End-to-end Remote Sensing Change Detection of Unregistered Bi-temporal Images for Natural Disasters

Change detection based on remote sensing images has been a prominent area of interest in the field of remote sensing. Deep networks have demonstrated significant success in detecting changes in bi-temporal remote sensing images and have found applications in various fields. Given the degradation of natural environments and the frequent occurrence of natural disasters, accurately and swiftly identifying damaged buildings in disaster-stricken areas through remote sensing images holds immense significance. This paper aims to investigate change detection specifically for natural disasters. Considering that existing public datasets used in change detection research are registered, which does not align with the practical scenario where bi-temporal images are not matched, this paper introduces an unregistered end-to-end change detection synthetic dataset called xBD-E2ECD. Furthermore, we propose an end-to-end change detection network named E2ECDNet, which takes an unregistered bi-temporal image pair as input and simultaneously generates the flow field prediction result and the change detection prediction result. It is worth noting that our E2ECDNet also supports change detection for registered image pairs, as registration can be seen as a special case of non-registration. Additionally, this paper redefines the criteria for correctly predicting a positive case and introduces neighborhood-based change detection evaluation metrics. The experimental results have demonstrated significant improvements

Delivery of coenzyme Q10 loaded micelle targets mitochondrial ROS and enhances efficiency of mesenchymal stem cell therapy in intervertebral disc degeneration

Stem cell transplantation has been proved a promising therapeutic instrument in intervertebral disc degeneration (IVDD). However, the elevation of oxidative stress in the degenerated region impairs the efficiency of mesenchymal stem cells (BMSCs) transplantation treatment via exaggeration of mitochondrial ROS and promotion of BMSCs apoptosis. Herein, we applied an emulsion-confined assembly method to encapsulate Coenzyme Q10 (Co-Q10), a promising hydrophobic antioxidant which targets mitochondria ROS, into the lecithin micelles, which renders the insoluble Co-Q10 dispersible in water as stable colloids. These micelles are injectable, which displayed efficient ability to facilitate Co-Q10 to get into BMSCs in vitro, and exhibited prolonged release of Co-Q10 in intervertebral disc tissue of animal models. Compared to mere use of Co-Q10, the Co-Q10 loaded micelle possessed better bioactivities, which elevated the viability, restored mitochondrial structure as well as function, and enhanced production of ECM components in rat BMSCs. Moreover, it is demonstrated that the injection of this micelle with BMSCs retained disc height and alleviated IVDD in a rat needle puncture model. Therefore, these Co-Q10 loaded micelles play a protective role in cell survival and differentiation through antagonizing mitochondrial ROS, and might be a potential therapeutic agent for IVDD

Multitask Learning Based on Improved Uncertainty Weighted Loss for Multi-Parameter Meteorological Data Prediction

With the exponential growth in the amount of available data, traditional meteorological data processing algorithms have become overwhelmed. The application of artificial intelligence in simultaneous prediction of multi-parameter meteorological data has attracted much attention. However, existing single-task network models are generally limited by the data correlation dependence problem. In this paper, we use a priori knowledge for network design and propose a multitask model based on an asymmetric sharing mechanism, which effectively solves the correlation dependence problem in multi-parameter meteorological data prediction and achieves simultaneous prediction of multiple meteorological parameters with complex correlations for the first time. The performance of the multitask model depends largely on the relative weights among the task losses, and manually adjusting these weights is a difficult and expensive process, which makes it difficult for multitask learning to achieve the expected results in practice. In this paper, we propose an improved multitask loss processing method based on the assumptions of homoscedasticity uncertainty and the Laplace loss distribution and validate it using the German Jena dataset. The results show that the method can automatically balance the losses of each subtask and has better performance and robustness

The comparison of clinical outcome of fresh type II odontoid fracture treatment between anterior cannulated screws fixation and posterior instrumentation of C1-2 without fusion: a retrospective cohort study

