Fungemia due to opportunistic fungi in patients with cancer.

BACKGROUND: Fungemia due to uncommon fungi and secondary to multiple risk factors has become an emergent health problem, particularly in oncology patients. AIMS: This study shows the following data collected during an 11-year period in a tertiary care oncologic center from patients with fungemia: demographic data, clinical characteristics, and outcome. METHODS: A retrospective study was performed at Instituto Nacional de Cancerología, a 135-bed referral cancer center in Mexico City, from July 2012 to June 2023. All episodes of non-Candida fungemia were included. RESULTS: Sixteen cases with uncommon fungemia were found in the database, representing 0.3% from all the blood cultures positive during the study period, and 8.5% from all the fungi isolated. The most common pathogens identified in our series were Histoplasma capsulatum, Acremonium spp., Trichosporon asahii, and Saccharomyces cerevisiae. Eight patients had hematologic malignancies, and five had severe neutropenia. In eight cases fungemia was considered catheter-related, in four cases was classified as primary, and in the last four it was diagnosed as disseminated fungal diseases. Mortality at 30 days was 43.8%. CONCLUSIONS: The improved diagnostic tools have led to a better diagnosis of uncommon fungal infections. More aggressive therapeutic approaches, particularly in patients with malignancies, would increase survival rates in these potentially fatal diseases.

Preliminary profile of the gut microbiota from amerindians in the Brazilian amazon experiencing a process of transition to urbanization.

The Yanomami are one of the oldest indigenous tribes in the Amazon and are direct descendants of the first people to colonize South America 12,000 years ago. They are located on the border between Venezuela and Brazil, with the Venezuelan side remaining uncontacted. While they maintain a hunter-gatherer society, they are currently experiencing contact with urbanized populations in Brazil. The human gut microbiota of traditional communities has become the subject of recent studies due to the Westernization of their diet and the introduction of antibiotics and other chemicals, which have affected microbial diversity in indigenous populations, thereby threatening their existence. In this study, we preliminarily characterized the diversity of the gut microbiota of the Yanomami, a hunter-gatherer society from the Amazon, experiencing contact with urbanized populations. Similarly, we compared their diversity with the population in Manaus, Amazonas. A metabarcoding approach of the 16 S rRNA gene was carried out on fecal samples. Differences were found between the two populations, particularly regarding the abundance of genera (e.g., Prevotella and Bacteroides) and the higher values of the phyla Bacteroidetes over Firmicutes, which were significant only in the Yanomami. Some bacteria were found exclusively in the Yanomami (Treponema and Succinivibrio). However, diversity was statistically equal between them. In conclusion, the composition of the Yanomami gut microbiota still maintains the profile characteristic of a community with a traditional lifestyle. However, our results suggest an underlying Westernization process of the Yanomami microbiota when compared with that of Manaus, which must be carefully monitored by authorities, as the loss of diversity can be a sign of growing danger to the health of the Yanomami.

Recognition of Patient Gender: A Machine Learning Preliminary Analysis Using Heart Sounds from Children and Adolescents.

Research has shown that X-rays and fundus images can classify gender, age group, and race, raising concerns about bias and fairness in medical AI applications. However, the potential for physiological sounds to classify sociodemographic traits has not been investigated. Exploring this gap is crucial for understanding the implications and ensuring fairness in the field of medical sound analysis. We aimed to develop classifiers to determine gender (men/women) based on heart sound recordings and using machine learning (ML). Data-driven ML analysis. We utilized the open-access CirCor DigiScope Phonocardiogram Dataset obtained from cardiac screening programs in Brazil. Volunteers < 21 years of age. Each participant completed a questionnaire and underwent a clinical examination, including electronic auscultation at four cardiac points: aortic (AV), mitral (MV), pulmonary (PV), and tricuspid (TV). We used Mel-frequency cepstral coefficients (MFCCs) to develop the ML classifiers. From each patient and from each auscultation sound recording, we extracted 10 MFCCs. In sensitivity analysis, we additionally extracted 20, 30, 40, and 50 MFCCs. The most effective gender classifier was developed using PV recordings (AUC ROC = 70.3%). The second best came from MV recordings (AUC ROC = 58.8%). AV and TV recordings produced classifiers with an AUC ROC of 56.4% and 56.1%, respectively. Using more MFCCs did not substantially improve the classifiers. It is possible to classify between males and females using phonocardiogram data. As health-related audio recordings become more prominent in ML applications, research is required to explore if these recordings contain signals that could distinguish sociodemographic features.

