Progressive auto-segmentation for cone-beam computed tomography-based online adaptive radiotherapy.

Background and purpose: Accurate and automated segmentation of targets and organs-at-risk (OARs) is crucial for the successful clinical application of online adaptive radiotherapy (ART). Current methods for cone-beam computed tomography (CBCT) auto-segmentation face challenges, resulting in segmentations often failing to reach clinical acceptability. Current approaches for CBCT auto-segmentation overlook the wealth of information available from initial planning and prior adaptive fractions that could enhance segmentation precision. Materials and methods: We introduce a novel framework that incorporates data from a patient's initial plan and previous adaptive fractions, harnessing this additional temporal context to significantly refine the segmentation accuracy for the current fraction's CBCT images. We present LSTM-UNet, an innovative architecture that integrates Long Short-Term Memory (LSTM) units into the skip connections of the traditional U-Net framework to retain information from previous fractions. The models underwent initial pre-training with simulated data followed by fine-tuning on a clinical dataset. Results: Our proposed model's segmentation predictions yield an average Dice similarity coefficient of 79% from 8 Head & Neck organs and targets, compared to 52% from a baseline model without prior knowledge and 78% from a baseline model with prior knowledge but no memory. Conclusions: Our proposed model excels beyond baseline segmentation frameworks by effectively utilizing information from prior fractions, thus reducing the effort of clinicians to revise the auto-segmentation results. Moreover, it works together with registration-based methods that offer better prior knowledge. Our model holds promise for integration into the online ART workflow, offering precise segmentation capabilities on synthetic CT images.

Discovery of a Highly Promising Disulfide Derivative Scaffold as Inhibitor of SARS-CoV-2 main protease.

The main protease (Mpro) of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) represents a promising target for antiviral drugs aimed at combating COVID-19. Consequently, the development of Mpro inhibitor  is an ideal strategy for combating the virus. In this study, we identified twenty-two dithiocarbamates (1a-h), dithiocarbamate-Cu(II) complexes (2a-hCu) and disulfide derivatives (2a-e, 2i) as potent inhibitors of Mpro, with IC50 value range of 0.09-0.72, 0.9-24.7 and 15.1-111 µM, respectively, through FRET screening. The enzyme kinetics, inhibition mode, jump dilution, and DTT assay revealed that 1g may be a partial reversible inhibitor, while 2d and 2f-Cu are the irreversible and dose- and time-dependent inhibitors, potentially covalently binding to the target. Binding of 2d, 2f-Cu and 1g to Mpro was found to decrease the stability of the protein. Additionally, DTT assays and thermal shift assays indicated that 2f-Cu and 2d are the nonspecific and promiscuous cysteine protease inhibitor. ICP-MS implied that the inhibitory activity of 2f-Cu may stem from the uptake of Cu(II) by the enzyme. Cytotoxicity assays demonstrated that 2d and 1g exhibit low cytotoxicity, whereas 2f-Cu show certain cytotoxicity in L929 cells. Overall, this work presents two promising scaffolds for the development of Mpro inhibitors to combat COVID-19.

BCAR3 and BCAR3-related competing endogenous RNA expression in hepatocellular carcinoma and their prognostic value.

BACKGROUND: Hepatocellular carcinoma (HCC) is a malignant tumor that has a high incidence and mortality worldwide. Despite extensive studies, the detailed molecular mechanism of HCC development remains unclear. Studies have shown that the occurrence and development of HCC are closely related to abnormal gene expression. BCAR3 has been shown to be overexpressed in a variety of malignant tumors. However, the role of BCAR3 in HCC remains unclear. AIM: To investigate the expression of BCAR3 and BCAR3-related competing endogenous RNAs (ceRNAs) in HCC and their clinical significance, in order to provide new ideas for the diagnosis and treatment of HCC. METHODS: The data of HCC were obtained from the Cancer Genome Atlas database and The Genotype Tissue Expression, including transcriptome data and clinical information. Multiple common databases, including UALCAN, Timer 2.0, cBioPortal, LinkedOmics, starBase, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, were used to analyse the expression of BCAR3, prognostic value, genetic alteration, co-expressed genes, differentially expressed genes, BCAR3 gene-related ceRNAs and functional enrichment analysis in HCC patients. Kaplan-Meier analysis, univariate and multivariate Cox regression analysis were used to analyze survival prognosis and the Spearman test was used to measure correlations between BCAR3 and immune functions. And R language package was used to analyze the correlation between BCAR3 and immune invasion of HCC. RESULTS: Our study indicated that BCAR3 was differentially expressed in various tumor tissues. The over-expression of BCAR3 gene was an unfavorable prognostic indicator for HCC patients, and associated with unfavorable cytogenetic risk and gene mutations. Moreover, most immune cells were positively correlated with BCAR3 (P < 0.05). According to the results of functional enrichment analysis, BCAR3 was involved in the positive regulation of epidermal growth factor receptor signaling pathway and ERBB signaling pathway, and was related to DNA replication and GTPase regulator activity. Finally, our study found that based on RAB30-DT and miR-19b-3p pathways, targeting BCAR3 might promote the occurrence and development of HCC. CONCLUSION: Collectively, this study indicated that the BCAR3 gene was involved in the occurrence and development of HCC, and it might be a new biomarker and therapeutic target for HCC, but the specific mechanism remains to be further verified.

