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Abstract Background Mobile upright PET devices have the potential to enable previously impossible neuroimaging studies. Currently available options are imagers with deep brain coverage that severely limit head/body movements or imagers with upright/motion enabling properties that are limited to only covering the brain surface. Methods In this study, we test the feasibility of an upright, motion-compatible brain imager, our Ambulatory Motion-enabling Positron Emission Tomography (AMPET) helmet prototype, for use as a neuroscience tool by replicating a variant of a published PET/fMRI study of the neurocorrelates of human walking. We validate our AMPET prototype by conducting a walking movement paradigm to determine motion tolerance and assess for appropriate task related activity in motor-related brain regions. Human participants (n = 11 patients) performed a walking-in-place task with simultaneous AMPET imaging, receiving a bolus delivery of F18-Fluorodeoxyglucose. Results Here we validate three pre-determined measure criteria, including brain alignment motion artifact of less than

Abstract Objectives To compare the diagnostic performance of intratumoral and peritumoral features from different contrast phases of breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) by building radiomics models for differentiating molecular subtypes of breast cancer. Methods This retrospective study included 377 patients with pathologically confirmed breast cancer. Patients were divided into training set (n = 202), validation set (n = 87) and test set (n = 88). The intratumoral volume of interest (VOI) and peritumoral VOI were delineated on primary breast cancers at three different DCE-MRI contrast phases: early, peak, and delayed. Radiomics features were extracted from each phase. After feature standardization, the training set was filtered by variance analysis, correlation analysis, and least absolute shrinkage and selection (LASSO). Using the extracted features, a logistic regression model based on each tumor subtype (Luminal A, Luminal B, HER2-enriched, triple-negative) was established. Ten models based on intratumoral or/plus peritumoral features from three different phases were developed for each differentiation. Results Radiomics features extracted from delayed phase DCE-MRI demonstrated dominant diagnostic performance over features from other phases. However, the differences were not statistically significant. In the full fusion model for differentiating different molecular subtypes, the most frequently screened features were those from the delayed phase. According to the Shapley additive explanation (SHAP) method, the most important features were also identified from the delayed phase. Conclusions The intratumoral and peritumoral radiomics features from the delayed phase of DCE-MRI can provide additional information for preoperative molecular typing. The delayed phase of DCE-MRI cannot be ignored. Critical relevance statement Radiomics features extracted and radiomics models constructed from the delayed phase of DCE-MRI played a crucial role in molecular subtype classification, although no significant difference was observed in the test cohort. Key Points The molecular subtype of breast cancer provides a basis for setting treatment strategy and prognosis. The delayed-phase radiomics model outperformed that of early-/peak-phases, but no differently than other phases or combinations. Both intra- and peritumoral radiomics features offer valuable insights for molecular typing. Graphical Abstract

Abstract Historically, the precipitation trend over the past few decades in the Contiguous United States (CONUS) exhibits a “Dry‐West Wet‐East” pattern; this is manifested by recent droughts/floods in the western/eastern US. However, it remains elusive what atmospheric phenomenon has potentially driven such a remarkable, and impactful precipitation pattern. Here we found that a coupled climate mode—the Pacific Meridional Mode (PMM) exerted strong impacts on the precipitation pattern over the CONUS during the summer season. We discovered a significant association between the PMM index and precipitation across the majority of the CONUS; this was manifested as a zonal dipole pattern—negative correlations in the western U.S. along with positive correlations in the eastern and central U.S. Overall, the physical mechanisms based on observations were supported by using Atmospheric Model Intercomparison Project simulations available from the Coupled Model Intercomparison Project Phase 6.

The smoking rate is high in patients with schizophrenia. Brain stimulation targeting conventional brain circuits associated with nicotine addiction has also yielded mixed results. We aimed to identify alternative circuitries associated with nicotine addiction in both the general population and schizophrenia, and then test whether modulation of such circuitries may alter nicotine addiction behaviors in schizophrenia. In Study I of 40 schizophrenia smokers and 51 non-psychiatric smokers, cross-sectional neuroimaging analysis identified resting state functional connectivity (rsFC) between the dorsomedial prefrontal cortex (dmPFC) and multiple extended amygdala regions to be most robustly associated with nicotine addiction severity in healthy controls and schizophrenia patients (p = 0.006 to 0.07). In Study II with another 30 patient smokers, a proof-of-concept, patient- and rater-blind, randomized, sham-controlled rTMS design was used to test whether targeting the newly identified dmPFC location may causally enhance the rsFC and reduce nicotine addiction in schizophrenia. Although significant interactions were not observed, exploratory analyses showed that this dmPFC–extended amygdala rsFC was enhanced by 4-week active 10Hz rTMS (p = 0.05) compared to baseline; the severity of nicotine addiction showed trends of reduction after 3 and 4 weeks (p ≤ 0.05) of active rTMS compared to sham; Increased rsFC by active rTMS predicted reduction of cigarettes/day (R = −0.56, p = 0.025 uncorrected) and morning smoking severity (R = −0.59, p = 0.016 uncorrected). These results suggest that the dmPFC–extended amygdala circuit may be linked to nicotine addiction in schizophrenia and healthy individuals, and future efforts targeting its underlying pathophysiological mechanisms may yield more effective treatment for nicotine addiction.

Abstract Background MRI-based tumor shrinkage patterns (TSP) after neoadjuvant therapy (NAT) have been associated with pathological response. However, the understanding of TSP after early NAT remains limited. We aimed to analyze the relationship between TSP after early NAT and pathological response after therapy in different molecular subtypes. Methods We prospectively enrolled participants with invasive ductal breast cancers who received NAT and performed pretreatment DCE-MRI from September 2020 to August 2022. Early-stage MRIs were performed after the first (1st-MRI) and/or second (2nd-MRI) cycle of NAT. Tumor shrinkage patterns were categorized into four groups: concentric shrinkage, diffuse decrease (DD), decrease of intensity only (DIO), and stable disease (SD). Logistic regression analysis was performed to identify independent variables associated with pathologic complete response (pCR), and stratified analysis according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype. Results 344 participants (mean age: 50 years, 113/345 [33%] pCR) with 345 tumors (1 bilateral) had evaluable 1st-MRI or 2nd-MRI to comprise the primary analysis cohort, of which 244 participants with 245 tumors had evaluable 1st-MRI (82/245 [33%] pCR) and 206 participants with 207 tumors had evaluable 2nd-MRI (69/207 [33%] pCR) to comprise the 1st- and 2nd-timepoint subgroup analysis cohorts, respectively. In the primary analysis, multivariate analysis showed that early DD pattern (OR = 12.08; 95% CI 3.34–43.75; p

Background Gynostemma pentaphyllum (Thunb.) Makino, a well-known edible and medicinal plant, has anti-aging properties and is used to treataging-associated conditions such as diabetes, metabolic syndrome, and cardiovascular diseases. Gypenosides (GYPs) are the primary constituents of G. pentaphyllum. Increasing evidence indicates that GYPs are effective at preserving mitochondrial homeostasis and preventing heart failure (HF). This study aimed to uncover the cardioprotective mechanisms of GYPs related to mitochondrial regulation. Methods The bioactive components in GYPs and the potential targets in treating HF were obtained and screened using the network pharmacology approach, followed by drug-disease target prediction and enrichment analyses. The pharmacological effects of GYPs in cardioprotection, mitochondrial function, mitochondrial quality control, and underlying mechanisms were further investigated in Doxorubicin (Dox)-stimulated H9c2 cardiomyocytes. Results A total of 88 bioactive compounds of GYPs and their respective 71 drug-disease targets were identified. The hub targets covered MAPK, EGFR, PI3KCA, and Mcl-1. Enrichment analysis revealed that the pathways primarily contained PI3K/Akt, MAPK, and FoxO signalings, as well as calcium regulation, protein phosphorylation, apoptosis, and mitophagy process. In Dox-stimulated H9c2 rat cardiomyocytes, pretreatment with GYPs increased cell viability, enhanced cellular ATP content, restored basal oxygen consumption rate (OCR), and improved mitochondrial membrane potential (MMP). Furthermore, GYPs improved PINK1/parkin-mediated mitophagy without influencing mitochondrial fission/fusion proteins and the autophagic LC3 levels. Mechanistically, the phosphorylation of PI3K, Akt, GSK-3β, and the protein level of Mcl-1 was upregulated by GYP treatment. Conclusion Our findings reveal that GYPs exert cardioprotective effects by rescuing the defective mitophagy, and PI3K/Akt/GSK-3β/Mcl-1 signaling is potentially involved in this process.

