The predictive value of inflammatory biomarkers for major pathological response in non-small cell lung cancer patients receiving neoadjuvant chemoimmunotherapy and its association with the immune-related tumor microenvironment: a multi-center study.

BACKGROUND: Inflammatory biomarkers in the peripheral blood have been established as predictors for immunotherapeutic efficacy in advanced non-small cell lung cancer (NSCLC). Whether they can also predict major pathological response (MPR) in neoadjuvant setting remains unclear. METHODS: In this multi-center retrospective study, 122 and 92 stage I-IIIB NSCLC patients from six hospitals who received neoadjuvant chemoimmunotherapy followed by surgery were included in the discovery and external validation cohort, respectively. Baseline and on-treatment neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII) were calculated and associated with MPR. Furthermore, resected tumor samples from 37 patients were collected for RNA-sequencing to investigate the immune-related tumor microenvironment. RESULTS: In both the discovery and validation cohorts, the on-treatment NLR, dNLR, PLR, and SII levels were significantly lower in the patients with MPR versus non-MPR. On-treatment SII remained an independent predictor of MPR in multivariate logistic regression analysis. The area under the curve (AUC) of on-treatment SII for predicting MPR was 0.75 (95%CI, 0.67-0.84) in the discovery cohort. Moreover, the predictive value was further improved by combining the on-treatment SII and radiological tumor regression data, demonstrating an AUC of 0.82 (95%CI, 0.74-0.90). The predictive accuracy was validated in the external cohort. Compared with the SII-high group, patients with SII-Low were associated with the activated B cell receptor signaling pathway and a higher intratumoral immune cell infiltration level. CONCLUSIONS: On-treatment SII was independently associated with MPR in NSCLC patients receiving neoadjuvant chemoimmunotherapy. Further prospective studies are warranted.

Diagnosis of invasive fungal infections: challenges and recent developments.

BACKGROUND: The global burden of invasive fungal infections (IFIs) has shown an upsurge in recent years due to the higher load of immunocompromised patients suffering from various diseases. The role of early and accurate diagnosis in the aggressive containment of the fungal infection at the initial stages becomes crucial thus, preventing the development of a life-threatening situation. With the changing demands of clinical mycology, the field of fungal diagnostics has evolved and come a long way from traditional methods of microscopy and culturing to more advanced non-culture-based tools. With the advent of more powerful approaches such as novel PCR assays, T2 Candida, microfluidic chip technology, next generation sequencing, new generation biosensors, nanotechnology-based tools, artificial intelligence-based models, the face of fungal diagnostics is constantly changing for the better. All these advances have been reviewed here giving the latest update to our readers in the most orderly flow. MAIN TEXT: A detailed literature survey was conducted by the team followed by data collection, pertinent data extraction, in-depth analysis, and composing the various sub-sections and the final review. The review is unique in its kind as it discusses the advances in molecular methods; advances in serology-based methods; advances in biosensor technology; and advances in machine learning-based models, all under one roof. To the best of our knowledge, there has been no review covering all of these fields (especially biosensor technology and machine learning using artificial intelligence) with relevance to invasive fungal infections. CONCLUSION: The review will undoubtedly assist in updating the scientific community's understanding of the most recent advancements that are on the horizon and that may be implemented as adjuncts to the traditional diagnostic algorithms.

Clinical utility of [18F]FDG PET/CT in the assessment of mediastinal lymph node disease after neoadjuvant chemoimmunotherapy for non-small cell lung cancer.

