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As an alternative method for the compensated neutron porosity measurement method, the neutron-gamma porosity measurement method is widely used in cased holes. However, the neutron-gamma porosity measurement method has some problems, such as the lack of detailed theoretical analysis and low sensitivity in high-porosity formations. The purpose of this paper is to clarify the theory of neutron-gamma porosity measurement, improve the measurement sensitivity, and eliminate the effects of environmental factors. Based on the neutron diffusion theory and the gamma transport theory, the distribution of capture gamma rays is described. A new neutron-gamma porosity measurement method is developed based on inelastic and capture gamma-ray distribution. The applicability of the new method in different environments is analyzed using the Monte Carlo method, and the effectiveness of this method is verified using the synthetic model. The results indicate that the capture gamma-ray ratio is only related to the source-detector distance, gamma-ray attenuation length, and neutron migration length. By combining density, different neutron cross sections, inelastic gamma-ray count ratio, and capture gamma-ray count ratio, the parameter secondary gamma-ray hydrogen index (SGH) related to hydrogen index can be extracted. The dynamic range of SGH is much higher than thermal neutron count ratio and the capture gamma-ray count ratio. The errors in porosity calculation by this method under different borehole and lithologic conditions are generally less than 2 pu. The calculation error of this method is close to that of the compensated neutron porosity measurement method. In addition, the applicability of the new method is analyzed without density data, and the results indicate that the calculation results are basically consistent with the results of calculation with density data. The new method has great potential for extensive applications in cased holes or open holes as an alternative for the compensated neutron porosity logging measurement method.

BACKGROUND: The main objective of this study was to predict the status of blood and the occurrence of lower limb deep vein thrombosis (DVT) after total knee arthroplasty(TKA) by means of mean platelet volume (MPV) combined with thromboelastography (TEG). METHODS: We collected 180 patients who underwent unilateral total knee arthroplasty between May 2015 and March 2022, and the patients were divided into DVT group and control group according to whole-leg ultrasonography on the seventh postoperative day. Blood count and TEG were performed on the day before surgery, the first day after surgery and the seventh day respectively. Multifactorial analysis was used to investigate whether the relevant parameters were independent predictors of DVT after TKA. RESULTS: MPV has the strongest correlation with the maximum amplitude (MA), followed by alpha-angle; MPV and alpha-angle on the first postoperative day are independent predictors of DVT. MPV in patients with thrombosis tends to rise and then fall in the perioperative period. The optimal threshold for MPV to predict thrombosis is 10.85 fL and the area under the ROC curve is 0.694, The area under the ROC curve increases to 0.815 using MPV combined with alpha-angle. In addition, MA, α-angle, composite coagulation index (CI) and MPV were all statistically higher in the DVT group than in the control group (p < 0.001). CONCLUSION: MPV is a predictor of DVT after TKA. It can reflect the hypercoagulable state of blood after surgery; Combination of MPV and alpha-angle on the first day after surgery in patients with TKA improves predictive power of DVT.

SUMMARY The accurate estimation of temperature distribution in the earth's crust and modelling of heat-related processes in geodynamics requires knowledge of the thermal conductivity of plutonic rocks. This study compiled an extensive data set of 530 representative plutonic rock samples, including thermal conductivity, major oxide composition and (for two subsets of data) modal mineralogy. For the first time, three machine learning algorithms (ML; i.e. support vector regression, random forest and extreme gradient boosting) were employed to estimate the thermal conductivity of plutonic rocks using the major oxide composition feature as input variables. The performance of these ML-based models was evaluated against a geochemically compositional model and eight mineral-driven physically based empirical mixing models. Results show that the means of predicted thermal conductivity by the ML-based models and the geochemically compositional model are not significantly different from the measured thermal conductivity at a significance level of 5 per cent. However, the ML-based models outperformed the best-performing non-ML model, the geochemically compositional model. The highest prediction accuracy was achieved by extreme gradient boosting, which reduced the mean absolute percentage error and root mean square error by more than 50 per cent. Furthermore, SiO2 is confirmed as the most important independent variable, followed by Al2O3, TiO2, CaO and K2O. The turning point observed in the thermal conductivity trend with SiO2 wt per cent may be primarily attributed to variations in mineral composition within the subgroup of igneous rock types classified based on SiO2 wt per cent. This study explores, for the first time, the use of ML algorithms to estimate the thermal conductivity of plutonic rocks from their major oxide composition.

