IκB kinase-α coordinates BRD4 and JAK/STAT signaling to subvert DNA damage-based anticancer therapy.

Activation of the IκB kinase (IKK) complex has recurrently been linked to colorectal cancer (CRC) initiation and progression. However, identification of downstream effectors other than NF-κB has remained elusive. Here, analysis of IKK-dependent substrates in CRC cells after UV treatment revealed that phosphorylation of BRD4 by IKK-α is required for its chromatin-binding at target genes upon DNA damage. Moreover, IKK-α induces the NF-κB-dependent transcription of the cytokine LIF, leading to STAT3 activation, association with BRD4 and recruitment to specific target genes. IKK-α abrogation results in defective BRD4 and STAT3 functions and consequently irreparable DNA damage and apoptotic cell death upon different stimuli. Simultaneous inhibition of BRAF-dependent IKK-α activity, BRD4, and the JAK/STAT pathway enhanced the therapeutic potential of 5-fluorouracil combined with irinotecan in CRC cells and is curative in a chemotherapy-resistant xenograft model. Finally, coordinated expression of LIF and IKK-α is a poor prognosis marker for CRC patients. Our data uncover a functional link between IKK-α, BRD4, and JAK/STAT signaling with clinical relevance.

Detection of elusive DNA copy-number variations in hereditary disease and cancer through the use of noncoding and off-target sequencing reads.

Copy-number variants (CNVs) play a substantial role in the molecular pathogenesis of hereditary disease and cancer, as well as in normal human interindividual variation. However, they are still rather difficult to identify in mainstream sequencing projects, especially involving exome sequencing, because they often occur in DNA regions that are not targeted for analysis. To overcome this problem, we developed OFF-PEAK, a user-friendly CNV detection tool that builds on a denoising approach and the use of "off-target" DNA reads, which are usually discarded by sequencing pipelines. We benchmarked OFF-PEAK on data from targeted sequencing of 96 cancer samples, as well as 130 exomes of individuals with inherited retinal disease from three different populations. For both sets of data, OFF-PEAK demonstrated excellent performance (>95% sensitivity and >80% specificity vs. experimental validation) in detecting CNVs from in silico data alone, indicating its immediate applicability to molecular diagnosis and genetic research.

Assessment of patient-reported outcomes measures in heart failure: a systematic review.

Heart failure (HF) is a prevalent global disease, particularly impacting developed countries. With the world's aging population, HF's impact on the quantity and quality of life is expected to grow. This review aims to ascertain the frequency, characteristics, and properties of all patient-reported outcomes measures (PROMs) studied in HF patients. We searched Ovid/Medline and Web of Science for original articles about PROMs performed in adults with HF. Using pre-established quality criteria for measurement properties, an overall rating was assigned to evaluate and compare different instruments. The quality of evidence was assessed with the COSMIN risk of bias checklist. Of 4283 records identified, we reviewed 296 full-text documents and included 64 papers, involving 30,185 participants. Thirty different PROMs were identified, with 14 specifically designed for HF being the most commonly used. Minnesota Living with Heart Failure (MLHF) and Kansas City Cardiomyopathy Questionnaire (KCCQ) were evaluated 16 and 13 times, respectively, demonstrating good psychometric properties. The MacNew Heart Disease Health-Related Quality of Life Questionnaire, a common heart disease-specific instrument, exhibited negative performances across various psychometric measures. Evidence for generic instruments was scant and unremarkable and they proved to be less responsive in HF populations. MLHF and KCCQ emerged as the most commonly used and well-supported PROMs, with robust overall evidence. They are comprehensive and accurate instruments, particularly suitable for application in clinical practice and research. Future research should explore how computer-adapted instruments can enhance precision, reduce respondent burden, and improve communication between clinicians and patients, thereby promoting more efficient and patient-centered services.

Knee landmarks detection via deep learning for automatic imaging evaluation of trochlear dysplasia and patellar height.

