sOCP: a framework predicting smORF coding potential based on TIS and in-frame features and effectively applied in the human genome.

Small open reading frames (smORFs) have been acknowledged to play various roles on essential biological pathways and affect human beings from diabetes to tumorigenesis. Predicting smORFs in silico is quite a prerequisite for processing the omics data. Here, we proposed the smORF-coding-potential-predicting framework, sOCP, which provides functions to construct a model for predicting novel smORFs in some species. The sOCP model constructed in human was based on in-frame features and the nucleotide bias around the start codon, and the small feature subset was proved to be competent enough and avoid overfitting problems for complicated models. It showed more advanced prediction metrics than previous methods and could correlate closely with experimental evidence in a heterogeneous dataset. The model was applied to Rattus norvegicus and exhibited satisfactory performance. We then scanned smORFs with ATG and non-ATG start codons from the human genome and generated a database containing about a million novel smORFs with coding potential. Around 72 000 smORFs are located on the lncRNA regions of the genome. The smORF-encoded peptides may be involved in biological pathways rare for canonical proteins, including glucocorticoid catabolic process and the prokaryotic defense system. Our work provides a model and database for human smORF investigation and a convenient tool for further smORF prediction in other species.

The influence of in situ purification system on pathogen in the river fed by the drainage of sewage plant.

An in situ integrated system, consisting of ecological floating islands (EFI), ecological riverbeds (ER), and ecological filter dams (EFD), was built in a ditch only receiving the effluent of sewage plant; the effect of in situ technologies on the distribution of aquatic pathogen was investigated. The results showed the aquatic pathogen decreased along the ditch. Specifically, the relative abundance of Legionella, Aeromonas, and Acinetobacter decreased from 0.032, 0.035, and 0.26 to 0.026%, 0.012%, and 0.08%, respectively. Sedimentation, filtration, and sorption (provided by plant roots and biofilms on substrates) were principal processes for the removal. The nitrogen removal bacteria to prevent the potential risk of eutrophication were also evaluated. The EFI and ER were the dominant sites for Nitrosomonas (34.96%, 32.84%) and Nitrospira (35.74%, 54.73%) enrichment, while EFI and EFD facilitated the enrichment of denitrification bacteria. Notably, the relative abundance of endogenous denitrifiers (DNB-en) (including Dechloromonas at 9.72%, Thermomonas at 0.58%, and Saccharibacteria at 2.55%) exceeded those of exogenous denitrifiers (DNB-ex) (Thauera at 0.20%, Staphylococcus at 0.005%, and Rhodobacter at 0.27%). This study demonstrated that the in situ integrated system was effective in reducing the abundance of pathogens in the drainage channel, and the deficiency of DNB-ex and carbon sources made nitrate removal difficult.

Peripheral amyloid-ß clearance mediates cognitive impairment in non-alcoholic fatty liver disease.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a prevalent risk factor for cognitive impairment. Cerebral amyloid-ß (Aß) accumulation, as an important pathology of cognitive impairment, can be caused by impaired Aß clearance in the periphery. The liver is the primary organ for peripheral Aß clearance, but the role of peripheral Aß clearance in NAFLD-induced cognitive impairment remains unclear. METHODS: We examined correlations between NAFLD severity, Aß accumulation, and cognitive performance in female Sprague-Dawley rats. The impact of NAFLD on hepatic Aß clearance and the involvement of low-density lipoprotein receptor-related protein 1 (LRP-1) were assessed in rat livers and cultured hepatocytes. Additionally, a case-control study, including 549 NAFLD cases and 549 controls (782 males, 316 females), investigated the interaction between NAFLD and LRP-1 rs1799986 polymorphism on plasma Aß levels. FINDINGS: The severity of hepatic steatosis and dysfunction closely correlated with plasma and cerebral Aß accumulations and cognitive deficits in rats. The rats with NAFLD manifested diminished levels of LRP-1 and Aß in liver tissue, with these reductions inversely proportional to plasma and cerebral Aß concentrations and cognitive performance. In vitro, exposure of HepG2 cells to palmitic acid inhibited LRP-1 expression and Aß uptake, which was subsequently reversed by a peroxisome proliferator-activated receptor α (PPARα) agonist. The case-control study revealed NAFLD to be associated with an increment of 8.24% and 10.51% in plasma Aß40 and Aß42 levels, respectively (both P < 0.0001). Moreover, the positive associations between NAFLD and plasma Aß40 and Aß42 levels were modified by the LRP-1 rs1799986 polymorphism (P for interaction = 0.0017 and 0.0015, respectively). INTERPRETATION: LRP-1 mediates the adverse effect of NAFLD on peripheral Aß clearance, thereby contributing to cerebral Aß accumulation and cognitive impairment in NAFLD. FUNDING: Major International (Regional) Joint Research Project, National Key Research and Development Program of China, National Natural Science Foundation of China, and the Angel Nutrition Research Fund.

