Search

Background: Hereditary transthyretin amyloidosis (ATTRv amyloidosis) is an inherited disease, where the study of family history holds importance. This study evaluates the changes of age-of-onset (AOO) and other age-related clinical factors within and among families affected by ATTRv amyloidosis., Methods: We analysed information from 934 trees, focusing on family, parents, probands and siblings relationships. We focused on 1494 female and 1712 male symptomatic ATTRV30M patients. Results are presented alongside a comparison of current with historical records. Clinical and genealogical indicators identify major changes., Results: Overall, analysis of familial data shows the existence of families with both early and late patients (1/6). It identifies long familial follow-up times since patient families tend to be diagnosed over several years. Finally, results show a large difference between parent-child and proband-patient relationships (20-30 years)., Conclusions: This study reveals that there has been a shift in patient profile, with a recent increase in male elderly cases, especially regarding probands. It shows that symptomatic patients exhibit less variability towards siblings, when compared to other family members, namely the transmitting ancestors' age of onset. This can influence genetic counselling guidelines.

Objective: To estimate the comparative efficacy of ciltacabtagene autoleucel (cilta-cel) versus idecabtagene vicleucel (ide-cel) in patients with relapsed/refractory multiple myeloma (RRMM) treated with 2-4 prior lines of therapy., Methods: Matching adjusted indirect comparison (MAICs) were performed using individual patient-level data (IPD) for cilta-cel from CARTITUDE-1 and CARTITUDE-4 and published aggregated data for ide-cel from KarMMa-3. Cilta-cel patients who met inclusion criteria from KarMMa-3 were selected, and outcomes were compared against data for ide-cel using simulated IPD derived from aggregate-level data from KarMMa-3. Patient characteristics were adjusted by reweighting cilta-cel IPD to match the distribution of prognostic factors in KarMMa-3. Comparative efficacy was estimated for response outcomes using a weighted logistic regression analysis and for progression-free survival using a weighted Cox proportional hazards model., Results: Patients treated with cilta-cel were 1.2 times more likely to achieve overall response (relative response ratio [RR]: 1.18 [95% confidence interval: 1.03-1.34]; p  = 0.04), 1.3 times more likely to achieve very good partial response or better (RR: 1.34 [1.15-1.57]; p  = 0.003), and 1.9 times more likely to achieve complete response or better (RR: 1.91 [1.54-2.37]; p  < 0.0001) versus ide-cel patients from KarMMa-3. Cilta-cel was associated with a significant 49% reduction in risk of disease progression or death versus ide-cel (hazard ratio: 0.51 [95% confidence interval: 0.31, 0.84]; p  = 0.0078)., Conclusion: For patients with triple-class exposed RRMM treated with 2-4 prior lines of treatment, cilta-cel was found to provide superior clinical benefit over ide-cel in terms of response and progression-free survival.

Aim: The phase III randomized controlled trial (RCT) CARTITUDE-4 (NCT04181827) demonstrated superiority of CARVYKTI (ciltacabtagene autoleucel; cilta-cel) over daratumumab, pomalidomide and dexamethasone (DPd) and pomalidomide, bortezomib and dexamethasone (PVd) for relapsed/refractory multiple myeloma (RRMM) patients who have received one to three prior line(s) of therapy (LOT[s]) including an immunomodulatory agent and a proteasome inhibitor, and are refractory to lenalidomide. These analyses estimate the relative efficacy between cilta-cel and other common treatment regimens, for which no direct comparative evidence is available. Materials & methods: Patient data were available from the CARTITUDE-4, CASTOR, CANDOR and APOLLO RCTs. Imbalances between cohorts on key patient characteristics were adjusted for using inverse probability of treatment weighting (IPTW). Relative efficacies were estimated with response rate ratios (RRs) and 95% confidence intervals (CIs) for overall response rate (ORR), very good partial response or better rate (≥VGPR) and complete response or better rate (≥CR), and with hazard ratios (HRs) and 95% CIs for progression-free survival (PFS). Sensitivity analyses using different analytical methods and additional covariates were explored. Results: Key characteristics were well balanced across cohorts after IPTW. Cilta-cel showed statistically significant benefit in PFS (HRs: 0.11-0.51), ≥VGPR (RRs: 1.51-5.13) and ≥CR (RRs: 2.90-35.24) versus all comparators, and statistically significant improvements in ORR over most comparator regimens (RRs: 1.22-1.90). Results were consistent across sensitivity analyses. Conclusion: Cilta-cel demonstrated benefit over other common treatment regimens, highlighting its potential to become a new standard of care option for lenalidomide-refractory RRMM patients with one to three prior LOT(s). These comparisons help to demonstrate the improved efficacy of cilta-cel in countries where the standard of care may differ from DPd/PVd.

In the management of early-stage breast cancer (BC), lymph nodes (LNs) are typically characterised using the One-Step Nucleic Acid Amplification (OSNA) assay, a standard procedure for assessing subclinical metastasis in sentinel LNs (SLNs). The pivotal role of LNs in coordinating the immune response against BC is often overlooked. Our aim was to improve prognostic information provided by the OSNA assay and explore immune-related gene signatures in SLNs. The expression of an immune gene panel was analysed in SLNs from 32 patients with Luminal A early-stage BC (cT1-T2 N0). Using an unsupervised approach based on these expression values, this study identified two clusters, regardless of the SLN invasion: one evidencing an adaptive anti-tumoral immune response, characterised by an increase in naive B cells, follicular T helper cells, and activated NK cells; and another with a more undifferentiated response, with an increase in the activated-to-resting dendritic cells (DCs) ratio. Through a protein-protein interaction (PPI) network, we identified seven immunoregulatory hub genes: CD80 , CD40 , TNF , FCGR3A , CD163 , FCGR3B , and CCR2 . This study shows that, in Luminal A early-stage BC, SLNs gene expression studies enable the identification of distinct immune profiles that may influence prognosis stratification and highlight key genes that could serve as potential targets for immunotherapy.

