Revolutionising food advertising monitoring: a machine learning-based method for automated classification of food videos

OBJECTIVE

Food advertising is an important determinant of unhealthy eating. However, analysing a large number of advertisements (ads) to distinguish between food and non-food content is a challenging task. This study aims to develop a machine learning-based method to automatically identify and classify food and non-food ad videos.

DESIGN

Methodological study to develop an algorithm model that prioritises both accuracy and efficiency in monitoring and classifying advertising videos.

SETTING

From a collection of Brazilian television (TV) ads data, we created a database and split it into three sub-databases (i.e. training, validation and test) by extracting frames from ads. Subsequently, the training database was classified using the EfficientNet neural network. The best models and data-balancing strategies were investigated using the validation database. Finally, the test database was used to apply the best model and strategy, and results were verified with field experts.

PARTICIPANTS

The study used 2124 recorded Brazilian TV programming hours from 2018 to 2020. It included 703 food ads and over 20 000 non-food ads, following the protocol developed by the INFORMAS network for monitoring food marketing on TV.

RESULTS

The results showed that the EfficientNet neural network associated with the balanced batches strategy achieved an overall accuracy of 90·5 % on the test database, which represents a reduction of 99·9 % of the time spent on identifying and classifying ads.

CONCLUSIONS

The method studied represents a promising approach for differentiating food and non-food-related video within monitoring food marketing, which has significant practical implications for researchers, public health policymakers, and regulatory bodies.

Communicating the External Beam Radiotherapy Experience (CEBRE) Discussion Guides: Real World Implementation and Evaluation

PURPOSE/OBJECTIVE(S)

Communicating about the radiotherapy treatment process can be difficult for patients and healthcare professionals. The "Communicating the External Beam Radiotherapy Experience" (CEBRE) and Communicating the Gynecologic Brachytherapy Experience (CoGBE) discussion guides use graphic narrative to explain external beam radiotherapy and gynecologic high-dose rate brachytherapy, respectively. The CEBRE, CoGBE, and CEBRE en Español guides have been available for free download since 10/2018, 6/2020, and 8/2021, respectively. This study aims to characterize how the guides are being implemented and used in practice.

MATERIALS/METHODS

Global downloads of the CEBRE, CoGBE, and CEBRE en Español guides were analyzed. Email addresses submitted at the time of download were used to contact study subjects. Duplicate emails, fake addresses, and expired emails were removed resulting in 500 individuals being invited to participate in the survey. A data collection web application survey was distributed on 1/27/23. Two reminders were sent prior to the survey closing on 2/13/23. The survey addressed how physicians or other radiotherapy team members use the CEBRE guides, where they are used, and how the guides can be improved. Likert-type data (1 = strongly disagree, 5 = strongly agree) are reported as median [interquartile range].

RESULTS

As of 10/16/22, the CEBRE guides (English) had been downloaded 602 times, CoGBE 86 times, and CEBRE en Español 63 times. 42/500 individuals responded to the survey for an 8% response rate. 40/42 (95%) of participants were healthcare providers with 35/40 (87.5%) radiation oncologists. 16/40 (40%) have used the CEBRE guides in some way. 6/16 (37.5%) "always use," 2/16 (12.5%) "often use," and 3/16 (18.8%) "sometimes use" the guides during consultation. 8/16 (50%) report using the guides for education of medical students, residents, and fellows. The 16 respondents that use the guides felt the guides were useful overall (5[5-5]), felt "very confident" using the guides (4.5[4-5]), and felt the guides "help patients prepare for their treatment" (5[4-5]). 40 respondents provided suggestions on additional language translations with 19/40 (48%) recommending translation into Mandarin, 6/40 (15%) into Cantonese, Portuguese, French and Arabic, and 5/40 (12.5%) into Haitian, Hindi, and Vietnamese.

CONCLUSION

The majority of respondents did not use the CEBRE guides which may be due to difficulty with implementation. However, respondents who use the guides are confident using them and rate them as useful for patients. These data, although limited by the low response rate, suggest that the CEBRE guides have accomplished the goal of facilitating patient-physician conversations. Moreover, there is an interest in translating the guides into additional languages other than Spanish. Due to the low response rate, definitive conclusions cannot be made from these data. Therefore, further research such as interviews and focus groups may be beneficial.