Remote-sensed vegetation indices (VIs) have emerged as essential tools for retrieving forest chlorophyll concentration. Although VIs are widely used, some concerns regarding VIs for estimating chlorophyll remain to be addressed, such as saturation effect, leaf area index (LAI) disturbance, and soil brightness influence. Currently, a systematic study on such performance evaluation of chlorophyll-related VIs considering these issues is still insufficient. This study coupled two radiative transfer models, the PROSPECT model and the LESS model, to simulate Eucalyptus monocultures with different chlorophyll content and systematically evaluated the 18 broad-band VIs’ ability in chlorophyll estimation at different scales. Our results indicate that most VIs designed for chlorophyll estimation were relatively resistant to saturation, except for SIPI and some classical VIs (e.g., NDVI and DVI), which were insensitive to chlorophyll decreases and tended to reach saturation quickly (when leaf chlorophyll content (LCC) exceeded 40 ug/cm2). The relationships between NDVI, SR, DVI, and LCC were easily influenced by soil brightness and LAI. S2REP, MTCI, TGI, TCARI, and EVI were insensitive to soil brightness when estimating LCC. Overall, S2REP was best at quantitatively retrieving chlorophyll and resisting interference from other factors. For practical applications, our study suggests that it is preferable to use S2REP for LCC estimation when the red-edge band is available; otherwise, CVI can be used instead. The judicious utilization of VI can effectively depict chlorophyll levels and improve the understanding of vegetation response to climate change. Our findings provide the necessary information for the selection of specific VIs tailored to specific vegetation parameters.

In this study, a novel human-size handheld magnetic particle imaging (MPI) system was developed for the high-precision detection of sentinel lymph nodes for breast cancer. The system consisted of a highly sensitive home-made MPI detection probe, a set of concentric coils pair for spatialization, a solenoid coil for uniform excitation at 8 kHz@1.5 mT, and a full mirrored coil set positioned far away from the scanning area. The mirrored coils formed an extremely effective differential pickup structure which suppressed the system noise as high as 100 dB. The different combination of the inner and outer gradient current made the field free point (FFP) move in the Z direction with a uniform intensity of 0.54T/m, while the scanning in the XY direction was implemented mechanically. The third-harmonic signal of the Superparamagnetic Iron Oxide Nanoparticles (SPIONs) at the FFP was detected and then reconstructed synchronously with the current changes. Experiment results showed that the tomographic detection limit was 30 mm in the Z direction, and the sensitivity was about 10 μg Fe SPIONs at 40 mm distance with a spatial resolution of about 5 mm. In the rat experiment, 54 μg intramuscular injected SPIONs were detected successfully in the sentinel lymph node, in which the tracer content was about 1.2% total injected Fe. Additionally, the effective detection time window was confirmed from 4 to 6 min after injection. Relevant clinical ethics are already in the application process. Large mammalian SLNB MPI experiments and 3D preoperative SLNB imaging will be performed in the future.

BackgroundPoor glycemic control with elevated levels of hemoglobin A1c (HbA1c) is associated with increased risk of cognitive impairment, with potentially varying effects between sexes. However, the causal impact of poor glycemic control on white matter brain aging in men and women is uncertain.MethodsWe used two nonoverlapping data sets from UK Biobank cohort: gene-outcome group (with neuroimaging data, (N = 15,193; males/females: 7,101/8,092)) and gene-exposure group (without neuroimaging data, (N = 279,011; males/females: 122,638/156,373)). HbA1c was considered the exposure and adjusted “brain age gap” (BAG) was calculated on fractional anisotropy (FA) obtained from brain imaging as the outcome, thereby representing the difference between predicted and chronological age. The causal effects of HbA1c on adjusted BAG were studied using the generalized inverse variance weighted (gen-IVW) and other sensitivity analysis methods, including Mendelian randomization (MR)-weighted median, MR-pleiotropy residual sum and outlier, MR-using mixture models, and leave-one-out analysis.ResultsWe found that for every 6.75 mmol/mol increase in HbA1c, there was an increase of 0.49 (95% CI = 0.24, 0.74; p-value = 1.30 × 10−4) years in adjusted BAG. Subgroup analyses by sex and age revealed significant causal effects of HbA1c on adjusted BAG, specifically among men aged 60–73 (p-value = 2.37 × 10−8).ConclusionPoor glycemic control has a significant causal effect on brain aging, and is most pronounced among older men aged 60–73 years, which provides insights between glycemic control and the susceptibility to age-related neurodegenerative diseases.

Abstract Manure is a leading source of methane (CH4), nitrous oxide (N2O), and ammonia (NH3) emissions, and alternative manure management practices can help society meet climate goals and mitigate air pollution. Recent studies show that biochar‐composting can substantially reduce emissions from manure. However, most studies test only one type of biochar applied at a single application rate, leading to high variation in emission reductions between studies. Here, we measured greenhouse gas and NH3 emissions during biochar‐composting of dairy manure with biochar applied at 5% or 20%, by mass, and made from walnut shells, almond shells, or almond clippings. We found little difference in emissions between biochar type. However, we found that the 20% application rates increased CH4 emissions and decreased N2O and NH3 emissions, resulting in a net reduction in global warming potential (GWP). We attribute this result to biochar increasing the formation of compost aggregates, which likely acted as anaerobic reactors for methanogenesis and complete denitrification. Biochar may have further fueled CH4 production and N2O consumption by acting as an electron shuttle within aggregates. We recommend lower application rates, as we found that the 5% treatments in our study led to a similar reduction in GWP without increasing CH4 emissions.

Abstract Background To evaluate the correlation between synthetic MRI (syMRI) relaxometry and apparent diffusion coefficient (ADC) maps in different breast cancer subtypes and treatment response subgroups. Methods Two hundred sixty-three neoadjuvant therapy (NAT)-treated breast cancer patients with baseline MRI were enrolled. Tumor annotations were obtained by drawing regions of interest (ROIs) along the lesion on T1/T2/PD and ADC maps respectively. Histogram features from T1/T2/PD and ADC maps were respectively calculated, and the correlation between each pair of identical features was analyzed. Meanwhile, features between different NAT treatment response groups were compared, and their discriminatory power was evaluated. Results Among all patients, 20 out of 27 pairs of features weakly correlated (r = – 0.13–0.30). For triple-negative breast cancer (TNBC), features from PD map in the pathological complete response (pCR) group (r = 0.60–0.86) showed higher correlation with ADC than that of the non-pCR group (r = 0.30–0.43), and the mean from the ADC and PD maps in the pCR group strongly correlated (r = 0.86). For HER2-positive, few correlations were found both in the pCR and non-pCR groups. For luminal HER2-negative, T2 map correlated more with ADC than T1 and PD maps. Significant differences were seen in T2 low percentiles and median in the luminal-HER2 negative subtype, yielding moderate AUCs (0.68/0.72/0.71). Conclusions The relationship between ADC and PD maps in TNBC may indicate different NAT responses. The no-to-weak correlation between the ADC and syMRI suggests their complementary roles in tumor microenvironment evaluation. Critical relevance statement The relationship between ADC and PD maps in TNBC may indicate different NAT responses, and the no-to-weak correlation between the ADC and syMRI suggests their complementary roles in tumor microenvironment evaluation. Key points • The relationship between ADC and PD in TNBC indicates different NAT responses. • The no-to-weak correlations between ADC and syMRI complementarily evaluate tumor microenvironment. • T2 low percentiles and median predict NAT response in luminal-HER2-negative subtype. Graphical Abstract

