Síndrome de Kartagener y artritis reumatoide. Reporte de caso / Kartagener Syndrome and Rheumatoid Arthritis. Case Report

Presentación del caso. Se trata de una mujer de 26 años de edad, en seguimiento por la especialidad de reumatología desde los 17 años, cuando consultó con historia de un año de evolución de síndrome poliarticular de grandes y pequeñas articulaciones, aditivo, simétrico acompañado de fatiga, rigidez matutina mayor de una hora. Se reportó además factor reumatoide positivo. La radiografía de ambas manos presentó erosiones, que confirmó el diagnóstico de artritis reumatoide. Adicionalmente, la paciente tenía el antecedente de procesos sinobronquiales a repetición desde su infancia. En la evaluación médica se identificó dolor en los senos paranasales, dextrocardia y bronquiectasias, confirmados por los estudios de imágenes, que permitió concluir en el diagnóstico de síndrome de Kartagener. Intervención terapéutica. La paciente presentaba actividad clínica severa de la artritis reumatoide, se inició el tratamiento con metotrexato 10 mg vía oral un día a la semana, prednisona 5 mg al día y ácido fólico 5 mg a la semana y citas periódicas, controlando los datos de actividad y efectos adversos de los medicamentos, con pruebas hepáticas, hemograma y transaminasas. La especialidad de neumología recomendó la inclusión de la paciente en un programa de rehabilitación respiratoria, así como el uso de azitromicina 500 mg cada día por tres días en los períodos de agudización. Evolución clínica. El tratamiento logró mantener una actividad leve de la artritis reumatoide y sin exacerbación de los síntomas respiratorios

Case presentation. A 26-year-old woman, under follow-up by the rheumatology specialty since she was 17 years old, when she consulted with a history of one year of evolution of polyarticular disease of large and small joints, additive, symmetrical, accompanied by fatigue and morning stiffness for more than one hour. Positive rheumatoid factor was also reported. Additionally, the patient had a history of repeated sinobronchial processes since childhood. Medical examination revealed sinus pain in the paranasal sinuses, dextrocardia, and bronchiectasis, confirmed by imaging studies, which led to the diagnosis of Kartagener's syndrome. Treatment. The patient presented the severe clinical activity of rheumatoid arthritis. The treatment was started with methotrexate 10 mg orally one day a week, prednisone 5 mg a day, and folic acid 5 mg a week and periodic appointments, controlling the activity data and adverse effects of the drugs, with liver tests, hemogram, and transaminases. The pneumology department recommended the inclusion of the patient in a respiratory rehabilitation program as well as the use of azithromycin 500 mg every day for three days during periods of exacerbation. Outcome. The treatment was successful in maintaining a mild activity of the rheumatoid arthritis and without exacerbation of respiratory symptoms

Automatic Update Summarization by a Multiobjective Number-One-Selection Genetic Approach.

Currently, the explosive growth of the information available on the Internet makes automatic text summarization systems increasingly important. A particularly relevant challenge is the update summarization task. Update summarization differs from traditional summarization in its dynamic nature. While traditional summarization is static, that is, the document collections about a specific topic remain unchanged, update summarization addresses dynamic document collections based on a specific topic. Therefore, update summarization consists of summarizing the new document collection under the assumption that the user has already read a previous summarization and only the new information is interesting. The multiobjective number-one-selection genetic algorithm (MONOGA) has been designed and implemented to address this problem. The proposed algorithm produces a summary that is relevant to the user's given query, and it also contains updates information. Experiments were conducted on Text Analysis Conference (TAC) datasets, and Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metrics were considered to assess the model performance. The results obtained by the proposed approach outperform those from the existing approaches in the scientific literature, obtaining average percentage improvements between 12.74% and 55.03% in the ROUGE scores.

Multidisciplinary approach as a treatment option for abdominal wall reconstruction in patients with heart failure: A case report.

