Sequence-Dependent Surface Coverage of ssDNA Coatings on Single-Wall Carbon Nanotubes.

A combination of experimental measurements and molecular dynamics (MD) simulations was used to investigate how the surfaces of single-wall carbon nanotubes (SWCNTs) are covered by adsorbed ssDNA oligos with different base compositions and lengths. By analyzing the UV absorption spectra of ssDNA-coated SWCNTs before and after coating displacement by a transparent surfactant, the mass ratios of adsorbed ssDNA to SWCNTs were determined for poly-T, poly-C, GT-containing, and AT-containing ssDNA oligos. Based on the measured mass ratios, it is estimated that an average of 20, 22, 26, or 32 carbon atoms are covered by one adsorbed thymine, cytosine, adenine, or guanine nucleotide, respectively. In addition, the UV spectra revealed electronic interactions of varying strengths between the nucleobase aromatic rings and the nanotube π-systems. Short poly-T DNA oligos show stronger π-π stacking interactions with SWCNT surfaces than do short poly-C DNA oligos, whereas both long poly-C and poly-T DNA oligos show strong interactions. These experiments were complemented by MD computations on simulated systems that were constrained to match the measured ssDNA/SWCNT mass ratios. The surface coverages computed from the MD results varied with oligo composition in a pattern that correlates higher measured yields of nanotube fluorescence with greater surface coverage.

Virus-Shaped Mesoporous Silica Nanostars to Improve the Transport of Drugs across the Blood-Brain Barrier.

Conditions affecting the brain are the second leading cause of death globally. One of the main challenges for drugs targeting brain diseases is passing the blood-brain barrier (BBB). Here, the effectiveness of mesoporous silica nanostars (MSiNSs) with two different spike lengths to cross an in vitro BBB multicellular model was evaluated and compared to spherical nanoparticles (MSiNP). A modified sol-gel single-micelle epitaxial growth was used to produce MSiNS, which showed no cytotoxicity or immunogenicity at concentrations of up to 1 µg mL-1 in peripheral blood mononuclear and neuronal cells. The nanostar MSiNS effectively penetrated the BBB model after 24 h, and MSiNS-1 with a shorter spike length (9 ± 2 nm) crossed the in vitro BBB model more rapidly than the MSiNS-2 with longer spikes (18 ± 4 nm) or spherical MSiNP at 96 h, which accumulated in the apical and basolateral sides, respectively. Molecular dynamic simulations illustrated an increase in configurational flexibility of the lipid bilayer during contact with the MSiNS, resulting in wrapping, whereas the MSiNP suppressed membrane fluctuations. This work advances an effective brain drug delivery system based on virus-like shaped MSiNS for the treatment of different brain diseases and a mechanism for their interaction with lipid bilayers.

A new fabricated hetero-atom doped carbon quantum dots as a fluorescent probe for metronidazole determination using garlic and red lentils with microwave assistance.

Biocompatible and highly fluorescent phosphorus, nitrogen and sulfur carbon quantum dots (P,N,S-CQDs) were synthesized using a quick and ecologically friendly process inspired from plant sources. Garlic and red lentils were utilized as natural and inexpensive sources for efficient synthesis of the carbon-based quantum dots using green microwave-irradiation, which provides an ultrafast route for carbonization of the organic biomass and subsequent fabrication of P,N,S-CQDs within only 3 min. The formed P,N,S-CQDs showed excellent blue fluorescence at λem = 412 nm when excited at 325 nm with a quantum yield up to 26.4%. These fluorescent dots were used as a nano-sensor for the determination of the commonly used antibacterial and antiprotozoal drug, metronidazole (MTR). As MTR lacked native fluorescence and prior published techniques had several limitations, the proposed methodology became increasingly relevant. This approach affords sensitive detection with a wide linear range of 0.5-100.0 µM and LOD and LOQ values of 0.14 µM and 0.42 µM, respectively. As well as, it is cost-effective and ecologically benign. The MTT test was used to evaluate the in-vitro cytotoxicity of the fabricated P,N,S-CQDs. The findings supported a minimally cytotoxic impact and good biocompatibility, which provide a future perspective for the applicability of these CQDs in biomedical applications.

Role of adaptive radiotherapy during concomitant chemoradiotherapy for limited-stage small-cell lung cancer.