A survey on deep learning for skin lesion segmentation

Skin cancer is a major public health problem that could benefit from computer-aided diagnosis to reduce the burden of this common disease. Skin lesion segmentation from images is an important step toward achieving this goal. However, the presence of natural and artificial artifacts (e.g., hair and air bubbles), intrinsic factors (e.g., lesion shape and contrast), and variations in image acquisition conditions make skin lesion segmentation a challenging task. Recently, various researchers have explored the applicability of deep learning models to skin lesion segmentation. In this survey, we cross-examine 177 research papers that deal with deep learning-based segmentation of skin lesions. We analyze these works along several dimensions, including input data (datasets, preprocessing, and synthetic data generation), model design (architecture, modules, and losses), and evaluation aspects (data annotation requirements and segmentation performance). We discuss these dimensions both from the viewpoint of select seminal works, and from a systematic viewpoint, examining how those choices have influenced current trends, and how their limitations should be addressed. To facilitate comparisons, we summarize all examined works in a comprehensive table as well as an interactive table available online³.

Tumor antigen-unbiased variable epitope library contains mimotopes with antitumor effect in a mouse model of breast cancer

Breast cancer is one of the leading causes of death that affects the female population worldwide. Despite advances in treatments and a greater understanding of the disease, there are still difficulties in successfully treating patients. Currently, the main challenge in the field of cancer vaccines is antigenic variability which can reduce antigen-specific T- cell response efficacy. The search for and validation of immunogenic antigen targets increased dramatically over the past few decades and, with the advent of modern sequencing techniques, permitting the fast and accurate identification of the neoantigen landscape of tumor cells, will undoubtedly continue to grow exponentially for years to come. We have previously implemented Variable Epitope Libraries (VEL) as an unconventional vaccine strategy in preclinical models and for identifying and selecting mutant epitope variants. Here, we used an alanine-based sequence to generate a 9-mer VEL-like combinatorial mimotope library G3d as a new class of vaccine immunogen. An in silico analysis of the 16,000 G3d-derived sequences revealed potential MHC-I binders and immunogenic mimotopes. We demonstrated the antitumor effect of treatment with G3d in the 4T1 murine model of breast cancer. Moreover, two different T cell proliferation screening assays against a panel of randomly selected G3d-derived mimotopes allowed the isolation of both stimulatory and inhibitory mimotopes showing differential therapeutic vaccine efficacy. Thus, the mimotope library is a promising vaccine immunogen and a reliable source for isolating molecular cancer vaccine components.

Benefits of individual preparation for team success: planning for virtual team communication, conflict resolution and belonging

Purpose

Team-based projects are being used at work in various industries and in education. This paper aims to share a training strategy that integrates training with casual games to effectively prepare individuals to perform better in team-based settings due to their acquisition of team skills combined with their knowledge of tools including a team charter, communication plan and conflict resolution plan.

Design/methodology/approach

A training module was developed, deployed and tested in a virtual classroom of an upper-level undergraduate business class to emulate real-world team experiences. In the study, 342 of the 631 participants enrolled chose to complete the optional training module, which included pre- and posttests followed by a perception survey. A quasi-experimental design was used to evaluate the impact of the training upon team skills including communication, conflict resolution and feelings of belonging.

Findings

The pre- and posttest results for trainees indicated a significant increase in team process and development knowledge, which included concepts such as communication, conflict resolution methods, roles, goal-setting and expectation-setting. Survey results indicated a correlation between completing the team training module and improved communication within teams, particularly for teams developing a communication plan in addition to a team charter and conflict resolution strategies.

Originality/value

This research contributes to the literature on preparing individuals for success in teams through training and education using interactive games, while equipping them with tools to contribute to favorable team dynamics and outcomes. The results are applicable to business, organizations and training settings that incorporate team-based projects in online, hybrid and face-to-face settings.

Rationale and design of the Brazilian diabetes study: a prospective cohort of type 2 diabetes

BACKGROUND

Optimal control of traditional risk factors only partially attenuates the exceeding cardiovascular mortality of individuals with diabetes. Employment of machine learning (ML) techniques aimed at the identification of novel features of risk prediction is a compelling target to tackle residual cardiovascular risk. The objective of this study is to identify clinical phenotypes of T2D which are more prone to developing cardiovascular disease.

