Confocal Raman microscopy for assessing effects of preservation methods on symbiotic deep-sea mussel gills

Confocal Raman microscopy (CRM) is a powerful tool for biological research, which can provide information regarding the composition and distribution of biomolecules in an in situ, label-free, non-destructive manner and with high spatial resolution. Sample preservation is often an unavoidable step, especially for symbiotic deep-sea samples. Moreover, protocols for the preservation of samples for CRM have not been established and specific effects of different preservation methods on biomolecules have not been studied for relevant samples. In this study, we used deep-sea mussel Gigantidas platifrons, an ideal model in the study of deep-sea symbiosis and investigated the effect of four common preservation methods on the results of CRM imaging and signals. The methods included snap-freeze (SF), SF followed by rapid fixation in methanol (SF-MeOH), 2.5% glutaraldehyde and 2% paraformaldehyde fixation (SF-GP), and 4% paraformaldehyde and alcohol fixation (PS-PA). The results of this study indicate that SF was the most effective method for the comprehensive analysis of the biomolecular composition although the sectioning success rate was relatively low. Moreover, SF-MeOH was found to be effective when SF is not sufficient in obtaining good morphology in sections, or when the effect of chemical bonding on the composition of biomolecules upon SF-MeOH can be neglected. Finally, SF-GP and PS-PA were found to be the most effective methods considering the overall morphological observation. However, they were less suitable for metabolic studies. We believe our results can provide guidance for further studies of Raman on symbiotic deep-sea biological samples. It is of great importance for the wide application of Raman technique

Heat wave characteristics, mortality and effect modification by temperature zones: a time-series study in 130 counties of China

Background: The substantial disease burden attributed to heat waves, and their increasing frequency and intensity due to climate change, highlight the importance of understanding the health consequences of heat waves. We explore the mortality risk due to heat wave characteristics, including the timing in the seasons, the day of the heat wave, the intensity and the duration, and the modifying effect of temperature zones. Methods: Heat waves were defined as ≥ 2 days with a temperature ≥99th percentile for the county from 1 May through 30 September. Heat waves were characterized by their intensity, duration, timing in the season, and day of the heat wave. Within each county, we estimated the total non-accidental death and cardiovascular disease mortality during each heat wave compared with non-heat wave days by controlling for potential confounders in summer. We combined individual heat wave effect estimates using a random-effects model to calculate overall effects at the temperature zone and national levels. Results: The average daily total number of non-accidental deaths was nine in the warm season (across all the counties). Approximately half of the daily total number of non-accidental deaths were cardiovascular-related deaths (approximately four persons per day). The average and maximum temperatures across the study area were 23.1 °C (range: -1.2–35.9 °C) and 28.3 °C (range: 5.4–42.8 °C), respectively. The average relative humidity during the study was 68.9% (range: 8.0–100.0%). Heat waves increase the risk of total non-accidental death by 15.7% [95% confidence interval (CI): 12.5, 18.9] compared with non-heat wave periods, and the risk of cardiovascular-related death increases by 22.0% (95% CI: 16.9, 27.4). The risk of non-accidental death during the first heat wave of the season increases by 16.3% (95% CI: 12.6, 20.2), the risk during the second heat wave increases by 6.3% (95% CI: 2.8, 9.9) and during subsequent heat waves increases by -2.1% (95% CI: -4.6, 0.4). The first day and the second to third days of heat waves increase the risk of total non-accidental death by 11.7% (95% CI: 7.6, 15.9) and 17.0% (95% CI: 13.1, 21.0), respectively. Effects of heat waves on mortality lasted more than 4 days (6.3%, 95% CI: 2.4, 10.5) and are non-significantly different from the first day of heat waves. We found non-significant differences of the heat wave-associated mortality risks across mid-, warm and subtropical temperature zones. Conclusions: In China, the effect of heat waves on mortality is acute, and varies by certain characteristics of heat waves. Given these results, national heat wave early warning systems should be developed, as well as precautions and protection warranted according to characteristics of heat waves

Short-term Exposure to Fine Particles and Risk of Cause-Specific Mortality — China, 2013-2018

