Autonomous enzymatic synthesis of functional nucleic acids for sensitive measurement of long noncoding RNA in human lung tissues

Aberrant long noncoding RNA (lncRNA) expression is linked to varied pathological processes and malignant tumors, and lncRNA can serve as potential disease biomarkers. Herein, we demonstrate the autonomous enzymatic synthesis of functional nucleic acids for sensitive measurement of lncRNA in human lung tissues on the basis of multiple primer generation-mediated rolling circle amplification (mPG-RCA). This assay involves two padlock probes that act as both a detection probe for recognizing target lncRNA and a domain for producing complementary DNAzyme. Two padlock probes can hybridize with target lncRNA at different sites, followed by ligation to form a circular template with the aid of RNA ligase. The circular template can initiate mPG-RCA to generate abundant Mg2+-dependent DNAzymes that can specifically cleave signal probes to induce the recovery of Cy3 fluorescence. The inherent characteristics of ligase-based ligation reaction and DNAzymes endow this assay with excellent specificity, and the introduction of multiple padlock probes endows this assay with high sensitivity. This strategy can rapidly and sensitively measure lncRNA with a wide linear range of 1 fM - 1 nM and a detection limit of 678 aM within 1.5 h, and it shows distinct advantages of simplicity and immobilization-free without the need of precise temperature control and tedious procedures of nanomaterial preparation. Moreover, it enables accurate measurement of lncRNA level in normal cells and malignant tumor cells as well as differentiation of lncRNA expressions in tissues of non-small cell lung cancer (NSCLC) patients and normal individuals, with promising applications in biomedical studies and disease diagnosis.

Clinical relevance and advances in detection of translational biomarker cardiac troponin

Cardiovascular diseases (CVD) are a range of diseases, pointing the functional hindrances in the heart and blood vessels of the human system that contributes to 48.6 % of the world's adult death rate. The diagnosis of CVD relies upon the Electro Cardio Gram (ECG) and detection of muscle markers such as troponins. Among the cardiac trio, Cardiac Troponin I (cTnI) weighing 23 KiloDalton (kDa) is a sorted biomarker for CVD. cTnI remains high in the blood after 1-2 weeks of myocardial damage. Testing of cTnI in CVD patients aids in diagnosis and risk stratification of the disease. Different determination systems including optical, electrochemical, and acoustic have been put forward for monitoring the cTnI which are Point of Care (POC) that promotes simple and sensitive detection of cTnI. The modern era has paved way to high-sensitivity Troponin I (hscTnI) devices that can detect up to 0.01 ng/ml in human blood/plasma/serum. Yet, the practice of hscTnI is impracticable due to cost inefficiency. Development of new hscTnI devices with minimal investment and maximal detection range will meet the global requirement. This review gives an over view on different detection systems of cardiac troponin I which stands as a translational detection molecule for CVDs.

Improving synthesis and binding affinities of nucleic acid aptamers and their therapeutics and diagnostic applications

Nucleic acid aptamers have captivated the attention of analytical and medicinal scientists globally due to their several advantages as recognition molecules over conventional antibodies because of their small size, simple and inexpensive synthesis, broad target range, and high stability in varied environmental conditions. These recognition molecules can be chemically modified to make them resistant to nuclease action in blood serum, reduce rapid renel clearance, improve the target affinity and selectivity, and make them amenable to chemically conjugate with a support system that facilitates their selective applications. This review focuses on the development of efficient aptamer candidates and their application in clinical diagnosis and therapeutic applications. Significant advances have been made in aptamer-based diagnosis of infectious and non-infectious diseases. Collaterally, the progress made in therapeutic applications of aptamers is encouraging, as evident from their use in diagnosing cancer, neurodegenerative diseases, microbial infection, and in imaging. This review also updates the progress on clinical trials of many aptamer-based products of commercial interests. The key development and critical issues on the subject have been summarized in the concluding remarks.

Prediction of visceral pleural invasion of clinical stage I lung adenocarcinoma using thoracoscopic images and deep learning

PURPOSE

To develop deep learning models using thoracoscopic images to identify visceral pleural invasion (VPI) in patients with clinical stage I lung adenocarcinoma, and to verify if these models can be applied clinically.

METHODS

Two deep learning models, one based on a convolutional neural network (CNN) and the other based on a vision transformer (ViT), were applied and trained via 463 images (VPI negative: 269 images, VPI positive: 194 images) captured from surgical videos of 81 patients. Model performances were validated via an independent test dataset containing 46 images (VPI negative: 28 images, VPI positive: 18 images) from 46 test patients.

RESULTS

The areas under the receiver operating characteristic curves of the CNN-based and ViT-based models were 0.77 and 0.84 (p = 0.304), respectively. The accuracy, sensitivity, specificity, and positive and negative predictive values were 73.91, 83.33, 67.86, 62.50, and 86.36% for the CNN-based model and 78.26, 77.78, 78.57, 70.00, and 84.62% for the ViT-based model, respectively. These models' diagnostic abilities were comparable to those of board-certified thoracic surgeons and tended to be superior to those of non-board-certified thoracic surgeons.

CONCLUSION

The deep learning model systems can be utilized in clinical applications via data expansion.

Construction of a label-free fluorescent biosensor for homogeneous detection of m6A eraser FTO in breast cancer tissues

Fat mass and obesity-associated protein (FTO) is a crucial eraser of RNA N6- methyladenosine (m6A) modification, and abnormal FTO expression level is implicated in pathogenesis of numerous cancers. Herein, we demonstrate the construction of a label-free fluorescent biosensor for homogeneous detection of m6A eraser FTO in breast cancer tissues. When FTO is present, it specifically erases the methyl group in m6A, inducing the cleavage of demethylated DNA by endonuclease DpnII and the generation of a single-stranded DNA (ssDNA) with a 3'-hydroxyl group. Subsequently, terminal deoxynucleotidyl transferase (TdT) promotes the incorporation of dTTPs into the ssDNA to obtain a long polythymidine (T) DNA sequence. The resultant long poly (T) DNA sequence can act as a template to trigger hyperbranched strand displacement amplification (HSDA), yielding numerous DNA fragments that may be stained by SYBR Gold to produce an enhanced fluorescence signal. This biosensor processes ultrahigh sensitivity with a detection limit of 1.65 × 10-10 mg/mL (2.6 fM), and it can detect the FTO activity in a single MCF-7 cell. Moreover, this biosensor can screen the FTO inhibitors, evaluate enzyme kinetic parameters, and discriminate the FTO expression levels in the tissues of breast cancer patients and healthy persons.

Differentiating Prodromal Dementia with Lewy Bodies from Prodromal Alzheimer's Disease: A Pragmatic Review for Clinicians

This pragmatic review synthesises the current understanding of prodromal dementia with Lewy bodies (pDLB) and prodromal Alzheimer's disease (pAD), including clinical presentations, neuropsychological profiles, neuropsychiatric symptoms, biomarkers, and indications for disease management. The core clinical features of dementia with Lewy bodies (DLB)-parkinsonism, complex visual hallucinations, cognitive fluctuations, and REM sleep behaviour disorder are common prodromal symptoms. Supportive clinical features of pDLB include severe neuroleptic sensitivity, as well as autonomic and neuropsychiatric symptoms. The neuropsychological profile in mild cognitive impairment attributable to Lewy body pathology (MCI-LB) tends to include impairment in visuospatial skills and executive functioning, distinguishing it from MCI due to AD, which typically presents with impairment in memory. pDLB may present with cognitive impairment, psychiatric symptoms, and/or recurrent episodes of delirium, indicating that it is not necessarily synonymous with MCI-LB. Imaging, fluid and other biomarkers may play a crucial role in differentiating pDLB from pAD. The current MCI-LB criteria recognise low dopamine transporter uptake using positron emission tomography or single photon emission computed tomography (SPECT), loss of REM atonia on polysomnography, and sympathetic cardiac denervation using meta-iodobenzylguanidine SPECT as indicative biomarkers with slowing of dominant frequency on EEG among others as supportive biomarkers. This review also highlights the emergence of fluid and skin-based biomarkers. There is little research evidence for the treatment of pDLB, but pharmacological and non-pharmacological treatments for DLB may be discussed with patients. Non-pharmacological interventions such as diet, exercise, and cognitive stimulation may provide benefit, while evaluation and management of contributing factors like medications and sleep disturbances are vital. There is a need to expand research across diverse patient populations to address existing disparities in clinical trial participation. In conclusion, an early and accurate diagnosis of pDLB or pAD presents an opportunity for tailored interventions, improved healthcare outcomes, and enhanced quality of life for patients and care partners.

Construction of a glycosylation-mediated fluorescent biosensor for label-free measurement of site-specific 5-hydroxymethylcytosine in cancer cells with zero background signal

BACKGROUND

5-hydroxymethylcytosine (5hmC) as an epigenetic modification can regulate gene expression, and its abnormal level is related with various tumor invasiveness and poor prognosis. Nevertheless, the current methods for 5hmC assay usually involve expensive instruments/antibodies, radioactive risk, high background, laborious bisulfite treatment procedures, and non-specific/long amplification time.

