bluuebunny/crossref_metadata_2025 huggingface dataset:
A Global Survey of Lithospheric Flexure at Steep‐Sided Domical Volcanoes on Venus Reveals Intermediate Elastic Thicknesses
Authors: Borrelli M. E. , O'Rourke J. G. , Smrekar S. E. , Ostberg C. M.
Published: July 2021

Topographic flexure in response to vertical loads reveals key lithospheric properties, including elastic thickness and the heat flow from the interior. Flexural stresses that depend on elastic thickness may in turn control volcano morphology. One previous study predicted that steep‐sided domes on Venus usually form where the elastic thickness is ∼15–40 km. Coronae and large volcanoes may typically form at regions with lower and higher elastic thickness, respectively. We surveyed flexural signatures around steep‐sided domes and confirmed this hypothesis. Specifically, we extracted radial profiles of topography from Magellan altimetry data and a new elevation model derived from stereo images. Nearly 20% of the identifiable domes had topographic profiles that were amenable to flexural interpretations. We determined elastic thicknesses using a curve‐fitting algorithm and plate bending models that treat each volcano as either a Cartesian line load or an axisymmetric disc load. We used a yield strength envelope featuring brittle failure and ductile flow at the top and bottom of the lithosphere, respectively, to convert elastic thickness into mechanical thickness and surface heat flow. The average elastic thickness for domes not near coronae is ∼30 km, corresponding to a heat flow of ∼60 mW/m2. Coronae on Venus are typically associated with elastic thicknesses of <10–15 km. Domes near coronae yielded elastic thicknesses in that range, and higher heat flows than domes not near coronae. Ultimately, flexural signatures are probably abundant around volcanic and tectonic features and would be further revealed in higher‐resolution topographic data.
Effects of Row Spaces on Windproof Effectiveness of Simulated Shrubs With Different Form Configurations
Authors: Pan Xia , Wang Zhenyi , Gao Yong , Dang Xiaohong
Published: July 2021

A better understanding of the distribution of the airflow field and wind velocity around the simulated shrubs is essential to provide optimized design and maximize the windproof efficiency of the wind barriers. In this study, a profiling set of Pitot Tubes was used to measure the airflow field and wind velocity of simulated shrubs by wind tunnel simulation. The effects of form configurations and row spaces of simulated shrubs on windproof effectiveness were in‐depth analyzed. We come to the following results: The weakening strength to wind velocities of hemisphere‐shaped and broom‐shaped shrubs at 26.25 cm was mainly concentrated below 2 cm near the basal and 6–14 cm in the middle‐upper part, while the spindle‐shaped shrubs were at 0.2–14 cm above the canopy, which meant the windproof effect of spindle‐shaped shrubs was better than that of hemisphere‐shaped and broom‐shaped. With the improvement of row spaces, the weakening height to wind velocities of the hemisphere‐shaped shrubs at 35 cm was concentrated below 2 cm except for the 6–14 cm at 26.25 cm. The designed windbreaks with Nitraria tangutorum, which reduced the wind velocity among the windbreaks more effectively compared to behind the windbreaks. In the wind control system of Ulan Buh Desert, the hemisphere‐shaped windbreak should be applied as near‐surface barriers, and the windbreaks of broom‐shaped and spindle‐shaped can be used as shelterbelts above the near‐surface. These analytical findings can offer theoretical guidelines on how to arrange the wind barriers for preventing wind erosion in the most convenient and efficient ways.
Correcting Weather and Climate Models by Machine Learning Nudged Historical Simulations
Authors: Watt‐Meyer Oliver , Brenowitz Noah D. , Clark Spencer K. , Henn Brian , Kwa Anna , McGibbon Jeremy , Perkins W. Andre , Bretherton Christopher S.
Published: July 2021

Due to limited resolution and inaccurate physical parameterizations, weather and climate models consistently develop biases compared to the observed atmosphere. Using the FV3GFS model at coarse resolution, we propose a method of machine learning corrective tendencies from a hindcast simulation nudged toward observational analysis. We show that a random forest can predict the nudging tendencies from this hindcast simulation with moderate skill using only the model state as input. This random forest is then coupled to FV3GFS, adding corrective tendencies of temperature, specific humidity and horizontal winds at each timestep. The coupled model shows no signs of instability in year‐long simulations and has significant reductions in short‐term forecast error for 500 hPa height, surface pressure and near‐surface temperature. Furthermore, the root mean square error of the annual‐mean precipitation is reduced by about 20%. Biases of other variables remain similar or in some cases, like upper‐atmospheric temperature, increase in the year‐long simulations.
Resolved Convection Improves the Representation of Equatorial Waves and Tropical Rainfall Variability in a Global Nonhydrostatic Model
Authors: Judt Falko , Rios‐Berrios Rosimar
Published: July 2021

Numerical weather and climate models continue to struggle with simulating equatorial waves and tropical rainfall variability. This study presents a potential remedy—high‐resolution global models with explicitly resolved convection. A series of global nonhydrostatic simulations was produced with horizontal cell spacings between 3.75 and 480 km; the share of resolved precipitation in these simulations ranged from 88% to 2%. The simulations in which convection was mostly resolved produced much more realistic equatorial waves than the simulations in which convection was mostly parameterized. Consequently, the simulations with resolved convection produced more realistic precipitation patterns and precipitation variances. The results demonstrate that high‐resolution global models with explicitly resolved convection are a promising tool to improve tropical weather forecasts and climate projections.
Limits on Runoff Episode Duration for Early Mars: Integrating Lake Hydrology and Climate Models
Authors: Stucky de Quay Gaia , Goudge Timothy A. , Kite Edwin S. , Fassett Caleb I. , Guzewich Scott D.
Published: July 2021

