Miracle-dz/UniFAR-FTUs huggingface dataset:
MicroRNAs and gene regulation in breast cancer

MicroRNAs (miRs) are non–protein‐coding small RNAs that control the gene expression posttranscriptionally. miRs can regulate different cellular functions as well as many pathological conditions. Dysregulated miR expression profiles have been identified in different cancer types including lung cancer, breast cancer, and prostate cancer. The expression of miRs varies according to their roles in each specific cancer type. Although many miRs and their target genes have been identified in different cancers, data are still scant to validate those target genes and the mechanistic role of these miRs. The possibility of targeting cancer‐associated miRs is suggested to open a new field for cancer therapy. Therapeutic strategies targeting miRs involve neutralization of the oncogenic miRs by antagomirs using locked nucleic acid oligonucleotides, miR sponges, or the restoration/overexpression of tumor‐suppressing miRs that are downregulated or depleted in cancers. Although it is suggested that therapeutic applications of miRs in different pathological conditions will make a huge revolution in gene therapy, there is still an enormous challenge in employing these strategies efficiently in cancer inhibition, seemingly, due to the complexity of cancer and the current inefficient development of delivery systems for the therapeutic miRs.
Pregnancy-associated arterial dissections: a nationwide cohort study.

AIMS Pregnancy is a known risk factor for arterial dissection, which can result in significant morbidity and mortality in the peripartum period. However, little is known about the risk factors, timing, distribution, and outcomes of arterial dissections associated with pregnancy. METHODS AND RESULTS We included all women ≥12 years of age with hospitalizations associated with pregnancy and/or delivery in the Nationwide Readmissions Database between 2010 and 2015. The primary outcome was any dissection during pregnancy, delivery, or the postpartum period (42-days post-delivery). Secondary outcomes included timing of dissection, location of dissection, and in-hospital mortality. Among 18 151 897 pregnant patients, 993 (0.005%) patients were diagnosed with a pregnancy-related dissection. Risk factors included older age (32.8 vs. 28.0 years), multiple gestation (3.6% vs. 1.9%), gestational diabetes (14.3% vs. 0.2%), gestational hypertension (6.0% vs. 0.6%), and pre-eclampsia/eclampsia (2.7% vs. 0.4%), in addition to traditional cardiovascular risk factors. Of the 993 patients with dissection, 150 (15.1%) dissections occurred in the antepartum period, 232 (23.4%) were diagnosed during the admission for delivery, and 611 (61.5%) were diagnosed in the postpartum period. The most common locations for dissections were coronary (38.2%), vertebral (22.9%), aortic (19.8%), and carotid (19.5%). In-hospital mortality was 3.7% among pregnant patients with a dissection vs. <0.001% in patients without a dissection. Deaths were isolated to patients with an aortic (8.6%), coronary (4.2%), or supra-aortic (<2.5%) dissection. CONCLUSION Arterial dissections occurred in 5.5/100 000 hospitalized pregnant or postpartum women, most frequently in the postpartum period, and were associated with high mortality risk. The coronary arteries were most commonly involved. Pregnancy-related dissections were associated with traditional risk factors, as well as pregnancy-specific conditions.
Contribution of Serotonin 3A Receptor to Motor Function and Its Expression in the Gastrointestinal Tract

