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Biopharmaceutical process development often involves the use of small-scale bioreactors (SSBR) for optimizing media formulations and process conditions during scale up to commercial scale production. Two key process parameters (CPP) used in SSBR studies are protein titre and viable cell density (VCD). Here, we explore the efficacy of parallel polarized total synchronous fluorescence spectroscopy (TSFS ||) and Synchronous Light Scattering (SyLS ||) to qualitatively monitor these CPPs and quantitatively predict titre and VCD for a large-scale cell culture media optimization SSBR study. The study involved 71 different media formulations (50+ components each), and the bioprocess was run for 13 days or more. Samples were extracted at set times (Day 0, 3, 9, and 13) and clarified by centrifugation. TSFS || spectra showed significant emission changes along with increased light scatter over the course of the bioprocess. SyLS || measurements strongly correlated with particle size data obtained from Dynamic Light Scattering but did not correlate well with VCD probably because of the centrifugation-based sample preparation. Statistical and principal component analysis (PCA) of the pTSFS data showed that spectral variation was greater between media formulations than due to the evolving bioprocess. This prevented the development of accurate global prediction models for media performance (e.g., predicting product titre at day 9 from media spectra measured at day 0). However, classification methods were successfully used to select media subsets with better quantitative prediction accuracy based on spectral similarities. A practical binary (high/low performance) classification model based on Support Vector Machines was generated for media formulation screening. Combining emission and scatter measurements with multivariate data analysis provides a more holistic, multi-attribute bioprocess monitoring method that minimizes the need to use different offline analytical methods. This methodology can be used to monitor process trajectories and deviations, and ultimately be used to predict bioprocess CPPs when implemented on production scale processes where there is much less compositional variation in the media. We believe this SSBR-pTSFS/SyLS approach will provide a valuable resource to develop the design/parameter space for in-process monitoring at production scale from early-stage process/media development studies. • First use of polarised emission (TSFS ‖) for analysis of small scale bioreactors (SSBR). • First use of polarised synchronous light scattering (SyLS ‖) for analysis of SSBR. • Combination of TSFS ‖ and SyLS ‖ used to monitor bioprocesses. • Support vector machine analysis of polarised emission predicts media performance. [ABSTRACT FROM AUTHOR]

In the production of polymeric drug delivery devices, dissolution profile and mechanical properties of the drug loaded polymeric matrix are considered important Critical Quality Attributes (CQA) for quality assurance. However, currently the industry relies on offline testing methods which are destructive, slow, labour intensive, and costly. In this work, a real-time method for predicting these CQAs in a Hot Melt Extrusion (HME) process is explored using in-line NIR and temperature sensors together with Machine Learning (ML) algorithms. The mechanical and drug dissolution properties were found to vary significantly with changes in processing conditions, highlighting that real-time methods to accurately predict product properties are highly desirable for process monitoring and optimisation. Nonlinear ML methods including Random Forest (RF), K-Nearest Neighbours (KNN) and Recursive Feature Elimination with RF (RFE-RF) outperformed commonly used linear machine learning methods. For the prediction of tensile strength RFE-RF and KNN achieved R2 values 98% and 99%, respectively. For the prediction of drug dissolution, two time points were considered with drug release at t = 6 h as a measure of the extent of burst release, and t = 96 h as a measure of sustained release. KNN and RFE-RF achieved R2 values of 97% and 96%, respectively in predicting the drug release at t = 96 h. This work for the first time reports the prediction of drug dissolution and mechanical properties of drug loaded polymer product from in-line data collected during the HME process. [ABSTRACT FROM AUTHOR]

Abstract In the production of polymeric drug delivery devices, dissolution profile and mechanical properties of the drug loaded polymeric matrix are considered important Critical Quality Attributes (CQA) for quality assurance. However, currently the industry relies on offline testing methods which are destructive, slow, labour intensive, and costly. In this work, a real-time method for predicting these CQAs in a Hot Melt Extrusion (HME) process is explored using in-line NIR and temperature sensors together with Machine Learning (ML) algorithms. The mechanical and drug dissolution properties were found to vary significantly with changes in processing conditions, highlighting that real-time methods to accurately predict product properties are highly desirable for process monitoring and optimisation. Nonlinear ML methods including Random Forest (RF), K-Nearest Neighbours (KNN) and Recursive Feature Elimination with RF (RFE-RF) outperformed commonly used linear machine learning methods. For the prediction of tensile strength RFE-RF and KNN achieved R 2 values 98% and 99%, respectively. For the prediction of drug dissolution, two time points were considered with drug release at t = 6 h as a measure of the extent of burst release, and t = 96 h as a measure of sustained release. KNN and RFE-RF achieved R 2 values of 97% and 96%, respectively in predicting the drug release at t = 96 h. This work for the first time reports the prediction of drug dissolution and mechanical properties of drug loaded polymer product from in-line data collected during the HME process.

Genetically modified (GM) maize DP910521 was developed to confer resistance against certain lepidopteran insect pests as well as tolerance to glufosinate herbicide; these properties were achieved by introducing the mo‐pat, pmi and cry1B.34 expression cassettes. The molecular characterisation data and bioinformatic analyses did not identify issues requiring food/feed safety assessment. None of the identified differences in the agronomic/phenotypic and compositional characteristics tested between maize DP910521 and its conventional counterpart needs further assessment except for the levels of iron in grain, which do not raise safety and nutritional concerns. The GMO Panel does not identify safety concerns regarding the toxicity and allergenicity of the Cry1B.34, PAT and PMI proteins as expressed in maize DP910521. The GMO panel finds no evidence that the genetic modification impacts the overall safety of maize DP910521. In the context of this application, the consumption of food and feed from maize DP910521 does not represent a nutritional concern in humans and animals. The GMO Panel concludes that maize DP910521 is as safe as its conventional counterpart and non‐GM maize varieties tested, and no post‐market monitoring of food/feed is considered necessary. In the case of accidental release of maize DP910521 material into the environment, this would not raise environmental safety concerns. The post‐market environmental monitoring plan and reporting intervals are in line with the intended uses of maize DP910521. The GMO Panel concludes that maize DP910521 is as safe as its conventional counterpart and the tested non‐GM maize varieties with respect to potential effects on human and animal health and the environment. [ABSTRACT FROM AUTHOR]

