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A suitable thermal environment is important for the economy, society and public health in urban areas. However, the understanding of the relationship between the urban heat island (UHI) effect and background temperature (T-UHI) is very limited. In this study, the UHI effect induced by the urbanization of the megacity Beijing was investigated using the weather research and forecasting model. Urban expansion and heatwaves both considerably enhanced the UHI effect over urban areas in summer. The strengthened UHI effect during the heatwave period can be clearly explained by the positive sensitivity of T-UHI. The urban expansion increased the sensitivity of T-UHI from 0.0207 °C °C−1 in 2000 to 0.0569 °C °C−1 in 2010 in the daytime and from 0.0715 °C °C−1 in 2000 to 0.0995 °C °C−1 in 2010 at nighttime, thus resulting in a much stronger UHI effect mainly by increasing the difference between the latent heat flux and sensible heat flux. This enhanced sensitivity may exacerbate the urban heat stress in the situation of further urban expansion and background climate warming. Our results suggest that the sensitivity of T-UHI is a meaningful indicator to assess the urban thermal environment change and support the designing of heat mitigation strategies in urban planning.

The existence of breast cancer stem cells (BCSCs) is a major reason underlying cancer metastasis and recurrence after chemotherapy and radiotherapy. Targeting BCSCs may ameliorate breast cancer relapse and therapy resistance. Here we report that expression of the pseudokinase Tribble 3 (TRIB3) positively associates with breast cancer stemness and progression. Elevated TRIB3 expression supports BCSCs by interacting with AKT to interfere with the FOXO1-AKT interaction and suppress FOXO1 phosphorylation, ubiquitination, and degradation by E3 ligases SKP2 and NEDD4L. The accumulated FOXO1 promotes transcriptional expression of SOX2, a transcriptional factor for cancer stemness, which in turn, activates FOXO1 transcription and forms a positive regulatory loop. Disturbing the TRIB3-AKT interaction suppresses BCSCs by accelerating FOXO1 degradation and reducing SOX2 expression in mouse models of breast cancer. Our study provides insights into breast cancer development and confers a potential therapeutic strategy against TRIB3-overexpressed breast cancer. Cancer stem cells contribute to breast cancer metastasis and recurrence. Here the authors show that TRIB3 enhances breast cancer stemness through interaction with AKT to promote FOXO1 stability, which then increases SOX2 activity.

The aim of this study was to observe the activation characteristics of calf muscles in healthy adults during plantar flexion by a new nonlinear electromyography index. The linear indices of sEMG, including the root mean square (RMS), median frequency (MF), and nonlinear index, degree centrality (DC) of the calf muscles of ten healthy male participants, were tested in the resting state and plantar flexion position to analyse their characteristics. The RMS was not normally distributed, and the MF and DC values were normally distributed. Compared with those in the resting state, the RMS, MF and DC values of all the tested muscles were significantly greater (P < 0.05) during plantar flexion. Among all the muscles, the peroneus longus (PL) changed the most. The RMS increased from 3.14 ± 1.61 µV to 49.31 ± 21.81 µV, the MF increased from 134.07 ± 30.86 Hz to 203.55 ± 28.36 Hz, and the DC changed from 2.24 ± 0.38 to 3.33 ± 0.41. Two linear indices and a nonlinear index of the PL were significantly elevated during prone plantar flexion. We speculate that the nonlinear index, DC can reflect the degree of single muscle synergistic involvement, and may become a new indicator for assessing the state of single muscle controlled by nervous system in a movement involving multiple muscles.

G9a, a H3K9 methyltransferase, shows elevated expression in many types of human cancers, particularly breast cancer. However, the tumorigenic mechanism of G9a is still far from clear. Here we report that G9a exerts its oncogenic function in breast cancer by repressing hephaestin and destruction cellular iron homeostasis. In the case of pharmacological inhibition or short hairpin RNA interference-mediated suppression of G9a, the expression and activity of hephaestin increases, leading to the observed decrease of intracellular labile iron content and the disturbance of breast cancer cell growth in vitro and in vivo. We also provide evidence that G9a interacts with HDAC1 and YY1 to form a multi-molecular complex that contributes to hephaestin silencing. Furthermore, high G9a expression and low hephaestin expression correlate with poor survival of breast cancer are investigated. All these suggest a G9a-dependent epigenetic program in the control of iron homeostasis and tumor growth in breast cancer. G9a is a histone methyltransferase highly expressed in several cancers including breast cancer. Here the authors propose a mechanism through which G9a promotes breast cancer by regulating iron metabolism through the repression of ferroxidase hephaestin.

