bluuebunny/crossref_metadata_2025 huggingface dataset:
Dual domain recognition determines SARS-CoV-2 PLpro selectivity for human ISG15 and K48-linked di-ubiquitin
Authors: Wydorski Pawel M. , Osipiuk Jerzy , Lanham Benjamin T. , Tesar Christine , Endres Michael , Engle Elizabeth , Jedrzejczak Robert , Mullapudi Vishruth , Michalska Karolina , Fidelis Krzysztof , Fushman David , Joachimiak Andrzej , Joachimiak Lukasz A.
Published: April 2023

The Papain-like protease (PLpro) is a domain of a multi-functional, non-structural protein 3 of coronaviruses. PLpro cleaves viral polyproteins and posttranslational conjugates with poly-ubiquitin and protective ISG15, composed of two ubiquitin-like (UBL) domains. Across coronaviruses, PLpro showed divergent selectivity for recognition and cleavage of posttranslational conjugates despite sequence conservation. We show that SARS-CoV-2 PLpro binds human ISG15 and K48-linked di-ubiquitin (K48-Ub2) with nanomolar affinity and detect alternate weaker-binding modes. Crystal structures of untethered PLpro complexes with ISG15 and K48-Ub2 combined with solution NMR and cross-linking mass spectrometry revealed how the two domains of ISG15 or K48-Ub2 are differently utilized in interactions with PLpro. Analysis of protein interface energetics predicted differential binding stabilities of the two UBL/Ub domains that were validated experimentally. We emphasize how substrate recognition can be tuned to cleave specifically ISG15 or K48-Ub2 modifications while retaining capacity to cleave mono-Ub conjugates. These results highlight alternative druggable surfaces that would inhibit PLpro function.
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies
Authors: Ruffolo Jeffrey A. , Chu Lee-Shin , Mahajan Sai Pooja , Gray Jeffrey J.
Published: April 2023

Antibodies have the capacity to bind a diverse set of antigens, and they have become critical therapeutics and diagnostic molecules. The binding of antibodies is facilitated by a set of six hypervariable loops that are diversified through genetic recombination and mutation. Even with recent advances, accurate structural prediction of these loops remains a challenge. Here, we present IgFold, a fast deep learning method for antibody structure prediction. IgFold consists of a pre-trained language model trained on 558 million natural antibody sequences followed by graph networks that directly predict backbone atom coordinates. IgFold predicts structures of similar or better quality than alternative methods (including AlphaFold) in significantly less time (under 25 s). Accurate structure prediction on this timescale makes possible avenues of investigation that were previously infeasible. As a demonstration of IgFold’s capabilities, we predicted structures for 1.4 million paired antibody sequences, providing structural insights to 500-fold more antibodies than have experimentally determined structures.
Protein stabilization of ITF2 by NF-κB prevents colitis-associated cancer development
Authors: Lee Mingyu , Kim Yi-Sook , Lim Suha , Shin Seung-Hyun , Kim Iljin , Kim Jiyoung , Choi Min , Kim Jung Ho , Koh Seong-Joon , Park Jong-Wan , Shin Hyun-Woo
Published: April 2023

Chronic colonic inflammation is a feature of cancer and is strongly associated with tumorigenesis, but its underlying molecular mechanisms remain poorly understood. Inflammatory conditions increased ITF2 and p65 expression both ex vivo and in vivo, and ITF2 and p65 showed positive correlations. p65 overexpression stabilized ITF2 protein levels by interfering with the binding of Parkin to ITF2. More specifically, the C-terminus of p65 binds to the N-terminus of ITF2 and inhibits ubiquitination, thereby promoting ITF2 stabilization. Parkin acts as a E3 ubiquitin ligase for ITF2 ubiquitination. Intestinal epithelial-specific deletion of ITF2 facilitated nuclear translocation of p65 and thus increased colitis-associated cancer tumorigenesis, which was mediated by Azoxymethane/Dextran sulfate sodium or dextran sulfate sodium. Upregulated ITF2 expression was lost in carcinoma tissues of colitis-associated cancer patients, whereas p65 expression much more increased in both dysplastic and carcinoma regions. Therefore, these findings indicate a critical role for ITF2 in the repression of colitis-associated cancer progression and ITF2 would be an attractive target against inflammatory diseases including colitis-associated cancer.
3D printing of unsupported multi-scale and large-span ceramic via near-infrared assisted direct ink writing
Authors: Zhao Yongqin , Zhu Junzhe , He Wangyan , Liu Yu , Sang Xinxin , Liu Ren
Published: April 2023

In the three-dimensional printing process of ceramic with low-angle structures, additional supporting structures are usually employed to avoid collapse of overhanging parts. However, the extra supporting structures not only affect printing efficiency, but the problems caused by their removal are also a matter of concern. Herein, we present a ceramic printing method, which can realize printing of unsupported multi-scale and large-span ceramics through the combination of direct ink writing and near-infrared induced up-conversion particles-assisted photopolymerization. This printing technology enables in-situ curing of multi-scale filaments with diameters ranging from 410 µm to 3.50 mm, and ceramic structures of torsion spring, three-dimensional bending and cantilever beam were successfully constructed through unsupported printing. This method will bring more innovation to the unsupported 3D manufacturing of complex shape ceramics.
Solvent-derived defects suppress adsorption in MOF-74
Authors: Fu Yao , Yao Yifeng , Forse Alexander C. , Li Jianhua , Mochizuki Kenji , Long Jeffrey R. , Reimer Jeffrey A. , De Paëpe Gaël , Kong Xueqian
Published: April 2023

