Metagenomic Next-Generation Sequencing as an Effective Diagnostic Tool for Talaromycosis in HIV-Negative Patients.

The diagnosis of Talaromyces marneffei infection in HIV-negative patients remains challenging. There is an urgent need for rapid and convenient methods to diagnose this complicated disease. The aim of this study was to evaluate the diagnostic efficiency of metagenomic next-generation sequencing (mNGS) for talaromycosis in non-HIV-infected patients by comparing mNGS with traditional microbial culture. In total, 66 samples from 57 patients were analyzed via both mNGS and microbial culture. The ROC curve showed a sensitivity for mNGS of 97.22%, which was greater than that of microbial culture (61.11%). Samples from the respiratory tract, infectious skin lesions, and lymph nodes are recommended as routine samples for talaromycosis detection via mNGS. Furthermore, mNGS significantly reduced the diagnostic time compared to microbial culture. Overall, our study demonstrated that mNGS is a promising tool for rapid and accurate pathogenic detection in HIV-negative patients with talaromycosis.

Video-based diagnosis support system for pianists with Musician's dystonia.

Background: Musician's dystonia is a task-specific movement disorder that deteriorates fine motor control of skilled movements in musical performance. Although this disorder threatens professional careers, its diagnosis is challenging for clinicians who have no specialized knowledge of musical performance. Objectives: To support diagnostic evaluation, the present study proposes a novel approach using a machine learning-based algorithm to identify the symptomatic movements of Musician's dystonia. Methods: We propose an algorithm that identifies the dystonic movements using the anomaly detection method with an autoencoder trained with the hand kinematics of healthy pianists. A unique feature of the algorithm is that it requires only the video image of the hand, which can be derived by a commercially available camera. We also measured the hand biomechanical functions to assess the contribution of peripheral factors and improve the identification of dystonic symptoms. Results: The proposed algorithm successfully identified Musician's dystonia with an accuracy and specificity of 90% based only on video footages of the hands. In addition, we identified the degradation of biomechanical functions involved in controlling multiple fingers, which is not specific to musical performance. By contrast, there were no dystonia-specific malfunctions of hand biomechanics, including the strength and agility of individual digits. Conclusion: These findings demonstrate the effectiveness of the present technique in aiding in the accurate diagnosis of Musician's dystonia.

Feasibility of Predicting Surgical Duration in Endometriosis Using Numerical Multi-Scoring System of Endometriosis (NMS-E).

BACKGROUND: Endometriosis is a multifaceted gynecological condition that poses diagnostic challenges and affects a significant number of women worldwide, leading to pain, infertility, and a reduction in patient quality of life (QoL). Traditional diagnostic methods, such as the revised American Society for Reproductive Medicine (r-ASRM) classification, have limitations, particularly in preoperative settings. The Numerical Multi-Scoring System of Endometriosis (NMS-E) has been proposed to address these shortcomings by providing a comprehensive preoperative diagnostic tool that integrates findings from pelvic examinations and transvaginal ultrasonography. METHODS: This retrospective study aims to validate the effectiveness of the NMS-E in predicting surgical outcomes and correlating with the severity of endometriosis. Data from 111 patients at Nippon Medical School Hospital were analyzed to determine the correlation between NMS-E scores, including E-score-a severity indicator-traditional scoring systems, surgical duration, blood loss, and clinical symptoms. This study also examined the need to refine parameters for deep endometriosis within the NMS-E to enhance its predictive accuracy for disease severity. RESULTS: The mean age of the patient cohort was 35.1 years, with the majority experiencing symptoms such as dysmenorrhea, dyspareunia, and chronic pelvic pain. A statistically significant positive correlation was observed between the NMS-E's E-score and the severity of endometriosis, particularly in predicting surgical duration (Spearman correlation coefficient: 0.724, p < 0.01) and blood loss (coefficient: 0.400, p < 0.01). The NMS-E E-score also correlated strongly with the r-ASRM scores (coefficient: 0.758, p < 0.01), exhibiting a slightly more excellent predictive value for surgical duration than the r-ASRM scores alone. Refinements in the methodology for scoring endometriotic nodules in uterine conditions improved the predictive accuracy for surgical duration (coefficient: 0.752, p < 0.01). CONCLUSIONS: Our findings suggest that the NMS-E represents a valuable preoperative diagnostic tool for endometriosis, effectively correlating with the disease's severity and surgical outcomes. Incorporating the NMS-E into clinical practice could significantly enhance the management of endometriosis by addressing current diagnostic limitations and guiding surgical planning.

