Pyramid Pixel Context Adaption Network for Medical Image Classification With Supervised Contrastive Learning.

Spatial attention (SA) mechanism has been widely incorporated into deep neural networks (DNNs), significantly lifting the performance in computer vision tasks via long-range dependency modeling. However, it may perform poorly in medical image analysis. Unfortunately, the existing efforts are often unaware that long-range dependency modeling has limitations in highlighting subtle lesion regions. To overcome this limitation, we propose a practical yet lightweight architectural unit, pyramid pixel context adaption (PPCA) module, which exploits multiscale pixel context information to recalibrate pixel position in a pixel-independent manner dynamically. PPCA first applies a well-designed cross-channel pyramid pooling (CCPP) to aggregate multiscale pixel context information, then eliminates the inconsistency among them by the well-designed pixel normalization (PN), and finally estimates per pixel attention weight via a pixel context integration. By embedding PPCA into a DNN with negligible overhead, the PPCA network (PPCANet) is developed for medical image classification. In addition, we introduce supervised contrastive learning to enhance feature representation by exploiting the potential of label information via supervised contrastive loss (CL). The extensive experiments on six medical image datasets show that the PPCANet outperforms state-of-the-art (SOTA) attention-based networks and recent DNNs. We also provide visual analysis and ablation study to explain the behavior of PPCANet in the decision-making process.

Development, validation and reliability testing of the hospice care environment scale.

BACKGROUND: WHO stated the environment is an important factor affecting the development of hospice care. The environment is the sum of factors affecting behavior besides the individual factors. Currently, a scale to comprehensively assess the hospice environment of nurse is still lacking. This study aimed to develop an instrument to investigate the environmental factors affecting hospice care of nurses. METHODS: Literature review and a semi-structured interview were conducted to form the items pool of the Hospice Care Environment Scale. Two rounds of Delphi expert consultation were conducted by 16 experts to revise the scale dimensions and entries to form the Hospice Care Environment Scale. A psychometric evaluation was then performed among 530 oncology nurses in a large tertiary oncology hospital in Hubei Province. The 500 valid questionnaires were randomly divided into two groups in a 1:1 ratio, sample 1 (n1 = 250) for item screening and sample 2 (n2 = 250) for quality evaluation of the resulting scale. Item analysis, reliability analysis, validity analysis and acceptability analysis were performed. RESULT: The Hospice Care Environment Scale consists of two dimensions and 13 entries. The Cronbach's α coefficient of the Hospice Care Environment Scale was 0.970, and the Cronbach's α coefficient of the two dimensions were 0.952 and 0.969, respectively, with the Item-content validity index and average Scale- content validity index of the scale was both 1.000. The validation factor analysis showed the standardized path coefficients of each item were basically above 0.5, and the factor structure model was stable and suitable. The average completion time of the scale was about 3 min, which had good feasibility. CONCLUSION: The Hospice Care Environment Scale to assess the environment of hospice care services, has good content and construct validity and reliability. This scale can provide guidance to evaluate the hospice care environment.

Robust inference for causal mediation analysis of recurrent event data.

Recurrent events, including cardiovascular events, are commonly observed in biomedical studies. Understanding the effects of various treatments on recurrent events and investigating the underlying mediation mechanisms by which treatments may reduce the frequency of recurrent events are crucial tasks for researchers. Although causal inference methods for recurrent event data have been proposed, they cannot be used to assess mediation. This study proposed a novel methodology of causal mediation analysis that accommodates recurrent outcomes of interest in a given individual. A formal definition of causal estimands (direct and indirect effects) within a counterfactual framework is given, and empirical expressions for these effects are identified. To estimate these effects, a semiparametric estimator with triple robustness against model misspecification was developed. The proposed methodology was demonstrated in a real-world application. The method was applied to measure the effects of two diabetes drugs on the recurrence of cardiovascular disease and to examine the mediating role of kidney function in this process.

Multifunctional Conductive Hydrogel Composites with Nickel Nanowires and Liquid Metal Conductive Highways.