Defects in metal-organic frameworks (MOFs) have great impact on their nano-scale structure and physiochemical properties. However, isolated defects are easily concealed when the frameworks are interrogated by typical characterization methods. In this work, we unveil the presence of solvent-derived formate defects in MOF-74, an important class of MOFs with open metal sites. With multi-dimensional solid-state nuclear magnetic resonance (NMR) investigations, we uncover the ligand substitution role of formate and its chemical origin from decomposed N,N-dimethylformamide (DMF) solvent. The placement and coordination structure of formate defects are determined by 13C NMR and density functional theory (DFT) calculations. The extra metal-oxygen bonds with formates partially eliminate open metal sites and lead to a quantitative decrease of N2 and CO2 adsorption with respect to the defect concentration. In-situ NMR analysis and molecular simulations of CO2 dynamics elaborate the adsorption mechanisms in defective MOF-74. Our study establishes comprehensive strategies to search, elucidate and manipulate defects in MOFs.
Colonization with ubiquitous protist Blastocystis ST1 ameliorates DSS-induced colitis and promotes beneficial microbiota and immune outcomes
Authors: Deng Lei , Wojciech Lukasz , Png Chin Wen , Kioh Yan Qin Dorinda , Ng Geok Choo , Chan Eric Chun Yong , Zhang Yongliang , Gascoigne Nicholas R. J. , Tan Kevin Shyong Wei
Published: April 2023

Blastocystisis a species complex that exhibits extensive genetic diversity, evidenced by its classification into several genetically distinct subtypes (ST). Although several studies have shown the relationships between a specific subtype and gut microbiota, there is no study to show the effect of the ubiquitousBlastocystisST1 on the gut microbiota and host health. Here, we show thatBlastocystisST1 colonization increased the proportion of beneficial bacteriaAlloprevotellaandAkkermansia, and induced Th2 and Treg cell responses in normal healthy mice. ST1-colonized mice showed decreases in the severity of DSS-induced colitis when compared to non-colonized mice. Furthermore, mice transplanted with ST1-altered gut microbiota were refractory to dextran sulfate sodium (DSS)-induced colitis via induction of Treg cells and elevated short-chain fat acid (SCFA) production. Our results suggest that colonization withBlastocystisST1, one of the most common subtypes in humans, exerts beneficial effects on host health through modulating the gut microbiota and adaptive immune responses.
Immunization with a Trypanosoma cruzi cyclophilin-19 deletion mutant protects against acute Chagas disease in mice
Authors: Jha Bijay Kumar , Varikuti Sanjay , Verma Chaitenya , Shivahare Rahul , Bishop Nicholas , Dos Santos Gregory P. , McDonald Jacquelyn , Sur Aakash , Myler Peter J. , Schenkman Sergio , Satoskar Abhay R. , McGwire Bradford S.
Published: April 2023

Human infection with the protozoan parasite Trypanosoma cruzi causes Chagas disease for which there are no prophylactic vaccines. Cyclophilin 19 is a secreted cis-trans peptidyl isomerase expressed in all life stages of Trypanosoma cruzi. This protein in the insect stage leads to the inactivation of insect anti-parasitic peptides and parasite transformation whereas in the intracellular amastigotes it participates in generating ROS promoting the growth of parasites. We have generated a parasite mutant with depleted expression of Cyp19 by removal of 2 of 3 genes encoding this protein using double allelic homologous recombination. The mutant parasite line failed to replicate when inoculated into host cells in vitro or in mice indicating that Cyp19 is critical for infectivity. The mutant parasite line also fails to replicate in or cause clinical disease in immuno-deficient mice further validating their lack of virulence. Repeated inoculation of mutant parasites into immuno-competent mice elicits parasite-specific trypanolytic antibodies and a Th-1 biased immune response and challenge of mutant immunized mice with virulent wild-type parasites is 100% effective at preventing death from acute disease. These results suggest that parasite Cyp19 may be candidate for small molecule drug targeting and that the mutant parasite line may warrant further immunization studies for prevention of Chagas disease.
A comprehensive review on LDH-based catalysts to activate persulfates for the degradation of organic pollutants
Authors: Abd El-Monaem Eman M. , Elshishini Hala M. , Bakr Sara S. , El-Aqapa Hisham G. , Hosny Mohamed , Andaluri Gangadhar , El-Subruiti Gehan M. , Omer Ahmed M. , Eltaweil Abdelazeem S.
Published: April 2023

Degradation of organic contaminants into less toxic substances is the best option to remove these compounds rather than using conventional techniques. The sulfate radical-based-advanced oxidation process is an effective strategy that degrades organic contaminants by activating peroxymonosulfate (PMS). Such a strategy generates singlet oxygen (1O2), hydroxyl ($$^ \bullet \!{{{\mathrm{OH}}}}$$∙OH), and sulfate ($${{{\mathrm{SO}}}}_4^{ \bullet\! - }$$SO4∙−) radicals.$${{{\mathrm{SO}}}}_4^{ \bullet \!- }$$SO4∙−is distinguished by its high oxidation selectivity and activity toward the degradation of organic contaminates compared to other radicals. Various catalysts are employed in PMS activation including layered doubled hydroxides (LDHs), which are characterized by their facile synthesis and high catalytic activity. This review article is the first attempt to compile the recent progress in the degradation of common organic pollutants including aromatic compounds, pharmaceutical residues, and dyes via the PMS activation using LDH-based catalysts. The degradation pathways, reaction parameters’ influence, stability of LDHs, and comparisons between different LDH-based catalysts are investigated in this work.
Complete Global Total Electron Content Map Dataset based on a Video Imputation Algorithm VISTA
Authors: Sun Hu , Chen Yang , Zou Shasha , Ren Jiaen , Chang Yurui , Wang Zihan , Coster Anthea
Published: April 2023

