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Saliva testing is a vital method for clinical applications, for its noninvasive features, richness in substances, and the huge amount. Due to its direct anatomical connection with oral, digestive, and endocrine systems, clinical usage of saliva testing for these diseases is promising. Furthermore, for other diseases that seeming to have no correlations with saliva, such as neurodegenerative diseases and psychological diseases, researchers also reckon saliva informative. Tremendous papers are being produced in this field. Updated summaries of recent literature give newcomers a shortcut to have a grasp of this topic. Here, we focused on recent research about saliva biomarkers that are derived from humans, not from other organisms. The review mostly addresses the proceedings from 2016 to 2022, to shed light on the promising usage of saliva testing in clinical diagnostics. We recap the recent advances following the category of different types of biomarkers, such as intracellular DNA, RNA, proteins and intercellular exosomes, cell-free DNA, to give a comprehensive impression of saliva biomarker testing.

By Jan 31, 2020, the National Medical Products Administration urgently approved six nucleic acid detection kits, and post-market evaluation with a multicentre clinical trial was completed by professional institutions by the end of February, 2020. NAAT laboratories have been in development across China for decades; thousands of NAAT laboratories for detecting infectious agents such as hepatitis B virus, hepatitis C virus, and HIV are established in large hospitals, blood centres, and in the Chinese Center for Disease Control and Prevention. To improve the efficiency of mass screening, China has adopted the sample pooling strategy in three patterns (five, ten, or 20 pooled samples) on the basis of different epidemic periods.4,5 With the optimisation of sample pooling methodology and development of an electronic information system, this sample pooling strategy ensures both high sensitivity and efficiency.

Clustered regularly interspaced short palindromic repeats (CRISPR)–Cas9 editing of immune checkpoint genes could improve the efficacy of T cell therapy, but the first necessary undertaking is to understand the safety and feasibility. Here, we report results from a first-in-human phase I clinical trial of CRISPR–Cas9 PD-1 -edited T cells in patients with advanced non-small-cell lung cancer (ClinicalTrials.gov NCT02793856 ). Primary endpoints were safety and feasibility, and the secondary endpoint was efficacy. The exploratory objectives included tracking of edited T cells. All prespecified endpoints were met. PD-1 -edited T cells were manufactured ex vivo by cotransfection using electroporation of Cas9 and single guide RNA plasmids. A total of 22 patients were enrolled; 17 had sufficient edited T cells for infusion, and 12 were able to receive treatment. All treatment-related adverse events were grade 1/2. Edited T cells were detectable in peripheral blood after infusion. The median progression-free survival was 7.7 weeks (95% confidence interval, 6.9 to 8.5 weeks) and median overall survival was 42.6 weeks (95% confidence interval, 10.3–74.9 weeks). The median mutation frequency of off-target events was 0.05% (range, 0–0.25%) at 18 candidate sites by next generation sequencing. We conclude that clinical application of CRISPR–Cas9 gene-edited T cells is generally safe and feasible. Future trials should use superior gene editing approaches to improve therapeutic efficacy. In a first-in-human phase I trial of patients with advanced lung cancer, infusions of autologous T cells edited to delete the PD-1 gene via CRISPR–Cas9 were well tolerated and did not lead to severe treatment-related adverse events.

Improved sanitation, increased access to health care, and advances in preventive and clinical medicine have reduced the mortality and morbidity rates of several infectious diseases. However, recent outbreaks of several emerging infectious diseases (EIDs) have caused substantial mortality and morbidity, and the frequency of these outbreaks is likely to increase due to pathogen, environmental, and population effects driven by climate change. Extreme or persistent changes in temperature, precipitation, humidity, and air pollution associated with climate change can, for example, expand the size of EID reservoirs, increase host-pathogen and cross-species host contacts to promote transmission or spillover events, and degrade the overall health of susceptible host populations leading to new EID outbreaks. It is therefore vital to establish global strategies to track and model potential responses of candidate EIDs to project their future behaviour and guide research efforts on early detection and diagnosis technologies and vaccine development efforts for these targets. Multi-disciplinary collaborations are demanding to develop effective inter-continental surveillance and modelling platforms that employ artificial intelligence to mitigate climate change effects on EID outbreaks. In this review, we discuss how climate change has increased the risk of EIDs and describe novel approaches to improve surveillance of emerging pathogens that pose the risk for EID outbreaks, new and existing measures that could be used to contain or reduce the risk of future EID outbreaks, and new methods to improve EID tracking during further outbreaks to limit disease transmission.

