Atomically dispersed Iridium on Mo2C as an efficient and stable alkaline hydrogen oxidation reaction catalyst.

Hydroxide exchange membrane fuel cells (HEMFCs) have the advantages of using cost-effective materials, but hindered by the sluggish anodic hydrogen oxidation reaction (HOR) kinetics. Here, we report an atomically dispersed Ir on Mo2C nanoparticles supported on carbon (IrSA-Mo2C/C) as highly active and stable HOR catalysts. The specific exchange current density of IrSA-Mo2C/C is 4.1 mA cm-2ECSA, which is 10 times that of Ir/C. Negligible decay is observed after 30,000-cycle accelerated stability test. Theoretical calculations suggest the high HOR activity is attributed to the unique Mo2C substrate, which makes the Ir sites with optimized H binding and also provides enhanced OH binding sites. By using a low loading (0.05 mgIr cm-2) of IrSA-Mo2C/C as anode, the fabricated HEMFC can deliver a high peak power density of 1.64 W cm-2. This work illustrates that atomically dispersed precious metal on carbides may be a promising strategy for high performance HEMFCs.

The role of FERMT2 in the tumor microenvironment and immunotherapy in pan-cancer using comprehensive single-cell and bulk sequencing.

FERMT2 has been identified as a participant in integrin-linked kinase signaling pathways, influencing epithelial-mesenchymal transition and thereby affecting tumor initiation, progression, and invasion. While the character of FERMT2 in the tumor microenvironment (TME) as well as its implications for immunotherapy remain unclear. Thus, we conducted a comprehensive analysis to assess the prognostic significance of FERMT2 using Kaplan-Meier analysis. In addition, we employed enrichment analysis to uncover potential underlying molecular mechanisms. Using "Immunedeconv" package, we evaluated the immune characteristics of FERMT2 within TME. Furthermore, we determined the expression levels of FERMT2 in various cell types within TME, based on single-cell sequencing data. To confirm the co-expression of FERMT2 and markers of cancer-associated fibroblasts (CAFs), we performed multiplex immunofluorescence staining on tissue paraffin sections across various cancer types. Our analysis disclosed a significant correlation between elevated FERMT2 expression and unfavorable prognosis in specific cancer types. Furthermore, we identified a strong correlation between FERMT2 expression and diverse immune-related factors, including immune checkpoint molecules, immune cell infiltration, microsatellite instability (MSI), and tumor mutational burden (TMB). Additionally, there was a significant correlation between FERMT2 expression and immune-related pathways, particularly those associated with activating, migrating, and promoting the growth of fibroblasts in diverse cancer types. Interestingly, we observed consistent co-expression of FERMT2 in both malignant tumor cells and stromal cells, particularly within CAFs. Notably, our findings also indicated that FERMT2, in particular, exhibited elevated expression levels within tumor tissues and co-expressed with α-SMA in CAFs based on the multiplex immunofluorescence staining results.

Influential Metrics Estimation and Dynamic Frequency Selection Based on Two-Dimensional Mapping for JPEG-Reversible Data Hiding.

JPEG Reversible Data Hiding (RDH) is a method designed to extract hidden data from a marked image and perfectly restore the image to its original JPEG form. However, while existing RDH methods adaptively manage the visual distortion caused by embedded data, they often neglect the concurrent increase in file size. In rectifying this oversight, we have designed a new JPEG RDH scheme that addresses all influential metrics during the embedding phase and a dynamic frequency selection strategy with recoverable frequency order after data embedding. The process initiates with a pre-processing phase of blocks and the subsequent selection of frequencies. Utilizing a two-dimensional (2D) mapping strategy, we then compute the visual distortion and file size increment (FSI) for each image block by examining non-zero alternating current (AC) coefficient pairs (NZACPs) and their corresponding run lengths. Finally, we select appropriate block groups based on the influential metrics of each block group and proceed with data embedding by 2D histogram shifting (HS). Extensive experimentation demonstrates how our method's efficiently and consistently outperformed existing techniques with a superior peak signal-to-noise Ratio (PSNR) and optimized FSI.

