The predictors of short and long term urinary continence recovery after laparoscopic radical prostatectomy: a single cancer center report in China.

PURPOSE: To evaluate the predictors for short and long term urinary continence (UC) recovery after laparoscopic radical prostatectomy (LRP) from clinical and oncological variables. METHODS: We retrospectively collected data from 142 prostate cancer patients who underwent LRP between September 2014 and June 2021 at a tumor specialist diagnosis and treatment center in China. The rate of post-prostatectomy incontinence (PPI) was evaluated from immediate and at 3, 6 and 12 mo after LRP, and UC was defined as the use of no or one safety pad. Sixteen clinical and oncological variables were analyzed by univariate and multivariate regression analysis to determine whether they were associated with short (3 mo) or long term (12 mo) UC recovery after LRP. RESULTS: After eliminating patients who were lost to follow-up, 129 patients were eventually included. The mean ± SD age was 68 ± 6.3 years. The UC rates of immediate, 3, 6 and 12 mo after the operation were 27.9%, 54.3%, 75.2% and 88.4%, respectively. Multivariate analyses revealed that membranous urethral length (MUL) was a protective predictor of UC after catheter extraction(P < 0.001), and at 3 mo (P < 0.001), 6 mo (P < 0.001) and 12 mo (P = 0.009) after surgery. CONCLUSION: MUL is a significant independent factor that can contribute to short and long term UC recovery post-LRP, which may assist clinicians and their patients in counseling of treatment.

Effect of fully automatic classification model from different tube voltage images on bone density screening: A self-controlled study.

PURPOSE: To develop two bone status prediction models combining deep learning and radiomics based on standard-dose chest computed tomography (SDCT) and low-dose chest computed tomography (LDCT), and to evaluate the effect of tube voltage on reproducibility of radiomics features and predictive efficacy of these models. METHODS: A total of 1508 patients were enrolled in this retrospective study. LDCT was conducted using 80 kVp, tube current ranging from 100 to 475 mA. On the other hand, SDCT was performed using 120 kVp, tube current ranging from 100 to 520 mA. We developed an automatic thoracic vertebral cancellous bone (TVCB) segmentation model. Subsequently, 1184 features were extracted and two classifiers were developed based on LDCT and SDCT images. Based on the diagnostic results of quantitative computed tomography examination, the first-level classifier was initially developed to distinguish normal or abnormal BMD (including osteoporosis and osteopenia), while the second-level classifier was employed to identify osteoporosis or osteopenia. The Dice coefficient was used to evaluate the performance of the automated segmentation model. The Concordance Correlation Coefficients (CCC) of radiomics features were calculated between LDCT and SDCT, and the performance of these models was evaluated. RESULTS: Our automated segmentation model achieved a Dice coefficient of 0.98 ± 0.01 and 0.97 ± 0.02 in LDCT and SDCT, respectively. Alterations in tube voltage decreased the reproducibility of the extracted radiomic features, with 85.05 % of the radiomic features exhibiting low reproducibility (CCC < 0.75). The area under the curve (AUC) using LDCT-based and SDCT-based models was 0.97 ± 0.01 and 0.94 ± 0.02, respectively. Nonetheless, cross-validation with independent test sets of different tube voltage scans suggests that variations in tube voltage can impair the diagnostic efficacy of the model. Consequently, radiomics models are not universally applicable to images of varying tube voltages. In clinical settings, ensuring consistency between the tube voltage of the image used for model development and that of the acquired patient image is critical. CONCLUSIONS: Automatic bone status prediction models, utilizing either LDCT or SDCT images, enable accurate assessment of bone status. Tube voltage impacts reproducibility of features and predictive efficacy of models. It is necessary to account for tube voltage variation during the image acquisition.

Long-term follow-up and prognostic analysis of parotid tumors in children and adolescents.

