Multistable inflatable origami structures at the metre scale.

From stadium covers to solar sails, we rely on deployability for the design of large-scale structures that can quickly compress to a fraction of their size1-4. Historically, two main strategies have been used to design deployable systems. The first and most frequently used approach involves mechanisms comprising interconnected bar elements, which can synchronously expand and retract5-7, occasionally locking in place through bistable elements8,9. The second strategy makes use of inflatable membranes that morph into target shapes by means of a single pressure input10-12. Neither strategy, however, can be readily used to provide an enclosed domain that is able to lock in place after deployment: the integration of a protective covering in linkage-based constructions is challenging and pneumatic systems require a constant applied pressure to keep their expanded shape13-15. Here we draw inspiration from origami-the Japanese art of paper folding-to design rigid-walled deployable structures that are multistable and inflatable. Guided by geometric analyses and experiments, we create a library of bistable origami shapes that can be deployed through a single fluidic pressure input. We then combine these units to build functional structures at the metre scale, such as arches and emergency shelters, providing a direct route for building large-scale inflatable systems that lock in place after deployment and offer a robust enclosure through their stiff faces.

Systematic Review of Literature on Vocal Demand Response: Understanding Physiology, Measurements, and Associated Factors.

PURPOSE: Considering the conceptual migration from vocal load and vocal loading to vocal demand and vocal demand response, this review of literature aimed to identify physiological explanations, reported measurements, and associated factors (vocal demands) reported in the literature when considering the phonatory response to a vocal demand. METHODS: A systematic review of literature, following the PRISMA Statement, was conducted using Web of Science, PubMed, Scopus, and ScienceDirect. Data were analyzed and presented in two parts. First, a bibliometric analysis, co-occurrence analysis, and content analysis were performed. Three criteria that got article inclusion were defined: (1) written in English, Spanish, and Portuguese; (2) published between 2009 and 2021; and (3) focused on vocal load and loading, vocal demand response, and voice assessment parameters. A total of 54 publications met the criteria and were included in this review. The second part included a conceptual framework based on the content analysis of three aspects of vocal demand response: (1) physiological explanations, (2) reported measurements, and (3) vocal demands. RESULTS AND CONCLUSION: As would be expected since vocal demand response is a relatively new term and not yet commonly used in literature when discussing way that the speakers respond to communicative scenarios, most of the studies reviewed (both historical and recent) still use the term of vocal load and vocal loading. Although there is a broad variety of literature discussing a wide range of vocal demands and voice parameters used to characterize the vocal demand response, results show that there is consistency across the studies. While vocal demand response is unique and intrinsic to the talker, associated factors that contribute to this response include both internal talker and external talker factors. Internal factors include muscle stiffness, viscosity in the phonatory system, vocal fold tissue damage, elevated sound pressure levels during occupational voice demands, extended periods of voice use, suboptimal body posture, difficulties in breathing technique, and sleep disturbances. Associated external factors include the working environment (noise, acoustics, temperature, humidity). In conclusion, although vocal demand response is intrinsic to the speaker, the speaker's response is affected by external vocal demands. However, due to the wide methods to evaluate vocal demand response, it has been difficult to establish its contribution to voice disorders in the general population and, specifically, among occupational voice users. This literature review identified commonly reported parameters and factors that may help clinicians and researchers define vocal demand response.

Detection of magnetic iron nanoparticles by single-particle ICP-TOFMS: case study for a magnetic filtration medical device.

Nanoparticles are increasingly used in medical products and devices. Their properties are critical for such applications, as particle characteristics determine their interaction with the biological system, and, therefore, the performance and safety of the final product. Among the most important nanoparticle characteristics and parameters are particle mass distribution, composition, total particle mass, and number concentration. In this study, we utilize single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS) for the characterization of inorganic nanoparticles in complex biological fluids. We report online microdroplet calibration for reference-nanomaterial-free and matrix-matched calibration of carbon-coated iron carbide nanoparticles (C/Fe3C NPs). As a case study, we analyze C/Fe3C NPs designed for targeted blood purification. Through the analysis of NP mass distributions, we study the effect of the NP surface modification on aggregation of C/Fe3C NPs in whole blood. We also demonstrate the efficiency of removal of coated C/Fe3C NP from saline by magnetically enhanced filters. Magnetic filtering is shown to reduce the mass concentration of detectable C/Fe3C NPs by 99.99 ± 0.01% in water.

