Cost-effectiveness of a novel AI technology to quantify coronary inflammation and cardiovascular risk in patients undergoing routine Coronary Computed Tomography Angiography.

AIMS: Coronary Computed Tomography Angiography (CCTA) is a first line investigation for chest pain in patients with suspected obstructive coronary artery disease (CAD). However, many acute cardiac events occur in the absence of obstructive CAD. We assessed the lifetime cost-effectiveness of integrating a novel artificial intelligence-enhanced image analysis algorithm (AI-Risk) that stratifies the risk of cardiac events by quantifying coronary inflammation, combined with the extent of coronary artery plaque and clinical risk factors, by analysing images from routine CCTA. METHODS AND RESULTS: A hybrid decision-tree with population cohort Markov model was developed from 3,393 consecutive patients who underwent routine CCTA for suspected obstructive CAD and followed up for major adverse cardiac events over a median(IQR) of 7.7(6.4-9.1) years. In a prospective real-world evaluation survey of 744 consecutive patients undergoing CCTA for chest pain investigation, the availability of AI-Risk assessment led to treatment initiation or intensification in 45% of patients. In a further prospective study of 1,214 consecutive patients with extensive guideline recommended cardiovascular risk profiling, AI-Risk stratification led to treatment initiation or intensification in 39% of patients beyond the current clinical guideline recommendations. Treatment guided by AI-Risk modelled over a lifetime horizon could lead to fewer cardiac events (relative reductions of 4%, 4%, 11%, and 12% for myocardial infarction, ischaemic stroke, heart failure and cardiac death, respectively). Implementing AI-Risk classification in routine interpretation of CCTA is highly likely to be cost-effective (Incremental cost-effectiveness ratio £1,371-3,244), both in scenarios of current guideline compliance or when applied only to patients without obstructive CAD. CONCLUSIONS: Compared with standard care, the addition of AI-Risk assessment in routine CCTA interpretation is cost effective, by refining risk guided medical management.

Physiological Metabolic Analysis of VB12 Accumulation in Ensifer adhaerens Casida A Enhanced by Oxygen Limitation.

Cobalamin (VB12) is in enormous demand across the fields of medicine, food, and feed additives. However, the oxygen supply plays a critical role in VB12 biosynthesis by Ensifer adhaerens Casida A and has been identified as a bottleneck for economical substrate consumption. This study elucidates the relationship between oxygen limitation and VB12 accumulation with transcriptomic and metabolomic analyses. Under oxygen limitation, E. adhaerens enhances oxygen transport and storage by increasing expression of flavin hemoglobin (Hmp), which was up-regulated 6-fold at 24 h of oxygen restriction compared to the oxygen restriction of 4 h (p < 0.01). Because of the cofactor of Hmp is heme, the demand for heme increases, leading to the upregulation of genes in the heme biosynthesis pathway. Similarly, genes involved in biosynthesis of its precursor, 5-ALA, were upregulated as well. 5-ALA is also a direct precursor of VB12, further leading to the upregulation of genes in the VB12 biosynthesis pathway. This process initiates biosynthesis and accumulation of VB12. As VB12 and heme biosynthesis progresses, genes associated with the biosynthesis and transportation pathways of compounds related to their biosynthesis were likewise upregulated, including genes involved in S-adenosyl methionine (SAM) biosynthesis, and the transport of Fe2+ and Co2+. Additionally, amino acids and organic acids associated with biosynthesis were also extensively consumed, such as methionine, which is used for synthesizing SAM, decreased by 310% after 24 h of oxygen limitation compared to 20% dissolved oxygen (p < 0.05). At the same time, genes related to growth-associated metabolic pathways, such as pentose phosphate pathway (PPP), were significantly downregulated. Therefore, the potential mechanism by which E. adhaerens accumulates VB12 under oxygen-limited conditions by enhancing Hmp expression, which facilitates the porphyrin metabolic pathway and promotes VB12 biosynthesis. This research provides valuable insights for increasing VB12 production through metabolic engineering and process optimization.

Intrathecal Dexmedetomidine as an Adjuvant to Low Dose Hyperbaric 0.5% Bupivacaine on Haemodynamic Parameters in Patients Undergoing Transurethral Resection of Prostate.

