Development of a multiplex real-time PCR assay for the simultaneous detection of mpox virus and orthopoxvirus infections.

Since May 2022, the multi-country outbreak of monkeypox (mpox) has raised a great concern worldwide. Early detection of mpox virus infection is recognized as an efficient way to prevent mpox transmission. Mpox specific detection methods reported up to now are based on the SNPs among mpox virus and other orthopoxviruses. We have therefore developed a real-time PCR based mpox detection method targeting mpox virus specific sequences (N3R and B18Rplus). We have also optimized an orthopoxvirus detection system which targets the highly conserved E9L and D6R genes. The mpox and orthopoxvirus real-time PCR assays have a high sensitivity (1 copy/reaction) and specificity. Mpox viral DNA and clinical samples from mpox patients are detected with the mpox detection system. Furthermore, we have established a multiplex real-time PCR detection system allowing simultaneous and efficient detection of mpox and orthopoxvirus infections.

Unlocking Predictive Capability and Enhancing Sensing Performances of Plasmonic Hydrogen Sensors via Phase Space Reconstruction and Convolutional Neural Networks.

This study innovates plasmonic hydrogen sensors (PHSs) by applying phase space reconstruction (PSR) and convolutional neural networks (CNNs), overcoming previous predictive and sensing limitations. Utilizing a low-cost and efficient colloidal lithography technique, palladium nanocap arrays are created and their spectral signals are transformed into images using PSR and then trained using CNNs for predicting the hydrogen level. The model achieves accurate predictions with average accuracies of 0.95 for pure hydrogen and 0.97 for mixed gases. Performance improvements observed are a reduction in response time by up to 3.7 times (average 2.1 times) across pressures, SNR increased by up to 9.3 times (average 3.9 times) across pressures, and LOD decreased from 16 Pa to an extrapolated 3 Pa, a 5.3-fold improvement. A practical application of remote hydrogen sensing without electronics in hydrogen environments is actualized and achieves a 0.98 average test accuracy. This methodology reimagines PHS capabilities, facilitating advancements in hydrogen monitoring technologies and intelligent spectrum-based sensing.

[Multi-scenario Simulation of Construction Land Expansion and Its Impact on Ecosystem Carbon Storage in Beijing-Tianjin-Hebei Urban Agglomeration].

