Advanced Diagnostic Tools Research Articles

Comprehensive Guide to Paravalvular Leak: Symptoms, Effects, and Treatments.

Paravalvular leak (PVL) represents a common complication often encountered following valve replacement surgeries, posing significant diagnostic and therapeutic challenges within the field of cardiology. The condition, characterized by an abnormal flow of blood around the edges of a prosthetic valve, can lead to a spectrum of clinical manifestations, from asymptomatic states to severe heart failure or hemolysis. Its relevance is underscored by its contribution to morbidity and mortality among affected individuals, necessitating a deeper understanding of its etiology, diagnosis, and management. The exploration of advanced diagnostic tools, such as echocardiography, computed tomography, and magnetic resonance, alongside novel treatment approaches, underscores the dynamic and evolving landscape of PVL management. This is a concentrated guide to understand the various aspects related to PVL, starting with defining the condition to determine its short- and long-term effects on the patient. It will further direct the reader through diagnosis, going through the advancements made in cardiac imaging, especially three-dimensional modeling and echocardiography. The discussion of predisposing factors, technical considerations intrinsic to procedural interventions, and clinical implications is therefore an important part of the discourse and helps set a foundation for an in-depth exploration of contemporary and emerging treatment modalities. From the incorporation of various surgical and percutaneous techniques to the tactical uses of devices, in particular, the AMPLATZer Vascular Plug, associated with the technical development of transcatheter closure, the current review tries to present a panoramic view of PVL management, from diagnosis to closure and insight into mitigation of its impact on outcomes.

A rare Coffin-Siris syndrome induced by SOX11: a de novo nonsense variant of short stature.

Coffin-Siris syndrome is a clinically elusive and rare genetic disease characterized by a wide range of clinical manifestations. This study deeply analyzed and identified the clinical phenotype and genetic variant location in a pediatric patient with Coffin-Siris syndrome, aiming to enhance the understanding of this syndrome and assist in its screening and diagnosis. A combination of advanced diagnostic tools, including high-throughput whole-exome sequencing (WES) and first-generation sequencing technologies, was employed to ascertain the etiology of the disease in the child. The clinical phenotype was characterized by stunted growth, reduced stature, spina bifida, enuresis, and a ventricular septal defect. WES revealed a de novo variant in the SOX11 gene locus (c.700G > T), identified as pathogenic. It is noteworthy that this variant has not been previously reported. The combination of clinical presentation and genetic testing results supports that the patient suffers from Coffin-Siris syndrome due to a genetic variant in the SOX11 gene. This de novo variant expands our understanding of human gene variation, which is conducive to genetic counseling and screening for early diagnosis of Coffin-Siris syndrome.

Liver metastasized pancreatic neuroendocrine tumor in a 17-year-old female: A case report.

Pancreatic neuroendocrine tumors (PNETs) are rare and often misdiagnosed due to their vague symptoms and tumor heterogeneity. Early detection using computed tomography (CT) is essential, particularly in regions without access to advanced diagnostic tools like immunohistochemistry and genetic testing. Neuroendocrine tumors (NETs) are rare tumors in adults and extremely rare in the pediatric population, as pancreatic NETs (pNETs) have an incidence rate of <0.1 per million. We present a case of a 17-year-old female with a liver metastasized pNET. A 17-year-old female with a history of intermittent abdomen-back pain presented to the clinic with severe upper abdominal pain radiating to the shoulder. The routine tests were normal. An ultrasound showed multiple lesions in the liver, which were confirmed by a computed tomography (CT) that uncovered a pancreatic lesion too. A liver biopsy proved it was a metastasized pNET with positive NET markers on IMC staining. The metaiodobenzylguanidine (MIBG) scan flared the liver lesion. The patient was started on Octreotide long-acting release (LAR) 30 mg once monthly. The rarity of these tumors makes their diagnosis difficult, but they should not be omitted and must be considered when there are long-lasting symptoms that are not compatible with common illnesses. These tumors are curable in their early stages.

