Accurate inference of gene regulatory interactions from spatial gene expression with deep contrastive learning.

MOTIVATION: Reverse engineering of gene regulatory networks (GRNs) has long been an attractive research topic in system biology. Computational prediction of gene regulatory interactions has remained a challenging problem due to the complexity of gene expression and scarce information resources. The high-throughput spatial gene expression data, like in situ hybridization images that exhibit temporal and spatial expression patterns, has provided abundant and reliable information for the inference of GRNs. However, computational tools for analyzing the spatial gene expression data are highly underdeveloped. RESULTS: In this study, we develop a new method for identifying gene regulatory interactions from gene expression images, called ConGRI. The method is featured by a contrastive learning scheme and deep Siamese convolutional neural network architecture, which automatically learns high-level feature embeddings for the expression images and then feeds the embeddings to an artificial neural network to determine whether or not the interaction exists. We apply the method to a Drosophila embryogenesis dataset and identify GRNs of eye development and mesoderm development. Experimental results show that ConGRI outperforms previous traditional and deep learning methods by a large margin, which achieves accuracies of 76.7% and 68.7% for the GRNs of early eye development and mesoderm development, respectively. It also reveals some master regulators for Drosophila eye development. AVAILABILITYAND IMPLEMENTATION: https://github.com/lugimzheng/ConGRI. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Universal Entanglement and Correlation Measure in Two-Dimensional Conformal Field Theories.

We calculate the amount of entanglement shared by two intervals in the ground state of a (1+1)-dimensional conformal field theory (CFT), quantified by an entanglement measure E based on the computable cross norm (CCNR) criterion. Unlike negativity or mutual information, we show that E has a universal expression even for two disjoint intervals, which depends only on the geometry, the central charge c, and the thermal partition function of the CFT. We prove this universal expression in the replica approach, where the Riemann surface for calculating E at each order n is always a torus topologically. By analytic continuation, the result of n=1/2 gives the value of E. Furthermore, the results of other values of n also yield meaningful conclusions: The n=1 result gives a general formula for the two-interval purity, which enables us to calculate the Rényi-2 N-partite information for N≤4 intervals; while the n=∞ result bounds the correlation function of the two intervals. We verify our findings numerically in the spin-1/2 XXZ chain, whose ground state is described by the Luttinger liquid.

Fundamental Limitation on the Detectability of Entanglement.

Entanglement detection is essential in quantum information science and quantum many-body physics. It has been proved that entanglement exists almost surely for a random quantum state, while the realizations of effective entanglement criteria usually consume exponentially many resources with regard to system size or qubit number, and efficient criteria often perform poorly without prior knowledge. This fact implies a fundamental limitation might exist in the detectability of entanglement. In this work, we formalize this limitation as a fundamental trade-off between the efficiency and effectiveness of entanglement criteria via a systematic method to evaluate the detection capability of entanglement criteria theoretically. For a system coupled to an environment, we prove that any entanglement criterion needs exponentially many observables to detect the entanglement effectively when restricted to single-copy operations. Otherwise, the detection capability of the criterion will decay double exponentially. Furthermore, if multicopy joint measurements are allowed, the effectiveness of entanglement detection can be exponentially improved, which implies a quantum advantage in entanglement detection problems. Our results may shed light on why quantum phenomena are difficult to observe in large noisy systems.

Detecting Entanglement in Quantum Many-Body Systems via Permutation Moments.

Multipartite entanglement plays an essential role in both quantum information science and many-body physics. Because of the exponentially large dimension and complex geometric structure of the state space, the detection of entanglement in many-body systems is extremely challenging in reality. Conventional means, like entanglement witness and entropy criterion, either highly depend on the prior knowledge of the studied systems or the detection capability is relatively weak. In this Letter, we propose a framework for designing multipartite entanglement criteria based on permutation moments, which have an effective implementation with either the generalized control-swap quantum circuits or the random unitary techniques. As an example, in the bipartite scenario, we develop an entanglement criterion that can detect bound entanglement and show strong detection capability in the multiqubit Ising model with a long-range XY Hamiltonian. In the multipartite case, the permutation-moment-based criteria can detect entangled states that are not detectable by any criteria extended from the bipartite case. Our framework also shows potential in entanglement quantification and entanglement structure detection.

