Instance-Specific Model Perturbation Improves Generalized Zero-Shot Learning

Zero-shot learning (ZSL) refers to the design of predictive functions on new classes (unseen classes) of data that have never been seen during training. In a more practical scenario, generalized zero-shot learning (GZSL) requires predicting both seen and unseen classes accurately. In the absence of target samples, many GZSL models may overfit training data and are inclined to predict individuals as categories that have been seen in training. To alleviate this problem, we develop a parameter-wise adversarial training process that promotes robust recognition of seen classes while designing during the test a novel model perturbation mechanism to ensure sufficient sensitivity to unseen classes. Concretely, adversarial perturbation is conducted on the model to obtain instance-specific parameters so that predictions can be biased to unseen classes in the test. Meanwhile, the robust training encourages the model robustness, leading to nearly unaffected prediction for seen classes. Moreover, perturbations in the parameter space, computed from multiple individuals simultaneously, can be used to avoid the effect of perturbations that are too extreme and ruin the predictions. Comparison results on four benchmark ZSL data sets show the effective improvement that the proposed framework made on zero-shot methods with learned metrics.

Construction of Isoquinolone Scaffolds on DNA via Rhodium(III)-Catalyzed C-H Activation

Isoquinolone is one of the most common heterocyclic core structures in countless natural products and many bioactive compounds. Here, a highly efficient approach to synthesize isoquinolone scaffolds on DNA via rhodium(III)-catalyzed C-H activation has been described. This chemistry transformation is robust and has shown good compatibility with DNA, which is suitable for DNA-encoded library synthesis.

Oxidative Dehydroxycyclization of Catechols with o-Mercaptoanilines to Access 1-Hydroxyphenothiazines

The protocol of aerobic oxidative dehydroxycyclization installed in the synthesis of rarely studied 1-hydroxyphenothiazines from catechols and o-mercaptoanilines is presented. Utilizing a natural renewable low-toxicity gallic acid as an organocatalyst, this established transformation proceeded smoothly in an aqueous ethanol solution under mild conditions with good functional group compatibility and up to a 94% isolated yield. This protocol is also characterized by its operational simple workup involving only recrystallization, revealing its sustainability and synthetic practicability.

Bioinspired Self-Assembly of Metalloporphyrins and Polyelectrolytes into Hierarchical Supramolecular Nanostructures for Enhanced Photocatalytic H2 Production in Water

Polypeptides, as natural polyelectrolytes, are assembled into tailored proteins to integrate chromophores and catalytic sites for photosynthesis. Mimicking nature to create the water-soluble nanoassemblies from synthetic polyelectrolytes and photocatalytic molecular species for artificial photosynthesis is still rare. Here, we report the enhancement of the full-spectrum solar-light-driven H2 production within a supramolecular system built by the co-assembly of anionic metalloporphyrins with cationic polyelectrolytes in water. This supramolecular photocatalytic system achieves a H2 production rate of 793 and 685 μmol h-1  g-1 over 24 h with a combination of Mg or Zn porphyrin as photosensitizers and Cu porphyrin as a catalyst, which is more than 23 times higher than that of free molecular controls. With a photosensitizer to catalyst ratio of 10000 : 1, the highest H2 production rate of >51,700 μmol h-1  g-1 with a turnover number (TON) of >1,290 per molecular catalyst was achieved over 24 h irradiation. The hierarchical self-assembly not only enhances photostability through forming ordered stackings of the metalloporphyrins but also facilitates both energy and electron transfer from antenna molecules to catalysts, and therefore promotes the photocatalysis. This study provides structural and mechanistic insights into the self-assembly enhanced photostability and catalytic performance of supramolecular photocatalytic systems.

STANet: Spatio-Temporal Adaptive Network and Clinical Prior Embedding Learning for 3D+T CMR Segmentation

The segmentation of cardiac structure in magnetic resonance images (CMR) is paramount in diagnosing and managing cardiovascular illnesses, given its 3D+Time (3D+T) sequence. The existing deep learning methods are constrained in their ability to 3D+T CMR segmentation, due to: (1) Limited motion perception. The complexity of heart beating renders the motion perception in 3D+T CMR, including the long-range and cross-slice motions. The existing methods' local perception and slice-fixed perception directly limit the performance of 3D+T CMR perception. (2) Lack of labels. Due to the expensive labeling cost of the 3D+T CMR sequence, the labels of 3D+T CMR only contain the end-diastolic and end-systolic frames. The incomplete labeling scheme causes inefficient supervision. Hence, we propose a novel spatio-temporal adaptation network with clinical prior embedding learning (STANet) to ensure efficient spatio-temporal perception and optimization on 3D+T CMR segmentation. (1) A spatio-temporal adaptive convolution (STAC) treats the 3D+T CMR sequence as a whole for perception. The long-distance motion correlation is embedded into the structural perception by learnable weight regularization to balance long-range motion perception. The structural similarity is measured by cross-attention to adaptively correlate the cross-slice motion. (2) A clinical prior embedding learning strategy (CPE) is proposed to optimize the partially labeled 3D+T CMR segmentation dynamically by embedding clinical priors into optimization. STANet achieves outstanding performance with Dice of 0.917 and 0.94 on two public datasets (ACDC and STACOM), which indicates STANet has the potential to be incorporated into computer-aided diagnosis tools for clinical application.

Learning Better Registration to Learn Better Few-Shot Medical Image Segmentation: Authenticity, Diversity, and Robustness

In this work, we address the task of few-shot medical image segmentation (MIS) with a novel proposed framework based on the learning registration to learn segmentation (LRLS) paradigm. To cope with the limitations of lack of authenticity, diversity, and robustness in the existing LRLS frameworks, we propose the better registration better segmentation (BRBS) framework with three main contributions that are experimentally shown to have substantial practical merit. First, we improve the authenticity in the registration-based generation program and propose the knowledge consistency constraint strategy that constrains the registration network to learn according to the domain knowledge. It brings the semantic-aligned and topology-preserved registration, thus allowing the generation program to output new data with great space and style authenticity. Second, we deeply studied the diversity of the generation process and propose the space-style sampling program, which introduces the modeling of the transformation path of style and space change between few atlases and numerous unlabeled images into the generation program. Therefore, the sampling on the transformation paths provides much more diverse space and style features to the generated data effectively improving the diversity. Third, we first highlight the robustness in the learning of segmentation in the LRLS paradigm and propose the mix misalignment regularization, which simulates the misalignment distortion and constrains the network to reduce the fitting degree of misaligned regions. Therefore, it builds regularization for these regions improving the robustness of segmentation learning. Without any bells and whistles, our approach achieves a new state-of-the-art performance in few-shot MIS on two challenging tasks that outperform the existing LRLS-based few-shot methods. We believe that this novel and effective framework will provide a powerful few-shot benchmark for the field of medical image and efficiently reduce the costs of medical image research. All of our code will be made publicly available online.

