Abstract
Photoelectrochemical cells are emerging as powerful tools for organic synthesis. However, they have rarely been explored for C–H halogenation to produce organic halides of industrial and ...medicinal importance. Here we report a photoelectrocatalytic strategy for C–H halogenation using an oxygen-vacancy-rich TiO
2
photoanode with NaX (X=Cl
−
, Br
−
, I
−
). Under illumination, the photogenerated holes in TiO
2
oxidize the halide ions to corresponding radicals or X
2
, which then react with the substrates to yield organic halides. The PEC C–H halogenation strategy exhibits broad substrate scope, including arenes, heteroarenes, nonpolar cycloalkanes, and aliphatic hydrocarbons. Experimental and theoretical data reveal that the oxygen vacancy on TiO
2
facilitates the photo-induced carriers separation efficiency and more importantly, promotes halide ions adsorption with intermediary strength and hence increases the activity. Moreover, we designed a self-powered PEC system and directly utilised seawater as both the electrolyte and chloride ions source, attaining chlorocyclohexane productivity of 412 µmol h
−1
coupled with H
2
productivity of 9.2 mL h
−1
, thus achieving a promising way to use solar for upcycling halogen in ocean resource into valuable organic halides.
Cardiovascular disease (CVD) and environmental degradation are leading global health problems of our time. Recent studies have linked exposure to heavy metals to the risks of CVD and diabetes, ...particularly in populations from low- and middle-income countries, where concomitant rapid development occurs. In this review, we 1) assessed the totality, quantity, and consistency of the available epidemiological studies, linking heavy metal exposures to the risk of CVD (including stroke and coronary heart disease); 2) discussed the potential biological mechanisms underlying some tantalizing observations in humans; and 3) identified gaps in our knowledge base that must be investigated in future work. An accumulating body of evidence from both experimental and observational studies implicates exposure to heavy metals, in a dose-response manner, in the increased risk of CVD. The limitations of most existing studies include insufficient statistical power, lack of comprehensive assessment of exposure, and cross-sectional design. Given the widespread exposure to heavy metals, an urgent need has emerged to investigate these putative associations of environmental exposures, either independently or jointly, with incident CVD outcomes prospectively in well-characterized cohorts of diverse populations, and to determine potential strategies to prevent and control the impacts of heavy metal exposure on the cardiometabolic health outcomes of individuals and populations.
The precise and large-scale identification of intact glycopeptides is a critical step in glycoproteomics. Owing to the complexity of glycosylation, the current overall throughput, data quality and ...accessibility of intact glycopeptide identification lack behind those in routine proteomic analyses. Here, we propose a workflow for the precise high-throughput identification of intact N-glycopeptides at the proteome scale using stepped-energy fragmentation and a dedicated search engine. pGlyco 2.0 conducts comprehensive quality control including false discovery rate evaluation at all three levels of matches to glycans, peptides and glycopeptides, improving the current level of accuracy of intact glycopeptide identification. The N-glycoproteome of samples metabolically labeled with
N/
C were analyzed quantitatively and utilized to validate the glycopeptide identification, which could be used as a novel benchmark pipeline to compare different search engines. Finally, we report a large-scale glycoproteome dataset consisting of 10,009 distinct site-specific N-glycans on 1988 glycosylation sites from 955 glycoproteins in five mouse tissues.Protein glycosylation is a heterogeneous post-translational modification that generates greater proteomic diversity that is difficult to analyze. Here the authors describe pGlyco 2.0, a workflow for the precise one step identification of intact N-glycopeptides at the proteome scale.
