lateral Horn targets (TLHONs), display ON responses to thermal stimuli, independent of direction of change (heating or cooling) and of absolute temperature. Instead, they track the rate of temperature change, with TLHONs firing exclusively to rapid changes (>0.2 °C/s). Next, we use connectomics to track TLHONs’ output to descending neurons that control walking and escape, and modeling and genetic silencing to demonstrate how ON transients can flexibly amplify aversive responses to small thermal change. Our results suggest that, across sensory systems, ON transients may represent a general mechanism to systematically anticipate and respond to salient or dangerous conditions.
Exhaustive search for optimal molecular geometries using imaginary-time evolution on a quantum computer
Authors: Kosugi Taichi , Nishi Hirofumi , Matsushita Yu-ichiro
Published: November 2023

This study proposes a nonvariational scheme for geometry optimization of molecules for the first-quantized eigensolver, which is a recently proposed framework for quantum chemistry using probabilistic imaginary-time evolution (PITE). In this scheme, the nuclei in a molecule are treated as classical point charges while the electrons are treated as quantum mechanical particles. The electronic states and candidate geometries are encoded as a superposition of many-qubit states, for which a histogram created from repeated measurements gives the global minimum of the energy surface. We demonstrate that the circuit depth per step scales as$${{{\mathcal{O}}}}({n}_{{\rm {e}}}^{2}{{{\rm{poly}}}}(\log {n}_{{\rm {e}}}))$$O(ne2poly(logne))for the electron numberne, which can be reduced to$${{{\mathcal{O}}}}({n}_{{\rm {e}}}{{{\rm{poly}}}}(\log {n}_{{\rm {e}}}))$$O(nepoly(logne))if extra$${{{\mathcal{O}}}}({n}_{{\rm {e}}}\log {n}_{{\rm {e}}})$$O(nelogne)qubits are available. Moreover, resource estimation implies that the total computational time of our scheme starting from a good initial guess may exhibit overall quantum advantage in molecule size and candidate number. The proposed scheme is corroborated using numerical simulations. Additionally, a scheme adapted to variational calculations is examined that prioritizes saving circuit depths for noisy intermediate-scale quantum (NISQ) devices. A classical system composed only of charged particles is considered as a special case of the scheme. The new efficient scheme will assist in achieving scalability in practical quantum chemistry on quantum computers.
Error per single-qubit gate below 10−4 in a superconducting qubit
Authors: Li Zhiyuan , Liu Pei , Zhao Peng , Mi Zhenyu , Xu Huikai , Liang Xuehui , Su Tang , Sun Weijie , Xue Guangming , Zhang Jing-Ning , Liu Weiyang , Jin Yirong , Yu Haifeng
Published: November 2023

Implementing arbitrary single-qubit gates with near perfect fidelity is among the most fundamental requirements in gate-based quantum information processing. In this work, we fabricate a transmon qubit with long coherence times and demonstrate single-qubit gates with the average gate error below 10−4, i.e. (7.42 ± 0.04) × 10−5 by randomized benchmarking (RB). To understand the error sources, we experimentally obtain an error budget, consisting of the decoherence errors lower bounded by (4.62 ± 0.04) × 10−5 and the leakage rate per gate of (1.16 ± 0.04) × 10−5. Moreover, we reconstruct the process matrices for the single-qubit gates by the gate set tomography (GST), with which we simulate RB sequences and obtain single-qubit fidelities consistent with experimental results. We also observe non-Markovian behavior in the experiment of long-sequence GST, which may provide guidance for further calibration. The demonstration extends the upper limit that the average fidelity of single-qubit gates can reach in a transmon-qubit system, and thus can be an essential step towards practical and reliable quantum computation in the near future.
Scalable and high throughput photothermal water disinfection with negligible CO2 footprint utilizing nanostructured carbon coatings
Authors: Sah Ananya , Mandal Atindra Kanti , Tiwari Shubham , Mukherji Soumyo , Subramaniam Chandramouli
Published: November 2023

