Evaluation of children's antibiotics use for outpatient pneumonia treatment in Vietnam.

OBJECTIVE: Antibiotic resistance is increasing globally, associated with many failures in pneumonia treatment. This study aimed to evaluate antibiotic use in children treated for outpatient CAP (Community-Acquired Pneumonia). METHODS: A cross-sectional descriptive retrospective study was conducted, focusing on data from outpatient prescriptions for pneumonia in patients aged 2‒192 months in 2019‒2021. RESULTS: All antibiotic prescriptions are considered empiric as no documented bacterial and viral tests exist for children with non-severe CAP. Single antibiotic therapy (66%) had a 2-fold higher rate than combination therapy (34%). Amoxicillin/clavulanic acid (50.77%) and azithromycin (30.74%) were the most commonly prescribed in both single and combination therapies, thus determining antibiotic cost (80.15%). Besides, azithromycin (97.92%), cefuroxime (86.26%), and cefpodoxime (60.48%) were prescribed with high adherence to dose guidelines, except for amoxicillin (34.57%). These medicines are prescribed highly compliant (>83%) with dosing interval guidelines. Furthermore, significantly more brand-name antibiotics (56.5%) are prescribed than generic antibiotics (43.5%). In particular, antibiotic class, antibiotic origin, and antibiotic therapies showed significant association with rational antibiotic prescriptions for dose and dose interval (p < 0.05). CONCLUSIONS: Amoxicillin/clavulanic acid is the most frequently prescribed medicine and the most inappropriate due to non-compliance with dose guidelines for CAP treatment. Generic antibiotic use for single therapy should be encouraged based on rapid and accurate diagnostic testing for viruses and bacteria to reduce antibiotic resistance in developing countries. Moreover, the study result has also shown that therapies and antibiotics (class and origin) exhibited significant association with rational prescriptions for CAP treatment for pediatrics.

Identification of film-based formulations that move mRNA lipid nanoparticles out of the freezer.

COVID-19 vaccines consisting of mRNA lipid nanoparticles (LNPs) encoding the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein antigen protected millions of people from severe disease; however, they must be stored frozen prior to use. The objective of this study was to evaluate the compatibility and stability of mRNA LNPs within a polymer-based film matrix. An optimized formulation of polymer base, glycerol, surfactants, and PEGylated lipid that prevents damage to the LNP due to physical changes during the film-forming process (osmotic stress, surface tension, spatial stress, and water loss) was identified. Surfactants added to LNP stock prior to mixing with other film components contributed to this effect. Formulations prepared at pH ≥ 8.5 extended transfection efficiency beyond 4 weeks at 4°C when combined with known nucleic acid stabilizers. mRNA LNPs were most stable in films when manufactured in an environment of ∼50% relative humidity. The optimized formulation offers 16-week stability at 4°C.

CBCT-DRRs superior to CT-DRRs for target-tracking applications for pancreatic SBRT.

Objective.In current radiograph-based intra-fraction markerless target-tracking, digitally reconstructed radiographs (DRRs) from planning CTs (CT-DRRs) are often used to train deep learning models that extract information from the intra-fraction radiographs acquired during treatment. Traditional DRR algorithms were designed for patient alignment (i.e.bone matching) and may not replicate the radiographic image quality of intra-fraction radiographs at treatment. Hypothetically, generating DRRs from pre-treatment Cone-Beam CTs (CBCT-DRRs) with DRR algorithms incorporating physical modelling of on-board-imagers (OBIs) could improve the similarity between intra-fraction radiographs and DRRs by eliminating inter-fraction variation and reducing image-quality mismatches between radiographs and DRRs. In this study, we test the two hypotheses that intra-fraction radiographs are more similar to CBCT-DRRs than CT-DRRs, and that intra-fraction radiographs are more similar to DRRs from algorithms incorporating physical models of OBI components than DRRs from algorithms omitting these models.Approach.DRRs were generated from CBCT and CT image sets collected from 20 patients undergoing pancreas stereotactic body radiotherapy. CBCT-DRRs and CT-DRRs were generated replicating the treatment position of patients and the OBI geometry during intra-fraction radiograph acquisition. To investigate whether the modelling of physical OBI components influenced radiograph-DRR similarity, four DRR algorithms were applied for the generation of CBCT-DRRs and CT-DRRs, incorporating and omitting different combinations of OBI component models. The four DRR algorithms were: a traditional DRR algorithm, a DRR algorithm with source-spectrum modelling, a DRR algorithm with source-spectrum and detector modelling, and a DRR algorithm with source-spectrum, detector and patient material modelling. Similarity between radiographs and matched DRRs was quantified using Pearson's correlation and Czekanowski's index, calculated on a per-image basis. Distributions of correlations and indexes were compared to test each of the hypotheses. Distribution differences were determined to be statistically significant when Wilcoxon's signed rank test and the Kolmogorov-Smirnov two sample test returnedp≤ 0.05 for both tests.Main results.Intra-fraction radiographs were more similar to CBCT-DRRs than CT-DRRs for both metrics across all algorithms, with allp≤ 0.007. Source-spectrum modelling improved radiograph-DRR similarity for both metrics, with allp< 10-6. OBI detector modelling and patient material modelling did not influence radiograph-DRR similarity for either metric.Significance.Generating DRRs from pre-treatment CBCT-DRRs is feasible, and incorporating CBCT-DRRs into markerless target-tracking methods may promote improved target-tracking accuracies. Incorporating source-spectrum modelling into a treatment planning system's DRR algorithms may reinforce the safe treatment of cancer patients by aiding in patient alignment.

