Clinical Diagnostic Tool Research Articles

Simple and sensitive detection of miRNA-122 based on a micro-biosensor through square wave voltammetry.

The simple and sensitive detection of miRNA-122 in blood is crucially important for early hepatocellular carcinoma (HCC) diagnosis. In this work, a platinum microelectrode (PtμE) was prepared and electrodeposited with molybdenum disulfide (MoS2) and gold nanoparticles (AuNP), respectively, and denoted as PtμE/MoS2/Au. The prepared PtμE/MoS2/Au was used as the microsensor for the detection of miRNA-122 combined with the probe DNA as a biorecognition element which is the complementary strand of miRNA-122. The PtμE/MoS2/Au conjugated with the probe DNA modified with sulfydryl units was used as the micro-biosensor for the detection of miRNA-122. The square wave voltammetry was performed for the quantitative detection of miRNA-122 using [Fe(CN)6]4-/3- as a mediator. Under the optimized conditions, the PtμE/MoS2/Au micro-biosensor shows a linear detection toward miRNA-122 ranging from 10-11 to 10-8 M (S = 6.9 nA dec-1, R2 = 0.9997), and the detection limit is 1.6 × 10-12 M (3σ/b). The PtμE/MoS2/Au micro-biosensor demonstrates good selectivity against other types of proteins and small molecules, and has good reproducibility. Moreover, the PtμE/MoS2/Au micro-biosensor was successfully applied for the measurement of miRNA-122 in real blood samples. Herein, the proposed detection assay could be a potential tool in HCC clinical diagnostics with high sensitivity.

Application of artificial intelligence in endoscopic gastrointestinal tumors.

With an increasing number of patients with gastrointestinal cancer, effective and accurate early diagnostic clinical tools are required provide better health care for patients with gastrointestinal cancer. Recent studies have shown that artificial intelligence (AI) plays an important role in the diagnosis and treatment of patients with gastrointestinal tumors, which not only improves the efficiency of early tumor screening, but also significantly improves the survival rate of patients after treatment. With the aid of efficient learning and judgment abilities of AI, endoscopists can improve the accuracy of diagnosis and treatment through endoscopy and avoid incorrect descriptions or judgments of gastrointestinal lesions. The present article provides an overview of the application status of various artificial intelligence in gastric and colorectal cancers in recent years, and the direction of future research and clinical practice is clarified from a clinical perspective to provide a comprehensive theoretical basis for AI as a promising diagnostic and therapeutic tool for gastrointestinal cancer.

Chapter 6: Diagnostic Considerations regarding Coronal Caries.

This chapter considers the main principles guiding diagnosis of the disease dental caries in clinical practice by means of clinical examination and radiographs as adjunct method. Dental professionals have been trained to diagnose caries disease by assessing clinical symptoms and signs of caries lesions complemented by radiographic examination as an adjunct method. Clinical examination is the foundation of the diagnosis and should be performed after removal of dental biofilm of tooth surfaces, air-drying, and under good illumination. Clinical diagnostic methods categorize caries lesions according to their severity and in some methods according to their activity. Caries lesion activity has been determined by surface reflection and texture. The detection of thick or heavy biofilm on tooth surfaces is an additional diagnostic clinical tool to estimate caries lesion activity. Patients with no caries experience, that is, without clinical and/or radiographic signs of caries lesions in the dentition, are considered caries inactive. Other caries-inactive patients may present inactive caries lesions/restorations in their dentition. In contrast, patients are considered caries active when presenting any active caries lesion at clinical level and/or any progressing lesion as demonstrated by at least two bitewing radiographs taken at different points in time. The main concern about caries-active patients is that caries lesions are likely to progress unless effective measures are implemented to interfere with its progression. Prescribed according to individual needs, bitewing radiographs provide additional information for clinical examination in the detection of approximal enamel and outer third dentine lesions that can be inactivated by nonoperative treatment.

