Rapid Progression Research Articles

C-Myc inhibition and p21 modulation contribute to unsymmetrical bisacridines-induced apoptosis and senescence in pancreatic cancer cells.

Pancreatic cancer (PC) is one of the most aggressive cancers and is the seventh leading cause of cancer-related death worldwide. PC is characterized by rapid progression and resistance to conventional treatments. Mutations in KRAS, CDKN2A, TP53, SMAD4/DPC4, and MYC are major genetic alterations associated with poor treatment outcomes in patients with PC. Therefore, optimizing PC therapy is a tremendous challenge. Unsymmetrical bisacridines (UAs), synthesized by our group, are new promising compounds that have exhibited high cytotoxicity and antitumor activity against several solid tumors, including pancreatic cancer. The cellular effects induced by UAs in PC cells were evaluated by MTT assay (cell growth inhibition), flow cytometry, and fluorescence and light microscopy (cell cycle distribution, apoptosis, and senescence detection). Analysis of the effects of UAs on the levels of proteins (c-Myc, p53, SMAD4, p21, and p16) was performed by Western blotting. Apoptosis was the main triggered mechanism of death after UAs treatment, and induction of the SMAD4 protein can facilitate this process. c-Myc, which is one of the molecular targets of UAs, can participate in the induction of cell death in a p53-independent manner. Moreover, UAs can also induce accelerated senescence through the upregulation of p21. Notably, senescent cells can die via apoptosis after prolonged exposure to UAs. UAs have emerged as potent anticancer agents that induce apoptosis by inhibiting c-Myc protein and triggering cellular senescence in a dose-dependent manner by increasing p21 levels. Thus, UAs exhibit desirable features as promising candidates for future pancreatic anticancer therapies.

Toward an animal model of Progressive Supranuclear Palsy.

Progressive Supranuclear Palsy (PSP) is a rare and fatal neurodegenerative tauopathy which, with a rapid clinical progression coupled to a strong degree of clinico-pathologic correlation, has been suggested to be a "frontrunner" in translational development for neurodegenerative proteinopathies. Elegant studies in animals have contributed greatly to our understanding of disease pathogenesis in PSP. However, presently no animal model replicates the key anatomical and cytopathologic hallmarks, the spatiotemporal spread of pathology, progressive neurodegeneration, or locomotor and cognitive symptoms that characterize PSP. Current models therefore likely fail to recapitulate the key mechanisms that underly the pathological progression of PSP, impeding their translational value. Here we review what we have learned about PSP from work in animals to date, examine the gaps in modeling the disease and discuss strategies for the development of refined animal models that will improve our understanding of disease pathogenesis and provide a critical platform for the testing of novel therapeutics for this devastating disease.

Myopic shift in female mice after ovariectomy

Myopia is a global public health concern, with a higher prevalence in women than that in male. As the relationship between sex hormone and myopia remains unclear, we aimed to reveal the relationship between sex hormone and myopia by removing the ovaries of mice and measuring changes in ocular parameters related to myopia. Lens-induced myopia (LIM) surgeries were performed on 3-week-old male mice and age-matched female mice to evaluate the effects of sex on myopia development, which indicated a high degree of myopia and rapid progression of axial elongation in male mice. Bilateral ovariectomy (OVX) performed on 4-week-old female mice induced myopic refraction status in ovariectomized mice. Although axial length elongation was larger in ovariectomized mice than that in sham control mice, the result was insignificant. To further reveal the relationship between female sex hormones and myopia, LIM combined with OVX was performed, which revealed a magnified myopic refraction status in ovariectomized mice. Nevertheless, elongation of the anterior chamber depth in the − 30 D lens-treated eyes significantly increased in LIM + OVX mice compared with the frame-treated eyes in LIM + OVX mice and − 30 D lens-treated eyes in LIM + Sham surgery mice. Sex hormones play a role in regulating myopia development in female mice.

