High Positive Rate Research Articles

Evaluation of anti-Pertussis antibody levels in Iranian infants and children: Is it time to include booster acellular Pertussis Vaccines in the immunization schedule?

The prevalence of anti-pertussis antibodies among infants and children in Iran has not been thoroughly investigated. Given that recommendations for booster vaccines are based on national disease epidemiology, we aimed to evaluate the seroprevalence of pertussis antibodies among infants and children in an Iranian referral hospital. A total of 1012 infants and children were included in the study. Serum samples were stored at -20°C until analysis. Demographic characteristics of patients, including age, sex, trivalent diphtheria, tetanus, and whole-cell pertussis (DTwP) vaccination status, and time since DTwP vaccination were collected. Anti-pertussis IgG antibodies were measured using a commercial ELISA kit. In this cross-sectional study, the median age of the participants was 35months (IQR:9-72months). In infants ≤2months, only 15% had positive anti-pertussis antibodies. This increased to 28% in the 3 to 4months group and 55% in the 5 to 6months group. The highest positivity rates (63% and 66%) were seen in the 7 to 18months and 19 to 36months age groups, respectively. Positivity declined to 45% in the 37 to 72months group, and 47% in those over 72months. A significant relationship was found between the time elapsed since vaccination and anti-pertussis IgG levels (p=0.005). Our study highlights a concerning prevalence of low anti-pertussis, especially among infants aged ≤2months, where the majority displayed negative results. This situation underscores the vulnerability of newborns to pertussis due to insufficient immunity and emphasizes the urgent need for effective maternal vaccination strategies. Additionally, we observed a decline in anti-pertussis IgG levels after 36months, raising concerns about waning immunity in older children. Continued research is crucial to evaluate the long-term efficacy of booster vaccines and to develop optimal vaccination strategies to protect infants and children from pertussis.

Loss function inversion for improved crack segmentation in steel bridges using a CNN framework

Automating bridge visual inspection using deep learning algorithms for crack detection in images is a prominent way to make these inspections more effective. This paper addresses several challenges associated with crack detection: (1) data imbalance, caused by a small crack area as compared to the background, and (2) a high false positive rate, due to a large amount of crack-like features in the background. First, a new benchmark dataset is presented, containing images of cracks in steel bridges along with pixel-wise annotations. Secondly, the importance of incorporating background patches is examined to assess their impact on network performance when applied to high resolution images of cracks in steel bridges. Finally, a loss function is introduced that enables the use of a relatively large number of background patches in neural network training. The proposed approaches yield a significant reduction in false positive rates, thereby improving the overall performance of crack segmentation.

300. Clinical Experience with 16S Ribosomal RNA Gene PCR and Sequencing of Normally Sterile Body Fluids and Tissues in Pediatric Patients

Abstract Background 16S ribosomal RNA (rRNA) gene PCR and sequencing may serve as an adjunctive diagnostic tool in complex infections, identifying bacteria in patients on antibiotics whose cultures may be negative. Data on the optimal clinical settings for utilizing this type of testing are limited. This study reviews a single center's 16S rRNA PCR/sequencing experience in children to identify clinical syndromes and optimize specimen choice for higher yield, leading to testing of appropriate patients. Methods A retrospective study was performed at Mayo Clinic, Rochester involving children aged 0 to 18 years whose normally sterile tissue or fluid samples underwent 16S rRNA gene PCR/sequencing. The assay involved an up-front real-time PCR assay, reported as negative or submitted to Sanger or next-generation sequencing depending on Ct values. Data was collected on patient characteristics and results of 16S rRNA gene PCR/sequencing and conventional tests. Impact on clinical decision-making was assessed as to whether the advanced molecular diagnostic changed antimicrobial therapy. Results A total of 162 tests were performed on 124 patients, including 47% females (58/124) with a median age of 9.6 (range, 2.2-15.0) years. Overall, 33/162 (20%) of tests were positive in 24/124 (19%) patients. 58% of positive tests (19/33) were from samples with negative bacterial cultures. Cerebrospinal fluid was the most common specimen tested (n=38; 31%). Positive results were more likely from fluid compared to tissue samples (OR [95% CI]: 3.1 [1.3, 7.1], p=.007; OR [95% CI]: 0.3 [0.1, 0.8], p=.007, respectively). Testing was positive in 5/10 (50%) pleural fluids tested, a higher positivity rate than any other specimen type (OR [95% CI]: 5 [1.3, 19.0], p=.011). No significant changes in antibiotics were made within 24 hours of reporting positive 16S rRNA gene PCR/sequencing results. Conclusion This study highlights the importance of selecting appropriate sample types for 16S rRNA gene PCR/sequencing in pediatric patients. The assay is most likely to yield positive results in children with pleural effusion and in other fluid samples such as subdural and synovial fluid. Further implementation science research is needed to achieve impact on clinical practice. Disclosures Robin Patel, MD, a patent on Bordetella pertussis/parapertussis PCR issued, a patent on a device/method for sonication with royalties paid by Samsung to Mayo Clinic, a: See above|MicuRx Pharmaceuticals and BIOFIRE: Grant/Research Support|PhAST, Day Zero Diagnostics, Abbott Laboratories, Sysmex, DEEPULL DIAGNOSTICS, S.L., Netflix, Oxford Nanopore Technologies and CARB-X: Advisor/Consultant|Up-to-Date and the Infectious Diseases Board Review Course.: Honoraria

