A data science pipeline applied to Australia's 2022 COVID-19 Omicron waves.

The field of software engineering is advancing at astonishing speed, with packages now available to support many stages of data science pipelines. These packages can support infectious disease modelling to be more robust, efficient and transparent, which has been particularly important during the COVID-19 pandemic. We developed a package for the construction of infectious disease models, integrated it with several open-source libraries and applied this composite pipeline to multiple data sources that provided insights into Australia's 2022 COVID-19 epidemic. We aimed to identify the key processes relevant to COVID-19 transmission dynamics and thereby develop a model that could quantify relevant epidemiological parameters. The pipeline's advantages include markedly increased speed, an expressive application programming interface, the transparency of open-source development, easy access to a broad range of calibration and optimisation tools and consideration of the full workflow from input manipulation through to algorithmic generation of the publication materials. Extending the base model to include mobility effects slightly improved model fit to data, with this approach selected as the model configuration for further epidemiological inference. Under our assumption of widespread immunity against severe outcomes from recent vaccination, incorporating an additional effect of the main vaccination programs rolled out during 2022 on transmission did not further improve model fit. Our simulations suggested that one in every two to six COVID-19 episodes were detected, subsequently emerging Omicron subvariants escaped 30-60% of recently acquired natural immunity and that natural immunity lasted only one to eight months on average. We documented our analyses algorithmically and present our methods in conjunction with interactive online code notebooks and plots. We demonstrate the feasibility of integrating a flexible domain-specific syntax library with state-of-the-art packages in high performance computing, calibration, optimisation and visualisation to create an end-to-end pipeline for infectious disease modelling. We used the resulting platform to demonstrate key epidemiological characteristics of the transition from the emergency to the endemic phase of the COVID-19 pandemic.

Pharmacodynamics of Sishen decoction in relieving rheumatoid arthritis: Chemical composition, regulatory pathway and online prediction simulation.

As a commonly used traditional Chinese medicine formula for treating rheumatoid arthritis (RA), Sishen Decoction (SSD) has anti-inflammatory, analgesic and swelling relief effects. However, at present, the pharmacodynamic basis of SSD and its mechanism of treating RA have not been clarified, and further research is needed. Analyzing the pharmacological basis of SSD was the aim of our study and further elucidate its therapeutic mechanism and potential targets for treating RA. LC‒MS was used to identify the high content and characteristic chemical components of SSD. On this basis, a network of pharmacological analysis was established between the chemical structure and RA. According to the predicted possible pathways and targets, in vivo pharmacodynamic experiments and related pathway analysis were conducted. Finally, the possible targets and mechanisms of SSD in treating RA were analyzed. Identified 78 compounds from SSD by LC-MS, including 23 flavonoids, 19 phenolic acids, 9 monoterpenoids and 26 other compounds. Network pharmacological analysis based on pharmacodynamic substances revealed that the most likely interaction pathway between SSD and RA was the PI3K/AKT/mTOR pathway. Foot swelling and inflammatory factors (IL-6, IL-10, IL-18, TGF, TNF-α, VEGF) in model mice were shown to be significantly improved in vivo. WB and qPCR experiments proved that SSD could significantly regulate the pathway of PI3K/AKT/mTOR. The interaction between SSD and AKT target was further analyzed by multispectroscopy. This study revealed that SSD alleviates RA by regulating the pathway of PI3K/AKT/mTOR and preliminarily revealed the pharmacodynamic mechanism of SSD for the first time.

An auxin homeostat allows plant cells to establish and control defined transmembrane auxin gradients.

Extracellular auxin maxima and minima are important to control plant developmental programs. Auxin gradients are provided by the concerted action of proteins from the three major plasma membrane (PM) auxin transporter classes AUX1/LAX, PIN and ATP-BINDING CASSETTE subfamily B (ABCB) transporters. But neither genetic nor biochemical nor modeling approaches have been able to reliably assign the individual roles and interplay of these transporter types. Based on the thermodynamic properties of the transporters, we show here by mathematical modeling and computational simulations that the concerted action of different auxin transporter types allows the adjustment of specific transmembrane auxin gradients. The dynamic flexibility of the 'auxin homeostat' comes at the cost of an energy-consuming 'auxin cycling' across the membrane. An unexpected finding was that potential functional ABCB-PIN synchronization appears to allow an optimization of the trade-off between the speed of PM auxin gradient adjustment on the one hand and ATP consumption and disturbance of general anion homeostasis on the other. In conclusion, our analyses provide fundamental insights into the thermodynamic constraints and flexibility of transmembrane auxin transport in plants.

