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Oncolytic Virus (OVs) is an emerging approach to tumour immunity that allows the use of natural or genetically modified viruses to specifically infect and lyse tumour cells without damaging normal cells. Oncolytic herpes simplex virus (oHSV) is one of the more widely researched and applied OVs in the field of oncology, which can directly kill tumour cells to promote anti-tumour immune responses. oHSV is one of the few viruses with good antiviral drugs, so oHSV is also more clinically safe. In recent years, in addition to monotherapy of oHSV in tumours, more and more studies have been devoted to exploring the anti-tumour effects of oHSV in combination with other therapeutic approaches. In this article we describe the progress of oHSV combination therapy against tumours in the nervous system, digestive system, reproductive system and other systems.

Treatments of glioblastoma (GBM) have not been very effective, largely due to the inefficiency of drugs in penetrating the blood brain barrier (BBB). In this study, we investigated the potential of exosome‐coated doxorubicin (DOX)‐loaded nanoparticles (ENPDOX) in BBB penetration, inducing immunogenic cell death (ICD) and promoting survival of GBM‐bearing mice. DOX‐loaded nanoparticles (NPDOX) were coated with exosomes prepared from mouse brain endothelial bEnd.3 cells. ENPDOX cellular uptake was examined. Penetration of ENPDOX through the BBB was tested in an in vitro transwell system and a GBM mouse model. The effects of ENPDOX in inducing apoptosis and ICD were assessed. Finally, the efficacy of ENPDOX in the treatment of GBM‐bearing mice was assessed. ENPDOX was taken up by bEnd.3 cells and could penetrate the BBB both in vitro and in vivo. In vitro, ENDDOX induced apoptosis and ICD of glioma GL261 cells. Systemic administration of ENPDOX resulted in maturation of dendritic cells, activation of cytotoxic cells, altered production of cytokines, suppressed proliferation and increased apoptosis of GBM cells in vivo and prolonged survival of GBM‐bearing mice. Our findings indicate that ENPDOX may be a potent therapeutic strategy for GBM which warrants further investigation in clinical application.

Background: Central nervous system (CNS) infections pose a fatal risk to patients. However, the limited sample volumes of cerebrospinal fluid (CSF) and low detection efficiency seriously hinder the accurate detection of pathogens using conventional methods.Methods: We evaluated the performance of metagenomics next-generation sequencing (mNGS) in diagnosing CNS infections. CSF samples from 390 patients clinically diagnosed with CNS infections were used for the mNGS of cell-free DNA (cfDNA) (n =394) and whole-cell DNA (wcDNA) (n =150).Results: The sensitivity of mNGS using cfDNA was 60.2% (237/394, 95% confidence interval [CI] 55.1%–65.0%), higher than that of mNGS using wcDNA (32.0%, 95% [CI] 24.8%–40.2%, 48/150) and conventional methods (20.9%, 95% [CI] 16.2%–26.5%, 54/258) (P < 0.01, respectively). The accuracy of mNGS using cfDNA in positive samples was 82.6%. Most of viral (72.6%) and mycobacterial (68.8%) pathogens were only detected by the mNGS of cfDNA. Meningitis and encephalitis with Streptococcus pneumoniae infection might be more likely to result in critically ill diseases, while Human alphaherpesvirus 3 was prone to cause non-critically ill diseases.Conclusions: This is the first report on evaluating and emphasizing the importance of mNGS using CSF cfDNA in diagnosing CNS infections, and its extensive application in diagnosing CNS infections could be expected, especially for viral and mycobacterial CNS infections.

Background Leptomeningeal metastases (LM) were rare in gastric cancer (GC), and GC patients with LM (GCLM) generally suffer from poor prognosis. Nevertheless, the clinical utility of cerebrospinal fluid (CSF) circulating tumor DNA (ctDNA) was underinvestigated in GCLM. Methods We retrospectively studied 15 GCLM patients, and all patients had paired primary tumor tissue samples and post-LM CSF samples while 5 patients also had post-LM plasma samples. All samples were analyzed using next-generation sequencing (NGS), and the molecular and clinical features were correlated with clinical outcomes. Results CSF had higher mutation allele frequency ( P  = 0.015), more somatic mutations ( P  = 0.032), and more copy-number variations ( P  < 0.001) than tumor or plasma samples. Multiple genetic alterations and aberrant signal pathways were enriched in post-LM CSF, including CCNE1 amplification and cell cycle-related genes, and CCNE1 amplification was significantly associated with patients’ overall survival ( P  = 0.0062). More potential LM progression-related markers were detected in CSF samples than in tumor samples, including PREX2 mutation ( P  = 0.014), IGF1R mutation ( P  = 0.034), AR mutation ( P  = 0.038), SMARCB1 deletion ( P  < 0.001), SMAD4 deletion ( P  = 0.0034), and TGF-beta pathway aberration ( P  = 0.0038). Additionally, improvement in intracranial pressure ( P  < 0.001), improvement in CSF cytology ( P  = 0.0038), and relatively low levels of CSF ctDNA ( P  = 0.0098) were significantly associated with better PFS. Lastly, we reported a GCLM case whose CSF ctDNA dynamic changes were well correlated with his clinical assessment. Conclusions CSF ctDNA could more sensitively detect molecular markers and metastasis-related mechanisms than tumor tissues in GCLM patients, and our study sheds light on utilizing CSF ctDNA in prognostic estimation and clinical assessment in GCLM.