Fluvio‐lacustrine features on the martian surface attest to a climate that was radically different in the past. Since climate models have difficulty sustaining a liquid hydrosphere at the surface, multiple cycles of runoff episodes may have characterized the ancient Mars climate. A fundamental question thus remains: what was the duration of these runoff‐producing episodes? Here we use morphometric measurements from newly identified coupled lake systems, containing both an open‐ and a closed‐basin lake (n = 7). We combined hydrological balances with precipitation outputs from climate models, and found that breaching runoff episodes likely lasted yr; other episodes may have been shorter but could not be longer. Runoff episode durations are model‐dependent and spatially variable, and no climate model scenario can satisfy a unique duration for all coupled systems. In the near future, these quantitative constraints on early Mars lake persistence may be tested through in situ observations from Perseverance rover.
Distinct Onset Mechanisms of Two Subtypes of CP El Niño and Their Changes in Future Warming
Authors: Chen Mengyan , Yu Jin‐Yi , Wang Xin , Chen Sheng
Published: July 2021

This study analyzes two subtypes of Central Pacific (CP) El Niño and shows that they possess different sea surface temperature evolution patterns in the Indo‐Pacific Oceans, distinct generation mechanisms, and can respond differently to global warming. The CP‐I type is triggered in the tropical western Pacific by the weaker‐than‐normal Australian winter monsoon (AM) through a subsurface thermocline mechanism and is accompanied by significant Indian Ocean warming. The CP‐II type onsets in the subtropical North Pacific by the Pacific Meridional Mode (PMM) through a surface coupling mechanism and is accompanied by weak warming anomalies in the Indian Ocean. Two climate models projections indicate that the CP‐II type may occur more frequently than the CP‐I type in the future due to changes in PMM and AM activities, which should weaken El Niño influences on the Indian Ocean and result in more El Niño events that onset from the North American coast.
Mapping Forest Height and Aboveground Biomass by Integrating ICESat‐2, Sentinel‐1 and Sentinel‐2 Data Using Random Forest Algorithm in Northwest Himalayan Foothills of India
Authors: Nandy Subrata , Srinet Ritika , Padalia Hitendra
Published: July 2021

The present study aims to map forest canopy height by integrating ICESat‐2 and Sentinel‐1 data and investigate the effect of integrating forest canopy height information with Sentinel‐2 data‐derived spectral variables on the prediction of spatial distribution of forest aboveground biomass (AGB). Random forest (RF) algorithm was used to develop forest canopy height and AGB models. It was observed that ICESat‐2 and Sentinel‐1 based model was able to predict forest canopy height with R2 = 0.84 and %RMSE = 4.48%. Two forest AGB models were developed, with only spectral variables and by incorporating forest height information with spectral variables. The results reflected that incorporation of forest canopy height in the forest AGB model improved the accuracy of the AGB predictions (R2 = 0.83, %RMSE = 4.64%). The study presents a comprehensive methodology for mapping forest canopy height and AGB.
Different Trends in Antarctic Temperature and Atmospheric CO2 During the Last Glacial
Authors: Zheng Peisong , Pedro Joel B. , Jochum Markus , Rasmussen Sune O. , Lai Zhongping
Published: July 2021

We analyze the past 67,000 years of climate using Antarctic ice‐core records to constrain the mechanisms involved in (a) the “bipolar seesaw” relationship between Greenland and Antarctic surface temperature variations, and (b) mechanisms of millennial‐scale atmospheric CO2 concentration variations. Specifically, we determine for each Greenland Stadial the rate of Antarctic temperature and atmospheric CO2 rise. We find that Antarctic warming rates significantly decrease as the climate cools during the glacial period, whereas the rate of atmospheric CO2 rise does not significantly change. Also, we find that the rates of Antarctic warming and atmospheric CO2 rise are both insensitive to whether a given stadial contains a Heinrich event. These results challenge the view that a single Southern‐Ocean‐based mechanism dominates the observed glacial variability in Antarctic temperature and atmospheric CO2. Instead, our results are consistent with an important contribution of low‐ and mid‐latitude processes to millennial‐scale atmospheric CO2 changes.
The Role of Clouds in Coral Bleaching Events Over the Great Barrier Reef
Authors: Zhao Wenhui , Huang Yi , Siems Steven , Manton Michael
Published: July 2021

Thermal coral bleaching events (CBEs) over the Pacific, including those over the Great Barrier Reef (GBR), have commonly been linked to the El Niño–Southern Oscillation (ENSO), with bleaching reported to be a direct result of sea surface temperature (SST) anomalies driven by El Niño. However, such a relationship cannot explain CBEs that occurred during La Niña or the neutral phase of the ENSO. Here, we show that the GBR is characterized by a significant negative correlation between total cloud cover anomaly (TCCA) and lagged SST anomaly (SSTA) whose magnitude and spatial extent are greater than the SSTA‐ENSO correlation. This significant negative TCCA‐SSTA (lagged) correlation prevails over two‐thirds of the study domain even after the ENSO signal is removed, which suggests that local‐scale reduced cloud cover is a key component of the regional warm shallow water formation over the GBR and the occurrence of thermal CBEs.
Laurentide Ice Saddle Mergers Drive Rapid Sea Level Drops During Glaciations
Authors: Ji Weiwen , Robel Alexander , Tziperman Eli , Yang Jun
Published: July 2021

