Seasonal Variation of Ectosymbiotic Ciliates on Farmed and Wild Shrimps from Coastal Yucatan, Mexico

High levels of ciliate infestation can affect respiration, feed intake, and locomotion in farmed shrimps in the tropics. Information on seasonal variation of the infestation parameters of ciliates is scarce, but it would be useful for determining the suitability of preventive measures or therapeutic treatment if necessary. This study aimed to describe the prevalence and mean intensity of infestation (MII) of ciliates on wild native shrimps Penaeus (Farfantepenaeus) brasiliensis and P. (Farfantepenaeus) duorarum and farm-cultured juvenile shrimp Penaeus (Litopenaeus) vannamei over an annual cycle and to determine whether an association existed among physicochemical factors and infestation on cultured shrimp. The ectosymbiotic ciliates Acineta tuberosa, Epistylis sp., and Zoothamnium sp. infested both farmed and wild shrimps. Based on examination of 360 farmed specimens of P. vannamei (30 examined each month), the species with highest infestation were Epistylis sp., (prevalence range = 22 –100%; MII range = 13 ± 28 – 126 ± 124) and Zoothamnium sp. (0–87%; 0 – 144 ± 132). For both species, the highest values occurred during the rainy season. A total of 288 wild specimens of P. brasiliensis plus 120 of P. duorarum obtained during three recognized seasons—dry (February to May), rainy (June to September), and north-wind (October to January)—had ciliate infestations that were significantly lower than those from farmed shrimp. For P. brasiliensis, the ciliate species with the highest infestation values were Zoothamnium sp. (0–66%; 0.03 ± 0.2 – 66 ± 92), while on P. duorarum, were for Epistylis sp. (0–46%; 0 – 8 ± 16). Using multiple linear regression, we found significant relationships between stocking density, survival, temperature, turbidity, and intensity of infestation of the ciliates. However, the regression accounted for only 11–26% of the variance (R2), meaning that there are still other environmental and biological variables that should be included to increase the reliability of the model. Thus, the physicochemical conditions of the farm increase the probability of ciliate transmission, especially during the rainy season

Maximum likelihood soft-output detection through Sphere Decoding combined with box optimization

This is the author’s version of a work that was accepted for publication in Signal Processing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Signal Processing 125 (2016) 249–260. DOI 10.1016/j.sigpro.2016.02.006.This paper focuses on the improvement of known algorithms for maximum likelihood soft-output detection. These algorithms usually have large computational complexity, that can be reduced by using clipping. Taking two well-known soft-output maximum likelihood algorithms (Repeated Tree Search and Single Tree Search) as a starting point, a number of modifications (based mainly on box optimization techniques) are proposed to improve the efficiency of the search. As a result, two new algorithms are proposed for soft-output maximum likelihood detection. One of them is based on Repeated Tree Search (which can be applied with and without clipping). The other one is based on Single Tree Search, which can only be applied to the case with clipping. The proposed algorithms are compared with the Single Tree Search algorithm, and their efficiency is evaluated in standard detection problems (4 4 16-QAM and 4 4 64-QAM) with and without clipping. The results show that the efficiency of the proposed algorithms is similar to that of the Single Tree Search algorithm in the case 4 4 16-QAM; however, in the case 4 4 64- QAM, the new algorithms are far more efficient than the Single Tree Search algorithm. & 2016 Elsevier B.V. All rights reserved.This work has been partially funded by Generalitat Valenciana through the projects ISIC/2012/006 and PROMETEO II/2014/003, and by Ministerio Espanol de Economia y Competitividad through the project TEC2012-38142-C04 and through the Grant RACHEL TEC2013-47141-C4-4-R.García Mollá, VM.; Simarro Haro, MDLA.; Martínez Zaldívar, FJ.; González Salvador, A.; Vidal Maciá, AM. (2016). Maximum likelihood soft-output detection through Sphere Decoding combined with box optimization. Signal Processing. 125:249-260. https://doi.org/10.1016/j.sigpro.2016.02.006S24926012

Population Characteristics of Human-Commensal Rodents Present in Households from Mérida, Yucatán, México