Objectives: The objective of this study is to summarize the clinical characteristics, treatment, and prognosis of parotid tumors in children and adolescents. Methods: Fifty-three children and adolescents diagnosed with parotid gland tumors were included. Survival was evaluated using the Kaplan-Meier method. Log-rank test and multivariate analysis were used to analyze the association between clinical factors and recurrence. Results: Of the 53 patients, 30 cases were benign and 23 cases were malignant. All patients underwent surgery. Patients with malignant tumors with high-risk factors received radiotherapy or chemotherapy. The median follow-up time was 61 months. Of these, 1 patient with benign tumor and 5 patients with malignant tumors recurred. Of the patients with malignant tumors, 2 developed distant metastases and 2 died. The 5-year overall survival (OS) and 5-year locoregional recurrence-free survival (LRFS) rates for benign tumors were 100.0% and 92.9%, respectively, whereas the 5-year OS and 5-year LRFS rates for malignant tumors were 94.4% and 72.5%, respectively. The log-rank univariate test showed that tumor size >3.5 cm (p = .056), distant metastasis (p = .056), and stage III and IV (p = .032) were associated with recurrence. However, multivariate analysis did not show the above factors to be independent prognostic factors for LRFS. Conclusion: Surgery for benign tumors depends on the location and size. Surgery for malignant parotid tumors depends mainly on the stage, grade, pathological type, and recurrence. Prophylactic lymph node dissection is required for high-grade tumors. Radiotherapy or chemotherapy for children needs more research. Both benign and malignant tumors have high survival rates after active treatment. Level of evidence: Level 2.

The potent potential of MFAP2 in prognosis and immunotherapy of triple-negative breast cancer.

BACKGROUNDS: Microfibril-associated protein 2 (MFAP2) is a protein presenting in the extracellular matrix that governs the activity of microfibrils through its interaction with fibrillin. While the involvement of MFAP2 in metabolic disorders has been documented, its expression and prognostic significance in triple-negative breast cancer (TNBC) remain unexplored. METHODS: We acquired datasets pertaining to breast cancer (BC) from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Next, a Venn diagram was used to identify the differentially expressed genes (DEGs). The DEGs were used to perform Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI), immune and survival analysis. The expressions of MFAP2, PD-1 and PD-L1 were examined by immunohistochemistry and western blot and their relationship with clinical pathological parameters were analyzed by clinical specimen samples from patients with TNBC. Tumor Immune Estimation Resource (TIMER, https://cistrome.shinyapps.io/timer/ ) was adopted to calculate the immune infiltration level of TNBC. The link between gene expression and tumor mutational burden (TMB) was described using Spearman's correlation analysis. RESULTS: We identified 66 differentially expressed genes (DEGs) that were up-regulated. Among these DEGs, MFAP2 was found to be overexpressed in TNBC and was associated with a lower probability of survival. This finding was confirmed through the use of immunohistochemistry and western blot techniques. Additionally, MFAP2 was found to be related to various pathological parameters in TNBC patients. Mechanistically, gene set enrichment analysis (GSEA) revealed that MFAP2 primarily influenced cellular biological behavior in terms of epithelial mesenchymal transition, glycolysis, and apical junction. Notably, MFAP2 expression was positively correlated with the abundance of macrophages, while a negative correlation was observed with the abundance of B cells, CD4 + T cells, CD8 + T cells, neutrophils and dendritic cells through immune analysis. Furthermore, it was observed that MFAP2 displayed a negative correlation not only with tumor mutational burden (TMB), a recognized biomarker for PD-1/PD-L1 immunotherapy, but also with PD-L1 in samples of TNBC. CONCLUSION: MFAP2 may be an important prognostic biomarker for TNBC, as well as a viable target for immunotherapy in this disease.

Cross-Modal Object Tracking via Modality-Aware Fusion Network and a Large-Scale Dataset.

