Lysozyme 1 Inflamed CCR2+ Macrophages Promote Obesity-Induced Cardiac Dysfunction.

BACKGROUND: Macrophages are key players in obesity-associated cardiovascular diseases, which are marked by inflammatory and immune alterations. However, the pathophysiological mechanisms underlying macrophage's role in obesity-induced cardiac inflammation are incompletely understood. Our study aimed to identify the key macrophage population involved in obesity-induced cardiac dysfunction and investigate the molecular mechanism that contributes to the inflammatory response. METHODS: In this study, we used single-cell RNA-sequencing analysis of Cd45+CD11b+F4/80+ cardiac macrophages to explore the heterogeneity of cardiac macrophages. The CCR2+ (C-C chemokine receptor 2) macrophages were specifically removed by a dual recombinase approach, and the macrophage CCR2 was deleted to investigate their functions. We also performed cleavage under target and tagmentation analysis, chromatin immunoprecipitation-polymerase chain reaction, luciferase assay, and macrophage-specific lentivirus transfection to define the impact of lysozyme C in macrophages on obesity-induced inflammation. RESULTS: We find that the Ccr2 cluster undergoes a functional transition from homeostatic maintenance to proinflammation. Our data highlight specific changes in macrophage behavior during cardiac dysfunction under metabolic challenge. Consistently, inducible ablation of CCR2+CX3CR1+ macrophages or selective deletion of macrophage CCR2 prevents obesity-induced cardiac dysfunction. At the mechanistic level, we demonstrate that the obesity-induced functional shift of CCR2-expressing macrophages is mediated by the CCR2/activating transcription factor 3/lysozyme 1/NF-κB (nuclear factor kappa B) signaling. Finally, we uncover a noncanonical role for lysozyme 1 as a transcription activator, binding to the RelA promoter, driving NF-κB signaling, and strongly promoting inflammation and cardiac dysfunction in obesity. CONCLUSIONS: Our findings suggest that lysozyme 1 may represent a potential target for the diagnosis of obesity-induced inflammation and the treatment of obesity-induced heart disease.

Association between plant-based dietary pattern and biological aging trajectory in a large prospective cohort.

BACKGROUND: Aging is a dynamic and heterogeneous process that may better be captured by trajectories of aging biomarkers. Biological age has been advocated as a better biomarker of aging than chronological age, and plant-based dietary patterns have been found to be linked to aging. However, the associations of biological age trajectories with mortality and plant-based dietary patterns remained unclear. METHODS: Using group-based trajectory modeling approach, we identified distinctive aging trajectory groups among 12,784 participants based on a recently developed biological aging measure acquired at four-time points within an 8-year period. We then examined associations between aging trajectories and quintiles of plant-based dietary patterns assessed by overall plant-based diet index (PDI), healthful PDI (hPDI), and unhealthful PDI (uPDI) among 10,191 participants who had complete data on dietary intake, using multivariable multinomial logistics regression adjusting for sociodemographic and lifestyles factors. Cox proportional hazards regression models were applied to investigate the association between aging trajectories and all-cause mortality. RESULTS: We identified three latent classes of accelerated aging trajectories: slow aging, medium-degree, and high-degree accelerated aging trajectories. Participants who had higher PDI or hPDI had lower odds of being in medium-degree (OR = 0.75, 95% CI: 0.65, 0.86 for PDI; OR = 0.73, 95% CI: 0.62, 0.85 for hPDI) or high-degree (OR = 0.63, 95% CI: 0.46, 0.86 for PDI; OR = 0.62, 95% CI: 0.44, 0.88 for hPDI) accelerated aging trajectories. Participants in the highest quintile of uPDI were more likely to be in medium-degree (OR = 1.72, 95% CI: 1.48, 1.99) or high-degree (OR = 1.70, 95% CI: 1.21, 2.38) accelerated aging trajectories. With a mean follow-up time of 8.40 years and 803 (6.28%) participants died by the end of follow-up, we found that participants in medium-degree (HR = 1.56, 95% CI: 1.29, 1.89) or high-degree (HR = 3.72, 95% CI: 2.73, 5.08) accelerated aging trajectory groups had higher risks of death than those in the slow aging trajectory. CONCLUSIONS: We identified three distinctive aging trajectories in a large Asian cohort and found that adopting a plant-based dietary pattern, especially when rich in healthful plant foods, was associated with substantially lowered pace of aging.

