Real-Time Shape Estimation of Hyper-Redundant Flexible Manipulator Using Coiled Fiber Sensors.

The shape of flexible endoscopic surgical robot should be obtained to increase control accuracy and prevent unwanted tissue damage. To estimate the shape of flexible manipulator, space efficiency, cost-effectiveness, system complexity, and ease of calibration should be considered to integrate sensors into the manipulator. In this article, we propose a real-time method to estimate the shape of a hyper-redundant manipulator having embedded coiled fiber sensors. The main advantage of this method is guaranteeing shape recognition even when the manipulator is subjected to an external load. The fiber sensors are highly flexible, compact, and inexpensive, as well as they can functionally measure both compressive and tensile strain of hyper-redundant manipulator. The sensor design was optimized to achieve durability and sensitivity. The numbers of sensor and the placements were determined by the analysis of the kinematics and moment distribution of the manipulator. The accuracy of shape estimation was validated experimentally under both free-loading and loading conditions. The proposed method achieved real-time estimating capability with a mean maximum error of each joint position smaller than 3.54% in free-loading condition and 5.47% in loading condition.

Development of innate and adaptive immunity to RSV in young children.

Infection of the respiratory tract with respiratory syncytial virus (RSV) is common and occurs repeatedly throughout life with most severe disease occurring at the extremes of age: in young infants and the elderly. Effective anti-viral therapeutics are not available and therefore prevention has been the primary strategy for reducing the disease burden. Our current understanding of respiratory mucosal cell biology and the immune response within the respiratory tract is inadequate to prevent infection caused by a pathogen like RSV that does not disseminate outside of this environment. Gaps in our understanding of the activation of innate and adaptive immunity in response to RSV and the role of age upon infection also limit improvements in the design of therapeutics and vaccines for young infants. However, advancements in structural biology have improved our ability to characterize antibodies against viral proteins and in 2023 the first vaccines for those over 60 years and pregnant women became available, potentially reducing the burden of disease. This review will examine our current understanding of the critical facets of anti-RSV immune responses in infants and young children as well as highlight areas where more research is needed.

Fabrication and validation of flexible neural electrodes based on polyimide tape and gold sheet.

This research was conducted to apply polyimide tape, which has the advantages of low price ans strong adhesive strength, to the neural electrode process. In addition, to maximize the low-cost characteristics, a fabrication process based on UV laser patterning rather than a photolithography process was introduced. The fabrication process started by attaching the gold sheet on the conductive double-sided tape without being torn or crushed. Then, the gold sheet and the double-sided tape were patterned together using UV laser. The patterned layer was transferred to the single-side polyimide tape. For insulation layer, electrode site opened single-sided polyimide tape was prepared. Polydimethylsiloxane was used as an adhesion layer, and alignment between electrode sites and opening sites was processed manually. The minimum line width achieved through the proposed fabrication process was approximately 100 µm, and the sheet resistance of the conductive layer was 0.635 Ω/sq. Measured cathodal charge storage capacity was 0.72 mC/cm2 and impedance at 1 kHz was 4.07 kΩ/cm2. Validation of fabricated electrode was confirmed by conducting 30 days accelerated soak test, flexibility test, adhesion test and ex vivo stimulation test. The novel flexible neural electrodes based on single-sided polyimide tape and UV laser patterned gold sheet was fabricated successfully. Conventional neural electrode fabrication processes based on polyimide substrate has a disadvantages such as long fabrication time, expensive costs, and probability of delamination between layers. However, the novel fabrication process which we introduced can overcome many shortcomings of existing processes, and offers great advantages such as simplicity of fabrication, inexpensiveness, flexibility and long-term reliability.

Implantable Neural Electrodes Fabrication Based on Perfluoroalkoxyalkane Film.