Recent glacial periods have included several periods of rapid sea level drop that are still not well understood. Here we show that rapid sea level drops can occur due to merger of two separate ice sheets without correspondingly rapid climate forcing. Using the Parallel Ice Sheet Model (PISM), we simulate glaciation of the Laurentide Ice Sheet (LIS) by gradually decreasing equilibrium‐line altitude (ELA). Merger of the extended Keewatin sector of the Laurentide Ice Sheet with Labrador sector of the Laurentide Ice Sheet south of Hudson Bay causes a positive feedback between increasing surface elevation and increasing surface mass balance in the merger region, leading to fast ice sheet growth. The simulated saddle merger of LIS lowers sea level by 20 m in less than 20 kyr with periods of sea level fall exceeding 2 m/kyr, similar to those observed in paleo‐sea level records.
Tropical Cyclones’ Contribution to Seasonal Precipitation and Streamflow Over the Southeastern and Southcentral United States
Authors: Chalise Dol Raj , Aiyyer Anantha , Sankarasubramanian A.
Published: July 2021

Studies have quantified the contribution of tropical cyclones (TCs) toward seasonal precipitation, but limited analysis is available on TC contribution toward seasonal streamflow over the southeastern and southcentral (SESC) United States (U.S.). Using an extensive network of hydroclimatic data that consists of 233 TC tracks and daily precipitation and streamflow, we estimate TC contribution toward precipitation and streamflow during the hurricane season over the SESC U.S. We found that TCs account for 12% of seasonal streamflow and 6% of seasonal precipitation over the region. Florida, North Carolina, and Louisiana have the highest fractional occurrence of TC‐generated annual maximum precipitation (∼20%–32%) and streamflow (∼15%–27%). We also found the fractional occurrence of TCs associated with peak‐over threshold precipitation (streamflow) events ranges from 5% to 8% in coastal regions (10%–20% over FL and 5%–10% over coastal NC). Increased antecedent moisture results in increased TCs contribution to streamflow leading to different land‐surface responses for similar hurricane events.
Machine Learning Prediction of Quartz Forming‐Environments
Authors: Wang Yu , Qiu Kun‐Feng , Müller Axel , Hou Zhao‐Liang , Zhu Zhi‐Hai , Yu Hao‐Cheng
Published: July 2021

Trace elements of quartz document the physical‐chemical evolutions of quartz growth, which has been a great and most applied tool in the study of geological settings in quartz‐forming environments. A classic method is using graphic diagram plots visualizing the quartz trace element discriminations and trends, examples including the Al‐Ti diagram (Rusk, 2012, https://doi.org/10.1007/978-3-642-22161-3_14) and the Ti‐Al‐Ge diagram (Schrön et al., 1988, https://www.researchgate.net/publication/236149159_Geochemische_Untersuchungen_an_Pegmatitquarzen). However, those diagrams are limited to two dimensions and cannot show the information in a higher dimension. In the study, we thus used a machine learning‐based approach to evaluate quartz trace elements, and visualized them for the first time in the high‐dimensional diagrams. We revisited 1,626 quartz samples from nine geological environments from previous studies, and applied a support vector machine to characterize values of the contained trace elements, including Al, Ti, Li, Ge, and Sr. We demonstrate that support vector machines can identify the crystallization environment of quartz with a significantly higher accuracy than the traditional plotting methods. Our work can massively improve the confidence on distinguishing quartz origin from different geological environments with a high efficiency. The method may also be applicable for other minerals, and we anticipate our research is a starting point for investigating mineral trace elements with machine learning techniques. Our quartz classifier can be accessed via https://quartz-classifier.herokuapp.com.
Age Uncertainty in Recurrence Analysis of Paleoseismic Records
Authors: Kempf Philipp , Moernaut Jasper
Published: July 2021

Determining the aperiodicity of large earthquake recurrences is key to forecast future rupture behavior. Aperiodicity is classically expressed as the coefficient of variation of recurrence intervals, though the recent trend to express it as burstiness is more intuitive and avoids minor inaccuracies. Due to the underestimation of burstiness in records with a low number of recurrence intervals, the paradigm is to obtain long paleoseismic records with many events. Here, we present a suite of synthetic paleoseismic records designed around the Weibull and inverse Gaussian distributions that demonstrate that age uncertainty relative to the mean recurrence interval causes overestimation of burstiness. The effects of overestimation and underestimation interact and give complex results for accurate estimates of aperiodicity. Furthermore, we show that the way recurrence intervals are sampled from a paleoseismic record can have strong influences on the resulting statistic and its implication for probabilistic seismic hazard assessment. Comparing values of burstiness between paleoseismic records should therefore be done with caution.
A Novel Atmospheric Removal Technique for TES Spectra Applied to Olivine and Carbonate‐Rich Bedrock in the Nili Fossae Region, Mars
Authors: Ruff Steven W. , Hamilton Victoria E.
Published: July 2021

