Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial Profiling of the Prostate Cancer Tumor Microenvironment Reveals Multiple Differences in Gene Expression and Correlation with Recurrence Risk

Simple Summary In prostate cancer (PCa), the tumor microenvironment plays a crucial role in both the development and progression of the disease. We used Digital Spatial Profiling multiplex technology to assess the expression of 58 protein and 1825 RNA transcripts in traditionally challenging samples (i.e., archived FFPE samples) while maintaining the spatial context of expression. First, we identified differences in protein and RNA expression among multiple cell types (stromal, epithelial, and immune cells). Second, we used a PCa tissue microarray of 1547 cores (97 patients) to further validate the protein expression of selected genes in a larger cohort of prostate cancer patients. We also computed survival models testing the relationship between OX40L, CTLA4, and CD11c protein expression in both tumor and tumor-adjacent stroma samples with time to biochemical relapse. Abstract The tumor microenvironment plays a crucial role in both the development and progression of prostate cancer. Furthermore, identifying protein and gene expression differences between different regions is valuable for treatment development. We applied Digital Spatial Profiling multiplex analysis to formalin-fixed paraffin embedded prostatectomy tissue blocks to investigate protein and transcriptome differences between tumor, tumor-adjacent stroma (TAS), CD45+ tumor, and CD45+ TAS tissue. Differential expression of an immunology/oncology protein panel (n = 58) was measured. OX40L and CTLA4 were expressed at higher levels while 22 other proteins, including CD11c, were expressed at lower levels (FDR < 0.2 and p-value < 0.05) in TAS as compared to tumor epithelia. A tissue microarray analysis of 97 patients with 1547 cores found positive correlations between high expression of CD11c and increased time to recurrence in tumor and TAS, and inverse relationships for CTLA4 and OX40L, where higher expression in tumor correlated with lower time to recurrence, but higher time to recurrence in TAS. Spatial transcriptomic analysis using a Cancer Transcriptome Atlas panel (n = 1825 genes) identified 162 genes downregulated and 69 upregulated in TAS versus tumor, 26 downregulated and 6 upregulated in CD45+ TAS versus CD45+ tumor. We utilized CIBERSORTx to estimate the relative immune cell fractions using CD45+ gene expression and found higher average fractions for memory B, naïve B, and T cells in TAS. In summary, the combination of protein expression differences, immune cell fractions, and correlations of protein expression with time to recurrence suggest that closely examining the tumor microenvironment provides valuable data that can improve prognostication and treatment techniques.
A deep learning approach of heartbeat classification for the single-lead ECG signals and inter-patient paradigm

The corresponding arrhythmia often occurs before the onset of cardiovascular disease (CVD), electrocardiogram (ECG) can more intuitively detect any abnormality in the heartbeat as a sign of arrhythmia. There are many traditional ECG classification methods, but these methods are constrained human costs and inaccuracy since they rely on manually extracting features, and cannot fully mine the deep pathological information hidden in the data. Consequently, a novel deep learning model based on single-lead ECG signals and inter-patient paradigm is developed to improve the shortcomings of traditional ECG heartbeat classification. The residual connection is adopted in the proposed method to improve classification accuracy and alleviate the gradient disappearance issue. Heartbeat complexes that included a targeted heartbeat and an adjacent heartbeat is selected as the input of the model. The MIT-BIH arrhythmia database is employed to valid proposed method. Besides, a focal loss function is used to address the classes imbalance of the database. The experimental results show that the positive predictive values of the proposed classification method for N, S, V, and F are 99.10%, 96.80%, 61.32%, and 95.36%, respectively. In addition, the sensitivity values are 95.83%, 95.54%, 90.43%, and 84.79%; the specificity values are 92.96%, 99.88%, 96.05%, and 99.97%, respectively. Compared with the art-of-state inter-patient ECG heartbeat classification approaches, our proposed approach achieved better results. Therefore, the proposed deep learning model of heartbeat classification is effective and feasible for the single-lead ECG signals and interpatient paradigm.
Functional Heterogeneity of Bone Marrow Mesenchymal Stem Cell Subpopulations in Physiology and Pathology