Upper Gastrointestinal Tract Video Capsule as an Alternative to Oesophago-Gastro-Duodenoscopy in Clinical Practice

Introduction. Upper gastrointestinal (UGI) video capsule endoscopy (VCE) provides a possible alternative to conventional oesophago-gastro-duodenoscopy (OGD). In Ireland, the COVID-19 pandemic led to unprecedented change in endoscopy services, accelerating the need for UGI VCE to help reduce patient exposure but allow the continuation of endoscopy services. We report on using UGI VCE as an alternative to OGD throughout all phases of COVID-related endoscopy adjustments. Aims/Background. Prospective observational study to assess identification of relevant UGI anatomical landmarks on UGI VCE as defined in the British Society of Gastroenterology. Method. Inclusion criteria were: patients with dyspepsia under 40 years of age with no alarm symptoms; known cirrhosis for variceal screening; UGI bleeds with the Blatchford score ≤ 2 . A protocol for preparation and a series of positional movements were adapted for the procedure. Landmarks and pathology detection were evaluated by two independent endoscopists. Results. 127 UGI VCE was performed from June 2020 to December 2021, of which 22 required further evaluation with OGD. The most common indications were dyspepsia and abdominal pain, 71% and 19%, respectively. With the use of the dual-facing camera, clear views of the OGJ in 100% of cases, cardia 100%, fundus 97%, greater curve 99%, lesser curve 98%, incisura angularis 95%, antrum 95%, pylorus 94%, D1/bulb 83%, and D2 82% were obtained. The main findings at UGI VCE were reflux oesophagitis and gastritis, with normal mucosa observed in 48% of cases. Findings suggesting a neoplastic lesion at the OG junction were detected in 1 case. Conclusion. Since June 2020, 81% ( N = 103 ) of a selected cohort of patients referred for UGI endoscopy avoided invasive traditional endoscopy and were successfully managed by VCE, thus reducing endoscopy waiting lists. UGI VCE may serve as a clinical diagnostic tool, used alongside OGD in appropriate cases, to help improve patient services and care delivery.

322. Clinical-Grade Metagenomics in Urinary Tract Infections: Improving Performance of Next-Generation Sequencing Assays Using Internal Controls and Machine Learning

Abstract Background Shotgun sequencing-based metagenomics is a useful approach to profiling microbiomes in environmental and patient samples. In a clinical setting, metagenomic techniques have the advantage of identifying organisms, which cannot be readily cultured or confirmed by other techniques. We have developed a clinical-grade, streamlined metagenomics-based pipeline that includes regulatory compliant method considerations, such as an internal control followed by a machine-based learning (ML) process to identify pathogens in urine samples. Methods We built an optimized novel end-to-end NGS assay pipeline that harnesses pathogen-specific genome data to detect bacterial species. We processed de-identified clinical urine specimens, collected from patients symptomatic for urinary tract infection (UTI). This workflow includes an IPC, QIACube-MDx extraction, library preparation and Illumina NextSeq 550 sequencing and a novel interpretable ML based analytic approach, Biotia-DX. Clinical culture results and qPCR were used as a baseline for the assay to train the ML model and to establish accuracy relative to the clinical standard of care. Results We clinically validated over 40 key uropathogens and conducted clinical studies of specificity, intra/inter reproducibility, accuracy in urine specimens (n=300), and limit of detection in E. coli, K. pneumoniae, P. mirabilis, S. aureus, E. faecalis and Candida. Additionally, the implementation of an internal control coupled with our Biotia-DX software provides an accurate (F1 score 94.3%) and highly sensitive clinical grade diagnostic tool. Conclusion Urine has historically presented a challenge for diagnostics via culturing, with a high rate of culture-negative results (∼30% on average). We improved the clinical utility of an NGS urine assay by leveraging an IPC and ML software. This decreased the rate of false positive species called in a sample relative to other NGS techniques and allows for greater sensitivity and taxonomic specificity. This assay may be especially useful for low colony-count or negative-culture samples to diagnose and guide patient treatment. Disclosures Mara Couto-Rodriguez, MS, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company David C. Danko, PhD, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company Xavier O. Jirau Serrano, MS, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company Taylor Paisie, MS, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company John C. Papciak, BS, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company Eszter Szollosi, BS, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company Christopher E. Mason, PhD, Biotia Inc.: Advisor/Consultant|Biotia Inc.: Board Member|Biotia Inc.: Ownership Interest Caitlin Otto, PhD, D(ABMM), Biotia Inc.: Advisor/Consultant Niamh B. O'Hara, PhD, Biotia Inc.: Board Member|Biotia Inc.: Ownership Interest Dorottya Nagy-Szakal, MD PhD, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company|Biotia Inc.: Stocks/Bonds.

