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Chimeric antigen receptor (CAR) T cell therapy represents a major breakthrough in cancer care since the approval of tisagenlecleucel by the Food and Drug Administration in 2017 for the treatment of pediatric and young adult patients with relapsed or refractory acute lymphocytic leukemia. As of April 2023, six CAR T cell therapies have been approved, demonstrating unprecedented efficacy in patients with B-cell malignancies and multiple myeloma. However, adverse events such as cytokine release syndrome and immune effector cell-associated neurotoxicity pose significant challenges to CAR T cell therapy. The severity of these adverse events correlates with the pretreatment tumor burden, where a higher tumor burden results in more severe consequences. This observation is supported by the application of CD19-targeted CAR T cell therapy in autoimmune diseases including systemic lupus erythematosus and antisynthetase syndrome. These results indicate that initiating CAR T cell therapy early at low tumor burden or using debulking strategy prior to CAR T cell infusion may reduce the severity of adverse events. In addition, CAR T cell therapy is expensive and has limited effectiveness against solid tumors. In this article, we review the critical steps that led to this groundbreaking therapy and explore ongoing efforts to overcome these challenges. With the promise of more effective and safer CAR T cell therapies in development, we are optimistic that a broader range of cancer patients will benefit from this revolutionary therapy in the foreseeable future.

Zika virus (ZIKV) was once considered an obscure member of the large and diverse family of mosquito-borne flaviviruses, and human infections with ZIKV were thought to be sporadic, with mild and self-limiting symptoms. The large-scale ZIKV epidemics in the Americas and the unexpected uncovering of a link to congenital birth defects escalated ZIKV infections to the status of a global public health emergency. Recent studies that combined reverse genetics with modelling in multiple systems have provided evidence that ZIKV has acquired additional amino acid substitutions at the same time as congenital Zika syndrome and other birth defects were detected. In this Progress article, we summarize the evolution of ZIKV during its spread from Asia to the Americas and discuss potential links to pathogenesis.

Virtual reality (VR) is the use of computer technology to create an interactive three-dimensional (3D) world, which gives users a sense of spatial presence. In nursing education, VR has been used to help optimize teaching and learning processes. The purpose of this study was to evaluate the effectiveness of VR in nursing education in the areas of knowledge, skills, satisfaction, confidence, and performance time. We conducted a meta-analysis of the effectiveness of VR in nursing education based on the Cochrane methodology. An electronic literature search using the Cochrane Library, Web of Science, PubMed, Embase, and CINAHL (Cumulative Index to Nursing and Allied Health Literature), up to December 2019 was conducted to identify studies that reported the effectiveness of VR on knowledge, skills, satisfaction, confidence, and performance time. The study selection and data extraction were carried out by two independent reviewers. The methodological quality of the selected studies was determined using the Cochrane criteria for risk-of-bias assessment. A total of 12 studies, including 821 participants, were selected for the final analysis. We found that VR was more effective than the control conditions in improving knowledge (standard mean difference [SMD]=0.58, 95% CI 0.41-0.75, P<.001, I =47%). However, there was no difference between VR and the control conditions in skills (SMD=0.01, 95% CI -0.24 to 0.26, P=.93, I =37%), satisfaction (SMD=0.01, 95% CI -0.79 to 0.80, P=.99, I =86%), confidence (SMD=0.00, 95% CI -0.28 to 0.27, P=.99, I =0%), and performance time (SMD=-0.55, 95% CI -2.04 to 0.94, P=.47, I =97%). The results of this study suggest that VR can effectively improve knowledge in nursing education, but it was not more effective than other education methods in areas of skills, satisfaction, confidence, and performance time. Further rigorous studies with a larger sample size are warranted to confirm these results.

