IntroductionPCL is a rare and aggressive variant of multiple myeloma (MM), distinguished by the presence of circulating plasma cells in the peripheral blood. A diagnosis of PCL is previously was 20 % but currently can be confirmed when there are at least 5% plasma cells present in the peripheral blood or an absolute plasma cell count of 2000/µl. However, the morphological characteristics of plasma cells can sometimes resemble those of myeloblasts under microscopic examination, which can make it difficult to differentiate between the two cell types. PCL is considered primary when it presents at initial diagnosis and secondary when it occurs in patients with pre-existing MM. Primary PCL accounts for 60–70% of all PCL; the secondary PCL rate is 30–40%.1The diagnostic approach and treatment of PCL is similar to that of MM, but the survival of PCL remains inferior despite novel therapies and stem cell transplantation.

Semiconductor dual-functional photocatalysis composed of selective organic oxidation and reduction has attracted increasing a ttention owing to the green and environmental advantages. Herein, the Nd@g-C 3N 4 dual-functional photocatalysis enabled fluoroalkylative heteroarylation of alkenes with R fSO 2Cl under visible-light and ultrasound conditions was firstly reported. The photogenerated electron-driven reductive production of fluoroalkyl radical paired with photogenerated hole-driven oxidative production of chloride radical resulted in the full utilization of photogenerated carrier for bond formation. The use of sono-photocatalysis enhances both energy efficiency and the rate of chemical reactions. A wide range of N-heteroarenes, alkenes and R fSO 2Cl, were well compatible for this reaction to access valuable fluoroalkylated N-heteroarenes with diverse structural features. We anticipate that this report will provide a sustainable synthetic protocol for fluoroalkylated N-heteroarenes but also develop the photoinduced chloride radical-mediated reaction and the dual-functional photocatalysis.

Land use change is a main factor of affecting water-related ecosystem services (WESs), critical for managing aquatic ecosystem. Nevertheless, how to establish the connection between realistic land management and optimizing WESs is unclear. To address this issue, we selected a typical ecologically vulnerable area, the Ussuri River Basin in China, as an analyzed domain to reveal the driving mechanism of WESs. Furthermore, four land scenarios were established to unfold the connection between land use and WESs. The results are as follows: from 2000 to 2018, cropland expansion led to increases of nitrogen export (+11.55%) and phosphorous export (+12.50%), along with increased food production (+127.27%) and water yield services (+1.41%). We found that the trade-offs occurred mainly within provisioning services (between water yield and food production) or regulating services (between water purification and soil retention). Regarding future scenarios, the traditional ”Grain for Green” scenario failed to benefit ecosystems, not only increasing the trade-off intensity of ecosystem services, but leading to competitive relationships in WESs. As a result, afforestation may not be an optimal solution for the restoration of degraded ecosystems, especially in water-limited areas. The forestland buffer zone scenario was regarded as the optimal land practice, in which WESs were enhanced significantly and trade-offs were reduced between provisioning services, indicating that tree-planting near waters maintained both ecological benefits and fundamental grain outputs. These results highlighted importance of land management on WESs, offering a prospective evaluation of ecosystem service benefits under future development pathway.

Objective and design: The growing demand for transparency about the efficacy of healthcare has accelerated the use of Patient-Reported Outcome Measures (PROMs), but their integration into daily practice is challenging. This observational study describes how the Septoplasty Healthcare Monitor (SHM) addresses these challenges and highlights the benefits of standardized outcome assessments and visualization for various stakeholders, including physicians and patients. Main outcome measures: Since 2014, all eligible septoplasty patients have been included in the SHM. Patients are automatically offered the Nasal Obstruction Symptom Evaluation (NOSE) scale and bilateral Visual Analogue Scales (VAS) to assess nasal obstruction before initial consultation, and during postoperative visits. Data are entered into a preformatted database and automatically analyzed. Real-time results are visually presented on a user-friendly dashboard. Results: A total of 173 patients participated. First, the dashboard provides insights into outcomes on a cohort level. The mean NOSE scores significantly decreased from 68.8 ± 19.0 at baseline to 19.8 ± 22.3 at 12 months. VAS scores improved from 4.6 ± 3.0 (left) and 4.7 ± 2.9 (right) preoperatively to 7.5 ± 2.1 (left) and 7.6 ± 1.7 (right) at 12 months ( p < 0.001). Second, quality of care is monitored through annual performance metrics, and can be improved by critically appraising auto-identified underperforming patients. Third, visualization of individual PROM symptom-severity scores in relation to peers assists in patient-counseling and shared decision-making. Conclusion: The integration of standardized outcome assessments into daily practice is highly valuable but challenging. The SHM addresses these challenges and offers opportunities to enhance septoplasty care standards.

