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Abstract Background The detection and management of intracranial aneurysms (IAs) are vital to prevent life-threatening complications like subarachnoid hemorrhage (SAH). Artificial Intelligence (AI) can analyze medical images, like CTA or MRA, spotting nuances possibly overlooked by humans. Early detection facilitates timely interventions and improved outcomes. Moreover, AI algorithms offer quantitative data on aneurysm attributes, aiding in long-term monitoring and assessing rupture risks. Methods We screened four databases (PubMed, Web of Science, IEEE and Scopus) for studies using artificial intelligence algorithms to identify IA. Based on algorithmic methodologies, we categorized them into classification, segmentation, detection and combined, and then their merits and shortcomings are compared. Subsequently, we elucidate potential challenges that contemporary algorithms might encounter within real-world clinical diagnostic contexts. Then we outline prospective research trajectories and underscore key concerns in this evolving field. Results Forty-seven studies of IA recognition based on AI were included based on search and screening criteria. The retrospective results represent that current studies can identify IA in different modal images and predict their risk of rupture and blockage. In clinical diagnosis, AI can effectively improve the diagnostic accuracy of IA and reduce missed detection and false positives. Conclusions The AI algorithm can detect unobtrusive IA more accurately in communicating arteries and cavernous sinus arteries to avoid further expansion. In addition, analyzing aneurysm rupture and blockage before and after surgery can help doctors plan treatment and reduce the uncertainties in the treatment process.

Abstract Patients who suffer from sepsis typically experience acute lung injury (ALI). Extracellular vesicles (EVs) contain miRNAs, which are potentially involved in ALI. However, strategies to screen more effective EV-miRNAs as therapeutic targets are yet to be elucidated. In this study, functional EV-miRNAs were identified based on multiomics analysis of single-cell RNA sequencing of targeted organs and serum EV (sEV) miRNA profiles in patients with sepsis. The proportions of neutrophils and macrophages were increased significantly in the lungs of mice receiving sEVs from patients with sepsis compared with healthy controls. Macrophages released more EVs than neutrophils. MiR-125a-5p delivery by sEVs to lung macrophages inhibited Tnfaip3, while miR-221-3p delivery to lung neutrophils inhibited Fos. Macrophage membrane nanoparticles (MM NPs) loaded with an miR-125a-5p inhibitor or miR-221-3p mimic attenuated the response to lipopolysaccharide (LPS)-induced ALI. Transcriptome profiling revealed that EVs derived from LPS-stimulated bone marrow-derived macrophages (BMDMs) induced oxidative stress in neutrophils. Blocking toll-like receptor, CXCR2, or TNFα signaling in neutrophils attenuated the oxidative stress induced by LPS-stimulated BMDM-EVs. This study presents a novel method to screen functional EV-miRNAs and highlights the pivotal role of macrophage-derived EVs in ALI. MM NPs, as delivery systems of key sEV-miRNA mimics or inhibitors, alleviated cellular responses observed in sepsis-induced ALI. This strategy can be used to reduce septic organ damage, particularly lung damage, by targeting EVs.

The paleo-tectonic stress fieldwas hereby inverted by using the stereographic projection method through field and underground observations of conjugate shear joints. On the basis of analyzing and studying the characteristics of gas occurrence in mining areas, the control effect of paleo-tectonic stress field on gas occurrence was discussed from three aspects of gas generation, preservation environment and gas migration. The results show that: (1) During the Indosinian and early-middle Yanshan period, the coal seam was buried deep, and the temperature and pressure conditions were suitable for massive gas generation, especially during the Indosinian period featuring massive gas generation and weak gas migration; (2) During the late Yanshan period, the metamorphic evolution rate of coal seams accelerated, secondary hydrocarbon generation occurred in the coal seams, and a large amount of gas was generated. Meanwhile, the gas migration was enhanced. The gas generation amount was much larger than the emission amount, therefore, making it still a period of massive gas generation in general; (3) During the Himalayan period, the coal measure stratum was in the uplift stage, and a large number of geological structures were developed in the stratum. The tectonic stress field in this period caused the escape of massive coal seam gas. Multi-stage tectonic stress field acted on coal measures strata in turn, resulting in gas generation in coal seam and gas migration at the same time. Besides, gas occurrence is the superposition effect of gas generation, preservation conditions, and gas migration in coal seam.

