Bioengineering, Volume 11, Issue 6 (June 2024) – 114 articles

(1) Background: When placing implants in the maxillary posterior region with insufficient alveolar bone, a maxillary sinus elevation is necessary. Autogenous bone, though biologically ideal, poses risks and discomfort due to donor site harvesting. Block-type autogenous tooth bone graft material, made from the patient’s own extracted tooth, offers similar biological stability without these drawbacks. (2) Methods: This study observed the progress of 19 implant patients who were treated with maxillary sinus elevation procedures using block-type autogenous tooth bone graft material at the Daegu Catholic University Medical Center. Extracted teeth were processed into demineralized tooth block bone. After elevating the sinus membrane, implants and the tooth bone graft material were placed in the space, and the bony window was repositioned. Postoperative evaluations through clinical observation and radiographic imaging assessed sinus membrane elevation, alveolar bone height increase, and implant osseointegration. (3) Results: Results showed proportional increases in alveolar bone height to the graft material size, with long-term stability. No postoperative complications occurred, even with sinus membrane perforation, and implants remained stable. (4) Conclusions: The study concludes that maxillary sinus lifts using block-type autogenous tooth bone graft material provide excellent bone induction and biocompatibility, making this a highly beneficial method for both dentists and patients. Full article

The rapid detection of the spore form of Clostridioides difficile has remained a challenge for clinicians. To address this, we have developed a novel, precise, microwave-enhanced approach for near-spontaneous release of DNA from C. difficile spores via a bespoke microwave lysis platform. C. difficile spores were microwave-irradiated for 5 s in a pulsed microwave electric field at 2.45 GHz to lyse the spore and bacteria in each sample, which was then added to a screen-printed electrode and electrochemical DNA biosensor assay system to identify presence of the pathogen’s two toxin genes. The microwave lysis method released both single-stranded and double-stranded genome DNA from the bacterium at quantifiable concentrations between 0.02 μg/mL to 250 μg/mL allowing for subsequent downstream detection in the biosensor. The electrochemical bench-top system comprises of oligonucleotide probes specific to conserved regions within tcdA and tcdB toxin genes of C. difficile and was able to detect 800 spores of C. difficile within 300 µL of unprocessed human stool samples in under 10 min. These results demonstrate the feasibility of using a solid-state power generated, pulsed microwave electric field to lyse and release DNA from human stool infected with C. difficile spores. This rapid microwave lysis method enhanced the rapidity of subsequent electrochemical detection in the development of a rapid point-of-care biosensor platform for C. difficile. Full article

Fatigue is believed to increase the risk of anterior cruciate ligament (ACL) injury by directly promoting high-risk biomechanics in the lower limbs. Studies have shown that dynamic taping can help normalize inadequate biomechanics during landings. This study aims to examine the effects of dynamic taping on landing biomechanics in fatigued football athletes. Twenty-seven high-school football athletes were recruited and randomly allocated to groups of either active taping or sham taping, with a crossover allocation two weeks later. In each group, the participants underwent a functional agility short-term fatigue protocol and were evaluated using the landing error scoring system before and after the fatigue protocol. The landing error scoring system (LESS) scores in the sham taping group increased from 4.24 ± 1.83 to 5.36 ± 2.00 (t = −2.07, p = 0.04, effect size = 0.61). In contrast, the pre–post difference did not reach statistical significance in the active taping group (from 4.24 ± 1.69 to 4.52 ± 1.69, t = −1.50, p = 0.15, effect size 0.46). Furthermore, the pre–post changes between the sham and active taping groups were statistically significant (sham taping: 1.12 ± 1.20; active taping: 0.28 ± 0.94, p = 0.007). Dynamic taping, particularly using the spiral technique, appeared to mitigate faulty landing biomechanics in the fatigued athletes by reducing hip and knee flexion and increasing hip internal rotation during landing. These results suggest that dynamic taping can potentially offer protective benefits in landing mechanics, which could further be applied to prevent ACL injuries in fatigued athletes. Full article

The estimation of distances and angles is a routine part of an orthopedic surgical procedure. However, despite their prevalence, these steps are most often performed manually, heavily relying on the surgeon’s skill and experience. To address these issues, this study presents a sensor-equipped drill system which enables automatic estimation of the drilling angle and channel length. The angular accuracy and precision of the system were tested over a range of inclination angles and proved to be superior to the manual approach, with mean absolute errors ranging from 1.9 to 4.5 degrees for the manual approach, and from 0.6 to 1.3 degrees with the guided approach. When sensors were used for simultaneous estimation of both the inclination and anteversion angles, the obtained mean absolute errors were 0.35 ± 0.25 and 2 ± 1.33 degrees for the inclination and anteversion angles, respectively. Regarding channel length estimation, using measurements obtained with a Vernier caliper as a reference, the mean absolute error was 0.33 mm and the standard deviation of errors was 0.41 mm. The obtained results indicate a high potential of smart drill systems for improvement of accuracy and precision in orthopedic surgical procedures, enabling better patient clinical outcomes. Full article

