Early Stage Research Articles

The clinical applications of dual-layer spectral detector CT in digestive system diseases.

Dual-layer spectral detector CT (DLCT) has several advantages in clinical practice, this study aims to reveal the clinical applications of DLCT in digestive system diseases. We searched PubMed and Cochrane Reviews for articles published from January 1, 2010 to May 31, 2024, using the terms "dual-layer spectral detector CT" or "dual-layer CT" combined with "hepatic fat" or "hepatic fibrosis" "hepatocellular carcinoma" or "pancreatic ductal adenocarcinoma" or "pancreatic neuroendocrine tumors" or "gastric cancer" or "colorectal cancer" or "Crohn's disease" or "bowel ischemia" or "acute abdominal conditions". DLCT consists of a top layer sensitive to lower-energy photons and a bottom layer sensitive to higher-energy photons. This configuration enables simultaneous acquisition of two energy spectra from a single X-ray beam ensuring consistent spatial alignment and temporal resolution. Spectral raw images allow image post-processing to improve image quality, reduce radiation doses and contrast media doses, and generate multiple quantitative parameters. It has broad potential for early detection, accurate staging, efficacy assessment, and prognosis prediction of liver, pancreatic, and gastrointestinal diseases, as well as for the assessment of digestive system vasculature. DLCT not only provides valuable information for the clinical diagnosis and therapeutic effect evaluation of digestive system diseases but also may play a more important role in the overall management of digestive diseases and in the decision-making of individualized medicine. Question What are the advantages of DLCT compared to traditional single-energy CT in the early detection, staging, and therapeutic evaluation of digestive system diseases? Findings DLCT enhances image quality, improves tissue characterization, and allows for multi-parametric analysis, making it superior in detecting and evaluating liver, pancreatic, and gastrointestinal diseases. Clinical relevance DLCT provides high-quality, multi-parametric imaging that improves the accuracy of diagnosing digestive diseases, facilitates more precise treatment planning, and enhances monitoring of treatment response, ultimately contributing to better patient management and prognosis.

Risk factors associated with senile cataract causes blindness and management practices in humans: An overview

Cataract is a condition in which lens visualization decreases. In Pulverulent cataract nuclear opaqueness varies among individuals. Blue dot cataract is non-hereditary and extends in earlier stage. Ralliform is an unusual type, like corals, show finger like projections. In severe cataract, methionine, about 60% or more have been originated in membrane in form of methionine sulfoxide and ionine sulfone. Cortical and posterior subcapsular cataracts are strongly associated with the environment, for example, UV exposures, diabetes, and use of medicines. Nuclear cataract is linked with smoking. In normal and cataractous lens, oxidation of methionine and cysteine was described. Cataract is caused by different abnormalities during development, metabolic disorders, and variations by taking drugs and trauma. Age is the main factor contributing to cataract in developed countries. Education, blood pressure, sex, tobacco usage, alcohol consumption, nutrition, UV exposure, diarrhea, diabetes and some medications are some age-related factors. Cataract increases as the age progresses. Light and oxygen is vital to regulate functions of eye. The only cure is the removal of lens by surgery. Globally, intraocular lens (IOL) surgery is used. Cataracts threat can be reduced by avoiding smoking and limiting exposure to UV-B radiations. It is concluded that some risk factors in cataract includes education, blood pressure, sex, tobacco usage, alcohol consumption, nutrition, UV radiations exposure, diarrhea, diabetes and medications. There is no an effective treatment for cataract. Currently, lens surgery is the main treatment included (IOL).

Decay experiments and microbial community analysis of water lily leaf biofilms: Sediment effects on leaf preservation potential.