The dramatic growth of smart wearable electronics has generated a demand for conductive hydrogels due to their tunability, stimulus responsiveness, and multimodal sensing capabilities. However, the substantial trade-off between mechanical and electrical properties hinders their multifunctionality. Here, we report a double-network hydrogel composite that features a conductive "highway" constructed using magnetic-field-aligned nickel nanowires and liquid metal. The liquid metal fills the gaps between the aligned nickel nanowires. Such interconnected structures can form efficient conductive paths at low filler content, resulting in high conductivity (1.11 × 104 S/m) and mechanical compliance (Young's modulus, 89 kPa; toughness, 721 kJ/m3). When used as a wearable sensor, the hydrogel displays a high sensitivity and fast response for wireless motion detection and human-machine interaction. Furthermore, by exploiting its outstanding conductivity and electrical heating capacity, the hydrogel integrates electromagnetic shielding and thermal management functionalities. Owing to these all-around properties, our design offers a broader platform for expanding hydrogel applications.

Impact of hyperuricemia and chronic kidney disease on the prevalence and mortality of cardiovascular disease in cancer survivors.

BACKGROUND: The risks of cardiovascular disease (CVD) and CVD mortality are prevalent among cancer survivors (CS) population. The 2022 ESC Guidelines on cardio-oncology have recommended that modifying cardiovascular risk factors (CVRF) could potentially improve long-term outcomes in CS. OBJECTIVES: To identify the independent and joint chronic kidney disease (CKD) associations of hyperuricemia with the incidence of CVD and mortality outcomes among CS. METHODS: Utilizing data from the US National Health and Nutrition Examination Survey spanning 2005-2018, we assessed the risk of CVD through weighted multivariable logistic regression and restricted cubic spline (RCS) regression. Additionally, all-cause and CVD-related mortality were evaluated using weighted multivariable Cox regression and Kaplan-Meier analysis. Subgroup analysis was conducted to further elucidate the interplay between hyperuricemia, CKD, and mortality within the CS population. RESULTS: A total of 3276 CS participants were enrolled in this study. Results showed that hyperuricemia was positively related to the incidence of CVD (OR [95% CI] = 1.86 [1.24, 2.81], p = 0.004). RCS analysis further demonstrated that uric acid levels ≥345 µmol/L positively correlated with CVD incidence (p value for nonlinearity = 0.0013). However, the association between hyperuricemia and CVD mortality, as well as all-cause mortality did not reach statistical significance in the fully adjusted model (HR = 1.48, 95% CI: 0.92-2.39, p = 0.11; HR = 1.11, 95% CI:0.92, 1.34, p = 0.28, respectively). Among CS participants with CKD, hyperuricemia could increase risks of all-cause (HR [95% CI] = 1.39 [1.08, 1.11], p = 0.02) and CVD mortality (HR [95% CI] =2.17 [1.29, 3.66], p = 0.004) after adjusting for sex, age, and ethnicity. CONCLUSIONS: In the CS population, hyperuricemia was positively associated with the incidence of CVD. In addition, CKD might be an intermediate variable among the CS population that mediated the effects of hyperuricemia on mortality.

Construction and validation of a nomogram for predicting remission of migraine patients with patent foramen ovale after closure.

OBJECTIVE: This study aimed to construct and validate a nomogram model that predicts the remission of migraine attacks by screening factors that affect the prognosis of migraine patients with patent foramen ovale (PFO) after closure. METHOD: Retrospective analysis was conducted in migraine patients with PFO who underwent PFO closure in the Department of Cardiology of Jiangsu Province Hospital from September 2020 to April 2023. Based on the Migraine Disability Assessment (MIDAS) scores from the 1-year follow-up after PFO closure, all patients who met the inclusion criteria were categorized into a remission group and a non-remission group. The primary efficacy endpoint was remission of migraine headache. After collecting clinical data, transcranial doppler sonography (TCD) results and MIDAS scores, LASSO (least absolute shrinkage and selection operator) regression and multivariable logistic regression analysis were used to filter variables predictive to migraine remission and construct the nomogram model. The Nomogram's accuracy and consistency were respectively assessed through Receiver Operating Characteristic (ROC) curves and calibration curves. Additionally, an analysis of decision curves (DCA) was conducted to evaluate the clinical utility of this newly developed model. RESULT: A total of 241 consecutive patients were included in the study. The remission group included 21 males and 93 females, with a median age of 39 (30.25,50) years. The non-remission group included 26 males and 101 females, with a median age of 35 (25.5,47.5) years. All Patients were randomly divided into a training cohort and a validation cohort. Multivariable logistic regression analysis showed that 5 independent predictors, including MIDAS before closure (p = 0.0002), mitigating factors (p = 0.0057), number of attacks/month (p = 0.0058), TCD (p = 0.0093) and Platelet Crit (PCT) (p = 0.0351), played a significant role in the prediction of remission of migraine patients with PFO after closure. Based on these independent predictors, the predictive nomogram model of migraine remission in PFO patients was constructed. The application of the nomogram in the training cohort exhibited good discrimination (area under the ROC curve was 0.7763[95% CI 0.7108-0.8418]), which was confirmed in the validation cohort (AUC was 0.704[95% CI 0.5533-0.8547]). The calibration curve showed that the nomogram model demonstrated good calibration performance. Additionally, the decision curve analysis indicated the clinical utility of the nomogram model. CONCLUSION: The construction of the nomogram model had a considerable predictive accuracy for migraine remission in patients after PFO closure, which may provide constructive guidance for clinical decision making.