A fast breeding strategy creates fragrance- and anthocyanin-enriched rice lines by marker-free gene-editing and hybridization.

As rice is a staple food for nearly half of the world's population, rice varieties with excellent agronomic traits as well as high flavor and nutritional quality such as fragrant rice and purple rice are naturally favored by the market. In the current study, we adopt a fast breeding strategy to improve the aroma and anthocyanin content in the excellent rice inbred line, F25. The strategy skillfully used the advantages of obtaining editing pure lines in T0 generation of CRISPR/Cas9 editing system and easy observation of purple character and grain shape, integrated the subsequent screening of non-transgenic lines, and the elimination of undesirable edited variants from gene-editing and cross-breeding at the same time as the separation of the progeny from the purple cross, thus expediting the breeding process. Compared with conventional breeding strategies, this strategy saves about 6-8 generations and reduces breeding costs. Firstly, we edited the OsBADH2 gene associated with rice flavor using an Agrobacterium-mediated CRISPR/Cas9 system to improve the aroma of F25. In the T0 generation, a homozygous OsBADH2-edited F25 line (F25B) containing more of the scented substance 2-AP was obtained. Then, we crossed F25B (♀) with a purple rice inbred line, P351 (♂), with high anthocyanin enrichment to improve the anthocyanin content of F25. After nearly 2.5 years of screening and identification over five generations, the undesirable variation characteristics caused by gene-editing and hybridization and the transgenic components were screened out. Finally, the improved F25 line with highly stable aroma component, 2-AP, increased anthocyanin content and no exogenous transgenic components were obtained. This study not only provides high-quality aromatic anthocyanin rice lines that meet the market demand, but also offers a reference for the comprehensive use of CRISPR/Cas9 editing technology, hybridization, and marker-assisted selection to accelerate multi-trait improvement and breeding process. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01369-1.

Transcriptomic Analysis Revealed Key Defense Genes and Signaling Pathways Mediated by the Arabidopsis thaliana Gene SAD2 in Response to Infection with Pseudomonas syringae pv. Tomato DC3000.

Nucleocytoplasmic transport receptors play key roles in the nuclear translocation of disease resistance proteins, but the associated mechanisms remain unclear. The Arabidopsis thaliana gene SAD2 encodes an importin ß-like protein. A transgenic Arabidopsis line overexpressing SAD2 (OESAD2/Col-0) showed obvious resistance to Pseudomonas syringae pv. tomato DC3000 (Pst DC3000) compared to the wild type (Col-0), but the knockout mutant sad2-5 was susceptible. Transcriptomic analysis was then performed on Col-0, OESAD2/Col-0, and sad2-5 leaves at 0, 1, 2, and 3 days post-inoculation with Pst DC3000. A total of 1825 differentially expressed genes (DEGs) were identified as putative biotic stress defense genes regulated by SAD2, 45 of which overlapped between the SAD2 knockout and overexpression datasets. Gene Ontology (GO) analysis indicated that the DEGs were broadly involved in single-organism cellular metabolic processes and in response to stimulatory stress. Kyoto Encyclopedia of Genes and Genomes (KEGG) biochemical pathway analysis revealed that many of the DEGs were associated with the biosynthesis of flavonoids and other specialized metabolites. Transcription factor analysis showed that a large number of ERF/AP2, MYB, and bHLH transcription factors were involved in SAD2-mediated plant disease resistance. These results provide a basis for future exploration of the molecular mechanisms associated with SAD2-mediated disease resistance and establish a set of key candidate disease resistance genes.

Self-Maintenance of Cardiac Resident Reparative Macrophages Attenuates Doxorubicin-Induced Cardiomyopathy Through the SR-A1-c-Myc Axis.

