bluuebunny/crossref_metadata_2025 huggingface dataset:
Constitutive activation of nitrate reductase in tobacco alters flowering time and plant biomass
Authors: Lu Jianli , Chandrakanth Niharika N. , Lewis Ramsey S. , Andres Karen , Bovet Lucien , Goepfert Simon , Dewey Ralph E.
Published: February 2021

Pyridine alkaloids produced in tobacco can react with nitrosating agents such as nitrite to form tobacco-specific nitrosamines (TSNA), which are among the most notable toxicants present in tobacco smoke. The market type known as burley tobacco is particularly susceptible to TSNA formation because its corresponding cultivars exhibit a nitrogen-use-deficiency phenotype which results in high accumulation of nitrate, which, in turn, is converted to nitrite by leaf surface microbes. We have previously shown that expression of a constitutively activated nitrate reductase (NR) enzyme dramatically decreases leaf nitrate levels in burley tobacco, resulting in substantial TSNA reductions without altering the alkaloid profile. Here, we show that plants expressing a constitutively active NR construct, designated 35S:S523D-NR, display an early-flowering phenotype that is also associated with a substantial reduction in plant biomass. We hypothesized that crossing 35S:S523D-NR tobaccos with burley cultivars that flower later than normal would help mitigate the undesirable early-flowering/reduced-biomass traits while maintaining the desirable low-nitrate/TSNA phenotype. To test this, 35S:S523D-NR plants were crossed with two late-flowering cultivars, NC 775 and NC 645WZ. In both cases, the plant biomass at harvest was restored to levels similar to those in the original cultivar used for transformation while the low-nitrate/TSNA trait was maintained. Interestingly, the mechanism by which yield was restored differed markedly between the two crosses. Biomass restoration in F1 hybrids using NC 645WZ as a parent was associated with delayed flowering, as originally hypothesized. Unexpectedly, however, crosses with NC 775 displayed enhanced biomass despite maintaining the early-flowering trait of the 35S:S523D-NR parent.
Gestational age-specific normative values and determinants of serum progesterone through the first trimester of pregnancy
Authors: Ku Chee Wai , Zhang Xiaoxuan , Zhang Valencia Ru-Yan , Allen John Carson , Tan Nguan Soon , Østbye Truls , Tan Thiam Chye
Published: February 2021

Progesterone is a steroid hormone that is critical for implantation and maintenance of pregnancy, and low levels are associated with higher miscarriage risk. However, little is known about its trajectory during early pregnancy. We sought to determine the gestational age-specific normative values of serum progesterone on a week-by-week basis, and its associated maternal and fetal factors, during the first trimester of a viable low-risk pregnancy. A cross-sectional study was conducted at KK Women’s and Children’s Hospital from 2013 to 2018. 590 women with a single viable intrauterine low-risk pregnancy, between gestational weeks 5 and 12, were recruited. Serum progesterone showed an increasing trend during the first trimester, with a transient decline between gestational weeks 6–8, corresponding to the luteal–placental shift. Lowest levels were seen at week 7. Maternal age, BMI, parity, gestational age and outcome of pregnancy at 16 weeks’ gestation were found to be associated with progesterone levels. Normative values of serum progesterone for low-risk pregnancies would form the basis for future work on pathological levels of serum progesterone that may increase risk of miscarriage. Larger studies are required to validate these normative values, and personalize them to account for maternal age, BMI, parity and gestational age.
Elongation and branching of stem channels produced by positive streamers in long air gaps
Authors: Zhao Xiangen , Becerra Marley , Yang Yongchao , He Junjia
Published: February 2021

The elongation and branching of long positive spark discharges in the laboratory and in lightning have been attributed to the formation of thermalized channels inside a diffuse, glow-like streamer section at the leader head. It is experimentally shown here that the structured morphology of streamers produce low-density stem channels that elongate and branch well before a new leader channel section is formed. These non-thermalized stems are also shown to develop ahead of a developing leader channel. These findings are based on high-speed photography and Schlieren imaging used to visualize both the morphology of streamer filaments and stem channels. Numerical analysis is also performed to estimate the axial temperature and density of the stem channels. A stem-driven mechanism for the propagation and branching of positive long air gap discharges is proposed and discussed based on the presence of not-yet thermalized, low density channels formed by streamer ensembles at the leader head.
The Late Miocene Rifian corridor as a natural laboratory to explore a case of ichnofacies distribution in ancient gateways
Authors: Miguez-Salas Olmo , Rodríguez-Tovar Francisco J. , de Weger Wouter
Published: February 2021

Oceanic gateways have modulated ocean circulation and have influenced climatic variations throughout the Earth´s history. During the late Miocene (7.8–7.35 Ma), the Atlantic Ocean and the Mediterranean Sea were connected through the Rifian Corridor (Morocco). This gateway is one of the few examples of deep ancient seaways with a semi-continuous sedimentary record. Deposits comprise turbidites intercalated between deep-sea mudstone (i.e., hemipelagites and drift deposits), channelized sandstone contourite facies, and shallow marine sandstone. Herein an ichnological analysis was conducted in these upper Miocene sediments to improve characterisation of palaeoenvironmental conditions. In addition, ichnofacies were analysed to elucidate how bottom currents control ichnofacies distribution and can modify their attributes. Turbidite deposits are typified by vertical trace fossils (i.e., Ophiomorpha), conforming the Ophiomorpha rudis ichnosubfacies. Contouritic sandstone exhibits high density and low diversity trace-fossil assemblage, with predominant Macaronichnus and Scolicia, resembling a proximal expression of the Cruziana ichnofacies. Shallow marine environments are dominated by vertical trace fossils (e.g., Conichnus, Ophiomorpha, Skolithos), allowing an assignation to the Skolithos ichnofacies. This study reveals for the first time a variability in ichnofacies attributes and distribution at the Rifian Corridor, associated with turbidites, contourite and shallow marine sediments. Hydrodynamic energy reveals as the major factor controlling trace maker communities in the studied seaway. Highly energetic conditions typical of shallower settings are present in deeper-water environments (i.e., slope), contributing to ichnodiversity impoverishment in ichnofacies.
Potential of spectroscopic analyses for non-destructive estimation of tea quality-related metabolites in fresh new leaves
Authors: Yamashita Hiroto , Sonobe Rei , Hirono Yuhei , Morita Akio , Ikka Takashi
Published: February 2021

