Peripheral blood stem cells collection by apheresis in very low-weight children with malignant diseases-A single center experience.

BACKGROUND: Hematopoietic stem cell transplantation is used in the treatment of children with malignant and non-malignant diseases. However, apheresis of peripheral blood stem cells (PBSC) represents a challenge in children below 10 kg. METHODS: A retrospective trial was conducted in the Cellular Therapy Department of Portuguese Oncology Institute of Porto. INCLUSION CRITERIA: children with body weight inferior to 10 kg who underwent autologous PBSC apheresis until 2021. Demographic and clinical data were collected and our institutional protocol was described. COBE Spectra apheresis system (TerumoBCT, Lakewood, Colorado) until 2012 and then Spectra Optia (TerumoBCT) were used. RESULTS: Sixteen leukocytaphereses were performed in 13 patients-nine females (69%). Mean age and weight were 13.31 months (±5.26) and 8.31 kg (±1.17), respectively. The initial CD34+ cells/µL in peripheral blood was 70.8 (±61.9). A central venous catheter (CVC) was exclusively used in all but one patient, in whom a peripheral vein was also required. In 10 procedures, both heparin and anticoagulant citrate dextrose solution-formula A (ACD-A) were used; in the remaining ones, only ACD-A was employed. The median duration of each procedure was 168 minutes (±45) and 2.96 blood volumes (±0.31) were processed. Median CD34+ cells yield per leukocytapheresis was 6.52 × 106 /kg (±9.87 × 106 ). CD34+ cell extraction rates were not significantly different between the two apheresis systems. Platelet and magnesium levels were significantly lower after collection (P < .001 and P = .009, respectively). CONCLUSIONS: Although recommendations are lacking, we have successfully and safely performed leukocytaphereses in children with body weight below 10 kg. The authors believe that a permanent and dynamic comprehensive evaluation of each child is paramount for attaining good results.

Fracture resistance and biomechanical behavior of different access cavities of maxillary central incisors restored with different composite resins.

OBJECTIVES: The aim of this study was to compare the effect of three different access cavities on the tissue removal, deflection, fracture resistance, and stress distribution of extracted maxillary central incisors. MATERIALS AND METHODS: Forty human maxillary central incisors were randomly assigned in four experimental group (n = 10) including conservative access cavity "CAC," traditional access cavity "TAC," invasive access cavity "IAC," and without access cavity (control group). Cone-beam computed tomography "CBCT" scans were used to evaluate the tissue removal during the different access cavities. All specimens were restored with composite resin (Admira Fusion, Voco, Cuxhaven, Germany) and embedded in acrylic resin blocks after simulating the periodontal ligament using red wax, then the specimens were submitted to the deflection test applying a load of 250 N and to the load-to-fracture test after artificial aging in a mechanical cycling machine (150 N, 5 × 106 cycles, 10 Hz). Lastly, stress distribution was assessed by three-dimensional finite element analysis (3D-FEA), simulating the specimens restoration by two types of composite resins of low and high elastic modulus (8 and 18 GPa respectively) after the access cavities. The data were submitted to Shapiro-Wilk and KS normality tests. Then, they were analyzed by one-way ANOVA and Tukey tests with a significance level (α ≤ 0.05). RESULTS: CBCT scans showed a significant difference of worn tissues in CAC and TAC when compared to the IAC (P < 0.0001). In deflection test, CAC showed lower deformation values than the TAC and IAC. Load-to-fracture test presented no significant difference among the three experimental groups (P = 0.6901). 3D-FEA showed that the more conservative the access cavity, the higher the stress magnitude. CONCLUSIONS: CAC promote less worn tissue; however, this does not improve the stress distribution or fracture resistance of endodontically treated maxillary incisors. CLINICAL RELEVANCE: Clinicians should reconsider the pros and cons of the conservative access cavity.

Mist and Edge Computing Cyber-Physical Human-Centered Systems for Industry 5.0: A Cost-Effective IoT Thermal Imaging Safety System.

