Impact mechanism of social-related social media use on the job performance of caregivers of older adults.

This study investigated the impact mechanism of social-related social media use on the job performance of caregivers of older adults through mental health and analyzed gender differences. A total of 358 valid questionnaires were collected and analyzed using SPSS and Smart PLS. The results showed that mental health plays an important role in the relationship between social-related social media use and job performance. Such social media use can improve psychological well-being and reduce psychological distress by promoting relaxation experience. Psychological well-being has a significant positive impact on job performance. In addition, significant differences exist in the impact path of social-related social media use on psychological distress among different gender groups. The findings of this study can assist nursing homes in assessing the use of social media within their organizations and provide methodological references for enhancing the job performance of caregivers of older adults.

Complete Region of Interest for Unconstrained Palmprint Recognition.

Unconstrained palmprint images have shown great potential for recognition applications due to their lower restrictions regarding hand poses and backgrounds during contactless image acquisition. However, they face two challenges: 1) Unclear palm contours and finger-valley points of unconstrained palmprint images make it difficult to locate landmarks to crop the palmprint region of interest (ROI), and 2) large intra-class diversities of unconstrained palmprint images hinder the learning of intra-class-invariant palmprint features. In this paper, we propose to directly extract the complete palmprint region as the ROI (CROI) using the detection-style CenterNet without requiring the detection of any landmarks, and large intra-class diversities may occur. To address this, we further propose a palmprint feature alignment and learning hybrid network (PalmALNet) for unconstrained palmprint recognition. Specifically, we first exploit and align the multi-scale shallow representation of unconstrained palmprint images via deformable convolution and alignment-aware supervision, such that the pixel gaps of the intra-class palmprint CROIs can be minimized in shallow feature space. Then, we develop multiple triple-attention learning modules by integrating spatial, channel, and self-attention operations into convolution to adaptively learn and highlight the latent identity-invariant palmprint information, enhancing the overall discriminative power of the palmprint features. Extensive experimental results on four challenging palmprint databases demonstrate the promising effectiveness of both the proposed PalmALNet and CROI for unconstrained palmprint recognition.

Tensorized Multi-View Low-Rank Approximation Based Robust Hand-Print Recognition.

Since hand-print recognition, i.e., palmprint, finger-knuckle-print (FKP), and hand-vein, have significant superiority in user convenience and hygiene, it has attracted greater enthusiasm from researchers. Seeking to handle the long-standing interference factors, i.e., noise, rotation, shadow, in hand-print images, multi-view hand-print representation has been proposed to enhance the feature expression by exploiting multiple characteristics from diverse views. However, the existing methods usually ignore the high-order correlations between different views or fuse very limited types of features. To tackle these issues, in this paper, we present a novel tensorized multi-view low-rank approximation based robust hand-print recognition method (TMLA_RHR), which can dexterously manipulate the multi-view hand-print features to produce a high-compact feature representation. To achieve this goal, we formulate TMLA_RHR by two key components, i.e., aligned structure regression loss and tensorized low-rank approximation, in a joint learning model. Specifically, we treat the low-rank representation matrices of different views as a tensor, which is regularized with a low-rank constraint. It models the across information between different views and reduces the redundancy of the learned sub-space representations. Experimental results on eight real-world hand-print databases prove the superiority of the proposed method in comparison with other state-of-the-art related works.

Exogenous methyl jasmonate treatment induced the transcriptional responses and accumulation of volatile terpenoids in Oenanthe javanica (Blume) DC.

Water dropwort is favored by consumers for its unique flavor and medicinal value. Terpenoids were identified as the main volatile compounds related to its flavor. In this study, water dropwort was treated with different concentrations of exogenous methyl jasmonate (MeJA). The contents of volatile terpenoids were determined under various MeJA treatments. The results indicated that 0.1 mM of MeJA most effectively promoted the biosynthesis of flavor-related terpenoids in water dropwort. Terpinolene accounted the highest proportion among terpene compounds in water dropwort. The contents of jasmonates in water dropwort were also increased after exogenous MeJA treatments. Transcriptome analysis indicated that DEGs involved in the terpenoid biosynthesis pathway were upregulated. The TPS family was identified from water dropwort, and the expression levels of Oj0473630, Oj0287510 and Oj0240400 genes in TPS-b subfamily were consistent with the changes of terpene contents under MeJA treatments. Oj0473630 was cloned from the water dropwort and designated as OjTPS3, which is predicted to be related to the biosynthesis of terpinolene in water dropwort. Subcellular localization indicated that OjTPS3 protein was localized in chloroplast. Protein purification and enzyme activity of OjTPS3 protein were conducted. The results showed that the purified OjTPS3 protein catalyzed the biosynthesis of terpinolene by using geranyl diphosphate (GPP) as substrate in vitro. This study will facilitate to further understand the molecular mechanism of terpenoid biosynthesis and provide a strategy to improve the flavor of water dropwort.

