Large-Scale Multi-Label Learning with Incomplete Label Assignments

Multi-label learning deals with the classification problems where each instance can be assigned with multiple labels simultaneously. Conventional multi-label learning approaches mainly focus on exploiting label correlations. It is usually assumed, explicitly or implicitly, that the label sets for training instances are fully labeled without any missing labels. However, in many real-world multi-label datasets, the label assignments for training instances can be incomplete. Some ground-truth labels can be missed by the labeler from the label set. This problem is especially typical when the number instances is very large, and the labeling cost is very high, which makes it almost impossible to get a fully labeled training set. In this paper, we study the problem of large-scale multi-label learning with incomplete label assignments. We propose an approach, called MPU, based upon positive and unlabeled stochastic gradient descent and stacked models. Unlike prior works, our method can effectively and efficiently consider missing labels and label correlations simultaneously, and is very scalable, that has linear time complexities over the size of the data. Extensive experiments on two real-world multi-label datasets show that our MPU model consistently outperform other commonly-used baselines

Cochlear homeostasis and its role in genetic deafness

AbstractEach component of the human ear performs a specific function in hearing. The actual process of sound transduction takes place in the auditory portion of the inner ear, the fluid-filled cochlea. In the cochlea, the sensitivity and efficiency of sensory apparatus to convert mechanical energy into neural activity, largely depends on the fluidic and ionic environment. In the lateral wall of cochlea, the secretory epithelium stria vascularis plays an important role in the maintenance of fluidic and ionic homeostasis. A variety of gene mutations disturbs the cochlear homeostasis and subsequently leads to hearing impairment. The review covers several aspects of cochlear homeostasis, from cochlear fluid and the functional role of stria vascularis, cochlear K+recycling and its molecular substrates to genetic deafness with abnormal cochlear homeostasis

T-Nb2O5 nanoparticle enabled pseudocapacitance with a fast Li-ion intercalation

Orthorhombic Nb2O5 (T-Nb2O5) nanocrystallites are successfully fabricated through evaporation induced self-assembly (EISA) method guided by a commericalised triblock copolymer – Pluronic F127. We demonstrate a morphology transition of T-Nb2O5 from continuous porous nanofilm to monodisperse nanoparticle by changing the content of Pluronic F127. The electrochemical results show that the optimized monodisperse of Nb-2 with particle size of 20 nm achieve premier Li-ion intercalation kinetics and higher rate capability than mesoporous T-Nb2O5 nanofilms. Nb-2 present an initial intercalation capacity of 528 and 451 C g-1 at current densities of 0.5 and 5 A g-1 and performed stable capacity of 499 C g-1 after 300 charge/discharge cycles and 380 C g-1 after 1000 cycles, respectively. We would expect this copolymer guided monodispersing of T-Nb2O5 nanoparticles with high Li+ intercalation performance to open up new window for novel EES technologies

Improved efficacy and reduced toxicity of doxorubicin encapsulated in sulfatide-containing nanoliposome in a glioma model

As a glycosphingolipid that can bind to several extracellular matrix proteins, sulfatide has the potential to become an effective targeting agent for tumors overexpressing tenasin-C in their microenvironment. To overcome the dose-limiting toxicity of doxorubicin (DOX), a sulfatide-containing nanoliposome (SCN) encapsulation approach was employed to improve treatment efficacy and reduce side effects of free DOX. This study analysed in vitro characteristics of sulfatidecontaining nanoliposomal DOX (SCN-DOX) and assessed its cytotoxicity in vitro, as well as biodistribution, therapeutic efficacy, and systemic toxicity in a human glioblastoma U-118MG xenograft model. SCN-DOX was shown to achieve highest drug to lipid ratio (0.5:1) and a remarkable in vitro stability. Moreover, DOX encapsulated in SCN was shown to be delivered into the nuclei and displayed prolonged retention over free DOX in U-118MG cells. This simple two-lipid SCN- DOX nanodrug has favourable pharmacokinetic attributes in terms of prolonged circulation time, reduced volume of distribution and enhanced bioavailability in healthy rats. As a result of the improved biodistribution, an enhanced treatment efficacy of SCNDOX was found in glioma-bearing mice compared to the free drug. Finally, a reduction in the accumulation of DOX in the drug’s principal toxicity organs achieved by SCN-DOX led to the diminished systemic toxicity as evident from the plasma biochemical analyses. Thus, SCN has the potential to be an effective and safer nano-carrier for targeted delivery of therapeutic agents to tumors with elevated expression of tenascin-C in their microenvironment

