Spatial-temporal trends in leprosy burden and its associations with socioeconomic and physical geographic factors: results from the Global Burden of Disease Study 2019

OBJECTIVES

The purpose of our study was to assess the multiscalar changes in leprosy burden and its associated risk factors over the last three decades.

STUDY DESIGN

We conducted an in-depth examination of leprosy's spatial-temporal trends at multiple geographical scale (global, regional, and national), utilizing information from Global Burden of Disease, Injuries, and Risk Factors Study (GBD 2019).

METHODS

Incidence and the estimated annual percentage change (EAPC) in age-standardized incidence rate (ASIR) of leprosy were determined, with countries categorized based on leprosy incidence changes. We examined socioeconomic and physical geography influences on leprosy incidence via Spearman correlation analysis, using ternary phase diagrams to reveal the synergetic effects on leprosy occurrence.

RESULTS

Globally, incident cases of leprosy decreased by 27.86% from 1990 to 2019, with a reduction in ASIR (EAPC = -2.53), yet trends were not homogeneous across regions. ASIR and EAPC correlated positively with sociodemographic index (SDI), and an ASIR growth appeared in high SDI region (EAPC = 3.07). Leprosy burden was chiefly distributed in Tropical Latin America, Oceania, Central Sub-Saharan Africa, and South Asia. Negative correlations were detected between the incidence of leprosy and factors of SDI, GDP per capita, urban population to total population, and precipitation, whereas the number of refugee population, temperature, and elevation showed opposite positive results.

CONCLUSIONS

Despite a global decline in leprosy over the past three decades, the disparities of disease occurrence at regional and national scales still persisted. Socioeconomic and physical geographic factors posed an obvious influence on the transmission risk of leprosy. The persistence and regional fluctuations of leprosy incidence necessitate the ongoing dynamic and multilayered control strategies worldwide in combating this ancient disease.

Cross-Layer Contrastive Learning of Latent Semantics for Facial Expression Recognition

Convolutional neural networks (CNNs) have achieved significant improvement for the task of facial expression recognition. However, current training still suffers from the inconsistent learning intensities among different layers, i.e., the feature representations in the shallow layers are not sufficiently learned compared with those in deep layers. To this end, this work proposes a contrastive learning framework to align the feature semantics of shallow and deep layers, followed by an attention module for representing the multi-scale features in the weight-adaptive manner. The proposed algorithm has three main merits. First, the learning intensity, defined as the magnitude of the backpropagation gradient, of the features on the shallow layer is enhanced by cross-layer contrastive learning. Second, the latent semantics in the shallow-layer and deep-layer features are explored and aligned in the contrastive learning, and thus the fine-grained characteristics of expressions can be taken into account for the feature representation learning. Third, by integrating the multi-scale features from multiple layers with an attention module, our algorithm achieved the state-of-the-art performances, i.e. 92.21%, 89.50%, 62.82%, on three in-the-wild expression databases, i.e. RAF-DB, FERPlus, SFEW, and the second best performance, i.e. 65.29% on AffectNet dataset. Our codes will be made publicly available.

An autonomous wheelchair with health monitoring system based on Internet of Thing

Assistive powered wheelchairs will bring patients and elderly the ability of remain mobile without the direct intervention from caregivers. Vital signs from users can be collected and analyzed remotely to allow better disease prevention and proactive management of health and chronic conditions. This research proposes an autonomous wheelchair prototype system integrated with biophysical sensors based on Internet of Thing (IoT). A powered wheelchair system was developed with three biophysical sensors to collect, transmit and analysis users' four vital signs to provide real-time feedback to users and clinicians. A user interface software embedded with the cloud artificial intelligence (AI) algorithms was developed for the data visualization and analysis. An improved data compression algorithm Minimalist, Adaptive and Streaming R-bit (O-MAS-R) was proposed to achieve a higher compression ratio with minimum 7.1%, maximum 45.25% compared with MAS algorithm during the data transmission. At the same time, the prototype wheelchair, accompanied with a smart-chair app, assimilates data from the onboard sensors and characteristics features within the surroundings in real-time to achieve the functions including obstruct laser scanning, autonomous localization, and point-to-point route planning and moving within a predefined area. In conclusion, the wheelchair prototype uses AI algorithms and navigation technology to help patients and elderly maintain their independent mobility and monitor their healthcare information in real-time.

Therapeutic potential of elema-1,3,7(11),8-tetraen-8,12-lactam from Curcuma wenyujin on diabetic retinopathy via anti-inflammatory and anti-angiogenic pathways

ETHNOPHARMACOLOGICAL RELEVANCE

In traditional Chinese medicine, the causes of diabetic retinopathy (DR) are blood stasis and heat. Curcuma wenyujin Y. H. Chen & C. Ling and its extracts have the effects of promoting blood circulation to remove blood stasis, clearing the heart, and cooling the blood, and have been used in the treatment of DR. Elema-1,3,7 (11),8-tetraen-8,12-lactam (Ele), an N-containing sesquiterpene isolated from this plant. However, the anti-inflammatory and anti-angiogenic effects of Ele and its therapeutic potential in DR are still unknown.

AIM OF THE STUDY

To evaluate the anti-inflammatory and anti-angiogenic effects of Ele and its therapeutic potential in DR.

MATERIALS AND METHODS

In vitro, anti-inflammatory and anti-angiogenic effects were assessed using TNF-α or VEGF-stimulated HUVECs. Protein expression was analyzed using Western blotting. ICAM-1 and TNF-α mRNA expressions were analyzed using real-time quantitative RT-PCR. The therapeutic potential in DR was assessed using both animal models of STZ-induced diabetes and oxygen-induced retinopathy. The retinal vascular permeability was measured using Evans blue, and the quantitation of retinal leukostasis using FITC-coupled Con A. The retinal neovascular tufts were analyzed using fluorescein angiography and counting pre-retinal vascular lumens.

RESULTS

Ele inhibited NF-κB pathway, and ICAM-1, TNF-α mRNA expression in TNF-α- stimulated HUVECs. It also inhibits the multistep process of angiogenesis by inhibiting the phosphorylation of VEGFR2 and its downstream signaling kinases Src, Erk1/2, Akt, and mTOR in VEGF-stimulated HUVECs. Intravitreal injection of Ele can significantly reduce retinal microvascular leakage, leukostasis, and expression of ICAM-1, TNF-α in diabetic rats and inhibits oxygen-induced retinal neovascularization and VEGFR2 phosphorylation in OIR mice.

CONCLUSIONS

Ele has anti-inflammatory and anti-angiogenic effects through inhibiting NF-κB and VEGFR2 signaling pathways, and it may be a potential drug candidate for DR.

Tislelizumab versus chemotherapy as second-line treatment for European and North American patients with advanced or metastatic esophageal squamous cell carcinoma: a subgroup analysis of the randomized phase III RATIONALE-302 study

BACKGROUND

The phase III RATIONALE-302 study evaluated tislelizumab, an anti-programmed cell death protein 1 antibody, as second-line (2L) treatment for advanced/metastatic esophageal squamous cell carcinoma (ESCC). This prespecified exploratory analysis investigated outcomes in patients from Europe and North America (Europe/North America subgroup).

PATIENTS AND METHODS

Patients with tumor progression during/after first-line systemic treatment were randomized 1 : 1 to open-label tislelizumab or investigator's choice of chemotherapy (paclitaxel, docetaxel, or irinotecan).

