Rusfertide, a Hepcidin Mimetic, for Control of Erythrocytosis in Polycythemia Vera.

BACKGROUND: Polycythemia vera is a chronic myeloproliferative neoplasm characterized by erythrocytosis. Rusfertide, an injectable peptide mimetic of the master iron regulatory hormone hepcidin, restricts the availability of iron for erythropoiesis. The safety and efficacy of rusfertide in patients with phlebotomy-dependent polycythemia vera are unknown. METHODS: In part 1 of the international, phase 2 REVIVE trial, we enrolled patients in a 28-week dose-finding assessment of rusfertide. Part 2 was a double-blind, randomized withdrawal period in which we assigned patients, in a 1:1 ratio, to receive rusfertide or placebo for 12 weeks. The primary efficacy end point was a response, defined by hematocrit control, absence of phlebotomy, and completion of the trial regimen during part 2. Patient-reported outcomes were assessed by means of the modified Myeloproliferative Neoplasm Symptom Assessment Form (MPN-SAF) patient diary (scores range from 0 to 10, with higher scores indicating greater severity of symptoms). RESULTS: Seventy patients were enrolled in part 1 of the trial, and 59 were assigned to receive rusfertide (30 patients) or placebo (29 patients) in part 2. The estimated mean (±SD) number of phlebotomies per year was 8.7±2.9 during the 28 weeks before the first dose of rusfertide and 0.6±1.0 during part 1 (estimated difference, 8.1 phlebotomies per year). The mean maximum hematocrit was 44.5±2.2% during part 1 as compared with 50.0±5.8% during the 28 weeks before the first dose of rusfertide. During part 2, a response was observed in 60% of the patients who received rusfertide as compared with 17% of those who received placebo (P = 0.002). Between baseline and the end of part 1, rusfertide treatment was associated with a decrease in individual symptom scores on the MPN-SAF in patients with moderate or severe symptoms at baseline. During parts 1 and 2, grade 3 adverse events occurred in 13% of the patients, and none of the patients had a grade 4 or 5 event. Injection-site reactions of grade 1 or 2 in severity were common. CONCLUSIONS: In patients with polycythemia vera, rusfertide treatment was associated with a mean hematocrit of less than 45% during the 28-week dose-finding period, and the percentage of patients with a response during the 12-week randomized withdrawal period was greater with rusfertide than with placebo. (Funded by Protagonist Therapeutics; REVIVE ClinicalTrials.gov number, NCT04057040.).

Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing.

Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station's capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station's use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station's open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors.

Advancements in Home-Based Devices for Detecting Obstructive Sleep Apnea: A Comprehensive Study.

Obstructive Sleep Apnea (OSA) is a respiratory disorder characterized by frequent breathing pauses during sleep. The apnea-hypopnea index is a measure used to assess the severity of sleep apnea and the hourly rate of respiratory events. Despite numerous commercial devices available for apnea diagnosis and early detection, accessibility remains challenging for the general population, leading to lengthy wait times in sleep clinics. Consequently, research on monitoring and predicting OSA has surged. This comprehensive paper reviews devices, emphasizing distinctions among representative apnea devices and technologies for home detection of OSA. The collected articles are analyzed to present a clear discussion. Each article is evaluated according to diagnostic elements, the implemented automation level, and the derived level of evidence and quality rating. The findings indicate that the critical variables for monitoring sleep behavior include oxygen saturation (oximetry), body position, respiratory effort, and respiratory flow. Also, the prevalent trend is the development of level IV devices, measuring one or two signals and supported by prediction software. Noteworthy methods showcasing optimal results involve neural networks, deep learning, and regression modeling, achieving an accuracy of approximately 99%.

Development of a Framework for the Communication System Based on KNX for an Interactive Space for UX Evaluation.

Domotics (Home Automation) aims to improve the quality of life of people by integrating intelligent systems within inhabitable spaces. While traditionally associated with smart home systems, these technologies have potential for User Experience (UX) research. By emulating environments to test products and services, and integrating non-invasive user monitoring tools for emotion recognition, an objective UX evaluation can be performed. To achieve this objective, a testing booth was built and instrumented with devices based on KNX, an international standard for home automation, to conduct experiments and ensure replicability. A framework was designed based on Python to synchronize KNX systems with emotion recognition tools; the synchronization of these data allows finding patterns during the interaction process. To evaluate this framework, an experiment was conducted in a simulated laundry room within the testing booth to analyze the emotional responses of participants while interacting with prototypes of new detergent bottles. Emotional responses were contrasted with traditional questionnaires to determine the viability of using non-invasive methods. Using emulated environments alongside non-invasive monitoring tools allowed an immersive experience for participants. These results indicated that the testing booth can be implemented for a robust UX evaluation methodology.

