Pluripotent human embryonic stem cell derived neural lineages for in vitro modelling of enterovirus 71 infection and therapy

The incidence of neurological complications and fatalities associated with Hand, Foot & Mouth disease has increased over recent years, due to emergence of newly-evolved strains of Enterovirus 71 (EV71). In the search for new antiviral therapeutics against EV71, accurate and sensitive in vitro cellular models for preliminary studies of EV71 pathogenesis is an essential prerequisite, before progressing to expensive and time-consuming live animal studies and clinical trials. This study thus investigated whether neural lineages derived from pluripotent human embryonic stem cells (hESC) can fulfil this purpose. EV71 infection of hESC-derived neural stem cells (NSC) and mature neurons (MN) was carried out in vitro, in comparison with RD and SH-SY5Y cell lines. Results: Upon assessment of post-infection survivability and EV71 production by the various types, it was observed that NSC were significantly more susceptible to EV71 infection compared to MN, RD (rhabdomyosarcoma) and SHSY5Y cells, which was consistent with previous studies on mice. The SP81 peptide had significantly greater inhibitory effect on EV71 production by NSC and MN compared to the cancer-derived RD and SH-SY5Y cell lines. Hence, this study demonstrates that hESC-derived neural lineages can be utilized as in vitro models for studying EV71 pathogenesis and for screening of antiviral therapeutics

Enhanced volcanic activity and long-term warmth in the middle Eocene revealed by mercury and osmium isotopes from IODP Expedition 369 Site U1514

Rapid plate reorganization may have influenced global climate during the Eocene; however, its linkage remains poorly constrained, particularly during the middle Eocene. To elucidate this tectonic–climatic relationship, here, we conducted a comprehensive analysis based on high-resolution mercury (Hg) and osmium (Os) abundance and isotope data obtained from the complete Eocene sedimentary sequence of Site U1514, drilled in the Mentelle Basin off southwest Australia. The Hg signals in this sedimentary sequence, which are characterized by significantly high enrichment and insignificant mass-independent fractionation (Δ199Hg) signal, confirm that the middle Eocene (∼45–38 Ma) was a period of persistent, increased volcanism, accompanied by intense tectonic activity. In particular, a remarkable seafloor volcanic eruption persisted for approximately 1.5 million years (∼42.0–40.5 Ma), immediately preceding the Middle Eocene Climate Optimum (MECO). Contemporaneously, the trends toward a slightly more radiogenic seawater 187Os/188Os (Osi) composition denote the prevalence of intensified continental weathering under a warm, humid climate during the middle Eocene, a phenomenon particularly evident during the MECO. Importantly, the Hg and Os records from Site U1514 reveal the occurrence of a multi-million-year warming reversal amid the long-term Eocene cooling trend, which likely contributed to significant CO2 reduction during the late Eocene. These findings significantly enhance our understanding of Eocene climate dynamics, which are fundamentally linked to intensive tectonic-driven volcanic activity and associated continental chemical weathering

A Novel Respiratory Rate Estimation Algorithm from Photoplethysmogram Using Deep Learning Model

Respiratory rate (RR) is a critical vital sign that can provide valuable insights into various medical conditions, including pneumonia. Unfortunately, manual RR counting is often unreliable and discontinuous. Current RR estimation algorithms either lack the necessary accuracy or demand extensive window sizes. In response to these challenges, this study introduces a novel method for continuously estimating RR from photoplethysmogram (PPG) with a reduced window size and lower processing requirements. To evaluate and compare classical and deep learning algorithms, this study leverages the BIDMC and CapnoBase datasets, employing the Respiratory Rate Estimation (RRest) toolbox. The optimal classical techniques combination on the BIDMC datasets achieves a mean absolute error (MAE) of 1.9 breaths/min. Additionally, the developed neural network model utilises convolutional and long short-term memory layers to estimate RR effectively. The best-performing model, with a 50% train–test split and a window size of 7 s, achieves an MAE of 2 breaths/min. Furthermore, compared to other deep learning algorithms with window sizes of 16, 32, and 64 s, this study’s model demonstrates superior performance with a smaller window size. The study suggests that further research into more precise signal processing techniques may enhance RR estimation from PPG signals