Spatial identification of restored priority areas based on ecosystem service bundles and urbanization effects in a megalopolis area.

Rapid urbanization has altered the structure and function of urban ecosystems with respect to the demand for planning ecological restoration to inhibit ecological degradation. However, there is still a challenge to quickly and effectively identify the restored priority areas to maximize ecological service (ES) supply and enhance human well-being. Taking the Shenzhen metropolitan region as a case study area, this study identified the restored priority sites based on the ES bundles evolution and urbanization effects. The ES bundles were identified by analyzing the spatial dynamics under the hybrid urban landscape, then the impact of urbanization on the ES bundles was explored using linear regression analysis characterized by different levels of urbanization in different stages. Furthermore, the spatial statistics were used to identify the priority sites. The results showed that 68.78% of the grids had changed their ES bundles in terms of their quantities, types, and sites in Shenzhen during 1978-2018. The urbanization driver spatially shifts from provision of service to regulation and cultural ecosystem services and significantly negatively influences the composition and structure of the ES bundles in different urbanization stages. 1196 of the 1 square kilometer grids, which accounted for 54.17%, were identified to prioritize for ecological restoration in Shenzhen. However, only 4.08% of them need to set as the key ecological restoration site. This study explored an effectively spatial way to implement ecological restoration planning in a rapidly urbanized area.

The effect of combined transcranial pulsed current stimulation and transcutaneous electrical nerve stimulation on lower limb spasticity in children with spastic cerebral palsy: a randomized and controlled clinical study.

BACKGROUND: In the current study, we applied a combination of non-invasive neuromodulation modalities concurrently with multiple stimulating electrodes. Specifically, we used transcranial pulsed current stimulation (tPCS) and transcutaneous electrical nerve stimulation (TENS) as a novel strategy for improving lower limb spasticity in children with spastic cerebral palsy (SCP) categorized on levels III-V of the Gross Motor Function Classification System (GMFCS) with minimal side effects. METHODS: Sixty-three SCP children aged 2-12 years, who were classified on levels III-V of the GMFCS were randomly assigned to one of two groups, resulting in 32 children in the experimental group and 31 children in the control group. The experimental group underwent a combination therapy of tPCS (400 Hz, 1 mA cerebello-cerebral stimulation) and TENS (400 Hz, max 10 mA) for 30 min, followed by 30 min of physiotherapy five times per week for 12 weeks. The control group underwent physiotherapy only 30 mins per day five times per week for 12 weeks. In total, all groups underwent 60 treatment sessions. The primary outcome measures were the Modified Ashworth Scale (MAS) and Modified Tardieu Scale (MTS). Evaluations were performed 3 days before and after treatment. RESULTS: We found a significant improvement in MAS and MTS scores of the lower limbs in the experimental group compared to the control group in the hip adductors (Left: p = 0.002; Right: p = 0.002), hamstrings (Left: p = 0.001; Right: p < 0.001, and gastrocnemius (Left: p = 0.001; Right: p = 0.000). Moreover, MTS scores of R1, R2 and R2-R1 in left and right hip adduction, knee joint, and ankle joint all showed significant improvements (p ≤ 0.05). Analysis of MAS and MTS scores compared to baseline scores showed significant improvements in the experimental group but declines in the control group. CONCLUSION: These results are among the first to demonstrate that a combination of tPCS and TENS can significantly improve lower limb spasticity in SCP children classified on GMFCS levels III-V with minimal side effects, presenting a novel strategy for addressing spasticity challenges in children with severe SCP. TRIAL REGISTRATION: ChiCTR.org, ChiCTR1800020283, Registration: 22 December 2018 (URL: http://www.chictr.org.cn/showproj.aspx?proj=33953 ).

Single-Copies Estimation of Entanglement Negativity.

Entanglement plays a central role in quantum information processing and quantum physics. However, few effective ways are known to detect the amount of entanglement of an unknown quantum state. Here, we propose a scheme to estimate the entanglement negativity for any bipartition of a composite system. The proposed scheme is based on the random unitary evolution and local measurements on a single-copy quantum state, which is more practical compared to former methods based on collective measurements on many copies of the identical state. Meanwhile, we generalize the scheme to quantify the total correlation. We demonstrate the efficiency of the scheme with statistical analyses and numerical simulations. Our scheme is quite suitable for state-of-the-art quantum platforms, which can serve as a useful benchmarking tool to advance quantum technologies and a probe to study fundamental quantum physics like entanglement dynamics.

