Miracle-dz/UniFAR-FTUs huggingface dataset:
Radical cystectomy compared to intravesical BCG immunotherapy for high-risk non-muscle invasive bladder cancer – is there a long-term survival difference? A Swedish nationwide analysis

Abstract Objectives High-risk non-muscle invasive urinary bladder cancer (NMIBC) presents an increased risk of progression and cancer death. To reduce these risks, two different treatments are recommended – BCG or radical cystectomy (RC). The purpose of this study is to analyze cancer-specific survival of these two initial treatments. Materials and Methods BladderBaSe links information from the SNRUBC from 1997 to 2014, with a number of national healthcare and demographic registers. BCG was used for 3,862 patients (399 had delayed RC), while 687 had initial RC. Propensity scores were used to match the patients treated with RC and with relevant variables such as age, gender, and tumor stage with the same number treated with BCG (673 each arm). In a further comparison, an instrumental variable analysis using hospital strategy as the instrument was used. Results The 5-year cancer-specific survival chance was higher for the BCG group than it was for the initial RC group, 87 vs 71%, respectively. In the population with propensity score matching, 78 died from cancer in the BCG group during follow-up and 162 in the RC group. In the instrumental variable analysis, the multivariate adjusted risk difference of cancer-specific death 2 years after diagnosis was 32 per 100 treated patients, in favor of the BCG group. Conclusions BCG therapy had better cancer-specific survival than RC also when two different statistic methods were used to try to control for confounding. A prospective randomized trial will be necessary to rule out that selection is a major factor for the outcome.
Non-prescription sale of antibiotics and service quality in community pharmacies in Guangzhou, China: A simulated client method

Objective To measure the situation of the non-prescription sale of antibiotics and the service quality of community pharmacies in Guangzhou, China. Methods A simulated client method was conducted to estimate the non-prescription sale of antibiotics and service quality based on scenarios about adult acute upper respiratory tract infection in 2019. A total of 595 community pharmacies from 11 districts were investigated in Guangzhou, China. We used binary logistic regression to evaluate the factors associated with the non-prescription sale of antibiotics. Results The proportion of non-prescription dispensing of antibiotics was 63.1% in Guangzhou, China, with a higher incidence of antibiotic dispensing without prescription in outer districts (69.3%). Cephalosporin (44.1%) and Amoxicillin (39.0%) were sold more often than other antibiotics. Chain pharmacies had better performance on the prescription sale of antibiotics and service quality. Traditional Chinese medicine was commonly recommended by pharmacy staff. Conclusion Since the non-prescription sale of antibiotics is prevalent in Guangzhou, effective solutions should be determined. Strengthened public awareness and regulatory system innovation are needed.
The comparative genomic landscape of adaptive radiation in crater lake cichlid fishes

Factors ranging from ecological opportunity to genome composition might explain why only some lineages form adaptive radiations. While being rare, particular systems can provide natural experiments within an identical ecological setting where species numbers and phenotypic divergence in two closely related lineages are notably different. We investigated one such natural experiment using two de novo assembled and 40 resequenced genomes and asked why two closely related Neotropical cichlid fish lineages, the Amphilophus citrinellus species complex (Midas cichlids; radiating) and Archocentrus centrarchus (Flyer cichlid; nonradiating), have resulted in such disparate evolutionary outcomes. Although both lineages inhabit many of the same Nicaraguan lakes, whole‐genome inferred demography suggests that priority effects are not likely to be the cause of the dissimilarities. Also, genome‐wide levels of selection, transposable element dynamics, gene family expansion, major chromosomal rearrangements and the number of genes under positive selection were not markedly different between the two lineages. To more finely investigate particular subsets of the genome that have undergone adaptive divergence in Midas cichlids, we also examined if there was evidence for ‘molecular pre‐adaptation’ in regions identified by QTL mapping of repeatedly diverging adaptive traits. Although most of our analyses failed to pinpoint substantial genomic differences, we did identify functional categories containing many genes under positive selection that provide candidates for future studies on the propensity of Midas cichlids to radiate. Our results point to a disproportionate role of local, rather than genome‐wide factors underlying the propensity for these cichlid fishes to adaptively radiate.
Comprehensive Review on Alzheimer’s Disease: Causes and Treatment

