Gradient conducting polymer surfaces with netrin-1-conjugation promote axon guidance and neuron transmission of human iPSC-derived retinal ganglion cells.

Major advances have been made in utilizing human-induced pluripotent stem cells (hiPSCs) for regenerative medicine. Nevertheless, the delivery and integration of hiPSCs into target tissues remain significant challenges, particularly in the context of retinal ganglion cell (RGC) restoration. In this study, we introduce a promising avenue for providing directional guidance to regenerated cells in the retina. First, we developed a technique for construction of gradient interfaces based on functionalized conductive polymers, which could be applied with various functionalized ehthylenedioxythiophene (EDOT) monomers. Using a tree-shaped channel encapsulated with a thin PDMS and a specially designed electrochemical chamber, gradient flow generation could be converted into a functionalized-PEDOT gradient film by cyclic voltammetry. The characteristics of the successfully fabricated gradient flow and surface were analyzed using fluorescent labels, time of flight secondary ion mass spectrometry (TOF-SIMS), and X-ray photoelectron spectroscopy (XPS). Remarkably, hiPSC-RGCs seeded on PEDOT exhibited improvements in neurite outgrowth, axon guidance and neuronal electrophysiology measurements. These results suggest that our novel gradient PEDOT may be used with hiPSC-based technologies as a potential biomedical engineering scaffold for functional restoration of RGCs in retinal degenerative diseases and optic neuropathies.

Parkin deficiency exacerbates particulate matter-induced injury by enhancing airway epithelial necroptosis.

Exposure to fine particulate matter (PM) disrupts the function of airway epithelial barriers causing cellular stress and damage. However, the precise mechanisms underlying PM-induced cellular injury and the associated molecular pathways remain incompletely understood. In this study, we used intratracheal instillation of PM in C57BL6 mice and PM treatment of the BEAS-2B cell line as in vivo and in vitro models, respectively, to simulate PM-induced cellular damage and inflammation. We collected lung tissues and bronchoalveolar lavage fluids to assess histopathological changes, necroptosis, and airway inflammation. Our findings reveal that PM exposure induces necroptosis in mouse airway epithelial cells. Importantly, concurrent administration of a receptor interacting protein kinases 3 (RIPK3) inhibitor or the deletion of the necroptosis effector mixed-lineage kinase domain-like protein (MLKL) effectively attenuated PM-induced airway inflammation. PM exposure dose-dependently induces the expression of Parkin, an E3 ligase we recently reported to play a pivotal role in necroptosis through regulating necrosome formation. Significantly, deletion of endogenous Parkin exacerbates inflammation by enhancing epithelial necroptosis. These results indicate that PM-induced Parkin expression plays a crucial role in suppressing epithelial necroptosis, thereby reducing airway inflammation. Overall, these findings offer valuable mechanistic insights into PM-induced airway injury and identify a potential target for clinical intervention.

Target modulation of glycolytic pathways as a new strategy for the treatment of neuroinflammatory diseases.

Neuroinflammation is an innate and adaptive immune response initiated by the release of inflammatory mediators from various immune cells in response to harmful stimuli. While initially beneficial and protective, prolonged or excessive neuroinflammation has been identified in clinical and experimental studies as a key pathological driver of numerous neurological diseases and an accelerant of the aging process. Glycolysis, the metabolic process that converts glucose to pyruvate or lactate to produce adenosine 5'-triphosphate (ATP), is often dysregulated in many neuroinflammatory disorders and in the affected nerve cells. Enhancing glucose availability and uptake, as well as increasing glycolytic flux through pharmacological or genetic manipulation of glycolytic enzymes, has shown potential protective effects in several animal models of neuroinflammatory diseases. Modulating the glycolytic pathway to improve glucose metabolism and ATP production may help alleviate energy deficiencies associated with these conditions. In this review, we examine six neuroinflammatory diseases-stroke, Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), and depression-and provide evidence supporting the role of glycolysis in their treatment. We also explore the potential link between inflammation-induced aging and glycolysis. Additionally, we briefly discuss the critical role of glycolysis in three types of neuronal cells-neurons, microglia, and astrocytes-within physiological processes. This review highlights the significance of glycolysis in the pathology of neuroinflammatory diseases and its relevance to the aging process.

Variability of morphology in photoplethysmographic waveform quantified with unsupervised wave-shape manifold learning for clinical assessment.