Application of magnetocardiography for myocarditis assessment in a testosterone-substituted female-to-male individual.

Background: The diagnosis of myocarditis remains challenging due to its diverse clinical manifestations. We recently demonstrated the ability of magnetocardiography (MCG) to screen for myocarditis and applied it successfully to detect myocarditis in this case study of a female-to-male (FtM) patient who had undergone sexual reassignment surgery. This case highlights two significant points: first, sex differences in myocarditis may be promoted by higher levels of testosterone, and second, the ability of MCG to diagnose myocarditis. Case presentation: We report on a 38-year-old FtM patient who was hospitalized for chest pain following testosterone therapy. The patient received testosterone every 2 weeks for 6 months following his FtM surgery. Two days after the last administration of testosterone, he developed chest pain. Electrocardiography identified non-significant ST elevations in V3-6, II and aVF and echocardiography revealed reduced left ventricular ejection fraction and apical hypokinesia. High-sensitivity troponin-T (539 ng/L to 676 ng/L) and creatine kinase elevation (592 U/L) were elevated. Coronary CT angiography ruled out coronary artery disease. Cardiac magnetic resonance imaging confirmed suspected myocarditis.Additionally, we used MCG to detect abnormalities in the electromagnetic field. A pathologic vector (0.179) supported the diagnosis of myocarditis in this patient. During therapy with ibuprofen the vector improved to 0.067 after 3 weeks accompanied by symptom improvement. Conclusion: Testosterone treatment may have promoted myocarditis in a FtM individual. Additional MCG assessment was consistent with a diagnosis of myocarditis and highlights the promising potential of this method to facilitate diagnostic screening for cardiomyopathy in the future.

Interference of Streptococcus agalactiae Blitz Therapy in Staphylococcus aureus Microbiological Diagnosis in Subclinical Bovine Mastitis.

Bovine mastitis is an important and costly disease to dairy cattle. Diagnostic methods usually performed in Brazil are somatic cell counts (SCC) and milk microbiology. Low bacteria shedding in milk implies no colony growth in microbiological tests and false negative results. Streptococcus agalactiae and Staphylococcus aureus are principal pathogens of mixed mastitis. However, S. agalactiae has a higher bacterial release from the mammary gland than S. aureus, affecting microbiological sensitivity to diagnose S. aureus. This study aimed to estimate the SCC and total bacterial count (TBC) from cows according to pathogen isolated in milk and to evaluate variation in S. aureus diagnosis by a microbiological test during S. agalactiae treatment, which is called blitz therapy. Both S. agalactiae and S. aureus presented high SCC means, although S. agalactiae showed shedding of bacteria 2.3 times greater than S. aureus. Microbiological sensitivity to S. aureus increased for 5 months during S. agalactiae treatment. The prevalence of S. agalactiae fell after 5 months of therapeutic procedures. The prevalence of S. aureus increased to 39.0. The results showed that due to high sensitivity, the polymerase chain reaction (PCR) could be used at the beginning of blitz therapy with the goal of S. agalactiae eradication from the dairy herd.

Editorial: Management of PJI/SSI after joint arthroplasty.

The management of periprosthetic joint infection (PJI) and surgical site infection (SSI) after joint arthroplasty poses a major challenge in orthopedic surgery. This Editorial provides an overview of the studies published in the special issue "Management of PJI/SSI after Joint Arthroplasty", summarizing the key findings from these studies, which cover a wide range of topics, including stringent preventive strategies, comprehensive diagnostic methods, and personalized treatment modalities. The authors concluded the editorial with their perspectives regarding the status quo of research in this field and future directions for research, such as the development of novel antibiotics, biofilm research, patient-specific risk factors, and the integration of technological advancements (such as machine learning and artificial intelligence) into clinical practice. The authors emphasized the need for continued research, interdisciplinary collaboration, and the application of innovative technologies to enhance patient outcomes and mitigate the burden of these infections on healthcare systems.

