Norepinephrine and Dobutamine-Induced Dynamic Left Ventricular Outflow Tract Obstruction Caused by Systolic Anterior Motion.

This study presents a case of norepinephrine and dobutamine-induced dynamic left ventricular outflow tract obstruction (LVOTO) caused by systolic anterior motion (SAM) in a patient experiencing acute anterior myocardial infarction (MI). In a 76-year-old patient presenting with acute MI, intensive use of norepinephrine and dobutamine may lead to the development of dynamic LVOTO and SAM. The presence of hypotension and a new cardiac murmur may suggest a mechanical complication such as acute mitral regurgitation (MR) or ventricular septal rupture (VSR). The assessment of the left ventricular outflow tract (LVOT) using echocardiography plays a critical role in the diagnosis of SAM and its associated MR and dynamic LVOTO. The patient's condition was stabilized through the cessation of inotropes and the implementation of aggressive fluid resuscitation, resulting in improved hemodynamics. In conclusion, prompt identification of the underlying pathophysiological mechanisms is imperative for effectively managing this condition and preventing hemodynamic exacerbation.

Accuracy and correlation of bed and standing scale weights in monitoring volume status in heart failure patients.

Introduction: Accurate volume status monitoring is crucial for effective diuretic therapy in patients with acute decompensated heart failure (ADHF). While guidelines recommend daily standing body weight measurement as an indicator of volume status, bed scales are commonly used in healthcare facilities. Methods: A method-comparison design was used to compare bed and standing scale weights among adults hospitalized with ADHF at Los Angeles County-University of Southern California Medical Center between March and April 2023. Results & Conclusion: Among 51 weight pairs from 43 participants, a clinically significant mean difference of 1.42 ± 1.18 kg was observed, exceeding the recommended threshold. Inaccuracies, with 71% showing differences >0.6 kg, highlight potential fluid management errors when relying on bed scales in ADHF hospitalizations.

Palliative procedures for malignant gastric outlet obstruction: a network meta-analysis.

BACKGROUND: The optimal treatment for malignant gastric outlet obstruction (GOO) remains uncertain. This systematic review aimed to comprehensively investigate the efficacy and safety of four palliative treatments for malignant GOO: gastrojejunostomy, endoscopic ultrasound-guided gastroenterostomy (EUS-GE), stomach-partitioning gastrojejunostomy (PGJ), and endoscopic stenting. METHODS: We searched PubMed, Embase, Cochrane Library, Scopus, and Web of Science databases, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform for randomized controlled trials (RCTs) and cohort studies comparing the four treatments for malignant GOO. We included studies that reported at least one of the following clinical outcomes: clinical success, 30-day mortality, reintervention rate, or length of hospital stay. Evidence from RCTs and non-RCTs was naïve combined to perform network meta-analysis through the frequentist approach using an inverse variance model. Treatments were ranked by P score. RESULTS: This network meta-analysis included 3617 patients from 4 RCTs, 4 prospective cohort studies, and 32 retrospective cohort studies. PGJ was the optimal approach in terms of clinical success and reintervention (P scores: 0.95 and 0.90, respectively). EUS-GE had the highest probability of being the optimal treatment in terms of 30-day mortality and complications (P scores: 0.82 and 0.99, respectively). Cluster ranking to combine the P scores for 30-day mortality and reintervention indicated the benefits of PGJ and EUS-GE (cophenetic correlation coefficient: 0.94; PGJ and EUS-GE were in the same cluster). CONCLUSION: PGJ and EUS-GE are recommended for malignant GOO. PGJ could be the alternative choice in centers with limited resources or in patients who are unsuitable for EUS-GE.

A novel network-based method identifies a cuproplasia-related pan-cancer gene signature to predict patient outcome.

