A loosened gating mechanism of RIG-I leads to autoimmune disorders.

DDX58 encodes RIG-I, a cytosolic RNA sensor that ensures immune surveillance of nonself RNAs. Individuals with RIG-IE510V and RIG-IQ517H mutations have increased susceptibility to Singleton-Merten syndrome (SMS) defects, resulting in tissue-specific (mild) and classic (severe) phenotypes. The coupling between RNA recognition and conformational changes is central to RIG-I RNA proofreading, but the molecular determinants leading to dissociated disease phenotypes remain unknown. Herein, we employed hydrogen/deuterium exchange mass spectrometry (HDX-MS) and single molecule magnetic tweezers (MT) to precisely examine how subtle conformational changes in the helicase insertion domain (HEL2i) promote impaired ATPase and erroneous RNA proofreading activities. We showed that the mutations cause a loosened latch-gate engagement in apo RIG-I, which in turn gradually dampens its self RNA (Cap2 moiety:m7G cap and N1-2-2'-O-methylation RNA) proofreading ability, leading to increased immunopathy. These results reveal HEL2i as a unique checkpoint directing two specialized functions, i.e. stabilizing the CARD2-HEL2i interface and gating the helicase from incoming self RNAs; thus, these findings add new insights into the role of HEL2i in the control of antiviral innate immunity and autoimmunity diseases.

Synthetic robust perfect adaptation achieved by negative feedback coupling with linear weak positive feedback.

Unlike their natural counterparts, synthetic genetic circuits are usually fragile in the face of environmental perturbations and genetic mutations. Several theoretical robust genetic circuits have been designed, but their performance under real-world conditions has not yet been carefully evaluated. Here, we designed and synthesized a new robust perfect adaptation circuit composed of two-node negative feedback coupling with linear positive feedback on the buffer node. As a key feature, the linear positive feedback was fine-tuned to evaluate its necessity. We found that the desired function was robustly achieved when genetic parameters were varied by systematically perturbing all interacting parts within the topology, and the necessity of the completeness of the topological structures was evaluated by destroying key circuit features. Furthermore, different environmental perturbances were imposed onto the circuit by changing growth rates, carbon metabolic strategies and even chassis cells, and the designed perfect adaptation function was still achieved under all conditions. The successful design of a robust perfect adaptation circuit indicated that the top-down design strategy is capable of predictably guiding bottom-up engineering for robust genetic circuits. This robust adaptation circuit could be integrated as a motif into more complex circuits to robustly implement more sophisticated and critical biological functions.

Computed tomography-based radiomics improves non-invasive diagnosis of Pneumocystis jirovecii pneumonia in non-HIV patients: a retrospective study.

BACKGROUND: Pneumocystis jirovecii pneumonia (PCP) could be fatal to patients without human immunodeficiency virus (HIV) infection. Current diagnostic methods are either invasive or inaccurate. We aimed to establish an accurate and non-invasive radiomics-based way to identify the risk of PCP infection in non-HIV patients with computed tomography (CT) manifestation of pneumonia. METHODS: This is a retrospective study including non-HIV patients hospitalized for suspected PCP from January 2010 to December 2022 in one hospital. The patients were randomized in a 7:3 ratio into training and validation cohorts. Computed tomography (CT)-based radiomics features were extracted automatically and used to construct a radiomics model. A diagnostic model with traditional clinical and CT features was also built. The area under the curve (AUC) were calculated and used to evaluate the diagnostic performance of the models. The combination of the radiomics features and serum ß-D-glucan levels was also evaluated for PCP diagnosis. RESULTS: A total of 140 patients (PCP: N = 61, non-PCP: N = 79) were randomized into training (N = 97) and validation (N = 43) cohorts. The radiomics model consisting of nine radiomic features performed significantly better (AUC = 0.954; 95% CI: 0.898-1.000) than the traditional model consisting of serum ß-D-glucan levels (AUC = 0.752; 95% CI: 0.597-0.908) in identifying PCP (P = 0.002). The combination of radiomics features and serum ß-D-glucan levels showed an accuracy of 95.8% for identifying PCP infection (positive predictive value: 95.7%, negative predictive value: 95.8%). CONCLUSIONS: Radiomics showed good diagnostic performance in differentiating PCP from other types of pneumonia in non-HIV patients. A combined diagnostic method including radiomics and serum ß-D-glucan has the potential to provide an accurate and non-invasive way to identify the risk of PCP infection in non-HIV patients with CT manifestation of pneumonia. TRIAL REGISTRATION: ClinicalTrials.gov (NCT05701631).

