Powerful Option Research Articles

Investigating the effect of combined radiofrequency cold plasma (RF-CP) treatment on techno-functional attributes of Cashewnut

In the realm of food safety, dried foods often find themselves on the favourable side of the risk spectrum, enjoying the reputation of being relatively safer. However, dried food products are reportedly contaminated by microorganism beyond permissible limits, thus, depleting their quality, shelf-life, etc. and pose a threat to the consumers. This study aims to explore the effect of radiofrequency low-pressure cold plasma (RF-CP) processing on cashew nuts, using four gas combinations: Nitrogen (N2), Argon (Ar), N2+O2, and Ar+O2. Dried cashew nut kernels underwent RF-CP treatment at six different power options (60, 90, 120, 150, 180, and 210 W), at four distinct time (5, 10, 15, and 20 min). Following the treatment, the samples underwent proximate analysis, microbial load reduction, sensory analysis, peroxide value, and texture analysis. The findings exhibited a direct relationship between plasma power and treatment duration, indicating that an escalation in both parameters induced proportional enhancement in the reduction rate of microbes, with a maximum reduction of over 99% in total plate count, yeast and mould count at 120 W for 20 min and 150 W for 15 min for N2+O2 and Ar+O2 gas combinations, respectively. No statistically significant difference was observed in the sensory, nutritional, and peroxide value between the treated and untreated samples (p > 0.05). However, the moisture content of treated sample decreased, and firmness increased with an increase of power and RF-CP exposure time. This research demonstrates the feasibility of using RF-CP to decontaminate cashews by inactivating microbes, extending shelf life, and altering surface properties, which may enhance texture and appearance. However, it may also induce oxidative changes in lipids and proteins, potentially affecting flavor, nutritional quality, and allergenicity. It is an emerging and alternative to high-temperature processing for disinfecting products like nuts, spices, aromatic plants, and other delicate and luxurious foods.

Adoption of Rooftop Solar Power as an Energy Option: A Household Level Study in Pune Smart City

Power generation using fossil fuels on a large scale contributes to global greenhouse gases and, therefore, impacts climate change. Renewable energy sources like solar power are needed to overcome such adverse impacts. Solar energy has received attention in the recent years due to both technological improvements resulting in cost reductions as well as the government policy push for renewable energy development and utilization. This research concerns with the adoption of rooftop solar power as an energy option at household level in the context of smart cities. We conducted a questionnaire survey on a sample of resident households in Pune smart city and analysed various parameters concerning households’ adoption. It has been found that the respondents are less willing to adopt rooftop solar power option for the lack of awareness of energy conservation and climate change issues, lack of financial incentives for the adoption and concern for operational issues that arise after the adoption; the respondents who are aware are more likely to adopt it in a timeframe of 1–3 years. Statistical analysis of various important relationships may be useful for future research on household adoption of renewable energy options, such as rooftop solar power.

A Comprehensive Review of CO2 Mineral Sequestration Methods Using Coal Fly Ash for Carbon Capture, Utilisation, and Storage (CCUS) Technology

CO2 emissions from fossil fuel combustion are the main source of anthropogenic greenhouse gases (GHGs). A method of reducing CO2 emissions is CCUS (carbon capture, utilisation, and storage) technology. One part of CCUS technology involves mineral sequestration as its final stage, utilisation, which can be carried out using natural raw materials or waste. This is a particularly interesting option for power and CHP plants that use coal as their primary fuel. Combustion processes produce fly ash as a waste by-product, which has a high potential for CO2 sequestration. Calcium fly ash from lignite combustion and fly ash from fluidised bed boilers have particularly high potential due to their high CaO content. Fly ash can be used in the mineral sequestration of CO2 via direct and indirect carbonation. Both methods use CO2 and flue gases. Studies conducted so far have analysed the influence of factors such as temperature, pressure, and the liquid-to-solid (L/S) ratio on the carbonation process, which have shown different effects depending on the ash used and the form of the process. Due to the large differences found in the properties of fly ash, related primarily to the type of fuel and boiler used, the process of mineral CO2 sequestration requires much research into its feasibility on an industrial scale. However, the method is promising for industrial applications due to the possibility of reducing CO2 emissions and, at the same time, recovering waste.

