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LEOPARD: missing view completion for multi-timepoint omics data via representation disentanglement and temporal knowledge transfer
Abstract Longitudinal multi-view omics data offer unique insights into the temporal dynamics of individual-level physiology, which provides opportunities to advance personalized healthcare. However, the common occurrence of incomplete views makes extrapolation tasks difficult, and there is a lack of tailored methods for this critical issue. Here, we introduce LEOPARD, an innovative approach specifically designed to complete missing views in multi-timepoint omics data. By disentangling longitudinal omics data into content and temporal representations, LEOPARD transfers the temporal knowledge to the omics-specific content, thereby completing missing views. The effectiveness of LEOPARD is validated on four real-world omics datasets constructed with data from the MGH COVID study and the KORA cohort, spanning periods from 3 days to 14 years. Compared to conventional imputation methods, such as missForest, PMM, GLMM, and cGAN, LEOPARD yields the most robust results across the benchmark datasets. LEOPARD-imputed data also achieve the highest agreement with observed data in our analyses for age-associated metabolites detection, estimated glomerular filtration rate-associated proteins identification, and chronic kidney disease prediction. Our work takes the first step toward a generalized treatment of missing views in longitudinal omics data, enabling comprehensive exploration of temporal dynamics and providing valuable insights into personalized healthcare.
Analyzing the impacts of employing demand response and creating optimal coalition on optimal scheduling of multi-microgrid
Peptide-based inflammation-responsive implant coating sequentially regulates bone regeneration to enhance interfacial osseointegration
Abstract Aseptic loosening is the primary cause of bone prosthesis failure, commonly attributed to inadequate osseointegration due to coatings misaligned with bone regeneration. Here, we modify the titanium surface with a mussel-inspired peptide to form a 3,4-dihydroxyphenylalanine (DOPA)-rich coating, then graft N 3 -K15-PVGLIG-K23 (P1) and N 3 -Y5-PVGLIG-K23 (P2), which are composed of anti-inflammatory (K23), angiogenic (K15), osteogenic (Y5), and inflammation-responsive (PVGLIG) sequences, onto the surface via click chemistry, forming the DOPA-P1@P2 coating. DOPA-P1@P2 promotes bone regeneration through sequential regulation. In the initial stage, the outermost K23 induces M2 macrophage polarization, establishing a pro-regenerative immune microenvironment. Subsequently, K15 and Y5, exposed by the release of K23, enhance angiogenesis and osteogenesis. In the final stage, DOPA-P1@P2 outperforms the TiO₂ control, showing a 161% increase in maximal push-out force, a 207% increase in bone volume fraction, and a 1409% increase in bone-to-implant contact. These findings show that DOPA-P1@P2 efficiently enhances interfacial osseointegration by sequentially regulating bone regeneration, providing viable insights into coating design.
Multi objective elk herd optimization for efficient structural design
Multi-proton dynamics near membrane-water interface
Abstract Protons are crucial for biological energy transduction between membrane proteins. While experiments suggest rapid proton motion over large distances at the membrane-water interface, computational studies employing a single excess proton found the proton immobilized near the lipid headgroup. To address this discrepancy, we conduct DFTB3 simulations by incrementally adding protons up to three. We show that a single proton moves rapidly toward the nearest headgroup, where it is either repelled by a choline group or binds covalently to phosphatic oxygen. With multiple protons, while some are trapped by the lipid headgroups, the remaining proton diffuses laterally faster than in bulk water. Driven by excess energy, this proton initially jumps to the center of the water slab before relaxing into the third- and second-hydration shells. Lateral diffusion rates increase as the proton stabilizes in the second hydration shell. These results provide insights into proton dynamics near membranes and explain experimental observations.