Facility Relocation (FR), which is an effort to reallocate the placement of facilities to adapt to the changes of urban planning, has remarkable impact on many areas. Existing solutions fail to guarantee the result quality on relocating k > 1 facilities. As k -FR problem is NP-complete and is not submodular or non-decreasing, traditional greedy algorithm cannot be directly applied. We propose to transform k -FR into another facility placement problem, which is submodular and non-decreasing. We prove that the optimal solutions of both problems are equivalent. Accordingly, we present the first approximate solution toward the k -FR, FR2FP. Our extensive comparison over both FR2FP and the state-of-the-art solution shows that FR2FP, although it provides approximation guarantee, cannot necessarily given superior results. The comparison motivates us to present an advanced approximate solution, FR2FP-ex. Moreover, based on Lagrangian relaxation, we develop an algorithm that can adjust the approximation ratio. Extensive experiments verified that, FR2FP-ex demonstrates the best result quality, and it is very close to the optimal solution. In addition, we also unveil the scenarios when the state-of-the-art would fail. We further generalize the k -FR problem, considering the budget for relocation and the cost of each facility. We also present corresponding approximate solutions toward the new problem and prove the approximation ratio.

Goals: Ion transporters play an important regulatory role in the progression and development of breast cancer (BC). Slc26a9 is a member of the Slc26a anion transporter family, which is mainly involved in regulating the secretion of chloride ions and bicarbonate, but the role of Slc26a9 in HER2-positive BC is still unclear. Methods: Tissue microarray and BC cell line were used to detect the expression level of Slc26a9 and its clinical relevance. By changing the expression level of Slc26a9 gene in BC cells, the effect of Slc26a9 gene on the biological behavior of BC cells and its related molecular mechanism were discussed. Results: We found that the expression of Slc26a9 was significantly upregulated in BC compared with adjacent tissues, and the upregulated Slc26a9 was associated with TNM staging and poor prognosis in BC patients. In addition, the expression of Slc26a9 was significantly upregulated in HER2-positive BC compared with HER2-negative BC, and similar results were obtained in BC cell lines, with Slc26a9 was the highest expression in HER2-enriched SKBR3 cells. Functionally, the proliferation, migration, invasion and anti-apoptotic abilities of SKBR3 cells were significantly inhibited after silencing Slc26a9, and tumorigenesis and metastasis were significantly inhibited in vivo. On the contrary, overexpression of Slc26a9 resulted in the opposite result. Mechanistically, overexpression of Slc26a9 activated the PI3K/AKT/mTOR signaling pathway, the key signaling pathway implicated in HER2-positive breast carcinogenesis, and promoted the expression of downstream proliferation related genes CCND1 (Cyclin D1) and c-Myc, and downregulated the expression of apoptosis related genes Caspase9, apoptosis-inducing factor (AIF) and endonuclease G (Endo G), indicating the simultaneous inhibition of caspase dependent and independent apoptosis pathway. At the same time, accompanied by changes in markers of epithelial-mesenchymal transition (EMT), including downregulation of E-cadherin and ZO-1, and upregulation of N-cadherin and Fibronectin, and SKBR3 cells changed from epithelioid morphology to mesenchymal morphology. In addition, immunofluorescence and protein nucleoplasm separation experiments showed that Slc26a9 upregulated the expression of HER2 and co-localized with HER2 in the nucleus. Co-immunoprecipitation experiments proved that Slc26a9 interacted with HER2. Furthermore, trastuzumab downregulated the expression of Slc26a9 by targeting HER2 in SKBR3 cells. Moreover, when Slc26a9 was overexpressed, the inhibitory effect of trastuzumab on HER2 was partially reversed, and we also verified the PI3K/AKT/mTOR signaling pathway. Not only that, we found that Slc26a9 was significantly upregulated in drug-resistant cell lines relative to parental cells by constructing SKBR3 drug-resistant cell lines, indicating that Slc26a9 expression was significantly correlated with chemotherapy resistance in HER2-positive BC. Conclusion(s): Slc26a9 may interact with HER2 in the form of molecular chaperones to activate PI3K/AKT/mTOR signaling pathway to promote the progression and development of HER2-positive BC and be associated with chemotherapy resistance, but the precise molecular mechanism needs further exploration. Conflict of Interest: No significant relationships. Citation Format: Zhengxing Zhou, Zhiyuan Ma, Xuemei Liu, Chengmin Zhang, Hu Wang, Renmin Mu, Xiaoming Cheng, Biguang Tuo, Taolang Li. Slc26a9 cooperates with HER2 to regulate the progression and development of HER2-positive breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-26-19.