BacDive in 2025: the core database for prokaryotic strain data.

In 2025, the bacterial diversity database BacDive is the leading database for strain-level bacterial and archaeal information. It has been selected as an ELIXIR Core Data Resource as well as a Global Core Biodata Resource. Since its initial release more than ten years ago, BacDive (https://bacdive.dsmz.de) has grown tremendously in content and functionalities, and is a comprehensive resource covering the phenotypic diversity of prokaryotes with data on taxonomy, morphology, physiology, cultivation, and more. The current release (2023.2) contains 2.6 million data points on 97334 strains, reflecting an increase by 52% since the previous publication in 2021. This remarkable growth can largely be attributed to the integration of the world-wide largest collection of Analytical Profile Index (API) test results, which are now fully integrated into the database and searchable. A novel BacDive knowledge graph provides powerful search options through a SPARQL endpoint, including the possibility for federated searches across multiple data sources. The high-quality data provided by BacDive is increasingly being used for the training of artificial intelligence models and resulting genome-based predictions with high confidence are now used to fill content gaps in the database.

A hybrid MAPbI3/PEDOT-ZrO2 perovskedot composite for enhanced stability and charge transport in photo-batteries

Designing flexible photo-batteries that are capable of charged directly by light is critical for improving off-grid power options. This paper presents a unique photo-battery design that uses a MAPbI3/PEDOT as the effective light-harvesting and hole-transporting layer, and zirconium oxide (ZrO2) as the channel for electrons and hole-blocking layer. The MAPbI3 perovskite material absorbs sunlight and develops charge carriers, while PEDOT helps transport holes to the anode, improving charge separation and minimizing recombination losses. ZrO2, with its strong electron mobility and great chemical stability, provides fast transport of electrons to the cathode. It also efficiently blocks holes, increasing overall charge transfer dynamics. This improved design improves photo-conversion efficiency by up to 0.51 % and has a high capacity retention rate of around 96 % after 500 cycles. This improved MAPbI3/PEDOT/ZrO2 photo-battery could decrease light charging time by three times, enabling adaptable, light-rechargeable batteries more practical for real-world applications.

Cyclization by Intramolecular Suzuki-Miyaura Cross-Coupling-A Review.

Ring systems of all sizes are frequent core or substructures in natural products and they are important elements of many drug molecules, as they often confer high binding affinity to and selectivity for disease-relevant biological targets. A uniform key transformation in the synthesis of such structures is the cyclization step. Among the various approaches that have been developed for ring closure, the intramolecular Suzuki-Miyaura reaction has emerged as a powerful option for the construction of normal- and medium-sized rings as well as macrocycles, due to its stereospecificity, the mild reaction conditions, and the non-toxic nature of the boron by-products. In this review, we summarize the state-of-the-art of the application of intramolecular Suzuki-Miyaura cross-coupling reactions in the construction of (macro)cyclic frameworks of natural products and bioactive molecules of synthetic origin, covering (mostly) examples that have been reported since 2015. Target molecules prepared via intramolecular Suzuki-Miyaura cross-coupling as a key step range from natural products/natural product analogs to synthetic drug candidates, featuring ring sizes from 4 to ≫12. We highlight the utility, scope, and limitations of the reaction for different ring sizes and arrays of functional groups. Where possible, comparisons with other methods of cyclization are provided.