River and lake health assessment (RLHA) is an important approach to alleviating the conflict between protecting river and lake ecosystems and fostering socioeconomic development, aiming for comprehensive protection, governance, and management. Vegetation, a key component of the riparian zone, supports and maintains river and lake health (RLH) by providing a range of ecological functions. While research on riparian zone vegetation is ongoing, these studies have not yet been synthesized from the perspective of integrating RLHA with the ecological functions of riparian zone vegetation. In this paper, based on the bibliometric method, the relevant literature studies on the topics of RLHA and unmanned aerial vehicle (UAV) remote sensing of vegetation were screened and counted, and the keywords were highlighted, respectively. Based on the connotation of RLH, this paper categorizes the indicators of RLHA into five aspects: water space: the critical area from the river and lake water body to the land in the riparian zone; water resources: the amount of water in the river and lake; water environment: the quality of water in the river and lake; water ecology:aquatic organisms in the river and lake; and water services:the function of ecosystem services in the river and lake. Based on these five aspects, this paper analyzes the key role of riparian zone vegetation in RLHA. In this paper, the key roles of riparian zone vegetation in RLHA are summarized as follows: stabilizing riverbanks, purifying water quality, regulating water temperature, providing food, replenishing groundwater, providing biological habitats, and beautifying human habitats. This paper analyzes the application of riparian zone vegetation ecological functions in RLH, summarizing the correlation between RLHA indicators and these ecological functions. Moreover, this paper analyzes the advantages of UAV remote sensing technology in the quantitative monitoring of riparian zone vegetation. This analysis is based on the high spatial and temporal resolution characteristics of UAV remote sensing technology and focuses on monitoring the ecological functions of riparian zone vegetation. On this basis, this paper summarizes the content and indicators of UAV quantitative remote sensing monitoring of riparian zone vegetation for RLHA. It covers several aspects: delineation of riparian zone extent, identification of vegetation types and distribution, the influence of vegetation on changes in the river floodplain, vegetation cover, plant diversity, and the impact of vegetation distribution on biological habitat. This paper summarizes the monitoring objects involved in monitoring riparian zones, riparian zone vegetation, river floodplains, and biological habitats, and summarizes the monitoring indicators for each category. Finally, this paper analyzes the challenges of UAV quantitative remote sensing for riparian zone vegetation at the current stage, including the limitations of UAV platforms and sensors, and the complexity of UAV remote sensing data information. This paper envisages the future application prospects of UAV quantitative remote sensing for riparian zone vegetation, including the development of hardware and software such as UAV platforms, sensors, and data technologies, as well as the development of integrated air-to-ground monitoring systems and the construction of UAV quantitative remote sensing platforms tailored to actual management applications.

AbstractBackground The rapid adoption of next-generation sequencing in clinical oncology has enabled detection of molecular biomarkers which are shared between multiple tumour types. Intra-tumour heterogeneity is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the tumour-related copy number variants (CNVs), as key regulators of cancer origination, development, and progression, across various types of cancers are poorly understood.Methods We performed pan-cancer CNV analysis of cancer-related genes in 15 types of cancers including 1438 cancerous patients by next-generation sequencing using a commercially available pan-cancer panel (Onco PanScan™). Downstream bioinformatics analysis was performed in order to detect CNVs, cluster analysis of the found CNVs, and comparison of the frequency of gained CNVs between different types of cancers. LASSO analysis was used for identification of the most important CNVs.Results We also identified 523 CNVs among which 16 CNVs were common while 22 CNVs were caner-specific CNVs. Meanwhile, FAM58A was most commonly found in all studied cancers in this study and significant differences were found in FAM58A between female and male patients (p = .001). Common CNVs, such as FOXA1, NFKBIA, HEY1, MECOM, CHD7, AGO2, were mutated in 6.79%, 8.45%, 7.51%, 6.43%, 7.59%, 8.16% of tumours, while most of these mutations have proven roles in positive regulation of transcription from RNA polymerase II promoter. 11 features including sex, DIS3, EPHB1, ERBB2, FLT1, HCK, KEAP1, MYD88, PARP3, TBX3, and TOP2A were found as the key features for classification of cancers using CNVs.Conclusion The 16 common CNVs between cancers can be used to identify the target of pan-cancer drug design and targeted therapies. Additionally, 22 caner-specific CNVs can be used as unique diagnostic markers for each cancer type.

With the continuous development, processing and utilization of coal resources in our province, the existence of typical harmful elements in coal is bound to have a negative impact on the efficient and clean utilization of coal resources. Based on the mass data analysis of typical hazardous elements in coal of Huainan coalfield, taking the main coal seams (No.13-1, No.11-2, No.8, No.6, No.4 and No.1) as the research objects, the occurrence characteristics and geological genesis of typical hazardous elements were comprehensively analyzed by the means of ICP-MS, AFS, stepwise chemical extraction and cluster analysis. The results were as follows: ① Typical hazardous elements Cr, Co, Se and Pb in coal of Huainan coalfield are “lightly enriched”, Hg is “highly enriched” and other elements are in “normal range”; ② The high value area of As element content in Huainan coalfield was mainly located in the west of coalfield; the high value region of Hg element was located in the east of coalfield, followed by the west; the remaining eight elements (Cr, Mn, Co, Ni, Se, Cd, Sb and Pb) were all higher in coal of Panji mining area of Huainan coalfield (especially near Pansan coal mine). The late magmatic hydrothermal process in Panji-Zhuji region may be the main reason for the relative enrichment of hazardous elements such as Cr, Mn, Co, Ni, Se, Cd, Sb and Pb. ③ There were many ion-exchange States in the occurrence state of Hg, and the inorganic components brought by magmatic hydrothermal action may have little influence on the enrichment degree of Hg element. The magmatic hydrothermal intrusion in the late diagenesis period had no obvious influence on As, and the low content of As in coal may be related to the low content of As in coal-forming plants.

