Miracle-dz/UniFAR-FTUs huggingface dataset:
Laparoscopic Trans-Abdominal Right Adrenalectomy for a Large Primitive Adrenal Oncocytic Carcinoma: A Case Report and Review of Literature

Patient: Male, 48 Final Diagnosis: Adrenal oncocytic carcinoma Symptoms: Asymptomatic Medication: — Clinical Procedure: Transabdominal laparoscopic right adrenalectomy Specialty: Surgery Objective: Rare disease Background: Adrenocortical oncocytic neoplasms (AONs) are extremely rare tumors. AONs are classified as: oncocytoma (AO), oncocytic neoplasm of uncertain malignant potential (AONUMP), and oncocytic carcinoma (AOC). Among the 162 reported cases of AONs in the literature, 30 cases were classified as malignant. Adrenalectomy is the treatment of choice for AON. Case Report: We report the case of a 48-year-old man with a primitive 12-cm mass affecting the right adrenal gland, detected by ultrasonography during follow-up for alcoholic liver cirrhosis. Computed tomography (CT) scan and magnetic resonance imaging (MRI) showed a mass of the right adrenal gland compressing the inferior vena cava (IVC) and dislocating the right lobe of the liver, with no invasion of kidney, liver, or IVC. Preoperative blood tests showed mild transaminase increase. Laparoscopic right adrenalectomy with lateral transperitoneal approach was performed. The postoperative course was uneventful. The lesion was diagnosed as a primitive adrenal oncocytic carcinoma (AOC). No recurrence was evidenced during 24-month follow-up. Conclusions: Although AONs are very rare, they must be considered in the differential diagnosis of adrenal masses due to their prognostic difference compared to non-oncocytic tumors. AOCs are a rare presentation of AONs. Only 30 cases are described in the literature. Laparotomic adrenalectomy is the treatment of choice for AOC. We report the first case of laparoscopic lateral trans-abdominal adrenalectomy for a voluminous AOC (120×95×110 mm) and we review the literature regarding AOCs. Laparoscopy in experienced hands is safe and effective for the treatment of AONs. Despite the rarity of AOC, a case series should be performed to confirm the results of our case report.
Doug Altman's legacy to Cochrane and evidence synthesis.

It is hard to find an area of medicine or health research where the initiatives Doug Altman instigated and championed have not had an influence. Doug was a man on several missions: advocating statistical peer review to reduce statistical errors in medical journals; improving doctors’ and health researchers’ understanding of statistics and research design through thoughtful teaching; writing accessible and well-used statistical notes; producing a major medical statistics textbook; advocating a focus on estimating effects and confidence intervals rather than hypothesis testing; and providing numerous templates and guidelines to educate journals and researchers as to how they should report their studies. [1][2][3][4][5][6] Doug was one of the leaders of the COMET Initiative, promoting the development of core outcome sets to be measured and reported in all randomized trials of a specific condition, making it easier for the results of trials to be compared, contrasted, and combined as appropriate. [7] He also pushed for the development of reviews for prognostic research. His dedication to his work continued until a few days before he died.
Effect of natural curcuminoids‐intercalated layered double hydroxide nanohybrid against Staphylococcus aureus, Pseudomonas aeruginosa, and Enterococcus faecalis: A bactericidal, antibiofilm, and mechanistic study

