Compositional structural brain signatures capture Alzheimer's genetic risk on brain structure along the disease continuum.

INTRODUCTION: Traditional brain imaging genetics studies have primarily focused on how genetic factors influence the volume of specific brain regions, often neglecting the overall complexity of brain architecture and its genetic underpinnings. METHODS: This study analyzed data from participants across the Alzheimer's disease (AD) continuum from the ALFA and ADNI studies. We exploited compositional data analysis to examine relative brain volumetric variations that (i) differentiate cognitively unimpaired (CU) individuals, defined as amyloid-negative (A-) based on CSF profiling, from those at different AD stages, and (ii) associated with increased genetic susceptibility to AD, assessed using polygenic risk scores. RESULTS: Distinct brain signatures differentiated CU A-individuals from amyloid-positive MCI and AD. Moreover, disease stage-specific signatures were associated with higher genetic risk of AD. DISCUSSION: The findings underscore the complex interplay between genetics and disease stages in shaping brain structure, which could inform targeted preventive strategies and interventions in preclinical AD.

Single-cell genomics and regulatory networks for 388 human brains.

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

An Insertion Within SIRPß1 Shows a Dual Effect Over Alzheimer's Disease Cognitive Decline Altering the Microglial Response.

Background: Microglial dysfunction plays a causative role in Alzheimer's disease (AD) pathogenesis. Here we focus on a germline insertion/deletion variant mapping SIRPß1, a surface receptor that triggers amyloid-ß(Aß) phagocytosis via TYROBP. Objective: To analyze the impact of this copy-number variant in SIRPß1 expression and how it affects AD molecular etiology. Methods: Copy-number variant proxy rs2209313 was evaluated in GERALD and GR@ACE longitudinal series. Hippocampal specimens of genotyped AD patients were also examined. SIRPß1 isoform-specific phagocytosis assays were performed in HEK393T cells. Results: The insertion alters the SIRPß1 protein isoform landscape compromising its ability to bind oligomeric Aß and its affinity for TYROBP. SIRPß1 Dup/Dup patients with mild cognitive impairment show an increased cerebrospinal fluid t-Tau/Aß ratio (p = 0.018) and a higher risk to develop AD (OR = 1.678, p = 0.018). MRIs showed that Dup/Dup patients exhibited a worse initial response to AD. At the moment of diagnosis, all patients showed equivalent Mini-Mental State Examination scores. However, AD patients with the duplication had less hippocampal degeneration (p < 0.001) and fewer white matter hyperintensities. In contrast, longitudinal studies indicate that patients bearing the duplication allele show a slower cognitive decline (p = 0.013). Transcriptional analysis also shows that the SIRPß1 duplication allele correlates with higher TREM2 expression and an increased microglial activation. Conclusions: The SIRPß1 internal duplication has opposite effects over MCI-to-Dementia conversion risk and AD progression, affecting microglial response to Aß. Given the pharmacological approaches focused on the TREM2-TYROBP axis, we believe that SIRPß1 structural variant might be considered as a potential modulator of this causative pathway.

Characterization, Bioactivity, and Biodistribution of 35 kDa Hyaluronan Fragment.

It has been reported that hyaluronic acid (HA) with a 35 kDa molecular weight (HA35) acts biologically to protect tissue from injury, but its biological properties are not yet fully characterized. This study aimed to evaluate the cellular effects and biodistribution of HA35 compared to HA with a 1600 kDa molecular weight (HA1600). We assessed the effects of HA35 and HA1600 on cell migration, NO and ROS generation, and gene expression in cultured macrophages, microglia, and lymphocytes. HA35 was separately radiolabeled with 99mTc and 125I and administered to C57BL/6J mice for in vivo biodistribution imaging. In vitro studies indicated that HA35 and HA1600 similarly enhanced cell migration through HA receptor binding mechanisms, reduced the generation of NO and ROS, and upregulated gene expression profiles related to cell signaling pathways in immune cells. HA35 showed a more pronounced effect in regulating a broader range of genes in macrophages and microglia than HA1600. Upon intradermal or intravenous administration, radiolabeled HA35 rapidly accumulated in the liver, spleen, and lymph nodes. In conclusion, HA35 not only exhibits effects on cellular bioactivity comparable to those of HA1600 but also exerts biological effects on a broader range of immune cell gene expression. The findings herein offer valuable insights for further research into the therapeutic potential of HA35 in inflammation-mediated tissue injury.

