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Purpose: Exercise has a positive regulatory effect on gut microbiota and is also involved in regulating multiple physiological functions of the human body. This article tested the effects of basketball exercises at different exercise intensities on the gut microbiota of college students. Methods: Athlete research subjects (male, aged 18 - 25) were selected from the basketball team and trained at different intensities to obtain a total of 101 fresh fecal samples. DNA was extracted by a DNA extraction kit and bacterial 16S rRNA gene V3-V4 region high-throughput sequencing using the Illumina Hiseq platform. The downstream data were spliced, filtered and de-trimerized and then used to study the difference in gut microbiota. Results: Key bacterial taxa in the gut that responded to exercise intensity differed among athletes of different exercise intensities but most belonged to Firmicutes. With increasing exercise intensity, Butyricicoccus, Anaerostipes, Oxalobacter and Clostridium_IV in basketball players enrich. Further analysis of the functional prediction revealed that carbohydrate metabolism, amino acid metabolism, metabolism of xenobiotics and glycans and metabolism were significantly expressed in the gut microbiota of basketball athletes with high intensity. Conclusion: The study demonstrated that after long-term professional training, the gut microbiota of athletes adapts to exercise stimulators and can quickly respond to changes in exercise intensity. In high-intensity training, the organism is protected from harm by enriching some beneficial bacteria.

In order to improve laser transmission efficiency at 1053 nm and 527 nm, a potassium deuterium phosphate (DKDP) crystal (a key component of high-power laser systems) needs a bi-layer antireflection coating system on its incident surface. UV-curable polysiloxane coatings with a refractive index varying from 1.500 to 1.485 were prepared through the polycondensation of a methacryloxy propyl trimethoxylsilane (MPS) monomer with a controllable degree of hydrolysis. Additionally, the influence rule of the coating structure on the refractive index was intensively studied, and the primary factors that dominate the hydrolysis process were discussed. Further refractive index adjustment was achieved using only a small amount of dopant based on the polysiloxane coating with refractive index of 1.485, allowing for high antireflection of the bi-layer coating system at desired wavelengths to be achieved. In addition, high laser damage resistance and remarkable mechanical properties of the coating were simultaneously realized through the incorporation of a minor quantity of dopants, which benefited from the successful modulation of the intrinsic refractive index of the polysiloxane coating.

ObjectiveTo systematically compare the bowel cleaning ability, patient tolerance and safety of oral sodium phosphate tablets (NaPTab) and oral polyethylene glycol electrolyte lavage solution (PEGL) to inform clinical decision making.MethodsPubMed, Embase, CBM, WanFang Data, CNKI, and VIP databases were searched for studies that used randomized controlled trials (RCTs) to compare the roles of NaPTab and PEGL in bowel preparation before colonoscopy. Two reviewers independently screened the studies, extracted data, and assessed the risk of bias in the included papers. A meta-analysis was performed using RevMan 5.3 software.ResultsA total of 13 RCTs were eligible for inclusion, including 2,773 patients (1,378 and 1,395 cases in the NaPTab and PEGL groups, respectively). Meta-analysis revealed no significant difference in the cleansing quality of the NaPTab and PEGL groups [RR 1.02, 95% CI (0.96–1.08), P = 0.46]. The incidence of nausea was lower in the NaPTab group than in the PEGL group [RR 0.67, 95% CI (0.58–0.76), p < 0.00001]. Patients rated the taste of NaPTab higher than PEGL [RR 1.33, 95% CI (1.26–1.40), P < 0.00001]. Willingness to repeat the treatment was also higher in the NaPTab group than in the PEGL group [RR 1.52, 95% CI (1.28–1.80), P < 0.00001]. Both serum potassium and serum calcium decreased in both groups after the preparation; however, meta-analysis revealed that both minerals decreased more in the NaPTab group than in the PEGL group [MD = 0.38, 95% CI (0.13–0.62), P = 0.006 for serum potassium and MD = 0.41, 95% CI (0.04–0.77), P = 0.03 for serum calcium]. Meanwhile, serum phosphorus increased in both groups after the preparation; however, levels increased more in the NaPTab group than in the PEGL group [MD 4.51, (95% CI 2.9–6.11), P < 0.00001].ConclusionsWhile NaP tablets and PEGL were shown to have a similar cleaning effect before colonoscopy, NaP tablets had improved patient tolerance. However, NaP tablets had a strong effect on serum potassium, calcium, and phosphorus levels. For patients with low potassium, low calcium, and renal insufficiency, NaP tablets should be prescribed with caution. For those at high-risk for acute phosphate nephropathy, NaP tablets should be avoided. Given the low number and quality of included studies, these conclusions will require additional verification by large high-quality studies.Systematic review registration10.37766/inplasy2023.5.0013, identifier: NPLASY202350013.

