bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamics of Interannual Eddy Kinetic Energy Variability in the Sulawesi Sea Revealed by OFAM3
Authors: Hao Zhanjiu , Xu Zhenhua , Feng Ming , Zhang Peiwen , Yin Baoshu 
Published: August 2022

AbstractInterannual variations in eddy kinetic energy (EKE) in the Sulawesi Sea and their driving mechanisms are investigated based on the outputs of Ocean Forecasting Australia Model version 3 from 1979 to 2014. The interannual EKE variability is found to be primarily modulated by the Mindanao Current intrusion transport (MCIT). By regulating the intensity of barotropic instability of the cyclonic loop current in the Sulawesi Sea, the MCIT fluctuation leads to the downstream interannual EKE variations. Further analysis suggests that the paths of Mindanao Current (MC) and New Guinea Coastal Current and Undercurrent (NGCC/NGCUC) influence the interannual MCIT variability. During high‐EKE periods, the NGCC/NGCUC is weakened, and the MC retroflection extends to south of 5°N, which causes MCIT to increase by 0.60 Sv and strengthens the barotropic energy conversion from mean kinetic energy to EKE in the Sulawesi Sea. During low‐EKE periods, the NGCC/NGCUC is intensified whereas the MC retroflection retreats to a northernmost path, resulting in a decrease of 0.58 Sv in MCIT and thus a low EKE level. In addition, mesoscale eddies to the east of the Sulawesi Sea in the western Pacific also have an impact on the MC intrusion. This study highlights the significance of the nonlinear dynamics of western boundary currents in modulating eddy activities in the formation region of the Indonesian Throughflow.
GNSS Radio Occultation Infilling of the African Radiosonde Data Gaps Reveals Drivers of Tropopause Climate Variability
Authors: Ding Tong , Awange Joseph L. , Scherllin‐Pirscher Barbara , Kuhn Michael , Khandu  , Anyah Richard , Zerihun Ayalsew , Bui Luyen K. 
Published: August 2022

AbstractRadiosonde data are important for understanding and monitoring the upper troposphere and lower stratosphere (UTLS) region. Over much of Africa, however, such data are lacking; consequently, the African UTLS is understudied, and potential proxies such as climate models and reanalysis products fail to fully capture the behavior of the UTLS. This study pioneers the use of Global Navigation Satellite System‐Radio Occultation (GNSS‐RO) data from 2001 to 2020 to address the radiosonde data gap over Africa and contributes to a better understanding of the tropopause (TP) characteristics under the influence of global and regional climate drivers over the continent. As a first step to using GNSS‐RO for infilling the radiosonde data gap over Africa, we analyzed the performance of GNSS‐RO (2001–2020) and reanalysis products (European Centre for Medium‐Range Weather Forecasts Reanalysis 5 (ERA5) and Modern‐Era Retrospective analysis for Research and Applications version 2 (MERRA‐2)) against radiosonde observations applying the Kling‐Gupta Efficiency metric. The analyses show that GNSS‐RO data from Challenging Mini‐satellite Payload, Gravity Recovery and Climate Experiment, Meteorological Operational, Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), and COSMIC‐2 are in good agreement with radiosonde measurements with differences being smaller than 1 K in the UTLS, thereby enabling infilling of missing radiosonde data in Africa during 2001–2020. By contrast, the smoothed vertical temperature profiles of reanalysis products lead to a warm bias of +0.8 K in ERA5 and +1.2 K in MERRA‐2 and these biases alter some vertical and temporal structure details, with possible implications on climate change detection and attribution. Furthermore, the analysis of GNSS‐RO data over Africa revealed: (a) the teleconnections of El Niño‐Southern Oscillation (ENSO), Quasi‐Biennial Oscillation (QBO), Indian Ocean Dipole (IOD), Madden‐Julian Oscillation (MJO), North Atlantic Oscillation (NAO) and Southern Annular Mode (SAM) at the tropopause boundary; (b) multiple coupled global climate drivers such as ENSO‐IOD, ENSO‐MJO, ENSO‐NAO, QBO‐IOD, and ENSO‐NAO‐MJO; (c) coupled global and regional climate drivers that influence the TP variability, for example, ENSO‐Inter Tropical Convergence Zone; and (d), the deep convection associated with the Asian Summer Monsoon and Tropical/African Easterly Jet also locally influence TP height. In conclusion, this study demonstrates the capability of GNSS‐RO to fill the vast radiosonde data gap over Africa. This opens the opportunity for further detailed studies toward a better understanding of the tropopause characteristics including localization, quantification of trends, and influences of global, regional, and coupled climate drivers.
Lower pass threshold (≥93%) for critical congenital heart disease screening at high altitude prevents repeat screening and reduces false positives
Authors: Sneeringer M. Rhonda , Vadlaputi Pranjali , Lakshminrusimha Satyan , Siefkes Heather 
Published: August 2022

Abstract
Objective
We evaluated first screen pass rate for two pass thresholds for critical congenital heart disease (CCHD) oxygen saturation (SpO2) screening at higher altitude.