Identifying intraoperative events in a simulated laparotomy video: a multinational study of inattentional blindness among anesthesiologists.

PURPOSE: Medical errors may be occasionally explained by inattentional blindness (IB), i.e., failing to notice an event/object that is in plain sight. We aimed to determine whether age/experience, restfulness/fatigue, and previous exposure to simulation education may affect IB in the anesthetic/surgical setting. METHODS: In this multicentre/multinational study, a convenience sample of 280 anesthesiologists watched an attention-demanding video of a simulated trauma patient undergoing laparotomy and (independently/anonymously) recorded the abnormalities they noticed. The video contained four expected/common abnormalities (hypotension, tachycardia, hypoxia, hypothermia) and two prominently displayed unexpected/rare events (patient's head movement, leaky central venous line). We analyzed the participants' ability to notice the expected/unexpected events (primary outcome) and the proportion of expected/unexpected events according to age group and prior exposure to simulation education (secondary outcomes). RESULTS: Anesthesiologists across all ages noticed fewer unexpected/rare events than expected/common ones. Overall, younger anesthesiologists missed fewer common events than older participants did (P = 0.02). There was no consistent association between age and perception of unexpected/rare events (P = 0.28), although the youngest cohort (< 30 yr) outperformed the other age groups. Prior simulation education did not affect the proportion of misses for the unexpected/rare events but was associated with fewer misses for the expected/common events. Self-perceived restfulness did not impact perception of events. CONCLUSION: Anesthesiologists noticed fewer unexpected/rare clinical events than expected/common ones in an attention-demanding video of a simulated trauma patient, in keeping with IB. Prior simulation training was associated with an improved ability to notice anticipated/expected events, but did not reduce IB. Our findings may have implications for understanding medical mishaps, and efforts to improve situational awareness, especially in acute perioperative and critical care settings.

RéSUMé: OBJECTIF: Les erreurs médicales peuvent parfois s'expliquer par la cécité d'inattention, soit le fait de ne pas remarquer un événement/objet qui est à la vue de tous et toutes. Notre objectif était de déterminer si l'âge/l'expérience, le repos/la fatigue et l'exposition antérieure à l'enseignement par simulation pouvaient affecter la cécité d'inattention dans le cadre de l'anesthésie/chirurgie. MéTHODE: Dans cette étude multicentrique/multinationale, un échantillon de convenance de 280 anesthésiologistes ont visionné une vidéo exigeant l'attention portant sur un patient de trauma simulé bénéficiant d'une laparotomie et ont enregistré (de manière indépendante/anonyme) les anomalies qu'ils et elles ont remarquées. La vidéo contenait quatre anomalies attendues/courantes (hypotension, tachycardie, hypoxie, hypothermie) et deux événements inattendus/rares bien en vue (mouvement de la tête du patient, fuite du cathéter veineux central). Nous avons analysé la capacité des participant·es à remarquer les événements attendus/inattendus (critère d'évaluation principal) et la proportion d'événements attendus/inattendus selon le groupe d'âge et l'exposition antérieure à l'enseignement par simulation (critères d'évaluation secondaires). RéSULTATS: Les anesthésiologistes de tous âges ont remarqué moins d'événements inattendus/rares que d'événements attendus/courants. Globalement, les anesthésiologistes plus jeunes ont manqué moins d'événements courants que leurs congénères plus âgé·es (P = 0,02). Il n'y avait pas d'association constante entre l'âge et la perception d'événements inattendus ou rares (P = 0,28), bien que la cohorte la plus jeune (< 30 ans) ait surpassé les autres groupes d'âge. La formation antérieure par simulation n'a pas eu d'incidence sur la proportion d'inobservation des événements inattendus ou rares, mais a été associée à moins de cécité d'inattention envers les événements attendus ou courants. Le repos perçu n'a pas eu d'impact sur la perception des événements. CONCLUSION: Les anesthésiologistes ont remarqué moins d'événements cliniques inattendus/rares que d'événements attendus/courants dans une vidéo exigeant l'attention portant sur la simulation d'un patient traumatisé, ce qui s'inscrit dans la cécité d'inattention. La formation préalable par simulation était associée à une meilleure capacité à remarquer les événements anticipés/attendus, mais ne réduisait pas la cécité d'inattention. Nos résultats peuvent avoir des implications pour la compréhension des accidents médicaux et les efforts visant à améliorer la conscience situationnelle, en particulier dans les contextes de soins périopératoires aigus et de soins intensifs.