A novel data‐driven methodology is presented for developing mathematical models for crystallization processes. The data‐driven approach is based on the sparse identification of nonlinear dynamics (SINDy) method, which iterates between a partial least‐squares fit and a sparsity‐promoting step leading to the discovery of sparse interpretable models. The performance of the SINDy methodology is characterized for the identification of crystallization kinetics in a mixed tank operated in a continuous mode, the isothermal crystallization of lysozyme in a batch stirred tank and cooling crystallization of paracetamol. The SINDy method is robust against noise. Good agreement is obtained between the data‐driven model and the data obtained from crystallization experiments. The presented data‐driven approach can be attractive for modeling industrial crystallization processes where process analytical technology tools are available for the measurement of process variables but functional forms of kinetic expressions are unknown. [ABSTRACT FROM AUTHOR]

In water distribution networks (WDN) equipped with pump as turbines (PATs), in addition to water pressure problems, energy production by PATs is also necessary in abnormal conditions. Reliability indices are the most important parameters in determining the efficiency of systems when components fail. In this research, while proving the correlation weakness of a number of previous indices with the energy, a new energy reliability index is introduced, and it's integrated with previous reliability indices. Since checking the performance of networks from different aspects leads to increasing accuracy and reducing design and operation costs, in the following, the correlation of each of the integrated indices with the performance indices (PI) of adequacy, equity, energy, adequacy- equity, adequacy-energy, equity-energy, and total are calculated for two WDNs. Finally, the most critical network pipes for repair and maintenance (for each of the performance indices) are determined. [ABSTRACT FROM AUTHOR]

Process Analytical Technologies (PATs) are taking a key role in the run for automatization in the biopharmaceutical industry. Spectroscopic methods such as Raman spectroscopy or mid‐infrared (MIR) spectroscopy are getting more recognition in the recent years for inline monitoring of bioprocesses due to their ability to measure various molecules simultaneously. However, their dependency on laborious model calibration making them a challenge to implement. In this study, a novel one‐point calibration that requires a single reference point prior to the inline monitoring of glucose and lactate in bioprocesses with MIR spectroscopy is assessed with 22 mammalian cell perfusion (PER) processes in two different scales and four different products. Concentrations are predicted over all PERs runs with a root mean square error (RMSE) of 0.29 g/L for glucose and 0.24 g/L for lactate, respectively. For comparison conventional partial least square regression (PLSR) models were used and trained with spectroscopic data from six bioreactor runs in two different scales and three products. The general accuracy of those models (RMSE of 0.41 g/L for glucose and 0.16 g/L for lactate) are in the range of the accuracy of the one‐point calibration. This shows the potential of the one‐point calibration as an approach making spectroscopy more accessible for bioprocess development. [ABSTRACT FROM AUTHOR]

Genetically modified maize DP202216 was developed to confer tolerance to glufosinate‐ammonium‐containing herbicides and to provide an opportunity for yield enhancement under field conditions. These properties were achieved by introducing the mo‐pat and zmm28 expression cassettes. The molecular characterisation data and bioinformatic analyses do not identify issues requiring food/feed safety assessment. None of the identified differences in the agronomic/phenotypic and compositional characteristics tested between maize DP202216 and its comparator needs further assessment, except for the levels of stearic acid (C18:0), which do not raise nutritional and safety concerns. The GMO Panel does not identify safety concerns regarding the toxicity and allergenicity of the PAT and ZMM28 proteins as expressed in maize DP202216, and finds no evidence that the genetic modification would change the overall allergenicity of maize DP202216. In the context of this application, the consumption of food and feed from maize DP202216 does not represent a nutritional concern in humans and animals. The GMO Panel concludes that maize DP202216 is as safe as the comparator and non‐GM reference varieties tested, and no post‐market monitoring of food/feed is considered necessary. In the case of accidental release of viable maize DP202216 grains into the environment, this would not raise environmental safety concerns. The post‐market environmental monitoring plan and reporting intervals are in line with the intended uses of maize DP202216. The GMO Panel concludes that maize DP202216 is as safe as its comparator and the tested non‐GM reference varieties with respect to potential effects on human and animal health and the environment. [ABSTRACT FROM AUTHOR]

Whey protein denaturation and aggregation have long been areas of research interest to the dairy industry, having significant implications for process performance and final product functionality and quality. As such, a significant number of analytical techniques have been developed or adapted to assess and characterize levels of whey protein denaturation and aggregation, to either maximize processing efficiency or create products with enhanced functionality (both technological and biological). This review aims to collate and critique these approaches based on their analytical principles and outline their application for the assessment of denaturation and aggregation. This review also provides insights into recent developments in process analytical technologies relating to whey protein denaturation and aggregation, whereby some of the analytical methods have been adapted to enable measurements in‐line. Developments in this area will enable more live, in‐process data to be generated, which will subsequently allow more adaptive processing, enabling improved product quality and processing efficiency. Along with the applicability of these techniques for the assessment of whey protein denaturation and aggregation, limitations are also presented to help assess the suitability of each analytical technique for specific areas of interest. [ABSTRACT FROM AUTHOR]

The main purpose of this research was to develop an experimental film flow cleaning rig that can be combined with Process analytical technology (PAT) tools to reduce cleaning time and costs. Here, we show that the use of in-line UV–Vis was successful for real-time monitoring of the cleaning process of olanzapine as a challenging residue to clean. The cleaning process was found to be affected by the properties of the olanzapine soil, and the study showed the competing effects of mechanical lift-off and dissolution action with methanol as a solvent. However, The method is limited by the cleaning mechanisms, with the dissolution being the only mechanism that can be accurately quantified using an in-line UV–Vis PAT tool. This experimental approach can be used to optimize cleaning process conditions and solvent choices at the bench scale before deployment. The material of which the cleaning rig was printed limited the solvent that could be used for this study, and future modifications will include a more chemical-resistant material.

