Accurate Diagnosis Research Articles

Study on the correlation between abdominal infection and psychological stress in children based on nucleic acid detection

BACKGROUND Diagnosing and treating abdominal infection in children remains a challenge. Nucleic acid detection, as a rapid and accurate diagnosis tool, has great significance in this field. AIM To investigate the diagnosis and treatment of abdominal infection by nucleic acid detection and its possible correlation with psychological stress in children. METHODS A total of 50 pediatric patients diagnosed with abdominal infections between September 2020 and July 2021 were included in this study. Intra-abdominal pus samples were collected for pathogen culture, drug susceptibility testing, and broad-spectrum bacterial nucleic acid testing. Psychological stress, anxiety, depression, and coping styles were assessed using the coping with a disease (CODI) scale. RESULTS Based on susceptibility testing, a regimen of cefazoxime, piperacillin/tazobactam, and metronidazole or ornidazole achieved 100% effectiveness in treating appendicitis. Psychological assessments revealed a positive correlation between pressure level and both anxiety (r = 0.324, P = 0.001) and depressive disorders (r = 0.325, P < 0.001). Acceptance and distancing as coping strategies were negatively correlated with anxiety and depression, while negative emotional responses were strongly associated with increased anxiety (r = 0.574, P < 0.001) and depression (r = 0.511, P = 0.001). Coping strategies such as illusion and escape showed no significant correlation with emotional outcomes. CONCLUSION Nucleic acid testing helps in the diagnosis of abdominal infections in children, and also focuses on children's mental health.

Protocol and research program of the European registry and biobank for interstitial lung diseases (eurILDreg)

Abstract Background and Aims Interstitial lung diseases (ILDs), encompassing both pediatric and adult cases, present a diverse spectrum of chronic conditions with variable prognosis. Despite limited therapeutic options beyond antifibrotic drugs and immunosuppressants, accurate diagnosis is challenging, often necessitating invasive procedures that may not be feasible for certain patients. Drawn against this background, experts across pediatric and adult ILD fields have joined forces in the RARE-ILD initiative to pioneer novel non-invasive diagnostic algorithms and biomarkers. Collaborating with the RARE-ILD consortium, the eurILDreg aims to comprehensively describe different ILDs, analyze genetically defined forms across age groups, create innovative diagnostic and therapeutic biomarkers, and employ artificial intelligence for data analysis. Methods The foundation of eurILDreg is built on a comprehensive parameter list developed and adopted by clinical experts, encompassing over 1,800 distinct parameters related to patient history, clinical examinations, diagnosis, lung function and biospecimen collection. This robust dataset is further enriched with daily assessments captured through the patientMpower app, including handheld spirometry and exercise tests, conducted on approximately 350 patients over the course of a year. This approach involves app-based daily assessments of quality of life, symptom tracking, handheld spirometry, saturation measurement, and the 1-min sit-to-stand test (1-STST). Additionally, pediatric data from the ChILD-EU registry will be integrated into the RARE-ILD Data Warehouse, with the ultimate goal of including a total of 4.000 ILD patients and over 100.000 biospecimen. Discussion The collaborative efforts within the consortium are poised to streamline research endeavors significantly, promising to advance patient-centered care, foster innovation, and shape the future landscape of interstitial lung disease research and healthcare practices. Trial Registration EurILDreg is registered in the German Clinical Trials Register (DRKS 00028968, 26.07.2022), and eurIPFreg is registered in ClinicalTrials.gov (NCT02951416).