Prostate cancer is a significant health concern with high mortality rates and substantial economic impact. Early detection plays a crucial role in improving patient outcomes. This study introduces a non-invasive computer-aided diagnosis (CAD) system that leverages intravoxel incoherent motion (IVIM) parameters for the detection and diagnosis of prostate cancer (PCa). IVIM imaging enables the differentiation of water molecule diffusion within capillaries and outside vessels, offering valuable insights into tumor characteristics. The proposed approach utilizes a two-step segmentation approach through the use of three U-Net architectures for extracting tumor-containing regions of interest (ROIs) from the segmented images. The performance of the CAD system is thoroughly evaluated, considering the optimal classifier and IVIM parameters for differentiation and comparing the diagnostic value of IVIM parameters with the commonly used apparent diffusion coefficient (ADC). The results demonstrate that the combination of central zone (CZ) and peripheral zone (PZ) features with the Random Forest Classifier (RFC) yields the best performance. The CAD system achieves an accuracy of 84.08% and a balanced accuracy of 82.60%. This combination showcases high sensitivity (93.24%) and reasonable specificity (71.96%), along with good precision (81.48%) and F1 score (86.96%). These findings highlight the effectiveness of the proposed CAD system in accurately segmenting and diagnosing PCa. This study represents a significant advancement in non-invasive methods for early detection and diagnosis of PCa, showcasing the potential of IVIM parameters in combination with machine learning techniques. This developed solution has the potential to revolutionize PCa diagnosis, leading to improved patient outcomes and reduced healthcare costs. Full article

In recent years, the use of smartphones and other wireless technology in medical care has developed rapidly. However, in some cases, especially for pediatric medical problems, the reliability of information accessed by mobile health technology remains debatable. The main aim of this paper is to evaluate the relevance of smartphone applications in the detection and diagnosis of pediatric medical conditions for which the greatest number of applications have been developed. This is the case of smartphone applications developed for the diagnosis of acute otitis media, otitis media with effusion, hearing impairment, obesity, amblyopia, and vision screening. In some cases, the information given by these applications has significantly improved the diagnostic ability of physicians. However, distinguishing between applications that can be effective and those that may lead to mistakes can be very difficult. This highlights the importance of a careful application selection before including smartphone-based artificial intelligence in everyday clinical practice. Full article

Medical imaging and deep learning models are essential to the early identification and diagnosis of brain cancers, facilitating timely intervention and improving patient outcomes. This research paper investigates the integration of YOLOv5, a state-of-the-art object detection framework, with non-local neural networks (NLNNs) to improve brain tumor detection’s robustness and accuracy. This study begins by curating a comprehensive dataset comprising brain MRI scans from various sources. To facilitate effective fusion, the YOLOv5 and NLNNs, K-means+, and spatial pyramid pooling fast+ (SPPF+) modules are integrated within a unified framework. The brain tumor dataset is used to refine the YOLOv5 model through the application of transfer learning techniques, adapting it specifically to the task of tumor detection. The results indicate that the combination of YOLOv5 and other modules results in enhanced detection capabilities in comparison to the utilization of YOLOv5 exclusively, proving recall rates of 86% and 83% respectively. Moreover, the research explores the interpretability aspect of the combined model. By visualizing the attention maps generated by the NLNNs module, the regions of interest associated with tumor presence are highlighted, aiding in the understanding and validation of the decision-making procedure of the methodology. Additionally, the impact of hyperparameters, such as NLNNs kernel size, fusion strategy, and training data augmentation, is investigated to optimize the performance of the combined model. Full article

The decision to extubate patients on invasive mechanical ventilation is critical; however, clinician performance in identifying patients to liberate from the ventilator is poor. Machine Learning-based predictors using tabular data have been developed; however, these fail to capture the wide spectrum of data available. Here, we develop and validate a deep learning-based model using routinely collected chest X-rays to predict the outcome of attempted extubation. We included 2288 serial patients admitted to the Medical ICU at an urban academic medical center, who underwent invasive mechanical ventilation, with at least one intubated CXR, and a documented extubation attempt. The last CXR before extubation for each patient was taken and split 79/21 for training/testing sets, then transfer learning with k-fold cross-validation was used on a pre-trained ResNet50 deep learning architecture. The top three models were ensembled to form a final classifier. The Grad-CAM technique was used to visualize image regions driving predictions. The model achieved an AUC of 0.66, AUPRC of 0.94, sensitivity of 0.62, and specificity of 0.60. The model performance was improved compared to the Rapid Shallow Breathing Index (AUC 0.61) and the only identified previous study in this domain (AUC 0.55), but significant room for improvement and experimentation remains. Full article

