First direct machine-specific parameters incorporated in Spot-scanning Proton Arc (SPArc) optimization algorithm.

BACKGROUND: Spot-scanning Proton Arc (SPArc) has been of significant interest in recent years because of its superior plan quality. Currently, the primary focus of research and development is on deliverability and treatment efficiency. PURPOSE: To address the challenges in generating a deliverable and efficient SPArc plan for a proton therapy system with a massive gantry, we developed a novel SPArc optimization algorithm (SPArcDMPO ) by directly incorporating the machine-specific parameters such as gantry mechanical constraints and proton delivery sequence. METHODS: SPArc delivery sequence model (DSMarc ) was built based on the machine-specific parameters of the prototype arc delivery system, IBA ProteusONE®, including mechanical constraint (maximum gantry speed, acceleration, and deceleration) and proton delivery sequence (energy and spot delivery sequence, and irradiation time). SPArcDMPO resamples and adjusts each control point's delivery speed based on the DSMarc calculation through the iterative approach. In SPArcDMPO, users could set a reasonable arc delivery time during the plan optimization, which aims to minimize the gantry momentum changes and improve the delivery efficiency. Ten cases were selected to test SPArcDMPO . Two kinds of SPArc plans were generated using the same planning objective functions: (1) original SPArc plan (SPArcoriginal ); (2) SPArcDMPO plan with a user-pre-defined delivery time. Additionally, arc delivery sequence was simulated based on the DSMarc and was compared. Treatment delivery time was compared between SPArcoriginal and SPArcDMPO . Dynamic arc delivery time, the static irradiation time, and its corresponding time differential (time differential = dynamic arc delivery time-static irradiation time) were analyzed, respectively. The total gantry velocity change was accumulated throughout the treatment delivery. RESULTS: With a similar plan quality, objective value, number of energy layers, and spots, both SPArcoriginal and SPArcDMPO plans could be delivered continuously within the ± 1 degree tolerance window. However, compared to the SPArcoriginal , the strategy of SPArcDMPO is able to reduce the time differential from 30.55 ± 11.42%(90 ± 32 s) to 14.67 ± 6.97%(42 ± 20 s), p < 0.01. Furthermore, the corresponding total variations of gantry velocity during dynamic arc delivery are mitigated (SPArcoriginal vs. SPArcDMPO ) from 14.73 ± 9.14 degree/s to 4.28 ± 2.42 degree/s, p < 0.01. Consequently, the SPArcDMPO plans could minimize the gantry momentum change based on the clinical user's input compared to the SPArcoriginal plans, which could help relieve the mechanical challenge of accelerating or decelerating the massive proton gantry. CONCLUSIONS: For the first time, clinical users not only could generate a SPArc plan meeting the mechanical constraint of their proton system but also directly control the arc treatment speed and momentum changes of the gantry during the plan optimization process. This work paved the way for the routine clinical implementation of proton arc therapy in the treatment planning system.

Impact of and interplay between proton arc therapy and range uncertainties in proton therapy for head-and-neck cancer.

Objective. Proton therapy reduces the integral dose to the patient compared to conventional photon treatments. However,in vivoproton range uncertainties remain a considerable hurdle. Range uncertainty reduction benefits depend on clinical practices. During intensity-modulated proton therapy (IMPT), the target is irradiated from only a few directions, but proton arc therapy (PAT), for which the target is irradiated from dozens of angles, may see clinical implementation by the time considerable range uncertainty reductions are achieved. It is therefore crucial to determine the impact of PAT on range uncertainty reduction benefits.Approach. For twenty head-and-neck cancer patients, four different treatment plans were created: an IMPT and a PAT treatment plan assuming current clinical range uncertainties of 3.5% (IMPT3.5%and PAT3.5%), and an IMPT and a PAT treatment plan assuming that range uncertainties can be reduced to 1% (IMPT1%and PAT1%). Plans were evaluated with respect to target coverage and organ-at-risk doses as well as normal tissue complication probabilities (NTCPs) for parotid glands (endpoint: parotid gland flow <25%) and larynx (endpoint: larynx edema).Main results. Implementation of PAT (IMPT3.5%-PAT3.5%) reduced mean NTCPs in the nominal and worst-case scenario by 3.2 percentage points (pp) and 4.2 pp, respectively. Reducing range uncertainties from 3.5% to 1% during use of IMPT (IMPT3.5%-IMPT1%) reduced evaluated NTCPs by 0.9 pp and 2.0 pp. Benefits of range uncertainty reductions subsequently to PAT implementation (PAT3.5%-PAT1%) were 0.2 pp and 1.0 pp, with considerably higher benefits in bilateral compared to unilateral cases.Significance. The mean clinical benefit of implementing PAT was more than twice as high as the benefit of a 3.5%-1% range uncertainty reduction. Range uncertainty reductions are expected to remain beneficial even after PAT implementation, especially in cases with target positions allowing for full leveraging of the higher number of gantry angles during PAT.

