Research on Phenolic Content and Its Antioxidant Activities in Fermented Rosa rugosa 'Dianhong' Petals with Brown Sugar.

Fermented Rosa rugosa 'Dianhong' petals with brown sugar, a biologically active food popularized in Dali Prefecture, Northwest Yunnan, China, are rich in bioactive compounds, especially polyphenols, exhibiting strong antioxidant activity. This study evaluated their antioxidant activities, total phenolic contents, and concentrations of polyphenols at different fermentation conditions using different assays: DPPH free-radical scavenging activity, Trolox equivalent antioxidant capacity (TEAC), ferric reducing antioxidant power (FRAP), Folin-Ciocalteu assays, and HPLC-MS/MS and HPLC-DAD methods. The results indicated that fermentation significantly increased (p < 0.05) the antioxidant activity and polyphenol concentration of R. rugosa 'Dianhong'. Furthermore, Saccharomyces rouxii TFR-1 fermentation achieved optimal bioactivity earlier than natural fermentation. Overall, we found that the use of Saccharomyces rouxii (TFR-1) is a more effective strategy for the production of polyphenol-rich fermented R. rugosa 'Dianhong' petals with brown sugar compared to natural fermentation.

Learning a Contact Potential Field for Modeling the Hand-Object Interaction.

Estimating and synthesizing the hand's manipulation of objects is central to understanding human behaviour. To accurately model the interaction between the hand and object (referred to as the "hand-object"), we must not only focus on the pose of the hand and object, but also consider the contact between them. This contact provides valuable information for generating semantically and physically plausible grasps. In this paper, we propose an explicit contact representation called Contact Potential Field (CPF). In CPF, we model the contact between a pair of hand-object vertices as a spring-mass system. This system encodes the distance of the pair, as well as a likelihood of that contact being stable. Therefore, the system of multiple extended and compressed springs forms an elastic potential field with minimal energy at the optimal grasp position. We apply CPF to two relevant tasks, namely, hand-object pose estimation and grasping pose generation. Extensive experiments on the two challenging tasks and three commonly used datasets have demonstrated that our method can achieve state-of-the-art in several reconstruction metrics, allowing us to produce more physically plausible hand-object poses even when the ground-truth exhibits severe interpenetration or disjointedness. Our model and source codes are made publicly available at https://github.com/lixiny/CPF.

Changes in the antioxidant and anti-inflammatory activities of Rosa rugosa 'Mohong' during fermentation.

Fermented rose petals are a traditional delicacy of the Dali Bai community in Yunnan, China. Fermentation enhances the quality and nutritional value of roses, as well as their efficacy, by increasing the levels of phenolic compounds. This study aimed to investigate the significant variations in four active compounds throughout the traditional fermentation process. Four compounds in Rosa rugosa 'Mohong' were examined, and significant variations among polyphenols and antioxidant and anti-inflammatory activities were observed. These variations were studied during fermentation by Saccharomyces rouxii at varying temperatures and durations. Moreover, the results showed that gallic acid and syringic acid content significantly increased (P < 0.05) with a rise in temperature from 20°C-35 °C during fermentation. Simultaneously, rutin and quercetin levels significantly decreased (P < 0.05) at all four temperatures throughout the five periods. The antioxidant and anti-inflammatory activities of fermented R. rugosa 'Mohong' methanol extracts were dose-dependent. Our results provide valuable insights into optimizing the processing scale and quality control of fermented rose products.

Metagenomics and untargeted metabolomics analyses to unravel the formation mechanism of characteristic metabolites in Cantonese soy sauce during different fermentation stages.

Cantonese soy sauce (CSS) is an important Chinese condiment due to its distinctive flavor. Microorganisms play a significant role in the flavor formation of CSS during fermentation. However, the correlation between microbes and flavor compounds as well as the potential fermentation mechanism remained poorly uncovered. Here we revealed the dynamic changes of microbial structure and characteristics metabolites as well as their correlation of CSS during the fermentation process. Metagenomics sequencing analysis showed that Tetragenococcus halophilus, Weissella confusa, Weissella paramesenteroides, Aspergillus oryzae, Lactiplantibacillus plantarum, Weissella cibaria were top six dominant species from day 0 to day 120. Sixty compounds were either positively or tentatively identified through untargeted metabolomics profile and they were 27 peptides, amino acids and derivatives, 8 carbohydrates and conjugates, 14 organic acids and derivatives, 5 amide compounds, 3 flavonoids and 3 nucleosides. Spearman correlation coefficient indicated that Tetragenococcus halophilus, Zygosaccharomyces rouxii, Pediococcus pentosaceus and Aspergillus oryzae were significantly related with the formation of taste amino acids and derivatives, peptides and functional substances. Additionally, the metabolisms of flavor amino acids including 13 main free amino acids were also profiled. These results provided valuable information for the production practice in the soy sauce industry.