Characterization of antimalarial activity of artemisinin-based hybrid drugs.

In response to the spread of artemisinin (ART) resistance, ART-based hybrid drugs were developed, and their activity profile was characterized against drug-sensitive and drug-resistant Plasmodium falciparum parasites. Two hybrids were found to display parasite growth reduction, stage-specificity, speed of activity, additivity of activity in drug combinations, and stability in hepatic microsomes of similar levels to those displayed by dihydroartemisinin (DHA). Conversely, the rate of chemical homolysis of the peroxide bonds is slower in hybrids than in DHA. From a mechanistic perspective, heme plays a central role in the chemical homolysis of peroxide, inhibiting heme detoxification and disrupting parasite heme redox homeostasis. The hybrid exhibiting slow homolysis of peroxide bonds was more potent in reducing the viability of ART-resistant parasites in a ring-stage survival assay than the hybrid exhibiting fast homolysis. However, both hybrids showed limited activity against ART-induced quiescent parasites in the quiescent-stage survival assay. Our findings are consistent with previous results showing that slow homolysis of peroxide-containing drugs may retain activity against proliferating ART-resistant parasites. However, our data suggest that this property does not overcome the limited activity of peroxides in killing non-proliferating parasites in a quiescent state.

Universe-inspired algorithms for control engineering: A review.

Control algorithms have been proposed based on knowledge related to nature-inspired mechanisms, including those based on the behavior of living beings. This paper presents a review focused on major breakthroughs carried out in the scope of applied control inspired by the gravitational attraction between bodies. A control approach focused on Artificial Potential Fields was identified, as well as four optimization metaheuristics: Gravitational Search Algorithm, Black-Hole algorithm, Multi-Verse Optimizer, and Galactic Swarm Optimization. A thorough analysis of ninety-one relevant papers was carried out to highlight their performance and to identify the gravitational and attraction foundations, as well as the universe laws supporting them. Included are their standard formulations, as well as their improved, modified, hybrid, cascade, fuzzy, chaotic and adaptive versions. Moreover, this review also deeply delves into the impact of universe-inspired algorithms on control problems of dynamic systems, providing an extensive list of control-related applications, and their inherent advantages and limitations. Strong evidence suggests that gravitation-inspired and black-hole dynamic-driven algorithms can outperform other well-known algorithms in control engineering, even though they have not been designed according to realistic astrophysical phenomena and formulated according to astrophysics laws. Even so, they support future research directions towards the development of high-sophisticated control laws inspired by Newtonian/Einsteinian physics, such that effective control-astrophysics bridges can be established and applied in a wide range of applications.

Maize yield prediction and condition monitoring at the sub-county scale in Kenya: synthesis of remote sensing information and crop modeling.

