Expanding the Role of Chiral Drugs and Chiral Nanomaterials as a Potential Therapeutic Tool.

Chirality, the property of molecules having mirror-image forms, plays a crucial role in pharmaceutical and biomedical research. This review highlights its growing importance, emphasizing how chiral drugs and nanomaterials impact drug effectiveness, safety, and diagnostics. Chiral molecules serve as precise diagnostic tools, aiding in accurate disease detection through unique biomolecule interactions. The article extensively covers chiral drug applications in treating cardiovascular diseases, CNS disorders, local anesthesia, anti-inflammatories, antimicrobials, and anticancer drugs. Additionally, it explores the emerging field of chiral nanomaterials, highlighting their suitability for biomedical applications in diagnostics and therapeutics, enhancing medical treatments.

Diagnostic accuracy of artificial intelligence in detecting left ventricular hypertrophy by electrocardiograph: a systematic review and meta-analysis.

Several studies suggested the utility of artificial intelligence (AI) in screening left ventricular hypertrophy (LVH). We hence conducted systematic review and meta-analysis comparing diagnostic accuracy of AI to Sokolow-Lyon's and Cornell's criteria. Our aim was to provide a comprehensive overview of the newly developed AI tools for diagnosing LVH. We searched MEDLINE, EMBASE, and Cochrane databases for relevant studies until May 2023. Included were observational studies evaluating AI's accuracy in LVH detection. The area under the receiver operating characteristic curves (ROC) and pooled sensitivities and specificities assessed AI's performance against standard criteria. A total of 66,479 participants, with and without LVH, were included. Use of AI was associated with improved diagnostic accuracy with summary ROC (SROC) of 0.87. Sokolow-Lyon's and Cornell's criteria had lower accuracy (0.68 and 0.60). AI had sensitivity and specificity of 69% and 87%. In comparison, Sokolow-Lyon's specificity was 92% with a sensitivity of 25%, while Cornell's specificity was 94% with a sensitivity of 19%. This indicating its superior diagnostic accuracy of AI based algorithm in LVH detection. Our study demonstrates that AI-based methods for diagnosing LVH exhibit higher diagnostic accuracy compared to conventional criteria, with notable increases in sensitivity. These findings contribute to the validation of AI as a promising tool for LVH detection.

Is There a Relationship between Salivary Cortisol and Temporomandibular Disorder: A Systematic Review.

BACKGROUND: This systematic review examines and evaluates the relationship between salivary cortisol levels and temporomandibular disorder (TMD) in young adult patients. METHOD: Six databases-PubMed, Scopus, Web of Science, Google Scholar, ProQuest, and Cochrane Library-were utilized to screen eligible studies. A systematic search was performed based on PECO questions and eligibility criteria. The research question for this review was "Do salivary cortisol levels correlate with TMD in individuals aged 18-40?" The risk of bias for quality assessment was determined by the Cochrane tool. PRISMA guidelines were followed while performing this review. RESULT: A total of fourteen studies were included in this review. Of these, eleven were observational studies (four cross-sectional and seven case-control), and three were randomized control trials. Eleven of the included studies presented a low to moderate risk in the qualitative synthesis. The total sample size of the included studies was 751 participants. The included studies suggest higher salivary cortisol levels in TMD patients than in healthy individuals. CONCLUSIONS: The findings of this review indicate higher salivary cortisol levels in adult patients with TMD than in healthy controls. Thus, supportive psychological treatment and clinical modalities should be provided to patients with TMD. Moreover, higher-quality studies with low heterogeneity are required to support this finding.

Development and evaluation of a high-sensitivity RT-PCR lateral flow assay for early detection of HIV-1 infection.

