bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mitochondrial damage and activation of the cytosolic DNA sensor cGAS–STING pathway lead to cardiac pyroptosis and hypertrophy in diabetic cardiomyopathy mice
Authors: Yan Meiling , Li Yun , Luo Qingmao , Zeng Wenru , Shao Xiaoqi , Li Lun , Wang Qing , Wang Dongwei , Zhang Yue , Diao Hongtao , Rong Xianglu , Bai Yunlong , Guo Jiao 
Published: May 2022

AbstractDiabetic cardiomyopathy (DCM) is a serious cardiac complication of diabetes that currently lacks specific treatment. The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway has been suggested to contribute to the pathogenesis of cardiovascular diseases. However, whether cGAS-STING is involved in the development of DCM has not been established. Our study aimed to determine the role of cGAS-STING in the initiation of nucleotide-binding oligomerization domain-like receptor pyrin domain containing 3 (NLRP3) inflammasome-induced cardiac pyroptosis and chronic inflammation during the pathogenesis of DCM. C57BL/6J mice were preinjected with adeno-associated virus 9 (AAV9) intravenously via the tail vein to specifically knock down myocardial STING. After four weeks, mice with myocardium-specific knockdown of STING received injections of streptozotocin (STZ; 50 mg/kg) and a high-fat diet to induce diabetes. Measurements included echocardiography, immunohistochemical analyses, wheat germ agglutinin (WGA) staining, and western blotting. Here, we showed that the cGAS-STING signaling pathway was activated in diabetic hearts, which was indicated by the increased phosphorylation of TANK-binding kinase 1 (TBK1) and interferon (IFN) regulatory factor 3 (IRF3), leading to the activation of the NLRP3 inflammasome in the hearts of diabetic mice and proinflammatory cytokine release into serum. Moreover, STING knockdown via adeno-associated virus-9 (AAV9) in diabetic mouse heart alleviated cardiac pyroptosis and the inflammatory response, prevented diabetes-induced hypertrophy, and restored cardiac function. Mechanistically, we showed that palmitic acid (PA)-induced lipotoxicity impairs mitochondrial homeostasis, producing excessive mitochondrial reactive oxygen species (mtROS), which results in oxidative damage to mitochondrial DNA (mtDNA) and its release into the cytoplasm while switching on cGAS-STING-mediated pyroptosis in cardiomyocytes, thereby worsening the progression of diabetic cardiomyopathy. Our study demonstrated that activation of the cGAS-STING pathway caused by mitochondrial oxidative damage and mtDNA escape induced by free fatty acids promoted pyroptosis and proinflammatory responses in cardiomyocytes in a NLRP3 inflammasome-dependent manner, thus promoting myocardial hypertrophy during the progression of DCM.
Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits
Authors: Choudhury Ananyo , Brandenburg Jean-Tristan , Chikowore Tinashe , Sengupta Dhriti , Boua Palwende Romuald , Crowther Nigel J. , Agongo Godfred , Asiki Gershim , Gómez-Olivé F. Xavier , Kisiangani Isaac , Maimela Eric , Masemola-Maphutha Matshane , Micklesfield Lisa K. , Nonterah Engelbert A. , Norris Shane A. , Sorgho Hermann , Tinto Halidou , Tollman Stephen , Graham Sarah E. , Willer Cristen J. ,   AWI-Gen study,   H3Africa Consortium, Hazelhurst Scott , Ramsay Michèle 
Published: May 2022

AbstractGenetic associations for lipid traits have identified hundreds of variants with clear differences across European, Asian and African studies. Based on a sub-Saharan-African GWAS for lipid traits in the population cross-sectional AWI-Gen cohort (N = 10,603) we report a novel LDL-C association in theGATBregion (P-value=1.56 × 10−8). Meta-analysis with four other African cohorts (N = 23,718) provides supporting evidence for the LDL-C association with theGATB/FHIP1Aregion and identifies a novel triglyceride association signal close to theFHITgene (P-value =2.66 × 10−8). Our data enable fine-mapping of several well-known lipid-trait loci includingLDLR, PMFBP1andLPA. The transferability of signals detected in two large global studies (GLGC and PAGE) consistently improves with an increase in the size of the African replication cohort. Polygenic risk score analysis shows increased predictive accuracy for LDL-C levels with the narrowing of genetic distance between the discovery dataset and our cohort. Novel discovery is enhanced with the inclusion of African data.
Observation of spin-current striction in a magnet
Authors: Arisawa Hiroki , Shim Hang , Daimon Shunsuke , Kikkawa Takashi , Oikawa Yasuyuki , Takahashi Saburo , Ono Takahito , Saitoh Eiji 
Published: May 2022

