Targeted Cyclo[8]pyrrole-Based NIR-II Photoacoustic Tomography Probe for Suppression of Orthotopic Pancreatic Tumor Growth and Intra-abdominal Metastases.

Pancreatic cancer is highly lethal. New diagnostic and treatment modalities are desperately needed. We report here that an expanded porphyrin, cyclo[8]pyrrole (CP), with a high extinction coefficient (89.16 L/g·cm) within the second near-infrared window (NIR-II), may be formulated with an αvß3-specific targeting peptide, cyclic-Arg-Gly-Asp (cRGD), to form cRGD-CP nanoparticles (cRGD-CPNPs) with promising NIR-II photothermal (PT) therapeutic and photoacoustic (PA) imaging properties. Studies with a ring-array PA tomography system, coupled with analysis of control nanoparticles lacking a targeting element (CPNPs), revealed that cRGD conjugation promoted the delivery of the NPs through abnormal vessels around the tumor to the solid tumor core. This proved true in both subcutaneous and orthotopic pancreatic tumor mice models, as confirmed by immunofluorescent studies. In combination with NIR-II laser photoirradiation, the cRGD-CPNPs provided near-baseline tumor growth inhibition through PTT both in vitro and in vivo. Notably, the combination of the present cRGD-CPNPs and photoirradiation was found to inhibit intra-abdominal metastases in an orthotopic pancreatic tumor mouse model. The cRGD-CPNPs also displayed good biosafety profiles, as inferred from PA tomography, blood analyses, and H&E staining. They thus appear promising for use in combined PA imaging and PT therapeutic treatment of pancreatic cancer.

SYT4 binds to SNAP25 to facilitate exosomal secretion and prostate cancer enzalutamide resistance.

Prostate carcinoma represents a predominant malignancy affecting the male population, with androgen deprivation therapy (ADT) serving as a critical therapeutic modality for advanced disease states, but it often leads to the development of resistance. Enzalutamide (Enz), a second-generation antiandrogen drug, initially offers substantial therapeutic benefit, but its efficacy wanes as drug resistance ensues. In this study, we found that synaptotagmin 4 (SYT4) is an upregulated gene in enzalutamide-resistant (EnzR) cell lines. The downregulation of SYT4, in combination with enzalutamide therapy, substantially enhances the antiproliferative effect on resistant prostate cancer cells beyond the capacity of enzalutamide monotherapy. SYT4 promotes vesicle efflux by binding to the synaptosome-associated protein 25 (SNAP25), thereby contributing to cell resistance against enzalutamide. The elevated expression of SYT4 is mediated by bromodomain-containing protein 4 (BRD4), and BRD4 inhibition effectively suppressed the expression of SYT4. Treatment with a therapeutic dose of enzalutamide combined with ASO-1, an antisense oligonucleotide drug targeting SYT4, shows promising results in reversing the resistance of prostate cancer to enzalutamide.

Efficient and Stable All-Polymer Solar Cells Enabled by Dual Working Mechanism.

Ternary strategy with integration characteristics and adaptability is a simple and effective method for blooming of the performance of photovoltaic devices. Herein, a novel wideband gap polymer donor PBB2-Hs is synthesized as the guest component to optimize all-polymer solar cells (all-PSCs). High-energy photon absorption and long exciton lifetime of PBB2-Hs constitute efficient energy transfer. Good miscibility and cascade energy levels promote the formation of alloy-like structure between PBB2-Hs and host system. The dual working mechanisms greatly improve photon capture and charge transfer in active layers. Additionally, the introduction of PBB2-Hs also optimizes the ordered molecular stacking of acceptors and suppresses molecular peristalsis. Upon adding 15 wt% PBB2-Hs, the ternary all-PSC achieved a champion efficiency of 17.66%, and can still maintain 82% photostability (24 h) and 91% storage stability (1000 h) of the original PCE. Moreover, the strong molecular stacking and entanglement between PBB2-Hs and the host material increased the elongation at break of ternary blend film by 1.6 times (16.2%), allowing the flexible device to maintain 83% of the original efficiency after 800 bends (R = 5 mm). This work highlights the effectiveness of guest polymer on simultaneously improving photovoltaic performance, photostability and mechanical stability in all-PSCs.