OBJECTIVES: To develop and validate a deep learning-based approach to automatically measure the patellofemoral instability (PFI) indices related to patellar height and trochlear dysplasia in knee magnetic resonance imaging (MRI) scans. METHODS: A total of 763 knee MRI slices from 95 patients were included in the study, and 3393 anatomical landmarks were annotated for measuring sulcus angle (SA), trochlear facet asymmetry (TFA), trochlear groove depth (TGD) and lateral trochlear inclination (LTI) to assess trochlear dysplasia, and Insall-Salvati index (ISI), modified Insall-Salvati index (MISI), Caton Deschamps index (CDI) and patellotrochlear index (PTI) to assess patellar height. A U-Net based network was implemented to predict the landmarks' locations. The successful detection rate (SDR) and the mean absolute error (MAE) evaluation metrics were used to evaluate the performance of the network. The intraclass correlation coefficient (ICC) was also used to evaluate the reliability of the proposed framework to measure the mentioned PFI indices. RESULTS: The developed models achieved good accuracy in predicting the landmarks' locations, with a maximum value for the MAE of 1.38 ± 0.76 mm. The results show that LTI, TGD, ISI, CDI and PTI can be measured with excellent reliability (ICC > 0.9), and SA, TFA and MISI can be measured with good reliability (ICC > 0.75), with the proposed framework. CONCLUSIONS: This study proposes a reliable approach with promising applicability for automatic patellar height and trochlear dysplasia assessment, assisting the radiologists in their clinical practice. CLINICAL RELEVANCE STATEMENT: The objective knee landmarks detection on MRI images provided by artificial intelligence may improve the reproducibility and reliability of the imaging evaluation of trochlear anatomy and patellar height, assisting radiologists in their clinical practice in the patellofemoral instability assessment. KEY POINTS: • Imaging evaluation of patellofemoral instability is subjective and vulnerable to substantial intra and interobserver variability. • Patellar height and trochlear dysplasia are reliably assessed in MRI by means of artificial intelligence (AI). • The developed AI framework provides an objective evaluation of patellar height and trochlear dysplasia enhancing the clinical practice of the radiologists.

Genetic profile of syndromic retinitis pigmentosa in Portugal.

PURPOSE: Retinitis pigmentosa (RP) comprises a genetically and clinically heterogeneous group of inherited retinal degenerations, where 20-30% of patients exhibit extra-ocular manifestations (syndromic RP). Understanding the genetic profile of RP has important implications for disease prognosis and genetic counseling. This study aimed to characterize the genetic profile of syndromic RP in Portugal. METHODS: Multicenter, retrospective cohort study. Six Portuguese healthcare providers identified patients with a clinical diagnosis of syndromic RP and available genetic testing results. All patients had been previously subjected to a detailed ophthalmologic examination and clinically oriented genetic testing. Genetic variants were classified according to the American College of Medical Genetics and Genomics; only likely pathogenic or pathogenic variants were considered relevant for disease etiology. RESULTS: One hundred and twenty-two patients (53.3% males) from 100 families were included. Usher syndrome was the most frequent diagnosis (62.0%), followed by Bardet-Biedl (19.0%) and Senior-Løken syndromes (7.0%). Deleterious variants were identified in 86/100 families for a diagnostic yield of 86.0% (87.1% for Usher and 94.7% for Bardet-Biedl). A total of 81 genetic variants were identified in 25 different genes, 22 of which are novel. USH2A and MYO7A were responsible for most type II and type I Usher syndrome cases, respectively. BBS1 variants were the cause of Bardet-Biedl syndrome in 52.6% of families. Best-corrected visual acuity (BCVA) records were available at baseline and last visit for 99 patients (198 eyes), with a median follow-up of 62.0 months. The mean BCVA was 56.5 ETDRS letters at baseline (Snellen equivalent ~ 20/80), declining to 44.9 ETDRS letters (Snellen equivalent ~ 20/125) at the last available follow-up (p < 0.001). CONCLUSION: This is the first multicenter study depicting the genetic profile of syndromic RP in Portugal, thus contributing toward a better understanding of this heterogeneous disease group. Usher and Bardet-Biedl syndromes were found to be the most common types of syndromic RP in this large Portuguese cohort. A high diagnostic yield was obtained, highlighting current genetic testing capabilities in providing a molecular diagnosis to most affected individuals. This has major implications in determining disease-related prognosis and providing targeted genetic counseling for syndromic RP patients in Portugal.