Introduction: The serotonin 3A receptor (5-HT<sub>3A</sub>R) is involved in vomiting and gastrointestinal motility. However, it is not well understood the expression pattern of 5-HT<sub>3A</sub>R in the gut immunohistochemically and how much contribution of 5-HT<sub>3A</sub>R to upper or lower intestinal motility. Objectives: We investigated the contribution of 5-HT<sub>3A</sub>R to gastrointestinal motor function by using 5-HT<sub>3A</sub>R KO mice and sought to identify 5-HT<sub>3A</sub>R-expressing cells via immunohistochemical staining using 5-HT<sub>3A</sub>R-GFP reporter mice. Methods: The expression of 5-HT<sub>3A</sub>R was measured in each section of the gut through real-time PCR. The motor function of the stomach and colon was assessed via the <sup>13</sup>C-octanoic acid breath test and colonic bead expulsion test, respectively, using 5-HT<sub>3A</sub>R KO mice. 5-HT<sub>3A</sub>R-expressing cells in the muscle layer of the gut were identified by immunohistochemical staining using 5-HT<sub>3A</sub>R-GFP reporter mice. Results: 5-HT<sub>3A</sub>R was expressed throughout the digestive tract, and 5-HT<sub>3A</sub>R expression in the stomach and lower digestive tract was higher than that in the other sections. Motor function in the stomach and colon was lower in 5-HT<sub>3A</sub>R KO mice than in WT mice. As a result of immunohistochemical staining using GFP reporter mice, cholinergic neurons and PDGFRα<sup>+</sup> cells were shown to express 5-HT<sub>3A</sub>R. In contrast, 5-HT<sub>3A</sub>R indicated by GFP fluorescence was rarely detected in ICC and smooth muscle cells. Conclusions: These results show that 5-HT<sub>3A</sub>R is highly expressed in the stomach and large intestine and that the activation of 5-HT<sub>3A</sub>R accelerates gastric emptying and large intestine transit. Additionally, 5-HT<sub>3A</sub>R is highly expressed in cholinergic neurons and some interstitial cells, such as PDGFRα<sup>+</sup> cells.
Evolutionary Phycology: Toward a Macroalgal Species Conceptual Framework

Species concepts formalize evolutionary and ecological processes, but often conflict with one another when considering the mechanisms that ultimately lead to species delimitation. Evolutionary biologists are, however, recognizing that the conceptualization of a species is separate and distinct from the delimitation of species. Indeed, if species are generally defined as separately evolving metapopulation lineages, then characteristics, such as reproductive isolation or monophyly, can be used as evidence of lineage separation and no longer conflict with the conceptualization of a species. However, little of this discussion has addressed the formalization of this evolutionary conceptual framework for macroalgal species. This may be due to the complexity and variation found in macroalgal life cycles. While macroalgal mating system variation and patterns of hybridization and introgression have been identified, complex algal life cycles generate unique eco‐evolutionary consequences. Moreover, the discovery of frequent macroalgal cryptic speciation has not been accompanied by the study of the evolutionary ecology of those lineages, and, thus, an understanding of the mechanisms underlying such rampant speciation remain elusive. In this perspective, we aim to further the discussion and interest in species concepts and speciation processes in macroalgae. We propose a conceptual framework to enable phycological researchers and students alike to portray these processes in a manner consistent with dialogue at the forefront of evolutionary biology. We define a macroalgal species as an independently evolving metapopulation lineage, whereby we can test for reproductive isolation or the occupation of distinct adaptive zones, among other mechanisms, as secondary lines of supporting evidence.
Automated Assessment of CO-RADS and Chest CT Severity Scores in Patients with Suspected COVID-19 Using Artificial Intelligence

