A model-by-model analysis for historical simulations was necessary for identifying reasonably performing models in the updated Coupled Model Intercomparison Project (CMIP6) over the Tibetan Plateau. ...To determine whether the capacity of the CMIP6 models in simulating temperature and precipitation over the Plateau has been enhanced, we compared the outputs of 23 CMIP6 models with an observational dataset (CN05.1) for the period 1961–2014. The results suggest the systematic model biases (cold bias and wet bias) in the Tibetan Plateau still exist in CMIP6. Most models in CMIP6 realistically simulated the surface temperature and spatial distribution of precipitation, with a pattern correlation exceeding 0.75. The bias in the mean surface temperature of the multi-model ensemble (MME) simulation was 1.08 °C lower than the observational data, which had been decreased compared with the cold bias of CMIP5 (1.52 °C). At the seasonal scale, most models exhibited a warm temperature bias in summer and a cold bias in winter. The CMIP6 MME displayed a higher reproducibility of the precipitation amplitude over dry regions compared with CMIP5 and a lower ability over wet regions.
Increased risk of colorectal cancer (CRC) is associated with altered intestinal microbiota as well as short‐chain fatty acids (SCFAs) reduction of output The energy source of colon cells relies ...mainly on three SCFAs, namely butyrate (BT), propionate, and acetate, while CRC transformed cells rely mainly on aerobic glycolysis to provide energy. This review summarizes recent research results for dysregulated glucose metabolism of SCFAs, which could be initiated by gut microbiome of CRC. Moreover, the relationship between SCFA transporters and glycolysis, which may correlate with the initiation and progression of CRC, are also discussed. Additionally, this review explores the linkage of BT to transport of SCFAs expressions between normal and cancerous colonocyte cell growth for tumorigenesis inhibition in CRC. Furthermore, the link between gut microbiota and SCFAs in the metabolism of CRC, in addition, the proteins and genes related to SCFAs‐mediated signaling pathways, coupled with their correlation with the initiation and progression of CRC are also discussed. Therefore, targeting the SCFA transporters to regulate lactate generation and export of BT, as well as applying SCFAs or gut microbiota and natural compounds for chemoprevention may be clinically useful for CRCs treatment. Future research should focus on the combination these therapeutic agents with metabolic inhibitors to effectively target the tumor SCFAs and regulate the bacterial ecology for activation of potent anticancer effect, which may provide more effective application prospect for CRC therapy.
Short‐chain fatty acids (SCFAs) produced in the human colon are the major products of bacterial fermentation of undigested dietary fiber and starch that escape absorption in the small intestine, and serve as a major source of energy for colonocytes. SCFAs are microbial‐derived metabolites, which are readily absorbed and used as an energy source by colonocytes. Several mechanisms have been proposed to underlie the anticancerous mechanisms of SCFAs. SCFAs reduce epithelial inflammation and trigger cancer cell apoptosis via p21 activity, providing an important defensive capacity against colorectal carcinogenesis.
The intelligent recognition of epileptic electro-encephalogram (EEG) signals is a valuable tool for the epileptic seizure detection. Recent deep learning models fail to fully consider both spectral ...and temporal domain representations simultaneously, which may lead to omitting the nonstationary or nonlinear property in epileptic EEGs and further produce a suboptimal recognition performance consequently. In this paper, an end-to-end EEG seizure detection framework is proposed by using a novel channel-embedding spectral-temporal squeeze-and-excitation network (CE-stSENet) with a maximum mean discrepancy-based information maximizing loss. Specifically, the CE-stSENet firstly integrates both multi-level spectral and multi-scale temporal analysis simultaneously. Hierarchical multi-domain representations are then captured in a unified manner with a variant of squeeze-and-excitation block. The classification net is finally implemented for epileptic EEG recognition based on features extracted in previous subnetworks. Particularly, to address the fact that the scarcity of seizure events results in finite data distribution and the severe overfitting problem in seizure detection, the CE-stSENet is coordinated with a maximum mean discrepancy-based information maximizing loss for mitigating the overfitting problem. Competitive experimental results on three EEG datasets against the state-of-the-art methods demonstrate the effectiveness of the proposed framework in recognizing epileptic EEGs, indicating its powerful capability in the automatic seizure detection.
