A Huntingtin Knockin Pig Model Recapitulates Features of Selective Neurodegeneration in Huntington's Disease.

Huntington's disease (HD) is characterized by preferential loss of the medium spiny neurons in the striatum. Using CRISPR/Cas9 and somatic nuclear transfer technology, we established a knockin (KI) pig model of HD that endogenously expresses full-length mutant huntingtin (HTT). By breeding this HD pig model, we have successfully obtained F1 and F2 generation KI pigs. Characterization of founder and F1 KI pigs shows consistent movement, behavioral abnormalities, and early death, which are germline transmittable. More importantly, brains of HD KI pig display striking and selective degeneration of striatal medium spiny neurons. Thus, using a large animal model of HD, we demonstrate for the first time that overt and selective neurodegeneration seen in HD patients can be recapitulated by endogenously expressed mutant proteins in large mammals, a finding that also underscores the importance of using large mammals to investigate the pathogenesis of neurodegenerative diseases and their therapeutics.

scGMAAE: Gaussian mixture adversarial autoencoders for diversification analysis of scRNA-seq data.

The progress of single-cell RNA sequencing (scRNA-seq) has led to a large number of scRNA-seq data, which are widely used in biomedical research. The noise in the raw data and tens of thousands of genes pose a challenge to capture the real structure and effective information of scRNA-seq data. Most of the existing single-cell analysis methods assume that the low-dimensional embedding of the raw data belongs to a Gaussian distribution or a low-dimensional nonlinear space without any prior information, which limits the flexibility and controllability of the model to a great extent. In addition, many existing methods need high computational cost, which makes them difficult to be used to deal with large-scale datasets. Here, we design and develop a depth generation model named Gaussian mixture adversarial autoencoders (scGMAAE), assuming that the low-dimensional embedding of different types of cells follows different Gaussian distributions, integrating Bayesian variational inference and adversarial training, as to give the interpretable latent representation of complex data and discover the statistical distribution of different types of cells. The scGMAAE is provided with good controllability, interpretability and scalability. Therefore, it can process large-scale datasets in a short time and give competitive results. scGMAAE outperforms existing methods in several ways, including dimensionality reduction visualization, cell clustering, differential expression analysis and batch effect removal. Importantly, compared with most deep learning methods, scGMAAE requires less iterations to generate the best results.

SERS Performance Factor: A Convenient Parameter for the Enhancement Evaluation of SERS Substrates.

Surface-enhanced Raman spectroscopy (SERS), with molecular fingerprint information and single-molecule sensitivity, has been widely used for qualitative and quantitative analysis in various fields. Plenty of nanostructured plasmonic materials have been fabricated to achieve high SERS activity. Currently, great difficulty lies in evaluating the SERS performance among substrates, making it difficult to standardize. Addressing this problem, this work proposed the SERS performance factor (SPF=ΔISERSΔCSERS/ΔIRamanΔCRaman) as a practically operational parameter to evaluate the sensitivity of SERS substrates. Experimentally, SPF can be obtained by taking the ratio of the slopes (i.e., the sensitivity) for concentration-dependent SERS and normal Raman measurements in the linear range of the intensity response under identical experimental conditions. Theoretically, SPF quantitatively describes the overall contribution to the SERS performance, (i.e., the electromagnetic (EM) enhancement of the SERS substrate and the interfacial interaction between the probe and substrate). The use of SPF as the criterion for evaluating the SERS performance was validated on Au nanoparticles in colloidal and solid states, where the tendency of SPF is consistent with that of the sensitivity of the probe molecules. Derived from the typically used surface enhancement factor EF in which accurate parameters are hardly achievable and different from concentration-dependent analytical enhancement factor AEF, SPF distinguishes itself with a simpler calculation and thereby offers a convenient and reliable protocol for the evaluation of the performance of different SERS substrates, which is very important to the practical application of SERS.

Neoadjuvant Chemotherapy or Adjuvant Chemotherapy for Esophageal Squamous Cell Carcinoma.