OBJECTIVE: To determine the role of dexmedetomidine in potentiating the local anaesthetic efficacy of a low dose of bupivacaine when used as an adjuvant. STUDY DESIGN: A prospective, double-blind, randomised study. Place and Duration of the Study: Department of Anaesthesia, Sindh Institute of Urology and Transplantation, Karachi, Pakistan, from July 2021 to February 2022. METHODOLOGY: One hundred and eight patients of ASA physical class I-III undergoing transurethral resection of the prostate (TURP) under sub-arachnoid block (SAB) were enroled and distributed into two equal groups. Group BUPIPURE (BP) was given 7.5 mg of pure 0.5% hyperbaric bupivacain whereas group BUPIDEX (BD) was given 6 mg of 0.5% hyperbaric bupivacain with 3 µg dexmedetomidine intrathecally. The effects in Both groups were compared using chi-square and unpaired t-tests. A significance level of p <0.05 was used to evaluate the statistical significance. RESULTS: Both groups demonstrated a steady decrease in mean heart rate (mean HR 98.9-62.7 per minute as compared to 79.1-59.4 per minute in groups BP and BD, respectively), however, no patient reached to HR <50/min. Group BP had a higher HR variability than group BD. The two groups' median peak sensory levels were similar. However, a statistically significant difference was revealed in the time taken for 2-segment regression (87.5 ± 11.3 min vs. 115.5 ± 6.2 min p <0.001 in BP and BD), as well as the time to reach T10 sensory level (13.56 ± 2.5 min vs. 10.9 ± 3.0 min p <0.001). CONCLUSION: In patients having TURP, intrathecal dexmedetomidine combined with low-dose bupivacaine results in a quicker start, extended sensory and motor block, and a decreased need for rescue analgesics. KEY WORDS: Adjuvants, Dexmedetomidine, Spinal anaesthesia, Transurethral Resection of Prostate.

Dexmedetomidine versus Ketofol for Moderate Sedation in Endoscopic Retrograde Cholangiopancreatography.

OBJECTIVE: To compare the efficacy of dexmedetomidine versus ketofol for moderate sedation in patients undergoing endoscopic retrograde cholangiopancreatography (ERCP). STUDY DESIGN: Randomised controlled trial. Place and Duration of the Study: Department of Anaesthesia, SICU and Pain Management, Sindh Institute of Urology and Transplantation, Karachi, Paksitan, from December 2021 to June 2022. METHODOLOGY: Sixty-two patients aged 20-60 years of any gender scheduled for elective ERCP were included. Patients were randomly divided into Dexmedetomidine group (2ml ampule of 100ug/ml diluted in 18ml of normal saline) and Ketofol group (2ml ketamine and 10ml of propofol 1% diluted in 8ml of normal saline) for sedation. The mean difference in time to achieve Ramsay Sedation Scale (RSS) score of 4 and Modified Aldrete's Score (MAS) of 9 were noted as outcomes in each group. In addition, complications during the procedure and recovery were also noted. RESULTS: The mean age was 39.15 ± 9.82 years. There were 33 (53.2%) males and 29 (46.8%) females. The mean time to achieve RSS 4 was significantly lower in patients who were treated with Dexmedetomidine as compared to Ketofol, i.e., 11.84 ± 1.77 minutes vs. 13.10 ± 1.64 minutes respectively (p-value 0.005, 95% CI -2.12 to -0.39). Similarly, the mean time to achieve MAS score 9 was significantly lower in patients who were treated with Dexmedetomidine as compared to Ketofol, i.e., 11.19 ± 1.72 minutes vs. 12.23 ± 1.84 minutes, respectively (p-value 0.026, 95% CI -1.94 to -0.13). CONCLUSION: Dexmedetomidine proved to be more effective than Ketofol for sedation in ERCP, achieving faster sedation and quicker recovery. KEY WORDS: Dexmedetomidine, Ketofol, Sedation, Endoscopic Retrograde Cholangiopancreatography.

Quality, Usability, and Trust Challenges to Effective Data Use in the Deployment and Use of the Bangladesh Nutrition Information System Dashboard: Qualitative Study.