Use of Robotic Platforms as a Tool to Support STEM and Physical Education in Developed Countries: A Descriptive Analysis.

The lack of interest of children at school is one of the biggest problems that Mexican education faces. Two important factors causing this lack of interest are the predominant methodology used in Mexican schools and the technology as a barrier for attention. The methodology that institutions have followed has become an issue because of its very traditional approach, with the professor giving all the theoretical material to the students while they listen and memorize the contents, and, if we add the issue of the growing access to technological devices for students, children carrying a phone are more likely to be distracted. This study aims to integrate technology through assistive robots as a beneficial tool for educators, in order to improve the attention span of students by making the learning process in multiple areas of the Mexican curriculum more dynamic, therefore obtaining better results. To prove this, four different approaches were implemented; three in elementary schools and one in higher education: the LEGO® robotic kit and the NAO robot for STEM (science, technology, engineering, and mathematics) teaching, the NAO robot for physical education (PE), and the PhantomX Hexapod, respectively. Each of these technological approaches was applied by considering both control and experimental groups, in order to compare the data and provide conclusions. Finally, this study proves that the attention span is indeed improved as a result of implementing robotic platforms during the teaching process, allowing the children to become more motivated during their PE class and become more proactive and retain more information during their STEM classes.

Automation Pyramid as Constructor for a Complete Digital Twin, Case Study: A Didactic Manufacturing System.

Nowadays, the concept of Industry 4.0 aims to improve factories' competitiveness. Usually, manufacturing production is guided by standards to segment and distribute its processes and implementations. However, industry 4.0 requires innovative proposals for disruptive technologies that engage the entire production process in factories, not just a partial improvement. One of these disruptive technologies is the Digital Twin (DT). This advanced virtual model runs in real-time and can predict, detect, and classify normal and abnormal operating conditions in factory processes. The Automation Pyramid (AP) is a conceptual element that enables the efficient distribution and connection of different actuators in enterprises, from the shop floor to the decision-making levels. When a DT is deployed into a manufacturing system, generally, the DT focuses on the low-level that is named field level, which includes the physical devices such as controllers, sensors, and so on. Thus, the partial automation based on the DT is accomplished, and the information between all manufacturing stages could be decremented. Hence, to achieve a complete improvement of the manufacturing system, all the automation pyramid levels must be included in the DT concept. An artificial intelligent management system could create an interconnection between them that can manage the information. As a result, this paper proposed a complete DT structure covering all automation pyramid stages using Artificial Intelligence (AI) to model each stage of the AP based on the Digital Twin concept. This work proposes a virtual model for each level of the traditional AP and the interactions among them to flow and control information efficiently. Therefore, the proposed model is a valuable tool in improving all levels of an industrial process. In addition, It is presented a case study where the DT concept for modular workstations underpins the development of technologies within the framework of the Automation Pyramid model is implemented into a didactic manufacturing system.

Driver's Personality and Behavior for Boosting Automobile Security and Sensing Health Problems Through Fuzzy Signal Detection Case Study: Mexico City.

Automobile security became an essential theme over the last years, and some automakers invested much money for collision avoidance systems, but personalization of their driving systems based on the user's behavior was not explored in detail. Furthermore, efficiency gains could be had with tailored systems. In Mexico, 80% of automobile accidents are caused by human beings; the remaining 20% are related to other issues such as mechanical problems. Thus, 80% represents a significant opportunity to improve safety and explore driving efficiency gains. Moreover, when driving aggressively, it could be connected with mental health as a post-traumatic stress disorder. This paper proposes a Tailored Collision Mitigation Braking System, which evaluates the driver's personality driving treats through signal detection theory to create a cognitive map that understands the driving personality of the driver. In this way, aggressive driving can be detected; the system is then trained to recognize the personality trait of the driver and select the appropriate stimuli to achieve the optimal driving output. As a result, when aggressive driving is detected continuously, an automatic alert could be sent to the health specialists regarding particular risky behavior linked with mental problems or drug consumption. Thus, the driving profile test could also be used as a detector for health problems.