At-home testing of glucose levels is crucial for safe monitoring of a variety of diseases, such as pancreatitis, psoriasis, cirrhosis, acute myocardial infarction, and, of course, diabetes. Current blood tests are invasive, leading to the research of alternative biofluids such as saliva, tears, and sweat. Nevertheless, such fluids are limited in quantity and contains various interfering molecules, posing stringent technological requirements. In this study, a simple paper-based glucose sensor is designed by using the conductive polymer poly(3,4-ethylene-dioxythiophene) polystyrene sulfonate (PEDOT:PSS) and a bi-enzymatic solution of Horseradish Peroxidase (HRP) and Glucose Oxidase (GOx). Unlike most electrochemical glucose sensors, this sensor employs a chemiresistive mechanism, allowing simple configurations, low costs, and easy signal measurements. The designed sensor demonstrates a working range suitable for various biofluid analysis, e.g., saliva, with a limit of detection of 1.1 µM and a linear detection range of 102 – 104 µM while only requiring 40 µL sample volume. Detection in whole artificial saliva is also carried out to demonstrate the sensor applicability. The limited analyte volume required, and the suitable detection range and limit of detection achieved by this sensor make it an excellent candidate for developing a non-invasive, at home glucose meter.

The rapid integration of technology in education has paved the way for innovative approaches to teaching and learning. Among these, social media and artificial intelligence (AI) stand out as transformative tools reshaping traditional pedagogical methods. This paper explores how digital pedagogy, augmented by these technologies, is unbinding the constraints of conventional education, fostering personalized learning, enhancing collaboration, and redefining the role of educators. By examining case studies and theoretical perspectives, we shed light on the profound implications of these tools for inclusivity, engagement, and lifelong learning.

The integration of artificial intelligence (AI) and social media into education has introduced significant shifts in pedagogy, prompting the evolution of traditional classroom dynamics into flexible, digitally enhanced learning environments. This paper explores the transformative effects of these technologies on teaching practices, focusing on their roles in enhancing accessibility, engagement, and personalized learning. The relationship between AI, social media, and pedagogy is examined through the lens of educational inclusivity, ethical implications, and the redefined role of educators. By analyzing how these digital tools reshape the learning process, this research provides insights into how technology can be harnessed to create more dynamic, inclusive, and equitable educational experiences.

The advent of Artificial Intelligence (AI) has transformed multiple fields of research, including qualitative research, by offering innovative tools and methodologies. These technological advancements have streamlined data analysis, enhanced data collection, and introduced novel ways to engage with qualitative data. However, the integration of AI into qualitative research also raises significant challenges related to ethics, data privacy, and the reliability of AI-driven results. This paper explores how AI is reshaping qualitative research, discusses the new tools emerging in the field, and addresses the challenges faced by researchers. By examining the implications of these technologies, the paper aims to provide insights into how qualitative researchers can navigate the complexities of an AI-enhanced research landscape while maintaining rigor and ethical standards.

The evolution of privacy legislation, including GDPR, CCPA, and similar frameworks, has significantly impacted the digital marketing ecosystem. These laws restrict traditional datadriven practices while opening pathways for more transparent and consumer-focused strategies. This paper explores how marketers are adapting to these changes, finding innovative ways to comply with regulations while maintaining the effectiveness of their campaigns. By analyzing case studies and current trends, it identifies how ethical practices, privacy-preserving technologies, and a shift toward first-party data are reshaping the industry. The study emphasizes the dual opportunities of compliance and innovation, highlighting the importance of building trust in a privacy-conscious world.

The digital marketing landscape is increasingly influenced by evolving privacy legislation, compelling businesses to innovate while ensuring compliance. Laws such as GDPR, CCPA, and other regional regulations aim to safeguard consumer data, creating a complex environment for marketers striving to personalize user experiences. This paper examines the implications of privacy legislation on digital marketing strategies, exploring how companies can balance consumer privacy with innovation. It highlights the challenges and opportunities presented by stricter data regulations, emphasizing the need for transparency, ethical practices, and the adoption of privacy-centric technologies. By analyzing real-world case studies and trends, the study offers actionable insights for businesses to adapt their marketing strategies while maintaining compliance and fostering consumer trust.

