Reproducible protocol for the extraction and semi-automated quantification of macroscopic charcoal from soil.

Charcoal fragments preserved in soils or sediments are used by scientists to reconstruct fire histories and thereby improve our understanding of past vegetation dynamics and human-plant relationships. Unfortunately, most published methods for charcoal extraction and analysis are incompletely described and are therefore difficult to reproduce. To improve the standardization and replicability of soil charcoal analysis, as well as to facilitate accessibility for non-experts, we developed a detailed, step-by-step protocol to isolate charcoal from soil and to efficiently count and measure charcoal fragments. The extraction phase involves the chemical soaking and wet sieving of soils followed by the collection of macrocharcoal (≥500 µm). The analysis phase is performed semi-automatically using the open-source software ImageJ to count and measure the area, length, and width of fragments from light stereo microscope images by means of threshold segmentation. The protocol yields clean charcoal fragments, a set of charcoal images, and datasets containing total charcoal mass, number of fragments, and morphological measurements (area, length, and width) for each sample. We tested and validated the protocol on 339 soil samples from tropical savannas and forests in eastern lowland Bolivia. We hope that this protocol will be a valuable resource for scientists in a variety of fields who currently study, or wish to study, macroscopic charcoal in soils as a proxy for past fires.

Destructuration of Canola Protein Gels during In Situ Gastrointestinal Digestion Studied by X-ray Scattering.

We are studying the destructuration of canola protein gels, as a solid food model, during in situ gastrointestinal digestion using synchrotron small-angle X-ray scattering (SAXS). Digestion of two gels, prepared by heating pH 8 and pH 11 solutions, was carried out by diffusion of enzymatic juices into the gel from the top of the capillary and monitored for several tens of hours. Very similar time evolutions of SAXS curves occur at different positions of the gel in the capillary, with a delay determined by the distance from the surface initially in contact with the digestive juice. The main phenomena observed are (i) at the scale of the protein conformation (1-5 nm). The scattering curve is a power law, the exponent of which measures the compactness (related to the degree of unfolding). It can be plotted as a function of the characteristic size of proteins/and interprotein distances and as a function of the scattering intensity. Such diagrams clearly show successive digestion processes. For the pH 11 gel, in which proteins are initially hardly unfolded, the digestive processes are unfolding (1st step), recompaction-aggregation phenomena (2nd step) due to gastrointestinal pH conditions and enzymatic cleavage, further unfolding-disaggregation (3rd step), and final protein cleavage (4th step) down to small peptides. For the pH 8 gel, proteins are initially unfolded, and only the last three steps are observed, showing the influence of easier access for the enzymes. (ii) At the scale of large aggregates (10-50 nm), we observe for both gels a decrease in the size and/or number of these aggregates during digestion and alteration of their interfaces. (iii) At the scale of the secondary protein structure, wide-angle X-ray scattering is very useful for detecting the degradation of the secondary protein structure at different steps of digestion.

Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data.

Machine learning and deep learning advancements have boosted Brain-Computer Interface (BCI) performance, but their wide-scale applicability is limited due to factors like individual health, hardware variations, and cultural differences affecting neural data. Studies often focus on uniform single-site experiments in uniform settings, leading to high performance that may not translate well to real-world diversity. Deep learning models aim to enhance BCI classification accuracy, and transfer learning has been suggested to adapt models to individual neural patterns using a base model trained on others' data. This approach promises better generalizability and reduced overfitting, yet challenges remain in handling diverse and imbalanced datasets from different equipment, subjects, multiple centres in different countries, and both healthy and patient populations for effective model transfer and tuning. In a setting characterized by maximal heterogeneity, we proposed P300 wave detection in BCIs employing a convolutional neural network fitted with adaptive transfer learning based on Poison Sampling Disk (PDS) called Active Sampling (AS), which flexibly adjusts the transition from source data to the target domain. Our results reported for subject adaptive with 40% of adaptive fine-tuning that the averaged classification accuracy improved by 5.36% and standard deviation reduced by 12.22% using two distinct, internationally replicated datasets. These results outperformed in classification accuracy, computational time, and training efficiency, mainly due to the proposed Active Sampling (AS) method for transfer learning.

