bluuebunny/crossref_metadata_2025 huggingface dataset:
Knowledge of the perturbation design is essential for accurate gene regulatory network inference
Authors: Seçilmiş Deniz , Hillerton Thomas , Tjärnberg Andreas , Nelander Sven , Nordling Torbjörn E. M. , Sonnhammer Erik L. L.
Published: October 2022

The gene regulatory network (GRN) of a cell executes genetic programs in response to environmental and internal cues. Two distinct classes of methods are used to infer regulatory interactions from gene expression: those that only use observed changes in gene expression, and those that use both the observed changes and the perturbation design, i.e. the targets used to cause the changes in gene expression. Considering that the GRN by definition converts input cues to changes in gene expression, it may be conjectured that the latter methods would yield more accurate inferences but this has not previously been investigated. To address this question, we evaluated a number of popular GRN inference methods that either use the perturbation design or not. For the evaluation we used targeted perturbation knockdown gene expression datasets with varying noise levels generated by two different packages, GeneNetWeaver and GeneSpider. The accuracy was evaluated on each dataset using a variety of measures. The results show that on all datasets, methods using the perturbation design matrix consistently and significantly outperform methods not using it. This was also found to be the case on a smaller experimental dataset fromE. coli. Targeted gene perturbations combined with inference methods that use the perturbation design are indispensable for accurate GRN inference.
A suite of agronomic factors can offset the effects of climate variability on rainfed maize production in Kenya
Authors: Oluoch Kevin Ong’are , De Groote Hugo , Gitonga Zachary M. , Jin Zhenong , Davis Kyle Frankel
Published: October 2022

Achieving food security in sub-Saharan Africa (SSA) is a multidimensional challenge. SSA reliance on food imports is expected to grow in the coming decades to meet the population's demand, projected to double to over 2 billion people by 2050. In addition, climate change is already affecting food production and supply chains across the region. Addressing these multiple food security challenges will necessitate rapid enhancements in agricultural productivity, which is influenced by a host of demographic, agronomic, and climatic factors. We use statistical approaches to examine rainfed maize in Kenya, where maize cultivation and consumption are widespread and central to livelihoods and national food security. We find that improving a suite of agronomic factors, such as applying fertilizer, planting certified seeds, and extension services, will have a greater effect on rainfed maize productivity than demographics and can offset the effects of climate change. These findings could also offer insights into similar challenges for other crops in Kenya and other SSA countries.
Evidence towards a continuum of impairment across neurodevelopmental disorders from basic ocular-motor tasks
Authors: Canu Daniela , Ioannou Chara , Müller Katarina , Martin Berthold , Fleischhaker Christian , Biscaldi Monica , Beauducel André , Smyrnis Nikolaos , van Elst Ludger Tebartz , Klein Christoph
Published: October 2022

Findings of genetic overlap between Schizophrenia, Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) contributed to a renewed conceptualization of these disorders as laying on a continuum based on aetiological, pathophysiological and neurodevelopmental features. Given that cognitive impairments are core to their pathophysiology, we compared patients with schizophrenia, ADHD, ASD, and controls on ocular-motor and manual-motor tasks, challenging crucial cognitive processes. Group comparisons revealed inhibition deficits common to all disorders, increased intra-subject variability in schizophrenia and, to a lesser extent, ADHD as well as slowed processing in schizophrenia. Patterns of deviancies from controls exhibited strong correlations, along with differences that posited schizophrenia as the most impaired group, followed by ASD and ADHD. While vector correlations point towards a common neurodevelopmental continuum of impairment, vector levels suggest differences in the severity of such impairment. These findings argue towards a dimensional approach to Neurodevelopmental Disorders’ pathophysiological mechanisms.
Cell-free protein crystallization for nanocrystal structure determination
Authors: Abe Satoshi , Tanaka Junko , Kojima Mariko , Kanamaru Shuji , Hirata Kunio , Yamashita Keitaro , Kobayashi Ayako , Ueno Takafumi
Published: October 2022

In-cell protein crystallization (ICPC) has been investigated as a technique to support the advancement of structural biology because it does not require protein purification and a complicated crystallization process. However, only a few protein structures have been reported because these crystals formed incidentally in living cells and are insufficient in size and quality for structure analysis. Here, we have developed a cell-free protein crystallization (CFPC) method, which involves direct protein crystallization using cell-free protein synthesis. We have succeeded in crystallization and structure determination of nano-sized polyhedra crystal (PhC) at a high resolution of 1.80 Å. Furthermore, nanocrystals were synthesized at a reaction scale of only 20 μL using the dialysis method, enabling structural analysis at a resolution of 1.95 Å. To further demonstrate the potential of CFPC, we attempted to determine the structure of crystalline inclusion protein A (CipA), whose structure had not yet been determined. We added chemical reagents as a twinning inhibitor to the CFPC solution, which enabled us to determine the structure of CipA at 2.11 Å resolution. This technology greatly expands the high-throughput structure determination method of unstable, low-yield, fusion, and substrate-biding proteins that have been difficult to analyze with conventional methods.
Cell-imaging studies of highly substituted oxazole derivatives as organelle targeting fluorophores (OTFPs)
Authors: Adhikary Saswati , Mukherjee Kaustuv , Banerji Biswadip
Published: October 2022