Circumventing drug resistance in gastric cancer: A spatial multi-omics exploration of chemo and immuno-therapeutic response dynamics.

BACKGROUND: Gastric Cancer (GC) characteristically exhibits heterogeneous responses to treatment, particularly in relation to immuno plus chemo therapy, necessitating a precision medicine approach. This study is centered around delineating the cellular and molecular underpinnings of drug resistance in this context. METHODS: We undertook a comprehensive multi-omics exploration of postoperative tissues from GC patients undergoing the chemo and immuno-treatment regimen. Concurrently, an image deep learning model was developed to predict treatment responsiveness. RESULTS: Our initial findings associate apical membrane cells with resistance to fluorouracil and oxaliplatin, critical constituents of the therapy. Further investigation into this cell population shed light on substantial interactions with resident macrophages, underscoring the role of intercellular communication in shaping treatment resistance. Subsequent ligand-receptor analysis unveiled specific molecular dialogues, most notably TGFB1-HSPB1 and LTF-S100A14, offering insights into potential signaling pathways implicated in resistance. Our SVM model, incorporating these multi-omics and spatial data, demonstrated significant predictive power, with AUC values of 0.93 and 0.84 in the exploration and validation cohorts respectively. Hence, our results underscore the utility of multi-omics and spatial data in modeling treatment response. CONCLUSION: Our integrative approach, amalgamating mIHC assays, feature extraction, and machine learning, successfully unraveled the complex cellular interplay underlying drug resistance. This robust predictive model may serve as a valuable tool for personalizing therapeutic strategies and enhancing treatment outcomes in gastric cancer.

MEF2D facilitates liver metastasis of gastric cancer cells through directly inducing H1X under IL-13 stimulation.

Liver metastasis is the most common metastatic occurrence in gastric cancer patients, although the precise mechanism behind it remains unclear. Through a combination of proteomics and quantitative RT-PCR, our study has revealed a significant correlation between the upregulation of myocyte enhancer factor-2D (MEF2D) and both distant metastasis and poor prognosis in gastric cancer patients. In mouse models, we observed that overexpressing or knocking down MEF2D in gastric cancer cells respectively promoted or inhibited liver metastasis. Furthermore, our research has demonstrated that MEF2D regulates the transcriptional activation of H1X by binding to the H1X promoter. This regulation leads to the upregulation of H1X, which, in turn, promotes the in vivo metastasis of gastric cancer cells along with the upregulation of the downstream gene ß-CATENIN. Additionally, we found that the expression of MEF2D and H1X at both mRNA and protein levels can be induced by the inflammatory factor IL-13, and this induction exhibits a time gradient dependence. In human gastric cancer tissues, the expression of IL13RA1, the receptor for IL-13, positively correlates with the expression of MEF2D and H1X. IL13RA1 has been identified as an intermediate receptor through which IL-13 regulates MEF2D. In conclusion, our findings suggest that MEF2D plays a crucial role in promoting liver metastasis of gastric cancer by upregulating H1X and downstream target ß-CATENIN in response to IL-13 stimulation. Targeting MEF2D could therefore be a promising therapeutic strategy for the clinical management of gastric cancer. STATEMENT OF SIGNIFICANCE: MEF2D promotes its transcriptional activation in gastric cancer cells by binding to the H1X promoter and is upregulated by IL-13-IL13RA1, thereby promoting distant metastasis of gastric cancer.

Surgical Resection of Giant Chest Wall Chondrosarcoma Combined with Sandwich Chest Wall Reconstruction in One Case.

