Case Report: Disseminated Intravascular Coagulation Induced by Aortic Valve Fibroelastoma.AUTHORSThumma, Milanya M.; Northeast Ohio Medical University, College of Medicine, Rootstown, Ohio, United StatesAbu Alya, Walaa; Department of Internal Medicine, Cleveland Clinic Fairview Hospital, Cleveland, Ohio, United States.Corresponding Author: Abu Alya, Walaa; Department of Internal Medicine, Cleveland Clinic Fairview Hospital, Cleveland, Ohio, United States.INTRODUCTIONPapillary fibroelastomas are the second most common type of cardiac tumors. Although the exact mechanism for the development of fibroelastomas is unknown, it is theorized that small microthrombi coalesce on the cusps of the valve. Fibroelastomas are benign on their own; however, they significantly increase the risk of embolizations. This is due to the microthrombi that are at risk to dislodge from the physiological pressures of left ventricular ejection and spread throughout the body. Possible complications include stroke, transient ischemic attack, myocardial infarction, angina, etc.Transesophageal echocardiogram is the gold standard for diagnosing fibroelastoma. They typically appear as pedunculated, mobile masses with stippled edges and are typically less than 10 millimeters. According to one study, surgical resection is recommended for symptomatic cases greater than 10 mm (Kaplan, et al 2020). In addition, prophylactic anticoagulation therapy is initiated to protect against thrombi. This patient’s fibroelastoma wasn’t discovered until after her ischemic stroke. Due to her lack of surgical candidacy, she suffered many complications of the fibroelastoma.Case history and examinationThis patient is a female in her 70s with a past medical history of thrombocytopenia and bladder cancer, originally diagnosed in 2023 with recurrence in mid-2024. A couple months later, she was admitted to the hospital due to an ischemic stroke. During that admission, there was concern for an embolic origin of the stroke, which led to an echo for workup. A fibroelastoma measuring 12 mm x 9 mm was found on the right coronary cusp [images 1 A and B]. She was not a candidate for surgical resection of the fibroelastoma due to her thrombocytopenia. The patient was discharged on Eliquis.Two weeks later, her hematologist/oncologist held the patient’s Eliquis due to thrombocytopenia and concerns for thrombocytic thrombocytopenic purpura. That evening, the patient began experiencing abdominal pain and headaches. The pain and symptoms worsened overnight, resulting in the patient coming to the ED the next morning. She was hemodynamically stable, alert, and oriented at that time without focal deficit.In the ED, CT Abdomen/Pelvis showed acute splenic and bilateral renal infarcts [image 2 and 3]; CT Brain demonstrated a small hemorrhagic infarct in the right frontal/parietal cortex [image 4] . In addition, lab workup indicated a picture similar to DIC, as platelets were 26; fibrinogen was acutely decreased; d-dimer was elevated; and PT/INR and PTT were prolonged.Upon admission, anticoagulants were held initially due to hemorrhagic infarct. She was given platelet infusions and steroids for 3 days to address thrombocytopenia. Two days later, the patient had acute left homonymous hemianopia. MRI brain at that time showed acute right PCA infarct.Differential Diagnosis:Differential diagnoses include disseminated intravascular coagulation (DIC) in the setting of fibroelastoma, cancer-associated coagulopathy, immune thrombocytopenic purpura (ITP), and thrombotic thrombocytopenic purpura (TTP). Vasculitis is less likely given the absence of typical symptoms and rash.Outcome and follow upAfter a lengthy discussion with the patient and her spouse, the decision was made to re-initiate anticoagulation with heparin. The next day, the patient complained of upper quadrant abdominal pain. At that time, a CT abdomen scan showed acute thrombotic occlusions of the proximal jejunal and ileal jejunal branches of the superior mesenteric artery.At that time, the patient was transitioned to inpatient hospice care considering the rapid worsening of her condition.DISCUSSIONThis case illustrates the complex interplay of risk factors contributing to disseminated intravascular coagulation (DIC) and thrombotic events in a patient with aortic valve fibroelastoma. Although fibroelastomas are generally benign tumors, they significantly increase the risk of forming microthrombi, particularly in patients with pre-existing conditions that predispose them to a