Agricultural production assessments are crucial for formulating strategies for closing yield gaps and enhancing production efficiencies. While in situ crop yield measurements can provide valuable and accurate information, such approaches are costly and lack scalability for large-scale assessments. Therefore, crop modeling and remote sensing (RS) technologies are essential for assessing crop conditions and predicting yields at larger scales. In this study, we combined RS and a crop growth model to assess phenology, evapotranspiration (ET), and yield dynamics at grid and sub-county scales in Kenya. We synthesized RS information from the Food and Agriculture Organization (FAO) Water Productivity Open-access portal (WaPOR) to retrieve sowing date information for driving the model simulations. The findings showed that grid-scale management information and progressive crop growth could be accurately derived, reducing the model output uncertainties. Performance assessment of the modeled phenology yielded satisfactory accuracies at the sub-county scale during two representative seasons. The agreement between the simulated ET and yield was improved with the combined RS-crop model approach relative to the crop model only, demonstrating the value of additional large-scale RS information. The proposed approach supports crop yield estimation in data-scarce environments and provides valuable insights for agricultural resource management enabling countermeasures, especially when shortages are perceived in advance, thus enhancing agricultural production.

Should a Stoma Be Used After Intestinal Transplant.

As we all acknowledge benefits of ostomies, they can come with significant morbidity, quality of life issues, and major complications, especially during reversal procedures. In recent years, we have started to observe that similar graft and patient survival can be achieved without ostomies in certain cases. This observation and practice adopted in a few large-volume transplant centers opened a new discussion about the necessity of ostomies in intestinal transplantation. There is still more time and randomized studies will be needed to better understand and analyze the risk/benefits of "No-ostomy" approach in intestinal transplantation.

Dimethyl fumarate modulates the regulatory T cell response in the mesenteric lymph nodes of mice with experimental autoimmune encephalomyelitis.

Dimethyl fumarate (DMF, Tecfidera) is an oral drug utilized to treat relapsing-remitting multiple sclerosis (MS). DMF treatment reduces disease activity in MS. Gastrointestinal discomfort is a common adverse effect of the treatment with DMF. This study aimed to investigate the effect of DMF administration in the gut draining lymph nodes cells of C57BL6/J female mice with experimental autoimmune encephalomyelitis (EAE), an animal model of MS. We have demonstrated that the treatment with DMF (7.5 mg/kg) significantly reduces the severity of EAE. This reduction of the severity is accompanied by the increase of both proinflammatory and anti-inflammatory mechanisms at the beginning of the treatment. As the treatment progressed, we observed an increasing number of regulatory Foxp3 negative CD4 T cells (Tr1), and anti-inflammatory cytokines such as IL-27, as well as the reduction of PGE2 level in the mesenteric lymph nodes of mice with EAE. We provide evidence that DMF induces a gradual anti-inflammatory response in the gut draining lymph nodes, which might contribute to the reduction of both intestinal discomfort and the inflammatory response of EAE. These findings indicate that the gut is the first microenvironment of action of DMF, which may contribute to its effects of reducing disease severity in MS patients.

Cachd1 interacts with Wnt receptors and regulates neuronal asymmetry in the zebrafish brain.

Neurons on the left and right sides of the nervous system often show asymmetric properties, but how such differences arise is poorly understood. Genetic screening in zebrafish revealed that loss of function of the transmembrane protein Cachd1 resulted in right-sided habenula neurons adopting left-sided identity. Cachd1 is expressed in neuronal progenitors, functions downstream of asymmetric environmental signals, and influences timing of the normally asymmetric patterns of neurogenesis. Biochemical and structural analyses demonstrated that Cachd1 can bind simultaneously to Lrp6 and Frizzled family Wnt co-receptors. Consistent with this, lrp6 mutant zebrafish lose asymmetry in the habenulae, and epistasis experiments support a role for Cachd1 in modulating Wnt pathway activity in the brain. These studies identify Cachd1 as a conserved Wnt receptor-interacting protein that regulates lateralized neuronal identity in the zebrafish brain.

