From Bench to Clinic: A Nitroreductase Rv3368c-Responsive Cyanine-Based Probe for the Specific Detection of Live Mycobacterium tuberculosis.

Tuberculosis (TB), characterized by high mortality and low diagnosis, is caused by a single pathogen, Mycobacterium tuberculosis (Mtb). Imaging tools that can be used to track Mtb without pre-labeling and to diagnose live Mtb in clinical samples can shorten the gap between bench and clinic, fuel the development of novel anti-TB drugs, strengthen TB prevention, and improve patient treatment. In this study, we report an unprecedented novel nitroreductase-responsive cyanine-based fluorescent probe (Cy3-NO2-tre) that rapidly and specifically labels Mtb and detects it in clinical samples. Cy3-NO2-tre generated fluorescence after activation by a specific nitroreductase, Rv3368c, which is conserved in the Mycobacteriaceae. Cy3-NO2-tre effectively imaged mycobacteria within infected host cells, tracked the infection process, and visualized Mycobacterium smegmatis being endocytosed by macrophages. Cy3-NO2-tre also detected Mtb in the sputum of patients with TB and exhibited excellent photostability. Furthermore, the Cy3-NO2-tre/auramine O percentage change within 7 ± 2 days post drug treatment in the sputum of inpatients was closely correlated with the reexamination results of the chest computed tomography, strongly demonstrating the clinical application of Cy3-NO2-tre as a prognostic indicator in monitoring the therapeutic efficacy of anti-TB drugs in the early patient care stage.

Identification and function analysis of GABA branch three gene families in the cotton related to abiotic stresses.

γ -aminobutyric acid (GABA) is closely related to the growth, development and stress resistance of plants. Combined with the previous study of GABA to promote the cotton against abiotic stresses, the characteristics and expression patterns of GABA branch gene family laid the foundation for further explaining its role in cotton stress mechanism. Members of GAD, GAB-T and SSADH (three gene families of GABA branch) were identified from the Gossypium hirsutum, Gossypium barbadense, Gossypium arboreum and Gossypium raimondii genome. The GABA branch genes were 10 GAD genes, 4 GABA-T genes and 2 SSADH genes. The promoter sequences of genes mainly contains response-related elements such as light, hormone and environment.Phylogenetic analysis shows that GAD indicating that even in the same species, the homologous sequences in the family. The GABA-T gene of each cotton genus was in sum the family had gene loss in the process of dicotyledon evolution. SSADH families Gossypium hirsutum, Gossypium barbadense, Gossypium arboreum and Gossypium raimondii were closely related to the dicot plants.GABA gene is involved in the regulation of salt stress and high temperature in Gossypium hirsutum.GABA attenuated part of the abiotic stress damage by increasing leaf protective enzyme activity and reducing reactive oxygen species production.This lays the foundation for a thorough analysis of the mechanism of GABA in cotton stress resistance.

Ultrasound-Based Multi-Planar Bilateral Comparisons as a Diagnostic and Treatment-Definition Method for Unilateral Peripheral Nerve Entrapment.

OBJECTIVE: The primary goal was to determine the performance of the cross-section area swelling rate (CSASR) for diagnostic and therapeutic purposes based on the reference standard of electrodiagnosis examination (EDX) in this diagnostic test study. METHODS: First, patients with symptoms like unilateral carpal tunnel syndrome (CTS), cubital tunnel syndrome (CuTS), and radial nerve compression (RNC) underwent EDX and ultrasound examination. Second, patients with positive ultrasound were calculated for the CSASR of diseased nerve. Based on previously established CSASR criteria, each patient was categorized as having or not having peripheral nerve entrapment, and for those meeting diagnostic criteria, non-surgical or surgical treatment was recommended. Then, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy rate (ACC) of ultrasound diagnosis and therapeutic decision-making were calculated based on the reference standard of EDX that had been historically used in the practice. RESULTS: The total sensitivity, specificity, PPV, NPV, and ACC of ultrasound diagnosis are respectively 93.4, 85.2, 94.7, 82.1, and 91.3%. Which of therapeutic decision-making by ultrasound are, respectively, 83.3, 52.2, 78.4, 60.0, and 73.2%. CONCLUSION: The sensitivity and Youden's index of CSASR diagnostic threshold for CuTS is higher than other ultrasound methods. The CSASR diagnostic threshold for CuTS has a potential diagnostic role, but the current date is still not enough to support the potential diagnostic role for CTS or RNS. There is insufficient evidence to suggest that CSASR for CuTS can be used in isolation for diagnosis. Additional research is needed to confirm the diagnostic role of CSASR. The current results suggest that this ultrasound examination method is not suitable for therapeutic decision-making.