Color and Attention for U : Modified Multi Attention U-Net for a Better Image Colorization

Image colorization is a tedious task that requires creativity and understanding of the image context and semantic information. Many models have been made by harnessing various deep learning architectures to learn the plausible colorization. With the rapid discovery of new architecture and image generation techniques, more powerful options can be explored and improved for image colorization tasks. This research explores a new architecture to colorize an image by using pre-trained embeddings on U-Net combined with several attention modules across the model. Using embeddings from a pre-trained classifier provides a high-level feature extraction from the image. Conversely, multi-attention gives a little taste of image segmentation so that the model can distinguish objects in the image and further enhance the additional information given by the pre-trained embeddings. Adversarial training is also utilized as a normalization to make the generated image more realistic. This research preferred Parch GAN over base GAN as the discriminator model to ensure that the colorization has a consistent quality across all patches. The study shows that this U-Net modification can improve the generated image quality compared to a normal U-Net. The proposed architecture reaches an FID of 48.6253, SSIM of 0.8568, and PSNR of 19.7831 by only training it for 25 epochs; hence, this research offers another view of image colorization by using modules that are often used for image segmentation tasks.

Soil Nutrient Analysis and Automatic Monitoring in Precision Agriculture

ABSTRACT The higher productivity from soil can be achieved through Wireless Sensor Networks (WSNs) technology; for this reason, the implementation of WSNs in precision agriculture is increasing day by day. Among the different technologies for crop monitoring, WSNs are recognized as a powerful option for collecting and processing data in the agricultural domain, with low cost and low energy consumption. The ultimate aim of this paper is to predict the precise values of soil nutrients nitrogen, phosphorus, and potassium (NPK) using a machine learning (ML)-based mathematical model formulation. The proposed system will use Global System for Mobile Communications (GSM) technology to automatically monitor soil parameters. It transfers soil data over the mobile network using a GSM modem. In the hardware part, sensor node units were developed to fetch and load data through the energy-efficient GSM, utilizing a bi-directional multi-level text messaging option to improve the alarm system’s efficiency. The system contains sensors such as potential of hydrogen and humidity (PH), which are used to monitor soil data collected from the sensors by the microcontroller. Additionally, as a novel contribution, machine learning based on regression models is applied to the NPK data. A novel data interpolation approach is proposed for data oversampling. The R2 values are compared, achieving nearly 99.5% accuracy in all cases. This paper focuses on various challenges and scalability issues encountered in research and discusses different results obtained by monitoring various soil parameters in a real-time agricultural environment.

Translational evaluation of metabolic risk factors impacting DBS efficacy for PD-Related sleep and depressive disorders: preclinical, prospective and cohort studies.

Parkinson's disease (PD) is linked with metabolic risk factors including body mass index (BMI), fasting blood glucose (FBG), cholesterol levels, and triglycerides (TG). The extent to which these factors affect motor symptoms, depression, and sleep problems in PD, as well as their role in determining the success of deep brain stimulation (DBS) therapy, is yet to be fully understood. This study delved into the effects of metabolic risk factors like BMI, FBG, cholesterol, and TG on the outcomes of DBS in treating PD-related depression and sleep disturbances, across both mouse models and human subjects. DBS showcased noticeable betterment in depression and sleep perturbations in both PD-afflicted mice and patients. High-sugar-high-fat diet aggravates MPTP-induced depression and sleep disorders in mice. PD-afflicted individuals presenting with depressive and sleep disorders demonstrated elevated metrics of BMI, FBG, blood cholesterol, and TG. Remarkably, these metrics bore considerable adverse influences on the efficiency of DBS in ameliorating depression and sleep issues, yet spared motor symptoms. The favorable impacts of DBS persisted for approximately 6 years, post which a significant decline was noted. Importantly, our translational evidence from both murine controls and patient cohorts indicated that antihyperglycemic and antihyperlipidemic therapies bolstered the efficacy of DBS in mitigating PD-related depression and sleep disturbances, without impinging upon motor functions in patients. In summary, this research emphasizes that DBS is a powerful treatment option for depression and sleep issues in PD, with its success influenced by metabolic risk factors. It further suggests that incorporating treatments for high blood sugar and cholesterol can enhance the efficacy of DBS in treating depression and sleep disturbances in PD, without impacting motor symptoms, highlighting the importance of metabolic risk management in PD patients receiving DBS.