The study aimed to determine the antibacterial/antibiofilm effect and mechanism of interaction of curcuminoids‐intercalated Mg/Al layered double hydroxide (curcuminoids‐LDH) against three different bacteria. Antimicrobial effect of curcuminoids‐LDH nanohybrid was investigated against P. aeruginosa, S. aureus, and E. faecalis (for both standard strains and clinical isolates), using agar well diffusion method. Minimum inhibitory concentrations (MIC) of planktonic bacteria were determined using the broth microdilution method. MIC of biofilms (MBIC50) and killing time for 48 hr matured biofilms were determined by MTT (3‐(4,5‐Dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide) assay. Scanning electron microscopy (SEM) was used to determine pre‐ and postexposure architecture of biofilms. The mechanism of the antibiofilm activity of curcuminoids‐LDH was determined using UV‐visible spectroscopy. All tested bacteria had given a zone of inhibition in the presence of curcuminoids‐LDH. The MIC values were 0.200 g/ml for P. aeruginosa, 0.025 g/ml for S. aureus, and 0.100 g/ml for E. faecalis. The 48 hr matured biofilms were reduced by curcuminoids‐LDH with an MBIC50 of 0.100 g/ml. The minimum time to achieve MBIC50 was 3 hr, and the reduction was constant until 48 hr. SEM images showed a significant reduction of biofilm cell density and exopolymer matrics for all biofilms in the presence of curcuminoids‐LDH. UV‐visible studies revealed the antibiofilm activity of curcuminoids‐LDH as due to the auto‐oxidation of curcuminoids. The oxidation products are more limited in both product concentration per unit time and the variety of products, compared to pure curcuminoids, resulting in sharper UV‐visible peaks than in the case of the latter. Curcuminoids‐LDH has a potential antibacterial activity against P. aeruginosa, S. aureus, and E. faecalis. An antibiofilm activity has been achieved within 3 hr of the treatment. Curcuminoids released from the LDH showed the antibacterial activity due to oxidation products interfering with bacterial cell functions, and also encapsulation in the LDH causes curcuminoids to exhibit the activity in a persistent manner compared to pure curcuminoids.
New Food and Drug Administration–Approved and Emerging Novel Treatment Options for Acute Myeloid Leukemia

Advancements in the treatment of acute myeloid leukemia (AML) have been sparse during the past several decades, and the disease continues to have a poor prognosis. However, in 2017 alone, four new medications approved by the U.S. Food and Drug Administration (FDA) for the treatment of AML reached the market. Midostaurin, liposomal cytarabine and daunorubicin, enasidenib, and gemtuzumab ogozamicin all showed benefit in respective clinical trials to gain approval for the treatment of AML in various patient populations. Additionally, many phase II and III clinical trials are currently ongoing to assess the safety and efficacy of other potential therapies for the treatment of AML. In this review, we summarize the results of the landmark clinical trials associated with the newly approved agents as well as the current ongoing clinical trials for the treatment of AML. A literature search was performed to retrieve data on agents currently being studied for use. Although the overall prognosis for patients with AML remains poor, the addition of the newly FDA‐approved medications is a step in the right direction for a disease state that has proved difficult to treat.
Golimumab in the treatment of psoriatic arthritis

ABSTRACT Introduction: Psoriatic arthritis (PsA) is an inflammatory arthritis that can be aggressive and destructive, resulting in significant morbidity. While many new agents have been approved for the treatment of PsA over the past decade, TNF inhibitors (TNFi)remain an anchor treatment, in part based on extensive clinical experience. Recently, the TNFi golimumab was approved for intravenous use in PsA. Areas covered: This expert review presents an overview of the currently available treatment options for PsA with a focus on the evidence from clinical trials supporting the use of golimumab in PsA. This information is placed in context with recent advances in the understanding of PsA pathogenesis and treatment. Expert commentary: The rapid growth of treatment options available for PsA has brought the prospect of personalized treatment selection closer to reality but improved understanding of the domains of PsA and new biomarkers may be needed before such changes reach the clinic. Until patients who are most likely to benefit from a given agent can be identified and then treated accordingly, TNFi will likely remain a central option and their further development, such as the introduction of an intravenous form of golimumab, remains an important part of treatment improvement.
Comments on “SCLPV: Secure Certificateless Public Verification for Cloud-Based Cyber-Physical-Social Systems Against Malicious Auditors”

With the development of cloud storage, how to protect the integrity of the data stored in the cloud becomes the clients’ major concern. Recently, Zhang et al. proposed a certificateless data integrity auditing scheme for cloud-assisted cyber-physical-social systems. However, we find that their scheme has some security flaws, i.e., if a client outsources a file with <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> blocks data and tags, the cloud server can store only one block of them, and pass the integrity auditing of the auditor. We refer to this attack as storing one block attack. Then, we give an improved scheme to amend these flaws.
Enhanced Optic Disk and Cup Segmentation with Glaucoma Screening from Fundus Images using Position encoded CNNs

