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Background Toxoplasma gondii is the third most important contributor to health burden caused by food-borne illness. Ingestion of tissue cysts from undercooked meat is an important source of horizontal transmission to humans. However, there is an increasing awareness of the consumption of fresh fruit and vegetables, as a possible source for oocyst transmission, since this stage of the parasite can persist and remain infective in soil and water for long time. Herein, we outline findings related with detection of T. gondii oocysts in vegetables and berry fruits, which are usually raw consumed. The procedure includes the estimation of the number of oocysts. Methods Food samples were collected from local producers and supermarket suppliers. Toxoplasma gondii oocysts were concentrated after washing the samples by applying high resolution water filtration and immunomagnetic separation (method 1623.1: EPA 816-R-12-001-Jan 2012), in order to (i) remove potential Cryptosporidium spp. oocysts and Giardia spp. cysts present in the samples; and (ii) select T. gondii oocysts. Toxoplasma gondii oocyst detection and an estimation of their numbers was performed by conventional PCR and real time qPCR, using specific primers for a 183-bp sequence of the T. gondii repetitive DNA region. All PCR-positive DNA samples were purified and sequenced. Restriction enzyme digestion with Eco RV endonuclease confirmed the presence of the T. gondii DNA fragment. In addition, the presence of the parasite was observed by fluorescent microscopy, taking advantage of the oocysts autofluorescence under UV light. Results Forty percent of the analysed samples (95% CI: 25.5–56.5%) presented the expected PCR and digested DNA fragments. These fragments were confirmed by sequencing. Microscopic autofluorescence supported the presence of T. gondii -like oocysts. The estimated mean (± SE) oocyst concentration was 23.5 ± 12.1 oocysts/g, with a range of 0.6–179.9 oocysts/g. Conclusions Our findings provide relevant evidence of contamination of fresh vegetables and berry fruits with T. gondii oocysts.

Tampered multimedia content is being increasingly used in a broad range of cybercrime activities. The spread of fake news, misinformation, digital kidnapping, and ransomware-related crimes are amongst the most recurrent crimes in which manipulated digital photos and videos are the perpetrating and disseminating medium. Criminal investigation has been challenged in applying machine learning techniques to automatically distinguish between fake and genuine seized photos and videos. Despite the pertinent need for manual validation, easy-to-use platforms for digital forensics are essential to automate and facilitate the detection of tampered content and to help criminal investigators with their work. This paper presents a machine learning Support Vector Machines (SVM) based method to distinguish between genuine and fake multimedia files, namely digital photos and videos, which may indicate the presence of deepfake content. The method was implemented in Python and integrated as new modules in the widely used digital forensics application Autopsy. The implemented approach extracts a set of simple features resulting from the application of a Discrete Fourier Transform (DFT) to digital photos and video frames. The model was evaluated with a large dataset of classified multimedia files containing both legitimate and fake photos and frames extracted from videos. Regarding deepfake detection in videos, the Celeb-DFv1 dataset was used, featuring 590 original videos collected from YouTube, and covering different subjects. The results obtained with the 5-fold cross-validation outperformed those SVM-based methods documented in the literature, by achieving an average F1-score of 99.53%, 79.55%, and 89.10%, respectively for photos, videos, and a mixture of both types of content. A benchmark with state-of-the-art methods was also done, by comparing the proposed SVM method with deep learning approaches, namely Convolutional Neural Networks (CNN). Despite CNN having outperformed the proposed DFT-SVM compound method, the competitiveness of the results attained by DFT-SVM and the substantially reduced processing time make it appropriate to be implemented and embedded into Autopsy modules, by predicting the level of fakeness calculated for each analyzed multimedia file.

