A Review of In Vitro and In Silico Swallowing Simulators: Design and Applications.

Swallowing is a primary and complex behaviour that transports food and drink from the oral cavity, through the pharynx and oesophagus, into the stomach at an appropriate rate and speed. To understand this sophisticated behaviour, a tremendous amount of research has been carried out by utilising the in vivo approach, which is often challenging to perform, poses a risk to the subjects if interventions are undertaken and are seldom able to control for confounding factors. In contrast, in silico (computational) and in vitro (instrumental) methods offer an alternate insight into the process of the human swallowing system. However, the appropriateness of the design and application of these methods have not been formally evaluated. The purpose of this review is to investigate and evaluate the state of the art of in vitro and in silico swallowing simulators, focusing on the evaluation of their mechanical or computational designs in comparison to the corresponding swallowing mechanisms during various phases of swallowing (oral phase, pharyngeal phase and esophageal phase). Additionally, the potential of the simulators is also discussed in various areas of applications, including the study of swallowing impairments, swallowing medications, food process design and dysphagia management. We also address current limitations and recommendations for the future development of existing simulators.

Biomimetic Closed-Loop Control of a Novel Soft Gastric Simulator Toward Emulating Antral Contraction Waves.

Soft gastric simulators are in vitro biomimetic modules that can reproduce the antral contraction waves (ACWs). Along with providing information concerning stomach contents, stomach simulators enable experts to evaluate the digestion process of foods and drugs. Traditionally, open-loop control approaches were implemented on stomach simulators to produce ACWs. Constructing a closed-loop control system is essential to improve the simulator's ability to imitate ACWs in additional scenarios and avoid constant tuning. Closed-loop control can enhance stomach simulators in accuracy, responding to various food and drug contents, timing, and unknown disturbances. In this article, a new generation of anatomically realistic soft pneumatic gastric simulators is designed and fabricated. The presented simulator represents the antrum, the lower portion of the stomach where ACWs occur. It is equipped with a real-time feedback system to implement diverse closed-loop controllers on demand. All the details of the physical design, fabrication, and assembly process are discussed. Also, the measures taken for the mechatronics design and sensory system are highlighted in this article. Through several implementation algorithms and techniques, three closed-loop controllers, including model-based and model-free schemes are designed and successfully applied on the presented simulator to imitate ACWs. All the experimental outcomes are carefully analyzed and compared against the biological counterparts. It is demonstrated that the presented simulator can serve as a reliable tool and method to scrutinize digestion and promote novel technologies around the human stomach and the digestion process. This research methodology can also be utilized to develop other biomimetic and bioinspired applications.

A Chewing Study of Abuse-Deterrent Tablets Containing Polyethylene Oxide Using a Robotic Simulator.

Abuse-deterrent formulations (ADFs) refer to formulation technologies aiming to deter the abuse of prescription drugs by making the dosage forms difficult to manipulate or extract the opioids. Assessments are required to evaluate the performance of the drugs through different routes including injection, ingestion, and insufflation and also when the drugs are manipulated. Chewing is the easiest and most convenient way to manipulate the drugs and deserves investigation. Chewing is one of the most complex bioprocesses, where the ingested materials are subject to periodic tooth crushing, mixed through the tongue, and lubricated and softened by the saliva. Inter- and intra-subject variations in chewing patterns may result in different chewing performances. The purpose of this study is to use a chewing simulator to assess the deterrent properties of tablets made of polyethylene oxide (PEO). The simulator can mimic human molar grinding with variable chewing parameters including molar trajectory, chewing frequency, and saliva flow rate. To investigate the effects of these parameters, the sizes of the chewed tablet particles and the chewing force were measured to evaluate the chewing performance. Thirty-four out of forty tablets were broken into pieces. The results suggested that the simulator can chew the tablets into smaller particles and that the molar trajectory and saliva flow rate had significant effect on reducing the size of the particles by analysis of variance (ANOVA) while the effect of chewing frequency was not clear. Additionally, chewing force can work as an indicator of the chewing performance.

Chemical and microbiological characterization of two traditional Mongolian high-fat dairy products produced in Xilin Gol, China.

