Persistent acute kidney injury biomarkers: A systematic review and meta-analysis.

BACKGROUND: Various biomarkers reportedly predict persistent acute kidney injury (AKI) despite their varying predictive performance across clinical trials. This study aims to compare the accuracy of various biomarkers in predicting persistent AKI in different populations and regions. METHODS: In this meta-analysis, we searched for urinary C-C motif chemokine ligand 14 (CCL14), Tissue inhibitor of metalloproteinase-2&insulin-like growth factor-binding protein-7 (TIMP-2&IGFBP7), Neutrophil Gelatinase-Associated Lipocalin (NGAL), plasma Cystatin C (pCysC), Soluble urokinase plasminogen activator receptor (suPAR), Proenkephalin (PenK) and urinary dickkopf-3:urinary creatinine (uDKK3:uCr) from various databases including Medline, PubMed, Embase, and Cochrane. This was geared towards predicting persistent AKI in adults (>18 years). Hierarchically summarized subject work characteristic curves (HSROC) and diagnostic odds ratio (DOR) values were used to summarize the diagnostic accuracy of the biomarkers. Further, meta-regression and subgroup analyses were carried out to identify sources of heterogeneity as well as evaluate the best predictive biomarkers in different populations and regions. RESULTS: We screened 31 studies from 2,356 studies and assessed the diagnostic value of 7 biomarkers for persistent AKI. Overall, CCL14 had the best diagnostic efficacy with an AUC of 0.79 (95 % CI 0.75-0.82), whereas TIMP-2 & IGFBP7, NGAL, and pCysC had diagnostic efficacy of 0.75 (95 % CI 0.71-0.79),0.71 (95 % CI 0.67-0.75), and 0.7007, respectively. Due to a limited number of studies, PenK, uDKK3:uCr, and suPAR were not subjected to meta-analysis; however, relevant literature reported diagnostic efficacy above 0.70. Subgroup analyses based on population, region, biomarker detection time, AKI onset time, and AKI duration revealed that in the intensive care unit (ICU) population, the AUC of CCL14 was 0.8070, the AUC of TIMP-2 & IGFBP7 was 0.726, the AUC of pCysC was 0.72, and the AUC of NGAL was 0.7344; in the sepsis population, the AUC of CCL14 was 0.85, the AUC of TIMP-2&IGFBP7 was 0.7438, and the AUC of NGAL was 0.544; in the post-operative population, the AUC of CCL14 was 0.83-0.93, the AUC of TIMP-2&IGFBP7 was 0.71, and the AUC of pCysC was 0.683. Regional differences were observed in biomarker prediction of persistent kidney injury, with AUCs of 0.8558 for CCL14, 0.7563 for TIMP-2 & IGFBP7, and 0.7116 for NGAL in the Eurasian American population. In the sub-African population, TIMP-2 & IGFBP7 had AUCs of 0.7945, 0.7418 for CCL14, 0.7097 for NGAL, and 0.7007 for pCysC. for TIMP-2 & IGFBP7 was 0.7945, AUC for CCL14 was 0.7418, AUC for NGAL was 0.7097, and AUC for pCysC was 0.7007 in the sub-African population. Duration of biomarker detection, AKI onset, and AKI did not influence the optimal predictive performance of CCL14. Subgroup analysis and meta-regression of CCL14-related studies revealed that CCL14 is the most appropriate biomarker for predicting persistent stage 2-3 AKI, with heterogeneity stemming from sample size and AKI staging. CONCLUSION: This meta-analysis discovered CCL14 as the best biomarker to predict persistent AKI, specifically persistent stage 2-3 AKI.

Copeptin associates with major adverse cardiovascular events in patients on maintenance hemodialysis.

