Features Of Instrument Research Articles

Enhancing the selection of heart failure patients for invasive procedures: how machine learning can predict the diagnostic yield of endomyocardial biopsy

Abstract Background Determining the etiology of heart failure (HF) is crucial for appropriate treatment. Endomyocardial biopsy (EMB) is an invasive procedure that complements clinical assessment and imaging in diagnosing various cardiac disorders. The diagnostic value of EBM depends upon the anticipated yield of the procedure. Whether results from non-invasive examinations may predict the diagnostic yield from EMB is unclear. Purpose We aimed to investigate the relative importance of clinical and instrumental features in predicting a diagnostic EMB result, using a machine learning (ML) approach. Methods We retrospectively examined 665 consecutive adult patients with HF symptoms who underwent right EBM as part of their diagnostic work-up. The primary outcome was a positive biopsy result with a clear diagnosis. The ML algorithm consisted of Gradient Boosting Machines (GBM), with computation of relative variable importance using conditional importance. We calculated the conditional variable importance for 53 clinical or instrumental variables. Model performance was evaluated using a receiver operating characteristic curve, which was compared to a logistic regression model using the same variables. Validation was performed using a 10-fold cross-validation model. Results Among the 665 patients (50±14 years, 67% male), the EMB provided a diagnosis in 138 cases (20.8%). Patients attaining diagnosis were more often older, had a shorter disease duration, presented with ventricular arrhythmia or cardiac arrest, had a pacemaker or defibrillator, displayed higher creatinine, NT-proBNP and high-sensitive troponin T levels, and had smaller ventricular volumes with higher ejection fraction at CMR. All patients with a diagnostic EMB showed late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in the right ventricle, the right atrium or in the left atrium. The relative importance of different variables predicting outcomes is presented in Figure 1. The top six included four distinct CMR features and two circulating biomarkers (NT-proBNP and high-sensitive troponin T). LGE in the right ventricle and the presence of left ventricular hypertrophy were stronger predictors compared to the remaining variables. The GBM model performed significantly better than the logistic regression model (AUC GBM 0.98, AUC logistic regression 0.93, DeLong’s test p<0.001) (Figure 2). Conclusion Using a ML algorithm, CMR LGE, left ventricular hypertrophy, and elevated cardiac biomarkers, stand out as strong overall predictors of an endomyocardial biopsy with a high diagnostic yield.Figure 1Figure 2

Approach for evaluating the effectiveness of ex vivo root canal instrumentation using microtomography

Endodontic treatment of a tooth involves effective elimination of the infectious process localized in the tooth cavity and root canals. The process of root canal treatment is carried out using specialized rotary instruments (files). In this paper, an approach is proposed for evaluating the effectiveness of root canal treatment using the ProTaper Next file system ex vivo using computed X-ray microtomography and VGSTUDIO MAX 3.5 software. This approach involves comparison of three-dimensional tooth models before and after the endodontic instrumentation procedure, segmentation, calculation of the root canal volume using software according to a specially developed protocol, as well as a study of their microgeometry. As an example of using the approach, a study of the features of root canal instrumentation of two- and three-rooted human molars is presented. The developed approach demonstrated high effectiveness in the process of examining human teeth, while the endodontic procedure was effective for both two- and three-rooted molars in terms of removing the internal biological content of the canals, which indicates the reliability of the applied method. The developed approach can be applied to evaluate the effectiveness of liquid dental materials and antibacterial solutions used during endodontic treatment of teeth.

TWINKLE: An open-source two-photon microscope for teaching and research.

Many laboratories use two-photon microscopy through commercial suppliers, or homemade designs of considerable complexity. The integrated nature of these systems complicates customization, troubleshooting as well as grasping the principles of two-photon microscopy. Here, we present "Twinkle": a microscope for Two-photon Imaging in Neuroscience, and Kit for Learning and Education. It is a fully open, high-performance and cost-effective research and teaching microscope without any custom parts beyond what can be fabricated in a university machine shop. The instrument features a large field of view, using a modern objective with a long working distance and large back aperture to maximize the fluorescence signal. We document our experiences using this system as a teaching tool in several two week long workshops, exemplify scientific use cases, and conclude with a broader note on the place of our work in the growing space of open-source scientific instrumentation.

