Unique biomarkers as a potential predictive tool for differentiation of Bacillus cereus group based on real-time PCR.

The aim of the study was to develop unique biomarkers for qPCR detection of Bacillus cereus group. Clinical and soil isolates were identified by specifically designed biomarkers - Lipoprotein (OPL-114-lipo), Methyltransferase (MT-17) and S-layer homology domain protein (151-1BC). In order to design biomarkers, we used 120 bacterial strains grouped into B. cereus and non-Bacillus group. The B. cereus group was confirmed by 108 strains of B. cereus and B. thuringiensis (30 reference and 78 wild), along with 3 strains of B. mycoides, B. pseudomycoides, and B. weihenstephanensis; while the non-Bacillus group was composed of 9 Gram-positive and Gram-negative strains. Direct analysis of samples revealed specificity towards identification and characterization of B. cereus group. The newly developed markers OPL-114-lipo and MT-17 showed specificity of 95% and 81%, respectively in identification of B. cereus. They are efficient tools to identify contaminated sources and the degree of bacterial contamination. Environmental and food samples do not require band isolation, re-amplification, sequencing or sequence identification. Thus, reducing the time and cost of analysis. Hence, it will be an alternative approach to traditional culture methods. Commercial food processing industries will be able to employ these biomarkers specific for B. cereus group as a detection tool to reduce economic loss due to B. cereus contamination.

Molecular discrimination of Bacillus cereus group species in foods (lettuce, spinach, and kimbap) using quantitative real-time PCR targeting groEL and gyrB.

The aim of the study was to identify and evaluate specific biomarkers to differentiate within Bacillus cereus group species from contaminated food samples with the use of real-time PCR. A total of 120 strains, comprising of 28 reference, 2 type, 78 wild strains of B. cereus and B. thuringiensis along with 12 strains representing 2 bacterial groups - B. mycoides, B. pseudomycoides, B. weihenstephanensis (B. cereus group); B. amyloliquefaciens, B. subtilis, Enterococcus faecalis, Escherichia coli, Listeria monocytogenes, Micrococcus luteus, Salmonella enterica, Staphylococcus aureus, Streptococcus pyogenes (non-Bacillus sp.) were identified by applying valid biomarkers (groEL and gyrB). In addition, the presence of B. cereus group was determined in three different artificially contaminated vegetable samples (lettuce, spinach, and kimbap), using prominent biomarkers targeting on chaperonin protein (GroEL) and topoisomerase enzyme protein (gyrB). Direct analysis of samples revealed the specificity towards identification and characterization of the B. cereus group among wild, reference and type strains and the type strain inoculated in vegetables. Our results demonstrated two existing biomarkers groEL and gyrB with a high specificity of 98% and 96% respectively to analyze the total B. cereus group. Further, we also reported the detection limit of groEL and gyrB in food samples was 3.5 and 3.7 log CFU/g respectively. Thus, the developed real-time PCR approach can be a reliable and effective tool for the identification of B. cereus group strains present in environment and food samples. This does not require band isolation, re-amplification, sequencing or sequence identification, thus reducing the time and cost of analysis.

Risk factors associated with early mortality in patients with multiple myeloma who were treated upfront with a novel agents containing regimen.

BACKGROUND: Although the introduction of novel agents improved the survival outcomes in patients with multiple myeloma (MM), some patients died within one year (early mortality, EM) following diagnosis. In this study, we evaluated the EM rate, and investigated the risk factors associated with EM in MM patients. METHODS: Retrospective data from 542 patients who were initially treated with a novel agent-containing regimen were analyzed. RESULTS: The median overall survival (OS) for the entire cohort was 56.5 months. The median OS in the 2010-2014 group was longer than in the 2002-2009 group (59.2 months vs. 49.1 months, P = 0.054). The rate of EM was 13.8 %, and the most common causes of EM were infection and comorbidity. In multivariate analysis, the age-adjusted Charlson comorbidity index (ACCI ≥ 4), low body mass index (BMI < 20 kg/m(2)), thrombocytopenia, and renal failure were significantly associated with EM. The presence of none, 1, or ≥ 2 factors was associated with a 4.1 %, 14.3 %, or 27.4 % risk of EM (P < 0.001), respectively. The median OS times were significantly different depending on the presence of factors associated with EM (P < 0.001). CONCLUSIONS: In conclusion, the ACCI (≥ 4), low BMI, thrombocytopenia and renal failure were strong predictors for EM in the novel agent era. The results of this study will help to identify patients at high risk for EM, and may be helpful to more accurately predict prognosis of MM patients in the novel-agent era.

