Modulation Steering Motion by Quantitative Electrical Stimulation in Pigeon Robots

The pigeon robot has attracted significant attention in the field of animal robotics thanks to its outstanding mobility and adaptive capability in complex environments. However, research on pigeon robots is currently facing bottlenecks, and achieving fine control over the motion behavior of pigeon robots through brain-machine interfaces remains challenging. Here, we systematically quantify the relationship between electrical stimulation and stimulus-induced motion behaviors, and provide an analytical method to demonstrate the effectiveness of pigeon robots based on electrical stimulation. In this study, we investigated the influence of gradient voltage intensity (1.2-3.0 V) on the indoor steering motion control of pigeon robots. Additionally, we discussed the response time of electrical stimulation and the effective period of the brain-machine interface. The results indicate that pigeon robots typically exhibit noticeable behavioral responses at a 2.0 V voltage stimulus. Increasing the stimulation intensity significantly controls the steering angle and turning radius (p < 0.05), enabling precise control of pigeon robot steering motion through stimulation intensity regulation. When the threshold voltage is reached, the average response time of a pigeon robot to the electrical stimulation is 220 ms. This study quantifies the role of each stimulation parameter in controlling pigeon robot steering behavior, providing valuable reference information for the precise steering control of pigeon robots. Based on these findings, we offer a solution for achieving precise control of pigeon robot steering motion and contribute to solving the problem of encoding complex trajectory motion in pigeon robots.

The Impact of Various Cockpit Display Interfaces on Novice Pilots' Mental Workload and Situational Awareness: A Comparative Study

Future airspace is expected to become more congested with additional in-service cargo and commercial flights. Pilots will face additional burdens in such an environment, given the increasing number of factors that they must simultaneously consider while completing their work activities. Therefore, care and attention must be paid to the mental workload (MWL) experienced by operating pilots. If left unaddressed, a state of mental overload could affect the pilot's ability to complete his or her work activities in a safe and correct manner. This study examines the impact of two different cockpit display interfaces (CDIs), the Steam Gauge panel and the G1000 Glass panel, on novice pilots' MWL and situational awareness (SA) in a flight simulator-based setting. A combination of objective (EEG and HRV) and subjective (NASA-TLX) assessments is used to assess novice pilots' cognitive states during this study. Our results indicate that the gauge design of the CDI affects novice pilots' SA and MWL, with the G1000 Glass panel being more effective in reducing the MWL and improving SA compared with the Steam Gauge panel. The results of this study have implications for the design of future flight deck interfaces and the training of future pilots.

Nonlinear dynamics of postural control system under visual-vestibular habituation balance practice: evidence from EEG, EMG and center of pressure signals

Human postural control system is inherently complex with nonlinear interaction among multiple subsystems. Accordingly, such postural control system has the flexibility in adaptation to complex environments. Previous studies applied complexity-based methods to analyze center of pressure (COP) to explore nonlinear dynamics of postural sway under changing environments, but direct evidence from central nervous system or muscular system is limited in the existing literature. Therefore, we assessed the fractal dimension of COP, surface electromyographic (sEMG) and electroencephalogram (EEG) signals under visual-vestibular habituation balance practice. We combined a rotating platform and a virtual reality headset to present visual-vestibular congruent or incongruent conditions. We asked participants to undergo repeated exposure to either congruent (n = 14) or incongruent condition (n = 13) five times while maintaining balance. We found repeated practice under both congruent and incongruent conditions increased the complexity of high-frequency (0.5-20 Hz) component of COP data and the complexity of sEMG data from tibialis anterior muscle. In contrast, repeated practice under conflicts decreased the complexity of low-frequency (<0.5 Hz) component of COP data and the complexity of EEG data of parietal and occipital lobes, while repeated practice under congruent environment decreased the complexity of EEG data of parietal and temporal lobes. These results suggested nonlinear dynamics of cortical activity differed after balance practice under congruent and incongruent environments. Also, we found a positive correlation (1) between the complexity of high-frequency component of COP and the complexity of sEMG signals from calf muscles, and (2) between the complexity of low-frequency component of COP and the complexity of EEG signals. These results suggested the low- or high-component of COP might be related to central or muscular adjustment of postural control, respectively.

Human mesenchymal stromal cells-laden crosslinked hyaluronic acid-alginate bioink for 3D bioprinting applications in tissue engineering

Three-dimensional (3D) bioprinting is considered one of the most advanced tools to build up materials for tissue engineering. The aim of this work was the design, development and characterization of a bioink composed of human mesenchymal stromal cells (hMSC) for extrusion through nozzles to create these 3D structures that might potentially be apply to replace the function of damaged natural tissue. In this study, we focused on the advantages and the wide potential of biocompatible biomaterials, such as hyaluronic acid and alginate for the inclusion of hMSC. The bioink was characterized for its physical (pH, osmolality, degradation, swelling, porosity, surface electrical properties, conductivity, and surface structure), mechanical (rheology and printability) and biological (viability and proliferation) properties. The developed bioink showed high porosity and high swelling capacity, while the degradation rate was dependent on the temperature. The bioink also showed negative electrical surface and appropriate rheological properties required for bioprinting. Moreover, stress-stability studies did not show any sign of physical instability. The developed bioink provided an excellent environment for the promotion of the viability and growth of hMSC cells. Our work reports the first-time study of the effect of storage temperature on the cell viability of bioinks, besides showing that our bioink promoted a high cell viability after being extruded by the bioprinter. These results support the suggestion that the developed hMSC-composed bioink fulfills all the requirements for tissue engineering and can be proposed as a biological tool with potential applications in regenerative medicine and tissue engineering.

Antibody-independent surface plasmon resonance assays for influenza vaccine quality control

Surface plasmon resonance (SPR)-based biosensors have emerged as a powerful platform for bioprocess monitoring due to their ability to detect biointeractions in real time, without the need for labeling. Paramount for the development of a robust detection platform is the immobilization of a ligand with high specificity and affinity for the in-solution species of interest. Following the 2009 H1N1 pandemic, much effort has been made toward the development of quality control platforms for influenza A vaccine productions, many of which have employed SPR for detection. Due to the rapid antigenic drift of influenza's principal surface protein, hemagglutinin, antibodies used for immunoassays need to be produced seasonally. The production of these antibodies represents a 6-8-week delay in immunoassay and, thus, vaccine availability. This review focuses on SPR-based assays that do not rely on anti-HA antibodies for the detection, characterization, and quantification of influenza A in bioproductions and biological samples. KEY POINTS: • The single radial immunodiffusion assay (SRID) has been the gold standard for the quantification of influenza vaccines since 1979. Due to antigenic drift of influenza's hemagglutinin protein, new antibody reagents for the SRID assay must be produced each year, requiring 6-8 weeks. The resulting delay in immunoassay availability is a major bottleneck in the influenza vaccine pipeline. This review highlights ligand options for the detection and quantification of influenza viruses using surface plasmon resonance biosensors.

Clinical Applicable Carboxymethyl Chitosan with Gel-Forming and Stabilizing Properties Based on Terminal Sterilization Methods of Electron Beam Irradiation

Carboxymethyl chitosan (CMC)-based hydrogels have great potential for clinical applications, but a critical sterilization process must be addressed to bring them to market. Compared to ethylene oxide sterilization or heat sterilization, irradiation sterilization avoids alkylation and heat damage, while available studies on γ-irradiated other polysaccharides show that solution polysaccharides are susceptible to degradation or cross-linking. Aiming at the challenges brought by the γ-irradiation process of polysaccharide aqueous solution, this paper innovatively proposes the lyophilized CMC using electron beam (EB) irradiation, which not only avoids the generation of free radicals in the irradiated water leading to the degradation and cross-linking of polysaccharides but also retains the properties of CMC in terms of gel formation, stabilization, and clinical application. We used FTIR, TG, GPC, and microbial load tests to demonstrate that lyophilized CMC did not have significant changes in structure and molecular weight after EB irradiation, complied with the requirements for sterilization, and still had gel stability, thus proving that lyophilized CMC could be used for EB irradiation and met the requirements for clinical application. Therefore, this work is expected to further advance CMC injectable hydrogels toward clinical applications and provide a new direction for the sterilization processes of other polysaccharide hydrogels.

Celiac disease - a pluripathological model in pediatric practice

Being defined as an autoimmune, chronic pathology, frequently encountered in any age group, but especially in pediatrics, celiac disease (also called gluten enteropathy), is gaining more and more ground in terms of diagnosis, but also interest in research. The data from the literature of the last decades attest the chameleonic way of its presentation, there may be both classic onset symptoms and atypical symptoms. Given the impact played by celiac disease, especially in the optimal growth and development of children, the current narrative review aims to highlight the atypical presentation methods, intended to guide the clinician towards the inclusion of the pathology in the differential diagnosis scheme. To these we add the summary presentation of the general data and therapeutic lines regarding the underlying condition and the existing comorbidities. In order to place the related information up to date, we performed a literature review of the recent articles published in international databases. We bring forward the current theories and approaches regarding both classic celiac disease and its atypical manifestations. Among these we note mainly constitutional, skin or mucous, bone, neuro-psychic, renal, reproductive injuries, but also disorders of biological constants and association with multiple autoimmunities. Knowing and correlating them with celiac disease is the key to optimal management of patients, thus reducing the subsequent burden of the disease.