Human-in-the-Loop Optimization of Knee Exoskeleton Assistance for Minimizing User's Metabolic and Muscular Effort.

Lower limb exoskeletons have the potential to mitigate work-related musculoskeletal disorders; however, they often lack user-oriented control strategies. Human-in-the-loop (HITL) controls adapt an exoskeleton's assistance in real time, to optimize the user-exoskeleton interaction. This study presents a HITL control for a knee exoskeleton using a CMA-ES algorithm to minimize the users' physical effort, a parameter innovatively evaluated using the interaction torque with the exoskeleton (a muscular effort indicator) and metabolic cost. This work innovates by estimating the user's metabolic cost within the HITL control through a machine-learning model. The regression model estimated the metabolic cost, in real time, with a root mean squared error of 0.66 W/kg and mean absolute percentage error of 26% (n = 5), making faster (10 s) and less noisy estimations than a respirometer (K5, Cosmed). The HITL reduced the user's metabolic cost by 7.3% and 5.9% compared to the zero-torque and no-device conditions, respectively, and reduced the interaction torque by 32.3% compared to a zero-torque control (n = 1). The developed HITL control surpassed a non-exoskeleton and zero-torque condition regarding the user's physical effort, even for a task such as slow walking. Furthermore, the user-specific control had a lower metabolic cost than the non-user-specific assistance. This proof-of-concept demonstrated the potential of HITL controls in assisted walking.

Mitochondrial DNA control region typing from highly degraded skeletal remains by single-multiplex next-generation sequencing.

Poor nuclear DNA preservation from highly degraded skeletal remains is the most limiting factor for the genetic identification of individuals. Mitochondrial DNA (mtDNA) typing, and especially of the control region (CR), using next-generation sequencing (NGS), enables retrieval of valuable genetic information in forensic contexts where highly degraded human skeletal remains are the only source of genetic material. Currently, NGS commercial kits can type all mtDNA-CR in fewer steps than the conventional Sanger technique. The PowerSeq CRM Nested System kit (Promega Corporation) employs a nested multiplex-polymerase chain reaction (PCR) strategy to amplify and index all mtDNA-CR in a single reaction. Our study analyzes the success of mtDNA-CR typing of highly degraded human skeletons using the PowerSeq CRM Nested System kit. We used samples from 41 individuals from different time periods to test three protocols (M1, M2, and M3) based on modifications of PCR conditions. To analyze the detected variants, two bioinformatic procedures were compared: an in-house pipeline and the GeneMarker HTS software. The results showed that many samples were not analyzed when the standard protocol (M1) was used. In contrast, the M3 protocol, which includes 35 PCR cycles and longer denaturation and extension steps, successfully recovered the mtDNA-CR from highly degraded skeletal samples. Mixed base profiles and the percentage of damaged reads were both indicators of possible contamination and can provide better results if used together. Furthermore, our freely available in-house pipeline can provide variants concordant with the forensic software.

Ultra-processed food consumption deteriorates the profile of micronutrients consumed by Portuguese adults and elderly: the UPPER project.

