Transverse myelitis associated with primary biliary cirrhosis: clinical, laboratory, and neuroradiological features.

PURPOSE: Only five patients diagnosed with transverse myelitis (TM) associated with primary biliary cirrhosis (PBC) have been reported in the literature to date. We report two additional patients with TM associated with PBC at our hospital and review all seven cases. MATERIALS AND METHODS: An association between neuromyelitis optic spectrum disease (NMOSD) and PBC is reported for the first time in one of our patients. The second patient was diagnosed with TM associated with PBC without Sjögren's syndrome (SS). A literature review was performed using the PubMed database. RESULTS: All patients diagnosed with TM associated with PBC were female with a median age of 53 years. TM was associated with SS in 71.4% of the patients. Complete TM and incomplete TM were diagnosed in 71.4% and 28.6% of the patients. The erythrocyte sedimentation rate was increased in 83.3% of patients. All patients were positive for anti-mitochondrial antibodies. Other autoantibodies, including anti-nuclear antibodies, rheumatoid factor, anti-SSA antibody, were detected in some patients. Cerebrospinal fluid analysis was abnormal in 83.3% of patients. The spinal cord lesions involved more than three vertebral segments in 85.7% of patients. Glucocorticoids were administered in 85.7% of patients, and good responses were observed. CONCLUSIONS: The association between TM and PBC may be missed by neurologists. More attention should be paid to the association between NMOSD and PBC. Most patients show SS and may experience relapse, and there is a good rationale for early commencement of immunosuppressive therapy.

Leaf Anthocyanin Content Retrieval with Partial Least Squares and Gaussian Process Regression from Spectral Reflectance Data.

Leaf pigment content retrieval is an essential research field in remote sensing. However, retrieval studies on anthocyanins are quite rare compared to those on chlorophylls and carotenoids. Given the critical physiological significance of anthocyanins, this situation should be improved. In this study, using the reflectance, partial least squares regression (PLSR) and Gaussian process regression (GPR) were sought to retrieve the leaf anthocyanin content. To our knowledge, this is the first time that PLSR and GPR have been employed in such studies. The results showed that, based on the logarithmic transformation of the reflectance (log(1/R)) with 564 and 705 nm, the GPR model performed the best (R2/RMSE (nmol/cm2): 0.93/2.18 in the calibration, and 0.93/2.20 in the validation) of all the investigated methods. The PLSR model involved four wavelengths and achieved relatively low accuracy (R2/RMSE (nmol/cm2): 0.87/2.88 in calibration, and 0.88/2.89 in validation). GPR apparently outperformed PLSR. The reason was likely that the non-linear property made GPR more effective than the linear PLSR in characterizing the relationship for the absorbance vs. content of anthocyanins. For GPR, selected wavelengths around the green peak and red edge region (one from each) were promising to build simple and accurate two-wavelength models with R2 > 0.90.

A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level.

Understanding large-scale crop growth and its responses to climate change are critical for yield estimation and prediction, especially under the increased frequency of extreme climate and weather events. County-level corn phenology varies spatially and interannually across the Corn Belt in the United States, where precipitation and heat stress presents a temporal pattern among growth phases (GPs) and vary interannually. In this study, we developed a long short-term memory (LSTM) model that integrates heterogeneous crop phenology, meteorology, and remote sensing data to estimate county-level corn yields. By conflating heterogeneous phenology-based remote sensing and meteorological indices, the LSTM model accounted for 76% of yield variations across the Corn Belt, improved from 39% of yield variations explained by phenology-based meteorological indices alone. The LSTM model outperformed least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) approaches for end-of-the-season yield estimation, as a result of its recurrent neural network structure that can incorporate cumulative and nonlinear relationships between corn yield and environmental factors. The results showed that the period from silking to dough was most critical for crop yield estimation. The LSTM model presented a robust yield estimation under extreme weather events in 2012, which reduced the root-mean-square error to 1.47 Mg/ha from 1.93 Mg/ha for LASSO and 2.43 Mg/ha for RF. The LSTM model has the capability to learn general patterns from high-dimensional (spectral, spatial, and temporal) input features to achieve a robust county-level crop yield estimation. This deep learning approach holds great promise for better understanding the global condition of crop growth based on publicly available remote sensing and meteorological data.

