The CARBA-MAP study: national mapping of carbapenemases in Spain (2014-2018).

Introduction: Infections caused by carbapenem-resistant Enterobacterales (CRE) and carbapenem-resistant Pseudomonas aeruginosa, including isolates producing acquired carbapenemases, constitute a prevalent health problem worldwide. The primary objective of this study was to determine the distribution of the different carbapenemases among carbapenemase-producing Enterobacterales (CPE, specifically Escherichia coli, Klebsiella pneumoniae, Enterobacter cloacae complex, and Klebsiella aerogenes) and carbapenemase-producing P. aeruginosa (CPPA) in Spain from January 2014 to December 2018. Methods: A national, retrospective, cross-sectional multicenter study was performed. The study included the first isolate per patient and year obtained from clinical samples and obtained for diagnosis of infection in hospitalized patients. A structured questionnaire was completed by the participating centers using the REDCap platform, and results were analyzed using IBM SPSS Statistics 29.0.0. Results: A total of 2,704 carbapenemase-producing microorganisms were included, for which the type of carbapenemase was determined in 2692 cases: 2280 CPE (84.7%) and 412 CPPA (15.3%), most often using molecular methods and immunochromatographic assays. Globally, the most frequent types of carbapenemase in Enterobacterales and P. aeruginosa were OXA-48-like, alone or in combination with other enzymes (1,523 cases, 66.8%) and VIM (365 cases, 88.6%), respectively. Among Enterobacterales, carbapenemase-producing K. pneumoniae was reported in 1821 cases (79.9%), followed by E. cloacae complex in 334 cases (14.6%). In Enterobacterales, KPC is mainly present in the South and South-East regions of Spain and OXA-48-like in the rest of the country. Regarding P. aeruginosa, VIM is widely distributed all over the country. Globally, an increasing percentage of OXA-48-like enzymes was observed from 2014 to 2017. KPC enzymes were more frequent in 2017-2018 compared to 2014-2016. Discussion: Data from this study help to understand the situation and evolution of the main species of CPE and CPPA in Spain, with practical implications for control and optimal treatment of infections caused by these multi-drug resistant organisms.

Psychiatric disorders in post-traumatic brain injury patients: A scoping review.

Background: Traumatic Brain Injury (TBI) is an important antecedent in the evaluation of patients with psychiatric disorders. The association between TBI and the subsequent appearance of psychiatric disorders has been documented, however, the findings found in the literature are diverse and controversial. Objective: To identify the most prevalent psychiatric disorders after head trauma. Design: An exploratory review (SCOPING) was carried out using the PRISMA extension protocol. Articles published between the years 2010-2022 were used to identify and describe the most prevalent psychiatric disorders after a TBI. Psychiatric disorders were classified according to clinical characteristics in neurotic syndromes, psychotic syndromes, cognitive disorders, among others. Results: A total of 32 articles were included. In the framework of neurotic syndromes, depression is the most prevalent psychiatric alteration after a TBI, becoming a sequel that shows a higher incidence in the first year after the traumatic event. The findings found in relation to post-traumatic stress disorder are controversial, showing great variability regarding the degree of severity of the injury. The prevalence of psychotic syndromes is relatively low because it is difficult to determine if the psychosis is a direct consequence of a TBI. In the cognitive sphere, it was found that people with TBI presented alterations in cognitive functions. Conclusions: The findings found in the review respond to the hypothesis initially raised, which assumes that head trauma is an important etiological factor in the appearance of psychiatric disorders.

Depressive symptomatology in adults during the COVID-19 pandemic.

Depression entails changes in the mental health of individuals worldwide. Episodes of depression lead to mood swings and changes in the motivational dimension. Our research focused on the prevalence of depression in the adult population and on how it affected the social and affective dimensions. Owing to the current pandemic, we deemed it necessary to explore how protective measures against COVID-19 infection, such as quarantines, could be related to mental health. Moreover, we found it important to determine the prevalence of depressive and anxious symptomatology in adults from the Valle del Cauca region in Colombia during the social isolation connected to COVID-19. Our study was descriptive, analytical and cross-sectional, and involved 1248 subjects. As tools, we used the Hamilton Depression Rating Scale and the Hamilton Anxiety Rating Scale. The data demonstrated that women were more likely to display symptoms of depression and that individuals aged between 24 and 29 were less likely to reveal symptoms of anxiety than those aged between 18 and 23. Moreover, childless or economically dependent individuals proved to be more likely to display symptoms of depression during the pandemic.

Noninvasive Prototype for Type 2 Diabetes Detection.

The present work demonstrates the design and implementation of a human-safe, portable, noninvasive device capable of predicting type 2 diabetes, using electrical bioimpedance and biometric features to train an artificial learning machine using an active learning algorithm based on population selection. In addition, there is an API with a graphical interface that allows the prediction and storage of data when the characteristics of the person are sent. The results obtained show an accuracy higher than 90% with statistical significance (p < 0.05). The Kappa coefficient values were higher than 0.9, showing that the device has a good predictive capacity which would allow the screening process of type 2 diabetes. This development contributes to preventive medicine and makes it possible to determine at a low cost, comfortably, without medical preparation, and in less than 2 minutes whether a person has type 2 diabetes.