Abstract Background As digital medicine has exerted profound influences upon diagnosis and treatment of hepatobiliary diseases, our study aims to investigate the accuracy of three-dimensional visualization and evaluation (3DVE) system in assessing the resectability of hilar cholangiocarcinoma (hCCA), and explores its potential clinical value. Materials and methods The discovery cohort, containing 111 patients from April 2013 to December 2019, was retrospectively included to determine resectability according to revised criteria for unresectability of hCCA. 3D visualization models were reconstructed to evaluate resectability parameters including biliary infiltration, vascular involvement, hepatic atrophy and metastasis. Evaluation accuracy were compared between contrast-enhanced CT and 3DVE. Logistic analysis was performed to identify independent risk factors of R0 resection. A new comprehensive 3DVE classification of hCCA based on factors influencing resectability was proposed to investigate its role in predicting R0 resection and prognosis. The main outcomes were also analyzed in cohort validation, including 34 patients from January 2020 to August 2022. Results 3DVE showed an accuracy rate of 91% (95%CI 83.6–95.4%) in preoperatively evaluating hCCA resectability, significantly higher than 81% (95%CI 72.8–87.7%) of that of CT (p = 0.03). By multivariable analysis, hepatic artery involvement in 3DVE was identified an independent risk factor for R1 or R2 resection (OR = 3.5, 95%CI 1.4,8.8, P

Tropical cyclone (TC) genesis prediction remains a major operational challenge. Using multiple satellite datasets and a state-of-the-art reanalysis dataset, this study identifies developing and non-developing tropical disturbances over the western North Pacific from June to November of 2000–2019 and conducts composite analyses of their water vapor budget components and relevant dynamic–thermodynamic parameters in the Lagrangian framework following three-day disturbance tracks. Both groups of disturbances have a similar initial 850 hPa synoptic-scale relative vorticity, while the water vapor budget of developing disturbances exhibits distinct stage-wise evolution characteristics from non-developing cases. Three days prior to TC genesis, developing cases are already associated with significantly higher total precipitable water (TPW), vertically integrated moisture flux convergence (VIMFC), and precipitation, of which TPW is the most important parameter to differentiate two groups of disturbances. One day later, all the water vapor budget components (i.e., TPW, VIMFC, precipitation, and evaporation) strengthened, linked with the enhancement of the mid-to lower-tropospheric vortices. A negative radial gradient of evaporation occurs, suggesting the beginning of the wind−evaporation feedback. On the day prior to TC genesis, the water vapor budget components, as well as the mid-to lower-tropospheric vortices, continue to intensify, eventually leading to TC genesis. By contrast, non-developing disturbances are associated with a drier environment and weaker VIMFC, precipitation, and evaporation during the three-day evolution. All these factors are not favorable for the intensification of the mid-to lower-tropospheric vortices; thus, the disturbances fail to upgrade to TCs. The results may shed light on TC genesis prediction.

Abstract Organic amendments, such as compost and biochar, mitigate the environmental burdens associated with wasting organic resources and close nutrient loops by capturing, transforming, and resupplying nutrients to soils. While compost or biochar application to soil can enhance an agroecosystem's capacity to store carbon and produce food, there have been few field studies investigating the agroecological impacts of amending soil with biochar co‐compost, produced through the composting of nitrogen‐rich organic material, such as manure, with carbon‐rich biochar. Here, we examine the impact of biochar co‐compost on soil properties and processes by conducting a field study in which we compare the environmental and agronomic impacts associated with the amendment of either dairy manure co‐composted with biochar, dairy manure compost, or biochar to soils in a winter wheat cropping system. Organic amendments were applied at equivalent C rates (8 Mg C ha−1). We found that all three treatments significantly increased soil water holding capacity and total plant biomass relative to the no‐amendment control. Soils amended with biochar or biochar co‐compost resulted in significantly less greenhouse gas emissions than the compost or control soils. Biochar co‐compost also resulted in a significant reduction in nutrient leaching relative to the application of biochar alone or compost alone. Our results suggest that biochar co‐composting could optimize organic resource recycling for climate change mitigation and agricultural productivity while minimizing nutrient losses from agroecosystems.

ABSTRACTNighttime light (NTL) remote sensing data plays a crucial role in comprehending changes in human activities. The availability of the daily lunar BRDF-corrected Black Marble NTL product (VNP46A2) enables the use of NTL data to detect and assess the impact of short-term emergencies. However, daily NTL data often experience missing values due to cloud cover and low-quality signals. To address this issue, many studies utilize monthly or annual time-composite NTL products, which restrict the timeliness and potential application scenarios of NTL data usage. Therefore, it is necessary to generate the gap-filled daily NTL product. This study presented a novel NTL gap-filling method comprising rough reconstruction based on spatiotemporal weighting and refined gap-filling using a Bidirectional Long Short-Term Memory (Bi-LSTM) model. We evaluate the accuracy of the proposed method using the “remove-reconstruct-compare” approach, which randomly removes some original data from the complete image, fills the gaps with the proposed gap-filling method, and compares the reconstructed NTL data with the original observations in Beijing, Shanghai, Xi’an and New York. The results reveal that when the rate of missing values in Beijing is 40% and 50%, the proposed gap-filling method achieves accuracy with mean coefficient of determination (R2) values of 0.834 and 0.841, accompanied by corresponding root mean square (RMSE) values of 7.793 and 7.171, respectively. Furthermore, the gap-filling accuracy was evaluated quantitatively, and our proposed gap-filling method performed better than the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). Our proposed gap-filling method had R2 values of 0.685, 0.781, 0.720 and 0.642, which were higher than those for STARFM (0.430, 0.662, 0.221 and 0.345). The RMSE values of our gap-filling method were 9.628, 12.083, 10.963 and 19.882 for the four sites, while those of STARFM were 12.953, 14.872, 18.280 and 26.990, respectively. The temporal and spatial analysis results demonstrate that this model is robust, capturing city boundaries and NTL high-brightness hotspots with high accuracy and stability. The gap-filling model proposed in this study provides a new technique for expanding the potential applications and reliability of NASA’s daily Black Marble product (VNP46A2) in remote sensing.

The limitation in metal-semiconductor contact has been a major challenge for high-performance organic field-effect transistors. Here, the authors fabricate the contact by transferring platinum electrode on solution-processed organic films, realizing ultralow total contact resistance down to 14 Ω ∙ cm.

Abstract Aberrant gamma frequency neural oscillations in schizophrenia have been well demonstrated using auditory steady-state responses (ASSR). However, the neural circuits underlying 40 Hz ASSR deficits in schizophrenia remain poorly understood. Sixty-six patients with schizophrenia spectrum disorders and 85 age- and gender-matched healthy controls completed one electroencephalography session measuring 40 Hz ASSR and one imaging session for resting-state functional connectivity (rsFC) assessments. The associations between the normalized power of 40 Hz ASSR and rsFC were assessed via linear regression and mediation models. We found that rsFC among auditory, precentral, postcentral, and prefrontal cortices were positively associated with 40 Hz ASSR in patients and controls separately and in the combined sample. The mediation analysis further confirmed that the deficit of gamma band ASSR in schizophrenia was nearly fully mediated by three of the rsFC circuits between right superior temporal gyrus—left medial prefrontal cortex (MPFC), left MPFC—left postcentral gyrus (PoG), and left precentral gyrus—right PoG. Gamma-band ASSR deficits in schizophrenia may be associated with deficient circuitry level connectivity to support gamma frequency synchronization. Correcting gamma band deficits in schizophrenia may require corrective interventions to normalize these aberrant networks.