Spectroscopic sensing provides physical and chemical information in a non-destructive and rapid manner. To develop non-destructive estimation methods of tea quality-related metabolites in fresh leaves, we estimated the contents of free amino acids, catechins, and caffeine in fresh tea leaves using visible to short-wave infrared hyperspectral reflectance data and machine learning algorithms. We acquired these data from approximately 200 new leaves with various status and then constructed the regression model in the combination of six spectral patterns with pre-processing and five algorithms. In most phenotypes, the combination of de-trending pre-processing and Cubist algorithms was robustly selected as the best combination in each round over 100 repetitions that were evaluated based on the ratio of performance to deviation (RPD) values. The mean RPD values were ranged from 1.1 to 2.7 and most of them were above the acceptable or accurate threshold (RPD = 1.4 or 2.0, respectively). Data-based sensitivity analysis identified the important hyperspectral regions around 1500 and 2000 nm. Present spectroscopic approaches indicate that most tea quality-related metabolites can be estimated non-destructively, and pre-processing techniques help to improve its accuracy.
AT1 receptor blocker, but not an ACE inhibitor, prevents kidneys from hypoperfusion during congestive heart failure in normotensive and hypertensive rats
Authors: Kratky Vojtech , Vanourkova Zdenka , Sykora Matus , Bacova Barbara Szeiffova , Hruskova Zdenka , Kikerlova Sona , Huskova Zuzana , Kopkan Libor
Published: February 2021

To provide novel insights into the pathogenesis of heart failure-induced renal dysfunction, we compared the effects of ACE inhibitor (ACEi) and AT1 receptor blocker (ARB) on systemic and kidney hemodynamics during heart failure in normotensive HanSD and hypertensive transgenic (TGR) rats. High-output heart failure was induced by creating an aorto-caval fistula (ACF). After five weeks, rats were either left untreated or treatment with ACEi or ARB was started for 15 weeks. Subsequently, echocardiographic, renal hemodynamic and biochemical measurements were assessed. Untreated ACF rats with ACF displayed significantly reduced renal blood flow (RBF) (HanSD: 8.9 ± 1.0 vs. 4.7 ± 1.6; TGR: 10.2 ± 1.9 vs. 5.9 ± 1.2 ml/min, both P < .001), ACEi had no major RBF effect, whereas ARB completely restored RBF (HanSD: 5.6 ± 1.1 vs. 9.0 ± 1.5; TGR: 7.0 ± 1.2 vs. 10.9 ± 1.9 ml/min, both P < .001). RBF reduction in untreated and ACEi-treated rats was accompanied by renal hypoxia as measured by renal lactate dehydrogenase activity, which was ameliorated with ARB treatment (HanSD: 40 ± 4 vs. 42 ± 3 vs. 29 ± 5; TGR: 88 ± 4 vs. 76 ± 4 vs. 58 ± 4 milliunits/mL, all P < .01). Unlike improvement seen in ARB-treated rats, ACE inhibition didn’t affect urinary nitrates compared to untreated ACF TGR rats (50 ± 14 vs. 22 ± 13 vs. 30 ± 13 μmol/mmol Cr, both P < .05). ARB was more effective than ACEi in reducing elevated renal oxidative stress following ACF placement. A marker of ACEi efficacy, the angiotensin I/angiotensin II ratio, was more than ten times lower in renal tissue than in plasma. Our study shows that ARB treatment, in contrast to ACEi administration, prevents renal hypoperfusion and hypoxia in ACF rats with concomitant improvement in NO bioavailability and oxidative stress reduction. The inability of ACE inhibition to improve renal hypoperfusion in ACF rats may result from incomplete intrarenal RAS suppression in the face of depleted compensatory mechanisms.
Author Correction: Tankyrase inhibitor XAV-939 enhances osteoblastogenesis and mineralization of human skeletal (mesenchymal) stem cells
Authors: Almasoud Nuha , Binhamdan Sarah , Younis Ghaydaa , Alaskar Hanouf , Alotaibi Amal , Manikandan Muthurangan , Alfayez Musaad , Kassem Moustapha , AlMuraikhi Nihal
Published: February 2021

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publisher Correction: Historical predictability of rainfall erosivity: a reconstruction for monitoring extremes over Northern Italy (1500–2019)
Authors: Diodato Nazzareno , Ljungqvist Fredrik Charpentier , Bellocchi Gianni
Published: February 2021

A Correction to this paper has been published: https://doi.org/10.1038/s41612-021-00164-z
Development and validation of a reinforcement learning algorithm to dynamically optimize mechanical ventilation in critical care
Authors: Peine Arne , Hallawa Ahmed , Bickenbach Johannes , Dartmann Guido , Fazlic Lejla Begic , Schmeink Anke , Ascheid Gerd , Thiemermann Christoph , Schuppert Andreas , Kindle Ryan , Celi Leo , Marx Gernot , Martin Lukas
Published: February 2021

