Accurate Treatment Research Articles

MR-Safe Cartesian Platform for Active Cardiac Shimming: Preliminary Validation.

Implanted Cardioverter Defibrillators (ICDs) induce a large (100 parts per million) inhomogeneous magnetic field in the magnetic resonance imaging (MRI) scanner which cannot be corrected by the scanner's built-in shim coils, leading to significant image artifacts that can make portions of the heart unreadable. To compensate for the field inhomogeneity, an active shim coil capable of countering the field deviation in user-defined regions was designed that must be optimally placed at patient-specific locations. We aim to develop and evaluate an MR-safe robotic solution for automated shim coil positioning. We designed and fabricated an MR-safe Cartesian platform that holds the shim coil inside the scanner. The platform consists of three lead screw stages actuated by pneumatic motors, achieving decoupled translations of 140 mm in each direction. The platform is made of plastics and fiberglass with the control electronics placed outside the scanner room, ensuring MR safety. Mechanical modeling was derived to provide design specifications. Experiments show that the platform achieves less than 2 mm average motion error and 0.5 mm repeatability in all directions, and reduces the adjustment time from 5 min to a few seconds. Phantom and animal trials were conducted, showing that the proposed system is able to position a heavy shim coil ( kg) for improved ICD artifact suppression. This robotic platform provides an effective method for reliable shim coil positioning inside the scanner. This work contributes to improving cardiac MRI quality that could facilitate accurate diagnosis and treatment planning for patients with implanted ICDs.

Precise photoionisation treatment and hydrodynamic effects in atmospheric modelling of warm and hot Neptunes

Context. Observational breakthroughs in the field of exoplanets in the last decade have motivated the development of numerous theoretical models, such as those describing atmospheres and mass loss, which is believed to be one of the main drivers of planetary evolution. Aims. We outline for which types of close-in planets in the Neptune-mass range the accurate treatment of photoionisation effects is most relevant, particularly with respect to atmospheric mass loss and the parameters relevant for interpreting observations, such as temperature and ion fraction. Methods. We developed the Cloudy e Hydro Ancora INsieme (CHAIN) model, which combines our 1D hydrodynamic upper atmosphere model with the non-local thermodynamical equilibrium (NLTE) photoionisation and radiative transfer code Cloudy accounting for ionisation, dissociation, detailed atomic level populations, and chemical reactions for all chemical elements up to zinc. The hydro-dynamic code is responsible for describing the outflow, while Cloudy solves the photoionisation and heating of planetary atmospheres. We applied CHAIN to model the upper atmospheres of a range of Neptune-like planets with masses between 1 and 50 M⊕, also varying the orbital parameters. Results. For the majority of warm and hot Neptunes, we find slower and denser outflows, with lower ion fractions, compared to the predictions of the hydrodynamic model alone. Furthermore, we find significantly different temperature profiles between CHAIN and the hydrodynamic model alone, though the peak values are similar for similar atmospheric compositions. The mass-loss rates predicted by CHAIN are higher for hot strongly irradiated planets and lower for more moderate planets. All differences between the two models are strongly correlated with the amount of high-energy irradiation. Finally, we find that the hydrodynamic effects significantly impact ionisation and heating. Conclusions. The impact of the precise photoionisation treatment provided by Cloudy strongly depends on the system parameters. This suggests that some of the simplifications typically employed in hydrodynamic modelling might lead to systematic errors when studying planetary atmospheres, even at a population-wide level.

Comparative study of arterial doppler with digital subtraction angiography in lower limb peripheral arterial disease: a protocol

Background One of the serious cardiovascular conditions is peripheral arterial disease; in which distinctive feature is diminished blood supply towards the lower extremities, frequently because of atherosclerotic occlusive disease. Methods We will compare arterial Doppler with digital subtraction angiography in peripheral lower limb occlusive arterial sickness; to determine Peripheral Arterial Disease along with its location and stenosis severity on Duplex Ultra-Sonography and Digital Subtraction Angiography; and to determine the segment-to-segment agreement of the arterial tree within Duplex Ultra-Sonography and Digital Subtraction Angiography. Implications This will encourage the participants for periodic investigation and proper use of medications which will improve hospital/facility outcome. It will be helpful for older individuals how are more susceptible to peripheral artery disease. A fair accurate treatment options will be given to patients. Limitations Findings will only be applicable to our organization because the study will be done at one tertiary care hospital, limiting their external validity and generalizability.