Alzheimer’s disease (AD) is a disorder that causes degeneration of the cells in the brain and it is the main cause of dementia, which is characterized by a decline in thinking and independence in personal daily activities. AD is considered a multifactorial disease: two main hypotheses were proposed as a cause for AD, cholinergic and amyloid hypotheses. Additionally, several risk factors such as increasing age, genetic factors, head injuries, vascular diseases, infections, and environmental factors play a role in the disease. Currently, there are only two classes of approved drugs to treat AD, including inhibitors to cholinesterase enzyme and antagonists to N-methyl d-aspartate (NMDA), which are effective only in treating the symptoms of AD, but do not cure or prevent the disease. Nowadays, the research is focusing on understanding AD pathology by targeting several mechanisms, such as abnormal tau protein metabolism, β-amyloid, inflammatory response, and cholinergic and free radical damage, aiming to develop successful treatments that are capable of stopping or modifying the course of AD. This review discusses currently available drugs and future theories for the development of new therapies for AD, such as disease-modifying therapeutics (DMT), chaperones, and natural compounds.
Improved Glioma Grading Using Deep Convolutional Neural Networks

Convolutional neural networks are able to learn discriminating features automatically, and these features provide added value for grading gliomas. BACKGROUND AND PURPOSE: Accurate determination of glioma grade leads to improved treatment planning. The criterion standard for glioma grading is invasive tissue sampling. Recently, radiomic features have shown excellent potential in glioma-grade prediction. These features may not fully exploit the underlying information in MR images. The objective of this study was to investigate the performance of features learned by a convolutional neural network compared with standard radiomic features for grade prediction. MATERIALS AND METHODS: A total of 237 patients with gliomas were included in this study. All images were resampled, registered, skull-stripped, and segmented to extract the tumors. The learned features from the trained convolutional neural network were used for grade prediction. The performance of the proposed method was compared with standard machine learning approaches, support vector machine, random forests, and gradient boosting trained with radiomic features. RESULTS: The experimental results demonstrate that using learned features extracted from the convolutional neural network achieves an average accuracy of 87%, outperforming the methods considering radiomic features alone. The top-performing machine learning model is gradient boosting with an average accuracy of 64%. Thus, there is a 23% improvement in accuracy, and it is an efficient technique for grade prediction. CONCLUSIONS: Convolutional neural networks are able to learn discriminating features automatically, and these features provide added value for grading gliomas. The proposed framework may provide substantial improvement in glioma-grade prediction; however, further validation is needed.
Strength training protects against prostate injury in alcoholic rats

Alcoholic injury can alter the hormonal signaling pathway and lead to glucose and lipid metabolism disorders. In this study, we investigated whether the strength training could exert protective effects against the alterations caused by ethanol consumption on prostatic metabolism. A UChB, ethanol‐preferring rats were used in this study. Strength training was conducted for 3 days per week for 13 weeks, rats performed jumps in water carrying a weight load strapped to their chests as part of a strength training protocol. The reduced alcohol consumption by strength training was accompanied by increased glucose, serum lipid profile, total protein levels, and reduced hormonal levels. The results of protein expression of prostatic tissues in the ethanol‐ and strength training‐treated groups indicated that “steroidal hormone receptors,” “fatty acid translocation,” and “cell regulation” were significantly different between ethanol‐ and strength training‐treated groups. Taken together, these findings show that strength training effectively ameliorated prostatic injuries in alcoholic rats at least partially by acting on lipids receptors and steroidal hormone receptors pathway, suggesting the strength training as a potential novel therapeutic strategy for treating prostate injuries caused by ethanol.
Electromyographic responses of knee isokinetic and single-leg hop tests in athletes :dominant vs. non-dominant sides