Ionospheric total electron content (TEC) derived from multi-frequency Global Navigation Satellite System (GNSS) signals and the relevant products have become one of the most utilized parameters in the space weather and ionospheric research community. However, there are a couple of challenges in using the global TEC map data including large data gaps over oceans and the potential of losing meso-scale ionospheric structures when applying traditional reconstruction and smoothing algorithms. In this paper, we describe and release a global TEC map database, constructed and completed based on the Madrigal TEC database with a novel video imputation algorithm called VISTA (Video Imputation with SoftImpute, Temporal smoothing and Auxiliary data). The complete TEC maps reveal important large-scale TEC structures and preserve the observed meso-scale structures. Basic ideas and the pipeline of the video imputation algorithm are introduced briefly, followed by discussions on the computational costs and fine tuning of the adopted algorithm. Discussions on potential usages of the complete TEC database are given, together with a concrete example of applying this database.
Blast loads and variability on cylindrical shells under different charge orientations
Authors: Yin Fei , Zhi Xudong , Fan Feng , Wei Wuchen , Zheng Dianshuang
Published: April 2023

Cylindrical shells are widely used in public buildings and military protection fields, and it has a high risk of terrorist attacks and military attacks, it is of great social benefit to carry out the anti-blast design of cylindrical shells, which needs to consider building shape and the shape of blast waves. In this paper, cylindrical charges in five directions were detonated on the outer ground of the scaled cylindrical shell, blast loads of the cylindrical shell were measured and blast waves were photographed. The variation of blast load is analyzed by combining the test and simulation results, the difference in peak overpressure of the blast waves on the end face between five orientations is nearly twice. The blast loads in the axial direction of cylindrical charges have a secondary peak phenomenon, and the blast loads between the axial direction and radial direction of cylindrical charges change abruptly at a specific angle. The experimental and simulation methods provide a reference for establishing a blast load database of typical buildings.
Assessment of experimental OpenCV tracking algorithms for ultrasound videos
Authors: Levin A. A. , Klimov D. D. , Nechunaev A. A. , Prokhorenko L. S. , Mishchenkov D. S. , Nosova A. G. , Astakhov D. A. , Poduraev Y. V. , Panchenkov D. N.
Published: April 2023

This study aims to compare the tracking algorithms provided by the OpenCV library to use on ultrasound video. Despite the widespread application of this computer vision library, few works describe the attempts to use it to track the movement of liver tumors on ultrasound video. Movements of the neoplasms caused by the patient`s breath interfere with the positioning of the instruments during the process of biopsy and radio-frequency ablation. The main hypothesis of the experiment was that tracking neoplasms and correcting the position of the manipulator in case of using robotic-assisted surgery will allow positioning the instruments more precisely. Another goal of the experiment was to check if it is possible to ensure real-time tracking with at least 25 processed frames per second for standard definition video. OpenCV version 4.5.0 was used with 7 tracking algorithms from the extra modules package. They are: Boosting, CSRT, KCF, MedianFlow, MIL, MOSSE, TLD. More than 5600 frames of standard definition were processed during the experiment. Analysis of the results shows that two algorithms—CSRT and KCF—could solve the problem of tumor tracking. They lead the test with 70% and more of Intersection over Union and more than 85% successful searches. They could also be used in real-time processing with an average processing speed of up to frames per second in CSRT and 100 + frames per second for KCF. Tracking results reach the average deviation between centers of neoplasms to 2 mm and maximum deviation less than 5 mm. This experiment also shows that no frames made CSRT and KCF algorithms fail simultaneously. So, the hypothesis for future work is combining these algorithms to work together, with one of them—CSRT—as support for the KCF tracker on the rarely failed frames.
Construction and analysis of a conjunctive diagnostic model of HNSCC with random forest and artificial neural network
Authors: Luo Yao , Zhou Liu-qing , Yang Fan , Chen Jing-cai , Chen Jian-jun , Wang Yan-jun
Published: April 2023

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous tumor that is highly aggressive and ranks fifth among the most common cancers worldwide. Although, the researches that attempted to construct a diagnostic model were deficient in HNSCC. Currently, the gold standard for diagnosing head and neck tumors is pathology, but this requires a traumatic biopsy. There is still a lack of a noninvasive test for such a high—incidence tumor. In order to screen genetic markers and construct diagnostic model, the methods of random forest (RF) and artificial neural network (ANN) were utilized. The data of HNSCC gene expression was accessed from Gene Expression Omnibus (GEO) database; we selected three datasets totally, and we combined 2 datasets (GSE6631 and GSE55547) for screening differentially expressed genes (DEGs) and chose another dataset (GSE13399) for validation. Firstly, the 6 DEGs (CRISP3, SPINK5, KRT4, MMP1, MAL, SPP1) were screened by RF. Subsequently, ANN was applied to calculate the weights of 6 genes. Besides, we created a diagnostic model and nominated it as neuralHNSCC, and the performance of neuralHNSCC by area under curve (AUC) was verified using another dataset. Our model achieved an AUC of 0.998 in the training cohort, and 0.734 in the validation cohort. Furthermore, we used the Cell-type Identification using Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm to investigate the difference in immune cell infiltration between HNSCC and normal tissues initially. The selected 6 DEGs and the constructed novel diagnostic model of HNSCC would make contributions to the diagnosis.
Tuning electronic and magnetic properties through disorder in V2O5 nanoparticles
Authors: Correal Sergio , Hernández-Gómez Daniel , Esquivel Andrea Steffania , Cardona-Rodríguez Alexander , Reiber Andreas , Hernandez Yenny , González-Hernández Rafael , Ramírez Juan Gabriel
Published: April 2023