Mongolian butter and Tude are traditional high-fat dairy products produced in Xilin Gol, China, which have unique chemical and microbiological characteristics. Mongolian Tude is made from Mongolian butter, dreg, and flour. In this study, the traditional manufacturing process of Mongolian butter and Tude was investigated for the first time. Mongolian butter was characterized by high-fat content (99.38 ± 0.63%) and high acidity (77.09 ± 52.91°T), whereas Mongolian Tude was considered a high-fat (21.45 ± 1.23%) and high-protein (8.28 ± 0.65%) dairy product obtained by butter, dreg, and flour. Mongolian butter and Tude were proven to be safe for human consumption in terms of benzopyrene content. In addition, Listeria monocytogenes, Staphylococcus aureus, Salmonella, coliforms, and aflatoxin M1 were not detected in the samples. Bacteria and molds were not isolated from Mongolian butter; in contrast, the total count of bacteria and molds in Mongolian Tude was within the range of 4.5 × 102 to 9.5 × 104 and 0 to 2.2 × 105, respectively. Moreover, Lactococcus (41.55%), Lactobacillus (11.05%), Zygosaccharomyces (40.20%), and Pichia (12.90%) were the predominant bacterial and fungal genera, and Lactobacillus helveticus (15.6%), Lactococcus raffinolactis (9.6%), Streptococcus salivarius (8.5%), Pantoea vagans (6.1%), Bacillus subtilis (4.2%), Kocuria rhizophila (3.5%), Acinetobacter johnsonii (3.5%), Zygosaccharomyces rouxii (46.2%), Pichia fermentans (14.7%), and Dipodascus geotrichum (11.7%) were the predominant species in the microbiota of Mongolian Tude. Thus, it can be stated that the microbiota of food products produced by different small families varied significantly. Collectively, the findings presented herein are the first report of chemical and microbiological characterization of products of geographical origin and highlight the need for standardization of manufacturing procedures of Mongolian butter and Tude in the future.

Conversion of Surface Residual Alkali to Solid Electrolyte to Enable Na-Ion Full Cells with Robust Interfaces.

The deposition of volatilized Na+ on the surface of the cathode during sintering results in the formation of surface residual alkali (NaOH/Na2 CO3 NaHCO3 ) in layered cathode materials, leading to serious interfacial reactions and performance degradation. This phenomenon is particularly evident in O3-NaNi0.4 Cu0.1 Mn0.4 Ti0.1 O2 (NCMT). In this study, a strategy is proposed to transform waste into treasure by converting residual alkali into a solid electrolyte. Mg(CH3 COO)2 and H3 PO4 are reacted with surface residual alkali to generate the solid electrolyte NaMgPO4 on the surface of NCMT, which can be labeled as NaMgPO4@NaNi0.4 Cu0.1 Mn0.4 Ti0.1 O2 -X (NMP@NCMT-X, where X indicates the different amounts of Mg2+ and PO4 3- ). NaMgPO4 acts as a special ionic conductivity channel on the surface to improve the kinetics of the electrode reactions, remarkably improving the rate capability of the modified cathode at a high current density in the half-cell. Additionally, NMP@NCMT-2 enables a reversible phase transition from the P3 to OP2 phase in the charge-discharge process above 4.2 V and achieves a high specific capacity of 157.3 mAh g-1 and outstanding capacity retention in the full cell. The strategy can effectively and reliably stabilize the interface and improve the performance of layered cathodes for Na-ion batteries (NIBs).

Manifold Learning Enables Interpretable Analysis of Raman Spectra from Extracellular Vesicle and Other Mixtures.

