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Oral microbiome dysbiosis mediates chronic periodontal disease, gut microbial dysbiosis, and mucosal barrier disfunction that leads to steatohepatitis via the enterohepatic circulation. Improving this dysbiosis towards health may improve liver disease. Treatment with antibiotics and probiotics have been used to modulate the microbial, immunological, and clinical landscape of periodontal disease with some success. The aim of the present investigation was to evaluate the potential for nisin, an antimicrobial peptide produced by Lactococcus lactis, to counteract the periodontitis-associated gut dysbiosis and to modulate the glycolipid-metabolism and inflammation in the liver. Periodontal pathogens, namely Porphyromonas gingivalis, Treponema denticola, Tannerella forsythia and Fusobacterium nucleatum, were administrated topically onto the oral cavity to establish polymicrobial periodontal disease in mice. In the context of disease, nisin treatment significantly shifted the microbiome towards a new composition, commensurate with health while preventing the harmful inflammation in the small intestine concomitant with decreased villi structural integrity, and heightened hepatic exposure to bacteria and lipid and malondialdehyde accumulation in the liver. Validation with RNA Seq analyses, confirmed the significant infection-related alteration of several genes involved in mitochondrial dysregulation, oxidative phosphorylation, and metal/iron binding and their restitution following nisin treatment. In support of these in vivo findings indicating that periodontopathogens induce gastrointestinal and liver distant organ lesions, human autopsy specimens demonstrated a correlation between tooth loss and severity of liver disease. Nisin's ability to shift the gut and liver microbiome towards a new state commensurate with health while mitigating enteritis, represents a novel approach to treating NAFLD-steatohepatitis-associated periodontal disease.

The impact of Gd doping on Ni-Mn-In alloys was investigated using a combination of experimental studies and first-principles calculations. The results of first-principles calculations reveal that Gd doping tends to occupy the sublattices of Ni and In in the Ni8Mn6In2 alloy. Gd substitution of either Ni or In increases the martensitic temperature and decreases the Curie temperature at the same time. In particular， the increase in phase transition temperature is more significant after Gd replaces In. The electron density of states analysis shows that Gd doping decreases the austenite stability and increases the martensite stability， which is the main reason for the increase in phase transition temperature. The Ni50-xMn35In15Gdx（x=0，1，2） and Ni50Mn35In15-xGdx（x=0，1，2） polycrystalline alloys are successfully prepared using a vacuum arc melting furnace， and analyzed by the DSC experimental data， it was observed that the doping of Gd enhances the phase transition temperature of alloy. Specifically， the martensitic transformation starts temperature of Ni50Mn35In13Gd2 reached 160 ℃， which can meet the high-temperature （≈97 ℃） operating conditions. The doping of a single Gd atom does not change the magnetic state of the alloy parent phases and martensitic phases in Ni-Mn-In alloys， resulting in a minor effect on the difference of magnetization. The mechanism of Gd doping affects the magnetic structure of the alloy is elucidated.

The safety and efficiency of drilling engineering are greatly impeded by destructive vibrations of drill string in air drilling, such as stick-slip, bit-bounce and their coupled vibrations. To avoid or suppress these vibrations improving the stability of drilling operations, revealing the occurrence mechanisms of abovementioned harmful vibrations are indispensable by investigating dynamics characteristics of drill string system. In this paper, an axial-torsional coupled dynamics model that can capture the motion behaviors of bottom hole assembly (BHA) is established adopting the lumped parameter method. Subsequently, a rate of penetration (ROP) model appropriating for air drilling is obtained firstly by linear fitting means. Meanwhile, a novel discontinuous support model is established to describe the bit-formation interactions. Then, BHA dynamics are discussed using numerical simulations under different vibration scenarios: normal operation; stick-slip; bit-bounce; bit-bounce and stick-slip combination. Subsequently, in two drilling modes: the continuous and intermittent drilling, the vibration mitigation strategies and dynamics sensibility study of BHA are carried out based on the parametric analysis. The results show that increasing torsional stiffness of drill-pipes, appropriately adjusting rotation speed of top driven system and dynamic weight on bit (WOB) are deemed as an effective strategy suppressing or eliminating stick-slip and bit-bounce vibrations of BHA. Suggest that the rotation speed of top driven system and dynamic WOB are 5 rad/s and 3.5 kN, respectively. Finally, the constructed probability maps allow to driller to choose reasonable mechanical parameters, thereby realizing smooth drilling operation in the air drilling.