RESULTS

The Europe/North America subgroup comprised 108 patients (tislelizumab: n = 55; chemotherapy: n = 53). Overall survival (OS) was prolonged with tislelizumab versus chemotherapy (median: 11.2 versus 6.3 months), with a hazard ratio (HR) of 0.55 [95% confidence interval (CI) 0.35-0.87]; HR was similar irrespective of programmed death-ligand 1 score [≥10%: 0.47 (95% CI 0.18-1.21); <10%: 0.55 (95% CI 0.30-1.01)]. Median progression-free survival was 2.3 versus 2.7 months with tislelizumab versus chemotherapy [HR: 0.97 (95% CI 0.64-1.47)]. Overall response rate was greater with tislelizumab (20.0%) versus chemotherapy (11.3%), with more durable response (median duration of response: 5.1 versus 2.1 months). Tislelizumab had a favorable safety profile versus chemotherapy, with fewer patients experiencing ≥grade 3 treatment-related adverse events (13.0% versus 51.0%). Those on tislelizumab experienced less deterioration in health-related quality of life, physical functioning, and/or disease- and treatment-related symptoms (i.e. fatigue, pain, and eating problems) as compared to those on chemotherapy, per the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (QLQ-C30) and QLQ-OES18 scores.

CONCLUSIONS

As a 2L therapy for advanced/metastatic ESCC, tislelizumab improved OS and had a favorable safety profile as compared to chemotherapy in European/North American ESCC patients in the randomized phase III RATIONALE-302 study.

A Chinese Face Dataset with Dynamic Expressions and Diverse Ages Synthesized by Deep Learning

Facial stimuli have gained increasing popularity in research. However, the existing Chinese facial datasets primarily consist of static facial expressions and lack variations in terms of facial aging. Additionally, these datasets are limited to stimuli from a small number of individuals, in that it is difficult and time-consuming to recruit a diverse range of volunteers across different age groups to capture their facial expressions. In this paper, a deep-learning based face editing approach, StyleGAN, is used to synthesize a Chinese face dataset, namely SZU-EmoDage, where faces with different expressions and ages are synthesized. Leverage on the interpolations of latent vectors, continuously dynamic expressions with different intensities, are also available. Participants assessed emotional categories and dimensions (valence, arousal and dominance) of the synthesized faces. The results show that the face database has good reliability and validity, and can be used in relevant psychological experiments. The availability of SZU-EmoDage opens up avenues for further research in psychology and related fields, allowing for a deeper understanding of facial perception.

[Preliminary analysis of seasonal pollen allergens of allergic rhinitis in a hospital of Nanchang City]

The study was aimed to analyze the seasonal pollen allergen spectrum of patients with allergic rhinitis (AR) in Nanchang city, and to provide evidence for improving the clinical diagnosis, treatment, prevention and epidemiology of seasonal AR. A retrospective analysis was conducted on the results of skin prick test (SPT) among 1 752 patients with AR in outpatient at Department of Otolaryngology, the First Affiliated Hospital of Nanchang University from September 2020 to August 2021 (a total of 1 069 males and 683 females, age ranged from 2 to 84 years old). SPSS 22.0 software was used to analyze the positive rates of main allergens and their differences in gender, age, and month of visit. Differences among groups were compared by student t test, Wilcox rank sum test, or χ2 test. The results showed that among 1 752 SPT-positive patients, the number of simple seasonal AR and the number of perennial combined seasonal AR were 102 (5.82%) and 281 (16.04%), respectively. There was no significant difference between male and female patients in positive seasonal pollen allergens (χ2=2.181, P>0.05), but the positive rate of indoor seasonal pollen allergens in males was higher than that in females (χ2=7.901, P<0.05). The seasonal pollen allergens ranking top 5 of the positive rates were willow (6.62%, 116/1 752), humulus scandens (5.71%, 100/1 752), rape (5.54%, 97/1 752), grey pigweed (4.62%, 81/1 752) and birch (3.60%, 63/1 752). The positive rates of indoor and seasonal pollen allergens increased first and then decreased in different age groups, and the highest positive rates of seasonal pollen allergens were in the age group of 31-40 years old, with statistical significance compared with other groups (χ2=61.269, P<0.05). The seasonal allergen positive rate showed two peaks in time: March to May and September to November. The positive rate of pollen in spring was 60.27% (132/219), which was significantly higher than that in autumn (39.73%,87/219) (χ2=9.247, P<0.05). The positive rate of pollen combination in spring and autumn was 68.29% (112/164), which was significantly higher than that in spring and autumn alone (18.9%,31/164) and (12.8%, 21/164) (χ2=14.731, P<0.05). In summary, pollen allergy in Nanchang City cannot be ignored, accounting for more than 20% of the total number of AR. The incidence of seasonal AR in Nanchang City showed two peaks (March to May and September to November). The common allergens for seasonal AR in Nanchang City were willow, humulus scandens, rape, grey chenopods and birch.

[Incidence and related factors of chronic neuropathic pain in elderly patients after video-assisted thoracoscopic surgery]

Objective: To investigate the incidence and related factors of chronic neuropathic pain (CNP) in elderly patients after thoracoscopic surgery. Methods: A total of 463 elderly patients (aged≥60 years) who underwent elective video-assisted thoracoscopic surgery from November 2020 to May 2021 at Peking Union Medical College Hospital were prospectively recruited. Among them, 283 were males and 180 were females, with an average age of (66.6±4.8) years. Chronic postsurgical pain (CPSP) was assessed by telephone at 6 months after surgery, and then the patients with CNP were screened using the ID-pain scale. Multivariable logistic regression was used to analyze the related factors for CNP in elderly patients after thoracoscopic surgery. Results: The incidence of CPSP was 41.9% (194/463), and the incidence of CNP was 18.8% (87/463). Multivariable logistic regression analysis showed that incision number<3 (OR=0.385, 95%CI: 0.156-0.949, P=0.038) and intraoperative N2O inhalation (OR=0.506, 95%CI: 0.304-0.842, P=0.009) were protective factors for CNP in elderly patients after thoracoscopic surgery, but high numeric rating scale (NRS) score on the first day after surgery (OR=1.180, 95%CI: 1.056-1.318, P=0.003) was a risk factor. Conclusions: The incidence of CNP in elderly patients after thoracoscopic surgery is 18.8%. Incision number<3 and intraoperative N2O inhalation are protective factors for CNP, but high NRS score on the first day after surgery is a risk factor.

[A phase I study of subcutaneous envafolimab (KN035) monotherapy in Chinese patients with advanced solid tumors]

Objective: To evaluate the safety and antitumor activity of envafolimab monotherapy in Chinese patients with advanced solid tumors. Methods: This open-label, multicenter phase I trial included dose escalation and dose expansion phases. In the dose escalation phase, patients received subcutaneous 0.1, 0.3, 1.0, 2.5, 5.0 or 10.0 mg/kg envafolimab once weekly (QW) following a modified "3+ 3" design. The dose expansion phase was performed in the 2.5 mg/kg and 5.0 mg/kg (QW) dose cohorts. Results: At November 25, 2019, a total of 287 patients received envafolimab treatment. During the dose escalation phase, no dose-limiting toxicities (DLT) was observed. In all dose cohorts, drug-related treatment-emergent adverse events (TEAEs) for all grades occurred in 75.3% of patients, and grade 3 or 4 occurred in 20.6% of patients. The incidence of immune-related adverse reactions (irAE) was 24.0% for all grades, the most common irAEs (≥2%) included hypothyroidism, hyperthyroidism, immune-associated hepatitis and rash. The incidence of injection site reactions was low (3.8%), all of which were grades 1-2. Among the 216 efficacy evaluable patients, the objective response rate (ORR) and disease control rate (DCR) were 11.6% and 43.1%, respectively. Median duration of response was 49.1 weeks (95% CI: 24.0, 49.3). Pharmacokinetic (PK) exposure to envafolimab is proportional to dose and median time to maximum plasma concentration is 72-120 hours based on the PK results from the dose escalation phase of the study. Conclusion: Subcutaneous envafolimab has a favorable safety and promising preliminary anti-tumor activity in Chinese patients with advanced solid tumors.