hypercoagulable state. In this patient, the presence of bladder cancer and thrombocytopenia further complicated her clinical picture.Anticoagulation management was a pivotal concern throughout her care. The decision to hold anticoagulants after her hemorrhagic stroke appeared prudent due to her thrombocytopenic state; however, this allowed thrombotic complications to escalate. While fibroelastomas typically present incidentally, they can lead to significant complications when symptomatic (Gopaldas et al., 2009). This is especially relevant in patients with malignancies, where a hypercoagulable state is often present due to various factors, including the release of procoagulant substances from tumor cells (Kaplan et al., 2020). In this case, the fibroelastoma likely exacerbated her hypercoagulability, leading to a paradoxical increase in thromboembolic events despite anticoagulation with Eliquis.The rapid onset of organ infarcts in this patient is particularly notable. Her CT findings of acute splenic, renal, and jejunal infarcts, coupled with the MRI results of a right PCA infarct, underscores the urgency and severity of her condition. The interplay between the fibroelastoma and her malignancy may have led to a vicious cycle of thrombosis and resultant end-organ damage. This case raises critical questions about the timing and management of anticoagulation in patients with fibroelastoma complicated by several comorbidities and emphasizes the importance of individualized treatment plans.In light of her declining condition and limited treatment options, transitioning to hospice care became a necessary consideration. This shift underscores the importance of a patient-centered approach in managing advanced malignancies and associated complications, focusing on quality of life over aggressive interventions when the prognosis is poor.CONCLUSIONSThis case underscores the intricate relationship between malignancies, benign cardiac tumors, and hypercoagulable states, emphasizing the need for careful monitoring and management of anticoagulation in such patients. The fibroblastoma’s contribution to thromboembolic events, especially in the context of this patient’s malignancy and thrombocytopenia, illustrates the challenges faced in clinical decision-making. As highlighted by Kaplan et al. (2020), timely recognition and intervention for symptomatic fibroelastomas are crucial to prevent serious complications. This case serves as a reminder of the importance of individualized care, balancing the risks of anticoagulation against the potential for life-threatening thrombotic events. Future studies may benefit from investigating the mechanisms linking fibroelastomas and malignancies to guide more effective management strategies and improve patient outcomes in similar cases.Authors’ Contributions:Thumma, Milanya M: Literature review and writing the case. Abu Alya, Walaa: reviewed the case and corresponding author.INFORMED CONSENTWritten informed consent was obtained from patient to publish this report in accordance with the journal’s patient consent policyACKNOWLEDGEMENTSWe would like to express our heartfelt gratitude to the patient and her husband for their willingness to share the medical details of her case in the hope of helping others. We also extend our thanks to the medical team, who provided exceptional care and support throughout her management. May the patient’s soul rest in peace.Key Clinical Message:This case highlights the complex interactions between aortic valve fibroelastoma, malignancy, and hypercoagulability, emphasizing the critical need for individualized management of anticoagulation in patients with such conditions. Fibroelastomas, although benign, can contribute to significant thromboembolic events, especially in patients with underlying malignancies and conditions like thrombocytopenia. Careful monitoring and timely intervention are essential to mitigate the risk of serious complications, such as disseminated intravascular coagulation and organ infarction.REFERENCESGopaldas RR, Atluri PV, Blaustein AS, Bakaeen FG, Huh J, Chu D. Papillary fibroelastoma of the aortic valve: operative approaches upon incidental discovery. Tex Heart Inst J. 2009;36(2):160-3. PMID: 19436815; PMCID: PMC2676606.Kaplan JG, Kanwal A, Bahoora J, Berquist J, Hunyadi V, Keirn R. Papillary fibroelastoma presenting with multi-organ symptoms. J Community Hosp Intern Med Perspect. 2020 Oct 29;10(6):597-599. doi: 10.1080/20009666.2020.1811067. PMID: 33194138; PMCID: PMC7598949.

