ID Embedding as Subtle Features of Content and Structure for Multimodal Recommendation

Multimodal recommendation aims to model user and item representations comprehensively with the involvement of multimedia content for effective recommendations. Existing research has shown that it is beneficial for recommendation performance to combine (user- and item-) ID embeddings with multimodal salient features, indicating the value of IDs. However, there is a lack of a thorough analysis of the ID embeddings in terms of feature semantics in the literature. In this paper, we revisit the value of ID embeddings for multimodal recommendation and conduct a thorough study regarding its semantics, which we recognize as subtle features of content and structures. Then, we propose a novel recommendation model by incorporating ID embeddings to enhance the semantic features of both content and structures. Specifically, we put forward a hierarchical attention mechanism to incorporate ID embeddings in modality fusing, coupled with contrastive learning, to enhance content representations. Meanwhile, we propose a lightweight graph convolutional network for each modality to amalgamate neighborhood and ID embeddings for improving structural representations. Finally, the content and structure representations are combined to form the ultimate item embedding for recommendation. Extensive experiments on three real-world datasets (Baby, Sports, and Clothing) demonstrate the superiority of our method over state-of-the-art multimodal recommendation methods and the effectiveness of fine-grained ID embeddings

Effects of a Cardiotonic Medicine Danshen Pills, on Cognitive Ability and Expression of PSD-95 in a Vascular Dementia Rat Model

A widely used Chinese cardiotonic proprietary medicine, compound Danshen dripping pills (CDDP, Fufang Danshen Diwan) has also begun to be used for treatment of vascular dementia (VaD). We tried to explore the mechanism of CDDP action in this case. A VaD experimental model was built in rats by bilateral ligation of the common carotid arteries. The cognitive ability of experimental animals was evaluated in the Morris water maze test. Synaptic ultrastructural changes in the hippocampus were detected by transmission electron microscopy; expression of PSD-95 mRNA in the hippocampus was examined using hybridization in situ. The latter index (mRNA expression) in the VaD group was significantly lower than those in the CDDP and shamoperated groups (P < 0.05). CDDP treatment considerably improved disturbed ultrastructural synaptic characteristics in the hippocampus of VaD rats. The mean escape latency in the Morris water maze test was significantly shorter in CDDP-treated VaD rats, compared with that those of the VD group (P < 0.05). In the CDDP group compared to the VaD one, escape strategies improved from edge and random searches to more linear swim pathway (P < 0.05). Thus, decreasing expression of PSD-95 plays an important role in the pathogenesis of VaD. CDDP treatment improves the learning and memory ability of VaD rats by improving neural synaptic ultrastructural characteristics and increasing expression of PSD-95 mRNA in the hippocampus.Широко вживаний у Китаї патентований кардіотонічний засіб «складні пілюлі Даншен» (CDDP) почав також використовуватися для лікування васкулярної деменції (ВД). Ми досліджували можливі механізми дії цього засобу в даному аспекті. ВД моделювали у щурів, застосовуючи білатеральну перев’язку загальних сонних артерій. Когнітивні здатності експериментальних тварин оцінювали в тесті водного лабіринту Морріса. Ультраструктурні зміни синаптичних утворень у гіпокампі спостерігали, використовуючи трансмісійну електронну мікроскопію. Експресію мРНК білка PSD-95 у гіпокампі оцінювали із застосуванням методики гібридизації in situ. Останній показник (експресія мРНК) у щурів групи ВД був вірогідно нижчим, ніж у тварин контрольної групи та щурів із ВД, лікованих за допомогою CDDP. Середня затримка реакції уникання у тварин групи ВД істотно перевищувала відповідне значення в групі CDDP (P < 0.05). Стратегії уникання в останній групі були вірогідно кращими, ніж у групі ВД (збільшувалася пропорція лінійних маршрутів порівняно з «крайовими» та випадковими; P < 0.05). Зроблено висновок, що зниження експресії PSD-95 відіграє важливу роль у патогенезі ВД. Лікувальний ефект CDDP забезпечує покращення пам’яті та здатності до навчання у щурів з ВД; цей ефект опосередковується покращенням ультраструктурних показників синаптичних структур та збільшенням експресії мРНК білка PSD-95 у гіпокампі

Evaluation of a computer-aided diagnostic model for corneal diseases by analyzing in vivo confocal microscopy images

