Microparticle Mediated Delivery of Apelin Improves Heart Function in Post Myocardial Infarction Mice.

BACKGROUND: Apelin is an endogenous prepropeptide that regulates cardiac homeostasis and various physiological processes. Intravenous injection has been shown to improve cardiac contractility in patients with heart failure. However, its short half-life prevents studying its impact on left ventricular remodeling in the long term. Here, we aim to study whether microparticle-mediated slow release of apelin improves heart function and left ventricular remodeling in mice with myocardial infarction (MI). METHODS: A cardiac patch was fabricated by embedding apelin-containing microparticles in a fibrin gel scaffold. MI was induced via permanent ligation of the left anterior descending coronary artery in adult C57BL/6J mice followed by epicardial patch placement immediately after (acute MI) or 28 days (chronic MI) post-MI. Four groups were included in this study, namely sham, MI, MI plus empty microparticle-embedded patch treatment, and MI plus apelin-containing microparticle-embedded patch treatment. Cardiac function was assessed by transthoracic echocardiography. Cardiomyocyte morphology, apoptosis, and cardiac fibrosis were evaluated by histology. Cardioprotective pathways were determined by RNA sequencing, quantitative polymerase chain reaction, and Western blot. RESULTS: The level of endogenous apelin was largely reduced in the first 7 days after MI induction and it was normalized by day 28. Apelin-13 encapsulated in poly(lactic-co-glycolic acid) microparticles displayed a sustained release pattern for up to 28 days. Treatment with apelin-containing microparticle-embedded patch inhibited cardiac hypertrophy and reduced scar size in both acute and chronic MI models, which is associated with improved cardiac function. Data from cellular and molecular analyses showed that apelin inhibits the activation and proliferation of cardiac fibroblasts by preventing transforming growth factor-ß-mediated activation of Smad2/3 (supporessor of mothers against decapentaplegic 2/3) and downstream profibrotic gene expression. CONCLUSIONS: Poly(lactic-co-glycolic acid) microparticles prolonged the apelin release time in the mouse hearts. Epicardial delivery of the apelin-containing microparticle-embedded patch protects mice from both acute and chronic MI-induced cardiac dysfunction, inhibits cardiac fibrosis, and improves left ventricular remodeling.

Calculation of solvation force in molecular dynamics simulation by deep-learning method.

Electrostatic calculations are generally used in studying the thermodynamics and kinetics of biomolecules in solvent. Generally, this is performed by solving the Poisson-Boltzmann equation on a large grid system, a process known to be time consuming. In this study, we developed a deep neural network to predict the decomposed solvation free energies and forces of all atoms in a molecule. To train the network, the internal coordinates of the molecule were used as the input data, and the solvation free energies along with transformed atomic forces from the Poisson-Boltzmann equation were used as labels. Both the training and prediction tasks were accelerated on GPU. Formal tests demonstrated that our method can provide reasonable predictions for small molecules when the network is well-trained with its simulation data. This method is suitable for processing lots of snapshots of molecules in a long trajectory. Moreover, we applied this method in the molecular dynamics simulation with enhanced sampling. The calculated free energy landscape closely resembled that obtained from explicit solvent simulations.

Clustering one million molecular structures on GPU within seconds.

Structure clustering is a general but time-consuming work in the study of life science. Up to now, most published tools do not support the clustering analysis on graphics processing unit (GPU) with root mean square deviation metric. In this work, we specially write codes to do the work. It supports multiple threads on multiple GPUs. To show the performance, we apply the program to a 33-residue fragment in protein Pin1 WW domain mutant. The dataset contains 1,400,000 snapshots, which are extracted from an enhanced sampling simulation and distribute widely in the conformational space. Various testing results present that our program is quite efficient. Particularly, with two NVIDIA RTX4090 GPUs and single precision data type, the clustering calculation on 1 million snapshots is completed in a few seconds (including the uploading time of data from memory to GPU and neglecting the reading time from hard disk). This is hundreds of times faster than central processing unit. Our program could be a powerful tool for fast extraction of representative states of a molecule among its thousands to millions of candidate structures.

An integrated machine learning model enhances delayed graft function prediction in pediatric renal transplantation from deceased donors.