BACKGROUND: Tumor shrinkage is frequently observed during conventionally fractionated chemoradiotherapy for limited-stage small-cell lung cancer (SCLC). The specific goals of this study are to evaluate the gross tumor volume (GTV) changes due to treatment-induced tumor reduction during the course of radiotherapy (RT) and to examine its potential use in adaptive radiotherapy (ART) for tumor dose escalation or normal tissue sparing in patients with SCLC. MATERIALS AND METHODS: A total of 10 patients with SCLC eligible for chemoradiotherapy underwent computed tomography (CT) scan after Fractions 13 and 23 (at nominal doses of 23.4 Gy and 41.4 Gy, respectively). The GTV was delineated on the repeat CT scans, and two treatment plans were generated with or without adaptation to tumor shrinkage during RT for each patient. Dosimetric and volumetric analyses were performed. RESULTS: The average GTV reduction observed over 13 fractions was 58.5% (range: 13.2%-92.3%; P < 0.001) and over 23 fractions was 70% (range: 36.9%-84.5%; P < 0.001). Compared with the plan without adaptation, ART resulted in mean lung dose relative decreases of 8.7%, mean lung volume receiving ≥20 Gy relative decreases of 5%, mean lung volume receiving ≥5Gy relative decreases of 10%, mean medulla spinalis dose relative decreases of 21 cGy, mean esophagus volume receiving ≥50 Gy relative decreases of 19%, and mean heart volume receiving ≥42 Gy relative decreases of 13%. The benefits of ART were the greatest for tumor volumes ≥30 cm 3 and are directly dependent on GTV reduction during treatment. CONCLUSION: ART for SCLC achieved a significant benefit in terms of organ at risk (OAR) and dose escalation.

Examining the quaternary ammonium chitosan Schiff base-ZnO nanocomposite's potential as protective therapy for rats' cisplatin-induced hepatotoxicity.

BACKGROUND: Despite cisplatin's long history as a cornerstone in cancer therapy, both acquired chemoresistance and significant impacts on healthy tissues limit its use. Hepatotoxicity is one of its side effects. Adjunct therapies have shown promise in not only attenuating liver damage caused by cisplatin but also in enhancing the efficacy of chemotherapy. In this context, a new quaternary ammonium chitosan Schiff base (QACSB) was synthesized and applied as an encapsulating agent for the in-situ synthesis of QACSB-ZnO nanocomposite. MATERIAL AND METHODS: Thirty male albino rats were classified into Group 1 (control) distilled water, Group 2 (Cisplatin-treated) (12 mg/kg, i.p), and Group 3 (QACSB-ZnO NCs/cisplatin-treated) (150 mg/kg/day QACSB-ZnO NCs, i.p) for 14 days + a single dose of cisplatin. Liver functions, tissue TNF-α, MDA, and GSH were measured as well as histopathological and immunohistochemical studies were performed. RESULTS: The QACSB-ZnO NCs significantly restore liver functions, tissue TNF-α, MDA, and GSH levels (p < 0.001). Histopathological examination showed patchy necrosis in the cisplatin-treated group versus other groups. The QACSB-ZnO NCs showed a weak TGF-ß1 (score = 4) and a moderate Bcl-2 immunohistochemistry expression (score = 6) versus the CP group. CONCLUSIONS: QACSB-ZnO NCs have been shown to protect the liver from cisplatin-induced hepatotoxicity.

Reactive Carbon Capture: Cooperative and Bifunctional Adsorbent-Catalyst Materials and Process Integration for a New Carbon Economy.

