RESUMEN
PURPOSE: Risk classification of primary prostate cancer in clinical routine is mainly based on prostate-specific antigen (PSA) levels, Gleason scores from biopsy samples, and tumor-nodes-metastasis (TNM) staging. This study aimed to investigate the diagnostic performance of positron emission tomography/magnetic resonance imaging (PET/MRI) in vivo models for predicting low-vs-high lesion risk (LH) as well as biochemical recurrence (BCR) and overall patient risk (OPR) with machine learning. METHODS: Fifty-two patients who underwent multi-parametric dual-tracer [18F]FMC and [68Ga]Ga-PSMA-11 PET/MRI as well as radical prostatectomy between 2014 and 2015 were included as part of a single-center pilot to a randomized prospective trial (NCT02659527). Radiomics in combination with ensemble machine learning was applied including the [68Ga]Ga-PSMA-11 PET, the apparent diffusion coefficient, and the transverse relaxation time-weighted MRI scans of each patient to establish a low-vs-high risk lesion prediction model (MLH). Furthermore, MBCR and MOPR predictive model schemes were built by combining MLH, PSA, and clinical stage values of patients. Performance evaluation of the established models was performed with 1000-fold Monte Carlo (MC) cross-validation. Results were additionally compared to conventional [68Ga]Ga-PSMA-11 standardized uptake value (SUV) analyses. RESULTS: The area under the receiver operator characteristic curve (AUC) of the MLH model (0.86) was higher than the AUC of the [68Ga]Ga-PSMA-11 SUVmax analysis (0.80). MC cross-validation revealed 89% and 91% accuracies with 0.90 and 0.94 AUCs for the MBCR and MOPR models respectively, while standard routine analysis based on PSA, biopsy Gleason score, and TNM staging resulted in 69% and 70% accuracies to predict BCR and OPR respectively. CONCLUSION: Our results demonstrate the potential to enhance risk classification in primary prostate cancer patients built on PET/MRI radiomics and machine learning without biopsy sampling.
Asunto(s)
Radioisótopos de Galio , Neoplasias de la Próstata , Ácido Edético , Humanos , Imagen por Resonancia Magnética , Masculino , Tomografía Computarizada por Tomografía de Emisión de Positrones , Tomografía de Emisión de Positrones , Estudios Prospectivos , Neoplasias de la Próstata/diagnóstico por imagen , Aprendizaje Automático SupervisadoRESUMEN
BACKGROUND: HbH disease results from dysfunction of three, less commonly two, α-globin genes through various combinations of deletion and non-deletion mutations. Characterization of the mutations and the underlying genotypes is fundamental for proper screening and prevention of thalassaemia in any region. The aim of this study was to explore the genetic arrangements of HbH disease and to correlate the genotypes with the clinical phenotypes. METHODS: A total of 44 HbH disease patients were enrolled in this study. They were clinically and haematologically assessed. The patients were tested for 21 common α-globin gene mutations using multiplex PCR and reverse hybridization. According to the genotype, the patients were categorized into two separate sub-groups, deletion and non-deletion types HbH disease. RESULTS: Within the studied HbH disease patients, eight different α-globin gene mutations were detected in nine different genetic arrangements. The --MED and -α3.7 deletions were the two most frequently encountered mutations (37.5 and 35.2% respectively). Patients with deletion genotypes constituted 70.4%. The most common detected genotype was --MED/-α3.7 (59.1%), followed by αpoly-A1α/αpoly-A1α (13.6%). For the first time, coinheritance of two relatively mild mutations (-α3.7/ααAdana) was unpredictably detected in a 1.5 year-old child with Hb of 7.1 g/dL. CONCLUSION: The HbH disease patients' clinical characteristics were variable with no ample difference between the deletion and non-deletion types. These results can be of benefit for the screening and management of thalassaemia in this region.