Reducing annotation burden in MR: A novel MR-contrast guided contrastive learning approach for image segmentation.

BACKGROUND: Contrastive learning, a successful form of representational learning, has shown promising results in pretraining deep learning (DL) models for downstream tasks. When working with limited annotation data, as in medical image segmentation tasks, learning domain-specific local representations can further improve the performance of DL models. PURPOSE: In this work, we extend the contrastive learning framework to utilize domain-specific contrast information from unlabeled Magnetic Resonance (MR) images to improve the performance of downstream MR image segmentation tasks in the presence of limited labeled data. METHODS: The contrast in MR images is controlled by underlying tissue properties (e.g., T1 or T2) and image acquisition parameters. We hypothesize that learning to discriminate local representations based on underlying tissue properties should improve subsequent segmentation tasks on MR images. We propose a novel constrained contrastive learning (CCL) strategy that uses tissue-specific information via a constraint map to define positive and negative local neighborhoods for contrastive learning, embedding this information in the representational space during pretraining. For a given MR contrast image, the proposed strategy uses local signal characteristics (constraint map) across a set of related multi-contrast MR images as a surrogate for underlying tissue information. We demonstrate the utility of the approach for downstream: (1) multi-organ segmentation tasks in T2-weighted images where a DL model learns T2 information with constraint maps from a set of 2D multi-echo T2-weighted images (n = 101) and (2) tumor segmentation tasks in multi-parametric images from the public brain tumor segmentation (BraTS) (n = 80) dataset where DL models learn T1 and T2 information from multi-parametric BraTS images. Performance is evaluated on downstream multi-label segmentation tasks with limited data in (1) T2-weighted images of the abdomen from an in-house Radial-T2 (Train/Test = 30/20), (2) public Cartesian-T2 (Train/Test = 6/12) dataset, and (3) multi-parametric MR images from the public brain tumor segmentation dataset (BraTS) (Train/Test = 40/50). The performance of the proposed CCL strategy is compared to state-of-the-art self-supervised contrastive learning techniques. In each task, a model is also trained using all available labeled data for supervised baseline performance. RESULTS: The proposed CCL strategy consistently yielded improved Dice scores, Precision, and Recall metrics, and reduced HD95 values across all segmentation tasks. We also observed performance comparable to the baseline with reduced annotation effort. The t-SNE visualization of features for T2-weighted images demonstrates its ability to embed T2 information in the representational space. On the BraTS dataset, we also observed that using an appropriate multi-contrast space to learn T1+T2, T1, or T2 information during pretraining further improved the performance of tumor segmentation tasks. CONCLUSIONS: Learning to embed tissue-specific information that controls MR image contrast with the proposed constrained contrastive learning improved the performance of DL models on subsequent segmentation tasks compared to conventional self-supervised contrastive learning techniques. The use of such domain-specific local representations could help understand, improve performance, and mitigate the scarcity of labeled data in MR image segmentation tasks.

Reduction in the incidence of invasive infections caused by encapsulated bacteria after the onset of the COVID-19 pandemic.

Interaction between severe acute respiratory coronavirus 2 (SARS-CoV-2) and IIEB remains under investigation. Objective: to compare IIEB incidence before and during COVID-19 pandemic, and assess incidence of coinfection with COVID-19 and case fatality. A cross-sectional study was performed on data from a centralized microbiology laboratory serving a network of healthcare centers comprising 713 pediatric and adult inpatient beds, expanded by 20% during the pandemic. Three periods were evaluated: (1) pre-pandemic: March 1, 2019-February 29, 2020; (2) pandemic year 1: March 1, 2020-February 28, 2021; (3) pandemic year 2: March 1, 2021-July 31, 2021. Descriptive statistical analysis was performed. 56 502 samples (96% blood cultures) from 27224 patients were analyzed. Of these, 54 samples (from 54 patients) were positive for encapsulated bacteria. IIEB incidence was: 167.4, 32.6, and 50.4 per 100000 samples for periods 1, 2, and 3, respectively. Twelve IIEB episodes occurred during the pandemic period: 10 Streptococcus pneumoniae, and 2 Haemophilus influenzae, of which 7 were SARS-CoV-2/S. pneumoniae coinfections, with an incidence of 5.68 per 10000 COVID-19-related hospitalizations (0.056%). IIEB case fatality was 31%, 29%, and 60% for each period, respectively, 3/7 patients with coinfection died (43%). Case fatality for invasive pneumococcal disease (IPD) in patients without COVID-19, was 32.5%. Significant reduction in IIEB incidence was observed during the pandemic, coinciding with implementation of containment measures. The incidence of SARS-CoV-2/S. pneumoniae coinfection was low, with higher case fatality than IPD patients without COVID-19.