Objective.We investigated fluctuations of the photoplethysmography (PPG) waveform in patients undergoing surgery. There is an association between the morphologic variation extracted from arterial blood pressure (ABP) signals and short-term surgical outcomes. The underlying physiology could be the numerous regulatory mechanisms on the cardiovascular system. We hypothesized that similar information might exist in PPG waveform. However, due to the principles of light absorption, the noninvasive PPG signals are more susceptible to artifacts and necessitate meticulous signal processing.Approach.Employing the unsupervised manifold learning algorithm, dynamic diffusion map, we quantified multivariate waveform morphological variations from the PPG continuous waveform signal. Additionally, we developed several data analysis techniques to mitigate PPG signal artifacts to enhance performance and subsequently validated them using real-life clinical database.Main results.Our findings show similar associations between PPG waveform during surgery and short-term surgical outcomes, consistent with the observations from ABP waveform analysis.Significance.The variation of morphology information in the PPG waveform signal in major surgery provides clinical meanings, which may offer new opportunity of PPG waveform in a wider range of biomedical applications, due to its non-invasive nature.

VPS34 Governs Oocyte Developmental Competence by Regulating Mito/Autophagy: A Novel Insight into the Significance of RAB7 Activity and Its Subcellular Location.

Asynchronous nuclear and cytoplasmic maturation in human oocytes is believed to cause morphological anomalies after controlled ovarian hyperstimulation. Vacuolar protein sorting 34 (VPS34) is renowned for its pivotal role in regulating autophagy and endocytic trafficking. To investigate its impact on oocyte development, oocyte-specific knockout mice (ZcKO) are generated, and these mice are completely found infertile, with embryonic development halted at 2- to 4-cell stage. This infertility is related with a disruption on autophagic/mitophagic flux in ZcKO oocytes, leading to subsequent failure of zygotic genome activation (ZGA) in derived 2-cell embryos. The findings further elucidated the regulation of VPS34 on the activity and subcellular translocation of RAS-related GTP-binding protein 7 (RAB7), which is critical not only for the maturation of late endosomes and lysosomes, but also for initiating mitophagy via retrograde trafficking. VPS34 binds directly with RAB7 and facilitates its activity conversion through TBC1 domain family member 5 (TBC1D5). Consistent with the cytoplasmic vacuolation observed in ZcKO oocytes, defects in multiple vesicle trafficking systems are also identified in vacuolated human oocytes. Furthermore, activating VPS34 with corynoxin B (CB) treatment improved oocyte quality in aged mice. Hence, VPS34 activation may represent a novel approach to enhance oocyte quality in human artificial reproduction.

Continuous Biosensor Based on Particle Motion: How Does the Concentration Measurement Precision Depend on Time Scale?

Continuous biosensors measure concentration-time profiles of biomolecular substances in order to allow for comparisons of measurement data over long periods of time. To make meaningful comparisons of time-dependent data, it is essential to understand how measurement imprecision depends on the time interval between two evaluation points, as the applicable imprecision determines the significance of measured concentration differences. Here, we define a set of measurement imprecisions that relate to different sources of variation and different time scales, ranging from minutes to weeks, and study these using statistical analyses of measurement data. The methodology is exemplified for Biosensing by Particle Motion (BPM), a continuous, affinity-based sensing technology with single-particle and single-molecule resolution. The studied BPM sensor measures specific small molecules (glycoalkaloids) in an industrial food matrix (potato fruit juice). Measurements were performed over several months at two different locations, on nearly 50 sensor cartridges with in total more than 1000 fluid injections. Statistical analyses of the measured signals and concentrations show that the relative residuals are normally distributed, allowing extraction and comparisons of the proposed imprecision parameters. The results indicate that sensor noise is the most important source of variation followed by sample pretreatment. Variations caused by fluidic transport, changes of the sensor during use (drift), and variations due to different sensor cartridges and cartridge replacements appear to be small. The imprecision due to sensor noise is recorded over few-minute time scales and is attributed to stochastic fluctuations of the single-molecule measurement principle, false-positive signals in the signal processing, and nonspecific interactions. The developed methodology elucidates both time-dependent and time-independent factors in the measurement imprecision, providing essential knowledge for interpreting concentration-time profiles as well as for further development of continuous biosensing technologies.