Peripheral Blood CD8+T Cell as a Prognostic Biomarker for Hospitalised COVID-19 Patients Without Antiviral Treatment.

Background: The status of T lymphocyte subset counts in patients with COVID-19 remains uncertain. This study aimed to assess alterations in peripheral blood CD3+CD8+T (CD8+T) cells among hospitalized COVID-19 patients who have not received antiviral treatment and to evaluate their prognostic value within this patient population. Methods: A single-center, retrospective cohort study and a meta-analysis were conducted. The cohort study was performed at Xiangya Hospital from December 5, 2022, to January 31, 2023. We conducted a meta-analysis to explore the association between peripheral blood CD3+CD8+T cells and mortality in COVID-19 patients who did not receive antiviral therapy. All relevant studies in Embase, PubMed, Web of Science databases were systematically searched for meta-analysis. Results: The retrospective cohort study included 201 patients. A significant decrease in peripheral blood CD8+ T cell count was found to be associated with an increased risk of mortality (adjusted odds ratio [aOR]: 13.88; 95% confidence interval [CI]: 3.15-61.23), after adjusting for gender, age, comorbidities, severity at admission, steroid therapy, and antibiotic therapy. The threshold value for CD8+T cell counts, determined by the receiver operating characteristic (ROC) curve analysis, was 145.5 (area under the curve [AUC]: 0.828, specificity: 90.3%, sensitivity: 72.9%, P<0.001). Additionally, A total of 7 studies with 2765 participants were included in the meta-analysis. The meta-analysis reveals a significant association between lower CD8+ T cell counts and mortality (odds ratio [OR] = 3.543, 95% CI: 1.726 to 7.272; I2=93%). Conclusion: Peripheral blood CD8+ T cell can serve as a valuable prognostic biomarker for hospitalized patients who do not receive antiviral treatment.

The added effects of cold spells on stroke admissions: Differential effects on ischemic and hemorrhagic stroke.

BACKGROUND: Epidemiological evidence suggests an association between low ambient temperature and stroke risk, but available data are limited particularly on associations with different stroke subtypes. AIMS: The aim of this study is to estimate the relationship between cold spells and stroke admissions, including the effect of cold spells on different stroke subtypes (ischemic stroke and intracerebral hemorrhage (ICH)). METHODS: A total of 144,405 stroke admissions from the Tianjin Centre for Health and Meteorology Multidisciplinary Innovation in China, covering the period from January 2016 to December 2020, were studied, as well as meteorological and air pollutant data. A generalized additive model with a distributed lag nonlinear model was employed to assess the relationship, considering 12 different definitions of a cold spell based on various temperature thresholds and durations. The analysis controlled for lagged and nonlinear effects of temperature. Analyses were performed on all strokes as well as ischemic stroke and ICH. RESULTS: There was a significant increase in stroke admissions during cold spells. Generally, the increased risk during cold spells increased as the temperature threshold decreased, but was not significantly affected by the duration. The optimal model was obtained using the cold-spell definition based on an average daily temperature below the 10th percentile (0.11°C) for 2 or more consecutive days. According to this model, the effect of cold spells on ischemic stroke admissions had a significant lag effect and was long-lasting, with a single-day effect occurring on lag 7d, peaking on lag 13d (relative risk (RR) = 1.05; 95% confidence interval (CI) = 1.02 to 1.09), and lasting until lag 20d. In contrast, the effect on ICH was immediate and short-lived, with the most significant single-day effect occurring on the current day (RR = 1.17; 95% CI = 1.06 to 1.29) and limited within 3 days. 14.15% of stroke cases could be attributed to cold spells, with ICH exhibiting a higher burden than ischemic stroke except for strict temperature threshold definitions. CONCLUSION: Cold spells are associated with an increased stroke risk. Different patterns of association were seen for different stroke subtypes. The effect on ischemic stroke had a lag effect and a longer duration, whereas the effect on ICH had an immediate effect and a shorter duration. These findings support the development and improvement of stroke cold-spell early warning systems and highlight the importance of public health interventions to mitigate the adverse health impacts of cold spells.

