暂无摘要。

The 100,000 Genomes Project diagnosed a quarter of affected participants, but 26% of diagnoses were not on the applied gene panel(s); with many being de novo variants. Assessing biallelic variants without a gene panel is more challenging.
We sought to identify missed biallelic diagnoses using GenePy, which incorporates allele frequency, zygosity, and a user-defined deleterious metric, generating an aggregate GenePy score per gene, per participant. We calculated GenePy scores for 2862 recessive disease genes in 78,216 100,000 Genomes Project participants. For each gene, we ranked participant GenePy scores and scrutinized affected participants without a diagnosis, whose scores ranked among the top 5 for each gene. In cases which participant phenotypes overlapped with the disease gene of interest, we extracted rare variants and applied phase, ClinVar, and ACMG classification.
3184 affected individuals without a molecular diagnosis had a top-5-ranked GenePy score and 682 of 3184 (21%) had phenotypes overlapping with a top-ranking gene. In 122 of 669 (18%) phenotype-matched cases (excluding 13 withdrawn participants), we identified a putative missed diagnosis (2.2% of all undiagnosed participants). A further 334 of 669 (50%) cases have a possible missed diagnosis but require functional validation.
Applying GenePy at scale has identified 456 potential diagnoses, demonstrating the value of novel diagnostic strategies.

Betalains are attractive natural pigments with potent antioxidant activity, mainly extracted from the roots, tubers, leaves, flowers, and fruits of certain plants and some fungi. They constitute a reliable alternative to synthetic dyes used in the food industry and are considered toxic for consumers. In addition, there is convincing evidence of their health benefits for consumers. However, betalains are highly unstable to environment factors, such as light, heat, oxygen, water activity, and pH change which can be degraded during food processing, handling, storage, or delivery. Therefore, newly developed extraction methods and micro/nano-encapsulation techniques are currently applied to enhance the extraction yield, solve their instability problems, and improve their application in the food industry. This article aims to summarize the new advanced extraction methods of betalains, discussing the recent encapsulation techniques concerning the different encapsulating materials utilization. Betalains, natural pigments with potent antioxidant activity, are increasingly extracted from the roots, tubers, leaves, flowers, and fruits of certain plants and some fungi as safe alternatives to synthetic food dyes used in the food industry. However, their susceptibility to degradation during food processing, storage, and delivery poses challenges. Recent developments in extraction methods (e.g., supercritical fluid, pressurized liquid, ultrasound- and microwave-assisted, and enzyme-assisted) enhance betalain recovery, minimizing degradation. Encapsulation techniques using biopolymers, proteins, lipids, and nanoparticles protect betalains from environmental factors, extending shelf life and enabling controlled release. These advancements offer improved extraction efficiency, reduced solvent use, shorter processing times, and enhanced stability. Integration of these techniques in the food industry presents opportunities for incorporating betalains into various products, including functional foods, beverages, and dietary supplements. By addressing stability challenges, these developments support the production of innovative, healthier food items enriched with betalains. This article provides an overview of recent advancements in betalain extraction and encapsulation, highlighting their potential applications in the food industry.

Motor Imagery (MI)-Brain Computer-Interfaces (BCI) illiteracy defines that not all subjects can achieve a good performance in MI-BCI systems due to different factors related to the fatigue, substance consumption, concentration, and experience in the use. To reduce the effects of lack of experience in the use of BCI systems (naïve users), this paper presents the implementation of three Deep Learning (DL) methods with the hypothesis that the performance of BCI systems could be improved compared with baseline methods in the evaluation of naïve BCI users. The methods proposed here are based on Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM)/Bidirectional Long Short-Term Memory (BiLSTM), and a combination of CNN and LSTM used for upper limb MI signal discrimination on a dataset of 25 naïve BCI users. The results were compared with three widely used baseline methods based on the Common Spatial Pattern (CSP), Filter Bank Common Spatial Pattern (FBCSP), and Filter Bank Common Spatial-Spectral Pattern (FBCSSP), in different temporal window configurations. As results, the LSTM-BiLSTM-based approach presented the best performance, according to the evaluation metrics of Accuracy, F-score, Recall, Specificity, Precision, and ITR, with a mean performance of 80% (maximum 95%) and ITR of 10 bits/min using a temporal window of 1.5 s. The DL Methods represent a significant increase of 32% compared with the baseline methods (p< 0.05). Thus, with the outcomes of this study, it is expected to increase the controllability, usability, and reliability of the use of robotic devices in naïve BCI users.