EBG-backed ultrawideband circularly polarized Archimedean spiral antenna scheme for IoT applications
Observation of a non-Hermitian supersonic mode on a trapped-ion quantum computer
Virtual reality enhanced mindfulness and yoga intervention for postpartum depression and anxiety in the post COVID era
Primordial neon and the deep mantle origin of kimberlites
Abstract The genesis of kimberlites is unclear despite the economic and scientific interest surrounding these diamond-bearing magmas. One critical question is whether they tap ancient, deep mantle domains or the shallow convecting mantle with partial melting triggered by plumes or plate tectonics. To address this question, we report the He-Ne-Ar isotopic compositions of magmatic fluids trapped in olivine from kimberlites worldwide. The kimberlites which have been least affected by addition of deeply subducted or metasomatic components have Ne isotopes less nucleogenic than the upper mantle, hence requiring a deep-mantle origin. This is corroborated by previous evidence of small negative W isotope anomalies and kimberlite location along age-progressive hot-spot tracks. The lack of strong primordial He isotope signatures indicates overprinting by lithospheric and crustal components, which suggests that Ne isotopes are more robust tracers of deep-mantle contributions in intraplate continental magmas. The most geochemically depleted kimberlites may preserve deep remnants of early-Earth heterogeneities.
Elucidating molecular lipid perturbations in trigeminal neuralgia using cerebrospinal fluid lipidomics
Aneuploidy confers a unique transcriptional and phenotypic profile to Candida albicans
Design and evaluation of a solar powered smart irrigation system for sustainable urban agriculture
Abstract Urban areas face significant challenges, including a lack of green spaces, scarce water resources, environmental pollution, and elevated heat emissions, particularly in developing countries experiencing rapid population growth. Therefore, the study aims to advance sustainable urban agriculture by designing and evaluating a solar-powered smart rooftop irrigation system for peppermint cultivation. The system incorporates two drip irrigation setups—conventional and smart irrigation—powered by photovoltaic (PV) panels. The smart system integrates real-time monitoring of critical variables, including (1) soil moisture, (2) relative humidity, (3) PV panel temperature, and (4) PV panel current and voltage. Key performance metrics such as water and energy consumption, water use efficiency, energy productivity, and carbon dioxide emissions were evaluated for both systems. In addition, the economic analysis of the smart system was determined. Results revealed that the smart system reduced water and energy consumption by 28.1% compared to conventional irrigation. Additionally, the smart system achieved a notable reduction in carbon footprint, with CO2 emissions of 0.181 kg CO₂/m2/year compared to 0.252 kg CO₂/m2/year for the conventional system. The system’s economic analysis demonstrated a payback period of 5.6 years, highlighting its financial viability. This study underscores the transformative potential of solar-powered smart irrigation systems in enhancing food security, conserving water, reducing energy consumption, and mitigating carbon emissions in urban agriculture.
High selectivity framework polymer membranes chemically tuned towards fast anion conduction
Construction of ubiquitination-related risk model for predicting prognosis in lung adenocarcinoma
Abstract Lung adenocarcinoma is the most prevalent lung cancer type. Ubiquitination, a critical post-translational modification process that regulates protein degradation and signaling pathways, has been implicated in various cancers, including LUAD. We aimed to explore the associations between ubiquitination and lung adenocarcinoma. TCGA-LUAD cohort served as the training set. Unsupervised clustering, univariate Cox regression, Random Survival Forests, and least absolute shrinkage and selection operator (LASSO) Cox regression were applied to identify ubiquitination-related genes (URGs), then ubiquitination-related risk scores (URRS) were calculated using gene expression and the univariate Cox’s coefficient. Comparisons between the high and the low URRS group regarding chemotherapy drug response, immune infiltration level, tumor mutation burden (TMB), tumor neoantigen load (TNB), PD1/L1 expression, and enriched pathways were performed. URRS was calculated based on the expression of DTL, UBE2S, CISH, and STC1. Patients with higher URRS had a worse prognosis (Hazard Ratio [HR] = 0.54, 95% Confidence Interval [CI]: 0.39–0.73, p < 0.001), and the prognosis of the URRS was further confirmed in 6 external validation cohorts (Hazard Ratio [HR] = 0.58, 95% Confidence Interval [CI]: 0.36–0.93, pmax = 0.023). The high URRS group had higher PD1/L1 expression level (p < 0.05), TMB (p < 0.001), TNB (p < 0.001), and TME scores (p < 0.001). The IC50 values of various chemotherapy drugs were lower in the high URRS group. In addition, we found that upregulation of STC1, UBE2S, and DTL was associated with worse, while upregulation of CISH was associated with better prognosis. We also performed a reverse transcription-quantitative polymerase chain reaction (RT-qPCR) for validation. In conclusion, the ubiquitination-based signature might serve as a biomarker to help evaluate the prognosis, biological features, and appropriate treatment for patients with lung adenocarcinoma.