Early deficits in an in vitro striatal microcircuit model carrying the Parkinson's GBA-N370S mutation.

Understanding medium spiny neuron (MSN) physiology is essential to understand motor impairments in Parkinson's disease (PD) given the architecture of the basal ganglia. Here, we developed a custom three-chambered microfluidic platform and established a cortico-striato-nigral microcircuit partially recapitulating the striatal presynaptic landscape in vitro using induced pluripotent stem cell (iPSC)-derived neurons. We found that, cortical glutamatergic projections facilitated MSN synaptic activity, and dopaminergic transmission enhanced maturation of MSNs in vitro. Replacement of wild-type iPSC-derived dopamine neurons (iPSC-DaNs) in the striatal microcircuit with those carrying the PD-related GBA-N370S mutation led to a depolarisation of resting membrane potential and an increase in rheobase in iPSC-MSNs, as well as a reduction in both voltage-gated sodium and potassium currents. Such deficits were resolved in late microcircuit cultures, and could be reversed in younger cultures with antagonism of protein kinase A activity in iPSC-MSNs. Taken together, our results highlight the unique utility of modelling striatal neurons in a modular physiological circuit to reveal mechanistic insights into GBA1 mutations in PD.

Digital profiling of cancer transcriptomes from histology images with grouped vision attention.

Cancer is a heterogeneous disease that demands precise molecular profiling for better understanding and management. Recently, deep learning has demonstrated potentials for cost-efficient prediction of molecular alterations from histology images. While transformer-based deep learning architectures have enabled significant progress in non-medical domains, their application to histology images remains limited due to small dataset sizes coupled with the explosion of trainable parameters. Here, we develop SEQUOIA, a transformer model to predict cancer transcriptomes from whole-slide histology images. To enable the full potential of transformers, we first pre-train the model using data from 1,802 normal tissues. Then, we fine-tune and evaluate the model in 4,331 tumor samples across nine cancer types. The prediction performance is assessed at individual gene levels and pathway levels through Pearson correlation analysis and root mean square error. The generalization capacity is validated across two independent cohorts comprising 1,305 tumors. In predicting the expression levels of 25,749 genes, the highest performance is observed in cancers from breast, kidney and lung, where SEQUOIA accurately predicts the expression of 11,069, 10,086 and 8,759 genes, respectively. The accurately predicted genes are associated with the regulation of inflammatory response, cell cycles and metabolisms. While the model is trained at the tissue level, we showcase its potential in predicting spatial gene expression patterns using spatial transcriptomics datasets. Leveraging the prediction performance, we develop a digital gene expression signature that predicts the risk of recurrence in breast cancer. SEQUOIA deciphers clinically relevant gene expression patterns from histology images, opening avenues for improved cancer management and personalized therapies.

DLL3 expression and methylation are associated with lower-grade glioma immune microenvironment and prognosis.

Notch signalling pathway, particularly its ligand delta-ligand 3 (DLL3), is important in glioma, however, little is known about DLL3 regulation and prognostic effects. Immunohistochemistry on a cohort of 163 gliomas revealed DLL3 upregulation in IDH1 mutant gliomas, where it was associated with a favourable prognosis (HR[95% CI]: 0.28[0.09-0.87]; p = 0.021). We investigated the epigenetic regulation of DLL3, and identified individual CpG sites correlating with DLL3 mRNA expression, which were significant prognostic markers in LGG. In silico analysis revealed that infiltrating immune cells significantly correlated with DLL3 expression, methylation and somatic copy number alterations. The prognostic effects of DLL3 expression was significantly affected by infiltration of immune cells. RNA Sequencing of 83 LGGs and GO Term analysis of differentially expressed genes showed that low DLL3 expression was related to ciliogenesis, which was confirmed by TCGA LGG analysis. Thus, DLL3 may play an important role in the immune microenvironment and prognosis of LGGs.

PODNL1 Methylation Serves as a Prognostic Biomarker and Associates with Immune Cell Infiltration and Immune Checkpoint Blockade Response in Lower-Grade Glioma.