Background: Non-syndromic orofacial cleft (NSOC) is a complex phenotype, involving multiple genetic and environmental factors. Association studies exploring the genetic susceptibility to this prevalent oral malformation show variability of results in different populations. Using a candidate gene approach, we aimed to verify the role of four single-nucleotide polymorphisms (SNPs) in the susceptibility to NSOC in Portuguese patients., Methods: A total of 254 non-consanguineous individuals of Portuguese were recruited, including 120 patients with NSOC and 134 controls. About 92% of these patients had non-syndromic cleft lip with or without cleft palate (NSCL/P) and 8% had only non-syndromic cleft palate (NSCP). SNPs in the MTHFR (rs1801133), IRF6 (rs642961), PAX7 (rs742071) and TP63 (rs9332461) genes were studied, using a real-time approach with TaqMan probes. Allelic, genotypic, dominant, recessive and over-dominant models were explored using a chi-squared test. Adjusted p-value was calculated for multiple comparisons using the Benjamini-Hochberg false discovery rate (FDR)., Results: All SNPs were in Hardy-Weinberg equilibrium. For MTHFR, IRF6, and PAX7 SNPs, no statistically significant difference was highlighted for any of the evaluated models. For TP63 SNP, data fitted an over-dominant model, with a protective effect for heterozygotes (OR 1.897; CI 95% [1.144-3.147]; p < .016, when comparing controls vs. cases), but significance was lost when applying adjusted p-value for multiple comparisons (4 × 5 tests)., Conclusion: In this Portuguese population, there was no evidence of an association between the evaluated SNPs and NSOC. For TP63 SNP, the possibility of a protective effect of heterozygotes should be further investigated., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Breast cancer remains a leading cause of mortality among women, with molecular subtypes significantly influencing prognosis and treatment strategies. Currently, identifying the molecular subtype of cancer requires a biopsy-a specialized, expensive, and time-consuming procedure, often yielding to results that must be supported with additional biopsies due to technique errors or tumor heterogeneity. This study introduces a novel approach for predicting breast cancer molecular subtypes using mammography images and advanced artificial intelligence (AI) methodologies. Using the OPTIMAM imaging database, 1397 images from 660 patients were selected. The pretrained deep learning model ResNet-101 was employed to classify tumors into five subtypes: Luminal A, Luminal B1, Luminal B2, HER2, and Triple Negative. Various classification strategies were studied: binary classifications (one vs. all others, specific combinations) and multi-class classification (evaluating all subtypes simultaneously). To address imbalanced data, strategies like oversampling, undersampling, and data augmentation were explored. Performance was evaluated using accuracy and area under the receiver operating characteristic curve (AUC). Binary classification results showed a maximum average accuracy and AUC of 79.02% and 64.69%, respectively, while multi-class classification achieved an average AUC of 60.62% with oversampling and data augmentation. The most notable binary classification was HER2 vs. non-HER2, with an accuracy of 89.79% and an AUC of 73.31%. Binary classification for specific combinations of subtypes revealed an accuracy of 76.42% for HER2 vs. Luminal A and an AUC of 73.04% for HER2 vs. Luminal B1. These findings highlight the potential of mammography-based AI for non-invasive breast cancer subtype prediction, offering a promising alternative to biopsies and paving the way for personalized treatment plans.

Background: Cytoreductive surgery with Hyperthermic Intraperitoneal Chemotherapy (CR-HIPEC) is a locorregional surgical therapy applied in patients with peritoneal-only metastatic disease of primary abdominal malignancies. Integrated in a multimodal treatment, CR-HIPEC is associated with increased overall survival. In cases of peritoneal-site only relapse, it may be carried out more than once., Methods: Patients who received a CR-HIPEC between January 2016 and December 2020 at Instituto Português de Oncologia do Porto, Portugal were included in a unicentric, retrospective, observational study. Short- and long-term outcomes after surgery were analyzed., Results: In this period, 259 CR-HIPEC were performed on 248 patients. Of these, 31 were CR-HIPEC repeats, with 6 being the third HIPEC in the same patient. Of the 31 cases, 15 (48.4 %) had an appendicular origin. Mean PCI in re-HIPEC group was 10.6 (SD ± 7.1). No significant differences in baseline characteristics between the first and re-HIPEC groups were found, except for mean PCI, higher in the 1st HIPEC group (p = 0.047). In re-HIPEC group, major complications rate (CT-CAE 3-4) was 12.9 % (n = 4), without postoperative mortality. The 1st and re-HIPEC group had similar morbidity rates and hospitalization time. With a median follow-up time of 44 months, relapse rate after repeat CR-HIPEC was 45.2 % (n = 14), with a mean overall survival (OS) of 68.7 months and 5-year OS of 78 %., Conclusions: Repeat CR-HIPEC is a safe approach with an acceptable complication rate for its complexity, associated with a survival benefit in selected patients. It should be presented as a valid therapeutic option in recurrent peritoneal disease., Competing Interests: Declarations of competing interest None., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Malignant hyperfunctioning thyroid nodules are rare and more likely to occur in follicular cancer types rather than papillary variants. The authors present a case of a papillary thyroid carcinoma associated with a hyperfunctioning nodule., Methods: A single adult patient submitted to total thyroidectomy with the presence of thyroid carcinoma within hyperfunctioning nodules was selected. Additionally, brief literature was conducted., Results: An asymptomatic 58-year-old male was subjected to routine blood analysis and a TSH level of <0.003 mIU/L was found. Ultrasonography revealed a 21 mm solid, hypoechoic, and heterogenous nodule with microcalcifications in the right lobe. A fine needle aspiration guided by ultrasound resulted in a follicular lesion of undetermined significance. A 99m Tc thyroid scintigram was followed and identified a right-sided hyperfunctioning nodule. Another cytology was performed and a papillary thyroid carcinoma was derived as a result. The patient underwent a total thyroidectomy. Postoperative histology confirmed the diagnosis and a tumor-free margin with no vascular or capsular invasions., Conclusion: Hyperfunctioning malignant nodules are a rare association, although a careful approach should be led since major clinical implications arise. Selective fine needle aspiration in all suspicious ≥1 cm nodules should be considered.

