Drug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. The fast-growing number of anti-cancer drugs has caused the ...experimental investigation of all drug combinations to become costly and time-consuming. Computational techniques can improve the efficiency of drug combination screening. Despite recent advances in applying machine learning to synergistic drug combination prediction, several challenges remain. First, the performance of existing methods is suboptimal. There is still much space for improvement. Second, biological knowledge has not been fully incorporated into the model. Finally, many models are lack interpretability, limiting their clinical applications. To address these challenges, we have developed a knowledge-enabled and self-attention transformer boosted deep learning model, TranSynergy, which improves the performance and interpretability of synergistic drug combination prediction. TranSynergy is designed so that the cellular effect of drug actions can be explicitly modeled through cell-line gene dependency, gene-gene interaction, and genome-wide drug-target interaction. A novel Shapley Additive Gene Set Enrichment Analysis (SA-GSEA) method has been developed to deconvolute genes that contribute to the synergistic drug combination and improve model interpretability. Extensive benchmark studies demonstrate that TranSynergy outperforms the state-of-the-art method, suggesting the potential of mechanism-driven machine learning. Novel pathways that are associated with the synergistic combinations are revealed and supported by experimental evidences. They may provide new insights into identifying biomarkers for precision medicine and discovering new anti-cancer therapies. Several new synergistic drug combinations have been predicted with high confidence for ovarian cancer which has few treatment options. The code is available at https://github.com/qiaoliuhub/drug_combination.
This paper focuses on a two-echelon supply chain consisting of a seller and a buyer. Considering the case where the buyer faces uncertain demand and yield, the paper investigates the buyback contract ...for the supply chain and studies how the yield uncertainty and the relative bargaining power affect the performance of buyback contract. The results suggest that when the seller's bargaining power is relatively high and can control the uncertain yield, the buyback contract is sufficient to coordinate the supply chain. Conversely, when the seller's bargaining power is relatively low or cannot guarantee yield stability, the buyback contract does not work. To coordinate such a supply chain, a combined contract named Buy-Back-Revenue-Sharing contract is proposed. Furthermore, this paper presents the optimal orders to maximize the profits of the buyer and the whole supply chain and it finds that if the seller cannot control the yield, the buyer will place fewer orders and both parties will gain lower profit with supply chain coordination.
The formation of the Himalaya was associated with the exhumation of high-grade metamorphosed rocks of the Higher Himalayan sequence (HHS) complex, which underwent amphibolite-, granulite- to ...eclogite-facies metamorphism and anatexis. Occurring along the Himalayan mountain crest in the south and the Lhagoi Kangri mountain in the north, the Himalayan leucogranites contain varying proportions of biotite (<5%), muscovite, tourmaline, and garnet, and are typically equigranular in texture with variable structures from foliated to massive. These peraluminous granites have been interpreted as purely crust-derived melts, without any input from the mantle, and may therefore record the timing of continental collision. However, they were emplaced between 44 and 7 Ma, much later than the timing of collision between India and Asia (c. 60 Ma). Although typically interpreted as products of in situ partial melting of the HHS during subduction and exhumation, we suggest that the Himalayan leucogranites underwent intense crystal fractionation, as recorded by crystal layering, sedimentary-like cross-bedding, and the occurrence of pegmatites with varying grain sizes. Geochemically, these leucogranites are low in siderophile but high in lithophile elements, with significant negative europium (Eu) anomalies, non-chondritic Nb/Ta and Zr/Hf ratios, and rare earth element (REE) tetrad effects. Many of the leucogranites and pegmatites contain rare-metal minerals, such as beryl and chrysoberyl; columbite–tantalite, tapiolite, and pyrochlore–microlite; rutile and fergusonite; and zinnwaldite, lepidolite, spodumene, and petalite, supporting an origin involving a high degree of magmatic fractionation. We suggest that the primary magma was generated through partial melting of subducted Indian crust due to input of heat from depth. The generation of magma triggered the exhumation of the Indian crust and subsequent formation of the Himalayan mountain chain. The magma ascended with the Indian crust along the South Tibetan Detachment System (STDS), during which time it underwent significant fractionation. Anatectic melts generated from exhumed Indian crust through decompression melting are distinct from the leucogranites, indicating that exhumation of the Indian crust had a limited contribution to the generation and evolution of the leucogranites. Extensional faulting facilitated a high degree of magma fractionation and rare-metal mineralization.
