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Abstract Pathological complete response (pCR) serves as a critical measure of the success of neoadjuvant chemotherapy (NAC) in breast cancer, directly influencing subsequent therapeutic decisions. With the continuous advancement of artificial intelligence, methods for early and accurate prediction of pCR are being extensively explored. In this study, we propose a cross-modal multi-pathway automated prediction model that integrates temporal and spatial information. This model fuses digital pathology images from biopsy specimens and multi-temporal ultrasound (US) images to predict pCR status early in NAC. The model demonstrates exceptional predictive efficacy. Our findings lay the foundation for developing personalized treatment paradigms based on individual responses. This approach has the potential to become a critical auxiliary tool for the early prediction of NAC response in breast cancer patients.

In a kind of precision industrial equipment, small diameter abreast optical fibers are used for high-speed communication among functional nodes. The arrangement order at both terminals of the abreast optical fibers need to comply with communication protocols. In this paper, we propose an automatic terminal sequence consistency verification method based on computer vision. The Hue Saturation Value (HSV) color space is used for improving the image feature extraction capability. An abreast optical fiber sequence dictionary which converts the protocol logic into an input-output mapping table is provided to follow protocol confidentiality and improve inspecting speed. A light control baffle position adaptive algorithm is designed for improving the accuracy of optical fiber incident light control. The experimental results show that the method can achieve the conductivity inspection of 1 optical fiber every 50 seconds, and the inspection accuracy is over 96.5%, which generally improves the inspection efficiency by 45% compared with manual inspection.

Background: A task assigned to space exploration satellites involves detecting the physical environment within a certain space. However, space detection data are complex and abstract. These data are not conducive for researchers' visual perceptions of the evolution and interaction of events in the space environment. Methods: A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time, and the corresponding relationships between data location features and other attribute features were established. A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data. The visualization process is optimized for rendering by merging materials, reducing the number of patches, and performing other operations. Results: The results of sampling, feature extraction, and uniform visualization of the detection data of complex types, long duration spans, and uneven spatial distributions were obtained. The real-time visualization of large-scale spatial structures using augmented reality devices, particularly low-performance devices, was also investigated. Conclusions: The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space, express the structure and changes in the spatial environment using augmented reality, and assist in intuitively discovering spatial environmental events and evolutionary rules.

The Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe. It pioneers the use of X-ray imaging technology to perform large-scale imaging of the Earth’s magnetosheath and polar cusp regions. It uses a high-precision ultraviolet imager to image the overall configuration of the aurora and monitor changes in the source of solar wind in real time, using in situ detection instruments to improve human understanding of the relationship between solar activity and changes in the Earth’s magnetic field. The SMILE satellite is scheduled to launch in 2025. The European Incoherent Scatter Sciences Association (EISCAT)-3D radar is a new generation of European incoherent scatter radar constructed by EISCAT and is the most advanced ground-based ionospheric experimental device in the high-latitude polar region. It has multibeam and multidirectional quasi-real-time three-dimensional (3D) imaging capabilities, continuous monitoring and operation capabilities, and multiple-baseline interferometry capabilities. Joint detection by the SMILE satellite and the EISCAT-3D radar is of great significance for revealing the coupling process of the solar wind–magnetosphere–ionosphere. Therefore, we performed an analysis of the joint detection capability of the SMILE satellite and EISCAT-3D, analyzed the period during which the two can perform joint detection, and defined the key scientific problems that can be solved by joint detection. In addition, we developed Web-based software to search for and visualize the joint detection period of the SMILE satellite and EISCAT-3D radar, which lays the foundation for subsequent joint detection experiments and scientific research.

Astronomical imaging technologies are basic tools for the exploration of the universe, providing basic data for the research of astronomy and space physics. The Soft X-ray Imager (SXI) carried by the Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) aims to capture two-dimensional (2-D) images of the Earth’s magnetosheath by using soft X-ray imaging. However, the observed 2-D images are affected by many noise factors, destroying the contained information, which is not conducive to the subsequent reconstruction of the three-dimensional (3-D) structure of the magnetopause. The analysis of SXI-simulated observation images shows that such damage cannot be evaluated with traditional restoration models. This makes it difficult to establish the mapping relationship between SXI-simulated observation images and target images by using mathematical models. We propose an image restoration algorithm for SXI-simulated observation images that can recover large-scale structure information on the magnetosphere. The idea is to train a patch estimator by selecting noise–clean patch pairs with the same distribution through the Classification–Expectation Maximization algorithm to achieve the restoration estimation of the SXI-simulated observation image, whose mapping relationship with the target image is established by the patch estimator. The Classification–Expectation Maximization algorithm is used to select multiple patch clusters with the same distribution and then train different patch estimators so as to improve the accuracy of the estimator. Experimental results showed that our image restoration algorithm is superior to other classical image restoration algorithms in the SXI-simulated observation image restoration task, according to the peak signal-to-noise ratio and structural similarity. The restoration results of SXI-simulated observation images are used in the tangent fitting approach and the computed tomography approach toward magnetospheric reconstruction techniques, significantly improving the reconstruction results. Hence, the proposed technology may be feasible for processing SXI-simulated observation images.