Effective Inhibition of TDP-43 Aggregation by Native State Stabilization.

Preventing the misfolding or aggregation of transactive response DNA binding protein with 43 kDa (TDP-43) is the most actively pursued disease-modifying strategy to treat amyotrophic lateral sclerosis and other neurodegenerative diseases. In this work, we provide proof of concept that native state stabilization of TDP-43 is a viable and effective strategy for treating TDP-43 proteinopathies. Firstly, we leveraged the Cryo-EM structures of TDP-43 fibrils to design C-terminal substitutions that disrupt TDP-43 aggregation. Secondly, we showed that these substitutions (S333D/S342D) stabilize monomeric TDP-43 without altering its physiological properties. Thirdly, we demonstrated that binding native oligonucleotide ligands stabilized monomeric TDP-43 and prevented its fibrillization and phase separation in the absence of direct binding to the aggregation-prone C-terminal domain. Fourthly, we showed that the monomeric TDP-43 variant could be induced to aggregate in a controlled manner, which enabled the design and implementation of a high-throughput screening assay to identify native state stabilizers of TDP-43. Altogether, our findings demonstrate that different structural domains in TDP-43 could be exploited and targeted to develop drugs that stabilize the native state of TDP-43 and provide a platform to discover novel drugs to treat TDP-43 proteinopathies.

Recombinant Full-Length TDP-43 Oligomers Retain Their Ability to Bind RNAs, Are Not Toxic, and Do Not Seed TDP-43 Aggregation in Vitro.

TAR DNA-binding protein with 43 kD (TDP-43) is a partially disordered protein that misfolds and accumulates in the brains of patients affected by several neurodegenerative diseases. TDP-43 oligomers have been reported to form due to aberrant misfolding or self-assembly of TDP-43 monomers. However, very little is known about the molecular and structural basis of TDP-43 oligomerization and the toxic properties of TDP-43 oligomers due to several reasons, including the lack of conditions available for isolating native TDP-43 oligomers or producing pure TDP-43 oligomers in sufficient quantities for biophysical, cellular, and in vivo studies. To address these challenges, we developed new protocols to generate different stable forms of unmodified and small-molecule-induced TDP-43 oligomers. Our results showed that co-incubation of TDP-43 with small molecules, such as epigallocatechin gallate (EGCG), dopamine, and 4-hydroxynonenal (4-HNE), increased the production yield of TDP-43 stable oligomers, which could be purified by size-exclusion chromatography. Interestingly, despite significant differences in the morphology and size distribution of the TDP-43 oligomer preparations revealed by transmission electron microscopy (TEM) and dynamic light scattering (DLS), they all retained the ability to bind to nucleotide DNA. Besides, circular dichroism (CD) analysis of these oligomers did not show much difference in the secondary structure composition. Surprisingly, none of these oligomer preparations could seed the aggregation of TDP-43 core peptide 279-360. Finally, we showed that all four types of TDP-43 oligomers exert very mild cytotoxicity to primary neurons. Collectively, our results suggest that functional TDP-43 oligomers can be selectively stabilized by small-molecule compounds. This strategy may offer a new approach to halt TDP-43 aggregation in various proteinopathies.

An updated patent review of GPR40/ FFAR1 modulators (2020 - present).

INTRODUCTION: Free fatty acid receptor 1 (FFAR1) is a potential therapeutic target for type 2 diabetes mellitus (T2DM) because it could clinically stimulate insulin release in a glucose-dependent manner without inducing hypoglycemia. In both the pharmaceutical industry and academic community, FFAR1 agonists have attracted considerable attention. AREAS COVERED: The review presents a patent overview of FFAR1 modulators in 2020-2023, along with chemical structures, the biological activities and therapeutic applications of the representative compounds. Our patent survey used the major electronic databases, namely SciFinder, and Web of Science and Innojoy. EXPERT OPINION: Although FFAR1 agonists exhibit outstanding advantages, they are also associated with significant challenges. At present, reducing the molecular weight and overall lipophilicity and developing tissue-specific FFAR1 agonists may be the strategies for alleviating hepatotoxicity.

