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Electrical signaling plays a crucial role in the cellular response to tissue injury in wound healing and an external electric field (EF) may expedite the healing process. Here, we have developed a standalone, wearable, and programmable electronic device to administer a well-controlled exogenous EF, aiming to accelerate wound healing in an in vivo mouse model to provide pre-clinical evidence. We monitored the healing process by assessing the re-epithelization rate and the ratio of M1/M2 macrophage phenotypes through histology staining. Following three days of treatment, the M1/M2 macrophage ratio decreased by 30.6% and the re-epithelization in the EF-treated wounds trended towards a non-statically significant 24.2% increase compared to the control. These findings provide point towards the effectiveness of the device in shortening the inflammatory phase by promoting reparative macrophages over inflammatory macrophages, and in speeding up re-epithelialization. Our wearable device supports the rationale for the application of programmed EFs for wound management in vivo and provides an exciting basis for further development of our technology based on the modulation of macrophages and inflammation to better wound healing.

Macrophages can exhibit pro-inflammatory or pro-reparatory functions, contingent upon their specific activation state. This dynamic behavior empowers macrophages to engage in immune reactions and contribute to tissue homeostasis. Understanding the intricate interplay between macrophage motility and activation status provides valuable insights into the complex mechanisms that govern their diverse functions. In a recent study, we developed a classification method based on morphology, which demonstrated that movement characteristics, including speed and displacement, can serve as distinguishing factors for macrophage subtypes. In this study, we develop a deep learning model to explore the potential of classifying macrophage subtypes based solely on raw trajectory patterns. The classification model relies on the time series of x-y coordinates, as well as the distance traveled and net displacement. We begin by investigating the migratory patterns of macrophages to gain a deeper understanding of their behavior. Although this analysis does not directly inform the deep learning model, it serves to highlight the intricate and distinct dynamics exhibited by different macrophage subtypes, which cannot be easily captured by a finite set of motility metrics. Our study uses cell trajectories to classify three macrophage subtypes: M0, M1, and M2. This advancement holds promising implications for the future, as it suggests the possibility of identifying macrophage subtypes without relying on shape analysis. Consequently, it could potentially eliminate the necessity for high-quality imaging techniques and provide more robust methods for analyzing inherently blurry images.

The composite material-like extracellular matrix (ECM) in the sinoatrial node (SAN) supports the native pacemaking cardiomyocytes (PCMs). To test the roles of SAN ECM in the PCM phenotype and function, we engineered reconstructed-SAN heart tissues (rSANHTs) by recellularizing porcine SAN ECMs with hiPSC-derived PCMs. The hiPSC-PCMs in rSANHTs self-organized into clusters resembling the native SAN and displayed higher expression of pacemaker-specific genes and a faster automaticity compared with PCMs in reconstructed-left ventricular heart tissues (rLVHTs). To test the protective nature of SAN ECMs under strain, rSANHTs and rLVHTs were transplanted onto the murine thoracic diaphragm to undergo constant cyclic strain. All strained-rSANHTs preserved automaticity, whereas 66% of strained-rLVHTs lost their automaticity. In contrast to the strained-rLVHTs, PCMs in strained-rSANHTs maintained high expression of key pacemaker genes (HCN4, TBX3, and TBX18). These findings highlight the promotive and protective roles of the composite SAN ECM and provide valuable insights for pacemaking tissue engineering.

For the problem of low accuracy and applicability of the model prediction in the study of mine water inflow, a method of mine water inflow prediction based on bidirectional short and long memory network(BiLSTM) and deep residual network (DRN) is proposed. First, the data of mine water inflow is processed by wavelet decomposition and normalization to obtain trend item data and detail item data. Secondly, the trend item data was predicted by DRN network method, and the detail item data was predicted by BiLSTM network method. Finally, the two parts of the prediction results will be combined to get the mine water inflow prediction results. The results show that the DRN-BiLSTM model has higher prediction accuracy than a single model, indicating that the model has better generalization.

Highlights In situ Raman spectroscopy study of the cation regulation for interfacial water on Au@Pd core–shell nanoparticle surface during hydrogen evolution reaction process. Direct spectral evidence reveals new strategies to optimize the structure of interfacial water by the adjusting of radius and valence of the cation in the electrolyte. The optimized structure of interfacial water will improve the charge transfer efficiency between the water and electrode increasing the performance of the hydrogen evolution reaction.

