Search

Abstract Background Lung injury and pulmonary fibrosis (PF), frequently arising as sequelae of severe and acute lung disease, currently face a dearth of effective therapeutic potions. Mesenchymal stem cells (MSCs) with immunomodulatory and tissue repair functions have immense potential to treat lung injury and PF. However, the optimal route of administration, timing, and frequency of dosing remain elusive. Human embryonic stem cell-derived immunity-and-matrix-regulatory cells (IMRCs) have shown therapeutic potential for lung injury and PF. Methods To ascertain the optimal therapeutic regimen for IMRCs in PF, we conducted an experimental study. Utilizing a mouse model of PF induced by bleomycin (BLM), IMRCs were administered via either a single or double intravenous (IV) or intratracheal (IT) injection on the first and seventh days post-BLM induction. Results Our findings revealed that IV infusion of IMRCs surpassed IT infusion in enhancing survival rates, facilitating body weight recovery, and optimizing Ashcroft and Szapiel scores among the model mice. Notably, IV administration exhibited a more profound ability to mitigate lung inflammation and fibrosis. Moreover, earlier and more frequent administrations of IMRCs were found to be advantageous in enhancing their therapeutic effects. Specifically, early administration with two IV infusions significantly improved body weight, lung organ coefficient, pulmonary ventilation and diffusion functions, and PF. This was accompanied by an increase in alveolar type I and II epithelial cells and a suppression of macrophage infiltration via CD24. Conclusion Collectively, these results suggested that IMRCs infusion ameliorated lung injury by promoting lung regeneration and inhibiting macrophage infiltration in a route, time, and frequency-dependent manner.

Abstract Background Patients with severe infection often require careful fluid management. Intravenous linezolid can increase the fluid volume, whereas oral linezolid can effectively limit the fluid volume. However, the differences in the treatment effect and incidence of thrombocytopenia between oral and intravenous linezolid in patients with severe infection remain unclear. Methods Patients who received linezolid in the intensive care unit of PLA General Hospital from December 2010 to December 2020 were divided into an oral group and intravenous group according to the route of administration, and we further established the PO group and PO-match group by propensity score matching. The anti-infection effect of linezolid and incidence of thrombocytopenia were compared between the two groups. Results In total, 177 patients were enrolled in the study (59 in PO group and 118 in PO-match group). The microbial clearance rate and clinical cure rate were similar between the two groups (70.0% vs. 79.3%, P = 0.293; 72.9% vs. 83.9%, P = 0.213). The 30-day mortality rate was slightly higher in the PO group than in the PO-match group, but the difference was not statistically significant (13.6% vs. 6.8%, P = 0.138). There was no difference in the incidence of thrombocytopenia between the two groups (62.7% vs. 65.3%, P = 0.739). Conclusions There were no significant differences in the treatment effect or incidence of thrombocytopenia between oral and intravenous administration of linezolid in patients with severe infection.

Abstract Background Dysfunction or deficiency of corneal epithelium results in vision impairment or blindness in severe cases. The rapid and effective regeneration of corneal epithelial cells relies on the limbal stem cells (LSCs). However, the molecular and functional responses of LSCs and their niche cells to injury remain elusive. Methods Single-cell RNA sequencing was performed on corneal tissues from normal mice and corneal epithelium defect models. Bioinformatics analysis was performed to confirm the distinct characteristics and cell fates of LSCs. Knockdown of Creb5 and OSM treatment experiment were performed to determine their roles of in corneal epithelial wound healing. Results Our data defined the molecular signatures of LSCs and reconstructed the pseudotime trajectory of corneal epithelial cells. Gene network analyses characterized transcriptional landmarks that potentially regulate LSC dynamics, and identified a transcription factor Creb5, that was expressed in LSCs and significantly upregulated after injury. Loss-of-function experiments revealed that silencing Creb5 delayed the corneal epithelial healing and LSC mobilization. Through cell–cell communication analysis, we identified 609 candidate regeneration-associated ligand-receptor interaction pairs between LSCs and distinct niche cells, and discovered a unique subset of Arg1 + macrophages infiltrated after injury, which were present as the source of Oncostatin M (OSM), an IL-6 family cytokine, that were demonstrated to effectively accelerate the corneal epithelial wound healing. Conclusions This research provides a valuable single-cell resource and reference for the discovery of mechanisms and potential clinical interventions aimed at ocular surface reconstruction.

Abstract Background Sleep deprivation (SD) is a common public health problem that contributes to various physiological disorders and increases the risk of ocular diseases. However, whether sleep loss can damage corneal endothelial function remains unclear. This study aimed to determine the effect and possible mechanism of SD on the corneal endothelium. Methods Male C57BL/6J mice were subjected to establish SD models. After 10 days, quantitative RT-PCR (qRT-PCR) and western blot or immunostaining for the expression levels of zonula occludens-1 (ZO-1), ATPase Na+/K + transporting subunit alpha 1 (Atp1a1), and core clock genes in the corneal endothelium were evaluated. Reactive oxygen species staining and mitochondrial abundance characterized the mitochondrial function. The regulatory role of Bmal1 was confirmed by specifically knocking down or overexpressing basic helix-loop-helix ARNT like 1 protein (Bmal1) in vivo. In vitro, a mitochondrial stress test was conducted on cultured human corneal endothelial cells upon Bmal1 knockdown. Results SD damaged the barrier and pump functions of mouse corneal endothelium, accompanied by mitochondrial dysfunction. Interestingly, SD dramatically downregulated the core clock gene Bmal1 expression level. Bmal1 knockdown disrupted corneal endothelial function, while overexpression of Bmal1 ameliorated the dysfunction induced by SD. Mitochondrial bioenergetic deficiency mediated by Bmal1 was an underlying mechanism for SD induced corneal endothelial dysfunction. Conclusion The downregulation of Bmal1 expression caused by SD led to corneal endothelial dysfunction via impairing mitochondrial bioenergetics. Our findings offered insight into how SD impairs the physiological function of the corneal endothelium and expanded the understanding of sleep loss leading to ocular diseases.

Abstract Sepsis is a dysregulated host response to severe infections, and immune dysfunction plays a crucial role in its pathogenesis. Elderly patients, a special population influenced by immunosenescence, are more susceptible to sepsis and have a worse prognosis. However, the immunopathogenic mechanisms underlying sepsis in elderly patients remain unclear. Here, we performed single-cell RNA sequencing of peripheral blood samples from young and old subjects and patients with sepsis. By exploring the transcriptional profiles of immune cells, we analyzed immune cell compositions, phenotype shifts, expression heterogeneities, and intercellular communication. In elderly patients with sepsis, innate immune cells (e.g., monocytes and DCs) exhibit decreased antigen presentation, presenting an overactive inflammatory and senescent phenotype. However, the immunophenotype of T cells shifted to characterize effector, memory, and exhaustion. Moreover, we identified strong interferon-γ responses of T cells in both aging and sepsis groups and a deranged inflammaging status in elderly sepsis patients. Tregs in elderly patients with sepsis showed increased abundance and enhanced immunosuppressive effects. In addition, metabolism-associated pathways were upregulated in T cells in elderly patients with sepsis, and the lysine metabolism pathway was enriched in Tregs. Cell–cell interaction analysis showed that the expression profile of ligand-receptor pairs was probably associated with aggravated immune dysfunction in elderly patients with sepsis. A novel HLA-KIR interaction was observed between Tregs and CD8 + T cells. These findings illustrate the immunological hallmarks of sepsis in elderly patients, and highlight that immunosuppressive and metabolic regulatory pathways may undergo important alterations in elderly patients with sepsis.