The dataset consists of FTIR spectra of ultra-filtered spent sulphite liquor (UF-SSL) from softwood pulping obtained from one paper mill biorefinery plant with the purpose of real-time quantification of the sugar content of UF-SSL. Data collection was performed using a submerged mid-IR probe placed in a continuously stirred tank reactor and reference sugar measurements were performed using HPLC. Spectra were obtained of raw and spiked UF-SSL. As “low complexity” case 25% UF-SSL from one batch was analysed for its 3 most abundant sugars (mannose, xylose, glucose) and as “high complexity” case 25/50/75% UF-SSL from 2 batches was analysed for its 5 most abundant sugars (the latter + galactose, arabinose). In both cases, independent single sugar spikes and simultaneous multiple sugar spikes were performed. Real time in-line data was generated by stepwise and gradual changes in sugar composition over time with a run time of >200 h.

In recent years, Beacon Chain known as the core of Ethereum 2.0, has gained considerable attention since its launch. Many validators have staked billions of Ether in the Proof of Stake (PoS) network. It is a mission critical system and its security and stability rely on the justification and finalization of checkpoints. These are essential elements of the Casper FFG consensus algorithm utilized by the Beacon Chain. This process is critical for establishing a trustworthy foundation and finalizing proposed blocks by confirming agreed upon checkpoints. Hence, ensuring the correctness of checkpoints in the Beacon Chain has significant importance because any bug in it can cause serious implications. To address this challenge, we employ formal methods, a popular mathematical approach used for verifying the correctness of such critical systems. In this work, we have done formal verification of the processes of Beacon Chain state initialization, justification and finalization of checkpoints using the Process Analysis Toolkit (PAT) model checker. The adoption of model checking through the PAT model checker presents a novel contribution of our work, as this approach is not previously utilized in the formal verification of Beacon Chain. The presented work is specified through the Communicating Sequential Programs, formal specification language, and the properties are described through Linear Temporal Logic. The PAT model checker takes the specified formal model and properties as input to assess whether the properties are satisfied. The properties are analyzed with respect to the verification time, visited states, total transitions, and memory used. Through this research, we aim to increase confidence in the correctness and reliability of the Beacon Chain.

The world's water infrastructures suffer from inefficiencies, such as high energy consumption and water losses due to inadequate management practices and feeble pressure regulation, leading to frequent water and energy losses. This strains vital water and energy resources, especially in the face of the worsening challenges of climate change and population growth. A novel method is presented that integrates micro-hydropower plants, with pumps as turbines (PATs), in the water network in the city of Funchal. Sensitivity analyses evaluated the microgrid's response to variations in the cost of energy components, showing favorable outcomes with positive net present value (NPV). PV solar and micro-wind turbines installed exclusively at the selected PRV sites within the Funchal hydro grid generate a combined 153 and 55 MWh/year, respectively, supplementing the 406 MWh/year generated by PATs. It should be noted that PATs consistently have the lowest cost of electricity (LCOE), confirming their economic viability and efficiency across different scenarios, even after accounting for reductions in alternative energy sources and grid infrastructure costs. [ABSTRACT FROM AUTHOR]

The semi and fully continuous production of monoclonal antibodies (mAbs) has been gaining traction as a lower cost, and efficient production of mAbs to broaden patient access. To be truly flexible and adaptive to process demands, the industry has lacked sufficient advanced control strategies. The variation of the upstream product concentration typically cannot be handled by the downstream capture step, which is configured for a constant feed concentration and fixed binding capacity. This inflexibility leads to losses of efficiency and product yield. This study shows that these challenges can be overcome by a novel advanced control strategy concept that includes dynamic control throughout a perfusion bioreactor, with cell retention by alternating tangential flow, integrated with simulated moving bed (SMB) multi‐column chromatography. The automation workflow and advanced control strategy were implemented through the use of a visual programming development environment. This enabled dynamic flow control across the upstream and downstream process integrated with a dynamic column loading of the SMB. A sensor prototype, based on continuous biolayer interferometry measurements was applied to detect mAb breakthrough within the last column flow‐through to manage column switching. This novel approach provided higher specificity and lower background signal compared to commonly used spectroscopy methods, resulting in an optimized resin utilization while simultaneously avoiding product loss. The dynamic loading was found to provide a twofold increase of the mAb concentration in the eluate compared to a conservative approach with a predefined recipe with similar impurity removal. This concept shows that advanced control strategies can lead to significant process efficiency and yield improvement. [ABSTRACT FROM AUTHOR]

In the magazine's previous issue, I tried to emphasize the symbols of rebirth in ancient Egyptian and Vedic cultures, mentioning the magical role of the animal skin and its textile substitutes as a protective placenta for the soul. These elements, with deep historical roots, are also present in traditional Romanian culture. The heavy fur and the delicate apple blossom once marked the boundary between the Cosmos and Chaos in ancient times. While the fur served the practical role of preserving the wearer in the underworld and the magical role of protecting the soul undergoing initiation in Chaos/Desolation, the apple blossom transcended the tangible world, existing outside of it in the boundless space of all possibilities, yet without physical form. Despite its apparent fragility, it has endured for several thousand years. [ABSTRACT FROM AUTHOR]