Thalidomide-based induction regimens are as effective as bortezomib-based regimens in elderly patients with multiple myeloma with cereblon expression.

Cereblon (CRBN) has been identified as a primary target of immunomodulatory drugs and is considered a biomarker for the prediction of outcomes after thalidomide- or lenalidomide-based treatments. In this study, we evaluated CRBN expression in bone marrow (BM) tissue at diagnosis and investigated the relationship between CRBN expression and treatment outcomes after thalidomide- or bortezomib-based front-line therapies in 89 elderly patients with multiple myeloma (MM). CRBN expression at the time of diagnosis was evaluated with immunohistochemical (IHC) staining for myeloma cells in paraffin wax-embedded BM tissue. CRBN-immunostained slides were scored by intensity and diffuseness, and a total score of >6 was defined as CRBN-positive (CRBN(+)). Thirty-eight patients (45.2 %) were CRBN(+). Among patients treated with thalidomide-based regimens, CRBN(+) patients showed a better treatment response than did CRBN-negative patients (35.0 vs. 11.8 % complete response rate, respectively; HR = 4.038, P = 0.137). During a median follow-up of 31.8 months, patients treated with bortezomib-based regimens had a longer time to progression (TTP) than did patients treated with thalidomide-based regimens (15.6 vs. 13.2 months, respectively; P = 0.047), but early mortality occurred frequently in patients treated with bortezomib-based regimens. Additionally, there was no significant difference in survival outcomes between thalidomide- and bortezomib-based regimens in CRBN(+) patients (median TTP, 13.8 vs. 15.6 months, respectively; P = 0.842 and median OS, 39.3 vs. 30.1 months, respectively; P = 0.074). These data suggest that thalidomide-based regimens are as effective as bortezomib-based regimens in elderly patients with MM who are CRBN(+). Thus, CRBN positivity, by IHC staining, may be useful in deciding appropriate treatment options in elderly patients with MM.

Pralatrexate in Combination with Bortezomib for Relapsed or Refractory Peripheral T Cell Lymphoma in 5 Elderly Patients.

Peripheral T cell lymphoma (PTCL) is a heterogeneous group of aggressive lymphomas with poor prognosis. Elderly (age ≥ 65years) patients generally have impaired bone marrow function, altered drug metabolism, comorbidities, and poor functional status. Thus, treatment of elderly patients with relapsed or refractory PTCL remains a challenge for clinicians. A recent study disclosed that pralatrexate has a synergistic effect in combination with bortezomib. Weekly pralatrexate and bortezomib were administered intravenously for 3 weeks in a 4-week cycle. Of 5 patients, one achieved complete response after 4 cycles which has lasted 12 months until now. Another patient attained partial response after 2 cycles. Only 1 patient experienced grade 3 thrombocytopenia and neutropenia. Two patients suffered from grade 3 mucositis. Combination therapy with pralatrexate and bortezomib may be used as a salvage therapy for relapsed or refractory PTCL in the elderly with a favorable safety profile.

Improved PCR assay for the species-specific identification and quantitation of Legionella pneumophila in water.

Legionellosis outbreak is a major global health care problem. However, current Legionella risk assessments may be compromised by uncertainties in Legionella detection methods, infectious dose, and strain infectivity. These limitations may place public health at significant risk, leading to significant monetary losses in health care. However, there are still unmet needs for its rapid identification and monitoring of legionellae in water systems. Therefore, in the present study, a primer set was designed based on a LysR-type transcriptional regulator (LTTR) family protein gene of Legionella pneumophila subsp. pneumophila str. Philadelphia 1 because it was found that this gene is structurally diverse among species through BLAST searches. The specificity of the primer set was evaluated using genomic DNA from 6 strains of L. pneumophila, 5 type strains of other related Legionella species, and other 29 reference pathogenic bacteria. The primer set used in the PCR assay amplified a 264-bp product for only targeted six strains of L. pneumophila. The assay was also able to detect at least 1.39 × 10(3) copies/µl of cloned amplified target DNA using purified DNA or 7.4 × 10(0) colony-forming unit per reaction when using calibrated cell suspension. In addition, the sensitivity and specificity of this assay were confirmed by successful detection of Legionella pneumophila in environmental water samples.