Motor imagery electroencephalography (EEG) decoding is an essential part of brain-computer interfaces (BCIs) which help motor-disabled patients to communicate with the outside world by external ...devices. Recently, deep learning algorithms using decomposed spectrums of EEG as inputs may omit important spatial dependencies and different temporal scale information, thus generated the poor decoding performance. In this paper, we propose an end-to-end EEG decoding framework, which employs raw multi-channel EEG as inputs, to boost decoding accuracy by the channel-projection mixed-scale convolutional neural network (CP-MixedNet) aided by amplitude-perturbation data augmentation. Specifically, the first block in CP-MixedNet is designed to learn primary spatial and temporal representations from EEG signals. The mixed-scale convolutional block is then used to capture mixed-scale temporal information, which effectively reduces the number of training parameters when expanding reception fields of the network. Finally, based on the features extracted in previous blocks, the classification block is constructed to classify EEG tasks. The experiments are implemented on two public EEG datasets (BCI competition IV 2a and High gamma dataset) to validate the effectiveness of the proposed approach compared to the state-of-the-art methods. The competitive results demonstrate that our proposed method is a promising solution to improve the decoding performance of motor imagery BCIs.
Developing novel luminescent materials for sensitive and rapid detection of phosphate (Pi) is vital in clinical diagnoses and water-quality monitoring. Herein, a lanthanide coordination polymer (NH
2
...-BDC-TbGMP CPs)-based ratiometric fluorescent probe is designed for quick and visual detection of Pi. The NH
2
-BDC-TbGMP CPs are prepared
via
the self-assembly of 2-aminoterephthalic acid (NH
2
-BDC) and guanine monophosphate (GMP) with terbium ions (Tb
3+
). After the formation of NH
2
-BDC-TbGMP CPs, the inherent fluorescence of NH
2
-BDC is quenched
via
static quenching, while the nonluminous Tb
3+
can emit strong green fluorescence due to the antenna effect between Tb
3+
and GMP. In the presence of Pi, Pi can competitively combine with Tb
3+
to interrupt the interaction of the NH
2
-BDC-TbGMP CP system, further causing a decrease in the fluorescence of Tb
3+
and an increase in the emission of NH
2
-BDC. Accordingly, the ratiometric fluorescence sensing of Pi can be achieved by continuously recording the variations of two fluorescence signals. The corresponding fluorescence intensity ratio of Tb
3+
to NH
2
-BDC (
F
547
/
F
425
) is linearly correlated with the Pi concentration in the range of 0.5 to 100 μM, with a detection limit of 0.13 μM. This strategy offers a simple, rapid, and sensitive method for the ratiometric fluorescence and visual sensing of Pi, which shows great application potential for water-quality monitoring.
A dual-ligand lanthanide coordination polymer is designed for ratiometric fluorescence and visual detection of Pi.
A novel copper‐catalyzed regiodivergent alkylboration of alkenes with bis(pinacolato)diboron and alkyl halides has been developed. The regioselectivity of the alkylboration was controlled by subtle ...differences in the ligand structure. The reaction thus enables the practical, regiodivergent synthesis of two different alkyl boronic esters with complex structures from a single alkene.
One way or another: The copper‐catalyzed regiodivergent alkylboration of alkenes with bis(pinacolato)diboron and alkyl halides is described. The regioselectivity of the carboboration can be controlled by fine‐tuning the ligand structure.
A
bstract
We calculate in this paper the perturbative gluon transverse momentum dependent parton distribution functions (TMDPDFs) and fragmentation functions (TMDFFs) using the exponential regulator ...for rapidity divergences. We obtain results for both unpolarized and linearly polarized distributions through next-to-next-to leading order in strong coupling constant, and through
O
(
ϵ
2
) in dimensional regulator. We find a nontrivial momentum conservation sum rule for the linearly polarized component for both TMDPDFs and TMDFFs in the
N
= 1 super-Yang-Mills theory. The TMDFFs are used to calculate the two-loop gluon jet function for the energy-energy correlator in Higgs gluonic decay in the back-to-back limit.