BACKGROUND: Chemotherapy and chemoradiation have become essential adjuncts to improve the survival of patients with resectable esophageal squamous cell carcinoma (ESCC) in the perioperative period. Although preoperative treatment plus surgery is commonly used, controversy remains regarding the optimal treatment strategy for patients with locally advanced ESCC. METHODS: A retrospective review of clinical stage II and III ESCC patients who underwent esophagectomy at Henan Cancer Hospital between October 2014 and October 2017 was performed. The patients were divided into a neoadjuvant chemotherapy (NAC) group and an adjuvant chemotherapy (AC) group. Propensity score matching (PSM) was used to exclude confounders. Survival was estimated using Kaplan‒Meier analysis and compared by the log-rank test. The Cox proportional hazards regression model was used for both the univariate and multivariate analyses. RESULTS: A total of 684 patients were enrolled, including 365 (53.4%) patients in the NAC group. After PSM, 294 pairs of patients were left. NAC prolonged the OS (not reached versus 57.3 months, P = 0.002) and DFS (57.2 vs. 36.4 months, P = 0.010) and decreased the total rate of recurrence (50.1% vs. 59.2%, P = 0.025) and local recurrence (27.9% vs. 36.7%, P = 0.022) compared with AC. The multivariable analyses showed that NAC plus surgery modality was an independent predictor for improved OS (HR: 0.582, 95% CI: 0.467-0.786, P = 0.001). CONCLUSION: NAC plus surgery prolonged OS and DFS, and significantly decreased the total rate of recurrence compared with surgery plus AC in patients with clinical stage II and III ESCC.

Preclinical characterization of [18F]D2-LW223: an improved metabolically stable PET tracer for imaging the translocator protein 18 kDa (TSPO) in neuroinflammatory rodent models and non-human primates.

Positron emission tomography (PET) targeting translocator protein 18 kDa (TSPO) can be used for the noninvasive detection of neuroinflammation. Improved in vivo stability of a TSPO tracer is beneficial for minimizing the potential confounding effects of radiometabolites. Deuteration represents an important strategy for improving the pharmacokinetics and stability of existing drug molecules in the plasma. This study developed a novel tracer via the deuteration of [18F]LW223 and evaluated its in vivo stability and specific binding in neuroinflammatory rodent models and nonhuman primate (NHP) brains. Compared with LW223, D2-LW223 exhibited improved binding affinity to TSPO. Compared with [18F]LW223, [18F]D2-LW223 has superior physicochemical properties and favorable brain kinetics, with enhanced metabolic stability and reduced defluorination. Preclinical investigations in rodent models of LPS-induced neuroinflammation and cerebral ischemia revealed specific [18F]D2-LW223 binding to TSPO in regions affected by neuroinflammation. Two-tissue compartment model analyses provided excellent model fits and allowed the quantitative mapping of TSPO across the NHP brain. These results indicate that [18F]D2-LW223 holds significant promise for the precise quantification of TSPO expression in neuroinflammatory pathologies of the brain.

The prognostic impact of tumor length on pathological stage IA-IC esophageal adenocarcinoma.

This study was completed to evaluate the relationship between tumor length and the prognosis of patients with pathological stage IA-IC esophageal adenocarcinoma (EAC). Patients were identified from the Surveillance, Epidemiology, and End Results Program database (United States, 2006-2015). X-tile software and ROC analysis were mainly used to explore the best threshold of tumor length for dividing patients into different groups, and then propensity score matching (PSM) was used to balance other variables between groups. The primary outcome assessed was overall survival (OS). A total of 762 patients were identified, and 500 patients were left after PSM. Twenty millimeters were used as the threshold of tumor length. Patients with longer tumor lengths showed worse OS (median: 93 vs. 128 months; P = 0.006). Multivariable Cox regression analysis showed that longer tumor length was an independent risk factor (hazard ratio 1.512, 95% confidence interval, 1.158-1.974, P = 0.002). Tumor length has an impact on patients with pathological stage IA-IC EAC who undergo surgery alone. The prognostic value of the pathological stage group may be improved after combining it with tumor length and age.

Multi-omics and gut microbiome: Unveiling the pathogenic mechanisms of early-life pesticide exposure.