Low ambient temperature exposure increases the risk of ischemic stroke by promoting platelet activation.

BACKGROUND: Accumulating epidemiological evidence suggests the association between low ambient temperature exposure and the risk of ischemic stroke, but the underlying mechanisms remain unclear. OBJECTIVE: Given the crucial role of platelet activation and thrombosis in ischemic stroke, this study aims to investigate the effect of ambient temperature on platelet activation through multi-center clinical data in Tianjin as well as animal experiments. METHODS: From 2018 to 2020, nearly 3000 ischemic stroke patients from three stroke centers in Tianjin were included in the analysis, among them the ADP induced platelet aggregation rate was available. Meteorological data from the same period had also been collected. After controlling for confounding factors, the generalized additive mixed model (GAMM) was used to evaluate the correlation between environmental temperature and platelet aggregation rate. In further animal experiments, platelet function assessments were conducted on mice from the cold exposure group and the normal temperature group, including platelet aggregation, spreading, and clot retraction. Additionally, tail bleeding and mesentery thrombosis were also tested to monitor hemostasis and thrombosis in vivo. RESULT: A nonlinear "S" shaped relationship between outdoor temperature and platelet aggregation was found. Each 1 °C decrease of mean temperature was associated with an increase of 7.77 % (95 % CI: 2.06 % - 13.48 %) in platelet aggregation. The ambient temperature is not related to other platelet parameters. Subgroup analysis found that males, people aged ≥65 years, and hypertensive individuals are more susceptible to temperature changes. Furthermore, animal experiments demonstrated that the increased CIRBP levels and subsequent activation of p-AKT/p-ERK may be one of the reasons for cold exposure induced platelets activation. CONCLUSION: Both clinical data and basic research support that low ambient temperature exposure has the potential to increase platelet activation. These results provide a basis for understanding the potential mechanism of temperature variations on the pathogenesis of cerebrovascular diseases.

Development of a standalone delivery sequence model for proton arc therapy.

BACKGROUND: Spot-scanning proton arc (SPArc) has been drawing significant interests in recent years because of its capability of continuous proton irradiation during the gantry rotation. Previous studies demonstrated SPArc plans were delivered on a prototype of the DynamicARC solution, IBA ProteusONE. PURPOSE: We built a novel delivery sequence model through an independent experimental approach: the first SPArc delivery sequence model (DSMSPArc ). Based on the model, we investigated SPArc treatment efficiency improvement in the routine proton clinical operation. METHODS: SPArc test plans were generated and delivered on a prototype of the DynamicARC solution, IBA ProteusONE. An independent gantry inclinometer and the machine logfiles were used to derive the DSMSPArc. Seventeen SPArc plans were used to validate the model's accuracy independently. Two random clinical operation dates (6th January and 22nd March, 2021) from a single-room proton therapy center (PTC) were selected to quantitatively assess the improvement of treatment efficiency compared to the IMPT. RESULTS: The difference between the logfile and DSMSPArc is about 3.2 ± 4.8%. SPArc reduced 58.1% of the average treatment delivery time per patient compared to IMPT (p < 0.01). Daily treatment throughput could be increased by 30% using SPArc using a single-room proton therapy system. CONCLUSIONS: The first model of dynamic arc therapy is established in this study through an independent experimental approach using logfiles and measurements which allows clinical users and investigators to simulate the dynamic treatment delivery and assess the daily treatment throughput improvement.

Clinical Characteristics and Molecular Epidemiology of ST23 Klebsiella pneumoniae in China.