Ultrasound (US) imaging is used in the diagnosis and monitoring of COVID-19 and breast cancer. The presence of Speckle Noise (SN) is a downside to its usage since it decreases lesion conspicuity. Filters can be used to remove SN, but they involve time-consuming computation and parameter tuning. Several researchers have been developing complex Deep Learning (DL) models (150,000-500,000 parameters) for the removal of simulated added SN, without focusing on the real-world application of removing naturally occurring SN from original US images. Here, a simpler (<30,000 parameters) Convolutional Neural Network Autoencoder (CNN-AE) to remove SN from US images of the breast and lung is proposed. In order to do so, simulated SN was added to such US images, considering four different noise levels (σ = 0.05, 0.1, 0.2, 0.5). The original US images (N = 1227, breast + lung) were given as targets, while the noised US images served as the input. The Structural Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR) were used to compare the output of the CNN-AE and of the Median and Lee filters with the original US images. The CNN-AE outperformed the use of these classic filters for every noise level. To see how well the model removed naturally occurring SN from the original US images and to test its real-world applicability, a CNN model that differentiates malignant from benign breast lesions was developed. Several inputs were used to train the model (original, CNN-AE denoised, filter denoised, and noised US images). The use of the original US images resulted in the highest Matthews Correlation Coefficient (MCC) and accuracy values, while for sensitivity and negative predicted values, the CNN-AE-denoised US images (for higher σ values) achieved the best results. Our results demonstrate that the application of a simpler DL model for SN removal results in fewer misclassifications of malignant breast lesions in comparison to the use of original US images and the application of the Median filter. This shows that the use of a less-complex model and the focus on clinical practice applicability are relevant and should be considered in future studies.

Introduction: Hereditary transthyretin amyloidosis (ATTRv amyloidosis) is a rare neurological hereditary disease clinically characterized as severe, progressive, and life-threatening while the age of onset represents the moment in time when the first symptoms are felt. In this study, we present and discuss our results on the study, development, and evaluation of an approach that allows for time-to-event prediction of the age of onset, while focusing on genealogical feature construction., Materials and Methods: This research was triggered by the need to answer the medical problem of when will an asymptomatic ATTRv patient show symptoms of the disease. To do so, we defined and studied the impact of 77 features (ranging from demographic and genealogical to familial disease history) we studied and compared a pool of prediction algorithms, namely, linear regression (LR), elastic net (EN), lasso (LA), ridge (RI), support vector machines (SV), decision tree (DT), random forest (RF), and XGboost (XG), both in a classification as well as a regression setting; we assembled a baseline (BL) which corresponds to the current medical knowledge of the disease; we studied the problem of predicting the age of onset of ATTRv patients; we assessed the viability of predicting age of onset on short term horizons, with a classification framing, on localized sets of patients (currently symptomatic and asymptomatic carriers, with and without genealogical information); and we compared the results with an out-of-bag evaluation set and assembled in a different time-frame than the original data in order to account for data leakage., Results: Currently, we observe that our approach outperforms the BL model, which follows a set of clinical heuristics and represents current medical practice. Overall, our results show the supremacy of SV and XG for both the prediction tasks although impacted by data characteristics, namely, the existence of missing values, complex data, and small-sized available inputs., Discussion: With this study, we defined a predictive model approach capable to be well-understood by medical professionals, compared with the current practice, namely, the baseline approach (BL), and successfully showed the improvement achieved to the current medical knowledge., Competing Interests: TC received support from Pfizer, Ionis, Alnylam, and Biogen to attend to scientific meetings. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Pedroto, Coelho, Jorge and Mendes-Moreira.)

Currently, breast cancer is the most commonly diagnosed type of cancer worldwide. Digital Breast Tomosynthesis (DBT) has been widely accepted as a stand-alone modality to replace Digital Mammography, particularly in denser breasts. However, the image quality improvement provided by DBT is accompanied by an increase in the radiation dose for the patient. Here, a method based on 2D Total Variation (2D TV) minimization to improve image quality without the need to increase the dose was proposed. Two phantoms were used to acquire data at different dose ranges (0.88-2.19 mGy for Gammex 156 and 0.65-1.71 mGy for our phantom). A 2D TV minimization filter was applied to the data, and the image quality was assessed through contrast-to-noise ratio (CNR) and the detectability index of lesions before and after filtering. The results showed a decrease in 2D TV values after filtering, with variations of up to 31%, increasing image quality. The increase in CNR values after filtering showed that it is possible to use lower doses (-26%, on average) without compromising on image quality. The detectability index had substantial increases (up to 14%), especially in smaller lesions. So, not only did the proposed approach allow for the enhancement of image quality without increasing the dose, but it also improved the chances of detecting small lesions that could be overlooked.

Objectives: Diet is important for the appropriate development and maturation of young amateur athletes. The aim of this study was to determine whether young gymnasts were consuming adequate amounts of nutrients, particularly calcium and iron., Methods: This cross-sectional survey was conducted in Portugal's Almada and Lisbon regions in 2020. To determine if participants' diet was adequate, weight, height, and skinfold measurements were taken. Dietary consumption was examined using two 24-h recalls. We collected data from 66 participants (60% females, 12-18 y of age), of whom 82% had normal weight and 39% had ideal body fat., Results: The daily total energy intake (TEI) was1605 ± 601 kcal. Of the TEI, 19%, 31%, and 50% were comprised of protein, fat, and carbohydrates, respectively. The most often consumed protein sources were poultry and ultra-processed meat products (52% and 45%, respectively). The average daily consumption of calcium and iron was 626 ± 293 and 9 ± 3 mg, respectively. Only 2 of the 66 participants had calcium intake within recommended levels, and 1of 5 had iron intake within recommended levels, the percentage of which was lower in girls than boys (7.5% versus 38.5%, P < 0.05)., Conclusions: Despite having a sufficient macronutrient distribution, Portuguese gymnasts consume a high amount of ultra-processed items and a low amount of calcium and iron. The low proportion of female gymnasts with adequate iron consumption is cause for worry in sports nutrition., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Localization is a crucial skill in mobile robotics because the robot needs to make reasonable navigation decisions to complete its mission. Many approaches exist to implement localization, but artificial intelligence can be an interesting alternative to traditional localization techniques based on model calculations. This work proposes a machine learning approach to solve the localization problem in the RobotAtFactory 4.0 competition. The idea is to obtain the relative pose of an onboard camera with respect to fiducial markers (ArUcos) and then estimate the robot pose with machine learning. The approaches were validated in a simulation. Several algorithms were tested, and the best results were obtained by using Random Forest Regressor, with an error on the millimeter scale. The proposed solution presents results as high as the analytical approach for solving the localization problem in the RobotAtFactory 4.0 scenario, with the advantage of not requiring explicit knowledge of the exact positions of the fiducial markers, as in the analytical approach.

