A comprehensive review of chitosan-based functional materials: From history to specific applications.

Chitosan (CTS), a natural biopolymer derived from chitin, has garnered significant attention owing to its potential chemical, biological, and physical properties, such as biocompatibility, bioactivity, and biosafety. This comprehensive review traces the historical development of CTS-based materials and delves into their specific applications across various fields. The study highlights the evolution of CTS from its initial discovery to its current state, emphasizing key milestones and technological advancements that have expanded its utility. Despite the extensive research, the synthesis and functionalization of CTS to achieve desired properties for targeted applications remain a challenge. This review addresses current problems such as the scalability of production, consistency in quality, and the environmental impact of extraction and modification processes. Additionally, it explores the novel applications of CTS-based materials in biomedicine, agriculture, environmental protection, and food industry, showcasing innovative solutions and future potentials. By providing a detailed analysis of the current state of CTS research and identifying gaps in knowledge, this review offers a valuable resource for researchers and industry professionals. The novelty of this work lies in its holistic approach, combining historical context with a forward-looking perspective on emerging trends and potential breakthroughs in the field of CTS-based functional materials. Therefore, this review will be helpful for readers by summarizing recent advances and discussing prospects in CTS-based functional materials.

Soft robotic artificial left ventricle simulator capable of reproducing myocardial biomechanics.

The heart's intricate myocardial architecture has been called the Gordian knot of anatomy, an impossible tangle of intricate muscle fibers. This complexity dictates equally complex cardiac motions that are difficult to mimic in physical systems. If these motions could be generated by a robotic system, then cardiac device testing, cardiovascular disease studies, and surgical procedure training could reduce their reliance on animal models, saving time, costs, and lives. This work introduces a bioinspired soft robotic left ventricle simulator capable of reproducing the minutiae of cardiac motion while providing physiological pressures. This device uses thin-filament artificial muscles to mimic the multilayered myocardial architecture. To demonstrate the device's ability to follow the cardiac motions observed in the literature, we used canine myocardial strain data as input signals that were subsequently applied to each artificial myocardial layer. The device's ability to reproduce physiological volume and pressure under healthy and heart failure conditions, as well as effective simulation of a cardiac support device, were experimentally demonstrated in a left-sided mock circulation loop. This work also has the potential to deliver faithful simulated cardiac motion for preclinical device and surgical procedure testing, with the potential to simulate patient-specific myocardial architecture and motion.

Antimicrobial Susceptibility Profile of Methicillin-Resistant Staphylococcus Aureus Isolated from Clinical Samples at Bac Ninh Provincial General Hospital, Vietnam.

Purpose: Staphylococcus aureus, including methicillin-resistant Staphylococcus aureus (MRSA) strain, can become resistant to all classes of clinically available antibiotics and causes skin infections and severe infections in the lungs, heart, and bloodstream. The study aimed to evaluate antimicrobial susceptibility patterns and MRSA exhibiting multidrug resistance obtained through a microbiological culture of clinical specimens at Bac Ninh Provincial General Hospital in Bac Ninh Province, Vietnam. Methods: We employed a cross-sectional analysis at Bac Ninh Provincial General Hospital in Vietnam. 15,232 clinical samples from inpatients were examined. S. aureus isolates were identified using established protocols and tested for MRSA and antibiotic susceptibility. Data was analyzed using R software, with statistical calculations to assess associations between variables. Results: Staphylococcus aureus was isolated from 417 samples (2.7%), with 77.2% being MRSA and 22.8% methicillin-susceptible Staphylococcus aureus (MSSA). Significant sources of MRSA were wounds (64.6%) and the surgical unit (50%) according to sample types and hospital wards, respectively. S. aureus showed high resistance rates, the highest being azithromycin (83.2%), and was fully susceptible to vancomycin. Among 294 multidrug-resistant (MDR) strains, the prevalence was 82.0% in MRSA and 18.0% in MSSA. Conclusion: The study highlights widespread antimicrobial resistance among MRSA isolates from a provincial hospital in Vietnam, emphasizing the urgent need for antibiotic surveillance, formulation of antibiotic policies, and preventive measures to tackle the increasing prevalence of multidrug-resistant MRSA.