Biosynthesis of long polyubiquitin chains in high yield and purity.

As one of the most prevalent protein post-translational modifications, ubiquitin modification plays a momentous role in regulating varied cellular functions. Different polyubiquitin linkage types have diverse effects on cell signaling. However, compared with short ubiquitin chains, the preparation of long ubiquitin chains remains difficult and expensive to purchase commercially. In this study, we constructed an enzyme library of ubiquitin-activating enzyme E1, ubiquitin-conjugating enzyme E2, and ubiquitin-ligase E3, which are specific for synthesizing K63, K48, and M1 linked polyubiquitin chains. We demonstrate that these distinctly linked polyubiquitin chains could be synthesized and purified with high yield and purity. More importantly, this method can synthesize longer ubiquitin chains, the longest can reach more than fifteen ubiquitin molecules, which provides great convenience for ubiquitin-related structural and functional studies.

A computerized tomography-based radiomic model for assessing the invasiveness of lung adenocarcinoma manifesting as ground-glass opacity nodules.

BACKGROUND: Clinically differentiating preinvasive lesions (atypical adenomatous hyperplasia, AAH and adenocarcinoma in situ, AIS) from invasive lesions (minimally invasive adenocarcinomas, MIA and invasive adenocarcinoma, IA) manifesting as ground-glass opacity nodules (GGOs) is difficult due to overlap of morphological features. Hence, the current study was performed to explore the diagnostic efficiency of radiomics in assessing the invasiveness of lung adenocarcinoma manifesting as GGOs. METHODS: A total of 1018 GGOs pathologically confirmed as lung adenocarcinoma were enrolled in this retrospective study and were randomly divided into a training set (n = 712) and validation set (n = 306). The nodules were delineated manually and 2446 intra-nodular and peri-nodular radiomic features were extracted. Univariate analysis and least absolute shrinkage and selection operator (LASSO) were used for feature selection. Clinical and semantic computerized tomography (CT) feature model, radiomic model and a combined nomogram were constructed and compared. Decision curve analysis (DCA) was used to evaluate the clinical value of the established nomogram. RESULTS: 16 radiomic features were selected and used for model construction. The radiomic model exhibited significantly better performance (AUC = 0.828) comparing to the clinical-semantic model (AUC = 0.746). Further analysis revealed that peri-nodular radiomic features were useful in differentiating between preinvasive and invasive lung adenocarcinomas appearing as GGOs with an AUC of 0.808. A nomogram based on lobulation sign and radiomic features showed the best performance (AUC = 0.835), and was found to have potential clinical value in assessing nodule invasiveness. CONCLUSIONS: Radiomic model based on both intra-nodular and peri-nodular features showed good performance in differentiating between preinvasive lung adenocarcinoma lesions and invasive ones appearing as GGOs, and a nomogram based on clinical, semantic and radiomic features could provide clinicians with added information in nodule management and preoperative evaluation.

The identifiability of gene regulatory networks: the role of observation data.