Learning-Based Hierarchical Decision-Making Framework for Automatic Driving in Incompletely Connected Traffic Scenarios.

The decision-making algorithm serves as a fundamental component for advancing the level of autonomous driving. The end-to-end decision-making algorithm has a strong ability to process the original data, but it has grave uncertainty. However, other learning-based decision-making algorithms rely heavily on ideal state information and are entirely unsuitable for autonomous driving tasks in real-world scenarios with incomplete global information. Addressing this research gap, this paper proposes a stable hierarchical decision-making framework with images as the input. The first step of the framework is a model-based data encoder that converts the input image data into a fixed universal data format. Next is a state machine based on a time series Graph Convolutional Network (GCN), which is used to classify the current driving state. Finally, according to the state's classification, the corresponding rule-based algorithm is selected for action generation. Through verification, the algorithm demonstrates the ability to perform autonomous driving tasks in different traffic scenarios without relying on global network information. Comparative experiments further confirm the effectiveness of the hierarchical framework, model-based image data encoder, and time series GCN.

LncRNA WEE2-AS1 is a diagnostic biomarker that predicts poor prognoses in patients with glioma.

BACKGROUND: Glioma is characterized by high morbidity, high mortality, and poor prognosis. Despite tremendous advances in the treatment of glioma, the prognosis of patients with glioma is still unsatisfactory. There is an urgent need to discover novel molecular markers that effectively predict prognosis in patients with glioma. The investigation of the role of WEE2-AS1 in various tumors is an emerging research field, but the biological function and prognostic value of WEE2-AS1 in glioma have rarely been reported. This study aimed to assess the value of WEE2-AS1 as a potential prognostic marker of glioma. METHODS: Gene expression (RNA-Seq) data of patients with glioma were extracted from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. The Wilcoxon rank sum test was used to analyze the expression of WEE2-AS1 in the cells and tissues of glioma. The Kruskal-Wallis rank sum test, Wilcoxon rank sum test, and logistic regression were used to evaluate the relationship between clinical variables and expression of WEE2-AS1. Cox regression analysis and the Kaplan-Meier method were used to evaluate the prognostic factors in glioma. A nomogram based on Cox multivariate analysis was used to predict the impact of WEE2-AS1 on glioma prognosis. Gene Set Enrichment Analysis (GSEA) was used to identify key WEE2-AS1-associated signaling pathways. Spearman's rank correlation was used to elucidate the association between WEE2-AS1 expression and immune cell infiltration levels. RESULTS: We found that WEE2-AS1 was overexpressed in a variety of cancers, including glioma. High expression of WEE2-AS1 was associated with glioma progression. We determined that the expression of WEE2-AS1 might be an independent risk factor for the survival and prognosis of patients with glioma. We further observed that the mechanism of WEE2-AS1-mediated tumorigenesis involved neuroactive ligand-receptor interaction, cell cycle, and the infiltration of immune cells into the glioma microenvironment. CONCLUSION: These findings demonstrate that WEE2-AS1 is a promising biomarker for the diagnosis and prognosis of patients with glioma. An increased understanding of its effects on the regulation of cell growth may lead to the development of clinical applications that improve the prognostic status of patients with glioma.

3D printable, thermo-responsive, self-healing, graphene oxide containing self-assembled hydrogels formed from block copolymer wormlike micelles.

Graphene oxide (GO) containing block copolymer nanocomposite hydrogels formed from poly(glycerol monomethacrylate-block-hydroxypropyl methacrylate) (PGMA-PHPMA) wormlike micelles were prepared by either mixing GO and copolymer at low temperature or via in situ reversible addition-fragmentation chain-transfer (RAFT) polymerisation-induced self-assembly (PISA) of HPMA in the presence of a PGMA macromolecular chain-transfer agent and GO flakes. Hydrogels containing 15-25% w/w copolymer and 0 and 8% w/w GO, based on copolymer, were investigated and the maximum gel strength measured was ∼33 kPa for a 25% w/w copolymer gel prepared by in situ polymerisation and containing 2% w/w GO based on copolymer. This gel strength represents a fifteen-fold increase over the same copolymer gel without the addition of GO. The nanocomposite gels were found to recover efficiently after the application of high shear, with up to 98% healing efficiency within seconds. These gels are also 3D printable, self-healing, adhesive and temperature responsive on cooling and re-heating. The observed properties were both GO and copolymer concentration dependent, and tensile testing demonstrated that the nanocomposite gels had higher moduli, elongation at break and toughness than gels prepared without GO.

