Bridging the divide: addressing discrepancies between clinical guidelines, policy guidelines, and biomarker utilization.

OBJECTIVES: This paper aims to identify and address gaps in cancer treatment and diagnosis within European health services, focusing specifically on discrepancies between clinical guidelines and policy guidelines. It seeks to highlight how the underutilization of advanced diagnostic techniques recommended by medical societies contributes to missed opportunities for improving patient outcomes. METHODS: A comprehensive analysis was conducted across multiple European countries to assess the compliance and integration of clinical guidelines with the availability of advanced diagnostic technologies. Secondary data related to clinical and policy guidelines in cancer care were collected and analyzed. Key indicators of adoption and utilization of next-generation sequencing and liquid biopsy were examined to evaluate their impact on health service efficiency and patient care. RESULTS: The analysis revealed significant discrepancies between the recommendations of medical societies regarding advanced diagnostic techniques and their adoption in health policy decisions across Europe. Country-specific assessments indicated varying levels of alignment between clinical guidelines and the availability of advanced diagnostics. These findings underscored missed opportunities for optimizing patient care and health service efficiency through better alignment and integration of clinical guidelines with policy decisions. CONCLUSIONS: This study concludes that there is a critical need for health policy decision-makers to prioritize the adoption of clinical guidelines in resource allocation and health service organization. Greater attention to the recommendations of medical societies regarding advanced diagnostic techniques could significantly enhance diagnostic accuracy, treatment efficacy, and overall patient outcomes in cancer care. The paper advocates for policy reforms that acknowledge and leverage the potential benefits of advanced diagnostics in improving health service performance and patient-centered care across Europe.

Investigating bottom phase extraction from aqueous two-phase systems for detecting bacteria using the lateral-flow immunoassay.

Lateral-flow immunoassays (LFAs) can be used to diagnose urinary tract infections caused by Escherichia coli (E. coli) at the point of care. Unfortunately, urine samples containing dilute concentrations of E. coli can yield false negative results on LFAs. Our laboratory was first to implement aqueous two-phase systems (ATPSs) to preconcentrate samples into smaller volumes prior to their application on LFAs. This is achieved by manipulating the ratio of the volume of the top phase to that of the bottom phase (volume ratio; VR) and concentrating biomarkers in the bottom phase which, when applied to LFAs in fixed volumes, leads to corresponding improvements in sensitivity. This work is the first demonstration that the same LOD can be achieved irrespective of the VR when the entire bottom phase is added to LFAs. A custom 3D-printed device was also developed to decrease liquid handling steps. Across different VRs expected from patient urine variability, this diagnostic workflow successfully detected E. coli concentrations down to 2 × 105 colony-forming units (cfu) mL-1 in synthetic urine, demonstrating consistent 10-fold improvements in sensitivity compared to trials conducted without ATPS preconcentration. This method successfully addresses the variability of patient samples while remaining easy to use at the point of care.

Detection of Mycobacterium tuberculosis transrenal DNA in urine samples among adults in Peru.

Diagnosis of pulmonary tuberculosis (TB) relies on a sputum sample, which cannot be obtained from all symptomatic individuals. Mycobacterium tuberculosis (Mtb) transrenal DNA (trDNA) has been detected in urine, an easily obtainable, noninvasive, alternative sample type. However, reported sensitivities have been variable and likely depend on collection and assay procedures and aspects of trDNA biology. We analyzed three serial urine samples from each of 75 adults with culture-confirmed pulmonary TB disease in Lima, Peru for detection of trDNA using short-fragment real-time PCR. Additionally, we examined host, urine, and sampling factors associated with detection. Overall per-sample sensitivity was 38 % (95 % Confidence Interval [CI] 30-45 %). On an individual level (i.e., any of the three samples positive), sensitivity was 73 % (95 % CI: 62-83 %). Sensitivity was highest among samples from patients with smear-positive TB, 92 % (95 % CI: 62-100 %). Specificity from a single sample from each of 10 healthy controls was 100 % (95 % CI: 69-100 %). Adjusting our assay positivity threshold increased individual-level sensitivity to 88 % (95 % CI: 78-94 %) overall without affecting the specificity. We did not find associations between Mtb trDNA detection and individual characteristics or urine sample characteristics. Overall, our results support the potential of trDNA detection for TB diagnosis.

Cardiac natriuretic peptides.

