Dynamics of sexual and parthenogenetic populations of Eucypris virens (Crustacea: Ostracoda) in three temporary ponds

Eucyprisvirens is a freshwater ostracod in which both sexual reproduction and parthenogenesis occur. Sympatric coexistence of both reproductive modes is known in zones of overlap. This renders the species a potentially valuable model organism to study the ‘queen of evolutionary problems', i.e. why sex is so successful despite its costs (paradox of sex). In order to maximally exploit this potential, a broad knowledge of the species' ecology is essential, including an understanding of its life history and population dynamics. Here, the phenology of the species was followed in three temporary ponds through monthly (Spain) or fortnightly (Poland) samplings, throughout an inundation period. This study confirms the wide ecological tolerances of E.virens. Although the species is generally assumed to be univoltine, two hatching periods were observed in the Spanish sites. Biotic interactions, especially predation, appear to be the important determinants of population dynamics in long-hydroperiod sites. Abiotic conditions may influence population dynamics through their impact on egg hatching. In the site with male presence, the initially female-biased sex ratio evolved towards a balanced sex ratio through the season. No consistent differences in limb morphology were observed between females originating from the three study sites. On the other hand, valve size of adult females varied among sites, possibly influenced by local environmental conditions (mainly salinity and pH) as well as the expected genetic diversit

Differential diagnosis between Parkinson's disease and essential tremor using the smartphone's accelerometer

Background: The differential diagnosis between patients with essential tremor (ET) and those with Parkinson's disease (PD) whose main manifestation is tremor may be difficult unless using complex neuroimaging techniques such as 123I-FP-CIT SPECT. We considered that using smartphone's accelerometer to stablish a diagnostic test based on time-frequency differences between PD an ET could support the clinical diagnosis. Methods: The study was carried out in 17 patients with PD, 16 patients with ET, 12 healthy volunteers and 7 patients with tremor of undecided diagnosis (TUD), who were re-evaluated one year after the first visit to reach the definite diagnosis. The smartphone was placed over the hand dorsum to record epochs of 30 s at rest and 30 s during arm stretching. We generated frequency power spectra and calculated receiver operating characteristics curves (ROC) curves of total spectral power, to establish a threshold to separate subjects with and without tremor. In patients with PD and ET, we found that the ROC curve of relative energy was the feature discriminating better between the two groups. This threshold was then used to classify the TUD patients. Results: We could correctly classify 49 out of 52 subjects in the category with/without tremor (97.96% sensitivity and 83.3% specificity) and 27 out of 32 patients in the category PD/ET (84.38% discrimination accuracy). Among TUD patients, 2 of 2 PD and 2 of 4 ET were correctly classified, and one patient having PD plus ET was classified as PD. Conclusions: Based on the analysis of smartphone accelerometer recordings, we found several kinematic features in the analysis of tremor that distinguished first between healthy subjects and patients and, ultimately, between PD and ET patients. The proposed method can give immediate results for the clinician to gain valuable information for the diagnosis of tremor. This can be useful in environments where more sophisticated diagnostic techniques are unavailable

Experimental test on the use of MS-222 for ostracod anaesthesia: concentration, immersion period and recovery time

Anaesthesia of animals may be useful for different purposes, particularly for veterinary reasons or in experimental research, for manipulation or treatment of immobilized but alive animals. Its use in crustaceans is not uncommon, but it has never been described for Ostracoda. We provide brief and preliminary guidelines on the use of the tricaine mesylate (MS-222) on the widespread freshwater ostracod Eucypris virens and we show that this compound is an effective anaesthetic used as a bath treatment at minimum concentrations of 500 mg L-1. This value is considerably higher than that recommended for other aquatic animals like fish. Recovery time, ranging from 5 to 15 minutes, is mostly determined by anaesthetic bath concentration, while bath duration influenced to a lesser extent. Anaesthesia induced with MS-222 can prove useful for minute manipulation of living ostracods e.g. for identification, marking or image capture under the microscope

Pyriproxyfen, a juvenoid hormone analog, does not induce male production in parthenogenetic lineages of Eucypris virens (Crustacea: Ostracoda)