A Novel Induction-Type Pressure Sensor based on Magneto-Stress Impedance and Magnetoelastic Coupling Effect for Monitoring Hand Rehabilitation.

Visualization of training effectiveness is critical to patients' confidence and eventual rehabilitation. Here, an innovative magnetoinductive pressure sensor is proposed for monitoring hand rehabilitation in stroke hemiplegic patients. It couples the giant magneto and stress-impedance effects of a square spiral amorphous wire with the giant magnetoelastic effect of a polymer magnet (NdFeB@PDMS). The addition of the magnetoelastic layer results in a sensitivity improvement of 178%, a wide sensing range (up to 1 MPa), fast response/recovery times (40 ms), and excellent mechanical robustness (over 15 000 cycles). Further integration with an LC oscillation circuit enables frequency adjustment into the MHz range resulting in a sensitivity of 6.6% kPa-1 and outstanding linearity (R2 =  0.99717) over a stress range of up to 100 kPa. When attached to a commercial split-fingerboard, the sensor is capable of dynamically monitoring the force in each finger, providing a reading of the rehabilitation process. Unlike conventional inductive sensors, the sensor is based on an inductive force-responsive material (amorphous wire), which significantly boosts the sensitivity. The approach also demonstrates the potential of magnetoelasticity in static pressure sensing, which is highly sensitive to dynamic pressure only through electromagnetic induction. This makes it more suitable for long-term and continuous human health monitoring.

Chitosan oligosaccharide-functionalized nano-prodrug for cascade chemotherapy through oxidative stress amplification.

Redox nanoparticles have been extensively developed for chemotherapy. However, the intracellular oxidative stress induced by constant aberrant glutathione (GSH), reactive oxygen species (ROS) and gamma-glutamyl transpeptidase (GGT) homeostasis remains the primary cause of evading tumor apoptosis. Herein, an oxidative stress-amplification strategy was designed using a pH-GSH-H2O2-GGT sensitive nano-prodrug for precise synergistic chemotherapy. The disulfide bond- conjugated doxorubicin prodrug (DOX-ss) was constructed as a GSH-scavenger. Then, phenylboronic acid (PBA), DOX-ss and poly (γ-glutamic acid) (γ-PGA) were successively conjugated using chitosan oligosaccharide (COS) to obtain the nano-prodrug PBA-COS-ss-DOX/γ-PGA. The PBA-COS-ss-DOX/γ-PGA prodrug could tightly attach to the polymer chain segment by atom transfer radical polymerization. Simultaneously, the drug interacted relatively weakly with the polymer by encapsulating ionic crosslinkers in DOX@PBA-COS/γ-PGA. The disulfide bond of the DOX-ss prodrug as a GSH-scavenger could be activated using overexpressed GSH to release DOX. Particularly, PBA-COS-ss-DOX/γ-PGA could prevent premature drug leakage and facilitate DOX delivery by GGT-targeting and intracellular H2O2-cleavable linker in human hepatocellular carcinoma (HepG2) cells. Concurrently, the nano-prodrug induced strong oxidative stress and tumor cell apoptosis. Collectively, the pH-GSH-H2O2-GGT responsive nano-prodrug shows potential for synergistic tumor therapy.

Delayed Commissuroplasty Increases Interincisal Distance in Buccogingival Cancer Patients Treated with Free Flap Reconstruction of the Oral Commissure.

