A comprehensive in silico scan of human respiratory viruses identified 3CLpro cleavage motifs within influenza NP and PA. Experimental validation confirmed that 3CLpro-mediated cleavage triggers rapid protein degradation and cytoplasmic mislocalization. Consequently, both ectopic 3CLpro expression and SARS-CoV-2 replication effectively inhibit replication across diverse influenza virus strains, revealing a broad-spectrum antiviral mechanism.

More than two-thirds of hospitalized COVID-19 survivors maintained stable cognition 2 years after Omicron infection, while one in five experienced reversible decline. Researchers report that only 10.8% developed irreversible cognitive decline, including 3.6% with progressive decline. Older age, reinfection, severe illness, hypertension, longer hospitalization, and white matter lesions increased the risk, while education and vaccination were protective. Findings highlight potential for cognitive recovery, supporting monitoring of patients at higher risk of progressive decline.

Inspired by the work of the RNA Therapeutics Institute at UMass Chan Medical School and the development of the COVID vaccine, UMass Chan scientistis Marcus Ruscetti, PhD, and Chaitanya Naimesh Parikh, PhD’26, have developed an immunotherapy using a cocktail of messenger RNAs (mRNA) that could potentially be transformative for pancreatic cancer treatment.

Scientific evidence alone does not automatically change human behavior. While the scientific community has reached broad consensus that infectious pathogens, such as viruses can spread through airborne transmission, one critical challenge remains: How can scientific evidence be transformed into public understanding and meaningful action for effective prevention and control of airborne diseases?

Published in Humanities and Social Sciences Communications, a Nature Portfolio journal, an international study led by researchers of Aerosol Science Research Center, National Sun Yat-sen University, Taiwan provides one of the first large-scale evidence-based evaluations of how different science communication formats influence scientific understanding and preventive health behaviors. Using the original educational resource "The Quest of the Virosols", developed by the Aerosol Science Research Center at National Sun Yat-sen University (NSYSU), the study compared plain text, explainer comics, and animation among 3,217 participants from Taiwan, Indonesia, Malaysia, and the Philippines, including healthcare professionals, educators, and university students.

The findings demonstrate that while all three communication formats improved scientific knowledge, animation was the most effective in promoting understanding, strengthening empathy and risk perception, and motivating preventive health behaviors. The study further shows that effective science communication extends beyond information delivery—it transforms scientific knowledge into understanding, understanding into empathy, and empathy into action.

Beyond COVID-19, these findings highlight science communication as an essential component of pandemic preparedness, public health communication, disease prevention, environmental health, sustainability, and evidence-informed policymaking. By fostering human capacities aligned with the Inner Development Goals (IDGs), effective science communication can also accelerate progress toward multiple United Nations Sustainable Development Goals (SDGs), strengthening more resilient, informed, and sustainable societies.

Science communication is not merely about transferring knowledge. It is about transforming knowledge into understanding, understanding into empathy, and empathy into action.

A simple ball-milling process dramatically enhanced the antiviral activity of manganese-based oxides, as reported by researchers from Science Tokyo. The team treated four manganese-containing materials with ball milling in ethanol, which altered their surface chemistry and greatly improved their ability to inactivate an enveloped virus similar to SARS-CoV-2. The findings reveal a promising strategy for designing low-cost, high-performance antiviral materials for coatings and other self-disinfecting surfaces.

Symptoms of coronavirus disease of 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), range from asymptomatic to life-threatening, affecting the respiratory system and many other organs, and involved in SARS-CoV-2 pathogenesis, particularly its viral entry, is the enzyme transmembrane protease serine 2 (TMPRSS2). In response, in this study, polymorphisms in the TMPRSS2 gene (rs2070788 and rs12329760) were examined for their association with COVID-19 susceptibility and severity in Jordanians. The study participants (n = 861) included 427 individuals who had never contracted COVID-19 (control group) and 434 who had experienced the disease (case group). The case group was subsequently divided into two subgroups: severe (n = 166) and non-severe (n = 268) COVID-19. The results show that rs2070788 is associated with disease susceptibility in all inheritance models (P < 0.05), as well as an association between rs12329760 and COVID-19 disease severity in both the dominant and over-dominant models (P < 0.05). Further, a higher body mass index (BMI) and older age were associated with disease severity (p < 0.05), though females were less likely to develop severe COVID-19 and to be hospitalized. In conclusion, polymorphisms in the TMPRSS2 gene may be considered a potential predictor of COVID-19 outcomes in the Jordanian population. The study findings could be used to manage similar viral infections in Jordan in the future.

Vaccines protect most people from serious illness, but the strength of that protection can vary considerably from one person to another. Some people produce a robust immune response, while others respond only weakly.

A new study led by Arizona State University helps us understand why. Before a vaccine ever enters your body, your immune system may already hold clues to how strongly it will respond.

In blood samples from more than 4,000 people, ASU researchers and their colleagues measured antibodies against 185 antigens—targets recognized by the immune system, including those from common viruses and bacteria as well as targets associated with autoimmune diseases. 

They then used artificial intelligence to analyze patterns in samples collected before and after COVID-19 vaccination, identifying antibody signatures that helped distinguish strong vaccine responders from weak ones.

The research opens a possible path toward more personalized vaccination strategies.