Copper is a vital micronutrient involved in many biological processes and is an essential component of tumour cell growth and migration. Copper influences tumour growth through a process called cuproplasia, defined as abnormal copper-dependent cell-growth and proliferation. Copper-chelation therapy targeting this process has demonstrated efficacy in several clinical trials against cancer. While the molecular pathways associated with cuproplasia are partially known, genetic heterogeneity across different cancer types has limited the understanding of how cuproplasia impacts patient survival. Utilising RNA-sequencing data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets, we generated gene regulatory networks to identify the critical cuproplasia-related genes across 23 different cancer types. From this, we identified a novel 8-gene cuproplasia-related gene signature associated with pan-cancer survival, and a 6-gene prognostic risk score model in low grade glioma. These findings highlight the use of gene regulatory networks to identify cuproplasia-related gene signatures that could be used to generate risk score models. This can potentially identify patients who could benefit from copper-chelation therapy and identifies novel targeted therapeutic strategies.

Hyperparathyroidism with acute pancreatitis in elderly patient treated by radiofrequency ablation: A case report.

Acute pancreatitis as an initial manifestation of primary hyperparathyroidism (PHPT) has been rarely reported. We report a case of acute pancreatitis from a hyperfunctioning parathyroid tumor in an 87-year-old woman with drowsy state. Laboratory tests showed high lipase, calcium, and intact parathyroid hormone level, and abdominal computed tomography scan revealed acute pancreatitis. Neck ultrasound and scintigraphy gave rise to the diagnosis of primary hyperparathyroidism due to a left parathyroid tumor. The patient underwent radiofrequency ablation of the parathyroid tumor. After the procedure, symptoms subsided and patient was discharged from the hospital 2 weeks later. Six months of treatment, the PTH and calcium serum significantly reduced, her clinical presentation was stable, and there were no signs or symptoms of recurrence pancreatitis.

Enhancing engineering optimization using hybrid sine cosine algorithm with Roulette wheel selection and opposition-based learning.

Meta-heuristic algorithms distinguish themselves from conventional optimization methods owing to their intrinsic adaptability and straightforward implementation. Among them, the sine cosine algorithm (SCA) is lauded for its ability to transition seamlessly between exploration and exploitation phases throughout the optimization process. However, there exists potential for enhancing the balance that SCA maintains between exploration and exploitation. To augment the proficiency in global optimization of SCA, an innovative strategy-nSCA-that integrates the roulette wheel selection (RWS) with opposition-based learning was formulated. The robustness of nSCA was rigorously evaluated against leading-edge methods such as the genetic algorithm (GA), particle swarm optimization, moth-flame optimization, ant lion optimization, and multi-verse optimizer, as well as the foundational SCA. This evaluation included benchmarks set by both CEC 2019 and CEC 2021 test functions. Additionally, the performance of nSCA was confirmed through numerous practical optimization problems, emphasizing its effectiveness in applied settings. In all evaluations, nSCA consistently showcased superior performance compared to its evolutionary algorithm counterparts, delivering top-tier solutions for both benchmark functions and real-world optimization challenges. Given this compelling evidence, one can posit that nSCA serves as a strong candidate for addressing intricate optimization challenges found in real-world contexts, regardless of whether they are of a discrete or continuous nature.

Apply EZStrobe to simulate the finishing work for reducing construction process waste.

Vietnam, classified as a developing nation, encounters numerous challenges within its construction sector, including the scarcity of comprehensive and documented historical data regarding risks and a deficiency in embracing contemporary methodologies to mitigate the impact of risk factors on construction project objectives. This paper outlines initial findings from an ongoing research endeavor that centers on implementing Lean Construction (LC) techniques to enhance construction management practices specifically for marble floor finishing work within Vietnam. Therefore, this study aims to apply the construction lean principle combined with discrete-event simulation (DES) by using EZStrobe to simulate the marble floor finishing process in reality, from observing and collecting data of each activity in the actual process on the site. By building, running simulations, and resulting from real-world simulations, we'll understand the sources of waste, and then apply lean construction principles through methods such as just in time, reduce the batch size and resources priorities, and multi-skilled teams for the initial construction process. The study's lean modeling results has led to a 13% reduction in construction cycle time, a 141% improvement in process efficiency, a 268% enhancement in average productivity, and a 96% reduction in labor cost. The result has become the reference document resource for the managers and construction engineers to improve the performance of not only general finishing work but also marble floor finishing work.