While many companies worldwide are still striving to adjust to Industry 4.0 principles, the transition to Industry 5.0 is already underway. Under such a paradigm, Cyber-Physical Human-centered Systems (CPHSs) have emerged to leverage operator capabilities in order to meet the goals of complex manufacturing systems towards human-centricity, resilience and sustainability. This article first describes the essential concepts for the development of Industry 5.0 CPHSs and then analyzes the latest CPHSs, identifying their main design requirements and key implementation components. Moreover, the major challenges for the development of such CPHSs are outlined. Next, to illustrate the previously described concepts, a real-world Industry 5.0 CPHS is presented. Such a CPHS enables increased operator safety and operation tracking in manufacturing processes that rely on collaborative robots and heavy machinery. Specifically, the proposed use case consists of a workshop where a smarter use of resources is required, and human proximity detection determines when machinery should be working or not in order to avoid incidents or accidents involving such machinery. The proposed CPHS makes use of a hybrid edge computing architecture with smart mist computing nodes that processes thermal images and reacts to prevent industrial safety issues. The performed experiments show that, in the selected real-world scenario, the developed CPHS algorithms are able to detect human presence with low-power devices (with a Raspberry Pi 3B) in a fast and accurate way (in less than 10 ms with a 97.04% accuracy), thus being an effective solution (e.g., a good trade-off between cost, accuracy, resilience and computational efficiency) that can be integrated into many Industry 5.0 applications. Finally, this article provides specific guidelines that will help future developers and managers to overcome the challenges that will arise when deploying the next generation of CPHSs for smart and sustainable manufacturing.

Towards circular economy in the textiles and clothing value chain through blockchain technology and IoT: A review.

The textile and clothing industry sector has today a big environmental impact, not only due to the consumption of water and the use of toxic chemicals but also due to the increasing levels of textile waste. One way to reduce the problem is to circularise the, currently linear, textile and clothing value chain, by using discarded clothes as raw material for the production of new clothes, transforming it into a model of circular economy. This way, while reducing the need to produce new raw materials (e.g. cotton), the problem of textile waste produced is also reduced, thus contributing to a more sustainable industry. In this article, we review the current approaches for traceability in the textile and clothing value chain, and study a set of technologies we deem essential for promoting the circular economy in this value chain - namely, the blockchain technology - for registering activities on traceable items through the value chain, and the Internet of Things (IoT) technology, for easily identifying the traceable items' digital twins.

Eliminating Plasmodium falciparum malaria: results from tailoring active case detection approaches to remote populations in forested border areas in north-eastern Cambodia.

BACKGROUND: Remaining Plasmodium falciparum cases in Cambodia are concentrated in forested border areas and in remote populations who are hard to reach through passive case detection. A key approach to reach these populations is active case detection by mobile malaria workers (MMWs). However, this is operationally challenging because of changing movement patterns of the target population moving into less accessible areas. From January 2018 to December 2020, a tailored package of active case detection approaches was implemented in forested border areas of three provinces in north-eastern Cambodia to reach remote populations and support the elimination of falciparum malaria. METHODS: Key elements of this project were to tailor approaches to local populations, use responsive monitoring systems, maintain operational flexibility, build strong relationships with local communities, and implement close supervision practices. MMWs were recruited from local communities. Proactive case detection approaches included mobile malaria posts positioned at frequented locations around and within forests, and locally informed outreach activities targeting more remote locations. Reactive case detection was conducted among co-travellers of confirmed cases. Testing for malaria was conducted independent of fever symptoms. Routine monitoring of programmatic data informed tactical adaptations, while supervision exercises ensured service quality. RESULTS: Despite operational challenges, service delivery sites were able to maintain consistently high testing rates throughout the implementation period, with each of 45 sites testing a monthly average of 64 (SD 6) people in 2020. In 2020, project MMWs detected only 32 P. falciparum cases. Over the project period, the P. falciparum/P. vivax ratio steadily inversed. Including data from neighbouring health centres and village malaria workers, 45% (80,988/180,732) of all people tested and 39% (1280/3243) of P. falciparum cases detected in the area can be attributed to project MMWs. Remaining challenges of the last elimination phase include maintaining intensified elimination efforts, addressing the issue of detecting low parasitaemia cases and shifting focus to P. vivax malaria. CONCLUSIONS: Reaching remote populations through active case detection should remain a key strategy to eliminate P. falciparum malaria. This case study presented a successful approach combining tailored proactive and reactive strategies that could be transferred to similar settings in other areas of the Greater Mekong Subregion.