RESULTS

We develop a glycosylation-mediated fluorescent biosensor based on helicase-dependent amplification (HDA) for label-free detection of site-specific 5hmC in cancer cells with zero background signal. The glycosylated 5hmC-DNA (5ghmC) catalyzed by β-glucosyltransferase (β-GT) can be cleaved by AbaSI restriction endonuclease to generate two dsDNA fragments with sticky ends. The resultant dsDNA fragments are complementary to the biotinylated probes and ligated by DNA ligases, followed by being captured by magnetic beads. After magnetic separation, the eluted ligation products act as the templates to initiate HDA reaction, generating abundant double-stranded DNA (dsDNA) products within 20 min. The dsDNA products are measured in a label-free manner with SYBR Green I as an indicator. This biosensor can measure 5hmC with a detection limit of 2.75 fM and a wide linear range from 1 × 10-14 to 1 × 10-8 M, and it can discriminate as low as 0.001% 5hmC level in complex mixture. Moreover, this biosensor can measure site-specific 5hmC in cancer cells, and distinguish tumor cells from normal cells.

SIGNIFICANCE

This biosensor can achieve a zero-background signal without the need of either 5hmC specific antibody or bisulfite treatment, and it holds potential applications in biological research and disease diagnosis.

Pityriasis lichenoides: assessment of 41 pediatric patients

OBJECTIVES

This study aims to evaluate the characteristics and treatment response of patients with pityriasis lichenoides seen in the last 43 years in a pediatric dermatology service.

METHODS

This was a retrospective, analytical, longitudinal study of patients under 15 years of age. The medical records were reviewed and data were presented as frequencies, means and variances. Student's t-test, Mann-Whitney test, Fisher's exact test, Pearson/Yates chi-square test and multivariate logistic regression model were used, with p < 0.05 considered.

RESULTS

41 patients were included, 32 (78.0%) with pityriasis lichenoides chronica (PLC), five (12.2%) with pityriasis lichenoides et varioliformis acuta (PLEVA) and four (9.8%) with clinical PLC without biopsy. The age range of school children and adolescents was 19 (46.3%) and 13 (31.7%) respectively and 27 (65.8%) were male. Two peaks of the highest frequency were observed between 2004 and 2006 (10 patients - 24.4%) and another between 2019 and 2021 (6 patients - 14.7%). There was remission in 71.9% (n = 23), with 56.6% (n = 17) of those who used antibiotic therapy and 80% (n = 4) of those who had phototherapy. The chance of remission was 13 times greater in patients with disease onset after 5 years of age.

CONCLUSIONS

The clinical form most commonly found was PLC mainly in school children and adolescents. The frequency peaks coincided with infectious outbreaks. The remission rate was satisfactory with antibiotic therapy, but higher with phototherapy. Remission was greater in patients with disease onset after 5 years of age.

Assessing the clinical diagnostic value of anti-Müllerian hormone in polycystic ovarian syndrome and its correlation with clinical and metabolism indicators

BACKGROUND

This study investigated the association between Anti-Müllerian Hormone (AMH) and relevant metabolic parameters and assessed its predictive value in the clinical diagnosis of polycystic ovarian syndrome (PCOS).

METHODS

A total of 421 women aged 20-37 years were allocated to the PCOS (n = 168) and control (n = 253) groups, and their metabolic and hormonal parameters were compared. Spearman correlation analysis was conducted to investigate associations, binary logistic regression was used to determine PCOS risk factors, and receiver operating characteristic (ROC) curves were generated to evaluate the predictive value of AMH in diagnosing PCOS.

RESULTS

The PCOS group demonstrated significantly higher blood lipid, luteinizing hormone (LH), and AMH levels than the control group. Glucose and lipid metabolism and hormonal disorders in the PCOS group were more significant than in the control group among individuals with and without obesity. LH, TSTO, and AMH were identified as independent risk factors for PCOS. AMH along with LH, and antral follicle count demonstrated a high predictive value for diagnosing PCOS.

CONCLUSION

AMH exhibited robust diagnostic use for identifying PCOS and could be considered a marker for screening PCOS to improve PCOS diagnostic accuracy. Attention should be paid to the effect of glucose and lipid metabolism on the hormonal and related parameters of PCOS populations.

Diagnosis of peripartum depression disorder: A state-of-the-art approach from the COST Action Riseup-PPD

BACKGROUND

Peripartum depression (PPD) is a major depression disorder (MDD) episode with onset during pregnancy or within four weeks after childbirth, as defined in DSM-5. However, research suggests that PPD may be a distinct diagnosis. The goal of this study was to summarize the similarities and differences between PPD and MDD by synthesizing the current research on PPD diagnosis concerning different clinical features and give directions for improving diagnosis of PPD in clinical practice.

METHODS

To lay the groundwork for this narrative review, several databases were searched using general search phrases on PPD and its components of clinical diagnosis.

RESULTS

When compared to MDD, peripartum depression exhibits several distinct characteristics. PPD manifests with a variety of symptoms, i.e., more anxiety, psychomotor symptoms, obsessive thoughts, impaired concentration, fatigue and loss of energy, but less sad mood and suicidal ideation, compared to MDD. Although PPD and MDD prevalence rates are comparable, there are greater cross-cultural variances for PPD. Additionally, PPD has some distinct risk factors and mechanisms such as distinct ovarian tissue expression, premenstrual syndrome, unintended pregnancy, and obstetric complications.

CONCLUSION

There is a need for more in-depth research comparing MDD with depression during pregnancy and the entire postpartum year. The diagnostic criteria should be modified, particularly with (i) addition of specific symptoms (i.e., anxiety), (ii) onset specifier extending to the first year following childbirth, (iii) and change the peripartum onset specifier to either "pregnancy onset" or "postpartum onset". Diagnostic criteria for PPD are further discussed.

Apoptosis-related prognostic biomarkers and potential targets for acute kidney injury based on machine learning algorithm and in vivo experiments

Acute kidney injury (AKI) is a common critical illness in hospitalized patients, characterized by a rapid decline in kidney function over a short period, which can seriously endanger the patient's life. Currently, there is a lack of precise and universal AKI diagnostic biomarkers in clinical practice. In this study, weighted gene coexpression network analysis (WGCNA), differential expression analysis, univariate and multivariate logistic regression analyses, receiver operating characteristic (ROC) curves, and immune cell infiltration were performed to identify apoptosis-related biomarkers that can be used for AKI diagnosis. Three core apoptosis-related genes (ARGs), CBFB, EGF and COL1A1, were identified as AKI biomarkers. More importantly, an apoptosis-related signature containing three hub ARGs was validated as a diagnostic model. The hub genes exhibited good correlations with glomerular filtration rate (GFR) and serum creatinine (SCr) in the Nephroseq kidney disease database. Additionally, CIBERSORT immune infiltration analysis indicated that these core ARGs may affect immune cell recruitment and infiltration in AKI patients. Subsequently, we investigated the alteration of the expression levels of three core ARGs in AKI samples using single-cell RNA sequencing analysis and analyzed the cell types that mainly expressed these ARGs. More importantly, the expression of core ARGs was validated in folic acid- and cisplatin-induced AKI mouse models. In summary, our study identified three diagnostic biomarkers for AKI, explored the roles of ARGs in AKI progression and provided new ideas for the clinical diagnosis and treatment of AKI.

Lumbar disc herniation: Epidemiology, clinical and radiologic diagnosis WFNS spine committee recommendations

Objective

To formulate the most current, evidence-based recommendations regarding the epidemiology, clinical diagnosis, and radiographic diagnosis of lumbar herniated disk (LDH).

Methods

A systematic literature search in PubMed, MEDLINE, and CENTRAL was performed from 2012 to 2022 using the search terms "herniated lumbar disc", "epidemiology", "prevention" "clinical diagnosis", and "radiological diagnosis". Screening criteria resulted in 17, 16, and 90 studies respectively that were analyzed regarding epidemiology, clinical diagnosis, and radiographic diagnosis of LDH. Using the Delphi method and two rounds of voting at two separate international meetings, ten members of the WFNS (World Federation of Neurosurgical Societies) Spine Committee generated eleven final consensus statements.

Results

The lifetime risk for symptomatic LDH is 1-3%; of these, 60-90% resolve spontaneously. Risk factors for LDH include genetic and environmental factors, strenuous activity, and smoking. LDH is more common in males and in 30-50 year olds. A set of clinical tests, including manual muscle testing, sensory testing, Lasegue sign, and crossed Lasegue sign are recommended to diagnose LDH. Magnetic resonance imaging (MRI) is the gold standard for confirming suspected LDH.

Conclusions

These eleven final consensus statements provide current, evidence-based guidelines on the epidemiology, clinical diagnosis, and radiographic diagnosis of LDH for practicing spine surgeons worldwide.

Impact of muscle biopsy on the clinical decision-making process in patients with suspected idiopathic inflammatory myopathy

BACKGROUND

The significance of muscle biopsy as a diagnostic tool in idiopathic inflammatory myopathies (IIM) remains elusive. We aimed to determine the diagnostic weight that has been given to muscle biopsy in patients with suspected IIM, particularly in terms of clinical diagnosis and therapeutic decisions.

