Clinical haematology of the great bustard (Otis tarda)

The haematological parameters of healthy great bustards (Otis tarda L.) have been determined. The values obtained were red cell count (3.0 x 10(12) +/- 0.2 x 10(12/)1), white cell count (33.0 x 10(9) +/- 2.6 x 10(9)/1), haematocrit value (0.51 +/- 0.01 1/1), haemoglobin (13.0 +/- 0.3 g/dl), mean corpuscular volume (178.7 +/- 12.5 fl), mean cell haemoglobin concentration (25.0 +/- 0.6 g/dl), mean corpuscular haemoglobin (42.5 +/- 3.2 pg), differential white cell count: heterophils (22.5 x 10(9) +/- 0.7 x 10(9)/1), lymphocytes (6.0 x 10(9)+/-0.7 x 10(9)/1), eosinophils (2.7 x 10(9) +/- 0.3 x 10(9)/1) and monocytes (1.8 x 10(9)+/-0.2 x 10(9)/1)

Disección transcripcional del Locus GH del genoma humano

El locus de la hormona del crecimiento humano (hGH) presenta variaciones en los niveles de expre- sión en algunos de sus componentes hasta en tres órdenes de magnitud. Este estudio comparó deleciones (140 a 3,100 pb) y la fuerza de transcrip- ción de todos los promotores del locus con un gen reportero (hGH-N) mediante expresión transitoria. Los promotores largos tuvieron mayor expresión, paradójicamente hGH-V fue uno de los más acti- vos. Se detectaron tres elementos promotores ne- gativos y se evaluó la activación transcripcional di- ferencial para los diferentes promotores, mediante su respuesta a la acción de hormonas y cotransfec- ción de vectores expresores de factores transcripcionales

Overview of progress in European medium sized tokamaks towards an integrated plasma-edge/wall solution

Integrating the plasma core performance with an edge and scrape-off layer (SOL) that leads to tolerable heat and particle loads on the wall is a major challenge. The new European medium size tokamak task force (EU-MST) coordinates research on ASDEX Upgrade (AUG), MAST and TCV. This multi-machine approach within EU-MST, covering a wide parameter range, is instrumental to progress in the field, as ITER and DEMO core/pedestal and SOL parameters are not achievable simultaneously in present day devices. A two prong approach is adopted. On the one hand, scenarios with tolerable transient heat and particle loads, including active edge localised mode (ELM) control are developed. On the other hand, divertor solutions including advanced magnetic configurations are studied. Considerable progress has been made on both approaches, in particular in the fields of: ELM control with resonant magnetic perturbations (RMP), small ELM regimes, detachment onset and control, as well as filamentary scrape-off-layer transport. For example full ELM suppression has now been achieved on AUG at low collisionality with n = 2 RMP maintaining good confinement HH(98,y2) 0.95. Advances have been made with respect to detachment onset and control. Studies in advanced divertor configurations (Snowflake, Super-X and X-point target divertor) shed new light on SOL physics. Cross field filamentary transport has been characterised in a wide parameter regime on AUG, MAST and TCV progressing the theoretical and experimental understanding crucial for predicting first wall loads in ITER and DEMO. Conditions in the SOL also play a crucial role for ELM stability and access to small ELM regimes.European Commission (EUROfusion 633053

Dinámica de innovaciones en la producción de jitomate (Solanum lycopersicum) bajo invernadero en Puebla, México

The use of technological innovations in greenhouse vegetable growing translates into high yields to the producers. This study analyzes the innovation adoption index (InAI) in tomato production units (TPUs) under greenhouses in the municipalities of Aquixtla, Tetela de Ocampo, Tecamachalco and Tochtepec, state of Puebla and its relationship with the crop’s yield, in addition to understanding the stakeholders implicit in the dissemination of innovations through a social networks analysis. Interviews (103) were applied to producers in the second semester of 2017, using a structured questionnaire. A global InAI of 36% was obtained, highlighting the components of health and nutrition that showed an InAI of 57%. The social networks analysis showed that learning about innovations is done primarily between producers despite not having a formal organization. Private technical assistance is responsible for technology transfer in the TPUs, which is why it is important for decision makers and particularly for producers, by generating formal communication channels that allow exchanging experiences and fostering learning as a whole, with the aim of increasing the InAI and consequently improving the yield of TPUs in the state.El uso de innovaciones tecnológicas en el cultivo de hortalizas bajo invernadero se traduce en altos rendimientos para los productores. Esta investigación, analiza el índice de adopción de innovaciones (InAI) en las unidades de producción de jitomate (UPJ) bajo invernadero en los municipios de Aquixtla, Tetela de Ocampo, Tecamachalco y Tochtepec, estado de Puebla y su relación con el rendimiento del cultivo, además de conocer los actores implícitos en la difusión de innovaciones mediante un análisis de redes sociales. Se aplicaron 103 entrevistas a productores en el segundo semestre de 2017, utilizando un cuestionario estructurado. Se obtuvo un InAI global de 36%, destacando los componentes sanidad y nutrición que registraron un InAI de 57%. El análisis de redes sociales mostró que el aprendizaje de innovaciones se realiza principalmente entre productores a pesar de no contar con una organización formal. La asesoría técnica privada es la responsable de la transferencia de tecnologías en las UPJ. El InAI tiene una correlación positiva (p<0.05) con el rendimiento de las UPJ, por lo que es de importancia para los tomadores de decisiones y en particular para los productores, el generar canales formales de comunicación que permitan intercambiar experiencias fomentando el aprendizaje en conjunto, con la finalidad de aumentar el InAI y en consecuencia mejorar el rendimiento de las UPJ en el estado