Abstract Background The objective of this paper is to explore the value of a delta-radiomic model of the axillary lymph node (ALN) using dynamic contrast-enhanced (DCE) MRI for early prediction of the axillary pathological complete response (pCR) of breast cancer patients after neoadjuvant chemotherapy (NAC). Methods A total of 120 patients with ALN-positive breast cancer who underwent breast MRI before and after the first cycle of NAC between October 2018 and May 2021 were prospectively included in this study. Patients were divided into a training (n = 84) and validation (n = 36) cohort based on the temporal order of their treatments. Radiomic features were extracted from the largest slice of targeted ALN on DCE-MRI at pretreatment and after one cycle of NAC, and their changes (delta-) were calculated and recorded. Logistic regression was then applied to build radiomic models using the pretreatment (pre-), first-cycle(1st-), and changes (delta-) radiomic features separately. A clinical model was also built and combined with the radiomic models. The models were evaluated by discrimination, calibration, and clinical application and compared using DeLong test. Results Among the three radiomic models, the ALN delta-radiomic model performed the best with AUCs of 0.851 (95% CI: 0.770–0.932) and 0.822 (95% CI: 0.685–0.958) in the training and validation cohorts, respectively. The clinical model yielded moderate AUCs of 0.742 (95% CI: 0.637–0.846) and 0.723 (95% CI: 0.550–0.896), respectively. After combining clinical features to the delta-radiomics model, the efficacy of the combined model (AUC = 0.932) in the training cohort was significantly higher than that of both the delta-radiomic model (Delong p = 0.017) and the clinical model (Delong p

Monitoring vegetation dynamics (VD) is crucial for environmental protection, climate change research, and understanding carbon and water cycles. Remote sensing is an effective method for large-scale and long-term VD monitoring, but it faces challenges due to changing data uncertainties caused by various factors, including observational conditions. Previous studies have demonstrated the significance of implementing proper quality control (QC) of remote sensing data for accurate vegetation monitoring. However, the impact of different QC methods on VD results (magnitude and trend) has not been thoroughly studied. The fraction of absorbed photosynthetically active radiation (FPAR) characterizes the energy absorption capacity of the vegetation canopy and is widely used in VD monitoring. In this study, we investigated the effect of QC methods on vegetation monitoring using a 20-year MODIS FPAR time series. The results showed several important findings. Firstly, we observed that the Mixed-QC (no QC on the algorithm path) generally produced a lower average FPAR during the growing season compared to Main-QC (only using the main algorithm). Additionally, the Mixed-QC FPAR showed a very consistent interannual trend with the Main-QC FPAR over the period 2002–2021 (p < 0.05). Finally, we found that using only the main algorithm for QC generally reduced the trend magnitude (p < 0.1), particularly in forests. These results reveal differences in FPAR values between the two QC methods. However, the interannual FPAR trends demonstrate greater consistency. In conclusion, this study offers a case study on evaluating the influence of different QC methods on VD monitoring. It suggests that while different QC methods may result in different magnitudes of vegetation dynamics, their impact on the time series trends is limited.

Dairy manure is one of the largest sources of methane (CH _4 ) emissions and air pollution from agriculture. In a previous study, we showed that composting dairy manure with biochar substantially reduces CH _4 emissions and could help the dairy industry meet climate goals. However, it remained unclear whether biochar could also mitigate the emission of air pollutants and odor during composting. Here, we conducted a full-scale composting study at a dairy farm and monitored the emission of greenhouse gases (CO _2 , CH _4 , N _2 O) and air pollutants (H _2 S, VOCs, NO _x , NH _3 ) from compost piles amended with or without biochar. We found that amending compost with biochar significantly reduced total CH _4 emissions by 58% (±22%) and cut H _2 S, VOCs, and NO _x emissions by 67% (±24%), 61% (±19%) and 70% (±22%), respectively. We attribute this reduction in emissions to improved oxygen diffusion from the porous biochar and the adsorption of gas precursors to the biochar surface. Interestingly, NO _x fluxes from the composting dairy manure were much higher than the few values reported in the literature, suggesting that dairy manure could also be a significant source of NO _x emissions. We estimate that biochar-composting of dairy manure would reduce the social cost of manure emissions from this farm by over $66 000 annually. Results from this study suggest that composting dairy manure with biochar, in addition to reducing CH _4 emissions, may help to improve air quality and the health and wellbeing of rural communities, but further studies are needed to test the quantitative impacts.

Abstract Finding feasible solutions for sustainable food production is challenging. Here we try to understand the balance between crop productivity and ecological stewardship using agroecological‐based soil management strategies. We evaluated the potential of different organic materials such as dairy manure compost and different biochar manure co‐composts, derived locally from agricultural wastes, to enhance soil ecosystem services. We assessed their potential impact on soil moisture and nutrient retention, greenhouse gas emissions, and crop productivity using data collected from an outdoor tomato column study. Results from the experiment showed potential of biochar co‐composts to positively affect soil health by lessening loss of essential nutrients such as NO3−‐N and NH4+‐N, sustained tomato yield, and uphold crop water use efficiency. However, yield response to soil organic amendment is constrained by external factors such as irrigation strategies, with treatments under deficit irrigation greatly impacted. Overall, we observed a positive effect of adding biochar manure co‐composts to soil, although best management practices are needed to optimize crop productivity and avoid unintentional consequences.

The authors demonstrate electron ptychographic computed tomography by simultaneously recording high contrast data from both the organic- and inorganic components in a 3D DNA-origami framework hybrid nanostructure.

Freestanding perovskite oxides pave the way to novel flexural properties. Here, the authors observe the nanoscale strain gradient induced flexoelectric polarization with an unusual flexo-expansion/shrinkage effect in freestanding ferroelectric oxide.

The bidirectional reflectance distribution function (BRDF) of the land surface contains information relating to its physical structure and composition. Accurate BRDF modeling for heterogeneous pixels is important for global ecosystem monitoring and radiation balance studies. However, the original kernel-driven models, which many operational BRDF/Albedo algorithms have adopted, do not explicitly consider the heterogeneity within heterogeneous pixels, which may result in large fitting residuals. In this paper, we attempted to improve the fitting ability of the kernel-driven models over heterogeneous pixels by changing the inversion approach and proposed a dynamic weighted least squares (DWLS) inversion approach. The performance of DWLS and the traditional ordinary least squares (OLS) inversion approach were compared using simulated data. We also evaluated its ability to reconstruct multiangle satellite observations and provide accurate BRDF using unmanned aerial vehicle observations. The results show that the developed DWLS approach improves the accuracy of modeled BRDF of heterogeneous pixels. The DWLS approach applied to satellite observations shows better performance than the OLS method in study regions and exhibits smaller mean fitting residuals both in the red and near-infrared bands. The DWLS approach also shows higher BRDF modeling accuracy than the OLS approach with unmanned aerial vehicle observations. These results indicate that the DWLS inversion approach can be a better choice when kernel-driven models are used for heterogeneous pixels.

Severe mental illnesses (SMIs) are often associated with compromised brain health, physical comorbidities, and cognitive deficits, but it is incompletely understood whether these comorbidities are intrinsic to SMI pathophysiology or secondary to having SMIs. We tested the hypothesis that cerebral, cardiometabolic, and cognitive impairments commonly observed in SMIs can be observed in non-psychiatric individuals with SMI-like brain patterns of deviation as seen on magnetic resonance imaging. 22,883 participants free of common neuropsychiatric conditions from the UK Biobank (age = 63.4 ± 7.5 years, range = 45–82 years, 50.9% female) were split into discovery and replication samples. The regional vulnerability index (RVI) was used to quantify each participant's respective brain similarity to meta-analytical patterns of schizophrenia spectrum disorder, bipolar disorder, and major depressive disorder in gray matter thickness, subcortical gray matter volume, and white matter integrity. Cluster analysis revealed five clusters with distinct RVI profiles. Compared with a cluster with no RVI elevation, a cluster with RVI elevation across all SMIs and brain structures showed significantly higher volume of white matter hyperintensities (Cohen's d = 0.59, pFDR < 10−16), poorer cardiovascular (Cohen's d = 0.30, pFDR < 10−16) and metabolic (Cohen's d = 0.12, pFDR = 1.3 × 10−4) health, and slower speed of information processing (|Cohen's d| = 0.11-0.17, pFDR = 1.6 × 10−3-4.6 × 10−8). This cluster also had significantly higher level of C-reactive protein and alcohol use (Cohen's d = 0.11 and 0.28, pFDR = 4.1 × 10−3 and 1.1 × 10−11). Three other clusters with respective RVI elevation in gray matter thickness, subcortical gray matter volume, and white matter integrity showed intermediate level of white matter hyperintensities, cardiometabolic health, and alcohol use. Our results suggest that cerebral, physical, and cognitive impairments in SMIs may be partly intrinsic via shared pathophysiological pathways with SMI-related brain anatomical changes.