Detection of Matrilysin Activity Using Polypeptide Functionalized Reduced Graphene Oxide Field-Effect Transistor Sensor.

A novel approach for rapid and sensitive detection of matrilysin (MMP-7, a biomarker involved in the degradation of various macromolecules) based on a polypeptide (JR2EC) functionalized reduced graphene oxide (rGO) field effect transistor (FET) is reported. MMP-7 specifically digests negatively charged JR2EC immobilized on rGO, thereby modulating the conductance of rGO-FET. The proposed assay enabled detection of MMP-7 at clinically relevant concentrations with a limit of detection (LOD) of 10 ng/mL (400 pM), attributed to the significant reduction of the net charge of JR2EC upon digestion by MMP-7. Quantitative detection of MMP-7 in human plasma was further demonstrated with a LOD of 40 ng/mL, illustrating the potential for the proposed methodology for tumor detection and carcinoma diagnostic (e.g., lung cancer and salivary gland cancer). Additionally, excellent specificity of the proposed assay was demonstrated using matrix metallopeptidase 1 (MMP-1), a protease of the same family. With appropriate selection and modification of polypeptides, the proposed assay could be extended for detection of other enzymes with polypeptide digestion capability.

Improved synthesis and growth of graphene oxide for field effect transistor biosensors.

Reduced graphene oxide (RGO) has many advantages over graphene such as low-cost, aqueous processable and industrial-scalable. However, two main limitations that prevent the use of RGO in electronics are the high electrical resistance and large electrical resistance deviation between fabricated devices. This limits RGO's use in biosensors, capacitors and other electronic devices. Herein, we present (1) a modified Hummer's method to obtain large RGO flakes via in-situ size fractionation and (2) the novel growth of RGO which can bridge the gaps in-between existing RGO flakes. Together, these two processes reduced the electrical resistance drastically from 1.99E + 06 to 4.68E + 03 Ω/square and the standard deviation decreased from 80.5 % to 16.5 %. The RGO was then fabricated into a field-effect transistor biosensor. A 1 pmol to 100 nmol change in Cytochrome C protein corresponded to a 3 % change in electrical resistance. The reported improved RGO synthesis method and subsequent growth enable large-scale application of RGO in practical electronic devices such as biosensors.

A review on electronic bio-sensing approaches based on non-antibody recognition elements.

In this review, recent advances in the development of electronic detection methodologies based on non-antibody recognition elements such as functional liposomes, aptamers and synthetic peptides are discussed. Particularly, we highlight the progress of field effect transistor (FET) sensing platforms where possible as the number of publications on FET-based platforms has increased rapidly. Biosensors involving antibody-antigen interactions have been widely applied in diagnostics and healthcare in virtue of their superior selectivity and sensitivity, which can be attributed to their high binding affinity and extraordinary specificity, respectively. However, antibodies typically suffer from fragile and complicated functional structures, large molecular size and sophisticated preparation approaches (resource-intensive and time-consuming), resulting in limitations such as short shelf-life, insufficient stability and poor reproducibility. Recently, bio-sensing approaches based on synthetic elements have been intensively explored. In contrast to existing reports, this review provides a comprehensive overview of recent advances in the development of biosensors utilizing synthetic recognition elements and a detailed comparison of their assay performances. Therefore, this review would serve as a good summary of the efforts for the development of electronic bio-sensing approaches involving synthetic recognition elements.

Mapping deforestation and urban expansion in Freetown, Sierra Leone, from pre- to post-war economic recovery.

Freetown, the capital of Sierra Leone has experienced vast land-cover changes over the past three decades. In Sierra Leone, however, availability of updated land-cover data is still a problem even for environmental managers. This study was therefore, conducted to provide up-to-date land-cover data for Freetown. Multi-temporal Landsat data at 1986, 2001, and 2015 were obtained, and a maximum likelihood supervised classification was employed. Eight land-cover classes or categories were recognized as follows: water, wetland, built-up, dense forest, sparse forest, grassland, barren, and mangrove. Land-cover changes were mapped via post-classification change detection. The persistence, gain, and loss of each land-cover class, and selected land conversions were also quantified. An overall classification accuracy of 87.3 % and a Kappa statistic of 0.85 were obtained for the 2015 map. From 1986 to 2015, water, built-up, grassland, and barren had net gains, whereas forests, wetlands, and mangrove had net loses. Conversion analyses among forests, grassland, and built-up show that built-up had targeted grassland and avoided forests. This study also revealed that, the overall land-cover change at 2001-2015 was higher (28.5 %) than that recorded at 1986-2001 (20.9 %). This is attributable to the population increase in Freetown and the high economic growth and infrastructural development recorded countrywide after the civil war. In view of the rapid land-cover change and its associated environmental impacts, this study recommends the enactment of policies that would strike a balance between urbanization and environmental sustainability in Freetown.