Water heating and disinfection with reduced energy and CO2 footprint demands new and efficient materials for solar-thermal conversion technologies. Here, we demonstrate nanostructured porous hard-carbon florets (NCF) as effective solar absorber coating achieving excellent photon thermalization efficiency (87%). Functional NCF coating on three-dimensionally tapered helical solar receivers generate high surface temperatures (up to 95 °C). Such ‘green-heat’ is channeled to heat water up to 82 °C that simultaneously results in water disinfection through thermal shock. Untreated lake-water with high turbidity (5 NTU), high bacterial load (106 CFU mL−1) and pathogenic fungi is effectively disinfected in a continuous flow process. Translating this, a fully automated SWAP prototype (solar water antimicrobial purifier), delivers bacteria free hot water at an output capacity of 42 L m−2 day−1 with the lowest CO2 footprint (5 kg L−1) in comparison to all other existing approaches (>40 kg L−1).
CreelCat, a Catalog of United States Inland Creel and Angler Survey Data
Authors: Sievert Nicholas A. , Lynch Abigail J. , Embke Holly S. , Robertson Ashley , Lang Mitchel , Kaz Anna L. , Robertson Matthew D. , Midway Stephen R. , Wszola Lyndsie , Paukert Craig P.
Published: November 2023

The United States Inland Creel and Angler Survey Catalog (CreelCat) contains a national compilation of angler and creel survey data collected by natural resource management agencies across the United States (including Washington, D.C. and Puerto Rico). These surveys are used to help inform the management of recreational fisheries, by collecting information about anglers including what they are catching and harvesting, the amount of effort they expend, their angling preferences, and demographic information. As of May 1, 2023, CreelCat houses over 14,729 surveys from 33 states, Puerto Rico, and Washington, D.C., comprising 235 data fields across 8 tables. These tables contain 235,015 records of fish catch and harvest metrics, 27,250 angler preference metrics, 14,729 records of survey characteristics, 13,576 records of effort metrics, and 409 records of angler demographics. Though individual creel surveys are often deployed to meet local science and management objectives, creel data aggregated across jurisdictions has the potential to address larger scale research and management needs.
Early and fair COVID-19 outcome risk assessment using robust feature selection
Authors: Giuste Felipe O. , He Lawrence , Lais Peter , Shi Wenqi , Zhu Yuanda , Hornback Andrew , Tsai Chiche , Isgut Monica , Anderson Blake , Wang May D.
Published: November 2023

Personalized medicine plays an important role in treatment optimization for COVID-19 patient management. Early treatment in patients at high risk of severe complications is vital to prevent death and ventilator use. Predicting COVID-19 clinical outcomes using machine learning may provide a fast and data-driven solution for optimizing patient care by estimating the need for early treatment. In addition, it is essential to accurately predict risk across demographic groups, particularly those underrepresented in existing models. Unfortunately, there is a lack of studies demonstrating the equitable performance of machine learning models across patient demographics. To overcome this existing limitation, we generate a robust machine learning model to predict patient-specific risk of death or ventilator use in COVID-19 positive patients using features available at the time of diagnosis. We establish the value of our solution across patient demographics, including gender and race. In addition, we improve clinical trust in our automated predictions by generating interpretable patient clustering, patient-level clinical feature importance, and global clinical feature importance within our large real-world COVID-19 positive patient dataset. We achieved 89.38% area under receiver operating curve (AUROC) performance for severe outcomes prediction and our robust feature ranking approach identified the presence of dementia as a key indicator for worse patient outcomes. We also demonstrated that our deep-learning clustering approach outperforms traditional clustering in separating patients by severity of outcome based on mutual information performance. Finally, we developed an application for automated and fair patient risk assessment with minimal manual data entry using existing data exchange standards.
How intra-source imbalanced datasets impact the performance of deep learning for COVID-19 diagnosis using chest X-ray images
Authors: Zhang Zhang , Zhang Xiaoyong , Ichiji Kei , Bukovský Ivo , Homma Noriyasu
Published: November 2023