An eNAMPT-neutralizing mAb reduces post-infarct myocardial fibrosis and left ventricular dysfunction.

Myocardial infarction (MI) triggers adverse ventricular remodeling (VR), cardiac fibrosis, and subsequent heart failure. Extracellular nicotinamide phosphoribosyltransferase (eNAMPT) is postulated to play a significant role in VR processing via activation of the TLR4 inflammatory pathway. We hypothesized that an eNAMPT specific monoclonal antibody (mAb) could target and neutralize overexpressed eNAMPT post-MI and attenuate chronic cardiac inflammation and fibrosis. We investigated humanized ALT-100 and ALT-300 mAb with high eNAMPT-neutralizing capacity in an infarct rat model to test our hypothesis. ALT-300 was 99mTc-labeled to generate 99mTc-ALT-300 for imaging myocardial eNAMPT expression at 2 hours, 1 week, and 4 weeks post-IRI. The eNAMPT-neutralizing ALT-100 mAb (0.4 mg/kg) or saline was administered intraperitoneally at 1 hour and 24 hours post-reperfusion and twice a week for 4 weeks. Cardiac function changes were determined by echocardiography at 3 days and 4 weeks post-IRI. 99mTc-ALT-300 uptake was initially localized to the ischemic area at risk (IAR) of the left ventricle (LV) and subsequently extended to adjacent non-ischemic areas 2 hours to 4 weeks post-IRI. Radioactive uptake (%ID/g) of 99mTc-ALT-300 in the IAR increased from 1 week to 4 weeks (0.54 ± 0.16 vs. 0.78 ± 0.13, P < 0.01). Rats receiving ALT-100 mAb exhibited significantly improved myocardial histopathology and cardiac function at 4 weeks, with a significant reduction in the collagen volume fraction (%LV) compared to controls (21.5 ± 6.1% vs. 29.5 ± 9.9%, P < 0.05). Neutralization of the eNAMPT/TLR4 inflammatory cascade is a promising therapeutic strategy for MI by reducing chronic inflammation, fibrosis, and preserving cardiac function.

Gastrointestinal Foreign Bodies: 14 Years of Experience in a University Clinic

Introduction: Ingesting foreign bodies is a common medical problem, especially in the emergency department. Some small studies describe experiences in this regard. Materials and methods: A descriptive retrospective study included patients with suspected ingestion of foreign bodies admitted to the gastroenterology and GI endoscopy service of the Clínica Universitaria Colombia between January 2007 and August 2020. Results: The age of occurrence of the event was 18 to 95 years, and the average age was 45 years. The foreign bodies ingested and found were variable. The most frequent was fish bones, representing 64.11% of the cases, followed by chicken bones and dietary impaction. Thirty-eight percent of patients required foreign body removal; the most frequently used tool was the foreign body forceps. The primary location was the esophagus in 12.53% of cases, followed by the cricopharynx in 11.18% and the hypopharynx in 10%. Conclusions: The Clínica Universitaria Colombia is a referral site for many gastroenterology emergencies due to its high technological level and extensive human resources. This paper probably describes the largest number of patients with this reason for consultation, which is why this retrospective descriptive study was designed. It shows the demographic characteristics, foreign body types, radiological and endoscopic findings, and associated complications, which help to provide a more accurate knowledge of this pathology.