BACKGROUND: Evidence-based decision-making is essential to improve public health benefits and resources, especially in low- and middle-income countries (LMICs), but the mechanisms of its implementation remain less straightforward. The availability of high-quality, reliable, and sufficient data in LMICs can be challenging due to issues such as a lack of human resource capacity and weak digital infrastructure, among others. Health information systems (HISs) have been critical for aggregating and integrating health-related data from different sources to support evidence-based decision-making. Nutrition information systems (NISs), which are nutrition-focused HISs, collect and report on nutrition-related indicators to improve issues related to malnutrition and food security-and can assist in improving populations' nutritional statuses and the integration of nutrition programming into routine health services. Data visualization tools (DVTs) such as dashboards have been recommended to support evidence-based decision-making, leveraging data from HISs or NISs. The use of such DVTs to support decision-making has largely been unexplored within LMIC contexts. In Bangladesh, the Mukto dashboard was developed to display and visualize nutrition-related performance indicators at the national and subnational levels. However, despite this effort, the current use of nutrition data to guide priorities and decisions remains relatively nascent and underused. OBJECTIVE: The goal of this study is to better understand how Bangladesh's NIS, including the Mukto dashboard, has been used and areas for improvement to facilitate its use for evidence-based decision-making toward ameliorating nutrition-related service delivery and the health status of communities in Bangladesh. METHODS: Primary data collection was conducted through qualitative semistructured interviews with key policy-level stakeholders (n=24). Key informants were identified through purposive sampling and were asked questions about the experiences and challenges with the NIS and related nutrition dashboards. RESULTS: Main themes such as trust, data usability, personal power, and data use for decision-making emerged from the data. Trust in both data collection and quality was lacking among many stakeholders. Poor data usability stemmed from unstandardized indicators, irregular data collection, and differences between rural and urban data. Insufficient personal power and staff training coupled with infrastructural challenges can negatively affect data at the input stage. While stakeholders understood and expressed the importance of evidence-based decision-making, ultimately, they noted that the data were not being used to their maximum potential. CONCLUSIONS: Leveraging DVTs can improve the use of data for evidence-based decision-making, but decision makers must trust that the data are believable, credible, timely, and responsive. The results support the significance of a tailored data ecosystem, which has not reached its full potential in Bangladesh. Recommendations to reach this potential include ensuring a clear intended user base and accountable stakeholders are present. Systems should also have the capacity to ensure data credibility and support ongoing personal power requirements.

Assessing anticancer, antidiabetic, and antioxidant capacities in green-synthesized zinc oxide nanoparticles and solvent-based plant extracts.

Cancer and diabetes represent significant challenges in the field of biomedicine, with major and global impacts on public health. Acacia nilotica, commonly called 'gum arabic tree,' is recognized for its unique biomedical properties. The current study aimed to investigate the pharmacological potential of A. nilotica-based zinc-oxide nanoparticles (ZnO-NPs) in comparison to the ethanol and methanol-based extracts against cancer, diabetes, and oxidative stress. Green synthesis of ZnO-NPs was performed using barks of Acacia nilotica. Different techniques for the characterization of ZnO-NPs, including UV-Visible spectroscopy, Scanning Electron Microscopy, Fourier Transmission Infrared (FT-IR) spectroscopy, and X-ray Diffraction (XRD), were utilized. The morphological analysis of ZnO-NPs revealed that the fine NPs have mean particle sizes of 15 ± 1.5 nm. For the solvent based-extraction, leaves and barks were utilized and dissolved into ethanol and methanol for further processing. The MTT assay revealed that the optimum concentration of ZnO-NPs to inhibit the proliferation of liver cancer cell line HepG2 was 100 µg/mL where 67.0 % inhibition was observed; and both ethanol- and methanol-based extracts showed optimum inhibition at 100 µg/mL. The DPPH assay further demonstrated that 250 µg/mL of ZnO-NPs and 1000 µg/mL of both ethanol- and methanol-based extracts, as the optimum concentration for antioxidant activity (with 73.1 %, 68.9 % and 68.2 % inhibition respectively). The α-Glucosidase inhibition assay revealed that 250 µg/mL of ZnO-NPs and 10 µg/mL of both ethanol- and methanol-based extracts as the optimum concentration for antidiabetic activity (with 95 %, 93.7 % and 93.4 % inhibition respectively). The study provided interesting insights into the efficacy and reliability of ZnO-NPs for potential pharmacological application. Further research should be focused on examining specific pathways and the safety of ZnO-NPs in comparison to solvent-based extracts.

Background radioactivity level estimation and passive shield optimization using adjoint Monte Carlo method.

