Vector Formulation Research Articles

Analysis of magnetic field formulation for transferred arc thermal plasma modelling

Abstract Thermal plasma modelling of arc plasma systems offers an efficient way to understand the arc dynamics inside the torch and the plume characteristics. Extensive usage of these plasma models necessitates the efforts to improve its fidelity to simulate the actual arc environment. Since the arc dynamics is highly influenced by the self-induced magnetic field, the choice of magnetic field formulations incorporated in the plasma model plays a crucial role. Existing magnetic field formulations based on Ampere’s law, referred as potential vector formulation (PVF), and Biot-Savart law lack accuracy and computational efficiency, respectively. Integration of Biot-Savart law with PVF, referred as mixed formulation (MF), improves the accuracy but still lack computational efficiency. Extended domain based magnetic field formulation (EDF) has the tendency to offer both accuracy and computational efficiency but rarely incorporated in arc plasma system simulations. The present work studies the influence of different magnetic formulations on the self-induced magnetic field prediction in a 2.6 kW transferred arc plasma system. It is inferred that EDF predicts the magnetic field close to that of MF in most of the regions when compared to PVF. Analysing the effect of predicted magnetic field by different formulations on plasma characteristics revealed minimal influence in the considered transferred arc plasma system due to the static arc behaviour. The incorporation of EDF is expected to have significant importance on the scenario with transient arc behaviour.

A lyophilised formulation of chimpanzee adenovirus vector for long-term stability outside the deep-freeze cold chain

BackgroundThe adenovirus-vaccine platform has come to prominence with the COVID-19 vaccination campaigns. The objective of this study was to validate a formulation that was suitable for lyophilisation and long-term storage at 5 (2–8) °C.MethodsVaccine stability was assessed up to five years at 5 °C using a lyophilised formulation of the chimpanzee-adenovirus vector ChAd155 encoding a respiratory syncytial virus (RSV) antigen. Vaccine potency was assessed by functional infectivity assay. Other assessments of vaccine stability included those for capsid integrity, particle content, and DNA release. Vaccine efficacy and safety were assessed after two years in a murine model of RSV challenge and a rabbit toxicology model, respectively.ResultsHere, we show that the potency loss from lyophilisation was 0.12 log10. The potency loss over five years at 5 °C was estimated at 0.21 log10 (95%CI 0.10–0.30). This coincides with a 25% increase in the ratio of non-infectious particles/infectious particles. After two years of storage at 5 °C, (i) the loss of infectivity was 0.17 log10; (ii) the vaccine remained immunogenic and effective at clearing RSV from the lungs in a mouse-challenge model; and (iii) the vaccine was not associated with any adverse safety signal in a rabbit toxicology model.ConclusionsThe 5-year stability of the lyophilised adenovirus-vector vaccine is within our acceptable limit ( < 0.3 log10 decrease). Its formulation process is amenable to manufacturing scale-up and should help in providing adenovirus-based vaccines where the cold chain is problematic, such as in low-income countries, and in pre-epidemic stockpiling.

Green Scalar Function Method for Analyzing Dielectric Media

In this work we present a formalism based on scalar Green’s functions to deal with electromagnetic scattering problems. Although the formulations of the Mie theory and Born approximations in terms of electromagnetic scattering are well known and relevant, they have certain disadvantages: complexity, computational time, few symmetries, etc. Therefore, the study with scalar Green’s functions allows dealing with these problems with greater simplicity and efficiency. However, the information provided by the vector formulation is sacrificed. Nevertheless, different cases of electromagnetic scattering of dielectric media with different dimensions, geometries and refractive indices will be presented. Thus, we will be able to verify the capacity of this scalar method in predicting light-scattering problems.

High ionic strength vector formulations enhance gene transfer to airway epithelia.

