Dapagliflozin attenuates fat accumulation and insulin resistance in obese mice with polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS), a common endocrine disorder affecting premenopausal women, is associated with various metabolic consequences such as insulin resistance, hyperlipidemia, obesity, and type 2 diabetes mellitus (T2DM). Insulin sensitizers, such as metformin and pioglitazone, though effective, often leads to significant gastrointestinal adverse effects or weight gain, limiting its suitability for women with PCOS. There is an urgent need for safe, effective and affordable agents. Dapagliflozin, a sodium-glucose co-transporter 2 (SGLT2) inhibitor, enhances glucose elimination through urine, thereby reducing body weight and improving glucose and lipid metabolism. Nevertheless, it is not currently recommended as a therapeutic option for PCOS in clinical guidelines. In this study, we systematically examined the impact of dapagliflozin on an obese PCOS mouse model, focusing on alterations in glucose metabolism, adipose tissue morphology, and plasma lipid profile. Obese PCOS was induced in mice by continuous dihydrotestosterone (DHEA) injections over 21 days and high-fat diet (HFD) feeding. PCOS mice were then orally gavaged with dapagliflozin (1 mg/kg), metformin (50 mg/kg), or vehicle daily for 8 weeks, respectively. Our results demonstrated that dapagliflozin significantly prevented body weight gain and reduced fat mass in obese PCOS mice. Meanwhile, dapagliflozin treatment improved glucose tolerance and increased insulin sensitivity compared to the control PCOS mice. Furthermore, dapagliflozin significantly improved adipocyte accumulation and morphology in white adipose tissue, resulting in a normalized plasma lipid profile in PCOS mice. In conclusion, our results suggest that dapagliflozin is an effective agent in managing glucose and lipid metabolism disorders in obese PCOS mice.

Exploring the underlying mechanisms of enteritis impact on golden pompano (Trachinotus ovatus) through multi-omics analysis.

Enteritis posed a significant health challenge to golden pompano (Trachinotus ovatus) populations. In this research, a comprehensive multi-omics strategy was implemented to elucidate the pathogenesis of enteritis by comparing both healthy and affected golden pompano. Histologically, enteritis was characterized by villi adhesion and increased clustering after inflammation. Analysis of the intestinal microbiota revealed a significant increase (P < 0.05) in the abundance of specific bacterial strains, including Photobacterium and Salinivibrio, in diseased fish compared to the healthy group. Metabolomic analysis identified 5479 altered metabolites, with significant impacts on terpenoid and polyketide metabolism, as well as lipid metabolism (P < 0.05). Additionally, the concentrations of several compounds such as calcitetrol, vitamin D2, arachidonic acid, and linoleic acid were significantly reduced in the intestines of diseased fish post-enteritis (P < 0.05), with the detection of harmful substances such as Efonidipine. In transcriptomic profiling, enteritis induced 68 upregulated and 73 downregulated genes, predominantly affecting steroid hormone receptor activity (P < 0.05). KEGG pathway enrichment analysis highlighted upregulation of SQLE and CYP51 in steroidogenesis, while the HSV-1 associated MHC1 gene exhibited significant downregulation. Integration of multi-omics results suggested a potential pathogenic mechanism: enteritis may have resulted from concurrent infection of harmful bacteria, specifically Photobacterium and Salinivibrio, along with HSV-1. Efonidipine production within the intestinal tract may have blocked certain calcium ion channels, leading to downregulation of MHC1 gene expression and reduced extracellular immune recognition. Upregulation of SQLE and CYP51 genes stimulated steroid hormone synthesis within cells, which, upon binding to G protein-coupled receptors, influenced calcium ion transport, inhibited immune activation reactions, and further reduced intracellular synthesis of anti-inflammatory substances like arachidonic acid. Ultimately, this cascade led to inflammation progression, weakened intestinal peristalsis, and villi adhesion. This study utilized multi-level omics detection to investigate the pathological symptoms of enteritis and proposed a plausible pathogenic mechanism, providing innovative insights into enteritis verification and treatment in offshore cage culture of golden pompano.