Introducción: La ingesta de cuerpos extraños es un problema médico frecuente, especialmente en el servicio de urgencias. Existen algunos estudios pequeños que describen las experiencias al respecto. Materiales y métodos: Estudio descriptivo, retrospectivo, en el cual se incluyó a pacientes con sospecha de ingesta de cuerpos extraños, ingresados al servicio de gastroenterología y endoscopia digestiva de La Clínica Universitaria Colombia, entre enero de 2007 y agosto de 2020. Resultados: La edad de ocurrencia del evento se presentó en pacientes desde los 18 hasta los 95 años, y la edad promedio fue de 45 años. Los cuerpos extraños ingeridos y encontrados fueron variables; los más frecuentes fueron la ingesta de espinas de pescado, que representó el 64,11% de los casos, seguido por la ingesta de huesos de pollo y la impactación alimentaria. Un 38% de los pacientes requirieron la extracción de cuerpo extraño y la herramienta usada con mayor frecuencia fue la pinza de cuerpo extraño. La localización principal fue el esófago, en el 12,53% de los casos, seguido por la cricofaringe, en el 11,18%, y la hipofaringe, en el 10%. Conclusiones: La Clínica Universitaria Colombia es un sitio de referencia de una gran cantidad de urgencias en gastroenterología debido a su alto nivel tecnológico y al gran recurso humano que requieren. Este trabajo representa probablemente la cantidad más grande de pacientes con este motivo de consulta, razón por la que se diseñó este estudio descriptivo retrospectivo, que muestra las características demográficas, los tipos de cuerpo extraño, los hallazgos radiológicos y endoscópicos y las complicaciones asociadas, que son de utilidad para tener un conocimiento más real de esta patología.

A fast non-parametric test of association for multiple traits.

The increasing availability of multidimensional phenotypic data in large cohorts of genotyped individuals requires efficient methods to identify genetic effects on multiple traits. Permutational multivariate analysis of variance (PERMANOVA) offers a powerful non-parametric approach. However, it relies on permutations to assess significance, which hinders the analysis of large datasets. Here, we derive the limiting null distribution of the PERMANOVA test statistic, providing a framework for the fast computation of asymptotic p values. Our asymptotic test presents controlled type I error and high power, often outperforming parametric approaches. We illustrate its applicability in the context of QTL mapping and GWAS.

Effects of peripheral electromagnetic stimulation after an eccentric exercise-induced delayed-onset muscle soreness protocol in professional soccer players: a randomized controlled trial.

Introduction: To examine the effects of peripheral electromagnetic stimulation in male professional soccer players on markers of Delayed Onset Muscular Soreness (DOMS), induced by a protocol of exercise (60 min of eccentric and plyometric). Methods: A randomized controlled trial with fourty-five professional soccer players aged 22.33 ± 4.82 years participated in the study. Twenty-three participants were assigned to the experimental group with peripheral electromagnetic stimulation (5 stimulations of 5 s at 100 HZ with 55 s of rest for a total of 5 min of treatment) and the remaining 22 participants were assigned to the control group. Pain pressure threshold (PPT) of the vastus medialis, the Visual Analogue Scale-Fatigue (VAS-F), half squat (HS) test and the maximum voluntary contraction of the quadriceps were assessed. All evaluations were performed before and after 1 h of the eccentric exercise induced DOMS, as well as at post 24-48, and 72 h. Results: Group-by-time interaction was observed in PPT of the vastus medialis (p = 0.040) with a medium effect size (η2 p = 0.069). From 48 to 72 h the experimental group showed an increase of PPT compared to control group (p = 0.015). There was no group-by-time interaction for HS, quadriceps strength and VAS-F (p > 0.05). Discussion: Peripheral electromagnetic stimulation in male professional soccer players did not produce significant improvements in the power and strength of the lower limbs but decreased the peripheral sensitization of the vastus medialis after eccentric exercise protocol. Clinical Trial Registration: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=384050&isReview=true, Identifier: ACTRN12622000841774.

Postnatal catch-up growth in term newborns with altered fetal weight patterns. The GROWIN study.