Worldwide cohort study of 46, XY differences/disorders of sex development genetic diagnoses: geographic and ethnic differences in variants.

Differences/disorders of sex development (DSDs) in individuals with a 46, XY karyotype are a group of congenital disorders that manifest as male gonadal hypoplasia or abnormalities of the external genitalia. Approximately 50% of patients with 46, XY DSDs cannot obtain a molecular diagnosis. The aims of this paper were to review the most common causative genes and rare genes in patients with 46, XY DSDs, analyze global molecular diagnostic cohorts for the prevalence and geographic distribution of causative genes, and identify the factors affecting cohort detection results. Although the spectrum of genetic variants varies across regions and the severity of the clinical phenotype varies across patients, next-generation sequencing (NGS), the most commonly used detection method, can still reveal genetic variants and aid in diagnosis. A comparison of the detection rates of various sequencing modalities revealed that whole-exome sequencing (WES) facilitates a greater rate of molecular diagnosis of the disease than panel sequencing. Whole-genome sequencing (WGS), third-generation sequencing, and algorithm advancements will contribute to the improvement of detection efficiency. The most commonly mutated genes associated with androgen synthesis and action are AR, SR5A2, and HSD17B3, and the most commonly mutated genes involved in gonadal formation are NR5A1 and MAP3K1. Detection results are affected by differences in enrollment criteria and sequencing technologies.

Salivary metabolites are promising noninvasive biomarkers of drug-induced liver injury.

BACKGROUND: Drug-induced liver injury (DILI) is one of the most common adverse events of medication use, and its incidence is increasing. However, early detection of DILI is a crucial challenge due to a lack of biomarkers and noninvasive tests. AIM: To identify salivary metabolic biomarkers of DILI for the future development of noninvasive diagnostic tools. METHODS: Saliva samples from 31 DILI patients and 35 healthy controls (HCs) were subjected to untargeted metabolomics using ultrahigh-pressure liquid chromatography coupled with tandem mass spectrometry. Subsequent analyses, including partial least squares-discriminant analysis modeling, t tests and weighted metabolite coexpression network analysis (WMCNA), were conducted to identify key differentially expressed metabolites (DEMs) and metabolite sets. Furthermore, we utilized least absolute shrinkage and selection operato and random fores analyses for biomarker prediction. The use of each metabolite and metabolite set to detect DILI was evaluated with area under the receiver operating characteristic curves. RESULTS: We found 247 differentially expressed salivary metabolites between the DILI group and the HC group. Using WMCNA, we identified a set of 8 DEMs closely related to liver injury for further prediction testing. Interestingly, the distinct separation of DILI patients and HCs was achieved with five metabolites, namely, 12-hydroxydodecanoic acid, 3-hydroxydecanoic acid, tetradecanedioic acid, hypoxanthine, and inosine (area under the curve: 0.733-1). CONCLUSION: Salivary metabolomics revealed previously unreported metabolic alterations and diagnostic biomarkers in the saliva of DILI patients. Our study may provide a potentially feasible and noninvasive diagnostic method for DILI, but further validation is needed.

Correlation between serum vitamin D levels and bone mass density evaluated by radiofrequency echographic multi-spectrometry technology (REMS) in menopausal women.

Osteoporosis is a common condition associated with an increased risk of bone fractures due to fragility. Bone mineral density (BMD) is lower in menopausal women due to estrogen deficiency, age-related decline in osteoblast function, decreased calcium absorption, and reduced synthesis of vitamin D, which lead to osteoporosis. The aim of this study was to determine the correlation between serum vitamin D levels and BMD assessed using radiofrequency echographic multi-spectrometry technology (REMS) in menopausal women. A cross-sectional study was conducted at Prof. Dr. Chairuddin P. Lubis Hospital of Universitas Sumatera Utara, Medan, Indonesia, from May 2023 to August 2023. Consecutive sampling method was employed to sample menopausal women with no history of hysterectomy or oophorectomy (unilateral or bilateral), and no history of hormone replacement therapy or vitamin D supplementation. Interviews and physical examinations were conducted to obtain the characteristics of the subjects (age, duration of menopause, and body mass index). The 25(OH)D level was measured using immunoassay and REMS examination was conducted to assess BMD. The Spearman correlation test was used to assess the correlation between serum vitamin D levels and BMD. A total of 32 menopausal women were included in this study with the average vitamin D level was 18.05±5.81 ng/mL, and the mean BMD level was -2.13±1.23. The data showed a significant positive correlation between serum vitamin D levels and BMD in menopausal women (r=0.710; p=0.020). This study highlights that REMS could be useful as an alternative to dual-energy x-ray absorptiometry (DXA) to assess DMD in postmenopausal women.