Abstract
We report the observations of FRB 20220912A using the Five-hundred-meter Aperture Spherical radio Telescope. We conducted 17 observations totaling 8.67 hr and detected a total of 1076 bursts ...with an event rate up to 390 hr
−1
. The cumulative energy distribution can be well described using a broken power-law function with the lower- and higher-energy slopes of −0.38 ± 0.02 and −2.07 ± 0.07, respectively. We also report the
L
-band (1–1.5 GHz) spectral index of the synthetic spectrum of FRB 20220912A bursts, which is −2.6 ± 0.21. The average rotation measure value of the bursts from FRB 20220912A is −0.08 ± 5.39 rad m
−2
, close to 0 rad m
−2
and was relatively stable over 2 months. Most bursts have nearly 100% linear polarization. About 45% of the bursts have circular polarization with Signal-to-Noise ratio > 3, and the highest circular polarization degree can reach 70%. Our observations suggest that FRB 20220912A is located in a relatively clean local environment with complex circular polarization characteristics. These various behaviors imply that the mechanism of circular polarization of FRBs likely originates from an intrinsic radiation mechanism, such as coherent curvature radiation or inverse Compton scattering inside the magnetosphere of the FRB engine source (e.g., a magnetar).
COVID‐19 is characterized by dysregulated immune responses, metabolic dysfunction and adverse effects on the function of multiple organs. To understand host responses to COVID‐19 pathophysiology, we ...combined transcriptomics, proteomics, and metabolomics to identify molecular markers in peripheral blood and plasma samples of 66 COVID‐19‐infected patients experiencing a range of disease severities and 17 healthy controls. A large number of expressed genes, proteins, metabolites, and extracellular RNAs (exRNAs) exhibit strong associations with various clinical parameters. Multiple sets of tissue‐specific proteins and exRNAs varied significantly in both mild and severe patients suggesting a potential impact on tissue function. Chronic activation of neutrophils, IFN‐I signaling, and a high level of inflammatory cytokines were observed in patients with severe disease progression. In contrast, COVID‐19‐infected patients experiencing milder disease symptoms showed robust T‐cell responses. Finally, we identified genes, proteins, and exRNAs as potential biomarkers that might assist in predicting the prognosis of SARS‐CoV‐2 infection. These data refine our understanding of the pathophysiology and clinical progress of COVID‐19.
SYNOPSIS
Proteomics, metabolomics and RNAseq data map immune responses in COVID‐19 patients with different disease severity, revealing molecular makers associated with disease progression and alterations of tissue‐specific proteins.
A multi‐omics profiling of the host response to SARS‐CoV2 infection in 66 clinically diagnosed and laboratory confirmed COVID‐19 patients and 17 uninfected controls.
Significant correlations between multi‐omics data and key clinical parameters.
Alteration of tissue‐specific proteins and exRNAs.
Enhanced activation of immune responses is associated with COVID‐19 pathogenesis.
Biomarkers to predict COVID‐19 clinical outcomes pending clinical validation as prospective marker.
Proteomics, metabolomics and RNAseq data map immune responses in COVID‐19 patients with different disease severity, revealing molecular makers associated with disease progression and alterations of tissue‐specific proteins.
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•The synergistic effects of algae and fungi greatly enhanced the pollutants removal.•The protein and lipid yield were significantly improved in the co-culture process.•Simultaneous ...culture and harvesting of cells was achieved in an integrated process.
A novel method of one-step co-cultivation and harvesting of microalgae and fungi, for efficient starch wastewater treatment and high-value biomass production was developed. By combination of Aspergillus oryzae and Chlorella pyrenoidosa, nutrients in wastewater could be converted to useful microbial biomass, while the wastewater was purified. Moreover, the microalgae C. pyrenoidosa could gradually be encapsulated in fungal pellets which promoted the biomass harvesting. The free algal cells could be completely harvested by fungal pellets within 72 h. The synergistic effects between them greatly improved the removal efficiencies of main pollutants as the removal efficiency of COD, TN, and TP reached 92.08, 83.56, and 96.58 %, respectively. In addition, the final biomass concentration was higher than that of individual cultures. The protein and lipid concentration was also significantly improved and reached 1.92 and 0.99 g/L, respectively. This study provides a simple and efficient strategy for simultaneous wastewater treatment and high-value biomass production.
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