Reporter-encapsulated liposomes on graphene field effect transistors for signal enhanced detection of physiological enzymes.

A novel approach for enzymatic assay using reporter-encapsulated liposomes on graphene field effect transistors (FET) is proposed. This approach involves real time monitoring of drain current (Id) of reduced graphene oxide (rGO) upon rupture of reporter-encapsulated 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) liposomes triggered by enzymes. For validation of the proposed approach, 2,4,6-trinitrophenol (TNP) is used as the reporter for specific detection of phospholipase A2 (PLA2), a key enzyme in various membrane related physiological processes. Experimental results revealed that Id increased with PLA2 concentration, which is attributed to the interaction between released TNP and rGO. The limit of detection (LOD) achieved by the proposed approach was 80 pM, which is superior to most assays reported previously and much lower than the cut-off level of circulating secretory PLA2 (2.07 nM). Besides the high accuracy of the electronic detection methodology, the signal enhancement effect realized by the excess concentration of TNP (approximately 1 mM) in liposomes is believed to be the main reason for the significantly enhanced sensitivity of the proposed assay, indicating great potential for further improvement in the sensitivity by increasing the concentration of TNP. In addition, the proposed approach is rapid (incubation time ≤ 10 min) and label-free, thus showing great potential for practical applications in the future.

Synergetically enhanced near-infrared photoresponse of reduced graphene oxide by upconversion and gold plasmon.

A new route to improve responsivity of reduced graphene oxide (rGO)-based near-infrared photodetectors is reported by coupling upconversion and gold plasmon. Near-infrared light is converted by upconversion nanoparticle into shorter wavelengths that can readily be absorbed by rGO. Further coupling of plasmonic layer increased upconversion emissions and rGO absorption, resulting in an overall enhancement of photo-responsivity by 10 times.

Diversity study of 12 X-chromosomal STR loci in Hui ethnic from China.

X-chromosomal STRs (X-STRs) have been used as complements of autosomal STR application in recent years. In this work, we present population genetic data of 12 X-STRs including DXS101, DXS10159, DXS10162, DXS10164, DXS6789, DXS7133, DXS7423, DXS7424, DXS8378, DXS981, GATA165B12, and GATA31E08 loci in a sample of 231 unrelated healthy individuals from the Hui ethnic group in Ningxia Hui Autonomous Region, China. Allelic frequencies of the 12 X-STR loci and haplotypic frequencies of the reported linkage groups (DXS7424-DXS101 and DXS10159-DXS10164-DXS10162) were investigated in the group, respectively. No STR loci showed significant deviations from the Hardy-Weinberg equilibriums and no linkage disequilibriums of pairwise loci were found after Bonferroni correction, respectively. A combined power of discrimination in female individuals was 0.999999999985 and that in male individuals was 0.99999967, respectively. The combined mean exclusion chance in deficiency cases, normal trios and duo cases were 0.999934, 0.995754, and 0.999796, respectively. Significant differences were observed from 0 to 8 loci, when making comparisons between the data of Hui ethnic group and previously reported data from other 16 populations. The results indicated the new panel of 12 X-STR loci might be useful for forensic science application.

The detection and measurement of interleukin-6 in venous and capillary blood samples, and in sweat collected at rest and during exercise.