Comprehensive Analysis of Fatty Acid Metabolism in Diabetic Nephropathy from the Perspective of Immune Landscapes, Diagnosis and Precise Therapy.

Objective: Diabetic nephropathy (DN) represents the principal cause of end-stage renal diseases worldwide, lacking effective therapies. Fatty acid (FA) serves as the primary energy source in the kidney and its dysregulation is frequently observed in DN. Nevertheless, the roles of FA metabolism in the occurrence and progression of DN have not been fully elucidated. Methods: Three DN datasets (GSE96804/GSE30528/GSE104948) were obtained and combined. Differentially expressed FA metabolism-related genes were identified and subjected to DN classification using "ConsensusClusterPlus". DN subtypes-associated modules were discovered by "WGCNA", and module genes underwent functional enrichment analysis. The immune landscapes and potential drugs were analyzed using "CIBERSORT" and "CMAP", respectively. Candidate diagnostic biomarkers of DN were screened using machine learning algorithms. A prediction model was constructed, and the performance was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). The online tool "Nephroseq v5" was conducted to reveal the clinical significance of the candidate diagnostic biomarkers in patients with DN. A DN mouse model was established to verify the biomarkers' expression. Results: According to 39 dysregulated FA metabolism-related genes, DN samples were divided into two molecular subtypes. Patients in Cluster B exhibited worse outcomes with a different immune landscape compared with those in Cluster A. Ten potential small-molecular drugs were predicted to treat DN in Cluster B. The diagnostic model based on PRKAR2B/ANXA1 was created with ideal predictive values in early and advanced stages of DN. The correlation analysis revealed significant association between PRKAR2B/ANXA1 and clinical characteristics. The DN mouse model validated the expression patterns of PRKAR2B/ANXA1. Conclusion: Our study provides new insights into the role of FA metabolism in the classification, immunological pathogenesis, early diagnosis, and precise therapy of DN.

Glufosinate-ammonium causes liver injury in zebrafish by blocking the Nrf2 pathway.

Glufosinate-ammonium (GLA) is a widely used herbicide, but less research has been done on its harmful effects on non-target organisms, especially aquatic organisms. In this study, 600 adult zebrafish were exposed to different concentration of GLA (0, 1.25, 2.5, 5, 10, and 20 mg/L) for 7 days, and the livers were dissected on the eighth day to examine the changes in liver structure, function, oxidative stress, inflammation, apoptosis, and Nrf2 pathway, and finally to clarify the mechanism of GLA induced liver injury in zebrafish. The levels of alanine aminotransferase, aspartate aminotransferase, reactive oxygen species, malondialdehyde, inflammatory factors (IL-6 and TNF-α), and caspase-3 gradually increased, while the levels of superoxide dismutase, catalase, glutathione, and glutathione peroxidase gradually decreased with the increase of GLA concentration. The Nrf2 pathway was activated at low concentrations (1.25-5 mg/L) and significantly inhibited at high concentrations (10 and 20 mg/L). These results suggested that GLA could cause oxidative stress, inflammation, and apoptosis in zebrafish liver. Therefore, GLA can cause liver injury in zebrafish, and at high concentrations, the inhibition of Nrf2 pathway is one of the important causes of liver injury.

Combined analysis of microRNA and mRNA profiles provides insights into the pathogenic resistant mechanisms of the lotus rhizome rot.