INTRODUCTION AND IMPORTANCE: Incisional hernias are among the most frequent complications of abdominal surgery, with an incidence of 4-10 % of patients [1]. The multidisciplinary approach according to the patient's needs and their comorbidities has been shown to improve postoperative outcomes. This case report highlights the importance of a multidisciplinary approach including cardiology, general surgery, plastic surgery anesthesiology and intensive care unit for abdominal wall reconstruction in a patient with heart failure and reduced ejection fraction. CLINICAL PRESENTATION: We present a case of a 61-year-old patient with long-standing incisional hernia, without surgical correction due to the patient's condition and multiple comorbidities, advanced heart failure with reduced left ejection fraction (10-15 %) who underwent a multidisciplinary approach by cardiology, plastic surgery, anesthesiology, intensive care unit, and general surgery. DISCUSSION: The patient underwent abdominal wall reconstruction without complications. Due to multiple comorbidities, the patient was admitted in the ICU in the immediate postoperative period. He was discharged 9 days after surgery. The patient did not report long-term complications. CONCLUSION: Heart failure is associated with an increased risk of cardiovascular complications during surgical hospitalization. In patients with multiple comorbidities, the multidisciplinary approach represents an essential strategy in order to improve the surgical outcome, reduce costs to the health care system, and improve the patient's quality of life.

Naked (N) mutant mice carry a nonsense mutation in the homeobox of Hoxc13.

Loss of function mutations in HOXC13 have been associated with Ectodermal Dysplasia-9, Hair/Nail Type (ECTD9) in consanguineous families, characterized by sparse to complete absence of hair and nail dystrophy. Here we characterize the spontaneous mouse mutation Naked (N) as a terminal truncation in the Hoxc13 (homeobox C13) gene. Similar to previous reports for homozygous Hoxc13 knock-out (KO) mice, homozygous N/N mice exhibit generalized alopecia with abnormal nails and a short lifespan. However, in contrast to Hoxc13 heterozygous KO mice, N/+ mice show generalized or partial alopecia, associated with loss of hair fibres, along with normal lifespan and fertility. Our data point to a lack of nonsense-mediated Hoxc13 transcript decay and the presence of the truncated mutant protein in N/N and N/+ hair follicles, thus suggesting a dominant-negative mutation. To our knowledge, this is the first report of a semi-dominant and potentially dominant-negative mutation affecting Hoxc13/HOXC13. Furthermore, recreating the N mutant allele in mice using CRISPR/Cas9-mediated genome editing resulted in the same spectrum of deficiencies as those associated with the spontaneous Naked mutation, thus confirming that N is indeed a Hoxc13 mutant allele. Considering the low viability of the Hoxc13 KO mice, the Naked mutation provides an attractive new model for studying ECTD9 disease mechanisms.

A mobile-assisted voice condition analysis system for Parkinson's disease: assessment of usability conditions.

BACKGROUND AND OBJECTIVE: Automatic voice condition analysis systems to detect Parkinson's disease (PD) are generally based on speech data recorded under acoustically controlled conditions and professional supervision. The performance of these approaches in a free-living scenario is unknown. The aim of this research is to investigate the impact of uncontrolled conditions (realistic acoustic environment and lack of supervision) on the performance of automatic PD detection systems based on speech. METHODS: A mobile-assisted voice condition analysis system is proposed to aid in the detection of PD using speech. The system is based on a server-client architecture. In the server, feature extraction and machine learning algorithms are designed and implemented to discriminate subjects with PD from healthy ones. The Android app allows patients to submit phonations and physicians to check the complete record of every patient. Six different machine learning classifiers are applied to compare their performance on two different speech databases. One of them is an in-house database (UEX database), collected under professional supervision by using the same Android-based smartphone in the same room, whereas the other one is an age, sex and health-status balanced subset of mPower study for PD, which provides real-world data. By applying identical methodology, single-database experiments have been performed on each database, and also cross-database tests. Cross-validation has been applied to assess generalization performance and hypothesis tests have been used to report statistically significant differences. RESULTS: In the single-database experiments, a best accuracy rate of 0.92 (AUC = 0.98) has been obtained on UEX database, while a considerably lower best accuracy rate of 0.71 (AUC = 0.76) has been achieved using the mPower-based database. The cross-database tests provided very degraded accuracy metrics. CONCLUSION: The results clearly show the potential of the proposed system as an aid for general practitioners to conduct triage or an additional tool for neurologists to perform diagnosis. However, due to the performance degradation observed using data from mPower study, semi-controlled conditions are encouraged, i.e., voices recorded at home by the patients themselves following a strict recording protocol and control of the information about patients by the medical doctor at charge.