BACKGROUND: Kidney transplantation is the optimal renal replacement therapy for children with end-stage renal disease; however, delayed graft function (DGF), a common post-operative complication, may negatively impact the long-term outcomes of both the graft and the pediatric recipient. However, there is limited research on DGF in pediatric kidney transplant recipients. This study aims to develop a predictive model for the risk of DGF occurrence after pediatric kidney transplantation by integrating donor and recipient characteristics and utilizing machine learning algorithms, ultimately providing guidance for clinical decision-making. METHODS: This single-center retrospective cohort study includes all recipients under 18 years of age who underwent single-donor kidney transplantation at our hospital between 2016 and 2023, along with their corresponding donors. Demographic, clinical, and laboratory examination data were collected from both donors and recipients. Univariate logistic regression models and differential analysis were employed to identify features associated with DGF. Subsequently, a risk score for predicting DGF occurrence (DGF-RS) was constructed based on machine learning combinations. Model performance was evaluated using the receiver operating characteristic curves, decision curve analysis (DCA), and other methods. RESULTS: The study included a total of 140 pediatric kidney transplant recipients, among whom 37 (26.4%) developed DGF. Univariate analysis revealed that high-density lipoprotein cholesterol (HDLC), donor after circulatory death (DCD), warm ischemia time (WIT), cold ischemia time (CIT), gender match, and donor creatinine were significantly associated with DGF (P < 0.05). Based on these six features, the random forest model (mtry = 5, 75%p) exhibited the best predictive performance among 97 machine learning models, with the area under the curve values reaching 0.983, 1, and 0.905 for the entire cohort, training set, and validation set, respectively. This model significantly outperformed single indicators. The DCA curve confirmed the clinical utility of this model. CONCLUSIONS: In this study, we developed a machine learning-based predictive model for DGF following pediatric kidney transplantation, termed DGF-RS, which integrates both donor and recipient characteristics. The model demonstrated excellent predictive accuracy and provides essential guidance for clinical decision-making. These findings contribute to our understanding of the pathogenesis of DGF.

Hierarchical MOFs with Good Catalytic Properties and Structural Stability in Oxygen-Rich and High-Temperature Environments.

Metal-organic framework materials are ideal materials characterized by open frameworks, adjustable components, and high catalytic activity. They are extensively utilized for catalysis. Due to decomposition and structural collapse under high temperatures and an oxygen-rich environment, the potential of thermal catalysis is greatly limited. In this research, Co-rich hollow spheres (Co-HSs) with a gradient composition are designed and synthesized to investigate their thermal catalytic properties in the ammonium perchlorate（AP）system. The results demonstrate that Co-HSs@AP exhibits good thermal catalytic activity and a high-temperature decomposition of 292.5 °C, which is 121.6 °C lower than pure AP. The hierarchical structure confers structural stability during the thermal decomposition process. Thermogravimetry-infrared indicates that the inclusion of Co-HSs successfully boosts the level of reactive oxygen species and achieves thorough oxidation of NH3. Based on the above phenomenon, macro dynamics calculations are carried out. The results show that Co-HSs can promote the circulation of lattice oxygen and reactive oxygen species and the multidimensional diffusion of NH3 in an oxygen-rich environment. This material has significant potential for application in the fields of thermal catalysis and ammonia oxidation.

FLZ13 interacts with FLC and ABI5 to negatively regulate flowering time in Arabidopsis.

The transition from vegetative to reproductive growth, known as flowering, is a critical developmental process in flowering plants to ensure reproductive success. This process is strictly controlled by various internal and external cues; however, the underlying molecular regulatory mechanisms need to be further characterized. Here, we report a plant-specific protein, FCS-LIKE ZINC FINGER PROTEIN 13 (FLZ13), which functions as a hitherto unknown negative modulator of flowering time in Arabidopsis thaliana. Biochemical analysis showed that FLZ13 directly interacts with FLOWERING LOCUS C (FLC), a major flowering repressor, and that FLZ13 largely depends on FLC to repress the transcription of two core flowering integrators: FLOWERING LOCUS T and SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1. In addition, FLZ13 works together with ABSCISIC ACID INSENSITIVE 5 to activate FLC expression to delay flowering. Taken together, our findings suggest that FLZ13 is an important component of the gene regulatory network for flowering time control in plants.

