Epidemiological, immunological, and treatment response profile of patients with lupus nephritis in Brazil.

BACKGROUND AND HYPOTHESIS: Brazil has the largest number of individuals of African descent outside Africa and a very admixed population. Among cases of lupus nephritis (LN) in the country, there are differences in incidence, and even in severity, depending on the location and characteristics of the population studied. The aim of this study was to describe the clinical and epidemiological characteristics of LN in Brazil, as well as to determine which of those characteristics would be risk factors for a poor renal prognosis. METHODS: This was a retrospective, descriptive observational study of patients diagnosed with LN who underwent kidney biopsy between 1999 and 2015 in the Nephrology Department of the Hospital das Clínicas, in São Paulo, Brazil. Data were collected from electronic medical records. RESULTS: We evaluated 398 patients, among who 94.1% and 77.7% tested positive for antinuclear antibodies and anti-DNA antibodies, respectively, whereas 33.7% showed the full-house pattern. The time from LN symptom onset to biopsy was <6 months in 47.5% (early biopsy group) and ≥6 months in 52.5% (late biopsy group). In the early biopsy group, the chronicity index was lower and the activity index was higher. Multivariate analysis showed that a higher chronicity index was the only independent risk factor for progression to requiring kidney replacement therapy. CONCLUSION: Late biopsy seems to be associated with negative renal outcomes in LN. However, it seems that a higher chronicity index is the main predictor of a poor renal outcome among patients with LN in Brazil.

Data Science Methods and Tools for Industry 4.0: A Systematic Literature Review and Taxonomy.

The Fourth Industrial Revolution, also named Industry 4.0, is leveraging several modern computing fields. Industry 4.0 comprises automated tasks in manufacturing facilities, which generate massive quantities of data through sensors. These data contribute to the interpretation of industrial operations in favor of managerial and technical decision-making. Data science supports this interpretation due to extensive technological artifacts, particularly data processing methods and software tools. In this regard, the present article proposes a systematic literature review of these methods and tools employed in distinct industrial segments, considering an investigation of different time series levels and data quality. The systematic methodology initially approached the filtering of 10,456 articles from five academic databases, 103 being selected for the corpus. Thereby, the study answered three general, two focused, and two statistical research questions to shape the findings. As a result, this research found 16 industrial segments, 168 data science methods, and 95 software tools explored by studies from the literature. Furthermore, the research highlighted the employment of diverse neural network subvariations and missing details in the data composition. Finally, this article organized these results in a taxonomic approach to synthesize a state-of-the-art representation and visualization, favoring future research studies in the field.

Imbalanced data preprocessing techniques for machine learning: a systematic mapping study.

Machine Learning (ML) algorithms have been increasingly replacing people in several application domains-in which the majority suffer from data imbalance. In order to solve this problem, published studies implement data preprocessing techniques, cost-sensitive and ensemble learning. These solutions reduce the naturally occurring bias towards the majority sample through ML. This study uses a systematic mapping methodology to assess 9927 papers related to sampling techniques for ML in imbalanced data applications from 7 digital libraries. A filtering process selected 35 representative papers from various domains, such as health, finance, and engineering. As a result of a thorough quantitative analysis of these papers, this study proposes two taxonomies-illustrating sampling techniques and ML models. The results indicate that oversampling and classical ML are the most common preprocessing techniques and models, respectively. However, solutions with neural networks and ensemble ML models have the best performance-with potentially better results through hybrid sampling techniques. Finally, none of the 35 works apply simulation-based synthetic oversampling, indicating a path for future preprocessing solutions.

IndoorPlant: A Model for Intelligent Services in Indoor Agriculture Based on Context Histories.