BACKGROUND: End-stage renal disease (ESRD) necessitating hemodialysis pose substantial cardiovascular risks, with cardiovascular disease (CVD) as a leading cause of mortality. Biomarkers like copeptin have emerged as potential indicators of cardiovascular stress and prognosis in CKD populations. OBJECTIVE: This study aimed to assess the prognostic value of copeptin in predicting major adverse cardiovascular events (MACEs) among hemodialysis patients, alongside traditional cardiac biomarkers. METHODS: ESRD patients undergoing maintenance hemodialysis were enrolled. Copeptin levels were measured, and patients were followed for MACEs, defined as cardiovascular deaths, myocardial infarction, stroke, or heart failure-related hospitalizations. Cox proportional-hazards models were used to evaluate the association between copeptin and outcomes, adjusting for relevant covariates. RESULTS: Among 351 patients followed for a median of 22.7 months, elevated copeptin levels were significantly associated with an increased risk of MACEs (HR 1.519, 95 % CI 1.140 to 2.023; p = 0.00425). Copeptin demonstrated predictive capability across multiple statistical tests (Log-rank p = 0.024; Gehan p < 0.001; Tarone-Ware p < 0.001; Peto-Peto p = 0.027), although significance was attenuated in pairwise comparisons post-adjustment for multiple testing. Combining copeptin with NT-proBNP or hs-cTnT further enhanced risk stratification for MACEs. CONCLUSION: Elevated copeptin levels independently predict adverse cardiovascular outcomes in hemodialysis patients. Integrating copeptin with traditional cardiac biomarkers may refine risk stratification and guide personalized therapeutic strategies in this high-risk population.

Emergency department clinical performance of ADVIA Centaur n-terminal prohormone of B-type natriuretic peptide assay.

BACKGROUND: Natriuretic peptide testing is guideline recommended as an aid to the diagnosis of heart failure (HF). We sought to evaluate the performance of the ADVIA Centaur (Siemens Healthcare Diagnostics, Tarrytown, NY) NT-proBNPII assay (PBNPII) in emergency department (ED) dyspneic patients. METHODS: Eligible patients presented to the ED with dyspnea, with their gold standard diagnosis determined by up to 3 cardiologists blinded to the PBNPII results. Patients were stratified into 3 groups based on PBNPII resultsa rule out group of NT-proBNP<300  pg/mL, an age-specific rule in group using cutoffs of 450, 900, and 1800 pg/mL, for <50, 50-75, and > 75 years respectively, and an intermediate cohort for results between the rule out and rule in groups. RESULTS: Of 3128 eligible patients, 1148 (36.7 %) were adjudicated as acute heart failure (AHF). The gold standard AHF diagnosis rate was 3.7, 24.3, and 67.2 % for patients with NTproBNPII in the negative, indeterminate, and positive groups, respectively. Overall likelihood ratios (LR) were 0.07 (95 % CI: 0.05,0.09), 0.55 (0.45,0.67), and 3.53 (3.26,3.83) for the same groups, respectively. Individual LR+for age dependent cutoffs were 5.01 (4.25,5.91), 3.71 (3.25,4.24), and 2.38 (2.10,2.69), respectively. NTproBNPII increased with increasing severity of HF when stratified by NYHA classification. CONCLUSIONS: The ADVIA Centaur PBNPII assay demonstrates acceptable clinical performance using the recommended single rule out and age dependent rule in cutoffs for an AHF diagnosis in dyspneic ED patients.

Interval-specific likelihood ratios and probability-based models for interpreting combined CSF biomarkers for Alzheimer's disease.

BACKGROUND: In Alzheimer's disease (AD) diagnosis, a cerebrospinal fluid (CSF) biomarker panel is commonly interpreted with binary cutoff values. However, these values are not generic and do not reflect the disease continuum. We explored the use of interval-specific likelihood ratios (LRs) and probability-based models for AD using a CSF biomarker panel. METHODS: CSF biomarker (Aß1-42, tTau and pTau181) data for both a clinical discovery cohort of 241 patients (measured with INNOTEST) and a clinical validation cohort of 129 patients (measured with EUROIMMUN), both including AD and non-AD dementia/cognitive complaints were retrospectively retrieved in a single-center study. Interval-specific LRs for AD were calculated and validated for univariate and combined (Aß1-42/tTau and pTau181) biomarkers, and a continuous bivariate probability-based model for AD, plotting Aß1-42/tTau versus pTau181 was constructed and validated. RESULTS: LR for AD increased as individual CSF biomarker values deviated from normal. Interval-specific LRs of a combined biomarker model showed that once one biomarker became abnormal, LRs increased even further when another biomarker largely deviated from normal, as replicated in the validation cohort. A bivariate probability-based model predicted AD with a validated accuracy of 88% on a continuous scale. CONCLUSIONS: Interval-specific LRs in a combined biomarker model and prediction of AD using a continuous bivariate biomarker probability-based model, offer a more meaningful interpretation of CSF AD biomarkers on a (semi-)continuous scale with respect to the post-test probability of AD across different assays and cohorts.