Initial psychometric validation of the questionnaire on pain caused by spasticity (QPS).

BACKGROUND: The Questionnaire on Pain caused by Spasticity (QPS) is a modular patient- and observer-reported outcome measure of spasticity-related pain (SRP) in children with cerebral palsy (CP). Originally developed for an English-speaking population, we conducted a psychometric validation of a recently developed Chinese language version of the QPS. METHODS: This was a prospective, observational study involving 137 children/adolescents with CP and upper and/or lower limb spasticity and their parents at three sites in China. Six QPS modules were used, three each for upper and lower limb SRP assessment: a patient self-report module; an interviewer-administered module used by site staff based on the cognitive, communicative, and motor abilities of a patient; and a parent/caregiver module administered for all children as an observer-reported outcome to complement the patient-reported outcome. If no assessment by the patient was possible because of age or cognitive impairments, only the parent/caregiver module was completed. Two visits with a 3-week interval provided data to evaluate and establish administrative ease of use, scoring of the QPS (factor analyses, Rasch analyses), reliability (Cronbach's α, intraclass correlation coefficient), validity (correlations with quality of life [PedsQL™], motor impairment [Gross Motor Function Classification System, Gross Motor Function Measure-66, Manual Ability Classification System], and spasticity [Ashworth Scale, Modified Tardieu Scale]). RESULTS: For most children, clinic staff reported no difficulties associated with general QPS use or deciding which module to use. Children (and parents) who reported more demanding activities also reported higher levels of associated SRP (or observed SRP behavior). Activity-related SRP items were combined for a total QPS score. Cronbach's α was low for child self-report, but was acceptable for interviewer-administered and parent reports on SRP. Test-retest reliability was high for all modules. Moderate-strong associations were frequently seen between QPS and quality of life, and were particularly strong in the child self-report group. Relatively weak associations were observed between QPS and motor impairment and spasticity. CONCLUSIONS: This first study was successful in providing initial evidence for the psychometric properties. Clinic staff were able to administer the QPS modules easily, and both children and parents were able to complete the designated QPS appropriately.

Chinese rice production area adaptations to climate changes, 1949-2010.

Climate change has great impact on cropping system. Understanding how the rice production system has historically responded to external forces, both natural and anthropogenic, will provide critical insights into how the system is likely to respond in the future. The observed historic rice movement provides insights into the capability of the rice production system to adapt to climate changes. Using province-level rice production data and historic climate records, here we show that the centroid of Chinese rice production shifted northeastward over 370 km (2.98°N in latitude and 1.88°E in longitude) from 1949 to 2010. Using a linear regression model, we examined the driving factors, in particular climate, behind such rice production movement. While the major driving forces of the rice relocation are such social economic factors as urbanization, irrigation investment, and agricultural or land use policy changes, climate plays a significant role as well. We found that temperature has been a significant and coherent influence on moving the rice center in China and precipitation has had a significant but less spatially coherent influence.

[Risk factors for interictal epileptiform discharges on electroencephalogram in children with spastic hemiplegic cerebral palsy].

OBJECTIVE: To investigate the clinical symptoms and features of interictal epileptiform discharges (IED) on electroencephalogram (EEG) in children with spastic hemiplegic cerebral palsy (CP) and to analyze the risk factors for IED. METHODS: Eighty-three children with spastic hemiplegic CP were recruited, and their clinical data, results of video-electroencephalogram, imaging findings, and cognitive levels were collected. The influencing factors for IED were determined by multiple logistic regression analysis. RESULTS: The incidence of epilepsy was 13% in children with spastic hemiplegic CP; 34% of these cases had IED. The incidence of epilepsy in children with IED (32%) was significantly higher than that in those without IED (4%) (P<0.01). The incidence of IED in children with complications and brain cortex impairment increased significantly (P<0.01). The incidence of IED varied significantly between patients with different cognitive levels (P<0.01). Brain cortex impairment (OR=11.521) and low cognitive level (OR=2.238)were risk factors for IED in children with spastic hemiplegic CP (P<0.05). CONCLUSIONS: Spastic hemiplegic CP is often found with IED on EEG, and the incidence of epilepsy is higher in children with IED than in those without IED. Brain cortex impairment and low cognitive level have predictive values for IED in children with spastic hemiplegic CP.