Natural products of plant origin: an emerging therapeutic for dermatomycosis.

Dermatomycosis or superficial mycosis is considered one of the chronic fungal infections and a global challenge for the public health system. The severity of dermatomycosis is proportionately increasing with the emerging population of immunocompromised individuals, and it is becoming more prevalent, even life-threatening, in several tropical countries. In this context, improper long-term treatment with synthetic antifungal drugs and their related side effects imposes additional challenges in treating dermatomycosis. Thus, the present scenario highlights the need for a novel and accurate treatment with minimal or no side effects. The multifaceted therapeutic properties of various natural products have garnered the interest of scientific communities in recent years. Generally, plant-based products have low toxicity levels and offer diverse formulations and unique biomolecules for clinical applicability against dermatomycosis. Thus, this study presents an overview of the pathogenesis and different treatment strategies for dermatomycosis. In addition, we highlight the implementation of natural products of plant origin for treating dermatomycosis infections and reducing adverse events. Further, their mode of action and role in the development of pharmaceutical drugs are discussed.

Clinical Characteristics of Adrenal Hemangioma.

Adrenal hemangioma (AH) is a rare, benign adrenal tumor often detected incidentally by imaging. This retrospective study aimed to investigate the clinical characteristics of AH, including clinical and diagnostic imaging features, to improve the recognition and understanding of AH. We retrospectively analyzed the medical records of patients diagnosed with AH at Peking Union Medical College Hospital between 2008 and 2022. Clinical manifestations, adrenal hormone levels, imaging findings, treatment approaches, and pathological results were collected and analyzed. Of the 7140 adrenal tumor patients, 40 (0.56%) had AH confirmed postoperatively. The mean age at diagnosis was 53.9 years, with a female predominance. Most (70%) were asymptomatic and diagnosed incidentally. Misdiagnosis before surgery was common, most frequently as pheochromocytoma. Imaging characteristics, especially enhanced computed tomography, revealed distinct features based on tumor size. Surgery was the main treatment, with laparoscopic adrenalectomy preferred. This study elucidates the clinical characteristics of AH, including demographics, diagnostic challenges, and imaging features. AH often presents incidentally and is frequently misdiagnosed preoperatively. Recognizing distinct imaging characteristics and appropriate surgical management can enable accurate diagnosis and optimal treatment.

Production of positronium chloride: A study of the charge exchange reaction between Ps and Cl.

We present cross sections for the formation of positronium chloride (PsCl) in its ground state from the charge exchange between positronium (Ps) and chloride (Cl-) in the range of 10 meV-100eV Ps energy. We have used theoretical models based on the first Born approximation in its three-body formulation. We simulated the collisions between Ps and Cl- using abinitio binding energies and positronic wave functions at both the mean-field and correlated levels extrapolated to the complete basis set limit. The accuracy of these abinitio data was benchmarked on the PsF system with the existing highly accurate results, including the very recent quantum Monte Carlo results. We have investigated Ps excited states up to n = 4. The results suggest that the channel Ps(n = 2) is of particular interest for the production of PsCl in the ground state and shows that an accurate treatment of correlation effects (i.e., electron-electron and electron-positron correlations) leads to a significant change in the magnitude of the PsCl production cross section with respect to the mean-field level.

Research advances in Peyronie's disease: a comprehensive review on genomics, pathways, phenotypic manifestation, and therapeutic targets.