Background Taenia solium and Taenia saginata are zoonotic parasites of public health importance. Data on their occurrence in humans and animals in western Europe are incomplete and fragmented. In this study, we aimed to update the current knowledge on the epidemiology of these parasites in this region. Methods We conducted a systematic review of scientific and grey literature published from 1990 to 2015 on the epidemiology of T. saginata and T. solium in humans and animals. Additionally, data about disease occurrence were actively sought by contacting local experts in the different countries. Results Taeniosis cases were found in twelve out of eighteen countries in western Europe. No cases were identified in Iceland, Ireland, Luxembourg, Norway, Sweden and Switzerland. For Denmark, Netherlands, Portugal, Slovenia, Spain and the UK, annual taeniosis cases were reported and the number of detected cases per year ranged between 1 and 114. Detected prevalences ranged from 0.05 to 0.27%, whereas estimated prevalences ranged from 0.02 to 0.67%. Most taeniosis cases were reported as Taenia spp. or T. saginata , although T. solium was reported in Denmark, France, Italy, Spain, Slovenia, Portugal and the UK. Human cysticercosis cases were reported in all western European countries except for Iceland, with the highest number originating from Portugal and Spain. Most human cysticercosis cases were suspected to have acquired the infection outside western Europe. Cases of T. solium in pigs were found in Austria and Portugal, but only the two cases from Portugal were confirmed with molecular methods. Germany, Spain and Slovenia reported porcine cysticercosis, but made no Taenia species distinction. Bovine cysticercosis was detected in all countries except for Iceland, with a prevalence based on meat inspection of 0.0002–7.82%. Conclusions Detection and reporting of taeniosis in western Europe should be improved. The existence of T. solium tapeworm carriers, of suspected autochthonous cases of human cysticercosis and the lack of confirmation of porcine cysticercosis cases deserve further attention. Suspected cases of T. solium in pigs should be confirmed by molecular methods. Both taeniosis and human cysticercosis should be notifiable and surveillance in animals should be improved.

Description of fractured reservoir rock under uncertainties in a 3D model and integration with reservoir simulation is still a challenging topic. In particular, mapping the potential zones with a reservoir quality can be very useful for making decisions and support development planning. This mapping can be done through the concept of flow units. In this paper, an integrated approach including a Hierarchical Cluster Analysis (HCA), geostatistical modeling and uncertainty analysis is developed and applied to a fractured carbonate in order to integrate on numerical simulation. The workflow begins with different HCA methods, performed to well-logs in three wells, to identify flow units and rock types. Geostatistical techniques are then applied to extend the flow units, petrophysical properties and fractures into the inter-well area. Finally, uncertainty analysis is applied to combine different types of uncertainties for generating ensemble reservoir simulation models. The obtained clusters from different HCA methods are evaluated by the cophenetic coefficient, correlation coefficient, and variation coefficient, and the most appropriate clustering method is used to identify flow units for geostatistical modeling. We subsequently define uncertainties for static and dynamic properties such as permeability, porosity, net-to-gross, fracture, water-relative permeability, fluid properties, and rock compressibility. Discretized Latin Hypercube with Geostatistical (DLHG) method is applied to combine the defined uncertainties and create an ensemble of 200 simulation models which can span the uncertainty space. Eventually, a base production strategy is defined under operational conditions to check the consistency and reliability of the models created with UNISIM-II-R (reference model) as a real reservoir with known results. Results represent the compatibility of the methodology to characterize fractured reservoirs since those models are consistent with the reference model (used to generate the simulation models). The proposed workflow provides an efficient and useful means of supporting development planning under uncertainty.