ABSTRACT The purpose of the study is to perform the electromyographic (EMG) analysis of isokinetic and single-leg hop tests (SLHTs). We included 20 healthy male athletes (age: 23.18 years, height: 178.82 cm, weight: 73.76 kg and BMI: 47 kg/m2) voluntarily. Isokinetic knee strength tests at at 60°sec−1, 180°sec−1, 240°sec−1 velocities and different SLHTs; Single leg (SL), Triple leg (THD) and Crossover (CHD) hop for distance tests, 6 m timed-hop test (6 m THT), Single leg vertical jump test (VJ) were measured. Muscle activations of quadriceps (Q); vastus medialis (VM), vastus lateralis (VL), rectus femoris (RF) and hamstring (H); biceps femoris (BF) were obtained. There were significant differences in SL, THD, CHD and VJ in DS (p < 0.05). VJ revealed a statistical significance in NDS (p = 0.003). The comparison of the activations produced by the same muscles in different tests showed statistically significant differences in all the muscles for both sides (p < 0.05). In conclusion, we determined that the muscles produce similar activations in the isokinetic tests for both the DS and NDS, whereas there are differences in some of the SLHTs. The most active muscles were VM and RF (medial muscles) in isokinetic tests, and VL (lateral muscle) in SLHTs.g
On Attractor Detection and Optimal Control of Deterministic Generalized Asynchronous Random Boolean Networks

Deterministic asynchronous Boolean networks play a crucial role in modeling and analysis of gene regulatory networks. In this paper, we focus on a typical type of deterministic asynchronous Boolean networks called deterministic generalized asynchronous random Boolean networks (DGARBNs). We first formulate the extended state transition graph, which captures the whole dynamics of a DGARBN and paves potential ways to analyze this DGARBN. We then propose two SMT-based methods for attractor detection and optimal control of DGARBNs. These methods are implemented in a JAVA tool called DABoolNet. Two experiments are designed to highlight the scalability of the proposed methods. We also formally state and prove several relations between DGARBNs and other models including deterministic asynchronous models, block-sequential Boolean networks, generalized asynchronous random Boolean networks, and mixed-context random Boolean networks. Several case studies are presented to show the applications of our methods.
Effects of early enteral nutrition on the prognosis of patients with sepsis: secondary analysis of acute gastrointestinal injury study.

BACKGROUND The time of enteral nutrition (EN) administration on patients with sepsis is controversial. The study was to explore the effect of early enteral nutrition (EEN) on the prognosis of patients with sepsis. METHODS We performed a secondary analysis of the acute gastrointestinal injury grade study. The patients were divided into two groups from the time of EN administration: EEN group (n=85): EN within 24 hours; Control group (N=78): EN after 24 hours. The key observation was the length of ICU stay, and length of hospital stay, and 28- and 60-day mortality. RESULTS Of 676 patients, 163 were included. There are no significant between-group differences in the characteristics at baseline. The overall mortality rate at 28 days in the EEN group was 28.2% vs. 43.6% in the control group (P=0.041). The mortality rate at 60 days in the EEN group was 36.5% vs. 52.6% in the control group (P=0.039). In a subgroup analysis of patients who whether used vasoactive drugs: the EEN group was found to be significantly associated with 60-day mortality (P=0.039). The ICU stay length in the EEN group was longer than in the control group {11 [8-22] vs. 10 [6-16]; P=0.022}. Also, the length of the hospital stay was longer than in the Control group {23 [14-53] vs. 18 [10-39]; P=0.023}. Univariate Cox regression analysis showed that EEN, using vasoactive drugs, Acute kidney injury (AKI), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and the global acute gastrointestinal injury (AGI) grade were significantly (P<0.05) associated with 60-day mortality. In a multivariate analysis including these variables, EEN (HR1.68, 95% CI: 1.02-2.62; P=0.040, global AGI grade (HR2.28, 95% CI: 1.30-4.00; P=0.004), and APACHE II score (HR 1.04, 95% CI: 1.01-1.07; P=0.021) were independently associated with 60-day mortality. CONCLUSIONS EEN within 24 hours can improve the survival of patients with sepsis, and that is an independent prognostic factor.
Probabilistic Graph Attention Network With Conditional Kernels for Pixel-Wise Prediction