P-108. Clinical Evaluation of a Sequencing-based Diagnostic for Bacterial and Fungal ID & AST Directly from Patient Blood Samples

Abstract Background Early pathogen ID and targeted treatment are key to reducing bloodstream infection (BSI) morbidity and mortality. Current diagnostics rely on culture which takes 1-2 days for ID and longer for antimicrobial susceptibility testing (AST) results, or molecular assays with limited panels, few resistance markers, and high false positive rates. We report interim results of a first-in-kind comprehensive ID and predictive AST assay directly from patient blood samples. The system can deliver results in ∼8 hrs, uses ultra-high enrichment of microbial DNA directly from blood, whole-genome sequencing, and a predictive AST machine-learning algorithm to identify a broad range of species and pathogen/drug combinations. Methods We enrolled subjects with suspicion of BSI from 3 EDs and 1 ICU/inpatient in 4 Boston area hospitals in 2 IRB approved observational studies. We collected whole blood in SPS vacutainers and 10mL were processed at Day Zero Diagnostics (DZD) and sequenced on an Oxford Nanopore platform. Sequencing data were analyzed by Keynome® algorithms to determine pathogen ID and predict AST profiles. Tables 1 & 2 list current on-panel pathogens and drug models tested. Performance was compared to hospital microbiology lab phenotypic ID/AST results from blood cultures collected within 0-24 hours of the research draw. Results Species-level ID results in 225 subjects (6525 calls) demonstrated 80.0% sensitivity, 99.9% specificity, 64% PPV, and 99.9% agreement with clinical culture. Eight distinct species were identified among the 20 (8.9%) clinical culture positive samples with on-panel organisms. Thirteen samples had sufficient genome coverage for on-panel AST predictions demonstrating 92.3% categoric agreement with phenotypic AST. Conclusion Our data suggests the DZD diagnostic system can provide accurate ID and AST results directly from blood in patients with suspected BSI. To our knowledge these results are the first demonstration of whole genome recovery and comprehensive ID & AST directly from patient blood samples. This assay has the potential to revolutionize speed to diagnosis of BSI, thus facilitating targeted therapy, improved outcomes, and reduced development of antimicrobial resistance. Disclosures Michael R. Filbin, MD, Day Zero Diagnostics: Grant/Research Support|Quidel: Grant/Research Support Peter Hou, MD, Center for Disease Control: Grant/Research Support|Day Zero Diagnostics: Grant/Research Support|iDoc Telehealth Solutions: Ownership Interest Michael Donnino, MD, Day Zero Diagnostics: Grant/Research Support Archana Asundi, MD, Day Zero Diagnostics: Grant/Research Support|Gilead Sciences: Grant/Research Support|GSK/ViiV Healthcare: Grant/Research Support|Theratechnologies: Grant/Research Support Zoe H. Rogers, MPH, Day Zero Diagnostics: employment Emma Briars, PhD, Day Zero Diagnostics: employment Alison Gassett, MPH, Day Zero Diagnostics: employment Alexander Reidel, BS, Day Zero Diagnostics: employment Alexis Campbell, MA, Day Zero Diagnostics: Grant/Research Support Jason Wittenbach, PhD, Day Zero Diagnostics: employment Nicole Billings, PhD, Day Zero Diagnostics: employment

P-1377. Rates of Screening of Sexually Transmitted Infections in Male Military Trainees who Present with Dysuria