This paper examines the shift toward privacy-first marketing strategies, including the use of zero-party and first-party data, privacy-preserving technologies, and contextual targeting to deliver meaningful customer experiences without infringing on personal data rights. It also highlights the growing importance of ethical storytelling, transparent communication, and consumer trust as key drivers of brand loyalty in a privacy-conscious era. Through real-world examples and emerging best practices, the research illustrates how businesses can maintain agility and creativity in their campaigns while adhering to strict compliance standards. It argues that privacy and innovation are not mutually exclusive but can coexist harmoniously to create a new paradigm of ethical, effective, and consumer-centric digital marketing.

The paper delves into the challenges posed by reduced access to third-party data and the deprecation of tracking technologies while highlighting solutions like privacy-by-design frameworks, first-party data strategies, and AI-powered contextual targeting. It emphasizes the importance of consumer trust, transparency, and ethical data practices as pivotal elements of successful marketing campaigns in this era. Through case studies and emerging trends, the research showcases how companies can balance compliance with creativity, ensuring their marketing efforts remain effective and innovative without breaching privacy standards. By adopting a privacy-first mindset and leveraging technology responsibly, organizations can redefine customer engagement, fostering loyalty and competitive advantage in the face of increasing regulation.

Objectives: Conducting a retrospective analysis of the clinical characteristics and evolution of patients with spinal muscular atrophy (SMA) type 1 and 2 which were treated with the new modifying therapies. Methods: A descriptive, cross-sectional and retrospective study was conducted with a target population of patients with a genetic diagnosis of SMA treated with nusinersen or onasemnogene abeparvovec-xioi (OAX) who were monitored by the external consultation services of pediatric pulmonology in a tertiary hospital. The data were collected from their electronic clinical records. Results: The study describes 6 patients with ages from 14 months to 11 years, 4 of whom had a diagnosis of SMA type 1 and 2 with a diagnosis of SMA type 2. With regard to their treatment, 3 patients received nusinersen, 2 patients received OAX, and 1 patient received OAX followed by nusinersen. The number of emergency consultations due to respiratory infections per year of treatment was 0.3/year for patients treated with OAX and 0.75/year for patients treated exclusively with nusinersen. None of the patients treated with OAX have required hospitalization for a respiratory infection to date. With regard to respiratory support, two patients had a tracheostomy, and the rest received nocturnal noninvasive mechanical ventilation as a preventive measure. Two of the patients had undergone gastrostomy. The patients treated with OAX have shown an improvement in their motor functions according to the CHOP INTEND score. Conclusions: The description of different real-life cohorts will make it possible to homogenize the management of these patients and provide realistic expectations regarding the evolution of their condition.

The Ramapo Seismic Zone (RSZ) in the Northeastern United States hosts frequent but poorly understood intraplate earthquakes, potentially posing a significant hazard to the nearby New York metropolitan area. The 5 April 2024, Mw4.8, Tewksbury, New Jersey earthquake, provides a rare opportunity to study the RSZ seismicity. We applied machine-learning-enhanced backprojection, matched-filtering, correlation-timing and double-difference methods to continuous waveforms recorded at local and regional stations to detect and locate about 2,000 aftershocks (Mw> 0.0) within the 74 days following the mainshock. They reveal a single, 51o east-southeast dipping fault plane possibly abutting the Ramapo fault at depth to the north. Aftershock locations are consistent with a shallow (∼ 4km) mainshock hypocenter with rupture propagating downward and terminating at a depth of about 6km. A relatively high Gutenberg-Richter _b_-value (b ≈ 1.19) and a low aftershock spatial fall-off rate (γ ≈ 1.8) suggest that the Tewksbury sequence activated a rough, immature fault.

The future of our nation’s semiconductor manufacturing capacity hinges on the industry’s ability to expand the workforce. Generating interest in semiconductor careers is crucial; without it, individuals may be less likely to pursue and fill these essential roles. Degree holders will be pivotal to these efforts, so workforce development initiatives must prioritize attracting college students to the industry. Given the high costs of hands-on semiconductor manufacturing experiences available to students, researchers must find more affordable experiential learning options. Augmented reality presents a promising solution by offering college students a more accessible learning experience, which can increase their interest in semiconductor manufacturing careers.