Identifying gene regulatory networks (GRN) from observation data is significant to understand biological systems. Conventional studies focus on improving the performance of identification algorithms. However, besides algorithm performance, the GRN identification is strongly depended on the observation data. In this work, for three GRN S-system models, three observation data collection schemes are used to perform the identifiability test procedure. A modified genetic algorithm-particle swarm optimization algorithm is proposed to implement this task, including the multi-level mutation operation and velocity limitation strategy. The results show that, in scheme 1 (starting from a special initial condition), the GRN systems are of identifiability using the sufficient transient observation data. In scheme 2, the observation data are short of sufficient system dynamic. The GRN systems are not of identifiability even though the state trajectories can be reproduced. As a special case of scheme 2, i.e., the steady-state observation data, the equilibrium point analysis is given to explain why it is infeasible for GRN identification. In schemes 1 and 2, the observation data are obtained from zero-input GRN systems, which will evolve to the steady state at last. The sufficient transient observation data in scheme 1 can be obtained by changing the experimental conditions. Additionally, the valid observation data can be also obtained by means of adding impulse excitation signal into GRN systems (scheme 3). Consequently, the GRN systems are identifiable using scheme 3. Owing to its universality and simplicity, these results provide a guide for biologists to collect valid observation data for identifying GRNs and to further understand GRN dynamics.

Adaptation through proportion.

Adaptation is a ubiquitous feature in biological sensory and signaling networks. It has been suggested that adaptive systems may follow certain simple design principles across diverse organisms, cells and pathways. One class of networks that can achieve adaptation utilizes an incoherent feedforward control, in which two parallel signaling branches exert opposite but proportional effects on the output at steady state. In this paper, we generalize this adaptation mechanism by establishing a steady-state proportionality relationship among a subset of nodes in a network. Adaptation can be achieved by using any two nodes in the sub-network to respectively regulate the output node positively and negatively. We focus on enzyme networks and first identify basic regulation motifs consisting of two and three nodes that can be used to build small networks with proportional relationships. Larger proportional networks can then be constructed modularly similar to LEGOs. Our method provides a general framework to construct and analyze a class of proportional and/or adaptation networks with arbitrary size, flexibility and versatile functional features.

Dietary Amino Acids Promote Glucagon-like Hormone Release to Generate Novel Calcium Waves in Adipose Tissues.

Nutrient sensing and the subsequent metabolic responses are fundamental functions of animals, closely linked to diseases such as type 2 diabetes and various obesity-related morbidities. Among different metabolic regulatory signals, cytosolic Ca2+ plays pivotal roles in metabolic regulation, including glycolysis, gluconeogenesis, and lipolysis. Recently, intercellular calcium waves (ICWs), the propagation of Ca2+ signaling through tissues, have been found in different systems to coordinate multicellular responses. Nevertheless, our understanding of how ICWs are modulated and operate within living organisms remains limited. In this study, we explore the real-time dynamics, both in organ culture and free-behaving animals, of ICWs in Drosophila larval and adult adipose tissues. We identified Adipokinetic hormone (AKH), the fly functional homolog of mammalian glucagon, as the key factor driving Ca2+ activities in adipose tissue. Interestingly, we found that AKH, which is released in a pulsatile manner into the circulating hemolymph from the AKH-producing neurosecretory cells (APCs) in the brain, stimulates ICWs in the larval fat by a previously unrecognized gap-junction-independent mechanism to promote lipolysis. In the adult fat body, however, gap-junction-dependent random ICWs are triggered by a presumably uniformly diffused AKH. This highlights the stage-specific interplay of hormone secretion, extracellular diffusion, and intercellular communication in the regulation of Ca2+ dynamics. Additionally, we discovered that specific dietary amino acids activate the APCs, leading to increased intracellular Ca2+ and subsequent AKH secretion. Altogether, our findings identify that dietary amino acids regulate the release of AKH peptides from the APCs, which subsequently stimulates novel gap-junction-independent ICWs in adipose tissues, thereby enhancing lipid metabolism.

Mitochondrial fission mediated by Drp1-Fis1 pathway and neurodegenerative diseases.