Screening for five prevalent mutations of SLC25A13 gene in Guangdong, China: a molecular epidemiologic survey of citrin deficiency.

Citrin is the liver-type aspartate/glutamate carrier isoform 2 (AGC2) encoded by SLC25A13 gene, playing important roles in the urea cycle and the malate-aspartate shuttle. Citrin deficiency (CD) has proven a disease entity with high prevalence in south China, including Guangdong with the largest population, but CD epidemiology in this province has not been well characterized. This study aims to screen for five prevalent SLC25A13 mutations, c.851_854del (p.R284fs286X), c.1638_1660dup (p.A554fs570X), c.615+5G>A (p.A206fs212X), IVS16ins3kb (p.A584fs585X) and c.1399C>T (p.R467X), to calculate the mutation carrier rate in Guangdong. A total of 2,428 used blood samples for health examination were collected as the research subjects, including 1,558 from 5 cities in the Pearl River Delta area and the remaining 870 from 4 peripheral cities, and the 5 mutations screened using High Resolution Melting Assay and HybProbe assay. A total of 52 carriers were detected, including 2 carriers of a novel c.1420G>A (p.V474M) mutation that impairs citrin function, as judged by the functional analysis in the yeast system. The carrier rate was higher in Pearl River Delta area than that in the peripheral cities (26/1,558 vs. 26/870, with χ(2) = 4.639 and P < 0.05). The carrier rate was around 1/47 (52/2,428), theoretically with the CD morbidity of 1/8,800 and the number of CD patients over 11,800 in Guangdong population. This study has provided primary epidemiologic data for the evaluation of CD effect in Guangdong province. Moreover, the newly identified c.1420G>A mutation that impairs AGC2 function has enriched the mutation spectrum of human SLC25A13 gene.

WTV2.0: A high-coverage plant volatilomics method with a comprehensive selective ion monitoring acquisition mode.

Volatilomics is essential for understanding the biological functions and fragrance contributions of plant volatiles. However, the annotation coverage achieved using current untargeted and widely targeted volatomics (WTV) methods has been limited by low sensitivity and/or low acquisition coverage. Here, we introduce WTV 2.0, which enabled the construction of a high-coverage library containing 2111 plant volatiles, and report the development of a comprehensive selective ion monitoring (cSIM) acquisition method, including the selection of characteristic qualitative ions with the minimal ion number for each compound and an optimized segmentation method, that can acquire the smallest but sufficient number of ions for most plant volatiles, as well as the automatic qualitative and semi-quantitative analysis of cSIM data. Importantly, the library and acquisition method we developed can be self-expanded by incorporating compounds not present in the library, utilizing the obtained cSIM data. We showed that WTV 2.0 increases the median signal-to-noise ratio by 7.6-fold compared with the untargeted method, doubled the annotation coverage compared with the untargeted and WTV 1.0 methods in tomato fruit, and led to the discovery of menthofuran as a novel flavor compound in passion fruit. WTV 2.0 is a Python library with a user-friendly interface and is applicable to profiling of volatiles and primary metabolites in any species.

Response of vegetation phenology to urbanization in urban agglomeration areas: A dynamic urban-rural gradient perspective.

