Previous studies have revealed that patients with hypertrophic cardiomyopathy (HCM) exhibit differences in symptom severity and prognosis, indicating potential HCM subtypes among these patients. Here, 793 patients with HCM were recruited at an average follow-up of 32.78 ± 27.58 months to identify potential HCM subtypes by performing consensus clustering on the basis of their echocardiography features. Furthermore, we proposed a systematic method for illustrating the relationship between the phenotype and genotype of each HCM subtype by using machine learning modeling and interactome network detection techniques based on whole-exome sequencing data. Another independent cohort that consisted of 414 patients with HCM was recruited to replicate the findings. Consequently, two subtypes characterized by different clinical outcomes were identified in HCM. Patients with subtype 2 presented asymmetric septal hypertrophy associated with a stable course, while those with subtype 1 displayed left ventricular systolic dysfunction and aggressive progression. Machine learning modeling based on personal whole-exome data identified 46 genes with mutation burden that could accurately predict subtype propensities. Furthermore, the patients in another cohort predicted as subtype 1 by the 46-gene model presented increased left ventricular end-diastolic diameter and reduced left ventricular ejection fraction. By employing echocardiography and genetic screening for the 46 genes, HCM can be classified into two subtypes with distinct clinical outcomes.

To realize the non-destructive and rapid origin discrimination of Poria cocos in batches, this study established the P. cocos origin recognition model based on hyperspectral imaging combined with machine learning. P. cocos samples from Anhui, Fujian, Guangxi, Hubei, Hunan, Henan and Yunnan were used as the research objects. Hyperspectral data were collected in the visible and near infrared band(V-band, 410-990 nm) and shortwave infrared band(S-band, 950-2 500 nm). The original spectral data were divided into S-band, V-band and full-band. With the original data(RD) of different bands, multiplicative scatter correction(MSC), standard normal variation(SNV), S-G smoothing(SGS), first derivative(FD), second derivative(SD) and other pretreatments were carried out. Then the data were classified according to three different types of producing areas: province, county and batch. The origin identification model was established by partial least squares discriminant analysis(PLS-DA) and linear support vector machine(LinearSVC). Finally, confusion matrix was employed to evaluate the optimal model, with F1 score as the evaluation standard. The results revealed that the origin identification model established by FD combined with LinearSVC had the highest prediction accuracy in full-band range classified by province, V-band range by county and full-band range by batch, which were 99.28%, 98.55% and 97.45%, respectively, and the overall F1 scores of these three models were 99.16%, 98.59% and 97.58%, respectively, indicating excellent performance of these models. Therefore, hyperspectral imaging combined with LinearSVC can realize the non-destructive, accurate and rapid identification of P. cocos from different producing areas in batches, which is conducive to the directional research and production of P. cocos.
Hyperspectral Imaging ; Wolfiporia ; China ; Least-Squares Analysis ; Support Vector Machine

In this study, visual-near infrared(VNIR), short-wave infrared(SWIR), and VNIR + SWIR fusion hyperspectral data of Polygonatum cyrtonema from different geographical origins were collected and preprocessed by first derivative(FD), second derivative(SD), Savitzky-Golay smoothing(S-G), standard normalized variate(SNV), multiplicative scatter correction(MSC), FD+S-G, and SD+S-G. Three algorithms, namely random forest(RF), linear support vector classification(LinearSVC), and partial least squares discriminant analysis(PLS-DA), were used to establish the identification models of P. cyrtonema origin from three spatial scales, i.e., province, county, and township, respectively. Successive projection algorithm(SPA) and competitive adaptive reweighted sampling(CARS) were used to screen the characteristic bands, and the P. cyrtonema origin identification models were established according to the selected characteristic bands. The results showed that(1)after FD preprocessing of VNIR+SWIR fusion hyperspectral data, the accuracy of recognition models established using LinearSVC was the highest, reaching 99.97% and 99.82% in the province origin identification model, 100.00% and 99.46% in the county origin identification model, and 99.62% and 98.39% in the township origin identification model. The accuracy of province, county, and township origin identification models reached more than 98.00%.(2)Among the 26 characteristic bands selected by CARS, after FD pretreatment, the accuracy of origin identification models of different spatial scales was the highest using LinearSVC, reaching 98.59% and 97.05% in the province origin identification model, 97.79% and 94.75% in the county origin identification model, and 90.13% and 87.95% in the township origin identification model. The accuracy of identification models of different spatial scales established by 26 characteristic bands reached more than 87.00%. The results show that hyperspectral imaging technology can realize accurate identification of P. cyrtonema origin from different spatial scales.
Spectroscopy, Near-Infrared ; Polygonatum ; Algorithms ; Random Forest ; Least-Squares Analysis