Over the last four decades, cardiac natriuretic peptides have changed our understanding of patients with chronic heart failure. From the discovery of the heart as an endocrine organ with its own hormones and receptors, the biochemistry and physiology of the system have been translated into useful biomarkers and drug targets in cardiovascular disease. The purpose of this review is to provide medical researchers not working in the field with a simple introduction to the system and its molecular components, its quantitative methods, and its physiology and pathophysiology. The hope is that this overview may help to broaden the knowledge of the endocrine heart with the intent that researchers in other areas of medical research will be inspired to seek new facets of the system, both in translational science and in clinical practice.

Advancing research on Blastocystis through a One Health approach.

Blastocystis is the most prevalent intestinal eukaryotic microorganism with significant impacts on both human and animal health. Despite extensive research, its pathogenicity remains controversial. The COST Action CA21105, " Blastocystis under One Health" (OneHealthBlastocystis), aims to bridge gaps in our understanding by fostering a multidisciplinary network. This initiative focuses on developing standardised diagnostic methodologies, establishing a comprehensive subtype and microbiome databank, and promoting capacity building through education and collaboration. The Action is structured into five working groups, each targeting specific aspects of Blastocystis research, including epidemiology, diagnostics, 'omics technologies, in vivo and in vitro investigations, and data dissemination. By integrating advances across medical, veterinary, public, and environmental health, this initiative seeks to harmonise diagnostics, improve public health policies, and foster innovative research, ultimately enhancing our understanding of Blastocystis and its role in health and disease. This collaborative effort is expected to lead to significant advancements and practical applications, benefiting the scientific community and public health.

Blastocystis is a common microorganism found in the intestines of humans and animals. Its role in causing disease is still debated among scientists. The " Blastocystis under One Health" initiative aims to unite experts from human medicine, veterinary science, and environmental science to better understand this microorganism and its health effects. The project focuses on improving diagnostic methods, creating a comprehensive database of Blastocystis samples, and analysing its genetic and molecular makeup. Researchers will also study how Blastocystis interacts with other gut microbes and impacts gut health. Additionally, the initiative aims to educate healthcare professionals and the public about Blastocystis. By working together, scientists hope to develop better ways to diagnose, treat (if necessary), and/or prevent Blastocystis infections, ultimately protecting both human and animal health and enhancing our understanding of this widespread microorganism.

Expert consensus on the terminology, diagnostics and management of persisting symptoms after concussion with a focus on mental health, postural stability, electroencephalogram and balance testing: A cross-sectional Delphi-like survey.

Background: Persisting symptoms after concussion (PSaC) are a pathological manifestation of head injuries that present with symptoms after the acute phase of head trauma has subsided. Insufficient research about PSaC has led to gaps in knowledge and incorrect terminology being applied. Furthermore, gaps exist in standardised assessment protocols and understanding of mental health symptoms associated with sports. Objectives: The study aimed to; 1) Determine expert consensus on appropriate terminology for symptoms lasting >4 weeks, 2) Investigate associations with mental health and postural stability symptoms, 3) Evaluate experts' views on quantitative balance and electroencephalogram (EEG) testing. Methods: A Delphi-like survey was designed in REDCap and sent to identified experts in the field of sports-related concussions (SRC). Expert consensus was defined as ≥75% agreement. Results: Expert consensus identified the following mood and motor control symptoms being associated with PSaC: increases in emotional state (80%), irritability (87%), nervousness (87%), sadness (80%), balance impairment (80%), dizziness (87%) and feeling slow (80%). Numbness and tingling were not considered longer-term effects (80%). Additionally, 93% of respondents acknowledged mental health symptoms as potential longer-term effects, with 80% agreeing on inadequate current management. Respondents indicated PSaC are only somewhat adequately managed (73%) or not managed well enough (27%). The use of EEG and quantitative balance testing remains open for debate. The survey response rate was 21%. Conclusion: Improving mental health management for athletes with PSaC and standardising terminology is crucial. Future research is required to establish effective diagnosis and treatment methods. Addressing these issues may result in better care and safer return to play for athletes.

[Development and validation of Russian olfactory test]. / Otechestvennyi obonyatel'nyi test: razrabotka i validizatsiya.