This paper proposes a magnetic system structure for a single crystal furnace that addresses the issue of unreasonable distribution of magnetic field lines on the free surface caused by DHL (Distance between the lower edge of the heat shield and the liquid surface) fluctuation during early stages of crystal growth. The proposed structure adjusts with the fluctuation of the free surface during the crystal pulling process, enabling the magnetic system to positively impact the thermal system. The thermo-magnetic coupling in a 160-type single crystal furnace before and after magnetic system optimization was simulated using the finite element method. Numerical simulation was employed to compare the temperature gradient, S-L (solid–liquid) boundary temperature distribution, and radial oxygen content in the single crystal furnace before and after magnetic system optimization under the conditions of Cr (crystal rotation) and Gr (graphite crucible rotation). The results reveal that the optimized magnetic system helps adjust the shape of the S-L boundary, decrease the temperature gradient, and lower the oxygen levels at the S-L boundary. However, when the Gr is rotated at high speed, although the S-L interface becomes flatter, the temperature gradient and oxygen concentration at the boundary increase. On the other hand, When Cr is at high speed, the S-L boundary tends to become flatter and the temperature gradient at this boundary decreases, but the oxygen concentration at the S-L boundary increases. Compared to the original single crystal furnace with a fixed magnetic system, the single crystal furnace with a lifting magnetic system experiences a 6.34% reduction in radial temperature gradient and a 3.02% reduction in axial temperature gradient during the actual crystal pulling process parameters. The temperature gradient at the S-L boundary decreases by 36.50%, and the radial average oxygen concentration decreases by 26.58%. Furthermore, the temperature distribution of the crystal and melt becomes more uniform, the oxygen content at the S-L boundary is effectively controlled, and the overall crystal quality improves. These findings can serve as a reference for designing a new magnetic system for a single crystal furnace.

We report a case of primary cutaneous γδT cell lymphoma complicated with hemophagocytic lymphohistiocytosis. A 33-year-old female presented with nodule on her left arm for 1 month and erythema on her both legs for a week. Physical examination revealed redness and swelling of the left upper arm with nodule sized 6.8 cm, accompanied with elevated skin temperature and tenderness. A sinus with yellow exudate was observed in the center of the lesion. There were more than 10 red nodular plaques in various sizes with unclear boundaries and tenderness around the ankles. Histology showed atypical lymphoid infiltrate in the dermis. Immunohistochemistry showed positive for CD3, CD5, CD8, Granzyme B, TIA-1, TCRγδ and Ki67(90%). Bone marrow aspiration showed abnormal maturation of granulocytes, erythroid hyperplasia and hemophagocytosis by reticular cells. TCRG gene rearrangement showed clonal amplification peak in the target band. PET-CT revealed multiple lymphadenopathy in her body. The diagnosis was primary cutaneous Gamma-Delta T-Cell lymphoma with hemophagocytic lymphohistiocytosis. After 2 weeks of CHOP+VP-16 combined with chemotherapy, patient's body temperature became normal, and the skin lesions gradually subsided. During the regular follow-up, the patient's symptoms recurred many times, and new skin lesions repeatedly developed, without significant improvement after the treatments with different chemotherapy. One year later, patient received hematopoietic stem cell transplantation, and her condition became stable. Currently the patient is still under follow-up.

The large amount of sensitive personal information used in deep learning models has attracted considerable attention for privacy security. Sensitive data may be memorialized or encoded into the parameters or the generation of the Wasserstein Generative Adversarial Networks (WGAN), which can be prevented by implementing privacy-preserving algorithms during the parameter training process. Meanwhile, the model is also expected to obtain effective generated results. We propose a vector-valued differential private bilateral alternative (DPBA) algorithm, a novel perturbation method for the training process. The vector-valued Gaussian (VVG) noise involving functional structure information is injected into the WGAN to generate data with privacy protection, and the model is verified to satisfy differential privacy. The bilateral alternative noise can eventually randomly perturb the gradient and generates informative feature-rich samples. The dynamic noise and vector-based perturbation approach ensure privacy strength. After extensive evaluation, our algorithm outperformed state-of-the-art techniques in terms of usability metrics for all validation datasets. The downstream classification accuracy for the generated Mnist was 97.04%, whereas that for the Fashion-Mnist dataset was 80.91%. Mnist improved the average accuracy of the neural network classifier by at least 16.81%, and Fashion-Mnist by at least 3.55%. In the multichannel generation tasks, the binary classification accuracy improved by at least 10.4% compared to CelebA, and the accuracy of the Street View House Numbers SVHN was as high as 86.1%. The perturbation method proved highly resilient to gradient attack recovery under simulated gradient attacks.