Relationship of the drying process of a corn grain with the thermal emissivity and optical interference in the mid infrared range.

A study of the effect of the thin layer of free water in corn kernels on the emissivity and interference in the mid infrared range was performed. The emissivity was measured through thermal infrared images by direct method for 8 days, allowing observance that the thickness of free water modifies the quantity of emitted energy and emissivity; however, in the first days when the layer of free water is not optically thick the interference caused by the thin film of superficial water averts a correct measurement of the emissivity. This interference effect was studied and characterized, finding that the number of oscillations in the energy of the grain, observed and counted in a very small area, can be used to compute the thickness of the free water layer contained between the endosperm and the pericarp of the grain.

Antioxidant, cytotoxic and alpha-glucosidase inhibition activities from the Mexican berry "Anacahuita" (Cordia boissieri).

This study describes the total phenolic and flavonoid content as well as cytotoxic, alpha-glucosidase inhibition and antiradical/antioxidant potential of extracts obtained from the edible fruits of Cordia boissieri, which is widely distributed throughout northeastern Mexico. Phenolic and flavonoid content were evaluated by means of the Folin-Ciocalteu method and aluminum chloride colorimetric assay respectively. The antiradical/antioxidant activity was determined by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging and Trolox Equivalent Antioxidant Capacity (TEAC) assays. Cytotoxic activity was assessed by means of human cancer cell lines (MCF-7 and HeLa), alpha-glucosidase inhibition was determined by colorimetric assay using p-Nitrophenyl a-D-glucopyranoside (PNPG) as a substrate. Results indicate that extract of C. boissieri fruit has a good antioxidant potential to show a EC50: 137.76 ± 35 ptg/mL and 65 ±2 ltM/g in the DPPH and TEAC assays respectively, inhibitor of the enzyme alpha-glu- cosidase involved in sugar uptake (ICSO: 215.20 ± 35 µg/ mL), cytotoxic activities against MCF-7 (IC50: 310 ± 42 µg/mL) and HeLa (IC500: 450.4 ±21µgg/mL) cancer cell lines as well as an important phenolic content with 230 t 23 mg/1OOg and 54±11 mg100g g of phenols and flavonoids totals respectively. These results point towards an interesting potential for the fruits of C. boissieri as chemopreventive properties and expand the possibilities.

Hollow Carbon Nanobubbles: Synthesis, Chemical Functionalization, and Container-Type Behavior in Water.

Thin-walled, hollow carbon nanospheres with a hydrophobic interior and good water dispersability can be synthesized in two steps: First, metal nanoparticles, coated with a few layers of graphene-like carbon, are selectively modified on the outside with a covalently attached hydrophilic polymer. Second, the metal core is removed at elevated temperature treatment with acid, leaving a well-defined carbon-based hydrophobic cavity. Loading experiments with the dye rhodamine B and doxorubicin confirmed the filling and release of a cargo and adjustment of a dynamic equilibrium (cargo-loaded versus release). Rhodamine B preferably accumulates in the interior of the bubbles. Filled nanobubbles allowed constant dye release into pure water. Studies of the concentration-dependent loading and release show an unusual hysteresis.

DarwinGSE: Towards better image retrieval systems for intellectual property datasets.

A trademark's image is usually the first type of indirect contact between a consumer and a product or a service. Companies rely on graphical trademarks as a symbol of quality and instant recognition, seeking to protect them from copyright infringements. A popular defense mechanism is graphical searching, where an image is compared to a large database to find potential conflicts with similar trademarks. Despite not being a new subject, image retrieval state-of-the-art lacks reliable solutions in the Industrial Property (IP) sector, where datasets are practically unrestricted in content, with abstract images for which modeling human perception is a challenging task. Existing Content-based Image Retrieval (CBIR) systems still present several problems, particularly in terms of efficiency and reliability. In this paper, we propose a new CBIR system that overcomes these major limitations. It follows a modular methodology, composed of a set of individual components tasked with the retrieval, maintenance and gradual optimization of trademark image searching, working on large-scale, unlabeled datasets. Its generalization capacity is achieved using multiple feature descriptions, weighted separately, and combined to represent a single similarity score. Images are evaluated for general features, edge maps, and regions of interest, using a method based on Watershedding K-Means segments. We propose an image recovery process that relies on a new similarity measure between all feature descriptions. New trademark images are added every day to ensure up-to-date results. The proposed system showcases a timely retrieval speed, with 95% of searches having a 10 second presentation speed and a mean average precision of 93.7%, supporting its applicability to real-word IP protection scenarios.