OBJECTIVES: The performance of positron emission tomography/computed tomography (PET/CT) for the prediction of ypN2 disease in non-small cell lung cancer (NSCLC) after neoadjuvant chemoimmunotherapy has not been reported. This multicenter study investigated the utility of PET/CT to assess ypN2 disease in these patients. METHODS: A total of 181 consecutive patients (chemoimmunotherapy = 86, chemotherapy = 95) at four institutions were enrolled in this study. Every patient received a PET/CT scan prior to surgery and complete resection with systematic nodal dissection. The diagnostic performance was evaluated through area under the curve (AUC). Kaplan-Meier method and Cox analysis were performed to identify the risk factors affecting recurrences. RESULTS: The sensitivity, specificity, and accuracy of PET/CT for ypN2 diseases were 0.667, 0.835, and 0.779, respectively. Therefore, the AUC was 0.751. Compared with the false positive cases, the mean value of max standardized uptake value (SUVmax) (6.024 vs. 2.672, p < 0.001) of N2 nodes was significantly higher in true positive patients. Moreover, the SUVmax of true positive (7.671 vs. 5.976, p = 0.365) and false (2.433 vs. 2.339, p = 0.990) positive cases were similar between chemoimmunotherapy and chemotherapy, respectively. Survival analysis proved that pathologic N (ypN) 2 patients could be stratified by PET/CT-N2(+ vs. -) for both chemoimmunotherapy (p = 0.023) and chemotherapy (p = 0.010). CONCLUSIONS: PET/CT is an accurate and non-invasive test for mediastinal restaging of NSCLC patients who receive neoadjuvant chemoimmunotherapy. The ypN2 patients with PET/CT-N2( +) are identified as an independent prognostic factor compared with PET/CT-N2(-). CLINICAL RELEVANCE STATEMENT: Imaging with 18F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) plays an integral role during disease diagnosis, staging, and therapeutic response assessments in patients with NSCLC. PET/CT could be an effective non-invasive tool for predicting ypN2 diseases after neoadjuvant chemoimmunotherapy. KEY POINTS: • PET/CT could serve as an effective non-invasive tool for predicting ypN2 diseases. • The ypN2 patients with PET/CT-N2( +) were a strong and independent prognostic factor. • The application of PET/CT for restaging should be encouraged in clinical practice.

Establishment of a risk prediction model for prolonged mechanical ventilation after lung transplantation: a retrospective cohort study.

BACKGROUND: Prolonged mechanical ventilation (PMV), mostly defined as mechanical ventilation > 72 h after lung transplantation with or without tracheostomy, is associated with increased mortality. Nevertheless, the predictive factors of PMV after lung transplant remain unclear. The present study aimed to develop a novel scoring system to identify PMV after lung transplantation. METHODS: A total of 141 patients who underwent lung transplantation were investigated in this study. The patients were divided into PMV and non-prolonged ventilation (NPMV) groups. Univariate and multivariate logistic regression analyses were performed to assess factors associated with PMV. A risk nomogram was then established based on the multivariate analysis, and model performance was further examined regarding its calibration, discrimination, and clinical usefulness. RESULTS: Eight factors were finally identified to be significantly associated with PMV by the multivariate analysis and therefore were included as risk factors in the nomogram as follows: the body mass index (BMI, P = 0.036); primary diagnosis as idiopathic pulmonary fibrosis (IPF, P = 0.038); pulmonary hypertension (PAH, P = 0.034); primary graft dysfunction grading (PGD, P = 0.011) at T0; cold ischemia time (CIT P = 0.012); and three ventilation parameters (peak inspiratory pressure [PIP, P < 0.001], dynamic compliance [Cdyn, P = 0.001], and P/F ratio [P = 0.015]) at T0. The nomogram exhibited superior discrimination ability with an area under the curve of 0.895. Furthermore, both calibration curve and decision-curve analysis indicated satisfactory performance. CONCLUSION: A novel nomogram to predict individual risk of receiving PMV for patients after lung transplantation was established, which may guide preventative measures for tackling this adverse event.

Towards Non-stick Silk: Tuning the Hydrophobicity of Silk Fibroin Protein.

Silk fibroin protein is a biomaterial with excellent biocompatibility and low immunogenicity. These properties have catapulted the material as a leader for extensive use in stents, catheters, and wound dressings. Modulation of hydrophobicity of silk fibroin protein to further expand the scope and utility however has been elusive. We report that installing perfluorocarbon chains on the surface of silk fibroin transforms this water-soluble protein into a remarkably hydrophobic polymer that can be solvent-cast. A clear relationship emerged between fluorine content of the modified silk and film hydrophobicity. Water contact angles of the most decorated silk fibroin protein exceeded that of Teflon®. We further show that water uptake in prefabricated silk bars is dramatically reduced, extending their lifetimes, and maintaining mechanical integrity. These results highlight the power of chemistry under moderate conditions to install unnatural groups onto the silk fibroin surface and will enable further exploration into applications of this versatile biomaterial.