Interrogating a Compound Library in Search of an Inhibitor for TREM-like Transcript-1 to Fibrinogen Binding.

Cardiovascular disease (CVD) remains one of leading causes of death worldwide. Aberrant platelet function mediate fibrin(ogen) rich thrombi that lead to occlusive thrombi associated with mortality. The receptor, TREM-like transcript-1 (TLT-1), stored in the platelet a-granules and released upon platelet activation, binds fibrinogen and von Willebrand factor. Once it is released from platelets TLT-1 is a potential therapeutic target to prevent the thrombosis associated with CVD. Here we design an assay to screen a compound library of small molecules inhibitors. HEK-293 cells stably transfected with a full length human treml-1 construct were used to screen library of 800 compounds, for inhibition of TLT-1 to fibrinogen binding in an attachment assay using crystal violet staining. The possible cytotoxicity of the best compounds was determined via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide MTT and calcein AM staining assays. Here we demonstrate that the addition of TLT-1 to HEK-293 cells increases cell adhesion by more than 2-fold. We identified ~80 compounds that inhibit binding by more than 80%. We further tested the top compounds and confirmed that reduction of hTLT-1 to fibrinogen bound in the top compounds was not caused by cytotoxicity, as per colorimetric and fluorescent viability assays. Four compounds were identified as potential small molecule inhibitors one of which, BM-8372, demonstrated significant effect in platelet aggregation assays. Significance Statement TLT-1 is a key platelet receptor that binds fibrinogen and mediates clot formation The developed assay successfully screens 800 small molecules, pinpointing ~80 potent inhibitors that reduce TLT-1 binding by over 80%. Importantly, the study rigorously rules out cytotoxicity concerns, affirming the therapeutic potential of the identified compounds. By elucidating TLT-1's role and presenting promising inhibitors, this research offers a significant stride toward developing novel strategies to combat CVD-related thrombosis.

A re-assessment of the value of markers of corticosteroid contact allergy in the Spanish baseline series: Clobetasol propionate in the spotlight.

BACKGROUND: Budesonide and tixocortol pivalate as markers of contact allergy to corticosteroids have been questioned, as they are not able to detect a significant percentage of allergic patients. OBJECTIVES: To investigate the potential role of clobetasol propionate in enhancing corticosteroid sensitisation detection. METHODS: Between January 2022 and December 2023, patients who attended centres involved in the Spanish Registry of Research in Contact Dermatitis and Cutaneous Allergy were tested with an extended baseline series that included budesonide, tixocortol pivalate, clobetasol propionate 0.1% in ethanol and 1% in petrolatum. RESULTS: A total of 4338 patients were tested. Twenty-four patients were allergic to budesonide (0.55%, 95% CI: 0.37-0.82); nine patients were allergic to tixocortol pivalate (0.21%, 95% CI: 0.11-0.39); and 23 patients were allergic to clobetasol (0.53%, 95% CI: 0.35-0.79). Only four of those patients allergic to clobetasol were detected by budesonide and one by tixocortol pivalate. No significant differences in the number of positive tests were found between clobetasol in petrolatum or ethanol. CONCLUSIONS: In Spain budesonide remains the main corticosteroid allergy marker whereas the role of tixocortol pivalate is questionable. The addition of clobetasol propionate to the Spanish baseline series would improve the ability to detect patients allergic to corticosteroids.

Association between widespread pain and psychosocial factors in people with knee osteoarthritis: a cross-sectional study of patients from primary care in Denmark.

