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Enteric viruses like norovirus, rotavirus and astrovirus have long been accepted as spreading in the population through fecal–oral transmission: viruses are shed into feces from one host and enter the oral cavity of another, bypassing salivary glands (SGs) and reaching the intestines to replicate, be shed in feces and repeat the transmission cycle 1 . Yet there are viruses (for example, rabies) that infect the SGs 2 , 3 , making the oral cavity one site of replication and saliva one conduit of transmission. Here we report that enteric viruses productively and persistently infect SGs, reaching titres comparable to those in the intestines. We demonstrate that enteric viruses get released into the saliva, identifying a second route of viral transmission. This is particularly significant for infected infants, whose saliva directly transmits enteric viruses to their mothers’ mammary glands through backflow during suckling. This sidesteps the conventional gut–mammary axis route 4 and leads to a rapid surge in maternal milk secretory IgA antibodies 5 , 6 . Lastly, we show that SG-derived spheroids 7 and cell lines 8 can replicate and propagate enteric viruses, generating a scalable and manageable system of production. Collectively, our research uncovers a new transmission route for enteric viruses with implications for therapeutics, diagnostics and importantly sanitation measures to prevent spread through saliva. Enteric viruses replicate in salivary glands, can be propagated in salivary gland-derived spheroids and cell lines, and are released into saliva, which is a new transmission route having implications for therapeutics, diagnostics and sanitation measures.  

Precise yield predictions are useful for implementing precision agriculture technologies and making better decisions in crop management. Convolutional neural networks (CNNs) have recently been used to predict crop yields in unmanned aerial vehicle (UAV)-based remote sensing studies, but weather data have not been considered in modeling. The aim of this study was to explore the potential of multimodal deep learning on rice yield prediction accuracy using UAV multispectral images at the heading stage, along with weather data. The effects of the CNN architectures, layer depths, and weather data integration methods on the prediction accuracy were evaluated. Overall, the multimodal deep learning model integrating UAV-based multispectral imagery and weather data had the potential to develop more precise rice yield predictions. The best models were those trained with weekly weather data. A simple CNN feature extractor for UAV-based multispectral image input data might be sufficient to predict crop yields accurately. However, the spatial patterns of the predicted yield maps differed from model to model, although the prediction accuracy was almost the same. The results indicated that not only the prediction accuracies, but also the robustness of within-field yield predictions, should be assessed in further studies.

Prediction of crop yield and quality is an essential component of successful implementation of precision agriculture. Given the recent commercialization of low-cost multispectral cameras mounted on unmanned aerial vehicles and advances in machine learning techniques, prediction systems for crop characteristics can be more precisely developed using machine learning techniques. Therefore, the model performances for predicting wheat grain yield and protein content between the machine learning algorithms based on spectral reflectance and plant height (e.g. random forest and artificial neural network) and the traditional linear regression based on vegetation indices were compared. Although the machine learning approaches based on reflectance could not improve the grain yield prediction accuracy, they have great potential for development in predicting protein content. The linear regression model based on a 2-band enhanced vegetation index was capable of predicting the yield with a root-mean-square error (RMSE) of 972 kg ha −1 . The random forest model based on reflectance was capable of predicting the protein content with an RMSE of 1.07%. The reflectance may have been linearly correlated with total biomass; thus, it was also linearly correlated with grain yield. There was a nonlinear relationship between the grain yield and protein content, which may have resulted in the higher model performance of the machine learning approaches in predicting protein content. However, this relationship would be variable according to the environment and agronomic practice. Further, field-scale research is required to assess how this relationship can be varied and affect the model generality, particularly when predicting protein content.

The lack of reliable measures of alcohol intake is a major obstacle to the diagnosis and treatment of alcohol-related diseases. Epigenetic modifications such as DNA methylation may provide novel biomarkers of alcohol use. To examine this possibility, we performed an epigenome-wide association study of methylation of cytosine-phosphate-guanine dinucleotide (CpG) sites in relation to alcohol intake in 13 population-based cohorts (ntotal =13 317; 54% women; mean age across cohorts 42-76 years) using whole blood (9643 European and 2423 African ancestries) or monocyte-derived DNA (588 European, 263 African and 400 Hispanic ancestry) samples. We performed meta-analysis and variable selection in whole-blood samples of people of European ancestry (n=6926) and identified 144 CpGs that provided substantial discrimination (area under the curve=0.90-0.99) for current heavy alcohol intake ([egs]42 g per day in men and [egs]28 g per day in women) in four replication cohorts. The ancestry-stratified meta-analysis in whole blood identified 328 (9643 European ancestry samples) and 165 (2423 African ancestry samples) alcohol-related CpGs at Bonferroni-adjusted P<1 × 10-7 . Analysis of the monocyte-derived DNA (n=1251) identified 62 alcohol-related CpGs at P<1 × 10-7 . In whole-blood samples of people of European ancestry, we detected differential methylation in two neurotransmitter receptor genes, the γ-Aminobutyric acid-A receptor delta and γ-aminobutyric acid B receptor subunit 1; their differential methylation was associated with expression levels of a number of genes involved in immune function. In conclusion, we have identified a robust alcohol-related DNA methylation signature and shown the potential utility of DNA methylation as a clinically useful diagnostic test to detect current heavy alcohol consumption.