Computational insights into the aggregation mechanism and amyloidogenic core of aortic amyloid medin polypeptide.

Medin amyloid, prevalent in the vessel walls of 97 % of individuals over 50, contributes to arterial stiffening and cerebrovascular dysfunction, yet our understanding of its aggregation mechanism remains limited. Dividing the full-length 50-amino-acid medin peptide into five 10-residue segments, we conducted individual investigations on each segment's self-assembly dynamics via microsecond-timescale atomistic discrete molecular dynamics (DMD) simulations. Our findings showed that medin1-10 and medin11-20 segments predominantly existed as isolated unstructured monomers, unable to form stable oligomers. Medin31-40 exhibited moderate aggregation, forming dynamic ß-sheet oligomers with frequent association and dissociation. Conversely, medin21-30 and medin41-50 segments demonstrated significant self-assembly capability, readily forming stable ß-sheet-rich oligomers. Residue pairwise contact frequency analysis highlighted the critical roles of residues 22-26 and 43-49 in driving the self-assembly of medin21-30 and medin41-50, acting as the ß-sheet core and facilitating ß-strand formation in other regions within medin monomers, expecting to extend to oligomers and fibrils. Regions containing residues 22-26 and 43-49, with substantial self-assembly abilities and assistance in ß-sheet formation, represent crucial targets for amyloid inhibitor drug design against aortic medial amyloidosis (AMA). In summary, our study not only offers deep insights into the mechanism of medin amyloid formation but also provides crucial theoretical and practical guidance for future treatments of AMA.

Computational Simulation of Virtual Patients Reduces Dataset Bias and Improves Machine Learning-Based Detection of ARDS from Noisy Heterogeneous ICU Datasets.

Goal: Machine learning (ML) technologies that leverage large-scale patient data are promising tools predicting disease evolution in individual patients. However, the limited generalizability of ML models developed on single-center datasets, and their unproven performance in real-world settings, remain significant constraints to their widespread adoption in clinical practice. One approach to tackle this issue is to base learning on large multi-center datasets. However, such heterogeneous datasets can introduce further biases driven by data origin, as data structures and patient cohorts may differ between hospitals. Methods: In this paper, we demonstrate how mechanistic virtual patient (VP) modeling can be used to capture specific features of patients' states and dynamics, while reducing biases introduced by heterogeneous datasets. We show how VP modeling can be used for data augmentation through identification of individualized model parameters approximating disease states of patients with suspected acute respiratory distress syndrome (ARDS) from observational data of mixed origin. We compare the results of an unsupervised learning method (clustering) in two cases: where the learning is based on original patient data and on data derived in the matching procedure of the VP model to real patient data. Results: More robust cluster configurations were observed in clustering using the model-derived data. VP model-based clustering also reduced biases introduced by the inclusion of data from different hospitals and was able to discover an additional cluster with significant ARDS enrichment. Conclusions: Our results indicate that mechanistic VP modeling can be used to significantly reduce biases introduced by learning from heterogeneous datasets and to allow improved discovery of patient cohorts driven exclusively by medical conditions.

Optimising Bioprinting Nozzles through Computational Modelling and Design of Experiments.

3D bioprinting is a promising technique for creating artificial tissues and organs. One of the main challenges of bioprinting is cell damage, due to high pressures and tensions. During the biofabrication process, extrusion bioprinting usually results in low cell viability, typically ranging from 40% to 80%, although better printing performance with higher cell viability can be achieved by optimising the experimental design and operating conditions, with nozzle geometry being a key factor. This article presents a review of studies that have used computational fluid dynamics (CFD) to optimise nozzle geometry. They show that the optimal ranges for diameter and length are 0.2 mm to 1 mm and 8 mm to 10 mm, respectively. In addition, it is recommended that the nozzle should have an internal angle of 20 to 30 degrees, an internal coating of ethylenediaminetetraacetic acid (EDTA), and a shear stress of less than 10 kPa. In addition, a design of experiments technique to obtain an optimal 3D bioprinting configuration for a bioink is also presented. This experimental design would identify bioprinting conditions that minimise cell damage and improve the viability of the printed cells.

