Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods.

When developing models for clinical information retrieval and decision support systems, the discrete outcomes required for training are often missing. These labels need to be extracted from free text in electronic health records. For this extraction process one of the most important contextual properties in clinical text is negation, which indicates the absence of findings. We aimed to improve large scale extraction of labels by comparing three methods for negation detection in Dutch clinical notes. We used the Erasmus Medical Center Dutch Clinical Corpus to compare a rule-based method based on ContextD, a biLSTM model using MedCAT and (finetuned) RoBERTa-based models. We found that both the biLSTM and RoBERTa models consistently outperform the rule-based model in terms of F1 score, precision and recall. In addition, we systematically categorized the classification errors for each model, which can be used to further improve model performance in particular applications. Combining the three models naively was not beneficial in terms of performance. We conclude that the biLSTM and RoBERTa-based models in particular are highly accurate accurate in detecting clinical negations, but that ultimately all three approaches can be viable depending on the use case at hand.

Influence of luminal and basal subtype in prognosis of high-grade non muscle invasive urothelial carcinoma.

BACKGROUND: Recent studies have shown that the classification of high-grade urothelial carcinoma non-muscle invasive (HGBCNMI) based on molecular subtypes might be a valuable strategy to identify patients with a worse clinical prognosis. OBJECTIVE: Determine the effect of the luminal and basal molecular subtype determined by immunistochemical on prognosis in patients with HGBC in Mexican population. METHODS: Phenotypes were evaluated by immunohistochemical staining of luminal (GATA3, FOXA1) and basal (CK5/6, CK14) markers in paraffin-embedded tissue samples from 45 patients with a diagnosis of HGBCNMI treated at Instituto Nacional de Cancerología-México (INCan) between 2009 and 2019. The association with prognosis was evaluated using Kaplan-Meier curves and multivariable-adjusted Cox models. RESULTS: HGBCNMI patients showed mean age of 58.77 years (SD: ±12.08 years). We identified expression of the luminal molecular subtype in 35 cases (77.78 %), and 10 cases (22.22 %) with "combined" expression of the molecular subtype (basal and luminal expression). The combined phenotype was statistically more frequent in metastatic cases (p-value = 0.028). In Kaplan-Meier curves, combined expression of luminal and basal molecular markers was associated with disease progression (p-value = 0.002, log-rank test). Cox regression models confirmed this association, which was not influenced by age (p-value = 0.007) or gender (p-value = 0.007). No association of phenotypes with overall survival (p-value = 0.860) or relapse (p-value = 0.5) was observed. CONCLUSION: The combined expression of immunohistochemical markers of the luminal and basal subtype might be considered as predictor for disease progression in patients with HGBCNMI in Mexican population.

Mutational Landscape of Bladder Cancer in Mexican Patients: KMT2D Mutations and chr11q15.5 Amplifications Are Associated with Muscle Invasion.

Bladder cancer (BC) is the most common neoplasm of the urinary tract, which originates in the epithelium that covers the inner surface of the bladder. The molecular BC profile has led to the development of different classifications of non-muscle invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). However, the genomic BC landscape profile of the Mexican population, including NMIBC and MIBC, is unknown. In this study, we aimed to identify somatic single nucleotide variants (SNVs) and copy number variations (CNVs) in Mexican patients with BC and their associations with clinical and pathological characteristics. We retrospectively evaluated 37 patients treated between 2012 and 2021 at the National Cancer Institute-Mexico (INCan). DNA samples were obtained from paraffin-embedded tumor tissues and exome sequenced. Strelka2 and Lancet packages were used to identify SNVs and insertions or deletions. FACETS was used to determine CNVs. We found a high frequency of mutations in TP53 and KMT2D, gains in 11q15.5 and 19p13.11-q12, and losses in 7q11.23. STAG2 mutations and 1q11.23 deletions were also associated with NMIBC and low histologic grade.

Evaluating pointwise reliability of machine learning prediction.

