Characterization and verification of CAF-relevant prognostic gene signature to aid therapy in bladder cancer.

Cancer-associated fibroblasts (CAFs) are significantly involved in determining the patient's prognosis and response to bladder cancer (BLCA) therapy. CAFs can induce epithelial-mesenchymal transformation (EMT) as well as complex interaction with immune cells. Hence, it is imperative to identify potential markers for enhancing our understanding of CAFs in BLCA progression and immune regulation. A variety of algorithms and analyses were employed in the study, leading to the development of a novel prognostic feature for CAFs-Stromal-EMT (CSE)-prognostic feature. This feature was constructed based on the genes MFAP5, PCOLCE2, and JUN. Furthermore, we revealed that patients with higher CSE risk scores responded to immunotherapy better compared to those with lower. Finally, we verified two CSE-related genes using in vitro experiments. Our results suggested that the CSE-prognostic feature could predict the prognosis and evaluate the response of patients to immune and chemotherapies. This would aid clinicians in designing treatment strategies for patients with BLCA.

A data-driven epidemic model with human mobility and vaccination protection for COVID-19 prediction.

Epidemiological models allow for quantifying the dynamic characteristics of large-scale outbreaks. However, capturing detailed and accurate epidemiological information often requires consideration of multiple kinetic mechanisms and parameters. Due to the uncertainty of pandemic evolution, such as pathogen variation, host immune response and changes in mitigation strategies, the parameter evaluation and state prediction of complex epidemiological models are challenging. Here, we develop a data-driven epidemic model with a generalized SEIR mechanistic structure that includes new compartments, human mobility and vaccination protection. To address the issue of model complexity, we embed the epidemiological model dynamics into physics-informed neural networks (PINN), taking the observed series of time instances as direct input of the network to simultaneously infer unknown parameters and unobserved dynamics of the underlying model. Using actual data during the COVID-19 outbreak in Australia, Israel, and Switzerland, our model framework demonstrates satisfactory performance in multi-step ahead predictions compared to several benchmark models. Moreover, our model infers time-varying parameters such as transmission rates, hospitalization ratios, and effective reproduction numbers, as well as calculates the latent period and asymptomatic infection count, which are typically unreported in public data. Finally, we employ the proposed data-driven model to analyze the impact of different mitigation strategies on COVID-19.

Double metals sites synergistically enhanced photocatalytic N2 fixation performance over Bi24O31Br10@Bi/Ti3C2Tx Ohm junctions.

At present, it is a research hotspot to realize green synthetic ammonia by using solar energy. Exploring cheap and efficient co-catalysts for enhancing the performance of photocatalysts is a challenge in the field of energy conversion. In order to boost the charge separation/transfer of the photocatalyst and widen the visible light absorption, Bi24O31Br10@Bi/Ti3C2Tx with double Ohm junction is successfully fabricated by in situ growth of metal Bi and loading Ti3C2Tx MXene on the surface of Bi24O31Br10. The dual active sites of Bi and Ti3C2Tx MXene not only broaden the light adsorption of Bi24O31Br10 but also serve as excellent 'electronic receptor' for synergically enhancing the separation/transfer efficiency of photogenerated electrons/holes. Meanwhile, temperature programmed desorption (TPD) result revealed that MXene and Bi can promote N2 adsorption/activation and NH3 desorption over Bi24O31Br10@Bi/Ti3C2Tx. As a result, under mild conditions and without the presence of hole scavenger, the ammonia synthesis efficiency of Bi24O31Br10@Bi/Ti3C2Tx-20 % reached 53.86 µmol g-1cat for three hours which is 3.2 and 53.8 times of Bi24O31Br10 and Ti3C2Tx, respectively. This study offers a novel scheme for the construction of photocatalytic systems and demonstrates Ti3C2Tx MXene and metal Bi as a promising and cheap co-catalyst.

Novel CH25H+ and OASL+ microglia subclusters play distinct roles in cerebral ischemic stroke.

BACKGROUND: Microglial polarization is one of the most promising therapeutic targets for multiple central nervous system (CNS) disorders, including ischemic stroke. However, detailed transcriptional alteration of microglia following cerebral ischemic stroke remains largely unclear. METHODS: Focal cerebral ischemia was induced by transient middle cerebral artery occlusion (tMCAO) for 60 min in mice. Single-cell RNA sequencing (scRNA-seq) was performed using ischemic brain tissues from tMCAO and sham mice 3 days after surgery. Ch25h-/- mice were used to investigate the role of specific microglia subcluster on post-stroke infarct volume and neuroinflammation. RESULTS: We identified a relatively homeostatic subcluster with enhanced antigen processing and three "ischemic stroke associated microglia" (ISAM): MKI67+, CH25H+ and OASL+ subclusters. We found the MKI67+ subcluster undergo proliferation and differentiation into CH25H+ and OASL+ subclusters. CH25H+ microglia was a critical subcluster of ISAM that exhibited increased phagocytosis and neuroprotective property after stroke. Ch25h-/- mice developed significantly increased infarct volume following ischemic stroke compared to Ch25h+/-. Meanwhile, the OASL+ subcluster accumulated in the ischemic brain and was associated with the evolving of neuroinflammation after stroke, which was further aggravated in the aged mice brain. CONCLUSIONS: Our data reveal previously unrecognized roles of the newly defined CH25H+ and OASL+ microglia subclusters following ischemic stroke, with novel insights for precise microglia modulation towards stroke therapy.