Lotus rhizome rot caused by Fusarium oxysporum is a common vascular fungal disease in plants that significantly impacts the yield. However, only a few studies have studied the mechanism of Nelumbo nucifera responding to lotus rhizome rot. Here, we investigated the pathogenic genes and miRNAs in lotus rhizome rot to uncover the pathogenic resistant mechanisms by transcriptome and small RNA sequencing of lotus roots after inoculation with Fusarium oxysporum. GO and KEGG functional enrichment analysis showed that differential miRNAs were mostly enriched in starch and sucrose metabolism, biosynthesis of secondary metabolites, glutathione metabolism, brassinosteroid biosynthesis and flavonoid biosynthesis pathways. Twenty-seven upregulated miRNAs, 19 downregulated miRNAs and their target genes were identified. Correlation analysis found that miRNAs negatively regulate target genes, which were also enriched in starch and sucrose metabolism and glutathione metabolism pathways. Their expression was measured by reverse transcription quantitative PCR (qRT-PCR), and the results were consistent with the transcriptome analysis, thus verifying the reliability of transcriptome data. We selected three miRNAs (miRNA858-y, miRNA171-z and a novel miRNA novel-m0005-5p) to test the relationship between miRNAs and their target genes. The activity of the GUS testing assay indicated that miRNA could decrease the GUS activity by inhibiting the expression of their target genes. Collectively, this study provides a comprehensive analysis of transcriptome and small RNA sequencing of lotus root after inoculation with Fusarium oxysporum, and we identified candidate miRNAs and their target genes for breeding strategies of Nelumbo nucifera.

Efficacy and Safety of Ferric Citrate on Hyperphosphatemia among Chinese Patients with Chronic Kidney Disease Undergoing Hemodialysis: A Phase III Multicenter Randomized Open-Label Active-Drug-Controlled Study.

INTRODUCTION: Hyperphosphatemia in chronic kidney disease (CKD) patients is positively associated with mortality. Ferric citrate is a potent phosphorus binder that lowers serum phosphorus level and improves iron metabolism. We compared its efficacy and safety with active drugs in Chinese CKD patients with hemodialysis. METHODS: Chinese patients undergoing hemodialysis were randomized into two treatment groups in a 1:1 ratio, receiving either ferric citrate or sevelamer carbonate, respectively, for 12 weeks. Serum phosphorus levels, calcium concentration, and iron metabolism parameters were evaluated every 2 weeks. Frequency and severity of adverse events were recorded. RESULTS: 217 (90.4%) patients completed the study with balanced demographic and baseline characteristics between two groups. Ferric citrate decreased the serum phosphorus level to 0.59 ± 0.54 mmol/L, comparable to 0.56 ± 0.62 mmol/L by sevelamer carbonate. There was no significant difference between two groups (p > 0.05) in the proportion of patients with serum phosphorus levels reaching the target range, the response rate to the study drug, and the changes of corrected serum calcium concentrations, and intact-PTH levels at the end of treatment. The change of iron metabolism indicators in the ferric citrate group was significantly higher than those in the sevelamer carbonate group. There are 47 (40.5%) patients in the ferric citrate group, and 26 (21.3%) patients in the sevelamer carbonate group experienced drug-related treatment emergent adverse events (TEAEs); most were mild and tolerable. Common drug-related TEAEs were gastrointestinal disorders, including diarrhea (12.9 vs. 2.5%), fecal discoloration (14.7 vs. 0%), and constipation (1.7 vs. 7.4%) in ferric citrate and sevelamer carbonate group. CONCLUSION: Ferric citrate capsules have good efficacy and safety in the control of hyperphosphatemia in adult patients with CKD undergoing hemodialysis. Efficacy is not inferior to sevelamer carbonate. The TEAEs were mostly mild and tolerated by the patients.

The willingness to continue using wearable devices among the elderly: SEM and FsQCA analysis.

BACKGROUND: With population aging and the scarcity of resources for elderly individuals, wearable devices pose opportunities and challenges for elderly care institutions. However, few studies have examined the effects of technical characteristics, personal characteristics, and health promotion on the willingness of elderly individuals to continue using wearable devices. OBJECTIVE: This study explored the effects of technical characteristics and personal characteristics on the willingness of elderly individuals to continue using wearable devices through health promotion, drawing on the technology acceptance model and the value attitude behaviour model. METHODS: We obtained 265 valid samples through questionnaire surveys and used structural equation modelling (SEM) and fuzzy set qualitative comparative analysis (FsQCA) to clarify the complex causal patterns of elderly people's willingness to continue using wearable devices. RESULTS: The SEM results showed that perceived usefulness, perceived reliability, self-perceived ageing, and health promotion affected willingness to continue using wearable devices. However, perceived ease of use had no effect. FsQCA showed that elderly individuals are highly willing to continue using wearable devices, yielding five solutions. Perceived ageing was essential in four of these solutions. The impact of perceived ease of use on continued use intention was dynamic and complex. CONCLUSIONS: This study used two methods to provide insight into the willingness of elderly individuals to continue using wearable devices. In addition, this study discussed associated implications, limitations, and future research directions.