Purpose: In clinical settings, CG23 Klebsiella pneumoniae (Kp) is the most virulent clonal group of Kp. Continuous fusions of hypervirulent (Hv) and highly resistant strains have been reported; however, few studies have analysed the molecular epidemiology and clinical characteristics of CG23 strains, especially MDR-sequence type ST23 strains. In this study, we investigated the molecular characteristics of ST23 Kp and analysed the clinical characteristics of ST23 Kp infections in a large teaching hospital of the third class in China. Methods: ST23 Kp isolates were screened using whole-genome sequencing data from a large single centre. We compared the clinical characteristics of ST23 strains isolated from community-acquired infections (CAI) and hospital acquired infection (HAI). In addition, the infection characteristics of MDR and poor-prognosis isolates were investigated. We analysed genetic characteristics of ST23 Kp and further investigated the evolutionary relationship based on single-nucleotide polymorphism phylogenetic trees. Results: We detected 184 ST23 strains between 2013 and July of 2018. There were no significant differences between the isolation rates of pulmonary, bloodstream, urinary tract, and cutaneous soft tissue infections in the community and hospitals, except for abscess infections. MDR strains primarily cause pulmonary infections and abscesses; infections with a poor prognosis are typically bloodstream and pulmonary infections. Fourteen MDR strains producing extended-spectrum or class C beta-lactamases, resulting in resistance to third-generation cephalosporins. In 3.8% of ST23 Kp strains, the clb locus was absent. The phylogenetic tree revealed that the isolates were primarily divided into three clades, and based on clinical data, it is inferred that three clonal transmission events have occurred, mainly in ICU causing lung infection. Conclusion: This study demonstrates that virulence and drug-resistance fusion events of ST23 strains occur gradually, and that the hypervirulent clones facilitate the widespread dissemination of CAI and HAI, particularly pulmonary. Monitoring genomics and developing antivirulence strategies are essential.

Extracting laboratory test information from paper-based reports.

BACKGROUND: In the healthcare domain today, despite the substantial adoption of electronic health information systems, a significant proportion of medical reports still exist in paper-based formats. As a result, there is a significant demand for the digitization of information from these paper-based reports. However, the digitization of paper-based laboratory reports into a structured data format can be challenging due to their non-standard layouts, which includes various data types such as text, numeric values, reference ranges, and units. Therefore, it is crucial to develop a highly scalable and lightweight technique that can effectively identify and extract information from laboratory test reports and convert them into a structured data format for downstream tasks. METHODS: We developed an end-to-end Natural Language Processing (NLP)-based pipeline for extracting information from paper-based laboratory test reports. Our pipeline consists of two main modules: an optical character recognition (OCR) module and an information extraction (IE) module. The OCR module is applied to locate and identify text from scanned laboratory test reports using state-of-the-art OCR algorithms. The IE module is then used to extract meaningful information from the OCR results to form digitalized tables of the test reports. The IE module consists of five sub-modules, which are time detection, headline position, line normalization, Named Entity Recognition (NER) with a Conditional Random Fields (CRF)-based method, and step detection for multi-column. Finally, we evaluated the performance of the proposed pipeline on 153 laboratory test reports collected from Peking University First Hospital (PKU1). RESULTS: In the OCR module, we evaluate the accuracy of text detection and recognition results at three different levels and achieved an averaged accuracy of 0.93. In the IE module, we extracted four laboratory test entities, including test item name, test result, test unit, and reference value range. The overall F1 score is 0.86 on the 153 laboratory test reports collected from PKU1. With a single CPU, the average inference time of each report is only 0.78 s. CONCLUSION: In this study, we developed a practical lightweight pipeline to digitalize and extract information from paper-based laboratory test reports in diverse types and with different layouts that can be adopted in real clinical environments with the lowest possible computing resources requirements. The high evaluation performance on the real-world hospital dataset validated the feasibility of the proposed pipeline.

A novel auxiliary diagnostic model for COVID-19 screening using enzymes based detection of serum biomarkers and clinical characteristics.