BACKGROUND: Cardiovascular safety of marathon running middle-aged amateurs remains unclear. We previously hypothesized that transient release of cardiac troponin I (cTnI) and N-terminal pro-B-type natriuretic peptide (NT-proBNP), in addition to an acute inflammatory response to exercise, may be the cause.
OBJECTIVE: To evaluate the effects of running a marathon on inflammatory biomarkers, and its impact on cardiovascular function.
METHODS: Thirty-three healthy male amateur runners aged ≥50 (mean age: 57 ±7 years) were enrolled in the study. Venous blood samples were obtained before the marathon, just after the race, and 2-4 days and 7 days after the marathon. Using novel single molecule counting (SMC) technology, we measured plasma concentrations of interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α). White blood cell (WBC) count was measured using a certified hematology analyzer. The results were related to previous analyses on cardiovascular stress and endothelial function biomarkers. Transthoracic echocardiography (TTE) and cardiac magnetic resonance (CMR) were used to determine myocardial function.
RESULTS: We observed a sharp rise of all studied biomarkers after the race, which subsequently normalized after 2-4 days and stayed within the normal range 7 days after the race. We found no correlation between inflammatory and cardiovascular stress biomarkers. Transthoracic echocardiography and CMR did not show ischemic or inflammatory myocardial damage.
CONCLUSIONS: Marathon running is associated with a sharp and significant rise in inflammatory and cardiovascular stress biomarkers. We found no connection between immune activation and cardiac biomarker release. Cardiovascular imaging showed no myocardial damage due to ischemia or inflammation.

Extensive use of α-pinene in cosmetics, and medicine, especially for its antioxidant/antibacterial, and anti-cancer properties, and also as a flavoring agent, has made it a versatile product. α-Pinene (one of the two pinene isomers) is the most abundant terpene in nature. When extracting α-pinene from plants and, to a lesser extent, fruits, given that its purity is essential, purification methods should also be used as described in this study. Also, an attempt has been made to describe the extraction techniques of α-pinene, carried out by conventional and novel methods. Some disadvantages of conventional methods (such as hydrodistillation or solvent extraction) are being time consuming, low capacity per batch and being labor intensive and the requirement of trained operators. Most novel methods, such as supercritical fluid extraction and microwave-assisted extraction, can reduce the extraction time, cost, and energy compared to conventional methods, and, in fact, the extraction and preservation efficiency of α-pinene in these methods is higher than conventional methods. Although the above-mentioned extraction methods are effective, they still require rather long extraction times. In fact, advanced methods such as green and solvent-free ultrasonic-microwave-assisted extraction are much more efficient than microwave-assisted extraction and ultrasound-assisted extraction because the extraction efficiency and separation of α-pinene in these methods are higher; furthermore, no solvent consumption and maximum extraction efficiency are some crucial advantages of these techniques. However, the application of some novel methods, such as ultrasound-assisted extraction, in industry scale is still problematic because of their intricate design data.

Ensuring that racial and ethnic minority women are involved in breast cancer research is important to address well-documented current disparities in cancer incidence, stages of diagnosis, and mortality rates. This study used a novel interactive focus group method to identify innovative communication strategies for recruiting women from two minority groups-Latinas and Asian Americans-into the Komen Tissue Bank, a specific breast cancer biobank clinical trial. Through activities that employed visual interactive tools to facilitate group discussion and self-reflection, the authors examined perspectives and motivations for Asian American women (N = 17) and Latinas (N = 14) toward donating their healthy breast tissue. Findings included three themes that, while common to both groups, were unique in how they were expressed: lack of knowledge concerning breast cancer risks and participation in clinical research, cultural influences in BC risk thinking, and how altruism relates to perceived personal connection to breast cancer. More significantly, this study illuminated the importance of using innovative methods to encourage deeper, more enlightened participation among underrepresented populations that may not arise in a traditional focus group format. The findings from this study will inform future health communication efforts to recruit women from these groups into clinical research projects like the Komen Tissue Bank.