Identifying heart failure dynamics using multi-point electrocardiograms and deep learning

Abstract Background Heart failure (HF) hospitalizations are related to poor survival outcomes, emphasizing the need for early detection and intervention. Recent studies have reported the potential of deep learning algorithms in identifying heart failure through electrocardiogram (ECG) with notable accuracy. However, evidence supporting their utility in the ongoing monitoring and follow-up of HF patients remains uncertain. Advanced diagnostic tools that can effectively track heart failure progression or improvement over time are needed. Purpose To address this challenge, we developed a deep learning model analyzing 12-lead ECG waveforms at two time points, aiming to detect HF deterioration or improvement, potentially revolutionizing HF management. Methods This study analyzed 32,045 ECGs from 6,892 unique adult patients (aged 18 years and older) visiting the Department of Cardiology at Kobe University Hospital. The participants were randomly assigned to training (4,284 patients), validation (1,034 patients), and test (1,034 patients) datasets. ElecTransformer was developed to classify HF status into deteriorated, improved, and no change classes based on ECG waveform signals at two different time points and to estimate brain natriuretic peptide (BNP) levels. Performance metrics, such as the area under the receiver operating characteristic curve (AUROC) and accuracy, were calculated, and attention mapping via gradient-weighted class activation mapping was utilized to interpret the model's decision-making ability. Results The patients had an average age of 65 years (±15.4 years) and BNP levels averaged 71.5 pg/mL (25.8 to 185.2 pg/mL). For HF status classification, ElecTransformer achieved an AUROC of 0.845 and an accuracy of 0.821, improving to an AUROC of 0.885 and an accuracy of 0.833 with baseline BNP integration. The ElecTransformer accurately estimated BNP levels from ECG data, evidenced by a correlation coefficient of 0.798. Averaged attention mapping showed that the QRS complex was the most important feature for determining model outputs with lesser effects seen for P waves and T waves variance Conclusions Harnessing a Transformer-based deep learning model to analyze multiple ECGs markedly improves the accuracy in detecting changes in heart failure status. This method offers a valuable non-invasive option for monitoring heart failure progression, potentially leading to better patient management and earlier intervention in heart failure treatment.Architecture and Performance of ModelsAveraged attention mapping

Preventive Preservation of Rammed Earth Historical Heritage Through Continuous Monitoring, Architectural Inspections, and Data Fusion

Rammed earth construction, an ancient and sustainable building technique, faces significant preservation challenges, particularly in historical contexts. This study aims to enhance the preventive preservation of rammed earth historical heritage through a comprehensive methodology combining continuous monitoring, architectural inspections, and data fusion. By integrating nondestructive testing techniques such as ultrasound, thermography, and ground-penetrating radar with operational modal analysis and modeling, the proposed approach allows for early detection and assessment of structural vulnerabilities. This methodology was applied to the Tower of Muhammad in the Alhambra of Granada, Spain, demonstrating its effectiveness in identifying and quantifying damage and predicting structural health. Using multi-source data (documentation, inspections, nondestructive tests, and continuous monitoring), a finite element model was built, calibrated (achieving an avg. error in modal frequencies of 1.28% and a minimum modal assurance criterion value of 0.94), and used to develop a surrogate model able to predict the modal properties of the tower in 0.02 s, becoming compatible with continuous system identification. The presented results highlight the importance of continuous data acquisition and advanced diagnostic tools for safeguarding rammed earth structures against environmental and anthropogenic threats. This study advocates for the adoption of digital twins in historical preservation, facilitating informed decision-making and sustainable management of cultural heritage.

Solid pancreatic masses: What’s hidden beneath? Insights into rare pancreatic lesions

The diagnostic approach to solid pancreatic masses has significantly evolved from the era when a focal pancreatic mass was almost synonymous to pancreatic ductal adenocarcinoma, to a wide spectrum of pancreatic lesions, some of which have good prognosis. With the advent of advanced diagnostic tools, particularly refined imaging and tissue acquisition techniques, a broader spectrum of differential diagnoses has been recognized, encompassing conditions ranging from neuroendocrine tumors or inflammatory masses, to rare entities like metastatic clear cell sarcoma or solitary fibrous tumors. We herein discuss case reports of some rare pancreatic lesions, which were diagnosed by combining clinical and imaging features and endoscopic ultrasound-guided tissue sampling and confirmed on surgical specimens. Further reports on these rare pancreatic tumors will contribute to a better understanding of their pathogenesis and effective management.