A fundamental challenge for cystic fibrosis (CF) gene therapy is ensuring sufficient transduction of airway epithelia to achieve therapeutic correction. Hypertonic saline (HTS) is frequently administered to people with CF to enhance mucus clearance. HTS transiently disrupts epithelial cell tight junctions, but its ability to improve gene transfer has not been investigated. Here, we asked if increasing the concentration of NaCl enhances the transduction efficiency of three gene therapy vectors: adenovirus, AAV, and lentiviral vectors. Vectors formulated with 3-7% NaCl exhibited markedly increased transduction for all three platforms, leading to anion channel correction in primary cultures of human CF epithelial cells and enhanced gene transfer in mouse and pig airways in vivo. The mechanism of transduction enhancement involved tonicity but not osmolarity or pH. Formulating vectors with a high ionic strength solution is a simple strategy to greatly enhance efficacy and immediately improve preclinical or clinical applications.

Homologous but not heterologous COVID-19 vaccine booster elicits IgG4+ B-cells and enhanced Omicron subvariant binding

Booster vaccinations are recommended to improve protection against severe disease from SARS-CoV-2 infection. With primary vaccinations involving various adenoviral vector and mRNA-based formulations, it remains unclear if these differentially affect the immune response to booster doses. We examined the effects of homologous (mRNA/mRNA) and heterologous (adenoviral vector/mRNA) vaccination on antibody and memory B cell (Bmem) responses against ancestral and Omicron subvariants. Healthy adults who received primary BNT162b2 (mRNA) or ChAdOx1 (vector) vaccination were sampled 1-month and 6-months after their 2nd and 3rd dose (homologous or heterologous) vaccination. Recombinant spike receptor-binding domain (RBD) proteins from ancestral, Omicron BA.2 and BA.5 variants were produced for ELISA-based serology, and tetramerized for immunophenotyping of RBD-specific Bmem. Dose 3 boosters significantly increased ancestral RBD-specific plasma IgG and Bmem in both cohorts. Up to 80% of ancestral RBD-specific Bmem expressed IgG1+. IgG4+ Bmem were detectable after primary mRNA vaccination, and expanded significantly to 5–20% after dose 3, whereas heterologous boosting did not elicit IgG4+ Bmem. Recognition of Omicron BA.2 and BA.5 by ancestral RBD-specific plasma IgG increased from 20% to 60% after the 3rd dose in both cohorts. Reactivity of ancestral RBD-specific Bmem to Omicron BA.2 and BA.5 increased following a homologous booster from 40% to 60%, but not after a heterologous booster. A 3rd mRNA dose generates similarly robust serological and Bmem responses in homologous and heterologous vaccination groups. The expansion of IgG4+ Bmem after mRNA priming might result from the unique vaccine formulation or dosing schedule affecting the Bmem response duration and antibody maturation.

Phlebotomine (Diptera: Psychodidae) species and their blood meal sources in a new leishmaniasis focus in Los Montes de María, Bolívar, in northern Colombia

Introduction. El Alférez, a village in Los Montes de María (Bolívar, Colombia) and a macro-focus of leishmaniasis, recorded its first case in 2018, evidencing changes in the distribution and eco-epidemiology of the disease, although interactions between vectors and local fauna remain unknown. Objective. To evaluate the diversity of sandflies and their blood meal sources in the community of El Alférez in the municipality of El Carmen de Bolívar (Bolívar, Colombia). Materials and methods. In 2018, sandflies were collected using LED-based light traps in domestic, peridomestic, and sylvatic ecotopes and identified at the species level. Multiplex polymerase chain reaction targeting the mitochondrial cytochrome B gene was used to analyze blood from the digestive tract. Results. Lutzomyia evansi was the most abundant species (71.85%; n = 485/675), followed by Lu. panamensis, Lu. gomezi, Lu. trinidadensis, Lu. dubitans, Lu. abonnenci, and Lu.aclydifera. Twenty-five percent of the species had blood meals from Canis familiaris (36.00%; n = 9/25), Ovis aries (36.00%; n=9:/25), Bos taurus (24.00%; n = 6/25), Sus scrofa (20.00%; n = 5/25), and Homo sapiens (8.00%; n = 2/25). Lutzomyia evansi registered the highest feeding frequency (68.00%; n = 17/25), predominantly on a single (44.00%; n = 11/25) or multiple species (24.00%; n = 6/25). Conclusion. Results indicate a eclectic feeding behavior in Lu. evansi, implying potential reservoir hosts for Leishmania spp. and increasing transmission risk. This study is a first step towards understanding the diversity of mammalian blood sources used by sandflies, that may be crucial for vector identification and formulation of effective control measures.