Dosimetric Predictors of Acute Diarrhea in Locally Advanced Rectal Cancer Patients Treated with Neoadjuvant Chemoradiation with Capecitabine and Irinotecan: A Discovery and Validation Study

PURPOSE/OBJECTIVE(S)

Additional irinotecan can increase the pCR rate from 15% to 30% compared with capecitabine-based neoadjuvant chemoradiotherapy in locally advanced rectal cancer, while more acute diarrhea was induced and predictors of diarrhea have yet to be fully elucidated. In this analysis, we report the incidence of and factors associated with grade 3+ acute diarrhea in LARC patients treated with the CaplriRT regimen in the CinClare trial.

MATERIALS/METHODS

We identified the dosimetric markers with a lasso-Cox risk scoring model tested on CaplriRT group patients in the CinClare trial at our institution from 2015 to 2017 (CinClare, NCT02605265), and then independently validated according to a predefined protocol in patients treated with neoadjuvant chemoradiation with capecitabine and irinotecan from 2019 to 2022 (NCT05688033). Clinical documentation and patient-reported outcomes were reviewed to determine grade 3+ acute diarrhea events.

RESULTS

A total of 116 patients from Cinclare trial treated with CaplriRT regimen were used as a training cohort to obtain dosimetric prediction model and 168 patients were used for independent validation. The majority received 50 Gray (Gy) in 25 fractions with concurrent capecitabine and irinotecan. Median number of concurrent chemotherapy cycles received was 4 (IQR: 3-4). Seventeen (23.6%) patients treated with the CaplriRT regimen in the CinClare trial experienced grade 3+ acute diarrhea. Dosimetric predictors of acute diarrhea included peritoneal space volume receiving 25 Gy or greater (V25Gy). The single multivariate Cox regression, and receiver operating characteristic (ROC) curve analysis showed that the model had good predictive ability (p<0.05). It was also validated using the validation cohort. Patients with peritoneal space V25Gy>950 cm3 were associated with a higher risk of 3+ acute diarrhea compared with those without constraints of V25Gy (p = 0.002).

CONCLUSION

Peritoneal space V25Gy as an important predictor of acute diarrhea during capecitabine and irinotecan neoadjuvant chemoradiation treatment. Peritoneal space V25Gy < 950 cm3 may reduce acute diarrhea toxicity.

Accelerating Volumetric CT and MRI Imaging by Reference-Free Deep Learning Transformation from Low-Resolution to High-Resolution

PURPOSE/OBJECTIVE(S)

High-resolution (HR) images are important in precision radiation oncology. However, acquiring HR volumetric CT and MRI images is often time consuming; also, the resolution in some direction(s) (e.g., z-direction in the case of CT) is often limited by imaging hardware or fundamental imaging principle. Super-resolution (SR) imaging, i.e., the low-resolution (LR) to HR image transformation, is widely used to improve image resolution. Data-driven deep learning (DL) methods have achieved great success in SR imaging, yet they can hardly be applied to medical imaging as they require large amount of LR-HR image pairs to train the model. We therefore propose a reference-free DL method to increase resolutions of volumetric medical images in an efficient way.

MATERIALS/METHODS

We propose a maximum likelihood estimation (MLE)-based implicit neural representation (INR) network for SR imaging. The INR network aims to represent an image as a continuous function parameterized by a coordinate-based multi-layer perceptron. The INR network takes image coordinates as input and outputs corresponding pixel intensities. To train the network without using any HR images, we use a MLE framework to model LR observations' statistics and their relation to the latent HR image. The predicted HR image from the INR's output is transformed to LR images based on the MLE, and the network parameters are then optimized by minimizing the distance between the transformed LR images and actual LR observations. We demonstrate the efficacy of the proposed method on CT and MRI images for 2x, 4x, and 8x SR using only one or two LR image(s). The performance is compared with a conventional SR method named plain MLE, in terms of visual quality and numerical qualities of PSNR and SSIM.

RESULTS

Our method outperformed the plain MLE method in the experiment. Table 1 reports the numerical improvements of our method over the compared plain MLE method. For 2x SR with a single LR image, our method achieved significant improvements in both PSNR and SSIM. When using two LR images, the better structural restoration capability of our method became more obvious with higher SR magnifications, as indicated by the increased SSIM differences. Better noise suppression capability of our method is observed in all our studies, as indicated by the PSNR values. In visual quality evaluation, we observed sharper image details with less noise in SR images generated by the proposed method, compared with the plain MLE method.

CONCLUSION

The proposed novel reference-free DL method can efficiently provide high-quality HR images with only one or two LR images for CT and MRI imaging. This method can be easily generalized to many other radiation therapy related applications without the requirement for HR reference images.

A Nomogram to Predict Pathological Axillary Status in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy

PURPOSE/OBJECTIVE(S)

This study aimed to identify factors influencing axillary pathological complete response (pCR) and to develop a predictive nomogram to evaluate axillary pCR rate in breast cancer patients treated with neoadjuvant chemotherapy (NAC).

MATERIALS/METHODS

A total of 2368 patients who received NAC and mastectomy between 2000 and 2014 from 12 grade A tertiary hospitals in China were analyzed retrospectively. The patients treated in three cancer hospitals (training set, n = 1629) were used to construct the nomogram based on multivariate logistic regression analyses. The nomograph was validated by the area under the receiver operating characteristic curve (AUC) and calibration curve in patients from 9 other general hospitals (validation set, n = 739).

RESULTS

The nomogram incorporated seven predicting factors including NACT cycles, response to NACT, clinical T stage, clinical N stage, grade, LVI, and molecular subtype. The AUC for the training set and validation set were 0.762 and 0.802, respectively. In addition, the calibration curve also showed good agreement between the nomogram-based predictions and the actual observations.

CONCLUSION

A nomogram was established to predict the status of axillary lymph nodes in breast cancer patients after NAC. The predictive model performed well both in the training set and external validation set.

Real Time Volumetric MRI for MR-Guided 3D Motion Tracking via Sparse Prior-Augmented Neural Representation Learning

PURPOSE/OBJECTIVE(S)

To reconstruct volumetric MRI from orthogonal cine acquisition aided by sparse priors of 2 static 3D MRI through implicit neural representation (NeRP) learning, with the goal of eliminating large-scale training datasets for data-driven sparse MRI reconstruction and supporting clinical workflow of real time 3D motion tracking during MR-guided radiotherapy.

