Integrated Dual-Channel Retrograde Signaling Directs Stress Responses by Degrading the HAT1/TPL/IMPα-9 Suppressor Complex and Activating CAMTA3.

The intricate communication between plastids and the nucleus, shaping stress-responsive gene expression, has long intrigued researchers. This study combines genetics, biochemical analysis, cellular biology, and protein modeling to uncover how the plastidial metabolite MEcPP activates the stress-response regulatory hub known as the Rapid Stress Response Element (RSRE). Specifically, we identify the HAT1/TPL/IMPα- 9 suppressor complex, where HAT1 directly binds to RSRE and its activator, CAMTA3, masking RSRE and sequestering the activator. Stress-induced MEcPP disrupts this complex, exposing RSRE and releasing CAMTA3, while enhancing Ca 2+ influx and raising nuclear Ca 2+ levels crucial for CAMTA3 activation and the initiation of RSRE- containing gene transcription. This coordinated breakdown of the suppressor complex and activation of the activator highlights the dual-channel role of MEcPP in plastid-to- nucleus signaling. It further signifies how this metabolite transcends its expected biochemical role, emerging as a crucial initiator of harmonious signaling cascades essential for maintaining cellular homeostasis under stress. Summary: This study uncovers how the stress-induced signaling metabolite MEcPP disrupts the HAT1/TPL/IMPα-9 suppressor complex, liberating the activator CAMTA3 and enabling Ca 2+ influx essential for CAMTA3 activation, thus orchestrating stress responses via repressor degradation and activator induction.

Impact of Dietary Patterns on Metabolic Syndrome in Young Adults: A Cross-Sectional Study.

Metabolic syndrome has become a significant public health concern. This study aims to investigate the impact of dietary patterns on metabolic syndrome in young adults and how physical activity modulates this effect. A cross-sectional study was conducted at a health management center in Tianjin, China, from September 2022 to March 2023. Participants aged 18-35 years were recruited using convenience sampling. Dietary intake was assessed using a validated food frequency questionnaire. Logistic regression models evaluated associations between these patterns and metabolic syndrome, adjusting for potential confounders. Among 442 participants, four dietary patterns were identified: Legume-Nut, Alcohol-Meat, Sugar-Processed, and Egg-Vegetable. The Legume-Nut dietary pattern was associated with a higher risk of metabolic syndrome (OR = 2.63, 95% CI: 1.08-6.37), while the Egg-Vegetable dietary pattern was associated with a lower risk (OR = 0.26, 95% CI: 0.10-0.70). No significant associations were found for the Sugar-Processed and Alcohol-Meat patterns. Subgroup analysis revealed that the Legume-Nut pattern increased the risk of metabolic syndrome among those with irregular physical activity, whereas the Egg-Vegetable pattern decreased the risk. These findings highlight the significant influence of dietary patterns on the risk of metabolic syndrome in young adults and the modifying effect of regular physical activity, underscoring the need for targeted dietary and lifestyle interventions to prevent metabolic syndrome in this population.

Forecasting carbon dioxide emissions in Chongming: a novel hybrid forecasting model coupling gray correlation analysis and deep learning method.

Predicting regional carbon dioxide (CO2) emissions is essential for advancing toward global carbon neutrality. This study introduces a novel CO2 emissions prediction model tailored to the unique environmental, economic, and energy consumption of Shanghai Chongming. Utilizing an innovative hybrid approach, the study first applies grey relational analysis to evaluate the influence of economic activity, natural conditions, and energy consumption on CO2 emissions. This is followed by the implementation of a dual-channel pooled convolutional neural network (DCNN) that captures both local and global features of the data, enhanced through feature stacking. Gated recurrent unit (GRU) network then assesses the temporal aspects of these features, culminating in precise CO2 emission predictions for the region. The results indicate: (1) The proposed hybrid model achieves accurate predictions based on accounting data, with high precision, low error, and good stability. (2) The study found an overall increase in Chongming's carbon emissions from 2000 to 2022, with the prediction results being generally consistent with existing research findings. (3) The proposed method, based on Chongming's CO2 emission predictions, addresses issues such as the scarcity of effective accounting data and inaccuracies in traditional calculation methods. The results can provide effective technical support for local government policies on carbon reduction and promote sustainable development.

Giant laryngeal neuroendocrine neoplasm causing airway obstruction: A case report and literature review.