Marine fungus Aspergillus c1. sp metabolite activates the HSF1/PGC-1α axis, inducing a thermogenic program for treating obesity

Background and aims: Obesity is one of the most prevalent diseases worldwide with less ideal approved agents in clinic. Activating the HSF1/PGC-1α axis in adipose tissues has been reported to induce thermogenesis in mice, which presents a promising therapeutic avenue for obesity treatment. The present study aimed to identified novel natural HSF1 activator and evaluated the therapeutic effects of the newly discovered compound on obesity-associated metabolic disorders and the molecular mechanisms of these effects. Methods: Our previous reported HSF1/PGC-1α activator screening system was used to identify novel natural HSF1 activator. The PGC-1α luciferase activity, immunoblot, protein nuclear-translocation, immunofluorescence, chromatin immunoprecipitation assays were used to evaluate the activity of compound HN-001 in activating HSF1. The experiments of mitochondrial number measurement, TG assay and imaging, cellular metabolic assay, gene assays, and CRISPR/Cas 9 were applied for investigating the metabolic effect of HN-001 in C3H10-T1/2 adipocytes. The in vivo anti-obesity efficacies and beneficial metabolic effects of HN-001 were evaluated by performing body and fat mass quantification, plasma chemical analysis, GTT, ITT, cold tolerance test, thermogenesis analysis. Results: HN-001 dose- and time-dependently activated HSF1 and induced HSF1 nuclear translocation, resulting in an enhancement in binding with the gene Pgc-1α. This improvement induced activation of adipose thermogenesis and enhancement of mitochondrial oxidation capacity, thus inhibiting adipocyte maturation. Deletion of HSF1 in adipocytes impaired mitochondrial oxidation and abolished the above beneficial metabolic effects of HN-001, including adipocyte browning induction, improvements in mitogenesis and oxidation capacity, and lipid-lowering ability. In mice, HN-001 treatment efficiently alleviated diet-induced obesity and metabolic disorders. These changes were associated with increased body temperature in mice and activation of the HSF1/PGC-1α axis in adipose tissues. UCP1 expression and mitochondrial biogenesis were increased in both white and brown adipose tissues of HN-001-treated mice. Conclusion: These data indicate that HN-001 may have therapeutic potential for obesity-related metabolic diseases by increasing the capacity of energy expenditure in adipose tissues through a mechanism involving the HSF1/PGC-1α axis, which shed new light on the development of novel anti-obesity agents derived from marine sources.

Enhancement of mitochondrial energy metabolism by melatonin promotes vascularized skeletal muscle regeneration in a volumetric muscle loss model

Volumetric muscle loss (VML) is a condition that results in the extensive loss of 20 % or more of skeletal muscle due to trauma or tumor ablation, leading to severe functional impairment and permanent disability. The current surgical interventions have limited functional regeneration of skeletal muscle due to the compromised self-repair mechanism. Melatonin has been reported to protect skeletal muscle from exercise-induced oxidative damage and holds great potential to treat muscle diseases. In this study, we hypothesize that melatonin can enhance myoblast differentiation and promote effective recovery of skeletal muscle following VML. In vitro administration of melatonin resulted in a significant enhancement of myogenesis in C2C12 myoblast cells, as evidenced by the up-regulation of myogenic marker genes in a dose-dependent manner. Further experiments revealed that silent information of regulator type 3 (SIRT3) played a critical role in the melatonin-enhanced myoblast differentiation through enhancement of mitochondrial energy metabolism and activation of mitochondrial antioxidant enzymes such as superoxide dismutase 2 (SOD2). Silencing of Sirt3 completely abrogated the protective effect of melatonin on the mitochondrial function of myoblasts, evidenced by the increased reactive oxygen species, decreased adenosine triphosphate production, and down-regulated myoblast-specific marker gene expression. In order to attain a protracted and consistent release, liposome-encapsuled melatonin was integrated into gelatin methacryloyl hydrogel (GelMA-Lipo@MT). The implantation of GelMA-Lipo@MT into a tibialis anterior muscle defect in a VML model effectively stimulated the formation of myofibers and new blood vessels in situ, while concurrently inhibiting fibrotic collagen deposition. The findings of this study indicate that the incorporation of melatonin with GelMA hydrogel has facilitated the de novo vascularized skeletal muscle regeneration by augmenting mitochondrial energy metabolism. This represents a promising approach for the development of skeletal muscle tissue engineering, which could be utilized for the treatment of VML and other severe muscle injuries.

The failure behavior of coal-rock combined body under compression-shear loading

As shallow coal reserves continue to deplete rapidly, deep mining has become an unavoidable course of action. In the process of deep coal mining, affected by blasting, mining, and excavation, the coal-rock interface often encounters the action of compression-shear composite load. The interface crack directly affects the stability of the coal-rock structure. Uniaxial compression experiments have been conducted on rock and coal-like material with pre-existing interfacial oblique cracks to study the crack propagation criterion of the rock and coal-like material interface. An image acquisition system is used to record the surface speckle field of the whole process of specimen failure. The strain fields and stress intensity factor of the sample at different times are obtained by digital image correlation. At the same time, the stress field near the crack tip is calculated. The results show that with the increase of loading, two strains of localization bands are formed on the surface of the specimen. One of the strain-localized bands starts at the lower tip of the prefabricated crack and propagates along the vertical interface. The other starts at the upper tip of the prefabricated damage and propagates along the interface direction. It can be seen that the lower tip of the prefabricated crack enters into the crack fracture process zone earlier than the upper tip. The strain localization band narrows gradually with the load increase, and then macro cracks appear. The initiation of two tips is suitable for different fracture criteria. The lower tip is dominated by the maximum circumferential tensile stress, and the upper tip is dominated by shear stress. The specimens eventually fracture along the interface. The evolution of the strain field during the failure process of rock and coal-like material can reflect the generation and propagation of the crack.

Identification of a natural PLA2 inhibitor from the marine fungus Aspergillus sp. c1 for MAFLD treatment that suppressed lipotoxicity by inhibiting the IRE-1α/XBP-1s axis and JNK signaling

Lipotoxicity is a pivotal factor that initiates and exacerbates liver injury and is involved in the development of metabolic-associated fatty liver disease (MAFLD). However, there are few reported lipotoxicity inhibitors. Here, we identified a natural anti-lipotoxicity candidate, HN-001, from the marine fungus Aspergillus sp. C1. HN-001 dose- and time- dependently reversed palmitic acid (PA)-induced hepatocyte death. This protection was associated with IRE-1α-mediated XBP-1 splicing inhibition, which resulted in suppression of XBP-1s nuclear translocation and transcriptional regulation. Knockdown of XBP-1s attenuated lipotoxicity, but no additional ameliorative effect of HN-001 on lipotoxicity was observed in XBP-1s knockdown hepatocytes. Notably, the ER stress and lipotoxicity amelioration was associated with PLA2. Both HN-001 and the PLA2 inhibitor MAFP inhibited PLA2 activity, reduced lysophosphatidylcholine (LPC) level, subsequently ameliorated lipotoxicity. In contrast, overexpression of PLA2 caused exacerbation of lipotoxicity and weakened the anti-lipotoxic effects of HN-001. Additionally, HN-001 treatment suppressed the downstream pro-apoptotic JNK pathway. In vivo, chronic administration of HN-001 (i.p.) in mice alleviated all manifestations of MAFLD, including hepatic steatosis, liver injury, inflammation, and fibrogenesis. These effects were correlated with PLA2/IRE-1α/XBP-1s axis and JNK signaling suppression. These data indicate that HN-001 has therapeutic potential for MAFLD because it suppresses lipotoxicity, and provide a natural structural basis for developing anti-MAFLD candidates.

Correlation study between bone metabolic markers, bone mineral density, and sarcopenia

OBJECTIVE

To investigate the correlation between bone metabolism markers, bone mineral density (BMD), and sarcopenia.

METHODS

A total of 331 consecutive patients aged ≥ 60 years who were hospitalized between November 2020 and December 2021 were enrolled. Participants were divided into sarcopenia and non-sarcopenia groups according to the Asian Working Group on Sarcopenia criteria (AWGS, 2019). The clinical data, bone metabolism markers (β-CTX, N-MID, and TP1NP), and BMD were compared between the two groups.