The application of ubiquitous computing has increased in recent years, especially due to the development of technologies such as mobile computing, more accurate sensors, and specific protocols for the Internet of Things (IoT). One of the trends in this area of research is the use of context awareness. In agriculture, the context involves the environment, for example, the conditions found inside a greenhouse. Recently, a series of studies have proposed the use of sensors to monitor production and/or the use of cameras to obtain information about cultivation, providing data, reminders, and alerts to farmers. This article proposes a computational model for indoor agriculture called IndoorPlant. The model uses the analysis of context histories to provide intelligent generic services, such as predicting productivity, indicating problems that cultivation may suffer, and giving suggestions for improvements in greenhouse parameters. IndoorPlant was tested in three scenarios of the daily life of farmers with hydroponic production data that were obtained during seven months of cultivation of radicchio, lettuce, and arugula. Finally, the article presents the results obtained through intelligent services that use context histories. The scenarios used services to recommend improvements in cultivation, profiles and, finally, prediction of the cultivation time of radicchio, lettuce, and arugula using the partial least squares (PLS) regression technique. The prediction results were relevant since the following values were obtained: 0.96 (R2, coefficient of determination), 1.06 (RMSEC, square root of the mean square error of calibration), and 1.94 (RMSECV, square root of the mean square error of cross validation) for radicchio; 0.95 (R2), 1.37 (RMSEC), and 3.31 (RMSECV) for lettuce; 0.93 (R2), 1.10 (RMSEC), and 1.89 (RMSECV) for arugula. Eight farmers with different functions on the farm filled out a survey based on the technology acceptance model (TAM). The results showed 92% acceptance regarding utility and 98% acceptance for ease of use.

Rapid, Noninvasive, and Nondestructive Method for Biofilm Imaging on Metallic Surfaces Using Active Thermography.

A simple, rapid, low-cost method was proposed for the imaging of Pseudomonas aeruginosa biofilms on metallic surfaces using an infrared camera. Stainless steel coupons were cooled to generate a thermal gradient in relation to biofilm for active thermography (AT). Both cooling and image acquisition times were optimized and the images obtained with AT were compared with those from scanning electron microscopy. A free software (Thermofilm) was developed for image processing and the results were compared with the software ImageJ, with good agreement (from 87.7 to 103.8%). Images of coupons treated with sanitizer (peracetic acid) were obtained to show the applicability of the proposed method for biofilm studies. All analytical steps could be performed in 3 min in a noncontact, nondestructive, low-cost, portable, and easy-to-use way.

A Case Study on the Development of a Data Privacy Management Solution Based on Patient Information.

Data on diagnosis of infection in the general population are strategic for different applications in the public and private spheres. Among them, the data related to symptoms and people displacement stand out, mainly considering highly contagious diseases. This data is sensitive and requires data privacy initiatives to enable its large-scale use. The search for population-monitoring strategies aims at social tracking, supporting the surveillance of contagions to respond to the confrontation with COVID-19. There are several data privacy issues in environments where IoT devices are used for monitoring hospital processes. In this research, we compare works related to the subject of privacy in the health area. To this end, this research proposes a taxonomy to support the requirements necessary to control patient data privacy in a hospital environment. According to the tests and comparisons made between the variables compared, the application obtained results that contribute to the scenarios applied. In this sense, we modeled and implemented an application. By the end, a mobile application was developed to analyze the privacy and security constraints with COVID-19.

Applied Computing to Education on Noncommunicable Chronic Diseases: A Systematic Mapping Study.

Background: The number of deaths from noncommunicable chronic diseases (NCDs) has increased worldwide. These deaths would be partly avoidable if prevention and follow-up measures were applied to reduce risk factors. Computing can help educate individuals, improving their knowledge about NCDs. This article presents a systematic mapping of studies that apply computing to education on NCDs. The results allow a general view of the literature and the identification of research opportunities. Materials and Methods: The methodology followed three steps: (1) definition of search databases from computer science and health sciences, (2) selection of keywords for search string composition, and (3) application of inclusion and exclusion criteria to filter the results. The survey occurred from January 2008 to April 2018. Results: The initial search resulted in 19,675 papers, of which 38 were selected after applying the filter criteria. The use of mobile computing stood out in 25 papers. The education modalities were self-management and educational content for diabetes (10 papers), asthma (1), cardiovascular disease (1) and chronic diseases (1), self-management of diabetes and games (1), educational content (15), games (6), personalized content (2), and virtual community (1). The percentage of papers on diabetes was 65%. Most solutions (55%) do not use data from individuals to provide information considering their health condition. In addition, 19 papers produced outcome measures by means of experiments. Conclusions: Mobile computing was the most used technology in the papers. In addition, self-management, educational content, and games were the most used mechanisms. A research opportunity consists of personalized assistance. In this sense, ubiquitous learning can provide a continuous and contextualized education.

Accuracy of linear measurements performed with two imaging software in cone-beam computed tomography scans of dry human mandibles.