INTRODUCTION: Primary chest wall tumors account for 5% of all thoracic neoplasms and 1% of all primary tumors. Chondrosarcoma is a rare solid tumor, with an annual incidence of <0.5 per million people per year. It predominantly occurs in the pelvis and femur, occasionally occurs in flat bones such as the sternum and ribs, and rarely invades lung tissue. Chest wall chondrosarcomas represent only 5-15% of all chondrosarcomas. Radical surgery often leads to a large range of chest wall defects, especially when the range exceeds 6 cm × 6 cm and involves the sternum, spine, or multiple consecutive ribs. The reconstruction of the chest wall bone should be considered to restore the integrity and stability of the chest, prevent chest wall softening and abnormal breathing, and ensure the stability of respiratory circulation. Chest wall reconstruction can help restore thoracic hardness and integrity, prevent lung hernia and abnormal breathing, while also ensuring a positive aesthetic outcome. The chest wall reconstruction includes reconstruction of the pleura, bony structures, and soft tissues. CASE REPORT: In our case of an adult male, after the resection of the third and fourth anterior rib chondrosarcoma, the common anatomical plate was shaped and fixed to the stump of the third rib with screws to ensure the stability of the thorax while retaining the mobility of the thorax. After applying hernia mesh pruning, the chest wall defect was stitched to complete the pleural reconstruction of the defect area. This procedure can effectively maintain the stability of the pleural cavity, provide more effective support for the chest wall soft tissue, and promote the recovery of upper limb function and lung function. CONCLUSION: The radical surgery of giant chest wall chondrosarcoma often leads to a large range of chest wall defects. Chest wall reconstruction needs to be carried out at the same time to restore the integrity and stability of the chest wall, to avoid chest wall softening and abnormal breathing, and to ensure the stability of respiratory circulation. Using the "sandwich" method for chest wall reconstruction, in which an anatomical plate is combined with hernia mesh and muscle soft tissue, and during which pleura, bony structure, and soft tissues are reconstructed, can provide more effective support for chest wall soft tissue, effectively prevent postoperative muscle tissue collapse, avoid postoperative abnormal breathing, and promote the recovery of postoperative upper limb function and lung function. It is a very effective method for chest wall reconstruction.

FTO-mediated autophagy inhibition promotes non-small cell lung cancer progression by reducing the stability of SESN2 mRNA.

The role of fat mass and obesity-associated protein (FTO), an N6-methyladenosine (m6A) demethylase, in non-small cell lung cancer (NSCLC) has recently received widespread attention. However the underlying mechanisms of FTO-mediated autophagy regulation in NSCLC progression remain elusive. In this study, we found that FTO was significantly upregulated in NSCLC, and downregulation of FTO suppressed the growth, invasion and migration of NSCLC cells by inducing autophagy. FTO knockdown resulted in elevated m6A levels in NSCLC cells. Methylated RNA immunoprecipitation sequencing showed that sestrin 2 (SESN2) was involved in m6A regulation during autophagy in NSCLC cells. Interestingly, m6A modifications in exon 9 of SESN2 regulated its stability. FTO deficiency promoted the binding of insulin-like growth factor 2 mRNA-binding protein 1 to SESN2 mRNA, enhancing its stability and elevating its protein expression. FTO inhibited autophagic flux by downregulating SESN2, thereby promoting the growth, invasion and migration of NSCLC cells. Besides, the mechanism by which FTO blocked SESN2-mediated autophagy activation was associated with the AMPK-mTOR signaling pathway. Taken together, these findings uncover an essential role of the FTO-autophagy-SESN2 axis in NSCLC progression.

Tuning the apparent hydrogen binding energy to achieve high-performance Ni-based hydrogen oxidation reaction catalyst.

High-performance platinum-group-metal-free alkaline hydrogen oxidation reaction catalysts are essential for the hydroxide exchange membrane fuel cells, which generally require high Pt loadings on the anode. Herein, we report a highly active hydrogen oxidation reaction catalyst, NiCuCr, indicated by the hydroxide exchange membrane fuel cell with a high peak power density of 577 mW cm-2 (18 times as high as the Ni/C anode) and a stability of more than 150 h (a degradation rate slower by 7 times than the Ni/C anode). The spectroscopies demonstrate that the alloy effect from Cu weakens the hydrogen binding, and the surface Cr2O3 species enhance the interfacial water binding. Both effects bring an optimized apparent hydrogen binding energy and thus lead to the high hydrogen oxidation reaction performance of NiCuCr. These results suggest that the apparent hydrogen binding energy determines the hydrogen oxidation reaction performance and that its tuning is beneficial toward high electrocatalytic performance.