Metastable austenitic steels having ultrafine grained (UFG) microstructures can be fabricated by conventional cold rolling and annealing processes by utilizing the deformation-induced martensitic transformation during cold rolling and its reverse transformation to austenite upon annealing. However, such processes are not applicable when the austenite has high mechanical stability against deformation-induced martensitic transformation, since there is no sufficient amount of martensite formed during cold rolling. In the present study, a two-step cold rolling and annealing process was applied to an Fe-24Ni-0.3C metastable austenitic steel having high mechanical stability. Prior to the cold rolling, a repetitive subzero treatment and reverse annealing treatment were applied. Such a treatment dramatically decreased the mechanical stability of the austenite and greatly accelerated the formation of deformation-induced martensite during the following cold rolling processes. As a result, the grain refinement was significantly promoted, and a fully recrystallized specimen with a mean austenite grain size of 0.5 μm was successfully fabricated, which exhibited both high strength and high ductility.

As an essential vegetation structural parameter, leaf area index (LAI) is involved in many critical biochemical processes, such as photosynthesis, respiration, and precipitation interception. The MODerate resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imager Radiometer Suite (VIIRS) LAI sequence products have long supported various global climate, biogeochemistry, and energy flux research. These applications all rely on the accuracy of the product's long time series. However, uncontrolled interferences (e.g., adverse observation conditions and sensor uncertainties) potentially introduce substantial uncertainties to time series in product applications. As one of the most sensitive areas in response to global climate change, the Tibet Plateau (TP) has been treated as a crucial testing ground for thousands of studies on vegetation. To ensure the credibility of the studies arising from MODIS/VIIRS LAI products, the temporal quality uncertainties of data need to be clarified. This article proposed a method to revisit the temporal stability of the MODIS (MOD and MYD) and VIIRS (VNP) LAI in the TP, expecting to provide useful information for better accounting for the uncertainties in this area. Results show that the MODIS and VIIRS LAI were relatively stable in time series and available to be used continuously, among which the temporal quality of the MODIS LAI was the most stable. Moreover, the MODIS and VIIRS LAI products performed similarly in both time-series stability and time-series anomaly distribution, magnitudes and fluctuations. The time-series stability evaluation strategy applied to the MODIS and VIIRS LAI can also be employed to other remote sensing products.

ABT-199 (venetoclax) is the first-in-class selective B-cell lymphoma 2 (BCL2) inhibitor, which is known to be ineffective towards liver cancer cells. Here, we investigated the efficacy and the underlying molecular processes of the sensitization effect of kaempferol isolated from persimmon leaves (KPL) on the ABT-199-resistant HepG2 cells. The effects of various doses of KPL coupled with ABT-199 on the proliferation of HepG2 cells and on the H22 liver tumor-bearing mouse model were examined, as well as the underlying mechanisms. Our findings showed that ABT-199 alone, in contrast to KPL, had no significant impact on hepatoma cell growth, both in vitro and in vivo. Interestingly, the combination therapy showed significantly higher anti-hepatoma efficacy. Mechanistic studies revealed that combining KPL and ABT-199 may promote both early and late apoptosis, as well as decrease the mitochondrial membrane potential in HepG2 cells. Western blot analysis showed that combination of KPL and ABT-199 significantly reduced the expression of the anti-apoptotic proteins Bcl-2, Bcl-xL, and Mcl-1, raised the expression of Bax and cleaved caspase 3, and enhanced cytochrome C release and Bax translocation. Therefore, KPL combined with ABT-199 has a potential application prospect in the treatment of hepatocellular carcinoma.

BackgroundRecent studies have reported that IGF2BP3 is linked to the pathogenesis of various malignancies. Since IGF2BP3 is associated with poor outcomes of gallbladder carcinoma (GBC), we aimed to explore the association between its N6-methyladenosine (m6A) RNA methylation and GBC progression.MethodsBioinformatic analysis of GSE136982, GSE104165, and RNA-seq was performed. In vitro and in vivo gain- and loss-of-function assays were done. qPCR, Western blotting, and IHC were conducted in cells or in collected clinical tissue samples. RNA immunoprecipitation, RNA stability measurement, methylated RNA immunoprecipitation, and dual-luciferase reporter assays were performed in this study.ResultsThe expression of IGF2BP3 was higher in GBC tissues than in peritumoral tissues. Functions such as cell proliferation and migration, both in vitro and in vivo, were inhibited by downregulation of IGF2BP3. The analysis of RNA-seq indicated that KLK5 was a downstream target of IGF2BP3. The expression of KLK5 was measured in GBC cells and tumor samples. It was found to be positively correlated with IGF2BP3 level. Upon IGF2BP3 depletion, ectopic expression of KLK5 could rescue cell function in part. Mechanistically, we found that IGF2BP3 directly binds to KLK5 mRNA and regulates its stability in an m6A-dependent manner. As a result, inhibition of KLK5 decreased the expression of PAR2, and deregulated phospho-Akt. Using bioinformatic prediction combined with miRNA microarray analysis, we identified that let-7g-5p is an inhibitor of IGF2BP3, and let-7g-5p expression was negatively correlated with IGF2BP3. Overexpression of let-7g-5p affected the aggressive phenotype of GBC cells by deregulating IGF2BP3, and inhibiting the KLK5/PAR2/AKT axis.ConclusionsOur data showed that IGF2BP3 is associated with the aggressive phenotype of GBC. Mechanistically, IGF2BP3 activated the PAR2/AKT axis by stabilizing KLK5 mRNA in an m6A-dependent manner. The loss of let-7g-5p enhanced the expression of IGF2BP3 and improved GBC progression. Thus, IGF2BP3 plays a crucial role in GBC, and the let-7g-5p/IGF2BP3/KLK5/PAR2 axis may be a therapeutic target for GBC.

Abstract Tensile mechanical properties of fully recrystallized TWIP steel specimens having various grain sizes (d) ranging from 0.79 μm to 85.6 μm were investigated. It was confirmed that the UFG specimens having the mean grain sizes of 1.5 μm or smaller abnormally showed discontinuous yielding characterized by a clear yield-drop while the specimens having grain sizes larger than 2.4 μm showed normal continuous yielding. In-situ synchrotron radiation XRD showed dislocation density around yield-drop in the UFG specimen quickly increased. ECCI observations revealed the nucleation of deformation twins and stacking faults from grain boundaries in the UFG specimen around yielding. Although it had been conventionally reported that the grain refinement suppresses deformation twinning in FCC metals and alloys, the number density of deformation twins in the 0.79 μm grain-sized specimen was much higher than that in the specimens with grain sizes of 4.5 μm and 15.4 μm. The unusual change of yielding behavior from continuous to discontinuous manner by grain refinement could be understood on the basis of limited number of free dislocations in each ultrafine grain. The results indicated that the scarcity of free dislocations in the recrystallized UFG specimens changed the deformation and twinning mechanisms in the TWIP steel.

The outbreak of COVID-19 has engendered extensive challenges for conventional hospital operations. To adapt to this problematic issue, a mixed-use hospital functioning system for normal and epidemic situations is proposed. However, the inherent complexity of a hospital embedded with a function of epidemic prevention and control renders a restrained construction process that may compromise quality. In this stance, we developed a BIM (building information modelling)-based simulation approach addressing life-cycle quality control in post-pandemic hospitals. An illustrative case study approach, which draws on the grey literature, was used to address the research question. BIM forward design was employed to integrate with such elements as functional streamline, emergency site, and ward conversion in the process of transformation from normal to epidemic-related operations. Computational fluid dynamics-based fluid simulation was conducted to obtain the most suitable air supply and exhaust solutions for negative pressure wards. BIM forward design method contributed to improving design efficiency and quality. The results of ventilation simulation and environmental analysis showed that the design scheme met all the functional requirements and technical specifications. Meanwhile, the best pipeline synthesis scheme was obtained, which reduced the rework and saved on construction time. The proposed method is beneficial to improve the efficiency of design information sharing and business collaboration. Implications generated from this study can be used as a significant reference for the future construction of various healthcare facilities.