(1) Background: This study aimed to integrate an augmented reality (AR) image-guided surgery (IGS) system, based on preoperative cone beam computed tomography (CBCT) scans, into clinical practice. (2) Methods: In preclinical and clinical surgical setups, an AR-guided visualization system based on Microsoft’s HoloLens 2 was assessed for complex lower third molar (LTM) extractions. In this study, the system’s potential intraoperative feasibility and usability is described first. Preparation and operating times for each procedure were measured, as well as the system’s usability, using the System Usability Scale (SUS). (3) Results: A total of six LTMs (n = 6) were analyzed, two extracted from human cadaver head specimens (n = 2) and four from clinical patients (n = 4). The average preparation time was 166 ± 44 s, while the operation time averaged 21 ± 5.9 min. The overall mean SUS score was 79.1 ± 9.3. When analyzed separately, the usability score categorized the AR-guidance system as “good” in clinical patients and “best imaginable” in human cadaver head procedures. (4) Conclusions: This translational study analyzed the first successful and functionally stable application of the HoloLens technology for complex LTM extraction in clinical patients. Further research is needed to refine the technology’s integration into clinical practice to improve patient outcomes. Full article

Prostate cancer remains a prevalent health concern, emphasizing the critical need for early diagnosis and precise treatment strategies to mitigate mortality rates. The accurate prediction of cancer grade is paramount for timely interventions. This paper introduces an approach to prostate cancer grading, framing it as a classification problem. Leveraging ResNet models on multi-scale patch-level digital pathology and the Diagset dataset, the proposed method demonstrates notable success, achieving an accuracy of 0.999 in identifying clinically significant prostate cancer. The study contributes to the evolving landscape of cancer diagnostics, offering a promising avenue for improved grading accuracy and, consequently, more effective treatment planning. By integrating innovative deep learning techniques with comprehensive datasets, our approach represents a step forward in the pursuit of personalized and targeted cancer care. Full article

Chemical compounds, such as the CS gas employed in military operations, have a number of characteristics that impact the ecosystem by upsetting its natural balance. In this work, the toxicity limit and microorganism’s reaction to the oxidative stress induced by O-chlorobenzylidenemalonitrile, a chemical found in CS gas, were assessed in relation to the green algae Chlorella pyrenoidosa. A number of parameters, including the cell growth curve, the percent inhibition in yield, the dry cell weight, the percentage viability and productivity of algal biomass flocculation activity, and the change in oxygen production, were analyzed in order to comprehend the toxicological mechanisms of O-chlorobenzylidenemalonitrile on algal culture. Using fluorescence and Fourier transform infrared spectroscopy (FTIR), the content of chlorophyll pigments was determined. The values obtained for pH during the adaptation period of the C. pyrenoidosa culture were between 6.0 and 6.8, O₂ had values between 6.5 and 7.0 mg/L, and the conductivity was 165–210 µS/cm. For the 20 µg/mL O-chlorobenzylidenemalonitrile concentration, the cell viability percentage was over 97.4%, and for the 150 µg/mL O-chlorobenzylidenemalonitrile concentration was 74%. The EC_b50 value for C. pyrenoidosa was determined from the slope of the calibration curve; it was estimated by extrapolation to the value of 298.24 µg/mL. With the help of this study, basic information on the toxicity of O-chlorobenzylidenemalonitrile to aquatic creatures will be available, which will serve as a foundation for evaluating the possible effects on aquatic ecosystems. The management of the decontamination of the impacted areas could take the results into consideration. Full article

Physical inactivity represents a significant public health challenge globally. Mobile applications, particularly those utilizing augmented reality (AR), have emerged as innovative tools for promoting physical activity. However, a systematic evaluation of their efficacy is essential. This systematic review aims to evaluate and synthesize the evidence regarding the effectiveness and benefits of mobile applications with augmented reality in enhancing physical activity and improving health outcomes. A comprehensive search was conducted in Scopus, PubMed, WOS, and the Cochrane Library databases following PRISMA guidelines. Observational and interventional studies evaluating AR mobile applications for physical exercise were included, without restrictions on publication date or language. The search terms included “Mobile Applications”, “Augmented Reality”, “Physical Fitness”, “Exercise Therapy”, and “Health Behavior”. The methodological quality was assessed using the ROBINS tool. The review identified twelve eligible studies encompassing 5,534,661 participants. The findings indicated significant increases in physical activity and improvements in mental health associated with the use of AR applications, such as Pokémon GO. However, potential risk behaviors were also noted. The evidence suggests that AR interventions can effectively promote physical activity and enhance health. Nonetheless, further research is needed to address limitations and optimize their efficacy. Future interventions should be tailored to diverse cultural contexts to maximize benefits and mitigate risks. AR mobile applications hold promise for promoting physical activity and improving health outcomes. Strategies to optimize their effectiveness and address identified risks should be explored to fully realize their potential. Full article

