Bioengineering最新文献

Recent advances in wearable devices and physiological signal monitoring technologies have motivated research into non-invasive glucose estimation for diabetes management. However, the existing studies are often limited by sample constraints, in terms of relatively small numbers of subjects, and few address personalized differences. Physiological signals vary considerably for different individuals, affecting the reliability of accuracy measurements, and training data and test data are both used from the same subjects, which makes the test result more affirmative than the truth. This study aims to compare the two scenarios mentioned above, regardless of whether the testing/training involves the same individual, in order to determine whether the proposed training method has better generalization ability. The publicly available MIMIC-III dataset, which contains 700,000 data points for 10,000 subjects, is used to create a more generalized model. The model architecture uses a ResNet CNN + Transformer block, and data quality is graded during preprocessing to select signals with less interference for training to increase data quality. This preprocessing method allows the model to extract useful features without being adversely affected by noise and anomalous data that decreases performance; therefore, the model's training results and generalization capability are increased. This study creates a model to predict blood glucose values from 70 to 250 for 180 classes, using mean absolute relative difference (MARD) as the evaluation metric and a Clarke error grid (CEG) to determine a reasonable error tolerance. For personalized cases (specific individual data during model training), the MARD is 11.69%, and the optimal Zone A (representing no clinical risk) in the Clarke error grid is 82.7%. Non-personalized cases (test subjects not included in the model training samples) using 60,000 unseen data yields MARD = 15.16%, and the optimal Zone A in the Clarke error grid is 75.4%. Across multiple testing runs, the proportion of predictions falling within Clarke error grid zones A and B consistently approached 100%. The small performance difference suggests that the proposed method has the potential to improve subject-independent estimation; however, further validation in broader populations is required. Therefore, the primary objective of this study is to improve subject-independent, non-personalized PPG-based glucose estimation and reduce the performance gap between personalized and non-personalized measurements.

Background: Total hip arthroplasty (THA) is a well-tolerated and effective procedure that can improve a patient's mobility and quality of life. A main concern, however, is the release of metal ions into the body due to wear and corrosion. Commonly reported ions are Co and Cr, while others, such as Ti, Mo, and Ni, are less frequently studied. The objective of this study was to characterize compartmentalization and time-dependent ion behaviors across serum, whole blood, and urine after hip prosthetic implantation. The goal of using Random Forest (RF) was to determine whether machine learning modeling could support temporal trends across data. Methods: Data was gathered from the literature of clinical studies, and we conducted a pooled analysis of the temporal kinetics from cohorts of patients who received hip prosthetics. Mean ion concentrations were normalized to µg/L across each fluid and weighted by cohort sample size. RF was used as a study-level test of predictive accuracy across ions. Results: For serum and whole blood, Co and Cr displayed one-phase association models, while Ti showed an exponential rise and decay. Ions typically rose quickly within the first 24 months postoperatively. Serum Co and whole blood had similar patterns, tapering off just under 2 µg/L, but serum Cr (~2.02 µg/L) was generally higher than that of whole blood (~0.99 µg/L). Mean urinary Co levels were greater than those of Cr, suggesting a larger, freely filterable fraction for Co. RF was implemented to determine predictive accuracy for each ion, showing a stronger fit for Co (R² = 0.86, RMSE = 0.57) compared to Cr (R² = 0.52, RMSE = 0.50). Conclusions: Sub-threshold exposure was prevalent across cohorts. Serum and whole blood Co and Cr displayed distinct kinetic profiles and, if validated, could support fluid-specific monitoring strategies. We present a methodology for interpreting ion kinetics and show potential for machine learning applications in postoperative monitoring.

We present a detailed, xeno-free protocol for the rapid differentiation of human induced pluripotent stem cells (hiPSCs) into microglia using the well-characterized KOLF2.1J reference line. This system employs doxycycline-inducible expression of six transcription factors (6-TF), stably integrated into the CLYBL safe harbor locus, to drive uniform microglial differentiation within two weeks. Building upon an established transcription factor-driven approach, our protocol includes key optimizations for KOLF2.1J, including culture on Laminin-521 to support xeno-free conditions. The resulting i-Microglia exhibit hallmark features of mature microglia, including expression of P2RY12, loss of the pluripotency marker SSEA4, phagocytic activity, and upregulation of immune markers (e.g., CD80, CD83) upon LPS stimulation. We also demonstrate compatibility with co-culture systems using iPSC-derived neurons. Additionally, we describe a modification of the line to include a constitutive mCherry reporter integrated into the SH4-2 safe harbor locus, enabling fluorescent tracking of microglia in mixed cultures or in vivo. This protocol provides a reproducible and scalable platform for generating functional human microglia from a widely used hiPSC line, supporting applications in brain tumors and disease modeling, neuroinflammation research, and therapeutic screening.