Polyphyllin I enhances tumor necrosis factor-related apoptosis-inducing ligand-induced inhibition of human osteosarcoma cell growth downregulating the Wnt/ß-catenin pathway.

OBJECTIVE: To investigate the synergistic effects of polyphyllin I (PPI) combined with tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) on the growth of osteosarcoma cells through downregulating the Wnt/ß-catenin signaling pathway. METHODS: Cell viability, apoptosis and cell cycle distribution were examined using cell counting kit-8 and flow cytometry assays. The morphology of cancer cells was observed with inverted phase contrast microscope. The migration and invasion abilities were examined by xCELLigence real time cell analysis DP system and transwell assays. The expressions of poly (adenosine diphosphate-ribose) polymerase, C-Myc, Cyclin B1, cyclin-dependent kinases 1, N-cadherin, Vimentin, Active-ß-catenin, ß-catenin, p-glycogen synthase kinase 3ß (GSK-3ß) and GSK-3ß were determined by Western blotting assay. RESULTS: PPI sensitized TRAIL-induced decrease of viability, migration and invasion, as well as increase of apoptosis and cell cycle arrest of MG-63 and U-2 OS osteosarcoma cells. The synergistic effect of PPI with TRAIL in inhibiting the growth of osteosarcoma cells was at least partially realized through the inactivation of Wnt/ß-catenin signaling pathway. CONCLUSION: The combination of PPI and TRAIL is potentially a novel treatment strategy of osteosarcoma.

Bone age assessment based on different MRI modalities of the proximal humerus epiphysis: the comparisons of T1WI, T2WI, and PDWI.

Bone age assessment (BAA) is crucial in various fields, including legal proceedings, athletic competitions, and clinical medicine. However, the use of X-ray methods for age estimation without medical indication is subject to ethical debate, especially in forensic and athletic fields. The application of magnetic resonance imaging (MRI) with non-ionizing radiation can overcome this limitation in BAA. This study aimed to compare the application value of several MRI modalities of proximal humeral in BAA. A total of 468 patients with shoulder MRIs were retrospectively collected from a Chinese Han population aged 12-30 years (259 males and 209 females) for training and testing, including T1 weighted MRI (T1WI), T2 weighted MRI (T2WI), and Proton density weighted MRI (PDWI). Optimal regression models were established for age estimation, yielding mean absolute error (MAE) values below 2.0 years. The MAE values of T1WI were the lowest, with 1.700 years in males and 1.798 years in females. The area under the curve (AUC) and accuracy values of different MRI modalities of 16-year and 18-year thresholds were all around 0.9. For the 18-year threshold, T1WI outperformed T2WI and PDWI. In conclusion, the three MRI modalities of the proximal humerus can serve as reliable indicators for age assessment, while the T1WI performed better in age assessment and classification.

Comparative proteomic analysis of seed germination between allotetraploid cotton Gossypium hirsutum and Gossypium barbadense.