Low-lying and small-scale coral reef islands are considered extremely vulnerable to the impacts of strong storms. Wave erosion is expected to destabilize reef islands and reduce them uninhabitable on the coast. Reef island morphodynamics have found to be dominated by nearshore wave hydrodynamics on reef platforms. Due to interactions between incident waves and reef morphology, wave characteristics on reefs are highly dependent on reef size, shape and island position, especially for the scale between O(100m) and O(1000m). In this study, laboratory experiments and numerical modeling are used to investigate wave transformation on a reef platform with a complex morphology. A prototype 1:100 three-dimensional reef island and platform were constructed on a wave basin of 50-m in length, 50-m in width and 1.0-m in depth, and nine wave gauges installed on the reef platform to observe water surface elevation under high-energy wave events from three incident directions. A numerical model XBeach is employed to compute short-period waves, long-period infragravity waves, wave setup and currents. Parameters in the wave-breaking dissipation formulation are calibrated against experimental data. Due to a varying of reef slopes surround the reef platform, the optimal breaking parametric values would be disparity between one- and two-dimensional simulations. The ideal values are decided by the model performance in two-dimensional simulation for wave and current fields. Long-period infragravity waves interlaced through refraction and diffraction on the complex localized reef morphology are further examined if the multiple mechanisms can drive shoreline amplification of long waves. The wave characteristics would provide critical indicators for accurate assessments of island shoreline change and better resolve the coast vulnerability.

The need for affect (NFA), which refers to the motivation to approach or avoid emotion-inducing situations, is a valuable indicator of mental health monitoring and intervention, as well as many other applications. Traditionally, NFA has been measured using self-reports, which is not applicable in today's online scenarios due to its shortcomings in fast, large-scale assessments. This study proposed an automatic and non-invasive method for recognizing NFA based on social media behavioral data. The NFA questionnaire scores of 934 participants and their social media data were acquired. Then we run machine learning algorithms to train predictive models, which can be used to automatically identify NFA degrees of online users. The results showed that Extreme Gradient Boosting (XGB) performed best among several algorithms. The Pearson correlation coefficients between predicted scores and NFA questionnaire scores achieved 0.25 (NFA avoidance), 0.31 (NFA approach) and 0.34 (NFA total), and the split-half reliabilities were 0.66–0.70. Our research demonstrated that adolescents' NFA can be identified based on their social media behaviors, and opened a novel way of non-intrusively perceiving users' NFA which can be used for mental health monitoring and other situations that require large-scale NFA measurements.

ObjectiveThe disclosure of mental illness is a first and crucial step in alleviating stigma and promoting mental recovery. However, at present, there is a lack of research on this subject in the Chinese context. Therefore, we conducted this survey among patients with mental illness and their family members and analyzed the influencing factors.MethodsQuestionnaires were distributed to qualified patients with mental illness and their family members, who were enrolled from the inpatient departments of two major mental health centers in China. Hierarchical linear regression analysis was used to evaluate the factors affecting the disclosure of disease information by patients with mental illness and their family members.ResultsA total of 153 patients and 159 family members were included. The percentages of patients and family members who intended to disclose disease information were 34.6 and 18.2%, respectively. Regarding the benefits of being out (BBO), marital status and the number of hospitalizations explained 13.1% of the variance, and stigma explained 4.3% of the variance. Regarding the reasons for staying in (RSI), marital status and family history of mental illness explained 14.4% of the variance, and stigma explained 14.8% of the variance. In the model predicting the influencing factors of family member disclosure, stigma was a predictor of both BBO and RSI, explaining 8.1 and 8.7% of the variance, respectively.ConclusionBoth patients and their families were more reluctant than willing to disclose. Marital status, number of hospitalizations and family history of mental illness were all influencing factors of patients’ intentions to disclose disease information. Stigma is closely related to disclosure intention and plays an important role in the disclosure intentions of patients and their families. This suggests that the disclosure of disease information is complex, and many factors need to be considered. Disclosure guidelines should be tailored to individuals.

The application of transformation optics to the development of intriguing electromagnetic devices can produce weakly anisotropic or isotropic media with the assistance of quasi-conformal and/or conformal mapping, as opposed to the strongly anisotropic media produced by general mappings; however, it is typically limited to two-dimensional applications. By addressing the conformal mapping between two manifolds embedded in three-dimensional space, we demonstrate that electromagnetic surface waves can be controlled without introducing singularity and anisotropy into the device parameters. Using fruitful surface conformal parameterization methods, a near-perfect conformal mapping between smooth manifolds with arbitrary boundaries can be obtained. Illustrations of cloaking and illusions, including surface Luneburg and Eaton lenses and black holes for surface waves, are provided. Our work brings the manipulation of surface waves at microwave and optical wavelengths one step closer.