Olfactory disorders is one of the first symptoms of diseases from various departments of medicine (otorhinolaryngology, psychology, neurology, etc.). Based on international clinical recommendations, olfactory tests are the gold standard for the diagnosis of olfactory disorders. There are many different psychophysical tests: UPSIT (USA, Pennsylvania), Sniffin' Sticks test (Germany), BAST-24 (Spain), etc. Currently, there is an acute shortage of olfactory tests available for clinical practice In Russia. This problem is related to the fact that there are no olfactory tests registered as medical devices on the territory of the Russian Federation. Also, a significant limitation is the unrecognizability of odors by the population of our country, which include foreign analogues (licorice, anise, turpentine, etc.). OBJECTIVE: To develop and validate the national olfactory test on healthy volunteers. MATERIAL AND METHODS: The development and validation of the olfactory test included several stages. First, the development of an olfactory test was carried out, the selection of aromas to assess the threshold and identification ability of olfaction. 25 dilutions of n-butanol were used for the assessment of the threshold olfactory ability. For the stage of assessing the identification ability of the sense of smell, in our previous study, an assessment of the recognition of odor names in the territory of the Russian Federation was carried out. A total of 3.000 people from 8 federal districts of the Russian Federation were interviewed. During the development of the test, 20 names of flavors with the highest rating were used. By the 8th, the selection of monocomponent substances was carried out. Commercially available certified food and perfume flavorings have been used for fragrances whose equivalent in the test cannot be a monocomponent substance. A group of 25 healthy volunteers selected a flavor or a monocomponent for each of the 20 positions. To carry out the identification stage of testing, a booklet was developed with answer options for each fragrance, including 80 images associated with the smell. A methodology for conducting diagnostics has been created. Next, the validation of the developed olfactory test was carried out on 150 healthy volunteers. The study included an assessment of the threshold and identification ability of the sense of smell using the developed test and conducting a comparative analysis with a set of flavors and descriptors corresponding to the Sniffin' Sticks test. RESULTS: The developed test includes: 2 panels - panel 1 to assess the threshold ability of smell, panel 2 to assess the identification ability of smell, a booklet with 80 images and captions to them. The norms of threshold and identification olfactory abilities were also determined in the developed test. The domestic test was validated against the relative foreign Sniffin' Sticks test. Spearman's correlation between the accuracy values of the domestic test (17-20; 85.00-100.00%) and the values of the foreign test (11-16; 68.75-100.00%) did not reveal statistically significant differences (rs=0.065, p=0.432), which confirms the equally effective assessment of olfactory ability by the domestic olfactory test in comparison with its foreign counterpart. CONCLUSION: In this work, a methodology for the use of Russian olfactory test was developed and validated on healthy volunteers. The features of the developed test are an assessment of the threshold and identification ability of smell, an adapted set of odors for the Russian population, the use of paper blotters when applying flavor and visual images of descriptors. Despite the wide variety of psychophysical tests, this problem requires further study and comparative analysis of olfactory tests available In Russia and foreign analogues in order to obtain a universal and effective diagnostic method for the populations of our country.This work was supported by the Russian Foundation for Basic Research (Project No. 24-25-00415).

Analytical and clinical evaluation of a novel real-time PCR-based detection kit for Mpox virus.

Outbreaks of emerging diseases, like Mpox in 2022, pose unprecedented challenges to global healthcare systems. Although Mpox cases globally decreased since the end of 2022, numbers are still significant in the African Region, European Region, Region of the Americas, and Western Pacific Region. Rapid and efficient detection of infected individuals by precise screening assays is crucial for successful containment. In these assays, analytical and clinical performance must be assessed to ensure high quality. However, clinical studies evaluating Mpox virus (MPXV) detection kits using patient-derived samples are scarce. This study evaluated the analytical and clinical performance of a new diagnostic MPXV real-time PCR detection kit (Sansure Monkeypox Virus Nucleic Acid Diagnostic Kit) using patient-derived samples collected in Germany during the MPXV clade IIb outbreak in 2022. Our experimental approach determined the Limit of Detection (LoD) to less than 200 cp/mL using whole blood samples and samples derived from vesicles or pustules. Furthermore, we tested potentially inhibiting substances and pathogens with homologous nucleic acid sequences or similar clinical presentation and detected no cross-reactivity or interference. Following this, the assay was compared to a CE-marked test in a clinical performance study and achieved a diagnostic sensitivity of 100.00% and diagnostic specificity of 96.97%. In summary, the investigated real-time PCR assay demonstrates high analytical performance and concurs with the competitor device with high specificity and sensitivity.

