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The rechargeable battery using uranium as an active material
Near-zero photon bioimaging by fusing deep learning and ultralow-light microscopy
Enhancing the reliability and reproducibility of optical microscopy by reducing specimen irradiance continues to be an important biotechnology target. As irradiance levels are reduced, however, the particle nature of light is heightened, giving rise to Poisson noise, or photon sparsity that restricts only a few (0.5%) image pixels to comprise a photon. Photon sparsity can be addressed by collecting approximately 200 photons per pixel; this, however, requires long acquisitions and, as such, suboptimal imaging rates. Here, we introduce near-zero photon bioimaging, a method that operates at kHz rates and 10,000-fold lower irradiance than standard microscopy. To achieve this level of performance, we uniquely combined a judiciously designed epifluorescence microscope enabling ultralow background levels and AI that learns to reconstruct biological images from as low as 0.01 photons per pixel. We demonstrate that near-zero photon bioimaging captures the structure of multicellular and subcellular features with high fidelity, including features represented by nearly zero photons. Beyond optical microscopy, the near-zero photon bioimaging paradigm can be applied in remote sensing, covert applications, and biomedical imaging that utilize damaging or quantum light.
Effects of solar elevation angle on the visible light vegetation index of a cotton field when extracted from the UAV
Physical activity stimulates clock neurons of the day-active rodent <i>Arvicanthis ansorgei</i>
Our biological clock, located in the suprachiasmatic nucleus (SCN), controls behavioral activity rhythms by producing circadian rhythms in SCN electrical activity. Behavioral studies in humans suggest that the clock is sensitive not only to light but also to physical activity. Here, we examined the effect of physical activity on the brain’s clock in the diurnal rodent, Arvicanthis ansorgei . We found that the electrical activity of SCN neurons in vitro is high during the day and low during the night. Recordings via stationary microelectrodes in freely moving Arvicanthis revealed that the SCN baseline rhythm in discharge was superimposed by increments in electrical activity. These increments in electrical activity occurred during brief (seconds) or long (hours) periods of spontaneous activity of the animal and were observed at each phase of the cycle, i.e., both day and night. To establish the causal relation, we manipulated the animal’s activity by providing it with a running wheel. The voluntary use of the wheel resulted in direct and significant increments in SCN electrical activity. We conclude that behavioral activity triggers the increments in SCN electrical activity, rather than vice versa. Consequently, physical activity during the day will raise the amplitude of the SCN electrical discharge rhythm, thereby strengthening clock function. In contrast, night-time activity will be countereffective and attenuate the rhythm in electrical activity. The data elucidate the route via which daytime exercise supports clock function.
The effects of Tai Chi on clinical outcomes and gait biomechanics in knee osteoarthritis patients: a pilot randomized controlled trial
Cave records reveal recent origin of North America’s deepest canyon
We explore how and when Hells Canyon, North America’s deepest river gorge (~2,400 m deep), formed, addressing these fundamental questions first posed by W. Lindgren [ The Gold Belt of the Blue Mountains of Oregon (1901)]. Existing hypotheses about the canyon’s formation and timing of incision remain speculative due to a lack of direct constraints and geomorphic analysis in the canyon. Herein, we combine cosmogenic nuclide dating of cave-bound river deposits, river profile analysis, and numerical modeling to provide the first direct age constraints and systematic analysis of incision processes at work in Hells Canyon. Our study reveals a significant drainage capture triggered rapid incision at ~2.1 ± 1.0 Ma, establishing the Snake River’s modern route into the Columbia River system. The increased drainage area and subsequent increase in stream power resulted in the rapid incision of Hells Canyon and the formation of tributary knickpoints (KPs) that decrease in elevation away from the capture location. Cosmogenic dating of cave deposits indicates incision rates increased from ~0.01 to ~0.16 mm y −1 . Numerical modeling of the stream capture supports these observations, demonstrating how abrupt drainage area increase drives rapid river incision. Our findings from Hells Canyon provide a well-constrained example of how drainage capture can dramatically shape the evolution of a major river gorge.
Quasi periodic photonic crystal as gamma detector using Poly nanocomposite and porous silicon
Engineered chemokines, resistant to cancer-mediated post-transcriptional modifications, as drugs to improve cancer immunotherapy
Efficient field correction of low-cost particulate matter sensors using machine learning, mixed multiplicative/additive scaling and extended calibration inputs
Abstract Particulate matter (PM) stands out as a highly perilous form of atmospheric pollution, posing significant risks to human health by triggering or worsening numerous heart, brain, and lung ailments, and even increasing the likelihood of cancer and premature mortality. Therefore, ensuring accurate monitoring of PM levels holds paramount significance, particularly urban zones of dense population. Still, achieving precise readings of PM concentration demands the use of bulky and costly equipment, typically stationed at widely spaced reference sites. The rise in popularity of low-cost PM sensors as potential substitutes has been noted, although their reliability is hampered by manufacturing flaws, instability, and susceptibility to environmental variations. In this work, we introduce a novel approach to field calibration for cheap PM sensors. Our method integrates multiplicative and additive corrections, with coefficients determined by an artificial neural network (ANN) surrogate. The ANN model accounts for environmental parameters and the sensor’s PM readings as inputs, with its architecture fine-tuned to ensure optimal generalization capability. Additionally, we consider an extended set of input parameters, including local temporal changes of environmental variables, and short sequences of low-sensor readings, to further enhance calibration reliability. We validate our technique using a non-stationary measurement equipment alongside reference data acquired by government-approved reference stations in Gdansk, Poland. The obtained values of coefficients of determination reach as high as 0.89 for PM1, 0.87 for PM2.5, and 0.77 for PM10, respectively, while the root mean square error (RMSE) is merely 3.0, 3.9, and 4.9 µg/m³. Such a performance positions the calibrated low-cost sensor as a potential alternative to stationary measurement equipment.