Pediatric Profound Dengue Shock Syndrome and Use of Point-of-Care Ultrasound During Mechanical Ventilation to Guide Treatment: Single-Center Retrospective Study, 2013-2021.

OBJECTIVES: Profound dengue shock syndrome (DSS) complicated by severe respiratory failure necessitating mechanical ventilation (MV) accounts for high case fatality rates among PICU-admitted patients. A major challenge to management is the assessment of intravascular volume, which can be hampered by severe plasma leakage and the use of MV. DESIGN: Retrospective cohort, from 2013 to 2021. PATIENTS: Sixty-seven children with profound DSS supported by MV, some of whom underwent bedside point-of-care ultrasound (POCUS) for assessment and monitoring of hemodynamics and fluid administration. SETTING: PICU of the tertiary Children's Hospital No. 2 in Vietnam. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed data clinical and laboratory data during PICU stay. In particular, during use of MV (i.e., at times 0-, 6-, and 24-hr after commencement) and fluid resuscitation. The primary study outcome was 28-day in-hospital mortality, and the secondary outcomes were associations with changes in hemodynamics, blood lactate, and vasoactive-inotrope score (VIS). Patients had a median age of 7 years (interquartile range, 4-9). Use of POCUS during fluid management (39/67), as opposed to not using (28/67), was associated with lower mortality (6/39 [15%] vs. 18/28 [64%]; difference 49 % [95% CI, 28-70%], p < 0.001). Use of POCUS was associated with lower odds of death (adjusted odds ratio 0.17 [95% CI, 0.04-0.76], p = 0.02). The utilization of POCUS, versus not, was associated with greater use of resuscitation fluid, and reductions in VIS and pediatric logistic organ dysfunction (PELOD-2) score at 24 hours after MV and PICU discharge. CONCLUSIONS: In our experience of pediatric patients with profound DSS and undergoing MV (2013-2021), POCUS use was associated with lower odds of death, a higher volume of resuscitation fluid, and improvements in the blood lactate levels, VIS, and PELOD-2 score.

The first clinical implementation of real-time 6 degree-of-freedom image-guided radiotherapy for liver SABR patients.

PURPOSE: Multiple survey results have identified a demand for improved motion management for liver cancer IGRT. Until now, real-time IGRT for liver has been the domain of dedicated and expensive cancer radiotherapy systems. The purpose of this study was to clinically implement and characterise the performance of a novel real-time 6 degree-of-freedom (DoF) IGRT system, Kilovoltage Intrafraction Monitoring (KIM) for liver SABR patients. METHODS/MATERIALS: The KIM technology segmented gold fiducial markers in intra-fraction x-ray images as a surrogate for the liver tumour and converted the 2D segmented marker positions into a real-time 6DoF tumour position. Fifteen liver SABR patients were recruited and treated with KIM combined with external surrogate guidance at three radiotherapy centres in the TROG 17.03 LARK multi-institutional prospective clinical trial. Patients were either treated in breath-hold or in free breathing using the gating method. The KIM localisation accuracy and dosimetric accuracy achieved with KIM + external surrogate were measured and the results were compared to those with the estimated external surrogate alone. RESULTS: The KIM localisation accuracy was 0.2±0.9 mm (left-right), 0.3±0.6 mm (superior-inferior) and 1.2±0.8 mm (anterior-posterior) for translations and -0.1◦±0.8◦ (left-right), 0.6◦±1.2◦ (superior-inferior) and 0.1◦±0.9◦ (anterior-posterior) for rotations. The cumulative dose to the GTV with KIM + external surrogate was always within 5% of the plan. In 2 out of 15 patients, >5% dose error would have occurred to the GTV and an organ-at-risk with external surrogate alone. CONCLUSIONS: This work demonstrates that real-time 6DoF IGRT for liver can be implemented on standard radiotherapy systems to improve treatment accuracy and safety. The observations made during the treatments highlight the potential false assurance of using traditional external surrogates to assess tumour motion in patients and the need for ongoing improvement of IGRT technologies.

