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Almost 9.9 million people develop dementia each year, the majority (63%) of whom reside in low- and middle-income countries. In Latin America, this represents a major burden for health systems and society, that directly impacts quality of life of those living with dementia, family members and caregivers. Therefore, in the absence of accessible pharmacological strategies for neurodegenerative disease, a renewed interest has emerged in non-pharmacological interventions, which enhance a more dignifying way of living. This encourages a shift towards solutions that are local and community-based, without requiring complex interventions of highly trained personnel. After many years of accumulated knowledge in the Montessori Model of Learning, researchers have adapted basic principles for people living with dementia. As a person-centered initiative, the intervention aims to promote independence, higher self-esteem, self-agency and an active involvement in society, while taking into account the unmet needs of neurodegeneration. This philosophy fosters a constructive and rewarding environment, which is especially valuable in long term care facilities and cases where patients may be experiencing reactive behaviors. We will provide an overview of the Montessori Approach for Dementia, focusing on easily implemented strategies and techniques.

•Low-frequency respiratory variations (RV) may be reconstructed from fMRI data alone.•Predicted and measured RV signals explained similar patterns of fMRI variance.•The approach is designed to work with fMRI scans of varying durations.•May enable reducing or studying RV effects in fMRI if respiration data is missing. Functional MRI signals can be heavily influenced by systemic physiological processes in addition to local neural activity. For example, widespread hemodynamic fluctuations across the brain have been found to correlate with natural, low-frequency variations in the depth and rate of breathing over time. Acquiring peripheral measures of respiration during fMRI scanning not only allows for modeling such effects in fMRI analysis, but also provides valuable information for interrogating brain-body physiology. However, physiological recordings are frequently unavailable or have insufficient quality. Here, we propose a computational technique for reconstructing continuous low-frequency respiration volume (RV) fluctuations from fMRI data alone. We evaluate the performance of this approach across different fMRI preprocessing strategies. Further, we demonstrate that the predicted RV signals can account for similar patterns of temporal variation in resting-state fMRI data compared to measured RV fluctuations. These findings indicate that fluctuations in respiration volume can be extracted from fMRI alone, in the common scenario of missing or corrupted respiration recordings. The results have implications for enriching a large volume of existing fMRI datasets through retrospective addition of respiratory variations information.

Resting-state functional magnetic resonance imaging (MRI) has yielded seemingly disparate insights into large-scale organization of the human brain. The brain’s large-scale organization can be divided into two broad categories: zero-lag representations of functional connectivity structure and time-lag representations of traveling wave or propagation structure. In this study, we sought to unify observed phenomena across these two categories in the form of three low-frequency spatiotemporal patterns composed of a mixture of standing and traveling wave dynamics. We showed that a range of empirical phenomena, including functional connectivity gradients, the task-positive/task-negative anti-correlation pattern, the global signal, time-lag propagation patterns, the quasiperiodic pattern and the functional connectome network structure, are manifestations of these three spatiotemporal patterns. These patterns account for much of the global spatial structure that underlies functional connectivity analyses and unifies phenomena in resting-state functional MRI previously thought distinct. The whole-brain organization of functional MRI signals has been studied in myriad ways. An in-depth study of these signals suggests a parsimonious description with a small number of spatiotemporal patterns.

The aim of the present study was to assess reproducibility and relative validity of a self-administered FFQ used in the PREDIMED Study, a clinical trial for primary prevention of CVD by Mediterranean diet in a population at high cardiovascular risk. The FFQ was administered twice (FFQ1 and FFQ2) to explore reproducibility at 1 year. Four 3 d dietary records (DR) were used as reference to explore validity; participants therefore recorded their food intake over 12 d in the course of 1 year. The degree of misclassification in the FFQ was also evaluated by a contingency table of quintiles comparing the information from the FFQ2 and the DR. A total of 158 men and women (aged 55–80 years) were asked not to modify their dietary habits during the study period. Reproducibility for food groups, energy and nutrient intake, explored by the Pearson correlation coefficient (r) ranged 0·50–0·82, and the intraclass correlation coefficient (ICC) ranged from 0·63 to 0·90. The FFQ2 tended to report higher energy and nutrient intake than the DR. The validity indices of the FFQ in relation to the DR for food groups and energy and nutrient intake ranged (r) from 0·24 to 0·72, while the range of the ICC was between 0·40 and 0·84. With regard to food groups, 68–83 % of individuals were in the same or adjacent quintile in both methods, a figure which decreased to 55–75 % for energy and nutrient intake. We concluded that FFQ measurements had good reproducibility and a relative validity similar to those of FFQ used in other prospective studies.