Replication-based regularization approaches to diagnose Reinke's edema by using voice recordings.

Reinke's edema is one of the most prevalent laryngeal pathologies. Its detection can be addressed by using computer-aided diagnosis systems based on features extracted from speech recordings. When extracting acoustic features from different voice recordings of a particular subject at a concrete moment, imperfections in technology and the very biological variability result in values that are close, but they are not identical. This suggests that the within-subject variability must be properly addressed in the statistical methodology. Regularization-based regression approaches can be used to reduce the classification errors by favoring the best predictors and penalizing the worst ones. Three replication-based regularization approaches for variable selection and classification have been specifically designed and implemented to take into account the underlying within-subject variability. In order to illustrate the applicability of these approaches, an experiment has been specifically conducted to discriminate Reinke's edema patients (30 subjects) from healthy people (30 subjects) in a hospital environment. The features have been extracted from four phonations of the sustained vowel /a/ recorded for each subject, leading to a database that has fed the proposed machine learning approaches. The proposed replication-based approaches have been proved to be reliable in terms of selected features and predictive ability, leading to a stable accuracy rate of 0.89 under a cross-validation framework. Also, a comparison with traditional independence-based regularization methods reports a great variability of the latter in terms of selected features and accuracy metrics. Therefore, the proposed approaches contribute to fill a gap in the scientific literature on statistical approaches considering within-subject variability and can be used to build a robust expert system.

Monitoring Parkinson's disease progression based on recorded speech with missing ordinal responses and replicated covariates.

Monitoring Parkinson's Disease (PD) progression is an important task to improve the life quality of the affected people. This task can be performed by extracting features from voice recordings and applying specifically designed statistical models, leading to systems that improve the ability of monitoring the progression of PD in an objective, remote, non-invasive, fast, and economically sustainable way. An experiment has been conducted with 36 subjects to study the progression of the PD over 4 years by using the Hoehn and Yahr (HY) scale and features extracted from the phonation of the vowel/a/. The collected dataset had many missing data, which should be addressed jointly with the non-decreasing nature of the disease and the within-subject variability due to the use of replicated features. In order to handle these issues, a Hidden Markov model for longitudinal data was designed and implemented by using a data augmentation scheme based on different latent variables. Markov chain Monte Carlo methods were used to generate from the posterior distribution. The proposed approach has been tested on simulated data, providing good accuracy rates in the context of a multiclass problem. It also has been applied to the real data obtained from the conducted experiment, providing imputed and predicted HY stages compatible with the progression of PD. The conducted experiment and the proposed approach contribute to fill a gap in the scientific literature on experiments and methodologies for tracking PD progression based on acoustic features and the HY scale. This would help to derive an expert system that can be integrated into the protocols of neurology units in hospital centers.

A stage-based approach to allocating water quality monitoring stations based on the WorldQual model: The Jubba River as a case study.

Ensuring adequate freshwater quality is an important aspect of integrated environmental management and sustainable development. One contribution towards this end is to monitor the water quality of river basins. An important issue in constructing a water quality monitoring network is how to allocate the stations. This is usually done by using in situ measurements of pollutants together with other information. A stage-based optimization approach has been developed to find the optimal sites to allocate the monitoring stations. The proposed approach constructs a network in a sequence of stages without the need for in situ pollution measurements. Instead, it uses pollutant estimates from the WorldQual model together with other social and hydrological criteria. The approach is computationally efficient and provides an ordered list of stations that can be used to initialize or augment a water quality network. This is especially relevant for consideration by developing countries since, with this approach, they can get an overview of their river basins, and then prioritize the initial distributions of the networks. The approach was applied successfully to the 741,751 km2 of the Jubba River basin, but it is applicable to river basins of any size.

Circulating angiogenic factors are associated with progression to preeclampsia and the occurrence of adverse outcomes in women with gestational hypertension.