Follow-up outcomes of different bypass surgical modalities for adults with ischaemic-type moyamoya disease.

PURPOSE: The preferred surgical method for treating adults with moyamoya disease (MMD) remains controversial. The purpose of this study was to compare the efficacy of different surgical methods in the treatment of adults with ischaemic-type MMD. METHODS: We retrospectively analyzed the data of patients with ischaemic-type MMD who underwent indirect bypass (IB), direct bypass (DB), or combined bypass (CB) at the First Affiliated Hospital of Zhengzhou University from January 2013 to December 2019. Postoperative complications, improvements in neurological function, haemodynamics, recurrent stroke and neovascularization were compared. RESULTS: A total of 310 adults (371 hemispheres) with ischaemic-type MMD were included in our study. Ninety, 127, and 154 hemispheres underwent IB, DB and CB, respectively. A total of 24 (6.5%) ischaemic events and 8 (2.8%) symptomatic hyperperfusion events occurred after the operations. There was no significant difference in postoperative complications among the three types of surgery (p = 0.300). During the follow-up period, there were 21 cases (5.7%) of recurrent ischaemia and 12 cases (3.2%) of recurrent haemorrhage. Kaplan-Meier survival analysis showed that the ischaemia-free survival of the CB group was significantly longer than that of the IB group (p = 0.047), but there was no significant difference in haemorrhage-free survival among the three groups (p = 0.660). Six months after the operation, DB and CB were superior to IB in improving cerebral blood flow and neovascularization (p = 0.002), but there was no significant difference in the improvement of neurological function among the three groups at the last follow-up (p = 0.784). CONCLUSION: The three surgical methods achieved satisfactory results in the treatment of ischaemic-type MMD. DB and CB can significantly improve haemodynamics and reduce recurrent stroke. In terms of improving neurological function, the curative effect of the three surgical methods remains to be further explored.

Research into Autonomous Vehicles Following and Obstacle Avoidance Based on Deep Reinforcement Learning Method under Map Constraints.

Compared with traditional rule-based algorithms, deep reinforcement learning methods in autonomous driving are able to reduce the response time of vehicles to the driving environment and fully exploit the advantages of autopilot. Nowadays, autonomous vehicles mainly drive on urban roads and are constrained by some map elements such as lane boundaries, lane driving rules, and lane center lines. In this paper, a deep reinforcement learning approach seriously considering map elements is proposed to deal with the autonomous driving issues of vehicles following and obstacle avoidance. When the deep reinforcement learning method is modeled, an obstacle representation method is proposed to represent the external obstacle information required by the ego vehicle input, aiming to address the problem that the number and state of external obstacles are not fixed.

Graph Reinforcement Learning-Based Decision-Making Technology for Connected and Autonomous Vehicles: Framework, Review, and Future Trends.

The proper functioning of connected and autonomous vehicles (CAVs) is crucial for the safety and efficiency of future intelligent transport systems. Meanwhile, transitioning to fully autonomous driving requires a long period of mixed autonomy traffic, including both CAVs and human-driven vehicles. Thus, collaborative decision-making technology for CAVs is essential to generate appropriate driving behaviors to enhance the safety and efficiency of mixed autonomy traffic. In recent years, deep reinforcement learning (DRL) methods have become an efficient way in solving decision-making problems. However, with the development of computing technology, graph reinforcement learning (GRL) methods have gradually demonstrated the large potential to further improve the decision-making performance of CAVs, especially in the area of accurately representing the mutual effects of vehicles and modeling dynamic traffic environments. To facilitate the development of GRL-based methods for autonomous driving, this paper proposes a review of GRL-based methods for the decision-making technologies of CAVs. Firstly, a generic GRL framework is proposed in the beginning to gain an overall understanding of the decision-making technology. Then, the GRL-based decision-making technologies are reviewed from the perspective of the construction methods of mixed autonomy traffic, methods for graph representation of the driving environment, and related works about graph neural networks (GNN) and DRL in the field of decision-making for autonomous driving. Moreover, validation methods are summarized to provide an efficient way to verify the performance of decision-making methods. Finally, challenges and future research directions of GRL-based decision-making methods are summarized.