MATERIALS/METHODS

A multi-layer perceptron network was trained to learn the NeRP of a patient-specific MRI dataset, where the network takes 4D data coordinates of voxel locations and motion states as inputs and outputs corresponding voxel intensities. By first learning the NeRP of 2 static 3D MRI with different breathing motion states, prior knowledge of patient breathing motion was embedded into network weights through optimization. The prior knowledge was then augmented from 2 to 31 motion states by querying the optimized network at interpolated/extrapolated motion state coordinates. Starting from the prior-augmented network as an initialization point, the network was further trained using sparse samples of 2 orthogonal cine slices. The final volumetric reconstruction was obtained by querying the trained network at desired 3D spatial locations. We evaluated the proposed method using 5-minute volumetric MRI time series with 340 ms temporal resolution collected from 7 liver carcinoma patients. The time series was acquired using golden-angle radial MRI sequence and reconstructed through retrospective sorting. Two MRI with inhale and exhale states respectively were selected from the first 30 sec of the time series for prior embedding and augmentation. The remaining 4.5-min time series was used for volumetric reconstruction evaluation, where we retrospectively subsampled each MRI to 2 orthogonal slices and compared network-reconstructed images to ground truth images in terms of image quality and the capability of supporting 3D target motion tracking.

RESULTS

Across the 7 patients evaluated, the peak signal to noise ratio between model reconstruction and ground truth was 54.66 ± 6.16 dB and the structural similarity index measure was 0.99 ± 0.01. Gross tumor volume (GTV) contours estimated by deforming a reference state MRI to model-reconstructed and ground truth MRI showed good consistency. The 95-percentile Hausdorff distance between GTV contours was 1.89 ± 1.13 mm, which is less than the voxel dimension. The mean GTV centroid position difference between ground truth and model estimation was less than 1 mm in all 3 orthogonal directions.

CONCLUSION

Volumetric MRI from orthogonal cine acquisition with sparse priors is feasible by modeling prior knowledge through implicit neural representation learning. The model-reconstructed images showed sufficient accuracy in supporting 3D motion tracking of abdominal targets. By eliminating the need for large scale training datasets, the method promises to enable clinical implementation of 3D motion tracking for precision radiation therapy.

Recurrence Risk Score Model for Evaluating the Impact of Postmastectomy Radiotherapy in Breast Cancer Patients with Pathologic Nodal Negative after Neoadjuvant Chemotherapy and Mastectomy

PURPOSE/OBJECTIVE(S)

Recurrence risk score model was established to distinguish the recurrent risk of patients with pathologic nodal negative (ypN0) after neoadjuvant chemotherapy (NACT) and mastectomy and determine the impact of postmastectomy radiotherapy (PMRT).

MATERIALS/METHODS

This multicenter retrospective study reviewed 766 patients who underwent mastectomy and NACT with ypN0 from 2000 to 2014. Recurrent risk score model was assigned proportionally to the relative contribution of independent prognostic factors in the multivariate Cox model of disease-free survival (DFS). Decision tree analysis was conducted to determine two optimal cutoff points for stratification.

RESULTS

The median follow-up time was 74 months. The 5-year locoregional control (LRC), DFS, and overall survival (OS) rates for the entire group were 96.5%, 89.1% and 95.3%, respectively. 353 (46.1%) patients received PMRT and 413 (53.9%) patients did not. Patients with PMRT have more high-risk factors, including age <40 years, clinical stage III, grade III, or ER and PR negative. Chest wall and regional nodal region were irradiated in 307 (87.0%) and chest wall only in 46 (13.0%). The median radiation dose was 50 Gy (range: 36-60 Gy) in 25 fractions (range: 15-30 fractions). There were no significant differences between the PMRT and No-PMRT groups in the LRC, DFS and OS rates. Recurrent risk score model consisted of five factors and used a range of zero to eleven scoring points: age <40 years and clinical N1 stage for one point; clinical N2, NACT ≥4 cycles, lymphovascular invasion and ypT1-2 for two points; ypT3-4 for four points. 456 (59.5%) patients scoring zero to four points, 188 (24.5%) scoring five points and 122 (15.9%) scoring six to eleven points were assigned to the low-, intermediate-, and high-risk group. LRC, DFS and OS rates in three risk groups were significantly distinct from each other (5yr-LRC: 98.6% vs. 95.5% vs. 89.8%, p < .001; 5yr-DFS: 94.4% vs. 87.4% vs. 71.5%, p < .001; 5yr-OS: 97.6% vs. 93.2% vs. 90.0%, p < .001). PMRT had no impact on the LRC, DFS and OS rates in either low-, intermediate-, or high-risk group.

CONCLUSION

The recurrence risk score model can effectively distinguish patients with different recurrent risk stratification. PMRT in patients with ypN0 after NAC and mastectomy cannot improve LRC, DFS or OS. Table 1. Survival outcomes and comparison between PMRT and No-PMRT arms in different groups.

[The efficacy of thin struct bare stents for the treatment of spontaneous isolated dissection of the superior mesenteric artery]

Objective: To examine the safety and effectiveness of thin struct bare stents for the treatment of spontaneous isolated dissection of the superior mesenteric artery (SIDSMA). Methods: The data of 32 patients admitted to First Hospital of Jiaxing (20 cases) and Jinling Hospital (12 cases) with SIDSMA from January 2016 to January 2021 were retrospectively analyzed. There were 27 males and 5 females, aging (54.8±9.4) years (range: 36 to 75 years). All patients were treated with thin struct bare stents. Controllable spring coils were used to fulfill the false lumen in 2 cases. Symptoms, vascular remodeling pattern at the SIDSMA lesion, and patency of the stents were observed during follow-up. Results: The surgical success rate was 100%. According to the length of the lesions and stents, the number of stents implanted was 1 in 17 cases, 2 in 11 cases and 3 in 4 cases. The angiography showed that blood flow in the stent was smooth and that the false lumen disappeared or weakened. The numerical rating scale for abdominal pain decreased from 6.1±1.5 (range: 4 to 10) preoperatively to 1.0 (1.0) (range: 0 to 3) 1 hour postoperatively (W=528, P<0.01). The compression rate of the true lumen of the superior mesenteric artery decreased from (92.3±6.7)% (range: 25% to 94%) preoperatively to 0.8 (1.2)% (range: 0 to 3.2%) 1 month postoperatively (W=528, P<0.01). The primary patency rate of CT angiography at 1 month postoperatively was 100%. The vascular remodeling rate was (92.3±6.7)% (range: 80% to 100%). All patients were followed for (46.3±17.0) months (range: 24 to 76 months). The cumulative patency rates in 1, 2 and 5 years were all 100%. Conclusion: The use of thin struct bare stents for SIDSMA is safety and efficacy.

[Safety evaluation of simultaneous administration of quadrivalent influenza split virion vaccine and 23-valent pneumococcal polysaccharide vaccine in adults aged 60 years and older]

Objective: To evaluate the safety of simultaneous administration of quadrivalent influenza split virion vaccine and 23-valent pneumococcal polysaccharide vaccine in adults aged 60 years and older. Methods: From November 2021 to May 2022, eligible participants aged 60 years and older were recruited in Taizhou City, Jiangsu Province, China, and a total of 2 461 participants were ultimately enrolled in this study. Each participant simultaneously received one dose of quadrivalent influenza split virion vaccine and one dose of 23-valent pneumococcal polysaccharide vaccine. The safety was observed within 28 days after vaccination. Safety information was collected through voluntary reporting and regular follow-ups. Results: All 2 461 participants completed the simultaneous administration of both vaccines and the safety follow-ups for 28 days after vaccination. The mean age of the participants was (70.66±6.18) years, with 54.61% (1 344) being male, and all participants were Han Chinese residents. About 22.51% (554) of the participants had underlying medical conditions. The overall incidence of adverse reactions within 0-28 days after simultaneous vaccination was 2.07% (51/2 461), mainly consisting of Grade 1 adverse reactions [1.83% (45/2 461)], with no reports of Grade 4 or higher adverse reactions or vaccine-related serious adverse events. The incidence of local adverse reactions was 0.98% (24/2 461), primarily presenting as pain at the injection site [0.93% (23/2 461)]. The incidence of systemic adverse reactions was 1.42% (35/2 461), with fever [0.85% (21/2 461)] being the main symptom. In the group with underlying medical conditions and the healthy group, their overall incidence of adverse reactions was 2.53% (14/554) and 1.94% (37/1 907), respectively. The incidence of local adverse reactions in the two groups was 1.62% (9/554) and 0.79% (15/1 907), respectively, and the incidence of systemic adverse reactions was 1.44% (8/554) and 1.42% (27/1 907), respectively, with no statistically significant differences between them (all P>0.05). Conclusion: It is safe for adults aged 60 years and older to receive quadrivalent influenza split virion vaccine and 23-valent pneumococcal polysaccharide vaccine at the same time.