Understanding the intricate dynamics of sediment-mediated microbial interactions and their impact on plant tissue preservation is crucial for unraveling the complexities of leaf decay and preservation processes. To elucidate the earliest stages of leaf preservation, a series of decay experiments was carried out for three months on Nymphaea water lily leaves in aquariums with pond water and one of three distinctly different, sterilized, fine-grained substrates-commercially purchased kaolinite clay or fine sand, or natural pond mud. One aquarium contained only pond water as a control. We use 16S and ITS rRNA gene amplicon sequencing to identify and characterize the complex composition of the bacterial and fungal communities on leaves. Our results reveal that the pond mud substrate produces a unique community composition in the biofilms compared to other substrates. The mud substrate significantly influences microbial communities, as shown by the correlation between high concentrations of minerals in the water and bacterial abundance. Furthermore, more biofilm formers are observed on the leaves exposed to mud after two months, contrasting with declines on other substrates. The mud substrate also enhanced leaf tissue preservation compared to the other sediment types, providing insight into the role of sediment and biofilms in fossilization processes. Notably, leaves on kaolinite clay have the fewest biofilm formers by the end of the experiment. We also identify key biofilm-forming microbes associated with each substrate. The organic-rich mud substrate emerges as a hotspot for biofilm formers, showing that it promotes biofilm formation on leaves and may increase the preservation potential of leaves better than other substrates. The mud's chemical composition, rich in minerals such as silica, iron, aluminum, and phosphate, may slow or suspend decay and facilitate biomineralization, thus paving the way toward leaf preservation. Our study bridges the information gap between biofilms observed on modern leaves and the mineral encrustation on fossil leaves by analyzing the microbial response in biofilms to substrate types in which fossil leaves are commonly found.

Locus coeruleus signal intensity and emotion regulation in agitation in Alzheimer’s disease

Abstract Hyperphosphorylated tau accumulation is seen in the noradrenergic locus coeruleus from the earliest stages of Alzheimer’s disease onwards and has been associated with symptoms of agitation. It is hypothesized that compensatory locus coeruleus-noradrenaline system overactivity and impaired emotion regulation could underlie agitation propensity, but to our knowledge this has not previously been investigated. A better understanding of the neurobiological underpinnings of agitation would help the development of targeted prevention and treatment strategies. Using a sample of individuals with amnestic mild cognitive impairment and probable mild Alzheimer’s disease dementia from the German Center for Neurodegenerative Diseases (DZNE)-Longitudinal Cognitive Impairment and Dementia (DELCODE) study cohort (N=309, aged 67-96 years, 51% female), we assessed cross-sectional relationships between a latent factor representing the functional integrity of an affect-related executive regulation network and agitation point prevalence and severity scores. In a subsample of individuals with locus coeruleus MRI imaging data (N=37, aged 68-93 years, 49% female), we also investigated preliminary associations between locus coeruleus MRI contrast ratios (a measure of structural integrity, whole or divided into rostral, middle, and caudal thirds) and individual affect-related regulation network factor scores and agitation measures. Regression models controlled for effects of age and clinical disease severity and, for models including resting state functional MRI connectivity variables, grey matter volume and education years. Agitation point prevalence showed a positive relationship with a latent factor representing the functional integrity (and a negative relationship with a corresponding structural measure) of the affect-related executive regulation network. Locus coeruleus MRI contrast ratios were positively associated with agitation severity (but only for the rostral third, in N=13) and negatively associated with the functional affect-related executive regulation latent factor scores. Resting-state functional connectivity between a medial prefrontal cortex region and left amygdala was related to locus coeruleus MRI contrast ratios. These findings implicate the involvement of locus coeruleus integrity and emotion dysregulation in agitation in Alzheimer’s disease and support the presence of potential compensatory processes. At the neural level, there may be a dissociation between mechanisms underlying agitation risk per se and symptom severity. Further studies are needed to replicate and extend these findings, incorporating longitudinal designs, measures of autonomic function and non-linear modeling approaches to explore potential causal and context-dependent relationships across Alzheimer’s disease stages.