Nerve merging repair in the replantation of a severed limb with defects in multiple nerves: five cases and long-term follow-up.

BACKGROUND: Repairing all nerves is challenging in cases of upper arm avulsion combined with defects in multiple nerves because the donor area for autogenous nerve transplantation is limited and the outcomes of long-segment allogeneic nerve transplantation are poor. Based on the principle of magnified nerve regeneration, we present a method called nerve merging repair, the feasibility of which needs to be confirmed in clinical practice. METHODS: The nerve merging repair method relies on the use of fewer proximal nerves to innervate more distal nerves and depends mainly on whether the radial nerve (RN) can repair itself. In the case of defects in multiple nerves precluding RN self-repair, median-(median + radial) (M-(M + R)) repair is performed. If the RN can undergo self-repair, median-(median + ulnar) (M-(M + U)) or ulnar-(ulnar + median) (U-(U + M)) is used to repair the three nerves. Five cases were included in the study and involved the analysis of joint motor function, muscle strength and sensory recovery of the affected limb. RESULTS: The replanted limb survived in all 5 cases. Follow-up visits were conducted with the patients for 51-80 months, during which they experienced satisfactory recovery of skin sensation, elbow flexion and extension and partial recovery of hand muscle strength. CONCLUSIONS: To a certain extent, treatment with the nerve merging repair method improved the sensory and motor function of the affected limb and limited the loss of function of the donor nerve area. This intervention provides a new approach for repairing long-segment defects in multiple nerves caused by avulsion amputation of the upper limb.

Multi-Agent Decision-Making Modes in Uncertain Interactive Traffic Scenarios via Graph Convolution-Based Deep Reinforcement Learning.

As one of the main elements of reinforcement learning, the design of the reward function is often not given enough attention when reinforcement learning is used in concrete applications, which leads to unsatisfactory performances. In this study, a reward function matrix is proposed for training various decision-making modes with emphasis on decision-making styles and further emphasis on incentives and punishments. Additionally, we model a traffic scene via graph model to better represent the interaction between vehicles, and adopt the graph convolutional network (GCN) to extract the features of the graph structure to help the connected autonomous vehicles perform decision-making directly. Furthermore, we combine GCN with deep Q-learning and multi-step double deep Q-learning to train four decision-making modes, which are named the graph convolutional deep Q-network (GQN) and the multi-step double graph convolutional deep Q-network (MDGQN). In the simulation, the superiority of the reward function matrix is proved by comparing it with the baseline, and evaluation metrics are proposed to verify the performance differences among decision-making modes. Results show that the trained decision-making modes can satisfy various driving requirements, including task completion rate, safety requirements, comfort level, and completion efficiency, by adjusting the weight values in the reward function matrix. Finally, the decision-making modes trained by MDGQN had better performance in an uncertain highway exit scene than those trained by GQN.

Generalized Single-Vehicle-Based Graph Reinforcement Learning for Decision-Making in Autonomous Driving.

In the autonomous driving process, the decision-making system is mainly used to provide macro-control instructions based on the information captured by the sensing system. Learning-based algorithms have apparent advantages in information processing and understanding for an increasingly complex driving environment. To incorporate the interactive information between agents in the environment into the decision-making process, this paper proposes a generalized single-vehicle-based graph neural network reinforcement learning algorithm (SGRL algorithm). The SGRL algorithm introduces graph convolution into the traditional deep neural network (DQN) algorithm, adopts the training method for a single agent, designs a more explicit incentive reward function, and significantly improves the dimension of the action space. The SGRL algorithm is compared with the traditional DQN algorithm (NGRL) and the multi-agent training algorithm (MGRL) in the highway ramp scenario. Results show that the SGRL algorithm has outstanding advantages in network convergence, decision-making effect, and training efficiency.

A combination of genome-wide and transcriptome-wide association studies reveals genetic elements leading to male sterility during high temperature stress in cotton.

Global warming has reduced the productivity of many field-grown crops, as the effects of high temperatures can lead to male sterility in such plants. Genetic regulation of the high temperature (HT) response in the major crop cotton is poorly understood. We determined the functionality and transcriptomes of the anthers of 218 cotton accessions grown under HT stress. By analyzing transcriptome divergence and implementing a genome-wide association study (GWAS), we identified three thermal tolerance associated loci which contained 75 protein coding genes and 27 long noncoding RNAs, and provided expression quantitative trait loci (eQTLs) for 13 132 transcripts. A transcriptome-wide association study (TWAS) confirmed six causal elements for the HT response (three genes overlapped with the GWAS results) which are involved in protein kinase activity. The most susceptible gene, GhHRK1, was confirmed to be a previously uncharacterized negative regulator of the HT response in both cotton and Arabidopsis. These functional variants provide a new understanding of the genetic basis for HT tolerance in male reproductive organs.

