Search Results (688)

Microsatellite instability (MSI) testing is frequently used to screen patients for the early detection of Lynch syndrome, the most common hereditary colorectal cancer syndrome. MSI testing compares microsatellite repeat lengths in tumor DNA with those in matched normal tissue from the same patient. Therefore, precise sample identification is critical for obtaining reliable test results. The Penta-C and Penta-D pentanucleotide markers are widely used for sample identification in MSI testing. We investigated instability, defined as allelic mismatches or shifts, discordant fragment sizes, or the appearance of alleles in tumor DNA that were absent in the corresponding normal DNA, in the Penta-C and Penta-D loci across 2609 paired colorectal tumor and matched normal tissue or blood DNA samples. The allele sizes of both markers did not match in 0.3% of microsatellite-stable (MSS) and 12.3% of microsatellite instability-high (MSI-H) patients (p < 0.001, difference in proportions, 12.0% (95% CI, 8.9–15.1%)). Non-matching allele sizes in 12.3% of the MSI-H tumors suggest that other repeat markers may also be unstable and not suitable for sample identification in these tumors. Full article

In this paper, we propose a novel multisecret sharing (MSS) scheme that integrates a recently developed exponential-speedup matrix spectral factorization algorithm into the construction of paraunitary matrices over finite fields. By exploiting the block-matrix generalization of the Janashia-Lagvilava method, we significantly enhance the efficiency and scalability of the MSS scheme. The proposed method ensures perfect secrecy, collusion resistance, and efficient reconstruction, while enabling practical deployment in large-scale distributed systems such as secure cloud storage, IoT networks, and blockchain authentication. Security and performance analyses demonstrate the superiority of the new approach over existing MSS schemes. Full article

The efficacy of immunotherapy in colorectal cancer (CRC) has long been considered to be closely associated with microsatellite instability (MSI) status. Patients with microsatellite stable (MSS) tumors typically exhibit poor responses to PD-1/PD-L1 inhibitors and a poor prognosis, often being categorized as immunologically ‘cold’ tumors. However, some MSS patients can still achieve favorable therapeutic responses, sometimes even surpassing those of certain MSI patients. Immune-cold and immune-hot tumor phenotypes are largely determined by the abundance, clonal expansion, and functional states of tumor-infiltrating T cells. This suggests that immunotherapy responses are driven by dynamic remodeling of T-cell clonality rather than by MSI status alone. To elucidate the underlying T cell clonal dynamics, integrated single-cell transcriptome (scRNA-seq) and T cell receptor sequencing (scTCR-seq) data analyses from 43 blood and tissue samples of MSI and MSS colorectal cancer patients before and after anti-PD-1 therapy were performed. Using our developed TCR reconstruction pipeline (TORBiT), we systematically analyzed the clonal architecture of the TCR repertoire, inter-tissue migration, and its association with T-cell functional state transitions. From a TCR clonal kinetic perspective, we revealed two distinct modes of immune Coercion that may further affect the immune response: a “high-fluctuation, deep-exhaustion” pattern in MSI tumors and a “high-baseline, strong-suppression” pattern in MSS tumors. These findings provide a novel theoretical foundation and research perspective for understanding the responsiveness and resistance mechanisms to immune checkpoint inhibitors. Full article

Field-Programmable Gate Arrays (FPGAs) have become an important platform for accelerating real-time communication systems, and System-on-Chip (SoC) devices provide the flexibility to design and optimize architectures that support high data rates, different modulation formats, and channel equalization schemes. Selecting the appropriate architecture can be guided through Design Space Exploration (DSE) using high-level synthesis tools, which enables the identification of numerical representations that balance performance with reduced hardware resource consumption. Despite their relevance, recent developments in communication systems often overlook the impact of numerical precision in Digital Signal Processing algorithms, particularly the trade-offs between floating- and fixed-point arithmetic when targeting hardware implementations. In this work, two widely used blind equalization algorithms, the Constant Modulus Algorithm (CMA) and the Multi-Modulus Algorithm (MMA), were implemented on a low-cost Ultra96 SoC-FPGA to analyze the effect of a fixed-point representation. A multi-objective Design Space Exploration methodology was applied to minimize hardware utilization while maintaining reliable transmission performance. Resource consumption, latency, and throughput were measured across different binary formats using the Minimum Mean Square Error (MMSE) criterion. Parallelization techniques were incorporated to improve throughput. The DSE generated comprehensive performance surfaces quantifying latency, MMSE convergence, and FPGA resource utilization (DSP48E/FF/LUT/BRAM) across fixed-point formats, achieving optimal 4 MS/s throughput configurations. Although this throughput is naturally lower than the Gigabit speeds required in backbone optical networks, the results demonstrate the effectiveness of numerical representation optimization in resource-constrained SoC-FPGA devices, offering a practical approach for real-time Edge and IoT implementations where cost and hardware limitations are critical. Full article