Extracellular vesicles (EVs) have emerged as promising diagnostic and therapeutic candidates in many biomedical applications. However, EV research continues to rely heavily on in vitro cell cultures for EV production, where the exogenous EVs present in fetal bovine (FBS) or other required serum supplementation can be difficult to remove entirely. Despite this and other potential applications involving EV mixtures, there are currently no rapid, robust, inexpensive, and label-free methods for determining the relative concentrations of different EV subpopulations within a sample. In this study, we demonstrate that surface-enhanced Raman spectroscopy (SERS) can biochemically fingerprint fetal bovine serum-derived and bioreactor-produced EVs, and after applying a novel manifold learning technique to the acquired spectra, enables the quantitative detection of the relative amounts of different EV populations within an unknown sample. We first developed this method using known ratios of Rhodamine B to Rhodamine 6G, then using known ratios of FBS EVs to breast cancer EVs from a bioreactor culture. In addition to quantifying EV mixtures, the proposed deep learning architecture provides some knowledge discovery capabilities which we demonstrate by applying it to dynamic Raman spectra of a chemical milling process. This label-free characterization and analytical approach should translate well to other EV SERS applications, such as monitoring the integrity of semipermeable membranes within EV bioreactors, ensuring the quality or potency of diagnostic or therapeutic EVs, determining relative amounts of EVs produced in complex co-culture systems, as well as many Raman spectroscopy applications.

Determination of the microbial community of traditional Mongolian cheese by using culture-dependent and independent methods.

Mongolian cheese is not only a requisite source of food for the nomadic Mongolian but also follows a unique Mongolian dairy artisanal method of production, possessing high nutritional value and long shelf-life. In this study, the ancient technique for the production of Mongolian cheese was investigated. The nutritional value of Mongolian cheese was characterized by its high-protein content (30.13 ± 2.99%) and low-fat content (9.66 ± 3.36%). Lactobacillus, Lactococcus, and Dipodascus were the predominant bacterial and fungal genera, and Lactobacillus helveticus, Lactococcus piscium, and Dipodascus geotrichum were the predominant species in the Mongolian cheese. The microbiota of products from different cheese factories varies significantly. The high-temperature (85°C-90°C) kneading of coagulated curds could eliminate most of the thermosensitive microorganisms for extending the shelf-life of cheese. The indigenous spore-forming microbes, which included yeasts, belonging to Pichia and Candida genera, and molds, belonging to Mucor and Penicillium genera, which originated from the surroundings during the process of cooling, drying, demolding, and vacuum packaging could survive and cause the package to swell and the cheese to grow mold. The investigation of production technology, nutrition, microbiota, and viable microbes related to shelf-life contributes to the protection of traditional technologies, extraction of highlights (nutritional profiles and curd scalding) for merchandise marketing, and standardization of Mongolian cheese production, including culture starters and aseptic technique.

Finite-Time Contraction Control of a Ring-Shaped Soft Pneumatic Actuator Mimicking Gastric Pathologic Motility Conditions.

Soft gastric simulators are the latest gastric models designed to imitate gastrointestinal (GI) functions in actual physiological conditions. They are used in in vitro tests for examining the drug and food behaviors in the GI tract. As the main motility function of the GI tract, the peristalsis can be altered in some gastric disorders, for example, by being delayed or accelerated. To simulate the stomach motility, a GI simulator must achieve a prescribed healthy or pathological peristalsis. This requires the simulator to be controlled in a closed loop. Unlike conventional controllers that stabilize a controlled plant asymptotically, a finite-time controller regulates state variables to their equilibrium points in a predetermined time interval. This article presents the design and implementation of a finite-time, model-based state feedback controller (based on the differential Riccati equation) on a soft robotic gastric simulator's actuators for the first time. We propose a mass-spring-damper model of a ring-shaped soft pneumatic actuator (RiSPA). RiSPA is a bellows-driven, elastomer-based actuator developed to reproduce motility functions of the lower part of the stomach (pyloric antrum). The proposed model is augmented by a new approach for modeling the soft tissues, where the moments of inertia of the system constituents are considered as time-varying functions. The finite-time controller is successfully applied on the RiSPA in numerical simulation and experimental implementation, and the results were thoroughly analyzed and discussed. Its accuracy and the ability to control in a predetermined time are highlighted in the tracking of peristalsis trajectory and contractive regulations.

SoRSS: A Soft Robot for Bio-Mimicking Stomach Anatomy and Motility.