In Vivo Imaging of Rodent Retina in Retinal Disease.

High-quality imaging of the retina is crucial to the diagnosis and monitoring of disease, as well as for evaluating the success of therapeutics in human patients and in preclinical animal models. Here, we describe the basic principles and methods for in vivo retinal imaging in rodents, including fundus imaging, fluorescein angiography, optical coherence tomography, fundus autofluorescence, and infrared imaging. After providing a concise overview of each method and detailing the retinal diseases and conditions that can be visualized through them, we will proceed to discuss the advantages and disadvantages of each approach. These protocols will facilitate the acquisition of optimal images for subsequent quantification and analysis. Additionally, a brief explanation will be given regarding the potential results and the clinical significance of the detected abnormalities.

Flow cytometry in acute myeloid leukemia and detection of minimal residual disease.

Acute myeloid leukemia (AML) is a common type of acute leukemia (AL), belonging to malignant tumors of the hematopoietic system with the characteristics of rapid disease development, control with extreme difficulties, easy recurrence, poor prognosis, and incidence rate increasing with age. The traditionally diagnostic standard of French American British (FAB), being based on the morphological examination with high human subjectivity, can no longer meet the demand of clinical diagnosis and treatment of AML. Requirements of objective accuracy and low-dose sample, have become the indispensable method for AML diagnosis and monitoring prognosis. Flow cytometry is a modern technology that can quickly and accurately detect the series, antigen distribution, differentiation stage of AML cells, minimal residual lesions after AML therapy, so as to provide the great significance in guiding clinical diagnosis, hierarchical treatment, and prognosis judgement. This article will systematically elaborate on the application of flow cytometry in the diagnosis and classification of AML, and the detection of minimal residual lesions, thereby providing reference significance for dynamic monitoring and prognostic observation of AML with different immune subtypes of FAB.

miRNA-based electrochemical biosensors for ovarian cancer.

Ovarian cancer, a prevalent and deadly cancer among women, presents a significant challenge for early detection due to its heterogeneous nature. MicroRNAs, short non-coding regulatory RNA fragments, play a role in various cellular processes. Aberrant expression of these microRNAs has been observed in the carcinogenesis-related processes of many cancer types. Numerous studies highlight the critical role of microRNAs in the initiation and progression of ovarian cancer. Given their clinical importance and predictive value, there has been considerable interest in developing simple, prompt, and sensitive miRNA biosensor strategies. Among these, electrochemical sensors have demonstrated advantageous characteristics such as simplicity, sensitivity, low cost, and scalability. These microRNA-based electrochemical biosensors are valuable tools for early detection and point-of-care applications. This article discusses the potential role of microRNAs in ovarian cancer and recent advances in the development of electrochemical biosensors for miRNA detection in ovarian cancer samples.

The Use of Multiplex Real-Time PCR for the Simultaneous Detection of Foodborne Bacterial Pathogens.

Foodborne pathogens continue to be a major health concern worldwide. Culture-dependent methodologies are still considered the gold standard to perform pathogen detection and quantification. These methods present several drawbacks, such as being time-consuming and labor intensive. The implementation of real-time PCR has allowed to overcome these limitations, and even reduce the cost associated with the analyses, due to the possibility of simultaneously and accurately detecting several pathogens in one single assay, with results comparable to those obtained by classical approaches. In this chapter, a protocol for the simultaneous detection of two of the most important foodborne pathogens, Salmonella spp. and Listeria monocytogenes, is described.