The aim of this work was to develop and evaluate the reinforcement learning algorithm VentAI, which is able to suggest a dynamically optimized mechanical ventilation regime for critically-ill patients. We built, validated and tested its performance on 11,943 events of volume-controlled mechanical ventilation derived from 61,532 distinct ICU admissions and tested it on an independent, secondary dataset (200,859 ICU stays; 25,086 mechanical ventilation events). A patient “data fingerprint” of 44 features was extracted as multidimensional time series in 4-hour time steps. We used a Markov decision process, including a reward system and a Q-learning approach, to find the optimized settings for positive end-expiratory pressure (PEEP), fraction of inspired oxygen (FiO2) and ideal body weight-adjusted tidal volume (Vt). The observed outcome was in-hospital or 90-day mortality. VentAI reached a significantly increased estimated performance return of 83.3 (primary dataset) and 84.1 (secondary dataset) compared to physicians’ standard clinical care (51.1). The number of recommended action changes per mechanically ventilated patient constantly exceeded those of the clinicians. VentAI chose 202.9% more frequently ventilation regimes with lower Vt (5–7.5 mL/kg), but 50.8% less for regimes with higher Vt (7.5–10 mL/kg). VentAI recommended 29.3% more frequently PEEP levels of 5–7 cm H2O and 53.6% more frequently PEEP levels of 7–9 cmH2O. VentAI avoided high (>55%) FiO2 values (59.8% decrease), while preferring the range of 50–55% (140.3% increase). In conclusion, VentAI provides reproducible high performance by dynamically choosing an optimized, individualized ventilation strategy and thus might be of benefit for critically ill patients.
CovidCTNet: an open-source deep learning approach to diagnose covid-19 using small cohort of CT images
Authors: Javaheri Tahereh , Homayounfar Morteza , Amoozgar Zohreh , Reiazi Reza , Homayounieh Fatemeh , Abbas Engy , Laali Azadeh , Radmard Amir Reza , Gharib Mohammad Hadi , Mousavi Seyed Ali Javad , Ghaemi Omid , Babaei Rosa , Mobin Hadi Karimi , Hosseinzadeh Mehdi , Jahanban-Esfahlan Rana , Seidi Khaled , Kalra Mannudeep K. , Zhang Guanglan , Chitkushev L. T. , Haibe-Kains Benjamin , Malekzadeh Reza , Rawassizadeh Reza
Published: February 2021

Coronavirus disease 2019 (Covid-19) is highly contagious with limited treatment options. Early and accurate diagnosis of Covid-19 is crucial in reducing the spread of the disease and its accompanied mortality. Currently, detection by reverse transcriptase-polymerase chain reaction (RT-PCR) is the gold standard of outpatient and inpatient detection of Covid-19. RT-PCR is a rapid method; however, its accuracy in detection is only ~70–75%. Another approved strategy is computed tomography (CT) imaging. CT imaging has a much higher sensitivity of ~80–98%, but similar accuracy of 70%. To enhance the accuracy of CT imaging detection, we developed an open-source framework, CovidCTNet, composed of a set of deep learning algorithms that accurately differentiates Covid-19 from community-acquired pneumonia (CAP) and other lung diseases. CovidCTNet increases the accuracy of CT imaging detection to 95% compared to radiologists (70%). CovidCTNet is designed to work with heterogeneous and small sample sizes independent of the CT imaging hardware. To facilitate the detection of Covid-19 globally and assist radiologists and physicians in the screening process, we are releasing all algorithms and model parameter details as open-source. Open-source sharing of CovidCTNet enables developers to rapidly improve and optimize services while preserving user privacy and data ownership.
Day-to-day variability in sleep parameters and depression risk: a prospective cohort study of training physicians
Authors: Fang Yu , Forger Daniel B. , Frank Elena , Sen Srijan , Goldstein Cathy
Published: February 2021

While 24-h total sleep time (TST) is established as a critical driver of major depression, the relationships between sleep timing and regularity and mental health remain poorly characterized because most studies have relied on either self-report assessments or traditional objective sleep measurements restricted to cross-sectional time frames and small cohorts. To address this gap, we assessed sleep with a wearable device, daily mood with a smartphone application and depression through the 9-item Patient Health Questionnaire (PHQ-9) over the demanding first year of physician training (internship). In 2115 interns, reduced TST (b = −0.11, p < 0.001), later bedtime (b = 0.068, p = 0.015), along with increased variability in TST (b = 0.4, p = 0.0012) and in wake time (b = 0.081, p = 0.005) were associated with more depressive symptoms. Overall, the aggregated impact of sleep variability parameters and of mean sleep parameters on PHQ-9 were similar in magnitude (both r2 = 0.01). Within individuals, increased TST (b = 0.06, p < 0.001), later wake time (b = 0.09, p < 0.001), earlier bedtime (b = − 0.07, p < 0.001), as well as lower day-to-day shifts in TST (b = −0.011, p < 0.001) and in wake time (b = −0.004, p < 0.001) were associated with improved next-day mood. Variability in sleep parameters substantially impacted mood and depression, similar in magnitude to the mean levels of sleep parameters. Interventions that target sleep consistency, along with sleep duration, hold promise to improve mental health.
Population subgroup differences in the use of a COVID-19 chatbot
Authors: Schubel Laura C. , Wesley Deliya B. , Booker Ethan , Lock John , Ratwani Raj M.
Published: February 2021