Benefits and Risks of AI in Health Care: Narrative Review

Background The integration of artificial intelligence (AI) into health care has the potential to transform the industry, but it also raises ethical, regulatory, and safety concerns. This review paper provides an in-depth examination of the benefits and risks associated with AI in health care, with a focus on issues like biases, transparency, data privacy, and safety. Objective This study aims to evaluate the advantages and drawbacks of incorporating AI in health care. This assessment centers on the potential biases in AI algorithms, transparency challenges, data privacy issues, and safety risks in health care settings. Methods Studies included in this review were selected based on their relevance to AI applications in health care, focusing on ethical, regulatory, and safety considerations. Inclusion criteria encompassed peer-reviewed articles, reviews, and relevant research papers published in English. Exclusion criteria included non–peer-reviewed articles, editorials, and studies not directly related to AI in health care. A comprehensive literature search was conducted across 8 databases: OVID MEDLINE, OVID Embase, OVID PsycINFO, EBSCO CINAHL Plus with Full Text, ProQuest Sociological Abstracts, ProQuest Philosopher’s Index, ProQuest Advanced Technologies & Aerospace, and Wiley Cochrane Library. The search was last updated on June 23, 2023. Results were synthesized using qualitative methods to identify key themes and findings related to the benefits and risks of AI in health care. Results The literature search yielded 8796 articles. After removing duplicates and applying the inclusion and exclusion criteria, 44 studies were included in the qualitative synthesis. This review highlights the significant promise that AI holds in health care, such as enhancing health care delivery by providing more accurate diagnoses, personalized treatment plans, and efficient resource allocation. However, persistent concerns remain, including biases ingrained in AI algorithms, a lack of transparency in decision-making, potential compromises of patient data privacy, and safety risks associated with AI implementation in clinical settings. Conclusions In conclusion, while AI presents the opportunity for a health care revolution, it is imperative to address the ethical, regulatory, and safety challenges linked to its integration. Proactive measures are required to ensure that AI technologies are developed and deployed responsibly, striking a balance between innovation and the safeguarding of patient well-being.

How Automation in Electronic Medical Records Can Lead to Errors in Dermatology

The integration of electronic health records has revolutionized healthcare by facilitating communication among providers, but it has also introduced significant challenges. In dermatology, a particular issue arises with the use of electronic medical record (EMR) systems that employ auto-populated fields on digital pathology requisition forms (RFs) for skin biopsies. These systems allow for the rapid selection of pre-set descriptions and differential diagnoses, which, while timesaving, frequently lead to diagnostic inaccuracies and potentially detrimental impacts on patient care. Dermatopathologists often receive biopsy specimens with RFs that list multiple provisional diagnoses based on generic, EMR-generated descriptions, which may not accurately represent the patient’s condition. This practice hampers the ability of dermatopathologists to perform effective clinicopathologic correlation, crucial for accurate diagnosis. We highlight that the convenience of EMR systems can discourage clinicians from recording detailed, accurate clinical observations. Consequently, this lack of detailed documentation prevents dermatopathologists from making informed diagnoses by correlating histologic features with clinical appearances. The current practice of using EMRs without consideration for their clinical relevance not only wastes healthcare resources but also poses a significant medico-legal risk. Therefore, refining EMR practices and integrating more comprehensive clinical data will ensure greater accuracy in dermatological diagnoses.

Blood Gene Expression Profiling and Donor-derived Cell-free DNA to Noninvasively Diagnose Clinical and Subclinical Kidney Transplant Rejection: A Real-life Appraisal Study

Background. Peripheral blood biomarkers aim to noninvasively diagnose kidney allograft rejection, but most lack robust independent validation. TruGraf is intended to exclude subclinical cellular rejection (TCMR), whereas donor-derived cell-free DNA Viracor-TRAC has proven value in excluding antibody-mediated rejection (AMR). We aim to validate both biomarkers for accurate rejection diagnosis in a real-world clinical setting. Methods. We prospectively included 230 unselected, consecutive kidney transplants from 6 centers undergoing for-cause and protocol biopsies with paired blood samples from December 2021 to 2022. TruGraf and Viracor-TRAC were blindly run by a central laboratory. Results. The incidence of rejection was 22.6% (17.3% surveillance; 27% for-cause biopsies). Inflammation was associated with higher TRAC levels, with AMR/mixed and microvascular inflammation (MVI) showing the highest levels (P < 0.05). TruGraf did not associate with any specific allograft injury. No biomarkers, individually or combined, accurately diagnosed any rejection (area under the receiver operating characteristic curve [AUROC] < 0.65). However, high TRAC levels, when combined with DSA in for-cause biopsies, predicted AMR/mixed rejection or MVI (AUROC = 0.817; P < 0.001), outperforming serum creatinine and DSA (AUROC < 0.65). Conclusions. In this large, prospective, observational real-life study, we were unable to validate TruGraf and TRAC to diagnose rejection but found a useful context of use for TRAC to noninvasively diagnose AMR/mixed or MVI in conjunction with DSA in dysfunctioning graft.

