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Background: Humans often use co‐speech gestures to promote effective communication. Attention has been paid to the cortical areas engaged in the processing of co‐speech gestures. Aims: To investigate the neural network underpinned in the processing of co‐speech gestures and to observe whether there is a relationship between areas involved in language and gesture processing. Methods & Procedures: We planned to include studies with neurotypical and/or stroke participants who underwent a bimodal task (i.e., processing of co‐speech gestures with relative speech) and a unimodal task (i.e., speech or gesture alone) during a functional magnetic resonance imaging (fMRI) session. After a database search, abstract and full‐text screening were conducted. Qualitative and quantitative data were extracted, and a meta‐analysis was performed with the software GingerALE 3.0.2, performing contrast analyses of uni‐ and bimodal tasks. Main Contribution: The database search produced 1024 records. After the screening process, 27 studies were included in the review. Data from 15 studies were quantitatively analysed through meta‐analysis. Meta‐analysis found three clusters with a significant activation of the left middle frontal gyrus and inferior frontal gyrus, and bilateral middle occipital gyrus and inferior temporal gyrus. Conclusions: There is a close link at the neural level for the semantic processing of auditory and visual information during communication. These findings encourage the integration of the use of co‐speech gestures during aphasia treatment as a strategy to foster the possibility to communicate effectively for people with aphasia. WHAT THIS PAPER ADDS: What is already known on this subject: Gestures are an integral part of human communication, and they may have a relationship at neural level with speech processing. What this paper adds to the existing knowledge: During processing of bi‐ and unimodal communication, areas related to semantic processing and multimodal processing are activated, suggesting that there is a close link between co‐speech gestures and spoken language at a neural level. What are the potential or actual clinical implications of this work?: Knowledge of the functions related to gesture and speech processing neural networks will allow for the adoption of model‐based neurorehabilitation programs to foster recovery from aphasia by strengthening the specific functions of these brain networks. [ABSTRACT FROM AUTHOR]

Basal cell carcinoma (BCC) is usually diagnosed by clinical and dermatoscopy examination, but diagnostic accuracy may be suboptimal. Reflectance confocal microscopy (RCM) imaging increases skin cancer diagnostic accuracy. To evaluate additional benefit in diagnostic accuracy of handheld RCM in a prospective controlled clinical setting. A prospective, multicenter study in 3 skin cancer reference centers in Italy enrolling consecutive lesions with clinical-dermatoscopic suspicion of BCC (ClinicalTrials.gov: NCT04789421). A total of 1005 lesions were included, of which 474 histopathologically confirmed versus 531 diagnosed by clinical-dermatoscopic-RCM correlation, confirmed with 2 years of follow-up. Specifically, 740 were confirmed BCCs. Sensitivity and specificity for dermatoscopy alone was 93.2% (95% CI, 91.2-94.9) and 51.7% (95% CI, 45.5-57.9); positive predictive value was 84.4 (95% CI, 81.7-86.8) and negative predictive value 73.3 (95% CI, 66.3-79.5). Adjunctive RCM reported higher rates: 97.8 (95% CI, 96.5-98.8) sensitivity and 86.8 (95% CI, 82.1-90.6) specificity, with positive predictive value of 95.4 (95% CI, 93.6-96.8) and negative predictive value 93.5 (95% CI, 89.7-96.2). Study conducted in a single country. Adjunctive handheld RCM assessment of lesions clinically suspicious for BCC permits higher diagnostic accuracy with minimal false negative lesions. [ABSTRACT FROM AUTHOR]

Copyright of CT Theory & Applications is the property of Editorial Department of CT Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aim: Joint damage due to haemarthrosis can be effectively monitored with point‐of care ultrasound using the Haemophilia Early Arthropathy Detection with US (HEAD‐US) scoring system. A post hoc comparative analysis of the joint status of patients with severe haemophilia A (HA) or B (HB) was performed. Methods: The databases of two observational, cross‐sectional studies that recruited patients with HA or HB from 12 Spanish centres were analysed to compare the status of the elbows, knees and ankles in patients with severe disease according to treatment modality. The HEAD‐US score was calculated in both studies by the same trained operators. Results: Overall, 95 HA and 41 HB severe patients were included, with a mean age of 35.2 ± 11.8 and 32.7 ± 14.2 years, respectively. The percentage of patients who received prophylaxis, over on‐demand (OD) treatment, was much higher in HA (91.6%) than in HB (65.8%) patients. With a similar number of target joints, the HEAD‐US score was zero in 6.3% HA and 22.0% HB patients (p <.01), respectively. The HA population showed significantly worse HEAD‐US scores. Whilst osteochondral damage occurred more frequently in patients OD or tertiary prophylaxis, our data suggest that articular damage is less prominent in primary/secondary prophylaxis, regardless of the type of haemophilia. These latter treatment modalities were also associated with a lower prevalence of synovial hypertrophy, particularly in HB patients. Conclusion: This post hoc analysis indicates that joint status seems to be significantly influenced by haemophilia type (HA or HB) and treatment modality in these severe Spanish populations with severe disease. Continuing HEAD‐US monitoring for the early detection and management of intra‐articular abnormalities, as well as more efficiently tailored therapies should be warranted. [ABSTRACT FROM AUTHOR]