ObjectiveIn order to automatically and rapidly recognize the layers of corneal images using in vivo confocal microscopy (IVCM) and classify them into normal and abnormal images, a computer-aided diagnostic model was developed and tested based on deep learning to reduce physicians’ workload.MethodsA total of 19,612 corneal images were retrospectively collected from 423 patients who underwent IVCM between January 2021 and August 2022 from Renmin Hospital of Wuhan University (Wuhan, China) and Zhongnan Hospital of Wuhan University (Wuhan, China). Images were then reviewed and categorized by three corneal specialists before training and testing the models, including the layer recognition model (epithelium, bowman’s membrane, stroma, and endothelium) and diagnostic model, to identify the layers of corneal images and distinguish normal images from abnormal images. Totally, 580 database-independent IVCM images were used in a human-machine competition to assess the speed and accuracy of image recognition by 4 ophthalmologists and artificial intelligence (AI). To evaluate the efficacy of the model, 8 trainees were employed to recognize these 580 images both with and without model assistance, and the results of the two evaluations were analyzed to explore the effects of model assistance.ResultsThe accuracy of the model reached 0.914, 0.957, 0.967, and 0.950 for the recognition of 4 layers of epithelium, bowman’s membrane, stroma, and endothelium in the internal test dataset, respectively, and it was 0.961, 0.932, 0.945, and 0.959 for the recognition of normal/abnormal images at each layer, respectively. In the external test dataset, the accuracy of the recognition of corneal layers was 0.960, 0.965, 0.966, and 0.964, respectively, and the accuracy of normal/abnormal image recognition was 0.983, 0.972, 0.940, and 0.982, respectively. In the human-machine competition, the model achieved an accuracy of 0.929, which was similar to that of specialists and higher than that of senior physicians, and the recognition speed was 237 times faster than that of specialists. With model assistance, the accuracy of trainees increased from 0.712 to 0.886.ConclusionA computer-aided diagnostic model was developed for IVCM images based on deep learning, which rapidly recognized the layers of corneal images and classified them as normal and abnormal. This model can increase the efficacy of clinical diagnosis and assist physicians in training and learning for clinical purposes

Targeting the miR-6734-3p/ZEB2 axis hampers development of non-small cell lung cancer (NSCLC) and increases susceptibility of cancer cells to cisplatin treatment

The unclear pathogenesis mechanisms and resistance of cancer cells to chemical drugs serious limits the development of effective treatment strategies for non-small cell lung cancer (NSCLC). In this study, we managed to investigate this issue, and identify potential cancer associated biomarkers for NSCLC diagnosis, prognosis and treatment. This study found that miR-6734-3p was downregulated in both NSCLC clinical specimens (tissues and serum) and cells, compared to the normal tissues and cells. Next, upregulation of miR-6734-3p inhibited cancer formation and progression in NSCLC cells in vitro and in vivo. Conversely, miR-6734-3p ablation had opposite effects and facilitated NSCLC development. In addition, miR-6734-3p bound to the 3ʹ untranslated region (3ʹUTR) of zinc finger E-box binding homeobox 2 (ZEB2) mRNA to suppress its expressions in NSCLC cells. Interestingly, the inhibiting effects of miR-6734-3p overexpression on NSCLC progression were abrogated by upregulating ZEB2. Furthermore, both upregulated miR-6734-3p and silencing of ZEB2 increased cisplatin-sensitivity in cisplatin-resistant NSCLC (CR-NSCLC) cells. Taken together, miR-6734-3p played an anti-tumor role to hinder cancer development and enhanced the cytotoxic effects of cisplatin treatment on NSCLC cells by downregulating ZEB2

Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation

Sequential recommendation is an important task to predict the next-item to access based on a sequence of interacted items. Most existing works learn user preference as the transition pattern from the previous item to the next one, ignoring the time interval between these two items. However, we observe that the time interval in a sequence may vary significantly different, and thus result in the ineffectiveness of user modeling due to the issue of preference drift. In fact, we conducted an empirical study to validate this observation, and found that a sequence with uniformly distributed time interval (denoted as uniform sequence) is more beneficial for performance improvement than that with greatly varying time interval. Therefore, we propose to augment sequence data from the perspective of time interval, which is not studied in the literature. Specifically, we design five operators (Ti-Crop, Ti-Reorder, Ti-Mask, Ti-Substitute, Ti-Insert) to transform the original non-uniform sequence to uniform sequence with the consideration of variance of time intervals. Then, we devise a control strategy to execute data augmentation on item sequences in different lengths. Finally, we implement these improvements on a state-of-the-art model CoSeRec and validate our approach on four real datasets. The experimental results show that our approach reaches significantly better performance than the other 9 competing methods. Our implementation is available: https://github.com/KingGugu/TiCoSeRec

