Meta-analysis of effectiveness of traditional Chinese medicine or its combination with Western medicine in the treatment of triple negative breast cancer

Purpose: To assess the efficacy and side effects of Traditional Chinese Medicine (TCM) in the management of triple negative breast cancer (TNBC). Methods: Full text data on randomized controlled trial (RCT) of TNBC treated with TCM or its combination with Western Medicine (WM) were retrieved from the Chinese biomedical literature database, Chinese periodicals, Chinese Science-Technology periodicals and VP and PubMed. The qualities of the RCTs were evaluated. Revman 5.3 was used to conduct the meta-analysis. Results: A total of 16 RCTs involving 1186 patients were included. Analysis of these RCTs showed significant differences in total effectiveness between WM and TCM or combination of TCM with WM {(OR = 2.63, 95 % CI = 1.37, 5.03), test of the combined effect (Z = 2.91, p ˂ 0.005)}. Conclusion: The results show that TCM is effective in the treatment TNB

Spatial variation of energy efficiency based on a Super-Slack-Based Measure: Evidence from 104 resource-based cities

Energy efficiency is tied to energy activities and environmental effects and serves as a useful tool for sustainability analysis. Few insights have been acquired for sustainability development from resource-based cities in developed or developing countries. A Super-Slack-Based Measure (Super-SBM) with undesirable outputs is established to account for the total-factor energy efficiency from an energy-economy-environment perspective. Using China as a case study, the spatial variation in energy efficiency from 104 resource-based cities is analysed, furthermore, the results are compared with a scenario that does not consider environmental constraints. Finally, resource-based cities are classified into three categories through K-means clustering technology: high-efficiency region, medium-efficiency region and low-efficiency region. The investigation results show the following: (1) Efficiency disparities exist in resource-based cities under different scenarios, as a whole, the energy efficiency in the scenario two considering by-products of energy activities is obviously lower, which can more truly represent the sustainability of resource-based cities. (2) Most resource-based cities are in low-efficiency zones with substantial room for improvement. Spatial agglomeration effect or spatial spillover effect appears in a few cities. (3) Urban development in developing countries may follow the full life cycle process of local resources. A total of 262 resource-based cities could be roughly categorized into four types. The energy efficiency of growing type is the highest, followed by grow-up type, recessionary type, and regenerative type. (4) The ordering of efficiency in resource-based city is as follows: oil and gas-based > multiple minerals-based > non-metallic-based > nonferrous metal-based > coal-based > forestry-based > ferrous metal-based. The discussion offered in this study for various types of resource-based cities could provide a reference for other cities or developing countries which are in similar industrialization phases and hope for sustainable development

Multi-Objective Personalized Product Retrieval in Taobao Search

In large-scale e-commerce platforms like Taobao, it is a big challenge to retrieve products that satisfy users from billions of candidates. This has been a common concern of academia and industry. Recently, plenty of works in this domain have achieved significant improvements by enhancing embedding-based retrieval (EBR) methods, including the Multi-Grained Deep Semantic Product Retrieval (MGDSPR) model [16] in Taobao search engine. However, we find that MGDSPR still has problems of poor relevance and weak personalization compared to other retrieval methods in our online system, such as lexical matching and collaborative filtering. These problems promote us to further strengthen the capabilities of our EBR model in both relevance estimation and personalized retrieval. In this paper, we propose a novel Multi-Objective Personalized Product Retrieval (MOPPR) model with four hierarchical optimization objectives: relevance, exposure, click and purchase. We construct entire-space multi-positive samples to train MOPPR, rather than the single-positive samples for existing EBR models.We adopt a modified softmax loss for optimizing multiple objectives. Results of extensive offline and online experiments show that MOPPR outperforms the baseline MGDSPR on evaluation metrics of relevance estimation and personalized retrieval. MOPPR achieves 0.96% transaction and 1.29% GMV improvements in a 28-day online A/B test. Since the Double-11 shopping festival of 2021, MOPPR has been fully deployed in mobile Taobao search, replacing the previous MGDSPR. Finally, we discuss several advanced topics of our deeper explorations on multi-objective retrieval and ranking to contribute to the community.Comment: 9 pages, 4 figures, submitted to the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Minin

Prediction of wheat SPAD using integrated multispectral and support vector machines

Rapidly obtaining the chlorophyll content of crop leaves is of great significance for timely diagnosis of crop health and effective field management. Multispectral imagery obtained from unmanned aerial vehicles (UAV) is being used to remotely sense the SPAD (Soil and Plant Analyzer Development) values of wheat crops. However, existing research has not yet fully considered the impact of different growth stages and crop populations on the accuracy of SPAD estimation. In this study, 300 materials from winter wheat natural populations in Xinjiang, collected between 2020 to 2022, were analyzed. UAV multispectral images were obtained in the experimental area, and vegetation indices were extracted to analyze the correlation between the selected vegetation indices and SPAD values. The input variables for the model were screened, and a support vector machine (SVM) model was constructed to estimate SPAD values during the heading, flowering, and filling stages under different water stresses. The aim was to provide a method for the rapid acquisition of winter wheat SPAD values. The results showed that the SPAD values under normal irrigation were higher than those under water restriction. Multiple vegetation indices were significantly correlated with SPAD values. In the prediction model construction of SPAD, the different models had high estimation accuracy under both normal irrigation and water limitation treatments, with correlation coefficients of predicted and measured values under normal irrigation in different environments the value of r from 0.59 to 0.81 and RMSE from 2.15 to 11.64, compared to RE from 0.10% to 1.00%; and under drought stress in different environments, correlation coefficients of predicted and measured values of r was 0.69–0.79, RMSE was 2.30–12.94, and RE was 0.10%–1.30%. This study demonstrated that the optimal combination of feature selection methods and machine learning algorithms can lead to a more accurate estimation of winter wheat SPAD values. In summary, the SVM model based on UAV multispectral images can rapidly and accurately estimate winter wheat SPAD value

