Radar forward-looking imaging is gaining significance due to its convenience in various applications like battlefield reconnaissance, target surveillance and precision guidance. Although synthetic aperture radar (SAR) techniques are commonly used to achieve high azimuth resolution, they suffer from limitations in forward-looking area due to the poor Doppler resolution and the “left-right” ambiguity problem. In recent years, generative adversarial networks (GANs), a common deep learning approach that produces excellent results in image motion blur removal, has been extensively used. This letter proposes building an end-to-end forward-looking imaging network using GAN to produce high-resolution images, which increases the efficiency and quality of imaging. Compared to conventional forward-looking imaging methods such as the deconvolution-based methods, this algorithm eliminates the design and iterative processes of the observation matrix. Simulated and real radar data verified that this approach offers robust recovery and better performance.

Lyme Neuroborreliosis: A case reportBabak Sayad1, Arefeh Babazadeh2, Mohammad Barary3, Rezvan Hosseinzadeh4, Soheil Ebrahimpour2, Zeinab Mohseni Afshar1, *Clinical Research Development Center, Imam Reza Hospital, Kermanshah University of Medical Sciences, Kermanshah, IranInfectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, IranStudent Research Committee, Virtual School of Medical Education and Management, Shahid Beheshti University of Medical Sciences, Tehran, IranStudent Research Committee, Babol University of Medical Sciences, Babol, Iran

Abstract Rationale: Recent studies suggest that both hypo- and hyper-inflammatory ARDS phenotypes characterize severe COVID-19-related pneumonia. The role of lung SARS-CoV-2 viral load in contributing to these phenotypes remains unknown. Objectives: To redefine COVID-19 ARDS phenotypes when considering semi-quantitative SARS-CoV-2 RT-PCR in the bronchoalveolar lavage of intubated patients. To compare the relevance of deep respiratory samples vs plasma in linking the immune response and the semi-quantitative viral loads. Methods: Eligible subjects were adults diagnosed with COVID-19 ARDS who required mechanical ventilation and underwent bronchoscopy. We recorded the immune response in the bronchoalveolar lavage and plasma and semi-quantitative SARS-CoV-2 RT-PCR in the bronchoalveolar lavage. Hierarchical clustering on principal components was applied separately on the two compartments datasets. Baseline characteristics were compared between clusters. Measurements and Results: 20 subjects were enrolled between August 2020 and March 2021. Subjects underwent bronchoscopy on average 3.6 days after intubation. All subjects were treated with dexamethasone prior to bronchoscopy, 11 of 20 (55.6%) received remdesivir and 1 of 20 (5%) received tocilizumab. Adding viral load information to the classic two cluster model of ARDS revealed a new cluster characterized by hypo-inflammatory responses and high viral load in 23.1% of the cohort. Hyperinflammatory ARDS was noted in 15.4% of subjects. Bronchoalveolar lavage clusters were more stable compared to plasma. Conclusions: We identified a unique group of critically ill subjects with COVID-19 ARDS who exhibit hypo-inflammatory responses but high viral loads in the lower airways. Our approach adds the infection dimension to ARDS phenotypes described in COVID-19 pneumonia

The extended phenotype of helical burrowing behavior in animals has evolved independently many times since first appearing after the Cambrian explosion (~540 million years ago). A number of hypotheses have been proposed to explain the evolution of helical burrowing in certain taxa, but no study has searched for a general explanation encompassing all taxa. We reviewed helical burrowing in both extant and extinct animals and from the trace fossil record and compiled from the literature 10 possible hypotheses for why animals construct helical burrows, including our own ideas. Of these, six were post-construction hypotheses—-benefits to the creator or offspring, realized after burrow construction—-and four were construction hypotheses reflecting direct benefits to the creator during construction. We examined the fit of these hypotheses to a total of 21 extant taxa and ichnotaxa representing 59–184 spp. Only two hypotheses—-antipredator, biomechanical advantage—-could not be rejected for any species (possible in 100% of spp.), but six of the hypotheses could not be rejected for most species (possible in 86–100 % of spp.): microclimate buffer, reduced falling sediment (soil), anticrowding, vertical patch, and the above two hypotheses. Four of these six were construction hypotheses, raising the possibility that helical burrowing might have evolved without providing post-construction benefits. Our analysis showed that increased drainage, deposit feeding, microbial farming, and offspring escape could not explain helical burrowing behavior in the majority of taxa (5–48%). Overall, the evidence does not support a general explanation for the evolution of helical burrowing in animals. The function and evolution of the helix as an extended phenotype would seem, at least in some cases, to provide different advantages for different taxa. Although direct tests of many of the hypotheses would be difficult, we nevertheless offer ways to test some of the hypotheses for selected taxa.