OBJECTIVE: Gestational hypertension is characterized by an imbalance in angiogenic factors. The goal of the current study was to evaluate whether circulating concentrations of proangiogenic and antiangiogenic factors are associated with the risk of progression to preeclampsia and development of adverse outcomes in women with gestational hypertension. METHODS: We studied 496 women with gestational hypertension. Patients were divided into three groups based on their degree of angiogenic imbalance, evaluated by the soluble fms-like tyrosine kinase-1/placental growth factor ratio: no angiogenic imbalance (≤38), mild angiogenic imbalance (>38-<85), and severe angiogenic imbalance (≥85) or stratified into tertiles according to soluble endoglin (sEng) levels. RESULTS: The concentrations of all angiogenic factors were significantly different in patients with gestational hypertension than in healthy pregnancy. A significant trend towards higher serum sEng levels was observed as the degree of angiogenic imbalance increased. Patients with severe angiogenic imbalance had higher rates of adverse maternal and perinatal outcomes and progression to preeclampsia (P < 0.001) when compared with patients with no or mild angiogenic imbalance. The risk of combined adverse maternal outcomes and specific adverse outcomes (hemolysis, elevated liver enzymes, low platelet count syndrome, preterm delivery, small-for-gestational-age infant, perinatal death, and progression to preeclampsia within 7, 14, 28, and 56 days) was higher in patients with severe angiogenic imbalance or sEng values in the highest tertile (odds ratio ≥5.6 and ≥2.0, respectively), compared with no angiogenic imbalance or the lowest tertile. CONCLUSION: In women with gestational hypertension at the time of initial evaluation, circulating concentrations of the soluble fms-like tyrosine kinase-1/placental growth factor ratio and sEng appear to be suitable markers to assess the risk of adverse maternal and perinatal outcomes and progression to preeclampsia.

A hidden Markov model addressing measurement errors in the response and replicated covariates for continuous nondecreasing processes.

Motivated by a study tracking the progression of Parkinson's disease (PD) based on features extracted from voice recordings, an inhomogeneous hidden Markov model with continuous state-space is proposed. The approach addresses the measurement error in the response, the within-subject variability of the replicated covariates and presumed nondecreasing response. A Bayesian framework is described and an efficient Markov chain Monte Carlo method is developed. The model performance is evaluated through a simulation-based example and the analysis of a PD tracking progression dataset is presented. Although the approach was motivated by a PD tracking progression problem, it can be applied to any monotonic nondecreasing process whose continuous response variable is subject to measurement errors and where replicated covariates play a key role.

An Acoustic-Signal-Based Preventive Program for University Lecturers' Vocal Health.

INTRODUCTION: Professional activities of university lecturers involve continued and sustained use of the voice, leading in many cases to increased risk of developing voice disorders. Risk identification followed by the fast application of preventive or corrective measures is a key issue in this context. OBJECTIVE: Define and implement a preventive program for the vocal health of university lecturers by using acoustic features automatically extracted from voice recordings to identify risk groups and manage preventive or corrective actions MATERIAL AND METHODS: A total of 170 subjects, aged between 18 and 65, were recruited at the San Pedro de Alcántara Hospital and at the University of Extremadura in Cáceres (Spain). They formed three groups-one of 25 people suffering from vocal fold nodules, another of 25 healthy people, and the third of 120 university lecturers. Medical history and voice status assessment was performed, and voice recordings were made following a research protocol. A feature extraction, selection, and classification procedure was applied to the voice recordings to provide the best predictors for discriminating between pathological and healthy voices. The model parameters were then used to determine the lecturers' probability of suffering vocal fold nodules or other pathologies with similar dysphonic speech. These probabilities were used to classify the lecturers into three risk groups-low, medium, and high. These groups were taken as the basis to assign the lecturers to a primary, secondary, or tertiary prevention level. Different preventive or corrective actions were applied for each prevention level. RESULTS: The best set of predictors comprised sample entropy, correlation dimension, pitch period entropy, glottal noise excitation, and sex, achieving an overall accuracy of 92% with a random forest classifier. They all showed statistically significant differences between vocal fold nodules and healthy groups (P < 0.05). Three out of the four best acoustic features were nonlinear, showing the importance of nonlinear dynamics for clinical practice. The model parameters were applied to the predictors of the lecturers so as to assign them to the different risk groups, leading to 60.8% (73 out of 120) of the lecturers in the low-risk group, 29.2% (35 out of 120) in the medium-risk group, and 10% (12 out of 120) in the high-risk group. The prevention levels were assigned on the basis of this classification and the medical history and laryngological evaluation of some specific subjects. A statistically significant association was found between the voice status and the assigned prevention level (P < 0.001), with there being a clear dependence relationship (Cramér's V = 0.630). CONCLUSION: It is feasible to develop and apply a preventive voice program for university lecturers that is aided by features automatically extracted from voice recordings. As the program progresses, it is expected that the information automatically provided for the assignment to prevention levels will become ever more precise. The method proposed can be extended to other voice professionals and other voice disorders.