Visual object tracking often faces challenges such as invalid targets and decreased performance in low-light conditions when relying solely on RGB image sequences. While incorporating additional modalities like depth and infrared data has proven effective, existing multimodal imaging platforms are complex and lack real-world applicability. In contrast, near-infrared (NIR) imaging, commonly used in surveillance cameras, can switch between RGB and NIR based on light intensity. However, tracking objects across these heterogeneous modalities poses significant challenges, particularly due to the absence of modality switch signals during tracking. To address these challenges, we propose an adaptive cross-modal object tracking algorithm called modality-aware fusion network (MAFNet). MAFNet efficiently integrates information from both RGB and NIR modalities using an adaptive weighting mechanism, effectively bridging the appearance gap and enabling a modality-aware target representation. It consists of two key components: an adaptive weighting module and a modality-specific representation module. The adaptive weighting module predicts fusion weights to dynamically adjust the contribution of each modality, while the modality-specific representation module captures discriminative features specific to RGB and NIR modalities. MAFNet offers great flexibility as it can effortlessly integrate into diverse tracking frameworks. With its simplicity, effectiveness, and efficiency, MAFNet outperforms state-of-the-art methods in cross-modal object tracking. To validate the effectiveness of our algorithm and overcome the scarcity of data in this field, we introduce CMOTB, a comprehensive and extensive benchmark dataset for cross-modal object tracking. CMOTB consists of 61 categories and 1000 video sequences, comprising a total of over 799K frames. We believe that our proposed method and dataset offer a strong foundation for advancing cross-modal object-tracking research. The dataset, toolkit, experimental data, and source code will be publicly available at: https://github.com/mmic-lcl/ Datasets-and-benchmark-code.

Knockdown of DJ-1 Exacerbates Neuron Apoptosis Induced by TgCtwh3 through the NF-κB Pathway.

Mutations or loss of function of DJ-1 and Toxoplasma gondii (T. gondii) infection has been linked to neurodegenerative diseases, which are often caused by oxidative stress. However, the relationship between DJ-1 and T. gondii infection is not yet fully understood. Therefore, this study aimed to investigate the expression of DJ-1 in the hippocampus tissue of mice or in HT22 infected with T. gondii Chinese 1 genotype Wh3 strain (TgCtwh3) and the effect of DJ-1 knockdown on neuronal apoptosis induced by TgCtwh3 tachyzoite, as well as the underlying mechanism at the cellular and molecular level. Firstly, we detected DJ-1 protein expression and cell apoptosis in the hippocampal tissue of mice infected by TgCtwh3. Then, we examined DJ-1 expression and apoptosis in HT22 challenged with TgCtwh3. Finally, we evaluated the apoptosis in HT22 with DJ-1 knockdown which was infected with TgCtwh3 and assayed the expression of NF-κBp65 and p-NF-κBp65. Our results showed that DJ-1 expression was reduced and neurons underwent apoptosis in the hippocampus of mice infected with TgCtwh3 tachyzoites. Additionally, the knockdown of DJ-1 followed by infection with TgCtwh3 tachyzoites led to increased apoptosis in HT22 cells through the NF-κB signaling pathway. Therefore, this study suggests that DJ-1 is an important target for preventing apoptosis caused by T. gondii TgCtwh3.

Noninvasive pressure-strain loop quantitative assessment of left ventricular function in anemic preterm infants with different modes of respiratory support.

To investigate noninvasive pressure-strain loop (PSL) combined with two-dimensional speck tracking imaging and left ventricular pressure measurement in the evaluation of cardiac function changes in anemia of prematurity (AOP) with different modes of respiratory support, and to explore its value in detecting subclinical myocardial injury in preterm infants. This retrospective study included 79 preterm infants with anemia, according to different modes of respiratory support, who were divided into invasive respiratory support group (39 cases) and noninvasive respiratory support group (40 cases). A control group of 40 nonanemic preterm infants with matched age, sex, and gestational age were also included. Complete echocardiography was performed for each included infant. There are PSL parameters that used to evaluate cardiac function, including global longitudinal strain (GLS), global work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE) among the three groups were compared. Compared with the control group, the value of GWI, GCW, and GWE were significantly lower and GWW was higher in the AOP groups (P < 0.05), and GWI, GCW and GWE were much significantly lower in the invasive respiratory support group than in the noninvasive respiratory support group (P < 0.05). There was no significant difference in GLS among the three groups (P > 0.05). Noninvasive PSL analysis can quantitatively assess myocardial work in AOP with different respiratory support, which is more sensitive than other conventional echocardiographic indices. This technique may provide a new method for monitoring subclinical myocardial injury with AOP.

Deep learning promoted target volumes delineation of total marrow and total lymphoid irradiation for accelerated radiotherapy: A multi-institutional study.