PURPOSE: This study aimed to quantify the relationship between venous and capillary blood sampling methods for the measurement of plasma interleukin-6 (IL-6). A parallel study was conducted to determine the possibility of measuring IL-6 in sweat using an enzyme-linked immunosorbent assay (ELISA) and investigate the relationship between plasma- and sweat-derived measures of IL-6. METHODS: Twelve male participants were recruited for the measurement of IL-6 at rest and during exercise (study 1). An additional group of five female participants was recruited for the measurement of IL-6 in venous blood versus sweat at rest and following exercise (study 2). In study 1, venous and capillary blood samples were collected at rest and in response to exercise. In study 2, venous and sweat samples were collected following exercise. RESULTS: Mean plasma IL-6 concentration was not different between venous and capillary blood sampling methods either at rest (4.27 ± 5.40 vs. 4.14 ± 4.45 pg ml(-1)), during (5.40 ± 5.17 vs. 5.58 ± 6.34 pg ml(-1)), or in response to exercise (6.95 ± 6.37 vs. 6.99 ± 6.74 pg ml(-1)). There was no IL-6 detectable in sweat either at rest or following exercise. CONCLUSION: There are no differences in the measurement of plasma IL-6 using either venous or capillary blood sampling methods. Capillary measurement represents a minimally invasive way of measuring IL-6 and detecting changes in IL-6, which are linked to fatigue and overtraining.

Prediction of acute coronary syndrome in patients with myeloproliferative neoplasms.

Background: Patients with myeloproliferative neoplasms (MPN) are exposed to a higher risk of cardiovascular disease, especially cardiovascular calcification. The present research aimed to analyze the clinical features and coronary artery calcium score (CACS) in MPN patients, and construct an effective model to predict acute coronary syndrome (ACS) in MPN patients. Materials and methods: A total of 175 MPN patients and 175 controls were recruited from the First Affiliated Hospital of Ningbo University. Based on cardiovascular events, the MPN patients were divided into the ACS group and the non-ACS group. Multivariate Cox analysis was completed to explore ACS-related factors. Furthermore, ROC curves were plotted to assess the predictive effect of CACS combined with white blood cells (WBC) and platelet for ACS in MPN patients. Results: The MPN group exhibited a higher CACS than the control group (133 vs. 55, P < 0.001). A total of 16 patients developed ACS in 175 MPN patients. Compared with non-ACS groups, significant differences in age, diabetes, smoking history, WBC, percentage of neutrophil, percentage of lymphocyte, neutrophil count, hemoglobin, hematocrit, platelet, lactate dehydrogenase, ß 2-microglobulin, and JAK2V617F mutation were observed in the ACS groups. In addition, the CACS in the ACS group was also significantly higher than that in the non-ACS group (374.5 vs. 121, P < 0.001). The multivariable Cox regression analysis identified WBC, platelet, and CACS as independent risk factors for ACS in MPN patients. Finally, ROC curves indicated that WBC, platelet, and CACS have a high predictive value for ACS in MPN patients (AUC = 0.890). Conclusion: CACS combined with WBC and platelet might be a promising model for predicting ACS occurrence in MPN patients.

Global convergence in terrestrial gross primary production response to atmospheric vapor pressure deficit.

Atmospheric vapor pressure deficit (VPD) increases with climate warming and may limit plant growth. However, gross primary production (GPP) responses to VPD remain a mystery, offering a significant source of uncertainty in the estimation of global terrestrial ecosystems carbon dynamics. In this study, in-situ measurements, satellite-derived data, and Earth System Models (ESMs) simulations were analysed to show that the GPP of most ecosystems has a similar threshold in response to VPD: first increasing and then declining. When VPD exceeds these thresholds, atmospheric drought stress reduces soil moisture and stomatal conductance, thereby decreasing the productivity of terrestrial ecosystems. Current ESMs underscore CO2 fertilization effects but predict significant GPP decline in low-latitude ecosystems when VPD exceeds the thresholds. These results emphasize the impacts of climate warming on VPD and propose limitations to future ecosystems productivity caused by increased atmospheric water demand. Incorporating VPD, soil moisture, and canopy conductance interactions into ESMs enhances the prediction of terrestrial ecosystem responses to climate change.

Antagonism of the histamine H4 receptor reduces LPS-induced TNF production in vivo.