As the semiconductor industry gains momentum, there is a significant focus on producing high-quality silicon wafers with larger diameters. However, the preparation of major-diameter, high-quality silicon single-crystal has encountered challenges such as intense convection inside the melt and high oxygen impurity concentration at the interface between the fluid and solid phases. To tackle these problems, the external superconducting CUSP electromagnetic field structure was designed to optimize the crystal growth parameters. A hybrid strategy of the multiphysics field coupling method, Group Method of Data Handling (GMDH) type neural network identification, and the Multiple Objective Snake Optimizer (MOSO) algorithm was proposed to optimize the superconducting CUSP electromagnetic field structure. A two-dimensional axisymmetric model was established for 18-inch silicon single-crystal preparation using the Magnet system Applied Czochralski (MCZ) method. The amount of longitudinal plies of superconducting CUSP electromagnetic field coils, coil spacing, and the thickness of magnetic shields were selected as design variables, and the radial electromagnetic induction intensity at the graphite crucible inner wall and the superconducting magnet volume were used as dual objective functions. The required samples for GMDH training were provided by COMSOL Multiphysics (COMSOL) numerical calculations, and polynomial mathematical equations were established with the radial electromagnetic induction intensity at the graphite crucible inner wall and the superconducting magnet volume as the dual objective functions. Then the Pareto optimal solution for the electromagnetic field structure design variables was obtained using the dual objective function optimized by MOSO. With the hybrid strategy, numerical simulations and theoretical analysis of the crystal preparation process parameters under the effect of the superconducting electromagnetic field with the optimal structure were carried out. The results displayed that the added superconducting CUSP electromagnetic field reduced the crystal radial and axial thermal gradients and greatly suppressed the melt convection. As a result, the heat distribution inside the hot fused silicon was more even, the thermal gradient at the solid–liquid interface was reduced by 68.4%, and the oxygen impurity content was reduced by 82.1%, which effectively improved the crystal quality. The thermal field simulation results verified that the proposed hybrid strategy provided a new numerical calculation method for obtaining the optimal superconducting electromagnetic field structure.

Nucleotide-binding and oligomerization domain (NOD)-like receptors (NLRs) are intracellular proteins with a central role in innate and adaptive immunity. As a member of pattern recognition receptors (PRRs), NLRs sense specific pathogen-associated molecular patterns, trigger numerous signaling pathways and lead to the secretion of various cytokines. In recent years, cumulative studies have revealed the significant impacts of NLRs in gastrointestinal (GI) inflammatory diseases and cancers. Deciphering the role and molecular mechanism of the NLR signaling pathways may provide new opportunities for the development of therapeutic strategies related to GI inflammatory diseases and GI cancers. This review presents the structures and signaling pathways of NLRs, summarizes the recent advances regarding NLR signaling in GI inflammatory diseases and GI cancers and describes comprehensive therapeutic strategies based on this signaling pathway.

Abstract Background Diagnosing seronegative rheumatoid arthritis (RA) can be challenging due to complex diagnostic criteria. We sought to discover diagnostic biomarkers for seronegative RA cases by studying metabolomic and lipidomic changes in RA patient serum. Methods We performed comprehensive metabolomic and lipidomic profiling in serum of 225 RA patients and 100 normal controls. These samples were divided into a discovery set (n = 243) and a validation set (n = 82). A machine-learning-based multivariate classification model was constructed using distinctive metabolites and lipids signals. Results Twenty-six metabolites and lipids were identified from the discovery cohort to construct a RA diagnosis model. The model was subsequently tested on a validation set and achieved accuracy of 90.2%, with sensitivity of 89.7% and specificity of 90.6%. Both seropositive and seronegative patients were identified using this model. A co-occurrence network using serum omics profiles was built and parsed into six modules, showing significant association between the inflammation and immune activity markers and aberrant metabolism of energy metabolism, lipids metabolism and amino acid metabolism. Acyl carnitines (20:3), aspartyl-phenylalanine, pipecolic acid, phosphatidylethanolamine PE (18:1) and lysophosphatidylethanolamine LPE (20:3) were positively correlated with the RA disease activity, while histidine and phosphatidic acid PA (28:0) were negatively correlated with the RA disease activity. Conclusions A panel of 26 serum markers were selected from omics profiles to build a machine-learning-based prediction model that could aid in diagnosing seronegative RA patients. Potential markers were also identified in stratifying RA cases based on disease activity.

Ecosystem health plays a vital role in the development of regional ecological environment. Gannan Plateau, an important water conservation area in the upper reaches of the Yellow River, is located at the northeastern margin of the Qinghai-Tibet Plateau. Due to the importance of the region, understanding the spatiotemporal patterns of the ecosystem health within this region is particularly critical. Previous studies on regional ecosystem health assessment mainly focused on single ecosystem type such as wetland, forest, and grassland, while there are relatively few studies that comprehensively assessed ecosystem health at high-spatial resolution in Gannan alpine areas. In this study, 11 counties and cities in Gannan Tibetan and Linxia Hui Autonomous Prefecture of the Gansu Province, China were used as the study area. We evaluated the ecosystem health of 154 township units from 2000 to 2020 with methods of Pressure-State-Response model (PSR) and Analytic Hierarchy Process (AHP), using a combination of satellite remote sensing data, social statistics data, meteorological data, and other geospatial data sources. The results showed that overall ecosystems in the southwestern part of the study area exhibited healthier condition than those located in the northeastern part, which is mainly due to the combination of the natural environment and the intensity of human activities in different regions. Over the past 20 years, due to the active implementation of relevant ecological protection and restoration policies by various regional governments and the improvement of the natural environment, the average ecosystem health status of Gannan Plateau has increased by 15.04 %, showing an improving trend in varying degrees or being stable, no declining trend was observed except for a small town. Our results implied that management should take different measures according to the differences of regional ecosystem health level, also pay more attention to areas where the ecosystem health status has not improved.