In radiomics studies, researchers usually need to develop a supervised machine learning model to map image features onto the clinical conclusion. A classical machine learning pipeline consists of several steps, including normalization, feature selection, and classification. It is often tedious to find an optimal pipeline with appropriate combinations. We designed an open-source software package named FeAture Explorer (FAE). It was programmed with Python and used NumPy, pandas, and scikit-learning modules. FAE can be used to extract image features, preprocess the feature matrix, develop different models automatically, and evaluate them with common clinical statistics. FAE features a user-friendly graphical user interface that can be used by radiologists and researchers to build many different pipelines, and to compare their results visually. To prove the effectiveness of FAE, we developed a candidate model to classify the clinical-significant prostate cancer (CS PCa) and non-CS PCa using the PROSTATEx dataset. We used FAE to try out different combinations of feature selectors and classifiers, compare the area under the receiver operating characteristic curve of different models on the validation dataset, and evaluate the model using independent test data. The final model with the analysis of variance as the feature selector and linear discriminate analysis as the classifier was selected and evaluated conveniently by FAE. The area under the receiver operating characteristic curve on the training, validation, and test dataset achieved results of 0.838, 0.814, and 0.824, respectively. FAE allows researchers to build radiomics models and evaluate them using an independent testing dataset. It also provides easy model comparison and result visualization. We believe FAE can be a convenient tool for radiomics studies and other medical studies involving supervised machine learning.

Conveyor belt deviation is a commmon and severe type of fault in belt conveyor systems, often resulting in significant economic losses and potential environment pollution. Traditional detection methods have obvious limitations in fault localization precision and analysis accuracy, unable to meet the demands of efficient and real-time fault detection in complex industrial scenarios. To address these issues, this paper proposes an improved detection algorithm based on YOLOv8, aiming to achieve efficient and accurate detection during the operation of the belt. Firstly, an Enhanced Squeeze-and-Excitation (ESE) module is incorporated into C2f to boost feature extraction for rollers and belts. Secondly, the construction of the BiFPN_DoubleAttention module in the neck network enhances bidirectional feature fusion and attention mechanism, thereby improving multi-scale object localization accuracy under complex environments. Then, a Multi-Head Self-Attention (MHSA) mechanism is introduced in the head network, better capturing positional features of small roller targets and belt areas in various environments, thus enhancing detection performance. Finally, extensive experiments are conducted on a self-built dataset, achieving an accuracy of 98.1%, mAP0.5 of 99.0%, and a detection speed of 46 frames per second (FPS). This method effectively handles variations and disturbances in the conveyor belt transportation environment, meeting real-time diagnostic needs for belt misalignment in the industry.

A multifunctional nanoplatform with core–shell structure was constructed in one-pot for the synergistic photothermal, photodynamic, and chemotherapy against breast cancer. In the presence of gambogic acid (GA) as the heat-shock protein 90 (HSP90) inhibitor and the gold nanostars (AuNS) as the photothermal reagent, the assembly of Zr 4+ with tetrakis (4-carboxyphenyl) porphyrin (TCPP) gave rise to the nanocomposite AuNS@ZrTCPP-GA ( AZG ), which in turn, further coated with PEGylated liposome (LP) to enhance the stability and biocompatibility, and consequently the antitumor effect of the particle. Upon cellular uptake, the nanoscale metal − organic framework (NMOF) of ZrTCPP in the resulted AuNS@ZrTCPP-GA@LP ( AZGL ) could be slowly degraded in the weak acidic tumor microenvironment to release AuNS, Zr 4+ , TCPP, and GA to exert the synergistic treatment of tumors via the combination of AuNS-mediated mild photothermal therapy (PTT) and TCPP-mediated photodynamic therapy (PDT). The introduction of GA serves to reduce the thermal resistance of the cell to re-sensitize PTT and the constructed nanoplatform demonstrated remarkable anti-tumor activity in vitro and in vivo. Our work highlights a facile strategy to prepare a pH-dissociable nanoplatform for the effective synergistic treatment of breast cancer. Graphical Abstract