Improved PCR assay for the specific detection and quantitation of Escherichia coli serotype O157 in water.

Escherichia coli serotype O157 is still a major global healthcare problem. However, only limited information is now available on the molecular and serological detection of pathogenic bacteria. Therefore, the development of appropriate strategies for their rapid identification and monitoring is still needed. In general, the sequence analysis based on stx, slt, eae, hlyA, rfb, and fliCh7 genes is widely employed for the identification of E. coli serotype O157; but there have been critical defects in the diagnosis and identification of E. coli serotype O157, in that they are also present in other E. coli serogroups. In this study, NCBI-BLAST searches using the nucleotide sequences of the putative regulatory protein gene from E. coli O157:H7 str. Sakai found sequence difference at the serotype level. The specific primers from the putative regulatory protein gene were designed and investigated for their sensitivity and specificity for detecting the pathogen in environment water samples. The specificity of the primer set was evaluated using genomic DNA from 8 isolates of E. coli serotype O157 and 32 other reference strains. In addition, the sensitivity and specificity of this assay were confirmed by successful identification of E. coli serotype O157 in environmental water samples. In conclusion, this study showed that the newly developed quantitative serotype-specific PCR method is a highly specific and efficient tool for the surveillance and rapid detection of high-risk E. coli serotype O157.

Personalized Deep Learning Model for Clinical Target Volume on Daily Cone Beam Computed Tomography in Breast Cancer Patients.

Purpose: Herein, we developed a deep learning algorithm to improve the segmentation of the clinical target volume (CTV) on daily cone beam computed tomography (CBCT) scans in breast cancer radiation therapy. By leveraging the Intentional Deep Overfit Learning (IDOL) framework, we aimed to enhance personalized image-guided radiation therapy based on patient-specific learning. Methods and Materials: We used 240 CBCT scans from 100 breast cancer patients and employed a 2-stage training approach. The first stage involved training a novel general deep learning model (Swin UNETR, UNET, and SegResNET) on 90 patients. The second stage used intentional overfitting on the remaining 10 patients for patient-specific CBCT outputs. Quantitative evaluation was conducted using the Dice Similarity Coefficient (DSC), Hausdorff Distance (HD), mean surface distance (MSD), and independent samples t test with expert contours on CBCT scans from the first to 15th fractions. Results: IDOL integration significantly improved CTV segmentation, particularly with the Swin UNETR model (P values < .05). Using patient-specific data, IDOL enhanced the DSC, HD, and MSD metrics. The average DSC for the 15th fraction improved from 0.9611 to 0.9819, the average HD decreased from 4.0118 mm to 1.3935 mm, and the average MSD decreased from 0.8723 to 0.4603. Incorporating CBCT scans from the initial treatments and first to third fractions further improved results, with an average DSC of 0.9850, an average HD of 1.2707 mm, and an average MSD of 0.4076 for the 15th fraction, closely aligning with physician-drawn contours. Conclusion: Compared with a general model, our patient-specific deep learning-based training algorithm significantly improved CTV segmentation accuracy of CBCT scans in patients with breast cancer. This approach, coupled with continuous deep learning training using daily CBCT scans, demonstrated enhanced CTV delineation accuracy and efficiency. Future studies should explore the adaptability of the IDOL framework to diverse deep learning models, data sets, and cancer sites.

Normal tissue complication probability models of hypothyroidism after radiotherapy for breast cancer.

Purpose: We aimed to develop Lyman-Kutcher-Burman (LKB) and multivariable normal tissue complication probability (NTCP) models to predict the risk of radiation-induced hypothyroidism (RIHT) in breast cancer patients. Materials and methods: A total of 1,063 breast cancer patients who underwent whole breast irradiation between 2009 and 2016 were analyzed. Individual dose-volume histograms were used to generate LKB and multivariable logistic regression models. LKB model was fit using the thyroid radiation dose-volume parameters. A multivariable model was constructed to identify potential dosimetric and clinical parameters associated with RIHT. Internal validation was conducted using bootstrapping techniques, and model performance was evaluated using the area under the curve (AUC) and Hosmer-Lemeshow (HL) goodness-of-fit test. Results: RIHT developed in 4 % of patients with a median follow-up of 77.7 months. LKB and multivariable NTCP models exhibited significant agreement between the predicted and observed results (HL P values > 0.05). The multivariable NTCP model outperformed the LKB model in predicting RIHT (AUC 0.62 vs. 0.54). In the multivariable model, systemic therapy, age, and percentage of thyroid volume receiving ≥ 10 Gy (V10) were significant prognostic factors for RIHT. The cumulative incidence of RIHT was significantly higher in patients who exceeded the cut-off values for all three risk predictors (systemic therapy, age ≥ 40 years, and thyroid V10 ≥ 26 %, P < 0.005). Conclusions: Systemic therapy, age, and V10 of the thyroid were identified as strong risk factors for the development of RIHT. Our NTCP models provide valuable insights to clinicians for predicting and preventing hypothyroidism by identifying high-risk patients.