COVID-19 chatbots are widely used to screen for symptoms and disseminate information about the virus, yet little is known about the population subgroups that interact with this technology and the specific features that are used. An analysis of 1,000,740 patients invited to use a COVID-19 chatbot, 69,451 (6.94%) of which agreed to participate, shows differences in chatbot feature use by gender, race, and age. These results can inform future public health COVID-19 symptom screening and information dissemination strategies.
Spermidine-induced recovery of human dermal structure and barrier function by skin microbiome
Authors: Kim Gihyeon , Kim Misun , Kim Minji , Park Changho , Yoon Youngmin , Lim Doo-Hyeon , Yeo Hyeonju , Kang Seunghyun , Lee Yeong-Geun , Beak Nam-In , Lee Jongsung , Kim Sujeong , Kwon Jee Young , Choi Won Woo , Lee Charles , Yoon Kyoung Wan , Park Hansoo , Lee Dong-Geol
Published: February 2021

An unbalanced microbial ecosystem on the human skin is closely related to skin diseases and has been associated with inflammation and immune responses. However, little is known about the role of the skin microbiome on skin aging. Here, we report that the Streptococcus species improved the skin structure and barrier function, thereby contributing to anti-aging. Metagenomic analyses showed the abundance of Streptococcus in younger individuals or those having more elastic skin. Particularly, we isolated Streptococcus pneumoniae, Streptococcus infantis, and Streptococcus thermophilus from face of young individuals. Treatment with secretions of S. pneumoniae and S. infantis induced the expression of genes associated with the formation of skin structure and the skin barrier function in human skin cells. The application of culture supernatant including Streptococcal secretions on human skin showed marked improvements on skin phenotypes such as elasticity, hydration, and desquamation. Gene Ontology analysis revealed overlaps in spermidine biosynthetic and glycogen biosynthetic processes. Streptococcus-secreted spermidine contributed to the recovery of skin structure and barrier function through the upregulation of collagen and lipid synthesis in aged cells. Overall, our data suggest the role of skin microbiome into anti-aging and clinical applications.
Quercetin 3,5,7,3′,4′-pentamethyl ether from Kaempferia parviflora directly and effectively activates human SIRT1
Authors: Zhang Mimin , Lu Peng , Terada Tohru , Sui Miaomiao , Furuta Haruka , Iida Kilico , Katayama Yukie , Lu Yi , Okamoto Ken , Suzuki Michio , Asakura Tomiko , Shimizu Kentaro , Hakuno Fumihiko , Takahashi Shin-Ichiro , Shimada Norimoto , Yang Jinwei , Ishikawa Tsutomu , Tatsuzaki Jin , Nagata Koji
Published: February 2021

Sirtuin 1 (SIRT1), an NAD+-dependent deacetylase, is a crucial regulator that produces multiple physiological benefits, such as the prevention of cancer and age-related diseases. SIRT1 is activated by sirtuin-activating compounds (STACs). Here, we report that quercetin 3,5,7,3′,4′-pentamethyl ether (KPMF-8), a natural STAC from Thai black gingerKaempferia parviflora, interacts with SIRT1 directly and stimulates SIRT1 activity by enhancing the binding affinity of SIRT1 with Ac-p53 peptide, a native substrate peptide without a fluorogenic moiety. The binding affinity between SIRT1 and Ac-p53 peptide was enhanced 8.2-fold by KPMF-8 but only 1.4-fold by resveratrol. The specific binding sites of KPMF-8 to SIRT1 were mainly localized to the helix2–turn–helix3 motif in the N-terminal domain of SIRT1. Intracellular deacetylase activity in MCF-7 cells was promoted 1.7-fold by KPMF-8 supplemented in the cell medium but only 1.2-fold by resveratrol. This work reveals that KPMF-8 activates SIRT1 more effectively than resveratrol does.
Climate change threatens Chinook salmon throughout their life cycle
Authors: Crozier Lisa G. , Burke Brian J. , Chasco Brandon E. , Widener Daniel L. , Zabel Richard W.
Published: February 2021

Widespread declines in Atlantic and Pacific salmon (Salmo salar and Oncorhynchus spp.) have tracked recent climate changes, but managers still lack quantitative projections of the viability of any individual population in response to future climate change. To address this gap, we assembled a vast database of survival and other data for eight wild populations of threatened Chinook salmon (O. tshawytscha). For each population, we evaluated climate impacts at all life stages and modeled future trajectories forced by global climate model projections. Populations rapidly declined in response to increasing sea surface temperatures and other factors across diverse model assumptions and climate scenarios. Strong density dependence limited the number of salmon that survived early life stages, suggesting a potentially efficacious target for conservation effort. Other solutions require a better understanding of the factors that limit survival at sea. We conclude that dramatic increases in smolt survival are needed to overcome the negative impacts of climate change for this threatened species.
Endosomal TLR3 co-receptor CLEC18A enhances host immune response to viral infection
Authors: Huang Ya-Lang , Huang Ming-Ting , Sung Pei-Shan , Chou Teh-Ying , Yang Ruey-Bing , Yang An-Suei , Yu Chung-Ming , Hsu Yu-Wen , Chang Wei-Chiao , Hsieh Shie-Liang
Published: February 2021

Human C-type lectin member 18A (CLEC18A) is ubiquitously expressed in human, and highest expression levels are found in human myeloid cells and liver. In contrast, mouse CLEC18A (mCLEC18A) is only expressed in brain, kidney and heart. However, the biological functions of CLEC18A are still unclear. We have shown that a single amino acid change (S339 →R339) in CTLD domain has profound effect in their binding to polysaccharides and house dust mite allergens. In this study, we further demonstrate that CLEC18A and its mutant CLEC18A(S339R) associate with TLR3 in endosome and bind poly (I:C) specifically. Compared to TLR3 alone, binding affinity to poly (I:C) is further increased in TLR3-CLEC18A and TLR3-CLEC18A(S339R) complexes. Moreover, CLEC18A and CLEC18A(S339R) enhance the production of type I and type III interferons (IFNs), but not proinflammatory cytokines, in response to poly (I:C) or H5N1 influenza A virus (IAV) infection. Compared to wild type (WT) mice, ROSA-CLEC18A and ROSA-CLEC18A(S339R) mice generate higher amounts of interferons and are more resistant to H5N1 IAV infection. Thus, CLEC18A is a TLR3 co-receptor, and may contribute to the differential immune responses to poly (I:C) and IAV infection between human and mouse.
Ex vivo visualization of RNA polymerase III-specific gene activity with electron microscopy
Authors: Manger Sina , Ermel Utz H. , Frangakis Achilleas S.
Published: February 2021