Green IoT and Edge AI as Key Technological Enablers for a Sustainable Digital Transition towards a Smart Circular Economy: An Industry 5.0 Use Case.

Internet of Things (IoT) can help to pave the way to the circular economy and to a more sustainable world by enabling the digitalization of many operations and processes, such as water distribution, preventive maintenance, or smart manufacturing. Paradoxically, IoT technologies and paradigms such as edge computing, although they have a huge potential for the digital transition towards sustainability, they are not yet contributing to the sustainable development of the IoT sector itself. In fact, such a sector has a significant carbon footprint due to the use of scarce raw materials and its energy consumption in manufacturing, operating, and recycling processes. To tackle these issues, the Green IoT (G-IoT) paradigm has emerged as a research area to reduce such carbon footprint; however, its sustainable vision collides directly with the advent of Edge Artificial Intelligence (Edge AI), which imposes the consumption of additional energy. This article deals with this problem by exploring the different aspects that impact the design and development of Edge-AI G-IoT systems. Moreover, it presents a practical Industry 5.0 use case that illustrates the different concepts analyzed throughout the article. Specifically, the proposed scenario consists in an Industry 5.0 smart workshop that looks for improving operator safety and operation tracking. Such an application case makes use of a mist computing architecture composed of AI-enabled IoT nodes. After describing the application case, it is evaluated its energy consumption and it is analyzed the impact on the carbon footprint that it may have on different countries. Overall, this article provides guidelines that will help future developers to face the challenges that will arise when creating the next generation of Edge-AI G-IoT systems.

Wearables and Internet of Things (IoT) Technologies for Fitness Assessment: A Systematic Review.

Wearable and Internet of Things (IoT) technologies in sports open a new era in athlete's training, not only for performance monitoring and evaluation but also for fitness assessment. These technologies rely on sensor systems that collect, process and transmit relevant data, such as biomarkers and/or other performance indicators that are crucial to evaluate the evolution of the athlete's condition, and therefore potentiate their performance. This work aims to identify and summarize recent studies that have used wearables and IoT technologies and discuss its applicability for fitness assessment. A systematic review of electronic databases (WOS, CCC, DIIDW, KJD, MEDLINE, RSCI, SCIELO, IEEEXplore, PubMed, SPORTDiscus, Cochrane and Web of Science) was undertaken according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. From the 280 studies initially identified, 20 were fully examined in terms of hardware and software and their applicability for fitness assessment. Results have shown that wearable and IoT technologies have been used in sports not only for fitness assessment but also for monitoring the athlete's internal and external workloads, employing physiological status monitoring and activity recognition and tracking techniques. However, the maturity level of such technologies is still low, particularly with the need for the acquisition of more-and more effective-biomarkers regarding the athlete's internal workload, which limits its wider adoption by the sports community.

Volumetric evaluation of temporomandibular joints in patients with a chewing-side preference: a CBCT study.

This study evaluated the influence of chewing-side preference on the volume of the mandibular condyle and coronoid process and the dynamic parameters of the temporomandibular joint (TMJ). Cone beam computed tomographic scans of both TMJs of 90 individuals with a chewing-side preference were obtained while the patients were in the closed-mouth and maximum mouth-opening positions (test power ≥ 0.80). The preferred chewing side was identified with a chewing gum test as well as by patient self-reports of preferred side and hemispheric dominance (ie, dominant side of the body). Two trained examiners assessed the volume of the mandibular condyle and coronoid process and the dynamic parameters of the TMJs on both sides. The volumes of the mandibular condyle on the 2 sides were compared using a paired t test (α = 0.05). McNemar and Bowker tests of symmetry (α = 0.05) were used for concordance analyses of the dynamic parameters of the TMJ on the chewing and nonchewing sides. No statistically significant difference was observed in the volume of the mandibular condyle (chewing gum test, P = 0.4548; interview, P = 0.7191; hemispheric dominance, P = 0.3471) or coronoid process (chewing gum test, P = 0.7718; interview, P = 0.8072; hemispheric dominance, P = 0.8301) on the chewing and nonchewing sides, regardless of the method used to identify chewing preference. The preferred chewing side also did not significantly affect the dynamic parameters of the mandibular condyle (P = 0.5538). Chewing-side preference does not influence the volume of the mandibular condyle or coronoid process or the dynamic parameters of the TMJ.

