Structural and spectral properties of Galactic plane variable radio sources

In the time domain, the radio sky in particular along the Galactic plane direction may vary significantly because of various energetic activities associated with stars, stellar, and supermassive black holes. Multi-epoch Very Large Array surveys of the Galactic plane at 5.0 GHz enabled the finding of a catalogue of 39 variable radio sources in the flux density range 1-70 mJy. To probe their radio structures and spectra, we observed 17 sources with the very-long-baseline interferometric (VLBI) imaging technique and collected additional multifrequency data from the literature. We detected all of the sources at 5 GHz with the Westerbork Synthesis Radio Telescope, but only G23.6644-0.0372 with the European VLBI Network (EVN). Together with its decadal variability and multifrequency radio spectrum, we interpret it as an extragalactic peaked-spectrum source with a size of less than or similar to 10 pc. The remaining sources were resolved out by the long baselines of the EVN because of either strong scatter broadening at the Galactic latitude < 1 degrees or intrinsically very extended structures on centi-arcsec scales. According to their spectral and structural properties, we find that the sample has a diverse nature. We notice two young H ii regions and spot a radio star and a candidate planetary nebula. The rest of the sources are very likely associated with radio active galactic nuclei (AGNs). Two of them also display arcsec-scale faint jet activity. The sample study indicates that AGNs are common place even among variable radio sources in the Galactic plane

Identifying interacting genetic variations by fish-swarm logic regression

Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds

KL-6 levels in the connective tissue disease population: typical values and potential confounders–a retrospective, real-world study

BackgroundKrebs von den Lungen 6 (KL-6) is a potential biomarker for determining the severity of interstitial lung disease (ILD) in patients with connective tissue disease (CTD). Whether KL-6 levels can be affected by potential confounders such as underlying CTD patterns, patient-associated demographics, and comorbidities needs further investigation.MethodsFrom the database created by Xiangya Hospital, 524 patients with CTD, with or without ILD, were recruited for this retrospective analysis. Recorded data included demographic information, comorbidities, inflammatory biomarkers, autoimmune antibodies, and the KL-6 level at admission. Results of CT and pulmonary function tests were collected one week before or after KL-6 measurements. The percent of predicted diffusing capacity of the lung for carbon monoxide (DLCO%) and computed tomography (CT) scans were used to determine the severity of ILD.ResultsUnivariate linear regression analysis showed that BMI, lung cancer, TB, lung infections, underlying CTD type, white blood cell (WBC) counts, neutrophil (Neu) counts, and hemoglobin (Hb) were related to KL-6 levels. Multiple linear regression confirmed that Hb and lung infections could affect KL-6 levels independently; the β were 9.64 and 315.93, and the P values were 0.015 and 0.039, respectively. CTD-ILD patients had higher levels of KL-6 (864.9 vs 463.9, P < 0.001) than those without ILD. KL-6 levels were closely correlated to the severity of ILD assessed both by CT and DLCO%. Additionally, we found that KL-6 level was an independent predictive factor for the presence of ILD and further constructed a decision tree model to rapidly determine the risk of developing ILD among CTD patients.ConclusionKL-6 is a potential biomarker for gauging the incidence and severity of ILD in CTD patients. To use this typical value of KL-6, however, doctors should take Hb and the presence of lung infections into account

Velocity-resolved high-J CO emission from massive star-forming clumps

(Abridged) Context. Massive star formation is associated with energetic processes, which result in significant gas cooling via far-infrared (IR) lines. Velocity-resolved observations can constrain the kinematics of the gas, allowing the identification of the physical mechanisms responsible for gas heating. Aims. Our aim is to quantify far-infrared CO line emission toward high-mass star-forming regions, identify the high-velocity gas component associated with outflows, and estimate the physical conditions required for the excitation of the observed lines. Methods. Velocity-resolved SOFIA/GREAT spectra of 13 high-mass star forming clumps of various luminosities and evolutionary stages are studied using CO 11-10 and 16-15 lines. Results. All targets show strong high-J CO emission in the far-IR, characterized by broad line wings associated with outflows, thereby significantly increasing the sample of sources with velocity-resolved high-J CO spectra. The contribution of the emission in the line wings does not correlate with the envelope mass or evolutionary stage. Gas rotational temperatures cover a narrow range of 120-220 K for the line wings. The non-LTE radiative transfer models indicate gas densities of 1e5-1e7 cm-3 and N(CO) of 1e17- 1e18 cm-2, similar to physical conditions in deeply-embedded low- and high-mass protostars. The velocity-integrated CO line fluxes correlate with the bolometric luminosity over 7 orders of magnitude including data on the low-mass protostars, suggesting similar processes are responsible for the high-J CO excitation over a significant range of physical scales. Conclusions. Velocity-resolved line profiles allow the detection of outflows toward massive star-forming clumps spanning a broad range of evolutionary stages. The lack of clear evolutionary trends suggest that mass accretion and ejection prevail during the entire lifetime of star-forming clumps.Comment: 21 pages, 19 figures, accepted to A&

Advances in exercise to alleviate sarcopenia in older adults by improving mitochondrial dysfunction