Feasibility of Peroral Cholangioscopy in the Initial Endoscopic Retrograde Cholangiopancreatography for Malignant Biliary Strictures

Background: Peroral cholangioscopy (POCS) is valuable for assessing malignant biliary strictures; however, biliary drainage prior to POCS often hinders accurate diagnosis. Objectives: This retrospective study aimed to investigate the feasibility of POCS using a newly developed cholangioscope, CHF-B290, during initial endoscopic retrograde cholangiopancreatography (ERCP) for malignant biliary strictures. Methods: This multicenter retrospective study included patients who underwent initial ERCP for malignant biliary strictures at two institutions between January 2018 and March 2022. Patients who underwent initial ERCP with POCS were classified into the POCS group, and those without POCS were classified into the non-POCS group. To prevent post-POCS cholangitis, the original irrigation system for CHF-B290 was used in all POCS examinations. The primary endpoint was the rate of post-ERCP biliary infections, and the secondary endpoints were other ERCP-related complications, including pancreatitis, bleeding, and perforation. Results: Overall, 53 and 94 patients were included in the POCS and non-POCS groups, respectively. For the primary endpoint, the rate of post-ERCP biliary infection was not significantly different between the two groups (1.9% vs. 5.3%, p = 0.42). For the secondary endpoints, no significant differences were observed in the rates of post-ERCP pancreatitis (5.7% vs. 6.4%, p = 1.00) and other ERCP-related complications. The overall complication rate was 9.4% in the POCS group and 13% in the non-POCS group (p = 0.60). Conclusions: POCS during the initial ERCP for malignant biliary strictures is feasible.

Haematological and Biochemical Profiles, Including Vitamin A and Zinc Status, in Clinical and Subclinical Oriental Theileriosis in Cattle

Aim: The present study investigated the clinical, haematological and biochemical profiles in cattle infected with Theileria orientalis, correlating disease severity with various parameters. Study Design: A total of 32 clinically ill, 10 subclinically infected, and 10 healthy control animals were included. Place and Duration of Study: Department of Veterinary Epidemiology and Preventive Medicine, College of Veterinary and Animal Sciences, Kerala Veterinary and Animal Sciences University, Pookode, Wayanad, Kerala, between November 2023 to September 2024. Methodology: Theileria piroplasms, observed via Giemsa staining, appeared as thick and thin rods with trailing cytoplasm and annular, pyriform, garland, and signet-ring shapes. PCR amplification of the T. orientalis major piroplasm surface protein (MPSP) yielded a specific 776 bp product in clinically and subclinically infected animals. Results: Haematological analysis revealed significant anaemia and thrombocytopenia in infected groups, without notable changes in leukocyte counts. Serum protein analysis indicated hypoproteinemia and hypoalbuminemia, while liver enzymes, particularly AST, were elevated in clinically infected cattle, suggesting hepatic involvement. Additionally, serum vitamin A and zinc concentrations were significantly lower in infected cattle, underscoring a possible role for oxidative stress in disease pathogenesis. Conclusion: These findings suggest that T. orientalis infection is associated with multi-systemic impacts, including haematological abnormalities, liver damage, and nutrient deficiencies, which are crucial for accurate diagnosis and effective management strategies.

