TARO: tree-aggregated factor regression for microbiome data integration.

MOTIVATION: Although the human microbiome plays a key role in health and disease, the biological mechanisms underlying the interaction between the microbiome and its host are incompletely understood. Integration with other molecular profiling data offers an opportunity to characterize the role of the microbiome and elucidate therapeutic targets. However, this remains challenging to the high dimensionality, compositionality, and rare features found in microbiome profiling data. These challenges necessitate the use of methods that can achieve structured sparsity in learning cross-platform association patterns. RESULTS: We propose Tree-Aggregated factor RegressiOn (TARO) for the integration of microbiome and metabolomic data. We leverage information on the taxonomic tree structure to flexibly aggregate rare features. We demonstrate through simulation studies that TARO accurately recovers a low-rank coefficient matrix and identifies relevant features. We applied TARO to microbiome and metabolomic profiles gathered from subjects being screened for colorectal cancer to understand how gut microrganisms shape intestinal metabolite abundances. AVAILABILITY AND IMPLEMENTATION: The R package TARO implementing the proposed methods is available online at https://github.com/amishra-stats/taro-package.

Axial-Equatorial Halide Ordering in Layered Hybrid Perovskites from Isotropic-Anisotropic 207 Pb NMR.

Bandgap-tuneable mixed-halide 3D perovskites are of interest for multi-junction solar cells, but suffer from photoinduced spatial halide segregation. Mixed-halide 2D perovskites are more resistant to halide segregation and are promising coatings for 3D perovskite solar cells. The properties of mixed-halide compositions depend on the local halide distribution, which is challenging to study at the level of single octahedra. In particular, it has been suggested that there is a preference for occupation of the distinct axial and equatorial halide sites in mixed-halide 2D perovskites. 207 Pb NMR can be used to probe the atomic-scale structure of lead-halide materials, but although the isotropic 207 Pb shift is sensitive to halide stoichiometry, it cannot distinguish configurational isomers. Here, we use 2D isotropic-anisotropic correlation 207 Pb NMR and relativistic DFT calculations to distinguish the [PbX6 ] configurations in mixed iodide-bromide 3D FAPb(Br1-x Ix )3 perovskites and 2D BA2 Pb(Br1-x Ix )4 perovskites based on formamidinium (FA+ ) and butylammonium (BA+ ), respectively. We find that iodide preferentially occupies the axial site in BA-based 2D perovskites, which may explain the suppressed halide mobility.

Hydrogen Diffusion in Hybrid Perovskites from Exchange NMR.

Ion migration is an important phenomenon affecting the performance of hybrid perovskite solar cells. It is particularly challenging, however, to disentangle the contribution of H+ diffusion from that of other ions, and the atomic-scale mechanism remains unclear. Here, we use 2H exchange NMR to prove that 2H+ ions exchange between MA+ cations on the time scale of seconds for both MAPbI3 and FA0.7MA0.3PbI3 perovskites. We do this by exploiting 15N-enriched MA+ to label the cations by their 15N spin state. The exchange rates and activation energy are then calculated by performing experiments as functions of mixing time and temperature. By comparing the measured exchange rates to previously measured bulk H+ diffusivities, we demonstrate that, after dissociating, H+ ions travel through the lattice before associating to another cation rather than hopping between adjacent cations.

Targeting Lysosomes: A Strategy Against Chemoresistance in Cancer.

Chemotherapy is still the major method of treatment for many types of cancer. Curative cancer therapy is hampered significantly by medication resistance. Acidic organelles like lysosomes serve as protagonists in cellular digestion. Lysosomes, however, are gaining popularity due to their speeding involvement in cancer progression and resistance. For instance, weak chemotherapeutic drugs of basic nature permeate through the lysosomal membrane and are retained in lysosomes in their cationic state, while extracellular release of lysosomal enzymes induces cancer, cytosolic escape of lysosomal hydrolases causes apoptosis, and so on. Drug availability at the sites of action is decreased due to lysosomal drug sequestration, which also enhances cancer resistance. This review looks at lysosomal drug sequestration mechanisms and how they affect cancer treatment resistance. Using lysosomes as subcellular targets to combat drug resistance and reverse drug sequestration is another method for overcoming drug resistance that is covered in this article. The present review has identified lysosomal drug sequestration as one of the reasons behind chemoresistance. The article delves deeper into specific aspects of lysosomal sequestration, providing nuanced insights, critical evaluations, or novel interpretations of different approaches that target lysosomes to defect cancer.