Reassessing determinants of urban energy intensity in China: insights from controllable and uncontrollable factors.

This study adopts a new approach to reassess the factors influencing urban energy intensity in China. Initially, the factors impacting energy intensity are classified into controllable and uncontrollable categories. Subsequently, employing a single-factor multi-stage method combined with the Adaboost method, 289 Chinese cities are categorized based on uncontrollable factors to eliminate the influence of inherent differences on energy intensity. Finally, panel data regression analyses are conducted using data from 289 Chinese cities between 2005 and 2016, individually for each city type, to evaluate the extent to which controllable factors contribute to energy intensity. The findings indicate that (1) heightened energy prices, an increased share of electricity consumption, and a greater proportion of centralized heating significantly influence the reduction of energy intensity across all city types; (2) to optimize energy consumption, each city type should adopt specific strategies. For instance, cities located in resource-rich heating regions with low economic outputs can reduce their energy intensity by increasing electricity consumption, while cities with high economic outputs can decrease their energy intensity by increasing natural gas consumption. The findings of this study carry substantial implications for the Chinese government in shaping targeted energy policies tailored to different city types.

Public knowledge, perception of and willingness-to-accept nuclear energy in China: Evidence from a representative national survey.

The Chinese government promotes nuclear energy development in the context of mitigating climate change. However, the large-scale development is still facing challenges related to the knowledge gap among the general public and the potential "not-in-my-back-yard" objection. Based on a representative national survey, we analyze Chinese people's knowledge and perceptions of nuclear energy and estimate their willingness-to-accept the potential risks of new nuclear programs in neighborhoods via the Contingent Valuation Method. Generally, more than half of people do not know anything about nuclear energy. The main factors influencing public knowledge are identified, such as the residential distance to existing nuclear power stations and the frequency of internet use. Moreover, approximately 12% of individuals with some knowledge seem to be willing to accept new nuclear power plants in their neighborhoods with no compensation needed. Specifically, the perceptions of nuclear risks and pollution from fossil fuels are significant factors influencing people's acceptance of nuclear energy. Although public knowledge does not directly influence acceptance, more knowledge seems to reduce risk perception and increase benefit perception. The residential distance to exiting nuclear stations has limited effects on people's acceptance of newly planned nuclear programs for those living in the same county with some knowledge. In general, a typical Chinese household is willing to accept USD $5.66 every month or USD $67.97 every year to bear the potential risks of the new nuclear program in neighborhoods. Significant practical implications that can be transferable to other new energy technologies and countries or regions are provided.

2D superlattices via interfacial self-assembly of polymer-grafted Au nanoparticles.

Nanoparticle (NP) superlattices are periodic arrays of nanoscale building blocks. Because of the collective effect between functional NPs, NP superlattices can exhibit exciting new properties that are distinct from those of individual NPs or corresponding bulk materials. In particular, two-dimensional (2D) NP superlattices have attracted increasing attention due to their emerging applications in micro/opto-electronics, catalysis, sensing, and other fields. Among various preparation methods, evaporation-induced interfacial self-assembly has become the most popular method for preparing 2D NP superlattices because it is a simple, low-cost, and scalable process that can be widely applied to various NPs. Introducing soft ligands, such as polymers, can not only provide convenience in controlling the self-assembly process and tuning superlattice structures but also improve the properties of 2D NP superlattices. This feature article focuses on the methods of evaporation-induced self-assembly of polymer-grafted Au NPs into free-standing 2D NP superlattice films at air/liquid interfaces and 2D NP superlattice coatings on substrates, followed by studies on in situ tracking of the self-assembly evolution process through small-angle X-ray scattering. Their application in nano-floating gate memory devices is also included. Finally, the challenges and perspectives of this direction are discussed.

Identification of active compounds of traditional chinese medicine derived from maxing shigan decoction for COVID-19 treatment: a meta-analysis and in silico study.