Developments in Image Processing Using Deep Learning and Reinforcement Learning.

The growth in the volume of data generated, consumed, and stored, which is estimated to exceed 180 zettabytes in 2025, represents a major challenge both for organizations and for society in general. In addition to being larger, datasets are increasingly complex, bringing new theoretical and computational challenges. Alongside this evolution, data science tools have exploded in popularity over the past two decades due to their myriad of applications when dealing with complex data, their high accuracy, flexible customization, and excellent adaptability. When it comes to images, data analysis presents additional challenges because as the quality of an image increases, which is desirable, so does the volume of data to be processed. Although classic machine learning (ML) techniques are still widely used in different research fields and industries, there has been great interest from the scientific community in the development of new artificial intelligence (AI) techniques. The resurgence of neural networks has boosted remarkable advances in areas such as the understanding and processing of images. In this study, we conducted a comprehensive survey regarding advances in AI design and the optimization solutions proposed to deal with image processing challenges. Despite the good results that have been achieved, there are still many challenges to face in this field of study. In this work, we discuss the main and more recent improvements, applications, and developments when targeting image processing applications, and we propose future research directions in this field of constant and fast evolution.

Robotic pelvic exenteration in males: systematization of the technique.

Male pelvic exenteration is a challenging procedure with high morbidity. In very selected cases, the robotic approach could make dissection easier and decrease morbidity due to the better vision provided and higher range of movements. In this paper, we describe port placement, instruments, minilaparotomy location, and the stepwise sequence of these procedures. We address 3 different situations: total pelvic exenteration with abdominoperineal resection, colostomy and urostomy; pelvic exenteration with colorectal/anal anastomosis and urostomy; and pelvic exenteration with abdominoperineal resection, colostomy and urinary tract reconstruction.

Association Between Bilingualism, Vocal Effort, and Background Noise With Voice Fundamental Frequency and LTAS Among Spanish-English Bilingual Teachers.

BACKGROUND: As the world becomes increasingly interconnected, the demand for bilingual teachers has grown exponentially. However, the unique combination of being a bilingual occupational voice user establishes challenges that warrant careful examination. OBJECTIVE: To investigate the association between bilingualism, vocal effort, and background noise with fundamental frequency and long-term spectrum average among Spanish-English bilingual teachers. METHODS: Exploratory cross-sectional correlational study with the participation of eight Spanish-English proficient bilingual teachers (native Spanish speakers) who were teaching online classes during the quarantines established to mitigate the propagation of COVID-19. Participants were asked to read two standardized texts (one in English and one in Spanish) under two background noise conditions (with and without background white noise). RESULTS: There was a significant interaction between language and vocal effort considering that the association of vocal effort with fo was different for Spanish and English. There was also a significant main effect of background noise on fo. There were significant differences in voice spectral characteristics between productions in Spanish and English and between productions with and without background noise. The alpha ratio was significantly higher in productions in English and with background noise compared with productions in Spanish without background noise. The mid to high spectral energy ratio (1-5 K/5-8 K) was significantly lower in productions in English and with higher perceived vocal effort compared with productions in Spanish and with lower scores on the Borg Scale. CONCLUSION: Our findings introduce a need perspective by emphasizing the impact of speaking a second language on the work-relatedness of voice disorders among teachers. These findings stress the necessity to factor in language and environmental conditions for the comprehensive evaluation and management of work-related voice disorders.

A Novel Trademark Image Retrieval System Based on Multi-Feature Extraction and Deep Networks.