Macrophages can exhibit pro-inflammatory or pro-reparatory functions, contingent upon their specific activation state. This dynamic behavior empowers macrophages to engage in immune reactions and contribute to tissue homeostasis. Understanding the intricate interplay between macrophage motility and activation status provides valuable insights into the complex mechanisms that govern their diverse functions. In a recent study, we developed a classification method based on morphology, which demonstrated that movement characteristics, including speed and displacement, can serve as distinguishing factors for macrophage subtypes. In this study, we develop a deep learning model to explore the potential of classifying macrophage subtypes based solely on raw trajectory patterns. The classification model relies on the time series of x-y coordinates, as well as the distance traveled and net displacement. We begin by investigating the migratory patterns of macrophages to gain a deeper understanding of their behavior. Although this analysis does not directly inform the deep learning model, it serves to highlight the intricate and distinct dynamics exhibited by different macrophage subtypes, which cannot be easily captured by a finite set of motility metrics. Our study uses cell trajectories to classify three macrophage subtypes: M0, M1, and M2. This advancement holds promising implications for the future, as it suggests the possibility of identifying macrophage subtypes without relying on shape analysis. Consequently, it could potentially eliminate the necessity for high-quality imaging techniques and provide more robust methods for analyzing inherently blurry images.

Many cell types migrate in response to naturally generated electric fields. Furthermore, it has been suggested that the external application of an electric field may be used to intervene in and optimize natural processes such as wound healing. Precise cell guidance suitable for such optimization may rely on predictive models of cell migration, which do not generalize. Here, we present a machine learning model that can forecast directedness of cell migration given a timeseries of previous directedness and electric field values. This model is trained using time series galvanotaxis data of mammalian cranial neural crest cells obtained through time-lapse microscopy of cells cultured at 37 °C in a galvanotaxis chamber at ambient pressure. Next, we show that our modeling approach can be used for a variety of cell types and experimental conditions with very limited training data using transfer learning methods. We adapt the model to predict cell behavior for keratocytes (room temperature, ~ 18-20 °C) and keratinocytes (37 °C) under similar experimental conditions with a small dataset (~ 2-5 cells). Finally, this model can be used to perform in silico studies by simulating cell migration lines under time-varying and unseen electric fields. We demonstrate this by simulating feedback control on cell migration using a proportional-integral-derivative (PID) controller. This data-driven approach provides predictive models of cell migration that may be suitable for designing electric field based cellular control mechanisms for applications in precision medicine such as wound healing.

Malignant melanoma (MM) frequently occurs in the skin or mucosa, whereas malignant melanoma of unknown primary (MUP) is diagnosed in patients with lymph nodes or visceral organs as the site of origin, where it is challenging to detect the primary lesion by comprehensive examination. MUP is possibly related to the spontaneous regression of the primary lesion. In addition, primary hepatic melanoma (PHM) usually refers to the primary MM occurring in the liver, with no typical primary lesions and no manifestations of tumor metastasis. A 61-year-old male patient with liver as the site of origin was diagnosed with MM by Melan-A, HMB-45, and S-100 immunohistochemistry staining of liver biopsy tissue. Based on a comprehensive examination, no basis was found for melanoma in sites such as the skin, mucosa, five sense organs, brain, digestive tract, respiratory tract, or genitalia, and the patient was subsequently diagnosed with MUP. MMs require a comprehensive inspection, beginning with the liver, to search for the primary lesion; if the primary lesion is not found, the possibility of PHM or MUP should be considered.

Abstract Ruthenium exhibits comparable or even better alkaline hydrogen evolution reaction activity than platinum, however, the mechanistic aspects are yet to be settled, which are elucidated by combining in situ Raman spectroscopy and theoretical calculations herein. We simultaneously capture dynamic spectral evidence of Ru surfaces, interfacial water, *H and *OH intermediates. Ru surfaces exist in different valence states in the reaction potential range, dissociating interfacial water differently and generating two distinct *H, resulting in different activities. The local cation tuning effect of hydrated Na+ ion water and the large work function of high-valence Ru(n+) surfaces promote interfacial water dissociation. Moreover, compared to low-valence Ru(0) surfaces, high-valence Ru(n+) surfaces have more moderate adsorption energies for interfacial water, *H, and *OH. They, therefore, facilitate the activity. Our findings demonstrate the regulation of valence state on interfacial water, intermediates, and finally the catalytic activity, which provide guidelines for the rational design of high-efficiency catalysts.