Homozygous deletion of the DSG3 terminal exon associated with acantholytic blistering of the oral and laryngeal mucosa.

We report a novel homozygous 49.6 kb deletion of chromosome 18q12.1 involving the last exon of DSG3 in dizygotic twins with phenotype consistent with acantholytic blistering of the oral and laryngeal mucosa (ABOLM). The twin siblings presented predominantly with friability of the laryngeal and respiratory mucosa. This is only the second report in the literature of this unusual autosomal recessive blistering disorder. The diagnosis explains the mucosal phenotype of a pemphigus-like disorder without evidence of autoimmune dysfunction. The exclusion of an autoimmune basis has management implications. The deletion also involved the DSG2 gene, which is associated with arrhythmogenic right ventricular dysplasia (ARVD). The affected siblings and heterozygous parents do not show any cardiac phenotype at this time. Functional studies would further clarify how deletions resulting in loss of function of DSG3 may cause the reported phenotypes of DSG3-related ABOLM.

Schwann cells transplantation improves nerve injury and alleviates neuropathic pain in rats.

The mechanism of neuropathic pain induced by nerve injury is complex and there are no effective treatment methods. P2X4 receptor expression is closely related to the occurrence of pain. Schwann cells (SCs) play a key protective role in the repair of peripheral nerve injury and myelin sheath regeneration. However, whether SCs can affect the expression of P2X4 receptor and play a role in pathological pain is still unclear. Therefore, this study investigated the effect of SCs on whether they can down regulate the expression of P2X4 receptor to affect pain. The results showed that in the neuropathic pain induced by sciatic nerve injury model, the expression of P2X4 receptor in spinal cord tissue was significantly increased and the pain sensation of rats was increased. While SCs transplantation could down regulate the expression of P2X4 receptors in spinal cord and increase the mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) of rats. These data indicate that SCs can reduce the expression of P2X4 receptors to alleviate neuropathic pain, indicating that SCs can mediate P2X4 receptor signalling as a new target for pain treatment.

MIST: multiple instance learning network based on Swin Transformer for whole slide image classification of colorectal adenomas.

Colorectal adenoma is a recognized precancerous lesion of colorectal cancer (CRC), and at least 80% of colorectal cancers are malignantly transformed from it. Therefore, it is essential to distinguish benign from malignant adenomas in the early screening of colorectal cancer. Many deep learning computational pathology studies based on whole slide images (WSIs) have been proposed. Most approaches require manual annotation of lesion regions on WSIs, which is time-consuming and labor-intensive. This study proposes a new approach, MIST - Multiple Instance learning network based on the Swin Transformer, which can accurately classify colorectal adenoma WSIs only with slide-level labels. MIST uses the Swin Transformer as the backbone to extract features of images through self-supervised contrastive learning and uses a dual-stream multiple instance learning network to predict the class of slides. We trained and validated MIST on 666 WSIs collected from 480 colorectal adenoma patients in the Department of Pathology, The Affiliated Drum Tower Hospital of Nanjing University Medical School. These slides contained six common types of colorectal adenomas. The accuracy of external validation on 273 newly collected WSIs from Nanjing First Hospital was 0.784, which was superior to the existing methods and reached a level comparable to that of the local pathologist's accuracy of 0.806. Finally, we analyzed the interpretability of MIST and observed that the lesion areas of interest in MIST were generally consistent with those of interest to local pathologists. In conclusion, MIST is a low-burden, interpretable, and effective approach that can be used in colorectal cancer screening and may lead to a potential reduction in the mortality of CRC patients by assisting clinicians in the decision-making process. © 2022 The Pathological Society of Great Britain and Ireland.

Oral mucosal lesions triage via YOLOv7 models.