Long-term trends in cancer incidence and mortality among U.S. children and adolescents: a SEER database analysis from 1975 to 2018.

Background: Childhood and adolescent cancer represent a significant health burden in the United States. Current and precise epidemiological data are crucial to develop effective cancer control plans and ultimately reduce the burden of childhood and adolescent cancer. Methods: We analyzed data obtained from cancer registries in the National Cancer Institute's Surveillance, Epidemiology, and End Results Program. Age-standardized incidence and death rates, assessed using joinpoint analysis, were quantified as annual percentage changes (APC) and average percentage changes (AAPC). Results: The overall cancer incidence rate in 2008-2018 was 187.9 per 1,000,000 persons. Cancer incidence rates demonstrated a sustained upward trend, with an APC of 0.8 from 1975 to 2018. Incidence rates during 2008-2018 remained stable among non-Hispanic Black children but increased among other racial and ethnic groups. Leukemias, central nervous system tumors, and lymphomas were the most common cancer groups for patients aged 0-19 years. Cancer death rates decreased among children [AAPC, -1.3 (95% CI, -1.5 to -1.1)] during 2009-2019, while were stable among adolescents during that period. Conclusions: In this study, we analyzed cancer incidence and mortality rates and trends in children aged 0-19 years in the United States. Our findings revealed an overall increase in cancer incidence rates among children and adolescents, accompanied by a decline in cancer mortality rates over time. These rates and trends varied by age, sex, and particularly race and ethnicity, highlighting the significance of comprehending and addressing disparities and ultimately reducing the disease burden of childhood and adolescent cancer.

Helicobacter pylori-Induced Angiopoietin-Like 4 Promotes Gastric Bacterial Colonization and Gastritis.

Helicobacter pylori infection is characterized as progressive processes of bacterial persistence and chronic gastritis with features of infiltration of mononuclear cells more than granulocytes in gastric mucosa. Angiopoietin-like 4 (ANGPTL4) is considered a double-edged sword in inflammation-associated diseases, but its function and clinical relevance in H. pylori-associated pathology are unknown. Here, we demonstrate both pro-colonization and pro-inflammation roles of ANGPTL4 in H. pylori infection. Increased ANGPTL4 in the infected gastric mucosa was produced from gastric epithelial cells (GECs) synergistically induced by H. pylori and IL-17A in a cagA-dependent manner. Human gastric ANGPTL4 correlated with H. pylori colonization and the severity of gastritis, and mouse ANGPTL4 from non-bone marrow-derived cells promoted bacteria colonization and inflammation. Importantly, H. pylori colonization and inflammation were attenuated in Il17a -/-, Angptl4 -/-, and Il17a -/- Angptl4 -/- mice. Mechanistically, ANGPTL4 bound to integrin αV (ITGAV) on GECs to suppress CXCL1 production by inhibiting ERK, leading to decreased gastric influx of neutrophils, thereby promoting H. pylori colonization; ANGPTL4 also bound to ITGAV on monocytes to promote CCL5 production by activating PI3K-AKT-NF-κB, resulting in increased gastric influx of regulatory CD4+ T cells (Tregs) via CCL5-CCR4-dependent migration. In turn, ANGPTL4 induced Treg proliferation by binding to ITGAV to activate PI3K-AKT-NF-κB, promoting H. pylori-associated gastritis. Overall, we propose a model in which ANGPTL4 collectively ensures H. pylori persistence and promotes gastritis. Efforts to inhibit ANGPTL4-associated pathway may prove valuable strategies in treating H. pylori infection.