AbstractThe interplay among magnetization and deformation of solids has long been an important issue in magnetism, the elucidation of which has made great progress in material physics. Controlling volume and shapes of matter is now indispensable to realizing various actuators for precision machinery and nanotechnology. Here, we show that the volume of a solid can be manipulated by injecting a spin current: a spin current volume effect (SVE). By using a magnet Tb0.3Dy0.7Fe2 exhibiting strong spin-lattice coupling, we demonstrate that the sample volume changes in response to a spin current injected by spin Hall effects. Theoretical calculation reflecting spin-current induced modulation of magnetization fluctuation well reproduces the experimental results. The SVE expands the scope of spintronics into making mechanical drivers.
Efficient preparation of unsymmetrical disulfides by nickel-catalyzed reductive coupling strategy
Authors: Wang Fei , Chen Ying , Rao Weidong , Ackermann Lutz , Wang Shun-Yi 
Published: May 2022

AbstractDisulfides are widely found in natural products and find a wide range of applications in life sciences, materials chemistry and other fields. The preparation of disulfides mainly rely on oxidative couplings of two sulfur containing compounds. This strategy has many side reactions and other shortcomings. Herein, we describe the reductive nickel-catalyzed cross-electrophile coupling of unactivated alkyl bromides with symmetrical alkyl- and aryltetrasulfides to form alkyl-alkyl and aryl-alkyl unsymmetrical disulfides. This approach for disulfide synthesis is practical, relies on easily available, unfunctionalized substrates, and is scalable. We investigated the mechanism of this transformation and found that the tetrasulfide compound does not selectively break the central S–S bond, but regio-selectively generates trisulfide intermediates.
Neural sampling machine with stochastic synapse allows brain-like learning and inference
Authors: Dutta Sourav , Detorakis Georgios , Khanna Abhishek , Grisafe Benjamin , Neftci Emre , Datta Suman 
Published: May 2022

AbstractMany real-world mission-critical applications require continual online learning from noisy data and real-time decision making with a defined confidence level. Brain-inspired probabilistic models of neural network can explicitly handle the uncertainty in data and allow adaptive learning on the fly. However, their implementation in a compact, low-power hardware remains a challenge. In this work, we introduce a novel hardware fabric that can implement a new class of stochastic neural network called Neural Sampling Machine (NSM) by exploiting the stochasticity in the synaptic connections for approximate Bayesian inference. We experimentally demonstrate an in silico hybrid stochastic synapse by pairing a ferroelectric field-effect transistor (FeFET)-based analog weight cell with a two-terminal stochastic selector element. We show that the stochastic switching characteristic of the selector between the insulator and the metallic states resembles the multiplicative synaptic noise of the NSM. We perform network-level simulations to highlight the salient features offered by the stochastic NSM such as performing autonomous weight normalization for continual online learning and Bayesian inferencing. We show that the stochastic NSM can not only perform highly accurate image classification with 98.25% accuracy on standard MNIST dataset, but also estimate the uncertainty in prediction (measured in terms of the entropy of prediction) when the digits of the MNIST dataset are rotated. Building such a probabilistic hardware platform that can support neuroscience inspired models can enhance the learning and inference capability of the current artificial intelligence (AI).
Translaminar recurrence from layer 5 suppresses superficial cortical layers
Authors: Onodera Koun , Kato Hiroyuki K. 
Published: May 2022