Background: Glioma is one of the most drug and radiation-resistant tumors. Gliomas suffer from inter- and intratumor heterogeneity which makes the outcome of similar treatment protocols vary from patient to patient. This article is aimed to overview the potential imaging markers for individual diagnosis, prognosis, and treatment response prediction in malignant glioma. Furthermore, the correlation between imaging findings and biological and clinical information of glioma patients is reviewed. Materials and Methods: The search strategy in this study is to select related studies from scientific websites such as PubMed, Scopus, Google Scholar, and Web of Science published until 2022. It comprised a combination of keywords such as Biomarkers, Diagnosis, Prognosis, Imaging techniques, and malignant glioma, according to Medical Subject Headings. Results: Some imaging parameters that are effective in glioma management include: ADC, FA, Ktrans, regional cerebral blood volume (rCBV), cerebral blood flow (CBF), ve, Cho/NAA and lactate/lipid ratios, intratumoral uptake of 18F-FET (for diagnostic application), RD, ADC, ve, vp, Ktrans, CBFT1, rCBV, tumor blood flow, Cho/ NAA, lactate/lipid, MI/Cho, uptakes of 18F-FET, 11C-MET, and 18F-FLT (for prognostic and predictive application). Cerebral blood volume and Ktrans are related to molecular markers such as vascular endothelial growth factor (VEGF). Preoperative ADCmin value of GBM tumors is associated with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. 2-hydroxyglutarate metabolite and dynamic 18F-FDOPA positron emission tomography uptake are related to isocitrate dehydrogenase (IDH) mutations. Conclusion: Parameters including ADC, RD, FA, rCBV, Ktrans, vp, and uptake of 18F-FET are useful for diagnosis, prognosis, and treatment response prediction in glioma. A significant correlation between molecular markers such as VEGF, MGMT, and IDH mutations with some diffusion and perfusion imaging parameters has been identified. [ABSTRACT FROM AUTHOR]

Chronic kidney disease (CKD) is a global health issue with a rising prevalence, affecting 697.5 million people worldwide. It imposes a substantial burden, contributing to 35.8 million disability-adjusted life years (DALYs) and 1.2 million deaths in 2017. The mortality rate for CKD has increased by 41.5% between 1990 and 2017, positioning it as a significant cause of global mortality. CKD is associated with diverse health complications, impacting cardiovascular, neurological, nutritional, and endocrine aspects. One prominent complication is CKD–mineral and bone disorder (MBD), a complex condition involving dysregulation of bone turnover, mineralization, and strength, accompanied by soft tissue and vascular calcification. Alterations in mineral metabolism, including calcium, phosphate, parathyroid hormone (PTH), vitamin D, fibroblast growth factor-23 (FGF-23), and Klotho, play pivotal roles in CKD-MBD. These disturbances, observed early in CKD, contribute to the progression of bone disorders and renal osteodystrophy (ROD). Vascular calcification (VC) is a key component of CKD-MBD, accelerated by CKD. The pathophysiology involves complex processes in vascular smooth muscle cells and the formation of calciprotein particles (CPP). VC is closely linked to cardiovascular events and mortality, emphasizing its prognostic significance. Various serum markers and imaging techniques, including lateral plain X-ray, Kauppila Score, Adragao Score, and pulse wave velocity, aid in VC detection. Additionally, pQCT provides valuable information on arterial calcifications, offering an advantage over traditional scoring systems. CKD poses a substantial global health burden, and its complications, including CKD-MBD and VC, significantly contribute to morbidity and mortality. Understanding the intricate relationships between mineral metabolism, bone disorders, and vascular calcification is crucial for effective diagnosis and therapeutic interventions. [ABSTRACT FROM AUTHOR]

Abstract Self‐assembled peptides have been among the important biomaterials due to its excellent biocompatibility and diverse functions. Over the past decades, substantial progress and breakthroughs have been made in designing self‐assembled peptides with multifaceted biomedical applications. The techniques for quantitative analysis, including imaging‐based quantitative techniques, chromatographic technique and computational approach (molecular dynamics simulation), are becoming powerful tools for exploring the structure, properties, biomedical applications, and even supramolecular assembly processes of self‐assembled peptides. However, a comprehensive review concerning these quantitative techniques remains scarce. In this review, recent progress in techniques for quantitative investigation of biostability, cellular uptake, biodistribution, self‐assembly behaviors of self‐assembled peptide etc., are summarized. Specific applications and roles of these techniques are highlighted in detail. Finally, challenges and outlook in this field are concluded. It is believed that this review will provide technical guidance for researchers in the field of peptide‐based materials and pharmaceuticals, and facilitate related research for newcomers in this field.

Background In vitro experiments are critical for understanding the impact of medical devices and techniques on blood vessels and blood flow. However, their interpretation is often limited by anatomical models’ inability to capture the wide range of vessel sizes observed in real‐world practice. The current study aims to address this limitation by describing the distribution of vessel diameters in a real‐world population. Methods This systematic literature review using the PubMed database analyzed cerebral vessel diameters in patients from 2000 to 2022. The diameter measurements of various vessels within the neurovasculature were extracted. Random‐effects meta‐analyses were performed to synthesize vessel diameters across studies. Predicted distributions were generated from the meta‐analytical results. Results Seventy‐six studies were included in the analysis. The M1 segment, internal carotid artery (cervical and communicating segments), A1 segment, V2 segment, V4 segment, and basilar artery had sufficient data for generating predicted distributions of vessel diameters. Predicted mean diameters were as follows: M1 segment, 2.55 ± 0.42 mm (95th interpercentile range [IPR]: 1.71–3.38); internal carotid artery‐cervical segment, 4.74 ± 0.64 mm (95th IPR: 3.49–5.99); internal carotid artery‐communicating segment, 3.40 ± 0.64 mm (95th IPR: 2.15–4.66); A1 segment, 1.89 ± 0.34 mm (95th IPR: 1.23–2.55); V2 segment, 3.36 ± 0.67 mm (95th IPR: 2.05–4.67); V4 segment, 2.42 ± 0.74 mm (95th IPR: 0.98–3.86); and basilar artery, 2.96 ± 0.52 mm (95th IPR: 1.94–3.97). Conclusion Cerebral vessel diameter measurements can vary substantially due to patient‐specific factors and imaging techniques. This literature review highlights the diverse range of vessel sizes observed in different patient populations, emphasizing the need for anatomical models that accurately represent clinical observations.

