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Background and Objective: This randomized controlled trial investigated the influence of perioperative lidocaine administration on the postoperative inflammatory response in patients undergoing robot-assisted radical prostatectomy, with the results having potential implications for postoperative recovery and cancer recurrence via neutrophil extracellular trapping (NETosis). Materials and Methods: In total, 58 patients with localized prostate cancer were randomly assigned to receive an intravenous infusion of 2% lidocaine or a saline placebo intraoperatively. Serum levels of interleukin (IL)-6, IL-10, and IL-17, tumor necrosis factor(TNF)-α, interferon(IFN)-γ, neutrophil elastase (NE), citrullinated histone3 (CitH3), and myeloperoxidase (MPO) were determined preoperatively and at 24 h postoperatively. Biochemical recurrence (BCR) was assessed over a follow-up period of 2 years. Results: The lidocaine group showed a significant change in MPO, a greater reduction in IL-10 level, and a smaller increase in the NE level compared to the placebo group, suggesting a modulatory effect of lidocaine on certain anti-inflammatory and neuroendocrine pathways. No significant difference in the BCR rate was observed between the two groups. Conclusions: Perioperative lidocaine administration selectively modulates certain inflammatory and neuroendocrine responses after robot-assisted radical prostatectomy surgery, potentially influencing recovery outcomes. These findings highlight the need for further investigations of the role of lidocaine in Enhanced Recovery After Surgery protocols, particularly in oncologic surgeries.

Background: Robot-assisted laparoscopic partial nephrectomy (RAPN) for renal tumor treatment provides ergonomic advantages to surgeons and improves surgical outcomes. However, moderate-to-severe pain is unavoidable even after minimally invasive surgery. Despite the growing interest in multimodal analgesia, few studies have directly compared its efficacy with intrathecal morphine, a traditional opioid-based analgesic. Methods: We retrospectively investigated the efficacy of multimodal analgesia compared with that of intrathecal analgesia and intravenous patient-controlled analgesia (IV-PCA) in patients who underwent transperitoneal RAPN at our institute between 2020 and 2022. Among the 334 patients who met the inclusion criteria, intrathecal analgesia using morphine 200 µg was performed in 131 patients, and multimodal analgesia, including transversus abdominis plane block and intraoperative infusion of paracetamol 1 g and nefopam 20 mg, was administered to 105 patients. The remaining 98 patients received postoperative IV-PCA alone. Results: As the primary outcome, the area under the curve of pain scores over 24 h was significantly lower in the intrathecal analgesia and multimodal analgesia groups than in the IV-PCA group (89 [62–108] vs. 86 [65–115] vs. 108 [87–126] h, p < 0.001). Cumulative opioid requirements were also significantly lower in the intrathecal analgesia and multimodal analgesia groups at 24 h after surgery (p < 0.001). However, postoperative nausea and vomiting were significantly increased in the intrathecal analgesia group (27.5% vs. 13.3% vs. 13.3%, p = 0.005). Conclusions: Multimodal analgesia with a transversus abdominis plane block is an efficient analgesic method with fewer adverse effects compared to other analgesic methods. Our findings suggest the efficacy and safety of a multimodal approach for opioid-sparing analgesia after RAPN in the current opioid epidemic.

The mechanical ventilation systems used in houses are designed to reduce carbon dioxide emissions while minimizing the energy loss resulting from ventilation. However, the increase in indoor fine particulate (PM2.5) concentration because of external PM2.5 influx through the ventilation system poses a problem. Here, we analyzed the changes in indoor PM2.5 concentration, distinguishing between cases of high and low outdoor PM2.5 concentrations and considering the efficiency of the filters used in residential mechanical ventilation systems. When using filters with the minimum efficiency reporting value (MERV) of 10 in the ventilation system, the outdoor PM2.5 concentration was 5 μg/m³; compared to the initial concentration, the indoor PM2.5 concentration after 60 min decreased to 73%. When the outdoor PM2.5 concentration was 30–40 μg/m³, the indoor PM2.5 concentration reached 91%. However, when MERV 13 filters were used, the indoor PM2.5 concentration consistently dropped to 73–76%, regardless of the outdoor PM2.5 concentration. Furthermore, by comparing the established equation with the mass balance model, the error was confirmed to be within 5%, indicating a good fit. This allows for the prediction of indoor PM2.5 under various conditions when using mechanical ventilation systems, enabling the formulation of strategies for maintaining indoor PM2.5, as recommended by the World Health Organization.

