The traditional gut-centric view of coeliac disease is evolving as immune and genetic insights underscore the central importance of a systemic, T cell immune response to gluten in disease pathogenesis. As the field increasingly recognize the limitations of small intestinal histology as the diagnostic standard, data supporting the accuracy of an immune (serologic) diagnosis of coeliac disease - well demonstrated in children - are growing for adults. Novel biomarkers such as interleukin-2 that identify the gluten-specific T cell demonstrate high sensitivity and specificity for coeliac disease and offer the potential for a diagnostic approach that avoids the need for gluten challenge. Asymptomatic disease and manifestations outside the gut pose considerable challenges for diagnosis using a case-finding strategy and enthusiasm for population screening is growing. The gluten-free diet remains a highly restrictive treatment and there is a paucity of controlled data to inform a safe gluten intake threshold. Ongoing symptoms and enteropathy are common and require systematic evaluation. Slowly-responsive disease is prevalent in the older patient diagnosed with coeliac disease, and super-sensitivity to gluten is an emerging concept that may explain many cases of nonresponsive disease. While there is great interest in developing novel therapies for coeliac disease, no drug has yet been registered. Efficacy studies are generally assessing drugs in patients with treated coeliac disease who undergo gluten challenge or in patients with nonresponsive disease; however, substantial questions remain around specific endpoints relevant for patients, clinicians and regulatory agencies and optimal trial design. Novel immune tools are providing informative readouts for clinical trials and are now shaping their design.

The utility of a universal DNA \'barcode\' fragment (658 base pairs of the Cytochrome C Oxidase I [COI] gene) has been established as a useful tool for species identification, and widely criticized as one for understanding the evolutionary history of a group. Large amounts of COI sequence data have been produced that hold promise for rapid species identification, for example, for biosecurity. The fruit fly tribe Dacini holds about a thousand species, of which 80 are pests of economic concern. We generated a COI reference library for 265 species of Dacini containing 5601 sequences that span most of the COI gene using circular consensus sequencing. We compared distance metrics versus monophyly assessments for species identification and although we found a \'soft\' barcode gap around 2% pairwise distance, the exceptions to this rule dictate that a monophyly assessment is the only reliable method for species identification. We found that all fragments regularly used for Dacini fruit fly identification >450 base pairs long provide similar resolution. 11.3% of the species in our dataset were non-monophyletic in a COI tree, which is mostly due to species complexes. We conclude with recommendations for the future generation and use of COI libraries. We revise the generic assignment of Dacus transversus stat. rev. Hardy 1982, and Dacus perpusillus stat. rev. Drew 1971 and we establish Dacus maculipterus White 1998 syn. nov. as a junior synonym of Dacus satanas Liang et al. 1993.

Plant viruses threaten global food security by infecting commercial crops, highlighting the critical need for efficient virus detection to enable timely preventive measures. Current techniques rely on polymerase chain reaction (PCR) for viral genome amplification and require laboratory conditions. This review explores the applications of CRISPR-Cas assisted diagnostic tools, specifically CRISPR-Cas12a and CRISPR-Cas13a/d systems for plant virus detection and analysis. The CRISPR-Cas12a system can detect viral DNA/RNA amplicons and can be coupled with PCR or isothermal amplification, allowing multiplexed detection in plants with mixed infections. Recent studies have eliminated the need for expensive RNA purification, streamlining the process by providing a visible readout through lateral flow strips. The CRISPR-Cas13a/d system can directly detect viral RNA with minimal preamplification, offering a proportional readout to the viral load. These approaches enable rapid viral diagnostics within 30 min of leaf harvest, making them valuable for onsite field applications. Timely identification of diseases associated with pathogens is crucial for effective treatment; yet developing rapid, specific, sensitive, and cost-effective diagnostic technologies remains challenging. The current gold standard, PCR technology, has drawbacks such as lengthy operational cycles, high costs, and demanding requirements. Here we update the technical advancements of CRISPR-Cas in viral detection, providing insights into future developments, versatile applications, and potential clinical translation. There is a need for approaches enabling field plant viral nucleic acid detection with high sensitivity, specificity, affordability, and portability. Despite challenges, CRISPR-Cas-mediated pathogen diagnostic solutions hold robust capabilities, paving the way for ideal diagnostic tools. Alternative applications in virus research are also explored, acknowledging the technology\'s limitations and challenges.