Silicon photocathode functionalized with osmium complex catalyst for selective catalytic conversion of CO2 to methane.

Solar-driven CO2 reduction to yield high-value chemicals presents an appealing avenue for combating climate change, yet achieving selective production of specific products remains a significant challenge. We showcase two osmium complexes, przpOs, and trzpOs, as CO2 reduction catalysts for selective CO2-to-methane conversion. Kinetically, the przpOs and trzpOs exhibit high CO2 reduction catalytic rate constants of 0.544 and 6.41 s-1, respectively. Under AM1.5 G irradiation, the optimal Si/TiO2/trzpOs have CH4 as the main product and >90% Faradaic efficiency, reaching -14.11 mA cm-2 photocurrent density at 0.0 VRHE. Density functional theory calculations reveal that the N atoms on the bipyrazole and triazole ligands effectively stabilize the CO2-adduct intermediates, which tend to be further hydrogenated to produce CH4, leading to their ultrahigh CO2-to-CH4 selectivity. These results are comparable to cutting-edge Si-based photocathodes for CO2 reduction, revealing a vast research potential in employing molecular catalysts for the photoelectrochemical conversion of CO2 to methane.

Stereotactic Ablative Radiotherapy for T1 to T2 Glottic Larynx Cancer: Mature Results From the Phase 2 GLoTtic Larynx-SABR Trial.

PURPOSE: Traditional radiation therapy for early-stage larynx cancer irradiates the whole larynx over 5.5 to 6 weeks. Phase 1 data suggest that stereotactic ablative radiotherapy (SABR) is a viable strategy to reduce the irradiated volume and compress treatment time. This phase 2 study evaluated the efficacy of gLoTtic larynx-SABR in 5 or 16 fractions. METHODS AND MATERIALS: Eligibility required stage 0 to II squamous cell carcinoma of the glottic larynx. The arytenoid cartilage could not be involved beyond the vocal process, and patients smoking more than one pack per day were excluded. The treatment volume consisted of the gross tumor volume, with a 3 mm margin (5 mm craniocaudal) to create the planning target volume. Patients without active smoking and planning target volume <10 cc received 4250 cGy in 5 fractions, twice per week; other patients received 58.08 Gy in 16 daily fractions. The primary endpoint was the 2-year incidence of local failure. RESULTS: Twenty-five patients were accrued to this study, with 21 and 4 treated with 5 and 16 fractions, respectively. The stage distribution was in situ (n = 1, 4%), T1a/b (n = 16/5, 64%/20%), and T2 (n = 3, 12%). The median age was 72 years, with a prior smoking history in 16 (64%) and active smoking in 1 (4%). At a median follow-up for surviving patients of 3.7 years (IQR, 3.1-4.4 years), there have been 2 in-field recurrences (1 in each dose cohort). The cumulative incidences of local failure were 4% (90% CI, 0.8%-20%) and 8% (90% CI, 3%-24%) at 1 and 2 years, respectively. There have been no acute or late grade 3+ toxicities in disease-free patients. The median baseline, 1, 6, 12, and 24 months Voice Handicap Index scores were 57 (IQR, 32-69), 28.5 (8-48), 4 (0-12), 7.5 (0-12), and 5 (0-24), respectively. CONCLUSIONS: Highly conformal stereotactic radiation therapy appears safe and efficacious for early-stage glottic larynx cancer, with encouraging patient-reported outcomes. These results need to be interpreted with caution given the small sample size and large noninferiority margin. Additional follow-up and ultimately comparative studies are necessary to validate this paradigm.

Four-Component Radical 1,2-Selenosulfonylation of Allenes.

Selenosulfones, as pivotal pharmaceutical molecule frameworks, have become a research hotspot in modern organic synthesis due to their vital need for efficient preparation. Herein, we have developed an iron-catalyzed four-component controllable radical tandem reaction of allenes involving cycloketone oxime esters, 1,4-diazabicyclo[2.2.2]octane bis(sulfur dioxide) adduct (DABSO), and diphenyl diselenides for the synthesis of complex selenosulfones. This is the first case of achieving the 1,2-selenosulfonylation of allenes via a radical process, wherein precise control of radical rates and polarity matching enhance high regioselective conversion. The reaction conditions are ecofriendly and mild with step-efficiency by forming two new C-S bonds and one C-Se bond in one pot. Moreover, the 1,2-selenosulfonylation of allenes can be achieved by replacing cycloketone oxime esters with aryldiazonium tetrafluoroborates in this system.