AbstractInformation flow in the sensory cortex has been described as a predominantly feedforward sequence with deep layers as the output structure. Although recurrent excitatory projections from layer 5 (L5) to superficial L2/3 have been identified by anatomical and physiological studies, their functional impact on sensory processing remains unclear. Here, we use layer-selective optogenetic manipulations in the primary auditory cortex to demonstrate that feedback inputs from L5 suppress the activity of superficial layers regardless of the arousal level, contrary to the prediction from their excitatory connectivity. This suppressive effect is predominantly mediated by translaminar circuitry through intratelencephalic neurons, with an additional contribution of subcortical projections by pyramidal tract neurons. Furthermore, L5 activation sharpened tone-evoked responses of superficial layers in both frequency and time domains, indicating its impact on cortical spectro-temporal integration. Together, our findings establish a translaminar inhibitory recurrence from deep layers that sharpens feature selectivity in superficial cortical layers.
Activation of Xist by an evolutionarily conserved function of KDM5C demethylase
Authors: Samanta Milan Kumar , Gayen Srimonta , Harris Clair , Maclary Emily , Murata-Nakamura Yumie , Malcore Rebecca M. , Porter Robert S. , Garay Patricia M. , Vallianatos Christina N. , Samollow Paul B. , Iwase Shigeki , Kalantry Sundeep 
Published: May 2022

AbstractXXfemale andXYmale therian mammals equalize X-linked gene expression through the mitotically-stable transcriptional inactivation of one of the two X chromosomes in female somatic cells. Here, we describe an essential function of the X-linked homolog of an ancestral X-Y gene pair,Kdm5c-Kdm5d, in the expression of Xist lncRNA, which is required for stable X-inactivation. Ablation ofKdm5cfunction in females results in a significant reduction in Xist RNA expression.Kdm5cencodes a demethylase that enhancesXistexpression by converting histone H3K4me2/3 modifications into H3K4me1. Ectopic expression of mouse and humanKDM5C, but not the Y-linked homologKDM5D, inducesXistin male mouse embryonic stem cells (mESCs). Similarly, marsupial (opossum)Kdm5cbut notKdm5dalso upregulatesXistin male mESCs, despite marsupials lackingXist, suggesting that the KDM5C function that activatesXistin eutherians is strongly conserved and predates the divergence of eutherian and metatherian mammals. In support, prototherian (platypus)Kdm5calso inducesXistin male mESCs. Together, our data suggest that eutherian mammals co-opted the ancestral demethylase KDM5C during sex chromosome evolution to upregulateXistfor the female-specific induction of X-inactivation.
Effects of Alzheimer’s genetic risk scores and CSF biomarkers in de novo Parkinson’s Disease
Authors: Lee Young-gun , Jeong Seong Ho , Park Mincheol , Kang Sung Woo , Baik Kyoungwon , Jeon Seun , Lee Phil Hyu , Sohn Young Ho , Ye Byoung Seok 
Published: May 2022

AbstractCoexisting Alzheimer’s disease (AD) pathology is common in Parkinson’s disease (PD). However, the implications of genetic risk scores (GRS) for AD have not been elucidated in PD. In 413 de novo PD and 195 healthy controls from the Parkinson’s Progression Marker Initiative database, the effects of GRS for AD (GRS-AD) and PD (GRS-PD) on the risk of PD and longitudinal CSF biomarkers and clinical outcomes were explored. Higher GRS-PD and lower baseline CSF α-synuclein were associated with an increased risk of PD. In the PD group, GRS-AD was correlated positively with CSF p-tau/Aβ and negatively with CSF α-synuclein. Higher GRS-PD was associated with faster CSF p-tau/Aβ increase, and GRS-AD and GRS-PD were interactively associated with CSF α-synuclein. In the PD group, higher GRS-AD was associated with poor visuospatial function, and baseline CSF p-tau/Aβ was associated with faster cognitive decline. Higher GRS-PD was associated with better semantic fluency and frontal-related cognition and motor function given the same levels of CSF biomarkers and dopamine transporter uptake. Taken together, our results suggest that higher GRS-AD and CSF p-tau/Aβ, reflecting AD-related pathophysiology, may be associated with cognitive decline in PD patients.
Mechanisms of peripheral levodopa resistance in Parkinson’s disease
Authors: Beckers Milan , Bloem Bastiaan R. , Verbeek Marcel M. 
Published: May 2022