METHODS

The Brazilian Diabetes Study is a single-center, ongoing, prospective registry of T2D individuals. Eligible patients are 30 years old or older, with a confirmed T2D diagnosis. After an initial visit for the signature of the informed consent form and medical history registration, all volunteers undergo biochemical analysis, echocardiography, carotid ultrasound, ophthalmologist visit, dual x-ray absorptiometry, coronary artery calcium score, polyneuropathy assessment, advanced glycation end-products reader, and ambulatory blood pressure monitoring. A 5-year follow-up will be conducted by yearly phone interviews for endpoints disclosure. The primary endpoint is the difference between ML-based clinical phenotypes in the incidence of a composite of death, myocardial infarction, revascularization, and stroke. Since June/2016, 1030 patients (mean age: 57 years, diabetes duration of 9.7 years, 58% male) were enrolled in our study. The mean follow-up time was 3.7 years in October/2021.

CONCLUSION

The BDS will be the first large population-based cohort dedicated to the identification of clinical phenotypes of T2D at higher risk of cardiovascular events. Data derived from this study will provide valuable information on risk estimation and prevention of cardiovascular and other diabetes-related events.

CLINICALTRIALS.GOV IDENTIFIER

NCT04949152.

Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Correlations

We present the first joint analysis of cluster abundances and auto or cross-correlations of three cosmic tracer fields: galaxy density, weak gravitational lensing shear, and cluster density split by optical richness. From a joint analysis (4×2pt+N) of cluster abundances, three cluster cross-correlations, and the auto correlations of the galaxy density measured from the first year data of the Dark Energy Survey, we obtain Ω_{m}=0.305_{-0.038}^{+0.055} and σ_{8}=0.783_{-0.054}^{+0.064}. This result is consistent with constraints from the DES-Y1 galaxy clustering and weak lensing two-point correlation functions for the flat νΛCDM model. Consequently, we combine cluster abundances and all two-point correlations from across all three cosmic tracer fields (6×2pt+N) and find improved constraints on cosmological parameters as well as on the cluster observable-mass scaling relation. This analysis is an important advance in both optical cluster cosmology and multiprobe analyses of upcoming wide imaging surveys.

Constraints on Dark Matter Properties from Observations of Milky Way Satellite Galaxies

We perform a comprehensive study of Milky Way (MW) satellite galaxies to constrain the fundamental properties of dark matter (DM). This analysis fully incorporates inhomogeneities in the spatial distribution and detectability of MW satellites and marginalizes over uncertainties in the mapping between galaxies and DM halos, the properties of the MW system, and the disruption of subhalos by the MW disk. Our results are consistent with the cold, collisionless DM paradigm and yield the strongest cosmological constraints to date on particle models of warm, interacting, and fuzzy dark matter. At 95% confidence, we report limits on (i) the mass of thermal relic warm DM, m_{WDM}>6.5  keV (free-streaming length, λ_{fs}≲10h^{-1}  kpc), (ii) the velocity-independent DM-proton scattering cross section, σ_{0}<8.8×10^{-29}  cm^{2} for a 100 MeV DM particle mass [DM-proton coupling, c_{p}≲(0.3  GeV)^{-2}], and (iii) the mass of fuzzy DM, m_{ϕ}>2.9×10^{-21}  eV (de Broglie wavelength, λ_{dB}≲0.5  kpc). These constraints are complementary to other observational and laboratory constraints on DM properties.

Detection of Cross-Correlation between Gravitational Lensing and γ Rays

In recent years, many γ-ray sources have been identified, yet the unresolved component hosts valuable information on the faintest emission. In order to extract it, a cross-correlation with gravitational tracers of matter in the Universe has been shown to be a promising tool. We report here the first identification of a cross-correlation signal between γ rays and the distribution of mass in the Universe probed by weak gravitational lensing. We use data from the Dark Energy Survey Y1 weak lensing data and the Fermi Large Area Telescope 9-yr γ-ray data, obtaining a signal-to-noise ratio of 5.3. The signal is mostly localized at small angular scales and high γ-ray energies, with a hint of correlation at extended separation. Blazar emission is likely the origin of the small-scale effect. We investigate implications of the large-scale component in terms of astrophysical sources and particle dark matter emission.

Detection of CMB-Cluster Lensing using Polarization Data from SPTpol

We report the first detection of gravitational lensing due to galaxy clusters using only the polarization of the cosmic microwave background (CMB). The lensing signal is obtained using a new estimator that extracts the lensing dipole signature from stacked images formed by rotating the cluster-centered Stokes QU map cutouts along the direction of the locally measured background CMB polarization gradient. Using data from the SPTpol 500  deg^{2} survey at the locations of roughly 18 000 clusters with richness λ≥10 from the Dark Energy Survey (DES) Year-3 full galaxy cluster catalog, we detect lensing at 4.8σ. The mean stacked mass of the selected sample is found to be (1.43±0.40)×10^{14}M_{⊙} which is in good agreement with optical weak lensing based estimates using DES data and CMB-lensing based estimates using SPTpol temperature data. This measurement is a key first step for cluster cosmology with future low-noise CMB surveys, like CMB-S4, for which CMB polarization will be the primary channel for cluster lensing measurements.