Dental outpatient departments and patient safety: Priority for a safe care

Patient safety is an essential aspect of healthcare, including dentistry. Dental Outpatient Departments (OPDs) pose unique challenges, where the risk of infections, procedural errors, and patient discomfort can compromise safety. This review examines patient safety issues in dental OPDs, focusing on common hazards, preventive measures, and evolving strategies to ensure safer care. Infection control, medical emergencies, equipment sterilization, and patient data protection are key concerns. The complex interplay of patient management, dental procedures, and clinician awareness requires robust protocols to mitigate risks. Dental professionals must be vigilant in managing cross-contamination risks, such as through the use of personal protective equipment (PPE) and strict hand hygiene practices. Moreover, regular staff training in handling medical emergencies, such as allergic reactions or fainting, is crucial for effective management.This article also explores the role of technological advancements in enhancing patient safety, such as digital record-keeping, which minimizes documentation errors, and advanced diagnostic tools that reduce invasive procedures. Additionally, patient-centered approaches, including improved communication and informed consent practices, foster trust and reduce misunderstandings. The implementation of evidence-based guidelines and adherence to professional standards further contribute to a culture of safety. By synthesizing current research, this review aims to highlight best practices for improving patient safety in dental OPDs and underscores the importance of continuous monitoring and improvement in these settings. Addressing these safety concerns is critical not only to improve patient outcomes but also to ensure that dental OPDs remain a safe and trusted environment for all.

Genetic Biomarkers in Heart Failure: From Gene Panels to Polygenic Risk Scores.

This review aims to provide a comprehensive overview of the current understanding of genetic markers associated with heart failure (HF) and its underlying causative diseases, such as cardiomyopathies. It highlights the relevance of genetic biomarkers in diagnosing HF, predicting prognosis, potentially identifying its preclinical stages and identifying targets to enable the implementation of individualized medicine approaches. The prevalence of HF is increasing due to an aging population but with greater access to disease-modifying therapies. Advanced diagnostic tools such as cardiac magnetic resonance, nuclear imaging, and AI-enabled diagnostic testing are now being utilized to further characterize HF patients. Additionally, the importance of genetic testing in HF diagnosis and management is increasingly being recognized. Genetic biomarkers, including single nucleotide polymorphisms (SNPs) and rare genetic variants, are emerging as crucial tools for diagnosing HF substrates, determining prognosis and increasingly directing therapy. These genetic insights are key to optimizing HF management and delivering personalized treatment tailored to individual patients. HF is a complex syndrome affecting millions globally, characterized by high mortality and significant economic burden. Understanding the underlying etiologies of HF is essential for improving management and clinical outcomes. Recent advances highlight the use of multimodal assessments, including AI-enabled diagnostics and genetic testing, to better characterize and manage HF. Genetic biomarkers are particularly promising in identifying preclinical HF stages and providing personalized treatment options. The genetic contribution to HF is heterogeneous, with both monogenic and polygenic bases playing a role. These developments underscore the shift towards personalized medicine in HF management.

Tuberculosis its Prevalence, Complications and Clinical Aspects among the Population of Northern Part of Bihar

Introduction: It is commonly known as death causing disease of reproductive age group people. It is one of the top five death causing disease. It effects upon every age group people. But dangerous impact of tuberculosis occurs on immunocompetent people. There are a number of complications occur only due to one disease that is tuberculosis. it effects almost all organs and impaired their vital functions. Even if we leave death, even after tuberculosis proved to be most dangerous disease. In this study our main aim to explore the aspects, complications and prevalence of genital tuberculosis. In this study we also explore the ancient technics as well as the modern technics and their methods to ruled out the disease and improvement of treatment from ancient time to modern time. Method: This study was carried out between January 22 to April 23. 342 subjects are selected by inclusion and exclusion method. Subjects are classified in to 3 groups according to their physical appearance clinical symptoms and family history. Further patients are again classified in to negative, positive and doubtful negative patients after conducting routine and special investigations. Results: After all pathological investigation we found that 45 (13.1%) subjects have found positive in which 5.8% were male and 7.2 % were female. Conclusion: Tuberculosis is present in different forms and should be ruled out in early stage to safe from tissue damages. But unfortunately, we haven’t any tools which can detect the disease in its early stage accurately. All the investigation has their own limitations and contamination errors. There are a number of patients in which some can easily identified by their clinical symptoms and related routine examination, some are asymptomatic and identified by advanced diagnostic tools where are some such patient are also found who were strong symptomatic but even not only routine but also advance investigations are fail to detect. In our study we found the root cause of the disease, which are high population density, economically lower standard, poor hygiene life style, compromise food habits, illiteracy, marriage in early stage, multiple marriage, multiple children, non- skilled medical practices are causing and enhancing the incident of tuberculosis.