We report on the synthesis and characterization of V2O5 nanoparticles grown using a sol–gel method at different calcination temperatures. We observed a surprising reduction in the optical band gap from 2.20 to 1.18 eV with increasing calcination temperature from 400 to 500 °C. Raman and X-Ray diffraction measurements indicated slight changes in the lattice parameters induced by the growth process. However, density functional theory calculations of the Rietveld-refined and pristine structures revealed that the observed optical gap reduction could not be explained by structural changes alone. By introducing oxygen vacancies to the refined structures, we could reproduce the reduction of the band gap. Our calculations also showed that the inclusion of oxygen vacancies at the vanadyl position creates a spin-polarized interband state that reduces the electronic band gap and promotes a magnetic response due to unpaired electrons. This prediction was confirmed by our magnetometry measurements, which exhibited a ferromagnetic-like behavior. Our findings suggest that oxygen vacancies play a crucial role in band gap reduction and the promotion of a ferromagnetic-like response in an otherwise paramagnetic material. This provides a promising route to engineer novel devices.
The increase in intensity and frequency of surface air temperature extremes throughout the western South Atlantic coast
Authors: Sanches Fábio H. C. , Martins Fernando R. , Conti William R. P. , Christofoletti Ronaldo A.
Published: April 2023

The climate is changing. At this stage, it is important to specify an ‘extreme’ climate and identify patterns that indicate its potential harm worldwide, including the coastal zones. Herein, we considered extremes based on the “Peaks Over Threshold” method from the “Extreme Value Theory”. We looked after geographical patterns of surface air temperature (SAT) extremes (e.g., Tmax, Tmin, daily temperature range (DTR), and inter-daily temperature range) over the last 40 years throughout the Brazilian coast. Overall, we found a trend increase in intensity and frequency, but the duration was barely affected. The latitudinal pattern of extremes and the temperatures considered extremes followed the settled perception that areas in higher latitudes will be more affected by the extent of warming. Additionally, the seasonal pattern of DTR demonstrated to be a good approach to make inferences about air mass changes, but joint analyses on extremes with other atmospheric variables are desirable. Given the potential effects of extreme climates on society and natural systems over the world, our study highlights the urge for action to mitigate the effects of the increase in SAT in coastal zones.
Deep generative model super-resolves spatially correlated multiregional climate data
Authors: Oyama Norihiro , Ishizaki Noriko N. , Koide Satoshi , Yoshida Hiroaki
Published: April 2023

Super-resolving the coarse outputs of global climate simulations, termed downscaling, is crucial in making political and social decisions on systems requiring long-term climate change projections. Existing fast super-resolution techniques, however, have yet to preserve the spatially correlated nature of climatological data, which is particularly important when we address systems with spatial expanse, such as the development of transportation infrastructure. Herein, we show an adversarial network-based machine learning enables us to correctly reconstruct the inter-regional spatial correlations in downscaling with high magnification of up to 50 while maintaining pixel-wise statistical consistency. Direct comparison with the measured meteorological data of temperature and precipitation distributions reveals that integrating climatologically important physical information improves the downscaling performance, which prompts us to call this approach $$\pi$$
π
SRGAN (Physics Informed Super-Resolution Generative Adversarial Network). The proposed method has a potential application to the inter-regionally consistent assessment of the climate change impact. Additionally, we present the outcomes of another variant of the deep generative model-based downscaling approach in which the low-resolution precipitation field is substituted with the pressure field, referred to as $$\psi$$
ψ
SRGAN (Precipitation Source Inaccessible SRGAN). Remarkably, this method demonstrates unexpectedly good downscaling performance for the precipitation field.
Prediction of 316 stainless steel low-cycle fatigue life based on machine learning
Authors: Duan Hongyan , Cao Mengjie , Liu Lin , Yue Shunqiang , He Hong , Zhao Yingjian , Zhang Zengwang , liu Yang
Published: April 2023

The low-cycle fatigue life of 316 stainless steel is a significant basis for safety assessment. Usually, many factors affect the low-cycle fatigue life of stainless steel, and the relationship between the influencing factors and fatigue life is complicated and nonlinear. Therefore, it is hard to predict fatigue life using the traditional empirical formula. Based on this, a machine learning algorithm is proposed. In this paper, based on the large amount of existing experimental data, machine learning methods are used to predict the low circumferential fatigue life of 316 stainless steel. The results show that the prediction accuracy of nu-SVR and ELM models is high and can meet engineering needs.
Predictive biosignature of major depressive disorder derived from physiological measurements of outpatients using machine learning
Authors: Ricka Nicolas , Pellegrin Gauthier , Fompeyrine Denis A. , Lahutte Bertrand , Geoffroy Pierre A.
Published: April 2023