Transcriptomic insights into UTUC: role of inflammatory fibrosis and potential for personalized treatment.

BACKGROUND: Upper tract urothelial carcinoma (UTUC) is a rare disease, belonging to the same category of urothelial cancers as bladder cancer (BC). Despite sharing similar non-surgical treatment modalities, UTUC demonstrates a higher metastasis propensity than BC. Furthermore, although both cancers exhibit similar molecular disease emergence mechanisms, sequencing data reveals some differences. Our study investigates the transcriptomic distinctions between UTUC and BC, explores the causes behind UTUC's heightened metastatic tendency, constructs a model for UTUC metastasis and prognosis, and propose personalized treatment strategies for UTUC. METHODS: In our research, we utilized differential gene expression analysis, interaction networks, and Cox regression to explore the enhanced metastatic propensity of UTUC. We formulated and validated a prognostic risk model using diverse techniques, including cell co-culture, reverse transcription quantitative polymerase chain reaction (rt-qPCR), western blotting, and transwell experiments. Our methodological approach also involved survival analysis, risk model construction, and drug screening leveraging the databases of CTRPv2, PRISM and CMap. We used the Masson staining technique for histological assessments. All statistical evaluations were conducted using R software and GraphPad Prism 9, reinforcing the rigorous and comprehensive nature of our research approach. RESULTS: Screening through inflammatory fibrosis revealed a reduction of extracellular matrix and cell adhesion molecules regulated by proteoglycans in UTUC compared with BC, making UTUC more metastasis-prone. We demonstrated that SDC1, LUM, VEGFA, WNT7B, and TIMP3, are critical in promoting UTUC metastasis. A risk model based on these five molecules can effectively predict the risk of UTUC metastasis and disease-free survival time. Given UTUC's unique molecular mechanisms distinct from BC, we discovered that UTUC patients could better mitigate the issue of poor prognosis associated with UTUC's easy metastasis through tyrosine kinase inhibitors (TKIs) alongside the conventional gemcitabine and cisplatin chemotherapy regimen. CONCLUSIONS: The poor prognosis of UTUC because of its high metastatic propensity is intimately tied to inflammatory fibrosis induced by the accumulation of reactive oxygen species. The biological model constructed using the five molecules SDC1, LUM, VEGFA, WNT7B, and TIMP3 can effectively predict patient prognosis. UTUC patients require specialized treatments in addition to conventional regimens, with TKIs exhibiting significant potential.

Observing perineuronal nets like structures via coaxial scattering quantitative interference imaging at multiple wavelengths.

Perineuronal nets (PNNs) are important functional structures on the surface of nerve cells. Observation of PNNs usually requires dyeing or fluorescent labeling. As a network structure with a micron grid and sub-wavelength thickness but no special optical properties, quantitative phase imaging (QPI) is the only purely optical method for high-resolution imaging of PNNs. We proposed a Scattering Quantitative Interference Imaging (SQII) method which measures the geometric rather than transmission or reflection phase during the scattering process to visualize PNNs. Different from QIP methods, SQII method is sensitive to scattering and not affected by wavelength changes. Via geometric phase shifting method, we simplify the phase shift operation. The SQII method not only focuses on interference phase, but also on the interference contrast. The singularity points and phase lines of the scattering geometric phase depict the edges of the network structure and can be found at the valley area of the interference contrast parameter SINDR under different wavelengths. Our SQII method has its unique imaging properties, is very simple and easy to implement and has more worth for promotion.

Effects of lianas on forest biogeochemistry during their lives and afterlives.