Interest in Machine Learning applications to tackle clinical and biological problems is increasing. This is driven by promising results reported in many research papers, the increasing number of AI-based software products, and by the general interest in Artificial Intelligence to solve complex problems. It is therefore of importance to improve the quality of machine learning output and add safeguards to support their adoption. In addition to regulatory and logistical strategies, a crucial aspect is to detect when a Machine Learning model is not able to generalize to new unseen instances, which may originate from a population distant to that of the training population or from an under-represented subpopulation. As a result, the prediction of the machine learning model for these instances may be often wrong, given that the model is applied outside its "reliable" space of work, leading to a decreasing trust of the final users, such as clinicians. For this reason, when a model is deployed in practice, it would be important to advise users when the model's predictions may be unreliable, especially in high-stakes applications, including those in healthcare. Yet, reliability assessment of each machine learning prediction is still poorly addressed. Here, we review approaches that can support the identification of unreliable predictions, we harmonize the notation and terminology of relevant concepts, and we highlight and extend possible interrelationships and overlap among concepts. We then demonstrate, on simulated and real data for ICU in-hospital death prediction, a possible integrative framework for the identification of reliable and unreliable predictions. To do so, our proposed approach implements two complementary principles, namely the density principle and the local fit principle. The density principle verifies that the instance we want to evaluate is similar to the training set. The local fit principle verifies that the trained model performs well on training subsets that are more similar to the instance under evaluation. Our work can contribute to consolidating work in machine learning especially in medicine.

Association between life-course leisure-time physical activity and prostate cancer.

OBJECTIVE: To evaluate the association between life-course leisure-time physical activity (PA) and prostate cancer (PC) among males living in Mexico City. Materials and meth-ods. Information from 394 incident PC cases and 794 popula-tion controls matched by age (± 5 years), was analyzed. Using leisure-time PA information at different life stages, life-course PA patterns were constructed. The association between PA and PC was estimated using an unconditional logistic regres-sion model. RESULTS: Three life-course PA patterns were identified: low PA (71.0%), moderate PA (22.0%), and high PA (7.0%); this last pattern was characterized by higher levels and consistent PA practice. Compared with inactive males, those in the high PA pattern (OR: 0.50; 95%CI: 0.26-0.93) had significantly lower PC odds. CONCLUSION: Intense and regular PA could reduce the possibility of PC. These results are in accordance with PA World Health Organization rec-ommendations.

Prefrontal Cortical Control of Activity in Nucleus Accumbens Core Is Weakened by High-Fat Diet and Prevented by Co-Treatment with N-Acetylcysteine: Implications for the Development of Obesity.

A loss of neuroplastic control on nucleus accumbens (NAc) neuronal activity exerted by the medial prefrontal cortex (mPFC) through long-term depression (LTD) is involved in triggering drug-seeking behavior and relapse on several substances of abuse due to impaired glutamate homeostasis in tripartite synapses of the nucleus accumbens (NAc) core. To test whether this maladaptive neuroplastic mechanism underlies the addiction-like behavior induced in young mice by a high-fat diet (HFD), we utilized 28-days-old male mice fed HFD ad-libitum over 2 weeks, followed by 5 days of HFD abstinence. Control groups were fed a regular diet. HFD fed mice showed increased ΔFosB levels in the NAc core region, whereas LTD triggered from the mPFC became suppressed. Interestingly, LTD suppression was prevented by an i.p. injection of 100 mg/kg N-acetylcysteine 2.5 h before inducing LTD from the mPFC. In addition, excessive weight gain due to HFD feeding was diminished by adding 2mg/mL N-acetylcysteine in drinking water. Those results show a loss of neuroplastic mPFC control over NAc core activity induced by HFD consumption in young subjects. In conclusion, ad libitum consumption of HFD can lead to neuroplastic changes an addiction-like behavior that can be prevented by N-acetylcysteine, helping to decrease the rate of excessive weight gain.

Do initial concentration and activated sludge seasonality affect pharmaceutical biotransformation rate constants?