Tuberculosis and associated factors among type 2 diabetic patients in Perak: a case control study

This is a case-control study conducted with diabetic patients in Kinta, Kampar and Larut-Matang-Selama districts of Perak, Malaysia. We intended to determine the factors contributing to the development of active tuberculosis among diabetes patients. Cases were culture-proven and registered in the Malaysian National Tuberculosis Surveillance Registry (MyTB) from 2012 to 2018. Controls were diabetes patients identified from the National Diabetes Registry and were matched with cases based on the clinic in which they were registered at a ratio of 1:1. 119 cases and 119 controls were included in this study. Multivariate analysis was used to identify clinical factors associated with tuberculosis. Patient had increased odds of having tuberculosis if they had higher glycaemic (HbA1c) levels (OR=1.41, 95% CI 0.22-0.96, p<0.001) or nephropathy (OR=8.91, 95% CI 2.31-34.05, p<0.001). The odds ratio was lower if they have diabetes for at or more than 5 years (OR=0.46, 95% CI 0.22-0.96, p=0.04) and older (OR=0.96, CI 0.92-0.99, p=0.02). In conclusion, this study suggests that routine screening for tuberculosis in patients with diabetes should consider the diabetic duration, glycemic control, presence of nephropathy, and age of the patient

A novel and anti-agglomerating Ni@yolk–ZrO₂ structure with sub-10 nm Ni core for high performance steam reforming of methane

Steam reforming of methane is a versatile technology for hydrogen production in oil refinery and fuel cell applications. Using natural gas is a promising method to produce rich-hydrogen gas. Ni@yolk–ZrO₂ catalyst is used to study steam reforming of methane under various GHSVs, steam-to-carbon (S/C) ratio, and its recyclability. The catalyst was characterized using a combination of XRD, TEM, AAS, TPR, TPH, TGA, BET, XPS, and Raman techniques. The catalyst is evaluated on time stream and identify its anti-agglomeration property and coking mechanism. From the characterization of TEM and XPS establish the information of Ni particles mobility in the catalyst, which active metal particle size was controlled under the yolk–shell structure framework. Furthermore, the results from TGA, TPH, and Raman analysis of the used Ni@yolk–ZrO₂ catalyst showed the characteristic of inhibiting formation of highly ordered carbon structure

A Decade of Progress in Deep Brain Stimulation of the Subcallosal Cingulate for the Treatment of Depression

Major depression contributes significantly to the global disability burden. Since the first clinical study of deep brain stimulation (DBS), over 406 patients with depression have now undergone this neuromodulation therapy, and 30 animal studies have investigated the efficacy of subgenual cingulate DBS for depression. In this review, we aim to provide a comprehensive overview of the progress of DBS of the subcallosal cingulate in humans and the medial prefrontal cortex, its rodent homolog. For preclinical animal studies, we discuss the various antidepressant-like behaviors induced by medial prefrontal cortex DBS and examine the possible mechanisms including neuroplasticity-dependent/independent cellular and molecular changes. Interestingly, the response rate of subcallosal cingulate Deep brain stimulation marks a milestone in the treatment of depression. DBS among patients with treatment-resistant depression was estimated to be approximately 54% across clinical studies. Although some studies showed its stimulation efficacy was limited, it still holds great promise as a therapy for patients with treatment-resistant depression. Overall, further research is still needed, including more credible clinical research, preclinical mechanistic studies, precise selection of patients, and customized electrical stimulation paradigms

Neural Differentiation of Human Pluripotent Stem Cells for Nontherapeutic Applications: Toxicology, Pharmacology, and In Vitro Disease Modeling

