Oxygenation of Phenols with Water as the Oxygen Source and Oxoammonium Salt as the Oxidant.

Aromatic C-H oxygenation is important in both industrial production and organic synthesis. Here we report a metal-free approach for phenol oxygenation with water as the oxygen source using oxoammonium salts as the renewable oxidant. Employing this protocol, various alkyl-substituted phenols were converted into benzoquinones in yields of 59-98%. On the basis of 18O-labeling and kinetic studies, the hydroxy-oxoammonium adduct was proposed to attack the aromatic ring similarly to electrophilic aromatic substitution. We suppose that the findings described here not only provide an efficient and highly selective protocol for aromatic C-H oxygenation but also may encourage further developments of possible transition-metal-free catalytic methods.

Developing deep learning-based strategies to predict the risk of hepatocellular carcinoma among patients with nonalcoholic fatty liver disease from electronic health records.

OBJECTIVE: The accuracy of deep learning models for many disease prediction problems is affected by time-varying covariates, rare incidence, covariate imbalance and delayed diagnosis when using structured electronic health records data. The situation is further exasperated when predicting the risk of one disease on condition of another disease, such as the hepatocellular carcinoma risk among patients with nonalcoholic fatty liver disease due to slow, chronic progression, the scarce of data with both disease conditions and the sex bias of the diseases. The goal of this study is to investigate the extent to which the aforementioned issues influence deep learning performance, and then devised strategies to tackle these challenges. These strategies were applied to improve hepatocellular carcinoma risk prediction among patients with nonalcoholic fatty liver disease. METHODS: We evaluated two representative deep learning models in the task of predicting the occurrence of hepatocellular carcinoma in a cohort of patients with nonalcoholic fatty liver disease (n = 220,838) from a national EHR database. The disease prediction task was carefully formulated as a classification problem while taking censorship and the length of follow-up into consideration. RESULTS: We developed a novel backward masking scheme to deal with the issue of delayed diagnosis which is very common in EHR data analysis and evaluate how the length of longitudinal information after the index date affects disease prediction. We observed that modeling time-varying covariates improved the performance of the algorithms and transfer learning mitigated reduced performance caused by the lack of data. In addition, covariate imbalance, such as sex bias in data impaired performance. Deep learning models trained on one sex and evaluated in the other sex showed reduced performance, indicating the importance of assessing covariate imbalance while preparing data for model training. CONCLUSIONS: The strategies developed in this work can significantly improve the performance of hepatocellular carcinoma risk prediction among patients with nonalcoholic fatty liver disease. Furthermore, our novel strategies can be generalized to apply to other disease risk predictions using structured electronic health records, especially for disease risks on condition of another disease.

FedFSA: Hybrid and federated framework for functional status ascertainment across institutions.

INTRODUCTION: Patients' functional status assesses their independence in performing activities of daily living, including basic ADLs (bADL), and more complex instrumental activities (iADL). Existing studies have discovered that patients' functional status is a strong predictor of health outcomes, particularly in older adults. Depite their usefulness, much of the functional status information is stored in electronic health records (EHRs) in either semi-structured or free text formats. This indicates the pressing need to leverage computational approaches such as natural language processing (NLP) to accelerate the curation of functional status information. In this study, we introduced FedFSA, a hybrid and federated NLP framework designed to extract functional status information from EHRs across multiple healthcare institutions. METHODS: FedFSA consists of four major components: 1) individual sites (clients) with their private local data, 2) a rule-based information extraction (IE) framework for ADL extraction, 3) a BERT model for functional status impairment classification, and 4) a concept normalizer. The framework was implemented using the OHNLP Backbone for rule-based IE and open-source Flower and PyTorch library for federated BERT components. For gold standard data generation, we carried out corpus annotation to identify functional status-related expressions based on ICF definitions. Four healthcare institutions were included in the study. To assess FedFSA, we evaluated the performance of category- and institution-specific ADL extraction across different experimental designs. RESULTS: ADL extraction performance ranges from an F1-score of 0.907 to 0.986 for bADL and 0.825 to 0.951 for iADL across the four healthcare sites. The performance for ADL extraction with impairment ranges from an F1-score of 0.722 to 0.954 for bADL and 0.674 to 0.813 for iADL across four healthcare sites. For category-specific ADL extraction, laundry and transferring yielded relatively high performance, while dressing, medication, bathing, and continence achieved moderate-high performance. Conversely, food preparation and toileting showed low performance. CONCLUSION: NLP performance varied across ADL categories and healthcare sites. Federated learning using a FedFSA framework performed higher than non-federated learning for impaired ADL extraction at all healthcare sites. Our study demonstrated the potential of the federated learning framework in functional status extraction and impairment classification in EHRs, exemplifying the importance of a large-scale, multi-institutional collaborative development effort.