Impact of Digital Marketing, Influencer, Live Features, and Reviews Shopee Purchase With Brand Image

The advancement of information and communication technology in the digital era has revolutionized various aspects of human life, including in the realm of business and marketing. Marketing activities that once relied on direct interaction between sellers and buyers have now shifted towards digital marketing that utilizes online platforms. Indonesia, as the largest economy in Southeast Asia, has made an e-commerce as the main driver of socioeconomic growth. Supported by a population of over 270 million people and ever-increasing internet penetration, the development of e-commerce in Indonesia has experienced rapid progress in recent years. This study aims to analyze the impact of digital marketing, influencer marketing, live features, and Online Customer Reviews on online purchase decisions on the Shopee platform with brand Image as an intervening variable. This research used a quantitative method with a data collection technique through an online questionnaire to 210 Shopee users in Indonesia. The measurement of construct validity and reliability was carried out using the measurement model (outer model). Then, the structural model (inner model) was used to test the model's strength, predictive ability, model significance, and the direct and indirect influence of independent variables on the dependent variable. The test tool employed SmartPLS 3.0. The results of this study indicate that the variables of Digital Marketing, Live Features, and Brand Image have a significant influence on Purchase Decisions on Shopee e-commerce. Furthermore, the variables of influencer marketing, live features, and Online Customer Review have a significant influence on Brand Image on Shopee e-commerce. Meanwhile, for the indirect influence, the variable live features have a significant influence on purchase decisions on Shopee e-commerce through Brand Image as an intervening variable.

B-103 Correlation of Novel Markers, Anti-Sa (Citrullinated Vimentin) and Anti-CarP (Carbamylated Protein), with High Vectra® DA Disease Activity Scores in Rheumatoid Arthritis (RA)

Abstract Background Citrullination and carbamylation are post-translational modifications where autoantibodies against citrullinated and carbamylated proteins in RA have been associated with more aggressive disease. At the same time, Vectra® DA is blood test that yields a RA disease activity score from 1 to 100. Here, 120 patient samples were analyzed to assess the relationship of disease activity as measured by Vectra® score and the presence of Anti-Sa (Citrullinated Vimentin) and Anti-CarP (Carbamylated Protein). Methods Serum samples were analyzed for Vectra® DA (which is validated for adults with RA) where 12 biomarker measurements (VCAM-1, EGF, VEGF-A, IL-6, TNF-RI, MMP-1, YKL-40, Leptin, Resistin, SAA, CRP) together with patient age, gender and adiposity are used to generate a score where established categories are low for 1 to 29, moderate for 30 to 44, and high for 45 to 100. Anti-Sa and Anti-CarP were by ELISA lab-developed tests (LDT) with a cut-off for positive of >20 Units (U). Results Anti-Sa and Anti-CarP for 40 samples from each Vectra® DA category are reported. Patients with the highest Vectra® scores (mean 58.2, range 46.8 - 87.5) had highest rates of positivity for Anti-Sa (52.5%) and Anti-CarP (35%). In contrast, the group with the lowest Vectra® scores (mean 11.8, range 3.8 - 18.1) were infrequently positive for Anti-Sa (17.5%) and Anti-CarP (0%). Frequencies with moderate Vectra® scores (mean 37.1, range 32.4 - 41.8) were mid-range: Anti-Sa (25%) and 7.5% for Anti-CarP (7.5%). Of note, positivity of Anti-Sa was analytically stronger, i.e. higher titer, in patients with moderate or high Vectra® (mean 90.0U or 81.7U), compared to values seen in those with low Vectra® (mean 60.4 U). Conclusions Our analysis of 120 patient samples demonstrates that high disease activity as determined by Vectra® DA corresponds to higher positivity of novel autoantibody markers, Anti-Sa and Anti-CarP. High Vectra® DA scores (>44) are associated with a 20% 1-year risk of radiographic progression while low scores (<30) carry only a 1% risk. Here, we found that patients with high Vectra® scores were 3 times more likely to test positive for Anti-Sa than those with low disease activity scores. At the same time, Anti-CarP occurred in high frequency (35%) with high Vectra® in contrast to zero positivity observed with low Vectra® scores. Thus, our findings support Anti-CarP’s reported association with more active disease with higher risk of developing joint erosions. Also of note, patients with high Vectra® scores had particularly high Anti-Sa positivity - both a 52.5% positivity rate as well as higher Anti-Sa levels (titers) than the group with lower Vectra® scores. These data corroborate other studies where Anti-Sa not only predicted more aggressive, rapid disease progression, but its titers correlated with clinical measures of disease activity. Taken together, our data support the consistency and clinical usefulness of the Vectra® score along with novel autoantibody markers, Anti- Anti-Sa and Anti-CarP, in order to assess RA severity, prognosis, and patient-specific treatment strategies.

