This study deals with the free-surface supercritical flow through a double-right-angled bend (DRAB), which can be found in storm drainage networks in steep terrains. Laboratory experiments showed that strong backwater effects and water-surface oscillations are generated upstream of the DRAB, especially in supercritical flow conditions. This paper investigated the DRAB hydraulic behavior and water-surface heading up (backwater), and oscillations under supercritical flow conditions. Thirty-four lab experiments were conducted with Froude numbers ranging between 1.03 and 2.63. Dye injection and video analysis were used to visually capture the flow structure and to record water-surface oscillations. A tracker package was utilized to analyze the collected visual data. Time series and spectral analysis were used to identify the statistical characteristics of recorded water level time series and the dominant frequencies. It was found that the dominant frequencies of water-surface oscillations upstream of the DRAB range between 1.6 and 4.6 Hz with an average value of about 3 Hz. The Strouhal number of the water-surface oscillations is more sensitive to the Froude number than to the Reynolds number. The Strouhal number ranged between 0.03 and 0.3 for Froude numbers ranging from 2.63 to 1.03. The study confirms that near critical flow conditions exhibit the highest water oscillation, and that the maximum nondimensional water depth upstream of the DRAB is underestimated by both the Grashof formula and Knapp and Ippen (1939) model. A new formula is proposed to estimate the maximum water depth upstream of the DRAB.

The enzyme arginase 1 (A1) hydrolyzes the amino acid arginine to form L-ornithine and urea. Ornithine is further converted to polyamines by the ornithine decarboxylase (ODC) enzyme. We previously reported that deletion of myeloid A1 in mice exacerbates retinal damage after ischemia/reperfusion (IR) injury. Furthermore, treatment with A1 protects against retinal IR injury in wild-type mice. PEG-A1 also mitigates the exaggerated inflammatory response of A1 knockout (KO) macrophages in vitro. Here, we sought to identify the anti-inflammatory pathway that confers macrophage A1-mediated protection against retinal IR injury. Acute elevation of intraocular pressure was used to induce retinal IR injury in mice. A multiplex cytokine assay revealed a marked increase in the inflammatory cytokines interleukin 1β (IL-1β) and tumor necrosis factor α (TNF-α) in the retina at day 5 after IR injury. In vitro, blocking the A1/ODC pathway augmented IL-1β and TNF-α production in stimulated macrophages. Furthermore, A1 treatment attenuated the stimulated macrophage metabolic switch to a pro-inflammatory glycolytic phenotype, whereas A1 deletion had the opposite effect. Screening for histone deacetylases (HDACs) which play a role in macrophage inflammatory response showed that A1 deletion or ODC inhibition increased the expression of HDAC3. We further showed the involvement of HDAC3 in the upregulation of TNF-α but not IL-1β in stimulated macrophages deficient in the A1/ODC pathway. Investigating HDAC3 KO macrophages showed a reduced inflammatory response and a less glycolytic phenotype upon stimulation. In vivo, HDAC3 co-localized with microglia/macrophages at day 2 after IR in WT retinas and was further increased in A1-deficient retinas. Collectively, our data provide initial evidence that A1 exerts its anti-inflammatory effect in macrophages via ODC-mediated suppression of HDAC3 and IL-1β. Collectively we propose that interventions that augment the A1/ODC pathway and inhibit HDAC3 may confer therapeutic benefits for the treatment of retinal ischemic diseases.

The enzyme arginase 1 (A1) hydrolyzes the amino acid arginine to form L-ornithine and urea. Ornithine is further converted to polyamines by the ornithine decarboxylase (ODC) enzyme. We previously reported that deletion of myeloid A1 in mice exacerbates retinal damage after ischemia/reperfusion (IR) injury. Furthermore, treatment with A1 protects against retinal IR injury in wild-type mice. PEG-A1 also mitigates the exaggerated inflammatory response of A1 knockout (KO) macrophages in vitro. Here, we sought to identify the anti-inflammatory pathway that confers macrophage A1-mediated protection against retinal IR injury. Acute elevation of intraocular pressure was used to induce retinal IR injury in mice. A multiplex cytokine assay revealed a marked increase in the inflammatory cytokines interleukin 1β (IL-1β) and tumor necrosis factor α (TNF-α) in the retina at day 5 after IR injury. In vitro, blocking the A1/ODC pathway augmented IL-1β and TNF-α production in stimulated macrophages. Furthermore, A1 treatment attenuated the stimulated macrophage metabolic switch to a pro-inflammatory glycolytic phenotype, whereas A1 deletion had the opposite effect. Screening for histone deacetylases (HDACs) which play a role in macrophage inflammatory response showed that A1 deletion or ODC inhibition increased the expression of HDAC3. We further showed the involvement of HDAC3 in the upregulation of TNF-α but not IL-1β in stimulated macrophages deficient in the A1/ODC pathway. Investigating HDAC3 KO macrophages showed a reduced inflammatory response and a less glycolytic phenotype upon stimulation. In vivo, HDAC3 co-localized with microglia/macrophages at day 2 after IR in WT retinas and was further increased in A1-deficient retinas. Collectively, our data provide initial evidence that A1 exerts its anti-inflammatory effect in macrophages via ODC-mediated suppression of HDAC3 and IL-1β. Collectively we propose that interventions that augment the A1/ODC pathway and inhibit HDAC3 may confer therapeutic benefits for the treatment of retinal ischemic diseases.

