Clinical analysis: 13 cases of pregnancy complicated with Takayasu arteritis

Objectives: To investigate the clinical features, disposition, and effect of pregnancy complicated with Takayasu arteritis (P-TA) on maternal and fetal outcomes. Material and methods: The clinical data (diagnosis and treatment, peri-pregnancy monitoring, and pregnancy outcomes) of patients with P-TA treated in our hospital between September 2007 and April 2016 were analyzed retrospectively. Results: Among the 13 P-TA cases, seven were diagnosed before pregnancy, and six were diagnosed during pregnancy; six cases were diagnosed as the generalized type, and seven cases were diagnosed as the cephalic-brachial type; six cases were in the stable stage, and seven cases were in the active stage. All the cases in the active stage underwent glucocorticoid therapy. Four cases developed complications, including cardiac dysfunction combined with preeclampsia in two cases, preeclampsia in one case, and stroke in one case. Eleven patients successfully delivered (nine cases of full-term delivery and two cases of premature delivery); one patient had late miscarriage; one patient had missed abortion. All the parturients survived and delivered 11 neonates (nine full-term neonates and two premature neonates) and one low-birth-weight neonate; no neonatal asphyxia or death occurred. Conclusions: Patients with P-TA can have better maternal and child outcomes through timely diagnosis and treatment, dynamic monitoring, or timely pregnancy termination

Shortcuts to Adiabatic Soliton Compression in Active Nonlinear Kerr Media

We implement variational shortcuts to adiabaticity for optical pulse compression in an active nonlinear Kerr medium with distributed amplification and spatially varying dispersion and nonlinearity. Starting with the hyperbolic secant ansatz, we employ a variational approximation to systematically derive dynamical equations, establishing analytical relationships linking the amplitude, width, and chirp of the pulse. Through the inverse engineering approach, we manipulate the distributed gain/loss, nonlinearity and dispersion profiles to efficiently compress the optical pulse over a reduced distance with high fidelity. In addition, we explore the dynamical stability of the system to illustrate the advantage of our protocol over conventional adiabatic approaches. Finally, we analyze the impact of tailored higher-order dispersion on soliton self-compression and derive physical constraints on the final soliton width for the complementary case of soliton expansion. The broader implications of our findings extend beyond optical systems, encompassing areas such as cold-atom and magnetic systems highlighting the versatility and relevance of our approach in various physical contexts.Comment: 9 pages, 6 figure

Diagnostic performance of deep learning in ultrasound diagnosis of breast cancer: a systematic review

Deep learning (DL) has been widely investigated in breast ultrasound (US) for distinguishing between benign and malignant breast masses. This systematic review of test diagnosis aims to examine the accuracy of DL, compared to human readers, for the diagnosis of breast cancer in the US under clinical settings. Our literature search included records from databases including PubMed, Embase, Scopus, and Cochrane Library. Test accuracy outcomes were synthesized to compare the diagnostic performance of DL and human readers as well as to evaluate the assistive role of DL to human readers. A total of 16 studies involving 9238 female participants were included. There were no prospective studies comparing the test accuracy of DL versus human readers in clinical workflows. Diagnostic test results varied across the included studies. In 14 studies employing standalone DL systems, DL showed significantly lower sensitivities in 5 studies with comparable specificities and outperformed human readers at higher specificities in another 4 studies; in the remaining studies, DL models and human readers showed equivalent test outcomes. In 12 studies that assessed assistive DL systems, no studies proved the assistive role of DL in the overall diagnostic performance of human readers. Current evidence is insufficient to conclude that DL outperforms human readers or enhances the accuracy of diagnostic breast US in a clinical setting. Standardization of study methodologies is required to improve the reproducibility and generalizability of DL research, which will aid in clinical translation and application

Genome-Wide Association Studies Identified Three Independent Polymorphisms Associated with α-Tocopherol Content in Maize Kernels