RESULTS

Age, β-CTX, and N-MID of the sarcopenia group were higher than those of the non-sarcopenia group (P < 0.05), but the BMD T values were lower than those of the non-sarcopenia group (P < 0.05). Binary logistic regression analysis showed that increased femoral neck BMD (FNBMD) was a protective factor for sarcopenia, while increased β-CTX was a risk factor. Pearson/Spearman correlation analysis showed that the diagnostic indices of sarcopenia were positively correlated with FNBMD and negatively correlated with β-CTX and N-MID. Multiple linear regression analysis revealed that BMI and FNBMD significantly positively affected muscle strength and appendicular skeletal muscle mass (ASM). The FNBMD significantly positively affected physical performance, while β-CTX significantly negatively affected muscle strength, ASM, and physical performance.

CONCLUSION

Increased FNBMD may be a protective factor against sarcopenia, and increased β-CTX may be a risk factor. The FNBMD significantly positively affected the diagnostic indices of sarcopenia, while β-CTX significantly negatively affected them. BMD and bone metabolism marker levels may be considered in early screening for sarcopenia.

An adaptive multi-frame parallel iterative method for accelerating real-time magnetic particle imaging reconstruction

Objective. Real-time reconstruction of magnetic particle imaging (MPI) shows promising clinical applications. However, prevalent reconstruction methods are mainly based on serial iteration, which causes large delay in real-time reconstruction. In order to achieve lower latency in real-time MPI reconstruction, we propose a parallel method for accelerating the speed of reconstruction methods.Approach. The proposed method, named adaptive multi-frame parallel iterative method (AMPIM), enables the processing of multi-frame signals to multi-frame MPI images in parallel. To facilitate parallel computing, we further propose an acceleration strategy for parallel computation to improve the computational efficiency of our AMPIM.Main results. OpenMPIData was used to evaluate our AMPIM, and the results show that our AMPIM improves the reconstruction frame rate per second of real-time MPI reconstruction by two orders of magnitude compared to prevalent iterative algorithms including the Kaczmarz algorithm, the conjugate gradient normal residual algorithm, and the alternating direction method of multipliers algorithm. The reconstructed image using AMPIM has high contrast-to-noise with reducing artifacts.Significance. The AMPIM can parallelly optimize least squares problems with multiple right-hand sides by exploiting the dimension of the right-hand side. AMPIM has great potential for application in real-time MPI imaging with high imaging frame rate.

Using CT imaging features to predict visceral pleural invasion of non-small-cell lung cancer

AIM

To examine the diagnostic performance of different models based on computed tomography (CT) imaging features in differentiating the invasiveness of non-small-cell lung cancer (NSCLC) with multiple pleural contact types.

MATERIALS AND METHODS

A total of 1,573 patients with NSCLC (tumour size ≤3 cm) were included retrospectively. The clinical and pathological data and preoperative imaging features of these patients were investigated and their relationships with visceral pleural invasion (VPI) were compared statistically. Multivariate logistic regression was used to eliminate confounding factors and establish different predictive models.

RESULTS

By univariate analysis and multivariable adjustment, surgical history, tumour marker (TM), number of pleural tags, length of solid contact and obstructive inflammation were identified as independent risk predictors of pleural invasiveness (p=0.014, 0.003, <0.001, <0.001, and 0.017, respectively). In the training group, comparison of the diagnostic efficacy between the combined model including these five independent predictors and the image feature model involving the latter three imaging predictors were as follows: sensitivity of 88.9% versus 77% and specificity of 73.5% versus 84.1%, with AUC of 0.868 (95% CI: 0.848-0.886) versus 0.862 (95% CI: 0.842-0.880; p=0.377). In the validation group, the sensitivity and specificity of these two models were as follow: the combined model, 93.5% and 74.3%, the imaging feature model, 77.4% and 81.3%, and their areas under the curve (AUCs) were both 0.884 (95% CI: 0.842-0.919). The best cut-off value of length of solid contact was 7.5 mm (sensitivity 68.9%, specificity 75.5%).

CONCLUSIONS

The image feature model showed great potential in predicting pleural invasiveness, and had comparable diagnostic efficacy compared with the combined model containing clinical data.

Burnout and turnover intention of primary health care providers during the COVID-19 pandemic in China

OBJECTIVES

This study explored the changes and new characteristics of burnout and turnover intention of primary health care (PHC) providers during the COVID-19 pandemic in China.

STUDY DESIGN

This was a cross-sectional study.

METHODS

This study investigated 1326 PHC providers during the COVID-19 outbreak in 2022 in one district of Shanghai, China. Independent t-test or one-way analysis of variance (ANOVA) test were used to analyse the between-group variation of variables associated to burnout and turnover intention. Then, hierarchical regression analysis was used to further determine the impact of certain variables on burnout and turnover intention, the relationship of burnout on turnover intention and the possible moderating effect.

RESULTS

The results showed that there was no significant change in the prevalence of overall burnout of PHC providers compared to the pre-epidemic period; however, there was a significant increase in high-level burnout. No significant change in turnover intention at the moderate level and above was observed. During the COVID-19 pandemic, PHC providers who were older, married, local and had a higher skill level had higher burnout, while PHC providers who were male, unmarried, non-local and separated from their family had a higher turnover intention. It was shown that burnout, with its three sub-dimensions, was a good predictor of turnover intention. The impact of burnout on turnover intention was shown to be alleviated by certain variables, including being married, living locally and receiving benefit packages, including the preferential education policy for children and talent incentive policies.

CONCLUSIONS

Results from this study have highlighted the importance of paying attention to vulnerable groups of PHC providers, for example those who are separated from their families, during emergency situations. Various incentive tools could be comprehensively used to ensure the stability and efficiency of PHC human resources.

A transformer-based dual-domain network for reconstructing FOV extended cone-beam CT images from truncated sinograms in radiation therapy

BACKGROUND AND OBJECTIVE

Cone-beam computed tomography (CBCT) is widely used in clinical radiotherapy, but its small field of view (sFOV) limits its application potential. In this study, a transformer-based dual-domain network (dual_swin), which combined image domain restoration and sinogram domain restoration, was proposed for the reconstruction of complete CBCT images with extended FOV from truncated sinograms.

METHODS

The planning CT images with large FOV (LFOV) of 330 patients who received radiation therapy were collected. The synthetic CBCT (sCBCT) images with LFOV were generated from CT images by the trained cycleGAN network, and CBCT images with sFOV were obtained through forward projection, projection truncation, and filtered back projection (FBP), comprising the training and test data. The proposed dual_swin includes sinogram domain restoration, image domain restoration, and FBP layer, and the swin transformer blocks were used as the basic feature extraction module in the network to improve the global feature extraction ability. The proposed dual_swin was compared with the image domain method, the sinogram domain method, the U-Net based dual domain network (dual_Unet), and the traditional iterative reconstruction method based on prior image and conjugate gradient least-squares (CGLS) in the test of sCBCT images and clinical CBCT images. The HU accuracy and body contour accuracy of the predicted images by each method were evaluated.

RESULTS

The images generated using the CGLS method were fuzzy and obtained the lowest structural similarity (SSIM) among all methods in the test of sCBCT and clinical CBCT images. The predicted images by the image domain methods are quite different from the ground truth and have low accuracy on HU value and body contour. In comparison with image domain methods, sinogram domain methods improved the accuracy of HU value and body contour but introduced secondary artifacts and distorted bone tissue. The proposed dual_swin achieved the highest HU and contour accuracy with mean absolute error (MAE) of 23.0 HU, SSIM of 95.7%, dice similarity coefficient (DSC) of 99.6%, and Hausdorff distance (HD) of 4.1 mm in the test of sCBCT images. In the test of clinical patients, images that were predicted by dual_swin yielded MAE, SSIM, DSC, and HD of 38.2 HU, 91.7%, 99.0%, and 5.4 mm, respectively. The predicted images by the proposed dual_swin has significantly higher accuracy than the other methods (P < 0.05).