BACKGROUND/PURPOSE: The global incidence of lip and oral cavity cancer continues to rise, necessitating improved early detection methods. This study leverages the capabilities of computer vision and deep learning to enhance the early detection and classification of oral mucosal lesions. METHODS: A dataset initially consisting of 6903 white-light macroscopic images collected from 2006 to 2013 was expanded to over 50,000 images to train the YOLOv7 deep learning model. Lesions were categorized into three referral grades: benign (green), potentially malignant (yellow), and malignant (red), facilitating efficient triage. RESULTS: The YOLOv7 models, particularly the YOLOv7-E6, demonstrated high precision and recall across all lesion categories. The YOLOv7-D6 model excelled at identifying malignant lesions with notable precision, recall, and F1 scores. Enhancements, including the integration of coordinate attention in the YOLOv7-D6-CA model, significantly improved the accuracy of lesion classification. CONCLUSION: The study underscores the robust comparison of various YOLOv7 model configurations in the classification to triage oral lesions. The overall results highlight the potential of deep learning models to contribute to the early detection of oral cancers, offering valuable tools for both clinical settings and remote screening applications.

Highly Localized Surface Plasmon Nanolasers via Strong Coupling.

Surface plasmons have robust and strong confinement to the light field which is beneficial for the light-matter interaction. Surface plasmon amplification by stimulated emission of radiation (SPACER) has the potential to be integrated on the semiconductor chip as a compact coherent light source, which can play an important role in further extension of Moore's law. In this study, we demonstrate the localized surface plasmon lasing at room temperature in the communication band using metallic nanoholes as the plasmonic nanocavity and InP nanowires as the gain medium. Optimizing laser performance has been demonstrated by coupling between two metallic nanoholes which adds another degree of freedom for manipulating the lasing properties. Our plasmonic nanolasers exhibit lower power consumption, smaller mode volumes, and higher spontaneous emission coupling factors due to enhanced light-matter interactions, which are very promising in the applications of high-density sensing and photonic integrated circuits.

[Effect of Naotaifang on microglial polarization and glial scar following cerebral ischemia reperfusion injury].

This study aims to investigate the effect of Naotaifang(NTF) on the proteins associated with microglial polarization and glial scar in the rat model of cerebral ischemia reperfusion injury(CIRI). The CIRI model was established by middle cerebral artery occlusion/reperfusion. The 48 successfully modeled rats were randomized into model 7 d, model 14 d, NTF 7 d, and NTF 14 d groups(n=12). In addition, 12 SD rats were selected as the sham group. The NTF group was administrated with NTF suspension at 27 g·kg~(-1)·d~(-1) by gavage, and the sham, model 7 d, and model 14 d groups were administrated with the same volume of normal saline every day by gavage for 7 and 14 days, respectively. After the intervention, Longa score was evaluated. The infarct volume was measured by 2,3,5-triphenyl-2H-tetrazolium chloride(TTC) staining. Morris water maze and open field tests were carried out to evaluate the spatial learning, memory, cognitive function, and anxiety degree of rats. Hematoxylin-eosin(HE) staining was employed to observe the morphological structure and damage of the brain tissue. The immunofluorescence assay was employed to measure the expression of glial fibrillary acidic protein(GFAP) and glial scar. Western blot was employed to determine the protein levels of GFAP, neurocan, phosphacan, CD206, arginase-1(Arg-1), interleukin(IL)-1ß, IL-6, and IL-4. Compared with the sham, model 7 d and model 14 d groups showed cerebral infarction of different degrees, severe pathological injury of cerebral cortex and hippocampus, neurological impairment, reduced spatial learning and memory, cognitive dysfunction, severe anxiety, astrocyte hyperplasia, thickening penumbra glial scar, and up-regulated protein levels of IL-1ß, IL-6, GFAP, neurocan, phosphacan, CD206, and Arg-1(P<0.01). Compared with the model group, NTF 7 d and NTF 14 d groups improved spatial learning, memory, and cognitive function, reduced anxiety, improved nerve function, reduced cerebral infarction volume, reduced astrocyte hyperplasia, thinned penumbra glial scar, down-regulated the protein levels of GFAP, neurocan, phosphacan, IL-6, and IL-1ß, and up-regulated the protein levels of IL-4, CD206, and Arg-1(P<0.05 or P<0.01). NTF exerts a neuroprotective effect on CIRI by inducing the M2 polarization of microglia, inhibiting inflammatory response, and reducing the formation of glial scar.

The role of regulatory T cells in the pathogenesis of acute kidney injury.