Penile induration disease, commonly known as Peyronie's disease (PD), is a connective tissue disorder that affects the penis, leading to the development of fibrous plaques, penile curvature, and erectile dysfunction. PD is a common male reproductive system disease with a complex etiology involving multiple genes, signaling pathways, and different phenotypes. The etiology and pathogenesis of PD remain poorly understood, hindering the development of effective treatment strategies. By understanding the underlying mechanisms of PD, we can pave the way for targeted therapies and improved patient outcomes. We reviewed the epidemiology and pathophysiology of PD. We performed database searches on Google Scholar, PubMed, Medline, and Web of Science from inception to September 2023. The literature reviewed included priapism guidelines, review articles, current trial studies, and various literature related to PD. This article provides a comprehensive overview of the current research progress on the disease, focusing on its genetic factors, signaling pathways, cellular mechanisms, phenotypic manifestations, and therapeutic targets. It can help identify individuals at higher risk, aid in early detection and intervention, and provide insights into fibrosis and tissue remodeling. It can also reveal potential therapeutic targets, guide accurate diagnoses and treatment strategies, and address the impact of the disease on patients' quality of life. By integrating insights from genomics, molecular pathways, clinical phenotypes, and therapeutic potentials, our research aims to achieve a deeper and more comprehensive understanding of PD, propelling the field toward innovative strategies that enhance the lives of those affected by PD. The complex manifestations and pathogenesis of PD necessitate the use of multiple treatment methods for personalized care.

Gastrointestinal Characteristics of Constipation from the Perspectives of Microbiome and Metabolome.

Constipation is one of the most common gastrointestinal complaints. Yet, the underlying mechanisms of constipation remain to be explored deeply. Integration of microbiome and metabolome is powerful and promising to demonstrate characteristics of constipation. This study aimed to characterize intestinal microbiome and metabolome of constipation. In addition, this study revealed the correlations among behaviors, intestinal microbiota, and metabolites interrupted by constipation. Firstly, the constipation model was successfully applied. At the macro level, the ability of learning, memory, locomotor activity, and the defecation index of rats with constipation-like phenotype were characterized. At the micro-level, 16S rRNA sequencing was applied to analyze the intestinal microbiota in rats with constipation-like phenotype. 1H nuclear magnetic resonance (NMR)-based metabolomics was employed to investigate the metabolic phenotype of constipation. In addition, we constructed a correlation network, intuitively showing the correlations among behaviors, intestinal microbiota, and metabolites. Constipation significantly attenuated the locomotor activity, memory recognition, and frequency of defecation of rats, while increased the time of defecation. Constipation significantly changed the diversity of intestinal microbial communities, which correspondingly involved in 5 functional pathways. Besides, 28 fecal metabolites were found to be associated with constipation, among which 14 metabolites were further screened that can be used to diagnose constipation. On top of this, associated networks intuitively showed the correlations among behaviors, intestinal microbiota, and metabolites. The current findings are significant in terms of not only laying a foundation for understanding characteristics of constipation, but also providing accurate diagnosis and treatments of constipation clinically.

The sensitivity of radiobiological models in carbon ion radiotherapy (CIRT) and its consequences on the clinical treatment plan: Differences between LEM and MKM models.

Carbon ion radiotherapy (CIRT) relies on relative biological effectiveness (RBE)-weighted dose calculations. Japanese clinics predominantly use the microdosimetric kinetic model (MKM), while European centers utilize the local effect model (LEM). Despite both models estimating RBE-distributions in tissue, their physical and mathematical assumptions differ, leading to significant disparities in RBE-weighted doses. Several European clinics adopted Japanese treatment schedules, necessitating adjustments in dose prescriptions and organ at risk (OAR) constraints. In the context of these two clinically used standards for RBE-weighted dose estimation, the objective of this study was to highlight specific scenarios for which the translations between models diverge, as shortcomings between them can influence clinical decisions. Our aim was to discuss planning strategies minimizing those discrepancies, ultimately striving for more accurate and robust treatments. Evaluations were conducted in a virtual water phantom and patient CT-geometry, optimizing LEM RBE-weighted dose first and recomputing MKM thereafter. Dose-averaged linear energy transfer (LETd) distributions were also assessed. Results demonstrate how various parameters influence LEM/MKM translation. Similar LEM-dose distributions lead to markedly different MKM-dose distributions and variations in LETd. Generally, a homogeneous LEM RBE-weighted dose aligns with lower MKM values in most of the target volume. Nevertheless, paradoxical MKM hotspots may emerge (at the end of the range), potentially influencing clinical outcomes. Therefore, translation between models requires great caution. Understanding the relationship between these two clinical standards enables combining European and Japanese based experiences. The implementation of optimal planning strategies ensures the safety and acceptability of the clinical plan for both models and therefore enhances plan robustness from the RBE-weighted dose and LETd distribution point of view. This study emphasizes the importance of optimal planning strategies and the need for comprehensive CIRT plan quality assessment tools. In situations where simultaneous LEM and MKM computation capabilities are lacking, it can provide guidance in plan design, ultimately contributing to enhanced CIRT outcomes.