Tocopherols are a class of four natural compounds that can provide nutrition and function as antioxidant in both plants and animals. Maize kernels have low α-tocopherol content, the compound with the highest vitamin E activity, thus, raising the risk of vitamin E deficiency in human populations relying on maize as their primary vitamin E source. In this study, two insertion/deletions (InDels) within a gene encoding γ-tocopherol methyltransferase, Zea mays VTE4 (ZmVTE4), and a single nucleotide polymorphism (SNP) located ∼85 kb upstream of ZmVTE4 were identified to be significantly associated with α-tocopherol levels in maize kernels by conducting an association study with a panel of ∼500 diverse inbred lines. Linkage analysis in three populations that segregated at either one of these three polymorphisms but not at the other two suggested that the three polymorphisms could affect α-tocopherol content independently. Furthermore, we found that haplotypes of the two InDels could explain ∼33% of α-tocopherol variation in the association panel, suggesting ZmVTE4 is a major gene involved in natural phenotypic variation of α-tocopherol. One of the two InDels is located within the promoter region and associates with ZmVTE4 transcript level. This information can not only help in understanding the underlying mechanism of natural tocopherol variations in maize kernels, but also provide valuable markers for marker-assisted breeding of α-tocopherol content in maize kernels, which will then facilitate the improvement of maize as a better source of daily vitamin E nutrition

Progressive Destabilization and Triggering Mechanism Analysis Using Multiple Data for Chamoli Rockslide of 7 February 2021

A catastrophic rockslide occurred on 7 February 2021 in Chamoli area in the high Himalaya. In the absence of field data, multiple satellites data of decade span have been used to investigate and understand the progressive destabilization of rockslide body. A 3D geometric model was developed using geospatial information about geology, terrain, and ice cover to understand the triggering mechanism. Several causes are uncovered as: the pronounced long-term change of land surface temperature facilitated local permafrost degradation and led to ice cover shrinking since 2010; the occurrence of ice avalanche nearby in 2016 accompanying with sidewall-to-bedrock fracturing enhanced the ice segregation beneath the rockslide body; and the development of side cracks in early February 2021 led to dropping of side support and percolating of surface water. Heavy precipitation several days before favoured the destabilization, top-corner cracks developing and top-side bergschrund breaking abruptly two days before, and ice strength reduction owing air temperature rising few hours before the event triggered finally the rockslide. The frequent disasters such as cloudburst, extreme precipitation, landslides, and snow avalanches responding to global warming and climate change in the Himalayan region needs immediate attention to the chain-like geohazards and collaborative observation with satellites and other platforms

Genome level analysis of rice mRNA 3′-end processing signals and alternative polyadenylation

The position of a poly(A) site of eukaryotic mRNA is determined by sequence signals in pre-mRNA and a group of polyadenylation factors. To reveal rice poly(A) signals at a genome level, we constructed a dataset of 55 742 authenticated poly(A) sites and characterized the poly(A) signals. This resulted in identifying the typical tripartite cis-elements, including FUE, NUE and CE, as previously observed in Arabidopsis. The average size of the 3′-UTR was 289 nucleotides. When mapped to the genome, however, 15% of these poly(A) sites were found to be located in the currently annotated intergenic regions. Moreover, an extensive alternative polyadenylation profile was evident where 50% of the genes analyzed had more than one unique poly(A) site (excluding microheterogeneity sites), and 13% had four or more poly(A) sites. About 4% of the analyzed genes possessed alternative poly(A) sites at their introns, 5′-UTRs, or protein coding regions. The authenticity of these alternative poly(A) sites was partially confirmed using MPSS data. Analysis of nucleotide profile and signal patterns indicated that there may be a different set of poly(A) signals for those poly(A) sites found in the coding regions. Based on the features of rice poly(A) signals, an updated algorithm termed PASS-Rice was designed to predict poly(A) sites

Ultrasensitive colorimetric detection of creatinine via its dual binding affinity for silver nanoparticles and silver ions

