Mammary tuberculosis is a rare entity. The incidence of the disease varies from 0.025% to 4.5% of all surgically treated breast diseases. The surgical resection is required for diagnosis of mammary tuberculosis, since the clinician may confuse tuberculosis mastitis with either carcinoma or breast abscess. Treatment is the combination of resection and chemotherapy. We report a case of mammary tuberculosis diagnosed by fine-needle aspiration and biopsy (FNAB), along with a review of literature.
Abscess ; Biopsy ; Biopsy, Fine-Needle ; Breast ; Breast Diseases ; Diagnosis ; Drug Therapy ; Female ; Incidence ; Mastitis ; Tuberculosis*

Acute pancreatitis (AP) is a common disorder characterized by the inflammation of the exocrine pancreas in dogs, and the severity of the clinical signs of pancreatitis varies greatly. Therefore, the diagnosis of pancreatitis is challenging. The canine pancreatic lipase immunoreactivity test (SNAP cPL; IDEXX Laboratories Inc., USA) is rapid and relatively accurate in diagnosing pancreatitis. The purpose of this study was to evaluate the positivity rate of the SNAP cPL test in dogs regarding the severity of gastrointestinal (GI) signs and concurrent diseases. Electronic medical records of dogs were reviewed. For retrospective classification, 80 dogs with GI signs who underwent the SNAP cPL test were enrolled. Additionally, concurrent diseases on the day of the SNAP cPL test were reviewed. A positive SNAP cPL test result was observed in 26 of the 80 dogs (32.5%) with GI signs. The severity of GI signs using a scoring system and the positivity rate of SNAP cPL were statistically related. Furthermore, dogs with concurrent chronic kidney disease had a significantly higher positivity rate of SNAP cPL than those without chronic kidney disease. This information might help clinicians to decide whether a SNAP cPL test is needed.

Acute pancreatitis (AP) is a common disorder characterized by the inflammation of the exocrine pancreas in dogs, and the severity of the clinical signs of pancreatitis varies greatly. Therefore, the diagnosis of pancreatitis is challenging. The canine pancreatic lipase immunoreactivity test (SNAP cPL; IDEXX Laboratories Inc., USA) is rapid and relatively accurate in diagnosing pancreatitis. The purpose of this study was to evaluate the positivity rate of the SNAP cPL test in dogs regarding the severity of gastrointestinal (GI) signs and concurrent diseases. Electronic medical records of dogs were reviewed. For retrospective classification, 80 dogs with GI signs who underwent the SNAP cPL test were enrolled. Additionally, concurrent diseases on the day of the SNAP cPL test were reviewed. A positive SNAP cPL test result was observed in 26 of the 80 dogs (32.5%) with GI signs. The severity of GI signs using a scoring system and the positivity rate of SNAP cPL were statistically related. Furthermore, dogs with concurrent chronic kidney disease had a significantly higher positivity rate of SNAP cPL than those without chronic kidney disease. This information might help clinicians to decide whether a SNAP cPL test is needed.

Acute pancreatitis (AP) is a common disorder characterized by the inflammation of the exocrine pancreas in dogs, and the severity of the clinical signs of pancreatitis varies greatly. Therefore, the diagnosis of pancreatitis is challenging. The canine pancreatic lipase immunoreactivity test (SNAP cPL; IDEXX Laboratories Inc., USA) is rapid and relatively accurate in diagnosing pancreatitis. The purpose of this study was to evaluate the positivity rate of the SNAP cPL test in dogs regarding the severity of gastrointestinal (GI) signs and concurrent diseases. Electronic medical records of dogs were reviewed. For retrospective classification, 80 dogs with GI signs who underwent the SNAP cPL test were enrolled. Additionally, concurrent diseases on the day of the SNAP cPL test were reviewed. A positive SNAP cPL test result was observed in 26 of the 80 dogs (32.5%) with GI signs. The severity of GI signs using a scoring system and the positivity rate of SNAP cPL were statistically related. Furthermore, dogs with concurrent chronic kidney disease had a significantly higher positivity rate of SNAP cPL than those without chronic kidney disease. This information might help clinicians to decide whether a SNAP cPL test is needed.