Graphical Search Engines are conceptually used in many development areas surrounding information retrieval systems that aim to provide a visual representation of results, typically associated with retrieving images relevant to one or more input images. Since the 1990s, efforts have been made to improve the result quality, be it through improved processing speeds or more efficient graphical processing techniques that generate accurate representations of images for comparison. While many systems achieve timely results by combining high-level features, they still struggle when dealing with large datasets and abstract images. Image datasets regarding industrial property are an example of an hurdle for typical image retrieval systems where the dimensions and characteristics of images make adequate comparison a difficult task. In this paper, we introduce an image retrieval system based on a multi-phase implementation of different deep learning and image processing techniques, designed to deliver highly accurate results regardless of dataset complexity and size. The proposed approach uses image signatures to provide a near exact representation of an image, with abstraction levels that allow the comparison with other signatures as a means to achieve a fully capable image comparison process. To overcome performance disadvantages related to multiple image searches due to the high complexity of image signatures, the proposed system incorporates a parallel processing block responsible for dealing with multi-image search scenarios. The system achieves the image retrieval through the use of a new similarity compound formula that accounts for all components of an image signature. The results shows that the developed approach performs image retrieval with high accuracy, showing that combining multiple image assets allows for more accurate comparisons across a broad spectrum of image typologies. The use of deep convolutional networks for feature extraction as a means of semantically describing more commonly encountered objects allows for the system to perform research with a degree of abstraction.

Graphical Image Region Extraction with K-Means Clustering and Watershed.

With a wide range of applications, image segmentation is a complex and difficult preprocessing step that plays an important role in automatic visual systems, which accuracy impacts, not only on segmentation results, but directly affects the effectiveness of the follow-up tasks. Despite the many advances achieved in the last decades, image segmentation remains a challenging problem, particularly, the segmenting of color images due to the diverse inhomogeneities of color, textures and shapes present in the descriptive features of the images. In trademark graphic images segmentation, beyond these difficulties, we must also take into account the high noise and low resolution, which are often present. Trademark graphic images can also be very heterogeneous with regard to the elements that make them up, which can be overlapping and with varying lighting conditions. Due to the immense variation encountered in corporate logos and trademark graphic images, it is often difficult to select a single method for extracting relevant image regions in a way that produces satisfactory results. Many of the hybrid approaches that integrate the Watershed and K-Means algorithms involve processing very high quality and visually similar images, such as medical images, meaning that either approach can be tweaked to work on images that follow a certain pattern. Trademark images are totally different from each other and are usually fully colored. Our system solves this difficulty given it is a generalized implementation designed to work in most scenarios, through the use of customizable parameters and completely unbiased for an image type. In this paper, we propose a hybrid approach to Image Region Extraction that focuses on automated region proposal and segmentation techniques. In particular, we analyze popular techniques such as K-Means Clustering and Watershedding and their effectiveness when deployed in a hybrid environment to be applied to a highly variable dataset. The proposed system consists of a multi-stage algorithm that takes as input an RGB image and produces multiple outputs, corresponding to the extracted regions. After preprocessing steps, a K-Means function with random initial centroids and a user-defined value for k is executed over the RGB image, generating a gray-scale segmented image, to which a threshold method is applied to generate a binary mask, containing the necessary information to generate a distance map. Then, the Watershed function is performed over the distance map, using the markers defined by the Connected Component Analysis function that labels regions on 8-way pixel connectivity, ensuring that all regions are correctly found. Finally, individual objects are labelled for extraction through a contour method, based on border following. The achieved results show adequate region extraction capabilities when processing graphical images from different datasets, where the system correctly distinguishes the most relevant visual elements of images with minimal tweaking.

Comparison of Diabetes Mellitus Risk Factors in Mexico in 2003 and 2014.

Objective: The prevalence of diabetes mellitus in Mexico is very high. This study aimed to compare the risk factors of diabetes mellitus in Mexican adults in 2003 and in 2014. Methods: This study had a repeated cross-sectional design. Data from the World Health Organization (WHO) Study on global AGEing and adult health (SAGE) from Mexico (Wave 0, 2003, and Wave 2, 2014) were compared. Self-reported diabetes mellitus (outcome) was evaluated with the yes/no question: "Have you ever been diagnosed with diabetes mellitus (high blood sugar)?" Bivariate analyses and multivariable logistic regression analyses adjusted for potential risk factors were conducted. Results: In 11 years (2003-2014), the prevalence of self-reported diabetes mellitus in Mexican adults increased by 2.6 times in those younger than 50 years (2003: 2.1%; 2014: 5.5%) and by 1.9 times in those ≥50 years (2003: 12.7%; 2014: 24.2%). In 2003, the risk factors associated with diabetes mellitus were female sex (OR 1.344, 95% CI 1.176-1.536), age ≥50 years (OR 6.734, 95% CI 5.843-7.760), being overweight (OR 1.359, 95% CI 1.175-1.571), obesity (OR 1.871, 95% CI 1.583-2.211), and lower physical activity of <600 MET-minutes/week (OR 1.349, 95% CI 1.117-1.630). In 2014, the exposure characteristics significantly associated with diabetes mellitus were female sex (OR 1.244, 95% CI 1.025-1.511), older age ≥50 years (OR 4.608, 95% CI 3.260-6.515), being overweight (OR 1.649, 95% CI 1.305-2.083), obesity (OR 1.778, 95% CI 1.398-2.261), and in those who had not attended/completed primary school (OR 1.360, 95% CI 1.042-1.773). Conclusion: The prevalence of diabetes mellitus in Mexico significantly increased from 2003 to 2014. Female sex, age older than 50 years, and being overweight or obese were significant risk factors in both 2003 and 2014. Not having completed primary school was a new significant risk factor in 2014. Public health policies and strategies should prioritize decreasing the high levels of overweight and obesity, and improve health literacy in Mexico.