Anthropocommensal rodents live in close proximity to humans in many habitats around the world. They are a threat to public health because of the pathogens they carry. Recent studies in Mérida, Yucatán, México, have shown that commensal rodents harbor potential zoonotic pathogens such as bacteria, helminths, and viruses. In this study, we describe reproductive and demographic parameters of house mice and black rats present in households from Mérida, Yucatán, México, a municipality located in a tropical region in southern México. Rodents were trapped in 142 households within the municipality of Mérida from 2011 to 2014. A total of 832 rodents were trapped, constituting 556 (66.8%) house mice (Mus musculus) and 276 (33.2%) black rats (Rattus rattus). The sex ratio in mice was different than parity, while in rats it was 1:1. Mice in the weight class 8.1–12 g were most abundant in both females (52.9%) and males (57.2%). On the other hand, rats weighing ≤ 40 g (25% of females and 28.6% of males) were most abundant. The percentage of pregnancy in mice was 46.7%, whereas in rats it was 21.3%. The mean number of embryos was 4.7 and 5.8 in mice and rats, respectively. This study provides relevant demographic information on the ecology of commensal rodents from a tropical region of Latin America. We consider that our findings could be useful as a first step toward understanding the ecological behavior of rodent populations in tropical regions

Parasitic copepods (Crustacea, Hexanauplia) on fishes from the lagoon flats of Palmyra Atoll, Central Pacific

We surveyed copepods parasitic on the fishes at Palmyra, a remote atoll in the Central Indo-Pacific faunal region. In total, we collected 849 individual fish, representing 44 species, from the intertidal lagoon flats at Palmyra and recovered 17 parasitic copepod species. The parasitic copepods were: Orbitacolax williamsi on Mulloidichthys flavolineatus; Anuretes serratus on Acanthurus xanthopterus; Caligus confusus on Carangoides ferdau, Carangoides orthogrammus, Caranx ignobilis, Caranx melampygus, and Caranx papuensis; Caligus kapuhili on Chaetodon auriga and Chaetodon lunula; Caligus laticaudus on Rhinecanthus aculeatus, Pseudobalistes flavimarginatus, M. flavolineatus, Upeneus taeniopterus, Chrysiptera glauca, and Epinephalus merra; Caligus mutabilis on Lutjanus fulvus and Lutjanus monostigma; Caligus randalli on C. ignobilis; Caligus sp. on L. fulvus; Caritus serratus on Chanos chanos; Lepeophtheirus lewisi on A. xanthopterus; Lepeophtheirus uluus on C. ignobilis; Dissonus similis on Arothron hispidus; Nemesis sp. on Carcharhinus melanopterus; Hatschekia longiabdominalis on A. hispidus; Hatschekia bicaudata on Chaetodon auriga and Chaetodon lunula; Kroyeria longicauda on C. melanopterus and Lernanthropus sp. on Kyphosus cinerascens. All copepod species reported here have been previously reported from the Indo-Pacific but represent new geographical records for Palmyra, demonstrating large-scale parasite dispersion strategies

Ocean monitoring, observation network and modelling of the Gulf of Mexico by CIGOM

The tragic accident of the Macondo platform operated by British Petroleum (BP) unleashed in 2010 one of the largest oil spills in history, lasting over three months, spilling nearly 500 million liters of oil in one of the most biodiverse ocean regions. This accident revealed the technological deficiencies for the control of a spill in deep waters of the hydrocarbon industry. Simultaneously it showed important gaps in knowledge to predict the propagation and fate of the large volumes of hydrocarbons at depth and on the surface ocean and, more importantly, on their impact on the great ecosystem of the Gulf of Mexico. The necessity to understand and predict the transport, fate and ecosystem-level impacts of large oil spills in the southern Gulf of Mexico, a key region for oil exploration and extraction, led policymakers, scientists, and industry representatives from PEMEX (the Mexican oil company) to jointly launch an ocean observation project (2015-22) aimed to provide a multi-layered environmental baseline, develop a modern monitoring and computational modeling capacity and promote scientific understanding of the marine environment throughout the Mexican Exclusive Economic Zone (EEZ). The initiative, led by the Research Consortium for the Gulf of Mexico (CIGoM), brought together more than 300 multidisciplinary researchers from more than a two dozen institutions in Mexico and abroad, including the Centre for Scientific Research and Higher Education of Ensenada (CICESE) as the leading institution, the National Autonomous University of Mexico (UNAM), the Centre for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV) in Mérida, the Autonomous University of Baja California (UABC), and the Centre for Engineering and Industrial Development (CIDESI). Financial support was provided by the National Council for Science and Technology and the Ministry of Energy Hydrocarbon Fund