Climate change and other anthropogenic disturbances are increasing liana abundance and biomass in many tropical and subtropical forests. While the effects of living lianas on species diversity, ecosystem carbon, and nutrient dynamics are receiving increasing attention, the role of dead lianas in forest ecosystems has been little studied and is poorly understood. Trees and lianas coexist as the major woody components of forests worldwide, but they have very different ecological strategies, with lianas relying on trees for mechanical support. Consequently, trees and lianas have evolved highly divergent stem, leaf, and root traits. Here we show that this trait divergence is likely to persist after death, into the afterlives of these organs, leading to divergent effects on forest biogeochemistry. We introduce a conceptual framework combining horizontal, vertical, and time dimensions for the effects of liana proliferation and liana tissue decomposition on ecosystem carbon and nutrient cycling. We propose a series of empirical studies comparing traits between lianas and trees to answer questions concerning the influence of trait afterlives on the decomposability of liana and tree organs. Such studies will increase our understanding of the contribution of lianas to terrestrial biogeochemical cycling, and help predict the effects of their increasing abundance.

Iodine Adsorption-Desorption-Induced Structural Transformation and Improved Ag+ Turn-On Luminescent Sensing Performance of a Nonporous Eu(III) Metal-Organic Framework.

Posttreatment of pristine metal-organic frameworks (MOFs) with suitable vapor may be an effective way to regulate their structures and properties but has been less explored. Herein, we report an interesting example in which a crystalline nonporous Eu(III)-MOF was transferred to a porous amorphous MOF (aMOF) via iodine vapor adsorption-desorption posttreatment, and the resulting aMOF showed improved turn-on sensing properties with respect to Ag+ ions. The crystalline Eu-MOF, namely, Eu-IPDA, was assembled from Eu(III) and 4,4'-{4-[4-(1H-imidazol-1-yl)phenyl]pyridine-2,6-diyl}dibenzoic acid (H2IPDA) and exhibited a two-dimensional (2D) coordination network based on one-dimensional secondary building blocks. The close packing of the 2D networks gives rise to a three-dimensional supramolecular framework without any significant pores. Interestingly, the nonporous Eu-IPDA could absorb iodine molecules when Eu-IPDA crystals were placed in iodine vapor at 85 °C, and the adsorption capacity was 1.90 g/g, which is comparable to those of many MOFs with large BET surfaces. The adsorption of iodine is attributed to the strong interactions among the iodine molecule, the carboxy group, and the N-containing group and leads to the amorphization of the framework. After immersion of the iodine-loaded Eu-IPDA in EtOH, approximately 89.7% of the iodine was removed, resulting in a porous amorphous MOF, denoted as a-Eu-IPDA. In addition, the remaining iodine in the a-Eu-IPDA framework causes strong luminescent quenching in the fluorescence emission region of the Eu(III) center when compared with that in Eu-IPDA. The luminescence intensity of a-Eu-IPDA in water suspensions was significantly enhanced when Ag+ ions were added, with a detection limit of 4.76 × 10-6 M, which is 1000 times that of pristine Eu-IPDA. It also showed strong anti-interference ability over many common competitive metal ions and has the potential to sense Ag+ in natural water bodies and traditional Chinese medicine preparations. A mechanistic study showed that the interactions between Ag+ and the absorbed iodine, the carboxylate group, and the N atoms all contribute to the sensing performance of a-Eu-IPDA.

Species-level understanding of the bacterial community in Daqu based on full-length 16S rRNA gene sequences.

Daqu is used as the fermentation starter of Baijiu and contributes diversified functional microbes for saccharifying grains and converting sugars into ethanol and aroma components in Baijiu products. Daqu is mainly classified into three types, namely low (LTD), medium (MTD) and high (HTD) temperature Daqu, according to the highest temperatures reached in their fermentation processes. In this study, we used the PacBio small-molecule real-time (SMRT) sequencing technology to determine the full-length 16 S rRNA gene sequences from the metagenomes of 296 samples of different types of Daqu collected from ten provinces in China, and revealed the bacterial diversity at the species level in the Daqu samples. We totally identified 310 bacteria species, including 78 highly abundant species (with a relative abundance >0.1% each) which accounted for 91.90% of the reads from all the Daqu samples. We also recognized the differentially enriched bacterial species in different types of Daqu, and in the Daqu samples with the same type but from different provinces. Specifically, Lactobacillales, Enterobacterales and Bacillaceae were significantly enriched in the LTD, MTD and HTD groups, respectively. The potential co-existence and exclusion relationships among the bacteria species involved in all the Daqu samples and in the LTD, MTD and HTD samples from a specific region were also identified. These results provide a better understanding of the bacterial diversity in different types of Daqu at the species level.