Smartphone-Based Digitized Neurological Examination Toolbox for Multi-test Neurological Abnormality Detection and Documentation.

Understanding the efficacy of digital biomarkers in vision-based human motion analysis is essential, not only for interpreting the computer-aided exam results but also for advancing the next generation of digital health tool solutions. This study extensively analyzes digitized neurological examination (DNE) biomarkers for detecting and documenting exam features of Parkinson's disease (PD) and other neurological disorders (OD). Collected over 113 participants, DNE-113, a multi-test DNE database of finger tapping, finger to finger, forearm roll, stand-up and walk, and facial activation tests, covering a broader range of neurological abnormalities beyond PD is first proposed. Subsequently, DNE-113 is integrated into pyDNE - a convenient open-source toolbox, streamlining the creation and assessment of digital biomarkers. This toolbox empowers us to assess the quality of DNE biomarkers across diverse classification tasks. We showcase the discriminative potency of DNE biomarkers, successfully characterizing abnormal signals in neurological patients. Our findings highlight not only the potential use cases but also the persisting challenges in constructing digital biomarkers for computer-aided movement analysis on PD and OD patients.

Point-of-Care Multiplex Detection of Respiratory Viruses.

The COVID-19 pandemic, in addition to the co-occurrence of influenza virus and respiratory syncytial virus (RSV), has emphasized the requirement for efficient and reliable multiplex diagnostic methods for respiratory infections. While existing multiplex detection techniques are based on reverse transcription quantitative polymerase chain reaction (RT-qPCR) and extraction and purification kits, the need for complex instrumentation and elevated cost limit their scalability and availability. In this study, we have developed a point-of-care (POC) device based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) that can simultaneously detect four respiratory viruses (SARS-CoV-2, Influenza A, Influenza B, and RSV) and perform two controls in less than 30 min, while avoiding the use of the RNA extraction kit. The system includes a disposable microfluidic cartridge with mechanical components that automate sample processing, with a low-cost and portable optical reader and a smartphone app to record and analyze fluorescent images. The application as a real point-of-care platform was validated using swabs spiked with virus particles in nasal fluid. Our portable diagnostic system accurately detects viral RNA specific to respiratory pathogens, enabling deconvolution of coinfection information. The detection limits for each virus were determined using virus particles spiked in chemical lysis buffer. Our POC device has the potential to be adapted for the detection of new pathogens and a wide range of viruses by modifying the primer sequences. This work highlights an alternative approach for multiple respiratory virus diagnostics that is well-suited for healthcare systems in resource-limited settings or at home.

Soft Fibrous Syringe Architecture for Electricity-Free and Motorless Control of Flexible Robotic Systems.

Flexible robotic systems (FRSs) and wearable user interfaces (WUIs) have been widely used in medical fields, offering lower infection risk and shorter recovery, and supporting amiable human-machine interactions (HMIs). Recently, soft electric, thermal, magnetic, and fluidic actuators with enhanced safety and compliance have innovatively boosted the use of FRSs and WUIs across many sectors. Among them, soft hydraulic actuators offer great speed, low noise, and high force density. However, they currently require bulky electric motors/pumps, pistons, valves, rigid accessories, and complex controllers, which inherently result in high cost, low adaptation, and complex setups. This paper introduces a novel soft fibrous syringe architecture (SFSA) consisting of two or more hydraulically connected soft artificial muscles that enable electricity-free actuation, motorless control, and built-in sensing ability for use in FRSs and WUIs. Its capabilities are experimentally demonstrated with various robotic applications including teleoperated flexible catheters, cable-driven continuum robotic arms, and WUIs. In addition, its sensing abilities to detect passive and active touch, surface texture, and object stiffness are also proven. These excellent results demonstrate a high feasibility of using a current-free and motor-less control approach for the FRSs and WUIs, enabling new methods of sensing and actuation across the robotic field.