The educational and play-related activities of children proceed mainly indoors in a kindergarten. High concentrations of indoor PM2.5 and CO2 have been linked to various harmful effects on children, considerably impacting their educational outcomes in kindergarten. In this study, we explore different scenarios involving the operation of mechanical ventilation systems and air purifiers in kindergartens. Using numerical models to analyze indoor CO2 and PM2.5 concentration, we aim to optimize strategies that effectively reduce these harmful pollutants. We found that the amount of ventilation required to maintain good air quality, per child, was approximately 20.4 m3/h. However, we also found that as the amount of ventilation increased, so did the concentration of indoor PM2.5; we found that this issue can be resolved using a high-grade filter (i.e., a MERV 13 grade filter with a collection efficiency of 75%). This study provides a scientific basis for reducing PM2.5 concentrations in kindergartens, while keeping CO2 levels low.

(1) In this study, we developed a deep learning (DL) model that can be used to predict late bladder toxicity. (2) We collected data obtained from 281 uterine cervical cancer patients who underwent definitive radiation therapy. The DL model was trained using 16 features, including patient, tumor, treatment, and dose parameters, and its performance was compared with that of a multivariable logistic regression model using the following metrics: accuracy, prediction, recall, F1-score, and area under the receiver operating characteristic curve (AUROC). In addition, permutation feature importance was calculated to interpret the DL model for each feature, and the lightweight DL model was designed to focus on the top five important features. (3) The DL model outperformed the multivariable logistic regression model on our dataset. It achieved an F1-score of 0.76 and an AUROC of 0.81, while the corresponding values for the multivariable logistic regression were 0.14 and 0.43, respectively. The DL model identified the doses for the most exposed 2 cc volume of the bladder (BD2cc) as the most important feature, followed by BD5cc and the ICRU bladder point. In the case of the lightweight DL model, the F-score and AUROC were 0.90 and 0.91, respectively. (4) The DL models exhibited superior performance in predicting late bladder toxicity compared with the statistical method. Through the interpretation of the model, it further emphasized its potential for improving patient outcomes and minimizing treatment-related complications with a high level of reliability.

[177Lu]Ludotadipep, which enables targeted delivery of beta-particle radiation to prostate tumor cells, had been suggested as a promising therapeutic option for mCRPC. From November 2020 to March 2022, a total of 30 patients were enrolled for single dose of [177Lu]Ludotadipep RPT, 6 subjects in each of the 5 different activity groups of 1.9 GBq, 2.8 GBq, 3.7 GBq, 4.6 GBq, and 5.6 GBq. [177Lu]Ludotadipep was administered via venous injection, and patients were hospitalized for three days to monitor for any adverse effects. Serum PSA levels were followed up at weeks 1, 2, 3, 4, 6, 8, and 12, and PSMA PET/CT with [18F]Florastamin was obtained at baseline and again at weeks 4 and 8. The subjects required positive PSMA PET/CT prior to [177Lu]Ludotadipep administration. Among the 29 subjects who received [177Lu]Ludotadipep, 36 treatment emergent adverse events (TEAEs) occurred in 17 subjects (58.6%) and 4 adverse drug reactions (ADRs) in 3 subjects (10.3%). Of the total 24 subjects who had full 12-week follow-up data, 16 (66.7%) showed decrease in PSA of any magnitude, and 9 (37.5%) showed a decrease in PSA by 50% or greater. A total of 5 of the 24 patients (20.8%) showed disease progression (PSA increase of 25% or higher from the baseline) at the 12th week following single dose of [177Lu]Ludotadipep. These data thus far suggest that [177Lu]Ludotadipep could be a promising RPT agent with low toxicity in mCRPC patients who have not been responsive to conventional treatments.