Optimizing lentiviral vector formulation conditions for efficient ex vivo transduction of primary human T cells in chimeric antigen receptor T-cell manufacturing

Background aimsChimeric antigen receptor (CAR) T-cell products are commonly generated using lentiviral vector (LV) transduction. Optimal final formulation buffer (FFB) supporting LV stability during cryostorage is crucial for cost-effective manufacturing. MethodsTo identify the ideal LV FFB composition for ex vivo CAR-T production, primary human T cells were transduced with vesicular stomatitis virus G-protein (VSV-G) -pseudotyped LVs (encoding a reporter gene or an anti-CD19-CAR). The formulations included phosphate-buffered saline (PBS), HEPES, or X-VIVOTM 15, and stabilizing excipients. The functional and viral particle titers and vector copy number were measured after LV cryopreservation and up to 24 h post-thaw incubation. CAR-Ts were produced with LVs in selected FFBs, and the resulting cells were characterized. ResultsPost-cryopreservation, HEPES-based FFBs provided higher LV functional titers than PBS and X-VIVOTM 15, and 10% trehalose-20 mM MgCl2 improved LV transduction efficiency in PBS and 50 mM HEPES. Thawed vectors remained stable at +4°C, while a ≤ 25% median decrease in the functional titer occurred during 24 h at room temperature. Tested excipients did not enhance LV post-thaw stability. CAR-Ts produced using LVs cryopreserved in 10% trehalose- or sucrose-20 mM MgCl2 in 50 mM HEPES showed comparable transduction rates, cell yield, viability, phenotype, and in vitro functionality. ConclusionA buffer consisting of 10% trehalose-20 mM MgCl2 in 50 mM HEPES provided a feasible FFB to cryopreserve a VSV-G -pseudotyped LV for CAR-T-cell production. The LVs remained relatively stable for at least 24 h post-thaw, even at ambient temperatures. This study provides insights into process development, showing LV formulation data generated using the relevant target cell type for CAR-T-cell manufacturing.

A closed-form expression of a ductile Fracture Limit Surface (FLS) for general plane stress deformation paths

Ductile fracture in metals is a complex phenomenon caused by the nucleation, growth, and aggregation of micron-sized voids. Existing theoretical models for fracture use experimentally determined Fracture Limit Curves (FLCs) in two-dimensional strain space, which require multiple curves to account for anisotropic effects. This paper proposes a practical closed-form analytical function for a Fracture Limit Surface (FLS) which has a conical shape in the Elastic Distortional Deformation Space (EDDS). The EDDS is a space generated by the components of the elastic distortional metric of the microstructural vectors that characterize elastic distortional deformations and the orientations of anisotropy. The FLS is determined by simulating only four experimental FLCs using a large deformation Eulerian formulation of the microstructural vectors and it depends only on the current state of elastic distortional deformation. It is shown that the failure limit points predicted by the FLS agreed very well with those predicted using a popular evolution equation for damage-based ductile fracture. Path-independence of the FLS is also examined using experimental data. In addition, the example of a B-pillar forming process is presented to show that the FLS can be applied to practical engineering problems with material points that experience general loading paths.

Global self-optimizing control of batch processes

This work considers to achieve near-optimal operation for a class of batch processes by employing self-optimizing control (SOC). Comparing with a continuous one, a batch process exhibits stronger nonlinearity with dynamics because of the non-steady operation condition. This necessitates a global version of SOC to achieve satisfactory performance. Meanwhile, it also makes the existing global SOC (gSOC) not directly applicable to batch processes due to the causality amongst variables. Therefore, it is necessary to extend the original gSOC to batch processes. In addition to the nonconvexity challenge of the original gSOC problem, the new extension for batch processes has to face even more challenges. Particularly, the causality due to dynamics of batch processes brings in structural constraints on controlled variables (CVs), making a CV selection problem even more difficult. To address these challenges, the gSOC problem is recast in a vectorized formulation and it is proved that the structural constraints considered are linear in the vectorized formulation. Moreover, a novel shortcut method is proposed to efficiently find sub-optimal but more transparent solutions for this problem. The effectiveness of the new approach is validated through a case study of a fed-batch reactor, where CVs are constructed through a combination matrix with a repetitive structure, resulting in a simple SOC scheme. This simplicity facilitates the implementation of the SOC approach and enhances its practical applicability and robustness.