Development and validation of a nomogram for predicting in-hospital mortality of intensive care unit patients with liver cirrhosis.

BACKGROUND: Liver cirrhosis patients admitted to intensive care unit (ICU) have a high mortality rate. AIM: To establish and validate a nomogram for predicting in-hospital mortality of ICU patients with liver cirrhosis. METHODS: We extracted demographic, etiological, vital sign, laboratory test, comorbidity, complication, treatment, and severity score data of liver cirrhosis patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and electronic ICU (eICU) collaborative research database (eICU-CRD). Predictor selection and model building were based on the MIMIC-IV dataset. The variables selected through least absolute shrinkage and selection operator analysis were further screened through multivariate regression analysis to obtain final predictors. The final predictors were included in the multivariate logistic regression model, which was used to construct a nomogram. Finally, we conducted external validation using the eICU-CRD. The area under the receiver operating characteristic curve (AUC), decision curve, and calibration curve were used to assess the efficacy of the models. RESULTS: Risk factors, including the mean respiratory rate, mean systolic blood pressure, mean heart rate, white blood cells, international normalized ratio, total bilirubin, age, invasive ventilation, vasopressor use, maximum stage of acute kidney injury, and sequential organ failure assessment score, were included in the multivariate logistic regression. The model achieved AUCs of 0.864 and 0.808 in the MIMIC-IV and eICU-CRD databases, respectively. The calibration curve also confirmed the predictive ability of the model, while the decision curve confirmed its clinical value. CONCLUSION: The nomogram has high accuracy in predicting in-hospital mortality. Improving the included predictors may help improve the prognosis of patients.

Master Breast Radiation Planning: Simple Guide for Radiation Oncology Residents.

This article focuses on various aspects of breast radiation treatment planning, from simulation to field design. It covers the most common techniques including tangents, mono isocentric, dual isocentric, electron-photon match, and VMAT. This can serve as a guide for radiation oncology residents and medical students to advance their understanding of key aspects of breast radiation treatment and planning processes.

Deep learning based automatic segmentation of the Internal Pudendal Artery in definitive radiotherapy treatment planning of localized prostate cancer.

Background and purpose: Radiation-induced erectile dysfunction (RiED) commonly affects prostate cancer patients, prompting clinical trials across institutions to explore dose-sparing to internal-pudendal-arteries (IPA) for preserving sexual potency. IPA, challenging to segment, isn't conventionally considered an organ-at-risk (OAR). This study proposes a deep learning (DL) auto-segmentation model for IPA, using Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) or CT alone to accommodate varied clinical practices. Materials and methods: A total of 86 patients with CT and MRI images and noisy IPA labels were recruited in this study. We split the data into 42/14/30 for model training, testing, and a clinical observer study, respectively. There were three major innovations in this model: 1) we designed an architecture with squeeze-and-excite blocks and modality attention for effective feature extraction and production of accurate segmentation, 2) a novel loss function was used for training the model effectively with noisy labels, and 3) modality dropout strategy was used for making the model capable of segmentation in the absence of MRI. Results: Test dataset metrics were DSC 61.71 ± 7.7 %, ASD 2.5 ± .87 mm, and HD95 7.0 ± 2.3 mm. AI segmented contours showed dosimetric similarity to expert physician's contours. Observer study indicated higher scores for AI contours (mean = 3.7) compared to inexperienced physicians' contours (mean = 3.1). Inexperienced physicians improved scores to 3.7 when starting with AI contours. Conclusion: The proposed model achieved good quality IPA contours to improve uniformity of segmentation and to facilitate introduction of standardized IPA segmentation into clinical trials and practice.

Clinical manifestations, diagnosis and long-term prognosis of adult autoimmune enteropathy: Experience from Peking Union Medical College Hospital.