A Microfluidic Platform with an Embedded Miniaturized Electrochemical Sensor for On-Chip Plasma Extraction Followed by In Situ High-Sensitivity C-Reactive Protein (hs-CRP) Detection.

Blood testing is a clinical diagnostic tool to evaluate physiological conditions, the immune system response, or the presence of infection from whole blood samples. Although conventional blood testing can provide rich biological information, it usually requires complicated and tedious whole blood processing steps operated by benchtop instruments and well-experienced technicians, limiting its usage in point-of-care (POC) settings. To address the above problems, we propose a microfluidic platform for on-chip plasma extraction directly from whole blood and in situ biomarker detection. Herein, we chose C-reactive protein (CRP) as the target biomarker, which can be used to predict fatal cardiovascular disease (CVD) events such as heart attacks and strokes. To achieve a rapid, undiluted, and high-purity on-chip plasma extraction, we combined two whole blood processing methods: (1) anti-D immunoglobulin-assisted sedimentation, and (2) membrane filtration. To perform in situ CRP detection, we fabricated a three-dimensional (3D) microchannel with an embedded electrochemical (EC) sensor, which has a modular design to attach the blood collector and buffer reservoir with standard Luer connectors. As a proof of concept, we first confirmed that the dual plasma extraction design achieved the same purity level as the standard centrifugation method with smaller sample (100 µL of plasma extracted from 400 µL of whole blood) and time (7 min) requirements. Next, we validated the functionalization protocol of the EC sensor, followed by evaluating the detection of CRP spiked in plasma and whole blood. Our microfluidic platform performed on-chip plasma extraction directly from whole blood and in situ CRP detection at a 0.1-10 μg/mL concentration range, covering the CVD risk evaluation level of the high-sensitivity CRP (hs-CRP) test. Based on the above features, we believe that this platform constitutes a flexible way to integrate the processing of complex samples with accurate biomarker detection in a sample-to-answer POC platform, which can be applied in CVD risk monitoring under critical clinical situations.

Does childhood chemotherapy affect mandibular bone structures in a lifetime?

Chemotherapy, one of the most important treatment modalities for treating childhood cancers, is a major cause of bone loss in patients and survivors. This study aimed to evaluate mandibular bone structures in childhood cancer survivors (CCSs) by means of fractal dimension (FD) analysis and the Klemetti index (KI), and to compare them with regard to the control group. In this retrospective study, the panoramic radiographs of 49 CCSs were included as the study group and the panoramic radiographs of 49 cancer-free volunteers were included as the control group. Based on the panoramic radiographs, FD and KI were determined. No significant differences were observed between the study and control groups in terms of mean FD values for regions of interest (ROIs) ROI_1, ROI_2 and ROI_3 (p = 0.750, p = 0.490 and p = 0.910, respectively). The mean FD values for ROI_1 for the study and control groups were 1.08 ±0.18 and 1.07 ±0.14, respectively. The mean FD values for ROI_2 for the study and control groups were 1.11 ±0.13 and 1.09 ±0.13, respectively. The mean FD values for ROI_3 for the study and control groups were 1.15 ±0.14 and 1.15 ±0.15, respectively. Statistically significant differences between the study and control groups were noted only in the distribution of the KI categories (p = 0.015). Childhood chemotherapy may affect mandibular bone structures during a lifetime. The Klemetti index should be considered a useful clinical diagnostic tool for the examination of mandibular bone structures.

Activatable Small Molecule Probes for Photoacoustic Imaging: Dyes and Applications.