BACKGROUND: Oral cavity cancers requiring excision of the oral commissure and free flap reconstruction often requires commissuroplasty to manage oral incontinence. We aimed to evaluate the implications of primary versus delayed commissuroplasty on drooling, and interincisal distance outcomes in this cohort. METHODS: A retrospective query of head and neck cancer patients operated by a single surgeon from 2017 to 2020 was performed. Patients were included if they underwent free flap reconstruction of the oral commissure, had an immediate or delayed commissuroplasty, and had 2 years of follow-up data including Thomas-Stonell and Greenberg drooling rating scales and interincisal distance measurements. RESULTS: Thirty-five patients were included in the review. Twelve patients received immediate commissuroplasty and 23 patients had delayed commissuroplasty. Interincisal distance was similar at baseline, although significantly varied between immediate and delayed commissuroplasty groups at 1 month and 2 years postoperative. Drooling scores were significantly elevated in the group treated with delayed commissuroplasty, but eventually normalized after staged surgery and follow-up. Patients treated with adjunct radiation therapy had lower interincisal distance than patients who did not have radiation. CONCLUSION: Delayed commissuroplasty increased interincisal distance and normalize drooling in patients who required full-thickness excision of the buccal mucosa and oral commissure and free tissue reconstruction. The presented data can help to educate patients on expected postoperative outcomes and likely advocates for a second-stage procedure after completion of adjunct radiotherapy to achieve optimal commissural placement and oral competence.

Albumin and C-reactive protein as diagnostic markers for neonatal sepsis: a retrospective study.

OBJECTIVE: To assess the applicability of albumin (ALB) and C-reactive protein (CRP) concentrations in the diagnosis of sepsis in neonates on the day of admission, and to help with early identification and intervention in the development of sepsis. METHODS: This retrospective study included all neonates who were admitted to the neonatal intensive care unit from January 2020 to June 2023. We studied 160 full-term neonates, including 80 with sepsis and 80 healthy controls. A multivariate analysis was conducted to evaluate the associations between ALB, CRP, and sepsis. RESULTS: CRP concentrations were significantly higher in neonates with sepsis than in controls (26.5 ± 8.6 vs. 3.6 ± 1.2 ng/L). At a cut-off point of 10.8 ng/L, CRP showed a sensitivity of 74.3% and a specificity of 80%. Moreover, ALB concentrations were significantly lower in neonates with sepsis than in controls (25.4 ± 2.5 g/L vs. 29.2 ± 2.6 g/L). At a cut-off point of 26.8, ALB showed a sensitivity of 75.6% and a specificity of 84.2%. CONCLUSIONS: Our findings suggest that ALB and CRP concentrations on the first day of admission are different between neonates who do and those who do not develop sepsis. Higher CRP concentrations and lower ALB concentrations may indicate an increased risk of sepsis.

Thyroid ultrasound diagnosis improvement via multi-view self-supervised learning and two-stage pre-training.

Thyroid nodule classification and segmentation in ultrasound images are crucial for computer-aided diagnosis; however, they face limitations owing to insufficient labeled data. In this study, we proposed a multi-view contrastive self-supervised method to improve thyroid nodule classification and segmentation performance with limited manual labels. Our method aligns the transverse and longitudinal views of the same nodule, thereby enabling the model to focus more on the nodule area. We designed an adaptive loss function that eliminates the limitations of the paired data. Additionally, we adopted a two-stage pre-training to exploit the pre-training on ImageNet and thyroid ultrasound images. Extensive experiments were conducted on a large-scale dataset collected from multiple centers. The results showed that the proposed method significantly improves nodule classification and segmentation performance with limited manual labels and outperforms state-of-the-art self-supervised methods. The two-stage pre-training also significantly exceeded ImageNet pre-training.

Review on ultrasonic technology enhanced biological treatment of wastewater.

As a clean, sustainable and efficient technology of wastewater treatment, ultrasonic irradiation has gained special attention in wastewater treatment. It has been widely studied for degrading pollutants and enhancing biological treatment processes for wastewater treatment. This review focuses on the mechanism and updated information of ultrasonic technology to enhance biological treatment of wastewater. The mechanism involved in improving biological treatment by ultrasonic includes: 1) degradation of refractory substances and release carbon from sludges, 2) promotion of mass transfer and change of cell permeability, 3) facilitation of enzyme-catalyzed reactions and 4) influence of cell growth. Based on the above discussion, the effects of ultrasound on the enhancement of wastewater biological treatment processes can be categorized into indirect and direct ways. The indirect effect of ultrasonic waves in enhancing biological treatment is mainly achieved through the use of high-intensity ultrasonic waves. These waves can be used as a pretreatment to improve biodegradability of the wastewater. Moreover, the ultrasonic-treated sludge or its supernatant can serve as a carbon source for the treatment system. Low-intensity ultrasound is often employed to directly enhance the biological treatment of wastewater. The propose of this process is to improve activated sludge, domesticate polyphosphate-accumulating organisms, ammonia-oxidizing bacteria, and anammox bacteria, and achieve speedy start-up of partial nitrification and anammox. It has shown remarkable effects on maintaining stable operation, tolerating adverse conditions (i.e., low temperature, low C/N, etc.), resisting shock load (i.e., organic load, toxic load, etc.), and collapse recovery. These results indicate a promising future for biological wastewater treatment. Furthermore, virous ultrasonic reactor designs were presented, and their potential for engineering application was discussed.