Applications of artificial intelligence in interventional oncology: An up-to-date review of the literature.

Interventional oncology provides image-guided therapies, including transarterial tumor embolization and percutaneous tumor ablation, for malignant tumors in a minimally invasive manner. As in other medical fields, the application of artificial intelligence (AI) in interventional oncology has garnered significant attention. This narrative review describes the current state of AI applications in interventional oncology based on recent literature. A literature search revealed a rapid increase in the number of studies relevant to this topic recently. Investigators have attempted to use AI for various tasks, including automatic segmentation of organs, tumors, and treatment areas; treatment simulation; improvement of intraprocedural image quality; prediction of treatment outcomes; and detection of post-treatment recurrence. Among these, the AI-based prediction of treatment outcomes has been the most studied. Various deep and conventional machine learning algorithms have been proposed for these tasks. Radiomics has often been incorporated into prediction and detection models. Current literature suggests that AI is potentially useful in various aspects of interventional oncology, from treatment planning to post-treatment follow-up. However, most AI-based methods discussed in this review are still at the research stage, and few have been implemented in clinical practice. To achieve widespread adoption of AI technologies in interventional oncology procedures, further research on their reliability and clinical utility is necessary. Nevertheless, considering the rapid research progress in this field, various AI technologies will be integrated into interventional oncology practices in the near future.

A Controllability Reinforcement Learning Method for Pancreatic Cancer Biomarker Identification.

Pancreatic cancer is one of the most malignant cancers with rapid progression and poor prognosis. The use of transcriptional data can be effective in finding new biomarkers for pancreatic cancer. Many network-based methods used to identify cancer biomarkers are proposed, among which the combination of network controllability appears. However, most of the existing methods do not study RNA, rely on priori and mutations information, or can only achieve classification tasks. In this study, we propose a method combined Relational Graph Convolutional Network and Deep Q-Network called RDDriver to identify pancreatic cancer biomarkers based on multi-layer heterogeneous transcriptional regulation network. Firstly, we construct a regulation network containing long non-coding RNA, microRNA, and messenger RNA. Secondly, Relational Graph Convolutional Network is used to learn the node representation. Finally, we use the idea of Deep Q-Network to build a model, which score and prioritize each RNA with the Popov-Belevitch-Hautus criterion. We train RDDriver on three small simulated networks, and calculate the average score after applying the model parameters to the regulation networks separately. To demonstrate the effectiveness of the method, we perform experiments for comparison between RDDriver and other eight methods based on the approximate benchmark of three types cancer drivers RNAs.

Biopolymer immune implants co-loaded with TMZ, R848 and IOX1 for perioperative therapy of glioblastoma

Glioblastoma (GBM), a prevalent and aggressive brain tumor, poses significant treatment challenges due to its rapid progression and the difficulty in achieving complete surgical resection. The current treatment regime, primarily surgery followed by radiotherapy and chemotherapy, offers limited success, with a five-year survival rate of less than 10 %. For addressing the challenges faced in the treatment of GBM, an approach using a biopolymer implant constructed with dynamic reversible covalent bonds, was designed to achieve controlled and constant-rate release of chemotherapy drug (Temozolomide, TMZ), immune adjuvant (Resiquimod, R848) and checkpoint inhibitor (5-carboxy-8-hydroxyquinoline, IOX1). The safety evaluation demonstrated the biocompatibility of the implants, with no significant inflammatory response or adverse effects on various systemic organs. In vivo antitumor study showed that the local delivery of drug combination via this implant significantly inhibited tumor recurrence of orthotopic GBM. Immune analysis revealed that the combination of the three drugs effectively activated systemic antitumor immune responses and induced memory effects. The synergistic mechanism of the drug combination was further validated by RNA whole sequencing. The innovative approach of combining chemotherapy and immunotherapy in biopolymer immune implants for GBM treatment showed promising and opens new avenues for treating GBM, particularly in addressing postoperative recurrence. Statement of significanceOur research introduces a pioneering approach in treating orthotopic brain glioblastoma (GBM), characterized by inevitable tumor recurrence, poor immune infiltration and the restrictive nature of the blood-brain barrier. To break the impasse of ineffective treatment for GBM, the innovative use of dynamically reversible covalent bonds in polymer matrix ensures the controlled, stable and sustained release of drug combinations of the chemotherapeutic agent temozolomide, immune adjuvants and checkpoint inhibitors, which maintains the optimal concentration in the tumor, overcoming problems associated with conventional chemotherapy such as systemic toxicity and low tumor targeting. Empirical evidence from in vivo experiments on the rat GBM model demonstrates significant outcomes: 90 % tumor size reduction and prolonged survival with over 70 % tumor cure rate.