Photoacoustic imaging (PAI) is a non-invasive modality for molecular imaging and is on the way to becoming a routine clinical diagnostic tool. The advantage of PAI over many other currently used modalities is its ability to potentially image in vivo a variety of enzymatic and physiological processes as well as metabolites in real time at high tissue depths. For this purpose, photoacoustic signal generating chromophores, which have the ability to change their signal characteristics upon reaction, to their environments or trapping reactive species, are important. This review article provides an overview of the concepts for activatable small molecule probes for photoacoustic imaging, highlights the requirements for structural and optical properties, and describes their responses to the selective triggers.

Highly Sensitive and Selective Detection of Melatonin in Biofluids by Antipyrine Based Fluorophore.

A simple fluorescent based organic fluorophore was synthesized and it shows significant fluorescent intensity with melatonin (MLN). Hence, it was applicable to the detection of MLN by colorimetric and fluorimetric techniques at neutral pH. Under optimized experimental condition, the synthesized organic fluorophore detects MLN selectively in the presence of other interfering biomolecules through ICT mechanism. The melatonin sensing mechanism is supported by DFT and 1H-NMR titration. Based on the findings, this method can be applied to design a simple clinical diagnostic tool for MLN.

Tumour catabolism independent of malnutrition and inflammation in upper GI cancer patients revealed by longitudinal metabolomics.

The detrimental impact of malnutrition and cachexia in cancer patients subjected to surgical resection is well established. However, how systemic and local metabolic alterations in cancer patients impact the serum metabolite signature, thereby leading to cancer-specific differences, is poorly defined. In order to implement metabolomics as a potential tool in clinical diagnostics and disease follow-up, targeted metabolite profiling based on quantitative measurements is essential. We hypothesized that the quantitative metabolic profile assessed by 1 H nuclear magnetic resonance (NMR) spectroscopy can be used to identify cancer-induced catabolism and potentially distinguish between specific tumour entities. Importantly, to prove tumour dependency and assess metabolic normalization, we additionally analysed the metabolome of patients' sera longitudinally post-surgery in order to assess metabolic normalization. Forty two metabolites in sera of patients with tumour entities known to cause malnutrition and cachexia, namely, upper gastrointestinal cancer and pancreatic cancer, as well as sera of healthy controls, were quantified by 1 H NMR spectroscopy. Comparing serum metabolites of patients with gastrointestinal cancer with healthy controls and pancreatic cancer patients, we identified at least 15 significantly changed metabolites in each comparison. Principal component and pathway analysis tools showed a catabolic signature in preoperative upper gastrointestinal cancer patients. The most specifically upregulated metabolite group in gastrointestinal cancer patients was ketone bodies (3-hydroxybutyrate, P<0.0001; acetoacetate, P<0.0001; acetone, P<0.0001; false discovery rate [FDR] adjusted). Increased glycerol levels (P<0.0001), increased concentration of the ketogenic amino acid lysine (P=0.03) and a significant correlation of 3-hydroxybutyrate levels with branched-chained amino acids (leucine, P=0.02; isoleucine, P=0.04 [FDR adjusted]) suggested that ketone body synthesis was driven by lipolysis and amino acid breakdown. Interestingly, the catabolic signature was independent of the body mass index, clinically assessed malnutrition using the nutritional risk screening score, and systemic inflammation assessed by CRP and leukocyte count. Longitudinal measurements and principal component analyses revealed a quick normalization of key metabolic alterations seven days post-surgery, including ketosis. Together, the quantitative metabolic profile obtained by 1 H NMR spectroscopy identified a tumour-induced catabolic signature specific to upper gastrointestinal cancer patients and enabled monitoring restoration of metabolic homeostasis after surgery. This approach was critical to identify the obtained metabolic profile as an upper gastrointestinal cancer-specific signature independent of malnutrition and inflammation.

Exhaled breath condensate as bioanalyte: from collection considerations to biomarker sensing.