Predictive values of stress hyperglycaemia and glycosylated haemoglobin on admission for long-term recovery of cardiac function in patients with acute myocardial infarction after primary percutaneous coronary intervention.

We aimed to explore the predictive values of stress hyperglycaemia (SHG) and glycosylated haemoglobin (HbA1c) levels on admission for long-term recovery of cardiac function in patients with acute myocardial infarction (AMI) after primary percutaneous coronary intervention (PPCI). A total of 210 AMI patients were randomly selected. The levels of SHG and HbA1c were measured on admission, and all patients were treated with PPCI and followed up for one year. According to the recovery status of cardiac function during follow up, the patients were divided into a good recovery group and a poor recovery group. At one year after treatment, there were statistically significant differences in the levels of SHG (6.75 ± 0.69 vs 7.81 ± 0.92 mmol/l) and HbA1c (5.13 ± 0.25 vs 5.91 ± 0.39%) between the good and poor recovery groups (p < 0.05). The levels of SHG and HbA1c were associated with long-term recovery of cardiac function (p < 0.05). The receiver operating characteristic curves were plotted, and the area under the curves of SHG and HbA1c for predicting the long-term recovery of cardiac function were > 0.70. The levels of SHG and HbA1c were closely associated with longterm recovery of cardiac function after PPCI in AMI patients, displaying high predictive values.

MECE: a method for enhancing the catalytic efficiency of glycoside hydrolase based on deep neural networks and molecular evolution.

The demand for high efficiency glycoside hydrolases (GHs) is on the rise due to their various industrial applications. However, improving the catalytic efficiency of an enzyme remains a challenge. This investigation showcases the capability of a deep neural network and method for enhancing the catalytic efficiency (MECE) platform to predict mutations that improve catalytic activity in GHs. The MECE platform includes DeepGH, a deep learning model that is able to identify GH families and functional residues. This model was developed utilizing 119 GH family protein sequences obtained from the Carbohydrate-Active enZYmes (CAZy) database. After undergoing ten-fold cross-validation, the DeepGH models exhibited a predictive accuracy of 96.73%. The utilization of gradient-weighted class activation mapping (Grad-CAM) was used to aid us in comprehending the classification features, which in turn facilitated the creation of enzyme mutants. As a result, the MECE platform was validated with the development of CHIS1754-MUT7, a mutant that boasts seven amino acid substitutions. The kcat/Km of CHIS1754-MUT7 was found to be 23.53 times greater than that of the wild type CHIS1754. Due to its high computational efficiency and low experimental cost, this method offers significant advantages and presents a novel approach for the intelligent design of enzyme catalytic efficiency. As a result, it holds great promise for a wide range of applications.

YOLO-SS-Large: A Lightweight and High-Performance Model for Defect Detection in Substations.

With the development of deep fusion intelligent control technology and the application of low-carbon energy, the number of renewable energy sources connected to the distribution grid has been increasing year by year, gradually replacing traditional distribution grids with active distribution grids. In addition, as an important component of the distribution grid, substations have a complex internal environment and numerous devices. The problems of untimely defect detection and slow response during intelligent inspections are particularly prominent, posing risks and challenges to the safe and stable operation of active distribution grids. To address these issues, this paper proposes a high-performance and lightweight substation defect detection model called YOLO-Substation-large (YOLO-SS-large) based on YOLOv5m. The model improves lightweight performance based upon the FasterNet network structure and obtains the F-YOLOv5m model. Furthermore, in order to enhance the detection performance of the model for small object defects in substations, the normalized Wasserstein distance (NWD) and complete intersection over union (CIoU) loss functions are weighted and fused to design a novel loss function called NWD-CIoU. Lastly, based on the improved model mentioned above, the dynamic head module is introduced to unify the scale-aware, spatial-aware, and task-aware attention of the object detection heads of the model. Compared to the YOLOv5m model, the YOLO-SS-Large model achieves an average precision improvement of 0.3%, FPS enhancement of 43.5%, and parameter reduction of 41.0%. This improved model demonstrates significantly enhanced comprehensive performance, better meeting the requirements of the speed and precision for substation defect detection, and plays an important role in promoting the informatization and intelligent construction of active distribution grids.