AbstractParkinson’s disease (PD) is an increasingly common neurodegenerative condition. The disease has a significant negative impact on quality of life, but a personalized management approach can help reduce disability. Pharmacotherapy with levodopa remains the cornerstone of treatment, and a gratifying and sustained response to this treatment is a supportive criterion that argues in favor of an underlying diagnosis of PD. Yet, in daily practice, it is not uncommon to encounter patients who appear to have true PD, but who nevertheless seem to lose the responsiveness to levodopa (secondary non-responders). Some patients may even fail to respond altogether (primary non-responders). Here, we address how two mechanisms of “peripheral resistance” may underlie this failing response to levodopa in persons with PD. The first explanation relates to impaired bowel motility leading to secondary bacterial overgrowth, and more specifically, to the excessive bacterial production of the enzyme tyrosine decarboxylase (TDC). This enzyme may convert levodopa to dopamine in the gut, thereby hampering entry into the circulation and, subsequently, into the brain. The second explanation relates to the systemic induction of the enzyme aromatic l-amino acid decarboxylase (AADC), leading to premature conversion of levodopa into dopamine, again limiting the bioavailability within the brain. We discuss these two mechanisms and focus on the clinical implications, potential treatments and directions for future research.
Using machine learning to predict COVID-19 infection and severity risk among 4510 aged adults: a UK Biobank cohort study
Authors: Willette Auriel A. , Willette Sara A. , Wang Qian , Pappas Colleen , Klinedinst Brandon S. , Le Scott , Larsen Brittany , Pollpeter Amy , Li Tianqi , Mochel Jonathan P. , Allenspach Karin , Brenner Nicole , Waterboer Tim 
Published: May 2022

AbstractMany risk factors have emerged for novel 2019 coronavirus disease (COVID-19). It is relatively unknown how these factors collectively predict COVID-19 infection risk, as well as risk for a severe infection (i.e., hospitalization). Among aged adults (69.3 ± 8.6 years) in UK Biobank, COVID-19 data was downloaded for 4510 participants with 7539 test cases. We downloaded baseline data from 10 to 14 years ago, including demographics, biochemistry, body mass, and other factors, as well as antibody titers for 20 common to rare infectious diseases in a subset of 80 participants with 124 test cases. Permutation-based linear discriminant analysis was used to predict COVID-19 risk and hospitalization risk. Probability and threshold metrics included receiver operating characteristic curves to derive area under the curve (AUC), specificity, sensitivity, and quadratic mean. Model predictions using the full cohort were marginal. The “best-fit” model for predicting COVID-19 risk was found in the subset of participants with antibody titers, which achieved excellent discrimination (AUC 0.969, 95% CI 0.934–1.000). Factors included age, immune markers, lipids, and serology titers to common pathogens like human cytomegalovirus. The hospitalization “best-fit” model was more modest (AUC 0.803, 95% CI 0.663–0.943) and included only serology titers, again in the subset group. Accurate risk profiles can be created using standard self-report and biomedical data collected in public health and medical settings. It is also worthwhile to further investigate if prior host immunity predicts current host immunity to COVID-19.
Spatiotemporal characteristics of ground microtremor in advance of rockfalls
Authors: Yang Yi-Rong , Lee Tzu-Tung , Wang Tai-Tien 
Published: May 2022

AbstractIdentifying cliffs that are prone to fall and providing a sufficient lead time for rockfall warning are crucial steps in disaster risk reduction and preventive maintenance work, especially that led by local governments. However, existing rockfall warning systems provide uncertain rockfall location forecasting and short warning times because the deformation and cracking of unstable slopes are not sufficiently detected by sensors before the rock collapses. Here, we introduce ground microtremor signals for early rockfall forecasting and demonstrate that microtremor characteristics can be used to detect unstable rock wedges on slopes, quantitatively describe the stability of slopes and lengthen the lead time for rockfall warning. We show that the change in the energy of ground microtremors can be an early precursor of rockfall and that the signal frequency decreases with slope instability. This finding indicates that ground microtremor signals are remarkably sensitive to slope stability. We conclude that microtremor characteristics can be used as an appropriate slope stability index for early rockfall warning systems and predicting the spatiotemporal characteristics of rockfall hazards. This early warning method has the advantages of providing a long lead time and on-demand monitoring, while increasing slope stability accessibility and prefailure location detectability.
Regression-based gap-filling methods show air temperature reductions and wind pattern changes during the 2019 total eclipse in Chile
Authors: Hammann Arno C. , MacDonell Shelley 
Published: May 2022