Naples prognostic score as a predictor of outcomes in lung cancer: a systematic review and meta-analysis

OBJECTIVE

The Naples prognostic score (NPS) is a newly developed indicator of inflammation and nutritional status. However, its role in predicting the prognosis of lung cancer is unclear. We hereby reviewed the association between NPS and outcomes of lung cancer.

MATERIALS AND METHODS

PubMed, Web of Science, Embase, and Google Scholar were searched up to 15th April 2023 for studies assessing the predictive role of NPS for overall survival (OS) and disease-free survival (DFS) in lung cancer.

RESULTS

Seven studies were included. All were from China. One study was on small cell lung cancer, while the rest were on non-small cell lung cancer. Meta-analysis demonstrated that a high NPS score was a significant predictor of OS (HR: 3.21 95% CI: 2.27, 4.54 I2=62%) and disease-free survival (DFS) (HR: 3.81 95% CI: 2.57, 5.64 I2=65%) in lung cancer patients. Subgroup analysis based on different NPS reference values also showed similar results. The results remained significant on sensitivity analysis.

CONCLUSIONS

The NPS is a strong and independent prognostic indicator of lung cancer patients. Higher NPS scores are associated with worse OS and DFS. Further studies from non-Chinese populations are needed to supplement the results.

[Chest hemorrhage after left total pulmonary resection for secondary rifampin-resistant tuberculosis:a case report]

The patient had received five courses of anti-tuberculosis treatment for recurrent tuberculosis. The drug sensitivity test results of the first three courses showed drug-sensitive pulmonary tuberculosis, and the fourth diagnosis was rifampin-resistant tuberculosis (RR-TB), complicated by chronic obstructive pulmonary disease, type Ⅱ respiratory failure, pulmonary heart disease, and heart failure (grade Ⅲ). The patient stopped taking the anti-tuberculosis drugs on his own in the eighth month of receiving the resistant treatment. After admission, the symptoms improved temporarily after receiving oxygen therapy, anti-infection, and anti-tuberculosis treatment. Because of hemoptysis, the patient underwent arterial embolization by catheterization, but a large amount of hemoptysis occurred shortly thereafter. Emergency left total lung resection and gauze packing for hemostasis were performed. After surgery, the patient's vital signs were maintained with mechanical ventilation and vasopressors. Forty-eight hours after surgery, the gauze was removed, and the patient underwent tracheotomy, enteral nutrition, and anti-tuberculosis treatment. After discharge, the patient underwent rehabilitative exercise and anti-resistant tuberculosis therapy. The patient's condition remained stable for more than six months of follow-up.

[Effect of Porphyromonas gingivalis infection on IFNGR1 palmitoylation in esophageal cancer cells]

OBJECTIVE

To investigate the effect of Porphyromonas gingivalis (Pg) infection on IFNGR1 palmitoylation and biological behaviors of esophageal squamous cell carcinoma (ESCC) cells and the clinical implications.

METHODS

The expression levels of IFNGR1 protein in ESCC cell lines KYSE30 and KYSE70 were detected using Western blotting at 24 and 48 h after Pg infection, and 2-BP was used to detect IFNGR1 palmitoylation in the cells. KYSE70 cells with wild-type IFNGR1 (IFNGR1-WT cells) and with IFNGR1-C122A palmitoylation site mutation induced by site-specific mutagenesis (IFNGR1-C122A cells) were both infected with Pg, and the changes in palmitoylation of IFNGR1-C122A were analyzed using immunofluorescence and Click-iT assays. The changes in proliferation, migration and invasion ability of the infected cells were evaluated using plate cloning assay, scratch assay and Transwell assay, and IFNGR1 co-localization with lysosomal marker LAMP2 was dected using immunofluorescence assay. Immunohistochemistry was used to detect Pg infection and IFNGR1 protein expression in 50 ESCC tissues, and their correlation with the clinicopathological characteristics and survival outcomes of the patients was analyzed.

RESULTS

Pg infection down-regulated the protein expression of IFNGR1 in ESCC and promoted IFNGR1 palmitoylation at site 122. In IFNGR1-WT cells, Pg infection significantly enhanced cell proliferation, migration and invasion (P < 0.05). Similarly, Pg also significantly promoted proliferation, migration and invasion of IFNGR1-C122A cells, but to a lesser extent as compared with the wild-type cells (P < 0.05). Immunofluorescence assay showed that Pg and ZDHHC3 promoted IFNGR1 degradation within the lysosome. Immunohistochemical studies of the ESCC tissue samples showed a negative correlation between IFNGR1 and Pg expression, and a reduced IFNGR1 expression was correlated with a poorer survival outcome of the patient.

CONCLUSION

Pg infection enhances IFNGR1 palmitoylation to promote progression of ESCC, and elimination of Pg and inhibiting IFNGR1 palmitoylation may effectively control ESCC progression.

[Comparison of corneal power assessment methods after small incision lenticule extraction]

Objective: To compare the accuracy of different corneal curvature parameters in assessing the corneal refractive status and tracking corneal power changes after small incision lenticule extraction (SMILE). Methods: This prospective cross-sectional study tracked and recorded total corneal curvature parameters measured by different instruments before and three months after SMILE for myopia. These parameters, including total keratometry (TK) from the IOLMaster 700, total corneal refractive power (TCRP) from the Pentacam AXL, real keratometry (RK) from the CASIA 2, and corrected parameters calculated using the Haigis, Shammas, and Maloney methods, were compared with data obtained using the clinical history method (CHM). Surgically induced changes in TK, TCRP, and RK were analyzed and compared with those in spherical equivalent on the corneal plane (ΔSEco). Results: The study included 40 eyes (40 participants). After SMILE, the difference was smallest between TK [(0.08±0.38) D] and CHM values (P>0.05). However, TCRP, RK, K_Haigis, K_Shammas, and K_Maloney were significantly different from CHM data (P<0.05). The width of the 95% limits of agreement of TK (1.49 D) was narrowest, followed by that of RK (1.57 D). Pearson analysis showed that each parameter had a good correlation with CHM data. The differences between the changes in TK, TCRP and RK caused by surgery and ΔSEco were (0.03±0.39) D, (0.17±0.43) D, and (-0.19±0.46) D, respectively. The width of the 95% limits of agreement of ΔTK (1.54 D) was narrowest, and the correlation coefficient of ΔTK (0.951) was highest. Conclusion: The parameter TK of the IOLMaster 700 can provide accurate and objective corneal power evaluation after SMILE.