Evaluating Temporal Correlations in Time Series Using Permutation Entropy, Ordinal Probabilities and Machine Learning.

Time series analysis comprises a wide repertoire of methods for extracting information from data sets. Despite great advances in time series analysis, identifying and quantifying the strength of nonlinear temporal correlations remain a challenge. We have recently proposed a new method based on training a machine learning algorithm to predict the temporal correlation parameter, α, of flicker noise (FN) time series. The algorithm is trained using as input features the probabilities of ordinal patterns computed from FN time series, xαFN(t), generated with different values of α. Then, the ordinal probabilities computed from the time series of interest, x(t), are used as input features to the trained algorithm and that returns a value, αe, that contains meaningful information about the temporal correlations present in x(t). We have also shown that the difference, Ω, of the permutation entropy (PE) of the time series of interest, x(t), and the PE of a FN time series generated with α=αe, xαeFN(t), allows the identification of the underlying determinism in x(t). Here, we apply our methodology to different datasets and analyze how αe and Ω correlate with well-known quantifiers of chaos and complexity. We also discuss the limitations for identifying determinism in highly chaotic time series and in periodic time series contaminated by noise. The open source algorithm is available on Github.

Malaria Test, Treat and Track policy implementation in Angola: a retrospective study to assess the progress achieved after 4 years of programme implementation.

BACKGROUND: Malaria is one of the main causes of death in Angola, particularly among children under 5 years of age. An essential means to improve the situation is with strong malaria case management; this includes diagnosing suspected patients with a confirmatory test, either with a rapid diagnostic test (RDT) or microscopy, prompt and correct treatment with artemisinin-based combination therapy (ACT), and proper case registration (track). In 2011, the United States President's Malaria Initiative (PMI) launched a country-wide programme to improve malaria case management through the provision of regular training and supervision at different levels of health care provision. An evaluation of malaria testing, treatment and registration practices in eight provinces, and at health facilities of various capacities, across Angola was conducted to assess progress of the national programme implementation. METHODS: A retrospective assessment analysed data collected during supervision visits to health facilities conducted between 2012 and 2016 in 8 provinces in Angola. The supervision tool used data collected for malaria knowledge, testing, treatment and case registration practices among health workers as well as health facilities stock outs from different levels of health care delivery. Contingency tables with Pearson chi-squared (χ2) tests were used to identify factors associated with "knowledge", "test", "treat" and "track." Multivariable logistic regression models were used to assess factors associated with the defined outcomes. RESULTS: A total of 7156 supervisions were conducted between September 2012 and July 2016. The overall knowledge, testing, treatment and tracking practices among health care workers (HCWs) increased significantly from 2013 to 2016. Health care workers in 2016 were 3.3 times (95% CI: 2.7-3.9) as likely to have a higher knowledge about malaria case management as in 2013 (p < 0.01), 7.4 (95% CI: 6.1-9.0) times as likely to test more suspected cases (p < 0.01), 10.9 (95% CI: 8.6-13.6) times as likely to treat more confirmed cases (p < 0.01) and 3.7 (95% CI: 3.2-4.4) times as likely to report more accurately in the same period (p < 0.01). DISCUSSION: Improvements demonstrated in knowledge about malaria case management, testing with RDT and treatment with artemisinin-based combinations among HCWs is likely associated with malaria case management trainings and supportive supervisions. Gaps in testing and treatment practices are associated with RDT and ACT medicines stock outs in health facilities. Tracking of malaria cases still poses a major challenge, despite training and supervision. Hospitals consistently performed better compared to other health facilities against all parameters assessed; likely due to a better profile of HCWs. CONCLUSION: Significant progress in malaria case management in eight provinces Angola was achieved in the period of 2013-2016. Continued training and supportive supervision is essential to sustain gains and close existing gaps in malaria case management and reporting in Angola.

Challenges in Resource-Constrained IoT Devices: Energy and Communication as Critical Success Factors for Future IoT Deployment.