BACKGROUND AND PURPOSE: One of the current roadblocks to the widespread use of Total Marrow Irradiation (TMI) and Total Marrow and Lymphoid Irradiation (TMLI) is the challenging difficulties in tumor target contouring workflow. This study aims to develop a hybrid neural network model that promotes accurate, automatic, and rapid segmentation of multi-class clinical target volumes. MATERIALS AND METHODS: Patients who underwent TMI and TMLI from January 2018 to May 2022 were included. Two independent oncologists manually contoured eight target volumes for patients on CT images. A novel Dual-Encoder Alignment Network (DEA-Net) was developed and trained using 46 patients from one internal institution and independently evaluated on a total of 39 internal and external patients. Performance was evaluated on accuracy metrics and delineation time. RESULTS: The DEA-Net achieved a mean dice similarity coefficient of 90.1 % ± 1.8 % for internal testing dataset (23 patients) and 91.1 % ± 2.5 % for external testing dataset (16 patients). The 95 % Hausdorff distance and average symmetric surface distance were 2.04 ± 0.62 mm and 0.57 ± 0.11 mm for internal testing dataset, and 2.17 ± 0.68 mm, and 0.57 ± 0.20 mm for external testing dataset, respectively, outperforming most of existing state-of-the-art methods. In addition, the automatic segmentation workflow reduced delineation time by 98 % compared to the conventional manual contouring process (mean 173 ± 29 s vs. 12168 ± 1690 s; P < 0.001). Ablation study validate the effectiveness of hybrid structures. CONCLUSION: The proposed deep learning framework achieved comparable or superior target volume delineation accuracy, significantly accelerating the radiotherapy planning process.

Evaluation of potentially harmful Maillard reaction products in different types of commercial formulae.

Pasteurisation and spray drying are critical steps to ensure the safety and shelf-life of formulae, but these treatments also induce formation of some potentially harmful Maillard reaction products. In this study, the occurrence of potentially harmful Maillard reaction products and proximate compositions in different commercial formulae were analysed. Our results showed that infant formulae had significantly higher concentrations of furosine, Nε-(carboxymethyl)lysine (CML) and Nε-(carboxyethyl)lysine (CEL) than follow-on/toddler formula. Specialty formulae had higher concentrations of glyoxal and CML than other types of formulae. Correlation analysis indicated that concentrations of 5-hydroxymethylfurfural, 3-deoxyglucosone, CML and CEL were closely related to fat contents. These results provided insight into concentrations of potentially harmful Maillard reaction products in different types of formulae and provide a theoretical basis for further optimisation of processing.

Natural language processing-driven artificial intelligence models for the diagnosis of lumbar disc herniation with L5 and S1 radiculopathy: a preliminary evaluation.

OBJECTIVE: To develop and validate natural language processing (NLP)-driven artificial intelligence (AI) models for the diagnosis of lumbar disc herniation (LDH) with L5 and S1 radiculopathy using electronic health records (EHRs). METHODS: EHRs of patients undergoing single-level Percutaneous Endoscopic Lumbar Discectomy (PELD) for the treatment of LDH at the L4/5 or L5/S1 level between June 1, 2013, and December 31, 2021, were collected. The primary outcome was LDH with L5 and S1 radiculopathy, which was defined as nerve root compression recorded in the operative notes. Datasets were created using the history of present illness (HPI) text and positive symptom (PS) text with radiculopathy (L5 or S1), respectively. The datasets were randomly split into a training set and a testing set in a 7:3 ratio. Two machine learning (ML) models, the Long Short-Term Memory (LSTM) network and Extreme Gradient Boosting (XGBoost), were developed using the training set. Performance evaluation of the models on the testing set was done using measures such as the receiver operating characteristic (ROC) curve, area under the curve (AUC), accuracy, recall, F1-score, and precision. RESULTS: The study included a total of 1681 patients, with 590 patients having L5 radiculopathy and 1091 patients having S1 radiculopathy. Among the four models developed, the LSTM model based on PS text showed the best discrimination in the testing set, with precision (0.9054), recall (0.9405), accuracy (0.8950), F1-score (0.9226), and AUC (0.9485). CONCLUSIONS: This study provides preliminary validation of the concept that NLP-driven AI models can be used for the diagnosis of lumbar disease using EHRs. This study could pave the way for future research that may develop more comprehensive and clinically impactful AI-driven diagnostic systems.