Breast cancer was the most diagnosed cancer around the world in 2020. Screening programs, based on mammography, aim to achieve early diagnosis which is of extreme importance when it comes to cancer. There are several flaws associated with mammography, with one of the most important being tissue overlapping that can result in both lesion masking and fake-lesion appearance. To overcome this, digital breast tomosynthesis takes images (slices) at different angles that are later reconstructed into a 3D image. Having in mind that the slices are planar images where tissue overlapping does not occur, the goal of the work done here was to develop a deep learning model that could, based on the said slices, classify lesions as benign or malignant. The developed model was based on the work done by Muduli et. al, with a slight change in the fully connected layers and in the regularization done. In total, 77 DBT volumes-39 benign and 38 malignant-were available. From each volume, nine slices were taken, one where the lesion was most visible and four above/below. To increase the quantity and the variability of the data, common data augmentation techniques (rotation, translation, mirroring) were applied to the original images three times. Therefore, 2772 images were used for training. Data augmentation techniques were then applied two more times-one set used for validation and one set used for testing. Our model achieved, on the testing set, an accuracy of 93.2% while the values of sensitivity, specificity, precision, F1-score, and Cohen's kappa were 92%, 94%, 94%, 94%, and 0.86, respectively. Given these results, the work done here suggests that the use of single-slice DBT can compare to state-of-the-art studies and gives a hint that with more data, better augmentation techniques and the use of transfer learning might overcome the use of mammograms in this type of studies.

Developing innovative systems and operations to monitor forests and send alerts in dangerous situations, such as fires, has become, over the years, a necessary task to protect forests. In this work, a Wireless Sensor Network (WSN) is employed for forest data acquisition to identify abrupt anomalies when a fire ignition starts. Even though a low-power LoRaWAN network is used, each module still needs to save power as much as possible to avoid periodic maintenance since a current consumption peak happens while sending messages. Moreover, considering the LoRaWAN characteristics, each module should use the bandwidth only when essential. Therefore, four algorithms were tested and calibrated along real and monitored events of a wildfire. The first algorithm is based on the Exponential Smoothing method, Moving Averages techniques are used to define the other two algorithms, and the fourth uses the Least Mean Square. When properly combined, the algorithms can perform a pre-filtering data acquisition before each module uses the LoRaWAN network and, consequently, save energy if there is no necessity to send data. After the validations, using Wildfire Simulation Events (WSE), the developed filter achieves an accuracy rate of 0.73 with 0.5 possible false alerts. These rates do not represent a final warning to firefighters, and a possible improvement can be achieved through cloud-based server algorithms. By comparing the current consumption before and after the proposed implementation, the modules can save almost 53% of their batteries when is no demand to send data. At the same time, the modules can maintain the server informed with a minimum interval of 15 min and recognize abrupt changes in 60 s when fire ignition appears.

Introduction: The SARS-CoV-2 pandemic has reshaped the global landscape as we know it and had a tremendous effect on healthcare systems around the world. However, its impact on oral healthcare is still to be fully assessed. The aim of this study was to understand if and how COVID-19 affected the demand and performance of oral healthcare, taking the Clinical and Academic Centre of Coimbra as an example, more specifically, the Department of Stomatology of the Coimbra Hospital and University Centre and the Dentistry Department of the Faculty of Medicine of the University of Coimbra., Material and Methods: An observational study was designed for collecting the data of a series of key oral healthcare indicators: number of appointments; referrals from primary healthcare; missed appointments; number of surgeries performed in the operating room; number of biopsies; number of patients admitted through the emergency department and epidemiologic parameters over two 18-month periods between September 2018 and August 2021: pre-COVID-19 and during the COVID-19 pandemic, with the latter divided in four stages. A statistical analysis which included descriptive and inferential procedures was then performed, with an established significance level of 5% and the application of parametric tests, t-Student test for a sample and for independent samples and One-Way ANOVA for the variance analysis., Results: There was a general decline in all indicators comparing the pre-COVID-19 with the COVID-19 period, with a reduction of 50.61% in the number of appointments, 44.06% in referrals, 24.41% in surgeries, 26.30% in biopsies and 32.33% in patients seen in the Emergency Room. The number of missed appointments also increased by 181.82%. All variations revealed statistically significant differences (p < 0.05). The individual COVID-19 stage analysis, when compared with the pre-COVID-19 reference, and variance analysis of these different stages also showed statistically significant differences (p < 0.05 and p < 0.001), except for the number of biopsies during the third and fourth stages., Conclusion: The results of this study suggest that the SARS-CoV-2 pandemic has had a considerable impact on oral healthcare demand and performance. However, results also show a remarkable adjustment and improvement in the provided care, with a positive evolution throughout the COVID-19 period.

The One Step Nucleic Acid Amplification (OSNA) is being adopted worldwide for sentinel lymph nodes (SLNs) staging in breast cancer (BC). As major disadvantage, OSNA precludes prognostic information based on structural evaluation of SLNs. Our aim is to identify biomarkers related to tumor-microenvironment interplay exploring gene expression data from the OSNA remaining lysate. This study included 32 patients with early stage hormone receptors-positive BC. Remaining OSNA lysates were prepared for targeted RNA-sequencing analysis. Identification of differentially expressed genes (DEGs) was performed by DESeq2 in R and data analysis in STATA. The results show that, in metastatic SLNs, several genes were upregulated: KRT7 , VTCN1 , CD44 , GATA3 , ALOX15B , RORC , NECTIN2 , LRG1 , CD276 , FOXM1 and IGF1R . Hierarchical clustering analysis revealed three different clusters. The identified DEGs codify proteins mainly involved in cancer aggressiveness and with impact in immune response. The overexpression of the immune suppressive genes VTCN1 and CD276 may explain that no direct evidence of activation of immune response in metastatic SLNs was found. We show that OSNA results may be improved incorporating microenvironment-related biomarkers that may be useful in the future for prognosis stratification and immunotherapy selection. As OSNA assay is being implemented for SLNs staging in other cancers, this approach could also have a wider utility.