RATIONALE: Laryngeal neuroendocrine neoplasm (NEN) is a rare and heterogeneous disease that originates from neuroendocrine cells. It mainly occurs in middle-aged and elderly men. Due to the lack of specific clinical and imaging manifestations, diagnosis and treatment of the disease pose a challenge. Therefore, a consensus on the diagnosis and treatment of the disease is necessary. By discussing this case, we will be able to gain further insight into laryngeal NEN and will be able to provide some recommendations for the future management of this rare disease. PATIENT CONCERNS: A 67-year-old man was admitted to our department with a history of sore throat and dyspnea. After admission, the patient experienced acute airway obstruction and experienced an emergency bedside tracheotomy. DIAGNOSES: Flexible fiberoptic laryngoscopy and enhanced CT showed a cauliflower-like mass in the left supraglottic region and obstructed most of the laryngeal cavity. We biopsied the mass, and the pathology showed a poorly differentiated adenocarcinoma. INTERVENTIONS: A horizontal hemilaryngectomy and left neck dissection were performed. At 4 weeks after the operation, the patient underwent chemotherapy and radical radiotherapy. OUTCOMES: After a 1-year postoperative follow-up, the patient recovered well and showed no signs of recurrence. LESSONS: Laryngeal neuroendocrine neoplasm is very rare, early diagnosis remains difficult. Radical surgery combined with postoperative chemoradiotherapy is currently the most appropriate treatment.

Ocular Disease Detection with Deep Learning (Fine-Grained Image Categorization) Applied to Ocular B-Scan Ultrasound Images.

INTRODUCTION: The aim of this work is to develop a deep learning (DL) system for rapidly and accurately screening for intraocular tumor (IOT), retinal detachment (RD), vitreous hemorrhage (VH), and posterior scleral staphyloma (PSS) using ocular B-scan ultrasound images. METHODS: Ultrasound images from five clinically confirmed categories, including vitreous hemorrhage, retinal detachment, intraocular tumor, posterior scleral staphyloma, and normal eyes, were used to develop and evaluate a fine-grained classification system (the Dual-Path Lesion Attention Network, DPLA-Net). Images were derived from five centers scanned by different sonographers and divided into training, validation, and test sets in a ratio of 7:1:2. Two senior ophthalmologists and four junior ophthalmologists were recruited to evaluate the system's performance. RESULTS: This multi-center cross-sectional study was conducted in six hospitals in China. A total of 6054 ultrasound images were collected; 4758 images were used for the training and validation of the system, and 1296 images were used as a testing set. DPLA-Net achieved a mean accuracy of 0.943 in the testing set, and the area under the curve was 0.988 for IOT, 0.997 for RD, 0.994 for PSS, 0.988 for VH, and 0.993 for normal. With the help of DPLA-Net, the accuracy of the four junior ophthalmologists improved from 0.696 (95% confidence interval [CI] 0.684-0.707) to 0.919 (95% CI 0.912-0.926, p < 0.001), and the time used for classifying each image reduced from 16.84 ± 2.34 s to 10.09 ± 1.79 s. CONCLUSIONS: The proposed DPLA-Net showed high accuracy for screening and classifying multiple ophthalmic diseases using B-scan ultrasound images across mutiple centers. Moreover, the system can promote the efficiency of classification by ophthalmologists.

A filter pad design-based multiplexed lateral flow immunoassay for rapid simultaneous detection of PDCoV, TGEV, and PEDV in swine feces.

Swine Enteric Coronaviruses (SECoVs), with high lethality and infectiousness, are the main pathogens causing fatal and watery diarrhea in piglets and spreading globally. Moreover, these SECoVs can cause similar clinical manifestations and are often co-infected, requiring an accurate assay suitable for rapid, in situ, and differential detection. Here, we developed a multiplexed fluorescent-based lateral flow immunoassay (mFB-LFIA) for the detection of three SECoVs, including porcine delta coronaviruses (PDCoV), transmissible gastroenteritis virus (TGEV), and porcine epidemic diarrhea virus (PEDV), in swine fecal samples. Thanks to the filter pad design and reasonable optimization, the mFB-LFIA was achieved within 15 min for three SECoVs detection simultaneously and improved the tolerance of the strips for feces samples. The limit of detection (LoD) of detecting PDCoV, TGEV, and PEDV were 2.1 × 104 TCID50 mL-1, 3.4 × 102 TCID50 mL-1, and 3.6 × 102 TCID50 mL-1, respectively. Additionally, the proposed assay was successfully applied to the detection of PDCoV, TGEV, and PEDV in swine feces with high accuracy. Compared with the gold standard nucleic acid testing, the total coincidence rate of the proposed assay was more than 90 %. Moreover, the mFB-LFIA performed excellent stability and repeatability. The proposed mFB-LFIA allows for rapid, in situ, more cost-effective and simultaneous detection of PDCoV, TGEV, and PEDV compared with nucleic acid testing. To the best of our knowledge, this is the first report to describe a multiplexed point-of-care assay capable of detecting PDCoV, TGEV, and PEDV in swine fecal samples. We believe our approach has a great potential for application to pig farm.