In recent years, the role of mitochondrial dynamics in neurodegenerative diseases has becoming increasingly important. More and more evidences have shown that in pathological conditions, abnormal mitochondrial divisions, especially Drp1-Fis1-mediated divisions, play an important role in the occurrence and development of Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease, glaucoma, and other neurodegenerative diseases. This review highlights several new mechanisms of physiological fission of mitochondria and the difference/connection of physiological/pathological mitochondrial fission. In addition, we described the relationship between abnormal mitochondrial dynamics and neurodegenerative diseases in detail and emphatically summarized its detection indicators in basic experiments, trying to provide references for further mechanism exploration and therapeutic targets.

Effects of growth feedback on gene circuits: A dynamical understanding.

The successful integration of engineered gene circuits into host cells remains a significant challenge in synthetic biology due to circuit-host interactions, such as growth feedback, where the circuit influences cell growth and vice versa. Understanding the dynamics of circuit failures and identifying topologies resilient to growth feedback are crucial for both fundamental and applied research. Utilizing transcriptional regulation circuits with adaptation as a paradigm, we systematically study 435 distinct topological structures and uncover six categories of failures. Three dynamical mechanisms of circuit failures are identified: continuous deformation of the response curve, strengthened or induced oscillations, and sudden switching to coexisting attractors. Our extensive computations also uncover a scaling law between a circuit robustness measure and the strength of growth feedback. Despite the negative effects of growth feedback on the majority of circuit topologies, we identify a few circuits that maintain optimal performance as designed, a feature important for applications.

MiR-93-5p inhibits retinal neurons apoptosis by regulating PDCD4 in acute ocular hypertension model.

The present study focused on the effect of miR-93-5p on apoptosis of retinal neurons in acute ocular hypertension (AOH) model by regulating PDCD4 and explored its related mechanism. We detected that miR-93-5p expression was decreased and PDCD4 expression was increased in the AOH retina by qRT-PCR. Therefore, we explored the role of miR-93-5p and PDCD4. MiR-93-5p overexpression inhibited the apoptosis of retinal neurons and the expression of PDCD4 in vivo and in vitro. Inhibiting the expression of PDCD4 via transfected interfering RNA decreased the apoptosis of retinal cells and increased the expression of PI3K/Akt pathway-related proteins in vitro. However, the addition of PI3K protein inhibitor LY294002 reversed this effect, leading to a decrease of PI3K/Akt pathway protein expression and an increase of apoptosis-related protein Bax/Bcl-2 expression ratio. Finally, up-regulating miR-93-5p or down-regulating PDCD4 increased the expression of PI3K/Akt pathway protein in vivo. In conclusion, under the condition of AOH injury, miR-93-5p-inhibiting PDCD4 expression reduced the apoptosis of retinal neurons by activating PI3K/Akt pathway.

RIG-I-like receptors: Molecular mechanism of activation and signaling.

During RNA viral infection, RIG-I-like receptors (RLRs) recognize the intracellular pathogenic RNA species derived from viral replication and activate antiviral innate immune response by stimulating type 1 interferon expression. Three RLR members, namely, RIG-I, MDA5, and LGP2 are homologous and belong to a subgroup of superfamily 2 Helicase/ATPase that is preferably activated by double-stranded RNA. RLRs are significantly different in gene architecture, RNA ligand preference, activation, and molecular functions. As switchable macromolecular sensors, RLRs' activities are tightly regulated by RNA ligands, ATP, posttranslational modifications, and cellular cofactors. We provide a comprehensive review of the structure and function of the RLRs and summarize the molecular understanding of sensing and signaling events during the RLR activation process. The key roles RLR signaling play in both anti-infection and immune disease conditions highlight the therapeutic potential in targeting this important molecular pathway.

Establishing a predictive model for tumor mutation burden status based on CT radiomics and clinical features of non-small cell lung cancer patients.

