We also found that significant difference of B cells infiltration based on TP 53 mutation. These findings suggest that DNMT1 related epigenetic alterations have close relationship with HNSCC progression, and DNMT1 could be a novel diagnostic biomarker and a promising therapeutic target for HNSCC.Tropical Pacific stalagmites are commonly affected by dating uncertainties because of their low U concentration and/or elevated initial 230Th content. This poses problems in establishing reliable trends and periodicities for droughts and pluvial episodes in a region vulnerable to climate change. Here we constrain the chronology of a Cook Islands stalagmite using synchrotron µXRF two-dimensional mapping of Sr concentrations coupled with growth laminae optical imaging constrained by in situ monitoring. Unidimensional LA-ICP-MS-generated Mg, Sr, Ba and Na variability series were anchored to the 2D Sr and optical maps. The annual hydrological significance of Mg, Sr, Ba and Na was tested by principal component analysis, which revealed that Mg and Na are related to dry-season, wind-transported marine aerosols, similar to the host-rock derived Sr and Ba signatures. Trace element annual banding was then used to generate a calendar-year master chronology with a dating uncertainty maximum of ± 15 years over 336 years. Our approach demonstrates that accurate chronologies and coupled hydroclimate proxies can be obtained from speleothems formed in tropical settings where low seasonality and problematic U-Th dating would discourage the use of high-resolution climate proxies datasets.Metastasis is the leading cause of mortalities in cancer patients due to the spreading of cancer cells to various organs. Detecting cancer and identifying its metastatic potential at the early stage is important. This may be achieved based on the quantification of the key biomolecular components within tissues and cells using recent optical spectroscopic techniques. The aim of this study was to develop a noninvasive label-free optical biopsy technique to retrieve the characteristic molecular information for detecting different metastatic potentials of prostate cancer cells. Herein we report using native fluorescence (NFL) spectroscopy along with machine learning (ML) to differentiate prostate cancer cells with different metastatic abilities. The ML algorithms including principal component analysis (PCA) and nonnegative matrix factorization (NMF) were used for dimension reduction and feature detection. The characteristic component spectra were used to identify the key biomolecules that are correlated with metastatic potentials. The relative concentrations of the molecular spectral components were retrieved and used to classify the cancer cells with different metastatic potentials. A multi-class classification was performed using support vector machines (SVMs). The NFL spectral data were collected from three prostate cancer cell lines with different levels of metastatic potentials. The key biomolecules in the prostate cancer cells were identified to be tryptophan, reduced nicotinamide adenine dinucleotide (NADH) and hypothetically lactate as well. The cancer cells with different metastatic potentials were classified with high accuracy using the relative concentrations of the key molecular components. The results suggest that the changes in the relative concentrations of these key fluorophores retrieved from NFL spectra may present potential criteria for detecting prostate cancer cells of different metastatic abilities.Treadmills are essential to the study of human and animal locomotion as well as for applied diagnostics in both sports and medicine. The quantification of relevant biomechanical and physiological variables requires a precise regulation of treadmill belt velocity (TBV). Here, we present a novel method for time-efficient tracking of TBV using standard 3D motion capture technology. Further, we analyzed TBV fluctuations of four different treadmills as seven participants walked and ran at target speeds ranging from 1.0 to 4.5 m/s. Using the novel method, we show that TBV regulation differs between treadmill types, and that certain features of TBV regulation are affected by the subjects’ body mass and their locomotion speed. With higher body mass, the TBV reductions in the braking phase of stance became higher, even though this relationship differed between locomotion speeds and treadmill type (significant body mass × speed × treadmill type interaction). Average belt speeds varied between about 98 and 103% of the target speed. For three of the four treadmills, TBV reduction during the stance phase of running was more intense (> 5% target speed) and occurred earlier (before 50% of stance phase) unlike the typical overground center of mass velocity patterns reported in the literature. Overall, the results of this study emphasize the importance of monitoring TBV during locomotor research and applied diagnostics. We provide a novel method that is freely accessible on Matlab’s file exchange server („getBeltVelocity.m”) allowing TBV tracking to become standard practice in locomotion research.Understanding the mechanisms underlying the metabolically unhealthy normal weight (MUHNW) and metabolically healthy obese (MHO) phenotypes is important for developing strategies to prevent cardiometabolic diseases. Here, we conducted genome-wide association studies (GWASs) to identify the MUHNW and MHO genetic indices. The study dataset comprised genome-wide single-nucleotide polymorphism genotypes and epidemiological data from 49,915 subjects categorised into four phenotypes-metabolically healthy normal weight (MHNW), MUHNW, MHO, and metabolically unhealthy obese (MUHO). We conducted two GWASs using logistic regression analyses and adjustments for confounding variables (model 1 MHNW versus MUHNW and model 2 MHO versus MUHO). GCKR, ABCB11, CDKAL1, LPL, CDKN2B, NT5C2, APOA5, CETP, and APOC1 were associated with metabolically