Since the SARS-CoV-2 pandemic, the potential of exhaled breath (EB) to provide valuable information and insight into the health status of a person has been revisited. Mass spectrometry (MS) has gained increasing attention as a powerful analytical tool for clinical diagnostics of exhaled breath aerosols (EBA) and exhaled breath condensates (EBC) due to its high sensitivity and specificity. Although MS will continue to play an important role in biomarker discovery in EB, its use in clinical setting is rather limited. EB analysis is moving toward online sampling with portable, room temperature operable, and inexpensive point-of-care devices capable of real-time measurements. This transition is happening due to the availability of highly performing biosensors and the use of wearable EB collection tools, mostly in the form of face masks. This feature article will outline the last developments in the field, notably the novel ways of EBA and EBC collection and the analytical aspects of the collected samples. The inherit non-invasive character of the sample collection approach might open new doors for efficient ways for a fast, non-invasive, and better diagnosis.

Development of an improved diagnostic nomogram for preoperative prediction of small cell neuroendocrine cancer of the cervix.

Accurate preoperative diagnosis of small cell neuroendocrine cancer of the cervix (SCNECC) is crucial for establishing the best treatment plan. This study aimed to develop an improved, non-invasive method for the preoperative diagnosis of SCNECC by integrating clinical, MR morphological, and apparent diffusion coefficient (ADC) information. A total of 105 pathologically confirmed cervical cancer patients (35 SCNECC, 70 non-SCNECC) from multiple centres with complete clinical and MR records were included. Whole lesion histogram analysis of the ADC was performed. Multivariate logistic regression analysis was used to develop diagnostic models based on clinical, morphological, and histogram data. The predictive performance in terms of discrimination, calibration, and clinical usefulness of the different models was assessed. A nomogram for preoperatively discriminating SCNECC was developed from the combined model. In preoperative SCNECC diagnosis, the combined model, which had a diagnostic AUC (area under the curve) of 0.937 (95% CI: 0.887-0.987), outperformed the clinical-morphological model, which had an AUC of 0.869 (CI: 0.788-0.949), and the histogram model, which had an AUC of 0.872 (CI: 0.792-0.951). The calibration curve and decision curve analyses suggest that the combined model achieved good fitting and clinical utility. Non-invasive preoperative diagnosis of SCNECC can be achieved with high accuracy by integrating clinical, MR morphological, and ADC histogram features. The nomogram derived from the combined model can provide an easy-to-use clinical preoperative diagnostic tool for SCNECC. It is clear that the therapeutic strategies for SCNECC are different from those for other pathological types of cervical cancer according to V 1.2021 of the NCCN clinical practice guidelines in oncology for cervical cancer. This research developed an improved, non-invasive method for the preoperative diagnosis of SCNECC by integrating clinical, MR morphological, and apparent diffusion coefficient (ADC) information.

Characterization of intra-tissue strain fields in articular cartilage explants during post-loading recovery using high frequency ultrasound

This study aims to demonstrate the potential of ultrasound elastography as a research tool for non-destructive imaging of intra-tissue strain fields and tissue quality assessment in cartilage explants. Osteochondral plugs from bovine patellae were loaded up to 10, 40, or 70 N using a hemi-spherical indenter. The load was kept constant for 15 min, after which samples were unloaded and ultrasound imaging of strain recovery over time was performed in the indented area for 1 h. Tissue strains were determined using speckle tracking and accumulated to LaGrangian strains in the indentation direction. For all samples, strain maps showed a heterogeneous strain field, with the highest values in the superficial cartilage under the indenter tip at the bottom of the indent and decreasing values in the deeper cartilage. Strains were higher at higher load levels and tissue recovery over time was faster after indentation at 10 N than at 40 N and 70 N. At lower compression levels most displacement occurred near the surface with little deformation in the deep layers, while at higher levels strains increased more evenly in all cartilage zones. Ultrasound elastography is a promising method for high resolution imaging of intra-tissue strain fields and evaluation of cartilage quality in tissue explants in a laboratory setting. In the future, it may become a clinical diagnostic tool used to identify the extent of cartilage damage around visible defects.