The field of biomedical science has progressed enormously in the past decade. With the advent of newer diagnostic tools for imaging and detection, identification of root cause of a disease is now remarkably accurate and specific. Small organic fluorophores in these connections are in great demand currently for cellular organelle sensing and detecting, due to their non-invasiveness, excellent accuracy and bio-sensitivity. Small molecule fluorescence probes offer most potent area for biological sensing with diagnostic imaging ability. These organelle targetable fluorescent probes are produced through synthetic manipulations to get the desired, decent fluorescence properties. When a suitable organelle specific functional group is installed within these highly fluorescent scaffolds, then these molecules turn out to be as lysotracker, mitotracker and cytoplasm-stainer in mammalian cells with high efficiencies (high Pearson co-efficient factors). The present work demonstrated an environmentally benign (green) one-pot, sp3 C–H functionalization of highly substituted oxazole derivatives with excellent photophysical properties. These molecules were further modified by installing organelle specific targetable groups (sensors/detectors) which selectively localize in specific intra-cellular organelles.
High-quality restoration image encryption using DCT frequency-domain compression coding and chaos
Authors: Wen Heping , Ma Linchao , Liu Linhao , Huang Yiming , Chen Zefeng , Li Rui , Liu Zhen , Lin Wenxing , Wu Jiahao , Li Yunqi , Zhang Chongfu
Published: October 2022

With the arrival of the age of big data, the amount and types of data in the process of information transmission have increased significantly, and the full-disk encryption mode used by traditional encryption algorithms has certain limitations of the times. In order to further improve the bandwidth efficiency of digital images in the transmission process and the information effectiveness of digital image transmission, this paper proposes an algorithm of high-quality restoration image encryption using DCT frequency-domain compression coding and chaos. Firstly, the image hash value is used for the generation of an encryption key with plaintext correlation, then lightweight chaos is generated based on the key to obtain a pseudo-random sequence. Secondly, the image is partitioned into subblock, and converted from time domain into frequency domain by employing Discrete Cosine Transform (DCT) on each block, then perform quantization operation based on frequency domain information to obtain DCT coefficient matrix. Thirdly, the direct current (DC) coefficients and alternating current (AC) coefficients are extracted in the DCT coefficient matrix and compressed by different encoding methods to obtain two sets of bitstream containing DC coefficient and AC coefficient information. Fourthly, permute the DC coefficient bit stream by the chaotic sequence, and reconstruct it with the AC coefficient bit stream to obtain the frequency domain ciphertext image. Finally, the chaotic sequence is used to diffuse ciphertext, and the processed hash value is hidden in the ciphertext to obtain the final ciphertext. The theoretical and experimental analysis showed that the key length reaches 341 bits, and the PSNR value of the restored image is close to 60, all of which satisfy the theoretical value. Therefore, the algorithm has the characteristics of high compression rate, high-quality image restoration large key space, strong plaintext sensitivity, strong key sensitivity and so on. Our method proposed in this paper is expected to provide a new idea for confidential and secure communication in the age of big data.
The impact of air travel on the precocity and severity of COVID-19 deaths in sub-national areas across 45 countries
Authors: Recchi Ettore , Ferrara Alessandro , Rodriguez Sanchez Alejandra , Deutschmann Emanuel , Gabrielli Lorenzo , Iacus Stefano , Bastiani Luca , Spyratos Spyridon , Vespe Michele
Published: October 2022

Human travel fed the worldwide spread of COVID-19, but it remains unclear whether the volume of incoming air passengers and the centrality of airports in the global airline network made some regions more vulnerable to earlier and higher mortality. We assess whether theprecocityandseverityof COVID-19 deaths were contingent on these measures of air travel intensity, adjusting for differences in local non-pharmaceutical interventions and pre-pandemic structural characteristics of 502 sub-national areas on five continents in April–October 2020. Ordinary least squares (OLS) models ofprecocity(i.e., the timing of the 1st and 10th death outbreaks) reveal that neither airport centrality nor the volume of incoming passengers are impactful once we consider pre-pandemic demographic characteristics of the areas. We assessseverity(i.e., the weekly death incidence of COVID-19) through the estimation of a generalized linear mixed model, employing a negative binomial link function. Results suggest that COVID-19 death incidence was insensitive to airport centrality, with no substantial changes over time. Higher air passenger volume tends to coincide with more COVID-19 deaths, but this relation weakened as the pandemic proceeded. Different models prove that either the lack of airports in a region or total travel bans did reduce mortality significantly. We conclude that COVID-19 importation through air travel followed a ‘travel as spark’ principle, whereby the absence of air travel reduced epidemic risk drastically. However, once some travel occurred, its impact on the severity of the pandemic was only in part associated with the number of incoming passengers, and not at all with the position of airports in the global network of airline connections.
Timing of vagus nerve stimulation during fear extinction determines efficacy in a rat model of PTSD
Authors: Souza Rimenez R. , Powers Mark B. , Rennaker Robert L. , McIntyre Christa K. , Hays Seth A. , Kilgard Michael P.
Published: October 2022