Seed germination, a key initial event in the plant life cycle, directly affects cotton yield and quality. Gossypium barbadense and Gossypium hirsutum gradually evolved through polyploidization, resulting in different characteristics, and this interspecific variation lacks genetic and molecular explanation. This work aimed to compare the proteomes between G. barbadense and G. hirsutum during seed germination. Here, we identified 2740 proteins for G. barbadense and 3758 for G. hirsutum. In the initial state, proteins in two cotton involved similar bioprocess, such as sugar metabolism, DNA repairing, and ABA signaling pathway. However, in the post-germination stage, G. hirsutum expressed more protein related to redox homeostasis, peroxidase activity, and pathogen interactions. Analyzing the different expression patterns of 915 single-copy orthogroups between the two kinds of cotton indicated that most of the differentially expressed proteins in G. barbadense were related to carbon metabolism. In contrast, most proteins in G. hirsutum were associated with stress response. Besides that, by proteogenomic analysis, we found 349 putative non-canonical peptides, which may be involved in plant development. These results will help to understand the different characteristics of these two kinds of cotton, such as fiber quality, yield, and adaptability. SIGNIFICANCE STATEMENT: Cotton is the predominant natural fiber crop worldwide; Gossypium barbadense and Gossypium hirsutum have evolved through polyploidization to produce differing traits. However, given their specific features, the divergence of mechanisms underlying seed germination between G. hirsutum and G. barbadense has not been discussed. Here, we explore what protein contributes to interspecific differences between G. barbadense and G. hirsutum during the seed germination period. This study helps to elucidate the evolution and domestication history of cotton polyploids and may allow breeders to understand their domestication history better and improve fiber quality and adaptability.

Multichannel-optical imaging for in vivo evaluating the safety and therapeutic efficacy of stem cells in tumor model in terms of cell tropism, proliferation and NF-κB activity.

Stem cell-based cancer treatment has garnered significant attention, yet its safety and efficacy remain incompletely understood. The nuclear factor-kappa B (NF-κB) pathway, a critical signaling mechanism involved in tumor growth, angiogenesis, and invasion, serves as an essential metric for evaluating the behavior of stem cells in tumor models. Herein, we report the development of a triple-channel imaging system capable of simultaneously monitoring the tropism of stem cells towards tumors, assessing tumor proliferation, and quantifying tumor NF-κB activity. In this system, we generated a CRISPR-Cas9 gene-edited human glioblastoma cell line, GE-U87-MG, which provided a reliable readout of the proliferation and NF-κB activity of tumors by EF1α-RFLuc- and NF-κB-GLuc-based bioluminescent imaging, respectively. Additionally, near infrared-II emitting Tat-PEG-AgAuSe quantum dots were developed for tracking of stem cell tropism towards tumor. In a representative case involving human mesenchymal stem cells (hMSCs), multichannel imaging revealed no discernible effect of hMSCs on the proliferation and NF-κB activity of GE-U87-MG tumors. Moreover, hMSCs engineered to overexpress the necrosis factor-related apoptosis-inducing ligand were able to inhibit NF-κB activity and growth of GE-U87-MG in vivo. Taken together, our imaging system represents a powerful and feasible approach to evaluating the safety and therapeutic efficacy of stem cells in tumor models.

Genome analysis and hyphal movement characterization of the hitchhiker endohyphal Enterobacter sp. from Rhizoctonia solani.

Bacterial-fungal interactions are pervasive in the rhizosphere. While an increasing number of endohyphal bacteria have been identified, little is known about their ecology and impact on the associated fungal hosts and the surrounding environment. In this study, we characterized the genome of an Enterobacter sp. Crenshaw (En-Cren), which was isolated from the generalist fungal pathogen Rhizoctonia solani, and examined the genetic potential of the bacterium with regard to the phenotypic traits associated with the fungus. Overall, the En-Cren genome size was typical for members of the genus and was capable of free-living growth. The genome was 4.6 MB in size, and no plasmids were detected. Several prophage regions and genomic islands were identified that harbor unique genes in comparison with phylogenetically closely related Enterobacter spp. Type VI secretion system and cyanate assimilation genes were identified from the bacterium, while some common heavy metal resistance genes were absent. En-Cren contains the key genes for indole-3-acetic acid (IAA) and phenylacetic acid (PAA) biosynthesis, and produces IAA and PAA in vitro, which may impact the ecology or pathogenicity of the fungal pathogen in vivo. En-Cren was observed to move along hyphae of R. solani and on other basidiomycetes and ascomycetes in culture. The bacterial flagellum is essential for hyphal movement, while other pathways and genes may also be involved.IMPORTANCEThe genome characterization and comparative genomics analysis of Enterobacter sp. Crenshaw provided the foundation and resources for a better understanding of the ecology and evolution of this endohyphal bacteria in the rhizosphere. The ability to produce indole-3-acetic acid and phenylacetic acid may provide new angles to study the impact of phytohormones during the plant-pathogen interactions. The hitchhiking behavior of the bacterium on a diverse group of fungi, while inhibiting the growth of some others, revealed new areas of bacterial-fungal signaling and interaction, which have yet to be explored.