MATERIAL AND METHODS

In this retrospective multicentric study, we analyzed muscle biopsy results of adult patients with suspected IIM referred to a tertiary center between January 1, 2007, and October 31, 2021. Information regarding referral department, suspected diagnosis, biopsy site, demographic, clinical, laboratory data, and imaging results were extracted. Statistical analyses included the level of agreement between suspected and histological diagnosis and calculation of diagnostic performance (positive and negative predictive values, positive and negative likelihood ratios, sensitivity, and specificity of muscle biopsy in relation to clinical diagnosis and/or treatment initiation). Performance was tested in different strata based on clinical pre-test probability.

RESULTS

Among 758 muscle biopsies, IIM was histologically compatible in 357/758 (47.1%) cases. Proportion of IIM was higher if there was a solid clinical pre-test probability (64.3% vs. 42.4% vs. 48% for high, medium and low pre-test probability). Sensitivity and specificity of muscle biopsy were highest (82%) when the diagnosis by the clinician was used as outcome scenario. Negative predictive value was only moderate (between 63% and 80%) and lowest if autoantibodies were positive (35%).

CONCLUSION

In patients with clinically suspected IIM, approximately 50% of biopsies revealed features indicative of IIM. Diagnostic performance of muscle biopsy was moderate to high depending on clinical pre-test probability.

Electrochemical peptide-based biosensor for the detection of the inflammatory disease biomarker, interleukin-1beta

This paper reports the development of a highly sensitive and selective electrochemical peptide-based biosensor for the detection of the inflammatory disease biomarker, interleukin-1beta (IL-1β). To this end, flower-like Au-Ag@MoS2-rGO nanocomposites were used as the signal amplification platform to achieve a label-free biosensor with a high sensitivity and selectivity. First, a high-affinity peptide for IL-1β was identified through biopanning with M13 random peptide libraries, and was newly designed by incorporating cysteine at the C-terminus. An IL-1β specific binding peptide was used as the bio-receptor, and the interaction between the IL-1β binding peptide and IL-1β was confirmed via enzyme-linked immunosorbent assay and various physicochemical and electrochemical analyses. Under optimal conditions, the biosensor achieved an ultrasensitive and specific IL-1β detection in a wide linear concentration range of 0-250 ng/mL with a picomolar-level detection limit (∼2.4 pM), low binding constant (∼0.62 pM), and a low coefficient of variation (<1.65 %). The biosensor was successfully utilized for IL-1β determination in the serum of Crohn's disease patients with a good correlation coefficient. In addition, the detection performance was comparable to that of commercially available IL-1β ELISA kit. This indicates that the electrochemical peptide-based biosensor may offer a potentially valuable platform for the clinical diagnosis of various inflammatory disease biomarkers.

Imaging mRNA in vitro and in vivo with nanofirecracker probes via intramolecular hybridization chain reaction

Hybridization chain reaction (HCR) based enzyme-free amplification techniques have recently been developed for the visualization of intracellular messenger RNA (mRNA). However, the slow kinetics and potential interference with the intricate biological environments hinder its application in the clinic and in vivo. Herein, we designed a nanofirecracker probe-based strategy using intramolecular hybridization chain reaction (IHCR) amplifier for rapid, efficient, sensitive, specific detection and imaging of survivin mRNA both in vitro and vivo. Two probes, HP1 and HP2, in IHCR were simultaneously incorporated into a DNA nanowire scaffolds to bring HP1 and HP2 to close proximity on the assembled nanowire scaffolds. Empowered by the DNA nanowire scaffolds and spatial confinement effect, the nanofirecracker probe-based IHCR sensing system exhibited improved biostability, accelerated reaction kinetics, and enhanced signal amplification. This new strategy has been successfully applied to imaging mRNA in both cultured cells and in mice. Importantly, this novel sensing method was capable of detecting survivin mRNA in clinical blood samples from subjects with colorectal cancer. Thus, this novel nanofirecracker probe-based IHCR strategy holds great potential in advancing both biomedical research and in molecular diagnostics.

An integrated electrochemical immunosensor based on Pd-Ir cubic nanozyme and Ketjen black for ultrasensitive detection of circulating tumor cells

Ultrasensitive detection of circulating tumor cells (CTCs) holds significant clinical importance in monitoring metastasis and therapeutic outcomes. In this study, we have developed a novel electrochemical sensing model based on nanomaterials for highly sensitive and specific determination of CTCs. A gold electrode co-modified with Ketjin black (KB) and Au nanoparticles (AuNPs) exhibits exceptional conductivity. By conjugating palladium-iridium cubic nanozyme (Pd-Ir CNE) with antibodies, we have created a detection probe capable of catalyzing hydrogen peroxide (H2O2), thereby amplifying the output signal and resulting in significantly enhanced current on the electrode for detecting CTCs. The constructed immunosensor has achieved a detection limit of 2 cell mL-1 for model MCF-7 cells. Furthermore, the as-constructed electrochemical immunosensor can accurately detect whole blood-spiked target CTCs, showing great promise for clinical applications in early cancer diagnosis and prognosis.

Exhaled breath condensate analysis in horses: A scoping review

Exhaled breath condensate (EBC) collection is a non-invasive sampling method that provides valuable information regarding the health status of the respiratory system by measuring inflammatory mediators, such as pH, hydrogen peroxide, and leukotriene B4. This scoping review aimed to provide an update on the collection and analysis of EBC in horses. A systematic search of three electronic databases, PubMed, Google Scholar, Science Direct, identified 40,978 articles, of which 1590 duplicates were excluded. Moreover, 39,388 articles were excluded because of irrelevance to this review, such as studies on other species, studies on respiratory exhalation, reviews, and theses. Finally, we evaluated 14 articles in this review. Our review revealed significant differences in the collection, storage, and processing of EBC samples, emphasizing the need for standardizing the technique and using specific equipment to improve the interpretation of the results.

Application of two-dimensional polymerase chain reaction to detect four types of microorganisms in feces for assisted diagnosis of IBD

BACKGROUND

The incidence of inflammatory bowel disease (IBD) continues to increase annually, accounting for about 6.8 million cases in 2017 worldwide. However, there is currently no gold standard for the diagnosis of IBD.

METHODS

A method for the detection of four microorganisms in feces by two-dimensional polymerase chain reaction (2D-PCR) has been developed. Plasmids were used to validate the sensitivity and specificity of the method. Clinical samples were tested using a 2D-PCR method. Optimal diagnostic thresholds for IBD were determined based on ROC results.

RESULTS

Of the 112 samples, 78 were from IBD patients and 34 from patients with other gastrointestinal (GI) diseases. Thomasclavelia ramosum and univ907-1062 positivity are necessary, and two or more positives of the three bacteria (Thomasclavelia spiroforme, Thomasclavelia saccharogumia or Clostridium cluster XVIII) are the optimal diagnostic thresholds for IBD. The area under the curve was 0.826 with a 95% confidence interval of 0.735-0.981 and a p-value of 0.000, corresponding to a sensitivity of 0.769 and a specificity of 0.853.

CONCLUSIONS

Based on the detection results of microorganisms, IBD and GI can be effectively distinguished. The detection of four microorganisms in feces can assist clinicians in the differential diagnosis of IBD. Our experiment aims to provide a better program for early clinical diagnosis and regular dynamic monitoring of IBD.

A new method applied for explaining the landing patterns: Interpretability analysis of machine learning

As one of many fundamental sports techniques, the landing maneuver is also frequently used in clinical injury screening and diagnosis. However, the landing patterns are different under different constraints, which will cause great difficulties for clinical experts in clinical diagnosis. Machine learning (ML) have been very successful in solving a variety of clinical diagnosis tasks, but they all have the disadvantage of being black boxes and rarely provide and explain useful information about the reasons for making a particular decision. The current work validates the feasibility of applying an explainable ML (XML) model constructed by Layer-wise Relevance Propagation (LRP) for landing pattern recognition in clinical biomechanics. This study collected 560 groups landing data. By incorporating these landing data into the XML model as input signals, the prediction results were interpreted based on the relevance score (RS) derived from LRP. The interpretation obtained from XML was evaluated comprehensively from the statistical perspective based on Statistical Parametric Mapping (SPM) and Effect Size. The RS has excellent statistical characteristics in the interpretation of landing patterns between classes, and also conforms to the clinical characteristics of landing pattern recognition. The current work highlights the applicability of XML methods that can not only satisfy the traditional decision problem between classes, but also largely solve the lack of transparency in landing pattern recognition. We provide a feasible framework for realizing interpretability of ML decision results in landing analysis, providing a methodological reference and solid foundation for future clinical diagnosis and biomechanical analysis.

Explaining predictors of discharge destination assessed along the patients' acute stroke journey

INTRODUCTION

Accurate prediction of outcome destination at an early stage would help manage patients presenting with stroke. This study assessed the predictive ability of three machine learning (ML) algorithms to predict outcomes at four different stages as well as compared the predictive power of stroke scores.

METHODS

Patients presenting with acute stroke to the Canberra Hospital between 2015 and 2019 were selected retrospectively. 16 potential predictors and one target variable (discharge destination) were obtained from the notes. k-Nearest Neighbour (kNN) and two ensemble-based classification algorithms (Adaptive Boosting and Bootstrap Aggregation) were employed to predict outcomes. Predictive accuracy was assessed at each of the four stages using both overall and per-class accuracy. The contribution of each variable to the prediction outcome was evaluated by the ensemble-based algorithm and using the Relief feature selection algorithm. Various combinations of stroke scores were tested using the aforementioned models.