Studies have indicated that vagus nerve stimulation (VNS) enhances extinction learning in rodent models. Here, we investigated if pairing VNS with the conditioned stimulus is required for the enhancing effects of VNS. Adult Sprague–Dawley rats were exposed to intense stress followed by fear conditioning training to produce resistant fear. Rats were then implanted with a cuff electrode around the left vagus. After recovery, rats underwent extinction training paired with VNS (0.5 s, 0.8 mA, 100 µs, and 30 Hz) or with Sham VNS (0 mA). VNS rats were randomized into the following subgroups: During VNS (delivered during presentations of the conditioned stimulus, CS), Between VNS (delivered between CS presentations), Continuous VNS (delivered during the entire extinction session), and Dispersed VNS (delivered at longer inter-stimulation intervals across the extinction session). Sham VNS rats failed to extinguish the conditioned fear response over 5 days of repeated exposure to the CS. Rats that received Between or Dispersed VNS showed modest improvement in conditioned fear at the retention test. During and Continuous VNS groups displayed the greatest reduction in conditioned fear. These findings indicate that delivering VNS paired precisely with CS presentations or continuously throughout extinction promotes the maximum enhancement in extinction learning.
Endoscopic ultrasound-guided radiofrequency ablation (EUS-RFA) for advanced pancreatic and periampullary adenocarcinoma
Authors: Thosani Nirav , Cen Putao , Rowe Julie , Guha Sushovan , Bailey-Lundberg Jennifer M. , Bhakta Dimpal , Patil Prithvi , Wray Curtis J.
Published: October 2022

Long term prognosis and 5-year survival for pancreatic adenocarcinoma (PDAC) remains suboptimal. Endoscopic ultrasound (EUS) guided RFA (EUS-RFA) is an emerging technology and limited data exist regarding safety and long-term outcomes. The aim of this study is to report safety-profile, feasibility and outcomes of EUS-RFA for advanced PDAC. Prospective review of patients with diagnosis of locally-advanced or metastatic PDAC undergoing EUS-RFA between October 2016 to March 2018 with long-term follow up (> 30 months). Study patients underwent a total of 1–4 RFA sessions. All patients were enrolled in longitudinal cohort study and received standard of care chemotherapy. 10 patients underwent EUS-RFA. Location of the lesions was in the head(4), neck(2), body(2), and tail(2). 22 RFA sessions were performed with a range of 1–4 sessions per patient. There were no major adverse events (bleeding, perforation, infection, pancreatitis) in immediate (up to 72 h) and short-term follow up (4 weeks). Mild worsening of existing abdominal pain was noted during post-procedure observation in 12/22 (55%) of RFA treatments. Follow-up imaging demonstrated tumor progression in 2 patients, whereas tumor regression was noted in 6 patients (> 50% reduction in size in 3 patients). Median survival for the cohort was 20.5 months (95% CI, 9.93–42.2 months). Currently, 2 patients remain alive at 61 and 81 months follow-up since initial diagnosis. One patient had 3 cm PDAC with encasement of the portal confluence, abutment of the celiac axis, common hepatic and superior mesenteric artery. This patient had significant reduction in tumor size and underwent standard pancreaticoduodenectomy. In our experience, EUS-RFA was safe, well-tolerated and could be concurrently performed with standard chemotherapy. In this select cohort, median survival was improved when compared to published survival based upon SEER database and clinical trials. Future prospective trials are needed to understand the role of EUS-RFA in overall management of PDAC.
Optimized multi-echo gradient-echo magnetic resonance imaging for gray and white matter segmentation in the lumbosacral cord at 3 T
Authors: Büeler Silvan , Yiannakas Marios C. , Damjanovski Zdravko , Freund Patrick , Liechti Martina D. , David Gergely
Published: October 2022

Atrophy in the spinal cord (SC), gray (GM) and white matter (WM) is typically measured in-vivo by image segmentation on multi-echo gradient-echo magnetic resonance images. The aim of this study was to establish an acquisition and analysis protocol for optimal SC and GM segmentation in the lumbosacral cord at 3 T. Ten healthy volunteers underwent imaging of the lumbosacral cord using a 3D spoiled multi-echo gradient-echo sequence (Siemens FLASH, with 5 echoes and 8 repetitions) on a Siemens Prisma 3 T scanner. Optimal numbers of successive echoes and signal averages were investigated comparing signal-to-noise (SNR) and contrast-to-noise ratio (CNR) values as well as qualitative ratings for segmentability by experts. The combination of 5 successive echoes yielded the highest CNR between WM and cerebrospinal fluid and the highest rating for SC segmentability. The combination of 3 and 4 successive echoes yielded the highest CNR between GM and WM and the highest rating for GM segmentability in the lumbosacral enlargement and conus medullaris, respectively. For segmenting the SC and GM in the same image, we suggest combining 3 successive echoes. For SC or GM segmentation only, we recommend combining 5 or 3 successive echoes, respectively. Six signal averages yielded good contrast for reliable SC and GM segmentation in all subjects. Clinical applications could benefit from these recommendations as they allow for accurate SC and GM segmentation in the lumbosacral cord.
Longitudinal evaluation of dehydroepiandrosterone (DHEA), its sulfated form and estradiol with cancer-related cognitive impairment in early-stage breast cancer patients receiving chemotherapy
Authors: Toh Yi Long , Tan Chia Jie , Yap Ning Yi , Parajuli Ritesh , Lau Aik Jiang , Chan Alexandre
Published: October 2022

