Miracle-dz/UniFAR-FTUs huggingface dataset:
KEYNOTE-C93/GOG-3064/ENGOT-en15: A phase 3, randomized, open-label study of first-line pembrolizumab versus platinum-doublet chemotherapy in mismatch repair deficient advanced or recurrent endometrial carcinoma.

TPS5623 Background: Carboplatin-paclitaxel chemotherapy (with trastuzumab for HER2+ uterine serous carcinoma) is the standard of care first-line systemic treatment for recurrent or metastatic endometrial carcinoma (EC), which has a 5-year relative survival rate of only 17%. Worse survival outcomes have been shown for the mismatch repair deficient (dMMR) subtype of EC. Pembrolizumab (pembro), an anti-PD-1 antibody, showed compelling antitumor activity in previously treated, advanced MSI-H/dMMR EC in the phase 2 KEYNOTE-158 study (ORR, 48%; median duration of response [DOR], not reached; O’Malley JCO 2022). KEYNOTE-C93/GOG-3064/ENGOT-en15 (NCT05173987) is a phase 3, randomized, open-label study evaluating first-line pembro versus carboplatin-paclitaxel chemotherapy in patients with dMMR advanced or recurrent EC. Methods: Patients aged ≥18 years with histologically confirmed stage III/IV recurrent EC including carcinosarcoma (mixed Mullerian tumor), radiographically evaluable disease (measurable or nonmeasurable per RECIST v1.1), no prior systemic therapy (prior radiation with or without radiosensitizing chemotherapy > 2 weeks before first dose or prior hormonal therapy ≥1 week before randomization is permitted), and an ECOG PS ≤1 are eligible. Patients must have central confirmation of dMMR status. Approximately 350 patients will be randomized 1:1 to receive pembro 400 mg IV Q6W for 18 cycles (̃2 years) or carboplatin AUC 5 or 6 mg/mL/min IV Q3W and paclitaxel 175 mg/m2 IV Q3W for 6 cycles (with option for > 6 cycles). Trastuzumab is permitted for patients in the chemotherapy arm with HER2+ serous EC. Randomization is stratified by disease status (newly diagnosed advanced EC vs recurrent EC) and histology (endometrioid vs nonendometrioid). Treatment will continue for the specified number of cycles or until PD or unacceptable toxicity. Patients in the chemotherapy arm have the option to receive pembro following confirmed PD by blinded independent central review (BICR). Tumor imaging will be performed Q9W from randomization to week 54 and Q12W thereafter. AEs will be assessed from randomization to 30 days (90 days for serious AEs) after treatment discontinuation and graded per NCI CTCAE version 5.0. Dual primary endpoints are PFS per RECIST v1.1 by BICR and OS. Secondary endpoints are ORR, disease control rate, and DOR per RECIST v1.1 by BICR; PFS per RECIST v1.1 by investigator review; PFS2 (ie, time from randomization to PD per investigator assessment or death from any cause after start of subsequent anticancer therapy); safety; and patient-reported outcomes. PFS and OS will be estimated by the Kaplan-Meier method, with treatment differences assessed by the stratified log-rank test and HRs with 95% CIs determined using a Cox proportional hazard model. Enrollment is ongoing. Clinical trial information: NCT05173987.
A compact tri‐band filter based on a dual‐capacitively loaded triple‐mode substrate integrated waveguide resonator

This letter presents a compact tri‐band filter using a dual‐capacitively loaded (DCL) substrate integrated waveguide (SIW) triple‐mode resonator. The frequencies of TE101, TE102, and TE103 are shifted lower by the capacitive loading effect, which is achieved by the DCL structure. A compact tri‐band example filter is then built by using two DCL triple mode SIW resonators. Following that, seven transmission zeros are generated to improve filter selectivity by vertical coupling of two cavities. The area of the filter occupies only 0.46 λg2. The measured results demonstrate that this compact tri‐band filter has the advantages of flexible control of passbands, easy interconnection with other planar radio frequency components, making it promising for millimeter wave implementations and 3D‐integrated systems.
Antitumor activity of sunvozertinib in NSCLC patients with EGFR Exon20 insertion mutations after platinum and anti-PD(L)1 treatment failures.