OBJECTIVE: Antagonism of the histamine H4 receptor (H4R) has been shown to be anti-inflammatory in a number of preclinical disease models, however the exact mechanisms behind this are still being uncovered. In vitro, the receptor interacts with TLR and impacts inflammatory mediator production from a number of different cell types. Here it is shown that this interaction also occurs in vivo. MATERIALS AND METHODS: Wild-type and H4R deficient BALB/c mice received an i.p. injection of LPS in PBS in conjunction with p.o. JNJ 7777120 or JNJ 28307474 (H4R antagonists). Two hours later blood was collected and TNF was measured. RESULTS: Two different H4R antagonists inhibited LPS-induced TNF production in mice and this production was also reduced in H4R-deficient mice. The TNF mRNA analysis showed that the major source of the cytokine was the liver and not blood, and that the H4R antagonist only reduced the expression levels in the liver. Depletion or inactivation of macrophages reduced the TNF levels and eliminated the H4R sensitivity. Treatment with an H4R antagonist also reduced LPS-induced liver injury and blocked LPS-enhanced lung inflammation in mice. CONCLUSION: The data support an interaction between H4R and TLR activation in vivo that can drive inflammatory responses.

Evaluation of reading speed and contrast sensitivity in dry eye disease.

PURPOSE: Visual disturbance is a common symptom reported by patients with dry eye disease (DED). The purpose of this study was to evaluate visual performance, including reading speed and contrast sensitivity, in control and DED subjects. METHODS: Fifty-two DED patients (mild, n = 17; moderate, n = 22; severe, n = 13; based on corneal staining and the Ocular Surface Disease Index ≥ 20) and 20 control subjects (Ocular Surface Disease Index <13, no corneal staining) took part in this study. The age ranges for the control and DED patients were 18 to 45 years and 19 to 84 years, respectively. Contrast sensitivity was measured using the Holladay Automated Contrast Sensitivity System, and reading speed was determined using the Wilkins Rate of Reading Test. Analysis of covariance was conducted to compare clinical characteristics among subject groups while adjusting for age, sex, and study site. Partial correlation coefficients from linear regression were used to measure the linear relationship between contrast sensitivity and reading speed with DED parameters. RESULTS: The log of the minimum angle of resolution visual acuities and contrast sensitivity were not significantly different across subject groups. The DED patients (134.9 ± 4.95 words per minute) exhibited slower reading speeds than the control subjects (158.3 ± 8.40 words per minute, p = 0.046). As DED severity increased, the reading speed decreased (141.0 ± 7.96 words per minute, 136.8 ± 7.15 words per minute, and 127.0 ± 9.63 words per minute in mild, moderate, and severe groups, respectively). Reading rate was found to correlate weakly with corneal staining based on a partial correlation coefficient (-0.345, p < 0.001) but not with other DED parameters. CONCLUSIONS: The reading rate was lower in DED subjects than that in control subjects. As the DED severity increased, the reading rate decreased. This finding is consistent with patient-reported symptoms and provides direct evidence for the impact of DED on reading performance. These findings suggest that reading speed may be used to monitor treatment benefit in DED.

Comparability of red/near-infrared reflectance and NDVI based on the spectral response function between MODIS and 30 other satellite sensors using rice canopy spectra.

Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The reflectance and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR reflectances and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy reflectances were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra MODIS, the mean relative percentage difference (RPD) ranged from -12.67% to 36.30% for the red reflectance, -8.52% to -0.23% for the NIR reflectance, and -9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra MODIS ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between MODIS and the other 30 satellite sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between MODIS and the other 30 satellite sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed higher differences than did the other sensors with respect to MODIS. A series of optimum models were presented for remote sensing data assimilation between MODIS and other sensors.

Evaluation of Coronary Artery Diffuse Calcification Stenosis by Corrected Coronary Opacification Difference.

OBJECTIVES: The artifacts produced by calcification on coronary computed tomographic angiography (CCTA) have a great influence on the diagnosis of coronary stenosis. The purpose of this study is to investigate the value of corrected coronary opacification (CCO) difference in the diagnosis of stenosis in diffusely calcified coronary arteries (DCCAs). METHODS: A total of 84 patients were enrolled. The CCO difference across the diffuse calcification was measured through CCTA. Coronary arteries were grouped according to the extent of stenosis obtained by invasive coronary angiography (ICA). The Kruskal-Wallis H test was used to compare the CCO differences between different groups and a receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the CCO difference. RESULTS: Among the 84 patients, 58 patients had one DCCA, 14 patients had 2 DCCAs, and 12 patients had 3 DCCAs. A total of 122 coronary arteries were examined, 16 showed no significant stenosis, 42 had <70% stenosis, and 64 had 70-99% stenosis. The median CCO differences among the 3 groups were 0.064, 0.117, and 0.176, respectively. There were significant differences between the group without stenosis and the group with 70-99% stenosis (H = -3.581, P = 0.001), and between the group with <70% stenosis and the group with 70-99% stenosis (H = -2.430, P = 0.045). The area under the ROC curve was 0.681 and the optimal cut-off point was 0.292. Taking the ICA results as the gold standard, the sensitivity and specificity for the diagnosis of ≥70% coronary stenosis with a cut-off point of 0.292 were 84.4% and 44.8%, respectively. CONCLUSION: CCO difference could be useful in the diagnosis of ≥70% severe coronary stenosis in DCCA. Through this non-invasive examination, the CCO difference could be a reference for clinical treatment.

