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Xiaoyi Ning,1,* Yun Kuang,1,* Shuwei Zhao,2 Wenjing Hou,2 Guoping Yang,1,3,4 Xuerui Zhu,5 Ruiling Liu,6 Jie Huang1 1Center of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China; 2Center of Clinical Medical Trial, Medical University General Hospital, Tianjin, People’s Republic of China; 3Research Center for Drug Clinical Evaluation of Central South University, Changsha, Hunan, People’s Republic of China; 4Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China; 5Department of clinical research and development, Zhejiang Wolwo Biopharmaceuticals, Deqing, Zhejiang, People’s Republic of China; 6Department of Allergy, Medical University General Hospital, Tianjin, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ruiling LiuDepartment of Allergy, Medical University General Hospital, Tianjin 300052, People’s Republic of ChinaTel/Fax +8618622930966Email lrly05@163.comJie HuangCenter for Clinical Pharmacology, The Third Xiangya Hospital, Central South University, 138 TongZiPo Road, Changsha, Hunan 410013, People’s Republic of ChinaTel/Fax +8615116469024Email cellahuang1988@163.comBackground: Eight extracts from common native allergens, Artemisia annua pollen, Platanus pollen, Humulus pollen, Betula platyphylla pollen, Ambrosia artemisiifolia pollen, Blattella germanica, cat dander and dog dander were developed for skin prick test (SPT). Since standardization and composition alone cannot guarantee that the allergen extracts are within the concentration range that give the best chance of a true diagnosis, it is necessary to explore the optimal diagnostic concentration (ODC) of allergens in SPT.Objective: To identify the optimal diagnostic concentration of eight allergen extracts in SPT and assess the safety of simultaneous administration.Patients and Methods: Patients with a history of allergic disease were enrolled in this two-part open-label, parallel study. In Study 1, 92 patients were enrolled into eight groups according to their disease-causing allergens and were given three increasing concentrations of the corresponding allergen. In Study 2, 20 patients were divided into two concentration groups and were given all of the eight allergens. Safety and sensitivity were evaluated to determine the optimal diagnostic concentration.Results: In Study 1, the sensitivity of seven allergen extracts was > 80% at middle and high concentrations, except for Ambrosia artemisiifolia pollen. The optimal diagnostic concentration (in DU/mL) for eight allergens was 33,333, 12,000, 8667, 50,000, 40,000, 3333, 7000, and 5000. In Study 2, the prevalence of adverse events in the two groups was 70% and 80%, respectively. A total of 10 wheals of 8 patients did not subside < 24 h after SPTs.Conclusion: The eight allergens showed high sensitivity and safety at a certain concentration, which was defined as optimal diagnostic concentration. The results support further clinical research of investigated allergens and our study offers a scheme to determine the ODC of allergens in SPT.Keywords: skin prick test, allergen, optimal diagnostic concentration

Cheng-hao Qu,1,2 Tong Li,1,2 Zhan-peng Tang,1,2 Xi-Rui Zhu,1,2 Jing-yi Han,1,2 Hui Tian2 1Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, People’s Republic of China; 2Department of Thoracic Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, People’s Republic of ChinaCorrespondence: Hui TianDepartment of Thoracic Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, People’s Republic of ChinaTel +86 18560080016Email tianhuiql@126.comPurpose: Emerging studies have revealed that platelets are involved in tumor metastasis in lung adenocarcinoma (ADC). The solid pathological subtype of lung ADC is associated with metastasis, recurrence, and poor prognosis. However, there is no study exploring the relationship between platelets and different lung pathological subtypes.Patients and Methods: The association between platelet counts and lymph node metastasis was analyzed in 852 patients with lung ADC who underwent surgery and lymph node dissection. Multivariate logistic analysis was conducted to identify the risk factors of lymph node metastasis. Then, lymph node metastasis and other factors were analyzed to determine their correlation with platelet count and histological subtype.Results: We found that the platelet count was associated with lymph node metastasis (P = 0.01) in multivariable analysis, independent of tumor size, predominant subtype, visceral pleural invasion, and microvessel invasion. In patients with a platelet count ≥ 300 × 109/L, the rate of lymph node metastasis was 38.5%, almost twice as high as that in patients with a platelet count < 300 × 109/L (23.2%). Additionally, elevated platelet counts, even those within the normal range, were significantly associated with a higher rate of lymph node metastasis. The mean platelet count in patients with solid-predominant histology (269.70 ± 69.38 × 109/L) was significantly higher than that in patients with other histologies (P < 0.001).Conclusion: Elevated platelet counts are significantly associated with a higher rate of lymph node metastasis, even if the platelet counts are within the reference range. Platelet counts were significantly higher in patients with solid-predominant histology than in patients with other histologies. In addition, VEGF-C may play an important role in lymphatic metastasis in patients with lung ADC. We hypothesize that antiplatelet therapy may reduce lymph node metastasis in lung ADC patients.Keywords: lung adenocarcinoma, platelets, lymph node, solid-predominant, pathological subtype

Heavy-ion collisions at very high colliding energies are expected to produce a quark-gluon plasma (QGP) at the highest temperature obtainable in a laboratory setting. Experimental studies of these reactions can provide an unprecedented range of information on properties of the QGP at high temperatures. We report theoretical investigations of the physics perspectives of heavy-ion collisions at a future high-energy collider. These include initial parton production, collective expansion of the dense medium, jet quenching, heavy-quark transport, dissociation and regeneration of quarkonia, photon and dilepton production. We illustrate the potential of future experimental studies of the initial particle production and formation of QGP at the highest temperature to provide constraints on properties of strongly interaction matter.

Objective . Previous methods for robustness evaluation rely on dose calculation for a number of uncertainty scenarios, which either fails to provide statistical meaning when the number is too small (e.g., ∼8) or becomes unfeasible in daily clinical practice when the number is sufficiently large (e.g., >100). Our proposed deep learning (DL)-based method addressed this issue by avoiding the intermediate dose calculation step and instead directly predicting the percentile dose distribution from the nominal dose distribution using a DL model. In this study, we sought to validate this DL-based statistical robustness evaluation method for efficient and accurate robustness quantification in head and neck (H&N) intensity-modulated proton therapy with diverse beam configurations and multifield optimization. Approach . A dense, dilated 3D U-net was trained to predict the 5th and 95th percentile dose distributions of uncertainty scenarios using the nominal dose and planning CT images. The data set comprised proton therapy plans for 582 H&N cancer patients. Ground truth percentile values were estimated for each patient through 600 dose recalculations, representing randomly sampled uncertainty scenarios. The comprehensive comparisons of different models were conducted for H&N cancer patients, considering those with and without a beam mask and diverse beam configurations, including varying beam angles, couch angles, and beam numbers. The performance of our model trained based on a mixture of patients with H&N and prostate cancer was also assessed in contrast with models trained based on data specific for patients with cancer at either site. Results . The DL-based model's predictions of percentile dose distributions exhibited excellent agreement with the ground truth dose distributions. The average gamma index with 2 mm / 2%, consistently exceeded 97% for both 5th and 95th percentile dose volumes. Mean dose-volume histogram error analysis revealed that predictions from the combined training set yielded mean errors and standard deviations that were generally similar to those in the specific patient training data sets. Significance . Our proposed DL-based method for evaluation of the robustness of proton therapy plans provides precise, rapid predictions of percentile dose for a given confidence level regardless of the beam arrangement and cancer site. This versatility positions our model as a valuable tool for evaluating the robustness of proton therapy across various cancer sites., (Creative Commons Attribution license.)