"Cell-addictive" dual-target traceable nanodrug for Parkinson's disease treatment via flotillins pathway

alpha-synclein (aS) aggregation is a representative molecular feature of the pathogenesis of Parkinson&#39;s disease (PD). Epigallocatechin gallate (EGCG) can prevent alpha S aggregation in vitro. However, the in vivo effects of PD treatment are poor due to the obstacles of EGCG accumulation in dopaminergic neurons, such as the blood brain barrier and high binding affinities between EGCG and membrane proteins. Therefore, the key to PD treatment lies in visual examination of EGCG accumulation in dopaminergic neurons. Methods: DSPE-PEG-B6, DSPE-PEG-MA, DSPE-PEG-phenylboronic acid, and superparamagnetic iron oxide nanocubes were self-assembled into tracing nanoparticles (NPs). EGCG was then conjugated on the surface of the NPs through the formation of boronate ester bonds to form a &quot;cell-addictive&quot; dual-target traceable nanodrug (B6ME-NPs). B6ME-NPs were then used for PD treatment via intravenous injection. Results: After treatment with B6ME-NPs, the PD-like characteristics was alleviated significantly. First, the amount of EGCG accumulation in PD lesions was markedly enhanced and traced via magnetic resonance imaging. Further, alpha S aggregation was greatly inhibited. Finally, the dopaminergic neurons were considerably increased. Conclusion: Due to their low price, simple preparation, safety, and excellent therapeutic effect on PD, B6ME-NPs are expected to have potential application in PD treatment.</p

Development of a surface plasmon resonance biosensing approach for the rapid detection of porcine circovirus type2 in sample solutions.

A sensitive and label-free analytical approach for the detection of porcine circovirus type 2 (PCV2) instead of PCV2 antibody in serum sample was systematically investigated in this research based on surface plasmon resonance (SPR) with an establishment of special molecular identification membrane. The experimental device for constructing the biosensing analyzer is composed of an integrated biosensor, a home-made microfluidic module, and an electrical control circuit incorporated with a photoelectric converter. In order to detect the PCV2 using the surface plasmon resonance immunoassay, the mercaptopropionic acid has been used to bind the Au film in advance through the known form of the strong S-Au covalent bonds formed by the chemical radical of the mercaptopropionic acid and the Au film. PCV2 antibodies were bonded with the mercaptopropionic acid by covalent -CO-NH- amide bonding. For the purpose of evaluating the performance of this approach, the known concentrations of PCV2 Cap protein of 10 µg/mL, 7.5 µg/mL, 5 µg/mL, 2.5 µg/mL, 1 µg/mL, and 0.5 µg/mL were prepared by diluting with PBS successively and then the delta response units (ΔRUs) were measured individually. Using the data collected from the linear CCD array, the ΔRUs gave a linear response over a wide concentration range of standard known concentrations of PCV2 Cap protein with the R-Squared value of 0.99625. The theoretical limit of detection was calculated to be 0.04 µg/mL for the surface plasmon resonance biosensing approach. Correspondingly, the recovery rate ranged from 81.0% to 89.3% was obtained. In contrast to the PCV2 detection kits, this surface plasmon resonance biosensing system was validated through linearity, precision and recovery, which demonstrated that the surface plasmon resonance immunoassay is reliable and robust. It was concluded that the detection method which is associated with biomembrane properties is expected to contribute much to determine the PCV2 in sample solutions instead of PCV2 antibody in serum samples quantitatively

PlGF/FLT-1 deficiency leads to reduced STAT3-C/EBPβ signaling and aberrant polarization in decidual macrophages during early spontaneous abortion

IntroductionDysregulated macrophage polarization (excessive M1-like or limited M2-like macrophages) in the early decidua contributes to allogeneic fetal rejection and thus early spontaneous abortion. However, the modulators of M1/M2 balance at the early maternal-fetal interface remain mostly unknown.MethodsFirst-trimester decidual tissues were collected from normal pregnant women undergoing elective pregnancy terminations and patients with spontaneous abortion. We measured the expression of placental growth factor (PlGF) and Fms-like-tyrosine-kinase receptor 1 (FLT-1), and characterized the profiles of macrophages in decidua. Notably, we investigated the effect of recombinant human PlGF (rhPlGF) on decidual macrophages (dMös) from normal pregnancy and revealed the underlying mechanisms both in vitro and in vivo.ResultsThe downregulated expression of PlGF/ FLT-1 may result in spontaneous abortion by inducing the M1-like deviation of macrophages in human early decidua. Moreover, the CBA/J×DBA/2 abortion-prone mice displayed a lower FLT-1 expression in uterine macrophages than did CBA/J×BALB/c control pregnant mice. In in vitro models, rhPlGF treatment was found to drive the M2-like polarization of dMös via the STAT3/CEBPB signaling pathway. These findings were further supported by a higher embryo resorption rate and uterine macrophage dysfunction in Pgf knockout mice, in addition to the reduced STAT3 transcription and C/EBPâ expression in uterine macrophages.DiscussionPlGF plays a key role in early pregnancy maintenance by skewing dMös toward an M2-like phenotype via the FLT-1-STAT3-C/EBP â signaling pathway. Excitingly, our results highlight a rationale that PlGF is a promising target to prevent early spontaneous abortion