Pharmaceuticals find their way to the aquatic environment via wastewater treatment plants (WWTPs). Biotransformation plays an important role in mitigating environmental risks; however, a mechanistic understanding of involved processes is limited. The aim of this study was to evaluate potential relationships between first-order biotransformation rate constants (kb) of nine pharmaceuticals and initial concentration of the selected compounds, and sampling season of the used activated sludge inocula. Four-day bottle experiments were performed with activated sludge from WWTP Groesbeek (The Netherlands) of two different seasons, summer and winter, spiked with two environmentally relevant concentrations (3 and 30 nM) of pharmaceuticals. Concentrations of the compounds were measured by LC-MS/MS, microbial community composition was assessed by 16S rRNA gene amplicon sequencing, and kb values were calculated. The biodegradable pharmaceuticals were acetaminophen, metformin, metoprolol, terbutaline, and phenazone (ranked from high to low biotransformation rates). Carbamazepine, diatrizoic acid, diclofenac, and fluoxetine were not converted. Summer and winter inocula did not show significant differences in microbial community composition, but resulted in a slightly different kb for some pharmaceuticals. Likely microbial activity was responsible instead of community composition. In the same inoculum, different kb values were measured, depending on initial concentration. In general, biodegradable compounds had a higher kb when the initial concentration was higher. This demonstrates that Michealis-Menten kinetic theory has shortcomings for some pharmaceuticals at low, environmentally relevant concentrations and that the pharmaceutical concentration should be taken into account when measuring the kb in order to reliably predict the fate of pharmaceuticals in the WWTP. KEY POINTS: • Biotransformation and sorption of pharmaceuticals were assessed in activated sludge. • Higher initial concentrations resulted in higher biotransformation rate constants for biodegradable pharmaceuticals. • Summer and winter inocula produced slightly different biotransformation rate constants although microbial community composition did not significantly change.

Hypertension in Prenatally Undernourished Young-Adult Rats Is Maintained by Tonic Reciprocal Paraventricular-Coerulear Excitatory Interactions.

Prenatally malnourished rats develop hypertension in adulthood, in part through increased α1-adrenoceptor-mediated outflow from the paraventricular nucleus (PVN) to the sympathetic system. We studied whether both α1-adrenoceptor-mediated noradrenergic excitatory pathways from the locus coeruleus (LC) to the PVN and their reciprocal excitatory CRFergic connections contribute to prenatal undernutrition-induced hypertension. For that purpose, we microinjected either α1-adrenoceptor or CRH receptor agonists and/or antagonists in the PVN or the LC, respectively. We also determined the α1-adrenoceptor density in whole hypothalamus and the expression levels of α1A-adrenoceptor mRNA in the PVN. The results showed that: (i) agonists microinjection increased systolic blood pressure and heart rate in normotensive eutrophic rats, but not in prenatally malnourished subjects; (ii) antagonists microinjection reduced hypertension and tachycardia in undernourished rats, but not in eutrophic controls; (iii) in undernourished animals, antagonist administration to one nuclei allowed the agonists recover full efficacy in the complementary nucleus, inducing hypertension and tachycardia; (iv) early undernutrition did not modify the number of α1-adrenoceptor binding sites in hypothalamus, but reduced the number of cells expressing α1A-adrenoceptor mRNA in the PVN. These results support the hypothesis that systolic pressure and heart rate are increased by tonic reciprocal paraventricular-coerulear excitatory interactions in prenatally undernourished young-adult rats.

Tissue Metabolic Changes Drive Cytokine Responses to Mycobacterium tuberculosis.

Cellular metabolism can influence host immune responses to Mycobacterium tuberculosis. Using a systems biology approach, differential expression of 292 metabolic genes involved in glycolysis, glutathione, pyrimidine, and inositol phosphate pathways was evident at the site of a human tuberculin skin test challenge in patients with active tuberculosis infection. For 28 metabolic genes, we identified single nucleotide polymorphisms that were trans-acting for in vitro cytokine responses to M. tuberculosis stimulation, including glutathione and pyrimidine metabolism genes that alter production of Th1 and Th17 cytokines. Our findings identify novel therapeutic targets in host metabolism that may shape protective immunity to tuberculosis.

High-Dimensional Feature Selection for Automatic Classification of Coronary Stenosis Using an Evolutionary Algorithm.