Dual-stage semantic segmentation of endoscopic surgical instruments.

Endoscopic instrument segmentation is essential for ensuring the safety of robotic-assisted spinal endoscopic surgeries. However, due to the narrow operative region, intricate surrounding tissues, and limited visibility, achieving instrument segmentation within the endoscopic view remainschallenging. This work aims to devise a method to segment surgical instruments in endoscopic video. By designing an endoscopic image classification model, features of frames before and after the video are extracted to achieve continuous and precise segmentation of instruments in endoscopicvideos. Deep learning techniques serve as the algorithmic core for constructing the convolutional neural network proposed in this study. The method comprises dual stages: image classification and instrument segmentation. MobileViT is employed for image classification, enabling the extraction of key features of different instruments and generating classification results. DeepLabv3+ is utilized for instrument segmentation. By training on distinct instruments separately, corresponding model parameters are obtained. Lastly, a flag caching mechanism along with a blur detection module is designed to effectively utilize the image features in consecutive frames. By incorporating specific parameters into the segmentation model, better segmentation of surgical instruments can be achieved in endoscopicvideos. The classification and segmentation models are evaluated on an endoscopic image dataset. In the dataset used for instrument segmentation, the training set consists of 7456 images, the validation set consists of 829 images, and the test set consists of 921 images. In the dataset used for image classification, the training set consists of 2400 images and the validation set consists of 600 images. The image classification model achieves an accuracy of 70% on the validation set. For the segmentation model, experiments are conducted on two common surgical instruments, and the mean Intersection over Union (mIoU) exceeds 98%. Furthermore, the proposed video segmentation method is tested using videos collected during surgeries, validating the effectiveness of the flag caching mechanism and blur detection module. Experimental results on the dataset demonstrate that the dual-stage video processing method excels in performing instrument segmentation tasks under endoscopic conditions. This advancement is significant for enhancing the intelligence level of robotic-assisted spinal endoscopic surgeries.

Assessment of validity and reliability of the feedback quality instrument

BackgroundThe purpose was to investigate the psychometric features of the Feedback Quality Instrument (FQI) in medical students, emphasizing the instrument’s utility for evaluating the quality of feedback provided in clinical contexts and the importance of performing so for medical trainees.Methods and materialThe Persian version of the FQI was evaluated for content validity through a focus group of medical education experts. The questionnaire’s face, content, and construct validity were assessed using Confirmatory Factor Analysis, internal consistency, and inter-rater reliability. The questionnaire was revised and pilot-tested, with medical students’ feedback in different clinical situations. The data was analyzed using AMOS26.ResultsThe content validity index equaled 0.88(> 0.79). The content validity ratio representing the proportion of participants who agreed on a selected item was 0.69(> 0.42). According to experts, item 25 is the only modified item, while items 23 and 24 are presented as one item. For reliability, Cronbach alpha was equaled to 0.98.ConclusionsThe Persian version of the Feedback Quality Instrument (FQI) was valid, reliable, and fair in assessing feedback quality in medical students, providing valuable insights for other institutions. Establishing a basis for systematically analyzing how certain educator behaviors affect student outcomes is practical.

Measuring the quality of philosophical dialogue: a high-inference rating instrument for research and teacher education

Various studies have shown that philosophizing with children at school can have a positive effect on cognitive, language and social skills. However, previous studies have not considered how the quality of the dialogue influences these outcomes. Addressing this gap, our article introduces a high-inference rating instrument to assess the quality of philosophical dialogue. This instrument features four quality dimensions: Philosophical Richness, Co-construction, Focus, and Restrained Facilitation. It was applied to evaluate 63 class dialogues from a Swiss study involving secondary-school students. The article presents the instrument using excerpts from the study, along with initial validation information, showing its reliability in measuring philosophical dialogue quality. The significance of this research lies in its focus on the quality of philosophical dialogue, an aspect often overlooked in educational settings. By providing a tool to assess this quality, we open up new pathways for analyzing the effectiveness of philosophical dialogues in schools. This is especially relevant as educational systems increasingly recognize the importance of developing students' critical thinking and discussion skills. The findings highlight the potential of high-quality philosophical dialogues to enrich students' educational experiences and offer insights for educators and researchers into enhancing these interactions. This study contributes to a deeper understanding of how philosophical dialogue can be used as a powerful educational tool, not just for engaging students but for fostering meaningful and impactful learning.