RESULTS

Of the three ML models, Adaptive Boosting demonstrated the highest accuracy (90%) at Stage 4 in predicting death while the highest overall accuracy (81.7%) was achieved by kNN (k=2/City-block distance). Feature importance analysis has shown that the most important features are the 24-hour Scandinavian Stroke Scale (SSS) and 24-hour National Institutes of Health Stroke Scale (NIHSS) scores, dyslipidaemia, hypertension and premorbid mRS score. For the initial and 24-hour scores, there was a higher correlation (0.93) between SSS scores than for NIHSS scores (0.81). Reducing the overall four scores to InitSSS/24hrNIHSS increased accuracy to 95% in predicting death (Adaptive Boosting) and overall accuracy to 85.4% (kNN). Accuracies at Stage 2 (pre-treatment, 11 predictors) were not far behind those at Stage 4.

CONCLUSION

Our findings suggest that even in the early stages of management, a clinically useful prediction regarding discharge destination can be made. Adaptive Boosting might be the best ML model, especially when it comes to predicting death. The predictors' importance analysis also showed that dyslipidemia and hypertension contributed to the discharge outcome even more than expected. Further, surprisingly using mixed score systems might also lead to higher prediction accuracies.

The accuracy of asynchronous tele-screening for detecting dental caries in patient-captured mobile photos: A pilot study

Objectives

Unaided visual inspection is a primary dental screening technique. Given the uneven distribution of dental services and prolonged waiting periods, an alternative screening approach is required to increase access to dental care. The purpose of this study was to evaluate the accuracy and reliability of tele-screening for detecting dental caries using mobile intra-oral photos taken by participants.

Methods

Dental care seekers attending Umm Al-Qura University Teaching Dental Hospital in 2022 were invited to participate in this study. The participants were initially examined by dental interns at the hospital under the supervision of faculty dentists (reference standard) before intra-oral photos were acquired by a trained sixth-year dental student using a Samsung S10 camera. Following an introduction to the photography guide, the same participants then took intra-oral photos of their teeth at home using their mobile devices, which were all uploaded to WhatsApp for later review. Two trained dental reviewers (sixth-year dental students) independently reviewed the intra-oral photos. Sensitivity, specificity, and Kappa scores were estimated to assess the performance of the tele-screening approach relative to the reference unaided dental examination.

Results

Twenty-three participants, with a mean age of 30 ± 12 years, were enrolled. The mean decayed, missing, and filled teeth (DMFT) was 13.43 ± 5.48. Patient-delivered tele-screening demonstrated a sensitivity, specificity, and inter-rater reliability kappa of 94 %, 90 %, and 0.81, respectively, when compared to unaided dental examination. Dentist-delivered tele-screening approach demonstrated a sensitivity of 88-89 %, specificity of 88-91 %, and kappa score of 0.75-0.79 relative to unaided dental examination.

Conclusions

This study demonstrated that the tele-screening approach based on reviewing intra-oral photos taken by participants can be a valid and reliable alternative to unaided dental examination. This is important for ensuring sustainable access to dental care.

Foodborne and airborne polyethersulfone nanoplastics respectively induce liver and lung injury in mice: Comparison with microplastics

Micro/nanoplastics (MNP) are ubiquitous in the environment and multiple living organisms. The toxicity of some common types of MNP, e.g., polyethersulfone (PES) MNP, remains poorly understood. Multi-omics approaches were used in this study to determine the effects of foodborne and airborne PES MNP on liver and lung, respectively. Foodborne MNP were capable of inducing gut microbial dysbiosis, gut and serum metabolic disruption, and liver transcriptomic dysregulation, and affecting serum antioxidant activity and liver function, resulting in liver injury. As for the airborne MNP, they were found to induce nasal and lung microbial dysbiosis, serum and lung metabolic disruption, and liver transcriptome disturbance, and cause disrupted serum antioxidant activity and lung injury. Foodborne and airborne PES NP were found to respectively induce greater liver and lung toxicity than MP, which could be associated with the differences between NP and MP exposures. The relevant results suggest that foodborne PES MNP could disrupt the "gut microbiota-gut-liver" axis and induce hepatic injury, while airborne PES MNP could affect the "airborne microbiota-lung" axis and cause lung injury. The findings could benefit the diagnoses of liver and lung injury respectively induced by foodborne and airborne PES MNP, as well as the proper use of PES in human living environment.

A new risk factor for coronary artery disease can be detected by an ApoA1 mAb-based assay

BACKGROUND

This study aimed to find coronary artery disease (CAD) related apolipoprotein A1 (ApoA1) monoclonal antibody (mAb) and to evaluate the diagnostic value of the assay based on it.

METHODS

Patients with CAD diagnosed by coronary angiography (disease group, n = 180) and healthy subjects (control group, n = 199) were recruited. The correlation between methods and CAD were evaluated by Spearman's rank correlation coefficients. Receiver operating characteristic (ROC) curve analysis was used to evaluate the auxiliary diagnostic value of methods for CAD. Odds ratios (ORs) of the test results in CAD were estimated using logistic regression analysis.

RESULTS

Measurements from an ApoA1 mAb were found significantly positively correlated with CAD (r = 0.243, P < 0.01), unlike the measurements from the ApoA1 pAb were negatively correlated with CAD (r = -0.341, P < 0.001). The areas under the ROC curve of the ApoA1 mAb and pAb measurements were 0.704 and 0.563, respectively, in patients with normal HDL-C levels. ApoA1 values from the mAb assay had a significant positive impact on CAD risk.

CONCLUSION

An ApoA1 mAb-based assay can distinguish a high-density lipoprotein (HDL) subclass positively related to CAD, which can be used to improve and reappraise CAD risk assessment.

Investigating the chemical pathway to the formation of a single biofilm using infrared spectroscopy

Diagnosing biofilm infections has remained a constant challenge for the last 50 years. Existing diagnostic methods struggle to identify the biofilm phenotype. Moreover, most methods of biofilm analysis destroy the biofilm making the resultant data interpretation difficult. In this study we introduce Fourier Transform Infra-Red (FTIR) spectroscopy as a label-free, non-destructive approach to monitoring biofilm progression. We have utilised FTIR in a novel application to evaluate the chemical composition of bacterial biofilms without disrupting the biofilm architecture. S. epidermidis (RP62A) was grown onto calcium fluoride slides for periods of 30 min-96 h, before semi-drying samples for analysis. We report the discovery of a chemical marker to distinguish between planktonic and biofilm samples. The appearance of new proteins in biofilm samples of varying maturity is exemplified in the spectroscopic data, highlighting the potential of FTIR for identifying the presence and developmental stage of a single biofilm.

Paper-based substrates for surface-enhanced Raman spectroscopy sensing

Surface-enhanced Raman scattering (SERS) has been recognized as one of the most sensitive analytical methods by adsorbing the target of interest onto a plasmonic surface. Growing attention has been directed towards the fabrication of various substrates to broaden SERS applications. Among these, flexible SERS substrates, particularly paper-based ones, have gained popularity due to their easy-to-use features by full contact with the sample surface. Herein, we reviewed the latest advancements in flexible SERS substrates, with a focus on paper-based substrates. Firstly, it begins by introducing various methods for preparing paper-based substrates and highlights their advantages through several illustrative examples. Subsequently, we demonstrated the booming applications of these paper-based SERS substrates in abiotic and biological matrix detection, with particular emphasis on their potential application in clinical diagnosis. Finally, the prospects and challenges of paper-based SERS substrates in broader applications are discussed.

Epidemiological and clinical differences of confirmed and discarded Mpox cases on the 2022 Chilean outbreak

Objectives

To improve Mpox diagnosis by identifying distinctive symptoms in confirmed vs discarded cases due to outdated case definition.

Methods

This is a case-control study conducted using data from the Institute of Public Health database, encompassing all suspected cases analyzed by real-time polymerase chain reaction between June 1 and September 30, 2022. We calculated means, frequencies, performed Fisher's test, and computed odds ratios (OR) using RStudio and Microsoft Excel.

Results

Among 1415 suspected Mpox cases, 87% were men aged 30-39 with exanthema. Confirmed cases had higher rates of lymphadenopathy (31% vs 12%), fever (42% vs 29%), myalgia (35% vs 25%), and specific lesions: pustules (36% vs 27%), scabs (25% vs 17%), and umbilicated lesions (24% vs 7%) (P <0.05). Key risk factors for Mpox included contact with a positive case (OR 2.33), multiple sexual partners (OR 3.52), and male gender (OR 29.93).

Conclusion

The symptomatology of confirmed Mpox cases closely aligns with that reported in the current outbreak. The primary risk factors identified include prior contact with another positive case, having multiple sexual partners, and male gender. However, to facilitate a more complete analysis, more evidence needs to be investigated.

Enhancing the clinical diagnosis of the acute and subacute phases of autoimmune encephalitis and predicting the risk factors: the potential advantages of 18F-FDG PET/CT

BACKGROUND

2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography (18F-FDG PET) could help evaluate metabolic abnormalities by semi-quantitative measurement to identify autoimmune encephalitis (AE). Few studies have been conducted to analyze the prognostic factors of AE. The study aimed to explore the values of diagnosis and treatment evaluation by 18F-FDG PET and preliminarily discussed the potential value in predicting the prognosis of AE patients.