The purpose of this study is to elucidate how patient-reported cognitive symptoms manifest from variations in hormone levels or precursors such as dehydroepiandrosterone (DHEA) and its sulfated form [collectively termed as DHEA(S)] and to investigate their association in breast cancer survivors. Levels of estradiol and DHEA(S) were compared between early-stage breast cancer patients with and without cancer-related cognitive impairment (CRCI) during adjuvant chemotherapy. Data were analyzed from 242 patients (mean age ± SD = 50.8 ± 9.2 years) who had completed FACT-Cog v.3.0, blood draws and questionnaires. Regression model was used to fit the magnitude of change in each respective biomarker levels against overall cognitive impairment status while adjusting for clinically important covariates. There was reduction in mean plasma levels of estradiol and DHEAS during and towards the end of chemotherapy (p-values < 0.001). Compared to non-impaired patients, smaller magnitude of decline was observed in DHEA(S) levels in patients reporting CRCI, with significant association between decline in DHEAS levels and acute onset of CRCI at 6 weeks from baseline (adjusted β of 0.40, p-value of 0.02). In contrast, patients reporting CRCI showed greater magnitude of decline in estradiol compared to non-impaired patients, although this was not found to be statistically significant. There was an association between magnitude of change in biomarker levels with self-reported CRCI which suggests that the hormonal pathway related to DHEAS may be implicated in acute CRCI for breast cancer survivors. Our findings help to improve biological understanding of the pathway from which DHEAS may correlate with cognitive dysfunction and its impact on cancer survivors.
Electron microscopy and calorimetry of proteins in supercooled water
Authors: Melillo Jorge H. , Nikulina Elizaveta , Iriarte-Alonso Maiara A. , Cerveny Silvina , Bittner Alexander M.
Published: October 2022

Some of the best nucleating agents in nature are ice-nucleating proteins, which boost ice growth better than any other material. They can induce immersion freezing of supercooled water only a few degrees below 0 °C. An open question is whether this ability also extends to the deposition mode, i.e., to water vapor. In this work, we used three proteins, apoferritin, InaZ (ice nucleation active protein Z), and myoglobin, of which the first two are classified as ice-nucleating proteins for the immersion freezing mode. We studied the ice nucleation ability of these proteins by differential scanning calorimetry (immersion freezing) and by environmental scanning electron microscopy (deposition freezing). Our data show that InaZ crystallizes water directly from the vapor phase, while apoferritin first condenses water in the supercooled state, and subsequently crystallizes it, just as myoglobin, which is unable to nucleate ice.
US county-level prevalence and spatial distribution of optimal birth outcomes 2018–2019
Authors: Dyer Lauren , Bell Caryn , Perez Susan , Crear-Perry Joia , Theall Katherine , Wallace Maeve
Published: October 2022

A shift in focus towards healthy reproductive outcomes may reveal opportunities for novel interventions and strategies to promote optimal health. Using variables from the National Center for Health Statistics restricted use natality files, we calculated Empirical Bayes smoothed (EBS) rates of optimal birth for the all live births—both overall and by maternal race/ethnicity—by applying the smoothing tool in GeoDa version 1.18.0.10 We defined counties achieving greater racial birth equity as those where the overall EBS optimal birth rate was greater than the national 75th percentile and the absolute difference between maternal racial/ethnic categories was smaller than the national 25th percentile difference. During the study period, 49.80% of overall births could be classified as an optimal birth according to the study definition. Of the 3140 US counties, only 282 (8.98%) appeared to advance White-Black equity in optimal births, and 205 (6.53%) appeared to advance White-Hispanic equity in optimal births. In the effort improve maternal health, we should focus not only on the absence of negative outcomes, but also the occurrence of positive outcomes. Our analytic results suggest that optimal births can be measured and that geographic inequities by race occur.
Preparation of novel B4C nanostructure/Si photodetectors by laser ablation in liquid
Authors: Hamd Salah S. , Ramizy Asmiet , Ismail Raid A.
Published: October 2022

In this study, boron carbide (B4C) nanoparticles (NPs) are synthesized by pulsed laser ablation of boron in ethanol at a laser fluence of 6.36 J cm−2 pulse−1. The effect of numbers of laser pulses on the structural, optical, and electrical properties of B4C NPs was studied. X-ray diffraction (XRD) results revealed that all B4C nanoparticles synthesized were polycrystalline in nature with a rhombohedral structure. When the laser pulses increased from 500 to 1500, the optical band gap of B4C decreased from 2.45 to 2.38 eV. Fluorescence measurements showed the emission of two emission peaks. The Raman spectra of B4C nanoparticles exhibit six vibration modes centered at 270, 480, 533, 722, 820, and 1080 cm−1. Field emission scanning electron microscope (FESEM) images show the formation of spherical nanoparticles of an average size of 68, 75, and 84 nm for samples prepared at 500, 1000, and 1500 pulses, respectively. The dark I–V characteristics of B4C/Si heterojunction photodetectors showed rectification characteristics, and the heterojunction prepared at 500 pulses exhibits the best junction characteristics. The illuminated I–V characteristics of B4C/p-Si heterojunction photodetectors exhibited high photosensitivity to white light. The spectral responsivity of the p-B4C/p-Si photodetector shows that the maximum responsivity was 0.66 A W−1at 500 nm for a photodetector prepared at 500 pulses. The highest specific detectivity and quantum efficiency were 2.18 × 1012Jones and 1.64 × 102% at 550 nm, respectively, for a heterojunction photodetector fabricated at 500 pulses, The ON/OFF ratio, rise time, and fall time are measured as a function of the number of laser pulses. The photodetector fabricated at 1500 laser pulses showed roughly rise and fall intervals of 1.5 and 0.8 s, respectively.
Potential mechanisms and prognostic model of eRNAs-regulated genes in stomach adenocarcinoma
Authors: Gao Liuying , Rong Hao
Published: October 2022