Physical characteristics and stability profile of recombinant plasmid DNA within a film matrix.

Plasmids are essential source material for production of biological drugs, vaccines and vectors for gene therapy. They are commonly formulated as frozen solutions. Considering the cost associated with maintenance of cold chain conditions during storage and transport, there is a significant need for alternative methods for stabilization of plasmids at ambient temperature. The objective of these studies was to identify a film-based formulation that preserved transfection efficiency of plasmids at 25 °C. A model plasmid, pAAVlacZ, was used for these studies. Transfection efficiency and agarose gel electrophoresis were utilized to assess bioactivity and changes in physical conformation of plasmid during storage. An amino acid, capable of sustaining a positive charge while supporting an alkaline environment within the film matrix, preserved transfection efficiency for 9 months at 25 °C. Addition of sugar and a plasticizer to the formulation preserved the plasmid in an amorphous state and improved handling properties of the film. The manner in which excipients were incorporated into bulk formulations and environmental humidity in which films were stored significantly impacted transfection efficiency of plasmid in the rehydrated solution. Taken together, these results suggest that plasmids can be stored for extended periods of time without refrigeration within a film matrix.

Hollow-Structured N-doped carbon-embedded CoFe NanoAlloy for boosting activation of Monopersulfate: Engineered interface and heteroatom Doping-Induced enhancements.

While transition metals are useful for activating monopersulfate (MPS) to degrade contaminants, bimetallic alloys exhibit stronger catalytic activities owing to several favorable effects. Therefore, even though Co is an efficient metal for MPS activation, CoFe alloys are even more promising heterogeneous catalysts for MPS activation. Immobilization/embedment of CoFe alloy nanoparticles (NPs) onto hetero-atom-doped carbon matrices appears as a practical strategy for evenly dispersing CoFe NPs and enhancing catalytic activities via interfacial synergies between CoFe and carbon. Herein, N-doped carbon-embedded CoFe alloy (NCCF) is fabricated here to exhibit a unique hollow-engineered nanostructure and the composition of CoFe alloy by using Co-ZIF as a precursor after the facile etching and Fe doping. The Fe dopant embeds CoFe alloy NPs into the hollow-structured N-doped carbon substrate, enabling NCCF to possess the higher mesoscale porosity, active N species as well as more superior electrochemical properties than its analogue without Fe dopants, carbon matrix-supported cobalt (NCCo). Thus, NCCF exhibits a considerably larger activity than NCCo and the benchmark catalyst, Co3O4 NP, for MPS activation to degrade an environmental hormone, dihydroxydiphenyl ketone (DHPK). Besides, NCCF + MPS shows an even lower activation energy for DHPK degradation than literatures, and retains its high efficiency for eliminating DHPK in different water media. DHPK degradation pathway and ecotoxicity assessment are unraveled based on the insights from the computational chemistry, demonstrating that DHPK degradation by NCCF + MPS did not result in the formation of toxic and highly toxic by-products. These features make NCCF a promising heterogeneous catalyst for MPS activation to degrade DHPK.

Realistic CT data augmentation for accurate deep-learning based segmentation of head and neck tumors in kV images acquired during radiation therapy.