BACKGROUND: Intensified ethanol fermentation produces higher ethanol concentrations while reducing water and energy requirements. Nevertheless, the inhibitory and detrimental effect of the cellular stress barriers in this process further complicates the nonlinear dynamic relationship between the variables that directly reflect the fermentation quality. These key variables are hard to measure in real time and therefore cannot be directly controlled. RESULTS: This work presents the development of a soft sensor that predicts in real time the ethanol and substrate concentrations of an intensified fermentation. The soft sensor uses feedforward neural networks (FNNs) with easily measurable process analytical technology (PAT) tools. The application of advanced PAT tools such as redox potential and capacitance, in addition to temperature and pH are explored as input variables. The complex kinetic relationship between the studied variables was captured with FNN architectures with a single hidden layer and between 95 and 175 hidden neurons for the different cases studied. Acceptable predictions are achieved for the concentration of ethanol (RMSE = 9.5 and R2 = 0.97) and substrate (RMSE = 17.02 and R2 = 0.92). CONCLUSIONS: The results confirm that the proposed soft sensor can accurately predict the ethanol and substrate concentrations. Collectively, capacitance, redox potential, temperature and pH provide a powerful platform of PAT tools that can directly infer key variables showing the fermentation quality in real time. This study provides a significant step towards the systematic development of a reliable soft sensor with integration of advanced PAT tools. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Degumming is an oil refinement process in which the naturally occurring phospholipids in crude vegetable oils are removed. Enzymatic degumming results in higher oil yield and more cost-efficient processing compared to traditional degumming processes using only water or acid. Phospholipase C hydrolyses phospholipids into diglycerides and phosphate groups during degumming. The diglyceride content can therefore be considered a good indicator of the state of the enzymatic reaction. This study investigates the use of near-infrared (NIR) spectroscopy and chemometrics to monitor the degumming process by quantifying diglycerides in soybean oil in both off-line and on-line settings. Fifteen enzymatic degumming lab scale batches originating from a definitive screening design (with varying water, acid, and enzyme dosages) were investigated with the aim to develop a NIR spectroscopy prediction method. By applying tailored preprocessing and variable selection methods, the diglyceride content can be predicted with a root mean square error of prediction of 0.06% (w/w) for the off-line set-up and 0.07% (w/w) for the on-line set-up. The results show that the diglyceride content is a good indicator of the enzyme performance and that NIR spectroscopy is a suitable analytical technique for robust real-time diglyceride quantification. Graphical abstract This is a visual representation of the abstract. [ABSTRACT FROM AUTHOR]

The aim of this study was to probe an unexpected relationship between the ice nucleation temperature (T IN), process efficiency and product attributes in a controlled ice nucleation (CIN) lyophilization process. An amorphous product was lyophilized with (CIN-5 °C, CIN-7 °C or CIN-10 °C) or without (NOCIN) control of ice nucleation. Process parameters and product attributes were monitored and compared using a series of advanced in-line and off-line process analytical technology (PAT) tools. Unexpectedly, an indirect relationship was observed between T IN and primary drying efficiency for the CIN processes. Further, the CIN-5 °C process was associated with higher product resistance to mass flow than corresponding CIN-7 °C and CIN-10 °C processes. Surprisingly, the air voids in some NOCIN products were larger than CIN-5 °C products but comparable to CIN-7 °C. Heat flux analysis revealed an indirect relationship between T IN and the minimum hold time required to complete solidification. The heat flux analysis also revealed all products underwent complete solidification prior to primary drying. The order of homogeneity in water activity of the products was CIN-5 °C ≥NOCIN>CIN-7 °C. The higher homogeneity in water activity of CIN-5 °C than corresponding CIN-7 °C processes indicated that the lower process efficiency of CIN-5 °C could not be attributed to unsuccessful induction of ice nucleation during CIN-5 °C. High resolution micro-CT imaging and Artificial Intelligence Image analysis revealed cake wall deformation in CIN-7 °C and NOCIN products but not in CIN-5 °C. In addition, NOCIN products had bimodal distribution in air voids with median size range of 4–5 µm and 151.9–309 µm, respectively, hence the lower process efficiency of NOCIN despite the higher D90. Thus, the observed relationship between T IN and process efficiency may be attributed to microstructural changes post freezing. This hypothesis was corroborated by visible macroscopic cake collapse in NOCIN products but not in CIN products after lyophilization at a higher shelf temperature. In conclusion, the advantages of controlling the ice nucleation temperature of a lyophilization process may only be attained through a robust process design that takes into consideration the primary and secondary drying process parameters. Further, combined use of advanced in-line and off-line PAT tools for process and product characterization may hasten the at scale adoption of advance techniques such as CIN. [ABSTRACT FROM AUTHOR]

Abstract Genetically modified maize DP202216 was developed to confer tolerance to glufosinate‐ammonium‐containing herbicides and to provide an opportunity for yield enhancement under field conditions. These properties were achieved by introducing the mo‐pat and zmm28 expression cassettes. The molecular characterisation data and bioinformatic analyses do not identify issues requiring food/feed safety assessment. None of the identified differences in the agronomic/phenotypic and compositional characteristics tested between maize DP202216 and its comparator needs further assessment, except for the levels of stearic acid (C18:0), which do not raise nutritional and safety concerns. The GMO Panel does not identify safety concerns regarding the toxicity and allergenicity of the PAT and ZMM28 proteins as expressed in maize DP202216, and finds no evidence that the genetic modification would change the overall allergenicity of maize DP202216. In the context of this application, the consumption of food and feed from maize DP202216 does not represent a nutritional concern in humans and animals. The GMO Panel concludes that maize DP202216 is as safe as the comparator and non‐GM reference varieties tested, and no post‐market monitoring of food/feed is considered necessary. In the case of accidental release of viable maize DP202216 grains into the environment, this would not raise environmental safety concerns. The post‐market environmental monitoring plan and reporting intervals are in line with the intended uses of maize DP202216. The GMO Panel concludes that maize DP202216 is as safe as its comparator and the tested non‐GM reference varieties with respect to potential effects on human and animal health and the environment.