OBJECTIVE: In this paper, the fabrication of perfluoro-alkoxy alkane (PFA) film-based planar neural electrodes was proposed. METHODS: The fabrication of PFA-based electrodes started with cleaning of PFA film. The argon plasma pretreatment was performed on the PFA film surface and attached to a dummy silicon wafer. Metal layers were deposited and patterned using the standard Micro Electro Mechanical Systems (MEMS) process. Electrode-sites and pads were opened using reactive ion etching (RIE). Lastly, the electrode patterned PFA substrate film was thermally laminated with the other bare PFA film. Electrical-physical evaluation tests were conducted along with in vitro tests, ex vivo tests and soak tests to evaluate the electrode performance and biocompatibility. RESULTS: The electrical and physical performance of PFA-based electrodes had better performances compared to other biocompatible polymer-based electrodes. Also, the biocompatibility and longevity were verified by cytotoxicity test, elution test, and accelerated life test. CONCLUSION: The PFA film-based planar neural electrode fabrication was established and evaluated. The PFA based electrodes showed excellent benefits such as long-term reliability, low water absorption rate, and flexibility using the neural electrode. SIGNIFICANCE: For implantable neural electrodes, hermetic sealing is required for in vivo durability. PFA fulfilled a low water absorption rate with relatively low Young's modulus to increase the longevity and biocompatibility of the devices.

Particulate matter-induced metabolic recoding of epigenetics in macrophages drives pathogenesis of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a group of illnesses associated with unresolved inflammation in response to toxic environmental stimuli. Persistent exposure to PM is a major risk factor for COPD, but the underlying mechanism remains unclear. Using our established mouse model of PM-induced COPD, we find that repeated PM exposure provokes macrophage-centered chronic inflammation and COPD development. Mechanistically, chronic PM exposure induces transcriptional downregulation of HAAO, KMO, KYNU, and QPRT in macrophages, which are the enzymes of de novo NAD+ synthesis pathway (kynurenine pathway; KP), via elevated chromatin binding of the CCCTC-binding factor (CTCF) near the transcriptional regulatory regions of the enzymes. Subsequent reduction of NAD+ and SIRT1 function increases histone acetylation, resulting in elevated expression of pro-inflammatory genes in PM-exposed macrophages. Activation of SIRT1 by nutraceutical resveratrol mitigated PM-induced chronic inflammation and COPD development. In agreement, increased levels of histone acetylation and decreased expression of KP enzymes were observed in pulmonary macrophages of COPD patients. We newly provide an evidence that dysregulated NAD+ metabolism and consecutive SIRT1 deficiency significantly contribute to the pathological activation of macrophages during PM-mediated COPD pathogenesis. Additionally, targeting PM-induced intertwined metabolic and epigenetic reprogramming in macrophages is an effective strategy for COPD treatment.

The Effectiveness of a Novel Air-Barrier Device for Aerosol Reduction in a Dental Environment: Computational Fluid Dynamics Simulation.

The use of equipment such as dental handpieces and ultrasonic tips in the dental environment has potentially heightened the generation and spread of aerosols, which are dispersant particles contaminated by etiological factors. Although numerous types of personal protective equipment have been used to lower contact with contaminants, they generally do not exhibit excellent removal rates and user-friendliness in tandem. To solve this problem, we developed a prototype of an air-barrier device that forms an air curtain as well as performs suction and evaluated the effect of this newly developed device through a simulation study and experiments. The air-barrier device derived the improved design for reducing bioaerosols through the simulation results. The experiments also demonstrated that air-barrier devices are effective in reducing bioaerosols generated at a distance in a dental environment. In conclusion, this study demonstrates that air-barrier devices in dental environments can play an effective role in reducing contaminating particles.

Prediction of efficiencies for diverse prime editing systems in multiple cell types.

Applications of prime editing are often limited due to insufficient efficiencies, and it can require substantial time and resources to determine the most efficient pegRNAs and prime editors (PEs) to generate a desired edit under various experimental conditions. Here, we evaluated prime editing efficiencies for a total of 338,996 pairs of pegRNAs including 3,979 epegRNAs and target sequences in an error-free manner. These datasets enabled a systematic determination of factors affecting prime editing efficiencies. Then, we developed computational models, named DeepPrime and DeepPrime-FT, that can predict prime editing efficiencies for eight prime editing systems in seven cell types for all possible types of editing of up to 3 base pairs. We also extensively profiled the prime editing efficiencies at mismatched targets and developed a computational model predicting editing efficiencies at such targets. These computational models, together with our improved knowledge about prime editing efficiency determinants, will greatly facilitate prime editing applications.

A case report of T cell/histiocyte-rich large B cell lymphoma misdiagnosed as lymphomatoid papulosis.