Integrated photonic reservoir computing has been demonstrated to be able to tackle different problems because of its neural network nature. A key advantage of photonic reservoir computing over other neuromorphic paradigms is its straightforward readout system, which facilitates both rapid training and robust, fabrication variation-insensitive photonic integrated hardware implementation for real-time processing. We present our recent development of a fully-optical, coherent photonic reservoir chip integrated with an optical readout system, capitalizing on these benefits. Alongside the integrated system, we also demonstrate a weight update strategy that is suitable for the integrated optical readout hardware. Using this online training scheme, we successfully solved 3-bit header recognition and delayed XOR tasks at 20 Gbps in real-time, all within the optical domain without excess delays.

It can be difficult to identify trends and perform quality control in large, high-dimensional fMRI or omics datasets. To remedy this, we develop ImageNomer, a data visualization and analysis tool that allows inspection of both subject-level and cohort-level features. The tool allows visualization of phenotype correlation with functional connectivity (FC), partial connectivity (PC), dictionary components (PCA and our own method), and genomic data (single-nucleotide polymorphisms, SNPs). In addition, it allows visualization of weights from arbitrary ML models. ImageNomer is built with a Python backend and a Vue frontend. We validate ImageNomer using the Philadelphia Neurodevelopmental Cohort (PNC) dataset, which contains multitask fMRI and SNP data of healthy adolescents. Using correlation, greedy selection, or model weights, we find that a set of 10 FC features can explain 15% of variation in age, compared to 35% for the full 34,716 feature model. The four most significant FCs are either between bilateral default mode network (DMN) regions or spatially proximal subcortical areas. Additionally, we show that whereas both FC (fMRI) and SNPs (genomic) features can account for 10-15% of intelligence variation, this predictive ability disappears when controlling for race. We find that FC features can be used to predict race with 85% accuracy, compared to 78% accuracy for sex prediction. Using ImageNomer, this work casts doubt on the possibility of finding unbiased intelligence-related features in fMRI and SNPs of healthy adolescents., Comment: 11 pages

BACKGROUND Decreased serum magnesium (Mg2+) is commonly seen in critically ill patients. Hypomagnesemia is significantly more frequent in patients with severe acute pancreatitis. Acute kidney injury (AKI) in patients with acute pancreatitis (AP) is associated with an extremely high mortality. The association underlying serum Mg2+ and AKI in AP has not been elucidated. AIM To explore the association between serum Mg2+ on admission and AKI in patients with AP. METHODS A retrospective observational study was conducted in a cohort of patients (n = 233) with AP without any renal injury before admission to our center from August 2015 to February 2019. Demographic characteristics on admission, severity score, laboratory values and in-hospital mortality were compared between patients with and without AKI. RESULTS A total of 233 patients were included for analysis, including 85 with AKI. Compared to patients without AKI, serum Mg2+ level was significantly lower in patients with AKI at admission [OR = 6.070, 95%CI: 3.374-10.921, P < 0.001]. Multivariate logistic analysis showed that lower serum Mg2+ was an independent risk factor for AKI [OR = 8.47, 95%CI: 3.02-23.72, P < 0.001]. CONCLUSION Our analysis indicates that serum Mg2+ level at admission is independently associated with the development of AKI in patients with AP and may be a potential prognostic factor.

Shizuishan is a typical exhausted resources-based city in the northern area of the Ningxia Hui autonomous region in China. In order to develop the planting industry of selenium (Se)-rich agricultural products and promote green and sustainable urban development and transformation, investigations on the quality of Se-rich land were carried out in Shizuishan City, where 7399 surface soil (0-20 cm) samples of farmlands, 30 atmospheric precipitation samples, and nine parent rocks were collected. By means of semi variogram model construction by GS

South China is a well-known grand felsic igneous rocks province. However, it is still controversial and not well understood whether the Mesozoic tectono-magmatic pattern is dominated by the subduction of the paleo-Pacific oceanic plate. In this study, we address this question by concentrating on the long-term evolutionary Guandimiao batholith, which has complex lithofacies with different formation ages and can be a superb record of the Mesozoic tectonic evolution in South China. Geochronologically, four stages of magmatism can be identified combined with previous reports: granodiorite (G1, 239 Ma), biotite monzogranite (G2-1) and two-mica monzogranite (G2-2) (230–203 Ma), granite porphyry (G3, 211–190 Ma), and lamprophyre (L4, 121 Ma). G1 and G2-1 have an affinity with I-type granite and were derived from metabasaltic to metatonalitic sources, whereas G2 and G3 show S-type granite characteristics and were derived from the para-metamorphic basement of the Cathaysia block. The L4 was derived from partial melting of garnet and spinel lherzolite and underwent mixing between Mesoproterozoic pelagic and/or terrigenous sediments and the subcontinental lithosphere mantle (SCLM) of South China. The granitoids of the Guandimiao batholith underwent intensely fractional crystallization of feldspar, Ti-bearing minerals, allanite and monazite. The zircon U–Pb dating of L4 in the Guandimiao batholith completely records the six stages of pre-Mesozoic tectonic events in the SCB. During the Mesozoic, the main body of the Guandimiao batholith (G1, G2-1 and G2-2) recorded the closure of the paleo-Tethys Ocean in the Triassic and the subsequent regional extension of the postcollision. G-3 and L4 of the Guandimiao batholith documented the transition of tectonic and dynamic regimes in the early Yanshanian and the rollback and steep subduction of the paleo-Pacific Ocean in the late Yanshanian.