The objective of this work is to characterize the anticancer mechanism of platinum nanoparticles coated with polyethylene glycol and conjugated with Rutin (Rutin-PEG-PtNPs) in a breast cancer cell line. PtNPs were synthesized using Dendrobium officinale extract, coated with PEG, conjugated with Rutin, and characterized by the FT-IR, XRD, DLS, and TEM. The viability of the breast cancer cells (MCF-7) and normal breast cells (MCF-10A) after treatment with PEG-PtNPs and Rutin-PEG-PtNPs was studied by the MTT assay. Superoxide dismutase (SOD) and catalase (CAT) activity, MDA level, and LDH leakage in the PEG-PtNPs and Rutin-PEG-PtNPs were measured. The expression of the p53, Bax, Bcl-2, and caspase −8, and −9 genes, as well as the NF-κB and IL-6 levels in the Rutin-PEG-PtNPs treated cells, were investigated by qPCR and ELISA assays. Results demonstrated that the NPs were in a size range of 30 to 60 nm. The Rutin-PEG-PtNPs showed greater cytotoxic effects on breast cancer cells (IC50: 45.5 µg/mL) than normal breast cells (IC50: 69.4 µg/mL). The expression of the p53, Bax, caspase-8, and −9 was upregulated by 1.96, 1.84, 1.31, and 2.79 folds, while the expression of the Bcl-2 was reduced in Rutin-PEG-PtNP-treated cells. The activity of the SOD and CAT decreased, while the LDH leakage and MDA levels increased after treating the cells with Rutin-PEG-PtNPs. Also, the NF-κB and IL-6 levels in the cell cultures treated with Rutin-PEG-PtNPs were reduced by 22.6 and 17.0 %, respectively. Rutin-PEG-Pt indicated promising inhibitory potential against MCF-7 cells.

Background & aims: Durable remissions of Crohn's Disease (CD) have followed myeloablative conditioning therapy and allogeneic marrow transplantation. For patients with treatment-refractory disease, we used reduced-intensity conditioning to minimize toxicity, marrow from donors with low Polygenic Risk Scores for CD as cell sources, and protracted immune suppression to lower the risk of graft-versus-host disease (GVHD). Our aim was to achieve durable CD remissions while minimizing transplant-related complications. Methods: DNA from patients and their HLA-matched unrelated donors was genotyped and Polygenic Risk Scores calculated. Donor marrow was infused following non-myeloablative conditioning. Patient symptoms and endoscopic findings were documented at intervals after transplant. Results: We screened 807 patients, 143 of whom met eligibility criteria; 2 patients received allografts. Patient 1 had multiple complications and died at day 332 from respiratory failure. Patient 2 had resolution of CD symptoms until day 178 when CD recurred, associated with persistent host chimerism in both peripheral blood and intestinal mucosa. Withdrawal of immune suppression was followed by dominant donor immune chimerism in peripheral blood and resolution of CD findings. Over time, mucosal T-cells became donor-dominant. At 5 years after allografting, Patient 2 remained off all medications but had mild symptoms related to a jejunal stricture that required stricturoplasty at 6 years. At 8 years, she remains stable off medications. Conclusions: The kinetics of immunologic chimerism after allogeneic marrow transplantation for CD patients depends on the intensity of the conditioning regimen and the magnitude of immune suppression. One patient achieved durable improvement of her previously refractory CD only after establishing donor immunologic chimerism in intestinal mucosa. Her course provides proof-of-principal for allografting as a potential treatment for refractory CD, but an immunoablative conditioning regimen should be considered for future studies.(ClinicalTrials.gov, NCT01570348)

Abstract Inflammatory bowel disease (IBD) is a group of chronic digestive tract inflammatory conditions whose genetic etiology is still poorly understood. The incidence of IBD is particularly high among Ashkenazi Jews. Here, we identify 8 novel and plausible IBD-causing genes from the exomes of 4453 genetically identified Ashkenazi Jewish IBD cases (1734) and controls (2719). Various biological pathway analyses are performed, along with bulk and single-cell RNA sequencing, to demonstrate the likely physiological relatedness of the novel genes to IBD. Importantly, we demonstrate that the rare and high impact genetic architecture of Ashkenazi Jewish adult IBD displays significant overlap with very early onset-IBD genetics. Moreover, by performing biobank phenome-wide analyses, we find that IBD genes have pleiotropic effects that involve other immune responses. Finally, we show that polygenic risk score analyses based on genome-wide high impact variants have high power to predict IBD susceptibility.

Imaging has been an important strategy for exploring space weather. The Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) is a joint Chinese Academy of Sciences (CAS) and European Space Agency (ESA) mission, aiming at studying the interaction between Earth’s magnetosphere and solar wind near the subsolar point via soft X-ray imaging. As the boundary of Earth’s magnetosphere, magnetopause is a significant detection target to mirror solar wind’s change for the SMILE mission. In preparation for inverting three-dimensional magnetopause, we proposed an OESA-UNet model to detect the magnetopause position. The model obtains magnetopause with a U-shaped structure, in an end-to-end manner. Inspired by attention mechanisms, these blocks are integrated into ours. OESA-UNet captures low and high-level feature maps by adjusting the receptive field for precise localization. Adaptively pre-processing the image provides a prior for the network. Availability metrics are designed to determine whether it can serve three-dimensional inversion. Lastly, we provided ablation and comparison experiments by qualitative and quantitative analysis. Our recall, precision, and f1 score are 93.8%, 92.1%, and 92.9%, respectively, with an average angle deviation of 0.005 under the availability metrics. Results indicate that OESA-UNet outperforms other methods. It can better serve the purpose of magnetopause tracing from an X-ray image.

