Search

Objective: The study aimed to optimize protocols for the joint extraction of deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) from 0.025 × 106 CFU of Candida albicans, targeting to overcome the challenges in the extraction of these genetic materials. Materials and methods: From this, treated silicon carbide (SiC) granules were added to fungal samples from methods 1, 2, and 3 obtained from aliquots of BHI or Sabouraud medium to cause cell lysis and enable the isolation of these macromolecules by phenol and chloroform. The concentration and integrity of the extracted nucleic acids were analyzed, respectively, by spectrophotometry using the A260/A280 ratios and 1% agarose gel electrophoresis. Results: Therefore, method 3 is the one that most comprises samples considered pure of both DNA and RNA, simultaneously. Furthermore, the presence of intact RNAs corresponding to the base pair size such as 5.8 S rRNA and tRNA was verified during electrophoresis, considering the particularities of RNA, which makes it very unstable and easily degraded. Conclusions: Thus, it results in a faster and simpler method in addition to obtain promising results using minimal amounts of biological sample and offering a valuable alternative for small laboratories to work with molecular biology. [ABSTRACT FROM AUTHOR]

Objectives To elicit and quantify expert opinion concerning the relative merits of two treatments for a rare inflammatory disease: JDM. The formal expression of expert opinion reported in this article will be used in a Bayesian analysis of a forthcoming randomized controlled trial known as BARJDM (baricitinib for JDM). Methods A Bayesian prior elicitation meeting was convened, following a previously described methodological template. Opinion was sought on the probability that a patient in the BARJDM trial would achieve clinically inactive disease, off glucocorticoids (GC) within a 12-month period with either MTX (standard of care); or baricitinib (a Janus kinase inhibitor, JAKi), with GC schedules identical in both arms of the trial. Experts' views were discussed and refined following presentation and further discussion of summated published data regarding efficacy of MTX or JAKi for JDM. Results Ten UK paediatric rheumatology consultants (including one adolescent paediatric rheumatologist) participated in the elicitation meeting. All had expertise in JDM, leading active National Health Service clinics for this disease. Consensus expert prior opinion was that the most likely probability of clinically inactive disease off GC within 12 months was 0.55 on baricitinib and 0.23 on MTX, with a greater degree of uncertainty for baricitinib. Conclusion Experts currently think that baricitinib is superior to MTX for the treatment of JDM, although there is uncertainty around this. BARJDM will therefore integrate randomized trial data with this expert prior opinion to derive a posterior distribution for the relative efficacy of baricitinib compared with MTX. [ABSTRACT FROM AUTHOR]

In the last ten years, the development of sensors with greater accuracy and precision due to improvements in manufacturing processes has enabled the expansion of their use in several areas. However, the purchase price, mainly of products from renowned manufacturers, in view of their applications, can make simpler projects unfeasible. The sensor data fusion technique is a viable alternative to resolve this issue, as mathematical models can be proposed and used in different situations. These models allow improving the data obtained in order to generate reliable information. Therefore, the objective of this work was to verify the performance of multiple linear regression applied to the fusion of redundant quantitative data from 5mm LDR sensors in estimating the luminous intensity (LUX) in simulated scenarios. To carry out the experiment, 3 LDR (Light Dependent Resistor) sensors, 3 LM393 signal conditioners, 1 USB 6009 DAQ data acquisition board (14 bits), 1 LT40 Extech luxmeter, in addition to the LabView software were used. It was found that LDR A and B sensors showed higher levels of accuracy. Furthermore, a significant improvement in the level of accuracy was found when combining data from sensors A and B in the form of multiple linear regression.

Restrictions on soil water supply can dramatically reduce crop yields by affecting the growth and development of plants. For this reason, screening tools that can detect crop water stress early have been long investigated, with canopy temperature (CT) being widely used for this purpose. In this study, we investigated the relationship between canopy temperature retrieved from unmanned aerial vehicles (UAV) based thermal imagery with soil and plant attributes, using a rainfed maize field as the area of study. The flight mission was conducted during the late vegetative stage and at solar noon, when a considerable soil water deficit was detected according to the soil water balance model used. While the images were being taken, soil sampling was conducted to determine the soil water content across the field. The sampling results demonstrated the spatial variability of soil water status, with soil volumetric water content (SVWC) presenting 10.4% of variation and values close to the permanent wilting point (PWP), reflecting CT readings that ranged from 32.8 to 40.6 °C among the sampling locations. Although CT correlated well with many of the physical attributes of soil that are related to water dynamics, the simple linear regression between CT and soil water content variables yielded coefficients of determination (R2) = 0.42, indicating that CT alone might not be sufficient to predict soil water status. Nonetheless, when CT was combined with some soil physical attributes in a multiple linear regression, the prediction capacity was significantly increased, achieving an R2 value = 0.88. This result indicates the potential use of CT along with certain soil physical variables to predict crop water status, making it a useful tool for studies exploring the spatial variability of in-season drought stress.