Magnesium-based multicomponent alloys with different compositions, namely Mg₆₀Al₂₀Zn₅Cu₁₀Mn₅ (Mg60 alloy), Mg₇₀Al₁₅Zn₅Cu₅Mn₅ (Mg70 alloy), and Mg₈₀Al₅Cu₅Mn₅Zn₅ (Mg 80) alloys, were prepared using the disintegrated melt deposition technique. The DMD technique is a distinctive method that merges the benefits from gravity die casting and spray forming. This approach facilitates high solidification rates, process yields, and reduced metal wastage, resulting in materials with a fine microstructure and minimal porosity. Their potential as biodegradable materials was assessed through corrosion in different simulated body fluids (SBFs), microstructure, and cytotoxicity tests. It was observed that the Mg60 alloy exhibited low corrosion rates (~× 10⁻⁵ mm/year) in all SBF solutions, with a minor amount of corrosive products, and cracks were observed. This can be attributed to the formation of the Mg₃₂(AlZn)₄₉ phase and to its stability due to Mg(OH)₂ film, leading to excellent corrosion resistance when compared to the Mg70 and M80 alloys. Conversely, the Mg80 alloy exhibited high corrosion rates, along with more surface degradation and cracks, due to active intermetallic phases, such as Al₆Mn, Al₂CuMg, and Al₂Cu phases. The order of corrosion resistance for the Mg alloy was found to be ASS > HBSS > ABP > PBS. Further, in vitro cytotoxicity studies were carried out using MDA-MB-231 tumor cells. By comparing all three alloys, in terms of proliferation and vitality, the Mg80 alloy emerged as a promising material for implants, with potential antitumor activity. Full article

Medical imaging has allowed for significant advancements in the field of ultrasound procedures over the years. However, each imaging modality exhibits distinct limitations that differently affect their accuracy. It is imperative to ensure the quality of each modality to identify and eliminate these limitations. To achieve this, a tissue-mimicking material (TMM) phantom is utilised for validation. This study aims to perform a systematic analysis of tissue-mimicking materials used for creating ultrasound phantoms. We reviewed 234 studies on the use of TMM phantoms in ultrasound that were published from 2013 to 2023 from two research databases. Our focus was on studies that discussed TMMs’ properties and fabrication for ultrasound, elastography, and flow phantoms. The screening process led to the selection of 16 out of 234 studies to include in the analysis. The TMM ultrasound phantoms were categorised into three groups based on the solvent used; each group offers a broad range of physical properties. The water-based material most closely aligns with the properties of ultrasound. This study provides important information about the materials used for ultrasound phantoms. We also compared these materials to real human tissues and found that PVA matches most of the human tissues the best. Full article

Biophysical factors play a fundamental role in human embryonic development. Traditional in vitro models of organogenesis focused on the biochemical environment and did not consider the effects of mechanical forces on developing tissue. While most human tissue has a Young’s modulus in the low kilopascal range, the standard cell culture substrate, plasma-treated polystyrene, has a Young’s modulus of 3 gigapascals, making it 10,000–100,000 times stiffer than native tissues. Modern in vitro approaches attempt to recapitulate the biophysical niche of native organs and have yielded more clinically relevant models of human tissues. Since Clevers’ conception of intestinal organoids in 2009, the field has expanded rapidly, generating stem-cell derived structures, which are transcriptionally similar to fetal tissues, for nearly every organ system in the human body. For this reason, we conjecture that organoids will make their first clinical impact in fetal regenerative medicine as the structures generated ex vivo will better match native fetal tissues. Moreover, autologously sourced transplanted tissues would be able to grow with the developing embryo in a dynamic, fetal environment. As organoid technologies evolve, the resultant tissues will approach the structure and function of adult human organs and may help bridge the gap between preclinical drug candidates and clinically approved therapeutics. In this review, we discuss roles of tissue stiffness, viscoelasticity, and shear forces in organ formation and disease development, suggesting that these physical parameters should be further integrated into organoid models to improve their physiological relevance and therapeutic applicability. It also points to the mechanotransductive Hippo-YAP/TAZ signaling pathway as a key player in the interplay between extracellular matrix stiffness, cellular mechanics, and biochemical pathways. We conclude by highlighting how frontiers in physics can be applied to biology, for example, how quantum entanglement may be applied to better predict spontaneous DNA mutations. In the future, contemporary physical theories may be leveraged to better understand seemingly stochastic events during organogenesis. Full article

This study investigated the effects of different surface conditions on postural stability in response to unexpected perturbations. Thirty healthy adults underwent balance assessments on flat, incline ramp, balance pad, and balance pad on incline ramp surfaces. The center of pressure (COP) displacement in the mediolateral (ML) and anteroposterior (AP) directions, the velocity, and the area were measured. We found that the flat and ramp conditions resulted in significantly lower COP ML (F(3, 87) = 38.272, p < 0.001, ηp² = 0.569) and AP displacements (F(3, 87) = 89.177, p < 0.001, ηp² = 0.755), velocity (F(3, 87) = 89.177, p < 0.001, ηp² = 0.755), and area (F(3, 87) = 52.659, p < 0.001, ηp² = 0.645) compared to the balance pad and balance pad on ramp conditions (p < 0.05). The use of a balance pad, particularly on a ramp, significantly increased all the COP measurements, suggesting greater challenges to postural control. Through these findings, we demonstrate the adaptability and limitations of the human postural control system in response to varying surface conditions and perturbations. Full article