Abstract Background A high burden of sexually transmitted infections (STIs) exists among trainees entering United States Air Force Basic Military Training (BMT). While women entering training are universally screened for STIs, men, who account for the majority of trainees, are rarely tested. The rates of testing among symptomatic men who present with dysuria during BMT are unknown. Furthermore, rates of follow-up testing among male service members who present with dysuria during BMT are unknown. Demographics of 82 men diagnosed with dysuria or urinary tract infection during BMT, 2019-2023 Methods All male basic trainees who received a diagnostic code of dysuria or urinary tract infection between 2019-2023 were retrospectively analyzed to evaluate their diagnostic workup and follow-up over the three years after diagnosis. To assess the impact of presumptive STI therapy on subsequent follow-up, patients who received empiric treatment for STIs were compared to those who did not, with a focus on evaluating future STI testing rates and incidence. Nominal variables were compared using Fisher’s Exact Test while continuous variables were analyzed using the Mann-Whitney U test. Diagnostic Workup and follow-up for male basic trainees diagnosed with dysuria or urinary tract infection compared by receipt of empiric antibiotics for sexually transmitted infections Results Of the 102,382 men who entered BMT during the study period, 82 (0.08%) were diagnosed with dysuria or a urinary tract infection during training. Dysuria accounted for the majority of diagnoses (79%) (Table 1). 70% of symptomatic men were tested for gonorrhea and chlamydia (GC/CT). Among those tested, 23% had a positive GC/CT test. Only 25 (30%) received any additional follow-up STI testing in their next 3 years in the military, with a positivity rate of 12%. Those who were empirically treated for STIs were more likely to have a documented sexual history (80% vs. 45%, p=0.004), receive a GC/CT test (96% vs. 57%, p=0.002), and have additional STI testing in the 3 years after diagnosis (46% vs. 23%, p=0.04) (Table 2). Conclusion There is limited data on the diagnostic workup and follow-up of men presenting with symptoms of dysuria during BMT. This study found that despite a high positivity rate for STIs in symptomatic men, sexual history documentation and STI screening were inconsistent in this population. As males account for the vast majority of basic trainees, efforts to accurately capture the burden of STIs are imperative to limit the impact on military populations. Disclosures All Authors: No reported disclosures

Comparison of the epidemiological characteristics of mycoplasma pneumoniae infections among children during two epidemics in Wuhan from 2018 to 2024

BackgroundMycoplasma pneumoniae (M pneumoniae, MP) is a common pathogen causing respiratory tract infections, particularly in children. In 2023, a resurgence of MP epidemics was observed in Wuhan, Hubei Province, China. This study aims to examine the epidemiological trends and clinical characteristics of MP infections among children in Wuhan from 2018 to 2024, providing valuable scientific evidence to guide local prevention strategies.MethodsFrom January 1, 2018, to June 30, 2024, samples were collected from children under 14 years with Acute Respiratory Tract Infections (ARTI) at Renmin Hospital of Wuhan University. MP infections were diagnosed through MP-IgM antibody detection and MP-DNA detection. Results were analyzed and compared across distinct epidemic periods.ResultsOf the 183 626 ARTI children, 57 393 (31.26%) tested positive for MP, with an average age of 4.87 ± 2.99 years and a male-to-female ratio of 1.12:1. The annual positive rates from 2018 to 2024 were 45.92%, 32.23%, 22.84%, 16.22%, 16.26%, and 42.93%, respectively. Across the study period, the highest positive rate was recored in autumn (35.13%, P < 0.05). Two distinct MP outbreaks were identified, in 2018–2019 and 2023. Significant differences were observed between the two outbreaks. The 2018–2019 epidemic peaked in summer, while the 2023 epidemic peaked in November and persisted into February 2024. By age, the 2018–2019 outbreaks predominantly affected pre-school children, whereas the 2023 outbreaks mainly involved school-aged children. In boths outbreaks, girls had higher positive rates. Antibody and DNA testing results followed similar trends.ConclusionThis study highlights the epidemiological trends and clinical characteristics of MP infections in Wuhan from 2018 to 2024, including two distinct outbreaks with differing seasonal patterns. The MP strain in 2023 appeared to predominantly affect older children.The trends observed suggest that MP infections may persist into the winter of 2024. Enhanced surveillance of respiratory pathogens and early diagnosis and prevention of MP infections in children remain critical in this region.

Classification of CT scan and X-ray dataset based on deep learning and particle swarm optimization.

In 2019, the novel coronavirus swept the world, exposing the monitoring and early warning problems of the medical system. Computer-aided diagnosis models based on deep learning have good universality and can well alleviate these problems. However, traditional image processing methods may lead to high false positive rates, which is unacceptable in disease monitoring and early warning. This paper proposes a low false positive rate disease detection method based on COVID-19 lung images and establishes a two-stage optimization model. In the first stage, the model is trained using classical gradient descent, and relevant features are extracted; in the second stage, an objective function that minimizes the false positive rate is constructed to obtain a network model with high accuracy and low false positive rate. Therefore, the proposed method has the potential to effectively classify medical images. The proposed model was verified using a public COVID-19 radiology dataset and a public COVID-19 lung CT scan dataset. The results show that the model has made significant progress, with the false positive rate reduced to 11.3% and 7.5%, and the area under the ROC curve increased to 92.8% and 97.01%.