The acceptance of social media as a channel of communication and livestock information for sheep farmers

Abstract The development of technology and information in the Industry 4.0 era, especially the internet, is experiencing very rapid progress. Searching for information through new media will increase human resource capacity and work efficiency. Using technology acceptance model (TAM) theory, this study aims to identify social media usage as a communication and information medium and analyze the influence between constructs in social media acceptance. A cross-sectional survey was used in this study design. A structured questionnaire from previous related studies was used as the instrument. One hundred and eleven sheep farmers from several villages in Sukabumi, West Java groups, participated in this survey. Stratified sampling was adopted to select and interview the respondents. The findings show that social media usage as a channel for communication and livestock information is quite adequate. Many farmers already use WhatsApp and YouTube. However, only a few farmers use Facebook and Instagram. The results of the TAM analysis (limited to only the WhatsApp application) indicate that perceived ease of use positively influences perceived usefulness (PU). A positive relationship is also shown between PU and behavioral intention to use. The theoretical implication is that this study proves how social media adopts in disseminating messages and seeking information. Regarding managerial implications, the findings suggest that stakeholders in the agricultural industry across the value chain could enhance their services by fostering a broader ecosystem of social media applications.

Intrusion Detection System Application with Machine Learning

Information security holds paramount importance for organizations and users alike, safeguarding against unauthorized access to sensitive data. Daily usage of the internet amplifies the importance of security measures and the detection of malicious activities. Cyber-attacks, as these malicious activities are commonly known, are continually evolving with advancements in hardware, software, and complex network algorithms. Intrusion Detection Systems play a crucial role in shielding data and information from cyberattacks. The rapid progression in machine learning and deep learning, two popular methodologies in data mining, has found applications in various fields, including security. This study focuses on the use of machine learning and deep learning methods to design an intelligent intrusion detection system. For the development of this smart intrusion detection system, two well-established datasets, NSL-KDD and Kyoto 2006+, were employed. Machine learning methods were implemented utilizing the classification algorithms available in the WEKA data mining tool. The results obtained from these classification algorithms were compared with the deep learning model designed within the scope of the study. Consequently, a detailed analysis of machine learning and deep learning methods on the NSL-KDD and Kyoto 2006+ datasets for an intelligent intrusion detection system was conducted, and suggestions were proposed for further research endeavors.

Opportunities and challenges for direct electrification of chemical processes with protonic ceramic membrane reactors

Abstract The necessity of developing sustainable energy storage and process electrification technologies has built an unprecedented momentum for protonic ceramic membrane reactors (PCMRs). PCMRs are practically electrolytic cells (or even fuel cells in case of cogeneration) that extend beyond the classical approach of electrolysis towards producing a variety of value-added chemicals or fuels. The use of a ceramic electrolyte membrane to electrochemically supply or remove hydrogen offers unique advantages, such as process intensification, cogeneration of chemicals and electricity, as well as the shift of the chemical equilibrium to the desired products. During the last few years, rapid progress has not only been made in the cell components, but also for upscaling, which reveals their high potential in terms of efficiency and flexibility. Herein, we discuss recent innovations and breakthroughs in the PCMR concepts and components for different processes, while we attempt to identify challenges that may hinder their wide deployment. Closer to commercialization is the production of pressurized hydrogen from sustainable sources, i.e. biogas and ammonia, while significant advancements have been made in reversible H2O electrolysis systems. CO2/H2O co-electrolysis, hydrocarbon conversion and ammonia synthesis have been also successfully demonstrated, albeit with different obstacles related to the product selectivity and stability of the cell reactors. We conclude that future projects should target beyond the experimental discovery of materials, such as, multiscale modeling that would aid optimization of the involved surfaces, interfaces, and the operating parameters towards enhancing the viability of electrosynthesis in PCMRs.