The significant growth of the global protein drug market, including fusion proteins, emphasizes the crucial role of optimizing amino acid sequences to enhance the productivity and bioefficacy. Among these fusion proteins, RBP-IIIA-IB, comprising retinol-binding protein in conjunction with the albumin domains, IIIA and IB, has displayed efficacy in alleviating liver fibrosis by inhibiting the activation of hepatic stellate cells (HSCs). This study aimed to address the issue of the low productivity in RBP-IIIA-IB. To induce structural changes, the linking sequence, EVDD, between domain IIIA and IB in RBP-IIIA-IB was modified to DGPG, AAAA, and GGPA. Among these, RBP-IIIA-AAAA-IB demonstrated an increase in yield (>4-fold) and a heightened inhibition of HSC activation. Furthermore, we identified amino acid residues that could form disulfide bonds when substituted with cysteine. Through the mutation of N453S-V480S in RBP-IIIA-AAAA-IB, the productivity further increased by over 9-fold, accompanied by an increase in anti-fibrotic activity. Overall, there was a more than 30-fold increase in the fusion protein’s yield. These findings demonstrate the effectiveness of modifying linker sequences and introducing extra disulfide bonds to improve both the production yield and biological efficacy of fusion proteins. Full article

Ultra-high-molecular-weight polyethylene (UHMWPE) components for orthopedic implants have historically been integrated into metal backings by direct-compression molding (DCM). However, metal backings are costly, stiffer than cortical bone, and may be associated with medical imaging distortion and metal release. Hybrid-manufactured DCM UHMWPE overmolded additively manufactured polyetheretherketone (PEEK) structural components could offer an alternative solution, but are yet to be explored. In this study, five different porous topologies (grid, triangular, honeycomb, octahedral, and gyroid) and three surface feature sizes (low, medium, and high) were implemented into the top surface of digital cylindrical specimens prior to being 3D printed in PEEK and then overmolded with UHMWPE. Separation forces were recorded as 1.97–3.86 kN, therefore matching and bettering the historical industry values (2–3 kN) recorded for DCM UHMWPE metal components. Infill topology affected failure mechanism (Type 1 or 2) and obtained separation forces, with shapes having greater sidewall numbers (honeycomb-60%) and interconnectivity (gyroid-30%) through their builds, tolerating higher transmitted forces. Surface feature size also had an impact on applied load, whereby those with low infill-%s generally recorded lower levels of performance vs. medium and high infill strategies. These preliminary findings suggest that hybrid-manufactured structural composites could replace metal backings and produce orthopedic implants with high-performing polymer–polymer interfaces. Full article

Urinary tract diseases are common in cats, and often require surgical reconstruction. Here, to explore the possibility of urinary tract reconstruction in cats using in-body tissue architecture (iBTA), biosheets fabricated using iBTA technology were implanted into the feline bladder and the regeneration process was histologically evaluated. The biosheets were prepared by embedding molds into the dorsal subcutaneous pouches of six cats for 2 months. A section of the bladder wall was removed, and the biosheets were sutured to the excision site. After 1 and 3 months of implantation, the biosheets were harvested and evaluated histologically. Implantable biosheets were formed with a success rate of 67%. There were no major complications following implantation, including tissue rejection, severe inflammation, or infection. Urinary incontinence was also not observed. Histological evaluation revealed the bladder lumen was almost entirely covered by urothelium after 1 month, with myofibroblast infiltration into the biosheets. After 3 months, the urothelium became multilayered, and mature myocytes and nerve fibers were observed at the implantation site. In conclusion, this study showed that tissue reconstruction using iBTA can be applied to cats, and that biosheets have the potential to be useful in both the structural and functional regeneration of the feline urinary tract. Full article

Quantitative and objective evaluation tools are essential for assessing the performance of machine learning (ML)-based magnetic resonance imaging (MRI) reconstruction methods. However, the commonly used fidelity metrics, such as mean squared error (MSE), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR), often fail to capture fundamental and clinically relevant MR image quality aspects. To address this, we propose evaluation of ML-based MRI reconstruction using digital image quality phantoms and automated evaluation methods. Our phantoms are based upon the American College of Radiology (ACR) large physical phantom but created in k-space to simulate their MR images, and they can vary in object size, signal-to-noise ratio, resolution, and image contrast. Our evaluation pipeline incorporates evaluation metrics of geometric accuracy, intensity uniformity, percentage ghosting, sharpness, signal-to-noise ratio, resolution, and low-contrast detectability. We demonstrate the utility of our proposed pipeline by assessing an example ML-based reconstruction model across various training and testing scenarios. The performance results indicate that training data acquired with a lower undersampling factor and coils of larger anatomical coverage yield a better performing model. The comprehensive and standardized pipeline introduced in this study can help to facilitate a better understanding of the performance and guide future development and advancement of ML-based reconstruction algorithms. Full article