The direct study of transcription or DNA–protein-binding events, requires imaging of individual genes at molecular resolution. Electron microscopy (EM) can show local detail of the genome. However, direct visualization and analysis of specific individual genes is currently not feasible as they cannot be unambiguously localized in the crowded, landmark-free environment of the nucleus. Here, we present a method for the genomic insertion of gene clusters that can be localized and imaged together with their associated protein complexes in the EM. The method uses CRISPR/Cas9 technology to incorporate several genes of interest near the 35S rRNA gene, which is a frequently occurring, easy-to-identify genomic locus within the nucleolus that can be used as a landmark in micrographs. As a proof of principle, we demonstrate the incorporation of the locus-native gene RDN5 and the locus-foreign gene HSX1. This led to a greater than 7-fold enrichment of RNA polymerase III (Pol III) complexes associated with the genes within the field of view, allowing for a significant increase in the analysis yield. This method thereby allows for the insertion and direct visualization of gene clusters for a range of analyses, such as changes in gene activity upon alteration of cellular or external factors.
Temporal association between human upper respiratory and gut bacterial microbiomes during the course of COVID-19 in adults
Authors: Xu Rong , Lu Renfei , Zhang Tao , Wu Qunfu , Cai Weihua , Han Xudong , Wan Zhenzhou , Jin Xia , Zhang Zhigang , Zhang Chiyu
Published: February 2021

SARS-CoV-2 is the cause of COVID-19. It infects multiple organs including the respiratory tract and gut. Dynamic changes of regional microbiomes in infected adults are largely unknown. Here, we performed longitudinal analyses of throat and anal swabs from 35 COVID-19 and 19 healthy adult controls, as well as 10 non-COVID-19 patients with other diseases, by 16 S rRNA gene sequencing. The results showed a partitioning of the patients into 3-4 categories based on microbial community types (I-IV) in both sites. The bacterial diversity was lower in COVID-19 patients than healthy controls and decreased gradually from community type I to III/IV. Although the dynamic change of microbiome was complex during COVID-19, a synchronous restoration of both the upper respiratory and gut microbiomes from early dysbiosis towards late more diverse status was observed in 6/8 mild COVID-19 adult patients. These findings reveal previously unknown interactions between upper respiratory and gut microbiomes during COVID-19.
Efficient alkane oxidation under combustion engine and atmospheric conditions
Authors: Wang Zhandong , Ehn Mikael , Rissanen Matti P. , Garmash Olga , Quéléver Lauriane , Xing Lili , Monge-Palacios Manuel , Rantala Pekka , Donahue Neil M. , Berndt Torsten , Sarathy S. Mani
Published: February 2021

Oxidation chemistry controls both combustion processes and the atmospheric transformation of volatile emissions. In combustion engines, radical species undergo isomerization reactions that allow fast addition of O2. This chain reaction, termed autoxidation, is enabled by high engine temperatures, but has recently been also identified as an important source for highly oxygenated species in the atmosphere, forming organic aerosol. Conventional knowledge suggests that atmospheric autoxidation requires suitable structural features, like double bonds or oxygen-containing moieties, in the precursors. With neither of these functionalities, alkanes, the primary fuel type in combustion engines and an important class of urban trace gases, are thought to have minor susceptibility to extensive autoxidation. Here, utilizing state-of-the-art mass spectrometry, measuring both radicals and oxidation products, we show that alkanes undergo autoxidation much more efficiently than previously thought, both under atmospheric and combustion conditions. Even at high concentrations of NOX, which typically rapidly terminates autoxidation in urban areas, the studied C6–C10 alkanes produce considerable amounts of highly oxygenated products that can contribute to urban organic aerosol. The results of this inter-disciplinary effort provide crucial information on oxidation processes in both combustion engines and the atmosphere, with direct implications for engine efficiency and urban air quality.
Organophotocatalytic dearomatization of indoles, pyrroles and benzo(thio)furans via a Giese-type transformation
Authors: Zhang Yueteng , Ji Peng , Gao Feng , Dong Yue , Huang He , Wang Changqing , Zhou Ziyuan , Wang Wei
Published: February 2021

Accessing fascinating organic and biological significant indolines via dearomatization of indoles represents one of the most efficient approaches. However, it has been difficult for the dearomatization of the electron deficient indoles. Here we report the studies leading to developing a photoredox mediated Giese-type transformation strategy for the dearomatization of the indoles. The reaction has been implemented for chemoselectively breaking indolyl C=C bonds embedded in the aromatic system. The synthetic power of this strategy has been demonstrated by using structurally diverse indoles bearing common electron-withdrawing groups including (thio)ester, amide, ketone, nitrile and even aromatics at either C2 or C3 positions and ubiquitous carboxylic acids as radical coupling partner with high trans-stereoselectivity (>20:1 dr). This manifold can also be applied to other aromatic heterocycles including pyrroles, benzofurans and benzothiophenes. Furthermore, enantioselective dearomatization of indoles has been achieved by a chiral camphorsultam auxiliary with high diastereoselectivity.
Universal mobility characteristics of graphene originating from charge scattering by ionised impurities
Authors: Gosling Jonathan H. , Makarovsky Oleg , Wang Feiran , Cottam Nathan D. , Greenaway Mark T. , Patanè Amalia , Wildman Ricky D. , Tuck Christopher J. , Turyanska Lyudmila , Fromhold T. Mark
Published: February 2021

