Electro-spinning/netting: A strategy for the fabrication of three-dimensional polymer nano-fiber/nets.

Since 2006, a rapid development has been achieved in a subject area, so called electro-spinning/netting (ESN), which comprises the conventional electrospinning process and a unique electro-netting process. Electro-netting overcomes the bottleneck problem of electrospinning technique and provides a versatile method for generating spider-web-like nano-nets with ultrafine fiber diameter less than 20 nm. Nano-nets, supported by the conventional electrospun nanofibers in the nano-fiber/nets (NFN) membranes, exhibit numerious attractive characteristics such as extremely small diameter, high porosity, and Steiner tree network geometry, which make NFN membranes optimal candidates for many significant applications. The progress made during the last few years in the field of ESN is highlighted in this review, with particular emphasis on results obtained in the author's research units. After a brief description of the development of the electrospinning and ESN techniques, several fundamental properties of NFN nanomaterials are addressed. Subsequently, the used polymers and the state-of-the-art strategies for the controllable fabrication of NFN membranes are highlighted in terms of the ESN process. Additionally, we highlight some potential applications associated with the remarkable features of NFN nanostructure. Our discussion is concluded with some personal perspectives on the future development in which this wonderful technique could be pursued

A thermal behavior of low-substituted hydroxyethyl cellulose and cellulose solutions in NaOH-water

The articles belonging to the special issue are open access, all published articles are freely available online.International audienceHydroxyethyl cellulose (HEC) with low molar substitution has better solubility in 8%NaOH-water solution than pure cellulose. The thermal behavior of ternary HEC/NaOH/water mixtures was investigated by DSC, and the results are compared with those of cellulose/NaOH/water solutions, aiming at providing better understanding about cellulose dissolution mechanism in NaOH-water. At low polymer concentrations and below 0°C, HEC and cellulose solutions exhibit a similar thermal behavior with ice, eutectic and/or melting and recrystallization peaks, showing that the overall interactions between NaOH, water and cellulose or HEC are identical. However, when the concentration increases above 2%, the eutectic peak of HEC solutions disappeared, leaving only the ice peak, which is different from previous results for cellulose where the disappearance of the eutectic peak was related to the maximum solubility of cellulose (around 8 wt%). This implies that the dissolution behavior of HEC in NaOH solution is changed due to possible changes of chain flexibility and/or increased attractions to water caused by the hydrophilic hydroxyethyl groups. The melting and recrystallization peaks visible only at low concentrations of HEC or cellulose in solution also support the conclusion that dissolution of cellulose and HEC at low concentrations bears features which are not yet understood

Dorsomorphin, a Selective Small Molecule Inhibitor of BMP Signaling, Promotes Cardiomyogenesis in Embryonic Stem Cells

Background: Pluripotent embryonic stem (ES) cells, which have the capacity to give rise to all tissue types in the body, show great promise as a versatile source of cells for regenerative therapy. However, the basic mechanisms of lineage specification of pluripotent stem cells are largely unknown, and generating sufficient quantities of desired cell types remains a formidable challenge. Small molecules, particularly those that modulate key developmental pathways like the bone morphogenetic protein (BMP) signaling cascade, hold promise as tools to study in vitro lineage specification and to direct differentiation of stem cells toward particular cell types. Methodology/Principal Findings: We describe the use of dorsomorphin, a selective small molecule inhibitor of BMP signaling, to induce myocardial differentiation in mouse ES cells. Cardiac induction is very robust, increasing the yield of spontaneously beating cardiomyocytes by at least 20 fold. Dorsomorphin, unlike the endogenous BMP antagonist Noggin, robustly induces cardiomyogenesis when treatment is limited to the initial 24-hours of ES cell differentiation. Quantitative-PCR analyses of differentiating ES cells indicate that pharmacological inhibition of BMP signaling during the early critical stage promotes the development of the cardiomyocyte lineage, but reduces the differentiation of endothelial, smooth muscle, and hematopoietic cells. Conclusions/Significance: Administration of a selective small molecule BMP inhibitor during the initial stages of ES cell differentiation substantially promotes the differentiation of primitive pluripotent cells toward the cardiomyocytic lineage, apparently at the expense of other mesodermal lineages. Small molecule modulators of developmental pathways like dorsomorphin could become versatile pharmacological tools for stem cell research and regenerative medicine

High CRLF2 expression associates with IKZF1 dysfunction in adult acute lymphoblastic leukemia without CRLF2 rearrangement.