Using computers to numerically simulate large-scale neuronal networks has become a common method for studying the mechanism of the human brain, and neuroimaging has brought forth multimodal brain data. Determining how to fully consider these multimodal data in the process of brain modeling has become a crucial issue. Data assimilation is an efficient method for combining the dynamic system with the observation data, and many related algorithms have been developed. In this paper, we utilize data assimilation to perform brain state variables estimation, put forward a general form of a diffusion Kalman filter named the deep diffusion Kalman filter, and provide a specific algorithm that is combined with data assimilation. Then, we theoretically demonstrate the deep diffusion Kalman filter’s effectiveness and further validate it by using an experiment in the toy model. Finally, according to the resting state functional magnetic resonance imaging signals, we assimilate a cortex networks model with the resting state brain, where the correlation is as high as 98.42%.

The study of climate element distribution models under complex terrain conditions is a popular topic in the field of GIS application in climatology, especially in plateau areas with a complex topography and scarce meteorological station information. In this paper, the spatial and temporal heterogeneity of temperature and precipitation at the northeastern edge of the Tibetan Plateau was analyzed by taking the northeastern edge of the plateau as the study area and constructing a topographic spatial statistical model using 47 meteorological stations and digital elevation models from 1981 to 2010. The following conclusions were drawn from the study: (1) The ME of the temperature distribution model for each month is below 0.9 °C; the maximum ME of the precipitation distribution model for each month is −5.808 mm in July, and the precipitation distribution model has similar error characteristics with the temperature distribution model, which can reflect the horizontal zone distribution pattern of meteorological data and can clearly show the changes of temperature and precipitation as the altitude increases. (2) The spatial distribution pattern of temperature is as follows: the temperature in the study area gradually increases from the southwest to the northeast, with Zhouqu County in Linxia Prefecture and Gannan Prefecture as the main high-temperature areas; the spatial distribution of precipitation is as follows: the precipitation in the southwest of the study area is significantly higher than that in the north, and the precipitation in Linxia Prefecture is significantly lower than that in Gannan Prefecture. (3) The temporal distribution pattern of the temperature distribution model is as follows: the overall temperature in the study area is at its lowest level in January, and the maximum temperature is only 2.6 °C, until July, when the maximum temperature rises to 24.2 °C and then gradually starts to decline; the spatial distribution of precipitation is as follows: the precipitation in the study area gradually rises from January, and the maximum precipitation rises to July and then starts to decline, and in December the precipitation falls to the lowest level. The temporal distribution characteristics of the precipitation distribution model are similar to those of the air temperature model, with obvious hydrothermal synchronization characteristics.

Abstract Background Noonan syndrome is an inherited disease involving multiple systems. More than 15 related genes have been discovered, among which LZTR1 was discovered recently. However, the pathogenesis and inheritance pattern of LZTR1 in Noonan syndrome have not yet been elucidated. Case presentation We herein describe a family with LZTR1-related Noonan syndrome. In our study, the proband, sister, mother, maternal aunt and grandmother and female cousin showed the typical or atypical features of Noonan syndrome. Only 3 patients underwent the whole-exome sequencing analysis and results showed that the proband as well as her sister inherited the same heterozygous LZTR1 variant (c.1149 + 1G > T) from their affected mother. Moreover, the proband accompanied by growth hormone deficiency without other associated variants. Conclusion In a Chinese family with Noonan syndrome, we find that the c.1149 + 1G > T variant in LZTR1 gene shows a different autosomal dominant inheritance from previous reports, which changes our understanding of its inheritance and improves our understanding of Noonan syndrome.

Abstract Background The objective of this study was to investigate genetic variations and the relationships between these genetic variations and clinicopathological features of high-recurrence risk papillary thyroid carcinoma in a southern Chinese population. Methods One hundred sixty-eight patients of high-recurrence risk papillary thyroid carcinoma were recruited for this study from 2017 to 2018. Formalin-fixed paraffin-embedded tissue and the data of clinicopathological characteristics were all collected and analyzed from these patients. We used next-generation sequencing technology to investigate the targeted gene mutations and gene fusions of the pathology specimens. Results The frequency of candidate tumor driver gene mutation was 85.1% in 143 patients, including BRAF V600E mutation in 119 patients(70.8%), RET fusion in 13 patients(7.7%), TERT promoter mutations in 11 patients(6.5%), RAS (HRAS, NRAS, KRAS) gene mutations in 10 patients(6.0%), and other mutations involving TP53, PIK3CA, AKT1, PTEN and NTRK1. Concomitant presence of more than two genetic aberrations was seen in 27 patients (16.1%). Our study showed that BRAF V600E mutation is highly correlated with conventional PTC (p 45, p = 0.003) and higher disease stage of III or IV (p = 0.002). RAS gene and BRAF V600E co-mutations were only seen in multifocal PTC (p = 0.015). Conclusion In our high-recurrence risk PTC cohort, most patients had more than one driver gene aberration. Coexistence of BRAF V600E with TERT promoter mutations or with RAS mutations were significantly correlated with worse clinicopathological characteristics.