The present study aimed to assess the accuracy of linear measurements performed with two software packages in multislice (MSCT) and cone beam (CBCT) computed tomography (CT) images. The sample consisted of 10 human mandibles marked standardly 8 times with metallic orthodontic wires. The mandibles underwent both MSCT and CBCT scanning and were measured linearly and digitally with two software packages, namely Studio 3.1® (Anne Solutions®, SP, Brazil) (ST) and Implant Viewer 2.817® (Anne Solutions®, SP, Brazil) (IV). The linear measurements were the mandibular height (MH) and width (MW), and the distance from the alveolar ridge to the mandibular canal (AC). To validate the measurements, the mandibles were sectioned in the marked regions and measured with a digital caliper. Statistically significant differences were not observed between the measurements (MH, MW, and AC) taken digitally with the two software packages from images obtained from the two scanning modalities (MSCT and CBCT) and the measurements taken manually with a digital caliper (p>0.05). MSCT and CBCT images measured digitally with ST and IV software packages resulted in reliable outcomes when compared to measurements obtained manually. Both software and imaging modalities are reliably useful for planning surgical procedure in the dental practice.

A Mapping Study on Mobile Games for Patients of Chronic Diseases.

There is a growing interest of using technologies to propose solutions for healthcare issues. One of such issues is the incidence of chronic diseases, which are responsible for a considerable proportion of worldwide mortality. It is possible to prevent the development of such diseases using tools and methods that instruct the population. To achieve this, mobile games provide a powerful environment for teaching different subjects to user, without them actively knowing that they are learning new concepts. Despite the growing interest of using mobile games in healthcare, more specifically by patients with chronic diseases, in the best of our knowledge there are no studies that address the current research being published in the area. To close this gap, we carried out a systematic mapping study to synthesize an overview of the area. Five databases were searched and more than 1200 studies were analyzed and filtered. Among them, 17 met the the inclusion and exclusion criteria defined in this work. The results show that there is still room for research in this area, since the studies focus on a younger audience rather than proposing solutions for all ages. Furthermore, the number of chronic conditions being addressed is still small, obesity and diabetes are prevalent. Besides, the full capacity of game features that foster learning through games are not being employed, the majority of games proposed by the articles encompass less than half of these features.

Molecular and microscopic evidence of viruses in marine copepods.

As dominant members of marine mesozooplankton communities, copepods play critical roles in oceanic food webs and biogeochemical cycling. Despite the ecological significance of copepods, little is known regarding the causes of copepod mortality, and up to 35% of total copepod mortality cannot be accounted for by predation alone. Viruses have been established as ecologically important infectious agents in the oceans; however, viral infection has not been investigated in mesozooplankton communities. Here we used molecular and microscopic techniques to document viral infection in natural populations of the calanoid copepods Acartia tonsa (Dana) and Labidocera aestiva (Wheeler) in Tampa Bay, FL. Viral metagenomics revealed previously undocumented viruses in each species, named Acartia tonsa copepod circo-like virus (AtCopCV) and Labidocera aestiva copepod circo-like virus (LaCopCV). LaCopCV was found to be extremely prevalent and abundant in L. aestiva populations, with up to 100% prevalence in some samples and average viral loads of 1.13 × 10(5) copies per individual. LaCopCV transcription was also detected in the majority of L. aestiva individuals, indicating viral activity. AtCopCV was sporadically detected in A. tonsa populations year-round, suggesting temporal variability in viral infection dynamics. Finally, virus-like particles of unknown identity were observed in the connective tissues of A. tonsa and L. aestiva by transmission electron microscopy, demonstrating that viruses were actively proliferating in copepod connective tissue as opposed to infecting gut contents, parasites, or symbionts. Taken together, these results provide strong independent lines of evidence for active viral infection in dominant copepod species, indicating that viruses may significantly influence mesozooplankton ecology.

Exercise Training Alters the Bone Mineral Density of Hemodialysis Patients.

Marinho, SM, Moraes, C, Barbosa, JEdSM, Eduardo, JCC, Fouqe, D, Pelletier, S, and Mafra, D. Exercise training alters the bone mineral density of hemodialysis patients. J Strength Cond Res 30(10): 2918-2923, 2016-Patients with chronic kidney disease undergoing hemodialysis (HD) frequently present low bone mineral density (BMD), and exercise may be useful for treating bone loss. This study aimed to assess the effects of an intradialytic resistance exercise training program (RETP) on BMD in HD patients. Twenty-one patients were enrolled into 2 groups; 10 patients performed exercise (80.0% men; 46.9 ± 12.1 years; 27.0 ± 3.4 kg·m) and 11 patients were in the control group (54.5% men; 50.5 ± 11.5 years; 24.1 ± 8.7 kg·m). Dual-energy x-ray absorptiometry was used to measure the BMD, lean mass, and body fat before and after the supervised RETP (performed with elastic bands and ankle cuffs in both lower limbs 3 times a week for 24 weeks-72 sessions). In the exercise group, 30.0% of patients presented with osteopenia and 20.0% osteoporosis and in the control group, 45.5% osteopenia and 36.4% osteoporosis. Only in the exercise group, the osteoporosis percentage was reduced to 10.0% and the femoral neck BMD and T-score improved from 0.89 ± 0.1 to 0.93 ± 0.1 g·cm and from -1.3 ± 0.8 to -1.0 ± 0.8 g·cm (p ≤ 0.05), respectively, after the intervention. In contrast, these parameters were reduced in the control group. The results suggest that resistance exercise may be useful for improving the BMD in HD patients. In summary, 24 weeks of the supervised RETP played a role in improving the BMD of HD patients.