Studies of Colletotrichum species causing cowpea anthracnose in Nigeria reveal two first-time reports globally

AbstractCowpea (Vigna unguiculata (L.) Walp.) is an important multipurpose crop in various countries in sub-Saharan Africa. However, cowpea production is affected by cowpea anthracnose disease (CAD). In Nigeria, Colletotrichum lindemuthianum and C. destructivum have been described as causal agents of CAD based on morphological features. Such characterization is unreliable because many similarities among and within Colletotrichum spp. exist. In the current study, Colletotrichum spp. were isolated from leaves showing CAD symptoms collected in farmers’ fields across four states in Nigeria. Isolates were characterized using morphological keys, severity scores in detached leaf assays, and sequencing of the ITS, ACT, GADPH, TUB, ApMat, and CAL genes. Two species, C. chrysophilum and C. siamense, were identified after comparing multigene sequences. Morphological characteristics and disease symptoms were very similar for both species. However, severity scores varied among and within species. Both C. chrysophilum and C. siamense are reported for the first time as causal agents of CAD across the globe. The accurate diagnosis of organisms causing CAD in the studied region will allow developing effective management strategies.

A Case of Acute Necrotizing Encephalitis Misdiagnosed as Opium Poisoning: A Case Report

Introduction: The coronavirus has been associated with significant neurologic complications, including encephalopathy, seizures, ataxia, and motor or sensory deficits. Among these complications, acute necrotizing encephalopathy (ANE) is a rare condition linked to viral infections such as influenza, HHV-6, and COVID-19. This study presents a unique case of ANE in a COVID-19 patient, initially misdiagnosed as opium poisoning. Despite the reduction in pandemic cases, COVID-19 continues to present serious side effects, emphasizing the need to recognize potential neurological manifestations of the virus. Increased awareness and accurate diagnosis are essential for managing these complex cases. Case Presentation: This case study involves a 29-year-old female patient presenting with loss of consciousness and other symptoms that led to a diagnosis of COVID-19-related acute necrotizing encephalitis. Initial suspicions of opium poisoning were ruled out, and imaging tests revealed bilateral ground-glass opacities (GGO) and consolidation in the chest, along with abnormal findings in the brain. The patient was treated with glucocorticoid pulse therapy and IVIG, resulting in symptom improvement, though some neurological deficits persisted at discharge. This case underscores the importance of considering COVID-19 in cases of acute encephalitis and highlights the neurological complications associated with the virus. Conclusions: This study explores ANE as a severe manifestation of COVID-19 infection, focusing on the diverse neurological presentations associated with ANE in COVID-19 patients and a case initially misdiagnosed as opium poisoning. Through a case study of a patient with ANE, characterized by loss of consciousness and meiotic pupils, the research emphasizes the need for early detection and appropriate treatment. Findings suggest that ANE in COVID-19 patients can present with varied symptoms, posing diagnostic challenges. The study underscores the value of timely intervention with glucocorticoid pulse therapy and gamma globulin injection to improve patient outcomes. These findings highlight the necessity for increased awareness among healthcare providers to promptly recognize ANE in COVID-19 patients, aiding in timely and effective intervention.

Rotor angle stability of a microgrid generator through polynomial approximation based on RFID data collection and deep learning.

The article proposes a novel approach to assess rotor angle stability in microgrids by enhancing the Modified Galerkin Method (MGM), which is based on the Polynomial Approximation, using real-time RFID data acquisition. Due to their reliance on assumptions, traditional rotor angle stability methodologies frequently fail in online transient stability testing. MGM successfully captures the dynamic behavior of microgrids by approximating state variables using a sequence of polynomials and coefficients. Redundant data, like as vibrations or noise signals, can cause delays in defect diagnosis and decrease diagnostic accuracy. This problem is addressed by integrating RFID technology. RFID technology could potentially be used with a hybrid CNN-LSTM model to develop a sophisticated fault diagnostic system. This entails identifying fault characteristics through the use of signal processing techniques and feature extraction methods, such as the Fourier transform and time-domain statistical features. In addition, we use Total Harmonic Distortion (THD) to reduce superfluous data. The suggested techniques significantly increase fault detection efficiency and precision, outperforming existing techniques with a 0.94 classification accuracy. An extensive case study on an IEEE 3-machine 9-bus system is used to illustrate its efficacy, showing observable improvements in fault detection speed and accuracy that make microgrid operations safer and more dependable.