Acid-Base Cascades in Zeotype Single Crystal for Sugar Conversion.

The chemically catalyzed production of fructose syrup from high concentrations of glucose is crucial for the food industry and biorefining. In this work, a single crystal catalyst was synthesized via protective desilication of zeolite while incorporating indium. Glucose was isomerized in methanol at concentrations as high as 33 wt % before being hydrolyzed with water. The final fructose production was 54.9 %, with 89.1 % selectivity and 93.3 % sugar recovery, the highest isomerization rate at the highest concentration ever reported. Indium was present in the single-crystal catalyst as oxide nanoparticles and boundary framework atoms, and it achieved intelligent cooperation in the production of fructose syrup in methanol by catalyzing isomerization and selective glycosidation, minimizing degradation due to fructose accumulation and eliminating side reactions. This study contributed to the advancement of the industrial practice of chemically catalyzed glucose isomerization.

Construction of a Diagnostic Model for Small Cell Lung Cancer Combining Metabolomics and Integrated Machine Learning.

BACKGROUND: To date, no study has systematically explored the potential role of serum metabolites and lipids in the diagnosis of small cell lung cancer (SCLC). Therefore, we aimed to conduct a case-cohort study that included 191 cases of SCLC, 91 patients with lung adenocarcinoma, 82 patients with squamous cell carcinoma, and 97 healthy controls. METHODS: Metabolomics and lipidomics were applied to analyze different metabolites and lipids in the serum of these patients. The SCLC diagnosis model (d-model) was constructed using an integrated machine learning technology and a training cohort (n = 323) and was validated in a testing cohort (n=138). RESULTS: Eight metabolites, including 1-mristoyl-sn-glycero-3-phosphocholine, 16b-hydroxyestradiol, 3-phosphoserine, cholesteryl sulfate, D-lyxose, dioctyl phthalate, DL-lactate and Leu-Phe, were successfully selected to distinguish SCLC from controls. The d-model was constructed based on these 8 metabolites and showed improved diagnostic performance for SCLC, with the area under curve (AUC) of 0.933 in the training cohort and 0.922 in the testing cohort. Importantly, the d-model still had an excellent diagnostic performance after adjusting the stage and related clinical variables and, combined with the progastrin-releasing peptide (ProGRP), showed the best diagnostic performance with 0.975 of AUC for limited-stage patients. CONCLUSION: This study is the first to analyze the difference between metabolomics and lipidomics and to construct a d-model to detect SCLC using integrated machine learning. This study may be of great significance for the screening and early diagnosis of SCLC patients.

Noninvasive 3D-CT simulation versus glue injection to localize small pulmonary nodules prior to anatomical segmentectomy: a randomized controlled trial.