Background. Recent studies have shown that Ras-like without CAAX2 (RIT2) polymorphism is a susceptible factor for Parkinson’s disease (PD) and autism spectrum disorder (ASD). SNP rs12456492 and rs16976358 show the emerging evidence of increased risk of PD and ASD, respectively. A meta-analysis examining the relationship between rs12456492 and PD was reported, but the association between rs16976358 and ASD has not been investigated. Methods. We searched literature from the databases PubMed, Embase, Google Scholar, ScienceDirect, EBSCOhost, OVID, Web of Science, and Wiley up to February 2021. Three studies including 1160 ASD cases and 1367 controls were eventually enrolled in the meta-analysis based on strict inclusion and exclusion criteria. Results. All genetics models indicate a significant association between rs16976358 polymorphism and ASD susceptibility (C vs. T: p = 0.001 ; CC vs. TT: p = 0.001 ; CT vs. TT: p = 0.009 ; CC+CT vs. TT: p = 0.001 ; CC vs. CT+TT: p = 0.001 ; TT+CC vs. CT: p = 0.013 ). The results of sensitivity analysis and publication bias of Begg’s and Egger’s tests were stable in the models of allele (C vs. T), codominant (CC vs. TT), dominant (CC+CT vs. TT), and recessive (CC vs. CT+TT). Conclusions. Our meta-analysis exhibits that the allele C, CC, and CT genotyping of rs16976358 suggest the risk for ASD, but additional studies using a large sample size and ethnically diverse populations need to be included in the future.

Reservoir landslide is a common geological disaster during the operation of hydropower projects. The fluctuation of reservoir water level is an important factor that induces slope instability. The natural slope will gradually lose stability under the rapid rise and fall of reservoir water level. A variety of landslide examples show that, on the premise of not suffering from extreme environmental conditions, the reservoir landslide often occurs after the rapid fluctuation of the reservoir water level for a period of time, and there is a certain time difference between its instability failure and the rapid rise and fall of the reservoir water level. In order to study the hysteresis effect between the stability change of the reservoir slope and the fluctuation of the reservoir water level, taking the Chana landslide in the reservoir area of Longyangxia Hydropower Station as an example, combining the field survey, geological survey data, and the actual change of the reservoir water level, the finite element simulation software is used to restore the actual working condition, and the research is carried out from three aspects of slope seepage field, displacement field, and stability. The results show the following: (1) The hysteresis of slope seepage change during the rising period of reservoir water level is more obvious than that during the falling period of reservoir water level. The deformation potential of Chana landslide is greater during the falling period of reservoir water level, while the deformation is restrained during the rising period of reservoir water level. (2) The incremental displacement simulation results of Chana landslide show that there are deformation incubation period and deformation release period of Chana landslide. The deformation incubation period occurs during the rapid rise and fall of reservoir water level, and the deformation release period occurs during the stable change of reservoir water level. (3) The incremental displacement produced during the deformation release period of the slope is large, but the slope remains stable, which reflects the existence of the internal antisliding mechanism of the landslide from the side. (4) The stability coefficient of Chana landslide changes greatly during the drawdown period. When the drawdown rate of water level is kept at 0.03~0.07 m/d, the stability coefficient of Chana landslide changes slightly and the slope is relatively stable.