Introduction: The phase 3 APOLLO study demonstrated significantly better progression-free survival (PFS) and clinical responses with daratumumab, pomalidomide, and dexamethasone (D-Pd) versus pomalidomide and dexamethasone (Pd) in patients with relapsed/refractory multiple myeloma (RRMM). On the basis of these results and those from the phase 1b EQUULEUS trial, D-Pd was approved in this patient population. In the absence of head-to-head data comparing D-Pd with further standard of care (SOC) therapies, indirect treatment comparisons (ITCs) can provide important information to help optimize treatment selection. The objective of this study was to indirectly compare PFS improvement with D-Pd versus daratumumab, bortezomib, and dexamethasone (D-Vd) and D-Pd versus bortezomib and dexamethasone (Vd) in patients with RRMM., Methods: Patient-level data were from APOLLO, EQUULEUS, and CASTOR. Three methods of adjusting imbalances in baseline characteristics including stabilized inverse probability of treatment weighting (sIPTW), cardinality matching (CM), and propensity score matching (PSM) were initially considered. CM offers mathematically guaranteed largest matched sample meeting pre-specified maximum standardized mean difference criteria for matching covariates. sIPTW and PSM were based on propensity scores derived from logistic regression. Feasibility assessment of the PSM method returned too low effective sample size to support a meaningful comparison. CM was chosen as the base case and sIPTW as a sensitivity analysis., Results: After harmonized eligibility criteria were applied, 253, 104, and 122 patients from the D-Pd, D-Vd, and Vd cohorts, respectively, were included in the ITC analyses. Some imbalances in baseline characteristics were identified between D-Pd and D-Vd/Vd cohorts that remained after adjustment. PFS hazard ratios showed significant improvement for D-Pd over D-Vd and Vd for CM and sIPTW analyses., Conclusions: Results showed consistent PFS benefit for D-Pd versus D-Vd and Vd regardless of the adjustment technique used. These findings support the use of D-Pd versus D-Vd or Vd in patients with difficult-to-treat RRMM., Trial Registration: NCT03180736; NCT02136134, NCT01998971., (© 2022. The Author(s).)

Breast cancer was the most diagnosed cancer in 2020. Several thousand women continue to die from this disease. A better and earlier diagnosis may be of great importance to improving prognosis, and that is where Artificial Intelligence (AI) could play a major role. This paper surveys different applications of AI in Breast Imaging. First, traditional Machine Learning and Deep Learning methods that can detect the presence of a lesion and classify it into benign/malignant-which could be important to diminish reading time and improve accuracy-are analyzed. Following that, researches in the field of breast cancer risk prediction using mammograms-which may be able to allow screening programs customization both on periodicity and modality-are reviewed. The subsequent section analyzes different applications of augmentation techniques that allow to surpass the lack of labeled data. Finally, still concerning the absence of big datasets with labeled data, the last section studies Self-Supervised learning, where AI models are able to learn a representation of the input by themselves. This review gives a general view of what AI can give in the field of Breast Imaging, discussing not only its potential but also the challenges that still have to be overcome.

Drug-induced liver injury (DILI) is an unpredictable and feared side effect of antituberculosis treatment (AT). The present study aimed to identify clinical and genetic variables associated with susceptibility to AT-associated hepatotoxicity in patients with pulmonary tuberculosis treated with a standard protocol. Of 233 patients enrolled, 90% prospectively, 103 developed liver injury: 37 with mild and 66 with severe phenotype (DILI). All patients with mild hepatitis had a RUCAM score ≥4 and all patients with DILI had a RUCAM score ≥ 6. Eight clinical variables and variants in six candidate genes were assessed. A logistic multivariate regression analysis identified four risk factors for AT-DILI: age ≥ 55 years (OR:3.67; 95% CI:1.82−7.41; p < 0.001), concomitant medication with other hepatotoxic drugs (OR:2.54; 95% CI:1.23−5.26; p = 0.012), NAT2 slow acetylator status (OR:2.46; 95% CI:1.25−4.84; p = 0.009), and carriers of p.Val444Ala variant for ABCB11 gene (OR:2.06; 95%CI:1.02−4.17; p = 0.044). The statistical model explains 24.9% of the susceptibility to AT-DILI, with an 8.9 times difference between patients in the highest and in the lowest quartiles of risk scores. This study sustains the complex architecture of AT-DILI. Prospective studies should evaluate the benefit of NAT2 and ABCB11 genotyping in AT personalization, particularly in patients over 55 years.

Introduction: Many treatment regimens have been evaluated in transplant-ineligible (TIE) patients with newly diagnosed multiple myeloma (NDMM). The objective of this study was to compare the efficacy of relevant therapies for the treatment of TIE patients with NDMM., Methods: Progression-free survival (PFS) and overall survival (OS) from large randomised controlled trials (RCTs) evaluating different treatment options for TIE patients with NDMM were compared in a network meta-analysis (NMA). The NMA includes recent primary and long-term OS readouts from SWOG S0777, ENDURANCE, MAIA, and ALCYONE. Relevant trials were identified through a systematic literature review. Relative efficacy measures (i.e., hazard ratios [HRs] for PFS and OS) were extracted and synthesised in random-effects NMAs., Results: A total of 122 publications describing 45 unique RCTs was identified. Continuous lenalidomide/dexamethasone (Rd) was selected as the referent comparator. Daratumumab-containing treatments (daratumumab/lenalidomide/dexamethasone [D-Rd], daratumumab/bortezomib/melphalan/prednisone [D-VMP]) and bortezomib/lenalidomide/dexamethasone (VRd) had the highest probabilities of being more effective than Rd continuous for PFS (HR: D-Rd, 0.53; D-VMP, 0.57, VRd, 0.77) and OS (HR: D-Rd, 0.68; VRd, 0.77, D-VMP, 0.78). D-Rd had the highest chance of being ranked as the most effective treatment with respect to PFS and OS. Results using a smaller network focusing on only those regimens that are relevant in Europe were consistent with the primary analysis., Conclusions: These comparative effectiveness data may help inform treatment selection in TIE patients with NDMM., (© 2022. The Author(s).)