OBJECTIVES: This study aimed to investigate whether adding glue injection to three-dimensional computed tomography bronchography and angiography (3D-CTBA) has extra benefits to facilitate anatomical segmentectomy for pulmonary nodules. METHODS: We conducted a randomized controlled trial. The patients undergoing thoracoscopic segmentectomy assisted with 3D-CTBA simulation were enrolled. Then, they were divided into the 3D-CTBA group and the glue-labelling group who received additional computed tomography-guided percutaneous glue (2-octyl cyanoacrylate) injection to label the nodules. The primary outcome was the resection rate of the nodules, and the secondary measures included the operation time, complications and thorax drainage. RESULTS: A total of 173 patients were randomized into the 3D-CTBA group (89 patients) and glue-labelling group (84 patients) between January 2018 and March 2019. Before the segmentectomy, the patients using glue labelling recorded 5 (6.0%) cases of pneumothorax, 2 (2.4%) cases of haemothorax and 1 (1.2%) case of severe chest pain. All the surgical procedure was performed fluently and safely. The resection rate of the nodules was 100% in both groups. Furthermore, these patients demonstrated similar operation time [(141.5 ± 41.9) vs (142.1 ± 38.9) min], estimated blood loss [(111.3 ± 74.0) vs (106.0 ± 63.8) ml], duration of chest tube duration [(5.1 ± 3.0) vs (5.0 ± 3.5) days] and total drainage volume [(872.3 ± 643.1) vs (826.7 ± 806.0) ml], with a P-value of >0.05 respectively. In addition, 6 (7.1%) patients in the glue-labelling group and 6 (6.7%) patients in the 3D-CTBA group reported air leakage (>5 days) and chylothorax. CONCLUSIONS: Noninvasive 3D-CTBA alone is probably sufficient to facilitate anatomical segmentectomy. The additional invasive glue labelling could be avoided in selected patients who undergo intentional segmentectomy. CLINICAL TRIAL REGISTRATION: The trial was registered under the Chinese Clinical Trial Registry (ChiCTR). Identifier: ChiCTR1800018293, https://www.chictr.org.cn/showproj.html?proj=29345.

Stem cell landscape aids in tumor microenvironment identification and selection of therapeutic agents in gastric cancer.

Gastric cancer stem cells (GCSCs) are strongly associated with the refractory characteristics of gastric cancer, including drug resistance, recurrence, and metastasis. The prognosis for advanced gastric cancer patients treated with multimodal therapy after surgery remains discouraging. GCSCs hold promise as therapeutic targets for GC patients. We obtained 26 sets of stem cell-related genes from the StemChecker database. The Consensus clustering algorithm was employed to discern three distinct stemness subtypes. Prognostic outcomes, components of the tumor microenvironment (TME), and responses to therapies were compared among these subtypes. Following this, a stemness-risk model was formulated using weighted gene correlation network analysis (WGCNA), alongside Cox regression and random survival forest analyses. The C2 subtype predominantly showed enrichment in negative prognostic CSC gene sets and demonstrated an immunosuppressive TME. This specific subtype exhibited minimal responsiveness to immunotherapies and demonstrated reduced sensitivity to drugs. Four pivotal genes were integrated into the construction of the stemness model. Gastric cancer patients with higher stemness-risk scores demonstrated poorer prognoses, a greater presence of immunosuppressive components in TME, and lower rates of treatment response. Subset analysis indicated that only the low-stemness risk subtype derives benefit from 5-fluorouracil-based adjuvant chemotherapy. The model's effectiveness in immunotherapeutic prediction was further validated in the PRJEB25780 cohort. Our study categorized gastric cancer patients into three stemness subtypes, each demonstrating distinct prognoses, components of TME infiltration, and varying sensitivity or resistance to standard chemotherapy or targeted therapy. We propose that the stemness risk model may help the development of well-grounded treatment recommendations and prognostic assessments.

miR-29c-3p represses the angiogenesis of esophageal squamous cell carcinoma by targeting SERPINH1 to regulate the Wnt signaling pathway.