Model based deep learning method for focused ultrasound pathway scanning.

The primary purpose of high-intensity focused ultrasound (HIFU), a non-invasive medical therapy, is to precisely target and ablate tumors by focusing high-frequency ultrasound from an external power source. A series of ablations must be performed in order to treat a big volume of tumors, as a single ablation can only remove a small amount of tissue. To maximize therapeutic efficacy while minimizing adverse side effects such as skin burns, preoperative treatment planning is essential in determining the focal site and sonication duration for each ablation. Here, we introduce a machine learning-based approach for designing HIFU treatment plans, which makes use of a map of the material characteristics unique to a patient alongside an accurate thermal simulation. A numerical model was employed to solve the governing equations of HIFU process and to simulate the HIFU absorption mechanism, including ensuing heat transfer process and the temperature rise during the sonication period. To validate the accuracy of this numerical model, a series of tests was conducted using ex vivo bovine liver. The findings indicate that the developed models properly represent the considerable variances observed in tumor geometrical shapes and proficiently generate well-defined closed treated regions based on imaging data. The proposed strategy facilitated the formulation of high-quality treatment plans, with an average tissue over- or under-treatment rate of less than 0.06%. The efficacy of the numerical model in accurately predicting the heating process of HIFU, when combined with machine learning techniques, was validated through quantitative comparison with experimental data. The proposed approach in cooperation with HIFU simulation holds the potential to enhance presurgical HIFU plan.

Computational simulation-assisted template selection of magnetic MOFs molecularly imprinted materials applying the adsorption and detection of multiple fluoroquinolones.

This study utilized computational simulation and surface molecular imprinting technology to develop a magnetic metal-organic framework molecularly imprinted polymer (Fe3O4@ZIF-8@SMIP) capable of selectively recognizing and detecting multiple fluoroquinolones (FQs). The Fe3O4@ZIF-8@SMIP material was synthesized using the "common" template-ofloxacin, identified by computational simulation, demonstrating notable adsorption capacity (88.61-212.93 mg g-1) and rapid mass-transfer features (equilibration time: 2-3 min) for all tested FQs, consistent with Langmuir adsorption model. Subsequently, this material was employed as a magnetic solid-phase-extraction adsorbent for adsorption and detection of multiple FQs by combining with high performance liquid chromatography. The developed method exhibited good linearity for various FQs within the concentration range of 0.1-500 µg L-1, with low limit of detection (0.0605-0.1529 µg L-1) and limit of quantitation (0.2017-0.5097 µg L-1). Satisfactory recoveries (88.38-103.44%) were obtained when applied to spiked food samples, demonstrating the substantial potential of this Fe3O4@ZIF-8@SMIP material for rapid enrichment and identification for multiple FQs residues.

Ascorbic acid and ascorbyl palmitate-loaded liposomes: Development, characterization, stability evaluation, in vitro security profile, antimicrobial and antioxidant activities.

The objective of this work was to prepare and characterize liposomes containing co-encapsulated ascorbic acid (AA) and ascorbyl palmitate (AP), as well as to evaluate their stability, cytotoxicity, antioxidant, and antimicrobial activity. Through the pre-formulation studies, it was possible to improve the formulation, as leaving it more stable and with a greater antioxidant activity, resulting in a formulation designated LIP-AAP, with 161 nm vesicle size, 0.215 polydispersity index, -31.7 mV zeta potential, and pH of 3.34. Encapsulation efficiencies were 37% for AA and 79% for AP, and the content was 1 mg/mL for each compound. The optimized liposomes demonstrated stability under refrigeration for 60 days, significant antioxidant activity (31.4 µMol of TE/mL), and non-toxicity, but no antimicrobial effects against bacteria and fungi were observed. These findings confirm that the co-encapsulated liposomes are potent, stable antioxidants that maintain their physical and chemical properties under optimal storage conditions.

Comprehending the inhibition mechanism of indole-based bis-acylhydrazone compounds on α-glucosidase: Spectral and theoretical approaches.