Outcomes of laparoscopic salvage radical prostatectomy after primary treatment of prostate cancer.

Introduction: Treatment of radio-recurrent prostate cancer (PC) is managed mainly by androgen deprivation therapy. Nonetheless, selected patients could benefit from local salvage treatment options.In this study we present our series of recurrent PC cases submitted to laparoscopic salvage radical prostatectomy (sRP) at our institution. Material and methods: A total of 29 patients with recurrent PC after primary non-surgical treatment were submitted to laparoscopic sRP at our institution, with a mean follow-up time of 7 years. Results: There were 7 post-operative complications Clavien-Dindo grade ≥2. At the end of the follow-up, 58.6% patients presented biochemical recurrence and five-year recurrence-free survival (RFS) was 50%.Positive lymph nodes, high preoperative prostate-specific antigen (PSA) and TNM stage were correlated with worse RFS. Cox regression analysis demonstrated that stage pT3b was independently associated with worse RFS in comparison with stage pT3a or less.At 12 months, pad-free continence or mild incontinence was observed in 62% of the patients. Conclusions: sRP is a technically challenging surgery, and in our series, we were able to perform this procedure with acceptable operative time and limited blood loss.Post-operative complications, functional results and oncological outcomes were similar to other published studies, being our series, to the best of our knowledge, the one with the longest follow-up, of 7 years.sRP is a feasible local treatment with curative intent for radio-recurrent prostate cancer, with good oncological outcomes and reasonable continence rates in selected patients.

Flu Vaccination Coverage and Predictors of Non-Vaccination in Military Health Corps Personnel 2016-2017 and 2019-2021.

(1) Background: Vaccination is the most effective intervention to control seasonal influenza morbidity and mortality. The present study aimed to determine the influenza vaccination coverage in the Military Health Corps personnel in the 2020−2021 season, as well as the time trend and the possible influence of the pandemic on coverage, in order to study the reasons that led to the non-vaccination of health professionals and to analyze adverse drug reactions (ADRs). (2) Methods: A descriptive, cross-sectional study was conducted from February to May 2021. All FAS CMS personnel were included. A self-administered questionnaire was sent by e-mail to the selected personnel. (3) Results: Vaccination coverage in the 2016−2017 season was 15.8% (n = 276), in the 2019−2020 season it was 17.41% (n = 424), and in the 2020−2021 season it was 24.22% (n = 590). The percentage of vaccinated men was higher than the percentage of women. In 2019 and 2020 the most vaccinated group was 31−40 years old. Lieutenants had the highest vaccination uptake in 2019 and 2020. The personnel with the highest uptake of vaccines were those in the specialty of nursing in each of 2016, 2019 and 2020, with >30 years of time worked in 2016. In terms of factors leading to refusal of vaccination, the most reported was "not considered a risk group" (23.0%), and the least reported was "avoidance of vaccine administration" (2.2%). Eighty individuals presented adverse reactions after vaccine administration (9.6%). (4) Conclusions: The rate of influenza vaccination among healthcare professionals was lower during the 2020 season compared to the previous season, but was expected to increase in the upcoming 2021 season.

Using the Khorana risk score to predict venous thromboembolism and overall survival in a cohort of Hispanic patients with solid malignancies.