Machine learning-enabled detection of attention-deficit/hyperactivity disorder with multimodal physiological data: a case-control study.

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psychiatric condition that typically emerges during childhood but often persists into adulthood, significantly impacting individuals' functioning, relationships, productivity, and overall quality of life. However, the current diagnostic process exhibits limitations that can significantly affect its overall effectiveness. Notably, its face-to-face and time-consuming nature, coupled with the reliance on subjective recall of historical information and clinician subjectivity, stand out as key challenges. To address these limitations, objective measures such as neuropsychological evaluations, imaging techniques and physiological monitoring of the Autonomic Nervous System functioning, have been explored. METHODS: The main aim of this study was to investigate whether physiological data (i.e., Electrodermal Activity, Heart Rate Variability, and Skin Temperature) can serve as meaningful indicators of ADHD, evaluating its utility in distinguishing adult ADHD patients. This observational, case-control study included a total of 76 adult participants (32 ADHD patients and 44 healthy controls) who underwent a series of Stroop tests, while their physiological data was passively collected using a multi-sensor wearable device. Univariate feature analysis was employed to identify the tests that triggered significant signal responses, while the Informative k-Nearest Neighbors (KNN) algorithm was used to filter out less informative data points. Finally, a machine-learning decision pipeline incorporating various classification algorithms, including Logistic Regression, KNN, Random Forests, and Support Vector Machines (SVM), was utilized for ADHD patient detection. RESULTS: Results indicate that the SVM-based model yielded the optimal performance, achieving 81.6% accuracy, maintaining a balance between the experimental and control groups, with sensitivity and specificity of 81.4% and 81.9%, respectively. Additionally, integration of data from all physiological signals yielded the best results, suggesting that each modality captures unique aspects of ADHD. CONCLUSIONS: This study underscores the potential of physiological signals as valuable diagnostic indicators of adult ADHD. For the first time, to the best of our knowledge, our findings demonstrate that multimodal physiological data collected via wearable devices can complement traditional diagnostic approaches. Further research is warranted to explore the clinical applications and long-term implications of utilizing physiological markers in ADHD diagnosis and management.

Innovative therapeutic strategies in the treatment of gastroesophageal reflux disease (GERD): A review of progress and perspectives.

Gastroesophageal Reflux Disease (GERD) is a commonly occurring condition that can significantly impact quality of life. Often considered a lifestyle disease. Traditional treatment methods focus on pharmacotherapy, lifestyle modifications, and in extreme cases, surgical interventions. This article discusses current and novel approaches to managing gastroesophageal reflux disease. The foundation of this work was medical articles and research gathered from the PubMed database. Keywords such as "esophageal reflux treatment", "new technologies in GERD treatment", "innovative reflux treatment methods", were used to facilitate the literature search. In managing gastroesophageal reflux disease, the application of appropriate pharmacological therapy and lifestyle changes for the patient remains key. However, new technologies and treatment methods, such as advanced endoscopic repair procedures, innovative medications, and personalized approaches, are gaining importance. These new strategies can significantly improve patients' quality of life, reduce symptoms, and minimize the need for surgical interventions.

Extensive differential DNA methylation between tuberculosis skin test positive and skin test negative cattle.

Bovine tuberculosis (bTB), caused by Mycobacterium bovis (M. bovis), represents a significant problem for the agriculture industry as well as posing a risk for human health. Current diagnostic tests for bTB target the cell-mediated immune (CMI) response to infection with M. bovis, primarily through screening of animals with the tuberculin skin test. Epigenetic modifications have been shown to alter the course of the immune response and differentially methylated regions (DMRs) might also influence the outcome of the skin test in cattle. Whole Genome Bisulphite Sequencing (WGBS) was used to profile DNA methylation levels from peripheral blood of a group of cattle identified as test positive for M. bovis (positive for the single intradermal comparative tuberculin test (SICTT) and/or the interferon-γ release assay compared to a test negative control group [n = 8/group, total of 16 WGBS libraries]. Although global methylation profiles were similar for both groups across the genome, 223 DMRs and 159 Differentially Promoter Methylated Genes (DPMGs) were identified between groups with an excess of hypermethylated sites in SICTT positive cattle (threshold > 15% differential methylation). Genes located within these DMRs included the Interleukin 1 receptor (IL1R1) and MHC related genes (BOLA and BOLA-DQB). KEGG pathway analysis identified enrichment of genes involved in Calcium and MAPK signalling, as well as metabolism pathways. Analysis of DMRs in a subset of SICTT negative cattle that were IFN-γ positive showed differential methylation of genes including Interleukin 10 Receptor, alpha (IL10RA), Interleukin 17 F (IL17F) and host defence peptides (DEFB and BDEF109). This study has identified a number of immune gene loci at which differential methylation is associated with SICTT test results and the degree of methylation could influence effective host immune responses.