BackgroundWearable devices have attracted much attention from the market in recent years for their fitness monitoring and other health-related metrics; however, the accuracy of fitness tracking results still plays a major role in health promotion. ObjectiveThe aim of this study was to evaluate the accuracy of a host of latest wearable devices in measuring fitness-related indicators under various seminatural activities. MethodsA total of 44 healthy subjects were recruited, and each subject was asked to simultaneously wear 6 devices (Apple Watch 2, Samsung Gear S3, Jawbone Up3, Fitbit Surge, Huawei Talk Band B3, and Xiaomi Mi Band 2) and 2 smartphone apps (Dongdong and Ledongli) to measure five major health indicators (heart rate, number of steps, distance, energy consumption, and sleep duration) under various activity states (resting, walking, running, cycling, and sleeping), which were then compared with the gold standard (manual measurements of the heart rate, number of steps, distance, and sleep, and energy consumption through oxygen consumption) and calculated to determine their respective mean absolute percentage errors (MAPEs). ResultsWearable devices had a rather high measurement accuracy with respect to heart rate, number of steps, distance, and sleep duration, with a MAPE of approximately 0.10, whereas poor measurement accuracy was observed for energy consumption (calories), indicated by a MAPE of up to 0.44. The measurements varied for the same indicator measured by different fitness trackers. The variation in measurement of the number of steps was the highest (Apple Watch 2: 0.42; Dongdong: 0.01), whereas it was the lowest for heart rate (Samsung Gear S3: 0.34; Xiaomi Mi Band 2: 0.12). Measurements differed insignificantly for the same indicator measured under different states of activity; the MAPE of distance and energy measurements were in the range of 0.08 to 0.17 and 0.41 to 0.48, respectively. Overall, the Samsung Gear S3 performed the best for the measurement of heart rate under the resting state (MAPE of 0.04), whereas Dongdong performed the best for the measurement of the number of steps under the walking state (MAPE of 0.01). Fitbit Surge performed the best for distance measurement under the cycling state (MAPE of 0.04), and Huawei Talk Band B3 performed the best for energy consumption measurement under the walking state (MAPE of 0.17). ConclusionsAt present, mainstream devices are able to reliably measure heart rate, number of steps, distance, and sleep duration, which can be used as effective health evaluation indicators, but the measurement accuracy of energy consumption is still inadequate. Fitness trackers of different brands vary with regard to measurement of indicators and are all affected by the activity state, which indicates that manufacturers of fitness trackers need to improve their algorithms for different activity states.

Background Given the increasing prevalence of the high incidence of bone and joint diseases in the elderly population, and significantly associated with higher mortality, more disability, decline in functional status and lower quality of life, this creates a large disease burden. There is currently no research on the prevalence and influencing factors of this disease in Henan Province. Objective To provide scientific basis for understanding the epidemic characteristics and influencing factors of bone and joint diseases in the elderly population in Henan Province and implementing precise prevention and control. Methods The multi-stage random cluster sampling method was used to obtain the demographic characteristics, past disease history, physical activity and physical indicators of permanent residents aged≥18 years old in Henan Province in 2018 through questionnaires, medical physical examination, laboratory testing and other methods. 1 055 people aged ≥60 years old were included in this study. Multivariate Logistic regression was used to analyze the characteristics and influencing factors of bone and joint diseases in the elderly population with different characteristics in Henan Province. Results The incidence rate of bone and joint diseases among the elderly population in Henan Province in 2018 was 28.13% (95%CI=28.10%-28.15%). Among them, women, urban areas, those with overweight or obesity, central obesity, dyslipidemia or hyperlipidemia, snoring history, moderate intensity activity, and non-smoking history have higher incidence rates, and the differences are statistically significant (P

Background: Recent studies have identified empathy deficit as a core impairment and diagnostic criterion for people with autism spectrum disorders; however, the improvement of empathy focuses primarily on behavioural interventions without the target regulation. We sought to compare brain regions associated with empathy-like behaviours of fear and pain, and to explore the role of the oxytocinoxytocin receptor system in fear empathy. Methods: We used C57BL mice to establish 2 models of fear empathy and pain empathy. We employed immunofluorescence histochemical techniques to observe the expression of c-Fos throughout the entire brain and subsequently quantified the number of c-Fos-positive cells in different brain regions. Furthermore, we employed chemogenetic technology to selectively manipulate these neurons in Oxt-[Cre.sup.-/+] mice to identify the role of oxytocin in this process. Results: The regions activated by fear empathy were the anterior cingulate cortex, basolateral amygdala, nucleus accumbens, paraventricular nucleus (PVN), lateral habenula, and ventral and dorsal hippocampus. The regions activated by pain empathy were the anterior cingulate cortex, basolateral amygdala, nucleus accumbens, and lateral habenula. We found that increasing the activity of oxytocin neurons in the PVN region enhanced the response to fear empathy. This enhancement may be mediated through oxytocin receptors. Limitations: This study included only male animals, which restricts the broader interpretation of the findings. Further investigations on circuit function need to be conducted. Conclusion: The brain regions implicated in the regulation of fear and pain empathy exhibit distinctions; the activity of PVN neurons was positively correlated with empathic behaviour in mice. These findings highlight the role of the PVN oxytocin pathway in regulating fear empathy and suggest the importance of oxytocin signalling in mediating empathetic responses., Introduction Empathy refers to an individual's perception and recognition of the internal emotions and feelings of others, including the ability to identify and respond to their voices, expressions, and physical [...]