Objectives: Patients with rheumatoid arthritis (RA) have an increased susceptibility to infections, including those caused by Streptococcus pneumoniae. Why RA is associated with increased susceptibility to S. pneumoniae is poorly understood. This study aims to assess the effects of RA and B‐cell depletion therapy on naturally acquired antibody responses to 289 S. pneumoniae protein antigens using a novel protein array. Methods: IgG responses to S. pneumoniae were characterised in serum from RA patients and disease controls (myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)) using whole‐cell ELISA, a flow cytometry opsonisation assay and an S. pneumoniae protein array. For the RA patients, results were compared before and after B‐cell depletion therapy. Results: Compared to a well‐characterised disease control group of ME/CFS patients, RA patients had reduced antibody responses to multiple S. pneumoniae protein antigens, with significant IgG recognition of approximately half the number of antigens along with reduced median strengths of these responses. Reduction in multiple array antigen‐specific responses also correlated with reduced IgG opsonisation of S. pneumoniae. Although B‐cell depletion therapy with rituximab did not reduce overall IgG recognition of S. pneumoniae in the RA group, it was associated with marked disruption of pre‐existing IgG repertoire to protein antigens in individual patients. Conclusion: These data show RA is associated with major disruption of naturally acquired adaptive immunity to S. pneumoniae, which can be assessed rapidly using a protein antigen array and is likely to contribute towards the increased incidence of pneumonia in patients with RA. [ABSTRACT FROM AUTHOR]

Developing recombinant Saccharomyces cerevisiae strains capable of transporting and fermenting cellobiose directly is a promising strategy for second-generation ethanol production from lignocellulosic biomass. In this study, we cloned and expressed in the S. cerevisiae CEN.PK2-1C strain an intracellular β-glucosidase (SpBGL7) from Spathaspora passalidarum and co-expressed the cellobiose transporter SiHXT2.4 from Scheffersomyces illinoinensis, and two putative transporters, one from Candida tropicalis (CtCBT1 gene), and one from Meyerozyma guilliermondii (MgCBT2 gene). While all three transporters allowed cell growth on cellobiose, only the MgCBT2 permease allowed cellobiose fermentation, although cellobiose consumption was incomplete. The analysis of the β-glucosidase and transport activities revealed that the cells stopped consuming cellobiose due to a drop in the transport activity. Since ubiquitinylation of lysine residues at the N- or C-terminal domains of the permease are involved in the endocytosis and degradation of sugar transporters, we constructed truncated versions of the permease lacking lysine residues at the C-terminal domain (MgCBT2ΔC), and at both the C- and N-terminal domain (MgCBT2ΔNΔC) and co-expressed these permeases with the SpBGL7 β-glucosidase in an industrial strain. While the strain harboring the MgCBT2ΔC transporter continued to produce incomplete cellobiose fermentations as the wild-type MgCBT2 permease, the strain with the MgCBT2ΔNΔC permease was able to consume and ferment all the cellobiose present in the medium. Thus, our results highlight the importance of expressing cellobiose transporters lacking lysine at the N- and C-terminal domains for efficient cellobiose fermentation by recombinant S. cerevisiae. [ABSTRACT FROM AUTHOR]

ABSTRACT: Key performance indicators (KPI) are essential to decision-making in an organization, but the approach to analysis and composition used in the formulation of the KPIs can lead to errors. Analysis based only on averages does not allow for discriminating between variations that are natural to the process or special cases which require investigation. The use of control charts can identify this differentiation. However, when several charts are presented encompassing different measurement units and scales, systemic interpretation can be impaired. To assist in this interpretation, this research study aimed at proposing a method to facilitate the analysis of control charts when multiple indicators are employed in the monitoring of agricultural operations. Based on the data obtained over 26 weeks from a mechanized sugarcane (Saccharum officinarum L.) harvesting front, six indicators were defined and analyzed through individual control charts and, systemically, through a standardized group control chart. Results show that the points identified as being outside the control zone (special causes of variation) according to the standardized group control chart were the same as those identified by the six individual charts, which demonstrates the potential of this method to summarize the information with no loss of quality of analysis.