Being an important theme in global warming, the response of vegetation phenology to urbanization has become an increasing concern at both the local and global levels. Previous studies have focused on spatial or temporal responses across urban-rural gradients; thus, the influence of urbanization on vegetation phenology along the dynamic urbanization gradient has not been well quantified. In this study, we comprehensively analyzed the response of vegetation phenology to urbanization in the Guangdong-Hong Kong-Macao Greater Bay Area (GHM-GBA) from a dynamic urban-rural gradient perspective. The results show that the response of vegetation phenology to urbanization level has a distinct spatiotemporal difference across the urban-rural gradient. Compared to rural areas, the change rate of advancements in the start-of-season (SOS) in urban domains was 1.16 DOY/year and that of the end-of-season (EOS) was 0.63 days/year from 2001 to 2020. In the GHM-GBA region, 61.03 % of the remote sensing pixels showed an advancing trend for SOS and 55.75 % for EOS. Urbanization advanced the SOS and EOS but did not extend the growing season length, and the SOS and EOS were advanced by 7 and 6 days along the urban-to-rural gradient, respectively. For every 10 % increase in urbanization levels, the SOS and EOS advanced by 1.085 and 1.091 days across the urban-rural gradient, respectively; the spring land surface temperature (LST) advanced the SOS at a rate of 1.71 days/°C, while the autumn LST advanced the EOS at a rate of 1.88 days/°C. The phenological shift in the urban-rural gradient was more significant than that over time, which was mainly because of land surface warming under different urbanization levels. These quantitative findings are of great importance for understanding the complicated impacts of urbanization on vegetation phenology and for developing models to predict vegetation phenological changes under future urbanization.

Traceability Research on Dendrobium devonianum Based on SWATHtoMRM.

SWATHtoMRM technology was used in this experiment to further identify and trace the sources of Dendrobium devonianum and Dendrobium officinale produced in the same area using TOF and MS-MRM. After the conversion of the R package of SWATHtoMRM, 191 MRM pairs of positive ions and 96 pairs of negative ions were obtained. Dendrobium devonianum and Dendrobium officinale can be separated very well using the PCA and PLS-DA analysis of MRM ion pairs; this shows that there are obvious differences in chemical composition between Dendrobium devonianum and Dendrobium officinale, which clearly proves that the pseudotargeted metabolomics method based on SWATHtoMRM can be used for traceability identification research. A total of 146 characteristic compounds were obtained, with 20 characteristic compounds in Dendrobium devonianum. The enrichment pathways of the characteristic compounds were mainly concentrated in lipids and atherosclerosis, chagas disease, fluid shear stress and atherosclerosis, proteoglycans in cancer, the IL-17 signaling pathway, the sphingolipid signaling pathway, diabetic cardiomyopathy, arginine and proline metabolism, etc., among which the lipid and atherosclerosis pathways were more enriched, and 11 characteristic compounds affected the expression levels of IL-1, TNFα, CD36, IL-1ß, etc. These can be used as a reference for research on variety improvement and active substance accumulation in Dendrobium devonianum and Dendrobium officinale.

Design of Blended Teaching Model Based on Emotion Recognition and Language Learning.

With the vigorous development of Internet technology, great changes have taken place in all aspects of human society. This change is also having an increasingly significant impact on the education sector. It is even a trend to subvert the tradition. This also makes the student's identity a passive recipient of knowledge. At the same time, the final orientation of China's education model is the result of examinations, and there is little guidance for students' interest. Of course, traditional teaching also has the ability to enable students' subject knowledge to be systematically established, and to communicate with teachers in the teaching process, which can improve students' learning efficiency in the classroom. In the face of the information explosion in today's society and the rapid development of the above-mentioned technologies, the change of students' learning mode of knowledge has also ushered in an opportunity to change. The purpose of this paper is to study the establishment of a blended teaching model that combines traditional classrooms with network applications. With the help of the characteristics of network big data, it transforms students' passive learning identities, and combines offline traditional learning classrooms with online learning. In addition to the advantages mentioned above, the advantage of online learning is that some network science and technology can be used for the online learning platform to serve the entire teaching process. Therefore, this paper proposes a blended teaching model based on the network platform for students' emotion recognition and language learning result analysis. And from the experimental results in this paper, it can be seen that the recognition evaluation rate of HTMC, the feature of emotion recognition, is 71.52% and the recognition frequency of ETMC is 73.89%. The above two recognition parameters can better reflect the emotional changes in the mixed teaching process.

Case report: Tongdu Xingshen acupuncture for a patient with persistent vegetative state after herpes simplex virus encephalitis.