Adult age estimation from the sternum using maximum intensity projection images of CT and data mining in a Chinese population.

This study aimed to explore and develop data mining models for adult age estimation based on CT reconstruction images from the sternum. Maximum intensity projection (MIP) images of chest CT were retrospectively collected from a modern Chinese population, and data from 2700 patients (1349 males and 1351 females) aged 20 to 70 years were obtained. A staging technique within four indicators was applied. Several data mining models were established, and mean absolute error (MAE) was the primary comparison parameter. The intraobserver and interobserver agreement levels were good. Within internal validation, the optimal data mining model obtained the lowest MAE of 9.08 in males and 10.41 in females. For the external validation (N = 200), MAEs were 7.09 in males and 7.15 in females. In conclusion, the accuracy of our model for adult age estimation was among similar studies. MIP images of the sternum could be a potential age indicator. However, it should be combined with other indicators since the accuracy level is still unsatisfactory.

Development of loop-mediated isothermal amplification assays for the rapid and accurate diagnosis of Exserohilum turcicum for field applications.

Northern corn leaf blight (NCLB), caused by Exserohilum turcicum, is one of the most devastating foliar diseases of maize. Rapid and accurate diagnosis for this disease is urgently needed but still limited. Here, we establish a field-deployable diagnostic method to detect E. turcicum based on loop-mediated isothermal amplification (LAMP) assays. A software application called K-mer Elimination by Cross-reference (KEC) was utilized to search for the specific sequences belonging to E. turcicum by comparing the whole genome sequence between E. turcicum and other known maize pathogens. Five LAMP primer sets were designed based on specific and single-copy fragments of E. turcicum. Post-LAMP analyses indicated that only the primer set, Et9468_set1, was the most suitable, producing a ladder-like amplification pattern in the agarose gel electrophoresis and a strong fluorescence signal in the presence of SYBR Green I. The LAMP assay using Et9468_set1 primers demonstrated a high level of specificity in distinguishing E. turcicum from six other common fungal pathogens of maize, as well as 12 more fungal and oomycete strains including the epiphytic fungi from maize leaves and other crop pathogens. Moreover, it exhibited remarkable sensitivity by detecting 5 copies per reaction which was approximately 104 times more sensitive compared to conventional PCR. The LAMP assay successfully detected E. turcicum in field maize leaves without DNA extraction, demonstrating its suitability for rapid on-spot detection of NCLB. Our study provides a direct LAMP diagnostic method to detect E. turcicum, which enables on-site pathogen detection in the field and the development of preventive strategies for NCLB management.

Incidence, risk factors for active tuberculosis infection and changes of IGRA in patients with Takayasu arteritis: a prospective cohort study.

There is limited evidence to support the association between tuberculosis (TB) and the occurrence of Takayasu arteritis (TAK). To investigate the incidence of active TB (ATB) in TAK and explore the impact of anti-rheumatic therapy on the occurrence of ATB or reactivation of Latent TB infection (LTBI) and their effect on interferon-γ release assay (IGRA) results, we conducted a prospective study based on the Chinese Registry for Systemic Vasculitis cohort. The standard incidence ratio (SIR) was calculated and stratified by age. Kaplan-Meier analysis was used to determine the effect of variables on ATB or LTBI reactivation in patients with TAK. Data from 825 patients with TAK in the registry were analysed. During a median follow-up of 5 years, 5 patients developed ATB with a crude incidence of 154 (95%CI:57-381) person-years/100,000. The SIR was 5.59 (95%CI:1.81-13.04). Glucocorticoids and conventional disease-modifying anti-rheumatic drugs (cDMARDs) did not increase the risk of ATB or LTBI reactivation (P > 0.05). However, the use of tumour necrosis factor inhibitor (TNFi) increased the risk of ATB in patients with LTBI (P < 0.001). Furthermore, the value of the IGRA assay decreased after treatment (P < 0.05). In conclusion, the incidence of TB infection is markedly increased in patients with TAK and patients with TAK are at high risk of developing ATB. Treatment with glucocorticoids and cDMARDs does not significantly increase the risk for ATB in patients with TAK. Moreover, IGRA may have limited effectiveness in monitoring ATB infection or LTBI reactivation in patients with TAK.