BACKGROUND: Coronavirus 2019 (COVID-19) poses a serious threat to human health. In China, traditional Chinese medicine (TCM), mainly based on the Maxing Shigan decoction (MXSGD), is used in conjunction with western medicine to treat COVID-19. RESEARCH DESIGN AND METHODS: We conducted a network meta-analysis to investigate whether MXSGD-related TCM combined with western medicine is more effective in treating COVID-19 compared to western medicine alone. Additionally, using network pharmacology, cross-docking, and molecular dynamics (MD) simulation to explore the potential active compounds and possible targets underlying the therapeutic effects of MXSGD-related TCM. RESULTS: MXSGD-related TCM combined with western medicine was better for treating COVID-19 compared to western medicine alone. Network pharmacological analysis identified 43 shared ingredients in the MXSGD-related TCM prescriptions and 599 common target genes. Cross-docking of the 43 compounds with 154 proteins that matched these genes led to the identification of 60 proteins. Pathway profiling revealed that the active ingredients participated in multiple signaling pathways that contribute to their efficacy. Molecular docking and MD simulation demonstrated that MOL007214, the most promising molecule, could stably bind to the active site of SARS-CoV-2 3CLpro. CONCLUSION: This study demonstrates the important role of MXSGD-related TCM in the treatment of COVID-19.

Image-Processing-Based Subway Tunnel Crack Detection System.

With the increase in urban rail transit construction, instances of tunnel disease are on the rise, and cracks have become the focus of tunnel maintenance and management. Therefore, it is essential to carry out crack detection in a timely and efficient manner to not only prolong the service life of the tunnel but also reduce the incidence of accidents. In this paper, the design and structure of a tunnel crack detection system are analyzed. On this basis, this paper proposes a new method for crack identification and feature detection using image processing technology. This method fully considers the characteristics of tunnel images and the combination of these characteristics with deep learning, while a deep convolutional network (Single-Shot MultiBox Detector (SSD)) is proposed based on deep learning for object detection in complex images. The experimental results show that the test set accuracy and training set accuracy of the support vector machine (SVM) in the classification comparison test are up to 88% and 87.8%, respectively; while the test accuracy of Alexnet's deep convolutional neural network-based classification and identification is up to 96.7%, and the training set accuracy is up to 97.5%. It can be seen that this deep convolutional network recognition algorithm based on deep learning and image processing is better and more suitable for the detection of cracks in subway tunnels.

Design, synthesis, and evaluation of novel benzoylhydrazone derivatives as Nur77 modulators with potent antitumor activity against hepatocellular carcinoma.

Nur77 modulators have emerged as a promising therapeutic approach for hepatocellular carcinoma. In this study, a structure-based rational drug design approach was used to design and synthesise a series of 4-((8-hydroxy-2-methylquinolin-4-yl)amino)benzoylhydrazone derivatives based on the binding characteristics of our previously reported 10g and the native ligand 3NB at the binding Site C of Nur77. Cell-based cytotoxicity assays revealed that compound TMHA37 demonstrated the highest cytotoxicity against all tested cancer cells. The induced fit docking and binding pose metadynamics simulation suggested that TMHA37 was the most promising Nur77 binder at Site C. Molecular dynamics simulation validated the stable binding of TMHA37 to Nur77's Site C but not to Sites A or B. Specifically, TMHA37 bound strongly to Nur77-LBD (KD = 445.3 nM) and could activate Nur77's transcriptional activity. Furthermore, TMHA37 exhibited antitumor effects by blocking the cell cycle at G2/M phase and inducing cell apoptosis in a Nur77-dependent manner.

Identification of the Genetic Influence of SARS-CoV-2 Infections on IgA Nephropathy Based on Bioinformatics Method.