Internet of Things (IoT) has been developing to become a free exchange of useful information between multiple real-world devices. Already spread all over the world in the most varied forms and applications, IoT devices need to overcome a series of challenges to respond to the new requirements and demands. The main focus of this manuscript is to establish good practices for the design of IoT devices (i.e., smart devices) with a focus on two main design challenges: power and connectivity. It groups IoT devices in passive, semi-passive, and active, giving details on multiple research topics. Backscatter communication, Wireless Power Transfer (WPT), Energy Harvesting (EH), chipless devices, Simultaneous Wireless Information and Power Transfer (SWIPT), and Wake-Up Radio (WUR) are some examples of the technologies that will be explored in this work.

Association of volume and voxel intensity of the articular disc and lateral pterygoid muscle in migraine patients: a study with magnetic resonance imaging.

Objectives: To compare the volume and voxel intensity of articular disc and lateral pterygoid muscle (LPM) between a group of migraine patients and a control group (those without history of headache) by using magnetic resonance imaging (MRI).Patients and methods: MRI scans of 17 migraine patients and 15 healthy controls subjects were analysed and processed, using ITK-SNAP software, by a single investigator, for calculation of volumes and voxel intensity of articular disc and superior and inferior head of LPM.Results: There were statistically significant differences between migraine patients and controls regarding the volume and voxel intensity of articular disc and inferior head of LPM, increasing in migraine patients. Intra-rater was highly consistent and reproducible (intra-class correlation coefficient [ICC] = 1).Conclusions: Higher voxel intensity in disc and inferior head of LPM of MRI scans was linked to the increased volume of articular disc, inferior head of LPM and migraine.

The tolerability of single low dose primaquine in glucose-6-phosphate deficient and normal falciparum-infected Cambodians.

BACKGROUND: The WHO recommends single low-dose primaquine (SLDPQ, 0.25 mg/kg body weight) in falciparum-infected patients to block malaria transmission and contribute to eliminating multidrug resistant Plasmodium falciparum from the Greater Mekong Sub region (GMS). However, the anxiety regarding PQ-induced acute haemolytic anaemia in glucose-6-phosphate dehydrogenase deficiency (G6PDd) has hindered its use. Therefore, we assessed the tolerability of SLDPQ in Cambodia to inform national policy. METHODS: This open randomised trial of dihydroartemisinin-piperaquine (DHAPP) + SLDPQ vs. DHAPP alone recruited Cambodians aged ≥1 year with acute uncomplicated P. falciparum. Randomisation was 4:1 DHAPP+SLDPQ: DHAPP for G6PDd patients and 1:1 for G6PDn patients, according to the results of the qualitative fluorescent spot test. Definitive G6PD status was determined by genotyping. Day (D) 7 haemoglobin (Hb) concentration was the primary outcome measure. RESULTS: One hundred nine patients (88 males, 21 females), aged 4-76 years (median 23) were enrolled; 12 were G6PDd Viangchan (9 hemizygous males, 3 heterozygous females). Mean nadir Hb occurred on D7 [11.6 (range 6.4 ─ 15.6) g/dL] and was significantly lower (p = 0.040) in G6PDd (n = 9) vs. G6PDn (n = 46) DHAPP+SLDPQ recipients: 10.9 vs. 12.05 g/dL, Δ = -1.15 (95% CI: -2.24 ─ -0.05) g/dL. Three G6PDn patients had D7 Hb concentrations < 8 g/dL; D7-D0 Hbs were 6.4 ─ 6.9, 7.4 ─ 7.4, and 7.5 ─ 8.2 g/dL. For all patients, mean (range) D7-D0 Hb decline was -1.45 (-4.8 ─ 2.4) g/dL, associated significantly with higher D0 Hb, higher D0 parasitaemia, and receiving DHAPP; G6PDd was not a factor. No patient required a blood transfusion. CONCLUSIONS: DHAPP+SLDPQ was associated with modest Hb declines in G6PD Viangchan, a moderately severe variant. Our data augment growing evidence that SLDPQ in SE Asia is well tolerated and appears safe in G6PDd patients. Cambodia is now deploying SLDPQ and this should encourage other GMS countries to follow suit. TRIAL REGISTRATION: The clinicaltrials.gov reference number is NCT02434952 .