Antimicrobial Resistance Patterns of Pathogens Isolated from Patients with Wound Infection at a Teaching Hospital in Vietnam.

Purpose: At a teaching Hospital in Vietnam, the persistently high incidence of diagnosed wound infection poses ongoing challenges to treatment. This study seeks to explore the causative agents of wound infection and their antimicrobial and multidrug resistance patterns. Methods: A cross-sectional study was conducted at the Department of Microbiology, Military Hospital 103, Vietnam. Data on microorganisms that caused wound infection and their antimicrobial resistance patterns was recorded from hospitalized patients from 2014 to 2021. Using the chi-square test, we analyzed the initial isolation from wound infection specimens collected from individual patients. Results: Over a third (34.9%) of wound infection samples yielded bacterial cultures. Staphylococcus aureus was the most prevalent bacteria, followed by Pseudomonas aeruginosa. Worryingly high resistance rates were observed for several antibiotics, particularly among Gram-negative bacteria. Ampicillin displayed the highest resistance (91.9%), while colistin and ertapenem remained the most effective. In Gram-positive bacteria, glycopeptides like teicoplanin and vancomycin (0% and 3.3% resistance, respectively) were most effective, but their use was limited. Clindamycin and tetracycline showed decreasing effectiveness. Resistance rates differed between surgical and non-surgical wards, highlighting the complex dynamics of antimicrobial resistance within hospitals. Multidrug resistance (MDR) was substantial, with Gram-negative bacteria exhibiting a 63.6% MDR rate. Acinetobacter baumannii showed the highest MDR rate (88.0%). Conclusion: This study investigated wound infection characteristics, antibiotic resistance patterns of common bacteria, and variations by hospital ward. S. aureus was the most prevalent bacteria, and concerning resistance rates were observed, particularly among Gram-negative bacteria. These findings highlight the prevalence of multidrug resistance in wound infections, emphasizing the importance of infection control measures and judicious antibiotic use.

Multivariate analysis of craniodental morphology in mouse-eared bats (Chiroptera, Vespertilionidae, Myotis) from Vietnam.

This study conducted biostatistical multivariate analyses on 23 craniodental morphological measurements from 209 specimens to study interspecific variations amongst 15 bat species of the genus Myotis in Vietnam. Univariate and multivariate analyses demonstrated that the studied species can be divided into four groups as follows: extra-large-sized species (M.chinensis), large-sized species (M.pilosus, M.indochinensis and M.annectans), medium-sized species (M.altarium, M.hasseltii, M.montivagus, M.horsfieldii, M.ater, M.laniger and M.muricola) and small-sized species (M.annamiticus, M.aff.siligorensis, M.rosseti and M.alticraniatus). Our data revealed that the main craniodental features contributing to the variations in distinguishing Myotis species are the width of the anterior palatal, least height of the coronoid process, length of the upper and lower canine-premolar, zygomatic width and width across the upper canines and lower premolar-molar length. Based on patterns of morphological differences, we conducted comparisons between morphometrically closely resembling species pairs and further discussed additional characteristics that are expected to support the taxonomy and systematics of Vietnamese Myotis bats.

Associations of COVID-19-related fear with kidney disease quality of life and its subscales among hemodialysis patients as modified by health literacy: a multi-hospital survey.

Background: Receiving hemodialysis treatment makes end-stage renal disease (ESRD) patients highly vulnerable amidst the COVID-19 pandemic. Hence, their kidney disease quality of life (KDQOL) is affected. We aimed to examine the association between fear of COVID-19 (FCoV-19) and KDQOL, and the effect modification of Health literacy (HL) on this association. Material and Methods: A survey was conducted at 8 hospitals from July 2020 to March 2021 on 972 patients. Data collection includes socio-demographic factors, clinical parameters, HL, digital healthy diet literacy (DDL), hemodialysis diet knowledge (HDK), FCoV-19, suspected COVID-19 symptoms (S-COVID-19-S), and KDQOL. Results: Higher HL scores B = 0.13 (95% CI = 0.06-0.21, p = 0.001) and HDK scores B = 0.58 (95% CI = 0.31-0.85, p = 0.001) were associated with higher KDQOL scores. Whereas, S-COVID-19-S B = -6.12 (95% CI = -7.66 to - 4.58, p = 0.001) and FCoV-19 B = -0.91 (95% CI = -1.03 to - 0.80, p = 0.001) were associated with lower KDQOL scores. Notably, higher HL scores significantly attenuate the negative impact of FCoV-19 on overall KDQOL and the kidney disease component summary. Conclusions: In hemodialysis patients, FCoV-19 and S-COVID-19-S were associated with a lower KDQOL. Health literacy significantly mitigates the negative impact of FCoV-19 on KDQOL. Strategic public health interventions to improve HL are suggested to protect patient's KDQOL during the pandemic.