In this manuscript, we present a robust method for glaucoma screening from fundus images using an ensemble of convolutional neural networks (CNNs). The pipeline comprises of first segmenting the optic disk and optic cup from the fundus image, then extracting a patch centered around the optic disk and subsequently feeding to the classification network to differentiate the image as diseased or healthy. In the segmentation network, apart from the image, we make use of spatial co-ordinate (X \& Y) space so as to learn the structure of interest better. The classification network is composed of a DenseNet201 and a ResNet18 which were pre-trained on a large cohort of natural images. On the REFUGE validation data (n=400), the segmentation network achieved a dice score of 0.88 and 0.64 for optic disc and optic cup respectively. For the tasking differentiating images affected with glaucoma from healthy images, the area under the ROC curve was observed to be 0.85.
Applying a cognitive‐emotional model to nonsuicidal self‐injury

The recently proposed cognitive-emotional model of nonsuicidal self-injury (NSSI) draws on emotion regulation models and social cognitive theory to understand the onset, maintenance, and cessation of NSSI. We tested the prediction of the model that the relationship between emotional reactivity and NSSI is moderated by specific cognitions about self-injury (i.e., self-efficacy to resist NSSI, NSSI outcome expectancies), emotion regulation, and rumination. A sample of 647 university students aged 17-25 years (M = 19.92, SD = 1.78) completed self-report measures of the constructs of interest. As expected, we found that emotional reactivity was positively related to NSSI, particularly for people who had weak self-efficacy to resist NSSI. However, emotional reactivity was negatively related to NSSI for people who were more likely to use expressive suppression to regulate emotion. Implications for the theoretical understanding of NSSI are discussed.
Reverse-engineering of graphene on metal surfaces: a case study of embedded ruthenium

Using scanning tunneling microscopy, x-ray photoelectron spectroscopy, and x-ray absorption spectroscopy, we show that Ru forms metallic nanoislands on graphite, covered by a graphene monolayer. These islands are air-stable, contain 2–4 layers of Ru, and have diameters on the order of 10 nm. To produce these nanoislands two conditions must be met during synthesis. The graphite surface must be ion-bombarded, and subsequently held at an elevated temperature (1000–1180 K) during Ru deposition. A coincidence lattice forms between the graphene overlayer and the Ru island top. Its characteristics—coincidence lattice constant, corrugation amplitude, and variation of carbon lattice appearance within the unit cell—closely resemble the well-established characteristics of single-layer graphene on the (0001) surface of bulk Ru. Quantitative analysis of the graphene lattice in relation to the coincidence lattice on the island tops show that the two-dimensional lattice constant of the underlying metal equals that of bulk Ru(0001), within experimental error. The embedded Ru islands are energetically favored over on-top (adsorbed) islands, based on density-functional-theory calculations for Ru films with 1–3 Ru layers. We propose a formation mechanism in which Ru atoms intercalate via defects that act as entry portals to the carbon galleries, followed by nucleation and growth in the galleries. In this model, high deposition temperature is necessary to prevent blockage of entry portals.
Suppression of long noncoding RNA NCK1‐AS1 increases chemosensitivity to cisplatin in cervical cancer

Cervical cancer remains a serious health problem till now, with nearly 500,000 women cases diagnosed each year around the world. Long noncoding RNA (lncRNA) is a novel class of RNA transcripts (>200 nucleotides in length) participating in gene transcription, cell proliferation, differentiation, and drug resistance. This study aimed to explore the regulatory relationship among lncRNA NCK1‐AS1, miR‐134‐5p, and MutS protein homolog 2 (MSH2), so that the resistance against cisplatin in cervical cancer treatment could be better understood. Comprehensive lncRNA profiling analysis was performed to screen lncRNAs differentially expressed in cervical cancer. The expression patterns of miR‐134‐5p, NCK1‐AS1, and MSH2 were evaluated in cancerous tissues and adjacent normal tissues obtained from 75 cervical cancer patients. Subsequently, anti‐NCK1‐AS1 small interfering RNA, miR‐134‐5p mimics, and miR‐134‐5p inhibitors were transfected into cervical cancer cells, and the effects of these transcripts on cisplatin resistance and cell apoptosis were investigated. The regulatory relationship among NCK1‐AS1, miR‐134‐5p, and MSH2 was identified using a dual‐luciferase reporter gene assay, and the results were further validated by RNA pull‐down and RNA immunoprecipitation assays. Based on the microarray data of GSE63514 and GSE27678, NCK1‐AS1 was upregulated in cervical cancer. Increased expression of NCK1‐AS1, MSH2, and decreased expression of miR‐134‐5p were observed in cervical cancer tissues. In addition, NCK1‐AS1 competitively bound to miR‐134‐5p to regulate MSH2. Therefore, si‐NCK1‐AS1 and miR‐134‐5p mimic both reduced MSH2 activity and increased cisplatin‐induced apoptosis in cervical cancer cells. Taken together, NCK1‐AS1 may become a novel target in improving the chemotherapeutic response and survival of cervical cancer patients.
Hardware-Aware Machine Learning: Modeling and Optimization