A human stomach is an organ in the digestive system that breaks down foods by physiological digestion, including mechanical and chemical functions. The mechanical function is controlled by peristaltic waves generated over the stomach body, known as antral contraction waves (ACW). The stomach's physiological digestion is essential to sustain nutrition and health in humans. Replicating the digestion process in a robot provides a test environment as an alternative solution to in vivo testing, which is difficult in practice. Stomach robots made of rigid rods and metal cylinders are unrealistic replicas to contract and expand like biological examples. With soft robotics technology, it is possible to translate biological behavior into an engineering context. Soft robotics introduce potential methods to replicate peristaltic waves and achieve a soft-bodied stomach simulator. This work presents a soft robotic stomach simulator's (SoRSS) concept, design, and experimental validation. A pneumatic bellows actuation for linear elongation and a ring of bellows actuation for circular contraction are proposed first. Multi-ring actuators are then arranged to form an SoRSS that generates ACW and antral contracting pressure (ACP). The SoRSS satisfies the specification of human stomach anatomy and motility and finally undergoes experimental validation using videofluoroscopy with the outcomes presenting the ACW, ACP, and the digestion phases during the actuation process. Those are compared with other medical studies to validate SoRSS functionality.

Cascaded Deep Convolutional Neural Networks as Improved Methods of Preprocessing Raman Spectroscopy Data.

Machine learning has had a significant impact on the value of spectroscopic characterization tools, particularly in biomedical applications, due to its ability to detect latent patterns within complex spectral data. However, it often requires extensive data preprocessing, including baseline correction and denoising, which can lead to an unintentional bias during classification. To address this, we developed two deep learning methods capable of fully preprocessing raw Raman spectroscopy data without any human input. First, cascaded deep convolutional neural networks (CNN) based on either ResNet or U-Net architectures were trained on randomly generated spectra with augmented defects. Then, they were tested using simulated Raman spectra, surface-enhanced Raman spectroscopy (SERS) imaging of chemical species, low resolution Raman spectra of human bladder cancer tissue, and finally, classification of SERS spectra from human placental extracellular vesicles (EVs). Both approaches resulted in faster training and complete spectral preprocessing in a single step, with more speed, defect tolerance, and classification accuracy compared to conventional methods. These findings indicate that cascaded CNN preprocessing is ideal for biomedical Raman spectroscopy applications in which large numbers of heterogeneous spectra with diverse defects need to be automatically, rapidly, and reproducibly preprocessed.

Identifying FecB genotypes in the muscle from sheep breeds indigenous to Xilingol, and establishment of a TaqMan real-time PCR technique to distinguish FecB alleles.

The muscle from Xilingol indigenous sheep breeds are famous in China, and the FecB genotype in this population remains uncharacterized. In this study, SNPs in the FecB locus were investigated by pyrosequencing, and an optimized PCR-RFLP technique was generated to identify SNPs. In addition, an efficient technique for high-throughput identification of SNPs in FecB was optimized using TaqMan real-time PCR and breed-conservative primers and SNP-specific probes. By genotyping the FecB locus in the muscle of Xilingol indigenous sheep breeds using a novel TaqMan real-time PCR assay, our study has generated the groundwork for the authentication of Xilingol mutton based on the specific gene and the prolificacy-oriented breeding of Xilingol sheep using marker-assisted selection strategies in the future.

Classification of Preeclamptic Placental Extracellular Vesicles Using Femtosecond Laser Fabricated Nanoplasmonic Sensors.

Placental extracellular vesicles (EVs) play an essential role in pregnancy by protecting and transporting diverse biomolecules that aid in fetomaternal communication. However, in preeclampsia, they have also been implicated in contributing to disease progression. Despite their potential clinical value, current technologies cannot provide a rapid and effective means of differentiating between healthy and diseased placental EVs. To address this, a fabrication process called laser-induced nanostructuring of SERS-active thin films (LINST) was developed to produce scalable nanoplasmonic substrates that provide exceptional Raman signal enhancement and allow the biochemical fingerprinting of EVs. After validating the performance of LINST substrates with chemical standards, placental EVs from tissue explant cultures were characterized, demonstrating that preeclamptic and normotensive placental EVs have classifiably distinct Raman spectra following the application of advanced machine learning algorithms. Given the abundance of placental EVs in maternal circulation, these findings encourage immediate exploration of surface-enhanced Raman spectroscopy (SERS) of EVs as a promising method for preeclampsia liquid biopsies, while this novel fabrication process will provide a versatile and scalable substrate for many other SERS applications.