Neutrophil: Lymphocyte and Platelet: Lymphocyte ratios measured before transplantation and their correlation with new-onset diabetes post-transplantation in renal transplant recipients.

PURPOSE: Our goal was to evaluate the neutrophil:lymphocyte (NLR) and platelet:lymphocyte (PLR) ratios measured before transplantation and their correlation with new-onset diabetes after transplantation (NODAT) in renal transplant recipients. PATIENTS AND METHODS: We conducted our study in 324 adult patients consecutively admitted to Military Hospital 103, Ha Noi, Viet Nam, who received kidney allografts from living donors. These patients were followed-up during the first 2 years post-transplantation for NODAT. We examined the association between NLR and PLR measured prior to transplantation in patients with NODAT: NLR and PLR were calculated based on the results of the complete blood count. The criteria for diagnosis of a fully symptomatic NODAT case were based on the guidelines established by the American Diabetes Association and included fasting venous blood glucose and glycosylated hemoglobin A1c (HbA1c) levels, with or without an oral glucose tolerance test. RESULTS: The overall rate of NODAT during the two years after kidney transplantation was 13.6%. We found mean values of age and body mass index (BMI), and median values of NLR, PLR, high sensitivity C-reactive protein (hs-CRP) levels, and the arteriosclerosis ratio in the NODAT group to be significantly higher than those of the non-NODAT group (all p < 0.05). Furthermore, an adjusted multivariate regression analysis showed that age (area under the curve [AUC] = 0.727, p < 0.001), BMI (AUC = 0.846, p < 0.001), serum hs-CRP levels (AUC = 0.884, p < 0.001), NLR (AUC = 0.888; p < 0.001), and PLR (AUC = 0.818; p < 0.001) had predictive value for NODAT. CONCLUSION: NLR and PLR measured before transplantation were good predictors for NODAT in the first 2 years post-renal transplantation.

Hybrid whale optimization algorithm for enhanced routing of limited capacity vehicles in supply chain management.

The present study focuses on the problem of vehicle routing with limited capacity, with the objective of minimizing the transportation distance required to serve h clients with predetermined locations and needs. The aim is to create k trips that cover the shortest possible distance. To achieve this goal, a hybrid whale optimization algorithm (hGWOA) is proposed, which combines the whale optimization algorithm (WOA) with the grey wolf optimizer (GWO). The proposed hybrid model is comprised of two main steps. First step, the GWO's hunting mechanism is integrated transitioning to the utilization phase of WOA, and a newly devised state is introduced that is linked to GWO. In the second step, a novel technique is incorporated into the exploration mission phase to enhance the resolve after per iteration. The algorithm's performance is assessed and compared with other modern algorithms, including the GWO, WOA, ant lion optimizer (ALO), and dragonfly algorithm (DA) using 23 benchmark test functions and CEC2017 benchmark test function. The results indicate that the hybrid hGWOA method outperforms other algorithms in terms of delivery distance optimization for scenarios involving scale and complexity. These findings are corroborated through case studies related to cement delivery and a real-world scenario in Viet Nam.

Optimizing daylight in west-facing facades for LEED V4.1 compliance using metaheuristic approach.

This study introduces an optimized design approach for west-facing room façades to improve daylighting while adhering to LEED v4.1 sustainability criteria. Employing parametric modeling, metaheuristic optimization, and validated daylight simulations, the research highlights the African Vulture Optimization Algorithm's success in achieving 100% LEED compliance and superior performance over random models in daylight sufficiency and glare reduction. Light-colored materials and transparent glazing emerged as beneficial for LEED points. Despite computational limitations and the need for empirical validation, this method offers architects versatile and sustainable design solutions. Comparative analysis reveals the algorithm's strong performance, although opportunities exist for refinement. Future research directions include contrasting this algorithm with other optimization methods, focusing on empirical backing, assessing environmental and human-centric impacts, adapting to varied building types and conditions, and examining diverse geographical and material factors. This work advances daylight-integrated façade design, suggesting a more comprehensive framework for building performance optimization.

