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Medication therapy seems to be an effective treatment for major depressive disorder (MDD). However, although the efficacies of various medicines are equal or similar on average, they vary widely among individuals. Therefore, an understanding of methods for the timely evaluation of short-term therapeutic response and prediction of symptom improvement after a specific course of medication at the individual level at the initial stage of treatment is very important. In our present study, we sought to identify a neurobiological signature of the response to short-term antidepressant treatment. Related brain network analysis was applied in resting-state electroencephalogram (EEG) datasets from patients with MDD. The corresponding EEG networks were constructed accordingly and then quantitatively measured to predict the efficacy after eight weeks of medication, as well as to distinguish the therapeutic responders from non-responders. The results of our present study revealed that the corresponding resting-state EEG networks became significantly weaker after one week of treatment, and the eventual medication efficacy was reliably predicted using the changes in those network properties within the one-week medication regimen. Moreover, the corresponding resting-state networks at baseline were also proven to precisely distinguish those responders from other individuals with an accuracy of 96.67% when using the spatial network topologies as the discriminative features. These findings consistently provide a deeper neurobiological understanding of antidepressant treatment and a reliable and quantitative approach for personalized treatment of MDD.

Patchouli (Pogostemon cablin) is an aromatic plant, and its oil has diverse applications in medicine, food, and cosmetics. Patchouli alcohol is the principal bioactive constituent of its volatile oil. In China, patchouli is typically categorized into two types: patchoulol-type (PA-type) and pogostone-type (PO-type). The study evaluated physiological and biochemical indicators, phytohormone metabolites and conducted transcriptome and proteome analyses on both two chemotypes. The PA-type exhibited higher levels of chlorophyll a, b, and carotenoids than the PO-type. In total, 35 phytohormone metabolites representing cytokinin, abscisic acid, gibberellin, jasmonic acid, and their derivatives were identified using UPLC-MS/MS, 10 of which displayed significant differences, mainly belong to cytokinins and jasmonates. Transcriptome analysis identified 4,799 differentially expressed genes (DEGs), while proteome analysis identified 150 differentially expressed proteins (DEPs). Regarding the transcriptome results, the DEGs of the PO-type showed significant downregulation in the pathways of photosynthesis, photosynthesis-antenna protein, porphyrin and chlorophyll metabolism, carotenoid biosynthesis, sesquiterpene and triterpenoid biosynthesis, and starch and sucrose metabolism, but upregulation in the pathway of zeatin synthesis. A combination of transcriptome and proteome analyses revealed that the DEGs and DEPs of lipoxygenase (LOX2), β-glucosidase, and patchouli synthase (PTS) were collectively downregulated, while the DEGs and DEPs of Zeatin O-xylosyltransferase (ZOX1) and α-amylase (AMY) were jointly upregulated in the PO-type compared to the PA-type. Differential levels of phytohormones, variations in photosynthetic efficiency, and differential expression of genes in the sesquiterpene synthesis pathway may account for the morphological and major active component differences between the two chemotypes of patchouli. The findings of this study offer novel perspectives on the underlying mechanisms contributing to the formation of the two patchouli chemotypes.