A rat model of cirrhosis with well-differentiated hepatocellular carcinoma induced by thioacetamide.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths, and commonly associated with hepatic fibrosis or cirrhosis. This study aims to establish a rat model mimicking the progression from liver fibrosis to cirrhosis and subsequently to HCC using thioacetamide (TAA). We utilized male Lewis rats, treating them with intra-peritoneal injections of TAA. These rats received bi-weekly injections of either 200 mg/kg TAA or saline (as a control) over a period of 34 weeks. The development of cirrhosis and hepatocarcinogenesis was monitored through histopathological examinations, biochemical markers, and immunohistochemical analyses. Our results demonstrated that chronic TAA administration induced cirrhosis and well-differentiated HCC, characterized by increased fibrosis, altered liver architecture, and enhanced hepatocyte proliferation. Biochemical analyses revealed significant alterations in liver function markers, including elevated alpha-fetoprotein (AFP) levels, without affecting kidney function or causing significant weight loss or mortality in rats. This TAA-induced cirrhosis and HCC rat model successfully replicates the clinical progression of human HCC, including liver function impairment and early-stage liver cancer characteristics. It presents a valuable tool for future research on the mechanisms of antitumor drugs in tumor initiation and development.

Carbon monoxide as a cellular protective agent in a swine model of cardiac arrest protocol.

Out-of-hospital cardiac arrest (OHCA) affects over 360,000 adults in the United States each year with a 50-80% mortality prior to reaching medical care. Despite aggressive supportive care and targeted temperature management (TTM), half of adults do not live to hospital discharge and nearly one-third of survivors have significant neurologic injury. The current treatment approach following cardiac arrest resuscitation consists primarily of supportive care and possible TTM. While these current treatments are commonly used, mortality remains high, and survivors often develop lasting neurologic and cardiac sequela well after resuscitation. Hence, there is a critical need for further therapeutic development of adjunctive therapies. While select therapeutics have been experimentally investigated, one promising agent that has shown benefit is CO. While CO has traditionally been thought of as a cellular poison, there is both experimental and clinical evidence that demonstrate benefit and safety in ischemia with lower doses related to improved cardiac/neurologic outcomes. While CO is well known for its poisonous effects, CO is a generated physiologically in cells through the breakdown of heme oxygenase (HO) enzymes and has potent antioxidant and anti-inflammatory activities. While CO has been studied in myocardial infarction itself, the role of CO in cardiac arrest and post-arrest care as a therapeutic is less defined. Currently, the standard of care for post-arrest patients consists primarily of supportive care and TTM. Despite current standard of care, the neurological prognosis following cardiac arrest and return of spontaneous circulation (ROSC) remains poor with patients often left with severe disability due to brain injury primarily affecting the cortex and hippocampus. Thus, investigations of novel therapies to mitigate post-arrest injury are clearly warranted. The primary objective of this proposed study is to combine our expertise in swine models of CO and cardiac arrest for future investigations on the cellular protective effects of low dose CO. We will combine our innovative multi-modal diagnostic platform to assess cerebral metabolism and changes in mitochondrial function in swine that undergo cardiac arrest with therapeutic application of CO.

Multimorbidity and acute infectious diseases in urban and semi-urban settings in Peru: A mixed-methods study.