This research addresses the problem of interobserver variability (IOV), in which different oncologists manually delineate varying primary gross tumor volume (pGTV) contours, adding risk to targeted radiation treatments. Thus, a method of IOV reduction is urgently needed. Hypothesizing that the radiation oncologist’s IOV may shrink with the aid of IOV maps, we propose IOV prediction network (IOV-Net), a deep-learning model that uses the fuzzy membership function to produce high-quality maps based on computed tomography (CT) images. To test the prediction accuracy, a ground-truth pGTV IOV map was created using the manual contour delineations of radiation therapy structures provided by five expert oncologists. Then, we tasked IOV-Net with producing a map of its own. The mean squared error (prediction vs. ground truth) and its standard deviation were 0.0038 and 0.0005, respectively. To test the clinical feasibility of our method, CT images were divided into two groups, and oncologists from our institution created manual contours with and without IOV map guidance. The Dice similarity coefficient and Jaccard index increased by ~6 and 7%, respectively, and the Hausdorff distance decreased by 2.5 mm, indicating a statistically significant IOV reduction (p < 0.05). Hence, IOV-net and its resultant IOV maps have the potential to improve radiation therapy efficacy worldwide.

This paper proposes a robotic system that automatically identifies and removes spatters generated while removing the back-bead left after the electric resistance welding of the outer and inner surfaces during pipe production. Traditionally, to remove internal spatters on the front and rear of small pipes with diameters of 18–25 cm and lengths of up to 12 m, first, the spatter locations (direction and length) are determined using a camera that is inserted into the pipe, and then a manual grinder is introduced up to the point where spatters were detected. To optimize this process, the proposed robotic system automatically detects spatters by analyzing the images from a front camera and removes them, using a grinder module, based on the spatter location and the circumferential coordinates provided by the detection step. The proposed robot can save work time by reducing the required manual work from two points (the front and back of the pipe) to a single point. Image recognition enables the detection of spatters with sizes between 0.1 and 10 cm with 94% accuracy. The internal average roughness, Ra, of the pipe was confirmed to be 1 µm or less after the spatters were finally removed.

It is important to control airborne particles in residential houses for protecting human health. Indoor particulate matter of 2.5) can be effectively monitored and managed using an air purifier. In this study, the actual clean air delivery rates in residential houses (CADRActual) were acquired by comparing decay rates of fine particles with and without operations of the air purifier under actual conditions, following the standard CADR of an air purifier obtained in a closed test chamber. The measurements of CADRActual at different outdoor PM2.5 concentrations over a month in two residential houses revealed different airtightness levels, compared to the standardized clean air delivery rate of the air purifier (CADRAP). Air changes per hour at 50 Pa (ACH50) was 4.8 h−1 for “house A” (built in 2007) and 2.1 h−1 for “house B” (built in 2018). The CADR of the air purifier used in this study was 10.6 m3/min, while the averaged CADRActual at the “house A” was 7.2 m3/min (approximately 66% of the CADR of the air purifier) and 9.5 m3/min at “house B” (approximately 90% of the CADR of the air purifier). Under the outdoor PM2.5 concentrations of 3, the averaged CADRActual of house A and house B were 7.8 ± 0.3 and 9.7 ± 0.4 m3/min, respectively. However, under the outdoor PM2.5 concentrations of >35 μg/m3, the analogous averaged concentrations were 6.8 ± 0.6 and 9.6 ± 0.3 m3/min for houses A and B, respectively. The measured CADRActual agreed well with the theoretical estimates of CADRActual acquired by the mass balance equation using the infiltration rate of ACH50/20. We also estimated CADRActual/CADRAP for house C built in 2017, where the ACH50 was 1.8 h−1. Overall, this study demonstrated how CADRActual/CADRAP of an air purifier at residential houses can be predicted according to outdoor PM2.5 concentration and airtightness of the house. As shown, it can be closer to 1 at lower ACH50 houses and at lower outdoor PM2.5 concentrations.