Background Pogostemon cablin (Blanco) Benth. also called patchouli, is a traditional medicinal and aromatic plant that grows mainly in Southeast Asia and China. In China, P. cablin is divided into two chemical types: the patchouliol-type and the pogostone-type. Patchouliol-type patchouli usually grow taller, with thicker stems and bigger leaves, and produce more aromatic oil. Methods To better understand the genetic differences between the two chemical types that contribute to their differences in morphology and biosynthetic capabilities, we constructed de novo transcriptomes from both chemical types using the Pacific Biosciences (PacBio) Sequel platform and performed differential expression analysis of multiple tissues using Illumina short reads. Results In this study, using single-molecule real-time (SMRT) long-read sequencing, we obtained 22.07 GB of clean data and 134,647 nonredundant transcripts from two chemical types. Additionally, we identified 126,576 open reading frames (ORFs), 100,638 coding sequences (CDSs), 4,106 long noncoding RNAs (lncRNAs) and 6,829 transcription factors (TFs) from two chemical types of P. cablin. We adopted PacBio and Illumina sequencing to identify differentially expressed transcripts (DEGs) in three tissues of the two chemical types. More DEGs were observed in comparisons of different tissues collected from the same chemical type relative to comparisons of the same tissue collected from different chemical types. Furthormore, using KEGG enrichment analysis of DEGs, we found that the most enriched biosynthetic pathways of secondary metabolites of the two chemical types were “terpenoid backbone biosynthesis”, “phenylpropanoid biosynthesis”, “plant hormone signal transduction”, “sesquiterpenoid and triterpenoid biosynthesis”, “ubiquinone and other terpenoid-quinone biosynthesis”, “flavonoid biosynthesis”, and “flavone and flavonol biosynthesis”. However, the main pathways of the patchouliol-type also included “diterpene biosynthesis” and “monoterpene biosynthesis”. Additionally, by comparing the expression levels of the three tissues verified by qRT-PCR, more DEGs in the roots were upregulated in the mevalonate (MVA) pathway in the cytoplasm, but more DEGs in the leaves were upregulated in the methylerythritol phosphate (MEP) pathway in the plastid, both of which are important pathways for terpenoids biosynthesis. These findings promote the study of further genome annotation and transcriptome research in P. cablin.

Abstract In this letter, the authors present a novel sewing gesture image detection method based on an improved single shot MultiBox detector (SSD) model. The deeper Resnet50 residual network replaces the VGG16 basic network of the original SSD model to improve the feature extraction ability. High and low level features are fused based on a feature pyramid network (FPN) for enhanced small‐target detection performance. The model is trained via transfer learning to resolve the small sample shortage problem. The proposed model shows an average precision of 88.69% on a sewing gesture data set constructed by the authors. The proposed model outperforms the Faster R‐CNN, YOLO, and SSD networks in terms of accuracy with acceptable operating speed on the same data set and fully satisfies the real‐time requirements for sewing gesture detection.

Surgery is a compelling application field for collaborative control robots. This paper proposes a gesture recognition method applied to a medical assistant robot delivering instruments to collaborate with surgeons to complete surgeries. The key to assisting the surgeon in passing instruments in the operating room is the ability to recognize the surgeon’s hand gestures accurately and quickly. Existing gesture recognition techniques suffer from poor recognition accuracy and low rate. To address the existing shortcomings, we propose an improved lightweight convolutional neural network called E-MobileNetv2. The ECA module is added to the original MobileNetv2 network model to obtain more useful features by computing the information interactions between the current channel and the adjacent channels and between the current channel and the distant channels in the feature map. We add R6-SELU activation function to enhance the network’s ability to extract features. By adjusting the shrinkable hyper-parameters, the number of parameters of the network is reduced to improve the recognition speed. The improved network model achieves excellent performance on both the self-built dataset Gesture_II and the public dataset Jester. The recognition accuracy of the improved model is 96.82%, which is 3.17 % higher than that of the original model, achieving an increase in accuracy and recognition speed.

To study the molecular mechanism by which miR-203a affects the development of CML, bioinformatics software was used to predict the upstream transcription factors and downstream target genes of miR-203a. A 5’-rapid amplification of cDNA ends assay was performed to detect gene transcription initiation sites. A chromatin immunoprecipitation assay was used to verify the binding of transcription factors and promoter regions. A double luciferase reporter gene vector was constructed to demonstrate the regulatory effect of miR-203a on target genes. Real-time PCR and western blotting were used to detect the relative expression levels of genes and proteins, respectively. The results showed that there was a binding site for the transcription factor EGR1 in the upstream promoter region of miR-203a. WT1, BMI1, and XIAP were identified as target genes regulated by miR-203a. EGR1 and miR-203a were downregulated in human peripheral blood mononuclear cells and the CML K562 cell line, while WT1, BMI1, and XIAP were upregulated. The transcription initiation site of miR-203a was identified in the upstream promoter region (G nucleotide at −339 bp), and the transcription factor EGR1 could bind to the promoter region (at −268 bp) of miR-203a and increase its expression. Over expression of miR-203a inhibited the proliferation of K562 cells. A rescue assay showed that overexpression of WT1, BMI1, and XIAP offset the antitumor effect of miR-203a. Conclusion, EGR1 positively regulated the expression of miR-203a, thus relieving the inhibition of miR-203a on the translation of its target genes (WT1, BMI1, and XIAP) and affecting the proliferation of K562 cells.