Predicting Adenomyosis Diagnosis Based on MRI

<h3>Study Objective</h3> Development of a prediction tool for histopathological adenomyosis diagnosis after hysterectomy based on MRI and clinical parameters. <h3>Design</h3> Single-centre retrospective cohort study. <h3>Setting</h3> Gynaecological department of regional referral hospital from 2007-2022. <h3>Patients or Participants</h3> 296 women undergoing a hysterectomy for benign pathology with preoperative pelvic MRI. <h3>Interventions</h3> MRI's were retrospectively re-assessed for all possible adenomyosis markers (junctional zone (JZ) parameters, high signal intensity foci (HSI foci), uterine size) in a blinded fashion by two researchers. Sensitivity, specificity, positive predictive value, negative predictive value, diagnostic accuracy, and odds ratio (dOR) were calculated. Threshold values of continuous variables were investigated using Receiver Operator Characteristics (ROC) curves and Area Under the Curve (AUC). A multivariate regression model for histopathological adenomyosis diagnosis was developed based on selection of MRI and clinical variables from univariate analysis with p>0.10 and factors determined to be of clinical importance. <h3>Measurements and Main Results</h3> 131 women (44.3%) had histopathological adenomyosis. In univariate analysis, patients had comparable age at hysterectomy, BMI and clinical symptoms, p>0.05. Patients with adenomyosis had more often undergone a curettage (221% vs. 8.9%, p=0.002), and had a higher mean JZ (9.35mm vs. 8.00, p=0.001), maximal JZ (15.05mm vs. 12.45mm, p=0.002), mean JZ to myometrium ratio (0.53 vs. 0.48 p=0.009) and JZ differential (8.45mm vs, 6.75mm, p=0.009). Presence of HSI foci on MRI was quasi-pathognomic for adenomyosis diagnosis (25.5% vs. 2.4%, p<0.001). A predictive model based on the parameters of: Age at MRI, History of Curettage, Dysmenorrhoea, Hypermenorrhoea, Mean JZ, JZ differential, JZ/Myometrium ratio, Presence of HSI Foci was created, with a good AUC of 0.761. <h3>Conclusion</h3> This is the first study to create a clinical diagnostic tool based on a combination of MRI and clinical parameters for adenomyosis diagnosis. As preoperative imaging-based diagnosis of adenomyosis remains challenging, this model, after sufficient external validation, could function to become a useful clinical-decision making tool in women with suspected adenomyosis.

Serum metabolome alterations in patients with early nonalcoholic fatty liver disease.

Background: Although metabolomic analysis for patients with nonalcoholic fatty liver disease (NAFLD) was a promising approach to identify novel biomarkers as targets for the diagnosis of NAFLD, the serum metabolomics profile of early-stage NAFLD patients from central China remain unknown. Objective: The aim of the present study was to explore the metabolic characteristics of patients with early-stage NAFLD based on the ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) technology, to identify differential metabolites and perform functional analysis, and especially, to establish a novel early NAFLD clinical diagnostic tool. Results: Compared with healthy controls, serum metabolite species increased significantly in early stage NAFLD patients. Expression of 88 metabolites including 1-naphthylmethanol, rosavin, and theophylline were up-regulated in early NAFLD, while 68 metabolites including 2-hydroxyphenylacetic acid and lysophosphatidylcholine (24:1(15Z)) were down-regulated. The early NAFLD classifier achieved a strong diagnostic efficiency in the discovery phases (80.99%) and was successfully verified in the validation phases (75.23%). Conclusions: These results advance our understanding about the composition and biological functions of serum metabolites of early NAFLD. In addition, serum metabolic markers can serve as an efficient diagnostic tool for the early-stage NAFLD.

A thin metallo-dielectric stacked metamaterial as “add-on” for magnetic field enhancement in clinical MRI