Summary: B and T cells collaborate to drive autoimmune disease (AID). Historically, B- and T-cell (B–T cell) co-interaction was targeted through different pathways such as alemtuzumab, abatacept, and dapirolizumab with variable impact on B-cell depletion (BCD), whereas the majority of patients with AID including rheumatoid arthritis, systemic lupus erythematosus, multiple sclerosis, and organ transplantation benefit from targeted BCD with anti-CD20 monoclonal antibodies such as rituximab, ocrelizumab, or ofatumumab. Refractory AID is a significant problem for patients with incomplete BCD with a greater frequency of IgD−CD27+ switched memory B cells, CD19+CD20− B cells, and plasma cells that are not directly targeted by anti-CD20 antibodies, whereas most lymphoid tissue plasma cells express CD19. Furthermore, B–T-cell collaboration is predominant in lymphoid tissues and at sites of inflammation such as the joint and kidney, where BCD may be inefficient, due to limited access to key effector cells. In the treatment of cancer, chimeric antigen receptor (CAR) T-cell therapy and T-cell engagers (TCE) that recruit T cells to induce B-cell cytotoxicity have delivered promising results for anti-CD19 CAR T-cell therapies, the CD19 TCE blinatumomab and CD20 TCE such as mosunetuzumab, glofitamab, or epcoritamab. Limited evidence suggests that anti-CD19 CAR T-cell therapy may be effective in managing refractory AID whereas we await evaluation of TCE for use in non-oncological indications. Therefore, here, we discuss the potential mechanistic advantages of novel therapies that rely on T cells as effector cells to disrupt B–T-cell collaboration toward overcoming rituximab-resistant AID. This graphical abstract compares the hypothetical timelines of CD19 CAR T-cell therapy (green line) and CD19-TCE (purple line) in the context of autoimmune disease flare. CAR T-cell therapy is often limited to specialized centers due to its high-production costs, labor-intensive process, delayed effector T-cell pool establishment, and tolerability issues with prerequisite toxic lymphodepleting chemotherapy, potentially restricting its use and impacting patient outcomes. In contrast, CD19-TCB, readily available and immediately deployable upon disease flare detection, mitigates the risks associated with disease progression due to delays in CAR T-cell therapy access. Graphical Abstract [ABSTRACT FROM AUTHOR]

Copyright of Saúde Coletiva is the property of MPM Comunicacao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The development of low-cost miniaturized thermal cameras has expanded the use of remotely sensed surface temperature and promoted advances in applications involving proximal and aerial data acquisition. However, deriving accurate temperature readings from these cameras is often challenging due to the sensitivity of the sensor, which changes according to the internal temperature. Moreover, the photogrammetry processing required to produce orthomosaics from aerial images can also be problematic and introduce errors to the temperature readings. In this study, we assessed the performance of the FLIR Lepton 3.5 camera in both proximal and aerial conditions based on precision and accuracy indices derived from reference temperature measurements. The aerial analysis was conducted using three flight altitudes replicated along the day, exploring the effect of the distance between the camera and the target, and the blending mode configuration used to create orthomosaics. During the tests, the camera was able to deliver results within the accuracy reported by the manufacturer when using factory calibration, with a root mean square error (RMSE) of 1.08 °C for proximal condition and ≤3.18 °C during aerial missions. Results among different flight altitudes revealed that the overall precision remained stable (R² = 0.94–0.96), contrasting with the accuracy results, decreasing towards higher flight altitudes due to atmospheric attenuation, which is not accounted by factory calibration (RMSE = 2.63–3.18 °C). The blending modes tested also influenced the final accuracy, with the best results obtained with the average (RMSE = 3.14 °C) and disabled mode (RMSE = 3.08 °C). Furthermore, empirical line calibration models using ground reference targets were tested, reducing the errors on temperature measurements by up to 1.83 °C, with a final accuracy better than 2 °C. Other important results include a simplified co-registering method developed to overcome alignment issues encountered during orthomosaic creation using non-geotagged thermal images, and a set of insights and recommendations to reduce errors when deriving temperature readings from aerial thermal imaging.