Global trends in research of melanoma differentiation-associated gene 5: a bibliometric analysis from 2002 to 2022.

BACKGROUND: Melanoma differentiation-associated gene 5 (MDA5), as a cytoplasmic sensor for viral double-stranded RNAs, has received increasing attention in recent years. Although considerable headway has been made on the functional role of MDA5 in antiviral immunity and autoimmune disease, the available literature is insufficient to assess the vast field. METHODS: This study performed a bibliometric analysis to investigate current hotspots in the global scientific output of MDA5 over the past two decades. Related publications and recorded information from 2002 to 2022 in the Web of Science Core Collection (WoSCC) database were retrieved. VOSviewer and CiteSpace were used for quantitative evaluation and visualization. RESULTS: A total of 2267 original articles and reviews were obtained, and the annual number of publications related to MDA5 was increasing rapidly. China has published the most papers, while the USA was the most influential country with the most citations and the highest H-index. The Chinese Academy of Sciences, the United States Department of Health and Human Services, and the Journal of Virology were the most prolific research affiliation, funding source, and journal, respectively. Fujita T (Kyoto University) was the most productive author with the highest H-index and had close cooperation with Kato H and Yoneyama M. The keywords "RIG-I," "MDA5," "innate immunity," "double-stranded-RNA," and "recognition" had the highest frequency, while "dermatomyositis" as well as "autoantibody" seemed to be the emerging hotspots. CONCLUSION: This study comprehensively demonstrated the research frontiers of MDA5 and will provide a useful resource for scholars to conduct future decisions. KEY POINTS: We conducted the first in-depth survey of the research frontiers on melanoma differentiation-associated gene 5 (MDA5) over the past two decades via bibliometric analysis. We found that many early breakthroughs have been made in the mechanism of MDA5-mediated antiviral immune responses, and the role of MDA5 in autoimmune and autoinflammatory diseases has raised the recent concern. We identified that the virus infection-associated pathogenesis and effective therapeutic strategy of anti-MDA5 antibody-positive dermatomyositis will remain the hotspots in the future.

Effects of Timing and Types of Protein Supplementation on Improving Muscle Mass, Strength, and Physical Performance in Adults Undergoing Resistance Training: A Network Meta-Analysis.

Precise protein supplementation strategies for muscle improvement are still lacking. The timing or type of protein supplementation has been debated as a window of opportunity to improve muscle mass, strength, and physical performance. We conducted a network meta-analysis of randomized controlled trials with protein supplements and resistance training. PubMed, Web of Science, Cochrane Library, and SPORTDiscus databases were searched until May 1, 2023. We included 116 eligible trials with 4,711 participants that reported on 11 timing and 14 types of protein supplementation. Compared with placebo, protein supplementation after exercise (mean difference [MD]: 0.54 kg [95% confidence intervals 0.10, 0.99] for fat-free mass, MD: 0.34 kg [95% confidence intervals 0.10, 0.58] for skeletal muscle mass) and at night (MD: 2.85 kg [0.49, 5.22] for handgrip strength, MD: 12.12 kg [3.26, 20.99] for leg press strength) was most effective in improving muscle mass and strength, respectively (moderate certainty). Milk proteins (milk, whey protein, yogurt, casein, and bovine colostrum), red meat, and mixed protein were effective for gains in both muscle mass and strength (moderate certainty). No timing or type of protein showed a significant enhancement in physical performance (timed up-to-go test, 6-min walk test, and gait speed). Pre/postexercise and Night are key recommended times of protein intake to increase muscle mass and strength, respectively. Milk proteins are the preferred types of protein supplements for improving muscle mass and strength. Future randomized controlled trials that directly compare the effects of protein timing or types are needed. This trial was registered at International Prospective Register of Systematic Reviews as CRD42022358766.