Magnetic resonance imaging (MRI) is a widely used clinical diagnostic tool, which is based on the principle of nuclear magnetic resonance of hydrogen atoms in human body. The Larmor frequency of precession of the hydrogen atoms is determined by the strength of static magnetic field ( B0) of MRI. A higher B0 can directly improve signal-to-noise ratio (SNR) of MRI. However, this method involves expensive hardware installation, which could have adverse effects of tissue-heating and make MRI unsafe for patients with medical implants. Hence, efforts have been made to increase the SNR of MRI without increasing B0. An effective solution in this direction would be to boost the radiofrequency (RF) magnetic fields emitted by the body part undergoing scan, particularly by using metamaterials. The higher the received RF signal strength, the greater the SNR of MRI. For a metamaterial to be used as an “add-on” in commercial scanners, its dimensions need to be designed appropriately so that it fits in the available gap between the transceiver coil and the human body. In this article, a 10-mm-thick metallo-dielectric metamaterial is designed by a stacking of alternate square-shaped capacitive patches and inductive apertures for enhancing the RF magnetic flux density and hence, the SNR of a 1.5 T MRI system. The inter-layer electromagnetic coupling in the stacked structure is deployed for spatial localization of magnetic fields at the resonant frequency (∼64 MHz) which is equal to the Larmor frequency of 1.5 T MRI. An equivalent circuit model, comprising a lumped-element third order bandpass filter, validated the transmissivity characteristics of the metamaterial obtained using full-wave simulations. Magnetic flux density enhancement by a factor of 55 is obtained when the metamaterial add-on is placed between a surface coil and a bio-model of human head.

Determination of phage susceptibility as a clinical diagnostic tool: A routine perspective

As the global burden of disease caused by multidrug resistant bacteria is a major source of concern, credible clinical alternatives to antibiotic therapy, such as personalized phage therapy, are actively explored. Although phage therapy has been used for more than a century, the issue of an easy to implement diagnostic tool for determining phage susceptibility that meets current routine clinical needs is still open. In this Review, we summarize the existing methods used for determining phage activity on bacteria, including the three reference methods: the spot test, the double agar overlay plaque assay, and the Appelmans method. The first two methods rely on the principle of challenging the overnight growth of a lawn of bacteria in an agar matrix to a known relative phage to bacteria concentration and represent good screening tools to determine if the tested phage can be used for a “passive” and or “active” treatment. Beside these methods, several techniques, based on “real-time” growth kinetics assays (GKA) have been developed or are under development. They all monitor the growth of clinical isolates in the presence of phages, but use various detection methods, from classical optical density to more sophisticated techniques such as computer-assisted imagery, flow-cytometry, quantitative real-time polymerase chain reaction (qPCR) or metabolic indicators. Practical considerations as well as information provided about phage activity are reviewed for each technique. Finally, we also discuss the analytical and interpretative requirements for the implementation of a phage susceptibility testing tool in routine clinical microbiology.

Droplet digital PCR as a first-tier molecular diagnostic tool for focal cortical dysplasia type II.

We read with interest the recent article by Pirozzi et al.1 demonstrating the utility of droplet digital PCR (ddPCR) for the molecular genetic diagnosis of focal malformations of cortical development (FMCD) including focal cortical dysplasia (FCD), hemimegalencephaly (HMEG) and dysplastic megalencephaly (DMEG). By targeting six recurrent variants in MTOR, PIK3CA and AKT3, Pirozzi et al.1 achieved a diagnostic rate of 24.2% for FCD (8 of 33 individuals) and 81.8% for HMEG/DMEG (9 of 11 individuals). Our research lab has also implemented a similar strategy to rapidly screen for recurrent variants in FCD samples, with favourable outcomes. As a result, ddPCR has become a routine research genetic testing method for FCD samples collected from the Epilepsy Surgery Program at the Royal Children’s Hospital, Melbourne. The purpose of this letter is to provide supporting evidence for the article by Pirozzi et al.,1 and to advocate for the implementation of ddPCR as a first-tier molecular diagnostic tool for FMCD, particularly FCD Type II (FCDII). We present the research findings generated at the Royal Children’s Hospital, Melbourne, and discuss how this approach can be further improved and utilized as a research or clinical grade diagnostic tool.