PURPOSE: Esophageal squamous cell carcinoma (ESCC) is characterized by early metastasis and late diagnosis. miR-29c-3p is confirmed to repress angiogenesis in multiple tumor types. Yet, the functions of miR-29c-3p in the mechanism of ESCC angiogenesis, which were not sufficiently explored previously, were exactly what we investigated here at the molecular level. METHODS: The mRNA level of miR-29c-3p and Serpin peptidase inhibitor clade H member 1 (SERPINH1) in ESCC tissues were assessed via bioinformatics analysis. Thereafter, miR-29c-3p and SERPINH1 (HSP47) mRNA level in ESCC cell lines was evaluated via quantitative real-time polymerase chain reaction. The effects of abnormal miR-29c-3p and SERPINH1 expression on ESCC cell viability, proliferation, migration, invasion, and HUVEC angiogenesis were examined via CCK8, colony formation, transwell, and angiogenesis assays, respectively. The protein levels of SERPINH1, vascular endothelial growth factor-A (VEGFA), Wnt-1, ?-catenin, and p-?-catenin were evaluated via Western blot. Expression of VEGFA secreted by ESCC cells was measured via enzyme-linked immunosorbent assay. Treatment with the Wnt activator BML-284 further revealed the way miR-29c-3p mediated the Wnt signaling pathway and its effects on angiogenesis. RESULTS: Herein, we revealed a decrease of miR-29c-3p expression in ESCC tissues and cells, while the overexpressed miR-29c-3p could remarkably suppress ESCC cell progression, as well as HUVEC angiogenesis. Meanwhile, overexpressed miR-29c-3p notably downregulated VEGFA and repressed the Wnt signaling pathway. Treatment with the Wnt activator BML-284 could reverse the inhibition of HUVEC angiogenesis caused by miR-29c-3p. SERPINH1 was a downstream target of miR-29c-3p. SERPINH1 knockdown suppressed the malignant phenotypes of ESCC cells and impeded the Wnt signaling activation, while such suppression was reversed through miR-29c-3p inhibitor. CONCLUSIONS: We confirmed the mechanism that miR-29c-3p targeted SERPINH1, thus regulating angiogenesis in ESCC through the Wnt signaling pathway. It improves the understanding of angiogenesis in ESCC and offers new ideas for the research of ESCC treatment strategies in the future.

Adenosine in cancer immunotherapy: Taking off on a new plane.

As a new pillar of cancer therapy, tumor immunotherapy has brought irreplaceable durable responses in tumors. Considering its low response rate, additional immune regulatory mechanisms will be critical for the development of next-generation immune therapeutics. As a key regulatory mechanism, adenosine (ADO) protects tissues from excessive immune responses, but as a metabolite highly concentrated in tumor microenvironments, extracellular adenosine acts on adenosine receptors (mainly A2A receptors) expressed on MDSCs, Tregs, NK cells, effector T cells, DCs, and macrophages to promote tumor cell escape from immune surveillance by inhibiting the immune response. Amounting preclinical studies have demonstrated the adenosine pathway as a novel checkpoint for immunotherapy. Large number of adenosine pathway targeting clinical trials are now underway, including antibodies against CD39 and CD73 as well as A2A receptor inhibitors. There has been evidence of antitumor efficacy of these inhibitors in early clinical trials among a variety of tumors such as breast cancer, prostate cancer, non-small cell lung cancer, etc. As more clinical trial results are published, the combination of blockade of this pathway with immune checkpoint inhibitors, targeted drugs, traditional chemotherapy medications, radiotherapy and endocrine therapy will provide cancer patients with better clinical outcomes. We would elaborate on the role of CD39-CD73-A2AR pathway in the contribution of tumor microenvironment and the targeting of the adenosinergic pathway for cancer therapy in the review.

Anti-PD-1/Her2 Bispecific Antibody IBI315 Enhances the Treatment Effect of Her2-Positive Gastric Cancer through Gasdermin B-Cleavage Induced Pyroptosis.

The majority of patients with human epidermal growth factor receptor 2 (Her2)-positive gastric cancer develop refractory to Her2-targeted therapy, where upregulation of immune checkpoints plays an essential role. Herein, a recombinant fully human IgG1 bispecific antibody IBI315 targeting both PD-1 and Her2 is developed  and its antitumor efficacy as well as the underlying mechanism is investigated. IBI315 crosslinks the physical interaction between Her2-positive tumor cells and PD-1-positive T cells, resulting in significantly enhanced antitumor effects compared to each parent antibody or their combination, both in vitro and in vivo mouse tumor models reconstituted with human immune cells using patient-derived xenografts and organoids. Moreover, IBI315 treatment also induces the recruitment and activation of immune cells in tumors. Mechanistically, IBI315 triggers gasdermin B (GSDMB)-mediated pyroptosis in tumor cells, leading to the activation and recruiments of T cells. The activated T cells secret IFNγ, enhancing GSDMB expression and establishing a positive feedback loop of T cell activation and tumor cell killing. Notably, GSDMB is found to be elevated in Her2-positive gastric cancer cells, providing a rationale for IBI315's efficacy. IBI315 is supported here as a promising bispecific antibody-based immunotherapy approach for Her2-positive gastric cancer in preclinical studies, broadening the therapeutic landscape of this patient population.