It is of great practical significance for regional sustainable development and ecological construction to quantitatively analyze the impact of construction land expansion on terrestrial ecosystem carbon storage and to explore the optimization scheme of simulating construction land expansion to improve future ecosystem carbon storage. Based on the land use and cover change (LUCC) and other geospatial data of the Beijing-Tianjin-Hebei Urban Agglomeration from 2000 to 2020, this study utilized the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and the patch-generating land-use simulation (PLUS) model to assess and analyze the changes in ecosystem carbon stocks and spatial patterns regionally. In this study, we performed linear regression analysis to investigate the relationship between urban land expansion and changes in ecosystem carbon stocks for varying urban land proportion levels during two distinct time intervals, 2000-2010 and 2010-2020, which was conducted at a spatial resolution of 2 km. Three distinct urban land expansion scenarios were subjected to simulation to forecast the prospective land use pattern by 2030. Subsequently, we quantified the ramifications of these scenarios on ecosystem carbon stocks during the period from 2020 to 2030. The results were as follows:① In the Beijing-Tianjin-Hebei Urban Agglomeration, the ecosystem carbon stocks exhibited notable variations over the study period, with values of 2 088.02, 2 106.78, and 2 121.25 Tg recorded for the years 2000, 2010, and 2020, respectively, resulting in a cumulative carbon sequestration of 33.23 Tg C during the study duration. It is noteworthy that forest carbon storage emerged as the dominant contributor, with an increase from 1 010.17 Tg in 2000 to 1 136.53 Tg in 2020. Throughout the study period, the spatial distribution of carbon stocks displayed relative stability. Regions characterized by lower carbon content were concentrated in the vicinity of the Bohai Rim region and in proximity to cities such as Beijing, Tianjin, and Shijiazhuang, as well as rural settlements. In contrast, grid units with moderate and high carbon stocks were predominantly situated in the western Taihang Mountain and the northern Yanshan Mountain. Additionally, there was a tendency of increasing carbon stocks in the Taihang Mountain and Yanshan Mountain region, whereas those surrounding major urban centers such as Beijing, Tianjin, Shijiazhuang, and Tangshan experienced a notable decline in carbon stocks. Such reductions were most pronounced in regions undergoing urban land expansion during the study period. ② In grid units with an urban land proportion exceeding 10% at each level, a strong correlation was observed between urban land expansion and changes in carbon stocks during both the 2000-2010 and 2010-2020 periods. The changes in urban land proportion adequately explained the variations in carbon stocks. However, the explanatory power of urban land on carbon stocks decreased during the 2010-2020 period, indicating that other factors played a more substantial role in influencing carbon stocks during this time. The regression coefficients for both periods exhibited a fluctuating upward trend. In comparison to that during the 2000-2010 period, the impact of urban land expansion on carbon stocks was relatively smaller during 2010-2020, indicating a weakening influence. ③ In light of three distinct development scenarios, namely natural development (Scenario Ⅰ), a 15% reduction in the rate of urban land expansion (Scenario Ⅱ), and a 30% reduction in the rate of urban land expansion (Scenario Ⅲ), the projected ecosystem carbon stocks for the Beijing-Tianjin-Hebei Urban Agglomeration in the year 2030 were estimated to be 2 129.12, 2 133.55, and 2 139.10 Tg, respectively. These projections indicated an increase of 7.88, 12.30, and 17.85 Tg in comparison to the current carbon stocks. All scenarios demonstrated that the terrestrial ecosystem would play a role of carbon sink, particularly with the greatest carbon sink observed in the scenario with a 30% reduction in urban land expansion. The fit performance between urban land expansion and carbon stock changes during the 2020-2030 period was significantly better than that during the 2000-2010 and 2010-2020 periods, and the regression coefficients showed a fluctuating increase with an increase in urban land proportion. Across grid units with different urban land proportion levels, the regression coefficients exhibited the order of Scenario Ⅰ < Scenario Ⅱ < Scenario Ⅲ. In pursuit of the carbon peaking and carbon neutrality goals, the Beijing-Tianjin-Hebei Urban Agglomeration should prioritize scenarios with reduced rates of urban land expansion, especially in regions with higher urban land proportions.

Intelligent Detection and Odor Recognition of Cigarette Packaging Paper Boxes Based on a Homemade Electronic Nose.

The printing process of box packaging paper can generate volatile organic compounds, resulting in odors that impact product quality and health. An efficient, objective, and cost-effective detection method is urgently needed. We utilized a self-developed electronic nose system to test four different cigarette packaging paper samples. Employing multivariate statistical methods like Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Statistical Quality Control (SQC), and Similarity-based Independent Modeling of Class Analogy (SIMCA), we analyzed and processed the collected data. Comprehensive evaluation and quality control models were constructed to assess sample stability and distinguish odors. Results indicate that our electronic nose system rapidly detects odors and effectively performs quality control. By establishing models for quality stability control, we successfully identified samples with acceptable quality and those with odors. To further validate the system's performance and extend its applications, we collected two types of cigarette packaging paper samples with odor data. Using data augmentation techniques, we expanded the dataset and achieved an accuracy rate of 0.9938 through classification and discrimination. This highlights the significant potential of our self-developed electronic nose system in recognizing cigarette packaging paper odors and odorous samples.

Uncovering Microbial Composition of the Tissue Microenvironment in Bladder Cancer using RNA Sequencing Data.