The application of wearable electroencephalogram (EEG) devices is growing in brain–computer interfaces (BCI) owing to their good wearability and portability. Compared with conventional devices, wearable devices typically support fewer EEG channels. Devices with few-channel EEGs have been proven to be available for steady-state visual evoked potential (SSVEP)-based BCI. However, fewer-channel EEGs can cause the BCI performance to decrease. To address this issue, an attention-based complex spectrum–convolutional neural network (atten-CCNN) is proposed in this study, which combines a CNN with a squeeze-and-excitation block and uses the spectrum of the EEG signal as the input. The proposed model was assessed on a wearable 40-class dataset and a public 12-class dataset under subject-independent and subject-dependent conditions. The results show that whether using a three-channel EEG or single-channel EEG for SSVEP identification, atten-CCNN outperformed the baseline models, indicating that the new model can effectively enhance the performance of SSVEP-BCI with few-channel EEGs. Therefore, this SSVEP identification algorithm based on a few-channel EEG is particularly suitable for use with wearable EEG devices. Full article

This study aimed to investigate the effect of the transverse sinus (TS) stenosis (TSS) position caused by arachnoid granulation on patients with venous pulsatile tinnitus (VPT) and to further identify the types of TSS that are of therapeutic significance for patients. Multiphysics interaction models of six patients with moderate TSS caused by arachnoid granulation and virtual stent placement in TSS were reconstructed, including three patients with TSS located in the middle segment of the TS (group 1) and three patients with TTS in the middle and proximal involvement segment of the TS (group 2). The transient multiphysics interaction simulation method was applied to elucidate the differences in biomechanical and acoustic parameters between the two groups. The results revealed that the blood flow pattern at the TS and sigmoid sinus junction was significantly changed depending on the stenosis position. Preoperative patients had increased blood flow in the TSS region and TSS downstream where the blood flow impacted the vessel wall. In group 1, the postoperative blood flow pattern, average wall pressure, vessel wall vibration, and sound pressure level of the three patients were comparable to the preoperative state. However, the postoperative blood flow velocity decreased in group 2. The postoperative average wall pressure, vessel wall vibration, and sound pressure level of the three patients were significantly improved compared with the preoperative state. Intravascular intervention therapy should be considered for patients with moderate TSS caused by arachnoid granulations in the middle and proximal involvement segment of the TS. TSS might not be considered the cause of VPT symptoms in patients with moderate TSS caused by arachnoid granulation in the middle segment of the TS. Full article

(1) Background: Medical devices, especially neuromodulation devices, are often explanted for a variety of reasons. The removal process imparts significant forces on these devices, which may result in device fracture and tissue trauma. We hypothesized that a device’s form factor interfacing with tissue is a major driver of the force required to remove a device, and we isolated helical and linear electrode structures as a means to study atraumatic removal. (2) Methods: Ductile linear and helical microwire structure electrodes were fabricated from either Gold (Au) or Platinum–Iridium (Pt-Ir, 90-10). Removal forces were captured from synthetic gel models and following chronic implantation in rodent and porcine models. Devices were fully implanted in the animal models, requiring a small incision (<10 mm) and removal via tissue forceps. (3) Results: Helical devices were shown to result in significantly lower maximal removal forces in both synthetic gel and rodent studies compared to their linear counterparts. Chronically (1 yr.), the maximal removal force of helical devices remained under 7.30 N, for which the Platinum–Iridium device’s tensile failure force was 32.90 ± 2.09 N, resulting in a safety factor of 4.50. (4) Conclusion: An open-core helical structure that can freely elongate was shown to result in reduced removal forces both acutely and chronically. Full article

The continuous manufacturing of biologics offers significant advantages in terms of reducing manufacturing costs and increasing capacity, but it is not yet widely implemented by the industry due to major challenges in the automation, scheduling, process monitoring, continued process verification, and real-time control of multiple interconnected processing steps, which must be tightly controlled to produce a safe and efficacious product. The process produces a large amount of data from different sensors, analytical instruments, and offline analyses, requiring organization, storage, and analyses for process monitoring and control without compromising accuracy. We present a case study of a cyber–physical production system (CPPS) for the continuous manufacturing of mAbs that provides an automation infrastructure for data collection and storage in a data historian, along with data management tools that enable real-time analysis of the ongoing process using multivariate algorithms. The CPPS also facilitates process control and provides support in handling deviations at the process level by allowing the continuous train to re-adjust itself via a series of interconnected surge tanks and by recommending corrective actions to the operator. Successful steady-state operation is demonstrated for 55 h with end-to-end process automation and data collection via a range of in-line and at-line sensors. Following this, a series of deviations in the downstream unit operations, including affinity capture chromatography, cation exchange chromatography, and ultrafiltration, are monitored and tracked using multivariate approaches and in-process controls. The system is in line with Industry 4.0 and smart manufacturing concepts and is the first end-to-end CPPS for the continuous manufacturing of mAbs. Full article