We describe pLink 2, a search engine with higher speed and reliability for proteome-scale identification of cross-linked peptides. With a two-stage open search strategy facilitated by fragment ...indexing, pLink 2 is ~40 times faster than pLink 1 and 3~10 times faster than Kojak. Furthermore, using simulated datasets, synthetic datasets,
N metabolically labeled datasets, and entrapment databases, four analysis methods were designed to evaluate the credibility of ten state-of-the-art search engines. This systematic evaluation shows that pLink 2 outperforms these methods in precision and sensitivity, especially at proteome scales. Lastly, re-analysis of four published proteome-scale cross-linking datasets with pLink 2 required only a fraction of the time used by pLink 1, with up to 27% more cross-linked residue pairs identified. pLink 2 is therefore an efficient and reliable tool for cross-linking mass spectrometry analysis, and the systematic evaluation methods described here will be useful for future software development.
Great advances have been made in mass spectrometric data interpretation for intact glycopeptide analysis. However, accurate identification of intact glycopeptides and modified saccharide units at the ...site-specific level and with fast speed remains challenging. Here, we present a glycan-first glycopeptide search engine, pGlyco3, to comprehensively analyze intact N- and O-glycopeptides, including glycopeptides with modified saccharide units. A glycan ion-indexing algorithm developed for glycan-first search makes pGlyco3 5-40 times faster than other glycoproteomic search engines without decreasing accuracy or sensitivity. By combining electron-based dissociation spectra, pGlyco3 integrates a dynamic programming-based algorithm termed pGlycoSite for site-specific glycan localization. Our evaluation shows that the site-specific glycan localization probabilities estimated by pGlycoSite are suitable to localize site-specific glycans. With pGlyco3, we confidently identified N-glycopeptides and O-mannose glycopeptides that were extensively modified by ammonia adducts in yeast samples. The freely available pGlyco3 is an accurate and flexible tool that can be used to identify glycopeptides and modified saccharide units.
Abstract
Background
Adding radiotherapy (RT) to systemic therapy improves progression-free survival (PFS) and overall survival (OS) in oligometastatic non-small cell lung cancer (NSCLC). Whether ...these findings translate to epidermal growth factor receptor (EGFR)–mutated NSCLC remains unknown. The SINDAS trial (NCT02893332) evaluated first-line tyrosine kinase inhibitor (TKI) therapy for EGFR-mutated synchronous oligometastatic NSCLC and randomized to upfront RT vs no RT; we now report the prespecified interim analysis at 68% accrual.
Methods
Inclusion criteria were biopsy-proven EGFR-mutated adenocarcinoma (per amplification refractory mutation system or next generation sequencing), with synchronous (newly diagnosed, treatment naïve) oligometastatic (≤5 metastases; ≤2 lesions in any one organ) NSCLC without brain metastases. All patients received a first-generation TKI (gefitinib, erlotinib, or icotinib), and randomization was between no RT vs RT (25-40 Gy in 5 fractions depending on tumor size and location) to all metastases and the primary tumor/involved regional lymphatics. The primary endpoint (intention to treat) was PFS. Secondary endpoints included OS and toxicities. All statistical tests were 2-sided.
Results
A total of 133 patients (n = 65 TKI only, n = 68 TKI with RT) were enrolled (2016-2019). The median follow-up was 23.6 months. The respective median PFS was 12.5 months vs 20.2 months (P < .001), and the median OS was 17.4 months vs 25.5 months (P < .001) for TKI only vs TKI with RT. Treatment yielded no grade 5 events and a 6% rate of symptomatic grade 3-4 pneumonitis in the TKI with RT arm. Based on the efficacy results of this prespecified interim analysis, the ethics committee recommended premature cessation of this trial.
Conclusions
As compared with a first-line TKI alone, addition of upfront local therapy using RT statistically significantly improved PFS and OS for EGFR-mutated NSCLC.