Oral cancer as a global health problem becomes more difficult to deal with, especially since developing countries are the hardest hit due to massive rates of mortality and morbidity. Detecting cancer in the early stage and providing an accurate diagnosis is important in improving the outcomes and causing less damage to the patients. The medical technology, particularly in the areas of deep learning, optimization algorithms, and imaging techniques, has begun a new paradigm in oral cancer diagnosing and detecting methodologies. Specialized algorithms such as the Recombination-Based Improved Population Optimization Parallel Covariance Matrix Adaptation Evolution Strategy (RB-IPOP CMA-ES) allow for better accuracy of deep learning models, as this enhances the performance of developing models for early diagnosis of oral cancer. A faithful system of devices with accessible point-of-care screening mechanisms, deployed with neural network classification mechanisms, might become a competitive assurance, especially in resource-deficient areas. For example, skills including Recursive Mean-Separate Histogram Equalization (RMSHE) come in handy in enhancing the resolution of the images and clarity which eventually leads to more accurate lesion identification. Trial-and-error type of survival prediction models, for instance, DeepSurv, offer superior results to conventional approaches and give medical experts the possibility to develop individualized treatment methods. Nevertheless, some obstacles compress the path of implementation. Through the synergy of scientists, clinicians, and policymakers, complexities in the utilization of high-tech solutions to the global effort in oral cancer can be eliminated and access can be paved to better health treatments worldwide.

Myocardial infarction is a serious medical condition that requires prompt and accurate diagnosis for effective treatment. In this paper, we present a novel approach for detecting and classifying MI in echocardiogram frames using an enhanced CNN algorithm and an ECV-3D network. The proposed method aims to improve the accuracy and efficiency of MI diagnosis by leveraging advanced deep learning techniques. Through extensive experimentation, we demonstrated the effectiveness of our approach in achieving high accuracy and robustness in MI detection and classification. These results indicate the potential of our method to aid in the early and precise diagnosis of MI, thereby contributing to improved patient outcomes and clinical decision-making. After conducting thorough experimentation, our proposed approach achieved an impressive accuracy of 97.05% in the detection and classification of myocardial infarction in echocardiogram frames. This shows the robustness and reliability of our method, indicating its potential to significantly impact the accurate diagnosis of MI and subsequently improve patient outcomes. Furthermore, the area under the curve attained by our model is 0.82, reaffirming the efficacy of the enhanced CNN algorithm and ECV-3D network in accurately detecting and classifying MI. It is noteworthy that all the parameters utilized in our approach have demonstrated a high level of accuracy, emphasizing the effectiveness of our deep learning techniques in enhancing the diagnostic process for MI. Moreover, the proposed method efficiently process large volumes of echocardiogram frames, making it suitable for real-time clinical applications.

Digital Precision Agriculture (DPA) is a comprehensive approach to agronomic management that utilizes advanced technologies, such as sensor data analysis and automation, to optimize crop productivity, enhance farm income, and minimize environmental impacts. DPA encompasses various agricultural domains, including pest control, pest management, fertilization, irrigation management, sowing, transplanting, crop health monitoring, yield forecasting, harvesting, and post-harvest stages. Among the enabling technologies for DPA, Unmanned Aerial Vehicles (UAVs) have gained significant attention and market growth. The advancements in control systems, robotics, electronics, and artificial intelligence have led to the development of sophisticated agricultural drones. UAVs offer advantages such as versatility, quick and accurate remote sensing capabilities, and high-quality imaging at affordable prices. Furthermore, the miniaturization of sensors and advancements in nanotechnology enable UAVs to perform multiple operations simultaneously without compromising flight autonomy. However, various variables, including aircraft mass, payload capacity, size, battery characteristics, flight autonomy, cost, and environmental conditions, impact the performance and applicability of UAV systems in agriculture. The economic considerations involve the purchase of drones, equipment, and the expertise of trained pilots for flight management and data processing. Payload capacity, flight range, and financial factors influence agriculture’s choice and implementation of UAVs. The research and patent trends show the growing interest in UAVs for agricultural applications. This paper provides a general review of UAV types, construction architectures, and their diverse applications in agriculture until 2022.

This research explores the use of the pepN activity fluorescent sensor DCM-Ala in bacterial biofilms, emphasizing its significance due to the critical role of biofilms in various biological processes. Advanced imaging techniques were employed to visualize pepN activity, introducing a novel approach to examining biofilm maturity. We found that the overexpression of pepN increases the ability of E. coli to form biofilm. The findings demonstrate varying levels of pepN activity throughout biofilm development, suggesting potential applications in biofilm research and management. The results indicate that the fluorescent emission from this sensor could serve as a reliable indicator of biofilm maturity, and the imaging techniques developed could enhance our understanding and control of biofilm-related processes. This work highlights the importance of innovative methods in biofilm study and opens new avenues for utilizing chemical emissions in biofilm management.

Considerable progress has been made in our knowledge of the morphological and functional varieties of anchoring junctions. Cell-cell adhesion contacts consist of discrete junctional structures responsible for the mechanical coupling of cytoskeletons and allow the transmission of mechanical signals across the cell collective. The three main adhesion complexes are adherens junctions, tight junctions, and desmosomes. Microscopy has played a fundamental role in understanding these adhesion complexes on different levels in both physiological and pathological conditions. In this review, we discuss the main light and electron microscopy techniques used to unravel the structure and composition of the three cell-cell contacts in epithelial and endothelial cells. It functions as a guide to pick the appropriate imaging technique(s) for the adhesion complexes of interest. We also point out the latest techniques that have emerged. At the end, we discuss the problems investigators encounter during their cell-cell adhesion research using microscopic techniques.

The spatiotemporal compartmentalization of membrane-associated glycosylphosphatidylinositol-anchored proteins (GPI-APs) on the cell surface regulates their biological activities. These GPI-APs occupy distinct cellular functions such as enzymes, receptors, and adhesion molecules, and they are implicated in several vital cellular processes. Thus, unraveling the mechanisms and regulators of their membrane organization is essential. In polarized epithelial cells, GPI-APs are enriched at the apical surface, where they form small cholesterol-independent homoclusters and larger heteroclusters accommodating multiple GPI-AP species, all confined within areas of approximately 65–70 nm in diameter. Notably, GPI-AP homoclustering occurs in the Golgi apparatus through a cholesterol- and calcium-dependent mechanism that drives their apical sorting. Despite the critical role of Golgi GPI-AP clustering in their cell surface organization and the importance of cholesterol in heterocluster formation, the regulatory mechanisms governing GPI-AP surface organization, particularly in the context of epithelial polarity, remain elusive. Given that the actin cytoskeleton undergoes substantial remodeling during polarity establishment, this study explores whether the actin cytoskeleton regulates the spatiotemporal apical organization of GPI-APs in MDCK cells. Utilizing various imaging techniques (number and brightness, FRET/FLIM, and dSTORM coupled to pair correlation analysis), we demonstrate that the apical organization of GPI-APs, at different scales, does not rely on the actin cytoskeleton, unlike in fibroblastic cells. Interestingly, calcium chelation disrupts the organization of GPI-APs at the apical surface by impairing Golgi GPI-AP clustering, emphasizing the existence of an interplay among Golgi clustering, apical sorting, and surface organization in epithelial cells. In summary, our findings unveil distinct mechanisms regulating the organization of GPI-APs in cell types of different origins, plausibly allowing them to adapt to different external signals and different cellular environments in order to achieve specialized functions.