PURPOSE: This study aims to describe micronutrient intake according to food processing degree and to investigate the association between the dietary share of ultra-processed foods and micronutrient inadequacies in a representative sample of Portuguese adult and elderly individuals. METHODS: Cross-sectional data from the National Food, Nutrition and Physical Activity Survey (2015/2016) were used. Food consumption data were collected through two 24-h food recalls, and food items were classified according to the NOVA system. Linear regression models were used to assess the association between the micronutrient density and the quintiles of ultra-processed food consumption-crude and adjusted. Negative Binomial regressions were performed to measure the prevalence ratio of micronutrient inadequacy according to ultra-processed food quintiles. RESULTS: For adults, all evaluated vitamins had significantly lower content in the fraction of ultra-processed foods compared to unprocessed or minimally processed foods, except vitamin B2. For the elderly, out of ten evaluated vitamins, seven presented significantly less content in ultra-processed foods compared to non-processed ones. The higher energy contribution of ultra-processed foods in adults was associated with a lower density of vitamins and minerals. This association was not observed in the elderly. For adults, compared with the first quintile of ultra-processed food consumption, the fifth quintile was positively associated with inadequate intakes of vitamin B6 (PR 1.51), vitamin C (PR 1.32), folate (PR 1.14), magnesium (PR 1.21), zinc (PR 1.33), and potassium (PR 1.19). CONCLUSION: Our results corroborate the importance of public health actions that promote a reduction in the consumption of ultra-processed foods.

Health-related quality of life of women with breast cancer being treated with hormone therapy: A scoping review.

OBJECTIVE: To map the evidence available in the literature on the health-related quality of life of women with breast cancer using hormone therapy. DATA SOURCES: This review followed the Joanna Briggs Institute methodological recommendations and Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews reporting guidelines. Searches were performed in nine databases using descriptors, synonyms and keywords; grey literature was also included. The review protocol was registered with the Open Science Framework under doi: http://doi.org/10.17605/OSF.IO/347FM. Inclusion criteria were established according to the Population, Concept, and Context strategy. The selection of studies was performed by two independent reviewers with the aid of RAYYAN software and disagreements were resolved by a third reviewer. The main information from the included articles was grouped into textual categories and presented by means of a narrative synthesis. DATA SUMMARY: A total of 5419 records were identified, of which 42 studies fully met the eligibility criteria. Most were multicenter studies (42.9%) and randomized controlled trials (62%). Most studies addressed anastrozole (39.5%), letrozole (34.2%), and tamoxifen (26.3%), which were studied alone or in combination. The most widely used health-related quality-of-life assessment tool was the EORTC-QLQ-C30. The concomitant use of hormone therapy and cyclin-dependent kinase inhibitors 4 and 6 showed improvement in health-related quality of life. CONCLUSION: In recent years there has been an increase in studies focused on health-related quality of life, and the evidence pointed to relevant information on health-related quality of life and the use of endocrine therapy, tamoxifen in combination with aromatase inhibitors, as well as aromatase inhibitor alone and the use of cyclin-dependent kinase 4 and 6.

Human-Robot Joint Misalignment, Physical Interaction, and Gait Kinematic Assessment in Ankle-Foot Orthoses.

Lower limb exoskeletons and orthoses have been increasingly used to assist the user during gait rehabilitation through torque transmission and motor stability. However, the physical human-robot interface (HRi) has not been properly addressed. Current orthoses lead to spurious forces at the HRi that cause adverse effects and high abandonment rates. This study aims to assess and compare, in a holistic approach, human-robot joint misalignment and gait kinematics in three fixation designs of ankle-foot orthoses (AFOs). These are AFOs with a frontal shin guard (F-AFO), lateral shin guard (L-AFO), and the ankle modulus of the H2 exoskeleton (H2-AFO). An experimental protocol was implemented to assess misalignment, fixation displacement, pressure interactions, user-perceived comfort, and gait kinematics during walking with the three AFOs. The F-AFO showed reduced vertical misalignment (peak of 1.37 ± 0.90 cm, p-value < 0.05), interactions (median pressures of 0.39-3.12 kPa), and higher user-perceived comfort (p-value < 0.05) when compared to H2-AFO (peak misalignment of 2.95 ± 0.64 and pressures ranging from 3.19 to 19.78 kPa). F-AFO also improves the L-AFO in pressure (median pressures ranging from 8.64 to 10.83 kPa) and comfort (p-value < 0.05). All AFOs significantly modified hip joint angle regarding control gait (p-value < 0.01), while the H2-AFO also affected knee joint angle (p-value < 0.01) and gait spatiotemporal parameters (p-value < 0.05). Overall, findings indicate that an AFO with a frontal shin guard and a sports shoe is effective at reducing misalignment and pressure at the HRI, increasing comfort with slight changes in gait kinematics.