Indole-based bis-acylhydrazone compounds can inhibit the activity of α-glucosidase and control the concentration of blood glucose. In this paper, the characteristics of three indole-based bis-acylhydrazone compounds with different inhibitory activities of α-glucosidase as well as the interaction with α-glucosidase were studied by experiments and computational simulation techniques. Enzyme kinetic and spectral experiments showed that the indole-based bis-acylhydrazone compounds were able to inhibit enzyme activity through mixed inhibition dominated by competitive inhibition, and during the binding reaction, indole-based bis-acylhydrazone compounds can quench the intrinsic fluorescence of α-glucosidase through static quenching and an aggregation of the indole-based bis-acylhydrazone with α-glucosidase produces a stable complex with a molar ratio of 1:1, and the combination of indole-based bis-acylhydrazone compounds could lead to slight change in the conformation of α-glucosidase. The theoretical simulation demonstrated that the stability of the complex systems was positively correlated with the inhibitory activity of indole-based bis-acylhydrazone compounds, and the indole-based bis-acylhydrazone compounds occupied the active site in the multi-ligand system, resulting in a significant decrease in the binding ability of starch to active amino acids. These results suggested that indole-based bis-acylhydrazone compound was expected to be a new type of α-glucosidase inhibitor.

Advancement in computational simulation and validation of congenital heart disease: a review.

The improvement in congenital heart disease (CHD) treatment and management has increased the life expectancy in infants. However, the long-term efficacy is difficult to assess and thus, computational modelling has been applied for evaluating this. Here, we provide an overview of the applications of computational modelling in CHD based on three categories; CHD involving large blood vessels only, heart chambers only, and CHD that occurs at multiple heart structures. We highlight the advancement of computational simulation of CHD that uses multiscale and multiphysics modelling to ensure a complete representation of the heart and circulation. We provide a brief future direction of computational modelling of CHD such as to include growth and remodelling, detailed conduction system, and occurrence of myocardial infarction. We also proposed validation technique using advanced three-dimensional (3D) printing and particle image velocimetry (PIV) technologies to improve the model accuracy.

Photochemical transformation of liquid crystal monomers in simulated environmental media: Kinetics, mechanism, toxicity variation and QSAR modeling.

Liquid crystal monomers (LCMs) are a new class of emerging pollutants with high octanol-water partition coefficients; however, their transformation behavior and associated risk to environments with high organic matter content has rarely been reported. In this study, we investigated the photodegradation kinetics, mechanism, and toxicity variation of 23 LCMs on leaf wax models (e.g., organic solvents methanol and n-hexane). The order of the photolysis rates of these LCMs were biphenylethyne LCMs > phenylbenzoate LCMs > diphenyl/terphenyl LCMs under simulated sunlight, while the phenylcyclohexane LCMs were resistant to photodegradation. The phenylbenzoate and biphenylethyne LCMs mainly undergo direct photolysis, while the diphenyl/terphenyl LCMs mainly undergo self-sensitized photolysis. The main photolysis pathways are the cleavage of ester bonds for phenylbenzoate LCMs, the addition, oxidation and cleavage of alkynyl groups for biphenylethyne LCMs, and the cleavage/oxidation of chains attached to phenyls and the benzene ring opening for diphenyl/terphenyls LCMs. Most photolysis products remained toxic to aquatic organisms to some degree. Additionally, two quantitative structure-activity relationship models for predicting kobs of LCMs in methanol and n-hexane were developed, and employed to predict kobs of 93 LCMs to fill the kobs data gap in systems mimicking leaf surfaces. These results can be helpful for evaluating the fate and risk of LCMs in environments with high content of organic phase.

Inversion of Left Ventricular Axial Shortening: In Silico Proof of Concept for Treatment of HFpEF.