Comparative analysis of international and Malaysia approaches to the treatment of patients with chronic gastritis from the point of view of evidence-based medicine

Background: Chronic gastritis, often resulting from *Helicobacter pylori* infection, is a widespread gastrointestinal disorder. The condition requires evidence-based treatment approaches to ensure effective management and improved patient outcomes. This study conducts a comparative analysis of the treatment approaches for chronic gastritis in Malaysia and internationally, focusing on adherence to evidence-based medicine (EBM) practices. Understanding the similarities and differences in these approaches is critical for enhancing Malaysia's healthcare strategies. Methods and Materials: The study employed a systematic review of relevant literature sourced from global medical databases, including PubMed, Embase, and Cochrane Library. The review focused on therapeutic options, diagnostic standards, and evidence-based protocols for managing chronic gastritis, with emphasis on both international and Malaysian healthcare systems. Studies included in the review primarily focused on adult patients diagnosed with chronic gastritis and treated using evidence-based methodologies. Results: The analysis revealed significant parallels in the treatment protocols between Malaysia and international guidelines, particularly in the use of proton pump inhibitors (PPIs) and antibiotic regimens for *H. pylori* eradication. However, differences emerged in the implementation of advanced diagnostic tools, accessibility of healthcare services, and the influence of local antibiotic resistance patterns. While Malaysia follows global best practices, rural-urban healthcare disparities impact the consistency of treatment delivery and patient outcomes. Conclusion: Both international and Malaysian approaches to chronic gastritis prioritize evidence-based medicine. The findings suggest that Malaysia effectively adapts international guidelines to its local healthcare context, though improvements are needed in addressing healthcare accessibility and antibiotic resistance. Enhanced implementation of EBM practices, particularly in rural areas, and personalization of treatment based on resistance patterns, could further optimize patient outcomes in Malaysia.

Whole Exome Sequencing and Panel-Based Analysis in 176 Spanish Children with Neurodevelopmental Disorders: Focus on Autism Spectrum Disorder and/or Intellectual Disability/Global Developmental Delay

Background: Neurodevelopmental disorders (NDDs) represent a significant challenge in pediatric genetics, often requiring advanced diagnostic tools for the accurate identification of genetic variants. Objectives: To determine the diagnostic yield of whole exome sequencing (WES) with targeted gene panels in children with neurodevelopmental disorders (NDDs). Methods: This observational, prospective study included a total of 176 Spanish-speaking pediatric patients with neurodevelopmental disorders (NDDs), encompassing intellectual disability (ID), global developmental delay (GDD), and/or autism spectrum disorder (ASD). Participants were recruited from January 2019 to January 2023 at a University Hospital in Madrid, Spain. Clinical and sociodemographic variables were recorded, along with genetic study results. The age range of the subjects was 9 months to 16 years, and the percentage of males was 72.1%. The diagnostic yield of whole exome sequencing (WES) was calculated both before and after parental testing via Sanger DNA sequencing. Results: The study included 176 children: 67 (38.1%) with ID, 62 (35.2%) with ASD, and 47 (26.7%) with ASD + ID. The diagnostic yield of proband-only exome sequencing was 12.5% (22/176). By group, the diagnostic yield of proband-only exome sequencing was 3.2% in the ASD, 12.7% in the ASD + ID, and 20.8% in the ID group. Variants of uncertain significance (VUS) were found in 39.8% (70/176). After parental testing, some variants were reclassified as “likely pathogenic”, increasing the diagnostic yield by 4.6%, with an overall diagnostic yield of 17.1%. Diagnostic yield was higher in patients with syndromic ID (70.6%% vs. 29.4%; p = 0.036). Conclusions: A sequential approach utilizing WES followed by panel-based analysis, starting with the index case and, when appropriate, including the parents, proves to be a cost-effective strategy. WES is particularly suitable for complex conditions, as it allows for the identification of potentially causative genes beyond those covered by targeted panels, providing a more comprehensive analysis. Including parental testing enhances the diagnostic yield and improves accuracy, especially in cases with variants of uncertain significance (VUS), thereby advancing our understanding of NDDs.