Is coffee, tea, and red wine consumption beneficial for individuals with hypertension?

OBJECTIVE: To investigate the associations of tea, coffee, and red wine intakes with health risks among individuals with hypertension. METHODS: This prospective cohort study included participants with hypertension from the UK Biobank cohort. Study exposures included self-reported intakes of coffee, tea, and red wine. The primary outcome was all-cause mortality, and the secondary outcomes were cardiovascular mortality and cardiovascular disease. The associations of beverage intake with outcomes were analyzed using Cox regression models. The hazard ratios and 95% confidence intervals were estimated. RESULTS: A total of 187 708 participants with hypertension were included. The median follow-up period was 13.8 years. In individuals with hypertension, drinking one to two cups/day of coffee or three to four cups/day of tea was significantly associated with the lowest risk of all-cause mortality compared with less than one cup/day [hazard ratio for coffee, 0.943 (95% confidence interval, 0.908-0.979); hazard ratio for tea, 0.882 (95% confidence interval, 0.841-0.924)]. Red wine intake was inversely associated with all-cause mortality risk. Dose-response analysis revealed that high coffee intake (approximately greater than or equal to six cups/day) was significantly associated with increased risks of cardiovascular mortality and cardiovascular disease, but high tea and red wine intakes were not. Furthermore, replacing plain water with tea, but not coffee, significantly reduced the risks of all-cause mortality and cardiovascular disease. Replacing other alcoholic beverages with red wine also significantly reduced the risks of all three outcomes. CONCLUSIONS: These findings suggest that tea and red wine, but not coffee, can be part of a healthy diet for the hypertensive population.

Application of membrane separation technology in the purification of pharmaceutical components.

Traditional Chinese medicine (TCM) is often composed of a variety of natural medicines. Its composition is complex, and many of its components can not be analyzed and identified. The first step in the rational application of TCM is to successfully separate the effective components which is also a great inspiration for the development of new drugs. Among the many separation technologies of TCM, the traditional heating concentration separation technology has high energy consumption and low efficiency. As a new separation technology, membrane separation technology has the characteristics of simple operation, high efficiency, environment-friendly and so on. The separation effect of high molecular weight difference solution is better. The applications of several main membrane separation technologies such as microfiltration, nanofiltration, ultrafiltration and reverse osmosis are reviewed, the methods of restoring membrane flux after membrane fouling are discussed, and their large-scale industrial applications in the future are prospected and summarized.

Tanshinone IIA changed the amniotic fluid volume and regulated expression of AQP1 and AQP3 in amniotic epithelium cells: a promising drug treating abnormal amniotic fluid volume.