Left ventricular (LV) longitudinal function is mechanically coupled to the elasticity of the ascending aorta (AA). The pathophysiologic link between a stiff AA and reduced longitudinal strain and the subsequent deterioration in longitudinal LV systolic function is likely relevant in heart failure with preserved ejection fraction (HFpEF). The proposed therapeutic effect of freeing the LV apex and allowing for LV inverse longitudinal shortening was studied in silico utilizing the Living Left Heart Human Model (Dassault Systémes Simulia Corporation). LV function was evaluated in a model with (A) an elastic AA, (B) a stiff AA, and (C) a stiff AA with a free LV apex. The cardiac model simulation demonstrated that freeing the apex caused inverse LV longitudinal shortening that could abolish the deleterious mechanical effect of a stiff AA on LV function. A stiff AA and impairment of the LV longitudinal strain are common in patients with HFpEF. The hypothesis-generating model strongly suggests that freeing the apex and inverse longitudinal shortening may improve LV function in HFpEF patients with a stiff AA.

Three-Dimensional Bowing Measurement of Distal Femur at Actual Size and Clinical Implications of Total Knee Arthroplasty.

Background and Objectives: To assess femoral shaft bowing (FSB) in coronal and sagittal planes and introduce the clinical implications of total knee arthroplasty (TKA) by analyzing a three-dimensional (3D) model with virtual implantation of the femoral component. Materials and Methods: Sixty-eight patients (average age: 69.1 years) underwent 3D model reconstruction of medullary canals using computed tomography (CT) data imported into Mimics® software (version 21.0). A mechanical axis (MA) line was drawn from the midportion of the femoral head to the center of the intercondylar notch. Proximal/distal straight centerlines (length, 60 mm; diameter, 1 mm) were placed in the medullary canal's center. Acute angles between these centerlines were measured to assess lateral and anterior bowing. The acute angle between the distal centerline and MA line was measured for distal coronal and sagittal alignment in both anteroposterior (AP) and lateral views. The diameter of curve (DOC) along the posterior border of the medulla was measured. Results: The mean lateral bowing in the AP view was 3.71°, and the mean anterior bowing in the lateral view was 11.82°. The average DOC of the medullary canal was 1501.68 mm. The average distal coronal alignment of all femurs was 6.40°, while the distal sagittal alignment was 2.66°. Overall, 22 femurs had coronal bowing, 42 had sagittal bowing, and 15 had both. Conclusions: In Asian populations, FSB can occur in coronal, sagittal, or both planes. Increased anterolateral FSB may lead to cortical abutment in the sagittal plane, despite limited space in the coronal plane. During TKA, distal coronal alignment guides the distal femoral valgus cut angle, whereas distal sagittal alignment aids in predicting femoral component positioning to avoid anterior notching. However, osteotomies along the anterior cortical bone intended to prevent notching may result in outliers due to differences between the distal sagittal alignment and the distal anterior cortical axis.

The Stiffness of the Ascending Aorta Has a Direct Impact on Left Ventricular Function: An In Silico Model.

During systole, longitudinal shortening of the left ventricle (LV) displaces the aortic root toward the apex of the heart and stretches the ascending aorta (AA). An in silico study (Living Left Heart Human Model, Dassault Systèmes Simulia Corporation) demonstrated that stiffening of the AA affects myocardial stress and LV strain patterns. With AA stiffening, myofiber stress increased overall in the LV, with particularly high-stress areas at the septum. The most pronounced reduction in strain was noted along the septal longitudinal region. The pressure-volume loops showed that AA stiffening caused a deterioration in LV function, with increased end-systolic volume, reduced systolic LV pressure, decreased stroke volume and effective stroke work, but elevated end-diastolic pressure. An increase in myofiber contractility indicated that stroke volume and effective stroke work could be recovered, with an increase in LV end-systolic pressure and a decrease in end-diastolic pressure. Longitudinal and radial strains remained reduced, but circumferential strains increased over baseline, compensating for lost longitudinal LV function. Myofiber stress increased overall, with the most dramatic increase in the septal region and the LV apex. We demonstrate a direct mechanical pathophysiologic link between stiff AA and reduced longitudinal left ventricular strain which are common in patients with HFpEF.

Computational simulation model of transcatheter edge-to-edge mitral valve repair: a proof-of-concept study.