BACKGROUND: Autoimmune enteropathy (AIE) is a rare disease whose diagnosis and long-term prognosis remain challenging, especially for adult AIE patients. AIM: To improve overall understanding of this disease's diagnosis and prognosis. METHODS: We retrospectively analyzed the clinical, endoscopic and histopathological characteristics and prognoses of 16 adult AIE patients in our tertiary medical center between 2011 and 2023, whose diagnosis was based on the 2007 diagnostic criteria. RESULTS: Diarrhea in AIE patients was characterized by secretory diarrhea. The common endoscopic manifestations were edema, villous blunting and mucosal hyperemia in the duodenum and ileum. Villous blunting (100%), deep crypt lymphocytic infiltration (67%), apoptotic bodies (50%), and mild intraepithelial lymphocytosis (69%) were observed in the duodenal biopsies. Moreover, there were other remarkable abnormalities, including reduced or absent goblet cells (duodenum 94%, ileum 62%), reduced or absent Paneth cells (duodenum 94%, ileum 69%) and neutrophil infiltration (duodenum 100%, ileum 69%). Our patients also fulfilled the 2018 diagnostic criteria but did not match the 2022 diagnostic criteria due to undetectable anti-enterocyte antibodies. All patients received glucocorticoid therapy as the initial medication, of which 14/16 patients achieved a clinical response in 5 (IQR: 3-20) days. Immunosuppressants were administered to 9 patients with indications of steroid dependence (6/9), steroid refractory status (2/9), or intensified maintenance medication (1/9). During the median of 20.5 months of follow-up, 2 patients died from multiple organ failure, and 1 was diagnosed with non-Hodgkin's lymphoma. The cumulative relapse-free survival rates were 62.5%, 55.6% and 37.0% at 6 months, 12 months and 48 months, respectively. CONCLUSION: Certain histopathological findings, including a decrease or disappearance of goblet and Paneth cells in intestinal biopsies, might be potential diagnostic criteria for adult AIE. The long-term prognosis is still unsatisfactory despite corticosteroid and immunosuppressant medications, which highlights the need for early diagnosis and novel medications.

Multimodal radiotherapy dose prediction using a multi-task deep learning model.

BACKGROUND: In radiation therapy (RT), accelerated partial breast irradiation (APBI) has emerged as an increasingly preferred treatment modality over conventional whole breast irradiation due to its targeted dose delivery and shorter course of treatment. APBI can be delivered through various modalities including Cobalt-60-based systems and linear accelerators with C-arm, O-ring, or robotic arm design. Each modality possesses distinct features, such as beam energy or the degrees of freedom in treatment planning, which influence their respective dose distributions. These modality-specific considerations emphasize the need for a quantitative approach in determining the optimal dose delivery modality on a patient-specific basis. However, manually generating treatment plans for each modality across every patient is time-consuming and clinically impractical. PURPOSE: We aim to develop an efficient and personalized approach for determining the optimal RT modality for APBI by training predictive models using two different deep learning-based convolutional neural networks. The baseline network performs a single-task (ST), predicting dose for a single modality. Our proposed multi-task (MT) network, which is capable of leveraging shared information among different tasks, can concurrently predict dose distributions for various RT modalities. Utilizing patient-specific input data, such as a patient's computed tomography (CT) scan and treatment protocol dosimetric goals, the MT model predicts patient-specific dose distributions across all trained modalities. These dose distributions provide patients and clinicians quantitative insights, facilitating informed and personalized modality comparison prior to treatment planning. METHODS: The dataset, comprising 28 APBI patients and their 92 treatment plans, was partitioned into training, validation, and test subsets. Eight patients were dedicated to the test subset, leaving 68 treatment plans across 20 patients to divide between the training and validation subsets. ST models were trained for each modality, and one MT model was trained to predict doses for all modalities simultaneously. Model performance was evaluated across the test dataset in terms of Mean Absolute Percent Error (MAPE). We conducted statistical analysis of model performance using the two-tailed Wilcoxon signed-rank test. RESULTS: Training times for five ST models ranged from 255 to 430 min per modality, totaling 1925 min, while the MT model required 2384 min. MT model prediction required an average of 1.82 s per patient, compared to ST model predictions at 0.93 s per modality. The MT model yielded MAPE of 1.1033 ± 0.3627% as opposed to the collective MAPE of 1.2386 ± 0.3872% from ST models, and the differences were statistically significant (p = 0.0003, 95% confidence interval = [-0.0865, -0.0712]). CONCLUSION: Our study highlights the potential benefits of a MT learning framework in predicting RT dose distributions across various modalities without notable compromises. This MT architecture approach offers several advantages, such as flexibility, scalability, and streamlined model management, making it an appealing solution for clinical deployment. With such a MT model, patients can make more informed treatment decisions, physicians gain more quantitative insight for pre-treatment decision-making, and clinics can better optimize resource allocation. With our proposed goal array and MT framework, we aim to expand this work to a site-agnostic dose prediction model, enhancing its generalizability and applicability.