Background The COVID-19 pandemic has spread across the globe with alarming speed, morbidity and mortality. Immediate triage of suspected patients with chest infections caused by COVID-19 using chest CT may be of assistance when results from definitive viral testing are delayed. Purpose To develop and validate an artificial intelligence (AI) system to score the likelihood and extent of pulmonary COVID-19 on chest CT scans using the CO-RADS and CT severity scoring systems. Materials and Methods CORADS-AI consists of three deep learning algorithms that automatically segment the five pulmonary lobes, assign a CO-RADS score for the suspicion of COVID-19 and assign a CT severity score for the degree of parenchymal involvement per lobe. This study retrospectively included patients who received an unenhanced chest CT scan due to clinical suspicion of COVID-19 at two medical centers. The system was trained, validated, and tested with data from one of the centers. Data from the second center served as an external test set. Diagnostic performance and agreement with scores assigned by eight independent observers were measured using receiver operating characteristic (ROC) analysis, linearly-weighted kappa and classification accuracy. Results 105 patients (62 ± 16 years, 61 men) and 262 patients (64 ± 16 years, 154 men) were evaluated in the internal and the external test set, respectively. The system discriminated between COVID-19 positive and negative patients with areas under the ROC curve of 0.95 (95% CI: 0.91-0.98) and 0.88 (95% CI: 0.84-0.93). Agreement with the eight human observers was moderate to substantial with a mean linearly-weighted kappa of 0.60 ± 0.01 for CO-RADS scores and 0.54 ± 0.01 for CT severity scores. Conclusion CORADS-AI correctly identified COVID-19 positive patients with high diagnostic performance from chest CT exams, assigned standardized CO-RADS and CT severity scores in good agreement with eight independent observers and generalized well to external data.
[Network analysis of cognitive, oculomotor and speech parameters in schizophrenia].

OBJECTIVE To determine the network connections between clinical, cognitive, speech and oculographic parameters in patients with schizophrenia. MATERIAL AND METHODS The study included 104 patients with schizophrenia and schizophrenia spectrum disorders and 70 healthy subjects. Clinical assessment of the patients was performed using a number of scales: PANSS, CDSS, YMRS, SAS and BAS. Basic cognitive functions were assessed by BACS. Eye movements were recorded using the SMI RED-500 non-invasive eye tracking system. Several experimental paradigms were used - free viewing of animal images with subsequent description of these images, performing progressive saccades in the experimental Go/NoGo scheme, and performing anti-saccades. RESULTS The severity of clinical symptoms, cognitive impairments, oculomotor parameters and characteristics of speech structure of written speech are largely independent, although not completely isolated from each other. Cognitive and oculomotor parameters have the largest number of connections. In this case, the results of cognitive tests are the central element of the «network» that connects other groups. CONCLUSION Further development of the approach should be aimed at studying the influence of node changes on the structure of the network that would potentially allows the identification of the most effective points of application of therapeutic and rehabilitation programs.
RNA Isolation from Adipose Tissue: An Optimized Procedure for High RNA Yield and Integrity

Adipose tissue physiology strongly differs between body regions. Reasonable amounts of intact RNA are required to analyze the local differences on a molecular level. Therefore, we developed an optimized RNA isolation procedure from adipose tissue samples. Excised human subcutaneous adipose tissue was obtained from elective operations, and the RNA Stabilization Reagent (RNAlater) was tested for its effect on RNA integrity. Additionally, 3 different RNA isolation kits were evaluated for efficacy in isolating RNA from tissue samples. The samples displayed a significant loss in recoverable RNA and signs of RNA degradation 30 to 60 minutes after tissue excision. The application of RNAlater significantly delayed this degradation. Using the RNeasy Lipid Tissue Kit resulted in a significantly higher RNA yield compared to the RNeasy Mini Kit. Our results demonstrate that combining the RNAlater and RNeasy Lipid Tissue Kit results in a higher yield of RNA even from relatively small tissue samples with guaranteed RNA integrity.
Transcriptome Profiling Associated with Carcass Quality of Loin Muscles in Crossbred Pigs