To improve the ride comfort of the cab of construction machinery and reduce the harm of vibration to the driver, a nonlinear lumped parameter model of passive hydraulic damping rubber mount (PHDRM) is first proposed. The nonlinearity of multi-inertial tracks is fully considered. Then, the global FE (finite element) fluid-solid coupling model of the isolator is developed in ABAQUS. The multi-field coupling solution and a joint simulation mode are employed in this paper. Meanwhile, the rubber element and inertial track parameters are identified respectively. Finally, multiple sets of dynamic performance experiments are performed on the different PHDRM samples. The experiment results indicate that the simulation results for two modeling methods of the vibration isolation system are consistent with the experimental datum. The modeling approaches have both reliability and accuracy under larger amplitude excitation at low frequency. Furthermore, the effects of different rubber elements and inertial track of PHDRM on low-frequency dynamic characteristics under larger amplitude are investigated and discussed, respectively. The experimental outcomes also provide a practical reference value for nonlinear modeling method research and dynamic performance analysis of PHDRM with complex structures further.

The advancement of secure communication and identity verification fields has significantly increased through the use of deep learning techniques for data hiding. By embedding information into a noise-tolerant signal such as audio, video, or images, digital watermarking and steganography techniques can be used to protect sensitive intellectual property and enable confidential communication, ensuring that the information embedded is only accessible to authorized parties. This survey provides an overview of recent developments in deep learning techniques deployed for data hiding, categorized systematically according to model architectures and noise injection methods. The objective functions, evaluation metrics, and datasets used for training these data hiding models are comprehensively summarised. Additionally, potential future research directions that unite digital watermarking and steganography on software engineering to enhance security and mitigate risks are suggested and deliberated. This contribution furthers the creation of a more trustworthy digital world and advances Responsible AI.

A multi-ratiometric fluorescence sensor was designed for the sensing of the anthrax biomarker based on a bimetallic lanthanide metal–organic framework.

The purpose of this meta-analysis was to identify if patient-specific instrumentation (PSI) could increase the accuracy of the correction in high tibial osteotomy (HTO) and to explore the assessment indices and the necessity of using a PSI in HTO. A systematic search was carried out using online databases. A total of 466 patients were included in 11 papers that matched the inclusion criteria. To evaluate the accuracy of PSI-assisted HTO, the weight bearing line ratio (WBL%), hip-knee-ankle angle (HKA), mechanical medial proximal tibial angle (mMPTA), and posterior tibial slope angle (PTSA) were measured preoperatively and postoperatively and compared to the designed target values. Statistical analysis was performed after strict data extraction with Review Manager (version 5.4). Significant differences were detected in WBL% (MD = -36.41; 95% CI: -42.30 to -30.53; p 0.00001), HKA (MD = -9.95; 95% CI: -11.65 to -8.25; p 0.00001), and mMPTA (MD = -8.40; 95% CI:-10.27 to -6.53; p 0.00001) but not in PTSA (MD = 0.34; 95% CI: -0.59 to 1.27; p = 0.47) between preoperative and postoperative measurements. There was no significant difference between the designed target values and the postoperative correction values of HKA (MD = 0.14; 95% CI: -0.19 to 0.47; p = 0.41) or mMPTA (MD = 0.11; 95% CI -0.34 to 0.55; p = 0.64). The data show that 3D-based planning of PSI for HTO is both accurate and safe. WBL%, HKA, and mMPTA were the optimal evaluation indicators of coronal plane correction. Sagittal correction is best evaluated by the PTSA. The present study reports that PSI is accurate but not necessary in typical HTO.

In 2019, a new coronavirus was identified that has caused significant morbidity and mortality worldwide. Like all RNA viruses, severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) evolves over time through random mutation resulting in genetic variations in the population. Although the currently approved coronavirus disease 2019 vaccines can be given to those over 5 years of age and older in most countries, strikingly, the number of people diagnosed positive for SARS-Cov-2 is still increasing. Therefore, to prevent and control this epidemic, early diagnosis of infected individuals is of great importance. The current detection of SARS-Cov-2 coronavirus variants are mainly based on reverse transcription-polymerase chain reaction. Although the sensitivity of reverse transcription-polymerase chain reaction is high, it has some disadvantages, for example, multiple temperature changes, long detection time, complicated operation, expensive instruments, and the need for professional personnel, which brings considerable inconvenience to the early diagnosis of this virus. This review comprehensively summarizes the development and application of various current detection technologies for novel coronaviruses, including isothermal amplification, CRISPR-Cas detection, serological detection, biosensor, ensemble, and microfluidic technology, along with next-generation sequencing. Those findings offer us a great potential to replace or combine with reverse transcription-polymerase chain reaction detection to achieve the purpose of allowing predictive diagnostics and targeted prevention of SARS-Cov-2 in the future.