Purpose: Bladder cancer (BC) is one of the top 10 common tumors in the world. It has been reported that microbiota can colonize tissues and play important roles in tumorigenesis and progression. However, the current understanding of microorganisms in the BC tissue microenvironment remains unclear. Methods: In this study, we integrated the RNA-seq data of 479 BC tissue samples from seven datasets combined with a range of bioinformatics tools to explore the landscape of microbiome in the BC tissue microenvironment. Results: The pan-microbiome was estimated to surpass 1,400 genera. A total of seven core microbiota (Bacillus, Corynebacterium, Cutibacterium, Escherichia, Halomonas, Pasteurella, and Streptomyces) were identified. Among them, Bacillus was widely distributed in all datasets with a high relative abundance (10.11% of all samples on average). Moreover, some biological factors, including tissue source and tumor grade, were found significant effects on the microbial composition of the bladder tissue. Pseudomonas, Porphyrobacter, and Acinetobacter were enriched in tumor tissues, while Mycolicibacterium and Streptomyces were enriched in patients who showed durable response to BCG therapy. In addition, we established microbial co-occurrence networks and found that the BCG therapy may attenuate the microbiological interactions. Conclusions: This study clearly provided a microbial landscape of the BC tissue microenvironment, which was important for exploring the interactions between microorganisms and BC tissues. The identified specific taxa might be potential biomarkers for BC.

Simulation of mangrove suitable habitat in the Guangdong-Hong Kong-Macao Area under the background of climate change.

Climate change has resulted in great influence on the geographical distribution of species. Mangrove forests are one of the most precious ecosystems on the planet, yet they are being threatened by the habitat destruction and degradation under the situation of global warming. Seeking suitable areas for planting mangroves to tackle climate change has been gradually popular in ecological restoration. In this study, we applied the Maximum Entropy algorithm to assess the contribution of environmental factors on mangrove distribution, simulated mangrove suitable habitat for present and future (scenario of SSP245-2070s), and used kernel density analysis for identifying priority of mangrove reserve construction. Results indicate that mean diurnal range and elevation made the highest contribution on mangrove distribution. At present, the mangrove habitat suitability along the western coast of the Guangdong-Hong Kong-Macao Area (GHMA) was the highest while that along the eastern coast was the lowest. By 2070s, mangrove suitable areas would show a decreasing trend under SSP245 scenario. High suitable areas (HSAs) would change fastest and shift to northeast in the same direction as dominant environmental factors. For further mangrove restoration, it is advisable to select sites with high suitability density in the future but low reclamation density at present as prior mangrove reserves, and these sites distribute along the northeastern and northwestern coast of Zhanjiang, Yangjiang and Jiangmen, the Pearl River Estuary and Honghai Bay of Shanwei. Meanwhile, regions with lower suitability density but higher reclamation density could be listed as secondary mangrove reserves.

CAR-Aptamers Enable Traceless Enrichment and Monitoring of CAR-Positive Cells and Overcome Tumor Immune Escape.

Chimeric antigen receptor (CAR)-positive cell therapy, specifically with anti-CD19 CAR-T (CAR19-T) cells, achieves a high complete response during tumor treatment for hematological malignancies. Large-scale production and application of CAR-T therapy can be achieved by developing efficient and low-cost enrichment methods for CAR-T cells, expansion monitoring in vivo, and overcoming tumor escape. Here, novel CAR-specific binding aptamers (CAR-ap) to traceless sort CAR-positive cells and obtain a high positive rate of CAR19-T cells is identified. Additionally, CAR-ap-enriched CAR19-T cells exhibit similar antitumor capacity as CAR-ab (anti-CAR antibody)-enriched CAR-T cells. Moreover, CAR-ap accurately monitors the expansion of CAR19-T cells in vivo and predicts the prognosis of CAR-T treatment. Essentially, a novel class of stable CAR-ap-based bispecific circular aptamers (CAR-bc-ap) is constructed by linking CAR-ap with a tumor surface antigen (TSA): protein tyrosine kinase 7 (PTK7) binding aptamer Sgc8. These CAR-bc-aps significantly enhance antitumor cytotoxicity with a loss of target antigens by retargeting CAR-T cells to the tumor in vitro and in vivo. Overall, novel CAR-aptamers are screened for traceless enrichment, monitoring of CAR-positive cells, and overcoming tumor cell immune escape. This provides a low-cost and high-throughput approach for CAR-positive cell-based immunotherapy.

Molecular modification of MAPbI3 surface: insights from first-principles theory studies.