CONCLUSIONS

The proposed dual_swin can accurately reconstruct FOV extended CBCT images from the truncated sinogram to improve the application potential of CBCT images in radiotherapy.

CREB3L2 Regulates Hemidesmosome Formation during Epithelial Sealing

The long-term success rate of dental implants can be improved by establishing a favorable biological sealing with a high-quality epithelial attachment. The application of mesenchymal stem cells (MSCs) holds promise for facilitating the soft tissue integration around implants, but the molecular mechanism is still unclear and the general application of MSC sheet for soft tissue integration is also relatively unexplored. We found that gingival tissue-derived MSC (GMSC) sheet treatment significantly promoted the expression of hemidesmosome (HD)-related genes and proteins in gingival epithelial cells (GECs). The formation of HDs played a key role in strengthening peri-implant epithelium (PIE) sealing. Further, high-throughput transcriptome sequencing showed that GMSC sheet significantly upregulated the PI3K/AKT pathway, confirming that cell adhesion and HD expression in GECs were regulated by GMSC sheet. We observed that the expression of transcription factor CREB3L2 in GECs was downregulated. After treatment with PI3K pathway inhibitor LY294002, CREB3L2 messenger RNA and protein expression levels were upregulated. Further experiments showed that overexpression or knockdown of CREB3L2 could significantly inhibit or promote HD-related genes and proteins, respectively. We confirmed that CREB3L2 was a transcription factor downstream of the PI3K/AKT pathway and participated in the formation of HDs regulated by GMSC sheet. Finally, through the establishment of early implant placement model in rats, we clarified the molecular function of CREB3L2 in PIE sealing as a mechanical transmission molecule in GECs. The application of GMSC sheet-implant complex could enhance the formation of HDs at the implant-PIE interface and decrease the penetration distance of horseradish peroxidase between the implant and PIE. Meanwhile, GMSC sheet reduced the length of CREB3L2 protein expression on PIE. These findings elucidate the potential function and molecular mechanism of MSC sheet regulating the epithelial sealing around implants, providing new insights and ideas for the application of stem cell therapy in regenerative medicine.

Prediction of Lymphopenia and Survival with Baseline Absolute Lymphocyte Count and Irradiated Dose to Immune Cells in Patients with Non-Small Cell Lung Cancer Treated with Concurrent Chemoradiotherapy

PURPOSE/OBJECTIVE(S)

This study aimed to investigate the effect of effective dose to immune cell (EDIC) combined with pre-radiotherapy (RT) absolute lymphocyte count (ALC) on treatment-related lymphopenia during RT and treatment outcome in patients with locally advanced non-small cell lung cancer (NSCLC). A subgroup analysis in patients who received consolidation immunotherapy was also conducted.

MATERIALS/METHODS

Between August 2008 and December 2021, 517 patients with locally advanced NSCLC treated with definitive concurrent chemoradiotherapy (CRT) were retrospectively analyzed. All patients had serial complete-blood-count tests at pre-, and during-CRT. Severe lymphopenia was defined as ALC < 0.5x109cells/L during RT. EDIC was calculated according to mean doses of the lung, heart and the total body. The patients were grouped according to high and low EDIC and pre-RT ALC and was assessed for its correlation with radiation induced lymphopenia and survival outcomes.

RESULTS

Of 517 eligible patients, most of the patients received weekly paclitaxel with carboplatin (90.3%) and 195 patients (37.7%) received consolidation immunotherapy following CRT. A median radiation dose of 63 Gy (IQR, 60-64.5) was delivered in 30 fractions. The optimal cutoff value of EDIC and pre-RT ALC for predicting severe lymphopenia were 2.89 Gy and 2.03x109cells/L, respectively. High risk group was defined as EDIC ≥ 2.89 Gy and pre-RT ALC < 2.03x109cells/L, low risk group as EDIC <2.89 Gy and pre-RT ALC ≥ 2.03x109cells/L, and intermediate group as EDIC ≥ 2.89 Gy and pre-RT ALC ≥ 2.03x109cells/L or EDIC < 2.89 Gy and pre-RT ALC < 2.03x109cells/L. The incidence of severe lymphopenia during RT in high, intermediate, and low risk group was 90.1%, 77.1%, and 52.3%, respectively (p<0.001). The risk groups were independent predictors for both progression-free survival (PFS) (p<0.001) and overall survival (OS) (p<0.001). The high-risk group had higher incidence of locoregional and distant recurrences (p<0.001). In the subset of patients who were treated with consolidation immunotherapy, the risk groups were predictive of severe lymphopenia (p = 0.001), PFS (p = 0.004), and OS (p = 0.012).

CONCLUSION

This study demonstrated that the combination of EDIC and pre-RT ALC is a predictor for severe lymphopenia during RT, recurrence, and survival in patients with locally advanced NSCLC who received CRT. Moreover, the combination of EDIC and pre-RT ALC may serve as a potential biomarker for the benefit of maintenance immunotherapy.

Erratum: Driving Pressure-Guided Ventilation in Obese Patients Undergoing Laparoscopic Sleeve Gastrectomy: A Randomized Controlled Trial [Corrigendum]

[This corrects the article DOI: 10.2147/DMSO.S405804.].

Fluorapatite nanorod arrays with enamel-like bundle structure regulated by iron ions

Pigmented rodent tooth enamel is mainly composed of parallel hydroxyapatite nanorods and a small amount of organic matrix. These hydroxyapatite nanorods tend to be carbonated and contain traces of iron, fluorine, and magnesium. The pigmented rodent tooth enamel which contains trace iron is stronger and more resistant to acid corrosion than unpigmented rodent enamel, which could provide inspiration for the preparation and synthesis of high performance and corrosion resistant artificial materials. However, the regulatory role and mechanical enhancement of iron ions in enamel growth are unclear. Here, we synthesized enamel-like fluorapatite nanorod arrays in vitro using a mineralization technique at room-temperature. To investigate the regulatory effect of iron ions on the fluorapatite nanorod arrays (FAP-Fe), the phosphate solution is slowly transfused dropwise in the calcium ion solution, and different concentrations of iron ions are added to the calcium ion solution in advance. We demonstrated that fluorapatite nanorod arrays (FAP) can be epitaxially grown from amorphous calcium phosphate nanoparticles and iron ions can improve the microstructure of FAP nanorod arrays and obtain the same enamel bundle structure as the natural enamel. Moreover, high concentration of iron ions can inhibit the crystallization of fluorapatite. The FAP-Fe nanorod arrays controlled by 0.02 mM Fe3+ have good mechanical properties. Their hardness is 1.34 ± 0.02 GPa and Young's modulus is 65.3 ± 0.4 GPa, respectively. This work is helpful to understand the role of trace elements in natural enamel in the regulation of enamel formation and to provide a theoretical foundation for the preparation of high strength artificial composites, which can play a greater role in the fields of biological alternative materials, anti-oil coating, oil/water separation, anti-bioadhesion and so on.