Cosmological Constraints from Multiple Probes in the Dark Energy Survey

The combination of multiple observational probes has long been advocated as a powerful technique to constrain cosmological parameters, in particular dark energy. The Dark Energy Survey has measured 207 spectroscopically confirmed type Ia supernova light curves, the baryon acoustic oscillation feature, weak gravitational lensing, and galaxy clustering. Here we present combined results from these probes, deriving constraints on the equation of state, w, of dark energy and its energy density in the Universe. Independently of other experiments, such as those that measure the cosmic microwave background, the probes from this single photometric survey rule out a Universe with no dark energy, finding w=-0.80_{-0.11}^{+0.09}. The geometry is shown to be consistent with a spatially flat Universe, and we obtain a constraint on the baryon density of Ω_{b}=0.069_{-0.012}^{+0.009} that is independent of early Universe measurements. These results demonstrate the potential power of large multiprobe photometric surveys and pave the way for order of magnitude advances in our constraints on properties of dark energy and cosmology over the next decade.

A data-driven approach to referable diabetic retinopathy detection

Prior art on automated screening of diabetic retinopathy and direct referral decision shows promising performance; yet most methods build upon complex hand-crafted features whose performance often fails to generalize.

OBJECTIVE

We investigate data-driven approaches that extract powerful abstract representations directly from retinal images to provide a reliable referable diabetic retinopathy detector.

METHODS

We gradually build the solution based on convolutional neural networks, adding data augmentation, multi-resolution training, robust feature-extraction augmentation, and a patient-basis analysis, testing the effectiveness of each improvement.

RESULTS

The proposed method achieved an area under the ROC curve of 98.2% (95% CI: 97.4-98.9%) under a strict cross-dataset protocol designed to test the ability to generalize - training on the Kaggle competition dataset and testing using the Messidor-2 dataset. With a 5 × 2-fold cross-validation protocol, similar results are achieved for Messidor-2 and DR2 datasets, reducing the classification error by over 44% when compared to most published studies in existing literature.

CONCLUSION

Additional boost strategies can improve performance substantially, but it is important to evaluate whether the additional (computation- and implementation-) complexity of each improvement is worth its benefits. We also corroborate that novel families of data-driven methods are the state of the art for diabetic retinopathy screening.

SIGNIFICANCE

By learning powerful discriminative patterns directly from available training retinal images, it is possible to perform referral diagnostics without detecting individual lesions.

Transferon™, a peptide mixture with immunomodulatory properties is not immunogenic when administered with various adjuvants

Transferon, a human dialyzable leukocyte extract (hDLE), is a biotherapeutic that comprises a complex mixture of low-molecular-weight peptides (< 10 kDa) and is used to treat diseases with an inflammatory component. Some biotherapeutics, including those composed of peptides, can induce anti-drug antibodies (ADA) that block or diminish their therapeutic effect. Nevertheless, few studies have evaluated peptide-derived drug immunogenicity. In this study, the immunogenicity of Transferon was examined in a murine model during an immunization scheme using the following adjuvants: Al(OH)₃, incomplete Freund's adjuvant (IFA), or Titermax Gold. The inoculation scheme entailed three routes of administration (intraperitoneal, Day 1; subcutaneous, Day 7; and intramuscular, Day 14) using 200 μg Transferon/inoculation. Serum samples were collected on Day 21. Total IgG levels were quantitated by affinity chromatography, and specific antibodies against components of Transferon were analyzed by dot-blot and ELISA. Ovalbumin (OVA, 44 kDa) and peptides from hydrolyzed collagen (PFHC, < 17 kDa) were used as positive and negative controls, respectively, in the same inoculation scheme and analyses for Transferon. OVA, PFHC, and Transferon increased total IgG concentrations in mice. However, only IgG antibodies against OVA were detected. Based on the results, it is concluded that Transferon does not induce generation of specific antibodies against its components in this model, regardless of adjuvant and route of administration. These results support the safety of Transferon by confirming its inability to induce ADA in this animal model.