The screening for the coronavirus disease 2019 (COVID-19) based on virus nuclear acid detection and radiology has encountered unprecedented difficulties due to the shortage of kits and facilities, and the lack of sensitivity and specificity, especially for developing countries. The study aimed to develop an auxiliary diagnostic score based on age, biomarkers, clinical characteristics (ABC) to rapidly and accurately screen COVID-19. Serum biomarkers were detected by enzymes catalyzed reaction method which is rapid and accurate. A retrospective case-control study among Chinese patients with laboratory-confirmed COVID-19 and those without COVID-19 was conducted. Data of age, sex, signs and symptoms, history of disease, complete blood counts, and serum biochemical items such as ALT and AST were used to establish the diagnostic model. ALT/AST was detected by enzymes based biochemical reaction method. Stepwise logistic regression and random forests with variable selection process were used to establish the model. Ten-fold cross-validation and out-of-bag error were used to assess the accuracy of the models. Decision curve analysis was used to compare different models. A total of 279 cases and 253 controls were recruited, with mean age of 60.7 ± 13.7 and 42.6 ± 20.2, respectively. The regression model selected nine variables with Kappa of 0.77, sensitivity of 0.90, and specificity of 0.87. The random forests retained eight variables with Kappa of 0.76, sensitivity of 0.87, and specificity of 0.89. Based on decision curve analysis, the ABC-based diagnostic score provided the largest net benefit compared to other models with less data input. Subgroup analysis by excluding severely ill cases showed a decreased but acceptable sensitivity (0.75) and unchanged overall accuracy. The ABC-based diagnostic score provides a rapid and valid method for COVID-19 screening, especially for regions with a shortage of facilities. The model performs less well in the diagnosis of mild-to-moderate COVID-19.

Clinical characteristics, outcomes, and risk factors of SARS-CoV-2 breakthrough infections among 572 fully vaccinated (BBIBP-CorV) hospitalized patients.

Background: Breakthrough infections have been widely reported in vaccinated individuals. However, the clinical characteristics, outcomes, and risk factors of SARS-CoV-2 breakthrough infections among fully vaccinated (BBIBP-CorV) hospitalized patients have not yet been fully elucidated. Methods: In the single-center cohort study conducted at Xiangya Hospital of Central South University, we enrolled the hospitalized COVID-19 patients who had received full (2 doses) vaccination with the BBIBP-CorV vaccine between December 5, 2022, and January 31, 2023. We collected and analyzed information related to clinical characteristics, laboratory results, treatments, outcomes and prognostic data. Univariate and multivariable Cox regression were performed to assess the impact of clinical characteristics and laboratory results on the composite outcome (including the initiation of endotracheal intubation, non-invasive respiratory support, intensive care unit admission, and all-cause death). Results: A total of 572 COVID-19 hospitalized patients with fully vaccinated (BBIBP-CorV) were included. The median age of the patients was 66 years (IQR 53, 74). The most common symptoms included fever (347 [60.7 %]), dry cough (401 [70.1 %]), and expectoration (333 [58.2 %]). Among those with pre-existing chronic comorbidities, 44.2 % had hypertension and 20.5 % had diabetes. Laboratory tests revealed that the majority of patients (425/549 [77.4 %]) had normal white blood cell counts. Composite outcome occurred in 11.9 % of patients, with 96.7 % of patients discharged and 3.3 % of patients died. Multivariate Cox regression analyses suggested that the NLR >4 (adjusted HR, 5.50 [95%CI: 1.56-19.47]; P = 0.008), D-dimer >0.5 mg/ml (adjusted HR, 2.17 [95%CI: 1.03-4.59]; P = 0.042) and procalcitonin >0.1 ng/ml (adjusted HR, 3.22 [95%CI: 1.38-7.52]; P = 0.007) were independently associated with the composite outcome. Conclusion: Breakthrough infection after being fully vaccinated (BBIBP-CorV) is more likely to occur in older patients and patients with pre-existing chronic comorbidities. NLR >4, D-dimer >0.5 mg/ml and procalcitonin >0.1 ng/ml were independent risk factors for composite outcome.

Features of architectural landscape fragmentation in traditional villages in Western Hunan, China.

With rapid industrialization and urbanization in China, inadequate preservation of traditional architecture coupled with natural deterioration have led to the fragmentation of architectural landscapes. Drawing from ecological fragmentation research in landscape ecology, we consider the cultural landscape as our research object, viewing buildings as landscape patches, and determine a system for measuring architectural landscape fragmentation in traditional villages. The study shows the degree of landscape fragmentation can reveal the characteristics of traditional villages and the process of regional modernization. The results are as follows: (1) From the perspective of landscape diversity, the study area was rich in landscape types in all dimensions, and the relative evenness index was high, signifying evident or severe fragmentation. (2) The index of landscape heterogeneity in the dimensions of building quality, height, and landscape appearance is low in the study area, with mild levels of landscape fragmentation caused by heterogeneity in the aforementioned dimensions. (3) Mild fragmentation suggests the integrity and homogeneity of architectural landscape types, reflecting a lagging level of economic development, whereas high fragmentation signifies rapid economic development, leading to a substantial deterioration in the integrity and homogeneity of architectural landscape types. Therefore, efforts to preserve and develop traditional villages should not solely aim for low fragmentation as it could potentially constrain sustainable development.