What is already known about this topic? Short-term exposure to PM2.5 has been associated with population excess death. This issue is of critical concern in China given its high level of exposure to PM2.5 compared to that of the rest of the world. What is added by this report? Existing studies were conducted from 2013-2015 and have failed to capture the full effects of China’s actions towards cleaner air in recent years, such as the first Action Plan for Air Pollution Prevention and Control issued in 2013. This study uses the longest time series data to date from 2013-2018, provides the latest evidence on PM2.5 and cause-specific death nationwide, and identifies regional patterns of PM2.5-related effects as well as PM2.5-related susceptible populations. What are the implications for public health practice? This study suggests that the development of standards and the implementation of actions to clean the air and protect public health should be tailored to PM2.5-related sensitive diseases, susceptible populations, and regional patterns

Role of the ISKpn element in mediating mgrB gene mutations in ST11 hypervirulent colistin-resistant Klebsiella pneumoniae

BackgroundColistin has emerged as a last-resort therapeutic against antibiotic-resistant bacterial infections, particularly those attributed to carbapenem-resistant Enterobacteriaceae (CRE) like CRKP. Yet, alarmingly, approximately 45% of multidrug-resistant Klebsiella pneumoniae strains now manifest resistance to colistin. Through our study, we discerned that the synergy between carbapenemase and IS elements amplifies resistance in Klebsiella pneumoniae, thereby narrowing the existing therapeutic avenues. This underscores the instrumental role of IS elements in enhancing colistin resistance through mgrB disruption.MethodsFrom 2021 to 2023, 127 colistin-resistant Klebsiella pneumoniae isolates underwent meticulous examination. We embarked on an exhaustive genetic probe, targeting genes associated with both plasmid-mediated mobile resistance-encompassing blaKPC, blaNDM, blaIMP, blaVIM, blaOXA-48-like, and mcr-1 to mcr-8-and chromosome-mediated resistance systems, including PhoP/Q, PmrA/B, and mgrB. PCR amplification revealed the presence of virulence-associated genes from the pLVPK plasmid, such as rmpA, rmpA2, iucA, iroB, and peg344. mgrB sequencing was delegated to Sangon Biotech, Shanghai, and the sequences procured were validated using BLAST. Our search for IS elements was navigated through the IS finder portal. Phenotypically, we harnessed broth microdilution (BMD) to ascertain the MICs of colistin. To sketch the clonal lineage of mgrB-mutated CoR-Kp isolates, sophisticated methodologies like MLST and PFGE were deployed. S1-PFGE unraveled the intrinsic plasmids in these isolates. Our battery of virulence assessment techniques ranged from the string test and capsular serotyping to the serum killing assay and the Galleria mellonella larval infection model.ResultsAmong the 127 analyzed isolates, 20 showed an enlarged mgrB PCR amplicon compared to wild-type strains. These emerged over a three-year period: three in 2021, thirteen in 2022, and four in 2023. Antimicrobial susceptibility tests revealed that these isolates consistently resisted several drugs, notably TCC, TZP, CAZ, and COL. Additionally, 85% resisted both DOX and TOB. The MICs for colistin across these strains ranged between 16 to 64 mg/L, with a median of 40 mg/L. From a genetic perspective, MLST unanimously categorized these mgrB-mutated CoR-hvKp isolates as ST11. PFGE further delineated them into six distinct clusters, with clusters A and D being predominant. This distribution suggests potential horizontal and clonal genetic transmission. Intriguingly, every mgrB-mutated CoR-hvKP isolate possessed at least two virulence genes akin to the pLVPK-like virulence plasmid, with iroB and rmpA2 standing out. Their virulence was empirically validated both in vitro and in vivo. A pivotal discovery was the identification of three distinct insertion sequence (IS) elements within or near the mgrB gene. These were:ISKpn26 in eleven isolates, mainly in cluster A, with various insertion sites including +74, +125, and an upstream −35.ISKpn14 in four isolates with insertions at +93, −35, and two upstream at −60.IS903B present in five isolates, marking positions like +74, +125, +116, and −35 in the promoter region. These diverse insertions, spanning six unique locations in or near the mgrB gene, underscore its remarkable adaptability.ConclusionOur exploration spotlights the ISKpn element’s paramount role in fostering mgrB gene mutations in ST11 hypervirulent colistin-resistant Klebsiella pneumoniae. Employing MLST and PFGE, we unearthed two primary genetic conduits: clonal and horizontal. A striking observation was the ubiquitous presence of the KPC carbapenemase gene in all the evaluated ST11 hypervirulent colistin-resistant Klebsiella pneumoniae strains, with a majority also harboring the NDM gene. The myriad mgrB gene insertion locales accentuate its flexibility and the overarching influence of IS elements, notably the pervasive IS5-like variants ISKpn26 and IS903B. Our revelations illuminate the escalating role of IS elements in antibiotic resistance within ST11 hypervirulent colistin-resistant Klebsiella pneumoniae, advocating for innovative interventions to counteract these burgeoning resistance paradigms given their profound ramifications for prevailing treatment modalities