Neuroanatomical correlates of distracted straight driving performance: a driving simulator MRI study across the lifespan

Background

Driving is the preferred mode of transportation for adults across the healthy age span. However, motor vehicle crashes are among the leading causes of injury and death, especially for older adults, and under distracted driving conditions. Understanding the neuroanatomical basis of driving may inform interventions that minimize crashes. This exploratory study examined the neuroanatomical correlates of undistracted and distracted simulated straight driving.

Methods

One-hundred-and-thirty-eight participants (40.6% female) aged 17-85 years old (mean and SD = 58.1 ± 19.9 years) performed a simulated driving task involving straight driving and turns at intersections in a city environment using a steering wheel and foot pedals. During some straight driving segments, participants responded to auditory questions to simulate distracted driving. Anatomical T1-weighted MRI was used to quantify grey matter volume and cortical thickness for five brain regions: the middle frontal gyrus (MFG), precentral gyrus (PG), superior temporal cortex (STC), posterior parietal cortex (PPC), and cerebellum. Partial correlations controlling for age and sex were used to explore relationships between neuroanatomical measures and straight driving behavior, including speed, acceleration, lane position, heading angle, and time speeding or off-center. Effects of interest were noted at an unadjusted p-value threshold of 0.05.

Results

Distracted driving was associated with changes in most measures of straight driving performance. Greater volume and cortical thickness in the PPC and cerebellum were associated with reduced variability in lane position and heading angle during distracted straight driving. Cortical thickness of the MFG, PG, PPC, and STC were associated with speed and acceleration, often in an age-dependent manner.

Conclusion

Posterior regions were correlated with lane maintenance whereas anterior and posterior regions were correlated with speed and acceleration, especially during distracted driving. The regions involved and their role in straight driving may change with age, particularly during distracted driving as observed in older adults. Further studies should investigate the relationship between distracted driving and the aging brain to inform driving interventions.

Transforming the CRISPR/dCas9-based gene regulation technique into a forward screening tool in Plasmodium falciparum

It is a significant challenge to assess the functions of many uncharacterized genes in human malaria parasites. Here, we present a genetic screening tool to assess the contribution of essential genes from Plasmodium falciparum by the conditional CRISPR-/deadCas9-based interference and activation (i/a) systems. We screened both CRISPRi and CRISPRa sets, consisting of nine parasite lines per set targeting nine genes via their respective gRNAs. By conducting amplicon sequencing of gRNA loci, we identified the contribution of each targeted gene to parasite fitness upon drug (artemisinin, chloroquine) and stress (starvation, heat shock) treatment. The screening was highly reproducible, and the screening libraries were easily generated by transfection of mixed plasmids expressing different gRNAs. We demonstrated that this screening is straightforward, robust, and can provide a fast and efficient tool to study essential genes that have long presented a bottleneck in assessing their functions using existing genetic tools.

Nano-hydroxyapatite promotes cell apoptosis by co-activating endoplasmic reticulum stress and mitochondria damage to inhibit glioma growth

Despite a growing body of studies demonstrating the specific anti-tumor effect of nano-hydroxyapatite (n-HA), the underlying mechanism remained unclear. Endoplasmic reticulum (ER) and mitochondria are two key players in intracellular Ca2+ homeostasis and both require Ca2+ to participate. Moreover, the ER-mitochondria interplay coordinates the maintenance of cellular Ca2+ homeostasis to prevent any negative consequences from excess of Ca2+, hence there needs in-depth study of n-HA effect on them. In this study, we fabricated needle-like n-HA to investigate the anti-tumor effectiveness as well as the underlying mechanisms from cellular and molecular perspectives. Data from in vitro experiments indicated that the growth and invasion of glioma cells were obviously reduced with the aid of n-HA. It is interesting to note that the expression of ER stress biomarkers (GRP78, p-IRE1, p-PERK, PERK, and ATF6) were all upregulated after n-HA treatment, along with the activation of the pro-apoptotic transcription factor CHOP, showing that ER stress produced by n-HA triggered cell apoptosis. Moreover, the increased expression level of intracellular reactive oxygen species and the mitochondrial membrane depolarization, as well as the downstream cell apoptotic signaling activation, further demonstrated the pro-apoptotic roles of n-HA induced Ca2+ overload through inducing mitochondria damage. The in vivo data provided additional evidence that n-HA caused ER stress and mitochondria damage in cells and effectively restrain the growth of glioma tumors. Collectively, the work showed that n-HA co-activated intracellular ER stress and mitochondria damage are critical triggers for cancer cells apoptosis, offering fresh perspectives on ER-mitochondria targeted anti-tumor therapy.

Swim bladder-derived biomaterials: structures, compositions, properties, modifications, and biomedical applications

Animal-derived biomaterials have been extensively employed in clinical practice owing to their compositional and structural similarities with those of human tissues and organs, exhibiting good mechanical properties and biocompatibility, and extensive sources. However, there is an associated risk of infection with pathogenic microorganisms after the implantation of tissues from pigs, cattle, and other mammals in humans. Therefore, researchers have begun to explore the development of non-mammalian regenerative biomaterials. Among these is the swim bladder, a fish-derived biomaterial that is rapidly used in various fields of biomedicine because of its high collagen, elastin, and polysaccharide content. However, relevant reviews on the biomedical applications of swim bladders as effective biomaterials are lacking. Therefore, based on our previous research and in-depth understanding of this field, this review describes the structures and compositions, properties, and modifications of the swim bladder, with their direct (including soft tissue repair, dural repair, cardiovascular repair, and edible and pharmaceutical fish maw) and indirect applications (including extracted collagen peptides with smaller molecular weights, and collagen or gelatin with higher molecular weights used for hydrogels, and biological adhesives or glues) in the field of biomedicine in recent years. This review provides insights into the use of swim bladders as source of biomaterial; hence, it can aid biomedicine scholars by providing directions for advancements in this field.

Influences of Polyphenols on the Properties of Crosslinked Acellular Fish Swim Bladders: Experiments and Molecular Dynamic Simulations

Acellular fish swim bladders (AFSBs) are a promising biomaterial in tissue engineering, however, they may suffer from rapid degradation due to enzyme invasion. In this work, natural polyphenols, including epigallocatechin gallate (EGCG), proanthocyanidin (PC), tannic acid (TA) and protocatechuic acid (PCA), were utilized to improve the properties of AFSBs through crosslinking modifications. Fourier transform infrared (FTIR) results indicate that the triple helix of the collagen in AFSBs is well preserved after crosslinking. The differential scanning calorimetry (DSC), water contact angle (WCA) and in vitro degradation tests indicate that the polyphenol-crosslinked AFSBs exhibit improved thermal stability, enzymatic stability, hydrophilicity and mechanical properties. Among them, EGCG with multiple phenolic hydroxyl groups and low potential resistance is more favorable for the improvement of the mechanical properties and enzymatic stability of AFSBs, as well as their biocompatibility and integrity with the collagen triple helix. Moreover, the crosslinking mechanism was demonstrated to be due to the hydrogen bonds between polyphenols and AFSBs, and was affected by the molecular size, molecular weight and the hydroxyl groups activity of polyphenol molecules, as clarified by molecular dynamic (MD) simulations. The approach presented in this work paves a path for improving the properties of collagen materials.

Graphene (GNP) reinforced 3D printing nanocomposites: An advanced structural perspective

The influence of macro-micro structural design on the mechanical response of structural nanocomposites is substantial. The advancement of additive manufacturing especially three-dimensional (3-D) printing technology offers a promising avenue for the efficient and precise fabrication of multi-functional low-weight and high-strength nanocomposites. In contemporary discourse, there is a notable emphasis on carbon-based nanomaterials as nanofillers for structural composites due to their substantial specific surface area and exceptional load-bearing ability in mechanical structures. Notably, graphene, a distinctive two-dimensional (2-D) nanomaterial, exhibits very large elastic modulus and ultimate strength as well as remarkable plasticity. The utilization of graphene nanoparticles (GNPs) in the field of 3-D printing enables the production of intricate three-dimensional structures of varying sizes and configurations. This is achieved through the macro-assembly process, which facilitates the creation of a well-organized distribution of graphene and the establishment of a comprehensive physical network through precise micro-regulation. This paper presents an overview of multiscale structural composites that are strengthened by the incorporation of graphene and prepared by 3-D printing. The composites discussed in this study encompass graphene-polymer composites, graphene-ceramic composites, and graphene-metal composites. Furthermore, an analysis of the present obstacles and potential future advancements in this rapidly expanding domain is anticipated.

Rapid eradication of vancomycin and methicillin-resistant Staphylococcus aureus by MDP1 antimicrobial peptide coated on photocrosslinkable chitosan hydrogel: in vitro antibacterial and in silico molecular docking studies

Introduction

Antibiotic resistance and weak bioavailability of antibiotics in the skin due to systemic administration leads to failure in eradication of vancomycin- and methicillin-resistant Staphylococcus aureus (VRSA and MRSA)-associated wound infections and subsequent septicemia and even death. Accordingly, this study aimed at designing a photocrosslinkable methacrylated chitosan (MECs) hydrogel coated by melittin-derived peptide 1 (MDP1) that integrated the antibacterial activity with the promising skin regenerative capacity of the hydrogel to eradicate bacteria by burst release strategy.