Evaluating the Effectiveness of a Novel Personalized Health Education Approach for Hemodialysis Patients: A Four-Week Study Using a Widely-Used Communication App in Taiwan.

Dialysis patients often have inadequate health literacy, affecting self-care and outcomes. This study used LINE app to provide personalized health education to Taiwanese dialysis patients and collected physiological data via wearables. While physical activity levels remained unchanged, participants' disease literacy significantly improved post-intervention. Patients' health literacy will evaluate by Health Literacy Questionnaire for Taiwanese Hemodialysis patients (HLQHD). The findings highlight technology-driven interventions' potential to enhance health literacy and disease management among dialysis patients.

CircETV6 acts as an oncogenic driver in hepatocellular carcinoma progression.

Circular RNA (circRNA) plays important role in hepatocellular carcinoma (HCC) progression. However, the role and mechanism of circETV6 in HCC progression remain unclear. The levels of circETV6, ETV6, miR-383-5p, and PTPRE were tested by quantitative reverse-transcription polymerase chain reaction. Cell functions were assessed using the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide assay, 5-ethynyl-2'-deoxyuridine assay, colony formation assay, wound healing assay, transwell assay, and flow cytometry. The protein levels of poptosis-related markers and PTPRE were determined by western blot analysis. RNA interaction was analyzed by dual-luciferase reporter assay and RNA pull-down assay. A xenograft model was established to assess circETV6 roles in vivo. CircETV6 was highly expressed in HCC tissues and cells. CircETV6 knockdown repressed HCC cell proliferation, migration, invasion, and cell cycle, while accelerated apoptosis. CircETV6 targeted miR-383-5p, and miR-383-5p inhibition reversed the regulation of circETV6 knockdown on HCC cell progression. CircETV6 promoted PTPRE level via targeting miR-383-5p. Overexpressed PTPRE abolished the inhibition effect of miR-383-5p on HCC cell progression. In addition, circETV6 knockdown slowed HCC tumor growth in vivo. CircETV6 might facilitate HCC progression via the miR-383-5p/PTPRE axis, providing a novel target for HCC treatment.

TEAM: Triangular-mEsh Adaptive and Multiscale proton spot generation method.

BACKGROUND: Proton therapy is preferred for its dose conformality to spare normal tissues and organs-at-risk (OAR) via Bragg peaks with negligible exit dose. However, proton dose conformality can be further optimized: (1) the spot placement is based on the structured (e.g., Cartesian) grid, which may not offer conformal shaping to complex tumor targets; (2) the spot sampling pattern is uniform, which may be insufficient at the tumor boundary to provide the sharp dose falloff, and at the same time may be redundant at the tumor interior to provide the uniform dose coverage, for example, due to multiple Coulomb scattering (MCS); and (3) the lateral spot penumbra increases with respect to the depth due to MCS, which blurs the lateral dose falloff. On the other hand, while (1) the deliverable spots are subject to the minimum-monitor-unit (MMU) constraint, and (2) the dose rate is proportional to the MMU threshold, the current spot sampling method is sensitive to the MMU threshold and can fail to provide satisfactory plan quality for a large MMU threshold (i.e., high-dose-rate delivery). PURPOSE: This work will develop a novel Triangular-mEsh-based Adaptive and Multiscale (TEAM) proton spot generation method to address these issues for optimizing proton dose conformality and plan delivery efficiency. METHODS: Compared to the standard clinically-used spot placement method, three key elements of TEAM are as follows: (1) a triangular mesh instead of a structured grid: the triangular mesh is geometrically more conformal to complex target shapes and therefore more efficient and accurate for dose shaping inside and around the target; (2) adaptive sampling instead of uniform sampling: the adaptive sampling consists of relatively dense sampling at the tumor boundary to create the sharp dose falloff, which is more accurate, and coarse sampling at the tumor interior to uniformly cover the target, which is more efficient; and (3) depth-dependent sampling instead of depth-independent sampling: the depth-dependent sampling is used to compensate for MCS, that is, with increasingly dense sampling at the tumor boundary to improve dose shaping accuracy, and increasingly coarse sampling at the tumor interior to improve dose shaping efficiency, as the depth increases. In the TEAM method the spot locations are generated for each energy layer and layer-by-layer in the multiscale fashion; and then the spot weights are derived by solving the IMPT problem of dose-volume planning objectives, MMU constraints, and robustness optimization with respect to range and setup uncertainties. RESULTS: Compared to the standard clinically-used spot placement method UNIFORM, TEAM achieved (1) better plan quality using <60% number of spots of UNIFORM; (2) better robustness to the number of spots; (3) better robustness to a large MMU threshold. Furthermore, TEAM provided better plan quality with fewer spots than other adaptive methods (Cartesian-grid or triangular-mesh). CONCLUSIONS: A novel triangular-mesh-based proton spot placement method called TEAM is proposed, and it is demonstrated to improve plan quality, robustness to the number of spots, and robustness to the MMU threshold, compared to the clinically-used spot placement method and other adaptive methods.

