mHealth hyperspectral learning for instantaneous spatiospectral imaging of hemodynamics

Hyperspectral imaging acquires data in both the spatial and frequency domains to offer abundant physical or biological information. However, conventional hyperspectral imaging has intrinsic limitations of bulky instruments, slow data acquisition rate, and spatiospectral tradeoff. Here we introduce hyperspectral learning for snapshot hyperspectral imaging in which sampled hyperspectral data in a small subarea are incorporated into a learning algorithm to recover the hypercube. Hyperspectral learning exploits the idea that a photograph is more than merely a picture and contains detailed spectral information. A small sampling of hyperspectral data enables spectrally informed learning to recover a hypercube from an RGB image. Hyperspectral learning is capable of recovering full spectroscopic resolution in the hypercube, comparable to high spectral resolutions of scientific spectrometers. Hyperspectral learning also enables ultrafast dynamic imaging, leveraging ultraslow video recording in an off-the-shelf smartphone, given that a video comprises a time series of multiple RGB images. To demonstrate its versatility, an experimental model of vascular development is used to extract hemodynamic parameters via statistical and deep-learning approaches. Subsequently, the hemodynamics of peripheral microcirculation is assessed at an ultrafast temporal resolution up to a millisecond, using a conventional smartphone camera. This spectrally informed learning method is analogous to compressed sensing; however, it further allows for reliable hypercube recovery and key feature extractions with a transparent learning algorithm. This learning-powered snapshot hyperspectral imaging method yields high spectral and temporal resolutions and eliminates the spatiospectral tradeoff, offering simple hardware requirements and potential applications of various machine-learning techniques.Comment: This paper will appear in PNAS Nexu

Cryotomography of budding influenza a virus reveals filaments with diverse morphologies that mostly do not bear a genome at their distal end

Influenza viruses exhibit striking variations in particle morphology between strains. Clinical isolates of influenza A virus have been shown to produce long filamentous particles while laboratory-adapted strains are predominantly spherical. However, the role of the filamentous phenotype in the influenza virus infectious cycle remains undetermined. We used cryo-electron tomography to conduct the first three-dimensional study of filamentous virus ultrastructure in particles budding from infected cells. Filaments were often longer than 10 microns and sometimes had bulbous heads at their leading ends, some of which contained tubules we attribute to M1 while none had recognisable ribonucleoprotein (RNP) and hence genome segments. Long filaments that did not have bulbs were infrequently seen to bear an ordered complement of RNPs at their distal ends. Imaging of purified virus also revealed diverse filament morphologies; short rods (bacilliform virions) and longer filaments. Bacilliform virions contained an ordered complement of RNPs while longer filamentous particles were narrower and mostly appeared to lack this feature, but often contained fibrillar material along their entire length. The important ultrastructural differences between these diverse classes of particles raise the possibility of distinct morphogenetic pathways and functions during the infectious process

Using honey to heal diabetic foot ulcers

Diabetic ulcers seem to be arrested in the inflammatory/proliferative stage of the healing process, allowing infection and inflammation to preclude healing. Antibiotic-resistant bacteria have become a major cause of infections, including diabetic foot infections. It is proposed here that the modern developments of an ancient and traditional treatment for wounds, dressing them with honey, provide the solution to the problem of getting diabetic ulcers to move on from the arrested state of healing. Honeys selected to have a high level of antibacterial activity have been shown to be very effective against antibiotic-resistant strains of bacteria in laboratory and clinical studies. The potent anti-inflammatory action of honey is also likely to play an important part in overcoming the impediment to healing that inflammation causes in diabetic ulcers, as is the antioxidant activity of honey. The action of honey in promotion of tissue regeneration through stimulation of angiogenesis and the growth of fibroblasts and epithelial cells, and its insulin-mimetic effect, would also be of benefit in stimulating the healing of diabetic ulcers. The availability of honey-impregnated dressings which conveniently hold honey in place on ulcers has provided a means of rapidly debriding ulcers and removing the bacterial burden so that good healing rates can be achieved with neuropathic ulcers. With ischemic ulcers, where healing cannot occur because of lack of tissue viability, these honey dressings keep the ulcers clean and prevent infection occurring