Reactive-diffusion epidemic model on human mobility networks: Analysis and applications to COVID-19 in China.

The complex dynamics of human mobility, combined with sporadic cases of local outbreaks, make assessing the impact of large-scale social distancing on COVID-19 propagation in China a challenge. In this paper, with the travel big dataset supported by Baidu migration platform, we develop a reactive-diffusion epidemic model on human mobility networks to characterize the spatio-temporal propagation of COVID-19, and a novel time-dependent function is incorporated into the model to describe the effects of human intervention. By applying the system control theory, we discuss both constant and time-varying threshold behavior of proposed model. In the context of population mobility-mediated epidemics in China, we explore the transmission patterns of COVID-19 in city clusters. The results suggest that human intervention significantly inhibits the high correlation between population mobility and infection cases. Furthermore, by simulating different population flow scenarios, we reveal spatial diffusion phenomenon of cases from cities with high infection density to cities with low infection density. Finally, our model exhibits acceptable prediction performance using actual case data. The localized analytical results verify the ability of the PDE model to correctly describe the epidemic propagation and provide new insights for controlling the spread of COVID-19.

Neuronal Serpina3n is an endogenous protector against blood brain barrier damage following cerebral ischemic stroke.

Ischemic stroke results in blood-brain barrier (BBB) disruption, during which the reciprocal interaction between ischemic neurons and components of the BBB appears to play a critical role. However, the underlying mechanisms for BBB protection remain largely unknown. In this study, we found that Serpina3n, a serine protease inhibitor, was significantly upregulated in the ischemic brain, predominantly in ischemic neurons from 6 hours to 3 days after stroke. Using neuron-specific adeno-associated virus (AAV), intranasal delivery of recombinant protein, and immune-deficient Rag1-/- mice, we demonstrated that Serpina3n attenuated BBB disruption and immune cell infiltration following stroke by inhibiting the activity of granzyme B (GZMB) and neutrophil elastase (NE) secreted by T cells and neutrophils. Furthermore, we found that intranasal delivery of rSerpina3n significantly attenuated the neurologic deficits after stroke. In conclusion, Serpina3n is a novel ischemic neuron-derived proteinase inhibitor that counterbalances BBB disruption induced by peripheral T cell and neutrophil infiltration after ischemic stroke. These findings reveal a novel endogenous protective mechanism against BBB damage with Serpina3n being a potential therapeutic target in ischemic stroke.

Primary central nervous system T-cell lymphoma: An analysis from the surveillance, epidemiology, and end results program.

BACKGROUND: Primary central nervous system T-cell lymphoma (PCNSTCL) is a rare neoplasm with few data regarding its common features and survival characteristics. OBJECTIVE: To explore the Surveillance, Epidemiology, and End Results 18 (SEER 18) database to determine the epidemiology of PCNSTCL. METHODS: The SEER 18 registry database was queried to identify patients diagnosed with PCNSTCL from 1973 to 2014 and extract their information. Age-specific rates and Kaplan-Meier overall survival (OS) were calculated. A Cox proportional hazards model was applied to investigate relationships between various demographic/treatment variables and OS. RESULTS: The age-specific incidence rates were higher in the older population (≥60 years). Among 59 PCNSTCL cases from the SEER 18, the mean age at presentation was 55.8 years (SD, ±17.95), with a male predominance (1.36:1.00). The median follow-up was 8 months, and the median OS was 8 months (SE, ±4.162). The 1-, 3-, and 5-year OS was 46.3% [95% CI, 33.4%-59.2%], 32.8% [20.3%-45.3%], and 32.8% [20.3%-45.3%], respectively. Seventeen of the 59 patients survived at last follow-up. Patients < 60 years had a greater 3-year OS compared with patients ≥ 60 years (52.6% [33.6%-71.6%] vs 13.9% [1.4%-26.4%]. Multivariate analysis has demonstrated that only age at diagnosis (≥60/<60 years) exhibited a significant relationship with OS (HR, 3.495 [1.688-7.235];p = 0.001). Sex (female/male) was observed to have a doubted trend towards significance (HR, 0.487 [0.231-1.030]; p = 0.060). CONCLUSIONS: PCNSTCL is generally of poor prognosis but younger age at diagnosis (<60 years) predicts a better prognosis.