Dynamic Analysis of an Epidemic Model Considering Personal Alert on a Complex Network.

This paper proposes a SIQRS epidemic model with birth and death on a complex network, considering individual alertness. In particular, we investigate the influence of the individual behavior in the transmission of epidemics and derive the basic reproduction number depending on birth rate, death rate, alertness rate, quarantine rate. In addition, the stabilities of the disease-free equilibrium point and endemic equilibrium point are analyzed via stability theory. It is found that the emergence of individual behavior can influence the process of transmission of epidemics. Our results show that individual alertness rate is negatively correlated with basic reproduction number, while the impact of individual alertness on infectious factor is positively correlated with basic reproduction number. When the basic reproduction number is less than one, the system is stable and the disease is eventually eradicated. Nevertheless, there is an endemic equilibrium point under the condition that the basic reproduction number is more than one. Finally, numerical simulations are carried out to illustrate theoretical results.

Peripheral blood microR-146a and microR-29c expression in children with Mycoplasma pneumoniae pneumonia and its clinical value.

BACKGROUND: We investigated changes in microR-29c and microR-146a expression in the serum of children with Mycoplasma pneumoniae pneumonia, analysed their relationship with inflammatory factors and disease severity, and evaluated their diagnostic significance. METHODS: Fifty-six children with Mycoplasma pneumoniae pneumonia were enrolled as the Mycoplasma pneumoniae pneumonia group; 37 healthy children were enrolled as the control group. The microR-29c or microR-146a serum expression levels were determined using real-time quantitative reverse transcription polymerase chain reaction. Interleukin-17, tumour necrosis factor-alpha, and interleukin-1 beta levels were detected using enzyme-linked immunosorbent assay. The correlation between serum microR-29c or microR-146a expression and inflammatory factors was analysed using the Pearson's method. Receiver operating characteristic curves were used to evaluate the diagnostic value of serum microR-29c, microR-146a, and their combined detection in Mycoplasma pneumoniae pneumonia. RESULTS: Compared with that in healthy children, the microR-29c and microR-146a serum levels were significantly downregulated in children with Mycoplasma pneumoniae pneumonia; the decrease was more obvious in children with severe cases than that in those with mild cases. In addition, microR-29c and microR-146a were negatively correlated with increased expression of interleukin-17, tumour necrosis factor-alpha, and interleukin-1 beta. Receiver operating characteristic curves showed that a combination of microR-29c and microR-146a was highly suitable for diagnosing Mycoplasma pneumoniae pneumonia. CONCLUSION: Serum microR-29c and microR-146a were underexpressed in children with Mycoplasma pneumoniae pneumonia, and diagnostic accuracy was significantly improved with combined microR-29c and microR-146a detection. Therefore, both microR-29c and microR-146a levels can be used as biomarkers for the diagnosis of Mycoplasma pneumoniae pneumonia.

Case report: A novel frameshift mutation in BRSK2 causes autism in a 16-year old Chinese boy.

Serine/threonine protein kinases are involved in axon formation and neuronal polarization and have recently been implicated in autism spectrum disorder (ASD) and neurodevelopmental disorders (NDD). Here, we focus on BRSK2, which encodes brain-specific serine/threonine protein kinase 2. Although previous studies have reported 19 unrelated patients with BRSK2 pathogenic variation, only 15 of 19 patients have detailed clinical data. Therefore, more case reports are needed to enrich the phenotype associated with BRSK2 mutations. In this study, we report a novel de novo frameshift variant (c.442del, p.L148Cfs*39) identified by exome sequencing in a 16 year-old Chinese boy with ASD. The proband presented with attention-deficit, auditory hallucinations, limb tremor, and abnormal brain electrical activity mapping. This study expands the phenotypic spectrum of BRSK2-related cases and reveals the highly variable severity of disorders associated with BRSK2.

Cell recognition based on atomic force microscopy and modified residual neural network.