The extensive application of pesticides in agricultural production has raised significant concerns about its impact on human health. Different pesticides, including fungicides, insecticides, and herbicides, cause environmental pollution and health problems for non-target organisms. Infants and young children are so vulnerable to the harmful effects of pesticide exposure that early-life exposure to pesticides deserves focused attention. Recent research lays emphasis on understanding the mechanism between negative health impacts and early-life exposure to various pesticides. Studies have explored the impacts of exposure to these pesticides on model organisms (zebrafish, rats, and mice), as well as the mechanism of negative health effects, based on advanced methodologies like gut microbiota and multi-omics. These methodologies help comprehend the pathogenic mechanisms associated with early-life pesticide exposure. In addition to presenting health problems stemming from early-life exposure to pesticides and their pathogenic mechanisms, this review proposes expectations for future research. These proposals include focusing on identifying biomarkers that indicate early-life pesticide exposure, investigating transgenerational effects, and seeking effective treatments for diseases arising from such exposure. This review emphasizes how to understand the pathogenic mechanisms of early-life pesticide exposure through gut microbiota and multi-omics, as well as the adverse health effects of such exposure.

Dual-Band Monopole MIMO Antenna Array for UAV Communication Systems.

This study proposes a compact, low-profile, four-port dual-band monopole multiple-input-multiple-output (MIMO) antenna array for unmanned aerial vehicle (UAV) communication systems. Each monopole antenna of the array features a modified T-shaped radiator configuration and is printed on a Rogers RT5880 substrate with compact dimensions of 134.96 mm × 134.96 mm × 0.8 mm. A four-element square MIMO configuration with sequential 0°, 90°, 180°, and 270° rotations was integrated smoothly into the UAV body. A prototype of the MIMO array was fabricated and experimentally evaluated, with measured results showing a close correlation to simulated results. The proposed dual-band monopole antenna demonstrated one of the widest impedance bandwidths of 46.15% at 2.4 GHz (2.04 to 3.25 GHz) IEEE 802.11b and 31.85% at 5.8 GHz (5.37 to 7.38 GHz) IEEE 802.11a on a thin 0.0064 λo substrate while achieving high transmission efficiency. The isolation of the proposed four-port MIMO design was measured at 23 dB at 2.4 GHz and 19 dB at 5.8 GHz. The MIMO array's total efficiency of each monopole antenna was measured at 96% at 2.4 GHz and 89% at 5.8 GHz. The design has measured diversity parameters such as an ECC below 0.01 and a DG of approximately 10. Based on these results, the proposed design suits the UAV communication system.

Metamaterial Inspired Varactor-Tuned Antenna with Frequency Reconfigurability and Pattern Diversity.

A metamaterial-inspired varactor-tuned antenna with frequency reconfigurability and pattern diversity is designed. Two different versions of a reconfigurable structure are integrated into a single antenna to excite two different orthogonal patterns, which realizes pattern diversity for MIMO applications. The outer annular Composite Right-/Left-Handed Transmission Line (CRLH-TL) works at the 1 mode and provides a broadside pattern, and the inner circular radiator loaded with split ring resonators (SRR) operates at the 0 mode and radiates an omnidirectional pattern, which realizes pattern diversity. By using surface-mounted varactors, the operating frequencies for the two radiation patterns can be tuned over a wide frequency range, from 1.7 GHz to 2.2 GHz, covering the 1.71-2.17 GHz LTE band, and a low mutual coupling between the two radiators is achieved. The antenna has also been prototyped. The measured results are in good agreement with the simulation results, verifying the proposed concept. The dual-mode MIMO system equipped with the proposed antenna elements is discussed within the context of a 3-D channel model, and it shows a superior array compactness and spectral efficiency (SE) performance compared to scenarios with single-mode elements.

Effect of Serotonin (5-Hydroxytryptamine) on Follicular Development in Porcine.

5-Hydroxytryptamine (5-HT) is an inhibitory neurotransmitter widely distributed in mammalian tissues, exerting its effects through binding to various receptors. It plays a crucial role in the proliferation of granulosa cells (GCs) and the development of follicles in female animals, however, its effect on porcine follicle development is not clear. The aim of this study is to investigate the expression of 5-HT and its receptors in various parts of the pig ovary, as well as the effect of 5-HT on porcine follicular development by using ELISA, quantitative real-time PCR (qPCR) and EdU assays. Firstly, we examined the levels of 5-HT and its receptors in porcine ovaries, follicles, and GCs. The findings revealed that the expression of different 5-HT receptors varied among follicles of different sizes. To investigate the relationship between 5-HT and its receptors, we exposed the GCs to 5-HT and found a decrease in 5-HT receptor expression compared to the control group. Subsequently, the treatment of GCs with 0.5 µM, 5 µM, and 50 µM 5-HT showed an increase in the expression of cell cycle-related genes, and EdU results indicated cell proliferation after the 0.5 µM 5-HT treatment. Additionally, the expression of genes involved in E2 synthesis was examined after the treatment of granulosa cells with 0.5 µM 5-HT. The results showed that CYP19A1 and HSP17ß1 expression was decreased. These results suggest that 5-HT might affect the development of porcine follicle by promoting the proliferation of GCs and inhibiting the synthesis of estrogen. This provides a new finding for exploring the effect of 5-HT on follicular development, and lays a foundation for further research on the mechanism of 5-HT in follicles.