Asunto(s)
Estudios de Asociación Genética/métodos , Hemoglobina H/genética , Mutación , Globinas alfa/genética , Talasemia alfa/genética , Adolescente , Adulto , Anciano , Niño , Preescolar , Femenino , Estudios de Asociación Genética/estadística & datos numéricos , Genotipo , Humanos , Lactante , Irak , Masculino , Persona de Mediana Edad , Fenotipo , Adulto Joven , Talasemia alfa/diagnósticoRESUMEN
Aging is a ubiquitous biological process that limits the maximal lifespan of most organisms. Significant efforts by many groups have identified mechanisms that, when triggered by natural or artificial stimuli, are sufficient to either enhance or decrease maximal lifespan. Previous aging studies using the nematode Caenorhabditis elegans (C. elegans) generated a wealth of publicly available transcriptomics datasets linking changes in gene expression to lifespan regulation. However, a comprehensive comparison of these datasets across studies in the context of aging biology is missing. Here, we carry out a systematic meta-analysis of over 1200 bulk RNA sequencing (RNASeq) samples obtained from 74 peer-reviewed publications on aging-related transcriptomic changes in C. elegans. Using both differential expression analyses and machine learning approaches, we mine the pooled data for novel pro-longevity genes. We find that both approaches identify known and propose novel pro-longevity genes. Further, we find that inter-lab experimental variance complicates the application of machine learning algorithms, a limitation that was not solved using bulk RNA-Seq batch correction and normalization techniques. Taken as a whole, our results indicate that machine learning approaches may hold promise for the identification of genes that regulate aging but will require more sophisticated batch correction strategies or standardized input data to reliably identify novel pro-longevity genes.
Asunto(s)
Proteínas de Caenorhabditis elegans , Caenorhabditis elegans , Animales , Caenorhabditis elegans/metabolismo , Proteínas de Caenorhabditis elegans/genética , Proteínas de Caenorhabditis elegans/metabolismo , RNA-Seq , Envejecimiento/genética , Longevidad/genéticaRESUMEN
Guillain-Barré syndrome (GBS) is a rare immune-mediated neuropathy causing destruction of the peripheral nervous system, with molecular mimicry playing a major role in its pathophysiology. Despite its rarity, it is considered the most common cause of acute flaccid neuromuscular paralysis in the United States. Although diagnosing GBS depends on the clinical presentation of the patient, cerebrospinal fluid sampling, nerve conduction studies, electromyography, magnetic resonance imaging, and ganglioside antibody screening can be used to confirm the diagnosis and rule out other differentials. Here, we report a rare case of GBS as a postoperative complication after a successful gastrojejunostomy to excise an adenocarcinoma in the second part of the duodenum. Such a complication is rare and not fully understood yet.
RESUMEN
BACKGROUND: Laser ultrasound detection systems are used for noninvasive imaging of internal structures and function of soft tissues. The detection systems with a high sensitivity can be used for detecting small tumors located deeply in human tissues, such as the breast. In this study, the sensitivity of existing ultrasonic detection systems has been compared experimentally by using thermoelastic waves as a broadband ultrasonic source. METHODS: For the comparison, an optical stress transducer, a polyvinylidene difluoride (PVDF) sheet and a calibrated PVDF needle hydrophone were used. To ensure that all detection systems were interrogated by the same ultrasonic field, a small optical instrument was constructed to fix the generating laser head. The sensitivity was evaluated by measuring signal-to-noise ratios (SNRs) and noise equivalent pressures (NEPs). RESULTS: The PVDF system, with a 4 kPa NEP, has a 22-dB better performance than the optical stress transducer. The optical stress transducer showed nearly the same sensitivity as the hydrophone for detecting ultrasound waves at a 1-cm distance. CONCLUSIONS: PVDF detection system provides a useful tool for imaging of soft tissues because of its high sensitivity and broadband detection range.
Asunto(s)
Tecnología Biomédica/instrumentación , Tecnología Biomédica/métodos , Rayos Láser , Ultrasonido , Diseño de Equipo , Presión , Sensibilidad y EspecificidadRESUMEN
OBJECTIVES: To determine the difference in response of NIRS of the bladder during voiding between men with and without BOO.LUTS. METHODS: A prospective, case series, study included 36 men with LUTS. Patients completed the IPSS questionnaire; prostate volumes were measured sonographically. Patients underwent pressure flow study (PFS) with simultaneous NIRS of the bladder. Amplitudes of HHb, O2Hb, and Hbsum were calculated at Qmax, relative to baseline. Patients were urodynamically classified as obstructed and unobstructed. Recursive partition analysis (RPA) was performed to reclassify patients using NIRS amplitudes, followed by combined data of NIRS amplitudes, prostate volume, IPSS, and Qmax to determine the best predictor(s) of BOO. RESULTS: PFS classified 28 patients as obstructed and 8 as unobstructed. The median HHb amplitude was significantly higher in obstructed group. RPA of NIRS amplitudes correctly reclassified 89% of patients [AUC: 0.91]. RPA of the combined IPSS, prostate volume, PVR, and Qmax correctly reclassified 72% of patients [AUC: 0.84]. When NIRS amplitudes were added to this combination, RPA revealed a significantly (P < 0.01) higher rate of correct reclassification in 89% of patients with 89.3% sensitivity and 88% specificity for obstruction [AUC: 0.96]. CONCLUSION: NIRS data can be of diagnostic value for BOO in men with LUTS.