MS-PyCloud: A Cloud Computing-Based Pipeline for Proteomic and Glycoproteomic Data Analyses.

Rapid development and wide adoption of mass spectrometry-based glycoproteomic technologies have empowered scientists to study proteins and protein glycosylation in complex samples on a large scale. This progress has also created unprecedented challenges for individual laboratories to store, manage, and analyze proteomic and glycoproteomic data, both in the cost for proprietary software and high-performance computing and in the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI), for proteomic and glycoproteomic data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignments to peptide sequences, false discovery rate estimation, protein inference, quantitation of global protein levels, and specific glycan-modified glycopeptides as well as other modification-specific peptides such as phosphorylation, acetylation, and ubiquitination. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open-source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at https://github.com/huizhanglab-jhu/ms-pycloud.

Methanotrophs mediated biogas valorization: Sustainable route to polyhydroxybutyrate production.

This study explores the ability of methanotrophs to convert biogas into biopolymers, addressing H2S as a limitation in the utilization of biogas as a carbon source for bioconversion. Transcriptomic analysis was conducted to understand the growth and changes in the expression patterns of Type I and II methanotrophs under varying H2S concentrations. Results suggested that Type II methanotrophs can possess a native H2S utilization pathway. Both Type I and II methanotrophs were evaluated for their growth and polyhydroxybutyrate (PHB) production from biogas. Methylocystis sp. MJC1 and Methylocystis sp. OK1 exhibited a maximum biomass production of 4.0 and 4.5 gDCW/L, respectively, in fed-batch culture, aligning with the transcriptome data. Furthermore, Methylocystis sp. MJC1 produced 2.9 g PHB/L from biogas through gas fermentation. These findings underscore biogas-based biotechnology as an innovative solution for environmental and industrial challenges with further optimization and productivity enhancement research expected to broaden the potential in this field.

Insight into chromium adsorption from contaminated soil using Mg/Al LDH-zeolite.

The study investigated the effectiveness of Mg/Al LDH-zeolite (MALZ) in immobilizing exchangeable Cr (e-Cr) within the soil. The research systematically evaluated various variables affecting the immobilization of e-Cr in contaminated soil (CS), including soil pH levels (ranging from 5.0 to 9.0), different weight ratios of MALZ (1 %, 3 %, and 5 %), durations of differing incubation periods (15, 30 and 45 days), and different SM content levels (30 %, 50 %, and 70 %). The initial concentration of Cr in the CS was maintained at 50 mg/kg. The investigation findings revealed that the optimal conditions for immobilizing the e-Cr were a soil pH of 5.0, an MALZ weight ratio of 3 %, an incubation period of 30 days, and an SM level of 70 %. Under these ideal conditions, the percentage of e-Cr within the CS decreased significantly, from 87.49 % (45.64 mg/kg) in the control treatment (CT) to just 19.82 % (10.08 mg/kg) when incubated with MALZ. The primary mechanisms responsible for immobilizing the e-Cr onto MALZ included pore filling, reduction processes, co-precipitation, organic interactions and electrostatic attractions leading to the formation of carbonate-bound complexes such as Cr(VI)-carbonate, Cr(III)-carbonate, and organic complexes. Surface functional groups on MALZ, housing iron and aluminium oxyhydroxides and silicon and oxygen elements, expedited these procedures. This study provided a valuable understanding of the mitigation of soils contaminated with chromium and contributed to understanding the relations between MALZ and the e-Cr in the soil. The discoveries carry substantial consequences for the advancement of efficient remediation technologies.