Bone marrow mesenchymal stem cells (BMSCs) are multi-potent cell populations and are capable of maintaining bone and body homeostasis. The stemness and potential therapeutic effect of BMSCs have been explored extensively in recent years. However, diverse cell surface antigens and complex gene expression of BMSCs have indicated that BMSCs represent heterogeneous populations, and the natural characteristics of BMSCs make it difficult to identify the specific subpopulations in pathological processes which are often obscured by bulk analysis of the total BMSCs. Meanwhile, the therapeutic effect of total BMSCs is often less effective partly due to their heterogeneity. Therefore, understanding the functional heterogeneity of the BMSC subpopulations under different physiological and pathological conditions could have major ramifications for global health. Here, we summarize the recent progress of functional heterogeneity of BMSC subpopulations in physiology and pathology. Targeting tissue-resident single BMSC subpopulation offers a potentially innovative therapeutic strategy and improves BMSC effectiveness in clinical application.
A LYMAN BREAK GALAXY IN THE EPOCH OF REIONIZATION FROM HUBBLE SPACE TELESCOPE GRISM SPECTROSCOPY

We present observations of a luminous galaxy at z = 6.573—the end of the reionization epoch—which has been spectroscopically confirmed twice. The first spectroscopic confirmation comes from slitless Hubble Space Telescope Advanced Camera for Surveys grism spectra from the PEARS survey (Probing Evolution And Reionization Spectroscopically), which show a dramatic continuum break in the spectrum at rest frame 1216 Å. The second confirmation is done with Keck + DEIMOS. The continuum is not clearly detected with ground-based spectra, but high wavelength resolution enables the Lyα emission line profile to be determined. We compare the line profile to composite line profiles at z = 4.5. The Lyα line profile shows no signature of a damping wing attenuation, confirming that the intergalactic gas is ionized at z = 6.57. Spectra of Lyman breaks at yet higher redshifts will be possible using comparably deep observations with IR-sensitive grisms, even at redshifts where Lyα is too attenuated by the neutral intergalactic medium to be detectable using traditional spectroscopy from the ground.
Asymmetric random walks in a discrete spacetime as a model for quantum mechanics

Introduction Despite being an extremely succesful theory to predict the outcome of ex- periments with particles and other microscopic objects, quantum mechanics (QM) is believed by many to be incomplete or, at least, not fully understood. In particular, the "strange" or non-classical phenomena of QM, like self- interference and Born's rule, are described in terms of abstract mathemati- cal objects. Although some have been ready to interpret the complex-valued wavefunction as a real object, wavefunctions are generally seen as mathe- matical tools serving to calculate probabilities from their square moduli. Contrasting to real-valued mathematics and one-to-one mapping between real variables and observables of classical theories, the standard description is thus sometimes considered as purely operational. In this paper a model is presented that, although very simple in terms of mathematical development and formalism, seems to be able to predict probability fields of at least free particles, and particularly self-interference, without using Schrodinger equation or wavefunctions. Unlike the standard QM picture, the proposed model only uses integer-valued quantities and arithmetic operations. In particular, it assumes a discrete spacetime under the form of an euclidean lattice. The proposed approach describes individual particle trajectories as random walks. Transition probabilities are simple functions of a few quantities that are either randomly associated to the particles during their preparation, or stored in the lattice sites they visit during the walk. Non-relativistic QM predictions are retrieved as probability distributions of similarly-prepared ensembles of particles.
Cork Development: What Lies Within