BACKGROUND: Small for gestational age (SGA) perform a postnatal catch-up growth to recover their genetic trajectory. We studied the postnatal catch-up growth pattern of fetuses born with an appropriate-for-gestational-age (AGA) weight but with fetal growth deceleration (FGD) to explore whether they catch up. METHODS: Nine hundred and sixty-six newborns at Villalba University General Hospital (HUGV), were followed from 34 to 37 weeks to birth. Z-scores, adjusted for sex and age, of weight, length, and BMI at 3, 6, 9, and 12 months were calculated. We define catch-up as an increase in z-score greater than 0.67 SD in the growth curves. RESULTS: AGA FGD had lower mean weight and length than AGA non-FGD at all time points; BMI was lower until 3 months. AGA FGD had a lower weight, length, and BMI z-score (until 9, 6 months, and at birth, respectively) than AGA non-FGD. AGA FGD newborns had a significantly increased likelihood of weight catch-up at 3 months (OR 1.79; 95% CI: 1.16, 2.78; p = 0.009) and BMI in all investigated periods (OR 1.90; 95% CI 1.30, 2.78; p < 0.001 at 3 months), compared to AGA non-FGD newborns. CONCLUSIONS: AGA FGD newborns perform catch-up growth, especially in weight and BMI, in the first year of life, compared to AGA non-FGD. IMPACT: Appropriate-for-gestational-age (AGA) newborns with fetal growth deceleration (FGD), between the third trimester of pregnancy and delivery, present a lower weight and height, during the first year of life, compared to AGA non-FGD. Appropriate-for-gestational-age (AGA) newborns with fetal growth deceleration (FGD), between the third trimester of pregnancy and delivery, present a higher likelihood of weight catch-up in the first 3 months of life and of BMI in the first year compared to AGA non-FGD. AGA FGD experienced early weight and BMI catch-up, especially in the first 3 months of life, like SGA. This finding should be considered in the future follow-up.

Potentially causal associations between placental DNA methylation and schizophrenia and other neuropsychiatric disorders.

Increasing evidence supports the role of placenta in neurodevelopment and potentially, in the later onset of neuropsychiatric disorders. Recently, methylation quantitative trait loci (mQTL) and interaction QTL (iQTL) maps have proven useful to understand SNP-genome wide association study (GWAS) relationships, otherwise missed by conventional expression QTLs. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation (DNAm). We constructed the first public placental cis-mQTL database including nearly eight million mQTLs calculated in 368 fetal placenta DNA samples from the INMA project, ran cell type- and gestational age-imQTL models and combined those data with the summary statistics of the largest GWAS on 10 neuropsychiatric disorders using Summary-based Mendelian Randomization (SMR) and colocalization. Finally, we evaluated the influence of the DNAm sites identified on placental gene expression in the RICHS cohort. We found that placental cis-mQTLs are highly enriched in placenta-specific active chromatin regions, and useful to map the etiology of neuropsychiatric disorders at prenatal stages. Specifically, part of the genetic burden for schizophrenia, bipolar disorder and major depressive disorder confers risk through placental DNAm. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, regional pleiotropic methylation signals associated to the same disorder, and cell type-imQTLs, additionally associated to the expression levels of relevant immune genes in placenta. In conclusion, the genetic risk of several neuropsychiatric disorders could operate, at least in part, through DNAm and associated gene expression in placenta.

A Novel Multi-Objective Binary Chimp Optimization Algorithm for Optimal Feature Selection: Application of Deep-Learning-Based Approaches for SAR Image Classification.

Removing redundant features and improving classifier performance necessitates the use of meta-heuristic and deep learning (DL) algorithms in feature selection and classification problems. With the maturity of DL tools, many data-driven polarimetric synthetic aperture radar (POLSAR) representation models have been suggested, most of which are based on deep convolutional neural networks (DCNNs). In this paper, we propose a hybrid approach of a new multi-objective binary chimp optimization algorithm (MOBChOA) and DCNN for optimal feature selection. We implemented the proposed method to classify POLSAR images from San Francisco, USA. To do so, we first performed the necessary preprocessing, including speckle reduction, radiometric calibration, and feature extraction. After that, we implemented the proposed MOBChOA for optimal feature selection. Finally, we trained the fully connected DCNN to classify the pixels into specific land-cover labels. We evaluated the performance of the proposed MOBChOA-DCNN in comparison with nine competitive methods. Our experimental results with the POLSAR image datasets show that the proposed architecture had a great performance for different important optimization parameters. The proposed MOBChOA-DCNN provided fewer features (27) and the highest overall accuracy. The overall accuracy values of MOBChOA-DCNN on the training and validation datasets were 96.89% and 96.13%, respectively, which were the best results. The overall accuracy of SVM was 89.30%, which was the worst result. The results of the proposed MOBChOA on two real-world benchmark problems were also better than the results with the other methods. Furthermore, it was shown that the MOBChOA-DCNN performed better than methods from previous studies.