AbstractSingular disruptive events like solar eclipses affect the measured values of meteorological variables at the earth’s surface. To quantify such an impact, it is necessary to estimate what value the parameter would have taken had the event not occurred. We design and compare several methods to perform such an estimate based on longer observational timeseries from individual meteorological surface stations. Our methods are based on regularised regressions (including a Bayesian variant) and provide both a point an associated error estimate of the disruptive event’s impact. With their help, we study the effect of the total solar eclipse of July 2nd, 2019, in the Coquimbo Region of Chile, on near-surface air temperatures and winds. The observational data used have been collected by the meteorological surface station network of the Centro de Estudios Avanzados en Zonas Áridas (CEAZA). Most stations inside the eclipse’s umbra registered a temperature drop of 1–2 $$^{\circ }$$

∘

C, while the most extreme estimated temperature drop surpassed 6 $$^{\circ }$$

∘

C. The presence of an ‘eclipse cyclone’ can neither be proven nor refuted. Application of the regression methods to other comparable problems like volcanic eruptions, forest fires, or simply gap filling of observational data, are conceivable.
The nasal microbiome of predicting bronchopulmonary dysplasia in preterm infants
Authors: Xu Yanping , Huang Yeqing , Shen Zhen , Shi Liping 
Published: May 2022

AbstractBronchopulmonary dysplasia (BPD) is a chronic lung disease of prematurity and may cause substantial long-term disabilities. To characterize and compare the nasal swabs microbiome of early stage in premature infants and determine whether microbial diversity or composition in the nostrils associated with BPD disease. We performed a prospective observational cohort design. Preterm neonates less than or equal to 30 weeks of gestation were recruited from NICU, Children's Hospital, Zhejiang University School of Medicine from 2019 to 2020. Sterile foam swabs were collected from anterior nares at 1 and 3 weeks of postnatal age. We used PCR amplification and 16S rDNA sequencing. Neonatal demographic data including gestational age, birth weight, medication administration history and discharge outcomes were recorded. A total of 49 nasal swab samples were collected from 28 premature infants. Thirteen infants with BPD and 15 controls were finally involved in the study. Birth weights ranged from 700 to 1550 g. Gestational age ranged from 252/7 to 30. We found increased in the expression of Prevotella and decreased of Caulobacter in BPD group at both times. Prevotella and Caulobacter were correlated with the severity of BPD (Spearman r = 0.551, r = − 0.545; P = 0.00005, 0.00006; respectively). Receiver operating characteristic analysis showed that the area under characteristic curve of Caulobacter model at first week reached 0.821 and Prevotella model at third week was 0.796. Moreover, microbial functional prediction analysis revealed that ABC-type transports were distinctively changed in BPD group. In summary, the use of non-invasive nasal swabs of microbiome to explore the pathophysiology in BPD is a compelling method worthy continuing to expand and research.
Modern aridity in the Altai-Sayan mountain range derived from multiple millennial proxies
Authors: Churakova-Sidorova Olga V. , Myglan Vladimir S. , Fonti Marina V. , Naumova Oksana V. , Kirdyanov Alexander V. , Kalugin Ivan A. , Babich Valery V. , Falster Georgina M. , Vaganov Eugene A. , Siegwolf Rolf T. W. , Saurer Matthias 
Published: May 2022

AbstractTemperature and precipitation changes are crucial for larch trees growing at high-elevation sites covered by permafrost in the Altai-Sayan mountain range (ASMR). To contextualize the amplitude of recent climate fluctuations, we have to look into the past by analyzing millennial paleoclimatic archives recording both temperature and precipitation. We developed annually resolved 1500-year tree-ring cellulose chronologies (δ13Ccell, δ18Ocell), and used these new records to reconstruct the variability in local summer precipitation and air temperature. We combined our new local reconstructions with existing paleoclimatic archives available for the Altai. The data show a strong decreasing trend by ca. 49% in regional summer precipitation, along with a regional summer temperature increase towards the twenty-first century, relative to the preceding 1500 years. Modern dry conditions (1966–2016 CE) in the ASMR are the result of simultaneous summer warming and decreased precipitation. Our new reconstructions also demonstrate that climate change in the ASMR is much stronger compared to the global average.