In Silico analysis of protein neoplastic biomarkers for cervix and uterine cancer

Comunicaciones a congreso

Application of machine learning and artificial intelligence in the diagnosis and classification of polycystic ovarian syndrome: a systematic review

IntroductionPolycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity. Artificial intelligence (AI) and machine learning (ML) hold promise in improving diagnostics. Thus, we performed a systematic review of literature to identify the utility of AI/ML in the diagnosis or classification of PCOS.MethodsWe applied a search strategy using the following databases MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, the Web of Science, and the IEEE Xplore Digital Library using relevant keywords. Eligible studies were identified, and results were extracted for their synthesis from inception until January 1, 2022.Results135 studies were screened and ultimately, 31 studies were included in this study. Data sources used by the AI/ML interventions included clinical data, electronic health records, and genetic and proteomic data. Ten studies (32%) employed standardized criteria (NIH, Rotterdam, or Revised International PCOS classification), while 17 (55%) used clinical information with/without imaging. The most common AI techniques employed were support vector machine (42% studies), K-nearest neighbor (26%), and regression models (23%) were the commonest AI/ML. Receiver operating curves (ROC) were employed to compare AI/ML with clinical diagnosis. Area under the ROC ranged from 73% to 100% (n=7 studies), diagnostic accuracy from 89% to 100% (n=4 studies), sensitivity from 41% to 100% (n=10 studies), specificity from 75% to 100% (n=10 studies), positive predictive value (PPV) from 68% to 95% (n=4 studies), and negative predictive value (NPV) from 94% to 99% (n=2 studies).ConclusionArtificial intelligence and machine learning provide a high diagnostic and classification performance in detecting PCOS, thereby providing an avenue for early diagnosis of this disorder. However, AI-based studies should use standardized PCOS diagnostic criteria to enhance the clinical applicability of AI/ML in PCOS and improve adherence to methodological and reporting guidelines for maximum diagnostic utility.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42022295287

Characterization of modular deposits for urban drainage networks using CFD techniques

[EN] The growing urban development of population centers in much of the world joined with the significant effects of climate change are causing an increasingly important and recurring increase of the damage caused by flooding. Much of the drainage networks of cities were designed for precipitation characteristics and return periods that have proved to be insufficient with the lapse of time. Therefore, solutions need to be addressed both to reduce runoff generated flows as to control circulating ones through the rainwater drainage networks. All these flow control rain technologies are commonly known as SUDS (Sustainable Urban Drainage), term that encompasses a multitude of solutions to control runoff although many of them require significant costs that make them practically unviable. Therefore, not only should focus on reducing runoff input to the network but also in the flow control techniques development. The idea is to design strategies to reduce flow rain peaks and maximize the capacity of existing networks. The use of detention and storm tanks for flood control is a solution increasingly used as an alternative one to control increased rainfall caused by climate change [1]. Nature and execution of storm tanks can be very diverse, from conventional way based on concrete structures to the most innovative ones in which modular structures are employed to improve the construction speed if many modular units are required at the same time that minimizing urban supply disruption is achieved. Currently, a wide range of modular structures exists on the market with both, different geometries and sizes. In this study the Aquacell brand supplied by Mexichem-PAVCO in Colombia shown in Fig. 1 has been chosen for the development of this study.S849218

The Medical Oncology resident mentor: situation and workload

Purpose: The Spanish Society for Medical Oncology (SEOM, for its acronym in Spanish) and the National Commission for the Specialty of Medical Oncology seek to highlight the important workload and unrecognized dedication entailed in working as a Medical Oncology (MO) resident mentor, as well as its relevance for the quality of teaching units and the future of the specialty. Materials and methods: The current situation and opinion regarding the activity of MO resident mentors was analyzed by reviewing the standing national and autonomic community regulations and via an online survey targeting mentors, residents, and physicians who are not MO mentors. The project was supervised by a specially designated group that agreed on a proposal containing recommendations for improvement. Results: Of the MO mentors, 90% stated that they did not have enough time to perform their mentoring duties. An estimated 172 h/year on average was dedicated to mentoring, which represents 10.1% of the total time. MO mentors dedicate an average of 6.9 h/month to these duties outside their workday. Forty-five percent of the mentors feel that their role is scantly recognized, if at all. Conclusions: The study reveals the substantial dedication and growing complexity of MO resident mentoring. A series of recommendations are issued to improve the conditions in which it is carried out, including the design of systems that adapt to the professional activity in those departments that have time set aside for mentoring tasks

Desarrollo de la Red Aerobiológica de Castilla y León (RACYL)

XV lnternational A.P.L.E. Symposium of Palynolog