Integrated morphological, metabolome, and transcriptome analyses revealed the mechanism of exogenous gibberellin promoting petiole elongation in Oenanthe javanica.

Oenanthe javanica (Blume) DC. is a popular vegetable with unique flavor and its leaf is the main product organ. Gibberellin (GA) is an important plant hormone that plays vital roles in regulating the growth of plants. In this study, the plants of water dropwort were treated with different concentrations of GA3. The plant height of water dropwort was significantly increased after GA3 treatment. Anatomical structure analysis indicated that the cell length of water dropwort was elongated under exogenous application of GA3. The metabolome analysis showed flavonoids were the most abundant metabolites and the biosynthesis of secondary metabolites were also regulated by GA3. The exogenous application of GA3 altered the gene expressions of plant hormone signal transduction (GID and DELLA) and metabolites biosynthesis pathways to regulate the growth of water dropwort. The GA contents were modulated by up-regulating the expression of GA metabolism gene GA2ox. The differentially expressed genes related to cell wall formation were significantly enriched. A total of 22 cellulose synthase involved in cellulose biosynthesis were identified from the genome of water dropwort. Our results indicated that GA treatment promoted the cell elongation by inducing the expression of cellulose synthase and cell wall formation in water dropwort. These results revealed the molecular mechanism of GA-mediated cell elongation, which will provide valuable reference for using GA to regulate the growth of water dropwort.

Metabolomics Analysis Reveals Metabolites and Metabolic Pathways Involved in the Growth and Quality of Water Dropwort [Oenanthe javanica (Blume) DC.] under Nutrient Solution Culture.

Water dropwort (Oenanthe javanica (Blume) DC.) is an important vegetable crop. Nutrient liquid culture has become an important cultivation method in the production of water dropwort. However, the effects of different nutrient solution cultivation methods on the growth and quality of water dropwort remains unclear. In this study, to screen the most suitable nutrient solution formula for the cultivation of water dropwort, the effects of different nutrient solution formulas (Hoagland, Cooper, Dutch greenhouse, Garden-style, Yamasaki and SCAU) on plant physiological and quality characteristics are investigated. The plant height, root length, water content (%), distribution rate of dry matter (%), chlorophyll, VC, flavonoid, total phenolic, DPPH and dietary fiber of water dropwort under different nutrient solutions were determined. According to the analytic hierarchy process (AHP) of the growth index and quality index of water dropwort under different nutrient solutions, the Yamazaki nutrient solution was considered to be the most suitable nutrient solution formula for water dropwort. To further confirm the differences of water dropwort under nutrient solution culture and soil culture, the broadly targeted metabolomics were performed. A total of 485 metabolites were detected in water dropwort under optimal nutrient solution and soil cultivation. Metabolomics analysis showed that flavonoids were the most abundant differential accumulated metabolites, and most flavonoids were up-regulated. A qRT-PCR assay indicated that the structural genes of the flavonoid biosynthesis pathway (PAL, C4H, CHS, CHI, F3H, DFR, UFGT) were significantly higher under the Yamasaki nutrient solution treatment. The current study provided a theoretical basis and technical guidance for the nutrient solution cultivation of water dropwort. Meanwhile, this study provides new insights into the study of flavonoids in water dropwort.

Robust fall detection in video surveillance based on weakly supervised learning.

Fall event detection has been a research hotspot in recent years in the fields of medicine and health. Currently, vision-based fall detection methods have been considered the most promising methods due to their advantages of a non-contact characteristic and easy deployment. However, the existing vision-based fall detection methods mainly use supervised learning in model training and require much time and energy for data annotations. To address these limitations, this work proposes a detection method that uses a weakly supervised learning-based dual-modal network. The proposed method adopts a deep multiple instance learning framework to learn the fall events using weak labels. As a result, the proposed method does not require time-consuming fine-grained annotations. The final detection result of each video is obtained by integrating the information obtained from two streams of the dual-modal network using the proposed dual-modal fusion strategy. Experimental results on two public benchmark datasets and a proposed dataset demonstrate the superiority of the proposed method over the current state-of-the-art methods.

Molecular identification of phenylalanine ammonia lyase-encoding genes EfPALs and EfPAL2-interacting transcription factors in Euryale ferox.