Expert considerations and consensus for using dogs to detect human SARS-CoV-2-infections

Funding Information: This Open Access publication was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 491094227 “Open Access Publication Funding” and the University of Veterinary Medicine Hannover, Foundation.Peer reviewe

Prognostic implications of comorbidity patterns in critically ill COVID-19 patients: A multicenter, observational study

Background The clinical heterogeneity of COVID-19 suggests the existence of different phenotypes with prognostic implications. We aimed to analyze comorbidity patterns in critically ill COVID-19 patients and assess their impact on in-hospital outcomes, response to treatment and sequelae. Methods Multicenter prospective/retrospective observational study in intensive care units of 55 Spanish hospitals. 5866 PCR-confirmed COVID-19 patients had comorbidities recorded at hospital admission; clinical and biological parameters, in-hospital procedures and complications throughout the stay; and, clinical complications, persistent symptoms and sequelae at 3 and 6 months. Findings Latent class analysis identified 3 phenotypes using training and test subcohorts: low-morbidity (n=3385; 58%), younger and with few comorbidities; high-morbidity (n=2074; 35%), with high comorbid burden; and renal-morbidity (n=407; 7%), with chronic kidney disease (CKD), high comorbidity burden and the worst oxygenation profile. Renal-morbidity and high-morbidity had more in-hospital complications and higher mortality risk than low-morbidity (adjusted HR (95% CI): 1.57 (1.34-1.84) and 1.16 (1.05-1.28), respectively). Corticosteroids, but not tocilizumab, were associated with lower mortality risk (HR (95% CI) 0.76 (0.63-0.93)), especially in renal-morbidity and high-morbidity. Renal-morbidity and high-morbidity showed the worst lung function throughout the follow-up, with renal-morbidity having the highest risk of infectious complications (6%), emergency visits (29%) or hospital readmissions (14%) at 6 months (p<0.01). Interpretation Comorbidity-based phenotypes were identified and associated with different expression of in-hospital complications, mortality, treatment response, and sequelae, with CKD playing a major role. This could help clinicians in day-to-day decision making including the management of post-discharge COVID-19 sequelae. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd

Design, Performance and Calibration of the CMS Forward Calorimeter Wedges

We report on the test beam results and calibration methods using charged particles of the CMS Forward Calorimeter (HF). The HF calorimeter covers a large pseudorapidity region (3\l |\eta| \le 5), and is essential for large number of physics channels with missing transverse energy. It is also expected to play a prominent role in the measurement of forward tagging jets in weak boson fusion channels. The HF calorimeter is based on steel absorber with embedded fused-silica-core optical fibers where Cherenkov radiation forms the basis of signal generation. Thus, the detector is essentially sensitive only to the electromagnetic shower core and is highly non-compensating (e/h \approx 5). This feature is also manifest in narrow and relatively short showers compared to similar calorimeters based on ionization. The choice of fused-silica optical fibers as active material is dictated by its exceptional radiation hardness. The electromagnetic energy resolution is dominated by photoelectron statistics and can be expressed in the customary form as a/\sqrt{E} + b. The stochastic term a is 198% and the constant term b is 9%. The hadronic energy resolution is largely determined by the fluctuations in the neutral pion production in showers, and when it is expressed as in the electromagnetic case, a = 280% and b = 11%

Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Funder: Funder: Fundación bancaria ‘La Caixa’ Number: LCF/PR/PR16/51110003 Funder: Grifols SA Number: LCF/PR/PR16/51110003 Funder: European Union/EFPIA Innovative Medicines Initiative Joint Number: 115975 Funder: JPco-fuND FP-829-029 Number: 733051061Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease