There are no effective therapies for patients with Coronavirus disease-2019 (COVID-19). Forty-one patients with confirmed COVID-19 were enrolled in the study and divided into two groups: artemisinin-piperaquine (AP) group (n=23) and control group (n=18). The primary outcome was the time taken to reach undetectable levels of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and the percentage of participants with undetectable SARS-CoV-2 on day 7, 10, 14, and 28. The computed tomography (CT) imaging changes within ten days, the corrected QT interval changes, adverse events, and abnormal laboratory parameters were the secondary outcomes. The mean time to reach undetectable viral RNA (mean± standard deviation) was 10.6±1.1 days (95% confidence interval [CI]: 8.4-12.8) for AP group and 19.3±2.1 days (95% CI: 15.1-23.5) for the control group. The percentage of patients with undetectable viral RNA on day 7, 10, 14, 21, and 28 were 26.1%, 43.5%, 78.3%, 100%, and 100%, respectively, in the AP group and 5.6%, 16.7%, 44.4%, 55.6% and 72.2%, respectively, in the control group. The CT imaging within ten days post-treatment showed no significant differences between the two groups (p>0.05). Both groups had mild adverse events. In patients with mild to moderate COVID-19, the time to reach undetectable SARS-CoV-2 was significantly shorter in the AP group than that in the control group. However, physicians should consider the QT interval changes before using AP.

The WHO recommends Artemisinin-based combination therapy (ACTs) as the first-line treatment for malaria. This meta-analysis aims to analyze the effects of artemisinin and its derivatives as well as non-artemisinin drugs on the gametophytes in the host during the treatment of falciparum malaria. Fourteen studies were included in this analysis, and the artemisinin combination drugs involved were: artemether-lumefantrine (AL), artemisinin (AST), artemether-benflumetol (AB), dihydroartemisinin-piperaquine + trimethoprim + primaquine (CV8), amodiaquine + sulfadoxine-pyrimethamine (ASP), pyronaridine-phosphate + dihydroartemisinin (PP-DHA), dihydroartemisinin (DHA), and mefloquine + artesunate (MA), with 1702 patients. The control intervention measures involved the following: sulfadoxine-pyrimethamine (SP), mefloquine (MQ), atovaquone-proguanil (AT-PG), chloroquine + sulfadoxine-pyrimethamine (C-SP), quinine (Q), pyronaridine-phosphate (PP), pyronaridine (PN), and mefloquine + primaquine (MP), with 833 patients. The effect of ACTs was more obvious (OR = 0.37, 95%CI: 0.22–0.62, p < 0.05). In the control group of second malaria attacks, the difference between the two groups was not statistically significant (RD = 1.16, 95%CI: 0.81–1.66, p < 0.05); there was no significant difference in treatment failure during follow-up (RD = -0.01, 95%CI: 0.04–0.03, p < 0.05). There were also very few serious adverse events in both groups. ACTs showed good therapeutic effects in preventing gametocythemia but did not control the recrudescence rate and overall cure, which indicated the effectiveness of the combination of antimalarial drugs. Further research is required to explore which compatibility method is most conducive to the development of clinical malaria control.

Background: Cerebral malaria (CM), a fatal neurological complication of Plasmodium falciparum infection, is partially driven by neuronal injury. Emerging evidence highlights exosomes as vital mediators of mast cell–neuron interactions in neurological disease progression. While mast cells and their exosomes were previously shown to exacerbate experimental cerebral malaria (ECM) severity, the specific role of mast cell-derived exosomes in CM-associated neuronal injury remains unclear. Methods: Exosomes were isolated from resting and lipopolysaccharide (LPS)-activated P815 mast cells (denoted as RE and AE, respectively) and characterized. These exosomes were administered to ECM mice and Plasmodium berghei ANKA (PbA)-infected red blood cell (iRBC)-stimulated neuronal HT-22 cells to investigate their functional impact and mechanisms. Results: Both RE and AE exhibited spherical morphology (20–100 nm diameter) and expressed exosomal markers (CD9, CD63, and CD81). Compared to infected controls, RE and AE treatments significantly reduced survival time, increased ECM incidence, and exacerbated brain pathology, blood–brain barrier disruption, neuronal injury, and apoptosis. Furthermore, RE and AE administration elevated messenger RNA (mRNA) levels of pro-inflammatory cytokines (interleukin [IL]-6, tumor necrosis factor alpha [TNF-α], and IL-1β) and increased numbers of neurons expressing endoplasmic reticulum (ER) stress markers (GRP78, CHOP, p-IRE1, XBP-1). Notably, AE treatment induced higher morbidity/mortality rates, more severe neuronal injury, and greater ER stress marker expression than RE. In vitro, RE-treated iRBC-stimulated neuronal HT-22 cells showed higher GRP78, CHOP, and XBP-1 mRNA levels than AE-treated cells. MicroRNA (miRNA) sequencing revealed three downregulated miRNAs (miR-330-3p, miR-185-5p, and miR-379-5p) and six upregulated miRNAs (miR-155-5p, miR-423-3p, miR-187-3p, miR-29c-3p, miR-188-5p, miR-192-5p) in AE versus RE, all previously implicated in targeting GRP78, CHOP, or XBP-1. Conclusions: Mast cell-derived exosomes, particularly those from activated cells (AE), exacerbated ECM neuronal injury through partial activation of ER stress pathways. Graphical

Objective Cerebral tuberculoma and brain metastasis are often indistinguishable on MRI, leading to misdiagnosis. This study develops a T1WI-enhanced MRI radiomics-based nomogram to accurately differentiate them. Methods A total of 482 patients (290 males, 192 females; mean age 56.08 ± 12.96 years) including 254 with cerebral tuberculoma and 228 with brain metastasis were enrolled from two centers. Radiomic features were extracted, standardized, and reduced via significance testing, Pearson correlation, and LASSO regression. A radiomic model was built, then integrated with clinical predictors into a nomogram. Performance was assessed across training, internal validation, and external validation cohorts using ROC curves, calibration, and decision curve analysis (DCA). Results A total of 20 radiomic features were selected for model development. The radiomic model demonstrated areas under the curve (AUC) of 0.907, 0.891and 0.886 in training, internal validation, and independent external validation cohorts, respectively, significantly outperforming models based solely on clinical factors, which achieved AUCs of 0.781, 0.712, and 0.828 ( p < 0.05). The nomogram, which integrated the radiomic scores, age, ring enhancement, meningeal thickening, and carcinoembryonic antigen (CEA) levels, exhibited superior performance with AUCs of 0.951, 0.937, and 0.940 across the three cohorts. DCA demonstrated that the nomogram provided greater clinical net benefits across a range of threshold probabilities, and calibration curves indicated strong consistency between predicted probabilities and actual outcomes. Conclusion A nomogram combining clinical factors and T1WI-enhanced MRI radiomics accurately differentiates cerebral tuberculoma from brain metastasis, offering robust decision support for individualized diagnosis and treatment.