X-point radiator control and its dynamics in ASDEX Upgrade and JET deuterium–tritium discharges

Abstract Control of heat exhaust is essential for the operation of power producing fusion reactors. Here, we present results of heat exhaust feedback control experiments in JET and AUG. In JET, we demonstrate the first X-point radiator (XPR) control in DD and DT discharges using argon seeding. In AUG, we improve the XPR control with nitrogen seeding, resulting in achieving the first detached L-H and H-L transition (in a single discharge). The controllers are designed using a model-based design procedure. The required models are obtained experimentally using perturbative (system identification) experiments. We study the dynamic response of the XPR to various seeding species and varying operating conditions. We find that the sensitivity (relative gain) of the XPR varies as function the height of the radiator inside the confined region but that the relative phase is consistent for all operating points. In AUG, the XPR is also less sensitive to impurity seeding changes for higher heating powers. In JET, we show that the XPR dynamics are the same for DD and DT plasmas. However, we observe that XPR control is only possible with argon and not with neon. The results show that a controller might well be designed in earlier stages of operation of a future device, but remains applicable and can be further tuned for full power operation.

Reform of the Preliminary Ruling Procedure in the EU Court System

In 2022, the Court of Justice of the European Union announced a new stage of reform of its system. In the face of an increase in the number of cases under consideration it is designed to maintain a professional and thorough approach to disputes resolution while reducing the time of legal proceedings. The changes are based on the new competence of the General Court to deal with requests under preliminary ruling procedure and certain other categories of disputes, as well as obtaining more freedom in matters of internal organization and the establishment of a permanent position of Advocate General. Taking into account the scientific and educational literature already published in Russia on the basics of the Court of Justice of the EU, the authors focused their attention on current issues and prospects for the development of the EU judicial system. The purpose of the article is a doctrinal study of the reasons that led to this reform, an analysis of the final text of the agreed draft regulation, as well as an overview of the measures that were implemented by the European Court of Justice at earlier stages and the reasons why they were insufficient. The authors consider new categories of cases, procedural guarantees to maintain uniformity of judicial practice and the stages of discussion of the draft regulation, which took place in 2023 in the EU institutions responsible for the adoption of the new legislation.

Synthesis and Preclinical Evaluation of Dual-Specific Probe Targeting Glypican-3 and Prostate-Specific Membrane Antigen for Hepatocellular Carcinoma PET Imaging.

Positron emission tomography (PET) is a promising modality for early diagnosis, accurate detection, and staging of hepatocellular carcinoma (HCC). Hereby, a dual-specific probe targeting Glypican-3 (GPC3) and prostate-specific membrane antigen (PSMA) was evaluated for HCC PET imaging. The probe was prepared by conjugating TJ12P2, a GPC3-targeting peptide previously reported by our group, to a highly potent PSMA inhibitor via a polyethylene glycol linker and further tethered to the 1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA) chelator. The resultant probe, NOTA-TJ12P2-PSMA, abbreviated as T2P, was labeled with gallium-68 and fluorine-18, respectively, and evaluated in murine HCC models of various levels of GPC3 and PSMA expression. Targeting specificity was confirmed by blocking studies. The synthesized [68Ga]Ga-T2P and [18F]AlF-T2P were stable in saline and fetal bovine serum for over 2 h, and bound to their respective targets with high affinity and specificity in cell assays. PET imaging at 60 min postinjection (p.i.) showed that [68Ga]Ga-T2P exhibited higher uptake (1.75 ± 0.16%ID/g) in Huh7 models with high expression of GPC3 and PSMA than gallium-68 labeled TJ12P2 (1.25 ± 0.07%ID/g, p < 0.01) or gallium-68 labeled PSMA-617 (1.07 ± 0.06%ID/g, p < 0.001). The uptake of [68Ga]Ga-T2P in Huh7 tumors was higher than that in PC-3 tumors with low expression of GPC3 or PSMA (0.55 ± 0.24%ID/g, p < 0.01). The uptake of [18F]AlF-T2P or [68Ga]Ga-T2P in the Huh7 tumor was substantially blocked by TJ12P2, TJ12P2 + PSMA, or T2P, but only partially blocked by PSMA. And the PSMA and TJ12P2 monomer blocking effect was less than that of TJ12P2 + PSMA and T2P. [18F]AlF-T2P had higher tumor-to-muscle ratios than [68Ga]Ga-T2P at 90 min postinjection (4.31 ± 0.10 vs 3.80 ± 0.17, p < 0.05) in Huh7 tumor models. To conclude, radiolabeled T2P exhibited a higher uptake and longer retention in Huh7 tumors than its monomeric counterparts. PET imaging via gallium-68 and fluorine-18 labeled T2P showed a similar imaging quality with comparable signal-to-background ratios. Our results demonstrate that T2P is a promising tool for future clinical diagnosis of HCC.