Optimizing time, cost, and carbon in construction: grasshopper algorithm empowered with tournament selection and opposition-based learning.

The global construction industry plays a pivotal role, yet its unique characteristics pose distinctive challenges. Each construction project, marked by its individuality, substantial value, intricate scale, and constrained adaptability, confronts crucial limitations concerning time and cost. Despite contributing significantly to environmental concerns throughout construction activities and infrastructure operations, environmental considerations remain insufficiently addressed by project managers. This research introduces an improved rendition of the muti-objective grasshopper optimization algorithm (MOGOA), termed eMOGOA, as a novel methodology to tackle time, cost, and carbon dioxide emission trade-off problems (TCCP) in construction project management. To gauge its efficacy, a case study involving 29 activities is employed. eMOGOA amalgamates MOGOA, tournament selection (TS), and opposition-based learning (OBL) techniques to enhance the performance of the original MOGOA. The outcomes demonstrate that eMOGOA surpasses other optimization algorithms, such as MODA, MOSMA, MOALO and MOGOA when applied to TCCP. These findings underscore the efficiency and relevance of the eMOGOA algorithm within the realm of construction project management.

Binding Mechanism and Surface-Enhanced Raman Scattering of the Antimicrobial Sulfathiazole on Gold Nanoparticles.

A combined study using the surface-enhanced Raman scattering (SERS) technique and quantum chemical calculations was carried out to elucidate the adsorption behavior of sulfathiazole, an antibiotic drug, on gold nanoparticles. The tetrahedral Au20 cluster was used as a simple model to mimic a nanostructured gold surface. Computations using density functional theory with the PBE functional were performed in both the gas phase and aqueous medium using a continuum model. The drug is found to bind to the Au metals via the nitrogen of the thiazole ring. The interaction is also partially stabilized by the ring-surface π coupling rather than a sideway adsorption as previously proposed. In an aqueous solution, the drug molecule mainly exists as a deprotonated form, which gives rise to a much greater affinity toward Au nanoparticles as compared to the neutral forms. The drug adsorption further induces a significant alteration on the energy gap of the gold cluster Aun, which could result in an electrical noise. Notable SERS signals below 1600 cm-1, which result from a coupling of several vibrations including the ring breathing, C-C stretching, and N-H bending, could be employed for both qualitative and quantitative detection and assessment of sulfathiazole at trace concentrations.

Economic burden of Thalassemia treatment: An analysis from the Vietnam Social Security perspective.

OBJECTIVES: Thalassemia is a genetic disorder that significantly impacts the health and well-being of individuals in Vietnam. This study aimed to assess the economic burden of Thalassemia treatment in Lam-Dong Province from the perspective of the Vietnam Social Security and to develop a model to forecast these costs. METHODS: This study analyzed the medical records of all 288 health-insured Thalassemia patients who received treatment in Lam-Dong Province from 2019-2021. The annual economic burden was calculated as the total direct medical cost of treatment per patient over one year. Bayesian Model Averaging (BMA) was utilized to forecast economic burdens. The best fit model was selected based on evaluation criteria including the R2 value, the Bayesian information criterion (BIC), and posterior model probabilities. RESULTS: The study found that the average annual economic burden of Thalassemia treatment was VND 9,947,000 (±6,854,000), equivalent to approximately USD 426.7 (±294.0), with blood transfusions being the main contributor to costs (63%). Using BMA, the best fit model to forecast economic burdens included variables including patient age, sex, and length of hospitalization, with age being the key factor with the greatest impact on the increase in economic burden. CONCLUSION: These findings provided important information for policymakers in Vietnam, as they highlighted the significant economic burden of Thalassemia treatment in the country. By developing a model to forecast these costs, policymakers can make informed decisions on how to allocate resources and support individuals with Thalassemia and their families.