Machine learning and deep learning enabled age estimation on medial clavicle CT images.

The medial clavicle epiphysis is a crucial indicator for bone age estimation (BAE) after hand maturation. This study aimed to develop machine learning (ML) and deep learning (DL) models for BAE based on medial clavicle CT images and evaluate the performance on normal and variant clavicles. This study retrospectively collected 1049 patients (mean± SD: 22.50±4.34 years) and split them into normal training and test sets, and variant training and test sets. An additional 53 variant clavicles were incorporated into the variant test set. The development stages of normal MCE were used to build a linear model and support vector machine (SVM) for BAE. The CT slices of MCE were automatically segmented and used to train DL models for automated BAE. Comparisons were performed by linear versus ML versus DL, and normal versus variant clavicles. Mean absolute error (MAE) and classification accuracy was the primary parameter of comparison. For BAE, the SVM had the best MAE of 1.73 years, followed by the commonly-used CNNs (1.77-1.93 years), the linear model (1.94 years), and the hybrid neural network CoAt Net (2.01 years). In DL models, SE Net 18 was the best-performing DL model with similar results to SVM in the normal test set and achieved an MAE of 2.08 years in the external variant test. For age classification, all the models exhibit superior performance in the classification of 18-, 20-, 21-, and 22-year thresholds with limited value in the 16-year threshold. Both ML and DL models produce desirable performance in BAE based on medial clavicle CT.

Deep learning based automatic internal gross target volume delineation from 4D-CT of hepatocellular carcinoma patients.

BACKGROUND: The location and morphology of the liver are significantly affected by respiratory motion. Therefore, delineating the gross target volume (GTV) based on 4D medical images is more accurate than regular 3D-CT with contrast. However, the 4D method is also more time-consuming and laborious. This study proposes a deep learning (DL) framework based on 4D-CT that can achieve automatic delineation of internal GTV. METHODS: The proposed network consists of two encoding paths, one for feature extraction of adjacent slices (spatial slices) in a specific 3D-CT sequence, and one for feature extraction of slices at the same location in three adjacent phase 3D-CT sequences (temporal slices), a feature fusion module based on an attention mechanism was proposed for fusing the temporal and spatial features. Twenty-six patients' 4D-CT, each consisting of 10 respiratory phases, were used as the dataset. The Hausdorff distance (HD95), Dice similarity coefficient (DSC), and volume difference (VD) between the manual and predicted tumor contour were computed to evaluate the model's segmentation accuracy. RESULTS: The predicted GTVs and IGTVs were compared quantitatively and visually with the ground truth. For the test dataset, the proposed method achieved a mean DSC of 0.869 ± 0.089 and an HD95 of 5.14 ± 3.34 mm for all GTVs, with under-segmented GTVs on some CT slices being compensated by GTVs on other slices, resulting in better agreement between the predicted IGTVs and the ground truth, with a mean DSC of 0.882 ± 0.085 and an HD95 of 4.88 ± 2.84 mm. The best GTV results were generally observed at the end-inspiration stage. CONCLUSIONS: Our proposed DL framework for tumor segmentation on 4D-CT datasets shows promise for fully automated delineation in the future. The promising results of this work provide impetus for its integration into the 4DCT treatment planning workflow to improve hepatocellular carcinoma radiotherapy.

Weakly supervised learning-based 3D bladder reconstruction from 2D ultrasound images for bladder volume measurement.