Abstract Microbiological Rapid On-Site Evaluation (M-ROSE) is based on smear staining and microscopic observation, providing critical references for the diagnosis and treatment of pulmonary infectious disease. Automatic identification of pathogens is the key to improving the quality and speed of M-ROSE. Recent advancements in deep learning have yielded numerous identification algorithms and datasets. However, most studies focus on artificially cultured bacteria and lack clinical data and algorithms. Therefore, we collected Gram-stained bacteria images from lower respiratory tract specimens of patients with lung infections in Chinese PLA General Hospital obtained by M-ROSE from 2018 to 2022 and desensitized images to produce 1705 images (4,912 × 3,684 pixels). A total of 4,833 cocci and 6,991 bacilli were manually labelled and differentiated into negative and positive. In addition, we applied the detection and segmentation networks for benchmark testing. Data and benchmark algorithms we provided that may benefit the study of automated bacterial identification in clinical specimens.

Abstract Background Many older adult patients receive low-dose teicoplanin with varied regimens, leading to a lack of clarity on its optimal regimens and toxicity profiles in China. This study aimed to clarify these aspects by analyzing teicoplanin treatment concentrations and toxicities. Methods We included older adult patients administered teicoplanin at four tertiary hospitals in Beijing from June 2021 to July 2023, targeting a trough concentration (Cmin) ≥ 10 mg/L. Teicoplanin concentrations and toxicities were monitored dynamically. Results From 204 patients, we obtained 632 teicoplanin concentrations. Most patients (83.3%) received low-dose regimens. Suboptimal concentrations were found in 66.4% of patients within 7 days of treatment and 17.0% after 15 days. Cmin gradually increased with treatment duration and was influenced initially by creatinine and by both body weight and creatinine from days 8 to 14. The target concentration was achieved in 53.1%, 33.9%, 15.6%, and 5.5% of patients at 3, ≤ 7, 8–14, and ≥ 15 days after withdrawal, respectively. Slow elimination was associated with average Cmin and eGFR. Nephrotoxicity, hepatotoxicity, and thrombocytopenia occurred in 12.5%, 4.1%, and 31.5% of patients, respectively, without significant differences between concentrations. Conclusions Most older adult patients were underdosed, indicating a need for dose adjustment. Given the varied risk factors for suboptimal concentrations in different treatment stages, a one-size-fits-all regimen was ineffective. We recommend an initial dose of 400 mg at 12-h intervals for the first three days, with subsequent doses from days 4 to 14 adjusted based on creatinine and body weight; after day 14, a maintenance dose of 200 mg daily is advised. Trial registration ChiCTR2100046811; 28/05/2021.

Background The proliferation of smart devices provides the possibility of early detection of the signs of pulmonary infections (PI) . This study validates a smartwatch-based algorithm to monitor the risk of PI in adults. Methods An algorithm that runs on smartwatches was developed and tested in 87 patients with PI and 408 healthy subjects. The algorithm examines heart rate variability, respiratory rate, oxygen saturation, body temperature, and cough sound. It was embedded into the Respiratory Health Study app for a smartwatch to detect the risk of PI and was further validated in the hospital. Doctors diagnosed PI using a clinical evaluation, lab tests, and imaging examination, the gold standard for diagnosis. The accuracy, sensitivity, and specificity of the algorithm predicting PI were evaluated. Results In all, 80 patients with PI and 85 healthy volunteers were recruited to validate the accuracy of the algorithm. The area under the curve of the algorithm for predicting PI was 0.86 (95% confidence interval: 0.82–0.91) ( P

IntroductionImmunosuppression is the main cause of the high mortality rate in patients with sepsis. The decrease in the number and dysfunction of CD4+ T lymphocytes is crucial to the immunosuppressed state of sepsis, in turn affecting the development and prognosis of sepsis. Autophagy has been shown to play an important role in the immune imbalance exhibited during sepsis.MethodsIn this study, we modulate the expression of miR-223 in CD4+ T lymphocytes, via the transfection of a mimic or an inhibitor of miR-223 to establish cell models of miR-223 overexpression and knockdown, respectively. Levels of autophagy were monitored using a double-labeled lentivirus (mRFP-GFP-LC3) and electron microscopy, and western blot analysis was used to estimate the levels of autophagy-related proteins and FOXO1 in the two cell models after co-treatment with lipopolysaccharide (LPS) and siRNA against FOXO1.ResultsWe found that when the expression of miR-223 increased, FOXO1 expression decreased and autophagy decreased; whereas, when FOXO1 expression was inhibited, autophagy decreased significantly in different cell models after LPS induction.ConclusionThus, this study proved that miR-223 participate in the regulation of LPS-induced autophagy via the regulation of FOXO1 expression in CD4+ T lymphocytes which shed a new light for the diagnosis and treatment of sepsis.

Abstract Background Although studies have demonstrated the value of the triglyceride–glucose (TyG) index for cardiovascular disease (CVD) and cardiovascular mortality, however, few studies have shown that the TyG index is associated with all-cause or CVD mortality in young patients with diabetes. This study aimed to investigate the association between the TyG index and all-cause and CVD mortality in young patients with diabetes in the United States. Methods Our study recruited 2440 young patients with diabetes from the National Health and Nutrition Examination Survey (NHANES) 2001–2018. Mortality outcomes were determined by linking to National Death Index (NDI) records up to December 31, 2019. Cox regression modeling was used to investigate the association between TyG index and mortality in young patients with diabetes. The nonlinear association between TyG index and mortality was analyzed using restricted cubic splines (RCS), and a two-segment Cox proportional risk model was constructed for both sides of the inflection point. Results During a median follow-up period of 8.2 years, 332 deaths from all causes and 82 deaths from cardiovascular disease were observed. Based on the RCS, the TyG index was found to have a U-shaped association with all-cause and CVD mortality in young patients with diabetes, with threshold values of 9.18 and 9.16, respectively. When the TyG index was below the threshold value (TyG index

Abstract Background Predicting patient mortality risk facilitates early intervention in intensive care unit (ICU) patients at greater risk of disease progression. This study applies machine learning methods to multidimensional clinical data to dynamically predict mortality risk in ICU patients. Methods A total of 33,798 patients in the MIMIC-III database were collected. An integrated model NIMRF (Network Integrating Memory Module and Random Forest) based on multidimensional variables such as vital sign variables and laboratory variables was developed to predict the risk of death for ICU patients in four non overlapping time windows of 0–1 h, 1–3 h, 3–6 h, and 6–12 h. Mortality risk in four nonoverlapping time windows of 12 h was externally validated on data from 889 patients in the respiratory critical care unit of the Chinese PLA General Hospital and compared with LSTM, random forest and time-dependent cox regression model (survival analysis) methods. We also interpret the developed model to obtain important factors for predicting mortality risk across time windows. The code can be found in https://github.com/wyuexiao/NIMRF . Results The NIMRF model developed in this study could predict the risk of death in four nonoverlapping time windows (0–1 h, 1–3 h, 3–6 h, 6–12 h) after any time point in ICU patients, and in internal data validation, it is suggested that the model is more accurate than LSTM, random forest prediction and time-dependent cox regression model (area under receiver operating characteristic curve, or AUC, 0–1 h: 0.8015 [95% CI 0.7725–0.8304] vs. 0.7144 [95%] CI 0.6824–0.7464] vs. 0.7606 [95% CI 0.7300–0.7913] vs 0.3867 [95% CI 0.3573–0.4161]; 1–3 h: 0.7100 [95% CI 0.6777–0.7423] vs. 0.6389 [95% CI 0.6055–0.6723] vs. 0.6992 [95% CI 0.6667–0.7318] vs 0.3854 [95% CI 0.3559–0.4150]; 3–6 h: 0.6760 [95% CI 0.6425–0.7097] vs. 0.5964 [95% CI 0.5622–0.6306] vs. 0.6760 [95% CI 0.6427–0.7099] vs 0.3967 [95% CI 0.3662–0.4271]; 6–12 h: 0.6380 [0.6031–0.6729] vs. 0.6032 [0.5705–0.6406] vs. 0.6055 [0.5682–0.6383] vs 0.4023 [95% CI 0.3709–0.4337]). External validation was performed on the data of patients in the respiratory critical care unit of the Chinese PLA General Hospital. Compared with LSTM, random forest and time-dependent cox regression model, the NIMRF model was still the best, with an AUC of 0.9366 [95% CI 0.9157–0.9575 for predicting death risk in 0–1 h]. The corresponding AUCs of LSTM, random forest and time-dependent cox regression model were 0.9263 [95% CI 0.9039–0.9486], 0.7437 [95% CI 0.7083–0.7791] and 0.2447 [95% CI 0.2202–0.2692], respectively. Interpretation of the model revealed that vital signs (systolic blood pressure, heart rate, diastolic blood pressure, respiratory rate, and body temperature) were highly correlated with events of death. Conclusion Using the NIMRF model can integrate ICU multidimensional variable data, especially vital sign variable data, to accurately predict the death events of ICU patients. These predictions can assist clinicians in choosing more timely and precise treatment methods and interventions and, more importantly, can reduce invasive procedures and save medical costs.