Clinical Value of Platelet Indices in Premature Coronary Artery Disease

Platelets play an important role in the pathophysiology of coronary artery disease. However, the clinical value of platelet indices in premature coronary heart disease remains largely unknown.Consecutive patients referred for coronary angiography were evaluated (n = 1675). Patients were stratified into premature coronary heart disease (n = 679, age < 55 for male and age < 65 for female), late-onset coronary heart disease (n = 772, age ≥ 55 for male and age ≥ 65 for female), and control (n = 224, age < 55 for male and age < 65 for female). Their clinical and laboratory parameters were collected. The relationship between platelet indices and premature coronary artery disease was analyzed.In univariate analysis, platelet indices showed no significant association with the presence of premature coronary heart disease (P > 0.05). After adjustment for traditional risk factors, mean platelet volume (0.823 [0.683-0.993], P = 0.042) and platelet-large cell ratio (0.976 [0.954-0.999], P = 0.040) were negatively correlated with the presence of premature coronary heart disease. The platelet-to-lymphocyte ratio was statistically significant among different numbers of coronary lesions (P = 0.035). In subgroup analysis, platelet-large cell ratio (1.190 [1.010-1.403], P = 0.038) was an independent risk factor of coronary restenosis after percutaneous coronary intervention.Platelet indices were associated with the prevalence, severity, and coronary restenosis after percutaneous coronary intervention suggesting their possible clinical application in premature coronary heart disease.

Evaluation of the Efficiency of TIMP-2 as a Biomarker for Acute Kidney Injury in Sepsis

The aim of this study was to evaluate the biomarker potential of TIMP-2 in septic-induced acute kidney injury (AKI). Healthy male rats (n=56, age 8-10 weeks, body weight 250-300 g) were randomized into 3 groups: controls (intact rats, n=6), sham-operated (SO, n=24), and sepsis model (cecum ligation and perforation, CLP, n=24). Thirty minutes before and 6, 12, 24, and 48 h after surgery, blood samples were collected to measure serum creatinine, blood urea nitrogen (BUN), and TIMP-2 and the kidneys were isolated for histopathological analysis and Western blotting. The key sepsis-related genes were screened through bioinformatics analysis. In 24 and 48 h after surgery, 2 rats in the SO group reached the diagnostic criteria of AKI (increased levels of serum creatinine and BUN). In the CLP group, serum creatinine in 6 h after the surgery was slightly higher than 30 min before the surgery, but this change did not meet the diagnostic criteria for AKI. In the CLP group, BUN was normal 6 h after the surgery, but increased after 12 h. In more than 50% rats of the CLP group, serum creatinine and BUN significantly increased 12 h after operation, so this can be diagnosed as AKI. In rats of the CLP group, plasma TIMP-2 was elevated 6 h after surgery and increased with time, suggesting that plasma TIMP-2 can be used as an early marker of AKI. Histological examination of the kidneys in this group revealed destruction of the renal tubular structure, swelling of renal tubular epithelium, the disappearance of brush edge and collapse of necrotic epithelial cells, etc., and the degree of damage increased with time. Immunohistochemistry showed that TIMP-2 was expressed in rats of the CLP group at all terms of the experiment. The expression of TIMP-2 and pyroptosis-related proteins (NLRP3, IL-1β, caspase-1, and GSDMD) in the CLP group was higher than in the SO group (p<0.05) and increased with time, suggesting that pyroptosis is involved in AKI. Thus, plasma TIMP-2 is sensitive indicator for the early detection of kidney injury and can be used as an early biomarker of AKI.

Enhanced robust spatial feature selection and correlation filter learning for UAV tracking

Spatial boundary effect can significantly reduce the performance of a learned discriminative correlation filter (DCF) model. A commonly used method to relieve this effect is to extract appearance features from a wider region of a target. However, this way would introduce unexpected features from background pixels and noises, which will lead to a decrease of the filter's discrimination power. To address this shortcoming, this paper proposes an innovative method called enhanced robust spatial feature selection and correlation filter Learning (EFSCF), which performs jointly sparse feature learning to handle boundary effects effectively while suppressing the influence of background pixels and noises. Unlike the ℓ₂-norm-based tracking approaches that are prone to non-Gaussian noises, the proposed method imposes the ℓ_2,1-norm on the loss term to enhance the robustness against the training outliers. To enhance the discrimination further, a jointly sparse feature selection scheme based on the ℓ_2,1 -norm is designed to regularize the filter in rows and columns simultaneously. To the best of the authors' knowledge, this has been the first work exploring the structural sparsity in rows and columns of a learned filter simultaneously. The proposed model can be efficiently solved by an alternating direction multiplier method. The proposed EFSCF is verified by experiments on four challenging unmanned aerial vehicle datasets under severe noise and appearance changes, and the results show that the proposed method can achieve better tracking performance than the state-of-the-art trackers.

[Self-reported quality of life in patients with coronary heart disease and analysis of the associated factors]

Objective: To investigate the quality of life and associated factors in patients with coronary heart disease (CHD) in China. Methods: A cross-sectional study of 25 provinces and cities in China was performed from June to September 2020. A questionnaire was used to collect the socio-demographic and clinical information of patients with CHD, while the European Five-dimensional Quality of Life Scale (EQ-5D) was used to assess the quality of life. Multiple linear regression model was performed to analyze the associated factors. Results: The median age of the 1 075 responders was 60 (52, 67) years, and 797 (74.1%) were men. The EQ-5D and EQ-VAS indices were 0.7 (0.5, 0.8) and 60.0 (40.0, 80.0). Among the five dimensions in the quality of life scale, the frequency of anxiety/depression was the highest (59.8%), while problems in self-care was the lowest (35.8%). In the multiple linear regression model, female, increasing age, obesity, comorbidity(ies), anxiety/depression, social media channels, and receiving the CABG therapy were associated with the lower EQ-5D index (all P<0.05). In addition, increasing age, obesity, comorbidity (ies), depression, anxiety and depression, social media channels, and receiving the CABG therapy were associated with lower EQ-VAS index (all P<0.05). Conclusion: Over half of the patients with CHD in China have a low quality of life, which is related to gender, age, obesity, treatment pathway, the presence or absence of comorbidity (ies), and psychological state. In addition to managing the adverse effects of traditional socio-demographic factors on the quality of life, clinical practices should pay attention to the psychological state of patients. Moreover, establishing a WeChat group for doctor-patient communication could improve the quality of life of CHD patients.

[Ultrasonographic features of retinal pigment epithelial adenoma]

Objective: To investigate the ultrasonographic features of retinal pigment epithelium (RPE) adenoma. Methods: It was a retrospective case series study. The clinical clata of 15 patients (15 eyes) with pathologically confirmed RPE adenoma after local resection of intraocular tumor was collected at Beijing Tongren Hospital, Capital Medical University from November 2013 to October 2019. The general conditions of the patients and the location, size, shape, internal echo features of the lesions in the ocular ultrasound sonogram were analyzed, and the blood flow in the lesions was checked by color Doppler flow imaging (CDFI). Results: Of all the patients included in the study, 7 were male and 8 were female. Their age ranged from 25 to 58 years, with a mean age of (45.7±10.2) years. The most common symptom was vision loss or blurred vision (11 cases). Other symptoms included dark shadows or obscuration in front of the eyes (3 cases) and no symptoms (1 case). A history of previous ocular trauma was present in one case, and the rest of the patients had no history of ocular trauma.The location of tumor growth is scattered. The ultrasonographic features were as follows: the average maximum basal diameter was (8.07±2.75) mm and the average height was (4.02±1.81) mm; the ultrasonographic features mostly demonstrated abruptly elevated dome-shaped echo (6 cases); the lesion edge was not smooth, the internal echo was medium or low, and there could be hollow features (2 cases), with no choroidal depression; and the blood flow signal could be seen in the CDFI lesion, which could lead to retinal detachment and vitreous opacification. Conclusion: The ultrasound imaging features of RPE adenomas mostly demonstrate abruptly elevated dome-shaped echo, unsmooth lesion edge, with no choroidal depression, which may provide valuable evidence for clinical diagnosis and differentiation.