Application of MinION Long-Read Sequencer for Semi-targeted Detection of Foodborne Pathogens.

Foodborne pathogens remain a serious health issue in developed and developing countries. Safeness of food products has been assured for years with culture-based microbiological methods; however, these present several limitations such as turnaround time and extensive hands-on work, which have been typically address taking advantage of DNA-based methods such as real-time PCR (qPCR). These, and other similar techniques, are targeted assays, meaning that they are directed for the specific detection of one specific microbe. Even though reliable, this approach suffers from an important limitation that unless specific assays are design for every single pathogen potentially present, foods may be considered erroneously safe. To address this problem, next-generation sequencing (NGS) can be used as this is a nontargeted method; thus it has the capacity to detect every potential threat present. In this chapter, a protocol for the simultaneous detection and preliminary serotyping of Salmonella enterica serovar Enteritidis, Salmonella enterica serovar Typhimurium, Listeria monocytogenes, and Escherichia coli O157:H7 is described.

Establishment of a rapid detection method for Mycoplasma pneumoniae based on RPA-CRISPR-Cas12a technology.

Mycoplasma pneumoniae can cause respiratory infections and pneumonia, posing a serious threat to the health of children and adolescents. Early diagnosis of Mycoplasma pneumoniae infection is crucial for clinical treatment. Currently, diagnostic methods for Mycoplasma pneumoniae infection include pathogen detection, molecular biology techniques, and bacterial culture, all of which have certain limitations. Here, we developed a rapid, simple, and accurate detection method for Mycoplasma pneumoniae that does not rely on large equipment or complex operations. This technology combines the CRISPR-Cas12a system with recombinase polymerase amplification (RPA), allowing the detection results to be observed through fluorescence curves and immunochromatographic lateral flow strips.It has been validated that RPA-CRISPR/Cas12a fluorescence analysis and RPA-CRISPR/Cas12-immunochromatographic exhibit no cross-reactivity with other common pathogens, and The established detection limit was ascertained to be as low as 102 copies/µL.Additionally, 49 clinical samples were tested and compared with fluorescence quantitative polymerase chain reaction, demonstrating a sensitivity and specificity of 100%. This platform exhibits promising clinical performance and holds significant potential for clinical application, particularly in settings with limited resources, such as clinical care points or resource-constrained areas.

Electrochemical biosensors for early detection of breast cancer.

Breast cancer continues to be a significant contributor to global cancer deaths, particularly among women. This highlights the critical role of early detection and treatment in boosting survival rates. While conventional diagnostic methods like mammograms, biopsies, ultrasounds, and MRIs are valuable tools, limitations exist in terms of cost, invasiveness, and the requirement for specialized equipment and trained personnel. Recent shifts towards biosensor technologies offer a promising alternative for monitoring biological processes and providing accurate health diagnostics in a cost-effective, non-invasive manner. These biosensors are particularly advantageous for early detection of primary tumors, metastases, and recurrent diseases, contributing to more effective breast cancer management. The integration of biosensor technology into medical devices has led to the development of low-cost, adaptable, and efficient diagnostic tools. In this framework, electrochemical screening platforms have garnered significant attention due to their selectivity, affordability, and ease of result interpretation. The current review discusses various breast cancer biomarkers and the potential of electrochemical biosensors to revolutionize early cancer detection, making provision for new diagnostic platforms and personalized healthcare solutions.

Circular RNAs in laryngeal cancer.

Laryngeal cancer remains a significant global health concern, with poor prognosis for advanced-stage disease highlighting the need for novel diagnostic, prognostic, and therapeutic approaches. Circular RNAs (circRNAs), a class of covalently closed non-coding RNAs, have emerged as important regulators of gene expression and cellular processes in various cancers, including laryngeal cancer. This review summarizes the current understanding of circRNAs in laryngeal cancer, covering their biogenesis, regulatory mechanisms, and potential clinical applications. We explore the diverse functions of circRNAs, including their roles as miRNA sponges, protein interactors, and direct mRNA regulators, and their influence on key cellular processes such as proliferation, invasion, and metastasis. The review highlights promising circRNAs as diagnostic and prognostic biomarkers, as well as potential therapeutic targets. We also outline current strategies for circRNA modulation, including suppression techniques like RNA interference and CRISPR/Cas systems, and overexpression methods using vectors and synthetic circRNAs.