Seawater electrolysis driven by offshore renewable energy is a promising avenue for large-scale hydrogen production but faces challenges in designing robust anodes that suppress surface chlorine reactions and corrosion at high current densities. Here we report a strategy by selectively docking PW 12 -polyoxometalate (PW 12 -POM) onto Fe sites of CoFe hydroxide anode to modulate the electronic structure of adjacent Co active centers and regulate Cl⁻/OH⁻ adsorption for efficient alkaline seawater oxidation. Our CoFe-based anode achieves low overpotentials, high catalytic selectivity, and notable durability, with continuous operation at 1 A cm⁻² for over 1300 hours and at 2 A cm⁻² more than 600 hours. Theoretical calculations and ex situ/in situ analyses reveal that PW 12 -POM coordination at Fe sites stabilizes Fe, suppresses its leaching, modulates Co acidity, promotes OH⁻ adsorption, and protects metal sites from Cl⁻ corrosion. Seawater electrolysis for hydrogen production faces challenges in creating robust anodes that resist corrosion. Here, the authors report a PW 12 -polyoxometalate-modified CoFe hydroxide anode that achieves selective and durable seawater oxidation over 1300 hours at 1 A cm⁻².

In this study, we aimed to elucidate the role of PBMC gene expression in ICI treatment response and prognosis. According to Response Evaluation Criteria in Solid Tumours version 1.1 (RECIST version 1.1), patients with no disease progression (PD) or tumor-induced deaths within 6 months of anti-PD-1/PD-L1 treatment, including those with complete response (CR), partial response (PR), or stable disease (SD), were grouped as ICI responders. Currently, the cause-and-effect relationship is not fully understood; however, our study proposes that the loss of chromosome Y (LOY) or extreme downregulation of chromosome Y (EDY) in immune cells may lead to a decrease in the proportion of lymphocytes, thereby resulting in primary resistance to PD-1/PD-L1 blockade immunotherapy. [...]DDX3Y and USP9Y emerge as useful biomarkers for predicting PD-1/PD-L1 blockade response.

It is generally recognized that tumor cells proliferate more rapidly than normal cells. Due to such an abnormally rapid proliferation rate, cancer cells constantly encounter the limits of insufficient oxygen and nutrient supplies. To satisfy their growth needs and resist adverse environmental events, tumor cells modify the metabolic pathways to produce both extra energies and substances required for rapid growth. Realizing the metabolic characters special for tumor cells will be helpful for eliminating them during therapy. Cell death is a hot topic of long-term study and targeting cell death is one of the most effective ways to repress tumor growth. Many studies have successfully demonstrated that metabolism is inextricably linked to cell death of cancer cells. Here we summarize the recently identified metabolic characters that specifically impact on different types of cell deaths and discuss their roles in tumorigenesis.