The current study proposes a procedure to estimate the activity concentration of natural radionuclides and to optimize passive shielding solutions for HPGe detectors using adjoint Monte Carlo (MC) simulation technique of Geant4 for the first time. The background spectrum is acquired for 1.56 × 106 s using an HPGe detector model (GC3020), set inside a shielding solution, during 2021-2022 to estimate the activity concentration of natural radionuclides inside the shielding. While, a background spectrum for 65,000 s is acquired with shielding removed to estimate the concentration of natural radionuclides in the building materials of the laboratory. The detector design used in the simulations is validated by comparing computed and measured Full Energy Peak Efficiency (FEPE) for point sources 241Am, 152Eu, 137Cs, 133Ba, and 60Co. Adjoint MC simulations are used to compute the activity concentration of natural radionuclides assuming an isotropic distribution. The activity concentration of 40K, 226Ra and 232Th in the building material is found to be 524 ± 140, 83 ± 20 and 65 ± 18 Bqkg-1, respectively. The computed values are found in good agreement with the published data. The natural radioactivity levels of 40K, 226Ra and 232Th measured in lead shielding are 155.7 ± 0.1 mBqkg-1, 24 ± 13 mBqkg-1 and 33 ± 17 mBqkg-1 respectively. The radiological risks arising due to natural radioactivity is assessed by calculating radium equivalent activity (Raeq), indoor radiation hazard index (Hin) and annual effective dose equivalent. All the radiological parameters are found below their permissible limits and building materials may be considered radiologically safe. The optimal lead shield thickness for the detector is determined to be 12 cm, resulting in reduction of background signal by two orders of magnitude compared to an unshielded detector. The adjoint MC simulations in Geant4 are 103-104 times more rapid as compared to normal simulations for shield optimization of HPGe detectors and therefore, are identified as viable computing solution to calculate the activity of the background radiation.

Polygonum bistorta Linn. as a green source for synthesis of biocompatible selenium nanoparticles with potent antimicrobial and antioxidant properties.

Here, we report for the first time, green-synthesized selenium nanoparticles (SeNPs) using pharmacologically potent herb of Polygonum bistorta Linn. for multiple biomedical applications. In the study, a facile and an eco-friendly approach is utilized for synthesis of SeNPs using an aqueous roots extract of P. bistorta Linn. followed by extensive characterization via Fourier transform infrared spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and Energy Dispersive X-Ray (EDX) analysis. The XRD and FTIR data determine the phase composition and successful capping of plant extract onto the surface of NPs while SEM and TEM micrographic examination reveals the elliptical and spherical morphology of the particles with a mean size of 69 ± 23 nm. After comprehensive characterization, the NPs are investigated for antifungal, antibacterial, antileishmanial, antioxidant, and biocompatibility properties. The study reveals that Polygonum bistorta Linn. synthesized SeNPs exhibit significant antibacterial and antifungal activities with Staphylococcus aureus and Fusarium oxysporum inducing the highest zone of inhibition of 14 ± 1.0 mm and 20 ± 1.2 mm, respectively at the concentration of 40 mg/mL. The NPs are also found to have antiparasitic potential against promastigote and amastigote forms of Leishmania tropica. Furthermore, the NPs are discovered to have excellent potential in neutralizing harmful free radicals thus exhibiting considerable antioxidant potential. Most importantly, Polygonum bistorta Linn. synthesized SeNPs showed substantial compatibility against blood cells in vitro studies, which signifies the nontoxic nature of the NPs. The study thus concludes that medicinally important Polygonum bistorta Linn. roots can be utilized as an eco-friendly, sustainable, and green source for the synthesis of pharmacologically potent selenium nanoparticles.

Solid Phase Synthesis, DFT Calculations, Molecular Docking, and Biological Studies of Symmetrical N 2,N 4,N 6-Trisubstituted-1,3,5-triazines.

A diversity-oriented, multicomponent convergent synthesis of symmetrical triazines through a one-pot protocol is presented in this research project. The assembly of trisubstituted triazines was initially carried out using easily available reagents through three different protocols, i.e., conventional, MW-assisted synthesis, and solid-supported MW-assisted synthesis using organic and inorganic support to carry out a comparative analysis as to which procedure best corresponds to a greener synthesis protocol. The compounds formed were characterized for structure elucidation and subjected to in vitro anticancer and antibacterial screening. Additionally, computational studies, such as DFT calculations and molecular docking analyses, were conducted.

Soft computing models for prediction of bentonite plastic concrete strength.

Bentonite plastic concrete (BPC) is extensively used in the construction of water-tight structures like cut-off walls in dams, etc., because it offers high plasticity, improved workability, and homogeneity. Also, bentonite is added to concrete mixes for the adsorption of toxic metals. The modified design of BPC, as compared to normal concrete, requires a reliable tool to predict its strength. Thus, this study presents a novel attempt at the application of two innovative evolutionary techniques known as multi-expression programming (MEP) and gene expression programming (GEP) and a boosting-based algorithm known as AdaBoost to predict the 28-day compressive strength ( ) of BPC based on its mixture composition. The MEP and GEP algorithms expressed their outputs in the form of an empirical equation, while AdaBoost failed to do so. The algorithms were trained using a dataset of 246 points gathered from published literature having six important input factors for predicting. The developed models were subject to error evaluation, and the results revealed that all algorithms satisfied the suggested criteria and had a correlation coefficient (R) greater than 0.9 for both the training and testing phases. However, AdaBoost surpassed both MEP and GEP in terms of accuracy and demonstrated a lower testing RMSE of 1.66 compared to 2.02 for MEP and 2.38 for GEP. Similarly, the objective function value for AdaBoost was 0.10 compared to 0.176 for GEP and 0.16 for MEP, which indicated the overall good performance of AdaBoost compared to the two evolutionary techniques. Also, Shapley additive analysis was done on the AdaBoost model to gain further insights into the prediction process, which revealed that cement, coarse aggregate, and fine aggregate are the most important factors in predicting the strength of BPC. Moreover, an interactive graphical user interface (GUI) has been developed to be practically utilized in the civil engineering industry for prediction of BPC strength.