Zika virus (ZIKV) has evolved into a global health threat because of its unexpected causal link to microcephaly. Phylogenetic analysis reveals that contemporary epidemic strains have accumulated multiple substitutions from their Asian ancestor. Here we show that a single serine-to-asparagine substitution [Ser139→Asn139 (S139N)] in the viral polyprotein substantially increased ZIKV infectivity in both human and mouse neural progenitor cells (NPCs) and led to more severe microcephaly in the mouse fetus, as well as higher mortality rates in neonatal mice. Evolutionary analysis indicates that the S139N substitution arose before the 2013 outbreak in French Polynesia and has been stably maintained during subsequent spread to the Americas. This functional adaption makes ZIKV more virulent to human NPCs, thus contributing to the increased incidence of microcephaly in recent ZIKV epidemics.

The recent Zika virus （ZIKV） epidemic in Latin America coincided with a marked increase in microcephaly in newborns. However, the causal link between maternal ZIKV infection and malformation of the fetal brain has not been firmly established. Here we show a vertical transmission of ZIKV in mice and a marked effect on fetal brain development. We found that intraperitoneal （i.p.） injection of a contemporary ZIKV strain in pregnant mice led to the infection of radial gila cells （RGs） of dorsal ventricular zone of the fetuses, the primary neural progenitors responsi- ble for cortex development, and caused a marked reduction of these cortex founder cells in the fetuses. Interestingly, the infected fetal mice exhibited a reduced cavity of lateral ventricles and a discernable decrease in surface areas of the cortex. This study thus supports l;he conclusion that vertically transmitted ZIKV affects fetal brain development and provides a valuable animal model for the evaluation of potential therapeutic or preventative strategies.

Geniposide is a naturally sourced active ingredient that has diverse pharmacological effects and great potential in improving or treating different kinds of diseases. In recent years, more and more studies have confirmed that geniposide can improve glucose and lipid metabolism disorder, which is an increasingly prevalent health problem causing various metabolic diseases globally. Our review aims to summarize basic information on the pharmacological effects of geniposide on glucolipid metabolism. Geniposide increases glucose utilization and insulin production, protects pancreatic islet [beta] cells, inhibits insulin resistance and hepatic glucose production, and suppresses gluconeogenesis. While in the aspect of lipid metabolism, geniposide can promote lipolysis, inhibit lipogenesis, and regulate lipid transport. Geniposide ameliorates lipid and glucose metabolic disorders, improving the entire glycolipid metabolism network in a three-dimensional manner at the level of molecular mechanism. Growing evidence revealed that geniposide may serve as an effective drug to combat metabolic diseases for the time to come. Keywords: geniposide, lipid metabolism, glucose metabolism, Gardenia Jasminoides Ellis, metabolic disease, glucolipid metabolism, naturally sourced active ingredient, pharmacological evidence

Mice are some of the widely used experimental animal models for studying human diseases. Defining the compositions of immune cell populations in various tissues from experimental mouse models is critical to understanding the involvement of immune responses in various physiological and patho-physiological conditions. However, non-lymphoid tissues are normally composed of vast and diverse cellular components, which make it difficult to quantify the relative proportions of immune cell types. Here we report the development of a computational algorithm, ImmuCC, to infer the relative compositions of 25 immune cell types in mouse tissues using microarray-based mRNA expression data. The ImmuCC algorithm showed good performance and robustness in many simulated datasets. Remarkable concordances were observed when ImmuCC was used on three public datasets, one including enriched immune cells, one with normal single positive T cells, and one with leukemia cell samples. To validate the performance of ImmuCC objectively, thorough cross-comparison of ImmuCC predicted compositions and flow cytometry results was done with in-house generated datasets collected from four distinct mouse lymphoid tissues and three different types of tumor tissues. The good correlation and biologically meaningful results demonstrate the broad utility of ImmuCC for assessing immune cell composition in diverse mouse tissues under various conditions.

WiFi is widely used for indoor positioning because of its advantages such as long transmission distance and ease of use indoors. To improve the accuracy and robustness of indoor WiFi fingerprint localization technology, this paper proposes a positioning system CCPos (CADE-CNN Positioning), which is based on a convolutional denoising autoencoder (CDAE) and a convolutional neural network (CNN). In the offline stage, this system applies the K-means algorithm to extract the validation set from the all-training set. In the online stage, the RSSI is first denoised and key features are extracted by the CDAE. Then the location estimation is output by the CNN. In this paper, the Alcala Tutorial 2017 dataset and UJIIndoorLoc are adopted to verify the performance of the CCpos system. The experimental results show that our system has excellent noise immunity and generalization performance. The mean positioning errors on the Alcala Tutorial 2017 dataset and the UJIIndoorLoc are 1.05 m and 12.4 m, respectively.