This paper describes the urban stream syndrome at Recife, a coastal city at northeast Brazil. The term “urban stream syndrome” have been used to describe ecological degradation of streams in urban environment. Recife city comprises by a low flat plain surrounded by small hills, with a network of water ways formed by three main rivers and almost a hundred of streams, some of them severely degraded. The accelerated population growth has generated disorderly urbanization and has negatively affected the water courses that suffer from problems of water quantity and quality. To carry out a diagnosis and check if the stream is sick, the integrity of the banks, color and smell of the water in the streams, the chemical quality of the water, the presence of organic matter and problems with the fauna were analyzed. Around 25% of the city sewage is not collected, which leads to the pollution of the entire water network. Most of the streams are eutrophic, with very low levels of dissolved oxygen and only more tolerant species can survive. Gradually society and public managers are becoming aware of the problems of urban streams and some initiatives are being taken to face the problem.

Neuromyelitis Optica (NMO) is a rare central nervous system demyelination syndrome predominantly targeting optic nerves and the spinal cord. Here we present a middle-aged female presenting with new onset quadriparesis and a history of persistent splenomegaly and pancytopenia, eventually being diagnosed as NMO along with autoimmune cirrhosis. The association of Neuromyelitis Optica spectrum disorders (NMOSD) with chronic liver disease has not been previously described in the literature. The purpose of this case report is to bring forward an unusual presentation and to ascertain whether it could be part of a heterogenous spectrum of an autoimmune disorder, or merely a co-incidence.

This article reports and analyzes the results of protein complex model accuracy estimation by our methods (DeepUMQA3 and GraphGPSM) in the 15 th Critical Assessment of techniques for protein Structure Prediction (CASP15). The new deep learning-based multimeric complex model accuracy estimation methods are proposed based on the ensemble of three level features coupling with deep residual/graph neural networks. For the input multimeric complex model, we describe it from three levels: overall complex features, intra-monomer features, and inter-monomer features. We designed an overall ultrafast shape recognition (USR) to characterize the relationship between local residues and the overall complex topology, and an inter-monomer USR to characterize the relationship between the residues of one monomer and the topology of other monomers. On the 39 complex targets of CASP15, DeepUMQA3 (Group name: GuijunLab-RocketX) ranked first in the assessment of interface residue accuracy. The Pearson correlation coefficient (PCC) between the interface residues lDDT predicted by DeepUMQA3 and the real lDDT is 0.570, and DeepUMQA3 achieved the highest PCC on 29 out of 39 targets. GraphGPSM (Group name: GuijunLab-PAthreader) had a TM-score PCC>0.9 on 14 targets, showing a good ability to estimate the overall fold accuracy.

The human predictor team PEZYFoldings got third place with GDT-TS (First place with the Assessor’s formulae) in the single-domain category and tenth place in the multimer category in CASP15. In this paper, I describe the exact method used by PEZYFoldings in competitions. As AlphaFold2 and AlphaFold-Multimer, developed by DeepMind, are state-of-the-art structure prediction tools, it was assumed that enhancing the input and output of the tools was an effective strategy to obtain the highest accuracy for structure prediction. Therefore, I used additional tools and databases to collect evolutionarily related sequences and introduced a deep-learning-based model in the refinement step. In addition to these modifications, manual interventions were performed to address various tasks. Detailed analyses were performed after the competition to identify the main contributors to performance. Comparing the number of evolutionarily related sequences I used with those of the other teams that provided AlphaFold2’s baseline predictions revealed that an extensive sequence similarity search was one of the main contributors. The impact of the refinement model was minimal (p <0.05 for the TM score). In addition, I noticed that I had gained large Z-scores with the subunits of H1137, for which I performed manual domain parsing considering the interfaces between the subunits. This finding implies that the manual intervention contributed to my performance. The prediction performance was low when I could not identify the evolutionarily related sequences. T1130 is an example; however, other teams can model better structures. Based on the discussions from the CASP15 conference, the two teams that ranked higher than PEZYFoldings had some hits for T1130. This may be because T1130 is a eukaryotic protein, whereas the additional databases used were mainly from metagenomic sequences, which primarily consist of prokaryotic proteins. These results highlight the opportunities for improvement in 1) multimer prediction, 2) building larger and more diverse databases, and 3) developing tools to predict structures from primary sequences alone. In addition, transferring the manual intervention process to automation is a future concern.