Involvement of eNAMPT/TLR4 inflammatory signaling in progression of non-alcoholic fatty liver disease, steatohepatitis, and fibrosis.

Although the progression of non-alcoholic fatty liver disease (NAFLD) from steatosis to steatohepatitis (NASH) and cirrhosis remains poorly understood, a critical role for dysregulated innate immunity has emerged. We examined the utility of ALT-100, a monoclonal antibody (mAb), in reducing NAFLD severity and progression to NASH/hepatic fibrosis. ALT-100 neutralizes eNAMPT (extracellular nicotinamide phosphoribosyltransferase), a novel damage-associated molecular pattern protein (DAMP) and Toll-like receptor 4 (TLR4) ligand. Histologic and biochemical markers were measured in liver tissues and plasma from human NAFLD subjects and NAFLD mice (streptozotocin/high-fat diet-STZ/HFD, 12 weeks). Human NAFLD subjects (n = 5) exhibited significantly increased NAMPT hepatic expression and significantly elevated plasma levels of eNAMPT, IL-6, Ang-2, and IL-1RA compared to healthy controls, with IL-6 and Ang-2 levels significantly increased in NASH non-survivors. Untreated STZ/HFD-exposed mice displayed significant increases in NAFLD activity scores, liver triglycerides, NAMPT hepatic expression, plasma cytokine levels (eNAMPT, IL-6, and TNFα), and histologic evidence of hepatocyte ballooning and hepatic fibrosis. Mice receiving the eNAMPT-neutralizing ALT-100 mAb (0.4 mg/kg/week, IP, weeks 9 to 12) exhibited marked attenuation of each index of NASH progression/severity. Thus, activation of the eNAMPT/TLR4 inflammatory pathway contributes to NAFLD severity and NASH/hepatic fibrosis. ALT-100 is potentially an effective therapeutic approach to address this unmet NAFLD need.

COSIBAS Platform-Cognitive Services for IoT-Based Scenarios: Application in P2P Networks for Energy Exchange.

The revolution generated by the Internet of Things (IoT) has radically changed the world; countless objects with remote sensing, actuation, analysis and sharing capabilities are interconnected over heterogeneous communication networks. Consequently, all of today's devices can connect to the internet and can provide valuable information for decision making. However, the data collected by different devices are in different formats, which makes it necessary to develop a solution that integrates comprehensive semantic tools to represent, integrate and acquire knowledge, which is a major challenge for IoT environments. The proposed solution addresses this challenge by using IoT semantic data to reason about actionable knowledge, combining next-generation semantic technologies and artificial intelligence through a set of cognitive components that enables easy interoperability and integration for both legacy systems and emerging technologies, such as IoT, to generate business value in terms of faster analytics and improved decision making. Thus, combining IoT environments with cognitive artificial intelligence services, COSIBAS builds an abstraction layer between existing platforms for IoT and AI technologies to enable cognitive solutions and increase interoperability across multiple domains. The resulting low-cost cross platform supports scalability and the evolution of large-scale heterogeneous systems and allows the modernization of legacy infrastructures with cognitive tools and communication mechanisms while reusing assets.

PEGylated and Non-PEGylated TCP-1 Probes for Imaging of Colorectal Cancer.