Engagement With Daily Symptom Reporting, Passive Smartphone Sensing, and Wearable Device Data Collection During Chemotherapy: Longitudinal Observational Study.

Chemotherapy can cause symptoms that impair quality of life and functioning. Remote monitoring of daily symptoms and activity during outpatient treatment may enable earlier detection and management of emerging toxicities but requires patients, including older and acutely ill patients, to engage with technology to report symptoms through smartphones and to charge and wear mobile devices. This study aimed to identify factors associated with participant engagement with collecting 3 data streams (ie, daily patient-reported symptom surveys, passive smartphone sensing, and a wearable Fitbit device [Google]) during chemotherapy. We enrolled 162 patients receiving outpatient chemotherapy into a 90-day prospective study. Patients were asked to install apps on their smartphones to rate daily symptoms and to collect passive sensor data and to wear a Fitbit device for the duration of the study. Participants completed baseline demographic and quality of life questionnaires, and clinical information was extracted from the electronic medical record. We fit a series of logistic generalized estimating equations to evaluate the association between demographic and clinical factors and daily engagement with each data stream. Participants completed daily surveys on 61% (SD 27%) of days and collected sufficient smartphone data and wearable sensor data on 73% (SD 35%) and 70% (SD 33%) of enrolled days, respectively, on average. Relative to White participants, non-White patients demonstrated lower odds of engagement with both symptom surveys (odds ratio [OR] 0.49, 95% CI 0.29-0.81; P=.006) and wearable data collection (OR 0.35, 95% CI 0.17-0.73; P=.005). Patients with stage 4 cancer also exhibited lower odds of engagement with symptom reporting than those with earlier stage disease (OR 0.69, 95% CI 0.48-1.00; P=.048), and patients were less likely to complete symptom ratings on the weekend (OR 0.90, 95% CI 0.83-0.97; P=.008). Older patients (OR 1.03, 95% CI 1.01-1.06; P=.01) and those who reported better cognitive functioning at study entry (OR 1.18, 95% CI 1.03-1.34; P=.02) were more likely to engage with Fitbit data collection, and patients who reported higher levels of depressive symptoms were less likely to engage with smartphone data collection (OR 1.18, 95% CI 1.03-1.36; P=.02). Remote patient monitoring during chemotherapy has the potential to improve clinical management, but only if patients engage with these systems. Our results suggest significant associations between demographic and clinical factors and long-term engagement with smartphone and wearable device assessments during chemotherapy. Non-White participants, those with metastatic cancer, or those with existing cognitive impairment may benefit from additional resources to optimize engagement. Contrary to hypotheses, older adults were more likely than younger adults to engage consistently with wearable device assessments.

Prioritizing Speech Test Cases

As automated speech recognition (ASR) systems gain widespread acceptance, there is a pressing need to rigorously test and enhance their performance. Nonetheless, the process of collecting and executing speech test cases is typically both costly and time-consuming. This presents a compelling case for the strategic prioritization of speech test cases, which consist of a piece of audio and the corresponding reference text . The central question we address is: In what sequence should speech test cases be collected and executed to identify the maximum number of errors at the earliest stage? In this study, we introduce Prophet ( PR i O ritising s P eec H t E s T cases), a tool designed to predict the likelihood that speech test cases will identify errors. Consequently, Prophet can assess and prioritize these test cases without having to run the ASR system, facilitating large-scale analysis. Our evaluation encompasses \(6\) distinct prioritization techniques across \(3\) ASR systems and \(12\) datasets. When constrained by the same test budget, our approach identified \(15.44\%\) more misrecognized words than the leading the state-of-the-art method. We select top-ranked speech test cases from the prioritized list to fine-tune ASR systems and analyze how our approach can improve the ASR system performance. Statistical evaluations show that our method delivers a considerably higher performance boost for ASR systems compared to established baseline techniques. Moreover, our correlation analysis confirms that fine-tuning an ASR system with a dataset where the model initially underperforms tends to yield greater performance improvements.