AIMS: As transcatheter mitral valve (MV) interventions are expanding and more device types and sizes become available, a tool supporting operators in pre-procedural planning and the clinical decision-making process is highly desirable. We sought to develop a finite element computational simulation model to predict the results of transcatheter edge-to-edge repair (TEER) interventions. METHODS AND RESULTS: We prospectively enrolled patients with secondary mitral regurgitation (MR) referred for a clinically indicated TEER. The 3D trans-oesophageal echocardiograms performed at the beginning of the procedure were used to perform the simulation. On the 3D dynamic model of the MV that was first obtained, we simulated the clip implantation using the same clip type, size, number, and implantation location that was used during the intervention. The 3D model of the MV obtained after the simulation of the clip implantation was compared with the clinical results obtained at the end of the intervention. We analysed the degree and location of residual MR and the shape and area of the diastolic MV area. We performed computational simulation on five patients. Overall, the simulated models predicted well the degree and location of the residual regurgitant orifice(s) but tended to underestimate the diastolic mitral orifice area. CONCLUSION: In this proof-of-concept study, we present preliminary results on our algorithm simulating clip implantation in five patients with functional MR. We show promising results regarding the feasibility and accuracy in terms of predicting residual MR and the need to improve the estimation of the diastolic MV area.

Computerized analysis of haptens for the ultrasensitive and specific detection of Pyriftalid.

Pyriftalid (Pyr) is one of the most commonly used herbicides and due to its widespread and improper use, it has led to serious pollution of groundwater, soil and other ecosystems, threatening human health. A rapid method to detect Pyr was urgently needed. A high specific monoclonal antibody (mAb) against Pyr with IC50 values of 4.7 ng/mL was obtained by mAb screening technique and method with enhanced matrix effect. The study firstly proposed colloidal gold immunochromatographic test strips (CGIA) for Pyr, which enables rapid qualitative and quantitative determination of a large number of samples anytime and anywhere, so as to effectively monitor Pyr in environment and grain samples. Based on the properties of the desired Pyr antibody, the hapten Pyr-hapten-4 with high structural similarity to Pyr molecule, similar electrostatic potential distribution, and the ability to expose Pyr functional groups was screened out from five different Pyr haptens, which was consistent with mouse antiserum test. The CGIA quickly analyze the Pyr content in positive samples such as water samples, soil samples, paddy samples, brown rice samples within 10 min, the LOD for Pyr by CGIA as low as 1.84 ng/g, the v LOD value as low as 6 ng/g, and the extinction value as low as 25 ng/g. The content of positive samples detected by CGIA was consistent with the quantitative results of LC-MS/MS, the relative accuracy was within the range of 97-103 %. The recovery rate range for Pyr by CGIA was 92.0-99.7 %, and the coefficient of variation was between 1.30-8.56 %. It indicated Pyr-targeted CGIA test strip was an efficient and fast detection method to detect real environment and food samples.

Anti-Melanogenic Effects of Takifugu flavidus Muscle Hydrolysate in B16F10 Melanoma Cells and Zebrafish.

Abnormal melanogenesis can lead to hyperpigmentation. Tyrosinase (TYR), a key rate-limiting enzyme in melanin production, is an important therapeutic target for these disorders. We investigated the TYR inhibitory activity of hydrolysates extracted from the muscle tissue of Takifugu flavidus (TFMH). We used computer-aided virtual screening to identify a novel peptide that potently inhibited melanin synthesis, simulated its binding mode to TYR, and evaluated functional efficacy in vitro and in vivo. TFMH inhibited the diphenolase activities of mTYR, reducing TYR substrate binding activity and effectively inhibiting melanin synthesis. TFMH indirectly reduced cAMP response element-binding protein phosphorylation in vitro by downregulating melanocortin 1 receptor expression, thereby inhibiting expression of the microphthalmia-associated transcription factor, further decreasing TYR, tyrosinase related protein 1, and dopachrome tautomerase expression and ultimately impeding melanin synthesis. In zebrafish, TFMH significantly reduced black spot formation. TFMH (200 µg/mL) decreased zebrafish TYR activity by 43% and melanin content by 52%. Molecular dynamics simulations over 100 ns revealed that the FGFRSP (T-6) peptide stably binds mushroom TYR via hydrogen bonds and ionic interactions. T-6 (400 µmol/L) reduced melanin content in B16F10 melanoma cells by 71% and TYR activity by 79%. In zebrafish, T-6 (200 µmol/L) inhibited melanin production by 64%. TFMH and T-6 exhibit good potential for the development of natural skin-whitening cosmetic products.