This study aims to conduct a comprehensive bibliometric analysis of rheumatoid arthritis (RA) and osteoarthritis (OA) research, identifying key trends in scientific output, geographic distribution, and biomarker research to improve early diagnosis and treatment strategies.A bibliometric analysis of 3,295 documents was performed using data from SCOPUS and Web of Science. Key metrics analyzed include annual scientific production, citation counts, Lotka’s Law for author productivity, and country-wise contributions. Biomarkers for early RA detection were also examined to assess their role in advancing personalized treatment.The USA, China, and the UK were identified as leading contributors to RA and OA research, while India ranked 12th globally. Biomarker research emerged as critical for early disease detection, emphasizing its growing relevance in personalized treatment strategies. Collaborative networks and global research productivity were also mapped, highlighting key trends and research gaps. This bibliometric analysis reveals global research trends in arthritis, underscoring the significance of biomarkers in early diagnosis and personalized care. The study provides valuable insights into the evolving landscape of RA and OA research, helping guide future research priorities and collaborative efforts.

The COVID-19 pandemic has significantly altered consumer behaviour, particularly in grocery shopping, leading to a rise in online grocery purchases. This shift has implications for food safety, especially concerning perishable items like raw chicken. Temperature fluctuations during delivery can increase microbial loads, particularly S. Typhimurium, a major cause of salmonellosis outbreaks. This study aims to understand the distribution of plasmid profiles and antibiotic resistance patterns in S. Typhimurium isolated from raw chicken purchased from three online stores in Malaysia. Seventy-two (n=72) strains of S. Typhimurium were collected from raw chicken meat sourced from Brand A (Kedah) with 38 isolates, Brand B (Selangor) with 19 isolates, and Brand C (Negeri Sembilan) with 15 isolates between January and March 2023. The strains were tested against 12 antibiotics using the disk diffusion method. Results showed that all strains were resistant to three or more antibiotics, with 63% (45/72) exhibiting resistance to at least six antibiotics. Most isolates were resistant to vancomycin (100%), tetracycline (91%), penicillin (94%), erythromycin (88%), and ampicillin (83%), while susceptibility was noted for cephalothin (27%), nalidixic acid (28%), and gentamicin (30%). The multiple antibiotic resistance (MAR) index ranged from 0.25 to 0.92, with 50 (A1-A50) different antibiogram profiles identified and 23 (P1-P23) plasmid profiles observed. Notably, two out of three resistant S. Typhimurium isolates transferred plasmids carrying antimicrobial resistance traits to the recipient E. coli DH5α. This study concludes that raw chicken meat from online retailers in Malaysia may serve as a reservoir for multiple antibiotic resistance-conferring plasmids.

The impact of cyberbullying on mental health is a significant concern among adolescents, yet there is limited research on the neurophysiological markers of cyberbullying. This study aims to address this by exploring whether resting state electroencephalography (EEG) power, among traditional frequency bands (delta, theta, alpha, beta), predicts cyberbullying experiences over time. Participants (N=167 with n=904 datapoints; aged 12.0-17.9 years) completed EEG and other assessments at 4 monthly-intervals for five years. Results revealed several associations between EEG power across brain regions and various cyberbullying roles. Key findings include a decrease in EEG power across all frequency bands over time across the entire sample, aligning with typical developmental patterns. However, in early adolescence, cyberbully-victims exhibited lower delta power compared to other groups, which may suggest heightened emotional reactivity. Conversely, later in adolescence there were decreases in delta power among cyberbullies, potentially reflective an adaptive stress response. Longitudinally, cyberbully-victims retained more alpha power over time (i.e. into later adolescence) in frontal and central regions, suggesting greater cognitive effort in processing emotional experiences. Conversely, cyberbullies showed a relative steeper decline in alpha power (into later adolescence) in frontal regions, possibly linked to impulsivity and higher levels of general aggression. Longitudinal analyses highlight the importance of early interventions to target cognitive and emotional processes that may be implicated in cyberbullying in order to reduce the impact of cyberbullying and protect the mental health of adolescents. Future research should involve larger, more diverse samples to improve our knowledge of complex relationships in this research area.

Land-use changes and climatic changes are two entwined stressors on ecosystems and studies on such interactions often focus on species-level or region-specific responses. Here we examine the influence of land-use and climate gradients on the abundance of functional groups and trait syndromes (based on diet breadth, habitat breadth, and dispersal mode) in arthropod communities within European agroecosystems. Using a previously compiled data set along with additional climatic data, we found that both climate and land-use gradients significantly influenced the abundance of pollinator and pest functional groups; examining trait syndromes with functional groups, only diet and habitat specialists were influenced by interactive effects of climate and land-use, but not generalists. Increasing semi-natural habitat in landscapes appeared to mitigate some of the negative effects of increasing temperature and precipitation on certain arthropods. We conclude that functional approaches examining impacts of qualitatively different stressors can help inform future conservation actions or mitigation efforts.