Major Depressive Disorder (MDD) has heterogeneous manifestations, leading to difficulties in predicting the evolution of the disease and in patient's follow-up. We aimed to develop a machine learning algorithm that identifies a biosignature to provide a clinical score of depressive symptoms using individual physiological data. We performed a prospective, multicenter clinical trial where outpatients diagnosed with MDD were enrolled and wore a passive monitoring device constantly for 6 months. A total of 101 physiological measures related to physical activity, heart rate, heart rate variability, breathing rate, and sleep were acquired. For each patient, the algorithm was trained on daily physiological features over the first 3 months as well as corresponding standardized clinical evaluations performed at baseline and months 1, 2 and 3. The ability of the algorithm to predict the patient's clinical state was tested using the data from the remaining 3 months. The algorithm was composed of 3 interconnected steps: label detrending, feature selection, and a regression predicting the detrended labels from the selected features. Across our cohort, the algorithm predicted the daily mood status with 86% accuracy, outperforming the baseline prediction using MADRS alone. These findings suggest the existence of a predictive biosignature of depressive symptoms with at least 62 physiological features involved for each patient. Predicting clinical states through an objective biosignature could lead to a new categorization of MDD phenotypes.
ANGPTL4 is a potential driver of HCV-induced peripheral insulin resistance
Authors: Gomes Diana , Sobolewski Cyril , Conzelmann Stéphanie , Schaer Tifany , Lefai Etienne , Alfaiate Dulce , Tseligka Eirini D. , Goossens Nicolas , Tapparel Caroline , Negro Francesco , Foti Michelangelo , Clément Sophie
Published: April 2023

Chronic hepatitis C (CHC) is associated with the development of metabolic disorders, including both hepatic and extra-hepatic insulin resistance (IR). Here, we aimed at identifying liver-derived factor(s) potentially inducing peripheral IR and uncovering the mechanisms whereby HCV can regulate the action of these factors. We found ANGPTL4 (Angiopoietin Like 4) mRNA expression levels to positively correlate with HCV RNA (r = 0.46, p < 0.03) and HOMA-IR score (r = 0.51, p = 0.01) in liver biopsies of lean CHC patients. Moreover, we observed an upregulation of ANGPTL4 expression in two models recapitulating HCV-induced peripheral IR, i.e. mice expressing core protein of HCV genotype 3a (HCV-3a core) in hepatocytes and hepatoma cells transduced with HCV-3a core. Treatment of differentiated myocytes with recombinant ANGPTL4 reduced insulin-induced Akt-Ser473 phosphorylation. In contrast, conditioned medium from ANGPTL4-KO hepatoma cells prevented muscle cells from HCV-3a core induced IR. Treatment of HCV-3a core expressing HepG2 cells with PPARγ antagonist resulted in a decrease of HCV-core induced ANGPTL4 upregulation. Together, our data identified ANGPTL4 as a potential driver of HCV-induced IR and may provide working hypotheses aimed at understanding the pathogenesis of IR in the setting of other chronic liver disorders.
CEA dynamics for predicting response after anti-EGFR monoclonal antibody treatment in metastatic colorectal cancer
Authors: Kang Sora , Kim Sun Young , Hong Yong Sang , Kim Tae Won , Choi Ki Eun , Kim Min Jung , Kim Jeong Eun
Published: April 2023

Carcinoembryonic antigen (CEA) is the most widely used tumor marker in metastatic colorectal cancer (mCRC). However, its potential as a predictive marker of progression in mCRC during systemic chemotherapy, particularly in patients receiving monoclonal antibodies as a combination therapy, has remained of interest. Herein, we investigated whether CEA changes could predict disease progression and clinical outcomes in patients with mCRC cotreated with systemic chemotherapy and/or biologic agents. A total of 1261 patients with mCRC undergoing a first-line systemic treatment were included in this retrospective study. We analyzed the optimal cut-off value for CEA changes to predict progression at the first response evaluation by the treatment arm (chemotherapy alone, chemotherapy plus anti-vascular endothelial growth factor (VEGF) monoclonal antibody [mAb], and chemotherapy plus anti-epidermal growth factor receptor [EGFR] mAb). These cut-off values were then used to predict overall survival (OS) and progression-free survival (PFS). When stratified by their treatment arm, 891 (70.6%), 266 (21.0%), and 104 (8.2%) of the study patients were included in the chemotherapy alone-, anti-VEGF mAb, and anti-EGFR mAb groups, respectively. The optimal CEA cut-off values were 16.5% and 38.9% increase in the whole cohort and anti-EGFR mAb group, respectively, and these values showed high sensitivity and specificity for predicting disease progression. The patients in the entire population and anti-EGFR mAb group with CEA changes below these cut-off values showed significantly better OS and PFS outcomes compared those whose changes were above cut-off values. Among the patients with mCRC treated with anti-VEGF mAb, no associations were found between OS or PFS outcomes and CEA changes. CEA is potentially a good surrogate marker for predicting disease progression and survival outcomes in patients with mCRC receiving first-line systemic chemotherapy alone or chemotherapy with anti-EGFR mAb, whereas it is less effective in those treated with anti-VEGF mAb.
Efficient low temperature Monte Carlo sampling using quantum annealing
Authors: Sandt Roland , Spatschek Robert
Published: April 2023