Methods

The MECs was coated with MDP1 (MECs-MDP1), characterized, and the hydrogel-peptide interaction was evaluated by molecular docking. Antibacterial activities of MECs-MDP1 were evaluated against VRSA and MRSA bacteria and compared to MECs-vancomycin (MECs-vanco). Antibiofilm activity of MECs-MDP1 was studied by our novel 'in situ biofilm inhibition zone (IBIZ)' assay, and SEM. Biocompatibility with human dermal fibroblast cells (HDFs) was also evaluated.

Results and Discussion

Molecular docking showed hydrogen bonds as the most interactions between MDP1 and MECs at a reasonable affinity. MECs-MDP1 eradicated the bacteria rapidly by burst release strategy whereas MECs-vanco failed to eradicate them at the same time intervals. Antibiofilm activity of MECs-MDP1 were also proved successfully. As a novel report, molecular docking analysis has demonstrated that MDP1 covers the structure of MECs and also binds to lysozyme with a reasonable affinity, which may explain the inhibition of lysozyme. MECs-MDP1 was also biocompatible with human dermal fibroblast skin cells, which indicates its safe future application. The antibacterial properties of a photocrosslinkable methacrylated chitosan-based hydrogel coated with MDP1 antimicrobial peptide were successfully proved against the most challenging antibiotic-resistant bacteria causing nosocomial wound infections; VRSA and MRSA. Molecular docking analysis revealed that MDP1 interacts with MECs mainly through hydrogen bonds with reasonable binding affinity. MECs-MDP1 hydrogels eradicated the planktonic state of bacteria by burst release of MDP1 in just a few hours whereas MECs-vanco failed to eradicate them. inhibition zone assay showed the anti-biofilm activity of the MECs-MDP1 hydrogel too. These findings emphasize that MECs-MDP1 hydrogel would be suggested as a biocompatible wound-dressing candidate with considerable and rapid antibacterial activities to prevent/eradicate VRSA/MRSA bacterial wound infections.

Evaluation of renovated double J stents using ureter models with and without stenosis

PURPOSE

Commercial double J stents (DJS) have a uniform shape regardless of the specific nature of various ureteral diseases. We tested renovated DJS and compared them with conventional DJS using ureter models.

METHODS

One straight ureter model included stenosis at the distal ureter near the ureterovesical junction and the other did not. We used conventional DJS and renovated 5- and 6-Fr soft DJS for ureter stones and 6-, 7-, and 8.5-Fr hard DJS for tumors. The DJS comprised holes in the upper, middle, or lower one-third of the shaft (length, 24 cm; 2-cm-diameter coils at both ends). More holes were created along the shaft based on the ureteral disease location. Conventional DJS had holes spaced 1 cm apart along the shaft. Renovated DJS had holes spaced 1 cm apart along the shaft with 0.5-cm intervals on the upper, middle, or lower one-third of the shaft. Urine flow was evaluated.

RESULTS

As the DJS diameter increased, the flow rate decreased. The flow rates of DJS with holes in the lower shaft were relatively lower than those of conventional DJS and DJS with holes in the upper and middle shafts. In the ureter model without stenosis, 6-, 7-, and 8.5-Fr renovated stents exhibited significantly higher flow rates than conventional stents. In the ureter model with stenosis, 5-, 6-, 7-, and 8.5-Fr renovated stents did not exhibit significantly higher flow rates than conventional stents.

CONCLUSION

Renovated stents and conventional stents did not exhibit significant differences in urine flow with stenosis.

Inflammatory liver diseases and susceptibility to sepsis

Patients with inflammatory liver diseases, particularly alcohol-associated liver disease and metabolic dysfunction-associated fatty liver disease (MAFLD), have higher incidence of infections and mortality rate due to sepsis. The current focus in the development of drugs for MAFLD is the resolution of non-alcoholic steatohepatitis and prevention of progression to cirrhosis. In patients with cirrhosis or alcoholic hepatitis, sepsis is a major cause of death. As the metabolic center and a key immune tissue, liver is the guardian, modifier, and target of sepsis. Septic patients with liver dysfunction have the highest mortality rate compared with other organ dysfunctions. In addition to maintaining metabolic homeostasis, the liver produces and secretes hepatokines and acute phase proteins (APPs) essential in tissue protection, immunomodulation, and coagulation. Inflammatory liver diseases cause profound metabolic disorder and impairment of energy metabolism, liver regeneration, and production/secretion of APPs and hepatokines. Herein, the author reviews the roles of (1) disorders in the metabolism of glucose, fatty acids, ketone bodies, and amino acids as well as the clearance of ammonia and lactate in the pathogenesis of inflammatory liver diseases and sepsis; (2) cytokines/chemokines in inflammatory liver diseases and sepsis; (3) APPs and hepatokines in the protection against tissue injury and infections; and (4) major nuclear receptors/signaling pathways underlying the metabolic disorders and tissue injuries as well as the major drug targets for inflammatory liver diseases and sepsis. Approaches that focus on the liver dysfunction and regeneration will not only treat inflammatory liver diseases but also prevent the development of severe infections and sepsis.

Effects of ceramic thickness, ceramic translucency, and light transmission on light-cured bulk-fill resin composites as luting cement of lithium disilicate based-ceramics

PURPOSE

To assess the effects of ceramic thickness, ceramic translucency, and light transmission on restorative composites used as luting cement for lithium disilicate-based ceramics.

METHODS

Four luting types of cement were tested (n=8); a dual-cured resin cement (Multilink N), a light-cured conventional flowable composite (Tetric N-Flow), and two light-cured bulk-fill flowable composites (Tetric N-Flow Bulk Fill and X-tra base). The 20 s- or 40 s-light (1000 mW/cm2) was transmitted through 1- or 2-mm-thick high- or low-translucency (HT- or LT-) ceramic discs (IPS e.Max press) to reach the 1-mm-thick luting cement. Light transmitted to cement without ceramic served as a control. Vickers hardness number (VHN), flexural strength (FS), fractography, and degree of conversion (DC) were evaluated. One-way and multi-way analysis of variance was conducted to determine the effects of factors on VHN and FS.

RESULTS

Ceramic thickness, light transmission time, and cement type significantly affected the VHN of the luting cement (P < .000). Only Multilink N (LT- and HT-1mm) and Tetric N-Flow (HT-1mm) reached 90% VHN of corresponding control by 20 s-light transmissions, but Tetric N-Flow exhibited lowest VHN and approximately 1/3-1/2 VHN of Multilink N (P < 0.05). X-tra base expressed superior physicochemical properties to Tetric N-Flow Bulk Fill (P < 0.05) and reached >90% VHN of control in all conditions with 40 s-light transmissions except for LT-2 mm. DC, FS, and fractography supported these findings.

CONCLUSIONS

The light-cured bulk-fill composite served as a luting cement for lithium-disilicate-based ceramics in a product-dependent manner. Light transmission time is crucial to ensure sufficient luting cement polymerization.

Advances and Trends of Photoresponsive Hydrogels for Bone Tissue Engineering

The development of static hydrogels as an optimal choice for bone tissue engineering (BTE) remains a difficult challenge primarily due to the intricate nature of bone healing processes, continuous physiological functions, and pathological changes. Hence, there is an urgent need to exploit smart hydrogels with programmable properties that can effectively enhance bone regeneration. Increasing evidence suggests that photoresponsive hydrogels are promising bioscaffolds for BTE due to their advantages such as controlled drug release, cell fate modulation, and the photothermal effect. Here, we review the current advances in photoresponsive hydrogels. The mechanism of photoresponsiveness and its advanced applications in bone repair are also elucidated. Future research would focus on the development of more efficient, safer, and smarter photoresponsive hydrogels for BTE. This review is aimed at offering comprehensive guidance on the trends of photoresponsive hydrogels and shedding light on their potential clinical application in BTE.

Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials

BACKGROUND

Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal carcinoma In Situ is safe (E. S. Hwang et al., BMJ Open, 9: e026797, 2019, A. Francis et al., Eur J Cancer. 51: 2296-2303, 2015, Chizuko Kanbayashi et al. The international collaboration of active surveillance trials for low-risk DCIS (LORIS, LORD, COMET, LORETTA),  L. E. Elshof et al., Eur J Cancer, 51, 1497-510, 2015). Low-risk is defined as grade I or II DCIS. Because DCIS grade is a major eligibility criteria in these trials, it would be very helpful to assess DCIS grade on mammography, informed by grade assessed on DCIS histopathology in pre-surgery biopsies, since surgery will not be performed on a significant number of patients participating in these trials.

OBJECTIVE

To assess the performance and clinical utility of a convolutional neural network (CNN) in discriminating high-risk (grade III) DCIS and/or Invasive Breast Cancer (IBC) from low-risk (grade I/II) DCIS based on mammographic features. We explored whether the CNN could be used as a decision support tool, from excluding high-risk patients for active surveillance.

METHODS

In this single centre retrospective study, 464 patients diagnosed with DCIS based on pre-surgery biopsy between 2000 and 2014 were included. The collection of mammography images was partitioned on a patient-level into two subsets, one for training containing 80% of cases (371 cases, 681 images) and 20% (93 cases, 173 images) for testing. A deep learning model based on the U-Net CNN was trained and validated on 681 two-dimensional mammograms. Classification performance was assessed with the Area Under the Curve (AUC) receiver operating characteristic and predictive values on the test set for predicting high risk DCIS-and high-risk DCIS and/ or IBC from low-risk DCIS.