Daily activity patterns and body temperature of the Oriental migratory locust, Locusta migratoria manilensis (Meyen), in natural habitat.

Current pest management techniques would benefit from understanding the behavioural rhythms of the target pest and its body temperature, a critical aspect not well studied and potentially limiting the effectiveness of biopesticides under natural conditions. This study aims 1) to understand under natural conditions the behavioural patterns of different stages of hoppers and adults of Locusta migratoria manilensis and 2) to identify the environmental factors modulating their body temperature through field observation. We carried out an intensive field sampling in two of the main locust breeding regions in China, recording the body temperature (day and night), morphological traits (stage, sex and size) and microhabitat of 953 individuals. The results revealed that locusts preferred the ground as their main activity subhabitat, particularly for hoppers. Adults tended to move upper in the reed canopy at two peaks (10-11 h and 14-15 h). Locusts body temperature during daytime increased with development stage and size, while the opposite pattern occurred during night time. Entompathogenic fungi are more effective if the body temperature of the target pest is in a proper range without too high or too low. Application of biopesticides should focus on younger locusts spraying in the morning or at dusk as the locusts have lower body temperatures.

Detect and attribute the extreme maize yield losses based on spatio-temporal deep learning.

Providing accurate crop yield estimations at large spatial scales and understanding yield losses under extreme climate stress is an urgent challenge for sustaining global food security. While the data-driven deep learning approach has shown great capacity in predicting yield patterns, its capacity to detect and attribute the impacts of climatic extremes on yields remains unknown. In this study, we developed a deep neural network based multi-task learning framework to estimate variations of maize yield at the county level over the US Corn Belt from 2006 to 2018, with a special focus on the extreme yield loss in 2012. We found that our deep learning model hindcasted the yield variations with good accuracy for 2006-2018 (R2 = 0.81) and well reproduced the extreme yield anomalies in 2012 (R2 = 0.79). Further attribution analysis indicated that extreme heat stress was the major cause for yield loss, contributing to 72.5% of the yield loss, followed by anomalies of vapor pressure deficit (17.6%) and precipitation (10.8%). Our deep learning model was also able to estimate the accumulated impact of climatic factors on maize yield and identify that the silking phase was the most critical stage shaping the yield response to extreme climate stress in 2012. Our results provide a new framework of spatio-temporal deep learning to assess and attribute the crop yield response to climate variations in the data rich era.

Lanthanide-doped Na(x)ScF(3+x) nanocrystals: crystal structure evolution and multicolor tuning.

Rare-earth-based nanomaterials have recently drawn considerable attention because of their unique energy upconversion (UC) capabilities. However, studies of Sc(3+)-based nanomaterials are still absent. Herein we report the synthesis and fine control of Na(x)ScF(3+x) nanocrystals by tuning of the ratio of oleic acid (OA, polar surfactant) to 1-octadecene (OD, nonpolar solvent). When the OA:OD ratio was increased from low (3:17) to high (3:7), the nanocrystals changed from pure monoclinic phase (Na(3)ScF(6)) to pure hexagonal phase (NaScF(4)) via a transition stage at an intermediate OA:OD ratio (3:9) where a mixture of nanocrystals in monoclinic and hexagonal phases was obtained and the coexistence of the two phases inside individual nanocrystals was also observed. More significantly, because of the small radius of Sc(3+), Na(x)ScF(3+x):Yb/Er nanocrystals show different UC emission from that of NaYF(4):Yb/Er nanocrystals, which broadens the applications of rare-earth-based nanomaterials ranging from optical communications to disease diagnosis.