We introduce a deep learning-based ligand pose scoring model called zPoseScore for predicting protein-ligand complexes in the 15th Critical Assessment of Protein Structure Prediction (CASP15). Our contributions are three-fold: firstly, we generate six training and evaluation datasets by employing advanced data augmentation and sampling methods. Secondly, we redesign the “zFormer” module, inspired by AlphaFold2’s Evoformer, to efficiently describe protein-ligand interactions. This module enables the extraction of protein-ligand paired features that lead to accurate predictions. Lastly, we develop the zPoseScore framework with zFormer for scoring and ranking ligand poses, allowing for atomic-level protein-ligand feature encoding and fusion to output refined ligand poses and ligand per-atom deviations. Our results demonstrate excellent performance on various testing datasets, achieving Pearson’s correlation R = 0.783 and 0.659 for ranking docking decoys generated based on experimental and predicted protein structures of CASF-2016 protein-ligand complexes. Additionally, we obtain an averaged lDDT = 0.558 of AIchemy_LIG2 in CASP15 for de novo protein-ligand complex structure predictions. Detailed analysis shows that accurate ligand binding site prediction and side-chain orientation are crucial for achieving better prediction performance. Our proposed model is one of the most accurate protein-ligand pose prediction models and could serve as a valuable tool in small molecule drug discovery.

AlphaFold has transformed structure prediction by enabling highly accurate predictions on par with experimentally determined structures. Still, for difficult cases, in particular, multimers, there is still room for improvement. Important for the success of AlphaFold is its ability to assess its own predictions. The basic idea for the Wallner group in CASP15 was to exploit the excellent ranking score in AlphaFold by massive sampling. To this end, we ran AlphaFold using six different settings, with and without templates, and with an increased number of recycles using both multimer v1 and v2 weights. In all cases, the dropout layers were enabled at inference to sample the uncertainty and increase the diversity of the generated models. A median of 4,810 models per target was generated and almost all (35/38) received a ranking_confidence >0.7. Compared to other groups in CASP15, Wallner obtained the highest sum of Z-scores based on the DockQ score, 40.8 compared to 26.3 for the second highest, much higher than -0.2 achieved by the AlphaFold baseline method, NBIS-AF2-multimer. The improvement over the baseline is substantial with the mean DockQ increasing from 0.43 to 0.56, with several targets showing a DockQ score increase by +0.6 units. Remarkable, considering Wallner and NBIS-AF2-multimer were using identical input data. The reason for the success can be attributed to the diversified sampling using dropout with different settings and, in particular, the use of multimer v1, which seems to be much more susceptible to sampling compared to v2. The method is available here: http://wallnerlab.org/AFsample/.

Background: Lympho-epithelial Kazal-type-related inhibitor (LEKTI) is a serine protease inhibitor consisting of multiple domains. A loss of function mutation is described in Netherton patients that show severe symptoms of atopic lesions and itch. Objectives: LEKTI domain 6 (LD6) has shown strong serine protease-inhibitory action in in vitro assays and thus it was tested in vitro and in vivo for potential anti-inflammatory action in models of atopic skin disease. Methods: Human skin equivalents were treated with LD6 and an inflammatory reaction was challenged by kallikrein-related endopeptidase 5 (KLK5). Furthermore, LD6 was tested on dorsal root ganglia cells stimulated with KLK5, SLIGRL and histamine by calcium imaging. The effect of topically administered LD6 (0.4–0.8 %) in lipoderm was compared to a topical formulation of betamethasone-diproprionate (0.5 %) in a therapeutic setting on atopic dermatitis-like lesions in NC/Nga mice sensitized to house dust mite antigen. Endpoints were clinical scoring of the mice as well as determination of scratching behaviour. Results: KLK5 induced an upregulation of CXCL-8, CCL20 and IL-6 in skin equivalents. This upregulation was reduced by pre-incubation with LD6. KLK5 as well as histamine induced calcium influx in a population of neurons. LD6 significantly reduced the calcium response to both stimuli. When administered onto lesional skin of NC/Nga mice, both LD6 and betamethasone-dipropionate significantly reduced the inflammatory reaction. The effect on itch behaviour was less pronounced. Conclusions: Topical administration of LD6 might be new therapeutic option for treatment of lesional atopic skin.