Creatinine is an important biomarker for the diagnosis of chronic kidney disease (CKD). Recently, it has been reported that the concentration of salivary creatinine correlates well with the concentration of serum creatinine, which makes the former useful for the development of non-invasive and point-of-care (POC) detection for CKD diagnosis. However, there exists a technical challenge in the rapid detection of salivary creatinine at low concentrations of 3-18 μM when using the current kidney function test strips as well as the traditional methods employed in hospitals. Herein, we demonstrate a simple, sensitive colorimetric assay for the detection of creatinine with a limit-of-detection (LOD) down to the nanomolar level. Our approach utilises the dual binding affinity of creatinine for citrate-capped silver nanoparticles (Ag NPs) and Ag(i) ions, which can trigger the aggregation of Ag NPs and thus lead to the colour change of a sample. The quantitative detection of creatinine was achieved using UV-Vis spectroscopy with a LOD of 6.9 nM in artificial saliva and a linear dynamic range of 0.01-0.06 μM. This method holds promise to be further developed into a POC platform for the CKD diagnosis

Predictive modeling of plant messenger RNA polyadenylation sites

BACKGROUND: One of the essential processing events during pre-mRNA maturation is the post-transcriptional addition of a polyadenine [poly(A)] tail. The 3'-end poly(A) track protects mRNA from unregulated degradation, and indicates the integrity of mRNA through recognition by mRNA export and translation machinery. The position of a poly(A) site is predetermined by signals in the pre-mRNA sequence that are recognized by a complex of polyadenylation factors. These signals are generally tri-part sequence patterns around the cleavage site that serves as the future poly(A) site. In plants, there is little sequence conservation among these signal elements, which makes it difficult to develop an accurate algorithm to predict the poly(A) site of a given gene. We attempted to solve this problem. RESULTS: Based on our current working model and the profile of nucleotide sequence distribution of the poly(A) signals and around poly(A) sites in Arabidopsis, we have devised a Generalized Hidden Markov Model based algorithm to predict potential poly(A) sites. The high specificity and sensitivity of the algorithm were demonstrated by testing several datasets, and at the best combinations, both reach 97%. The accuracy of the program, called poly(A) site sleuth or PASS, has been demonstrated by the prediction of many validated poly(A) sites. PASS also predicted the changes of poly(A) site efficiency in poly(A) signal mutants that were constructed and characterized by traditional genetic experiments. The efficacy of PASS was demonstrated by predicting poly(A) sites within long genomic sequences. CONCLUSION: Based on the features of plant poly(A) signals, a computational model was built to effectively predict the poly(A) sites in Arabidopsis genes. The algorithm will be useful in gene annotation because a poly(A) site signifies the end of the transcript. This algorithm can also be used to predict alternative poly(A) sites in known genes, and will be useful in the design of transgenes for crop genetic engineering by predicting and eliminating undesirable poly(A) sites

Rapid Visual Detection of Pathogenic Streptococcus suis Type 2 through a Recombinase Polymerase Amplification Assay Coupled with Lateral Flow Test

Streptococcus suis serotype 2 (SS2) is an important zoonotic pathogen causing serious disease and even death in pigs and humans. Public health events and economic losses caused by SS2 have prompted widespread concern. Because of the unavailability of vaccines, the development of rapid detection methods for timely diagnosis of SS2 infection or contaminated products, and monitoring of its prevalence in susceptible animals and populations, is required to aid in the prevention and control of SS2 infections. Several sets of primers and one probe for a recombinase polymerase amplification (RPA) assay targeting the cpsJ2 gene were designed and synthesized. Lateral flow (LF) tests in combination with RPA were used to provide visual results. Primers with high amplification efficiency were screened, and the reaction system was optimized. Indicators of detection effectiveness were evaluated. The established method had a detection limit of 100 copies/reaction for recognizing SS2 rather than other organisms. The sensitivity was 100%, as evaluated in infected animal samples. The detection could be completed within 20 min and required only constant temperature equipment. The established rapid, visual, sensitive and specific RPA-LF assay showed superior detection performance and is expected to be widely applied to fight SS2 infection in resource-limited areas