Stability of general cognitive ability from infancy to adulthood: A combined twin and genomic investigation
Measures of general cognitive ability (GCA) are highly stable from adolescence onward, particularly at the level of genetic influences. In contrast, measurement of GCA in early life (before 3 y old) is less reliable and less is known about the stability of GCA across this period, including its relation to adult GCA. Using data from the Colorado Longitudinal Twin study (N = 1,098), we examined the stability of GCA measures across 5 time-points (years 1 to 2, 3, 7, 16, and 29), including how an array of cognitive measures given at 7 and 9 mo relate to later GCA. We then examined the genetic and environmental stability of GCA across the first 30 y of life using complementary methods: twin analyses and polygenic scores (PGSs). Two infant cognition measures, object novelty and tester-rated task orientation, predicted GCA in adulthood ( r = 0.16 and 0.18, respectively). Correlational analyses were consistent with a pattern of increasing stability across development for GCA measures between year 1 to 2 and adulthood ( r = 0.39 to 0.85). Subsequent twin analyses revealed that 22% of variance in adulthood GCA was captured by genetic influences on GCA from year 3 or earlier, with an additional 10% explained by shared environmental influences on GCA at year 1 to 2. PGSs for adulthood GCA and educational attainment predicted GCA from 1 to 2 y onward ( β s = 0.09 to 0.44) but not infant cognition. Findings suggest that genetic and environmental influences on GCA demonstrate considerable stability as early as age 3 y, but that measures of infant cognition are less predictive of later cognitive ability.
Study on the effect of ammonium (NH4+) as impurity and seed ratio on batch cooling crystallization of nickel sulfate hexahydrate
Experimental investigation to enhancing the energy efficiency of a solar-powered Visi cooler
Serum levels of trace elements in diabetic pregnant women and their relationship with growth indicators in newborns
Harnessing Molecular Recognition for Small‐Molecule‐Mediated Reversible Photochemical Control Over mRNA Translation
Abstract Chemical probes that control the function of complex RNA molecules offer unique opportunities to interrogate biological systems. In this study, we demonstrate that a small molecule ligand selectively recognizes and undergoes traceless, reversible photocrosslinking to PreQ 1 RNA aptamers. This effect is selective and dependent on both the chemical structure and RNA sequence/structure. A homogeneously modified, caged mRNA construct containing a PreQ 1 aptamer and an eGFP or wild type p53 coding sequence displayed repressed translation in vitro or in cells until irradiated with 302 nm light, resulting in cleavage of the photocage and restoration of translation. This method demonstrates for the first time that aptamer‐based molecular recognition of a small molecule ligand can be used to precisely and photochemically activate the translation of a complex mRNA in cells.
Cyperus rotundus mediated green synthesis of silver nanoparticles for antibacterial wound dressing applications
Enhanced osteogenic and angiogenic capabilities of adipose-derived stem cells in fish collagen scaffolds for treatment of femoral head osteonecrosis
Abstract Osteonecrosis of the femoral head (ONFH) is a debilitating condition that often leads to femoral head collapse due to insufficient blood supply and impaired bone regeneration. However, effective treatment options for this condition are limited. This study explored a novel fish collagen (FC) scaffold combined with adipose-derived stem cells (ADSCs) to enhance osteogenesis and angiogenesis in ONFH. ADSCs were isolated and cultured on FC scaffolds to evaluate their biocompatibility and differentiation capacity. Osteogenic and angiogenic differentiation potentials were assessed in vitro, and the FC/ADSC combination was further evaluated in vivo using a rat model of ONFH. The molecular mechanisms were investigated via gene expression profiling and Hippo signaling pathway analysis. The FC scaffolds promoted ADSCs adhesion, proliferation, and migration without cytotoxicity. In vitro, FC/ADSCs significantly enhanced mineralization and capillary-like structure formation compared to the controls. FC/ADSCs improved bone regeneration and neovascularization in the femoral head in vivo, as confirmed by histological and immunohistochemical analyses. Mechanistically, the Hippo pathway is activated, increasing HIF-1α expression, which enhances osteogenic and angiogenic differentiation. FC scaffolds combined with ADSCs provide a promising therapeutic strategy for ONFH by facilitating bone regeneration and vascularization through the p-YAP/HIF-1α/VEGF axis. This scaffold-cell approach represents a potential advancement in ONFH treatment.
Sustainable uric acid sensor based on a lab-fabricated electrode modified with rice straw-derived carbon materials
Optical Probes for Cellular Imaging of G‐quadruplexes: Beyond Fluorescence Intensity Probes
Abstract The study of G‐quadruplex (G4) structures that form in DNA and RNA is a rapidly growing field, which has evolved from in vitro studies of isolated G4 sequences to genome‐wide detection of G4s in a cellular context. This work has revealed the tangible and significant effects that G4s may have on biological regulation. This minireview describes recent progress in the design of photoluminescent intensity‐independent optical probes for G4s. We discuss the design and use of probes based on fluorescence or phosphorescence lifetime, rather than intensity‐based detection; spectral ratiometric probes; and fluorescent probes for single‐molecule G4‐detection. We argue that each of these modalities improve unbiased G4 detection in cellular experiments, overcoming problems associated with unknown cellular uptake of probes or their organelle concentration. We discuss the improvements offered by these types of probes, as well as limitations and future research directions needed to facilitate more robust research into G4 biology.