Comprehensive analysis based on the disulfidptosis-related genes identifies hub genes and immune infiltration for pancreatic adenocarcinoma.

Pancreatic adenocarcinoma (PAAD) is a prevalent and aggressive malignancy in the digestive tract, requiring accurate prediction and effective treatment strategies. Recently, the discovery of disulfidptosis, a novel form of programmed cell death characterized by abnormal disulfide accumulation, has sparked interest in its role in PAAD. In this study, we aimed to investigate the involvement of disulfidptosis-related genes (DRGs) in PAAD. Using publicly available databases, we conducted a comprehensive analysis exploring the complex relationships between DRGs and important aspects of PAAD, including gene expression, immune response, mutation, drug sensitivity, and functional enrichment. Notably, we observed significant heterogeneity among different disulfidptosis subclusters and identified specific differentially expressed genes in PAAD. Through machine learning techniques, we identified SLC7A11, S100A4, DIAPH3, PRDX1, and SLC7A7 as the most relevant hub genes. We further validated their significance in PAAD by considering their expression patterns, prognostic value, diagnostic potential, diagnostic model, and immune infiltration. This study presents exciting opportunities and challenges in unraveling the underlying mechanisms of PAAD prognosis. It also establishes a foundation for personalized cancer care and the development of innovative immunotherapeutic strategies. By shedding light on the role of DRGs, particularly hub genes, we enhance our understanding and management of PAAD.

Marker-controlled watershed algorithm and fuzzy C-means clustering machine learning: automated segmentation of glioblastoma from MRI images in a case series.

Automated segmentation of glioblastoma multiforme (GBM) from MRI images is crucial for accurate diagnosis and treatment planning. This paper presents a new and innovative approach for automating the segmentation of GBM from MRI images using the marker-controlled watershed segmentation (MCWS) algorithm. The technique involves several image processing techniques, including adaptive thresholding, morphological filtering, gradient magnitude calculation, and regional maxima identification. The MCWS algorithm efficiently segments images based on local intensity structures using the watershed transform, and fuzzy c-means (FCM) clustering improves segmentation accuracy. The presented approach achieved improved segmentation accuracy in detecting and segmenting GBM tumours from axial T2-weighted (T2-w) MRI images, as demonstrated by the mean characteristics performance metrics for GBM segmentation (sensitivity: 0.9905, specificity: 0.9483, accuracy: 0.9508, precision: 0.5481, F_measure: 0.7052, and jaccard: 0.9340). The results of this study underline the importance of reliable and accurate image segmentation for effective diagnosis and treatment planning of GBM tumours. The MCWS technique provides an effective and efficient approach for the segmentation of challenging medical images.

Photoacoustic Imaging of Human Skin for Accurate Diagnosis and Treatment Guidance

Photoacoustic imaging (PAI) is a cutting-edge biomedical imaging modality, providing detailed anatomical and functional information about the area beneath the skin surface. Its light energy deposition is such that PAI typically provides clear images of the skin with high signal-to-noise ratios. Specifically, the rich optical contrast of PAI allows biological information related to lesion growth, malignancy, treatment response, and prognosis to be seen. Given its significant advantages and emerging role in imaging skin lesions, we summarize and comment on representative studies of skin PAI, such as the guidance of skin cancer biopsies and surgical excisions, and the accurate diagnosis of psoriasis. We conclude with our insights about the clinical significance of skin PAI, showing how its use to identify biological characteristics in lesion microenvironments allows early diagnosis and prognosis of disease.