Four Phragmalin Orthoesters from the Chinese Mangrove Xylocarpus granatum

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Systematic review and meta-analysis of Chinese herbal formula Tongxie Yaofang for diarrhea-predominant irritable bowel syndrome: Evidence for clinical practice and future trials

Introduction: Diarrhea-predominant irritable bowel syndrome (IBS-D) significantly decreases the quality of life of patients and their families, and affects patients’ mental health. No specific western medications are available. Ancient classical Chinese medical texts have recognized Tongxie Yaofang (TXYF) as a therapy for diarrhea which is widely used in clinical practice. Standard TXYF prescription (S-TXYF) is composed of four herbal medicines: Atractylodes macrocephala Koidz. [Asteraceae; Rhizoma Atractylodis Macrocephalae.], Paeonia lactiflora Pall. [Ranunculaceae; Paeoniae Radix Alba], Citrus × aurantium L. [Rutaceae; Citri Reticulatae Pericarpium] and Saposhnikovia divaricata (Turcz. ex Ledeb.) Schischk. [Umbelliferae; Saposhnikoviae Radix]. This review aimed to evaluate the therapeutic effects and safety of S-TXYF for IBS-D. Methods: Eight English and Chinese electronic databases were searched from their inception to 25 December 2021 for randomized controlled trials (RCTs) comparing S-TXYF with placebo, western medications or no treatment for IBS-D. The primary outcome was the global improvement of IBS-D symptoms. Data were analyzed using Cochrane’s Revman 5.4 software. Evidence certainty was assessed using the online GRADEpro tool for the primary outcome. Results: Eleven RCTs involving 985 adults with IBS-D were included. For global improvement of symptoms, S-TXYF was superior to western medication and placebo (moderate evidence by GRADE). Regarding the improvement of stool consistency, stool frequency and abdominal pain, S-TXYF was significantly effective than placebo. In addition, S-TXYF was superior to western medication on improving the quality of life and relieving anxiety. Six trials reported adverse events: five of them reported (non-serious) adverse events occurred in both groups, and one trial reported that 3 cases with adverse events (constipation, elevation in liver-enzyme, nausea) occurred in S-TXYF group and 3 cases with adverse events (abdominal distension, nausea) occurred in placebo group. Conclusion: Although current results showed that S-TXYF may have potential to treat IBS-D and its use appears to be safe, no a clear and confirmed conclusion can be drawn from our review as the overall inadequate design of the included trials reviewed. So more rigorous trials are warranted to establish confirmed evidence on its benefits and safety

JSSDR: Joint-Sparse Sensory Data Recovery in Wireless Sensor Networks

Abstract-Data loss is ubiquitous in wireless sensor networks (WSNs) mainly due to the unreliable wireless transmission, which results in incomplete sensory data sets. However, the completeness of a data set directly determines its availability and usefulness. Thus, sensory data recovery is an indispensable operation against the data loss problem. However, existing solutions cannot achieve satisfactory accuracy due to special loss patterns and high loss rates in WSNs. In this work, we propose a novel sensory data recovery algorithm which exploits the spatial and temporal jointsparse feature. Firstly, by mining two real datasets, namely the Intel Indoor project and the GreenOrbs project, we find that: (1) for one attribute, sensory readings at nearby nodes exhibit inter-node correlation; (2) for two attributes, sensory readings at the same node exhibit inter-attribute correlation; (3) these inter-node and inter-attribute correlations can be modeled as the spatial and temporal joint-sparse features, respectively. Secondly, motivated by these observations, we propose two JointSparse Sensory Data Recovery (JSSDR) algorithms to promote the recovery accuracy. Finally, real data-based simulations show that JSSDR outperforms existing solutions. Typically, when the loss rate is less than 65%, JSSDR can estimate missing values with less than 10% error. And when the loss rate reaches as high as 80%, the missing values can be estimated by JSSDR with less than 20% error