Influence of ultrasonic pretreatment on the quality attributes and pectin structure of chili peppers (Capsicum spp.).

Chili peppers (Capsicum spp.) exhibit a diverse range of quality characteristics and pectin structures, which are influenced by various factors. This study aimed to investigate the effects of ultrasound (US), ultrasonic combined hot blanching (US-BL), and ultrasonic combined freezing and thawing (US-FT) on the quality characteristics and pectin structure of vacuum pulsation-dried (VP) chili peppers. The results indicated that US-BL samples exhibited the highest L* and a* values, retained maximum capsorubin, and showed an increase in vitamin C, total phenols, and rehydration by 14.28 %, 40.87 %, and 8.66 %, respectively. In contrast, the US-FT samples exhibited the highest capsaicin and dihydrocapsaicin content, which increased by 54.97 % and 64.04 %, respectively. Pretreatment resulted in higher pectin linearity, a lower degree of branching, and a reduced molecular weight in the US-BL sample. Atomic force microscopy confirmed the degrading effect of pretreatment on the pectin structure. Pearson's correlation analysis revealed that capsorubin, capsaicin analogs, vitamin C, and total phenols were highly correlated with pectin linearity and molecular weight. This study found that US-BL was the most effective pretreatment method for improving the quality of pulsatile chili peppers and provides theoretical support for the application of VP chili peppers.

Foliar Co-Applications of Nitrogen and Iron on Vines at Different Developmental Stages Impacts Wine Grape (Vitis vinifera L.) Composition.

The co-application of N and Fe can improve wine grape composition and promote the formation of flavor compounds. To understand the effects of foliar co-application of N and Fe on wine grape quality and flavonoid content, urea and EDTA-FE were sprayed at three different developmental stages. Urea and EDTA-Fe were sprayed during the early stage of the expansion period, at the end of the early stage of the expansion period to the late stage of the veraison period, and during the late stage of the veraison period. The results demonstrated that the co-application of urea and EDTA-Fe, particularly N application during the late stage of the veraison period and Fe application during the early stage of the berry expansion period (N3Fe1), significantly improved grape quality. Specifically, the soluble solid content of berries increased by 2.78-19.13%, titratable acidity decreased by 6.67-18.84%, the sugar-acid ratio became more balanced, and yield increased by 13.08-40.71%. Further, there was a significant increase in the relative content of amino acids and flavonoids. In conclusion, the application of Fe and N fertilizers at the pre-expansion and late veraison stages of grapes can significantly improve the quality and yield of berries; ultimately, this establishes a foundation for future improvement in the nutritional value of grapes and wine.

Global research trends and hotspots in overweight/obese comorbid with depression among children and adolescents: A bibliometric analysis.

BACKGROUND: Overweight/obesity combined with depression among children and adolescents (ODCA) is a global concern. The bidirectional relationship between depression and overweight/obesity often leads to their comorbidity. Childhood and adolescence represent critical periods for physical and psychological development, during which the comorbidity of overweight/obesity and depression may increase the risk of adverse health outcomes. AIM: To evaluate the relationship between ODCA, we conduct a bibliometric analysis to aid in formulating prevention and treatment strategies. METHODS: From 2004 to 2023, articles related to ODCA were selected using the Science Citation Index Expanded from the Web of Science Core Collection. Bibliometric analysis of relevant publications, including countries/regions, institutions, authors, journals, references, and keywords, was conducted using the online bibliometric analysis platforms, CiteSpace, VOSviewer, and bibliometrix. RESULTS: Between 2004 and 2023, a total of 1573 articles were published on ODCA. The United States has made leading contributions in this field, with Harvard University emerging as the leading contributor in terms of research output, and Tanofsky being the most prolific author. The J Adolescent Health has shown significant activity in this domain. Based on the results of the keyword and reference analyses, inequality, adverse childhood experiences, and comorbidities have become hot topics in ODCA. Moreover, the impact of balanced-related behavior and exploration of the biological mechanisms, including the potential role of key adipocytokines and lipokines, as well as inflammation in ODCA, have emerged as frontier topics. CONCLUSION: The trend of a significant increase in ODCA publications is expected to continue. The research findings will contribute to elucidating the pathogenic mechanisms of ODCA and its prevention and treatment.