Leaf Area Index (LAI) is one of the most important biophysical parameters of vegetation, and its dynamic changes can be used as a reflective indicator and differentiation basis of vegetation function. In this study, a VCA–MLC (Vertex Component Analysis–Maximum Likelihood Classification) algorithm is proposed from the perspective of multi-temporal satellite LAI image classification to monitor and quantify the spatial and temporal variability of vegetation dynamics in China since 2000. The algorithm extracts the vegetation endmembers from 46 multi-temporal images of MODIS LAI in 2011 without the aid of other a priori knowledge and uses the maximum likelihood classification method to select the categories that satisfy the requirements of the number of missing periods, absolute distance, and relative distance for the rest pixels to be classified, ultimately dividing the vegetation area of China into 10 vegetation zones called China Vegetation Functional Zones (CVFZ). CVFZ outperforms MCD12Q1 and CLCD land cover datasets in the overall differentiation of vegetation functions and can be used synergistically with other land cover datasets. In this study, CVFZ is used to cut the constant vegetation-type pixels of MCD12Q1 during 2001–2022. The results of the LAI mean time series decomposition of each subregion using the STL (Seasonal-Trend Decomposition based on Loess) method show that the rate of vegetation greening ranges from 9.02 × 10−4 m2m−2yr−1 in shrubland subregions to 2.34 × 10−2 m2m−2yr−1 in savanna subregions. In relative terms, the average greening speed of forests is moderate, and savannas tend to have the fastest average greening speed. The greening speed of grasslands and croplands in different zones varies widely. In contrast, the average greening speed of shrublands is the slowest. In addition, CVFZ detected grasslands with one or two phenological cycles, broadleaf croplands with one or two phenological cycles, and shrublands with no apparent or one phenological cycle.

ABSTRACT: The objective of this study was to assess the effects of dietary supplementation of keratinase on the production of broilers fed a diet containing feather meal. A total of 162 1-d-old Cobb 500 male broiler (n = 9 cages/diet with 6 chicks/cage) were randomly allocated to 3 dietary treatments. The broilers were fed a corn-soybean-feather meal based diet (BD), or BD supplemented with keratinase at 100,000 or 200,000 U/kg for 6 weeks. Compared to the control, dietary supplementation with 200,000 U/kg keratinase increased (P < 0.05) body weight gain (3.6–4.3%) and reduced feed conversion ratio (2.4–5.6%) during the various experimental periods, and also improved (P < 0.05) apparent total tract digestibility of ash and calcium by 45.0% and 8.8%, respectively. Meanwhile, dietary supplementation of keratinase at 100,000 U/kg reduced (P < 0.05) the drip loss (29.2%), while 200,000 U/kg keratinase supplementation increased (P < 0.05) the pH value (1.6%) at 45 min and decreased (P < 0.05) the lightness (L* value; 13.6%) and drip loss (22.1%) of pectoral muscle. Moreover, dietary supplementation of keratinase at both levels of 100,000 and 200,000 U/kg increased (P < 0.05) Glutathione peroxidase activity (82.5–87.5%) and decreased the Malondialdehyde concentration (14.5–18.3%) in the pectoral muscle. In conclusion, dietary supplementation of keratinase at 200,000 U/kg can improve the performance, meat quality, apparent total tract digestibility of nutrients, and redox status of broiler chickens fed a diet containing feather meal.

Abstract Background Coronavirus disease 2019 (COVID-19) has emerged as a global pandemic. According to the diagnosis and treatment guidelines of China, negative reverse transcription-polymerase chain reaction (RT-PCR) is the key criterion for discharging COVID-19 patients. However, repeated RT-PCR tests lead to medical waste and prolonged hospital stays for COVID-19 patients during the recovery period. Our purpose is to assess a model based on chest computed tomography (CT) radiomic features and clinical characteristics to predict RT-PCR negativity during clinical treatment. Methods From February 10 to March 10, 2020, 203 mild COVID-19 patients in Fangcang Shelter Hospital were retrospectively included (training: n = 141; testing: n = 62), and clinical characteristics were collected. Lung abnormalities on chest CT images were segmented with a deep learning algorithm. CT quantitative features and radiomic features were automatically extracted. Clinical characteristics and CT quantitative features were compared between RT-PCR-negative and RT-PCR-positive groups. Univariate logistic regression and Spearman correlation analyses identified the strongest features associated with RT-PCR negativity, and a multivariate logistic regression model was established. The diagnostic performance was evaluated for both cohorts. Results The RT-PCR-negative group had a longer time interval from symptom onset to CT exams than the RT-PCR-positive group (median 23 vs. 16 days, p

To explore the role of contextual information in determining manner of death, four cases involving single gunshot wounds were presented to participants (n = 252) involved in medicolegal death investigation. The participants received identical autopsy information but different contextual information. The data demonstrated that participants tended to rely on contextual information more than autopsy information: In the suicide context, participants across the four cases reached 153 final decisions of suicide (and 25 of homicide), whereas in the homicide context, participants reached only 10 final decisions of suicide (and 181 of homicide) --all while examining identical autopsy information. The impact of the contextual information was so powerful that many participants changed initial autopsy-based conclusions to align with the contextual information. Given the significant role and impact that contextual information has on expert decision making, one must consider what, how, and when contextual information should be used.

Abstract This experiment was conducted to evaluate the impact of yeast and lactic acid bacteria (LAB) on mastitis and milk microbiota composition of dairy cows. Thirty lactating Holstein cows with similar parity, days in milk were randomly assigned to five treatments, including: (1) Health cows with milk SCC 500,000 cells/mL, fed basal TMR without supplementation (M); (3) Mastitis cows fed basal TMR supplemented with 8 g day−1 yeast (M + Y); (4) Mastitis cows fed basal TMR supplemented with 8 g day−1 LAB (M + L); (5) Mastitis cows (milk SCC > 500,000 cells/mL) fed basal TMR supplemented with 4 g day−1 yeast and 4 g day−1 LAB (M + Y + L). Blood and milk sample were collected at day 0, day 20 and day 40. The results showed efficacy of probiotic: On day 20 and day 40, milk SCC in H, M + Y, M + L, M + Y + L was significantly lower than that of M (P

Abstract. Background. Despite the growing epidemic of heart failure (HF), there is limited data available to systematically compare non-cardiac comorbidities in the young-old, old-old, and oldest-old patients hospitalized for HF. The precise differences will add valuable information for better management of HF in elderly patients. Methods. A total of 1053 patients aged 65 years or older hospitalized with HF were included in this study. Patients were compared among three age groups: (1) young-old: 65 to 74 years, (2) old-old: 75 to 84 years, and (3) oldest-old: ≥85 years. Clinical details of presentation, comorbidities, and prescribed medications were recorded. Results. The mean age was 76.7 years and 12.7% were 85 years or older. Most elderly patients with HF (97.5%) had at least one of the non-cardiac comorbidities. The patterns of common non-cardiac comorbidities were different between the young-old and oldest-old group. The three most common non-cardiac comorbidities were anemia (53.6%), hyperlipidemia (45.9%), and diabetes (42.4%) in the young-old group, while anemia (73.1%), infection (58.2%), and chronic kidney disease (44.0%) in the oldest-old group. Polypharmacy was observed in 93.0% elderly patients with HF. Additionally, 29.2% patients were diagnosed with infection, and 67.0% patients were prescribed antibiotics. However, 60.4% patients were diagnosed with anemia with only 8.9% of them receiving iron repletion. Conclusions. Non-cardiac comorbidities are nearly universal in three groups but obviously differ by age, and inappropriate medications are very common in elderly patients with HF. Further treatment strategies should be focused on providing optimal medications for age-specific non-cardiac conditions.