RATIONALE: T cell/histiocyte-rich large B cell lymphoma (THRLBCL) is an uncommon B cell lymphoma characterized by < 10% large neoplastic B cells in a background of abundant T cells and frequent histiocytes. If a skin lesion is the first clinical sign of lymphoma, the diagnosis might be difficult and misdiagnosed. PATIENT CONCERNS: A 60-year-old woman presented with multiple erythematous umbilicated nodules on her left upper back for 3 months. DIAGNOSES: Through punch biopsy of the back lesion and additional excisional right inguinal lymph node biopsy, the patient was diagnosed with cutaneous metastasis of THRLBCL. INTERVENTIONS: The patient was referred to the Hemato-oncology Department for chemotherapy. OUTCOMES: R-CHOP chemotherapy is currently in progress, and some skin lesions show improvement. LESSONS: Skin lesions might be the first clinical sign of THRLBCL and when THRLBCL is suspected, careful further evaluation is essential for accurate diagnosis and treatment.

A Scalp Scar-Reducing Procedure for the Hair Transplant Donor Area Using a Columnar Trichophytic Suture: A Case Report.

BACKGROUND: One of the main concerns of patients who undergo hair transplantation surgery such as follicular unit strip surgery is scar widening on surgical sites. Until now, trichophytic suture, double-layer suture, tattoos, follicular unit transplantation on scars are suggested as a solution. CASE REPORT: A 23-year-old man with frontal hair loss underwent follicular unit strip surgery. To reduce hair donor area scarring, we tried a new trichophytic suture method. After surgery, the patient's hair loss degree was corrected with about C1 in the basic and specific (BASP) classification. Also, there was less scar in the columnar trichophytic suture part, compared with almost 7 mm of scar widening in the simple primary closure part. CONCLUSION: This study highlights that a columnar trichophytic suture may be useful for patients undergoing scalp surgery for cosmetic purposes.

Statistical discrimination using different machine learning models reveals dissimilar key compounds of soybean leaves in targeted polyphenol-metric metabolomics in terms of traits and cultivation.

Soybean (SB) leaves (SLs) contain diverse flavonoids with health-promoting properties. To investigate the chemical constituents of SB and their correlations across phenotypes, growing periods, and environmental factors, a validated separation method for mass detection was used with targeted metabolomics. Thirty-six polyphenols (1 coumestrol, 5 flavones, 18 flavonols, and 12 isoflavones) were identified in SLs, 31 of which were quantified. Machine learning (ML) modelling was used to differentiate between the variety, bean color, growing period, and cultivation area and identify the key compounds responsible for these differences. The isoflavone and flavonol profiles were influenced by the growing period and cultivation area based on bootstrap forest modelling. The neural model showed the best predictive capacity for SL differences among the various ML models. Discriminant polyphenols can differ depending on the ML method applied; therefore, a cautious approach should be ensured when using statistical ML outputs, including orthogonal partial least squares discriminant analysis.

Neurostimulators for high-resolution artificial retina: ASIC design challenges and solutions.

Objective.Neurostimulator is one of the most important part in artificial retina design. In this paper, we discuss the main challenges in the design of application-specific integrated circuit for high-resolution artificial retina and suggest corresponding solutions.Approach. Problems in the design of the neurostimulator for the existing artificial retina have not been solved yet are analyzed and solutions are presented. For verification of the solutions, mathematical proof, MATLAB and Ansys simulations are used.Main results. The drawbacks of resorting to a high-voltage complementary metal oxide semiconductor (CMOS) process to deal with the large voltage compliance demanded by the stimulator output stage are pointed out, and an alternative approach based on a circuit that switches the voltage of the common reference electrode is proposed to overcome. The necessity of an active discharge circuit to remove the residual charge of electrodes caused by an unbalanced stimulus is investigated. We present a circuit analysis showing that the use of a passive discharge circuit is sufficient to suppress problematic direct current in most situations. Finally, possible restrictions on input and output (I/O) count are investigated by estimating the resistive-capacitive delay caused by the interconnection between the I/O pad and the microelectrode array.Significance. The results of this paper clarified the problems currently faced by neurostimulator design for the artificial retina. Through the solutions presented in this study, circuits with more competitiveness in power and area consumption can be designed.

The Design and Analysing Heating Effect of Spiral Planar Coil in COMSOL Multiphysics for Implantable Artificial Retina.