Objective: Diabetic retinopathy (DR) is the most common cause of adult blindness in China. Screening of DR is important for early detection, prevention, and treatment. However, there is still controversy in the research on the prevalence and risk factors of DR in China. This study was designed to evaluate the prevalence of DR and related risk factors in patients with type 2 diabetes mellitus in Beijing City. Methods: A cross-sectional survey was conducted in in Dongcheng District and Tongzhou District, Beijing City. Patients with type 2 diabetes aged 18-80 years were selected from four communities, and all subjects underwent questionnaires, physical examinations, laboratory examinations and fundus photography. The logistic regression model was used to analyze the associated factors of DR. Results: A total of 1 531 subjects were included, with the median age of 66 years old and the average age of (65.6±7.4) years old, and the glycosylated hemoglobin level in the subjects was 7.2%±1.3%, and the glycosylated hemoglobin compliance rate was 56.0%(857/1 531). A total of 254 patients with diabetic retinopathy were detected, and the prevalence of DR was 16.6%(254/1 531). Among them, there were 218 cases of non-proliferative diabetic retinopathy and 36 cases of proliferative diabetic retinopathy. Compared with the non-DR group, there were statistically significant differences in fasting blood glucose ( Z= -3.74, P <0.001), glycosylated hemoglobin( Z =-10.664, P <0.001), urinary microalbumin excretion rate( Z =-7.767, P <0.001), low-density lipoprotein cholesterol( Z =-2.589, P =0.01), and duration of diabetes( Z =-10.189, P <0.001) between the DR group and the non-DR group. Multivariate regression analysis showed that the duration of diabetes ( OR =1.08, 95% CI : 1.06-1.10, P <0.001), glycosylated hemoglobin ( OR =1.38, 95% CI : 1.23-1.55, P <0.001), and FPG ( OR =1.11, 95% CI : 1.03-1.19, P =0.008) were associated factors for DR. Conclusion: In this study, the prevalence of DR in 4 communities of type 2 diabetes in Beijing City was 16.6%. Besides, this study further confirmed that the duration of diabetes, fasting blood glucose levels, and glycosylated hemoglobin are associated factors for DR in patients with type 2 diabetes.

Zinc is a significant source of heavy metal pollution that poses risks to both human health and biodiversity. Excessive concentrations of zinc can hinder the growth and development of insects and trigger cell death through oxidative damage. The midgut is the main organ affected by exposure to heavy metals. The silkworm, a prominent insect species belonging to the Lepidoptera class and widely used in China, serves as a model for studying the genetic response to heavy metal stress. In this study, high-throughput sequencing technology was employed to investigate detoxification-related genes in the midgut that are induced by zinc exposure. A total of 11,320 unigenes and 14,723 transcripts were identified, with 553 differentially expressed genes (DEGs) detected, among which 394 were up-regulated and 159 were down-regulated. The Gene Ontology (GO) analysis revealed that 452 DEGs were involved in 18 biological process subclasses, 14 cellular component subclasses and 8 molecular functional subclasses. Furthermore, the KEGG analysis demonstrated enrichment in pathways such as Protein digestion, absorption and Lysosome. Validation of the expression levels of 9 detoxification-related DEGs through qRT-PCR confirmed the accuracy of the RNA-seq results. This study not only contributes new insights into the detoxification mechanisms mechanism of silkworms against zinc contamination, but also serves as a foundation basis for understanding the molecular detoxification processes in lepidopteran insects., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as no potential conflict of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objective. Develop a prototype on-line positron emission tomography (PET) scanner and evaluate its capability of on-line imaging and intra-fractionated proton-induced radioactivity range measurement. Approach. Each detector consists of 32 × 32 array of 2 × 2 × 30 mm 3 Lutetium-Yttrium Oxyorthosilicate scintillators with single-scintillator-end readout through a 20 × 20 array of 3 × 3 mm 2 Silicon Photomultipliers. The PET can be configurated with a full-ring of 20 detectors for conventional PET imaging or a partial-ring of 18 detectors for on-line imaging and range measurement. All detector-level readout and processing electronics are attached to the backside of the system gantry and their output signals are transferred to a field-programable-gate-array based system electronics and data acquisition that can be placed 2 m away from the gantry. The PET imaging performance and radioactivity range measurement capability were evaluated by both the offline study that placed a radioactive source with known intensity and distribution within a phantom and the online study that irradiated a phantom with proton beams under different radiation and imaging conditions. Main results. The PET has 32 cm diameter and 6.5 cm axial length field-of-view (FOV), ∼2.3-5.0 mm spatial resolution within FOV, 3% sensitivity at the FOV center, 18%-30% energy resolution, and ∼9 ns coincidence time resolution. The offline study shows the PET can determine the shift of distal falloff edge position of a known radioactivity distribution with the accuracy of 0.3 ± 0.3 mm even without attenuation and scatter corrections, and online study shows the PET can measure the shift of proton-induced positron radioactive range with the accuracy of 0.6 ± 0.3 mm from the data acquired with a short-acquisition (60 s) and low-dose (5 MU) proton radiation to a human head phantom. Significance. This study demonstrated the capability of intra-fractionated PET imaging and radioactivity range measurement and will enable the investigation on the feasibility of intra-fractionated, range-shift compensated adaptive proton therapy., (Creative Commons Attribution license.)

We previously proposed range-guided adaptive proton therapy (RGAPT) that uses mid-range treatment beams as probing beams and intra-fractionated range measurements for online adaptation. In this work, we demonstrated experimental verification and reported the dosimetric accuracy for RGAPT. A STEEV phantom was used for the experiments, and a 3 × 3 × 3 cm 3 cube inside the phantom was assigned to be the treatment target. We simulated three online range shift scenarios: reference, overshoot, and undershoot, by placing upstream Lucite sheets, 4, 0, and 8 that corresponded to changes of 0, 6.8, and -6.8 mm, respectively, in water-equivalent path length. The reference treatment plan was to deliver single-field uniform target doses in pencil beam scanning mode and generated on the Eclipse treatment planning system. Different numbers of mid-range layers, including single, three, and five layers, were selected as probing beams to evaluate beam range (BR) measurement accuracy in positron emission tomography (PET). Online plans were modified to adapt to BR shifts and compensate for probing beam doses. In contrast, non-adaptive plans were also delivered and compared to adaptive plans by film measurements. The mid-range probing beams of three (5.55MU) and five layers (8.71MU) yielded accurate range shift measurements in 60 s of PET acquisition with uncertainty of 0.5 mm while the single-layer probing (1.65MU) was not sufficient for measurements. The adaptive plans achieved an average gamma (2%/2 mm) passing rate of 95%. In contrast, the non-adaptive plans only had an average passing rate of 69%. RGAPT planning and delivery are feasible and verified by the experiments. The probing beam delivery, range measurements, and adaptive planning and delivery added a small increase in treatment delivery workflow time but resulted in substantial dose improvement. The three-layer mid-range probing was most suitable considering the balance of high range measurement accuracy and the low number of probing beam layers., (Creative Commons Attribution license.)

Patients with EGFR-mutated non-small cell lung cancer (NSCLC) respond poorly to immune checkpoint inhibitors (ICIs). It has been reported that the number of CD8 + T cells is reduced in EGFR-mutated NSCLC. However, the extent of heterogeneity and effector function of distinct populations of CD8 + T cells has not been investigated intensively. In addition, studies investigating whether a combination of radiotherapy and ICIs can improve the efficacy of ICIs in EGFR-mutated lung cancer are lacking. Single-cell RNA sequencing (scRNA-seq) was used to investigate the heterogeneity of CD8 + T cell populations in EGFR-mutated NSCLC. The STING pathway was explored after hypofractionated radiation of EGFR-mutated and wild-type cells. Mice bearing LLC-19del and LLC-EGFR tumors were treated with radiotherapy plus anti-PD-L1. The scRNA-seq data showed the percentage of progenitor exhausted CD8 + T cells was lower in EGFR-mutated NSCLC. In addition, CD8 + T cells in EGFR-mutated NSCLC were enriched in oxidative phosphorylation. In EGFR-mutated and wild-type cells, 8 Gy × 3 increased the expression of chemokines that recruit T cells and activate the cGAS-STING pathway. In the LLC-19del and LLC-EGFR mouse model, the combination of radiation and anti-PD-L1 significantly inhibited the growth of abscopal tumors. The enhanced abscopal effect was associated with systemic CD8 + T cell infiltration. This study provided an intensive understanding of the heterogeneity and effector functions of CD8 + T cells in EGFR-mutated NSCLC. We showed that the combination of hypofractionated radiation and anti-PD-L1 significantly enhanced the abscopal responses in both EGFR-mutated and wild-type lung cancer by activating CD8 + T cells in mice., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Multiview attributed graph clustering is an important approach to partition multiview data based on the attribute characteristics and adjacent matrices from different views. Some attempts have been made in using graph neural network (GNN), which have achieved promising clustering performance. Despite this, few of them pay attention to the inherent specific information embedded in multiple views. Meanwhile, they are incapable of recovering the latent high-level representation from the low-level ones, greatly limiting the downstream clustering performance. To fill these gaps, a novel dual information enhanced multiview attributed graph clustering (DIAGC) method is proposed in this article. Specifically, the proposed method introduces the specific information reconstruction (SIR) module to disentangle the explorations of the consensus and specific information from multiple views, which enables graph convolutional network (GCN) to capture the more essential low-level representations. Besides, the contrastive learning (CL) module maximizes the agreement between the latent high-level representation and low-level ones and enables the high-level representation to satisfy the desired clustering structure with the help of the self-supervised clustering (SC) module. Extensive experiments on several real-world benchmarks demonstrate the effectiveness of the proposed DIAGC method compared with the state-of-the-art baselines.

Currently, the relationship between household size and incident dementia, along with the underlying neurobiological mechanisms, remains unclear. This prospective cohort study was based on UK Biobank participants aged ≥ 50 years without a history of dementia. The linear and non-linear longitudinal association was assessed using Cox proportional hazards regression and restricted cubic spline models. Additionally, the potential mechanisms driven by brain structures were investigated by linear regression models. We included 275,629 participants (mean age at baseline 60.45 years [SD 5.39]). Over a mean follow-up of 9.5 years, 6031 individuals developed all-cause dementia. Multivariable analyses revealed that smaller household size was associated with an increased risk of all-cause dementia (HR, 1.06; 95% CI 1.02-1.09), vascular dementia (HR, 1.08; 95% CI 1.01-1.15), and non-Alzheimer's disease non-vascular dementia (HR, 1.09; 95% CI 1.03-1.14). No significant association was observed for Alzheimer's disease. Restricted cubic splines demonstrated a reversed J-shaped relationship between household size and all-cause and cause-specific dementia. Additionally, substantial associations existed between household size and brain structures. Our findings suggest that small household size is a risk factor for dementia. Additionally, brain structural differences related to household size support these associations. Household size may thus be a potential modifiable risk factor for dementia., (© 2024. The Author(s).)

Multiview attribute graph clustering aims to cluster nodes into disjoint categories by taking advantage of the multiview topological structures and the node attribute values. However, the existing works fail to explicitly discover the inherent relationships in multiview topological graph matrices while considering different properties between the graphs. Besides, they cannot well handle the sparse structure of some graphs in the learning procedure of graph embeddings. Therefore, in this article, we propose a novel contrastive multiview attribute graph clustering (CMAGC) with adaptive encoders method. Within this framework, the adaptive encoders concerning different properties of distinct topological graphs are chosen to integrate multiview attribute graph information by checking whether there exists high-order neighbor information or not. Meanwhile, the number of layers of the GCN encoders is selected according to the prior knowledge related to the characteristics of different topological graphs. In particular, the feature-level and cluster-level contrastive learning are conducted on the multiview soft assignment representations, where the union of the first-order neighbors from the corresponding graph pairs is regarded as the positive pairs for data augmentation and the sparse neighbor information problem in some graphs can be well dealt with. To the best of our knowledge, it is the first time to explicitly deal with the inherent relationships from the interview and intraview perspectives. Extensive experiments are conducted on several datasets to verify the superiority of the proposed CMAGC method compared with the state-of-the-art methods.

Introduction: Adjuvant immunotherapy (IO) following concurrent chemotherapy and photon radiation therapy confers an overall survival (OS) benefit for patients with inoperable locally advanced non-small cell lung carcinoma (LA-NSCLC); however, outcomes of adjuvant IO after concurrent chemotherapy with proton beam therapy (CPBT) are unknown. We investigated OS and toxicity after CPBT with adjuvant IO versus CPBT alone for inoperable LA-NSCLC., Materials and Methods: We analyzed 354 patients with LA-NSCLC who were prospectively treated with CPBT with or without adjuvant IO from 2009 to 2021. Optimal variable ratio propensity score matching (PSM) matched CPBT with CPBT + IO patients. Survival was estimated with the Kaplan-Meier method and compared with log-rank tests. Multivariable Cox proportional hazards regression evaluated the effect of IO on disease outcomes., Results: Median age was 70 years; 71 (20%) received CPBT + IO and 283 (80%) received CPBT only. After PSM, 71 CPBT patients were matched with 71 CPBT + IO patients. Three-year survival rates for CPBT + IO vs CPBT were: OS 67% vs 30% (P < 0.001) and PFS 59% vs 35% (P = 0.017). Three-year LRFS (P = 0.137) and DMFS (P = 0.086) did not differ. Receipt of adjuvant IO was a strong predictor of OS (HR 0.40, P = 0.001) and PFS (HR 0.56, P = 0.030), but not LRFS (HR 0.61, P = 0.121) or DMFS (HR 0.61, P = 0.136). There was an increased incidence of grade ≥3 esophagitis in the CPBT-only group (6% CPBT + IO vs 17% CPBT, P = 0.037)., Conclusion: This study, one of the first to investigate CPBT followed by IO for inoperable LA-NSCLC, showed that IO conferred survival benefits with no increased rates of toxicity., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Current fiducial markers (FMs) in external-beam radiotherapy (EBRT) for prostate cancer (PCa) cannot be positively visualized on magnetic resonance imaging (MRI) and create dose perturbation and significant imaging artifacts on computed tomography (CT) and MRI. We report our initial experience with clinical imaging of a novel multimodality FM, NOVA., Methods: We tested Gold Anchor [G-FM], BiomarC [carbon, C-FM], and NOVA FMs in phantoms imaged with kilovoltage (kV) X-rays, transrectal ultrasound (TRUS), CT, and MRI. Artifacts of the FMs on CT were quantified by the relative streak artifacts level (rSAL) metric. Proton dose perturbations (PDPs) were measured with Gafchromic EBT3 film, with FMs oriented either perpendicular to or parallel with the beam axis. We also tested the performance of NOVA-FMs in a patient., Results: NOVA-FMs were positively visualized on all 4 imaging modalities tested. The rSAL on CT was 0.750 ± 0.335 for 2-mm reconstructed slices. In F-tests, PDP was associated with marker type and depth of measurement ( p < 10 -6 ); at 5-mm depth, PDP was significantly greater for the G-FM (12.9%, p = 10 -6 ) and C-FM (6.0%, p = 0.011) than NOVA (4.5%). EBRT planning with MRI/CT image co-registration and daily alignments using NOVA-FMs in a patient was feasible and reproducible., Conclusions: NOVA-FMs were positively visible and produced less PDP than G-FMs or C-FMs. NOVA-FMs facilitated MRI/CT fusion and identification of regions of interest.

The recently observed FLASH effect related to high doses delivered with high rates has the potential to revolutionize radiation cancer therapy if promising results are confirmed and an underlying mechanism understood. Comprehensive measurements are essential to elucidate the phenomenon. We report the first-ever demonstration of measurements of successive in-spill and post-spill emissions of gammas arising from irradiations by a FLASH proton beam. A small positron emission tomography (PET) system was exposed in an ocular beam of the Proton Therapy Center at MD Anderson Cancer Center to view phantoms irradiated by 3.5 × 10 10 protons with a kinetic energy of 75.8 MeV delivered in 101.5 ms-long spills yielding a dose rate of 164 Gy s -1 . Most in-spill events were due to prompt gammas. Reconstructed post-spill tomographic events, recorded for up to 20 min, yielded quantitative imaging and dosimetric information. These findings open a new and novel modality for imaging and monitoring of FLASH proton therapy exploiting in-spill prompt gamma imaging followed by post-spill PET imaging., (Creative Commons Attribution license.)

Excessive fructose consumption increases hepatic de novo lipogenesis, resulting in cellular stress, inflammation and liver injury. Nogo-B is a resident protein of the endoplasmic reticulum that regulates its structure and function. Hepatic Nogo-B is a key protein in glycolipid metabolism, and inhibition of Nogo-B has protective effects against metabolic syndrome, thus small molecules that inhibit Nogo-B have therapeutic benefits for glycolipid metabolism disorders. In this study we tested 14 flavones/isoflavones in hepatocytes using dual luciferase reporter system based on the Nogo-B transcriptional response system, and found that 6-methyl flavone (6-MF) exerted the strongest inhibition on Nogo-B expression in hepatocytes with an IC 50 value of 15.85 μM. Administration of 6-MF (50 mg· kg -1  ·d -1 , i.g. for 3 weeks) significantly improved insulin resistance along with ameliorated liver injury and hypertriglyceridemia in high fructose diet-fed mice. In HepG2 cells cultured in a media containing an FA-fructose mixture, 6-MF (15 μM) significantly inhibited lipid synthesis, oxidative stress and inflammatory responses. Furthermore, we revealed that 6-MF inhibited Nogo-B/ChREBP-mediated fatty acid synthesis and reduced lipid accumulation in hepatocytes by restoring cellular autophagy and promoting fatty acid oxidation via the AMPKα-mTOR pathway. Thus, 6-MF may serve as a potential Nogo-B inhibitor to treat metabolic syndrome caused by glycolipid metabolism dysregulation., (© 2023. The Author(s), under exclusive licence to Shanghai Institute of Materia Medica, Chinese Academy of Sciences and Chinese Pharmacological Society.)

Non-small-cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancer cases. NSCLC patients often have poor prognosis demanding urgent identification of novel biomarkers and potential therapeutic targets. KCNAB2 (regulatory beta subunit2 of voltage-gated potassium channel), encoding aldosterone reductase, plays a pivotal role in regulating potassium channel activity. In this research, we tested the expression of KCNAB2 as well as its potential functions in human NSCLC. Bioinformatics analysis shows that expression of KCNAB2 mRNA is significantly downregulated in human NSCLC, correlating with poor overall survival. In addition, decreased KCNAB2 expression was detected in different NSCLC cell lines and local human NSCLC tissues. Exogenous overexpression of KCNAB2 potently suppressed growth, proliferation and motility of established human NSCLC cells and promoted NSCLC cells apoptosis. In contrast, CRISPR/Cas9-induced KCNAB2 knockout further promoted the malignant biological behaviors of NSCLC cells. Protein chip analysis in the KCNAB2-overexpressed NSCLC cells revealed that KCNAB2 plays a possible role in AKT-mTOR cascade activation. Indeed, AKT-mTOR signaling activation was potently inhibited following KCNAB2 overexpression in NSCLC cells. It was however augmented by KCNAB2 knockout. In vivo, the growth of subcutaneous KCNAB2-overexpressed A549 xenografts was significantly inhibited. Collectively, KCNAB2 could be a novel effective gene for prognosis prediction of NSCLC. Targeting KCNAB2 may lead to the development of advanced therapies., (© 2023. Cell Death Differentiation Association (ADMC).)

DFT calculations of reaction mechanisms in solution have always been a hot topic, especially for transition-metal-catalyzed reactions, in which the traditional DFT-D3 method has been extensively employed. The overestimation of the dispersion from the traditional DFT-D3 method leads to a quite low activation free-energy barrier, so it is worth finding a proper way to deal with the dispersion for solution systems. The solvent-solute dispersion is also important for solution systems, and thus it should be calculated together with the solute dispersion. The newly generated solute-solute dispersion energy should be shared equally with the newly formed cavity between two interacting species; therefore, only half of the solute-solute and solvent-solute dispersion terms belong to the solute molecule. The detailed treatment of dispersion correction for solution systems has been fully addressed, and this method has been confirmed with the examples of ligand exchange reactions and catalytic reactions.

Electroencephalogram (EEG) is an important technology to explore the central nervous mechanism of tinnitus. However, it is hard to obtain consistent results in many previous studies for the high heterogeneity of tinnitus. In order to identify tinnitus and provide theoretical guidance for the diagnosis and treatment, we propose a robust, data-efficient multi-task learning framework called Multi-band EEG Contrastive Representation Learning (MECRL). In this study, we collect resting-state EEG data from 187 tinnitus patients and 80 healthy subjects to generate a high-quality large-scale EEG dataset on tinnitus diagnosis, and then apply the MECRL framework on the generated dataset to obtain a deep neural network model which can distinguish tinnitus patients from the healthy controls accurately. Subject-independent tinnitus diagnosis experiments are conducted and the result shows that the proposed MECRL method is significantly superior to other state-of-the-art baselines and can be well generalized to unseen topics. Meanwhile, visual experiments on key parameters of the model indicate that the high-classification weight electrodes of tinnitus' EEG signals are mainly distributed in the frontal, parietal and temporal regions. In conclusion, this study facilitates our understanding of the relationship between electrophysiology and pathophysiology changes of tinnitus and provides a new deep learning method (MECRL) to identify the neuronal biomarkers in tinnitus.

Background: With the rapid advancement of medical imaging technology, the demand for accurate segmentation of medical images is increasing. However, most existing methods are unable to capture locality and long-range dependency information in integrated ways for medical images., Method: In this paper, we propose an elegant segmentation framework for medical images named TC-Net, which can utilize both the locality-aware and long-range dependencies in the medical images. As for the locality-aware perspective, we employ a CNN-based encoder and decoder structure. The CNN branch uses the locality of convolution operations to dig out local information in medical images. As for the long-range dependencies, we construct a Transformer branch to focus on the global context. Additionally, we proposed a locality-aware and long-range dependency concatenation strategy (LLCS) to aggregate the feature maps obtained from the two subbranches. Finally, we present a dynamic cyclical focal loss (DCFL) to address the class imbalance problem in multi-lesion segmentation., Results: Comprehensive experiments were conducted on lesion segmentation tasks using two fundus image databases and a skin image database. The TC-Net achieves scores of 0.6985 and 0.5171 in the metric of mean pixel accuracy on the IDRiD and DDR databases, respectively. Moreover, on the skin image database, the TC-Net reached mean pixel accuracy of 0.8886. The experiment results demonstrate that the proposed method achieves better performance than other deep learning segmentation schemes. Furthermore, the proposed DCFL achieves higher performance than other loss functions in multi-lesion segmentation., Significance: The proposed TC-Net is a promising new framework for multi-lesion medical image segmentation and many other challenging image segmentation tasks. © 2001 Elsevier Science. All rights reserved., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yu Li reports financial support was provided by National Natural Science Foundation of China., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Purpose: We developed and tested a novel method of creating intensity modulated proton arc therapy (IMPAT) plans that uses computing resources similar to those for regular intensity-modulated proton therapy (IMPT) plans and may offer a dosimetric benefit for patients with ependymoma or similar tumor geometries., Methods: Our IMPAT planning method consists of a geometry-based energy selection step with major scanning spot contributions as inputs computed using ray-tracing and single-Gaussian approximation of lateral spot profiles. Based on the geometric relation of scanning spots and dose voxels, our energy selection module selects a minimum set of energy layers at each gantry angle such that each target voxel is covered by sufficient scanning spots as specified by the planner, with dose contributions above the specified threshold. Finally, IMPAT plans are generated by robustly optimizing scanning spots of the selected energy layers using a commercial proton treatment planning system (TPS). The IMPAT plan quality was assessed for four ependymoma patients. Reference three-field IMPT plans were created with similar planning objective functions and compared with the IMPAT plans., Results: In all plans, the prescribed dose covered 95% of the clinical target volume (CTV) while maintaining similar maximum doses for the brainstem. While IMPAT and IMPT achieved comparable plan robustness, the IMPAT plans achieved better homogeneity and conformity than the IMPT plans. The IMPAT plans also exhibited higher relative biological effectiveness (RBE) enhancement than did the corresponding reference IMPT plans for the CTV in all four patients and brainstem in three of them., Conclusions: The proposed method demonstrated potential as an efficient technique for IMPAT planning and may offer a dosimetric benefit for patients with ependymoma or tumors in close proximity to critical organs. IMPAT plans created using this method had elevated RBE enhancement associated with increased linear energy transfer (LET) in both targets and abutting critical organs., (© 2023 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.)

In this study, a model was developed to investigate the partial denitrification(PD) process. The heterotrophic biomass (X H ) proportion in the sludge was determined to be 66.4% based on metagenomic sequencing. The kinetic parameters were first calibrated, then validated using the batch tests results. The results showed rapid decreases in the chemical oxygen demand (COD) and nitrate concentrations and gradual increases in the nitrite concentrations in the first four hours, then remained constant from 4 to 8 h. Anoxic reduction factor (η NO3 and η NO2 ) and half saturation constant (K S1 and K S2 ) were calibrated at 0.097, 0.13, 89.28 mg COD/L, and 102.29 mg COD/L, respectively. Whereas the simulation results demonstrated that the increase in carbon-to-nitrogen (C/N) ratios and the reduction in X H contributed to the increase in the nitrite transformation rate. This model provides potential strategies for optimizing the PD/A process., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Natriuretic peptides, which are produced by the heart, bind to natriuretic peptide receptor A (NPR1 encoded by natriuretic peptide receptor 1 gene) and cause vasodilation and natriuresis. Thus, they serve an important role in regulating blood pressure. In the present study, microinjection of CRISPR associated protein 9/single guide RNA into fertilized C57BL/6N mouse eggs was performed to generate filial generation zero (F0) Npr1 knockout homozygous mice (Npr1 -/- ). F0 mice mated with wild-type (WT) mice to obtain F1 Npr1 knockout heterozygous mice with stable heredity (Npr1 +/- ). F1 self-hybridization was used to expand the population of heterozygous mice (Npr1 +/- ). The present study performed echocardiography to investigate the impact of NPR1 gene knockdown on cardiac function. Compared with those in the WT group (C57BL/6N male mice), the left ventricular ejection fraction, myocardial contractility and renal sodium and potassium excretion and creatinine-clearance rates were decreased, indicating that Npr1 knockdown induced cardiac and renal dysfunction. In addition, expression of serum glucocorticoid-regulated kinase 1 (SGK1) increased significantly compared with that in WT mice. However, glucocorticoids (dexamethasone) upregulated NPR1 and inhibited SGK1 and alleviated cardiac and renal dysfunction caused by Npr1 gene heterozygosity. SGK1 inhibitor GSK650394 ameliorate cardiorenal syndrome by suppressing SGK1. Briefly, glucocorticoids inhibited SGK1 by upregulating NPR1, thereby ameliorating cardiorenal impairment caused by Npr1 gene heterozygosity. The present findings provided novel insight into the understanding of cardiorenal syndrome and suggested that glucocorticoids targeting the NPR1/SGK1 pathway may be a potential therapeutic target to treat cardiorenal syndrome., Competing Interests: The authors declare that they have no competing interests., (Copyright: © Huang et al.)

We demonstrate the first ever recorded positron-emission tomography (PET) imaging and dosimetry of a FLASH proton beam at the Proton Center of the MD Anderson Cancer Center. Two scintillating LYSO crystal arrays, read out by silicon photomultipliers, were configured with a partial field of view of a cylindrical poly-methyl methacrylate (PMMA) phantom irradiated by a FLASH proton beam. The proton beam had a kinetic energy of 75.8 MeV and an intensity of about 3.5 × 10 10 protons that were extracted over 101.5 ms-long spills. The radiation environment was characterized by cadmium-zinc-telluride and plastic scintillator counters. Preliminary results indicate that the PET technology used in our tests can efficiently record FLASH beam events. The instrument yielded informative and quantitative imaging and dosimetry of beam-activated isotopes in a PMMA phantom, as supported by Monte Carlo simulations. These studies open a new PET modality that can lead to improved imaging and monitoring of FLASH proton therapy., (Creative Commons Attribution license.)

Background: Hemiplegic shoulder pain (HSP) is a common complication in patients with stroke. The pathogenesis of HSP is complex, and muscle hypertonia, especially the hypertonia of internal rotation muscles of the shoulder, may be one of the important causes of shoulder pain. However, the relationship between muscle stiffness and HSP has not been well studied. The purpose of this study is to explore the correlations between the stiffness of internal rotation muscles and clinical symptoms in patients with HSP., Methods: A total of 20 HSP patients and 20 healthy controls were recruited for this study. The stiffness of internal rotation muscles was quantified using shear wave elastography, and Young's modulus (YM) of the pectoralis major (PM), anterior deltoid (AD), teres major ™, and latissimus dorsi (LD) were measured. Muscle hypertonia and pain intensity were evaluated using the Modified Ashworth Scale (MAS) and Visual Analog Scale (VAS), respectively. The mobility of the shoulder was evaluated using the Neer score. The correlations between muscle stiffness and the clinical scales were analyzed., Results: YM of internal rotation muscles on the paretic side was higher than that of the control group in the resting and passive stretching positions ( P < 0.05). YM of internal rotation muscles on the paretic side during passive stretching was significantly higher than that at rest ( P < 0.05). YM of PM, TM, and LD during passive stretching were correlated with MAS ( P < 0.05). In addition, the YM of TM during passive stretching was positively correlated with VAS and negatively correlated with the Neer score ( P < 0.05)., Conclusion: Increased stiffness of PM, TM, and LD was observed in patients with HSP. The stiffness of TM was associated with pain intensity of the shoulder and shoulder mobility., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Jia, Zhu, Kong, Fan, Zhu, Lin, Zhang and Yuan.)

Objective . Robustness evaluation is critical in particle radiotherapy due to its susceptibility to uncertainties. However, the customary method for robustness evaluation only considers a few uncertainty scenarios, which are insufficient to provide a consistent statistical interpretation. We propose an artificial intelligence-based approach that overcomes this limitation by predicting a set of percentile dose values at every voxel and allows for the evaluation of planning objectives at specific confidence levels. Approach . We built and trained a deep learning (DL) model to predict the 5th and 95th percentile dose distributions, which corresponds to the lower and upper bounds of a two-tailed 90% confidence interval (CI), respectively. Predictions were made directly from the nominal dose distribution and planning computed tomography scan. The data used to train and test the model consisted of proton plans from 543 prostate cancer patients. The ground truth percentile values were estimated for each patient using 600 dose recalculations representing randomly sampled uncertainty scenarios. For comparison, we also tested whether a common worst-case scenario (WCS) robustness evaluation (voxel-wise minimum and maximum) corresponding to a 90% CI could reproduce the ground truth 5th and 95th percentile doses. Main results . The percentile dose distributions predicted by DL yielded excellent agreements with the ground truth dose distributions, with mean dose errors below 0.15 Gy and average gamma passing rates (GPR) at 1 mm/1% above 93.9, which were substantially better than the WCS dose distributions (mean dose error above 2.2 Gy and GPR at 1 mm/1% below 54). We observed similar outcomes in a dose-volume histogram error analysis, where the DL predictions generally yielded smaller mean errors and standard deviations than the WCS evaluation doses. Significance . The proposed method produces accurate and fast predictions (∼2.5 s for one percentile dose distribution) for a given confidence level. Thus, the method has the potential to improve robustness evaluation., (© 2023 Institute of Physics and Engineering in Medicine.)

Objective: This study aimed to study the cytokines in gingival crevicular fluid (GCF) of the teeth opposing to dental implants and 3-unit fixed partial dentures (FPDs)., Materials and Methods: A total of 74 participants were recruited for this cross-sectional study. Based on the status of lower first molars, the participants were divided into dental implants group and 3-unit FPDs group. Social index and oral hygiene were recorded. Occlusal loading was evaluated with a T-scan. GCF was sampled from the upper first molar and assessed with a commercial cytokine assay kit., Results: Forty three dental implants patients and 31 3-unit FPDs patients received all of the clinical and laboratory evaluation. The dental implants group had a higher occlusion force distribution on first molars region. IL-10, IL-17, RANK had a higher mean in dental implants group and was associated with occlusion force of first molar. There was a weakly association between IL-10 and dental implants in the binary logistic regression analyses., Conclusions: In this study, the teeth opposing implants have a higher level of cytokines in the GCF than teeth opposing to 3-unit FPDs in periodontal healthy participants because of the poor osseoperception of dental implants. IL-10 might reflect a higher occlusion force in dental implants region., Clinical Relevance: This study provided that different tooth restoration methods could influence the periodontal status of the contact teeth., (© 2023. The Author(s).)

Increasing evidence suggests that astrocytes play an important role in the progression of Parkinson's disease (PD). Previous studies on our parkin knockout mouse demonstrated a higher accumulation of damaged mitochondria in astrocytes than in surrounding dopaminergic (DA) neurons, suggesting that Parkin plays a crucial role regarding their interaction during PD pathogenesis. In the current study, we examined primary mesencephalic astrocytes and neurons in a direct co-culture system and discovered that the parkin deletion causes an impaired differentiation of mesencephalic neurons. This effect required the parkin mutation in astrocytes as well as in neurons. In Valinomycin-treated parkin-deficient astrocytes, ubiquitination of Mitofusin 2 was abolished, whereas there was no significant degradation of the outer mitochondrial membrane protein Tom70. This result may explain the accumulation of damaged mitochondria in parkin-deficient astrocytes. We examined differential gene expression in the substantia nigra region of our parkin-KO mouse by RNA sequencing and identified an upregulation of the endoplasmic reticulum (ER) Ca 2+ -binding protein reticulocalbin 1 (RCN1) expression, which was validated using qPCR. Immunostaining of the SN brain region revealed RCN1 expression mainly in astrocytes. Our subcellular fractionation of brain extract has shown that RCN1 is located in the ER and in mitochondria-associated membranes (MAM). Moreover, a loss of Parkin function reduced ATP-stimulated calcium-release in ER mesencephalic astrocytes that could be attenuated by siRNA-mediated RCN1 knockdown. Our results indicate that RCN1 plays an important role in ER-associated calcium dyshomeostasis caused by the loss of Parkin function in mesencephalic astrocytes, thereby highlighting the relevance of astrocyte function in PD pathomechanisms., (© 2023 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Pancreatic cancer has an extremely poor prognosis. Here we examined expression, potential functions and underlying mechanisms of MXRA5 (matrix remodeling associated 5) in pancreatic cancer. Bioinformatics studies revealed that MXRA5 transcripts are significantly elevated in pancreatic cancer tissues, correlating with the poor overall survival, high T-stage, N1 and pathologic stage of the patients. MXRA5 mRNA and protein expression is significantly elevated in microarray pancreatic cancer tissues and different pancreatic cancer cells. In primary and immortalized (BxPC-3 and PANC-1 lines) pancreatic cancer cells, shRNA-induced MXRA5 silencing or CRISPR/Cas9-mediated MXRA5 knockout suppressed cell survival, proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), while provoking cell apoptosis. Conversely, forced overexpression of MXRA5 further promoted pancreatic cancer cell progression and EMT. Bioinformatics studies and the protein chip analyses revealed that differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) in MXRA5-overexpressed primary pancreatic cancer cells were enriched in the PI3K-Akt-mTOR cascade. Indeed, Akt-mTOR activation in primary human pancreatic cancer cells was inhibited by MXRA5 shRNA or knockout, but was augmented following MXRA5 overexpression. In vivo, the growth of MXRA5 KO PANC-1 xenografts was largely inhibited in nude mice. Moreover, intratumoral injection of adeno-associated virus-packed MXRA5 shRNA potently inhibited primary pancreatic cancer cell growth in nude mice. Akt-mTOR activation was also largely inhibited in the MXRA5-depleted pancreatic cancer xenografts. Contrarily MXRA5 overexpression promoted primary pancreatic cancer cell growth in nude mice. Together, overexpressed MXRA5 is important for pancreatic cancer cell growth possibly through promoting EMT and Akt-mTOR activation. MXRA5 could be a potential therapeutic oncotarget for pancreatic cancer., (© 2023. The Author(s).)

DFT calculations of reaction mechanisms in solution have always been a hot topic, especially for transition-metal-catalyzed reactions. The calculation of solvation energy is performed using either the polarizable continuum model (PCM) or the universal solvation model SMD. The PCM calculation is very sensitive to the choice of atomic radii to form a cavity, where the self-consistent isodensity PCM (SCI-PCM) has been recognized as the best choice and our IDSCRF radii can provide a similar cavity. Moving from a gas-phase case to a solution case, dispersion energy and entropy should be carefully treated. The solvent-solute dispersion is also important in solution systems, and it should be calculated together with the solute dispersion. Only half of the solvent-solute dispersion energy from the PCM calculation belongs to the solute molecules to maintain a thermal equilibrium between a solute molecule and its cavity, similar to the treatment of electrostatic energy. Relative solute dispersion energy should also be shared equally with the newly formed cavity. The entropy change from a gas phase to a liquid phase is quite large, but the modern quantum chemistry programs can only calculate the gas-phase translational entropy based on the idea-gas equation. In this review, we will provide an operable method to calculate the solution translational entropy, which has been coded in our THERMO program.

Our randomized clinical study comparing stereotactic body radiotherapy (SBRT) and stereotactic body proton therapy (SBPT) for early stage non-small cell lung cancer (NSCLC) was closed prematurely owing to poor enrollment, largely because of lack of volumetric imaging and difficulty in obtaining insurance coverage for the SBPT group. In this article, we describe technology improvements in our new proton therapy center, particularly in image guidance with cone beam CT (CBCT) and CT on rail (CTOR), as well as motion management with real-time gated proton therapy (RGPT) and optical surface imaging. In addition, we have a treatment planning system that provides better treatment plan optimization and more accurate dose calculation. We expect to re-start the SBPT program, including for early stage NSCLC as well as for other disease sites soon after starting patient treatment at our new proton therapy center., Competing Interests: Authors’ disclosure of potential conflicts of interest The authors have nothing to disclose., (© 2023 Old City Publishing, Inc.)

Objective: The present study aims to investigate the alterations of serum proteomic and metabolomic profiles in Chinese patients with severe and active Graves' Orbitopathy (GO)., Materials and Methods: Thirty patients with GO and 30 healthy volunteers were enrolled. The serum concentrations of FT3, FT4, T3, T4, and thyroid-stimulating hormone (TSH) were analyzed, after which TMT labeling-based proteomics and untargeted metabolomics were performed. Metabo- Analyst and Ingenuity Pathway Analysis (IPA) was used for integrated network analysis. A nomogram was established based on the model to explore the disease prediction ability of the identified feature metabolites., Results: One hundred thirteen proteins (19 up-regulated and 94 down-regulated) and 75 metabolites (20 increased and 55 decreased) were significantly altered in GO compared to the control group. By combining the lasso regression, IPA network, and protein-metabolite-disease sub-networks, we extracted feature proteins (CPS1, GP1BA, and COL6A1) and feature metabolites (glycine, glycerol 3-phosphate, and estrone sulfate). The logistic regression analysis revealed that the full model with the prediction factors and three identified feature metabolites had better prediction performance for GO compared to the baseline model. The ROC curve also indicated better prediction performance (AUC = 0.933 vs. 0.789)., Conclusion: A new biomarker cluster combined with three blood metabolites with high statistical power can be used to discriminate patients with GO. These findings provide further insights into the pathogenesis, diagnosis, and potential therapeutic targets for this disease., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

The high incidence and mortality of cervical cancer (CC) require an urgent need for exploring novel valuable therapeutics. Triptonide (TN) is a small molecule monomer extracted from the Chinese herb Tripterygium wilfordii Hook . Our results showed that TN, at only nanomolar concentrations, strongly inhibited growth, colony formation, proliferation, migration, and invasion of established and primary human cervical cancer cells. TN induced apoptosis and cell cycle arrest in cervical cancer cells. Moreover, cervical cancer cell in vitro migration and invasion were suppressed by TN. It was however noncytotoxic and proapoptotic to normal cervical epithelial cells and human skin fibroblast cells. Gene set enrichment analysis (GSEA) of RNA sequencing data of differentially expressed genes (DEGs) in TN-treated cervical cancer cells implied that DEGs were enriched in the receptor tyrosine kinase (RTK) signaling and PI3K-Akt-mTOR cascade. In cervical cancer cells, RTKs, including EGFR and PDGFR α , were significantly downregulated and Akt-mTOR activation was largely inhibited after TN treatment. In vivo , oral administration of TN significantly inhibited subcutaneous cervical cancer xenograft growth in nude mice. EGFR and PDGFR α downregulation as well as Akt-mTOR inactivation was detected in TN-treated HeLa xenograft tumor tissues. Thus, TN inhibits human cervical cancer cell growth in vitro and in vivo . Its anticervical cancer activity was associated with RTK downregulation and Akt-mTOR inactivation., Competing Interests: The authors have no conflict of interests., (Copyright © 2022 Li-na Zhou et al.)

Background: Multiple classes of molecular biomarkers have been studied as potential predictors for rectal cancer (RC) response. Carcinoembryonic antigen (CEA) is the most widely used blood-based marker of RC and has proven to be an effective predictive marker. Cancer antigen 19-9 (CA19-9) is another tumor biomarker used for RC diagnosis and postoperative monitoring, as well as monitoring of the therapeutic effect. Using a panel of tumor markers for RC outcome prediction is a practical approach., Aim: To assess the predictive effect of pre-neoadjuvant chemoradiotherapy (NCRT) CEA and CA19-9 levels on the prognosis of stage II/III RC patients., Methods: CEA and CA19-9 levels were evaluated 1 wk before NCRT. According to the receiver operating characteristic curve analysis, the optimal cut-off point of CEA and CA19-9 levels for the prognosis were 3.55 and 19.01, respectively. The novel serum tumor biomarker (NSTB) scores were as follows: score 0: Pre-NCRT CEA < 3.55 and CA19-9 < 19.01; score 2: Pre-NCRT CEA > 3.55 and CA19-9 > 19.01; score 1: Other situations. Pathological information was recorded according to histopathological reports after the operation., Results: In the univariate analysis, pre-NCRT CEA < 3.55 [ P = 0.025 for overall survival (OS), P = 0.019 for disease-free survival (DFS)], pre-NCRT CA19-9 < 19.01 ( P = 0.014 for OS, P = 0.009 for DFS), a lower NSTB score (0-1 vs 2, P = 0.009 for OS, P = 0.005 for DFS) could predict a better prognosis. However, in the multivariate analysis, only a lower NSTB score (0-1 vs 2; for OS, HR = 0.485, 95%CI: 0.251-0.940, P = 0.032; for DFS, HR = 0.453, 95%CI: 0.234-0.877, P = 0.019) and higher pathological grade, node and metastasis stage (0-I vs II-III; for OS, HR = 0.363, 95%CI: 0.158-0.837, P = 0.017; for DFS, HR = 0.342, 95%CI: 0.149-0.786, P = 0.012) were independent predictive factors., Conclusion: The combination of post-NCRT CEA and CA19-9 was a predictive factor for clinical stage II/III RC patients receiving NCRT, and the combined index had a stronger predictive effect., Competing Interests: Conflict-of-interest statement: All author reports no conflict of interest., (©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.)

Objective . Irradiation with ultra-high dose rates (>40 Gy s -1 ), also known as FLASH irradiation, has the potential to shift the paradigm of radiation therapy because of its reduced toxicity to normal tissues compared to that of conventional irradiations. The goal of this study was to (1) achieve FLASH irradiation conditions suitable for pre-clinical i n vitro and in vivo biology experiments using our synchrotron-based proton beamline and (2) commission the FLASH irradiation conditions achieved. Approach . To achieve these suitable FLASH conditions, we made a series of adaptations to our proton beamline, including modifying the spill length and size of accelerating cycles, repurposing the reference monitor for dose control, and expanding the field size with a custom double-scattering system. We performed the dosimetric commissioning with measurements using an Advanced Markus chamber and EBT-XD films as well as with Monte Carlo simulations. Main results . Through adaptations, we have successfully achieved FLASH irradiation conditions, with an average dose rate of up to 375 Gy s -1 . The Advanced Markus chamber was shown to be appropriate for absolute dose calibration under our FLASH conditions with a recombination factor ranging from 1.002 to 1.006 because of the continuous nature of our synchrotron-based proton delivery within a spill. Additionally, the absolute dose measured using the Advanced Markus chamber and EBT-XD films agreed well, with average and maximum differences of 0.32% and 1.63%, respectively. We also performed a comprehensive temporal analysis for FLASH spills produced by our system, which helped us identify a unique relationship between the average dose rate and the dose in our FLASH irradiation. Significance. We have established a synchrotron-based proton FLASH irradiation platform with accurate and precise dosimetry that is suitable for pre-clinical biology experiments. The unique time structure of the FLASH irradiation produced by our synchrotron-based system may shed new light onto the mechanism behind the FLASH effect., (© 2022 Institute of Physics and Engineering in Medicine.)

Objective: As an extension of optical coherence tomography (OCT), optical coherence tomographic angiography (OCTA) provides information on the blood flow status at the microlevel and is sensitive to changes in the fundus vessels. However, due to the distinct imaging mechanism of OCTA, existing models, which are primarily used for analyzing fundus images, do not work well on OCTA images. Effectively extracting and analyzing the information in OCTA images remains challenging. To this end, a deep learning framework that fuses multilevel information in OCTA images is proposed in this study. The effectiveness of the proposed model was demonstrated in the task of diabetic retinopathy (DR) classification., Method: First, a U-Net-based segmentation model was proposed to label the boundaries of large retinal vessels and the foveal avascular zone (FAZ) in OCTA images. Then, we designed an isolated concatenated block (ICB) structure to extract and fuse information from the original OCTA images and segmentation results at different fusion levels., Results: The experiments were conducted on 301 OCTA images. Of these images, 244 were labeled by ophthalmologists as normal images, and 57 were labeled as DR images. An accuracy of 93.1% and a mean intersection over union (mIOU) of 77.1% were achieved using the proposed large vessel and FAZ segmentation model. In the ablation experiment with 6-fold validation, the proposed deep learning framework that combines the proposed isolated and concatenated convolution process significantly improved the DR diagnosis accuracy. Moreover, inputting the merged images of the original OCTA images and segmentation results further improved the model performance. Finally, a DR diagnosis accuracy of 88.1% (95%CI ± 3.6%) and an area under the curve (AUC) of 0.92 were achieved using our proposed classification model, which significantly outperforms the state-of-the-art classification models. As a comparison, an accuracy of 83.7 (95%CI ± 1.5%) and AUC of 0.76 were obtained using EfficientNet. Significance . The visualization results show that the FAZ and the vascular region close to the FAZ provide more information for the model than the farther surrounding area. Furthermore, this study demonstrates that a clinically sophisticated designed deep learning model is not only able to effectively assist in the diagnosis but also help to locate new indicators for certain illnesses., Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this paper., (Copyright © 2022 Qiaoyu Li et al.)

Background: Liver cancer is among the leading causes of death related to cancer around the world. The most frequent type of human liver cancer is hepatocellular carcinoma (HCC). Fatty acid (FA) metabolism is an emerging hallmark that plays a promoting role in numerous malignancies. This study aimed to discover a FA metabolism-related risk signature and formulate a better model for HCC patients' prognosis prediction., Methods: We collected mRNA expression data and clinical parameters of patients with HCC using the TCGA databases, and the differential FA metabolism-related genes were explored. To create a risk prognostic model, we carried out the consensus clustering as well as univariate and multivariate Cox regression analyses. 16 genes were used to establish a prognostic model, which was then validated in the ICGC dataset. The accuracy of the model was performed using receiver operating characteristic (ROC) analyses, decision curve analysis (DCA) and nomogram. The immune cell infiltration level of risk genes was evaluated with single-sample GSEA (ssGSEA) algorithm. To reflect the response to immunotherapy, immunophenoscore (IPS) was obtained from TCGA-LIHC. Then, the expression of the candidate risk genes (p < 0.05) was validated by qRT-PCR, Western blotting and single-cell transcriptomics. Cellular function assays were performed to revealed the biological function of HAVCR1., Results: According to the TCGA-LIHC cohort analysis, the majority of the FA metabolism-related genes were expressed differentially in the HCC and normal tissues. The prognosis of patients with high-risk scores was observed to be worse. Multivariate COX regression analysis confirmed that the model can be employed as an independent prognosis factor for HCC patients. Furthermore, ssGSEA analysis revealed a link between the model and the levels of immune cell infiltration. Our model scoring mechanism also provides a high predictive value in HCC patients receiving anti-PDL1 immunotherapy. One of the FA metabolism-related genes, HAVCR1, displays a significant differential expression between normal and HCC cell lines. Hepatocellular carcinoma cells (Huh7, and HepG2) proliferation, motility, and invasion were all remarkably inhibited by HAVCR1 siRNA., Conclusion: Our study identified a novel FA metabolism-related prognostic model, revealing a better potential treatment and prevention strategy for HCC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhu, Zhu, Chen, Liu, Lu, Sun, Peng, Chen and Du.)

Neural infiltration is a critical component of the tumor microenvironment; however, owing to technological limitations, its role in hepatocellular cancer remains obscure. Herein, we obtained the RNA-sequencing data of liver hepatocellular carcinoma (LIHC) from The Cancer Genome Atlas database and performed a series of bioinformatic analyses, including prognosis analysis, pathway enrichment, and immune analysis, using the R software packages, Consensus Cluster Plus and Limma. LIHC could be divided into two subtypes according to the expression of neural-related genes (NRGs); moreover, there are statistic differences in the prognosis, stage, and immune regulation between the two subtypes. The prognostic model showed that high expression of NRGs correlated with a poor survival prognosis ( P <0.05). Further, CHRNE , GFRA2 , GFRA3 , and GRIN2D was significantly correlated with LIHC clinical prognosis, clinical stage, immune infiltration, immune response, and vital signaling pathways. There was nerve-cancer crosstalk in LIHC. A reclassification of LIHC based on NRG expression may prove beneficial to clinical practice. CHRNE , GFRA2 , GFRA3 , and GRIN2D may serve as potential biomarker for liver cancer prognosis or immune response., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhang, Jin, Zhu and Jin.)

Objectives: This study was aimed to assess the prevalence of anxiety and depression and the possible contributions of the caregiver's anxiety and depression, disease status, and socio-demographic characteristics to psychopathological comorbidities among adult patients with epilepsy., Methods: A total of 262 participants (131 adult patient-caregiver pairs) were enrolled in this study. The Hamilton Rating Scale for Depression (HAM-D) and the Hamilton Rating Scale for Anxiety (HAM-A) were applied to evaluate the depression and anxiety status among adult patients with epilepsy and their caregivers, respectively. We collected caregivers' anxiety and depression, patients' sociodemographic characteristic data, and disease status as independent variables using stepwise multiple linear regression analysis that were correlated to the degree of anxiety and depression among these adult patients with epilepsy., Results: Among adult patients with epilepsy, 46 (35.11%) subjects showed anxiety symptoms (HAM-A scores > 6), and 48 (36.64%) had depression symptoms (HAM-D scores > 6). Caregivers' anxiety levels and place of residence were significant independent predictors of both anxiety and depression levels among adult patients with epilepsy., Conclusions: Adult patients with epilepsy are at a high risk of suffering from anxiety and depression. Caregivers' anxiety and place of residence are definite independent predictors for anxiety and depression severity among adult patients with epilepsy. Therefore, clinicians should be careful in closely monitoring the psychological status of adult patients with epilepsy and their caregivers. Furthermore, the government and medical institutions should increase educational awareness about epilepsy and its cure, especially among adult patients with epilepsy who live in rural areas and consider offering a multidisciplinary management program to improve these patients' psychological status., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: It is still unknown whether tranexamic acid (TXA) is beneficial for the minimally invasive surgical approach to total hip arthroplasty (THA). The aim of this study is to investigate the efficacy and safety of intravenous TXA in primary THA via the direct anterior approach (DAA)., Materials and Methods: We performed a retrospective analysis of prospectively collected data on 70 patients with nontraumatic avascular necrosis of the femoral head who underwent THA via the DAA between October 2017 and October 2018. Patients were divided into two groups: TXA group (39 patients received 1.5 g TXA intravenously) and control group (31 patients did not receive TXA). Patients were assessed by operative time, postoperative hemoglobin (HB) drop, transfusion rate, postoperative length of hospital stays (LHS), deep vein thrombosis (DVT), and Harris hip score (HHS)., Results: Total blood loss, hidden blood loss, and postoperative HB drop in the TXA group were significantly lower than in the control group (p < 0.05). There was no statistical difference between the two groups in terms of intraoperative blood loss, operative time, transfusion rate, postoperative LHS, HHS, or incidence of DVT (p > 0.05)., Conclusions: TXA may reduce perioperative blood loss without increasing complications in THA via the DAA., Level of Evidence: Level IV, therapeutic study., (© 2022. The Author(s).)

Purpose: The main purpose of this work was to generate and validate the dosimetric accuracy of proton beams of dimensions that are appropriate for in vivo small animal and in vitro ultrahigh dose rate (FLASH) radiotherapy experiments using a synchrotron-based treatment delivery system. This study was performed to enable future investigations of the relevance of a spread-out Bragg peak (SOBP) under FLASH conditions., Methods: The spill characteristics of the small field fixed horizontal beam line were modified to deliver accelerated protons in times as short as 2 ms and to control the dose delivered. A Gaussian-like transverse beam profile was transformed into a square uniform one at FLASH dose rates, while avoiding low-dose regions, a crucial requirement to protect normal tissue during FLASH irradiation. Novel beam-shaping devices were designed using Monte Carlo techniques to produce up to about 6 cm 3 of uniform dose in SOBPs while maximizing the dose rate. These included a scattering foil, a conical flattening filter to maximize the flux of protons into the region of interest, energy filters, range compensators, and collimators. The shapes, sizes, and positions of the components were varied to provide the required field sizes and SOBPs., Results: The designed and fabricated devices were used to produce 10-, 15-, and 20-mm diameter, circular field sizes and 10-, 15-, and 20-mm SOBP modulation widths at uniform physical dose rates of up to 375 Gy/s at the center of the SOBP and a minimum dose rate of about 255 Gy/s at the entrance, respectively, in cylindrical volumes. The flatness of lateral dose profiles at the center could be adjusted to within ±1.5% at the center of the SOBP. Assessment of systematic uncertainties, such as impact of misalignments and positioning uncertainties, was performed using simulations, and the results were used to provide appropriate adjustments to ensure high-accuracy FLASH beam delivery for both in vitro and in vivo preclinical experiments., Conclusions: It is feasible to use synchrotron-generated proton beams of sufficient dimensions for FLASH radiobiology experiments. We expect to use the system we developed to acquire in vitro and in vivo small animal FLASH radiobiology data as a function of dose, dose rate, oxygen content, and linear energy transfer to help us understand the underlying mechanisms of the FLASH phenomenon., (© 2021 American Association of Physicists in Medicine.)