PURPOSE: Previous studies indicate that 99mTc- and fluorescent-labeled c[Cys-Thr-Pro-Ser-Pro-Phe-Ser-His-Cys]OH (TCP-1) peptides were able to detect colorectal cancer (CRC) and tumor-associated vasculature. This study was designed to characterize the targeting properties of PEGylated and non-PEGylated TCP-1 peptides for CRC imaging. PROCEDURES: Cell uptake of cyanine 7 (Cy7)-labeled TCP-1 probes (Cy7-PEG4-TCP-1 and Cy7-TCP-1) was investigated in three CRC cell lines (human, HCT116 and HT29; mouse, CT26). Xenograft and orthotopic CRC tumor models with HCT116 and CT26 cells were used to characterize biodistribution and CRC tumor-targeting properties of TCP-1 fluorescence and radioligand with and without PEGylation, [99mTc]Tc-HYNIC-PEG4-TCP-1 vs. [99mTc]Tc-HYNIC-TCP-1. RESULTS: Fluorescence images showed that TCP-1 probes were distributed in the cytoplasm and nucleus of CRC cells. When CT26 cells were treated with unlabeled TCP-1 peptide prior to the cell incubation with Cy7-PEG4-TCP-1, cell fluorescent signals were significantly reduced relative to the cells without blockade. Relative to Cy7-TCP-1, superior brilliance and visibility of fluorescence was observed in the tumor with Cy7-PEG4-TCP-1 and maintained up to 18 h post-injection. [99mTc]Tc-HYNIC-PEG4-TCP-1 images in xenograft and orthotopic CRC models demonstrated that TCP-1 PEGylation preserved tumor-targeting capability of TCP-1, but its distribution (%ID/g) in the liver and intestine was higher than that of [99mTc]Tc-HYNIC-TCP-1 (1.51 ± 0.29 vs 0.53 ± 0.12, P < 0.01). Better tumor visualization by [99mTc]Tc-HYNIC-TCP-1 was observed in the orthotopic CRC model due to lower intestinal radioactivity. CONCLUSIONS: TCP-1-based probes undergo endocytosis and localize in the cytoplasm and nucleus of human and mouse CRC cells. Tumor detectability of fluorescent TCP-1 peptide with a PEG4 spacer is promising due to its enhanced tumor binding affinity and rapid clearance kinetics from nontumor tissues. Non-PEGylated [99mTc]Tc-HYNIC-TCP-1 exhibits lower nonspecific accumulation in the liver and gastrointestinal tract and might have better capability for detecting CRC lesions in clinical sites. TCP-1 may represent an innovative targeting molecule for detecting CRC noninvasively.

Theory of overparametrization in quantum neural networks.

The prospect of achieving quantum advantage with quantum neural networks (QNNs) is exciting. Understanding how QNN properties (for example, the number of parameters M) affect the loss landscape is crucial to designing scalable QNN architectures. Here we rigorously analyze the overparametrization phenomenon in QNNs, defining overparametrization as the regime where the QNN has more than a critical number of parameters Mc allowing it to explore all relevant directions in state space. Our main results show that the dimension of the Lie algebra obtained from the generators of the QNN is an upper bound for Mc, and for the maximal rank that the quantum Fisher information and Hessian matrices can reach. Underparametrized QNNs have spurious local minima in the loss landscape that start disappearing when M ≥ Mc. Thus, the overparametrization onset corresponds to a computational phase transition where the QNN trainability is greatly improved. We then connect the notion of overparametrization to the QNN capacity, so that when a QNN is overparametrized, its capacity achieves its maximum possible value.

Psychological, Pain, and Disability Factors Influencing the Perception of Improvement/Recovery from Physiotherapy in Patients with Chronic Musculoskeletal Pain: A Cross-Sectional Study.

OBJECTIVES: The aim of this study was to identify the possible relationships between psychological, pain, and disability variables with respect to the perception of change/recovery from physiotherapy in patients with chronic musculoskeletal pain (CMP). METHODS: A cross-sectional observational study was performed with 150 patients. All patients completed a series of self-administered questionnaires and a series of self-reports to quantify the perception of change with respect to the physiotherapy they underwent, the level of disability and pain intensity, the level of fear of movement, the level of catastrophism, the degree of self-efficacy, the level of therapeutic alliance and their adherence to the physiotherapy. RESULTS: The strongest correlations were between the subjective perception of change and the number of sessions, treatment beliefs, self-efficacy, pain intensity, collaboration, and bonding. The linear regression model showed that the number of sessions, treatment beliefs, self-efficacy, compliance, pain intensity, and bonding were predictors of subjective perception of improvement, with 50% of the variance. CONCLUSIONS: Treatment beliefs, therapeutic alliance, degree of self-efficacy, and pain intensity have been shown to be predictors of a subjective perception of improvement in patients with CMP. In turn, multimodal treatments had the greatest positive impact on the subjective perception of improvement.