Beyond conventional bounds: Surpassing system limits for stereotactic ablative (SAbR) lung radiotherapy using CBCT-based adaptive planning system.

PURPOSE: Online adaptive radiotherapy relies on a high degree of automation to enable rapid planning procedures. The Varian Ethos intelligent optimization engine (IOE) was originally designed for conventional treatments so it is crucial to provide clear guidance for lung SAbR plans. This study investigates using the Ethos IOE together with adaptive-specific optimization tuning structures we designed and templated within Ethos to mitigate inter-planner variability in meeting RTOG metrics for both online-adaptive and offline SAbR plans. METHODS: We developed a planning strategy to automate the generation of tuning structures and optimization. This was validated by retrospective analysis of 35 lung SAbR cases (total 105 fractions) treated on Ethos. The effectiveness of our planning strategy was evaluated by comparing plan quality with-and-without auto-generated tuning structures. Internal target volume (ITV) contour was compared between that drawn from CT simulation and from cone-beam CT (CBCT) at time of treatment to verify CBCT image quality and treatment effectiveness. Planning strategy robustness for lung SAbR was quantified by frequency of plans meeting reference plan RTOG constraints. RESULTS: Our planning strategy creates a gradient within the ITV with maximum dose in the core and improves intermediate dose conformality on average by 2%. ITV size showed no significant difference between those contoured from CT simulation and first fraction, and also trended towards decreasing over course of treatment. Compared to non-adaptive plans, adaptive plans better meet reference plan goals (37% vs. 100% PTV coverage compliance, for scheduled and adapted plans) while improving plan quality (improved GI (gradient index) by 3.8%, CI (conformity index) by 1.7%). CONCLUSION: We developed a robust and readily shareable planning strategy for the treatment of adaptive lung SAbR on the Ethos system. We validated that automatic online plan re-optimization along with the formulated adaptive tuning structures can ensure consistent plan quality. With the proposed planning strategy, highly ablative treatments are feasible on Ethos.

Adapt-On-Demand: A Novel Strategy for Personalized Adaptive Radiation Therapy for Locally Advanced Lung Cancer.

PURPOSE: Real-time adaptation of thoracic radiation plans is compelling because offline adaptive experiences show that tumor volumes and lung anatomy can change during therapy. We present and analyze a novel adaptive-on-demand (AOD) workflow combining online adaptive radiation therapy (o-ART) on the ETHOS system with image guided radiation therapy delivery on a Halcyon unit for conventional fractionated radiation therapy of locally advanced lung cancer (LALC). METHODS AND MATERIALS: We analyzed 26 patients with LALC treated with the AOD workflow, adapting weekly. We timed segments of the workflow to evaluate efficiency in a real-world clinic. Target coverage and organ at risk (OAR) doses were compared between adaptive plans (ADP) and nonadaptive scheduled plans (SCH). Planning robustness was evaluated by the frequency of preplanning goals achieved in ADP plans, stratified by tumor volume change. RESULTS: The AOD workflow was achievable within 30 minutes for most radiation fractions. Over the course of therapy, we observed an average 26.6% ± 23.3% reduction in internal target volume (ITV). Despite these changes, with o-ART, ITV and planning target volume (PTV) coverage (V100%) was 99.2% and 93.9% for all members of the cohort, respectively. This represented a 2.9% and 6.8% improvement over nonadaptive plans (P < .05), respectively. For tumors that grew >10%, V100% was 93.1% for o-ART and 76.4% for nonadaptive plans, representing a median 17.2% improvement in the PTV coverage (P < .05). In these plans, critical OAR constraints were met 94.1% of the time, whereas in nonadaptive plans, this figure was 81.9%. This represented reductions of 1.32 Gy, 1.34 Gy, or 1.75 Gy in the heart, esophagus, and lung, respectively. The effect was larger when tumors had shrunk more than 10%. Regardless of tumor volume alterations, the PTV/ITV coverage was achieved for all adaptive plans. Exceptional cases, where dose constraints were not met, were due to large initial tumor volumes or tumor growth. CONCLUSIONS: The AOD workflow is efficient and robust in responding to anatomic changes in LALC patients, providing dosimetric advantages over standard therapy. Weekly adaptation was adequate to keep pace with changes. This approach is a feasible alternative to conventional offline replanning workflows for managing anatomy changes in LALC radiation therapy.

Rational design of a near-infrared fluorescent probe for monitoring butyrylcholinesterase activity and its application in development of inhibitors.

Butyrylcholinesterase (BChE) is widely expressed in multiple tissues and has a vital role in several key human disorders, such as Alzheimer's disease and tumorigenesis. However, the role of BChE in human disorders has not been investigated. Thus, to quantitatively detect and visualize dynamical variations in BChE activity is essential for exploring the biological roles of BChE in the progression of a number of human disorders. Herein, based on the substrate characteristics of BChE, we customized and synthesized three near-infrared (NIR) fluorescent probe substrates with cyanine-skeleton, and finally selected a NIR fluorescence probe substrate named CYBA. The CYBA demonstrated a significant increase in fluorescence when interacting with BChE, but mainly avoided AChE. Upon the addition of BChE, CYBA could be specifically hydrolyzed to TBO, resulting in a significant NIR fluorescence signal enhancement at 710 nm. Systematic evaluation revealed that CYBA exhibited exceptional chemical stability in complex biosamples and possessed remarkable selectivity and sensitivity towards BChE. Moreover, CYBA was successfully applied for real-time imaging of endogenous BChE activity in two types of nerve-related living cells. Additionally, CYBA demonstrated exceptional stability in the detection of complex biological samples in plasma recovery studies (97.51%-104.01%). Furthermore, CYBA was used to construct a high-throughput screening (HTS) method for BChE inhibitors using human plasma as the enzyme source. We evaluated inhibitory effects of a series of natural products and four flavonoids were identified as potent inhibitors of BChE. Collectively, CYBA can serve as a practical tool to track the changes of BChE activity in complicated biological environments due to its excellent capabilities.

Reassessing clinical presentations of emamectin benzoate poisoning: A comprehensive study.

BACKGROUND: The mechanism of emamectin benzoate (EMB-a macrocyclic lactone insecticide like abamectin) action involves the disruption of glutamate-gated chloride channels and GABA receptors in insects, leading to paralysis and death. EMB overdose can breach the blood-brain barrier, resulting in severe poisoning and altered consciousness. AIM: Review EMB poisoning presentations in patients and reevaluate clinical manifestations. MATERIALS AND METHODS: This retrospective study reviewed (August 31, 2008-August 31, 2023) medical university hospital records. We analyzed symptoms, patient characteristics, vital signs, Glasgow Coma Scale scores, laboratory findings, and outcomes. RESULTS: Ten patients (males: 6, females: 4, median age = 64.5 years) experienced EMB poisoning. Common symptoms included sore throat, gastrointestinal distress, dyspnea, and altered consciousness; two patients showed laryngeal corrosive injuries. Management involved activated charcoal administration, gastric lavage, and intensive care unit admission. DISCUSSION: Sore throat and corrosive injuries were distinctive presentations of EMB poisoning, warranting vigilance. Potential mechanisms of corrosive injury include skin and eye irritation effects of EMB, the solvents of which might exert corrosive action. CONCLUSION: EMB poisoning manifests as diverse symptoms, including sore throat, gastrointestinal symptoms, central nervous system depression, and potential aspiration pneumonia. Recognizing and promptly managing EMB poisoning are crucial for enhancing patient outcomes and minimizing complications.

Iron-Catalyzed Allylic C(sp3)-H Silylation: Spin-Crossover-Efficiency-Determined Chemoselectivity.

The nuanced role of spin effects remains a critical gap in designing proficient open-shell catalysts. This study elucidates an iron-catalyzed allylic C(sp3)-H silylation/alkyne hydrosilylation reaction, in which the spin state of the open-shell iron catalyst dictates the reaction kinetics and pathway. Specifically, spin crossover led to alkyne hydrosilylation, whereas spin conservation resulted in a novel allylic C(sp3)-H silylation reaction. This chemoselectivity, governed by the spin-crossover efficiency, reveals an unexpected dimension in spin effects and a first in the realm of transition-metal-catalyzed in situ silylation of allylic C(sp3)-H bonds, which had been previously inhibited by the heightened reactivity of alkenes in hydrosilylation reactions. Furthermore, this spin crossover can either accelerate or hinder the reaction at different stages within a single catalytic reaction, a phenomenon scarcely documented. Moreover, we identify a substrate-assisted C-H activation mechanism, a departure from known ligand-assisted processes, offering a fresh perspective on C-H activation strategies.