Aberrant splicing of mutant huntingtin in Huntington's disease knock-in pigs.

Huntington's disease (HD) is an autosomal-dominant inherited neurodegenerative disease caused by a CAG repeat expansion in exon1 of the huntingtin gene (HTT). This expansion leads to the production of N-terminal mutant huntingtin protein (mHtt) that contains an expanded polyglutamine tract, which is toxic to neurons and causes neurodegeneration. While the production of N-terminal mHtt can be mediated by proteolytic cleavage of full-length mHtt, abnormal splicing of exon1-intron1 of mHtt has also been identified in the brains of HD mice and patients. However, the proportion of aberrantly spliced exon1 mHTT in relation to normal mHTT exon remains to be defined. In this study, HTT exon1 production was examined in the HD knock-in (KI) pig model, which more closely recapitulates neuropathology seen in HD patient brains than HD mouse models. The study revealed that aberrant spliced HTT exon1 is also present in the brains of HD pigs, but it is expressed at a much lower level than the normally spliced HTT exon products. These findings suggest that careful consideration is needed when assessing the contribution of aberrantly spliced mHTT exon1 to HD pathogenesis, and further rigorous investigation is required.

Lack of association of somatic CAG repeat expansion with striatal neurodegeneration in HD knock-in animal models.

Our previous work has established a huntingtin knock-in (KI) pig model that displays striatal neuronal loss, allowing us to examine if somatic CAG expansion in striatum accounts for the preferential neurodegeneration in Huntington disease (HD). We found that HD KI pigs do not display somatic CAG expansion in striatum as HD KI mice and that the majority of polyQ repeats in exon 1 HTT in the striatum of HD KI mice are fairly stable. We also found that striatal MSH2 and MLH3, which are involved in DNA repair, are more abundant in mouse brains than pig brains. Consistently inhibiting MSH2 and MLH3 reduced the somatic CAG expansion in HD KI mouse striatum with no influence on neuropathology. Our findings suggest that somatic CAG expansion is species-dependent, occurs in a small fraction of the HD gene in mice, and does not critically contribute to HD neuropathology.

TBN improves motor function and prolongs survival in a TDP-43M337V mouse model of ALS.

Amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) are serious neurodegenerative diseases. Although their pathogenesis is unclear, the abnormal accumulation of TAR DNA-binding protein of 43 kDa (TDP-43) is a pathological feature that exists in almost all patients. Thus far, there is no drug that can cure ALS/FTLD. Tetramethylpyrazine nitrone (TBN) is a derivative of tetramethylapyrazine, derived from the traditional Chinese medicine Ligusticum chuanxiong, which has been widely proven to have therapeutic effects on models of various neurodegenerative diseases. TBN is currently under clinical investigation for several indications including a Phase II trial of ALS. Here, we explored the therapeutic effect of TBN in an ALS/FTLD mouse model. We injected the TDP-43 M337V virus into the striatum of mice unilaterally and bilaterally, and then administered 30 mg/kg TBN intragastrically to observe changes in behavior and survival rate of mice. The results showed that in mice with unilateral injection of TDP-43M337V into the striatum, TBN improved motor deficits and cognitive impairment in the early stages of disease progression. In mice with bilateral injection of TDP-43M337V into the striatum, TBN not only improved motor function but also prolonged survival rate. Moreover, we show that its therapeutic effect may be through activation of the Akt/mTOR/GSK-3ß and AMPK/PGC-1α/Nrf2 signaling pathways. In summary, TBN is a promising agent for the treatment of ALS/FTLD.

scCNC: a method based on capsule network for clustering scRNA-seq data.