Expression of TSPAN1 and its link to thyroid nodules: one step forward on the path to thyroid tumorigenesis biomarkers.

Thyroid cancer is ranked as the most common malignancy within the endocrine system and the seventh most prevalent cancer in women globally. Thyroid malignancies require evaluating biomarkers capable of distinguishing between them for accurate diagnosis. We examined both mRNA and protein levels of TSPAN1 in plasma and tissue samples from individuals with thyroid nodules to aid this endeavour. In this case-control study, TSPAN1 was assessed at both protein and mRNA levels in 90 subjects, including papillary thyroid cancer (PTC; N = 60), benign (N = 30), and healthy subjects (N = 26) using enzyme-linked immunosorbent assay (ELISA) and SYBR-Green Real-Time PCR, respectively. TSPAN1 plasma levels were decreased in PTC and benign compared to healthy subjects (P = 0.002). TSPAN1 mRNA levels were also decremented in the tumoral compared to the paired normal tissues (P = 0.012); this drop was also observed in PTC patients compared to benign patients (P = 0.001). Further, TSPAN1 had an appropriate diagnostic value for detecting PTC patients from healthy plasma samples with a sensitivity of 76.7% and specificity of 65.4% at the cutoff value < 2.7 (ng/ml). TSPAN1 levels are significantly reduced in patients with benign and PTC, demonstrating its potential value as a diagnostic biomarker. Additionally, the significant reduction in TSPAN1 mRNA expression within PTC tumor tissues may suggest its involvement in tumor progression and development. Further studies, including larger-scale validation studies and mechanistic investigations, are imperative to clarify the molecular mechanisms behind TSPAN1 and, ultimately, its clinical utility for treating thyroid disorders.

Radioiodinated Nanobody immunoPET probe for in vivo detection of CD147 in pan-cancer.

To develop the extracellular matrix metalloproteinase inducer (CD147)-targeting therapeutic strategies, accurate detection of CD147 expression in tumors is crucial. Owing to their relatively low molecular weights and high affinities, nanobodies (Nbs) may be powerful candidates for cancer diagnosis and therapy. In this study, we developed a novel CD147-targeted nanobody radiotracer, [124I]I-NB147, which provides guidance for the noninvasive detection of CD147-overexpressing cancers. CD147 expression in human cancers was detected via immunohistochemistry (IHC) on tissue microarrays (TMAs). Western blot (WB) and flow cytometry were used to screen CD147-positive malignant melanoma (MM), triple-negative breast cancer (TNBC), and pancreatic cancer (PCA) cell lines. The CD147 nanobody (NB147) was labeled with [124I]INa using Iodogen as the oxidizing agent and was purified by the PD-10 column. The physicochemical properties, affinity, metabolic characteristics, biodistribution, and immunoPET imaging of [124I]I-NB147 were evaluated Moreover, [18F]F-FDG was used as a control. Finally, CD147 expression analysis was performed via multiplex immunofluorescence (MxIF) and autoradiography on human cancer specimens and tumor-bearing mice tissues. TMAs results revealed that CD147 is highly expressed in MM, TNBC, and PCA. A CD147-specific nanobody, NB147, was successfully generated with excellent in vitro binding characteristics. [124I]I-NB147 was obtained with high radiochemical yield and purity, and was stable for at least 4h in vitro. WB and FCM revealed that CD147 was positive in A375, MDA-MB-435 and ASPC1 cells, whereas SK-MEL-28, 4T1 and BXPC3 cells presented low expression levels. The radio-ELISA results indicated that [124I]I-NB147 had a high binding affinity to CD147. The uptake of [124I]I-NB147 was significantly different between CD147 high-expression cells and CD147 low-expression cells (P < 0.001). The biological half-life of the distribution and clearance phases were 0.05h and 1.58h, respectively. In CD147-positive tumor models, the [124I]I-NB147 accumulated in A375, MDA-MB-435, and ASPC1 tumors, and the uptake value was significantly higher than that of [18F]F-FDG. Uptake in SK-MEL-28, BXPC3, and 4T1 tumors was not clearly observed. Finally, through autoradiography and histological studies, the correlation analysis between tumor uptake and CD147 expression level was determined. The high expression of CD147 in MM, TNBC, and PCA tissuesand in tumor cells was verified. The CD147 nanobody, NB147 was produced and radiolabeled to obtain the immunoPET probe, [124I]I-NB147, which showed high affinity to CD147 and precise visualization for accurate diagnosis of CD147-expressing lesions in different cancers. These results provide insight into the imaging and binding properties of nanobody NB147 over extended periods of time, reinforcing its potential in developing radionuclide therapies for CD147-positive cancer patients.