Introduction: Urbanization has increased the prevalence of asthma in lower- and middle-income countries. Severe eosinophilic asthma (SEA), a subtype of asthma, can be refractory to standard therapy. Biologics such as benralizumab target interleukin-5 and have demonstrated effectiveness in managing SEA. There exists no real-world evidence on the effectiveness of benralizumab in Mexico. Therefore, this study presents data on the role of benralizumab in managing SEA in Mexican patients. Objective: The effectiveness of benralizumab on the quality of life (QoL), asthma control, lung function, symptoms of asthma, and benralizumab’s safety profile were assessed. Methods: The study sample comprised 10 patients with SEA treated with a subcutaneous (SC) administration of benralizumab 30 mg once in 4 weeks for the first three doses followed by a dose every 8 weeks for 2 years. Laboratory tests, resting spirometry, and skin prick tests were conducted. Levels of fractional exhaled nitric oxide (FeNO) were evaluated, when possible, with the intent to phenotype asthma, as T2 high or non-T2, before starting benralizumab therapy. The Asthma Quality of Life Questionnaire (AQLQ), Asthma Control Questionnaire (ACQ), and Asthma Control Test (ACT) were administered to evaluate the effectiveness of benralizumab on asthma control and QoL. Results: All patients showed significant symptom control, QoL, and lung function over 2 years. Mild adverse effects, such as headache and arthralgia, were observed. Conclusion: Benralizumab appears to be a promising agent in controlling SEA. This study has focused on measuring tangible outcomes, such as a reduction in symptoms, a reduction in exacerbation, and an improvement in QoL. Thus, benralizumab may constitute an important addition to the arsenal of medications against SEA.

The Solvency II Directive, in its standard formula, proposes that a permanent 15% increase should be applied to mortality rates for covering normal deviations of mortality and that the rates should be increased uniformly over just the following year by 1.5‰ to cover catastrophic mortality deviations. The latter increase means disproportionally raising the rates for some ages, especially young people, with hardly any modification for others. In this paper we show, using data from Spain, the inadequacy of these loadings and this timing (for 1 year only) in protecting against a pandemic. As a solution, we propose a new methodology that allows the catastrophic risk of life to be modelled/calibrated through two parameters: a parameter to mainly cover catastrophic risks linked to specific extreme disasters (such as earthquakes, hurricanes or nuclear explosions) and another parameter to mainly cover catastrophic risks linked to pandemics. After establishing the relationships between these parameters in three different scenarios where the aggregate levels of risk/mortality associated with the Solvency II catastrophic shock are kept constant, we study its effect in terms of Solvency Capital Requirements (SCR) on a real life insurance portfolio. The results obtained show that the new methodology leads to SCRs, over total BEL, less dependent on the age structure of the portfolio.

Brushed DC motors and generators (DCMs) are extensively used in various industrial applications, including the automotive industry, where they are critical for electric vehicles (EVs) due to their high torque, power, and efficiency. Despite their advantages, DCMs are prone to premature failure due to sparking between brushes and commutators, which can lead to significant economic losses. This study proposes two approaches for determining the temporal and frequency evolution of Shannon entropy in armature current and stray flux signals. One approach indirectly achieves this through prior analysis using the Short-Time Fourier Transform (STFT), while the other applies the Stockwell Transform (S-Transform) directly. Experimental results show that increased sparking activity generates significant low-frequency harmonics, which are more pronounced compared to mid and high-frequency ranges, leading to a substantial rise in system entropy. This finding enables the introduction of fault-severity indicators or Key Performance Indicators (KPIs) that relate the current condition of commutation quality to a baseline established under healthy conditions. The proposed technique can be used as a predictive maintenance tool to detect and assess sparking phenomena in DCMs, providing early warnings of component failure and performance degradation, thereby enhancing the reliability and availability of these machines.

Next-Generation Sequencing (NGS) is widely used to investigate genomic variation. In several studies, the genetic variation of Mycobacterium tuberculosis has been analyzed in sputum samples without previous culture, using target enrichment methodologies for NGS. Alignments obtained by different programs generally map the sequences under default parameters, and from these results, it is assumed that only Mycobacterium reads will be obtained. However, variants of interest microorganism in clinical samples can be confused with a vast collection of reads from other bacteria, viruses, and human DNA. Currently, there are no standardized pipelines, and the cleaning success is never verified since there is a lack of rigorous controls to identify and remove reads from other sputum - microorganisms genetically similar to M . tuberculosis . Therefore, we designed a bioinformatic pipeline to process NGS data from sputum samples, including several filters and quality control points to identify and eliminate non- M . tuberculosis reads to obtain a reliable genetic variant report. Our proposal uses the SURPI software as a taxonomic classifier to filter input sequences and perform a mapping that provides the highest percentage of Mycobacterium reads, minimizing the reads from other microorganisms. We then use the filtered sequences to perform variant calling with the GATK software, ensuring the mapping quality, realignment, recalibration, hard-filtering, and post-filter to increase the reliability of the reported variants. Using default mapping parameters, we identified reads of contaminant bacteria, such as Streptococcus , Rhotia , Actinomyces , and Veillonella . Our final mapping strategy allowed a sequence identity of 97.8% between the input reads and the whole M . tuberculosis reference genome H37Rv using a genomic edit distance of three, thus removing 98.8% of the off-target sequences with a Mycobacterium reads loss of 1.7%. Finally, more than 200 unreliable genetic variants were removed during the variant calling, increasing the report’s reliability.