Interactive segmentation for accurately isolating metastatic lesions from low-resolution, large-size bone scintigrams.

Bone is a common site for the metastasis of malignant tumors, and Single Photon Emission Computed Tomography (SPECT) is widely used to detect these metastases. Accurate delineation of metastatic bone lesions in SPECT images is essential for developing treatment plans. However, current clinical practices rely on manual delineation by physicians, which is prone to variability and subjective interpretation. While computer-aided diagnosis (CAD) systems have the potential to improve diagnostic efficiency, fully automated segmentation approaches frequently suffer from high false positive rates, limiting their clinical utility.&#xD;Approach: This study proposes an interactive segmentation framework for SPECT images, leveraging the deep convolutional neural networks (DCNN) to enhance segmentation accuracy. The proposed framework incorporates a U-shaped backbone network that effectively addresses inter-patient variability, along with an interactive attention module that enhances feature extraction in densely packed bone regions.&#xD;Main results: Extensive experiments using clinical data validate the effectiveness of the proposed framework. Furthermore, a prototype tool was developed based on this framework to assist in the clinical segmentation of metastatic bone lesions and to support the creation of a large-scale dataset for bone metastasis segmentation.&#xD;Significance: In this study, we proposed an interactive segmentation framework for metastatic lesions in bone scintigraphy to address the challenging task of labeling low-resolution, large-size SPECT bone scans. The experimental results show that the model can effectively segment the bone metastases of lung cancer interactively. In addition, the prototype tool developed based on the model has certain clinical application value.

The Epidemiology and Clinical Burdens of Human Parainfluenza Virus Infections Amongst Hospitalized Children Under 5 Years of Age in Jordan: A National Multi-Center Cross-Sectional Study

Human parainfluenza virus (HPIV) is a major cause of respiratory illnesses in children under five years, with clinical manifestations ranging from mild upper respiratory tract infections to severe lower respiratory tract diseases. This multi-center, cross-sectional study investigated the burden, clinical features, and predictors of respiratory viral infections in hospitalized children across four sites in Jordan. Nasopharyngeal specimens from 1000 eligible children were analyzed. In this article, we focused on HPIV infections. The overall HPIV positivity rate was 22.6%, with HPIV-3 accounting for 90.3% of cases. Significant geographic variability was observed, with higher positivity rates in the southern region. HPIV-positive cases frequently presented with symptoms like nasal congestion, tachypnea, and poor feeding. Co-infections with respiratory syncytial virus (RSV) or influenza were associated with worse outcomes, including an increased need for invasive ventilation. The logistic regression identified male gender, asthma, and respiratory acidosis as predictors of complications. Geographic differences in HPIV prevalence and severity were notable, emphasizing the influence of environmental and socioeconomic factors. These findings underscore the urgent need for enhanced HPIV surveillance, targeted public health interventions, and vaccine development to mitigate the disease burden. This study provides critical insights that guide healthcare strategies and improve outcomes in young children at risk of severe HPIV infections.

Unmasking the potential: a historical perspective on the evolution of exfoliative cytology in oral cavity neoplasms.

Exfoliative cytology has proven to be a valuable diagnostic tool in the early detection of malignant neoplasms. However, its application in the oral cavity has been met with skepticism and limited investigation due to the perception that clinical examination alone is sufficient for early diagnosis. Nonetheless, recent research efforts have focused on the utility of exfoliative cytology in oral cavity neoplasms, motivated by the high mortality rate associated with oral cancer. This manuscript reviews the historical development of exfoliative cytology in the oral cavity, highlighting key findings and advancements in the field. Early studies demonstrated the presence of neoplastic cells in oral cavity lesions and emphasized the diagnostic potential of cytology. Subsequent research explored different staining methods and observed the differential reaction of oral cavity cells to radiation therapy. The diagnostic accuracy of exfoliative cytology was reported to be as high as 92%, with a significant number of cases diagnosed as carcinomas without any clinical suspicion. The technique also proved valuable in identifying precancerous and dysplastic lesions and obviating the need for unnecessary biopsies. The manuscript delves into the difficulties encountered in sampling techniques and stresses the significance of appropriate specimen collection and handling. Various staining methods, including Papanicolaou and acridine orange, were utilized for cytological analysis. The manuscript emphasizes the extensive use of exfoliative cytology in oral cavity examinations and stresses the importance of recognizing it as a crucial diagnostic tool. Various studies have reported high positivity rates and the detection of clinically unsuspected malignant lesions. The authors recommend extensive use of exfoliative cytology in routine practice and underscore the necessity of proper sampling and evaluation techniques.