Spectra from the Mars Global Surveyor Thermal Emission Spectrometer (TES) display a combination of features attributable to surface and atmospheric components. In order to fully recognize and interpret surface spectral features, the atmospheric spectral features must be removed through some form of surface‐atmosphere separation (SAS). Multiple SAS techniques are available representing a range of complexity and accuracy. A ratio between spectra from a region of interest and a relatively spectrally bland, dusty location is an effective SAS technique, but the resulting ratio spectrum contains spectral features of surface dust (SD) from the dusty location. We exploit the uniform spectral character of SD across Mars to produce dust‐removed ratio spectra (DRRS). This simple and robust technique allows TES spectra to be compared directly to laboratory spectra and to Miniature‐TES spectra from the Mars Exploration Rovers. Although previous SAS techniques yield atmospherically corrected spectra that can serve this purpose, they are more challenging to implement, retain fewer data points, and are less accurate in some cases. The DRRS technique provides an option that is well suited to both quick‐look assessments of TES spectra and in‐depth analyses using follow‐on spectral modeling techniques. We show that DRRS of olivine‐rich bedrock in the Nili Fossae region display spectral features that match olivine with a composition ranging from ∼Fo50 to <Fo90 and that match olivine‐rich Algonquin‐class rocks in the Columbia Hills of Gusev crater.
Characteristics and outcomes of 627 044 COVID-19 patients living with and without obesity in the United States, Spain, and the United Kingdom
Authors: Recalde Martina , Roel Elena , Pistillo Andrea , Sena Anthony G. , Prats-Uribe Albert , Ahmed Waheed-Ul-Rahman , Alghoul Heba , Alshammari Thamir M. , Alser Osaid , Areia Carlos , Burn Edward , Casajust Paula , Dawoud Dalia , DuVall Scott L. , Falconer Thomas , Fernández-Bertolín Sergio , Golozar Asieh , Gong Mengchun , Lai Lana Yin Hui , Lane Jennifer C. E. , Lynch Kristine E. , Matheny Michael E. , Mehta Paras P. , Morales Daniel R. , Natarjan Karthik , Nyberg Fredrik , Posada Jose D. , Reich Christian G. , Rijnbeek Peter R. , Schilling Lisa M. , Shah Karishma , Shah Nigam H. , Subbian Vignesh , Zhang Lin , Zhu Hong , Ryan Patrick , Prieto-Alhambra Daniel , Kostka Kristin , Duarte-Salles Talita
Published: July 2021

Background

A detailed characterization of patients with COVID-19 living with obesity has not yet been undertaken. We aimed to describe and compare the demographics, medical conditions, and outcomes of COVID-19 patients living with obesity (PLWO) to those of patients living without obesity.

Methods

We conducted a cohort study based on outpatient/inpatient care and claims data from January to June 2020 from Spain, the UK, and the US. We used six databases standardized to the OMOP common data model. We defined two non-mutually exclusive cohorts of patients diagnosed and/or hospitalized with COVID-19; patients were followed from index date to 30 days or death. We report the frequency of demographics, prior medical conditions, and 30-days outcomes (hospitalization, events, and death) by obesity status.

Results

We included 627 044 (Spain: 122 058, UK: 2336, and US: 502 650) diagnosed and 160 013 (Spain: 18 197, US: 141 816) hospitalized patients with COVID-19. The prevalence of obesity was higher among patients hospitalized (39.9%, 95%CI: 39.8−40.0) than among those diagnosed with COVID-19 (33.1%; 95%CI: 33.0−33.2). In both cohorts, PLWO were more often female. Hospitalized PLWO were younger than patients without obesity. Overall, COVID-19 PLWO were more likely to have prior medical conditions, present with cardiovascular and respiratory events during hospitalization, or require intensive services compared to COVID-19 patients without obesity.

Conclusion

We show that PLWO differ from patients without obesity in a wide range of medical conditions and present with more severe forms of COVID-19, with higher hospitalization rates and intensive services requirements. These findings can help guiding preventive strategies of COVID-19 infection and complications and generating hypotheses for causal inference studies.
Sequential CD19/22 CAR T-cell immunotherapy following autologous stem cell transplantation for central nervous system lymphoma
Authors: Wu Jiaying , Meng Fankai , Cao Yang , Zhang Yicheng , Zhu Xiaojian , Wang Na , Wang Jue , Huang Lifang , Zhou Jianfeng , Xiao Yi
Published: July 2021

Chimeric antigen receptor (CAR) T-cell immunotherapy following autologous stem cell transplantation (ASCT) is a promising method for refractory or relapsed multiple myeloma, but explicit data for central nervous system lymphoma (CNSL) are lacking. Here, we treated 13 CNSL patients with ASCT sequential CD19/22 CAR T-cell infusion and simultaneously evaluated the clinical efficacy and toxicity. The 13 CNSL patients analyzed included four primary CNSL and nine secondary CNSL patients. Patients 1 and 10, who had complete remission status before enrollment, maintained clinical efficacy without recurrence. Nine of the remaining 11 patients responded to our protocol with a median durable time of 14.03 months, and the overall response and complete remission rate were 81.81% and 54.55%, respectively. No patient suffered grades 3–4 cytokine-release syndrome (CRS), and only patient 10 experienced severe immune effector cell-associated neurotoxicity syndrome (ICANS). In addition, increases in serum ferritin and interleukin-6 levels were often accompanied by CRS and ICANS. After a median follow-up time of 14.20 months, the estimated 1-year progression-free survival and overall survival rates were 74.59% and 82.50%, respectively. Sequential CD19/22 CAR T-cell immunotherapy following ASCT as a novel method for CNSL appears to have encouraging long-term efficacy with relatively manageable side effects.
PGE2-JNK signaling axis non-canonically promotes Gli activation by protecting Gli2 from ubiquitin-proteasomal degradation
Authors: Yang Jun , Wang Juan , Liu Yuan , Zhang Yu , Huang Wenjing , Zou Yu , Qiu Yanyan , Cai Weiyang , Gao Jing , Zhou Hu , Wu Yingli , Liu Weijun , Ding Qingqing , Zhang Yanjie , Yin Pei-hao , Tan Wenfu
Published: July 2021