Incorporation of a machine learning pathological diagnosis algorithm into the thyroid ultrasound imaging data improves the diagnosis risk of malignant thyroid nodules

ObjectiveThis study aimed at establishing a new model to predict malignant thyroid nodules using machine learning algorithms.MethodsA retrospective study was performed on 274 patients with thyroid nodules who underwent fine-needle aspiration (FNA) cytology or surgery from October 2018 to 2020 in Xianyang Central Hospital. The least absolute shrinkage and selection operator (lasso) regression analysis and logistic analysis were applied to screen and identified variables. Six machine learning algorithms, including Decision Tree (DT), Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Naive Bayes Classifier (NBC), Random Forest (RF), and Logistic Regression (LR), were employed and compared in constructing the predictive model, coupled with preoperative clinical characteristics and ultrasound features. Internal validation was performed by using 10-fold cross-validation. The performance of the model was measured by the area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, F1 score, Shapley additive explanations (SHAP) plot, feature importance, and correlation of features. The best cutoff value for risk stratification was identified by probability density function (PDF) and clinical utility curve (CUC).ResultsThe malignant rate of thyroid nodules in the study cohort was 53.2%. The predictive models are constructed by age, margin, shape, echogenic foci, echogenicity, and lymph nodes. The XGBoost model was significantly superior to any one of the machine learning models, with an AUC value of 0.829. According to the PDF and CUC, we recommended that 51% probability be used as a threshold for determining the risk stratification of malignant nodules, where about 85.6% of patients with malignant nodules could be detected. Meanwhile, approximately 89.8% of unnecessary biopsy procedures would be saved. Finally, an online web risk calculator has been built to estimate the personal likelihood of malignant thyroid nodules based on the best-performing ML-ed model of XGBoost.ConclusionsCombining clinical characteristics and features of ultrasound images, ML algorithms can achieve reliable prediction of malignant thyroid nodules. The online web risk calculator based on the XGBoost model can easily identify in real-time the probability of malignant thyroid nodules, which can assist clinicians to formulate individualized management strategies for patients

The effect of parenting styles on adolescent bullying behaviours in China: The mechanism of interpersonal intelligence and intrapersonal intelligence

Bullying is a problematic public behaviour of great concern worldwide, which occurs commonly in China. Parenting and emotional intelligence have previously been verified as crucial aspects in determining the bullying behaviours of adolescents. However, evidence of the interactive effect of these vital factors needs to be more extensive. This study attempts to analyze the relationships and mechanisms of parenting on bullying through emotional intelligence, which consists of interpersonal and intrapersonal intelligence. Based on Chinese education panel survey data of 8730 adolescents, this paper used OLS regression and SEM methods to estimate the impact and mechanisms of parenting styles on bullying behaviours among adolescents. High-demand and responsive parenting styles can significantly reduce adolescents' bullying behaviours. Intrapersonal and interpersonal intelligence are important mediating variables, and parenting with high demandingness and high responsiveness can significantly improve the interpersonal intelligence of adolescents, thereby reducing children's bullying behaviour. Although low levels of intrapersonal intelligence would increase bullying behaviours in adolescents, high demandingness and high responsiveness of parenting can significantly improve adolescents' intrapersonal intelligence. Parents can reduce adolescents' bullying behaviours by increasing emotional responses and normative requirements. This result provides a new perspective on the solution to the problem of youth bullying