Pediatric Intraabdominal Cysts-A Case Series from a Single Tertiary Center Experience.

We aimed to analyze the clinical presentation, imaging, histopathology, and surgical management of pediatric intraabdominal cysts, which are relatively common but diverse lesions that pose diagnostic challenges. We conducted a retrospective analysis of pediatric intraabdominal cysts from 2010 to 2021 in a single tertiary center. We collected data on demographics, symptoms, radiological findings, surgical approaches, and histopathological diagnoses and compared them with the current literature. A total of 36 cases were included. There were 30 females and 6 males, aged 1 to 16 years. Abdominal pain was the most common symptom, followed by tenderness and distention. Diarrhea and vomiting were also reported in some cases. The cysts varied in size, location, and origin and were diagnosed as lymphangioma, mucinous cystadenoma, paratubal cyst, lowgrade mucinous neoplasm, mature cystic teratoma, duplication cyst, mesothelial cyst, pseudocyst, serous cystadenoma, and simple hepatic cyst. The surgical management depended on the type and location of the cysts and involved excision, oophorectomy, appendectomy, or resection. Pediatric intraabdominal cysts are heterogeneous lesions that require timely diagnosis and surgical resection. They may present with various symptoms and complications, depending on their size and location. Radiological and histopathological evaluation is essential for accurate diagnosis and optimal treatment.

Multi-Frequency Ultrasound Imaging Fusion Method Based on Wavelet Transform for Guided Screw Insertion.

Intraosseous ultrasound imaging can serve as a guiding tool for the placement of pedicle screws during spinal fusion surgery; thus far, there has been limited scholarly exploration of methods for intraosseous multifrequency ultrasound imaging, which can achieve simultaneous high resolution and deep penetration. The proposed method introduced a dynamic fusion strategy grounded in wavelet transformation for multifrequency image decomposition. This strategy accomplished the effective amalgamation of high-frequency ultrasound images and low-frequency ultrasound images, enabling the obtaining of fused images with enhanced details and better overall image quality. A novel near-field effect elimination method was also proposed to improve the quality of ultrasound imaging in the near-field region. Experimental evaluations were conducted on isolated bovine circle bone and sheep spine with pedicle screw tracks. The fusion images are capable of effectively detecting areas within the pedicle screw track that have either ruptured or are in close proximity to rupture, even measuring the size of breaches. Evaluation criteria, including information entropy (IE), spatial frequency (SF), average gradient (AG), mutual information (MI), structural similarity index (SSIM), and edge information-based image fusion quality metric (QAB/F), were employed to assess the fusion performance; moreover, the influence of mother wavelet function selection and decomposition levels on computational complexity and fusion image quality was thoroughly discussed. The proposed method exhibited promising potential for intraosseous imaging navigation, which can aid in accurate diagnosis, treatment planning, and monitoring in fields such as orthopedics, surgery, and interventional procedures.

Autism spectrum disorder: pathogenesis, biomarker, and intervention therapy.

Autism spectrum disorder (ASD) has become a common neurodevelopmental disorder. The heterogeneity of ASD poses great challenges for its research and clinical translation. On the basis of reviewing the heterogeneity of ASD, this review systematically summarized the current status and progress of pathogenesis, diagnostic markers, and interventions for ASD. We provided an overview of the ASD molecular mechanisms identified by multi-omics studies and convergent mechanism in different genetic backgrounds. The comorbidities, mechanisms associated with important physiological and metabolic abnormalities (i.e., inflammation, immunity, oxidative stress, and mitochondrial dysfunction), and gut microbial disorder in ASD were reviewed. The non-targeted omics and targeting studies of diagnostic markers for ASD were also reviewed. Moreover, we summarized the progress and methods of behavioral and educational interventions, intervention methods related to technological devices, and research on medical interventions and potential drug targets. This review highlighted the application of high-throughput omics methods in ASD research and emphasized the importance of seeking homogeneity from heterogeneity and exploring the convergence of disease mechanisms, biomarkers, and intervention approaches, and proposes that taking into account individuality and commonality may be the key to achieve accurate diagnosis and treatment of ASD.