Both bench and bedside investigations have challenged the supportive role of Hedgehog (Hh) activity in the progression of colorectal cancers, thus raising a critical need to further deeply determine the contribution of Hh to the growth of colorectal cancer. Combining multiple complementary means, including in vitro and in vivo inflammatory colorectal cancer models, and pathological analysis of clinical colorectal cancer patients samples. We report that colorectal cancer cells hijack prostaglandin E2 (PGE2) to non-canonically promote Hh transcriptional factor Gli activity and Gli-dependent proliferation of colorectal cancer cells in a Smo-independent manner. Mechanistically, PGE2 activates c-Jun N-terminal kinase (JNK), which in turn enables Gli2 to evade ubiquitin-proteasomal degradation by phosphorylating Gli2 at Thr1546. This study not only presents evidence for understanding the contribution of Hh to colorectal cancers, but also provides a novel molecular portrait underlying how PGE2-activated JNK fine-tunes the evasion of Gli2 from ubiquitin-proteasomal degradation. Therefore, it proposes a rationale for the future evaluation of chemopreventive and selective therapeutic strategies for colorectal cancers by targeting PGE2-JNK-Gli signaling route.
Interferon-armed RBD dimer enhances the immunogenicity of RBD for sterilizing immunity against SARS-CoV-2
Authors: Sun Shiyu , Cai Yueqi , Song Tian-Zhang , Pu Yang , Cheng Lin , Xu Hairong , Sun Jing , Meng Chaoyang , Lin Yifan , Huang Haibin , Zhao Fang , Zhang Silin , Gao Yu , Han Jian-Bao , Feng Xiao-Li , Yu Dan-Dan , Zhu Yalan , Gao Pu , Tang Haidong , Zhao Jincun , Zhang Zheng , Yang Jiaming , Hu Zhenxiang , Fu Yang-Xin , Zheng Yong-Tang , Peng Hua
Published: July 2021

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global crisis, urgently necessitating the development of safe, efficacious, convenient-to-store, and low-cost vaccine options. A major challenge is that the receptor-binding domain (RBD)-only vaccine fails to trigger long-lasting protective immunity if used alone for vaccination. To enhance antigen processing and cross-presentation in draining lymph nodes (DLNs), we developed an interferon (IFN)-armed RBD dimerized by an immunoglobulin fragment (I-R-F). I-R-F efficiently directs immunity against RBD to DLNs. A low dose of I-R-F induces not only high titers of long-lasting neutralizing antibodies (NAbs) but also more comprehensive T cell responses than RBD. Notably, I-R-F provides comprehensive protection in the form of a one-dose vaccine without an adjuvant. Our study shows that the pan-epitope modified human I-R-F (I-P-R-F) vaccine provides rapid and complete protection throughout the upper and lower respiratory tracts against a high-dose SARS-CoV-2 challenge in rhesus macaques. Based on these promising results, we have initiated a randomized, placebo-controlled, phase I/II trial of the human I-P-R-F vaccine (V-01) in 180 healthy adults, and the vaccine appears safe and elicits strong antiviral immune responses. Due to its potency and safety, this engineered vaccine may become a next-generation vaccine candidate in the global effort to overcome COVID-19.
A systematic review assessing the existence of pneumothorax-only variants of FLCN. Implications for lifelong surveillance of renal tumours
Authors: Matsumoto Kenki , Lim Derek , Pharoah Paul D. , Maher Eamonn R. , Marciniak Stefan J.
Published: July 2021

Individuals with Birt–Hogg–Dubé syndrome (BHDS) may develop fibrofolliculomas, pneumothorax and/or renal cell carcinoma (RCC). Currently, all patients with pathogenicFLCNvariants are recommended to have renal surveillance. It has however been suggested that someFLCNvariants only cause pneumothorax, which would make surveillance unnecessary in certain cases. This review assesses this possibility. We provide an up-to-date analysis of clinical and genetic features of BHDS. The PUBMED database was systematically searched to find all articles describing patients with pathogenicFLCNvariants. The relevant clinical and genetic features of these patients were recorded and analysed. The prevalence of pneumothorax, pulmonary cysts, RCC and characteristic skin lesions in BHDS were 50.9% (n = 1038), 91.9% (n = 720), 22.5% (n = 929) and 47.9% (n = 989), respectively. There was a higher prevalence of pneumothoraces (p < 0.0001) but lower prevalence of dermatological findings (p < 0.0001) in patients from East Asia compared to North America or Europe. Of the 194 pathogenicFLCNvariants, 76 could be defined as ‘pneumothorax-only’. Pneumothorax only pathogenic variants (POPVs) were distributed throughout the gene, and there were no statistical differences in variant type. The majority of POPVs (65/76) affected no more than three individuals. Individuals with ‘POPVs’ also tended to be younger (45 vs. 47 years,p < 0.05). Many apparent POPVs in the literature could result from variable expressivity, age-related penetrance and other confounding factors. We therefore recommend that all individuals found to carry a pathogenicFLCNvariant be enroled in lifelong surveillance for RCC.
Enhancing sub-bandgap external quantum efficiency by photomultiplication for narrowband organic near-infrared photodetectors
Authors: Kublitski Jonas , Fischer Axel , Xing Shen , Baisinger Lukasz , Bittrich Eva , Spoltore Donato , Benduhn Johannes , Vandewal Koen , Leo Karl
Published: July 2021