The cork layer present in all dicotyledonous plant species with radial growth is the result of the phellogen activity, a secondary meristem that produces phellem (cork) to the outside and phelloderm inwards. These three different tissues form the periderm, an efficient protective tissue working as a barrier against external factors such as environmental aggressions and pathogen attacks. The protective function offered by cork cells is mainly due to the abundance of suberin in their cell walls. Chemically, suberin is a complex aliphatic network of long chain fatty acids and alcohols with glycerol together with aromatic units. In most woody species growing in temperate climates, the first periderm is replaced by a new functional periderm upon a few years after being formed. One exception to this bark development can be found in cork oak (Quercus suber) which display a single periderm that grows continuously. Quercus suber stands by its thick cork layer development with continuous seasonal growth. Cork raw material has been exploited by man for centuries, especially in Portugal and Spain. Nowadays, its applications have widened vastly, from the most known product, stoppers, to purses or insulating materials used in so many industries, such as construction and car production. Research on how cork develops, and the effect environmental factors on cork oak trees is extremely important to maintain production of good-quality cork, and, by maintaining cork oak stands wealthy, we are preserving a very important ecosystem both by its biodiversity and its vital social and economic role in areas already showing a population declination.
Healthcare Barriers, Health Outcomes, and Annual Health Checks for Autistic Adults: A Cross-Sectional Study of General Practitioners’ Knowledge, Attitudes and Practices

Various physical conditions appear with greater frequency in autistic individuals in comparison to non-autistic people and can lead to higher morbidity, lower quality of life, and lower life expectancy. A voluntary primary care annual health check (AHC) scheme is in place in the UK for patients with intellectual disabilities (ID), some of whom will also be autistic. We report the results of a study involving an online questionnaire disseminated via Twitter to investigate knowledge, attitudes, and practices of UK General Practitioners (GPs) concerning barriers and enablers to autistic adults accessing primary healthcare services. Amongst other matters, we found that (1) autistic people who are independent for the most part face the greatest struggles accessing primary healthcare, and (2) advocates of AHCs for autistic adults face the twin challenges of convincing extremely busy GPs to prioritise AHCs, and of advocacy on behalf of people with other conditions.
Spectral variations along the branches in GX 5-1

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Joint Scheduling and Power Control for V2V Broadcast Communication with Adjacent Channel Interference

This paper investigates how to mitigate the impact of adjacent channel interference (ACI) in vehicular broadcast communication, using scheduling and power control. Our objective is to maximize the number of connected vehicles. First, we formulate the joint scheduling and power control problem as a mixed Boolean linear programming (MBLP) problem. From this problem formulation, we derive scheduling alone problem as Boolean linear programming (BLP) problem, and power control alone problem as an MBLP problem. Due to the hardness in solving joint scheduling and power control for multiple timeslots, we propose a column generation method to reduce the computational complexity. We also observe that the problem is highly numerically sensitive due to the high dynamic range of channel parameters and adjacent channel interference ratio (ACIR) values. Therefore, we propose a novel sensitivity reduction technique, which can compute the optimal solution. Finally, we compare the results for optimal scheduling, near-optimal joint scheduling and power control schemes, and conclude that the effective scheduling and power control schemes indeed significantly improve the performance.
STUDYING FREQUENCY RELATIONSHIPS OF KILOHERTZ QUASI-PERIODIC OSCILLATIONS FOR 4U 1636−53 AND Sco X-1: OBSERVATIONS CONFRONT THEORIES

By fitting the frequencies of simultaneous lower and upper kilohertz quasi-periodic oscillations (kHz QPOs) in two prototype neutron star (NS) QPO sources (4U 1636−53 and Sco X-1), we test the predictive power of all currently proposed QPO models. Models predict a linear, power law, or other relationship between the two frequencies. We found that for plausible NS parameters (mass and angular momentum), no model can satisfactorily reproduce the data, leading to very large chi-square values in our fittings. For both 4U 1636−53 and Sco X-1, this is largely due to the fact that the data significantly differ from a linear relationship. Some models perform relatively better but still have their own problems. Such a detailed comparison of data from models enables identification of routes for improving those models further.
Carbon Black Functionalized with Naturally Occurring Compounds in Water Phase for Electrochemical Sensing of Antioxidant Compounds