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Deep generative models, such as variational autoencoders (VAE), have gained increasing attention in computational biology due to their ability to capture complex data manifolds which subsequently can be used to achieve better performance in downstream tasks, such as cancer type prediction or subtyping of cancer. However, these models are difficult to train due to the large number of hyperparameters that need to be tuned. To get a better understanding of the importance of the different hyperparameters, we examined six different VAE models when trained on TCGA transcriptomics data and evaluated on the downstream tasks of cluster agreement with cancer subtypes and survival analysis. We studied the effect of the latent space dimensionality, learning rate, optimizer, initialization and activation function on the quality of subsequent downstream tasks on the TCGA samples. We found β-TCVAE and DIP-VAE to have a good performance, on average, despite being more sensitive to hyperparameters selection. Based on these experiments, we derived recommendations for selecting the different hyperparameters settings. To ensure generalization, we tested all hyperparameter configurations on the GTEx dataset. We found a significant correlation (ρ = 0.7) between the hyperparameter effects on clustering performance in the TCGA and GTEx datasets. This highlights the robustness and generalizability of our recommendations. In addition, we examined whether the learned latent spaces capture biologically relevant information. Hereto, we measured the correlation and mutual information of the different representations with various data characteristics such as gender, age, days to metastasis, immune infiltration, and mutation signatures. We found that for all models the latent factors, in general, do not uniquely correlate with one of the data characteristics nor capture separable information in the latent factors even for models specifically designed for disentanglement.

Leptomeningeal disease (LMD) occurs when tumors seed into the leptomeningeal space and cerebrospinal fluid (CSF), leading to severe neurological deterioration and poor survival outcomes. We utilized comprehensive multi-omics analyses of CSF from patients with lymphoma LMD to demonstrate an immunosuppressive cellular microenvironment and identified dysregulations in proteins and lipids indicating neurodegenerative processes. Strikingly, we found a significant accumulation of toxic branched-chain keto acids (BCKA) in the CSF of patients with LMD. The BCKA accumulation was found to be a pan-cancer occurrence, evident in lymphoma, breast cancer, and melanoma LMD patients. Functionally, BCKA disrupted the viability and function of endogenous T lymphocytes, chimeric antigen receptor (CAR) T cells, neurons, and meningeal cells. Treatment of LMD mice with BCKA-reducing sodium phenylbutyrate significantly improved neurological function, survival outcomes, and efficacy of anti-CD19 CAR T cell therapy. This is the first report of BCKA accumulation in LMD and provides preclinical evidence that targeting these toxic metabolites improves outcomes.

Cernunnos deficiency is a rare genetic disorder characterized by immunodeficiency, microcephaly, growth retardation, bird-like facies, sensitivity to ionizing radiation, few autoimmune manifestations, premature aging of hematopoietic stem cells at an early age, and occasional myeloproliferative disease. Herein we present five Egyptian Cernunnos patients from 3 different families. We describe the patients' clinical phenotypes, their immunological profile as well as genetic results. Sequence analysis revealed three different mutations in the NHEJ1 gene: a nonsense variant c.532C > T; p.(Arg178Ter), an intronic variant c.178-1G > A and a frameshift insertion variant c.233dup; p.(Asn78LysfsTer14). In conclusion, Cernunnos deficiency can have a wide range of clinical features. The characteristic immune profile including a decrease in recent thymic emigrants and naive T cells, markedly elevated memory T cells together with normal to high IgM, and a decrease in IgG and IgA. This immune profile is highly suggestive of Cernunnos deficiency in T-B-NK + SCID patients especially surviving for older ages.