Cerebrovascular diseases, including ischemic strokes, hemorrhagic strokes, and vascular malformations, are major causes of morbidity and mortality worldwide. The advancements in neuroimaging techniques have revolutionized the field of cerebrovascular disease diagnosis and assessment. This comprehensive review aims to provide a detailed analysis of the novel imaging methods used in the diagnosis and assessment of cerebrovascular diseases. We discuss the applications of various imaging modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and angiography, highlighting their strengths and limitations. Furthermore, we delve into the emerging imaging techniques, including perfusion imaging, diffusion tensor imaging (DTI), and molecular imaging, exploring their potential contributions to the field. Understanding these novel imaging methods is necessary for accurate diagnosis, effective treatment planning, and monitoring the progression of cerebrovascular diseases.

Gastrointestinal stromal tumors (GISTs) are rare mesenchymal subepithelial tumors originating from abnormal proliferation of interstitial cells of Cajal, with worldwide incidence of about 1–2 per 100,000. Herein, we report an unusual case of a 55-year-old man who presented a severe digestive hemorrhage as a rare post-surgical complication after intestinal GIST surgical removal. The patient was admitted to the Emergency Department of our center affected by abdominal epigastric pain. Different imaging techniques were performed leading to the final diagnosis of a GIST and surgical intervention planning. Immediately after intervention the patient developed a severe intestinal hemorrhage. Multidetector computed tomography (MDCT) confirmed the ongoing bleeding and the patient underwent a new intervention to control the hemorrhage. The aim of the paper is to show the different imaging techniques used to assess GIST. MDCT represents the gold standard for diagnosis and in the emergency setting is used to identify post-surgical complications.

Background: Pulmonary atelectasis is a commonly occurs during anesthesia. In these cases, mechanical ventilation (MV) associated with alveolar recruitment maneuvers (ARMs) and positive end-expiratory pressure (PEEP) is indicated to reverse the condition, ensure adequate gas exchange and improve oxygenation. ARMs can trigger volutrauma, barotrauma, and atelectrauma. Therefore, computed tomography (CT) is the gold-standard method for monitoring lung aeration after ARM. Objective: To evaluate lung volume distribution after stepwise ARMs using computed tomography (CT). Methods: Twelve dogs weighing 24.0 ± 6.0 kg, aged 3 ± 1 years, of both sexes and different breeds, underwent orchiectomy or ovariohysterectomy. The animals were anesthetized and ventilated in volume-controlled mode. ARMs were then initiated by positive end-expiratory pressure (PEEP) titration (5, 10, 15, and 20 cmH2O). CT scans, cardiovascular parameters, and ventilatory mechanics were evaluated at all time points. Data were assessed for normality using the Shapiro-Wilk test and a two-way analysis of variance, followed by a post-hoc Bonferroni test to identify differences between time points. Statistical significance was attributed to a value of p of <0.05. Results: CT demonstrated that the ARMs increased ventilation throughout the lung, including the dependent regions, with volumes that increased and decreased proportionally with PEEP titration. When they reached PEEP 10 and 5 cmH2O descending (d), they remained significantly higher than those in PEEP 0 cmH2O (baseline). Static compliance improved about 40% at PEEP 10d and PEEP 5d compared to baseline. There was an increase in heart rate (HR) from PEEP 15 increasing (i) (74.5%) to PEEP 10d (54.8%) compared to baseline. Mean arterial blood pressure (MABP) decreased approximately 9% from PEEP 15i to PEEP 15d compared to baseline. Conclusion: Lung attenuation and regional and global volumes assessed by CT showed that maximum pulmonary aeration distribution followed by PEEP titration occurred at PEEP 20 cmH2O, maintaining the lungs normoaerated and without hyperaeration. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Significance: Optical-resolution optoacoustic microscopy (OR-OAM) enables labelfree imaging of the microvasculature by using optical pulse excitation and acoustic detection, commonly performed by a focused optical beam and an ultrasound transducer. One of the main challenges of OR-OAM is the need to combine the excitation and detection in a coaxial configuration, often leading to a bulky setup that requires physically scanning the ultrasound transducer to achieve a large field of view. Aim: The aim of this work is to develop an OR-OAM configuration that does not require physically scanning the ultrasound transducer or the acoustic beam path. Approach: Our OR-OAM system is based on a non-coaxial configuration in which the detection is performed by a silicon-photonics acoustic detector (SPADE) with a semi-isotropic sensitivity. The system is demonstrated in both epi- and transillumination configurations, where in both configurations SPADE remains stationary during the imaging procedure and only the optical excitation beam is scanned. Results: The system is showcased for imaging resolution targets and for the in vivo visualization of the microvasculature in a mouse ear. Optoacoustic imaging with focal spots down to 1.3 µm, lateral resolution of 4 µm, and a field of view higher than 4 mm in both lateral dimensions were demonstrated. Conclusions: We showcase a new OR-OAMdesign, compatible with epi-illumination configuration. This setup enables relatively large fields of view without scanning the acoustic detector or acoustic beam path. Furthermore, it offers the potential for high-speed imaging within compact, miniature probe and could potentially facilitate the clinical translation of OR-OAM technology. [ABSTRACT FROM AUTHOR]