Plasmonic bio/chemical sensing based on optical fibers combined with molecularly imprinted nanoparticles (nanoMIPs), which are polymeric receptors prepared by a template-assisted synthesis, has been demonstrated as a powerful method to attain ultra-low detection limits, particularly when exploiting soft nanoMIPs, which are known to deform upon analyte binding. This work presents the development of a surface plasmon resonance (SPR) sensor in silica light-diffusing fibers (LDFs) functionalized with a specific nanoMIP receptor, entailed for the recognition of the protein human serum transferrin (HTR). Despite their great versatility, to date only SPR-LFDs functionalized with antibodies have been reported. Here, the innovative combination of an SPR-LFD platform and nanoMIPs led to the development of a sensor with an ultra-low limit of detection (LOD), equal to about 4 fM, and selective for its target analyte HTR. It is worth noting that the SPR-LDF-nanoMIP sensor was mounted within a specially designed 3D-printed holder yielding a measurement cell suitable for a rapid and reliable setup, and easy for the scaling up of the measurements. Moreover, the fabrication process to realize the SPR platform is minimal, requiring only a metal deposition step.

Purpose: As the most abundant neuropeptides in Central Nervous System, Substance P and Neuropeptide Y are arguably involved in the response to brain trauma. This study aims to characterize a new concept of multi-staged neuropeptide response to TBI., Methods: This study assessed Substance P, Neuropeptide Y, S100B, standard inflammatory parameters and ionic disturbance in TBI victims, with and without intracranial lesions, and healthy controls. In the group with intracranial lesions, blood samples were drawn until 6 h after initial trauma, at 48 h and 7 days post-TBI., Results: An early increase in Substance P (mean 613.463 ± 49.055 SE 6 h post-TBI with brain contusions vs. 441.441 ± 22.572 SE pg/dL control group) is evident. Concerning TBI without intraparenchymatous lesions, an increase in substance P is also present (825.60 ± 23.690 SE pg/dL). Following an initial increase and subsequent fall in NPY levels (45.997 ± 4.96 SE 6 h post-TBI vs. 32.395 ± 4.056 SE 48 h post-TBI vs. 19.700 ± 1.462 SE pg/mL control group), a late increase in NPY is obvious (43.268 ± 6.260 SE pg/mL 7 day post-TBI). Post-traumatic hypomagnesemia (0.754 ± 0.015 SE 6 h post-TBI vs. 0.897 ± 0.021 SE mmol/L control group) and a peak in S100B (95.668 ± 14.102 SE 6 h post-TBI vs. 30.187 ± 3.347 SE pg/mL control group) are also present., Conclusion: A multi-staged neuropeptide response to TBI is obvious and represents a potential therapeutic strategy for the treatment of intraparenchymal lesions and cerebral edema following TBI., (© 2020. Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: To characterise the posterior and total corneal astigmatism using colour point-source light-emitting diodes (LED) topography., Methods: In a prospective case series 400 eyes from 400 patients were evaluated by colour-LED topography. Only eyes with normal topographies were considered. The following parameters were studied: magnitude and distribution of SimK and posterior corneal astigmatism, correlation between SimK and posterior corneal astigmatism, and differences in magnitude and axis between total and anterior corneal astigmatism., Results: The mean SimK corneal astigmatism was 1.21 ± 0.94 D. The mean posterior corneal astigmatism was 0.37 ± 0.24 D. Posterior astigmatism was vertically oriented in 68% of eyes. Twenty-two percent of eyes showed a posterior corneal astigmatism ≥ 0.50 D. The correlation coefficients between SimK and posterior corneal astigmatism were: r 2  = 0.066; p = 0.371 in WTR eyes, r 2  = 0.112; p = 0.173 in ATR eyes and r 2  = -0.019; p = 0.879 in oblique eyes. A difference between SimK and total corneal astigmatism ≥ 0.50 D was found in 7% of eyes. A difference in axis between SimK and total corneal astigmatism ≥ 10° was found in 24% of eyes., Conclusions: The percentage of eyes with posterior corneal astigmatism ≥ 0.50 D and the differences between anterior and total corneal astigmatism were higher than those previously reported in the literature. Therefore, this study supports the consideration of total corneal astigmatism magnitude and axis is mandatory for a precise surgical correction of astigmatism., (© 2020. The Author(s), under exclusive licence to The Royal College of Ophthalmologists.)

Breast cancer affects thousands of women across the world, every year. Methods to predict risk of breast cancer, or to stratify women in different risk levels, could help to achieve an early diagnosis, and consequently a reduction of mortality. This paper aims to review articles that extracted texture features from mammograms and used those features along with machine learning algorithms to assess breast cancer risk. Besides that, deep learning methodologies that aimed for the same goal were also reviewed. In this work, first, a brief introduction to breast cancer statistics and screening programs is presented; after that, research done in the field of breast cancer risk assessment are analyzed, in terms of both methodologies used and results obtained. Finally, considerations about the analyzed papers are conducted. The results of this review allow to conclude that both machine and deep learning methodologies provide promising results in the field of risk analysis, either in a stratification in risk groups, or in a prediction of a risk score. Although promising, future endeavors in this field should consider the possibility of the implementation of the methodology in clinical practice.

Background: Preterm birth (PTB) is one of the major causes of neonatal morbidity and mortality worldwide. It is commonly accepted that the act of giving birth is the final step in a proinflammatory signaling cascade, orchestrated by an intrauterine milieu coupled to hormonal cues. Consequently, the inflammatory process plays a pivotal role during the pathogenesis of human labor, both in term and preterm deliveries. The ability of innate lymphoid cells (ILCs) to act as pro-inflammatory mediators arose the interest to study their role in normal and pathological pregnancies. The aim of this work was to analyze the relative frequencies of ILCs subsets in pregnancy and the levels of IL-4, IL-17, IL-22, and IFN-γ as inflammatory mediators. Accordingly, we hypothesized that changes in the proportions of ILCs subpopulations could be related to preterm birth., Methods: We analyzed 15 full-term delivery samples and six preterm delivery samples. In the full-term group (FTB) peripheral blood was taken during routine blood analysis, on 3 occasions: 1st, 2nd and 3rd trimester. After delivery, peripheral blood, cord blood and placenta were collected. In PTB group, peripheral blood samples were obtained on two occasions: before and 24 h after treatment with progesterone. We used flow cytometry to analyze ILCs in maternal peripheral blood, placenta, and cord blood samples. Maternal peripheral blood and cord blood samples were analyzed by enzyme-linked immunosorbent assay for IL-4, IL-17, IL-22, and IFN-γ plasma levels at the time of labor., Results: We observed significantly increased relative frequencies of ILC2 and ILC3 in the decidua, as well as an increase of ILC2 in cord blood samples in PTB group, compared to FTB samples. We also found a decrease in IFN-γ in peripheral blood samples of the PTB group, suggesting a functional withdrawal. Additionally, IL-4, IL-17, IL-22 levels were similar in PTB and FTB groups, denoting a relevant role in mediating labor., Conclusion: Our results suggest that ILC2 and ILC3 play a role in PTB by mediating an inflammatory response. Further work is necessary to evaluate the importance of ILCs in the regulation of labor.