Autoimmune encephalitis (AE) is a severe neuroinflammatory disease with a substantial risk of progression to critical illness requiring intensive care. Early identification of patients at high risk of severe disease is essential but remains challenging because of heterogeneous presentations and the lack of objective, readily available prognostic tools. Lactate dehydrogenase (LDH), a ubiquitous enzyme associated with cellular injury and immune activation, has been linked to disease severity in systemic autoimmune disorders; however, its prognostic value in AE remains unexplored. This study aimed to develop a clinical prediction model for severe AE and to evaluate serum LDH as a core biomarker for prognosis and differential diagnosis. In this multicenter retrospective study, 299 adult patients with AE were analyzed. Severe AE was defined by intensive care unit admission or the presence of major disability (modified Rankin Scale ≥ 3). Independent predictors were identified using multivariable logistic regression and incorporated into a nomogram. The model underwent both internal and external validation. Serum LDH was additionally evaluated as a standalone biomarker by comparison with viral encephalitis (VE) controls (n = 243) and across AE antibody subtypes. Elevated serum LDH, impaired consciousness at admission, and prodromal infection were identified as independent predictors of severe AE. The resulting nomogram demonstrated excellent discriminatory performance (area under the curve [AUC] 0.947 in the training cohort, 0.882 in the validation cohort) and good calibration. Serum LDH remained a robust predictor in the multivariable model. As a standalone predictor, LDH achieved an AUC of 0.887 for severe AE; an optimal cutoff value of 215 U/L yielded a sensitivity of 83.3% and a specificity of 84.1%. Notably, LDH levels were significantly higher in AE than in VE. Furthermore, elevated LDH demonstrated a significant positive correlation with the risk of severe disease across key AE subtypes, including anti-N-methyl-D-aspartate receptor, seronegative, anti-LGI1, anti-GAD65, and anti-GFAP encephalitis. This study presents a validated and readily applicable nomogram for early risk stratification in AE. Serum LDH emerges as a robust, accessible biomarker that supports both prognostic assessment and differential diagnosis, providing a simple objective threshold (215 U/L) to inform timely clinical decision-making.

Background Neurobrucellosis (NB) presents a challenge for rapid and specific diagnosis. Next-generation sequencing (NGS) of cerebrospinal fluid (CSF) has showed power in detection of causative pathogens, even some infrequent and unexpected pathogens. In this study, we presented 8 cases of NB diagnosed by the NGS of CSF. Methods Between August 1, 2018 and September 30, 2020, NGS was used to detect causative pathogens in clinically suspected central nervous system (CNS) infections. Data on demographics, clinical features, and laboratory tests, imaging results and NGS results were collected and reviewed. Results Among the presented 8 patients, Brucella was rapidly detected using NGS of CSF within 1–4 days, despite those eight patients had variable medical history, disease course, clinical manifestations, laboratory tests and imaging findings. NGS showed the sequence reads corresponded to Brucella species were 8 to 448, with genomic coverage of 0.02 to 0.87%. The relative abundance was 0.13% to 82.40% and sequencing depth was 1.06 to 1.24. Consequently, patients were administered with 3 to 6 months of doxycycline, ceftriaxone and rifampicin, double or triple combination, supplemented with symptomatic therapy and were fully recovered except for case 1. Conclusion NGS of CSF provides a powerful tool in detection of Brucella in a prompt and specific manner, and can be considered for first-line diagnostic use in practice.

Varicella-zoster virus (VZV) involvement of the central nervous system (CNS) can cause severe complications; however, the underlying pathogenic mechanisms remain incompletely understood. This study describes the clinical characteristics of VZV CNS infection and explores the molecular mechanisms involved through cerebrospinal fluid (CSF) proteomic analysis. This study included 69 patients diagnosed with VZV CNS infection at our center. Their clinical symptoms, laboratory tests, and neuroimaging results were analyzed. CSF samples from nine patients with VZV CNS infection (VZV group) and 10 controls without CNS infection (Ctrl group) were subjected to proteomic analysis. The most common clinical manifestations were headache (79.7%), fever (56.5%), and motor/sensory disturbances (30.4%). Neuroimaging revealed abnormal brain parenchyma in 18.8% of the cases. CSF from most patients showed elevated white blood cell counts (0-1400 × 10 /L) and protein levels (0.11-7.61 g/L), and elevated cerebrospinal fluid pressure (60-330 mmH O). Proteomic analysis indicated the number and abundance of CSF proteins to be markedly higher in the VZV group than in the Ctrl group. Up-regulated proteins in the VZV group were primarily associated with type I interferon signaling, pyroptosis, and increased blood-brain barrier permeability. Gene Ontology enrichment analysis indicated that upregulated proteins were predominantly associated with innate antiviral immunity. Wikipathways were enriched for lymphocyte activation and inflammatory signaling pathways. This study integrates clinical and proteomic analyses to reveal the clinical and molecular features of VZV CNS infection. Synergistic over-activation of the type I interferon response, inflammatory signaling, and lymphocyte activation drives a robust neuroinflammatory reaction, which may underlie blood-brain barrier disruption and neurological deficits. Furthermore, over-activation of the complement system in severe encephalitis provides new insights for understanding disease severity and potential therapeutic targets. These findings underscore the potential of this approach for developing diagnostic markers and targeted therapeutic strategies.