Imaging genetics analyses use neuroimaging traits as intermediate phenotypes to infer the degree of genetic contribution to brain structure and function in health and/or illness. Coefficients of relatedness (CR) summarize the degree of genetic similarity among subjects and are used to estimate the heritability – the proportion of phenotypic variance explained by genetic factors. The CR can be inferred directly from genome-wide genotype data to explain the degree of shared variation in common genetic polymorphisms (SNP-heritability) among related or unrelated subjects. We developed a central processing and graphics processing unit (CPU and GPU) accelerated Fast and Powerful Heritability Inference (FPHI) approach that linearizes likelihood calculations to overcome the ∼N2–3 computational effort dependency on sample size of classical likelihood approaches. We calculated for 60 regional and 1.3 × 105 voxel-wise traits in N = 1,206 twin and sibling participants from the Human Connectome Project (HCP) (550 M/656 F, age = 28.8 ± 3.7 years) and N = 37,432 (17,531 M/19,901 F; age = 63.7 ± 7.5 years) participants from the UK Biobank (UKBB). The FPHI estimates were in excellent agreement with heritability values calculated using Genome-wide Complex Trait Analysis software (r = 0.96 and 0.98 in HCP and UKBB sample) while significantly reducing computational (102–4 times). The regional and voxel-wise traits heritability estimates for the HCP and UKBB were likewise in excellent agreement (r = 0.63–0.76, p < 10−10). In summary, the hardware-accelerated FPHI made it practical to calculate heritability values for voxel-wise neuroimaging traits, even in very large samples such as the UKBB. The patterns of additive genetic variance in neuroimaging traits measured in a large sample of related and unrelated individuals showed excellent agreement regardless of the estimation method. The code and instruction to execute these analyses are available at www.solar-eclipse-genetics.org.

Compound extremes pose immense challenges and hazards to communities, and this is particularly true for compound hydrometeorological extremes associated with deadly floods, surges, droughts, and heat waves. To mitigate and better adapt to compound hydrometeorological extremes, we need to better understand the state of knowledge of such extremes. Here we review the current advances in understanding compound hydrometeorological extremes: compound heat wave and drought (hot-dry), compound heat stress and extreme precipitation (hot-wet), cold-wet, cold-dry and compound flooding. We focus on the drivers of these extremes and methods used to investigate and quantify their associated risk. Overall, hot-dry compound extremes are tied to subtropical highs, blocking highs, atmospheric stagnation events, and planetary wave patterns, which are modulated by atmosphere-land feedbacks. Compared with hot-dry compound extremes, hot-wet events are less examined in the literature with most works focusing on case studies. The cold-wet compound events are commonly associated with snowfall and cold frontal systems. Although cold-dry events have been found to decrease, their underlying mechanisms require further investigation. Compound flooding encompasses storm surge and high rainfall, storm surge and sea level rise, storm surge and riverine flooding, and coastal and riverine flooding. Overall, there is a growing risk of compound flooding in the future due to changes in sea level rise, storm intensity, storm precipitation, and land-use-land-cover change. To understand processes and interactions underlying compound extremes, numerical models have been used to complement statistical modeling of the dependence between the components of compound extremes. While global climate models can simulate certain types of compound extremes, high-resolution regional models coupled with land and hydrological models are required to simulate the variability of compound extremes and to project changes in the risk of such extremes. In terms of statistical modeling of compound extremes, previous studies have used empirical approach, event coincidence analysis, multivariate distribution, the indicator approach, quantile regression and the Markov Chain method to understand the dependence, greatly advancing the state of science of compound extremes. Overall, the selection of methods depends on the type of compound extremes of interests and relevant variables.

Tobacco smoking is an addictive behavior that supports nicotine dependence and is an independent risk factor for cancer and other illnesses. Its neurogenetic mechanisms are not fully understood but may act through alterations in the cerebral white matter (WM). We hypothesized that the vertical pleiotropic pathways, where genetic variants influence a trait that in turn influences another trait, link genetic factors, integrity of cerebral WM, and nicotine addiction. We tested this hypothesis using individual genetic factors, WM integrity measured by fractional anisotropy (FA), and nicotine dependence-related smoking phenotypes, including smoking status (SS) and cigarettes per day (CPDs), in a large epidemiological sample collected by the UK Biobank. We performed a genome-wide association study (GWAS) to identify previously reported loci associated with smoking behavior. Smoking was found to be associated with reduced WM integrity in multiple brain regions. We then evaluated two competing vertical pathways: Genes → WM integrity → Smoking versus Genes → Smoking → WM integrity and a horizontal pleiotropy pathway where genetic factors independently affect both smoking and WM integrity. The causal pathway analysis identified 272 pleiotropic single-nucleotide polymorphisms (SNPs) whose effects on SS were mediated by FA, as well as 22 pleiotropic SNPs whose effects on FA were mediated by CPD. These SNPs were mainly located in important susceptibility genes for smoking-induced diseases NCAM1 and IREB2. Our findings revealed the role of cerebral WM in the maintenance of the complex addiction and provided potential genetic targets for future research in examining how changes in WM integrity contribute to the nicotine effects on the brain.

In both hardware and software, masking can represent an effective means of hardening an implementation against side-channel attack vectors such as Differential Power Analysis (DPA). Focusing on software, however, the use of masking can present various challenges: specifically, it often 1) requires significant effort to translate any theoretical security properties into practice, and, even then, 2) imposes a significant overhead in terms of efficiency. To address both challenges, this paper explores the use of an Instruction Set Extension (ISE) to support masking in software-based implementations of a range of (symmetric) cryptographic kernels including AES: we design, implement, and evaluate such an ISE, using RISC-V as the base ISA. Our ISE-supported first-order masked implementation of AES, for example, is an order of magnitude more efficient than a software-only alternative with respect to both execution latency and memory footprint; this renders it comparable to an unmasked implementation using the same metrics, but also first-order secure.

Objective: To investigate the value of delta-radiomics after the first cycle of neoadjuvant chemotherapy (NAC) using dynamic contrast-enhanced (DCE) MRI for early prediction of pathological complete response (pCR) in patients with breast cancer. Methods: From September 2018 to May 2021, a total of 140 consecutive patients (training, n = 98: validation, n = 42), newly diagnosed with breast cancer who received NAC before surgery, were prospectively enrolled. All patients underwent DCE-MRI at pre-NAC (pre-) and after the first cycle (1st-) of NAC. Radiomic features were extracted from the postcontrast early, peak, and delay phases. Delta-radiomics features were computed in each contrast phases. Least absolute shrinkage and selection operator (LASSO) and a logistic regression model were used to select features and build models. The model performance was assessed by receiver operating characteristic (ROC) analysis and compared by DeLong test. Results: The delta-radiomics model based on the early phases of DCE-MRI showed a highest AUC (0.917/0.842 for training/validation cohort) compared with that using the peak and delay phases images. The delta-radiomics model outperformed the pre-radiomics model (AUC = 0.759/0.617, p = 0.011/0.047 for training/validation cohort) in early phase. Based on the optimal model, longitudinal fusion radiomic models achieved an AUC of 0.871/0.869 in training/validation cohort. Clinical-radiomics model generated good calibration and discrimination capacity with AUC 0.934 (95%CI: 0.882, 0.986)/0.864 (95%CI: 0.746, 0.982) for training and validation cohort. Delta-radiomics based on early contrast phases of DCE-MRI combined clinicopathology information could predict pCR after one cycle of NAC in patients with breast cancer.