This paper presents a robust control framework for quadrupedal pronking by integrating template-based control with model predictive control (MPC) to achieve stable and adaptable locomotion. We begin by formulating a template model that encapsulates the core dynamics of pronking, generating reference motions to guide the robot’s gait. A novel linear time varying MPC strategy is designed to track these references and compute control inputs, while a nonlinear model predictive controller (NMPC) handles foot placement planning based on the template’s dynamic equations. Our approach is implemented and validated through MuJoCo simulations, where we evaluate its performance against existing methods. Stability and robustness are rigorously assessed through analysis of convergence across varied initial conditions and disturbance rejection tests. The results demonstrate that this method effectively produces stable, robust pronking motions, illustrating the potential of combining template-based and predictive control strategies for advanced quadrupedal locomotion.

Epithelial ovarian cancer (EOC) is a deadly malignant tumor that impacts the female reproductive system, ranking third in incidence after cervical and endometrial cancers and first in mortality rate among these three major tumors. The conventional treatments include chemotherapy, radiotherapy, and surgery, but their effectiveness is very limited and their side effects are serious. This situation calls for alternative therapeutic strategies, such as drug combinations, to enhance treatment efficacy and at the same time reduce adverse consequences. Previous research has demonstrated the inhibitory effects of enterolactone (ENL) on EOC by mechanisms such as inhibiting malignant angiogenesis. Gemcitabine (Gem) is a chemotherapeutic agent commonly used for the treatment of EOC. In this study, we aimed to explore the combined inhibitory effects of ENL and Gem on EOC. We examined the combined inhibitory effects of ENL and Gem on EOC proliferation, migration, and invasion, as well as the in vitro and in vivo modulation of the related proteins AKT/Bax/MMP-9/VEGFR2. We used tube formation and zebrafish neovascularization assays to assess the anti-angiogenic activity and established mouse cancer models to assess the hypothesized synergistic inhibitory effects on EOC between the drugs. ENL and Gem demonstrated significant synergistic inhibitory effects on cancer cell proliferation, migration, angiogenesis and AKT/Bax/MMP-9/VEGFR2 modulation. In animal experiments, the combined use of ENL and Gem also synergistically inhibited tumor growth and in the meantime markedly reduced the side effects of Gem. ENL ameliorated gut dysbacteriosis of ovarian cancer animals, which significantly enhanced the synergistic anti-cancer effect of ENL and Gem.

In our research, we focus on the existence, non-existence, and multiplicity of positive solutions to a Quasilinear Schrödinger equation in the form: −∆𝑢 + 𝜆𝑢 + 𝑘 2 [∆(𝑢 2)]𝑢 = 𝑓(𝑢), 𝑢 ∈ 𝐻 1 (ℝ 𝑵) With prescribed mass: ∫ ℝ 𝑁 |𝑢| 2 𝑑𝑥 = 𝑐, Here 𝑁 ≥ 3, The dual approach is used to transform this equation into a corresponding semilinear form. Then, we implement a global branch approach, adeptly handling nonlinearities 𝑓(𝑠) that fall into mass subcritical, critical, or supercritical categories. Key aspects of this study include examining the positive solutions' asymptotic behaviors as 𝜆 → 0 + 𝑜𝑟 𝜆 → +∞ and identifying a continuum of unbounded solutions in (0, +∞) × 𝐻 1 (ℝ 𝑵).

Plants exude a wide variety of compounds into the rhizosphere, modulating soil functioning and diversity. The number of studies investigating exudation has exponentially increased over the past decades. Yet, the high inter-study variability of the results is slowing down our understanding of the root-soil interactions. Such variability is partly due to the absence of harmonized methodologies to collect and characterize exudation. Here, we discuss how various experimental aspects influence exudation profiles by performing a literature review, and we suggest best practices for different experimental setups. We discuss state-of-the art of spatially resolved exudate collection, collection in controlled vs field conditions, and plant growth setups ranging from hydroponics to soil. We highlight the importance of preparing experimental blanks, in situ vs ex situ exudate collection, various collection media and timing of collection, exudate storage and processing, and analytical considerations. We summarize best practices for experimental setup and reporting of parameters in an easily accessible table format to facilitate discussion of best practices in the field. An increased standardization in the field together with the systematic studies suggested will improve our knowledge on how plant exudation shapes interactions with organisms in soil.