Photosynthetic responses of Larix kaempferi and Pinus densiflora seedlings are affected by summer extreme heat rather than by extreme precipitation.

The frequency and intensity of summer extreme climate events are increasing over time, and have a substantial negative effect on plants, which may be evident in their impact on photosynthesis. Here, we examined the photosynthetic responses of Larix kaempferi and Pinus densiflora seedlings to extreme heat (+ 3 °C and + 6 °C), drought, and heavy rainfall by conducting an open-field multifactor experiment. Leaf gas exchange in L. kaempferi showed a decreasing trend under increasing temperature, showing a reduction in the stomatal conductance, transpiration rate, and net photosynthetic rate by 135.2%, 102.3%, and 24.8%, respectively, in the + 6 °C treatment compared to those in the control. In contrast, P. densiflora exhibited a peak function in the stomatal conductance and transpiration rate under + 3 °C treatment. Furthermore, both species exhibited increased total chlorophyll contents under extreme heat conditions. However, extreme precipitation had no marked effect on photosynthetic activities, given the overall favorable water availability for plants. These results indicate that while extreme heat generally reduces photosynthesis by triggering stomatal closure under high vapor pressure deficit, plants employ diverse stomatal strategies in response to increasing temperature, which vary among species. Our findings contribute to the understanding of mechanisms underlying the photosynthetic responses of conifer seedlings to summer extreme climate events.

Dose-toxicity surface histogram-based prediction of radiation dermatitis severity and shape.

Objective.This study aimed to develop a new approach to predict radiation dermatitis (RD) by using the skin dose distribution in the actual area of RD occurrence to determine the predictive dose by grade.Approach.Twenty-three patients with head and neck cancer treated with volumetric modulated arc therapy were prospectively and retrospectively enrolled. A framework was developed to segment the RD occurrence area in skin photography by matching the skin surface image obtained using a 3D camera with the skin dose distribution. RD predictive doses were generated using the dose-toxicity surface histogram (DTH) calculated from the skin dose distribution within the segmented RD regions classified by severity. We then evaluated whether the developed DTH-based framework could visually predict RD grades and their occurrence areas and shapes according to severity.Main results.The developed framework successfully generated the DTH for three different RD severities: faint erythema (grade 1), dry desquamation (grade 2), and moist desquamation (grade 3); 48 DTHs were obtained from 23 patients: 23, 22, and 3 DTHs for grades 1, 2, and 3, respectively. The RD predictive doses determined using DTHs were 28.9 Gy, 38.1 Gy, and 54.3 Gy for grades 1, 2, and 3, respectively. The estimated RD occurrence area visualized by the DTH-based RD predictive dose showed acceptable agreement for all grades compared with the actual RD region in the patient. The predicted RD grade was accurate, except in two patients.Significance. The developed DTH-based framework can classify and determine RD predictive doses according to severity and visually predict the occurrence area and shape of different RD severities. The proposed approach can be used to predict the severity and shape of potential RD in patients and thus aid physicians in decision making.

Improved PCR for identification of Pseudomonas aeruginosa.