Measurements of neutrino oscillation parameters from the T2K experiment using 3.6×1021 protons on target

The T2K experiment presents new measurements of neutrino oscillation parameters using 19.7 ( 16.3 ) × 10 20 protons on target (POT) in (anti-)neutrino mode at the far detector (FD). Compared to the previous analysis, an additional 4.7 × 10 20 POT neutrino data was collected at the FD. Significant improvements were made to the analysis methodology, with the near-detector analysis introducing new selections and using more than double the data. Additionally, this is the first T2K oscillation analysis to use NA61/SHINE data on a replica of the T2K target to tune the neutrino flux model, and the neutrino interaction model was improved to include new nuclear effects and calculations. Frequentist and Bayesian analyses are presented, including results on sin 2 θ 13 and the impact of priors on the δ CP measurement. Both analyses prefer the normal mass ordering and upper octant of sin 2 θ 23 with a nearly maximally CP-violating phase. Assuming the normal ordering and using the constraint on sin 2 θ 13 from reactors, sin 2 θ 23 = 0 . 561 - 0.032 + 0.021 using Feldman-Cousins corrected intervals, and Δ m 32 2 = 2 . 494 - 0.058 + 0.041 × 10 - 3 eV 2 using constant Δ χ 2 intervals. The CP-violating phase is constrained to δ CP = - 1 . 97 - 0.70 + 0.97 using Feldman-Cousins corrected intervals, and δ CP = 0 , π is excluded at more than 90% confidence level. A Jarlskog invariant of zero is excluded at more than 2 σ credible level using a flat prior in δ CP , and just below 2 σ using a flat prior in sin δ CP . When the external constraint on sin 2 θ 13 is removed, sin 2 θ 13 = 28 . 0 - 6.5 + 2.8 × 10 - 3 , in agreement with measurements from reactor experiments. These results are consistent with previous T2K analyses.

Virtual Pain Unit Is Associated with Improvement of Postoperative Analgesia Quality: A Retrospective Single-Center Clinical Study

INTRODUCTION

Acute postoperative pain is a major concern among surgical patients. Thus, this study established a new acute pain management model and compared the effects of the acute pain service (APS) model in 2020 and the virtual pain unit (VPU) model in 2021 on postoperative analgesia quality.

METHODS

This retrospective, single-center clinical study involved 21,281 patients from 2020 to 2021. First, the patients were grouped on the basis of their pain management model (APS and VPU). The incidence of moderate to severe postoperative pain (MSPP) [numeric rating scale (NRS) score ≥ 5], postoperative nausea and vomiting (PONV), and postoperative dizziness were recorded.

RESULTS

The VPU group recorded significantly lower MSPP incidence (1-12 months), PONV, and postoperative dizziness (1-10 months and 12 months) compared with the APS group. In addition, the annual average incidence of MSPP, PONV, and postoperative dizziness in the VPU group was significantly lower than in the APS group.

CONCLUSIONS

The VPU model reduces the incidence of moderate to severe postoperative pain, nausea, vomiting, and dizziness; hence, it is a promising acute pain management model.

[Long term follow-up evaluation of combined surgery for congenital tibial pseudarthrosis in children]

Objective: To explore the long-term effect of combined surgery for the treatment of congenital tibial pseudarthrosis in children. Methods: The clinical data of 44 children with congenital tibial pseudarthrosis who underwent combined surgery (tibial pseudarthrosis tissue resection, intramedullary rod fixation, Ilizarov external fixator fixation, wrapped autologous iliac bone graft) from August 2007 to October 2011 at the Department of Pediatric Orthopedics, Hunan Children's Hospital were collected retrospectively. There were 33 males and 11 females. The age at the time of surgery was (3.7±2.2)years (range:0.6 to 12.4 years), including 25 cases under 3 years old and 19 cases above 3 years old.Among them, 37 cases were complicated with neurofibromatosis type 1.The operation status, postoperative complications and follow-up results were recorded. Results: The follow-up time after surgery was (10.9±0.7)years (range:10 to 11 years).Thirty-nine out of 44 patients (88.6%) achieved initial healing of tibial pseudarthrosis, with an average healing time of (4.3±1.1)months (range:3 to 10months).In the last follow-up, 36 cases (81.8%) had unequal tibial length, 20 cases (45.4%) had refractures, 18 cases (40.9%) had ankle valgus, 9 cases (20.4%) had proximal tibial valgus, and 11 cases (25.0%) had high arched feet.Nine cases (20.4%) developed distal tibial epiphyseal plate bridging.17 cases (38.6%) had abnormal tibial mechanical axis.Seven cases (15.9%) developed needle infection, and one case (2.3%) developed tibial osteomyelitis. 21 patients (47.7%) had excessive growth of the affected femur.Five patients (11.3%) had ankle stiffness, and 34 patients (77.2%) had intramedullary rod displacement that was not in the center of the tibial medullary cavity.Among them, 8 cases (18.1%) protruded the tibial bone cortex and underwent intramedullary rod removal.18 children have reached skeletal maturity, while 26 children have not been followed up until skeletal maturity. Conclusion: Combined surgery for the treatment of congenital pseudarthrosis of the tibia in children has a high initial healing rate, but complications such as unequal tibia length, refracture, and ankle valgus occur during long-term follow-up, requiring multiple surgical treatments.

Rebalanced Zero-shot Learning

Zero-shot learning (ZSL) aims to identify unseen classes with zero samples during training. Broadly speaking, present ZSL methods usually adopt class-level semantic labels and compare them with instance-level semantic predictions to infer unseen classes. However, we find that such existing models mostly produce imbalanced semantic predictions, i.e. these models could perform precisely for some semantics, but may not for others. To address the drawback, we aim to introduce an imbalanced learning framework into ZSL. However, we find that imbalanced ZSL has two unique challenges: (1) Its imbalanced predictions are highly correlated with the value of semantic labels rather than the number of samples as typically considered in the traditional imbalanced learning; (2) Different semantics follow quite different error distributions between classes. To mitigate these issues, we first formalize ZSL as an imbalanced regression problem which offers empirical evidences to interpret how semantic labels lead to imbalanced semantic predictions. We then propose a re-weighted loss termed Re-balanced Mean-Squared Error (ReMSE), which tracks the mean and variance of error distributions, thus ensuring rebalanced learning across classes. As a major contribution, we conduct a series of analyses showing that ReMSE is theoretically well established. Extensive experiments demonstrate that the proposed method effectively alleviates the imbalance in semantic prediction and outperforms many state-of-the-art ZSL methods.

Mutational landscape of SWI/SNF complex genes reveal correlation to predictive biomarkers for immunotherapy sensitivity in lung adenocarcinoma patients

BACKGROUND

The search for prognostic biomarkers indicating sensitivity to immunotherapy in lung adenocarcinoma patients has zeroed in on genes in the switch/sucrose non-fermentable (SWI/SNF) pathway. The mutational profiles of key genes are not clearly defined, however, and no comparisons have been conducted on whether mutations in the genes involved provide the same predictive value.

METHODS

In this study, analysis of clinical factors, tumor mutation burden (TMB), chromosomal instability, and co-alterations was conducted for 4344 lung adenocarcinoma samples. Independent online cohorts (N = 1661 and 576) were used to supplement the analysis with survival and RNA-seq data.

RESULTS

Mutational burden and chromosomal instability analysis showed that ARID family mutations (including ARID1A, ARID1B, or ARID2 mutations) and SMARC family mutations (including SMARCA4 or SMARCB1 mutations) display different profiles from wild-type (WT) samples (TMB: ARID versus WT: P < 2.2 × 10^-16, SMARC versus WT: P < 2.2 × 10^-16; CIN: ARID versus WT: P = 1.8 × 10^-5, SMARC versus WT: P = 0.027). Both mutant groups have a higher proportion of transversions than transitions, whereas the ratio is more equal for wild-type samples. Survival analysis shows that patients with ARID mutations were more sensitive to immunotherapy treatment than wild-type and SMARC-mutated patients (P < 0.001 and P = 0.013, respectively), and multivariate Cox analysis reveals that the presence of ARID mutations is likely the main cause.