EVALUATION OF THE MOSAIC 7 TEST FOR THE DIAGNOSIS OF IMMUNOBULLOUS SKIN DISEASE

Objective: To determine the positive rate of the Mosaic 7 test in autoimmune bullous diseases at the National Hospital of Dermatology and Venereology. Materials and methods: A cross-sectional retrospective study was conducted on 44 medical records and serology of patients with autoimmune bullous diseases at the National Hospital of Dermatology and Venereology from October 2021 to September 2022. Data collected included gender, age, diagnosis, histopathology results, indirect immunofluorescence, direct immunofluorescence, and Mosaic 7 test results. Result: Of the 44 patients with autoimmune bullous diseases, 22 had pemphigus vulgaris, 5 had pemphigus foliaceus, and 17 had bullous pemphigoid. The Mosaic 7 test results varied among the different types of bullous diseases. In pemphigus vulgaris patients, the Mosaic 7 test showed a high positive rate on the esophageal well (90.9%), Desmoglein 1 well (95.5%), and Desmoglein 3 well (86.4%). In pemphigus foliaceus patients, the test showed a 100% positive rate on the esophageal and Desmoglein 1 wells, but 0% on the Desmoglein 3 well. In bullous pemphigoid patients, the positive rates varied across different wells of the Mosaic 7 test. Conclusion: The Mosaic 7 test demonstrated high utility in diagnosing autoimmune bullous skin diseases, particularly in identifying Desmoglein 1 and Desmoglein 3 in pemphigus vulgaris. However, further studies with larger sample sizes are warranted to validate and refine the test's accuracy. Received 10 April 2023Revised 08 June 2023Accepted 03 November 2023

Recent HCMV infection in early pregnancy associates with congenital transmission &amp; adverse pregnancy outcome: A prospective cohort study

Background &amp; objectives Human Cytomegalovirus (HCMV) infection, leading to &gt;90 per cent seropositivity in women of reproductive age from India, is the largest cause of congenital infections worldwide. HCMV infection status was prospectively monitored together with congenital transmission (cCMV) and adverse pregnancy outcomes (APO) in a public health setting where maternal or neonatal screening was not in practice. Methods Eighty three pregnant women, with (n=45) and without (n=38) bad obstetric history (BOH), were monitored for HCMV infection by ELISA-(IgM, IgG, IgG avidity) for all TORCH (Toxoplasma, Rubella, HCMV, HSV 1 &amp; 2) pathogens along with HCMV-specific chemiluminescent microparticle immunoassay (CMIA) and nested polymerase chain reaction (PCR). Descriptive statistics were applied on data sets to determine associations between maternal infection status, pregnancy outcome and cCMV in 52 mother-neonate dyads. Results Combined avidity, PCR-based and HCMV IgM screening, compared to the latter alone, was successful in identifying incident infection during early pregnancy. Pregnancy loss was associated strongly with BOH and concurrent HCMV infection. Features associated with APO and cCMV, were high PCR positivity (first trimester) and high rates of HCMV-specific IgM and intermediate IgG avidity (P=0.0211, 0.0455). Also, recent HCMV infection (intermediate IgG avidity), observed mainly in the BOH group, but not recurrent infection (IgM positivity), in first and second trimesters, was associated with neonatal saliva positivity and adverse outcomes, including neonatal death (P=0.0762). Exposure to other TORCH pathogens, while detected, did not include IgM positivity or low/intermediate IgG. Conclusion This study highlights the significance of conducting early, multi-pronged screening for maternal HCMV infection during pregnancy, especially in public health settings with high HCMV seroprevalence.