Comprehensive dosimetric commissioning of proton minibeam radiotherapy on a single gantry proton system.

Background: Proton minibeam radiation therapy (pMBRT) can deliver spatially fractionated dose distributions with submillimeter resolution. These dose distributions exhibit significant heterogeneity in both depth and lateral directions. Accurate characterization of pMBRT doses requires dosimetry devices with high spatial resolution and a wide dynamic range. Furthermore, the dependency of dosimetric measurements on Linear Energy Transfer (LET), as observed in conventional proton therapy, is also present in pMBRT depth dose measurements. Purpose: This work demonstrates the process of performing comprehensive dosimetric measurements to characterize the pMBRT collimator on a clinical single-gantry proton machine, utilizing commercially available dosimetry devices. Methods: The minibeam collimator is designed to be mounted on the clinical nozzle as a beam-modifying accessory. Three collimators, each with a slit opening of 0.4 mm, are thoroughly evaluated. The center-to-center (c-t-c) distances of the slits for these collimators are 2.8 mm, 3.2 mm, and 4.0 mm, respectively. High spatial resolution dosimetry devices are essential for PMBRT dose characterizations. To meet this requirement, two-dimensional (2D) dose measurement devices, Gafchromic films, are used to measure lateral profiles at various depths. Films are also used for depth dose profile measurements in solid water. Additionally, high-resolution point dose detectors, microDiamond, and Razor diode detectors are employed for lateral profile measurements at various depths. Percent depth dose (PDD) measurements of pMBRT in solid water, with various proton energies, collimators, and air gaps, are performed using Gafchromic films. The film's LET dependency for proton beams is corrected to ensure accurate pMBRT PDD measurements. The Monte Carlo simulation tool TOPAS is utilized to compare and validate all experimental measurements. Results: At depths where LET is not a concern, film dose measurements were consistent with microDiamond and Razor diode point measurements. The point detectors need to be orientated with the thin side aligned to the incoming beam. Comparison of the lateral dose profiles extracted from TOPAS simulations, films, microDiamond, and Razor diode detectors shows a passing rate exceeding 98% in 1D gamma analysis at 3% 0.1 mm criteria.However, when the microDiamond detector is orientated to face the pMBRT beam, its spatial resolution may not be sufficient to capture the peak and valley dose accurately. Nevertheless, an accuracy within 2% can still be achieved when comparing the average dose. The PDD measurements show that the peak valley dose ratio (PVDR) of pMBRT can be altered at different depths with different air gaps using the same collimator or different collimators of different c-t-c distances. Conclusion: Our study demonstrates that comprehensive dose measurements for pMBRT can be conducted using standard clinical dose measurement devices. These measurements are indispensable for guiding and ensuring accurate dose reporting in pre-clinical studies using the pMBRT technique.

Enhancing Outcomes in Chronic Fibrotic Interstitial Lung Disease Through Aggressive Management of Nintedanib-Induced Adverse Drug Reactions: A Retrospective Analysis.