Quantum annealing is an efficient technology to determine ground state configurations of discrete binary optimization problems, described through Ising Hamiltonians. Here we show that—at very low computational cost—finite temperature properties can be calculated. The approach is most efficient at low temperatures, where conventional approaches like Metropolis Monte Carlo sampling suffer from high rejection rates and therefore large statistical noise. To demonstrate the general approach, we apply it to spin glasses and Ising chains.
Deep learning-based automated detection and multiclass classification of focal interictal epileptiform discharges in scalp electroencephalograms
Authors: Chung Yoon Gi , Lee Woo-Jin , Na Sung Min , Kim Hunmin , Hwang Hee , Yun Chang-Ho , Kim Ki Joong
Published: April 2023

Detection and spatial distribution analyses of interictal epileptiform discharges (IEDs) are important for diagnosing, classifying, and treating focal epilepsy. This study proposes deep learning-based models to detect focal IEDs in electroencephalography (EEG) recordings of the frontal, temporal, and occipital scalp regions. This study included 38 patients with frontal (n = 15), temporal (n = 13), and occipital (n = 10) IEDs and 232 controls without IEDs from a single tertiary center. All the EEG recordings were segmented into 1.5-s epochs and fed into 1- or 2-dimensional convolutional neural networks to construct binary classification models to detect IEDs in each focal region and multiclass classification models to categorize IEDs into frontal, temporal, and occipital regions. The binary classification models exhibited accuracies of 79.3–86.4%, 93.3–94.2%, and 95.5–97.2% for frontal, temporal, and occipital IEDs, respectively. The three- and four-class models exhibited accuracies of 87.0–88.7% and 74.6–74.9%, respectively, with temporal, occipital, and non-IEDs F1-scores of 89.9–92.3%, 84.9–90.6%, and 84.3–86.0%; and 86.6–86.7%, 86.8–87.2%, and 67.8–69.2% for the three- and four-class (frontal, 50.3–58.2%) models, respectively. The deep learning-based models could help enhance EEG interpretation. Although they performed well, the resolution of region-specific focal IED misinterpretations and further model improvement are needed.
Ensemble machine learning algorithm for predicting acute kidney injury in patients admitted to the neurointensive care unit following brain surgery
Authors: Wu Muying , Jiang Xuandong , Du Kailei , Xu Yingting , Zhang Weimin
Published: April 2023

Acute kidney injury (AKI) is a common postoperative complication among patients in the neurological intensive care unit (NICU), often resulting in poor prognosis and high mortality. In this retrospective cohort study, we established a model for predicting AKI following brain surgery based on an ensemble machine learning algorithm using data from 582 postoperative patients admitted to the NICU at the Dongyang People's Hospital from March 1, 2017, to January 31, 2020. Demographic, clinical, and intraoperative data were collected. Four machine learning algorithms (C5.0, support vector machine, Bayes, and XGBoost) were used to develop the ensemble algorithm. The AKI incidence in critically ill patients after brain surgery was 20.8%. Intraoperative blood pressure; postoperative oxygenation index; oxygen saturation; and creatinine, albumin, urea, and calcium levels were associated with the postoperative AKI occurrence. The area under the curve value for the ensembled model was 0.85. The accuracy, precision, specificity, recall, and balanced accuracy values were 0.81, 0.86, 0.44, 0.91, and 0.68, respectively, indicating good predictive ability. Ultimately, the models using perioperative variables exhibited good discriminatory ability for early prediction of postoperative AKI risk in patients admitted to the NICU. Thus, the ensemble machine learning algorithm may be a valuable tool for forecasting AKI.
Marital status and long-term cardiovascular risk in general population (Gubbio, Italy)
Authors: Humbert Xavier , Rabiaza Andry , Fedrizzi Sophie , Alexandre Joachim , Menotti Alessandro , Touzé Emmanuel , Laurenzi Martino , Terradura-Vagnarelli Oscar , Puddu Paolo E.
Published: April 2023

To investigate whether marital status is associated to long-term major fatal and non-fatal cardiovascular events in men and women from the Gubbio Population Study. The incidence of cardiovascular disease (CVD), including stroke and coronary heart disease (CHD) and CVD death together with all-cause mortality were analyzed. The analysis included 2832 persons (44% men, 54 ± 11 years old). Marital status was defined at entry as married (married or living conjugally) versus unmarried subjects (widowed, separated, divorced or single). Married and unmarried subjects did not differ concerning socio-demographic, anthropometric and biological variables at baseline. Over 191 months median follow-up, the incidence of CHD was lower among married versus unmarried women [HR: 0.63 (95% CI 0.41–0.96)] only; the same was true for CHD mortality [HR: 0.43 (95% CI 0.22–0.84)] and all-cause mortality [HR: 0.75 (95% CI 0.59–0.96)] independently of traditional risk factors (age, SBP, total and HDL cholesterol, cigarette smoke and BMI). In men, marital status was not associated to any of the investigated outcomes. In primary care, marital status should be investigated as it can be associated with long-term CHD and all-cause incidence and mortality risks among women.
Beat-to-beat finger photoplethysmography in atrial fibrillation patients undergoing electrical cardioversion
Authors: Saglietto Andrea , Scarsoglio Stefania , Canova Daniela , De Ferrari Gaetano Maria , Ridolfi Luca , Anselmino Matteo
Published: April 2023