ConspectusTo say the least, releasing CO2 into the atmosphere is reaping undue environmental consequences given the ever-present increase in severe global weather events over the past five years. However, it can be argued that-at least in the confines of current technological capabilities-the atmospheric release of CO2 is somewhat unavoidable given that even shifting toward clean energy sources-such as solar, nuclear, wind, battery, or H2 power-incurs an initial carbon requirement by way of manufacturing the very production abilities through which "clean" energy is generated. Even years from now, experts agree that energy production will be diversified and-as the global population continues to drive the growth of global energy consumption-thermal power derived from carbon combustion is likely to remain one intrinsic energetic source, of which CO2 will always be a byproduct. In this context, it is the responsibility of the scientific community to devise improved pathways of carbon management such that (i) the consequences of combustion on the global environment are reduced and (ii) carbon fuels can be leveraged in a sustainable fashion.In this Account, we discuss a pivotal perspective shift on CO2 emissions derived from a considerable breakthrough in material science from our work at Missouri University of Science and Technology. This account details the development of materials which no longer vilify CO2 emissions as a valueless combustion byproduct, instead providing a path for them to become a potential feedstock. In more specific terms, this work details the development of structured, cooperative "bifunctional" materials (BFMs) comprised of (i) a high-temperature adsorbent and (ii) a heterogeneous catalyst that enable single-bed CO2 capture and utilization in oxidative ethane dehydrogenation (ODHE), oxidative propane dehydrogenation (ODHP), and dry methane reforming (DMR) processes. This Account begins with the conceptual development of the BFMs in the powdered state, followed by detailing the first-ever reports of structuring the materials into facile honeycomb contactors by 3D printing. The Account then summarizes the impressive performance of the 3D-printed BFMs, specifically focusing on how their catalysts (metal oxides and perovskites) influence their reactive CO2 capture performances in ODHE, ODHP, and DMR processes. Such promise of CO2-as-fuel offers a glimpse into the future of a diversified energy economy, in which CO2/fuel looping can play an important role. A major factor in achieving this future is, of course, developing an appropriately active catalyst; an account of whose first breakthroughs in material science are detailed herein.

Nurturing Success: E-Learning readiness and academic self-efficacy in nursing students.

BACKGROUND: As nursing education embraces e-learning as a vital component of its pedagogical approach, understanding the interplay between students' readiness for E-learning and their academic self-efficacy becomes imperative in nurturing successful learning outcomes amidst evolving educational paradigms. PURPOSE: This study aimed to explore the relationship between e-learning readiness, academic self-efficacy, and the academic achievement of nursing students within the dynamic educational environment. DESIGN: This study employed a cross-sectional design. METHODS: A total of 208 nursing students were recruited through convenience sampling at the end of the second semester in 2022. The evaluation included the utilization of Grade Point Average, the Online Learning Readiness Scale, and the Academic Self-Efficacy Scale. FINDINGS: Previous research has indicated a significant positive correlation between academic achievement and readiness for e-learning, suggesting that higher levels of readiness for e-learning among nursing students lead to improved academic achievement (p ≤ 0.001). Additionally, the findings of the current study revealed a notable positive correlation between academic achievement and academic self-efficacy (p ≤ 0.001). CONCLUSION: This study provides valuable insights into the critical role of academic self-efficacy and e-learning readiness in enhancing academic achievement among nursing students.

Hyperglycemia-driven signaling bridges between diabetes and cancer.

Growing epidemiological evidence indicates an association between obesity, type 2 diabetes, and certain cancers, suggesting the existence of common underlying mechanisms in these diseases. Frequent hyperglycemias in type 2 diabetes promote pro-inflammatory responses and stimulate intracellular metabolic flux which rewires signaling pathways and influences the onset and advancement of different types of cancers. Here, we review the provocative impact of hyperglycemia on a subset of interconnected signalling pathways that regulate (i) cell growth and survival, (ii) metabolism adjustments, (iii) protein function modulation in response to nutrient availability (iv) and cell fate and proliferation and which are driven respectively by PI3K (Phosphoinositide 3-kinase), AMPK (AMP-activated protein kinase), O-GlcNAc (O-linked N-acetylglucosamine) and Wnt/ß-catenin. Specifically, we will elaborate on their involvement in glucose metabolism, inflammation, and cell proliferation, highlighting their interplay in the pathogenesis of diabetes and cancer. Furthermore, the influence of antineoplastic and antidiabetic drugs on the unbridled cellular pathways will be examined. This review aims to inspire the next molecular studies to understand how type 2 diabetes may lead to certain cancers. This will contribute to personalized medicine and direct better prevention strategies.

Impact of Nonsurgical Periodontal Treatment of Periodontitis Stages 2 and 3 on Oral Health-Related Quality of Life.