Occult Tumor Cells in Lymph Nodes of Patients with Gastric Cancer: A Systematic Review on Their Prevalence and Predictive Role.

BACKGROUND AND AIMS: The presence of lymph node (LN) metastasis is a key prognostic factor for gastric adenocarcinoma. However, even among patients without LN metastasis (N0), recurrence may occur. In some of these cases, occult tumor cells (OTC) are thought to play an important role. We aimed to determine the prevalence of OTC and its clinical relevance. METHODS: We conducted a systematic review of studies in English published until September 2013 that addressed OTC prevalence and/or its clinical relevance. The studies were retrieved from the MEDLINE database. RESULTS: We included 42 studies. The most frequently used methods for detecting OTC were immunohistochemical examination (IHC) and/or polymerase chain reaction (PCR) with a wide range of markers. Using IHC for OTC detection, in patients and in LN, the prevalence varied from 9 to 88% and 0.4 to 42%, respectively. With PCR, it ranged from 17 to 46% in patients, and from 3 to 33% in LN. In the studies assessing the predictive role of OTC in gastric cancer recurrence (n=24), 8 studies found no statistical association, while 18 concluded that OTC presence was associated with poorer prognosis. However, only 6 studies presented a significantly different 5-year survival rate between patients with and without LN micrometastasis. CONCLUSIONS: OTC seems to occur in gastric cancer patients with a variable prevalence, depending on the definition, methods and setting. The majority of the retrieved studies (75%) evaluating the predictive role of OTC conclude that its presence is associated with a worse prognosis.

Amanitin determination in bile samples by UHPLC-MS: LR-MS and HR-MS analytical performance.

Consumption of misidentified foraged mushrooms containing bicyclic amanitin octapeptides is a worldwide public health and veterinary problem, being considered one of the deadliest accidental human and canine food ingestion due to acute liver failure (ALF). Reversal of advanced ALF and complete clinical recovery can be achieved following definitive removal of accumulated amatoxin laden bile from the gallbladder. An accurate means of quantifying amanitin content in aspirated bile is, therefore, urgently needed. Building on our prior work validating a method to detect and quantify amanitin in hepatic autopsy tissue, the development of an accurate method of measuring α- and ß-amanitin in aspirated gallbladder bile was performed to evaluate the efficiency of this emergency procedure applied as a clinical treatment for intoxicated patients. A solid-phase extraction (SPE) procedure was optimized followed by detection based on ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS). Low resolution mass spectrometry (LRMS) was compared with high resolution (HRMS) by the validation of UHPLC-MS/MS (triple quadrupole MS) and UHPLC-ToF-MS (time-of-flight MS). Both methods were able to detect amatoxins in bile with limits of detection and quantification ranging from 2.71 to 3.46 µg.kg-1, and 8.36-9.03 µg.kg-1 for α-amanitin and, 0.32-1.69 µg.kg-1 and 0.55-5.62 µg.kg-1 for ß-amanitin, respectively. Validation was completed with the evaluation of linearity, specificity, robustness, recovery, and precision following the ICH guidelines and CIR 808/2021. The validated methods were finally applied to bile samples obtained 48-96 hours + post-ingestion from 4 amatoxin poisoning patients who underwent gallbladder drainage procedures in Vietnam, Canada, and California. Gallbladder bile from patients with amatoxin mushroom poisoning contained significant amanitin content, even when aspirated several days post-ingestion, thus confirming the important role of enterohepatic circulation in amatoxin hepatotoxicity. This work represents a high and unique analytical throughput in amanitin poisoning allowing to efficiently respond to this fatal health problem.