Pristine graphene and graphene-based heterostructures can exhibit exceptionally high electron mobility if their surface contains few electron-scattering impurities. Mobility directly influences electrical conductivity and its dependence on the carrier density. But linking these key transport parameters remains a challenging task for both theorists and experimentalists. Here, we report numerical and analytical models of carrier transport in graphene, which reveal a universal connection between graphene’s carrier mobility and the variation of its electrical conductivity with carrier density. Our model of graphene conductivity is based on a convolution of carrier density and its uncertainty, which is verified by numerical solution of the Boltzmann transport equation including the effects of charged impurity scattering and optical phonons on the carrier mobility. This model reproduces, explains, and unifies experimental mobility and conductivity data from a wide range of samples and provides a way to predict a priori all key transport parameters of graphene devices. Our results open a route for controlling the transport properties of graphene by doping and for engineering the properties of 2D materials and heterostructures.
Revealing the intrinsic superconducting gap anisotropy in surface-neutralized BaFe2(As0.7P0.3)2
Authors: Xin Ziming , Wang Yudi , Cai Cong , Wang Zhengguo , Chen Lei , Han Tingting , Zhang Yan
Published: February 2021

Alkaline-earth iron arsenide (122) is one of the most studied families of iron-based superconductors, especially for angle-resolved photoemission spectroscopy. While extensive photoemission results have been obtained, the surface complexity of 122 caused by its charge-non-neutral surface is rarely considered. Here, we show that the surface of 122 can be neutralized by potassium deposition. In potassium-coated BaFe2(As0.7P0.3)2, the surface-induced spectral broadening is strongly suppressed, and hence the coherent spectra that reflect the intrinsic bulk electronic state recover. This enables the measuring of superconducting gap with unpreceded precision. The result shows the existence of two pairing channels. While the gap anisotropy on the outer hole/electron pockets can be well fitted using an s± gap function, the gap anisotropy on the inner hole/electron shows a clear deviation. Our results provide quantitative constraints for refining theoretical models and also demonstrate an experimental method for revealing the intrinsic electronic properties of 122 in future studies.
Photovoltaic neurointerface based on aluminum antimonide nanocrystals
Authors: Han Mertcan , Bahmani Jalali Houman , Yildiz Erdost , Qureshi Mohammad Haroon , Şahin Afsun , Nizamoglu Sedat
Published: February 2021

Light activated modulation of neural activity is an emerging field for the basic investigation of neural systems and development of new therapeutic methods such as artificial retina. Colloidal inorganic nanocrystals have great potential for neural interfaces due to their adjustable optoelectronic properties via high-level structural, compositional, and size control. However, toxic heavy metal content (e.g., cadmium, mercury), electrochemical coupling to the cells and low photon-to-current efficiency limit their effective use. Here, we introduce the use of aluminum antimonide (AlSb) nanocrystals as the cell interfacing layer for capacitive neural stimulation in the blue spectrum. We demonstrate successful photostimulation of primary hippocampal neurons below ocular safety limits. In addition, our device shows high biocompatibility in vitro and passive accelerated ageing tests indicate a functional lifetime over 3 years showing their feasible use for chronic implants. We demonstrate that nanocrystal biointerfaces hold high promise for future bioelectronics and protheses.
Biological nitrous oxide consumption in oxygenated waters of the high latitude Atlantic Ocean
Authors: Rees Andrew P. , Brown Ian J. , Jayakumar Amal , Lessin Gennadi , Somerfield Paul J. , Ward Bess B.
Published: February 2021

Nitrous oxide (N2O) is important to the global radiative budget of the atmosphere and contributes to the depletion of stratospheric ozone. Globally the ocean represents a large net flux of N2O to the atmosphere but the direction of this flux varies regionally. Our understanding of N2O production and consumption processes in the ocean remains incomplete. Traditional understanding tells us that anaerobic denitrification, the reduction of NO3− to N2 with N2O as an intermediate step, is the sole biological means of reducing N2O, a process known to occur in anoxic environments only. Here we present experimental evidence of N2O removal under fully oxygenated conditions, coupled with observations of bacterial communities with novel, atypical gene sequences for N2O reduction. The focus of this work was on the high latitude Atlantic Ocean where we show bacterial consumption sufficient to account for oceanic N2O depletion and the occurrence of regional sinks for atmospheric N2O.
Chemolithotrophy on the Noachian Martian breccia NWA 7034 via experimental microbial biotransformation
Authors: Milojevic Tetyana , Albu Mihaela , Kölbl Denise , Kothleitner Gerald , Bruner Robert , Morgan Matthew L.
Published: February 2021

Multiple lines of evidence indicate an active hydrogeological history of Mars and chemolithoautotrophy-suited environments within its Noachian terrains. As a result, one of the primary aims of upcoming missions to Mars is to search for signs of ancient life. Here we report on laboratory-scaled microbially assisted chemolithoautotrophic biotransformation of the Noachian Martian breccia Northwest Africa (NWA) 7034 composed of ancient (~4.5 Gyr old) crustal materials from Mars. Nanoanalytical hyperspectral analysis provides clues for the trafficking and distribution of meteorite inorganic constituents in the microbial cell. We decipher biomineralization patterns associated with the biotransformation and reveal microbial nanometer-sized lithologies located inside the cell and on its outer surface layer. These investigations provide an opportunity to trace the putative bioalteration processes of the Martian crust and to assess the potential biogenicity of Martian materials.
The vulnerability of lakes to climate change along an altitudinal gradient
Authors: Råman Vinnå Love , Medhaug Iselin , Schmid Martin , Bouffard Damien
Published: February 2021