Low-dose ondansetron: A candidate prospective precision medicine to treat alcohol use disorder endophenotypes.

BACKGROUND: Alcohol use disorder (AUD) is among the leading causes of morbidity and mortality worldwide, and over 95 million people live with alcohol dependence globally. The estimated heritability of AUD is 50-60 %, and multiple genes are thought to contribute to various endophenotypes of the disease. Previous clinical trials support a precision medicine approach using ondansetron (AD04, a 5-HT3 antagonist) by segregating AUD populations by the bio-genetic endophenotype of specific serotonergic genotypes and the bio-psychosocial endophenotype of the severity of drinking or both. By targeting the modulation of biogenetic signaling within the biopsychosocial context of AUD, low-dose AD04 holds promise in reducing alcohol consumption among affected individuals while minimizing adverse effects. METHODS: This was a phase III, 6-month, 25-site, randomized, placebo-controlled clinical trial using AD04 to treat DSM-V-categorized AUD individuals who were pre-stratified into the endophenotypes of heavy or very heavy drinking individuals and possessed a pre-defined profile of genetic variants related to the serotonin transporter and serotonin-3AB receptor. Participants (N = 303) presented moderate to severe AUD, >80 % were men, mostly in their fifties, and >95 % were of European descent. Low-dose AD04 (approx. 033 mg twice daily) or a matching placebo was administered twice daily for 6 months. Brief Behavioral Compliance Enhancement Treatment (BBCET [53]) was administered every two weeks to enhance medication compliance and clinic attendance. RESULTS: There was a significant reduction in the monthly percentage of heavy drinking days, PHDD (-46·7 % (2·7 %), 95 %CI: -52·1 % to -41·2 % vs. -38·1 % (2·9 %), 95 %CI: -43·8 % to -32·5 %, respectively; LS mean difference=-8·5 %; p = 0.03) among AD04-treated vs. placebo-receiving heavy drinking individuals at month 6. Heavy drinking individuals were also less likely to be diagnosed with AUD [Month 1: -32·0 % (2·8 %), 95 %CI: -37·5 % to -26·5 % vs. -23·2 % (2·9 %), 95 %CI: -28·9 to -17·5 %; LS mean difference= -8·8 %; p = 0·026)], and improved on the WHO quality of life BREF scale with a significant effect for at least a 1-level downward shift (OR = 3.4; 95 % CI: 1·03-11·45, p = 0·044). Importantly, heavy drinking individuals, as distinct from very heavy drinking individuals, were the bio-psychosocial endophenotype more predictive of therapeutic response to AD04. AD04 had an exceptional safety and tolerability profile, like the placebo's. CONCLUSIONS: In this Phase 3 clinical trial, AD04 was shown to be a promising treatment for currently drinking heavy drinking individuals with AUD who also possess a specific genotypic profile in the serotonin transporter and serotonin-3AB receptor complex. Using AD04 to reduce the harm of AUD in heavy drinking individuals who are currently drinking, without the necessity of abstinence or detoxification from alcohol use, is an important advance in the field of precision medicine. AD04's adverse events profile, which was like placebo, should enhance accessibility and acceptance of modern medical treatment for AUD by lowering the incorrect but commonly perceived stigma of personal failure.

Deep Amplicon Sequencing Reveals Culture Selection of Mycobacterium Tuberculosis by Clinical Samples.

The commonly-used drug susceptibility testing (DST) relies on bacterial culture and faces shortcomings such as long turnaround time and clone/subclone selection. We developed a targeted deep amplification sequencing (DAS) method directly applied to clinical specimens. In this DAS panel, we examined 941 drug-resistant mutations associated with 20 anti-tuberculosis drugs with an initial amount of 4 pg DNA and reduced clinical testing time from 20 days to two days. A prospective study was conducted using 115 clinical specimens mainly with Xpert® Mycobacterium tuberculosis/rifampicin (Xpert MTB/RIF) assay positive to evaluate drug-resistant mutation detection. DAS was performed on culture-free specimens, while culture-dependent isolates were used for phenotypic DST, DAS, and whole-genome sequencing (WGS). For in silico molecular DST, our result based on DAS panel revealed the similar accuracy to three published reports based on WGS. For 82 isolates, application of DAS showed better sensitivity (93.03% vs. 92.16%), specificity (96.10% vs. 95.02%), and accuracy (91.33% vs. 90.62%) than Mykrobe software using WGS. Compared to culture-dependent WGS, culture-free DAS provides a full picture of sequence variation at population level, exhibiting in detail the gain-and-loss variants caused by bacterial culture. Our study performs a systematic verification of the advantages of DAS in clinical applications and comprehensively illustrates the discrepancy in Mycobacterium tuberculosis before and after culture.