Establish a noninvasive model to screen metabolic dysfunction-associated steatotic liver disease in children aged 6-14 years in China and its applications in high-obesity-risk countries and regions.

Background: The prevalence of metabolic-associated steatotic liver disease (MASLD) is rising precipitously among children, particularly in regions or countries burdened with high prevalence of obesity. However, identifying those at high risk remains a significant challenge, as the majority do not exhibit distinct symptoms of MASLD. There is an urgent need for a widely accepted non-invasive predictor to facilitate early disease diagnosis and management of the disease. Our study aims to 1) evaluate and compare existing predictors of MASLD, and 2) develop a practical screening strategy for children, tailored to local prevalence of obesity. Methods: We utilized a school-based cross-sectional survey in Beijing as the training dataset to establish predictive models for screening MASLD in children. An independent school-based study in Ningbo was used to validate the models. We selected the optimal non-invasive MASLD predictor by comparing logistic regression model, random forest model, decision tree model, and support vector machine model using both the Beijing and Ningbo datasets. This was followed by serial testing using the best performance index we identified and indices from previous studies. Finally, we calculated the potential MASLD screening recommendation categories and corresponding profits based on national and subnational obesity prevalence, and applied those three categories to 200 countries according to their obesity prevalence from 1990 to 2022. Findings: A total of 1018 children were included (NBeijing = 596, NNingbo = 422). The logistic regression model demonstrated the best performance, identifying the waist-to-height ratio (WHtR, cutoff value ≥0.48) as the optimal noninvasive index for predicting MASLD, with strong performance in both training and validation set. Additionally, the combination of WHtR and lipid accumulation product (LAP) was selected as an optimal serial test to improve the positive predictive value, with a LAP cutoff value of ≥668.22 cm × mg/dL. Based on the obesity prevalence among 30 provinces, three MASLD screening recommendations were proposed: 1) "Population-screening-recommended": For regions with an obesity prevalence ≥12.0%, where MASLD prevalence ranged from 5.0% to 21.5%; 2) "Resources-permitted": For regions with an obesity prevalence between 8.4% and 12.0%, where MASLD prevalence ranged from 2.3% to 4.4%; 3) "Population-screening-not-recommended": For regions with an obesity prevalence <8.4%, where MASLD prevalence is difficult to detect using our tool. Using our proposed cutoff for screening MASLD, the number of countries classified into the "Population-screening-recommended" and "Resources-permitted" categories increased from one and 11 in 1990 to 95 and 28 in 2022, respectively. Interpretation: WHtR might serve as a practical and accessible index for predicting pediatric MASLD. A WHtR value ≥0.48 could facilitate early identification and management of MASLD in areas with obesity prevalence ≥12.0%. Furthermore, combining WHtR ≥0.48 with LAP ≥668.22 cm × mg/dL is recommended for individual MASLD screening. Moreover, linking these measures with population obesity prevalence not only helps estimate MASLD prevalence but also indicates potential screening profits in regions at varying levels of obesity risk. Funding: This study was supported by grants from Capital's Funds for Health Improvement and Research (Grant No. 2022-1G-4251), National Natural Science Foundation of China (Grant No. 82273654), Major Science and Technology Projects for Health of Zhejiang Province (Grant No. WKJ-ZJ-2216), Cyrus Tang Foundation for Young Scholar 2022 (2022-B126) and Sino-German Mobility Programme (M-0015).

Latent transition of social participation and its effects on depression among older adults in China: A National Longitudinal Study.