Smart Homes as Enablers for Depression Pre-Diagnosis Using PHQ-9 on HMI through Fuzzy Logic Decision System.

Depression is a common mental illness characterized by sadness, lack of interest, or pleasure. According to the DSM-5, there are nine symptoms, from which an individual must present 4 or 5 in the last two weeks to fulfill the diagnosis criteria of depression. Nevertheless, the common methods that health care professionals use to assess and monitor depression symptoms are face-to-face questionnaires leading to time-consuming or expensive methods. On the other hand, smart homes can monitor householders' health through smart devices such as smartphones, wearables, cameras, or voice assistants connected to the home. Although the depression disorders at smart homes are commonly oriented to the senior sector, depression affects all of us. Therefore, even though an expert needs to diagnose the depression disorder, questionnaires as the PHQ-9 help spot any depressive symptomatology as a pre-diagnosis. Thus, this paper proposes a three-step framework; the first step assesses the nine questions to the end-user through ALEXA or a gamified HMI. Then, a fuzzy logic decision system considers three actions based on the nine responses. Finally, the last step considers these three actions: continue monitoring through Alexa and the HMI, suggest specialist referral, and mandatory specialist referral.

Mobile Phone Usage Detection by ANN Trained with a Metaheuristic Algorithm †.

Artificial neural networks (ANN) are widely used to classify high non-linear systems by using a set of input/output data. Moreover, they are trained using several optimization methodologies and this paper presents a novel algorithm for training ANN through an earthquake optimization method. Usually, gradient optimization method is implemented for the training process, with perhaps the large number of iterations leading to slow convergence, and not always achieving the optimal solution. Since metaheuristic optimization methods deal with searching for weight values in a broad optimization space, the training computational effort is reduced and ensures an optimal solution. This work shows an efficient training process that is a suitable solution for detection of mobile phone usage while driving. The main advantage of training ANN using the Earthquake Algorithm (EA) lies in its versatility to search in a fine or aggressive way, which extends its field of application. Additionally, a basic example of a linear classification is illustrated using the proposal-training method, so the number of applications could be expanded to nano-sensors, such as reversible logic circuit synthesis in which a genetic algorithm had been implemented. The fine search is important for the studied logic gate emulation due to the small searching areas for the linear separation, also demonstrating the convergence capabilities of the algorithm. Experimental results validate the proposed method for smart mobile phone applications that also can be applied for optimization applications.

Abiraterone in metastatic prostate cancer without previous chemotherapy.

BACKGROUND: Abiraterone acetate, an androgen biosynthesis inhibitor, improves overall survival in patients with metastatic castration-resistant prostate cancer after chemotherapy. We evaluated this agent in patients who had not received previous chemotherapy. METHODS: In this double-blind study, we randomly assigned 1088 patients to receive abiraterone acetate (1000 mg) plus prednisone (5 mg twice daily) or placebo plus prednisone. The coprimary end points were radiographic progression-free survival and overall survival. RESULTS: The study was unblinded after a planned interim analysis that was performed after 43% of the expected deaths had occurred. The median radiographic progression-free survival was 16.5 months with abiraterone-prednisone and 8.3 months with prednisone alone (hazard ratio for abiraterone-prednisone vs. prednisone alone, 0.53; 95% confidence interval [CI], 0.45 to 0.62; P<0.001). Over a median follow-up period of 22.2 months, overall survival was improved with abiraterone-prednisone (median not reached, vs. 27.2 months for prednisone alone; hazard ratio, 0.75; 95% CI, 0.61 to 0.93; P=0.01) but did not cross the efficacy boundary. Abiraterone-prednisone showed superiority over prednisone alone with respect to time to initiation of cytotoxic chemotherapy, opiate use for cancer-related pain, prostate-specific antigen progression, and decline in performance status. Grade 3 or 4 mineralocorticoid-related adverse events and abnormalities on liver-function testing were more common with abiraterone-prednisone. CONCLUSIONS: Abiraterone improved radiographic progression-free survival, showed a trend toward improved overall survival, and significantly delayed clinical decline and initiation of chemotherapy in patients with metastatic castration-resistant prostate cancer. (Funded by Janssen Research and Development, formerly Cougar Biotechnology; ClinicalTrials.gov number, NCT00887198.).