Detection of Mtb and NTM: preclinical validation of a new asymmetric PCR-binary deoxyribozyme sensor assay.

Tuberculosis (TB) and infectious diseases caused by non-tuberculous mycobacteria (NTM) are global concerns. The development of a rapid and accurate diagnostic method, capable of detecting and identifying different mycobacteria species, is crucial. We propose a molecular approach, the BiDz-TB/NTM, based on the use of binary deoxyribozyme (BiDz) sensors for the detection of Mycobacterium tuberculosis (Mtb) and NTM of clinical interest. A panel of DNA samples was used to evaluate Mtb-BiDz, Mycobacterium abscessus/Mycobacterium chelonae-BiDz, Mycobacterium avium-BiDz, Mycobacterium intracellulare/Mycobacterium chimaera-BiDz, and Mycobacterium kansasii-BiDz sensors in terms of specificity, sensitivity, accuracy, and limit of detection. The BiDz sensors were designed to hybridize specifically with the genetic signatures of the target species. To obtain the BiDz sensor targets, amplification of a fragment containing the hypervariable region 2 of the 16S rRNA was performed, under asymmetric PCR conditions using the reverse primer designed based on linear-after-the-exponential principles. The BiDz-TB/NTM was able to correctly identify 99.6% of the samples, with 100% sensitivity and 0.99 accuracy. The individual values of specificity, sensitivity, and accuracy, obtained for each BiDz sensor, satisfied the recommendations for new diagnostic methods, with sensitivity of 100%, specificity and accuracy ranging from 98% to 100% and from 0.98 to 1.0, respectively. The limit of detection of BiDz sensors ranged from 12 genome copies (Mtb-BiDz) to 2,110 genome copies (Mkan-BiDz). The BiDz-TB/NTM platform would be able to generate results rapidly, allowing the implementation of the appropriate therapeutic regimen and, consequently, the reduction of morbidity and mortality of patients.IMPORTANCEThis article describes the development and evaluation of a new molecular platform for accurate, sensitive, and specific detection and identification of Mycobacterium tuberculosis and other mycobacteria of clinical importance. Based on BiDz sensor technology, this assay prototype is amenable to implementation at the point of care. Our data demonstrate the feasibility of combining the species specificity of BiDz sensors with the sensitivity afforded by asymmetric PCR amplification of target sequences. Preclinical validation of this assay on a large panel of clinical samples supports the further development of this diagnostic tool for the molecular detection of pathogenic mycobacteria.

Prevalence of viral agents causing swine reproductive failure in Korea and the development of multiplex real-time PCR and RT-PCR assays.

This study aimed to investigate the prevalence of viral agents causing reproductive failure in pigs in Korea. In addition, two types of multiplex real-time PCR (mqPCR) were developed for the simultaneous detection of Aujeszky's disease virus (ADV) and porcine parvovirus (PPV) in mqPCR and encephalomyocarditis virus (EMCV) and Japanese encephalitis virus (JEV) in reverse transcription mqPCR (mRT-qPCR). A total of 150 aborted fetus samples collected from 2020 to 2022 were analyzed. Porcine reproductive and respiratory syndrome virus was the most prevalent (49/150 32.7%), followed by porcine circovirus type 2 (31/150, 20.7%), and PPV1 (7/150, 4.7%), whereas ADV, EMCV, and JEV were not detected. The newly developed mqPCR and mRT-qPCR could simultaneously detect and differentiate with high sensitivities and specificities. When applied to aborted fetuses, the newly developed mqPCR for PPV was 33.3% more sensitivities than the previously established diagnostic method. Amino acid analysis of the VP2 sequences of PPV isolates revealed considerable similarity to the highly pathogenic Kresse strain. This study successfully evaluated the prevalence of viral agents causing reproductive failure among swine in Korea, the developed mqPCR and mRT-qPCR methods could be utilized as effective and accurate diagnostic methods for the epidemiological surveillance of ADV, PPV, EMCV, and JEV.