UniEmbed: A Novel Approach to Detect XSS and SQL Injection Attacks Leveraging Multiple Feature Fusion with Machine Learning Techniques

Abstract Web applications are essential in the digital age, but their security vulnerabilities expose sensitive data and organizational integrity to sophisticated attacks. Among the most prevalent and damaging vulnerabilities in web applications are cross-site scripting (XSS) and SQL injection attacks. In this paper, we introduce UniEmbed, a unified approach for detecting XSS and SQL injection attacks using machine learning classifiers. This novel approach leverages natural language processing techniques, combining features from Word2Vec, the Universal Sentence Encoder (USE), and FastText to extract meaningful data from web applications. Extensive experiments were conducted using various machine learning classifiers on three benchmark datasets to evaluate the performance of the unified detection approach, demonstrating exceptional results. Experimental results demonstrate the superior performance of the MLP classifier. For the XSS attack dataset, the MLP classifier achieved an accuracy of 0.9982 and an F1-score of 0.9983, with minimal false positives and false negatives. Similarly, the hard voting classifier yielded the same outstanding results. For SQL injection attacks, the MLP classifier maintained exceptional performance, achieving an F1-score of 0.9980 and accuracy rates exceeding 0.9980 across two datasets. The classifier effectively minimized false positives and false negatives. The ROC curves further corroborate the effectiveness of the proposed method, indicating high true positive rates and low false positive rates. Furthermore, comparative analysis showed that the UniEmbed method consistently outperformed individual feature extraction methods across all classifiers. These findings indicate that the proposed UniEmbed method, particularly when combined with the MLP classifier, is highly effective in detecting both XSS and SQL injection attacks, making it a promising approach for enhancing web application security.

In-Vehicle Network Anomaly Detection Based on a Graph Attention Network

&lt;div&gt;The increased connectivity of vehicles expands the attack surface of in-vehicle networks, enabling attackers to infiltrate through external interfaces and inject malicious traffic. These malicious flows often contain anomalous semantic information, potentially leading to misleading control instructions or erroneous decisions. While most semantic-based anomaly detection methods for in-vehicle networks focus on extracting semantic context, they often overlook interactions and associations between multiple semantics, resulting in a high false positive rate (FPR). To address these challenges, the Adaptive Structure Graph Attention Network Model (AS-GAT) is proposed for in-vehicle network anomaly detection. Our approach combines a semantic extractor with a continuously updated graph structure learning method based on attention weight similarity constraints. The semantic extractor identifies semantic features within messages, while the graph structure learning module adaptively updates the graph structure based on attention weights between semantics. This model effectively learns relationships between multiple semantics in in-vehicle network packets, thereby enhancing anomaly detection accuracy. A case study on a CAN-FD dataset from real vehicles demonstrates that using AS-GAT achieves an F1 score of 97.56% in anomaly detection, outperforming baseline methods by effectively identifying attack packets causing abnormal semantic time series changes, such as fuzzing, spoofing, and replay attacks. Additional experiments on two public datasets, SWaT and WADI, further validate AS-GAT’s superior anomaly detection performance compared to baseline models, highlighting the universal applicability of our approach.&lt;/div&gt;

PAH-Finder: A Pattern Recognition Workflow for Identification of PAHs and Their Derivatives.

Polycyclic aromatic hydrocarbons (PAHs) are pervasive environmental pollutants with significant health risks due to their carcinogenic, mutagenic, and teratogenic properties. Traditional methods for PAH identification, primarily relying on gas chromatography-mass spectrometry (GC-MS), utilize spectral library searches together with other techniques, such as mass defect analysis. However, these methods are limited by incomplete spectral libraries and a high false positive rate. Here, we present PAH-Finder, a data-driven workflow that integrates machine learning with high-resolution mass spectrometry (HRMS). PAH-Finder introduces a novel approach to evaluate the fragment distribution of PAH backbones in MS spectra by normalizing fragment m/z values to a 0-100% range relative to the molecular ion peak. Seven machine learning features capture PAH fragmentation characteristics, and a random forest model trained on 98 PAH spectra and 1003 background spectra achieved an F1 score of ∼0.9 in 5-fold cross validation. Additionally, PAH-Finder leverages the presence of doubly charged fragments and molecular formula prediction to enhance the identification accuracy. In a case study, PAH-Finder identified 135 PAHs, including 7 types of previously unreported PAH formulas in particulate matter samples, demonstrating a 246% increase in annotation efficiency compared to the NIST20 library search. It also identified 32 heteroatom-doped PAHs not included in the training data set, showcasing its robustness of generalization. PAH-Finder's high accuracy in detecting a broad spectrum of PAHs facilitates efficient data processing and interpretation for nontargeted analysis, enhancing our understanding of air pollution and public health protection. PAH-Finder is freely available at Github (https://github.com/FangLabNTU/PAH-Finder).