Continuous cropping (CC) restricts the development of the medicinal plant cultivation industry because it alters soil properties and the soil microbial micro-ecological environment. It can also lead to reductions in the chemical contents of medicinal plants. In this study, we intercropped continuously cropped Pogostemon cablin (patchouli) with turmeric or ginger. High-throughput sequencing was used to study the soil bacteria and fungi. Community composition, diversity, colony structure, and colony differences were also analyzed. A redundancy analysis (RDA) was used to study the interactions between soil physical and chemical factors, and the bacteria and fungi. The correlations between the soil community and the soil physical and chemical properties were also investigated. The results showed that intercropping turmeric and ginger with patchouli can improve soil microbial abundance, diversity, and community structure by boosting the number of dominant bacteria, and by improving soil bacterial metabolism and the activities of soil enzymes. They also modify the soil physical and chemical properties through changes in enzyme activity, soil pH, and soil exchangeable Ca (Ca). In summary, turmeric and ginger affect the distribution of dominant bacteria, and increase the contents of the active ingredient in patchouli. The results from this study suggested that the problems associated with continuously cropping patchouli can be ameliorated by intercropping it with turmeric and ginger.

The complete plastome of Rhoiptelea chiliantha was sequenced and assembled in this study. The circular plastome of R. chiliantha is 161,702 bp in size, which contains a large single-copy region (LSC, 90,447 bp), a short single-copy region (SSC, 19,081 bp) and two inverted repeat sequences (IRs, 26,087 bp, each). It is totally comprised of 133 genes, including 88 protein-coding genes, eight ribosomal RNA, and 37 transfer RNA. The phylogenetic analysis shows that R. chiliantha is sister to the clade including remaining Juglandaceae species.

Alstonia scholaris is an evergreen tropical tree with significant medicinal values. To better understand its genetic and genomic profiles, we sequenced and assembled the completed plastome of A. scholaris. The plastome is 154,699 bp in length, consisting of a large (LSC, 85,364 bp) and a small single-copy region (SSC, 18,027 bp), which are separated by a pair of inverted repeat regions (IRs, 25,654 bp). It possesses 116 unique genes (82 protein-coding genes, 30 tRNAs, and 4 rRNAs). Phylogenetic analysis suggests that A. scholaris is sister to the clade including remaining Apocynaceae species.

The complete plastome of Gymnotheca chinensis, an important medicinal herb, was firstly elucidated and analyzed in this study. The plastome is 161,621 bp in size, which comprises of one large single-copy (LSC) region and one small single-copy (SSC) region of 89,291 bp and 18,592 bp, respectively, separated by a pair of IR regions of 26,869 bp each. It encodes a total of 132 genes, including 87 protein-coding genes, 37 tRNA, and 8 rRNA. The phylogeny robustly supports that G. chinensis is sister to the clade including Piper kadsura, Piper cenocladum, Saruma henryi, Asarum sieboldii.

The complete plastome of Houttuynia cordata, an important medicinal and edible plant, was identified and sequenced in this study. The circular plastome is 160,217 bp in length and consists of a pair of inverted repeats (IRs 26,854 bp each), which is separated by a large single-copy region (LSC, 88,189 bp) and a small single-copy region (SSC, 18,320 bp). It encodes 132 genes, of which 114 are unique genes (80 protein-coding genes, 30 tRNAs, and 4 rRNAs). The phylogenetic analysis strongly reveals the sister group between H. cordata and the clade including Piper kadsura, Piper cenocladum, Saruma henryi, and Asarum sieboldii.

Saururus chinensis is an important medicinal plant in Southeast Asia. Here, we determined the first complete plastome of S. chinensis using high throughput Illumina sequencing technology. The S. chinensis plastome is 161,494 bp in length and presents a typical quadripartite structure consisting of one large single-copy region (LSC, 88,863 bp), one small single-copy region (SSC, 18,679 bp), and a pair of inverted repeat regions (IRs, 26,976 bp each). The phylogenetic analysis robustly supports that S. chinensis is sister to the group including the Saruma henryi, Asarum sieboldii, Piper kadsura, Piper cenocladum.