Heterocyclic-Modified Imidazoquinoline Derivatives: Selective TLR7 Agonist Regulates Tumor Microenvironment against Melanoma.

Immunotherapy targeting the toll-like receptor 7 (TLR7) is a promising strategy for cancer treatment. Herein, we describe the design and synthesis of a series of imidazoquinoline-based TLR7 agonists and assess NF-κB pathway activation using HEK-Blue hTLR7 cells to identify the most potent small-molecule TLR7 agonist, SMU-L11 (EC50 = 0.024 ± 0.002 µM). In vitro experiments demonstrated that SMU-L11 specifically activated TLR7, resulting in recruitment of the MyD88 adaptor protein and activation of the NF-κB and MAPK signaling pathways. Moreover, SMU-L11 was found to exert immune-enhancing effects by significantly inducing the secretion of proinflammatory cytokines in murine dendritic cells, macrophages, and human peripheral blood mononuclear cells while promoting M1 macrophage polarization. In vivo studies using a B16-F10 mouse tumor model showed that SMU-L11 significantly enhanced immune cell activation and augmented CD4+ T and CD8+ T-cell proliferation, directly killing tumor cells and inhibiting tumor growth.

Thrombospondin-1 promotes mechanical stress-mediated ligamentum flavum hypertrophy through the TGFß1/Smad3 signaling pathway.

Lumbar spinal canal stenosis is primarily caused by ligamentum flavum hypertrophy (LFH), which is a significant pathological factor. Nevertheless, the precise molecular basis for the development of LFH remains uncertain. The current investigation observed a notable increase in thrombospondin-1 (THBS1) expression in LFH through proteomics analysis and single-cell RNA-sequencing analysis of clinical ligamentum flavum specimens. In laboratory experiments, it was demonstrated that THBS1 triggered the activation of Smad3 signaling induced by transforming growth factor ß1 (TGFß1), leading to the subsequent enhancement of COL1A2 and α-SMA, which are fibrosis markers. Furthermore, experiments conducted on a bipedal standing mouse model revealed that THBS1 played a crucial role in the development of LFH. Sestrin2 (SESN2) acted as a stress-responsive protein that suppressed the expression of THBS1, thus averting the progression of fibrosis in ligamentum flavum (LF) cells. To summarize, these results indicate that mechanical overloading causes an increase in THBS1 production, which triggers the TGFß1/Smad3 signaling pathway and ultimately results in the development of LFH. Targeting the suppression of THBS1 expression may present a novel approach for the treatment of LFH.

Lysine acetyltransferase 6A maintains CD4+ T cell response via epigenetic reprogramming of glucose metabolism in autoimmunity.

Augmented CD4+ T cell response in autoimmunity is characterized by extensive metabolic reprogramming. However, the epigenetic molecule that drives the metabolic adaptation of CD4+ T cells remains largely unknown. Here, we show that lysine acetyltransferase 6A (KAT6A), an epigenetic modulator that is clinically associated with autoimmunity, orchestrates the metabolic reprogramming of glucose in CD4+ T cells. KAT6A is required for the proliferation and differentiation of proinflammatory CD4+ T cell subsets in vitro, and mice with KAT6A-deficient CD4+ T cells are less susceptible to experimental autoimmune encephalomyelitis and colitis. Mechanistically, KAT6A orchestrates the abundance of histone acetylation at the chromatin where several glycolytic genes are located, thus affecting glucose metabolic reprogramming and subsequent CD4+ T cell responses. Treatment with KAT6A small-molecule inhibitors in mouse models shows high therapeutic value for targeting KAT6A in autoimmunity. Our study provides novel insights into the epigenetic programming of immunometabolism and suggests potential therapeutic targets for patients with autoimmunity.