Analysis of antibody detection data of Mycoplasma pneumoniae in a hospital in Beijing City from 2017 to 2024

Objective: To explore the distribution characteristics of Mycoplasma pneumoniae (MP) antibody detection data in hospital, provide data reference for the prevention and control of MP infections. Methods: A single-center retrospective study was conducted on 20 639 patients with suspected Mycoplasma pneumoniae (MP) infection from March 2017 to February 2024 at the outpatient, emergency, and inpatient departments of Peking University Third Hospital. The age range was from 0 to 105 years, with 11 286 males and 9 353 females. The passive agglutination method was used to detect MP antibodies in patient serum, and SPSS 22.0 statistical software was used for statistical analysis. The χ2 test was used to analyze the differences in positive rates of MP antibodies among different genders, age groups, seasons, years, and antibody titers. The trend χ2 test was used to analyze the trend of detection rates with age changes. Results: Among the 20 639 patients, the positive rate of MP antibodies was 23.19%(4 786/20 639), with a higher positive rate in females was 27.16%(2 540/9 353) compared to males (19.90%, 2 246/11 286;χ²=151.191, P<0.01). The positive rate in children was 37.13%(2 731/7 356)significantly higher than in adults(15.47%, 2 055/13 283;χ²=1 246.433, P<0.01). The 6 to <12 year age group (63.11%, 1 223/1 938) had the highest positive rate of MP antibodies, followed by 12 to <18 year old group (56.78%, 385/678). The positive rate of MP antibodies increased with age from 0 to 12 years old but gradually decreased after 12 to <18 years old (χ2=3 848.393, P trend<0.01). The annual MP antibody positivity rates from 2017 to 2023 were 26.92%, 29.23%, 27.46%, 18.43%, 17.16%, 11.89%, and 23.72%, respectively, with statistically significant differences among the years (χ²=387.519, P<0.01). The MP antibody positive rate was high in autumn over the course of 7 years (χ²=242.560, P<0.01). The positive rates of MP antibodies for the years 2017-2019, 2020-2022, and 2023-2024 are (28.00%, 16.60%, 21.84%), respectively, with statistically significant differences among the three periods(χ²=295.845, P<0.01).The monthly positive rates of MP antibody in different years were (5.63% to 43.11%). In the MP antibody titer, qualitative testing was conducted on 4 563 patients and 16 076 patients had a semi-quantitative MP antibody titer of ≥1∶160 with a positive rate of 16.03%(2 577/16 076). Among the proportion of children with high titers of MP antibodies ≥1∶1 280 was 11.11%(798/7 182). Conclusion: The positive rates of MP antibodies in hospital in the Beijing area vary among different genders, ages, and seasons, with a higher incidence in autumn, mainly among children and adolescents.

Hyperhomocysteinemia-associated Thrombosis in Patients With Pernicious Anemia.

Cobalamin deficiency (CD) due to pernicious anemia (PA) leads to hyperhomocystinemia, a risk factor for thrombosis. However, the clinical presentations and outcomes of hyperhomocystinemia-associated thrombosis (HAT) are not fully understood. We undertook a literature search using PUBMED, SCOPUS and WEB OF SCIENCE databases for the terms "pernicious anemia AND thrombosis", "pernicious anemia AND embolism", "pernicious anemia AND thromboembolism", "autoimmune gastritis AND thrombosis", "autoimmune gastritis AND embolism", "autoimmune gastritis AND thromboembolism" through January 2024 and reviewed the published literature. Our aim was to illustrate the clinical features of PA-related HAT. Of 20 patients, the median age was 54.5 years (60 % males). 35 % of patients were elderly. The median serum homocysteine level was 67.75 umol/L. 35 % of patients developed thromboses at multiple locations while 20 % had thromboses at unusual sites. 45 % of patients had co-existing neuropsychiatric symptoms. 80 % of patients were positive for anti-IF (anti-intrinsic factor) antibodies. All patients received cobalamin replacement and the median duration of antithrombotic therapy was 6.5 months for reported cases. None developed recurrent thromboembolism. This rare condition is associated with high incidence of thromboses at unusual sites, multiple-site thromboses, co-existing neuropsychiatric symptoms, high positivity rate for anti-IF antibodies and low recurrent thrombosis rate.

Modifiable risk factors for culture positivity after primary Latarjet procedure. Should we change any practice?