Abstract Process Analytical Technologies (PATs) are taking a key role in the run for automatization in the biopharmaceutical industry. Spectroscopic methods such as Raman spectroscopy or mid‐infrared (MIR) spectroscopy are getting more recognition in the recent years for inline monitoring of bioprocesses due to their ability to measure various molecules simultaneously. However, their dependency on laborious model calibration making them a challenge to implement. In this study, a novel one‐point calibration that requires a single reference point prior to the inline monitoring of glucose and lactate in bioprocesses with MIR spectroscopy is assessed with 22 mammalian cell perfusion (PER) processes in two different scales and four different products. Concentrations are predicted over all PERs runs with a root mean square error (RMSE) of 0.29 g/L for glucose and 0.24 g/L for lactate, respectively. For comparison conventional partial least square regression (PLSR) models were used and trained with spectroscopic data from six bioreactor runs in two different scales and three products. The general accuracy of those models (RMSE of 0.41 g/L for glucose and 0.16 g/L for lactate) are in the range of the accuracy of the one‐point calibration. This shows the potential of the one‐point calibration as an approach making spectroscopy more accessible for bioprocess development.

Background: This work performs a literature review of photoacoustic imaging (PAI) in dentistry and discusses the development of PAI in relation to oral health. Methods: A search method was used to locate papers published between 2011 and 2023 in Google Scholar and PubMed databases, and 25 studies were selected. Reports on PAI in dentistry were included. Articles not written in English or whose full text could not be accessed were excluded. The remaining publications were checked and evaluated to determine whether they contain supportive materials for PAI in dentistry. Results: The majority of articles about PAI in dentistry are associated with caries studies. Photoacoustic microscopy is the most commonly utilized PAI system. PAI studies generally focus on ex-vivo investigations using extracted human teeth. The acoustic signal obtained from carious teeth is greater than that obtained from normal teeth. In addition to imaging oral soft tissues from animal models and the periodontal pocket depth in human volunteers, PAI is applied to evaluate dental implants and oral biofilms. Conclusion: There have been numerous investigation on PAI in dentistry, but it is not yet applicable in dental practice. In the future, PAI studies are expected to contribute to the invention of an alternative non-ionizing imaging technology that is comfortable for patients, user friendly, and capable of providing reliable information at a reasonable cost.

Spaceborne data can be seamlessly handled using a laser-communication system that enables super-high-speed data transfers, greater than or equal to 1 Gbps, and provides size, weight, and power (SWaP) efficiencies at low costs. Laser-communication systems have garnered attention owing to their ability to enhance SWaP efficiencies, and thus they may complement or potentially replace traditional radio frequency (RF) systems in future space networks. Here, we propose a novel space-to-space laser communication system, called very-high-speed inter-satellite link system using infrared optical terminal and nanosatellite (VISION). This study aims to establish and validate laser-crosslink systems and advanced space technologies using two 6U nanosatellites in formation flying. The payload is a laser-communication terminal (LCT) containing a deployable space telescope. The LCT shares beam paths for communication as well as pointing, acquisition, and tracking (PAT) with a single aperture, thereby providing feedback control for the PAT and help mitigate steady-state beam pointing errors. The nanosatellites include a precise formation-flying guidance, navigation, and control system with an S-band RF crosslink and propulsion system. Each nanosatellite is equipped with a propulsion system that can change its inter-satellite ranges rapidly and accurately based on the mission operation scenarios. LCT payload prototypes are constructed, and the PAT system is evaluated using a testbed. Additionally, the components of the nanosatellite bus are electrically integrated for flatsat testing. The proposed laser-crosslink systems are anticipated to contribute to the establishment of high-speed and secure space-to-space networks at low costs in the forthcoming years. • Proposed a novel space-to-space laser communication system called VISION. • Preliminary design of laser-crosslink and advanced space optics systems with two 6U nanosatellites. • Nanosatellites in formation flying included control and propulsion systems. • Constructed a laser-communication terminal payload prototype and evaluated PAT. • VISION system enables development of low-cost super-high-speed space networks. [ABSTRACT FROM AUTHOR]

Biologics manufacturing is increasingly moving toward intensified processes that require novel control strategies in order to achieve higher titers in shorter periods of time compared to traditional fed-batch cultures. In order to implement these strategies for intensified processes, continuous process monitoring is often required. To this end, inline Raman spectroscopy was used to develop partial least squares models to monitor changes in residual concentrations of glucose, phenylalanine and methionine during the culture of five different glutamine synthetase piggyBac® Chinese hamster ovary clones cultured using an intensified high inoculation density fed-batch platform process. Continuous monitoring of residual metabolite concentrations facilitated automated feed-rate adjustment of three supplemental feeds to maintain glucose, phenylalanine, and methionine at desired setpoints, while maintaining other nutrient concentrations at acceptable levels across all clones cultured on the high inoculation density platform process. Furthermore, all clones cultured on this process achieved high viable cell concentrations over the course of culture, indicating no detrimental impacts from the proposed feeding strategy. Finally, the automated control strategy sustained cultures inoculated at high cell densities to achieve product concentrations between 5 and 8.3 g/L over the course of 12 days of culture. [ABSTRACT FROM AUTHOR]

An efficient monitoring and control strategy is the basis for a reliable production process. Conventional optical density (OD) measurements involve superpositions of light absorption and scattering, and the results are only given in arbitrary units. In contrast, photon density wave (PDW) spectroscopy is a dilution‐free method that allows independent quantification of both effects with defined units. For the first time, PDW spectroscopy was evaluated as a novel optical process analytical technology tool for real‐time monitoring of biomass formation in Escherichia coli high‐cell‐density fed‐batch cultivations. Inline PDW measurements were compared to a commercially available inline turbidity probe and with offline measurements of OD and cell dry weight (CDW). An accurate correlation of the reduced PDW scattering coefficient µs′ with CDW was observed in the range of 5–69 g L−1 (R2 = 0.98). The growth rates calculated based on µs′ were comparable to the rates determined with all reference methods. Furthermore, quantification of the reduced PDW scattering coefficient µs′ as a function of the absorption coefficient µa allowed direct detection of unintended process trends caused by overfeeding and subsequent acetate accumulation. Inline PDW spectroscopy can contribute to more robust bioprocess monitoring and consequently improved process performance. [ABSTRACT FROM AUTHOR]