Validation of the Portuguese version of the supportive care needs survey short-form questionnaire (SCNS-SF34-Pt) and the breast cancer supplementary module (SCNS-BR8-Pt).

OBJECTIVE: This study aimed to test the psychometric properties of the Portuguese Supportive Care Needs Survey-Short Form-34 (SCNS-SF34-Pt) and its breast cancer-specific complementary module (SCNS-BR8-Pt). A further aim was to characterize Portuguese Breast Cancer Survivors' (BCS) unmet supportive care needs, using these measures. METHODS: A convenient sample of BCS was recruited from five hospitals in Portugal and invited to complete SCNS-SF34-Pt and SCNS-BR8-Pt, EORTCQLQC30 and QLQBR23, the Generalized Anxiety Disorder, and the Patient Health-Questionnaire. The validity (i.e. convergent, discriminant and convergent validity) and reliability of SCNS-SF34-Pt and SCNS-BR8-Pt were statistically evaluated. BCS' unmet supportive care needs were descriptively assessed. FINDINGS: 336 BCS participated in the study. A four-factor solution was produced for SCNS-SF34-Pt. This solution included the Physical and daily living needs, Psychological needs, Sexuality needs, and Health system, information, and patient support needs dimensions (73% of the total variance; Cronbach's alpha=.82 to .97). SCNS-SF34-Pt demonstrated good convergent validity. It could also discriminate between known-groups regarding age, disease staging, treatment performed, and ECOG performance status. SCNS-BR8-Pt revealed a single-factor structure (62% of the total variance; Cronbach's alpha=.91).Portuguese BCS' most prevalent unmet supportive care needs were associated with the Psychological, and Physical and daily living domains. Fear of cancer spreading, the inability to do things as usual, and lack of energy/tiredness were perceived as issues requiring further supportive care. CONCLUSIONS: SCNS-SF34-Pt and the SCNS-BR8-Pt are valid and reliable tools to assess Portuguese BCS' unmet supportive care needs. Fear of cancer spreading and lack of energy/tiredness concerns should be a target of supportive care services.

Extracellular Vesicles Isolation from Large Volume Samples Using a Polydimethylsiloxane-Free Microfluidic Device.

Extracellular vesicles (EV) have many attributes important for biomedicine; however, current EV isolation methods require long multi-step protocols that generally involve bulky equipment that cannot be easily translated to clinics. Our aim was to design a new cyclic olefin copolymer-off-stoichiometry thiol-ene (COC-OSTE) asymmetric flow field fractionation microfluidic device that could isolate EV from high-volume samples in a simple and efficient manner. We tested the device with large volumes of urine and conditioned cell media samples, and compared it with the two most commonly used EV isolation methods. Our device was able to separate particles by size and buoyancy, and the attained size distribution was significantly smaller than other methods. This would allow for targeting EV size fractions of interest in the future. However, the results were sample dependent, with some samples showing significant improvement over the current EV separation methods. We present a novel design for a COC-OSTE microfluidic device, based on bifurcating asymmetric flow field-flow fractionation (A4F) technology, which is able to isolate EV from large volume samples in a simple, continuous-flow manner. Its potential to be mass-manufactured increases the chances of implementing EV isolation in a clinical or industry-friendly setting, which requires high repeatability and throughput.

Extracellular vesicles as a source of prostate cancer biomarkers in liquid biopsies: a decade of research.