Multivariate pattern analysis (MVPA) has played an extensive role in interpreting brain activity, which has been applied in studies with modalities such as functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) and Electroencephalography (EEG). The advent of wearable MEG systems based on optically pumped magnetometers (OPMs), i.e., OP-MEG, has broadened the application of bio-magnetism in the realm of neuroscience. Nonetheless, it also raises challenges in temporal decoding analysis due to the unique attributes of OP-MEG itself. The efficacy of decoding performance utilizing multimodal fusion, such as MEG-EEG, also remains to be elucidated. In this regard, we investigated the impact of several factors, such as processing methods, models and modalities, on the decoding outcomes of OP-MEG. Our findings indicate that the number of averaged trials, dimensionality reduction (DR) methods, and the number of cross-validation folds significantly affect the decoding performance of OP-MEG data. Additionally, decoding results vary across modalities and fusion strategy. In contrast, decoder type, resampling frequency, and sliding window length exert marginal effects. Furthermore, we introduced mutual information (MI) to investigate how information loss due to OP-MEG data processing affect decoding accuracy. Our study offers insights for linear decoding research using OP-MEG and expand its application in the fields of cognitive neuroscience. Full article

Muscle fascicles are shorter and stiffer than normal in spastic Cerebral Palsy (CP). Increasing fascicle length (FL) has been attempted in CP, the outcomes of which have been unsatisfactory. In healthy muscles, FL can be increased using eccentric exercise at high velocities (ECC). Three conditions are possibly met during such ECC: muscle micro-damage, positive fascicle strain, and momentary muscle deactivation during lengthening. Participants with and without CP underwent a single bout of passive stretching at (appropriately) high velocities using isokinetic dynamometry, during which we examined muscle and fascicle behaviour. Vastus lateralis (VL) FL change was measured using ultrasonography and showed positive fascicle strain. Measures of muscle creatine kinase were used to establish whether micro-damage occurred in response to stretching, but the results did not confirm damage in either group. Vastus medialis (VM) and biceps femoris muscle activity were measured using electromyography in those with CP. Results supported momentary spastic muscle deactivation during lengthening: all participants experienced at least one epoch (60 ms) of increased activation followed by activation inhibition/deactivation of the VM during knee flexion. We argue that high-velocity passive stretching in CP provides a movement context which mimics ECC and could be used to increase spastic FL with training. Full article

(1) Background: A rise in intraocular pressure (IOP) and decreased retinal ganglion cells are frequent indicators of effective modeling of chronic ocular hypertension in mice. In this study, the sensitivity of the mouse model to pharmaceutical therapy to reduce intraocular tension was assessed, the model’s safety was confirmed using a cytotoxicity test, and the success rate of the mouse model of ocular hypertension was assessed by assessing alterations in IOP and neurons in the ganglion cell layer. (2) Methods: A mouse model of chronic ocular hypertension was produced in this study by employing photocrosslinkable sericin hydrogel injection and LED lamp irradiation. The eyes of 25 C57BL/6 male mice were subjected to 405 nm UV light from the front for 2 min after being injected with 5 μL of sericin hydrogel in the anterior chamber of the left eye. IOP in the mice was measured daily, and IOP rises greater than 5 mmHg were considered intraocular hypertension. When the IOP was lowered, the intervention was repeated once, but the interval between treatments was at least 2 weeks. The right eyes were not treated with anything as a normal control group. Mice eyeballs were stained with HE, Ni-type, and immunofluorescence to assess the model’s efficacy. Two common drugs (tafluprost eye drops and timolol eye drops) were provided for one week after four weeks of stable IOP, and IOP changes were assessed to determine the drug sensitivity of the mouse model of chronic ocular hypertension. Furthermore, CellTiter 96^® AQueous One Solution Cell Proliferation Assay (MTS) was utilized to investigate the safety of the ocular hypertension model by evaluating the deleterious effects of photocrosslinkable sericin hydrogel on cells. (3) Results: Before injection, the basal IOP was (9.42 ± 1.28) mmHg (1 kPa = 7.5 mmHg) in the experimental group and (9.08 ± 1.21) in the control group. After injection, cataract occurred in one eye, corneal edema in one eye, endophthalmitis in one eye, iris incarceration in one eye, and eyeball atrophy in one eye. Five mice with complications were excluded from the experiment, and twenty mice were left. Four weeks after injection, the IOP of the experimental group was maintained at (19.7 ± 4.52) mmHg, and that of the control group was maintained at (9.92 ± 1.55) mmHg, and the difference between the two groups was statistically significant (p < 0.05). Before the intervention, the IOP in the experimental group was (21.7 ± 3.31) mmHg in the high IOP control group, (20.33 ± 2.00) mmHg in the tafluprost eye drops group, and (20.67 ± 3.12) mmHg in the timolol maleate eye drops group. The IOP after the intervention was (23.2 ± 1.03) mmHg, (12.7 ± 2.11) mmHg, and (10.4 ± 1.43) mmHg, respectively. Before and after the intervention, there were no significant differences in the high-IOP control group (p > 0.05), there were statistically significant differences in the timolol eye drops group (p < 0.05), and there were statistically significant differences in the tafluprost eye drops group (p < 0.05). One week after drug withdrawal, there was no significant difference in IOP among the three groups (p > 0.05). In the high-IOP group, the protein (sericin hydrogel) showed a short strips or fragmented structure in the anterior chamber, accompanied by a large number of macrophages and a small number of plasma cells. The shape of the chamber angle was normal in the blank control group. The number of retinal ganglion cells decreased significantly 8 weeks after injection of sericin hydrogel into the anterior chamber, and the difference was statistically significant compared with the blank control group (p < 0.05). After the cells were treated with photocrosslinkable sericin hydrogel, there was no significant difference in the data of the CellTiter 96^® assay kit of MTS compared with the blank control group (p > 0.05). (4) Conclusions: A mouse model of chronic intraocular hypertension can be established successfully by injecting sericin in the anterior chamber and irradiating with ultraviolet light. The model can simulate the structural and functional changes of glaucoma and can effectively reduce IOP after the action of most antihypertensive drugs, and it is highly sensitive to drugs. Sericin has no obvious toxic effect on cells and has high safety. Full article