Gastric Carcinoma is the fourth leading cause of cancer deaths worldwide, in which stomach adenocarcinoma (STAD) is the most common histological type. A growing amount of evidence has suggested the importance of enhancer RNAs (eRNAs) in the cancer. However, the potential mechanism of eRNAs in STAD remains unclear. The eRNAs-regulated genes (eRRGs) were identified through four different enhancer resources. The differentially expressed eRRGs were obtained by ‘DESeq2’ R package. The prognosis prediction model was constructed by Cox and Lasso regression analysis. The ‘ChAMP’ R package and ‘maftools’ R package were used to investigate the multi-omics characters. In this study, combining the concept of contact domain, a total of 9014 eRRGs including 4926 PCGs and 4088 lncRNAs were identified and these eRRGs showed higher and more stable expression. Besides, the functions of these genes were mainly associated with tumor-related biological processes. Then, a prognostic prediction model was constructed and the AUC values of the 1-, 3- and 5-year survival prediction reached 0.76, 0.84 and 0.84, respectively, indicating that this model has a high accuracy. Finally, the difference between high-risk group and low-risk group were investigated using multi-omics data including gene expression, DNA methylation and somatic mutations. Our study provides significant clues for the elucidation of eRNAs in STAD and may help improve the overall survival for STAD patients.
Giant clam (Tridacna) distribution in the Gulf of Oman in relation to past and future climate
Authors: Reuter Markus , Spreter Philipp M. , Brachert Thomas C. , Mertz-Kraus Regina , Wrozyna Claudia
Published: October 2022

The Oman upwelling zone (OUZ) creates an unfavorable environment and a major biogeographic barrier for many coral reef species, such as giant clams, thus promoting and maintaining faunal differences among reefs on the east and west side of the Arabian Peninsula. We record the former existence of Tridacna in the Gulf of Oman and review its stratigraphic distribution in the Persian Gulf to provide new insights on the connectivity of coral reef habitats around southern Arabia under changing climate and ocean conditions. Fossil shells were carbon-14 dated and employed as sclerochronological proxy archives. This reveals that the Omani population represents a last glacial colonization event during the Marine Isotope Stage 3 interstadial under colder-than-present temperatures and variable upwelling intensity linked to Dansgaard-Oeschger climate oscillations. It was favored by temperatures just above the lower threshold for the habitat-forming reef coral communities and instability of the upwelling barrier. We conclude that the distribution of Tridacna in the northern Arabian Sea is generally limited by either strong upwelling or cool sea surface temperature under gradually changing climate conditions at the interglacial-glacial scale. Opportunities for dispersal and temporary colonization existed only when there was a simultaneous attenuation of both limiting factors due to high-frequency climate variability. The OUZ will unlikely become a future climate change refuge for giant clams because they will be exposed either to thermal stress by rapid anthropogenic Indian Ocean warming or to unfavorable upwelling conditions.
Prone positioning may increase lung overdistension in COVID-19-induced ARDS
Authors: Otáhal Michal , Mlček Mikuláš , Borges João Batista , Alcala Glasiele Cristina , Hladík Dominik , Kuriščák Eduard , Tejkl Leoš , Amato Marcelo , Kittnar Otomar
Published: October 2022

Real-time effects of changing body position and positive end-expiratory pressure (PEEP) on regional lung overdistension and collapse in individual patients remain largely unknown and not timely monitored. The aim of this study was to individualize PEEP in supine and prone body positions seeking to reduce lung collapse and overdistension in mechanically ventilated patients with coronavirus disease (COVID-19)-induced acute respiratory distress syndrome (ARDS). We hypothesized that prone positioning with bedside titrated PEEP would provide attenuation of both overdistension and collapse. In this prospective observational study, patients with COVID-19-induced ARDS under mechanical ventilation were included. We used electrical impedance tomography (EIT) with decremental PEEP titration algorithm (PEEPEIT-titration), which provides information on regional lung overdistension and collapse, along with global respiratory system compliance, to individualize PEEP and body position. PEEPEIT-titration in supine position followed by PEEPEIT-titration in prone position were performed. Immediately before each PEEPEIT-titration, the same lung recruitment maneuver was performed: 2 min of PEEP 24 cmH2O and driving pressure of 15 cmH2O. Forty-two PEEPEIT-titration were performed in ten patients (21 pairs supine and prone positions). We have found larger % of overdistension along the PEEP titration in prone than supine position (P = 0.042). A larger % of collapse along the PEEP titration was found in supine than prone position (P = 0.037). A smaller respiratory system compliance was found in prone than supine position (P < 0.0005). In patients with COVID-19-induced ARDS, prone body position, when compared with supine body position, decreased lung collapse at low PEEP levels, but increased lung overdistension at PEEP levels greater than 10 cm H2O.