Clinical and ultrasound findings of 'swimmer's shoulder' and its association with training history in elite Portuguese swimmers: a cross-sectional study.

OBJECTIVES: To assess the prevalence of shoulder injuries and ultrasound findings in elite Portuguese swimmers and their association with symptoms and personal or training-related factors. METHODS: This cross-sectional study was conducted at the Portuguese Open and Youth Swimming National Championships between 27 and 30th July 2022. Each athlete entered details regarding personal and training history into a questionnaire and underwent a physical and ultrasound shoulder examination. RESULTS: A total of 102 swimmers out of 662 Portuguese athletes were included in the study. Shoulder pain experienced during the previous season was reported by 42% of the athletes. A high prevalence of shoulder structural abnormalities was noted, specifically supraspinatus tendinosis (91%), tears (29%), and subacromial bursitis (29%). Specific training for injury prevention was associated with higher rates of infraspinatus tendinosis (p = 0.047), and supraspinatus tears were linked to greater swimming distances per week (p < 0.001) and practice (p < 0.001), more years of practice (p = 0.018), shoulder pain at the time of evaluation (p = 0.023), a higher number of missed competitions (p = 0.041), and shoulder injections (p = 0.009). Subacromial bursitis was associated with shoulder pain at the time of evaluation (p = 0.002) and during the previous season (p < 0.001), missed competitions (p < 0.001), and requirement for physical therapy (p = 0.006). CONCLUSIONS: A high prevalence of shoulder morphological changes was found in surveyed swimmers and there were several associations with training load, regardless of individual characteristics of each athlete. It is essential to understand the true impact of current injury prevention programs and to develop effective measures to protect swimmers' health.

Diversity and botanical composition of native species in the Pampa biome in vineyards cultivated on soils with high levels of copper, zinc and manganese and phytoremediation potential.

Viticulture allows the preservation of native species inside vineyards in the Pampa biome. However, phytosanitary treatments in these areas can increase the levels of Cu, Zn and Mn. The study aimed to (i) verify the influence of Cu, Zn and Mn contents in Pampa biome soils; (ii) identify variables related to Cu, Zn and Mn that most contribute to the variation in richness, diversity, and dry matter production of native vegetation, (iii) investigate the phytoremediation potential of species present in vineyards. Botanical composition, Cu, Zn, Mn available in the soil, and plant nutritional composition in two vineyards (V1 and V2) and native field (NF) were evaluated. Vineyards showed higher Cu, Zn and Mn contents in the soil, resulting in the lowest biomass, richness, and diversity of native species. Mn in tissue was the most important variable in explaining the variation in dry matter. Zn in the soil helped to explain the difference in species richness and diversity. P concentration in tissue was important in elucidating the variation in species diversity. Paspalum plicatulum and Paspalum notatum have potential for phytostabilization of metals in vineyards.

Paraplegia Following Ultrasound-Guided Caudal Epidural Block in Chronic Lumbosciatica: What Can Be Learned From This Complication?

Caudal epidural block is a procedure that involves the injection of anesthetic agents through the sacral hiatus, commonly used for regional anesthesia. It is also valuable for chronic pain management in lumbosacral conditions, trauma, and palliative care. Ultrasound-guided caudal epidural blocks can be an alternative to fluoroscopy-guided techniques and have demonstrated a notably high success rate. However, despite both techniques being generally regarded as safe, they can lead to severe complications, such as abscesses, epidural hematomas, and subdural punctures. Furthermore, documented instances of lumbosacral region anomalies, stemming from either anatomical variations or underlying pathology, have been associated with an elevated risk of some of these complications. The authors report a rare case of paraplegia following an ultrasound-guided caudal block in a patient with refractory chronic lumbosciatica. This case underscores the need for vigilance in risk assessment and detailed procedural planning. It also highlights the importance of transparent communication, particularly during informed consent, to convey risks and benefits to the patient and their family.

Ubiquitous computing in light of human phenotypes: foundations, challenges, and opportunities.

The interest in human phenotypes has leveraged interdisciplinary efforts encouraging a better understanding of the broad spectrum of psychological and behavioral disorders. Moreover, the usage of mobile and wearable devices along with unobtrusive computational capabilities provides an extensive amount of information that allows the characterization of phenotypes. This article describes the human phenotype through the lens of computational range and reviews state-of-the-art computational phenotyping. Furthermore, the article discusses computational phenotyping's extension concerning the combination of intelligent environments and personal mobile devices, addressing technical, managerial, and ethical challenges. This combination reinforces ubiquitous computational capabilities for phenotyping as a facilitator of interdisciplinary information convergence in favor of clinical and biomedical research.