Herbivory plays a significant role in shaping plant-insect interactions. In this study, we investigated the relationship between leaf color and insect herbivory in the cannonball trees Lecythis pisonis. We focused on the temporal patterns of herbivory and leaf defense, taking into account the changes in leaf color throughout the season. Our findings revealed that young pink leaves exhibited smaller leaf area and greater specific leaf area (SLA) compared to green leaves. This higher SLA indicates that young pink leaves may be more susceptible to herbivory due to lower physical defense. However, despite these differences, there was no significant effect of leaf color on herbivory levels in the month of bud burst. This finding suggests that during the early stages of ontogeny, L. pysonis leaves do not suffer significant herbivory, which may indicate that their coloration acts as a deterrent to herbivore attack. Throughout the rainy season, no significant differences were found in herbivory, with an average of 4.5% of leaf area removed and 9.3% frequency of leaves attacked. While our results indicate a lack of significant differences in herbivory between pink and green leaves the increase in the number of attacked leaves following the change in leaf coloration suggests an increase in herbivore activity over the season. This study provides insights into the complex dynamics of herbivory and leaf coloration in cannonball trees and highlights the need for further research to elucidate the relationship between leaf pigments and levels of chemical and mechanical defense against herbivory.

The Internet of Things (IoT) represents a rapidly advancing technological framework enabling the global interconnection and interaction of millions of devices. With the growth of IoT networks, security has become a crucial concern due to the frequent exchange of sensitive data. Among IoT services, secure communication between devices is particularly vital. MQTT, or Message Queue Telemetry Transport, is a messaging protocol that operates on a publish/subscribe service model and is notably vulnerable to Denial of Service (DoS) attacks, which severely disrupt its normal functioning. DoS attacks are particularly challenging as they lead to network performance degradation and are difficult to detect. This paper introduces a lightweight fuzzy rule-based detection system, LFDNI-DA, designed to mitigate DoS attacks within MQTT-based IoT networks. The approach leverages a fuzzy inference engine (FIE) to identify various network intrusions and compromised devices, and it applies FIE in message-forwarding behavior analysis. LFDNI-DA utilizes aggregate logging from legitimate nodes to select trusted nodes for message forwarding. Key performance metrics such as false positive rate, true negative rate, intrusion detection accuracy, detection efficiency, and precision rate are evaluated using the Cooja network simulator. Simulation results reveal that the proposed LFDNI-DA system can detect and prevent DoS attacks with a 99.9% accuracy rate and achieves a 94% average precision in identifying and differentiating among various DoS attack types. The F1-score, recall, and precision rates for LFDNI-DA stand at 97.62%, 93.28%, and 98.29%, respectively, highlighting its effectiveness in enhancing IoT network security.

Title: Diagnostic Dilemma of Culture Negative Infective Endocarditis in the Setting of Intermittent Complete Heart BlockAuthors: Gabriel Velez Oquendo, MD1; Nivedha Balaji, DO1; Sheriff N. Dodoo, MD2; Shalabh Chandra, MD3

INTRODUCTIONEagles syndrome or stylohyoid syndrome refers to set of symptoms arising due to elongation of styloid process, which further leads to compression of nearby neurovascular structures, resulting into symptoms like pharyngeal and neck pain,sensation of foreign body in throat ,pain while moving head, dysphagia etc. It often ressembles to symptomatology of head and neck pathologies, as a consequence of which ES most of time gets misdiagnosed by the clinicians. Along with thorough clinical examination ,radiographic analysis is best way to confirm the diagnosis .Treatment plan can be further tailored according to severity of symptoms of patient, which can be either conservative or surgical . Surgically stylohoid complex can be approached either intraorally or extraorally.We present Retromandibular approach as a surgical management of eagle’s syndrome.

Runs of homozygosity (ROH) are increasingly being analyzed using whole genome sequences in non-model species as a measure of inbreeding and to assess demographic history, thus providing useful information for conservation. However, most studies have used Plink for ROH inference which has been shown to perform poorly when sequencing depth is below 10X, often underestimating the true proportion of the genome in ROH, which could lead to erroneous status assessment and management decisions. We use whole genome sequences from caribou, a non-model species at risk, subsampled to sequencing depths ranging from 1X to 15X, to assess the performance of ROHan, a program developed to enable ROH estimation using lower coverage sequences but so far only optimized for human data. We use 22 individuals with varying extent of inbreeding to assess the effects of sequencing depth, input parameters, and demographic history on the inference of ROH. We found that accurate estimation of the percentage of the genome and lengths of ROH can be achieved down to depths as low as 3-5X. However, input parameters and the demographic history of the individual can have a dramatic effect on results. Using our optimized settings, we then re-analyze low coverage sequences from a small and isolated caribou population and demonstrate high levels of inbreeding which had previously been missed. We provide recommendations for thorough optimization of parameters including the need for multiple runs as well as careful interpretation of outputs to enable robust ROH inference using low coverage whole genome sequences in wildlife species.