Trial registration number: NCT04460859.
Cognitive genomics of learning delay and low level of social performance monitoring in macaque
Authors: Ninomiya Taihei , Noritake Atsushi , Tatsumoto Shoji , Go Yasuhiro , Isoda Masaki
Published: October 2022

Cognitive skills and the underlying neural architecture are under the influence of genetics. Cognitive genomics research explores the triadic relationship between genes, brain, and cognition, with its major strategy being genotype-driven. Here we show that an inverse strategy is feasible to identify novel candidate genes for particular neuro-cognitive phenotypes in macaques. Two monkeys, originally involved in separate psychological studies, exhibited learning delay and low levels of social performance monitoring. In one monkey, mirror neurons were fewer compared to controls and mu suppression was absent in the frontal cortex. The other monkey showed heightened visual responsiveness in both frontal cortex and dopamine-rich midbrain, with a lack of inter-areal synchronization. Exome analyses revealed that the two monkeys were most likely cousins and shared variants in MAP2, APOC1, and potentially HTR2C. This phenotype-driven strategy in cognitive genomics provides a useful means to clarify the genetic basis of phenotypic variation and develop macaque models of neuropsychiatric disorders.
Modelling brain dynamics by Boolean networks
Authors: Bertacchini Francesca , Scuro Carmelo , Pantano Pietro , Bilotta Eleonora
Published: October 2022

Understanding the relationship between brain architecture and brain function is a central issue in neuroscience. We modeled realistic spatio-temporal patterns of brain activity on a human connectome with a Boolean networks model with the aim of computationally replicating certain cognitive functions as they emerge from the standardization of many fMRI studies, identified as patterns of human brain activity. Results from the analysis of simulation data, carried out for different parameters and initial conditions identified many possible paths in the space of parameters of these network models, with normal (ordered asymptotically constant patterns), chaotic (oscillating or disordered) but also highly organized configurations, with countless spatial–temporal patterns. We interpreted these results as routes to chaos, permanence of the systems in regimes of complexity, and ordered stationary behavior, associating these dynamics to cognitive processes. The most important result of this work is the study of emergent neural circuits, i.e., configurations of areas that synchronize over time, both locally and globally, determining the emergence of computational analogues of cognitive processes, which may or may not be similar to the functioning of biological brain. Furthermore, results put in evidence the creation of how the brain creates structures of remote communication. These structures have hierarchical organization, where each level allows for the emergence of brain organizations which behave at the next superior level. Taken together these results allow the interplay of dynamical and topological roots of the multifaceted brain dynamics to be understood.
Automated fracture screening using an object detection algorithm on whole-body trauma computed tomography
Authors: Inoue Takaki , Maki Satoshi , Furuya Takeo , Mikami Yukio , Mizutani Masaya , Takada Ikko , Okimatsu Sho , Yunde Atsushi , Miura Masataka , Shiratani Yuki , Nagashima Yuki , Maruyama Juntaro , Shiga Yasuhiro , Inage Kazuhide , Orita Sumihisa , Eguchi Yawara , Ohtori Seiji
Published: October 2022

The emergency department is an environment with a potential risk for diagnostic errors during trauma care, particularly for fractures. Convolutional neural network (CNN) deep learning methods are now widely used in medicine because they improve diagnostic accuracy, decrease misinterpretation, and improve efficiency. In this study, we investigated whether automatic localization and classification using CNN could be applied to pelvic, rib, and spine fractures. We also examined whether this fracture detection algorithm could help physicians in fracture diagnosis. A total of 7664 whole-body CT axial slices (chest, abdomen, pelvis) from 200 patients were used. Sensitivity, precision, and F1-score were calculated to evaluate the performance of the CNN model. For the grouped mean values for pelvic, spine, or rib fractures, the sensitivity was 0.786, precision was 0.648, and F1-score was 0.711. Moreover, with CNN model assistance, surgeons showed improved sensitivity for detecting fractures and the time of reading and interpreting CT scans was reduced, especially for less experienced orthopedic surgeons. Application of the CNN model may lead to reductions in missed fractures from whole-body CT images and to faster workflows and improved patient care through efficient diagnosis in polytrauma patients.
Damage evolution and fracture behavior of different materials specimens containing a central hole subjected to local loading
Authors: Ji Dongliang , Zhao Hongbao , Cheng Hui , Yang Xiuhan , Ge Lina
Published: October 2022

The strength of the different materials specimens containing a central hole subjected to varying loading areas constitutes lots of underground engineering such as entry arrangement and mining process. In this study, the failure resulted from micro-fracturing in the specimen, which can be characterized by the crack propagation path if the damage events are monitored by using Digital Image Correlation (DIC), infrared thermal imager and high-speed camera. The experimental results demonstrate that there are three different types of typical failure modes for specimens with central holes according to the loading areas. The evolution of the temperature field is shown for various loading areas, the smaller loading area, the greater the stress concentration, and the more pronounced the thermodynamic features. The temperature field can also be associated with material properties in addition to loading area. Additionally, failure around the hole with redistributed stress has been observed, and strain energy density (SED) can help explain the failure mechanisms. The progressive damage process, which takes into account the heterogeneity in elastic modulus and rock strength characteristic, is demonstrated by developing a constitutive model that uses the uniaxial compression and Brazilian disc tests to parameterize it. By comparison with plastic zone, the proposed constitutive model is used to quantitatively evaluate the accumulation of damage. Failure mechanisms are established based on this work and are anticipated to be extensively utilized in engineering applications.
Metaheuristic algorithm integrated neural networks for well-test analyses of petroleum reservoirs
Authors: Kumar Pandey Rakesh , Aggarwal Shrey , Nath Griesha , Kumar Anil , Vaferi Behzad
Published: October 2022