Metanephrine mirage: distinguishing the phaeocopies, a case report and literature review.

We present one of only seven reported cases of a catecholamine-secreting adrenal neuroblastoma in an adult. The case is used as a platform to discuss key biochemical, genomic and imaging considerations that are central to the successful, targeted management of catecholamine-secreting adrenal tumours. A 63-year-old male was urgently reviewed at a tertiary hospital endocrinology outpatient clinic for a 12cm right-sided adrenal incidentaloma. Plasma normetanephrine and 3-methoxytyramine levels were approximately 10 times the upper limit of normal at 9272pmol/L (< 900) and 1023pmol/L (< 110), respectively. The adrenal mass appeared to be inseparable from the liver on imaging, and thus wassuspected to be an invasive malignant phaeochromocytoma. FDG positron emission tomography (PET)/CT demonstrated moderate to intense metabolic activity within the right adrenal mass. [68Ga]Ga-DOTATATE (Ga-TATE) PET-CT demonstrated patchy, heterogenous somatostatin receptor (SSTR) expression in the adrenal lesion, at most Krenning 3 (intensity above liver). The patient underwent a right adrenalectomy and segment 6/7 liver resection. Histopathology revealed a 130mm diameter neuroblastoma of the differentiating subtype with a low Mitosis-Karyorrhexis Index. There was lymphovascular invasion and tumour focally present at the resection margin, but no tumour in one periadrenal lymph node, and no tumour invasion in the adherent liver. Immunohistochemistry revealed ALK positivity (+ 3) and wild type ATRX. At nine months following adrenalectomy, the plasma normetanephrine level has reduced to 991pmol/L (< 900). Post-operative GaTate PET/CT shows no definite abnormal SSTR-expressing lesions in the surgical bed or elsewhere. The patient has completed adjuvant radiotherapy and is a candidate for ALK-targeted therapy if required for recurrence in the future. Neuroblastomas may be misdiagnosed as phaeochromocytomas given the ability to secrete catecholamines and similarities in radiological appearance. Differentiating neuroblastomas from phaeochromocytomas and paragangliomas (PPGL) is critical, but clinically difficult. Genomics are central for management; diagnosing ALK-positive neuroblastoma triggers consideration of ALK-targeted therapy, which is not relevant for PPGL. A critical eye is required for the accurate diagnosis and management of malignant adrenal incidentalomas.

Unilateral Vestibular Hypofunction in an Adolescent: Case Report and Literature Review