The integration of blockchain technology into Cyber–Physical Systems (CPS) offers decentralized resilience against data manipulation. This also introduces stochastic consensus latencies that threaten real-time control stability. We present a Stochastic-Aware Blockchain Predictive Control (SAB-PC) framework, which models blockchain-induced jitter as a state-dependent Markovian process, and embeds it within a Markovian Jump Linear System (MJLS) formulation. Using mode-dependent Linear Matrix Inequalities (LMIs), we derive Mean Square Stability (MSS) conditions, which capture the interaction between decentralized consensus dynamics and closed-loop control behavior. The framework is validated on the Tennessee Eastman Process (TEP) benchmark, using a calibrated stochastic delay model that reflects realistic blockchain congestion patterns. Our results show that standard blockchain-mediated control architectures become unstable under Practical Byzantine Fault Tolerance (PBFT)-induced quadratic latency growth, whereas SAB-PC maintains stable operation across decentralized networks up to 60 validator nodes. The predictive Safety Runway effectively masks long-tail delay distributions, ensuring real-time feasibility and preserving safe Reactor Pressure trajectories. Under coordinated False Data Injection (FDI) attacks, SAB-PC limits pressure deviations to only 1.2 kPa despite an 8.0 kPa adversarial bias, demonstrating cryptographic and control-theoretic resilience. Full article

High-resolution microdisplay driver applications impose stringent requirements on the static linearity and dynamic performance of digital-to-analog converters (DACs). To meet these requirements, this paper presents a 200 MS/s 12-bit current-steering DAC. To reduce mismatches among high-weight current sources, a split–sort–symmetric grouping calibration (SSSGC) scheme is introduced, in which each most-significant-bit (MSB) current source is split into sub-cells and reorganized through sorting and symmetric pairing. This approach improves static linearity without complex current measurement or compensation loops. Additionally, a group-domain dynamic element matching (DEM) technique is employed to randomize current-source selection and suppress harmonic distortion. Designed in a 0.18 μm BCD process, the proposed DAC achieves an integral nonlinearity (INL) of 0.79 LSB, a differential nonlinearity (DNL) of 0.42 LSB, and a spurious-free dynamic range (SFDR) of 74.9 dB at an output signal of 4.05 MHz. Full article

Background/Objectives: Immune checkpoint inhibitors (ICIs) are among the transformative and manageable systemic therapies for several cancer types, including colorectal cancer (CRC). Nevertheless, their clinical benefit is limited to mismatch-deficient or microsatellite instability-high diseases, which represent only a small percentage of cases. Despite this initial major and stringent selection, primary and acquired resistance remain clinically relevant. Therefore, the identification of additional biomarkers is essential to refine patient selection and guide rational combinational strategies. This review aims to summarize the current evidence regarding established and emerging biomarkers of response and resistance to ICIs in CRC. Methods: This narrative review identified and synthesized relevant clinical trials, translational studies, and reviews through a literature search of emerging biomarkers of immunotherapy response in colorectal cancer. Results: Deficient mismatch repair/high microsatellite instability remains the most reliable predictive biomarker of ICI response, emphasized by high tumor mutational burden, POLE/POLD mutations, and specific tumor microenvironment features. Emerging indicators, including molecular alterations, antigen presentation machinery integrity, PD-L1-mediated signaling, microbiome connections, and circulating tumor DNA kinetics, have demonstrated significant potential as sources for therapeutic response prediction and have informed the development of innovative combination strategies in both MSI-H and MSS CRCs. Conclusions: Immunotherapy response in CRC is determined by a complex interplay between tumor-intrinsic, immune, microenvironmental, and systemic factors. Integrating multiple biomarkers may provide superior stratification and guide therapeutic strategies. Prospective validation and standardized biomarker assessment will be imperative to translate these insights into clinical practice. Full article

In this paper, a 12-bit, 10 MS/s two-step sub-ranging successive approximation register (SAR) analog-to-digital converter (ADC) is proposed. The proposed architecture enables residue amplification within a single-stage SAR ADC by dividing the top-plate sampling node, thereby avoiding the requirement for a multi-stage design. This structure also eliminates gain and offset mismatches between the coarse and fine conversions, enhancing robustness and linearity. Owing to the two-step operation, the total capacitance of the capacitive digital-to-analog converter (CDAC) is reduced by 86% compared to that of a conventional SAR ADC with the same unit-capacitor size. In addition, the residue amplifier drives only one-fourth of the total CDAC capacitance, significantly relaxing its power consumption. A prototype fabricated in a 65 nm CMOS process occupies an area of 252 $\mathsf{\mu }$m × 227 $\mathsf{\mu }$m and demonstrates a signal-to-noise and distortion ratio (SNDR) of 65.7 dB at Nyquist-rate input. The total power consumption is 227.7 $\mathsf{\mu }$W under a 1.2 V supply, resulting in a Walden figure of merit (FoM) of 14.5 fJ/conversion step. These results confirm competitive performance and energy efficiency, even with the use of an analog residue amplifier. Full article