Atrial fibrillation (AF)-induced peripheral microcirculatory alterations have poorly been investigated. The present study aims to expand current knowledge through a beat-to-beat analysis of non-invasive finger photoplethysmography (PPG) in AF patients restoring sinus rhythm by electrical cardioversion (ECV). Continuous non-invasive arterial blood pressure and left middle finger PPG pulse oximetry waveform (POW) signals were continuously recorded before and after elective ECV of consecutive AF or atrial flutter (AFL) patients. The main metrics (mean, standard deviation, coefficient of variation), as well as a beat-to-beat analysis of the pulse pressure (PP) and POW beat-averaged value (aPOW), were computed to compare pre- and post-ECV phases. 53 patients (mean age 69 ± 8 years, 79% males) were enrolled; cardioversion was successful in restoring SR in 51 (96%) and signal post-processing was feasible in 46 (87%) patients. In front of a non-significant difference in mean PP (pre-ECV: 51.96 ± 13.25, post-ECV: 49.58 ± 10.41 mmHg; p = 0.45), mean aPOW significantly increased after SR restoration (pre-ECV: 0.39 ± 0.09, post-ECV: 0.44 ± 0.06 a.u.; p < 0.001). Moreover, at beat-to-beat analysis linear regression yielded significantly different slope (m) for the PP (RR) relationship compared to aPOW(RR) [PP(RR): 0.43 ± 0.18; aPOW(RR): 1.06 ± 0.17; p < 0.001]. Long (> 95th percentile) and short (< 5th percentile) RR intervals were significantly more irregular in the pre-ECV phases for both PP and aPOW; however, aPOW signal suffered more fluctuations compared to PP (p < 0.001 in both phases). Present findings suggest that AF-related hemodynamic alterations are more manifest at the peripheral (aPOW) rather than at the upstream macrocirculatory level (PP). Restoring sinus rhythm increases mean peripheral microvascular perfusion and decreases variability of the microvascular hemodynamic signals. Future dedicated studies are required to determine if AF-induced peripheral microvascular alterations might relate to long-term prognostic effects.
Impact of adenomyosis and endometriosis on IVF/ICSI pregnancy outcome in patients undergoing gonadotropin-releasing hormone agonist treatment and frozen embryo transfer
Authors: Wang Yu , Yi Yu-Chiao , Guu Hwa-Fen , Chen Ya-Fang , Kung Hsiao-Fan , Chang Jui-Chun , Chen Li-Yu , Chuan Shih-Ting , Chen Ming-Jer
Published: April 2023

Although numerous studies have attempted to establish the relationship between adenomyosis and infertility, no consensus has emerged. Our aim was to investigate whether adenomyosis and endometriosis affected IVF outcomes in our patients. This was a retrospective study of 1720 patients from January 2016 to December 2019. In total, 1389 cycles were included: 229 cycles in the endometriosis group (group E), 89 cycles in the adenomyosis group (group A), 69 cycles in the endometriosis and adenomyosis group (group EA), and 1002 cycles in the control group (group C). Most patients in groups A and EA received GnRH agonist treatment before FET. The 1st FET live birth rates (LBR) were 39.3%, 32.1%, 25% and 48.1% in groups E, A, EA, and C. The miscarriage rates were 19.9%, 34.7%, 39%, and 17.6%. The per retrieval cycle cumulative live birth rates (cLBRs) in patients < 38 y/o were 56.4%, 58.1%, 44.8%, and 63%. The per retrieval cycle cLBRs in patients ≥ 38 y/o were 25%, 9.8%, 17.2%, and 29.5%. Among groups A and EA, LBRs were 25.58% and 18.89% in patients with a ≥ sevenfold decrease and a < sevenfold decrease in CA-125 level, respectively, after GnRH agonist treatment. Endometriosis was not associated with a poorer pregnancy outcome. Patients with adenomyosis with/without endometriosis had higher miscarriage rates, lower LBRs, and lower cLBRs, especially in patients aged ≥ 38 years, even after GnRH agonist treatment before FET cycles. Patients who have a greater than sevenfold decrease in CA-125 level after GnRH agonist treatment might have better clinical pregnancy outcomes.
FDG PET texture indices as imaging biomarkers for epidermal growth factor receptor mutation status in lung adenocarcinoma
Authors: Ishimura Mariko , Norikane Takashi , Mitamura Katsuya , Yamamoto Yuka , Manabe Yuri , Murao Mitsumasa , Murota Makiko , Kanaji Nobuhiro , Nishiyama Yoshihiro
Published: April 2023

Identifying the epidermal growth factor receptor (EGFR) mutation status is important for the optimal treatment of patients with EGFR mutations. We investigated the relationship between 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) texture indices and EGFR mutation status in patients with newly diagnosed lung adenocarcinoma. We retrospectively analyzed data of patients with newly diagnosed lung adenocarcinoma who underwent pretreatment FDG PET/computed tomography and EGFR mutation testing between August 2014 and November 2020. Patients were divided into mutated EGFR and wild-type EGFR groups. The maximum standardized uptake value (SUVmax) and 31 texture indices for the primary tumor were calculated from PET images and compared between the two groups. Of the 66 patients included, 22 had mutated EGFR and 44 had wild-type EGFR. The SUVmax did not significantly differ between the two groups. Among the 31 evaluated texture indices, the following five showed a statistically significant difference between the groups: correlation (P = 0.003), gray-level nonuniformity for run (P = 0.042), run length nonuniformity (P = 0.02), coarseness (P = 0.006), and gray-level nonuniformity for zone (P = 0.04). Based on the preliminary results of this study in a small patient population, FDG PET texture indices may be potential imaging biomarkers for the EGFR mutation status in patients with newly diagnosed lung adenocarcinoma.
Structural insights into the broad protection against H1 influenza viruses by a computationally optimized hemagglutinin vaccine
Authors: Dzimianski John V. , Han Julianna , Sautto Giuseppe A. , O’Rourke Sara M. , Cruz Joseph M. , Pierce Spencer R. , Ecker Jeffrey W. , Carlock Michael A. , Nagashima Kaito A. , Mousa Jarrod J. , Ross Ted M. , Ward Andrew B. , DuBois Rebecca M.
Published: April 2023