OBJECTIVES: As populations age, the issue of social participation among older adults has gained prominence. Studies indicate variability in social participation trajectories among this demographic, yet the transition patterns and their effects on depression remain unclear. This longitudinal study aims to explore the latent classes and transition patterns in social participation among older adults and to evaluate their effects on depression. METHODS: Data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2014 (T1) and 2018 (T2) were analyzed, including 2293 older adults. Latent class analysis (LCA) and latent transition analysis (LTA) were employed to identify latent classes of social participation at T1 and T2, as well as the transition probabilities between these classes. Multinomial logistic regression was used to examine predictors of transitions, and depression levels at T2 were compared across transition patterns. RESULTS: The LCA results supported a 3-class model labeled as low, moderate, and high social participation. The probabilities of remaining stable and transitioning to other classes were similar across the three classes (ranging from 0.50 to 0.54). Age, gender, and other baseline characteristics emerged as significant predictors of transition patterns. Older adults experiencing positive transitions exhibited reduced depression compared to those in their original class over time, while those with negative transitions showed increased depression. CONCLUSIONS: This research prompts a deep understanding of social participation dynamics in older adults and their effects on depression. Identifying social participation classes and transition patterns could inform interventions to enhance social participation and reduce depression among older adults.

Enhancing the ophthalmic AI assessment with a fundus image quality classifier using local and global attention mechanisms.

Background: The assessment of image quality (IQA) plays a pivotal role in the realm of image-based computer-aided diagnosis techniques, with fundus imaging standing as the primary method for the screening and diagnosis of ophthalmic diseases. Conventional studies on fundus IQA tend to rely on simplistic datasets for evaluation, predominantly focusing on either local or global information, rather than a synthesis of both. Moreover, the interpretability of these studies often lacks compelling evidence. In order to address these issues, this study introduces the Local and Global Attention Aggregated Deep Neural Network (LGAANet), an innovative approach that integrates both local and global information for enhanced analysis. Methods: The LGAANet was developed and validated using a Multi-Source Heterogeneous Fundus (MSHF) database, encompassing a diverse collection of images. This dataset includes 802 color fundus photography (CFP) images (302 from portable cameras), and 500 ultrawide-field (UWF) images from 904 patients with diabetic retinopathy (DR) and glaucoma, as well as healthy individuals. The assessment of image quality was meticulously carried out by a trio of ophthalmologists, leveraging the human visual system as a benchmark. Furthermore, the model employs attention mechanisms and saliency maps to bolster its interpretability. Results: In testing with the CFP dataset, LGAANet demonstrated remarkable accuracy in three critical dimensions of image quality (illumination, clarity and contrast based on the characteristics of human visual system, and indicates the potential aspects to improve the image quality), recording scores of 0.947, 0.924, and 0.947, respectively. Similarly, when applied to the UWF dataset, the model achieved accuracies of 0.889, 0.913, and 0.923, respectively. These results underscore the efficacy of LGAANet in distinguishing between varying degrees of image quality with high precision. Conclusion: To our knowledge, LGAANet represents the inaugural algorithm trained on an MSHF dataset specifically for fundus IQA, marking a significant milestone in the advancement of computer-aided diagnosis in ophthalmology. This research significantly contributes to the field, offering a novel methodology for the assessment and interpretation of fundus images in the detection and diagnosis of ocular diseases.

Comparison of the Long-term Survival Outcome of Surgery versus Stereotactic Body Radiation Therapy as Initial Local Treatment for Pulmonary Oligometastases from Colorectal Cancer: A Propensity Score Analysis.