Overexpression of cytokine receptor-like factor 2 (CRLF2) due to chromosomal rearrangement has been observed in acute lymphoblastic leukemia (ALL) and reported to contribute to oncogenesis and unfavorable outcome in ALL. We studied B-ALL and T-ALL patients without CRLF2 rearrangement and observed that CRLF2 is significantly increased in a subset of these patients. Our study shows that high CRLF2expression correlates with high-risk ALL markers, as well as poor survival. We found that the IKZF1-encoded protein, Ikaros, directly binds to the CRLF2 promoter and regulates CRLF2 expression in leukemia cells. CK2 inhibitor, which can increase Ikaros activity, significantly increases Ikaros binding in ALL cells and suppresses CRLF2 expression in an Ikaros-dependent manner. CRLF2 expression is significantly higher in patients with IKZF1 deletion as compared to patients without IKZF1 deletion. Treatment with CK2 inhibitor also results in an increase in IKZF1 binding to the CRLF2 promoter and suppression of CRLF2 expression in primary ALL cells. We further observed that CK2 inhibitor induces increased H3K9me3 histone modifications in the CRLF2 promoter in ALL cell lines and primary cells. Taken together, our results demonstrate that high expression of CRLF2 correlates with high-risk ALL and short survival in patients without CRLF2 rearrangement. Our results are the first to demonstrate that the IKZF1-encoded Ikaros protein directly suppresses CRLF2 expression through enrichment of H3K9me3 in its promoter region. Our data also suggest that high CRLF2 expression works with the IKZF1 deletion to drive oncogenesis of ALL and has significance in an integrated prognostic model for adult high-risk ALL

Interpretable Knowledge Tracing via Response Influence-based Counterfactual Reasoning

Knowledge tracing (KT) plays a crucial role in computer-aided education and intelligent tutoring systems, aiming to assess students' knowledge proficiency by predicting their future performance on new questions based on their past response records. While existing deep learning knowledge tracing (DLKT) methods have significantly improved prediction accuracy and achieved state-of-the-art results, they often suffer from a lack of interpretability. To address this limitation, current approaches have explored incorporating psychological influences to achieve more explainable predictions, but they tend to overlook the potential influences of historical responses. In fact, understanding how models make predictions based on response influences can enhance the transparency and trustworthiness of the knowledge tracing process, presenting an opportunity for a new paradigm of interpretable KT. However, measuring unobservable response influences is challenging. In this paper, we resort to counterfactual reasoning that intervenes in each response to answer \textit{what if a student had answered a question incorrectly that he/she actually answered correctly, and vice versa}. Based on this, we propose RCKT, a novel response influence-based counterfactual knowledge tracing framework. RCKT generates response influences by comparing prediction outcomes from factual sequences and constructed counterfactual sequences after interventions. Additionally, we introduce maximization and inference techniques to leverage accumulated influences from different past responses, further improving the model's performance and credibility. Extensive experimental results demonstrate that our RCKT method outperforms state-of-the-art knowledge tracing methods on four datasets against six baselines, and provides credible interpretations of response influences.Comment: ICDE'24 (fixing a few typos). Source code at https://github.com/JJCui96/RCKT. Keywords: knowledge tracing, interpretable machine learning, counterfactual reasoning, artificial intelligence for educatio