Taming Self-Supervised Learning for Presentation Attack Detection: De-Folding and De-Mixing

Biometric systems are vulnerable to presentation attacks (PAs) performed using various PA instruments (PAIs). Even though there are numerous PA detection (PAD) techniques based on both deep learning and hand-crafted features, the generalization of PAD for unknown PAI is still a challenging problem. In this work, we empirically prove that the initialization of the PAD model is a crucial factor for generalization, which is rarely discussed in the community. Based on such observation, we proposed a self-supervised learning-based method, denoted as DF-DM. Specifically, DF-DM is based on a global-local view coupled with de-folding and de-mixing to derive the task-specific representation for PAD. During de-folding, the proposed technique will learn region-specific features to represent samples in a local pattern by explicitly minimizing the generative loss. While de-mixing drives detectors to obtain the instance-specific features with global information for more comprehensive representation by minimizing the interpolation-based consistency. Extensive experimental results show that the proposed method can achieve significant improvements in terms of both face and fingerprint PAD in more complicated and hybrid datasets when compared with the state-of-the-art methods. When training in CASIA-FASD and Idiap Replay-Attack, the proposed method can achieve an 18.60% equal error rate (EER) in OULU-NPU and MSU-MFSD, exceeding the baseline performance by 9.54%. The source code of the proposed technique is available at https://github.com/kongzhecn/dfdm.

Automatic Learning Rate Adaption for Memristive Deep Learning Systems

As a possible device to further enhance the performance of the hybrid complementary metal oxide semiconductor (CMOS) technology in the hardware, the memristor has attracted widespread attention in implementing efficient and compact deep learning (DL) systems. In this study, an automatic learning rate tuning method for memristive DL systems is presented. Memristive devices are utilized to adjust the adaptive learning rate in deep neural networks (DNNs). The speed of the learning rate adaptation process is fast at first and then becomes slow, which consist of the memristance or conductance adjustment process of the memristors. As a result, no manual tuning of learning rates is required in the adaptive back propagation (BP) algorithm. While cycle-to-cycle and device-to-device variations could be a significant issue in memristive DL systems, the proposed method appears robust to noisy gradients, various architectures, and different datasets. Moreover, fuzzy control methods for adaptive learning are presented for pattern recognition, such that the over-fitting issue can be well addressed. To our best knowledge, this is the first memristive DL system using an adaptive learning rate for image recognition. Another highlight of the presented memristive adaptive DL system is that quantized neural network architecture is utilized, and there is therefore a significant increase in the training efficiency, without the loss of testing accuracy.

Effect of Climate Change on the Potentially Suitable Distribution Pattern of Castanopsis hystrix Miq. in China

Climate warming poses a great threat to ecosystems worldwide, which significantly affects the geographical distribution and suitable growth area of species. Taking Castanopsis hystrix Miq. as the research object, the potentially suitable cultivation regions under present and future climatic emission scenarios in China were predicted based on the MaxEnt model with 360 effective individual distributions and eight environmental variables. The min temperature of coldest month (bio6), precipitation of driest month (bio14), and precipitation of warmest quarter (bio18) are three leading factors affecting the geographical distribution area of C. hystrix Miq. The suitable cultivation regions of C. hystrix Miq. range from 18°-34° N, 89°-122° E in central and southern China and cover an area of 261.95 × 10⁴ km². The spatial pattern of C. hystrix Miq. will migrate to the southern region of low latitudes with a decreasing suitable area when in ssp1-2.6, and to the southwestern region of low latitudes or expand to the northeast region at high latitudes in ssp5-8.5, with an increasing suitable area; no significant change on the spatial pattern in ssp2-2.4. For ssp1-2.6 or ssp2-4.5 climate scenarios, the southern region of high latitudes will be appropriate for introducing and cultivating C. hystrix Miq., and the cultivation area will increase. For ssp5-8.5, its cultivation will increase and expand to the northeast of high-latitude areas slightly.

[Evaluation of uniportal video-assisted thoracoscopic decortication in treatment of drug-resistant tuberculous empyema]

Objective: To examine the safety and efficacy of the uniportal video-assisted thoracoscopic decortication in treatment of drug-resistant tuberculosis empyema. Methods: From January 2018 to December 2020, 122 cases of tuberculous empyema treated by decortication in Department of Surgery, Wuhan Pulmonary Hospital were retrospectively analyzed, including 100 males and 22 females, aged(M(IQR)) 29.5(28.0) years (range: 13 to 70 years). According to the surgical approach and drug resistance, patients with drug-resistant tuberculosis who underwent uniportal video-assisted thoracoscopic decortication were included in group A (n=22), and those who underwent thoracotomy decortication were included in group B (n=28). Drug-sensitive patients who underwent uniportal video-assisted thoracoscopic decortication were included in group C (n=72). There was no statistical difference in the baseline data of the three groups (P>0.05). The operation, early postoperative recovery, and prognosis-related indicators were compared among three groups by Kruskal-Wallis test and χ² test by Mann-Whitney U test and Bonferroni method between groups A and B, groups A and C. Results: The intraoperative blood loss of group A, group B, and group C was 200(475) ml, 300(200) ml, and 225(300) ml, respectively. There was no significant difference in intraoperative hemorrhage (H=2.74, P=0.254) and treatment outcome (χ²=4.76, P=0.575) among the three groups. Compared with group B, the operation time of group A (302.5(187.5) minutes vs. 200.0(60.0) minutes, U=171.0, P=0.007) and postoperative pulmonary reexpansion duration (4.5(3.0) months vs. 3.0 (2.2) months, U=146.5, P=0.032) were longer, and the postoperative drainage duration (9.5(7.8) days vs. 13.0(10.0) days, U=410.0, P=0.044), and the postoperative hospitalization time (12.0(7.8) days vs. 14.5(4.8) days, U=462.2, P=0.020) were shorter. There was no significant difference in complications between group A and group B (63.6%(14/22) vs. 71.4%(20/28), χ²=0.34, P=0.558). Compared with group C, the postoperative drainage duration of group A (9.5(7.8) days vs. 7.0(4.0) days, U=543.5, P=0.031), the postoperative hospitalization time (12.0(7.8) days vs. 9.0(4.0) days, U=533.0, P=0.031) and postoperative pulmonary reexpansion duration (4.5(3.0) months vs. 3.0(2.0) months, U=961.5, P=0.001) were longer. The operation time (302.5(187.5) minutes vs. 242.5(188.8) minutes, U=670.5, P=0.278), and complications (63.6%(14/22) vs. 40.3%(29/72), χ²=3.70, P=0.054) were not different between group A and group C. Conclusions: For drug-resistant tuberculous empyema, the uniportal video-assisted thoracoscopic decortication can achieve the same good therapeutic effect as drug-sensitive tuberculous empyema, and it is as safe as thoracotomy. At the same time, it has the advantage of minimally invasive and can accelerate the early postoperative recovery of patients.