Legal provision of state financial support to the agricultural sector in the war and postwar periods

The article is devoted to the study of the current state of legal support of the state financial support of the domestic agricultural sector, the formulation of vectors for the improvement of the relevant legislation in the war and post-war periods, the development of proposals for the proper legal support of the outlined sphere.&#x0D; The analysis of normative acts regulating relations in the sphere of state support of the agricultural sector in the conditions of martial law showed their significant renewal. In particular, in terms of state credit support, the support of agricultural producers has been recognized as a priority area and a number of preferences have been preserved specifically for these subjects. A similar approach is applied to the financial support of economic entities of the agro-industrial complex through the compensation of leasing payments. The abolition of the zero compensatory rate for loans and zero compensatory remuneration for leasing is positioned by the authors of the article as a negative factor that makes it difficult for agribusiness subjects to realize the right to state financial support. The ineffectiveness of state support to the agricultural sector in the form of budget subsidies has been proven. This is a confirmation of the difficult situation in the economy of Ukraine, the reduction of budget funding in this direction and an argument in favor of finding alternative, less burdensome for the state, ways of support. The effectiveness of the activation of indirect and indirect support to the agricultural sector, through the creation of conditions for the better functioning of agribusiness (preferential taxation, customs benefits), involvement of the functions of international institutions, is substantiated.&#x0D; Attention is focused on the need to consolidate at the legislative level already introduced at the level of by-laws this type of state support for the agricultural sector, such as grant support, with further development of this direction in the post­war period.&#x0D; The legal principles of state support of agribusiness entities in terms of compensation for damage caused as a result of the war have been analyzed. It has been proven that the expansion of the directions for determining damage and losses caused to Ukraine as a result of the armed aggression of the Russian Federation in the direction of «damage caused to personal peasant farms and/or farms registered as natural persons - entrepreneurs», as well as the approval of the methodology for determining this damage is a progressive step in the direction of realizing the right of these subjects of the agricultural sector to compensation for the damage caused to them by the war and will contribute to post-war reconstruction.

A virtual element method for the solution of 2D time-harmonic elastic wave equations via scalar potentials

In this paper, we propose and analyse a numerical method to solve 2D Dirichlet time-harmonic elastic wave equations. The procedure is based on the decoupling of the elastic vector field into scalar Pressure (P-) and Shear (S-) waves via a suitable Helmholtz–Hodge decomposition. For the approximation of the two scalar potentials we apply a virtual element method associated with different mesh sizes and degrees of accuracy. We provide for the stability of the method and a convergence error estimate in the L2-norm for the displacement field, in which the contributions to the error associated with the P- and S- waves are separated. In contrast to standard approaches that are directly applied to the vector formulation, this procedure allows for keeping track of the two different wave numbers, that depend on the P- and S- speeds of propagation and, therefore, for using a high-order method for the approximation of the wave associated with the higher wave number. Some numerical tests, validating the theoretical results and showing the good performance of the proposed approach, are presented.

Three-Dimensional Homodyne Light Detection (3D-HLD) for High-Throughput Submicron Particle Analysis in (Highly Concentrated) Protein Biopharmaceuticals, Viral Vectors, and LNPs

During biopharmaceutical development, particle monitoring and characterization are crucial. Notably, particles can be impurities considered as critical quality attribute, or active pharmaceutical ingredient (e.g., viral vectors) or drug delivery system (e.g., lipid nanoparticles) itself. Three-dimensional homodyne light detection (3D-HLD) is a novel technique that can characterize particles in the ∼0.2 µm to 2.0 µm size range.We evaluated 3D-HLD for the analysis of high concentration protein formulations (up to 200 mg/mL), where formulation refractive index and background noise became limiting factors with increasing protein concentration. Sample viscosity however did not impact 3D-HLD results, in contrast to comparative analyses with NTA and MRPS. We also applied 3D-HLD in high-throughput screenings at high protein concentration or of lipid nanoparticle and viral vector formulations, where impurities were analyzed in the presence of a small (<0.2 µm) particulate active pharmaceutical ingredient. 3D-HLD turned out to be in good agreement with or a good complement to other state-of-the-art particle characterization techniques, including BMI, MRPS, and DLS.The main application of 3D-HLD is high-throughput particle analysis at low sample volume. Follow-up investigation of the optimized particle sizing approach and of detection settings could further improve the understanding of the method and potentially increase ease of operation.