Text-image multimodal fusion model for enhanced fake news detection.

In the era of rapid internet expansion and technological progress, discerning real from fake news poses a growing challenge, exposing users to potential misinformation. The existing literature primarily focuses on analyzing individual features in fake news, overlooking multimodal feature fusion recognition. Compared to single-modal approaches, multimodal fusion allows for a more comprehensive and enriched capture of information from different data modalities (such as text and images), thereby improving the performance and effectiveness of the model. This study proposes a model using multimodal fusion to identify fake news, aiming to curb misinformation. The framework integrates textual and visual information, using early fusion, joint fusion and late fusion strategies to combine them. The proposed framework processes textual and visual information through data cleaning and feature extraction before classification. Fake news classification is accomplished through a model, achieving accuracy of 85% and 90% in the Gossipcop and Fakeddit datasets, with F1-scores of 90% and 88%, showcasing its performance. The study presents outcomes across different training periods, demonstrating the effectiveness of multimodal fusion in combining text and image recognition for combating fake news. This research contributes significantly to addressing the critical issue of misinformation, emphasizing a comprehensive approach for detection accuracy enhancement.

Frequent Cocaine Use is Associated With Larger HIV Latent Reservoir Size.

Cocaine-one of the most frequently abused illicit drugs among persons living with HIV [people living with HIV (PLWH)]-slows the decline of viral production after antiretroviral therapy and is associated with higher HIV viral load, more rapid HIV progression, and increased mortality. We examined the impact of cocaine use on the CD4+ T-cell HIV latent reservoir (HLR) in virally suppressed PLWH participating in a national, longitudinal cohort study of the natural and treated history of HIV in the United States. CD4+ T-cell genomic DNA from 434 women of diverse ancestry (ie, 75% Black, 14% Hispanic, 12% White) who self-reported cocaine use (ie, 160 cocaine users, 59 prior users, 215 non-users) was analyzed using the Intact Proviral HIV DNA Assay, measuring intact provirus per 106 CD4+ T cells. HIV latent reservoir size differed by cocaine use (ie, median [interquartile range]: 72 [14-193] for never users, 165 [63-387] for prior users, 184 [28-502] for current users), which was statistically significantly larger in both prior (P = 0.023) and current (P = 0.001) cocaine users compared with never users. Cocaine use may contribute to a larger replication competent HLR in CD4+ T cells among virologically suppressed women living with HIV. Our findings are important because women are underrepresented in HIV reservoir studies and in studies of the impact of cocaine use on outcomes among PLWH.

Circulating tumor DNA in conjunctival melanoma: landscape and surveillance value

PurposeTo evaluate the surveillance value of circulating tumor DNA (ctDNA) for detecting distant metastasis and indicating systemic therapeutic efficacy in conjunctival melanoma (CoM). DesignRetrospective, observational case series. MethodsFrom July 2021 to June 2023, 30 CoM patients in our center underwent plasma ctDNA assessment, out of which 12 individuals presented with distant metastases. We employed a 437-gene panel containing common mutations in CoM and common drug-sensitive mutations using next-generation sequencing (NGS) technology to analyze ctDNA mutations in plasma. Clinical and radiological records were used to assess tumor status. The relationship between ctDNA characteristics, tissue gene mutations, and clinical manifestations were explored. ResultsCoM-related driver mutations were detected in ctDNA of 11 patients with distant metastasis. The ctDNA were highly consistent with tissue sequencing, mutual driver mutation including BRAF, NRAS, KRAS, NF1, CTNNB1, and TP53 mutation. those with a higher VAF had shorter progression-free survival (PFS, p=0.0475) and overall survival (OS, p=0.0043). The ctDNA variant allele fraction (VAF) was not correlated with the sum of the longest diameters (SLD, p=0.8192) in distant metastasis patients. ConclusionsPositive plasma ctDNA reflected the presence of metastases. The ctDNA could be used as a complement or alternative to tissue sequencing. High VAF ctDNA might indicate rapid disease progression in distant metastasis patients.