Acute resistance to BET inhibitors remodels compensatory transcriptional programs via p300 coactivation.

Initial clinical trials with drugs targeting epigenetic modulators - such as bromodomain and extraterminal protein (BET) inhibitors - demonstrate modest results in acute myeloid leukemia (AML). A major reason for this involves an increased transcriptional plasticity within AML, which allows cells to escape the therapeutic pressure. In this study, we investigated immediate epigenetic and transcriptional responses following BET inhibition and could demonstrate that BET inhibitor-mediated release of BRD4 from chromatin is accompanied by an acute compensatory feedback that attenuates down-regulation, or even increases expression, of specific transcriptional modules. This adaptation is marked at key AML maintenance genes and is mediated by p300, suggesting a rational therapeutic opportunity to improve outcomes by combining BET- and p300- inhibition. p300 activity is required during all steps of resistance adaptation, however, the specific transcriptional programs that p300 regulates to induce resistance to BET inhibition differ in part between AML subtypes. As a consequence, in some AMLs the requirement for p300 is highest during earlier stages of resistance to BET inhibition, where p300 regulates transitional transcriptional patterns that allow leukemia-homeostatic adjustments. In other AMLs, p300 shapes a linear resistance to BET inhibition and remains crucial throughout all stages of the evolution of resistance. Altogether, our study elucidates the mechanisms that underlie an "acute" state of resistance to BET inhibition, achieved through p300 activity, and how these mechanisms remodel to mediate "chronic" resistance. Importantly, our data also suggest that sequential treatment with BET- and p300-inhibition may prevent resistance development, thereby improving outcomes.

Early diagnosis of Alzheimer’s disease: potential of &lt;sup&gt;18&lt;/sup&gt;F-FDG PET as a biomarker of neurodegeneration

BACKGROUND: Dementia is considered one of the most actual medical problems of our time, being one of the main causes of disability among the elderly, and its prevalence will only increase in the coming years. The first place among conditions leading to dementia is given to Alzheimer’s disease (up to 70%). The effectiveness of Alzheimer’s disease therapy largely depends on the timeliness of diagnosis, which leads to the need to search for diagnostic markers that allow to detect the disease at the earliest stages. AIM: To evaluate the possibilities of using 18F-FDG PET for the early diagnosis of Alzheimer’s disease. MATERIALS AND METHODS: Cerebral metabolism was assessed using positron emission tomography with 18F-FDG. A total of 183 patients were divided into groups depending on their diagnosis and the severity of cognitive impairment. RESULTS: A characteristic pattern of cerebral metabolic disorders has been established in patients with Alzheimer’s disease. It can be detected in the early pre-dementia stages and has developmental features as the disease progresses. The pattern was characterized by bilateral hypometabolism in the parietal and temporal cortex with a predominance in its mediobasal sections. An important marker of the development of the neurodegenerative process was a metabolic disorder of the cingulate gyrus, the posterior sections of which are affected already at the earliest stages of the disease, while the involvement of its anterior sections reflects the transition to the stage of severe dementia. Described metabolic disorders prevailed in the dominant (left) brain hemisphere at all stages of the disease. CONCLUSION: Currently 18F-FDG PET can be considered the most informative of the available methods for the early diagnosis of Alzheimer’s disease which have a fairly high degree of accuracy.