RATIONALE: Doxorubicin-induced cardiomyopathy (DiCM) is a primary cause of heart failure and mortality in cancer patients, in which macrophage-orchestrated inflammation serves as an essential pathological mechanism. However, the specific roles of tissue-resident and monocyte-derived macrophages in DiCM remain poorly understood. OBJECTIVE: Uncovering the origins, phenotypes, and functions of proliferative cardiac resident macrophages and mechanistic insights into the self-maintenance of cardiac macrophage during DiCM progression. METHODS AND RESULTS: Mice were administrated with doxorubicin to induce cardiomyopathy. Dynamic changes of resident and monocyte-derived macrophages were examined by lineage tracing, parabiosis, and bone marrow transplantation. We found that the monocyte-derived macrophages primarily exhibited a proinflammatory phenotype that dominated the whole DiCM pathological process and impaired cardiac function. In contrast, cardiac resident macrophages were vulnerable to doxorubicin insult. The survived resident macrophages exhibited enhanced proliferation and conferred a reparative role. Global or myeloid specifically ablation of SR-A1 (class A1 scavenger receptor) inhibited proliferation of cardiac resident reparative macrophages and, therefore, exacerbated cardiomyopathy in DiCM mice. Importantly, the detrimental effect of macrophage SR-A1 deficiency was confirmed by transplantation of bone marrow. At the mechanistic level, we show that c-Myc (Avian myelocytomatosis virus oncogene cellular homolog), a key transcriptional factor for the SR-A1-P38-SIRT1 (Sirtuin 1) pathway, mediated the effect of SR-A1 in reparative macrophage proliferation in DiCM. CONCLUSIONS: The SR-A1-c-Myc axis may represent a promising target to treat DiCM through augmentation of cardiac resident reparative macrophage proliferation.

Macrophage MSR1 promotes the formation of foamy macrophage and neuronal apoptosis after spinal cord injury.

BACKGROUND: A sustained inflammatory response following spinal cord injury (SCI) contributes to neuronal damage, inhibiting functional recovery. Macrophages, the major participants in the inflammatory response, transform into foamy macrophages after phagocytosing myelin debris, subsequently releasing inflammatory factors and amplifying the secondary injury. Here, we assessed the effect of macrophage scavenger receptor 1 (MSR1) in phagocytosis of myelin debris after SCI and explained its possible mechanism. METHODS: The SCI model was employed to determine the critical role of MSR1 in phagocytosis of myelin debris in vivo. The potential functions and mechanisms of MSR1 were explored using qPCR, western blotting, and immunofluorescence after treating macrophages and RAW264.7 with myelin debris in vitro. RESULTS: In this study, we found improved recovery from traumatic SCI in MSR1-knockout mice over that in MSR1 wild-type mice. Furthermore, MSR1 promoted the phagocytosis of myelin debris and the formation of foamy macrophage, leading to pro-inflammatory polarization in vitro and in vivo. Mechanistically, in the presence of myelin debris, MSR1-mediated NF-κB signaling pathway contributed to the release of inflammatory mediators and subsequently the apoptosis of neurons. CONCLUSIONS: Our study elucidates a previously unrecognized role of MSR1 in the pathophysiology of SCI and suggests that its inhibition may be a new treatment strategy for this traumatic condition.

A transformer-based unified multimodal framework for Alzheimer's disease assessment.

In Alzheimer's disease (AD) assessment, traditional deep learning approaches have often employed separate methodologies to handle the diverse modalities of input data. Recognizing the critical need for a cohesive and interconnected analytical framework, we propose the AD-Transformer, a novel transformer-based unified deep learning model. This innovative framework seamlessly integrates structural magnetic resonance imaging (sMRI), clinical, and genetic data from the extensive Alzheimer's Disease Neuroimaging Initiative (ADNI) database, encompassing 1651 subjects. By employing a Patch-CNN block, the AD-Transformer efficiently transforms image data into image tokens, while a linear projection layer adeptly converts non-image data into corresponding tokens. As the core, a transformer block learns comprehensive representations of the input data, capturing the intricate interplay between modalities. The AD-Transformer sets a new benchmark in AD diagnosis and Mild Cognitive Impairment (MCI) conversion prediction, achieving remarkable average area under curve (AUC) values of 0.993 and 0.845, respectively, surpassing those of traditional image-only models and non-unified multimodal models. Our experimental results confirmed the potential of the AD-Transformer as a potent tool in AD diagnosis and MCI conversion prediction. By providing a unified framework that jointly learns holistic representations of both image and non-image data, the AD-Transformer paves the way for more effective and precise clinical assessments, offering a clinically adaptable strategy for leveraging diverse data modalities in the battle against AD.

A biological age model based on physical examination data to predict mortality in a Chinese population.

Biological age could be reflective of an individual's health status and aging degree. Limited estimations of biological aging based on physical examination data in the Chinese population have been developed to quantify the rate of aging. We developed and validated a novel aging measure (Balanced-AGE) based on readily available physical health examination data. In this study, a repeated sub-sampling approach was applied to address the data imbalance issue, and this approach significantly improved the performance of biological age (Balanced-AGE) in predicting all-cause mortality with a 10-year time-dependent AUC of 0.908 for all-cause mortality. This mortality prediction tool was found to be effective across different subgroups by age, sex, smoking, and alcohol consumption status. Additionally, this study revealed that individuals who were underweight, smokers, or drinkers had a higher extent of age acceleration. The Balanced-AGE may serve as an effective and generally applicable tool for health assessment and management among the elderly population.