Thoracic aortic dissection (TAD) without familial clustering or syndromic features is known as sporadic TAD (STAD). So far, the genetic basis of STAD remains unknown. Whole exome sequencing was performed in 223 STAD patients and 414 healthy controls from the Chinese Han population (N = 637). After population structure and genetic relationship and ancestry analyses, we used the optimal sequence kernel association test to identify the candidate genes or variants of STAD. We found that COL3A1 was significantly relevant to STAD (P = 7.35 × 10
Aneurysm, Dissecting/genetics* ; Case-Control Studies ; Cluster Analysis ; Cohort Studies ; Collagen Type III/genetics* ; Computational Biology ; Genetic Predisposition to Disease ; Humans

The research on endophytes of medicinal plants mainly relies on the traditional culture and isolation methods. Because of their functions such as promoting host growth, improving stress resistance, promoting the accumulation of medicinal active ingredients or directly producing medicinal active ingredients, the endophytes of medicinal plants have gradually attracted wide attention. However, it was found that the strains isolated by traditional methods were not the true dominant endophytes of medicinal plants by comparing the results of traditional culture isolation with high-throughput sequencing. The blind and random nature of traditional methods leads to the lack of standards in terms of medium selection, culture time and interaction between species. On the contrary, high-throughput sequencing technology is an emerging molecular biology technology developed in recent decades. Due to its high resolution level and indepen-dent culture, it can be used for thorough analysis of the community structure and diversity of environmental microorganisms. Therefore, we proposed the strategy of using high-throughput sequencing technology to guide the traditional culture and isolation of endophytes from medicinal plants. Firstly, the endophytic structure and diversity of medicinal plants were completely clear by high-throughput sequencing technology, and the dominant endophytes of the host were unequivocal. Then according to the characteristics of each dominant endophytes design or query suitable medium for its growth to culture and isolation. Finally, the function of the isolates was studied. This method can prevent researchers from missing out on the important functional strains of the host, expand the research scope of endophytes of medicinal plants, and facilitate the in-depth excavation and utilization of endophytes of medicinal plants.
Endophytes/genetics* ; High-Throughput Nucleotide Sequencing ; Plants, Medicinal ; Research Design

Using the 260 geographical distribution records of Polygonatum cyrtonema in China, combined with 53 environmental factors, the maximum entropy modeling(MaxEnt) was used to study the ecological factors affecting the suitability distribution of P. cyrtonema. The ArcGIS software was used to predict the potential distribution of the population of P. cyrtonema. The dominant factors were chosen by using the Jackknife test and the Receiver Operating Characteristic(ROC) curve was used to evaluate the simulation. The results showed that high value of area under curve(AUC) denoted good results, which significantly differed from random predictions. Based on the evaluation criterion, the accuracies of the predictions of P. cyrtonema potential distribution in the current periods were excellent. The main environmental factors affecting the suitable growth of P. cyrtonema were the monthly precipitation, the wettest monthly precipitation, the annual average temperature range and the precipitation of November, March, February, April, May and October. There are 9 environmental factors in soil type. The potential fitness of P. cyrtonema in China is high, mainly concentra-ted in Hunan, western Hubei, Guangdong, northeastern Guangxi, southeastern Guizhou, Jiangxi, southwestern Anhui, Fujian, Zhejiang, Shaanxi, southwestern Henan and Chongqing. The growth distribution of the potential distribution area of P. cyrtonema was divided, and the zoning map of the growth suitability of P. cyrtonema was formed. Through the comparative analysis of the potential distribution range based on MaxEnt and the distribution range of literature records, the understanding of the distribution range of P. cyrtonema was expanded.
China ; Ecology ; Entropy ; Polygonatum ; Research Design ; Soil