Remediation of soil contaminated by mixed heavy metals and metalloids has been a major challenge in the global environmental field. To address this critical issue, we tested a new technology for simultaneous immobilization of lead (Pb) and arsenic (As) in a field contaminated soil using a microwave-assisted FeSO

The risk of soil phosphorus leaching increases in basin regions in light of large-scale use of phosphorus fertilizers because of agricultural modernization. In this study, we conducted an earth pillar simulation test on the infiltration threshold of red soil, Vaseline-coated PVC pipe, intact soil core, fine sand, and nylon filter was used for Penetration test, which covers the largest area of the Dianchi Lake Basin in China. Results showed that: 1) The contents of the total available phosphorus in algae (NaOH-P) and dissolved labile phosphorus (CaCl2-P) in red soil were consistent with the content of available phosphorus (Olsen-P) under different use patterns manifested by the law of greenhouse > open field > grassland. Grassland had the highest phosphorus sorption index (PSI), followed by the greenhouse and then by the open field. 2) The leachate under the same use pattern had the characteristics of total phosphorus (TP) > particle phosphorus (PP) > total dissolved phosphorus (TDP) > dissolved organic phosphorus (DOP) > molybdate reactive phosphorus (MRP). The TP contents in the leachates of grassland, greenhouse, and open field were 0.46, 0.61, and 0.49 mg/L, respectively. DOP, TDP, PP, and MRP had similar contents, and their distributions in the three land types were consistent with that of TP. 3) Olsen-P had a significant correlation with TP, TDP, PP, and DOP in the leachates. Olsen-P of 50 slightly influenced eutrophication. Moreover, Olsen-P of >40 and 40 had minimal influence on the environment. Olsen-P of >70.90 mg/kg and PSI of 26.09 mg/kg, the TP content in the leachate increased sharply.

Menghai is a large tea-producing county in Yunnan Province. In order to provide a scientific basis for soil improvement and precise fertilization, we studied the soil nutrient status and fertility level of tea gardens in Menghai County. In this study, soil samples from 151 tea gardens was analyzed in terms of pH, organic matter content, and nutrient elements, through field investigation and spot sampling in six towns within an area of concentrated tea gardens in Menghai County. The integrated fertility index(IFI)was also calculated to evaluate the soil nutrient status of the tea plantations. The pH of tea garden soil varied from 3.83 to 6.16, with most soil pH suitable for the growth of tea trees. The organic matter contents ranged from 20.88 g·kg-1 to 101.80 g·kg-1 and the content of organic matter was rich, reaching grade Ⅰ standard. The total nitrogen, total phosphorus, and total potassium contents in Menghai County tea gardens were high, but the supply of available nitrogen and available phosphorus were insufficient. The available potassium supply was sufficient, with only Meng'a and Menghun towns having soil with available potassium lower than the grade Ⅲ standard(6.25% and 20.00%, respectively). The integrated fertility index varied from 0.30 to 0.84, and some tea garden soils in Meng' a, Mengzhe, Gelanghe, and Bulangshan townships met the standards of grade Ⅰ or grade Ⅱ. However, the soil fertility of tea gardens in the villages and towns fell mainly in the grade Ⅲ or grade Ⅳ categories. More than 60% of tea gardens had low or medium soil fertility levels, except for the Bulangshan townships. The soil pH levels of tea gardens in Menghai County are suitable for the growth of tea trees. The contents of organic matter, total nitrogen, total phosphorus, total potassium, and available potassium in these soils are high, but the supply of available nitrogen and available phosphorus is insufficient. This highlights the need for suitable fertilization schemes.

We proposed a novel temperature-compensated multi-point strain sensing system based on cascaded FBG and optical FMCW interferometry. The former is used for simultaneous sensing of temperature and strain, and the latter is used for position information reading and multiplexing. In the experiment, a narrow linewidth laser with continuous frequency-sweeping was used as the light source. After demodulating the beat-frequency signal, the link information of the 16 m fiber was obtained, and the measured result was identical to the actual position. The measurement accuracy reached 50.15 mm, and the dynamic range was up to 22.68 dB. Meanwhile, we completed the sensing experiments for temperature range from 20 °C to 90 °C and strain range from 0 με to 7000 με. The sensitivity of the sensing system to temperature was 10.21 pm/°C, the sensitivity and accuracy to strain were as high as 1.163 pm/με and 10 με, respectively. Finally, the measured strain and temperature values were obtained using the sensing matrix. The sensing system has important practical significance in the field of quasi-distributed strain measurement.