This study investigates the impact of nonsurgical periodontal treatment (NSPT) on oral health-related quality of life (OHRQoL) in patients with periodontitis stages (S)2 and S3, and the factors associated with the prediction of patient-reported outcomes. Periodontitis patients (n = 68) with moderately deep periodontal pockets were recruited. Responses to the Oral Health Impact Profile (OHIP)-14 questionnaire and clinical parameters including plaque index, bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment loss (CAL) were recorded. All patients received supra- and subgingival professional mechanical plaque removal. All clinical parameters and questionnaire responses were recorded again 3 months after NSPT. Clinical parameters and OHIP-14 scores for both stages of periodontitis were significantly improved 3 months after treatment. However, participants with periodontitis S3 had significantly higher total OHIP-14, physical pain, and functional limitation domains scores than periodontitis S2 cases. Baseline CAL, BOP, and the presence of PPD in anterior teeth were positively associated with increased OHIP-14 scores after NSPT. NSPT improved OHRQoL in participants with periodontitis S2 and S3. This was more pronounced in participants having periodontitis S3 than S2. Poorer OHRQoL could be anticipated in people having severe CAL, high BOP, and presence of pockets in the anterior teeth.

TRAF1 Deficiency in Macrophages Drives Exacerbated Joint Inflammation in Rheumatoid Arthritis.

The tumor necrosis factor receptor-associated factor 1 (TRAF1) plays a key role in promoting lymphocyte survival, proliferation, and cytokine production. Recent evidence showed that TRAF1 plays opposing roles in monocytes and macrophages where it controls NF-κB activation and limits pro-inflammatory cytokine production as well as inflammasome-dependent IL-1ß secretion. Importantly, TRAF1 polymorphisms have been strongly linked to an increased risk of rheumatoid arthritis (RA). However, whether and how TRAF1 contributes to RA pathogenesis is not fully understood. Moreover, investigating the role of TRAF1 in driving RA pathogenesis is complicated by its multifaceted and opposing roles in various immune cells. In this study, we subjected wildtype (WT) mice to the collagen antibody-induced arthritis (CAIA) model of RA and injected them intra-articularly with WT- or TRAF1-deficient macrophages. We show that mice injected with TRAF1-deficient macrophages exhibited significantly exacerbated joint inflammation, immune cell infiltration, and tissue damage compared to mice injected with WT macrophages. This study may lay the groundwork for novel therapies for RA that target TRAF1 in macrophages.

A population analysis of delayed ejaculation using a claims database: characteristics and national trends in prevalence, incidence, and pharmacotherapy.

We investigated the prevalence, incidence, and rates of pharmacological treatment of delayed ejaculation using the TriNetX Diamond Network. We included all men evaluated in the inpatient, outpatient, and emergency settings. Prevalence was determined by comparing the number of men diagnosed with delayed ejaculation to the entire population. Incidence was determined by comparing the number of men diagnosed with delayed ejaculation without a prior diagnosis to the overall population without a prior diagnosis. Rates of pharmacologic treatment were calculated by comparing the number of men who received a prescription to the total number of men with delayed ejaculation. Trends in prevalence and incidence were compared using six-month intervals, while trends in pharmacologic treatment were compared using one-year intervals. A total of 23,164 adult males were diagnosed with delayed ejaculation from 2013 to 2019. During the final six-month interval (July to December 2019), 2,747 of 16,496,744 men received a delayed ejaculation diagnosis, and 1,375 of 16,488,270 men without a prior diagnosis were diagnosed with delayed ejaculation. In 2019, only 916 of 4,733 (19.4%) men diagnosed with delayed ejaculation received any prescription, with the most common being testosterone (9.5%), bupropion (6.6%), and buspirone (2.3%). Prevalence, incidence and pharmacologic treatment all had increasing trends.

Clinical meaningfulness and psychometric robustness of the MG Symptoms PRO scales in clinical trials in adults with myasthenia gravis.

Objectives: The objective of this research was to generate psychometric evidence supporting the myasthenia gravis (MG) symptoms patient-reported outcome (PRO) scales as a fit-for-purpose measure of severity of core symptoms of MG and provide information allowing their meaningful interpretation using data from a phase 3 study in MG. Methods: Data from the MycarinG study, a phase 3 study of rozanolixizumab in patients with generalized MG who experience moderate to severe symptoms (ClinicalTrials.gov Identifier: NCT03971422) were analyzed with both classical test theory (CTT) and Rasch measurement theory (RMT). Meaningful within-individual change and group-level meaningful change were estimated for three MG Symptoms PRO scales using anchor- and distribution-based methods. Anchor-based methods used patient global impression of severity (PGIS) and change (PGIC) in MG symptoms as anchors. Results: Good measurement properties of the MG Symptoms PRO scales were shown in the sample of 200 participants: good to excellent reliability (test-retest and internal consistency reliability) and validity (associations between items and scores within the MG Symptoms PRO scales and between the MG Symptoms PRO scores and other clinical outcomes-MG ADL, QMG score, MGC score, and MGFA classes-were as expected); and the items showed good coverage of the continuum and fit to the Rasch model. Triangulation of the anchor- and distribution-based method results led to the definition of clinically meaningful within-patient improvement in scores for Muscle Weakness Fatigability (-16.67), Physical Fatigue (-20.00), and Bulbar Muscle Weakness (-20.00), with associated ranges. Benchmarks are also proposed for the interpretation of group-level results. Conclusion: The strong psychometric performance of the MG Symptoms PRO scales and the information generated to guide its interpretation supports its use in clinical trials for demonstrating the clinical benefits of new treatments targeting core symptoms of MG (muscle weakness fatigability, physical fatigue, bulbar muscle weakness, respiratory muscle weakness, and ocular muscle weakness).