AbstractBackground The effectiveness of nirmatrelvir–ritonavir has mainly been shown in non-hospitalized patients with mild-to-moderate coronavirus disease 2019 (COVID-19). The real-world effectiveness of nirmatrelvir-ritonavir urgently needs to be determined using representative in-hospital patients with COVID-19 during the Omicron wave of the pandemic.Methods We performed a multicentre, retrospective study in five Chinese PLA General Hospital medical centers in Beijing, China. Patients hospitalized with COVID-19 from 10 December 2022 to 20 February 2023 were eligible for inclusion. A 1:1 propensity score matching was performed between the nirmatrelvir-ritonavir group and the control group.Results 1010 recipients of nirmatrelvir-ritonavir and 1010 matched controls were finally analyzed after matching. Compared with matched controls, the nirmatrelvir-ritonavir group had a lower incidence rate of all-cause death (4.6/1000 vs. 6.3/1000 person-days, p = 0.013) and a higher incidence rate of clinical improvement (47.6/1000 vs. 45.8/1000 person-days, p = 0.012). Nirmatrelvir-ritonavir was associated with a 22% lower all-cause mortality and a 14% higher incidence of clinical improvement. Initiation of nirmatrelvir-ritonavir within 5 days after symptom onset was associated with a 50% lower mortality and a 26% higher clinical improvement rate. By contrast, no significant associations were identified among patients receiving nirmatrelvir-ritonavir treatment more than 5 days after symptom onset. Nirmatrelvir-ritonavir was also associated with a 50% increase in survival days and a 12% decrease in days to clinical improvement.Conclusion Among hospitalized patients with COVID-19 during the Omicron wave in Beijing, China, the early initiation of nirmatrelvir-ritonavir was associated with clinical benefits of lowering mortality and improving clinical recovery.

BackgroundKlebsiella pneumoniae is a major cause of hospital-acquired infections (HAIs), primarily spread through environmental contamination in hospitals. The effectiveness of current chemical disinfectants is waning due to emerging resistance, which poses environmental hazards and fosters new resistance in pathogens. Developing environmentally friendly and effective disinfectants against multidrug-resistant organisms is increasingly important.MethodsThis study developed a bacteriophage cocktail targeting two common carbapenem-resistant Klebsiella pneumoniae (CRKP) strains, ST11 KL47 and ST11 KL64. The cocktail was used as an adjunctive disinfectant in a hospital’s respiratory intensive care unit (RICU) via ultrasonic nebulization. Digital PCR was used to quantify CRKP levels post-intervention. The microbial community composition was analyzed via 16S rRNA sequencing to assess the intervention’s impact on overall diversity.ResultsThe phage cocktail significantly reduced CRKP levels within the first 24 hours post-treatment. While a slight increase in pathogen levels was observed after 24 hours, they remained significantly lower than those treated with conventional disinfectants. 16S rRNA sequencing showed a decrease in the target pathogens’ relative abundance, while overall species diversity remained stable, confirming that phages selectively target CRKP without disrupting ecological balance.DiscussionThe findings highlight the efficacy and safety of phage-based biocleaners as a sustainable alternative to conventional disinfectants. Phages selectively reduce multidrug-resistant pathogens while preserving microbial diversity, making them a promising tool for infection control.

Abstract Background and aim Two oral antivirals (Nirmatrelvir- ritonavir and Azvudine) are widely used in China practice during the Omicron wave of the pandemic. However, little evidence regarding the real-world effectiveness of these two oral antivirals in in-hospital patients. We aimed to evaluate the clinical effectiveness of nirmatrelvir-ritonavir versus azvudine among adult hospitalized patients with COVID-19. Methods This retrospective cohort study used data from three Chinese PLA General Hospital medical centres. Hospitalized patients with COVID-19 treated with azvudine or nirmatrelvir-ritonavir from Dec 10, 2022, to February 20, 2023, and did not require invasive ventilation support on admission were eligible for inclusion. Results After exclusions and propensity-score matching, the final analysis included 486 azvudine recipients and 486 nirmatrelvir-ritonavir recipients. By 28 days of initiation of the antivirus treatment, the crude incidence rate of all-cause death was similar in both types of antivirus treatment (nirmatrelvir-ritonavir group 2.8 events 1000 person-days [95% CI, 2.1–3.6] vs azvudine group 3.4 events/1000 person-days [95% CI, 2.6–4.3], P = 0.38). Landmark analysis showed that all-cause death was lower in the nirmatrelvir-ritonavir (3.5%) group than the azvudine (6.8%, P = 0.029) within the initial 10-day admission period, while no significant difference was observed for results between 10 and 28 days follow-up. There was no significant difference between the nirmatrelvir-ritonavir group and the azvudine group in cumulative incidence of the composite disease progression event (8.6% with nirmatrelvir-ritonavir vs. 10.1% with azvudine, HR, 1.22; 95% CI 0.80–1.86, P = 0.43). Conclusion Among patients hospitalized with COVID-19 during the omicron wave in Beijing, similar in-hospital clinical outcomes on 28 days were observed between patients receiving nirmatrelvir-ritonavir and azvudine. However, it is worth noticing that nirmatrelvir-ritonavir appears to hold an advantage over azvudine in reducing early mortality. Further randomized controlled trials are needed to verify the efficacy of those two antivirus medications especially in early treatment.

The separation of a toluene/methanol/water ternary mixture is a difficult task due to the toluene/water and toluene/methanol azeotropes. In this article, low-energy pervaporation is proposed for the separation of the ternary azeotrope toluene–methanol–water. This work investigates the effects of feed temperature, feed flow rate, and vacuum on pervaporation and compares the energy consumption of pervaporation with that of distillation. The results showed that at the optimized flow rate of 50 L/h and a permeate side vacuum of 60 kPa at 50 °C, the water and methanol content in the permeate was about 63.2 wt.% and 36.8 wt.%, respectively, the water/ methanol separation factor was 24.04, the permeate flux was 510.7 g/m2·h, the water content in the feed out was reduced from 2.5 wt.% to less than 0.66 wt.%, and the dehydration of toluene methanol could be realized. Without taking into account the energy consumption of pumps and other power equipment, pervaporation requires an energy consumption of 43.53 kW·h to treat 1 ton of raw material, while the energy consumption of distillation to treat 1 ton of raw material is about 261.5 kW·h. Compared to the existing distillation process, the pervaporation process consumes much less energy (about one-sixth of the energy consumption of distillation). There is almost no effect on the surface morphology and chemical composition of the membrane before and after use. The method provides an effective reference for the dehydration of organic solvents from ternary mixtures containing toluene/methanol/water.