INTRODUCTION: Coronavirus disease-2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. It was initially detected in Wuhan, China, in December 2019. In March 2020, the World Health Organization (WHO) declared COVID-19 a global pandemic. Compared to healthy individuals, patients with IgA nephropathy (IgAN) are at a higher risk of SARS-CoV-2 infection. However, the potential mechanisms remain unclear. This study explores the underlying molecular mechanisms and therapeutic agents for the management of IgAN and COVID-19 using the bioinformatics and system biology way. METHODS: We first downloaded GSE73953 and GSE164805 from the Gene Expression Omnibus (GEO) database to obtain common differentially expressed genes (DEGs). Then, we performed the functional enrichment analysis, pathway analysis, protein-protein interaction (PPI) analysis, gene regulatory networks analysis, and potential drug analysis on these common DEGs. RESULTS: We acquired 312 common DEGs from the IgAN and COVID-19 datasets and used various bioinformatics tools and statistical analyses to construct the PPI network to extract hub genes. Besides, we performed gene ontology (GO) and pathway analyses to reveal the common correlation between IgAN and COVID-19. Finally, on the basis of common DEGs, we determined the interactions between DEGs-miRNAs, the transcription factor-genes (TFs-genes), protein-drug, and gene-disease networks. CONCLUSION: We successfully identified hub genes that may act as biomarkers of COVID-19 and IgAN and also screened out some potential drugs to provide new ideas for COVID-19 and IgAN treatment.

Effects of China's low-carbon policy under stochastic shocks-a multi-agent DSGE model analysis.

China has announced a target of achieving carbon peaking by 2030 and carbon neutrality by 2060. Therefore, it is important to assess the economic impacts and emission reduction effects of China's low-carbon policies. In this paper, a multi-agent dynamic stochastic general equilibrium (DSGE) model is established. We analyze the effects of carbon tax and carbon cap-and-trade policies under both deterministic and stochastic conditions, as well as their ability to cope with stochastic shocks. We found that (1) from a deterministic perspective, these two policies have the same effect. Every 1% cut in CO2 emissions will bring a 0.12% output loss, a 0.5% drop in demand for fossil fuels, and a 0.05% rise in demand for renewable energy; (2) from a stochastic perspective, effects of these two policies are different. This is mainly because economic uncertainty does not change the cost of CO2 emissions under a carbon tax policy, but it does change the price of CO2 quotas and the emission reduction behaviors under a carbon cap-and-trade policy; (3) from an economic volatility perspective, both two policies can act as automatic stabilizers. Compared to a carbon tax, a cap-and-trade policy can better ease economic fluctuations. The results of this study provide implications for policy-making.

Sunitinib versus imatinib dose escalation after failure of imatinib standard dose in patients with advanced Gastrointestinal stromal tumors - a real-world multi-center study.

BACKGROUND: Whether to escalate imatinib dosage or directly switch to sunitinib in gastrointestinal stromal tumors (GISTs) failing on standard dose 400 mg/d of imatinib is still controversial. METHODS: We evaluated progression-free survival (PFS), overall survival (OS), and time to sunitinib failure (TTSF) of patients selecting imatinib dose escalation or directly switching to sunitinib after the failure of imatinib 400 mg/d therapy from 3 tertery referring centers between January 2008 to December 2016. RESULTS: A total of 240 patients receiving sunitinib (37.5 mg continuous daily dose or 50 mg 4 weeks on with 2 weeks off) for at least 8 weeks were examined. After failure on imatinib 400 mg/d, 100 (49.3%) patients had dose escalation to 600 mg or 800 mg per day (IM group, imatinib group), and 103 (50.7%) directly switched to sunitinib (SU group, sunitinib group). The PFS in the SU and IM groups was 12 months and 5.0 months (P < 0.001), respectively. TTSF or OS in both groups was not statistically significantly different. CONCLUSIONS: After the progression of imatinib standard-dose treatment in recurrent/metastatic GISTs, the PFS of patients directly switching to sunitinib was significantly longer compared with the PFS of patients with imatinib dose escalation. However, when the patients continued with sunitinib therapy after the failure of IM dose escalation, TTSF and OS in the IM group were similar to those in the SU group. Further exploration of the characteristics of the population benefiting from imatinib dose escalation are warranted.

Predictors for short-term successful weaning from continuous renal replacement therapy: a systematic review and meta-analysis.