SAD2 functions in plant pathogen Pseudomonas syringae pv tomato DC3000 defense by regulating the nuclear accumulation of MYB30 in Arabidopsis thaliana.

Accurate nucleocytoplasmic transport of signal molecules is essential for plant growth and development. Multiple studies have confirmed that nucleocytoplasmic transport and receptors are involved in regulating plant disease resistance responses, however, little is known about the regulatory mechanism in plants. In this study, we showed that the mutant of the importin beta-like protein SAD2 exhibited a more susceptible phenotype than wild-type Col-0 after treatment with Pseudomonas syringae pv tomato DC3000 (Pst DC3000). Coimmunoprecipitation (Co-IP) and bimolecular fluorescence complementation (BiFC) experiments demonstrated that SAD2 interacts with the hypersensitive response (HR)-positive transcriptional regulator MYB30. Subcellular localization showed that MYB30 was not fully localized in the nucleus in sad2-5 mutants, and western-blot experiments further indicated that SAD2 was required for MYB30 nuclear trafficking during the pathogen infection process. A phenotypic test of pathogen inoculation demonstrated that MYB30 partially rescued the disease symptoms of sad2-5 caused by Pst DC3000, and that MYB30 worked downstream of SAD2 in plant pathogen defense. These results suggested that SAD2 might be involved in plant pathogen defense by mediating MYB30 nuclear trafficking. Taken together, our results revealed the important function of SAD2 in plant pathogen defense and enriched understanding of the mechanism of nucleocytoplasmic transport-mediated plant pathogen defense.

Shaping school for childhood myopia: the association between floor area ratio of school environment and myopia in China.

AIM: To investigate the association of floor area ratio (FAR), an indicator of built environments, and myopia onset. METHODS: This prospective cohort study recruited 136 753 children aged 6-10 years from 108 schools in Shenzhen, China at baseline (2016-2017). Refractive power was measured with non-cycloplegic autorefraction over a 2-year follow-up period. FAR was objectively evaluated using geographical information system technology. Mixed-effects logistic regression models were constructed to examine the association of FAR with a 2-year cumulative incidence of myopia among individuals without baseline myopia; multiple linear regression model, with a 2-year cumulative incidence rate of myopia at each school. RESULTS: Of 101 624 non-myopic children (56.3% boys; mean (SE) age, 7.657±1.182 years) included in the study, 26 391 (26.0%) of them developed myopia after 2 years. In the individual-level analysis adjusting for demographic, socioeconomic and greenness factors, an IQR in FAR was associated with a decreased risk of 2-year myopia incidence (OR 0.898, 95% CI 0.866 to 0.932, p<0.001). Similar findings were observed in the analysis additionally adjusted for genetic and behavioural factors (OR 0.821, 95% CI 0.766 to 0.880, p<0.001). In the school-level, an IQR increase in FAR was found to be associated with a 2.0% reduction in the 2-year incidence rate of myopia (95% CI 1.3% to 2.6%, p<0.001). CONCLUSIONS: Exposure to higher FAR was associated with a decreased myopia incidence, providing insights into myopia prevention through school built environments in China.

Pathologist-level diagnosis of ulcerative colitis inflammatory activity level using an automated histological grading method.