The pathways through which mature blood cells in the bone marrow (BM) enter the blood stream and exit the BM, hematopoietic stem cells in the peripheral blood return to the BM, and other substances exit the BM are referred to as the marrow–blood barrier (MBB). This barrier plays an important role in the restrictive sequestration of blood cells, the release of mature blood cells, and the entry and exit of particulate matter. In some blood diseases and tumors, the presence of immature cells in the blood suggests that the MBB is damaged, mainly manifesting as increased permeability, especially in angiogenesis. Some imaging methods have been used to monitor the integrity and permeability of the MBB, such as DCE-MRI, IVIM, ASL, BOLD-MRI, and microfluidic devices, which contribute to understanding the process of related diseases and developing appropriate treatment options. In this review, we briefly introduce the theory of MBB imaging modalities along with their clinical applications. [ABSTRACT FROM AUTHOR]

Echocardiographic evaluation of the right side of the heart is limited by inherent difficulties in accessing views, and thus a variety of other diagnostic modalities, including computed tomography, have been proposed for right heart evaluation. The aim of this cross-sectional study was to review previously reported data and add computed tomography as a new tool for assessment of the right side of the heart, using echocardiography as a reference. Physical examination, electrocardiogram, echocardiogram, and thoracic computed tomography images were acquired in 6 healthy dogs. Structural assessments of the right atrium, the right ventricle, and the pulmonary artery were performed. Data from computed tomography were compared with conventional echocardiography. The agreement between the techniques was satisfactory for most of the evaluated parameters. There was no correlation between tomographic variables and weight and heart rate. Males had a higher mean basal right ventricle diameter (20.92 ± 1.45) compared to females (16.84 ± 0.03). There was a statistically significant difference between the medium right ventricle, right atrium, right ventricle free wall, aorta, pulmonary artery, and left ventricle diameters and the right ventricle/ left ventricle ratio between computed tomography and ultrasound. Good repeatability was found for the tomographic analyses, and the coefficients of variation were similar for most variables between the intraobserver and interobserver analyses. Computed tomography-derived measurements are simple to perform and have good repeatability and satisfactory agreement for most of the parameters evaluated on the echocardiogram. [ABSTRACT FROM AUTHOR]

As a sign of chronic kidney disease (CKD) progression, renal fibrosis is an irreversible and alarming pathological change. The accurate diagnosis of renal fibrosis depends on the widely used renal biopsy, but this diagnostic modality is invasive and can easily lead to sampling error. With the development of imaging techniques, an increasing number of noninvasive imaging techniques, such as multipara meter magnetic resonance imaging (MRI) and ultrasound elastography, have gained attention in assessing kidney fibrosis. Depending on their ability to detect changes in tissue stiffness and diffusion of water molecules, ultrasound elastography and some MRI techniques can indirectly assess the degree of fibrosis. The worsening of renal tissue oxygenation and perfusion measured by blood oxygenation level-dependent MRI and arterial spin labeling MRI separately is also an indirect reflection of renal fibrosis. Objective and quantitative indices of fibrosis may be available in the future by using novel techniques, such as photoacoustic imaging and fluorescence microscopy. However, these imaging techniques are susceptible to interference or may not be convenient. Due to the lack of sufficient specificity and sensitivity, these imaging techniques are neither widely accepted nor proposed by clinicians. These obstructions must be overcome by conducting technology research and more prospective studies. In this review, we emphasize the recent advancement of these noninvasive imaging techniques and provide clinicians a continuously updated perspective on the assessment of kidney fibrosis. [ABSTRACT FROM AUTHOR]

Purpose of Review: To analyze the pathophysiologic importance of the right heart in different types of congenital heart disease (CHD), summarize current diagnostic modalities, and discuss treatment options. Recent Findings: The right ventricle (RV) plays a key role in disease progression and prognosis, either as the subpulmonary or as the systemic ventricle. Volume and/or pressure overload as well as intrinsic myocardial disease are the main factors for RV remodeling. Echocardiography and cardiac magnetic resonance imaging are important noninvasive modalities for assessing anatomy, size, and function of the right heart. Timely repair of related lesions is essential for preventing RV dysfunction. Few inconclusive data exist on conventional pharmacotherapy in CHD-related RV dysfunction. Cardiac resynchronization therapy and ventricular assist devices are an option in patients with advanced systemic RV failure. Summary: Right heart disease is highly related with adverse clinical outcomes in CHD. Research should focus on early identification of patients at risk and development of medical and interventional treatments that improve RV function. [ABSTRACT FROM AUTHOR]

The glymphatic system is a newly discovered waste-clearing system that is analogous to the lymphatic system in our central nervous system. Furthermore, disruption in the glymphatic system has also been associated with many neurodegenerative disorders (e.g., Alzheimer’s disease), traumatic brain injury, and subarachnoid hemorrhage. Thus, understanding the function and structure of this system can play a key role in researching the progression and prognoses of these diseases. In this review article, we discuss the current ways to map the glymphatic system and address the advances being made in preclinical mapping. As mentioned, the concept of the glymphatic system is relatively new, and thus, more research needs to be conducted in order to therapeutically intervene via this system.

The COVID-19 pandemic, caused by a novel coronavirus, has become a global epidemic. Although the reverse transcription-polymerase chain reaction (RT-PCR) test is the current gold standard for detecting the virus, its low reliability has led to the use of CT and X-ray imaging in diagnostics. As limited vaccine availability necessitates rapid and accurate detection, this study applies k-means and fuzzy c-means segmentation to CT and X-ray images to classify COVID-19 cases as either diseased or healthy for CT scans and diseased, healthy, or non-COVID pneumonia for X-rays. Our research employs four open-access, widely-used datasets and is conducted in four stages: preprocessing, segmentation, feature extraction, and classification. During feature extraction, we employ the Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Pattern (LBP), and Histogram of Oriented Gradients (HOG). In the classification process, our approach involves utilizing k-Nearest Neighbor (kNN), Support Vector Machines (SVM), and Extreme Learning Machines (ELM) techniques. Our research achieved a sensitivity rate exceeding 99%, which is higher than the 60-70% sensitivity rate of PCR tests. As a result, our study can serve as a decision support system that can help medical professionals make rapid and precise diagnoses with a high level of sensitivity.