Exploration of the hypoglycemic mechanism of Fuzhuan brick tea based on integrating global metabolomics and network pharmacology analysis

Introduction: Fuzhuan brick tea (FBT) is a worldwide popular beverage which has the appreciable potential in regulating glycometabolism. However, the reports on the hypoglycemic mechanism of FBT remain limited.Methods: In this study, the hypoglycemic effect of FBT was evaluated in a pharmacological experiment based on Kunming mice. Global metabolomics and network pharmacology were combined to discover the potential target metabolites and genes. In addition, the real-time quantitative polymerase chain reaction (RT-qPCR) analysis was performed for verification.Results: Seven potential target metabolites and six potential target genes were screened using the integrated approach. After RT-qPCR analysis, it was found that the mRNA expression of VEGFA, KDR, MAPK14, and PPARA showed significant differences between normal and diabetes mellitus mice, with a retracement after FBT treatment.Conclusion: These results indicated that the hypoglycemic effect of FBT was associated with its anti-inflammatory activities and regulation of lipid metabolism disorders. The exploration of the hypoglycemic mechanism of FBT would be meaningful for its further application and development

Two-stage deep neural network for diagnosing fungal keratitis via in vivo confocal microscopy images

Timely and effective diagnosis of fungal keratitis (FK) is necessary for suitable treatment and avoiding irreversible vision loss for patients. In vivo confocal microscopy (IVCM) has been widely adopted to guide the FK diagnosis. We present a deep learning framework for diagnosing fungal keratitis using IVCM images to assist ophthalmologists. Inspired by the real diagnostic process, our method employs a two-stage deep architecture for diagnostic predictions based on both image-level and sequence-level information. To the best of our knowledge, we collected the largest dataset with 96,632 IVCM images in total with expert labeling to train and evaluate our method. The specificity and sensitivity of our method in diagnosing FK on the unseen test set achieved 96.65% and 97.57%, comparable or better than experienced ophthalmologists. The network can provide image-level, sequence-level and patient-level diagnostic suggestions to physicians. The results show great promise for assisting ophthalmologists in FK diagnosis

Consensus interpretation of the p.Met34Thr and p.Val37Ile variants in GJB2 by the ClinGen Hearing Loss Expert Panel

Purpose: Pathogenic variants in GJB2 are the most common cause of autosomal recessive sensorineural hearing loss. The classification of c.101T>C/p.Met34Thr and c.109G>A/p.Val37Ile in GJB2 are controversial. Therefore, an expert consensus is required for the interpretation of these two variants. Methods: The ClinGen Hearing Loss Expert Panel collected published data and shared unpublished information from contributing laboratories and clinics regarding the two variants. Functional, computational, allelic, and segregation data were also obtained. Case-control statistical analyses were performed. Results: The panel reviewed the synthesized information, and classified the p.Met34Thr and p.Val37Ile variants utilizing professional variant interpretation guidelines and professional judgment. We found that p.Met34Thr and p.Val37Ile are significantly overrepresented in hearing loss patients, compared with population controls. Individuals homozygous or compound heterozygous for p.Met34Thr or p.Val37Ile typically manifest mild to moderate hearing loss. Several other types of evidence also support pathogenic roles for these two variants. Conclusion: Resolving controversies in variant classification requires coordinated effort among a panel of international multi-institutional experts to share data, standardize classification guidelines, review evidence, and reach a consensus. We concluded that p.Met34Thr and p.Val37Ile variants in GJB2 are pathogenic for autosomal recessive nonsyndromic hearing loss with variable expressivity and incomplete penetrance

Detecting Neutrinos from Supernova Bursts in PandaX-4T

Neutrinos from core-collapse supernovae are essential for the understanding of neutrino physics and stellar evolution. The dual-phase xenon dark matter detectors can provide a way to track explosions of galactic supernovae by detecting neutrinos through coherent elastic neutrino-nucleus scatterings. In this study, a variation of progenitor masses as well as explosion models are assumed to predict the neutrino fluxes and spectra, which result in the number of expected neutrino events ranging from 6.6 to 13.7 at a distance of 10 kpc over a 10-second duration with negligible backgrounds at PandaX-4T. Two specialized triggering alarms for monitoring supernova burst neutrinos are built. The efficiency of detecting supernova explosions at various distances in the Milky Way is estimated. These alarms will be implemented in the real-time supernova monitoring system at PandaX-4T in the near future, providing the astronomical communities with supernova early warnings.Comment: 9 pages,6 figure

Search for light dark matter from atmosphere in PandaX-4T

We report a search for light dark matter produced through the cascading decay of $\eta$ mesons, which are created as a result of inelastic collisions between cosmic rays and Earth's atmosphere. We introduce a new and general framework, publicly accessible, designed to address boosted dark matter specifically, with which a full and dedicated simulation including both elastic and quasi-elastic processes of Earth attenuation effect on the dark matter particles arriving at the detector is performed. In the PandaX-4T commissioning data of 0.63 tonne$\cdot$year exposure, no significant excess over background is observed. The first constraints on the interaction between light dark matter generated in the atmosphere and nucleus through a light scalar mediator are obtained. The lowest excluded cross-section is set at $5.9 \times 10^{-37}{\rm cm^2}$ for dark matter mass of $0.1$ MeV$/c^2$ and mediator mass of 300 MeV$/c^2$. The lowest upper limit of $\eta$ to dark matter decay branching ratio is $1.6 \times 10^{-7}$