Rare Presentation of Papillary Thyroid CancerMahfujul Z. Haque, BS1Michael Burcescu, MD2Zirak Sajjad, BS11Michigan State University College of Human Medicine, Grand Rapids, MI, USA2Detroit Medical Center, Detroit, MI, USAWord Count: 444Table/Figure Count: 4Reference Count: 4Acknowledgements: N/AFunding Sources: NoneConflicts of Interest: NoneConsent Statement: N/ACorresponding author:Mahfujul Haque15 Michigan St NE,Grand Rapids, MI 49503Email: haquema4@msu.eduWritten informed consent was obtained from the patient to publish this report in accordance with the journal’s patient consent policy.Key Words: papillary thyroid cancer, thyroid nodule, neoplasm, endocrine cancerArticle Type: Case ImageThe patient is a 51-year-old African American female with incidental thyroid nodules identified on MRI of the cervical spine. Patient describes a tender palpable right thyroid nodule but is otherwise asymptomatic. There is no history of tobacco use or toxic occupational exposure. There is no palpable neck mass. Thyroid panel was within normal limits. The majority of parathyroid adenomas are located adjacent and posterior or just inferior to the thyroid gland. Rarely, an intrathyroidal ectopic parathyroid gland may become adenomatous and mimic thyroid nodule. When it does, it is usually homogenously hypoechoic to thyroid tissue and may demonstrate a peripheral rim of hyper-vascularity. Here we describe the case of an incidental nodule with irregular margins and punctate echogenic foci consistent with a TI-RADS 5 nodule and suggestive of malignancy.Fine needle aspiration biopsy of right upper thyroid nodule showed moderately cellular with cohesive groups as sheets and singly scattered cells exhibiting nuclear grooves, powdery chromatin, irregular nuclear outlines. A few intranuclear pseudo-inclusions are seen with some colloids in the background. True papillae, psammoma bodies, and necrosis were not detectable despite sampling with 3 adequate passes.Figure 1A is an axial T1 that demonstrates an unexpected nodule of the right thyroid lobe after gadolinium administration.Figure 1B demonstrates the same nodule with a traditional T1 view. Figure 1C demonstrates a T2 hyper intensive nodularity of the right thyroid lobe. Figure 2A demonstrates a long-axis ultrasound image of the right thyroid lobe revealed a 1.5 x 1.0 x 1.3 cm hypoechoic solid nodule with irregular margins, punctate echogenic foci, and mildly increased vascularity on color Doppler investigation.Figure 2B demonstrates a transverse ultrasound image of the right thyroid lobe showed a 1.5 x 1.0 x 1.3 cm hypoechoic solid nodule with irregular margins and punctate echogenic foci. Figure 3Ademonstrates a longitudinal-axis ultrasound image of the right thyroid lobe with a slight enlargement of the nodule, measuring 1.5 x 1.2 x 1.3 cm, with hypoechoic wider than tall features, irregular margins, and punctate echogenic foci, which are consistent with the previous sonographic evaluation. Figure 3B demonstrates a longitudinal-axis color Doppler image of the right thyroid lobe reveals increased vascularity within the thyroid nodule, indicating heightened blood flow to the nodule. Figure 4A demonstrates a Longitudinal-axis ultrasound image of the right thyroid lobe with further nodule enlargement to 1.9 x 1.3 x 0.9 cm.Studies report that 5-15% of all detected thyroid nodules and up to 11% of incidental thyroid nodules, represent malignancy [2]. The SEER database reports the USA incidence of thyroid carcinoma to be 14.9 per 100,000 with a 1:2.8 male to female predilection [3]. Papillary thyroid cancer (PTC), a common endocrine tumor originating from thyroid follicular cells, represents 85% of thyroid malignancy [1]. PTC is invasive and known to metastasize to adjacent structures including: lungs, mediastinal lymph nodes, and bone. Well-established risk factors for thyroid cancer include radiation exposure, family history of thyroid cancer, occupational exposure, and obesity [1].PTC is associated with favorable mortality of 11-17% and a low recurrence rate of 5-15% [1][4]. Extra-thyroidal growth, larger tumor size, and older age at diagnosis detrimentally impact outcome [1]. The primary treatment for PTC is surgical. Preprocedural considerations include tumor size, metastases, extra-thyroidal extension, and airway compromise. Patients with unifocal PTC, measuring > 4 cm, are candidates for thyroid lobectomy [1][5]. For larger lesions, total or near-total thyroidectomy is often required [1][5]. Ablation with radioactive iodine (RAI) is recommended for patients with residual tumor or metastasis. Additional considerations include patient age, microvascular invasion, and histologic subtyping [1]. RAI is performed 4 - 6 weeks following excision and repeated until residual radiotracer uptake is eliminated [1]. Successful intervention results in decreased serum thyroglobulin within 4 - 6 weeks. Thyroid hormone supplementation reduces tumor stimulation by suppressing TSH production [1]. Sonographic and biochemical recurrence monitoring are typically performed at 6-12 month intervals for at least 5 years.

