Respiratory syncytial virus (RSV) infection causes significant morbidity and mortality in infants, immunocompromised individuals, and older individuals. There is an urgent need for effective antivirals and vaccines for high-risk individuals. We used 2 complementary in vivo models to analyze RSV-associated human lung pathology and human immune correlates of protection. RSV infection resulted in widespread human lung epithelial damage, a proinflammatory innate immune response, and elicited a natural adaptive human immune response that conferred protective immunity. We demonstrated a key role for human T cells in controlling RSV infection. Specifically, primed human CD8 ⁺ T cells or CD4 ⁺ T cells effectively and independently control RSV replication in human lung tissue in the absence of an RSV-specific antibody response. These preclinical data support the development of RSV vaccines, which also elicit effective T cell responses to improve RSV vaccine efficacy.

Background: Since the pandemic outbreak of coronavirus disease 2019 (COVID-19), the health system capacity in highly endemic areas has been overwhelmed. Approaches to efficient management are urgently needed. We aimed to develop and validate a score for early prediction of clinical deterioration of COVID-19 patients. Methods: In this retrospective multicenter cohort study, we included 1138 mild to moderate COVID-19 patients admitted to 33 hospitals in Guangdong Province from December 27, 2019 to March 4, 2020 (N =818; training cohort), as well as two hospitals in Hubei Province from January 21 to February 22, 2020 (N =320; validation cohort) in the analysis. Results: The 14-day cumulative incidences of clinical deterioration were 7.9% and 12.1% in the training and validation cohorts, respectively. An Early WArning Score (EWAS) (ranging from 0 to 4.5), comprising of age, underlying chronic disease, neutrophil to lymphocyte ratio, C-reactive protein, and D-dimer levels, was developed (AUROC: 0.857). By applying the EWAS, patients were categorized into low-, medium-, and high risk groups (cut-off values: two and three). The 14-day cumulative incidence of clinical deterioration in the low-risk group was 1.8%, which was significantly lower than the incidence rates in the medium-(14.4%) and high-risk (40.9%) groups (P <.001). The predictability of EWAS was similar in the validation cohort (AUROC =0.781), patients in the low-, medium-, and high-risk groups had 14-day cumulative incidences of 2.6%, 10.0%, and 25.7%, respectively (P <.001). Conclusion: The EWAS, which is based on five common parameters, can predict COVID-19-related clinical deterioration and may be a useful tool for a rapid triage and establishing a COVID-19 hierarchical management system that will greatly focus clinical management and medical resources to reduce mortality in highly endemic areas.

: Guangdong, China, has experienced several dengue epidemics involving thousands of confirmed cases in recent decades, and elderly individuals suffered severe dengue (SD) most seriously. However, the clinical characteristics and risk factors for SD among elderly patients in Guangdong have not been investigated. Patients older than 65 years were recruited and divided into a dengue fever (DF) group and an SD group according to the 2009 Dengue Guidelines of the WHO. We analyzed the clinical manifestations of the elderly patients with dengue and then assessed the risk factors for SD. Of a total of 1,027 patients, 868 patients were diagnosed as having DF and 159 as having SD. Of the 159 elderly patients with SD, 129 (81%) had comorbidities, with hypertension being the most common. Severe organ impairment (SOI) (115, 54%) was the most common presentation in SD patients, followed by severe plasma leakage (52, 24.4%) and severe hemorrhage (46, 21.6%). The most common symptom of SOI was kidney injury, followed by heart injury and central nervous system injury. Furthermore, multivariate regression revealed that the presence of chronic obstructive pulmonary disease (COPD), a lower red blood cell (RBC) count (≤3.5 × 10¹²/L; odds ratio [OR], 0.35; 95% CI, 0.17–0.55; P <0.001), lower serum albumin (ALB) (≤35 U/L; OR, 0.18; 95% CI, 0.09–0.32; P <0.001), and hyperpyrexia (body temperature ≥39°C; OR, 1.8; 95% CI, 1.2–2.6, P <0.001) were risk factors for SD. Severe organ impairment was the predominant manifestation in elderly individuals with SD characterized by kidney injury. The potential risk factors of SD such as presence of COPD and hyperpyrexia and lower RBC and ALB levels might help clinicians identify patients with SD early.

Hepatocellular carcinoma (HCC) ranks among the top causes of cancer-related mortality worldwide, and its complex tumor microenvironment (TME) contributes to poor responses to immunotherapy. Although PD-1/PD-L1 blockade has emerged as an effective treatment strategy, therapeutic resistance frequently limits its clinical benefit. Here, we uncover a distinct macrophage population associated with anti-PD-1 resistance in HCC. Single-cell transcriptomic profiling reveals an NFKBIZ⁺ M0 macrophage subset predominantly present in non-responders. Notably, these macrophages exhibit a hypoxia-induced phenotype characterized by the secretion of VEGFA and HBEGF, which cooperatively enhance tumor angiogenesis, alongside an elevated expression of the inflammatory chemokines CXCL2, CXCL3, and CXCL8 that consolidate an immunosuppressive, pro-tumorigenic microenvironment. Transcriptional regulatory network analysis further identified FOSB–VEGFA and FOS–HBEGF axes as key drivers of this pathogenic macrophage phenotype. Our findings define a distinct NFKBIZ⁺ macrophage population that mechanistically links hypoxia, angiogenesis, and immune evasion to PD-1 blockade resistance. This work provides new insights into the cellular and molecular basis of immunotherapy failure in HCC and highlights potential targets for overcoming treatment resistance.

The COVID-19 pandemic has highlighted the urgent need for accurate, rapid, and cost-effective diagnostic methods to identify and track the disease. Traditional diagnostic methods, such as PCR and serological assays, have limitations in terms of sensitivity, specificity, and timeliness. To investigate the potential of using protein–peptide hybrid microarray (PPHM) technology to track the dynamic changes of antibodies in the serum of COVID-19 patients and evaluate the prognosis of patients over time. A discovery cohort of 20 patients with COVID-19 was assembled, and PPHM technology was used to track the dynamic changes of antibodies in the serum of these patients. The results were analyzed to classify the patients into different disease severity groups, and to predict the disease progression and prognosis of the patients. PPHM technology was found to be highly effective in detecting the dynamic changes of antibodies in the serum of COVID-19 patients. Four polypeptide antibodies were found to be particularly useful for reflecting the actual status of the patient’s recovery process and for accurately predicting the disease progression and prognosis of the patients. The findings of this study emphasize the multi-dimensional space of peptides to analyze the high-volume signals in the serum samples of COVID-19 patients and monitor the prognosis of patients over time. PPHM technology has the potential to be a powerful tool for tracking the dynamic changes of antibodies in the serum of COVID-19 patients and for improving the diagnosis and prognosis of the disease.