Most marine macroalgae such as red seaweeds are potential alternative sources of useful bioactive compounds. Beside serving as food source, recent studies have shown that red seaweeds are rich ...sources of bioactive polysaccharides. Red seaweed polysaccharides (RSPs) have various physiological and biological activities, which allow them to be used as immunomodulators, anti-obesity agents, and prebiotic ingredients. Lack of summary information and human clinical trials on the various polysaccharides from red seaweeds, however limits industrial-scale utilization of RSPs in functional foods. This review summarizes recent information on the approaches used for RSPs extraction and purification, mechanistic investigations of their biological activities, and related molecular principles behind their purported ability to prevent diseases. The information here also provides a theoretical foundation for further research into the structure and mechanism of action of RSPs and their potential applications in functional foods.
•Advancements in red seaweed polysaccharides extraction, purification, are summarized.•Red seaweed polysaccharides have various impressive biological activities.•Red seaweed polysaccharides are carbohydrates with potential of functional foods.•The structure and mechanism of action of red seaweed polysaccharides are discussed.
•Synergistic effects of magnetic field and hybrid nanoparticles on TES is experimentally investigated.•Thermochromic liquid crystal is used to extract dynamic phase change interface ...evolution.•Magnetic nanoparticles form a “thermal conductivity layer” at solid-liquid interface.•Non-Newtonian effect induced by high concentration of HNEPCM weaken convection intensity.•High hybrid ratios are more favorable to dynamic adjustment condition at interface.
The present study aims to explore the synergistic enhanced phase change heat transfer behavior between magnetic field and hybrid nanoparticles under the consideration of non-Newtonian effects. The visualized experiments are conducted using thermochromic liquid crystal technology to extract the interconnection between dynamic phase change interface evolution and temperature change of hybrid nano-enhanced phase change material (HNEPCM), and thermocouples to measure temperature data inside the latent heat thermal energy storage unit. The magnetic field and hybrid nanoparticles synergistic mechanism is then further revealed based on the analysis of liquid phase fraction, Nusselt number, energy storage and energy storage efficiency. The results show that under magnetic field, the magnetic nanoparticles form a “thermal conductivity layer” at the solid-liquid interface, while the non-magnetic nanoparticles in the liquid phase region drive the phase change heat transfer to proceed. The non-Newtonian effect induced by high concentration of HNEPCM can weaken the convection intensity. The competition between natural convection and magnetic viscous effect under magnetic field is induced at different hybrid ratios of magnetic and non-magnetic nanoparticles. High hybrid ratios (R = 1.0, 1.5 and 2.0) will be more favorable to satisfy the high thermal conductivity requirement in the liquid phase region and the dynamic adjustment condition at the phase change interface. Under a non-uniform magnetic field, 1 wt.% HNEPCM with R = 1.0 is considered as the optimum strategy with better energy storage performance and higher magnetic field effect.
In tandem mass spectrometry (MS/MS)-based proteomics, search engines rely on comparison between an experimental MS/MS spectrum and the theoretical spectra of the candidate peptides. Hence, accurate ...prediction of the theoretical spectra of peptides appears to be particularly important. Here, we present pDeep, a deep neural network-based model for the spectrum prediction of peptides. Using the bidirectional long short-term memory (BiLSTM), pDeep can predict higher-energy collisional dissociation, electron-transfer dissociation, and electron-transfer and higher-energy collision dissociation MS/MS spectra of peptides with >0.9 median Pearson correlation coefficients. Further, we showed that intermediate layer of the neural network could reveal physicochemical properties of amino acids, for example the similarities of fragmentation behaviors between amino acids. We also showed the potential of pDeep to distinguish extremely similar peptides (peptides that contain isobaric amino acids, for example, GG = N, AG = Q, or even I = L), which were very difficult to distinguish using traditional search engines.
We present a sequence-tag-based search engine, Open-pFind, to identify peptides in an ultra-large search space that includes coeluting peptides, unexpected modifications and digestions. Our method ...detects peptides with higher precision and speed than seven other search engines. Open-pFind identified 70-85% of the tandem mass spectra in four large-scale datasets and 14,064 proteins, each supported by at least two protein-unique peptides, in a human proteome dataset.
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