Donkey milk as a possible alternative for cow’s milk allergic patients

Comment on: Viral infections in pediatric brain tumor patients treated with targeted therapiesAimen Waqar KhanDepartment of Medicine, Jinnah Sindh Medical University, Karachi, PakistanDear Dr. Newburger,We have read with great enthusiasm the article titled Viral infections in pediatric brain tumor patients treated with targeted therapies by Lisa Mayr et al [1]. We commend the authors’ efforts in collating epidemiologic data and investigating infectious outcomes between pediatric patients being treated with targeted therapy versus conventional therapies. It was a pleasure to read such a well-written paper. We concur with the conclusion that patients receiving targeted therapies are made more susceptible to developing viral infections than those receiving conventional treatment. However, we would like to draw attention to some key points regarding the study following a thorough appraisal.To begin with, the retrospective nature of the study adds several unavoidable biases such as recollection bias and incorrect data retrieval, which may have been mitigated had the investigators included current cases at the time. The study is also limited in its single-centered scope making it difficult to generalize the findings to this particular pediatric demographic. Moreover, the comparison between the two subsets of brain tumor patients is also subject to several partialities. For instance, it is noted that those receiving targeted therapies were managed in an outpatient setting and by extension, exposed to greater environmental stressors than those being managed on conventional chemotherapy. As a result, a greater proportion of virological infections were reported in children receiving targeted therapy than those being managed conventionally. Further, due to the lack of available data correlating disease severity with treatment option, the possibility that patients receiving conventional chemotherapy simply had a lower disease grade than those on targeted therapies and vice versa exists. Knowing this is pertinent as the body’s ability to fight off infections is greatly influenced by the grade of cancer and hence degree of inflammation [2]. Next, it remains to be seen what the baseline nutritional status of the participants was as nutrition and metabolism are known to have a bearing on immune status and hence infectious susceptibility [3]. Finally, the deduction that patients treated with bevacizumab or mTOR (mechanistic target of rapamycin) inhibitors suffered more infections than those treated with other targeted therapeutic drugs cannot be made with certainty as not enough patients were treated with drugs other than bevacizumab or mTOR inhibitors for a fair and accurate comparison.In conclusion, multi-centered prospective studies are required to better lay claims regarding infectious outcomes and attention to potential influencers of immunity must be given to minimize bias in future studies.

This study provides a novel resume parsing solution using a hybrid Spacy Transformer BERT and Spacy NLP methodology. The main goal is to create a resume parser that can efficiently extract pertinent data from unstructured resumes that do not adhere to a predetermined resume structure and may contain information presented in a non-standardized manner. We also intend to investigate the usage of video resumes as a fresh source of candidate data and put forth a cutting-edge method for video resume parsing that combines visual and audio processing methods. We employed a hybrid methodology of Spacy Transformer BERT and Spacy NLP to accomplish these goals. A pre-trained deep learning model called Spacy Transformer BERT captures the text's semantic meaning, and Spacy NLP employs natural language processing to glean pertinent information from it. Our method combines the strengths of the two models for high accuracy and efficiency in collecting pertinent information from resumes. Using a dataset of resumes, we ran experiments to gauge how well our suggested system performed. The outcomes demonstrate that our system was highly accurate in retrieving pertinent data, including candidate names, contact information, qualifications, work experience, and other pertinent characteristics.