Abstract Background The emergence of COVID-19 and the implementation of preventive measures and behavioral changes have led to a significant decrease in the prevalence of other respiratory viruses. However, the manner in which seasonal viruses will reemerge in the absence of COVID-19-related restrictions remains unknown. Methods Patients presenting with influenza-like illness in two hospitals in Beijing were subjected to testing for COVID-19, influenza A, and influenza B to determine the causative agent for viral infections. The prevalence of influenza B across China was confirmed using data from the Centers for Disease Control, China (China CDC). Clinical characteristics, laboratory findings, imaging results, and mortality data were collected for a cohort of 70 hospitalized patients with confirmed influenza B from 9 hospitals across China. Results Starting from October 2021, a substantial increase in the number of patients visiting the designated fever clinics in Beijing was observed, with this trend continuing until January 2022. COVID-19 tests conducted on these patients yielded negative results, while the positivity rate for influenza rose from approximately 8% in October 2021 to over 40% by late January 2022. The cases started to decline after this peak. Data from China CDC confirmed that influenza B is a major pathogen during the season. Sequencing of the viral strain revealed the presence of the Victoria-like lineage of the influenza B strain, with minor variations from the Florida/39/2018 strain. Analysis of the hospitalized patients' characteristics indicated that severe cases were relatively more prevalent among younger individuals, with an average age of 40.9 ± 24.1 years. Among the seven patients who succumbed to influenza, the average age was 30 ± 30.1 years. These patients exhibited secondary infections involving either bacterial or fungal pathogens and displayed elevated levels of cell death markers (such as LDH) and coagulation pathway markers (D-dimer). Conclusion Influenza B represents a significant infection threat and can lead to substantial morbidity and mortality, particularly among young patients. To mitigate morbidity and mortality rates, it is imperative to implement appropriate vaccination and other preventive strategies.

Abstract Introduction The mortality rate of hospitalized patients with severe hospital-acquired pneumonia (SHAP) remains high. Empirical broad-spectrum antibiotic coverage and the misuse of high-grade antibiotics could lead to the emergence of multi-drug and even pandrug-resistant bacteria. In addition to metagenomic next-generation sequencing (mNGS), microbiological rapid on-site evaluation (M-ROSE) might be a useful technique to identify the pathogens in the early stage; however, the effect of M-ROSE guiding anti-infection treatment on prognostic outcomes of SHAP patients is still unclear. Methods/design This is a multicenter, single-blind, prospective, randomized controlled trial to evaluate the effect of M-ROSE guiding anti-infection treatment in SHAP patients, which will provide new strategies for the prevention and control of clinical multi-drug resistance bacteria. A total of 166 patients with SHAP, aged 18 years and over, will be recruited from seven centers in Beijing and randomly assigned to the intervention group (M-ROSE combined with mNGS) or the control group (mNGS only) in a 1:1 ratio using the central randomization system. Patients in the intervention group will accept M-ROSE and mNGS analysis, and the control group will accept mNGS analysis. Individualized anti-infective treatment and routine treatment will be selected according to the analysis results. The primary outcome is the ICU outcome (mortality). The safety of the intervention measures will be evaluated during the entire trial period. This trial will be the first randomized controlled trial to evaluate the effect of M-ROSE guiding treatment on mortality in patients with SHAP and may change the prevalence of multi-drug resistant bacteria. Ethics and dissemination This trial adheres to the Declaration of Helsinki and guidelines of Good Clinical Practice. Signed informed consent will be obtained from all participants. The trial has been approved by the Chinese PLA General Hospital (Approval Number: 20220322001). Trial registration ClinicalTrials.gov NCT05300776. Registered on 25 March 2022.

Background: Linezolid-associated thrombocytopenia (LAT) leads to drug withdrawal associated with a poor prognosis. Some risk factors for LAT have been identified; however, the sample size of previous studies was small, data from elderly individuals are limited, and a simple risk score scale was not established to predict LAT at an early stage, making it difficult to identify and intervene in LAT at an early stage. Methods: In this single-center retrospective case-control study, we enrolled elderly patients treated with linezolid in the intensive care unit from January 2015 to December 2020. All the data of enrolled patients, including demographic information and laboratory findings at baseline, were collected. We analyzed the incidence and risk factors for LAT and established a nomogram risk prediction model for LAT in the elderly population. Results: A total of 428 elderly patients were enrolled, and the incidence of LAT was 35.5% (152/428). Age ≥80 years old (OR=1.980; 95% CI: 1.179–3.325; P=0.010), duration of linezolid ≥ 10 days (OR=1.100; 95% CI: 1.050–1.152; P 150 was defined as high risk, and the probability of LAT was >67.5%. Conclusions: We created the ADPLCP risk score scale to predict the occurrence of LAT in elderly individuals. ADPLCP is simple and feasible and is helpful for the early determination of LAT to guide drug withdrawal or early intervention.

Abstract The lung immune response consists of various cells involved in both innate and adaptive immune processes. Innate immunity participates in immune resistance in a nonspecific manner, whereas adaptive immunity effectively eliminates pathogens through specific recognition. It was previously believed that adaptive immune memory plays a leading role during secondary infections; however, innate immunity is also involved in immune memory. Trained immunity refers to the long‐term functional reprogramming of innate immune cells caused by the first infection, which alters the immune response during the second challenge. Tissue resilience limits the tissue damage caused by infection by controlling excessive inflammation and promoting tissue repair. In this review, we summarize the impact of host immunity on the pathophysiological processes of pulmonary infections and discuss the latest progress in this regard. In addition to the factors influencing pathogenic microorganisms, we emphasize the importance of the host response.

ABSTRACTAcinetobacter baumannii is a major opportunistic pathogen causing hospital-acquired infections, and it is imperative to comprehend its evolutionary and epidemiological dynamics in hospitals to prevent and control nosocomial transmission. Here, we present a comprehensive genomic epidemiological study involving the genomic sequencing and antibiotic resistance profiling of 634 A. baumannii strains isolated from seven intensive care units (ICUs) of a Chinese general hospital over 2 consecutive years. Our study reveals that ST2 is highly dominant (90.54%) in the ICUs, with 98.90% of the ST2 exhibiting multidrug resistant or extensively drug resistant. Phylogenetic analyses of newly sequenced genomes and public data suggest that nosocomial isolates originated outside the hospital but evolved inside. The major lineages appear to be stable, with 9 of the 28 identified nosocomial epidemic clones infecting over 60% of the affected patients. However, outbreaks of two highly evolved clones have been observed in different hospitals, suggesting significant inter-hospital transmission chains. By coupling patient medical records and genomic divergence of the ST2, we found that cross-ward patient transfer played a crucial role in pathogen’s nosocomial transmission. Additionally, we identified 831 potential adaptive evolutionary loci and 44 associated genes by grouping and comparing the genomes of clones with different prevalence. Overall, our study provides a comprehensive and contemporary survey on the epidemiology and genomic evolution of A. baumannii in a large Chinese general hospital. These findings shed light on the nosocomial evolution and transmission of A. baumannii and offers valuable information for transmission prevention and antibiotic therapy.IMPORTANCEThis study delved into the genomic evolution and transmission of nosocomial Acinetobacter baumannii on a large scale, spanning both an extended time period and the largest sample size to date. Through molecular epidemiological investigations based on genomics, we can directly trace the origin of the pathogen, detecting and monitoring outbreaks of infectious diseases in a timely manner, and ensuring public health safety. In addition, this study also collects a large amount of genomic and antibiotic resistance detection data, which is helpful for phenotype prediction based on genomic sequencing. It enables patients to receive personalized antibiotic treatment quickly, helps doctors select antibiotics more accurately, and contributes to reducing the use of antibiotics and lowering the risk of antibiotic resistance development.