Multi-scale representations deeply learned via convolutional neural networks have shown tremendous importance for various pixel-level prediction problems. In this paper we present a novel approach that advances the state of the art on pixel-level prediction in a fundamental aspect, i.e. structured multi-scale features learning and fusion. In contrast to previous works directly considering multi-scale feature maps obtained from the inner layers of a primary CNN architecture, and simply fusing the features with weighted averaging or concatenation, we propose a probabilistic graph attention network structure based on a novel Attention-Gated Conditional Random Fields (AG-CRFs) model for learning and fusing multi-scale representations in a principled manner. In order to further improve the learning capacity of the network structure, we propose to exploit feature dependant conditional kernels within the deep probabilistic framework. Extensive experiments are conducted on four publicly available datasets (i.e. BSDS500, NYUD-V2, KITTI and Pascal-Context) and on three challenging pixel-wise prediction problems involving both discrete and continuous labels (i.e. monocular depth estimation, object contour prediction and semantic segmentation). Quantitative and qualitative results demonstrate the effectiveness of the proposed latent AG-CRF model and the overall probabilistic graph attention network with feature conditional kernels for structured feature learning and pixel-wise prediction.
Recovery and Characterization Studies of Post-Production Alloy Waste from the Automotive Industry

Superalloys provide high corrosion resistance and are widely used as high-performance materials in aerospace, automotive, chemical, and other industries. Herein, the investigation into the characteristics and properties of alloy waste; Inconel 625, Inconel 718, and Titanium Grade 5, from the automotive industry, was introduced as a result of a recovery in various processes. For this reason, the following procedures were carried as follows; the washing process to remove oil from the swarf was evaluated using several commercial agents and for the process of thermal disposal of processing fluids, a temperature of 900 °C was used in a muffle furnace without air access. The presented studies show that the commercially available series of washing agents did not modify the composition of the surface. However, the high temperatures during the calcination of oil residues are affecting the elemental composition of the alloys. According to the results of the analyses, it is not possible to remove 100% of the oil residues from alloy waste using washing agents based on light organic fractions; however, the effectiveness of this method reaches 99%. In this report, accurate SEM-EDS analyses show changes that occur on the surface after machining and removal of processing fluids. The NMR and GC/MS investigations indicate contaminants as a mixture of aliphatic and cycloaliphatic hydrocarbons with carbon numbers from C8–C30.
Usefulness of Muscle Synergy Analysis in Individuals With Knee Osteoarthritis During Gait

Objective: To clarify whether there are any muscle synergy changes in individuals with knee osteoarthritis, and to determine whether muscle synergy analysis could be applied to other musculoskeletal diseases. Methods: Subjects in this study included 11 young controls (YC), 10 elderly controls (EC), and 10 knee osteoarthritis patients (KOA). Gait was assessed on a split-belt treadmill at 3 km/h. A non-negative matrix factorization (NNMF) was applied to the electromyogram data matrix to extract muscle synergies. To assess the similarity of each module, we performed the NNMF analysis assuming four modules for all of the participants. Further, we calculated joint angles to compare the kinematic data between the module groups. Results: The number of muscle modules was significantly lower in the EC (2–3) and KOA (2–3) groups than in the YC group (3–4), which reflects the merging of late swing and early stance modules. The EC and KOA groups also showed greater knee flexion angles in the early stance phase. Contrarily, by focusing on the module structure, we found that the merging of early and late stance modules is characteristic in KOA. Conclusion: The lower number of modules in the EC and KOA groups was due to the muscle co-contraction with increased knee flexion angle. Contrarily, the merging of early and late stance modules are modular structures specific to KOA and may be biomarkers for detecting KOA. Significance: Describing the changes in multiple muscle control associated with musculoskeletal degeneration can serve as a fundamental biomarker in joint disease.
Temperature and oxygen level determine N2O respiration activities of heterotrophic N2O‐reducing bacteria: Biokinetic study