Background: The co-occurrence of chronic diseases and acute infectious events exacerbates disability and diminishes quality of life, yet research in Low- and Middle-Income countries is scarce. We aimed to investigate the relationship between infectious events and multimorbidity in resource-constrained settings. Methods: We conducted a sequential mixed-method study in Lima and Tumbes, Peru, with participants having multimorbidity from the CRONICAS Cohort Study. They completed a questionnaire on the occurrence, treatment, and health-seeking behaviour related to acute infectious events. Qualitative interviews explored the perceptions and links between multimorbidity and acute infectious events for a subgroup of participants. Findings: Among individuals with multimorbidity, low awareness of chronic conditions and poor medication adherence. The cumulative incidence for respiratory and gastrointestinal infections, the most reported acute conditions, was 2.0 [95%CI: 1.8-2.2] and 1.6 [1.2-1.9] events per person per year, respectively. Individuals with cancer (6.4 [1.6-11.2] events per person per year) or gastrointestinal reflux (7.2 [4.4-10.1] events per person per year) reported higher cumulative incidence of infectious events than others, such as those with cardiovascular and metabolic conditions (5.2 [4.6-5.8] events per person per year). Those with three or more chronic conditions had a slightly higher cumulative incidence compared with individuals with two conditions (5.7 [4.4-7.0] vs 5.0 [4.4-5.6] events per person per year). Around 40% of individuals with multimorbidity sought healthcare assistance, while others chose drugstores or didn't seek help. Our qualitative analysis showed diverse perceptions among participants regarding the connections between chronic and acute conditions. Those who recognized a connection emphasized the challenges in managing these interactions. Interpretation: Our study advances understanding of multimorbidity challenges in resource-limited settings, highlighting the impact of acute infections on patients' existing multimorbidity burden.

Infrared spectroscopy as a predictive tool for the severity of COVID-19 using patient's saliva: A strategy to avoid hyperinflammation.

Discriminate the severity level of COVID-19 disease is still a challenge. Here we investigate the capability of micro-infrared absorption spectroscopy (micro-FTIR) to probe COVID-19 severity level and predict hyperinflammation, correlating the assigned vibrational data to relevant biomolecules related to the immune system. Saliva of 184 patients was analysed by ELISA assay (Hepcidin) and micro-FTIR. Vibrational bands related to IgM and IgA can discriminate healthy from Severe individuals (sensitivity ≥ 0.749, specificity ≥ 0.945) and are less effective in discriminating Mild or Moderate individuals from the Severe group (sensitivity ≥ 0.628, specificity ≥ 0.867). Analysis of the second derivative of spectra probed increased levels of IL-6 in the saliva a key additional information for the degree of severity prediction. Because the model discriminates all the groups regarding the Severe group, it predicts an intense state of inflammation based on FTIR analysis. It is a powerful tool for predicting hyperinflammation conditions related to SARS-CoV-2 infection and may be an ally in implementing drugs or therapeutic approaches to manage COVID-19 in the Severe stage in healthcare facilities.

Transport Properties in Multicomponent Systems Containing Cyclodextrins and Nickel Ions.

In this work, we propose a comprehensive experimental study of the diffusion of nickel ions in combination with different cyclodextrins as carrier molecules for enhanced solubility and facilitated transport. For this, ternary mutual diffusion coefficients measured by Taylor dispersion method are reported for aqueous solutions containing nickel salts and different cyclodextrins (that is, α-CD, ß-CD, and γ-CD) at 298.15 K. A combination of Taylor dispersion and other methods, such as UV-vis spectroscopy, will be used to obtain complementary information on these systems. The determination of the physicochemical properties of these salts with CDs in aqueous solution provides information that allows us to understand solute-solvent interactions, and gives a significant contribution to understanding the mechanisms underlying diffusional transport in aqueous solutions, and, consequently, to mitigating the potential toxicity associated with these metal ions. For example, using mutual diffusion data, it is possible to estimate the number of moles of each ion transported per mole of the cyclodextrin driven by its own concentration gradient.

Thermodynamic Study of Alkylsilane and Alkylsiloxane-Based Ionic Liquids.