RESULTS

When classifying DCIS as high-risk, the deep learning network achieved a Positive Predictive Value (PPV) of 0.40, Negative Predictive Value (NPV) of 0.91 and an AUC of 0.72 on the test dataset. For distinguishing high-risk and/or upstaged DCIS (occult invasive breast cancer) from low-risk DCIS a PPV of 0.80, a NPV of 0.84 and an AUC of 0.76 were achieved.

CONCLUSION

For both scenarios (DCIS grade I/II vs. III, DCIS grade I/II vs. III and/or IBC) AUCs were high, 0.72 and 0.76, respectively, concluding that our convolutional neural network can discriminate low-grade from high-grade DCIS.

Detection of cardiac abnormalities from 12-lead ecg using complex wavelet sub-band features

AIM OF THE STUDY

This research endeavours to optimize cardiac anomaly detection by introducing a method focused on selecting the most effective Daubechis wavelet families. The principal aim is to differentiate between cardiac states that are normal and abnormal by utilizing longer electrocardiogram (ECG) signal events based on the Apnea ECG dataset. Apnea ECG is often used to detect sleep apnea, a sleep disorder characterized by repeated interruptions in breathing during sleep. By using machine learning methods, such as Principal Component Analysis (PCA) and different classifiers, the goal is to improve the precision of cardiac irregularity identification. Used method. To extract important statistical and sub-band information from lengthy ECG signal episodes, the study uses a novel method that combines discrete wavelet transform with Principal Component Analysis (PCA) for dimension reduction. The methodology focuses on successfully categorizing ECG signals by utilizing several classifiers, including multilayer perceptron (MLP) neural network, Ensemble Subspace K-Nearest Neighbour(KNN), and Ensemble Bagged Trees, together with varied Daubechis wavelet families (db2, db3, db4, db5, db6). Brief Description of Results. The results emphasize the importance of the chosen Daubechis wavelet family, db5, and its superiority in ECG representation. The method distinguishes normal and abnormal ECG signals well on the Physionet Apnea ECG database. The Neural Network-based method accurately recognizes 100% of healthy signals and 97.8% of problematic ones with 98.6% accuracy.

FINDINGS

The Ensemble Subspace K-Nearest Neighbour (KNN) and Ensemble Bagged Trees methods got 87.1% accuracy and 0.89 and 0.87 AOC curve values on this dataset, showing that the method works. Precision values of 0.96, 0.86, and 0.86 for MLP Neural Network, KNN Subspace, and Ensemble Bagged Trees confirm their robustness. These findings suggest wavelet families and machine learning can improve cardiac abnormality detection and categorization.

The impact of high nicotine concentrations on the viability and cardiac differentiation of mesenchymal stromal cells: a barrier to regenerative therapy for smokers

Background: Current treatment methods are not successful in restoring the lost cardiomyocytes after injury. Stem cell-based strategies have attracted much attention in this regard. Smoking, as a strong cardiovascular risk factor, not only affects the cardiac cells adversely but also deteriorates the function of stem cells. Since mesenchymal stem cells (MSCs) are one of the popular candidates in cardiovascular disease (CVD) clinical trials, we investigated the impact of nicotine on the regenerative properties (viability and cardiac differentiation) of these cells. Methods: MSCs were isolated from rat bone marrow and characterized based on morphology, differentiation capability, and the expression of specific mesenchymal markers. The MTT assay was used to assess the viability of MSCs after being exposed to different concentrations of nicotine. Based on MTT findings and according to the concentration of nicotine in smokers' blood, the growth curve and population doubling time were investigated for eight consecutive days. Cells were treated with 5-azacytidine (an inducer of cardiac differentiation), and then the expressions of cardiac-specific markers were calculated by qPCR. Results: MSCs were spindle-shaped, capable of differentiating into adipocyte and osteocyte, and expressed CD73 and CD90. The viability of MSCs was reduced upon exposure to nicotine in a concentration- and time-dependent manner. The growth curve showed that nicotine reduced the proliferation of MSCs, and treated cells needed more time to double. In addition, the expressions of GATA4 and troponin were downregulated in nicotine-treated cells on day 3. However, these two cardiac markers were overexpressed on day 7. Conclusion: Nicotine decreased normal growth and reduced the expression of cardiac markers in MSCs. This aspect is of eminent importance to smokers with cardiovascular disease who are candidates for stem cell therapy.

Measuring cell proliferation in bioprinting research

Tissue-like constructs, intended for application in tissue engineering and regenerative medicine, can be produced by three-dimensional (3D) bioprinting of cells in hydrogels. It is essential that the viability and proliferation of the encapsulated cells can be reliably determined. Methods currently used to evaluate cell proliferation, such as quantification of DNA and measurement of metabolic activity, have been developed for application in 2D cultures and might not be suitable for bioinks. In this study, human fibroblasts were either cast or printed in gelatin methacryloyl (GelMA) or sodium alginate hydrogels and cell proliferation was assessed by AlamarBlue, PicoGreen and visual cell counts. Comparison of data extrapolated from standard curves generated from 2D cultures and 3D hydrogels showed potential inaccuracies. Moreover, there were pronounced discrepancies in cell numbers obtained from these assays; the different bioinks strongly influenced the outcomes. Overall, the results indicate that more than one method should be applied for better assessment of cell proliferation in bioinks.

Automated cardiac arrhythmia detection techniques: a comprehensive review for prospective approach

Abnormal cardiac functionality produces irregular heart rhythms which are commonly known as arrhythmias. In some conditions, arrhythmias are treated as very dangerous which may lead to sudden cardiac arrest. The incidence and prevalence of cardiac anomalies seeks early detection of arrhythmias using automated classification techniques. In the past, numerous automated arrhythmia detection techniques have been developed that are based on electrocardiogram (ECG) signal analysis. Focusing on the prospective research in this field, this article reports a comprehensive review of existing techniques that are obtained using search engines such as IEEE explore, Google scholar and science direct. Based on the review, the existing techniques are broadly categorized into two types: machine-learning and deep-learning-based techniques. In this study, it is noticed that the performance of the machine-learning-based arrhythmia detection techniques depend on pre-processing of ECG signal, R-peaks detection, features extraction and classification tools while the deep-learning-based techniques do not require the features extraction step. Generally, the existing techniques utilize Massachusetts Institute of Technology-Beth Israel Hospital arrhythmia database to evaluate the classification performance. The classification performance of automated techniques also depends on ECG data used for training and testing of the classifier. It is expected that the performance should be evaluated using a variety of ECG signals including the cases of inter-patient and intra-patient paradigm. The existing techniques also require to deal with the class-imbalance problem. In addition to this, a specific partition-ratio between training and testing datasets should be maintained for fair comparison of performance of different techniques.

Proteome of Personalized Tissue-Engineered Veins

Vascular diseases are the largest cause of death globally and impose a major global burden on healthcare. The gold standard for treating vascular diseases is the transplantation of autologous veins, if applicable. Alternative treatments still suffer from shortcomings, including low patency, lack of growth potential, the need for repeated intervention, and a substantial risk of developing infections. The use of a vascular ECM scaffold reconditioned with the patient's own cells has shown successful results in preclinical and clinical studies. In this study, we have compared the proteomes of personalized tissue-engineered veins of humans and pigs. By applying tandem mass tag (TMT) labeling LC/MS-MS, we have investigated the proteome of decellularized (DC) veins from humans and pigs and reconditioned (RC) DC veins produced through perfusion with the patient's whole blood in STEEN solution, applying the same technology as used in the preclinical studies. The results revealed high similarity between the proteomes of human and pig DC and RC veins, including the ECM texture after decellularization and reconditioning. In addition, functional enrichment analysis showed similarities in signaling pathways and biological processes involved in the immune system response. Furthermore, the classification of proteins involved in immune response activity that were detected in human and pig RC veins revealed proteins that evoke immunogenic responses, which may lead to graft rejection, thrombosis, and inflammation. However, the results from this study imply the initiation of wound healing rather than an immunogenic response, as both systems share the same processes, and no immunogenic response was reported in the preclinical and clinical studies. Finally, our study assessed the application of STEEN solution in tissue engineering and identified proteins that may be useful for the prediction of successful transplantations.

In vivo study to assess fat embolism resulting from the Reamer-Irrigator-Aspirator 2 system compared to a novel aspirator-based concept for intramedullary bone graft harvesting

INTRODUCTION

Fat embolism (FE) following intramedullary (IM) reaming can cause severe pulmonary complications and sudden death. Recently, a new harvesting concept was introduced in which a novel aspirator is used first for bone marrow (BM) aspiration and then for subsequent aspiration of morselized endosteal bone during sequential reaming (A + R + A). In contrast to the established Reamer-Irrigator-Aspirator (RIA) 2 system, the new A + R + A concept allows for the evacuation of fatty BM prior to reaming. In this study, we hypothesized that the risk of FE, associated coagulopathic reactions and pulmonary FE would be comparable between the RIA 2 system and the A + R + A concept.

MATERIALS AND METHODS

Intramedullary bone graft was harvested from intact femora of 16 Merino sheep (age: 1-2 years) with either the RIA 2 system (n = 8) or the A + R + A concept (n = 8). Fat intravasation was monitored with the Gurd test, coagulopathic response with D-dimer blood level concentration and pulmonary FE with histological evaluation of the lungs.