Development and validation of a rapid loop-mediated isothermal amplification assay for the detection of Chrysomyxa and characterization of Chrysomyxa woroninii overwintering on Picea in China.

Chrysomyxa rusts cause significant damage to spruce in both natural forests and plantations. Particularly, Three Chrysomyxa species, Chrysomyxa deformans, Chrysomyxa qilianensis, and Chrysomyxa rhododendri, listed as National Forest Dangerous Pests in China, have severely affected many economically and ecologically important spruce native species in China. Also, Chrysomyxa arctostaphyli, an important plant quarantine fungus, causes a damaging broom rust disease on spruce. Therefore, rapid, and efficient detection tools are urgently needed for proper rust disease detection and management. In this study, a sensitive, genus-specific loop-mediated isothermal amplification (LAMP) assay targeting the ITS-28S rRNA region was developed to detect the presence of Chrysomyxa in spruce needle and bud samples. After optimization and validation, the LAMP assay was found to be sensitive to detect as low as 5.2 fg/µL DNA, making it suitable for rapid on-site testing for rust infection. The assay was also specific to Chrysomyxa species, with no positive signals from other rust genus/species. The application of LAMP in the early detection of rust infections in spruce needles and buds was investigated, and spatial colonization profiles as well as the means of overwintering of Chrysomyxa woroninii in infected buds and branches were verified using the LAMP assay. This LAMP detection method will facilitate further studies on the characteristics of the life cycle and inoculation of other systemic rusts.

Enhancing the Appeal of Clinical Diagnostics Education for Medical Undergraduates Through the Innovative Incorporation of Cultural and Historical Elements Alongside the Inclusion of the COVID-19 Pandemic and Its Innovative Solutions.

Clinical diagnostics is a fundamental course required for clinical medical students and serves as a prerequisite for several advanced clinical subjects. However, recent observations indicate a decline in interest among eight-year clinical medicine students at Peking Union Medical College regarding clinical diagnostics courses. Instead, these students seem to prioritize the publication of high-impact articles and involvement in scientific research over their medical coursework, leading to a lack of sufficient attention to clinical diagnostics. In the clinical diagnostics course conducted in the first half of 2024, our objective was to engage medical students by presenting the subject matter in an interesting and relevant manner. We curated textual information regarding the health condition of Lin Daiyu, the protagonist from the Chinese literary classic "The Dream of the Red Chamber," and encouraged students to deduce potential diseases she may have experienced based on the original text. Additionally, we sourced historical photographs of Empress Dowager Cixi from the Qing Dynasty, which facilitated the hypothesis that she likely suffered from goiter. These images were employed as a practical examination question during the mid-semester assessment to evaluate the students' proficiency in conducting neck physical examinations. Furthermore, we shared an inspiring anecdote about healthcare professionals who repurposed potato chip packaging into stethoscopes during the COVID-19 pandemic, underscoring the critical role of physical diagnosis and examination in urgent situations. Following the mid-term exam in clinical diagnosis, a questionnaire survey was administered to the medical students who participated in the examination. The results indicated that 93% of the students found the question regarding Lin Daiyu to be highly engaging, while 89% found the question about Empress Dowager Cixi equally captivating. These innovative teaching strategies significantly enhanced the medical students' enthusiasm for learning clinical diagnostics.

Rapid detection of SARS-CoV-2 with a mobile device based on pulse controlled amplification.