Indoor PM2.5 must be effectively controlled to minimize adverse impacts on public health. Cooking is one of the main sources of PM2.5 in residential areas, and indoor air quality (IAQ) management methods such as natural and mechanical ventilation, range hood, and air purifier are typically used to reduce cooking-generated PM2.5 concentrations. However, studies on the combined effects of various IAQ management methods on indoor PM2.5 reduction and energy consumption are limited. In this study, a theoretical model was established to estimate the performance of various IAQ management methods for controlling indoor PM2.5 concentrations and energy consumption. The model was verified by comparative experiments in which, various IAQ management methods were operated individually or combined. Seasonal energy consumption was calculated through the verified model, and energy consumption saving scenarios were derived for maintaining indoor PM2.5 concentrations less than 10 μg/m3, a World Health Organization annual guideline, under fair and poor outdoor PM2.5 concentrations of 15 and 50 μg/m3, respectively. Based on our results, we found that energy consumption could be reduced significantly by applying natural ventilation in spring, autumn, and summer and mechanical ventilation in winter. Our study identified efficient energy saving PM2.5 management scenarios using various IAQ management methods by predicting indoor PM2.5 concentration and energy consumption according to the annual life patterns of typical residents in South Korea.

To identify the long-term trend of particle size variation, we analyzed aerosol optical depth (AOD, τ) separated as dust (τD) and coarse-(τPC) and fine-pollution particles (τPF) depending on emission sources and size. Ångström exponent values are also identified separately as total and fine-mode particles (αT and αPF). We checked these trends in various ways; (1) first-order linear regression analysis of the annual average values, (2) percent variation using the slope of linear regression method, and (3) a reliability analysis using the Mann–Kendall (MK) test. We selected 17 AERONET sun/sky radiometer sites classified into six regions, i.e., Europe, North Africa, the Middle East, India, Southeast Asia, and Northeast Asia. Although there were regional differences, τ decreased in Europe and Asian regions and increased in the Middle East, India, and North Africa. Values of τPC and τPF, show that aerosol loading caused by non-dust aerosols decreased in Europe and Asia and increased in India. In particular, τPF considerably decreased in Europe and Northeast Asia (95% confidential levels in MK-test), and τPC decreased in Northeast Asia (Z-values for Seoul and Osaka are −2.955 and −2.306, respectively, statistically significant if |z| ≥ 1.96). The decrease in τPC seems to be because of the reduction of primary and anthropogenic emissions from regulation by air quality policies. The meaningful result in this paper is that the particle size became smaller, as seen by values of αT that decreased by −3.30 to −30.47% in Europe, North Africa, and the Middle East because αT provides information on the particle size. Particle size on average became smaller over India and Asian regions considered in our study due to the decrease in coarse particles. In particular, an increase of αPF in most areas shows the probability that the average particle size of fine-mode aerosols became smaller in recent years. We presumed the cause of the increase in αT is because relatively large-sized fine-mode particles were eliminated due to air quality policies.

Several detectors have been developed to measure radiation doses during radiotherapy. However, most detectors are not flexible. Consequently, the airgaps between the patient surface and detector could reduce the measurement accuracy. Thus, this study proposes a dose measurement system based on a flexible copper indium gallium selenide (CIGS) solar cell. Our system comprises a customized CIGS solar cell (with a size 10 × 10 cm2 and thickness 0.33 mm), voltage amplifier, data acquisition module, and laptop with in-house software. In the study, the dosimetric characteristics, such as dose linearity, dose rate independence, energy independence, and field size output, of the dose measurement system in therapeutic X-ray radiation were quantified. For dose linearity, the slope of the linear fitted curve and the R-square value were 1.00 and 0.9999, respectively. The differences in the measured signals according to changes in the dose rates and photon energies were