Analyzing COVID-19 and Air Pollution Effects on Pediatric Asthma Emergency Room Visits in Taiwan.

(1) Background: An asthma exacerbation that is not relieved with medication typically requires an emergency room visit (ERV). The coronavirus disease 2019 (COVID-19) pandemic began in Taiwan in January of 2020. The influence of the COVID-19 pandemic on pediatric ERVs in Taiwan was limited. Our aim was to survey pediatric asthma ERVs in the COVID-19 era; (2) Methods: Data were collected from the health quality database of the Taiwanese National Health Insurance Administration from 2019 to 2021. Air pollution and climatic factors in Taipei were used to evaluate these relationships. Changes in the rates of pediatric asthma ERVs were assessed using logistic regression analysis. Poisson regression was used to evaluate the impact of air pollution and climate change; (3) Results: The rate of pediatric asthma ERVs declined in different areas and at different hospital levels including medical centers, regional and local hospitals. Some air pollutants (particulate matter ≤ 2.5 µm, particulate matter ≤ 10 µm, nitrogen dioxide, and carbon monoxide) reduced during the COVID-19 lockdown. Ozone increased the relative risk (RR) of pediatric asthma ERVs during the COVID-19 period by 1.094 (95% CI: 1.095-1.12) per 1 ppb increase; (4) Conclusions: The rate of pediatric asthma ERVs declined during the COVID-19 pandemic and ozone has harmful effects. Based on these results, the government could reduce the number of pediatric asthma ERVs through healthcare programs, thereby promoting children's health.

Unravelling the mechanisms of underweight in Parkinson's disease by investigating into the role of gut microbiome.

Approximately half of patients with Parkinson's disease (PD) suffer from unintentional weight loss and are underweight, complicating the clinical course of PD patients. Gut microbiota alteration has been proven to be associated with PD, and recent studies have shown that gut microbiota could lead to muscle wasting, implying a possible role of gut microbiota in underweight PD. In this study, we aimed to (1) investigate the mechanism underlying underweight in PD patients with respect to gut microbiota and (2) estimate the extent to which gut microbiota may mediate PD-related underweight through mediation analysis. The data were adapted from Hill-Burns et al., in which 330 participants (199 PD, 131 controls) were enrolled in the study. Fecal samples were collected from participants for microbiome analysis. 16S rRNA gene sequence data were processed using DADA2. Mediation analysis was performed to quantify the effect of intestinal microbial alteration on the causal effect of PD on underweight and to identify the key bacteria that significantly mediated PD-related underweight. The results showed that the PD group had significantly more underweight patients (body mass index (BMI) < 18.5) after controlling for age and sex. Ten genera and four species were significantly different in relative abundance between the underweight and non-underweight individuals in the PD group. Mediation analysis showed that 42.29% and 37.91% of the effect of PD on underweight was mediated through intestinal microbial alterations at the genus and species levels, respectively. Five genera (Agathobacter, Eisenbergiella, Fusicatenibacter, Roseburia, Ruminococcaceae_UCG_013) showed significant mediation effects. In conclusion, we found that up to 42.29% of underweight PD cases are mediated by gut microbiota, with increased pro-inflammatory bacteria and decreased SCFA-producing bacteria, which indicates that the pro-inflammatory state, disturbance of metabolism, and interference of appetite regulation may be involved in the mechanism of underweight PD.

A modified U-net with graph representation for dose prediction in esophageal cancer radiotherapy plans.

The manual design of esophageal cancer radiotherapy plan is time-consuming and labor-intensive. Automatic planning (AP) is prevalent nowadays to increase physicists' work efficiency. Because of the intuitiveness of dose distribution in AP evaluation, obtaining reasonable dose prediction provides effective guarantees to generate a satisfactory AP. Existing fully convolutional network-based methods for predicting dose distribution in esophageal cancer radiotherapy plans often capture features in a limited receptive field. Additionally, the correlations between voxel pairs are often ignored. This work modifies the U-net architecture and exploits graph convolution to capture long-range information for dose prediction in esophageal cancer plans. Meanwhile, attention mechanism gets correlations between planning target volume (PTV) and organs at risk, and adaptively learns their feature weights. Finally, a novel loss function that considers features between voxel pairs is used to highlight the predictions. 152 subjects with prescription doses of 50 Gy or 60 Gy are collected in this study. The mean absolute error and standard deviation of conformity index, homogeneity index, and max dose for PTV achieved by the proposed method are 0.036 ± 0.030, 0.036 ± 0.027, and 0.930 ± 1.162, respectively, which outperform other state-of-the-art models. The superior performance demonstrates that our proposed method has great potential for AP generation.