A SSVEP-BCI Setup Based on Depth-of-Field.

In optical systems, the range of distance near the point of focus where objects are perceived sharply is referred as depth-of-field; objects outside this region are defocused and blurred. Furthermore, ophthalmology studies state that the amplitude and the latency of visual evoked potentials are affected by defocusing. In this context, this paper evaluates a novel setup for a steady-state visual evoked potential (SSVEP) brain-computer interface, in which two stimuli are presented together in the center of the user's field of view but at different distances ensuring that if one stimulus is focused on, the other one is non-focused, and vice versa. The evaluationwas conductedwith eight healthy subjects who were asked to focus on just one stimulus at a time. An average accuracy rate of 0.93 was achieved for a time window of 4 s by employing well know SSVEP detection methods. Results show that distinguishable SSVEP can be elicited by the focused stimulus regardless of the non-focused one is also present in the field of view. Finally, this approach allows users to send commands through a stimuli selection by focusing mechanism that does not demand neck, head, and/or eyeball movements.

Statistical evaluation of a novel SSVEP-BCI stimulation setup based on depth-of-field

Abstract Introduction The main drawback of a Brain-computer Interface based on Steady-State Visual Evoked Potential (SSVEP-BCI) that detects the emergence of visual evoked potentials (VEP) in reaction to flickering stimuli is its muscular dependence due to users must redirect their gaze to put the target stimulus in their field of view. In this work, a novel setup is evaluated in which two stimuli are placed together in the center of users' field of view, but with dissimilar distances from them, so that the target selection is performed by focus shifting instead of head, neck and/or eyeball movements. Methods A model of VEP generation for the novel setup was developed. The Spectral F-test based on Bartett periodogram was used to evaluate the null hypothesis of absence of effects of the non-focused stimulus (NFS) within the VEP elicited by the focused stimulus (FS). To reinforce that there is not statistical evidence to support the presence of NFS effects, the PSDA detection method was employed to find the frequency of FS. Electroencephalographic signals of nine subjects were recorded. Results Approximately in 80% of the tests, the null hypothesis with 5% level of significance was non-rejected at the fundamental frequency of NFS. The average of the accuracy rate attained with PSDA detection method was 79.4%. Conclusion Results of this work become further evident to state that if the focused stimulus (FS) will be able to elicit distinguishable VEP pattern regardless the non-focused stimulus (NFS) is also present.

Adaptive BCI based on software agents.

The selection of features is generally the most difficult field to model in BCIs. Therefore, time and effort are invested in individual feature selection prior to data set training. Another great difficulty regarding the model of the BCI topology is the brain signal variability between users. How should this topology be in order to implement a system that can be used by large number of users with an optimal set of features? The proposal presented in this paper allows for obtaining feature reduction and classifier selection based on software agents. The software agents contain Genetic Algorithms (GA) and a cost function. GA used entropy and mutual information to choose the number of features. For the classifier selection a cost function was defined. Success rate and Cohen's Kappa coefficient are used as parameters to evaluate the classifiers performance. The obtained results allow finding a topology represented as a neural model for an adaptive BCI, where the number of the channels, features and the classifier are interrelated. The minimal subset of features and the optimal classifier were obtained with the adaptive BCI. Only three EEG channels were needed to obtain a success rate of 93% for the BCI competition III data set IVa.

Prevalence and characterization of extended-spectrum beta-lactamases-producing Salmonella enterica isolates in Saragossa, Spain (2001-2008).

We analyzed the prevalence of resistance to extended-spectrum cephalosporins (ESCs) among clinical strains of Salmonella enterica collected by the Laboratory of Clinical Microbiology in the University Clinical Hospital Lozano Blesa in the region of Aragón (Spain), for which very few epidemiological information exists. A total of 2,092 strains of S. enterica were identified in stool samples from patients with gastroenteritis. Five isolates showed an extended-spectrum beta-lactamase (ESBL) phenotype: four isolates of S. enterica serotype Virchow harbored the ESBL-encoding bla(CTX-M-9) gene and an isolate of serotype Enteritidis carried a bla(CTX-M-1) gene, which, to the best of our knowledge, is described here for the first time in this serotype of S. enterica. The five ESC-resistant isolates were also resistant to spectinomycin, streptomycin, kanamycin, sulfonamides, tetracycline, and trimethoprim as well as to nalidixic acid. The ESBL isolate of serotype Enteritidis, however, remained susceptible to kanamycin and nalidixic acid. A class 1 integron of 1.5 kb was detected for the four serotype Virchow isolates with the gene cassette dfrA16-aadA2. The bla(CTX-M-9) gene was carried by an ∼300-kb IncHI2 conjugative plasmid in the case of the S. enterica serotype Virchow isolates. The bla(CTX-M-1) gene was carried by an ∼100-kb IncI1-N conjugative plasmid for the serotype Enteritidis ESC-resistant isolate. All the four ESC-resistant strains of S. enterica serotype Virchow clustered together in a XbaI pulsed-field gel electrophoresis, which also revealed a strong similarity between them and some pulsotypes of S. enterica serotype Virchow from France.