Over the past decade, the use of deep learning has been widely increasing in the medical image diagnosis field. Deep learning-based methods’ (DLMs) performance strongly relies on training data. Therefore, researchers often focus on collecting as much data as possible from different medical facilities or developing approaches to avoid the impact of inter-category imbalance (ICI), which means a difference in data quantity among categories. However, due to the ICI within each medical facility, medical data are often isolated and acquired in different settings among medical facilities, known as the issue of intra-source imbalance (ISI) characteristic. This imbalance also impacts the performance of DLMs but receives negligible attention. In this study, we study the impact of the ISI on DLMs by comparison of the version of a deep learning model that was trained separately by an intra-source imbalanced chest X-ray (CXR) dataset and an intra-source balanced CXR dataset for COVID-19 diagnosis. The finding is that using the intra-source imbalanced dataset causes a serious training bias, although the dataset has a good inter-category balance. In contrast, the deep learning model performed a reliable diagnosis when trained on the intra-source balanced dataset. Therefore, our study reports clear evidence that the intra-source balance is vital for training data to minimize the risk of poor performance of DLMs.
Small signal modulation of photonic crystal surface emitting lasers
Authors: Orchard Jonathan R. , Ivanov Pavlo , McKenzie Adam F. , Hill Calum H. , Javed Ibrahim , Munro Connor W. , Kettle Jeff , Hogg Richard A. , Childs David T. D. , Taylor Richard J. E.
Published: November 2023

We report the small-signal characterization of a PCSEL device, extracting damping factors and modulation efficiencies, and demonstrating -3 dB modulation bandwidths of up to 4.26 GHz. Based on modelling we show that, by reducing the device width and improving the active region design for high-speed modulation, direct modulation frequencies in excess of 50 GHz are achievable.
Characterization of nano-silica vegetable grease with diffusing wave spectroscopy DWS and Raman spectroscopy
Authors: Drabik Jolanta , Kozdrach Rafal , Szczerek Marian
Published: November 2023

The diffusing wave spectroscopy (DWS) method made it possible to identify changes in the dynamics of the free movement of particles in the grease under the influence of temperature, which changed the viscoelastic properties of the grease. Changes in the parameters determined by DWS method influenced changes in the chemical structure, which was confirmed by Raman spectroscopy, determining the integral intensity of the unsaturated to saturated bond bands found in the grease. The article presents the results of the influence of temperature on changes in the viscoelastic states of vegetable grease evaluated on the basis of properties determined by DWS (diffusing wave spectroscopy). The following parameters were used to evaluate the viscoelastic states: the intensity correlation function (ICF), the correlation function of mean square displacement (MSD), the elastic modulus G′ and the viscosity modulus G″. A significant effect of temperature on changes in the microstructure of vegetable grease was observed, which was reflected in the viscoelastic parameters. The dynamics of the free movement of molecules in the grease was changed, which affected the elasticity of the system and the displacement of the G′ and G″ modules towards higher frequencies.
Distribution of sika deer (Cervus nippon) and the bioclimatic impact on their habitats in South Korea
Authors: Dhakal Thakur , Kim Tae-Su , Kim Seong-Hyeon , Tiwari Shraddha , Kim Jun-Young , Jang Gab-Sue , Lee Do-Hun
Published: November 2023

Invasive species and climate change are primary factors influencing biodiversity, and examining the behavior of invasive species is essential for effective conservation management. Here, we report the global distribution of the sika deer (Cervus nippon) based on locations reported in published literature (Google Scholar), the Global Biodiversity Information Facility (GBIF) database, and the International Union for Conservation of Nature report. We used the maximum entropy (Maxent) model to examine the impact of climate change on sika deer habitats in South Korea based on GBIF occurrence data and WorldClim bioclimatic variables. Habitat suitability analysis was performed using the Maxent model under Representative Concentration Pathways (RCPs) 4.5 and 8.5 (for predicted climatic conditions in both 2050 and 2070) to project the effects of different climate change scenarios on South Korean sika deer habitats. We identified that the sika deer is distributed in 39 countries worldwide. Due to climate change effects, South Korean sika deer habitats will decline by approximately 24.98% and 20.63% (under RCP 4.5) and by 50.51% and 57.35% (under RCP 8.5) by 2050 and 2070, respectively. Our findings shed light on sika deer ecology and provide reference data for future conservation management strategies and policy design.
DNA damage repair-related gene signature for identifying the immune status and predicting the prognosis of hepatocellular carcinoma
Authors: Lu Yongpan , Wang Sen , Chi Tingting , Zhao Yuli , Guo Huimin , Wang Haizheng , Feng Li
Published: November 2023