9015 Background: Platinum-based chemotherapy is the 1st line standard of care for NSCLC patients with EGFR exon 20 insertion mutations (Exon20ins), with anti-PD(L)1 frequently used as well. Here we present anti-tumor activity of sunvozertinib in these patients whose disease had progressed on these therapies from two ongoing phase 1/2 studies (WK-KONG1, NCT03974022 and WU-KONG2, CTR20192097). Based on these data, sunvozertinib was granted the Breakthrough Therapy Designation by both US FDA and China NMPA. Methods: The objective of this study is to characterize the safety and efficacy of sunvozertinib in platinum-pretreated advanced NSCLC patients harboring EGFR Exon20ins, with or without anti-PD(L1) treatment. In addition, the effect of prior treatment on sunvozertinib’s safety and efficacy were explored. Results: As of July 30, 2021, a total of 52 locally advanced or metastatic NSCLC patients harboring EGFR Exon20ins post platinum treatment were enrolled into WU-KONG1 and WU-KONG2 studies, and included in the efficacy analysis set (dose range: 50 mg to 400 mg, once daily). Male/Female: 21/31; Median age 59; Asian/White: 44/8; Prior therapies: median 2.5 (range 1-10); 31% received prior anti-PD(L)1 treatment (all in £ 300 mg cohorts); 40% of the subjects with baseline brain metastasis. Partial response was observed at ≥ 100 mg. At the dose level of 100 mg, 200 mg, 300 mg and 400 mg, confirmed ORR was 50% (1/2), 55.6 % (5/9), 44.8% (13/29) and 22.2% (2/9), respectively. With a median follow-up time of 10.5 months, median DoR was not reached for 200 mg cohort; with a median follow-up of 7 months, median DoR of 300 mg group was 5.6 months. Progression free survival (PFS) rate at 6 months for 100 mg, 200 mg, 300 mg and 400 mg cohorts was 50%, 53.3%, 44.6% and 44.4%, respectively. In patients with/without prior anti-PD(L)1 treatment, comparable efficacy and safety profiles were observed. Conclusions: The data suggest sunvozertinib is active in platinum-pretreated patients with EGFR Exon20ins, irrespective of prior or after anti-PD(L)1 treatment. The updated data will be presented at the meeting. Sunvozertinib is currently in phase 2 pivotal clinical development (NCT03974022 and China CTR20211009). Clinical trial information: NCT03974022.
Real-world utilization of ctDNA in the management of colorectal cancer.

3075 Background: The utilization of circulating tumor DNA (ctDNA) as a non-invasive biomarker for the detection of minimal residual disease, prediction of recurrence in the post-operative setting, and real-time monitoring of treatment efficacy has the potential to vastly improve the care and outcomes of patients with colorectal cancer (CRC). In August of 2020, ctDNA testing first gained approval for use in solid tumors and its prognostic benefit after curative intent surgery has been demonstrated to exceed that of prior standard of care clinicopathological criteria in CRC patients. The comprehensive integration of validated ctDNA approaches into the routine clinical care of patients with CRC would not only fundamentally change how risk of recurrence is assessed but could also reduce treatment with unneeded/unwarranted toxic therapies and allow for earlier recognition and treatment in cases with a high risk of relapse. This survey-based study aimed to evaluate the utilization of ctDNA testing in the management of CRC among practicing community oncologists in the U.S. Methods: Questions related to ctDNA utilization for patients with CRC were presented to community oncologists during a virtual meeting held in July 2021. Descriptive statistics were used to analyze the results. Results: Of 55 participating oncologists geographically distributed across the U.S., 49% indicated not using ctDNA to make treatment decisions in CRC. A proportion of physicians reported using ctDNA to detect recurrence (27% of physicians); make decisions around post-resection adjuvant therapy (25%); monitor disease progression/relapse (18%); and track tumor resistance during treatment (9%). The most frequently cited barriers to ordering ctDNA testing for patients with metastatic CRC were reimbursement issues (reported by 56% of oncologists), insufficient clinical evidence (46%), and limited familiarity with ctDNA use (28%). Oncologists reported that the following would increase their utilization of ctDNA testing: more clinical evidence of the utility of ctDNA (reported by 66% of physicians), increased education on methodology (60%), more education on the use of ctDNA (57%), more financial aid and reimbursement support for patients (49%), more decision support tools (47%), and better communication between physicians and vendors (26%). Conclusions: These findings demonstrate limited adoption of ctDNA testing by community oncologists in the care of CRC patients. Insufficient demonstration of clinical utility, limited familiarity with methodology, and reimbursement issues were cited as barriers to uptake. Education for community oncology providers about ctDNA testing and its demonstrated clinical utility, and increased financial support for patients may improve its utilization and adoption in CRC to improve patient outcomes and care.
OpenCL and OpenGL Implementation of Simultaneous Localization and Mapping Algorithm using High-End GPU