With climate change, drought is expected to increase, and its negative impacts will be particularly important in developing countries, usually with rainfall-dependent agriculture. The Cabo Verde archipelago is characterized by limited resources, remoteness, vulnerability to natural disasters, and a fragile environment. In this study, we provide the first report of the current status and trends of agriculture in Cabo Verde. We present data on the current performance of agricultural production areas in these islands and discuss them in terms of their most important natural constraint, water. Also, we assess the impact of institutional strategies on crop production and evaluate recent mechanisms that have been engaged towards agrarian development in this archipelago. Our results show that, among the ten Cabo Verde Islands, Santiago has the largest area used for agriculture (52.5%), followed by Santo Antão (16%) and Fogo (15.8%), and that rainfed farming dominates in all of them. The staple crops, such as maize and beans, are produced through rainfed subsistence farming, whereas irrigated crops (i.e., sugarcane, tomatoes) are mostly grown for commercial purposes. The prolonged drought periods, exposure, erosion and soil degradation, which led to increasing desertification over the last decades, have been identified as the main constraints to agrarian development across the ten islands of the archipelago. The strategies of Cabo Verde government to mitigate water scarcity through small-scale irrigation based mainly on small dams and drip irrigation technology have a marked effect on agricultural production in the predominantly arid and semi-arid areas of this archipelago.

The present study provides a critical analysis of the introduction of exotic food crop species and their impact on agricultural transformations in Guinea-Bissau, based on survey data and a review of the literature from the 1800s to the present. It applies a multidisciplinary analysis to map historical and contemporary agrarian knowledge in Guinea-Bissau, presenting the first list of exotic cultivated species introduced in the country. Our results show that many introduced crops have gained widespread acceptance among local producers, with 63 exotic cultivated species native to America and Asia. The most representative families are Fabaceae, Solanaceae, and Anacardiaceae, including the country’s main former and current cash crops. First driven by peanuts in colonial times and by cashew after independence from 1980s onwards, Guinea-Bissau rapidly became one of Africa’s major exporters. The current cashew monoculture—like peanuts before it—relies almost exclusively on smallholder agriculture, raising concerns with regard to biodiversity, sustainability, and food security. The paper analyses historical trends in agro-economic transformations taking into account policies, programs, performance, and scientific research. Despite the existence of a long-standing single crop economy, further research is needed in this largely understudied country to assess the impact of long-term agrarian change.

Background Madelung’s disease (MD) is a rare disease, more common in Mediterranean countries and associated with alcohol abuse. However, MD etiology remains not completely understood. Objective The aim of this study was to investigate clinical features, treatment options and outcomes in patients with MD treated in our plastic surgery department. Methods We retrospectively reviewed 59 cases of MD operated on between 2004 and 2013. Demographic information, location of the deposits, associated pathology and habits, number and type of surgeries performed, surgical complications and disease evolution were analyzed. Results Ninety percent of the patients were males. Active or past history of alcohol abuse was reported by 86%. The main affected areas were anterior and posterior neck. A total of 230 surgical procedures were performed. Open surgery was used on 192 occasions (83.5%), liposuction alone on 30 procedures (13%) and lipectomy combined with liposuction on 8 interventions (3.5%). Surgical complications were found in 41 procedures (17.8%). Twenty-three patients (39%) were identified as having disease recurrence of the operated site in a mean time of 3.8 years. Alcohol consumption was not clearly associated with disease recurrence. Conclusions Demographic characteristics of the studied cohort stand for published data. It is our opinion that lipectomy/dermolipectomy provides better aesthetic and functional results. Lipectomy procedures allow a thorough excision, correct identification of noble structures and careful hemostasis. Liposuction techniques, even ultrasound-assisted ones, had limited efficacy for the treatment of large masses. A long follow-up period is recommended considering the high propensity and mean time to recurrence. Level of Evidence IV This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Toxoplasmosis is the most reported parasitic zoonosis in Europe, with implications in human health and in the veterinary field. There is an increasing need to develop serotyping of Toxoplasma gondii (T. gondii) in view of greater sensitivity and efficiency, through the definition of new targets and new methodologies. Nanotechnology is a promising approach, with impact in the development of point-of-care devices. The aim of this work was to develop a simple but highly efficient method for Toxoplasma gondii serotyping based on gold nanoparticles. A simple colorimetric method was developed using gold nanoparticles modified with the synthetic polymorphic peptide derived from GRA6 antigen specific for type II T. gondii. The method of preparation of the gold nanoprobes and the experimental conditions for the detection were found to be critical for a sensitive discrimination between positive and negative sera. The optimized method was used to detect antibodies anti-GRA6II both in mice and human serum samples. These results clearly demonstrate that a biosensor-based immunoassay using AuNPs conjugated with polymorphic synthetic peptides can be developed and used as a serotyping device