Study design
A retrospective cohort of 948 newborns underwent CCHD screening near sea-level (n = 463) vs 6250 ft altitude (n = 485) over 3 years. Standard SpO2 pass threshold ≥95% and lower SpO2 pass threshold ≥93% (high-altitude screen) were applied to first measurements to compare pass frequencies.

Results
The median SpO2 was lower in high-altitude newborns (96% vs 99%—p < 0.001). The high-altitude newborns passed the AAP algorithm first screen less often (89.3% vs 99.6%—p < 0.001). With the high-altitude algorithm, 98% of high-altitude newborns passed the first screen.

Conclusion
Lowering the SpO2 pass threshold by 2% at >6000 ft, significantly increased first screen pass rate. Adjustments for altitude may reduce nursing time to conduct repeat measurements and prevent transfers for echocardiograms. Larger studies are necessary to assess impact on false negatives.
Continuous pressure monitoring of inpatient spinal cord injured patients: implications for pressure ulcer development
Authors: Fryer Sarah , Caggiari Silvia , Major Denise , Bader Dan L. , Worsley Peter R. 
Published: August 2022

Abstract
Study design
Cohort observational study.

Objectives
To examine the movement profiles of individuals with spinal cord injury (SCI) during their inpatient rehabilitative phase using continuous pressure monitoring (CPM), evaluating the trends in those with skin damage.

Setting
SCI specialist rehabilitation centre in the United Kingdom.

Methods
Individuals with SCI (n = 12) were assessed using CPM in the bed and chair over a 24–72 h. Pressure data was used as a surrogate for movement using both nursing interpretation and an intelligent algorithm. Clinical features were obtained including participants age, injury level, ASIA score, co-morbidities and prescribed support surfaces. Trends between movement profiles (frequency and intervals), SCI demographics and observed skin damage were assessed using cross-tabulation and histograms.

Results
The data revealed significant correlations (p < 0.05) between the nursing observation and algorithm for predicting movement, although the algorithm was more sensitive. Individuals with high level injuries (C1-T6) were observed to have a lower frequency of movement and larger intervals between movements when compared to low level injuries (T7-L5) during both lying and sitting periods. The individuals observed to have skin damage were predominantly those who had both a low frequency of movement and extended gaps between movements.

Conclusions
Movements for pressure relief in both the bed and chair environments were dependent on the level of injury in individuals with SCI during their inpatient rehabilitation. Distinct movement patterns corresponded with those who acquired skin damage, revealing the potential clinical applications for technologies to monitor PU risk and inform personalised care.
Applying a genetic risk score for prostate cancer to men with lower urinary tract symptoms in primary care to predict prostate cancer diagnosis: a cohort study in the UK Biobank
Authors: Green Harry D. , Merriel Samuel W. D. , Oram Richard A. , Ruth Katherine S. , Tyrrell Jessica , Jones Samuel E. , Thirlwell Chrissie , Weedon Michael N. , Bailey Sarah E. R. 
Published: August 2022

Abstract
Background
Prostate cancer is highly heritable, with >250 common variants associated in genome-wide association studies. It commonly presents with non-specific lower urinary tract symptoms that are frequently associated with benign conditions.

Methods
Cohort study using UK Biobank data linked to primary care records. Participants were men with a record showing a general practice consultation for a lower urinary tract symptom. The outcome measure was prostate cancer diagnosis within 2 years of consultation. The predictor was a genetic risk score of 269 genetic variants for prostate cancer.

Results
A genetic risk score (GRS) is associated with prostate cancer in symptomatic men (OR per SD increase = 2.12 [1.86–2.41] P = 3.5e-30). An integrated risk model including age and GRS applied to symptomatic men predicted prostate cancer (AUC 0.768 [0.739–0.796]). Prostate cancer incidence was 8.1% (6.7–9.7) in the highest risk quintile. In the lowest quintile, prostate cancer incidence was <1%.

Conclusions
This study is the first to apply GRS in primary care to improve the triage of symptomatic patients. Men with the lowest genetic risk of developing prostate cancer could safely avoid invasive investigation, whilst those identified with the greatest risk could be fast-tracked for further investigation. These results show that a GRS has potential application to improve the diagnostic pathway of symptomatic patients in primary care.
A novel long noncoding RNA SP100-AS1 induces radioresistance of colorectal cancer via sponging miR-622 and stabilizing ATG3
Authors: Zhou You , Shao Yingjie , Hu Wenwei , Zhang Jinping , Shi Yufang , Kong Xiangyin , Jiang Jingting 
Published: August 2022

AbstractAlthough radiotherapy is an essential modality in the treatment of colorectal cancer (CRC), the incidence of radioresistance remains high clinically. Long noncoding RNAs (lncRNAs) reportedly play critical roles in CRC radioresistance by regulating genes or proteins at the transcriptional or post-translational levels. This study aimed to identify novel lncRNAs involved in radioresistance. We found that SP100-AS1 (lncRNA targeting antisense sequence of SP100 gene) was upregulated in radioresistant CRC patient tissues using RNA-seq analysis. Importantly, knockdown of SP100-AS1 significantly reduced radioresistance, cell proliferation, and tumor formation in vitro and in vivo. Mechanistically, mass spectrometry and bioinformatics analyses were used to identify the interacting proteins and microRNAs of SP100-AS1, respectively. Moreover, SP100-AS1 was found to interact with and stabilize ATG3 protein through the ubiquitination-dependent proteasome pathway. In addition, it could serve as a sponge for miR-622, which targeted ATG3 mRNA and affected autophagic activity. Thus, lncRNA SP100-AS1 could act as a radioresistance factor in CRC patients via RNA sponging and protein stabilizing mechanisms. In conclusion, the present study indicates that SP100-AS1/miR-622/ATG3 axis contributes to radioresistance and autophagic activity in CRC patients, suggesting it has huge prospects as a therapeutic target for improving CRC response to radiation therapy.
The role of immunomodulators in treatment-resistant depression: case studies
Authors: Beckett Charles W. , Niklison-Chirou Maria Victoria 
Published: August 2022

AbstractDepression is a common mental disorder affecting more than 264 million people worldwide. The first-line treatment for most cases of depression are selective serotonin reuptake inhibitors (SSRIs), such as sertraline, reboxetine and fluoxetine. Recently, it has been found that one-quarter of depressed patients have excessive activation of the immune system. This potentially warrants sub-categorisation of depressed patients into inflammatory and non-inflammatory subtypes. Such a sub-category of depression already exists for those not responding to various traditional antidepressants and is known as treatment-resistant depression. Those with treatment-resistant depression are far more likely to have raised inflammatory markers relative to those whose depression is treatment-responsive. Chronic, low-level inflammation seems to trigger depression via a multitude of mechanisms. These include kynurenine pathway and microglial cell activation, resulting in a reduction in hippocampal volume. Raised inflammatory cytokines also cause perturbations in monoaminergic signalling, which perhaps explains the preponderance of treatment resistance in those patients with inflammatory depression. Therefore, if treatment-resistant depression and inflammatory depression are semi-synonymous then it should follow that anti-inflammatory drugs will display high efficacy in both sub-types. Ketamine is a drug recently approved for use in depression in the USA and displays a particularly good response rate in those patients with treatment resistance. It has been suggested that the antidepressant efficacy of ketamine results from its anti-inflammatory effects. Ketamine seems to produce anti-inflammatory effects via polarisation of monocytes to M2 macrophages. Furthermore, another anti-inflammatory drug with potential use in treatment-resistant depression is Celecoxib. Celecoxib is a long-acting, selective COX-2 inhibitor. Early clinical trials show that Celecoxib has an adjuvant effect with traditional antidepressants in treatment-resistant patients. This paper highlights the importance of classifying depressed patients into inflammatory and non-inflammatory subtypes; and how this may lead to the development of more targeted treatments for treatment-resistant depression.
Ribosomal protein L22-like1 (RPL22L1) mediates sorafenib sensitivity via ERK in hepatocellular carcinoma
Authors: Zhang Dongmei , Zhou Yunzhen , Ma Yanan , Jiang Ping , Lv Hongchao , Liu Sijia , Mu Yu , Zhou Chong , Xiao Shan , Ji Guohua , Liu Peng , Zhang Ning , Sun Donglin , Sun Haiming , Wu Nan , Jin Yan 
Published: August 2022

AbstractPrecision medicine in hepatocellular carcinoma (HCC) relies on validated biomarkers that help subgroup patients for targeted treatment. Here, we identified a novel candidate oncogene, ribosomal protein L22-like1 (RPL22L1), which was markedly elevated in HCC, contributed to HCC malignancy and adverse patient survival. Functional studies indicated RPL22L1 overexpression accelerated cell proliferation, migration, invasion and sorafenib resistance. Mechanism studies revealed that RPL22L1 activated ERK to induce atypical epithelial-to-mesenchymal transition (EMT) progress. Importantly, the ERK inhibitor (ERKi) could potentiate sorafenib efficiency in RPL22L1-high HCC cells. In summary, these data uncover RPL22L1 is a potential marker to guide precision therapy for utilizing ERKi to enhance the sorafenib efficacy in RPL22L1-high HCC patients.
Emergent hypernetworks in weakly coupled oscillators
Authors: Nijholt Eddie , Ocampo-Espindola Jorge Luis , Eroglu Deniz , Kiss István Z. , Pereira Tiago 
Published: August 2022

AbstractNetworks of weakly coupled oscillators had a profound impact on our understanding of complex systems. Studies on model reconstruction from data have shown prevalent contributions from hypernetworks with triplet and higher interactions among oscillators, in spite that such models were originally defined as oscillator networks with pairwise interactions. Here, we show that hypernetworks can spontaneously emerge even in the presence of pairwise albeit nonlinear coupling given certain triplet frequency resonance conditions. The results are demonstrated in experiments with electrochemical oscillators and in simulations with integrate-and-fire neurons. By developing a comprehensive theory, we uncover the mechanism for emergent hypernetworks by identifying appearing and forbidden frequency resonant conditions. Furthermore, it is shown that microscopic linear (difference) coupling among units results in coupled mean fields, which have sufficient nonlinearity to facilitate hypernetworks. Our findings shed light on the apparent abundance of hypernetworks and provide a constructive way to predict and engineer their emergence.
The origin and evolution of open habitats in North America inferred by Bayesian deep learning models
Authors: Andermann Tobias , Strömberg Caroline A. E. , Antonelli Alexandre , Silvestro Daniele 
Published: August 2022

AbstractSome of the most extensive terrestrial biomes today consist of open vegetation, including temperate grasslands and tropical savannas. These biomes originated relatively recently in Earth’s history, likely replacing forested habitats in the second half of the Cenozoic. However, the timing of their origination and expansion remains disputed. Here, we present a Bayesian deep learning model that utilizes information from fossil evidence, geologic models, and paleoclimatic proxies to reconstruct paleovegetation, placing the emergence of open habitats in North America at around 23 million years ago. By the time of the onset of the Quaternary glacial cycles, open habitats were covering more than 30% of North America and were expanding at peak rates, to eventually become the most prominent natural vegetation type today. Our entirely data-driven approach demonstrates how deep learning can harness unexplored signals from complex data sets to provide insights into the evolution of Earth’s biomes in time and space.
AAA + ATPase Thorase inhibits mTOR signaling through the disassembly of the mTOR complex 1
Authors: Umanah George K. E. , Abalde-Atristain Leire , Khan Mohammed Repon , Mitra Jaba , Dar Mohamad Aasif , Chang Melissa , Tangella Kavya , McNamara Amy , Bennett Samuel , Chen Rong , Aggarwal Vasudha , Cortes Marisol , Worley Paul F. , Ha Taekjip , Dawson Ted M. , Dawson Valina L. 
Published: August 2022

AbstractThe mechanistic target of rapamycin (mTOR) signals through the mTOR complex 1 (mTORC1) and the mTOR complex 2 to maintain cellular and organismal homeostasis. Failure to finely tune mTOR activity results in metabolic dysregulation and disease. While there is substantial understanding of the molecular events leading mTORC1 activation at the lysosome, remarkably little is known about what terminates mTORC1 signaling. Here, we show that the AAA + ATPase Thorase directly binds mTOR, thereby orchestrating the disassembly and inactivation of mTORC1. Thorase disrupts the association of mTOR to Raptor at the mitochondria-lysosome interface and this action is sensitive to amino acids. Lack of Thorase causes accumulation of mTOR-Raptor complexes and altered mTORC1 disassembly/re-assembly dynamics upon changes in amino acid availability. The resulting excessive mTORC1 can be counteracted with rapamycin in vitro and in vivo. Collectively, we reveal Thorase as a key component of the mTOR pathway that disassembles and thus inhibits mTORC1.
High impact of bacterial predation on cyanobacteria in soil biocrusts
Authors: Bethany Julie , Johnson Shannon Lynn , Garcia-Pichel Ferran 
Published: August 2022