Microarray analysis of circRNAs sequencing profile in exosomes derived from bone marrow mesenchymal stem cells in postmenopausal osteoporosis patients.

INTRODUCTION: Bone marrow-derived mesenchymal stem cells (BMSCs)-derived exosomes are involved in the modulation of tissue repair and regeneration. CircRNAs play important roles in BMSCs exosomes. The current study sought to explore the role of circRNAs in exosomes derived from BMSCs of postmenopausal osteoporosis (PMOP) patients and the underlying mechanisms. METHODS: RNA was extracted from BMSCs exosomes of PMOP and a control group. RNA microarray and bioinformatics analyses were used to explore the expression profile and functions circRNAs. Differentially expressed circRNAs from 20 PMOP and 20 controls were analyzed using RT-qPCR. RESULTS: A total of 237 upregulated and 279 downregulated circRNAs were identified in the current study. The top-10 most upregulated circRNAs in the PMOP group were hsa_circ_0069691, hsa_circ_0005678, hsa_circ_0006464, hsa_circ_0015813, hsa_circ_0000511, hsa_circ_0076527, hsa_circ_0009127, hsa_circ_0047285, hsa_circ_0027741, and hsa_circ_0090949. The top-10 most downregulated circRNAs were hsa_circ_0048669, hsa_circ_0090247, hsa_circ_0070899, hsa_circ_0087557, hsa_circ_0045963, hsa_circ_0090180, hsa_circ_0058392, hsa_circ_0040751, hsa_circ_0067910, and hsa_circ_0049484. RT-PCR verified dysregulation of 5 circRNAs including hsa_circ_0009127, hsa_circ_0090759, hsa_circ_0058392, hsa_circ_0090247, and hsa_circ_0049484. Moreover, a circRNA-microRNA-mRNA interaction network was developed based on differentially expressed circRNAs. Functional analysis showed that pathways involved in the regulation of autophagy, PI3K-Akt signaling, FoxO signaling, and MAPK signaling were associated with the differentially expressed circRNAs in PMOP patients. CONCLUSION: The findings of this study show dysregulated circRNAs in BMSCs exosomes of PMOP patients, which may affect the progression of PMOP. These circRNAs can be used as predictive biomarkers and as therapeutic targets for the treatment of PMOP.

Effect of TGF-ß1-Mediated Exercise Analgesia in Spared Nerve Injury Mice.

Peripheral nerve injury leads to severe neuropathic pain. Previous studies have highlighted the beneficial effects of physical exercise on alleviating neuropathic pain. Exercise regulating transforming growth factor-ß1 (TGF-ß1) can improve several diseases and relieve neuropathic pain induced by peripheral nerve injury. Here, we investigated whether exercise could alleviate neuropathic pain by modulating TGF-ß1 expression. We assessed mechanical and cold pain behavior and conducted molecular evaluation of the spinal cord. We found that spared nerve injury (SNI) led to mechanical and cold allodynia in the hind paw, elevated the expression of latency-associated peptide- (LAP-) TGF-ß1, and activated astroglial in the spinal cord. Exercise decreases allodynia, astroglial activation, and LAP-TGF-ß1 in SNI mice. Intrathecal injection of a TGF-type I receptor inhibitor attenuated exercise analgesia and enhanced astroglial activation. These findings demonstrate that exercise induces analgesia by promoting TGF-ß1 activation and inhibiting astrogliosis. Our study reveals a new underlying mechanism for exercise-attenuated neuropathic pain in the maintenance stage of neuropathic pain after nerve injury.

The association between perioperative pupillary parameters and postoperative acute pain: A pilot cross-sectional study.

