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.

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.

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.

Investigation of physicochemical composition and microbial communities in traditionally fermented vrum from Inner Mongolia.

Mongolian traditionally fermented vrum is known for its functional characteristics, and indigenous microbial flora plays a critical role in its natural fermentation. However, studies of traditionally fermented vrum are still rare. In this study, we investigated the artisanal production of traditionally fermented vrum from Inner Mongolia. In general, its physicochemical composition was characterized by 34.5 ± 8% moisture, 44.9 ± 12.1% fat, 10.6 ± 3.2% protein, and 210 ± 102°T. The total lactic acid bacteria and yeast counts ranged from 50 to 2.8 × 108 cfu/g and from 0 to 1.1 × 106 cfu/g, respectively. We studied bacterial and fungal community structures in 9 fermented vrum; we identified 5 bacterial phyla represented by 11 genera (an average relative abundance >1%) and 8 species (>1%), and 3 fungal phyla represented by 8 genera (>1%) and 8 species (>1%). Relative abundance values showed that Lactococcus and Lactobacillus were the most common bacterial genera, and Dipodascus was the predominant fungal genus. This scientific investigation of the nutritional components, microbial counts, and community profiles in Mongolian traditionally fermented vrum could help to develop future functional biomaterials and probiotics.

Study of bacterial and fungal community structures in traditional koumiss from Inner Mongolia.

Koumiss is notable for its nutritional functions, and microorganisms in koumiss determine its versatility. In this study, the bacterial and fungal community structures in traditional koumiss from Inner Mongolia, China, were investigated. Our results demonstrated that 6 bacterial phyla represented by 126 genera and 49 species and 3 fungal phyla represented by 59 genera and 57 species were detected in 11 samples of artisanal koumiss. Among them, Lactobacillus was the predominant genus of bacterium, and Kluyveromyces and Saccharomyces dominated at the fungal genus level. In addition, there were no differences in the bacterial and fungal richness and diversity of koumiss from 3 neighboring administrative divisions in Inner Mongolia, and the bacterial and fungal community structures (the varieties and relative abundance of bacterial and fungal genera and species) were clearly distinct in individual samples. This study provides a comprehensive understanding of the bacterial and fungal population profiles and the predominant genus and species, which would be beneficial for screening, isolation, and culture of potential probiotics to simulate traditional fermentation of koumiss for industrial and standardized production in the future.

Recent advances in racemic protein crystallography.

Solution of the three-dimensional structures of proteins is a critical step in deciphering the molecular mechanisms of their bioactivities. Among the many approaches for obtaining protein crystals, racemic protein crystallography has been developed as a unique method to solve the structures of an increasing number of proteins. Exploiting unnatural protein enantiomers in crystallization and resolution, racemic protein crystallography manifests two major advantages that are 1) to increase the success rate of protein crystallization, and 2) to obviate the phase problem in X-ray diffraction. The requirement of unnatural protein enantiomers in racemic protein crystallography necessitates chemical protein synthesis, which is hitherto accomplished through solid phase peptide synthesis and chemical ligation reactions. This review highlights the fundamental ideas of racemic protein crystallography and surveys the harvests in the field of racemic protein crystallography over the last five years from early 2012 to late 2016.

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 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.

Deep autoencoder as an interpretable tool for Raman spectroscopy investigation of chemical and extracellular vesicle mixtures.

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool that provides valuable insight into the molecular contents of chemical and biological samples. However, interpreting Raman spectra from complex or dynamic datasets remains challenging, particularly for highly heterogeneous biological samples like extracellular vesicles (EVs). To overcome this, we developed a tunable and interpretable deep autoencoder for the analysis of several challenging Raman spectroscopy applications, including synthetic datasets, chemical mixtures, a chemical milling reaction, and mixtures of EVs. We compared the results with classical methods (PCA and UMAP) to demonstrate the superior performance of the proposed technique. Our method can handle small datasets, provide a high degree of generalization such that it can fill unknown gaps within spectral datasets, and even quantify relative ratios of cell line-derived EVs to fetal bovine serum-derived EVs within mixtures. This simple yet robust approach will greatly improve the analysis capabilities for many other Raman spectroscopy applications.

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.

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.

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.

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.

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).

Metal amidoboranes: superior double-hydrogen-transfer agents in the reduction of ketones and imines.

Metal amidoboranes (MABs), such as lithium amidoborane (LiAB), show superior ability in reducing ketones and imines directly into their corresponding secondary alcohols and amines, respectively, at room temperature with high conversion and yields. A mechanistic study indicates that the reduction proceeds through a double-hydrogen-transfer process. Both protic H(N) and hydridic H(B) protons in the amidoborane participate in the reaction. Theoretical investigations show that the first (and rate-determining) step of the reduction reaction is the elimination of LiH from LiAB, followed by the transfer of H(Li) to the C site of the unsaturated bond.

Lithium amidoborane, a highly chemoselective reagent for the reduction of α,ß-unsaturated ketones to allylic alcohols.

Lithium amidoborane (LiNH(2)BH(3), LiAB for short), is capable of chemoselectively reducing α,ß-unsaturated ketones to the corresponding allylic alcohols at ambient temperature. A mechanistic study shows that the reduction is via a double hydrogen transfer process. The protic H(N) and hydridic H(B) in amidoborane add to the O and C sites of the carbonyl group, respectively.

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.

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.