Discovery of Taurocholic Acid Sodium Hydrate as a Novel Repurposing Drug for Intervertebral Disc Degeneration by Targeting MAPK3.

OBJECTIVE: Nowadays, more than 90% of people over 50 years suffer from intervertebral disc degeneration (IDD), but there are exist no ideal drugs. The aim of this study is to identify a new drug for IDD. METHODS: An approved small molecular drug library including 2040 small molecular compounds was used here. We found that taurocholic acid sodium hydrate (NAT) could induce chondrogenesis and osteogenesis in mesenchymal stem cells (MSCs). Then, an in vivo mouse model of IDD was established and the coccygeal discs transcriptome analysis and surface plasmon resonance analysis (SPR) integrated with liquid chromatography-tandem mass spectrometry assay (LC-MS) were performed in this study to study the therapy effect and target proteins of NAT for IDD. Micro-CT was used to evaluate the cancellous bone. The expression of osteogenic (OCN, RNX2), chondrogenic (COL2A1, SOX9), and the target related (ERK1/2, p-ERK1/2) proteins were detected. The alkaline phosphatase staining was performed to estimate osteogenic differentiation. Blood routine and blood biochemistry indexes were analyzed for the safety of NAT. RESULTS: The results showed that NAT could induce chondrogenesis and osteogenesis in MSCs. Further experiments confirmed NAT could ameliorate the secondary osteoporosis and delay the development of IDD in mice. Transcriptome analysis identified 128 common genes and eight Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for NAT. SPR-LC-MS assay detected 57 target proteins for NAT, including MAPK3 (mitogen-activated protein kinase 3), also known as ERK1 (extracellular regulated protein kinase 1). Further verification experiment confirmed that NAT significantly reduced the expression of ERK1/2 phosphorylation. CONCLUSION: NAT would induce chondrogenesis and osteogenesis of MSCs, ameliorate the secondary osteoporosis and delay the progression of IDD in mice by targeting MAPK3.Furthermore, MAPK3, especially the phosphorylation of MAPK3, would be a potential therapeutic target for IDD treatment.

Development and Comparison of Prediction Models Based on Sonovue- and Sonazoid-Enhanced Ultrasound for Pathologic Grade and Microvascular Invasion in Hepatocellular Carcinoma.

OBJECTIVE: This study was aimed at developing and comparing prediction models based on Sonovue and Sonazoid contrast-enhanced ultrasound (CEUS) in predicting pathologic grade and microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Also investigated was whether Kupffer phase images have additional predictive value for the above pathologic features. METHODS: Ninety patients diagnosed with primary HCC who had undergone curative hepatectomy were prospectively enrolled. All patients underwent conventional ultrasound (CUS), Sonovue-CEUS and Sonazoid-CEUS examinations pre-operatively. Clinical, radiologic and pathologic features including pathologic grade, MVI and CD68 expression were collected. We developed prediction models comprising clinical, CUS and CEUS (Sonovue and Sonazoid, respectively) features for pathologic grade and MVI with both the logistic regression and machine learning (ML) methods. RESULTS: Forty-one patients (45.6%) had poorly differentiated HCC (p-HCC) and 37 (41.1%) were MVI positive. For pathologic grade, the logistic model based on Sonazoid-CEUS had significantly better performance than that based on Sonovue-CEUS (area under the curve [AUC], 0.929 vs. 0.848, p = 0.035), whereas for MVI, these two models had similar accuracy (AUC, 0.810 vs. 0.786, p = 0.068). Meanwhile, we found that well-differentiated HCC tended to have a higher enhancement ratio in 6-12 min during the Kupffer phase of Sonazoid-CEUS, as well as higher CD68 expression compared with p-HCC. In addition, all of these models can effectively predict the risk of recurrence (p < 0.05). CONCLUSION: Sonovue-CEUS and Sonazoid-CEUS were comparably excellent in predicting MVI, while Sonazoid-CEUS was superior to Sonovue-CEUS in predicting pathologic grade because of the Kupffer phase. The enhancement ratio in the Kupffer phase has additional predictive value for pathologic grade prediction.