RESULTS

The total number and average size of intravasated fat particles was similar between groups (p = 0.13 and p = 0.98, respectively). D-dimer concentration did not significantly increase within 4 h after completion of surgery (RIA 2: p = 0.82; A + R + A: p = 0.23), with an interaction effect similar between groups (p = 0.65). The average lung area covered with fat globules was similar between groups (p = 0.17).

CONCLUSIONS

The use of the RIA 2 system and the novel A + R + A harvesting concept which consists of BM evacuation followed by sequential IM reaming and aspiration of endosteal bone, resulted in only minor fat intravasation, coagulopathic reactions and pulmonary FE, with no significant differences between the groups. Our results, therefore, suggest that both the RIA 2 system and the new A + R + A concept are comparable technologies in terms of FE-related complications.

Enzymatic properties and immobilization of a thermostable prenyltransferase from Aspergillus fumigatiaffinis for the production of prenylated naringenin

Prenyltransferases catalyze the synthesis of prenylated flavonoids, providing these with greater lipid solubility, biological activity, and availability. In this study, a thermostable prenyltransferase (AfPT) from Aspergillus fumigatiaffinis was cloned and expressed in Escherichia coli. By optimizing induction conditions, the expression level of AfPT reached 39.3 mU/mL, which was approximately 200 % of that before optimization. Additionally, we determined the enzymatic properties of AfPT. Subsequently, AfPT was immobilized on carboxymethyl cellulose magnetic nanoparticles (CMN) at a maximum load of 0.6 mg/mg. Optimal activity of CMN-AfPT was achieved at pH 8.0 and 55 °C. Thermostability assays showed that the residual activity of CMN-AfPT was greater than 50 % after incubation at 55 °C for 4 h. Km and Vmax of CMN-AfPT for naringenin were 0.082 mM and 5.57 nmol/min/mg, respectively. The Kcat/Km ratio of CMN-AfPT was higher than that of AfPT. Residual prenyltransferase activity of CMN-AfPT remained higher than 70 % even after 30 days of storage. Further, CMN-AfPT retained 68 % of its original activity after 10 cycles of reuse. Compared with free AfPT, CMN-AfPT showed higher catalytic efficiency, thermostability, metal ion tolerance, substrate affinity, storage stability, and reusability. Our study presents a thermostable prenyltransferase and its immobilized form for the production of prenylated flavonoids in vitro.

Adaptive radiotherapy for head and neck cancer: Pitfalls and possibilities from the radiation oncologist's point of view

BACKGROUND

Patients with head and neck cancer (HNC) may experience substantial anatomical changes during the course of radiotherapy treatment. The implementation of adaptive radiotherapy (ART) proves effective in managing the consequent impact on the planned dose distribution.

METHODS

This narrative literature review comprehensively discusses the diverse strategies of ART in HNC and the documented dosimetric and clinical advantages associated with these approaches, while also addressing the current challenges for integration of ART into clinical practice.

RESULTS AND CONCLUSION

Although based on mainly non-randomized and retrospective trials, there is accumulating evidence that ART has the potential to reduce toxicity and improve quality of life and tumor control in HNC patients treated with RT. However, several questions remain regarding accurate patient selection, the ideal frequency and timing of replanning, and the appropriate way for image registration and dose calculation. Well-designed randomized prospective trials, with a predetermined protocol for both image registration and dose summation, are urgently needed to further investigate the dosimetric and clinical benefits of ART.

Implantation of hUCB-MSCs generates greater hyaline-type cartilage than microdrilling combined with high tibial osteotomy

PURPOSE

To compare the outcomes of treating large cartilage defects in knee osteoarthritis using human allogeneic umbilical cord blood-derived mesenchymal stem cell (hUCB-MSC) implantation or arthroscopic microdrilling as a supplementary cartilage regenerative procedure combined with high tibial osteotomy (HTO).

METHODS

This 1-year prospective comparative study included 25 patients with large, near full-thickness cartilage defects (International Cartilage Repair Society grade ≥ IIIB) in the medial femoral condyles and varus malalignment. Defects were treated with hUCB-MSC implantation or arthroscopic microdrilling combined with HTO. The primary outcomes were pain visual analogue scale and International Knee Documentation Committee subjective scores at 12, 24 and 48 weeks. Secondary outcomes included arthroscopic, histological and magnetic resonance imaging assessments at 1 year.

RESULTS

Fifteen and 10 patients were treated via hUCB-MSC implantation and microdrilling, respectively. Baseline demographics, limb alignment and clinical outcomes did not significantly differ between the groups. Cartilage defects and total restored areas were significantly larger in the hUCB-MSC group (7.2 ± 1.9 vs. 5.2 ± 2.1 cm2, p = 0.023; 4.5 ± 1.4 vs. 3.0 ± 1.6 cm2, p = 0.035). The proportion of moderate-to-strong positive type II collagen staining was significantly higher in the hUCB-MSC group compared to that in the microdrilled group (93.3% vs. 60%, respectively). Rigidity upon probing resembled that of normal cartilage tissue more in the hUCB-MSC group (86.7% vs. 50.0%, p = 0.075). Histological findings revealed a higher proportion of hyaline cartilage in the group with implanted hUCB-MSC (p = 0.041).

CONCLUSION

hUCB-MSC implantation showed comparable clinical outcomes to those of microdrilling as supplementary cartilage procedures combined with HTO in the short term, despite the significantly larger cartilage defect in the hUCB-MSC group. The repaired cartilage after hUCB-MSC implantation showed greater hyaline-type cartilage with rigidity than that after microdrilling.

LEVEL OF EVIDENCE

Level II, Prospective Comparative Cohort Study.

Impact of Viscosity on Human Hepatoma Spheroids in Soft Core-Shell Microcapsules

The extracellular environment regulates the structures and functions of cells, from the molecular to the tissue level. However, the underlying mechanisms influencing the organization and adaptation of cancer in three-dimensional (3D) environments are not yet fully understood. In this study, the influence of the viscosity of the environment is investigated on the mechanical adaptability of human hepatoma cell (HepG2) spheroids in vitro, using 3D microcapsule reactors formed with droplet-based microfluidics. To mimic the environment with different mechanical properties, HepG2 cells are encapsulated in alginate core-shell reservoirs (i.e., microcapsules) with different core viscosities tuned by incorporating carboxymethylcellulose. The significant changes in cell and spheroid distribution, proliferation, and cytoskeleton are observed and quantified. Importantly, changes in the expression and distribution of F-actin and keratin 8 indicate the relation between spheroid stiffness and viscosity of the surrounding medium. The increase of F-actin levels in the viscous medium can indicate an enhanced ability of tumor cells to traverse dense tissue. These results demonstrate the ability of cancer cells to dynamically adapt to the changes in extracellular viscosity, which is an important physical cue regulating tumor development, and thus of relevance in cancer biology.

Strategies for Constructing Tissue-Engineered Fat for Soft Tissue Regeneration

BACKGROUND

Repairing soft tissue defects caused by inflammation, tumors, and trauma remains a major challenge for surgeons. Adipose tissue engineering (ATE) provides a promising way to solve this problem.

METHODS

This review summarizes the current ATE strategies for soft tissue reconstruction, and introduces potential construction methods for ATE.

RESULTS

Scaffold-based and scaffold-free strategies are the two main approaches in ATE. Although several of these methods have been effective clinically, both scaffold-based and scaffold-free strategies have limitations. The third strategy is a synergistic tissue engineering strategy and combines the advantages of scaffold-based and scaffold-free strategies.

CONCLUSION

Personalized construction, stable survival of reconstructed tissues and functional recovery of organs are future goals of building tissue-engineered fat for ATE.

Association between silicosis and autoimmune disease

PURPOSE OF REVIEW

There is a well established association between silica inhalational exposure and autoimmune disease, particularly in the context of intense exposure. We will provide in this article an update overview of new sources of silica dust exposure, with evidences of mechanisms from human and animal studies for association between silica and autoimmune diseases, their early detection of silicosis and new options for treatment.

RECENT FINDINGS

New industries such as jewelry polishing, denim jean production, fabrication of artificial stone benchtops, glass manufacturing and glassware has led to re-emergence of silicosis around the world. Silicosis with long term exposure to dust containing crystalline silica has been examined as a possible risk factor with respect to several autoimmune diseases as scleroderma, rheumatoid arthritis, lupus erythematosus, and some types of small vessel vasculitis with renal involvement. The dust may act to promote or accelerate disease development, requiring some other factors to break immune tolerance or initiate autoimmunity. Autophagy, apoptosis, or pyroptosis-related signaling pathways have also been suggested to contribute to the formation of those pathways with coordination of environmental co-exposure that can magnify autoimmune vulnerability.

SUMMARY

Better understanding the mechanisms that involve silica -induced autoimmune diseases may contribute to early diagnosis.