Abiraterone acetate plus prednisone versus placebo plus prednisone in chemotherapy-naive men with metastatic castration-resistant prostate cancer (COU-AA-302): final overall survival analysis of a randomised, double-blind, placebo-controlled phase 3 study.

BACKGROUND: Abiraterone acetate plus prednisone significantly improved radiographic progression-free survival compared with placebo plus prednisone in men with chemotherapy-naive castration-resistant prostate cancer at the interim analyses of the COU-AA-302 trial. Here, we present the prespecified final analysis of the trial, assessing the effect of abiraterone acetate plus prednisone on overall survival, time to opiate use, and use of other subsequent therapies. METHODS: In this placebo-controlled, double-blind, randomised phase 3 study, 1088 asymptomatic or mildly symptomatic patients with chemotherapy-naive prostate cancer stratified by Eastern Cooperative Oncology performance status (0 vs 1) were randomly assigned with a permuted block allocation scheme via a web response system in a 1:1 ratio to receive either abiraterone acetate (1000 mg once daily) plus prednisone (5 mg twice daily; abiraterone acetate group) or placebo plus prednisone (placebo group). Coprimary endpoints were radiographic progression-free survival and overall survival analysed in the intention-to-treat population. The study is registered with ClinicalTrials.gov, number NCT00887198. FINDINGS: At a median follow-up of 49.2 months (IQR 47.0-51.8), 741 (96%) of the prespecified 773 death events for the final analysis had been observed: 354 (65%) of 546 patients in the abiraterone acetate group and 387 (71%) of 542 in the placebo group. 238 (44%) patients initially receiving prednisone alone subsequently received abiraterone acetate plus prednisone as crossover per protocol (93 patients) or as subsequent therapy (145 patients). Overall, 365 (67%) patients in the abiraterone acetate group and 435 (80%) in the placebo group received subsequent treatment with one or more approved agents. Median overall survival was significantly longer in the abiraterone acetate group than in the placebo group (34.7 months [95% CI 32.7-36.8] vs 30.3 months [28.7-33.3]; hazard ratio 0.81 [95% CI 0.70-0.93]; p=0.0033). The most common grade 3-4 adverse events of special interest were cardiac disorders (41 [8%] of 542 patients in the abiraterone acetate group vs 20 [4%] of 540 patients in the placebo group), increased alanine aminotransferase (32 [6%] vs four [<1%]), and hypertension (25 [5%] vs 17 [3%]). INTERPRETATION: In this randomised phase 3 trial with a median follow-up of more than 4 years, treatment with abiraterone acetate prolonged overall survival compared with prednisone alone by a margin that was both clinically and statistically significant. These results further support the favourable safety profile of abiraterone acetate in patients with chemotherapy-naive metastatic castration-resistant prostate cancer. FUNDING: Janssen Research & Development.

The development of an artificial organic networks toolkit for LabVIEW.

Two of the most challenging problems that scientists and researchers face when they want to experiment with new cutting-edge algorithms are the time-consuming for encoding and the difficulties for linking them with other technologies and devices. In that sense, this article introduces the artificial organic networks toolkit for LabVIEW™ (AON-TL) from the implementation point of view. The toolkit is based on the framework provided by the artificial organic networks technique, giving it the potential to add new algorithms in the future based on this technique. Moreover, the toolkit inherits both the rapid prototyping and the easy-to-use characteristics of the LabVIEW™ software (e.g., graphical programming, transparent usage of other softwares and devices, built-in programming event-driven for user interfaces), to make it simple for the end-user. In fact, the article describes the global architecture of the toolkit, with particular emphasis in the software implementation of the so-called artificial hydrocarbon networks algorithm. Lastly, the article includes two case studies for engineering purposes (i.e., sensor characterization) and chemistry applications (i.e., blood-brain barrier partitioning data model) to show the usage of the toolkit and the potential scalability of the artificial organic networks technique.

Efficacy and Safety of Abiraterone Acetate in Elderly (75 Years or Older) Chemotherapy Naïve Patients with Metastatic Castration Resistant Prostate Cancer.