In this work, the performance of two fast chemical imaging techniques, Raman and near-infrared (NIR) imaging is compared by utilizing these methods to predict the rate of drug release from sustained-release tablets. Sustained release is provided by adding hydroxypropyl methylcellulose (HPMC), as its concentration and particle size determine the dissolution rate of the drug. The chemical images were processed using classical least squares; afterwards, a convolutional neural network was applied to extract information regarding the particle size of HPMC. The chemical images were reduced to an average HPMC concentration and a predicted particle size value; these were used as inputs in an artificial neural network with a single hidden layer to predict the dissolution profile of the tablets. Both NIR and Raman imaging yielded accurate predictions. As the instrumentation of NIR imaging allows faster measurements than Raman imaging, this technique is a better candidate for implementing a real-time technique. The introduction of chemical imaging in the routine quality control of pharmaceutical products would profoundly change quality assurance in the pharmaceutical industry. [ABSTRACT FROM AUTHOR]

The need for electrical energy increases yearly; this study aims to analyze the feasibility of constructing a pico-hydro power plant in remote villages that do not yet have a power grid using a centrifugal pump as a turbine. The results of the analysis of technical aspects get information that there are about 25 houses that require electrical energy. The electrical power requirement of each house is about 100 W, which is used for lighting with five energy-efficient LED lamps of 20 W each. After adding street lighting and power losses to the network of about 500 W, the total electrical power needed is around 3000 W. A pico-hydro power generation system can meet the 3000 W power with a potential power of 5 kW and an effective turbine power of 3.51 kW. The water discharge requirement for the turbine is 104 liters/s, the turbine rotational speed is 543 rpm, the generator rotation speed is 1500 rpm, the specific speed is 133, the PAT runner diameter is 8 inches, and the distance from the power plant to the resident's house is 150 m, network losses 8 V, and the household electricity voltage is 210.45 V. The results of the technical aspect analysis show that the pico-hydro power plant is considered feasible to be built. The results of this analysis are the initial stage of feasibility study activities and can be continued with analysis from other aspects such as financial, economic, social, and environmental aspects. [ABSTRACT FROM AUTHOR]

This work performs a literature review of photoacoustic imaging (PAI) in dentistry and discusses the development of PAI in relation to oral health. A search method was used to locate papers published between 2011 and 2023 in Google Scholar and PubMed databases, and 25 studies were selected. Reports on PAI in dentistry were included. Articles not written in English or whose full text could not be accessed were excluded. The remaining publications were checked and evaluated to determine whether they contain supportive materials for PAI in dentistry. The majority of articles about PAI in dentistry are associated with caries studies. Photoacoustic microscopy is the most commonly utilized PAI system. PAI studies generally focus on ex-vivo investigations using extracted human teeth. The acoustic signal obtained from carious teeth is greater than that obtained from normal teeth. In addition to imaging oral soft tissues from animal models and the periodontal pocket depth in human volunteers, PAI is applied to evaluate dental implants and oral biofilms. There have been numerous investigation on PAI in dentistry, but it is not yet applicable in dental practice. In the future, PAI studies are expected to contribute to the invention of an alternative non-ionizing imaging technology that is comfortable for patients, user friendly, and capable of providing reliable information at a reasonable cost. [ABSTRACT FROM AUTHOR]

3D printing technology can be used to develop individualized medicines in hospitals and pharmacies, allowing a high degree of personalization and the possibility to adjust the dose of the API based on the quantity of material extruded. The main goal of incorporating this technology is to have a stock of API-load print cartridges that could be used at different storage times and for different patients. However, it is necessary to study the extrudability, stability, and buildability of these print cartridges during storage time. A paste-like formulation containing hydrochlorothiazide as a model drug was prepared and distributed in five print cartridges, each of which was studied for different storage times (0 h–72 h) and conditions, for repeated use on different days. For each print cartridge, an extrudability analysis was performed, and subsequently, 100 unit forms of 10 mg hydrochlorothiazide were printed. Finally, various dosage units containing different doses were printed, taking into account the optimized printing parameters based on the results of the extrudability analysis carried out previously. An appropriate methodology for the rapid development of appropriate SSE 3DP inks for pediatrics was established and evaluated. The extrudability analysis and several parameters allowed the detection of changes in the mechanical behavior of the printing inks, the pressure interval of the steady flow, and the selection of the volume of ink to be extruded to obtain each of the required doses. The print cartridges were stable for up to 72 h after processing, and orodispersible printlets containing 6 mg to 24 mg of hydrochlorothiazide can be produced using the same print cartridge and during the same printing process with guaranteed content and chemical stability. The proposed workflow for the development of new printing inks containing APIs will allow the optimization of feedstock material and human resources in pharmacy or hospital pharmacy services, thus speeding up their development and reducing costs. [ABSTRACT FROM AUTHOR]

Pointing, acquisition, and tracking (PAT) is a major technical challenge of laser inter-satellite links (ISLs). For the fast establishment of laser link and the maximization of communication time, it is of importance to minimize the acquisition time. Satellite vibrations affect the PAT procedure adversely, and thus serve to increase the acquisition time. In this paper, we investigate through theoretical analysis the average acquisition time of laser ISLs in the presence of satellite vibrations. The analytic expression about the time taken from the beginning of spiral scan to the acquisition of the scan beam is provided in the presence of the pointing errors caused by vibrations. We also derive the optimum beam divergence angle for the acquisition time. The analyses are validated by Monte-Carlo computer simulations and a proof-of-concept experiment. The results show that the acquisition time can be minimized by adjusting the beam divergence angle adaptively to the link conditions.