Prostate cancer is a global cancer burden and considerable effort has been made through the years to identify biomarkers for the disease. Approximately a decade ago, the potential of analysing extracellular vesicles in liquid biopsies started to be envisaged. This was the beginning of a new exciting area of research investigating the rich molecular treasure found in extracellular vesicles to identify biomarkers for a variety of diseases. Vesicles released from prostate cancer cells and cells of the tumour microenvironment carry molecular information about the disease that can be analysed in several biological fluids. Numerous studies document the interest of researchers in this field of research. However, methodological issues such as the isolation of vesicles have been challenging. Remarkably, novel technologies, including those based on nanotechnology, show promise for the further development and clinical use of extracellular vesicles as liquid biomarkers. Development of biomarkers is a long and complicated process, and there are still not many biomarkers based on extracellular vesicles in clinical use. However, the knowledge acquired during the last decade constitutes a solid basis for the future development of liquid biopsy tests for prostate cancer. These are urgently needed to bring prostate cancer treatment to the next level in precision medicine.

Effects of urinary extracellular vesicles from prostate cancer patients on the transcriptomes of cancer-associated and normal fibroblasts.

BACKGROUND: Increasing evidence suggests that cancer-derived extracellular vesicles (EVs) alter the phenotype and functions of fibroblasts and trigger the reprogramming of normal fibroblasts into cancer-associated fibroblasts (CAFs). Here, we for the first time studied the effects of urinary EVs from PC patients and healthy males on the transcriptional landscape of prostate CAFs and normal foreskin fibroblasts. METHODS: Patient-derived prostate fibroblast primary cultures PCF-54 and PCF-55 were established from two specimens of PC tissues. EVs were isolated from urine samples of 3 patients with PC and 2 healthy males and used for the treatment of prostate fibroblast primary cultures and normal foreskin fibroblasts. The EV-treated fibroblasts were subjected to RNA sequencing analysis. RESULTS: RNA sequencing analysis showed that the fibroblast cultures differed significantly in their response to urinary EVs. The transcriptional response of foreskin fibroblasts to the urinary EVs isolated from PC patients and healthy controls was very similar and mostly related to the normal functions of fibroblasts. On the contrary, PCF-54 cells responded very differently - EVs from PC patients elicited transcriptional changes related to the regulation of the cell division and chromosome segregation, whereas EVs from healthy males affected mitochondrial respiration. In PCF-55 cells, EVs from both, PC-patients and controls induced the expression of a number of chemokines such as CCL2, CCL13, CXCL1, CXCL8, whereas pathways related to regulation of apoptotic signaling and production of cell adhesion molecules were triggered specifically by EVs from PC patients. CONCLUSION: This study demonstrates that urinary EVs from PC patients and healthy controls elicit distinct transcriptional responses in prostate CAFs and supports the idea that EVs contribute to the generation of functional heterogeneity of CAFs. Moreover, this study suggests that the changes in the gene expression pattern in EV recipient cells might serve as a novel type of functional cancer biomarkers.

Intraocular pressure after myopic laser refractive surgery measured with a new Goldmann convex prism: correlations with GAT and ORA.

BACKGROUND: The purpose of this study is to describe measurements using a newly developed modified Goldmann convex tonometer (CT) 1 year after myopic laser refractive surgery. Intraocular pressure (IOP) measurements were compared with IOP values obtained by Goldmann applanation tonometer (GAT), and Ocular Response Analyzer (ORA). METHODS: Prospective double-masked study performed on thirty eyes of thirty patients that underwent laser in situ keratomileusis (LASIK; n = 19) or photorefractive keratectomy (PRK; n = 11). IOP was measured before and 3 and 12 months after surgery. Intraclass correlation coefficient (ICC) and Bland-Altman plot were calculated to assess the agreement between GAT, CT, IOPg (Goldmann-correlated IOP) and IOPcc (corneal-compensated IOP) from ORA. RESULTS: Twelve months after LASIK, IOP measured with CT showed the best correlation with IOP measured with GAT before surgery (GATpre) (ICC = 0.886, 95% CI: 0.703-0.956) (15.60 ± 3.27 vs 15.80 ± 3.22; p < 0.000). However, a moderate correlation was found for IOP measured with IOPcc and CT 12 months after LASIK (ICC = 0.568, 95% CI: - 0.185 - 0.843) (15.80 ± 3.22 vs 12.87 ± 2.77; p < 0.004). Twelve months after PRK, CT showed a weak correlation (ICC = - 0.266, 95% CI: - 3.896 - 0.663), compared to GATpre (17.30 ± 3.47 vs 16.01 ± 1.45; p < 0.642), as well as poor correlation (ICC = 0.256, 95% CI: - 0.332 - 0.719) with IOPcc (17.30 ± 3.47 vs 13.38 ± 1.65; p < 0.182). CONCLUSIONS: Twelve months after LASIK, IOP measured with CT strongly correlated with GAT before surgery and could therefore provide an alternative method for measuring IOP after this surgery. More studies regarding this new convex prism are needed to assess its accuracy.