Lactobacillus species are widely used in various food products, including conventional food products, dairy products, and health food products. To achieve the desired functional properties, manufacturers commonly incorporate two or more distinct Lactobacillus species during production. In this study, a multiplex PCR detection method was developed for four Lactobacillus species commonly used in food based on TaqMan real-time fluorescent PCR technology, enabling the efficient and rapid identification of multiple Lactobacillus strains in food matrices. The research team selected and validated four representative species—Lactobacillus rhamnosus, Lactobacillus plantarum, Lactobacillus acidophilus, and Lactobacillus paracasei—as targets for the multiplex PCR assay, designing specific primer–probe combinations for each. The accuracy and reliability of the detection method were rigorously evaluated through a series of validation experiments, including the assessment of primer–probe specificity, optimization of fluorescent signal labeling chemistries, determination of the limits of detection for individual strains, evaluation of the method’s repeatability, and analysis of commercial food samples. The results demonstrated that the selected primer–probe sets exhibited no cross-reactivity in the multiplex system and specifically amplified their target Lactobacillus species, with no amplification observed for non-target strains. The established method achieved a minimum LOD for L. acidophilus of 102 CFU/g and showed high repeatability across replicates. Furthermore, the successful detection of labeled Lactobacillus strains in commercial products confirmed the method’s practical applicability. Therefore, the developed multiplex real-time PCR assay provides a reliable, sensitive, and high-throughput tool for the simultaneous detection of multiple Lactobacillus species in complex food products and holds potential for application in quality control, product authentication, and regulatory compliance monitoring.

Background Numerous studies have highlighted that long non-coding RNAs (lncRNAs) can bind to microRNA (miRNA) sites as competing endogenous RNAs (ceRNAs), thereby affecting and regulating the expression of mRNAs and target genes. These lncRNA-associated ceRNAs have been theorized to play a significant role in cancer initiation and progression. However, the roles and functions of the lncRNA-miRNA-mRNA ceRNA network in squamous cell carcinoma of the tongue (SCCT) are still unclear. Methods The miRNA, mRNA and lncRNA expression profiles from 138 patients with SCCT were downloaded from The Cancer Genome Atlas database. We identified the differential expression of miRNAs, mRNAs, and lncRNAs using the limma package of R software. We used the clusterProfiler package for GO and KEGG pathway annotations. The survival package was used to estimate survival analysis according to the Kaplan-Meier curve. Finally, the GDCRNATools package was used to construct the lncRNA-miRNA-mRNA ceRNA network. Results In total, 1943 SCCT-specific mRNAs, 107 lncRNAs and 100 miRNAs were explored. Ten mRNAs (CSRP2, CKS2, ADGRG6, MB21D1, GMNN, RIPOR3, RAD51, PCLAF, ORC1, NAGS), 9 lncRNAs (LINC02560, HOXC13 − AS, FOXD2 − AS1, AC105277.1, AC099850.3, STARD4 − AS1, SLC16A1 − AS1, MIR503HG, MIR100HG) and 8 miRNAs (miR − 654, miR − 503, miR − 450a, miR − 379, miR − 369, miR − 190a, miR − 101, and let−7c) were found to be significantly associated with overall survival (log-rank p  < 0.05). Based on the analysis of the lncRNA-miRNA-mRNA ceRNA network, one differentially expressed (DE) lncRNA, five DEmiRNAs, and three DEmRNAs were demonstrated to be related to the pathogenesis of SCCT. Conclusions In this study, we described the gene regulation by the lncRNA-miRNA-mRNA ceRNA network in the progression of SCCT. We propose a new lncRNA-associated ceRNA that could help in the diagnosis and treatment of SCCT.