Efficient Sampling of Cavity Hydration in Proteins with Nonequilibrium Grand Canonical Monte Carlo and Polarizable Force Fields.

Prediction of the hydration levels of protein cavities and active sites is important to both mechanistic analysis and ligand design. Due to the unique microscopic environment of these buried water molecules, a polarizable model is expected to be crucial for an accurate treatment of protein internal hydration in simulations. Here we adapt a nonequilibrium candidate Monte Carlo approach for conducting grand canonical Monte Carlo simulations with the Drude polarizable force field. The GPU implementation enables the efficient sampling of internal cavity hydration levels in biomolecular systems. We also develop an enhanced sampling approach referred to as B-walking, which satisfies detailed balance and readily combines with grand canonical integration to efficiently calculate quantitative binding free energies of water to protein cavities. Applications of these developments are illustrated in a solvent box and the polar ligand binding site in trypsin. Our simulation results show that including electronic polarization leads to a modest but clear improvement in the description of water position and occupancy compared to the crystal structure. The B-walking approach enhances the range of water sampling in different chemical potential windows and thus improves the accuracy of water binding free energy calculations.

Whole-exome sequencing combined with postoperative data identify c.1614dup (CAMKK2) as a novel candidate monogenic obesity variant.

Early-onset obesity is a rising health concern influenced by heredity. However, many monogenic obesity variants (MOVs) remain to be discovered due to differences in ethnicity and culture. Additionally, patients with known MOVs have shown limited weight loss after bariatric surgery, suggesting it can be used as a screening tool for new candidates. In this study, we performed whole-exome sequencing (WES) combined with postoperative data to detect candidate MOVs in a cohort of 62 early-onset obesity and 9 late-onset obesity patients. Our findings demonstrated that patients with early-onset obesity preferred a higher BMI and waist circumference (WC). We confirmed the efficacy of the method by identifying a mutation in known monogenic obesity gene, PCSK1, which resulted in less weight loss after surgery. 5 genes were selected for further verification, and a frameshift variant in CAMKK2 gene: NM_001270486.1, c.1614dup, (p. Gly539Argfs*3) was identified as a novel candidate MOV. This mutation influenced the improvement of metabolism after bariatric surgery. In conclusion, our data confirm the efficacy of WES combined with postoperative data in detecting novel candidate MOVs and c.1614dup (CAMKK2) might be a promising MOV, which needs further confirmation. This study enriches the human monogenic obesity mutation database and provides a scientific basis for clinically accurate diagnosis and treatment.

Development of a CD8+ T cell associated signature for predicting the prognosis and immunological characteristics of gastric cancer by integrating single-cell and bulk RNA-sequencing

The universally poor clinical outcome makes gastric cancer (GC) still a significant public health threat, the main goal of our research is to develop a prognostic signature that can forecast the outcomes and immunological characteristics of GC via integrating single-cell and bulk RNA-sequencing. The CD8+ T cell feature genes were screened out by exploring single-cell RNA-sequencing (scRNA-seq) profiles retrieved from the TISCH2 database. Then, Cox and LASSO regressions were exploited for constructing a prognostic model in TCGA cohort based on these CD8+ T cell feature genes. Survival analysis was conducted to investigate the predictive capability of the signature for the clinical outcome of GC patients in TCGA and GEO cohorts. Additionally, we further examined the correlations between the risk signature and tumor immunotherapeutic response from the perspectives of immune infiltration, tumor mutation burden (TMB), immune checkpoint biomarker (ICB) expression, tumor microenvironment (TME), microsatellite instability (MSI), TIDE, and TCIA scores. In total, 703 CD8+ T cell feature genes were identified, eight of which were selected for constructing a prognostic signature. GC patients who possess high-risk score had significantly poorer survival outcomes than those who possess low-risk score in TCGA and GEO cohorts. Immune infiltration analysis proved that the risk score was negatively connected with the infiltration abundance of CD8+ T cells. Then, our findings demonstrated that GC patients in the high-risk subgroup possess a higher proportion of MSI-L/MSS, lower immune checkpoint biomarker expression, lower TMB, higher TIDE scores and lower TCIA scores compared to those in the low-risk subgroup. What’s more, immunotherapy cohort analysis confirmed that patients who possess high-risk score are not sensitive to anti-cancer immunotherapy. Our study developed a reliable prognostic signature for GC that was significantly correlated with the immune landscape and immunotherapeutic responsiveness. The risk signature may guide clinicians to adopt more accurate and personalized treatment strategies for GC patients.