Recent breakthroughs in Machine Learning (ML) applications, and especially in Deep Learning (DL), have made DL models a key component in almost every modern computing system. The increased popularity of DL applications deployed on a wide-spectrum of platforms (from mobile devices to datacenters) have resulted in a plethora of design challenges related to the constraints introduced by the hardware itself. “What is the latency or energy cost for an inference made by a Deep Neural Network (DNN)? ” “Is it possible to predict this latency or energy consumption before a model is even trained? ” “If yes, how can machine learners take advantage of these models to design the hardware-optimal DNN for deployment? ” From lengthening battery life of mobile devices to reducing the runtime requirements of DL models executing in the cloud, the answers to these questions have drawn significant attention. One cannot optimize what isn't properly modeled. Therefore, it is important to understand the hardware efficiency of DL models during serving for making an inference, before even training the model. This key observation has motivated the use of predictive models to capture the hardware performance or energy efficiency of ML applications. Furthermore, ML practitioners are currently challenged with the task of designing the DNN model, i.e., of tuning the hyper-parameters of the DNN architecture, while optimizing for both accuracy of the DL model and its hardware efficiency. Therefore, state-of-the-art methodologies have proposed hardware-aware hyper-parameter optimization techniques. In this paper, we provide a comprehensive assessment of state-of-the-art work and selected results on the hardware-aware modeling and optimization for ML applications. We also highlight several open questions that are poised to give rise to novel hardware-aware designs in the next few years, as DL applications continue to significantly impact associated hardware systems and platforms.
Pediatric sickle cell disease and obstructive sleep apnea: A cross-sectional study in a tertiary pediatric center in Saudi Arabia

Objective: The aim of the study was to evaluate snoring and obstructive sleep apnea (OSA) in Saudi children with sickle cell disease (SCD). Materials and Methods: This cross-sectional study was conducted among children with SCD attending a hematology clinic were recruited. Demographics, clinical data, and sleep questionnaires were collected and overnight polysomnographies performed. Results: Seventy children (31 of whom were females) with SCD were included in the study. Their median (interquartile) age was 9 (6.5, 11) years and their body mass index z-score was −1.2 (−2.0, −0.4). Seventy-four percent of SCD patients snored and 32 (46%) had evidence of OSA (obstructive apnea-hypopnea index [OAHI] ≥2 events per hour of sleep), 13 of whom had moderate OSA (OAHI ≥5 and <10 events per hour of sleep) and 10 had severe OSA (OAHI ≥10 events per hour of sleep). Conclusion: Snoring and the proportion of OSA were high in children with SCD. This underlines the importance of screening for OSA in all children with SCD.
A combined compression molding, heating, and leaching process for fabrication of micro-porous poly(ε-caprolactone) scaffolds