Molecular surface modification has been widely used to improve the stability and the power conversion efficiency of perovskite solar cells. First-principles studies have played a crucial role in the mechanism of surface modification. However, the design of surface modification molecules lacks theoretical guidelines. Herein, we studied the surface modifications of a series of typical small molecules based on first-principles calculations. The relevance of the calculated properties and experimental performance has been investigated. It was found that molecules with nitrogen-containing groups, including amino, π-conjugated N-heterocycle, and (thio)amide groups, could have strong adsorption energies, and may be suitable modifiers. Molecules such as oxygen-containing six-membered rings and 1,2,4-triazine may induce defect states. Based on our calculations, design guidelines for perovskite surface modification molecules have been proposed based on three aspects: interfacial buffering, defect avoidance, and energy level alignment. This work may shed light on the development of perovskite surface modification molecules towards higher power conversion efficiency and more stable perovskite solar cells.

Rapid and sensitive one-tube detection of mpox virus using RPA-coupled CRISPR-Cas12 assay.

Mpox is caused by a zoonotic virus belonging to the Orthopoxvirus genus and the Poxviridae family. In this study, we develop a recombinase polymerase amplification (RPA)-coupled CRISPR-Cas12a detection assay for the mpox virus. We design and test a series of CRISPR-derived RNAs(crRNAs) targeting the conserved D6R and E9L genes for orthopoxvirus and the unique N3R and N4R genes for mpox viruses. D6R crRNA-1 exhibits the most robust activity in detecting orthopoxviruses, and N4R crRNA-2 is able to distinguish the mpox virus from other orthopoxviruses. The Cas12a/crRNA assay alone presents a detection limit of 108 copies of viral DNA, whereas coupling RPA increases the detection limit to 1-10 copies. The one-tube RPA-Cas12a assay can, therefore, detect viral DNA as low as 1 copy within 30 min and holds the promise of providing point-of-care detection for mpox viral infection.

Risk factors analysis of surgical site infections in postoperative colorectal cancer: a nine-year retrospective study.

BACKGROUND: Colorectal cancer (CRC) patients undergoing surgery are at a high risk of developing surgical site infections (SSIs), which contribute to increased morbidity, prolonged hospitalization, and escalated healthcare costs. Understanding the incidence, risk factors, and impact of SSIs is crucial for effective preventive strategies and improved patient outcomes. METHODS: This retrospective study analyzed data from 431 CRC patients who underwent surgery at Huangshan Shoukang Hospital between 2014 and 2022. The clinical characteristics and demographic information were collected. The incidence and impact of SSIs were evaluated, and independent risk factors associated with SSIs were identified using multivariable logistic regresison. A nomogram plot was constructed to predict the likelihood of SSIs occurrence. RESULTS: The overall incidence rate of SSIs was 7.65% (33/431). Patients with SSIs had significantly longer hospital stays and higher healthcare costs. Risk factors for SSIs included elevated Body Mass Index (BMI) levels (odds ratio, 1.12; 95% CI, 1.02-1.23; P = 0.017), the presence of diabetes (odds ratio, 3.88; 95% CI, 1.42 - 9.48; P = 0.01), as well as specific surgical factors such as open surgical procedures (odds ratio, 2.39; 95% CI [1.09; 5.02]; P = 0.031), longer surgical duration (odds ratio, 1.36; 95% CI [1.01; 1.84]; P = 0.046), and the presence of a colostomy/ileostomy (odds ratio, 3.17; 95% CI [1.53; 6.62]; P = 0.002). Utilizing multivariable regression analysis, which encompassed factors such as open surgical procedures, the presence of diabetes and colostomy/ileostom, the nomogram plot functions as a visual aid in estimating the individual risk of SSIs for patients. CONCLUSIONS: Risk factors for SSIs included higher BMI levels, the presence of diabetes, open surgical procedures, longer surgical duration, and the presence of colostomy/ileostomy. The nomogram plot serves as a valuable tool for risk assessment and clinical decision-making.

Eukaryotic translation initiation factor 2α kinase 2 in pancreatic cancer: An approach towards managing clinical prognosis and molecular immunological characterization.