BACKGROUND AND OBJECTIVES: Nintedanib, a tyrosine kinase inhibitor, is integral in slowing pulmonary fibrosis progression in chronic fibrotic interstitial lung disease (ILD). However, the occurrence of adverse drug reactions (ADRs) often limits its use, leading to treatment discontinuation, typically within 3-12 months. Discontinuation adversely affects patient outcomes. The study investigated whether aggressive ADR management can prolong nintedanib therapy and improve patient outcomes. METHODS: This retrospective, single-center study enrolled Taiwanese patients with chronic fibrotic ILD who were treated with nintedanib from January 2016 to December 2022 in Kaohsiung Chang Gung Memorial Hospital. Patients were categorized into those who discontinued treatment within 180 days and those continuing beyond. Management of ADRs was identified through concurrent prescriptions for symptoms such as nausea, vomiting, diarrhea, or hepatic dysfunction. Baseline demographics, comorbidities, pulmonary function tests, and instances of acute exacerbation were analyzed. RESULTS: The study enrolled 94 patients, with 71 (75.5%) experiencing ADRs. Among these, 41 (43.6%) discontinued nintedanib within 180 days. The administration of medications for managing nausea/vomiting [17 (41.5%) versus 36 (67.9%), p = 0.0103] and diarrhea [12 (29.3%) versus 33 (62.3%), p = 0.0015] was less frequent in the discontinued group compared with the continued group. Additionally, a higher incidence of acute exacerbation was observed in the discontinued group (34.1% versus 20.8%, p = 0.016). CONCLUSION: Aggressive management of ADRs may enhance patient tolerance to nintedanib, potentially prolonging treatment duration and improving outcomes in chronic fibrotic ILD.

A novel treatment planning method via scissor beams for uniform-target-dose proton GRID with peak-valley-dose-ratio optimization.

BACKGROUND: Proton spatially fractionated RT (SFRT) can potentially synergize the unique advantages of using proton Bragg peak and SFRT peak-valley dose ratio (PVDR) to reduce the radiation-induced damage for normal tissues. Uniform-target-dose (UTD) proton GRID is a proton SFRT modality that can be clinically desirable and conveniently adopted since its UTD resembles target dose distribution in conventional proton RT (CONV). However, UTD proton GRID is not used clinically, which is likely due to the lack of an effective treatment planning method. PURPOSE: This work will develop a novel treatment planning method using scissor beams (SB) for UTD proton GRID, with the joint optimization of PVDR and dose objectives. METHODS: The SB method for spatial dose modulation in normal tissues with UTD has two steps: (1) a primary beam (PB) is halved with interleaved beamlets, to generate spatial dose modulation in normal tissues; (2) a complementary beam (CB) is added to fill in previously valley-dose positions in the target to generate UTD, while the CB is angled slightly from the PB, to maintain spatial dose modulation in normal tissues. A treatment planning method with PVDR optimization via the joint total variation and L1 (TVL1) regularization is developed to jointly optimize PVDR and dose objectives. The plan optimization solution is obtained using an iterative convex relaxation algorithm. RESULTS: The new methods SB and SB-TVL1 were validated in comparison with CONV. Compared to CONV of relatively homogeneous dose distribution, SB had modulated spatial dose pattern in normal tissues with UTD and comparable plan quality. Compared to SB, SB-TVL1 further maximized PVDR, with comparable dose-volume parameters. CONCLUSIONS: A novel SB method is proposed that can generate modulated spatial dose pattern in normal tissues to achieve UTD proton GRID. A treatment planning method with PVDR optimization capability via TVL1 regularization is developed that can jointly optimize PVDR and dose objectives for proton GRID.

Designing Evidence-based Simulation Scenarios for Clinical Practice.

Simulation-based education is a widely used teaching technique in healthcare education. Simulation can provide a rich learning environment for caregivers at all levels. Creating simulation-based scenarios is a systematic, evidence-based, learner-centered process that requires skill and expertise. There are 11 known criteria of best practice in simulation design. Using best practices in simulation scenario design development can provide the bedrock for learners to engage in clinical practice with competency, confidence, and caring. Examples and suggestions are provided to guide readers to create quality, learner-centered simulation scenarios using the Healthcare Simulation Standards of Best Practice: Simulation Design.

Centralised visual processing center for remote sensing target detection.

Target detection in satellite images is an essential topic in the field of remote sensing and computer vision. Despite extensive research efforts, accurate and efficient target detection in remote sensing images remains unsolved due to the large target scale span, dense distribution, and overhead imaging and complex backgrounds, which result in high target feature similarity and serious occlusion. In order to address the above issues in a comprehensive manner, within this paper, we first propose a Centralised Visual Processing Center (CVPC), this structure is a parallel visual processing center for Transformer encoder and CNN, employing a lightweight encoder to capture broad, long-range interdependencies. Pixel-level Learning Center (PLC) module is used to establish pixel-level correlations and improve the depiction of detailed features. CVPC effectively improves the detection efficiency of remote sensing targets with high feature similarity and severe occlusion. Secondly, we propose a centralised feature cross-layer fusion pyramid structure to fuse the results with the CVPC in a top-down manner to enhance the detailed feature representation capability at each layer. Ultimately, we present a Context Enhanced Adaptive Sparse Convolutional Network (CEASC), which improves the accuracy while ensuring the detection efficiency. Based on the above modules, we designed and conducted a series of experiments. These experiments are conducted on three challenging public datasets, DOTA-v1.0, DIOR, and RSDO, showing that our proposed 3CNet achieves a more advanced detection accuracy while balancing the detection speed (78.62% mAP for DOTA-v1.0, 79.12% mAP for DIOR, and 95.50% mAP for RSOD).