BACKGROUND: Many studies have confirmed the association of aquaporins (AQPs) with abnormal amniotic fluid volume (AFV). In our previous experiments, we found that Tanshinone IIA was able to regulate the expression of AQP1 and AQP3. However, the exact mechanism by which Tanshinone IIA regulates AQPs protein expression and its effect on AFV remains unclear. The purpose of this study was to investigate the effects of Tanshinone IIA on AFV and the possible molecular mechanism of regulation of AQP1 and AQP3. METHODS: The expression of AQPs protein in the amniotic membranes was compared between pregnant women with normal pregnancy and those with isolated oligohydramnios. The AQP1 knockout (AQP1-KO) mice and wild-type (WT) mice were treated with saline or Tanshinone IIA (10 mg/kg) at 13.5GD and 16.5GD. Human amniotic epithelium cells (hAECs) from pregnant women with normal AFV and isolated oligohydramnios were incubated with 35 µmmol/L Tanshinone IIA or 25 mmol/L LiCl [inhibitor of glycogen synthetic kinase 3ß (GSK-3ß)]. The protein expressions of AQPs, GSK-3ß, phospho-GSK-3ß (Ser9) in fetal membranes of mice and human amniotic epithelium cells were detected by western blotting. RESULTS: The expression of AQP1 protein in the amniotic membrane of isolated oligohydramnios was increased compared with normal pregnancy. The AFV in AQP1-KO mice is higher than that in WT mice. In wild-type mice, AFV in Tanshinone IIA group was significantly higher than that in control group, and AQP1 protein expression was significantly lower than that in control group, but in AQP1 knockout mice, Tanshinone IIA reduced amniotic fluid volume and AQP3 protein expression at 16.5GD. Tanshinone IIA reduced AQP1, AQP3 and p-GSK-3ß (Ser9) protein expression in normal hAECs, and this effect was inhibited by LiCl. In hAECs with oligohydramnios, the down-regulation of AQP1 and up-regulation of AQP3 by Tanshinone IIA was independent of GSK-3ß signaling pathway. CONCLUSIONS: Tanshinone IIA may increase AFV in normal pregnancy by downregulating AQP1 protein expression in the fetal membranes, which may be associated with p-GSK-3ß signaling pathway. But a larger AFV in AQP1-KO mice was significantly attenuated by Tanshinone IIA, which may be related to AQP3. Tanshinone IIA is a promising drug for the treatment of amniotic fluid abnormality.

Associations between the size and duration of asymptomatic subchorionic hematoma and pregnancy outcomes in women with singleton pregnancies.

BACKGROUND: The purpose of this study was to investigate the relationship between the size and duration of asymptomatic subchorionic hematoma and pregnancy outcomes in women with singleton pregnancies. METHODS: This was a retrospective study that enrolled 701 singleton pregnant women who were diagnosed with asymptomatic subchorionic hematoma by ultrasound at 5-10 gestational weeks. The control group recruited 640 normal pregnant women without subchorionic hematoma who were matched with subchorionic hematoma group on baseline characteristics. The pregnancy outcomes were compared between the two groups, and the associations of the size and duration of subchorionic hematoma with pregnancy outcomes were analyzed by logistic regression model. RESULTS: Compared with the normal pregnancy group, the incidence of, gestational diabetes mellitus, gestational thrombocytopenia, placenta adhesion, fetal growth restriction, macrosomia in subchorionic hematoma group were higher (all P < 0.05). After adjusting for confounding factors, the hematoma size was positively associated with the occurrence of gestational hypothyroidism (adjusted OR[95%CI]: 1.029[1.004-1.054]), intrahepatic cholestasis of pregnancy (adjusted OR[95%CI]: 1.095[1.047-1.146]), term premature rupture of membranes (adjusted OR[95%CI]: 1.044[1.005-1.085]), hypertensive disorders of pregnancy (adjusted OR[95%CI]: 1.030[1.0004-1.060]), gestational thrombocytopenia (adjusted OR[95%CI]: 1.078 [1.045-1.113]), placenta adhesion (adjusted OR[95%CI]: 1.054 [1.027-1.082]), and the duration of hematoma was positively associated with the incidence of term premature rupture of membranes (adjusted OR[95%CI]: 1.070[1.027-1.115]), gestational diabetes mellitus (adjusted OR[95%CI]: 1.938 [1.886-1.993]) and fetal growth restriction (adjusted OR[95%CI]: 1.194 [1.124-1.268]). CONCLUSIONS: The presence, size and duration of a first-trimester asymptomatic subchorionic hematoma may be associated with adverse pregnancy outcomes at later gestations such as term premature rupture of membranes and fetal growth restriction.