Abstract Background The study is aimed to provide prediction for fertility risk in the setting of assisted reproduction for a woman with complex chromosomal rearrangements (CCRs). Methods We implemented a robust approach, which combined whole-genome low-coverage mate-pair sequencing (WGL-MPS), junction-spanning PCR and preimplantation genetic testing for aneuploidy (PGT-A) method to provide accurate chromosome breakpoint junctional sequences in the embryo selection process in the setting of assisted reproduction for a couple with recurrent abortions due to CCRs. Result WGL-MPS was applied to a female carrying CCRs which consisted of 9 breakpoints and 1 cryptic deletion related to fertility risks. Sequencing data provided crucial information for designing junction-spanning PCR and PGT-A process, which was performed on the 11 embryos cultivated. One embryo was considered qualified for transplanting, which carried the exact same CCRs as the female carrier, whose phenotype was normal. The amniotic fluid was also investigated by WGL-MPS and karyotyping at 19 weeks’ gestation, which verified the results that the baby carried the same CCRs. A healthy baby was born at 39 weeks’ gestation by vaginal delivery. Conclusion(s) Our study illustrates the WGL-MPS approach combining with junction-spanning PCR and PGT-A is a powerful and practical method in the setting of assisted reproduction for couples with recurrent miscarriage due to chromosomal abnormalities, especially CCRs carriers.

Accumulated evidence shows that complex microbial communities resides in the healthy human urinary tract and can change in urological disorders. However, there lacks a comprehensive profiling of the genitourinary microbiota in healthy cohort. Here, we performed 16S rRNA gene sequencing of midstream urine specimens from 1,172 middle-aged and elderly healthy individuals. The core microbiota included 6 dominant genera (mean relative abundance >5%), including Prevotella, Streptococcus, Lactobacillus, Gardnerella, Escherichia-Shigella, and Veillonella, and 131 low-abundance genera (0.01–5%), displaying a distinct microbiome profiles to that of host-matched gut microbiota. The composition and diversity of genitourinary microbiome (GM) were distinct between genders and may fluctuate with ages. Several urotypes were identified by the stratification of microbiome profiles, which were mainly dominated by the six most predominant genera. The prevalence of urotypes was disparate between genders, and the male sample additionally harbored other urotypes dominated by Acinetobacter, Corynebacterium, Staphylococcus, or Sphingomonas. Peptoniphilus, Ezakiella, and Porphyromonas were co-occurred and co-abundant, and they may play crucial roles as keystone genera and be associated with increased microbial diversity. Our results delineated the microbial structure and diversity landscape of the GM in healthy middle-aged and elderly adults and provided insights into the influence of gender and age to it.

Crystal structure and magnetic properties of Heusler alloys MnXNiSn (X = Mn, Fe, Co) are investigated using density functional theory and compared with experimental results. The parent alloy Mn2NiSn, which crystallizes in the inverse Heusler structure, is found to be ferrimagnetic, in agreement with previous experimental and theoretical work. The Fe and Co substitutions cause the alloys to assume a fairly well-ordered Y structure and enhance the magnetization substantially. We find that the strong nearest neighbour Mn-X exchange changes from antiferromagnetic (X = Mn) to ferromagnetic (X = Fe, Co), which explains and actually overestimates the experimental changes. A striking feature of the system is that Fe and Co have opposite effects on the Curie temperature Tc: they reduce and enhance Tc, respectively. We qualitatively explain this behaviour in terms of two-sublattice model based on the nearest-neighbour exchange.

Familial chylomicronemia syndrome (FCS) is a rare monogenic autosomal recessive disease caused by loss-of-function mutations in genes involved in chylomicron breakdown through hydrolysis of triglycerides into free fatty acids. Patients are often diagnosed in early childhood with extremely high triglyceride levels and symptoms including abdominal pain, eruptive cutaneous xanthomata, hepatosplenomegaly, and significant cognitive, psychological, and social impairment. The most serious medical condition suffered by FCS patients is recurrent acute pancreatitis. Lipoprotein lipase (LPL) gene mutation accounts for majority of the known pathogenic mutations. Early diagnosis and strict low-fat diet are critical for successful management of the triglyceride concentration to lower the risk of pancreatitis. The true prevalence of FCS in China is unknown and here we report a Chinese female preterm neonate presented with an extremely high triglyceride level of 22.11 mmol/L on day 13 after birth. Clinical and laboratory workup including whole-exome sequencing revealed two novel compound heterozygous LPL mutations (c.406G > C and c.829G > C) that are co-segregated with her non-consanguineous parents, consistent with autosomal recessive inheritance. A diagnosis of FCS based on clinical, biochemical, and genetic ground was made to guide her management.

Permanent-magnet materials are one cornerstone of today’s technology, abundant in disk drives, motors, medical equipment, wind generators, and cars. A continuing challenge has been to reconcile high permanent-magnet performance with low raw-material costs. This work reports a Mn-Bi-Sn alloy exclusively made from inexpensive elements, exhibiting high values of Curie-temperature, magnetization, anisotropy, coercivity, and energy product. The samples are produced by field annealing of rapidly quenched Sn-containing MnBi alloys, where the improvement of the magnetic properties is caused by the substitutional occupancy of the 2c sites in the hexagonal NiAs structure by Sn. The substitution modifies the electronic structure of the compound and enhances the magnetocrystalline anisotropy, thereby improving the coercivity of the compound. The energy product reaches 114 kJ/m3 (14.3 MGOe) at room temperature and 86 kJ/m3 (10.8 MGOe) at 200 °C; this value is similar to that of the Dy-free Nd2Fe14B and exceeds that of other rare-earth-free permanent-magnet bulk alloys, as encountered in automotive applications.