Problem: Chest radiography is a crucial tool for diagnosing thoracic disorders, but interpretation errors and a lack of qualified practitioners can cause delays in treatment. Aim: This study aimed to develop a reliable multi-classification artificial intelligence (AI) tool to improve the accuracy and efficiency of chest radiograph diagnosis. Methods: We developed a convolutional neural network (CNN) capable of distinguishing among 26 thoracic diagnoses. The model was trained and externally validated using 795,055 chest radiographs from 13 datasets across 4 countries. Results: The CNN model achieved an average area under the curve (AUC) of 0.961 across all 26 diagnoses in the testing set. COVID-19 detection achieved perfect accuracy (AUC 1.000, [95% confidence interval {CI}, 1.000 to 1.000]), while effusion or pleural effusion detection showed the lowest accuracy (AUC 0.8453, [95% CI, 0.8417 to 0.8489]). In external validation, the model demonstrated strong reproducibility and generalizability within the local dataset, achieving an AUC of 0.9634 for lung opacity detection (95% CI, 0.9423 to 0.9702). The CNN outperformed both radiologists and nonradiological physicians, particularly in trans-device image recognition. Even for diseases not specifically trained on, such as aortic dissection, the AI model showed considerable scalability and enhanced diagnostic accuracy for physicians of varying experience levels (all P < 0.05). Additionally, our model exhibited no gender bias (P > 0.05). Conclusion: The developed AI algorithm, now available as professional web-based software, substantively improves chest radiograph interpretation. This research advances medical imaging and offers substantial diagnostic support in clinical settings.

AbstractObjective To explore a machine learning model for the early prediction of acute kidney injury (AKI) and to screen the related factors affecting new-onset AKI in the ICU.Methods A retrospective analysis was performed used the MIMIC-III data source. New onset of AKI defined based on the serum creatinine changed. We included 19 variables for AKI assessment using four machine learning models: support vector machines, logistic regression, and random forest. and XGBoost, using accuracy, specificity, precision, recall, F1 score, and AUROC (area under the ROC curve) to evaluate model performance. The four models predicted new-onset AKI 3–6–9–12 h ahead. The SHapley Additive exPlanation (SHAP) value is used to evaluate the feature importance of the model.Results We finally respectively extracted 1130 AKI patients and non-AKI patients from the MIMIC-III database. With the extension of the early warning time, the prediction performance of each model showed a downward trend, but the relative performance was consistent. The prediction performance comparison of the four models showed that the XGBoost model performed the best in all evaluation indicators in all the time point at new-onset AKI 3–6–9–12 h ahead (accuracy 0.809 vs 0.78 vs 0.744 vs 0.741, specificity 0.856 vs 0.826 vs 0.797 vs 0.787, precision 0.842 vs 0.81 vs 0.775 vs 0.766, recall 0.759 vs 0.734 vs 0.692 vs 0.694, Fl score 0.799 vs 0.769 vs 0.731 vs 0.729, AUROC 0.892 vs 0.857 vs 0.827 vs 0.818). In the prediction of AKI 6, 9 and 12 h ahead, the importance of creatinine, platelets, and height was the most important based on SHapley.Conclusions The machine learning model described in this study can predict AKI 3–6–9–12 h before the new-onset of AKI in ICU. In particular, platelet plays an important role.Key messageThe new-onset of AKI in ICU is a common and important problem, which early be identified the risk of AKI can improve patients’ outcomes.We explored MIMIC-III and determined the exact time point of occurrence of AKI as the basis for the new-onset of AKI in ICU.XGBoost model performed the best prediction in all the time point at new-onset AKI 3–6–9–12 h ahead.For patients with the new-onset of AKI in ICU, platelets become an important factor associated with AKI.

Abstract Background Multiple organ dysfunction syndrome (MODS) is one of the leading causes of death in critically ill patients. MODS is the result of a dysregulated inflammatory response that can be triggered by various causes. Owing to the lack of an effective treatment for patients with MODS, early identification and intervention are the most effective strategies. Therefore, we have developed a variety of early warning models whose prediction results can be interpreted by Kernel SHapley Additive exPlanations (Kernel-SHAP) and reversed by diverse counterfactual explanations (DiCE). So we can predict the probability of MODS 12 h in advance, quantify the risk factors, and automatically recommend relevant interventions. Methods We used various machine learning algorithms to complete the early risk assessment of MODS, and used a stacked ensemble to improve the prediction performance. The kernel-SHAP algorithm was used to quantify the positive and minus factors corresponding to the individual prediction results, and finally, the DiCE method was used to automatically recommend interventions. We completed the model training and testing based on the MIMIC-III and MIMIC-IV databases, in which the sample features in the model training included the patients’ vital signs, laboratory test results, test reports, and data related to the use of ventilators. Results The customizable model called SuperLearner, which integrated multiple machine learning algorithms, had the highest authenticity of screening, and its Yordon index (YI), sensitivity, accuracy, and utility_score on the MIMIC-IV test set were 0.813, 0.884, 0.893, and 0.763, respectively, which were all maximum values of eleven models. The area under the curve of the deep–wide neural network (DWNN) model on the MIMIC-IV test set was 0.960, and the specificity was 0.935, which were both the maximum values of all these models. The Kernel-SHAP algorithm combined with SuperLearner was used to determine the minimum value of glasgow coma scale (GCS) in the current hour (OR = 0.609, 95% CI 0.606–0.612), maximum value of MODS score corresponding to GCS in the past 24 h (OR = 2.632, 95% CI 2.588–2.676), and maximum score of MODS corresponding to creatinine in the past 24 h (OR = 3.281, 95% CI 3.267–3.295) were generally the most influential factors. Conclusion The MODS early warning model based on machine learning algorithms has considerable application value, and the prediction efficiency of SuperLearner is superior to those of SubSuperLearner, DWNN, and other eight common machine learning models. Considering that the attribution analysis of Kernel-SHAP is a static analysis of the prediction results, we introduce the DiCE algorithm to automatically recommend counterfactuals to reverse the prediction results, which will be an important step towards the practical application of automatic MODS early intervention.

The removal of dissolved organic matter (DOM) from seawater before the reverse osmosis (RO) processes is crucial for alleviating organic fouling of RO membranes. However, research is still insufficiently developed in the comparison of the effectiveness of integrating coagulation with ultrafiltration (UF) or sand filtration (SF) in the pretreatment stage of seawater reverse osmosis (SWRO) for the removal of DOM. In this study, we investigated the effect of pretreatment technologies on RO fouling caused by DOM in seawater, including the integration of coagulation and sand filtration (C-S pretreatment) and the integration of coagulation and ultrafiltration (C-U pretreatment). Both integrated pretreatments achieved comparable DOM removal rates (70.2% for C-U and 69.6% for C-S), and C-S exhibited enhanced removal of UV-absorbing compounds. Although C-U was more proficient in reducing the silt density index (below 2) compared to C-S (above 3) and improved the elimination of humic acid-like organics, it left a higher proportion of tyrosine-protein-like organics, soluble microbial by-product-like organics, and finer organics in the effluent, leading to the formation of a dense cake layer on RO membrane and a higher flux decline. Therefore, suitable technologies should be selected according to specific water conditions to efficiently mitigate RO membrane fouling.

Two-stage reverse osmosis (RO) processes with intermediate concentrate demineralization (ICD) provide an efficient strategy to treat brines with high CaSO4 contents and reduce concentrate discharge. In this paper, an SRO concentrate is treated using ICD to remove CaSO4 and then mixed with a PRO concentrate for further desalination in SRO, thereby reducing the discharge of the concentrate. We investigate the selection and degradation of scale inhibitors, as well as seeded precipitation in the two-stage RO process with ICD, to achieve a high water recovery rate. A scale inhibitor is added to restrain CaSO4 crystallization on the membrane surface, and the optimized scale inhibitor, RO-400, is found to inhibit calcium sulfate scaling effectively across a wide range of the saturation index of gypsum (SIg) from 2.3 to 6. Under the optimized parameters of 40 W UV light and 70 mg/L H2O2, UV/H2O2 can degrade RO-400 completely in 15 min to destroy the scale inhibitor in the SRO concentrate. After scale inhibitor degradation, the SRO concentrate is desaturated by seeded precipitation, and the reaction degree of CaSO4 reaches 97.12%, leading to a concentrate with a low SIg (1.07) for cyclic desalination. Three UVD-GSP cycle tests show that the reused gypsum seeds can also ensure the effect of the CaSO4 precipitation process. This paper provides a combined UVD-GSP strategy in two-stage RO processes to improve the water recovery rate for CaSO4-contained concentrate.