Background: Tumor mutation burden (TMB) is one of the biomarkers for efficacy of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC). Due to the potential of radiomic signatures to identify microscopic genetic and molecular differences, thus radiomics is considered a suitable tool for judging the TMB status probably. In this paper, the radiomics method was applied to analyze the TMB status of NSCLC patients, so as to construct a prediction model for distinguishing between TMB-high and TMB-low status. Methods: A total of 189 NSCLC patients with TMB detection result were retrospectively included between 30 November 2016 and 1 January 2021, and were divided into two groups: TMB-high (≥10/Mb, 46 patients) and TMB-low (<10/Mb, 143 patients). Some clinical features related to TMB status were screened out in 14 clinical features and 2,446 radiomic features were extracted. All patients were randomly divided into a training set (n=132) and a validation set (n=57). Univariate analysis and least absolute shrinkage and selection operator (LASSO) were used for radiomics feature screening. A clinical model, radiomics model, and nomogram were constructed with the above screened features and compared. Decision curve analysis (DCA) was used to evaluate the clinical value of the established models. Results: Two clinical features (smoking history, pathological type) and 10 radiomics features were significantly correlated with the TMB status. The prediction efficiency of the intra-tumoral model was better than that of the peritumoral model (AUC: 0.819 vs. 0.816; accuracy: 0.773 vs. 0.632, specificity: 0.767 vs. 0.558). The efficacy of the prediction model based on radiomic features was significantly better than that of the clinical model (AUC: 0.822 vs. 0.683; specificity: 0.786 vs. 0.643). The nomogram, established by combining smoking history, pathologic type, and rad-score, showed the best diagnostic efficacy (AUC =0.844) and had potential clinical value in assessing the TMB status of NSCLC. Conclusions: The radiomics model based on CT images of NSCLC patients performed well in distinguishing the status of TMB-high and TMB-low, and the nomogram could provide additional information on the timing and regimen of immunotherapy.

Tri-Channel Electrochemical Immunobiosensor for Combined Detections of Multiple Exosome Biomarkers of Lung Cancer.

Current methods for the early diagnosis of cancer can be invasive and costly. In recent years, exosomes have been recognized as potential biomarkers for cancer diagnostics. The common methods for quantitative detection of exosomes, such as nanoparticle tracking analysis (NTA) and flow cytometry, rely on large-scale instruments and complex operation, with results not specific for cancer. Herein, we present a tri-channel electrochemical immunobiosensor for enzyme-free and label-free detecting carcino-embryonic antigen (CEA), neuron-specific enolase (NSE), and cytokeratin 19 fragments (Cyfra21-1) from exosomes for specific early diagnosis of lung cancer. The electrochemical immunobiosensor showed good selectivity and stability. Under optimum experimental conditions, the linear ranges were from 10-3 to 10 ng/mL for CEA, 10-4 to 102 ng/mL for NSE, and 10-3 to 102 ng/mL for Cyfra21-1, and a detection limit down to 10-4 ng/mL was achieved. Furthermore, we performed exosome analysis in three kinds of lung cancer. The results showed a distinct expression level of exosomal markers in different types. These works provide insight into a promising alternative for the quantification of exosomal markers in specific diseases in the following clinical bioassays.

Predicting Ki-67 labeling index level in early-stage lung adenocarcinomas manifesting as ground-glass opacity nodules using intra-nodular and peri-nodular radiomic features.