A Machine Learning Application Based in Random Forest for Integrating Mass Spectrometry-Based Metabolomic Data: A Simple Screening Method for Patients With Zika Virus

Recent Zika outbreaks in South America, accompanied by unexpectedly severe clinical complications have brought much interest in fast and reliable screening methods for ZIKV (Zika virus) identification. Reverse-transcriptase polymerase chain reaction (RT-PCR) is currently the method of choice to detect ZIKV in biological samples. This approach, nonetheless, demands a considerable amount of time and resources such as kits and reagents that, in endemic areas, may result in a substantial financial burden over affected individuals and health services veering away from RT-PCR analysis. This study presents a powerful combination of high-resolution mass spectrometry and a machine-learning prediction model for data analysis to assess the existence of ZIKV infection across a series of patients that bear similar symptomatic conditions, but not necessarily are infected with the disease. By using mass spectrometric data that are inputted with the developed decision-making algorithm, we were able to provide a set of features that work as a "fingerprint" for this specific pathophysiological condition, even after the acute phase of infection. Since both mass spectrometry and machine learning approaches are well-established and have largely utilized tools within their respective fields, this combination of methods emerges as a distinct alternative for clinical applications, providing a diagnostic screening-faster and more accurate-with improved cost-effectiveness when compared to existing technologies.

Process signatures in glatiramer acetate synthesis: structural and functional relationships

Glatiramer Acetate (GA) is an immunomodulatory medicine approved for the treatment of multiple sclerosis, whose mechanisms of action are yet to be fully elucidated. GA is comprised of a complex mixture of polypeptides with different amino acid sequences and structures. The lack of sensible information about physicochemical characteristics of GA has contributed to its comprehensiveness complexity. Consequently, an unambiguous determination of distinctive attributes that define GA is of highest relevance towards dissecting its identity. Herein we conducted a study of characteristic GA heterogeneities throughout its manufacturing process (process signatures), revealing a strong impact of critical process parameters (CPPs) on the reactivity of amino acid precursors; reaction initiation and polymerization velocities; and peptide solubility, susceptibility to hydrolysis, and size-exclusion properties. Further, distinctive GA heterogeneities were correlated to defined immunological and toxicological profiles, revealing that GA possesses a unique repertoire of active constituents (epitopes) responsible of its immunological responses, whose modification lead to altered profiles. This novel approach established CPPs influence on intact GA peptide mixture, whose physicochemical identity cannot longer rely on reduced properties (based on complete or partial GA degradation), providing advanced knowledge on GA structural and functional relationships to ensure a consistent manufacturing of safe and effective products.

Pornography classification: The hidden clues in video space-time

As web technologies and social networks become part of the general public's life, the problem of automatically detecting pornography is into every parent's mind - nobody feels completely safe when their children go online. In this paper, we focus on video-pornography classification, a hard problem in which traditional methods often employ still-image techniques - labeling frames individually prior to a global decision. Frame-based approaches, however, ignore significant cogent information brought by motion. Here, we introduce a space-temporal interest point detector and descriptor called Temporal Robust Features (TRoF). TRoF was custom-tailored for efficient (low processing time and memory footprint) and effective (high classification accuracy and low false negative rate) motion description, particularly suited to the task at hand. We aggregate local information extracted by TRoF into a mid-level representation using Fisher Vectors, the state-of-the-art model of Bags of Visual Words (BoVW). We evaluate our original strategy, contrasting it both to commercial pornography detection solutions, and to BoVW solutions based upon other space-temporal features from the scientific literature. The performance is assessed using the Pornography-2k dataset, a new challenging pornographic benchmark, comprising 2000 web videos and 140h of video footage. The dataset is also a contribution of this work and is very assorted, including both professional and amateur content, and it depicts several genres of pornography, from cartoon to live action, with diverse behavior and ethnicity. The best approach, based on a dense application of TRoF, yields a classification error reduction of almost 79% when compared to the best commercial classifier. A sparse description relying on TRoF detector is also noteworthy, for yielding a classification error reduction of over 69%, with 19× less memory footprint than the dense solution, and yet can also be implemented to meet real-time requirements.