In this paper, a novel strategy to perform high-dimensional feature selection using an evolutionary algorithm for the automatic classification of coronary stenosis is introduced. The method involves a feature extraction stage to form a bank of 473 features considering different types such as intensity, texture and shape. The feature selection task is carried out on a high-dimensional feature bank, where the search space is denoted by O(2n) and n=473. The proposed evolutionary search strategy was compared in terms of the Jaccard coefficient and accuracy classification with different state-of-the-art methods. The highest feature selection rate, along with the best classification performance, was obtained with a subset of four features, representing a 99% discrimination rate. In the last stage, the feature subset was used as input to train a support vector machine using an independent testing set. The classification of coronary stenosis cases involves a binary classification type by considering positive and negative classes. The highest classification performance was obtained with the four-feature subset in terms of accuracy (0.86) and Jaccard coefficient (0.75) metrics. In addition, a second dataset containing 2788 instances was formed from a public image database, obtaining an accuracy of 0.89 and a Jaccard Coefficient of 0.80. Finally, based on the performance achieved with the four-feature subset, they can be suitable for use in a clinical decision support system.

Fe(II)Cl2 amendment suppresses pond methane emissions by stimulating iron-dependent anaerobic oxidation of methane.

Aquatic ecosystems are large contributors to global methane (CH4) emissions. Eutrophication significantly enhances CH4-production as it stimulates methanogenesis. Mitigation measures aimed at reducing eutrophication, such as the addition of metal salts to immobilize phosphate (PO43-), are now common practice. However, the effects of such remedies on methanogenic and methanotrophic communities-and therefore on CH4-cycling-remain largely unexplored. Here, we demonstrate that Fe(II)Cl2 addition, used as PO43- binder, differentially affected microbial CH4 cycling-processes in field experiments and batch incubations. In the field experiments, carried out in enclosures in a eutrophic pond, Fe(II)Cl2 application lowered in-situ CH4 emissions by lowering net CH4-production, while sediment aerobic CH4-oxidation rates-as found in batch incubations of sediment from the enclosures-did not differ from control. In Fe(II)Cl2-treated sediments, a decrease in net CH4-production rates could be attributed to the stimulation of iron-dependent anaerobic CH4-oxidation (Fe-AOM). In batch incubations, anaerobic CH4-oxidation and Fe(II)-production started immediately after CH4 addition, indicating Fe-AOM, likely enabled by favorable indigenous iron cycling conditions and the present methanotroph community in the pond sediment. 16S rRNA sequencing data confirmed the presence of anaerobic CH4-oxidizing archaea and both iron-reducing and iron-oxidizing bacteria in the tested sediments. Thus, besides combatting eutrophication, Fe(II)Cl2 application can mitigate CH4 emissions by reducing microbial net CH4-production and stimulating Fe-AOM.

Real-time EEG-based emotion recognition for neurohumanities: perspectives from principal component analysis and tree-based algorithms.

Within the field of Humanities, there is a recognized need for educational innovation, as there are currently no reported tools available that enable individuals to interact with their environment to create an enhanced learning experience in the humanities (e.g., immersive spaces). This project proposes a solution to address this gap by integrating technology and promoting the development of teaching methodologies in the humanities, specifically by incorporating emotional monitoring during the learning process of humanistic context inside an immersive space. In order to achieve this goal, a real-time emotion recognition EEG-based system was developed to interpret and classify specific emotions. These emotions aligned with the early proposal by Descartes (Passions), including admiration, love, hate, desire, joy, and sadness. This system aims to integrate emotional data into the Neurohumanities Lab interactive platform, creating a comprehensive and immersive learning environment. This work developed a ML, real-time emotion recognition model that provided Valence, Arousal, and Dominance (VAD) estimations every 5 seconds. Using PCA, PSD, RF, and Extra-Trees, the best 8 channels and their respective best band powers were extracted; furthermore, multiple models were evaluated using shift-based data division and cross-validations. After assessing their performance, Extra-Trees achieved a general accuracy of 94%, higher than the reported in the literature (88% accuracy). The proposed model provided real-time predictions of VAD variables and was adapted to classify Descartes' six main passions. However, with the VAD values obtained, more than 15 emotions can be classified (reported in the VAD emotion mapping) and extend the range of this application.