The feasibility of proton minibeam radiation therapy (pMBRT) using a multislit collimator (MSC) and a scattering device was evaluated for clinical use at a clinical proton therapy facility. We fabricated, through Monte Carlo (MC) simulations, not only an MSC with a high peak-to-valley dose ratio (PVDR) at the entrance of the proton beam, to prevent radiation toxicity, but also a scattering device to modulate the PVDR in depth. The slit width and center-to-center distance of the diverging MSC were 2.5 mm and 5.0 mm at the large end, respectively, and its thickness and available field size were 100 mm and 76 × 77.5 mm2, respectively. Spatially fractionated dose distributions were measured at various depths using radiochromic EBT3 films and also tested on bacterial cells. MC simulation showed that the thicker the MSC, the higher the PVDR at the phantom surface. Dosimetric evaluations showed that lateral dose profiles varied according to the scatterer’s thickness, and the depths satisfying PVDR = 1.1 moved toward the surface as their thickness increased. The response of the bacterial cells to the proton minibeams’ depth was also established, in a manner similar to the dosimetric pattern. Conclusively, these results strongly suggest that pMBRT can be implemented in clinical centers by using MSC and scatterers.

Aerosol types in Asian capital cities were classified using a random forest (RF) satellite-based aerosol classification model during 2018–2020 in an investigation of the contributions of aerosol types, with or without Aerosol Robotic Network (AERONET) observations. In this study, we used the recently developed RF aerosol classification model to detect and classify aerosols into four types: pure dust, dust-dominated aerosols, strongly absorbing aerosols, and non-absorbing aerosols. Aerosol optical and microphysical properties for each aerosol type detected by the RF model were found to be reasonably consistent with those for typical aerosol types. In Asian capital cities, pollution-sourced aerosols, especially non-absorbing aerosols, were found to predominate, although Asian cities also tend to be seasonally affected by natural dust aerosols, particularly in East Asia (March–May) and South Asia (March–August). No specific seasonal effects on aerosol type were detected in Southeast Asia, where there was a predominance of non-absorbing aerosols. The aerosol types detected by the RF model were compared with those identified by other aerosol classification models. This study indicates that the satellite-based RF model may be used as an alternative in the absence of AERONET sites or observations.

Brachytherapy is an important technique to increase the overall survival of cervical cancer patients. However, a possible shift of the applicators in relation to the target and organs at risk may occur between imaging and treatment. Without daily adaptive brachytherapy planning, these applicator displacements can lead to a significant change in dose distribution. In order to resolve it, a robust optimization method had been developed using a genetic algorithm combined with a median absolute deviation as a robustness evaluation function. The resulting robustness plans from our strategy might be worth considering according to the GEC-ESTRO guidelines. From the point of view of dose delivery uncertainty from applicator displacement, the robust optimization may be considered with caution in a single-plan approach for High Dose Rate brachytherapy treatment planning and should be confirmed by a more thorough investigation.

This study describes the development of a beam monitoring system for the verification of entrance dose map in pencil beam scanning (PBS) proton therapy based on fiber optic radiation sensors (FORS) and the validation of this system through a feasibility study. The beam monitoring system consisted of 128 optical fibers optically coupled to photo-multiplier tubes. The performance of the beam monitoring system based on FORS was verified by comparing 2D dose maps of square-shaped fields of various sizes, which were obtained using conventional dosimeters such as MatriXX and EBT3 film, with those measured using FORS. The resulting full-width at half maximum and penumbra were compared for PBS proton beams, with a ≤2% difference between each value, indicating that measurements using the conventional dosimetric tool corresponded to measurements based on FORS. For irregularly-shaped fields, a comparison based on the gamma index between 2D dose maps obtained using MatriXX and EBT3 film and the 2D dose map measured by the FORS showed passing rates of 96.9 ± 1.3% and 96.2 ± 1.9%, respectively, confirming that FORS-based measurements for PBS proton therapy agreed well with those measured using the conventional dosimetric tools. These results demonstrate that the developed beam monitoring system based on FORS is good candidate for monitoring the entrance dose map in PBS proton therapy.