Acute pancreatitis (AP) is a common disorder characterized by the inflammation of the exocrine pancreas in dogs, and the severity of the clinical signs of pancreatitis varies greatly. Therefore, the diagnosis of pancreatitis is challenging. The canine pancreatic lipase immunoreactivity test (SNAP cPL; IDEXX Laboratories Inc., USA) is rapid and relatively accurate in diagnosing pancreatitis. The purpose of this study was to evaluate the positivity rate of the SNAP cPL test in dogs regarding the severity of gastrointestinal (GI) signs and concurrent diseases. Electronic medical records of dogs were reviewed. For retrospective classification, 80 dogs with GI signs who underwent the SNAP cPL test were enrolled. Additionally, concurrent diseases on the day of the SNAP cPL test were reviewed. A positive SNAP cPL test result was observed in 26 of the 80 dogs (32.5%) with GI signs. The severity of GI signs using a scoring system and the positivity rate of SNAP cPL were statistically related. Furthermore, dogs with concurrent chronic kidney disease had a significantly higher positivity rate of SNAP cPL than those without chronic kidney disease. This information might help clinicians to decide whether a SNAP cPL test is needed.

Acute pancreatitis (AP) is a common disorder characterized by the inflammation of the exocrine pancreas in dogs, and the severity of the clinical signs of pancreatitis varies greatly. Therefore, the diagnosis of pancreatitis is challenging. The canine pancreatic lipase immunoreactivity test (SNAP cPL; IDEXX Laboratories Inc., USA) is rapid and relatively accurate in diagnosing pancreatitis. The purpose of this study was to evaluate the positivity rate of the SNAP cPL test in dogs regarding the severity of gastrointestinal (GI) signs and concurrent diseases. Electronic medical records of dogs were reviewed. For retrospective classification, 80 dogs with GI signs who underwent the SNAP cPL test were enrolled. Additionally, concurrent diseases on the day of the SNAP cPL test were reviewed. A positive SNAP cPL test result was observed in 26 of the 80 dogs (32.5%) with GI signs. The severity of GI signs using a scoring system and the positivity rate of SNAP cPL were statistically related. Furthermore, dogs with concurrent chronic kidney disease had a significantly higher positivity rate of SNAP cPL than those without chronic kidney disease. This information might help clinicians to decide whether a SNAP cPL test is needed.

Noroviruses (NoV) are the major viral pathogen causing epidemic acute gastroenteritis and outbreaks of foodborne and waterborne illness. During the local festival in Chungnam province, group food poisoning occurred outbreak by NoV infections in Jan 2019. In this study, epidemiological analysis and molecular characterization were conducted such as genotyping, phylogeny. The prevalent genotypes of food poisoning events were NoV GII.3 and GII.17, and NoV GII.3 and GII.17 isolates of this study were completely matched in nucleotide sequence comparison of capsid gene region, respectively. In underground water and stream water, various multiple genotypes of noroviruses were detected including NoV GII.3, GII.8 and GI.4 in aquatic environment of the local festival site. Among 32 worker samples, various NoVs of five genotypes (GI.7, GI.8, GII.3, GII.8, GII.17) were detected in 12 samples and expected to causing NoV contaminated by exposure to groundwater. NoV genotype GII.3, which was detected from groundwater 2, was completely consistent with that of patients and workers. Therefore, groundwater within the local festival site could be main cause of food poisoning event. Because NoV outbreaks are caused by fecal to oral transmission, proper management of sewage purification facilities, groundwater and sanitary toilets is required for many visitors, and efforts are needed to maintain clean environment.
Base Sequence ; Capsid ; Chungcheongnam-do ; Disease Outbreaks ; Epidemiologic Studies ; Foodborne Diseases ; Gastroenteritis ; Genotype ; Groundwater ; Holidays ; Humans ; Korea ; Norovirus ; Phylogeny ; Rivers ; Sewage ; Water