BACKGROUND: Using radiation therapy (RT) to treat head and neck (H&N) cancers requires precise targeting of the tumor to avoid damaging the surrounding healthy organs. Immobilisation masks and planning target volume margins are used to attempt to mitigate patient motion during treatment, however patient motion can still occur. Patient motion during RT can lead to decreased treatment effectiveness and a higher chance of treatment related side effects. Tracking tumor motion would enable motion compensation during RT, leading to more accurate dose delivery. PURPOSE: The purpose of this paper is to develop a method to detect and segment the tumor in kV images acquired during RT. Unlike previous tumor segmentation methods for kV images, in this paper, a process for generating realistic and synthetic CT deformations was developed to augment the training data and make the segmentation method robust to patient motion. Detecting the tumor in 2D kV images is a necessary step toward 3D tracking of the tumor position during treatment. METHOD: In this paper, a conditional generative adversarial network (cGAN) is presented that can detect and segment the gross tumor volume (GTV) in kV images acquired during H&N RT. Retrospective data from 15 H&N cancer patients obtained from the Cancer Imaging Archive were used to train and test patient-specific cGANs. The training data consisted of digitally reconstructed radiographs (DRRs) generated from each patient's planning CT and contoured GTV. Training data was augmented by using synthetically deformed CTs to generate additional DRRs (in total 39 600 DRRs per patient or 25 200 DRRs for nasopharyngeal patients) containing realistic patient motion. The method for deforming the CTs was a novel deformation method based on simulating head rotation and internal tumor motion. The testing dataset consisted of 1080 DRRs for each patient, obtained by deforming the planning CT and GTV at different magnitudes to the training data. The accuracy of the generated segmentations was evaluated by measuring the segmentation centroid error, Dice similarity coefficient (DSC) and mean surface distance (MSD). This paper evaluated the hypothesis that when patient motion occurs, using a cGAN to segment the GTV would create a more accurate segmentation than no-tracking segmentations from the original contoured GTV, the current standard-of-care. This hypothesis was tested using the 1-tailed Mann-Whitney U-test. RESULTS: The magnitude of our cGAN segmentation centroid error was (mean ± standard deviation) 1.1 ± 0.8 mm and the DSC and MSD values were 0.90 ± 0.03 and 1.6 ± 0.5 mm, respectively. Our cGAN segmentation method reduced the segmentation centroid error (p < 0.001), and MSD (p = 0.031) when compared to the no-tracking segmentation, but did not significantly increase the DSC (p = 0.294). CONCLUSIONS: The accuracy of our cGAN segmentation method demonstrates the feasibility of this method for H&N cancer patients during RT. Accurate tumor segmentation of H&N tumors would allow for intrafraction monitoring methods to compensate for tumor motion during treatment, ensuring more accurate dose delivery and enabling better H&N cancer patient outcomes.

Deep learning enables MV-based real-time image guided radiation therapy for prostate cancer patients.

Objective. Using MV images for real-time image guided radiation therapy (IGRT) is ideal as it does not require additional imaging equipment, adds no additional imaging dose and provides motion data in the treatment beam frame of reference. However, accurate tracking using MV images is challenging due to low contrast and modulated fields. Here, a novel real-time marker tracking system based on a convolutional neural network (CNN) classifier was developed and evaluated on retrospectively acquired patient data for MV-based IGRT for prostate cancer patients.Approach. MV images, acquired from 29 volumetric modulated arc therapy (VMAT) prostate cancer patients treated in a multi-institutional clinical trial, were used to train and evaluate a CNN-based marker tracking system. The CNN was trained using labelled MV images from 9 prostate cancer patients (35 fractions) with implanted markers. CNN performance was evaluated on an independent cohort of unseen MV images from 20 patients (78 fractions), using a Precision-Recall curve (PRC), area under the PRC plot (AUC) and sensitivity and specificity. The accuracy of the tracking system was evaluated on the same unseen dataset and quantified by calculating mean absolute (±1 SD) and [1st, 99th] percentiles of the geometric tracking error in treatment beam co-ordinates using manual identification as the ground truth.Main results. The CNN had an AUC of 0.99, sensitivity of 98.31% and specificity of 99.87%. The mean absolute geometric tracking error was 0.30 ± 0.27 and 0.35 ± 0.31 mm in the lateral and superior-inferior directions of the MV images, respectively. The [1st, 99th] percentiles of the error were [-1.03, 0.90] and [-1.12, 1.12] mm in the lateral and SI directions, respectively.Significance. The high classification performance on unseen MV images demonstrates the CNN can successfully identify implanted prostate markers. Furthermore, the sub-millimetre accuracy and precision of the marker tracking system demonstrates potential for adaptation to real-time applications.

The dosimetric error due to uncorrected tumor rotation during real-time adaptive prostate stereotactic body radiation therapy.