PURPOSE: Metastatic castration resistant prostate cancer primarily affects elderly men. In this post hoc analysis we investigated the safety and efficacy of abiraterone acetate in elderly (age 75 years or greater) and younger (less than 75 years) patient subgroups at the prespecified interim analysis (55% of total overall survival events) for the COU-AA-302 (Abiraterone Acetate in Asymptomatic or Mildly Symptomatic Patients with Metastatic Castration-Resistant Prostate Cancer) trial. MATERIALS AND METHODS: Patients were stratified and randomized 1:1 to abiraterone acetate 1,000 mg plus prednisone/prednisolone 5 mg twice daily (abiraterone-prednisone) vs placebo plus prednisone/prednisolone 5 mg twice daily (prednisone alone). Co-primary end points were radiographic progression-free and overall survival. Median time to event and HR were estimated using the Kaplan-Meier method and a Cox model, respectively. RESULTS: A total of 350 elderly patients treated with abiraterone-prednisone had significant improvements in overall and radiographic progression-free survival vs those with prednisone alone (HR 0.71, 95% CI 0.53-0.96 vs HR 0.63, 95% CI 0.48-0.83), similar to 738 younger patients (HR 0.81, 95% CI 0.63-1.03 vs HR 0.49, 95% CI 0.40-0.59). All secondary end points favored the abiraterone-prednisone arm for both age subgroups. Specific adverse events with abiraterone-prednisone were similar between the age subgroups. Elderly patients in both treatment arms had higher rates of fluid retention and cardiac disorders than younger patients, although rates of dose reduction or treatment interruptions due to adverse events were low in both age subgroups. CONCLUSIONS: Abiraterone acetate demonstrated clinical benefit and was well tolerated in elderly and younger men with chemotherapy naïve, metastatic castration resistant prostate cancer. Thus, findings support it as a treatment option for elderly patients who may not tolerate other therapies with greater toxicity.

Abiraterone acetate for patients with metastatic castration-resistant prostate cancer progressing after chemotherapy: final analysis of a multicentre, open-label, early-access protocol trial.

BACKGROUND: In the final analysis of the phase 3 COU-AA-301 study, abiraterone acetate plus prednisone significantly prolonged overall survival compared with prednisone alone in patients with metastatic castration-resistant prostate cancer progressing after chemotherapy. Here, we present the final analysis of an early-access protocol trial that was initiated after completion of COU-AA-301 to enable worldwide preapproval access to abiraterone acetate in patients with metastatic castration-resistant prostate cancer progressing after chemotherapy. METHODS: We did a multicentre, open-label, early-access protocol trial in 23 countries. We enrolled patients who had metastatic castration-resistant prostate cancer progressing after taxane chemotherapy. Participants received oral doses of abiraterone acetate (1000 mg daily) and prednisone (5 mg twice a day) in 28-day cycles until disease progression, development of sustained side-effects, or abiraterone acetate becoming available in the respective country. The primary outcome was the number of adverse events arising during study treatment and within 30 days of discontinuation. Efficacy measures (time to prostate-specific antigen [PSA] progression and time to clinical progression) were gathered to guide treatment decisions. We included in our analysis all patients who received at least one dose of abiraterone acetate. This study is registered with ClinicalTrials.gov, number NCT01217697. FINDINGS: Between Nov 17, 2010, and Sept 30, 2013, 2314 patients were enrolled into the early-access protocol trial. Median follow-up was 5·7 months (IQR 3·5-10·6). 952 (41%) patients had a grade 3 or 4 treatment-related adverse event, and grade 3 or 4 serious adverse events were recorded in 585 (25%) people. The most common grade 3 and 4 adverse events were hepatotoxicity (188 [8%]), hypertension (99 [4%]), cardiac disorders (52 [2%]), osteoporosis (31 [1%]), hypokalaemia (28 [1%]), and fluid retention or oedema (23 [1%]). 172 (7%) patients discontinued the study because of adverse events (64 [3%] were drug-related), as assessed by the investigator, and 171 (7%) people died. The funder assessed causes of death, which were due to disease progression (85 [4%]), an unrelated adverse experience (72 [3%]), and unknown reasons (14 [1%]). Of the 86 deaths not attributable to disease progression, 18 (<1%) were caused by a drug-related adverse event, as assessed by the investigator. Median time to PSA progression was 8·5 months (95% CI 8·3-9·7) and median time to clinical progression was 12·7 months (11·8-13·8). INTERPRETATION: No new safety signals or unexpected adverse events were found in this early-access protocol trial to assess abiraterone acetate for patients with metastatic castration-resistant prostate cancer who progressed after chemotherapy. Future work is needed to ascertain the most effective regimen of abiraterone acetate to optimise patients' outcomes. FUNDING: Janssen Research & Development.