•Leucogranites are widely distributed in the Himalayan mountains.•These rocks are peraluminous, and were considered as purely crustal derived.•They were not an in-situ melt, but formed by intensive magma fractionation.•Rare-metal mineralization is documented in these rocks and associated pegmatites.
Proteolysis-targeting chimeras (PROTACs) are hetero-bifunctional molecules that induce the degradation of target proteins by recruiting an E3 ligase. PROTACs have the potential to inactivate ...disease-related genes that are considered undruggable by small molecules, making them a promising therapy for the treatment of incurable diseases. However, only a few hundred proteins have been experimentally tested for their amenability to PROTACs, and it remains unclear which other proteins in the entire human genome can be targeted by PROTACs. In this study, we have developed PrePROTAC, an interpretable machine learning model based on a transformer-based protein sequence descriptor and random forest classification. PrePROTAC predicts genome-wide targets that can be degraded by CRBN, one of the E3 ligases. In the benchmark studies, PrePROTAC achieved a ROC-AUC of 0.81, an average precision of 0.84, and over 40% sensitivity at a false positive rate of 0.05. When evaluated by an external test set which comprised proteins from different structural folds than those in the training set, the performance of PrePROTAC did not drop significantly, indicating its generalizability. Furthermore, we developed an embedding SHapley Additive exPlanations (eSHAP) method, which extends conventional SHAP analysis for original features to an embedding space through in silico mutagenesis. This method allowed us to identify key residues in the protein structure that play critical roles in PROTAC activity. The identified key residues were consistent with existing knowledge. Using PrePROTAC, we identified over 600 novel understudied proteins that are potentially degradable by CRBN and proposed PROTAC compounds for three novel drug targets associated with Alzheimer’s disease.
The Nanyangshan Li-Cs-Ta (LCT) pegmatite is the largest of hundreds of pegmatite dikes in the eastern Qinling orogenic district, North China. The Nanyangshan pegmatite is strongly zoned into a ...contact zone, border zone, wall zone, intermediate zone, and core, with Li mineralization occurring predominantly in the intermediate zone. Inward through the intermediate zone, Li mineralization is divided into subzones of Spd (spodumene), Mbs (montebrasite), Elb (elbaite), and Lpd (lepidolite). Lithium minerals include spodumene, montebrasite, lithiophilite, elbaite, lepidolite, and possible former petalite. Paragenetic assemblages of Li minerals are variable, with spodumene ± Li-phosphates (montebrasite and lithiophilite), Fe-rich elbaite, lepidolite, and possible former petalite in the Spd subzone; Li-phosphates (main montebrasite and rare lithiophilite) + spodumene + Fe-bearing elbaite + lepidolite in the Mbs subzone; Fe-poor elbaite + lepidolite ± montebrasite in the Elb subzone; and lepidolite ± Fe-poor elbaite in the Lpd subzone. Whole-rock contents of Li2O, P2O5, B2O3, and F are consistent with the high contents of various Li minerals. Spodumene was formed first and dominantly from a Li-saturated melt in the Spd subzone (1.66 wt% Li2O). This subzone graduates into the P-rich Mbs subzone (3.75 wt% P2O5) with montebrasite gradually succeeding Li-aluminosilicates, followed by the appearance of abundant Fe-poor elbaite in the Elb subzone (1.04 wt% B2O3), reflecting the consumption of P in the melt. Lepidolite formed after early-formed Li phases in the F-rich Lpd subzone (2.03 wt% F), as indicated by replacement textures. Among the numerous LCT pegmatites worldwide, the Li mineralization sequence can be suggested as Li-aluminosilicates (commonly spodumene and less commonly petalite) → Li-phosphates (montebrasite-amblygonite and triphylite-lithiophilite) → elbaite → lepidolite, and can be regarded as a general sequence for Li mineralization.