Detection of electromagnetic signals for applications such as health, product quality monitoring or astronomy requires highly responsive and wavelength selective devices. Photomultiplication-type organic photodetectors have been shown to achieve high quantum efficiencies mainly in the visible range. Much less research has been focused on realizing near-infrared narrowband devices. Here, we demonstrate fully vacuum-processed narrow- and broadband photomultiplication-type organic photodetectors. Devices are based on enhanced hole injection leading to a maximum external quantum efficiency of almost 2000% at −10 V for the broadband device. The photomultiplicative effect is also observed in the charge-transfer state absorption region. By making use of an optical cavity device architecture, we enhance the charge-transfer response and demonstrate a wavelength tunable narrowband photomultiplication-type organic photodetector with external quantum efficiencies superior to those of pin-devices. The presented concept can further improve the performance of photodetectors based on the absorption of charge-transfer states, which were so far limited by the low external quantum efficiency provided by these devices.
Pure spin photocurrent in non-centrosymmetric crystals: bulk spin photovoltaic effect
Authors: Xu Haowei , Wang Hua , Zhou Jian , Li Ju
Published: July 2021

Spin current generators are critical components for spintronics-based information processing. In this work, we theoretically and computationally investigate the bulk spin photovoltaic (BSPV) effect for creating DC spin current under light illumination. The only requirement for BSPV is inversion symmetry breaking, thus it applies to a broad range of materials and can be readily integrated with existing semiconductor technologies. The BSPV effect is a cousin of the bulk photovoltaic (BPV) effect, whereby a DC charge current is generated under light. Thanks to the different selection rules on spin and charge currents, a pure spin current can be realized if the system possesses mirror symmetry or inversion-mirror symmetry. The mechanism of BSPV and the role of the electronic relaxation time $$\tau$$
τ
are also elucidated. We apply our theory to several distinct materials, including monolayer transition metal dichalcogenides, anti-ferromagnetic bilayer MnBi2Te4, and the surface of topological crystalline insulator cubic SnTe.
Crystal and electronic facet analysis of ultrafine Ni2P particles by solid-state NMR nanocrystallography
Authors: Papawassiliou Wassilios , Carvalho José P. , Panopoulos Nikolaos , Al Wahedi Yasser , Wadi Vijay Kumar Shankarayya , Lu Xinnan , Polychronopoulou Kyriaki , Lee Jin Bae , Lee Sanggil , Kim Chang Yeon , Kim Hae Jin , Katsiotis Marios , Tzitzios Vasileios , Karagianni Marina , Fardis Michael , Papavassiliou Georgios , Pell Andrew J.
Published: July 2021

Structural and morphological control of crystalline nanoparticles is crucial in the field of heterogeneous catalysis and the development of “reaction specific” catalysts. To achieve this, colloidal chemistry methods are combined with ab initio calculations in order to define the reaction parameters, which drive chemical reactions to the desired crystal nucleation and growth path. Key in this procedure is the experimental verification of the predicted crystal facets and their corresponding electronic structure, which in case of nanostructured materials becomes extremely difficult. Here, by employing31P solid-state nuclear magnetic resonance aided by advanced density functional theory calculations to obtain and assign the Knight shifts, we succeed in determining the crystal and electronic structure of the terminating surfaces of ultrafine Ni2P nanoparticles at atomic scale resolution. Our work highlights the potential of ssNMR nanocrystallography as a unique tool in the emerging field of facet-engineered nanocatalysts.
Dietary thiols accelerate aging of C. elegans
Authors: Gusarov Ivan , Shamovsky Ilya , Pani Bibhusita , Gautier Laurent , Eremina Svetlana , Katkova-Zhukotskaya Olga , Mironov Alexander , Makarov Alexander А. , Nudler Evgeny
Published: July 2021

Glutathione (GSH) is the most abundant cellular antioxidant. As reactive oxygen species (ROS) are widely believed to promote aging and age-related diseases, and antioxidants can neutralize ROS, it follows that GSH and its precursor, N-acetyl cysteine (NAC), are among the most popular dietary supplements. However, the long- term effects of GSH or NAC on healthy animals have not been thoroughly investigated. We employed C. elegans to demonstrate that chronic administration of GSH or NAC to young or aged animals perturbs global gene expression, inhibits skn-1-mediated transcription, and accelerates aging. In contrast, limiting the consumption of dietary thiols, including those naturally derived from the microbiota, extended lifespan. Pharmacological GSH restriction activates the unfolded protein response and increases proteotoxic stress resistance in worms and human cells. It is thus advantageous for healthy individuals to avoid excessive dietary antioxidants and, instead, rely on intrinsic GSH biosynthesis, which is fine-tuned to match the cellular redox status and to promote homeostatic ROS signaling.
Fast holographic scattering compensation for deep tissue biological imaging
Authors: May Molly A. , Barré Nicolas , Kummer Kai K. , Kress Michaela , Ritsch-Marte Monika , Jesacher Alexander
Published: July 2021

Scattering in biological tissues is a major barrier for in vivo optical imaging of all but the most superficial structures. Progress toward overcoming the distortions caused by scattering in turbid media has been made by shaping the excitation wavefront to redirect power into a single point in the imaging plane. However, fast, non-invasive determination of the required wavefront compensation remains challenging. Here, we introduce a quickly converging algorithm for non-invasive scattering compensation, termed DASH, in which holographic phase stepping interferometry enables new phase information to be updated after each measurement. This leads to rapid improvement of the wavefront correction, forming a focus after just one measurement iteration and achieving an order of magnitude higher signal enhancement at this stage than the previous state-of-the-art. Using DASH, we demonstrate two-photon fluorescence imaging of microglia cells in highly turbid mouse hippocampal tissue down to a depth of 530 μm.
Ion mobility-based sterolomics reveals spatially and temporally distinctive sterol lipids in the mouse brain
Authors: Li Tongzhou , Yin Yandong , Zhou Zhiwei , Qiu Jiaqian , Liu Wenbin , Zhang Xueting , He Kaiwen , Cai Yuping , Zhu Zheng-Jiang
Published: July 2021