Closed Loop Vector Formulation in Eulers Complex Numbers for Multi Loop Planar Mechanisms With N bars A Novel Modeling Approach and Algorithm

This paper presents a novel iterative algorithm incorporated in a user-friendly GUI for modeling the kinematics of multiple looped N-bar closed-loop mechanisms. Past research works have used custom coding or expensive commercial software to analyze the mechanisms of specific applications. The proposed algorithm focuses on kinematics and offers a quick, easy-to-use, cost-effective solution to analyze a wide range of generic mechanisms, reducing the need for custom coding and lowering computational costs. The algorithm employs algebraic equations, such as solving complex closed-loop vector equations using the Euler form of complex numbers, to simulate and derive the unknowns necessary to characterise any generic closed-loop mechanism. The Python code implemented in the algorithm adapts to various scenarios by utilising available information on the position, velocity, and acceleration variables of the mechanisms. The simulation tool can display real-time color contour plots (RGB color scale) for linear and angular velocities and accelerations, simulate mechanisms with multiple loops and switch configurations, and find inverse mechanisms. The approach for solving multiple loop problems and the algorithm utilized to solve the configurations, methods, equations used and GUI features implementation are all described in this study. The case study considered for a four-bar mechanism indicates a strong agreement between the results obtained from the proposed kinematics-based simulator and ANSYS software. These results demonstrate the simulator’s effectiveness in providing low-cost and user-friendly simulation results for various generic mechanisms involving multiple interconnected loops.

Векторная постановка задачи совместного сведения материального и энергетического балансов при расчете фактических показателей тепловой экономичности газотурбинных установок

A scalar formulation of the problem of regularization of material flows in respect to gas turbine units is known. It allows you to consider the maximum permissible overall imbalance of mass and energy, as well as the maximum deviation of parameter values adjusted according to the results of balancing of their initial values. At the same time, there is no possibility to consider the individual standardized metrological characteristics of the measuring instruments used to obtain the initial values of the controlled parameters. The problem of simultaneous equations of the material and energy balances of a gas turbine unit is formulated in a vector value within the framework of Tikhonov’s regularization concept when solving ill-posed problems. To solve the problem, the authors have used the analytical method, the method of iteration of analytical solutions, as well as the method of statistical programming. Analytical and numerical solutions of the stated problem are obtained. They, among other things, consider restrictions on the range of permissible parameter values which are determined by the standardized metrological characteristics of measuring instruments. The impact of the applied method of balancing procedure on the results of calculation of the thermal efficiency indicators of gas turbine plants is shown. To apply thermal efficiency indicators of gas turbine units in the systems of automated monitoring, it is recommended to use a vector formulation of the problem of simultaneous equations when solving it by the method of iterations of analytical solutions or by the method of statistical programming. The developed methodology makes it possible to determine reasonable actual values of the indicators of equipment thermal efficiency under condition of the coincidence of the permissible error of the gross efficiency values of a gas turbine plant, calculated according to direct heat and indirect heat balances.

An Ab Initio Correction Vector Restricted Active Space Approach to the L-Edge XAS and 2p3d RIXS Spectra of Transition Metal Complexes.

We describe an ab initio approach to simulate L-edge X-ray absorption (XAS) and 2p3d resonant inelastic X-ray scattering (RIXS) spectroscopies. We model the strongly correlated electronic structure within a restricted active space and employ a correction vector formulation instead of sum-over-state expressions for the spectra, thus eliminating the need to calculate a large number of intermediate and final electronic states. We present benchmark simulations of the XAS and RIXS spectra of the iron complexes [FeCl4]1-/2- and [Fe(SCH3)4]1-/2- and interpret the spectra by deconvolving the correction vectors. Our approach represents a step toward simulating the X-ray spectroscopies of larger metal cluster systems that play a pivotal role in biology.