Mapping a sustainable approach: biosynthesis of lactobacilli-silver nanocomposites using whey-based medium for antimicrobial and bioactivity applications.

This study explores a sustainable approach for synthesizing silver nanocomposites (AgNCs) with enhanced antimicrobial and bioactivity using safe Lactobacillus strains and a whey-based medium (WBM). WBM effectively supported the growth of Lactobacillus delbrueckii and Lactobacillus acidophilus, triggering a stress response that led to AgNCs formation. The synthesized AgNCs were characterized using advanced spectroscopic and imaging techniques such as UV‒visible, Fourier transform infrared (FT-IR) spectroscopy, transmission electron (TEM), and scanning electron microscopy with energy dispersive X-ray analysis (SEM-Edx). Lb acidophilus-synthesized AgNCs in WBM (had DLS size average 817.2-974.3 ± PDI = 0.441 nm with an average of metal core size 13.32 ± 3.55 nm) exhibited significant antimicrobial activity against a broad spectrum of pathogens, including bacteria such as Escherichia coli (16.47 ± 2.19 nm), Bacillus cereus (15.31 ± 0.43 nm), Clostridium perfringens (25.95 ± 0.03 mm), Enterococcus faecalis (32.34 ± 0.07 mm), Listeria monocytogenes (23.33 ± 0.05 mm), methicillin-resistant Staphylococcus aureus (MRSA) (13.20 ± 1.76 mm), and filamentous fungi such as Aspergillus brasiliensis (33.46 ± 0.01 mm). In addition, Lb acidophilus-synthesized AgNCs in WBM exhibit remarkable free radical scavenging abilities, suggesting their potential as bioavailable antioxidants. These findings highlight the dual functionality of these biogenic AgNCs, making them promising candidates for applications in both medicine and nutrition.

Designing energy-efficient buildings in urban centers through machine learning and enhanced clean water managements.

Rainwater Harvesting (RWH) is increasingly recognized as a vital sustainable practice in urban environments, aimed at enhancing water conservation and reducing energy consumption. This study introduces an innovative integration of nano-composite materials as Silver Nanoparticles (AgNPs) into RWH systems to elevate water treatment efficiency and assess the resulting environmental and energy-saving benefits. Utilizing a regression analysis approach with Support Vector Machines (SVM) and K-Nearest Neighbors (KNN), this study will reach the study objective. In this study, the inputs are building attributes, environmental parameters, sociodemographic factors, and the algorithms SVM and KNN. At the same time, the outputs are predicted energy consumption, visual comfort outcomes, ROC-AUC values, and Kappa Indices. The integration of AgNPs into RWH systems demonstrated substantial environmental and operational benefits, achieving a 57% reduction in microbial content and 20% reductions in both chemical usage and energy consumption. These improvements highlight the potential of AgNPs to enhance water safety and reduce the environmental impact of traditional water treatments, making them a viable alternative for sustainable water management. Additionally, the use of a hybrid SVM-KNN model effectively predicted building energy usage and visual comfort, with high accuracy and precision, underscoring its utility in optimizing urban building environments for sustainability and comfort.

The role of TNF-α and il-6 SNP in polycystic ovary syndrome susceptibility.