BACKGROUND AND AIMS: Inflammatory bowel disease (IBD) is a global disease that is evolving with increasing incidence. However, there are few works on computationally assisted diagnosis of IBD based on pathological images. Therefore, based on the UK and Chinese IBD diagnostic guidelines, our study established an artificial intelligence-assisted diagnostic system for histologic grading of inflammatory activity in ulcerative colitis (UC). METHODS: We proposed an efficient deep-learning (DL) method for grading inflammatory activity in whole-slide images (WSIs) of UC pathology. Our model was constructed using 603 UC WSIs from Nanjing Drum Tower Hospital for model train set and internal test set. We collected 212 UC WSIs from Zhujiang Hospital as an external test set. Initially, the pre-trained ResNet50 model on the ImageNet dataset was employed to extract image patch features from UC patients. Subsequently, a multi-instance learning (MIL) approach with embedded self-attention was utilized to aggregate tissue image patch features, representing the entire WSI. Finally, the model was trained based on the aggregated features and WSI annotations provided by senior gastrointestinal pathologists to predict the level of inflammatory activity in UC WSIs. RESULTS: In the task of distinguishing the presence or absence of inflammatory activity, the Area Under Curve (AUC) value in the internal test set is 0.863 (95% confidence interval [CI] 0.829, 0.898), with a sensitivity of 0.913 (95% [CI] 0.866, 0.961), and specificity of 0.816 (95% [CI] 0.771, 0.861). The AUC in the external test set is 0.947 (95% confidence interval [CI] 0.939, 0.955), with a sensitivity of 0.889 (905% [CI] 0.837, 0.940), and specificity of 0.858 (95% [CI] 0.777, 0.939). For distinguishing different levels of inflammatory activity in UC, the average Macro-AUC in the internal test set and the external test set are 0.827 (95% [CI] 0.803, 0.850) and 0.908 (95% [CI] 0.882, 0.935). the average Micro-AUC in the internal test set and the external test set are 0.816 (95% [CI] 0.792, 0.840) and 0.898 (95% [CI] 0.869, 0.926). CONCLUSIONS: Comparative analysis with diagnoses made by pathologists at different expertise levels revealed that the algorithm reached a proficiency comparable to the pathologist with 5 years of experience. Furthermore, our algorithm performed superior to other MIL algorithms.

Comparing the impact of three-dimensional digital visualization technology versus traditional microscopy on microsurgeons in microsurgery: a prospective self-controlled study.

BACKGROUND: Emerging three-dimensional digital visualization technology (DVT) provides more advantages than traditional microscopy in microsurgery; however, its impact on microsurgeons' visual and nervous systems and delicate microsurgery is still unclear, which hinders the wider implementation of DVT in digital visualization for microsurgery. METHODS AND MATERIAL: Forty-two microsurgeons from the Zhongshan Ophthalmic Center were enrolled in this prospective self-controlled study. Each microsurgeon consecutively performed 30 min conjunctival sutures using a three-dimensional digital display and a microscope, respectively. Visual function, autonomic nerve activity, and subjective symptoms were evaluated before and immediately after the operation. Visual functions, including accommodative lag, accommodative amplitude, near point of convergence and contrast sensitivity function (CSF), were measured by an expert optometrist. Heart rate variability was recorded by a wearable device for monitoring autonomic nervous activity. Subjective symptoms were evaluated by questionnaires. Microsurgical performance was assessed by the video-based Objective Structured Assessment of Technical Skill (OSATS) tool. RESULTS: Accommodative lag decreased from 0.63 (0.18) diopters (D) to 0.55 (0.16) D ( P =0.014), area under the log contrast sensitivity function increased from 1.49 (0.15) to 1.52 (0.14) ( P =0.037), and heart rate variability decreased from 36.00 (13.54) milliseconds (ms) to 32.26 (12.35) ms ( P =0.004) after using the DVT, but the changes showed no differences compared to traditional microscopy ( P >0.05). No statistical significance was observed for global OSATS scores between the two rounds of operations [mean difference, 0.05 (95% CI: -1.17 to 1.08) points; P =0.95]. Subjective symptoms were quite mild after using both techniques. CONCLUSIONS: The impact of DVT-based procedures on microsurgeons includes enhanced accommodation and sympathetic activity, but the changes and surgical performance are not significantly different from those of microscopy-based microsurgery. Our findings indicate that short-term use of DVT is reliable for microsurgery and the long-term effect of using DVT deserve more consideration.

Development of a Novel Multidimensional Measure of Aging to Predict Mortality and Morbidity in the Prospective MJ Cohort.