INTRODUCTION: The relationship between psychosocial factors and bodily pain in people with knee osteoarthritis (KOA) is unclear. PURPOSE: To examine whether widespread pain was associated with poorer self-efficacy, more anxiety, depression, and kinesiophobia in people with KOA. METHODS: This was a cross-sectional study based on data from Good Life with osteoArthritis in Denmark (GLA:D®). The association between widespread pain (multiple pain sites) and self-efficacy (Arthritis Self-Efficacy Scale), anxiety and depression (item from the EQ-5D-5 L), and kinesiophobia (yes/no) was examined using multiple linear tobit or logistic regression models. RESULTS: Among 19,323 participants, 10% had no widespread pain, 37% had 2 pain sites, 26% had 3-4 pain sites, and 27% had ≥5 pain sites. Widespread pain was associated with poorer self-efficacy (-0.9 to -8.3 points), and the association was stronger with increasing number of pain sites (p-value <.001). Significant increasing odds ratios (ORs) were observed for having anxiety or depression with 3-4 pain sites (OR 1.29, 95% CI 1.12; 1.49) and ≥5 pain sites (OR 1.80, 95% CI 1.56; 2.07). Having 2 and 3-4 pain sites were associated with lower odds of kinesiophobia compared to having no widespread pain. CONCLUSION: Widespread pain was associated with lower self-efficacy and more anxiety and depression but also lower kinesiophobia in people with KOA.

Risk of prostate cancer in the proximity of industrial installations: A multicase-control study in Spain (MCC-Spain).

BACKGROUND: Prostate cancer (PC) is the second most frequent tumor in men worldwide; however, its etiology remains largely unknown, with the exception of age and family history. The wide variability in incidence/mortality across countries suggests a certain role for environmental exposures that has not yet been clarified. OBJECTIVE: To evaluate the association between risk of PC (by clinical profile) and residential proximity to pollutant industrial installations (by industrial groups, groups of carcinogens, and specific pollutants released), within the context of a Spanish population-based multicase-control study of incident cancer (MCC-Spain). METHODS: This study included 1186 controls and 234 PC cases, frequency matched by age and province of residence. Distances from participants' residences to the 58 industries located in the study area were calculated and categorized into "near" (considering different limits between ≤1 km and ≤ 3 km) or "far" (>3 km). Odds ratios (ORs) and 95 % confidence intervals (95%CIs) were estimated using mixed and multinomial logistic regression models, adjusted for potential confounders and matching variables. RESULTS: No excess risk was detected near the overall industries, with ORs ranging from 0.66 (≤2 km) to 1.11 (≤1 km). However, positive associations (OR; 95%CI) were found, by industrial group, near (≤3 km) industries of ceramic (2.54; 1.28-5.07), food/beverage (2.18; 1.32-3.62), and disposal/recycling of animal waste (2.67; 1.12-6.37); and, by specific pollutant, near plants releasing fluorine (4.65; 1.45-14.91 at ≤1.5 km) and chlorine (5.21; 1.56-17.35 at ≤1 km). In contrast, inverse associations were detected near industries releasing ammonia, methane, dioxins+furans, polycyclic aromatic hydrocarbons, trichloroethylene, and vanadium to air. CONCLUSIONS: The results suggest no association between risk of PC and proximity to the overall industrial installations. However, some both positive and inverse associations were detected near certain industrial groups and industries emitting specific pollutants.

First X-ray spectral ptychography and resonant ptychographic computed tomography experiments at the SWING beamline from Synchrotron SOLEIL.