OBJECTIVE: Aim: To shed the light on the impact of TNF-α 1031 T/C (rs-1800629) and IL-6 174 G/C (rs1800795) polymorphism with disease susceptibility and development. PATIENTS AND METHODS: Materials and Methods: A case-control study has been established based on 50 women with confirmed diagnosed polycystic ovarian syndrome, and 50 healthy controls. Allele specific PCR have been done in order to study SNP of TNF-alpha and IL-6 in both groups. RESULTS: Result: The findings of the present investigation indicated that there was a signif i cant dif f erence in the frequency distribution of TNF-alpha 1031 T/C SNP according to genotype between patients and controls group p = 0.02. In addition, there is a high significant difference in the frequencies of distribution of alleles (T/C) between patients and control group p = 0.001. There was a signif i cant dif f erence in the frequency distribution of IL-6 174 G/C between patients and controls group p = 0.026. In addition, there is a signif i cant dif f erence in the frequencies of distribution of participants according to allele (G/C) between patients and control group p = 0.047. Genotype GC was significantly lower in patients' group and genotype GG was high significant in patients' group in comparison with a control group and the differences were significant, p = 0.024 and 0.006, respectively. CONCLUSION: Conclusions: The present study concluded that IL-6 174 G/C, (rs:1800795) single nucleotide polymorphism (SNP) and TNF-alpha 1031 T/C (rs-1800629) were associated with PCOS susceptibility, and GG genotype in IL-6 and C allele in TNF are considered as risk factor.

Colon Cancer Disease Diagnosis Based on Convolutional Neural Network and Fishier Mantis Optimizer.

Colon cancer is a prevalent and potentially fatal disease that demands early and accurate diagnosis for effective treatment. Traditional diagnostic approaches for colon cancer often face limitations in accuracy and efficiency, leading to challenges in early detection and treatment. In response to these challenges, this paper introduces an innovative method that leverages artificial intelligence, specifically convolutional neural network (CNN) and Fishier Mantis Optimizer, for the automated detection of colon cancer. The utilization of deep learning techniques, specifically CNN, enables the extraction of intricate features from medical imaging data, providing a robust and efficient diagnostic model. Additionally, the Fishier Mantis Optimizer, a bio-inspired optimization algorithm inspired by the hunting behavior of the mantis shrimp, is employed to fine-tune the parameters of the CNN, enhancing its convergence speed and performance. This hybrid approach aims to address the limitations of traditional diagnostic methods by leveraging the strengths of both deep learning and nature-inspired optimization to enhance the accuracy and effectiveness of colon cancer diagnosis. The proposed method was evaluated on a comprehensive dataset comprising colon cancer images, and the results demonstrate its superiority over traditional diagnostic approaches. The CNN-Fishier Mantis Optimizer model exhibited high sensitivity, specificity, and overall accuracy in distinguishing between cancer and non-cancer colon tissues. The integration of bio-inspired optimization algorithms with deep learning techniques not only contributes to the advancement of computer-aided diagnostic tools for colon cancer but also holds promise for enhancing the early detection and diagnosis of this disease, thereby facilitating timely intervention and improved patient prognosis. Various CNN designs, such as GoogLeNet and ResNet-50, were employed to capture features associated with colon diseases. However, inaccuracies were introduced in both feature extraction and data classification due to the abundance of features. To address this issue, feature reduction techniques were implemented using Fishier Mantis Optimizer algorithms, outperforming alternative methods such as Genetic Algorithms and simulated annealing. Encouraging results were obtained in the evaluation of diverse metrics, including sensitivity, specificity, accuracy, and F1-Score, which were found to be 94.87%, 96.19%, 97.65%, and 96.76%, respectively.

Comparison of the ability of short time low PEEP challenge and mini fluid challenge to predict fluid responsiveness in patients undergoing open pancreaticoduodenectomy: an observational cohort study.