Study of microbial sulfur metabolism in a near real-time pathway through confocal Raman quantitative 3D imaging.zip

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Anti-Oxidant and Anti-Melanogenic Properties of Essential Oil from Peel of Pomelo cv. Guan Xi

Here, we investigated the anti-oxidant and anti-melanogenic effects of pomelo peel essential oil (PPEO) from pomelo cv. Guan Xi. The volatile chemical composition of PPEO was analyzed with gas chromatography–mass spectrometry (GC/MS). The most abundant component of PPEO was limonene (55.92%), followed by β-myrcene (31.17%), and β-pinene (3.16%). PPEO showed strong anti-oxidant activities against 1,1-diphenyl-2-picryhydrazyl (DPPH) (,2,2'-azinobis-(3-ethylbenzthiazoline-6-sulphonate) (ABTS) (, and superoxide anion free radicals. Based on the B16 melanoma cell system, the effects of PPEO on the viability and morphology of B16 cells and the production of melanin were evaluated. The results revealed that PPEO at concentrations below 50 μg/mL could decrease the melanin content without affecting cell viability and morphology. Intracellular tyrosinase (TYR) activity and Western blot analysis showed that PPEO could down-regulate the expression level of TYR in B16 cells and dose-dependently inhibit TYR activity (by a maximum of 64.54%). Meanwhile, the main active components responsible for the effect are citral and β-myrcene. In conclusion, PPEO has good anti-oxidant and anti-melanogenic activity, and thus can be widely used as a natural antioxidant in the food, pharmaceutical, and cosmetic industries

Provenance differentiation and earth surface process of the Mu Us sandy land constrained by detrital zircon U–Pb dating

Abstract Understanding the provenance and sediment surface processes of the Mu Us sandy land (MU) is critical for comprehending aeolian deposits and dust transportation in inland Asia and the Chinese Loess Plateau (CLP). In this study, we analyzed the detrital zircon U–Pb ages in the sediments of the MU, together with the previously collected data from sediments in the Hobq desert and CLP. Our findings demonstrate that there is spatial heterogeneity in the sediment characteristics of the MU and Hobq regions, with noticeable differences between northeastern and southwestern areas. In addition, the northeastern part of the CLP displays significant dissimilarities from other regions of the CLP. The NE MU, Eastern Hobq, and NE CLP inherit the main characteristics of basement rocks from the Western North China Craton, with prominent age ranges of 1600–2200 Ma and 2200–2800 Ma, indicating that this region is likely more controlled by in-situ weathering and recycling. In contrast, the SW MU, West-Middle Hobq and most parts of CLP show multiple sources, with a higher proportion of 200–350 Ma and 350–600 Ma, reflecting that the aeolian deposits in this area may be associated with more frequent earth surface processes such as sand-driving winds and fluvial transport. Although all three regions are situated within the square bend of the Yellow River and under the prevailing winds direction, sediments in the first two areas appear to have a more mixed contribution of both local and distal sources. In contrast, deposits in the CLP region were primarily sourced from the northeast Tibetan Plateau via the upper Yellow River. This indicates a variation in dust sources from north to south and suggests that the MU is part of the same sedimentary system as the CLP, rather than its direct source

Energy Efficient Path Planning for Indoor Wheeled Mobile Robots

There has been an increased interest in the optimal robot path planning study. However, the optimal path found by the traditional path planning methods only considers distance and time constraints. Thus, it is not necessarily the most energy efficient path. In order to make robots perform more tasks under insufficient energy supply efficiently, reducing energy consumption has become essential in the path planning. In this paper, we proposed a novel path smoothing method that overcomes the deficiencies (e.g., some redundant inflection points in path.) of the traditional A* algorithm. We designed an energy-based adjacency matrix to represent the environmental information in grid map. Then we added a new energy-related criterion based on an adjacency matrix to the cost function of the A* algorithm for path planning. The simulation results demonstrated that the proposed method is more energy efficient than the existing A* algorithm. Moreover, the method realizes a good trade-off between preserving energy and not extending too much the path length. With such advantages, the proposed methods can help indoor wheeled mobile robots or automated guided vehicles (AGVs) to complete path planning tasks with limited power