Comparative efficiency of differential diagnostic methods for the identification of BRAF V600E gene mutation in papillary thyroid cancer (Review).

V-Raf murine sarcoma viral oncogene homolog B1 (BRAF) encodes a serine-threonine kinase. The V600E point mutation in the BRAF gene is the most common mutation, predominantly occurring in melanoma, and colorectal, thyroid and non-small cell lung cancer. Particularly in the context of thyroid cancer research, it is routinely employed as a molecular biomarker to assist in diagnosing and predicting the prognosis of papillary thyroid cancer (PTC), and to formulate targeted therapeutic strategies. Currently, several methods are utilized in clinical settings to detect BRAF V600E mutations in patients with PTC. However, the sensitivity and specificity of various detection techniques vary significantly, resulting in diverse detection outcomes. The present review highlights the advantages and disadvantages of the methods currently employed in medical practice, with the aim of guiding clinicians and researchers in selecting the most suitable detection approach for its high sensitivity, reproducibility and potential to develop targeted therapeutic regimens for patients with BRAF gene mutation-associated PTC.

Ov-RPA-CRISPR/Cas12a assay for the detection of Opisthorchis viverrini infection in field-collected human feces.

BACKGROUND: Opisthorchis viverrini infection is traditionally diagnosed using the Kato-Katz method and formalin ethyl-acetate concentration technique. However, the limited sensitivity and specificity of these techniques have prompted the exploration of various molecular approaches, such as conventional polymerase chain reaction (PCR) and real-time PCR, to detect O. viverrini infection. Recently, a novel technique known as recombinase polymerase amplification (RPA)-clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) (RPA-CRISPR/Cas) assay was developed as a point-of-care tool for the detection of various pathogens, including viruses and bacteria such as severe acute respiratory syndrome coronavirus 2 and Mycobacterium tuberculosis. This technology has demonstrated high sensitivity and specificity. Therefore, we developed and used the RPA-CRISPR/Cas assay to detect O. viverrini infection in field-collected human feces. METHODS: To detect O. viverrini infection in fecal samples, we developed a CRISPR/Cas12a (RNA-guided endonuclease) system combined with RPA (Ov-RPA-CRISPR/Cas12a). Several fecal samples, both helminth-positive and helminth-negative, were used for the development and optimization of amplification conditions, CRISPR/Cas detection conditions, detection limits, and specificity of the RPA-CRISPR/Cas12a assay for detecting O. viverrini infection. The detection results were determined using a real-time PCR system based on fluorescence values. Additionally, as the reporter was labeled with fluorescein, the detection results were visually inspected using an ultraviolet (UV) transilluminator. A receiver operating characteristic curve (ROC) was used to determine the optimal cutoff value for fluorescence detection. The diagnostic performance, including sensitivity and specificity, of the Ov-RPA-CRISPR/Cas12a assay was evaluated on the basis of comparison with standard methods. RESULTS: The Ov-RPA-CRISPR/Cas12a assay exhibited high specificity for detecting O. viverrini DNA. On the basis of the detection limit, the assay could detect O. viverrini DNA at concentrations as low as 10-1 ng using the real-time PCR system. However, in this method, visual inspection under UV light required a minimum concentration of 1 ng. To validate the Ov-RPA-CRISPR/Cas12a assay, 121 field-collected fecal samples were analyzed. Microscopic examination revealed that 29 samples were positive for O. viverrini-like eggs. Of these, 18 were confirmed as true positives on the basis of the Ov-RPA-CRISPR/Cas12a assay and microscopic examination, whereas 11 samples were determined as positive solely via microscopic examination, indicating the possibility of other minute intestinal fluke infections. CONCLUSIONS: The Ov-RPA-CRISPR/Cas12a assay developed in this study can successfully detect O. viverrini infection in field-collected feces. Due to the high specificity of the assay reported in this study, it can be used as an alternative approach to confirm O. viverrini infection, marking an initial step in the development of point-of-care diagnosis.