Aim: This study aims to explore the clinical significance of measuring the oropharyngeal cavity area (S) in children with tonsillar hypertrophy using CBCT-based 3D reconstruction imaging. Methods: A retrospective analysis was conducted on 174 children aged 4-6 years with adenoid hypertrophy and tonsillar hypertrophy. The children were divided into two groups: the surgery group (87 cases, who underwent tonsillectomy) and the non-surgery group (87 cases, who did not undergo tonsillectomy). All children underwent nasopharyngeal CBCT scans for upper airway 3D reconstruction, and the oropharyngeal area was measured on the CT images for both groups. Logistic regression analysis was employed to investigate the factors significantly affecting the oropharyngeal area, and the performance of the logistic regression model in distinguishing between the surgical and non-surgical groups was evaluated using ROC curves. Results: Logistic regression analysis revealed a statistically significant difference in oropharyngeal area between the surgery and non-surgery groups (p < 0.05). ROC curve analysis showed that the logistic regression model demonstrated a high diagnostic efficacy in distinguishing between the two groups, with an area under the curve (AUC) of 0.78. A threshold value of S = 141.07 mm 2 was found to provide a good balance between sensitivity and specificity in the ROC curve. Conclusion: Oropharyngeal area can serve as an important imaging indicator for diagnosing and assessing the severity of tonsillar hypertrophy in children aged 4-6 years. This result can offer valuable clinical guidance for comprehensive surgical decision-making. Keywords: Tonsillar hypertrophy; Adenoid hypertrophy; Pediatric snoring; CBCT; Upper airway; 3D reconstruction

AbstractGlobally, the increasing frequency of heatwaves and droughts are impacting tropical forests, which are vital for maintaining biodiversity, carbon sequestration and climate regulation. But vulnerability to warming may vary between and within species due to phenotypic divergence. Leaf functional trait variation is known to affect leaf operating temperatures – a phenomenon termed ‘limited homeothermy’ when it helps avoid lethal temperatures in warmer conditions. Yet, evidence of this purported thermoregulatory ability and the relative roles of acclimation or adaptation remain limited. Here we measured photosynthetic heat tolerance and leaf thermal traits of three, co-occurring tropical rainforest trees across a wide thermal gradient in the Australian Wet Tropics. We used observed leaf traits to predict leaf-to-air temperature differences (∆Ttrait) and combined this with genotypic and environmental data from field collections and glasshouse experiments to assess evidence for intraspecific adaptive selection across the landscape. Intraspecific trait variation led to enhanced leaf cooling (lower or more negative ∆Ttrait) and partial maintenance of modelled thermal safety margins in warmer sites for Darlingia darlingiana and Elaeocarpus grandis, but not Cardwellia sublimis. Genomic signals of selection were detected in all three species, with adaptive genomic variation associated with climate for D. darlingiana and E. grandis, but edaphic factors for C. sublimis. Additionally, E. grandis seedlings from different provenances grown under contrasting temperature and humidity regimes showed clines in ∆Ttrait variation related to mean annual temperature of origin but not treatment environment, despite individual traits acclimating to treatments. Our work implicates local adaptation to climate as a driver of intraspecific variation in leaf thermoregulatory traits, supporting limited homeothermy in these key tropical rainforest tree species. Our results highlight how leaf energy balance modelling can be combined with ecological genomics to better understand the strategies plants use to cope with rising temperatures.

In this paper, we consider the H e ̵́ non equation { − ∆ u = | x | α u 2 ∗ − 1 + ϵ , u > 0 , in Ω , u = 0 , on ∂ Ω . where Ω is a bounded smooth domain in R N containing the origin, N≥3 and ϵ is a positive constant. M. Ben Ayed et.[2] proved the equation without | x | α doesn’t have the single peaked solution. Moreover, there are few works on the H e ̵́ non equation in a general domain. Inspired by them, we proved the non-existence of the single peak solution to the H e ̵́ non problem by Pohozaev identities.