An Identification Potential of Legal Values in a Transitive Society

The article examines the role of legal values in the social identification of citizens in a transitive society. Based on the analysis of the value foundations of legislation and its role in the construction of social identification, a conclusion is made about the primacy of the axiological level of legal reality over ontological ones in a transitive society. The constitutional identification of a person in these conditions is determined not by belonging to a certain nation and the implementation of the rules developed by it, but by positioning identification with the community on value grounds. Often, such identification is not so much an identification as an imitation, since it involves only articulating compliance with the rules, and not following them. Based on this, identification in a transitive society is situational and fragmented. In these conditions, the role of legislation in social identification is changing. It becomes a tool that the addressee of communication uses to broadcast to the addressee a system of values that ensure not only the identification of citizens, but also lawful behavior. At the same time, legislation, due to its instrumental features, is able to overcome transitivity and bring society to stable development and functioning.

Financing infrastructure projects: a review of definitional issues and thematic areas

The purpose of the article is to identify current problems and thematic areas of financing infrastructure projects. To do this, both a systematization of approaches is carried out on the basis of thematic analysis and a review of Russian and foreign sources is done. A methodological plurality of definitions of the main categories was discovered. Inductively identified thematic areas of research cover: general trends in the development of types of economic infrastructure, microanalysis of the creation of specific infrastructure facilities and local needs for infrastructure development, local economic impact of individual types of infrastructure, cross-sectoral effects of infrastructure development, integration aspects of the creation of infrastructure facilities, infrastructure in the context of sustainable development, features of instruments and forms of financing infrastructure projects, infrastructure facilities as a separate class of investment assets.

Legal regulation of the monetary system of the Russian Federation in the digital economy: financial and legal problems

The article discusses current problems of digitalization of the monetary system of the Russian Federation. A conclusion is made about the place and content of the sub-growth of the rights of the monetary system in the structure of financial law. It is argued that digitalization does not change the essence of financial relations, the essence of money as a financial and legal category, it only gives them an electronic form. The author’s assessments of the legal nature and qualifying features of new financial payment instruments that are a response to the challenges of the digital economy are given: electronic money, digital currencies, digital ruble. It is argued that they are subtypes of non-cash money circulation along with classic bank money. Proposals for improving the current legislation on the national payment system are substantiated in terms of systemic legal regulation of all types of digital forms of monetary circulation.

Survey of Students’ Experiences with Electronic Communication for Writing Improvement

The introduction of electronic communication has caused a considerable evolution in the dynamic interaction between teachers and students in today's educational environments. In order to improve writing skills in school settings, this study explores the transformative potential of internet communication. The present abstract outlines the complex features of this revolutionary teaching instrument, clarifying its many aspects and significant consequences for promoting writing abilities in learning environments. This investigation, which is based on constructivist pedagogy and cognitive learning theories, reveals the mutually beneficial connection between internet communications and increasing writing ability through leveraging the collaborative relationship between technology and education. Teachers can enable learners to reach their full creative potential and produce a generation of articulate speakers ready to handle the challenges of the digital age.

Machine learning-driven diagnostic signature provides new insights in clinical management of hypertrophic cardiomyopathy.