The heterogeneity of hepatocellular carcinoma (HCC) poses a challenge for accurate prognosis prediction. DNA damage repair genes (DDRGs) have an impact on a wide range of malignancies. However, the relevance of these genes in HCC prognosis has received little attention. In this study, we aimed to develop a prognostic signature to identify novel therapy options for HCC. We acquired mRNA expression profiles and clinical data for HCC patients from The Cancer Genome Atlas (TCGA) database. A polygenic prognostic model for HCC was constructed using selection operator Cox analysis and least absolute shrinkage. The model was validated using International Cancer Genome Consortium (ICGC) data. Overall survival (OS) between the high-risk and low-risk groups was compared using Kaplan‒Meier analysis. Independent predictors of OS were identified through both univariate and multivariate Cox analyses. To determine immune cell infiltration scores and activity in immune-related pathways, a single-sample gene set enrichment analysis was performed. The protein and mRNA expression levels of the prognostic genes between HCC and normal liver tissues were also examined by immunohistochemistry (IHC), immunofluorescence (IF) and quantitative real-time PCR (qRT-PCR). A novel ten-gene signature (CHD1L, HDAC1, KPNA2, MUTYH, PPP2R5B, NEIL3, POLR2L, RAD54B, RUVBL1 and SPP1) was established for HCC prognosis prediction. Patients in the high-risk group had worse OS than those in the low-risk group. Receiver operating characteristic curve analysis confirmed the predictive ability of this prognostic gene signature. Multivariate Cox analysis showed that the risk score was an independent predictor of OS. Functional analysis revealed a strong association with cell cycle and antigen binding pathways, and the risk score was highly correlated with tumor grade, tumor stage, and types of immune infiltrate. High expression levels of the prognostic genes were significantly correlated with increased sensitivity of cancer cells to antitumor drugs. IHC, IF and qRT-PCR all indicated that the prognostic genes were highly expressed in HCC relative to normal liver tissue, consistent with the results of bioinformatics analysis. Ten DDRGs were utilized to create a new signature for identifying the immunological state of HCC and predicting prognosis. In addition, blocking these genes could represent a promising treatment.
Williams–Beuren syndrome shapes the gut microbiota metaproteome
Authors: Marzano Valeria , Levi Mortera Stefano , Vernocchi Pamela , Del Chierico Federica , Marangelo Chiara , Guarrasi Valerio , Gardini Simone , Dentici Maria Lisa , Capolino Rossella , Digilio Maria Cristina , Di Donato Maddalena , Spasari Iolanda , Abreu Maria Teresa , Dallapiccola Bruno , Putignani Lorenza
Published: November 2023

Williams–Beuren syndrome (WBS) is a rare genetic neurodevelopmental disorder with multi-systemic manifestations. The evidence that most subjects with WBS face gastrointestinal (GI) comorbidities, have prompted us to carry out a metaproteomic investigation of their gut microbiota (GM) profile compared to age-matched healthy subjects (CTRLs). Metaproteomic analysis was carried out on fecal samples collected from 41 individuals with WBS, and compared with samples from 45 CTRLs. Stool were extracted for high yield in bacterial protein group (PG) content, trypsin-digested and analysed by nanoLiquid Chromatography-Mass Spectrometry. Label free quantification, taxonomic assignment by the lowest common ancestor (LCA) algorithm and functional annotations by COG and KEGG databases were performed. Data were statistically interpreted by multivariate and univariate analyses. A WBS GM functional dissimilarity respect to CTRLs, regardless age distribution, was reported. The alterations in function of WBSs GM was primarily based on bacterial pathways linked to carbohydrate transport and metabolism and energy production. Influence of diet, obesity, and GI symptoms was assessed, highlighting changes in GM biochemical patterns, according to WBS subsets’ stratification. The LCA-derived ecology unveiled WBS-related functionally active bacterial signatures: Bacteroidetes related to over-expressed PGs, and Firmicutes, specifically the specie Faecalibacterium prausnitzii, linked to under-expressed PGs, suggesting a depletion of beneficial bacteria. These new evidences on WBS gut dysbiosis may offer novel targets for tailored interventions.
Wolbachia dominance influences the Culex quinquefasciatus microbiota
Authors: Flores Guillermo A. M. , Lopez Rocio P. , Cerrudo Carolina S. , Perotti M. Alejandra , Consolo V. Fabiana , Berón Corina M.
Published: November 2023