The thermodynamic properties of ionic liquids (ILs) bearing alkylsilane and alkylsiloxane chains, as well as their carbon-based analogs, were investigated. Effects such as the replacement of carbon atoms by silicon atoms, the introduction of a siloxane linkage, and the length of the alkylsilane chain were explored. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were used to study the thermal and phase behavior (glass transition temperature, melting point, enthalpy and entropy of fusion, and thermal stability). Heat capacity was obtained by high-precision drop calorimetry and differential scanning microcalorimetry. The volatility and cohesive energy of these ILs were investigated via the Knudsen effusion method coupled with a quartz crystal microbalance (KEQCM). Gas phase energetics and structure were also studied to obtain the gas phase heat capacity as well as the energy profile associated with the rotation of the IL side chain. The computational study suggested the existence of an intramolecular interaction in the alkylsiloxane-based IL. The obtained glass transition temperatures seem to follow the trend of chain flexibility. An increase of the alkylsilane chain leads to a seemingly linear increase in molar heat capacity. A regular increment of 30 J·K-1·mol-1 in the molar heat capacity was found for the replacement of carbon by silicon in the IL alkyl chain. The alkylsilane series was revealed to be slightly more volatile than its carbon-based analogs. A further increase in volatility was found for the alkylsiloxane-based IL, which is likely related to the decrease of the cohesive energy due to the existence of an intramolecular interaction between the siloxane linkage and the imidazolium headgroup. The use of Si in the IL structure is a suitable way to significantly reduce the IL's viscosity while preserving its large liquid range (low melting point and high thermal stability) and low volatilities.

Environmental impact assessment of the electrokinetic adsorption barriers to remove different herbicides from agricultural soils.

In this study, the sustainability of the electrokinetic remediation soil flushing (EKSFs) process integrated without and with adsorption barriers (EKABs) have been evaluated for the treatment of four soils contaminated with Atrazine, Oxyfluorfen, Chlorosulfuron and 2,4-D. To this purpose, the environmental effects of both procedures (EKSFs and EKABs) have been determined through a life cycle assessment (LCA). SimaPro 9.3.0.3 was used as software tool and Ecoinvent 3.3 as data base to carry out the inventory of the equipment of each remediation setup based on experimental measurements. The environmental burden was quantified using the AWARE, USEtox, IPPC, and ReCiPe methods into 3 Endpoint impact categories (and damage to human health, ecosystem and resources) and 7 Midpoints impact categories (water footprint, global warming potential, ozone depletion, human toxicity (cancer and human non-cancer), freshwater ecotoxicity and terrestrial ecotoxicity). In general terms, the energy applied to treatment (using the Spanish energy mix) was the parameter with the greatest influence on the carbon footprint, ozone layer depletion and water footprint accounting for around 70 % of the overall impact contribution. On the other hand, from the point of view of human toxicity and freshwater ecotoxicity of soil treatments with 32 mg kg-1 of the different pesticides, the EKSF treatment is recommended for soils with Chlorosulfuron. In this case, the carbon footprint and water footprint reached values around 0.36 kg of CO2 and 114 L of water per kg of dry soil, respectively. Finally, a sensitivity analysis was performed assuming different scenarios.

Brazilian Version of the Yale Food Addiction Scale for Individuals with Severe Obesity.

PURPOSE: Adapting and validating the Portuguese version of Br-YFAS 2.0-Obes to allow it to be used by the Brazilian candidates for bariatric surgery. MATERIALS AND METHODS: This study included 329 individuals with body mass indexes (BMI) ≥ 30 kg/m2, candidates for bariatric surgery at a reference hospital in Brazil. They were given a questionnaire that identified sociodemographic data, and the YFAS 2.0 scale, Portuguese version (BR-YFAS2.0-Obes), was applied to assess their food dependence levels. The Food Craving Questionnaire - Trait: The FCQ-T-reduced was subsequently used for a correlation analysis. RESULTS: The patients' average BMI was 41.6 ± 8.8 kg/m2. Br-YFAS2.0-Obes presented an average of 4.9 ± 3.1 for the FA diagnostic criteria. The resulting values of the Comparative Fit Index, Tucker Lewis Index, and Standardized Root Mean Square Residual were 0.990, 0.986, and 0.074, respectively. The internal consistency analysis of the 11 domains presented a Kuder-Richardson α of 0.82. The convergent validity, obtained through an analysis of the Pearson correlation coefficient, was r = 0.43 (p < 0.001). It was found that an increase in the number of Br-YFAS 2.0-Obes symptoms is associated with an increase in the FCQ-T-r mean. CONCLUSION: Much like the YFAS 2.0 in other languages, the BR-YFAS 2.0-Obes presented adequate convergent validity, reliability, and one-factor structure results, which makes it suitable for Brazilian candidates for bariatric surgery or any individual who is within BMI > = 30 kg/m2.

