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.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.

[Factors influencing cognitive function among the older adults in Beijing].

OBJECTIVE: To explore the current status of cognitive function of the older adults in Beijing, and to analyze the factors affecting their cognitive function. METHODS: It was a cross-sectional study. A questionnaire survy was conducted in 2023 among the older adults in Beijing. The cognitive function of the older adults was assessed with the Hong Kong brief cognitive test (HKBC) scale, a simple cognitive assessment tool. Using SPSS 27.0 to perform the descriptive analysis and multiple linear regression analysis of factors, which affect cognitive function among the older adults. RESULTS: Totally 349 older adults were recruited, with the highest percentage of respondents aged 60-69 years (41.3%), of whom 58.7% were female, 88.0% of the respondents had a junior high school or above education level. Most of the older adults (68.8%) worked 35-48 h/week before they retired, and 14.0% of the older adults had a family history of dementia. After controlling age and gender, the linear regression analysis showed that marital status married (ß=0.501, 95%CI: 0.144-0.859) and 3-4 times physical activity per week (ß=0.617, 95%CI: 0.087-1.148) were protective factors of cognitive function in the older adults, and depressive symptoms were a risk factor (ß= -0.723, 95%CI: -1.198 to -0.247) of cognitive function for the older adults. CONCLUSION: In this study, the factors influencing cognitive function among the older adults was analyzed based on a life-cycle perspective. Lack of physical activity and depressive symptoms were risk factors for cognitive function among the older adults. It was suggested that strengthening physical activity, improving mental health of the older adults, as well as conducting preventive intervention in early stages of the life-cycle will be benefit for preventing and slowing cognitive decline in the older adults.

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.

Cardinality-constrained plan-quality and delivery-time optimization method for proton therapy.

BACKGROUND: While minimizing plan delivery time is beneficial for proton therapy in terms of motion management, patient comfort, and treatment throughput, it often poses a tradeoff with optimizing plan quality. A key component of plan delivery time is the energy switching time, which is approximately proportional to the number of energy layers, that is, the cardinality. PURPOSE: This work aims to develop a novel optimization method that can efficiently compute the pareto surface between plan quality and energy layer cardinality, for the planner to navigate through this quality-and-efficiency tradeoff and select the appropriate plan of a balanced tradeoff. METHODS: A new IMPT method CARD is proposed that (1) explicitly incorporates the minimization of energy layer cardinality as an optimization objective, and (2) automatically generates a set of plans sequentially with a descending order in number of energy layers. The energy layer cardinality is penalized through the l1,0-norm regularization with an upper bound, and the upper bound is monotonically decreased to compute a series of treatment plans with gradually decreased energy layer cardinality on the quality-and-efficiency pareto surface. For any given treatment plan, the plan optimality is enforced using dose-volume planning objectives and the plan deliverability is imposed through minimum-monitor-unit (MMU) constraints, with optimization solution algorithm based on iterative convex relaxation. RESULTS: The new method CARD was validated in comparison with the benchmark plan of all energy layers (P0), and a state-of-the-art method called MMSEL, using prostate, head-and-neck (HN), lung, pancreas, liver and brain cases. While labor-intensive and time-consuming manual parameter tuning was needed for MMSEL to generate plans of predefined energy layer cardinality, CARD automatically and efficiently computed all plans with sequentially decreasing predefined energy layer cardinality all at once. With the acceptable plan quality (i.e., no more than 110% of total optimization objective value from P0), CARD achieved the reduction of number of energy layers to 52% (from 77 to 40), 48% (from 135 to 65), 59% (from 85 to 50), 67% (from 52 to 35), 80% (from 50 to 40), and 30% (from 66 to 20), for prostate, HN, lung, pancreas, liver, and brain cases, respectively, compared to P0, with overall better plan quality than MMSEL. Moreover, due to the nonconvexity of the MMU constraint, CARD provided the similar or even smaller optimization objective than P0, at the same time with fewer number of energy layers, that is, 55 versus 77, 85 versus 135, 45 versus 52, and 25 versus 66 for prostate, HN, pancreas, and brain cases, respectively. CONCLUSIONS: We have developed a novel optimization algorithm CARD that can efficiently and automatically compute a series of treatment plans of any given energy layer sequentially, which allows the planner to navigate through the plan-quality and energy-layer-cardinality tradeoff and select the appropriate plan of a balanced tradeoff.

Fabrication of an Fe-Doped ZIF-67 Derived Magnetic Fe/Co/C Composite for Effective Removal of Congo Red.