The systemic review and meta-analysis aimed to identify the predictors for short-term successful weaning from CRRT in severe AKI patients. PubMed, Embase, the Cochrane Library, and grey literature were searched for relevant studies investigating variables for short-term successful weaning from CRRT to August 2022. Our criteria included patients with AKI who required CRRT but excluded patients with kidney failure. The pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated using fixed-effect (I2≤50% and P-value of the Q statistic > 0.1) or random-effect models (I2>50% or p-value of the Q statistic ≤ 0.1) as appropriate. Our search yielded 11 studies and described 11 variables. The pooled analysis showed that chronic kidney disease (OR = 0.638, 95% CI: 0.491-0.829), CRRT duration (OR = 0.913, 95% CI: 0.882-0.946), and urine output at the cessation of CRRT (per 100 mL/day increase) (OR = 1.084, 95% CI: 1.061-1.108) were predictive factors for short-term successful weaning from CRRT. Male (OR = 0.827, 95% CI: 0.627-1.092), diabetes mellitus (OR = 0.970, 95% CI: 0.761-1.237), and sepsis (OR = 0.911, 95% CI: 0.717-1.158) were unrelated to the short-term weaning from CRRT. The relationship between hypertension, use of vasopressors or inotropes at the starting of CRRT, use of vasopressors or inotropes at the cessation of CRRT, use of diuretics at the cessation of CRRT, serum creatinine at the cessation of CRRT, and short-term weaning from CRRT remains unclear. Additional prospective studies are needed to evaluate this relationship further.

Identification of potential ATP-competitive cyclin-dependent kinase 1 inhibitors: De novo drug generation, molecular docking, and molecular dynamics simulation.

Cyclin-dependent kinases 1 (CDK1) has been identified as a potential target for the search for new antitumor drugs. However, no clinically effective CDK1 inhibitors are now available for cancer treatment. Therefore, this study aimed to offer potential CDK1 inhibitors using de novo drug generation, molecular docking, and molecular dynamics (MD) simulation studies. We first utilized the BREED algorithm (a de novo drug generation approach) to produce a novel library of small molecules targeting CDK1. To initially obtain novel potential CDK1 inhibitors with favorable physicochemical properties and excellent druggability, we performed a virtual rule-based rational drug screening on our generated library and found ten initial hits. Then, the molecular interactions and dynamic stability of these ten initial hits and CDK1 complexes during their all-atom MD simulations (total 18 µs) and binding pose metadynamics simulations were investigated, resulting in five final hits. Furthermore, another MD simulation (total 2.1 µs) with different force fields demonstrated the binding ability of the five hits to CDK1. It was found that these five hits, CBMA001 (ΔG = -29.88 kcal/mol), CBMA002 (ΔG = -34.89 kcal/mol), CBMA004 (ΔG = -32.47 kcal/mol), CBMA007 (ΔG = -31.16 kcal/mol), and CBMA008 (ΔG = -34.78 kcal/mol) possessed much greater binding affinity to CDK1 than positive compound Flavopiridol (FLP, ΔG = -25.38 kcal/mol). Finally, CBMA002 and CBMA004 were identified as excellent selective CDK1 inhibitors in silico. Together, this study provides a workflow for rational drug design and two promising selective CDK1 inhibitors that deserve further investigation.

Combination of Type I and II tyrosine kinase inhibitors-avapritinib and sunitinib-in refractory gastrointestinal stromal tumor after failure to multi-line therapy: a case report.

Background: Tyrosine kinase inhibitors (TKIs) are currently the main treatment choice for gastrointestinal stromal tumors (GISTs). However, the long-term use of TKIs can lead to drug resistance. There is no study or clinical report of combination therapies of TKIs that have been approved for marketing. Combination pharmacotherapy is a new approach for patients who do not respond to monotherapy. This case provides a reference value for selective combination of TKIs in treating advanced GIST. Case Description: In this article, we report the case of a 55-year-old female who was diagnosed with duodenal GIST in April 2018 and underwent R0 resection. KIT exon 9 mutation was detected. The patient had disease recurrence with multiple abdominal metastases during imatinib adjuvant therapy after 27 months, and failure to 2nd-line sunitinib treatment after 6 months. She underwent a cytoreductive surgery (R1), and the postoperative mutation analysis suggested KIT exon 9 mutation, with newly found secondary KIT_exon16_p. L783V mutation and other mutations on TP53, POT1, and SETD2, etc. The patient experienced short-term tumor control of standard 3rd-line therapy of regorafenib and the rapid progression of the 4th-line of ripretinib afterwards. Different TKI combination therapies (i.e., ripretinib plus sunitinib, ripretinib plus avapritinib and avapritinib plus sunitinib) were administered to the patient sequentially. Ripretinib plus sunitinib led to stable disease but was discontinued due to intolerable adverse effects. Finally, the patient received a combination regimen of avapritinib plus sunitinib. The patient's tumor showed continuous shrinking in 2 consecutive computed tomography scan evaluations within 4 months with acceptable side effects. Conclusions: Combined type I and type II TKIs of avapritinib combined with sunitinib therapy achieved tumor regression for a heavily multi-line treated patient. Our case provides a reference for a savage treatment choice in refractory GISTs after failure to all standard treatment.