Table_1_Identification of copper metabolism and cuproptosis-related subtypes for predicting prognosis tumor microenvironment and drug candidates in hepatocellular carcinoma.xlsx

Copper (Cu) is an essential element of organisms, which can affect the survival of cells. However, the role of copper metabolism and cuproptosis on hepatic carcinoma is still unclear. In this study, the TCGA database was used as the test set, and the ICGC database and self-built database were used as the validation set. We screened out a class of copper metabolism and cuproptosis-related genes (CMCRGs) that could influence hepatic carcinoma prognosis by survival analysis and differential comparison. Based on CMCRGs, patients were divided into two subtypes by cluster analysis. The C2 subtype was defined as the high copper related subtype, while the C1 subtype was defied as the low copper related subtype. At the clinical level, compared with the C1 subtype, the C2 subtype had higher grade pathological features, risk scores, and worse survival. In addition, the immune response and metabolic status also differed between C1 and C2. Specifically, C2 subtype had a higher proportion of immune cell composition and highly expressed immune checkpoint genes. C2 subtype had a higher TIDE score with a higher proportion of tumor immune dysfunction and exclusion. At the molecular level, the C2 subtype had a higher frequency of driver gene mutations (TP53 and OBSCN). Mechanistically, the single nucleotide polymorphisms of C2 subtype had a very strong transcriptional strand bias for C>A mutations. Copy number variations in the C2 subtype were characterized by LOXL3 CNV gain, which also showed high association with PDCD1/CTLA4. Finally, drug sensitivity responsiveness was assessed in both subtypes. C2 subtype had lower IC50 values for targeted and chemotherapeutic agents (sorafenib, imatinib and methotrexate, etc.). Thus, CMCRGs related subtypes showed poor response to immunotherapy and better responsiveness to targeted agents, and the results might provide a reference for precision treatment of hepatic carcinoma.</p

DataSheet_1_Identification of copper metabolism and cuproptosis-related subtypes for predicting prognosis tumor microenvironment and drug candidates in hepatocellular carcinoma.docx

Copper (Cu) is an essential element of organisms, which can affect the survival of cells. However, the role of copper metabolism and cuproptosis on hepatic carcinoma is still unclear. In this study, the TCGA database was used as the test set, and the ICGC database and self-built database were used as the validation set. We screened out a class of copper metabolism and cuproptosis-related genes (CMCRGs) that could influence hepatic carcinoma prognosis by survival analysis and differential comparison. Based on CMCRGs, patients were divided into two subtypes by cluster analysis. The C2 subtype was defined as the high copper related subtype, while the C1 subtype was defied as the low copper related subtype. At the clinical level, compared with the C1 subtype, the C2 subtype had higher grade pathological features, risk scores, and worse survival. In addition, the immune response and metabolic status also differed between C1 and C2. Specifically, C2 subtype had a higher proportion of immune cell composition and highly expressed immune checkpoint genes. C2 subtype had a higher TIDE score with a higher proportion of tumor immune dysfunction and exclusion. At the molecular level, the C2 subtype had a higher frequency of driver gene mutations (TP53 and OBSCN). Mechanistically, the single nucleotide polymorphisms of C2 subtype had a very strong transcriptional strand bias for C>A mutations. Copy number variations in the C2 subtype were characterized by LOXL3 CNV gain, which also showed high association with PDCD1/CTLA4. Finally, drug sensitivity responsiveness was assessed in both subtypes. C2 subtype had lower IC50 values for targeted and chemotherapeutic agents (sorafenib, imatinib and methotrexate, etc.). Thus, CMCRGs related subtypes showed poor response to immunotherapy and better responsiveness to targeted agents, and the results might provide a reference for precision treatment of hepatic carcinoma.</p