Introduction: A persistent vegetative state (PVS) can be caused by traumatic or non-traumatic brain injury. PVS is a complex clinical condition with numerous complications. Nursing care, medical treatment, and comprehensive rehabilitation are necessary to improve the outcomes of PVS. However, the prognosis remains unsatisfactory. Acupuncture therapy has been used as a rehabilitation strategy to treat patients with PVS in China, showing better results in the recovery of consciousness, intellectual capability, and motor function. Case description: We present the case of a 4-month-long PVS after herpes simplex virus encephalitis (HSVE) in a 3.5-year-old boy who underwent Tongdu Xingshen acupuncture integrated with Western medicine and rehabilitation. The patient regained consciousness post-treatment. His intelligence and motor function gradually recovered after seven treatment sessions. Conclusion: Tongdu Xingshen acupuncture is a potential complementary therapy to optimize clinical outcomes in PVS.

Development of a widely targeted volatilomics method for profiling volatilomes in plants.

Volatile organic compounds play essential roles in plant environment interactions as well as determining the fragrance of plants. Although gas chromatography-mass spectrometry-based untargeted metabolomics is commonly used to assess plant volatiles, it suffers from high spectral convolution, low detection sensitivity, a limited number of annotated metabolites, and relatively poor reproducibility. Here, we report a widely targeted volatilomics (WTV) method that involves using a "targeted spectra extraction" algorithm to address spectral convolution, constructing a high-coverage MS2 spectral tag library to expand volatile annotation, adapting a multiple reaction monitoring mode to improve sensitivity, and using regression models to adjust for signal drift. The newly developed method was used to profile the volatilome of rice grains. Compared with the untargeted method, the newly developed WTV method shows higher sensitivity (for example, the signal-to-noise ratio of guaicol increased from 4.1 to 18.8), high annotation coverage (the number of annotated volatiles increased from 43 to 132), and better reproducibility (the number of volatiles in quality control samples with relative standard deviation value below 30.0% increased from 14 to 92 after normalization). Using the WTV method, we studied the metabolic responses of tomato to environmental stimuli and profiled the volatilomes of different rice accessions. The results identified benzothiazole as a potential airborne signal priming tomato plants for enhanced defense and 2-nonanone and 2-heptanone as novel aromatic compounds contributing to rice fragrance. These case studies suggest that the widely targeted volatilomics method is more efficient than those currently used and may considerably promote plant volatilomics studies.

Etiological analysis of neurodevelopmental disabilities: single-center eight-year clinical experience in south China.

Etiology determination of neurodevelopmental disabilities (NDDs) currently remains a worldwide common challenge on child health. We herein reported the etiology distribution feature in a cohort of 285 Chinese patients with NDDs. Although concrete NDD etiologies in 48.4% of the total patients could not be identified, genetic diseases (with the proportion of 35.8% in the total cases) including inborn errors of metabolism (IEM) and congenital dysmorphic diseases, constituted the commonest etiology category for NDDs in this study. The two key experimental technologies in pediatric metabolomics, gas chromatography-mass spectrometry (GC-MS), and tandem mass spectrometry (MS-MS), proved to be substantially helpful for the exploration of the NDD etiologies in this clinical investigation. The findings in this paper provided latest epidemiologic information on the etiology distribution of NDDs in Chinese, and the syndromic NDDs caused by citrin deficiency and the novel chromosomal karyotype, respectively, further expanded the etiology spectrum of NDDs.

Using Artificial Intelligence-Based Collaborative Teaching in Media Learning.

With the advent of the 5G era, humans must not only learn the knowledge and skills of cross-border integration but must also get to grips with the breadth and efficiency of artificial intelligence (AI) technology in order to jointly overcome current difficulties and create a happy and beautiful life. In this article, we use the example of an elementary school to discuss the decision-making factors that influence teachers when choosing AI technology, where the digital content of schools is imported into artificial intelligence-based collaborative teaching. After discussing the relevant literature, this study will introduce the concept of digital media education, and then compare the development and application of smart technology and human-computer collaborative teaching methods, describing three key aspects and factors that influence elementary school teachers' choice of AI technology. There are 12 evaluation criteria in total. After the completion of expert questionnaires and data analysis, it was found that the main factors affecting teachers' choice of AI technology are "collaborative tasks," "functional characteristics," and "modeling characteristics." In terms of evaluation criteria, the four most important aspects were found to be "learning assistance," "security," "teaching observation," and "record review." The results of this research analysis will help provide a reference for digital content development and individual recommendation services. In future work, this study can further discuss teaching innovations in digital media education, aimed at improving the quality and effectiveness of teaching and learning.