ABSTRACT INTRODUCTION There is scarce information about the usefulness and prognostic value of left ventriculo-arterial coupling (VAC) in the context of acute coronary syndromes. In addition, there is a paucity of data of its use in late presenters with STEMI (12-72 hours after symptom onset). OBJETIVES In this retrospective study, we investigated the association of altered VAC with in-hospital mortality in late presenters with STEMI. Additionally, we studied the association between VAC and multiple clinical, biochemical, echocardiographic, and angiographic variables. METHODS 74 hemodynamically stable late presenters with STEMI were included. Mean age was 61.7±10.7 years, 85.1% were male. Mean LVEF was 42.8±11.3 %. VAC was estimated using transthoracic echocardiography with the single-beat method before coronary angiography. The sample was divided into two groups: 1) Patients with normal VAC (<1.36) and 2) Patients with altered VAC (>1.36). A statistically significant difference was found in the left ventricular ejection fraction (LVEF) (44.4±10.9% vs 36.2±11%, p=0.014), and in the blood urea nitrogen (BUN) level (19.45±8.00 mg/dL vs 25.45±10.40 mg/dL, p=0.02) between both groups. No statistically significant differences were found in other variables, including in-hospital mortality. CONCLUSION A higher VAC value was found (i.e., ventriculo-arterial uncoupling) in late presenters with lower LVEF and higher BUN level. No significant differences in in-hospital mortality were found. VAC may be used with point-of-care ultrasound as an approximate estimation of left ventricular systolic function in patients with late presentation STEMI, as it correlates with LVEF but is less operator-dependent. Larger studies are needed to confirm these findings.

Formic acid (FA) is an ideal carrier for hydrogen (H2) and carbon monoxide (CO). Thus, photocatalytic reforming of FA is considered a promising energy conversion method for producing solar fuels and valuable chemical feedstocks to achieve the carbon-neutral goal. However, the application of FA photocatalytic reforming has been restricted by the low efficiency and relatively fixed selectivity due to limited knowledge about the reaction mechanism. Herein, we show 1D CdS/2D W2N3 heterojunction as an efficient photocatalyst for photoreforming of FA with tunable selectivity to realize the conversion of products from H2 to syngas under simulated sunlight. Widely tunable CO:H2 ratios between 0 and 2.18 along with a record-high apparent quantum yield (AQY) of 61.00% (H2) and 76.84% (syngas) at 420 nm have been demonstrated. Both theoretical investigation and experimental results show that intrinsic N vacancies and spatially separated active sites are vital factors in achieving tunable selectivity. This work provides a brand-new strategy and insightful information to construct a noble-metal-free photocatalytic system for efficiently reforming of FA with tunable selectivity.

Crossed pulmonary arteries (CPA) is a rare abnormality in which the ostium of the left pulmonary artery is located rightward and the ostium of the right pulmonary artery is leftward. CPA has been reported only once at prenatal period and has not been associated with CHARGE syndrome as yet. Prenatally left pulmonary artery was seen to pass beneath the ductus and directing towards the left side and pulmonary artery bifurcation could not be demonstrated at the same plane. Postnatal echocardiography reconfirmed the presence of CPA. Bilateral choanal atresia, genital hypoplasia, hearing loss with facial and external ear asymmetry and psychomotor retardation of the newborn led to clinical diagnosis of CHARGE syndrome and was confirmed by gene analysis.