Implantable intrabody communication (IBC) is a method that enables low-power, high-security communication between implanted in-body devices that could track biomedical signals and an on-body receiver by using the human body as a communication medium. As the human body consists of various tissues that each have different conductivity, this paper explores the effects of the conductivity of the communication medium on the channel gain over a wide frequency range from 10 MHz up to 300 MHz through the measurements and two models: an electrical circuit model and a FEM simulation model. Measurements are conducted using a liquid phantom with varying conductivity values from 0 S/m up to 1 S/m, covering most human tissues in the frequency range of interest. The circuit and FEM models are designed to mimic the measurement setup in order to verify the measurement results. Results show that the circuit model predicts the communication channel characteristics well at lower frequencies but cannot account for the influence of the measurement setup at higher frequencies. The influence of wire inductances, which can cause a resonant behavior when measuring at frequencies above 100 MHz, was observed using the FEM model. The results also show that the higher the conductivity of the tissue in which the device is implanted, the lower the gain of the signal, with the difference in gain being more prominent when capacitive termination with a high-impedance load is used instead of low-impedance termination. These findings provide valuable insight for selecting the appropriate interface (low-impedance vs. high-impedance termination) across specific frequency ranges for in-body to on-body (IB2OB) communication devices, while illustrating the effect of tissue conductivity on an IBC channel, thereby supporting the optimized design and implementation of reliable IB2OB communication systems.

To identify hypertension, Ballistocardiograph (BCG) signals can be primarily utilized. The BCG signal must be thoroughly understood and interpreted so that its application in the classification process could become clearer and more distinct. Various unhealthy habits such as excess consumption of alcohol and tobacco, accompanied by a lack of good diet and a sedentary lifestyle, lead to hypertension. Common symptoms of hypertension include chest pain, shortness of breath, blurred vision, mood swings, frequent urination, etc. In this work, two pragmatic models are proposed for the detection of hypertension using BCG signals and machine learning models. The first model uses K-means clustering, the maximum overlap discrete wavelet transform (MODWT) and the Empirical Wavelet Transform (EWT) techniques for feature extraction, followed by the Binary Tunicate Swarm Algorithm (BTSA) and Information Gain (IG) for feature selection, as well as two efficient hybrid classifiers such as the Hybrid AdaBoost--Maximum Uncertainty Linear Discriminant Analysis (MULDA) classifier and the Hybrid AdaBoost-Random Forest (RF) classifier for the classification of BCG signals. The second model uses Principal Component Analysis (PCA), Kernel Principal Component Analysis (KPCA) and the Random Feature Mapping (RFM) technique for feature extraction, followed by IG and the Aquila Optimization Algorithm (AOA) for feature selection, as well as two versatile hybrid classifiers such as the Hybrid AutoRegressive Integrated Moving Average (ARIMA)-AdaBoost classifier and the Time-weighted Hybrid AdaBoost-Support Vector Machine (TW-HASVM) classifier for the classification of BCG signals. The proposed methodology was tested on a publicly available BCG dataset, and the best results were obtained when the KPCA feature extraction technique was used with the AOA feature selection technique and classified using the Hybrid ARIMA-AdaBoost classifier, reporting a good classification accuracy of 96.89%.

Background: To compare clinical outcomes of Lotrafilcon A and Balafilcon A silicone hydrogel bandage contact lenses (BCLs) following transepithelial photorefractive keratectomy (TPRK).

Methods: A randomized, double-blind, contralateral eye study enrolled 41 TPRK patients (82 eyes), with each eye randomly assigned one BCL type. Assessments included uncorrected (UDVA) and corrected (CDVA) distance visual acuity, ocular pain and irritation, epithelial healing, limbal and conjunctival hyperemia, lens mobility, and the amount of protein deposition on the BCLs.

Results: Postoperative day 1 pain score was lower in Group A (2.80 ± 2.35) than in Group B (4.44 ± 2.46, p = 0.003). Group A had significantly less protein deposition (day 3: 9.92 ± 9.82 vs. 25.75 ± 9.86 μg, p < 0.001; day 4: 9.47 ± 10.06 vs. 32.60 ± 16.71 μg, p = 0.005). No statistically significant differences were observed between the two groups in terms of corneal epithelial defect area, corneal epithelial healing time, UDVA, CDVA, limbal or conjunctival hyperemia, and lens movement.

Conclusions: Lotrafilcon A outperformed Balafilcon A in reducing ocular pain, foreign body sensation, and protein deposition, suggesting that Lotrafilcon A may be a more suitable therapeutic BCL option following TPRK.