Domain adaptation can handle data distribution in different domains and has been successfully applied to bearing fault diagnosis under variable working conditions. However, most of these methods ignore the influences of noise and data distribution discrepancy on marking pseudo labels. Additionally, most domain adaptive methods require a large amount of data and training time. To overcome the aforementioned challenges, firstly, sample rejection and pseudo label correction using K-means (SRPLC-K-means) were developed and explored to filter the noisy samples and correct the pseudo labels to obtain pseudo labels with higher confidence. Furthermore, a bearing fault diagnosis method based on the improved transfer component analysis and deep belief network is proposed, which can achieve subdomain adaptation and improve the compactness of the samples, leading to a complete bearing fault diagnosis under variable working conditions that is faster and more accurate. Finally, the results of the comparative tests confirmed that the proposed method could boost the average accuracy of 0.73%, 0.99%, and 5.55% in the three tests than the state-of-the-art methods, respectively. Moreover, the comparison of the time required for a fault diagnosis using different methods shows that compared to the end-to-end models, the proposed method reduces the time required by 594.9 s and 1431.6 s, respectively.

Summary: Crohn's disease (CD) and ulcerative colitis (UC) are two etiologically related yet distinctive subtypes of the inflammatory bowel diseases (IBD). Differentiating CD from UC can be challenging using conventional clinical approaches in a subset of patients. We designed and evaluated a novel molecular-based prediction model aggregating genetics, serum biomarkers, and tobacco smoking information to assist the diagnosis of CD and UC in over 30,000 samples. A joint model combining genetics, serum biomarkers and smoking explains 46% (42–50%, 95% CI) of phenotypic variation. Despite modest overlaps with serum biomarkers, genetics makes unique contributions to distinguishing IBD subtypes. Smoking status only explains 1% (0–6%, 95% CI) of the phenotypic variance suggesting it may not be an effective biomarker. This study reveals that molecular-based models combining genetics, serum biomarkers, and smoking information could complement current diagnostic strategies and help classify patients based on biologic state rather than imperfect clinical parameters.

Abstract Background Crohn’s disease (CD) patients demonstrate distinct intestinal microbial compositions and metabolic characteristics compared to unaffected controls. However, the impact of inflammation and underlying genetic risk on these microbial profiles and their relationship to disease phenotype are unclear. We used lavage sampling to characterize the colonic mucosal-luminal interface (MLI) microbiome of CD patients in endoscopic remission and unaffected controls relative to obesity, disease genetics, and phenotype. Methods Cecum and sigmoid colon were sampled from 110 non-CD controls undergoing screening colonoscopy who were stratified by body mass index and 88 CD patients in endoscopic remission (396 total samples). CD polygenic risk score (GRS) was calculated using 186 known CD variants. MLI pellets were analyzed by 16S ribosomal RNA gene sequencing, and supernatants by untargeted liquid chromatography-mass spectrometry. Results CD and obesity were each associated with decreased cecal and sigmoid MLI bacterial diversity and distinct bacterial composition compared to controls, including expansion of Escherichia/Shigella. Cecal and sigmoid dysbiosis indices for CD were significantly greater in obese controls than non-overweight controls. CD, but not obesity, was characterized by altered biogeographic relationship between the sigmoid and cecum. GRS was associated with select taxonomic shifts that overlapped with changes seen in CD compared to controls including Fusobacterium enrichment. Stricturing or penetrating Crohn’s disease behavior was characterized by lower MLI bacterial diversity and altered composition, including reduced Faecalibacterium, compared to uncomplicated CD. Taxonomic profiles including reduced Parasutterella were associated with clinical disease progression over a mean follow-up of 3.7 years. Random forest classifiers using MLI bacterial abundances could distinguish disease state (area under the curve (AUC) 0.93), stricturing or penetrating Crohn’s disease behavior (AUC 0.82), and future clinical disease progression (AUC 0.74). CD patients showed alterations in the MLI metabolome including increased cholate:deoxycholate ratio compared to controls. Conclusions Obesity, CD in endoscopic remission, and high CD genetic risk have overlapping colonic mucosal-luminal interface (MLI) microbiome features, suggesting a shared microbiome contribution to CD and obesity which may be influenced by genetic factors. Microbial profiling during endoscopic remission predicted Crohn’s disease behavior and progression, supporting that MLI sampling could offer unique insight into CD pathogenesis and provide novel prognostic biomarkers.

New artificial intelligence scenarios, such as high-precision online industrial detection, unmanned driving, etc., are constantly emerging and have resulted in an increasing demand for real-time image processing with high frame rates and low power consumption. Histogram equalization (HE) is a very effective and commonly used image preprocessing algorithm designed to improve the quality of image processing results. However, most existing HE acceleration methods, whether run on general-purpose CPUs or dedicated embedded systems, require further improvement in their frame rate to meet the needs of more complex scenarios. In this paper, we propose an HE acceleration method for FPGAs based on a two-dimensional configurable pipeline architecture. We first optimize the parallelizability of HE with a fully configurable two-dimensional pipeline architecture according to the principle of adapting the algorithm to the hardware, where one dimension can compute the cumulative histogram in parallel and the other dimension can process multiple inputs simultaneously. This optimization also helps in the construction of a simple architecture that achieves a higher frequency when implementing HE on FPGAs, which consist of configurable input units, calculation units, and output units. Finally, we optimize the pipeline and critical path of the calculation units. In the experiments, we deploy the optimized HE on a VCU118 test board and achieve a maximum frequency of 891 MHz (which is up to 22.6 times more acceleration than CPU implementations), as well as a frame rate of 1899 frames per second for 1080p images.