Objective − The report presents a case of an adolescent girl with vertigo resulting from unilateral vestibular hypofunction, diagnosed after extensive pediatric and otorhinolaryngological evaluations.Case Report − A seventeen-year-old female adolescent sought medical assistance at the pediatric emergency hospital service on several occasions within one year due to feelings of weakness and darkened vision occurring during abrupt standing, exposure to heat, and stress. Symptoms were initially attributed to school obligations, low blood pressure, and the menstrual cycle. After an episode that also involved a brief loss of consciousness, an extensive neurological evaluation was conducted, excluding epileptogenic causes. Subsequent diagnostic procedures included evoked visual potential tests, psychological assessments, laboratory blood tests, thyroid hormone assays, and Borrelia burgdorferi serology, all yielding normal results. Finally, otorhinolaryngological examinations were performed, including pure tone audiometry, tympanometry, video head impulse tests, videonystagmography, and vestibular evoked myogenic potential tests. These tests indicated symptoms arising from unilateral labyrinthine hypofunction of the inner ear. The patient underwent vestibular rehabilitation, resulting in symptom resolution and confirmed functional recovery.Conclusion − Diagnosing vertigo in adolescence is challenging, as impaired balance can manifest as a symptom of various diseases. Presentation with atypical symptoms for peripherally caused balance disorders complicates diagnosis. Otorhinolaryngologists and audio-vestibular diagnosticians play pivotal roles in establishing accurate diagnoses.

Sexually transmitted infections in sexually abused children: an audit project to implement PCR tests in a child advocacy center in Türkiye

Background. Sexual abuse in children can sometimes result in sexually transmitted infections (STIs), which can serve as crucial forensic evidence. Although PCR methods are now accepted as the gold standard for STI screening, they have not yet widely replaced traditional culture methods in Türkiye. This study aims to assess the necessity of implementing PCR-based STI testing at Child Advocacy Centers in Türkiye, where such testing is not routinely available. Methods. Conducted between February and November 2023, this study included children who presented to the Child Advocacy Center of Marmara University Pendik Training and Research Hospital. High-risk victims were identified based on criteria including a history of penetrative sexual abuse and factors such as multiple perpetrators or significant age disparity. Serological tests and genital swabs were collected and analyzed using both bacterial culture methods and a comprehensive STI PCR panel. Results. The study included 20 victims, with a median age of 16 years. STI PCR testing detected pathogens in 19 out of 21 samples, including Chlamydia trachomatis (20%) and Neisseria gonorrhoeae (5%). In contrast, culture methods identified no sexually transmitted pathogens. Conclusion. PCR testing demonstrated significantly higher sensitivity for detecting STIs compared to traditional bacterial culture methods, as expected. Implementing PCR-based STI testing in Child Advocacy Centers is an urgent and essential need for providing an accurate diagnosis and robust forensic evidence, enhancing the care and legal protection of sexually abused children.

Generalized composite multiscale improved diversity entropy and its application to diesel injector fault feature extraction and diagnosis

The diesel injector is the core component of marine diesel engines, and its health monitoring is one of the keys to ensuring the efficient and reliable operation of diesel engines and even ships. However, extracting effective feature information from nonlinear dynamic signals is the difficulty in realizing intelligent fault diagnosis of diesel fuel injectors. The existing diversity entropy (DE) is an advanced algorithm for extracting fault features. Still, it has the problem of failing to obtain sufficiently effective fault features, thus affecting diagnostic accuracy due to its inherent defects. To solve the above problem, a new generalized composite multiscale improved diversity entropy (GCMIDE) is first proposed, and the comparative advantages of the proposed entropy in terms of consistency, robustness, and computational efficiency are verified with common noise-simulated signals. GCMIDE is further utilized as an excellent means of feature extraction, and a new injector fault diagnosis method, GCMIDE-Relieff-SSA-BP, is proposed to meet the needs of efficiency and practicality in fault diagnosis. Finally, the method is adopted for the diagnostic experiments of diesel fuel injectors with different fault types and different fault degrees for full validation. The experimental results all indicate that, in comparison with six commonly used entropy-based fault diagnosis methods, the proposed method has the best feature extraction performance and fault diagnosis accuracy under a different number of features or different training sample ratios. This provides an effective tool for fault diagnosis of injectors and even intelligent operation and maintenance of diesel engines.