Cell recognition methods are in high demand in cell biology and medicine, and the method based on atomic force microscopy (AFM) shows a great value in application. The difference in mechanical properties or morphology of cells has been frequently used to detect whether cells are cancerous, but this detection method cannot be a general means for cancer cell detection, and the traditional artificial feature extraction method also has its limitations. In this work, we proposed an analytic method based on the physical properties of cells and deep learning method for recognizing cell types. The residual neural network used for recognition was modified by multi-scale convolutional fusion, attention mechanism and depthwise separable convolution, so as to optimize feature extraction and reduce operation costs. In the method, the collected cells were imaged by AFM, and the processed images were analyzed by the optimized convolutional neural network. The recognition results of two groups of cells (HL-7702 and SMMC-7721, SGC-7901 and GES-1) by this method show that the recognition rate of dataset with the combination of cell surface morphology, adhesion and Young's modulus is higher, and the recognition rate of the dataset with optimal resolution is higher. Our study indicated that the recognition of physical properties of cells using deep learning technology can serve as a universal and effective method for the automated analysis of cell information.

Methylmercury induces ectopic expression of complement components and apoptotic cell death in the retina of the zebrafish embryo.

Methylmercury (MeHg) is a well-known neurotoxin of humans and wildlife. Visual impairments, including blindness, are frequently present in human patients with MeHg poisoning and in affected animals. It is widely assumed that MeHg-induced damage to the visual cortex is the sole or primary cause of vision loss. MeHg has been shown to accumulate in the outer segments of photoreceptor cells, and to alter the thickness of the inner nuclear layer of the fish retina. However, it is unclear whether the bioaccumulated MeHg has direct deleterious effects on the retina. Herein we report that the genes encoding complement components 5 (c5), c7a, c7b, and c9 were ectopically expressed in the inner nuclear layer of the retinas of zebrafish embryos exposed to MeHg (6-50 µg/L). The numbers of apoptotic cell deaths scored in the retinas of MeHg-treated embryos significantly increased in a concentration-dependent manner. In comparison with cadmium and arsenic, ectopic expression of c5, c7a, c7b, and c9, and the observed apoptotic cell death in the retina were specific to MeHg exposure. Our data provide evidence supporting the hypothesis that MeHg has deleterious impacts on the retinal cells, especially the inner nuclear layer. We propose that MeHg-induced retinal cell death may trigger the activation of the complement system.

[Tissue distribution of Qingfei Paidu Decoction based on HPLC-MS/MS].

The tissue distribution of Qingfei Paidu Decoction was studied by HPLC-MS/MS in vivo. Hypersil GOLD C_(18) column(2.1 mm×50 mm, 1.9 µm) was used for gradient elution with acetonitrile as the mobile phase A and 0.1% formic acid solution as the mobile phase B. High-resolution liquid chromatography-mass spectrometry in both positive and negative ion scanning mode and multiple response monitoring(MRM) mode was employed to analyze the behaviors of the active components of Qingfei Paidu Decoction in diffe-rent tissues. The results showed that 19, 9, 17, 14, 22, 19, 24, and 2 compounds were detected in plasma, heart, liver, spleen, lung, kidney, large intestine, and brain, respectively. The compounds belonged to 8 groups, covering 14 herbs in the prescription. After administration with Qingfei Paidu Decoction, the compounds were rapidly distributed in various tissues, especially in the lung, liver, large intestine, and kidney. The majority of the compounds displayed secondary distribution. This study comprehensively analyzed the distribution rules of the main active components in Qingfei Paidu Decoction and provided a basis for the clinical application.

Expression patterns of serum miR-27a-3p and activating transcription factor 3 in children with bronchial asthma and their correlations with airway inflammation.

INTRODUCTION: Bronchial asthma (BA) is a heterogeneous disease characterized by chronic airway inflammation. This study investigated the serum miR-27a-3p/activating transcription factor 3 (ATF3) expression in children with BA and their correlations with airway inflammation. METHODS: Children with BA (N = 120) and healthy children (N = 108) were enrolled. Serum levels of interleukin (IL)-17, IL-6, tumor necrosis factor (TNF)-α, immunoglobulin E (IgE), miR-27a-3p, ATF3, and the number of eosinophils (EOS) were measured using enzyme-linked immunosorbent assay (ELISA), reverse transcription quantitative polymerase chain reaction (RT-qPCR), and an automatic hematology analyzer. The correlations between miR-27a-3p and ATF3 and between miR-27a-3p/ATF3 and inflammation-related factors were analyzed by the Pearson method. The diagnostic values of miR-27a-3p and ATF3 in BA were evaluated using receiver operating characteristic (ROC) curves. The influencing factors of BA were assessed using multivariate logistic regression. Finally, the targeting relation between miR-27a-3p and ATF3 was predicted and analyzed by TargetScan and Starbase databases, and dual-luciferase assay. RESULTS: There were significant differences in forced expiratory volume in 1 s (FEV1)% predicted and FEV1/forced vital capacity (FVC)%, serum levels of IgE, IL-17, IL-6, and TNF-α, and EOS numbers between healthy children and BA children. Serum miR-27a-3p was negatively correlated with ATF3 and positively correlated with inflammation-related factors in BA children. Serum ATF3 mRNA levels were negatively correlated with inflammatory factors in BA children. miR-27a-3p and ATF3 had good diagnostic values in BA children. FEV% predicted, IL-6, TNF-α, miR-27a-3p, and ATF3 were independent risk factors for BA. miR-27a-3p targeted ATF3. CONCLUSION: Serum miR-27a-3p was highly expressed, whereas ATF3 was poorly expressed in BA children, and they were significantly correlated with airway inflammation, had good diagnostic values in BA children, and were independent risk factors for asthma.