Dietary Plant Metabolites Induced Epigenetic Modification as a Novel Strategy for the Management of Prostate Cancer.

Prostate cancer is a widespread malignancy among men, with a substantial global impact on morbidity and mortality. Despite advances in conventional therapies, the need for innovative and less toxic treatments remains a priority. Emerging evidence suggests that dietary plant metabolites possess epigenetic-modifying properties, making them attractive candidates for prostate cancer treatment. The present work reviews the epigenetic effects of dietary plant metabolites in the context of prostate cancer therapy. We first outline the key epigenetic mechanisms involved in prostate cancer pathogenesis, including histone modifications, DNA methylation, and miRNA or Long Noncoding RNA (lncRNA) dysregulation. Next, we delve into the vast array of dietary plant metabolites that have demonstrated promising anti-cancer effects through epigenetic regulation. Resveratrol, minerals, isothiocyanates, curcumin, tea polyphenols, soy isoflavones and phytoestrogens, garlic compounds, anthocyanins, lycopene, and indoles are among the most extensively studied compounds. These plant-derived bioactive compounds have been shown to influence DNA methylation patterns, histone modifications, and microRNA expression, thereby altering the gene expression allied with prostate cancer progression, cell proliferation, and apoptosis. We also explore preclinical and clinical studies investigating the efficacy of dietary plant metabolites as standalone treatments or in combination with traditional treatments for people with prostate cancer. The present work highlights the potential of dietary plant metabolites as epigenetic modulators to treat prostate cancer. Continued research in this field may pave the way for personalized and precision medicine approaches, moving us closer to the goal of improved prostate cancer management.

Stabilization of highly efficient perovskite solar cells with a tailored supramolecular interface.

The presence of defects at the interface between the perovskite film and the carrier transport layer poses significant challenges to the performance and stability of perovskite solar cells (PSCs). Addressing this issue, we introduce a dual host-guest (DHG) complexation strategy to modulate both the bulk and interfacial properties of FAPbI3-rich PSCs. Through NMR spectroscopy, a synergistic effect of the dual treatment is observed. Additionally, electro-optical characterizations demonstrate that the DHG strategy not only passivates defects but also enhances carrier extraction and transport. Remarkably, employing the DHG strategy yields PSCs with power conversion efficiencies (PCE) of 25.89% (certified at 25.53%). Furthermore, these DHG-modified PSCs exhibit enhanced operational stability, retaining over 96.6% of their initial PCE of 25.55% after 1050 hours of continuous operation under one-sun illumination, which was the highest initial value in the recently reported articles. This work establishes a promising pathway for stabilizing high-efficiency perovskite photovoltaics through supramolecular engineering, marking a significant advancement in the field.

Soil moisture precipitation feedbacks in the Eastern European Alpine region in convection-permitting climate simulations.

A novel convection permitting modelling framework that combines a pseudo-global warming approach with continuously forced deep soil moisture from prescribed perturbation storylines is applied in the Eastern European Alpine region and parts of the Pannonian Basin to investigate soil moisture precipitation (SMP) feedbacks on summertime precipitation and the feedbacks' role under changed climate conditions. A set of 1-year convection-permitting (3 km horizontal grid spacing) soil moisture sensitivity simulations with the regional climate model of the Consortium for Small-Scale Modelling in Climate Mode are conducted. In order to account for global warming, end-of-the-century climate change effects from four global climate models, projecting the greenhouse gas concentration scenario RCP 8.5, are imprinted. The simulations reveal that (1) the locations of precipitation events are highly sensitive to soil moisture modifications while intensities and the internal structure of precipitation events are nearly unaffected and (2) high precipitation intensities are more likely in combinations with positive temporal but distinctive (either strong positive or strong negative) spatial SMP coupling. Low precipitation intensities are in favour of combinations of negative temporal and positive spatial coupling. The analyses suggest that soil moisture at a given time acts as a guiding field for the location of the next precipitation event. Interestingly, this behaviour is independent of climate change, although the coupling strength's increase is 1.5-1.7 times larger than expected from linear climate change scaling when climate becomes 50% dryer. Finally, it is found that (1) local deviations in the climate change signal of summertime precipitation in the range of up to ±40% are caused by uncertainty in deep soil moisture in the range of ±10% and (2) these local deviations in the climate change signal are dominated by soil moisture uncertainty in future climate conditions.