In an era of evolving diagnostic possibilities, existing diagnostic systems are not fully sufficient to promptly recognize patients with early-stage hypertrophic cardiomyopathy (HCM) without symptomatic and instrumental features. Considering the sudden death of HCM, developing a novel diagnostic model to clarify the patients with early-stage HCM and the immunological characteristics can avoid misdiagnosis and attenuate disease progression. Three hundred eighty-five samples from four independent cohorts were systematically retrieved. The weighted gene co-expression network analysis, differential expression analysis (|log2(foldchange)|>0.5 and adjusted P<0.05), and protein-protein interaction network were sequentially performed to identify HCM-related hub genes. With a machine learning algorithm, the least absolute shrinkage and selection operator regression algorithm, a stable diagnostic model was developed. The immune-cell infiltration and biological functions of HCM were also explored to characterize its underlying pathogenic mechanisms and the immune signature. Two key modules were screened based on weighted gene co-expression network analysis. Pathogenic mechanisms relevant to extracellular matrix and immune pathways have been discovered. Twenty-seven co-regulated genes were recognized as HCM-related hub genes. Based on the least absolute shrinkage and selection operator algorithm, a stable HCM diagnostic model was constructed, which was further validated in the remaining three cohorts (n=385). Considering the tight association between HCM and immune-related functions, we assessed the infiltrating abundance of various immune cells and stromal cells based on the xCell algorithm, and certain immune cells were significantly different between high-risk and low-risk groups. Our study revealed a number of hub genes and novel pathways to provide potential targets for the treatment of HCM. A stable model was developed, providing an efficient tool for the diagnosis of HCM.

Stochastic dynamics mass spectrometric structural analysis of poly(methyl methacrylate)

Polymers such as poly(methyl methacrylate), comprising of all-carbon backbones are regarded as ubiquitous functional materials mainly due to their low cost, unique physical properties, and impressive robustness. The latter properties are results from relative chemical inertness of the polymer backbone carbon–carbon bonds. The highlighted stability crucially challenges not only innovations to plastic recycling polymer materials, but also developments of reliable analytical protocols for determining both quantitatively and structurally polymers. Despite, the fact that there are numerous applications of mass spectrometric methods to polymer science, the analysis involves chiefly annotation of monomers of polymers and additives, owing to the fact that the additives are low molecular weight analytes. The exact structural determining of end-chain groups, particularly highlighting chemically substituted end carbon–carbon bond represents significant challenge even utilizing the superior features of the analytical mass spectrometric instrumentation. This study, in the latter context, illustrates innovative stochastic dynamics approach and model equations capable of not only determining unambiguously substituted carbon–carbon end chain of the entitled polymer but also to predict mass spectra of its derivatives: thus, extending crucially the applicability of the method to many fields of the fundamental scientific and industrial research. The latter claim is argued still at the beginning of the study with the achieved method performances showing |r|=0.99998. The study utilizes experimental and theoretical mass spectrometric data on high resolution electrospray ionization mass spectrometry; high accuracy quantum chemical static methods, molecular dynamics; and chemometrics.

Teaching Experimental Instrumental Analytical Chemistry Are we forming professionals, training operators or illuding students (and ourselves)?

Teaching Experimental Instrumental Analytical Chemistry Are we forming professionals, training operators or illuding students (and ourselves)?

SurgNet: Self-Supervised Pretraining With Semantic Consistency for Vessel and Instrument Segmentation in Surgical Images.

Blood vessel and surgical instrument segmentation is a fundamental technique for robot-assisted surgical navigation. Despite the significant progress in natural image segmentation, surgical image-based vessel and instrument segmentation are rarely studied. In this work, we propose a novel self-supervised pretraining method (SurgNet) that can effectively learn representative vessel and instrument features from unlabeled surgical images. As a result, it allows for precise and efficient segmentation of vessels and instruments with only a small amount of labeled data. Specifically, we first construct a region adjacency graph (RAG) based on local semantic consistency in unlabeled surgical images and use it as a self-supervision signal for pseudo-mask segmentation. We then use the pseudo-mask to perform guided masked image modeling (GMIM) to learn representations that integrate structural information of intraoperative objectives more effectively. Our pretrained model, paired with various segmentation methods, can be applied to perform vessel and instrument segmentation accurately using limited labeled data for fine-tuning. We build an Intraoperative Vessel and Instrument Segmentation (IVIS) dataset, comprised of ~3 million unlabeled images and over 4,000 labeled images with manual vessel and instrument annotations to evaluate the effectiveness of our self-supervised pretraining method. We also evaluated the generalizability of our method to similar tasks using two public datasets. The results demonstrate that our approach outperforms the current state-of-the-art (SOTA) self-supervised representation learning methods in various surgical image segmentation tasks.