Chemical reactions as a means of installing adlayers on electron transport layers

Adlayers are often placed at metal-on-organic interfaces as a common strategy to alleviate damage during metal deposition by thermal evaporation. Methods of chemically installing adlayers have been recently demonstrated on organic semiconductors that address these interfacial issues while providing many secondary benefits. Chemical installation has yet to be attempted at the cathode-electron transport layer (ETL) interface within organic light-emitting devices (OLEDs), offering a powerful option to optimize electron injection, improve surface wetting, and reduce metal penetration. Here, a reaction between TPBi (2,2′,2′’-(1,2,5-benzinetriyl)-tris(1-phenyl-1-H-benzimidazole) and propylene oxide results in a controllable 1–3 nm thick layer of propylene oxide as shown by high-resolution X-ray photoelectron spectroscopy (XPS) and energy dispersive X-ray spectroscopy (EDX). The reactive addition of the adlayer at temperatures below 40℃ does not affect the morphology of the thin film and reaches a high degree of coverage within 3 h. Integration of this layer into a phosphorescent OLED does not introduce any significant negative impact on device function. This result opens up the possibility of introducing further specific functionality into the adlayer to engineer OLED performance.

A comprehensive protocol for efficient differentiation of human NPCs into electrically competent neurons

BackgroundThe study of neurons is fundamental to unraveling the complexities of the nervous system. Primary neuronal cultures from rodents have long been a cornerstone of experimental studies, yet limitations related to their non-human nature and ethical concerns have prompted the development of alternatives. In recent years, the derivation of neurons from human-induced pluripotent stem cells (hiPSCs) has emerged as a powerful option, offering a scalable source of cells for diverse applications. Neural progenitor cells (NPCs) derived from hiPSCs can be efficiently differentiated into functional neurons, providing a platform to study human neural physiology and pathology in vitro. However, challenges persist in achieving consistent and reproducible outcomes across experimental settings. Comparison with existing methodsOur aim is to provide a step-by-step methodological protocol, augmenting existing procedures with additional instructions and parameters, to guide researchers in achieving reproducible results. Methods and resultsWe outline procedures for the differentiation of hiPSC-derived NPCs into electrically competent neurons, encompassing initial cell density, morphology, maintenance, and differentiation. We also describe the analysis of specific markers for assessing neuronal phenotype, along with electrophysiological analysis to evaluate biophysical properties of neuronal excitability. Additionally, we conduct a comparative analysis of three different chemical methods—KCl, N-methyl-D-aspartate (NMDA), and bicuculline—to induce neuronal depolarization and assess their effects on the induction of both fast and slow post-translational, transcriptional, and post-transcriptional responses. ConclusionOur protocol provides clear instructions for generating reliable human neuronal cultures with defined electrophysiological properties to investigate neuronal differentiation and model diseases in vitro.

Pricing Asian options under the mixed fractional Brownian motion with jumps

The mixed fractional Brownian motion (mfBm) has gained popularity in finance because it can effectively model long-range dependence, self-similarity, and is arbitrage-free. This paper focuses on mfBm with jumps modeled by the Poisson process and derives an analytical formula for valuing geometric Asian options. Additionally, approximate closed-form solutions for pricing arithmetic Asian options and arithmetic Asian power options are obtained. Numerical examples are provided to demonstrate the accuracy of these formulas, which rely on a convenient approximation of the option strike price. The proposed approximation demonstrates significantly higher computational efficiency compared to Monte Carlo simulation.

Digital Functional Blocks Implementation of PWM and Control for a High-Frequency Interleaved Y-Inverter Motor Drive

This paper is about the development and demonstration of a motor drive for e-transport applications based on an innovative hybrid Si-SiC dual switching frequency interleaved buck–boost Y-inverter and a single-rotor Halbach machine. In particular, the focus is the implementation of the required discontinuous inverter modulation scheme, input voltage feed-forward and motor currents feedback control loops, as well as over-voltage, over-current, and over-temperature protections, using an off-the-shelf commercial hardware platform enabling straightforward Simulink-environment programming of all parts, while ensuring the high switching frequency capability required by wide-band-gap semiconductors. Experimental results showed good inverter efficiency, transient dynamic response to load changes, input voltage regulation, and fully functional protection capability, validating the proposed approach as a powerful option for reducing system development time and cost.