The 9p21.3 risk of childhood acute lymphoblastic leukaemia is explained by a rare high-impact variant in CDKN2A

Genome-wide association studies (GWAS) have provided strong evidence for inherited predisposition to childhood acute lymphoblastic leukaemia (ALL) identifying a number of risk loci. We have previously shown common SNPs at 9p21.3 influence ALL risk. These SNP associations are generally not themselves candidates for causality, but simply act as markers for functional variants. By means of imputation of GWAS data and subsequent validation SNP genotyping totalling 2,177 ALL cases and 8,240 controls, we have shown that the 9p21.3 association can be ascribed to the rare highimpact CDKN2A p.Ala148Thr variant (rs3731249; Odds ratio=2.42, P=3.45×10−19). The association between rs3731249 genotype and risk was not specific to particular subtype of B-cell ALL. The rs3731249 variant is associated with predominant nuclear localisation of the CDKN2A transcript suggesting the functional effect of p.Ala148Thr on ALL risk may be through compromised ability to inhibit cyclin D within the cytoplasm

CD28 Costimulation Regulates Genome-Wide Effects on Alternative Splicing

CD28 is the major costimulatory receptor required for activation of naïve T cells, yet CD28 costimulation affects the expression level of surprisingly few genes over those altered by TCR stimulation alone. Alternate splicing of genes adds diversity to the proteome and contributes to tissue-specific regulation of genes. Here we demonstrate that CD28 costimulation leads to major changes in alternative splicing during activation of naïve T cells, beyond the effects of TCR alone. CD28 costimulation affected many more genes through modulation of alternate splicing than by modulation of transcription. Different families of biological processes are over-represented among genes alternatively spliced in response to CD28 costimulation compared to those genes whose transcription is altered, suggesting that alternative splicing regulates distinct biological effects. Moreover, genes dependent upon hnRNPLL, a global regulator of splicing in activated T cells, were enriched in T cells activated through TCR plus CD28 as compared to TCR alone. We show that hnRNPLL expression is dependent on CD28 signaling, providing a mechanism by which CD28 can regulate splicing in T cells and insight into how hnRNPLL can influence signal-induced alternative splicing in T cells. The effects of CD28 on alternative splicing provide a newly appreciated means by which CD28 can regulate T cell responses

X-Ray Repair Cross-Complementing Group 1 (XRCC1) Genetic Polymorphisms and Risk of Childhood Acute Lymphoblastic Leukemia: A Meta-Analysis

Background: Recently, there have been a number of studies on the association between XRCC1 polymorphisms and childhood acute lymphoblastic leukemia (ALL) risk. However, the results of previous reports are inconsistent. Thus, we performed a meta-analysis to clarify the effects of XRCC1 variants on childhood ALL risk. Methods: A meta-analysis was performed to examine the association between XRCC1 polymorphisms (Arg399Gln, Arg194Trp, and Arg280His) and childhood ALL risk. We critically reviewed 7 studies with a total of 880 cases and 1311 controls for Arg399Gln polymorphism, 3 studies with a total of 345 cases and 554 controls for Arg280His polymorphism, and 6 studies with a total of 783 cases and 1180 controls for Arg194Trp polymorphism, respectively. Odds ratio (OR) and its 95% confidence interval (CI) were used. Results: Significant association between XRCC1 Arg399Gln polymorphism and childhood ALL risk was observed in total population analyses (OR additive model = 1.501, 95 % CI 1.112–2.026, P OR = 0.008; OR dominant model = 1.316, 95 % CI = 1.104–1.569, POR = 0.002) and Asian subgroup analyses (ORadditive model = 2.338, 95%CI = 1.254–4.359, POR = 0.008; ORdominant model = 2.108, 95%CI = 1.498–2.967, POR = 0.000). No association was detected in Caucasians, Metizo and mixed populations. Ethnicity was considered as a significant source of heterogeneity in the meta-regression model. For the other two XRCC1 polymorphisms, no association with childhood ALL risk was found