Prospects of the Multi-channel Photometric Survey Telescope in the Cosmological Application of Type Ia Supernovae

The Multi-channel Photometric Survey Telescope (Mephisto) is a real-time, three-color photometric system designed to capture the color evolution of stars and transients accurately. This telescope system can be crucial in cosmological distance measurements of low-redshift (low-z, z ≲0.1) Type Ia supernovae (SNe Ia). To optimize the capabilities of this instrument, we perform a comprehensive simulation study before its official operation is scheduled to start. By considering the impact of atmospheric extinction, weather conditions, and the lunar phase at the observing site involving the instrumental features, we simulate light curves of SNe Ia obtained by Mephisto. The best strategy in the case of SN Ia cosmology is to take the image at an exposure time of 130 s with a cadence of 3 days. In this condition, Mephisto can obtain hundreds of high-quality SNe Ia to achieve a distance measurement better than 4.5%. Given the on-time spectral classification and monitoring of the Lijiang 2.4 m Telescope at the same observatory, Mephisto, in the whole operation, can significantly enrich the well-calibrated sample of supernovae at low-z and improve the calibration accuracy of high-z SNe Ia.

Posterior Semicircular Canal Dehiscence with Vestibulo-Ocular Reflex Reduction for the Affected Canal at the Video-Head Impulse Test: Considerations to Pathomechanisms.

Posterior semicircular canal dehiscence (PSCD) has been demonstrated to result in a third mobile window mechanism (TMWM) in the inner ear similar to superior semicircular canal dehiscence (SSCD). Typical clinical and instrumental features of TMWM, including low-frequency conductive hearing loss (CHL), autophony, pulsatile tinnitus, sound/pressure-induced vertigo and enhanced vestibular-evoked myogenic potentials, have been widely described in cases with PSCD. Nevertheless, video-head impulse test (vHIT) results have been poorly investigated. Here, we present six patients with PSCD presenting with a clinical scenario consistent with a TMWM and an impaired vestibulo-ocular reflex (VOR) for the affected canal on vHIT. In two cases, an additional dehiscence between the facial nerve and the horizontal semicircular canal (HSC) was detected, leading to a concurrent VOR impairment for the HSC. While in SSCD, a VOR gain reduction could be ascribed to a spontaneous "auto-plugging" process due to a dural prolapse into the canal, the same pathomechanism is difficult to conceive in PSCD due to a different anatomical position, making a dural herniation less likely. Alternative putative pathomechanisms are discussed, including an endolymphatic flow dissipation during head impulses as already hypothesized in SSCD. The association of symptoms/signs consistent with TMWM and a reduced VOR gain for the posterior canal might address the diagnosis toward PSCD.

The rise of nanomechanical biomarkers: how cell and tissue mechanics can help medicine?

The rise of nanomechanical biomarkers: how cell and tissue mechanics can help medicine? “MechaDynA” develops two novel nanotools to allow force measurements on living cells. The goal is to obtain a complete, multi-scale picture of the physics of leucocyte adhesion. Technologically, it will establish two nanotools for force measurements on living cells covering the widest temporal range. This will open the door to unexplored physical phenomena in cell biology, biological physics and soft condensed matter. Biomedically, the expected outcomes will provide a mechanistic description of the physics of leucocyte immune response that may lead to better diagnosis and therapeutics. “Phys2BioMed” aims to identify biomechanical markers for the early detection of disease. The objective is to create an interdisciplinary research training network for early-stage researchers on the application of physical tools for the mechanical phenotyping of cells and tissues applied to early diagnostics. The network merged training from fields such as nanotechnology, physics, biology and medicine, defining the main features of new-generation instrumentation optimised for the mechanical phenotyping of clinical samples.