Rapid visual detection of Helicobacter pylori and vacA subtypes by Dual-Target RAA-LFD assay.

BACKGROUND: Helicobacter pylori (H. pylori) infects over 50% of the global population and is a significant risk factor for gastric cancer. The pathogenicity of H. pylori is primarily attributed to virulence factors such as vacA. Timely and accurate identification, along with genotyping of H. pylori virulence genes, are essential for effective clinical management and controlling its prevalence. METHODS: In this study, we developed a dual-target RAA-LFD assay for the rapid, visual detection of H. pylori genes (16s rRNA, ureA, vacA m1/m2), using recombinase aided amplification (RAA) combined with lateral flow dipstick (LFD) methods. Both 16s rRNA and ureA were selected as identification genes to ensure reliable detection accuracy. RESULTS: A RAA-LFD assay was developed to achieve dual-target amplification at a stable 37 °C within 20 min, followed by visualization using the lateral flow dipstick (LFD). The whole process, from amplification to results, took less than 30 min. The 95 % limit of detection (LOD) for 16 s rRNA and ureA, vacA m1, vacA m2 were determined as 3.8 × 10-2 ng/µL, 5.8 × 10-2 ng/µL and 1.4 × 10-2 ng/µL, respectively. No cross-reaction was observed in the detection of common pathogens including Escherichia coli, Klebsiella pneumoniae, Enterococcus faecalis, Staphylococcus aureus, Pseudomonas aeruginosa, and Bacillus subtilis, showing the assay's high specificity. In the evaluation of the clinical performance of the RAA-LFD assay. A total of 44 gastric juice samples were analyzed, immunofluorescence staining (IFS) and quantitative polymerase chain reaction (qPCR) were used as reference methods. The RAA-LFD results for the 16s rRNA and ureA genes showed complete agreement with qPCR findings, accurately identifying H. pylori infection as confirmed by IFS in 10 out of the 44 patients. Furthermore, the assay successfully genotyped vacA m1/m2 among the positive samples, showing complete agreement with qPCR results and achieving a kappa (κ) value of 1.00. CONCLUSION: The dual-target RAA-LFD assay developed in this study provides a rapid and reliable method for detecting and genotyping H. pylori within 30 min, minimizing dependency on sophisticated laboratory equipment and specialized personnel. Clinical validation confirms its efficacy as a promising tool for effectively control of its prevalence and aiding in the precise treatment of H. pylori-associated diseases.

Accuracy study of Angiotensin 1-7 composite index test to predict pulmonary fibrosis and guide treatment.

BACKGROUND: Pulmonary fibrosis can develop after acute respiratory distress syndrome (ARDS). The hypothesis is we are able to measure phenotypes that lie at the origin of ARDS severity and fibrosis development. The aim is an accuracy study of prognostic circulating biomarkers. METHODS: A longitudinal study followed COVID-related ARDS patients with medical imaging, pulmonary function tests and biomarker analysis, generating 444 laboratory data. Comparison to controls used non-parametrical statistics; p < 0·05 was considered significant. Cut-offs were obtained through receiver operating curve. Contingency tables revealed predictive values. Odds ratio was calculated through logistic regression. RESULTS: Angiotensin 1-7 beneath 138 pg/mL defined Angiotensin imbalance phenotype. Hyper-inflammatory phenotype showed a composite index test above 34, based on high Angiotensin 1-7, C-Reactive Protein, Ferritin and Transforming Growth Factor-ß. Analytical study showed conformity to predefined goals. Clinical performance gave a positive predictive value of 95 % (95 % confidence interval, 82 %-99 %), and a negative predictive value of 100 % (95 % confidence interval, 65 %-100 %). Those severe ARDS phenotypes represented 34 (Odds 95 % confidence interval, 3-355) times higher risk for pulmonary fibrosis development (p < 0·001). CONCLUSIONS: Angiotensin 1-7 composite index is an early and objective predictor of ARDS evolving to pulmonary fibrosis. It may guide therapeutic decisions in targeted phenotypes.