Genomic and clinical characterization of Klebsiella pneumoniae carrying the pks island.

Background: The pks island and its production of the bacterial secondary metabolite genotoxin, colibactin, have attracted increasing attention. However, genomic articles focusing on pks islands in Klebsiella pneumoniae, as well as comparative genomic studies of mobile genetic elements, such as prophages, plasmids, and insertion sequences, are lacking. In this study, a large-scale analysis was conducted to understand the prevalence and evolution of pks islands, differences in mobile genetic elements between pks-negative and pks-positive K. pneumoniae, and clinical characteristics of infection caused by pks-positive K. pneumoniae. Methods: The genomes of 2,709 K. pneumoniae were downloaded from public databases, among which, 1,422 were from NCBI and 1,287 were from the China National GeneBank DataBase (CNGBdb). Screening for virulence and resistance genes, phylogenetic tree construction, and pan-genome analysis were performed. Differences in mobile genetic elements between pks-positive and pks-negative strains were compared. The clinical characteristics of 157 pks-positive and 157 pks-negative K. pneumoniae infected patients were investigated. Results: Of 2,709 K. pneumoniae genomes, 245 pks-positive genomes were screened. The four siderophores, type VI secretion system, and nutritional factor genes were present in at least 77.9% (191/245), 66.9% (164/245), and 63.3% (155/245) of pks-positive strains, respectively. The number and fragment length of prophage were lower in pks-positive strains than in pks-negative strains (p < 0.05). The prevalence of the IS6 family was higher in pks-negative strains than in pks-positive strains, and the prevalence of multiple plasmid replicon types differed between the pks-positive and pks-negative strains (p < 0.05). The detection rate of pks-positive K. pneumoniae in abscess samples was higher than that of pks-negative K. pneumoniae (p < 0.05). Conclusion: The pks-positive strains had abundant virulence genes. There were differences in the distribution of mobile genetic elements between pks-positive and pks-negative isolates. Further analysis of the evolutionary pattern of pks island and epidemiological surveillance in different populations are needed.

Flexible and broadband colloidal quantum dots photodiode array for pixel-level X-ray to near-infrared image fusion.

Combining information from multispectral images into a fused image is informative and beneficial for human or machine perception. Currently, multiple photodetectors with different response bands are used, which require complicated algorithms and systems to solve the pixel and position mismatch problem. An ideal solution would be pixel-level multispectral image fusion, which involves multispectral image using the same photodetector and circumventing the mismatch problem. Here we presented the potential of pixel-level multispectral image fusion utilizing colloidal quantum dots photodiode array, with a broadband response range from X-ray to near infrared and excellent tolerance for bending and X-ray irradiation. The colloidal quantum dots photodiode array showed a specific detectivity exceeding 1012 Jones in visible and near infrared range and a favorable volume sensitivity of approximately 2 × 105 µC Gy-1 cm-3 for X-ray irradiation. To showcase the advantages of pixel-level multispectral image fusion, we imaged a capsule enfolding an iron wire and soft plastic, successfully revealing internal information through an X-ray to near infrared fused image.

The first investigation of spot-scanning proton arc (SPArc) delivery time and accuracy with different delivery tolerance window settings.