Simple Summary Carcass quality traits, such as lean depth and loin depth, are of extreme economic importance for the swine industry. This study aimed to identify the gene expression pattern related to carcass quality in crossbred pigs ((Landrace × Yorkshire) × Duroc). In total, 20 crossbred pigs were used in this study and divided into two groups based on the loin muscle quality grade. Total RNA samples extracted from the loin muscles of both groups were submitted for RNA-seq. Differentially expressed gene (DEG) analysis of the two groups revealed 282 up-regulated and 189 down-regulated genes (p ≤ 0.01), linked to tissue development, striated muscle tissue development, tissue morphogenesis, and lipid metabolic process gene ontology (GO) terms. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis highlighted genes related to the calcium signaling pathway, apelin signaling pathway, and the mammalian target of rapamycin (mTOR) signaling pathway. We constructed an expressed gene catalog, which may serve as a resource for genomic studies focused on uncovering the molecular mechanisms underlying carcass quality in crossbred pigs. Abstract Carcass quality traits, such as lean depth and loin depth, are of extreme economic importance for the swine industry. This study aimed to identify the gene expression pattern related to carcass quality in crossbred pigs ((Landrace × Yorkshire) × Duroc). In total, 20 crossbred pigs were used in this study and they were divided into two groups (class I grade, n = 10; class II grade, n = 10) based on the carcass grades. Total RNA samples extracted from the loin muscles of both groups were submitted for RNA-seq. The quality assessment of the sequencing reads resulted in 25,458 unigenes and found 12,795 candidate coding unigenes with homology to other species after annotation. Differentially expressed gene (DEG) analysis of the two groups revealed 282 up-regulated and 189 down-regulated genes (p ≤ 0.01), linked to tissue development, striated muscle tissue development, tissue morphogenesis, and lipid metabolic process gene ontology (GO) terms. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis highlighted genes related to the calcium signaling pathway, melanogenesis, the sphingolipid signaling pathway, the apelin signaling pathway, and the mTOR signaling pathway. We constructed an expressed gene profile, which may serve as a resource for genomic studies focused on uncovering the molecular mechanisms underlying carcass quality in crossbred pigs.
Gangliosides and Neuroblastomas

The focus of this review is the ganglio-series of glycosphingolipids found in neuroblastoma (NB) and the myriad of unanswered questions associated with their possible role(s) in this cancer. NB is one of the more common solid malignancies of children. Five-year survival for those diagnosed with low risk NB is 90–95%, while that for children with high-risk NB is around 40–50%. Much of the survival rate reflects age of diagnosis with children under a year having a much better prognosis than those over two. Identification of expression of GD2 on the surface of most NB cells led to studies of the effectiveness and subsequent approval of anti-GD2 antibodies as a treatment modality. Despite much success, a subset of patients, possibly those whose tumors fail to express concentrations of gangliosides such as GD1b and GT1b found in tumors from patients with a good prognosis, have tumors refractory to treatment. These observations support discussion of what is known about control of ganglioside synthesis, and their actual functions in NB, as well as their possible relationship to treatment response.
Perancangan Software as a Service sebagai Layanan Penyedia Aplikasi Enkripsi Dekripsi

Encryption is the process of securing information by making the information can not be read or understood. Once the data is encrypted, then the means to be able to read such information is by way of decryption. Decryption is the process of reading the information that has been encrypted. Encryption and decryption application is expected to be used and can help to keep the information in a text file, but still a few users are using the application encryption decryption. Cloud computing is a technology that provides computing needs in the form of services, with centralized management. One of the services of cloud computing is software as a service that provides services to users in the form of an application in accordance with the request, which was built in a private cloud infrastructure. Private cloud is, one of the deployment model of cloud computing, where the manager of the necessary infrastructure is managed in the internal network and is used only by users on the internal network.
Carbon cycling and storage in world forests: biome patterns related to forest age