Precise Facial Landmark Detection by Reference Heatmap Transformer

Most facial landmark detection methods predict landmarks by mapping the input facial appearance features to landmark heatmaps and have achieved promising results. However, when the face image is suffering from large poses, heavy occlusions and complicated illuminations, they cannot learn discriminative feature representations and effective facial shape constraints, nor can they accurately predict the value of each element in the landmark heatmap, limiting their detection accuracy. To address this problem, we propose a novel Reference Heatmap Transformer (RHT) by introducing reference heatmap information for more precise facial landmark detection. The proposed RHT consists of a Soft Transformation Module (STM) and a Hard Transformation Module (HTM), which can cooperate with each other to encourage the accurate transformation of the reference heatmap information and facial shape constraints. Then, a Multi-Scale Feature Fusion Module (MSFFM) is proposed to fuse the transformed heatmap features and the semantic features learned from the original face images to enhance feature representations for producing more accurate target heatmaps. To the best of our knowledge, this is the first study to explore how to enhance facial landmark detection by transforming the reference heatmap information. The experimental results from challenging benchmark datasets demonstrate that our proposed method outperforms the state-of-the-art methods in the literature.

Style attention based global-local aware GAN for personalized facial caricature generation

Introduction

Caricature is an exaggerated pictorial representation of a person, which is widely used in entertainment and political media. Recently, GAN-based methods achieved automatic caricature generation through transferring caricature style and performing shape exaggeration simultaneously. However, the caricature synthesized by these methods cannot perfectly reflect the characteristics of the subject, whose shape exaggeration are not reasonable and requires facial landmarks of caricature. In addition, the existing methods always produce the bad cases in caricature style due to the simpleness of their style transfer method.

Methods

In this paper, we propose a Style Attention based Global-local Aware GAN to apply the characteristics of a subject to generate personalized caricature. To integrate the facial characteristics of a subject, we introduce a landmark-based warp controller for personalized shape exaggeration, which employs the facial landmarks as control points to warp image according to its facial features, without requirement of the facial landmarks of caricature. To fuse the facial feature with caricature style appropriately, we introduce a style-attention module, which adopts an attention mechanism, instead of the simple Adaptive Instance Normalization (AdaIN) for style transfer. To reduce the bad cases and increase the quality of generated caricatures, we propose a multi-scale discriminator to both globally and locally discriminate the synthesized and real caricature, which improves the whole structure and realistic details of the synthesized caricature.

Results

Experimental results on two publicly available datasets, the WebCaricature and the CaVINet datasets, validate the effectiveness of our proposed method and suggest that our proposed method achieves better performance than the existing methods.

Discussion

The caricatures generated by the proposed method can not only preserve the identity of input photo but also the characteristic shape exaggeration for each person, which are highly close to the real caricatures drawn by real artists. It indicates that our method can be adopted in the real application.

Universal pre-mixing dry-film stickers capable of retrofitting existing microfluidics

Integrating microfluidic mixers into lab-on-a-chip devices remains challenging yet important for numerous applications including dilutions, extractions, addition of reagents or drugs, and particle synthesis. High-efficiency mixers utilize large or intricate geometries that are difficult to manufacture and co-implement with lab-on-a-chip processes, leading to cumbersome two-chip solutions. We present a universal dry-film microfluidic mixing sticker that can retrofit pre-existing microfluidics and maintain high mixing performance over a range of Reynolds numbers and input mixing ratios. To attach our pre-mixing sticker module, remove the backing material and press the sticker onto an existing microfluidic/substrate. Our innovation centers around the multilayer use of laser-cut commercially available silicone-adhesive-coated polymer sheets as microfluidic layers to create geometrically complex, easy to assemble designs that can be adhered to a variety of surfaces, namely, existing microfluidic devices. Our approach enabled us to assemble the traditional yet difficult to manufacture "F-mixer" in minutes and conceptually extend this design to create a novel space-saving spiral F-mixer. Computational fluid dynamic simulations and experimental results confirmed that both designs maintained high performance for 0.1 < Re < 10 and disparate input mixing ratios of 1:10. We tested the integration of our system by using the pre-mixer to fluorescently tag proteins encapsulated in an existing microfluidic. When integrated with another microfluidic, our pre-mixing sticker successfully combined primary and secondary antibodies to fluorescently tag micropatterned proteins with high spatial uniformity, unlike a traditional pre-mixing "T-mixer" sticker. Given the ease of this technology, we anticipate numerous applications for point-of-care devices, microphysiological-systems-on-a-chip, and microfluidic-based biomedical research.

MIB-ANet: A novel multi-scale deep network for nasal endoscopy-based adenoid hypertrophy grading

Introduction

To develop a novel deep learning model to automatically grade adenoid hypertrophy, based on nasal endoscopy, and asses its performance with that of E.N.T. clinicians.

Methods

A total of 3,179 nasoendoscopic images, including 4-grade adenoid hypertrophy (Parikh grading standard, 2006), were collected to develop and test deep neural networks. MIB-ANet, a novel multi-scale grading network, was created for adenoid hypertrophy grading. A comparison between MIB-ANet and E.N.T. clinicians was conducted.

Results

In the SYSU-SZU-EA Dataset, the MIB-ANet achieved 0.76251 F1 score and 0.76807 accuracy, and showed the best classification performance among all of the networks. The visualized heatmaps show that MIB-ANet can detect whether adenoid contact with adjacent tissues, which was interpretable for clinical decision. MIB-ANet achieved at least 6.38% higher F1 score and 4.31% higher accuracy than the junior E.N.T. clinician, with much higher (80× faster) diagnosing speed.

Discussion

The novel multi-scale grading network MIB-ANet, designed for adenoid hypertrophy, achieved better classification performance than four classical CNNs and the junior E.N.T. clinician. Nonetheless, further studies are required to improve the accuracy of MIB-ANet.

Learning from pseudo-lesion: a self-supervised framework for COVID-19 diagnosis

The Coronavirus disease 2019 (COVID-19) has rapidly spread all over the world since its first report in December 2019, and thoracic computed tomography (CT) has become one of the main tools for its diagnosis. In recent years, deep learning-based approaches have shown impressive performance in myriad image recognition tasks. However, they usually require a large number of annotated data for training. Inspired by ground glass opacity, a common finding in COIVD-19 patient's CT scans, we proposed in this paper a novel self-supervised pretraining method based on pseudo-lesion generation and restoration for COVID-19 diagnosis. We used Perlin noise, a gradient noise based mathematical model, to generate lesion-like patterns, which were then randomly pasted to the lung regions of normal CT images to generate pseudo-COVID-19 images. The pairs of normal and pseudo-COVID-19 images were then used to train an encoder-decoder architecture-based U-Net for image restoration, which does not require any labeled data. The pretrained encoder was then fine-tuned using labeled data for COVID-19 diagnosis task. Two public COVID-19 diagnosis datasets made up of CT images were employed for evaluation. Comprehensive experimental results demonstrated that the proposed self-supervised learning approach could extract better feature representation for COVID-19 diagnosis, and the accuracy of the proposed method outperformed the supervised model pretrained on large-scale images by 6.57% and 3.03% on SARS-CoV-2 dataset and Jinan COVID-19 dataset, respectively.