Musculoskeletal symptoms (MSS) and sleep problems are prevalent in nurses. Evidence exploring associations between sleep and MSS in nurses is limited by self-reported sleep measures and recalling MSS over a long period. The purpose of this study was to examine the relationship between MSS and sleep in nurses using objective sleep measures and real-time MSS assessment. This 7-day observational study included 31 nurses who work day shifts. Sleep duration and efficiency were measured using accelerometers, and MSS were reported using ecological momentary assessment. Sleep metrics and MSS were compared between workdays and days off, and a regression model analyzed the effect of sleep duration on MSS while controlling for age and body mass index (BMI). On average, nurses did not sleep the minimum recommended duration of 7 h (6.28, SD = 1.31), and they slept significantly less prior to a workday (5.98 h, SD = 1.12) than a day off work (6.69 h, SD = 1.43) (t(185) = −5.92, p < 0.0001). Short sleep duration was associated with 18% higher MSS when controlling for age and BMI (t(822) = 2.63, p = 0.009). Understanding the association between sleep and MSS is important to healthcare organizations and policy makers because sleep is essential for health and recovery, and occupational characteristics, such as shift length and consecutive shifts, influence sleep. Nurse fatigue is detrimental to patient safety and the health of the nursing workforce, and musculoskeletal problems contribute to nurse attrition. This study may inform future research on organizational policies related to nurse fatigue and musculoskeletal symptoms. Full article

Background: Marinesco–Sjögren syndrome (MSS, MIM #248800) is a condition that is characterized by biallelic pathogenic variants in the SIL1 gene. Manifestations include congenital cataracts, cerebellar ataxia, progressive muscle weakness and skeletal deformities, delay in psychomotor development, hypergonadotropic hypogonadism and short stature. Muscular involvement has been extensively discussed as a clinical finding but there is little literature on muscle imaging. The aim of this paper is to systematically review muscular imaging techniques in MSS reported in the literature, and to describe the clinical and imaging features of two pediatric subjects with MSS. Methods: Having searched through three electronic databases (PubMed, Scopus and Web of Science) two articles, written in English, describing twelve patients with MSS mutations on whom muscle MRI imaging was performed, were selected. In addition, two paediatric cases (brother and sister) with Marinesco–Sjögren syndrome (MSS) and MRI muscle findings were added. Data on type of study, cohort characteristics, type of mutation, neuromuscular signs and symptoms, imaging assessment, electrophysiological findings, biopsies, CNS symptoms, ocular signs and muscle imaging data were collected and stored in a table. Results: Of the 239 articles examined, only 3 used a muscle imaging technique to describe myopathy in MSS; one used a CT while another a muscle MRI. All 14 patients showed signs of fatty replacement. The infiltration mainly affected the lower limbs, but involvement in the upper limb was described in some adult patients. Conclusions: Performing a muscle MRI in MSS can lead to the early identification of muscle involvement and may be a useful biomarker to monitor disease progression. Full article

Music source separation (MSS) focuses on decomposing a mixed audio signal into individual instrumental components and is increasingly relevant for music production, restoration, remixing, education, and music information retrieval. Deep learning methods, particularly U-Net architectures operating on time–frequency representations, have recently advanced the state of the art beyond traditional signal-processing techniques. This work presents an optimized multi-source U-Net model for separating selected musical instruments from stereo mixtures. The system uses magnitude spectrograms generated by the short-time Fourier transform and is trained and evaluated on the MUSDB18 dataset. We systematically examine architectural and training-related factors, including normalization strategies, dropout placement, optimizer selection, loss weighting, data augmentation, and spectrogram-domain modifications. Separation quality is measured using BSS Eval metrics, assessing artifacts, interference, and distortion. Experimental results show that the proposed configuration achieves competitive performance relative to established convolutional and U-Net-based open-source systems, especially in terms of vocal track separation, offering practical insights into designing efficient models for multi-instrument separation. Full article