The Acute Impact of Propofol on Blood-Brain Barrier Integrity in Mice.

PURPOSE: We investigated whether short term infusion of propofol, a highly lipophilic agonist at GABAA receptors, which is in widespread clinical use as anesthetic and sedative, affects passive blood-brain barrier (BBB) permeability in vivo. METHODS: Mice were anesthetized with an intraperitoneal injection of ketamine/xylazine followed by a continuous IV infusion of propofol in lipid emulsion through a tail vein catheter. Control groups received ketamine/xylazine anesthesia and an infusion of Intralipid, or ketamine/xylazine anesthesia only. [13C12]sucrose as a permeability marker was injected as IV bolus 15 min after start of the infusions. Brain uptake clearance, Kin, of sucrose was calculated from the brain concentrations at 30 min and the area under the plasma-concentration time curve. We also measured the plasma and brain concentration of propofol at the terminal time point. RESULTS: The Kin value for propofol-infused mice was significantly higher, by a factor of 1.55 and 1.87, compared to the Intralipid infusion and the ketamine/xylazine groups, respectively, while the control groups were not significantly different. No difference was seen in the expression levels of tight junction proteins in brain across all groups. The propofol plasma concentration at the end of infusion (10.7 µM) matched the clinically relevant range of blood concentrations reported in humans, while concentration in brain was 2.5-fold higher than plasma. CONCLUSIONS: Propofol at clinical plasma concentrations acutely increases BBB permeability, extending our previous results with volatile anesthetics to a lipophilic injectable agent. This prompts further exploration, potentially refining clinical practices and ensuring safety, especially during extended propofol infusion schemes.

Spatial patterns and environmental functions of dissolved organic matter in grassland soils of China.

Soil dissolved organic matter (DOM) is crucial to atmospheric, terrestrial and aquatic environments as well as human life. Here, by characterizing DOM from 89 grassland soils throughout China, we reveal the spatial association between DOM geochemistry in the dry season vs annual ecosystem exchange and cancer cases. The humic-like and high molecular weight (3.4-25 kDa) fractions with lower biodegradability, decline from the northern to the southern regions of China, and are correlated with lower soil respiration and net ecosystem productivity at the continental scale. The <1.2 kDa and proteinaceous fractions could serve as a geographical indicator of nasopharyngeal cancer incidence and mortality, while the 3.4-25 kDa and humified fractions are potentially associated with pancreatic cancer cases (P < 0.05). Our findings highlight that exploiting the environmental functions of soil DOM and mitigating the negative impacts are necessary, and require actions tailored to local soil DOM conditions.

Predicting 28-day compressive strength of fibre-reinforced self-compacting concrete (FR-SCC) using MEP and GEP.

The utilization of Self-compacting Concrete (SCC) has escalated worldwide due to its superior properties in comparison to normal concrete such as compaction without vibration, increased flowability and segregation resistance. Various other desirable properties like ductile behaviour, increased strain capacity and tensile strength etc. can be imparted to SCC by incorporation of fibres. Thus, this study presents a novel approach to predict 28-day compressive strength (C-S) of FR-SCC using Gene Expression Programming (GEP) and Multi Expression Programming (MEP) for fostering its widespread use in the industry. For this purpose, a dataset had been compiled from internationally published literature having six input parameters including water-to-cement ratio, silica fume, fine aggregate, coarse aggregate, fibre, and superplasticizer. The predictive abilities of developed algorithms were assessed using error metrices like mean absolute error (MAE), a20-index, and objective function (OF) etc. The comparison of MEP and GEP models indicated that GEP gave a simple equation having lesser errors than MEP. The OF value of GEP was 0.029 compared to 0.031 of MEP. Thus, sensitivity analysis was performed on GEP model. The models were also checked using some external validation checks which also verified that MEP and GEP equations can be used to forecast the strength of FR-SCC for practical uses.