A New Multiplex TaqMan qPCR for Precise Detection and Quantification of Clavibacter michiganensis in Seeds and Plant Tissue.

Bacterial canker of tomato caused by Clavibacter michiganensis (Cm) is one of the most devastating bacterial diseases affecting the tomato industry worldwide. As the result of Cm colonization of the xylem, the susceptible host shows typical symptoms of wilt, marginal leaf necrosis, stem cankers, and ultimately plant death. However, what makes Cm an even more dangerous pathogen is its ability to infect seeds and plants without causing symptoms. Unfortunately, there are no resistant cultivars or effective chemical or biological control methods available to growers against Cm. Its control relies heavily on prevention. The implementation of a rapid and accurate detection tool is imperative to monitor the presence of Cm and prevent its spread. In this study, we developed a specific and sensitive multiplex TaqMan qPCR assay to detect Cm and distinguish it from related bacterial species that affect tomato plants. Two Cm chromosomal virulence-related genes, rhuM and tomA, were used as specific targets. The plant internal control tubulin alpha-3 was included in each of the multiplexes to improve the reliability of the assay. Specificity was evaluated with 37 bacterial strains including other Clavibacter spp. and related and unrelated bacterial pathogens from different geographic locations affecting a wide variety of hosts. Results showed that the assay is able to discriminate Cm strains from other related bacteria. The assay was validated on tissue and seed samples following artificial infection, and all tested samples accurately detected the presence of Cm. The tool described here is highly specific, sensitive, and reliable for the detection of Cm and allows the quantification of Cm in seeds, roots, stems, and leaves. The diagnostic assay can also be adapted for multiple purposes such as seed certification programs, surveillance, biosafety, the effectiveness of control methods, border protection, and epidemiological studies.[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Multimodal Method for Differentiating Various Clinical Forms of Basal Cell Carcinoma and Benign Neoplasms In Vivo.

Correct classification of skin lesions is a key step in skin cancer screening, which requires high accuracy and interpretability. This paper proposes a multimodal method for differentiating various clinical forms of basal cell carcinoma and benign neoplasms that includes machine learning. This study was conducted on 37 neoplasms, including benign neoplasms and five different clinical forms of basal cell carcinoma. The proposed multimodal screening method combines diffuse reflectance spectroscopy, optical coherence tomography and high-frequency ultrasound. Using diffuse reflectance spectroscopy, the coefficients of melanin pigmentation, erythema, hemoglobin content, and the slope coefficient of diffuse reflectance spectroscopy in the wavelength range 650-800 nm were determined. Statistical texture analysis of optical coherence tomography images was used to calculate first- and second-order statistical parameters. The analysis of ultrasound images assessed the shape of the tumor according to parameters such as area, perimeter, roundness and other characteristics. Based on the calculated parameters, a machine learning algorithm was developed to differentiate the various clinical forms of basal cell carcinoma. The proposed algorithm for classifying various forms of basal cell carcinoma and benign neoplasms provided a sensitivity of 70.6 ± 17.3%, specificity of 95.9 ± 2.5%, precision of 72.6 ± 14.2%, F1 score of 71.5 ± 15.6% and mean intersection over union of 57.6 ± 20.1%. Moreover, for differentiating basal cell carcinoma and benign neoplasms without taking into account the clinical form, the method achieved a sensitivity of 89.1 ± 8.0%, specificity of 95.1 ± 0.7%, F1 score of 89.3 ± 3.4% and mean intersection over union of 82.6 ± 10.8%.

A retrospective study of 3D measurement and analysis applied in the morphological evaluation of achalasia cardia.