Cooperative strand displacement circuit with dual-toehold and bulge-loop structure for single-nucleotide variations discrimination

Nucleic acid nanotechnologies based on toehold-mediated strand displacement are ideally suited for single-nucleotide variations (SNVs) detection. But only a limited number of means could be used to construct selective hybridization probes via finely designed toehold and regulation of branching migration. Herein, we present a cooperative hybridization strategy relying on a dual-toehold and bulge-loop (DT&BL) probe, coupled with the strand displacement catalytic (SDC) cycle to identify SNVs. The dual-toehold can simultaneously hybridize the 5′ and 3′ ends of the target, so that it possessed the mutual correction function for improving the specificity in comparison with the single target-binding domain. Insertion of BLs into the dual-toehold probe allows tuning of Gibbs free energy change (ΔG) and control of the reaction rate during branching migration. Using the SDC cycle, the reactivity and selectivity of the DT&BL probe were increased drastically without elaborate competitive sequences. The feasibilities of this platform were demonstrated by the identification of three cancer-related genes. Moreover, the applicability of this biosensor to detect clinical samples showed satisfactory accuracy and reliability. We envision it would offer a new perspective for the construction of highly specific probes based on dynamic DNA nanotechnology, and serves as a promising tool for clinical diagnostics.

Construction and verification of a nomogram prediction model of severe adult community-acquired pneumonia

To construct and verify the nomogram prediction model based on inflammatory indicators, underlying diseases, etiology and the British Thoracic Society modified pneumonia score (CURB-65 score) in adults with severe community acquired pneumonia (CAP). The clinical data of 172 adult inpatients first diagnosed as CAP at Taikang Xianlin Drum Tower Hospital from January 2018 to December 2021 were divided into severe and non-severe diseases groups according to the severity of their conditions. The baseline conditions (including gender, age, past history, comorbidities and family history), clinical data (including chief symptoms, onset time, CURB-65 score), first laboratory results on admission (including whole blood cell count, liver and kidney function, blood biochemistry, coagulation function, microbiological culture results) and whether the antimicrobial therapy was adjusted according to the microbiological culture results were recorded in both groups. Univariate analysis was used to screen for differential indicators between severe and non-severe patients. After covariate analysis, multi-factor Logistic regression analysis was performed based on the Aakaike information criterion (AIC) forward stepwise regression method to rigorously search for risk factors for constructing the model. Based on the results of the multi-factor analysis, a nomogram prediction model was constructed, and the discriminatory degree and calibration degree of the model were assessed using the receiver operator characteristic curve (ROC curve) and calibration curve. A total of 172 adult CAP patients were included, 48 in severe group and 124 in non-severe group. The median age was 74 (57, 83) years old, onset time was 5.0 (3.0, 10.0) days, total number of comorbidities was 3 (2, 5), including 58 cases (33.7%) with hypertension and 17 (9.9%) with heart failure, 113 (65.7%) with CURB-65 score ≤ 1, 34 cases (19.8%) had a CURB-65 score = 2 and 25 cases (14.5%) had a CURB-65 score ≥ 3. Univariate analysis showed that there were statistically significant differences between the two groups in age, smoking history, CURB-65 score, heart rate, onset time, total comorbidity, pathogenic microorganisms, fibrinogen (FIB), D-dimer, C-reactive protein (CRP), procalcitonin (PCT), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Multi-factor Logistic regression analysis showed that hypertension [odds ratio (OR) = 3.749, 95% confidence interval (95%CI) 1.411 to 9.962], heart failure (OR = 4.616, 95%CI was 1.116 to 19.093), co-infection (OR = 2.886, 95%CI was 1.073 to 7.760), history of smoking (OR = 8.268, 95%CI was 2.314 to 29.537), moderate to high CURB-65 score (OR = 4.833, 95%CI was 1.892 to 12.346), CRP (OR = 1.012, 95%CI was 1.002 to 1.022), AST (OR = 1.015, 95%CI was 1.001 to 1.030) were risk factors for severe CAP (all P < 0.05). The filtered indicators were included in the nomogram model, and the results showed that the area under the ROC curve (AUC) for the model to identify patients with severe adult CAP was 0.896, 95%CI was 0.840 to 0.937 (P < 0.05), and the calibration curve showed that the predicted probability of severe CAP was in good agreement with the observed probability (Hosmer-Lemeshow test: χ2 = 6.088, P = 0.665). The nomogram model has a good ability to identify patients with severe adult CAP and can be used as a comprehensive and reliable clinical diagnostic tool to provide a evidence for timely intervention in the treatment of adults with severe CAP.