A pilot study of nimotuzumab plus single agent chemotherapy as second- or third-line treatment or more in patients with recurrent, persistent or metastatic cervical cancer

Nimotuzumab is a humanized IgG1 monoclonal antibody against the EGFR extracellular domain that has been evaluated in solid tumors as a single agent or in combination with chemotherapy and radiation. Cervical cancer patients who are refractory or progressive to first-line chemotherapy have a dismal prognosis, and no second- or third-line chemotherapy is considered standard. This pilot trial aimed to evaluate the efficacy and safety of nimotuzumab in 17 patients with pre-treated advanced refractory or progressive cervical cancer. Nimotuzumab was administered weekly at 200 mg/m(2) as single agent for 4 weeks (induction phase), then concurrent with 6 21-day cycles of gemcitabine (800 mg/m(2)) or cisplatin (50 mg/m(2)) for 18 weeks (concurrent phase) and then once every 2 weeks (maintenance phase). Nimotuzumab could be continued beyond disease progression. Seventeen patients were accrued and evaluated for safety and efficacy. The median number of nimotuzumab applications was 20 (5-96). The median number of chemotherapy cycles administered was 6 (1-6). No toxicity occurred during induction and maintenance phases (single agent nimotuzumab). In the concurrent phase, grade 3 toxicity events observed were leucopenia, anemia and diarrhea in 11.7%, 5.8% and 11.7% respectively. No complete or partial responses were observed. The stable disease (SD) rate was 35%. The median PFS and OS rates were 163 days (95% CI, 104 to 222), and 299 days (95% IC, 177 to 421) respectively. Nimotuzumab is well tolerated and may have a role in the treatment of advanced cervical cancer.

Automatic Diabetic Retinopathy detection using BossaNova representation

The biomedical community has shown a continued interest in automated detection of Diabetic Retinopathy (DR), with new imaging techniques, evolving diagnostic criteria, and advancing computing methods. Existing state of the art for detecting DR-related lesions tends to emphasize different, specific approaches for each type of lesion. However, recent research has aimed at general frameworks adaptable for large classes of lesions. In this paper, we follow this latter trend by exploring a very flexible framework, based upon two-tiered feature extraction (low-level and mid-level) from images and Support Vector Machines. The main contribution of this work is the evaluation of BossaNova, a recent and powerful mid-level image characterization technique, which we contrast with previous art based upon classical Bag of Visual Words (BoVW). The new technique using BossaNova achieves a detection performance (measured by area under the curve - AUC) of 96.4% for hard exudates, and 93.5% for red lesions using a cross-dataset training/testing protocol.

Antioxidant therapy attenuates oxidative stress in the blood of subjects exposed to occupational airborne contamination from coal mining extraction and incineration of hospital residues

Coal mining and incineration of solid residues of health services (SRHS) generate several contaminants that are delivered into the environment, such as heavy metals and dioxins. These xenobiotics can lead to oxidative stress overgeneration in organisms and cause different kinds of pathologies, including cancer. In the present study the concentrations of heavy metals such as lead, copper, iron, manganese and zinc in the urine, as well as several enzymatic and non-enzymatic biomarkers of oxidative stress in the blood (contents of lipoperoxidation = TBARS, protein carbonyls = PC, protein thiols = PT, α-tocopherol = AT, reduced glutathione = GSH, and the activities of glutathione S-transferase = GST, glutathione reductase = GR, glutathione peroxidase = GPx, catalase = CAT and superoxide dismutase = SOD), in the blood of six different groups (n = 20 each) of subjects exposed to airborne contamination related to coal mining as well as incineration of solid residues of health services (SRHS) after vitamin E (800 mg/day) and vitamin C (500 mg/day) supplementation during 6 months, which were compared to the situation before the antioxidant intervention (Ávila et al., Ecotoxicology 18:1150-1157, 2009; Possamai et al., Ecotoxicology 18:1158-1164, 2009). Except for the decreased manganese contents, heavy metal concentrations were elevated in all groups exposed to both sources of airborne contamination when compared to controls. TBARS and PC concentrations, which were elevated before the antioxidant intervention decreased after the antioxidant supplementation. Similarly, the contents of PC, AT and GSH, which were decreased before the antioxidant intervention, reached values near those found in controls, GPx activity was reestablished in underground miners, and SOD, CAT and GST activities were reestablished in all groups. The results showed that the oxidative stress condition detected previously to the antioxidant supplementation in both directly and indirectly subjects exposed to the airborne contamination from coal dusts and SRHS incineration, was attenuated after the antioxidant intervention.

Sedation with propofol controlled by endoscopists during percutaneous endoscopic gastrostomy

BACKGROUND

propofol is a hypnotic used with increasing frequency for sedation during endoscopic procedures. Most of the reports published related with its employment by non-anaesthesiologists, refers to basic endoscopy, with little reference to its use in advanced endoscopy.