Unraveling the Mechanism of Zhibaidihuang Decoction against IgA Nephropathy Using Network Pharmacology and Molecular Docking Analyses.

Zhibaidihuang Decoction (ZBDHD) is a traditional Chinese medicine with immense potential to treat IgA nephropathy. However, its core ingredients and representative mechanism remain unclear. In this study, we uncovered the key component and underlying mechanisms of ZBDHD for IgA nephropathy by applying network pharmacology and molecular docking approaches. This was done by first identifying the active ingredients and, subsequently, their corresponding gene targets in ZBDHD with the help of the Traditional Chinese Medicine Systems Pharmacology and analysis platform (TCMSP) database, thereby constructing the drug-compound-target network. The IgA nephropathy-associated genes were then identified using GeneCards, Drugbank, and OMIM databases. The overlapped targets were later obtained to establish Protein-Protein Interaction (PPI) networks, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, we performed molecular docking among active compounds and hub genes, and thereby verified the key compound of ZBDHD. The drug-compound-gene network consisted of 289 nodes and 1,113 edges. The top four active ingredients were beta-sitosterol, kaempferol, quercetin and stigmasterol. The top five hub genes in the PPI network were AKT1, ILB1, IL-6, TNF, and TP53. Molecular docking results could demonstrate that there was high affinity among active compounds and the core targets, while quercetin may possibly be the key compound of ZBDHD. We first identified the positive compound and the candidate molecular mechanisms of ZBDHD in an IgA nephropathy treatment and discovered that quercetin might be the core compound of ZBDHD in the treatment of IgA nephropathy.

Quantifying the drivers of PM2.5 variation in Shenyang, China: A factor decomposition model.

Taking variations in PM2.5 as indicators for assessing the performance of authority in air quality management will probably lead to misjudgment, as PM2.5 concentration is affected not only by anthropogenic emissions but also by uncontrollable circumstances. To solve this problem, we proposed a decomposition method to attribute the variations in PM2.5 to the contributions of meteorological conditions, cross-regional transports of pollutants, secondary aerosols, and local emissions. This method estimated the relationship between PM2.5 concentration and the various influencing factors using a semi-parametric generalized additive model. A case study was conducted in Shenyang, a heavily polluted city in northeast China, based on up to 595,000 hourly data samples from 2014 to 2017. The decomposition results indicated that the average PM2.5 in 2017 decreased by 39.80% compared with 2014, far exceeding the government's target of 15%, but only 11.79% of the decrease was benefited from the control of local emissions. The severe pollution event that occurred in November 2015 was induced by the combination of massive emissions from heating and meteorological conditions conducive to pollutant accumulation. Furthermore, the approach we proposed can be extended to any location that has monitoring data on air pollutant concentrations and meteorological conditions.

Efficacy of immune checkpoint inhibitors in EGFR-Mutant NSCLC patients with EGFR-TKI resistance: A systematic review and meta-analysis.