Background: Achalasia cardia (AC) is defined as a disorder of esophageal motility whose diagnostic gold standard depends on high-resolution manometry (HRM). The invasiveness of HRM can cause difficulties in diagnosis, treatment, and follow-up for patients with AC. Thus, we aimed to investigate the function of 3D reconstruction and measurement to prove the wide application of this alternative non-invasive approach for AC. Methods: A total of 126 patients with AC and 40 healthy subjects in Tianjin Medical University General Hospital from January 2018 to October 2022 were enrolled in this retrospective study. Chest CT images of these subjects were used to reconstruct the 3D models of the esophagus, stomach, spine, left crus, and right crus. Measurements of esophagus length, volume of esophagus, gastroesophageal insertion angle (His angle), max thickness of esophageal wall, esophagus maximum transverse and longitudinal diameter, esophagus-spine angle, and spine-lower esophageal sphincter (LES) angle were applied based on the models. Results: Retrocardiac esophagus length, volume of esophagus, max thickness of esophageal wall, esophagus maximum transverse and longitudinal diameter, thoracic esophagus-spine angle, and spine-LES angle in the AC group were higher than those in the control group (all P values <0.05). Among the three subtypes of AC, thoracic esophagus length, intra-abdominal LES length, volume of esophagus, His angle, esophagus maximum transverse and longitudinal diameter, and thoracic esophagus-spine angle all presented statistical differences (all P values <0.05). Correlation analysis revealed that manometric types were positively associated with His angle [r=0.196; 95% confidence interval (CI): 0.009, 0.372; P=0.028] but negatively associated with volume of esophagus (r=-0.480; 95% CI: -0.639, -0.310; P<0.001), esophagus maximum transverse diameter (r=-0.551; 95% CI: -0.679, -0.400; P<0.001), esophagus maximum longitudinal diameter (r=-0.518; 95% CI: -0.649, -0.366; P<0.001), and thoracic esophagus-spine angle (r=-0.324; 95% CI: -0.479, -0.157; P<0.001). Conclusions: This study successfully presented the differences in esophageal length, volume, thickness, and angles between healthy subjects and different AC subtypes on the basis of 3D reconstruction and measurement. Thus, 3D model and measurement can be regarded as a good support for further research and make a valuable contribution to developing non-invasive approaches for AC management.

Development and evaluation of an integrated liver nodule diagnostic method by combining the liver segment division and lesion localization/classification models for enhanced focal liver lesion detection.

The purpose of the study was to develop a liver nodule diagnostic method that accurately localizes and classifies focal liver lesions and identifies the specific liver segments in which they reside by integrating a liver segment division algorithm using a four-dimensional (4D) fully convolutional residual network (FC-ResNet) with a localization and classification model. We retrospectively collected data and divided 106 gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid-enhanced magnetic resonance examinations into Case-sets 1, 2, and 3. A liver segment division algorithm was developed using a 4D FC-ResNet and trained with semi-automatically created silver-standard annotations; performance was evaluated using manually created gold-standard annotations by calculating the Dice scores for each liver segment. The performance of the liver nodule diagnostic method was assessed by comparing the results with those of the original radiology reports. The mean Dice score between the output of the liver segment division model and the gold standard was 0.643 for Case-set 2 (normal liver contours) and 0.534 for Case-set 1 (deformed liver contours). Among the 64 lesions in Case-set 3, the diagnostic method localized 37 lesions, classified 33 lesions, and identified the liver segments for 30 lesions. A total of 28 lesions were true positives, matching the original radiology reports. The liver nodule diagnostic method, which integrates a liver segment division algorithm with a lesion localization and classification model, exhibits great potential for localizing and classifying focal liver lesions and identifying the liver segments in which they reside. Further improvements and validation using larger sample sizes will enhance its performance and clinical applicability.

Potassium deficiency diagnosis method of apple leaves based on MLR-LDA-SVM.

Introduction: At present, machine learning and image processing technology are widely used in plant disease diagnosis. In order to address the challenges of subjectivity, cost, and timeliness associated with traditional methods of diagnosing potassium deficiency in apple tree leaves. Methods: The study proposes a model that utilizes image processing technology and machine learning techniques to enhance the accuracy of detection during each growth period. Leaf images were collected at different growth stages and processed through denoising and segmentation. Color and shape features of the leaves were extracted and a multiple regression analysis model was used to screen for key features. Linear discriminant analysis was then employed to optimize the data and obtain the optimal shape and color feature factors of apple tree leaves during each growth period. Various machine-learning methods, including SVM, DT, and KNN, were used for the diagnosis of potassium deficiency. Results: The MLR-LDA-SVM model was found to be the optimal model based on comprehensive evaluation indicators. Field experiments were conducted to verify the accuracy of the diagnostic model, achieving high diagnostic accuracy during different growth periods. Discussion: The model can accurately diagnose whether potassium deficiency exists in apple tree leaves during each growth period. This provides theoretical guidance for intelligent and precise water and fertilizer management in orchards.