Phase angle (PhA) can be determined through bioelectrical impedance analysis and is a unique variable for skeletal muscle. The objective of this study was to evaluate the relationship between PhA and muscle mass/quality in older adults. In addition, we attempted to determine the cutoff value of PhA for poor muscle function. Community-dwelling Japanese older men (n=285, 81.1±7.1 years) and women (n=724, 80.4±6.8 years) participated in this study and were classified into four groups based on the Asian Working Group for Sarcopenia (normal, presarcopenia, dynapenia, and sarcopenia). We measured PhA using bioelectrical impedance analysis, muscle quantity and quality indicators using ultrasonography, muscle strength, and physical performance and compared them in four groups. We also tried to determine the cutoff value of PhA for poor muscle function. We found a significant difference in PhA among the four groups in men (P<0.05), and the dynapenia (3.61±0.75°) and sarcopenia groups (3.40±0.74°) showed significantly lower values than the normal group (4.50±0.86°) (P<0.05), but not the presarcopenia group (4.12±0.85°). In women, a significant difference was also observed among the four groups (P<0.05), and the dynapenia (3.41±0.65°) and sarcopenia groups (3.31±0.66°) showed significantly lower measures than the normal group (4.14±0.71°) (P<0.05), but not the presarcopenia group (4.07±0.51°). The receiver-operating characteristic curve analysis indicated the best cutoff value of PhA (men: 4.05°, women: 3.55°) to discriminate sarcopenia and dynapenia from normal and presarcopenia. These findings suggest that PhA is a useful indicator for muscle function.

The androgen receptor (AR) has a central role in prostate cancer progression, particularly treatment-resistance disease including castration-resistant prostate cancer. Loss of the p53 tumor suppressor, a nuclear transcription factor, is also known to contribute to prostate malignancy. Here we report that p53 is translocated to the cytoplasm by androgen-mediated induction of G3BP2, a newly described direct target gene of AR. G3BP2 induces both cell cycle progression and blocks apoptosis. Translocation of p53 is regulated by androgen-dependent sumoylation mediated by the G3BP2-interacting SUMO-E3 ligase, RanBP2. G3BP2 knockdown results in reduced tumor growth and increased nuclear p53 accumulation in mouse xenograft models of prostate cancer with or without long-term androgen deprivation. Moreover, strong cytoplasmic p53 localization is correlated clinically with elevated G3BP2 expression and predicts poor prognosis and disease progression to the hormone-refractory state. Our findings reveal a new AR-mediated mechanism of p53 inhibition that promotes treatment-resistant prostate cancer.

By performing a global magnetohydrodynamic (MHD) simulation, we investigated magnetic disturbances on the ground at high‐latitudes in response to jumps in the solar wind dynamic pressure, namely a sudden commencement (SC). After the arrival of the jump, a pair of field‐aligned currents (FACs), related to the preliminary impulse, develop and travel in the anti‐sunward direction. Soon after another pair related to the main impulse (MI) appears and travels in the anti‐sunward direction. The horizontal ionospheric current associated with the MI remains strong when propagating to the nightside. On the dawnside the MI current flows sunward (anti‐sunward) resulting in northward (southward) ground magnetic disturbance at higher (lower) latitude in the post‐midnight sector. These features are similar to those observed in Canada in the high‐latitude post‐midnight sector when the Québec blackout took place on 13 March 1989. The nighttime geomagnetic perturbations associated with the MI occur regardless of the magnitude of the solar wind dynamic pressure and IMF orientation. The amplitude of the geoelectric field, which is closely related to the geomagnetically induced currents (GICs), reaches the maximum value just before and around the maximum of the southward magnetic disturbance. This is consistent with the moment at which the blackout occurred during the southward magnetic perturbation. We suggest that the blackout in Québec could be caused by the MI‐associated Hall current passing over the Hydro‐Québec power system on the nightside. The nighttime polar region is shown to be sensitive to hazardous GICs for large‐amplitude jumps in the solar wind dynamic pressure.