PURPOSE: Optimal local treatment for pulmonary oligometastases from colorectal cancer (CRC) remains unclear. We aimed to compare the long-term survival outcomes between surgery and stereotactic body radiation therapy (SBRT) as the initial local treatment for CRC pulmonary oligometastases. MATERIALS AND METHODS: We retrospectively reviewed 335 consecutive patients who initially underwent surgery or SBRT for CRC pulmonary metastases from 2011 to 2022, and 251 patients (173 surgery and 78 SBRT) were ultimately included. Freedom from intrathoracic progression (FFIP), progression-free survival (PFS), and overall survival (OS) were compared using stabilized inverse probability of treatment weighting (sIPTW) analysis. In addition, patterns of intrathoracic progression and subsequent treatment were analyzed. RESULTS: Median follow-up was 61.6 months for surgery and 54.4 months for SBRT. After sIPTW adjustment, significant differences emerged in both FFIP and PFS between surgery and SBRT (FFIP: hazard ratio [HR] = 0.50, 95% confidence interval [CI], 0.31-0.79; PFS: HR = 0.56, 95% CI, 0.36-0.87). The 3- and 5-year FFIP rates were 58.6% and 54.8%, respectively, after surgery, and 34.6% and 31.3%, respectively, after SBRT (P = .006). The 3- and 5-year PFS rates were 49.4% and 45.2%, respectively, after surgery, and 28.8% and 26.1%, respectively, after SBRT (P = .010). However, OS was not significantly affected by treatment approach (HR = 0.93, 95% CI, 0.49-1.76). The 3- and 5-year OS rates were 85.9% and 73.1%, respectively, after surgery, and 78.9% and 68.7%, respectively, after SBRT (P = .849). Recurrence at the treated site was more prevalent after SBRT than after surgery (33.3% vs 16.9%), whereas new intrathoracic tumors occurred more frequently after surgery than after SBRT (71.8% vs 43.1%). Both groups chose radiation therapy as the primary local salvage treatment. CONCLUSIONS: Notwithstanding the significant differences in FFIP and PFS between surgery and SBRT, the long-term survival of patients with CRC pulmonary oligometastases did not depend on the initial choice of the local treatment approach.

Purification, characterization, simulated gastrointestinal digestion and gut microbiota fermentation of a Bifidobacterium-directed mannoglucan from Lilium brownii var. viridulum.

Lilium brownii var. viridulum (Longya lily) is an edible vegetable and medicinal plant with the effects of moistening lungs, relieving coughs, and removing phlegm. In this study, a homogenous mannoglucan LLP11 was purified from Longya lily using membrane ultrafiltration followed by ion exchange chromatography. The M w of LLP11 was 12.0 kDa. LLP11 exhibited a backbone of →4)-α-D-Glcp-(1 â†’ and →4)-ß-D-Manp-(1 â†’ with a branch of T-α-D-Glcp-(1 â†’ substituted at C-6 of →4,6)-α-D-Glcp-(1→. During the simulated digestion, LLP11 remained indigestible to digestive enzymes. Furthermore, through its interaction with the gut microbiota, LLP11 was able to significantly boost Bifidobacterium and decrease the harmful bacteria Klebsiella, that was linked to pneumonia. Additionally, LLP11 promoted the growth of B. pseudocatenulatum and B. longum and was utilized to produce acetic acid. Our findings introduced an alternative approach for the investigation of microbiota-targeted polysaccharides and underscored the potential of LLP11 as a prebiotic for supplementary treatment in respiratory diseases.

Association between obesity and systemic immune inflammation index, systemic inflammation response index among US adults: a population-based analysis.

BACKGROUND: Obesity is characterized by a chronic low-grade inflammatory condition. Two emerging inflammatory biomarkers, the systemic immune-inflammation index (SII) and the systemic inflammation response index (SIRI), have gained attention. However, the relationships between obesity and SII/SRI remain unclear. METHODS: In this study, we analyzed data from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018 among adults. SII-SIRI/SII/SIRI were categorized into three groups based on tertiles. The association between obesity and SII-SIRI/SII/SIRI was assessed by multivariable logistic regression models. Restricted cubic spline (RCS) plots were used to examine the nonlinear association between obesity and SII/SIRI. Finally, potential independent associations between obesity and SII/SIRI were further explored using subgroup analyses. RESULTS: The study included 20,011 adults, of whom 7,890 (39.32%) were obesity. In model 1, participants in the high (Q3) level of SII-SIRI had a significantly association with obesity than those in the low (Q1) level group. The high level of SII and SIRI were positively associated with obesity as compared to low levels. Model 2 revealed a positive association between obesity and high levels of SII-SIRI/SII/SIRI. Model 3 demonstrated a similar trend. RCS curves revealed a nonlinear association linking obesity to SII/SIRI. Subgroup analysis showed an interaction between SII/SIRI and age. CONCLUSIONS: Our research suggested that obesity was positively associated with SII-SIRI/SII/SIRI in U.S. adults. SII/SIRI may represent a cost-effective and direct approach to assessing obesity.

PM2.5 constituents associated with mortality and kidney failure in childhood-onset lupus nephritis: A 19-year cohort study.