CONCLUSIONS

The research presented in this study shows that mutations in the ARID gene family, including ARID1A, ARID1B, and ARID2, are primarily responsible for the sensitive response to immunotherapy treatment in patients with lung adenocarcinoma.

Driving Pressure-Guided Ventilation in Obese Patients Undergoing Laparoscopic Sleeve Gastrectomy: A Randomized Controlled Trial

Purpose

This study aims to compare the conventional lung protective ventilation strategy (LPVS) with driving pressure-guided ventilation in obese patients undergoing laparoscopic sleeve gastrectomy (LSG).

Methods

Forty-five patients undergoing elective LSG under general anesthesia were randomly assigned to the conventional LPVS group (group L) or the driving pressure-guided ventilation group (group D) using random numbers generated by Excel. The primary outcome was the driving pressure of both groups 90 min after pneumoperitoneum.

Results

After 30 min of pneumoperitoneum, 90 min of pneumoperitoneum, 10 min of closing the pneumoperitoneum, and restoring the supine position, the driving pressure of group L and group D were 20.0 ± 2.9 cm H2O vs 16.6 ± 3.0 cm H2O (P < 0.001), 20.7 ± 3.2 cm H2O vs 17.3 ± 2.8 cm H2O (P < 0.001), and 16.3 ± 3.1 cm H2O vs 13.3 ± 2.5 cm H2O (P = 0.001), respectively; the respiratory compliance of groups L and D were 23.4 ± 3.7 mL/cm H2O vs 27.6 ± 5.1 mL/cm H2O (P = 0.003), 22.7 ± 3.8 mL/cm H2O vs 26.4 ± 3.5 mL/cm H2O (P = 0.005), and 29.6 ± 6.8 mL/cm H2O vs 34.7 ± 5.3 mL/cm H2O (P = 0.007), respectively. The intraoperative PEEP in groups L and group D was 5 (5-5) cm H2O vs 10 (9-11) cm H2O (P < 0.001).

Conclusion

An individualized peep-based driving pressure-guided ventilation strategy can reduce intraoperative driving pressure and increase respiratory compliance in obese patients undergoing LSG.

[Application and research progress of autologous soft tissue substitute materials in gingival augmentation of natural teeth]

Subepithelial connective tissue or free gingival grafts are often used in traditional mucogingival surgery to treat gingival recession and keratinized gingival insufficiency. However, due to the disadvantages of autologous soft tissue grafts, such as the preparation of the second surgical site, the limited amount of tissue in the donor site, and postoperative discomfort for patients, the research on autologous soft tissue substitute materials has attracted extensive attention. A variety of donor-substitute materials from different sources are currently used in membranous gingival surgeries, including platelet-rich fibrin, acellular dermal matrix, xenogeneic collagen matrix, etc. This paper reviews the research progress and application of several different types of substitute materials in soft tissue augmentation for natural teeth, providing a reference for the application of autologous soft tissue substitutes in clinical gingival augmentation surgery.

Alloreactivity and autoreactivity converge to support B cell epitope targeting in transplant rejection

Antibody (Ab) responses against human leukocyte antigen (HLA) proteins mismatched between donor and recipient are leading cause of allograft loss in kidney transplantation. However, therapies targeting alloreactive B cell and Ab-secreting cell (ASC) are lacking, motivating the need to understand how to prevent and abrogate these alloresponses. Using molecular, structural, and proteomic techniques, we profiled the B cell response in a kidney transplant recipient with antibody-mediated rejection and graft loss. We found that this response spanned the rejected organ and peripheral blood, stimulated the differentiation of multiple B cell subsets, and produced a high-affinity, donor-specific, anti-HLA response. We found epitopic immunodominance that relied on highly exposed, solvent-accessible mismatched HLA residues as well as structural and biomolecular evidence of autoreactivity against the recipient's self-HLA allele. These alloreactive and autoreactive signatures converged in the recipient's circulating donor-specific Ab repertoire, suggesting that rejection requires both the recognition of non-self and breaches of tolerance to lead to alloinjury and graft loss.

[Optimized pathway to schistosomiasis elimination in China: a scrutiny using a marginal benefit approach]

Following concerted efforts for over 7 decades, great achievements have been gained in the national schistosomiasis control program of China. Currently, China is moving towards the stage of schistosomiasis elimination, when the major task is to make full use of available resources to improve schistosomiasis surveillance and response to sustainably consolidate gained schistosomiasis control achievements and prevent re-emerging schistosomiasis. There is therefore an urgent need for optimization of interventions for schistosomiasis elimination. Based on analysis of socioeconomic features at different stages of the national schistosomiasis control program in China, this review discusses the relationship between the needs of assessment of schistosomiasis elimination interventions and the optimized strategy of schistosomiasis elimination at different stages of the national schistosomiasis control program using a marginal benefit approach and proposes the optimized schistosomiasis elimination strategy that allows the highest marginal benefit with currently available schistosomiasis elimination costs, so as to provide the optimal strategic pathway to schistosomiasis elimination and facilitate the achievement of the targets set in Healthy China 2030.

Downregulated FGFR3 Expression Inhibits In Vitro Osteogenic Differentiation of Bone Marrow Mesenchymal Stem Cells of Mice with TBXT Gene Mutation

We studied the effect of fibroblast growth factor receptor 3 (FGFR3) inhibitor BGJ-398 on the differentiation of bone marrow mesenchymal stem cells (BM MSC) into osteoblasts in wild type (wt) mice and in animals with mutation in TBXT gene (mt) and possible differences in the pluripotency of these cells. Cytology tests showed that the cultured BM MSC could differentiate into osteoblasts and adipocytes. The effect of different BGJ-398 concentrations on the expression of FGFR3, RUNX2, SMAD1, SMAD4, SMAD5, SMAD6, SMAD7, and SMAD8 were studied by quantitative reverse transcription PCR. The expression of RUNX2 protein was evaluated by Western blotting. BM MSC of mt and wt mice did not differ in pluripotency and expressed the same membrane marker antigens. BGJ-398 inhibitor reduced the expression of FGFR3 and RUNX2. In BM MSC from mt and wt mice have similar gene expression (and its changing) in FGFR3, RUNX2, SMAD1, SMAD4, SMAD5, SMAD6, SMAD7, and SMAD8 genes. Thus, our experiments confirmed the effect of decreased expression of FGFR3 on osteogenic differentiation of BM MSC from wt and mt mice. However, BM MSC from mt and wt mice did not differ in pluripotency and are an adequate model for laboratory research.

Oxidative stress mediated immunosuppression caused by ammonia gas via antioxidant/oxidant imbalance in broilers

1. Ammonia is one of major air pollutants in intensive poultry houses, where it causes immunosuppression in broilers. Although previous studies have focused on a particular organ, data on multiple organs have not been reported.2. In the following work, broilers were exposed to environmental ammonia (0, 10, 20, and 40 mg/m³ from 1-21 d old; and 0, 15, 30, and 60 mg/m³ from 22-42 d old).3. Ammonia exposure reduced bird spleen index at 42 d and thymus index at 14, 28, 35 and 42 d, meaning that ammonia caused immunosuppression in birds. Moreover, high ammonia exposure down-regulated the expression of toll-like receptor 4 (TLR4) in lung tissue at 21 d, as well as TLR4 in lung and tracheal mucosa at 42 d when analysed using qRT-PCR. It increased SIgA in saliva at 42 d when analysed by ELISA. Ammonia increased interleukin-6 (IL-6), IL-1β, interferon-α (IFN-α), and IFN-γ in serum at 28 d from the ELISA assay, which indicated that all of these factors took part in ammonia-immunosuppression in birds.4. Three antioxidants (CAT, SOD, T-AOC) decreased, and one oxidant MDA increased after ammonia exposure in the liver and blood, which indicated that ammonia caused oxidative stress via the imbalance of antioxidants/oxidants in birds.5. Correlation analysis showed that TLR4 and TLR15 in the tracheal mucosa were significantly positively related to IFN-γ and negatively related to IL-6. TLR2 in the lung was significantly positively related to IL-1β, and TLR2 in bird tracheal mucosa was negatively related to IL-6 in serum.6. The results suggested that oxidative stress mediated immunosuppression caused by ammonia gas via antioxidant/oxidant imbalance in broilers.