Recent Trends of Bioanalytical Sensors with Smart Health Monitoring Systems: From Materials to Applications.

Smart biosensors attract significant interest due to real-time monitoring of user health status, where bioanalytical electronic devices designed to detect various activities and biomarkers in the human body have potential applications in physical sign monitoring and health care. Bioelectronics can be well integrated by output signals with wireless communication modules for transferring data to portable devices used as smart biosensors in performing real-time diagnosis and analysis. In this review, the scientific keys of biosensing devices and the current trends in the field of smart biosensors, (functional materials, technological approaches, sensing mechanisms, main roles, potential applications and challenges in health monitoring) will be summarized. Recent advances in the design and manufacturing of bioanalytical sensors with smarter capabilities and enhanced reliability indicate a forthcoming expansion of these smart devices from laboratory to clinical analysis. Therefore, a general description of functional materials and technological approaches used in bioelectronics will be presented after the sections of scientific keys to bioanalytical sensors. A careful introduction to the established systems of smart monitoring and prediction analysis using bioelectronics, regarding the integration of machine-learning-based basic algorithms, will be discussed. Afterward, applications and challenges in development using these smart bioelectronics in biological, clinical, and medical diagnostics will also be analyzed. Finally, the review will conclude with outlooks of smart biosensing devices assisted by machine learning algorithms, wireless communications, or smartphone-based systems on current trends and challenges for future works in wearable health monitoring.

Discovery of a small-molecule inhibitor that traps Polθ on DNA and synergizes with PARP inhibitors.

The DNA damage response (DDR) protein DNA Polymerase θ (Polθ) is synthetic lethal with homologous recombination (HR) factors and is therefore a promising drug target in BRCA1/2 mutant cancers. We discover an allosteric Polθ inhibitor (Polθi) class with 4-6 nM IC50 that selectively kills HR-deficient cells and acts synergistically with PARP inhibitors (PARPi) in multiple genetic backgrounds. X-ray crystallography and biochemistry reveal that Polθi selectively inhibits Polθ polymerase (Polθ-pol) in the closed conformation on B-form DNA/DNA via an induced fit mechanism. In contrast, Polθi fails to inhibit Polθ-pol catalytic activity on A-form DNA/RNA in which the enzyme binds in the open configuration. Remarkably, Polθi binding to the Polθ-pol:DNA/DNA closed complex traps the polymerase on DNA for more than forty minutes which elucidates the inhibitory mechanism of action. These data reveal a unique small-molecule DNA polymerase:DNA trapping mechanism that induces synthetic lethality in HR-deficient cells and potentiates the activity of PARPi.

A missense mutation in the Hspa8 gene encoding heat shock cognate protein 70 causes neuroaxonal dystrophy in rats.

Neuroaxonal dystrophy (NAD) is a neurodegenerative disease characterized by spheroid (swollen axon) formation in the nervous system. In the present study, we focused on a newly established autosomal recessive mutant strain of F344-kk/kk rats with hind limb gait abnormalities and ataxia from a young age. Histopathologically, a number of axonal spheroids were observed throughout the central nervous system, including the spinal cord (mainly in the dorsal cord), brain stem, and cerebellum in F344-kk/kk rats. Transmission electron microscopic observation of the spinal cord revealed accumulation of electron-dense bodies, degenerated abnormal mitochondria, as well as membranous or tubular structures in the axonal spheroids. Based on these neuropathological findings, F344-kk/kk rats were diagnosed with NAD. By a positional cloning approach, we identified a missense mutation (V95E) in the Hspa8 (heat shock protein family A (Hsp70) member 8) gene located on chromosome 8 of the F344-kk/kk rat genome. Furthermore, we developed the Hspa8 knock-in (KI) rats with the V95E mutation using the CRISPR-Cas system. Homozygous Hspa8-KI rats exhibited ataxia and axonal spheroids similar to those of F344-kk/kk rats. The V95E mutant HSC70 protein exhibited the significant but modest decrease in the maximum hydrolysis rate of ATPase when stimulated by co-chaperons DnaJB4 and BAG1 in vitro, which suggests the functional deficit in the V95E HSC70. Together, our findings provide the first evidence that the genetic alteration of the Hspa8 gene caused NAD in mammals.