X-ray ptychography and ptychographic computed tomography have seen a rapid rise since the advent of fourth-generation synchrotrons with a high degree of coherent radiation. In addition to quantitative multiscale structural analysis, ptychography with spectral capabilities has been developed, allowing for spatial-localized multiscale structural and spectral information of samples. The SWING beamline of Synchrotron SOLEIL has recently developed a nanoprobe setup where the endstation's first spectral and resonant ptychographic measurements have been successfully conducted. A metallic nickel wire sample was measured using 2D spectral ptychography in XANES mode and resonant ptychographic tomography. From the 2D spectral ptychography measurements, the spectra of the components of the sample's complex-valued refractive index, δ and ß, were extracted, integrated along the sample thickness. By performing resonance ptychographic tomography at two photon energies, 3D maps of the refractive index decrement, δ, were obtained at the Ni K-edge energy and another energy above the edge. These maps allowed the detection of impurities in the Ni wire. The significance of accounting for the atomic scattering factor is demonstrated in the calculation of electron density near a resonance through the use of the δ values. These results indicate that at the SWING beamline it is possible to conduct state-of-the-art spectral and resonant ptychography experiments using the nanoprobe setup.

Cemiplimab plus chemotherapy versus chemotherapy alone in non-small cell lung cancer with PD-L1 ≥ 1 %: A subgroup analysis from the EMPOWER-Lung 3 part 2 trial.

OBJECTIVES: EMPOWER-Lung 3 part 2 (NCT03409614), a double-blind, placebo-controlled phase 3 study, assessed cemiplimab (anti-programmed cell death protein 1) plus chemotherapy versus chemotherapy alone in patients with advanced non-small cell lung cancer (NSCLC) without EGFR, ALK, or ROS1 aberrations, regardless of histology or PD-L1 expression levels. We report results from subgroup analysis of patients with PD-L1 expression ≥ 1 %. MATERIALS AND METHODS: Patients were randomized to receive cemiplimab 350 mg or placebo with chemotherapy every 3 weeks for up to 108 weeks. Overall survival (OS), progression-free survival (PFS), overall response rates (ORRs), patient-reported outcomes (PROs), and safety were assessed. RESULTS: Of the 327 patients with PD-L1 ≥ 1 % (466 in the overall study), 217 received cemiplimab plus chemotherapy and 110 received chemotherapy alone. After median follow-up of 28.0 months, median OS for cemiplimab plus chemotherapy was 23.5 months (95 % confidence interval [CI]: 20.9-27.2) vs. 12.1 months (95 % CI: 10.1-15.7) for chemotherapy alone (hazard ratio [HR] = 0.51, 95 % CI: 0.38-0.69, P < 0.0001); median PFS was 8.3 months (95 % CI: 6.7-10.8) versus 5.5 months (95 % CI: 4.3-6.2; HR = 0.48; 95 % CI: 0.37-0.62, P < 0.0001), and ORR was 47.9 % versus 22.7 %, respectively. PRO results favored cemiplimab plus chemotherapy over chemotherapy alone. Improved efficacy over chemotherapy alone was observed in both squamous and non-squamous histology. Safety was consistent with previous reports. CONCLUSION: In this subgroup analysis from EMPOWER-Lung 3 part 2, cemiplimab plus chemotherapy demonstrated clinical benefit over chemotherapy alone in patients with advanced squamous or non-squamous NSCLC with PD-L1 ≥ 1 %.

Shared Decision-making in Breast Cancer Reconstructive Surgery: Experience in a Leading Hospital.

Background: The paradigm of healthcare has evolved toward patient-centered approaches, where shared decision-making (SDM) plays a pivotal role. This study aimed to explore the implementation of SDM during breast cancer reconstruction consultations and assess its impact on patient satisfaction and the decision-making process as a whole. Methods: A total of 102 female patients undergoing breast reconstruction were included in a multidisciplinary breast pathology unit. A streamlined SDM model involving choice introduction, option description, and preference exploration was implemented. A validated Spanish version of the nine-item Shared Decision Making Questionnaire was used alongside a complementary questionnaire. Data analysis was carried out using electronic data capture software. Results: The nine-item Shared Decision Making Questionnaire results indicate strong agreement in presenting various options and explaining their advantages and disadvantages. Patients were less confident about their participation in decision-making. The Complementary Shared Decision Making Questionnaire highlighted high satisfaction with interview times and language clarity but areas for improvement in consultation space and therapeutic choice participation. Conclusions: Integrating SDM into breast reconstruction consultations empowers patients in the decision-making process and enhances satisfaction. Decision aids prove effective in this context, facilitating patients' comprehension and reducing decisional conflict. There are areas for improvement within the SDM strategy, and they are detectable through scales. Although challenges in information transmission and patient involvement persist, adopting an SDM model has potential benefits that warrant further investigation.