Resumen: La extracción de dispositivos de estimulación cardiaca es una técnica segura en manos expertas, con una tasa de complicaciones entre el 0,5-15%. Estas complicaciones deben ser conocidas y siempre tenidas en cuenta por el operador, por lo que es siempre útil poder prevenirlas o al menos minimizar sus consecuencias.El objetivo de este trabajo es poner en valor la utilidad de las técnicas de imagen como herramientas diagnósticas que nos permiten realizar un abordaje seguro en la extracción de dispositivos, analizando sus características esenciales.La radiografía de tórax convencional aporta información del estado del generador y los electrodos (número, tipo, fijación, estado y recorrido). La tomografía axial computarizada (TAC) nos revela el recorrido intravascular de los electrodos, las eventuales perforaciones en las cámaras cardiacas, una obstrucción en la vena cava superior y, también, la enfermedad asociada. La tomografía por emisión de positrones/TAC (PET/TAC) nos ayuda a diagnosticar en algunos casos una infección incierta. La ecocardiografía intraoperatoria permite un registro dinámico de las cavidades cardiacas, detectando de forma precoz las eversiones bajo tracción del ventrículo derecho y las roturas valvulares o cardiacas que pueden ocurrir durante el procedimiento. La toracoscopia permite además, bajo visión directa el diagnóstico precoz de complicaciones vasculares (subclavias, tronco innominado y cava superior) o cardiacas. Finalmente, con la realidad aumentada obtenemos imágenes en 3D que superponemos con las obtenidas por radioscopia, identificando bucles y adherencias con mucha facilidad.En conclusión, las técnicas de imagen son una ayuda esencial para la prevención de complicaciones durante la extracción percutánea y, en caso de producirse, actuar rápidamente en consecuencia. Abstract: The removal of cardiac pacing devices is a safe technique in experienced hands, with a complication rate between 0.5-15%. These complications should be known and always taken into account by the operator, so it is always useful to prevent them or, at least, minimize their consequences.The aim of this work is to highlight the usefulness of imaging techniques as diagnostic Con tecnología de Editorial Manager® y ProduXion Manager® de Aries Systems Corporation tools that allow us to perform a safe approach in the extraction of devices, analyzing their essential characteristics.Conventional chest X-ray provides information on the state of the generator and electrodes (number, type of electrode, fixation, state and route). Axial computed tomography reveals the intravascular path of the electrodes, possible perforations in cardiac chambers, obstruction in the superior vena cava and associated pathology.Positron emission tomography (PET-CT) helps us to diagnose in some cases an uncertain infection. Intraoperative echocardiography allows a dynamic recording of the cardiac cavities, detecting early eversions under traction of the RV and valvular or cardiac ruptures that may occur during the procedure. Thoracoscopy also allows early diagnosis of vascular (subclavian, innominate trunk and superior cava) or cardiac complications under direct vision. Finally, with Augmented Reality we obtain 3D images that we superimpose with those obtained by fluoroscopy, identifying loops and adhesions very easily.In conclusion, imaging techniques are an essential aid in preventing complications during percutaneous extraction and, should they occur, to act quickly accordingly.

Host-pathogen interactions play a critical role in infectious diseases, and understanding the underlying mechanisms is vital for developing effective therapeutic strategies. The visualization and characterization of bacterial proteins within host cells is key to unraveling the dynamics of these interactions. Various protein labeling strategies have emerged as powerful tools for studying host-pathogen interactions, enabling the tracking, localization, and functional analysis of bacterial proteins in real-time. However, the labeling and localization of Salmonella secreted type III secretion system (T3SS) effectors in host cells poses technical challenges. Conventional methods disrupt effector stoichiometry and often result in non-specific staining. Bulky fluorescent protein fusions interfere with effector secretion, while other tagging systems such as 4Cys-FLaSH/Split-GFP suffer from low labeling specificity and a poor signal-to-noise ratio. Recent advances in state-of-the-art techniques have augmented the existing toolkit for monitoring the translocation and dynamics of bacterial effectors. This comprehensive review delves into the bacterial protein labeling strategies and their application in imaging host-pathogen interactions. Lastly, we explore the obstacles faced and potential pathways forward in the realm of protein labeling strategies for visualizing interactions between hosts and pathogens.

BackgroundPulmonary atelectasis is a commonly occurs during anesthesia. In these cases, mechanical ventilation (MV) associated with alveolar recruitment maneuvers (ARMs) and positive end-expiratory pressure (PEEP) is indicated to reverse the condition, ensure adequate gas exchange and improve oxygenation. ARMs can trigger volutrauma, barotrauma, and atelectrauma. Therefore, computed tomography (CT) is the gold-standard method for monitoring lung aeration after ARM.ObjectiveTo evaluate lung volume distribution after stepwise ARMs using computed tomography (CT).MethodsTwelve dogs weighing 24.0 ± 6.0 kg, aged 3 ± 1 years, of both sexes and different breeds, underwent orchiectomy or ovariohysterectomy. The animals were anesthetized and ventilated in volume-controlled mode. ARMs were then initiated by positive end-expiratory pressure (PEEP) titration (5, 10, 15, and 20 cmH2O). CT scans, cardiovascular parameters, and ventilatory mechanics were evaluated at all time points. Data were assessed for normality using the Shapiro–Wilk test and a two-way analysis of variance, followed by a post-hoc Bonferroni test to identify differences between time points. Statistical significance was attributed to a value of p of

Lung neuroendocrine neoplasms (LNENs) are lesions originating from diffuse endocrine cells within the bronchial walls and lung parenchyma. In recent years, there have been significant advances in the diagnosis and therapy of these neoplasms. This paper reviews recent developments in these areas, focusing on the latest research and treatment strategies. In the context of diagnosis, new imaging technologies including high-resolution computed tomography (CT), high-resolution and positron emission tomography-computed tomography (PET-CT) imaging, are providing more precise information on tumor spread and evaluation of metabolic activity. Advances in the field of molecular biomarkers allow a more personalized approach to the diagnosis of LNENs. In the therapeutic area, new targeted drugs and immunotherapy are showing promise in the treatment of LNENs. The development of molecular therapies such as tyrosine kinase inhibitors and somatostatin analogs, is opening up new treatment perspectives, increasing the efficacy of therapy, and improving patient quality of life. The paper also focuses on important research directions and clinical advances in the diagnosis and therapy of LNENs, presenting the current state of knowledge about these rare tumors. The conclusions aim to provide a synthetic view of the latest developments in the field, encouraging further research and improving treatment strategies for LNENs. [ABSTRACT FROM AUTHOR]