Neisseria gonorrhoeae induces a tolerogenic phenotype in macrophages to modulate host immunity.

Neisseria gonorrhoeae is the etiological agent of gonorrhoea, which is a sexually transmitted disease widespread throughout the world. N. gonorrhoeae does not improve immune response in patients with reinfection, suggesting that gonococcus displays several mechanisms to evade immune response and survive in the host. N. gonorrhoeae is able to suppress the protective immune response at different levels, such as B and T lymphocytes and dendritic cells. In this study, we determined whether N. gonorrhoeae directly conditions the phenotype of RAW 264.7 murine macrophage cell line and its response. We established that gonococcus was effectively phagocytosed by the RAW 264.7 cells and upregulates production of immunoregulatory cytokines (IL-10 and TGF- ß 1) but not the production of proinflammatory cytokine TNF- α , indicating that gonococcus induces a shift towards anti-inflammatory cytokine production. Moreover, N. gonorrhoeae did not induce significant upregulation of costimulatory CD86 and MHC class II molecules. We also showed that N. gonorrhoeae infected macrophage cell line fails to elicit proliferative CD4+ response. This implies that macrophage that can phagocytose gonococcus do not display proper antigen-presenting functions. These results indicate that N. gonorrhoeae induces a tolerogenic phenotype in antigen-presenting cells, which seems to be one of the mechanisms to induce evasion of immune response.

TNFR2+ regulatory T cells protect against bacteremic pneumococcal pneumonia by suppressing IL-17A-producing γδ T cells in the lung.

Streptococcus pneumoniae is a pathogen of global morbidity and mortality. Pneumococcal pneumonia can lead to systemic infections associated with high rates of mortality. We find that, upon pneumococcal infection, pulmonary Treg cells are activated and have upregulated TNFR2 expression. TNFR2-deficient mice have compromised Treg cell responses and highly activated IL-17A-producing γδ T cell (γδT17) responses, resulting in significantly enhanced neutrophil infiltration, tissue damage, and rapid development of bacteremia, mirroring responses in Treg cell-depleted mice. Deletion of total Treg cells predominantly activate IFNγ-T cell responses, whereas adoptive transfer of TNFR2+ Treg cells specifically suppress the γδT17 response, suggesting a targeted control of γδT17 activation by TNFR2+ Treg cells. Blocking IL-17A at early stage of infection significantly reduces bacterial blood dissemination and improves survival in TNFR2-deficient mice. Our results demonstrate that TNFR2 is critical for Treg cell-mediated regulation of pulmonary γδT17-neutrophil axis, with impaired TNFR2+ Treg cell responses increasing susceptibility to disease.

Clinical and epidemiological aspects of the infection by Babesia, Theileria and Trypanosoma species in horses from northeastern Colombia.

Piroplasmosis and trypanosomiasis are debilitating diseases of great economic impact on the equine industry of Latin America. Considering the lack of studies in the northeastern part of Colombia, this study aimed to determine the epidemiological, clinical and genetic features associated with infection of the Babesia, Theileria, and Trypanosoma species in horses from this geographical area. Two hundred and eighty horses from the Arauca, Meta, and Santander departments were molecularly analyzed for infection with Babesia caballi, Theileria equi, Trypanosoma evansi, and Trypanosoma vivax. Furthermore, clinical, epidemiological and entomological analyses were performed on the data sets. Molecular analysis showed 25.7% and 3.9% prevalence for T. equi and T. evansi, respectively, without positive animals for B. caballi and T. vivax. There were no differences in the prevalence of T. equi between departments, whereas T. evansi was detected exclusively in Santander. A total of 633 ticks were collected from 72 horses across the three departments, with 84.7% corresponding to Dermacentor nitens, 10.9% to Amblyomma cajennense (sensu lato) (s.l). and 4.4% to Rhipicephalus microplus. For T. equi, genetic analyses showed that Colombian isolates belong to genotype C of species, along with sequences of Brazil and Mexico. Epidemiological analysis revealed a significant association between tick infestation and lack of vector control with molecular infection of T. equi, whereas clinical analysis revealed a significant reduction in packed cell volume, red blood cells, and mean corpuscular volume in positive animals to this pathogen. Furthermore, molecular infection by T. evansi was associated with epidemiological characteristics in the Santander department. In conclusion, our analysis revealed a moderate infection rate by T. equi of genotype C in horses from northeastern Colombia, which affects their clinical conditions. Control of ticks and treatment of symptomatic animals should be considered to reduce the economic impact associated with these infections in the equine industry.