Beryllium is a critical metal typically concentrated in highly fractionated granitic rocks such as the leucogranites in the Himalaya. Here, we report beryl mineralization that was continuous from the ...earlier and less-evolved two-mica granite to the highly evolved albite granite and pegmatite in a typical leucogranite pluton at Pusila in the central of Himalaya. Textural and mineral chemical evidence support a magmatic origin for beryl, and the trends of beryl crystal chemistry indicate magma differentiation. Despite low to moderate fractionation of the biotite granite and two-mica granite in the Pusila leucogranite pluton, the Be contents (∼7 µg/g, beryl-free and ∼22 µg/g, beryl-bearing, respectively) of these granites are much higher than the average for biotite- and two-mica granites worldwide (∼3-4 and 5-10 µg/g, respectively), indicating that the initial magma had a relatively high-Be concentration. The gneisses of Greater Himalayan System, considered the protolith, also show a higher Be abundance (∼4-6 µg/g) than the mean value of pelitic rocks worldwide (∼2-3 µg/g), which could be the source reservoir of Be. The source contributed the initial Be to the melt, and fractionation resulted in the onset of beryl crystallization from the interstitial residual melt in the two-mica granite. The ubiquity of beryl in two-mica granite to pegmatite stages of the Pusila pluton is explained by a continuous crystallization model, although there was a delay in the onset of beryl crystallization in the two-mica granite. Modeling based on Rayleigh fractionation indicates that Be becomes compatible once saturation is attained because of the beryl crystallization. Our findings indicate that the enrichment of critical elements (e.g., Be) is controlled not only by fractional crystallization but also by the buffering action of a saturating phase (e.g., beryl) on the concentration of the critical element in the melt.
Based on the sharing economy, crowdsourcing logistics services share social delivery freelancers instead of traditional full-time delivery employees. The optimal dynamic pricing model of ...crowdsourcing logistics services, which could be applied to adjust the social delivery capacity supply to meet the stochastic demand especially during the peak period, is established based on optimal control theory. We study optimal pricing strategies under both conditions when the supply and the demand is balanced and accumulated delivery orders are minimized. Moreover, the impact of delivery riders’ wage ratio on pricing and platforms’ expected revenue are analyzed. It is verified by numerical simulation results that optimal dynamic pricing strategies of crowdsourcing logistics services could effectively balance supply and demand, further maximize the expected revenue of platforms. The growth rate of optimal pricing of crowdsourcing logistics services is increasing with respect to the delivery riders’ wage ratio. However, the expected revenue of crowdsourcing logistics platforms declines as the wage ratio increases.
The Himalayan leucogranite occurs as two extensive（〉1000 km） E-W trending belts on the Tibetan Plateau with the unique features. The leucogranite comprised biotite granite, two-mica/muscovite ...granite, tourmaline granite and garnet granite, which have been identified in previous studies, as well as albite granite and granitic pegmatite that were identified in this investigation. Fifteen leucogranite plutons were studied and 12 were found to contain rare-metal bearing minerals such as beryl（the representative of Be mineralization）, columbite-group minerals, tapiolite, pyrochlore-microlite, fergusonite, Nb-Ta rutile（the representative of Nb-Ta mineralization）, and cassiterite（the representative of Sn mineralization） mainly based on the field trip,microscope observation and microprobe analysis. The preliminary result shows that the Himalayan leucogranite is commonly related to the rare-metal mineralization and warrants future investigation. Further exploration and intensive research work is important in determining the rare-metal resource potential of this area.
Colloidal nanoparticles with anisotropic architectures have attracted a variety of interest and attention due to different physical and chemical properties compared with the isotropic counterparts, ...making them promising candidates in many fundamental studies and practical applications. Particularly, carbon and silica-based anisotropic nanoparticles can be one stand out by combing both intrinsic merits of carbons and silica, such as structural stability, biocompatibility, large surface area, and ease of functionalization with the anisotropic structural complexity. In this review, we aim to provide an updated summary of the research related to the anisotropic carbon and silica-based nanostructures, covering both their synthesis and applications.
Applied energy principle analysis natural frequency equations of Euler beam and Timoshenko respectively. The expression of natural frequency is calculated by the separation of variables. Consider the ...natural frequency ratio between the Euler beam and Timoshenko one to analyze the relationship between geometric parameters and frequency ratio that effect by parameters of frequency. Calculations show that the relationship between frequency ratio and geometric parameters present non-linear parabola characteristic. When the increment of geometric parameters is identical, the frequency value of the beam was lowered by both transverse shear effect and rotary inertia whereby non-linear characteristics are mainly determined by the transverse shear effect.
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