Disrupted Genome Methylation in Response to High Temperature Has Distinct Affects on Microspore Abortion and Anther Indehiscence.

High-temperature (HT) stress induces male sterility, leading to yield reductions in crops. DNA methylation regulates a range of processes involved in plant development and stress responses, but its role in male sterility under HT remains unknown. Here, we investigated DNA methylation levels in cotton (Gossypium hirsutum) anthers under HT and normal temperature (NT) conditions by performing whole-genome bisulfite sequencing to investigate the regulatory roles of DNA methylation in male fertility under HT. Global disruption of DNA methylation, especially CHH methylation (where H = A, C, or T), was detected in an HT-sensitive line. Changes in the levels of 24-nucleotide small-interfering RNAs were significantly associated with DNA methylation levels. Experimental suppression of DNA methylation led to pollen sterility in the HT-sensitive line under NT conditions but did not affect the normal dehiscence of anther walls. Further transcriptome analysis showed that the expression of genes in sugar and reactive oxygen species (ROS) metabolic pathways were significantly modulated in anthers under HT, but auxin biosynthesis and signaling pathways were only slightly altered, indicating that HT disturbs sugar and ROS metabolism via disrupting DNA methylation, leading to microspore sterility. This study opens up a pathway for creating HT-tolerant cultivars using epigenetic techniques.

Review on Vehicle Detection Technology for Unmanned Ground Vehicles.

Unmanned ground vehicles (UGVs) have great potential in the application of both civilian and military fields, and have become the focus of research in many countries. Environmental perception technology is the foundation of UGVs, which is of great significance to achieve a safer and more efficient performance. This article firstly introduces commonly used sensors for vehicle detection, lists their application scenarios and compares the strengths and weakness of different sensors. Secondly, related works about one of the most important aspects of environmental perception technology-vehicle detection-are reviewed and compared in detail in terms of different sensors. Thirdly, several simulation platforms related to UGVs are presented for facilitating simulation testing of vehicle detection algorithms. In addition, some datasets about UGVs are summarized to achieve the verification of vehicle detection algorithms in practical application. Finally, promising research topics in the future study of vehicle detection technology for UGVs are discussed in detail.

Ruthenium-Catalyzed Selectively Oxidative C-H Alkenylation of N-Acylated Aryl Sulfonamides by Using Molecular Oxygen as an Oxidant.

A ruthenium-catalyzed sulfonamide-directed ortho aryl C-H alkenylation/annulation to afford five-membered sultam by using of molecular oxygen as an oxidant is reported in this article. Compared to the previous transition-metal-catalyzed C-H alkenylation of aryl sulfonamides, no excess metal salt oxidant was required in this method. A wide sulfonamide substrates scope and good regioselectivity and site-selectivity make this Ru-catalyzed method more attractive. Importantly, this method can not only be used to effectively prepare the biologically active five-membered sultam molecules but also be efficiently applied to the late-stage modification of sulfonamide drugs.

Bone marrow-derived mesenchymal stem cells-derived exosomes prevent oligodendrocyte apoptosis through exosomal miR-134 by targeting caspase-8.

Ischemic stroke causes severe brain damage and remains one of the leading causes of morbidity and mortality worldwide. The microRNA-134 (miR-134) is involved in regulating the process of ischemia injury in neural cells and brain with ischemia stroke. The role of miR-134 in ischemic stroke remains poorly understood. The purpose of the current study was to investigate the effect of bone marrow-derived mesenchymal stem cells (BMSCs)-derived exosomal miR-134 on rat oligodendrocytes (OLs) apoptosis and its underlying mechanism of action. The results demonstrated that levels of miR-134 in BMSCs-exosome decreased but increased incaspase-8 after oxygen-glucose deprivation (OGD) treatment. Exosomal miR-134 significantly inhibited apoptosis by decreasing caspase-8 expression and activity in OGD-treated group cultured with BMSCs-exosome and OLs. In addition, the miR-134 mimics decreased caspase-8 expression in OGD-treated OLs, whereas miR-134 inhibitors exacerbated the changes in the expression of the procaspase-8 and caspase-8 cleaved product proteins caused by OGD. The caspase-8 knockdown using caspase-8 small interfering RNA decreased OLs apoptosis, reversing the improvements that the miR-134 inhibited cells apoptosis by targeting caspase-8. Taken together, these results demonstrated that BMSCs-derived exosomes suppressed OLs apoptosis through exosomal miR-134 by negatively regulating the caspase-8-dependent apoptosis pathway and may, therefore, be a novel potential therapeutic target for ischemic stroke treatment.