Objective. To investigate the impact of various delivery tolerance window settings on the treatment delivery time and dosimetric accuracy of spot-scanning proton arc (SPArc) therapy.Approach. SPArc plans were generated for three representative disease sites (brain, lung, and liver cancer) with an angle sampling frequency of 2.5°. An in-house dynamic arc controller was used to simulate the arc treatment delivery with various tolerance windows (±0.25, ±0.5, ±1, and ±1.25°). The controller generates virtual logfiles during the arc delivery simulation, such as gantry speed, acceleration and deceleration, spot position, and delivery sequence, similar to machine logfiles. The virtual logfile was then imported to the treatment planning system to reconstruct the delivered dose distribution and compare it to the initial SPArc nominal plan. A three-dimensional gamma index was used to quantitatively assess delivery accuracy. Total treatment delivery time and relative lost time (dynamic arc delivery time-fix beam delivery time)/fix beam delivery time) were reported.Main Results. The 3D gamma passing rate (GPR) was greater than 99% for all cases when using 3%/3 mm and 2%/2 mm criteria and the GPR (1%/1 mm criteria) degraded as the tolerance window opens. The total delivery time for dynamic arc delivery increased with the decreasing delivery tolerance window length. The average delivery time and the relative lost time (%) were 630 ± 212 s (253% ± 68%), 322 ± 101 s (81% ± 31%), 225 ± 60 s (27% ± 16%), 196 ± 41 s (11% ± 6%), 187 ± 29 s (6% ± 1%) for tolerance windows ±0.25, ±0.5, ±1, and ±1.25° respectively.Significance. The study quantitatively analyzed the dynamic SPArc delivery time and accuracy with different delivery tolerance window settings, which offer a critical reference in the future SPArc plan optimization and delivery controller design.

Novel Jasmonic Acid-Coumarin Pathway in the Eggplant That Inhibits Vitellogenin Gene Expression To Prevent Mite Reproduction.

Plants activate direct and indirect defense mechanisms in response to perceived herbivore invasion, which results in negative consequences for herbivores. Tetranychus cinnabarinus is a polyphagous generalist herbivore that inflicts substantial agricultural and horticultural damage. Our study revealed that mite feeding significantly increased jasmonic acid (JA) in the eggplant. The damage inflicted by the mites decreased considerably following the artificial application of JA, thereby indicating that JA initiated the defense response of the eggplant against mites. The transcriptomic and metabolomic analyses demonstrated the activation of the JA-coumarin pathway in response to mite feeding. This pathway protects the eggplant by suppressing the reproductive capacity and population size of the mites. The JA and coumarin treatments suppressed the vitellogenin gene (TcVg6) expression level. Additionally, RNA interference with TcVg6 significantly reduced the egg production and hatching rate of mites. In conclusion, the JA-coumarin pathway in the eggplant decreases the egg-hatching rate of mites through suppression of TcVg6.

EdgeMap: An Optimized Mapping Toolchain for Spiking Neural Network in Edge Computing.

Spiking neural networks (SNNs) have attracted considerable attention as third-generation artificial neural networks, known for their powerful, intelligent features and energy-efficiency advantages. These characteristics render them ideally suited for edge computing scenarios. Nevertheless, the current mapping schemes for deploying SNNs onto neuromorphic hardware face limitations such as extended execution times, low throughput, and insufficient consideration of energy consumption and connectivity, which undermine their suitability for edge computing applications. To address these challenges, we introduce EdgeMap, an optimized mapping toolchain specifically designed for deploying SNNs onto edge devices without compromising performance. EdgeMap consists of two main stages. The first stage involves partitioning the SNN graph into small neuron clusters based on the streaming graph partition algorithm, with the sizes of neuron clusters limited by the physical neuron cores. In the subsequent mapping stage, we adopt a multi-objective optimization algorithm specifically geared towards mitigating energy costs and communication costs for efficient deployment. EdgeMap-evaluated across four typical SNN applications-substantially outperforms other state-of-the-art mapping schemes. The performance improvements include a reduction in average latency by up to 19.8%, energy consumption by 57%, and communication cost by 58%. Moreover, EdgeMap exhibits an impressive enhancement in execution time by a factor of 1225.44×, alongside a throughput increase of up to 4.02×. These results highlight EdgeMap's efficiency and effectiveness, emphasizing its utility for deploying SNN applications in edge computing scenarios.

Rapid Detection of Trace Nitro-Explosives under UV Irradiation by Electronic Nose with Neural Networks.