Microorganisms present in mosquitoes and their interactions are key factors affecting insect development. Among them, Wolbachia is closely associated with the host and affects several fitness parameters. In this study, the bacterial and fungal microbiota from two laboratory Culex quinquefasciatus isolines (wild type and tetracycline-cured) were characterized by metagenome amplicon sequencing of the ITS2 and 16S rRNA genes at different developmental stages and feeding conditions. We identified 572 bacterial and 61 fungal OTUs. Both isolines presented variable bacterial communities and different trends in the distribution of diversity among the groups. The lowest bacterial richness was detected in sugar-fed adults of the cured isoline, whereas fungal richness was highly reduced in blood-fed mosquitoes. Beta diversity analysis indicated that isolines are an important factor in the differentiation of mosquito bacterial communities. Considering composition, Penicillium was the dominant fungal genus, whereas Wolbachia dominance was inversely related to that of Enterobacteria (mainly Thorsellia and Serratia). This study provides a more complete overview of the mosquito microbiome, emphasizing specific highly abundant components that should be considered in microorganism manipulation approaches to control vector-borne diseases.
Wavelet scattering transform application in classification of retinal abnormalities using OCT images
Authors: Baharlouei Zahra , Rabbani Hossein , Plonka Gerlind
Published: November 2023

To assist ophthalmologists in diagnosing retinal abnormalities, Computer Aided Diagnosis has played a significant role. In this paper, a particular Convolutional Neural Network based on Wavelet Scattering Transform (WST) is used to detect one to four retinal abnormalities from Optical Coherence Tomography (OCT) images. Predefined wavelet filters in this network decrease the computation complexity and processing time compared to deep learning methods. We use two layers of the WST network to obtain a direct and efficient model. WST generates a sparse representation of the images which is translation-invariant and stable concerning local deformations. Next, a Principal Component Analysis classifies the extracted features. We evaluate the model using four publicly available datasets to have a comprehensive comparison with the literature. The accuracies of classifying the OCT images of the OCTID dataset into two and five classes were$$100\%$$100%and$$82.5\%$$82.5%, respectively. We achieved an accuracy of$$96.6\%$$96.6%in detecting Diabetic Macular Edema from Normal ones using the TOPCON device-based dataset. Heidelberg and Duke datasets contain DME, Age-related Macular Degeneration, and Normal classes, in which we achieved accuracy of$$97.1\%$$97.1%and$$94.4\%$$94.4%, respectively. A comparison of our results with the state-of-the-art models shows that our model outperforms these models for some assessments or achieves nearly the best results reported so far while having a much smaller computational complexity.
Cross-cultural validation of the COVID-19 peritraumatic distress index (CPDI) among Spanish and Peruvian populations
Authors: Böttcher Fabian , Pedraz-Petrozzi Bruno , Lamadé Eva Kathrin , Jimenez Maria Pilar , Rieker Jennifer , Reales José Manuel , Arevalo-Flores Martin , Anculle-Arauco Víctor , Krüger-Malpartida Hever , Ballesteros Soledad
Published: November 2023

