384 Search Results

Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%–20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.

Spatial confinement of electronic topological surface states (TSSs) in topological insulators poses a formidable challenge because TSSs are protected by time-reversal symmetry. In previous works formation of a gap in the electronic spectrum of TSSs has been successfully demonstrated in topological insulator/magnetic material heterostructures, where ferromagnetic exchange interactions locally lift the time-reversal symmetry. Here we report experimental evidence of exchange interaction between a topological insulator $$\mathrm{Bi_2}$$ $$\mathrm{Se_3}$$ and a magnetic insulator EuSe. Spin-polarized neutron reflectometry reveals a reduction of the in-plane magnetic susceptibility within a 2 nm interfacial layer of EuSe, and the combination of superconducting quantum interference device (SQUID) magnetometry and Hall measurements points to the formation of an interfacial layer with a suppressed net magnetic moment. This suppressed magnetization survives up to temperatures five times higher than the Néel temperature of EuSe. Its origin is attributed to the formation of an interfacial antiferromagnetic state. Abrupt resistance changes observed in high magnetic fields are consistent with antiferromagnetic domain reconstruction affecting transport in a TSS via exchange coupling. Importantly, the high-temperature local control of TSSs with zero net magnetization unlocks new opportunities for the design of electronic, spintronic, and quantum computation devices, ranging from quantization of Hall conductance in zero fields to spatial localization of non-Abelian excitations in superconducting topological qubits.

Objective This study examined the moderating effect of overall social support and the different types of social support on cognitive functioning in depressed older adults. We also investigated whether the moderating effect varied according to age. Methods A total of 2,500 older adults (≥60 years old) from Shanghai, China were enrolled using a multistage cluster sampling method. Weighted linear regression and multiple linear regression was utilized to analyze the moderating effect of social support on the relationship between depressive symptoms and cognitive function and to explore its differences in those aged 60–69, 70–79, and 80 years and above. Results After adjusting for covariates, the results indicated that overall social support (β = 0.091, p  = 0.043) and support utilization (β = 0.213, p  < 0.001) moderated the relationship between depressive symptoms and cognitive function. Support utilization reduced the possibility of the cognitive decline in depressed older adults aged 60–69 years (β = 0.310, p   < 0.001) and 80 years and above (β = 0.199, p   < 0.001), while objective support increased the possibility of cognitive decline in depressed older people aged 70–79 years (β = −0.189, p   < 0.001). Conclusion Our findings highlight the buffering effects of support utilization on cognitive decline in depressed older adults. We suggest that age-specific measures should be taken when providing social support to depressed older adults in order to reduce the deterioration of cognitive function.

According to industry estimates, approximately 7 billion day-old male chicks are disposed of annually worldwide because they are not of use to the layer industry. A practical process to identify the sex of the egg early in incubation without penetrating the egg would improve animal welfare, reduce food waste and mitigate environmental impact. We implemented a moderate vacuum pressure system through commercial egg-handling suction cups to collect volatile organic compounds (VOCs). Three separate experiments were set up to determine optimal conditions to collect eggs VOCs to discriminate male from female embryos. Optimal extraction time (2 min), storage conditions (short period of incubation during egg storage (SPIDES) at days 8–10 of incubation), and sampling temperature (37.5°C) were determined. Our VOC-based method could correctly differentiate male from female embryos with more than 80% accuracy. These specifications are compatible with the design of specialized automation equipment capable of high-throughput, in-ovo sexing based on chemical sensor microchips.

CdO has been shown to achieve a high electron concentration N (> 10²¹cm^-3) and at the same time a high mobility μ (> 100cm²/V s) when doped with conventional shallow dopants (In or Ga), and consequently making it a transparent conducting oxide with very low resistivity ρ <10^-4 $$\Omega$$ cm. In this work, the properties of CdO thin films doped with a series of transition metal elements (CdO:TM) with partially filled 3d and 4d shells, including Sc, Ti, V, Cr, Fe, Y, Mo, and W, were investigated. We find that doping with these TM elements can effectively increase the N in CdO to a maximum N (N_max) of ~(7-12)×10²⁰cm^-3 with a dopant concentration x_max of 4-7 %. However, unlike CdO:In, the μ of CdO:TM films drops rapidly from > 100 to < 10cm²/Vs as the dopant concentration x increases, so that they can only achieve a minimum ρ of ~ (1-2) × 10^-4 $$\Omega$$ cm, ~ a factor of 2-3 higher than that in CdO:In. As a result, free-carrier absorption and plasma reflection effects limit their optical transparency to <1200 nm. For most 3d TM dopants, a qualitatively higher d-donor level E_d,donor gives rise to higher E_F,max or a higher N_max. Although at low x, the optical band gap E_opt of CdO:TM follows the calculated values due to free-carrier effects, as x increases, E_opt values are significantly higher than the calculated values. This is believed to be an effect of the anticrossing interaction of the localized d-levels and the extended CdO conduction-band (CB) states, giving rise to a lower occupied E_- and an upper unoccupied E₊ subband. In conclusion, the restructured CBs have much flatter dispersion, which also results in a much higher effective mass $$m^{\star}_{e}$$, hence it can also explain the much lower μ of CdO:TM films with high N.