Removal of quartz from iron ore was accomplished industrially via an anionic reverse flotation technique. However, in that kind of flotation, the interaction of the flotation reagents with the components of the feed sample makes the flotation a complicated system. Thus, the selection and optimization of regent dosages at various temperatures were performed using a uniform experimental design to estimate the optimum separation efficiency. Besides, the produced data as well as the reagent system were mathematically modeled at different flotation temperatures, and the graphical user interface GUI of MATLAB was conducted. The advantage of this procedure is that the user interface displayed in real-time can be conducted by adjusting the temperature at different values to automatically control the reagent system, besides predicting the concentrate yield, total iron grade, and total iron recovery.

The occurrence of osteoarthritis (OA) is highly correlated with the reduction of joint lubrication performance, in which persistent excessive inflammation and irreversible destruction of cartilage dominate the mechanism. The inadequate response to monotherapy methods, suboptimal efficacy caused by undesirable bioavailability, short retention, and lack of stimulus-responsiveness, are few unresolved issues. Herein, we report a pH-responsive metal-organic framework (MOF), namely, MIL-101-NH 2 , for the co-delivery of anti-inflammatory drug curcumin (CCM) and small interfering RNA (siRNA) for hypoxia inducible factor (HIF-2α). CCM and siRNA were loaded via encapsulation and surface coordination ability of MIL-101-NH 2 . Our vitro tests showed that MIL-101-NH 2 protected siRNA from nuclease degradation by lysosomal escape. The pH-responsive MIL-101-NH 2 gradually collapsed in an acidic OA microenvironment to release the CCM payloads to down-regulate the level of pro-inflammatory cytokines, and to release the siRNA payloads to cleave the target HIF-2α mRNA for gene-silencing therapy, ultimately exhibiting the synergetic therapeutic efficacy by silencing HIF-2α genes accompanied by inhibiting the inflammation response and cartilage degeneration of OA. The hybrid material reported herein exhibited promising potential performance for OA therapy as supported by both in vitro and in vivo studies and may offer an efficacious therapeutic strategy for OA utilizing MOFs as host materials.

Ongoing climate change is modifying snow dynamics, further altering streamflow (Q) in cold regions. Despite extensive research over the past decades, the impact of changes in snow on mean annual Q remains debated, and the underlying mechanisms driving these responses are still unclear. In this study, we employ the Budyko framework to establish multivariate relationships between a Budyko model parameter and several variables, including snowfall fraction (fs), across 931 carefully selected snow‐influenced catchments in the Northern Hemisphere. Our results show that the average elasticity of Q to fs across all catchments is 0.13. However, mean annual Q responses vary among catchments, with 78% of catchments experiencing decreased Q and others exhibiting increased Q with declining fs. These variations are manifested in decreased warm‐season Q and increased cold‐season Q, respectively. Additionally, attribution analysis of Q change highlights a critical role of fs changes as a second‐order control on Q after precipitation. Examining possible mechanisms behind the varying Q responses reveal that the influence of fs on snowmelt intensity and snow season available energy is more pronounced in catchments exhibiting positive Q feedback to fs. In contrast, its impact on rainfall intensity and the asynchrony between available energy and liquid water input is greater in catchments displaying negative Q feedback to fs. Our findings enhance the understanding of Q responses to changing fs and provide valuable insights for water resource management in snow‐influenced regions in a warming climate. Key Points Changes in snowfall fraction are the second most significant factor affecting long‐term streamflow, after changes in precipitation Catchments with positive streamflow responses show more pronounced snowmelt intensity and energy availability changes under varying snowfall In catchments with negative streamflow responses, rainfall intensity and energy‐liquid water asynchrony are more significant factors