Geometric Asian power option pricing with transaction cost under the geometric fractional Brownian motion with [formula omitted] sources of risk in fuzzy environment

In this paper, we obtain an explicit formula to calculate the geometric Asian power option price with floating strike price and transaction cost under the fractional geometric Brownian motion model with w sources of risk and fuzzy parameters. First, by considering the Leland and Kabanov theorems, we derive a non-linear PDE with the transaction cost formula to obtain the option price. Then, using the Green function find a closed form solution for the PDE and achieve the price of the option under different amounts of the model and option parameters. Next, we consider the model’s parameters as fuzzy numbers and acquire a general formula to obtain intervals for the option price under different belief degrees and power option parameter amounts.

NASAKOM DILEMMA AND THE POLITICS OF ISLAMIC ORGANIZATIONS

The political opinions of Islamic organizations throughout the Guided Democracy (1959- 66) era are diverse. For some, this is a dismal period. The rest saw this era as an opportunity to preserve Islamic dominance. Cooperative and non-cooperative politics with power are strategic options for the long-term political power of Islamic mass groups like Nahdhatul 'Ulama (NU) and Muhammadiyah. This study seeks to understand the political perspectives of Indonesia's two largest Islamic organizations in the face of the imposition of Nasakom (religious nationalist and communist) ideology during the Soekarno era. This study takes a qualitative descriptive comparative method. The study's findings suggest that, in terms of character, numerous NU figures found theological grounds to reconcile with Nasakom politics. Meanwhile, Muhammadiyah, whose members include numerous senior Masyumi officials, leans toward the opposition. An accommodating mindset helps the organization to breathe for longer. Meanwhile, the opposition faces the possibility of political stunting. In terms of impact, the two Islamic mass organizations failed to arrest the flow of authoritarianism. They attempted to survive by honoring the Great Leader of the Revolution.

Could coal-fired power plants with CCS be an effective way for carbon neutrality in China?

The transition toward carbon neutrality in China necessitates integrating more renewable energy sources (RES) into the power grid. However, a high share of RES can destabilize the grid, making it crucial to add clean, flexible power sources, such as battery energy storage systems (BESS) and flexible coal power combined with carbon capture and storage (CCS). This study shifted focus from traditional power plants to flexible power solutions, including BESS and CCS, and adopted a macro perspective. An hourly basis simulation model of the power system was developed to assess the cost-effectiveness of these flexible power options. The results revealed that BESS is more cost-effective when RES penetration rates are low, whereas CCS becomes more advantageous as RES constitutes a larger portion of the power supply. Combining BESS and CCS can ensure grid stability and maximize RES utilization. Sensitivity analysis indicated the need to control power demand growth to support this transition effectively.

Adaptive forest management improves stand-level resilience of temperate forests under multiple stressors

Forests are expected to be strongly affected by modifications in climate and disturbance regimes, threatening their ability to sustain the provision of essential services. Promoting drought-tolerant species or functionally diverse stands have recently emerged as management options to cope with global change. Our study aimed at evaluating the impact of contrasting stand-level management scenarios on the resilience of temperate forests in eastern North America and central-western Europe using the individual process-based model HETEROFOR. We simulated the evolution of eight stands over 100 years under a future extreme climate according to four management scenarios (business as usual - BAU; climate change adaptation - CC; functional diversity approach - FD; no management - NM) while facing multiple disturbances, resulting in a total of 160 simulations. We found that FD demonstrated the greatest resilience regarding transpiration and tree biomass, followed by CC and then BAU, while these three scenarios were equivalent concerning the net primary production. These results were however dependent on forest type: increasing functional diversity was a powerful option to increase the resilience of coniferous plantations whereas no clear differences between BAU and adaptive management scenarios were detected in broadleaved and mixed stands. The FD promoted a higher level of tree species diversity than any other scenario, and all scenarios of management were similar regarding the amount of harvested wood. The NM always showed the lowest resilience, demonstrating that forest management could be an important tool to mitigate adverse effects of global change. Our study highlighted that tree-level process-based models are a relevant tool to identify suitable management options for adapting forests to global change provided that model limitations are considered, and that alternative management options, particularly those based on functional diversity, are promising and should be promoted from now on.