Flavonoids are one of the most important secondary metabolites in plants, and phenylalanine ammonia-lyase (PAL) is the first rate-limiting enzyme for their biosynthesis. However, detailed information on the regulation of PAL in plants is still little. In this study, PAL in E. ferox was identified and functionally analyzed, and its upstream regulatory network was investigated. Through genome-wide identification, we obtained 12 putative PAL genes from E. ferox. Phylogenetic tree and synteny analysis revealed that PAL in E. ferox was expanded and mostly preserved. Subsequently, enzyme activity assays demonstrated that EfPAL1 and EfPAL2 both catalyzed the production of cinnamic acid from phenylalanine only, with EfPAL2 exhibiting a superior enzyme activity. Overexpression of EfPAL1 and EfPAL2 in Arabidopsis thaliana, respectively, both enhanced the biosynthesis of flavonoids. Furthermore, two transcription factors, EfZAT11 and EfHY5, were identified by yeast one-hybrid library assays as binding to the promoter of EfPAL2, and further luciferase (LUC) activity analysis indicated that EfZAT11 promoted the expression of EfPAL2, while EfHY5 repressed the expression of EfPAL2. These results suggested that EfZAT11 and EfHY5 positively and negatively regulate flavonoid biosynthesis, respectively. Subcellular localization revealed that EfZAT11 and EfHY5 were localized in the nucleus. Our findings clarified the key EfPAL1 and EfPAL2 of flavonoid biosynthesis in E. ferox and established the upstream regulatory network of EfPAL2, which would provide novel information for the study of flavonoid biosynthesis mechanism.

Effects of Slow-Release Fertilizer on Lotus Rhizome Yield and Starch Quality under Different Fertilization Periods.

Slow-release fertilizer is an environmentally friendly fertilizer that is widely used in crop cultivation instead of traditional nitrogen fertilizer. However, the optimal application time of slow-release fertilizer and its effect on starch accumulation and rhizome quality of lotus remains unclear. In this study, two slow-release fertilizer applications (sulfur-coated compound fertilizer, SCU, and resin-coated urea, RCU) were fertilized under three fertilization periods (the erect leaf stage, SCU1 and RCU1; the erect leaf completely covering the water stage, SCU2 and RCU2; and the swelling stage of lotus rhizomes, SCU3 and RCU3) to study the effects of different application periods. Compared with CK (0 kg∙ha-1 nitrogen fertilizer), leaf relative chlorophyll content (SPAD) and net photosynthetic rate (Pn) remained at higher levels under SCU1 and RCU1. Further studies showed that SCU1 and RCU1 increased yield, amylose content, amylopectin and total starch, and the number of starch particles in lotus, and also significantly reduced peak viscosity, final viscosity and setback viscosity of lotus rhizome starch. To account for these changes, we measured the activity of key enzymes in starch synthesis and the relative expression levels of related genes. Through analysis, we found that these parameters increased significantly under SCU and RCU treatment, especially under SCU1 and RCU1 treatment. The results of this study showed that the one-time application at the erect leaf stage (SCU1 and RCU1) could improve the physicochemical properties of starch by regulating the key enzymes and related genes of starch synthesis, thus improving the nutritional quality of lotus rhizome. These results provide a technical choice for the one-time application of slow-release fertilizer in lotus rhizome production and cultivation.

Network pharmacology and in vivo studies reveal the pharmacological effects and molecular mechanisms of Celastrol against acute hepatic injury induced by LPS.

Sepsis is currently the main factor of death in the ICU, and the liver, as an important organ of immunity and stable metabolism, can be acutely damaged during sepsis, and the mortality rate of patients with sepsis complicated by acute liver injury is greatly increased. Celastrol (CEL) is derived from the root bark of Tripterygium wilfordii Hook.f.. As a traditional Chinese medicine, CEL has anti-inflammatory, anti-cancer, anti-oxidant, and other biological activities. Obtain CEL and AHI intersection targets via database and construct protein-protein interaction (PPI) network by STRING. GO functional enrichment and KEGG pathway analyses were performed by R studio. Targets were finally selected to perform molecular docking simulations with CEL. In vivo experiments based on the model of AHI were established by intraperitoneal injection of Lipopolysaccharide (LPS) 4 h, and pre-treated with CEL (0.5 mg/kg, 1 mg/kg, 1.5 mg/kg). The results are as follows: 273 genes with the intersection of CEL and AHI were obtained, and GO and KEGG enrichment analysis were used to design the mechanism of inflammation, apoptosis, and oxidative stress-related injury. By constructing the PPI network selected top 10 targets are: STAT3, RELA, MAPK1, MAPK3, TP53, AKT1, HSP90AA1, JUN, TNF, MAPK14, predicted CEL protection AHI design related pathways of MAPK and PI3K/AKT-related signal pathways. In vivo experiments, CEL inhibited the activation of MAPK and PI3K/AKT related pathways, reduced inflammatory response, apoptosis, and oxidative stress, and significantly improved LPS-induced AHI. In summary, this study predicted the mechanisms involved in the protective effect of CEL on AHI through network pharmacology. In vivo, CEL inhibited MAPK and PI3K/AKT-related signaling pathways, and reduced inflammatory response, apoptosis, and oxidative stress to protect LPS-induced AHI.