Forest age, which is affected by stand‐replacing ecosystem disturbances (such as forest fires, harvesting, or insects), plays a distinguishing role in determining the distribution of carbon (C) pools and fluxes in different forested ecosystems. In this synthesis, net primary productivity (NPP), net ecosystem productivity (NEP), and five pools of C (living biomass, coarse woody debris, organic soil horizons, soil, and total ecosystem) are summarized by age class for tropical, temperate, and boreal forest biomes. Estimates of variability in NPP, NEP, and C pools are provided for each biome‐age class combination and the sources of variability are discussed. Aggregated biome‐level estimates of NPP and NEP were higher in intermediate‐aged forests (e.g., 30–120 years), while older forests (e.g., >120 years) were generally less productive. The mean NEP in the youngest forests (0–10 years) was negative (source to the atmosphere) in both boreal and temperate biomes (−0.1 and –1.9 Mg C ha−1 yr−1, respectively). Forest age is a highly significant source of variability in NEP at the biome scale; for example, mean temperate forest NEP was −1.9, 4.5, 2.4, 1.9 and 1.7 Mg C ha−1 yr−1 across five age classes (0–10, 11–30, 31–70, 71–120, 121–200 years, respectively). In general, median NPP and NEP are strongly correlated (R2=0.83) across all biomes and age classes, with the exception of the youngest temperate forests. Using the information gained from calculating the summary statistics for NPP and NEP, we calculated heterotrophic soil respiration (Rh) for each age class in each biome. The mean Rh was high in the youngest temperate age class (9.7 Mg C ha−1 yr−1) and declined with age, implying that forest ecosystem respiration peaks when forests are young, not old. With notable exceptions, carbon pool sizes increased with age in all biomes, including soil C. Age trends in C cycling and storage are very apparent in all three biomes and it is clear that a better understanding of how forest age and disturbance history interact will greatly improve our fundamental knowledge of the terrestrial C cycle.
Zebrafish as a Model for Fish Diseases in Aquaculture

The use of zebrafish as a model for human conditions is widely recognized. Within the last couple of decades, the zebrafish has furthermore increasingly been utilized as a model for diseases in aquacultured fish species. The unique tools available in zebrafish present advantages compared to other animal models and unprecedented in vivo imaging and the use of transgenic zebrafish lines have contributed with novel knowledge to this field. In this review, investigations conducted in zebrafish on economically important diseases in aquacultured fish species are included. Studies are summarized on bacterial, viral and parasitic diseases and described in relation to prophylactic approaches, immunology and infection biology. Considerable attention has been assigned to innate and adaptive immunological responses. Finally, advantages and drawbacks of using the zebrafish as a model for aquacultured fish species are discussed.
Review on Network Intrusion Detection Techniques using Machine Learning

The security given to a network from unapproved access and dangers is broadly called as network security. It is the obligation of network managers to embrace preventive measures to shield their networks from potential security dangers. Computer networks that are associated with consistent data transactions inside the administration or business require security. The exponential development in the information that streams inside network, the quantity of individuals active on network, makes it essential to have a productive system that disallows outsiders to attack and access secret information. Consistently developing digital attacks should be checked to defend classified information. Machine learning methods which have a critical part in distinguishing the attacks are for the most part utilized as a part of the advancement of Intrusion Detection Systems. Because of colossal increment in network activity and diverse sorts of attacks, checking every single parcel in the system movement is tedious and computationally expensive.
Second-movers’ advantage of utilizing Big Data to enhance sustainability performance: the case of elevator industry

Increasing digitization of contemporary business under the Internet era has created the big data phenomenon. Such a phenomenon would present opportunities and challenges for enterprises to compete vigorously under an environment driven by timely management decision that hinges on intelligence to predict potential performance. There are new business models that exploit potentials to improve sustainability performance. Organizations could analyze differential wants and needs of specific customers in big data so as to develop strategies to tackle operational weaknesses and reduce unwise utilization of resources. First, this paper articulates a conceptual framework on second-mover advantages in light of the entrepreneurial opportunities with big data analytics. Such second-mover initiatives using big data analytics could be created by an enterprise seeking second-mover advantages within its organization or by a startup that attempts to unveil opportunities to improve operational performance with disruptive innovation within an industry. Second, we explore potential sustainability performance that can be enhanced with big data analytics for the case of elevator operators that serve the high rises. Energy efficiency can be improved through optimization of activity-based programming for specific needs of the end users. Enhancement of sustainability performance could be achieved with transfer of proven technologies, including the latest development of regenerative converter in the elevator industry. Keywords—big data; second-movers’ advantage; sustainability; elevator industry (key words)