Patients' pathways to cancer care in Tanzania: documenting and addressing social inequalities in reaching a cancer diagnosis.

BACKGROUND: This article investigates the extent and sources of late diagnosis of cancer in Tanzania, demonstrating how delayed diagnosis was patterned by inequities rooted in patients' socio-economic background and by health system responses. It provides evidence to guide equity-focused policies to accelerate cancer diagnosis. METHODS: Tanzanian cancer patients (62) were interviewed in 2019. Using a structured questionnaire, respondents were encouraged to recount their pathways from first symptoms to diagnosis, treatment, and in some cases check-ups as survivors. Patients described their recalled sequence of events and actions, including dates, experiences and expenditures at each event. Socio-demographic data were also collected, alongside patients' perspectives on their experience. Analysis employed descriptive statistics and qualitative thematic analysis. RESULTS: Median delay, between first symptoms that were later identified as indicating cancer and a cancer diagnosis, was almost 1 year (358 days). Delays were strongly patterned by socio-economic disadvantage: those with low education, low income and non-professional occupations experienced longer delays before diagnosis. Health system experiences contributed to these socially inequitable delays. Many patients had moved around the health system extensively, mainly through self-referral as symptoms worsened. This "churning" required out-of-pocket payments that imposed a severely regressive burden on these largely low-income patients. Causes of delay identified in patients' narratives included slow recognition of symptoms by facilities, delays in diagnostic testing, delays while raising funds, and recourse to traditional healing often in response to health system barriers. Patients with higher incomes and holding health insurance that facilitated access to the private sector had moved more rapidly to diagnosis at lower out-of-pocket cost. CONCLUSIONS: Late diagnosis is a root cause, in Tanzania as in many low- and middle-income countries, of cancer treatment starting at advanced stages, undermining treatment efficacy and survival rates. While Tanzania's policy of free public sector cancer treatment has made it accessible to patients on low incomes and without insurance, reaching a diagnosis is shown to have been for these respondents slower and more expensive the greater their socio-economic disadvantage. Policy implications are drawn for moving towards greater social justice in access to cancer care.

Do surrogates predict patient preferences more accurately after a physician-led discussion about advance directives? A randomized controlled trial.

BACKGROUND: Caregivers frequently assume the role of surrogate decision-makers but often are unable to accurately predict patients' preferences. This trial aims to find if the use of the Advance Directives documents as a communication tool, improves the agreement between patients and caregivers. METHODS: This trial occurred in a palliative care service of a Portuguese hospital center. A prospective, single-blinded, controlled, randomized trial, enrolling patients and caregivers as a dyad was conducted. Participants individually fulfilled an Advance Directive document, in which patients reported their end-of-life preferences and caregivers reported their decisions as patients' health surrogates. Dyads were randomly assigned to the Intervention or the Control group, in which the physician respectively promoted an open discussion about patients' Advance Directives or evaluated patients' clinical condition. Caregivers' Advance Directives as surrogates were collected one month later. Proportions of agreement and Cohen's κ were used to access agreement and reliability, respectively, between the dyads. RESULTS: Results from 58 dyads were analyzed. We observed an improvement in agreement between the caregivers' answers and the patients' wishes on two-thirds (8/12) of the answers, in the Intervention group, contrasting to one-quarter (3/12) of the answers, in the Control group, despite statistical significance in differences wasn´t obtained. CONCLUSIONS: Although not reaching statistical significance, the results suggest that discussions of advance directives with physicians may lead to better prepared surrogates. TRIAL REGISTRATION: ClinicalTrials.gov ID NCT05090072 . Retrospectively registered on 22/10/2021.