Lower-grade glioma (LGG) is a diffuse infiltrative tumor of the central nervous system, which lacks targeted therapy. We investigated the role of Podocan-like 1 (PODNL1) methylation in LGG clinical outcomes using the TCGA-LGG transcriptomics dataset. We identified four PODNL1 CpG sites, cg07425555, cg26969888, cg18547299, and cg24354933, which were associated with unfavorable overall survival (OS) and disease-free survival (DFS) in univariate and multivariate analysis after adjusting for age, gender, tumor-grade, and IDH1-mutation. In multivariate analysis, the OS and DFS hazard ratios ranged from 0.44 to 0.58 (p < 0.001) and 0.62 to 0.72 (p < 0.001), respectively, for the four PODNL1 CpGs. Enrichment analysis of differential gene and protein expression and analysis of 24 infiltrating immune cell types showed significantly increased infiltration in LGGs and its histological subtypes with low-methylation levels of the PODNL1 CpGs. High PODNL1 expression and low-methylation subgroups of the PODNL1 CpG sites were associated with significantly increased PD-L1, PD-1, and CTLA4 expressions. PODNL1 methylation may thus be a potential indicator of immune checkpoint blockade response, and serve as a biomarker for determining prognosis and immune subtypes in LGG.

TP53 Mutation Is a Prognostic Factor in Lower Grade Glioma and May Influence Chemotherapy Efficacy.

BACKGROUND: Identification of prognostic biomarkers in cancers is a crucial step to improve overall survival (OS). Although mutations in tumour protein 53 (TP53) is prevalent in astrocytoma, the prognostic effects of TP53 mutation are unclear. METHODS: In this retrospective study, we sequenced TP53 exons 1 to 10 in a cohort of 102 lower-grade glioma (LGG) subtypes and determined the prognostic effects of TP53 mutation in astrocytoma and oligodendroglioma. Publicly available datasets were analysed to confirm the findings. RESULTS: In astrocytoma, mutations in TP53 codon 273 were associated with a significantly increased OS compared to the TP53 wild-type (HR (95% CI): 0.169 (0.036-0.766), p = 0.021). Public datasets confirmed these findings. TP53 codon 273 mutant astrocytomas were significantly more chemosensitive than TP53 wild-type astrocytomas (HR (95% CI): 0.344 (0.13-0.88), p = 0.0148). Post-chemotherapy, a significant correlation between TP53 and YAP1 mRNA was found (p = 0.01). In O (6)-methylguanine methyltransferase (MGMT) unmethylated chemotherapy-treated astrocytoma, both TP53 codon 273 and YAP1 mRNA were significant prognostic markers. In oligodendroglioma, TP53 mutations were associated with significantly decreased OS. CONCLUSIONS: Based on these findings, we propose that certain TP53 mutant astrocytomas are chemosensitive through the involvement of YAP1, and we outline a potential mechanism. Thus, TP53 mutations may be key drivers of astrocytoma therapeutic efficacy and influence survival outcomes.

Liposomal drug delivery of Corchorus olitorius leaf extract containing phytol using design of experiment (DoE): In-vitro anticancer and in-vivo anti-inflammatory studies.

Phytol, a pharmacologically active compound present in Corchorus olitorius leaf exhibit a range of activity including anti-inflammatory, antioxidant, anticancer, hepatoprotective etc. However, phytol is poorly soluble and absorbed through the intestine wall, therefore the aim of this study is to develop liposomal drug delivery of Corchorus olitorius leaf extract with an average particle size below 150 nm and drug loading efficiency of ≥ 85 %. The impact of different process parameters and material attributes were studied on the average particle size and polydispersity of liposomal batches using design of experiment (DoE). Corchorus olitorius leaf extraction was performed using maceration method and characterised using GC-MS. Liposomal batches of Corchorus olitorius leaf extract were characterized using Malvern zetasizer, transmission electron microscopy (TEM) and UV spectroscopy. The in-vivo anti-inflammatory study of the liposomal preparation of phytol was evaluated using a rat model and in-vitro cancer cell line study was performed on AML and Leukamia cell lines. GC-MS study data showed that phytol is present in C. olitorius leaf extract. Process parameters and material attributes perspective processing temperature, buffer pH and drug: lipid ratio is found as major parameters affecting the average particle size and PDI value of liposomes. Liposomes were prepared in the range of 80-250 nm and optimized batches of liposomes showed drug entrapment efficiency of 60-88 %. In-vivo anti-inflammatory study showed significant activity for C. olitorius leaf extract against carrageenan induced paw edema, which is significantly increased while delivered through liposomes. In-vitro cancer cell line study data suggests that liposomal delivery of phytol was more active at lower concentration compared to pure phytol, for specific cell lines.