Metagenomic analysis of healthy and diseased peri-implant microbiome under different periodontal conditions: a cross-sectional study.

BACKGROUND: Peri-implantitis is a polybacterial infection that can lead to the failure of dental implant rehabilitation. This study aimed to profile the microbiome of the peri-implant plaque and estimate the effect of periodontitis on it among 40 Chinese participants with dental implant prostheses and presenting with varying peri-implant and periodontal health states. METHODS: Submucosal plaque samples were collected from four distinct clinical categories based on both their implant and periodontal health status at sampling point. Clinical examinations of dental implant and remaining teeth were carried out. Metagenomic analysis was then performed. RESULTS: The microbiome of the peri-implantitis sites differed from that of healthy implant sites, both taxonomically and functionally. Moreover, the predominant species in peri-implantitis sites were slightly affected by the presence of periodontitis. T. forsythia, P. gingivalis, T. denticola, and P. endodontalis were consistently associated with peri-implantitis and inflammatory clinical parameters regardless of the presence of periodontitis. Prevotella spp. and P. endodontalis showed significant differences in the peri-implantitis cohorts under different periodontal conditions. The most distinguishing function between diseased and healthy implants is related to flagellar assembly, which plays an important role in epithelial cell invasion. CONCLUSIONS: The composition of the peri-implant microbiome varied in the diseased and healthy states of implants and is affected by individual periodontal conditions. Based on their correlations with clinical parameters, certain species are associated with disease and healthy implants. Flagellar assembly may play a vital role in the process of peri-implantitis.

Enhancing the Localization Accuracy of UAV Images under GNSS Denial Conditions.

Unmanned aerial vehicles (UAVs) are widely used in many industries. The use of UAV images for surveying requires that the images contain high-precision localization information. However, the accuracy of UAV localization can be compromised in complex GNSS environments. To address this challenge, this study proposed a scheme to improve the localization accuracy of UAV sequences. The combination of traditional and deep learning methods can achieve rapid improvement of UAV image localization accuracy. Initially, individual UAV images with high similarity were selected using an image retrieval and localization method based on cosine similarity. Further, based on the relationships among UAV sequence images, short strip sequence images were selected to facilitate approximate location retrieval. Subsequently, a deep learning image registration network, combining SuperPoint and SuperGlue, was employed for high-precision feature point extraction and matching. The RANSAC algorithm was applied to eliminate mismatched points. In this way, the localization accuracy of UAV images was improved. Experimental results demonstrate that the mean errors of this approach were all within 2 pixels. Specifically, when using a satellite reference image with a resolution of 0.30 m/pixel, the mean error of the UAV ground localization method reduced to 0.356 m.

LAFL Factors in Seed Development and Phase Transitions.

Development is a chain reaction in which one event leads to another until the completion of a life cycle. Phase transitions are milestone events in the cycle of life. LEAFY COTYLEDON1 (LEC1), ABA INSENSITIVE3 (ABI3), FUSCA3 (FUS3), and LEC2 proteins, collectively known as LAFL, are master transcription factors (TFs) regulating seed and other developmental processes. Since the initial characterization of the LAFL genes, more than three decades of active research has generated tremendous amounts of knowledge about these TFs, whose roles in seed development and germination have been comprehensively reviewed. Recent advances in cell biology with genetic and genomic tools have allowed the characterization of the LAFL regulatory networks in previously challenging tissues at a higher throughput and resolution in reference species and crops. In this review, we provide a holistic perspective by integrating advances at the epigenetic, transcriptional, posttranscriptional, and protein levels to exemplify the spatiotemporal regulation of the LAFL networks in Arabidopsis seed development and phase transitions, and we briefly discuss the evolution of these TF networks.

Prediction of heavy-section ductile iron fracture toughness based on machine learning.