Emotional Awareness and Expression Therapy vs Cognitive Behavioral Therapy for Chronic Pain in Older Veterans

Chronic pain is common and disabling in older adults, and psychological interventions are indicated. However, the gold standard approach, cognitive-behavioral therapy (CBT), produces only modest benefits, and more powerful options are needed. To evaluate whether emotional awareness and expression therapy (EAET) is superior to CBT for treatment of chronic pain among predominantly male older veterans and whether higher baseline depression, anxiety, or posttraumatic stress disorder (PTSD) symptoms-key targets of EAET-moderate treatment response. This 2-arm randomized clinical trial was conducted from May 16, 2019, to September 14, 2023, in the US Department of Veterans Affairs Greater Los Angeles Healthcare System. The trial included a racially and ethnically diverse group of veterans aged 60 to 95 years with at least 3 months of musculoskeletal pain. Emotional awareness and expression therapy or CBT, conducted concurrently, each presented as one 90-minute individual session followed by eight 90-minute group sessions. The primary outcome was Brief Pain Inventory pain severity (range, 0 to 10) from baseline to posttreatment (week 10, primary end point) and 6-month follow-up. Secondary outcomes included Patient Reported Outcomes Institute Measurement System Anxiety, Depression, Fatigue, General Life Satisfaction (NIH Toolbox), Pain Interference, and Sleep Disturbance Short Forms, Patient Global Impression of Change (PGIC), and Satisfaction with Therapy and Therapist Scale-Revised. A subset of participants completed the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition). All analyses were for the intention-to-treat population and included all randomized participants. Among 126 randomized participants (66 in the EAET group and 60 in the CBT group; mean [SD] age, 71.9 [5.9] years; 116 [92%] male), 111 (88%) completed posttreatment, and 104 (82%) completed the 6-month follow-up. The EAET was superior to CBT for the primary outcome of reduction in pain severity at posttreatment (estimate, -1.59 [95% CI, -2.35 to -0.83]; P < .001) and follow-up (estimate, -1.01 [95% CI, -1.78 to -0.24]; P = .01). A greater percentage of participants in EAET vs CBT had clinically significant (at least 30%) pain reduction (63% vs 17%; odds ratio, 21.54 [95% CI, 4.66-99.56]; P < .001) at posttreatment. In addition, EAET was superior to CBT on 50% pain reduction (35% vs 7%; odds ratio, 11.77 [95% CI, 2.38-58.25]; P = .002), anxiety (estimate, -2.49 [95% CI, -4.30 to -0.68]; P = .006), depression (estimate, -3.06 [95% CI, -5.88 to -0.25]; P = .03), general life satisfaction (estimate, 1.23 [95% CI, 0.36-2.10]; P = .005), PTSD symptoms (estimate, -4.39 [95% CI, -8.44 to -0.34]; P = .03), PGIC score (estimate, 1.46 [95% CI, 0.77-2.15]; P < .001), and global treatment satisfaction (estimate, 0.28 [95% CI, 0.12-0.45]; P < .001) at posttreatment. Higher baseline depression (estimate, -1.55 [95% CI, -0.37 to 2.73]; P < .001), anxiety (estimate, -1.53 [95% CI, -2.19 to -0.88]; P < .001), and PTSD symptoms (estimate, -1.69 [95% CI, -2.96 to -0.42]; P = .009) moderated greater reduction in pain severity after EAET but not CBT. The results of this randomized clinical trial suggest that EAET may be a preferred intervention for medically and psychiatrically complex patients with pain. The societal burden of chronic pain could be improved by further incorporating the principles of EAET into mainstream clinical pain medicine. ClinicalTrials.gov Identifier: NCT03918642.