Virtual reality exposure reduce acute postoperative pain in female patients undergoing laparoscopic gynecology surgery: A Randomized Control Trial (RCT) study.

STUDY OBJECTIVE: Few studies have focused on the effect of virtual reality (VR) exposure on postoperative acute pain in adult female patients undergoing gynecology surgery. DESIGN: A randomized control trial (RCT) study. SETTING: At Beijing Fuxing Hospital. PATIENTS: 115 patients aged between 20 and 60 years, American Society of Anesthesiologists (ASA) physical status I - II were consecutively enrolled and randomly divided into VR group (n = 58) or control group (n = 57). INTERVENTIONS: Patients in the VR group received 15 min of VR video viewing before surgery. MEASUREMENTS: The primary outcome was acute postoperative pain at 8 h which was measured by the Visual Analogue Scale (VAS) scores. The secondary outcomes including the use of analgesic drugs, the incidence of moderate pain and postoperative recovery which were recorded 24 h after surgery. The Hospital Anxiety and Depression Scale (HADS) was also used to evaluate patients' emotional status before surgery. MAIN RESULTS: The VAS scores at 30 min [2 (1,2) vs. 3 (2,3)], 2 h [2 (2,3) vs. 4 (3,4)], 4 h [3 (2,4) vs. 4 (4,5)], 8 h [3 (2,4) vs. 4 (4,5)], 12 h [2 (2,3) vs. 4 (3,4)], 24 h [1 (1,2) vs. 3 (2,3)] after surgery. Generalized estimation equation (GEE) indicated that VR intervention was negatively correlated with postoperative VAS values (ß = -0.830, S.E = 0.199, 95%CI (-1.220,-0.439), Wald χ2 = 17.359, p<0.05), in the meanwhile, VR also lower the incidence of moderate pain (VAS > 4) at 8 h postoperatively (12.1% vs 31.0%, p = 0.013). However, the 24 h tramadol usage remained unchanged. Patients in the VR group had better sleep quality (6.33 ± 2.3 vs. 4.12 ± 2.5, p < 0.001) and lower incidence of nausea (43.1% vs. 63.2%, p < 0.05), dizziness (0% vs. 14.0%, p < 0.05), and headache (12.1% vs. 29.8%, p < 0.05). VR could reduce the median HADS scores (9.81 ± 6.1 vs 3.14 ± 3.9, p < 0.001) and blood pressure preoperatively. CONCLUSIONS: VR intervention can reduce acute postoperative pain with better postoperative recovery and lower preoperative anxiety level in adult female patients undergoing laparoscopic gynecology surgery.

Quantitative Characterization of Protein N-Linked Core-Fucosylation by an Efficient Glycan Truncation Strategy.

Dysregulation of protein core-fucosylation plays a pivotal role in the onset, progression, and immunosuppression of cancer. However, analyzing core-fucosylation, especially the accurate determination of the core-fucosylation (CF) site occupancy ratio, remains challenging. To address these problems, we developed a truncation strategy that efficiently converts intact glycopeptides with hundreds of different glycans into two truncated forms, i.e., a monosaccharide HexNAc and a disaccharide HexNAc+core-fucose. Further combination with data-independent analysis to form an integrated platform allowed the measurement of site-specific core-fucosylation abundances and the determination of the CF occupancy ratio with high reproducibility. Notably, three times CF sites were identified using this strategy compared to conventional methods based on intact glycopeptides. Application of this platform to characterize protein core-fucosylation in two breast cancer cell lines, i.e., MDA-MB-231 and MCF7, yields a total of 1615 unique glycosites and about 900 CF sites from one single LC-MS/MS analysis. Differential analysis unraveled the distinct glycosylation pattern for over 201 cell surface drug targets between breast cancer subtypes and provides insights into developing new therapeutic strategies to aid precision medicine. Given the robust performance of this platform, it would have broad application in discovering novel biomarkers based on the CF glycosylation pattern, investigating cancer mechanisms, as well as detecting new intervention targets.