Theoretical study of the binding mechanism between anticancerous drug mercaptopurine and gold nanoparticles using a cluster model.

CONTEXT: Mercaptopurine is an effective anticancer medicine yet known with serious adverse reactions, thus requiring further attempts to enhance its biological targeting. Small gold clusters Aun (n = 2-10) were used as model reactants to simulate the surface of gold nanoparticles. The computed results show that the drug molecules tend to anchor on the gold clusters at the S atom with the associated binding energies varying from -50 to -34 kcal mol-1 (in vacuum) and from -42 to -28 kcal mol-1 (in aqueous solution). Furthermore, the adsorption of the drug onto the gold surface is considered as a reversible process, and the mechanism of drug releasing was found to be triggerable by internal factors, such as a pH change or the concentrated presence of thiol amino acids in cancerous protein structures. METHOD: Calculations based on density functional theory (DFT) were performed to probe the nature of interactions between the drug and gold nanoparticles. Structural features, thermodynamic parameters, bonding characteristics, and electronic properties of the resulting complexes were investigated at the PBE//cc-pVTZ/cc-pVDZ-PP level.

Impact of the COVID-19 Pandemic on the Severity and Early Postoperative Outcomes of Acute Appendicitis.

Background The coronavirus disease 2019 (COVID-19) pandemic caused changes in surgical practice. For acute appendicitis (AA), measures to control the pandemic might hinder patients from seeking medical care timely, resulting in increasing severity, postoperative complications, and mortality. This study aimed to investigate whether the COVID-19 pandemic had a negative impact on the severity and postoperative outcomes of patients with AA. Methodology We retrospectively reviewed medical records of AA patients treated operatively at Nhan Dan Gia Dinh Hospital hospital from June 1st to September 30th in three consecutive years: pre-pandemic (2019)/Group 1, minor waves (2020)/Group 2, and major wave (2021)/Group 3 (2021). Data were collected focusing on the duration of symptoms, severity of AA, time from admission to operation, postoperative complications, and mortality. Results There were 1,055 patients, including 452 patients in Group 1, 409 in Group 2, and 194 in Group 3. The overall number of patients decreased mainly in non-complicated AA. The percentages of hospital admission after 24 hours gradually increased (20.8%, 27.9%, and 43.8%, p < 0.05). The percentages of complicated AA in Group 2 and Group 3 were statistically higher than in Group 1 (39% and 55% vs. 31%, p < 0.05). Waiting time for operation increased to five hours during the major wave. Laparoscopic appendectomy was performed in 98-99% of AA patients during the pandemic, with an early postoperative complication rate of 5-9% and a mortality rate of 0.2-1%. Conclusions Although the percentages of hospital admission after 24 hours and complicated AA increased, laparoscopic appendectomy was still feasible and effective and should be maintained as the standard management for AA during the COVID-19 pandemic.

A new look at the structure of the neutral Au18 cluster: hollow versus filled golden cage.

The geometry of the neutral Au18 gold cluster was probed by a combination of quantum chemical calculations and far-infrared multiple photon dissociation (FIR-MPD) spectroscopy of a Kr messenger complex. Two low-lying isomers are identified to potentially contribute to the experimental IR spectrum, both being derived from a star-like Au17 structure upon capping with one extra Au atom either inside (18_1) or outside (18_5) the star. In particular, the present detection of structure 18_1 by DFT computations where a golden cage encapsulates an endohedral Au atom, is intriguing as a stable core-shell isomer has, to our knowledge, never been found before for such small neutral gold clusters. DFT and local coupled-cluster (DLPNO and PNO-CCSD(T)) computations indicate that both Au18 isomers are close to each other, within ∼3 kcal mol-1, on the energy scale. Although the exact energy ordering is again method-dependent and remains, at present, inconclusive, the most striking spectral signatures of both isomers are related to vibrational modes localized at atoms capping the inner pentaprism sub-structure that result in prominent peaks centered at ∼80 cm-1, close to the most prominent experimental feature found at 78 cm-1. The calculated IR spectra of both core-shell and hollow isomers are very similar to each other and both agree comparably well with the experimental FIR-MPD spectra of the Au18Kr1,2 complexes.