BACKGROUND: During prostate stereotactic body radiation therapy (SBRT), prostate tumor translational motion may deteriorate the planned dose distribution. Most of the major advances in motion management to date have focused on correcting this one aspect of the tumor motion, translation. However, large prostate rotation up to 30° has been measured. As the technological innovation evolves toward delivering increasingly precise radiotherapy, it is important to quantify the clinical benefit of translational and rotational motion correction over translational motion correction alone. PURPOSE: The purpose of this work was to quantify the dosimetric impact of intrafractional dynamic rotation of the prostate measured with a six degrees-of-freedom tumor motion monitoring technology. METHODS: The delivered dose was reconstructed including (a) translational and rotational motion and (b) only translational motion of the tumor for 32 prostate cancer patients recruited on a 5-fraction prostate SBRT clinical trial. Patients on the trial received 7.25 Gy in a treatment fraction. A 5 mm clinical target volume (CTV) to planning target volume (PTV) margin was applied in all directions except the posterior direction where a 3 mm expansion was used. Prostate intrafractional translational motion was managed using a gating strategy, and any translation above the gating threshold was corrected by applying an equivalent couch shift. The residual translational motion is denoted as T r e s $T_{res}$ . Prostate intrafractional rotational motion R u n c o r r $R_{uncorr}$ was recorded but not corrected. The dose differences from the planned dose due to T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ , ΔD( T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ ) and due to T r e s $T_{res}$ alone, ΔD( T r e s $T_{res}$ ), were then determined for CTV D98, PTV D95, bladder V6Gy, and rectum V6Gy. The residual dose error due to uncorrected rotation, R u n c o r r $R_{uncorr}$ was then quantified: Δ D R e s i d u a l $\Delta D_{Residual}$ = ΔD( T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ ) - ΔD( T res ${T}_{\textit{res}}$ ). RESULTS: Fractional data analysis shows that the dose differences from the plan (both ΔD( T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ ) and ΔD( T r e s $T_{res}$ )) for CTV D98 was less than 5% in all treatment fractions. ΔD( T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ ) was larger than 5% in one fraction for PTV D95, in one fraction for bladder V6Gy, and in five fractions for rectum V6Gy. Uncorrected rotation, R u n c o r r $R_{uncorr}$ induced residual dose error, Δ D R e s i d u a l $\Delta D_{Residual}$ , resulted in less dose to CTV and PTV in 43% and 59% treatment fractions, respectively, and more dose to bladder and rectum in 51% and 53% treatment fractions, respectively. The cumulative dose over five fractions, ∑D( T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ ) and ∑D( T r e s $T_{res}$ ), was always within 5% of the planned dose for all four structures for every patient. CONCLUSIONS: The dosimetric impact of tumor rotation on a large prostate cancer patient cohort was quantified in this study. These results suggest that the standard 3-5 mm CTV-PTV margin was sufficient to account for the intrafraction prostate rotation observed for this cohort of patients, provided an appropriate gating threshold was applied to correct for translational motion. Residual dose errors due to uncorrected prostate rotation were small in magnitude, which may be corrected using different treatment adaptation strategies to further improve the dosimetric accuracy.

Enzymatic Treatment of Spent Green Tea Leaves and Their Use in High-Fibre Cookie Production.

Research background: By-products of food industry have been studied as sources of high fibre and antioxidant ingredients for healthy food products, because of their economic and environmental benefits. However, the soluble dietary fibre content of these materials is usually lower than the recommended value that is claimed to bring positive health effects. Enzymatic treatment could be an efficient method for modifying insoluble and soluble dietary fibre contents of these materials. The purpose of this study is to investigate the effects of enzymatic treatment conditions on soluble, insoluble and total dietary fibre mass fractions in spent green tea leaves, and evaluate the quality of dough and cookies when different mass fractions of untreated and treated leaves were added to the recipe. Experimental approach: The mass fractions of soluble, insoluble and total dietary fibre in spent tea leaf powder was evaluated after the leaves were treated with cellulase amount of 0-25 U/g for 0 to 2 h. Wheat flour was replaced by untreated and treated spent tea leaf powder at 0, 10, 20, 30 and 40% in cookie formulation. Textural properties of dough, proximate composition, physical properties and overall acceptability of cookies were analysed. Results and conclusions: The appropriate conditions for enzymatic treatment were enzyme loading of 20 U/g and biocatalytic time of 1.5 h, under which the mass fraction of soluble dietary fibre in spent tea leaves increased by 144.5% compared to that of the control sample. The addition of spent tea leaves led to the increase in dough hardness. Increase in the spent tea leaf amount also enhanced fibre mass fraction, antioxidant activity and hardness of cookies but reduced their overall acceptability. Moreover, the enzymatic treatment of spent tea leaves improved the soluble to total dietary fibre ratio of the cookies, which influenced their textural properties and health benefits. The cookies with added 20% untreated or treated spent tea leaves were overall accepted by the panel. Novelty and scientific contribution: For the first time, spent tea leaves have been treated with enzymes to improve their soluble to total dietary fibre ratio. The treated spent tea leaves are a new promising high-fibre antioxidant ingredient for cookie preparation.

Thermostability and in vivo performance of AAV9 in a film matrix.