A new sustainable route to nanodispersed and functionalized carbon black in water phase (W-CB) is proposed. The sonochemical strategy exploits ultrasounds to disaggregate the CB, while two selected functional naturally derived compounds, sodium cholate (SC) and rosmarinic acid (RA), act as stabilizing agents ensuring dispersibility in water adhering onto the CB nanoparticles’ surface. Strategically, the CB-RA compound is used to drive the AuNPs self-assembling at room temperature, resulting in a CB surface that is nanodecorated; further, this is achieved without the need for additional reagents. Electrochemical sensors based on the proposed nanomaterials are realized and characterized both morphologically and electrochemically. The W-CBs’ electroanalytical potential is proved in the anodic and cathodic window using caffeic acid (CF) and hydroquinone (HQ), two antioxidant compounds that are significant for food and the environment. For both antioxidants, repeatable (RSD ≤ 3.3%; n = 10) and reproducible (RSD ≤ 3.8%; n = 3) electroanalysis results were obtained, achieving nanomolar detection limits (CF: 29 nM; HQ: 44 nM). CF and HQ are successfully determined in food and environmental samples (recoveries 97–113%), and also in the presence of other phenolic classes and HQ structural isomers. The water dispersibility of the proposed materials can be an opportunity for (bio) sensor fabrication and sustainable device realization.
Assessment of suitable referral, effectiveness and long-term outcomes of standard vs intensive pain management programmes for people with chronic pain

Background Chronic pain is a leading cause of disability, often requiring multidisciplinary management. 2021 NICE guidance has questioned the quality of the evidence surrounding the efficacy of pain management programmes (PMPs), with only minor benefit demonstrated in psychological and physical outcomes. There is need for further high-quality evidence for the efficacy of PMPs for a range of chronic pain conditions and to identify barriers to successful management of chronic pain. Objective This service evaluation utilised routinely collected outcome data of 508 PMP attendees to investigate change in pain- and patient-related outcomes across two distinct PMPs; a standard and an intensive PMP, and establish their longer-term efficacy and appropriateness for patients with differing degrees of need. Results More people with chronic widespread pain, fibromyalgia, and osteoarthritis were referred to the intensive PMP (reflecting greater disability and distress in these conditions). Those referred to the intensive PMP demonstrated greater distress (such as more severe depression and anxiety), lower pain acceptance and poorer physical function. Improvements were observed in all outcomes across both PMPs (including physical function, pain catastrophising and pain acceptance). Depression and disability demonstrated clinically meaningful improvements in the intensive PMP, and pain severity showed clinically meaningful improvement in both PMPs. However, depression severity, disability, pain severity, and pain interference significantly deteriorated at 6-month follow-up for those on the intensive PMP, with pain severity increasing to a clinically meaningful degree (by more than 10%), though these outcomes remained better than at baseline. Conclusion This evaluation identified that people with chronic pain most at risk of deterioration in physical and psychological wellbeing after completing a PMP require early identification to mitigate such deterioration. Established and emerging PMPs need to be tailored to the needs of this group, particularly at follow-up to reduce risks of pain severity increasing, alongside establishing/reinforcing safeguards against deterioration post-PMP.
Energy aware data harvesting strategy based on optimal node selection for extended network lifecycle in smart dust