An integrated method for detecting lung cancer via CT scanning via optimization, deep learning, and IoT data transmission.

With its increasing global prevalence, lung cancer remains a critical health concern. Despite the advancement of screening programs, patient selection and risk stratification pose significant challenges. This study addresses the pressing need for early detection through a novel diagnostic approach that leverages innovative image processing techniques. The urgency of early lung cancer detection is emphasized by its alarming growth worldwide. While computed tomography (CT) surpasses traditional X-ray methods, a comprehensive diagnosis requires a combination of imaging techniques. This research introduces an advanced diagnostic tool implemented through image processing methodologies. The methodology commences with histogram equalization, a crucial step in artifact removal from CT images sourced from a medical database. Accurate lung CT image segmentation, which is vital for cancer diagnosis, follows. The Otsu thresholding method and optimization, employing Colliding Bodies Optimization (CBO), enhance the precision of the segmentation process. A local binary pattern (LBP) is deployed for feature extraction, enabling the identification of nodule sizes and precise locations. The resulting image underwent classification using the densely connected CNN (DenseNet) deep learning algorithm, which effectively distinguished between benign and malignant tumors. The proposed CBO+DenseNet CNN exhibits remarkable performance improvements over traditional methods. Notable enhancements in accuracy (98.17%), specificity (97.32%), precision (97.46%), and recall (97.89%) are observed, as evidenced by the results from the fractional randomized voting model (FRVM). These findings highlight the potential of the proposed model as an advanced diagnostic tool. Its improved metrics promise heightened accuracy in tumor classification and localization. The proposed model uniquely combines Colliding Bodies Optimization (CBO) with DenseNet CNN, enhancing segmentation and classification accuracy for lung cancer detection, setting it apart from traditional methods with superior performance metrics.

Predicting noise and vibration in electric brake systems at mass production stage using q-axis current

This study explores the challenges of noise, vibration, and harshness (NVH) in electric brake systems within the context of the automotive industry's shift towards environmentally friendly technologies. The electrification of vehicles and their braking systems leads to weight reduction and enhanced braking efficiency. However, these advancements also yield new NVH challenges. The intricate motor-driven mechanisms of electric brake systems are prone to cogging torque, magnetic imbalance, and radial electromagnetic forces, which degrade the user experience and necessitate service interventions. Therefore, this study presents an approach to predicting noise and vibration levels using q-axis current measurements obtained during the initial actuation of electric brake systems in the mass production stage. This study aims to establish a predictive model that can identify potential NVH problems early, enhance the quality and reliability of electric brake systems, and improve user satisfaction. This method enhances sustainable vehicle technologies, improving the overall user experience. The study delves into the intricate relationship between electrical currents and NVH phenomena by integrating electromagnetic analysis with mechanical dynamics. Therefore, this paves the way for the development of advanced diagnostic tools in electric vehicle technology.

Platelet-to-Lymphocyte Ratio as a Potential Diagnostic Marker for Acute Coronary Syndromes in Resource-Limited Settings: A Cross-Sectional Study from Single Center in Banten, Indonesia