Background: Epidermal growth factor receptor (EGFR) mutations are common in patients with non-small-cell lung cancer (NSCLC), particularly in Asian populations. Tyrosine kinase inhibitors (TKIs) are a first-line treatment in patients with mutant EGFR, but their use is often accompanied by drug resistance, which leads to disease progression. Chemotherapy and immunotherapy are the main treatment options after progression. The efficacy of immune checkpoint inhibitors (ICIs) and their combination therapy in patients with EGFR-TKI resistant is not clear. It is thus necessary to evaluate the efficacy of ICIs and ICI-based combination therapies in patients with EGFR-TKI-resistant NSCLC. Methods: We searched for randomized controlled trials (RCTs) comparing ICI therapy alone or in combination versus other therapies using PubMed, the Cochrane Library, Web of Science, EMBASE, MEDLINE, ClinicalTrials.gov, and several international conference databases, from database inception to 10 March 2022. The hazard ratio (HR) and 95% confidence interval (95% CI) for median overall survival (OS) and median progression-free survival (PFS) were evaluated. Odds ratio (OR), risk ratio (RR), and 95% CI were used as effect indicators for objective response rate (ORR) and safety data. Results: Seven eligible RCTs were included in the present meta-analysis. The results showed that neither ICIs nor combination therapy prolonged median OS in EGFR-TKI resistant NSCLC patients (HR = 1.04, 95% CI: 0.84-1.29, p = 0.73). However, compared with the control group, the patients treated with ICI-based combination therapy had better PFS (HR = 0.62, 95% CI: 0.45-0.86, p = 0.004) and ORR (OR = 1.84, 95% CI: 1.28-2.66, p = 0.001). Conclusion: ICI monotherapy did not improve the OS or PFS of NSCLC patients previously treated with EGFR-TKIs, whereas patients treated with ICI-based combination therapy had better PFS compared with those receiving conventional chemotherapy, indicating that this therapy could be offered to patients with EGFR-mutant NSCLC after progression following TKI treatment. There was no significant difference in all-grade treatment-related adverse events (TRAEs) between the combination therapy group and the control group. However, a higher incidence of discontinuation due to TRAEs was observed; this requires attention in future studies. The results of this meta-analysis provide a reference for clinical practice and future trial design. PROSPERO registration number: CRD42021282207.

Research Advances of Injectable Functional Hydrogel Materials in the Treatment of Myocardial Infarction.

Myocardial infarction (MI) has become one of the serious diseases threatening human life and health. However, traditional treatment methods for MI have some limitations, such as irreversible myocardial necrosis and cardiac dysfunction. Fortunately, recent endeavors have shown that hydrogel materials can effectively prevent negative remodeling of the heart and improve the heart function and long-term prognosis of patients with MI due to their good biocompatibility, mechanical properties, and electrical conductivity. Therefore, this review aims to summarize the research progress of injectable hydrogel in the treatment of MI in recent years and to introduce the rational design of injectable hydrogels in myocardial repair. Finally, the potential challenges and perspectives of injectable hydrogel in this field will be discussed, in order to provide theoretical guidance for the development of new and effective treatment strategies for MI.

A High-Quality, Chromosome-Level Genome Provides Insights Into Determinate Flowering Time and Color of Cotton Rose (Hibiscus mutabilis).

Hibiscus mutabilis (cotton rose) is a deciduous shrub or small tree of the Malvaceae family. Here, we report a chromosome-scale assembly of the H. mutabilis genome based on a combination of single-molecule sequencing and Hi-C technology. We obtained an optimized assembly of 2.68 Gb with a scaffold N50 length of 54.7 Mb. An integrated strategy of homology-based, de novo, and transcriptome-based gene predictions identified 118,222 protein-coding genes. Repetitive DNA sequences made up 58.55% of the genome, and LTR retrotransposons were the most common repetitive sequence type, accounting for 53.15% of the genome. Through the use of Hi-C data, we constructed a chromosome-scale assembly in which Nanopore scaffolds were assembled into 46 pseudomolecule sequences. We identified important genes involved in anthocyanin biosynthesis and documented copy number variation in floral regulators. Phylogenetic analysis indicated that H. mutabilis was closely related to H. syriacus, from which it diverged approximately 15.3 million years ago. The availability of cotton rose genome data increases our understanding of the species' genetic evolution and will support further biological research and breeding in cotton rose, as well as other Malvaceae species.