C–H bond activation and decarboxylation are two significant processes in organic synthesis. The combination of these processes provides a novel synthetic strategy, that is, decarboxylative C–H bond ...functionalization. Considerable attention has been focused on such an active research field. This review offers an overview of the utility of decarboxylative C–H bond functionalization in the synthesis of various organic compounds, such as styrenes, chalcones, biaryls, and heterocycles, covering most of the recent advances of the decarboxylative functionalization of Csp–H, Csp2–H, and Csp3–H bonds, as well as their scopes, limitations, practical applications, and synthetic potentials.
In many real-world applications, an object can be described from multiple views or styles, leading to the emerging multi-view analysis. To eliminate the complicated (usually highly nonlinear) view ...discrepancy for favorable cross-view recognition and retrieval, we propose a Multi-view Linear Discriminant Analysis Network (MvLDAN) by seeking a nonlinear discriminant and view-invariant representation shared among multiple views. Unlike existing multi-view methods which directly learn a common space to reduce the view gap, our MvLDAN employs multiple feedforward neural networks (one for each view) and a novel eigenvalue-based multi-view objective function to encapsulate as much discriminative variance as possible into all the available common feature dimensions. With the proposed objective function, the MvLDAN could produce representations possessing: 1) low variance within the same class regardless of view discrepancy, 2) high variance between different classes regardless of view discrepancy, and 3) high covariance between any two views. In brief, in the learned multi-view space, the obtained deep features can be projected into a latent common space in which the samples from the same class are as close to each other as possible (even though they are from different views), and the samples from different classes are as far from each other as possible (even though they are from the same view). The effectiveness of the proposed method is verified by extensive experiments carried out on five databases, in comparison with the 19 state-of-the-art approaches.
Efficient degradation of plastics, the vital challenge for a sustainable future, stands in need of better chemical recycling procedures that help produce commercially valuable small molecules and ...redefine plastic waste as a rich source of chemical feedstock. However, the corresponding chemical recycling methods, while being generally restricted to polar polymers, need improvement. Particularly, degradation of chemically inert nonpolar polymers, the major constitutes of plastics, suffers from low selectivity and very harsh transformation conditions. Herein, an efficient method was developed for selective degradation of styrene‐related plastics under gentle conditions through multiple oxidation of sp3 C−H bonds and sp3 C−C bonds. The procedure was catalyzed with inexpensive iron salts under visible light, using oxygen as green oxidant. Furthermore, simple iron salts could be used to degrade plastics in the absence of solvent under natural conditions, highlighting the potential application of iron salts as additives for degradable plastics.
Plastics degradation: An iron photocatalysis system improves the multiple C−H and C−C bond oxidative cleavage of substituted benzenes, applying oxygen as the terminal oxidant to produce benzoic acid selectively. The system is used to degrade styrene‐related plastics successfully, even under natural conditions without solvent.
The global death toll from coronavirus disease (COVID-19) virus as of May 12, 2020, exceeds 286,000. The risk factors for death were attributed to advanced age and comorbidities but have not been ...accurately defined.
To report the clinical features of 85 fatal cases of COVID-19 in two hospitals in Wuhan.
Medical records were collected of 85 fatal cases of COVID-19 between January 9, 2020, and February 15, 2020. Information recorded included medical history, exposure history, comorbidities, symptoms, signs, laboratory findings, computed tomographic scans, and clinical management.
The median age of the patients was 65.8 years, and 72.9% were male. Common symptoms were fever (78 91.8%), shortness of breath (50 58.8%), fatigue (50 58.8%), and dyspnea (60 70.6%). Hypertension, diabetes, and coronary heart disease were the most common comorbidities. Notably, 81.2% of patients had very low eosinophil counts on admission. Complications included respiratory failure (80 94.1%), shock (69 81.2%), acute respiratory distress syndrome (63 74.1%), and arrhythmia (51 60%), among others. Most patients received antibiotic (77 90.6%), antiviral (78 91.8%), and glucocorticoid (65 76.5%) treatments. A total of 38 (44.7%) and 33 (38.8%) patients received intravenous immunoglobulin and IFN-α2b, respectively.
In this depictive study of 85 fatal cases of COVID-19, most cases were males aged over 50 years with noncommunicable chronic diseases. The majority of the patients died of multiple organ failure. Early onset of shortness of breath may be used as an observational symptom for COVID-19 exacerbations. Eosinophilopenia may indicate a poor prognosis. A combination of antimicrobial drugs did not offer considerable benefit to the outcome of this group of patients.
Quantum computers promise to perform certain tasks that are believed to be intractable to classical computers. Boson sampling is such a task and is considered a strong candidate to demonstrate the ...quantum computational advantage. We performed Gaussian boson sampling by sending 50 indistinguishable single-mode squeezed states into a 100-mode ultralow-loss interferometer with full connectivity and random matrix-the whole optical setup is phase-locked-and sampling the output using 100 high-efficiency single-photon detectors. The obtained samples were validated against plausible hypotheses exploiting thermal states, distinguishable photons, and uniform distribution. The photonic quantum computer,
, generates up to 76 output photon clicks, which yields an output state-space dimension of 10
and a sampling rate that is faster than using the state-of-the-art simulation strategy and supercomputers by a factor of ~10
.