Marginal changes at bone-level implants supporting dental prostheses with or without intermediate standardised abutments after 36 months: Randomised controlled clinical trial.

OBJECTIVE: The objective of this study is to evaluate the changes at marginal bone level at implants restored with screw-retained prosthesis connected directly to the implants or with an intermediate abutment, after 3-year follow-up. MATERIAL AND METHODS: Thirty-six partially edentulous patients received 72 implants. Each patient received 2 implants and a 2-4-unit screw-retained implant-prosthesis. The test group implants received a screw-retained prosthesis connected directly to the implant shoulder, the control group prosthesis were connected through a 3-mm standardised intermediate abutment. Clinical and radiological data were recorded at baseline and at 6-, 12-, and 36-month follow-up. RESULTS: At 36 months, the mean marginal bone loss was 0.13 ± 0.18 mm for the control group and 0.20 ± 0.24 for the test group, with no significant differences between groups (p > .05). Clinical variables (Probing Pocket Depth, Bleeding on Probing and Plaque Index) at 36 months also showed no significant difference between groups. Minor complications frequency was 6.7% in the control group and 5.3% in test group. None of the groups suffered from mayor complications. Patient Reported Outcomes (PROs) showed a General Satisfaction mean score in the control group of 9.40 (SD 0.82) and 9.37 (SD 1.06) in the test group with no significant differences between groups. CONCLUSIONS: Bone-level implants restored with screw-retained partial prostheses with or without intermediate abutments showed similar radiographic and clinical outcomes after 3 years.

Exploring the Performance of ChatGPT Versions 3.5, 4, and 4 With Vision in the Chilean Medical Licensing Examination: Observational Study.

Background: The deployment of OpenAI's ChatGPT-3.5 and its subsequent versions, ChatGPT-4 and ChatGPT-4 With Vision (4V; also known as "GPT-4 Turbo With Vision"), has notably influenced the medical field. Having demonstrated remarkable performance in medical examinations globally, these models show potential for educational applications. However, their effectiveness in non-English contexts, particularly in Chile's medical licensing examinations-a critical step for medical practitioners in Chile-is less explored. This gap highlights the need to evaluate ChatGPT's adaptability to diverse linguistic and cultural contexts. Objective: This study aims to evaluate the performance of ChatGPT versions 3.5, 4, and 4V in the EUNACOM (Examen Único Nacional de Conocimientos de Medicina), a major medical examination in Chile. Methods: Three official practice drills (540 questions) from the University of Chile, mirroring the EUNACOM's structure and difficulty, were used to test ChatGPT versions 3.5, 4, and 4V. The 3 ChatGPT versions were provided 3 attempts for each drill. Responses to questions during each attempt were systematically categorized and analyzed to assess their accuracy rate. Results: All versions of ChatGPT passed the EUNACOM drills. Specifically, versions 4 and 4V outperformed version 3.5, achieving average accuracy rates of 79.32% and 78.83%, respectively, compared to 57.53% for version 3.5 (P<.001). Version 4V, however, did not outperform version 4 (P=.73), despite the additional visual capabilities. We also evaluated ChatGPT's performance in different medical areas of the EUNACOM and found that versions 4 and 4V consistently outperformed version 3.5. Across the different medical areas, version 3.5 displayed the highest accuracy in psychiatry (69.84%), while versions 4 and 4V achieved the highest accuracy in surgery (90.00% and 86.11%, respectively). Versions 3.5 and 4 had the lowest performance in internal medicine (52.74% and 75.62%, respectively), while version 4V had the lowest performance in public health (74.07%). Conclusions: This study reveals ChatGPT's ability to pass the EUNACOM, with distinct proficiencies across versions 3.5, 4, and 4V. Notably, advancements in artificial intelligence (AI) have not significantly led to enhancements in performance on image-based questions. The variations in proficiency across medical fields suggest the need for more nuanced AI training. Additionally, the study underscores the importance of exploring innovative approaches to using AI to augment human cognition and enhance the learning process. Such advancements have the potential to significantly influence medical education, fostering not only knowledge acquisition but also the development of critical thinking and problem-solving skills among health care professionals.