OBJECTIVE: The mini-fluid challenge (MFC), which assesses the change in stroke volume index (SVI) following the administration of 100 mL of crystalloids, and the short-time low positive end-expiratory pressure (PEEP) challenge (SLPC), which evaluates the temporary reduction in SVI due to a PEEP increment, are two functional hemodynamic tests used to predict fluid responsiveness in the operating room. However, SLPC has not been assessed in patients undergoing abdominal surgery, and there is no study comparing these two methods during laparotomy. Therefore, we aimed to compare the SLPC and MFC in patients undergoing open pancreaticoduodenectomy. PATIENTS AND METHODS: All patients received a standard hemodynamic management. The study protocol evaluated the percentage change in SVI following the application of an additional 5 cmH2O PEEP (SVIΔ%-SLPC) and the infusion of 100 mL crystalloid (SVIΔ%-MFC). Challenges that resulted in an increase of more than 15% in SVI after the 500 ml of fluid loading were classified as positive challenges (PC). Areas under the receiver operating characteristics curves (ROC AUCs) were used for the comparison of the methods. RESULTS: Thirty-three patients completed the study with 94 challenges. Fifty-five (58.5%) of them were PCs. The ROC AUC of SVIΔ%-MFC was observed to be significantly higher than that of SVIΔ%-SLPC (0.97 vs. 0.64, p < 0.001). The best cut-off value for SVIΔ%-MFC was 5.6%. If we had stopped the bolus fluid administration when SVIΔ%-MFC ≤ 5% was observed (lower limit of the gray zone), we would have postponed the fluid loading in 35 (89.7%) of 39 negative challenges. The amount of fluid deferred would have corresponded to up to 40% of the total fluid given. CONCLUSIONS: SVIΔ%-MFC predicts fluid responsiveness with high diagnostic performance and is better than SVIΔ%-SLPC in patients undergoing open pancreatoduodenectomy. Additionally, the use of SVIΔ%-MFC has the potential to defer up to 40% of the total fluid given. CLINICALTRIALS: gov: NCT05419570.

A retrospective cohort study to evaluate disease burden, health care resource utilization, and costs in patients with breast cancer in Dubai, UAE.

BACKGROUND: The current study evaluated the disease burden, health care resource utilization and analyzed the cost burden due to events of special interest among patients with breast cancer (BC) diagnosed and treated in Dubai, United Arab Emirates (UAE), in general and in the subset of patients treated with cyclin-dependent kinase (CDK) 4/6 inhibitors. METHODS: This retrospective cohort study, using insurance e-claims data from Dubai Real-World Database, was conducted from 01 January 2014 to 30 September 2021. Female patients aged ≥ 18 years with at least 1 diagnosis claim for BC and with continuous enrollment during the index period were included. RESULTS: Overall, 8,031 patients were diagnosed with BC (median age: 49.0 years), with the majority (68.1%) being in 41-60-year age group. During the post-index period, BC-specific costs contributed to 84% of the overall disease burden among patients with BC. Inpatient costs (USD 16,956.2) and medication costs (USD 10,251.3) contributed significantly to BC-specific costs. In the subgroup of patients in whom CDK4/6 inhibitors were part of the treatment regimen (n = 174), CDK4/6 inhibitors were commonly prescribed in combination with aromatase inhibitors (41.4%) and estrogen receptor antagonists (17.9%). In patients with BC, health care costs due to events of special interest (n = 1,843) contributed to 17% of the overall disease cost burden. CONCLUSION: The study highlights the significant cost burden among patients with BC, with BC-specific costs contributing to 84% of the overall disease cost burden. Despite few limitations such as study population predominantly comprising of privately insured expatriate patients and only direct healthcare costs being assessed in the current study, most indicative costs have been captured in the study, by careful patient selection and cost comparisons, as applicable. The findings can guide key health care stakeholders (payers and providers) on future policy measures aiming to reduce the cost burden among patients with BC.

Removal of organic contamination from wastewater using granular activated carbon modified-Polyethylene glycol: Characterization, kinetics and isotherm study.

To effectively remove Diazinon (DZ), Amoxicillin (AMX), and Crystal Violet (CV) from aquatic environments, a novel granular activated carbon (GAC) modified with Polyethylene glycol 600 (PEG) was created and manufactured. The chemical properties were investigated using a variety of characteristic analyses, including FT-IR, XRD, FESEM, and N2 adsorption/desorption. The effectiveness of GAC-PEG's adsorption for the removal of DZ, AMX, and CV was assessed under a variety of conditions, including a pH of 4-9 for the solution, 0.003-0.05 g doses of adsorbent, 50-400 ppm starting concentration, and a reaction time of 5-25 min. For DZ, AMX, and CV adsorption, the maximum adsorption capacity (Qmax) was 1163.933, 1163.100, and 1150.300 mg g-1, respectively. The Langmuir isotherm described all of the data from these adsorption experiments, and the pseudo-second-order well explains all-adsorption kinetics. Most contacts between molecules, electrostatic interactions, π-π interactions, hydrogen bonding, and entrapment in the modified CAG network were used to carry out the DZ, AMX, and CV adsorption on the GAC-PEG. The retrievability of the prepared adsorbent was successfully investigated in studies up to two cycles without loss of adsorption efficiency, and it was shown that it can be efficiently separated.