BACKGROUND: Childhood-onset lupus nephritis (cLN) is a severe form of systemic lupus erythematosus (SLE) with high morbidity and mortality. The impact of long-term exposure to fine particulate matter (PM2.5) on adverse outcomes in cLN remains unclear. METHODS: We combined a 19-years cLN cohort from seven provinces in China with high-resolution PM2.5 dataset from 2001 to 2020, investigating the association between long-term exposure to PM2.5 and its constituents (sulfate, nitrate, organic matter, black carbon, ammonium) with the risk of death and kidney failure, analyzed with multiple variables Cox models. We also evaluated the association between 3-year average PM2.5 exposure before study entry and baseline SLE disease activity index (SLEDAI) scores using linear regression models. RESULTS: Each 10 µg/m3 increase in annual average PM2.5 exposure was associated with an increased risk of death and kidney failure (HR = 1.58, 95 % CI: 1.24-2.02). Black carbon showed the strongest association (HR = 2.14, 95 % CI: 1.47-3.12). Higher 3-year average exposures to PM2.5 and its constituents were significantly associated with higher baseline SLEDAI scores. CONCLUSIONS: These findings highlight the significant role of environmental pollutants in cLN progression and emphasize the need for strategies to mitigate exposure to harmful PM2.5 constituents, particularly in vulnerable pediatric populations.

Volume replacement in tumor plastic surgery and breast-conserving surgery using 3D grid and strip­shaped acellular dermal matrix: Two case reports.

The present study was driven by the scarcity of suitable materials for mending partial breast defects and the imperative considerations of safety and durability. The current study presents findings from two female patients, aged 59 and 40, who underwent breast cancer treatment. Patient 1 underwent a mastectomy with a sentinel lymph node biopsy, while patient 2 underwent a partial mastectomy with axillary lymph node dissection. Core needle biopsy confirmed invasive ductal carcinoma in both cases. Breast ultrasound revealed hypoechoic lesions with smooth edges. The reconstruction of the breast defect employed an acellular dermal matrix, and the safety and cosmetic outcomes for each patient were analyzed. At 3 months post-radiotherapy, neither patient experienced significant complications. The preservation of breast contour and volume was satisfactory, with no postoperative tumor recurrences detected. In summary, utilizing an acellular dermal matrix with a three-dimensional grid design for partial breast defect reconstruction offers a viable alternative that aligns with oncological safety standards and provides good cosmetic results.

Shearo-caloric effect enhances elastocaloric responses in polymer composites for solid-state cooling.

Room-temperature elastocaloric cooling is considered as a zero-global-warming-potential alternative to conventional vapor-compression refrigeration technology. However, the limited entropy and large-deformation features of elastocaloric polymers hinder the creation of the breakthrough in their caloric responses and device development. Herein, we report that the addition of a small amount of inorganic nanofillers into the polymer induces the aggregate of the effective elastic chains via shearing the interlaminar molecular chains, which provides an additional contribution to the entropy in elastocaloric polymers. Consequently, the adiabatic temperature change of -18.0 K and the isothermal entropy change of 187.4 J kg-1 K-1 achieved in the polymer nanocomposites outperform those of current elastocaloric polymers. Moreover, a large-deformation cooling system with a work recovery efficiency of 56.3% is demonstrated. This work opens a new avenue for the development of high-performance elastocaloric polymers and prototypes for solid-state cooling applications.

ChineseMPD: A Semantic Segmentation Dataset of Chinese Martial Arts Classic Movie Props.

Recent advances in computer vision and deep learning techniques have facilitated significant progress in video scene understanding, thus helping film and television practitioners achieve accurate video editing. However, so far, publicly available semantic segmentation datasets are mostly limited to indoor scenes, city streets, and natural images, often ignoring example objects in action movies, which is a research gap that needs to be urgently filled. In this paper, we introduce a large-scale, high-precision semantic segmentation dataset of props in Chinese martial arts movie clips, named ChineseMPD. Specifically, this dataset first establishes segmentation rules and general review criteria for audiovisual data, and then provides semantic segmentation annotations for six weapon props (Gun, Sword, Stick, Knife, Hook, and Arrow) with a summary of 32,992 objects.To the best of our knowledge, this dataset is the largest semantic segmentation dataset for movie props to date. ChineseMPD dataset not only significantly expands the application of traditional tasks of computer vision such as object detection and scene understanding, but also opens up new avenues for interdisciplinary research.