Aberrant sterol lipid metabolism is associated with physiological dysfunctions in the aging brain and aging-dependent disorders such as neurodegenerative diseases. There is an unmet demand to comprehensively profile sterol lipids spatially and temporally in different brain regions during aging. Here, we develop an ion mobility-mass spectrometry based four-dimensional sterolomics technology leveraged by a machine learning-empowered high-coverage library (>2000 sterol lipids) for accurate identification. We apply this four-dimensional technology to profile the spatially resolved landscapes of sterol lipids in ten functional regions of the mouse brain, and quantitatively uncover ~200 sterol lipids uniquely distributed in specific regions with concentrations spanning up to 8 orders of magnitude. Further spatial analysis pinpoints age-associated differences in region-specific sterol lipid metabolism, revealing changes in the numbers of altered sterol lipids, concentration variations, and age-dependent coregulation networks. These findings will contribute to our understanding of abnormal sterol lipid metabolism and its role in brain diseases.
Mechanism for enhancing the growth of mung bean seedlings under simulated microgravity
Authors: Nakajima Shusaku , Nagata Masayasu , Ikehata Akifumi
Published: July 2021

To elucidate a mechanism for enhancing mung bean seedlings’ growth under microgravity conditions, we measured growth, gene expression, and enzyme activity under clinorotation (20 rpm), and compared data obtained to those grown under normal gravity conditions (control). An increase in fresh weight, water content, and lengths were observed in the clinostat seedlings, compared to those of the control seedlings. Real-time PCR showed that aquaporin expression and the amylase gene were upregulated under clinorotation. Additionally, seedlings under clinorotation exhibited a significantly higher amylase activity. Near-infrared image showed that there was no restriction of water evaporation from the seedlings under clinorotation. Therefore, these results indicate that simulated microgravity could induce water uptake, resulting in enhanced amylase activity and seedling growth. Upregulated aquaporin expression could be the first trigger for enhanced growth under clinorotation. We speculated that the seedlings under clinorotation do not use energy against gravitational force and consumed surplus energy for enhanced growth.
Highly thermally conductive carbon nanotubes pillared exfoliated graphite/polyimide composites
Authors: Guo Yongqiang , Wang Shuangshuang , Ruan Kunpeng , Zhang Haitian , Gu Junwei
Published: July 2021

In this work, carbon nanotubes pillared grew on exfoliated graphite by the microwave-assisted method is utilized as thermally conductive fillers (CPEG) in polyimide (PI) to fabricate CPEG/PI thermally conductive composites with the combining ways of “in-situ polymerization, electrospinning, lay-up, and hot-pressing”. The prepared CPEG/PI composites realized the maximum thermal conductivity (λ, 1.92 W m−1 K−1) at low CPEG amount (10 wt%), much higher than that of pure PI (0.28 W m−1 K−1). The λ of CPEG/PI composites show almost no change after 1000 cycles of heating and cooling at the temperature of 25−100 °C. The finite element analysis simulates the nano-/microscale heat transfer in CPEG/PI composites to reveal the internal reason of the λ enhancement. The improved thermal conductivity model and empirical equation could better reflect the actual λ change trend of CPEG/PI composites. The actual application test shows the CPEG/PI composites could significantly reduce the operating temperature of the CPU in mobile phone.
Efficient computation of the Nagaoka–Hayashi bound for multiparameter estimation with separable measurements
Authors: Conlon Lorcán O. , Suzuki Jun , Lam Ping Koy , Assad Syed M.
Published: July 2021

Finding the optimal attainable precisions in quantum multiparameter metrology is a non-trivial problem. One approach to tackling this problem involves the computation of bounds which impose limits on how accurately we can estimate certain physical quantities. One such bound is the Holevo Cramér–Rao bound on the trace of the mean squared error matrix. The Holevo bound is an asymptotically achievable bound when one allows for any measurement strategy, including collective measurements on many copies of the probe. In this work, we introduce a tighter bound for estimating multiple parameters simultaneously when performing separable measurements on a finite number of copies of the probe. This makes it more relevant in terms of experimental accessibility. We show that this bound can be efficiently computed by casting it as a semidefinite programme. We illustrate our bound with several examples of collective measurements on finite copies of the probe. These results have implications for the necessary requirements to saturate the Holevo bound.
Quantum-inspired machine learning on high-energy physics data
Authors: Felser Timo , Trenti Marco , Sestini Lorenzo , Gianelle Alessio , Zuliani Davide , Lucchesi Donatella , Montangero Simone
Published: July 2021

Tensor Networks, a numerical tool originally designed for simulating quantum many-body systems, have recently been applied to solve Machine Learning problems. Exploiting a tree tensor network, we apply a quantum-inspired machine learning technique to a very important and challenging big data problem in high-energy physics: the analysis and classification of data produced by the Large Hadron Collider at CERN. In particular, we present how to effectively classify so-called b-jets, jets originating from b-quarks from proton–proton collisions in the LHCb experiment, and how to interpret the classification results. We exploit the Tensor Network approach to select important features and adapt the network geometry based on information acquired in the learning process. Finally, we show how to adapt the tree tensor network to achieve optimal precision or fast response in time without the need of repeating the learning process. These results pave the way to the implementation of high-frequency real-time applications, a key ingredient needed among others for current and future LHCb event classification able to trigger events at the tens of MHz scale.
COVID-19 European regional tracker
Authors: Naqvi Asjad
Published: July 2021

