We synthesize data from 77 independent studies, annotating and integrating it to reveal the transcriptional ITH patterns observed in 1163 tumor samples, including 24 different tumor types. In cancerous cell populations, we've discovered 41 recurring patterns of gene activity, each involving numerous genes that are activated together in particular groups of tumor cells. Meta-programs encompass a variety of cellular functions, including general functions (such as the cell cycle and stress responses) and lineage-specific activities, which we categorize into 11 transcriptional ITH hallmarks. Similar meta-programs are apparent in both carcinoma cells and non-malignant epithelial cells, hinting that a substantial percentage of malignant ITH programs display variability before oncogenic transformation, demonstrating the cellular origin's influence. Our meta-program analysis was subsequently extended to encompass six typical non-malignant cell types, allowing for the charting of cell-cell interactions within the tumor microenvironment. In conclusion, a comprehensive pan-cancer single-cell RNA-sequencing dataset, accessible via the Curated Cancer Cell Atlas, has been compiled and utilized for a thorough analysis of transcriptional ITH.Almost any interaction between light and materials begins with the electrons' electrodynamic response to the light wave's optical cycles, which occur on sub-wavelength and sub-cycle dimensions. Consequently, mastery of electromagnetic material responses, from 2-11, is crucial for modern optical and nanophotonic technologies, 12-19. Electron beams' de Broglie wavelength, small enough to allow for attosecond and angstrom-scale measurements, has not yet translated into corresponding time resolutions in ultrafast electron microscopy and diffraction. Current systems are confined to the femtosecond domain, rendering them insufficient for the study of fundamental material responses on the light cycle scale. Optical responses within a single light excitation cycle are now resolvable with attosecond time resolution, enabled by advancements in transmission electron microscopy. A continuous-wave laser24 modulates the electron wave function into a succession of swift electron pulses, with an energy filter used to resolve the electromagnetic near-fields within and around the material, displaying a movie through space and time. The experimental study of nanostructured needle tips, dielectric resonators, and metamaterial antennas reveals directional launching of chiral surface waves, a delay in the transition from dipole to quadrupole dynamics, a subluminal field confined within a buried waveguide, and a broken symmetry multi-antenna response. A combined approach employing electron microscopy and attosecond laser science allows for the investigation of light-matter interactions in terms of their fundamental dimensions in both space and time, showcasing its significant value.Mapping the relationships between genes within a network necessitates a substantial volume of transcriptomic data, thereby obstructing investigations in settings with scarce data availability, including research on rare diseases and conditions affecting inaccessible tissues. Through transfer learning, which leverages deep learning models pre-trained on broad general datasets, the fields of natural language understanding and computer vision have experienced a revolution, permitting the fine-tuning of models for a wide range of downstream tasks with limited task-specific data. To address the limitations of data in network biology, we developed Geneformer, a context-conscious, attention-based deep learning model pre-trained on approximately 30 million single-cell transcriptome data, enabling specific predictions based on context. The self-supervised pretraining of Geneformer resulted in a fundamental understanding of network dynamics, with the network's hierarchy encoded within the model's attentional weights. With fine-tuning on a diverse panel of downstream tasks relevant to chromatin and network dynamics using limited task-specific data, Geneformer consistently demonstrated a boost in predictive accuracy. Limited patient data prompted Geneformer to pinpoint potential therapeutic targets for cardiomyopathy via disease modeling. The pre-trained deep learning model Geneformer offers a pathway for fine-tuning across a spectrum of downstream applications, expediting the process of identifying crucial network regulators and candidate therapeutic targets.The rhythmic beating of motile cilia and flagella across cell surfaces drives fluid flow and empowers the locomotion of spermatozoa and single-celled eukaryotes. In humans, a defect in ciliary movement can lead to male infertility and a congenital condition known as primary ciliary dyskinesia (PCD), in which inefficient clearance of mucus by cilia results in chronic respiratory infections. microrna inhibitor Microtubules, ATP-powered dynein motors, and regulatory complexes within the axoneme, a molecular mechanism, collectively drive ciliary movement. The axoneme's extensive size and intricate composition have so far prevented the creation of an atomic model, thereby obstructing the elucidation of its operational principles. Recent advancements in cryo-electron microscopy (cryo-EM) and artificial intelligence-based structural prediction techniques allowed us to determine the structural arrangement of the 96-nanometer modular repeats in axonemes from the flagella of Chlamydomonas reinhardtii and human respiratory cilia. Atomic descriptions of axonemes demonstrate the conservation and specialization of these structures, the intricate connections between dynein and their controlling factors, and the processes responsible for maintaining their periodic arrangement. Axonemal dynein motors, in concert with correlated conformational shifts within mechanoregulatory complexes, offer a mechanism for the long-hypothesized mechanotransduction pathway's regulation of ciliary movement. Microtubule structures of respiratory cilia doublets, from four individuals with PCD, illustrate how the loss of individual docking factors can cause the specific elimination of recurring patterns.The incidence of Alzheimer's disease (AD), the leading cause of dementia, escalates significantly with advancing age, yet the underlying mechanisms for age as the primary risk factor are still not fully elucidated. The aging brain influences oligodendrocytes and the structural integrity of myelin sheaths, which in turn are associated with the development of secondary neuroinflammation. Considering oligodendrocytes' critical role in supporting axonal energy metabolism and neuronal health, we posited that loss of myelin integrity could be a contributing upstream factor in neuronal amyloid- (A) deposition, a defining neuropathological characteristic of Alzheimer's disease. In mouse models of Alzheimer's Disease, we find that genetic pathways of myelin malfunction and demyelinating lesions serve as significant drivers for the accumulation of amyloid deposits. The mechanistic action of myelin dysfunction is to cause an accumulation of the A-producing machinery within axonal swellings, which in turn increases the cleavage of cortical amyloid precursor protein. In a surprising finding, AD mice with impaired myelin show a shortage of microglia tasked with containing plaques, even with a general upsurge in their numbers. Mouse models of Alzheimer's Disease, characterized by myelin defects, display, via bulk and single-cell transcriptomic profiling, a correlated increase in distinctive but related disease-associated microglia signatures specifically linked to myelin damage and amyloid plaques, respectively. Successful induction notwithstanding, microglia associated with amyloid disease (DAM), usually charged with the removal of amyloid plaques, appear distracted by nearby myelin damage. Our data supports a model where age-dependent structural damage to myelin is a driving force behind A plaque formation in both direct and indirect ways, making it an antecedent risk factor for Alzheimer's disease. The enhancement of oligodendrocyte health and myelin integrity presents a promising therapeutic target for mitigating the development and slowing the progression of Alzheimer's disease.Phosphorus, the limiting nutrient, is considered to have a substantial impact on the oxygenation levels of the ocean, based on research 1-3. It has been hypothesized that an upsurge in marine phosphorus levels during the Ediacaran Period (spanning from 635 to 549 million years ago) might have fueled an increase in oxygen levels. However, the evolution and properties of phosphorus cycling processes during this era are not well documented. Carbonate-associated phosphate (CAP) from six locations across the globe is used to reconstruct oceanic phosphorus levels during the Shuram excursion (SE), a substantial negative carbon isotope event linked to the concurrent global oceanic oxygenation. Our observations reveal periodic surges in oceanic phosphorus levels concurrent with both the downswing and upswing of the SE. Using a quantitative biogeochemical modeling framework, we propose that the observed data are explainable by the release of carbon dioxide and phosphorus from marine organic matter oxidation, predominantly via sulfate, with an additional release of phosphorus from carbon dioxide-driven weathering on land. The elevated organic-pyrite burial and the resulting ocean oxygenation may be directly linked to the collective influence of these occurrences. The Southeastern region's ocean anoxia, across its peak and trough, seems to possess consistent oceanic phosphorus concentrations, as per our CAP data. The observed phenomenon could indicate a disconnection between phosphorus and ocean anoxia cycles, contrasting with their interconnectedness in today's ocean. Our investigation reveals external influences, such as sulfate weathering, as a more probable mechanism controlling oceanic oxygenation in the Ediacaran compared to the internal oceanic phosphorus-oxygen cycle alone. This could potentially account for the long-term elevation of atmospheric oxygen.The Earth system's inherent stability and human prosperity are profoundly linked, yet their interdependence is often underestimated, thus resulting in their separate management. To establish the safe and equitable thresholds of Earth's systems (ESBs) for climate, biosphere, water and nutrient cycles, and aerosols, at both a global and sub-global level, we combine modeling and literature reviews.