Most patients with pancreatic cancer are already in the late stages of the disease when they are diagnosed, and pancreatic cancer is a deadly disease with a poor prognosis. With the advancement of research, immunotherapy has become a new focus in the treatment of tumors. To the best of our knowledge, there is currently no reliable diagnostic or prognostic marker for pancreatic cancer; therefore, the present study investigated the potential of eukaryotic translation initiation factor 2α kinase 2 (EIF2AK2) as a predictive and diagnostic marker for pancreatic cancer. Immunohistochemical staining of clinical samples independently verified that EIF2AK2 expression was significantly higher in clinically operated pancreatic cancer tissues than in adjacent pancreatic tissues., and EIF2AK2 expression and differentially expressed genes (DEGs) were identified using downloadable RNA sequencing data from The Cancer Genome Atlas and Genomic Tumor Expression Atlas. In addition, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes analyses and immune cell infiltration were used for functional enrichment analysis of EIF2AK2-associated DEGs. The clinical importance of EIF2AK2 was also determined using Kaplan-Meier survival, Cox regression and time-dependent survival receiver operating characteristic curve analyses, and a predictive nomogram model was generated. Finally, the functional role of EIF2AK2 was assessed in PANC-1 cells using a short hairpin RNA-EIF2AK2 knockdown approach, including CCK-8, wound healing assay, cell cycle and apoptosis assays. The findings suggested that EIF2AK2 may have potential as a diagnostic and prognostic biomarker for patients with pancreatic cancer. Furthermore, EIF2AK2 may provide a new therapeutic target for patients with pancreatic cancer.

Anti-CD79b/CD3 bispecific antibody combined with CAR19-T cells for B-cell lymphoma treatment.

CD19 CAR-T (chimeric antigen receptor-T) cell immunotherapy achieves a remission rate of approximately 70% in recurrent and refractory lymphoma treatment. However, the loss or reduction of CD19 antigen on the surface of lymphoma cells results in the escape of tumor cells from the immune killing of CD19 CAR-T cells (CAR19-T). Therefore, novel therapeutic strategies are urgently required. In this study, an anti-CD79b/CD3 bispecific antibody (BV28-OKT3) was constructed and combined with CAR19-T cells for B-cell lymphoma treatment. When the CD19 antigen was lost or reduced, BV28-OKT3 redirected CAR19-T cells to CD79b+ CD19- lymphoma cells; therefore, BV28-OKT3 overcomes the escape of CD79b+ CD19- lymphoma cells by the killing action of CAR19-T cells in vitro and in vivo. Furthermore, BV28-OKT3 triggered the antitumor function of CAR- T cells in the infusion product and boosted the antitumor immune response of bystander T cells, markedly improving the cytotoxicity of CAR19-T cells to lymphoma cells in vitro and in vivo. In addition, BV28-OKT3 elicited the cytotoxicity of donor-derived T cells toward lymphoma cells in vitro, which depended on the presence of tumor cells. Therefore, our findings provide a new clinical treatment strategy for recurrent and refractory B-cell lymphoma by combining CD79b/CD3 BsAb with CAR19-T cells.

Intermolecular 3D-MoRSE Descriptors for Fast and Accurate Prediction of Electronic Couplings in Organic Semiconductors.

The theoretical rational design of organic semiconductors faces an obstacle in that the performance of organic semiconductors depends very much on their stacking and local morphology (for example, phase domains), which involves numerous molecules. Simulation becomes computationally expensive as intermolecular electronic couplings have to be calculated from density functional theory. Therefore, developing fast and accurate methods for intermolecular electronic coupling estimation is essential. In this work, by developing a series of new intermolecular 3D descriptors, we achieved fast and accurate prediction of electronic couplings in both crystalline and amorphous thin films. Three groups of developed descriptors could perform faster and higher accuracy prediction on electronic couplings than the most advanced state-of-the-art descriptors. This work paves the way for large-scale simulations, high-throughput calculations, and screening of organic semiconductors.

Tandem Ene/[4 + 2] Cycloaddition Reaction for the Synthesis of 9-Benzylphenanthrenes from Arynes and α-(Bromomethyl)styrenes.