The preparation process and composition design of heavy-section ductile iron are the key factors affecting its fracture toughness. These factors are challenging to address due to the long casting cycle, high cost and complex influencing factors of this type of iron. In this paper, 18 cubic physical simulation test blocks with 400 mm wall thickness were prepared by adjusting the C, Si and Mn contents in heavy-section ductile iron using a homemade physical simulation casting system. Four locations with different cooling rates were selected for each specimen, and 72 specimens with different compositions and cooling times of the heavy-section ductile iron were prepared. Six machine learning-based heavy-section ductile iron fracture toughness predictive models were constructed based on measured data with the C content, Si content, Mn content and cooling rate as input data and the fracture toughness as the output data. The experimental results showed that the constructed bagging model has high accuracy in predicting the fracture toughness of heavy-section ductile iron, with a coefficient of coefficient (R2) of 0.9990 and a root mean square error (RMSE) of 0.2373.

Influence mechanism of the temporal duration of laser irradiation on photoacoustic technique: a review.

Significance: In the photoacoustic (PA) technique, the laser irradiation in the time domain (i.e., laser pulse duration) governs the characteristics of PA imaging-it plays a crucial role in the optical-acoustic interaction, the generation of PA signals, and the PA imaging performance. Aim: We aim to provide a comprehensive analysis of the impact of laser pulse duration on various aspects of PA imaging, encompassing the signal-to-noise ratio, the spatial resolution of PA imaging, the acoustic frequency spectrum of the acoustic wave, the initiation of specific physical phenomena, and the photothermal-PA (PT-PA) interaction/conversion. Approach: By surveying and reviewing the state-of-the-art investigations, we discuss the effects of laser pulse duration on the generation of PA signals in the context of biomedical PA imaging with respect to the aforementioned aspects. Results: First, we discuss the impact of laser pulse duration on the PA signal amplitude and its correlation with the lateral resolution of PA imaging. Subsequently, the relationship between the axial resolution of PA imaging and the laser pulse duration is analyzed with consideration of the acoustic frequency spectrum. Furthermore, we examine the manipulation of the pulse duration to trigger physical phenomena and its relevant applications. In addition, we elaborate on the tuning of the pulse duration to manipulate the conversion process and ratio from the PT to PA effect. Conclusions: We contribute to the understanding of the physical mechanisms governing pulse-width-dependent PA techniques. By gaining insight into the mechanism behind the influence of the laser pulse, we can trigger the pulse-with-dependent physical phenomena for specific PA applications, enhance PA imaging performance in biomedical imaging scenarios, and modulate PT-PA conversion by tuning the pulse duration precisely.

Primary cervical malignant melanoma that was successfully treated with pembrolizumab: a case report and literature review.

Primary malignant melanoma (MM) arising from the cervix is an exceedingly rare occurrence, and patients diagnosed with this condition often face a dismal clinical prognosis. Here, we present a case study of a postmenopausal woman presenting with vaginal bleeding and a conspicuous 5-centimeter black mass on the cervix. Based on the staging criteria established by the International Federation of Gynecology and Obstetrics, she was diagnosed with stage IIB primary cervical MM. The patient underwent neoadjuvant therapy prior to a radical hysterectomy and a bilateral salpingo-oophorectomy. Subsequently, she completed 18 cycles of pembrolizumab therapy, achieving clinical complete remission. Notably, at the 31-month follow-up, there were no signs of recurrence. This successful treatment outcome serves as a valuable clinical reference for the management of primary cervical MM.

Voice from both sides: a molecular dialogue between transcriptional activators and repressors in seed-to-seedling transition and crop adaptation.

High-quality seeds provide valuable nutrients to human society and ensure successful seedling establishment. During maturation, seeds accumulate storage compounds that are required to sustain seedling growth during germination. This review focuses on the epigenetic repression of the embryonic and seed maturation programs in seedlings. We begin with an extensive overview of mutants affecting these processes, illustrating the roles of core proteins and accessory components in the epigenetic machinery by comparing mutants at both phenotypic and molecular levels. We highlight how omics assays help uncover target-specific functional specialization and coordination among various epigenetic mechanisms. Furthermore, we provide an in-depth discussion on the Seed dormancy 4 (Sdr4) transcriptional corepressor family, comparing and contrasting their regulation of seed germination in the dicotyledonous species Arabidopsis and two monocotyledonous crops, rice and wheat. Finally, we compare the similarities in the activation and repression of the embryonic and seed maturation programs through a shared set of cis-regulatory elements and discuss the challenges in applying knowledge largely gained in model species to crops.