In silico evaluation and feasibility of near margin-less head and neck daily adaptive radiotherapy.

OBJECTIVE: We explore the potential dosimetric benefits of reducing treatment volumes through daily adaptive radiation therapy for head and neck cancer (HNC) patients using the Ethos system/Intelligent Optimizer Engine (IOE). We hypothesize reducing treatment volumes afforded by daily adaption will significantly reduce the dose to adjacent organs at risk. We also explore the capability of the Ethos IOE to accommodate this highly conformal approach in HNC radiation therapy. METHODS: Ten HNC patients from a phase II trial were chosen, and their cone-beam CT (CBCT) scans were uploaded to the adaptive RT (ART) emulator. A new initial reference plan was generated using both a 1 mm and 5 mm planning target volume (PTV) expansion. Daily adaptive ART plans (1 mm) were simulated from the clinical CBCT taken every fifth fraction. Additionally, using physician-modified ART contours the larger 5 mm plan was recalculated on this recontoured on daily anatomy. Changes in target and OAR contours were measured using Dice coefficients as a surrogate of clinician effort. PTV coverage and organ-at-risk (OAR) doses were statistically compared, and the robustness of each ART plan was evaluated at fractions 5 and 35 to observe if OAR doses were within 3 Gy of pre-plan. RESULTS: This study involved six patients with oropharynx and four with larynx cancer, totaling 70 adaptive fractions. The primary and nodal gross tumor volumes (GTV) required the most adjustments, with median Dice scores of 0.88 (range: 0.80-0.93) and 0.83 (range: 0.66-0.91), respectively. For the 5th and 35th fraction plans, 80 % of structures met robustness criteria (quartile 1-3: 67-100 % and 70-90 %). Adaptive planning improved median PTV V100% coverage for doses of 70 Gy (96 % vs. 95.6 %), 66.5 Gy (98.5 % vs. 76.5 %), and 63 Gy (98.9 % vs. 74.9 %) (p < 0.03). Implementing ART with total volume reduction yielded median dose reductions of 7-12 Gy to key organs-at-risk (OARs) like submandibular glands, parotids, oral cavity, and constrictors (p < 0.05). CONCLUSIONS: The IOE enables feasible daily ART treatments with reduced margins while enhancing target coverage and reducing OAR doses for HNC patients. A phase II trial recently finished accrual and forthcoming analysis will determine if these dosimetric improvements correlate with improved patient-reported outcomes.

A simple, organized web-based system improved the transfer efficiency and patient outcomes for endovascular thrombectomy in regional stroke network.

BACKGROUND: Endovascular thrombectomy (EVT) is a time-sensitive treatment for acute ischemic stroke with large vessel occlusion. To optimize transfer efficiency, a web-based platform was introduced in the Tainan Stroke Network (TSN). We assessed its application and effectiveness in regional stroke care. METHOD: This new web-based platform containing a questionnaire-style interface was introduced on October 1, 2021. To assess the transfer efficiency and patient outcomes, acute stroke patients transferred from PSCs to CSC for EVT from April 01, 2020, to December 30, 2022, were enrolled. The patients were classified into the traditional transferal pathway (TTP) group and the new transferal pathway (NTP) group depending on mode of transfer. Patient characteristics, time segments after stroke onset and outcome were compared between groups. RESULT: A total of 104 patients were enrolled, with 77 in the TTP group and 27 in the NTP group. Compared to the TTP group, the NTP group had a significantly shorter onset-to-CSC door time (TTP vs. NTP: 267 vs. 198 min; p = 0.041) and a higher EVT rate (TTP vs. NTP: 18.2% vs. 48.1%, p = 0.002). Among EVT patients, those in the NTP group had a significantly shorter CSC door-to-puncture time (TTP vs. NTP: 131.5 vs. 110 min; p = 0.029). The NTP group had a higher rate of good functional outcomes at 3 months (TTP vs. NTP: 21% vs. 61.5%; p = 0.034). CONCLUSION: This new web-based EVT transfer system provides notable improvements in clinical outcomes, transfer efficiency, and EVT execution for potential EVT candidates without markedly changing the regional stroke care paradigm.