BACKGROUND Cardiac resynchronization therapy (CRT) is a well-established therapy for patients with cardiomyopathy. CASE SUMMARY The patient underwent left bundle branch area and left ventricular (reaching the left ventricular lateral vein through the coronary sinus) pacing. The optimal CRT was performed under the right bundle branch of the patient by adjusting the optimal a-v and v-v interphases to achieve the maximal benefit of the treatment. CONCLUSION The patient was diagnosed with left bundle branch block and heart failure. A left bundle branch area pacemaker assisted in correcting the complete left bundle branch block. However, the shorter QRS wave shape after pacemaker implantation through the left bundle branch area indicated a complete right bundle branch block pattern. Hence, the left bundle branch area pacemaker is not always considered as the optimal treatment. The left bundle branch pacing with the optimization of cardiac resynchronization treatment may serve as a new CRT strategy.

Faced with the increasing colorectal cancer (CRC) cases, the interrogation of pivotal molecules in CRC appears to be vitally important. Long non-coding RNAs (lncRNAs) are well-known regulators of gene expression at transcriptional, post-transcriptional or epigenetic level, among which the competing endogenous RNA (ceRNA) network is a common way that lncRNAs exert their properties. The current study aimed to provide a new insight into improving the outcomes of CRC patients. Our study detected that ELFN1-AS1 expression was elevated in CRC tissues and cells, and ELFN1-AS1 upregulation was correlated with poor prognosis of CRC sufferers. Besides, it was viewed that ELFN1-AS1 knockdown impeded the proliferation and migration abilities as well as activated the apoptosis ability of CRC cells. In subsequence, mechanism assays also displayed that ELFN1-AS1 targeted miR-4644 to augment TRIM44 level. Finally, rescue experiments confirmed that TRIM44 took part in the ELFN1-AS1-medatied promotional influences on CRC cells proliferation and migration. In conclusion, ELFN1-AS1 exerted pro-proliferation, anti-apoptosis and pro-migration functions on CRC cells by acting as a sponge of miR-4644 to increase TRIM44 expression at mRNA and protein level, providing an additional molecule responsible for the carcinogenesis and progression for CRC.

Previous studies have shown conflicting findings regarding the relationship between maternal vitamin D deficiency (VDD) and fetal growth restriction (FGR). We hypothesised that parathyroid hormone (PTH) may be an underlying factor relevant to this potential association. In a prospective birth cohort study, descriptive statistics were evaluated for the demographic characteristics of 3407 pregnancies in the second trimester from three antenatal clinics in Hefei, China. The association of the combined status of vitamin D and PTH with birth weight and the risk of small for gestational age (SGA) was assessed by a multivariate linear and binary logistic regression. We found that declined status of 25-hydroxyvitamin D is associated with lower birth weight (for moderate VDD: adjusted β = −49·4 g, 95 % CI −91·1, −7·8, P < 0·05; for severe VDD: adjusted β = −79·8 g, 95 % CI −127·2, −32·5, P < 0·01), as well as ascended levels of PTH (for elevated PTH: adjusted β = −44·5 g, 95 % CI −82·6, −6·4, P < 0·05). Compared with the non-VDD group with non-elevated PTH, pregnancies with severe VDD and elevated PTH had the lowest neonatal birth weight (adjusted β = −124·7 g, 95 % CI −194·6, −54·8, P < 0·001) and the highest risk of SGA (adjusted risk ratio (RR) = 3·36, 95 % CI 1·41, 8·03, P < 0·01). Notably, the highest risk of less Ca supplementation was founded in severe VDD group with elevated PTH (adjusted RR = 4·67, 95 % CI 2·78, 7·85, P < 0·001). In conclusion, elevated PTH induced by less Ca supplementation would further aggravate the risk of FGR in pregnancies with severe VDD through impaired maternal Ca metabolism homoeostasis.

A configurable silicon modulator is proposed, consisting of a phase modulator embedded in a tunable Mach-Zehnder interferometer. We present the analytical analysis and numerical simulations, as well as the experimental results for carrier suppressed intensity modulation.

Additional file 3: Polygenic risk score methodology and reclassification metrics.