Analogs of juvenoid hormones are increasingly recommended for controlling insect pests in agriculture. One of these analogs, pyriproxyfen, was found to be very potent in inducing male production in Daphnia under laboratory conditions, even after acute exposure. Other studies also demonstrated a major role of juvenoid hormones for the sex determination in arthropods that have sex chromosomes. We exposed parthenogenetic lineages of the freshwater ostracod Eucypris virens to a wide range of pyriproxyfen concentrations, and compared mortality and fecundity between treated and control animals. Animals exposed to the highest concentrations of pyriproxyfen (3-30 nM) experienced a higher mortality than control animals, but no treatment effects were found on the production rates of eggs and hatchlings. Also, hatchlings that emerged from eggs deposited by treated individuals did not suffer from an increased mortality rate. No males were found among the 91 hatchlings that could be grown to adulthood. These results suggest that previous observations of a reduced population growth of ostracods in treated field crops might not be due to an alteration of the sex ratio, but rather to an increased mortality of the exposed females

Deep diving in the PACIFIC: Practical issues in stage III non-small cell lung cancer to avoid shipwreck

After publication of the PACIFIC trial results, immune checkpoint inhibitor-based immunotherapy was included in the treatment algorithm of locally advanced non-small cell lung cancer (NSCLC). The PACIFIC trial demonstrated that 12 mo of durvalumab consolidation therapy after radical-intent platinum doublet chemotherapy with concomitant radiotherapy improved both progression-free survival and overall survival in patients with unresectable stage III NSCLC. This is the first treatment in decades to successfully improve survival in this clinical setting, with manageable toxicity and without deterioration in quality of life. The integration of durvalumab in the management of locally advanced NSCLC accentuates the need for multidisciplinary, coordinated decision-making among lung cancer specialists, bringing new challenges and controversies as well as important changes in clinical work routines. The aim of the present article is to review-from a practical, multidisciplinary perspective-the findings and implications of the PACIFIC trial. We evaluate the immunobiological basis of durvalumab as well as practical aspects related to programmed cell death ligand 1 determination. In addition, we comprehensively assess the efficacy and toxicity data from the PACIFIC trial and discuss the controversies and practical aspects of incorporating durvalumab into routine clinical practice. Finally, we discuss unresolved questions and future challenges. In short, the present document aims to provide clinicians with a practical guide for the application of the PACIFIC regimen in routine clinical practice.Sin financiaciónNo data 2020UE

Machine Learning Model for Predicting Mortality Risk in Patients With Complex Chronic Conditions: Retrospective Analysis

Background: The health care system is undergoing a shift toward a more patient-centered approach for individuals with chronic and complex conditions, which presents a series of challenges, such as predicting hospital needs and optimizing resources. At the same time, the exponential increase in health data availability has made it possible to apply advanced statistics and artificial intelligence techniques to develop decision-support systems and improve resource planning, diagnosis, and patient screening. These methods are key to automating the analysis of large volumes of medical data and reducing professional workloads. Objective: This article aims to present a machine learning model and a case study in a cohort of patients with highly complex conditions. The object was to predict mortality within the following 4 years and early mortality over 6 months following diagnosis. The method used easily accessible variables and health care resource utilization information. Methods: A classification algorithm was selected among 6 models implemented and evaluated using a stratified cross-validation strategy with k=10 and a 70/30 train-test split. The evaluation metrics used included accuracy, recall, precision, F1 -score, and area under the receiver operating characteristic (AUROC) curve. Results: The model predicted patient death with an 87% accuracy, recall of 87%, precision of 82%, F1 -score of 84%, and area under the curve (AUC) of 0.88 using the best model, the Extreme Gradient Boosting (XGBoost) classifier. The results were worse when predicting premature deaths (following 6 months) with an 83% accuracy (recall=55%, precision=64% F1 -score=57%, and AUC=0.88) using the Gradient Boosting (GRBoost) classifier. Conclusions: This study showcases encouraging outcomes in forecasting mortality among patients with intricate and persistent health conditions. The employed variables are conveniently accessible, and the incorporation of health care resource utilization information of the patient, which has not been employed by current state-of-the-art approaches, displays promising predictive power. The proposed prediction model is designed to efficiently identify cases that need customized care and proactively anticipate the demand for critical resources by health care providers