Sexual transmission of HTLV-1 resulting in uveitis with short-term latency and low proviral load.

Human T-cell Lymphotropic Virus Type 1 (HTLV-1) is traditionally linked to severe conditions such as adult T-cell leukemia/lymphoma, HTLV-1-associated myelopathy, and HTLV-1 uveitis, with vertical transmission, particularly mother to child thorough breastfeeding, considered the primary route. Despite efforts to reduce vertical transmission through antenatal screening in Japan, horizontal transmission has contributed to the rising prevalence of HTLV-1 in metropolitan areas. This case reports the youngest documented instance of HTLV-1 uveitis resulting from horizontal transmission through sexual contact in an 18-year-old woman. The patient presented with blurred vision in her right eye, and a comprehensive ophthalmologic examination identified vitreous opacity and retinal vasculitis. Serological tests confirmed HTLV-1 infection, with a proviral load of 2.66 copies per 100 peripheral blood mononuclear cells, measured by real-time PCR. A differential diagnosis confirmed HTLV-1 uveitis. Further family and partner investigations confirmed horizontal transmission, most likely through sexual contact. Over 6 years of follow-up, the patient experienced multiple recurrences of HTLV-1 uveitis and developed HTLV-1-associated keratopathy. This case highlights the potential for rapid disease progression with relatively low proviral loads and short latency, emphasizing the need for updated public health strategies for sexually active young populations.

Research progress of biomarkers in evaluating the severity and prognostic value of severe pneumonia in children.

Pneumonia is a serious and common infectious disease in children. If not treated in time, it may develop into severe pneumonia. Severe pneumonia in children is mainly characterized by hypoxia and acidosis, often accompanied by various complications such as sepsis and multiple organ dysfunction. Severe pneumonia has a rapid onset and progression, and a high mortality rate. Biomarkers assist clinicians in the early diagnosis and treatment of patients by quickly and accurately identifying their conditions and prognostic risks. In this study, common clinical and novel biomarkers of severe pneumonia in children were reviewed, and the application value of biomarkers related to the severity and prognosis of severe pneumonia in children was evaluated to provide help for early identification and precise intervention by clinicians.

UCHL1 Overexpression Is Related to the Aggressive Phenotype of Non-small Cell Lung Cancer.

Ubiquitin C-terminal hydrolase L1 (UCHL1), which encodes thiol protease that hydrolyzes a peptide bond at the C-terminal glycine residue of ubiquitin, regulates cell differentiation, proliferation, transcriptional regulation, and numerous other biological processes and may be involved in lung cancer progression. UCHL1 is mainly expressed in the brain and plays a tumor-promoting role in a few cancer types; however, there are limited reports regarding its role in lung cancer. Single-cell RNA (scRNA) sequencing using 10X chromium v3 was performed on a paired normal-appearing and tumor tissue from surgical specimens of a patient who showed unusually rapid progression. To validate clinical implication of the identified biomarkers, immunohistochemical (IHC) analysis was performed on 48 non-small cell lung cancer (NSCLC) tissue specimens, and the correlation with clinical parameters was evaluated. We identified 500 genes overexpressed in tumor tissue compared to those in normal tissue. Among them, UCHL1, brain expressed X-linked 3 (BEX3), and midkine (MDK), which are associated with tumor growth and progression, exhibited a 1.5-fold increase in expression compared to that in normal tissue. IHC analysis of NSCLC tissues showed that only UCHL1 was specifically overexpressed. Additionally, in 48 NSCLC specimens, UCHL1 was specifically upregulated in the cytoplasm and nuclear membrane of tumor cells. Multivariable logistic analysis identified several factors, including smoking, tumor size, and high-grade dysplasia, to be typically associated with UCHL1 overexpression. Survival analyses using The Cancer Genome Atlas (TCGA) datasets revealed that UCHL1 overexpression is substantially associated with poor survival outcomes. Furthermore, a strong association was observed between UCHL1 expression and the clinicopathological features of patients with NSCLC. UCHL1 overexpression was associated with smoking, tumor size, and high-grade dysplasia, which are typically associated with a poor prognosis and survival outcome. These findings suggest that UCHL1 may serve as an effective biomarker of NSCLC.