Solving large-scale discrete time-cost trade-off problem using hybrid multi-verse optimizer model.

The analysis of the relationship between time and cost is a crucial aspect of construction project management. Various optimization techniques have been developed to solve time-cost trade-off problems. A hybrid multi-verse optimizer model (hDMVO) is introduced in this study, which combines the multi-verse optimizer (MVO) and the sine cosine algorithm (SCA) to address the discrete time-cost trade-off problem (DTCTP). The algorithm's optimality is evaluated by using 23 well-known benchmark test functions. The results demonstrate that hDMVO is competitive with MVO, SCA, the dragonfly algorithm and ant lion optimization. The performance of hDMVO is evaluated using four benchmark test problems of DTCTP, including two medium-scale instances (63 activities) and two large-scale instances (630 activities). The results indicate that hDMVO can provide superior solutions in the time-cost optimization of large-scale and complex projects compared to previous algorithms.

The Impacts of Collaborative Writing on Individual Writing Skills.

The current study was to see if collaborative writing activities would impact each student's writing quality after getting engaged in an academic writing course for argumentative essays. The study enrolled 62 third-year English majors at the Faculty of Foreign Languages, Van Lang University, Ho Chi Minh City, Vietnam, 35 in the experimental group and 27 in the control group. The ages of the students ranged from 19 to 21. All teaching/learning activities, such as the selection of topics, brainstorming, or peer/lecturer feedback, applied to train the students of the two groups were similar except for the essay-composing stage. While the control-group students composed an essay individually, the experimental-group students conducted it collaboratively. That is, the group members composed an essay together. Data from pre-and post-tests of students' writing were analyzed to compare the students' writing quality. The study discovered that jointly authored papers performed much better than those written alone and that collaborative writing activity significantly affected each student's writing quality.

Binding mechanism and SERS spectra of 5-fluorouracil on gold clusters.

The adsorption behaviour of the 5-fluorouracil (5FU) on small gold clusters Au N with N = 6, 8, 20 was evaluated by means of density functional theory using the PBE-D3 functional in combination with a mixed basis set, i.e. cc-pVDZ-PP for gold atoms and cc-pVTZ for non-metal elements. The binding energies between 5FU and gold clusters were determined in the range of 16-24 and 11-19 kcal/mol in gas-phase and aqueous media, respectively. The corresponding Gibbs energies were found to be around -7 to -10 kcal/mol in vacum and sigificantly reduced to -1 to -6 kcal/mol in water solution, indicating that both the association and dissociation processes are likely spontaneous. An analysis on the charge density difference tends to confirm the existence of a charge transfer from the 5FU molecule to Au atoms. Analysis of the surface-enhanced Raman scattering (SERS) spectra of 5FU adsorbed on the Au surfaces shows that the stretching vibrations of N-H and C=O bonds play a major role in the SERS phenomenon. A mechanism for the drug releasing from the gold surfaces is also proposed. The process is triggered by either the low pH in cancerous tumors or the presence of cysteine residues in protein matrices.

Utilizing artificial intelligence to solving time - cost - quality trade-off problem.

This study presents the Slime Mold Algorithm (SMA) to solve the time-cost-quality trade-off problem in a construction project. The proposed SMA is a flexible and efficient algorithm in exploration and exploitation to reach the best optimal solution to process the input model's data. This paper aims to discuss and solve the optimization problem and compare the evaluation with other algorithms such as Opposition-based Multiple Objective Differential Evolution, Non-dominated sorting genetic algorithm, Multiple objective particle swarm optimization, Multiple objective differential evolution and Chaotic initialized multiple objective differential evolution (CAMODE) to verify the efficiency and potential of the proposed algorithm. According to the analysis results, the SMA model generated a diversification measure for case studies, producing superior outcomes to those of previous algorithms.