Parkinson’s disease (PD) is characterized by asymmetric motor symptoms (MSs), which may influence non-motor symptoms (NMSs). This study investigated the relationship between NMSs and the neurometabolic profile of the substantia nigra (SN) and globus pallidus (GP) of patients with PD, examining how these associations vary according to MS asymmetry. Forty-three PD patients (20 with right-predominant motor symptoms—RPD, and 23 with left-predominant motor symptoms—LPD) and 20 healthy controls (HCs) underwent single-voxel proton magnetic resonance spectroscopy, along with comprehensive clinical assessments of MSs and NMSs. Compared with HCs, PD patients showed higher N-acetylaspartate (NAA) levels in the SN, lower myo-inositol (Ins) levels in both sides of the SN, and higher glutamate/glutamine (Glx) levels in the right GP. Choline (Cho) in the left GP was positively associated with cognitive performance. In LPD patients, compared with HCs, NAA levels were increased in the right SN, whereas Ins levels were reduced in both hemispheres. These patients reported higher anxiety and exhibited marked hemispheric asymmetry of SN NAA. In this group, higher NAA levels in the right SN were associated with fewer sleep disturbances, while Ins in the right GP was related to both cognitive function and NMS severity. RPD patients showed elevated Glx levels in the right GP compared with HCs, with no significant hemispheric differences in metabolite levels. Nevertheless, Cho in the right SN was positively associated with sleep disturbances. Overall, these findings suggest that motor asymmetry in PD influences the neurometabolic correlates of NMSs, revealing distinct metabolic-clinical profiles in RPD and LPD patients. Full article

Colibactin, a genotoxin produced by pks⁺ E. coli, imprints highly specific mutational signatures SBS88 and ID18 in colorectal cancer (CRC) and even in normal colonic crypts. Population-scale analyses show these signatures are enriched in early-onset CRC, vary geographically, and are imprinted early during tumor evolution, where probabilistic attribution indicates that colibactin contributes to a measurable fraction of APC driver mutations in colibactin-positive cancers. Beyond colibactin, Fusobacterium nucleatum exerts clade-specific effects on tumor ecology and therapy response, with data supporting both chemoresistance and sensitization to anti-PD-1 in microsatellite stable (MSS) CRC. This article covers mechanistic, genomic, and molecular epidemiology evidence, outlines analytic standards for signature detection (whole-genome sequencing (WGS)/whole-exome sequencing (WES), single-sample fitting, and limits at low mutation counts), and charts translational paths spanning noninvasive screening (stool metagenomics + mutational signatures in tissue/circulating tumor DNA (ctDNA)), risk stratification, and microbial-targeted interventions (antibiotics, phages, ClbP inhibitors). Framing microbiome–genome crosstalk as a tractable axis enables testable clinical hypotheses for precision oncology. Full article

Background/Objective: Effective topical delivery of 4-phenylbutyric acid (4-PBA) for arsenical vesicant-induced skin injury requires nanocarrier systems that maintain physicochemical and chemical stability during extended storage. This study systematically evaluated the six-month stability of five 4-PBA-loaded micro/nanoparticulate formulations—chitosan nanoparticles (N31, N35), emulsomes (E2), microsponges (MSs), and PLGA nanoparticles (P1)—to identify lead candidates suitable for field deployment and foam integration. Methods: Formulations were subjected to ICH-accelerated stability testing at 25 °C/60% RH and 40 °C/75% RH, with monthly evaluation of particle size, polydispersity index, zeta potential, drug content by HPLC, and chemical/thermal stability by FTIR and DSC. Results: N31 demonstrated superior colloidal stability, maintaining particle size within acceptable limits at both conditions despite progressive surface charge neutralization. E2 showed consistent drug content retention and preserved chemical integrity, though moderate vesicle fusion occurred. MS underwent complete physical degradation at 40 °C within the first month, while P1 exhibited hydrolytic degradation with substantial drug loss. N35 showed severe aggregation indicating colloidal instability. Conclusions: N31 and E2 emerged as lead candidates: N31 is recommended for field deployment where environmental control is limited, while E2 is suitable for controlled storage settings prioritizing drug loading capacity. Full article

It has been reported that quantum correction modifies the topological charges of Anti-de-Sitter Reissner–Nordström (AdS-RN) black holes in Kiselev spacetime, yielding new perspectives on topological classification. This leads us to focus on how quantum corrections and other parameters collectively influence the long-term dynamic evolution of strings. First, we analytically examine whether the strings’ motion violates the Maldacena–Shenker–Stanford (MSS) bound. Then, we employ numerical integration to study the influence of various parameters on string chaotic dynamics. Our results demonstrate that the quantum-correction parameter a, the normalization factor c, and black-hole charge Q significantly influence chaotic behavior and the violation of the MSS bound. In particular, as a increases, the system undergoes an order–chaos–order transition, whereas an increase in c or a decrease in Q drives the system from order to chaos. Full article