This Tracker presents data on daily COVID-19 cases at the sub-national level for 26 European countries from January 2020 till present. Country-level data sources are identified and processed to form a homogenized panel at the NUTS 3 or NUTS 2 level, the two lowest standardized administrative units in Europe. The strengths and weaknesses of each country dataset are discussed in detail. The raw data, spatial layers, the code, and the final homogenized files are provided in an online repository for replication. The data highlights the spatial distribution of cases both within and across countries that can be utilized for a disaggregated analysis on the impacts of the pandemic. The Tracker is updated monthly to expand its coverage.
A sub-national real-time epidemiological and vaccination database for the COVID-19 pandemic in Canada
Authors: Berry Isha , O’Neill Meghan , Sturrock Shelby L. , Wright James E. , Acharya Kamal , Brankston Gabrielle , Harish Vinyas , Kornas Kathy , Maani Nika , Naganathan Thivya , Obress Lindsay , Rossi Tanya , Simmons Alison E. , Van Camp Matthew , Xie Xiao , Tuite Ashleigh R. , Greer Amy L. , Fisman David N. , Soucy Jean-Paul R.
Published: July 2021

The COVID-19 pandemic has demonstrated the need for real-time, open-access epidemiological information to inform public health decision-making and outbreak control efforts. In Canada, authority for healthcare delivery primarily lies at the provincial and territorial level; however, at the outset of the pandemic no definitive pan-Canadian COVID-19 datasets were available. The COVID-19 Canada Open Data Working Group was created to fill this crucial data gap. As a team of volunteer contributors, we collect daily COVID-19 data from a variety of governmental and non-governmental sources and curate a line-list of cases and mortality for all provinces and territories of Canada, including information on location, age, sex, travel history, and exposure, where available. We also curate time series of COVID-19 recoveries, testing, and vaccine doses administered and distributed. Data are recorded systematically at a fine sub-national scale, which can be used to support robust understanding of COVID-19 hotspots. We continue to maintain this dataset, and an accompanying online dashboard, to provide a reliable pan-Canadian COVID-19 resource to researchers, journalists, and the general public.
DEDDIAG, a domestic electricity demand dataset of individual appliances in Germany
Authors: Wenninger Marc , Maier Andreas , Schmidt Jochen
Published: July 2021

Real-world domestic electricity demand datasets are the key enabler for developing and evaluating machine learning algorithms that facilitate the analysis of demand attribution and usage behavior. Breaking down the electricity demand of domestic households is seen as the key technology for intelligent smart-grid management systems that seek an equilibrium of electricity supply and demand. For the purpose of comparable research, we publish DEDDIAG, a domestic electricity demand dataset of individual appliances in Germany. The dataset contains recordings of 15 homes over a period of up to 3.5 years, wherein total 50 appliances have been recorded at a frequency of 1 Hz. Recorded appliances are of significance for load-shifting purposes such as dishwashers, washing machines and refrigerators. One home also includes three-phase mains readings that can be used for disaggregation tasks. Additionally, DEDDIAG contains manual ground truth event annotations for 14 appliances, that provide precise start and stop timestamps. Such annotations have not been published for any long-term electricity dataset we are aware of.
A comprehensive annotation dataset of intact LTR retrotransposons of 300 plant genomes
Authors: Zhou Shan-Shan , Yan Xue-Mei , Zhang Kai-Fu , Liu Hui , Xu Jie , Nie Shuai , Jia Kai-Hua , Jiao Si-Qian , Zhao Wei , Zhao You-Jie , Porth Ilga , El Kassaby Yousry A. , Wang Tongli , Mao Jian-Feng
Published: July 2021

LTR retrotransposons (LTR-RTs) are ubiquitous and represent the dominant repeat element in plant genomes, playing important roles in functional variation, genome plasticity and evolution. With the advent of new sequencing technologies, a growing number of whole-genome sequences have been made publicly available, making it possible to carry out systematic analyses of LTR-RTs. However, a comprehensive and unified annotation of LTR-RTs in plant groups is still lacking. Here, we constructed a plant intact LTR-RTs dataset, which is designed to classify and annotate intact LTR-RTs with a standardized procedure. The dataset currently comprises a total of 2,593,685 intact LTR-RTs from genomes of 300 plant species representing 93 families of 46 orders. The dataset is accompanied by sequence, diverse structural and functional annotation, age determination and classification information associated with the LTR-RTs. This dataset will contribute valuable resources for investigating the evolutionary dynamics and functional implications of LTR-RTs in plant genomes.
Single-cell RNA sequencing of freshly isolated bovine milk cells and cultured primary mammary epithelial cells
Authors: Becker Doreen , Weikard Rosemarie , Hadlich Frieder , Kühn Christa
Published: July 2021

Bovine mammary function at molecular level is often studied using mammary tissue or primary bovine mammary epithelial cells (pbMECs). However, bulk tissue and primary cells are heterogeneous with respect to cell populations, adding further transcriptional variation in addition to genetic background. Thus, understanding of the variation in gene expression profiles of cell populations and their effect on function are limited. To investigate the mononuclear cell composition in bovine milk, we analyzed a single-cell suspension from a milk sample. Additionally, we harvested cultured pbMECs to characterize gene expression in a homogeneous cell population. Using the Drop-seq technology, we generated single-cell RNA datasets of somatic milk cells and pbMECs. The final datasets after quality control filtering contained 7,119 and 10,549 cells, respectively. The pbMECs formed 14 indefinite clusters displaying intrapopulation heterogeneity, whereas the milk cells formed 14 more distinct clusters. Our datasets constitute a molecular cell atlas that provides a basis for future studies of milk cell composition and gene expression, and could serve as reference datasets for milk cell analysis.