Abstract Kohn–Sham density functional theory is widely used in chemistry, but no functional can accurately predict the whole range of chemical properties, although recent progress by some doubly hybrid functionals comes close. Here, we optimized a singly hybrid functional called CF22D with higher across-the-board accuracy for chemistry than most of the existing non-doubly hybrid functionals by using a flexible functional form that combines a global hybrid meta-nonseparable gradient approximation that depends on density and occupied orbitals with a damped dispersion term that depends on geometry. We optimized this energy functional by using a large database and performance-triggered iterative supervised training. We combined several databases to create a very large, combined database whose use demonstrated the good performance of CF22D on barrier heights, isomerization energies, thermochemistry, noncovalent interactions, radical and nonradical chemistry, small and large systems, simple and complex systems and transition-metal chemistry.

Background Akkermansia muciniphila is a member of the gut microbiome, using mucin as sources of carbon, nitrogen, and energy. Since the first discovery of this unique bacterium in 2004, A. muciniphila has been extensively studied. It is considered a promising “next-generation beneficial microbe.” The purpose of this paper is to sort out the research status and summarize the hotspots through bibliometric analysis of the publications of A. muciniphila. Methods The publications about A. muciniphila from January 2004 to February 2022 were obtained from the Web of Science Core Collection. Visualization analyses were performed using three bibliometric tools and GraphPad Prism. Results A total of 1,478 published documents were analyzed. Annual publication number grew from 1 in 2004 to 336 in 2021, with China being the leading producer (33.36%). De Vos, Willem M was the most productive author with the highest H-index (documents = 56, H-index = 37), followed by Cani, Patrice D (documents = 35, H-index = 25). And Scientific Reports published the most papers. PNAS was the keystone taxa in this field, with high betweenness centrality (0.11) and high frequency. The keywords with high frequency in recent years include: oxidative stress, diet, metformin, fecal microbiota transplantation, short-chain fatty acids, polyphenols, microbiota metabolites and so on. The keyword “oxidative stress” was observed to be increasing in frequency recently. Conclusion Over time, the scope of the research on the clinical uses of A. muciniphila has gradually increased, and was gradually deepened and developed toward a more precise level. A. muciniphila is likely to remain a research hotspot in the foreseeable future and may contribute to human health.

Plate-based proteomic sample preparation offers a solution to the large sample throughput demands in the biotechnology field where hundreds or thousands of engineered microbes are constructed for testing is routine. Meanwhile, sample preparation methods that work efficiently on broader microbial groups are desirable for new applications of proteomics in other fields, such as microbial communities. Here, we detail a step-by-step protocol that consists of cell lysis in an alkaline chemical buffer (NaOH/SDS) followed by protein precipitation with high-ionic strength acetone in 96-well format. The protocol works for a broad range of microbes e.g., Gram-negative bacteria, Gram-positive bacteria, non-filamentous fungi) and the resulting proteins are ready for tryptic digestion for bottom-up quantitative proteomic analysis without the need for desalting column cleanup. The yield of protein using this protocol increases linearly with respect to the amount of starting biomass from 0.5–2.0 OD*mL of cells. By using a bench-top automated liquid dispenser, a cost-effective and environmentally-friendly option to eliminating pipette tips and reducing reagent waste, the protocol takes approximately 30 minutes to extract protein from 96 samples. Tests on mock mixtures showed expected results that the biomass composition structure is in close agreement with the experimental design. Lastly, we applied the protocol for the composition analysis of a synthetic community of environmental isolates grown on two different media. This protocol has been developed to facilitate rapid, low-variance sample preparation of hundreds of samples and allow flexibility for future protocol development.

We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological slides from 657 patients across 6 cancer types from CPTAC. Our models effectively recapitulate distinctions readily made by human pathologists: tumor vs. normal (AUROC = 0.995) and tissue-of-origin (AUROC = 0.979). We further investigate predictive power on tasks not normally performed from H&E alone, including TP53 prediction and pathologic stage. Importantly, we describe predictive morphologies not previously utilized in a clinical setting. The incorporation of transcriptomics and proteomics identifies pathway-level signatures and cellular processes driving predictive histology features. Model generalizability and interpretability is confirmed using TCGA. We propose a classification system for these tasks, and suggest potential clinical applications for this integrated human and machine learning approach. A publicly available web-based platform implements these models.

Abstract Inhibins are transforming growth factor-β family heterodimers that suppress follicle-stimulating hormone (FSH) secretion by antagonizing activin class ligands. Inhibins share a common β chain with activin ligands. Follistatin is another activin antagonist, known to bind the common β chain of both activins and inhibins. In this study, we characterized the antagonist-antagonist complex of inhibin A and follistatin to determine if their interaction impacted activin A antagonism. We isolated the inhibin A:follistatin 288 complex, showing that it forms in a 1:1 stoichiometric ratio, different from previously reported homodimeric ligand:follistatin complexes, which bind in a 1:2 ratio. Small angle X-ray scattering coupled with modeling provided a low-resolution structure of inhibin A in complex with follistatin 288. Inhibin binds follistatin via the shared activin β chain, leaving the α chain free and flexible. The inhibin A:follistatin 288 complex was also shown to bind heparin with lower affinity than follistatin 288 alone or in complex with activin A. Characterizing the inhibin A:follistatin 288 complex in an activin-responsive luciferase assay and by surface plasmon resonance indicated that the inhibitor complex readily dissociated upon binding type II receptor activin receptor type IIb, allowing both antagonists to inhibit activin signaling. Additionally, injection of the complex in ovariectomized female mice did not alter inhibin A suppression of FSH. Taken together, this study shows that while follistatin binds to inhibin A with a substochiometric ratio relative to the activin homodimer, the complex can dissociate readily, allowing both proteins to effectively antagonize activin signaling.