OBJECTIVES: To explore the diagnostic value of radiomics in differentiating between lung adenocarcinomas appearing as ground-glass opacity nodules (GGO) with high- and low Ki-67 expression levels. MATERIALS AND METHODS: From January 2018 to January 2021, patients with pulmonary GGO who received lung resection were evaluated for potential enrollment. The included GGOs were then randomly divided into a training cohort and a validation cohort with a ratio of 7:3. Logistic regression (LR), decision tree (DT), support vector machines (SVM), and adaboost (AB) were applied for radiomic model construction. Area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the established models. RESULTS: Seven hundred and sixty-nine patients with 769 GGOs were included in this study. Two hundred and forty-five GGOs were confirmed to be of high Ki-67 labeling index (LI). In the training cohort, gender, age, spiculation sign, pleural indentation sign, bubble sign, and maximum 2D diameter of the nodule were found to be significantly different between high- and low Ki-67 LI groups (p < 0.05), and spiculation sign and maximum 2D diameter of the nodule were further confirmed to be risk factors for Ki-67 LI. The radiomic model established using SVM exhibited an AUC of 0.731 in the validation cohort, which was higher than that of the clinical-radiographic model (AUC = 0.675). Moreover, radiomic model combining both intra- and peri-nodular features showed better diagnostic efficacy than using intra-nodular features alone (AUC = 0.731 and 0.720, respectively). CONCLUSIONS: The established radiomic model exhibited good diagnostic efficacy in differentiating between lung adenocarcinoma GGOs with high and low Ki-67 LI, which was higher than the clinical-radiographic model. Peri-nodular radiomic features showed added benefits to the radiomic model. As a novel noninvasive method, radiomics have the potential to be applied in the preliminary classification of Ki-67 expression level in lung adenocarcinoma GGOs.

Correlation between PD-L1 expression and radiomic features in early-stage lung adenocarcinomas manifesting as ground-glass nodules.

Background: Immunotherapy might be a promising auxiliary or alternative systemic treatment for early-stage lung adenocarcinomas manifesting as ground-glass nodules (GGNs). This study intended to investigate the PD-L1 expression in these patients, and to explore the non-invasive prediction model of PD-L1 expression based on radiomics. Methods: We retrospectively analyzed the PD-L1 expression of patients with postoperative pathological diagnosis of lung adenocarcinomas and with imaging manifestation of GGNs, and divided patients into positive group and negative group according to whether PD-L1 expression ≥1%. Then, CT-based radiomic features were extracted semi-automatically, and feature dimensions were reduced by univariate analysis and LASSO in the randomly selected training cohort (70%). Finally, we used logistic regression algorithm to establish the radiomic models and the clinical-radiomic combined models for PD-L1 expression prediction, and evaluated the prediction efficiency of the models with the receiver operating characteristic (ROC) curves. Results: A total of 839 "GGN-like lung adenocarcinoma" patients were included, of which 226 (26.9%) showed positive PD-L1 expression. 779 radiomic features were extracted, and 9 of them were found to be highly corelated with PD-L1 expression. The area under the curve (AUC) values of the radiomic models were 0.653 and 0.583 in the training cohort and test cohort respectively. After adding clinically significant and statistically significant clinical features, the efficacy of the combined model was slightly improved, and the AUC values were 0.693 and 0.598 respectively. Conclusions: GGN-like lung adenocarcinoma had a fairly high positive PD-L1 expression rate. Radiomics was a hopeful noninvasive method for predicting PD-L1 expression, with better predictive efficacy in combination with clinical features.

(-)-Epigallocatechin Gallate is a Noncompetitive Inhibitor of NAD Kinase.

Nicotinamide adenine dinucleotide kinase (NADK) controls the intracellular NADPH content and provides reducing power for the synthesis of macromolecules and anti-ROS. Moreover, NADK is considered to be a synthetic lethal gene for KRAS mutations. To discover NADK-targeted probes, a high-throughput screening assay was established and optimized with a Z factor of 0.71. The natural product (-)-epigallocatechin gallate (EGCG) was found to be a noncompetitive inhibitor of NADK with K i = 3.28 ± 0.32 µΜ. The direct binding of EGCG to NADK was determined by several biophysical methods, including NMR spectroscopy, surface plasmon resonance (SPR) assay, and hydrogen-deuterium exchange mass spectrometry (HDX-MS). The SPR assay showed a K d of 1.78 ± 1.15 µΜ. The HDX-MS experiment showed that EGCG was bound at the non-substrate-binding sites of NADK. Besides, binding mode prediction and derivative activity analysis revealed a potential structure-activity relationship between EGCG and NADK. Furthermore, EGCG can specifically inhibit the proliferation of KRAS-mutated lung cancer cell lines without affecting KRAS wild-type lung cancer cell lines.