A Biologically Inspired Ring-Shaped Soft Pneumatic Actuator for Large Deformations.

Biomimicry of the stomach's peristaltic contractions can be challenging in the design, modeling, and control of a soft actuator. The mimicking of organ contractions advances our knowledge of the digestive system and analyzes the biological behavior by testing with a physical robot. This article proposes a ring-shaped soft pneumatic actuator (RiSPA) as a segment of the digestive tract. RiSPA is made of a ring frame with embedded bellow actuators that generate contractive motions. An embedded sensory system measures the contraction using range sensors. The kinematics and dynamics of RiSPA's contraction are modeled and simulated, while a state feedback algorithm is applied to them. The simulation results are validated experimentally by comparing the RiSPA measurements with desired applied signals. The proposed actuator provides controllable symmetrical and asymmetrical contractions analog to the human stomach. The results of RiSPA validate the prediction performance of the simulation and controller with applied sinusoidal signals as a peristaltic wave. RiSPA contractions can be applied to a broad range of applications, such as imitating the esophagus and intestine contractions.

A glutamic acid-based traceless linker to address challenging chemical protein syntheses.

Native chemical ligation (NCL) enables the total chemical synthesis of proteins. However, poor peptide segment solubility remains a frequently encountered challenge. Here we introduce a traceless linker that can be temporarily attached to Glu side chains to overcome this problem. This strategy employs a new tool, Fmoc-Glu(AlHx)-OH, which can be directly installed using standard Fmoc-based solid-phase peptide synthesis. The incorporated residue, Glu(AlHx), is stable to a wide range of chemical protein synthesis conditions and is removed through palladium-catalyzed transfer under aqueous conditions. General handling characteristics, such as efficient incorporation, stability and rapid removal were demonstrated through a model peptide modified with Glu(AlHx) and a Lys6 solubilizing tag. Glu(AlHx) was incorporated into a highly insoluble peptide segment during the total synthesis of the bacteriocin AS-48. This challenging peptide was successfully synthesized and folded, and it has comparable antimicrobial activity to the native AS-48. We anticipate widespread use of this easy-to-use, robust linker for the preparation of challenging synthetic peptides and proteins.

Space curvature-inspired nanoplasmonic sensor for breast cancer extracellular vesicle fingerprinting and machine learning classification.

Extracellular vesicles (EVs) are micro and nanoscale lipid-enclosed packages that have shown potential as liquid biopsy targets for cancer because their structure and contents reflect their cell of origin. However, progress towards the clinical applications of EVs has been hindered due to the low abundance of disease-specific EVs compared to EVs from healthy cells; such applications thus require highly sensitive and adaptable characterization tools. To address this obstacle, we designed and fabricated a novel space curvature-inspired surfaced-enhanced Raman spectroscopy (SERS) substrate and tested its capabilities using bioreactor-produced and size exclusion chromatography-purified breast cancer EVs of three different subtypes. Our findings demonstrate the platform's ability to effectively fingerprint and efficiently classify, for the first time, three distinct subtypes of breast cancer EVs following the application of machine learning algorithms on the acquired spectra. This platform and characterization approach will enhance the viability of EVs and nanoplasmonic sensors towards clinical utility for breast cancer and many other applications to improve human health.

Improved triplex real-time PCR with endogenous control for synchronous identification of DNA from chicken, duck, and goose meat.

The authentication and labeling of meat products, concerning origins and species, are key to fair trade and to protect consumer interests in the market. We developed an improved triplex real-time PCR approach to simultaneously identify chicken, duck, and goose DNA in meat, including an endogenous control to avoid false negatives. Our method specifically detected DNA from chicken, duck, and goose, and showed no cross-reaction with DNA extracted from other meat types. The detection limits of chicken, duck, and goose DNA were 0.001-0.00025 ng, 0.0025-0.0001 ng, and 0.001-0.00001 ng, respectively, and we were able to simultaneously identify DNA from two distinct origins using as little as 0.1% of total meat weight. Our newly generated triplex real-time PCR method with endogenous control exhibited high specificity, sensitivity, and efficiency for simultaneous identification of DNA from chicken, duck, and goose in meat.

A snapshot study of the microbial community dynamics in naturally fermented cow's milk.