"Assessing the quality by distinguishing features of traditional Chinese medicinal materials" is a characteristic quality evaluation system of traditional Chinese medicine, and it is also the basis of "Rating according to characters and setting the price by the grade" on the market. Astragali Radix was regarded as a famous traditional Chinese medicine (TCM), and this paper has carried out herbal textual research on the development and formation of the concept, "assessing the quality by distinguishing features of traditional Chinese medicinal materials", of Astragali Radix. The authentic medicine producing areas of Astragalus in China have experienced a great change, Gansu , Sichuan and adjacent areas before the Tang Dynasty; Shanxi during the Tang and Song Dynasty. The concept, "assessing the quality by distinguishing features of traditional Chinese medicinal materials", of Astragali Radix was formed in the Song and Ming Dynasty and still used today, which described as that the shape is "straight as an arrow"; the texture is "soft as cotton"; the section looks like" gold well and jade hurdle"; it was sweet in taste and has beany flavor. The system, "assessing the quality by distinguishing features of traditional Chinese medicinal materials", of Astragali Radix has undergone the adjustments from "true or false" to "good or bad", advance with the times, pick out the advantages from others and absorb the experience of traditional identification actively. Besides, it always returns to laconism from erudition and was summarized highly. Assessing the quality by distinguishing features of traditional Chinese medicinal materials and commodity specifications have the same root, so the former has reference meaning to revise the latter.

As a kind of famous ornamental flowers, Moutan, known as "the king of flower", mainly originates from various cultivars of Paeonia suffruticosa. Moutan Cortex, a common traditional Chinese medicine, has a long medicinal history for more than 2 000 years. At present, "Fengdanpi", which is the root bark of P. ostii mainly growing in Tongling, Anhui, is a sort of Dao-di herbs in traditional Chinese medicine. However,various editions of Chinese pharmacopoeia has been stipulating that Moutan Cortex originates from the bark root of P. suffruticosa. Textual researches on germplasm of ornamental and medicinal Moutan provided that, Xi'an, Luoyang, Pengcheng, Bozhou, Heze and some other famous cultivation centers had been formed throughout the history. In addition, medicinal practitioners in Song Dynasty had been fully aware of the medicinal differences between ornamental and wild Moutan, and preferred wild single flowers as medicinal Moutan. Moreover, none of cultivation centers of ornamental Moutan were recorded in producing areas of medicinal Moutan. So far, Fengdan and Dianjiang Moutan in Chongqing are single flowers, which is consistent with the ancient herbal books. Therefore, this paper believes that the medicinal and ornamental Moutan are two different germplasm since ancient times. And we proposethat Chinese pharmacopoeia should record P. ostii and the single-flower varieties of P. suffruticosa as the original plants of Moutan Cortex.

Based on the "Zhong Guo Ben Cao Yao Ji Kao", Chinese herbalists in past dynasties were counted and analyzed by their living period,numbers and native places. Combined with GIS, the geographical distribution and the formation causes of the four distribution centers of herbalists in past dynasties were discussed. The results showed that, there was a greater difference between the numbers of herbalists in different periods of time, which achieved to the peak in the Ming and Qing Dynasties. In addition, the distribution of herbalists in past dynasties characterized east more and west less, forming the distribution areas centered by Huizhou, Shanghai, Hangzhou and Suzhou. Besides, the geographical distributions of Chinese herbalists showed an obvious southward trend since the Song Dynasty.

Nerolidol is an important constituent of terpenoid essential oil and has excellent anti-tumor, anti-bacterial, and anti-oxidative properties. For realizing heterogenous production of nerolidol, our research firstly integrated the codon-optimized Actinidia sinensis nerolidol synthase gene (NES) into the terpenoid chassis strain FPP-001, and obtained NES-001 that could produce 2.71 mg•L⁻¹ nerolidol. Then, the N-terminal of the NES was fused with FPS by linker peptide GGGS. With this strategy, nerolidol production improved by 59.80-fold, reaching 162.07 mg•L⁻¹. Finally, by introduction of auxotrophic marker TRP1 in NES-002, the resulting strain NES-003 could produce 1 711.53 mg•L⁻¹ by high cell density fermentation method. This study provides the basis for the fermentative production of nerolidol and other sesquiterpenoids.