Gene-activated hyaluronic acid-based cryogels for cartilage tissue engineering

Articular cartilage injuries are very frequent lesions that if left untreated may degenerate into osteoarthritis. Gene transfer to mesenchymal stem cells (MSCs) provides a powerful approach to treat these lesions by promoting their chondrogenic differentiation into the appropriate cartilage phenotype. Non-viral vectors constitute the safest gene transfer tools, as they avoid important concerns of viral systems including immunogenicity and insertional mutagenesis. However, non-viral gene transfer usually led to lower transfection efficiencies when compared with their viral counterparts. Biomaterial-guided gene delivery has emerged as a promising alternative to increase non-viral gene transfer efficiency by achieving sustained delivery of the candidate gene into cellular microenvironment. In the present study, we designed hyaluronic acid-based gene-activated cryogels (HACGs) encapsulating a novel formulation of non-viral vectors based on niosomes (P80PX) to promote MSCs in situ transfection. The developed HACG P80PX systems showed suitable physicochemical properties to promote MSCs in situ transfection with very low cytotoxicity. Incorporation of a plasmid encoding for the transcription factor SOX9 (psox9) into HACG P80PX systems led to an effective MSCs chondrogenic differentiation with reduced expression of fibrocartilage and hypertrophic markers. The capacity of the developed systems to restore cartilage extracellular matrix was further confirmed in an ex vivo model of chondral defect.

An investigation of excipients for a stable Orf viral vector formulation

The Orf virus (ORFV) is a promising candidate for vector vaccines as well as for immunomodulatory and oncolytic therapies. However, few publications are available on its infectivity degradation or on suitable additives for prolonging its viral stability. In this study, the non-supplemented ORFV itself showed a very high stability at storage temperatures up to 28 °C, with a linear titer loss of 0.10 log infectious particles per day at 4 °C over a period of five weeks. To prolong this inherent stability, thirty additives, i.e., detergents, sugars, proteins, salts, and buffers as well as amino acids, were tested for their time- and temperature-dependent influence on the ORFV infectivity. A stabilizing effect on the infectivity was identified for the addition of all tested proteins, i.e., gelatine, bovine serum albumin, and recombinant human serum albumin (rHSA), of several sugars, i.e., mannitol, galactose, sucrose, and trehalose, of amino acids, i.e., arginine and proline, of the detergent Pluronic F68, and of the salt Na2SO4. The infectivity preservation was especially pronounced for proteins in liquid and frozen formulations, sugars in frozen state, and arginine und Pluronic in liquid formulations at high storage temperatures (37 °C). The addition of 1% rHSA with and without 5% sucrose was evaluated as a very stable formulation with a high safety profile and economic validity at storage temperatures up to 28 °C. At increased temperatures, the supplementation with 200 mM arginine performed better than with rHSA. In summary, this comprehensive data provides different options for a stable ORFV formulation, considering temperature, storage time, economic aspects, and downstream processing integrity.

Life-Limiting Peripheral Organ Dysfunction in Feline Sandhoff Disease Emerges after Effective CNS Gene Therapy.

GM2 gangliosidosis is usually fatal by 5 years of age in its 2 major subtypes, Tay-Sachs and Sandhoff disease. First reported in 1881, GM2 gangliosidosis has no effective treatment today, and children succumb to the disease after a protracted neurodegenerative course and semi-vegetative state. This study seeks to further develop adeno-associated virus (AAV) gene therapy for human translation. Cats with Sandhoff disease were treated by intracranial injection of vectors expressing feline β-N-acetylhexosaminidase, the enzyme deficient in GM2 gangliosidosis. Hexosaminidase activity throughout the brain and spinal cord was above normal after treatment, with highest activities at the injection sites (thalamus and deep cerebellar nuclei). Ganglioside storage was reduced throughout the brain and spinal cord, with near complete clearance in many regions. While untreated cats with Sandhoff disease lived for 4.4 ± 0.6 months, AAV-treated cats lived to 19.1 ± 8.6 months, and 3 of 9 cats lived >21 months. Correction of the central nervous system was so effective that significant increases in lifespan led to the emergence of otherwise subclinical peripheral disease, including megacolon, enlarged stomach and urinary bladder, soft tissue spinal cord compression, and patellar luxation. Throughout the gastrointestinal tract, neurons of the myenteric and submucosal plexuses developed profound pathology, demonstrating that the enteric nervous system was inadequately treated. The vector formulation in the current study effectively treats neuropathology in feline Sandhoff disease, but whole-body targeting will be an important consideration in next-generation approaches. ANN NEUROL 2023;94:969-986.