Dynamic assemblies of parvalbumin interneurons in brain oscillations.

Brain oscillations are crucial for perception, memory, and behavior. Parvalbumin-expressing (PV) interneurons are critical for these oscillations, but their population dynamics remain unclear. Using voltage imaging, we simultaneously recorded membrane potentials in up to 26 PV interneurons in vivo during hippocampal ripple oscillations in mice. We found that PV cells generate ripple-frequency rhythms by forming highly dynamic cell assemblies. These assemblies exhibit rapid and significant changes from cycle to cycle, varying greatly in both size and membership. Importantly, this variability is not just random spiking failures of individual neurons. Rather, the activities of other PV cells contain significant information about whether a PV cell spikes or not in a given cycle. This coordination persists without network oscillations, and it exists in subthreshold potentials even when the cells are not spiking. Dynamic assemblies of interneurons may provide a new mechanism to modulate postsynaptic dynamics and impact cognitive functions flexibly and rapidly.

Exploring keratin composition variability for sustainable thermal insulator design.

In pursuing sustainable thermal insulation solutions, this study explores the integration of human hair and feather keratin with alginate. The aim is to assess its potential in thermal insulation materials, focusing on the resultant composites' thermal and mechanical characteristics. The investigation uncovers that the type and proportion of keratin significantly influence the composites' porosity and thermal conductivity. Specifically, higher feather keratin content is associated with lesser sulfur and reduced crosslinking due to shorter amino acids, leading to increased porosity and pore sizes. This, in turn, results in a decrease in ß-structured hydrogen bond networks, raising non-ordered protein structures and diminishing thermal conductivity from 0.044 W/(m·K) for pure alginate matrices to between 0.033 and 0.038 W/(m·K) for keratin-alginate composites, contingent upon the specific ratio of feather to hair keratin used. Mechanical evaluations further indicate that composites with a higher ratio of hair keratin exhibit an enhanced compressive modulus, ranging from 60 to 77 kPa, demonstrating the potential for tailored mechanical properties to suit various applications. The research underscores the critical role of sulfur content and the crosslinking index within keratin's structures, significantly impacting the thermal and mechanical properties of the matrices. The findings position keratin-based composites as environmentally friendly alternatives to traditional insulation materials.

Oriented Antibody Coupling to an Antifouling Polymer Using Glycan Remodeling for Biosensing by Particle Motion.

Biosensors based on immobilized antibodies require molecular strategies that (i) couple the antibodies in a stable fashion while maintaining the conformation and functionality, (ii) give outward orientation of the paratope regions of the antibodies for good accessibility to analyte molecules in the biofluid, and (iii) surround the antibodies by antibiofouling molecules. Here, we demonstrate a method to achieve oriented coupling of antibodies to an antifouling poly(l-lysine)-grafted-poly(ethylene glycol) (PLL-g-PEG) substrate, using glycan remodeling to create antibody-DNA conjugates. The coupling, orientation, and functionality of the antibodies were studied using two analysis methods with single-molecule resolution, namely single-molecule localization microscopy and continuous biosensing by particle motion. The biosensing functionality of the glycan-remodeled antibodies was demonstrated in a sandwich immunosensor for procalcitonin. The results show that glycan-remodeled antibodies enable oriented immobilization and biosensing functionality with low nonspecific binding on antifouling polymer substrates.

Simultaneous dose and dose rate optimization via dose modifying factor modeling for FLASH effective dose.