Integrating pretest probability for rheumatoid arthritis with likelihood ratios of RF and ACPA to improve clinical utility of rheumatoid arthritis autoantibody testing.

BACKGROUND AND AIMS: Rheumatoid arthritis (RA) manifests through various symptoms and systemic manifestations. Diagnosis involves serological markers like rheumatoid factor (RF) and anti-citrullinated protein antibodies (ACPA). Past studies have shown the added value of likelihood ratios (LRs) in result interpretation. LRs can be combined with pretest probability to estimate posttest probability for RA. There is a lack of information on pretest probability. This study aimed to estimate pretest probabilities for RA. MATERIALS AND METHODS: This retrospective study included 133 consecutive RA patients and 651 consecutive disease controls presenting at a rheumatology outpatient clinic. Disease characteristics, risk factors associated with RA and laboratory parameters were documented for calculating pretest probabilities and LRs. RESULTS: Joint involvement, erosions, morning stiffness, and positive CRP, ESR tests significantly correlated with RA. Based on these factors, probabilities for RA were estimated. Besides, LRs for RA were established for RF and ACPA and combinations thereof. LRs increased with antibody levels and were highest for double high positivity. Posttest probabilities were estimated based on pretest probability and LR. CONCLUSION: By utilizing pretest probabilities for RA and LRs for RF and ACPA, posttest probabilities were estimated. Such approach enhances diagnostic accuracy, offering laboratory professionals and clinicians insights in the value of serological testing during the diagnostic process.

Criteria for second generation comparator tests in validation of novel HPV DNA tests for use in cervical cancer screening.

While HC2 and GP5+/6+ PCR-EIA were pivotal in test validation of new HPV assays, they represent the first generation of comparator tests based upon technologies that are not in widespread use anymore. In the current guideline, criteria for second-generation comparator tests are presented that include more detailed resolution of HPV genotypes. Second-generation comparator tests should preferentially target only the 12 genotypes classified as carcinogenic (IARC-group I), and show consistent non-inferior sensitivity for CIN2+ and CIN3+ and specificity for ≤CIN1 compared to one of the first-generations comparators, in at least three validation studies using benchmarks of 0.95 for relative sensitivity and 0.98 for relative specificity. Validation should take into account used storage media and other sample handling procedures. Meta-analyses were conducted to identify the assays that fulfill these stringent criteria. Four tests fulfilled the new criteria: (1) RealTime High-Risk HPV Test (Abbott), (2) Cobas-4800 HPV test (Roche Molecular System), (3) Onclarity HPV Assay (BD Diagnostics), and (4) Anyplex II HPV HR Detection (Seegene), each evaluated in three to six studies. Whereas the four assays target 14 carcinogenic genotypes, the first two identify separately HPV16 and 18, the third assay identifies five types separately and the fourth identifies all the types separately.

The diagnostic value and associated molecular mechanism study for fibroblast-related mitochondrial genes on keloid.