The aim of the present study was to develop a noble and specific marker for a quantitative polymerase chain reaction (PCR) assay for the species-specific detection of Pseudomonas aeruginosa based on the O-antigen acetylase gene. It is an important challenge to characterize populations of the bacterium P. aeruginosa, an opportunist by virtue of its physiological and genetic adaptability. However, molecular and serological methods currently available for sensitive and specific detection of P. aeruginosa are by no means satisfactory because there have been critical defects in the diagnosis and identification of P. aeruginosa strains in that these assays also detect other Pseudomonas species, or do not obtain amplified products from P. aeruginosa strains. Therefore, a primer set was designed based on the O-antigen acetylase gene of P. aeruginosa PA01 because it has been known that this gene is structurally diverse among species. The specificity of the primer set was evaluated using genomic DNA from six isolates of P. aeruginosa, 18 different species of Pseudomonas, and 23 other reference pathogenic bacteria. The primer set used in the PCR assay amplified a 232-bp amplicon for only six P. aeruginosa strains. The assay was also able to detect at least 1.41 × 10(3) copies/µl of cloned amplified target DNA using purified DNA, or 2.7 × 10(2) colony-forming unit per reaction when using calibrated cell suspension. In conclusion, this assay can be applied as a practical diagnostic method for epidemiological research and the sanitary management of water with a low level or latent infection of P. aeruginosa.

The influence of herbal medicine on serum motilin and its effect on human and animal model: a systematic review.

Introduction: Motilin (MLN) is a gastrointestinal (GI) hormone produced in the upper small intestine. Its most well understood function is to participate in Phase III of the migrating myoelectric complex component of GI motility. Changes in MLN availability are associated with GI diseases such as gastroesophageal reflux disease and functional dyspepsia. Furthermore, herbal medicines have been used for several years to treat various GI disorders. We systematically reviewed clinical and animal studies on how herbal medicine affects the modulation of MLN and subsequently brings the therapeutic effects mainly focused on GI function. Methods: We searched the PubMed, Embase, Cochrane, and Web of Science databases to collect all articles published until 30 July 2023, that reported the measurement of plasma MLN levels in human randomized controlled trials and in vivo herbal medicine studies. The collected characteristics of the articles included the name and ingredients of the herbal medicine, physiological and symptomatic changes after administering the herbal medicine, changes in plasma MLN levels, key findings, and mechanisms of action. The frequency patterns (FPs) of botanical drug use and their correlations were investigated using an FP growth algorithm. Results: Nine clinical studies with 1,308 participants and 20 animal studies were included in the final analyses. Herbal medicines in clinical studies have shown therapeutic effects in association with increased levels of MLN, including GI motility regulation and symptom improvement. Herbal medicines have also shown anti-stress, anti-tumor, and anti-inflammatory effects in vivo. Various biochemical markers may correlate with MLN levels. Markers may have a positive correlation with plasma MLN levels included ghrelin, acetylcholine, and secretin, whereas a negative correlation included triglycerides and prostaglandin E2. Markers, such as gastrin and somatostatin, did not show any correlation with plasma MLN levels. Based on the FP growth algorithm, Glycyrrhiza uralensis and Paeonia japonica were the most frequently used species. Conclusion: Herbal medicine may have therapeutic effects mainly on GI symptoms with involvement of MLN regulation and may be considered as an alternative option for the treatment of GI diseases. Further studies with more solid evidence are needed to confirm the efficacy and mechanisms of action of herbal medicines. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=443244, identifier CRD42023443244.

Novel framework for determining TPS-calculated doses corresponding to detector locations using 3D camera inin vivosurface dosimetry.

Purpose. To address the shortcomings of current procedures for evaluating the measured-to-planned dose agreement inin vivodosimetry (IVD), this study aimed to develop an accurate and efficient novel framework to identify the detector location placed on a patient's skin surface using a 3D camera and determine the planned dose at the same anatomical position corresponding to the detector location.Methods. Breast cancer treatment was simulated using an anthropomorphic adult female phantom (ATOM 702D; CIRS, Norfolk, VA, USA). An optically stimulated luminescent dosimeter was used for surface dose measurements (MyOSLchip, RadPro International GmbH, Germany) at six IVD points. Three-dimensional surface imaging (3DSI) of the phantom with the detector was performed in the treatment position using a 3D camera. The developed framework, iSMART, was designed to import 3DSI and treatment planning data for determining the position of the IVD detectors in the 3D treatment planning DICOM image. The clinical usefulness of iSMART was evaluated in terms of accuracy and efficiency, for comparison with the results obtained using cone-beam computed tomography (CBCT) image guidance.Results. The relative dose difference between the planned doses determined using iSMART and CBCT images displayed similar accuracies (within approximately ±2.0%) at all detector locations. The relative dose differences between the planned and measured doses at the six detector locations ranged from -4.8% to 3.1% for the CBCT images and -3.5% to 2.1% for iSMART. The total time required to read the planned doses at six detector locations averaged at 8.1 and 0.8 min for the CBCT images and iSMART, respectively.Conclusions. The proposed framework can improve the robustness of IVD analyses and aid in accurate and efficient evaluations of the measured-to-planned dose agreement.