Abiraterone and increased survival in metastatic prostate cancer.

BACKGROUND: Biosynthesis of extragonadal androgen may contribute to the progression of castration-resistant prostate cancer. We evaluated whether abiraterone acetate, an inhibitor of androgen biosynthesis, prolongs overall survival among patients with metastatic castration-resistant prostate cancer who have received chemotherapy. METHODS: We randomly assigned, in a 2:1 ratio, 1195 patients who had previously received docetaxel to receive 5 mg of prednisone twice daily with either 1000 mg of abiraterone acetate (797 patients) or placebo (398 patients). The primary end point was overall survival. The secondary end points included time to prostate-specific antigen (PSA) progression (elevation in the PSA level according to prespecified criteria), progression-free survival according to radiologic findings based on prespecified criteria, and the PSA response rate. RESULTS: After a median follow-up of 12.8 months, overall survival was longer in the abiraterone acetate-prednisone group than in the placebo-prednisone group (14.8 months vs. 10.9 months; hazard ratio, 0.65; 95% confidence interval, 0.54 to 0.77; P<0.001). Data were unblinded at the interim analysis, since these results exceeded the preplanned criteria for study termination. All secondary end points, including time to PSA progression (10.2 vs. 6.6 months; P<0.001), progression-free survival (5.6 months vs. 3.6 months; P<0.001), and PSA response rate (29% vs. 6%, P<0.001), favored the treatment group. Mineralocorticoid-related adverse events, including fluid retention, hypertension, and hypokalemia, were more frequently reported in the abiraterone acetate-prednisone group than in the placebo-prednisone group. CONCLUSIONS: The inhibition of androgen biosynthesis by abiraterone acetate prolonged overall survival among patients with metastatic castration-resistant prostate cancer who previously received chemotherapy. (Funded by Cougar Biotechnology; COU-AA-301 ClinicalTrials.gov number, NCT00638690.).

Abiraterone acetate plus prednisone versus prednisone alone in chemotherapy-naive men with metastatic castration-resistant prostate cancer: patient-reported outcome results of a randomised phase 3 trial.

BACKGROUND: Abiraterone acetate plus prednisone significantly improves radiographic progression-free survival in asymptomatic or mildly symptomatic, chemotherapy-naive patients with metastatic castration-resistant prostate cancer compared with prednisone alone. We describe analyses of data for patient-reported pain and functional status in a preplanned interim analysis of a phase 3 trial. METHODS: Between April 28, 2009, and June 23, 2010, patients with progressive, metastatic castration-resistant prostate cancer were enrolled into a multinational, double-blind, placebo-controlled trial. Patients were eligible if they were asymptomatic (score of 0 or 1 on item three of the Brief Pain Inventory Short Form [BPI-SF] questionnaire) or mildly symptomatic (score of 2 or 3) and had not previously received chemotherapy. Patients were randomly assigned (1:1) to receive oral abiraterone (1 g daily) plus prednisone (5 mg twice daily) or placebo plus prednisone in continuous 4-week cycles. Pain was assessed with the BPI-SF questionnaire, and health-related quality of life (HRQoL) with the Functional Assessment of Cancer Therapy-Prostate (FACT-P) questionnaire. We analysed data with prespecified criteria for clinically meaningful pain progression and deterioration in HRQoL. All patients who underwent randomisation were included in analyses. FINDINGS: 1088 patients underwent randomisation: 546 were assigned to abiraterone plus prednisone and 542 to placebo plus prednisone. At the time of the second prespecified interim analysis, median follow-up was 22·2 months (IQR 20·2-24·8). Median time to progression of mean pain intensity was longer in patients assigned to abiraterone plus prednisone (26·7 months [95% CI 19·3-not estimable]) than in those assigned to placebo plus prednisone (18·4 months [14·9-not estimable]; hazard ratio [HR] 0·82, 95% CI 0·67-1·00; p=0·0490), as was median time to progression of pain interference with daily activities (10·3 months [95% CI 9·3-13·0] vs 7·4 months [6·4-8·6]; HR 0·79, 95% CI 0·67-0·93; p=0·005). Median time to progression of worst pain was also longer with abiraterone plus prednisone (26·7 months [95% CI 19·4-not estimable]) than with placebo plus prednisone (19·4 months [16·6-not estimable]), but the difference was not significant (HR 0·85, 95% CI 0·69-1·04; p=0·109). Median time to HRQoL deterioration was longer in patients assigned to abiraterone plus prednisone than in those assigned to placebo plus prednisone as assessed by the FACT-P total score (12·7 months [95% CI 11·1-14·0] vs 8·3 months [7·4-10·6]; HR 0·78, 95% CI 0·66-0·92; p=0·003) and by the score on its prostate-cancer-specific subscale (11·1 months [8·6-13·8] vs 5·8 months [5·5-8·3]; HR 0·70, 95% CI 0·60-0·83; p<0·0001). INTERPRETATION: Abiraterone plus prednisone delays patient-reported pain progression and HRQoL deterioration in chemotherapy-naive patients with metastatic castration-resistant prostate cancer. These results provide further support for the efficacy of abiraterone in this population.