Studies of future 21stcentury climate warming in lakes along altitudinal gradients have been partially obscured by local atmospheric phenomena unresolved in climate models. Here we forced the physical lake model Simstrat with locally downscaled climate models under three future scenarios to investigate the impact on 29 Swiss lakes, varying in size along an altitudinal gradient. Results from the worst-case scenario project substantial change at the end of the century in duration of ice-cover at mid to high altitude (−2 to −107 days), stratification duration (winter −17 to −84 days, summer −2 to 73 days), while lower and especially mid altitude (present day mean annual air temperature from 9 °C to 3 °C) dimictic lakes risk shift to monomictic regimes (seven out of the eight lakes). Analysis further indicates that for many lakes shifts in mixing regime can be avoided by adhering to the most stringent scenario.
Author Correction: Coincident locations of rupture nucleation during the 2019 Le Teil earthquake, France and maximum stress change from local cement quarrying
Authors: De Novellis Vincenzo , Convertito Vincenzo , Valkaniotis Sotiris , Casu Francesco , Lanari Riccardo , Monterroso Tobar Mario Fernando , Pino Nicola Alessandro
Published: February 2021

A Correction to this paper has been published: https://doi.org/10.1038/s43247-021-00109-7
Author Correction: Airborne microplastic particles detected in the remote marine atmosphere
Authors: Trainic Miri , Flores J. Michel , Pinkas Iddo , Pedrotti Maria Luiza , Lombard Fabien , Bourdin Guillaume , Gorsky Gabriel , Boss Emmanuel , Rudich Yinon , Vardi Assaf , Koren Ilan
Published: February 2021

A Correction to this paper has been published: https://doi.org/10.1038/s43247-021-00119-5
The designed synthesis of a hydrophobic covalent polymer composite to expel toxic dyes and oil from wastewater: theoretical corroboration
Authors: Dey Debanjan , Mondal Amita , Nag Somrita , Mondal Udayan , Hirani Harish , Banerjee Priyabrata
Published: February 2021

In pursuit of addressing a global issue linked to the purification of contaminated water bodies, hydrophobic covalent organic framework (CPCMERI-2020) and its post-synthetically modified composites CPWCS and MS@CPWCS are reported herein.
Light-responsive dual-functional biodegradable mesoporous silica nanoparticles with drug delivery and lubrication enhancement for the treatment of osteoarthritis
Authors: Zhao Weiwei , Wang Hua , Wang Haimang , Han Ying , Zheng Zhibo , Liu Xudong , Feng Bin , Zhang Hongyu
Published: February 2021

Visible light-responsive biodegradable mesoporous silica nanoparticles (bMSNs-AZO/CD-PMPC) were developed for osteoarthritis treatment, which simultaneously achieved lubrication enhancement and anti-inflammation.
Organometallic AIEgens for biological theranostics
Authors: Qi Chunxuan , Wang Xiaoxuan , Chen Zhengpeng , Xiang Song , Wang Tao , Feng Hai-Tao , Tang Ben Zhong
Published: February 2021

The marriage of AIEgens and organometallic complexes has shown great potential in biological probes and photosensitizers.
Techno-economic analysis of metal–organic frameworks for adsorption heat pumps/chillers: from directional computational screening, machine learning to experiment
Authors: Shi Zenan , Yuan Xueying , Yan Yaling , Tang Yuanlin , Li Junjie , Liang Hong , Tong Lianpeng , Qiao Zhiwei
Published: February 2021

The equipment cost, cycle cost, and material cost analyses of adsorption heat pumps/chillers using 6013 real and 137 953 hypothetical MOFs were performed by computational screening, machine learning and experiment.
Engineering cation defect-mediated Z-scheme photocatalysts for a highly efficient and stable photocatalytic hydrogen production
Authors: Yu Kai , Huang Hai-Bo , Wang Jun-Tao , Liu Gui-Fang , Zhong Zhou , Li Ya-Feng , Cao Hai-Lei , Lü Jian , Cao Rong
Published: February 2021

Z-scheme CdS/ZnS heterostructures with cation defects show enhanced photocatalytic activity and stability of water splitting.
Non-linear light emission of inorganic protonic diodes, H+LEDs
Authors: Langer Jerzy J. , Frąckowiak Ewelina
Published: February 2021

H+LEDs are light emitting devices based on a protonic p–n junction; now with no organic polymers. The unique are non-linear optical effects: collimated light beams and stimulated Raman scattering (SRS), observed while generating intense light pulses.
Pyrolyzed M–Nx catalysts for oxygen reduction reaction: progress and prospects
Authors: Luo Ergui , Chu Yuyi , Liu Jie , Shi Zhaoping , Zhu Siyuan , Gong Liyuan , Ge Junjie , Choi Chang Hyuck , Liu Changpeng , Xing Wei
Published: February 2021

This review showcases the recent progress in understanding and designing M–Nx/C electrocatalysts towards the ORR, aiming to provide some guidelines for their practical applications in PEMFCs.
Optimizing the vectorial component of first hyperpolarizabilities of push–pull chromophores to boost the electro-optic activities of poled polymers over broad telecom wavelength bands
Authors: Zou Jie , Zhang Di , Chen Weilong , Luo Jingdong
Published: February 2021

Alternating the sequence of thiophene-based π-conjugation bridge of push–pull chromophores significantly improves the vectorial component of first hyperpolarizabilities and polar order of molecules for large electro-optic activities of poled films.
A high-performance asymmetric supercapacitor-based (CuCo)Se2/GA cathode and FeSe2/GA anode with enhanced kinetics matching
Authors: Tian Zhen , Zhao Zhenxin , Wang Xiaomin , Chen Yanjun , Li Dan , Linghu Yaoyao , Wang Yongzhen , Wang Chao
Published: February 2021