Biobased furfural is a sustainable alternative to petrochemical intermediates for bulk chemicals and fuel production. However, existing methods for the conversion of xylose or lignocelluloses in mono-/bi-phasic systems to furfural involve non-selective sugar isolation or lignin condensation, limiting the valorisation of lignocelluloses. Herein, we used diformylxylose (DFX), a xylose derivative that is formed during the lignocellulosic fractionation process with formaldehyde protection, as a substitute for xylose to produce furfural in biphasic systems. Under kinetically optimized conditions, over 76 mol% of DFX could be converted to furfural in water-methyl isobutyl ketone system at a high reaction temperature with a short reaction time. Finally, isolation of xylan in eucalyptus wood as DFX with formaldehyde protection followed by converting DFX in a biphasic system gave a final furfural yield of 52 mol% (on the basis of xylan in wood), which was more than two times of that without formaldehyde. Combined with the value-added utilization of formaldehyde-protected lignin, this study would enable the full and efficient utilization of lignocellulosic biomass components and further improve the economics of the formaldehyde protection fractionation process.

Quantitative metrics for vaccine-induced T-cell responses are an important need for developing correlates of protection and their use in vaccine-based medical management and population health. Molecular TCR analysis is an appealing strategy but currently requires a targeted methodology involving complex integration of ex vivo data (antigen-specific functional T-cell cytokine responses and TCR molecular responses) that uncover only public antigen-specific metrics. Here, we describe an untargeted private TCR method that measures breadth and depth metrics of the T-cell response to vaccine challenge using a simple pre- and post-vaccine subject sampling, TCR immunoseq analysis, and a bioinformatic approach using self-organizing maps and GLIPH2. Among 515 subjects undergoing SARS-CoV-2 mRNA vaccination, we found that breadth and depth metrics were moderately correlated between the targeted public TCR response and untargeted private TCR response methods. The untargeted private TCR method was sufficiently sensitive to distinguish subgroups of potential clinical significance also observed using public TCR methods (the reduced T-cell vaccine response with age and the paradoxically elevated T-cell vaccine response of patients on anti-TNF immunotherapy). These observations suggest the promise of this untargeted private TCR method to produce T-cell vaccine-response metrics in an antigen-agnostic and individual-autonomous context.

Abstract Objective Immediate reconstruction (IR) is a safe and effective surgical treatment for patients with breast cancer. We aimed to assess the prognosis, aesthetic outcomes, and patient satisfaction of IR compared with breast conservation surgery (BCS) and total mastectomy (TM). Methods This retrospective matched-cohort study was conducted between May 2005 and December 2014. We established two cohorts according to the tumor (T) size of breast cancer. In the T≤3cm group, cases (IR) and controls (BCS or TM) were matched for age, pathological tumor size, and pathologic nodal status in a 1:1:1 ratio. In the T>3cm group, cases (IR) and controls (TM) were matched with the same factors and ratio. The primary outcome was the 5-year disease-free survival (DFS). The secondary outcome was patient satisfaction and quality of life. Results A total of 12,678 breast cancer patients were assessed for eligibility, of which 587 were included (T≤3 cm group: 155 IR vs 155 BCS vs 155 TM; T>3cm group: 61 IR vs 61 TM). In the T≤3 cm cohort, patients who underwent IR had no difference compared with those who underwent BCS or TM regarding the 5-year DFS (P=0.539); however, an improved aesthetic satisfaction, psychosocial, and sexual well-being were achieved in the IR group (P3 cm cohort, the IR group had a worse median 5-year DFS (P=0.044), especially for Her2+ or triple-negative breast carcinoma (TNBC) subtypes compared with the TM group. Conclusions IR improves aesthetic satisfaction, psychosocial, and sexual well-being for breast cancer patients with T≤3 cm. For patients with T > 3 cm invasive breast cancer, TM is superior to IR as it predicts a better 5-year DFS.