Immune regulation enhances osteogenesis and angiogenesis using an injectable thiolated hyaluronic acid hydrogel with lithium-doped nano-hydroxyapatite (Li-nHA) delivery for osteonecrosis

Osteonecrosis is a devastating orthopedic disease in clinic that generally occurs in the femoral head associating with corticosteroid use up to 49 % in patients. In particular, glucocorticoids induced osteonecrosis of the femoral head is closely related to the local immune response that characterized by abnormal macrophage activation and inflammatory cell infiltration at the necrotic site, forming a pro-inflammatory microenvironment dominated by M1 macrophages, and thus leads to failure of bone repair and regeneration. Here, we report a bone regeneration strategy that constructs an immune regulatory biomaterial platform using an injectable thiolated hyaluronic acid hydrogel with lithium-doped nano-hydroxyapatite (Li-nHA@Gel) delivery for osteonecrosis treatment. Li-nHA@Gel achieved a sustain and longterm release of Li ions, which might enhance M2 macrophage polarization through the activation of the JAK1/STAT6/STAT3 signaling pathway, and the following induced pro-repair immune microenvironment mediated the enhancement of the osteogenic and angiogenic differentiation. Moreover, both in vitro and in vivo studies indicated that Li-nHA@Gel enhanced M2 macrophage polarization, osteogenesis, and angiogenesis, and thus promoted the bone and blood vessel formation. Taken together, this novel bone immunomodulatory biomaterial platform that promotes bone regeneration by enhancing M2 macrophage polarization, osteogenesis, and angiogenesis could be a promising strategy for osteonecrosis treatment.

Stem Cell-Based Strategies: The Future Direction of Bioartificial Liver Development

Acute liver failure (ALF) results from severe liver damage or end-stage liver disease. It is extremely fatal and causes serious health and economic burdens worldwide. Once ALF occurs, liver transplantation (LT) is the only definitive and recommended treatment; however, LT is limited by the scarcity of liver grafts. Consequently, the clinical use of bioartificial liver (BAL) has been proposed as a treatment strategy for ALF. Human primary hepatocytes are an ideal cell source for these methods. However, their high demand and superior viability prevent their widespread use. Hence, finding alternatives that meet the seed cell quality and quantity requirements is imperative. Stem cells with self-renewing, immunogenic, and differentiative capacities are potential cell sources. MSCs and its secretomes encompass a spectrum of beneficial properties, such as anti-inflammatory, immunomodulatory, anti-ROS (reactive oxygen species), anti-apoptotic, pro-metabolomic, anti-fibrogenesis, and pro-regenerative attributes. This review focused on the recent status and future directions of stem cell-based strategies in BAL for ALF. Additionally, we discussed the opportunities and challenges associated with promoting such strategies for clinical applications.

Combining the potential of 3D printed buccal films and nanostructured lipid carriers for personalised cannabidiol delivery

Cannabidiol (CBD) has been recognized for its numerous therapeutic benefits, such as neuroprotection, anti-inflammatory effects, and cardioprotection. However, CBD has some limitations, including unpredictable pharmacokinetics and low oral bioavailability. To overcome the challenges associated with CBD delivery, we employed Design of Experiments (DoE), lipid carriers, and 3D printing techniques to optimize and develop buccal film loaded with CBD-NLCs. Three-factor Box-Behnken Design was carried out to optimise the NLCs and analyse the effect of independent factors on dependent factors. The emulsification-ultrasonication technique was used to prepare the NLCs. A pressure-assisted micro-syringe printing technique was used to produce the films. The produced films were studied for physicochemical, and mechanical properties, release profiles, and predicted in vivo performance. The observed particle size of the NLCs ranged from 12.17 to 84.91 nm whereas the PDI varied from 0.099 to 0.298. Lipid and sonication time positively affected the particle size whereas the surfactant concentration was inversely related. CBD was incorporated into the optimal formulation and the observed particle size, PDI, and zeta potential for the CBD-NLCs were 94.2 ± 0.47 nm, 0.11 ± 0.01 and - 11.8 ± 0.52 mV. Hydroxyethyl cellulose (HEC)-based gel containing the CBD-NLCs was prepared and used as a feed for 3D printing. The CBD-NLCs film demonstrated a slow and sustained in vitro release profile (84. 11 ± 7.02% in 6 h). The predicted AUC0-10 h, Cmax, and Tmax were 201.5 µg·h/L, 0.74 µg/L, and 1.28 h for a film with 0.4 mg of CBD, respectively. The finding demonstrates that a buccal film of CBD-NLCs can be fabricated using 3D printing.

Artificial intelligence-based three-dimensional templating for total joint arthroplasty planning: a scoping review

PURPOSE

The purpose of this review is to evaluate the current status of research on the application of artificial intelligence (AI)-based three-dimensional (3D) templating in preoperative planning of total joint arthroplasty.

METHODS

This scoping review followed the PRISMA, PRISMA-ScR guidelines, and five stage methodological framework for scoping reviews. Studies of patients undergoing primary or revision joint arthroplasty surgery that utilised AI-based 3D templating for surgical planning were included. Outcome measures included dataset and model development characteristics, AI performance metrics, and time performance. After AI-based 3D planning, the accuracy of component size and placement estimation and postoperative outcome data were collected.

RESULTS

Nine studies satisfied inclusion criteria including a focus on computed tomography (CT) or magnetic resonance imaging (MRI)-based AI templating for use in hip or knee arthroplasty. AI-based 3D templating systems reduced surgical planning time and improved implant size/position and imaging feature estimation compared to conventional radiographic templating. Several components of data processing and model development and testing were insufficiently covered in the studies included in this scoping review.

CONCLUSIONS

AI-based 3D templating systems have the potential to improve preoperative planning for joint arthroplasty surgery. This technology offers more accurate and personalized preoperative planning, which has potential to improve functional outcomes for patients. However, deficiencies in several key areas, including data handling, model development, and testing, can potentially hinder the reproducibility and reliability of the methods proposed. As such, further research is needed to definitively evaluate the efficacy and feasibility of these systems.

Atomic force microscopy in disease-related studies: Exploring tissue and cell mechanics

Despite significant progress in human medicine, certain diseases remain challenging to promptly diagnose and treat. Hence, the imperative lies in the development of more exhaustive criteria and tools. Tissue and cellular mechanics exhibit distinctive traits in both normal and pathological states, suggesting that "force" represents a promising and distinctive target for disease diagnosis and treatment. Atomic force microscopy (AFM) holds great promise as a prospective clinical medical device due to its capability to concurrently assess surface morphology and mechanical characteristics of biological specimens within a physiological setting. This review presents a comprehensive examination of the operational principles of AFM and diverse mechanical models, focusing on its applications in investigating tissue and cellular mechanics associated with prevalent diseases. The findings from these studies lay a solid groundwork for potential clinical implementations of AFM. RESEARCH HIGHLIGHTS: By examining the surface morphology and assessing tissue and cellular mechanics of biological specimens in a physiological setting, AFM shows promise as a clinical device to diagnose and treat challenging diseases.

MES-CTNet: A Novel Capsule Transformer Network Base on a Multi-Domain Feature Map for Electroencephalogram-Based Emotion Recognition

Emotion recognition using the electroencephalogram (EEG) has garnered significant attention within the realm of human-computer interaction due to the wealth of genuine emotional data stored in EEG signals. However, traditional emotion recognition methods are deficient in mining the connection between multi-domain features and fitting their advantages. In this paper, we propose a novel capsule Transformer network based on a multi-domain feature for EEG-based emotion recognition, referred to as MES-CTNet. The model's core consists of a multichannel capsule neural network(CapsNet) embedded with ECA (Efficient Channel Attention) and SE (Squeeze and Excitation) blocks and a Transformer-based temporal coding layer. Firstly, a multi-domain feature map is constructed by combining the space-frequency-time characteristics of the multi-domain features as inputs to the model. Then, the local emotion features are extracted from the multi-domain feature maps by the improved CapsNet. Finally, the Transformer-based temporal coding layer is utilized to globally perceive the emotion feature information of the continuous time slices to obtain a final emotion state. The paper fully experimented on two standard datasets with different emotion labels, the DEAP and SEED datasets. On the DEAP dataset, MES-CTNet achieved an average accuracy of 98.31% in the valence dimension and 98.28% in the arousal dimension; it achieved 94.91% for the cross-session task on the SEED dataset, demonstrating superior performance compared to traditional EEG emotion recognition methods. The MES-CTNet method, utilizing a multi-domain feature map as proposed herein, offers a broader observation perspective for EEG-based emotion recognition. It significantly enhances the classification recognition rate, thereby holding considerable theoretical and practical value in the EEG emotion recognition domain.

Progress of Micro-Stimulation Techniques to Alter Pigeons' Motor Behavior: A Review from the Perspectives of the Neural Basis and Neuro-Devices

Pigeons have natural advantages in robotics research, including a wide range of activities, low energy consumption, good concealment performance, strong long-distance weight bearing and continuous flight ability, excellent navigation, and spatial cognitive ability, etc. They are typical model animals in the field of animal robot research and have important application value. A hot interdisciplinary research topic and the core content of pigeon robot research, altering pigeon motor behavior using brain stimulation involves multiple disciplines including animal ethology, neuroscience, electronic information technology and artificial intelligence technology, etc. In this paper, we review the progress of altering pigeon motor behavior using brain stimulation from the perspectives of the neural basis and neuro-devices. The recent literature on altering pigeon motor behavior using brain stimulation was investigated first. The neural basis, structure and function of a system to alter pigeon motor behavior using brain stimulation are briefly introduced below. Furthermore, a classified review was carried out based on the representative research achievements in this field in recent years. Our summary and discussion of the related research progress cover five aspects including the control targets, control parameters, control environment, control objectives, and control system. Future directions that need to be further studied are discussed, and the development trend in altering pigeon motor behavior using brain stimulation is projected.