Simultaneous Localization And Mapping (SLAM) algorithms are being used in many robotic applications and autonomous navigation systems. The FastSLAM2.0 addresses an issue of the SLAM problem and allows a robot to navigate in an unknown environment. Several works have presented many algorithmic optimizations to reduce the computational complexity of such algorithm. In this paper, a GPGPU (general-purpose computing on graphics processing units) is exploited to achieve a parallel implementation of the FastSLAM2.0. The GPGPU acceleration is done using two different implementations for parallel programming. The first implementation used OpenGL shading language which is based on the characteristics of graphics hardwares. The second implementation used OpenCL which allows hardware acceleration across heterogeneous architectures. We also explored the impact of the two approaches on the the resulting GPGPU implementation. A comparison related to processing-time and localization accuracy is made using a real indoor dataset. Our results show a significant speedup of the GPGPU implementation over a Quad-Core CPU. We show also that, by adopting the same optimization methodology using the two approachs, the OpenCL implementation is faster and suitable for GPGPU accelerated SLAM algorithms.
Recent Advances in Machine Learning Applied to Ultrasound Imaging

Machine learning (ML) methods are pervading an increasing number of fields of application because of their capacity to effectively solve a wide variety of challenging problems. The employment of ML techniques in ultrasound imaging applications started several years ago but the scientific interest in this issue has increased exponentially in the last few years. The present work reviews the most recent (2019 onwards) implementations of machine learning techniques for two of the most popular ultrasound imaging fields, medical diagnostics and non-destructive evaluation. The former, which covers the major part of the review, was analyzed by classifying studies according to the human organ investigated and the methodology (e.g., detection, segmentation, and/or classification) adopted, while for the latter, some solutions to the detection/classification of material defects or particular patterns are reported. Finally, the main merits of machine learning that emerged from the study analysis are summarized and discussed.
PREDICTIVE MODELS APPLIED IN SPORTS MANAGEMENT –LITERATURE REVIEW ON RESEARCH TRENDS

: In recent years, numerous studies have been conducted to obtain by extracting the most accurate estimate of the main parameters in a given field. The techniques were diverse, and the main purpose was to identify how information can become useful knowledge. My area of interest, sports prediction, is constantly evolving, so many organizations have begun to focus on these methods that can provide them with valuable data. Therefore, this article is actually a literature review on how sports data is exploited. On this basis, I can present an overview of what has been studied, research proposals, topics addressed, algorithms and technologies used and future opportunities. Analysing these discoveries I want to offer a mining potential in this field and to attract as many researchers as possible to research the subject of sports predictions.
Application of Machine Learning Methods for Asset Management on Power Distribution Networks