Anti-inflammatory Property of AMP-activated Protein Kinase.

BACKGROUND: One of the many debated topics in inflammation research is whether this scenario is really an accelerated form of human wound healing and immunityboosting or a push towards autoimmune diseases. The answer requires a better understanding of the normal inflammatory process, including the molecular pathology underlying the possible outcomes. Exciting recent investigations regarding severe human inflammatory disorders and autoimmune conditions have implicated molecular changes that are also linked to normal immunity, such as triggering factors, switching on and off, the influence of other diseases and faulty stem cell homeostasis, in disease progression and development. METHODS: We gathered around and collected recent online researches on immunity, inflammation, inflammatory disorders and AMPK. We basically searched PubMed, Scopus and Google Scholar to assemble the studies which were published since 2010. RESULTS: Our findings suggested that inflammation and related disorders are on the verge and interfere in the treatment of other diseases. AMPK serves as a key component that prevents various kinds of inflammatory signaling. In addition, our table and hypothetical figures may open a new door in inflammation research, which could be a greater therapeutic target for controlling diabetes, obesity, insulin resistance and preventing autoimmune diseases. CONCLUSION: The relationship between immunity and inflammation becomes easily apparent. Yet, the essence of inflammation turns out to be so startling that the theory may not be instantly established and many possible arguments are raised for its clearance. However, this study might be able to reveal some possible approaches where AMPK can reduce or prevent inflammatory disorders.

Preventive Role of Resveratrol Against Inflammatory Cytokines and Related Diseases.

BACKGROUND: Immunity is the ultimate barrier between foreign stimuli and a host cell. Unwanted immune responses can threaten the host cells and may eventually damage a vital organ. Overproduction of inflammatory cytokines may also lead to autoimmune diseases. Inflammatory cells and pro-inflammatory cytokines can eventually progress to renal, cardiac, brain, hepatic, pancreatic and ocular inflammation that can result in severe damage in the long run. Evidence also suggests that inflammation may lead to atherosclerosis, Alzheimer's, hypertension, stroke, cysts and cancers. METHODS: This study was designed to correlate the possible molecular mechanisms for inflammatory diseases and prevent biochemical changes owing to inflammatory cytokines by using Resveratrol. Therefore, we searched and accumulated very recent literature on inflammatory disorders and Resveratrol. We scoured PubMed, Scopus, Science Direct, PLoS One and Google Scholar to gather papers and related information. RESULTS: Reports show that inflammatory diseases are very complex, as multiple cascade systems are involved; therefore, they are quite difficult to cure. However, our literature search also correlates some possible molecular interactions by which inflammation can be prevented. We noticed that Resveratrol is a potent lead component and has multiple activities against harmful inflammatory cytokines and related microRNA. Our study also suggests that the anti-inflammatory properties of Resveratrol have been highly studied on animal models, cell lines and human subjects and proven to be very effective in reducing inflammatory cell production and pro-inflammatory cytokine accumulation. Our tables and figures also demonstrate recent findings and possible preventive activities to minimize inflammatory diseases. CONCLUSION: This study would outline the role of harmful inflammatory cytokines as well as how they accelerate pathophysiology and progress to an inflammatory disorder. Therefore, this study might show a potential therapeutic value of using Resveratrol by health professionals in preventing inflammatory disorders.