Quantifying entropy using recurrence matrix microstates.

We conceive a new recurrence quantifier for time series based on the concept of information entropy, in which the probabilities are associated with the presence of microstates defined on the recurrence matrix as small binary submatrices. The new methodology to compute the entropy of a time series has advantages compared to the traditional entropies defined in the literature, namely, a good correlation with the maximum Lyapunov exponent of the system and a weak dependence on the vicinity threshold parameter. Furthermore, the new method works adequately even for small segments of data, bringing consistent results for short and long time series. In a case where long time series are available, the new methodology can be employed to obtain high precision results since it does not demand large computational times related to the analysis of the entire time series or recurrence matrices, as is the case of other traditional entropy quantifiers. The method is applied to discrete and continuous systems.

Optimizing the detection of nonstationary signals by using recurrence analysis.

Recurrence analysis and its quantifiers are strongly dependent on the evaluation of the vicinity threshold parameter, i.e., the threshold to regard two points close enough in phase space to be considered as just one. We develop a new way to optimize the evaluation of the vicinity threshold in order to assure a higher level of sensitivity to recurrence quantifiers to allow the detection of even small changes in the dynamics. It is used to promote recurrence analysis as a tool to detect nonstationary behavior of time signals or space profiles. We show that the ability to detect small changes provides information about the present status of the physical process responsible to generate the signal and offers mechanisms to predict future states. Here, a higher sensitive recurrence analysis is proposed as a precursor, a tool to predict near future states of a particular system, based on just (experimentally) obtained signals of some available variables of the system. Comparisons with traditional methods of recurrence analysis show that the optimization method developed here is more sensitive to small variations occurring in a signal. The method is applied to numerically generated time series as well as experimental data from physiology.

Hematopoietic progenitor cells collection in pediatric patients with brain tumor.

AIM: To analyze the efficacy and safety of hematopoietic progenitor cells (HPC) collections by leukapheresis in pediatric patients with brain tumors. RESULTS: Between 2003 and 2014, we collected HPC from 19 children (12 boys/7 girls), median age at the diagnosis of 5 years old (<1-15 years old) and weight of 16.8 Kg (6.7-42). Diagnoses were Medulloblastoma (n = 10), Primitive Neuroectodermal Tumor (n = 5), Atypical Teratoid Rhabdoid Tumor (n = 3) and Secreting Germ Cell Tumor (n = 1). All patients performed leukapheresis by a central venous catheter, at the fifth day of mobilization with G-CSF (median dose 11.7 µg/Kg/day), 9 of them with COBE® Spectra and 10 with Spectra Optia®. The anticoagulant used was ACD-A, ratio of 14:1 or ACD-A plus heparin, ratio 25:1. The tubing set was primed with a compatible, irradiated, leukodepleted and hematocrit adjusted packed red cells for all children <30 kg (n = 17). A median of 1.5 (1-3) leukapheresis per patient was performed with an average of 3 (1.5-5.4) blood volumes processed; 3 children did a second mobilization and one additional leukapheresis. The median number of CD34+ cells collected was 4.6 × 10(6) /Kg (0.18-22.6) of patient body weight; 12 children collected for a tandem transplant. The median time between cell collection and infusion was 3 (0.6-9.1) months. CONCLUSIONS: HPC collection in children is an efficient and well tolerated technique, performed as an outpatient procedure. With the new mobilization schemes and leukapheresis technology, we can collect a high number of HPC allowing pediatric oncologist to establish more aggressive chemotherapy protocols hoping to improve patient outcome.

Keratocystic odontogenic tumor: role of cone beam computed tomography and magnetic resonance imaging.

Keratocystic odontogenic tumors (KCOTs) are known for unique and varied behavior, high recurrence rates, and distinctive histopathologic findings. Differential diagnosis and management of KCOTs may be challenging because other jaw lesions may present similar characteristics. Careful interpretation of cone beam computed tomograms and magnetic resonance images has great significance for precise assessment of KCOTs and their relationships to adjacent anatomic structures as well as for treatment planning. This case report describes a KCOT that developed in the left angle and mandibular ramus in association with a semierupted third molar.

Mathematical model of brain tumour with glia-neuron interactions and chemotherapy treatment.