Comparative Performance Analysis of Ensemble Models for Breast Cancer Classification

Breast cancer remains a prevalent global health issue, accounting for approximately 2.3 million new cases and 670,000 deaths worldwide in 2022. Early detection and accurate diagnosis are crucial to improving patient outcomes, as delayed identification can lead to severe complications. Advances in machine learning (ML) have facilitated improvements in cancer diagnosis, with various algorithms enhancing predictive accuracy. This study proposes a novel ensemble model for breast cancer classification, utilizing 31 features from the University of Wisconsin Breast Cancer dataset. We applied six algorithms—K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Logistic Regression, Random Forest, Gradient Boosting, and XGBoost—and combined them with ensemble techniques, specifically Hard Voting, to develop a high-accuracy model. The model was evaluated on classification performance metrics, achieving improvements in accuracy, precision, recall, and F1 score. Results indicate that the proposed ensemble model outperforms individual classifiers and other ensembles, showing potential as a reliable tool for early breast cancer detection.

Modern Endoscopic Approaches to Video-Assisted Sentinel Lymph Node Biopsy and Axillary Lymph Node Dissection: A Review

This article aims to analyze modern endoscopic techniques of sentinel lymph node biopsy and axillary lymph node dissection in breast cancer surgery.Owing to more accurate diagnosis and minimized patient morbidity and risks, endoscopic techniques have significantly expanded capabilities of breast cancer surgery.We review the main endoscopic techniques of sentinel lymph node biopsy and axillary lymph node dissection, analyze their efficacy and safety, and compare their benefits with those of conventional open techniques.The article discusses results of recent studies regarding diagnostic accuracy and complication rates. Furthermore, we discuss the impact of endoscopic axillary lymph node dissection on the prognosis and quality of life in patients with breast cancer.

Impact of Feature Selection Techniques on the Performance of Machine Learning Models for Depression Detection Using EEG Data

Major depressive disorder (MDD) poses a significant challenge in mental healthcare due to difficulties in accurate diagnosis and timely identification. This study explores the potential of machine learning models trained on EEG-based features for depression detection. Six models and six feature selection techniques were compared, highlighting the crucial role of feature selection in enhancing classifier performance. This study investigates the six feature selection methods: Elastic Net, Mutual Information (MI), Chi-Square, Forward Feature Selection with Stochastic Gradient Descent (FFS-SGD), Support Vector Machine-based Recursive Feature Elimination (SVM-RFE), and Minimal-Redundancy-Maximal-Relevance (mRMR). These methods were combined with six diverse classifiers: Logistic Regression, Support Vector Machine (SVM), Random Forest, Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Light Gradient Boosting Machine (LightGBM). The results demonstrate the substantial impact of feature selection on model performance. SVM-RFE with SVM achieved the highest accuracy (93.54%) and F1 score (95.29%), followed by Logistic Regression with an accuracy of 92.86% and F1 score of 94.84%. Elastic Net also delivered strong results, with SVM and Logistic Regression both achieving 90.47% accuracy. Other feature selection methods yielded lower performance, emphasizing the importance of selecting appropriate feature selection and machine learning algorithms. These findings suggest that careful selection and application of feature selection techniques can significantly enhance the accuracy of EEG-based depression detection.

CNN-Based Cancer Image Diagnosis: Current Progress and Future Directions

Abstract. With the development of deep learning technology, CNN (Convolutional Neural Network) models have shown great value in medical image analysis, especially in diagnosing early lung cancer, breast cancer, and brain tumors. In this study, we recall and organize the application and progress of CNN models in the field of cancer and tumor diagnosis in the past five years to provide a theoretical basis and reference for related researchers. This article introduces the principles of different CNN cancer diagnostic models and compares and analyzes their results, and ultimately finds that these models have significant advantages in improving the accuracy and efficiency of cancer diagnosis, but at the same time, there are also problems such as too much reliance on large datasets, high model complexity, and poor generalization ability. In the future, we can consider optimizing the performance of CNN network models, enhancing the generalization ability of the models, and developing data enhancement techniques on this basis, so that CNN models can be better applied in the field of cancer diagnosis.