BACKGROUND: Accurate measurement of bladder volume is necessary to maintain the consistency of the patient's anatomy in radiation therapy for pelvic tumors. As the diversity of the bladder shape, traditional methods for bladder volume measurement from 2D ultrasound have been found to produce inaccurate results. PURPOSE: To improve the accuracy of bladder volume measurement from 2D ultrasound images for patients with pelvic tumors. METHODS: The bladder ultrasound images from 130 patients with pelvic cancer were collected retrospectively. All data were split into a training set (80 patients), a validation set (20 patients), and a test set (30 patients). A total of 12 transabdominal ultrasound images for one patient were captured by automatically rotating the ultrasonic probe with an angle step of 15°. An incomplete 3D ultrasound volume was synthesized by arranging these 2D ultrasound images in 3D space according to the acquisition angles. With this as input, a weakly supervised learning-based 3D bladder reconstruction neural network model was built to predict the complete 3D bladder. The key point is that we designed a novel loss function, including the supervised loss of bladder segmentation in the ultrasound images at known angles and the compactness loss of the 3D bladder. Bladder volume was calculated by counting the number of voxels belonging to the 3D bladder. The dice similarity coefficient (DSC) was used to evaluate the accuracy of bladder segmentation, and the relative standard deviation (RSD) was used to evaluate the calculation accuracy of bladder volume with that of computed tomography (CT) images as the gold standard. RESULTS: The results showed that the mean DSC was up to 0.94 and the mean absolute RSD can be reduced to 6.3% when using 12 ultrasound images of one patient. Further, the mean DSC also was up to 0.90 and the mean absolute RSD can be reduced to 9.0% even if only two ultrasound images were used (i.e., the angle step is 90°). Compared with the commercial algorithm in bladder scanners, which has a mean absolute RSD of 13.6%, our proposed method showed a considerably huge improvement. CONCLUSIONS: The proposed weakly supervised learning-based 3D bladder reconstruction method can greatly improve the accuracy of bladder volume measurement. It has great potential to be used in bladder volume measurement devices in the future.

Associations of Various Physical Activities with Mortality and Life Expectancy are Mediated by Telomere Length.

OBJECTIVES: Physical activity (PA) and telomeres both contribute to healthy aging and longevity. To investigate the optimal dosage of various PA for longevity and the role of telomere length in PA and mortality. DESIGN: Prospective cohort study. SETTING AND PARTICIPANTS: A total of 333,865 adults (mean age of 56 years) from the UK Biobank were analyzed. METHODS: Walking, moderate PA (MPA), and vigorous PA (VPA) were self-reported via questionnaire, and leukocyte telomere length (LTL) was measured. Cox proportional hazards regression was used to predict all-cause mortality risk. A flexible parametric Royston-Parmar survival model was used to estimate life expectancy. RESULTS: During a median follow-up of 13.8 years, 19,789 deaths were recorded. Compared with the no-walking group, 90 to 720 minutes/week of walking was similarly associated with 27% to 31% of lower mortality and about 6 years of additional life expectancy. We observed nearly major benefits for mortality and life expectancy among those meeting the PA guidelines [151-300 minutes/wk for MPA: hazard ratio (HR) 0.80, 95% CI 0.75-0.85, 3.40-3.42 additional life years; 76-150 minutes/wk for VPA: HR 0.78, 95% CI 0.75-0.82, 2.61 years (2.33-2.89)] vs the no-PA group. Similar benefits were also observed at 76-150 and 301-375 minutes/wk of MPA (18%-19% lower mortality, 3.20-3.42 gained years) or 151-300 minutes/wk of VPA (20%-26% lower mortality, 2.41-2.61 gained years). The associations between MPA, VPA, and mortality risk were slightly mediated by LTL (≈1% mediation proportion, both P < .001). CONCLUSIONS AND IMPLICATIONS: Our study suggests a more flexible range of PA than the current PA guidelines, which could gain similar benefits and is easier to achieve: 90 to 720 minutes/wk of walking, 75 to 375 minutes/wk of MPA, and 75 to 300 minutes/wk of VPA. Telomeres might be a potential mechanism by which PA promotes longevity.

Automated bone age assessment from knee joint by integrating deep learning and MRI-based radiomics.

Bone age assessment (BAA) is a crucial task in clinical, forensic, and athletic fields. Since traditional age estimation methods are suffered from potential radiation damage, this study aimed to develop and evaluate a deep learning radiomics method based on multiparametric knee MRI for noninvasive and automatic BAA. This retrospective study enrolled 598 patients (age range,10.00-29.99 years) who underwent MR examinations of the knee joint (T1/T2*/PD-weighted imaging). Three-dimensional convolutional neural networks (3D CNNs) were trained to extract and fuse multimodal and multiscale MRI radiomic features for age estimation and compared to traditional machine learning models based on hand-crafted features. The age estimation error was greater in individuals aged 25-30 years; thus, this method may not be suitable for individuals over 25 years old. In the test set aged 10-25 years (n = 95), the 3D CNN (a fusion of T1WI, T2*WI, and PDWI) demonstrated the lowest mean absolute error of 1.32 ± 1.01 years, which is higher than that of other MRI modalities and the hand-crafted models. In the classification for 12-, 14-, 16-, and 18- year thresholds, accuracies and the areas under the ROC curves were all over 0.91 and 0.96, which is similar to the manual methods. Visualization of important features showed that 3D CNN estimated age by focusing on the epiphyseal plates. The deep learning radiomics method enables non-invasive and automated BAA from multimodal knee MR images. The use of 3D CNN and MRI-based radiomics has the potential to assist radiologists or medicolegists in age estimation.