Rapamycin ameliorates brain damage and maintains mitochondrial dynamic balance in diabetic rats subjected to middle cerebral artery occlusion.

To investigate the effect of rapamycin on mitochondrial dynamic balance in diabetic rats subjected to cerebral ischemia-reperfusion injury. Male Sprague Dawley (SD) rats (n = 78) were treated with high fat diet combined with streptozotocin injection to construct diabetic model in rats. Transient middle cerebral artery occlusion (MCAO) of 2 hours was induced and the brains were harvested after 1 and 3 days of reperfusion. Rapamycin was injected intraperitoneally for 3 days prior to and immediately after operation, once a day. The neurological function was assessed, infarct volumes were measured and HE staining as well as immunohistochemistry were performed. The protein of hippocampus was extracted and Western blotting were performed to detect the levels of mTOR, mitochondrial dynamin related proteins (DRP1, p-DRP1, OPA1), SIRT3, and Nix/BNIP3L. Diabetic hyperglycemia worsened the neurological function performance (p < 0.01), enlarged infarct size (p < 0.01) and increased ischemic neuronal cell death (p < 0.01). The increased damage was associated with elevations of p-mTOR, p-S6, and p-DRP1; and suppressions of SIRT3 and Nix/BNIP3L. Rapamycin ameliorated diabetes-enhanced ischemic brain damage and reversed the biomarker alterations caused by diabetes. High glucose activated mTOR pathway and caused mitochondrial dynamics toward fission. The protective effect of rapamycin against diabetes-enhanced ischemic brain damage was associated with inhibiting mTOR pathway, redressing mitochondrial dynamic imbalance, and elevating SIRT3 and Nix/BNIP3L expression.

Indications for Magnetic Resonance Imaging in Patients With Behcet Uveitis.

BACKGROUND: Behcet disease is a systemic vasculitis, which may involve the eyes and central nervous system. The true prevalence of neurological involvement is not precisely known but may be associated with ocular involvement. This study investigates the association between Behcet uveitis and neuro-Behcet disease. METHODS: A retrospective single-center analysis was conducted for consecutive patients with Behcet uveitis at the Massachusetts Eye Research and Surgery Institution. Uveitis characteristics, neurological symptoms, fluorescein fundus angiography, and MRI results were recorded. RESULTS: Our population included 108 patients with Behcet uveitis, and 26 (24.1%) were found to have neurological involvement associated with Behcet disease. Optic nerve leakage on fundus angiography and neurological symptoms were associated with an increased risk of neurological involvement. Three cases (11.5%) were nonparenchymal, while 23 (88.5%) were parenchymal with lesions in the cortex, subcortical white matter, thalamus, basal ganglia, and brainstem. CONCLUSIONS: There is a high comorbidity between ocular and neurological involvement in Behcet disease. Careful assessment of neurological symptoms and baseline fluorescein fundus angiography are recommended for patients with Behcet disease. MRI has a high diagnostic yield and should be pursued if there is concern for progressive or pre-existing neurological involvement.

Ameliorative effect of Luffa cylindrica fruits on Caenorhabditis elegans and cellular models of Alzheimer's disease-related pathology via autophagy induction.

BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder without an effective cure. Natural products, while showing promise as potential therapeutics for AD, remain underexplored. AIMS: This study was conducted with the goal of identifying potential anti-AD candidates from natural sources using Caenorhabditis elegans (C. elegans) AD-like models and exploring their mechanisms of action. MATERIALS & METHODS: Our laboratory's in-house herbal extract library was utilized to screen for potential anti-AD candidates using the C. elegans AD-like model CL4176. The neuroprotective effects of the candidates were evaluated in multiple C. elegans AD-like models, specifically targeting Aß- and Tau-induced pathology. In vitro validation was conducted using PC-12 cells. To investigate the role of autophagy in mediating the anti-AD effects of the candidates, RNAi bacteria and autophagy inhibitors were employed. RESULTS: The ethanol extract of air-dried fruits of Luffa cylindrica (LCE), a medicine-food homology species, was found to inhibit Aß- and Tau-induced pathology (paralysis, ROS production, neurotoxicity, and Aß and pTau deposition) in C. elegans AD-like models. LCE was non-toxic and enhanced C. elegans' health. It was shown that LCE activates autophagy and its anti-AD efficacy is weakened with the RNAi knockdown of autophagy-related genes. Additionally, LCE induced mTOR-mediated autophagy, reduced the expression of AD-associated proteins, and decreased cell death in PC-12 cells, which was reversed by autophagy inhibitors (bafilomycin A1 and 3-methyladenine). DISCUSSION: LCE, identified from our natural product library, emerged as a valuable autophagy enhancer that effectively protects against neurodegeneration in multiple AD-like models. RNAi knockdown of autophagy-related genes and cotreatment with autophagy inhibitors weakened its anti-AD efficacy, implying a critical role of autophagy in mediating the neuroprotective effects of LCE. CONCLUSION: Our findings highlight the potential of LCE as a functional food or drug for targeting AD pathology and promoting human health.

Improving Mitochondrial Function in Skeletal Muscle Contributes to the Amelioration of Insulin Resistance by Nicotinamide Riboside.

High-fat diet (HFD)-induced insulin resistance (IR) in skeletal muscle is often accompanied by mitochondrial dysfunction and oxidative stress. Boosting nicotinamide adenine dinucleotide (NAD) using nicotinamide riboside (NR) can effectively decrease oxidative stress and increase mitochondrial function. However, whether NR can ameliorate IR in skeletal muscle is still inconclusive. We fed male C57BL/6J mice with an HFD (60% fat) ± 400 mg/kg·bw NR for 24 weeks. C2C12 myotube cells were treated with 0.25 mM palmitic acid (PA) ± 0.5 mM NR for 24 h. Indicators for IR and mitochondrial dysfunction were analyzed. NR treatment alleviated IR in HFD-fed mice with regard to improved glucose tolerance and a remarkable decrease in the levels of fasting blood glucose, fasting insulin and HOMA-IR index. NR-treated HFD-fed mice also showed improved metabolic status regarding a significant reduction in body weight and lipid contents in serum and the liver. NR activated AMPK in the skeletal muscle of HFD-fed mice and PA-treated C2C12 myotube cells and upregulated the expression of mitochondria-related transcriptional factors and coactivators, thereby improving mitochondrial function and alleviating oxidative stress. Upon inhibiting AMPK using Compound C, NR lost its ability in enhancing mitochondrial function and protection against IR induced by PA. In summary, improving mitochondrial function through the activation of AMPK pathway in skeletal muscle may play an important role in the amelioration of IR using NR.

Inverse Association of Serum Adipsin with the Remission of Nonalcoholic Fatty-Liver Disease: A 3-Year Community-Based Cohort Study.