The impact of climate change on surface runoff and soil moisture in the source region of the Yellow River is analyzed, which will provide a scientific basis for the rational use and protection of water resources in the source area. In this paper, the SWAT hydrological model was coupled with the Coupled Model Intercomparison Project (CMIP) to predict future changes in surface runoff and soil moisture in the source region of the Yellow River. The prediction of surface runoff and soil moisture in the Yellow River Basin was analyzed by a linear regression model. The SWAT model rate had a calibration period R2 of 0.876 and a validation period R2 of 0.972. The trend of surface runoff and annual mean temperature in the source region of the Yellow River from 2011 to 2022 showed an overall increasing trend, and soil moisture showed a general decreasing trend. 2011–2022 trends between surface runoff and annual mean temperature in the source region of the Yellow River showed a highly significant difference, indicating that surface runoff flow was significantly influenced by temperature. The difference between the trends in soil moisture and the annual mean temperature was highly significant. The surface runoff fluctuated greatly in different years, and the surface runoff changed greatly in different scenarios of CMIP5 (RCP2.6, RCP4.5, and RCP8.5). For all three climate change scenarios, the surface runoff displayed a downward trend. The surface runoff showed a similar uneven distribution for all scenarios on a yearly cycle. Under the three climate scenarios, the runoff was highest between May and August, with a slowly increasing trend from January to April and a slightly decreasing trend from September to December. The interannual and interannual distribution of soil water was basically consistent with the distribution of surface runoff, and there was an overall trend in the length of all soil water reduction scenarios. Surface runoff and soil moisture are and will be greatly affected by climate change (mainly temperature and precipitation). Under the three climate scenarios, the precipitation increases to some extent, but the surface runoff and soil moisture will both decrease, which may be attributed to the greater evaporation than the precipitation.

Wetlands play an important role in water storage and water conservation, but with global climate change, the degradation of wetland ecosystems is accelerating. In this study, we conducted research on the current situation and future prediction of water quality in typical wetlands in the source region of the Yangtze River to provide a scientific basis for the protection and restoration of wetlands in the source region of the Yangtze River. The Bayesian water quality assessment method and Yao Zhiqi evaluation method were used to evaluate the water quality of typical wetlands in the source region of the Yangtze River from 2016 to 2021 and based on the climate change scenarios of three RCPs (Representative Concentration Pathways) under the CMIP5 (Coupled Model Intercomparison Project Phase 5) global climate model and SWAT (soil and water assessment tool) hydrological model, the wetland water quality in the source region of the Yangtze River from 2022 to 2100 was predicted. The results show that the inter-annual changes in CODMn, NH3-N, and TN in a typical wetland show a downward trend, while the temperature and DO concentration show an upward trend from 2016–2021. The changes in CODMn, temperature, and conductivity within the year are abundant season > flat season > dry season; and DO, NH3-A, TN, and TP concentrations within the year are opposite. The water quality of typical wetlands in the source region of the Yangtze River has reached Class II and above. From 2022 to 2100, under climate change in the future, TN, TP, CODMn, NH3-N, and temperature in the wetland water in the source region of the Yangtze River will continue to rise, and the concentration of DO will continue to decline. Therefore, the pressure on water resources in the source region of the Yangtze River is further aggravated, so it is urgent to strengthen water resources protection.

With the disturbance of human factors, the groundwater resources in the source region of the Yellow River have gradually depleted and the water quality has become worse, which has seriously affected the development of high-altitude areas. The groundwater quality of the source region of the Yellow River from 2016 to 2020 was evaluated using single-component and comprehensive evaluation methods, following by a prediction of the groundwater quality from 2021 to 2100 based on the RCPS (RCP 2.6, RCP 4.5, and RCP 8.5) scenarios coupled with the SWAT hydrological model under the CMIP5 global climate model. The results indicated that the groundwater temperature had an increasing trend, pH showed an obvious decreasing trend, and total hardness (Th), sulfate, and ammonia nitrogen (NH4+-N) contents exhibited no obvious increasing or decreasing trend in the source region of the Yellow River during 2016–2020. The increase rate of total nitrogen (TN) and total phosphorus (TP) in the future climate scenario followed the order of RCP 8.5 > RCP 4.5 > RCP 2.6, and the groundwater contents of TN and TP in the source region of the Yellow River gradually increased. This result is of great significance, as it can help clarify the current situation of groundwater in high-altitude and cold regions, showing the influence of groundwater on global climate change. It provides a reference for the development and utilization planning of groundwater resources in the source region of the Yellow River in the future.