We report phase-programmable Gaussian boson sampling (GBS) which produces up to 113 photon detection events out of a 144-mode photonic circuit. A new high-brightness and scalable quantum light source ...is developed, exploring the idea of stimulated emission of squeezed photons, which has simultaneously near-unity purity and efficiency. This GBS is programmable by tuning the phase of the input squeezed states. The obtained samples are efficiently validated by inferring from computationally friendly subsystems, which rules out hypotheses including distinguishable photons and thermal states. We show that our GBS experiment passes a nonclassicality test based on inequality constraints, and we reveal nontrivial genuine high-order correlations in the GBS samples, which are evidence of robustness against possible classical simulation schemes. This photonic quantum computer, Jiuzhang 2.0, yields a Hilbert space dimension up to ∼ 1043, and a sampling rate ∼ 1024 faster than using brute-force simulation on classical supercomputers.
A
bstract
We investigate which 4-derivative extensions of Einstein-Maxwell theory admit multi-extremal black hole solutions with gravitational force balanced by Coulomb force. We obtain a set of ...constraints on the 4-derivative couplings by exploring various probe limits in multi-black hole systems. It turns out that these constraints are tighter than those needed to protect the mass-charge ratio of extremal black holes from higher derivative corrections. In fact, they are so strong that the Majumdar-Papapetrou multi-black solutions are unmodified by the force-free combinations of the 4-derivative couplings. Explicit examples of such 4-derivative couplings are given in 4-and 5-spacetime dimensions. Interestingly these include curvature-squared supergravity actions and the quasi-topological
F
4
term.
Neurotransmitters are conventionally viewed as nerve-secreted substances that mediate the stimulatory or inhibitory neuronal functions through binding to their respective receptors. In the past ...decades, many novel discoveries come to light elucidating the regulatory roles of neurotransmitters in the physiological and pathological functions of tissues and organs. Notably, emerging data suggest that cancer cells take advantage of the neurotransmitters-initiated signaling pathway to activate uncontrolled proliferation and dissemination. In addition, neurotransmitters can affect immune cells and endothelial cells in the tumor microenvironment to promote tumor progression. Therefore, a better understanding of the mechanisms underlying neurotransmitter function in tumorigenesis, angiogenesis, and inflammation is expected to enable the development of the next generation of antitumor therapies. Here, we summarize the recent important studies on the different neurotransmitters, their respective receptors, target cells, as well as pro/antitumor activity of specific neurotransmitter/receptor axis in cancers and provide perspectives and insights regarding the rationales and strategies of targeting neurotransmitter system to cancer treatment.
Branched-chain amino acid (BCAA) metabolism is potentially linked with development of pancreatic ductal adenocarcinoma (PDAC)
. BCAA transaminase 2 (BCAT2) was essential for the collateral lethality ...conferred by deletion of malic enzymes in PDAC and the BCAA-BCAT metabolic pathway contributed to non-small-cell lung carcinomas (NSCLCs) other than PDAC
. However, the underlying mechanism remains undefined. Here we reveal that BCAT2 is elevated in mouse models and in human PDAC. Furthermore, pancreatic tissue-specific knockout of Bcat2 impedes progression of pancreatic intraepithelial neoplasia (PanIN) in LSL-Kras
; Pdx1-Cre (KC) mice. Functionally, BCAT2 enhances BCAA uptake to sustain BCAA catabolism and mitochondrial respiration. Notably, BCAA enhances growth of pancreatic ductal organoids from KC mice in a dose-dependent manner, whereas addition of branched-chain α-keto acid (BCKA) and nucleobases rescues growth of KC organoids that is suppressed by BCAT2 inhibitor. Moreover, KRAS stabilizes BCAT2, which is mediated by spleen tyrosine kinase (SYK) and E3 ligase tripartite-motif-containing protein 21 (TRIM21). In addition, BCAT2 inhibitor ameliorates PanIN formation in KC mice. Of note, a lower-BCAA diet also impedes PDAC development in mouse models of PDAC. Thus, BCAT2-mediated BCAA catabolism is critical for development of PDAC harbouring KRAS mutations. Targeting BCAT2 or lowering dietary BCAA may have translational significance.
Electroencephalogram (EEG) data are often contaminated by various electrophysiological artifacts. Among all these artifacts, the muscle activity is particularly difficult to remove. In the ...literature, independent component analysis (ICA) and canonical correlation analysis (CCA), as blind source separation techniques, are the most popular methods. In this paper, we introduce a novel method for removing muscle artifacts in EEG data based on independent vector analysis. This method exploits both the second-order and higher order statistical information and thus takes advantage of both ICA and CCA. The proposed method is evaluated on realistic simulated data and is shown to significantly outperform ICA and CCA. In addition, the proposed method is applied on real ictal EEG data seriously contaminated with muscle artifacts. The proposed method is able to largely suppress muscle artifacts without altering the underlying EEG activity.
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