Influenza virus poses an ongoing human health threat with pandemic potential. Due to mutations in circulating strains, formulating effective vaccines remains a challenge. The use of computationally optimized broadly reactive antigen (COBRA) hemagglutinin (HA) proteins is a promising vaccine strategy to protect against a wide range of current and future influenza viruses. Though effective in preclinical studies, the mechanistic basis driving the broad reactivity of COBRA proteins remains to be elucidated. Here, we report the crystal structure of the COBRA HA termed P1 and identify antigenic and glycosylation properties that contribute to its immunogenicity. We further report the cryo-EM structure of the P1-elicited broadly neutralizing antibody 1F8 bound to COBRA P1, revealing 1F8 to recognize an atypical receptor binding site epitope via an unexpected mode of binding.
Creating measurement-based oil and gas sector methane inventories using source-resolved aerial surveys
Authors: Johnson Matthew R. , Conrad Bradley M. , Tyner David R.
Published: April 2023

Critical mitigation of methane emissions from the oil and gas (OG) sector is hampered by inaccurate official inventories and limited understanding of contributing sources. Here we present a framework for incorporating aerial measurements into comprehensive OG sector methane inventories that achieves robust, independent quantification of measurement and sample size uncertainties, while providing timely source-level insights. This hybrid inventory combines top-down, source-resolved, multi-pass aerial measurements with bottom-up estimates of unmeasured sources leveraging continuous probability of detection and quantification models for a chosen aerial technology. Notably, the technique explicitly considers skewed source distributions and finite facility populations that have not been previously addressed. The protocol is demonstrated to produce a comprehensive upstream OG sector methane inventory for British Columbia, Canada, which while approximately 1.7 times higher than the most recent official bottom-up inventory, reveals a lower methane intensity of produced natural gas (<0.5%) than comparable estimates for several other regions. Finally, the method and data are used to upper bound the potential influence of source variability/intermittency, directly addressing an open question in the literature. Results demonstrate that even for an extreme case, variability/intermittency effects can be addressed by sample size and survey design and have a minor impact on overall inventory uncertainty.
Functional annotation and importance of marine bacterial transporters of plankton exometabolites
Authors: Schroer William F , Kepner Hannah E , Uchimiya Mario , Mejia Catalina , Rodriguez Lidimarie Trujillo , Reisch Christopher R , Moran Mary Ann
Published: April 2023

Metabolite exchange within marine microbial communities transfers carbon and other major elements through global cycles and forms the basis of microbial interactions. Yet lack of gene annotations and concern about the quality of existing ones remain major impediments to revealing currencies of carbon flux. We employed an arrayed mutant library of the marine bacterium Ruegeria pomeroyi DSS-3 to experimentally annotate substrates of organic compound transporter systems, using mutant growth and compound drawdown analyses to link transporters to their cognate substrates. Mutant experiments verified substrates for thirteen R. pomeroyi transporters. Four were previously hypothesized based on gene expression data (taurine, glucose/xylose, isethionate, and cadaverine/putrescine/spermidine); five were previously hypothesized based on homology to experimentally annotated transporters in other bacteria (citrate, glycerol, N-acetylglucosamine, fumarate/malate/succinate, and dimethylsulfoniopropionate); and four had no previous annotations (thymidine, carnitine, cysteate, and 3-hydroxybutyrate). These bring the total number of experimentally-verified organic carbon influx transporters to 18 of 126 in the R. pomeroyi genome. In a longitudinal study of a coastal phytoplankton bloom, expression patterns of the experimentally annotated transporters linked them to different stages of the bloom, and also led to the hypothesis that citrate and 3-hydroxybutyrate were among the most highly available bacterial substrates. Improved functional annotation of the gatekeepers of organic carbon uptake is critical for deciphering carbon flux and fate in microbial ecosystems.
Optimizing ex vivo culture conditions to study human gut microbiome
Authors: Tao Xin , Huang Wenjin , Pan Lingyun , Sheng Lili , Qin Yuan , Chen Luo , Yu Linhuan , Wu Gaosong , Wan Jianbo , Li Houkai
Published: April 2023

The inter-individual variations of gut microbiome contribute to the different responses toward drug therapy among populations, developing a reliable ex vivo culture method for mixed bacteria is the urgent need for predicting personal reaction to drug therapy. Unfortunately, very few attentions have been paid to the bias that could be introduced during the culture process for mixed bacteria. Here we systemically evaluated the factors that may affect the outcomes of cultured bacteria from human feces. We demonstrated that inter-individual difference of host gut microbiome was the main factor affecting the outcomes of cultured bacteria, followed by the culture medium and time point. We further optimized a new medium termed GB based on our established multi-dimensional evaluation method, which could mimic the status of in situ host gut microbiome to the highest extent. Finally, we assessed the inter-individual metabolism by host gut microbiome from 10 donors on three frequently used clinical drugs (aspirin, levodopa and doxifluridine) based on the optimized GB medium. Our results revealed obvious variation in drug metabolism by microbiome from different donors, especially levodopa and doxifluridine. This work suggested the optimized culture medium had the potential for exploring the inter-individual impacts of host gut microbiome on drug metabolism.