Abstract Idiopathic pulmonary fibrosis (IPF) is a fatal interstitial lung disease characterized by chronic, progressive, and fibrotic lung injury. Although remarkable progress has been made toward understanding the pathogenesis of PF, finding more effective treatments for this fatal disease remains a challenge. In this study, we describe an innovative macrophage‐based approach to deliver anti‐fibrotic protein to the lung and inhibit PF in a mouse model of bleomycin (BLM)‐induced lung injury. We engineered macrophages to continuously secrete three types of proteins: interleukin‐10, which prevents inflammation; TGFRcFc, a soluble truncated TGF‐βR2 that blocks TGF‐β; and CD147, which induces matrix metalloproteinases (MMPs) and causes collagen degradation. Infusing these engineered macrophages into the lungs of BLM‐induced PF mouse models in an optimal pattern significantly ameliorated PF in mice. Specifically, the most effective therapeutic outcome was achieved by infusing IL‐10‐secreting macrophages on day 1, followed by TGFRcFc‐secreting macrophages on day 7 and CD147‐secreting macrophages on day 14 into the same mice after BLM treatment. Our data suggest that macrophage‐based delivery of anti‐fibrotic proteins to the lungs is a promising therapy for fibrotic lung disorders.

The therapeutic efficacy of umbilical cord mesenchymal stem cells (UCMSCs) in acute respiratory distress syndrome (ARDS) is mainly limited by the efficiency of homing of UCMSCs toward tissue damage. C-X-C chemokine receptor type 7 (CXCR7), which is involved in the mobilization of UCMSCs, is only expressed on the surface of a small proportion of UCMSCs. This study examined whether overexpression of CXCR7 in UCMSCs (UCMSCsOE-CXCR7) could improve their homing efficiency, and therefore, improve their effectiveness in fibrosis repair at the site of lung injury caused by ARDS. A lentiviral vector expressing CXCR7 was built and then transfect into UCMSCs. The impacts of CXCR7 expression of the proliferationand homing of UCMSCs were examined in a lipopolysaccharide-induced ARDS mouse model. The potential role and underlying mechanism of CXCR7 were examined by performing scratch assays, transwell assays, and immunoassays. The therapeutic dose and treatment time of UCMSCsOE-CXCR7 were directly proportional to their therapeutic effect on lung injury. In addition, overexpression of CXCR7 increased SDF-1-induced proliferation and migration of lung epithelial cells (Base-2b cells), and upregulation of CXCR7 inhibited α-SMA expression, suggesting that CXCR7 may have a role in alleviating pulmonary fibrosis caused by ARDS. Overexpression of CXCR7 in UCMSCs may improve their therapeutic effect of acute lung injury mouse, The mechanism of fibrosis repair by CXCR7 is inhibition of Jag1 via suppression of the Wnt/β-catenin pathway under the chemotaxis of SDF-1.

Abstract Pseudomonas aeruginosa infection is a severe acute suppurative ulcer that engulfs virtually the entire tissue in a short period and leads to devastating destruction. Antibiotic therapy is a common approach for the prophylaxis and treatment of P. aeruginosa infection. However, it is often associated with serious side effects, complications, and multidrug resistance. Therefore, it has been a long-standing challenge to explore safe and effective methods for controlling P. aeruginosa infection. Herein, tannin-coordinated nanozyme composite-based hybrid hydrogels (TCNH) are developed and characterized for the prophylactic treatment of P. aeruginosa and multidrug-resistant P. aeruginosa infections using mouse keratitis as the animal model. The TCNH eye drops are constructed by photoinitiated free radical polymerization of acetylated gelatin solution containing self-synthesized tannin-coordinated Co3O4/Ag nanozyme composite. The as-prepared TCNH displays good dispersibility, peroxidase-like activity and in vitro/in vivo biocompatibility. The nanozyme composite in TCNH seems to penetrate the interior of bacteria and exhibited significant broad-spectrum antibacterial activity owing to its intrinsic and nanozymic catalytic properties. Furthermore, TCNH eye drops can be successfully applied to treat P. aeruginosa and multidrug-resistant P. aeruginosa keratitis. The findings of this study reveal the potential of tannin-coordinated nanozyme composite-based hybrid hydrogel eye drops for treating infectious diseases. Graphical Abstract

BackgroundThis study explored novel biomarkers for diagnosing sepsis, a severe disease prevalent in clinical settings, particularly threatening to elderly patients.MethodsUsing microarray gene expression datasets and fatty acid metabolism signatures, we identified differentially expressed genes between sepsis and healthy control groups. Correlations between candidate genes, immune cells, and immune function were assessed. Logistic regression analysis and single-gene GSEA analysis were performed to identify potential biomarkers. The biomarkers’ association with different types of tumors was investigated.ResultsTwelve genes related to fatty acid metabolism were excluded. CA4, OLAN, and VNN1 were found relevant to immune cells and function. Among these, only VNN1 showed statistical significance (p

PurposeTo compare the surgical outcomes of combined penetrating keratoplasty (PK) and cataract surgery with those of sequential surgery (cataract surgery after PK) for herpes simplex keratitis (HSK).MethodsThe medical records of consecutive patients diagnosed with HSK who underwent combined or sequential PK and cataract surgery in active and stable stages between June 2015 and June 2022 were reviewed retrospectively. Complications, graft survival, endothelial cell density (ECD), and final BCVA were compared and analyzed between both surgical methods in each stage.ResultsA total of 171 eyes of 171 patients were enrolled, including active stage (69 combined, 46 sequential) and stable stage (34 combined, 22 sequential). The average follow up was 24.2 ± 15.8 months (range, 3 months – 48 months). The final BCVA had obvious improvement and the postoperative ECD was not different in combined and sequential groups of each stage. In sequential group of active stage, 66.7% of persistent epithelial defects and 50% of HSK recurrence occurred within 3 months after cataract surgery; nevertheless, compared to that in sequential group, capsular rupture (p = 0.021), persistent epithelial defects (p = 0.027), and HSK recurrence (p = 0.035) occurred more frequently in combined group, leading to a lower graft survival rate (p = 0.045); at the last visit, 46.4 and 67.4% of grafts remained clear in combined and sequential groups, respectively. By contrary, 82.4 and 50.0% of grafts remained clear in stable stages of combined and sequential groups at the last visit, respectively, and a higher graft survival rate was observed in combined group (p = 0.030).ConclusionAlthough the postoperative ECD is not different between two surgical groups in each stage, sequential surgery in active stage of HSK seems to have advantages in less complications and higher graft survival rate, whereas combined surgery in stable stage has a better outcome than that in sequential surgery.

Objective: The goal of this study was to examine the prognostic performance of optical flow ratio (OFR) among patients with coronary artery disease (CAD) after percutaneous coronary intervention (PCI). Methods: We recruited patients with CAD undergoing optical coherence tomography (OCT)-directed PCI between January 2019 and June 2021 for our single-center, hospital-based, retrospective cohort investigation. We assessed the link between post-PCI OFR and major adverse cardiovascular events (MACE) via multivariate Cox regression analysis. Results: Receiver operating characteristic analysis revealed that the best post-PCI OFR threshold for MACE was 0.91, and introduction of OFR into the baseline profile and OCT results markedly enhanced MACE identification after PCI. On the basis of survival curves, patients with OFR ≤0.91 (P < 0.001) and thin-cap fibroatheroma (TCFA) (P = 0.007) exhibited higher MACE incidence, and myocardial infarction (MI) incidence was considerably greater among patients with OFR ≤0.91 (P < 0.001), compared with OFR >0.91. Multivariate Cox regression analysis suggested that OFR ≤0.91 (hazard ratio [HR]: 3.60; 95% confidence interval [CI]: 1.24–10.44; P = 0.019), and TCFA (HR: 3.63; 95% CI: 1.42–9.20; P = 0.007) were independent risk factors for MACE, and OFR ≤0.91 was independently associated with MI (HR: 14.64; 95% CI: 3.27–65.54; P < 0.001). Conclusion: OFR after PCI is an independent MACE bio-indicator among patients with CAD. Adding OFR to post-PCI OCT results may potentially enhance MACE prediction.