The COVID-19 pandemic has had a significant psychological impact worldwide. The COVID-19 Peritraumatic Distress Index (CPDI) is widely used to assess psychological stress during the COVID-19 pandemic. Although CPDI has been validated in Peru and Spain, no cross-cultural validation studies have been conducted. As an exploratory aim, differences in CPDI factorial scores between the most prevalent medical conditions in the two samples (arterial hypertension, respiratory diseases and anxious-depressive disorders) from a general population of Peru and Spain were investigated. We conducted secondary data analysis with data from Peru and Spain to validate the CPDI in a cross-cultural context. Exploratory factor analysis (EFA) and multigroup confirmatory factor analysis (MGCFA) were performed to evaluate the factor structure and measurement invariance of the CPDI across cultural contexts. Concerning the exploratory analysis, we performed a U-Mann–Whitney test to evaluate differences in the factorial scores in the two samples. This study revealed a two-factor solution (stress and rumination/information) for the CPDI that included 21 of the 24 original items, and consistent with previous studies. The MGCFA demonstrated measurement invariance across cultural contexts (scalar invariance), indicating that the CPDI construct has the same meaning across both groups, regardless of cultural context and language variations of Spanish. Patients with anxious-depressive disorders showed higher CPDI factorial scores for both factors, whereas patients with respiratory diseases were only associated with the stress factor. This study provides evidence for the cross-cultural validity of the CPDI, highlighting its utility as a reliable instrument for assessing psychological stress in the context of COVID-19 across different cultures. These findings have important implications for developing and validating measures to assess psychological distress in different cultural contexts.
Machine learning-based prediction models for parathyroid carcinoma using pre-surgery cognitive function and clinical features
Authors: Wang Yuting , Wei Bojun , Zhao Teng , Shen Hong , Liu Xing , Wang Jiacheng , Wang Qian , Shen Rongfang , Feng Dalin
Published: November 2023

Patients with parathyroid carcinoma (PC) are often diagnosed postoperatively, due to incomplete resection during the initial surgery, resulting in poor outcomes. The aim of our study was to investigate the pre-surgery indicators of PC and try to develop a predictive model for PC utilizing machine learning. Evaluation of pre-surgery neuropsychological function and confirmation of pathology were carried out in 133 patients with primary hyperparathyroidism in Beijing Chaoyang Hospital from December 2019 to January 2023. Patients were randomly divided into a training cohort (n = 93) and a validating cohort (n = 40). Analysis of the clinical dataset, two machine learning including the extreme gradient boosting (XGBoost) and the least absolute shrinkage and selection operator (LASSO) regression were utilized to develop the prediction model for PC. Logistic regression analysis was also conducted for comparison. Significant differences in elevated parathyroid hormone and decreased serum phosphorus in PC compared to (BP). The lower score of MMSE and MOCA was observed in PC and a cutoff of MMSE < 24 was the optimal threshold to stratify PC from BP (area under the curve AUC 0.699 vs 0.625). The predicted probability of PC by machine learning was similar to the observed probability in the test set, whereas the logistic model tended to overpredict the possibility of PC. The XGBoost model attained a higher AUC than the logistic algorithms and LASSO models. (0.835 vs 0.683 vs 0.607). Preoperative cognitive function may be a probable predictor for PC. The cognitive function-based prediction model based on the XGBoost algorithm outperformed LASSO and logistic regression, providing valuable preoperative assistance to surgeons in clinical decision-making for patients suspected PC.
Expression of G protein-coupled receptor GPR19 in normal and neoplastic human tissues
Authors: Gerlach Lorena , Beyer Anna-Sophia Liselott , Kaemmerer Daniel , Sänger Jörg , Evert Katja , Schulz Stefan , Lupp Amelie
Published: November 2023

Little is known about the expression of the orphan G protein-coupled receptor GPR19 at the protein level. Therefore, we developed a rabbit antibody, targeting human GPR19. After verification of the antibody specificity using GPR19-expressing cell lines and a GPR19-specific siRNA, the antibody was used for immunohistochemical staining of a variety of formalin-fixed, paraffin-embedded normal and neoplastic human tissue samples. In normal tissues, GPR19 expression was detected in a distinct cell population within the cortex, in single cells of the pancreatic islets, in intestinal ganglia, gastric chief cells, and in endocrine cells of the bronchial tract, the gastrointestinal tract, and the prostate. Among the 30 different tumour entities investigated, strong GPR19 expression was found in adenocarcinomas, typical and atypical carcinoids of the lung, and small cell lung cancer. To a lesser extent, the receptor was also present in large cell neuroendocrine carcinomas of the lung, medullary thyroid carcinomas, parathyroid adenomas, pheochromocytomas, and a subpopulation of pancreatic neuroendocrine neoplasms. In lung tumours, a negative correlation with the expression of the proliferation marker Ki-67 and a positive interrelationship with patient survival was observed. Overall, our results indicate that in adenocarcinomas and neuroendocrine tumours of the lung GPR19 may serve as a suitable diagnostic or therapeutic target.
Nocturnal activity as a useful indicator of adaptability of dogs in an animal shelter and after subsequent adoption
Authors: van der Laan Janneke Elisabeth , Vinke Claudia Maureen , Arndt Saskia Stefanie
Published: November 2023

