The outbreak of the novel coronavirus in China (SARS-CoV-2) that began in December 2019 presents a significant and urgent threat to global health. This study was conducted to provide the international community with a deeper understanding of this new infectious disease. Epidemiological, clinical features, laboratory findings, radiological characteristics, treatment, and clinical outcomes of 135 patients in northeast Chongqing were collected and analyzed in this study. A total of 135 hospitalized patients with COVID-19 were enrolled. The median age was 47 years (interquartile range, 36-55), and there was no significant gender difference (53.3% men). The majority of patients had contact with people from the Wuhan area. Fortythree (31.9%) patients had underlying disease, primarily hypertension (13 [9.6%]), diabetes (12 [8.9%]), cardiovascular disease (7 [5.2%]), and malignancy (4 [3.0%]). Common symptoms included fever (120 [88.9%]), cough (102 [76.5%]), and fatigue (44 [32.5%]). Chest computed tomography scans showed bilateral patchy shadows or ground glass opacity in the lungs of all the patients. All patients received antiviral therapy (135 [100%]) (Kaletra and interferon were both used), antibacterial therapy (59 [43.7%]), and corticosteroids (36 [26.7%]). In addition, many patients received traditional Chinese medicine (TCM) (124 [91.8%]). It is suggested that patients should receive Kaletra early and should be treated by a combination of Western and Chinese medicines. Compared to the mild cases, the severe ones had lower Suxin Wan, Yi Xiang, and Wei Fang are the co-first authors.

Tumorigenesis is a complex and dynamic process, consisting of three stages: initiation, progression, and metastasis. Tumors are encircled by extracellular matrix (ECM) and stromal cells, and the physiological state of the tumor microenvironment (TME) is closely connected to every step of tumorigenesis. Evidence suggests that the vital components of the TME are fibroblasts and myofibroblasts, neuroendocrine cells, adipose cells, immune and inflammatory cells, the blood and lymphatic vascular networks, and ECM. This manuscript, based on the current studies of the TME, offers a more comprehensive overview of the primary functions of each component of the TME in cancer initiation, progression, and invasion. The manuscript also includes primary therapeutic targeting markers for each player, which may be helpful in treating tumors.

Circular RNAs (circRNAs) are connected at the 3′ and 5′ ends by exon or intron cyclization, forming a complete ring structure. circRNA is more stable and conservative than linear RNA and abounds in various organisms. In recent years, increasing numbers of reports have found that circRNA plays a major role in the biological functions of a network of competing endogenous RNA (ceRNA). circRNAs can compete together with microRNAs (miRNAs) to influence the stability of target RNAs or their translation, thus, regulating gene expression at the transcriptional level. circRNAs are involved in biological processes such as tumor cell proliferation, apoptosis, invasion, and migration as ceRNAs. circRNAs, therefore, represent promising candidates for clinical diagnosis and treatment. Here, we review the progress in studying the role of circRNAs as ceRNAs in tumors and highlight the participation of circRNAs in signal transduction pathways to regulate cellular functions.

The ability of engineered biological nanomachines to communicate with biological systems at the molecular level is anticipated to enable future applications such as monitoring the condition of a human body, regenerating biological tissues and organs, and interfacing artificial devices with neural systems. From the viewpoint of communication theory and engineering, molecular communication is proposed as a new paradigm for engineered biological nanomachines to communicate with the natural biological nanomachines which form a biological system. Distinct from the current telecommunication paradigm, molecular communication uses molecules as the carriers of information; sender biological nanomachines encode information on molecules and release the molecules in the environment, the molecules then propagate in the environment to receiver biological nanomachines, and the receiver biological nanomachines biochemically react with the molecules to decode information. Current molecular communication research is limited to small-scale networks of several biological nanomachines. Key challenges to bridge the gap between current research and practical applications include developing robust and scalable techniques to create a functional network from a large number of biological nanomachines. Developing networking mechanisms and communication protocols is anticipated to introduce new avenues into integrating engineered and natural biological nanomachines into a single networked system. In this paper, we present the state-of-the-art in the area of molecular communication by discussing its architecture, features, applications, design, engineering, and physical modeling. We then discuss challenges and opportunities in developing networking mechanisms and communication protocols to create a network from a large number of bio-nanomachines for future applications.