Synthesis of 2,6-Dimethoxy-p-aminophenol from Hardwood Lignin.

Although the multiple functional groups in biomass offer notable chances for producing high-value chemicals, most of the current studies focused on the (deep) defunctionalization of biomass and its derivates. Herein, we present a catalytic approach to valorize birch wood lignin with maintaining the methoxy and hydroxy groups in the final product (i. e., 2,6-dimethoxy-p-aminophenol), which has applications in different sectors such as pharmaceuticals. The proved approach involves four steps with a high yield (19.8 wt % on the basis of used lignin) to 2,6-dimethoxy-p-aminophenol. The native lignin in birch wood was first converted using alkaline aerobic oxidation in the presence of copper ions toward high-yield syringaldehyde, which was then selectively oxidized toward 2,6-dimethoxy-1,4-benzoquinone using H2 O2 and V2 O5 . Oximation of 2,6-dimethoxy-1,4-benzoquinone can selectively form 2,6-dimethoxy-1,4-benzoquinone-4-oxime, which can be quantitatively hydrogenated toward 2,6-dimethoxy-p-aminophenol. This work highlights the unique potential of biomass and its derivates for the sustainable production of high-value products with exploring the value of inherent functional groups.

Orchestrating smart therapeutics to achieve optimal treatment in small cell lung cancer: recent progress and future directions.

Small cell lung cancer (SCLC) is a recalcitrant malignancy with elusive mechanism of pathogenesis and dismal prognosis. Over the past decades, platinum-based chemotherapy has been the backbone treatment for SCLC. However, subsequent chemoresistance after initial effectiveness urges researchers to explore novel therapeutic targets of SCLC. Recent years have witnessed significant improvements in targeted therapy in SCLC. New molecular candidates such as Ataxia telangiectasia and RAD3-related protein (ATR), WEE1, checkpoint kinase 1 (CHK1) and poly-ADP-ribose polymerase (PARP) have shown promising therapeutic utility in SCLC. While immune checkpoint inhibitor (ICI) has emerged as an indispensable treatment modality for SCLC, approaches to boost efficacy and reduce toxicity as well as selection of reliable biomarkers for ICI in SCLC have remained elusive and warrants our further investigation. Given the increasing importance of precision medicine in SCLC, optimal subtyping of SCLC using multi-omics have gradually applied into clinical practice, which may identify more drug targets and better tailor treatment strategies to each individual patient. The present review summarizes recent progress and future directions in SCLC. In addition to the emerging new therapeutics, we also focus on the establishment of predictive model for early detection of SCLC. More importantly, we also propose a multi-dimensional model in the prognosis of SCLC to ultimately attain the goal of accurate treatment of SCLC.

A spike-targeting bispecific T cell engager strategy provides dual layer protection against SARS-CoV-2 infection in vivo.

Neutralizing antibodies exert a potent inhibitory effect on viral entry; however, they are less effective in therapeutic models than in prophylactic models, presumably because of their limited efficacy in eliminating virus-producing cells via Fc-mediated cytotoxicity. Herein, we present a SARS-CoV-2 spike-targeting bispecific T-cell engager (S-BiTE) strategy for controlling SARS-CoV-2 infection. This approach blocks the entry of free virus into permissive cells by competing with membrane receptors and eliminates virus-infected cells via powerful T cell-mediated cytotoxicity. S-BiTE is effective against both the original and Delta variant of SARS-CoV2 with similar efficacy, suggesting its potential application against immune-escaping variants. In addition, in humanized mouse model with live SARS-COV-2 infection, S-BiTE treated mice showed significantly less viral load than neutralization only treated group. The S-BiTE strategy may have broad applications in combating other coronavirus infections.