Abstract Background Recently, the excellent outcomes of temporary fixation of C1-2 without fusion in the treatment of odontoid fracture had been reported. It is still unclear if this technique could achieve the equivalent outcomes as the golden standard technique of anterior screw fixation. The objective of this study is to compare the clinical outcome of two treatments of fresh type II odontoid fracture: anterior cannulated screws fixation (ACSF) versus posterior instrumentation of C1-2 without fusion (PIWF). Methods This is a retrospective study. This series included 28 males and 8 females, and the mean age was 41.5 years (range, 22 to 70 years). Eleven patients were treated with ACSF, and 25 patients with PIWF. For PIWF, the implants were removed after fracture union was confirmed at 0.75~1.5 years later. All patients underwent preoperative and serial postoperative clinical examinations at approximately 3 months, 6 months, and annually thereafter. The neck disability index (NDI) was used to assess the neck discomfort caused by the operation. The range of rotary motion was evaluated at each visit. All fractures were reassessed postoperatively with serial X-films and CT scans of the cervical spine at each follow-up visit, to evaluate screw position, fracture alignment, and fusion status. Results All patients achieved immediate spinal stabilization after surgery, and none experienced neurologic deterioration. The follow-up periods ranged from 24 to 60 months. The average range of neck rotation was dramatically lost in PIWF after fixation (46° and 89° respectively in ACSF and PIWF), and recovered to 83° after the implant was removed. The NDI in PIWF was statistically higher than that in ACSF (5 and 13% respectively in ACSF and PIWF) after the first operation and decreased to 8% 1 year after the secondary operation. The fusion rates were 90.9 and 96% respectively in ACSF and PIWF. Both groups had a case of fracture non-union. Conclusions For fresh type II odontoid fractures, high rate of fracture union can be achieved by both ACSF and PIWF. For most fresh type II odontoid fractures, anterior screw fixation was the best option for its simplicity and preservation of normal atlanto-axial rotary function. Posterior instrumentation without fusion could preserve most of the atlanto-axial rotary function and lead to moderate neck discomfort and is also a good alternative if anterior screw fixation is contraindicated

Ultrasonic vibration micro-jet ejection for metal additive manufacture

In comparison to laser additive manufacturing, metal droplet deposition technology presents substantial cost benefits by obviating the necessity for costly metal powders and high-power lasers. Nonetheless, prevalent metal droplet deposition methodologies often grapple with challenges such as intricate drive architectures, substantial droplet volumes, and diminished jetting frequencies. This paper proposes an ultrasonic vibration micro-jet ejection technique and constructs a prototype for metal additive manufacturing. Utilizing ultrasonic vibration of a tool rod, the technique generates a high-frequency acoustic pressure field within the crucible, which facilitates the ejection of molten metal from the nozzle. The study explores two operational modes: continuous jet and on-demand jet. It was determined that the tool rod's amplitude must exceed a certain threshold to initiate metal ejection. As the amplitude further increases, the droplet jetting behavior transitions from uniform to non-uniform ejection states. To enhance formability quality, the study examined the influence of various process parameters on single-pass and three-dimensional forming. The examination of jetted parts revealed that both uniform and non-uniform jets provide satisfactory formability and mechanical performance. This research presents a new direction for achieving efficient metal droplet jetting forming

Mutational burden and potential oligogenic model of TBX6

Abstract Background Congenital scoliosis (CS) is a spinal deformity due to vertebral malformations. Although insufficiency of TBX6 dosage contributes to a substantial proportion of CS, the molecular etiology for the majority of CS remains largely unknown. TBX6‐mediated genes involved in the process of somitogenesis represent promising candidates. Methods Individuals affected with CS and without a positive genetic finding were referred to this study. Proband‐only exome sequencing (ES) were performed on the recruited individuals, followed by analysis of TBX6‐mediated candidate genes, namely MEOX1, MEOX2, MESP2, MYOD1, MYF5, RIPPLY1, and RIPPLY2. Results A total of 584 patients with CS of unknown molecular etiology were recruited. After ES analysis, protein‐truncating variants in RIPPLY1 and MYF5 were identified from two individuals, respectively. In addition, we identified five deleterious missense variants (MYOD1, n = 4; RIPPLY2, n = 1) in TBX6‐mediated genes. We observed a significant mutational burden of MYOD1 in CS (p = 0.032) compared with the in‐house controls (n = 1854). Moreover, a potential oligogenic disease‐causing mode was proposed based on the observed mutational co‐existence of MYOD1/MEOX1 and MYOD1/RIPPLY1. Conclusion Our study characterized the mutational spectrum of TBX6‐mediated genes, prioritized core candidate genes/variants, and provided insight into a potential oligogenic disease‐causing mode in CS