Smart Dust environment face additional challenges as a result of the use of movable Smart Dust basestation(BS), despite its benefits. The main point of contention is the BS positioning updates to the smart dust nodes. Each smart object ought to be aware of the BS location so that it can send its data to the BS. According to the prevailing Flooding approach, the moveable BS must continuously distribute its location throughout the network in order to inform smart dust nodes about the BS location. In every case, visit positioning upgrades from the BS can result in maximal power usage as well as enhanced network breakdowns. Different sorts of routing architectures can be used to reduce BS position updating. A routing strategy based on the movable BS is successful if it preserves the network network’s power consumption and latencies to a minimum. The study’s main goal is to develop an energy-efficient routing mechanism focused on adaptive movable BS modification. In the Smart Dust Head (SDH) establishing the inferred surroundings, the most latest movable BS location will be preserved. As a result, rather than soliciting SDH in the environment, the location of the BS is propagated to the smart dust nodes located at the sectors in integrated networking. By transmitting request information to the nearest sector, the remaining SDH can find the most current BS location. The message’s recipient is determined based on the information gathered. The best fuzzy related clustering algorithm will be used to accomplish this. The Enhanced Oppositional grey wolf optimization (EOGWO) methodology can be used to perform the improvement. Optimum network throughput, low latency, and other metrics are used to assess performance. To enhance productivity, the findings will be analyzed and compared to previous routing methodologies.
Identification and Structure–Activity Relationship of Recovered Phenolics with Antioxidant and Antihyperglycemic Potential from Sugarcane Molasses Vinasse

Sugarcane molasses vinasse is the residue of the fermentation of molasses and the water and soil environmental pollutants from distilleries. However, its recycling value has been neglected. The chemical analysis of the molasses vinasse led to the isolation of a new benzoyl chloride called 2,3,4-trihydroxy-5-methoxy benzoyl chloride, as well as thirteen known compounds, including six benzoic acids. The structure of the new benzoyl chloride was elucidated on the basis of extensive spectroscopic analysis. The antioxidant activity of all isolated compounds was measured using the ORAC assay. Moreover, we compared the cellular antioxidant activity (CAA) and inhibitory activity against α-amylase and α-glucosidase for structure–activity analysis. The results showed that only vanillic acid had CAA (8.64 μmol QE/100 μmol in the no PBS wash protocol and 6.18 μmol QE/100 μmol in the PBS wash protocol), although other benzoic acid derivatives had high ORAC values ranging between 1879.9 and 32,648.1 μmol TE/g. Additional methoxy groups at the ortho-positions of the p-hydroxy group of benzoic acids enhanced the inhibition of α-glucosidase but reduced the ORAC activity unless at the para-position. This work indicated that phenolics, especially phenolic acids in the sugarcane molasses vinasse, possessed potential antioxidant and antihyperglycemic activity, which improved the utilization rate of resources and reduced the discharge of pollutants.
Mass Composition Sensitivity of an Array of Water Cherenkov and Scintillation Detectors

We consider a hybrid array composed of scintillation and water Cherenkov detectors designed to measure the cosmic ray primary mass composition at energies of about 1 EeV. We have developed a simulation and reconstruction chain to study the theoretical performance of such an array. In this work we investigate the sensitivity of mass composition observables in relation to the geometry of the array. The detectors are arranged in a triangular grid with fixed 750 m spacing and the configuration of the scintillator detectors is optimized for mass composition sensitivity. We show that the performance for composition determination can be compared favorably to that of Xmax measurements after the difference in duty cycles is considered.
On the Dynamics of New 4D and 6D Hyperchaotic Systems

One of the most interesting problems is the investigation of the boundaries of chaotic or hyperchaotic systems. In addition to estimating the Lyapunov and Hausdorff dimensions, it can be applied in chaos control and chaos synchronization. In this paper, by means of the analytical optimization, comparison principle, and generalized Lyapunov function theory, we find the ultimate bound set for a new six-dimensional hyperchaotic system and the globally exponentially attractive set for a new four-dimensional Lorenz- type hyperchaotic system. The novelty of this paper is that it not only shows the 4D hyperchaotic system is globally confined but also presents a collection of global trapping regions of this system. Furthermore, it demonstrates that the trajectories of the 4D hyperchaotic system move at an exponential rate from outside the trapping zone to its inside. Finally, some numerical simulations are shown to demonstrate the efficacy of the findings.