The incidence of acute kidney injury (AKI) is on the rise and is associated with high mortality; however, there are currently few effective treatments. Moreover, the relationship between Tregs and other components of the immune microenvironment (IME) in the pathogenesis of AKI remains unclear. We downloaded four publicly accessible AKI datasets, GSE61739, GSE67401, GSE19130, GSE81741, GSE19288 and GSE106993 from the gene expression omnibus (GEO) database. Additionally, we gathered two kidney single-cell sequencing (scRNA-seq) samples from the Department of Organ Transplantation at Zhujiang Hospital of Southern Medical University to investigate chronic kidney transplant rejection (CKTR). Moreover, we also collected three samples of normal kidney tissue from GSE131685. By analysing the differences in immune cells between the AKI and Non-AKI groups, we discovered that the Non-AKI group contained a significantly greater number of Tregs than the AKI group. Additionally, the activation of signalling pathways, such as inflammatory molecules secretion, immune response, glycolytic metabolism, NOTCH, FGF, NF-κB and TLR4, was significantly greater in the AKI group than in the Non-AKI group. Additionally, analysis of single-cell sequencing data revealed that Tregs in patients with chronic kidney rejection and in normal kidney tissue have distinct biology, including immune activation, cytokine production, and activation fractions of signalling pathways such as NOTCH and TLR4. In this study, we found significant differences in the IME between AKI and Non-AKI, including differences in Tregs cells and activation levels of biologically significant signalling pathways. Tregs were associated with lower activity of signalling pathways such as inflammatory response, inflammatory molecule secretion, immune activation, glycolysis.

Near-Infrared II Hyperspectral Imaging Improves the Accuracy of Pathological Sampling of Multiple Cancer Types.

Pathological histology is the "gold standard" for clinical diagnosis of cancer. Incomplete or excessive sampling of the formalin-fixed excised cancer specimen will result in inaccurate histologic assessment or excessive workload. Conventionally, pathologists perform specimen sampling relying on naked-eye observation, which is subjective and limited by human perception. Precise identification of cancer tissue, size, and margin is challenging, especially for lesions with inconspicuous tumors. To overcome the limits of human eye perception (visible: 400-700 nm) and improve the sampling efficiency, in this study, we propose using a second near-infrared window (NIR-II: 900-1700 nm) hyperspectral imaging (HSI) system to assist specimen sampling on the strength of the verified deep anatomical penetration and low scattering characteristics of the NIR-II optical window. We used selected NIR-II HSI narrow bands to synthesize color images for human eye observation and also applied a machine learning-based algorithm on the complete NIR-II HSI data for automatic tissue classification to assist pathologists in specimen sampling. A total of 92 tumor samples were collected, including 7 types. Sixty-two (62/92) samples were used as the validation set. Five experienced pathologists marked the contour of the cancer tissue on conventional color images by using different methods, and compared it with the "gold standard," showing that NIR-II HSI-assisted methods had significant improvements in determining cancer tissue compared with conventional methods (conventional color image with or without X-ray). The proposed system can be easily integrated into the current workflow, with high imaging efficiency and no ionizing radiation. It may also find applications in intraoperative detection of residual lesions and identification of different tissues.

Exploration of immunotherapy in advanced pulmonary lymphoepithelioma-like carcinoma.

Pulmonary lymphoepithelioma-like carcinoma (PLELC) is a rare and histologically distinctive subtype of nonsmall cell lung cancer (NSCLC). High expression of programmed death ligand 1 (PD-L1) and scarcity of druggable driver mutations raise the potential of immunotherapy for advanced PELEC. However, evidence on the clinical impact of immune-checkpoint inhibitors (ICIs) remained limited and unconvincing. The present study retrospectively enrolled advanced PLELC patients who received ICIs either as up-front or salvage therapy in SYSUCC between March 15, 2017 and March 15, 2022. The comparative efficacy of chemoimmunotherapy vs chemotherapy in the first-line setting and chemoimmunotherapy vs ICIs monotherapy in the ≥2 line setting was investigated. A total of 96 patients were finally enrolled; 49 PLELC patients received immunotherapy plus platinum-based chemotherapy, while 45 patients received platinum-based chemotherapy as first-line treatment. Patients with chemoimmunotherapy significantly obtain more survival benefits than those receiving chemotherapy (median progression-free survival [PFS]: 15.6 vs 8.6 months, P = .0015). Additionally, patients with chemoimmunotherapy obtained more PFS benefits than those with ICIs monotherapy in the ≥2 line of therapy (median PFS: 21.7 months vs 7.8 months, P = .094). A significant correlation was observed between prognostic nutritional index (PNI) and favorable treatment outcomes in patients receiving first-line chemoimmunotherapy (median PFS: 17.8 months vs 7.6 months, P < .0001). Likewise, patients in the monocyte-to-lymphocyte ratio (MLR)-high group had significantly shorter PFS than the MLR-low group (median PFS: 11.2 months vs not reached, P = .0009). Our study elucidated the superior efficacy of ICIs therapy, especially chemoimmunotherapy in advanced PLELC, which may provide new insight into the role of immunotherapy in advanced PLELC.