Joint association of physical activity and dietary quality with survival among US cancer survivors: a population-based cohort study.

BACKGROUND: Limited studies have explored the joint effect of physical activity (PA) and dietary quality (DQ) on the mortality outcomes of the cancer population. We aim to investigate the separate and joint prognostic effect of PA and DQ on the survival of US cancer survivors. METHODS: Data of cancer survivors (n=3,007, representing 22 million cancer survivors) were from the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2018. PA was assessed using the self-reported Global Physical Activity Questionnaire (GPAQ) and DQ was evaluated through the Health Eating Index-2015 (HEI-2015). Kaplan-Meier (KM) curves and the Cox proportional hazard model were used to evaluate the associations between separate and joint prognostic effects of PA and DQ with mortality outcomes among cancer survivors. RESULTS: In the joint analyses, cancer survivors with sufficiently active PA (≥600 MET-min/week) and qualified DQ (≥60) presented reduced risks of all-cause mortality (HR 0.45, 95% CI 0.35-0.59) as compared with each lifestyle intervention separately. Meanwhile, the joint effects of either insufficiently or sufficiently active PA (>0 MET-min/week) and qualified DQ (≥60) were associated with lower risks for cancer (HR 0.60, 95% CI 0.40-0.90) and non-cancer mortality (HR 0.43, 95% CI 0.32-0.59). CONCLUSIONS: Our study highlights the combination of active PA and qualified DQ was strongly associated with reduced mortality risk of cancer survivors. Our findings might help to refine the lifestyle intervention recommendations for this population.

Impacts of Fuel Stage Ratio on the Morphological and Nanostructural Characteristics of Soot Emissions from a Twin Annular Premixing Swirler Combustor.

Soot particles emitted from aircraft engines constitute a major anthropogenic source of pollution in the vicinity of airports and at cruising altitudes. This emission poses a significant threat to human health and may alter the global climate. Understanding the characteristics of soot particles, particularly those generated from Twin Annular Premixing Swirler (TAPS) combustors, a mainstream combustor in civil aviation engines, is crucial for aviation environmental protection. In this study, a comprehensive characterization of soot particles emitted from TAPS combustors was conducted using scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), and Raman spectroscopy. The morphology and nanostructure of soot particles were examined across three distinct fuel stage ratios (FSR), at 10%, 15%, and 20%. The SEM analysis of soot particle morphology revealed that coated particles constitute over 90% of the total particle sample, with coating content increasing proportionally to the fuel stage ratio. The results obtained from HRTEM indicated that average primary particle sizes increase with the fuel stage ratio. The results of HRTEM and Raman spectroscopy suggest that the nanostructure of soot particles becomes more ordered and graphitized with an increasing fuel stage ratio, resulting in lower oxidation activity. Specifically, soot fringe length increased with the fuel stage ratio, while soot fringe tortuosity and separation distance decreased. In addition, there is a prevalent occurrence of defects in the graphitic lattice structure of soot particles, suggesting a high degree of elemental carbon disorder.

Hydrological profile observation scheme based on optical fiber sensing for polar sea ice buoy monitoring.

The monitoring of hydrological elements in the polar region is the basis for the study of the dynamic environment under the ice. The traditional cross-season subglacial hydrological environment monitoring mainly relies on tether-type vertical profile measurement ice-based buoys, which have the advantages such as high reliability, high measurement accuracy, and real-time communication, while also has disadvantages of high-cost, large volume and weight, high power consumption, and complex layout. Therefore, it is urgent to develop a new type of ice-based profile buoy with low-cost, miniaturization, low power consumption, convenient deployment, and high reliability. In this paper, a novel optical fiber sensing scheme for ice-based buoy monitoring is proposed, which uses arrayed fiber grating to measure seawater temperature and depth profile and uses a dual-conduction mode resonance mechanism to measure seawater salinity. The temperature, depth, and salinity of seawater can be detected by an all-optical fiber technology in real-time. Preliminary experiments show that the temperature accuracy is ±0.1 °C in the range of -5∼35 °C, the salinity accuracy is ±0.03‰ in the range of 30‰âˆ¼40‰, and the vertical spatial resolution of depth can be adjusted in the range of 0∼1000 m, which can better meet the requirements of polar hydrological multi-layer profile observation. It can provide an innovative technology and equipment support for studying the spatiotemporal change process of the polar subglacial ocean.