High cell-free DNA is associated with disease progression, inflammasome activation and elevated levels of inflammasome-related cytokine IL-18 in patients with myelofibrosis.

Myelofibrosis (MF) is a clonal hematopoietic stem cell disorder classified among chronic myeloproliferative neoplasms, characterized by exacerbated myeloid and megakaryocytic proliferation and bone marrow fibrosis. It is induced by driver (JAK2/CALR/MPL) and high molecular risk mutations coupled to a sustained inflammatory state that contributes to disease pathogenesis. Patient outcome is determined by stratification into risk groups and refinement of current prognostic systems may help individualize treatment decisions. Circulating cell-free (cf)DNA comprises short fragments of double-stranded DNA, which promotes inflammation by stimulating several pathways, including inflammasome activation, which is responsible for IL-1ß and IL-18 maturation and release. In this work, we assessed the contribution of cfDNA as a marker of disease progression and mediator of inflammation in MF. cfDNA was increased in MF patients and higher levels were associated with adverse clinical outcome, a high-risk molecular profile, advanced disease stages and inferior overall survival, indicating its potential value as a prognostic marker. Cell-free DNA levels correlated with tumor burden parameters and markers of systemic inflammation. To mimic the effects of cfDNA, monocytes were stimulated with poly(dA:dT), a synthetic double-stranded DNA. Following stimulation, patient monocytes released higher amounts of inflammasome-processed cytokine, IL-18 to the culture supernatant, reflecting enhanced inflammasome function. Despite overexpression of cytosolic DNA inflammasome sensor AIM2, IL-18 release from MF monocytes was shown to rely mainly on the NLRP3 inflammasome, as it was prevented by NLRP3-specific inhibitor MCC950. Circulating IL-18 levels were increased in MF plasma, reflecting in vivo inflammasome activation, and highlighting the previously unrecognized involvement of this cytokine in MF cytokine network. Monocyte counts were higher in patients and showed a trend towards correlation with IL-18 levels, suggesting monocytes represent a source of circulating IL-18. The close correlation shown between IL-18 and cfDNA levels, together with the finding of enhanced DNA-triggered IL-18 release from monocytes, suggest that cfDNA promotes inflammation, at least in part, through inflammasome activation. This work highlights cfDNA, the inflammasome and IL-18 as additional players in the complex inflammatory circuit that fosters MF progression, potentially providing new therapeutic targets.

Radiomics Analyses to Predict Histopathology in Patients with Metastatic Testicular Germ Cell Tumors before Post-Chemotherapy Retroperitoneal Lymph Node Dissection.

BACKGROUND: The identification of histopathology in metastatic non-seminomatous testicular germ cell tumors (TGCT) before post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND) holds significant potential to reduce treatment-related morbidity in young patients, addressing an important survivorship concern. AIM: To explore this possibility, we conducted a study investigating the role of computed tomography (CT) radiomics models that integrate clinical predictors, enabling personalized prediction of histopathology in metastatic non-seminomatous TGCT patients prior to PC-RPLND. In this retrospective study, we included a cohort of 122 patients. METHODS: Using dedicated radiomics software, we segmented the targets and extracted quantitative features from the CT images. Subsequently, we employed feature selection techniques and developed radiomics-based machine learning models to predict histological subtypes. To ensure the robustness of our procedure, we implemented a 5-fold cross-validation approach. When evaluating the models' performance, we measured metrics such as the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, precision, and F-score. RESULT: Our radiomics model based on the Support Vector Machine achieved an optimal average AUC of 0.945. CONCLUSIONS: The presented CT-based radiomics model can potentially serve as a non-invasive tool to predict histopathological outcomes, differentiating among fibrosis/necrosis, teratoma, and viable tumor in metastatic non-seminomatous TGCT before PC-RPLND. It has the potential to be considered a promising tool to mitigate the risk of over- or under-treatment in young patients, although multi-center validation is critical to confirm the clinical utility of the proposed radiomics workflow.