Rapid and Specific Detection of Burkholderia glumae in Rice Seed by Real-Time Bio-PCR Using Species-Specific Primers Based on an rhs Family Gene.

In this study, we developed a reliable, quick, and accurate quantitative polymerase chain reaction (qPCR) assay to detect grain rot caused by Burkholderia glumae in rice seed. The control of bacterial grain rot is difficult, and the only practical methods for disease management rely on the use of pathogen-free seed, appropriate culture practices, and resistant cultivars. Therefore, the specific detection of this pathogen in seed is essential for effective control of the disease. However, other Burkholderia spp. are also detected by currently available molecular and serological methods. In this study, we exploited the available genome sequence information in public databases to develop specific PCR primers for accurate diagnosis of B. glumae. An SYBR Green real-time PCR primer set was designed based on the rhs family gene (YD repeat protein) of B. glumae BGR1 because these genes are structurally diverse. The specificity of the primers was evaluated using purified DNA from 5 isolates of B. glumae, 6 different species of Burkholderia, and 18 other reference pathogenic bacteria. The assay was able to detect at least one genome equivalent of cloned amplified target DNA using purified DNA or 1 CFU per reaction when using calibrated cell suspension. This method is rapid and reliable and has great potential for analyzing large numbers of samples.

Quantitative Real-Time Polymerase Chain Reaction Assay for Detection of Pectobacterium wasabiae Using YD Repeat Protein Gene-Based Primers.

The aim of this study was to develop a quantitative polymerase chain reaction (qPCR) assay for specific detection of Pectobacterium wasabiae using a primer pair based on the YD repeat protein gene for amplification of a 140-bp DNA fragment from infected wasabi (Wasabia japonica), a member of the crucifer family. The soft rot caused by P. wasabiae is an emerging disease that is present in many wasabi-producing areas. However, specific and reliable methods for identifying the pathogen are not available. Therefore, a qPCR primer set for accurate diagnosis of P. wasabiae was developed from publically available genome sequences. A SYBR Green qPCR primer set was designed based on a YD repeat protein gene of P. wasabiae WPP163 because it is known that this gene is structurally diverse among species, pathovars, or subspecies. The specificity of the primer set was evaluated using genomic DNA from 5 isolates of P. wasabiae, 5 different species of Pectobacterium, and 16 other pathogenic reference bacteria. The primer set used in the PCR assay successfully amplified a 140-bp amplicon for all five P. wasabiae strains. No amplification was obtained from 29 other pathogenic bacteria. The assay was also able to detect at least two genomic DNA, or 3 CFU per reaction, when using calibrated cell suspension.

Development of a Real-Time Thermoplastic Mask Compression Force Monitoring System Using Capacitive Force Sensor.

Purpose: Thermoplastic masks keep patients in an appropriate position to ensure accurate radiation delivery. For a thermoplastic mask to maintain clinical efficacy, the mask should wrap the patient's surface properly and provide uniform pressure to all areas. However, to our best knowledge, no explicit method for achieving such a goal currently exists. Therefore, in this study, we intended to develop a real-time thermoplastic mask compression force (TMCF) monitoring system to measure compression force quantitatively. A prototype system was fabricated, and the feasibility of the proposed method was evaluated. Methods: The real-time TMCF monitoring system basically consists of four force sensor units, a microcontroller board (Arduino Bluno Mega 2560), a control PC, and an in-house software program. To evaluate the reproducibility of the TMCF monitoring system, both a reproducibility test using a micrometer and a setup reproducibility test using a head phantom were performed. Additionally, the reproducibility tests of mask setup and motion detection tests were carried out with a cohort of six volunteers. Results: The system provided stable pressure readings in all 10 trials during the sensor unit reproducibility test. The largest standard deviation (SD) among trials was about 36 gf/cm2 (∼2.4% of the full-scale range). For five repeated mask setups on the phantom, the compression force variation of the mask was less than 39 gf/cm2 (2.6% of the full-scale range). We were successful in making masks together with the monitoring system connected and demonstrated feasible utilization of the system. Compression force variations were observed among the volunteers and according to the location of the sensor (among forehead, both cheekbones, and chin). The TMCF monitoring system provided the information in real time on whether the mask was properly pressing the human subject as an immobilization tool. Conclusion: With the developed system, it is possible to monitor the effectiveness of the mask in real time by continuously measuring the compression force between the mask and patient during the treatment. The graphical user interface (GUI) of the monitoring system developed provides a warning signal when the compression force of the mask is insufficient. Although the number of volunteers participated in the study was small, the obtained preliminary results suggest that the system could ostensibly improve the setup accuracy of a thermoplastic mask.