The equations of electrodynamics must, first of all, satisfy the law of conservation of energy. It is shown that Maxwell's equations can be obtained from the Cauchy-Riemann conditions for a quaternion in 4D space. Electrons are written as 4D vectors in energy space, in which the first elements represent the real part of the quaternion (scalar), and the other three represent the imaginary part. From the point of view of conservation of energy, an electron cannot move into an arbitrary state, but only makes quantum jumps to those places in space in which it stores energy. Consequently, the movement of electrons in time occurs along an orbit. Since scalars are formed by the interaction of electromagnetic waves, 4D electrons have a spectrum. The mathematically obtained equations of quaternion electrodynamics have the same form for electric and magnetic intensity, but differ from Maxwell's equations by the presence of a scalar part. A charged electron is considered as the scalar part in the equation of circulation of the electric field strength. The electron spin is considered as the scalar part in the equation of magnetic intensity circulation. The equations of the scalar parts correspond to Gauss's law and form a single connection with the equations of the imaginary parts. Also, unlike Maxwell's equations, instead of currents induced by circulations of intensities, the electromotive forces that form these currents are shown. As is known, in the equation for the circulation of magnetic intensity, Maxwell added a current formed by the change in electric flux over time. In the obtained expressions, this term appeared mathematically and represents the electromotive force generated by the change in the magnetic field over time.

The increasing number of ransomware attacks requires the development of advanced detection mechanisms capable of addressing the dynamic and complex nature of such threats. The Adaptive Cascaded Deep Learning (ACDL) framework introduces a novel, multi-layered approach to ransomware detection, integrating pattern-based preemptive analysis, cognitive decomposition of execution chains, real-time anomaly tracking with reinforcement learning, and autonomous network traffic profiling. Each layer contributes uniquely to the overall efficacy: the initial pattern-based preemptive analysis identifies malicious intent prior to execution, thereby preventing potential harm; the cognitive decomposition of execution chains allows for the detection of anomalies in system calls, file manipulations, and registry modifications, facilitating targeted intervention; the realtime anomaly tracking, utilizing reinforcement learning, enhances responsiveness to emerging threats through dynamic adjustment of detection parameters; and the autonomous profiling of outgoing network traffic identifies covert data transfers indicative of ransomware activity, providing an additional security layer. Collectively, these innovations result in a comprehensive detection mechanism capable of addressing the complexities of modern ransomware threats. Experimental evaluations demonstrate the framework's superior detection accuracy and adaptability compared to traditional methods, showing its potential to significantly enhance cybersecurity measures against ransomware attacks.

not-yet-known not-yet-known not-yet-known unknown Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder that leads to motor neuron degeneration, muscle weakness, and respiratory failure. Despite ongoing research, effective treatments for ALS are limited. This study aimed to apply network biology and machine learning (ML) techniques to identify novel repurposed drug candidates for ALS. In this study, we conducted a meta-analysis using 4 transcriptome data in ALS patients (including motor neuron and muscle tissue) and healthy controls. Through this analysis, we uncovered common shared differentially expressed genes (DEGs) separately for motor neurons and muscle tissue. Using common DEGs as proxies, we identified two distinct clusters of highly clustered differentially co-expressed genes: the ’Muscle Tissue Cluster’ for muscle tissue and the ’Motor Neuron Cluster’ for motor neurons. We then evaluated the performance of the nodes of these two modules to distinguish between diseased and healthy states with ML algorithms: KNN, SVM, and Random Forest. Furthermore, we performed drug repurposing analysis and text mining analyses, employing the nodes of these clusters as drug targets to identify novel drug candidates for ALS. The potential impact of these drug candidates on the expression of cluster genes was predicted using linear regression, SVR, Random Forest, Gradient Boosting, and neural network algorithms. As a result, we identified five novel drug candidates for the treatment of ALS: Nilotinib, Trovafloxacin, Apratoxin A, Carboplatin, and Clinafloxacin. Clinafloxacin. These findings highlight the potential of drug repurposing in ALS treatment and suggest that further validation through experimental studies could lead to new therapeutic avenues.

Insider threats represent a significant security challenge within organizations due to their often stealthy nature and the inherent trust placed in internal personnel. To address this complex issue, this study explores the efficacy of advanced graph-based neural network models in identifying potential insider threats from organizational data. Using the CMU CERT 4.2 dataset, we first constructed a comprehensive knowledge graph from existing datasets to model the intricate relationships and interactions among employees. Subsequently, we employ three distinct graph convolutional network (GCN) architectures: a standard GCN, a Spatio-Temporal GCN (STGCN), and a Capsule GNN (Graph Neural Network). Our experiments are methodically conducted across varying sizes of dataset, focusing on detection accuracy as a primary metric. The performance of each model is rigorously compared, with the STGCN consistently demonstrating superior accuracy of roughly 94% while maintaining lower false positive rates across all datasets tested. The findings indicate that incorporating both spatial and temporal data dimensions via STGCN significantly enhances the ability to detect and predict insider threats more effectively than traditional GCN and Capsule GNN architectures. This research underscores the potential of spatio-temporal graph analytics as a promising approach in the proactive management of internal security risks.