The high salt concentration in kitchen waste (KW) can impede the performance of subsequent biological treatment. However, the impact of salt stress on the quality of vermicomposting products generated from KW remains unclear. In this study, the effects of high salt concentration in KW on earthworm function and vermicompost quality were investigated by comparing two groups: a 1.5% salt (ST) group and a control (CK) group without salt. Results showed a significant decrease in the number and weight of earthworms in the ST (p < 0.01), with a mortality rate of 24.33% (p < 0.05) after vermicomposting. Compared to the CK, ST treatment resulted in a significant increase in catalase activity and a significant decrease in superoxide dismutase activity (p < 0.01). In addition, mucus secretion by earthworms decreased by 82.6% in ST (p < 0.01). Moreover, salt stress reduced KW humification during vermicomposting, lowering the humification index and β:α index by 23.7% and 41.2%, respectively. Microbial composition shifted under spatially heterogeneous selection pressures, leading to a 37.5% decrease in Ascomycota abundance, a 58.3% increase in Bacteroidetes abundance, and a 72.3% reduction in Proteobacteria abundance. Furthermore, the vertical stratification of physicochemical conditions significantly affected both microbial abundance and earthworm biomass in the ST treatment (p < 0.01), suggesting a salt-microbe-earthworm interaction mechanism. This study reveals that salt stress disrupts humification by impairing key microbial functions and ecological roles of earthworms during vermicomposting of KW.

This narrative review examines degenerative disc disease (DDD), a major cause of chronic back pain and disability worldwide. It is a multifactorial condition resulting from a complex interplay of genetic, mechanical, metabolic, and environmental factors that progressively impair disc structure and function. The pathophysiology of DDD involves disruption of extracellular matrix homeostasis, cellular senescence, oxidative stress, and chronic inflammation mediated by cytokines such as IL-1β, TNF-α, and IL-6. These processes are further modulated by signalling pathways including NF-κB, MAPK, and Wnt/β-catenin, leading to matrix degradation, dehydration, and loss of disc height. Epidemiological studies highlight the contribution of lifestyle and metabolic disorders, such as obesity, smoking, and diabetes, to disease progression. Traditional conservative and surgical treatments primarily alleviate symptoms but do not halt or reverse degeneration. In contrast, recent advances in molecular biology and regenerative medicine have opened new therapeutic avenues. Mesenchymal stem cell therapy, biomaterial scaffolds, and gene-based interventions aim to restore disc homeostasis by promoting matrix synthesis and suppressing catabolic activity. Despite promising experimental results, clinical translation remains limited by challenges in cell viability, delivery methods, and long-term efficacy. Future research integrating molecular, biomechanical, and regenerative strategies offers the potential for true biological repair and disc regeneration.

Diabetic wounds are typically difficult to heal. They are usually characterized by prolonged healing time and increased susceptibility to bacterial infection. Therefore, altering the wound microenvironment and improving antibacterial property are effective treatment strategies. In this study, a plant hydrogel with antimicrobial activity and pro-healing properties was designed to integrate silver nanoparticles (AgNPs) with antimicrobial activity into the natural Tofu Chai (Premna microphylla Turcz, PMT) hydrogel, which exhibits strong pro-healing ability and antibacterial infections on the wound surface. In vitro experiments showed that AgNPs-PMT had a significant killing effect on Methicillin-resistant Staphylococcus aureus (MRSA), with an antibacterial efficiency reaching 95.6%. In vivo results showed that AgNPs-PMT efficiently cleared bacteria at the wound site to promote the formation of neovascularization, collagen and granulation tissue, and facilitated wound healing in a diabetic wound model with MRSA infection. On the 11th day, the wound area was only 5.4% of its original size. Overall, AgNPs-PMT demonstrated favorable antibacterial effects against MRSA and showed great potential in the treatment of chronic diabetic wounds.

This study aimed to evaluate the new orthodontic TiNb wires in direct comparison to the gold standard in orthodontics, NiTi wires, when treating. There is limited literature on patients with severe malocclusions being treated from start to end with TiNb, and TiNb wires were mostly used in the final stages of treatment. Our protocol consisted of three orthodontic wires: 0.016, 0.016 × 0.025, and 0.019 × 0.025 for levelling and aligning the stage and 0.019 × 0.025 stainless steel for the finishing stage, in order to treat the same case reproduced on a modified scientific simulator. The bracket system used was made by GC slot 0.22, TiNb wires made by Morita, and NiTi wires produced by GC. We ligated all brackets using SS wire ligatures 0.008, and for anchorage, we used a transpalatal arch. The temperature of the scientific simulator was set between 20 and 25 degrees Celsius. We have used upper arches and studied the repositioning of upper ectopic canines and space closure in order to obtain an equilibrated maxillary arch. After each change of orthodontic wires, we scanned the upper arch using Medit i600 (Medit, Seoul, Republic of Korea). After concluding all stages on all upper arches, we assessed the results using LITTLE's Irregularity index and stereo microscopy to explain metal stress on NiTi and TiNb. We propose an optimized process for using TiNb and NiTi wires when treating class II severe malocclusions with premolar extractions. Thus, we observed permanent deformation for all 0.016 TiNb wires used in the first stage, so TiNb underperformed in comparison with NiTi. Also, the Little's Irregularity Index was superior in the NiTi wires group on 0.016 wires, verifying the change of state in the TiNb wires group.