In recent years, well-test research has witnessed several works to automate reservoir model identification and characterization using computer-assisted models. Since the reservoir model identification is a classification problem, while its characterization is a regression-based task, their simultaneous accomplishment is always challenging. This work combines genetic algorithm optimization and artificial neural networks to identify and characterize homogeneous reservoir systems from well-testing data automatically. A total of eight prediction models, including two classifiers and six regressors, have been trained. The simulated well-test pressure derivatives with varying noise percentages comprise the training samples. The feature selection and hyperparameter tuning have been performed carefully using the genetic algorithm to enhance the prediction accuracy. The models were validated using nine simulated and one real-field test case. The optimized classifier identifies all the reservoir models with a classification accuracy higher than 79%. In addition, the statistical analysis approves that the optimized regressors accurately perform the reservoir characterization with mean relative errors of lower than 4.5%. The minimized manual interference reduces human bias, and the models have significant noise tolerance for practical applications.
Serum level of IFNβ distinguishes early from late relapses after biologics withdrawal in rheumatoid arthritis
Authors: Sakashita Eiji , Nagatani Katsuya , Endo Hitoshi , Minota Seiji
Published: October 2022

Since the advent of biological disease modifying anti-rheumatic drugs (bDMARDs) in the treatment of rheumatoid arthritis (RA), most RA patients receiving such drugs have achieved remission at the expense of cost and infection risk. After bDMARDs are withdrawn, a substantial proportion of patients would have relapses even if they were in complete remission. In our previous report, relapse prediction could be made at the time of bDMARD withdrawal by measuring the serum levels of five cytokines. We report herein that, among 73 cytokines examined, serum levels of only interferon β (IFNβ) at the time of bDMARD withdrawal could predict early relapse (within 5 months) in patients who were categorized to relapse by the five cytokines in our previous report, with a cut-off value of 3.38 in log2 and AUC of 0.833. High serum levels of IFNβ in the early-relapse group remained high until actual relapse occurred. Therefore, patients who relapse early might be biochemically different from those who relapse late or do not relapse at all. We recommend that patients who are predicted to relapse early continue bDMARDs even if they are in complete remission. This finding contributes to shared decision-making regarding how and when bDMARDs should be discontinued.
Mining the equine gut metagenome: poorly-characterized taxa associated with cardiovascular fitness in endurance athletes
Authors: Mach Núria , Midoux Cédric , Leclercq Sébastien , Pennarun Samuel , Le Moyec Laurence , Rué Olivier , Robert Céline , Sallé Guillaume , Barrey Eric
Published: October 2022

Emerging evidence indicates that the gut microbiome contributes to endurance exercise performance. Still, the extent of its functional and metabolic potential remains unknown. Using elite endurance horses as a model system for exercise responsiveness, we built an integrated horse gut gene catalog comprising ~25 million unique genes and 372 metagenome-assembled genomes. This catalog represents 4179 genera spanning 95 phyla and functional capacities primed to exploit energy from dietary, microbial, and host resources. The holo-omics approach shows that gut microbiomes enriched inLachnospiraceaetaxa are negatively associated with cardiovascular capacity. Conversely, more complex and functionally diverse microbiomes are associated with higher glucose concentrations and reduced accumulation of long-chain acylcarnitines and non-esterified fatty acids in plasma, suggesting increased ß-oxidation capacity in the mitochondria. In line with this hypothesis, more fit athletes show upregulation of mitochondrial-related genes involved in energy metabolism, biogenesis, and Ca2+cytosolic transport, all of which are necessary to improve aerobic work power, spare glycogen usage, and enhance cardiovascular capacity. The results identify an associative link between endurance performance and gut microbiome composition and gene function, laying the basis for nutritional interventions that could benefit horse athletes.
Cryo-EM structure-based selection of computed ligand poses enables design of MTA-synergic PRMT5 inhibitors of better potency
Authors: Zhou Wei , Yadav Gaya P. , Yang Xiaozhi , Qin Feng , Li Chenglong , Jiang Qiu-Xing
Published: October 2022

Projected potential of 2.5–4.0 Å cryo-EM structures for structure-based drug design is not well realized yet. Here we show that a 3.1 Å structure of PRMT5 is suitable for selecting computed poses of a chemical inhibitor and its analogs for enhanced potency. PRMT5, an oncogenic target for various cancer types, has many inhibitors manifesting little cooperativity with MTA, a co-factor analog accumulated in MTAP−/− cells. To achieve MTA-synergic inhibition, a pharmacophore from virtual screen leads to a specific inhibitor (11-2 F). Cryo-EM structures of 11-2 F / MTA-bound human PRMT5/MEP50 complex and itsapoform resolved at 3.1 and 3.2 Å respectively show that 11-2 F in the catalytic pocket shifts the cofactor-binding pocket away by ~2.0 Å, contributing to positive cooperativity. Computational analysis predicts subtype specificity of 11-2 F among PRMTs. Structural analysis of ligands in the binding pockets is performed to compare poses of 11-2 F and its redesigned analogs and identifies three new analogs predicted to have significantly better potency. One of them, after synthesis, is ~4 fold more efficient in inhibiting PRMT5 catalysis than 11-2 F, with strong MTA-synergy. These data suggest the feasibility of employing near-atomic resolution cryo-EM structures and computational analysis of ligand poses for small molecule therapeutics.
Interpretable machine learning prediction of all-cause mortality
Authors: Qiu Wei , Chen Hugh , Dincer Ayse Berceste , Lundberg Scott , Kaeberlein Matt , Lee Su-In
Published: October 2022

Background

Unlike linear models which are traditionally used to study all-cause mortality, complex machine learning models can capture non-linear interrelations and provide opportunities to identify unexplored risk factors. Explainable artificial intelligence can improve prediction accuracy over linear models and reveal great insights into outcomes like mortality. This paper comprehensively analyzes all-cause mortality by explaining complex machine learning models.