Abstract Biomaterial scaffolds have been increasingly used for tissue engineering applications as well as three dimensional (3D) cell culture models. Herein, we report a simple procedure combining compression molding, heating, and leaching methods for the fabrication of 3D micro-porous poly(ε-caprolactone) (PCL) biomaterial scaffolds. In this procedure, PCL micro particles are mixed with NaCl of defined sizes and compression molded, followed by heating and subsequent leaching of NaCl particles. This technique eliminates the gas foaming method, which is commonly used in the fabrication of PCL scaffolds. Process and scaffold parameters (i.e., heating time, NaCl concentration, and NaCl particle size) were varied and analyzed to determine their impact on the overall scaffold structural and mechanical properties. An increase in NaCl particle size led to an increase in pore area but did not significantly impact the mechanical properties of the scaffolds. Additionally, NaCl concentration did not show a significant effect on pore area, but considerably impacted the mechanical properties, water absorption capacity and porosity of the scaffolds. Variations in the heating time did not have an effect in the pore area, porosity, water absorption capacity or mechanical properties of the scaffolds. We also demonstrated the ability of these scaffolds to support the proliferation of breast cancer cells. Overall, these results elucidated structure-property relationships in the fabricated micro-porous PCL scaffolds. Further, this procedure could be potentially scaled up for the fabrication of micro-porous PCL scaffolds.
Fast Iterative Combinatorial Auctions via Bayesian Learning

Iterative combinatorial auctions (CAs) are often used in multibillion dollar domains like spectrum auctions, and speed of convergence is one of the crucial factors behind the choice of a specific design for practical applications. To achieve fast convergence, current CAs require careful tuning of the price update rule to balance convergence speed and allocative efficiency. Brero and Lahaie (2018) recently introduced a Bayesian iterative auction design for settings with singleminded bidders. The Bayesian approach allowed them to incorporate prior knowledge into the price update algorithm, reducing the number of rounds to convergence with minimal parameter tuning. In this paper, we generalize their work to settings with no restrictions on bidder valuations. We introduce a new Bayesian CA design for this general setting which uses Monte Carlo Expectation Maximization to update prices at each round of the auction. We evaluate our approach via simulations on CATS instances. Our results show that our Bayesian CA outperforms even a highly optimized benchmark in terms of clearing percentage and convergence speed.
Evaluation of the effectiveness of mobile diabetes management system with social networking and cognitive behavioural therapy (CBT) for T2D.

Background In the Saudi Arabia region there are no previous studies related to the use of social networks combined with the management of mobile diabetes. In this sense, the aim of this feasibility investigation is to evaluate the application and utility of the SANAD system (Saudi Arabia Networking for Aiding Diabetes) to support Saudi type 2 diabetes adult patients. Methods Twenty patients from a clinic in Saudi Arabia-Dammam were recruited to use the SANAD system. The study design was a randomized controlled trial (RCT) with two groups: an intervention group using SANAD system and a control group using conventional diabetes treatment. Glycated hemoglobin (HbA1c), diabetes knowledge test (DKT) and Self-efficacy Scale (SES) were documented. Results Nineteen patients completed the study. Mean baseline HbA1c (%) was 8.14 (SD 1.20) and decreased to 7.54 (SD 0.96) after the SANAD intervention process [mean (SEM) decrease 0.600 (0.102)]. A paired-samples t-test showed this change to be significant (P=0.000). Linear regression analyzed each study group separately, and revealed that age significantly predicted change in HbA1c (%) in the intervention group, with older age (i.e., 41-50 years) associated with higher HbA1c (%) at 6 months, as compared with baseline values (β=0.865, t=3.67, P<0.05). The mean diabetes knowledge score prior to the intervention (baseline) was 12.11 (SD 2.09), which rose to 14.56 (SD 1.59) afterward. This increase [mean (SEM), 2.44 (0.530)] was shown to be significant using the paired-samples t-test (P=0.002). Linear regression demonstrated that age, gender, and educational level were not related to increased diabetes knowledge in each study group. The mean self-efficacy score prior to the intervention (baseline) was 5.17 (SD 0.45), which rose to 6.17 (SD 0.39) afterward. This increase [mean (SEM), 0.944 (0.192)] was shown to be significant using the paired-samples t-test (P=0.001). Linear regression demonstrated that age, gender, and educational level were not related to increased self-efficacy in each study group. Conclusions This study demonstrates that using of SANAD system is acceptable, and feasible in supporting diabetes care in Saudi Arabia. This study is the first in Saudi Arabia to demonstrate similar benefits of using this technology on social diabetes and management. A national clinical trial is needed to assess precise benefits of self-care and knowledge.