Inertial Data-Based AI Approaches for ADL and Fall Recognition.

The recognition of Activities of Daily Living (ADL) has been a widely debated topic, with applications in a vast range of fields. ADL recognition can be accomplished by processing data from wearable sensors, specially located at the lower trunk, which appears to be a suitable option in uncontrolled environments. Several authors have addressed ADL recognition using Artificial Intelligence (AI)-based algorithms, obtaining encouraging results. However, the number of ADL recognized by these algorithms is still limited, rarely focusing on transitional activities, and without addressing falls. Furthermore, the small amount of data used and the lack of information regarding validation processes are other drawbacks found in the literature. To overcome these drawbacks, a total of nine public and private datasets were merged in order to gather a large amount of data to improve the robustness of several ADL recognition algorithms. Furthermore, an AI-based framework was developed in this manuscript to perform a comparative analysis of several ADL Machine Learning (ML)-based classifiers. Feature selection algorithms were used to extract only the relevant features from the dataset's lower trunk inertial data. For the recognition of 20 different ADL and falls, results have shown that the best performance was obtained with the K-NN classifier with the first 85 features ranked by Relief-F (98.22% accuracy). However, Ensemble Learning classifier with the first 65 features ranked by Principal Component Analysis (PCA) presented 96.53% overall accuracy while maintaining a lower classification time per window (0.039 ms), showing a higher potential for its usage in real-time scenarios in the future. Deep Learning algorithms were also tested. Despite its outcomes not being as good as in the prior procedure, their potential was also demonstrated (overall accuracy of 92.55% for Bidirectional Long Short-Term Memory (LSTM) Neural Network), indicating that they could be a valid option in the future.

Fall Risk Assessment Using Wearable Sensors: A Narrative Review.

Recently, fall risk assessment has been a main focus in fall-related research. Wearable sensors have been used to increase the objectivity of this assessment, building on the traditional use of oversimplified questionnaires. However, it is necessary to define standard procedures that will us enable to acknowledge the multifactorial causes behind fall events while tackling the heterogeneity of the currently developed systems. Thus, it is necessary to identify the different specifications and demands of each fall risk assessment method. Hence, this manuscript provides a narrative review on the fall risk assessment methods performed in the scientific literature using wearable sensors. For each identified method, a comprehensive analysis has been carried out in order to find trends regarding the most used sensors and its characteristics, activities performed in the experimental protocol, and algorithms used to classify the fall risk. We also verified how studies performed the validation process of the developed fall risk assessment systems. The identification of trends for each fall risk assessment method would help researchers in the design of standard innovative solutions and enhance the reliability of this assessment towards a homogeneous benchmark solution.

A Review on Locomotion Mode Recognition and Prediction When Using Active Orthoses and Exoskeletons.

Understanding how to seamlessly adapt the assistance of lower-limb wearable assistive devices (active orthosis (AOs) and exoskeletons) to human locomotion modes (LMs) is challenging. Several algorithms and sensors have been explored to recognize and predict the users' LMs. Nevertheless, it is not yet clear which are the most used and effective sensor and classifier configurations in AOs/exoskeletons and how these devices' control is adapted according to the decoded LMs. To explore these aspects, we performed a systematic review by electronic search in Scopus and Web of Science databases, including published studies from 1 January 2010 to 31 August 2022. Sixteen studies were included and scored with 84.7 ± 8.7% quality. Decoding focused on level-ground walking along with ascent/descent stairs tasks performed by healthy subjects. Time-domain raw data from inertial measurement unit sensors were the most used data. Different classifiers were employed considering the LMs to decode (accuracy above 90% for all tasks). Five studies have adapted the assistance of AOs/exoskeletons attending to the decoded LM, in which only one study predicted the new LM before its occurrence. Future research is encouraged to develop decoding tools considering data from people with lower-limb impairments walking at self-selected speeds while performing daily LMs with AOs/exoskeletons.