Objectives (i) Estimate the proportion of non-registered prenatal ultrasound examinations; (ii) Examine associations between non-registered ultrasound examinations and adverse perinatal outcomes, by migrant-related factors, in women giving birth in Norway. Design A national population-based study. Setting and sample Individually linked data from the Medical Birth Registry of Norway and Statistics Norway, 1999-2016, comprising 999,760 singleton pregnancies to immigrants ( n = 196,220) and non-immigrants ( n = 803,540). Methods Crude and adjusted odds ratios (aOR) with 95% confidence intervals (CI) were estimated using logistic regression with robust standard error estimations, adjusted for year of childbirth, maternal age, parity, maternal smoking during pregnancy, educational level, and Norwegian health region at birth. Main outcome measures Prenatal ultrasound examinations; perinatal mortality; placental abruption; preeclampsia. Results Compared to non-immigrants, immigrant women had a higher proportion of non-registered ultrasound examinations (2.3% vs. 4.3% respectively). Compared to women with ultrasound examination, the aOR for perinatal mortality for women with non-registered ultrasound was 2.27 [95% CI 1.85, 2.79] for immigrants and 3.61 [3.21, 4.07] for non-immigrants. Non-registered ultrasound examination was also associated with placental abruption (aOR 1.32 [1.08, 1.63]) for non-immigrant women, but not for immigrant women. Non-registered ultrasound examination was not associated with preeclampsia in either immigrant or non-immigrant women. Conclusion Compared to non-immigrants, immigrant women have a higher proportion of non-registered data on prenatal ultrasound examinations. Both immigrants and non-immigrants with non-registered ultrasound examinations have an increased aOR of perinatal mortality, but no association was found for preeclampsia. Non-immigrant women had an increased aOR for placental abruption.

The multi-scale flexibility coordination of multiple storages is a key technology to enhance the diversified regulation ability of the power system.This paper first considered the interaction mechanism of multi-type storage peak regulation time sequences based on the Euclidian distance, Dynamic time warping distance, and storage correlation distance. A matching index was proposed to consider the temporal correlation, overall distribution characteristics, and dynamic characteristics of the net load and energy storage. The multitype storage coordination mode, including battery storage, pumped storage, and electric vehicles, was formulated, and a collaborative optimal scheduling system architecture of source-grid-load-storage (SGLS) was constructed. To attain a low-carbon economy, a collaborative optimal scheduling model of SGLS considering the dynamic time-series complementarity of multiple energy storage systems was constructed. The Nash equilibrium theory was used to achieve friendly interaction among the source, grid, load, and storage. Then, an improved transfer reinforcement learning algorithm for SGLS was proposed, which used reinforcement learning and transfer learning algorithms combined with K-means clustering and dual-structure experience pool technology. The test results of actual regional power grid data indicated that the proposed strategy can effectively reduce the economic and carbon treatment costs of the system and improve the absorption capacity of renewable energy.

Recurrent right atrial tumor? evoking a leiomyomatosis. A case report.

With the large-scale development of drugs, understanding the drug phase behaviors in complex systems become increasingly important. Among them, the solubility of drugs in biorelevant media needs to be urgently understood. To address this challenge, new strategies based on machine learning models are proposed. First, the strategy trains five machine learning models based on fifteen molecular descriptors of the drug molecular properties. The XGboost model was identified as the best predictive model for predicting drug solubility performance in various solvents. Next, the input feature vectors were expanded for machine learning using the MACCS chemical fingerprint coupled with the XGboost model. The MACCS chemical fingerprint coupled with the XGboost model has significantly improved the prediction accuracy of drug solubility. This finding demonstrates that the proposed strategy has solubility prediction capability, which is expected to provide valid information for drug development and drug solvent screening.

IntroductionVasculitis is an inflammatory disease with variable end-organ damage that is classified based on involvement of small, medium or large vessels.1 Leukocytoclastic vasculitis is a small-vessel vasculitis predominantly affecting dermal capillaries and venules, and often secondary to underlying systemic vasculitis, infection or drug exposure.1 Commonly implicated drugs include beta-lactam antibiotics and non-steroidal anti-inflammatory drugs,1 while calcium channel blockers and hydroxymethylglutaryl-coA reductase inhibitors (statins) have been rarely associated2-6 – with no previous formal case report for verapamil. We present a case of cutaneous leukocytoclastic vasculitis associated with recently initiated verapamil and atorvastatin.

Title: Outcome of PML-RARα Short Isoform and FLT3-ITD in a Patient with Several Adverse Prognostic Markers: a Case ReportMohammed A Bafail1, Rahaf AlTahan1Manar A Samman1, Suha A Tashkandi1, Ibraheem H Motabi2 , Abdul Ali Peer-Zada1*