Securing an accurate autism-spectrum-condition diagnosis, particularly among women, remains challenging for autistic adults. Building upon previous research highlighting the short-story task (SST) as a promising tool for detecting fiction-based mentalizing difficulties in autistic adults, this study expands its scope. We investigated the SST\'s discriminative capacity across three distinct groups: autistic individuals (n = 32), nonautistic individuals without mental health problems (n = 32), and nonautistic individuals with clinical depression (n = 30). All three groups differed significantly from each other in their SST mentalizing score with the nonautistic group having the highest scores, the nonautistic but depressed group having medium scores and the autistic group showing the lowest scores. Receiver operator curve (ROC) analysis reaffirmed the SST\'s efficacy as a discriminator. Moreover, a linear regression analysis identified the SST mentalizing score, the SST comprehension score, and the number of books read per month as significant predictors of autism-spectrum-condition diagnosis. These findings bolster the SST\'s potential as a valuable adjunct in autism diagnostics, highlighting its discriminatory ability across diverse samples.

UNASSIGNED: Eagle syndrome is caused by an elongated styloid process affecting carotid arteries and cranial nerves. Pain, dysphagia, tinnitus, paresthesia (classic subtype), and neurovascular events (vascular subtype) may be triggered by head movements or arise spontaneously. However, Eagle syndrome remains underappreciated in the neurological community. We aimed to determine the most common neurological and non-neurological clinical presentations in patients with Eagle syndrome and to assess the clinical outcome post-surgical resection in comparison to non-surgical therapies.
UNASSIGNED: We conducted a systematic review of patient-level data on adults with Eagle syndrome, following PRISMA guidelines. We extracted data on demographics, presenting symptoms, neurological deficits, radiological findings, and treatments, including outcomes and complications, from studies in multiple indexing databases published between 2000 and 2023. The study protocol is registered with PROSPERO.
UNASSIGNED: In total, 285 studies met inclusion criteria, including 497 patients with Eagle syndrome (mean age 47.3 years; 49.8% female). Classical Eagle (370 patients, 74.5%) was more frequent than vascular Eagle syndrome (117 patients, 23.5%, p < 0.0001). Six patients (1.2%) presented with both variants and the subvariant for four patients (0.8%) was unknown. There was a male preponderance (70.1% male) in the vascular subtype. A history of tonsillectomy was more frequent in classic (48/153 cases) than in vascular (2/33 cases) Eagle syndrome (Odds Ratio 5.2, 95% CI [1.2-22.4]; p = 0.028). By contrast, cervical movements as trigger factors were more prevalent in vascular (12/33 cases) than in classic (7/153 cases) Eagle syndrome (Odds Ratio 7.95, 95% CI [2.9-21.7]; p = 0.0001). Headache and Horner syndrome were more frequent in vascular Eagle syndrome and dysphagia and neck pain more prominent in classic Eagle syndrome (all p < 0.01). Surgically treated patients achieved overall better outcomes than medically treated ones: Eighty-one (65.9%) of 123 medically treated patients experienced improvement or complete resolution, while the same applied to 313 (97.8%) of 320 surgical patients (Odds Ratio 1.49, 95% CI [1.1-2.0]; p = 0.016).
UNASSIGNED: Eagle syndrome is underdiagnosed with potentially serious neurovascular complications, including ischemic stroke. Surgical treatment achieves better outcomes than conservative management. Although traditionally the domain of otorhinolaryngologist, neurologist should include this syndrome in differential diagnostic considerations because of the varied neurological presentations that are amenable to effective treatment.