Abstract Pulmonary microbial diversity may be influenced by biotic or abiotic conditions (e.g., disease, smoking, invasive mechanical ventilation (MV), etc.). Specially, invasive MV may trigger structural and physiological changes in both tissue and microbiota of lung, due to gastric and oral microaspiration, altered body posture, high O2 inhalation-induced O2 toxicity in hypoxemic patients, impaired airway clearance and ventilator-induced lung injury (VILI), which in turn reduce the diversity of the pulmonary microbiota and may ultimately lead to poor prognosis. Furthermore, changes in (local) O2 concentration can reduce the diversity of the pulmonary microbiota by affecting the local immune microenvironment of lung. In conclusion, systematic literature studies have found that invasive MV reduces pulmonary microbiota diversity, and future rational regulation of pulmonary microbiota diversity by existing or novel clinical tools (e.g., lung probiotics, drugs) may improve the prognosis of invasive MV treatment and lead to more effective treatment of lung diseases with precision.

Abstract Keratoconus is a common ectatic corneal disorder in adolescents and young adults that can lead to progressive visual impairment or even legal blindness. Despite the high prevalence, its etiology is not fully understood. In this study, we performed single-cell RNA sequencing (scRNA-Seq) analysis on 39,214 cells from central corneas of patients with keratoconus and healthy individuals, to define the involvement of each cell type during disease progression. We confirmed the central role of corneal stromal cells in this disease, where dysregulation of collagen and extracellular matrix (ECM) occurred. Differential gene expression and histological analyses revealed two potential novel markers for keratoconus stromal cells, namely CTSD and CTSK. Intriguingly, we detected elevated levels of YAP1 and TEAD1, the master regulators of biomechanical homeostasis, in keratoconus stromal cells. Cyclical mechanical experiments implicated the mechanical stretch in prompting protease production in corneal stromal cells during keratoconus progression. In the epithelial cells of keratoconus corneas, we observed reduced basal cells and abnormally differentiated superficial cells, unraveling the corneal epithelial lesions that were usually neglected in clinical diagnosis. In addition, several elevated cytokines in immune cells of keratoconus samples supported the involvement of inflammatory response in the progression of keratoconus. Finally, we revealed the dysregulated cell-cell communications in keratoconus, and found that only few ligand-receptor interactions were gained but a large fraction of interactional pairs was erased in keratoconus, especially for those related to protease inhibition and anti-inflammatory process. Taken together, this study facilitates the understanding of molecular mechanisms underlying keratoconus pathogenesis, providing insights into keratoconus diagnosis and potential interventions.

Resistance and tolerance are two important strategies employed by the host immune response to defend against pathogens. Multidrug-resistant bacteria affect the resistance mechanisms involved in pathogen clearance. Disease tolerance, defined as the ability to reduce the negative impact of infection on the host, might be a new research direction for the treatment of infections. The lungs are highly susceptible to infections and thus are important for understanding host tolerance and its precise mechanisms. This review focuses on the factors that induce lung disease tolerance, cell and molecular mechanisms involved in tissue damage control, and the relationship between disease tolerance and sepsis immunoparalysis. Understanding the exact mechanism of lung disease tolerance could allow better assessment of the immune status of patients and provide new ideas for the treatment of infections.

Diabetic keratopathy (DK), the diabetic complication in the cornea, is characterized by the delayed epithelial regeneration and sensory nerve degeneration. The involvement of limbal stem/progenitor cells (LSPCs) dysfunction has been reported, however the pathogenic mechanisms remain unclear. Here, we confirmed the dysfunction of LSPCs in diabetic mouse and human corneas. The sympathetic nerve in the cornea was adjacent to LSPCs, and the sympathetic overactivation was found in diabetic mice. Surgical and pharmacological ablation of sympathetic nerves rescued the LSPCs function and promoted corneal epithelial regeneration in diabetic mice. In contrast, both topical norepinephrine (NE) application and chemogenetic sympathetic overactivation directly impaired the stemness and proliferation characteristics of LSPCs, as well as the normal epithelial regeneration. Moreover, we identified that β2-adrenoceptor (Adrb2) was the predominant adrenergic receptor expressed in LSPCs by corneal limbal single-cell sequencing and real time PCR (RT-PCR) analysis of sorted LSPCs. The Adrb2 knockout mice exhibited the enhancement of epithelial regeneration and LSPCs function, compared with the wild-type mice. Similarly, topical application of the Adrb2 specific antagonist ICI 118, 551 effectively accelerated diabetic corneal epithelial regeneration with the restored LSPCs function. Mechanistically, sonic hedgehog (Shh) activity mediated the downstream effects of NE-Adrb2 signaling pathway in regulating LSPCs and epithelial regeneration. Taken together, our data revealed the involvement of sympathetic overactivation in the impairment of diabetic LSPCs function and corneal epithelial regeneration through the NE-Adrb2-Shh signaling pathway. The interference of sympathetic overactivation may provide novel treatment strategies for diabetic keratopathy.

Abstract Background Mammalian lens regeneration holds great potential as a cataract therapy. However, the mechanism of mammalian lens regeneration is unclear, and the methods for optimization remain in question. Methods We developed an in vitro lens regeneration model using mouse capsular bag culture and improved the transparency of the regenerated lens using nicotinamide (NAM). We used D4476 and SSTC3 as a casein kinase 1A inhibitor and agonist, respectively. The expression of lens-specific markers was examined by real-time PCR, immunostaining, and western blotting. The structure of the in vitro regenerated lens was investigated using 3,3′-dihexyloxacarbocyanine iodide (DiOC6) and methylene blue staining, terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), and transmission electron microscopy. Results The in vitro lens regeneration model was developed to mimic the process of in vivo mammalian lens regeneration in a mouse capsular bag culture. In the early stage, the remanent lens epithelial cells proliferated across the posterior capsule and differentiated into lens fiber cells (LFCs). The regenerated lenses appeared opaque after 28 days; however, NAM treatment effectively maintained the transparency of the regenerated lens. We demonstrated that NAM maintained lens epithelial cell survival, promoted the differentiation and regular cellular arrangement of LFCs, and reduced lens-related cell apoptosis. Mechanistically, NAM enhanced the differentiation and transparency of regenerative lenses partly by inhibiting casein kinase 1A activity. Conclusion This study provides a new in vitro model for regeneration study and demonstrates the potential of NAM in in vitro mammalian lens regeneration.