Abstract Mammography is used to detect breast cancer (BC), but its sensitivity is limited, especially for dense breasts. Circulating cell-free DNA (cfDNA) methylation tests is expected to compensate for the deficiency of mammography. We derived a specific panel of markers based on computational analysis of the DNA methylation profiles from The Cancer Genome Atlas (TCGA). Through training (n = 160) and validation set (n = 69), we developed a diagnostic prediction model with 26 markers, which yielded a sensitivity of 89.37% and a specificity of 100% for differentiating malignant disease from normal lesions [AUROC = 0.9816 (95% CI: 96.09-100%), and AUPRC = 0.9704 (95% CI: 94.54–99.46%)]. A simplified 4-marker model including cg23035715, cg16304215, cg20072171, and cg21501525 had a similar diagnostic power [AUROC = 0.9796 (95% CI: 95.56–100%), and AUPRC = 0.9220 (95% CI: 91.02–94.37%)]. We found that a single cfDNA methylation marker, cg23035715, has a high diagnostic power [AUROC = 0.9395 (95% CI: 89.72–99.27%), and AUPRC = 0.9111 (95% CI: 88.45–93.76%)], with a sensitivity of 84.90% and a specificity of 93.88%. In an independent testing dataset (n = 104), the obtained diagnostic prediction model discriminated BC patients from normal controls with high accuracy [AUROC = 0.9449 (95% CI: 90.07–98.91%), and AUPRC = 0.8640 (95% CI: 82.82–89.98%)]. We compared the diagnostic power of cfDNA methylation and mammography. Our model yielded a sensitivity of 94.79% (95% CI: 78.72–97.87%) and a specificity of 98.70% (95% CI: 86.36–100%) for differentiating malignant disease from normal lesions [AUROC = 0.9815 (95% CI: 96.75–99.55%), and AUPRC = 0.9800 (95% CI: 96.6–99.4%)], with better diagnostic power and had better diagnostic power than that of using mammography [AUROC = 0.9315 (95% CI: 89.95–96.34%), and AUPRC = 0.9490 (95% CI: 91.7–98.1%)]. In addition, hypermethylation profiling provided insights into lymph node metastasis stratifications (p

Existing studies show that moral identity promotes green consumption, but its influence mechanism and boundary conditions remain unidentified. However, moral identity includes internalization and symbolization, which affect green consumption in different ways. Advertising goal framing also has an impact on green consumption. Existing studies often focus on moral identity internalization but neglect the role of moral identity symbolization and fail to fully consider the interaction, mechanism, and boundary conditions between moral identity and advertising goal framing. This study assumes that advertising goal framing includes both intrinsic and extrinsic goals. We attempt to verify the combined influence of internalization and symbolization of moral identity, advertising goal framing, and moral awareness on green purchasing intention. Through two experiments, we found that: (1) the internalization and symbolization of moral identity can promote consumers’ green purchasing intention; (2) consumers with high internalization of moral identity have more positive responses to intrinsic goal advertising; (3) moral awareness can enhance the combined influence of moral identity internalization and intrinsic goal advertising on consumers’ green purchasing intention; and (4) self-consistency and social approval mediate the combined impact of moral identity and advertising goal framing on consumers’ green purchasing intention. This study enriches the literature on the influence of moral identity on green consumption. Businesses can also draw on these findings to improve the effectiveness of green marketing.

Hybrid recommendation algorithms perform well in improving the accuracy of recommendation systems. However, in specific applications, they still cannot reach the requirements of the recommendation target due to the gap between the design of the algorithms and data characteristics. In this paper, in order to learn higher-order feature interactions more efficiently and to distinguish the importance of different feature interactions better on the prediction results of recommendation algorithms, we propose a light and FM deep neural network (LFDNN), a hybrid recommendation model including four modules. The LightGBM module applies gradient boosting decision trees for feature processing, which improves LFDNN’s ability to handle dense numerical features; the shallow model introduces the FM model for explicitly modeling the finite-order feature crosses, which strengthens the expressive ability of the model; the deep neural network module uses a fully connected feedforward neural network to allow the model to obtain more high-order feature crosses information and mine more data patterns in the features; finally, the Fusion module allows the shallow model and the deep model to obtain a better fusion effect. The results of comparison, parameter influence and ablation experiments on two real advertisement datasets shows that the LFDNN reaches better performance than the representative recommendation models.

The sensitivity and photoelectric noise of UV photodetectors are challenges that need to be overcome in pharmaceutical solute detection applications. This paper presents a new device concept for a CsPbBr3 QDs/ZnO nanowire heterojunction structure for phototransistors. The lattice match of the CsPbBr3 QDs and ZnO nanowire reduces the generation of trap centers and avoids carrier absorption by the composite center, which greatly improves the carrier mobility and high detectivity (8.13 × 1014 Jones). It is worth noting that by using high-efficiency PVK quantum dots as the intrinsic sensing core, the device has a high responsivity (6381 A/W) and responsivity frequency (300 Hz). Thus, a UV detection system for pharmaceutical solute detection is demonstrated, and the type of solute in the chemical solution is estimated by the waveform and the size of the output 2f signals.

Being one of the most dynamic entities in the human body, glycosylation of proteins fine-tunes the activity of the organismal machinery, including the immune system, and mediates the interaction with the human microbial consortium, typically represented by the gut microbiome. Using data from 194 healthy individuals, we conducted an associational study to uncover potential relations between the gut microbiome and the blood plasma N-glycome, including N-glycome of immunoglobulin G. While lacking strong linkages on the multivariate level, we were able to identify associations between alpha and beta microbiome diversity and the blood plasma N-glycome profile. Moreover, for two bacterial genera, namely, Bilophila and Clostridium innocuum, significant associations with specific glycans were also shown. The study’s results suggest a non-trivial, possibly weak link between the total plasma N-glycome and the gut microbiome, predominantly involving glycans related to the immune system proteins, including immunoglobulin G. Further studies of glycans linked to microbiome-related proteins in well-selected patient groups are required to conclusively establish specific associations.