Since COVID-19 pandemic has been continuously rising and spreading, several original contributions and review articles on COVID-19 started to appear in the literature. The review articles are mainly focus on the current status of the pandemic along with current status of the corona diagnosis and treatment process. Due to some disadvantages of the currently used methods, the improvement on the novel promising diagnosis and treatment methods of corona virus is very important issue. In this review, after briefly discussing the status of current diagnosis and treatment methods, we present to the scientific community, novel promising methods in the diagnosis and treatment of COVID-19. As with other novel approaches, first, the diagnosis potential of mass spectroscopy and optical spectroscopic methods such as UV/visible, infrared, and Raman spectroscopy coupled with chemometrics will be discussed for the corona virus infected samples based on the relevant literature. In vibrational spectroscopy studies, due to complexity of the data, multivariate analysis methods are also applied to data. The application of multivariate analysis tools that can be used to extract useful information from the data for diagnostic and characterisation purposes is also included in this review. The reviewed methods include hierarchical cluster analysis, principal component analysis, linear and quadratic discriminant analysis, support vector machine algorithm, and one form of neural networks namely deep learning method. Second, novel treatment methods such as photodynamic therapy and the use of nanoparticles in the in-corona virus therapy will be discussed. Finally, the advantages of novel promising diagnosis and treatment methods in COVID-19, over standard methods will be discussed. One of the main aims of this paper is to encourage the scientific community to explore the potential of this novel tools for their use in corona virus characterization, diagnosis, and treatment.

Neck of femur fractures have often been termed as \"The Unsolved Fractures\", since they have a guarded outcome even after improved understanding of biomechanics and biology of this area. Gap-nonunion is one such dreaded complication of this fracture, especially in younger (<60 years) population, where arthroplasty may not be the best go-to option. We have earlier described \"The AIIMS BOX\" technique to manage such cases of gap non-union in neglected neck femur fractures [1]. Here we intend to describe a more successful modification of this technique. We operated 7 cases of gap non-union with our new \"Cage in Box\" strategy and followed these cases for 5 years. 6 patients from this group achieved excellent to good outcomes and only 1 reported a poor outcome. All the patients, except the one with poor outcome, could walk without aid and do activities of daily living independently. 3 patients developed AVN but had no evidence of collapse. 3 patients also developed Coxa vara, but it was significant only in one case. 6/7 patients were able to squat. We describe this method in detail and feel this can be a viable option in the armamentarium of orthopedic surgeons, along with valgus osteotomy, vascularized and non-vascularized fibular strut graft as well as Meyer\'s Graft, to help them solve this unsolved fracture.

The transient nature of the internal pore structure of particulate wall flow filters, caused by the continuous deposition of particulate matter, makes studying their flow and filtration characteristics challenging. In this article we present a new methodology and first experimental demonstration of time resolved in-situ synchrotron micro X-ray computed tomography (micro-CT) to study aerosol filtration. We directly imaged in 4D (3D plus time) pore scale deposits of TiO2 nanoparticles (nominal mean primary diameter of 25 nm) with a pixel resolution of 1.6 μm. We obtained 3D tomograms at a rate of ∼1 per minute. The combined spatial and temporal resolution allows us to observe pore blocking and filling phenomena as they occur in the filter\'s pore space. We quantified the reduction in filter porosity over time, from an initial porosity of 0.60 to a final porosity of 0.56 after 20 min. Furthermore, the penetration depth of particulate deposits and filtration rate was quantified. This novel image-based method offers valuable and statistically relevant insights into how the pore structure and function evolves during particulate filtration. Our data set will allow validation of simulations of automotive wall flow filters. Evolutions of this experimental design have potential for the study of a wide range of dry aerosol filters and could be directly applied to catalysed automotive wall flow filters.