Background: The Khorana risk score (KRS) for prognosis of venous thromboembolism (VTE) has been rarely explored in Hispanic populations. Objective: To determine the value of the KRS for prediction of VTE and overall survival (OS) among Hispanic individuals with cancer. Methods: We retrospectively evaluated all outpatients with newly diagnosed solid tumours receiving systemic chemotherapy in Hospital San Juan Dios, San José, Costa Rica, from January to December 2021. The 6-month cumulative VTE incidence according to the KRS categories was estimated using the Fine & Gray competing risk model. A Kaplan-Meier analysis was used to compare OS among KRS categories. The Cox regression analysis was performed to calculate the hazard ratio (HR) and its corresponding 95% confidence interval (CI). The receiver operating characteristic (ROC) analysis was performed to identify the optimal cutoff value to predict VTE during follow-up. Results: A total of 708 patients were included in the analysis. After a median follow-up of 8.13 months, the cumulative incidence of VTE at 6 months was 1.56% (95% CI: 0.83%-6.82%), 4.83% (95% CI: 2.81%-7.66%) and 8.84% (95% CI: 4.30%-15.42%) for low-, intermediate- and high-risk Khorana score categories, respectively (Gray's p value: 0.0178). The optimal cutoff for the KRS to predict VTE was 2 (area under the ROC curve: 0.65; 95% CI: 0.55-0.756). The KRS was independently associated with overall mortality (HR: 1.83; 95% CI: 1.46-2.29; p < 0.001, for the comparison of 'high-risk' and 'low-risk' KRS). Conclusions: The KRS is a valid tool to predict VTE and mortality in a cohort of Hispanic outpatients with newly diagnosed solid tumours.

COVID-19 Long-Term Effects: Is There an Impact on the Simple Reaction Time and Alternative-Forced Choice on Recovered Patients?

A comparative single-evaluation cross-sectional study was performed to evaluate cognitive damage in post-COVID-19 patients. The psychophysics tests of Two-Alternative Forced Choice (2AFC) and Simple Reaction Time (SRT), under a designed virtual environment, were used to evaluate the cognitive processes of decision-making, visual attention, and information processing speed. The population under study consisted of 147 individuals, 38 controls, and 109 post-COVID patients. During the 2AFC test, an Emotiv EPOC+® headset was used to obtain EEG signals to evaluate their Focus, Interest, and Engagement metrics. Results indicate that compared to healthy patients or recovered patients from mild-moderate COVID-19 infection, patients who recovered from a severe-critical COVID infection showed a poor performance in different cognitive tests: decision-making tasks required higher visual sensitivity (p = 0.002), Focus (p = 0.01) and information processing speed (p < 0.001). These results signal that the damage caused by the coronavirus on the central nervous and visual systems significantly reduces the cognitive processes capabilities, resulting in a prevalent deficit of 42.42% in information processing speed for mild-moderate cases, 46.15% for decision-making based on visual sensitivity, and 62.16% in information processing speed for severe-critical cases. A psychological follow-up for patients recovering from COVID-19 is recommended based on our findings.

[Laparoscopic extraperitoneal prostatic adenomectomy: description of the surgical technique]. / Adenomectomía extraperitoneal laparoscópica: descripción de la técnica quirúrgica.

Historically, the surgical treatment of benign prostatic hyperplasia (BPH)in glands with volumes over 75-80 grams was performed using the conventional surgical approaches described by Terence Millin and Peter Freyer. Due to technological advancement over the past three decades, at present, minimally invasive techniques are being used with good results in the treatment of BPH. The incorporation of the laparoscopic approach to urologic surgery has allowed the technical development of adenomectomy using the same guidelines followed by conventional approaches. The aim of this paper is to describe in detail, step by step, the surgical technique of laparoscopic prostatectomy to treat BPH in glands larger than 60 cc., and to perform a retrospective analysis of preliminary results obtained in the immediate postoperative period of our initial series.

Continued dysregulation of the B cell lineage promotes multiple sclerosis activity despite disease modifying therapies.

A clear understanding of the origin and role of the different subtypes of the B cell lineage involved in the activity or remission of multiple sclerosis (MS) is important for the treatment and follow-up of patients living with this disease. B cells, however, are dynamic and can play an anti-inflammatory or pro-inflammatory role, depending on their milieu. Depletion of B cells has been effective in controlling the progression of MS, but it can have adverse side effects. A better understanding of the role of the B cell subtypes, through the use of surface biomarkers of cellular activity with special attention to the function of memory and other regulatory B cells (Bregs), will be necessary in order to offer specific treatments without inducing undesirable effects.