In high-elevation mountains, seasonal snow cover affects land surface phenology and the functioning of the ecosystem. However, studies regarding the long-term effects of snow cover on phenological changes for high mountains are still limited. Our study is based on MODIS data from 2003 to 2021. First, the NDPI was calculated, time series were reconstructed, and an SG filter was used. Land surface phenology metrics were estimated based on the dynamic thresholding method. Then, snow seasonality metrics were also estimated based on snow seasonality extraction rules. Finally, correlation and significance between snow seasonality and land surface phenology metrics were tested. Changes were analyzed across elevation and vegetation types. Results showed that (1) the asymmetry in the significant correlation between the snow seasonality and land surface phenology metrics suggests that a more snow-prone non-growing season (earlier first snow, later snowmelt, longer snow season and more snow cover days) benefits a more flourishing vegetation growing season in the following year (earlier start and later end of growing season, longer growing season). (2) Vegetation phenology metrics above 3500 m is sensitive to the length of the snow season and the number of snow cover days. The effect of first snow day on vegetation phenology shifts around 3300 m. The later snowmelt favors earlier and longer vegetation growing season regardless of the elevation. (3) The sensitivity of land surface phenology metrics to snow seasonality varied among vegetation types. Grass and shrub are sensitive to last snow day, alpine vegetation to snow season length, desert to number of snow cover days, and forest to first snow day. In this study, we used a more reliable NDPI at high elevations and confirmed the past conclusions about the impact of snow seasonality metrics. We also described in detail the curves of snow seasonal metrics effects with elevation change. This study reveals the relationship between land surface phenology and snow seasonality in the Qilian Mountains and has important implications for quantifying the impact of climate change on ecosystems.

The compound heat wave and extreme precipitation events are responsible for severe damages to the environment and human societies. Although major advances have been made in understanding the compound extremes (e.g., drought and heat wave), little is known about two types of extremes synchronized/connected in different regions in China. Here we identify a new type of compound extreme termed as “remote compound extreme” with the aid of a new extreme value detection method that combines isolated forest and quantile statistics. The new compound extremes are reflected by a statistically significant correlation (i.e., 0.52) between heat wave in the Pearl River Delta and extreme precipitation in the Yangtze River Delta. The remote compound extreme may be tied to the western Pacific subtropical high that modulates typhoons, surface temperature in the Pearl River Delta and extreme precipitation in the middle and lower reaches of the Yangtze River.

The clinical application of doxorubicin (DOX) in cancer chemotherapy is limited by its life-threatening cardiotoxic effects. Chrysophanol (CHR), an anthraquinone compound isolated from the rhizome of Rheum palmatum L., is considered to play a broad role in a variety of biological processes. However, the effects of CHR׳s cardioprotection in DOX-induced cardiomyopathy is poorly understood. In this study, we found that the cardiac apoptosis, mitochondrial injury and cellular PARylation levels were significantly increased in H9C2 cells treated by Dox, while these effects were suppressed by CHR. Similar results were observed when PARP1 activity was suppressed by its inhibitors 3-aminobenzamide (3AB) and ABT888. Ectopic expression of PARP1 effectively blocked this CHR׳s cardioprotection against DOX-induced cardiomyocyte injury in H9C2 cells. Furthermore, pre-administration with both CHR and 3AB relieved DOX-induced cardiac apoptosis, mitochondrial impairment and heart dysfunction in Sprague–Dawley rat model. These results revealed that CHR protects against DOX-induced cardiotoxicity by suppressing cellular PARylation and provided critical evidence that PARylation may be a novel target for DOX-induced cardiomyopathy. KEY WORDS: Chrysophanol, Doxorubicin, PARylation, Cardiotoxicity, Apoptosis, Mitochondria

Abstract Acanthopanacis Senticosi Radix et Rhizoma seu Caulis, the dried root and rhizome or stem of Acanthopanax senticosus, is commonly known as Siberian ginseng or Ciwujia in Chinese. It is used all over the world as an adaptogen to enhance physical and mental performance for the sake of normal physiological functioning of human bodies under stress. In the theory of traditional Chinese medicine, Ciwujia can strengthen the spleen that is an essential organ for immunological response. Its traditional applications include inflammation, fatigue and cancer in which the immune-regulating function is always involved. In this article, the immunomodulatory activities of Ciwujia extracts, fractions and pure compounds were extensively reviewed first. Then, the possibility of upgrading the chemical markers to bioactive markers was explored. Finally, the potency of aqueous extract and ethanol extract in regulating cytokines production from human peripheral blood mononuclear cells was compared. We conclude that although various phytochemicals such as isofraxidin, syringin and eleutheroside E from Ciwujia have been shown to modulate immunological functions, the aqueous extract of Ciwujia as a whole possesses the most potent efficacy. Therefore, aqueous (rather than ethanol) extract of Ciwujia should be used in order to benefit from its immunomodulatory properties.

The interdecadal change of the winter-spring tropospheric temperature over Asia and its impact on the South China Sea summer monsoon (SCSSM) onset are investigated in this study. The SCSSM onset experiences a significant advance around the mid-1990s, which is attributed to the positive interdecadal anomaly of meridional temperature gradient in the mid-upper troposphere in May over the South China Sea monsoon region. This positive interdecadal anomaly can be traced back to the previous winter and spring, mainly associated with the mid-upper tropospheric warming in the East Asian subtropics. During the interdecadal anomalous seasonal evolution of the East Asian subtropical mid-upper tropospheric temperature, advection of the warm temperature anomaly by climatological mean wind overtakes the effects of anomalous adiabatic cooling and diabatic cooling, leading to a net interdecadal seasonal warming in winter. In spring, the adiabatic heating caused by the interdecadal anomalous subsidence flow cannot offset the effects of interdecadal anomalous cold advection and diabatic cooling, resulting in a net interdecadal seasonal cooling. However, the interdecadal seasonal cooling in spring is not strong enough to offset the interdecadal seasonal warming in winter, preserving an interdecadal mid-upper tropospheric warming over the subtropical East Asia in late spring. This interdecadal warming provides a favorable condition for the interdecadal advance of the SCSSM onset. Both observational analyses and numerical experiments suggest that the interdecadal change of atmospheric thermodynamic processes in winter−spring is related to the interdecadal warming in the tropical western Pacific. The enhanced convection and condensation heating over the regions from the South China Sea to the Philippines, forced by the tropical western Pacific warming, stimulates an anomalous anticyclone in the upper troposphere and warming in the whole troposphere over the subtropical East Asia.

Forecasting rapid intensification (RI) of the South China Sea (SCS) tropical cyclones (TCs) remains an operational challenge, mainly owing to the incomplete understanding of its physical mechanisms. Based on TC best-track data, atmospheric analysis data, and sea surface temperature data, this study compares temporal evolution characteristics of environmental conditions from the previous 24 h to the onset time for RI and non-RI TCs in the SCS during 2000–2018, and then identifies key factors for RI of the SCS TCs using the box difference index and stepwise regression. A combination of strong divergence in the upper troposphere and strong convergence in the boundary layer, weak deep-layer vertical wind shear, fast storm translation speed, and high TC intensification potential (i.e., maximum potential intensity minus current intensity) north of the storm center at the previous 24 h are favorable for RI of the SCS TCs, and their importance for RI is in descending order. The results may shed light on operational forecasting of rapid intensification of the SCS TCs.

Responses of terrestrial ecosystems to decreased nitrogen (N) deposition has brought considerable attention. Soil organic carbon (SOC) turnover is an important parameter in the terrestrial ecosystem model and ecosystem management. However, how SOC turnover responds to decreased N deposition has not yet been evaluated. Here we addressed this issue by the comparison of the SOC turnover in the treatment that receiving high N addition for 4 years and then none for 6 years (48 g N·m−2·yr−1, N48-cessation) with that derived from the control treatment (0 g N·m−2·yr−1, N0) in Inner Mongolia grassland, China. In this study, 14C isotope technology was used to directly reveal SOC turnover time. Our results showed that SOC turnover time in the N48-cessation treatment had no statistical difference compared with that in the N0 treatment after 6 years of N cessation, indicating that its SOC turnover had recovered from high N enrichment. The reduction of SOC storage (274 g/m2) in N48-cessation treatment from 2010 to 2014 also proved this recovery. Moreover, we also found that the species richness and Shannon diversity index in the N48-cessation treatment were significantly lower than those in the N0 treatment. It indicated that the recovery of SOC turnover was faster than plant diversity in the grassland when high N addition was ceased. This study suggested that the grasslands experienced high N deposition should reduce grazing and mowing in order to increase soil carbon input and offset the negative effect of the rapid recovery of SOC turnover on soil C storage when N deposition was decreased.