Exploring inter-trial coherence for inner speech classification in EEG-based brain-computer interface.

Objective. In recent years, electroencephalogram (EEG)-based brain-computer interfaces (BCIs) applied to inner speech classification have gathered attention for their potential to provide a communication channel for individuals with speech disabilities. However, existing methodologies for this task fall short in achieving acceptable accuracy for real-life implementation. This paper concentrated on exploring the possibility of using inter-trial coherence (ITC) as a feature extraction technique to enhance inner speech classification accuracy in EEG-based BCIs.Approach. To address the objective, this work presents a novel methodology that employs ITC for feature extraction within a complex Morlet time-frequency representation. The study involves a dataset comprising EEG recordings of four different words for ten subjects, with three recording sessions per subject. The extracted features are then classified using k-nearest-neighbors (kNNs) and support vector machine (SVM).Main results. The average classification accuracy achieved using the proposed methodology is 56.08% for kNN and 59.55% for SVM. These results demonstrate comparable or superior performance in comparison to previous works. The exploration of inter-trial phase coherence as a feature extraction technique proves promising for enhancing accuracy in inner speech classification within EEG-based BCIs.Significance. This study contributes to the advancement of EEG-based BCIs for inner speech classification by introducing a feature extraction methodology using ITC. The obtained results, on par or superior to previous works, highlight the potential significance of this approach in improving the accuracy of BCI systems. The exploration of this technique lays the groundwork for further research toward inner speech decoding.

Learning manufacturing computer vision systems using tiny YOLOv4.

Implementing and deploying advanced technologies are principal in improving manufacturing processes, signifying a transformative stride in the industrial sector. Computer vision plays a crucial innovation role during this technological advancement, demonstrating broad applicability and profound impact across various industrial operations. This pivotal technology is not merely an additive enhancement but a revolutionary approach that redefines quality control, automation, and operational efficiency parameters in manufacturing landscapes. By integrating computer vision, industries are positioned to optimize their current processes significantly and spearhead innovations that could set new standards for future industrial endeavors. However, the integration of computer vision in these contexts necessitates comprehensive training programs for operators, given this advanced system's complexity and abstract nature. Historically, training modalities have grappled with the complexities of understanding concepts as advanced as computer vision. Despite these challenges, computer vision has recently surged to the forefront across various disciplines, attributed to its versatility and superior performance, often matching or exceeding the capabilities of other established technologies. Nonetheless, there is a noticeable knowledge gap among students, particularly in comprehending the application of Artificial Intelligence (AI) within Computer Vision. This disconnect underscores the need for an educational paradigm transcending traditional theoretical instruction. Cultivating a more practical understanding of the symbiotic relationship between AI and computer vision is essential. To address this, the current work proposes a project-based instructional approach to bridge the educational divide. This methodology will enable students to engage directly with the practical aspects of computer vision applications within AI. By guiding students through a hands-on project, they will learn how to effectively utilize a dataset, train an object detection model, and implement it within a microcomputer infrastructure. This immersive experience is intended to bolster theoretical knowledge and provide a practical understanding of deploying AI techniques within computer vision. The main goal is to equip students with a robust skill set that translates into practical acumen, preparing a competent workforce to navigate and innovate in the complex landscape of Industry 4.0. This approach emphasizes the criticality of adapting educational strategies to meet the evolving demands of advanced technological infrastructures. It ensures that emerging professionals are adept at harnessing the potential of transformative tools like computer vision in industrial settings.