In this paper, simulation data and heat generation due to electromagnetic from spiral planar pair of coils for arti-ficial retinal implant were analyzed by COMSOL Multiphysics. Planar spiral outer and inner coils for an implantable artificial retina were designed and analyzed. The whole geometry was designed in a transplant situation. The parameters of the coil were set within the design limits due to the limitations of im-plant space. The inductance for the coil and the thermal change due to the electromagnetic force generated in the inductively coupled coil were calculated. Analysis of heat transfer in a biological model showed that the maximum heat did not exceed the internal tissue damage temperature. The results showed that a pair of coils designed for artificial retinas can be implanted in vivo without destruction of body tissues.

Selective Edge Rounding of Cyclic Olefin Copolymer Film Using UV Laser for Implantable Electrode Package.

Cyclic Olefin Copolymer is emerging as a packaging material for implantable electrodes due to its physical properties such as low water absorption rate and low water vapor permeability. The electrode-tissue interface is often regarded as a major focus of implantable electrodes, but its packaging should also be considered thoroughly since it directly contacts the adjoining body cells. Therefore, eliminating any sharp boundaries or edges around the package would be beneficial to minimize potential inflammatory responses caused by physical/mechanical stresses. To smooth both inner/outer edges of a cyclic olefin copolymer packaging, an optimal UV laser condition was investigated by varying its marking speed and iterations. Clinical relevance - This establishes a method that can selectively smooth the edges around a cyclic olefin copolymer pack-aged implantable electrodes for reduced mechanical mismatch after insertion.

Investigation of neural electrode fabrication process on Polycarbonate substrate.

Polycarbonate is a polymer that has been widely used including medical application due to its useful properties. It has high temperature resistance, biocompatibility, transparency and low water absorption rate, which are needful characteristics for packaging material of implantable neural prosthetic devices. In this study, we investigated fabrication of neural electrode with polycarbonate film using standard photolithography process and heated hydraulic press for thermal lamination. First, oxygen plasma surface treatment was performed to increase the adhesion between metal and polycarbonate film. Then thin layer of titanium and gold layer were deposited. Metal layer is patterned through standard photolithography techniques. After completing the metal patterning, thermal lamination was performed with site opened polycarbonate film.

Fabrication of a light screen-aperture integrated flexible thin film micro-lens array for a biomimetic superposition compound eye.

Micro-lens array, an artificial compound eye vision system, provides a wide field of view and multi-perspective view. However, it has not been adopted as a computer vision application due to its limited visible range and high optical interference. In this research, a novel fabrication method for the flexible polydimethylsiloxane micro-lens array with a polytetrafluoroethylene light screen-aperture integrated layer was established by the simple protrusion method. The integrated layer provided longer visible range by one meter while maintaining the wide field-of-view of 100 °. The resulting images were used for obtaining depth information of a target as an example and for analyzing the rectangular and hexagonal arrangements of the micro-lenses for the future applications. With the improved visual range, wide field-of-view and flexibility, the fabricated micro-lens array can be applied to the small and curved CMOS image sensors in the future.

A Colorimetric Test to Differentiate Patients Infected with Influenza from COVID-19.

Patients infected with SARS-CoV-2 and influenza display similar symptoms, but treatment requirements are different. Clinicians need to accurately distinguish SARS-CoV-2 from influenza to provide appropriate treatment. Here, the authors develope a color-based technique to differentiate between patients infected with SARS-CoV-2 and influenza A using a nucleic acid enzyme-gold nanoparticle (GNP) molecular test requiring minimal equipment. The MNAzyme and GNP probes are designed to be robust to viral mutations. Conserved regions of the viral genomes are targeted, and two MNAzymes are created for each virus. The ability of the system to distinguish between SARS-CoV-2 and influenza A using 79 patient samples is tested. When detecting SARS-CoV-2 positive patients, the clinical sensitivity is 90%, and the specificity is 100%. When detecting influenza A, the clinical sensitivity and specificity are 93% and 100%, respectively. The high clinical performance of the MNAzyme-GNP assay shows that it can be used to help clinicians choose effective treatments.

Diagnosing Antibiotic Resistance Using Nucleic Acid Enzymes and Gold Nanoparticles.