Dogs in shelters are faced with the challenge of adapting to a kennel after relinquishment and to a novel home after adoption. To measure adaptability of dogs, more feasible behavioural and physiological parameters need to be validated in different contexts. To evaluate nocturnal activity as an indicator of adaptability, we compared nocturnal activity, urinary cortisol:creatinine ratio (UCCR), and body weight changes of sheltered dogs the first period after intake in the shelter and after adoption. Nocturnal activity and UCCRs were significantly lower the first days after adoption than in the shelter. After adoption, nocturnal activity was significantly lower on night 2 than night 1, but not on night 3 and 4, suggesting a form of ‘rebound of resting’ during night 2 in the new home. UCCRs significantly decreased 7 days after adoption. Body weight decreased in the shelter but increased again after adoption. These findings suggest that overall, dogs rest better in a novel home than in a novel shelter but, in both contexts, some form of adaptation takes place. Nocturnal activity measured by an accelerometer differentiated well between shelter and home environments, and corresponded to UCCR responses, which supports usefulness of the method to monitor canine adaptability to novel environments.
Numerical assessment of irreversibility in radiated Sutterby nanofluid flow with activation energy and Darcy Forchheimer
Authors: ur Rahman Mujeeb , Haq Fazal , Ijaz Khan M. , Awwad Fuad A. , Ismail Emad A. A.
Published: November 2023

Entropy generation is a concept that is primarily associated with thermodynamics and engineering, and it plays a crucial role in understanding and optimizing various processes and systems. Applications of entropy generation can be seen in turbo machinery, reactors, chillers, desert coolers, vehicle engines, air conditioners, heat transfer devices and combustion. Due to industrial applications entropy generation has gained attention of researchers. Owing such applications, current communication aims to model and analyzed the irreversibility in Sutterby nanoliquid flow by stretched cylinder. Momentum equation is reported by considering porosity, Darcy Forchheimer and magnetic field. While in energy equation radiation and Joule heating effects are accounted. Activation energy impact is accounted in the modeling of concentration equation. Thermodynamics second law is utilized for physical description of irreversibility analysis. Through similarity transformations dimensional equations representing flow are transformed to dimensionless ones. Numerical solution for ordinary system is obtained via Runge–Kutta-Fehlberg scheme in Mathematica platform through NDsolve code. Influence of prominent variables on velocity, entropy, temperature, Bejan number and concentration are graphically analyzed. Coefficient of skin friction, gradient of temperature and Sherwood number are numerically analyzed. The obtained results show that velocity field decreases through higher porosity and Forchheimer variables. Velocity and temperature curves shows an opposite trend versus magnetic parameter. A decay in concentration distribution is noticed through larger Schmidt number. Entropy generation amplifies against magnetic parameter and Brinkman number.
Comprehensive analysis of heterojunction compatibility of various perovskite solar cells with promising charge transport materials
Authors: Jan Shayan Tariq , Noman Muhammad
Published: November 2023