BACKGROUND: Although biological aging has been proposed as a more accurate measure of aging, few biological aging measures have been developed for Asians, especially for young adults. METHODS: A total of 521 656 participants were enrolled in the MJ cohort (1996-2011) and were followed until death, loss-to-follow-up, or December 31, 2011, whichever came first. We selected 14 clinical biomarkers, including chronological age, using a random forest algorithm, and developed a multidimensional aging measure (MDAge). Model performance was assessed by area under the curve (AUC) and internal calibration. We evaluated the associations of MDAge and residuals from regressing MDAge on chronological age (MDAgeAccel) with mortality and morbidity, and assessed the robustness of our findings. RESULTS: MDAge achieved an excellent AUC of 0.892 in predicting all-cause mortality (95% confidence interval [CI]: 0.889-0.894). Participants with higher MDAge at baseline were at a higher risk of death (per 5 years, hazard ration [HR] = 1.671, 95% CI: 1.662-1.680), and the association remained after controlling for other variables and in different subgroups. Furthermore, participants with higher MDAgeAccel were associated with shortened life expectancy. For instance, compared to men who were biologically younger (MDAgeAccel ≤ 0) at baseline, men in the highest tertiles of MDAgeAccel had shortened life expectancy by 17.23 years. In addition, higher MDAgeAccel was associated with having chronic disease either cross-sectionally (per 1-standard deviation [SD], odds ratio [OR] = 1.564, 95% CI: 1.552-1.575) or longitudinally (per 1-SD, OR = 1.218, 95% CI: 1.199-1.238). CONCLUSION: MDAge accurately predicted mortality and morbidity, which has great potential in the early identification of individuals at higher risk and therefore promoting early intervention.

LensAge index as a deep learning-based biological age for self-monitoring the risks of age-related diseases and mortality.

Age is closely related to human health and disease risks. However, chronologically defined age often disagrees with biological age, primarily due to genetic and environmental variables. Identifying effective indicators for biological age in clinical practice and self-monitoring is important but currently lacking. The human lens accumulates age-related changes that are amenable to rapid and objective assessment. Here, using lens photographs from 20 to 96-year-olds, we develop LensAge to reflect lens aging via deep learning. LensAge is closely correlated with chronological age of relatively healthy individuals (R2 > 0.80, mean absolute errors of 4.25 to 4.82 years). Among the general population, we calculate the LensAge index by contrasting LensAge and chronological age to reflect the aging rate relative to peers. The LensAge index effectively reveals the risks of age-related eye and systemic disease occurrence, as well as all-cause mortality. It outperforms chronological age in reflecting age-related disease risks (p < 0.001). More importantly, our models can conveniently work based on smartphone photographs, suggesting suitability for routine self-examination of aging status. Overall, our study demonstrates that the LensAge index may serve as an ideal quantitative indicator for clinically assessing and self-monitoring biological age in humans.

Early detection of visual impairment in young children using a smartphone-based deep learning system.

Early detection of visual impairment is crucial but is frequently missed in young children, who are capable of only limited cooperation with standard vision tests. Although certain features of visually impaired children, such as facial appearance and ocular movements, can assist ophthalmic practice, applying these features to real-world screening remains challenging. Here, we present a mobile health (mHealth) system, the smartphone-based Apollo Infant Sight (AIS), which identifies visually impaired children with any of 16 ophthalmic disorders by recording and analyzing their gazing behaviors and facial features under visual stimuli. Videos from 3,652 children (≤48 months in age; 54.5% boys) were prospectively collected to develop and validate this system. For detecting visual impairment, AIS achieved an area under the receiver operating curve (AUC) of 0.940 in an internal validation set and an AUC of 0.843 in an external validation set collected in multiple ophthalmology clinics across China. In a further test of AIS for at-home implementation by untrained parents or caregivers using their smartphones, the system was able to adapt to different testing conditions and achieved an AUC of 0.859. This mHealth system has the potential to be used by healthcare professionals, parents and caregivers for identifying young children with visual impairment across a wide range of ophthalmic disorders.

Prognostic factors of severe pneumonia in patients treated with rituximab in the intensive care unit.

OBJECTIVE: The aim of this study was to describe the clinical characteristics and prognostic factors of patients treated with rituximab (RTX) who developed severe pneumonia in the intensive care unit (ICU). METHODS: We systematically reviewed the medical records of 40 patients who received RTX and developed severe pneumonia in the ICU at our hospital from January 2009 to January 2019 to evaluate the underlying conditions, clinical course, and possible prognostic factors. RESULTS: Most patients had underlying hematologic malignancies (n = 21, 52.5%), followed by rheumatologic diseases (n = 17, 42.5%). The most frequent causative pathogens were fungi (n = 11, 27.5%), followed by bacteria (n = 9, 22.5%) and Pneumocystis jirovecii pneumonia (n = 8, 20%). Thirty patients (75%) died, and the other 10 patients (25%) survived. Compared with survivors, patients who died were significantly older (60.6 ± 10.6 vs 44.4 ± 18.3 years) and had chronic lung disease (40% vs 0%). CONCLUSION: Older age and chronic lung disease were significantly associated with mortality in patients treated with RTX.

tRF-20-S998LO9D inhibits endometrial carcinoma by upregulating SESN2.