Abstract Background 1q43-q44 deletion syndrome is a well-defined chromosomal disorder which is characterized by moderate to severe mental retardation, and variable but characteristic facial features determined by the size of the segment and the number of genes involved. However, patients with 1q43-q44 duplication with a clinical phenotype comparable to that of 1q43-q44 deletion are rarely reported. Moreover, pure 1q43-q44 deletions and duplications derived from balanced insertional translocation within the same family with precisely identified breakpoints have not been reported. Case presentation The proband is a 6-year-old girl with profound developmental delay, mental retardation, microcephaly, epilepsy, agenesis of the corpus callosum and hearing impairment. Her younger brother is a 3-month-old boy with macrocephaly and mild developmental delay in gross motor functions. G-banding analysis of the subjects at the 400-band level did not reveal any subtle structural changes in their karyotypes. However, single-nucleotide polymorphism (SNP) array analysis showed a deletion and a duplication of approximately 6.0 Mb at 1q43-q44 in the proband and her younger brother, respectively. The Levicare analysis pipeline of whole-genome sequencing (WGS) further demonstrated that a segment of 1q43-q44 was inserted at 14q23.1 in the unaffected mother, which indicated that the mother was a carrier of a 46,XX,ins(14;1)(q23.1;q43q44) insertional translocation. Moreover, Sanger sequencing was used to assist the mapping of the breakpoints and the final validation of those breakpoints. The breakpoint on chromosome 1 disrupted the EFCAB2 gene in the first intron, and the breakpoint on chromosome 14 disrupted the PRKCH gene within the 12th intron. In addition, fluorescence in situ hybridization (FISH) further confirmed that the unaffected older sister of the proband carried the same karyotype as the mother. Conclusion Here, we describe a rare family exhibiting pure 1q43-q44 deletion and duplication in two siblings caused by a maternal balanced insertional translocation. Our study demonstrates that WGS with a carefully designed analysis pipeline is a powerful tool for identifying cryptic genomic balanced translocations and mapping the breakpoints at the nucleotide level and could be an effective method for explaining the relationship between karyotype and phenotype.

The structural, magnetic and magnetocaloric properties of Fe deficient Pr2-xNdxFe17 (x = 0.5, 0.7) alloys prepared by arc-melting and melt-spinning have been investigated. The room temperature x-ray diffraction patterns show that the samples are nearly single-phase and crystallize in the rhombohedral Th2Zn17-type crystal structure. The Curie temperatures determined from the thermomagnetic curves are 302 K and 307 K for Pr1.5Nd0.5Fe17 and Pr1.3Nd0.7Fe17, respectively. The peak magnetic entropy change and the relative cooling power at field change of 50 kOe are 3.01 J/kgK and 345 J/kg for Pr1.5Nd0.5Fe17, and 4.31 J/kgK and 487 J/kg for Pr1.3Nd0.7Fe17, respectively. The absence of magnetic and thermal hysteresis with relatively high cooling efficiency suggests that the alloys have potential for magnetic refrigeration.

Owing to the complexity and heterogeneity of coal during pyrolysis, the ex situ analytical techniques cannot accurately reflect the real coal pyrolysis process. In this study, according to the joint investigation of Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD), the structural evolution characteristics of lignite-subbituminous coal-bituminous coal-anthracite series under heat treatment were discussed in depth. The results of the infrared spectrum of coal show that the different functional groups of coal show different changes with the increase of coal rank before pyrolysis experiment. Based on in situ infrared spectroscopy experiments, it was found that the infrared spectrum curves of the same coal sample have obvious changes at different pyrolysis temperatures. As a whole, when the pyrolysis temperature is between 400 and 500°C, the coal structure can be greatly changed. By fitting the infrared spectrum curve, the infrared spectrum parameters of coal were obtained. With the change of temperature, these parameters show regular changes in coal with different ranks. In the XRD study of coal, the absorption intensity of the diffraction peak (002) of coal increases with increasing coal rank. The XRD patterns of coal have different characteristics at different pyrolysis temperatures. Overall, the area of (002) diffraction peak of the same coal sample increases obviously with the increase of temperature. The XRD structural parameter of coal was obtained by using the curve fitting method. The changing process of two parameters (interlayer spacing (d002) and stacking height (Lc)) can be divided into two main stages, but the average lateral size (La) does not change significantly and remains at the 2.98 ± 0.09 nm. In summary, the above two technologies complement each other in the study of coal structure. The temperature range of both experiments is different, but the XRD parameters of coal with different ranks are reduced within the temperature range of less than 500°C, which reflects that the size of coal-heated aromatic ring lamellae is reduced and the distance between lamellae is also reduced, indicating that the degree of condensation of coal aromatic nuclei may be increased. Correspondingly, the FTIR parameters of coal also reflect that, with increasing temperature, the side chains of coal are constantly cracked, the oxygen-containing functional groups are reduced, and the degree of aromatization of coal may be increased.