The use of nondestructive techniques that can guarantee in situ monitoring of the quality of food products during drying processes can promote improvements in industrial processes. In this context, digital imaging and near infrared spectroscopy can play an important role. Red beet moisture content, betalain content, shrinkage, and color were measured during drying. The digital images showed changes in color, which intensified with increasing temperature and correlated with betalain content through multivariate linear regression (R2 of 0.90). In addition, sample shrinkage was identified by digital images. The volumetric shrinkage increased proportionally to the drying air temperature, with a shrinkage of 85.4 ± 0.3% at 70 °C. Spectral data were obtained by a low-cost portable near infrared spectrometer. Partial least square regression was used to predict the product moisture content ( R P 2 = 0.89 ; RMSEP = 0.79 %) and total betalain content ( R P 2 = 0.79 ; RMSEP = 0.30 m g g d. b.) during drying. These tools can be used for the in situ control of red beet drying. [ABSTRACT FROM AUTHOR]

In this study, we developed a method to build Raman calibration models without culture data for cell culture monitoring. First, Raman spectra were collected and then analyzed for the signals of all the mentioned analytes: glucose, lactate, glutamine, glutamate, ammonia, antibody, viable cells, media, and feed agent. Using these spectral data, the specific peak positions and intensities for each factor were detected. Next, according to the design of the experiment method, samples were prepared by mixing the above-mentioned factors. Raman spectra of these samples were collected and were used to build calibration models. Several combinations of spectral pretreatments and wavenumber regions were compared to optimize the calibration model for cell culture monitoring without culture data. The accuracy of the developed calibration model was evaluated by performing actual cell culture and fitting the in-line measured spectra to the developed calibration model. As a result, the calibration model achieved sufficiently good accuracy for the three components, glucose, lactate, and antibody (root mean square errors of prediction, or RMSEP = 0.23, 0.29, and 0.20 g/L, respectively). This study has presented innovative results in developing a culture monitoring method without using culture data, while using a basic conventional method of investigating the Raman spectra of each component in the culture media and then utilizing a design of experiment approach. Graphical Abstract This is a visual representation of the abstract. [ABSTRACT FROM AUTHOR]

Spatially offset Raman spectroscopy (SORS) is a subset of Raman spectroscopy devised for probing subsurface compositions in non-homogenous media. An example of such media is the wet filter cake during pharmaceutical drying. This non-homogeneity poses a challenge for process monitoring as it could render the determined solvent content during drying, and the end point, inaccurate. In this study, a SORS probe was developed for the monitoring of pharmaceutical drying. The probe includes a 45° illumination point and 0–5 mm equidistant collection offsets. Using the SORS probe, solvent signal detection through variable thicknesses of dry paracetamol was examined. The solvent content during the drying of paracetamol in anisole was then monitored using the SORS probe. Partial least squares regression (PLSR) analysis was applied to evaluate the performance of offset configurations in monitoring the solvent content during drying. The results showed that the solvent signal is detected through thicknesses beyond 6 mm of paracetamol from the larger offsets of 4–5 mm. A more accurate prediction of the solvent content was obtained from larger offsets. PLSR models using offset spectra showed a decrease in estimation error up to 50 % compared to backscattering spectra, with a further decrease upon using standard normal variate pre-processing. This suggests that SORS could offer improved monitoring of pharmaceutical drying processes. • A spatially offset Raman spectroscopy probe was developed for in-line process monitoring. • SORS probe characteristics include 45° illumination and 0–5 mm offsets. • Spatial offsets of 4–5 mm could probe samples up to a depth of 6 mm. • Partial least squares regression analysis of offset spectra showed a decreased estimation error up to 50 % compared to backscattering spectra. • Spatially offset Raman spectroscopy offers improved monitoring of solvent content during pharmaceutical drying. [ABSTRACT FROM AUTHOR]

Background/aim: Allergic rhinitis (AR) is characterized by chronic inflammation of the nasal mucosa. Under the influence of exogenous factors - allergens, reactive oxygen species (ROS) are released during cellular metabolism. They induce a series of pathological changes in the mucosa. Oxidative stress is а result of an imbalance between the production of ROS and the ability to neutralize them. The aim of this study is to compare the levels of oxidative stress between healthy children and children with allergic rhinitis. Material and methods: A total number of 60 children were included (30 healthy children and 30 children with AR). The oxidative stress index was determined by using the FRAS 5 (Free Radical Analytical System) Bravo system. Demographic characteristics, medical history, children's living conditions and eating habits were obtained from the questionnaire. Anthropometric measurements and the absolute number of eosinophils in the peripheral smear were performed on each child. Results: This study showed high oxidative stress index and a significantly higher value of the absolute number of eosinophils in the peripheral smear in children with AR in comparison to healthy children (p<0.05). The group of children with AR had more atopic characteristics and was more exposed to passive smoking than healthy children. Conclusion: Compared to healthy children, children with AR have a high index of oxidative stress, despite of the very high mean value of the concentration of water-soluble antioxidants in serum (PAT test) in the group of children with AR. [ABSTRACT FROM AUTHOR]

The world’s water infrastructures suffer from inefficiencies, such as high energy consumption and water losses due to inadequate management practices and feeble pressure regulation, leading to frequent water and energy losses. This strains vital water and energy resources, especially in the face of the worsening challenges of climate change and population growth. A novel method is presented that integrates micro-hydropower plants, with pumps as turbines (PATs), in the water network in the city of Funchal. Sensitivity analyses evaluated the microgrid’s response to variations in the cost of energy components, showing favorable outcomes with positive net present value (NPV). PV solar and micro-wind turbines installed exclusively at the selected PRV sites within the Funchal hydro grid generate a combined 153 and 55 MWh/year, respectively, supplementing the 406 MWh/year generated by PATs. It should be noted that PATs consistently have the lowest cost of electricity (LCOE), confirming their economic viability and efficiency across different scenarios, even after accounting for reductions in alternative energy sources and grid infrastructure costs.