BACKGROUND: Although the FLASH radiotherapy (FLASH) can improve the sparing of organs-at-risk (OAR) via the FLASH effect, it is generally a tradeoff between the physical dose coverage and the biological FLASH coverage, for which the concept of FLASH effective dose (FED) is needed to quantify the net improvement of FLASH, compared to the conventional radiotherapy (CONV). PURPOSE: This work will develop the first-of-its-kind treatment planning method called simultaneous dose and dose rate optimization via dose modifying factor modeling (SDDRO-DMF) for proton FLASH that directly optimizes FED. METHODS: SDDRO-DMF models and optimizes FED using FLASH dose modifying factor (DMF) models, which can be classified into two categories: (1) the phenomenological model of the FLASH effect, such as the FLASH effectiveness model (FEM); (2) the mechanistic model of the FLASH radiobiology, such as the radiolytic oxygen depletion (ROD) model. The general framework of SDDRO-DMF will be developed, with specific DMF models using FEM and ROD, as a demonstration of general applicability of SDDRO-DMF for proton FLASH via transmission beams (TB) or Bragg peaks (BP) with single-field or multi-field irradiation. The FLASH dose rate is modeled as pencil beam scanning dose rate. The solution algorithm for solving the inverse optimization problem of SDDRO-DMF is based on iterative convex relaxation method. RESULTS: SDDRO-DMF is validated in comparison with IMPT and a state-of-the-art method called SDDRO, with demonstrated efficacy and improvement for reducing the high dose and the high-dose volume for OAR in terms of FED. For example, in a SBRT lung case of the dose-limiting factor that the max dose of brachial plexus should be no more than 26 Gy, only SDDRO-DMF met this max dose constraint; moreover, SDDRO-DMF completely eliminated the high-dose (V70%) volume to zero for CTV10mm (a high-dose region as a 10 mm ring expansion of CTV). CONCLUSION: We have proposed a new proton FLASH optimization method called SDDRO-DMF that directly optimizes FED using phenomenological or mechanistic models of DMF, and have demonstrated the efficacy of SDDO-DMF in reducing the high-dose volume or/and the high-dose value for OAR, compared to IMPT and a state-of-the-art method SDDRO.

Exogenous putrescine plays a switch-like influence on the pH stress adaptability of biofilm-based activated sludge.

Microbial community adaptability to pH stress plays a crucial role in biofilm formation. This study aims to investigate the regulatory mechanisms of exogenous putrescine on pH stress, as well as enhance understanding and application for the technical measures and molecular mechanisms of biofilm regulation. Findings demonstrated that exogenous putrescine acted as a switch-like distributor affecting microorganism pH stress, thus promoting biofilm formation under acid conditions while inhibiting it under alkaline conditions. As pH decreases, the protonation degree of putrescine increases, making putrescine more readily adsorbed. Protonated exogenous putrescine could increase cell membrane permeability, facilitating its entry into the cell. Subsequently, putrescine consumed intracellular H+ by enhancing the glutamate-based acid resistance strategy and the γ-aminobutyric acid metabolic pathway to reduce acid stress on cells. Furthermore, putrescine stimulated ATPase expression, allowing for better utilization of energy in H+ transmembrane transport and enhancing oxidative phosphorylation activity. However, putrescine protonation was limited under alkaline conditions, and the intracellular H+ consumption further exacerbated alkali stress and inhibits cellular metabolic activity. Exogenous putrescine promoted the proportion of fungi and acidophilic bacteria under acidic stress and alkaliphilic bacteria under alkali stress while having a limited impact on fungi in alkaline biofilms. Increasing Bdellovibrio under alkali conditions with putrescine further aggravated the biofilm decomposition. This research shed light on the unclear relationship between exogenous putrescine, environmental pH, and pH stress adaptability of biofilm. By judiciously employing putrescine, biofilm formation could be controlled to meet the needs of engineering applications with different characteristics.IMPORTANCEThe objective of this study is to unravel the regulatory mechanism by which exogenous putrescine influences biofilm pH stress adaptability and understand the role of environmental pH in this intricate process. Our findings revealed that exogenous putrescine functioned as a switch-like distributor affecting the pH stress adaptability of biofilm-based activated sludge, which promoted energy utilization for growth and reproduction processes under acidic conditions while limiting biofilm development to conserve energy under alkaline conditions. This study not only clarified the previously ambiguous relationship between exogenous putrescine, environmental pH, and biofilm pH stress adaptability but also offered fresh insights into enhancing biofilm stability within extreme environments. Through the modulation of energy utilization, exerting control over biofilm growth and achieving more effective engineering goals could be possible.