OBJECTIVE: We aim to explore the capacity of perioperative pupillary variables to predict acute pain in the post-anesthesia care unit (PACU). METHODS: Patients scheduled to undergo thoracic or abdominal surgery under general anesthesia between April 2021 and June 2021 were enrolled. We measured the pupil diameter, pupillary light reflex (PLR), and pupillary reflex dilatation 5 min before anesthesia induction (T1), 5 min after intubation (T2), at the end of anesthesia (T3), immediately before extubation (T4), and 5 min after extubation (T5). We assessed the early postoperative pain intensity in the PACU using Numeric Rating Scales (NRS) at recovery, 5 min after recovery, and 10 min after recovery. Logistic regression models were used to evaluate the association between perioperative pupillary variables and postoperative pain intensity. RESULTS: Fifty-one patients were enrolled, 50 of whom were included in the final analysis. A total of 13 patients (26%) needed remedial analgesia in the PACU. Pupil parameters at T1, T2, T3, and T5 were not associated with NRS in the PACU. Multiple logistic regression models and receiver operating characteristic (ROC) curves indicated that only latency of PLR at T4 can predict postoperative acute pain. The ROC analysis showed that the cutoff value for latency of PLR at T4 was 0.29 s to discriminate between no pain and pain, and the area under the curve was 0.778 (95% CI 0.634-0.922, p = 0.002) with sensitivity 50.0% and specificity 91.7%. CONCLUSION: The latency of PLR immediately before extubation may be a useful predictor for postoperative acute pain in the PACU.

The learning curve for uniportal video-assisted thoracoscopic anatomical segmentectomy.

OBJECTIVES: The aim of this study is to evaluate the time course and caseload required to achieve proficiency by plotting the learning curve of uniportal thoracoscopic segmentectomy. METHODS: We retrospectively analyzed the first 238 and 159 cases of uniportal thoracoscopic segmentectomy performed by two surgeons (A and B). The learning curves were assessed using cumulative sum analysis. Perioperative outcomes were evaluated as the learning curve developed. Two subtypes of this surgical approach, simple and complex segmentectomy, were separately analyzed. RESULTS: Based on the learning curve, the inflection points occurred at 64 and 90 cases for surgeon A, 71 and 100 cases for surgeon B. Significantly longer operative time (p = .013), length of stay (p = .002), and drainage duration (p = .039) were observed between phase I and phase II compared to phase III for surgeon A. Operative times (p = .001) were significantly reduced for surgeon B. Furthermore, 26-28 and 52-56 cases were necessary to master the simple and complex segmentectomy, respectively. CONCLUSIONS: A total 64-71 cases were required to master uniportal thoracoscopic segmentectomy and 90-100 cases were necessary to achieve proficiency.

Isolation, synthesis and absolute configuration of 4,5-dihydroxypiperines improving behavioral disorder in AlCl3-induced dementia.

A pair of stereoisomers of new 4,5-dihydroxypiperine was isolated from P. retrofractum and showed profound activity on AlCl3-induced dementia. In order to determine their absolute configurations and biological activities, all four possible stereoisomers of 4,5-dihydroxypiperine were synthesized from piperidine by Sharpless asymmetric dihydroxylation and Mitsunobu reaction. Their absolute configurations were established as (4R,5R) (1), (4S,5S) (2), (4S,5R) (3) and (4R,5S) (4) by NMR, optical rotation and CD spectra. It is note that only compound 4 improved behavioral disorder in AlCl3-induced dementia. Accordingly, the pair of stereoisomers isolated from P. retrofractum was determined to be (4S,5S) and (4R,5S)-isomers (2 and 4). The ratio of the epimers was present as 1:0.7 (4:2).

Variation in water density related to pollutants removal in wastewater treatment processes and its use in explaining the working principles of the Unifed SBR.

The wastewater quality of several municipal wastewater treatment plants (MWTPs) in Beijing was studied, and the water densities of different processing units were also measured during the wastewater treatment process. The results clearly showed that the water density declined from influent to effluent of the wastewater treatment process. Meanwhile, the variation in water density had good statistical correlation with the concentrations of total organic carbon, total phosphorus, suspended solids and total solids. Furthermore, the variation in water density could be used to explain the working principles of the Unifed sequencing batch reactor (SBR). Tracer tests were conducted in the Unifed SBR to investigate the hydraulic characteristics of the reactor. The experimental results showed that the variable values of water density from influent to effluent in the Fangzhuang MWTPs were greater than those caused by the temperature difference of >3 °C between the influent and the liquid in the reactor at 13 °C. Moreover, the flow regime of wastewater in the Unifed SBR was affected by the variation in water density, which may lead to stratification or a density current. Ascribed to the appearance of stratification in the Unifed SBR reactor, the water quality of the effluent could not be affected by that of the influent.