BACKGROUND: Adeno-associated virus (AAV) vectors are stored and shipped frozen which poses logistic and economic barriers for global access to these therapeutics. To address this issue, we developed a method to stabilize AAV serotype 9 (AAV9) in a film matrix that can be stored at ambient temperature and administered by systemic injection. METHODS: AAV9 expressing the luciferase transgene was mixed with formulations, poured into molds and films dried under aseptic conditions. Films were packaged in individual particle-free bags with foil overlays and stored at various temperatures under controlled humidity. Recovery of AAV9 from films was determined by serial dilution of rehydrated film in media and infection of HeLa RC32 cells. Luciferase expression was compared to that of films rehydrated immediately after drying. Biodistribution of vector was determined by in vivo imaging and quantitative real-time PCR. Residual moisture in films was determined by Karl Fischer titration. RESULTS: AAV9 embedded within a film matrix and stored at 4 °C for 5 months retained 100% of initial titer. High and low viscosity formulations maintained 90 and 85% of initial titer after 6 months at 25 °C respectively. AAV was not detected after 4 months in a Standard Control Formulation under the same conditions. Biodistribution and transgene expression of AAV stored in film at 25 or 4 °C were as robust as vector stored at -80 °C in a Standard Control Formulation. CONCLUSIONS: These results suggest that storage of AAV in a film matrix facilitates easy transport of vector to remote sites without compromising in vivo performance.

Adeno-associated viruses (AAVs) are small viruses that are used to deliver medicines and vaccines. Prior to administration, they are stored in freezers set to very low temperatures and must be discarded if they thaw during transportation to clinics. AAV was embedded in a film to protect the virus during transportation and storage. The virus remained stable for 6 months at room temperature and during shipment from Texas to North Carolina. The ability to store and transport AAV without the need for complex packaging and temperature control will increase global access to vaccines and other medicines that use AAVs for delivery.

Optimising multi-target multileaf collimator tracking using real-time dose for locally advanced prostate cancer patients.

Objective. The accuracy of radiotherapy for patients with locally advanced cancer is compromised by independent motion of multiple targets. To date, MLC tracking approaches have used 2D geometric optimisation where the MLC aperture shape is simply translated to correspond to the target's motion, which results in sub-optimal delivered dose. To address this limitation, a dose-optimised multi-target MLC tracking method was developed and evaluated through simulated locally advanced prostate cancer treatments.Approach. A dose-optimised multi-target tracking algorithm that adapts the MLC aperture to minimise 3D dosimetric error was developed for moving prostate and static lymph node targets. A fast dose calculation algorithm accumulated the planned dose to the prostate and lymph node volumes during treatment in real time, and the MLC apertures were recalculated to minimise the difference between the delivered and planned dose with the included motion. Dose-optimised tracking was evaluated by simulating five locally advanced prostate plans and three prostate motion traces with a relative interfraction displacement. The same simulations were performed using geometric-optimised tracking and no tracking. The dose-optimised, geometric-optimised, and no tracking results were compared with the planned doses using a 2%/2 mmγcriterion.Main results. The mean dosimetric error was lowest for dose-optimised MLC tracking, withγ-failure rates of 12% ± 8.5% for the prostate and 2.2% ± 3.2% for the nodes. Theγ-failure rates for geometric-optimised MLC tracking were 23% ± 12% for the prostate and 3.6% ± 2.5% for the nodes. When no tracking was used, theγ-failure rates were 37% ± 28% for the prostate and 24% ± 3.2% for the nodes.Significance. This study developed a dose-optimised multi-target MLC tracking method that minimises the difference between the planned and delivered doses in the presence of intrafraction motion. When applied to locally advanced prostate cancer, dose-optimised tracking showed smaller errors than geometric-optimised tracking and no tracking for both the prostate and nodes.

mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis.

We introduce mirTarRnaSeq, an R/Bioconductor package for quantitative assessment of miRNA-mRNA relationships within sample cohorts. mirTarRnaSeq is a statistical package to explore predicted or pre-hypothesized miRNA-mRNA relationships following target prediction.We present two use cases applying mirTarRnaSeq. First, to identify miRNA targets, we examined EBV miRNAs for interaction with human and virus transcriptomes of stomach adenocarcinoma. This revealed enrichment of mRNA targets highly expressed in CD105+ endothelial cells, monocytes, CD4+ T cells, NK cells, CD19+ B cells, and CD34 cells. Next, to investigate miRNA-mRNA relationships in SARS-CoV-2 (COVID-19) infection across time, we used paired miRNA and RNA sequenced datasets of SARS-CoV-2 infected lung epithelial cells across three time points (4, 12, and 24 hours post-infection). mirTarRnaSeq identified evidence for human miRNAs targeting cytokine signaling and neutrophil regulation immune pathways from 4 to 24 hours after SARS-CoV-2 infection. Confirming the clinical relevance of these predictions, three of the immune specific mRNA-miRNA relationships identified in human lung epithelial cells after SARS-CoV-2 infection were also observed to be differentially expressed in blood from patients with COVID-19. Overall, mirTarRnaSeq is a robust tool that can address a wide-range of biological questions providing improved prediction of miRNA-mRNA interactions.