Non-apoptotic programmed cell deaths in diabetic pulmonary dysfunction: the new side of advanced glycation end products.

Diabetes mellitus (DM) is a chronic metabolic disorder that affects multiple organs and systems, including the pulmonary system. Pulmonary dysfunction in DM patients has been observed and studied for years, but the underlying mechanisms have not been fully understood. In addition to traditional mechanisms such as the production and accumulation of advanced glycation end products (AGEs), angiopathy, tissue glycation, oxidative stress, and systemic inflammation, recent studies have focused on programmed cell deaths (PCDs), especially the non-apoptotic ones, in diabetic pulmonary dysfunction. Non-apoptotic PCDs (NAPCDs) including autophagic cell death, necroptosis, pyroptosis, ferroptosis, and copper-induced cell death have been found to have certain correlations with diabetes and relevant complications. The AGE-AGE receptor (RAGE) axis not only plays an important role in the traditional pathogenesis of diabetes lung disease but also plays an important role in non-apoptotic cell death. In this review, we summarize novel studies about the roles of non-apoptotic PCDs in diabetic pulmonary dysfunction and focus on their interactions with the AGE-RAGE axis.

Yangqing Chenfei formula alleviates crystalline silica induced pulmonary inflammation and fibrosis by suppressing macrophage polarization.

OBJECTIVE: To explore the underlying mechanisms of the effects of Yangqing Chenfei formula (, YCF) on inflammation and fibrosis in silicosis via inhibition of macrophage polarization. METHODS: A silicotic rat model was established via a single intratracheal instillation of silica particles on the first day of week 0. Subsequently, YCF was administered intragastrically to silicotic rats during weeks 0-2 and 5-8 twice daily. The mouse-derived alveolar macrophage cell line was used to investigate the mechanisms of YCF in M1/M2 polarization. RESULTS: YCF treatment effectively inhibited lung pathological changes, including inflammatory cell infiltration and tissue damage, and increased the forced expiratory volume in the first 0.3 s, functional residual capacity, and maximal mid-expiratory flow in weeks 2 and 8. Furthermore, the treatment improved lung functions by upregulating tidal volume, pause increase, and expiratory flow at 50% tidal volume from weeks 5 to 8. Moreover, YCF could significantly suppressed the progression of inflammation and fibrosis, by reducing the levels of inflammatory cytokines, as well as collagen- I and III. YCF treatment also decreased the numbers of macrophages and M1/M2 macrophages and the level of transforming growth factor-ß (TGF-ß). Additionally, YCF5, the effective substance in YCF, decreased lipopolysaccharide and interferon-γ-induced M1 macrophage polarization in a concentration-dependent manner. The mechanism of anti-M1 polarization might be related to a decrease in extracellular signal-regulated kinase, c-JUN N-terminal kinase, P38, and P65 phosphorylation. Furthermore, YCF5 inhibited interleukin-4-induced M2 macrophages by decreasing the protein and mRNA expressions of arginase-1 and CD206 as well as the levels of profibrotic factors, such as TGF-ß and connective tissue growth factor. The mechanisms underlying the anti-M2 polarization of YCF5 were primarily associated with the inhibition of the nuclear translocation of phosphorylated signal transducer and activator of transcription 6 (p-STAT6). CONCLUSION: YCF significantly inhibits inflammation and fibrosis in silicotic rats probably via the suppression of M1/M2 macrophage polarization mediated by the inhibition of mitogen-activated protein kinase and nuclear factor kappa B signaling pathways and Janus kinase/STAT6 pathways.