[Construction of three HLA-A*0201-peptide tetramers and their preliminary application in detection of vitiligo-specific cytotoxic T lymphocytes].

OBJECTIVE: To construct vitiligo-specific HLA-A*0201-peptide tetramers and to apply the constructed tetramers in detection of vitiligo-specific cytotoxic T lymphocytes (CTL). METHODS: Proteins HLA-A0201*-BSP and ß2M were obtained by effective prokaryotic expression. The purified proteins were refolded with vitiligo antigen peptides MelanA 26-35, gp100 209-217, and tyrosinase 1-9, respectively to form HLA-A*0201-peptide complex. The complex was biotinylated by BirA enzyme and purified by gel-filtration chromatography. The tetramers were generated by mixing the complex with phycoerythrin (PE)-streptavidin at a ratio of 4∶1 and identified by Dot-blot assay. The capacity of tetramer to detect vitiligo-specific CTL was analyzed by flow cytometry. RESULTS: The biotinylation of vitiligo-specific HLA-A*0201-peptide tetramers were successfully performed by Dot-blot. Flow cytometry analysis indicated that the tetramer effectively bound to specific CTL from peripheral blood of patients with vitiligo. CONCLUSION: Three kinds of biotinylated vitiligo-specific HLA-A*0201-peptide tetramers have been constructed successfully. The tetramer can detect antigen specific CTL from patients with vitiligo.

Analyzing activity and injury risk in elite curling athletes: seven workload monitoring metrics from session-RPE.

Objective: The study aimed to compare the differences in the performance of seven session-rating of perceived exertion (RPE)-derived metrics (coupled and uncoupled acute: chronic workload ratio (ACWR), weekly ratio of workload change, monotony, standard deviation of weekly workload change, exponentially weighted moving average (EWMA), and robust exponential decreasing index (REDI)) in classifying the performance of an injury prediction model after taking into account the time series (no latency, 5-day latency, and 10-day latency). Design: The study documented the RPE of eight curlers in their daily training routine for 211 days prior to the Olympic Games. Methods: Seven Session-RPE (sRPE)-derived metrics were used to build models at three time series nodes using logistic regression and multilayer perceptron. Receiver operating characteristic plots were plotted to evaluate the model's performance. Results: Among the seven sRPE-derived metrics multilayer perceptron models, the model without time delay (same-day load corresponding to same-day injury) exhibited the highest average classification performance (86.5%, AUC = 0.773). EMWA and REDI demonstrated the best classification performance (84.4%, p < 0.001). Notably, EMWA achieved the highest classifying accuracy in the no-delay time series (90.0%, AUC = 0.899), followed by the weekly load change rate under the 5-day delay time series (88.9%, AUC = 0.841). Conclusion: EWMA without delay is a more sensitive indicator for detecting injury risk.

Understanding epidemic spread patterns: a visual analysis approach.

Epidemics present significant challenges for public health policy globally, but current tools for visualizing and analyzing epidemic spread are limited, especially at a large scale. This paper presents a novel visual analysis approach for exploring and comparing pandemic patterns in spatial and temporal dimensions across various regions. The method incorporates a potential flow technique to model the spatiotemporal dynamics of epidemics and a visual exploration tool, EPViz, for interactive data analysis. Utilizing COVID-19 data from Illinois and Pennsylvania in the United States, the paper evaluates the method and tool's effectiveness. These states were chosen for their differing epidemic scenarios and policies. Additionally, interviews with public health policy experts were conducted to gather feedback on the approach and EPViz's effectiveness, design, and usability. The findings indicate that this new approach and tool enhance expert understanding, support decision-making, and can inform effective strategies for epidemic prevention and control.