Variability and Performance Study of the Sound Absorption of Used Cigarette Butts.

There has been increasing interest in new sustainable materials that can be used as construction materials. Among them, sound-absorbing materials have an important role in both acoustical room conditioning and in room insulation. As a proposal for recycling, one of the most common residues in the world, cigarette butts, is studied. Samples were prepared with used cigarette butts as acoustical absorbent materials. Several samples were prepared and grouped by similarity. Variability analyses of the samples prepared in each group were performed. Moreover, the analysis of some possible influences on absorption properties, such as the length of butts, presence of burnt regions, presence of wrapping paper, etc., were analyzed. The results show the potentiality of this residue to be used as an acoustical absorbent since the absorption coefficients found are greater than 0.8 for frequencies over 2000 Hz. The observed variability in the study group and samples can be considered low, as it was below 2% for the major part of frequencies. Influences on the absorption coefficient, for both the length and status of the butts, were statistically confirmed.

Exploring the importance of mixed autogenous vaccines as a potential determinant of lung consolidation in lambs using Bayesian networks.

Bayesian networks are used to evaluate the effectiveness of mixed autogenous vaccines in fattening lambs to prevent the ovine respiratory syndrome. An experiment was performed with 460 fattening lambs, which were clustered into four groups according to the kind of vaccine received (Pasteurella spp., Mycoplasma spp., Mixed Mycoplasma-Pasteurella or placebo). After slaughtering, lungs were collected, and macroscopic and microscopic studies were performed. A microbiological study was carried out to evaluate the presence of Mycoplasma spp. and Pasteurellaceae by conventional culture and identification by nested polymerase chain reaction. To the best of the authors' knowledge, Bayesian networks have not been used to evaluate the effect of vaccines on the absence/presence of lung consolidation. Our results revealed that the use of mixed autogenous vaccines can decrease lung consolidation from 15.75% (12.42-19.08) to 9.24% (6.59-11.89). Therefore, the use of these autogenous vaccines in farms could be considered an effective control tool against ovine respiratory syndrome.

A Bayesian decision analysis approach to assess voice disorder risks by using acoustic features.

Vocal fold nodules are recognized as an occupational disease for all collective of workers performing activities for which maintained and continued use of voice is required. Computer-aided systems based on features extracted from voice recordings have been considered as potential noninvasive and low cost tools to diagnose some voice-related diseases. A Bayesian decision analysis approach has been proposed to classify university lectures in three levels of risk: low, medium, and high, based on the information provided by acoustic features extracted from healthy controls and people suffering from vocal fold nodules. The proposed risk groups are associated with different treatments. The approach is based on the calculation of posterior probabilities of developing vocal fold nodules and considers utility functions that include the financial cost and the probability of recovery for the corresponding treatment. Maximization of the expected utilities is considered. By using this approach, the risk of having vocal fold nodules is identified for each university lecturer, so he/she can be properly assigned to the right treatment. The approach has been applied to university lecturers according to the Disease Prevention Program of the University of Extremadura. However, it can also be applied to other voice professionals (singers, speakers, coaches, actors…).

Mismatch repair gene mutations lead to lynch syndrome colorectal cancer in rhesus macaques.

