Since December 2019, COVID-19 has spread across the world almost through 2.5 years. As of 16 June 2022, the cumulative number of confirmed cases of COVID-19 worldwide has reached 542.62 million, and the death toll has risen to 6.33 million. With the increasing number of deaths, it is urgent to find effective treatment drugs. Remdesivir, an investigational broad-spectrum antiviral drug produced by Gilead has been shown to inhibit SARS-CoV-2, in vitro and in vivo. This review is aimed to analyze the feasibility of remdesivir in COVID-19 and put forward the shortcomings of present clinical studies. We systematically searched PubMed and Web of Science up until 24 May 2022, using several specific terms such as “remdesivir” or “GS-5734” and “COVID-19” or “SARS-CoV-2” and retrieved basic researches and clinical studies of remdesivir in COVID-19. In this review, we summarized and reviewed the mechanism of remdesivir in SARS-COV-2, clinical trials of using remdesivir in COVID-19, analyzed the efficacy and safety of remdesivir, and judged whether the drug was effective for the treatment of COVID-19. In different clinical trials, remdesivir showed a mixed result in the treatment of COVID-19. It seemed that remdesivir shortened the time to recovery and had an acceptable safety profile. However, more clinical trials are needed to test the efficacy and safety of remdesivir.

Purpose: This study aimed to identify the clinical outcomes, microbiological features and risk factors for difficult-to-treat resistance (DTR) Klebsiella pneumoniae (Kp) infection. Materials and Methods: A retrospective study was conducted at Peking University Third Hospital from January 2020 to March 2021. DTR was defined as resistance to ≥ 1 carbapenem, ≥ 1 extended-spectrum cephalosporin, and ≥ 1 fluoroquinolone. Hypervirulent Kp (HvKp) was defined as peg-344-, iroB-, iucA-, rmpA-, or rmpA2-positive. Clinical data were collected. Antimicrobial susceptibility testing and string tests were performed to determine resistance and hypermucoviscosity phenotype. Whole genome sequencing was performed to analyze the sequence type (ST), capsular serotypes, resistance and virulence genes. Risk factors for 30-day mortality were analyzed. Results: Fifty DTR-Kp (50.0%) strains were identified among 100 patients. Compared to non-DTR-Kp group, a significant number of patients with DTR-Kp infection experienced ICU admission (44.0% versus 10.0%, P< 0.001) and mechanical ventilation after Kp detection (26.0% versus 10.0%, P=0.037). Notably, the percentage of hvKp among the DTR-Kp isolates increased consistently over the 15 months evaluated. Most DTR-Kp strains belonged to ST11 (82.0%), followed by ST15 (12.0%), ST86 (2.0%), ST996 (2.0%), and ST3157 (2.0%). DTR-Kp isolates possessed various resistance genes, such as bla_KPC-2, bla_TEM-1D and fosA3 (90.0%, 80.0% and 72.0%, respectively). Importantly, the yersiniabactin genes were significantly clustered in DTR group (48/50, 96.0%). The 30-day mortality was significantly higher in patients with DTR-Kp infection than non-DTR-Kp group (38.0% versus 8.2%, P=0.001). DTR-Kp infection (odds ratio [OR] = 4.196) was an independent risk factor for the 30-day mortality of Kp-infected patients. Additionally, cerebrovascular disease (OR = 2.780) and Charlson comorbidity index (OR= 1.584) were independent risk factors for DTR-Kp infections. Conclusion: DTR-hvKp is rapidly emerging. The DTR-Kp strains harbored various resistance genes and high rates of yersiniabactin siderophore genes. DTR-Kp infection was an independent risk factor for mortality, suggesting that enhanced awareness essential.

N-lactoyl-phenylalanine (Lac-Phe), an exercise-induced metabolite that suppresses appetite, has quickly emerged as a key molecule in metabolic signaling networks. Lac-Phe, following its CNDP2-mediated synthesis, mediates key appetite- and weight-modulating effects of metformin, which acts primarily by mitochondrial inhibition in gut epithelial cells. Both Lac-Phe and related N-lactoyl-amino acids serve as potent biomarkers of mitochondrial dysfunction. Elevated levels of these metabolites are found in genetic mitochondrial diseases, offering potentially superior prognostic value compared to lactate in conditions alike. Despite uncertainties regarding its specific receptor(s) and signaling mechanisms, the expanding roles of Lac-Phe underscore its critical position at the intersection of exercise physiology, pharmacology, energy metabolism, and disease pathology, suggesting significant potential for future diagnostics and therapeutics in mitochondrial and metabolic disorders.

Recent studies showed ferritin increase and hemoglobin decrease to COVID‐19 severity and sepsis mortality. However, the potential relationship between iron metabolism disorders and susceptibility to pneumonia remains unclear. This study explores the association between iron metabolism disorder and susceptibility to bacterial pneumonia, viral pneumonia, and sepsis. GWAS data from the FinnGen and UK biobank is used for a two‐sample Mendelian randomization (MR) analysis, followed by MR meta‐analysis. Low serum iron levels were negatively associated with the risk of bacterial pneumonia (OR, 0.85; p = 0.04), influenza pneumonia (OR, 0.86; p = 0.03), and sepsis (OR, 0.81; p = 0.0004). Increased transferrin saturation and decreased total iron‐binding capacity were linked to higher risks of bacterial pneumonia and sepsis. Elevated liver iron content correlated positively with susceptibility to bacterial pneumonia (OR, 1.11; p = 0.007), influenza pneumonia (OR, 1.08; p = 0.03), and sepsis (OR, 1.13; p = 0.0007), but negatively with pneumococcal pneumonia (OR, 37.62; p = 0.0013). Neutrophils mediated the impact of serum iron and transferrin saturation on susceptibility to bacterial pneumonia and sepsis. This MR study confirms that disruptions in iron metabolism, including low serum iron levels and elevated liver iron content, increase susceptibility to bacterial and viral pneumonia as well as sepsis by affecting neutrophil function and cytokine levels. The findings emphasize the need for monitoring iron metabolism indicators in high‐risk populations and provide valuable insights for further mechanistic research and clinical intervention.

The spectre of ‘Disease X,’1 a pathogen currently unknown but with the potential to cause a serious international epidemic, has shifted from a hypothetical scenario to an acknowledged reality, urging a fundamental change in our approach to global health security and urban resilience.2 When outbreak data remain confined within discrete institutional silos, essential insights for tracking disease spread and optimising interventions are lost or delayed.3 In the USA, the absence of a national public health system and centralised leadership forced state, local, tribal and territorial health departments to operate in isolated silos, resulting in critical gaps in COVID-19 data tracking, ineffective guidance development and a torrent of falsehoods.4 While past decades have seen us react to specific named threats like SARS, MERS, Ebola, and most recently COVID-19, the core challenge lies in preparing for an undefined future, demanding not just reactive countermeasures but proactive, networked and deeply integrated systems.5 This requires moving beyond traditional, siloed approaches to embrace innovative strategies that acknowledge the hyperconnected and complex nature of our modern world.

Objective: To identify risk factors for progression to sepsis in patients with non-ventilator hospital-acquired pneumonia (NV-HAP) and to develop a practical nomogram for individualized risk assessment in this population. Methods: We retrospectively screened 408 hospitalized patients with hospital-acquired pneumonia at Peking University Third Hospital between January 2017 and December 2021. After excluding patients with an unclear diagnosis date or missing critical variables required for SOFA score calculation, 368 eligible patients with NV-HAP were included and randomly divided into a training cohort (n = 260) and an internal validation cohort (n = 108). An independent temporal validation cohort of 68 patients admitted between January 2022 and December 2022 at the same center was further used for temporal validation. Univariable and multivariable logistic regression analyses with backward stepwise selection were performed in the training cohort to identify predictors associated with progression to sepsis. A nomogram was then constructed based on the final model and evaluated by discrimination, calibration, and decision curve analysis. Results: A total of 368 patients were included in the model development dataset. The final multivariable model retained six predictors: male sex (OR = 2.393, 95% CI: 1.333–4.296), diabetes (OR = 2.205, 95% CI: 1.126–4.319), coagulation dysfunction (OR = 3.327, 95% CI: 1.726–6.413), PaO₂/FiO₂ (OR = 0.955 per 10-unit increase, 95% CI: 0.912–1.001), platelet count (OR = 0.900 per 10 × 10⁹/L increase, 95% CI: 0.853–0.949), and bilirubin (OR = 1.176 per 1 μmol/L increase, 95% CI: 1.100–1.258). The nomogram showed acceptable performance, with an apparent C-index of 0.809 and a bootstrap-corrected C-index of 0.792 in the training cohort. The C-index was 0.750 (95% CI: 0.658–0.841) in the internal validation cohort and 0.754 (95% CI: 0.639–0.870) in the temporal validation cohort. Calibration analysis showed acceptable agreement between predicted and observed probabilities, and decision curve analysis indicated a positive net clinical benefit across clinically relevant threshold probabilities. Conclusions: In patients with NV-HAP, male sex, diabetes, coagulation dysfunction, lower PaO₂/FiO₂, lower platelet count, and higher bilirubin were associated with progression to sepsis. The developed nomogram showed acceptable discrimination, calibration, and clinical utility, and may serve as a practical tool for early individualized risk stratification in patients with NV-HAP.