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Abstract Neuropragmatics investigates brain functions and neural activities responsible for pragmatic language abilities, often impaired in disorders such as hemisphere damage, autism, schizophrenia, and neurodegenerative disorders. This study examined the development of neuropragmatics and existing neuroimaging evidence using bibliometric and scientometric indicators, analyzing 4,247 documents published between 1967 and 2022 with CiteSpace and VOSviewer. Our cluster analysis revealed key themes. 1) Language comprehension loss due to brain injury: Studies exploring the impact of brain injuries on language comprehension and underlying neural mechanisms. 2) Right hemisphere damage and pragmatic language skills: Research focusing on the relationship between right hemisphere damage and pragmatic language abilities, investigating impairments in social language use and potential neural correlates. 3) Traumatic brain injury and social communication assessment: Research on traumatic brain injury effects on social communication skills, using various assessment tools to evaluate communication effectiveness in social situations. These clusters provide valuable insights into the neuropragmatics field and serve as a framework for future investigations. By building upon existing knowledge, researchers can improve our understanding of brain functions, language behavior, and enhance rehabilitation for individuals with pragmatic language impairments. [ABSTRACT FROM AUTHOR]

Some reports in the literature show the advantages of fluoride-containing apatite ceramics over hydroxyapatite (HAP), at least in some aspects. While HAP has been used extensively in the treatment of bone defects, fluoridated apatite has hardly been tested in vivo. In order to verify the biological properties of fluoride-doped apatite and to assess its therapeutic potential, we synthesized fluorapatite (FAP) and applied it as a filling in bone defects of experimental animals (rabbits). The treatment effects were evaluated on extracted bones after 3 and 6 months from implantation using peripheral quantitative computed tomography (pQCT), dual-energy X-ray absorptiometry (DXA), radiography (X-ray) and histological staining. The study proved the integration between FAP and the bone tissue, thus indicating its stimulating effect on new bone formation and mineralization. The results achieved after 3 months of treatment were difficult to interpret unequivocally and suggested the transient delay in FAP integration of bone in comparison with HAP. The reasons for this phenomenon are unclear. Most likely, these differences between FAP and HAP resulted mainly from the different porosities, densities and ionic reactivity of the ceramics, which in our opinion affected their solubility, integration and degree of bone tissue resorption. However, it was shown that 6 months after implantation, similar level of bone defect regeneration was achieved for both FAP and HAP. In this article, we present our hypothesis concerning the basis of this phenomenon. [ABSTRACT FROM AUTHOR]

In the last two decades, forensic pathology and crime scene investigations have seen a rapid increase in examination tools due to the implementation of several imaging techniques, e.g., CT and MR scanning, surface scanning and photogrammetry. These tools encompass relatively simple visualization tools to powerful instruments for performing virtual 3D crime scene reconstructions. A multi-modality and multiscale approach to a crime scene, where 3D models of victims and the crime scene are combined, offers several advantages. A permanent documentation of all evidence in a single 3D environment can be used during the investigation phases (e.g., for testing hypotheses) or during the court procedures (e.g., to visualize the scene and the victim in a more intuitive manner). Advanced computational approaches to understand what might have happened during a crime can also be applied by, e.g., performing a virtual animation of the victim in the actual context, which can provide important information about possible dynamics during the event. Here, we present an overview of the different techniques and modalities used in forensic pathology in conjunction with crime scene investigations. Based on our experiences, the advantages and challenges of an image-based multi-modality approach will be discussed, including how their use may introduce new visualization modalities in court, e.g., virtual reality (VR) and 3D printing. Finally, considerations about future directions in research will be mentioned. [ABSTRACT FROM AUTHOR]

The glymphatic system is a newly discovered waste-clearing system that is analogous to the lymphatic system in our central nervous system. Furthermore, disruption in the glymphatic system has also been associated with many neurodegenerative disorders (e.g., Alzheimer's disease), traumatic brain injury, and subarachnoid hemorrhage. Thus, understanding the function and structure of this system can play a key role in researching the progression and prognoses of these diseases. In this review article, we discuss the current ways to map the glymphatic system and address the advances being made in preclinical mapping. As mentioned, the concept of the glymphatic system is relatively new, and thus, more research needs to be conducted in order to therapeutically intervene via this system. [ABSTRACT FROM AUTHOR]

Today there is a rapid development taking place in phenotyping of plants using non-destructive image based machine vision techniques. Machine vision based plant phenotyping ranges from single plant trait estimation to broad assessment of crop canopy for thousands of plants in the field. Plant phenotyping systems either use single imaging method or integrative approach signifying simultaneous use of some of the imaging techniques like visible red, green and blue (RGB) imaging, thermal imaging, chlorophyll fluorescence imaging (CFIM), hyperspectral imaging, 3-dimensional (3-D) imaging or high resolution volumetric imaging. This paper provides an overview of imaging techniques and their applications in the field of plant phenotyping. This paper presents a comprehensive survey on recent machine vision methods for plant trait estimation and classification. In this paper, information about publicly available datasets is provided for uniform comparison among the state-of-the-art phenotyping methods. This paper also presents future research directions related to the use of deep learning based machine vision algorithms for structural (2-D and 3-D), physiological and temporal trait estimation, and classification studies in plants.

Liver cancer is a common tumor that seriously threatens human life and health. Given that the early onset of liver cancer is insidious and lacks specific symptoms, hence it is difficult to screen through routine examination. Thus, clinical diagnosis of liver cancer is mostly in the advanced stage. However, advanced liver cancer has few treatment options, poor prognosis and high relapse rate, thereby causing a high mortality rate. Therefore, early diagnosis of liver cancer is particularly important. Currently, non-invasive screening of liver cancer widely used in clinical setups lacks sufficient sensitivity and specificity, hence, a more reliable diagnostic method needs to be found urgently. This article reviews the research progress of noninvasive early diagnosis of liver cancer to provide a reference for raising the early diagnosis rate of liver cancer.