A pilot study of a novel method to visualize three-dimensional dose distribution on skin surface images to evaluate radiation dermatitis.

Predicting the radiation dose‒toxicity relationship is important for local tumor control and patients' quality of life. We developed a first intuitive evaluation system that directly matches the three-dimensional (3D) dose distribution with the skin surface image of patients with radiation dermatitis (RD) to predict RD in patients undergoing radiotherapy. Using an RGB-D camera, 82 3D skin surface images (3DSSIs) were acquired from 19 patients who underwent radiotherapy. 3DSSI data acquired included 3D skin surface shape and optical imaging of the area where RD occurs. Surface registration between 3D skin dose (3DSD) and 3DSSI is performed using the iterative closest point algorithm, then reconstructed as a two-dimensional color image. The developed system successfully matched 3DSSI and 3DSD, and visualized the planned dose distribution onto the patient's RD image. The dose distribution pattern was consistent with the occurrence pattern of RD. This new approach facilitated the evaluation of the direct correlation between skin-dose distribution and RD and, therefore, provides a potential to predict the probability of RD and thereby decrease RD severity by enabling informed treatment decision making by physicians. However, the results need to be interpreted with caution due to the small sample size.

Sensitive and Specific Detection of Xanthomonas oryzae pv. oryzae by Real-Time Bio-PCR Using Pathovar-Specific Primers Based on an rhs Family Gene.

The present study describes bio-polymerase chain reaction (PCR) assays to detect bacterial leaf blight caused by Xanthomonas oryzae pv. oryzae in rice. Successful control of X. oryzae. pv. oryzae requires a specific and reliable diagnostic tool. However, other X. oryzae pathovars are detected by currently available molecular and serological methods. In this study, SYBR Green real-time and conventional PCR primer sets were designed based on an rhs family gene of X. oryzae pv. oryzae KACC10331 because these genes are structurally diverse. The specificity of the primers was evaluated using purified DNA from 11 isolates of two X. oryzae pathovars, 21 other Xanthomonas species, and 4 other reference phytopathogenic bacteria and fungi. The assay was also able to detect at least two genome equivalents of cloned amplified target DNA using purified DNA. Thus, the SYBR Green real-time PCR-based method can be used for the rapid and specific detection of X. oryzae pv. oryzae and will potentially simplify and facilitate diagnosis and monitoring of this pathogen and guide plant disease management.

Characterization of Gut Microbiome in Korean Patients with Metabolic Associated Fatty Liver Disease.

Metabolic associated fatty liver disease (MAFLD) is a new concept where the presence of both fatty liver and metabolic abnormality are necessary for diagnosis. Several studies have reported that altered gut microbiome is closely associated with metabolic diseases and non-alcoholic fatty liver disease. However, the studies on MAFLD population are scarce. This prospective study aimed to identify differences in gut microbiome between patients with MAFLD and healthy controls in Korean population. In this study, patients with MAFLD and age, sex-matched healthy controls were included, and their stool samples were collected. Taxonomic composition of gut microbiota was analyzed using 16S ribosomal ribonucleic acid pyrosequencing. Twenty-two MAFLD patients and 44 healthy controls were included. Taxonomic diversity was lower in patients with MAFLD in the aspect of alpha and beta diversity. The differences were also found at phylum, class, family, and genus levels between the two groups. Phylum Proteobacteria, family Enterobactereriaceae, genus Citrobacter abundance was significantly increased and genus Faecalibacterium was significantly decreased in patients with MAFLD. In addition, butyrate-producing bacteria were decreased and ethanol-producing bacteria were increased in patients with MAFLD. The composition of gut microbiome was different between MAFLD and healthy controls in Korean population. This could offer potential targets for therapeutic intervention in MAFLD.