Background: Multiple myeloma (MM) is the second most common hematological cancer worldwide and has significant morbidity and mortality and is increasing in incidence. While MM management costs are considerable, specific economic data at the country level remain scarce., Objective: This study assesses the burden and cost of MM in Portugal from the perspective of the National Health Service (NHS) to support the definition of health policies, resource allocation and patient care., Methods: Developed by the Portuguese Multiple Myeloma Group, this study considers the most recent available data. Burden of disease was measured using disability-adjusted life-years (DALYs). The cost of MM was estimated using a prevalence-based model that estimated direct costs for the NHS considering all costs associated with diagnosis, hospitalizations, surgeries, emergency visits, medical appointments, drugs and transportation. Costs were quantified based on the diagnosis-related group funding price, except for drug usage, which was calculated using the average hospital product stock price., Results: The burden of disease attributable to MM for 2018 was estimated at 8931 DALYs: 8570 resulting from premature deaths and 361 from disability. Average yearly direct costs per patients with MM amounted to €31,449 (year 2018 values). Total direct costs are estimated at €61 million per year., Conclusions: The mortality rate in MM means that most DALYs are due to years of life lost rather than years lost due to disability. This study generates comprehensive data on the burden and cost of MM in Portugal and provides updated insights into the costs associated with the management of MM.

Innate lymphoid cells (ILCs) are a new set of cells considered to be a part of the innate immune system. ILCs are classified into five subsets (according to their transcription factors and cytokine profile) as natural killer cells (NK cells), group 1 ILCs, group 2 ILCs, group 3 ILCs, and lymphoid tissue inducers (LTi). Functionally, these cells resemble the T helper population but lack the expression of recombinant genes, which is essential for the formation of T cell receptors. In this work, the authors address the distinction between peripheral and decidual NK cells, highlighting their diversity in ILC biology and its relevance to human pregnancy. ILCs are effector cells that are important in promoting immunity, inflammation, and tissue repair. Recent studies have directed their attention to ILC actions in pregnancy. Dysregulation or expansion of pro-inflammatory ILC populations as well as abnormal tolerogenic responses may directly interfere with pregnancy, ultimately resulting in pregnancy loss or adverse outcomes. In this review, we characterize these cells, considering recent findings and addressing knowledge gaps in perinatal medicine in the context of ILC biology. Moreover, we discuss the relevance of these cells not only to the process of immune tolerance, but also in disease., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Mendes, Areia, Rodrigues-Santos, Santos-Rosa and Mota-Pinto.)

Background: As genome sequencing projects grow rapidly, the diversity of organisms with recently assembled genome sequences peaks at an unprecedented scale, thereby highlighting the need to make gene functional annotations fast and efficient. However, the (high) quality of such annotations must be guaranteed, as this is the first indicator of the genomic potential of every organism. Automatic procedures help accelerating the annotation process, though decreasing the confidence and reliability of the outcomes. Manually curating a genome-wide annotation of genes, enzymes and transporter proteins function is a highly time-consuming, tedious and impractical task, even for the most proficient curator. Hence, a semi-automated procedure, which balances the two approaches, will increase the reliability of the annotation, while speeding up the process. In fact, a prior analysis of the annotation algorithm may leverage its performance, by manipulating its parameters, hastening the downstream processing and the manual curation of assigning functions to genes encoding proteins., Results: Here SamPler, a novel strategy to select parameters for gene functional annotation routines is presented. This semi-automated method is based on the manual curation of a randomly selected set of genes/proteins. Then, in a multi-dimensional array, this sample is used to assess the automatic annotations for all possible combinations of the algorithm's parameters. These assessments allow creating an array of confusion matrices, for which several metrics are calculated (accuracy, precision and negative predictive value) and used to reach optimal values for the parameters., Conclusions: The potential of this methodology is demonstrated with four genome functional annotations performed in merlin, an in-house user-friendly computational framework for genome-scale metabolic annotation and model reconstruction. For that, SamPler was implemented as a new plugin for the merlin tool.

The increasingly aging society in developed countries has raised attention to the role of technology in seniors' lives, namely concerning isolation-related issues. Independent seniors that live alone frequently neglect meals, hydration and proper medication-taking behavior. This work aims at eating and drinking recognition in free-living conditions for triggering smart reminders to autonomously living seniors, keeping system design considerations, namely usability and senior-acceptance criteria, in the loop. To that end, we conceived a new dataset featuring accelerometer and gyroscope wrist data to conduct the experiments. We assessed the performance of a single multi-class classification model when compared against several binary classification models, one for each activity of interest (eating vs. non-eating; drinking vs. non-drinking). Binary classification models performed consistently better for all tested classifiers ( k -NN, Naive Bayes, Decision Tree, Multilayer Perceptron, Random Forests, HMM). This evidence supported the proposal of a semi-hierarchical activity recognition algorithm that enabled the implementation of two distinct data stream segmentation techniques, the customization of the classification models of each activity of interest and the establishment of a set of restrictions to apply on top of the classification output, based on daily evidence. An F1-score of 97% was finally attained for the simultaneous recognition of eating and drinking in an all-day acquisition from one young user, and 93% in a test set with 31 h of data from 5 different unseen users, 2 of which were seniors. These results were deemed very promising towards solving the problem of food and fluids intake monitoring with practical systems which shall maximize user-acceptance.