This study aims to study the different kinds of Machine Learning (ML) models and their working principles for asset management in power networks. Also, it investigates the challenges behind asset management and its maintenance activities. In this review article, Machine Learning (ML) models are analyzed to improve the lifespan of the electrical components based on the maintenance management and assessment planning policies. The articles are categorized according to their purpose: 1) classification, 2) machine learning, and 3) artificial intelligence mechanisms. Moreover, the importance of using ML models for proper decision making based on the asset management plan is illustrated in a detailed manner. In addition to this, a comparative analysis between the ML models is performed, identifying the advantages and disadvantages of these techniques. Then, the challenges and managing operations of the asset management strategies are discussed based on the technical and economic factors. The proper functioning, maintenance and controlling operations of the electric components are key challenging and demanding tasks in the power distribution systems. Typically, asset management plays an essential role in determining the quality and profitability of the elements in the power network. Based on this investigation, the most suitable and optimal machine learning technique can be identified and used for future work. Doi: 10.28991/ESJ-2022-06-04-017 Full Text: PDF
Epigenetic dysregulation in meningiomas

Abstract Background Meningiomas are the most common primary brain tumor. Though typically benign with a low mutational burden, tumors with benign histology may behave aggressively and there are no proven chemotherapies. Although DNA methylation patterns distinguish subgroups of meningiomas and have higher predictive value for tumor behavior than histologic classification, little is known about differences in DNA methylation between meningiomas and surrounding normal dura tissue. Methods Whole-exome sequencing and methylation array profiling were performed on 12 dura/meningioma pairs (11 WHO grade I and 1 WHO grade II). Single-nucleotide polymorphism (SNP) genotyping and methylation array profiling were performed on an additional 19 meningiomas (9 WHO grade I, 5 WHO grade II, 4 WHO grade III). Results Using multimodal studies of meningioma/dura pairs, we identified 4 distinct DNA methylation patterns. Diffuse DNA hypomethylation of malignant meningiomas readily facilitated their identification from lower-grade tumors by unsupervised clustering. All clusters and 12/12 meningioma-dura pairs exhibited hypomethylation of the gene promoters of a module associated with the craniofacial patterning transcription factor FOXC1 and its upstream lncRNA FOXCUT. Furthermore, we identified an epigenetic continuum of increasing hypermethylation of polycomb repressive complex target promoters with increasing histopathologic grade. Conclusion These findings support future investigations of the role of epigenetic dysregulation of FOXC1 and cranial patterning genes in meningioma formation as well as studies of the utility of polycomb inhibitors for the treatment of malignant meningiomas.
From Seeing to Simulating: A Survey of Imaging Techniques and Spatially-Resolved Data for Developing Multiscale Computational Models of Liver Regeneration

Liver regeneration, which leads to the re-establishment of organ mass, follows a specifically organized set of biological processes acting on various time and length scales. Computational models of liver regeneration largely focused on incorporating molecular and signaling detail have been developed by multiple research groups in the recent years. These modeling efforts have supported a synthesis of disparate experimental results at the molecular scale. Incorporation of tissue and organ scale data using noninvasive imaging methods can extend these computational models towards a comprehensive accounting of multiscale dynamics of liver regeneration. For instance, microscopy-based imaging methods provide detailed histological information at the tissue and cellular scales. Noninvasive imaging methods such as ultrasound, computed tomography and magnetic resonance imaging provide morphological and physiological features including volumetric measures over time. In this review, we discuss multiple imaging modalities capable of informing computational models of liver regeneration at the organ-, tissue- and cellular level. Additionally, we discuss available software and algorithms, which aid in the analysis and integration of imaging data into computational models. Such models can be generated or tuned for an individual patient with liver disease. Progress towards integrated multiscale models of liver regeneration can aid in prognostic tool development for treating liver disease.
Machine Learning as a Tool to the Diagnosis of Diabetes

Machine learning is the field of computer science that uses data to make predictions and decisions. The problem we consider in this article belongs to the class known as supervised learning and the technique we use is logistic regression. After explaining supervised learning and logistic regression, we use a data set to develop a computational model able to give a diabetes diagnosis to patients. We discuss the accuracy of the model developed.
The muon magnetic moment: a precision test shaking the Standard Model