PURPOSES: Adipokine alterations contribute to the development and remission of nonalcoholic fatty-liver disease (NAFLD). Adipsin is one of the most abundant adipokines and is almost exclusively produced by adipocytes. However, data on adipsin in human NAFLD are limited and controversial. We performed this study to investigate the association between adipsin and the remission of NAFLD in middle-aged and elderly Chinese adults. METHODS: Whether adipsin is associated with the remission of NAFLD in a 3-year community-based prospective cohort study was investigated. Baseline levels of adipsin were measured in serum samples collected from 908 NAFLD participants. NAFLD was diagnosed using abdominal ultrasonography. Logistic regression analysis and a multiple stepwise logistic regression model including different variables were conducted to evaluate the association between serum adipsin levels and the remission of NAFLD. RESULTS: During a mean follow-up of 3.14 ± 0.36 years, 247 (27.20%) participants with NAFLD at baseline were in remission. At baseline, serum adipsin concentration was positively correlated with body mass index (r: 0.39, p < 0.001), insulin (r: 0.31, p < 0.001), and homeostasis model assessment of insulin resistance (r: 0.31, p < 0.001) and was inversely associated with NAFLD remission with a fully adjusted odds ratio (OR) of 0.28 (0.16-0.48) (p trend < 0.001). In a multiple stepwise logistic regression model, circulating adipsin independently predicted NAFLD remission (OR: 0.284, 95% confidence interval [CI]: 0.172-0.471, p for trend <0.001). The area under the receiver operating characteristic curve was 0.751 (95% CI: 0.717-0.785) (p < 0.001) for the prediction model of NAFLD remission. CONCLUSIONS: We provide evidence for an association between serum adipsin levels and the remission of NAFLD in a community-based prospective cohort study. Serum adipsin can be a potential biomarker for predicting NAFLD remission.

Automatic segmentation model of intercondylar fossa based on deep learning: a novel and effective assessment method for the notch volume.

BACKGROUND: Notch volume is associated with anterior cruciate ligament (ACL) injury. Manual tracking of intercondylar notch on MR images is time-consuming and laborious. Deep learning has become a powerful tool for processing medical images. This study aims to develop an MRI segmentation model of intercondylar fossa based on deep learning to automatically measure notch volume, and explore its correlation with ACL injury. METHODS: The MRI data of 363 subjects (311 males and 52 females) with ACL injuries incurred during non-contact sports and 232 subjects (147 males and 85 females) with intact ACL were retrospectively analyzed. Each layer of intercondylar fossa was manually traced by radiologists on axial MR images. Notch volume was then calculated. We constructed an automatic segmentation system based on the architecture of Res-UNet for intercondylar fossa and used dice similarity coefficient (DSC) to compare the performance of segmentation systems by different networks. Unpaired t-test was performed to determine differences in notch volume between ACL-injured and intact groups, and between males and females. RESULTS: The DSCs of intercondylar fossa based on different networks were all more than 0.90, and Res-UNet showed the best performance. The notch volume was significantly lower in the ACL-injured group than in the control group (6.12 ± 1.34 cm3 vs. 6.95 ± 1.75 cm3, P < 0.001). Females had lower notch volume than males (5.41 ± 1.30 cm3 vs. 6.76 ± 1.51 cm3, P < 0.001). Males and females who had ACL injuries had smaller notch than those with intact ACL (p < 0.001 and p < 0.005). Men had larger notches than women, regardless of the ACL injuries (p < 0.001). CONCLUSION: Using a deep neural network to segment intercondylar fossa automatically provides a technical support for the clinical prediction and prevention of ACL injury and re-injury after surgery.

Genome-Wide Identification, Expression and Interaction Analysis of GmSnRK2 and Type A PP2C Genes in Response to Abscisic Acid Treatment and Drought Stress in Soybean Plant.

As a typical ancient tetraploid, soybean (Glycine max) is an important oil crop species and plays a crucial role in supplying edible oil, plant protein and animal fodder worldwide. As global warming intensifies, the yield of soybean in the field is often strongly restricted by drought stress. SNF1-related protein kinase 2 (SnRK2) and type A protein phosphatase 2C (PP2C-A) family members are core components of the abscisic acid (ABA) signal transduction pathway in plants and have been suggested to play important roles in increasing plant tolerance to drought stress, but genetic information supporting this idea is still lacking in soybean. Here, we cloned the GmSnRK2s and GmPP2C-A family genes from the reference genome of Williams 82 soybean. The results showed that the expression patterns of GmSnRK2s and GmPP2C-As are spatiotemporally distinct. The expression of GmSnRK2s in response to ABA and drought signals is not strictly the same as that of Arabidopsis SnRK2 homologous genes. Moreover, our results indicated that the duplicate pairs of GmSnRK2s and GmPP2C-As have similar expression patterns, cis-elements and relationships. GmSnRK2.2 may have a distinct function in the drought-mediated ABA signaling pathway. Furthermore, the results of yeast two-hybrid (Y2H) assays between GmSnRK2s and GmPP2C-As revealed that GmSnRK2.17, GmSnRK2.18, GmSnRK2.22, GmPP2C5, GmPP2C7, GmPP2C10 and GmPP2C17 may play central roles in the crosstalk among ABA signals in response to drought stress. Furthermore, GmPP2C-As and GmSnRKs were targeted by miRNA and validated by degradome sequencing, which may play multiple roles in the crosstalk between ABA and drought signals and other stress signals. Taken together, these results indicate that GmSnRK2s and GmPP2C-As may play a variety of roles in the drought-mediated ABA signaling pathway.