Diastasis recti abdominis (DRA) is a common postpartum condition characterized by separation of the rectus abdominis muscles along the linea alba (LA). This condition can lead to significant physical and functional impairment. Conventional physiotherapy interventions, such as targeted abdominal exercises, have been reported to be effective in improving abdominal function. However, the transcutaneous radiofrequency diathermy (TRD) in the treatment of DRA has not yet been explored in this pathology. This case study reports on the treatment of a 29-year-old woman with a severe supraumbilical DRA (6.5 cm at rest) following a twin pregnancy. The intervention combined conventional physiotherapy and TRD over 13 weeks. The therapeutic exercise program included hypopressive exercises and targeted abdominal muscle strengthening, while the TRD aimed to enhance tissue regeneration and reduce the intra-rectus distance (IRD). The outcomes were the IRD, the distortion index (DI), the involuntary pre-activation of transversus abdominis, and the Physical Function Scale (PF-10). A significant reduction in the IRD was observed after eight weeks of physiotherapy, at rest (-38%), supraumbilical contraction (-33%) and infraumbilical contraction (-38%). At the end of the TRD intervention, the IRD at rest decreased from 6.5 cm to 2.1 cm (-47.5%), supraumbilical contraction (-64%) and infraumbilical contraction (-64.25%). The distortion index of the LA improved by 50%. Additionally, the patient's physical function, measured using the PF-10 scale, clinically improved. This case study suggests that conservative physiotherapy based on therapeutic exercises and TRD may be an effective treatment for DRA, especially in severe cases following twin pregnancies. However, larger studies are needed to confirm these findings and to establish TRD as a standard adjunctive therapy in the management of DRA.

The Cognitive Function Index (CFI) was developed to identify individuals with Subjective Cognitive Decline (SCD), which is defined by the self-perception of cognitive impairment, not detected in neuropsychological tests. Limited research has been done with this tool in Latin America (LA). We aimed to investigate the association between CFI and global cognition and to investigate whether CFI scores can identify participants with cognitive performance below 1.0 standard deviation (SD) of the sample mean. The LatAm-FINGERS study is a dementia prevention feasibility study in 12 LA countries. For the present analysis, 815 participants with complete cognitive data (604 women, 74.1%; 436 mestizo 53.5%; mean age=67.5, SD=4.8; mean education = 13.0, SD=3.6; mean GDS=2.7, SD=2.8) were included. The CFI is a 14-item self-report measure of cognitive change; higher scores indicate higher concerns. CFI total score was normalized into a z-score, as some questions were not applicable to all participants and total score differed among them. Cognition was assessed with the Preclinical Alzheimer Cognitive Composite (PACC-5) - Mini-Mental State Examination; Logical Memory Delayed Recall; Free and Cued Selective Reminding Test; Digit Symbol Substitution Test; and Animal Category Fluency. Participants were classified into those with PACC-5 at or above 1 SD from the mean (n = 764) and those below (n = 51). Bivariate and partial correlations (controlling for sex, age, education and GDS score) were used to assess the association between the CFI and PACC-5 scores. Receiver operating characteristic (ROC) analyses were used to assess CFI accuracy to identify participants with PACC-5 scores below 1 SD. CFI and PACC-5 scores were negatively associated with each other (r =  -0.27; p <0.001; partial r = -0.12; p <0.001). ROC analyses indicated an area under the curve (AUC) of 0.71 (sensitivity=0.64; specificity=0.70) with an optimal threshold of 0.36 (Youden Index=0.35) as a suggested cutoff score for the normalized CFI score. The CFI may be added to cognitive screening protocols to identify individuals who may need further assessment. Integrating the CFI into screening strategies in LA could play a pivotal role in reducing cognitive health disparities and advancing tailored dementia prevention initiatives that address the region's specific sociocultural and healthcare challenges.