Human Services During the COVID Pandemic: Using Behavioral Safety Programs to Protect Human Services Workers and Students.

Objectives: Behavioral safety programs have been effective in decreasing injuries across a number of industries. The COVID-19 pandemic is placing stress on the human services field-an industry already noted for its high injury rate. As most organizations resume full operation in the midst of the pandemic, procedures to mitigate the risk of virus transmission are vital. The current manuscript describes the use of a behavioral safety program and its effects on COVID-19 transmission in a school serving setting. Methods: This case study consisted of implementing an organization-wide behavioral safety program in a private school that served students diagnosed with autism spectrum disorder. During the course of the study, 124 to 128 direct care staff were employed by the school and served 168 students during the COVID-19 pandemic. Results: During the behavioral safety program, there were a variable but continuous number of safety observations. The percent of safe behavior in the classrooms began near 90% and approached 100% at the conclusion of data collection. During the study there were no documented COVID-19 infections traced to the school. Conclusions: Behavioral safety programs could be effective in promoting behavior associated with minimizing virus transmission; therefore, these programs may also have utility in preventing communicable diseases in human service settings.

Accumulated and distributed response-reinforcer arrangements during the treatment of escape-maintained problem behavior.

Contingent positive reinforcement has proven more effective in treating escape-maintained problem behavior than contingent negative reinforcement, particularly when problem behavior continues to produce escape. However, this research has overwhelmingly used distributed-reinforcement arrangements, where tasks and reinforcer access are interspersed throughout the work period. An alternative to interspersal involves allowing the individual to accumulate and then receive a larger quantity of reinforcement once work requirements are completed; this is known as an accumulated-reinforcement arrangement. The current study examined the efficacy of, and preference for positive (food) and negative (break) reinforcement contingencies delivered in accumulated and distributed arrangements in the treatment of escape-maintained problem behavior. In Experiment 1, accumulated break was preferred for 4 of 5 participants and accumulated food was preferred for 3 of 5. In Experiment 2, accumulated break was similarly effective to distributed break for 3 of 5 participants and accumulated and distributed food were equally effective for 4 participants.

Standardization of DNA amount for bisulfite conversion for analyzing the methylation status of LINE-1 in lung cancer.

Highly methylated Long Interspersed Nucleotide Elements 1 (LINE-1) constitute approximately 20% of the human genome, thus serving as a surrogate marker of global genomic DNA methylation. To date, there is still lacking a consensus about the precise location in LINE-1 promoter and its methylation threshold value, making challenging the use of LINE-1 methylation as a diagnostic, prognostic markers in cancer. This study reports on a technical standardization of bisulfite-based DNA methylation analysis, which ensures the complete bisulfite conversion of repeated LINE-1 sequences, thus allowing accurate LINE-1 methylation value. In addition, the study also indicated the precise location in LINE-1 promoter of which significant variance in methylation level makes LINE-1 methylation as a potential diagnostic biomarker for lung cancer. A serial concentration of 5-50-500 ng of DNA from 275 formalin-fixed paraffin-embedded lung tissues were converted by bisulfite; methylation level of two local regions (at nucleotide position 300-368 as LINE-1.1 and 368-460 as LINE-1.2) in LINE-1 promoter was measured by real time PCR. The use of 5 ng of genomic DNA but no more allowed to detect LINE-1 hypomethylation in lung cancer tissue (14.34% versus 16.69% in non-cancerous lung diseases for LINE-1.1, p < 0.0001, and 30.28% versus 32.35% for LINE-1.2, p < 0.05). Our study thus highlighted the optimal and primordial concentration less than 5 ng of genomic DNA guarantees the complete LINE-1 bisulfite conversion, and significant variance in methylation level of the LINE-1 sequence position from 300 to 368 allowed to discriminate lung cancer from non-cancer samples.

Clinical evaluation of RB1 genetic testing reveals novel mutations in Vietnamese patients with retinoblastoma.