The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion. Method: We developed new models using multi-view variational autoencoder (MVAE) for feature representation learning and a product of expert (PoE) model for multi-view information fusion. We applied the proposed models to an in-house Louisiana Osteoporosis Study (LOS) cohort with 931 male subjects, including 345 African Americans and 586 Caucasians. With an analytical solution of the product of Gaussian distribution, we adopted variational inference to train the designed MVAE-PoE model to perform common latent feature extraction. We performed genome-wide association studies (GWAS) to select 256 genetic variants with the lowest p-values for each proximal femoral strength and integrated whole genome sequence (WGS) features and DXA-derived imaging features to predict proximal femoral strength. Results: The best prediction model for fall fracture load was acquired by integrating WGS features and DXA-derived imaging features. The designed models achieved the mean absolute percentage error of 18.04%, 6.84% and 7.95% for predicting proximal femoral fracture loads using linear models of fall loading, nonlinear models of fall loading, and nonlinear models of stance loading, respectively. Compared to existing multi-view information fusion methods, the proposed MVAE-PoE achieved the best performance. Conclusion: The proposed models are capable of predicting proximal femoral strength using WGS features and DXA-derived imaging features. Though this tool is not a substitute for FEA using QCT images, it would make improved assessment of hip fracture risk more widely available while avoiding the increased radiation dosage and clinical costs from QCT., Comment: 16 pages, 3 figures

Additional file 1: Figures S1–S17 in.docx format are included in the supplementary information.

Many statistical machine approaches could ultimately highlight novel features of the etiology of complex diseases by analyzing multi-omics data. However, they are sensitive to some deviations in distribution when the observed samples are potentially contaminated with adversarial corrupted outliers (e.g., a fictional data distribution). Likewise, statistical advances lag in supporting comprehensive data-driven analyses of complex multi-omics data integration. We propose a novel non-linear M-estimator-based approach, "robust kernel machine regression (RobKMR)," to improve the robustness of statistical machine regression and the diversity of fictional data to examine the higher-order composite effect of multi-omics datasets. We address a robust kernel-centered Gram matrix to estimate the model parameters accurately. We also propose a robust score test to assess the marginal and joint Hadamard product of features from multi-omics data. We apply our proposed approach to a multi-omics dataset of osteoporosis (OP) from Caucasian females. Experiments demonstrate that the proposed approach effectively identifies the inter-related risk factors of OP. With solid evidence (p-value = 0.00001), biological validations, network-based analysis, causal inference, and drug repurposing, the selected three triplets ((DKK1, SMTN, DRGX), (MTND5, FASTKD2, CSMD3), (MTND5, COG3, CSMD3)) are significant biomarkers and directly relate to BMD. Overall, the top three selected genes (DKK1, MTND5, FASTKD2) and one gene (SIDT1 at p-value= 0.001) significantly bond with four drugs- Tacrolimus, Ibandronate, Alendronate, and Bazedoxifene out of 30 candidates for drug repurposing in OP. Further, the proposed approach can be applied to any disease model where multi-omics datasets are available., Comment: 19 pages, 10 figures

Additional file 5: Additional figures. Figure S1. Correlation matrix of PRS methods in tuning dataset, White British population. Figure S2. Calibration and recalibration plots in UK Biobank testing dataset.

Additional file 1: Variable definitions and data protocol.

Additional file 1: Fig. S1. Analysis of Sensitivity and publication bias in meta-analysis. A Sensitivity analysis of selected datasets. B A Begg’s funnel plot with 95% confidence limits.

Additional file 2: Variable definition codes. Table S1. Definition of Codes for Variables in UK Biobank. Table S2. Definition of Codes for Coronary Artery Disease.

Additional file 4: Additional tables and detailed results. Table S3. AUC results for individual PRS methods trained in European meta-analysis dataset. Table S4. AUC results for individual PRS methods trained in Japan Biobank dataset. Table S5. Descriptive characteristics of tuning dataset, White British population. Table S6. Descriptive characteristics of testing dataset, White British population. Table S7. Descriptive characteristics of excluded participants, White British population. Table S8. Tuning parameter selection for PRS with CAD in European meta-analysis dataset. Table S9. Tuning parameter selection for PRS with CAD in Japan Biobank dataset. Table S10. C-statistic results for integrated PRS method stratified by GWAS dataset, White British population. Table S11. C-statistic results for individual PRS methods in CAD for testing dataset trained in European meta-analysis, White British population. Table S12. C-statistic results for individual PRS methods in CAD for testing dataset trained in Japan Biobank dataset, White British population. Table S13. Risk reclassification metrics in White British population stratified by gender and age group. Table S14. Descriptive characteristics of tuning dataset, African population. Table S15. Descriptive characteristics of testing dataset, African population. Table S16. Descriptive characteristics of excluded participants, African population. Table S17. C-statistic results for integrated PRS method stratified by GWAS dataset, African population. Table S18. NRI and IDI metrics, African Population. Table S19. Descriptive characteristics of tuning dataset, East Asian population. Table S20. Descriptive characteristics of testing dataset, East Asian population. Table S21. Descriptive characteristics of excluded participants, East Asian population. Table S22. C-statistic results for integrated PRS method, East Asian population. Table S23. C-statistic results for integrated PRS method stratified by GWAS dataset, East Asian population. Table S24. NRI and IDI metrics, East Asian population.