Effect of angled abutments in the posterior maxillary region on tilted implants: a 3D finite element analysis.

The aim of this study was to evaluate the bone tissue effects under dynamic loading using finite element analysis (FEA) for four angled abutments with different deviated palatal lateral tilt angles. A three-dimensional model of the posterior maxillary region and an implant crown model were reconstructed and assembled with a three-dimensional model of the implant, angled abutment, and central screw to create a total of 10 three-dimensional finite element models tilted at 15 ∘ , 20 ∘ , 25 ∘ , and 30 ∘ in three groups, and the dynamic loads simulating oral mastication were loaded on the implant crown to analyze the equivalent stresses and strains in the peri-implant bone tissues. Under the dynamic loading, the cortical bone on the buccal side of the implant neck showed different degrees of stress concentration, and the cortical bone stress was much higher than the cancellous bone, and the strain concentration area of each model was located in the bone tissue around the implant neck and base. For the use of angular abutment, under the premise that the cortical bone stresses and strains of the 10 models meet the requirements for use, the peak stresses of 2.907 MPa, 3.018 MPa, and 2.164 MPa were achieved by using the 20 ∘ angular abutment to achieve the tilt angles of 20 ∘ , 25 ∘ , and 30 ∘ implantation, which is more advantageous compared with other models.

Decoding Bilingual EEG Signals With Complex Semantics Using Adaptive Graph Attention Convolutional Network.

Decoding neural signals of silent reading with Brain-Computer Interface (BCI) techniques presents a fast and intuitive communication method for severely aphasia patients. Electroencephalogram (EEG) acquisition is convenient and easily wearable with high temporal resolution. However, existing EEG-based decoding units primarily concentrate on individual words due to their low signal-to-noise ratio, rendering them insufficient for facilitating daily communication. Decoding at the word level is less efficient than decoding at the phrase or sentence level. Furthermore, with the popularity of multilingualism, decoding EEG signals with complex semantics under multiple languages is highly urgent and necessary. To the best of our knowledge, there is currently no research on decoding EEG signals during silent reading of complex semantics, let alone decoding silent reading EEG signals with complex semantics for bilingualism. Moreover, the feasibility of decoding such signals remains to be investigated. In this work, we collect silent reading EEG signals of 9 English Phrases (EP), 7 English Sentences (ES), 10 Chinese Phrases (CP), and 7 Chinese Sentences (CS) from the subject within 26 days. We propose a novel Adaptive Graph Attention Convolution Network (AGACN) for classification. Experimental results demonstrate that our proposed method outperforms state-of-the-art methods, achieving the highest classification accuracy of 54.70%, 62.26%, 44.55%, and 57.14% for silent reading EEG signals of EP, ES, CP, and CS, respectively. Moreover, our results prove the feasibility of complex semantics EEG signal decoding. This work will aid aphasic patients in achieving regular communication while providing novel ideas for neural signal decoding research.

Encapsulation of ß-carotene in gelatin-gum Arabic-sodium carboxymethylcellulose complex coacervates: Enhancing surimi gel properties and exploring 3D printing potential.

This study investigates the utilization of functional additives (ß-carotene microcapsules) and 3D printing technology for the production of innovative surimi products. The ß-carotene microcapsules were prepared using different ratios of gelatin (Ge), gum Arabic (Ara), and carboxymethylcellulose sodium (CMC). Among these ratios, the ratio of 5:5:1 (Ge:Ara:CMC) resulted in more stable microcapsules spherical structures and better environmental stability. Subsequently, different concentrations (5-20 %) of the obtained ß-carotene microcapsules were added to surimi samples. As the concentration increased, there was an improvement in the gel strength of the surimi. However, no significant changes were observed when the concentration was 15 % (p > 0.05). All samples exhibited shear thinning behavior. The addition of microcapsules improved the resilience and thixotropy of surimi, making it more suitable for 3D printing applications. The inclusion of ß-carotene microcapsules in surimi products not only meets the nutritional needs of consumers, but also provides valuable insights for the development of functional surimi products.