Colorectal cancer accounts for a substantial number of deaths each year worldwide. Lynch Syndrome is a genetic form of colorectal cancer (CRC) caused by inherited mutations in DNA mismatch repair (MMR) genes. Although researchers have developed mouse models of Lynch Syndrome through targeted mutagenesis of MMR genes, the tumors that result differ in important ways from those in Lynch Syndrome patients. We identified 60 cases of CRC in rhesus macaques (Macaca mulatta) at our facility since 2001. The tumors occur at the ileocecal junction, cecum and proximal colon and display clinicopathologic features similar to human Lynch Syndrome. We conducted immunohistochemical analysis of CRC tumors from several rhesus macaques, finding they frequently lack expression of MLH1 and PMS2 proteins, both critical MMR proteins involved in Lynch Syndrome. We also found that most macaque cases we tested exhibit microsatellite instability, a defining feature of Lynch Syndrome. Whole genome sequencing of rhesus macaque CRC cases identified mutations in MLH1 and/or MSH6 that are predicted to disrupt protein function. We conclude that this population of rhesus macaques constitutes a spontaneous model of Lynch Syndrome, matching the human disease in several significant characteristics, including genetic risk factors that parallel human Lynch Syndrome.

Deficient LRRC8A-dependent volume-regulated anion channel activity is associated with male infertility in mice.

Ion channel-controlled cell volume regulation is of fundamental significance to the physiological function of sperm. In addition to volume regulation, LRRC8A-dependent volume-regulated anion channel (VRAC) activity is involved in cell cycle progression, insulin signaling, and cisplatin resistance. Nevertheless, the contribution of LRRC8A and its dependent VRAC activity in the germ cell lineage remain unknown. By utilizing a spontaneous Lrrc8a mouse mutation (c.1325delTG, p.F443*) and genetically engineered mouse models, we demonstrate that LRRC8A-dependent VRAC activity is essential for male germ cell development and fertility. Lrrc8a-null male germ cells undergo progressive degeneration independent of the apoptotic pathway during postnatal testicular development. Lrrc8a-deficient mouse sperm exhibit multiple morphological abnormalities of the flagella (MMAF), a feature commonly observed in the sperm of infertile human patients. Importantly, we identified a human patient with a rare LRRC8A hypomorphic mutation (c.1634G>A, p.Arg545His) possibly linked to Sertoli cell-only syndrome (SCOS), a male sterility disorder characterized by the loss of germ cells. Thus, LRRC8A is a critical factor required for germ cell development and volume regulation in the mouse, and it might serve as a novel diagnostic and therapeutic target for SCOS patients.

COX-2 mediates pro-tumorigenic effects of PKCε in prostate cancer.

The pro-oncogenic kinase PKCε is overexpressed in human prostate cancer and cooperates with loss of the tumor suppressor Pten for the development of prostatic adenocarcinoma. However, the effectors driving PKCε-mediated phenotypes remain poorly defined. Here, using cellular and mouse models, we showed that PKCε overexpression acts synergistically with Pten loss to promote NF-κB activation and induce cyclooxygenase-2 (COX-2) expression, phenotypic traits which are also observed in human prostate tumors. Targeted disruption of PKCε from prostate cancer cells impaired COX-2 induction and PGE2 production. Notably, COX-2 inhibitors selectively killed prostate epithelial cells overexpressing PKCε, and this ability was greatly enhanced by Pten loss. Long-term COX-2 inhibition markedly reduced adenocarcinoma formation, as well as angiogenesis in a mouse model of prostate-specific PKCε expression and Pten loss. Overall, our results provide strong evidence for the involvement of the canonical NF-κB pathway and its target gene COX2 as PKCε effectors, and highlight the potential of PKCε as a useful biomarker for the use of COX inhibition for chemopreventive and/or chemotherapeutic purposes in prostate cancer.

Boar sperm hyperactivated motility is induced by temperature via an intracellular calcium-dependent pathway.