Early diagnosis of HIV-1 is crucial to minimize transmission, morbidity, and mortality, particularly for neonates with developing immune systems. This study aimed to develop and evaluate a simplified, high-sensitivity assay for early HIV-1 detection before seroconversion. The assay utilizes reverse-transcription-polymerase chain reaction (RT-PCR) to amplify the HIV-1 RNA protease gene. Digoxigenin (dig)-labeled forward, and biotin-labeled universal reverse primers are used, generating digoxigenin-amplicon-biotin (DAB) products. These products are detected using a lateral flow assay (LFA) containing a conjugated pad with colloidal gold-labeled 6-histidine tag-fused maltose-binding protein-monomeric streptavidin (6HISMBP-mSA-CGC). Anti-dig monoclonal antibody (mAb) and biotinylated-BSA are immobilized in the test and control line zones, respectively. Five plasma samples with known viral load (VL) were used to simulate the efficacy of early HIV-1 detection. RNA extracted from these samples was amplified by RT-PCR using the labeled primers, and DAB products were examined on agarose gel electrophoresis and LFA. RT-PCR from diluted clinical samples yielded visible DNA bands in agarose gel electrophoresis, consistent with positive LFA results. Conversely, negative samples only displayed the control line on LFA. This assay exhibited a limit of detection (LOD) of 82.29 RNA copies/mL, comparable to other nucleic acid amplification tests (NAATs). This novel technique provides a highly sensitive assay for early HIV-1 diagnosis, even with low VL, making it suitable for resource-limited settings.

Delirium diagnostic tools in the postoperative setting: A scoping review protocol.

BACKGROUND: Delirium is an acute and fluctuating disturbance in attention, awareness, and cognition, commonly observed in hospital settings, particularly among older adults, critically ill and surgical patients. Delirium poses significant challenges in patient care, leading to increased morbidity, mortality, prolonged hospital stays, and functional decline. AIM: The aim of this review is to map existing evidence on delirium diagnostic tools suitable for use in patients treated surgically due to hip fracture, to inform clinical practice and enhance patient care protocols in the postoperative setting. METHOD: We will conduct a scoping review on delirium diagnostic tools used for adult patients in the postoperative setting according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Eligibility criteria encompass all languages, publications dates, and study designs, with exception of case-reports. We will systematically search multiple databases and include unpublished trials, ensuring a comprehensive review based on a predefined protocol. RESULTS: Results will be presented descriptively, with supplementary tables and graphs. Studies will be grouped by design, surgical specialties, and diagnostic tools to identify potential variations. CONCLUSION: This scoping review will provide an overview of existing delirium diagnostic tools used in the postoperative setting and highlight knowledge-gaps to support future research. Due to the large number of patients affected by postoperative delirium, evidence mapping is much needed to facilitate evidence-based practice.

Divergent Gender Identity in a Phenotypic Male with 46XX Karyotype Caused by a Mutation in CYP21A2 Gene with Congenital Adrenal Hyperplasia.

A male patient in his late twenties presented with ambiguous genitalia to our tertiary specialist unit with complaints of short stature and inadequate copulation. There was no history of consanguinity, and a physical examination raised concerns about possible disorders of sexual development (DSD). Karyotyping and fluorescence in situ hybridization results were consistent with the presence of two X chromosomes, revealing the patient to be a genotypic female. Sanger sequencing showed a heterozygous pathogenic mutation in the CYP21A2 gene known to be associated with 21-hydroxylase deficiency, thus confirming the diagnosis of congenital adrenal hyperplasia (CAH), Prader stage V. DSD with CAH is distressing for the patient and their families, and the management needs a multidimensional approach involving diverse medical, genetic, and psychological considerations. Cytogenetic and molecular genetic studies play an essential role in diagnosis and decision-making and should be made affordable in developing countries for better patient care.

New diagnostic criteria for metopic ridges and trigonocephaly: a 3D geometric approach.

BACKGROUND: Trigonocephaly occurs due to the premature fusion of the metopic suture, leading to a triangular forehead and hypotelorism. This condition often requires surgical correction for morphological and functional indications. Metopic ridges also originate from premature metopic closure but are only associated with mid-frontal bulging; their surgical correction is rarely required. Differential diagnosis between these two conditions can be challenging, especially in minor trigonocephaly. METHODS: Two hundred seven scans of patients with trigonocephaly (90), metopic rigdes (27), and controls (90) were collected. Geometric morphometrics were used to quantify skull and orbital morphology as well as the interfrontal angle and the cephalic index. An innovative method was developed to automatically compute the frontal curvature along the metopic suture. Different machine-learning algorithms were tested to assess the predictive power of morphological data in terms of classification. RESULTS: We showed that control patients, trigonocephaly and metopic rigdes have distinctive skull and orbital shapes. The 3D frontal curvature enabled a clear discrimination between groups (sensitivity and specificity > 92%). Furthermore, we reached an accuracy of 100% in group discrimination when combining 6 univariate measures. CONCLUSION: Two diagnostic tools were proposed and demonstrated to be successful in assisting differential diagnosis for patients with trigonocephaly or metopic ridges. Further clinical assessments are required to validate the practical clinical relevance of these tools.