In the past, vast research has been conducted on biosensors and point-of-care (PoC) diagnostics. Despite rapid advances especially during the SARS-CoV-2 pandemic in this research field a low-cost molecular biosensor exhibiting the user-friendliness of a rapid antigen test, and also the sensitivity and specificity of a PCR test, has not been developed yet. To this end we developed a novel microfluidics based and handheld PoC device, that facilitates viral detection at PCR sensitivity and specificity in less than 40 min, including 15 min sample preparation. This was attained by incorporation of pulse controlled amplification (PCA), a method which uses short electrical pulses to rapidly increase the temperature of a small fraction of the sample volume. In this work, we present a low-cost PCA device with a microfluidic consumable intended for the use in a decentralized or home-setting. We used finite element analysis (FEA) simulations to display the fundamental principle and highlight the critical parameter dependency of PCA, such as pulse length and resistor shape. Furthermore, we integrated a simple and fast workflow for sample preparation and evaluated the limit of detection (LoD) for SARS-CoV-2 viral RNA, which is 0.88 copies/µL (=44 copies/reaction), and thus, comparable to conventional RT-qPCR. Additionally, target specificity of the device was validated. Our device and PCA approach enables cost-effective, rapid and mobile molecular diagnostics while remaining highly sensitive and specific.

Critical Insights from Recent Outbreaks of Mycoplasma pneumoniae: Decoding the Challenges and Effective Interventions Strategies.

Mycoplasma pneumoniae (M. pneumoniae) continues to pose a significant disease burden on global public health as a respiratory pathogen. The antimicrobial resistance among M. pneumoniae strains has complicated the outbreak control efforts, emphasizing the need for robust surveillance systems and effective antimicrobial stewardship programs. This review comprehensively investigates studies stemming from previous outbreaks to emphasize the multifaceted nature of M. pneumoniae infections, encompassing epidemiological dynamics, diagnostic innovations, antibiotic resistance, and therapeutic challenges. We explored the spectrum of clinical manifestations associated with M. pneumoniae infections, emphasizing the continuum of disease severity and the challenges in gradating it accurately. Artificial Intelligence and Machine Learning have emerged as promising tools in M. pneumoniae diagnostics, offering enhanced accuracy and efficiency in identifying infections. However, their integration into clinical practice presents hurdles that need to be addressed. Further, we elucidate the pivotal role of pharmacological interventions in controlling and treating M. pneumoniae infections as the efficacy of existing therapies is jeopardized by evolving resistance mechanisms. Lessons learned from previous outbreaks underscore the importance of adaptive treatment strategies and proactive management approaches. Addressing these complexities demands a holistic approach integrating advanced technologies, genomic surveillance, and adaptive clinical strategies to effectively combat this pathogen.

Applications of Fog Computing in Healthcare.

Fog computing is a decentralized computing infrastructure that processes data at or near its source, reducing latency and bandwidth usage. This technology is gaining traction in healthcare due to its potential to enhance real-time data processing and decision-making capabilities in critical medical scenarios. A systematic review of existing literature on fog computing in healthcare was conducted. The review included searches in major databases such as PubMed, IEEE Xplore, Scopus, and Google Scholar. The search terms used were "fog computing in healthcare," "real-time diagnostics and fog computing," "continuous patient monitoring fog computing," "predictive analytics fog computing," "interoperability in fog computing healthcare," "scalability issues fog computing healthcare," and "security challenges fog computing healthcare." Articles published between 2010 and 2023 were considered. Inclusion criteria encompassed peer-reviewed articles, conference papers, and review articles focusing on the applications of fog computing in healthcare. Exclusion criteria were articles not available in English, those not related to healthcare applications, and those lacking empirical data. Data extraction focused on the applications of fog computing in real-time diagnostics, continuous monitoring, predictive analytics, and the identified challenges of interoperability, scalability, and security. Fog computing significantly enhances diagnostic capabilities by facilitating real-time data analysis, crucial for urgent diagnostics such as stroke detection, by processing data closer to its source. It also improves monitoring during surgeries by enabling real-time processing of vital signs and physiological parameters, thereby enhancing patient safety. In chronic disease management, continuous data collection and analysis through wearable devices allow for proactive disease management and timely adjustments to treatment plans. Additionally, fog computing supports telemedicine by enabling real-time communication between remote specialists and patients, thereby improving access to specialist care in underserved regions. Fog computing offers transformative potential in healthcare, improving diagnostic precision, patient monitoring, and personalized treatment. Addressing the challenges of interoperability, scalability, and security will be crucial for fully realizing the benefits of fog computing in healthcare, leading to a more connected and efficient healthcare environment.

Towards unified reporting of genome sequencing results in clinical microbiology.