Background: Acute coronary syndrome (ACS) poses a significant global health burden, particularly in resource-limited settings where access to advanced diagnostic tools is often constrained. The platelet-to-lymphocyte ratio (PLR), a simple and readily available marker from routine blood tests, has shown promise as a potential diagnostic tool for ACS. This study aimed to evaluate the diagnostic accuracy of PLR in identifying ACS patients in a resource-limited setting in Indonesia. Methods: A cross-sectional study was conducted at Hermina Periuk Hospital, Tangerang, Banten, Indonesia, between December 2020 and December 2022. Patients presenting to the Emergency Room with a diagnosis of ACS were included. PLR was calculated from complete blood count data, and cardiac troponin I (cTnI) served as the gold standard for ACS diagnosis. The diagnostic performance of PLR in predicting elevated cTnI levels was assessed. Results: Of the 121 patients initially identified, 39 met the inclusion and exclusion criteria. Elevated PLR values (&gt;116) were observed in 25 patients (64.1%), while 15 patients (38.5%) had elevated cTnI levels. A statistically significant correlation was found between elevated PLR and elevated cTnI (p = 0.018). No significant association was observed between neutrophil-to-lymphocyte ratio (NLR) and elevated cTnI. Conclusion: PLR demonstrates potential as a diagnostic marker for ACS in resource-limited settings. Its simplicity, accessibility, and cost-effectiveness make it a valuable tool for early identification and risk stratification of ACS patients, particularly in areas with limited access to advanced cardiac diagnostics.

Non-Surgical Endodontic Management of Teeth with Aberrant Anatomy: A Case Series

The root canal therapy aims to remove the necrotic and vital pulp tissue remnants from the root canal to treat the periradicular inflammation. The knowledge of the tooth anatomy is essential to ensure a successful treatment. However, the deviation of the tooth anatomy complicates the diagnostic and treatment processes. Effective management of such complexities requires a tailored approach, utilizing detailed imaging and precise endodontic techniques to achieve successful outcomes and restore patient function and comfort. This case series presents the endodontic management of three different anatomic variations of permanent teeth that include taurodontism in the mandibular molar, two rooted mandibular canine and dilacerated maxillary central incisor and underscores the importance of personalized treatment planning and advanced diagnostic tools in managing complex dental anomalies.

Centromeres in cancer: Unraveling the link between chromosomal instability and tumorigenesis.

Centromeres are critical structures involved in chromosome segregation, maintaining genomic stability, and facilitating the accurate transmission of genetic information. They are key in coordinating the assembly and help keep the correct structure, location, and function of the kinetochore, a proteinaceous structure vital for ensuring proper chromosome segregation during cell division. Abnormalities in centromere structure can lead to aneuploidy or chromosomal instability, which have been implicated in various diseases, including cancer. Accordingly, abnormalities in centromeres, such as structural rearrangements and dysregulation of centromere-associated proteins, disrupt gene function, leading to uncontrolled cell growth and tumor progression. For instance, altered expression of CENP-A, CENP-E, and others such as BUB1, BUBR1, MAD1, and INCENP, have been shown to ascribe to centromere over-amplification, chromosome missegregation, aneuploidy, and chromosomal instability; this, in turn, can culminate in tumor progression. These centromere abnormalities also promoted tumor heterogeneity by generating genetically diverse cell populations within tumors. Advanced techniques like fluorescence in situ hybridization (FISH) and chromosomal microarray analysis are crucial for detecting centromere abnormalities, enabling accurate cancer classification and tailored treatment strategies. Researchers are exploring strategies to disrupt centromere-associated proteins for targeted cancer therapies. Thus, this review explores centromere abnormalities in cancer, their molecular mechanisms, diagnostic implications, and therapeutic targeting. It aims to advance our understanding of centromeres' role in cancer and develop advanced diagnostic tools and targeted therapies for improved cancer management and treatment.

Artificial Intelligence (AI) enable advanced and accurate diagnostics eye health station for critical eye conditions

Millions worldwide suffer from various eye conditions such as Diabetic retinopathy, Cataract, Myopia, glaucoma, Age-related eye disorders, and those arising from hypertension. However, the existing healthcare infrastructure often falls short in providing timely intervention and prevention strategies. Many individuals lack access to advanced diagnostic tools and expert medical professionals, leading to undetected or poorly managed eye conditions. Consequently, irreversible damage occurs, diminishing the quality of life for affected individuals and placing a significant burden on healthcare systems. The Eye Health Station work aims to address these challenges by establishing a visionary and comprehensive medical facility dedicated to eye healthcare. Central to our approach is early intervention and prevention. Through the utilization of cutting-edge technology, including advanced imaging and diagnostic tools, we empower our team of seasoned ophthalmologists, optometrists, and medical professionals to deliver precise and timely assessments. Regular screenings and vigilant monitoring enable us to detect eye conditions at their incipient stages, facilitating effective intervention before irreversible damage occurs. Additionally, our commitment extends to personalize treatment plans tailored to each patient's unique needs, ensuring comprehensive and holistic care. By combining state-of-the-art technology with expert medical expertise, the Eye Health Station stands as a beacon of hope, preserving and restoring vision for individuals across all age groups and enhancing their quality of life.