T-cells specifically bind antigens to induce adaptive immune responses using highly specific molecular recognition, and a diverse T-cell repertoire with expansion of antigen-specific clones can indicate robust immune responses after infection or vaccination. For patients with inflammatory bowel disease (IBD), a spectrum of chronic intestinal inflammatory diseases usually requiring immunomodulatory treatment, the T-cell response has not been well characterized. Understanding the patient factors that result in strong vaccination responses is critical to guiding vaccination schedules and identifying mechanisms of T-cell responses in IBD and other immune-mediated conditions. Here we used T-cell receptor sequencing to show that T-cell responses in an IBD cohort were influenced by demographic and immune factors, relative to a control cohort of health care workers (HCWs). Subjects were sampled at the time of SARS-CoV-2 vaccination, and longitudinally afterwards; TCR Vβ gene repertoires were sequenced and analyzed for COVID-19-specific clones. We observed significant differences in the overall strength of the T-cell response by age and vaccine type. We further stratified the T-cell response into Class-I- and Class-II-specific responses, showing that Ad26.COV2.S vector vaccine induced Class-I-biased T-cell responses, whereas mRNA vaccine types led to different responses, with mRNA-1273 vaccine inducing a more Class-I-deficient T-cell response compared to BNT162b2. Finally, we showed that these T-cell patterns were consistent with antibody levels from the same patients. Our results account for the surprising success of vaccination in nominally immuno-compromised IBD patients, while suggesting that a subset of IBD patients prone to deficiencies in T-cell response may warrant enhanced booster protocols.

The importance of long noncoding RNA (lncRNA) in tumorigenesis has been supported by increasing evidence in recent years. However, the mechanism linking lncRNA function with cancer progression remains poorly understood. lncRNA LCPAT1 plays a role in lung cancer. However, how it works in breast cancer (BC) is largely unclear. In this study, we found that LCPAT1 was highly expressed in BC tissues and cell lines. High LCPAT1 expression predicted a low survival rate in BC patients. LCPAT1 promoted BC cell proliferation, migration, and invasion while inhibiting apoptosis in vitro. LCPAT1 knockdown suppressed BC growth in vivo and vice versa. LCPAT1 interacted with RBBP4 and recruited it to the MFAP2 (microfibril-associated protein 2) promoter and then activated MFAP2 transcription. Restoration of MFAP2 rescued the effects of LCPAT1 knockdown in BC cells. In sum, LCPAT1 promotes BC progression through recruiting RBBP4 to initiate MFAP2 transcription.

Speech recognition technology has played an indispensable role in realizing human-computer intelligent interaction. However, most of the current Chinese speech recognition systems are provided online or offline models with low accuracy and poor performance. To improve the performance of offline Chinese speech recognition, we propose a hybrid acoustic model of deep convolutional neural network, long short-term memory, and deep neural network (DCNN-LSTM-DNN, DLD). This model utilizes DCNN to reduce frequency variation and adds a batch normalization (BN) layer after its convolutional layer to ensure the stability of data distribution, and then use LSTM to effectively solve the gradient vanishing problem. Finally, the fully connected structure of DNN is utilized to efficiently map the input features into a separable space, which is helpful for data classification. Therefore, leveraging the strengths of DCNN, LSTM, and DNN by combining them into a unified architecture can effectively improve speech recognition performance. Our model was tested on the open Chinese speech database THCHS-30 released by the Center for Speech and Language Technology (CSLT) of Tsinghua University, and it was concluded that the DLD model with 3 layers of LSTM and 3 layers of DNN had the best performance, reaching 13.49% of words error rate (WER).

Swarm intelligence algorithms (SIAs) have demonstrated excellent performance when solving optimization problems including many real-world problems. However, because of their expensive computational cost for some complex problems, SIAs need to be accelerated effectively for better performance. This paper presents a high-performance general framework to accelerate SIAs (FASI). Different from the previous work which accelerates SIAs through enhancing the parallelization only, FASI considers both the memory architectures of hardware platforms and the dataflow of SIAs, and it reschedules the framework of SIAs as a converged dataflow to improve the memory access efficiency. FASI achieves higher acceleration ability by matching the algorithm framework to the hardware architectures. We also design deep optimized structures of the parallelization and convergence of FASI based on the characteristics of specific hardware platforms. We take the quantum behaved particle swarm optimization algorithm as a case to evaluate FASI. The results show that FASI improves the throughput of SIAs and provides better performance through optimizing the hardware implementations. In our experiments, FASI achieves a maximum of 290.7 Mb/s throughput which is higher than several existing systems, and FASI on FPGAs achieves a better speedup than that on GPUs and multi-core CPUs. FASI is up to 123 times and not less than 1.45 times faster in terms of optimization time on Xilinx Kintex Ultrascale xcku040 when compares to Intel Core i7-6700 CPU/NVIDIA GTX1080 GPU. Finally, we compare the differences of deploying FASI on hardware platforms and provide some guidelines for promoting the acceleration performance according to the hardware architectures.