Simultaneous primary thyroid MALT lymphoma and papillary thyroid cancer

The mucosa-associated lymphoid tissue (MALT) lymphoma subtype, specifically extranodal marginal zone B-cell lymphoma, is a rare variant. Within this subtype, primary thyroid MALT lymphoma is an uncommon occurrence. The literature provides limited documentation on thyroid MALT lymphomas, as their prevalence is comparatively lower than in other organ sites. The coexistence of papillary thyroid carcinoma (PTC) and thyroid MALT lymphomas is exceedingly rare. It presents a rare case of primary thyroid MALT lymphoma accompanied by PTC, thyroid lymphoma not being considered before surgery. A 64-year-old female patient, who had been experiencing symptoms related to a substantial thyroid tumor for a duration of three years, she refused to do a needle biopsy before surgery and expressed a preference for surgical resection. Consequently, the patient underwent a total thyroidectomy along with lymphadenectomy of the central compartment. A histological examination subsequently confirmed the presence of papillary thyroid carcinoma (PTC) and mucosa-associated lymphoid tissue (MALT) lymphoma. Due to the favorable response of the MALT lymphoma to local treatment and the absence of metastasis in other organs, no further treatment was administered for the MALT lymphoma following the surgery. Currently, the patient exhibits no signs of tumor recurrence based on ultrasound and laboratory evaluations. We also provide an overview of the clinical findings on PTC and MALT lymphoma patients already reported and discuss the possible treatment strategy

Study on the Nonsingular Problem of Fractional-Order Terminal Sliding Mode Control

An improved type of control strategy combining the fractional calculus with nonsingular terminal sliding mode control named non-singular fractional terminal sliding mode control (NFOTSM) is proposed for the nonlinear tire-road friction control system of vehicle in this paper. A fractional-order switching manifold is proposed, and the corresponding control law is formulated based on the Lyapunov stability theory to guarantee the sliding condition. The proposed controller ensures the finite time stability of the closed-loop system. Then, a terminal attractor is introduced to solve the singularity problem of fractional terminal sliding mode control (FOTSM). Finally, the performance of the NFOTSM is fully investigated compared with other related algorithms to find the effectiveness for the tire-road friction system. The results show that the NFOTSM has better performance than other related algorithms.</jats:p

FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering

Knowledge base question answering (KBQA) is a critical yet challenging task due to the vast number of entities within knowledge bases and the diversity of natural language questions posed by users. Unfortunately, the performance of most KBQA models tends to decline significantly in real-world scenarios where high-quality annotated data is insufficient. To mitigate the burden associated with manual annotation, we introduce FlexKBQA by utilizing Large Language Models (LLMs) as program translators for addressing the challenges inherent in the few-shot KBQA task. Specifically, FlexKBQA leverages automated algorithms to sample diverse programs, such as SPARQL queries, from the knowledge base, which are subsequently converted into natural language questions via LLMs. This synthetic dataset facilitates training a specialized lightweight model for the KB. Additionally, to reduce the barriers of distribution shift between synthetic data and real user questions, FlexKBQA introduces an executionguided self-training method to iterative leverage unlabeled user questions. Furthermore, we explore harnessing the inherent reasoning capability of LLMs to enhance the entire framework. Consequently, FlexKBQA delivers substantial flexibility, encompassing data annotation, deployment, and being domain agnostic. Through extensive experiments on GrailQA, WebQSP, and KQA Pro, we observe that under the few-shot even the more challenging zero-shot scenarios, FlexKBQA achieves impressive results with a few annotations, surpassing all previous baselines and even approaching the performance of supervised models, achieving a remarkable 93% performance relative to the fully-supervised models. We posit that FlexKBQA represents a significant advancement towards exploring better integration of large and lightweight models. The code is open-sourced.Comment: Accepted as AAAI-24 Oral paper; Knowledge Base Question Answering; Large Language Model; Data Generation; Few-Shot & Zero-Sho