Predicting and improving the microbial removal of organic micropollutants during wastewater treatment: A review.

Organic micropollutants (OMPs) consist of widely used chemicals such as pharmaceuticals and pesticides that can persist in surface and groundwaters at low concentrations (ng/L to µg/L) for a long time. The presence of OMPs in water can disrupt aquatic ecosystems and threaten the quality of drinking water sources. Wastewater treatment plants (WWTPs) rely on microorganisms to remove major nutrients from water, but their effectiveness at removing OMPs varies. Low removal efficiency might be the result of low concentrations, inherent stable chemical structures of OMPs, or suboptimal conditions in WWTPs. In this review, we discuss these factors, with special emphasis on the ongoing adaptation of microorganisms to degrade OMPs. Finally, recommendations are drawn to improve the prediction of OMP removal in WWTPs and to optimize the design of new microbial treatment strategies. OMP removal seems to be concentration-, compound-, and process-dependent, which poses a great complexity to develop accurate prediction models and effective microbial processes targeting all OMPs.

Time intervals to care and health service use experiences of uninsured cancer patients treated under public financing in Mexico City.

BACKGROUND: The present study assesses the time intervals from symptom discovery to treatment start and describes the health service use experiences of uninsured patients with cancer of the breast, cervix uteri, testicle, and prostate before their arrival to the cancer hospital. METHODS: This cross-sectional study included 1468 patients who were diagnosed between June 2016 and May 2017 and received treatment for the selected cancers in two of the largest public cancer hospitals in Mexico City, financed through Seguro Popular. Data was collected through a survey administered via face-to-face interviews with patients and a review of their medical files. RESULTS: The median time between detection (symptom discovery or first abnormal screening test) and treatment start was 6.6 months. For all types of cancer, the longest interval was the diagnostic interval -between the first use of healthcare services and the confirmation of cancer. Less than 20% cancer patients were diagnosed in the earliest stages that are associated with the best chances of long-term survival. The participants described a high use of private services for their first consultation, the use of several different types of health services and multiple consultations before arrival to the cancer centers, and 35% perceived being misdiagnosed by the first doctor they consulted. CONCLUSIONS: Most cancer patients treated in the two largest public institutions available for the uninsured faced long delays to get diagnosed and started treatment at advanced stages. Strengthening quality and access for effective early cancer diagnosis and treatment is key to improve patient outcomes in low and middle-income settings.

Benzimidazole fungicide biotransformation by comammox Nitrospira bacteria: Transformation pathways and associated proteomic responses.

Benzimidazole fungicides are frequently detected in aquatic environments and pose a serious health risk. Here, we investigated the metabolic capacity of the recently discovered complete ammonia-oxidizing (comammox) Nitrospira inopinata and kreftii to transform a representative set of benzimidazole fungicides (i.e., benzimidazole, albendazole, carbendazim, fuberidazole, and thiabendazole). Ammonia-oxidizing bacteria and archaea, as well as the canonical nitrite-oxidizing Nitrospira exhibited no or minor biotransformation activity towards all the five benzimidazole fungicides. In contrast, the investigated comammox bacteria actively transformed all the five benzimidazole fungicides, except for thiabendazole. The identified transformation products indicated hydroxylation, S-oxidation, and glycosylation as the major biotransformation pathways of benzimidazole fungicides. We speculated that these reactions were catalyzed by comammox-specific ammonia monooxygenase, cytochrome P450 monooxygenases, and glycosylases, respectively. Interestingly, the exposure to albendazole enhanced the expression of the antibiotic resistance gene acrB of Nitrospira inopinata, suggesting that some benzimidazole fungicides could act as environmental stressors that trigger cellular defense mechanisms. Altogether, this study demonstrated the distinct substrate specificity of comammox bacteria towards benzimidazole fungicides and implies their significant roles in the biotransformation of these fungicides in nitrifying environments.