High levels of high-density lipoprotein cholesterol may increase the risk of diabetic kidney disease in patients with type 2 diabetes.

Studies have indicated that low high-density lipoprotein cholesterol (HDL-C) level is an important risk factor for diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D). However, whether higher HDL-C levels decrease the risk of developing DKD remains unclear. This study aimed to clarify the relationship between HDL-C levels and DKD risk in individuals with T2D in China. In total, 936 patients with T2D were divided into DKD and non-DKD groups. The association between HDL-C levels and DKD risk was evaluated using logistic regression analysis and restricted cubic spline curves adjusted for potential confounders. Threshold effect analysis of HDL-C for DKD risk was also performed. Higher HDL-C levels did not consistently decrease the DKD risk. Furthermore, a nonlinear association with threshold interval effects between HDL-C levels and the incidence of DKD was observed. Patients with HDL-C ≤ 0.94 mmol/L or HDL-C > 1.54 mmol/L had significantly higher DKD risk after adjusting for confounding factors. Interestingly, the association between high HDL-C levels and increased DKD risk was more significant in women. A U-shaped association between HDL-C levels and DKD risk was observed; therefore, low and high HDL-C levels may increase the DKD risk in patients with T2D.

Low-Protein Diet Inhibits the Synovial Tissue Macrophage Pro-Inflammatory Polarization Via NRF2/SIRT3/SOD2/ROS Pathway in K/BxN Rheumatoid Arthritis Mice.

Rheumatoid arthritis (RA) is a chronic inflammatory disorder characterized by pain, swelling, stiffness, and impaired function. Attenuating inflammation is a crucial objective in RA management. Diet and nutrition are believed to influence RA symptomatology, with a low-protein diet being one potential nutritional strategy, although its underlying mechanisms remain to be fully elucidated. In this research, serum derived from arthritic transgenic K/BxN mice was administered to naive mice to establish a K/BxN rheumatoid arthritis model. Physiological assessments and histological staining were performed to evaluate joint pathology. (Enzyme-linked immunosorbent assay) ELISA was used to measure inflammatory cytokines. Flow cytometry and immunofluorescence were applied to characterize macrophage phenotypes. Transcriptomic analysis elucidated molecular pathways under the effect of a low-protein diet and verified by immunoblotting. Mitochondrial reactive oxygen species (ROS) was detected by Mito-SOX. Protein expression was silenced through the application of siRNA transfection. Our results indicate that a low-protein diet significantly alleviates disease symptoms and decreases pro-inflammatory cytokine levels in synovial fluid. Furthermore, this dietary intervention inhibits M1 macrophage polarization while promoting a shift towards the M2 phenotype. Transcriptomic analysis revealed that the beneficial effects of the low-protein diet in alleviating rheumatoid arthritis are closely linked to the NRF2 pathway. In vitro, low protein treatment can promote the activity of NRF2 via inhibiting the ubiquitin mediated proteolysis and activate the NRF2/SIRT3/SOD2 pathway to inhibit the production of ROS, which will further inhibit the M1 macrophage polarization. NRF2 knockdown can abolish the effects of low-protein treatment, indicating that the inhibition of M1 polarization and the anti-inflammatory response induced by low-protein treatment are dependent on NRF2. In summary, our findings propose that low-protein diet can inhibit synovial macrophage M1 polarization via activating NRF2/SIRT3/SOD2 pathway to reduce mitochondrial ROS production. This mechanism effectively decreases synovial inflammation and alleviates RA symptoms.

Photoreceptor-targeted extracellular vesicles-mediated delivery of Cul7 siRNA for retinal degeneration therapy.