MOTIVATION: A large number of studies have shown that clustering is a crucial step in scRNA-seq analysis. Most existing methods are based on unsupervised learning without the prior exploitation of any domain knowledge, which does not utilize available gold-standard labels. When confronted by the high dimensionality and general dropout events of scRNA-seq data, purely unsupervised clustering methods may not produce biologically interpretable clusters, which complicate cell type assignment. RESULTS: In this article, we propose a semi-supervised clustering method based on a capsule network named scCNC that integrates domain knowledge into the clustering step. Significantly, we also propose a Semi-supervised Greedy Iterative Training method used to train the whole network. Experiments on some real scRNA-seq datasets show that scCNC can significantly improve clustering performance and facilitate downstream analyses. AVAILABILITY AND IMPLEMENTATION: The source code of scCNC is freely available at https://github.com/WHY-17/scCNC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Patterns and Influence of Lymph Nodal Metastases After Neoadjuvant Chemotherapy and Surgery for Thoracic Esophageal Squamous Cell Carcinoma.

PURPOSE: The purpose of this retrospective study was to define the pattern of lymph nodal metastases in patients with esophageal squamous cell carcinoma (ESCC) after neoadjuvant chemotherapy (NCT) followed by esophagectomy and to evaluate its influence on prognosis. METHODS: A total of 398 patients with clinical stage T3N0 or T1-3N+ ESCC who underwent NCT and radical esophagectomy with two-field lymphadenectomy were included. The distribution and frequency of metastases were counted separately for each lymph node station. The ypN stage, number of positive lymph node stations and lymph node stations with a metastasis rate greater than 5% were analyzed by using univariate Cox regression, followed by separate multivariable Cox regression analyses after adjusting for various clinical factors. RESULTS: Lymph node metastases were most frequently observed in the right upper paratracheal (16.8%) and left gastric artery (13.1%) stations. Multivariable models controlling for clinical factors showed that ypN stage remained a significant independent predictor of survival (N1 vs. N0: hazard ratio [HR], 2.30, 95% confidence interval [CI] 1.38-3.83, P < 0.001; N2 vs. N0: HR, 3.76, 95% CI 2.21-6.38, P < 0.001; N3 vs. N0: HR, 7.14, 95% CI 3.78-13.48, P < 0.001). The model from the multivariable analysis with the highest c-index score, indicating superior discriminatory preference, was ypN stage (c-index, 0.72). CONCLUSIONS: The pattern and influence of lymph node metastases after NCT will provide guidance on the extent of lymphadenectomy. Common positive lymph node stations for thoracic ESCC after NCT include the paratracheal, subcarinal, paraesophageal, paracardial, and left gastric artery stations.

Promoter prediction in nannochloropsis based on densely connected convolutional neural networks.

Promoter is a key DNA element located near the transcription start site, which regulates gene transcription by binding RNA polymerase. Thus, the identification of promoters is an important research field in synthetic biology. Nannochloropsis is an important unicellular industrial oleaginous microalgae, and at present, some studies have identified some promoters with specific functions by biological methods in Nannochloropsis, whereas few studies used computational methods. Here, we propose a method called DNPPro (DenseNet-Predict-Promoter) based on densely connected convolutional neural networks to predict the promoter of Nannochloropsis. First, we collected promoter sequences from six Nannochloropsis strains and removed 80% similarity using CD-HIT for each strain to yield a reliable set of positive datasets. Then, in order to construct a robust classifier, within-group scrambling method was used to generate negative dataset which overcomes the limitation of randomly selecting a non-promoter region from the same genome as a negative sample. Finally, we constructed a densely connected convolutional neural network, with the sequence one-hot encoding as the input. Compared with commonly used sequence processing methods, DNPPro can extract long sequence features to a greater extent. The cross-strain experiment on independent dataset verifies the generalization of our method. At the same time, T-SNE visualization analysis shows that our method can effectively distinguish promoters from non-promoters.

A multicenter randomized, controlled clinical trial of adjuvant sintilimab for esophageal squamous cell carcinoma.