Streaking artifact reduction for CBCT-based synthetic CT generation in adaptive radiotherapy

BACKGROUND

Cone-beam computed tomography (CBCT) is widely used for daily image guidance in radiation therapy, enhancing the reproducibility of patient setup. However, its application in adaptive radiotherapy (ART) is limited by many imaging artifacts and inaccurate Hounsfield units (HUs). The correction of CBCT image is necessary and of great value for CBCT-based ART.

PURPOSE

To explore the synthetic CT (sCT) generation from CBCT images of thorax and abdomen patients, which usually surfer from serious artifacts duo to organ state changes. In this study, a streaking artifact reduction network (SARN) is proposed to reduce artifacts and combine with cycleGAN to generate high-quality sCT images from CBCT and achieve an accurate dose calculation.

METHODS

The proposed SARN was trained in a self-supervised manner. Artifact-CT images were generated from planning CT by random deformation and projection replacement, and SARN was trained based on paired artifact-CT and CT images. The planning CT and CBCT images of 260 patients with cancer, including 120 thoracic and 140 abdominal CT scans, were used to train and evaluate neural networks. The CBCT images of another 12 patients in late treatment fractions, which contained large anatomy changes, were also tested by trained models. The trained models include commonly used U-Net, cycleGAN, attention-gated cycleGAN (cycAT), and cascade models combined SARN with cycleGAN or cycAT. The generated sCT images were compared in terms of image quality and dose calculation accuracy.

RESULTS

The sCT images generated by SARN combined with cycleGAN and cycAT showed the best image quality, removed the most artifacts, and retained the normal anatomical structure. The SARN+cycleGAN performed best in streaking artifacts removal with the maximum percent integrity uniformity (PIU_m ) of 91.0% and minimum standard deviation (SD) of 35.4 HU for delineated artifact regions among all models. The mean absolute error (MAE) of CBCT images in the thorax and abdomen were 71.6 and 55.2 HU, respectively, using planning CT images after deformable registration as ground truth. Compared with CBCT, the thoracic and abdominal sCT images generated by each model had significantly improved image quality with smaller MAE (p < 0.05). The SARN+cycAT obtained the minimum MAEs of 42.5 HU in the thorax while SARN+cycleGAN got the minimum MAEs of 32.0 HU in the abdomen. The sCT generated by U-Net had a remarkably lower anatomical structure accuracy compared with the other models. The thoracic and abdominal sCT images generated by SARN+cycleGAN showed optimal dose calculation accuracy with gamma passing rates (2 mm/2%) of 98.2% and 96.9%, respectively.

CONCLUSIONS

The proposed SARN can reduce serious streaking artifacts in CBCT images. The SARN combined with cycleGAN can generate high-quality sCT images with fewer artifacts, high-accuracy HU values, and accurate anatomical structures, thus providing reliable dose calculation in ART.

Hybrid Exercise Program Enhances Physical Fitness and Reverses Frailty in Older Adults: Insights and Predictions from Machine Learning

PURPOSE

The declining physical condition of the older adults is a pressing issue. Wu Qin Xi exercise, despite being low-intensity, is highly effective among older adults. Inspired by its characteristics, we designed a new exercise program for frail older adults, combining strength, endurance, and Wu Qin Xi. Furthermore, we employed machine learning to predict whether frailty can be reversed in older adults after the intervention.

METHODS

A total of 181 community-dwelling frail older adults aged 65 years or older participated in this single-center, randomized controlled study, with 54.7% (n=99) being female. The study assessed the effectiveness of several exercise modalities in reversing frailty. The Fried's frailty criterion was used to assess the degree of frailty of the subjects. Participants were assigned a three-digit code 001-163 and randomly assigned (1:1:1) by computer to three different groups based on the study participant number: the Wu Qin Xi group (WQX), the strength exercise mixed with endurance exercise training group (SE), and the WQXSE hybrid exercise group incorporated the above two. Body composition and frailty-related physical fitness factors were measured before and after a 24-week intervention. The measurements included Body height, Body mass, Timed Up and Go Test (TUGT), grip strength assessment (GS), 6min walk test (6 min WT), and 10 m maximum walk speed (10 m MWS). Data were analyzed using repeated measures ANOVA to determine group and time interaction effects and machine learning models were used to predict program effectiveness.

RESULTS

A total of 163 participants completed the study, with 53.9% (n=88) of them being female. The two items, 10 m maximum walking speed (10 m MWS) and grip strength, were significantly affected by the interaction of group and time. Compared to the other two groups, the WQXSE group showed the most improvement in the item 10 m MWS. In addition, following 24 weeks of training, 68 (41.7%) of the initially frail older adults had reversed their frailty status. Among them, 19 (36.5%) were in the WQX group, 24 (44.4%) were in the WQXSE group, and 25 (43.9%) were in the SE group. The stacking model exhibited superior performance when compared to other algorithms.

CONCLUSION

A hybrid exercise regimen comprising the Wu Qin Xi routine and exercises focused on both strength and endurance holds the potential to yield greater improvements in the physical fitness of older adults, as well as reducing frailty. Leveraging a stacking model, it is possible to forecast the likelihood of older adults successfully reversing their frailty status following participation in a prevention exercise program.

Multi-Task Learning for Pulmonary Arterial Hypertension Prognosis Prediction Via Memory Drift and Prior Prompt Learning on 3D Chest CT

Pulmonary arterial hypertension (PAH) prognosis prediction on 3D non-contrast CT images is one of the most important tasks for PAH treatment. It will help clinicians stratify patients into different groups for early diagnosis and timely intervention via automatically extracting the potential biomarkers of PAH to predict mortality. However, it is still a task of great challenges due to the large volume and low-contrast regions of interest in 3D chest CT images. In this paper, we propose the first multi-task learning-based PAH prognosis prediction framework, P ²-Net, which effectively optimizes the model and powerfully represents task-dependent features via our Memory Drift (MD) and Prior Prompt Learning (PPL) strategies. 1) Our MD maintains a large memory bank to provide a dense sampling of the deep biomarkers' distribution. Therefore, although the batch size is very small caused by our large volume, a reliable (negative log partial) likelihood loss is still able to be calculated on a representative probability distribution for robust optimization. 2) Our PPL simultaneously learns an additional manual biomarkers prediction task to embed clinical prior knowledge into our deep prognosis prediction task in hidden and explicit ways. Therefore, it will prompt the prediction of deep biomarkers and improve the perception of task-dependent features in our low-contrast regions. Our P ²-Net achieves a high prognostic correlation of the prediction and great generalization with the highest 70.19% C-index and 2.14 HR. Extensive experiments with promising results on our PAH prognosis prediction reveal powerful prognosis performance and great clinical significance in PAH treatment. All of our code will be made publicly available online Opened source: https://github.com/YutingHe-list/P2-Net.