We systematically summarized tuberculosis (TB)‐related non‐coding RNA (ncRNA) diagnostic panels, validated and compared panel performance. We searched TB‐related ncRNA panels in PubMed, OVID and Web of Science up to 28 February 2020, and available datasets in GEO, SRA and EBI ArrayExpress up to 1 March 2020. We rebuilt models and synthesized the results of each model in validation sets by bivariate mixed models. Specificity at 90% sensitivity, area under curve (AUC) and inconsistence index (I2) were calculated. NcRNA biofunctions were analysed. Nineteen models based on 18 ncRNA panels (miRNA, lncRNA, circRNA and snoRNA panels) and 18 datasets were included. Limited available datasets only allowed to evaluate miRNA panels further. Cui 2017 and Latorre 2015 exhibited specificity >70% at 90% sensitivity and AUC >80% in all validation sets. Cui 2017 showed higher specificity at 90% sensitivity (92%) and AUC (95%) and lower heterogeneity (I2 = 0%) in ethological‐confirmation validation sets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that most ncRNAs in panels involved in immune cell activation, oxidative stress, and Wnt and MAPK signalling pathway. Cui 2017 outperformed other models in both all available and aetiological‐confirmed validation sets, meeting the criteria of target product profile of WHO. This work provided a basis for clinical choice of TB‐related ncRNA diagnostic panels to a certain extent.

Objective Programmed death 1 (PD-1) and macrophages are the most intriguing candidates in sepsis-induced inflammatory disorders. We aimed to investigate the association between monocyte PD-1 and sepsis severity and the mechanism by which blocking macrophage-associated PD-1 causes inflammatory disorders in sepsis. Materials and methods We first measured whether the expression of PD-1 on the monocyte subset is clinically associated with sepsis severity in an observational study. This study included 42 septic patients and 16 healthy controls (HCs) whose serum inflammatory factors were examined by Luminex MagPix. Then, we investigated the effect of PD-1 blockade on macrophages from septic mice (C57BL/6 mice) constructed by caecal ligation and puncture (CLP) via RNA sequencing. The positive genes screened by RNA-seq were verified in LPS-stimulated RAW264.7 cells by Western blot. Results The results showed that the expression of PD-1 on CD14 + CD16 + monocytes (intermediate monocytes, IM Mo) was significantly higher in both septic and septic shock patients than in HCs. Further analysis of serum cytokines in septic patients showed that the levels of IL-6 and TNF-α were significantly higher than those in HCs, while serum PD-1 levels were decreased in septic patients. More interestingly, blockade of PD-1 on macrophages from septic mice suppressed the gene expression levels of NLRP3/Caspase-4/AKT2/STAT3. The protein levels associated with pyroptosis including NLRP3, Caspase4, GSDMD and NT-GSDMD were significantly decreased in LPS-stimulated RAW264.7 cells treated with PD-1 antibody. Conclusion Our results suggested that intermediate monocytes with high expression of PD-1 may be involved in the progression of sepsis. PD-1 might play a critical role in regulating the pyroptosis signalling pathway in sepsis.

Tuberculosis (TB) remains one of the leading causes of death among infectious diseases worldwide. Early screening and diagnosis of pulmonary tuberculosis (PTB) is crucial in TB control, and tend to benefit from artificial intelligence. Here, we aimed to evaluate the diagnostic efficacy of a variety of artificial intelligence methods in medical imaging for PTB. We searched MEDLINE and Embase with the OVID platform to identify trials published update to November 2022 that evaluated the effectiveness of artificial-intelligence-based software in medical imaging of patients with PTB. After data extraction, the quality of studies was assessed using quality assessment of diagnostic accuracy studies 2 (QUADAS-2). Pooled sensitivity and specificity were estimated using a bivariate random-effects model. In total, 3987 references were initially identified and 61 studies were finally included, covering a wide range of 124,959 individuals. The pooled sensitivity and the specificity were 91% (95% confidence interval (CI), 89–93%) and 65% (54–75%), respectively, in clinical trials, and 94% (89–96%) and 95% (91–97%), respectively, in model-development studies. These findings have demonstrated that artificial-intelligence-based software could serve as an accurate tool to diagnose PTB in medical imaging. However, standardized reporting guidance regarding AI-specific trials and multicenter clinical trials is urgently needed to truly transform this cutting-edge technology into clinical practice.