Herein we describe a new protocol to induce boar sperm hypermotility: temperature-induced hypermotility (TIH). Briefly, spermatozoa stored at 17°C in a calcium-free Tyrode's basal medium (containing EGTA) were exposed to increased temperature by incubation at 38.5°C. Hypermotility induced by the calcium ionophore A23187 was used as a control (calcium ionophore-induced hyperactivity (CIIH)). The increase in temperature led to an increase in the percentage of hypermotile spermatozoa. When the slope of the temperature increase is near zero, sperm hyperactivity becomes a more progressive movement. Motility parameters of sperm hyperactivation induced by TIH were different from those following CIIH. Cluster analysis revealed that these two populations of hyperactivated spermatozoa are different. TIH is independent of extracellular Ca2+ but dependent on intracellular Ca2+ release. Moreover, TIH is unaffected by protein kinase A (PKA) inhibition, whereas CIIH is reduced by half in the presence of a PKA inhibitor. In conclusion, we have demonstrated that: (1) a temperature increase in boar spermatozoa is a stimulus that can induce a hyperactive population, which is differs from the hyperactive sperm population induced by calcium ionophore; (2) the temperature increase in spermatozoa triggers the release of Ca2+ from intracellular stores; (3) extracellular calcium is not required for TIH; and (4) TIH in boar spermatozoa is independent of PKA activity.

MLH1-rheMac hereditary nonpolyposis colorectal cancer syndrome in rhesus macaques.

Over the past two decades, 33 cases of colonic adenocarcinomas have been diagnosed in rhesus macaques (Macaca mulatta) at the nonhuman primate colony of the Keeling Center for Comparative Medicine and Research at The University of Texas MD Anderson Cancer Center. The distinctive feature in these cases, based on PET/computed tomography (CT) imaging, was the presence of two or three tumor lesions in different locations, including proximal to the ileocecal juncture, proximal to the hepatic flexure, and/or in the sigmoid colon. These colon carcinoma lesions selectively accumulated [18F]fluorodeoxyglucose ([18F]FDG) and [18F]fluoroacetate ([18F]FACE) at high levels, reflecting elevated carbohydrate and fatty acid metabolism in these tumors. In contrast, the accumulation of [18F]fluorothymidine ([18F]FLT) was less significant, reflecting slow proliferative activity in these tumors. The diagnoses of colon carcinomas were confirmed by endoscopy. The expression of MLH1, MSH2, and MSH6 proteins and the degree of microsatellite instability (MSI) was assessed in colon carcinomas. The loss of MLH1 protein expression was observed in all tumors and was associated with a deletion mutation in the MLH1 promoter region and/or multiple single-nucleotide polymorphism (SNP) mutations in the MLH1 gene. All tumors exhibited various degrees of MSI. The pedigree analysis of this rhesus macaque population revealed several clusters of affected animals related to each other over several generations, suggesting an autosomal dominant transmission of susceptibility for colon cancer. The newly discovered hereditary nonpolyposis colorectal cancer syndrome in rhesus macaques, termed MLH1-rheMac, may serve as a model for development of novel approaches to diagnosis and therapy of Lynch syndrome in humans.

A Diadochokinesis-based expert system considering articulatory features of plosive consonants for early detection of Parkinson's disease.

BACKGROUND AND OBJECTIVE: A new expert system is proposed to discriminate healthy people from people with Parkinson's Disease (PD) in early stages by using Diadochokinesis tests. METHODS: The system is based on temporal and spectral features extracted from the Voice Onset Time (VOT) segments of /ka/ syllables, whose boundaries are delimited by a novel algorithm. For comparison purposes, the approach is applied also to /pa/ and /ta/ syllables. In order to develop and validate the system, a voice recording database composed of 27 individuals diagnosed with PD and 27 healthy controls has been collected. This database reflects an average disease stage of 1.85 ±â€¯0.55 according to Hoehn and Yahr scale. System design is based on feature extraction, feature selection and Support Vector Machine learning. RESULTS: The novel VOT algorithm, based on a simple and computationally efficient approach, demonstrates accurate estimation of VOT boundaries on /ka/ syllables for both healthy and PD-affected speakers. The PD detection approach based on /k/ plosive consonant achieves the highest discrimination capability (92.2% using 10-fold cross-validation and 94.4% in the case of leave-one-out method) in comparison to the corresponding versions based on the other two plosives (/p/ and /t/). CONCLUSION: A high accuracy has been obtained on a database with a lower average disease stage than previous articulatory databases presented in the literature.