Immunohistochemistry as a Reliable Tool for the Diagnosis of Cystic Echinococcosis in Patients from Sardinia, Italy-A Confirmatory Study.

Cystic Echinococcosis (CE) is a zoonotic disease caused by the larval stage of the tapeworm Echinococcus granulosus sensu lato (s.l.). This study aims to investigate the use of two monoclonal antibodies (mAbEmG3 and mAbEm2G11) by immunohistochemistry (IHC) to confirm the diagnosis of CE in human patients, in particular in those cases in which other techniques fail to provide a correct or conclusive diagnosis. For this purpose, a survey on 13 patients was performed. These subjects were referred to Sardinian hospitals (Italy) from 2017 to 2022 and were suspected to be affected by CE. Our findings from these 13 patients showed the detection of E. granulosus sensu stricto by IHC in 12 of 13 echinococcal cysts, as one sample was of a non-parasitological origin. The results confirmed that IHC, by means of the mAbEmG3 and mAbEm2G11, is a reliable diagnostic tool that showed a very high performances when tested on strain of E. granulosus s.l. from Sardinia.

NanoImprint: A DNA methylation tool for clinical interpretation and diagnosis of common imprinting disorders using nanopore long-read sequencing.

INTRODUCTION: Long-read whole genome sequencing like Oxford Nanopore Technology, is increasingly being introduced in clinical settings. With its ability to simultaneously call sequence variation and DNA modifications including 5-methylcytosine, nanopore is a promising technology to improve diagnostics of imprinting disorders. METHODS: Currently, no tools to analyze DNA methylation patterns at known clinically relevant imprinted regions are available. Here we present NanoImprint, which generates an easily interpretable report, based on long-read nanopore sequencing, to use for identifying clinical relevant abnormalities in methylation levels at 14 imprinted regions and diagnosis of common imprinting disorders. RESULTS AND CONCLUSION: NanoImprint outputs a summarizing table and visualization plots displays methylation frequency (%) and chromosomal positions for all regions, with phased data color-coded for the two alleles. We demonstrate the utility of NanoImprint using three imprinting disorder samples from patients with Beckwith-Wiedemann syndrome (BWS), Angelman syndrome (AS) and Prader-Willi syndrome (PWS). NanoImprint script is available from https://github.com/carolinehey/NanoImprint.

Advancements in microRNA-based electrochemical biosensors for preeclampsia detection.

Highlighting a recently proposed mechanism for early detection of preeclampsia using microRNA-based electrochemical biosensors, showcasing their transformative potential for improved prenatal care.

Identifying and Validating Alcohol Diagnostics for Injury-Related Trauma in South Africa: Protocol for a Mixed Methods Study.

BACKGROUND: The burden of alcohol use among patients with trauma and the relative injury risks is not routinely measured in South Africa. Given the prominent burden of alcohol on hospital trauma departments, South Africa needs practical, cost-effective, and accurate alcohol diagnostic tools for testing, surveillance, and clinical management of patients with trauma. OBJECTIVE: This study aims to validate alcohol diagnostics for injury-related trauma and assess its use for improving national health practice and policy. METHODS: The Alcohol Diagnostic Validation for Injury-Related Trauma study will use mixed methods across 3 work packages. Five web-based focus group discussions will be conducted with 6 to 8 key stakeholders, each across 4 areas of expertise (clinical, academic, policy, and operational) to determine the type of alcohol information that will be useful for different stakeholders in the injury prevention and health care sectors. We will then conduct a small pilot study followed by a validation study of alcohol diagnostic tools (clinical assessment, breath analysis, and fingerprick blood) against enzyme immunoassay blood concentration analysis in a tertiary hospital trauma setting with 1000 patients. Finally, selected alcohol diagnostic tools will be tested in a district hospital setting with a further 1000 patients alongside community-based participatory research on the use of the selected tools. RESULTS: Pilot data are being collected, and the protocol will be modified based on the results. CONCLUSIONS: Through this project, we hope to identify and validate the most appropriate methods of diagnosing alcohol-related injury and violence in a clinical setting. The findings from this study are likely to be highly relevant and could influence our primary beneficiaries-policy makers and senior health clinicians-to adopt new practices and policies around alcohol testing in injured patients. The findings will be disseminated to relevant national and provincial government departments, policy experts, and clinicians. Additionally, we will engage in media advocacy and with our stakeholders, including community representatives, work through several nonprofit partners to reach civil society organizations and share findings. In addition, we will publish findings in scientific journals. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52949.