Causal Genetic Variants in Stillbirth.

BACKGROUND: In the majority of cases, the cause of stillbirth remains unknown despite detailed clinical and laboratory evaluation. Approximately 10 to 20% of stillbirths are attributed to chromosomal abnormalities. However, the causal nature of single-nucleotide variants and small insertions and deletions in exomes has been understudied. METHODS: We generated exome sequencing data for 246 stillborn cases and followed established guidelines to identify causal variants in disease-associated genes. These genes included those that have been associated with stillbirth and strong candidate genes. We also evaluated the contribution of 18,653 genes in case-control analyses stratified according to the degree of depletion of functional variation (described here as "intolerance" to variation). RESULTS: We identified molecular diagnoses in 15 of 246 cases of stillbirth (6.1%) involving seven genes that have been implicated in stillbirth and six disease genes that are good candidates for phenotypic expansion. Among the cases we evaluated, we also found an enrichment of loss-of-function variants in genes that are intolerant to such variation in the human population (odds ratio, 2.15; 95% confidence interval [CI], 1.46 to 3.06). Loss-of-function variants in intolerant genes were concentrated in genes that have not been associated with human disease (odds ratio, 2.22; 95% CI, 1.41 to 3.34), findings that differ from those in two postnatal clinical populations that were also evaluated in this study. CONCLUSIONS: Our findings establish the diagnostic utility of clinical exome sequencing to evaluate the role of small genomic changes in stillbirth. The strength of the novel risk signal (as generated through the stratified analysis) was similar to that in known disease genes, which indicates that the genetic cause of stillbirth remains largely unknown. (Funded by the Institute for Genomic Medicine.).

Enhanced sampling in explicit solvent by deep learning module in FSATOOL.

FSATOOL is an integrated molecular simulation and data analysis program. Its old molecular dynamics engine only supports simulations in vacuum or implicit solvent. In this work, we implement the well-known smooth particle mesh Ewald method for simulations in explicit solvent. The new developed engine is runnable on both CPU and GPU. All the existed analysis modules in the program are compatible with the new engine. Moreover, we also build a complete deep learning module in FSATOOL. Based on the module, we further implement two useful trajectory analysis methods: state-free reversible VAMPnets and time-lagged autoencoder. They are good at searching the collective variables related to the conformational transitions of biomolecules. In FSATOOL, these collective variables can be further used to construct a bias potential for the enhanced sampling purpose. We introduce the implementation details of the methods and present their actual performances in FSATOOL by a few enhanced sampling simulations.

Oriented Assembled Prussian Blue Analogue Framework for Confined Catalytic Decomposition of Ammonium Perchlorate.

The design of highly dispersed active sites of hollow materials and unique contact behavior with the components to be catalyzed provide infinite possibilities for exploring the limits of catalyst capacity. In this study, the synthesis strategy of highly open 3-dimensional frame structure Prussian blue analogues (CoFe-PBA) was explored through structure self-transformation, which was jointly guided by template mediated epitaxial growth, restricted assembly and directional assembly. Additionally, good application prospect of CoFe-PBA as combustion catalyst was discussed. The results show that unexpected thermal decomposition behavior can be achieved by limiting AP(ammonium perchlorate) to the framework of CoFe-PBA. The high temperature decomposition stage of AP can be advanced to 283.6 °C and the weight loss rate can reach 390.03% min-1 . In-situ monitoring shows that CoFe-PBA can accelerate the formation of NO and NO2 . The calculation of reaction kinetics proved that catalytic process was realized by increasing the nucleation factor. On this basis, the catalytic mechanism of CoFe-PBA on the thermal decomposition of AP was discussed, and the possible interaction process between AP and CoFe-PBA during heating was proposed. At the same time, another interesting functional behavior to prevent AP from caking was discussed.