Objective: To investigate the feasibility of using a deep learning-based analysis of auscultation data to predict significant stenosis of arteriovenous fistulas (AVF) in patients undergoing hemodialysis requiring percutaneous transluminal angioplasty (PTA). Materials and Methods: Forty patients (24 male and 16 female; median age, 62.5 years) with dysfunctional native AVF were prospectively recruited. Digital sounds from the AVF shunt were recorded using a wireless electronic stethoscope before (pre-PTA) and after PTA (post-PTA), and the audio files were subsequently converted to mel spectrograms, which were used to construct various deep convolutional neural network (DCNN) models (DenseNet201, EfficientNetB5, and ResNet50). The performance of these models for diagnosing ≥ 50% AVF stenosis was assessed and compared. The ground truth for the presence of ≥ 50% AVF stenosis was obtained using digital subtraction angiography. Gradient-weighted class activation mapping (Grad-CAM) was used to produce visual explanations for DCNN model decisions. Results: Eighty audio files were obtained from the 40 recruited patients and pooled for the study. Mel spectrograms of “pre-PTA” shunt sounds showed patterns corresponding to abnormal high-pitched bruits with systolic accentuation observed in patients with stenotic AVF. The ResNet50 and EfficientNetB5 models yielded an area under the receiver operating characteristic curve of 0.99 and 0.98, respectively, at optimized epochs for predicting ≥ 50% AVF stenosis. However, GradCAM heatmaps revealed that only ResNet50 highlighted areas relevant to AVF stenosis in the mel spectrogram. Conclusion Mel spectrogram-based DCNN models, particularly ResNet50, successfully predicted the presence of significant AVF stenosis requiring PTA in this feasibility study and may potentially be used in AVF surveillance.

Multiple primary malignancies are defined as the presence of more than one malignant neoplasm with a distinct histology occurring at different sites in the same individual. They are classified as synchronous or metachronous according to the diagnostic time interval of different malignancies. Diagnosis of multiple primary malignancies should avoid misclassification from multifocal/multicentric tumors or recurrent/metastatic lesions.In multiple primary malignancies, with increase in the number of primary tumors, the frequency rapidly decreases. Here, we report an exceptionally rare case of a woman who was diagnosed with metachronous sporadic sextuple primary malignancies including bilateral breast cancers (gastric cancer, ovarian Sertoli-Leydig cell tumor, left breast cancer, thyroid cancer, right breast cancer, and rectal neuroendocrine tumor). The sextuple primary malignancies in this case involved 5 different organs: the stomach, ovary, thyroid, rectum, and bilateral breasts. Further studies are needed to elucidate the current epidemiologic status of patients with multiple primary malignancies.

Background: Few studies have evaluated the use of automated artificial intelligence (AI)-based pain recognition in postoperative settings or the correlation with pain intensity. In this study, various machine learning (ML)-based models using facial expressions, the analgesia nociception index (ANI), and vital signs were developed to predict postoperative pain intensity, and their performances for predicting severe postoperative pain were compared. Methods: In total, 155 facial expressions from patients who underwent gastrectomy were recorded postoperatively; one blinded anesthesiologist simultaneously recorded the ANI score, vital signs, and patient self-assessed pain intensity based on the 11-point numerical rating scale (NRS). The ML models’ area under the receiver operating characteristic curves (AUROCs) were calculated and compared using DeLong’s test. Results: ML models were constructed using facial expressions, ANI, vital signs, and different combinations of the three datasets. The ML model constructed using facial expressions best predicted an NRS ≥ 7 (AUROC 0.93) followed by the ML model combining facial expressions and vital signs (AUROC 0.84) in the test-set. ML models constructed using combined physiological signals (vital signs, ANI) performed better than models based on individual parameters for predicting NRS ≥ 7, although the AUROCs were inferior to those of the ML model based on facial expressions (all P < 0.050). Among these parameters, absolute and relative ANI had the worst AUROCs (0.69 and 0.68, respectively) for predicting NRS ≥ 7. Conclusions The ML model constructed using facial expressions best predicted severe postoperative pain (NRS ≥ 7) and outperformed models constructed from physiological signals.