Background/Aims: Little is known about the potential mechanism of action for androgen receptor (AR) targeting treatment in estrogen receptor (ER)-negative breast cancer. This study aimed to evaluate AR status and its prognosis in four breast cancer subtypes. Bicalutamide has been identified as an AR antagonist and used for treating AR+/ER- breast cancer in a phase II trial. Our studies will clarify its mechanism in breast cancer treatment. Methods: A total of 510 consecutive cases of invasive ductal cancer (IDC) were evaluated in this study. The expression of AR was analyzed by immunohistochemistry and compared with patient survival, and its implications were evaluated in four subtypes of IDC. We examined bicalutamide as an AR antagonist to inhibit proliferation and increased apoptosis in AR+/ER- breast cancer cell lines. We explored the tumor suppressive functions of bicalutamide in vitro and vivo and its related mechanisms in AR+/ER- breast cancer. Results: AR expression was related to that of ER (P

Background and aims: Cholesterol crystals have been shown to cause inflammation. As a response to cholesterol crystal accumulation, the NLRP3 inflammasome is activated to produce IL-1β which eventually leads to atherosclerotic lesions. As a part of innate immunity, CARD8 is involved in the modulation of above mentioned inflammatory activities. The primary objective of this study was to investigate the association between polymorphism of CARD8 rs2043211 and susceptibility to arteriosclerosis obliterans (ASO) in Chinese Han male population. Methods: 758 male arteriosclerosis obliterans patients and 793 male controls were genotyped for rs2043211 with the TaqMan allele assays. Fasting blood-glucose (FBG), total cholesterol (TC), triglycerides (TG), urea nitrogen, creatinine, Serum uric acid, high density lipoprotein, low density lipoprotein, ALT, AST, and IL-1β in the blood were detected for all subjects. Clinical data were recorded to analyze the genotype-phenotype. Independent samples t-test was used to perform the comparisons between two groups. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to measure the strength of relationship in the genotype distribution and allele frequencies between patients and controls. The analysis of variance was used for a genotype-phenotype analysis of the ASO patients. Results: The genotypic and allelic frequencies in the ASO group were significantly different from that in the control group (P = 0.014 by genotype, P = 0.003 by allele). Those carrying the genotype TT had a higher risk for ASO than those carrying the genotype AA (OR = 1.494, 95%CI1.131-1.974, P = 0.005).The difference was also significant after the adjustment for the history of smoking, TC, LDL, fasting blood glucose, systolic blood pressure and BMI(OR = 1.525, 95%CI1.158-2.009, P = 0.003). Conclusion: Our finding suggests that the polymorphism of CARD8 rs2043211 is probably associated with the development of ASO in Chinese Han male population.

While hundreds of loci are linked with inflammatory bowel diseases (IBDs), the functional consequences of the associated variants remain unclear. Here, the authors screened in ulcerative colitis (UC) patients’ genomes for protein-truncating variants near IBD loci, and identify a protein truncating variant in RNF186to be protective against UC.

Lampposts, traffic lights, traffic signs, utility poles and so forth are important road furniture in urban areas. The fast and accurate localization and extraction of this type of furniture is urgent for the construction and updating of infrastructure databases in cities. This paper proposes a pipeline for mobile laser scanning data processing to locate and extract road poles. The proposed method is based on the vertical continuity with isolation feature of the pole part and the overall roughness feature of the attachment part of road poles. The isolation feature of the pole part is analysed by constructing two concentric cylinders from bottom to top and there should be no or a limited number of, points between these two cylinders. After splitting up the pole part and the attachment part of a road pole, the roughness of the candidate attachment points is computed and the attachment is obtained by performing region growing method based on roughness values. By applying the proposed pipeline to different situations in two datasets, the proposed method proves to be efficient not only in simple scenes but also in cluttered scenes.

The fast and stable reconstruction of building interiors from scanned point clouds has recently attracted considerable research interest. However, reconstructing long corridors and connected areas across multiple floors has emerged as a substantial challenge. This paper presents a comprehensive segmentation method for reconstructing a three-dimensional (3D) indoor structure with multiple stories. With this method, the over-segmentation that usually occurs in the reconstruction of long corridors in a complex indoor environment is overcome by morphologically eroding the floor space to segment rooms and by overlapping the segmented room-space with partitioned cells via extracted wall lines. Such segmentation ensures both the integrity of the room-space partitions and the geometric regularity of the rooms. For spaces across floors in a multistory building, a peak-nadir-peak strategy in the distribution of points along the z-axis is proposed in order to extract connected areas across multiple floors. A series of experimental tests while using seven real-world 3D scans and eight synthetic models of indoor environments show the effectiveness and feasibility of the proposed method.