METHODS

AE patients underwent 18F-FDG PET/CT and magnetic resonance imaging (MRI). There were two steps to analyse 18F-FDG PET imaging data. The first step was visual assessment. The second step was to analyse 18F-FDG PET parameters using Scenium software (Siemens Molecular Imaging Ltd). The mean standardized uptake value (SUVmean) and maximum standardized uptake value (SUVmax) of brain relative regional metabolism (BRRM) were quantified in the case and control groups according to the anatomical automatic labeling (AAL) partition. The main statistical method was the Kruskal-Wallis test. Finally, the simple linear regression method was used to analyse the relationships between 18F-FDG PET parameters and the modified Rankin Scale (mRS) scores before and after treatment.

RESULTS

The results on 18F-FDG PET showed that visual assessment abnormalities were in the mesial temporal lobe (MTL) (70.8%), (mainly infringing on the hippocampus and amygdala), basal ganglia (62.5%), frontal lobes (37.5%), occipital lobes (29.2%), and parietal lobes (12.5%). The positive rate of abnormalities on 18F-FDG PET was more sensitive than that on MRI (95.5% vs 32.2%, p = 0.001). The number of lesions on PET was positively correlated with the mRS scores before and after treatment, and the correlation before treatment was more significant. Before treatment, the SUVmean of the left occipital lobe was the most remarkable (SUVmean, R2 = 0.082, p > 0.05) factor associated with the mRS score, and the correlation was negative. With regard to prognosis, the SUVmax of the MTL was the most notable (R2 = 0.1471, p > 0.05) factor associated with the mRS score after treatment, and the correlation was positive.

CONCLUSIONS

18F-FDG PET could be more sensitive and informative than MRI in the early phases of AE. The common pattern of AE was high MTL metabolism on 18F-FDG PET, which was associated with hypometabolism of the occipital lobe, and the number of lesions on PET before treatment may be significant factors in assessing disease severity. The SUVmax of MTL hypermetabolism may serve as a prognostic biomarker in AE.

Next-Generation sequencing transforming clinical practice and precision medicine

Next-generation sequencing (NGS) has revolutionized the field of genomics and is rapidly transforming clinical diagnosis and precision medicine. This advanced sequencing technology enables the rapid and cost-effective analysis of large-scale genomic data, allowing comprehensive exploration of the genetic landscape of diseases. In clinical diagnosis, NGS has proven to be a powerful tool for identifying disease-causing variants, enabling accurate and early detection of genetic disorders. Additionally, NGS facilitates the identification of novel disease-associated genes and variants, aiding in the development of targeted therapies and personalized treatment strategies. NGS greatly benefits precision medicine by enhancing our understanding of disease mechanisms and enabling the identification of specific molecular markers for disease subtypes, thus enabling tailored medical interventions based on individual characteristics. Furthermore, NGS contributes to the development of non-invasive diagnostic approaches, such as liquid biopsies, which can monitor disease progression and treatment response. The potential of NGS in clinical diagnosis and precision medicine is vast, yet challenges persist in data analysis, interpretation, and protocol standardization. This review highlights NGS applications in disease diagnosis, prognosis, and personalized treatment strategies, while also addressing challenges and future prospects in fully harnessing genomic potential within clinical practice.

Performance evaluation of in-house developed Covid-19 IgG/IgM antibody rapid diagnostic kit

In the interest of preventing the Coronavirus Disease 2019 (COVID-19) pandemic from spreading, it is crucial to promptly identify and confine afflicted patients. Serological antibody testing is a significant diagnostic technique that is increasingly employed in clinics, however its clinical use is still being investigated. The present study was carried out to scrutinize how well Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) antibody testing using in-house developed rapid antibody assay worked against the chemiluminescence (CLIA) assay. Either IgG positive (IgG + IgM-) or IgM positive (IgM + IgG-); both IgG and IgM positive (IgM + IgG+); and negatives (IgM- IgG-) have been evaluated. A total of 300 samples with diverse age and sexual identity data were included. The combined sensitivities for IgG + IgM+, IgM + IgG-, IgG + IgM- and IgG-IgM- were evaluated. More accurate diagnostic results may be obtained using molecular diagnostic tools. The Antibody Rapid Diagnostic kit's (in-house developed) performance was satisfactory for determining the presence of Covid-19 infection with IgG and IgM positivity. The IgG and IgM positivity helped evaluate the immune response in the individual for the COVID-19 infection. These results lend support to the additional utilisation of serological antibody tests in the COVID-19 diagnosis.

Clinical value of droplet digital PCR in the diagnosis and dynamic monitoring of suspected bacterial bloodstream infections

BACKGROUND

Bloodstream infections (BSIs) represent a significant public health challenge due to their high morbidity and mortality. The clinical prognosis of BSIs is closely related to the timely and accurate diagnosis and the rational use of initial antimicrobials. We aimed to evaluate the clinical value of droplet digital PCR (ddPCR) in rapid diagnosis and dynamic monitoring of BSIs.

METHODS

In this prospective study, using a ddPCR-based approach which detects 18 common pathogens, we compared the detection results and clinical concordance rates of ddPCR with blood culture (BC) in 211 patients with suspected BSIs. Further, the inflammatory profile of BSIs with Gram-negative bacteria was analyzed by Olink proteomics platform.

RESULTS

Our data showed that the positive detection rate of ddPCR was 48.82%, which was higher than that of BC (9.48%). For BC-validated BSIs, ddPCR had a sensitivity of 90.00% and a specificity of 55.50%. When considering clinically-validated BSIs, the diagnostic value of ddPCR improved with a sensitivity of 92.59% and a specificity of 78.46%.The bacterial load detected by ddPCR was correlated with traditional clinical inflammatory indicators such as interleukin-6 (IL-6) and C-reactive protein (CRP). In addition, using Olink proteomics platform, we revealed that serological osteoprotegerin (OPG), interleukin-8 (IL-8), interleukin-18 receptor 1 (IL-18R1), C-C motif chemokine 20 (CCL20) and IL-6 were substantially elevated in Gram-negative bacteria-associated BSIs, which could serve as novel auxiliary diagnostic indicators for Gram-negative bacteria BSIs.

CONCLUSION

ddPCR has the potential to provide early pathogen diagnosis, dynamic monitoring, and treatment regimen optimization for patients with BSIs.

Novel biomarkers identified by weighted gene co-expression network analysis for atherosclerosis

BACKGROUND

This study aimed to screen out the potential diagnostic biomarkers for atherosclerosis (AS).

METHODS

We downloaded the gene expression profiles GSE66360, GSE28829, GSE41571, GSE71226, and GSE100927 from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using the "limma" package in R. Weighted gene co-expression network analysis (WGCNA) was applied to reveal the correlation between genes in different samples. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. The interaction pairs of proteins were retained by the STRING database, and the protein-protein interaction (PPI) network was visualized with the hub genes. Finally, the R packages "ggpubr" and "preprocessCore" were used to analyze immune cell infiltration.

RESULTS

In total, 40 overlapping genes both in GSE66360 and GSE28829 were found to be related to the occurrence of AS. Further, the top 10 network hub genes including TYROBP, CSF1R, TLR2, CD14, CCL4, FCER1G, CD163, TREM1, PLEK, and C5AR1 were identified as significant key genes. Moreover, four genes (TYROBP, CSF1R, FCGR1B, and CD14) were verified that could efficiently diagnose AS. Finally, the gene TYROBP was found to have a strong correlation with immune-infiltrating cells.

CONCLUSION

Our study identified four genes (TYROBP, CSF1R, FCGR1B, and CD14) that may be effective biomarkers for AS, with the potential to guide the clinical diagnosis of AS.

A study on the multidisciplinary diagnostic approach of leprosy: Can we prevent the recrudescence in the post-elimination Indian scenario?

Introduction

Leprosy also widely known by the name Hansen's disease is a chronic disease caused by Mycobacterium leprae affecting mankind with various clinico-pathological forms. It remained a major public health issue due to associated case load, morbidity and stigma attached to it. India declared elimination of leprosy in the year 2005. However, it is surprising to see that in some parts of the country, the prevalence is still significant. The objective of the study is to describe the spectrum of histopathological profile of leprosy and compare its correlation with clinical diagnosis in this post elimination era.

Methods

A 24-months prospective study was conducted with clinically diagnosed leprosy cases in a tertiary care hospital in eastern India. Lesions were graded and the histopathological slides along with its bacteriological index (BI) on slit skin smears where possible was reviewed and analyzed. Agreement of histopathological finding with clinical finding was established.

Results

A total of 220 cases were included in the study. On histopathology, borderline category was the most frequently reported with borderline tuberculoid the most common subtype. Most common clinical feature was hypopigmented plaque, followed by erythematous skin lesions, nodules, macules etc. Bacteriological index was studied in 192 slit skin smears. Moderate agreement between clinical and histopathological diagnosis with kappa measure of inter-rater agreement as 0.457 was noted.

Conclusion

Clinico-histopathological correlation is pivotal in the accurate diagnosis of leprosy to prevent, treat, and control the resurgence of the disease in the post-elimination era.