Soaring cases of coronavirus disease (COVID-19) are pummeling the global health system. Overwhelmed health facilities have endeavored to mitigate the pandemic, but mortality of COVID-19 continues to increase. Here, we present a mortality risk prediction model for COVID-19 (MRPMC) that uses patients’ clinical data on admission to stratify patients by mortality risk, which enables prediction of physiological deterioration and death up to 20 days in advance. This ensemble model is built using four machine learning methods including Logistic Regression, Support Vector Machine, Gradient Boosted Decision Tree, and Neural Network. We validate MRPMC in an internal validation cohort and two external validation cohorts, where it achieves an AUC of 0.9621 (95% CI: 0.9464–0.9778), 0.9760 (0.9613–0.9906), and 0.9246 (0.8763–0.9729), respectively. This model enables expeditious and accurate mortality risk stratification of patients with COVID-19, and potentially facilitates more responsive health systems that are conducive to high risk COVID-19 patients.

BackgroundRadioresistance is a major factor leading to the failure of radiotherapy and poor prognosis in tumor patients. Following the application of radiotherapy, the activity of various metabolic pathways considerably changes, which may result in the development of resistance to radiation.Main bodyHere, we discussed the relationships between radioresistance and mitochondrial and glucose metabolic pathways, aiming to elucidate the interplay between the tumor cell metabolism and radiotherapy resistance. In this review, we additionally summarized the potential therapeutic targets in the metabolic pathways.Short conclusionThe aim of this review was to provide a theoretical basis and relevant references, which may lead to the improvement of the sensitivity of radiotherapy and prolong the survival of cancer patients.

Purpose: Multiplexing assay of biomarkers at the point-of-care is an elusive goal for molecular diagnostics. Experimental Design: Here, we report an electrochemical (EC) sensor for oral cancer detection based on the simultaneous detection of two salivary biomarkers: interleukin (IL)-8 mRNA and IL-8 protein.Results: Under the multiplexing mode, the limit of detection of salivary IL-8 mRNA reaches to 3.9 fM and 7.4 pg/mL for IL-8 protein in saliva. Multiplex assay of these 2 biomarkers directly from 28 cancer and 28 matched control saliva samples shows significant difference between the two groups. From the receiver operating characteristic analysis, the EC sensor yields around 90% sensitivity and specificity for both IL-8 mRNA and IL-8 protein, which are very close to the data measured by traditional assays (ELISA and PCR) with the same group of saliva. Combined IL-8 mRNA and protein show better AUC compared with single biomarker. Conclusions: We show, for the first time, concurrently multiplexing detection of salivary mRNA and protein biomarkers using point-of-care EC sensor.

The retinoblastoma protein-interacting zinc finger gene RIZ (PRDM2) is a member, by sequence homology, of a nuclear protein-methyltransferase (MTase) superfamily involved in chromatin-mediated gene expression. The gene produces two protein products, RIZ1 that contains a conserved MTase domain and RIZ2 that lacks the domain. RIZ1 gene expression is frequently silenced in human cancers, and the gene is also a common target of frameshift mutation in microsatellite-unstable cancers. We now report studies of mice with a targeted mutation in the RIZ1 locus. The mutation inactivates RIZ1 but not RIZ2. These RIZ1 mutant mice were viable and fertile but showed a high incidence of diffuse large B-cell lymphomas (DLBL) and a broad spectrum of unusual tumors. RIZ1 deficiency also accelerated tumorigenesis in p53 heterozygous mutant mice. Finally, several missense mutations of RIZ1 were found in human tumor tissues and cell lines; one of these was particularly common in human DLBL tumors. These missense mutations, as well as the previously described frameshift mutation, all mapped to the MTase functional domains. All abolished the capacity of RIZ1 to enhance estrogen receptor activation of transcription. These data suggest a direct link between tumor formation and the MTase domain of RIZ1 and describe for the first time a tumor susceptibility gene among methyltransferases.