Aim: To explore the roles of transfer RNA-derived small RNAs (tsRNAs) in endometrial carcinoma (EC). Materials & methods: tsRNA profiles for EC from TCGA were analyzed. The functions and mechanisms of tsRNA were explored using in vitro experiments. Results: 173 dysregulated tsRNAs were identified. After validating in EC tissues and serumal exosome samples from EC patients, a downregulated tsRNA in both EC tissues and serumal exosomes (i.e., tRF-20-S998LO9D) was observed. Exosomal tRF-20-S998LO9D had an area under the curve of 0.768. tRF-20-S998LO9D overexpression inhibited proliferation, migration and invasion and promoted apoptosis of EC cells and tRF-20-S998LO9D knockdown further confirmed its effects. Further analyses showed that tRF-20-S998LO9D upregulated SESN2 in protein levels. Conclusion: tRF-20-S998LO9D inhibits EC cells by upregulating SESN2.

Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung Cancer.

Background: Immune checkpoint inhibition therapy has been achieved significant success in the treatment of non-small cell lung cancer (NSCLC). However, the role of soluble immune checkpoint- related proteins in NSCLC remains obscure. Methods: We evaluated the circulating levels of 14 immune checkpoint-related proteins panel (BTLA, LAG-3, GITR, IDO, PD-L2, PD-L1, PD-1, HVEM, Tim-3, CD28, CD27, CD80, CD137 and CTLA-4) and their associations with the risk of invasive disease and the risk of NSCLC in 43 pre-invasive (AIS), 81 invasive NSCLC (IAC) patients and matched 35 healthy donors using a multiplex Luminex assay. Gene expression in tumors from TCGA were analyzed to elucidate potential mechanisms. The multivariate logistic regression model was applied in the study. ROC(receiver operator characteristic) curve and calibration curve were used in the performance evaluation. Results: We found that sCD27, sCD80, CD137 and sPDL2 levels were significantly increased in IAC cases compared to AIS cases (P= 1.05E-06, 4.44E-05, 2.30E-05 and 1.16E-06, respectively), whereas sPDL1 and sPDL2 levels were significantly increased in NSCLC cases compared to healthy controls (P=3.25E-05 and 1.49E-05, respectively). Unconditional univariate logistic regression analysis indicated that increased sCD27, sCD80, sCD137, and sPDL2 were significantly correlated with the risk of invasive diseases. The model with clinical variables, sCD27 and sPDL2 demonstrated the best performance (AUC=0.845) in predicting the risk of IAC. CD27 and PDCD1LG2 (PDL2) showed significant association with cancer invasion signature in TCGA dataset. Conclusion: Our study provides evidence that soluble immune checkpoint-related proteins may associate with the risk of IAC, and we further established an optimized multivariate predictive model, which highlights their potential application in the treatment of NSCLC patients. Future studies may apply these biomarkers to test their predictive value of survival and treatment outcome during immunotherapy in NSCLC patients.

Application of Surgical Decision Model for Patients With Childhood Cataract: A Study Based on Real World Data.

Reliable validated methods are necessary to verify the performance of diagnosis and therapy-assisted models in clinical practice. However, some validated results have research bias and may not reflect the results of real-world application. In addition, the conduct of clinical trials has executive risks for the indeterminate effectiveness of models and it is challenging to finish validated clinical trials of rare diseases. Real world data (RWD) can probably solve this problem. In our study, we collected RWD from 251 patients with a rare disease, childhood cataract (CC) and conducted a retrospective study to validate the CC surgical decision model. The consistency of the real surgical type and recommended surgical type was 94.16%. In the cataract extraction (CE) group, the model recommended the same surgical type for 84.48% of eyes, but the model advised conducting cataract extraction and primary intraocular lens implantation (CE + IOL) surgery in 15.52% of eyes, which was different from the real-world choices. In the CE + IOL group, the model recommended the same surgical type for 100% of eyes. The real-recommended matched rates were 94.22% in the eyes of bilateral patients and 90.38% in the eyes of unilateral patients. Our study is the first to apply RWD to complete a retrospective study evaluating a clinical model, and the results indicate the availability and feasibility of applying RWD in model validation and serve guidance for intelligent model evaluation for rare diseases.