Expanding the mutation and phenotype spectrum of MYH3-associated skeletal disorders

Pathogenic variants in MYH3 cause distal arthrogryposis type 2A and type 2B3 as well as contractures, pterygia and spondylocarpotarsal fusion syndromes types 1A and 1B. These disorders are ultra-rare and their natural course and phenotypic variability are not well described. In this study, we summarize the clinical features and genetic findings of 17 patients from 10 unrelated families with vertebral malformations caused by dominant or recessive pathogenic variants in MYH3. Twelve novel pathogenic variants in MYH3 (NM_002470.4) were identified: three of them were de novo or inherited in autosomal dominant way and nine were inherited in autosomal recessive way. The patients had vertebral segmentation anomalies accompanied with variable joint contractures, short stature and dysmorphic facial features. There was a significant phenotypic overlap between dominant and recessive MYH3-associated conditions regarding the degree of short stature as well as the number of vertebral fusions. All monoallelic variants caused significantly decreased SMAD3 phosphorylation, which is consistent with the previously proposed pathogenic mechanism of impaired canonical TGF-beta signaling. Most of the biallelic variants were predicted to be protein-truncating, while one missense variant c.4244T&amp;gt;G,p.(Leu1415Arg), which was inherited in an autosomal recessive way, was found to alter the phosphorylation level of p38, suggesting an inhibition of the non-canonical pathway of TGF-beta signaling. In conclusion, the identification of 12 novel pathogenic variants and overlapping phenotypes in 17 affected individuals from 10 unrelated families expands the mutation and phenotype spectrum of MYH3-associated skeletal disorders. We show that disturbances of canonical or non-canonical TGF-beta signaling pathways are involved in pathogenesis of MYH3-associated skeletal fusion (MASF) syndrome.Funding Agencies|National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [81930068, 81772299, 81822030, 82072391, 81972132, 81672123, 81972037, 81902178]; Beijing Natural Science FoundationBeijing Natural Science Foundation [JQ20032, 7191007]; CAMS Innovation Fund for Medical Sciences (CIFMS) [2021-I2M-1-051, 2021-I2M-1-052]; Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences [2019PT320025]; Tsinghua University-Peking Union Medical College Hospital Initiative Scientific Research Program; PUMC Youth Fund &amp; the Fundamental Research Funds for the Central Universities [3332019021]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [K2015-54X-22 736-01-4, 2015-02227, 2018-03046]; Swedish Governmental Agency for Innovation Systems (Vinnova)Vinnova [2014-01438]; Marianne and Marcus Wallenberg Foundation; IngaBritt och Arne Lundbergs forskningsstiftelse; Byggmastare Olle Engkvist Stiftelse; Promobilia; Nyckelfonden; Stiftelsen Frimurare Barnhuset i Stockholm; Region Stockholm; Karolinska Institutet, Stockholm, Sweden; orebro University, orebro, Sweden; Sallskapet Barnavard; Karolinska InstitutetKarolinska Institutet; Stiftelsen Sallsyntafonden; Stiftelsen Samariten; Stiftelsen Promobilia; Region Stockholm [20180131, 20200500]; US National Institutes of Health (NIH), National Institute of Neurological Disorders and Stroke [NINDS R35 NS105078]; National Human Genome Research Institute/National Heart, Lung, and Blood Institute [NHGRI/NHLBI UM1 HG006542]; US NIH National Human Genome Research Institute [NHGRI K08 HG008986]</p