The paediatric polytrauma CT-indication (PePCI)-score-Development of a prognostic model to reduce unnecessary CT scans in paediatric trauma patients.

BACKGROUND: Whole-Body CT (WBCT) is frequently used in emergency situations for promptly diagnosing paediatric polytrauma patients, given the challenges associated with obtaining precise details about the mechanism and progression of trauma. However, WBCT does not lead to reduced mortality in paediatric patients, but is associated with high radiation exposure. We therefore wanted to develop a screening tool for CT demand-driven emergency room (ER)-trauma diagnostic to reduce radiation exposure in paediatric patients. METHODS: A retrospective study in a Level I trauma centre in Germany was performed. Data from 344 paediatric emergency patients with critical mechanism of injury who were pre-announced by the ambulance for the trauma room were collected. Patients' symptoms, clinical examination, extended Focused Assessment with Sonography for Trauma (eFAST), routinely, laboratory tests and blood gas and - when obtained - WBCT images were analysed. To identify potential predictors of severe injuries (ISS > 23), 300 of the 344 cases with complete data were subjected to regression analyses model. RESULTS: Multiple regression analysis identified cGCS, base excess (BE), medically abnormal results from eFAST screening, initial unconsciousness, and injuries involving three or more body regions as significant predictors for a screening tool for decision-making to perform WBCT or selective CT. The developed Paediatric polytrauma CT-Indication (PePCI)-Score was divided into three risk categories and achieved a sensitivity of 87 % and a specificity of 71 % when comparing the low and medium risk groups with the high risk group. Comparing only the low-risk group with the high-risk group for the decision to perform WBCT, 32/35 (91 %) of patients with an ISS >23 were correctly identified, as were 124/137 (91 %) with lower ISS scores. CONCLUSION: With the newly developed PePCI-Score, the frequency of WBCT in a paediatric emergency patients collective can be significantly reduced according to our data. After prospective validation, the initial assessment of paediatric trauma patients in the future could be made not only by the mechanism of injury, but also by the new PePCI-Score, deriving on clinical findings after thorough clinical assessment and the discretion of the trauma team.

Towards a diagnostic tool for neurological gait disorders in childhood combining 3D gait kinematics and deep learning.

Gait abnormalities are frequent in children and can be caused by different pathologies, such as cerebral palsy, neuromuscular disease, toe walker syndrome, etc. Analysis of the "gait pattern" (i.e., the way the person walks) using 3D analysis provides highly relevant clinical information. This information is used to guide therapeutic choices; however, it is underused in diagnostic processes, probably because of the lack of standardization of data collection methods. Therefore, 3D gait analysis is currently used as an assessment rather than a diagnostic tool. In this work, we aimed to determine if deep learning could be combined with 3D gait analysis data to diagnose gait disorders in children. We tested the diagnostic accuracy of deep learning methods combined with 3D gait analysis data from 371 children (148 with unilateral cerebral palsy, 60 with neuromuscular disease, 19 toe walkers, 60 with bilateral cerebral palsy, 25 stroke, and 59 typically developing children), with a total of 6400 gait cycles. We evaluated the accuracy, sensitivity, specificity, F1 score, Area Under the Curve (AUC) score, and confusion matrix of the predictions by ResNet, LSTM, and InceptionTime deep learning architectures for time series data. The deep learning-based models had good to excellent diagnostic accuracy (ranging from 0.77 to 0.99) for discrimination between healthy and pathological gait, discrimination between different etiologies of pathological gait (binary and multi-classification); and determining stroke onset time. LSTM performed best overall. This study revealed that the gait pattern contains specific, pathology-related information. These results open the way for an extension of 3D gait analysis from evaluation to diagnosis. Furthermore, the method we propose is a data-driven diagnostic model that can be trained and used without human intervention or expert knowledge. Furthermore, the method could be used to distinguish gait-related pathologies and their onset times beyond those studied in this research.