The prevalence of positive cultures in primarily operated shoulders represents a growing concern. Previous studies have documented high rates of culture positivity in primary prosthetic shoulder surgery, yet the Latarjet procedure has not been specifically explored in this context. The aim of this study was to identify the rate of culture positivity in patients treated with a primary Latarjet procedure, and to identify risk factors for culture positivity. This prospective, multicentric study conducted between September 2021 and October 2022 targeted patients undergoing primary open Latarjet procedures. Patients with a history of shoulder surgery were excluded. Six deep preoperative bacteriological samples were collected: three from soft tissues (capsulolabral) and three from bony (glenoid) areas. The primary outcome was the rate of culture positivity. Secondary outcomes included the type of germs and the rate of complications. Risk factor analysis for positive cultures was undertaken using both univariate and multivariate analyses. This study encompassed 122 patients with a mean age of 26.63 ± 7.45. The rates of having at least 1, 2, and 3 cultures positive were 44.8%, 40.16%, and 34.43%, respectively. Predominantly, cultures yielded Cutibacterium acnes in 96.2% of cases. Multivariate analysis identified one main risk factor for culture positivity: preoperative shoulder CT arthrogram (CTA) use (OR = 4.44, 95% CI [1.65 - 11.9], p = 0.003) for at least one positive culture. For at least 2 positive cultures, ORs were 4.17 (p = 0.005) for CTA and 3.88 (p = 0.009) (p < 0.001) for at least 3 positive cultures. Elimination the identified modifiable risk factors reduced the rate of positive cultures to 29.27%, 24.39%, and 19.51% for at least 1, 2, and 3 positive cultures. One patient who had positive culture experienced early sepsis caused by Cutibacterium acnes. This study showed a high rate of positive cultures in Latarjet patients post surgeries. Analysis highlighted preoperative CTA use as a significant risk factor, increasing positive culture risk fourfold.

E-Cadherin-Mediated Cell-Cell Adhesion and Invasive Lobular Breast Cancer.

E-cadherin is a transmembrane protein and central component of adherens junctions (AJs). The extracellular domain of E-cadherin forms homotypic interactions with E-cadherin on adjacent cells, facilitating the formation of cell-cell adhesions, known as AJs, between neighbouring cells. The intracellular domain of E-cadherin interacts with α-, β- and p120-catenins, linking the AJs to the actin cytoskeleton. Functional AJs maintain epithelial tissue identity and integrity. Transcriptional downregulation of E-cadherin is the first step in epithelial-to-mesenchymal transition (EMT), a process essential in development and tissue repair, which, in breast cancer, can contribute to tumour progression and metastasis. In addition, loss-of-function mutations in E-cadherin are a defining feature of invasive lobular breast cancer (also known as invasive lobular carcinoma (ILC)), the second most common histological subtype of breast cancer. ILC displays a discohesive, single-file invasive growth pattern due to the loss of functional AJs. Despite being so prevalent, until recently there has been limited ILC-focused research and historically ILC patients have often been excluded from clinical trials. Despite displaying a number of good prognostic indicators, such as low grade and high rates of estrogen receptor positivity, ILC patients tend to have similar or poorer outcomes relative to the most common subtype of breast cancer, invasive ductal carcinoma (IDC). In ILC, E-cadherin loss promotes hyperactivation of growth factor receptors, in particular insulin-like growth factor 1 receptor, anoikis resistance and synthetic lethality with ROS1 inhibition. These features introduce clinical vulnerabilities that could potentially be exploited to improve outcomes for ILC patients, for whom there are currently limited tailored treatments available.

Serum mature microRNA panel: A novel approach for primary prostate cancer diagnosis.

Prostate cancer (PC) is the second most common malignant tumor in males and a leading cause of cancer-related morbidity and mortality among men. Early detection is essential for improving outcomes. Although prostate-specific antigen (PSA) is widely used for PC screening, it suffers from high false positive and false negative rates. Our study aimed to identify a panel of serum mature microRNAs (miRNAs) for PC diagnosis. We conducted a PubMed search to identify candidate mature miRNAs associated with PC. We then used quantitative reverse transcription-polymerase chain reaction (RT-qPCR) to assess the expression profiles of these mature miRNAs in serum samples from 112 PC patients and 112 healthy controls (HCs). We selected mature miRNAs with favorable diagnostic potential by analyzing receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC). Subsequently, we developed a highly diagnostically efficient panel of three mature miRNAs using stepwise logistic regression based on their expression levels. We identified three mature miRNAs (hsa-miR-143-5p, hsa-miR-23b-3p, and hsa-miR-148b-3p) with significant diagnostic value, constructing a panel with an AUC of 0.891, sensitivity of 84.15%, and specificity of 80.49%. Bioinformatics analysis also revealed LDB3 and RBMS3 as potential therapeutic targets for PC. Our study introduces a novel diagnostic approach by identifying a panel of three mature miRNAs (hsa-miR-143-5p, hsa-miR-23b-3p, and hsa-miR-148b-3p) as novel and non-intrusive biomarkers for PC.