The integration of biochips with AI opened up new possibilities and is expected to revolutionize smart healthcare tools within the next five years. The combination of miniaturized, multi-functional, rapid, high-throughput sample processing and sensing capabilities of biochips, with the computational data processing and predictive power of AI, allows medical professionals to collect and analyze vast amounts of data quickly and efficiently, leading to more accurate and timely diagnoses and prognostic evaluations. Biochips, as smart healthcare devices, offer continuous monitoring of patient symptoms. Integrated virtual assistants have the potential to send predictive feedback to users and healthcare practitioners, paving the way for personalized and predictive medicine. This review explores the current state-of-the-art biochip technologies including gene-chips, organ-on-a-chips, and neural implants, and the diagnostic and therapeutic utility of AI-assisted biochips in medical practices such as cancer, diabetes, infectious diseases, and neurological disorders. Choosing the appropriate AI model for a specific biomedical application, and possible solutions to the current challenges are explored. Surveying advances in machine learning models for biochip functionality, this paper offers a review of biochips for the future of biomedicine, an essential guide for keeping up with trends in healthcare, while inspiring cross-disciplinary collaboration among biomedical engineering, medicine, and machine learning fields.

BACKGROUND: Molecular diagnostics may enable early, noninvasive detection of invasive fungal disease (IFD) in immunocompromised patients. Cell-free deoxyribonucleic acid (cfDNA) fungal polymerase chain reaction (PCR) assays were recently incorporated into institutional prolonged febrile neutropenia pathways. We aimed to evaluate the performance of plasma cfDNA PCR panels (mold and Candida panels) in pediatric oncology and hematopoietic stem cell transplant (HSCT) patients with clinical concern for IFD.
METHODS: This single-center, observational study assessed plasma cfDNA fungal PCR performance for noninvasive IFD detection in hospitalized pediatric oncology and HSCT patients. The primary outcome was IFD diagnosis per published consensus definitions within 1 month. Positive and negative agreement between plasma cfDNA fungal PCR and consensus definitions were calculated. We also described test turnaround time and patient survival.
RESULTS: From October 2021 to 2022, 54 patients underwent 60 evaluations with 11 proven/probable IFD cases. Comparing plasma cfDNA fungal PCRs to consensus definitions for proven/probable IFD, there was 73% positive agreement and 96% negative agreement. Two proven/probable cases with negative PCRs were caused by organisms not included on either panel. Median time to cfDNA fungal PCR result was 35 hours (interquartile range: 19-69) in eight proven/probable cases detected by cfDNA fungal PCR. There were 17 deaths among 54 patients, and IFD contributed to 45% of deaths in patients with proven/probable IFD.
CONCLUSIONS: Plasma cfDNA fungal PCRs detected relevant molds or yeast in most cases classified as proven/probable IFD. However, this targeted approach missed some cases. More studies are required to determine optimal utilization of molecular diagnostics in pediatric patients.