Human pluripotent stem cells (hPSCs) derived from either blastocyst stage embryos (hESCs) or reprogrammed somatic cells (iPSCs) can provide an abundant source of human neuronal lineages that were previously sourced from human cadavers, abortuses, and discarded surgical waste. In addition to the well-known potential therapeutic application of these cells in regenerative medicine, these are also various promising nontherapeutic applications in toxicological and pharmacological screening of neuroactive compounds, as well as for in vitro modeling of neurodegenerative and neurodevelopmental disorders. Compared to alternative research models based on laboratory animals and immortalized cancer-derived human neural cell lines, neuronal cells differentiated from hPSCs possess the advantages of species specificity together with genetic and physiological normality, which could more closely recapitulate in vivo conditions within the human central nervous system. This review critically examines the various potential nontherapeutic applications of hPSC-derived neuronal lineages and gives a brief overview of differentiation protocols utilized to generate these cells from hESCs and iPSCs

Godtfredsen syndrome – recurrent clival chondrosarcoma with 6years follow up: a case report and literature review

Background: We report a rare case of Godtfredsen syndrome caused by clival chondrosarcoma and perform a review of literatures. This article also explains the clinico-anatomical correlation of this rare neurological syndrome. Case presentation: A 22-year-old gentleman presented with binocular diplopia. Clinical examination revealed an isolated right abducent nerve and right hypoglossal nerve palsy, with other cranial nerves intact. Neuroimaging revealed a right clival mass. Supraorbital craniotomy and tumour debulking were done in the same year. Histopathological examination showed low-grade chondrosarcoma. After 5-years of default, he came back with the tumour enlarged. He underwent a right orbitozygomatic craniotomy and tumour excision with 33 cycles of radiotherapy. Despite two surgeries and radiotherapy, the abducent nerve and hypoglossal nerve did not improve throughout 6 years of follow-up. Cranial nerve VI palsy is not always a false localizing sign, in Godtfredsen syndrome it serves as a localizing sign. Conclusion: To the best of our knowledge, this is the frst case report of Godtfredsen Syndrome secondary to clival chondrosarcoma. Cranial nerve VI and XII palsy with no involvement of other cranial nerves, most likely the pathology is located at the clivu

A Universal Approach to the Synthesis of Noble Metal Nanodendrites and Their Catalytic Properties

A universal approach is presented for high-yield synthesis of Au, Pt, and Pd nanoflowers using the surfactant sodium N-(4-n-dodecyloxybenzoyl)-L-isoleucinate (SDBIL). The pH-dependent self-assembly using SDBIL is critical for nanoflower growth. The Pt and Pd nanoflowers show superior catalytic activity for Suzuki–Miyaura and Heck coupling reactions over spherical counterparts

Additive and multiplicative hazards modeling for recurrent event data analysis

<p>Abstract</p> <p>Background</p> <p>Sequentially ordered multivariate failure time or recurrent event duration data are commonly observed in biomedical longitudinal studies. In general, standard hazard regression methods cannot be applied because of correlation between recurrent failure times within a subject and induced dependent censoring. Multiplicative and additive hazards models provide the two principal frameworks for studying the association between risk factors and recurrent event durations for the analysis of multivariate failure time data.</p> <p>Methods</p> <p>Using emergency department visits data, we illustrated and compared the additive and multiplicative hazards models for analysis of recurrent event durations under (i) a varying baseline with a common coefficient effect and (ii) a varying baseline with an order-specific coefficient effect.</p> <p>Results</p> <p>The analysis showed that both additive and multiplicative hazards models, with varying baseline and common coefficient effects, gave similar results with regard to covariates selected to remain in the model of our real dataset. The confidence intervals of the multiplicative hazards model were wider than the additive hazards model for each of the recurrent events. In addition, in both models, the confidence interval gets wider as the revisit order increased because the risk set decreased as the order of visit increased.</p> <p>Conclusions</p> <p>Due to the frequency of multiple failure times or recurrent event duration data in clinical and epidemiologic studies, the multiplicative and additive hazards models are widely applicable and present different information. Hence, it seems desirable to use them, not as alternatives to each other, but together as complementary methods, to provide a more comprehensive understanding of data.</p