BackgroundThe interaction of tumor necrosis factor-α (TNF-α) with its receptors: TNFRSF1A and TNFRSF1B is critical for the promotion of tumor growth, invasion and metastasis. To better understand the roles of single nucleotide polymorphisms (SNPs) in the TNF-α, TNFRSF1A and TNFRSF1B genes in the development of breast cancer, we explored the associations between SNPs in these three genes and breast cancer susceptibility in northeast Chinese Han women.Methodology/principal findingsThis case-control study was conducted among 1016 breast cancer patients and 806 age-matched healthy controls. Seven SNPs in the TNF-α (rs1800629, rs361525), TNFRSF1A (rs767455, rs4149577 and rs1800693) and TNFRSF1B (rs1061622 and rs1061624) genes were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. In TNFRSF1B, the rs1061622 GT genotype and the G allele conferred a reduced susceptibility to breast cancer (P = 0.000662, OR = 0.706, 95% CI: 0.578-0.863; P = 0.002, OR = 0.769, 95% CI; 0.654-0.905, respectively). Moreover, the AG genotype, the AA genotype and the A allele in rs1061624 conferred an increased risk of breast cancer (P = 0.007, OR = 1.470, 95% CI:1.112-1.943; P = 0.00109, OR = 1.405 95% CI:1.145-1.724; P = 0.001, OR = 1.248 95% CI:1.092-1.426, respectively). These two SNPs also had associations with breast cancer risk under the dominant model. In haplotype analysis, the CTA (rs767455 C-rs4149577 T-rs1800693 A) haplotype in TNFRSF1A and the TA (rs1061622 T-rs1061624 A) haplotype in TNFRSF1B had higher frequencies in breast cancer patients (P = 0.00324; P = 0.000370, respectively), but the frequency of GG (rs1061622 G-rs1061624 G) haplotype in TNFRSF1B was lower in breast cancer patients (P = 0.000251). The associations of the three haplotypes remained significant after correcting for multiple testing. In addition, significant associations were also observed between TNFRSF1A polymorphisms and lymph node metastasis, P53, estrogen receptor (ER) and progesterone receptor (PR) statuses.ConclusionsOur results suggest that rs1061622 and rs1061624 in TNFRSF1B may affect breast cancer risk, and SNPs in TNFRSF1A are associated with the clinical features of breast cancer.

The Puerto Rico population may be modeled as an admixed population with contributions from three continents: Sub-Saharan Africa, Ancient America, and Europe. Extending the study of the genetics of inflammatory bowel disease (IBD) to an admixed population such as Puerto Rico has the potential to shed light on IBD genes identified in studies of European populations, find new genes contributing to IBD susceptibility, and provide basic information on IBD for the care of US patients of Puerto Rican and Latino descent. In order to study the association between immune-related genes and Crohn's disease (CD) and ulcerative colitis (UC) in Puerto Rico, we genotyped 1159 Puerto Rican cases, controls, and family members with the ImmunoChip. We also genotyped 832 subjects from the Human Genome Diversity Panel to provide data for estimation of global and local continental ancestry. Association of SNPs was tested by logistic regression corrected for global continental descent and family structure. We observed the association between Crohn's disease and NOD2 (rs17313265, 0.28 in CD, 0.19 in controls, OR 1.5, p = 9×10-6) and IL23R (rs11209026, 0.026 in CD, 0.0.071 in controls, OR 0.4, p = 3.8×10-4). The haplotype structure of both regions resembled that reported for European populations and "local" continental ancestry of the IL23R gene was almost entirely of European descent. We also observed suggestive evidence for the association of the BAZ1A promoter SNP with CD (rs1200332, 0.45 in CD, 0.35 in controls, OR 1.5, p = 2×10-6). Our estimate of continental ancestry surrounding this SNP suggested an origin in Ancient America for this putative susceptibility region. Our observations underscored the great difference between global continental ancestry and local continental ancestry at the level of the individual gene, particularly for immune-related loci.

As a costimulatory molecule, Herpesvirus entry mediator (HVEM) can bind with several costimulatory members, thus HVEM plays different roles in T cell immunity. HVEM and its ligands have been involved in the pathogenesis of various autoimmune, inflammatory diseases and tumors. In the current study, we conducted a case-control study comparing polymorphisms of HVEM and breast cancer. Subjects included 575 females with breast cancer and 604 age-matched healthy controls. Six HVEM SNPs (rs2281852, rs1886730, rs2234163, rs11573979, rs2234165, and rs2234167) were genotyped by PCR-RFLP. The results showed significant differences in genotypes and alleles between rs1886730 and rs2234167 (P

Nature Communications 7 Article number: 12342 (2016); Published 9 August 2016; Updated 13 September 2016 The HTML version of this Article incorrectly listed the authors of the UK IBD Genetics Consortium and the NIDDK IBD Genetics Consortium individually in the main author list. This has now been corrected in the HTML; the PDF version of the paper was correct from the time of publication.

BACKGROUND: CD28 is one of a number of costimulatory molecules that play crucial roles in immune regulation and homeostasis. Accumulating evidence indicates that immune factors influence breast carcinogenesis. To clarify the relationships between polymorphisms in the CD28 gene and breast carcinogenesis, a case-control study was conducted in women from Heilongjiang Province in northeast of China. METHODOLOGY/PRINCIPAL FINDINGS: Our research subjects consisted of 565 female patients with sporadic breast cancer and 605 age- and sex-matched healthy controls. In total, 12 single nucleotide polymorphisms (SNPs) in the CD28 gene were successfully determined using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. The relationship between the CD28 variants and clinical features, including histological grade, tumor size, lymph node metastasis, human epidermal growth factor receptor 2 (C-erbB2), estrogen receptor (ER), progesterone receptor (PR), and tumor protein 53 (P53) status were analyzed. A statistically significant association was observed between rs3116496 and breast cancer risk under different genetic models (additive P = 0.0164, dominant P = 0.0042). Different distributions of the rs3116496 'T' allele were found in patients and controls, which remained significant after correcting the P value for multiple testing using Haploview with 10,000 permutations (corrected P = 0.0384). In addition, significant associations were observed between rs3116487/rs3116494 (D' = 1, r(2) = 0.99) and clinicopathological features such as C-erbB2 and ER status, in breast cancer patients. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that CD28 gene polymorphisms contribute to sporadic breast cancer risk and have a significant association with clinicopathological features in a northeast Chinese Han population.