Circulating Tumor Cells in Oral Cancer.

Till now, oral squamous cell carcinoma (OSCC) is graded as well-differentiated, moderately-differentiated, poorly-differentiated, and undifferentiated. However, this grading does not have a prediction of the prognosis of the patient. Also, prognosis impacts lymph node metastases, surgical margins, and vascular invasions (neural invasion, muscular invasion, salivary gland invasion). The prognosis of lymph node metastases is significant, which affects the survival of the patients which is 50%. So, a dependable blood marker is needed for prognosis in OSCC patients with loco-regional and distant recurrence. Some factors can be assisted only after surgery and invasive techniques to check the prognosis of the disease. Despite the ease of examining the oral cavity, there is no practical approach for non-invasive screening and detecting cancer. As it is abrupt to use such invasive procedures from time to time, there is a need for nonsurgical and reliable techniques to assess the progression of tumors. Also, frozen sections are helpful during the intraoperative procedure to evaluate the lymph node metastases. An increase in the number of tumor cells through blood is a significant event in disease metastases toward the peripheral blood. Oral health impact assessment instruments could aid in determining the quality of life, and their usage in the initial stages of oral carcinoma could help physicians choose the best treatment option for enhancing the quality of life.

A New Method Used to Enhance the SPAIR Image of the Spine MRI.

BACKGROUND: Magnetic resonance imaging (MRI) is a handy diagnostic tool for orthopedic disorders, particularly spinal and joint diseases. METHODS: The lumbar intervertebral disc is visible in the T1 and T2 weight sequences of the spine MRI, which aids in diagnosing lumbar disc herniation, lumbar spine tuberculosis, lumbar spine tumors, and other conditions. The lumbar intervertebral disc cannot be seen accurately in the Spectral Attenuated Inversion Recovery (SPAIR) due to weaknesses in the fat and frequency offset parameters, which is not conducive to developing the intelligence diagnosis model of medical image. RESULTS: In order to solve this problem, we propose a composite framework, which is first to use the contrast limited adaptive histogram equalization (CLAHE) method to enhance the SPAIR image contrast of the spine MRI and then use the non-local means method to remove the noise of the image to ensure that the image contrast is uniform without losing details. We employ the Information Entropy (IE), Peak signal-to-noise ratio (PSNR), and feature similarity index measure (FSIM) to quantify image quality after enhancement by the composite framework. CONCLUSION: The outcomes of the experiments' output images and quantitative data indicate that our composite framework is better than others.

PLUS-IS-LESS project: Procalcitonin and Lung UltraSonography-based antibiotherapy in patients with Lower rESpiratory tract infection in Swiss Emergency Departments: study protocol for a pragmatic stepped-wedge cluster-randomized trial.