Nitrous oxide (N2O), a potent greenhouse gas, is reduced to N2 gas by N2O‐reducing bacteria (N2ORB), a process which represents an N2O sink in natural and engineered ecosystems. The N2O sink activity by N2ORB depends on temperature and O2 exposure, yet the specifics are not yet understood. This study explores the effects of temperature and oxygen exposure on biokinetics of pure culture N2ORB. Four N2ORB, representing either clade I type nosZ (Pseudomonas stutzeri JCM5965 and Paracoccus denitrificans NBRC102528) or clade II type nosZ (Azospira sp. strains I09 and I13), were individually tested. The higher activation energy for N2O by Azospira sp. strain I13 (114.0 ± 22.6 kJ mol−1) compared with the other tested N2ORB (38.3–60.1 kJ mol−1) indicates that N2ORB can adapt to different temperatures. The O2 inhibition constants (KI) of Azospira sp. strain I09 and Ps. stutzeri JCM5965 increased from 0.06 ± 0.05 and 0.05 ± 0.02 μmol L−1 to 0.92 ± 0.24 and 0.84 ± 0.31 μmol L−1, respectively, as the temperature increased from 15°C to 35°C, while that of Azospira sp. strain I13 was temperature‐independent (p = 0.106). Within the range of temperatures examined, Azospira sp. strain I13 had a faster recovery after O2 exposure compared with Azospira sp. strain I09 and Ps. stutzeri JCM5965 (p < 0.05). These results suggest that temperature and O2 exposure result in the growth of ecophysiologically distinct N2ORB as N2O sinks. This knowledge can help develop a suitable N2O mitigation strategy according to the physiologies of the predominant N2ORB.
A review on medical imaging synthesis using deep learning and its clinical applications

Abstract This paper reviewed the deep learning‐based studies for medical imaging synthesis and its clinical application. Specifically, we summarized the recent developments of deep learning‐based methods in inter‐ and intra‐modality image synthesis by listing and highlighting the proposed methods, study designs, and reported performances with related clinical applications on representative studies. The challenges among the reviewed studies were then summarized with discussion.
What COVID‐19 tells us about the self: The deep intersubjective and cultural layers of our brain

The COVID‐19 crisis is affecting our sense of self and touches upon our existential fears. This extends to the self–other relationship, as there is both being infected and infecting the other. What does this pandemic crisis tell us about our self and relatedness, its cultural differences, and how these are rooted in the brain's relation to the world? First, we discuss the psychological and neuronal features of self and self–other relation and how they are rooted in a deeper layer of the brain's neural activity complementing its cognitive surface layer. Second, we demonstrate cultural differences of Eastern and Western concepts of the self (i.e., independency and interdependency) and how these reflect the manifestation of the brain's neuro‐social and neuro‐ecological alignment. Finally, we highlight the intersubjective and cultural nature of the self and its surface in the COVID‐19 crisis. Discussing various lines of empirical data showing the brain's intimate alignment to both social and ecological environmental contexts, our results support the assumption of the brain's deep layer features by laying bare a continuum of different degrees of neuro‐social and neuro‐ecological alignment. This entails a two‐stage model of self with neuro‐social‐ecological and psychological levels that extends the previously suggested basis model of self‐specificity. We conclude that the current pandemic shows the importance of the deeper intersubjective and cultural layers of both the self and brain; their neglect can be life‐threatening for the self and others and, paradoxically, might reduce, rather than enlarge, the self's sense of freedom and independence.