N-acetylcysteine absorption and its potential dual effect improve fitness and fruit yield in Xylella fastidiosa infected plants.

BACKGROUND: Xylella fastidiosa is a multi-host bacterium that can be detected in hundreds of plant species including several crops. Diseases caused by X. fastidiosa are considered a threat to global food production. The primary method for managing diseases caused by X. fastidiosa involves using insecticides to control the vector. Hence, it is necessary to adopt new and sustainable disease management technologies to control not only the insect but also the bacteria and plant health. We demonstrated that N-acetylcysteine (NAC), a low-cost cysteine analogue, is a sustainable molecule that can be used in agriculture to decrease the damage caused by X. fastidiosa and improve plant health. RESULTS: Using 15N-NAC we proved that this analogue was absorbed by the roots and transported to different parts of the plant. Inside the plant, NAC reduced the bacterial population by 60-fold and the number of xylem vessels blocked by bacterial biofilms. This reflected in a recovery of 0.28-fold of the daily sap flow compared to health plants. In addition, NAC-treated citrus variegated chlorosis (CVC) plants decreased the oxidative stress by improving the activity of detoxifying enzymes. Moreover, the use of NAC in field conditions positively contributed to the increase in fruit yield of CVC-diseased plants. CONCLUSION: Our research not only advances the understanding of NAC absorption in plants, but also indicates its dual effect as an antimicrobial and antioxidant molecule. This, in turn, negatively affects bacterial survival while improving plant health by decreasing oxidative stress. Overall, the positive field-based evidence supports the viability of NAC as a sustainable agricultural application. © 2024 Society of Chemical Industry.

A multimodal approach using fundus images and text meta-data in a machine learning classifier with embeddings to predict years with self-reported diabetes - An exploratory analysis.

AIMS: Machine learning models can use image and text data to predict the number of years since diabetes diagnosis; such model can be applied to new patients to predict, approximately, how long the new patient may have lived with diabetes unknowingly. We aimed to develop a model to predict self-reported diabetes duration. METHODS: We used the Brazilian Multilabel Ophthalmological Dataset. Unit of analysis was the fundus image and its meta-data, regardless of the patient. We included people 40 + years and fundus images without diabetic retinopathy. Fundus images and meta-data (sex, age, comorbidities and taking insulin) were passed to the MedCLIP model to extract the embedding representation. The embedding representation was passed to an Extra Tree Classifier to predict: 0-4, 5-9, 10-14 and 15 + years with self-reported diabetes. RESULTS: There were 988 images from 563 people (mean age = 67 years; 64 % were women). Overall, the F1 score was 57 %. The group 15 + years of self-reported diabetes had the highest precision (64 %) and F1 score (63 %), while the highest recall (69 %) was observed in the group 0-4 years. The proportion of correctly classified observations was 55 % for the group 0-4 years, 51 % for 5-9 years, 58 % for 10-14 years, and 64 % for 15 + years with self-reported diabetes. CONCLUSIONS: The machine learning model had acceptable accuracy and F1 score, and correctly classified more than half of the patients according to diabetes duration. Using large foundational models to extract image and text embeddings seems a feasible and efficient approach to predict years living with self-reported diabetes.