Image-free active autofocusing with dual modulation and its application to Fourier single-pixel imaging.

Autofocusing is widely used in applications where sharp image acquisition or projection is needed. Here we report an active autofocusing method for sharp image projection. The method works with wide-field structured illumination and single-pixel detection. To find the focus position, the method illuminates the target object with a set of 3-step phase-shifting Fourier basis patterns repeatedly and collects the backscattered light by using a single-pixel detector through a grating. Dual modulation-dynamic modulation by the time-varying structured illumination and static modulation by the grating-embeds the depth information for the target object in the resulting single-pixel measurements. As such, the focus position can be determined by recovering the Fourier coefficients from the single-pixel measurements and searching for the coefficient with the maximum magnitude. High-speed spatial light modulation not only enables rapid autofocusing but also makes the method work even when the lens system is in continuous motion or the focal length of the lens is continuously adjusted. We experimentally validate the reported method in a self-built digital projector and demonstrate the application of the method in Fourier single-pixel imaging.

Role of antiangiogenic agents in first-line treatment for advanced NSCLC in the era of immunotherapy.

BACKGROUND & OBJECTIVE: "Anti-angiogenetic drugs plus chemotherapy" (anti-angio-chemo) and "immune checkpoint inhibitors plus chemotherapy" (ICI-chemo) are superior to traditional chemotherapy in the first-line treatment of patients with advanced non-small-cell lung cancer (NSCLC). However, in the absence of a direct comparison of ICI-chemo with anti-angio-chemo, the superior one between them has not been decided, and the benefit of adding anti-angiogenetic agents to ICI-chemo remains controversial. This study aimed to investigate the role of antiangiogenic agents for advanced NSCLC in the era of immunotherapy. METHODS: Eligible randomized controlled trials (RCTs) comparing chemotherapy versus therapeutic regimens involving ICIs or anti-angiogenetic drugs were included. Outcomes included progression-free survival (PFS), overall survival (OS), objective response rate (ORR), and rate of grade 3-4 toxicity assessment. R-4.3.1 was utilized to perform the analysis. RESULTS: A total of 54 studies with a sample size of 25,046 were finally enrolled. "Atezolizumab + Bevacizumab + Chemotherapy" significantly improved the ORR compared with "Atezolizumab + Chemotherapy" (Odds ratio (OR) = 2.73, 95% confidence interval (CI): 1.27-5.87). The trend also favored "Atezolizumab + Bevacizumab + Chemotherapy" in PFS and OS (hazard ratio (HR) = 0.71, 95% CI: 0.39-1.31; HR = 0.94, 95% CI: 0.77-1.16, respectively). In addition, "Pembrolizumab + Chemotherapy" and "Camrelizumab + Chemotherapy" significantly prolonged the PFS compared to "Bevacizumab + Chemotherapy" (HR = 0.65, 95% CI: 0.46-0.92; HR = 0.63, 95% CI: 0.41-0.97; respectively). Meanwhile, "Pembrolizumab + Chemotherapy" and "Sintilimab + Chemotherapy" yielded more OS benefits than "Bevacizumab + Chemotherapy" (HR = 0.69, 95% CI: 0.56-0.83; HR = 0.64, 95%CI: 0.46-0.91; respectively). Scheme between "Atezolizumab + Bevacizumab + Chemotherapy" and "Atezolizumab + Chemotherapy" made no significant difference (OR = 1.18, 95%CI: 0.56-2.42) concerning the rate of grade 3-4 toxicity. It seemed that ICI-chemo yielded more improvement in quality-adjusted life-year (QALY) than "Bevacizumab + Chemotherapy" in cost-effectiveness analysis. CONCLUSION: Our results suggest that ICI-chemo is associated with potentially longer survival, better cost-effectiveness outcomes, and comparable safety profiles than anti-angio-chemo. Also, adding bevacizumab to ICI-chemo seemed to provide additional therapeutic benefits without adding treatment burden. Our findings would supplement the current standard of care and help the design of future clinical trials for the first-line treatment of patients with advanced NSCLC.