Peranan medan magnet dan campuran etanol-biodiesel minyak jelantah pada pembakaran droplet terhadap perilaku api dan emisi gas buang

Petroleum reserves are increasingly depleting, causing a scarcity of petroleum fuel caused by the rapid progress of transportation and the manufacturing industry. This condition forces researchers to search for and develop new renewable energy source. The purpose of research is to understanding and determines role of north-south (U-S) and south-south (S-S) magnetic fields to blend waste cooking oil biodiesel-ethanol on flame evolution, flue gas emissions, and temperature during droplet combustion. Waste cooking oil biodiesel and ethanol were used in this research by adding variations in the direction of repulsive and attractive magnetic fields with an intensity of 11000 gauss. Diameter of droplets tested was 0.3 mm and was placed on a type K thermocouple wire with diameter of 0.1 mm. This research found the role of attractive magnetic field (U-S) in blend waste cooking oil biodiesel-ethanol 20% to produce the shortest flame evolution of 704 ms, lowest CO of 165 ppm, and highest temperature of 828.5 oC. This happens because ethanol has a low flash point and large oxygen content, causing the combustion reaction to occur rapidly. The attractive of magnetic field (U-S) plays a role on attracting oxygen around flame to enter combustion reaction, while the H2O resulting from combustion is pumped out of flame.

Case Report: Steven Johnson Syndrome (SIS) Induced By Antibiotics: A Detailed Analysis

Background: Stevens-Johnson Syndrome SJS is a rare but very serious mucocutaneous disease primarily caused by medications that includes antibiotics. This case report is about a 35-year-old male who suffered from SJS due to treatment for urinary tract infection using co-trimoxazole. Case Presentation: The patient began with symptoms of flu, later on followed by rapid progression of erythematous rash and painful mucosal involvement. On clinical examination, there were blisters, skin detachment involving 10% of the body surface area, and oral and ocular mucosal lesions. This reaction developed in a temporal association with co-trimoxazole therapy, making the drug a likely cause. She was systemically treated with corticosteroids and supportive care and showed marked recovery in two weeks from hospitalization. Conclusion: This case underlines the importance of early suspicion of SJS in patients receiving antibiotic treatment. Removal of the offending drug and timely initiation of multi-disciplinary management will only improve the outcome in such patients.

Fabrication of copper coated aminated graphene oxide based textiles for electromagnetic interference shielding applications

The issue of electromagnetic radiation pollution and interference has been triggered due to rapid progress in electronic and telecommunication technologies. Serious health issues such as cancer, headaches, and improper development of the brain take place due to long-term exposure to dangerous radiation. Therefore, materials are required to provide efficient protection against electromagnetic interference (EMI). This study aimed to protect humans from dangerous radiations of different frequency by developing EMI shielding textiles. For this, a bilayer textile structure was fabricated by the electroless plating of copper on aminated GO cotton fabric. GO was applied on cotton fabric by simple dip and dry method and then amine groups were generated by solvothermal reaction. After that, copper electroless plating was done on aminated GO fabric. According to the results, remarkable EMI SE in different frequency bands was observed in developed fabrics and the maximum EMI SE was about 34 dB at 13.6 GHz. In all the frequency bands ranging between (100 MHz and 13.6 GHz), more than 99.9 % of EMI shielding observed in the developed fabric. Moreover, the developed fabric exhibited high thermal stability and surface resistance of about ~0.18 Ω/cm. The results of this study clearly showed that the efficacy of EMI shielding developed fabric is a remarkable strategy for controlling electromagnetic radiation pollution exposing humans.