Recent advances in surface enhanced Raman spectroscopy for bacterial pathogen identifications

BACKGROUND

The rapid and reliable detection of pathogenic bacteria at an early stage is a highly significant research field for public health. However, most traditional approaches for pathogen identification are time-consuming and labour-intensive, which may cause physicians making inappropriate treatment decisions based on an incomplete diagnosis of patients with unknown infections, leading to increased morbidity and mortality. Therefore, novel methods are constantly required to face the emerging challenges of bacterial detection and identification. In particular, Raman spectroscopy (RS) is becoming an attractive method for rapid and accurate detection of bacterial pathogens in recent years, among which the newly developed surface-enhanced Raman spectroscopy (SERS) shows the most promising potential.

AIM OF REVIEW

Recent advances in pathogen detection and diagnosis of bacterial infections were discussed with focuses on the development of the SERS approaches and its applications in complex clinical settings.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The current review describes bacterial classification using surface enhanced Raman spectroscopy (SERS) for developing a rapid and more accurate method for the identification of bacterial pathogens in clinical diagnosis. The initial part of this review gives a brief overview of the mechanism of SERS technology and development of the SERS approach to detect bacterial pathogens in complex samples. The development of the label-based and label-free SERS strategies and several novel SERS-compatible technologies in clinical applications, as well as the analytical procedures and examples of chemometric methods for SERS, are introduced. The computational challenges of pre-processing spectra and the highlights of the limitations and perspectives of the SERS technique are also discussed.Taken together, this systematic review provides an overall summary of the SERS technique and its application potential for direct bacterial diagnosis in clinical samples such as blood, urine and sputum, etc.

Cervicogenic headache

INTRODUCTION

Cervicogenic headache, first proposed as a distinct headache in 1983, is a secondary headache to a primary cervical musculoskeletal disorder. Research into physical impairments was integral to clinical diagnosis and to develop and test research informed conservative management as the first line approach.

PURPOSE

This narrative presents an overview of the body of cervicogenic headache research from our laboratory which was undertaken in the context of a broad program of research into neck pain disorders.

IMPLICATIONS

Early research validated manual examination of the upper cervical segments against anaesthetic nerve blocks, which was vital to clinical diagnosis of cervicogenic headache. Further studies identified reduced cervical motion, altered motor control of the neck flexors, reduced strength of flexor and extensor muscles, and occasional presentation of mechanosensitivity of the upper cervical dura. Single measures are variable and not reliable in diagnosis. We proved that a pattern of reduced motion, upper cervical joint signs and impaired deep neck flexor function accurately identified cervicogenic headache and differentiated it from migraine and tension-type headache. The pattern was validated against placebo controlled diagnostic nerve blocks. A large multicentre clinical trial determined that a combined program of manipulative therapy and motor control exercise is effective in the management of cervicogenic headache and outcomes are maintained in the long term. More specific research into cervical related sensorimotor controlled is warranted in cervicogenic headache. Further adequately powered clinical trials of current research informed multimodal programs are advocated to further strengthen the evidence base for conservative management of cervicogenic headache.

A universal diagnosis syntax

BACKGROUND

Diagnoses are crucial assets of clinical work and provide the foundation for treatment and follow up. They should be informative and customized to the patient's problem. Common prefixes, morphemes, and suffixes may aid the implementation of expressions that generate diagnoses.

RESULTS

Apt choices of symbols plays a major role in science. In this study, the variables e, o, and p are assigned to names of an etiological agent, a disorder, and a pathogenetic mechanism, respectively. The suffix -itis designates infections, allergies, inflammation, and/or immune reactions. Diagnoses (d) are generated by the formula d:= e&o&p where '&' means concatenation and ':= ' means assignment. Thus, with e:= 'Staphylococcus aureus ', o:= 'endocard', and p:= 'itis', d:= e&o&p generates the diagnosis d = 'Staphylococcus aureus endocarditis'. Diagnoses formed this way comply with common clinical diagnoses. Certain extensions generate complete, systematic medical diagnoses that are applicable to all medical specialties. For example, common medical prefixes, morphemes, and suffixes give rise to o = 'hypothyroidism', o = 'tachycardia', and o = 'hypophagocytosis'. The formula scales well with the developments in clinical medicine, systems biology, molecular biology, and microbiology. The diagnosis generating formula d:= e&o&p requires meticulous analysis of the components of diagnoses plus the introduction of appropriate variables and terms. Terms partition on established clinical categories and adhere to established clinical nomenclature. The syntax generates universal medical diagnoses.

CONCLUSIONS

The present study concerns a universal diagnosis syntax (UDS) that generates diagnoses using the formula d:= e&o&p with several extensions described in the study. The formula is easy to learn and covers diagnoses in all medical specialties. The present work succeeded in creating diagnoses from the formula. The fundamental insight is that no matter how complicated a diagnosis is it can be generated by a systematic process, which adds terms one by one. UDS may have implications for medical education and classifications. The formula lays a foundation for structured clinical decision-making. Formulas are hallmarks of hard science. So, d:= e&o&p anticipates a scientific medical revolution.

A multidisciplinary approach to inherited retinal dystrophies from diagnosis to initial care: a narrative review with inputs from clinical practice

BACKGROUND

Non-syndromic inherited retinal dystrophies (IRDs) such as retinitis pigmentosa or Leber congenital amaurosis generally manifest between early childhood and late adolescence, imposing profound long-term impacts as a result of vision impairment or blindness. IRDs are highly heterogeneous, with often overlapping symptoms among different IRDs, and achieving a definite diagnosis is challenging. This narrative review provides a clinical overview of the non-syndromic generalized photoreceptor dystrophies, particularly retinitis pigmentosa and Leber congenital amaurosis. The clinical investigations and genetic testing needed to establish a diagnosis are outlined, and current management approaches are discussed, focusing on the importance of the involvement of an interdisciplinary team from diagnosis and initial care to long-term follow-up and support.

RESULTS

The effective management of IRDs requires a multidisciplinary, and ideally interdisciplinary, team of experts knowledgeable about IRDs, with experienced professionals from fields as diverse as ophthalmology, neuropsychiatry, psychology, neurology, genetics, orthoptics, developmental therapy, typhlology, occupational therapy, otolaryngology, and orientation and mobility specialties. Accurate clinical diagnosis encompasses a range of objective and subjective assessments as a prerequisite for the genetic testing essential in establishing an accurate diagnosis necessary for the effective management of IRDs, particularly in the era of gene therapies. Improvements in genome sequencing techniques, such as next-generation sequencing, have greatly facilitated the complex process of determining IRD-causing gene variants and establishing a molecular diagnosis. Genetic counseling is essential to help the individual and their family understand the condition, the potential risk for offspring, and the implications of a diagnosis on visual prognosis and treatment options. Psychological support for patients and caregivers is important at all stages of diagnosis, care, and rehabilitation and is an essential part of the multidisciplinary approach to managing IRDs. Effective communication throughout is essential, and the patient and caregivers' needs and expectations must be acknowledged and discussed.

CONCLUSION

As IRDs can present at an early age, clinicians need to be aware of the clinical signs suggesting visual impairment and follow up with multidisciplinary support for timely diagnoses to facilitate appropriate therapeutic or rehabilitation intervention to minimize vision loss.

Tau Protein Biosensors in the Diagnosis of Neurodegenerative Diseases

Tau protein plays a crucial role in diagnosing neurodegenerative diseases. However, performing an assay to detect tau protein on a nanoscale is a great challenge for early diagnosis of diseases. Enzyme-linked immunosorbent assay (ELISA), western-blotting, and molecular-based methods, e.g., PCR and real-time PCR, are the most widely used methods for detecting tau protein. These methods are subject to certain limitations: the need for advanced equipment, low sensitivity, and specificity, to name a few. With the above said, it is necessary to discover advanced and novel methods for monitoring tau protein. Counted among remarkable approaches adopted by researchers, biosensors can largely eliminate the difficulties and limitations associated with conventional methods. The main objective of the present study is to review the latest biosensors developed to detect the tau protein. Furthermore, the problems and limitations of conventional diagnosis methods were discussed in detail.

Accuracy of Dengue, Chikungunya, and Zika diagnoses by primary healthcare physicians in Tegucigalpa, Honduras

BACKGROUND

Dengue, Chikungunya, and Zika are co-endemic in Honduras and are often misdiagnosed due to similar clinical and epidemiological behavior. Most arboviral infections reported in primary care are based on clinical diagnoses without laboratory confirmation. Therefore, the accuracy of physicians' diagnoses and the factors that affect them needs to be evaluated.

METHODS

A cross-sectional study with convenience sampling at primary healthcare centers was conducted from June to September 2016 and 2017. Clinical data and dried blood spots on Whatman 903 filter paper from 415 arboviral cases and 248 non-arboviral febrile cases were collected. Viral RNA was extracted from a 6-mm DBS paper disc and confirmed by RT-qPCR and sequencing.