The development of an electronic nose (E-nose) for rapid explosive trace detection (ETD) has been extensively studied. However, the extremely low saturated vapor pressure of explosives becomes the major obstacle for E-nose to be applied in practical environments. In this work, we innovatively combine the decomposition characteristics of nitro explosives when exposed to ultraviolet light into gas sensors for detecting explosives, and an E-nose consisting of a SnO2/WO3 nanocomposite-based chemiresistive sensor array with an artificial neural network is utilized to identify trace nitro-explosives by detecting their photolysis gas products, rather than the explosive molecules themselves or their saturated vapor. The ultralow detection limits for nitro-explosives can be achieved, and the detection limits toward three representative nitro-explosives of trinitrotoluene, pentaerythritol tetranitrate, and cyclotetramethylene tetranitroamine are as low as 500, 100, and 50 ng, respectively. Moreover, by extracting the features of sensor responses within 15 s, a classification system based on convolutional neural network (CNN) and long short-term memory network (LSTM) is introduced to realize fast and accurate classification. The 5-fold cross-validation results demonstrate that the CNN-LSTM model exhibits the highest classification accuracy of 97.7% compared with those of common classification models. This work realizes the detection of explosives photolysis gases using sensor technology, which provides a unique insight for the classification of trace explosives.

Molecular epidemiology and clinical characteristics of the type VI secretion system in Klebsiella pneumoniae causing abscesses.

Purpose: The type VI system (T6SS) has the potential to be a new virulence factor for hypervirulent Klebsiella pneumoniae (hvKp) strains. This study aimed to characterize the molecular and clinical features of T6SS-positive and T6SS-negative K. pneumoniae isolates that cause abscesses. Patients and methods: A total of 169 non-duplicate K. pneumoniae strains were isolated from patients with abscesses in a tertiary hospital in China from January 2018 to June 2022, and clinical data were collected. For all isolates, capsular serotypes, T6SS genes, virulence, and drug resistance genes, antimicrobial susceptibility testing, and biofilm formation assays were assessed. Multilocus sequence typing was used to analyze the genotypes of hvKp. T6SS-positive hvKp, T6SS-negative hvKp, T6SS-positive cKP, and T6SS-negative cKP (n = 4 strains for each group) were chosen for the in vivo Galleria mellonella infection model and in vitro competition experiments to further explore the microbiological characteristics of T6SS-positive K. pneumoniae isolates. Results: The positive detection rate for T6SS was 36.1%. The rates of hvKp, seven virulence genes, K1 capsular serotype, and ST23 in T6SS-positive strains were all higher than those in T6SS-negative strains (p < 0.05). Multivariate logistic regression analysis indicated that the carriage of aerobactin (OR 0.01) and wcaG (OR 33.53) were independent risk factors for T6SS-positive strains (p < 0.05). The T6SS-positive strains had a stronger biofilm-forming ability than T6SS-negative strains (p < 0.05). The T6SS-positive and T6SS-negative strains showed no significant differences in competitive ability (p = 0.06). In the in vivo G. mellonella infection model, the T6SS(+)/hvKP group had the worst prognosis. Except for cefazolin and tegacyclin, T6SS-positive isolates displayed a lower rate of antimicrobial resistance to other drugs (p < 0.05). The T6SS-positive isolates were more likely to be acquired from community infections (p < 0.05). Conclusion: Klebsiella pneumoniae isolates causing abscesses have a high prevalence of T6SS genes. T6SS-positive K. pneumoniae isolates are associated with virulence, and the T6SS genes may be involved in the hvKp virulence mechanism.

Association between polymorphisms in connexin 40 gene (Cx40) and risk of atrial fibrillation: a meta-analysis based on 3,452 subjects.

INTRODUCTION: Atrial fibrillation (AF) is a common cardiac arrhythmia that is associated with heart failure and stroke, leading sometimes to death. But the pathogenesis of AF remains unclear. Numerous studies have investigated whether the connexin 40 (Cx40) polymorphisms influences the risk of AF, but the results are controversial. METHODS: We searched English and Chinese databases and calculated the odds ratio (OR) and 95% confidence interval (CI) to examine the existence of genetic associations between the Cx40 polymorphisms and the risk of AF. All relevant studies were screened and meta-analyzed using Review Manager 5.0. RESULTS: A total of 12 studies, including 10 studies for -44 polymorphism (rs35594137) and 4 studies for -26 polymorphism (rs10465885), were identified for the meta-analysis. For -44 polymorphism, the results showed a significantly increased risk of AF in the five genetic models in the overall analysis. Furthermore, in subgroup analysis, increased AF risks were also observed in Asian and non-Asian populations. For -26 polymorphism, the overall OR revealed an increased risk of AF in dominant model. In subgroup analysis, increased AF risk was only found in recessive genetic model of the Asian population. CONCLUSIONS: The Cx40 polymorphisms were positively associated with AF in both populations, especially on -44 polymorphism.