Methods

We propose the IMPACT framework that uses XAI technique to explain a state-of-the-art tree ensemble mortality prediction model. We apply IMPACT to understand all-cause mortality for 1-, 3-, 5-, and 10-year follow-up times within the NHANES dataset, which contains 47,261 samples and 151 features.

Results

We show that IMPACT models achieve higher accuracy than linear models and neural networks. Using IMPACT, we identify several overlooked risk factors and interaction effects. Furthermore, we identify relationships between laboratory features and mortality that may suggest adjusting established reference intervals. Finally, we develop highly accurate, efficient and interpretable mortality risk scores that can be used by medical professionals and individuals without medical expertise. We ensure generalizability by performing temporal validation of the mortality risk scores and external validation of important findings with the UK Biobank dataset.

Conclusions

IMPACT’s unique strength is the explainable prediction, which provides insights into the complex, non-linear relationships between mortality and features, while maintaining high accuracy. Our explainable risk scores could help individuals improve self-awareness of their health status and help clinicians identify patients with high risk. IMPACT takes a consequential step towards bringing contemporary developments in XAI to epidemiology.
Confinement of nano-gold in 3D hierarchically structured gadolinium-doped ceria mesocrystal: synergistic effect of chemical composition and structural hierarchy in CO and propane oxidation
Authors: Woźniak Piotr , Małecka Małgorzata A. , Kraszkiewicz Piotr , Miśta Włodzimierz , Bezkrovnyi Oleksii , Chinchilla Lidia , Trasobares Susana
Published: October 2022

Gadolinium-doped ceria hierarchical gold catalyst shows four-fold TOF increase compared to undoped non-hierarchical system, proving the synergistic effect of doping and structural hierarchy in propane oxidation.
Two-dimensional β-PdSeO3 monolayer as a high-efficiency photocatalyst for solar-to-hydrogen conversion
Authors: Qiao Man , Li Yafei
Published: October 2022

The β-PdSeO3 monolayer is semiconducting with a considerable band gap and shows appropriate band edge positions for photocatalytic water splitting.
Facile synthesis of high-efficiency magnetic graphitic carbon nitride adsorbents for the selective removal of hazardous anionic dyes in wastewater
Authors: Li Anwen , Qiao Yongyao , Jiang Xu , Zhao Min , Zhao Longshan
Published: October 2022

A novel composite adsorbent was successfully prepared by a simple impregnation method. The prepared adsorbent not only exhibits ultra-efficient and selective removal of anionic dyes, but also shows excellent performance in practical water samples.
Assessing the substrate specificity of a micropollutant degrading strain: generalist or specialist?
Authors: Schittich Anna-Ricarda , McKnight Ursula S. , Stedmon Colin , Smets Barth F.
Published: October 2022

An organic micropollutant (OMP) degrader's ability to metabolize and compete for dissolved organic matter constituents might support its survival in natural aquatic environments.
Suppression of endoplasmic reticulum stress-associated pathways and hepatocyte apoptosis participates in the attenuation of betulinic acid on alcohol-provoked liver injury in mice
Authors: He Enqi , Ma Yurong , Kong Li , Huang You , Huang Chunlin , Yang Wenjiang , Yi Jine , Zhu Lijuan
Published: October 2022

BA protects against alcohol-induced liver damage through the alleviation of oxidative stress and suppression of ERS-induced apoptosis.
Propolis supplementation in obese patients with non-alcoholic fatty liver disease: effects on glucose homeostasis, lipid profile, liver function, anthropometric indices and meta-inflammation
Authors: Nikbaf-Shandiz Mahlagha , Tutunchi Helda , Khoshbaten Manuchehr , Nazari Bonab Hamideh , Ebrahimi-Mameghani Mehrangiz
Published: October 2022

Possible mechanisms of action of propolis in the management of NAFLD.
Organosulfur polymer-based cathode materials for rechargeable batteries
Authors: Ren Siyuan , Sang Pengfei , Guo Wei , Fu Yongzhu
Published: October 2022

Organosulfur polymer cathode materials have shown promising electrochemical performances in rechargeable batteries. This review covers recent developments of the polymer cathodes and the remaining challenges and future prospects are discussed.
CB[10]-driven self-assembly of a homotrimer from a symmetric organic dye: tunable multicolor fluorescence and higher solid-state stability than that of a CB[8]-included homodimer
Authors: Zhang Le-Ping , Liu Chuan-Zhi , Liu Ming , Lu Shuai , Yu Shang-Bo , Qi Qiao-Yan , Yang Guan-Yu , Li Xiaopeng , Yang Bo , Li Zhan-Ting
Published: October 2022

A symmetric organic dye can form a highly stable homotrimer in the cavity of CB[10], which exhibits unique multicolour fluorescence different from that of the single molecule or its dimer.