Rationale: Photoreceptor loss is a primary pathological feature of retinal degeneration (RD) with limited treatment strategies. RNA interference (RNAi) has emerged as a promising method of gene therapy in regenerative medicine. However, the transfer of RNAi therapeutics to photoreceptors and the deficiency of effective therapeutic targets are still major challenges in the treatment of RD. Methods: In this study, photoreceptor-derived extracellular vesicles (PEVs) conjugated with photoreceptor-binding peptide MH42 (PEVsMH42) were prepared using the anchoring peptide CP05. Transcriptome sequencing was applied to investigate the potential therapeutic target of RD. We then engineered PEVsMH42 with specific small-interfering RNAs (siRNAs) through electroporation and evaluated their therapeutic efficacy in N-methyl-N-nitrosourea (MNU)-induced RD mice and Pde6ßrd1/rd1 mutant mice. Results: PEVsMH42 were selectively accumulated in photoreceptors after intravitreal injection. Cullin-7 (Cul7) was identified as a novel therapeutic target of RD. Taking advantage of the established PEVsMH42, siRNAs targeting Cul7 (siCul7) were efficiently delivered to photoreceptors and consequently blocked the expression of Cul7. Moreover, suppression of Cul7 effectively protected photoreceptors to alleviate RD both in MNU-induced mouse model and Pde6ßrd1/rd1 mutant mouse model. Mechanistically, PEVsMH42 loaded with siCul7 (PEVsMH42-siCul7)-induced Cul7 downregulation was responsible for preventing Cul7-mediated glutathione peroxidase 4 (Gpx4) ubiquitination and degradation, resulting in the inhibition of photoreceptor ferroptosis. Conclusions: In summary, PEVsMH42-siCul7 attenuate photoreceptor ferroptosis to treat RD by inhibiting Cul7-induced ubiquitination of Gpx4. Our study develops a PEVs-based platform for photoreceptor-targeted delivery and highlights the potential of PEVsMH42-siCul7 as effective therapeutics for RD.

Identification of particle distribution pattern in vertical profile via unmanned aerial vehicles observation.

Below the boundary layer, the air pollutants have been confirmed to present the decreasing trend with the height in most situaitons. However, the disperiosn rate of air pollutants in the vertical profile is rarely investigated in detail, especially through in-situ measurement. With this consideration, we employed an unmanned aerial vehicle equipped with portable monitoring equipments to scrutinize the vertical distribution of PM2.5. Based on the original data, we found that PM2.5 concentration decreases gradually with altitude below the boundary layer and demonstrated an obvious linear correlation. Therefore, the vertical distribution of PM2.5 was quantified by representing the distribution of PM2.5 with the slope of PM2.5 vertical distribution. We used backward trajectories to reveal the causes of outliers (PM2.5 increasing with altitude), and found that PM2.5 in the high altitude came from the southwest. Besides, the relationship between the vertical distribution of PM2.5 and various meteorological factors was investigated using stepwise regression analysis. The results show that the four meteorological factors most strongly correlated with the slope values are: (a) the difference in relative humidity between the ground and the air; (b) the difference in temperature between the ground and the air; (c) the height of the boundary layer; and (d) the wind speed. The slope values increase with increasing the difference in relative humidity between ground and air and the difference in temperature between the ground and the air, and decrease with increasing boundary layer height and wind speed. According to the Random Forest calculations, the ground-to-air relative humidity difference is the most important at 0.718; the wind speed is the least important at 0.053; and the ground-to-air temperature difference and boundary layer height are 0.140 and 0.088, respectively.

OoD-Control: Generalizing Control in Unseen Environments.

Generalizing out-of-distribution (OoD) is critical but challenging in real applications such as unmanned aerial vehicle (UAV) flight control. Previous machine learning-based control has shown promise in dealing with complex real-world environments but suffers huge performance degradation facing OoD scenarios, posing risks to the stability and safety of UAVs. In this paper, we found that the introduced random noises during training surprisingly yield theoretically guaranteed performances via a proposed functional optimization framework. More encouragingly, this framework does not involve common Lyapunov assumptions used in this field, making it more widely applicable. With this framework, the upperbound for control error is induced. We also proved that the induced random noises can lead to lower OoD control errors. Based on our theoretical analysis, we further propose OoD-Control to generalize control in unseen environments. Numerical experiments demonstrate the superiority of the proposed algorithm, surpassing previous state-of-the-art by 65% under challenging unseen environments. We further extend to outdoor real-world experiments and found that the control error is reduced by 50% approximately. Our code is available athttps://github.com/Ulricall/OoD-Control.