The dyes in printing and dyeing wastewater are harmful to the human body and the environment. It is essential to develop practical and effective adsorbents to deal with them. In this study, an Fe-doped, ZIF-67 derived Fe/Co/C composite material with strong magnetism was successfully synthesized. The effects of pH, initial concentration, and adsorption time on the properties of the adsorbent were investigated. To further improve the removal efficiency and enhance the practicality, potassium peroxymonosulfate (PMS) was added to the system due to its Fenton-like effect. Then, an Fe/Co/C composite was used with PMS to remove Congo red (CR) with a 98% removal of 250 mg·L-1. Moreover, for its high saturation magnetization of 85.4 emu·g-1, the Fe/Co/C composite can be easily recovered by applying a magnetic field, solving the problem that powdery functional materials are difficult to recover and, thus, avoiding secondary pollution. Furthermore, since the composite material was doped before carbonization, this synthetic strategy is flexible and the required metal elements can be added at will to achieve different purposes. This study demonstrates that this Fe-doped, ZIF-67 derived magnetic material has potential application prospects for dye adsorption.

Evidence that a Novel Chalcone Derivative, Compound 27, Acts on the Epithelium Via the PI3K/AKT/Nrf2-Keap1 Signaling Pathway, to Mitigate LPS-Induced Acute Lung Injury in Mice.

Acute lung injury (ALI) is a highly heterogeneous clinical syndrome and an important cause of mortality in critically ill patients, with limited treatment options currently available. Chalcone, an essential secondary metabolite found in edible or medicinal plants, exhibits good antioxidant activity and simple structure for easy synthesis. In our study, we synthesized a novel chalcone derivative, compound 27 (C27). We hypothesized that C27 could be a potential treatment for acute respiratory distress syndrome (ARDS). Therefore, the protective effects of C27 on lung epithelial cells during ALI and the underlying molecular mechanisms were investigated. In vivo, Intratracheal instillation of LPS (10 mg/kg) was used to induce acute lung injury in mice. In vitro, the bronchial epithelial cell line (Beas-2b) was treated with 30 µM tert-butyl hydroperoxide (t-BHP) to simulate oxidative stress. Our findings demonstrate that pretreatment with C27 reduces LPS-induced oxidative destruction and cellular apoptosis in lung tissues of mice. Furthermore, it significantly attenuates t-BHP-induced cellular reactive oxygen species (ROS) generation, mitochondrial damage, and apoptosis in vitro. Mechanistically, the signaling pathway involving Nrf2-Keap1 and the downstream antioxidative proteins were activated by C27 in vivo. Additionally, PI3K inhibitor LY294002 and Nrf2 inhibitor ML385 abolished the effect of C27 in vitro, indicating that the protective effect of C27 is mediated via the PI3K/AKT/Nrf2-Keap1 pathway. Our study provides evidence that C27 protects against LPS-induced ALI by mitigating oxidative stress via activation of the PI3K/AKT/Nrf2-Keap1 signaling pathway. Therefore, we hypothesize that C27 represents a viable alternative for ALI therapy.

Stochastic processes shape microbial community assembly in biofilters: Hidden role of rare taxa.

Stochastic and deterministic processes are the major themes governing microbial community assembly; however, their roles in bioreactors are poorly understood. Herein, the mechanisms underlying microbial assembly and the effect of rare taxa were studied in biofilters. Phylogenetic tree analysis revealed differences in microbial communities at various stages. Null model analysis showed that stochastic processes shaped the community assembly, and deterministic processes emerged only in the inoculated activated sludge after domestication. This finding indicates the dominant role of stochastic factors (biofilm formation, accumulation, and aging). The Sloan neutral model corroborated the advantages of stochastic processes and mainly attributed these advantages to rare taxa. Cooccurrence networks revealed the importance of rare taxa, which accounted for more than 85% of the keystones. Overall, these results provide good foundations for understanding community assembly, especially the role of rare taxa, and offer theoretical support for future community design and reactor regulation.

Uterine mesothelial cysts mimicking ovarian cysts in a primipara patient with a history of Cesarean section: A case report and review of the literature.

OBJECTIVE: We describe a rare case of uterine mesothelial cysts mimicking ovarian cysts in a primipara patient with a history of Cesarean section. CASE REPORT: A 39-year-old female patient with history of Cesarean section presented with dysmenorrhea. Sonography revealed that a hypoechoic and anechoic multicystic complex, which was located on the right side of the pelvic cavity, had infiltrated the adjacent posterior wall of the uterus, and it was preoperatively misdiagnosed as ovarian cysts with suspected endometrioma. Laparoscopic surgery revealed multiple cystic lesions filled with clear yellow fluid on the posterior uterine wall instead of the adnexa. Laparoscopic uterine cystectomy was performed, and the patient's recovery was uneventful. Pathohistological and immunohistochemical examinations confirmed the diagnosis of uterine mesothelial cysts. CONCLUSION: Uterine mesothelial cysts should be considered in the differential diagnosis of pelvic lesions. Increasing the awareness of this rare disease can contribute to improved evaluation, decision-making, and disease management.