unhealthy phenotypes among normal weight individuals (model 1). LPL, APOA5, and CETP were associated with metabolically unhealthy phenotypes among obese individuals (model 2). The genes common to both models are related to lipid metabolism (LPL, APOA5, and CETP), and those associated with model 1 are related to insulin or glucose metabolism (GCKR, CDKAL1, and CDKN2B). This study reveals the genetic architecture of the MUHNW and MHO phenotypes in a Korean population-based cohort. These findings could help identify individuals at a high metabolic risk in normal weight and obese populations and provide potential novel targets for the management of metabolically unhealthy phenotypes.Idiopathic pure red cell aplasia (PRCA) and secondary PRCA associated with thymoma and large granular lymphocyte leukemia are generally considered to be immune-mediated. The PRCA2004/2006 study showed that poor responses to immunosuppression and anemia relapse were associated with death. PRCA may represent the prodrome to MDS. Thus, clonal hematopoiesis may be responsible for treatment failure. We investigated gene mutations in myeloid neoplasm-associated genes in acquired PRCA. We identified 21 mutations affecting amino acid sequences in 11 of the 38 adult PRCA patients (28.9%) using stringent filtering of the error-prone sequences and SNPs. Four PRCA patients showed 7 driver mutations in TET2, DNMT3A and KDM6A, and 2 PRCA patients carried multiple mutations in TET2. Five PRCA patients had mutations with high VAFs exceeding 0.3. These results suggest that clonal hematopoiesis by stem/progenitor cells might be related to the pathophysiology of chronic PRCA in certain adult patients.Stability is a physical attribute that stands opposite the change. However, it is still unclear how the arrangement of links called topology affects network stability. In this study, we tackled this issue in the resting-state brain network using structural balance. Structural balance theory employs the quality of triadic associations between signed links to determine the network stability. In this study, we showed that negative links of the resting-state network make hubs to reduce balance-energy and push the network into a more stable state compared to null-networks with trivial topologies. In this regard, we created a global measure entitled 'tendency to make hub’ to assess the hubness of the network. Besides, we revealed nodal degrees of negative links have an exponential distribution that confirms the existence of negative hubs. Our findings indicate that the arrangement of negative links plays an important role in the balance (stability) of the resting-state brain network.When contemplating the alarming depression rates in adults with autism spectrum disorder (ASD), there is a need to find factors explaining heightened symptoms of depression. Beyond the impact of autism traits, markedly increased levels of alexithymia traits should be considered as a candidate for explaining why individuals with ASD report higher levels of depressive symptoms. Here, we aim to identify the extent to which autism or alexithymia traits indicate depressive symptoms in ASD and whether the pattern of association are specific to ASD. Data of a large (N = 400) representative clinical population of adults referred to autism diagnostics have been investigated and split by cases with a confirmed ASD diagnosis (N = 281) and cases with a ruled out ASD diagnosis (N = 119). Dominance analysis revealed the alexithymia factor, difficulties in identifying feelings, as the strongest predictor for depressive symptomatology in ASD, outweighing autism traits and other alexithymia factors. This pattern of prediction was not specific to ASD and was shared by clinical controls from the referral population with a ruled out ASD diagnosis. Thus, the association of alexithymia traits with depression is not unique to ASD and may constitute a general psychopathological mechanism in clinical samples.Detecting vascular endothelial growth factor C (VEGF-C), a kind of tumor biomarker, is of significant clinical importance in evaluating the prognosis of patients with cancer. However, laboratory analyses are usually not suitable for point-of-care testing because they are expensive and time consuming. In response to these challenges, we fabricated an origami paper-based microfluidic electrochemical device. To improve the specificity of VEGF-C detection, nanocomposites, synthesized by new methylene blue (NMB), amino-functional single-walled carbon nanotubes (NH2-SWCNTs), and gold nanoparticles (AuNPs), were used to modify the surface of working electrodes. Results of electrochemical detection showed that the immunosensor had excellent linearity, ranging from 0.01 to 100 ng mL-1 (R2 = 0.988), and the limit of detection was 10 pg mL-1. To confirm the high specificity of the device under real-world conditions, we evaluated the device using clinical serum samples from our hospital. The results demonstrated that the device had an excellent performance and could provide a platform for real-time detection of cancers.Approximately 25% of Antarctic Bottom Water has its origin as dense water exiting the western Ross Sea, but little is known about what controls the release of dense water plumes from the Drygalski Trough. We deployed two moorings on the slope to investigate the water properties of the bottom water exiting the region at Cape Adare. Salinity of the bottom water has increased in 2018 from the previous measurements in 2008-2010, consistent with the observed salinity increase in the Ross Sea. We find High Salinity Shelf Water from the Drygalski Trough contributes to two pulses of dense water at Cape Adare. The timing and magnitude of the pulses is largely explained by an inverse relationship with the tidal velocity in the Ross Sea. We suggest that the diurnal and low frequency tides in the western Ross Sea may control the magnitude and timing of the dense water outflow.