Development of Industrial Oil Crop Crambe abyssinica for Wax Ester Production through Metabolic Engineering and Cross Breeding.

As an important industrial feedstock, wax esters (WEs) have been used as lubricants in a number of technical processes. There is however currently no large-scale biological source for WE production and alteration in metabolic pathways of plant oils for producing WEs could be attractive to the commercial markets. Here, we present the breeding results of long-term studies on successful development of new crambe lines producing WEs through genetic engineering and cross breeding. The transgenic crambe lines producing WEs at over 25% of the total seed oil were first generated by introduction of the jojoba WE biosynthetic genes ScFAR and ScWS. Further improvement of the lines aiming at improving oxidative stability of WEs was achieved through introducing the CaFAD2-RNAi gene into these lines by crossing. The hybrid lines possessed similar agronomic traits to the wild type and a stable level of WEs over several generations, suggesting a high potential of crambe as an industrial crop for WE production.

Comparison of Dinoprostone and Oxytocin for the Induction of Labor in Late-Term Pregnancy and the Rate of Cesarean Section: A Retrospective Study in Ten Centers in South China.

BACKGROUND Dinoprostone is the recommended primary option for induction of labor (IOL) in late-term pregnancies (LTPs). However, oxytocin is used in developing and rural areas, and studies have supported similar effectiveness for oxytocin and dinoprostone in reducing the rate of cesarean delivery of LTPs with a Bishop's score of between 4-6. This study aimed to compare dinoprostone and oxytocin for IOL in LTPs and the rate of cesarean section in ten centers in South China. MATERIAL AND METHODS A retrospective study included 1,408 women with LTP, with subgroups including a Bishop's score of 0-3 and 4-6. Rates of cesarean delivery were compared between women given vaginal dinoprostone and intravenous oxytocin for IOL. Secondary outcomes included the duration of labor, and maternal and fetal complications. RESULTS Comparison between women who received oxytocin (N=365) and dinoprostone (N=1,043) showed significantly lower rates of cesarean delivery with dinoprostone, but no significant difference between the subgroups with Bishop's scores of 0-3 and 4-6. The interval between induction to labor and duration of the active phase of labor were significantly reduced in the dinoprostone group with a Bishop's score of between 4-6. CONCLUSIONS For LTPs with a Bishop's score of 0-3, dinoprostone was superior to oxytocin for IOL with a lower rate of cesarean delivery, but both agents had a similar outcome for women with a Bishop's score of 4-6. These findings may have implications for the choice of agent used in IOL when dinoprostone is unavailable.

Propeller perforator flaps from the dorsal digital artery perforator chain for repairing soft tissue defects of the finger.

BACKGROUND: When restoring the appearance and function of the fingers, hand surgeons face a challenge in choosing a suitable surgical method to repair finger skin defects. METHODS: In this study, we designed a long elliptical flap based on a propeller perforator flap and located slightly toward the dorsal lateral aspect of the finger. The flap with a pedicle consisting of the dorsal perforator of the distal digital artery and dorsal digital artery perforator chain is rotated to cover a large wound on the distal end. From December 2014 to December 2017, 10 patients with finger soft tissue defects were treated with the propeller perforator flap described in this study. RESULTS: All flaps survived after surgery, and 2 had a transient venous congestion. After a follow-up period of 3 to 12 months, the static two-point discrimination of the flap was 8.06 ± 1.75 mm, and the range of motion was 149.4 ± 12.9°. This designed flap can span several angiosomes supplied by the perforators. Due to the inclusion of a vessel chain between the dorsal digital artery perforators, the length-to-width ratio of the flap can be up to 3:1. CONCLUSIONS: This technique increases the size of flap that can be harvested safely while retaining a reliable blood supply. The present study describes a new method for repairing soft tissue defects of the finger by using the technique of propeller perforator flaps based on dorsal digital artery perforator chains. TRIAL REGISTRATION: The registration number of this study is ChiCTR1800014588; it has been retrospectively registered with Chinese Clinical Trial Registry (chictr.org.cn), 18/11/2019.