CGP-based IO biomarker assessment and treatment utilization across a major US health system.

e23109 Background: Immune checkpoint inhibitors (IO) have become a powerful precision therapy option to treat advanced stage cancer with biomarkers such as PD-L1, tumor mutational burden (TMB), and microsatellite instability (MSI) associated with improved patient response rates. Despite this, many patients do not receive genomic testing for all IO biomarkers. Providence, a large US community health system, developed a pathologist-directed testing protocol where comprehensive genomic profiling (CGP) was routinely used at time of diagnosis for advanced cancer patients. Methods: Advanced cancer patients who received CGP (ProvSeq 523) and IHC testing for PD-L1 between 2019-2023 were included in the study. Patients were required to be treated at Providence and were assessed for presence of IO biomarkers and subsequent therapy selection. Real world data were curated from patient charts and genomic laboratory data by employing a novel natural-language processing (NLP) approach to accelerate abstraction. Results: The study included 2,502 patients (53% female, median age 68y, 83% white). Top 3 tumor types tested were lung (40%), colorectal (9%), and breast (8%). Overall, 58% (N = 1,455) of patients had presence of ≥1 IO biomarker, with 46% (N = 1,155) being PD-L1 positive, and 27% (N = 682) being TMB-H. In PD-L1 negative patients (N = 1,347; 54%), 300 (22%) were TMB-H and 18 (1%) were MSI-H. 53% (N = 767) of patients who harbored an actionable IO biomarker received IO-based therapy. Fewer patients with an IO biomarker received chemotherapy compared to patients without an IO biomarker (23% vs 35%, p &lt; 0.001). Patients who possessed ≥2 IO biomarkers received an IO precision therapy 68% of the time vs 47% in patients with 1 IO biomarker (p &lt; 0.001). In PD-L1 negative patients, 26% (N = 78) of TMB-H patients received IO monotherapy compared to 5% (N = 49) of TMB-L patients. Conclusions: IO biomarker presence is associated with increased precision therapy use. CGP identified many TMB-H patients for IO monotherapy that would have been missed with PD-L1 testing alone. More than half of patients eligible for IO therapy don’t receive it; ongoing analyses will evaluate the impact of pathology-directed reflex testing on IO as well as targeted therapy approaches. [Table: see text]

Electrochemical advanced oxidation of glucosinolates derived from rapeseed meal: Parameter optimization, degradation mechanism and toxicity assessment

Glucosinolates (GLS) are a group of antinutritional compounds present in rapeseed meal that limit its use as feed ingredients. Considering their potentially hazardous effects on both the aquatic environment and animal health, it is necessary to develop green and efficient degradation options for GLS. In the current work, the electrochemical advanced oxidation technology with a boron-doped diamond (BDD) electrode was initially employed for the degradation of GLS. To facilitate parameter optimization, a sequential strategy comprising a definitive screening design and a central composite rotatable design was implemented. Particular attention was paid to the differing roles of five electrolyte salts (NaCl, NaNO3, Na2SO4, NaHCO3 and Na3PO4) during the electrolytic oxidations. The optimal conditions for GLS degradation were found to be a flow rate of 400 mL min−1, a applied current density of 7.75 mA cm−2 and a 2.0 mM NaNO3 medium, yielding mineralization of 82.2 % at 120 min of electrolysis. By combining the results of computational simulation and LC/MS analysis, four possible degradation pathways of allyl GLS at the BDD anode were proposed. And the ecotoxicity of each detected degradation product was determined using the ECOSAR program. Further biological toxicity assay revealed that crude GLS electrolysis reduced the toxicity on model organism Caenorhabditis elegans, reducing its death percentage by 26.80 % and its lipofuscin level by 37.59 % at 48 h. The results showed great promise of BDD technology in engineering applications as a powerful option for the treatment of GLS derived from rapeseed meal.