Natural fermentation of milk is a prerequisite in the production of traditional dairy products and is considered a bioresource of fermentative microorganisms and probiotics. To understand the microbial dynamics during distinct fermentative phases, the roles of different microbes, and the relationship between bacteria and fungi, microbial community dynamics was investigated by culture-dependent and culture-independent approaches. Natural, static fermentation of milk induces the formation of the underlying curds and the superficial sour cream (Zuohe in the Mongolian language). From an overall perspective, viable LAB increased remarkably. Yeast showed an initial increase in their abundance (from 0 hr to 24 hr), which was followed by a decrease, and mold was detected at the later stages of fermentation (after 68 hr). The observed trends in microbiota variation suggest an antagonistic interaction between bacteria (LAB) and fungi (yeast and mold). The beneficial bacterial and fungal genus and species (e.g., Lactococcus, Streptococcus, Leuconostoc, Dipodascus, Lactococcus lacti, Dipodascus australiensis) are gradually increased in concentration, and the potentially detrimental microbial genus and species (e.g., Acinetobacter, Pseudomonas, Fusarium, Aspergillus, Mortierella, Acinetobacter johnsonii, Fusarium solani) decrease during the decline of bacterial and fungi diversity from natural fermentation. The study of microbial community dynamics could make a great contribution to understand the mechanism of natural fermentation of milk and the formation of curds and Zuohe, and to discover the potentially fermentative microbes for industrial starter cultures.

Comparative study of physicochemical composition and microbial community of Khoormog, Chigee, and Airag, traditionally fermented dairy products from Xilin Gol in China.

Due to their outstanding nutritional and functional properties, the traditionally fermented dairy products (TFDP) from camel, mare, and cow gained universal praise during their long history of production. In this study, the physicochemical composition and microbial communities of Khoormog, Chigee, and Airag, the TFDP from Xilin Gol in China, were investigated and compared. The physicochemical analysis revealed a higher content of total solid content, protein, and fat in Khoormog (12.5 ± 1.6%; 4.6 ± 0.7%; 4.4 ± 1.3%) compared to Chigee (7.8 ± 1.3%; 2.1 ± 0.2%; 0.8 ± 0.2%) and Airag (8.9 ± 0.7%; 3.7 ± 0.4%; 1.4 ± 0.5%). All three types of TFDP shared 41.2% of bacterial and 25.4% of fungal OTUs, and 95.34% of bacterial and 95.52% of fungal sequence reads. The bacterial and fungal community consisted of four phyla and five genera, and three phyla and seven genera, respectively. Lastly, Lactobacillus predominated in Khoormog, Chigee, and Airag at the genus level, while the dominant fungal genera varied among the samples. In conclusion, the microbial community structures of TFDP from camel, mare, and cow were not significantly different in a definite area (Xilingol region), and Khoormog, Chigee, and Airag bred the common "core microbiota".

SoGut: A Soft Robotic Gastric Simulator.

The human stomach breaks down and transports food by coordinated radial contractions of the gastric walls. The radial contractions periodically propagate through the stomach and constitute the peristaltic contractions, also called the gastric motility. The force, amplitude, and frequency of peristaltic contractions are relevant to massaging and transporting the food contents in the gastric lumen. However, existing gastric simulators have not faithfully replicated gastric motility. Herein, we report a soft robotic gastric simulator (SoGut) that emulates peristaltic contractions in an anatomically realistic way. SoGut incorporates an array of circular air chambers that generate radial contractions. The design and fabrication of SoGut leverages principles from the soft robotics field, which features compliance and adaptability. We studied the force and amplitude of the contractions when the lumen of SoGut was empty or filled with contents of different viscosity. We examined the contracting force using manometry. SoGut exhibited a similar range of contracting force as the human stomach reported in the literature. Besides, we investigated the amplitude of the contractions through videofluoroscopy where the contraction ratio was derived. The contraction ratio as a function of inflation pressure is found to match the observations of in vivo situations. We demonstrated that SoGut can achieve in vitro peristaltic contractions by coordinating the inflation sequence of multiple air chambers. It exhibited the functions to massage and transport the food contents. SoGut can simulate the physiological motions of the human stomach to advance research of digestion.