A novel rat model of Dravet syndrome recapitulates clinical hallmarks.

Dravet syndrome (DS) is a debilitating infantile epileptic encephalopathy characterized by seizures induced by high body temperature (hyperthermia), sudden unexpected death in epilepsy (SUDEP), cognitive impairment, and behavioral disturbances. The most common cause of DS is haploinsufficiency of the SCN1A gene, which encodes the voltage-gated sodium channel Nav1.1. In current mouse models of DS, the epileptic phenotype is strictly dependent on the genetic background and most mouse models exhibit drastically higher SUDEP rates than patients. Therefore, we sought to develop an alternative animal model for DS. Here, we report the generation and characterization of a Scn1a halploinsufficiency rat model of DS by disrupting the Scn1a allele. Scn1a+/- rats show reduced Scn1a expression in the cerebral cortex, hippocampus and thalamus. Homozygous null rats die prematurely. Heterozygous animals are highly susceptible to heat-induced seizures, the clinical hallmark of DS, but are otherwise normal in survival, growth, and behavior without seizure induction. Hyperthermia-induced seizures activate distinct sets of neurons in the hippocampus and hypothalamus in Scn1a+/- rats. Electroencephalogram (EEG) recordings in Scn1a+/- rats reveal characteristic ictal EEG with high amplitude bursts with significantly increased delta and theta power. After the initial hyperthermia-induced seizures, non-convulsive, and convulsive seizures occur spontaneously in Scn1a+/- rats. In conclusion, we generate a Scn1a haploinsufficiency rat model with phenotypes closely resembling DS, providing a unique platform for establishing therapies for DS.

Effects of Community Connectivity on the Spreading Process of Epidemics.

Community structure exists widely in real social networks. To investigate the effect of community structure on the spreading of infectious diseases, this paper proposes a community network model that considers both the connection rate and the number of connected edges. Based on the presented community network, a new SIRS transmission model is constructed via the mean-field theory. Furthermore, the basic reproduction number of the model is calculated via the next-generation matrix method. The results reveal that the connection rate and the number of connected edges of the community nodes play crucial roles in the spreading process of infectious diseases. Specifically, it is demonstrated that the basic reproduction number of the model decreases as the community strength increases. However, the density of infected individuals within the community increases as the community strength increases. For community networks with weak strength, infectious diseases are likely not to be eradicated and eventually will become endemic. Therefore, controlling the frequency and range of intercommunity contact will be an effective initiative to curb outbreaks of infectious diseases throughout the network. Our results can provide a theoretical basis for preventing and controlling the spreading of infectious diseases.

Absence of critical thickness for polar skyrmions with breaking the Kittel's law.

The period of polar domain (d) in ferroics was commonly believed to scale with corresponding film thicknesses (h), following the classical Kittel's law of d ∝ [Formula: see text]. Here, we have not only observed that this relationship fails in the case of polar skyrmions, where the period shrinks nearly to a constant value, or even experiences a slight increase, but also discovered that skyrmions have further persisted in [(PbTiO3)2/(SrTiO3)2]10 ultrathin superlattices. Both experimental and theoretical results indicate that the skyrmion periods (d) and PbTiO3 layer thicknesses in superlattice (h) obey the hyperbolic function of d = Ah + [Formula: see text] other than previous believed, simple square root law. Phase-field analysis indicates that the relationship originates from the different energy competitions of the superlattices with PbTiO3 layer thicknesses. This work exemplified the critical size problems faced by nanoscale ferroelectric device designing in the post-Moore era.