Digital twins are a relatively new form of digital modeling that has been gaining popularity in recent years. This is in large part due to their ability to update in real time to their physical counterparts and connect across multiple devices. As a result, much interest has been directed towards using digital twins in the healthcare industry. Recent advancements in smart wearable technologies have allowed for the utilization of human digital twins in healthcare. Human digital twins can be generated using biometric data from the patient gathered from wearables. These data can then be used to enhance patient care through a variety of means, such as simulated clinical trials, disease prediction, and monitoring treatment progression remotely. This revolutionary method of patient care is still in its infancy, and as such, there is limited research on using wearables to generate human digital twins for healthcare applications. This paper reviews the literature pertaining to human digital twins, including methods, applications, and challenges. The paper also presents a conceptual method for creating human body digital twins using wearable sensors. Full article

Background/Objectives: We defined the value of a machine learning algorithm to distinguish between the EEG response to no light or any light stimulations, and between light stimulations with different brightnesses in awake volunteers with closed eyelids. This new method utilizing EEG analysis is visionary in the understanding of visual signal processing and will facilitate the deepening of our knowledge concerning anesthetic research. Methods: X-gradient boosting models were used to classify the cortical response to visual stimulation (no light vs. light stimulations and two lights with different brightnesses). For each of the two classifications, three scenarios were tested: training and prediction in all participants (all), training and prediction in one participant (individual), and training across all but one participant with prediction performed in the participant left out (one out). Results: Ninety-four Caucasian adults were included. The machine learning algorithm had a very high predictive value and accuracy in differentiating between no light and any light stimulations (AUCROC_all: 0.96; accuracy_all: 0.94; AUCROC_individual: 0.96 ± 0.05, accuracy_individual: 0.94 ± 0.05; AUCROC_oneout: 0.98 ± 0.04; accuracy_oneout: 0.96 ± 0.04). The machine learning algorithm was highly predictive and accurate in distinguishing between light stimulations with different brightnesses (AUCROC_all: 0.97; accuracy_all: 0.91; AUCROC_individual: 0.98 ± 0.04, accuracy_individual: 0.96 ± 0.04; AUCROC_oneout: 0.96 ± 0.05; accuracy_oneout: 0.93 ± 0.06). The predictive value and accuracy of both classification tasks was comparable between males and females. Conclusions: Machine learning algorithms could almost continuously and reliably differentiate between the cortical EEG responses to no light or light stimulations using visual evoked potentials in awake female and male volunteers with eyes closed. Our findings may open new possibilities for the use of visual evoked potentials in the clinical and intraoperative setting. Full article

The majority of observations and criteria related to brain injuries predominantly focus on acceleration and forces, leaving the understanding of the brain in the frequency domain relatively limited. The impact of an injury can be more profound when considering the brain’s resonant frequencies in conjunction with external applied loading and motion. This paper employs a finite element method to conduct an analysis of a human brain under impacts from various angles on the human head. A numerical technique, specifically dynamic mode decomposition (DMD), is utilized to extract modal properties for brain tissue in regions proximate to the corpus callosum and brain stem. Three distinct modal frequencies have been identified, spanning the ranges of 44–68 Hz, 68–155 Hz, and 114–299 Hz. The findings underscore the significance of impact angle, displacement direction, and the specific region of the brain in influencing the modal response of brain tissue during an impact event. Full article