Whole genome sequencing (WGS) has become a vital tool in clinical microbiology, playing an important role in outbreak investigations, molecular surveillance, and identification of bacterial species, resistance mechanisms and virulence factors. However, the complexity of WGS data presents challenges in interpretation and reporting, requiring tailored strategies to enhance efficiency and impact. This study explores the diverse needs of key stakeholders in healthcare, including clinical management, laboratory work, public surveillance and epidemiology, infection prevention and control, and academic research, regarding WGS-based reporting of clinically relevant bacterial species. In order to determine preferences regarding WGS reports, human-centered design approach was employed, involving an online survey and a subsequent workshop with stakeholders. The survey gathered responses from 64 participants representing the above mentioned healthcare sectors across geographical regions. Key findings include the identification of barriers related to data accessibility, integration with patient records, and the complexity of interpreting WGS results. As the participants designed their ideal report using nine pre-defined sections of a typical WGS report, differences in needs regarding report structure and content across stakeholders became evident. The workshop discussions further highlighted the need to feature critical findings and quality metrics prominently in reports, as well as the demand for flexible report designs. Commonalities were observed across stakeholder-specific reporting templates, such as the uniform ranking of certain report sections, but preferences regarding the depth of content within these sections varied. Using these findings, we suggest stakeholder-specific structures which should be considered when designing customized reporting templates. In conclusion, this study underscores the importance of tailoring WGS-based reports of clinically relevant bacteria to meet the distinct needs of diverse healthcare stakeholders. The evolving landscape of digital reporting increases the opportunities with respect to WGS reporting and its utility in managing infectious diseases and public health surveillance.

Flow-Field Inference for Turbulent Exhale Flow Measurement.

BACKGROUND: Vision-based pulmonary diagnostics present a unique approach for tracking and measuring natural breathing behaviors through remote imaging. While many existing methods correlate chest and diaphragm movements to respiratory behavior, we look at how the direct visualization of thermal CO2 exhale flow patterns can be tracked to directly measure expiratory flow. METHODS: In this work, we present a novel method for isolating and extracting turbulent exhale flow signals from thermal image sequences through flow-field prediction and optical flow measurement. The objective of this work is to introduce a respiratory diagnostic tool that can be used to capture and quantify natural breathing, to identify and measure respiratory metrics such as breathing rate, flow, and volume. One of the primary contributions of this work is a method for capturing and measuring natural exhale behaviors that describe individualized pulmonary traits. By monitoring subtle individualized respiratory traits, we can perform secondary analysis to identify unique personalized signatures and abnormalities to gain insight into pulmonary function. In our study, we perform data acquisition within a clinical setting to train an inference model (FieldNet) that predicts flow-fields to quantify observed exhale behaviors over time. RESULTS: Expiratory flow measurements capturing individualized flow signatures from our initial cohort demonstrate how the proposed flow field model can be used to isolate and analyze turbulent exhale behaviors and measure anomalous behavior. CONCLUSIONS: Our results illustrate that detailed spatial flow analysis can contribute to unique signatures for identifying patient specific natural breathing behaviors and abnormality detection. This provides the first-step towards a non-contact respiratory technology that directly captures effort-independent behaviors based on the direct measurement of imaged CO2 exhaled airflow patterns.

Advancing Pathogen Identification: The Role of Digital PCR in Enhancing Diagnostic Power in Different Settings.

Digital polymerase chain reaction (dPCR) has emerged as a groundbreaking technology in molecular biology and diagnostics, offering exceptional precision and sensitivity in nucleic acid detection and quantification. This review highlights the core principles and transformative potential of dPCR, particularly in infectious disease diagnostics and environmental surveillance. Emphasizing its evolution from traditional PCR, dPCR provides accurate absolute quantification of target nucleic acids through advanced partitioning techniques. The review addresses the significant impact of dPCR in sepsis diagnosis and management, showcasing its superior sensitivity and specificity in early pathogen detection and identification of drug-resistant genes. Despite its advantages, challenges such as optimization of experimental conditions, standardization of data analysis workflows, and high costs are discussed. Furthermore, we compare various commercially available dPCR platforms, detailing their features and applications in clinical and research settings. Additionally, the review explores dPCR's role in water microbiology, particularly in wastewater surveillance and monitoring of waterborne pathogens, underscoring its importance in public health protection. In conclusion, future prospects of dPCR, including methodological optimization, integration with innovative technologies, and expansion into new sectors like metagenomics, are explored.