Transactional and relational contract breach occur when organizations fail to deliver on promised personal benefits for employees and are associated with negative behaviors reciprocating such mistreatment. However, recent research suggests that ideological contract breach, a unique form of contract breach, may yield constructive behaviors because it is not organizations’ direct personal mistreatment of employees, but organizations’ abandonment of a valued cause to benefit a third party. Such an interesting prediction goes beyond the dominant social-exchange framework, which mainly forecasts destructive responses to breach. In this research, we develop a novel self-affirmation model to explain how ideological contract breach results in counterintuitive positive outcomes. In a hospital field study among medical professionals (N = 362) and their supervisors (N = 129), we found that ideological contract breach induces employees’ rumination about the breach, which in turn prompts them to self-affirm core values at work. This self-affirmation eventually spurs proactive serving behavior and self-improvement behavior to compensate for the breached ideology. Professional identification enhances this self-affirmation process.

Time evolution characteristics of spectrum and temperature of lightning discharge plasma: supplemental document

Additional file 2: Tables S1–S12 in.docx format are included in the supplementary information.

The safety of drinking and irrigation water is an issue of great concern worldwide. The rational development and utilization of water resources are vital for the economic and societal stability of Altay, an extremely arid area. In this study, three types of water samples (25 river waters, 10 groundwaters, 6 lake waters) were collected from main rivers and lakes in Altay and analyzed for electrical conductivity, total dissolved solids, pH, major ions (i.e., K

Euphorbia motuogensis M. T. Li, X. Z. Lan, H. P. Deng & W. L. Zheng, sp. nov. (Figs. 1���2) Type:��� CHINA. Tibet: Motuo, the fourth national survey on Chinese materia medica resources, coniferous forest, meadows; 29��41���46.4���N, 95��32���03.95���E, ca. 2600m a.s.l., 2 July 2016, M. T . Li & X. Z . Lan 542624150702036 LY (holotype SWU). Diagnosis:��� Euphorbia motuogensis is similar to Euphorbia sikkimensis, but it differs by its pileous stems, secondary involucral leaves absent, 3 yellow green cyathophylls, margin entire or concave in the middle and five similar glands. Herbs, 20���80 cm tall. Root terete, 20���40 cm �� 3���5 mm. Stems single or clustered, 3���7 mm thick, mostly unbranched, pileous. Leaves alternate, all but lowermost uniform in size; stipules absent; petiole very short to almost absent; leaf blade ovate-oblong to elliptic, 3���6 �� 1.5���2.5 cm, glabrous, base attenuate-cuneate, margin entire, apex obtuse; midrib prominent on both surfaces, lateral veins slender, lateral veins not reaching margin. Inflorescence a terminal pseudumbel; primary involucral leaves usually one round, 5 pecies, even two rounds, the second round involucral leaves usually 3, green, leaves long elliptic to ovate-elliptic, somewhat unequal, 3���4 �� 1.5���2.5 cm, base attenuatecuneate, apex obtuse, primary rays 7 (8), 2���4 cm; secondary involucral leaves absent. Cyathophylls 3, yellow green, broad ovate, 1���1.4 �� 1���1.2 cm, margin entire or concave in the middle, base and apex rounded. Cyathium; involucre campanulate, ca. 3.5���5�� 5���5.5mm, 5 lobes, rounded; glands 5, rounded, densely pilose on the inside. Male flowers many, most exserted from involucre. Female flower: ovary pedicellate and extended out of cup, smooth, glabrous; styles free, style arms slightly 2-lobed. Capsule globose, ca. 5 �� 5 mm, smooth, glabrous. Ovary 3-loculed with parietal placentation. Fl. and fr. Jun.���Oct. Etymology:��� The specific epithet refers to Motuo, Tibet, China, the type locality of the new species. Distribution and Habitat:��� Euphorbia motuogensis is currently known only from its type locality, i.e. the fourth national survey on Chinese materia medica resources. It grows at coniferous forest and meadows at an elevation of ca. 2600 m a.s.l. Phenology:��� Flowering and fruiting were observed in June to October. Additionally specimens examined (paratypes):��� CHINA. Tibet: Motuo, M . T. Li, X. Z . Lan 542624150702037 LY (SWU), Published as part of Li, Man-Ting, Lan, Xiao-Zhong, Zuo, You-Wei & Deng, Hong-Ping, 2021, Euphorbia motuogensis (Euphorbiaceae), a new species from Xizang, China, pp. 107-116 in Phytotaxa 527 (2) on page 108, DOI: 10.11646/phytotaxa.527.2.3, http://zenodo.org/record/5744423