Clinical evaluation of the genetic testing strategy is essential for ensuring the correct determination of mutation carriers. The current study retrospectively analyzed genetic and clinicopathological data from 62 Vietnamese patients with retinoblastoma (RB) referred to the Vinmec Hi-Tech Center for RB transcriptional corepressor 1 (RB1) genetic testing between 2017 and 2019. The present study aimed to evaluate the sensitivity of the Next Generation Sequencing (NGS) method to identify novel RB1 mutations, and to consider using age at diagnosis as a risk factor. Genomic DNA was analyzed with custom panel based targeted NGS. NGS was performed on the Beijing Genomics Institute (BGI) sequencing platform, and pathogenic or likely pathogenic variants were confirmed by Sanger sequencing, quantitative PCR (qPCR) or Multiplex Ligation-dependent Probe Amplification assay (MLPA). Constitutional RB1 variants were identified in 100% (25/25) of the bilateral cases, while several common previously reported RB1 mutations were also recorded. In addition, in Vietnamese patients with RB, nine novel RB1 mutations were identified. Children aged between 0-36 months were more likely to be RB1 carriers compared with those aged >36 months. The current findings indicated that the NGS method implemented in the Vinmec Hi-Tech Center was highly accurate, and age at diagnosis may be used to assess the risk of hereditary RB. Furthermore, the newly identified RB1 mutations may provide additional data to improve the current understanding of the mechanisms underlying RB1 inactivation and the development of rapid assays for detecting RB1 mutations. Overall, the present study suggested that NGS may be applied for detecting germline RB1 mutations in routine clinical practice.

A review of artificial intelligence applications for motion tracking in radiotherapy.

During radiotherapy, the organs and tumour move as a result of the dynamic nature of the body; this is known as intrafraction motion. Intrafraction motion can result in tumour underdose and healthy tissue overdose, thereby reducing the effectiveness of the treatment while increasing toxicity to the patients. There is a growing appreciation of intrafraction target motion management by the radiation oncology community. Real-time image-guided radiation therapy (IGRT) can track the target and account for the motion, improving the radiation dose to the tumour and reducing the dose to healthy tissue. Recently, artificial intelligence (AI)-based approaches have been applied to motion management and have shown great potential. In this review, four main categories of motion management using AI are summarised: marker-based tracking, markerless tracking, full anatomy monitoring and motion prediction. Marker-based and markerless tracking approaches focus on tracking the individual target throughout the treatment. Full anatomy algorithms monitor for intrafraction changes in the full anatomy within the field of view. Motion prediction algorithms can be used to account for the latencies due to the time for the system to localise, process and act.

A real-time IGRT method using a Kalman filter framework to extract 3D positions from 2D projections.

Purpose.To estimate 3D prostate motion in real-time during irradiation from 2D prostate positions acquired from a kV imager on a standard linear accelerator utilising a Kalman filter (KF) framework. The advantage of this novel method is threefold: (1) eliminating the need of an initial learning period, therefore reducing patient imaging dose, (2) more robust against measurement noise and (3) more computationally efficient. In this paper, the novel KF method was evaluatedin silicousing patients' 3D prostate motion and simulated 2D projections.Methods.A KF framework was implemented to estimate 3D motion from 2D projection measurements in real-time during prostate cancer treatments. The noise covariance matrix was adaptively estimated from the previous 10 measurements. This method did not require an initial learning period as the KF process distribution was initialised using a population covariance matrix. This method was evaluated using a ground-truth motion dataset of 17 prostate cancer patients (536 trajectories) measured with electromagnetic transponders. 3D motion was projected onto a rotating imager (SID = 180 cm) (pixel size = 0.388 mm) and rotation speed of 6°/s and 2°/s to simulate VMAT treatments. Gantry-varying additive random noise (≤5 mm) was added to ground-truth measurements to simulate segmentation error and image quality degradation due to the patient's pelvic bones. For comparison, motion was also estimated using the clinically implemented Gaussian probability density function (PDF) method initialised with 600 projections.Results.Without noise, the 3D root mean square-errors (3D RMSEs) of motion estimated by the KF method were 0.4 ± 0.1 mm and 0.3 ± 0.2 mm for 2°/s and 6°/s gantry rotation, respectively. With noise, 3D RMSEs of KF estimated motion were 1.1 ± 0.1 mm for both slow and fast gantry rotation scenarios. In comparison, using a Gaussian PDF method, with noise, 3D RMSE was 2 ± 0.1 mm for both gantry rotation scenarios.Conclusion.This work presents a fast and accurate method for real-time 2D to 3D motion estimation using a KF approach to handle the random-walk component of prostate cancer motion. This method has sub-mm accuracy and is highly robust against measurement noise.