Identification of YABBY Transcription Factors and Their Function in ABA and Salinity Response in Nelumbo nucifera.

The plant-specific transcription factor family YABBY plays important roles in plant responses to biotic and abiotic stresses. Although the function of YABBY has been identified in many species, systematic analysis in lotus (Nelumbo nucifera) is still relatively lacking. The present study aimed to characterize all of the YABBY genes in lotus and obtain better insights into NnYABBYs in response to salt stress by depending on ABA signaling. Here, we identified nine YABBY genes by searching the whole lotus genome based on the conserved YABBY domain. Further analysis showed that these members were distributed on six different chromosomes and named from YABBY1 to YABBY9, which were divided into five subgroups, including YAB1, YAB2, YAB5, INO, and CRC. The analysis of cis-elements in promotors revealed that NnYABBYs could be involved in plant hormone signaling and plant responses to abiotic stresses. Quantitative real-time PCR (qRT-PCR) showed that NnYABBYs could be up-regulated or down-regulated by ABA, fluridone, and salt treatment. Subcellular localization indicated that NnYABBY4, NnYABBY5, and NnYABBY6 were mainly localized in the cell membrane and cytoplasm. In addition, the intrinsic trans-activity of NnYABBY was tested by a Y2H assay, which revealed that NnYABBY4, NnYABBY5, and NnYABBY6 are deprived of such a property. This study provided a theoretical basis and reference for the functional research of YABBY for the molecular breeding of lotus.

GmDof41 regulated by the DREB1-type protein improves drought and salt tolerance by regulating the DREB2-type protein in soybean.

Despite their essential and multiple roles in biological processes, the molecular mechanism of Dof transcription factors (TFs) for responding to abiotic stresses is rarely reported in plants. We identified a soybean Dof gene GmDof41 which was involved in the responses to drought, salt, and exogenous ABA stresses. Overexpression of GmDof41 in soybean transgenic hairy roots attenuated H2O2 accumulation and regulated proline homeostasis, resulting in the drought and salt tolerance. Yeast one-hybrid and electrophoretic mobility shift assay (EMSA) illustrated that GmDof41 was regulated by the DREB1-type protein GmDREB1B;1 that could improve drought and salt tolerance in plants. Further studies illustrated GmDof41 can directly bind to the promoter of GmDREB2A which encodes a DREB2-type protein and affects abiotic stress tolerance in plants. Collectively, our results suggested that GmDof41 positively regulated drought and salt tolerance by correlating with GmDREB1B;1 and GmDREB2A. This study provides an important basis for further exploring the abiotic stress-tolerance mechanism of Dof TFs in soybean.

Toward Efficient Palmprint Feature Extraction by Learning a Single-Layer Convolution Network.

In this article, we propose a collaborative palmprint-specific binary feature learning method and a compact network consisting of a single convolution layer for efficient palmprint feature extraction. Unlike most existing palmprint feature learning methods, such as deep-learning, which usually ignore the inherent characteristics of palmprints and learn features from raw pixels of a massive number of labeled samples, palmprint-specific information, such as the direction and edge of patterns, is characterized by forming two kinds of ordinal measure vectors (OMVs). Then, collaborative binary feature codes are jointly learned by projecting double OMVs into complementary feature spaces in an unsupervised manner. Furthermore, the elements of feature projection functions are integrated into OMV extraction filters to obtain a collection of cascaded convolution templates that form a single-layer convolution network (SLCN) to efficiently obtain the binary feature codes of a new palmprint image within a single-stage convolution operation. Particularly, our proposed method can easily be extended to a general version that can efficiently perform feature extraction with more than two types of OMVs. Experimental results on five benchmark databases show that our proposed method achieves very promising feature extraction efficiency for palmprint recognition.