The status of the measurement of the muon magnetic moment and of its prediction within the Standard Model is reviewed. Both approaches have been followed for decades with ever increasing precision. Their relative progress is a necessity in order to test the present theory and possibly find hints for new physical phenomena. Indeed, the recent measurement from Fermilab shows a tanta-lizing 4.2 standard-deviation excess over the up-to-date prediction. Particular emphasis is placed on the contribution from hadronic vacuum polarization which controls the theoretical precision of the prediction. It is evaluated through a dispersion relation using as input experimental results on electron-positron annihilation into hadrons which are thus playing a key role in establishing the prediction.
ON THE IMPORTANCE TO STUDY OLDER ADULT’S WELL-BEING

Human progress in increasing life expectancy does not appear to be slowing down. This can be understood as an achievement for humanity, but can also pose a challenge to aging populations. Despite the fact that aging is inevitable, it is also an experience to be cherished. Consequently, to address the issue of an increasingly aging population in the future, new strategies are necessary to combat the challenges that individuals may face, given that as they age, individuals are more likely to encounter adversity. In light of this, it is becoming increasingly clear that the assessment of individual well-being should be at the centre of governments' attention, as it underpins healthy and productive aging. The growing trend of aging is putting an increased emphasis on healthy living and maintaining well-being is imperative. Enhancing individuals' well-being makes them more productive for the economy and helps to reduce healthcare costs at the same time. The study and promotion of older adults’ well-being therefore has a significant impact, not only on the individual but also on society as a whole.
“We Are Having a Huge Problem with Compliance”: Exploring Preconception Care Utilization in South Africa

Background: Preconception care (PCC), a policy directive from the World Health Organisation (WHO), comprises all the health interventions offered to women and couples before conception and is intended to improve their overall health status and the pregnancy outcomes. Although PCC should be an essential part of maternal and child health services in most African countries, its provision and utilization are not widely documented. Hence, this study aimed to explore the factors influencing preconception care utilization among high-risk women in South Africa. Methods: A descriptive qualitative study of 29 purposively selected women and healthcare workers was conducted through individual in-depth interviews using a semi-structured interview guide. The interviews were transcribed verbatim, and the analyses were performed using Nvivo version 12. The Social-Ecological Model (SEM) guided the data analysis. Four levels of factors (the individual, the interpersonal, the community and social, and the policy and institutional) were used to assess what can influence PCC utilization. Findings: The availability of PCC services, the intrahospital referral of women, the referral practices of other healthcare workers, the underutilization of the PCC facility, and resources emerged at the institutional levels, while compliance with PCC appointments, socioeconomic factors, pregnancy planning, assumptions, and knowledge was at the individual levels. Conclusion: The utilization of the preconception care services was inadequate. The primary influencer of preconception care utilization was at the individual, policy, and institutional levels. The availability of preconception care services and the intrahospital referral of women at high risk of adverse pregnancy outcomes positively influenced the women’s PCC utilization, while poor pregnancy planning, and unavailability of PCC policies and guidelines negatively influenced preconception care utilization. Therefore, interventions to improve PCC utilization should focus on the four SEM levels for effectiveness. There is a need to raise PCC awareness and develop policy and guidelines to ensure consistent, standardized practice among healthcare workers.
Millimeter-Wave Digital Beamforming Receiver Using RFSoC FPGA for MIMO Communications

The paper presents a first-of-its-kind digital beam-former using single-ADC for multiple-input-multiple-output (MIMO) applications. The efficacy of this low power ultrawideband (UWB) beamformer is demonstrated by evaluating inter-channel interference (ICI), a major challenge in MIMO. Central to the approach is a code multiplexing method using orthogonal Walsh-Hadamard (WH) codes generated via a radiofrequency system-on-chip (RFSoC) field programmable gate array (FPGA). This is done at a maximum of 400 MHz clock frequency. The multiplexed signals are passed through a single channel for digitization. Experimental validation is performed using UWB tightly-coupled dipole array (TCDA) and a directconversion receiver architecture. Measurements results showed beamforming capabilities and ICI cancellation of 36 dB with little or no signal-to-noise ratio (SNR) degradation. To the best of our knowledge, this is the highest clock frequency and ICI value achieved to date.