Mechanisms Underlying Memory Impairment Induced by Fructose.

Fructose consumption has increased over the years, especially in adolescents living in urban areas. Growing evidence indicates that daily fructose consumption leads to some pathological conditions, including memory impairment. This review summarizes relevant data describing cognitive deficits after fructose intake and analyzes the underlying neurobiological mechanisms. Preclinical experiments show sex-related deficits in spatial memory; that is, while males exhibit significant imbalances in spatial processing, females seem unaffected by dietary supplementation with fructose. Recognition memory has also been evaluated; however, only female rodents show a significant decline in the novel object recognition test performance. According to mechanistic evidence, fructose intake induces neuroinflammation, mitochondrial dysfunction, and oxidative stress in the short term. Subsequently, these mechanisms can trigger other long-term effects, such as inhibition of neurogenesis, downregulation of trophic factors and receptors, weakening of synaptic plasticity, and long-term potentiation decay. Integrating all these neurobiological mechanisms will help us understand the cellular and molecular processes that trigger the memory impairment induced by fructose.

Residential exposure to traffic pollution and mammographic density in premenopausal women.

BACKGROUND: Mammographic density (MD) is the most important breast cancer biomarker. Ambient pollution is a carcinogen, and its relationship with MD is unclear. This study aims to explore the association between exposure to traffic pollution and MD in premenopausal women. METHODOLOGY: This Spanish cross-sectional study involved 769 women attending gynecological examinations in Madrid. Annual Average Daily Traffic (AADT), extracted from 1944 measurement road points provided by the City Council of Madrid, was weighted by distances (d) between road points and women's addresses to develop a Weighted Traffic Exposure Index (WTEI). Three methods were employed: method-1 (1dAADT), method-2 (1dAADT), and method-3 (e1dAADT). Multiple linear regression models, considering both log-transformed percentage of MD and untransformed MD, were used to estimate MD differences by WTEI quartiles, through two strategies: "exposed (exposure buffers between 50 and 200 m) vs. not exposed (>200 m)"; and "degree of traffic exposure". RESULTS: Results showed no association between MD and traffic pollution according to buffers of exposure to the WTEI (first strategy) for the three methods. The highest reductions in MD, although not statistically significant, were detected in the quartile with the highest traffic exposure. For instance, method-3 revealed a suggestive inverse trend (eßQ1 = 1.23, eßQ2 = 0.96, eßQ3 = 0.85, eßQ4 = 0.85, p-trend = 0.099) in the case of 75 m buffer. Similar non-statistically significant trends were observed with Methods-1 and -2. When we examined the effect of traffic exposure considering all the 1944 measurement road points in every participant (second strategy), results showed no association for any of the three methods. A slightly decreased MD, although not significant, was observed only in the quartile with the highest traffic exposure: eßQ4 = 0.98 (method-1), and eßQ4 = 0.95 (methods-2 and -3). CONCLUSIONS: Our results showed no association between exposure to traffic pollution and MD in premenopausal women. Further research is needed to validate these findings.

Effects of antidiabetic drugs on bone metabolism.