Antimicrobial Resistance Patterns of Staphylococcus Aureus Isolated at a General Hospital in Vietnam Between 2014 and 2021.

Purpose: Staphylococcus aureus is a commensal bacteria species that can cause various illnesses, from mild skin infections to severe diseases, such as bacteremia. The distribution and antimicrobial resistance (AMR) pattern of S. aureus varies by population, time, geographic location, and hospital wards. In this study, we elucidated the epidemiology and AMR patterns of S. aureus isolated from a general hospital in Vietnam. Methods: This was a cross-sectional study. Data on all S. aureus infections from 2014 to 2021 were collected from the Microbiology department of Military Hospital 103, Vietnam. Only the first isolation from each kind of specimen from a particular patient was analyzed using the Cochran-Armitage and chi-square tests. Results: A total of 1130 individuals were diagnosed as S. aureus infection. Among them, 1087 strains were tested for AMR features. Most patients with S. aureus infection were in the age group of 41-65 years (39.82%). S. aureus isolates were predominant in the surgery wards, and pus specimens were the most common source of isolates (50.62%). S. aureus was most resistant to azithromycin (82.28%), erythromycin (82.82%), and clindamycin (82.32%) and least resistant to teicoplanin (0.0%), tigecycline (0.16%), quinupristin-dalfopristin (0.43%), linezolid (0.62%), and vancomycin (2.92%). Methicillin-resistant S. aureus (MRSA) and multidrug-resistant (MDR) S. aureus were prevalent, accounting for 73.02% and 60.90% of the total strains respectively, and the strains isolated from the intensive care unit (ICU) had the highest percentage of multidrug resistance (77.78%) among the wards. Conclusion: These findings highlight the urgent need for continuous AMR surveillance and updated treatment guidelines, particularly considering high resistance in MRSA, MDR strains, and ICU isolates. Future research focusing on specific resistant populations and potential intervention strategies is crucial to combat this rising threat.

Engineered methane biocatalysis: strategies to assimilate methane for chemical production.

Methane (CH4), one of the greenhouse gases, is considered a promising feedstock for the biological production of fuels and chemicals. Although recent studies have demonstrated the capability of methanotrophs to convert CH4 into various bioproducts by metabolic engineering, the productivity has not reached commercial levels. As such, there is a growing interest in synthetic methanotrophic systems as an alternative. This review summarizes the strategies for enhancing native CH4 assimilation and discusses the challenges for the construction of synthetic methanotrophy into nonmethanotrophic industrial strains. Additionally, we suggest a mixed heterotrophic approach that integrates CH4 assimilation with glucose and xylose metabolism to improve productivity. The synthetic methanotrophic system presented in this review could pave the way for sustainable and efficient biomanufacturing using CH4.

Enhancing/Improving Forming Limit Curve and Fracture Height Predictions in the Single-Point Incremental Forming of Al1050 Sheet Material.