BACKGROUND: Lower respiratory tract infections (LRTIs) are among the most frequent infections and a significant contributor to inappropriate antibiotic prescription. Currently, no single diagnostic tool can reliably identify bacterial pneumonia. We thus evaluate a multimodal approach based on a clinical score, lung ultrasound (LUS), and the inflammatory biomarker, procalcitonin (PCT) to guide prescription of antibiotics. LUS outperforms chest X-ray in the identification of pneumonia, while PCT is known to be elevated in bacterial and/or severe infections. We propose a trial to test their synergistic potential in reducing antibiotic prescription while preserving patient safety in emergency departments (ED). METHODS: The PLUS-IS-LESS study is a pragmatic, stepped-wedge cluster-randomized, clinical trial conducted in 10 Swiss EDs. It assesses the PLUS algorithm, which combines a clinical prediction score, LUS, PCT, and a clinical severity score to guide antibiotics among adults with LRTIs, compared with usual care. The co-primary endpoints are the proportion of patients prescribed antibiotics and the proportion of patients with clinical failure by day 28. Secondary endpoints include measurement of change in quality of life, length of hospital stay, antibiotic-related side effects, barriers and facilitators to the implementation of the algorithm, cost-effectiveness of the intervention, and identification of patterns of pneumonia in LUS using machine learning. DISCUSSION: The PLUS algorithm aims to optimize prescription of antibiotics through improved diagnostic performance and maximization of physician adherence, while ensuring safety. It is based on previously validated tests and does therefore not expose participants to unforeseeable risks. Cluster randomization prevents cross-contamination between study groups, as physicians are not exposed to the intervention during or before the control period. The stepped-wedge implementation of the intervention allows effect calculation from both between- and within-cluster comparisons, which enhances statistical power and allows smaller sample size than a parallel cluster design. Moreover, it enables the training of all centers for the intervention, simplifying implementation if the results prove successful. The PLUS algorithm has the potential to improve the identification of LRTIs that would benefit from antibiotics. When scaled, the expected reduction in the proportion of antibiotics prescribed has the potential to not only decrease side effects and costs but also mitigate antibiotic resistance. TRIAL REGISTRATION: This study was registered on July 19, 2022, on the ClinicalTrials.gov registry using reference number: NCT05463406. TRIAL STATUS: Recruitment started on December 5, 2022, and will be completed on November 3, 2024. Current protocol version is version 3.0, dated April 3, 2023.

A minimally invasive, field-applicable CRISPR/Cas biosensor to aid in the detection of Pseudogymnoascus destructans, the causative fungal agent of white-nose syndrome in bats.

The accessibility to CRISPR/Cas (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein) genetic tools has given rise to applications beyond site-directed genome editing for the detection of DNA and RNA. These tools include precise diagnostic detection of human disease pathogens, such as SARS-CoV-2 and Zika virus. Despite the technology being rapid and cost-effective, the use of CRISPR/Cas tools in the surveillance of the causative agents of wildlife diseases has not been prominent. This study presents the development of a minimally invasive, field-applicable and user-friendly CRISPR/Cas-based biosensor for the detection of Pseudogymnoascus destructans (Pd), the causative fungal agent of white-nose syndrome (WNS), an infectious disease that has killed more than five million bats in North America since its discovery in 2006. The biosensor assay combines a recombinase polymerase amplification (RPA) step followed by CRISPR/Cas12a nuclease cleavage to detect Pd DNA from bat dermal swab and guano samples. The biosensor had similar detection results when compared to quantitative PCR in distinguishing Pd-positive versus negative field samples. Although bat dermal swabs could be analysed with the biosensor without nucleic acid extraction, DNA extraction was needed when screening guano samples to overcome inhibitors. This assay can be applied to help with more rapid delineation of Pd-positive sites in the field to inform management decisions. With further optimization, this technology has broad translation potential to wildlife disease-associated pathogen detection and monitoring applications.

Developing radiology diagnostic tools for pulmonary fibrosis using machine learning methods.

BACKGROUND: Accurate and prompt diagnosis of the different patterns for pulmonary fibrosis is essential for patient management. However, accurate diagnosis of the specific pattern is challenging due to overlapping radiographic characteristics. MATERIALS AND METHODS: We conducted a retrospective chart review utilizing two machine learning methods, classification and regression tree and Bayesian additive regression tree, to select the most important radiographic features for diagnosing the three most common fibrosis patterns and created an online diagnostic app for convenient implementation. RESULTS: Four hundred patients (median age of 67 with inter quartile range 58-73; 200 males) were included in the study. Peripheral distribution, homogeneity, lower lobe predominance and mosaic attenuation of fibrosis are the four most important features identified. Bayesian additive regression tree demonstrates better performance than classification and regression tree in diagnosis prediction and provides the predicted probability of each diagnosis with uncertainty intervals for each combination of features. CONCLUSION: The model and app built with Bayesian additive regression tree can be used as an effective tool in assisting radiologists in the diagnostic process of pulmonary fibrosis pattern recognition.