Prevalence of measurable residual disease in patients with refractory/relapsed multiple myeloma who reached complete response: a cross-sectional multicentric study

BackgroundMultiple myeloma (MM) is an incurable hematologic malignancy, and even though the complete response (CR) rate has been growing, a high percentage of patients continues to relapse. Recent research showed that most relapses may be related to the persistence of measurable residual disease (MRD). In this study, we intended to evaluate the MRD status in MM patients who reached CR in their second or third lines of treatment.MethodsThis was a cross-sectional, multicentre, non-interventional study to describe the MRD status in patients with relapsed or refractory MM (rrMM), with documented CR; adult male and female patients, from 11 Portuguese sites, in their second or third line of treatment were included. Bone marrow MRD was assessed through next-generation flow cytometry (NGF) technology.ResultsAmong the 68 subjects who gave informed consent, 48 were considered eligible for the study. Of the 48 subjects with confirmed CR, 31 (64.6%) had undetectable MRD levels. The incidence of undetectable MRD was lower in International Staging System (ISS) III patients compared with ISS I/II patients (60% vs. 70.8%; p = 0.45), and lower in patients treated without daratumumab-containing regimens compared with those treated with daratumumab-containing regimens (57.1% vs. 75.0%; p = 0.30). Notably, despite the small sample size, the incidence of undetectable MRD was significantly lower in patients with high-risk cytogenetics compared to those with standard risk (33.3% vs. 76.0%; p = 0.04).DiscussionOur results highlight the possibility of achieving undetectable MRD in the rrMM setting, especially in earlier stages and with highly effective protocols. We expect that this work leverages the implementation of larger real-world evidence studies in rrMM patients, in which MRD may also be defined as a primary endpoint.

Global longitudinal strain in pre-symptomatic patients with mutation for transthyretin amyloidosis

BackgroundHereditary transthyretin (ATTRv) amyloidosis is rare, autosomal dominant disease with a fatal outcome if left untreated. Early stages detection is crucial for intervention. We aimed identifying early indexes of cardiac involvement and their eventual correlation with neurological indexes, in pre-symptomatic subjects with TTR gene mutation.MethodsSixteen TTR-mutation carriers (mean age 51 ± 9 years, 6 males, 7 with Val30Met and 9 with Phe64Leu mutation) without left ventricular hypertrophy were studied. Predicted Age of Disease Onset (PADO) and time to PADO (Time-to PADO = PADO-age at evaluation) were computed. Subjects underwent: cardiological and echocardiographic assessment including global longitudinal strain (GLS); tactile and thermal quantitative sensory testing (QST); Perugini score by bone scintigraphy.ResultsTime to PADO was 30 ± 15 years. Nine subjects showed abnormal GLS (> −20%), unrelated to age, LVMi, MWT, E/e’, NT-proBNP or Time-to PADO. QST findings were abnormal in most subjects. At a worse cold pain threshold corresponded a worse GLS (r = 0.786, p < 0.001). Perugini score was positive in 1 subject.ConclusionsGLS and QST findings support an early involvement of heart and small nerve fibers even many years before PADO. Interestingly, cardiac impairment seems to parallel that of small, nerve fibers, at least in the earliest stage of disease.

Cervical Cancer 2010-2019: An Upper Midwest Catchment of 40,000 Square Miles.

American Indian (AI) women have a higher incidence and mortality from cervical cancer than non-Hispanic White (NHW) women in the US. Our purpose is to detail the clinical events in the cervical cancer prevention continuum among the AI and White women with cervical cancer on the US frontier. A cancer center with a nearly 40,000 square-mile catchment area maintained a detailed cancer registry connected to the clinic records of all cervical cancer patients between 2010-2019. This catchment area provided records of both an AI and a White population. Descriptive and inferential statistics and modeling predictions detailed the prevention continuum. Among the 126 with cervical cancer, 20% were AI, and 78% were White. Sixty percent did not participate in cervical cancer screening within the 5 years before their diagnosis, and on average, 9.2 years passed since the last cervical cancer screening. 91% presented with symptoms, and most women presented with 2 or more symptoms. Thirteen percent underwent a colposcopic diagnostic step, significantly delaying the time to diagnosis compared to other diagnostic steps. Sixty-nine percent of the histopathologic diagnoses were squamous cell carcinoma, and 27% were adenocarcinoma. Forty-nine percent presented at stage I regardless of histopathology. Chemotherapy and radiation therapy were most commonly combined. Sixty-three percent of the population survived, and 42% survived at least 3 years from diagnosis. Younger age and earlier stages at diagnosis were the significant adjusted predictors of survival. Our detailed cervical cancer prevention continuum events provide new data questioning the use of colposcopy for women symptomatic at presentation.