PURPOSE: This study aims to reveal the mechanism of fibroblast-related mitochondrial genes on keloid formation and explore promising signature genes for keloid diagnosis. METHOD: The distribution of fibroblasts between the keloid sample and control sample based on three keloid datasets, followed by the differentially expressed genes (DEGs) investigation and associated enrichment analysis. Then, hub genes were explored based on DEGs, mitochondrial genes from an online database, as well as fibroblast-related genes that were revealed by WCGNA. Subsequently, signature genes were screened through machine learning, and their diagnostic value was validated by nomogram. Moreover, the targeted drugs and related transcriptional regulation of these genes were analyzed. Finally, the verification analysis was performed on signature genes using qPCR analysis. RESULT: A total of totally 329 DEGs were revealed based on three datasets, followed by enrichment analysis. WGCNA revealed a total of 258 fibroblast-related genes, which were primarily assembled in functions like muscle tissue development. By using machine learning, we screened four signature genes (ACSF2, ALDH1B1, OCIAD2, and SIRT4) based on eight hub genes (fibroblast-related mitochondrial genes). Nomogram and validation analyses confirmed the well-diagnostic performance of these four genes in keloid. Immune infiltration and drug correlation analyses showed that SIRT4 was significantly associated with immune cell type 2 T helper cells and molecular drug cyclosporin. All these findings provided new perspectives for the clinical diagnosis and therapy of keloid. CONCLUSION: The fibroblast-related mitochondrial genes including SIRT4, OCIAD2, ALDH1B1, and ACSF2 were novel signature genes for keloid diagnosis, offering novel targets and strategies for diagnosis and therapy of keloid.

Large language model produces high accurate diagnosis of cancer from end-motif profiles of cell-free DNA.

Instruction-tuned large language models (LLMs) demonstrate exceptional ability to align with human intentions. We present an LLM-based model-instruction-tuned LLM for assessment of cancer (iLLMAC)-that can detect cancer using cell-free deoxyribonucleic acid (cfDNA) end-motif profiles. Developed on plasma cfDNA sequencing data from 1135 cancer patients and 1106 controls across three datasets, iLLMAC achieved area under the receiver operating curve (AUROC) of 0.866 [95% confidence interval (CI), 0.773-0.959] for cancer diagnosis and 0.924 (95% CI, 0.841-1.0) for hepatocellular carcinoma (HCC) detection using 16 end-motifs. Performance increased with more motifs, reaching 0.886 (95% CI, 0.794-0.977) and 0.956 (95% CI, 0.89-1.0) for cancer diagnosis and HCC detection, respectively, with 64 end-motifs. On an external-testing set, iLLMAC achieved AUROC of 0.912 (95% CI, 0.849-0.976) for cancer diagnosis and 0.938 (95% CI, 0.885-0.992) for HCC detection with 64 end-motifs, significantly outperforming benchmarked methods. Furthermore, iLLMAC achieved high classification performance on datasets with bisulfite and 5-hydroxymethylcytosine sequencing. Our study highlights the effectiveness of LLM-based instruction-tuning for cfDNA-based cancer detection.

Multidisciplinary perspectives in Demodex blepharitis: A new view of treatment from clinical, payer, and patient perspectives.

Demodex infestation is the cause of more than two-thirds of all cases of blepharitis in the United States. Although symptoms may include crustiness, redness, or itching of the eyelids, diagnosis can be accomplished through a simple examination of the eyelashes. The presence of a waste product of the Demodex mite, known as collarettes, on the base of the eyelashes is a pathognomonic sign of Demodex blepharitis. Demodex infestation that results in blepharitis may cause blockage and ultimately atrophy of the meibomian glands, worsening dry eye disease. Until recently, management of Demodex blepharitis has been limited by a lack of approved therapy options. Lotilaner ophthalmic solution 0.25%, the first approved therapy for treatment of Demodex blepharitis, has not only been shown to eradicate Demodex mites in one-half to two-thirds of patients following short-term treatment but also demonstrated continued benefits through 1 year of follow-up. In addition to managing Demodex blepharitis, treatment with lotilaner ophthalmic solution 0.25% may aid in the management of dry eye disease and other forms of ocular surface disease caused by complications of Demodex infestation. As a result, it is possible that successful management of Demodex blepharitis may reduce chronic use of health care resources dedicated to managing other chronic ocular conditions. As eye care professionals recognize Demodex infestation as a key mediator of ocular surface disease, increasing diagnostic awareness and addressing this underlying cause of Demodex blepharitis may reduce the need for specialist follow-up care, decrease the need for chronic therapy, and improve patient outcomes. Through routine screening for Demodex infestation and Demodex blepharitis, eye care professionals can now address an underlying factor in ocular surface disease to improve use of health care resources in the community.