RESULTS

Only 30.84% of diagnostic accuracy was observed in physicians in primary care when comparing arboviral clinical diagnosis with RT-qPCR detection. Moreover, in Dengue and Zika clinical cases, only 8.23% and 27.08% were RT-qPCR confirmed, respectively. No Chikungunya cases were confirmed. In 2017, 20.96% of febrile cases were RT-qPCR confirmed arboviral infections. The symptoms of 45.5% of arboviral cases can fit more than one case definition for arboviruses. The "symptom compliance" and "patient with suspected close contact" were the criteria most utilized by physicians for arboviral diagnosis. The pattern of the epidemiological curves of the arboviral clinical cases didn't match the one of the RT-qPCR confirmed cases.

CONCLUSIONS

Low diagnostic accuracy for overall and individual arboviral infections was observed in physicians. Unspecific symptomatology, overlapping case definitions, and reported close contact to an arboviral patient might contribute to misdiagnosis. Without laboratory confirmation, surveillance data may not reflect the real behavior of these diseases and could impact health interventions.

A case report of brainstem hemorrhage due to Rhizopus delemar-induced encephalitis diagnosed by metagenomic next-generation sequencing (mNGS)

BACKGROUND

Rhizopus delemar is an invasive fungal pathogen that can cause fatal mucormycosis in immunodeficient individuals. Encephalitis caused by R. delemar is rare and difficult to diagnose early. Clinical detection methods for R. delemar include blood fungal culture, direct microscopic examination, and histopathological examination, but the detection is often inadequate for clinical diagnosis and can easily lead to missed diagnosis with delayed treatment.

CASE PRESENTATION

We report a case of a 47-year-old male with brainstem hemorrhage caused by encephalitis due to R. delemar. The patient had a history of hypertension, type 2 diabetes, and irregular medication. No pathogens were detected in cerebrospinal fluid (CSF) and nasopharyngeal secretion cultures. R. delemar was identified by metagenomic next-generation sequencing (mNGS) in CSF, and in combination with the patient's clinical characteristics, encephalitis caused by R. delemar was diagnosed. Antibiotic treatment using amphotericin B liposome in combination with posaconazole was given immediately. However, due to progressive aggravation of the patient's symptoms, he later died due to brainstem hemorrhage after giving up treatment.

CONCLUSIONS

mNGS technique is a potential approach for the early diagnosis of infections, which can help clinicians provide appropriate antibiotic treatments, thus reducing the mortality and disability rate of patients.

NMR-based metabolomics applied to ecotoxicology with zebrafish (Danio rerio) as a prominent model for metabolic profiling and biomarker discovery: Overviewing the most recent approaches

Metabolomics is an innovative approach used in the medical, toxicological, and biological sciences. As an interdisciplinary topic, metabolomics and its relation with the environment and toxicological research are extensive. The use of substances, such as drugs and pesticides, contributes to the continuous releasing of xenobiotics into the environment, harming organisms and their habitats. In this context, fish are important bioindicators of the environmental condition and have often been used as model species. Among them, zebrafish (Danio rerio) presents itself as a versatile and straightforward option due to its unique attributes for research. Zebrafish proves to be a valuable model for toxicity assays and also for metabolomics profiling by analytical tools. Thus, NMR-based metabolomics associated with statistical analysis can reasonably assist researchers in critical factors related to discovering and validating biomarkers through accurate diagnosis. Therefore, this review aimed to report the studies that applied zebrafish as a model for (eco)toxicological assays and essentially utilized NMR-based metabolomics analysis to assess the biochemical profile and thus suggest the potential biological marker.

Test development, optimization and validation of a WGS pipeline for genetic disorders

BACKGROUND

With advances in massive parallel sequencing (MPS) technology, whole-genome sequencing (WGS) has gradually evolved into the first-tier diagnostic test for genetic disorders. However, deployment practice and pipeline testing for clinical WGS are lacking.

METHODS

In this study, we introduced a whole WGS pipeline for genetic disorders, which included the entire process from obtaining a sample to clinical reporting. All samples that underwent WGS were constructed using polymerase chain reaction (PCR)-free library preparation protocols and sequenced on the MGISEQ-2000 platform. Bioinformatics pipelines were developed for the simultaneous detection of various types of variants, including single nucleotide variants (SNVs), insertions and deletions (indels), copy number variants (CNVs) and balanced rearrangements, mitochondrial (MT) variants, and other complex variants such as repeat expansion, pseudogenes and absence of heterozygosity (AOH). A semiautomatic pipeline was developed for the interpretation of potential SNVs and CNVs. Forty-five samples (including 14 positive commercially available samples, 23 laboratory-held positive cell lines and 8 clinical cases) with known variants were used to validate the whole pipeline.

RESULTS

In this study, a whole WGS pipeline for genetic disorders was developed and optimized. Forty-five samples with known variants (6 with SNVs and Indels, 3 with MT variants, 5 with aneuploidies, 1 with triploidy, 23 with CNVs, 5 with balanced rearrangements, 2 with repeat expansions, 1 with AOHs, and 1 with exon 7-8 deletion of SMN1 gene) validated the effectiveness of our pipeline.

CONCLUSIONS

This study has been piloted in test development, optimization, and validation of the WGS pipeline for genetic disorders. A set of best practices were recommended using our pipeline, along with a dataset of positive samples for benchmarking.

Comparison of long-term outcomes of stereotactic body radiotherapy (SBRT) via Helical tomotherapy for early-stage lung cancer with or without pathological proof

BACKGROUND

Stereotactic body radio therapy (SBRT) has emerged as a standard treatment option for nonsurgical candidates with early-stage non-small cell lung cancer (NSCLC). Pathological proof is sometimes difficult to obtain in patients with solitary pulmonary nodules (SPNs). We aimed to compare the clinical outcomes of stereotactic body radiotherapy via helical tomotherapy (HT-SBRT) for early-stage lung cancer patients with or without a pathological diagnosis.

METHODS

Between June 2011 and December 2016, we treated 119 lung cancer patients with HT-SBRT, including 55 with a clinical diagnosis and 64 with a pathological diagnosis. Survival outcomes, including local control (LC), progression-free survival (PFS), cancer-specific survival (CSS), and overall survival (OS), were compared between two cohorts with and without a pathological diagnosis.

RESULTS

The median follow-up for the whole group was 69 months. Patients with a clinical diagnosis were significantly older (p = 0.002). No significant differences were observed between the clinical and pathological diagnosis cohorts in terms of the long-term outcome, with 5-year LC, PFS, CSS, and OS of 87% versus 83% (p = 0.58), 48% versus 45% (p = 0.82), 87% versus 84% (p = 0.65), and 60% versus 63% (p = 0.79), respectively. Recurrence patterns and toxicity were also similar.

CONCLUSIONS

Empiric SBRT appears to be a safe and effective treatment option in a multidisciplinary setting when patients with SPNs highly suggestive of malignancy are unable/refuse to obtain a definitive pathological diagnosis.

Clinical characteristics of cerebral venous sinus thrombosis patients with new-onset of headache

OBJECTIVE

This study aimed to assess the clinical characteristics of cerebral venous sinus thrombosis (CVT) patients with new-onset headache and to identify the risk factors for headache in this population.

METHODS

We retrospectively reviewed the demographic and clinical data of 69 CVT patients recruited between September 2017 and September 2019. Patients were classified into two groups, the headache group and the non-headache group, according to the presence or absence of new-onset headache symptoms at admission. The following characteristics and parameters were measured and analyzed, including gender, age, amount of thromboembolic cerebral venous sinus(ATCVS), and other relevant indicators.

RESULTS

The incidence of headache was 75% in this cohort. The proportion of female patients in the headache group was higher than that in the non-headache group. Patients in the headache group were younger than those without headache. CVT patients of headache group showed higher lymphocyte ratio (LR), blood urea nitrogen (BUN), and intracranial pressure (ICP) compared to the non-headache group, whereas mean corpuscular volume (MCV) and levels of protein (cerebrospinal fluid, CSF) and lactic dehydrogenase (LDH) in CSF were lower in headache patients. The data also revealed younger age and the increased level of chloride ion CI-(CSF) were the risk factors for the occurrence of headache in CVT patients.

CONCLUSION

Age, LR, MCV, BUN levels, ICP, protein (CSF), and LDH (CSF) in patients with headache were significantly different from those in the non-headache group at admission. Younger age and a level of CI- (CSF) were risk factors for headache in CVT patients. These findings may provide guidance for clinical diagnosis and treatment of CVT.