Deepfake and manipulated digital photos and videos are being increasingly used in a myriad of cybercrimes. Ransomware, the dissemination of fake news, and digital kidnapping-related crimes are the most recurrent, in which tampered multimedia content has been the primordial disseminating vehicle. Digital forensic analysis tools are being widely used by criminal investigations to automate the identification of digital evidence in seized electronic equipment. The number of files to be processed and the complexity of the crimes under analysis have highlighted the need to employ efficient digital forensics techniques grounded on state-of-the-art technologies. Machine Learning (ML) researchers have been challenged to apply techniques and methods to improve the automatic detection of manipulated multimedia content. However, the implementation of such methods have not yet been massively incorporated into digital forensic tools, mostly due to the lack of realistic and well-structured datasets of photos and videos. The diversity and richness of the datasets are crucial to benchmark the ML models and to evaluate their appropriateness to be applied in real-world digital forensics applications. An example is the development of third-party modules for the widely used Autopsy digital forensic application. This paper presents a dataset obtained by extracting a set of simple features from genuine and manipulated photos and videos, which are part of state-of-the-art existing datasets. The resulting dataset is balanced, and each entry comprises a label and a vector of numeric values corresponding to the features extracted through a Discrete Fourier Transform (DFT). The dataset is available in a GitHub repository, and the total amount of photos and video frames is 40,588 and 12,400, respectively. The dataset was validated and benchmarked with deep learning Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) methods; however, a plethora of other existing ones can be applied. Generically, the results show a better F1-score for CNN when comparing with SVM, both for photos and videos processing. CNN achieved an F1-score of 0.9968 and 0.8415 for photos and videos, respectively. Regarding SVM, the results obtained with 5-fold cross-validation are 0.9953 and 0.7955, respectively, for photos and videos processing. A set of methods written in Python is available for the researchers, namely to preprocess and extract the features from the original photos and videos files and to build the training and testing sets. Additional methods are also available to convert the original PKL files into CSV and TXT, which gives more flexibility for the ML researchers to use the dataset on existing ML frameworks and tools.

BackgroundEndovascular treatment (EVT) is the standard of care for selected patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO).ObjectiveTo systematically review the available data on: (1) incidence, predictors, and outcomes of patients with reocclusion after successful EVT for AIS and, (2) the characteristics, complications, and outcomes of patients with reocclusion treated with repeated EVT (rEVT) within 30 days of the first procedure.MethodsPubMed was searched (between January 2012 and April 2021) to identify studies reporting reocclusion following successful EVT (Thrombolysis in Cerebral Infarction ≥2b) in patients with AIS due to LVO. Pooled incidence of reocclusion per 100 patients with successful recanalization following EVT was calculated using a random-effects model with Freeman-Tukey double arcsine transformation. Extracted incidences of reocclusion according to etiology and use of intravenous thrombolysis were pooled using random-effects meta-analytic models.ResultsA total of 840 studies was identified and seven studies qualified for the quantitative analysis, which described 91 same-vessel reocclusions occurring within the first 7 days after treatment among 2067 patients (4.9%; 95% CI 3% to 7%, I2=70.2%). Large vessel atherosclerosis was associated with an increased risk of reocclusion (OR=3.44, 95% CI 1.12 to 10.61, I2=50%). We identified 90 patients treated with rEVT for recurrent LVO, described in five studies. The rates of procedural complications, mortality, and unfavorable functional outcome at 3 months were 18.0%, 18.9%, and 60.3%, respectively.ConclusionIn cohorts of patients with AIS due to LVO, 5% of patients experienced reocclusion within 7 days after successful EVT. Repeated EVT can be a safe and effective treatment for selected patients with reocclusion.