Climatological reference stations: Definitions and requirements

AbstractGround‐based stations are one of many observing systems contributing to the generation of data to evaluate climate trends and variations locally and globally. Networks of stations are made of various numbers of observing sites, equipped with different typologies and varieties of instruments, differently managed and maintained. Among such networks a limited number of stations are required as a reference, to provide top quality traceable measurements and as the top level of a tiered approach; it is these stations which are here designated as Climatological Reference Stations (CRS). At present, there is no agreed definition of the key instrumental and technical features of a CRS, nor are there defined reference measurement procedures. This leads to the situation of a multitude of approaches among different National Meteorological and Hydrological Services (NMHSs), research institutes and other agencies that reduces the comparability of results in space and in time. The lack of CRSs, moreover, is a major contributor to the huge efforts required to harmonize data and detect biases locally, regionally and globally, as in their absence there is a need to fall back on other stations which are more likely to have such biases. This article reports on the outcomes of the work of a group of experts, nominated by the World Meteorological Organization (WMO) Commission for Climatology (CCI), tasked to promote a standardized and agreed concept about the definitions, specifications and technical characteristics of climate reference data and stations for ground‐based networks, with the addition of a practical example of climatological reference station installed in the framework of an European funded project, with the purpose of comparing and confirming the prescribed characteristics and guidance, with respect to practical field use and available instrumentation. The adoption of a unique definition and prescription on the technical setup, measurement procedures and uncertainty evaluation will substantially progress towards a common approach in detecting climate trends. This will improve data comparability in space and time and allow a more robust understanding of climate evolution locally and globally.

Bronchiectasis: literature review for preparation of 2024 clinical guidelines

Bronchiectasis, ICD-10 – J47, (BE) is a chronic respiratory disease characterized clinically by cough, sputum production and bronchial infection, and radiographically by abnormal and persistent dilation of the bronchi. Common causes include cystic fibrosis, primary ciliary dyskinesia, immune disorders, systemic inflammatory diseases and infections, and other factors. However, some cases are idiopathic, when the cause cannot be identified. In practice, patients with bronchiectasis are divided into two groups: associated and not associated with cystic fibrosis. The prevalence of the disease varies significantly worldwide; it is not reliably known in the Russian Federation.The aim of the review is to analyze the literature data on modern approaches to the diagnosis of BE and to familiarize readers with diagnostic methods and basic approaches to the treatment.Methods. Data from 77 articles and the expert opinion of specialists providing care to patients with BE were used.Results. The main causes, frequency of occurrence, clinical phenotypes and treatment approaches for BE are described. There are many clinical, laboratory, instrumental and radiological features that provide insight into the etiology of BE. The European consensus is that the goal of treating BE is to restore or maintain normal lung function. There are no randomized trials on the treatment of BE, so all treatment guidelines are based on very low-level evidence or extrapolated from cystic fibrosis guidelines. Recommendations for mucolytic, antibacterial and anti-inflammatory therapy for BE are described, taking into account international and national experience.Conclusion. The development of a new version of clinical guidelines with modern relevant information will improve the diagnosis and treatment of BE in the Russian Federation.

The Refl ection of the Timbre Characteristics of Chinese Folk Instruments in Piano Works by the Chinese Composer Chu Wanhua

The article discusses Chinese piano music and the refl ection of the timbre features of Chinese folk instruments in it. The author of the article focuses on the work of the outstanding Chinese composer Chu Wanhua as very revealing regarding the refl ection of the timbres of Chinese folk instruments in the piano sound. In his research, the author focuses on the composer’s three piano works. As a result of the work, the researcher comes to the conclusion that the refl ection of the timbre features of Chinese folk instruments in the piano works of Chinese composers is a way to preserve and enrich the piano music of the Celestial Empire. Chu Wanhua managed to create such works for piano (fi rst of all, “My Homeland” piano concerto), in which adherence to traditions is organically combined with modern composing techniques. The composer masterfully “weaves” the achievements of Western European pianistic art into the national musical tradition, demonstrating brilliant imitation of the timbres of Chinese folk instruments and outlining the ways of development of Chinese piano art.