Automatic CT segmentation of proximal femur is crucial for the diagnosis and risk stratification of orthopedic diseases; however, current methods for the femur CT segmentation mainly rely on manual interactive segmentation, which is time-consuming and has limitations in both accuracy and reproducibility. In this study, we proposed an approach based on deep learning for the automatic extraction of the periosteal and endosteal contours of proximal femur in order to differentiate cortical and trabecular bone compartments. A three-dimensional (3D) end-to-end fully convolutional neural network, which can better combine the information between neighbor slices and get more accurate segmentation results, was developed for our segmentation task. 100 subjects aged from 50 to 87 years with 24,399 slices of proximal femur CT images were enrolled in this study. The separation of cortical and trabecular bone derived from the QCT software MIAF-Femur was used as the segmentation reference. We randomly divided the whole dataset into a training set with 85 subjects for 10-fold cross-validation and a test set with 15 subjects for evaluating the performance of models. Two models with the same network structures were trained and they achieved a dice similarity coefficient (DSC) of 97.87% and 96.49% for the periosteal and endosteal contours, respectively. To verify the excellent performance of our model for femoral segmentation, we measured the volume of different parts of the femur and compared it with the ground truth and the relative errors between predicted result and ground truth are all less than 5%. It demonstrated a strong potential for clinical use, including the hip fracture risk prediction and finite element analysis.

Debye-screening effects on the electron-impact excitation (EIE) processes for the dipole-allowed transition 1s2 1 S → 1s2p 1P in He-like Al11+ and Fe24+ ions are investigated using the fully relativistic distorted-wave methods with the Debye–Hückel (DH) model potential. Debye-screening effects on the continuum-bound (CB) interaction and target ion are discussed, both of which result in reduction of EIE cross sections. This reduction due to screening on the CB interaction is dominant. The non-spherical and spherical DH potentials are adopted for considering the screening effect on the CB interaction. It is found that the spherical DH potential could significantly overestimate the influence of plasma screening on EIE cross sections for multielectron He-like ions.

In this study, we analyzed several pollution episodes that occurred in the autumn and winter of 2018-2019 using multiple methods including the hierarchical clustering analysis, backward trajectory, and potential source contribution analysis based on monitored air quality and meteorological data. Bengbu, being a representative city to the north of the Yangtze River Delta (YRD) region and located in a heavily polluted area during these two pollution processes, is the focus of this work. The results indicated that the northern part of the YRD region is affected because of unfavorable meteorological conditions such as weak ground pressure, high humidity, low temperature, low wind speeds, and regional transport. The regional pollution processes over the YRD region in the autumn and winter seasons exhibit characteristics of wide influence and long duration with mainly two types of pollution:regional transport and intra-regional accumulation. During the two selected pollution episodes, the average PM

Purpose: Proximal femur image analyses based on quantitative computed tomography (QCT) provide a method to quantify the bone density and evaluate osteoporosis and risk of fracture. We aim to develop a deep-learning-based method for automatic proximal femur segmentation. Methods and Materials: We developed a 3D image segmentation method based on V-Net, an end-to-end fully convolutional neural network (CNN), to extract the proximal femur QCT images automatically. The proposed V-net methodology adopts a compound loss function, which includes a Dice loss and a L2 regularizer. We performed experiments to evaluate the effectiveness of the proposed segmentation method. In the experiments, a QCT dataset which included 397 QCT subjects was used. For the QCT image of each subject, the ground truth for the proximal femur was delineated by a well-trained scientist. During the experiments for the entire cohort then for male and female subjects separately, 90% of the subjects were used in 10-fold cross-validation for training and internal validation, and to select the optimal parameters of the proposed models; the rest of the subjects were used to evaluate the performance of models. Results: Visual comparison demonstrated high agreement between the model prediction and ground truth contours of the proximal femur portion of the QCT images. In the entire cohort, the proposed model achieved a Dice score of 0.9815, a sensitivity of 0.9852 and a specificity of 0.9992. In addition, an R2 score of 0.9956 (p

In recent years, a comprehensive study of multi-view datasets (e.g., multi-omics and imaging scans) has been a focus and forefront in biomedical research. State-of-the-art biomedical technologies are enabling us to collect multi-view biomedical datasets for the study of complex diseases. While all the views of data tend to explore complementary information of a disease, multi-view data analysis with complex interactions is challenging for a deeper and holistic understanding of biological systems. In this paper, we propose a novel generalized kernel machine approach to identify higher-order composite effects in multi-view biomedical datasets. This generalized semi-parametric (a mixed-effect linear model) approach includes the marginal and joint Hadamard product of features from different views of data. The proposed kernel machine approach considers multi-view data as predictor variables to allow more thorough and comprehensive modeling of a complex trait. The proposed method can be applied to the study of any disease model, where multi-view datasets are available. We applied our approach to both synthesized datasets and real multi-view datasets from adolescence brain development and osteoporosis study, including an imaging scan dataset and five omics datasets. Our experiments demonstrate that the proposed method can effectively identify higher-order composite effects and suggest that corresponding features (genes, region of interests, and chemical taxonomies) function in a concerted effort. We show that the proposed method is more generalizable than existing ones., 19 pages, 9 figures, and Under review