Automatic segmentation for plan-of-the-day selection in CBCT-guided adaptive radiation therapy of cervical cancer

Objective.Plan-of-the-day (PoD) adaptive radiation therapy (ART) is based on a library of treatment plans, among which, at each treatment fraction, the PoD is selected using daily images. However, this strategy is limited by PoD selection uncertainties. This work aimed to propose and evaluate a workflow to automatically and quantitatively identify the PoD for cervix cancer ART based on daily CBCT images.Approach.The quantification was based on the segmentation of the main structures of interest in the CBCT images (clinical target volume [CTV], rectum, bladder, and bowel bag) using a deep learning model. Then, the PoD was selected from the treatment plan library according to the geometrical coverage of the CTV. For the evaluation, the resulting PoD was compared to the one obtained considering reference CBCT delineations.Main results.In experiments on a database of 23 patients with 272 CBCT images, the proposed method obtained an agreement between the reference PoD and the automatically identified PoD for 91.5% of treatment fractions (99.6% when considering a 5% margin on CTV coverage).Significance.The proposed automatic workflow automatically selected PoD for ART using deep-learning methods. The results showed the ability of the proposed process to identify the optimal PoD in a treatment plan library.

[Efficacy analysis of high-sensitivity troponin I concentration and its changes in the diagnosis of acute myocardial infarction]

Objective: To explore the feasibility and accuracy of 0-1 h high sensitivity cardiac troponin I (hs-cTnI) concentration and its changes in judging non-ST segment elevation myocardial infarction (NSTEMI), and to investigate the feasibility of a simplified process. Methods: Patients with acute chest pain and suspected NSTEMI who were admitted to the emergency department of Fuwai Hospital, the First Affiliated Hospital of Sun Yat-sen University and Nanjing First Hospital from January 2017 to September 2020 were selected. Hs-cTnI test was carried out for the selected patients at the time of visit (0 h) and 1 h after visit. According to the 0-1 h hs-cTnI diagnostic process and threshold standard recommended by European Society of Cardiology (ESC) guidelines in 2015, the laboratory adjudication was determined. Cardiologists who did not participate in the project design and did not know the results of hs-cTnI test performed the clinical judgment according to the routine diagnosis and treatment process of emergency department. Taking clinical judgment as the gold standard, the diagnostic efficacy of 0-1 h hs-cTnI concentration and its change recommended by the guidelines for judging NSTEMI in Chinese population was analyzed. The guide process was simplified. Under the condition of not considering the time of chest pain, the guideline threshold was used for test and judgement, and the diagnostic efficacy of the simplified process was evaluated. Results: A total of 1 534 patients were enrolled in the study, aged (62±12) years and 952 (62.1%) patients were male. Among them, 402 patients (26.2%) were clinically diagnosed as NSTEMI and 1 132 patients (73.8%) were diagnosed as non-NSTEMI. According to the diagnosis and determination process recommended by the guidelines, NSTEMI was excluded in 672 patients (42.8%), and 464 patients (30.2%) were diagnosed as NSTEMI. The consistency rate with clinical determination reached 92.4% (1 050/1 136), the sensitivity of excluding diagnosis was 99.5% (95%CI: 98.0%-99.9%), the negative predictive value was 99.7% (95%CI: 98.8%-99.9%), and the negative likelihood ratio was 0.008 (95%CI: 0.002-0.335). The diagnostic specificity was 92.6% (95%CI: 90.9%-94.0%), the positive predictive value was 81.9% (95%CI: 78.0%-85.2%), and the positive likelihood ratio was 12.739 (95%CI: 10.356-15.670). According to the simplified process, NSTEMI was excluded in 675 patients (44.0%), and 463 patients (30.2%) were diagnosed as NSTEMI. The consistency rate with clinical judgment was 92.4% (1 051/1 138), the sensitivity of exclusion diagnosis was 99.3% (95%CI: 97.6%-99.8%), the negative predictive value was 99.6% (95%CI: 98.6%-99.9%), and the negative likelihood ratio was 0.012 (95%CI: 0.004-0.389). The diagnostic specificity was 92.6% (95%CI: 90.9%-94.0%), the positive predictive value was 81.9% (95%CI: 78.0%-85.2%), and the positive likelihood ratio was 12.705 (95%CI: 10.328-15.630). There was no significant difference in diagnostic efficacy between the simplified process and the recommended process (all P>0.05). Conclusion: The diagnostic process for judging NSTEMI according to the 0-1 h hs-cTnI concentration and its change criteria recommended by the 2015 ESC guidelines is applicable in the Chinese population and remains highly accurate in judging NSTEMI without considering the duration of chest pain at the time of presentation.

A novel 3D deep learning model to automatically demonstrate renal artery segmentation and its validation in nephron-sparing surgery

Purpose

Nephron-sparing surgery (NSS) is a mainstream treatment for localized renal tumors. Segmental renal artery clamping (SRAC) is commonly used in NSS. Automatic and precise segmentations of renal artery trees are required to improve the workflow of SRAC in NSS. In this study, we developed a tridimensional kidney perfusion (TKP) model based on deep learning technique to automatically demonstrate renal artery segmentation, and verified the precision and feasibility during laparoscopic partial nephrectomy (PN).

Methods

The TKP model was established based on convolutional neural network (CNN), and the precision was validated in porcine models. From April 2018 to January 2020, TKP model was applied in laparoscopic PN in 131 patients with T1a tumors. Demographics, perioperative variables, and data from the TKP models were assessed. Indocyanine green (ICG) with near-infrared fluorescence (NIRF) imaging was applied after clamping and dice coefficient was used to evaluate the precision of the model.

Results

The precision of the TKP model was validated in porcine models with the mean dice coefficient of 0.82. Laparoscopic PN was successfully performed in all cases with segmental renal artery clamping (SRAC) under TKP model’s guidance. The mean operation time was 100.8 min; the median estimated blood loss was 110 ml. The ischemic regions recorded in NIRF imaging were highly consistent with the perfusion regions in the TKP models (mean dice coefficient = 0.81). Multivariate analysis revealed that the feeding lobar artery number was strongly correlated with tumor size and contact surface area; the supplying segmental arteries number correlated with tumor size.

Conclusions

Using the CNN technique, the TKP model is developed to automatically present the renal artery trees and precisely delineate the perfusion regions of different segmental arteries. The guidance of the TKP model is feasible and effective in nephron-sparing surgery.

Fucoxanthin ameliorated myocardial fibrosis in STZ-induced diabetic rats and cell hypertrophy in HG-induced H9c2 cells by alleviating oxidative stress and restoring mitophagy

Diabetic cardiomyopathy (DCM) is one of the leading causes of death in diabetic patients, and is accompanied by increased oxidative stress and mitochondrial dysfunction. Fucoxanthin (FX), as a marine carotenoid, possesses strong antioxidant activity. The main purpose of our study was to explore whether FX could attenuate experimental cardiac hypertrophy by affecting mitophagy and oxidative stress. We found that FX improved lipid metabolism, myocardial damage, myocardial fibrosis and hypertrophy in the myocardial tissue of STZ-induced diabetic rats. Additionally, FX upregulated Nrf2 signaling to reduce the level of reactive oxygen species (ROS). FX also promoted Bnip3/Nix signaling to improve mitochondrial function and reduced the levels of mitochondrial and intracellular ROS, thereby reversing HG-induced H9c2 cell hypertrophy. However, treatment with the autophagy inhibitor CQ abolished the anti-hypertrophic effect of FX, accompanied by impaired mitochondrial function and increased ROS levels. In conclusion, we found that FX reduced the accumulation of TGF-β1, FN and α-SMA to relieve myocardial fibrosis in STZ-induced diabetic rats, and FX up-regulated Bnip3/Nix to promote mitophagy and enhanced Nrf2 signaling to alleviate oxidative stress, thereby inhibiting hypertrophy in HG-induced H9c2 cells. These results imply that FX may be developed as a functional food for DCM.

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.