Clinical Predictive Score for Identifying Metabolic Dysfunction-Associated Steatotic Liver Disease in Individuals with Prediabetes Using Transient Elastography.

Scoring systems for metabolic dysfunction-associated steatotic liver disease (MASLD) in individuals with prediabetes have not been extensively explored. This study aimed to investigate the prevalence of MASLD and to develop predictive tools for its detection in high cardiometabolic people with prediabetes. A cross-sectional study was conducted using baseline data from the prediabetes cohort. All participants underwent transient elastography to assess liver stiffness. MASLD was defined using a controlled attenuation parameter value > 275 dB/m and/or a liver stiffness measurement ≥ 7.0 kPa. Cases with secondary causes of hepatic steatosis were excluded. Out of 400 participants, 375 were included. The observed prevalence of MASLD in individuals with prediabetes was 35.7%. The most effective predictive model included FPG ≥ 110 mg/dL; HbA1c ≥ 6.0%; sex-specific cutoffs for HDL; ALT ≥ 30 IU/L; and BMI levels. This model demonstrated good predictive performance with an AUC of 0.80 (95% CI 0.73-0.86). At a cutoff value of 4.5, the sensitivity was 70.7%, the specificity was 72.3%, the PPV was 58.8%, and the NPV was 81.5%. Our predictive model is practical, easy to use, and relies on common parameters. The scoring system should aid clinicians in determining when further investigations of MASLD are warranted among individuals with prediabetes, especially in settings with limited resources.

Case report: Recurrence of inflammatory cardiomyopathy detected by magnetocardiography.

Background: The diagnosis of inflammatory cardiomyopathies remains challenging. Life-threatening conditions such as acute coronary syndrome (ACS) always have to be considered as differential diagnoses due to similarities in presentation. Diagnostic methods for inflammatory cardiomyopathy include endomyocardial biopsy (EMB), cardiac magnetic resonance imaging (CMR), and positron emission tomography-computed tomography (PET-CT). We report a case in whom magnetocardiography (MCG) led to an initial diagnosis of inflammatory cardiomyopathy and in whom MCG was used for subsequent monitoring of treatment response under immunosuppression. Case presentation: A 53-year-old man presented with two recurrent episodes of inflammatory cardiomyopathy within a 2-year period. The patient initially presented with reduced exercise capacity. Echocardiography revealed a moderately reduced left ventricular ejection fraction (LVEF 40%). Coronary angiography ruled out obstructive coronary artery disease (CAD) and an EMB was performed. The EMB revealed inflammatory cardiomyopathy without viral pathogens or replication. Moreover, we performed MCG, which confirmed a pathological Tbeg-Tmax vector of 0.108. We recently established a cutoff value of Tbeg-Tmax of 0.051 or greater for the diagnosis of inflammatory cardiomyopathy. Immunosuppressive therapy with prednisolone was initiated, resulting in clinical improvement and an LVEF increase from 40% to 45% within 1 month. Furthermore, the MCG vector improved to 0.036, which is considered normal based on our previous findings. The patient remained clinically stable for 23 months. During a routine follow-up, MCG revealed an abnormal Tbeg-Tmax vector of 0.069. The patient underwent additional testing including routine laboratory values, echocardiography (LVEF 35%), and PET-CT. PET-CT revealed increased metabolism in the myocardium-primarily in the lateral wall. Therapy with prednisolone and azathioprine was initiated and MCG was used to monitor the effect of immunosuppressive therapy. Conclusion: In addition to diagnostic screening, MCG has the potential to become a valuable method for surveillance monitoring of patients who have completed treatment for inflammatory cardiomyopathy. Furthermore, it could be used for treatment monitoring. While changes in the magnetic vector of the heart are not specific to inflammatory cardiomyopathy, as they may also occur in other types of cardiomyopathies, MCG offers a tool of broad and efficient diagnostic screening for cardiac pathologies without side effects.