AbstractDiverse bacteria lead a life as pathogens or predators of other bacteria in many environments. However, their impact on emerging ecological processes in natural settings remains to be assessed. Here we describe a novel type of obligate, intracellular predatory bacterium of widespread distribution that preys on soil cyanobacteria in biocrusts. The predator,CandidatusCyanoraptor togatus, causes localized, cm-sized epidemics that are visible to the naked eye, obliterates cyanobacterial net primary productivity, and severely impacts crucial biocrust properties like nitrogen cycling, dust trapping and moisture retention. The combined effects of high localized morbidity and areal incidence result in decreases approaching 10% of biocrust productivity at the ecosystem scale. Our findings show that bacterial predation can be an important loss factor shaping not only the structure but also the function of microbial communities.
Direct control of lysosomal catabolic activity by mTORC1 through regulation of V-ATPase assembly
Authors: Ratto Edoardo , Chowdhury S. Roy , Siefert Nora S. , Schneider Martin , Wittmann Marten , Helm Dominic , Palm Wilhelm 
Published: August 2022

AbstractMammalian cells can acquire exogenous amino acids through endocytosis and lysosomal catabolism of extracellular proteins. In amino acid-replete environments, nutritional utilization of extracellular proteins is suppressed by the amino acid sensor mechanistic target of rapamycin complex 1 (mTORC1) through an unknown process. Here, we show that mTORC1 blocks lysosomal degradation of extracellular proteins by suppressing V-ATPase-mediated acidification of lysosomes. When mTORC1 is active, peripheral V-ATPase V1domains reside in the cytosol where they are stabilized by association with the chaperonin TRiC. Consequently, most lysosomes display low catabolic activity. When mTORC1 activity declines, V-ATPase V1domains move to membrane-integral V-ATPase Vodomains at lysosomes to assemble active proton pumps. The resulting drop in luminal pH increases protease activity and degradation of protein contents throughout the lysosomal population. These results uncover a principle by which cells rapidly respond to changes in their nutrient environment by mobilizing the latent catabolic capacity of lysosomes.
Experimental exploration of a ribozyme neutral network using evolutionary algorithm and deep learning
Authors: Rotrattanadumrong Rachapun , Yokobayashi Yohei 
Published: August 2022

AbstractA neutral network connects all genotypes with equivalent phenotypes in a fitness landscape and plays an important role in the mutational robustness and evolvability of biomolecules. In contrast to earlier theoretical works, evidence of large neutral networks has been lacking in recent experimental studies of fitness landscapes. This suggests that evolution could be constrained globally. Here, we demonstrate that a deep learning-guided evolutionary algorithm can efficiently identify neutral genotypes within the sequence space of an RNA ligase ribozyme. Furthermore, we measure the activities of all 216 variants connecting two active ribozymes that differ by 16 mutations and analyze mutational interactions (epistasis) up to the 16th order. We discover an extensive network of neutral paths linking the two genotypes and reveal that these paths might be predicted using only information from lower-order interactions. Our experimental evaluation of over 120,000 ribozyme sequences provides important empirical evidence that neutral networks can increase the accessibility and predictability of the fitness landscape.
Structural basis for proton coupled cystine transport by cystinosin
Authors: Löbel Mark , Salphati Sacha P. , El Omari Kamel , Wagner Armin , Tucker Stephen J. , Parker Joanne L. , Newstead Simon 
Published: August 2022

AbstractAmino acid transporters play a key role controlling the flow of nutrients across the lysosomal membrane and regulating metabolism in the cell. Mutations in the gene encoding the transporter cystinosin result in cystinosis, an autosomal recessive metabolic disorder characterised by the accumulation of cystine crystals in the lysosome. Cystinosin is a member of the PQ-loop family of solute carrier (SLC) transporters and uses the proton gradient to drive cystine export into the cytoplasm. However, the molecular basis for cystinosin function remains elusive, hampering efforts to develop novel treatments for cystinosis and understand the mechanisms of ion driven transport in the PQ-loop family. To address these questions, we present the crystal structures of cystinosin from Arabidopsis thaliana in both apo and cystine bound states. Using a combination of in vitro and in vivo based assays, we establish a mechanism for cystine recognition and proton coupled transport. Mutational mapping and functional characterisation of human cystinosin further provide a framework for understanding the molecular impact of disease-causing mutations.