Target recognition and segmentation in turbid water using data from non-turbid conditions: a unified approach and experimental validation.

Semantic segmentation of targets in underwater images within turbid water environments presents significant challenges, hindered by factors such as environmental variability, difficulties in acquiring datasets, imprecise data annotation, and the poor robustness of conventional methods. This paper addresses this issue by proposing a novel joint method using deep learning to effectively perform semantic segmentation tasks in turbid environments, with the practical case of efficiently collecting polymetallic nodules in deep-sea while minimizing damage to the seabed environment. Our approach includes a novel data expansion technique and a modified U-net based model. Drawing on the underwater image formation model, we introduce noise to clear water images to simulate images captured under varying degrees of turbidity, thus providing an alternative to the required data. Furthermore, traditional U-net-based modified models have shown limitations in enhancing performance in such tasks. Based on the primary factors underlying image degradation, we propose a new model which incorporates an improved dual-channel encoder. Our method significantly advances the fine segmentation of underwater images in turbid media, and experimental validation demonstrates its effectiveness and superiority under different turbidity conditions. The study provides new technical means for deep-sea resource development, holding broad application prospects and scientific value.

Long-term relatively high dietary manganese intake could decrease the risk of hyperuricemia: Twelve-year distinct dietary manganese consumption trajectories and the China Health and Nutrition Survey.

BACKGROUND AND AIM: Currently, the relationship between dynamic changes in dietary manganese (Mn) intake and risk of hyperuricemia (HU) is still unclear. This study aimed to identify dietary Mn consumption trajectories in the Chinese adults and assess their relation with the risk of HU. METHODS AND RESULTS: Cohort data from the China Health and Nutrition Survey (CHNS) 1997-2009 were employed in this study. Overall, 6886 adult participants were included. Participants were designated into subgroups based on the trajectories of dietary Mn consumption by sex. Cox proportional hazard models were used to explore the associations between different trajectories and the risk of HU. For men, compared with low stable trajectory group, moderate to high trajectory group was significantly related to reduced risk of HU (HR = 0.61, 95% CI: 0.38 to 0.98) with adjustment for covariates. TC, HDL-C, ApoB, and TG exerted partial regulation function between trajectories and HU. For women, compared with low stable trajectory group, high stable trajectory group was significantly related to reduced risk of HU (HR = 0.76, 95% CI: 0.60 to 0.95) with adjustment for covariates. Similarly, TC, HDL-C, ApoB, and ApoA exerted partial regulation function between trajectories and HU. CONCLUSIONS: Long-term relatively high dietary Mn consumption may have a protective effect against HU in Chinese adults. The differences in HU-related factors among different dietary Mn intake trajectories partially regulated the association between these trajectories and HU.

A Two-color Single-molecule Sequencing Platform and Its Clinical Applications.

DNA sequencers have become increasingly important research and diagnostic tools over the past 20 years. In this study, we developed a single-molecule desktop sequencer, GenoCare 1600 (GenoCare), which utilizes amplification-free library preparation and two-color sequencing-by-synthesis chemistry, making it more user-friendly compared with previous single-molecule sequencing platforms for clinical use. Using the GenoCare platform, we sequenced an Escherichia coli standard sample and achieved a consensus accuracy exceeding 99.99%. We also evaluated the sequencing performance of this platform in microbial mixtures and coronavirus disease 2019 (COVID-19) samples from throat swabs. Our findings indicate that the GenoCare platform allows for microbial quantitation, sensitive identification of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, and accurate detection of virus mutations, as confirmed by Sanger sequencing, demonstrating its remarkable potential in clinical application.