Objectives: The prevalence of diabetes mellitus type 2 (DMT2) is increasing exponentially worldwide. DMT2 patients have been found to be at a higher risk for bone fractures than the healthy population. Hence, improving our understanding of the impact of antidiabetic drugs on bone metabolism is crucial. Methods: A descriptive, retrospective study involving 106 patients receiving six groups of antidiabetic drugs: insulin; dipeptidylpeptidase four inhibitors (DPP4i); glucagon-like peptide type 1 receptor agonists (GLP1ra); sulfonylureas; sodium-glucose cotransporter two inhibitors (SGLT2i); and pioglitazone, in which osteocalcin (OC), bone alkaline phosphatase (BAP) and C-terminal telopeptide of collagen type 1 or beta-crosslaps (ß-CTx) were determined. Results: ß-CTx concentrations were higher in the patients treated with pioglitazone, as compared to patients treated with DPP4i (p=0.035), SGLT2i (p=0.020) or GLP1ra (p<0.001). The lowest ß-CTx concentrations were observed in the patients treated with GLP1ra. Conclusions: Bone remodeling is influenced by the type of antidiabetic drug administered to DMT2 patients. In our study, the patients who received pioglitazone showed higher ß-CTx concentrations, as compared to patients treated with other types of antidiabetic drugs. This finding highlights the convenience of avoiding these drugs, especially in postmenopausal women with DMT2. GLP1ra drugs were associated with the lowest ß-CTx concentrations, which suggests that these agents could exert beneficial effects on bone metabolism.

7.10 MAG. A Novel Host Monoacylglyceride for In Meso (Lipid Cubic Phase) Crystallization of Membrane Proteins.

A novel monoacylglycerol, 7.10 MAG, has been produced for use in the in meso (lipid cubic phase) crystallization of membrane proteins and complexes. 7.10 MAG differs from monoolein, the most extensively used lipid for in meso crystallization, in that it is shorter in chain length by one methylene and its cis olefinic bond is two carbons closer to the glycerol headgroup. These changes in structure alter the phase behavior of the hydrated lipid and the microstructure of the corresponding mesophases formed. Temperature-composition phase diagrams for 7.10 MAG have been constructed using small- and wide-angle X-ray scattering over a range of temperatures and hydration levels that span those used for crystallization. The phase diagrams include lamellar crystalline, fluid isotropic, lamellar liquid-crystalline, cubic-Ia3d, and cubic-Pn3m phases, as observed with monoolein. Conspicuous by its absence is the inverted hexagonal phase which is rationalized on the basis of 7.10 MAG's chemical constitution. The cubic phase prepared with the new lipid facilitates the growth of crystals that were used to generate high-resolution structures of intramembrane ß-barrel and α-helical proteins. Compatibility of fully hydrated 7.10 MAG with cholesterol and phosphatidylcholine means that these two lipids can be used as additives to optimize crystallogenesis in screening trials with 7.10 MAG as the host lipid.

A Self-Adaptive Automatic Incident Detection System for Road Surveillance Based on Deep Learning.

We present an automatic road incident detector characterised by a low computational complexity for easy implementation in affordable devices, automatic adaptability to changes in scenery and road conditions, and automatic detection of the most common incidents (vehicles with abnormal speed, pedestrians or objects falling on the road, vehicles stopped on the shoulder, and detection of kamikaze vehicles). To achieve these goals, different tasks have been addressed: lane segmentation, identification of traffic directions, and elimination of unnecessary objects in the foreground. The proposed system has been tested on a collection of videos recorded in real scenarios with real traffic, including areas with different lighting. Self-adaptability (plug and play) to different scenarios has been tested using videos with significant scene changes. The achieved system can process a minimum of 80 video frames within the camera's field of view, covering a distance of 400 m, all within a span of 12 s. This capability ensures that vehicles travelling at speeds of 120 km/h are seamlessly detected with more than enough margin. Additionally, our analysis has revealed a substantial improvement in incident detection with respect to previous approaches. Specifically, an increase in accuracy of 2-5% in automatic mode and 2-7% in semi-automatic mode. The proposed classifier module only needs 2.3 MBytes of GPU to carry out the inference, thus allowing implementation in low-cost devices.