The allure of perovskite solar cells (PSCs), which has captivated the interest of researchers, lies in their versatility to incorporate a wide range of materials within the cell’s structure. The compatibility of these materials plays a vital role in the performance enhancement of the PSC. In this study, multiple perovskite materials including FAPbI3, MAGeI3 and MASnI3 are numerically modelled along with the recently emerged kesterite (CBTS, CMTS, and CZTS) and zinc-based (ZnO and CdZnS) charge transport materials. To fully explore the potential of PSCs and comprehend the interplay among these materials, a total of 18 PSC structures are modeled from different material combinations. The impact of band gap, electron affinity, absorption, band alignment, band offset, electric field, recombination rate, thickness, defects, and work function were analyzed in detail through a systematic approach. The reasons for varying performance of different PSCs are also identified. Based on the simulated results, the most suitable charge transport materials are CdZnS/CMTS for FAPbI3 producing a power conversion efficiency (PCE) of 22.05%, ZnO/CZTS for MAGeI3 with PCE of 17.28% and ZnO/CBTS for MASnI3 with a PCE of 24.17%.
Lorlatinib and capmatinib in a ROS1-rearranged NSCLC with MET-driven resistance: tumor response and evolution
Authors: Schneider Jaime L. , Shaverdashvili Khvaramze , Mino-Kenudson Mari , Digumarthy Subba R. , Do Andrew , Liu Audrey , Gainor Justin F. , Lennerz Jochen K. , Burns Timothy F. , Lin Jessica J.
Published: November 2023

Acquired drug resistance remains a major problem across oncogene-addicted cancers. Elucidation of mechanisms of resistance can inform rational treatment strategies for patients relapsing on targeted therapies while offering insights into tumor evolution. Here, we report acquired MET amplification as a resistance driver in a ROS1-rearranged lung adenocarcinoma after sequential treatment with ROS1 inhibitors. Subsequent combination therapy with lorlatinib plus capmatinib, a MET-selective inhibitor, induced intracranial and extracranial tumor response. At relapse, sequencing of the resistant tumor revealed a MET D1246N mutation and loss of MET amplification. We performed integrated molecular analyses of serial tumor and plasma samples, unveiling dynamic alterations in the ROS1 fusion driver and MET bypass axis at genomic and protein levels and the emergence of polyclonal resistance. This case illustrates the complexity of longitudinal tumor evolution with sequential targeted therapies, highlighting challenges embedded in the current precision oncology paradigm and the importance of developing approaches that prevent resistance.
Disrupted network interactions serve as a neural marker of dyslexia
Authors: Turker Sabrina , Kuhnke Philipp , Jiang Zhizhao , Hartwigsen Gesa
Published: November 2023

Dyslexia, a frequent learning disorder, is characterized by severe impairments in reading and writing and hypoactivation in reading regions in the left hemisphere. Despite decades of research, it remains unclear to date if observed behavioural deficits are caused by aberrant network interactions during reading and whether differences in functional activation and connectivity are directly related to reading performance. Here we provide a comprehensive characterization of reading-related brain connectivity in adults with and without dyslexia. We find disrupted functional coupling between hypoactive reading regions, especially between the left temporo-parietal and occipito-temporal cortices, and an extensive functional disruption of the right cerebellum in adults with dyslexia. Network analyses suggest that individuals with dyslexia process written stimuli via a dorsal decoding route and show stronger reading-related interaction with the right cerebellum. Moreover, increased connectivity within networks is linked to worse reading performance in dyslexia. Collectively, our results provide strong evidence for aberrant task-related connectivity as a neural marker for dyslexia that directly impacts behavioural performance. The observed differences in activation and connectivity suggest that one effective way to alleviate reading problems in dyslexia is through modulating interactions within the reading network with neurostimulation methods.
Half-life of the nuclear cosmochronometer 176Lu measured with a windowless 4π solid angle scintillation detector
Authors: Hayakawa Takehito , Shizuma Toshiyuki , Iizuka Tsuyoshi
Published: November 2023

The 176Lu-176Hf nuclear decay is a powerful tool to measure the age of astrophysical and geological events and has been used as a “cosmochronometer”. However, the half-life values of 176Lu measured with various experiments differ significantly. Furthermore, the half-life values evaluated from Lu-Hf isochrons in meteorites and terrestrial rocks with known ages show two different values. Here we report half-life measurements using a method that is almost independent of various uncertainties. To the best of our knowledge this is the most accurate value of 176Lu half-life. We measure the total energy released from 176Lu decay using a windowless 4π solid angle detector based upon bismuth germanate (BGO) scintillation crystals, where a natural Lu sample is located inside of the detector. The measured half-life of (3.719 ± 0.007) × 1010 yr corresponding to a decay constant of (1.864 ± 0.003) × 10−11 yr−1 is consistent with that obtained from the analysis of terrestrial rocks within the uncertainty.