The pharmaceutical industry has begun incorporating continuous manufacturing technology in synthetic routes toward active pharmaceutical ingredients (APIs). The development of smart manufacturing routes can be accelerated by utilizing digitalization, process analytical technology (PAT), and data-rich experimentation from an early stage. Here, we present the key aspects of implementing automated flow chemistry reactor platforms with real-time process analytics. Based on our experiences in this field, we aim to highlight the potential of these platforms to conduct self-optimization, automated reaction model building, dynamic experiments and to implement advanced process control strategies

Intervals of low-quality photoplethysmogram (PPG) signals might lead to significant inaccuracies in estimation of pulse arrival time (PAT) during polysomnography (PSG) studies. While PSG is considered to be a "gold standard" test for diagnosing obstructive sleep apnea (OSA), it also enables tracking apnea-related nocturnal blood pressure fluctuations correlated with PAT. Since the electrocardiogram (ECG) is recorded synchronously with the PPG during PSG, it makes sense to use the ECG signal for PPG signal-quality assessment. (1) Objective: to develop a PPG signal-quality assessment algorithm for robust PAT estimation, and investigate the influence of signal quality on PAT during various sleep stages and events such as OSA. (2) Approach: the proposed algorithm uses R and T waves from the ECG to determine approximate locations of PPG pulse onsets. The MESA database of 2055 PSG recordings was used for this study. (3) Results: the proportions of high-quality PPG were significantly lower in apnea-related oxygen desaturation (matched-pairs r c = 0.88 and r c = 0.97, compared to OSA and hypopnea, respectively, when p < 0.001) and arousal ( r c = 0.93 and r c = 0.98, when p < 0.001) than in apnea events. The significantly large effect size of interquartile ranges of PAT distributions was between low- and high-quality PPG (p < 0.001, r c = 0.98), and regular and irregular pulse waves (p < 0.001, r c = 0.74), whereas a lower quality of the PPG signal was found to be associated with a higher interquartile range of PAT across all subjects. Suggested PPG signal quality-based PAT evaluation reduced deviations (e.g., r c = 0.97, r c = 0.97, r c = 0.99 in hypopnea, oxygen desaturation, and arousal stages, respectively, when p < 0.001) and allowed obtaining statistically larger differences between different sleep stages and events. (4) Significance: the implemented algorithm has the potential to increase the robustness of PAT estimation in PSG studies related to nocturnal blood pressure monitoring. [ABSTRACT FROM AUTHOR]

Monitoring the protein concentration and buffer composition during the Ultrafiltration/Diafiltration (UF/DF) step enables the further automation of biopharmaceutical production and supports Real-time Release Testing (RTRT). Previously, in-line Ultraviolet (UV) and Infrared (IR) measurements have been used to successfully monitor the protein concentration over a large range. The progress of the diafiltration step has been monitored with density measurements and Infrared Spectroscopy (IR). Raman spectroscopy is capable of measuring both the protein and excipient concentration while being more robust and suitable for production measurements in comparison to Infrared Spectroscopy (IR). Regardless of the spectroscopic sensor used, the low concentration of excipients poses a challenge for the sensors. By combining sensor measurements with a semi-mechanistic model through an Extended Kalman Filter (EKF), the sensitivity to determine the progress of the diafiltration can be improved. In this study, Raman measurements are combined with an EKF for three case studies. The advantages of Kalman-filtered Raman measurements for excipient monitoring are shown in comparison to density measurements. Furthermore, Raman measurements showed a higher measurement speed in comparison to Variable Pathlength (VP) UV measurement at the trade-off of a slightly worse prediction accuracy for the protein concentration. However, the Raman-based protein concentration measurements relied mostly on an increase in the background signal during the process and not on proteinaceous features, which could pose a challenge due to the potential influence of batch variability on the background signal. Overall, the combination of Raman spectroscopy and EKF is a promising tool for monitoring the UF/DF step and enables process automation by using adaptive process control. [ABSTRACT FROM AUTHOR]

Quality by Design (QbD) is one of the most important tools for the implementation of Process Analytical Technology (PAT) in biopharmaceutical production. For optimal characterization of a monoclonal antibody (mAb) upstream process a stepwise approach was implemented. The upstream was divided into three process stages, namely inoculum expansion, production, and primary recovery, which were investigated individually. This approach enables analysis of process parameters and associated intermediate quality attributes as well as systematic knowledge transfer to subsequent process steps. Following previous research, this study focuses on the primary recovery of the mAb and thereby marks the final step toward a holistic characterization of the upstream process. Based on gained knowledge during the production process evaluation, the cell viability and density were determined as critical parameters for the primary recovery. Directed cell viability adjustment was achieved using cytotoxic camptothecin in a novel protocol. Additionally, the cell separation method was added to the Design of Experiments (DoE) as a qualitative factor and varied between filtration and centrifugation. To assess the quality attributes after cell separation, the bioactivity of the mAb was analyzed using a cell‐based assay and the purity of the supernatant was evaluated by measurement of process related impurities (host cell protein proportion, residual DNA). Multivariate data analysis of the compiled data confirmed the hypothesis that the upstream process has no significant influence on the bioactivity of the mAb. Therefore, process control must be tuned towards high mAb titers and purity after the primary recovery, enabling optimal downstream processing of the product. To minimize amounts of host cell proteins and residual DNA the cell viability should be maintained above 85% and the cell density should be controlled around 15 × 106 cells/ml during the cell removal. Thereby, this study shows the importance of QbD for the characterization of the primary recovery of mAbs and highlights the useful implementation of the stepwise approach over subsequent process stages. [ABSTRACT FROM AUTHOR]