The rapid and accurate detection of antimicrobial resistance is critical to limiting the spread of infections and delivering effective treatments. Here, we developed a rapid, sensitive, and simple colorimetric nanodiagnostic platform to identify disease-causing pathogens and their associated antibiotic resistance genes within 2 h. The platform can detect bacteria from different biological samples (i.e., blood, wound swabs) with or without culturing. We validated the multicomponent nucleic acid enzyme-gold nanoparticle (MNAzyme-GNP) platform by screening patients with central line associated bloodstream infections and achieved a clinical sensitivity and specificity of 86% and 100%, respectively. We detected antibiotic resistance in methicillin-resistant Staphylococcus aureus (MRSA) in patient swabs with 90% clinical sensitivity and 95% clinical specificity. Finally, we identified mecA resistance genes in uncultured nasal, groin, axilla, and wound swabs from patients with 90% clinical sensitivity and 95% clinical specificity. The simplicity and versatility for detecting bacteria and antibiotic resistance markers make our platform attractive for the broad screening of microbial pathogens.

Crash narrative classification: Identifying agricultural crashes using machine learning with curated keywords.

OBJECTIVE: Traditionally, structured or coded data fields from a crash report are the basis for identifying crashes involving different types of vehicles, such as farm equipment. However, using only the structured data can lead to misclassification of vehicle or crash type. The objective of the current article is to examine the use of machine learning methods for identifying agricultural crashes based on the crash narrative and to transfer the application of models to different settings (e.g., future years of data, other states). METHODS: Different data representations (e.g., bag-of-words [BoW], bag-of-keywords [BoK]) and document classification algorithms (e.g., support vector machine [SVM], multinomial naïve Bayes classifier [MNB]) were explored using Texas and Louisiana crash narratives across different time periods. RESULTS: The BoK-support vector classifier (SVC), BoK-MNB, and BoW-SVC models trained with Texas data were better predictive models than the baseline rule-based algorithm on the future year test data, with F1 scores of 0.88, 0.89, 0.85 vs. 0.84. The BoK-MNB trained with Louisiana data performed the closest to the baseline rule-based algorithm on the future year test data (F1 scores, 0.91 baseline rule-based algorithm vs. 0.89 BoK-MNB). The BoK-SVC and BoK-MNB models trained with Texas and Louisiana data were better productive models for Texas future year test data with F1 scores 0.89 and 0.90 vs. 0.84. The BoK-MNB model trained with both states' data was a better predictive model for the Louisiana future year test data, F1 score 0.94 vs. 0.91. CONCLUSIONS: The findings of this study support that machine learning methodologies can potentially reduce the amount of human power required to develop key word lists and manually review narratives.

Marker-Based Structural Displacement Measurement Models with Camera Movement Error Correction Using Image Matching and Anomaly Detection.

To prevent collapse accidents at construction sites, the marker-based displacement measurement method was developed. However, it has difficulty in obtaining accurate measurements at long distances (>50 m) in an outdoor environment because of camera movements. To overcome this problem, marker-based structural displacement measurement models using image matching and anomaly detection were designed in this study. Then, the performance of each model in terms of camera movement error correction was verified through comparison with that of a conventional model. The results show that the systematic errors due to camera movements (<1.7°) were corrected. The detection rate of markers with displacement reached 95%, and the probability that the error size would be less than 10 mm was ≥ 95% with a 95% confidence interval at a distance of more than 100 m. Moreover, the normalized mean square error was less than 0.1. The models developed in this study can measure the pure displacement of an object without the systematic errors caused by camera movements. Furthermore, these models can be used to measure the displacements of distant structures using closed-circuit television cameras and markers in an outdoor environment with high accuracy.

Epiphora after nasolacrimal duct fracture in patients with midfacial trauma: A retrospective study.

The aim of this study was to identify the factors related to occurrence of epiphora or requirement of dacryocystorhinostomy (DCR) in patients with midfacial trauma.We performed a retrospective analysis of the medical records of 1038 patients with midfacial trauma from January 2005 to December 2015. Fifty-one patients (55 cases) diagnosed with nasolacrimal duct (NLD) fracture using facial bone computed tomography were enrolled. Correlation analysis was performed of patient- and injury-related factors, including age, sex, facial trauma etiology, accompanying injury, type and level of the NLD fracture, and time from injury to initial surgery, with the occurrence of epiphora and requirement for DCR.Epiphora occurred in 14.5% and DCR was performed in 5.5% of the patients with NLD fracture. The correlation analysis revealed no significant relationship among the factors with the occurrence of epiphora and requirement for DCR.In patients with midfacial trauma and NLD fracture, epiphora occurred in 14.5% and endoscopic DCR was performed due to persistent epiphora in 5.5% and its result was all successful.