Objective: To evaluate the predictive value of maternal neutrophil-to-lymphocyte ratio (NLR) for spontaneous delivery within 24 hours in women with preterm premature rupture of membranes (PPROM). Study Design and setting: Retrospective cohort study in a single, university-affiliated tertiary medical center. Population: Women with PPROM at <33+6 weeks’ gestation planning vaginal delivery. Exclusions included cases of labor induction or cesarean delivery. Main outcome measure: Women who delivered spontaneously within 24 hours from rupture of membrane Methods: Maternal demographic and clinical data, including age, gestational age, body mass index, parity, and mode of conception, were collected. Women who delivered spontaneously within 24 hours of membrane rupture were compared to those who did not via univariate and multivariate Cox analyses.   Results:  Among 145,833 deliveries during the study period, 1,442 women (0.9%) presented with PPROM. After exclusions, 249 women were included, with 115 (46.2%) delivering spontaneously within 24 hours. Cox regression analysis identified NLR >10 (HR = 2.86, 95% CI 1.42–5.7, p = 0.003) and multiple gestation (HR = 5.87, 95% CI 2.57–13.45, p < 0.001) as independent risk factors for spontaneous delivery within 24 hours. Conclusion: An elevated maternal NLR is a promising predictor of spontaneous delivery within 24 hours in PPROM cases. These findings support the potential of NLR as a practical clinical tool for anticipating imminent preterm delivery, aiding in management decisions for this population. Funding: None.

Atmospheric Pressure Solids Analysis Probe (ASAP) Mass Spectrometry was used for the rapid analysis of 250 synthetic opioid standards, including 210 fentanyl analogs of similar molecular weight and structure, 32 non-fentanyl related opioids, and 8 fentanyl precursors. Using four cone voltages (5, 15, 35 and 50 V) both precursor and product ion mass information was obtained for all standards. The accumulated spectral data was used to build a spectral library, which was utilized to create and validate a statistical model via LiveID software. To assess the accuracy of the database, 5 blind and 4 dirty cook fentanyl samples were analyzed. Using LiveID, obtained data for each sample was processed and matched against all compounds in the spectral library to produce matching scores that ranged from 0- 999. For all samples, the correct identity of each fentanyl analog was ranked within a score of 800 -997. Thus, proving that ASAP, when used alongside a real-time sample recognition software, such as LiveID, can help conduct presumptive testing for fentanyl and fentanyl analogs in blind and dirty samples, making it a promising alternative to some of the most commonly used analytical screening techniques.

Background: Genital tuberculosis (TB) is a significant cause of infertility in high disease burden countries. Assisted Reproductive Therapy (ART) success in this population remains unclear. Objectives: To conduct a systematic review and meta-analysis to assess ART outcomes in women with a history of TB. Search Strategy: Studies were identified through PubMed, Embase, Global Health and Cinhal. Selection Criteria: Studies reporting ART outcomes in women with a history of TB, compared to women without TB, were included. Studies without a non-TB comparison group were excluded. Data Collection and Analysis: Four authors independently screened articles. Risk of bias was assessed with the Newcastle-Ottawa Score. Meta-analysis was performed with random-effects models to compute odds of clinical pregnancy, miscarriage, live birth and mean differences in oocytes retrieved. Main Results: Of 1184 records identified, 12 studies were included. Ten studies underwent meta-analysis, comprising 3,532 TB patients and 9,163 non-TB patients. Women with TB had significantly lower odds of clinical pregnancy (odds ratio [OR] 0.82, 95% CI [0.67, 1.01], p=0.06) and live births (OR 0.74, 95% CI [0.61, 0.90], p=<0.001). The odds of miscarriage (OR 1.37, 95% CI [0.91, 2.05], p=0.13) was higher in TB patients with a trend towards significance. Mean number of oocytes retrieved (mean difference -0.20, 95% confidence interval CI [-1.32, 0.92], p=0.73) was not different between the groups. Conclusions: ART outcomes are poorer in women with a history of TB. Variability in study quality and bias suggests the need for multi-centre studies with standardized reporting of ART outcomes and TB treatment.