Asymmetric Bubble Formation at Rectangular Orifices.

Bubble formation in liquids is frequently observed in nature and applied in various industrial processes. These include pool and flow boiling for thermal management systems, where bubbles may form asymmetrically at narrow slits and in convective flows. While previous studies have focused on symmetric bubble formation at circular orifices, the dynamics of asymmetric bubble formation remains poorly understood. Here, we experimentally investigate bubble formation at rectangular orifices and examine the effects of the orifice size and aspect ratio and the gas flow rate on the bubble size. The asymmetric bubble shape evolution at the rectangular orifice is analyzed, and we find that the size of the bubble neck is controlled either by the orifice size or by the capillary length. Based on these findings, we develop a static force balance model to predict the bubble size in the quasi-static regime, where the roles of Bond number and aspect ratio are identified. The bubble size evolution in the dynamic regime is further understood by introducing a Weber number that evaluates the effect of the virtual mass force induced by gas flow. Our study provides physical understanding of the dynamics of asymmetric bubble formation and guidance to predict the bubble size at asymmetric orifices.

Increased Intracranial Pressure Without Hydrocephalus Associated With Spinal Cord Tumor: Literature Review.

ABSTRACT: Spinal cord tumors (SCTs) may rarely cause increased intracranial pressure without hydrocephalus (IICPWH). A review of the English literature published after 1970 revealed 29 cases of IICPWH secondary to SCT. The following data were acquired: demographics, tumor characteristics, ophthalmic and neurological manifestations, and cerebral spinal fluid (CSF) features. We summarize the existing literature regarding various theories of pathophysiology, spinal imaging recommendations, and treatment modalities used in managing such patients. Patients with papilledema who also have neurological signs or symptoms of myelopathy or elevated CSF protein particularly in the setting of an atypical demographic for pseudotumor cerebri should raise a suspicion for a spinal tumor and prompt further investigation with a spinal MRI.

Upregulation of autophagy in M2 macrophage by vitamin D alleviates crystalline silica-induced pulmonary inflammatory damage.

Crystalline silica (CS) is a universal environmental pollutant, which causes a typical inflammatory lung injury. Vitamin D shows huge potential against particles-induced lung injury, while little known about the molecular mechanism involved in macrophage autophagy. In this study, we aim to identify the protective effects of vitamin D on CS caused lung inflammatory injury and clarify the detail mechanism. After exposure to CS (3 mg/mice in 50 µl PBS), wildtype and Atg7flox/flox Lyz2-cre mice were treated with or without vitamin D3 (40,000 IU/kg). The results indicated that exposure to CS caused an obvious lung injury, manifesting as pathological structural changes, macrophage-dominated inflammatory cell infiltration and increased pro-inflammatory cytokines. Remarkably, these damages were more serious in Atg7flox/flox Lyz2-cre mice. Vitamin D was found to inverse CS-induced inflammatory cell infiltration and restored anti-inflammatory M2 macrophages by inducing autophagy, which attenuated lung injury, as determined by decreased levels of apoptosis and inflammatory response. While, this effects of vitamin D were slashed in Atg7flox/flox Lyz2-cre mice. This study reveals the adverse effect of CS on lung tissue and the protective mechanism of vitamin D involved in M2 macrophages autophagy, which attenuates CS-caused lung injury.