In recent years, it became clear that a better understanding of the interactions among the main elements involved in the cancer network is necessary for the treatment of cancer and the suppression of cancer growth. In this work we propose a system of coupled differential equations that model brain tumour under treatment by chemotherapy, which considers interactions among the glial cells, the glioma, the neurons, and the chemotherapeutic agents. We study the conditions for the glioma growth to be eliminated, and identify values of the parameters for which the inhibition of the glioma growth is obtained with a minimal loss of healthy cells.

Floristic similarity and dispersal syndromes in a rocky outcrop in semi-arid Northeastern Brazil.

Floristic studies provide valuable information on species richness in a region, and are particularly important if these areas belong to less studied environments, such as rocky outcrops, that may increase our knowledge. An important aspect for species colonization includes the mechanisms of diaspores dispersal in each community; these are essential to understand its structure, dynamics, and the regeneration process, and constitute an important tool for conservation. We developed a floristic survey on a granite-gneiss outcrop with the objective to increase the knowledge on plant diversity, through a floristic similarity analysis and detection of dispersal syndromes of sampled species, in a semi-arid region of Brazil. The fieldwork included collection and observation of the botanical material in loco during a period of 12 months. A total of 161 species belonging to 127 genera and 50 families of angiosperms were recorded. Fabaceae, Asteraceae and Convolvulaceae were the most representative families in number of species. Allophylus quercifolius (Mart.) Radlk. (Capparaceae) and Lafoensia pacari A. St.-Hil. (Lythraceae) represented new records for the State of Paraiba. The autochoric syndrome was the most representative, with 51.5 % of the recorded species; the anemochory was the second most representative syndrome with 26.7 % of the species; and finally the zoochory, representing 22.3 % of the species. The floristic similarity dendrogram showed the formation of three well-defined groups, whose area with the highest value (J = 33.2) is located in a Caatinga region called Cariri Paraibano, while the lowest value observed (J = 5.2), occurred in a settled area in two geomorphological units, a crystalline complex and a plateau region. These results may be due to the varying topographic conditions and edaphic heterogeneity arising from the specific geological formation of the region. These results yet demonstrate that, in rocky outcrops, abiotic syndromes represent an effective dispersion of its diaspores, favoring plant specie's colonization dynamics.

Community health workers: to train or to restrain? A longitudinal survey to assess the impact of training community health workers in the Bolama Region, Guinea-Bissau.

BACKGROUND: The shortage in human resources for health affects most dramatically developing countries which frequently use community health workers (CHW) as the basis for health programmes and services. The traditional definition refers CHWs as members of the community who are recruited and trained in health prevention and promotion to provide services within their community. In Guinea-Bissau, CHWs play a fundamental role in the diagnosis and treatment of childhood diarrheal diseases - one of the main health problems in the country. METHODS: This study is based on 22 CHW, 79% of the total number of CHW in the Sanitary Region of Bolama. The main goal was to assess how training CHW on diarrheal diseases impacted the accuracy of the diagnosis and treatment of these diseases in children under the age of 5 years. Three evaluations were made throughout time - one evaluation before the training and two follow-up evaluations.An observation grid was developed to evaluate the identified signs, symptoms, diagnosis and treatments prescribed by the CHW in consultations to children with a suspicion of diarrhoeal disease. A similar grid was filled by a medical doctor who took the role of the external validation standard.Friedman's variance analysis and Cochran's Q test were performed to compare the accuracy depicted by CHWs in identifying items throughout time. A logistic regression model was also used to check the possible influence of socio-demographic characteristics of CHWs on the accuracy of the diagnosis and treatment prescribed by the CHW. RESULTS: The results show that CHWs improve significantly their performance in identifying the correct diagnosis in the first follow-up moment after the training (P = 0.001, n = 22) but, 3 months later, the effectiveness decreases. No statistical evidence was found for the logistic regression models applied. This progressive loss of performance after training may occur because CHWs fail to apply treatment algorithms and guidelines over time. A limited set of socio-demographic characteristics of the CHWs can influence their performance and should not be disregarded when selecting CHW candidates. CONCLUSION: The selection, supervision, support and continuous training of CHW are as important as the training provided.