No adjuvant treatment has been established for patients who remain at high risk of recurrence and incidental pathologic lymph node metastasis for esophageal squamous cell carcinoma (ESCC). In this open-label, multicenter, phase III, randomized controlled trial, ESCC patients who did not achieve pathologic complete response after neoadjuvant chemotherapy plus surgery and clinical T1-2 N0 patients with incidental pathologic lymph node metastasis following initial surgery were randomized at a 2:1 ratio to receive either a sintilimab regimen or observational management (NCT05495152). The primary end point was disease-free survival for all randomized patients. The results of this randomized controlled trial addressed controversy regarding the survival benefits of adjuvant sintilimab treatment for patients with resected locally advanced ESCC. Clinical Trial Registration: NCT05495152 (ClinicalTrials.gov).

Differential expression and roles of Huntingtin and Huntingtin-associated protein 1 in the mouse and primate brains.

Huntingtin-associated protein 1 (HAP1) is the first identified protein whose function is affected by its abnormal interaction with mutant huntingtin (mHTT), which causes Huntington disease. However, the expression patterns of Hap1 and Htt in the rodent brain are not correlated. Here we found that the primate HAP1, unlike the rodent Hap1, is correlatively expressed with HTT in the primate brains. CRISPR/Cas9 targeting revealed that HAP1 deficiency in the developing human neurons did not affect neuronal differentiation and gene expression as seen in the mouse neurons. However, deletion of HAP1 exacerbated neurotoxicity of mutant HTT in the organotypic brain slices of adult monkeys. These findings demonstrate differential HAP1 expression and function in the mouse and primate brains, and suggest that interaction of HAP1 with mutant HTT may be involved in mutant HTT-mediated neurotoxicity in adult primate neurons.

Survival impact of the number of lymph nodes dissection in patients receiving neoadjuvant chemotherapy for esophageal squamous cell carcinoma.

This study aimed to investigate the survival impact of the number of lymph nodes dissection (LND) in patients receiving neoadjuvant chemotherapy (NCT) for esophageal squamous cell carcinoma (ESCC). We retrospectively analyzed the clinical pathological data and survival of 407 ESCC patients who underwent esophagectomy after NCT between January 2015 and December 2016. The relationship between the number of LNDs and 5-year overall survival (OS) or disease-free survival (DFS) was plotted by using restricted cubic spline analysis. A Cox proportional hazards regression model was used to identify prognostic factors of OS and DFS. We observed an obvious non-linear relationship between LND and the hazard ratios (HRs) for OS (P = 0.0015) and DFS (P < 0.001) of all the patients. In the multivariate analysis of OS and DFS, the number of LNDs (greater than 28 and less than 46) had a significant protective effect on survival (OS: HR: 0.61, 95% CI: 0.42-0.88, P = 0.007; DFS: HR: 0.50, 95% CI: 0.36-0.70, P < 0.001). For patients with nodal metastases, it was also an independent prognostic factor for OS (HR, 0.56, 95% CI, 0.35-0.90, P = 0.017) and DFS (HR, 0.42, 95% CI, 0.28-0.65, P < 0.001). Some degree of lymphadenectomy after NCT was beneficial in improving 5-year OS and DFS for ESCC patients with nodal metastases. For patients with nodal negativity, more extended lymphadenectomy did not improve patient survival.

Dual-Polarization Ambient Backscatter Communications and Signal Detection.

Ambient backscatter communication (AmBC), an emerging mechanism for batteryless communications that can utilize ambient radio-frequency signals to modulate information and thus reduce power consumption, has attracted considerable attention and has been considered as a critical technology in green "Internet of Things" sensor networks due to its ultra-low power consumption. This paper presents the first a complete dual-polarization AmBC (DPAm) system model, which can extend AmBC into polarization diversity and improve the data-transmission rate of backscatter symbols. We proposed two scenarios: direct dual-polarization-based DPAm node structures and polarization-conversion-based DPAm node structures. In addition, we consider a parallel backscatter mode with differential coding and develop corresponding detectors, which also give the analytical detection thresholds. Moreover, we consider a simultaneous backscatter mode with Manchester coding in order to avoid complex-parameter estimation. To address the power imbalance problem of the DPAm system that arises because the polarization deflection angle would cause the power level to change with different polarization patterns, we also develop a power-average detector and a clustering detector. Simulation results show the throughput performance on each DPAm node structure with each detector, demonstrating the feasibility and efficiency of the proposed DPAm nodes and detectors. Compared with single-polarization AmBC (SPAm), the proposed DPAm node can achieve higher throughput in most cases. Finally, the clustering detector is shown to be more robust to short training sequences and complex environments.