Managing Photophobia with the Utilisation of Smart Light Bulbs.

Photophobia can affect a person's quality of life. We present a case of idiopathic photophobia that was successfully managed with smart light bulbs that allowed the patient to participate in daily activities. Smart light can complement other treatment options including tinted lenses. In conclusion, smart light is a novel way of treating photophobia and should be considered by clinicians.

Deep Learning Approach for Anterior Cruciate Ligament Lesion Detection: Evaluation of Diagnostic Performance Using Arthroscopy as the Reference Standard.

BACKGROUND: MRI is the most commonly used imaging method for diagnosing anterior cruciate ligament (ACL) injuries. However, the interpretation of knee MRI is time-intensive and depends on the clinical experience of the reader. An automated detection system based on a deep-learning algorithm may improve interpretation time and reliability. PURPOSE: To determine the feasibility of using a deep learning approach to detect ACL injuries within the knee joint on MRI. STUDY TYPE: Retrospective. POPULATION: In all, 163 subjects with an ACL tear and 245 subjects with an intact ACL. There were 285, 81, and 42 volumes for training, validation, and test sets, respectively. FIELD STRENGTH/SEQUENCE: 2D sagittal proton density-weighted spectral attenuated inversion recovery sequences at 1.5T and 3.0T. ASSESSMENT: Based on the architecture of 3D DenseNet, we constructed a classification convolutional neural network. We tested this deep learning approach with different inputs and two other algorithms, including VGG16 and ResNet. Then we had both inexperienced radiologists and senior radiologists read the MR images. STATISTICAL TESTS: Using arthroscopic results as the reference standard, the performance of three different inputs and three different algorithms, the residents and senior radiologists assessed the classification accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC). RESULTS: The accuracy, sensitivity, specificity, PPV, and NPV of our customized 3D deep learning architecture was 0.957, 0.976, 0.944, 0.940, and 0.976, respectively. The average AUCs were 0.946, 0.859, 0.960 for ResNet, VGG16, and our proposed network, respectively. The diagnostic accuracy of our model, residents, and senior radiologists was 0.957, 0.814, and 0.899, respectively. DATA CONCLUSION: Our study demonstrated the feasibility of using an automated deep-learning-based detection system to evaluate ACL injury. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 1 J. MAGN. RESON. IMAGING 2020;52:1745-1752.

Asthma Exacerbation Prediction and Risk Factor Analysis Based on a Time-Sensitive, Attentive Neural Network: Retrospective Cohort Study.

BACKGROUND: Asthma exacerbation is an acute or subacute episode of progressive worsening of asthma symptoms and can have a significant impact on patients' quality of life. However, efficient methods that can help identify personalized risk factors and make early predictions are lacking. OBJECTIVE: This study aims to use advanced deep learning models to better predict the risk of asthma exacerbations and to explore potential risk factors involved in progressive asthma. METHODS: We proposed a novel time-sensitive, attentive neural network to predict asthma exacerbation using clinical variables from large electronic health records. The clinical variables were collected from the Cerner Health Facts database between 1992 and 2015, including 31,433 adult patients with asthma. Interpretations on both patient and cohort levels were investigated based on the model parameters. RESULTS: The proposed model obtained an area under the curve value of 0.7003 through a five-fold cross-validation, which outperformed the baseline methods. The results also demonstrated that the addition of elapsed time embeddings considerably improved the prediction performance. Further analysis observed diverse distributions of contributing factors across patients as well as some possible cohort-level risk factors, which could be found supporting evidence from peer-reviewed literature such as respiratory diseases and esophageal reflux. CONCLUSIONS: The proposed neural network model performed better than previous methods for the prediction of asthma exacerbation. We believe that personalized risk scores and analyses of contributing factors can help clinicians better assess the individual's level of disease progression and afford the opportunity to adjust treatment, prevent exacerbation, and improve outcomes.