OBJECTIVE

to evaluate the efficacy and safety of propofol sedation administered by endoscopists, while performing percutaneous endoscopic gastrostomy, an advanced technique that is usually performed in high anesthetic level risk patients.

MATERIAL AND METHODS

prospective study of a series of endoscopic gastrostomy performed consecutively in our department; the sedation was carried out exclusively with propofol. The staff in the room consisted of two medical gastroenterologists, a nurse and a nursing assistant. Propofol was administered by bolus doses adjusted to patient weight. Arterial oxygen saturation, heart rate and blood pressure were monitored; respiratory activity was monitored visually by observing respiratory excursions of the patient.

RESULTS

we included 47 patients, with an average age of 82 years. 87% were ASA III and the rest, ASA IV. The mean dose of propofol was 51 mgr. Complications were recorded: 8 cases of desaturation and two of hypotension, all of them minor and quickly reversible. All procedures were carried out successfully, at a median time of 8 minutes.

CONCLUSION

the propofol sedation carried out by non-anaesthesiologist trained staff, seems to appear as a safe and effective procedure while performing percutaneous endoscopic gastrostomy.

Occupational airborne contamination in South Brazil: 2. Oxidative stress detected in the blood of workers of incineration of hospital residues

One of the most useful methods for elimination of solid residues of health services (SRHS) is incineration. However, it also provokes the emission of several hazardous air pollutants such as heavy metals, furans and dioxins, which produce reactive oxygen species and oxidative stress. The present study, which is parallel to an accompanied paper (Avila Jr. et al., this issue), investigated several enzymatic and non-enzymatic biomarkers of oxidative stress in the blood (contents of vitamin E, lipoperoxidation = TBARS, reduced glutathione = GSH, oxidized glutathione = GSSG, and activities of glutathione S-transferase = GST, glutathione reductase = GR, glutathione peroxidase = GPx, catalase = CAT and superoxide dismutase = SOD), in three different groups (n = 20 each) exposed to airborne contamination associated with incineration of SRHS: workers directly (ca. 100 m from the incinerator) and indirectly exposed (residents living ca. 5 km the incineration site), and controls (non-exposed subjects). TBARS and GSSG levels were increased whilst GSH, TG and alpha-tocopherol contents were decreased in workers and residents compared to controls. Increased GST and CAT activities and decreased GPx activities were detected in exposed subjects compared to controls, while GR did not show any difference among the groups. In conclusion, subjects directly or indirectly exposed to SRHS are facing an oxidative insult and health risk regarding fly ashes contamination from SRHS incineration.

The Transcription Factor PLA-1/SKN-1A is Expressed in Human Placenta and Regulates the Placental Lactogen-3 Gene Expression

Here we report the selective expression of two POU transcription factor genes, PLA-1 and OCT-1, in human placenta and choriocarcinoma cell lines JAR, JEG-3 and BeWo. Pla-1 protein binds to a POU-consensus DNA sequence in the human placental lactogen-3 (PL-3) promoter and it is capable of trans-activating its transcription up to 18-fold. Other tissue-specific or ubiquitous POU transcription factors such as Pit-1/GHF-1 or Oct-1 showed none or low levels of trans-activation of the PL-3 promoter. In addition, we identified an unique and highly charged region in the N-terminal portion of Pla-1 protein required for full trans-activation of the PL-3 promoter.

Dew points of quaternary ethane + carbon dioxide + water + methanol mixtures — Measurement and modelling

Dew points have been measured for eight ethane + carbon dioxide + water + methanol mixtures at pressures from 0.11 to 2.17 MPa and temperatures from 249.0 to 288.7 K. The results are analysed in terms of a predictive excess-function equation of state (EF-EOS) method based on the zeroth approximation of Guggenheim's reticular model. This method can be used to adequately predict the dew points of the mixtures in the temperature and pressure ranges used in the present study. In fact, the model reproduces the experimental dew point temperature data with ≤3.1 K average absolute deviation.Key words: dew point, equation of state, excess function.