A tandem reaction for the synthesis of phenanthrenes from arynes and α-(bromomethyl)styrenes is reported. The transformation proceeds via an ene reaction of α-(bromomethyl)styrenes with arynes, followed by a [4 + 2] cycloaddition reaction. The reaction generates 9-benzylphenanthrene derivatives in moderate to excellent yields.

Uncovering the special microbiota associated with occurrence and progression of gastric cancer by using RNA-sequencing.

Gastric cancer (GC) has been identified as the third deadly cancer in the world. Accumulating researches suggest a potential role of microorganisms in tumorigenesis. However, the composition of microbiota in GC tissues is not clear and it changes throughout the different stages of GC remain mostly elusive. Our study integrated RNA-Seq data of 727 samples derived from gastric tissues across four datasets and revealed its microbial composition. In order to remove the false positive results, core taxa were defined and characterized. Based on it, we analyzed the influence of biological factors on its composition. The pan-microbiome of gastric tissues was estimated to be over than 1400 genera. Seventeen core genera were identified. Among them, Helicobacter, Lysobacter were significantly enriched in normal tissues, while Pseudomonas was enriched in tumor tissues. Interestingly, Acinetobacter, Pasteurella, Streptomyces, Chlamydia, and Lysobacter, showed a significant increase trend during tumor development and formed strong intra/inter-correlations among them or with other genera. Furthermore, we found that tumor stage played an important role in altering the microbial composition of GC tissues. This study provides support for the in-depth study of tumor microbiome, and the specific microbiome excavated provides a possibility for the subsequent identification of potential biomarkers for GC.

Genome-wide identification of A-to-I RNA editing events provides the functional implications in PDAC.

Introduction: RNA editing, a wide-acknowledged post-transcriptional mechanism, has been reported to be involved in the occurrence and development of cancer, especially the abnormal alteration of adenosine to inosine. However, fewer studies focus on pancreaticcancer. Therefore, we aimed to explore the possible linkages between altered RNA editing events and the development of PDAC. Method: We characterized the global A-to-I RNA editing spectrum from RNA and matched whole-genome sequencing data of 41 primary PDAC and adjacent normal tissues. The following analyses were performed: different editing level and RNA expression analysis,pathway analysis, motif analysis, RNA secondary structure analysis, alternative splicing events analysis, and survival analysis.The RNA editing of single-cell RNA public sequencing data was also characterized. Result: A large number of adaptive RNA editing events with significant differences in editing levels were identified, which are mainly regulated by ADAR1. Moreover, RNA editing in tumors has a higher editing level and more abundant editing sites in general. 140genes were screened out since they were identified with significantly different RNA editing events and were significantly different in expression level between tumor and matched normal samples. Further analysis showed a preference that in the tumor-specific group, they are mainly enriched in cancer-related signal pathways, while in the normal tissue-specific group, they are mainly enriched in pancreatic secretion. At the same time, we also found positively selected differentially edited sites in a series of cancer immune genes, including EGF, IGF1R, and PIK3CD. RNA editing might participate in pathogenisis of PDAC through regulating the alternative splicing and RNA secondary structure of important genesto further regulate gene expression and protein synthesis, including RAB27B and CERS4. Furthermore, single cell sequencing results showed that type2 ductal cells contributed the most to RNA editing events in tumors. Conclusion: RNA editing is an epigenetic mechanism involved in the occurrence and development of pancreatic cancer, which has the potential to diagnose of PDAC and is closely related to the prognosis.

The screening of compounds regulating PD-L1 transcriptional activity in a cell functional high-throughput manner.

Immune checkpoints are protein molecules expressed on the immune cell membrane, which regulate the immune system to kill tumor cells. As an essential immune checkpoint, overexpressed PD-1 on tumor cells could inhibit T-cell activation after being bonded to PD-1. Due to this inhibitory effect, T-cell proliferation and cytokine secretion are suppressed, leading to immune escape of tumor cells. Here, we established a high-throughput method based on cell function screening technology to screen drugs regulating PD-L1 expression in tumor cells at the transcriptional level. After two screening rounds, 12 compounds that enhanced PD-L1 transcription while seven weakened were sorted out among 1018 FDA-approved drugs. Finally, a tumor cell line was used to verify the upregulation of endogenous PD-L1 expression for a drug named "vorinostat," a histone deacetylation inhibitor, after the two rounds of optional selection. Therefore, our research provides another perspective for using "vorinostat" in treating tumors and offers a convenient method to detect the transcriptional expression of other intracellular proteins besides PD-L1.