Key points Sharp convolution kernel combined with ADMIRE iterative reconstruction improves the imaging efficacy. 80 kV tube voltage with high flow contrast agent ensures the perforator enhancement. Cinematic rendering reconstruction model facilitates the visualization of perforator anatomic variations. Preoperative CTA mapping contributes to the localization and design of the ALTP flap.

Preterm birth is a leading cause of neonatal mortality and morbidity, affecting more than 15 million babies worldwide each year. Preterm infants also have higher rates of motor, functional, and cognitive deficits. Modern imaging has contributed significantly to a better understanding of the etiology of various forms of brain injury in neonates. The follow-up of premature newborns is essential to prevent and diminish neurological sequelae in time. A multi-disciplinary team is needed to adequately monitor this category of children, in which the family doctor has a significant role. The variety of adverse events that preterm infants can be exposed to before, during, and after birth poses significant obstacles to developing therapeutic interventions to prevent brain damage, including developmental vulnerability to injury during a particular gestational age. In addition, several procedures required for neonatal critical care, reduce mortality but increase the risk of brain injury. This review is aimed to update the reader about the complications of preterm birth, current therapeutic uses, imaging techniques, as well as present and future research on preterm birth.

High-resolution optoacoustic imaging at depths beyond the optical diffusion limit is conventionally performed using a microscopy setup where a strongly focused ultrasound transducer samples the image object point-by-point. Although recent advancements in miniaturized ultrasound detectors enables one to achieve microscopic resolution with an unfocused detector in a tomographic configuration, such an approach requires illuminating the entire object, leading to an inefficient use of the optical power, and imposing a trans-illumination configuration that is limited to thin objects. We developed an optoacoustic micro-tomography system in an epi-illumination configuration, in which the illumination is scanned with the detector. The system is demonstrated in phantoms for imaging depths of up to 5 mm and in vivo for imaging the vasculature of a mouse ear. Although image-formation in optoacoustic tomography generally requires static illumination, our numerical simulations and experimental measurements show that this requirement is relaxed in practice due to light diffusion, which homogenizes the fluence in deep tissue layers. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, caused by a novel coronavirus, has become a global epidemic. Although the reverse transcription-polymerase chain reaction (RT-PCR) test is the current gold standard for detecting the virus, its low reliability has led to the use of CT and X-ray imaging in diagnostics. As limited vaccine availability necessitates rapid and accurate detection, this study applies k-means and fuzzy c-means segmentation to CT and X-ray images to classify COVID-19 cases as either diseased or healthy for CT scans and diseased, healthy, or non-COVID pneumonia for X-rays. Our research employs four open-access, widely used datasets and is conducted in four stages: preprocessing, segmentation, feature extraction, and classification. During feature extraction, we employ the Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Pattern (LBP), and Histogram of Oriented Gradients (HOG). In the classification process, our approach involves utilizing k-Nearest Neighbor (kNN), Support Vector Machines (SVM), and Extreme Learning Machines (ELM) techniques. Our research achieved a sensitivity rate exceeding 99%, which is higher than the 60-70% sensitivity rate of PCR tests. As a result, our study can serve as a decision support system that can help medical professionals make rapid and precise diagnoses with a high level of sensitivity. [ABSTRACT FROM AUTHOR]

Featured Application: Telescopes, remote sensing, and surveying instruments, incorporating highly specialized requirements, from a compact design to one with a wide field of view for remote sensing applications. Each may be designed starting from the paraxial optics (first principles), featuring a three-element on-axis system, and using only the paraxial optics as displayed in the Y-Ȳ diagram. The off-axis three-mirror optical system is derived from the classical Cooke triplet or a derivative of the inverse-telephoto lens. By properly arranging an internal reimaging mechanism or altering the location of the optical stop, one can create different versions of three-mirror optical systems. They include very compact configurations and wide field-of-view imagers. Insights into the optical design process, manufacturing, stray light management, and remote sensing applications are presented. [ABSTRACT FROM AUTHOR]

The performance of asphalt concrete (AC) mixtures depends highly on their internal structure and the interaction of the mixture components under different loading conditions. Imaging techniques provide effective tools that can assess the microstructure and failure mechanisms of materials. Imaging techniques have been used in recent research studies to examine and analyze the evolution of the internal structure of AC mixtures resulting from traffic and environmental loading. Increasing knowledge of the microstructural properties and mechanical behaviour of AC mixtures could improve the design process and enable researchers to develop more accurate prediction models for the long-term performance of pavements. This paper reviews three imaging techniques which were used to characterize the microstructure of AC mixtures. These three imaging techniques are digital camera imaging, scanning electron microscope (SEM) imaging, and X-ray computed tomography (CT) scan. Extensive insight has been presented into these imaging techniques, including their principles, methods, sample preparation, and associated instruments. This review provides guidelines for future research on using these imaging techniques to analyze the microstructure of AC mixtures and assess their long-term performance. [ABSTRACT FROM AUTHOR]

Dual or multimodal imaging probes have emerged as powerful tools that improve detection sensitivity and accuracy in disease diagnosis by imaging techniques. Two imaging techniques that are complementary and do not use ionizing radiation are magnetic resonance imaging (MRI) and optical fluorescence imaging (OFI). Herein, we prepared metal-free organic species based on dendrimers with magnetic and fluorescent properties as proof-of-concept of bimodal probes for potential MRI and OFI applications. We used oligo(styryl)benzene (OSB) dendrimers core that are fluorescent on their own, and TEMPO organic radicals anchored on their surfaces, as the magnetic component. In this way, we synthesized six radical dendrimers and characterized them by FT-IR, 1H NMR, UV-Vis, MALDI-TOF, SEC, EPR, fluorimetry, and in vitro MRI. Importantly, it was demonstrated that the new dendrimers present two properties: on one hand, they are paramagnetic and show the ability to generate contrast by MRI in vitro, and, on the other hand, they also show fluoresce emission. This is a remarkable result since it is one of the very few cases of macromolecules with bimodal magnetic and fluorescent properties using organic radicals as the magnetic probe. [ABSTRACT FROM AUTHOR]