Application of solid phase microextraction to the determination of strychnine in blood

A simple and rapid method based on solid phase microextraction (SPME) via direct immersion followed by gas chromatography coupled with electron impact ionization/mass spectrometry (GC/EI-MS) was developed for the determination of strychnine in blood. Papaverine was used as internal standard (I.S.). Two types of fibre coating were tested, 100 microm polydimethylsiloxane and 65 microm Carbowax/Divinylbenzene, the latter giving higher recoveries of the compound. The main factors affecting the SPME process, such as sample dilution (1:10), adsorption and desorption times (20 and 10 min, respectively), carry-over effect (not observed), pH and salt addition (no modifications on pH or salt concentration) were optimized. The procedure was validated in terms of linearity (r(2)=0.9992 for concentrations ranging from 0.10 to 5.00 microg/mL), intra and interday precision (0.93 and 4.62%, respectively at 0.50 microg/mL; 3.33 and 8.06%, respectively at 2.50 microg/mL), sensitivity (6.83 and 8.91 ng/mL for LOD and LOQ, respectively) and extraction recovery (0.54 and 0.39% at 0.50 and 2.50 microg/mL, respectively). The developed procedure was found suitable for forensic investigations and was considered a good alternative to the liquid-liquid extraction methods normally used for the determination of this compound in biological media.

Results of 60 consecutive hepatectomies for pediatric living donor liver transplantation

Several technical improvements have been made to increase donor pool for pediatric liver transplantation, including reduced-size grafts, split-liver, and recently living donors. The objective of the present study is to report our single-center experience with 60 hepatectomies for living donor liver transplantation in pediatric recipients between June 2000 and December 2002. Donor workup consisted of a complete history and physical examination followed by laboratory test and liver function tests. Graft size was estimated using computed tomography scan or abdominal ultrasound. Liver biopsy was performed in all donors. Arteriogram was performed to evaluate hepatic arterial anatomy. All donors survived the procedure. Only seven patients experienced complications (10.2%), most of which were short term. We conclude that liver living donation for pediatric population is a safe procedure.

Analysis of the CODIS autosomal STR loci in four main Colombian regions

Genotype polymorphism studies at the 13 loci STRs included in the combined DNA index system [CODIS and PCR-based short tandem repeat loci, in: Proceedings of the Second European Symposium on Human Identification, Promega Corporation, Madison, WI, 1998, pp. 73-88; J. Forensic Sci. 46 (2001) 453] (CODIS: D3S1358, HUMvWA31, HUMFGA, D8S1179 D21S11, D18S51, D5S818, D13S317, D7S820, HUMTH01, HUMTPOX, HUMCSF1PO and D16S539) were carried out in a sample of 1429 unrelated Colombian individuals belonging to 25 different departments. As many other countries in Latino-America, Colombia shows an important admixture component, basically integrated by Amerindians, European-descendants and African-descendants. Due to the fact that only partial population analyses have been carried out in the country, the main aim of the present analysis is to establish a database of forensic interest based on the widely used CODIS systems covering the main Colombian regions.

A fatal forensic intoxication with fenarimol: analysis by HPLC/DAD/MSD

Fenarimol (Rubigan) is a pyrimidine ergosterol biosynthesis inhibitor used as a systemic fungicide. The authors present a fatal fenarimol intoxication case analysed in the Forensic Toxicology Service of the National Institute of Legal Medicine. The results were used to compare two different HPLC techniques, regarding selectivity and sensitivity: an HPLC system with a diode array detector (DAD) and an HPLC system with a DAD and a mass spectrometry detector (MSD) with an electrospray interface. All biological samples were submitted to a solid-phase extraction procedure. The detection and quantification limits of fenarimol, linearity, precision and accuracy were evaluated. The fenarimol concentration levels determined were of 89.0 mg/ml in gastric contents, 1.9 mg/g in liver and 0.4 mg/g in kidney. Blood was not available at autopsy. No published data related to fenarimol self-poisoning were found, so it was not possible to interpret the results obtained by comparison with toxic/lethal levels.

Inter-test reliability of the anti-RESA indices based on ELISA tests using eluates from whole blood spots dried on filter paper

The ring-infected erythrocyte surface antigen (RESA), is one of the falciparum malaria vaccine candidates rarely studied in Brazil. Fieldwork logistics to conduct serology studies is simplified when eluates from whole blood dried on filter paper can be used. Therefore, this study aimed to assess the inter-test reliability for the anti-RESA ELISA-based indices using eluates from filter paper and from serum samples. The study population consisted of 210 individuals (Brazil) from whom matched samples were collected. Anti-RESA ELISA-based index means (+/- S.D.) were 15.29% (+/-28.13%) for filter paper and 11.79% (+/-23.67%) for serum samples. The intra-class correlation coefficient was estimated to be 82.38%, indicating high test reliability. However, there was a significant tendency for filter paper test results to have higher values than serum sample test results (P < 0.001). Explanations for this finding may be the presence of haemoglobin in the eluates from filter paper, which may interfere with ELISA testing.