A 30-day follow-up study on the prevalence of SARS-COV-2 genetic markers in wastewater from the residence of COVID-19 patient and comparison with clinical positivity

Wastewater based epidemiology (WBE) is an important tool to fight against COVID-19 as it provides insights into the health status of the targeted population from a small single house to a large municipality in a cost-effective, rapid, and non-invasive way. The implementation of wastewater based surveillance (WBS) could reduce the burden on the public health system, management of pandemics, help to make informed decisions, and protect public health. In this study, a house with COVID-19 patients was targeted for monitoring the prevalence of SARS-CoV-2 genetic markers in wastewater samples (WS) with clinical specimens (CS) for a period of 30 days. RT-qPCR technique was employed to target nonstructural (ORF1ab) and structural-nucleocapsid (N) protein genes of SARS-CoV-2, according to a validated experimental protocol. Physiological, environmental, and biological parameters were also measured following the American Public Health Association (APHA) standard protocols. SARS-CoV-2 viral shedding in wastewater peaked when the highest number of COVID-19 cases were clinically diagnosed. Throughout the study period, 7450 to 23,000 gene copies/1000 mL were detected, where we identified 47 % (57/120) positive samples from WS and 35 % (128/360) from CS. When the COVID-19 patient number was the lowest (2), the highest CT value (39.4; i.e., lowest copy number) was identified from WS. On the other hand, when the COVID-19 patients were the highest (6), the lowest CT value (25.2 i.e., highest copy numbers) was obtained from WS. An advance signal of increased SARS-CoV-2 viral load from the COVID-19 patient was found in WS earlier than in the CS. Using customized primer sets in a traditional PCR approach, we confirmed that all SARS-CoV-2 variants identified in both CS and WS were Delta variants (B.1.617.2). To our knowledge, this is the first follow-up study to determine a temporal relationship between COVID-19 patients and their discharge of SARS-CoV-2 RNA genetic markers in wastewater from a single house including all family members for clinical sampling from a developing country (Bangladesh), where a proper sewage system is lacking. The salient findings of the study indicate that monitoring the genetic markers of the SARS-CoV-2 virus in wastewater could identify COVID-19 cases, which reduces the burden on the public health system during COVID-19 pandemics.

Development and clinical applications of an enclosed automated targeted NGS library preparation system

The rapid development of next-generation sequencing (NGS) technology has promoted its wide clinical application in precision medicine for oncology. However, laborious and time-consuming manual operations, highly skilled personnel requirements, and cross-contamination are major challenges for the clinical implementation of NGS technology-based tests. The Automated NGS Diagnostic Solutions (ANDiS) 500 system is a fully enclosed cassette-dependent automated NGS library preparation system. This platform could produce qualified targeted amplicon library in three steps with only 15 min of hands-on time. Rigorous cross-contamination test using simulated contaminant plasmids confirmed that the design of disposable cassette guarantees zero sample cross-contamination. The BRCA1 and BRCA2 mutation detection panel and gastrointestinal cancer-related gene analysis panel for the ANDiS 500 platform showed 100% accuracy and precision in detecting germ-line mutations and somatic mutations respectively. Furthermore, those panels showed 100% concordance with verified methods in a prospective cohort study enrolling 363 patients and a cohort of 45 pan-cancer samples. In conclusion, the ANDiS 500 automated platform could overcome major challenges for implementing NGS assays clinically and is eligible for routine clinical tests.

SERS-based antibiotic susceptibility testing: Towards point-of-care clinical diagnosis

Emerging antibiotic resistant bacteria constitute one of the biggest threats to public health. Surface-enhanced Raman scattering (SERS) is highly promising for detecting such bacteria and for antibiotic susceptibility testing (AST). SERS is fast, non-destructive (can probe living cells) and it is technologically flexible (readily integrated with robotics and machine learning algorithms). However, in order to integrate into efficient point-of-care (PoC) devices and to effectively replace the current culture-based methods, it needs to overcome the challenges of reliability, cost and complexity. Recently, significant progress has been made with the emergence of both new questions and new promising directions of research and technological development. This article brings together insights from several representative SERS-based AST studies and approaches oriented towards clinical PoC biosensing. It aims to serve as a reference source that can guide progress towards PoC routines for identifying antibiotic resistant pathogens. In turn, such identification would help to trace the origin of sporadic infections, in order to prevent outbreaks and to design effective medical treatment and preventive procedures.

Comparison of clinician diagnosis of COVID-19 with real time polymerase chain reaction in an adult-representative population in Sweden

BACKGROUND

Due to the high transmissibility of SARS-CoV-2, accurate diagnosis is essential for effective infection control, but the gold standard, real-time reverse transcriptase-polymerase chain reaction (RT-PCR), is costly, slow, and test capacity has at times been insufficient. We compared the accuracy of clinician diagnosis of COVID-19 against RT-PCR in a general adult population.

METHODS

COVID-19 diagnosis data by 30th September 2021 for participants in an ongoing population-based cohort study of adults in Western Sweden were retrieved from registers, based on positive RT-PCR and clinician diagnosis using recommended ICD-10 codes. We calculated accuracy measures of clinician diagnosis using RT-PCR as reference for all subjects and stratified by age, gender, BMI, and comorbidity collected pre-COVID-19.

RESULTS

Of 42,621 subjects, 3,936 (9.2%) and 5705 (13.4%) had had COVID-19 identified by RT-PCR and clinician diagnosis, respectively. Sensitivity and specificity of clinician diagnosis against RT-PCR were 78% (95%CI 77-80%) and 93% (95%CI 93-93%), respectively. Positive predictive value (PPV) was 54% (95%CI 53-55%), while negative predictive value (NPV) was 98% (95%CI 98-98%) and Youden's index 71% (95%CI 70-72%). These estimates were similar between men and women, across age groups, BMI categories, and between patients with and without asthma. However, while specificity, NPV, and Youden's index were similar between patients with and without chronic obstructive pulmonary disease (COPD), sensitivity was slightly higher in patients with (84% [95%CI 74-90%]) than those without (78% [95%CI 77-79%]) COPD.

CONCLUSIONS

The accuracy of clinician diagnosis for COVID-19 is adequate, regardless of gender, age, BMI, and asthma, and thus can be used for screening purposes to supplement RT-PCR.

Comparison of clinical characteristics and outcome measures of PCR-positive and PCR-negative patients diagnosed as COVID-19: Analyses focusing on the older adults

PURPOSE

While the definitive diagnosis of COVID-19 relies on PCR confirmation of the virus, the sensitivity of this technique is limited. The clinicians had to go on with the clinical diagnosis of COVID-19 in selected cases. We aimed to compare PCR-positive and PCR-negative patients diagnosed as COVID-19 with a specific focus on older adults.

METHODS

We studied 601 hospitalized adults. The demographics, co-morbidities, triage clinical, laboratory characteristics, and outcomes were noted. Differences between the PCR (+) and (-) cases were analyzed. An additional specific analysis focusing on older adults (≥65 years) (n = 184) was performed.

RESULTS

The PCR confirmation was present in 359 (59.7 %). There was not any difference in terms of age, sex, travel/contact history, hospitalization duration, ICU need, the time between first symptom/hospitalization to ICU need, ICU days, or survival between PCR-positive and negative cases in the total study group and older adults subgroup. The only symptoms that were different in prevalence between PCR-confirmed and unconfirmed cases were fever (73.3 % vs. 64 %, p = 0.02) and fatigue/myalgia (91.1 % vs. 79.3 %, p = 0.001). Bilateral diffuse pneumonia was also more prevalent in PCR-confirmed cases (20 % vs. 13.3 %, p = 0.03). In older adults, the PCR (-) cases had more prevalent dyspnea (72.2 % vs. 51.4 %, p = 0.004), less prevalent fatigue/myalgia (70.9 % vs. 88.6 %, p = 0.002).

CONCLUSION

The PCR (+) and (-) cases displayed very similar disease phenotypes, courses, and outcomes with few differences between each other. The presence of some worse laboratory findings may indicate a worse immune protective response in PCR (-) cases.

Effect of comorbid ADHD on mortality in women with borderline personality disorder

BACKGROUND

Many similarities exist between borderline personality disorder (BPD) and attention-deficit/hyperactivity disorder (ADHD), more so in women than in men. People with comorbid ADHD and BPD represent a subgroup of BPD patients with distinct symptom expression and, consequently, a different prognosis. We used Swedish national high quality registers to assess whether such comorbidity is related to increased mortality risk. The study focused on women with BPD because they are more likely than men to be clinically diagnosed with BPD and present a higher mortality risk, especially for unnatural causes of death, including suicide.

FINDINGS

In a cohort of 15 847 women diagnosed with BPD a subsequent clinical diagnosis of ADHD did not influence the overall risk of mortality, including suicide.

CONCLUSIONS

Women with comorbid ADHD and BPD have a similar mortality risk as those only diagnosed with BPD.

Concatenated Xception-ResNet50 - A novel hybrid approach for accurate skin cancer prediction

Skin cancer is a malignant disease that affects millions of people around the world every year. It is an invasive disease characterised by an abnormal proliferation of skin cells in the body that multiply and spread through the lymph nodes, killing the surrounding tissue. The number of skin cancer cases is on the rise due to lifestyle changes and sun-seeking behaviour. As skin cancer is a deadly disease, early diagnosis and grading are crucial to save lives. In this work, state-of-the-art AI approaches are applied to develop a unique deep learning model that integrates Xception and ResNet50. This network achieves maximum accuracy by combining the properties of two robust networks. The proposed concatenated Xception-ResNet50 (X-R50) model can classify skin tumours as basal cell carcinoma, melanoma, melanocytic nevi, dermatofibroma, actinic keratoses and intraepithelial carcinoma, vascular and non-cancerous benign keratosis-like lesions. The performance of the proposed method is compared with a DeepCNN and other state-of-the-art transfer learning models. The Human Against Machine (HAM10000) dataset assesses the suggested method's performance. For this study, 10,500 skin images were used. The model is trained and tested with the sliding window technique. The proposed concatenated X-R50 model is cutting-edge, with a 97.8% prediction accuracy. The performance of the model is also validated by a statistical hypothesis test using analysis of variance (ANOVA). The reported approach is both accurate and efficient and can help dermatologists and clinicians detect skin cancer at an early stage of the clinical process.