Research on the composition and structure of coal is the most important and complex basic research in the coal chemistry field. Various methods have been used to study the structure of coal from different perspectives. However, due to the complexity of coal and the limitations of research methods, research on the macromolecular structure of coal still lacks systematicness. Huainan coalfield is located in eastern China and is the largest coal production and processing base in the region. In this study, conventional proximate analysis and ultimate analysis, as well as advanced instrumental analysis methods, such as Fourier transform infrared spectroscopy (FITR), X-ray diffraction (XRD), 13C-CP/MAS NMR, and other methods (SEM and AFM), were used to analyze the molecular structure of Huainan coal (HNC) and the distribution characteristics of oxygen in different oxygen-containing functional groups (OCFGs) in an in-depth manner. On the basis of SEM observation, it could be concluded that the high-resolution morphology of HNC’s surface contains pores and fractures of different sizes. The loose arrangement pattern of HNC’s molecular structure could be seen from 3D AFM images. The XRD patterns show that the condensation degree of HNC’s aromatic ring is low, and the orientation degree of carbon network lamellae is poor. The calculated ratio of the diameter of aromatic ring lamellae to their stacking height (La/Lc = 1.05) and the effective stacking number of aromatic nuclei (Nave = 7.3) show that the molecular space structure of HNC is a cube formed of seven stacked aromatic lamellae. The FTIR spectra fitting results reveal that the aliphatic chains in HNC’s molecular structure are mainly methyne and methylene. Oxygen is mainly –O–, followed by –C=O, and contains a small amount of –OH, the ratio of which is about 8:1:2. The molar fraction of binding elements has the approximate molecular structure C100H76O9N of organic matter in HNC. The results of the 13C NMR experiments show that the form of aromatic carbon atoms in HNC’s structure (the average structural size Xb of aromatic nucleus = 0.16) is mainly naphthalene with a condensation degree of 2, and the rest are aromatic rings composed of benzene rings and heteroatoms. In addition, HNC is relatively rich in ≡CH and –CH2– structures.

This paper aimed to perform systematical study on the distribution of landslide thrust in pile-anchor support system, which has been a widely applicable treatment method in landslide control with safety, highly efficiency and adaptation. The advantage of photoelastic technique is visualization of strain and stress fields, therefore photoelastic model tests are conducted to show the distribution of landslide thrust in pile-anchor structure before failure in landslide. The effects of different materials and pile lengths are investigated by 6 photoelastic test cases under different loading conditions. It can be found from quantitative analysis of experimental results that load proportion of anchor would increase gradually with the decrease of pile embedded depth or the increase of landslide thrust force. Meanwhile, landslide thrust distribution in pile-anchor structure is directly affected by the stiffness of piles. The pile-anchor structure is significantly better at reducing bending moment value and optimizing bending moment distribution of pile. Finally, some theoretical analysis and design suggestions are proposed based on the experimental study.

The effect of Y addition and magnetic field on texture and magnetic properties of arc-melted alnico 9 magnets has been investigated. Small additions of Y (1.5 wt.%) develop a (200) texture for the arc-melted alnico 9 magnet. Such a texture is hard to form in cast samples. To achieve this goal, we set up a high-field annealing system with a maximum operation temperature of 1250 °C. This system enabled annealing in a field of 45 kOe with subsequent draw annealing for the solutionized buttons; we have been able to substantially increase remanence ratio and coercivity, from 0.70 and 1200 Oe for the Y-free alnico 9 to 0.90 and 1400 Oe for the Y-doped alnico 9, respectively. A high energy product of 7.3 MGOe has been achieved for the fully heat-treated Y-doped alnico 9. The enhancement of coercivity is believed to arise from the introduction of magnetocrystalline anisotropy from 80 nm Y2Co17-type grains, which are exchange-coupled to the main-phase alnico rods.

The role of B on the microstructure and magnetism of Zr16Co82.5-xMo1.5Bx ribbons prepared by arc melting and melt spinning is investigated. Microstructure analysis show that the ribbons consist of a hard-magnetic rhombohedral Zr2Co11 phase and a minor amount of soft-magnetic Co. We show that the addition of B increases the amount of hard-magnetic phase, reduces the amount of soft-magnetic Co and coarsens the grain size from about 35 nm to 110 nm. There is a monotonic increase in the volume of the rhombohedral Zr2Co11 unit cell with increasing B concentration. This is consistent with a previous theoretical prediction that B may occupy a special type of large interstitial sites, called interruption sites. The optimum magnetic properties, obtained for x = 1, are a saturation magnetization of 7.8 kG, a coercivity of 5.4 kOe, and a maximum energy product of 4.1 MGOe.

Mn2CrGa in the disordered cubic structure has been synthesized using rapid quenching and subsequent annealing. The cubic phase transforms to a stable tetragonal phase when a fraction of Cr or Ga is replaced by Pt or Al, respectively. All samples are ferrimagnetic with high Curie temperatures (Tc); Mn2CrGa exhibits the highest Tc of about 813 K. The tetragonal samples have appreciable values of magnetocrystalline anisotropy energy, which leads to an increase in coercivity (Hc) that approaches about 10 kOe in the Pt-doped sample. The Hc linearly increases with a decrease of temperature, concomitant with the anisotropy change with temperature. All samples are metallic and show negative magnetoresistance with room-temperature resistivities on the order of 1 mΩcm. The magnetic properties including high Tc and low magnetic moment suggest that these tetragonal materials have potential for spin-transfer-torque-based devices.