Feature Extraction and Classification of Gray-Scale Images of Brain Tumor using Deep Learning

Deep Learning using CNN plays a paramount role for the classification methods applied on medical image data. With a crucial role in accurate diagnosis, treatment planning and patient management for medical and healthcare systems, CNNs won accolades in the Deep Learning research. As simple the learning model so precise are the results for decision making. The proposed Sequential model of CNN is built with Parametric ReLU with the values aligned to geometric mean, attains a specific goal of tumor classification. The additional support of ground-truth aid in deciding the shape and severity of tumor in the Grayscale MRI of brain tumor. The simple Sequential model, although a minimal version has proved achieved significant classification goals using the GMP-ReLU. Comparative results with variants of ReLU have been charted in this article standing with the proof of consistent classification model with parametric-ReLU. The proposed design is conducted on images from Kaggle and a model is trained (classifier is built), which can be considered as ideal filter for all the benchmark images. The accuracy of proposed design is considerably improved compared to normal ReLU up to 89.214%.

Novel plasma microRNA expression features in diagnostic use for Epstein-Barr virus-associated febrile diseases

BackgroundEpstein-Barr virus (EBV) is widely infected in humans and causes various diseases. Among them, microRNAs of EBV play a key role in the progression of EBV-associated febrile diseases. There're few specific indicators for rapid differential diagnosis of various febrile diseases associated with EBV, and the lack of more reliable screening methods with high diagnostic utility has led to spaces for improvement in the accurate diagnosis and efficient treatment of relevant patients, making EBV infection a complicated clinical problem. With recent advances in plasma microRNA testing, the apparent presence of EBV microRNAs in plasma can help screen for EBV infection. The gene networks targeted by these microRNAs can also indicate potential biomarkers of EBV-associated febrile diseases. This study aimed to identify some novel miRNAs as potential biomarkers for early diagnosis of respectively EBV-associated febrile diseases. Materials and methodsA total of 110 participants were recruited for this task. First, we performed high-throughput sequencing and preliminary PCR validation of differentially expressed miRNAs in 15 participants with EBV-associated fever (divided into 5 groups, common EBV carriers, infectious mononucleosis (IM) and chronic active EBV infection (CAEBV), EBV-associated Hemophagocytic Lymphohistiocytosis (EBV-HLH), and 3 healthy individuals). After a comprehensive analysis, 10 miRNAs with abnormal expression were screened, and then qRT-PCR was performed in the rest of 95 participants to detect the validation of miRNAs expression in plasma samples. Thereafter, we further investigated their potential for clinical application in EBV-related febrile diseases by using a combination of Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Protein-protein interaction network analysis. ResultsThrough identification and detailed analysis of the obtained data, we found significant differences in the expression of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p in blood samples from patients with different EBV-related febrile diseases. We found that the expression levels of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p in plasma are indicative of determining different disease types of EBV-related febrile diseases, while EBV-miR-BART22 and EBV-miR-BART2-3p may be potential therapeutic targets. ConclusionThe expression levels of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p suggest that they may be used as transcriptional features for early differential diagnosis of EBV-related febrile diseases, and EBV-miR-BART22 and EBV-miR-BART2-3p may be potential therapeutic targets.