Radiation enteritis (RE) is a prevalent complication of radiotherapy for pelvic malignant tumors, characterized by severe intestinal epithelial destruction and progressive submucosal fibrosis. However, little is known about the pathogenesis of this disease and so far, there is no specific targeted therapy. Here, we report that CXCL16 is up-regulated in the injured intestinal tissues of RE patients and in a mouse model. Genetic deletion of Cxcl16 mitigates fibrosis and promotes intestinal stem cell-mediated epithelial regeneration after radiation injury in mice. Mechanistically, CXCL16 functions on myofibroblasts through its receptor CXCR6 and activates JAK3/STAT3 signaling to promote fibrosis, and meanwhile to transcriptionally modulate the levels of BMP4 and HGF in myofibroblasts. Moreover, we find that CXCL16 and CXCR6 auto- and cross-regulate themselves in positive feedback loops. Treatment with CXCL16 neutralizing monoclonal antibody attenuates fibrosis and improves the epithelial repair in RE mouse model. Our findings emphasize the important role of CXCL16 in the progression of RE, and suggest that CXCL16 signaling could be a potential therapeutic target for RE. This article is protected by copyright. All rights reserved.

Parkinson's disease (PD) is characterized by the progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc). In this study, we generated a transgenic model by crossing germline Parkin–/–mice with PolgAD257Amice, an established model of premature aging and mitochondrial stress. We hypothesized that loss of Parkin–/–in PolgAD257A/D257Amice would exacerbate mitochondrial dysfunction, leading to loss of dopamine neurons and nigral-striatal specific neurobehavioral motor dysfunction. We found that aged Parkin–/–/PolgAD257A/D257Amale and female mice exhibited severe behavioral deficits, nonspecific to the nigral-striatal pathway, with neither dopaminergic neurodegeneration nor reductions in striatal dopamine. We saw no difference in expression levels of nuclear-encoded subunits of mitochondrial markers and mitochondrial Complex I and IV activities, although we did observe substantial reductions in mitochondrial-encoded COX41I, indicating mitochondrial dysfunction as a result of PolgAD257A/D257AmtDNA mutations. Expression levels of mitophagy markers LC3I/LC3II remained unchanged between cohorts, suggesting no overt mitophagy defects. Expression levels of the parkin substrates, VDAC, NLRP3, and AIMP2 remained unchanged, suggesting no parkin dysfunction. In summary, we were unable to observe dopaminergic neurodegeneration with corresponding nigral-striatal neurobehavioral deficits, nor Parkin or mitochondrial dysfunction in Parkin–/–/PolgAD257A/D257Amice. These findings support a lack of synergism of Parkin loss on mitochondrial dysfunction in mouse models of mitochondrial deficits.SIGNIFICANCE STATEMENTProducing a mouse model of Parkinson's disease (PD) that is etiologically relevant, recapitulates clinical hallmarks, and exhibits reproducible results is crucial to understanding the underlying pathology and in developing disease-modifying therapies. Here, we show that Parkin–/–/PolgAD257A/D257Amice, a previously reported PD mouse model, fails to reproduce a Parkinsonian phenotype. We show that these mice do not display dopaminergic neurodegeneration nor nigral-striatal-dependent motor deficits. Furthermore, we report that Parkin loss does not synergize with mitochondrial dysfunction. Our results demonstrate that Parkin–/–/PolgAD257A/D257Amice are not a reliable model for PD and adds to a growing body of work demonstrating that Parkin loss does not synergize with mitochondrial dysfunction in mouse models of mitochondrial deficits.