Entropy-Based Methods for Motor Fault Detection: A Review

In the signal analysis context, the entropy concept can characterize signal properties for detecting anomalies or non-representative behaviors in fiscal systems. In motor fault detection theory, entropy can measure disorder or uncertainty, aiding in detecting and classifying faults or abnormal operation conditions. This is especially relevant in industrial processes, where early motor fault detection can prevent progressive damage, operational interruptions, or potentially dangerous situations. The study of motor fault detection based on entropy theory holds significant academic relevance too, effectively bridging theoretical frameworks with industrial exigencies. As industrial sectors progress, applying entropy-based methodologies becomes indispensable for ensuring machinery integrity based on control and monitoring systems. This academic endeavor enhances the understanding of signal processing methodologies and accelerates progress in artificial intelligence and other modern knowledge areas. A wide variety of entropy-based methods have been employed for motor fault detection. This process involves assessing the complexity of measured signals from electrical motors, such as vibrations or stator currents, to form feature vectors. These vectors are then fed into artificial-intelligence-based classifiers to distinguish between healthy and faulty motor signals. This paper discusses some recent references to entropy methods and a summary of the most relevant results reported for fault detection over the last 10 years.

Microelement strontium and human health: comprehensive analysis of the role in inflammation and non-communicable diseases (NCDs)

Strontium (Sr), a trace element with a long history and a significant presence in the Earth's crust, plays a critical yet often overlooked role in various biological processes affecting human health. This comprehensive review explores the multifaceted implications of Sr, especially in the context of non-communicable diseases (NCDs) such as cardiovascular diseases, osteoporosis, hypertension, and diabetes mellitus. Sr is predominantly acquired through diet and water and has shown promise as a clinical marker for calcium absorption studies. It contributes to the mitigation of several NCDs by inhibiting oxidative stress, showcasing antioxidant properties, and suppressing inflammatory cytokines. The review delves deep into the mechanisms through which Sr interacts with human physiology, emphasizing its uptake, metabolism, and potential to prevent chronic conditions. Despite its apparent benefits in managing bone fractures, hypertension, and diabetes, current research on Sr's role in human health is not exhaustive. The review underscores the need for more comprehensive studies to solidify Sr's beneficial associations and address the gaps in understanding Sr intake and its optimal levels for human health.

Optimization of a tunable process for rapid production of calcium phosphate microparticles using a droplet-based microfluidic platform

Calcium phosphate (CaP) biomaterials are amongst the most widely used synthetic bone graft substitutes, owing to their chemical similarities to the mineral part of bone matrix and off-the-shelf availability. However, their ability to regenerate bone in critical-sized bone defects has remained inferior to the gold standard autologous bone. Hence, there is a need for methods that can be employed to efficiently produce CaPs with different properties, enabling the screening and consequent fine-tuning of the properties of CaPs towards effective bone regeneration. To this end, we propose the use of droplet microfluidics for rapid production of a variety of CaP microparticles. Particularly, this study aims to optimize the steps of a droplet microfluidic-based production process, including droplet generation, in-droplet CaP synthesis, purification and sintering, in order to obtain a library of CaP microparticles with fine-tuned properties. The results showed that size-controlled, monodisperse water-in-oil microdroplets containing calcium- and phosphate-rich solutions can be produced using a flow-focusing droplet-generator microfluidic chip. We optimized synthesis protocols based on in-droplet mineralization to obtain a range of CaP microparticles without and with inorganic additives. This was achieved by adjusting synthesis parameters, such as precursor concentration, pH value, and aging time, and applying heat treatment. In addition, our results indicated that the synthesis and fabrication parameters of CaPs in this method can alter the microstructure and the degradation behavior of CaPs. Overall, the results highlight the potential of the droplet microfluidic platform for engineering CaP microparticle biomaterials with fine-tuned properties.

Effects of Sitting and Supine Positions on Tongue Color as Measured by Tongue Image Analyzing System and Its Relation to Biometric Information

Tongue diagnosis is one of the important diagnostic methods in Kampo (traditional Japanese) medicine, in which the color and shape of the tongue are used to determine the patient's constitution and systemic symptoms. Tongue diagnosis is performed with the patient in the sitting or supine positions; however, the differences in tongue color in these two different positions have not been analyzed. We developed tongue image analyzing system (TIAS), which can quantify tongue color by capturing tongue images in the sitting and supine positions. We analyzed the effects on tongue color in two different body positions. Tongue color was quantified as L∗a∗b∗ from tongue images of 18 patients in two different body positions by taking images with TIAS. The CIEDE 2000 color difference equation (ΔE00) was used to assess the difference in tongue color in two different body positions. Correlations were also determined between ΔE00, physical characteristics, and laboratory test values. The mean and median ΔE00 for 18 patients were 2.85 and 2.34, respectively. Of these patients, 77.8% had a ΔE00 < 4.1. A weak positive correlation was obtained between ΔE00 and systolic blood pressure and fasting plasma glucose. Approximately 80% of patients' tongue color did not change between the sitting and supine positions. This indicates that the diagnostic results of tongue color are trustworthy even if medical professionals perform tongue diagnosis in two different body positions.

Long-term observation of polycaprolactone small-diameter vascular grafts with thickened outer layer and heparinized inner layer in rabbit carotid arteries

In our previous study, the pristine bilayer small-diameterin situtissue engineered vascular grafts (pTEVGs) were electrospun from a heparinized polycaprolactone (PCL45k) as an inner layer and a non-heparinized PCL80k as an outer layer in the thickness of about 131 μm and 202 μm, respectively. However, the hydrophilic enhancement of inner layer stemmed from the heparinization accelerated the degradation of grafts leading to the early formation of arterial aneurysms in a period of 3 months, severely hindering the perennial observation of the neo-tissue regeneration, host cell infiltration and graft remodeling in those implanted pTEVGs. Herein to address this drawback, the thickness of the outer layers was increased with PCL80k to around 268 μm, while the inner layer remained unchangeable. The thickened TEVGs named as tTEVGs were evaluated in six rabbits via a carotid artery interpositional model for a period of 9 months. All the animals kept alive and the grafts remained patent until explantation except for one whose one side of arterial blood vessels was occluded after an aneurysm occurred at 6 months. Although a significant degradation was observed in the implanted grafts at 9 month, the occurrence of aneurysms was obviously delayed compared to pTEVGs. The tissue stainings indicated that the endothelial cell remodeling was substantially completed by 3 months, while the regeneration of elastin and collagen remained smaller and unevenly distributed in comparison to autologous vessels. Additionally, the proliferation of macrophages and smooth muscle cells reached the maximum by 3 months. These tTEVGs possessing a heparinized inner layer and a thickened outer layer exhibited good patency and significantly delayed onset time of aneurysms.

Causal association between thyroid dysfunction and sepsis: a two-sample mendelian randomization study

Background

The causal association between thyroid dysfunction (including hyperthyroidism and hypothyroidism) and sepsis is controversial in previous studies. Therefore, we used Mendelian randomization (MR) to explore the causal association between hyperthyroidism or hypothyroidism and the susceptibility to four distinct subtypes of sepsis (streptococcal sepsis, puerperal sepsis, asthma-associated pneumonia or sepsis, and other sepsis).

Methods

In our research, we conducted two-sample Mendelian randomization (MR) analyses utilizing publicly available genome-wide association studies (GWAS) data from Sakaue et al. and the Finnish database to investigate the potential causal associations between hyperthyroidism, hypothyroidism, and each of the four distinct subtypes of sepsis, in addition to reverse MR analyses of the positive results to examine the existence of reverse causality.

Results

Genetic hypothyroidism was causally related to the development of asthma-associated pneumonia or sepsis (ORIVW: 1.097, 95% CI: 1.024 to 1.174, P = 0.008); hypothyroidism was significantly associated with the development of other sepsis (ORIVW: 1.070, 95% CI: 1.028 to 1.115, P < 0.001). In addition, sensitivity analysis substantiated the robustness of these two MR findings, with no evidence of horizontal pleiotropy observed (P > 0.05). MR Egger regression analysis demonstrated no heterogeneity between instrumental variables (IVs). Inverse MR results confirmed no reverse causality between hypothyroidism and asthma-associated pneumonia or sepsis, or between hypothyroidism and other sepsis. The findings of this study also unveiled that there is no evidence of a causal link between hypothyroidism and the development of streptococcal sepsis or puerperal sepsis. Additionally, the research provided evidence indicating the absence of a causal relationship between hyperthyroidism and streptococcal sepsis, puerperal sepsis, asthma-associated pneumonia or sepsis, and other sepsis.

Conclusions

This study identified a causal link between hypothyroidism and the occurrence of asthma-associated pneumonia or sepsis, and other sepsis, but not with the development of streptococcal sepsis and puerperal sepsis. Moreover, our findings did not reveal any causal association between hyperthyroidism and streptococcal sepsis, puerperal sepsis, asthma-associated pneumonia or sepsis, and other sepsis.