Neuroimaging techniques, gene therapy, and gut microbiota: frontier advances and integrated applications in Alzheimer's Disease research.

Alzheimer's Disease (AD) is a neurodegenerative disorder marked by cognitive decline, for which effective treatments remain elusive due to complex pathogenesis. Recent advances in neuroimaging, gene therapy, and gut microbiota research offer new insights and potential intervention strategies. Neuroimaging enables early detection and staging of AD through visualization of biomarkers, aiding diagnosis and tracking of disease progression. Gene therapy presents a promising approach for modifying AD-related genetic expressions, targeting amyloid and tau pathology, and potentially repairing neuronal damage. Furthermore, emerging evidence suggests that the gut microbiota influences AD pathology through the gut-brain axis, impacting inflammation, immune response, and amyloid metabolism. However, each of these technologies faces significant challenges, including concerns about safety, efficacy, and ethical considerations. This article reviews the applications, advantages, and limitations of neuroimaging, gene therapy, and gut microbiota research in AD, with a particular focus on their combined potential for early diagnosis, mechanistic insights, and therapeutic interventions. We propose an integrated approach that leverages these tools to provide a multi-dimensional framework for advancing AD diagnosis, treatment, and prevention.

Comparing E-MOSAICS predictions of high-redshift proto-globular clusters with JWST observations in lensed galaxies

ABSTRACT High-resolution imaging and strong gravitational lensing of high-redshift galaxies have enabled the detection of compact sources with properties similar to nearby massive star clusters. Often found to be very young, these sources may be globular clusters detected in their earliest stages. In this work, we compare predictions of high-redshift ($z \sim 1$–10) star cluster properties from the E-MOSAICS simulation of galaxy and star cluster formation with those of the star cluster candidates in strongly lensed galaxies from JWST and Hubble Space Telescope (HST) imaging. We select galaxies in the simulation that match the luminosities of the majority of lensed galaxies with star cluster candidates observed with JWST. We find that the luminosities, ages, and masses of the brightest star cluster candidates in the high-redshift galaxies are consistent with the E-MOSAICS model. In particular, the brightest cluster ages are in excellent agreement. The results suggest that star clusters in both low- and high-redshift galaxies may form via common mechanisms. However, the brightest clusters in the lensed galaxies tend to be $\approx 1$–$1.5 \, \rm {mag}$ brighter and $\approx 0.5$ dex more massive than the median E-MOSAICS predictions. We discuss the large number of effects that could explain the discrepancy, including simulation and observational limitations, stellar population models, cluster detection biases, and nuclear star clusters. Understanding these limitations would enable stronger tests of globular cluster formation models.

Longitudinal evaluation of the early auditory gamma-band response and its modulation by attention in first-episode psychosis.