Strategies to optimize chimeric antigen receptor T-cell therapy in hematologic malignancies: Chinese experience.

Chimeric antigen receptor (CAR) T-cell therapy has emerged as a promising form of adoptive T-cell immunotherapy for selected hematologic malignancies including leukemia, lymphoma and multiple myeloma. China has become the country with the largest number of registered CAR T-cell trials. Despite the remarkable clinical outcomes achieved with CAR Tcell therapy, challenges such as disease relapse, the process of manufacturing the CAR T cells and safety have limited the therapeutic efficacy of CAR T cells in hematologic malignancies. In this period of innovation, several clinical trials have reported the design of CAR directed at new targets in hematologic malignancies. In this review, we comprehensively summarize the contemporary landscape and clinical development of CAR T-cell therapy in China. In addition, we present strategies for further improving the clinical utility of CAR T-cell therapy, such as increasing the efficacy and response duration, in hematologic malignancies.

Increased endogenous PKG I activity attenuates EGF-induced proliferation and migration of epithelial ovarian cancer via the MAPK/ERK pathway.

The type I cGMP-dependent protein kinase (PKG I) is recognized as a tumor suppressor, but its role in EGFR regulated epithelial ovarian cancer (EOC) progression remains unclear. We evaluated the in vivo and in vitro effects of activated PKG I in EGF-induced EOC cell proliferation, migration, and invasion. The expressions of EGFR and PKG I were elevated, but the activated PKG I was decreased in EOC tissues of patients and cells lines. The addition of 8-Br-cGMP, a specific PKG I activator, attenuated the EGF-induced EOC cell proliferation, migration, and invasion in vitro. Similarly, activated PKG I also attenuated EOC progression in vivo using an EOC xenograft nude mouse model. The activated PKG I interacted with EGFR, causing increased threonine (693) phosphorylation and decreased tyrosine (1068) phosphorylation of EGFR, which resulted in disrupted EGFR-SOS1-Grb2 combination. Subsequently, the cytoplasmic phosphorylation of downstream proteins (c-Raf, MEK1/2, and ERK1/2) were declined, impeding the phosphorylated ERK1/2's nucleus translocation, and this reduction of phosphorylated tyrosine (1068) EGFR and ERK1/2 were also abolished by Rp-8-Br-cGMPS. Our results suggest that the activation of PKG I attenuates EGF-induced EOC progression, and the 8-Br-cGMP-PKG I-EGFR/MEK/ERK axis might be a potential target for EOC therapy.

Rapid Detection of SARS-CoV-2 RNA in Human Nasopharyngeal Specimens Using Surface-Enhanced Raman Spectroscopy and Deep Learning Algorithms.

A rapid and cost-effective method to detect the infection of SARS-CoV-2 is fundamental to mitigating the current COVID-19 pandemic. Herein, a surface-enhanced Raman spectroscopy (SERS) sensor with a deep learning algorithm has been developed for the rapid detection of SARS-CoV-2 RNA in human nasopharyngeal swab (HNS) specimens. The SERS sensor was prepared using a silver nanorod array (AgNR) substrate by assembling DNA probes to capture SARS-CoV-2 RNA. The SERS spectra of HNS specimens were collected after RNA hybridization, and the corresponding SERS peaks were identified. The RNA detection range was determined to be 103-109 copies/mL in saline sodium citrate buffer. A recurrent neural network (RNN)-based deep learning model was developed to classify 40 positive and 120 negative specimens with an overall accuracy of 98.9%. For the blind test of 72 specimens, the RNN model gave a 97.2% accuracy prediction for positive specimens and a 100% accuracy for negative specimens. All the detections were performed in 25 min. These results suggest that the DNA-functionalized AgNR array SERS sensor combined with a deep learning algorithm could serve as a potential rapid point-of-care COVID-19 diagnostic platform.