Algorithmic detection of sleep-disordered breathing using respiratory signals: a systematic review

Background and Objective. Sleep-disordered breathing (SDB) poses health risks linked to hypertension, cardiovascular disease, and diabetes. However, the time-consuming and costly standard diagnostic method, polysomnography (PSG), limits its wide adoption and leads to underdiagnosis. To tackle this, cost-effective algorithms using single-lead signals (like respiratory, blood oxygen, and electrocardiogram) have emerged. Despite respiratory signals being preferred for SDB assessment, a lack of comprehensive reviews addressing their algorithmic scope and performance persists. This paper systematically reviews 2012-2022 literature, covering signal sources, processing, feature extraction, classification, and application, aiming to bridge this gap and provide future research references.Methods. This systematic review followed the registered PROSPERO protocol (CRD42022385130), initially screening 342 papers, with 32 studies meeting data extraction criteria.Results. Respiratory signal sources include nasal airflow (NAF), oronasal airflow (OAF), and respiratory movement-related signals such as thoracic respiratory effort (TRE) and abdominal respiratory effort (ARE). Classification techniques include threshold rule-based methods (8), machine learning models (13), and deep learning models (11). The NAF-based algorithm achieved the highest average accuracy at 94.11%, surpassing 78.19% for other signals. Hypopnea detection sensitivity with single-source respiratory signals remained modest, peaking at 73.34%. The TRE and ARE signals proved to be reliable in identifying different types of SDB because distinct respiratory disorders exhibited different patterns of chest and abdominal motion.Conclusions. Multiple detection algorithms have been widely applied for SDB detection, and their accuracy is closely related to factors such as signal source, signal processing, feature selection, and model selection.

Biofabrication of engineered blood vessels for biomedical applications

To successfully engineer large-sized tissues, establishing vascular structures is essential for providing oxygen, nutrients, growth factors and cells to prevent necrosis at the core of the tissue. The diameter scale of the biofabricated vasculatures should range from 100 to 1,000 µm to support the mm-size tissue while being controllably aligned and spaced within the diffusion limit of oxygen. In this review, insights regarding biofabrication considerations and techniques for engineered blood vessels will be presented. Initially, polymers of natural and synthetic origins can be selected, modified, and combined with each other to support maturation of vascular tissue while also being biocompatible. After they are shaped into scaffold structures by different fabrication techniques, surface properties such as physical topography, stiffness, and surface chemistry play a major role in the endothelialization process after transplantation. Furthermore, biological cues such as growth factors (GFs) and endothelial cells (ECs) can be incorporated into the fabricated structures. As variously reported, fabrication techniques, especially 3D printing by extrusion and 3D printing by photopolymerization, allow the construction of vessels at a high resolution with diameters in the desired range. Strategies to fabricate of stable tubular structures with defined channels will also be discussed. This paper provides an overview of the many advances in blood vessel engineering and combinations of different fabrication techniques up to the present time.

Machine learning-based prediction of proteins' architecture using sequences of amino acids and structural alphabets

In addition to the growth of protein structures generated through wet laboratory experiments and deposited in the PDB repository, AlphaFold predictions have significantly contributed to the creation of a much larger database of protein structures. Annotating such a vast number of structures has become an increasingly challenging task. CATH is widely recognized as one the most common platforms for addressing this challenge, as it classifies proteins based on their structural and evolutionary relationships, offering the scientific community an invaluable resource for uncovering various properties, including functional annotations. While CATH annotation involves - to some extent - human intervention, keeping up with the classification of the rapidly expanding repositories of protein structures has become exceedingly difficult. Therefore, there is a pressing need for a fully automated approach. On the other hand, the abundance of protein sequences stemming from next generation sequencing technologies, lacking structural annotations, presents an additional challenge to the scientific community. Consequently, 'pre-annotating' protein sequences with structural features, ensuring a high level of precision, could prove highly advantageous. In this paper, after a thorough investigation, we introduce a novel machine-learning model capable of classifying any protein domain, whether it has a known structure or not, into one of the 40 main CATH Architectures. We achieve an F1 Score of 0.92 using only the amino acid sequence and a score of 0.94 using both the sequence of amino acids and the sequence of structural alphabets.Communicated by Ramaswamy H. Sarma.

Sequential Approach for Water Purification Using Seashell-Derived Calcium Oxide through Disinfection and Flocculation with Polyphosphate for Chemical Pollutant Removal

Safe water supply is usually inadequate in areas without water treatment plants and even in a city under emergency conditions due to a disaster, even though safe water is essential for drinking and other various purposes. The purification of surface water from a river, lake, or pond requires disinfection and removal of chemical pollutants. In this study, we report a water purification strategy using seashell-derived calcium oxide (CaO) via disinfection and subsequent flocculation with polyphosphate for chemical pollutant removal. Seashell-derived CaO at a concentration (2 g L-1) higher than its saturation concentration caused the >99.999% inactivation of bacteria, mainly due to the alkalinity of calcium hydroxide (Ca(OH)2) produced by hydration. After the disinfection, the addition of sodium polyphosphate at 2 g L-1 allowed for the flocculation of CaO/Ca(OH)2 particles with adsorbing chemical pollutants, such as Congo red, dichlorodiphenyltrichloroethane, di(2-ethylhexyl)phthalate, and polychlorinated biphenyls, for removing these pollutants; purified water was obtained through filtration. Although this purified water was initially highly alkaline (pH ∼ 12.5), its pH decreased into a weak alkaline region (pH ∼ 9) during exposure to ambient air by absorbing carbon dioxide from the air with the precipitating calcium carbonate. The advantages of this water purification strategy include the fact that the saturation of CaO/Ca(OH)2 potentially serves as a visual indicator of disinfection, that the flocculation by polyphosphate removes excessive CaO/Ca(OH)2 as well as chemical pollutants, and that the high pH and Ca2+ concentrations in the resulting purified water are readily decreased. Our findings suggest the usability of seashell-derived material-polymer assemblies for water purification, especially under emergency conditions due to disasters.

Celiac disease diagnosis from endoscopic images based on multi-scale adaptive hybrid architecture model

Objective. Celiac disease (CD) has emerged as a significant global public health concern, exhibiting an estimated worldwide prevalence of approximately 1%. However, existing research pertaining to domestic occurrences of CD is confined mainly to case reports and limited case analyses. Furthermore, there is a substantial population of undiagnosed patients in the Xinjiang region. This study endeavors to create a novel, high-performance, lightweight deep learning model utilizing endoscopic images from CD patients in Xinjiang as a dataset, with the intention of enhancing the accuracy of CD diagnosis.Approach. In this study, we propose a novel CNN-Transformer hybrid architecture for deep learning, tailored to the diagnosis of CD using endoscopic images. Within this architecture, a multi-scale spatial adaptive selective kernel convolution feature attention module demonstrates remarkable efficacy in diagnosing CD. Within this module, we dynamically capture salient features within the local channel feature map that correspond to distinct manifestations of endoscopic image lesions in the CD-affected areas such as the duodenal bulb, duodenal descending segment, and terminal ileum. This process serves to extract and fortify the spatial information specific to different lesions. This strategic approach facilitates not only the extraction of diverse lesion characteristics but also the attentive consideration of their spatial distribution. Additionally, we integrate the global representation of the feature map obtained from the Transformer with the locally extracted information via convolutional layers. This integration achieves a harmonious synergy that optimizes the diagnostic prowess of the model.Main results. Overall, the accuracy, specificity, F1-Score, and precision in the experimental results were 98.38%, 99.04%, 98.66% and 99.38%, respectively.Significance. This study introduces a deep learning network equipped with both global feature response and local feature extraction capabilities. This innovative architecture holds significant promise for the accurate diagnosis of CD by leveraging endoscopic images captured from diverse anatomical sites.

3D Printing of Alginate/Chitosan-Based Scaffold Empowered by Tyrosol-Loaded Niosome for Wound Healing Applications: In Vitro and In Vivo Performances

This study introduces a tyrosol-loaded niosome integrated into a chitosan-alginate scaffold (Nio-Tyro@CS-AL), employing advanced electrospinning and 3D printing techniques for wound healing applications. The niosomes, measuring 185.40 ± 6.40 nm with a polydispersity index of 0.168 ± 0.012, encapsulated tyrosol with an efficiency of 77.54 ± 1.25%. The scaffold's microsized porous structure (600-900 μm) enhances water absorption, promoting cell adhesion, migration, and proliferation. Mechanical property assessments revealed the scaffold's enhanced resilience, with niosomes increasing the compressive strength, modulus, and strain to failure, indicative of its suitability for wound healing. Controlled tyrosol release was demonstrated in vitro, essential for therapeutic efficacy. The scaffold exhibited significant antibacterial activity against Pseudomonas aeruginosa and Staphylococcus aureus, with substantial biofilm inhibition and downregulation of bacterial genes (ndvb and icab). A wound healing assay highlighted a notable increase in MMP-2 and MMP-9 mRNA expression and the wound closure area (69.35 ± 2.21%) in HFF cells treated with Nio-Tyro@CS-AL. In vivo studies in mice confirmed the scaffold's biocompatibility, showing no significant inflammatory response, hypertrophic scarring, or foreign body reaction. Histological evaluations revealed increased fibroblast and macrophage activity, enhanced re-epithelialization, and angiogenesis in wounds treated with Nio-Tyro@CS-AL, indicating effective tissue integration and repair. Overall, the Nio-Tyro@CS-AL scaffold presents a significant advancement in wound-healing materials, combining antibacterial properties with enhanced tissue regeneration, and holds promising potential for clinical applications in wound management.