The aim of this work is to optimize the existing formula based on Wilson's theorem to reduce the magnitude of the computation results. Wilson's theorem states: if p is a prime number, then (p-1)! + 1 is divisible by p (p-1)! ≡ -1 (mod p). The function (p-1)! increases very rapidly and reaches huge values. When the values of p are large, the calculations become resource-intensive, so it is necessary to reduce the upper limit of the calculation results.

Semi-arid ecosystems offer very limited resources to plants, but they are inhabited by incredibly diverse communities of winter annual plants. Ecological theory suggests that a high degree of specialization in resource use and in interactions among plants and soil fungi may explain the coexistence of ecologically similar species in such diverse communities. Species-specific variation in net outcome (positive vs negative) of plant-soil fungi interactions, may lead to variation in mean fitness differences thus increasing opportunities of coexistence. Few studies tested how resources (water and nutrients) in combination with soil fungi affect plants’ fundamental niche across life stages. We experimentally tested germination and fitness differences under different combinations of water, nutrients and soil fungi treatments, using six winter annual species with different degrees of mycorrhizal dependence. Germination success of four out of six species was reduced by the absence of soil fungi, and this response was more severe for obligate mycorrhizal species. Presence of soil fungi ameliorated the production of plant biomass especially under limited water or nutrients, corroborating findings that beneficial interactions with soil fungi alleviate abiotic stress. This response was strong in mycorrhizal dependent species, but highly variable among non-mycorrhizal species, likely due to species-specific outcomes of interactions among plants and pathogenic fungi. We suggest that absence of important symbionts may reduce germination and increase seed dormancy, thus favoring temporal niche partitioning among species, while the net outcomes of plant-soil fungi interactions may reduce mean fitness differences favoring coexistence via equalizing processes.

Dysregulated proteostasis in the retina represents a promising avenue for discovering novel therapeutic targets and diagnostic biomarkers for neurodegenerative diseases with ocular manifestations. Advanced mass spectrometry-based proteomics techniques have shown considerable potential in investigating the retinal proteome in diseases such as glaucoma, age-related macular degeneration, diabetic retinopathy, retinitis pigmentosa, as well as Alzheimer’s disease (AD), amyotrophic lateral sclerosis, and Parkinson’s disease. Recent proteomics innovations are overcoming challenges such as limited sample size and protein coverage that previously hindered comprehensive retinal proteome analysis. Notably, the incorporation of artificial intelligence (AI)-driven computational pipelines, including GPU-accelerated deep learning architectures, has markedly enhanced the precision and effectiveness of retinal proteomics. These advances facilitate high-resolution identification of novel protein signatures within large-scale multi-omics datasets. Furthermore, the integration of advanced AI with state-of-the-art big data infrastructures supports the early detection of biomarkers in neurodegenerative diseases with ocular involvement, offering unprecedented disease specificity and sensitivity. In addition to these computational strides, emerging complementary and alternative technologies continue to provide valuable tools for retinal analysis, expanding the potential for biomarker discovery in both ophthalmic and neurodegenerative disorders. The development of novel proteomic workflows is expected to play a critical role in advancing biomarker discovery, not only for ophthalmic conditions but also for other neurodegenerative diseases, including AD. This review summarizes recent advancements in retinal proteomics, with a particular focus on neurodegenerative and ocular diseases.

Purpose: Guidelines-directed medical therapy (GDMT) may benefit patients with heart failure (HF) reduced ejection fraction ((HFrEF, ≤40%), however, there are significant gaps between guidelines and real-world practices. The aim of this study was to evaluated prescribing adherence to the recommended GDMT in HFrEF patients using the global guideline adherence score. Method: A retrospective study among HFrEF patients at the National Heart Centre in Muscat, Oman, was conducted between 1st January and 30th June 2022. The optimum target doses were identified according to the 2021 European Society of Cardiology HF guidelines. Thus, for eligible patients, prescribing all indicated GDMT in doses ≥50% of the target dose is considered good adherence; the use of more than half of the medications in doses ≥50% of the target dose, moderate adherence; and the use of less than half the recommended medications and/or in doses <50% of target dose, poor adherence. Univariate statistics were used for the analysis. Results: The overall mean age of the cohort was 57 ±13.6 years with a predominance of male patients (70%; n=180). The overall prescribing adherence to guideline-recommended HF medications was 71% good, 22% moderate, and 7% poor. There was a significate association between the sub-optimal dose of GDMT and patients with hypertension (P=0.004), dilated cardiomyopathy (P=0.015), older age (P=0.004) and chronic kidney disease (P=0.001). Conclusion: Prescribing adherence to recommended GDMT in Oman is similar to that of international studies. Furthermore, sub-optimal GDMT titration was significantly associated with older age and comorbidity, suggesting that frailty perception may have an impact on GDMT titration.