Abstract Background Several studies have investigated the correlation between physiological parameters and the risk of acute respiratory distress syndrome (ARDS), in addition, etiology-associated heterogeneity in ARDS has become an emerging topic quite recently; however, the intersection between the two, which is early prediction of target conditions in etiology-specific ARDS, has not been well-studied. We aimed to develop and validate a machine-learning model for the early prediction of moderate-to-severe condition of inhalation-induced ARDS. Methods Clinical expertise was applied with data-driven analysis. Using data from electronic intensive care units (retrospective derivation cohort) and the three most accessible vital signs (i.e. heart rate, temperature, and respiratory rate) together with feature engineering, we applied a random forest approach during the time window of 90 h that ended 6 h prior to the onset of moderate-to-severe respiratory failure (the ratio of partial pressure of arterial oxygen to fraction of inspired oxygen ≤ 200 mmHg). Results The trained random forest classifier was validated using two independent validation cohorts, with an area under the curve of 0.9127 (95% confidence interval 0.8713–0.9542) and 0.9026 (95% confidence interval 0.8075–1), respectively. A Stable and Interpretable RUle Set (SIRUS) was used to extract rules from the RF to provide guidelines for clinicians. We identified several predictive factors, including resp_96h_6h_min 100, that could be used for predicting inhalation-induced ARDS (moderate-to-severe condition) 6 h prior to onset in critical care units. (‘xxx_96h_6h_min/mean/max’: the minimum/mean/maximum values of the xxx vital sign collected during a 90 h time window beginning 96 h prior to the onset of ARDS and ending 6 h prior to the onset from every recorded blood gas test). Conclusions This newly established random forest‑based interpretable model shows good predictive ability for moderate-to-severe inhalation-induced ARDS and may assist clinicians in decision-making, as well as facilitate the enrolment of patients in prevention programmes to improve their outcomes.

Abstract Background Myopic maculopathy (MM) has become a major cause of visual impairment and blindness worldwide, especially in East Asian countries. Deep learning approaches such as deep convolutional neural networks (DCNN) have been successfully applied to identify some common retinal diseases and show great potential for the intelligent analysis of MM. This study aimed to build a reliable approach for automated detection of MM from retinal fundus images using DCNN models. Methods A dual-stream DCNN (DCNN-DS) model that perceives features from both original images and corresponding processed images by color histogram distribution optimization method was designed for classification of no MM, tessellated fundus (TF), and pathologic myopia (PM). A total of 36,515 gradable images from four hospitals were used for DCNN model development, and 14,986 gradable images from the other two hospitals for external testing. We also compared the performance of the DCNN-DS model and four ophthalmologists on 3000 randomly sampled fundus images. Results The DCNN-DS model achieved sensitivities of 93.3% and 91.0%, specificities of 99.6% and 98.7%, areas under the receiver operating characteristic curves (AUC) of 0.998 and 0.994 for detecting PM, whereas sensitivities of 98.8% and 92.8%, specificities of 95.6% and 94.1%, AUCs of 0.986 and 0.970 for detecting TF in two external testing datasets. In the sampled testing dataset, the sensitivities of four ophthalmologists ranged from 88.3% to 95.8% and 81.1% to 89.1%, and the specificities ranged from 95.9% to 99.2% and 77.8% to 97.3% for detecting PM and TF, respectively. Meanwhile, the DCNN-DS model achieved sensitivities of 90.8% and 97.9% and specificities of 99.1% and 94.0% for detecting PM and TF, respectively. Conclusions The proposed DCNN-DS approach demonstrated reliable performance with high sensitivity, specificity, and AUC to classify different MM levels on fundus photographs sourced from clinics. It can help identify MM automatically among the large myopic groups and show great potential for real-life applications.

The corneal endothelium is critical for maintaining corneal clarity by mediating hydration through barrier and pump functions. Progressive loss of corneal endothelial cells during aging has been associated with the development of Fuchs endothelial corneal dystrophy (FECD), one of the main causes of cornea-related vision loss. The mechanisms underlying FECD development remain elusive. Single-cell RNA sequencing of isolated healthy human corneas discovered 4 subpopulations of corneal endothelial cells with distinctive signatures. Unsupervised clustering analysis uncovered nuclear enriched abundant transcript 1 (NEAT1), a long non-coding RNA (lncRNA), as the top expressed gene in the C0-endothelial subpopulation, but markedly downregulated in FECD. Consistent with human corneas, a UVA-induced mouse FECD model validated the loss of NEAT1 expression. Loss of NEAT1 function by an in vivo genetic approach reproduced the exacerbated phenotype of FECD by ablating corneal endothelial cells. Conversely, gain of function by a CRISPR-activated adenoviral delivery system protected corneas from UVA-induced FECD. Our findings provide novel mechanistic insights into the development of FECD, and targeting NEAT1 offers an attractive approach for treating FECD.

With the global prevalence of diabetes mellitus over recent decades, more patients suffered from various diabetic complications, including diabetic ocular surface diseases that may seriously affect the quality of life and even vision sight. The major diabetic ocular surface diseases include diabetic keratopathy and dry eye. Diabetic keratopathy is characterized with the delayed corneal epithelial wound healing, reduced corneal nerve density, decreased corneal sensation and feeling of burning or dryness. Diabetic dry eye is manifested as the reduction of tear secretion accompanied with the ocular discomfort. The early clinical symptoms include dry eye and corneal nerve degeneration, suggesting the early diagnosis should be focused on the examination of confocal microscopy and dry eye symptoms. The pathogenesis of diabetic keratopathy involves the accumulation of advanced glycation end-products, impaired neurotrophic innervations and limbal stem cell function, and dysregulated growth factor signaling, and inflammation alterations. Diabetic dry eye may be associated with the abnormal mitochondrial metabolism of lacrimal gland caused by the overactivation of sympathetic nervous system. Considering the important roles of the dense innervations in the homeostatic maintenance of cornea and lacrimal gland, further studies on the neuroepithelial and neuroimmune interactions will reveal the predominant pathogenic mechanisms and develop the targeting intervention strategies of diabetic ocular surface complications.

Abstract Transmembrane protein (TMEM) is a family of protein that spans cytoplasmic membranes and allows cell–cell and cell–environment communication. Dysregulation of TMEMs has been observed in multiple cancers. However, little is known about TMEM116 in cancer development. In this study, we demonstrate that TMEM116 is highly expressed in non-small-cell lung cancer (NSCLC) tissues and cell lines. Inactivation of TMEM116 reduced cell proliferation, migration and invasiveness of human cancer cells and suppressed A549 induced tumor metastasis in mouse lungs. In addition, TMEM116 deficiency inhibited PDK1-AKT-FOXO3A signaling pathway, resulting in accumulation of TAp63, while activation of PDK1 largely reversed the TMEM116 deficiency induced defects in cancer cell motility, migration and invasive. Together, these results demonstrate that TMEM116 is a critical integrator of oncogenic signaling in cancer metastasis.

Abstract Epithelial cysts run a high risk of recurrence and conversion to sheet-like ingrowth after surgical intervention. In this retrospective study, we introduced a modified iridectomy for treatment of secondary epithelial iris cysts (EICs) in the anterior chamber. Twenty-nine patients (29 eyes) aged 2–61 years received “open iridectomy” for EICs between April 1995 and July 2019. After viscodissection, most of the cyst wall was cut using a 20-gauge aspiration cutter via a 2.5-mm clear corneal incision. The residue closely adhering to the iris stroma was remained to avoid photophobia and diplopia. At 3 months, best corrected visual acuity was ≥ 20/100 in 55.5% (15/27, except two pediatric patients with poor cooperation) of patients. Among the eight patients suffering partial corneal edema preoperatively, six patients received surgery treatment at 3–6.5 months, and the cornea in the other two patients became transparent after medication. In a mean follow-up of 47.4 months, recurrence occurred in 3 patients at 7, 37, and 118 months, respectively. The percentage of treatment success was 96%, 87%, and 65% at 1, 5, and 10 years, respectively. “Open iridectomy” was effective for EICs, with a minimal invasion, less damage to the corneal endothelium, and a low recurrence rate.

Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) is a critical clinical syndrome with high morbidity and mortality that poses a major challenge in critical care medicine. The development of ALI/ARDS involves excessive inflammatory response, and macrophage autophagy plays an important role in regulating the inflammatory response in ALI/ARDS. In this paper, we review the effects of autophagy in regulating macrophage function, discuss the roles of macrophage autophagy in ALI/ARDS, and highlight drugs and other interventions that can modulate macrophage autophagy in ALI/ARDS to improve the understanding of the mechanism of macrophage autophagy in ALI/ARDS and provide new ideas and further research directions for the treatment of ALI/ARDS.