Machine learning accurately predicts food exchange list and the exchangeable portion.

Food Exchange Lists (FELs) are a user-friendly tool developed to help individuals aid healthy eating habits and follow a specific diet plan. Given the rapidly increasing number of new products or access to new foods, one of the biggest challenges for FELs is being outdated. Supervised machine learning algorithms could be a tool that facilitates this process and allows for updated FELs-the present study aimed to generate an algorithm to predict food classification and calculate the equivalent portion. Data mining techniques were used to generate the algorithm, which consists of processing and analyzing the information to find patterns, trends, or repetitive rules that explain the behavior of the data in a food database after performing this task. It was decided to approach the problem from a vector formulation (through 9 nutrient dimensions) that led to proposals for classifiers such as Spherical K-Means (SKM), and by developing this idea, it was possible to smooth the limits of the classifier with the help of a Multilayer Perceptron (MLP) which were compared with two other algorithms of machine learning, these being Random Forest and XGBoost. The algorithm proposed in this study could classify and calculate the equivalent portion of a single or a list of foods. The algorithm allows the categorization of more than one thousand foods with a confidence level of 97% at the first three places. Also, the algorithm indicates which foods exceed the limits established in sodium, sugar, and/or fat content and show their equivalents. Accurate and robust FELs could improve implementation and adherence to the recommended diet. Compared with manual categorization and calculation, machine learning approaches have several advantages. Machine learning reduces the time needed for manual food categorization and equivalent portion calculation of many food products. Since it is possible to access food composition databases of various populations, our algorithm could be adapted and applied in other databases, offering an even greater diversity of regional products and foods. In conclusion, machine learning is a promising method for automation in generating FELs. This study provides evidence of a large-scale, accurate real-time processing algorithm that can be useful for designing meal plans tailored to the foods consumed by the population. Our model allowed us not only to distinguish and classify foods within a group or subgroup but also to perform the calculation of an equivalent food. As a neural network, this model could be trained with other food bases and thus improve its predictive capacity. Although the performance of the SKM model was lower compared to other types of classifiers, our model allows selecting an equivalent food not from a group previously classified by machine learning but with a fully interpretable algorithm such as cosine similarity for comparing food.

Single-Pass Tangential Flow Filtration (SPTFF) of Nanoparticles: Achieving Sustainable Operation with Dilute Colloidal Suspensions for Gene Therapy Applications.

Recent approval of several viral-vector-based therapeutics has led to renewed interest in the development of more efficient bioprocessing strategies for gene therapy products. Single-Pass Tangential Flow Filtration (SPTFF) can potentially provide inline concentration and final formulation of viral vectors with enhanced product quality due. In this study, SPTFF performance was evaluated using a suspension of 100 nm nanoparticles that mimics a typical lentivirus system. Data were obtained with flat-sheet cassettes having 300 kDa nominal molecular weight cutoff, either in full recirculation or single-pass mode. Flux-stepping experiments identified two critical fluxes, one based on boundary-layer particle accumulation (Jbl) and one based on membrane fouling (Jfoul). The critical fluxes were well-described using a modified concentration polarization model that captures the observed dependence on feed flow rate and feed concentration. Long-duration filtration experiments were conducted under stable SPTFF conditions, with the results suggesting that sustainable performance could potentially be achieved for as much as 6 weeks of continuous operation. These results provide important insights into the potential application of SPTFF for the concentration of viral vectors in the downstream processing of gene therapy agents.