Single-point incremental forming (SPIF) has emerged as a cost-effective and rapid manufacturing method, especially suitable for small-batch production due to its minimal reliance on molds, swift production, and affordability. Nonetheless, SPIF's effectiveness is closely tied to the specific characteristics of the employed sheet materials and the intricacies of the desired shapes. Immediate experimentation with SPIF often leads to numerous product defects. Therefore, the pre-emptive use of numerical simulations to predict these defects is of paramount importance. In this study, we focus on the critical role of the forming limit curve (FLC) in SPIF simulations, specifically in anticipating product fractures. To facilitate this, we first construct the forming limit curve for Al1050 sheet material, leveraging the modified maximum force criterion (MMFC). This criterion, well-established in the field, derives FLCs based on the theory of hardening laws in sheet metal yield curves. In conjunction with the MMFC, we introduce a graphical approach that simplifies the prediction of forming limit curves at fracture (FLCF). Within the context of the SPIF method, FLCF is established through both uniaxial tensile deformation (U.T) and simultaneous uniform tensile deformation in bi-axial tensile (B.T). Subsequently, the FLCF predictions are applied in simulations and experiments focused on forming truncated cone parts. Notably, a substantial deviation in fracture height, amounting to 15.97%, is observed between simulated and experimental samples. To enhance FLCF prediction accuracy in SPIF, we propose a novel method based on simulations of truncated cone parts with variable tool radii. A FLCF is then constructed by determining major/minor strains in simulated samples. To ascertain the validity of this enhanced FLCF model, our study includes simulations and tests of truncated cone samples with varying wall angles, revealing a substantial alignment in fracture height between corresponding samples. This research contributes to the advancement of SPIF by enhancing our ability to predict and mitigate product defects, ultimately expanding the applicability of SPIF in diverse industrial contexts.

Room temperature roll-to-roll additive manufacturing of polydimethylsiloxane-based centrifugal microfluidic device for on-site isolation of ribonucleic acid from whole blood.

Polymer-based lab-on-a-disc (LoaD) devices for isolating ribonucleic acid (RNA) from whole blood samples have gained considerable attention for accurate biomedical analysis and point-of-care diagnostics. However, the mass production of these devices remains challenging in manufacturing cost and sustainability, primarily due to the utilization of a laser cutter or router computer numerical control (CNC) machine for engraving and cutting plastics in the conventional prototyping process. Herein, we reported the first energy-efficient room-temperature printing-imprinting integrated roll-to-roll manufacturing platform for mass production of a polydimethylsiloxane (PDMS)-based LoaD to on-site isolate ribonucleic acid (RNA) from undiluted blood samples. We significantly reduced energy consumption and eliminated thermal expansion variations between the mold, substrate, and resists by accelerating the PDMS curing time to less than 10 min at room temperature without using heat or ultraviolet radiation. The additive manufacturing technology was applied to fabricate a multi-depth flexible polymer mold that integrated macro (2 mm) and micro-sized (500 µm) features, which overcomes the economic and environmental challenges of conventional molding techniques. Our integrated R2R platform was enabled to print adhesion-promoting films at the first printing unit and continuously in-line imprint with a high replication accuracy (99%) for high-volume manufacturing of a new centrifugal microfluidic chip with an enhancement of mixing performance by integrating an efficient mixing chamber and serpentine micromixer. This research paved the way for scalable green manufacturing of large-volume polymer-based microfluidic devices, often required in real-world sample-driven analytical systems for clinical bioanalysis.

A Smart, Textile-Driven, Soft Exosuit for Spinal Assistance.

Work-related musculoskeletal disorders (WMSDs) are often caused by repetitive lifting, making them a significant concern in occupational health. Although wearable assist devices have become the norm for mitigating the risk of back pain, most spinal assist devices still possess a partially rigid structure that impacts the user's comfort and flexibility. This paper addresses this issue by presenting a smart textile-actuated spine assistance robotic exosuit (SARE), which can conform to the back seamlessly without impeding the user's movement and is incredibly lightweight. To detect strain on the spine and to control the smart textile automatically, a soft knitting sensor that utilizes fluid pressure as a sensing element is used. Based on the soft knitting hydraulic sensor, the robotic exosuit can also feature the ability of monitoring and rectifying human posture. The SARE is validated experimentally with human subjects (N = 4). Through wearing the SARE in stoop lifting, the peak electromyography (EMG) signals of the lumbar erector spinae are reduced by 22.8% ± 12 for lifting 5 kg weights and 27.1% ± 14 in empty-handed conditions. Moreover, the integrated EMG decreased by 34.7% ± 11.8 for lifting 5 kg weights and 36% ± 13.3 in empty-handed conditions. In summary, the artificial muscle wearable device represents an anatomical solution to reduce the risk of muscle strain, metabolic energy cost and back pain associated with repetitive lifting tasks.