There has been a significant increase in unexpected deaths due to major adverse cardiocerebrovascular events (MACCE) in the post-COVID-19 era. How to effectively control and prevent these events and adverse clinical outcomes is a vital topic in the globe. Since the innovative “magic polypill” or E(e)SEEDi plays a crucial role in human health and longevity, it just likes a “super-vaccine” due to improvement of immunity and prevention of cardiovascular diseases (acute myocardial infarction, venous thrombosis, stroke and sudden cardiac death), as well as diabetes and cancer. Additionally, it can benefit the health of individuals who are more prone to have unhealthy lifestyle. The interconnected nature of these factors, as explained by game theory, may contribute to the increased risk of MACCE and understanding related macro-mechanisms. In conclusions, as a “super-vaccine” with crucial effects on blood and vascular health, the E(e)SEEDi helps prevent MACCE among individuals, particular young and middle-aged those.

Panic responses often lead to irrational behaviors. This study examines the influence of personality traits on panic-induced emotional contagion and phototaxis behavior, combining physiological measurements (Skin Conductance Level (SCL) and Electroencephalography (EEG)) with personality assessments (OCEAN model). The aim is to reveal the corresponding physiological and neurophysiological changes in panic-driven evacuation behavior across different personality types. 28 participants were divided into high extraversion-neuroticism (HEN) and low extraversion-neuroticism (LEN) groups based on their OCEAN traits. Two virtual reality experiments’results show that personality traits significantly affect phototaxis behavior, skin conductance response, and EEG activity. Specifically, the HEN group exhibited more pronounced phototaxis behavior, while the LEN group showed greater skin conductance increases and a significant reduction in θ-band. Additionally, under panic-inducing emotional contagion stimuli, the LEN group exhibited significant increases in both θ-band and α-band, whereas the HEN group showed only a notable increase in θ-band. These findings highlight the need to account for individual differences in emergency evacuation planning and suggest that personalized evacuation strategies could reduce risks and improve efficiency during emergencies.

The dynamics of reproductive allocation (RA) in herbaceous plant communities, particularly in response to varying environmental conditions such as drought stress and competitive interactions, remain underexplored. This study aims to fill this gap by hypothesising that both belowground resource limitation and the presence of dominant species significantly influence RA strategies within plant communities, leading to different patterns of reproductive synchrony. We also expected different effects of resource limitations on intraspecific synchrony in RA compared to interspecific synchrony. We conducted a mesocosm experiment in an experimental garden over five years, exposing wetland plant communities (one dominant species and three subordinate species) to different drought stress regimes and a dominant removal treatment. The results suggested that belowground resource limitation and aboveground competition critically influence RA synchrony, with increased synchrony under reduced competition and increased stress. The competitively dominant species require more belowground resources for seed reproduction, while competitively weaker subordinate species can reproduce at lower resource levels. Furthermore, our findings highlighted contrasting responses in intra- and interspecific flowering synchrony to the resource limitations, which may reflect the different importance of evolutionary synchronising factors and competitive and facilitative effects between conspecifics and between species within the community. Individuals of species synchronised flowering mainly at their favourable sites where generative reproduction is more efficient, i.e. dominant species at wet sites, whereas subordinate species at drought stress treatments with reduced competition. This research provides empirical evidence for the multiple resource limitation model and highlights the strategies of plants in resource-limited environments, as well as the ecological importance of reproductive synchrony within herbaceous plant communities.

The 14 paralogs of the POTE gene family are distributed across eight distinct chromosomes in humans. The POTEE (POTE ankyrin domain family member E) has been shown to express in several human malignancies, including colon, prostate, lung, breast, ovarian, and pancreatic cancers. This study aimed to raise POTE2B (isoform 2 of POTEE protein) polyclonal antibodies in BALB/c mice to characterise and investigate the early detection of human POTEE protein in malignant cells. To generate a specific pol

Tolerance of the Venom Immunotherapy Switch from a Highly Purified Aluminium Hydroxide Adsorbed Hymenoptera Venom Extract to a Nonpurified Aqueous Venom ExtractAnna Gschwend1, Lukas Joerg11Division of Allergology and Clinical Immunology, Department of Pulmonary Medicine, Allergology and Clinical Immunology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland