Design principles of heterointerfacial redox chemistry for highly reversible lithium metal anode

High electrochemical reversibility is required for the application of high-energy-density lithium (Li) metal batteries; however, inactive Li formation and SEI (solid electrolyte interface)-instability-induced electrolyte consumption cause low Coulombic efficiency (CE). The prior interfacial chemical designs in terms of alloying kinetics have been used to enhance the CE of Li metal anode; however, the role of its redox chemistry at heterointerfaces remains a mystery. Herein, the relationship between heterointerfacial redox chemistry and electrochemical transformation reversibility is investigated. It is demonstrated that the lower redox potential at heterointerface contributes to higher CE, and this enhancement in CE is primarily due to the regulation of redox chemistry to Li deposition behavior rather than the formation of SEI films. Low oxidation potential facilitates the formation of the surface with the highly electrochemical binding feature after Li stripping, and low reduction potential can maintain binding ability well during subsequent Li plating, both of which homogenize Li deposition and thus optimize CE. In particular, Mg hetero-metal with ultra-low redox potential enables Li metal anode with significantly improved CE (99.6%) and stable cycle life for 700 cycles at 3.0 mA cm-2. This work provides insight into the heterointerfacial design principle of next-generation negative electrodes for highly reversible metal batteries.

J-2156, a small molecule somatostatin type 4 receptor agonist, alleviated hindpaw hypersensitivity in the streptozotocin-induced rat model of painful diabetic neuropathy but with a 2-fold decrease in potency at an advanced stage in the model, mimicking morphine

There is a large unmet need for novel pain-killers to improve relief of painful diabetic neuropathy (PDN). Herein, we assessed the efficacy of the somatostatin type 4 (SST4) receptor agonist, J-2156, for relief of PDN in rats. Diabetes was induced with streptozotocin (STZ; 70 mg/kg) and bilateral hindpaw hypersensitivity was fully developed by 8-week post-STZ. In the intervals, 8-12-weeks (morphine-sensitive phase; Phase 1) and 16-18-weeks (morphine-hyposensitive phase; Phase 2) post-STZ, rats received a single dose of intraperitoneal (i.p.) J-2156 (10, 20, 30 mg/kg), gabapentin (100 mg/kg i.p.), subcutaneous morphine (1 mg/kg) or vehicle. Hindpaw withdrawal thresholds (PWTs) were assessed using von Frey filaments pre-dose and at regular intervals over 3-h post-dose. In Phase 1, J-2156 at 30 mg/kg evoked significant anti-allodynia in the hindpaws with maximal effect at 1.5 h compared with 1 h for gabapentin and morphine. The durations of action for all three compounds were greater than 3 h. The corresponding mean (±SEM) extent and duration of anti-allodynia (ΔPWT AUC) for gabapentin did not differ significantly from that for J-2156 (30 mg/kg) or morphine. However, in Phase 2, the ΔPWT AUC for morphine was reduced to approximately 25% of that in Phase 1, mirroring our previous work. Similarly, the mean (±SEM) ΔPWT AUC for J-2156 (30 mg/kg) in Phase 2 was approximately 45% of that for Phase 1 whereas for gabapentin the mean (±SEM) ΔPWT AUCs did not differ significantly (p > 0.05) between the two phases. Our findings further describe the preclinical pain relief profile of J-2156 and complement previous work in rat models of inflammatory pain, neuropathic pain and low back pain. SST4 receptor agonists hold promise as novel therapeutics for the relief of PDN, a type of peripheral neuropathic pain that is often intractable to relief with clinically used drug treatment options.

SpSrtA-Catalyzed Isopeptide Ligation on Lysine Residues

Sortase-mediated ligation (SML) is widely used for protein bioconjugation. However, the sortase used in this strategy typically recognizes only the N-terminal oligoglycine, which is absent in most natural proteins. To broaden the spectrum of substrates compatible with SML, we focus on a novel sortase, sortase A from Streptococcus pneumoniae (SpSrtA), known for its expanded substrate specificity (N-terminal glycine, alanine, and serine). We present the first evidence showing that the reported SpSrtA mutant (SpSrtA*) can modify lysine residues in itself and other proteins. The modification sites of SpSrtA* were identified through LC-MS/MS analysis. Moreover, we discovered an optimal lysine-containing peptide tag by fusing it onto sfGFP, resulting in a labeling efficiency of 57%. Inspired by this, we applied the method to modify proteins on microorganism surfaces up to 13.5-fold. To enhance labeling efficiency, we fused the SpSrtA* onto a surface protein and achieved a 2.64-fold improvement. We further developed a high-throughput yeast display screening method for the directed evolution of SpSrtA*, achieving a 10-fold improvement in the labeling efficiency of this surface protein. Our study provides a novel strategy for modifying the lysine residues that will be a powerful addition to the protein bioconjugation toolbox.

Spatial-Temporal Knowledge-Embedded Transformer for Video Scene Graph Generation

Video scene graph generation (VidSGG) aims to identify objects in visual scenes and infer their relationships for a given video. It requires not only a comprehensive understanding of each object scattered on the whole scene but also a deep dive into their temporal motions and interactions. Inherently, object pairs and their relationships enjoy spatial co-occurrence correlations within each image and temporal consistency/transition correlations across different images, which can serve as prior knowledge to facilitate VidSGG model learning and inference. In this work, we propose a spatial-temporal knowledge-embedded transformer (STKET) that incorporates the prior spatial-temporal knowledge into the multi-head cross-attention mechanism to learn more representative relationship representations. Specifically, we first learn spatial co-occurrence and temporal transition correlations in a statistical manner. Then, we design spatial and temporal knowledge-embedded layers that introduce the multi-head cross-attention mechanism to fully explore the interaction between visual representation and the knowledge to generate spatial- and temporal-embedded representations, respectively. Finally, we aggregate these representations for each subject-object pair to predict the final semantic labels and their relationships. Extensive experiments show that STKET outperforms current competing algorithms by a large margin, e.g., improving the mR@50 by 8.1%, 4.7%, and 2.1% on different settings over current algorithms.

[Molecular epidemiological characteristics of newly diagnosed HIV-1 cases in Fujian Province in 2020]

OBJECTIVE

To investigate the HIV-1 genotype and distribution of newly diagnosed HIV-1 cases in Fujian Province in 2020, so as to provide insights into formulation of the precise AIDS control strategy in the province.

METHODS

Newly diagnosed HIV-1 cases without antiretroviral therapy (excluding AIDS patients) were randomly sampled from each city of Fujian Province in 2020 at a proportion of 50% of the mean number of HIV-infected cases reported across 9 cities of Fujian Province during the past three years. Subjects' demographic and epidemiological data were collected and blood samples were collected. The HIV-1 pol gene was amplified using nested reverse-transcription PCR assay, and the gene sequences were used for HIV-1 genotyping and phylogenetic analysis. The gene sequences were uploaded to the HIV Drug Resistance Database (http://hivdb.stanford.edu) for genotypic drug resistance assays, and the scores and level of HIV drug resistance were estimated using the HIVDB Algorithm version 9.5.

RESULTS

A total of 1 043 newly diagnosed HIV-1 cases were reported in Fujian Province in 2020, and 936 gene sequences were successfully obtained following sequencing of blood samples. There were 9 HIV-1 genotypes characterized in blood samples from 936 newly diagnosed HIV-1 cases, with CRF07_BC (52.1%) and CRF01_AE (30.4%) as predominant subtypes, followed by CRF08_BC (4.9%), CRF55_01B (3.0%), subtype C (2.5%), subtype B (2.1%), CRF85_BC (1.7%), CRF59_01B (0.3%) and CRF65_CPX (0.1%), and unidentified subtypes were found in 26 blood samples. HIV-1 drug resistance was detected in 43 out of the 936 newly diagnosed HIV-1 cases, with 4.6% prevalence of HIV-1 drug resistance prior to therapy, and the highest drug resistance was found in the HIV CRF59_01B subtype, followed by in CRF08_BC, B, C, CRF01_AE, CRF07_BC and other subtypes, with a significant difference in the genotype-specific prevalence of HIV-1 drug resistance (χ2 = 45.002, P < 0.05).

CONCLUSIONS

There was a HIV-1 genotype diversity in Fujian Province in 2020, and emerging recombinant and drug-resistant HIV-1 strains were detected and spread across patients and regions. Monitoring of HIV-1 genotypes is recommended to be reinforced for timely understanding of the transmission and spread of novel recombinant and drug-resistant HIV-1 strains.

Resveratrol Attenuates Sepsis-Induced Cardiomyopathy in Rats through Anti-Ferroptosis via the Sirt1/Nrf2 Pathway

Background: Sepsis-induced cardiomyopathy (SIC) is a severe myocardial dysfunction secondary to septicemia. It is a major concern owing to the high mortality and morbidity, which are greatly influenced by ferroptosis. Resveratrol (RSV) is a naturally existing agonist of the silent information regulator 1 (Sirt1). It has cardioprotective effects against sepsis-induced myocardial injury, However, the detailed mechanism is unknown.Methods: In this study, cecal ligation and puncture (CLP)-induced septic rats were employed to assess the changes in ferroptosis with RSV administration. According to the different treatments the rats were divided into the following groups: (1) the Sham, (2) CLP, (3) CLP + RSV at various doses (10, 30, and 50 mg/kg), and (4) CLP + Fer-1(a ferroptotic inhibitor) groups. After 24 h, the structure and function of the cardiac system in rats were evaluated, and mitochondrial morphology, ferroptosis-related biomarkers, and the levels of Sirt1/Nrf2 were assessed.Results: The rats that underwent CLP had suffered cardiac dysfunction, accompanied with myocardial damage, impaired mitochondria, elevated lipid peroxidation, and reduced Sirt1/Nrf2 expression in the myocardium. High-dose RSV successfully improved heart function, reversing the abnormalities in a dose-dependent manner. We then used EX527, a selective Sirt1 inhibitor, to further identify the intermediate signaling targets of RSV that regulate ferroptosis. EX527 diminished the curative effects of high-doses RSV.Conclusions: Summarily, our findings suggest a novel mechanism of RSV in reducing SIC: ferroptosis inhibition via upregulation of Sirt1/Nrf2 signaling pathways. This may be an effective therapeutic approach against organ failure in sepsis, particularly SIC.

Upregulating miR-181b promotes ferroptosis in osteoarthritic chondrocytes by inhibiting SLC7A11

BACKGROUND

Osteoarthritis (OA) is a common disease with a complex pathology. This study aimed to investigate the correlation between the aberrant upregulation of miR-181b and ferroptosis in chondrocytes during the progression of OA.

METHODS

An OA cell model was constructed with erastin. Ferrostatin-1 (Fer), bioinformatics, and dual-luciferase activity reports were used to investigate the effect of miR-181b on OA. Finally, a rat model of OA was induced by monosodium iodoacetate to verify that miR-181b inhibits SLC7A11 gene expression and increases ferroptosis.

RESULTS

The results showed that Fer could effectively reverse the erastin-induced inhibition of human chondrocyte viability, increase the level of collagenous proteins in human chondrocytes, and inhibit oxidative stress and ferroptosis. MiR-181b is abnormally elevated in OA cell models. Transfection of a miR-181b inhibitor could increase the expression levels of the ferroptosis-related proteins solute carrier family 7 members 11 (SLC7A11) and glutathione peroxidase 4 (GPX4), thereby inhibiting the occurrence of ferroptosis in chondrocytes. In addition, hsa-miR-181b-5p and SLC7A11 have a targeted regulatory effect. Transfection of SLC7A11 siRNA effectively abrogated the increase in chondrocyte viability induced by the miR-181 inhibitor and increased ferroptosis. Finally, miR-181b was shown to exacerbate OA disease progression by inhibiting SLC7A11 gene expression and increasing ferroptosis in a rat OA model.

CONCLUSIONS

Elevating miR-181b may mediate chondrocyte ferroptosis by targeting SLC7A11 in OA.

Road Network-Guided Fine-Grained Urban Traffic Flow Inference

Accurate inference of fine-grained traffic flow from coarse-grained one is an emerging yet crucial problem, which can help greatly reduce the number of the required traffic monitoring sensors for cost savings. In this work, we note that traffic flow has a high correlation with road network, which was either completely ignored or simply treated as an external factor in previous works. To facilitate this problem, we propose a novel road-aware traffic flow magnifier (RATFM) that explicitly exploits the prior knowledge of road networks to fully learn the road-aware spatial distribution of fine-grained traffic flow. Specifically, a multidirectional 1-D convolutional layer is first introduced to extract the semantic feature of the road network. Subsequently, we incorporate the road network feature and coarse-grained flow feature to regularize the short-range spatial distribution modeling of road-relative traffic flow. Furthermore, we take the road network feature as a query to capture the long-range spatial distribution of traffic flow with a transformer architecture. Benefiting from the road-aware inference mechanism, our method can generate high-quality fine-grained traffic flow maps. Extensive experiments on three real-world datasets show that the proposed RATFM outperforms state-of-the-art models under various scenarios. Our code and datasets are released at https://github.com/luimoli/RATFM.

[Clinical and imaging features of acute encephalopathy with biphasic seizures and late reduced diffusion in children]

Objective: To explore the clinical and imaging features of acute encephalopathy with biphasic seizures and late reduced diffusion(AESD) in children. Methods: For the case series study, 21 children with AESD from Peking University First Hospital, Provincial Children's Hospital Affiliated to Anhui Medical University, Children's Hospital of Fudan University, and Shanxi Children's Hospital who were diagnosed and treated from October 2021 to July 2023 were selected. Clinical data were collected to summarize their clinical information, imaging, and laboratory tests, as well as treatment and prognostic characteristics. Descriptive statistical analysis was applicated. Results: Of the 21 cases with AESD, 11 were males and 10 were females, with the age of onset of 2 years and 6 months (1 year and 7 months, 3 years and 6 months). Of the 21 cases, 18 were typical cases with biphasic seizures. All typical cases had early seizures within 24 hours before or after fever onset. Among them, 16 cases had generalized seizures, 2 cases had focal seizures, and 7 cases reached the status epilepticus. Of the 21 cases, 3 atypical cases had late seizures in biphasic only. The late seizures in the 21 cases occurred on days 3 to 9. The types of late seizures included focal seizures in 12 cases, generalized seizures in 6 cases, and both focal and generalized seizures in 3 cases. Diffusion-weighted imaging (DWI) test on days 3 to 11 showed reduced diffusion of subcortical white matter which was named "bright tree sign" in all cases. The diffuse cerebral atrophy predominantly presented in the front-parietal-temporal lobes was found in 19 cases between day 12 and 3 months after the onset of the disease. Among 21 cases, 20 had been misdiagnosed as autoimmune encephalitis, central nervous system infection, febrile convulsions, posterior reversible encephalopathy syndrome, acute disseminated encephalomyelitis, and hemiconvulsion-hemiplegia-epilepsy syndrome. All the cases received high-dose gammaglobulin and methylprednisolone pulse therapy with poor therapeutic effect. By July 2023, 18 cases were under follow-up. Among them, 17 cases were left with varying degrees of neurologic sequelae, including 11 cases with post-encephalopathic epilepsy; 1 recovered completely. Conclusions: AESD is characterized by biphasic seizures clinically and "bright tree sign" on DWI images. Symptomatic and supportive treatments are recommended. The immunotherapy is ineffective. The prognosis of AESD is poor, with a high incidence of neurological sequelae and a low mortality.

Activation of HDAC8 Can Suppress the Proliferation of Osteosarcoma Cells via TP53 and STAT3/ERK Signaling Pathways

OBJECTIVE

Osteosarcoma is the most common malignant bone cancer and is typically associated with poor prognosis. Histone deacetylase 8 (HDAC8) presents as an effective target in anti-tumor treatment in various tumors. As the functions of HDAC8 in osteosarcoma have not been studied thoroughly, our study aims to explore the effects of HDAC8 in osteosarcoma proliferation.

METHODS

HDAC8 expression was analyzed in The Cancer Genome Atlas (TCGA)-pan-cancer dataset. The expression of HDAC8 in osteosarcoma cell lines was detected by western blot. TM-2-51, an activator of HDAC8, was taken to promote HDAC8 expression in osteosarcoma cells. Cell Counting Kit-8 (CCK-8) assay was applied to analyze cell viability changes and colony formation while 5-ethynyl-29-deoxyuridine (EdU) assays were used to evaluate cell proliferation. The migration and invasion abilities were analyzed by transwell assay, the distributions of cell cycle were analyzed by flow cytometry, and xenograft models were used to study the effect of HDAC8 activation in vivo. Furthermore, the mechanism underlying HDAC8's influence in osteosarcoma was analyzed by western blot assay.

RESULTS

Our study demonstrated that activation of HDAC8 in osteosarcoma cells can suppress cell viability, proliferation, migration, invasion, and arrest cell cycle of the osteosarcoma cells via TP53 and STAT3/ERK signaling pathway. Xenograft models confirmed that HDAC8 activation can reduce tumor growth in vivo.

CONCLUSION

The activation of HDCA8 could contribute negatively to osteosarcoma proliferation, and HDAC8 may represent a valuable therapeutic target in osteosarcoma therapy.

The impact of a complex school nutrition intervention on double burden of malnutrition among Thai primary school children: a 2-year quasi-experiment

OBJECTIVE

This study assessed the impacts of the Dekthai Kamsai programme on overweight/obesity, underweight and stunting among male and female primary school students.

STUDY DESIGN

A quasi-experiment was conducted in 16 intervention and 19 control schools across Thailand in 2018 and 2019. In total, 896 treated and 1779 control students from grades 1 to 3 were recruited. In intervention schools, a set of multifaceted intervention components were added into school routine practices. Anthropometric outcomes were measured at baseline and at the beginning and end of every school term.

METHODS

Propensity score matching with linear and Poisson difference-in-difference analyses were used to adjust for the non-randomisation and to analyse the intervention's effects over time.

RESULTS

Compared with controls, the increases in mean BMI-for-age Z-score (BAZ) and the incidence rate of overweight/obesity were lower in the intervention schools at the 3rd, 4th and 8th measurements and the 3rd measurement, respectively. The decrease in mean height-for-age Z-score (HAZ) was lower at the 4th measurement. The decrease in the incidence rate of wasting was lower at the 5th, 7th and 8th measurements. The favourable impacts on BAZ and HAZ were found in both sexes, while the favourable impact on overweight/obesity and unfavourable impact on wasting were found in girls.

CONCLUSIONS

This intervention might be effective in reducing BAZ, overweight/obesity, poor height gain, but not wasting. These findings highlight the benefits of a multifaceted school nutrition intervention and a need to incorporate tailor-made interventions for wasting to comprehensively address the double burden of malnutrition.

Quantification of human embryonic ζ-globin chains in Southeast Asian deletion (--SEA) carriers

AIMS

Reactivation of embryonic ζ-globin is a promising strategy for genetic treatment of α-thalassaemia. However, quantification of ζ-globin as a quantitative trait in α-thalassaemia carriers and patients remains incompletely understood. In this study, we aimed to set up a reliable approach for the quantification of ζ-globin in α-thalassaemia carriers, followed by a population study to investigate its expression patterns.

METHODS

ζ-globin was purified as monomers from cord blood haemolysate of a Hb Bart's fetus, followed by absolute protein quantification, which was then tested by in-house ELISA system and introduced as protein standard. It was then used for large-scale quantification in peripheral blood samples from 6179 individuals. Finally, liquid chromatography-tandem mass spectrometry (LC-MS/MS) introduced as an independent validating approach by measuring ζ-globin expression in a second cohort of 141-SEA/αα carriers.

RESULTS

The ELISA system was proved sensitive in distinguishing individuals with varied extent of ζ-globin. Large scale quantitative study of this --SEA/αα carrier cohort indicated the high diversity of ζ-globin expression ranging from 0.00155 g/L to 1.48778 g/L. Significant positive correlation between ELISA and LC-MS/MS (R=0.400, p<0.001) was observed and it is more sensitive in distinguishing the samples with extreme expression of ζ-globin (R=0.650, p<0.001).

CONCLUSION

Our study has reported reliable approaches for the quantification of ζ-globin and presented the expression patterns of ζ-globin among the --SEA/αα carrier population, which might lay a foundation on subsequent genotype-phenotype studies on mechanisms of delayed haemoglobin switch in α-thalassaemia.

Towards Causality-Aware Inferring: A Sequential Discriminative Approach for Medical Diagnosis

Medical diagnosis assistant (MDA) aims to build an interactive diagnostic agent to sequentially inquire about symptoms for discriminating diseases. However, since the dialogue records for building a patient simulator are collected passively, the collected records might be deteriorated by some task-unrelated biases, such as the preference of the collectors. These biases might hinder the diagnostic agent to capture transportable knowledge from the simulator. This work identifies and resolves two representative non-causal biases, i.e., (i) default-answer bias and (ii) distributional inquiry bias. Specifically, Bias (i) originates from the patient simulator which tries to answer the unrecorded inquiries with some biased default answers. To eliminate this bias and improve upon a well-known causal inference technique, i.e., propensity score matching, we propose a novel propensity latent matching in building a patient simulator to effectively answer unrecorded inquiries; Bias (ii) inherently comes along with the passively collected data that the agent might learn by remembering what to inquire within the training data while not able to generalize to the out-of-distribution cases. To this end, we propose a progressive assurance agent, which includes the dual processes accounting for symptom inquiry and disease diagnosis respectively. The diagnosis process pictures the patient mentally and probabilistically by intervention to eliminate the effect of the inquiry behavior. And the inquiry process is driven by the diagnosis process to inquire about symptoms to enhance the diagnostic confidence which alters as the patient distribution changes. In this cooperative manner, our proposed agent can improve upon the out-of-distribution generalization significantly. Extensive experiments demonstrate that our framework achieves new state-of-the-art performance and possesses the advantage of transportability.

Alcoholic drink produced by pea is a risk factor for incident knee surgery in patients with knee osteoarthritis

Objective

The objective of this study is to investigate whether alcohol exposure and specific alcoholic drinks are independent risk factors for incident knee surgery in knee osteoarthritis (KOA) patients.

Methods

We identified all patients who were clinically diagnosed as KOA between January 2010 and January 2018 in our outpatient department. Demographic, clinical, and radiographic data were collected from the database of our hospital. Next, we analyzed the association between alcohol consumption and incident knee surgery.

Results

A total of 4,341 KOA patients completed the current study and were included in the final analysis. Incident knee surgery for the purpose of treating osteoarthritis was observed in 242 patients. Incident knee surgery was significantly associated with age (OR [95%CI], 1.023 [1.009-1.039], P = 0.002), BMI (OR [95%CI], 1.086 [1.049-1.123], P < 0.001), baseline K-L grade 3 (OR [95%CI], 1.960 [1.331-2.886], P = 0.001), baseline K-L grade 4 (OR [95%CI], 1.966 [1.230-3.143], P = 0.005), 7.1-14 drinks per week (OR [95%CI], 2.013 [1.282-3.159], P = 0.002), >14 standard drinks per week (OR [95%CI], 2.556 [1.504-4.344], P = 0.001), and the most common alcoholic drink produced by pea (OR [95%CI], 3.133 [1.715-5.723], P < 0.001).

Conclusion

KOA patients who consumed more than seven standard drinks per week were at substantial risk of incident knee surgery. In addition, alcoholic drink produced by pea is also an independent risk factor.

Identification and Automated Delineation of Radioresistant Biological Tumor Volume in Nasopharyngeal Carcinoma Based on Magnetic Resonance Imaging Radiomics

PURPOSE/OBJECTIVE(S)

Widespread use of intensity modulated radiotherapy (IMRT) has improved the tumor control rate of nasopharyngeal carcinoma (NPC). However, nearly 20% of the patients with local-advanced NPC would relapse after precise irradiation and 80% of the recurrent lesions occur within the high dose field, suggesting that there are radiation-resistant cancer cell subsets within the tumor. In this context, identification and contouring of radiation resistance region of NPC for dose escalation at primary IMRT could be advantageous. In this work, we proposed a two-step radiomics workflow to predict local relapse and the recurrent region of NPC before primary IMRT.

MATERIALS/METHODS

In this single-center, retrospective study, pre-treatment magnetic resonance (MR) sequences of T1-weighted imaging (T1-w) and contrast-enhanced T1-weighted imaging (CET1-w) were collected from 800 patients of newly diagnosed and non-metastatic NPC between April 2009 and December 2015. The primary gross tumor volume (GTVp) of all patients and the actual recurrent lesion (GTVr) of patients who suffered from local recurrence were manually contoured for further analysis. A two-step complete radiomics workflow was designed to predict tumor recurrence and segment the region. First, least absolute shrinkage and selection operator (LASSO) was utilized for radiomics features selection of GTVp and support vector machine (SVM) was adopted to predict the recurrence. If the model predicts a recurrence, then the workflow utilizes an improved 3D U-Net to segment the recurrent region. Area under receiver operating characteristic curve (ROC-AUC) was used to evaluate the performance of tumor recurrence prediction, and Dice similarity coefficient (DSC) was used to assess the consistence between the actual and predicted GTVr.

RESULTS

Of 800 NPC patients, 95 (11.9%) patients developed in-field local recurrence. For recurrence risk prediction, the SVM ensemble model (T1-w+CET1-w) was selected for further application with higher sensitivity. The average ROC-AUC, specificity, sensitivity of the SVM ensemble model in a 5-fold cross-validation and in the independent test set of 160 patients were 0.922, 0.922, 0.777 and 0.928, 0.915, 0.737, respectively. Moreover, for recurrent region segmentation, the multi-modality (T1-w+CET1-w) model was superior to the single-modality (T1-w or CET1-w) model. In an independent test set of 15 patients, the DSC, sensitivity and 95% Hausdorff Distance between actual and predicted GTVr was 0.549±0.176, 0.696±0.118 and 9.813±4.788 which was superior to 0.444±0.188, 0.497±0.218 and 12.047±5.361 of original 3D U-Net.

CONCLUSION

The proposed two-step radiomics workflow showed a good performance in predicting tumor recurrence of NPC. The predicted location of the recurrence lesion was all accurate, but there was still a certain difference between the volume of the automated delineated and actual GTVr, which needed to be further optimized to be used as biological tumor volume.

Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering

Existing visual question answering methods often suffer from cross-modal spurious correlations and oversimplified event-level reasoning processes that fail to capture event temporality, causality, and dynamics spanning over the video. In this work, to address the task of event-level visual question answering, we propose a framework for cross-modal causal relational reasoning. In particular, a set of causal intervention operations is introduced to discover the underlying causal structures across visual and linguistic modalities. Our framework, named Cross-Modal Causal RelatIonal Reasoning (CMCIR), involves three modules: i) Causality-aware Visual-Linguistic Reasoning (CVLR) module for collaboratively disentangling the visual and linguistic spurious correlations via front-door and back-door causal interventions; ii) Spatial-Temporal Transformer (STT) module for capturing the fine-grained interactions between visual and linguistic semantics; iii) Visual-Linguistic Feature Fusion (VLFF) module for learning the global semantic-aware visual-linguistic representations adaptively. Extensive experiments on four event-level datasets demonstrate the superiority of our CMCIR in discovering visual-linguistic causal structures and achieving robust event-level visual question answering.

Analysis of maternal and fetal outcomes and establishment of prediction model of vaginal delivery in pregnant women with pre-eclampsia complicated with fetal growth restriction

OBJECTIVE

This study aimed to analyze the maternal and fetal outcomes of pregnant women with pre-eclampsia (PE), complicated with fetal growth restriction (FGR), and establish a prediction model of vaginal delivery to guide the selection of the delivery mode.

PATIENTS AND METHODS

The study included 208 pregnant women with PE complicated with FGR. Of them, 49 patients were in the vaginal delivery group, and 159 patients were in the cesarean section group. The relevant maternal and fetal outcomes were analyzed. Patients were randomly divided into the training sample group and the test group with a ratio of 2:1. The three-layer neural network was used to select 24 maternal and infant outcome factors as the input nodes of the neural network to build a vaginal delivery prediction model.

RESULTS

Results showed that the gestational age, the highest systolic and diastolic blood pressure, body weight, body length, and placental weight of the newborns in the vaginal delivery group were significantly higher than those in the cesarean section group. Incidence of preterm birth, amniotic fluid grade III, oligohydramnios, and severe small-for-gestational-age (sSGA) neonates were significantly lower in the vaginal delivery group compared to the cesarean section group (p < 0.05). A three-layer neural network delivery prediction model was constructed, and the accuracy rate of fitting with test samples was 91.80%.

CONCLUSIONS

There is no significant difference in the incidence of maternal and fetal complications in PE complicated with FGR in different delivery methods. The three-layer neural network prediction model has good prediction ability for vaginal delivery of PE complicated with FGR and may be applied in clinical practice.

Watching intense movies increase IOP of primary open angle glaucoma patients: A prospective study

PURPOSE

To investigate intraocular pressure (IOP) changes while viewing smartphone movies under artificial intelligence (AI) monitoring.

METHODS

In all, 48 subjects were recruited from the glaucoma clinic of Xianyou maternal and child health hospital from January 2018 to March 2020. The research consisted of three parts. In part 1, movies rated by the Motion Picture Association of America (MPAA) were viewed via smartphones of various screen sizes under AI supervision for 90minutes, at a distance of 40cm. IOP and biological parameters including anterior chamber angle, Schlemm's canal (SC) cross-sectional area, heart rate, systolic and diastolic blood pressures (SBP and DBP) were measured and analyzed. In part 2, blue-blocking glasses (BB glasses) were worn to repeat the above experiments. In part 3, the efficacy of AI in decreasing attention loss was analyzed. In addition, results were analyzed to determine whether interval breaks, prompted by AI, prevented IOP from rising.

RESULTS

In part 1, the mean IOP of primary open angle glaucoma (POAG) subjects' right eyes significantly increased by 4.828 and 4.974mmHg after watching R and NC-17 movies, respectively. In their left eyes, it increased by 2.876 and 5.767 after watching R and NC-17 movies, respectively. The maximum IOP difference was also increased by 4.782 and 4.510 on right and left eyes, respectively, after viewing NC-17 movies on a 6.1-inch screen. Furthermore, the SC became narrower, whereas heart rate, DBP and SBP increased in the POAG group. In addition, maximum IOP difference was significantly correlated with SC cross-sectional area, DBP and SBP in the POAG group. In part 2, symptom scores were improved by BB glasses; however, IOP was not decreased. In part 3, attention loss was significantly decreased by AI monitoring. On the contrary, AI also prevented IOP from rising via promoting interval rest.

CONCLUSION

Watching adult movies (NC-17) can significantly increase the IOP of POAG patients. AI can prevent IOP from rising by promoting interval rest when viewing NC-17 movies.

All-in-One Online Radiotherapy for Nasopharyngeal Carcinoma: Preliminary Results of Treatment Time, Contouring Accuracy, Treatment Plan Quality and Patient Compliance

PURPOSE/OBJECTIVE(S)

To explore the feasibility of Fan-beam CT (FBCT)-based all in one (AIO) online workflow for nasopharyngeal carcinoma (NPC) in radical radiotherapy setting, and to preliminarily describe the timing of different steps in the process, contouring accuracy of regions of interest (ROIs), target coverage, organs at risk (OARs) dose and patient compliance.

MATERIALS/METHODS

From March 16, 2022 to January 04, 2023, 25 NPC patients (22/25 diagnosed as phase III/IV disease according to 8th edition of the AJCC/UICC staging system) consecutively treated with AIO radiotherapy were prospectively enrolled. All patients received mask fixation and MRI simulation scan in advance. Primary gross tumor volume (GTVp) of nasopharynx was automatically delineated by AI and edited manually on MRI images. AIO online workflow started with an integrated KV-level CT in a CT-integrated linear accelerator. After that GTVp was registrated to CT images and other ROIs was contoured automatically and then modified manually as needed. Subsequently automatic treatment plan was calculated and optimized until the dose of target and OARs was evaluated satisfactory by physicians and physicists. Finally, treatment was delivered using volumetric modulated arc treatment (VMAT), with prescribed dose of 6996 cGy/ 33 fractions to the GTVp.

RESULTS

Twenty-four patients (24/25, 96%) completed the AIO radiotherapy workflow successfully, with average treatment time of 28.3 min (range: 19.9-42.4 min). the AI-assisted ROIs automatically contouring took 1.55 min in average (range: 1.32-1.77 min), with an average DICE of 97.7% compared with modified contouring, and the average DICE was 95.7% for clinical tumor volume 1 (CTV1), 88.6% for CTV2, 73.6% for GTVn (cervical lymph node), 99.3% for 30 OARs. The automatic treatment plan averagely needed 3.5 min, and the pass rate of radiotherapy planning was 91.7% (22/24). The target coverage for PTVs for GTVp, CTV1, and CTV2 was 99.3%, 99.8%, 98.0% respectively. As for the dose of OARs, the average Dmax of brainstem was 5,583cGy; the Dmax of spinal cord was 3,467cGy; the Dmean of parotid was 3,285 cGy. The average monitor units of all patients was 643 MU and the delivery took 2.93 min. Patient compliance with respect to AIO workflow and total treatment time was excellent.

CONCLUSION

The AIO online radiotherapy was promising for NPC patients, with clinically acceptable AI assisted ROIs contouring and treatment planning, as well as favorable patient compliance to the AIO online workflow.

Infantile spasms caused by NEXMIF mutation: A case report and literature review

BACKGROUND

Infantile spasms are rare epileptic syndromes associated with neurodevelopment and genes. The NEXMIF gene, identified as KIDLIA, KIAA2022 or Xpn, is a gene of unknown biological identity located on the q13.2 X chromosome.

CASE DESCRIPTION

We presented a 4-month-old infant with a diagnosis of infantile spasms with NEXMIF mutation. Clinical manifestations include psychomotor retardation, loss of consciousness, and seizures. After oral therapy with vigabatrin, sodium valproate, and levetiracetam, the syndrome was alleviated and no recurrence was observed during one month of follow-up.

CONCLUSIONS

A loss-of-function mutation in the NEXMIF gene has been reported. There are few reports on this mutation worldwide. This study provides a new idea for the clinical treatment of infantile spasms.

Automated Contouring of Cervical Lymph Nodes and Clinical Target Volumes for Nasopharyngeal Carcinoma Based on Deep Learning and Experience Constraints

PURPOSE/OBJECTIVE(S)

Application of artificial intelligence (AI) for automated contouring of tumor volumes and organs at risk (OARs) for radiotherapy of nasopharyngeal carcinoma (NPC) leads to improved contouring accuracy and efficiency. However, few studies have involved the automated contouring of gross tumor volume of cervical lymph nodes (GTVn) and clinical target volumes (CTVs). In this work, we proposed an AI automated contouring tool for GTVn and CTVs for radiotherapy of NPC on the plain scans of planning compute tomography (CT).

MATERIALS/METHODS

In this retrospective study, plain scan datasets of planning CT covering the nasopharynx and neck from 139 patients with NPC between March 2022 and December 2022 were collected and divided into training, validation, and testing cohorts of 95, 24, and 20 patients, respectively. Ground truth contours of primary gross tumor volume (GTVp), GTVn (divided into GTVn_L in left neck and GTVn_R in right neck), CTVs (including high risk CTV1 contains GTVp and low risk CTV2 contains GTVp and cervical nodal levels) and OARs were delineated and were defined by consensus of two experts. We first proposed a three-dimensional (3D) U-net using GTVp and OARs as experience constrains to guide the automated delineation of GTVn and CTVs. The average Dice similarity coefficient (DSC) and average surface distance (ASD) were used to quantify the performance of the AI tool. Next, five prospective patients were enrolled for clinical evaluation of our AI tool. DSC between automated contours and radiation oncologist-revised contours and time consuming of the revision were record.

RESULTS

Clinical characteristics of 139 retrospective and 5 prospective patients are list in Table 1. In the independent testing set of 20 patients, our AI tool showed high performance in GTVn and CTVs contouring when compared with the ground truth contours. The mean DSC were 0.73 ± 0.07, 0.74 ± 0.05, 0.93 ± 0.03, and 0.88 ± 0.03, and the mean ASD were 1.01 ± 0.43 mm, 1.14 ± 0.61 mm, 0.51 ± 0.13 mm, 1.17 ± 0.43 mm for GTVn_L, GTVn_R, CTV1 and CTV2, respectively. In the five prospective patients, mean DSC were 0.74 ± 0.07, 0.74 ± 0.10, 0.95 ± 0.01 and 0.89 ± 0.04, respectively. The median time consuming for GTVn and CTVs revision was 2minutes and 10 seconds (range, 1 minutes to 3 minutes).

CONCLUSION

The proposed AI tool integrating clinical experience as constrains showed high accuracy for contouring GTVn and CTVs of NPC. With the assistance of AI contours, contouring efficiency could be probably increased, which is promising in online adaptive radiotherapy of NPC.

First Implementation of Full-Workflow Automation for Online Adaptive Radiotherapy of Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

The aim of this work is to established the technical characteristics and implementation procedures of an artificial intelligence (AI)-powered radiotherapy workflow that enables full-process automation for online adaptive radiotherapy (ART); and evaluate its feasibility and performance implemented for ART of nasopharyngeal carcinoma (NPC).

MATERIALS/METHODS

This single center, prospective study has been approved by the ethical committee of the institution. The online ART workflow was developed based on a CT-integrated linear accelerator. During the course of radiotherapy, the patient underwent daily pre-treatment fan-beam CT (FBCT) scan. Then the FBCT was automatically registered to the original planning CT and used to assess the need for the patient to implement ART according to radiation oncologist's discretionary. The online ART workflow incorporates critical radiotherapy procedures from re-simulation, auto-segmentation by integrating image fusion and deep learning method, auto-replanning, beam delivery, and in vivo quality assurance (QA) into one scheme, while the patient is on the treatment couch during the whole process.

RESULTS

From 2th April 2022 to 5th January 2023, 20 patients with newly-diagnosed, non-metastatic NPC were enrolled in this study. Only one-time online ART was performed for each patient, because that the appropriate timing for triggering online ART was explored in parallel with this study. According to radiation oncologists' discretionary, the median fraction for performing online ART was at 21 fractions (interquartile range, 19-24 fractions). All patients were well tolerated and successfully completed the treatment. For tumor targets contouring, minor revisions were required for automated contours of the primary gross tumor volume (GTVp) and clinical target volumes (CTVs, including CTV1 and CTV2), with the mean DSC between before and after revision of 0.91±0.042, 0.94 ± 0.042 and 0.91 ± 0.061, respectively; and much more revisions for the automated contours of cervical lymph nodes GTV (GTVn), with the mean DSC of 0.74 ± 0.28. The automated contours of normal tissues were clinically acceptable with little modifications. Median time consuming for auto-segmentation and revision was 9.5 minutes (min). For treatment planning, 18 automated plans (90%) were passed at their first auto-optimization and two plans (10%) were passed after further optimization of the dose coverage of CTVs by physicist; and the median time consuming for auto-planning was 6.2 min. Time consuming for other procedures were as follows: re-simulation, 2.3 min; plan evaluation, 3.3 min; beam delivery, 4.6 min; and the duration of the entire process was 25.9 min, range from 19.4 min to 32.5 min.

CONCLUSION

We successfully established an AI-powered online ART workflow for adaptive radiotherapy of NPC, and confirmed that current auto-segmentation and auto-replanning methods are powered enough to support the clinical application of its online ART.