Developing a virtual reality and AI-based framework for advanced digital manufacturing and nearshoring opportunities in Mexico.

The growing expansion of the manufacturing sector, particularly in Mexico, has revealed a spectrum of nearshoring opportunities yet is paralleled by a discernible void in educational tools for various stakeholders, such as engineers, students, and decision-makers. This paper introduces a state-of-the-art framework, incorporating virtual reality (VR) and artificial intelligence (AI) to metamorphose the pedagogy of advanced manufacturing systems. Through a case study focused on the design, production, and evaluation of a robotic platform, the framework endeavors to offer an exhaustive educational experience via an interactive VR environment, encapsulating (1) Robotic platform system design and modeling, enabling users to immerse themselves in the design and simulation of robotic platforms under varied conditions; (2) Virtual manufacturing company, presenting a detailed virtual manufacturing setup to enhance users' comprehension of manufacturing processes and systems, and problem-solving in realistic settings; and (3) Product evaluation, wherein users employ VR to meticulously assess the robotic platform, ensuring optimal functionality and customer satisfaction. This innovative framework melds theoretical acumen with practical application in advanced manufacturing, preparing entities to navigate Mexico's manufacturing sector's vibrant and competitive nearshoring landscape. It creates an immersive environment for understanding modern manufacturing challenges, fostering Mexico's manufacturing sector growth, and maximizing nearshoring opportunities for stakeholders.

Abiraterone acetate for treatment of metastatic castration-resistant prostate cancer: final overall survival analysis of the COU-AA-301 randomised, double-blind, placebo-controlled phase 3 study.

BACKGROUND: Abiraterone acetate improved overall survival in metastatic castration-resistant prostate cancer at a preplanned interim analysis of the COU-AA-301 double-blind, placebo-controlled phase 3 study. Here, we present the final analysis of the study before crossover from placebo to abiraterone acetate (after 775 of the prespecified 797 death events). METHODS: Between May 8, 2008, and July 28, 2009, this study enrolled 1195 patients at 147 sites in 13 countries. Patients were eligible if they had metastatic castration-resistant prostate cancer progressing after docetaxel. Patients were stratified according to baseline Eastern Cooperative Oncology Group (ECOG) performance status, worst pain over the past 24 h on the Brief Pain Inventory-Short Form, number of previous chemotherapy regimens, and type of progression. Patients were randomly assigned (ratio 2:1) to receive either abiraterone acetate (1000 mg, once daily and orally) plus prednisone (5 mg, orally twice daily) or placebo plus prednisone with a permuted block method via an interactive web response system. The primary endpoint was overall survival, analysed in the intention-to-treat population. This study is registered with ClinicalTrials.gov, number NCT00091442. FINDINGS: Of the 1195 eligible patients, 797 were randomly assigned to receive abiraterone acetate plus prednisone (abiraterone group) and 398 to receive placebo plus prednisone (placebo group). At median follow-up of 20·2 months (IQR 18·4-22·1), median overall survival for the abiraterone group was longer than in the placebo group (15·8 months [95% CI 14·8-17·0] vs 11·2 months [10·4-13·1]; hazard ratio [HR] 0·74, 95% CI 0·64-0·86; p<0·0001). Median time to PSA progression (8·5 months, 95% CI 8·3-11·1, in the abiraterone group vs 6·6 months, 5·6-8·3, in the placebo group; HR 0·63, 0·52-0·78; p<0·0001), median radiologic progression-free survival (5·6 months, 5·6-6·5, vs 3·6 months, 2·9-5·5; HR 0·66, 0·58-0·76; p<0·0001), and proportion of patients who had a PSA response (235 [29·5%] of 797 patients vs 22 [5·5%] of 398; p<0·0001) were all improved in the abiraterone group compared with the placebo group. The most common grade 3-4 adverse events were fatigue (72 [9%] of 791 patients in the abiraterone group vs 41 [10%] of 394 in the placebo group), anaemia (62 [8%] vs 32 [8%]), back pain (56 [7%] vs 40 [10%]), and bone pain (51 [6%] vs 31 [8%]). INTERPRETATION: This final analysis confirms that abiraterone acetate significantly prolongs overall survival in patients with metastatic castration-resistant prostate cancer who have progressed after docetaxel treatment. No new safety signals were identified with increased follow-up.