Mycotoxins in Raw Bovine Milk: UHPLC-QTrap-MS/MS Method as a Biosafety Control Tool.

Mycotoxins are compounds produced by several fungi that contaminate agricultural fields and, either directly or by carry-over, final food products. Animal exposure to these compounds through contaminated feed can lead to their excretion into milk, posing threats to public health. Currently, aflatoxin M1 is the sole mycotoxin with a maximum level set in milk by the European Union, as well as the most studied. Nonetheless, animal feed is known to be contaminated by several groups of mycotoxins with relevance from the food safety point of view that can be carried over into milk. To evaluate the multi-mycotoxin occurrence in this highly consumed food product it is crucial to develop precise and robust analytical methodologies towards their determination. In this sense, an analytical method for the simultaneous identification of 23 regulated, non-regulated, and emerging mycotoxins in raw bovine milk using ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) was validated. A modified QuEChERS protocol for extraction purposes was used, and further validation was performed by assessing the selectivity and specificity, limits of detection and quantification (LOD and LOQ), linearity, repeatability, reproducibility, and recovery. The performance criteria were compliant with mycotoxin-specific and general European regulations for regulated, non-regulated, and emerging mycotoxins. The LOD and LOQ ranged between 0.001 and 9.88 ng mL-1 and 0.005 and 13.54 ng mL-1, respectively. Recovery values were between 67.5 and 119.8%. The repeatability and reproducibility parameters were below 15 and 25%, respectively. The validated methodology was successfully applied to determine regulated, non-regulated, and emerging mycotoxins in raw bulk milk from Portuguese dairy farms, proving the importance of widening the monitoring scope of mycotoxins in dairy products. Additionality, this method presents itself as a new strategic and integrated biosafety control tool for dairy farms for the analysis of these natural and relevant human risks.

Regulated and Emerging Mycotoxins in Bulk Raw Milk: What Is the Human Risk?

Mycotoxins are abiotic hazards whose contamination occurs at the pre- and post-harvest stages of the maize value chain, with animal exposure through contaminated feed leading to their excretion into milk. Currently, only aflatoxin M1 is regulated in milk products. Since feed materials and complete feed present a multi-mycotoxin composition and are the main mycotoxin source into milk, it is important to recognize the occurrence of multiple toxins and their co-occurrence in this highly consumed food product. The aim of this study was to determine the content of regulated and emerging mycotoxins in milk samples, which allowed for evaluating the occurrence and co-occurrence patterns of different mycotoxins known to contaminate feed materials and complete animal feed. Human exposure considering the occurrence patterns obtained was also estimated. Aflatoxins, fumonisins, zearalenone, and emerging mycotoxins were among the mycotoxins found to be present in the 100 samples analyzed. Concentrations ranged from 0.006 to 16.3 µg L-1, with no sample exceeding the AFM1 maximum level. Though several mycotoxins were detected, no exceeding values were observed considering the TDI or PMTDI. It can be concluded that the observed exposure does not pose a health risk to milk consumers, though it is important to recognize vulnerable age groups.

Posture monitoring in healthcare: a systematic mapping study and taxonomy.

Palliative treatments for back pain usually include exercise, analgesics, physiotherapy, prostheses, and surgery in severe cases. Technologies for postural monitoring are growing, and they are important in preventing back pain and mitigating permanent damage. Remote work, especially after the COVID-19 pandemic, made people spend more time than usual in chairs and environments not certified by the health aspects of work. This research investigated through a Systematic Mapping Study (SMS) contributions in posture monitoring for healthcare in smart environments, including the different methods to obtain the posture, the limitations, and the target audience of the proposed models. The SMS was conducted in eight databases, including articles from January 2012 to March 2022. The initial search yielded 3161 articles, of which 34 were selected after applying the filtering criteria. Moreover, this study presents the challenges related to posture behavior monitoring, identifying studies and implementations that apply assistive technology for postural monitoring and improving the health and life of remote workers. In addition, three commercial postural devices are presented, and what challenges they currently face. Regarding healthcare, results showed a prevalence of using the Internet of Things (IoT) devices such as wireless sensor networks and inertial measurement unit (IMU) sensors. This article also proposes a taxonomy, showing the most used technologies and algorithms for improving posture, besides the posture-monitoring hierarchy classifying into three important branches: (a) Data Collect; (b) Data Transmission; and (c) Data Analysis.