Culture-Negative Native Vertebral Osteomyelitis: A Narrative Review of an Underdescribed Condition.

The incidence of culture-negative NVO (CN-NVO) cases is increasing, presenting significant diagnostic and therapeutic challenges due to the inability to isolate causative organisms with conventional microbiological methods. Factors influencing the diagnosis of CN-NVO include prior antimicrobial therapy, low pathogen burden, fastidious or intracellular organisms, technical issues, and non-infectious mimickers. Diagnosis often relies on imaging modalities like magnetic resonance imaging (MRI) and computed tomography (CT)-guided biopsy, though these methods can sometimes fail to yield positive microbiological results. Advanced diagnostic tools, such as polymerase chain reaction (PCR), metagenomic next-generation sequencing (mNGS), and cell-free DNA analysis, may be necessary to identify the pathogen. The causative pathogen cannot be isolated in some patients, among which an empirical antimicrobial therapy should be initiated. This narrative review discusses the management, monitoring, surgical indications, and outcomes for patients with CN-NVO.

The Intriguing Pattern of Nontuberculous Mycobacteria in Bulgaria and Description of Mycobacterium bulgaricum sp. nov.

We investigated the rise of nontuberculous mycobacteria (NTM) infections in Bulgaria, focusing on species identification and distribution from 2018 to 2022. Utilizing advanced diagnostic tools, including the Hain Mycobacterium CM/AS method, Myco-biochip assay, and whole-genome sequencing, the study identifies and characterizes a diverse range of Mycobacterium species from clinical samples. While M. avium, M. gordonae, M. fortuitum, and M. chelonae were dominating, a number of rare species were also found. They include such species as M. marseillense and M. celatum. Moreover, the noticeable prevalence of M. terrae complex species missed by conventional testing was observed. We identified a rare species, highly homologous to previously described strains from Japan; based on genome-genome distance data, we propose its reannotation as a new species. Further, a novel species was identified, which is significantly distinct from its closest neighbor, M. iranicum, with ANI = 87.18%. Based on the SeqCode procedure, we propose to name this new species Mycobacterium bulgaricum sp. nov. Dynamic changes in NTM species prevalence in Bulgaria observed from 2011 to 2022 highlight the emergence of new species and variations tied to environmental and demographic factors. This underscores the importance of accurate species identification and genotyping for understanding NTM epidemiology, informing public health strategies, and enhancing diagnostic accuracy and treatment protocols.

Development and evaluation of an EMP course to teach fMRI technology and brain science in handwriting for university nursing students

In traditional nursing education, brain science is often limited to physiology, anatomy, and pathology, with little emphasis on advanced diagnostic tools like fMRI or the brain’s functional processes, such as language learning and handwriting. This study developed an English for Medical Purposes (EMP) course to teach university nursing students about fMRI technology and brain science related to handwriting, highlighting the importance of interprofessional education. The study aimed to (a) assess the course’s effectiveness in enhancing students’ knowledge in fMRI, brain science, and handwriting; and (b) evaluate the students’ satisfaction and perceptions toward the course. A single-group quasi-experimental design with pre/post-tests involved 49 nursing students. Data were collected using the Brain Science Related Knowledge Test (BSKT), assignments, and a Course Satisfaction Questionnaire (CSQ). Results showed significant improvements in students’ knowledge of fMRI and brain science in handwriting, with high assignment scores and overall course satisfaction. Students also reported increased awareness of reading professional English journals and learned about fMRI safety issues. This pioneering EMP course effectively introduced nursing students to fMRI technology and brain science in handwriting, potentially enhancing their understanding of normal brain function and its contrast with brain injury cases.