Modeling the Spatiotemporal Association Between COVID-19 Transmission and Population Mobility Using Geographically and Temporally Weighted Regression.

The ongoing Coronavirus Disease 2019 (COVID-19) has posed a serious threat to human public health and global economy. Population mobility is an important factor that drives the spread of COVID-19. This study aimed to quantitatively evaluate the impact of population flow on the spread of COVID-19 from a spatiotemporal perspective. To this end, a case study was carried out in Hubei Province, which was once the most affected area of COVID-19 outbreak in Mainland China. The geographically and temporally weighted regression (GTWR) model was applied to model the spatiotemporal association between COVID-19 epidemic and population mobility. Two patterns of population flows, including the population inflow from Wuhan and intra-city population movement, were considered to construct explanatory variables. Results indicate that the GTWR model can reveal the spatial-temporal-varying relationships between COVID-19 and population mobility. Moreover, the association between COVID-19 case counts and population movements presented three stages of temporal variation characteristics due to the virus incubation period and implementation of strict lockdown measures. In the spatial dimension, evident geographical disparities were observed across Hubei Province. These findings can provide policymakers useful knowledge about the impact of population movement on the spatio-temporal transmission of COVID-19. Thus, targeted interventions, if necessary in certain time periods, can be implemented to restrict population flow in cities with high transmission risk.

Biomarkers or factors for predicting the efficacy and adverse effects of immune checkpoint inhibitors in lung cancer: achievements and prospective.

Immune checkpoint inhibitors (ICIs) are widely used in lung cancer therapy due to their effectiveness and minimal side effects. However, only a few lung cancer patients benefit from ICI therapy, driving the need to develop alternative biomarkers. Programmed death-ligand 1 (PD-L1) molecules expressed in tumor cells and immune cells play a key role in the immune checkpoint pathway. Therefore, PD-L1 expression is a prognostic biomarker in evaluating the effectiveness of programmed death-1 (PD-1)/PD-L1 inhibitors. Nevertheless, adverse predictive outcomes suggest that other factors are implicated in the response. In this review, we present a detailed introduction of existing biomarkers concerning tumor abnormality and host immunity. PD-L1 expression, tumor mutation burden, neoantigens, specific gene mutations, circulating tumor DNA, human leukocyte antigen class I, tumor microenvironment, peripheral inflammatory cells, and microbiome are discussed in detail. To sum up, this review provides information on the current application and future prospects of ICI biomarkers.

The Potential Transmission of SARS-CoV-2 from Patients with Negative RT-PCR Swab Tests to Others: Two Related Clusters of COVID-19 Outbreak.

In December 2019, a cluster of cases of acute respiratory illness, novel coronavirus-infected pneumonia, occurred in Wuhan, Hubei Province, China. The false-negative nasopharyngeal swabs for SARS-CoV-2 caused delayed diagnosis of COVID-19, which hindered the prevention and control of the pandemic. The transmission risk of SARS-CoV-2 in negative nasopharyngeal swabs cases has rarely been addressed previously. This study evaluated two clusters of COVID-19 in six patients, four of whom (66.7%) tested negative for RNA of SARS-CoV-2 on RT-PCR of nasopharyngeal swabs. All epidemiological, clinical, and laboratory data were collected. The first cluster was a nosocomial infection of four health care providers in early January. One case resulted in a sequential familial cluster of infection. All patients either self-quarantined at home or were admitted to hospital for isolated treatment. All recovered and were anti-SARS-CoV-2 IgG- and/or IgM-positive (100%) for serological detection of SARS-CoV-2 at the recovery stage. Our study provides a cautionary warning that negative results for nasopharyngeal swabs of suspected SARS-CoV-2 infection can increase the risk of nosocomial infection among health care providers. Serologic detection for anti-SARS-CoV-2 IgG and/or IgM is an important test in the diagnosis of COVID-19.