Classification of Marine Mammals Using the Trained Multilayer Perceptron Neural Network with the Whale Algorithm Developed with the Fuzzy System.

The existence of various sounds from different natural and unnatural sources in the deep sea has caused the classification and identification of marine mammals intending to identify different endangered species to become one of the topics of interest for researchers and activist fields. In this paper, first, an experimental data set was created using a designed scenario. The whale optimization algorithm (WOA) is then used to train the multilayer perceptron neural network (MLP-NN). However, due to the large size of the data, the algorithm has not determined a clear boundary between the exploration and extraction phases. Next, to support this shortcoming, the fuzzy inference is used as a new approach to developing and upgrading WOA called FWOA. Fuzzy inference by setting FWOA control parameters can well define the boundary between the two phases of exploration and extraction. To measure the performance of the designed categorizer, in addition to using it to categorize benchmark datasets, five benchmarking algorithms CVOA, WOA, ChOA, BWO, and PGO were also used for MLPNN training. The measured criteria are concurrency speed, ability to avoid local optimization, and the classification rate. The simulation results on the obtained data set showed that, respectively, the classification rate in MLPFWOA, MLP-CVOA, MLP-WOA, MLP-ChOA, MLP-BWO, and MLP-PGO classifiers is equal to 94.98, 92.80, 91.34, 90.24, 89.04, and 88.10. As a result, MLP-FWOA performed better than other algorithms.

Use of radiolabeled hyaluronic acid for preclinical assessment of inflammatory injury and acute respiratory distress syndrome.

Acute respiratory distress syndrome (ARDS) is accompanied by a dramatic increase in lung hyaluronic acid (HA), leading to a dose-dependent reduction of pulmonary oxygenation. This pattern is associated with severe infections, such as COVID-19, and other important lung injury etiologies. HA actively participates in molecular pathways involved in the cytokine storm of COVID-19-induced ARDS. The objective of this study was to evaluate an imaging approach of radiolabeled HA for assessment of dysregulated HA deposition in mouse models with skin inflammation and lipopolysaccharide (LPS)-induced ARDS using a novel portable intensified Quantum Imaging Detector (iQID) gamma camera system. METHODS: HA of 10 kDa molecular weight (HA10) was radiolabeled with 125I and 99mTc respectively to produce [125I]I-HA10 and [99mTc]Tc-HA10, followed by comparative studies on stability, in vivo biodistribution, and uptake at inflammatory skin sites in mice with 12-O-tetradecanoylphorbol-13-acetate (TPA)-inflamed ears. [99mTc]Tc-HA10 was used for iQID in vivo dynamic imaging of mice with ARDS induced by intratracheal instillation of LPS. RESULTS: [99mTc]Tc-HA10 and [125I]I-HA10 had similar biodistribution and localization at inflammatory sites. [99mTc]Tc-HA10 was shown to be feasible in measuring skin injury and monitoring skin wound healing. [99mTc]Tc-HA10 dynamic pulmonary images yielded good visualization of radioactive uptake in the lungs. There was significantly increased lung uptake and slower lung washout in mice with LPS-induced ARDS than in control mice. Postmortem biodistribution measurement of [99mTc]TcHA10 (%ID/g) was 11.0 ± 3.9 vs. 1.3 ± 0.3 in the ARDS mice (n = 6) and controls (n = 6) (P < 0.001), consistent with upregulated HA expression as determined by enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry (IHC) staining. CONCLUSIONS: [99mTc]Tc-HA10 is promising as a biomarker for evaluating HA dysregulation that contributes to pulmonary injury in ARDS. Rapid iQID imaging of [99mTc]Tc-HA10 clearance from injured lungs may provide a functional template for timely assessment and quantitative monitoring of pulmonary pathophysiology and intervention in ARDS.