An ASC device is assembled by constructing a CuCo2Se4/GA cathode and a FeSe2/GA anode, and the potential variation during cycling is monitored.
Rational construction of Au3Cu@Cu nanocages with porous core–shell heterostructured walls for enhanced electrocatalytic N2fixation
Authors: Liu Songliang , Xu You , Jiao Shiqian , Tian Wenjing , Zhou Tongqing , Wang Ziqiang , Li Xiaonian , Wang Liang , Wang Hongjing
Published: February 2021

Au3Cu@Cu nanocages have been synthesized for electrocatalytic N2fixation with enhanced catalytic performance.
Diagnosis and detection of dynamic eccentricity fault for permanent magnet transverse flux generator
Authors: Pourmoosa Ali. A. , Ghods Mehrage , Faiz Jawad , Vaez‐Zadeh Sadegh
Published: February 2021

The authors analyse no‐load and full‐load performance of a permanent magnet transverse flux generators (PMTFGs) in fully aligned condition as well as under different types of mechanical faults including static eccentricity (SE), dynamic eccentricity (DE), inclined rotor (IR) and run‐out (RO) faults. An analytical model is developed to calculate the air‐gap permeance. This permeance is used to estimate the flux density and back‐electromotive force in the healthy and faulty machine. Performance of the machine is predicted using the proposed analytical model and verified by comparing it with the results obtained using three‐dimensional time stepping finite element method. Finally, the spectra of stator current in the PMTFG under SE, DE, IR and OR faults are determined through which the amplitude of side‐band components with a specific frequency pattern is extracted. It can detect the eccentricity fault precisely, recognise its type and determines its severity.
Segmentation using fuzzy cluster‐based thresholding method for apple fruit sorting
Authors: Henila Manickam , Chithra Palaniappan
Published: February 2021

Apple fruit sorting has been an important postharvest process carried on for the sorting of diseased apple fruits. A fuzzy cluster‐based thresholding (FCBT) method for segmenting the region of interest from an apple image has been proposed for sorting apples in this study. As the first step, the acquired RGB colour image of an apple fruit was converted into a greyscale image. Then, five different fuzzy cluster bins with overlapped pixel ranges were taken and greypixel values were binned into them. A cluster with the maximum number of pixels was selected for calculating the threshold value. The region of interest from the apple image was then segmented using the proposed FCBT value. Features extracted from the segmented images were given as input to a fully‐connected deep neural network for a classification. The performance of the FCBT method was compared with similar greyscale thresholding methods like Otsu's and Kapur's methods. The visual segmentation accuracy and the execution speed showed that the FCBT outperformed the other methods in segmenting the diseased area. A fully‐connected deep neural network model with the FCBT image extracted features as input values gave a 98.33% accuracy rate in sorting the apple images.
Machine learning and deep learning for clinical data and PET/SPECT imaging in Parkinson's disease: a review
Authors: Khachnaoui Hajer , Mabrouk Rostom , Khlifa Nawres
Published: February 2021

Machine Learning (ML) is a subfield of Artificial Intelligence (AI) that is increasingly applied to several medical diagnosis tasks, including a wide range of diseases. Importantly, various ML models were developed to address the complexity of Parkinson's Disease (PD) diagnosis. PD is a neurodegenerative disease characterized by motor and non‐motor disorders where its syndromes affect the daily lives of patients. Several Computer Aided Diagnosis and Detection (CADD) systems based on hand‐crafted ML algorithms achieved promising results in distinguishing PD patients from Healthy Control (HC) subjects and other Parkinsonian syndrome categories using clinical data (e.g., speech and gait impairments) and medical imaging [e.g., Position Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT)]. Despite the good performance of hand‐crafted ML algorithms, there is still a problem linked to the features' extraction and selection. In fact, Deep Learning DL has provided an ultimate solution for the features' extraction and selection related issue. An important number of studies on the diagnosis of PD using DL algorithms were developed recently. This study provides an overview of the application of hand‐crafted ML algorithms and DL techniques for PD diagnosis. It also introduces key concepts for understanding the application of ML methods to diagnose PD.
Ensemble learning‐based COVID‐19 detection by feature boosting in chest X‐ray images
Authors: Upadhyay Kamini , Agrawal Monika , Deepak Desh
Published: February 2021

The novel coronavirus has spread quite rapidly across the globe. The current testing rate is failing to match the exponential rate of rising cases. Moreover, the available testing methodologies are expensive and time‐consuming. A sensitive automated diagnosis is one of the biggest need of the hour. In the proposed work, the authors analyse the chest X‐ray images of normal, pneumonia and coronavirus disease‐2019 (COVID‐19) patients and process them to boost the COVID‐specific features (opacities etc.), which enable to perform sensitive identification of COVID‐19 patients. The sets of original and processed images are used with a stack of pre‐trained deep models for ensemble learning. They used VGG‐16 as base‐learners, trained with a diverse set of inputs followed by a logistic regression model, the meta learner, to combine the base‐learner predictions. The proposed fusion‐based model is trained and tested for three types of classification, TYPE‐I: binary (NORMAL/ABNORMAL), TYPE‐II: binary (PNEUMONIA/COVID‐19) and TYPE‐III: multi‐class (NORMAL/PNEUMONIA/COVID‐19). The diagnosis results are quite promising, with high accuracy and sensitivity values for all the cases. The proposed algorithm can be used to assist the medical experts for quick identification and isolation of COVID‐19 patients and thereby mitigating the effect of the virus.