The Gorlin-Goltz syndrome is a rare autosomal dominant hereditary condition, with complete penetrance and variable expressivity. Characterized by the appearance of multiple basaliomas, and often the development of keratocyst, it can also express itself by the presence of palmar/plantar depressions, calcification of brain sickle, and skeletal birth defects, although less frequently. This article presents two cases involving direct relatives, referred after the identification of several basaliomas and jaw cysts. After establishing the diagnosis, given the identification of three major criteria, the treatment consisted in the excision of the lesions followed, in one case, with vismodegib treatment resulting in complete remission. Gorlin-Goltz syndrome is therefore a multidisciplinary challenge, whose variable morbidity and high risk of recurrence make treatment and surveillance critical. However, new molecular targeted therapies have brought a new hope in treating these patients.

Ostertagiosis caused by Ostertagia ostertagi is considered the most important parasitosis in dairy cattle raised in temperate areas. The aim of this investigation was to determinate the prevalence of ostertagiosis in cattle slaughtered in São Miguel Island (SMI), Azores, the geographical distribution of positive cases, its economic impact and farmers awareness regarding preventive and control measurements against this parasitosis. From the 2000 animals sampled, 1282 presented lesions compatible with ostertagiosis representing a prevalence of 49.0% in young animals and 75.7% in adults. Positive animals had significantly worse carcass rating when slaughtered and the fat rating of positive uncastrated males older than 24months was also significantly lower. The presence of lesions compatible with ostertagiosis resulted in a total weight loss of 2.810.89kg (2.19kg mean weight loss per animal - 1.07% carcass weight drop), which extrapolating to the total of animals slaughtered in SMI in 2014 corresponds to a value of losses of roughly about 91.000.00€. Our data also indicate that ostertagiosis has a widespread distribution throughout the Island and that 85.7% of the farmers dewormed calves and 42.9% dewormed cows (only one administration was provided for each deworming). Data shows that ostertagiosis represents an important economical lost in dairy cattle from SMI and a significant lack of knowledge by farmers about the benefits of deworming and preventive management practices., (Copyright © 2016 Elsevier B.V. All rights reserved.)

The simultaneous multiple surface (SMS) design method is extended to include design of diffractive optical surfaces besides refractive and reflective ones. This method involves the simultaneous and direct (no optimization) calculation of diffractive and refractive/reflective surfaces. Using the phase-shift properties of diffractive elements as an extra degree of freedom, two rays for each point on each diffractive surface are controlled. Representative diffractive systems designed by the SMS method are shown.

PTCRIS (Portuguese Current Research Information System) is a program aiming at the creation and sustained development of a national integrated information ecosystem, to support research management according to the best international standards and practices. This paper reports on the experience of designing and prototyping a synchronization framework for PTCRIS based on ORCID (Open Researcher and Contributor ID). This framework embraces the "input once, re-use often" principle, and will enable a substantial reduction of the research output management burden by allowing automatic information exchange between the various national systems. The design of the framework followed best practices in rigorous software engineering, namely well-established principles in the research field of consistency management, and relied on formal analysis techniques and tools for its validation and verification. The notion of consistency between the services was formally specified and discussed with the stakeholders before the technical aspects on how to preserve said consistency were explored. Formal specification languages and automated verification tools were used to analyze the specifications and generate usage scenarios, useful for validation with the stakeholder and essential to certificate compliant services.

Non-uniform irradiance patterns over Multi-Junction Cells gives rise to power losses, especially when considering spectral irradiance distributions over different junctions. Thermal effects on Silicone-on-Glass lenses affect spectral irradiance distributions. A new Photovoltaic Concentrator (CPV), formed by nine optical channels, each one with a Köhler configuration, has been designed to overcome these effects at high concentrations for a large acceptance angle. A Fresnel Lens with a Variable Focal Point is proposed to prevent optical crosstalk in multichannel systems. When integrated into the concentrator, improves the acceptance angle. These designs are designed to fulfill the expected requirements of four junction CPV systems.

Introduction: In tissues and organs exposed to large pressure amplitude low frequency noise fibrosis occurs in the absence of inflammatory signs, which is thought to be a protective response. In the parotid gland the perivasculo-ductal connective tissue surrounds arteries, veins and the ductal tree. Perivasculo-ductal connective tissue is believed to function as a mechanical stabilizer of the glandular tissue., Material and Methods: In order to quantify the proliferation of perivasculo-ductal connective tissue in large pressure amplitude low frequency noise-exposed rats we used sixty Wistar rats which were equally divided into 6 groups. One group kept in silence, and the remaining five exposed to continuous large pressure amplitude low frequency noise: g1-168h (1 week); g2-504h (3 weeks); g3-840h (5 weeks); g4-1512h (9 weeks); and g5-2184h (13 weeks). After exposure, parotid glands were removed and the perivasculo-ductal connective tissue area was measured in all groups. We applied ANOVA statistical analysis, using SPSS 13.0., Results: The global trend is an increase in the average perivasculo-ductal connective tissue areas, that develops linearly and significantly with large pressure amplitude low frequency noise exposure time (p < 0.001)., Discussion: It has been suggested that the biological response to large pressure amplitude low frequency noise exposure is associated with the need to maintain structural integrity. The structural reinforcement would be achieved by increased perivasculo-ductal connective tissue., Conclusions: Hence, these results show that in response to large pressure amplitude low frequency noise exposure, rat parotid glands increase their perivasculo-ductal connective tissue.

Primary tumours of the heart are uncommon entities, cardiac myxomas being the most frequent. However, mitral valve myxomas are exceptionally rare. In the last 12 years, there have been 25 myxomas diagnosed at our institution, with only two of them originating from the mitral valve. Both patients were female, the first, 25, and the second, 72 years old. The younger patient was very symptomatic with a large mass, 4 cm long, which involved both leaflets causing significant obstruction to the left ventricular inflow. The second one had a smaller mass located at the atrial side of the posterior leaflet that only produced some flow divergence. Neither of them had constitutional nor embolic symptoms. Both patients were submitted to emergent surgical resection that in the first case involved the mitral valve and replacement with mechanical prosthesis. The macroscopic appearance of these tumours suggested a malignant aetiology which may represent somewhat different features of the myxomas when originating from the cardiac valves. Both patients are well reflecting the good prognosis of this illness after resection, although the younger patient was re-operated because of prosthetic valve obstruction and suspicion of recurrence that was not confirmed. Because of the illustrative images and different presentations, we found it interesting to report and discuss them together.