Sarcopenia is a chronic degenerative disease affecting primarily older adults. A growing aging population is gradually increasing the number of patients suffering from sarcopenia, placing increasing financial pressure on patients’ families and society in general. There is a strong link between mitochondrial dysfunction and sarcopenia pathogenesis. As a result, treating sarcopenia by improving mitochondrial dysfunction is an effective strategy. Numerous studies have demonstrated that exercise has a positive effect on mitochondrial dysfunction when treating sarcopenia. Exercise promotes mitochondrial biogenesis and mitochondrial fusion/division to add new mitochondria or improve dysfunctional mitochondria while maintaining mitochondrial calcium homeostasis, mitochondrial antioxidant defense system, and mitochondrial autophagy to promote normal mitochondrial function. Furthermore, exercise can reduce mitochondrial damage caused by aging by inhibiting mitochondrial oxidative stress, mitochondrial DNA damage, and mitochondrial apoptosis. Exercise effectiveness depends on several factors, including exercise duration, exercise intensity, and exercise form. Therefore, Moderate-intensity exercise over 4 weeks potentially mitigates sarcopenia in older adults by ameliorating mitochondrial dysfunction. HIIT has demonstrated potential as a viable approach to addressing sarcopenia in aged rats. However, further investigation is required to validate its efficacy in treating sarcopenia in older adults

Novel compounds in fruits of coriander (Coşkuner & Karababa) with anti-inflammatory activity

© 2020 Coriander, Coriandrum Sativum L., is one of the commonest food and medicinal plants in many countries, but its chemical ingredients and pivotal role in anti-inflammatory activity have not been fully explored. The present study aimed to identify new compounds in the fruits of coriander and explore their anti-inflammatory activity. The compounds were isolated by chromatographic seperations and identified using spectroscopic and spectrometric methods. RAW264.7 macrophage cells were used to detect the anti-inflammatory activity of the compounds via Griess assay, western blotting, ELISA, and flow cytometry methods. The study resulted in the discovery of four new compounds, which were identified as: 4α-(furo[2,3-d]pyrimidin-6′-ylmethyl)-9α-propylnonolactone (1), 4-(formyloxy)-4-(6′-methylcyclohex-1-en-1-yl)butanoate(2), (7α,8α)-3α-hydroxyl-12,13α-dimethyl-5(6)-en-bicyclo[5,3,0]caprolactone (3), 7-methoxy-4-methyl-5,6-dihydro-7H-(2-hydroxypropan-2-yl)furo[2,3-f] coumarin (4). Compound 3 showed the highest anti-inflammatory activity with IC50 of 6.25 μM for an inhibitory effect on nitrite oxide (NO) level. In addition, compound 3 decreased the lipopolysaccharides-stimulated generations of ROS and the inflammatory cytokines (IL-6 and TNF-α). Mechanism exploration indicated that compound 3 suppressed inflammatory mediators’ expression, like iNOS and COX-2. Furthermore, the NF-κB and MAPK pathways were involved in the anti-inflammatory process of compound 3

Baichuan 2: Open Large-scale Language Models

Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages other than English. In this technical report, we present Baichuan 2, a series of large-scale multilingual language models containing 7 billion and 13 billion parameters, trained from scratch, on 2.6 trillion tokens. Baichuan 2 matches or outperforms other open-source models of similar size on public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan 2 excels in vertical domains such as medicine and law. We will release all pre-training model checkpoints to benefit the research community in better understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github: https://github.com/baichuan-inc/Baichuan

A global view on star formation: the GLOSTAR Galactic plane survey III. 6.7 GHz methanol maser survey in Cygnus X

The Cygnus X complex is covered by the Global View of Star Formation in the Milky Way (GLOSTAR) survey, an unbiased radio-wavelength Galactic plane survey, in 4–8 GHz continuum radiation and several spectral lines. The GLOSTAR survey observed the 6.7 GHz transition of methanol (CH$_3$OH), an exclusive tracer of high-mass young stellar objects. Using the Very Large Array in both the B and D configurations, we observed an area in Cygnus X of 7° × 3° in size and simultaneously covered the methanol line and the continuum, allowing cross-registration. We detected thirteen sources with Class II methanol maser emission and one source with methanol absorption. Two methanol maser sources are newly detected; in addition, we found four new velocity components associated with known masers. Five masers are concentrated in the DR21 ridge and W75N. We determined the characteristics of the detected masers and investigated the association with infrared, (sub)millimeter, and radio continuum emission. All maser sources are associated with (sub)millimeter dust continuum emission, which is consistent with the picture of masers tracing regions in an active stage of star formation. On the other hand, only five masers (38 ± 17%) have radio continuum counterparts seen with GLOSTAR within ~1″, testifying to their youth. Comparing the distributions of the bolometric luminosity and the luminosity-to-mass ratio of cores that host 6.7 GHz methanol masers with those of the full core population, we identified lower limits L$_{Bol}$ ~ 200 L$_⊙$ and L$_{Bol}$/M$_{core}$ ~ 1 L$_⊙$M$_⊙^{−1}$ for a dust source to host maser emission

A probabilistic method for identifying rare variants underlying complex traits

Abstract Background Identifying the genetic variants that contribute to disease susceptibilities is important both for developing methodologies and for studying complex diseases in molecular biology. It has been demonstrated that the spectrum of minor allelic frequencies (MAFs) of risk genetic variants ranges from common to rare. Although association studies are shifting to incorporate rare variants (RVs) affecting complex traits, existing approaches do not show a high degree of success, and more efforts should be considered. Results In this article, we focus on detecting associations between multiple rare variants and traits. Similar to RareCover, a widely used approach, we assume that variants located close to each other tend to have similar impacts on traits. Therefore, we introduce elevated regions and background regions, where the elevated regions are considered to have a higher chance of harboring causal variants. We propose a hidden Markov random field (HMRF) model to select a set of rare variants that potentially underlie the phenotype, and then, a statistical test is applied. Thus, the association analysis can be achieved without pre-selection by experts. In our model, each variant has two hidden states that represent the causal/non-causal status and the region status. In addition, two Bayesian processes are used to compare and estimate the genotype, phenotype and model parameters. We compare our approach to the three current methods using different types of datasets, and though these are simulation experiments, our approach has higher statistical power than the other methods. The software package, RareProb and the simulation datasets are available at: http://www.engr.uconn.edu/~jiw09003.</p