Dosimetric Benefits of Online Adaptive Radiotherapy in Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

Online adaptive radiotherapy (ART) has the advantage of compensating for potential underdosing to targets and overdosing to organs-at-risk (OARs) caused by variations in patient anatomy and tumor geometry. Artificial intelligence (AI)-assisted rapid generation of new plans makes online ART possible. We aimed to evaluate the dosimetric benefits of online ART on tumor coverage and OARs sparing in nasopharyngeal carcinoma (NPC).

MATERIALS/METHODS

Twenty patients diagnosed with NPC (19 with stage III and 1 with stage II according to the 8th edition of the AJCC/UICC staging system) who underwent definitive radiotherapy or concurrent chemoradiotherapy and received online ART on CT-Linac between April 2022 and December 2022 were included in this study, consisting of 14 males and 6 females with a median age of 48 years (range: 29-68 years). The prescription dose was 6996 cGy/33 fractions for primary gross tumor volume (GTVp), 6600-6996 cGy/33 fractions for gross tumor volume of nodes (GTVn), 6006 cGy/33 fractions for high-risk clinical tumor volume (CTV1), 5412 cGy/33 fractions for low-risk clinical tumor volume (CTV2). The majority of the patients (15/20) received online ART during the fourth to fifth week of their radiotherapy treatment The auto-segmented contours and auto-plan generated by AI were manually reviewed and edited by radiotherapists and physicists. The paired samples t-test was used to compare the dose and volumes metrics of targets and OARs between scheduled plan and online ART plan.

RESULTS

The results of this study showed that compared to the scheduled plan, the online ART plan resulted in significant reductions in the volumes of all targets and 8/12 OARs (temporal lobes, optic nerves, lenses, eyes, parotids, submandibulars, mandibles, and thyroid) (P<0.05). The online ART plan also improved target coverage, with D98% for GTVp in the scheduled plan compared to the online ART plan being 7063.4 ± 76.1 cGy and 7096.1 ± 53.9 cGy (P = 0.1), CTV1 being 6266.7 ± 114.9 cGy and 6208.7 ± 54.7 cGy (P<0.05), and CTV2 being 4142.5 ± 1700.9 cGy and 5416.4 ± 23.8 cGy (P<0.01), respectively. The dose to all 12 OARs was reduced with the use of online ART, with 5/12 OARs showing statistical significance. The D0.03cm3 for the spinal cord in the scheduled plan and online ART plan were 3630.9 ± 197.6 and 3454.1 ± 132.0 cGy; for the temporal lobes were 7075.2 ± 303.0 and 6994.2 ± 345.1 cGy; and 4396.0 ± 2575.0 and for the pituitary were 4214.5 ± 2499.2 cGy. Meanwhile the Dmean for the eyes in the scheduled plan and online ART plan was 769.0 ± 232.0 and 714.8 ± 200.1 cGy; and for the mandibles were 3187.7 ± 211.5 and 3066.0 ± 152.1 cGy.

CONCLUSION

Online ART was effective in protecting most of the OARs in NPC patients, while simultaneously indicating a trend towards enhancing target coverage. This study demonstrated the promising potential of online ART for patients with NPC. This approach will be tested in an upcoming phase III trial.

Discourse-Aware Graph Networks for Textual Logical Reasoning

Textual logical reasoning, especially question-answering (QA) tasks with logical reasoning, requires awareness of particular logical structures. The passage-level logical relations represent entailment or contradiction between propositional units (e.g., a concluding sentence). However, such structures are unexplored as current QA systems focus on entity-based relations. In this work, we propose logic structural-constraint modeling to solve the logical reasoning QA and introduce discourse-aware graph networks (DAGNs). The networks first construct logic graphs leveraging in-line discourse connectives and generic logic theories, then learn logic representations by end-to-end evolving the logic relations with an edge-reasoning mechanism and updating the graph features. This pipeline is applied to a general encoder, whose fundamental features are joined with the high-level logic features for answer prediction. Experiments on three textual logical reasoning datasets demonstrate the reasonability of the logical structures built in DAGNs and the effectiveness of the learned logic features. Moreover, zero-shot transfer results show the features' generality to unseen logical texts.

Towards Deviation-Robust Agent Navigation via Perturbation-Aware Contrastive Learning

Vision-and-language navigation (VLN) asks an agent to follow a given language instruction to navigate through a real 3D environment. Despite significant advances, conventional VLN agents are trained typically under disturbance-free environments and may easily fail in real-world navigation scenarios, since they are unaware of how to deal with various possible disturbances, such as sudden obstacles or human interruptions, which widely exist and may usually cause an unexpected route deviation. In this paper, we present a model-agnostic training paradigm, called Progressive Perturbation-aware Contrastive Learning (PROPER) to enhance the generalization ability of existing VLN agents to the real world, by requiring them to learn towards deviation-robust navigation. Specifically, a simple yet effective path perturbation scheme is introduced to implement the route deviation, with which the agent is required to still navigate successfully following the original instruction. Since directly enforcing the agent to learn perturbed trajectories may lead to insufficient and inefficient training, a progressively perturbed trajectory augmentation strategy is designed, where the agent can self-adaptively learn to navigate under perturbation with the improvement of its navigation performance for each specific trajectory. For encouraging the agent to well capture the difference brought by perturbation and adapt to both perturbation-free and perturbation-based environments, a perturbation-aware contrastive learning mechanism is further developed by contrasting perturbation-free trajectory encodings and perturbation-based counterparts. Extensive experiments on the standard Room-to-Room (R2R) benchmark show that PROPER can benefit multiple state-of-the-art VLN baselines in perturbation-free scenarios. We further collect the perturbed path data to construct an introspection subset based on the R2R, called Path-Perturbed R2R (PP-R2R). The results on PP-R2R show unsatisfying robustness of popular VLN agents and the capability of PROPER in improving the navigation robustness under deviation.