Executive control over low-level information processing is impaired proximal to psychosis onset with evidence of recovery over the first year of illness. However, previous studies demonstrating diminished perceptual modulation via attention are complicated by simultaneously impaired perceptual responses. The present study examined the early auditory gamma-band response (EAGBR), a marker of early cortical processing that appears preserved in first-episode psychosis (FEP), and its modulation by attention in a longitudinal FEP sample. Magnetoencephalography was recorded from 25 FEP and 32 healthy controls (HC) during active and passive listening conditions in an auditory oddball task at baseline and follow-up (4-12 months) sessions. EAGBR inter-trial phase coherence (ITPC) and evoked power were measured from responses to standard tones. Symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS). There was no group difference in EAGBR power or ITPC. While EAGBR ITPC increased with attention in HC, this modulation was impaired among FEP. Diminished EAGBR modulation in FEP persisted at longitudinal follow-up. However, among FEP, recovery of EAGBR modulation was associated with reduced PANSS negative scores. FEP exhibit impaired executive control over the flow of information at the earliest stages of sensory processing within auditory cortex. In contrast to previous work, this deficit was observed despite an intact measure of sensory processing, mitigating potential confounds. Recovery of sensory gain modulation over time was associated with reductions in negative symptoms, highlighting a source of potential resiliency against some of the most debilitating and treatment refractory symptoms in early psychosis.

Application Research Progress of Nanomaterial Graphene and its Derivative Complexes in Tumor Diagnosis and Therapy.

Functional nanomaterial graphene and its derivatives have attracted considerable attention in many fields because of their unique physical and chemical properties. Most notably, graphene has become a research hotspot in the biomedical field, especially in relation to malignant tumors. In this study, we briefly review relevant research from recent years on graphene and its derivatives in tumor diagnosis and antitumor therapy. The main contents of the study include the graphene-derivative diagnosis of tumors in the early stage, graphene quantum dots, photodynamics, MRI contrast agent, acoustic dynamics, and the effects of ultrasonic cavitation and graphene on tumor therapy. Moreover, the biocompatibility of graphene is briefly described. This review provides a broad overview of the applications of graphene and its derivatives in tumors. Conclusion, graphene and its derivatives play an important role in tumor diagnosis and treatment.

Medical Image Classification Using DL-based Feature Extraction in IoMT

Aim:: Recent advances in Artificial Intelligence (AI) and the addition of Deep Learning (DL) have made it possible to analyse both real-time and historical data from the Internet of Things (IoT). Recently, IoT technology has been implemented in healthcare schemes as IoMT to aid in medical diagnoses. Medical image classification is useful for predicting and identifying serious diseases at an early stage, which is crucial in the diagnostic process. Background:: When it comes to managing, treating, and preventing illness, medical photographs are an essential element of a patient’s health record. However, it is a difficult issue in computer-based diagnostics to classify images using efficient characteristics. Objective:: The study aimed to develop a deep learning-based classification model for feature extraction. Methods:: Levy flight optimization is employed to pick the weight for the classification model optimally. At the end of the day, the optimal weight led to a better classification result and a higher degree of precision when analyzing medical photos for disease. Result:: We tested the proposed results in MATLAB and compared them with conventional methods of classification. The suggested model’s best results include 97.71% accuracy on a brain dataset and 97.2% accuracy on an Alzheimer’s disease dataset. Conclusion:: The proposed algorithm’s high rate of convergence proves that it can successfully balance the exploration and exploitation phases by avoiding capturing in local optimization and classifying thresholds rapidly. In light of the need for improved accuracy, precision, and computational speed in clinical picture classification, a novel approach based on soft sets has been presented.

Gene Variant Analysis for the Detection of Hemophilia: A Literature Review

Background:: Proteins act as clotting factors to stop bleeding at the lesion site. This implies that people with hemophilia tend to bleed longer after an injury and are more prone to internal bleeding. Depending on the type of hemophilia, individuals with hemophilia will have lesser amounts of factor VIII or factor IX than people without it. Objective:: By analyzing the gene variant of hemophilia affected patient we can predict the severity of disease at earlier stage which helps to avoid further complications. Methods:: Predicting hemophilia can be achieved through potential technologies like machine learning. Using these technologies, one can detect and predict the severity of hemophilia, such as mild, moderate, or severe. Results:: y comparing the methods used in protein structure analysis, the advantages and limitations of methods used in protein structure analysis are discussed. Conclusion:: The best practices in predicting hemophilia are highlighted in this study and particularly aim at the basic understanding of applying the potential technologies in the prediction of hemophilia and its severity. This study represents recent research on hemophilia and the use of different machine learning techniques (MLT) in this area.