BACKGROUND: Rheumatoid arthritis (RA) and psoriatic arthritis (PsA) are chronic inflammatory diseases in which innate and adaptive responses of the immune system are induced. RA and PsA have complex signaling pathways. Despite the differences in their clinical presentation, there is a great demand for fast and accurate diagnosis of diseases to implement treatment and plan an individual therapeutic strategy quickly. In this report, we present the results of differential diagnosis of patients with RA and PsA and healthy subjects (C, control group), allowing for reliable differentiation of groups of rheumatoid patients based on biochemical parameters, attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectra, and combined data sets.
METHODS: Biochemical analyses, ELISA (enzyme-linked immunosorbent assays), and multiplex assays were conducted for blood sera from patients with RA (n = 32), patients with PsA (n = 28), and the control group (n = 18). ATR-FTIR spectra were collected for lyophilized sera.
RESULTS: The combination of six biochemical parameters (WBC, ESR, RF, CRP, HCC-4/CCL16, and HMGB1/HMGB) allowed the development of the partial least squares discriminant analysis (PLS-DA) model with an overall accuracy (OA) of 80% for test samples. The best separation between RA, PsA, and the control group was obtained utilizing spectral data. Using the interval PLS algorithm (iPLS) specific spectral ranges were selected and a classifier characterized by OA value for test set equal to 88% was obtained. This parameter, for the hybrid PLS-DA model constructed using selected biochemical parameters and a significantly reduced number of spectral variables, reached the level of 84%.
CONCLUSIONS: PLS-DA models developed on the basis of spectral data enable effective differentiation of patients with RA, patients with PsA, and healthy subjects. They appeared to be insensitive to existing inflammation processes which opens interesting perspectives for new diagnostic tests and algorithms for identification of patients with RA and PsA.

Introduction Magnetic resonance enterography (MRE) has emerged as a promising technique for evaluating the extent and severity of Crohn\'s disease activity. To compare how we measure Crohn\'s disease activity with MRE and endoscopy. Material and methods We retrospectively reviewed MRE studies of 60 patients with suspicious Crohn\'s disease who underwent 1.5-T MRI examinations (T1-weighted images pre- and post-IV contrast medium administration and T2-weighted images) and endoscopy within one month, and they were evaluated by one radiology consultant with experience of 17 years. Endoscopy was used as the reference standard for diagnosing active Crohn\'s disease cases. Data analysis was performed using the websites (www.graphpad.com and www.medcalc.org) and Microsoft Excel (Microsoft® Corp., Redmond, USA). Results A total of 35 patients were included in the study. The remaining 25 patients were excluded either due to non-available data in the endoscopy report or cases of non-Crohn\'s disease. The MRI examinations were reviewed by one radiology consultant and revealed 27 active and eight non-active Crohn\'s disease cases compared to 30 active and five non-active Crohn\'s disease cases in endoscopy. The sensitivity of MRI in detecting active cases of Crohn\'s disease compared to endoscopy was 83.3% and the specificity of 60%. The strength of agreement between both methods was fair to good (Kappa = 0.347, p-value = 0.4497, Chi-squared = 0.571 with one degree of freedom). Conclusion MRE statistically has a good impact on the assessment of Crohn\'s disease as well as endoscopy with the parameters used in this study. Non-invasiveness and the changes of activity seen in the bowel proximal to the ileocecal junction undetectable by endoscopy make MRE more practically applicable in this aspect.

Extracellular vesicles (EVs) are lipid-membrane nanoparticles that are shed or secreted by many different cell types. The EV research community has rapidly expanded in recent years and is leading efforts to deepen our understanding of EV biological functions in human physiology and pathology. These insights are also providing a foundation on which future EV-based diagnostics and therapeutics are poised to positively impact human health. However, current limitations in our understanding of EV heterogeneity, cargo loading mechanisms and the nascent development of EV metrology are all areas that have been identified as important scientific challenges. The field of synthetic biology is also contending with the challenge of understanding biological complexity as it seeks to combine multidisciplinary scientific knowledge with engineering principles, to build useful and robust biotechnologies in a responsible manner. Within this context, cell-free systems have emerged as a powerful suite of in vitro biotechnologies that can be employed to interrogate fundamental biological mechanisms, including the study of aspects of EV biogenesis, or to act as a platform technology for medical biosensors and therapeutic biomanufacturing. Cell-free gene expression (CFE) systems also enable in vitro protein production, including membrane proteins, and could conceivably be exploited to rationally engineer, or manufacture, EVs loaded with bespoke molecular cargoes for use in foundational or translational EV research. Our pilot data herein, also demonstrates the feasibility of cell-free EV engineering. In this perspective, we discuss the opportunities and challenges for accelerating EV research and healthcare applications with cell-free synthetic biology.