The magnetic moment of the antiproton is measured at the parts-per-billion level, improving on previous measurements by a factor of about 350. Magnetic moment of the antiproton Comparing the fundamental properties of normal-matter particles with their antimatter counterparts tests charge–parity–time (CPT) invariance, which is an important part of the standard model of particle physics. Many properties have been measured to the parts-per-billion level of uncertainty, but the magnetic moment of the antiproton has not. Christian Smorra and colleagues have now done so, and report that it is −2.7928473441 ± 0.0000000042 in units of the nuclear magneton. This is consistent with the magnetic moment of the proton, 2.792847350 ± 0.000000009 in the same units. Assuming CPT invariance, these two values should be the same, except for the difference in sign, so this result provides a more stringent constraint on certain CPT-violating effects. Precise comparisons of the fundamental properties of matter–antimatter conjugates provide sensitive tests of charge–parity–time (CPT) invariance 1 , which is an important symmetry that rests on basic assumptions of the standard model of particle physics. Experiments on mesons 2 , leptons 3 , 4 and baryons 5 , 6 have compared different properties of matter–antimatter conjugates with fractional uncertainties at the parts-per-billion level or better. One specific quantity, however, has so far only been known to a fractional uncertainty at the parts-per-million level 7 , 8 : the magnetic moment of the antiproton, . The extraordinary difficulty in measuring with high precision is caused by its intrinsic smallness; for example, it is 660 times smaller than the magnetic moment of the positron 3 . Here we report a high-precision measurement of in units of the nuclear magneton μ N with a fractional precision of 1.5 parts per billion (68% confidence level). We use a two-particle spectroscopy method in an advanced cryogenic multi-Penning trap system. Our result  = −2.7928473441(42) μ N (where the number in parentheses represents the 68% confidence interval on the last digits of the value) improves the precision of the previous best measurement 8 by a factor of approximately 350. The measured value is consistent with the proton magnetic moment 9 , μ p  = 2.792847350(9) μ N , and is in agreement with CPT invariance. Consequently, this measurement constrains the magnitude of certain CPT-violating effects 10 to below 1.8 × 10 −24 gigaelectronvolts, and a possible splitting of the proton–antiproton magnetic moments by CPT-odd dimension-five interactions to below 6 × 10 −12 Bohr magnetons 11 .

Convection is the most fundamental process in understanding the structure of geospace and disturbances observed in the magnetosphere-ionosphere (M-I) system. In this paper, a self-consistent configuration of the global convection system is considered under the real topology as a compound system. Investigations are made based on the M-I coupling scheme by analyzing numerical results obtained from magnetohydrodynamic (MHD) simulations which guarantee the self-consistency in the whole system under the Bv (magnetic field and velocity) paradigm. It is emphasized in the M-I coupling scheme that convection and field-aligned current (FAC) are different aspects of same physical process characterizing the open magnetosphere. Special attention is given in this paper to the energy supplying (dynamo) process that drives the FAC system. In the convection system, the dynamo must be constructed from shear motion together with plasma population regimes to steadily drive the convection. Convection patterns observed in the ionosphere are also the manifestation of achievement in global self-consistency. A primary approach to apply these concepts to the study of geospace is to consider how the M-I system adjusts the relative motion between the compressible magnetosphere and the incompressible ionosphere when responding to given solar-wind conditions. The above principle is also applicable for the study of disturbance phenomena such as the substorm as well as for the study of apparently unique processes such as the flux transfer event (FTE), the sudden commencement (SC), and the theta aurora. Finally, an attempt is made to understand the substorm as the extension of enhanced convection under the southward interplanetary magnetic field (IMF) condition.

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) has curative potential against hematological malignancies. However, there are concerns about the associated risk of non-relapse mortality (NRM). We performed a retrospective single-center study to assess changes in outcomes after allo-HSCT and causes of NRM over three 5-year periods. The rates of 2-year NRM and overall survival (OS) were 16% and 59%, respectively. We found a significant decrease in NRM ( P< 0.001), with 2-year NRM of 26, 14 and 9%, and a significant increase in OS ( P =0.005), with 2-year OS of 52%, 58% and 65%, over the three periods (1998–2002, 2003–2007 and 2008–2012), respectively. Of note, a steady improvement was observed in NRM, period by period, among patients aged 50 years or older, patients who underwent HSCT from an unrelated bone marrow donor and patients who underwent HSCT with a reduced-intensity conditioning regimen. Our data showed that the improved NRM can mainly be attributed to a decreased mortality related to infection after starting systemic steroid as GVHD treatment, and a decreased mortality related to organ failure.