In this study, a novel fluidized-bed homogeneous granulation (FBHo-G) process was developed to recover lithium (Li) from industrial Li-impacted wastewater. Five important operational variables (i.e., temperatures, pH, [P]0/[Li]0 molar ratios, surface loadings, and up-flow velocities (Umf)) were selected to optimize the Li recovery (TR%) and granulation ratio (GR%) efficiencies of the process. The optimal operational conditions were determined as the following: a temperature of 75 °C, pH of 11.5, [P]0/[Li]0 of 0.5, surface loading of 2.5 kg/m2·h, and Umf of 35.7 m/h). The TR% and GR% at optimal condition could be as much as 90%. The material characterization of the recovery pellet products showed that they were highly crystallized Li3PO4 (purity ~88.2%). The pellets had a round shape and smooth surface with an average size of 0.65 mm, so could easily be stored and transported. The high purity enables them to be further directly reused as raw materials for a wide range of industrial applications (e.g., in the synthesis of cathode materials). Our calculation shows that the FBHo-G process could recover up to 0.1845 kg of lithium per cubic meter of Li-containing wastewater, at a recovery rate of ~90%. A brief technoeconomic analysis shows that FBHG process had economic viability, with an estimate production cost of USD 26/kg Li removed, while the potential gained profit for selling lithium phosphate pellets could be up to USD 48 per the same volume of wastewater and the net profit up to USD 22/m3 Li treated. In all, fluidized-bed homogeneous granulation, a seedless one-step recovery process, opens a promising pathway toward a green and sustainable recycling industry for the recovery and application of the resource-limited lithium element from nonconventional water sources.

Electrical signaling plays a crucial role in the cellular response to tissue injury in wound healing and an external electric field (EF) may expedite the healing process. Here, we have developed a standalone, wearable, and programmable electronic device to administer a well-controlled exogenous EF, aiming to accelerate wound healing in an in vivo mouse model to provide pre-clinical evidence. We monitored the healing process by assessing the re-epithelization rate and the ratio of M1/M2 macrophage phenotypes through histology staining. Following three days of treatment, the M1/M2 macrophage ratio decreased by 30.6% and the re-epithelization in the EF-treated wounds trended towards a non-statically significant 24.2% increase compared to the control. These findings provide point towards the effectiveness of the device in shortening the inflammatory phase by promoting reparative macrophages over inflammatory macrophages, and in speeding up re-epithelialization. Our wearable device supports the rationale for the application of programmed EFs for wound management in vivo and provides an exciting basis for further development of our technology based on the modulation of macrophages and inflammation to better wound healing.

Despite having similar histologic features, patients with high-grade serous ovarian carcinoma (HGSC) often experience highly variable outcomes. The underlying determinants for long-term survival (LTS, ≥10 years) versus short-term survival (STS, 2; false discovery rate < 0.01). In the subsequent validation cohort, transmembrane protein 62 (TMEM62) was found to be related to LTS. CIBERSORT analysis showed that T cells (follicular helper) were found at higher levels in tumors from LTS than STS groups. In vitro data using OVCAR5 and OVCAR8 cells showed decreased proliferation with TMEM62 overexpression and positive correlation with a longevity-regulating pathway (KEGG HSA04213) at the RNA level. In vivo analysis using the OVCAR8-TMEM62-TetON model showed decreased tumor burden in mice with high- vs. low-expressing TMEM62 tumors. Our results demonstrate that restoring TMEM62 may be a novel approach for treatment of HGSC. These findings may have implications for biomarker and intervention strategies to help improve patient outcomes

Summary: The composite material-like extracellular matrix (ECM) in the sinoatrial node (SAN) supports the native pacemaking cardiomyocytes (PCMs). To test the roles of SAN ECM in the PCM phenotype and function, we engineered reconstructed-SAN heart tissues (rSANHTs) by recellularizing porcine SAN ECMs with hiPSC-derived PCMs. The hiPSC-PCMs in rSANHTs self-organized into clusters resembling the native SAN and displayed higher expression of pacemaker-specific genes and a faster automaticity compared with PCMs in reconstructed-left ventricular heart tissues (rLVHTs). To test the protective nature of SAN ECMs under strain, rSANHTs and rLVHTs were transplanted onto the murine thoracic diaphragm to undergo constant cyclic strain. All strained-rSANHTs preserved automaticity, whereas 66% of strained-rLVHTs lost their automaticity. In contrast to the strained-rLVHTs, PCMs in strained-rSANHTs maintained high expression of key pacemaker genes (HCN4, TBX3, and TBX18). These findings highlight the promotive and protective roles of the composite SAN ECM and provide valuable insights for pacemaking tissue engineering.

Summary: PRMT1 plays a vital role in breast tumorigenesis; however, the underlying molecular mechanisms remain incompletely understood. Herein, we show that PRMT1 plays a critical role in RNA alternative splicing, with a preference for exon inclusion. PRMT1 methylome profiling identifies that PRMT1 methylates the splicing factor SRSF1, which is critical for SRSF1 phosphorylation, SRSF1 binding with RNA, and exon inclusion. In breast tumors, PRMT1 overexpression is associated with increased SRSF1 arginine methylation and aberrant exon inclusion, which are critical for breast cancer cell growth. In addition, we identify a selective PRMT1 inhibitor, iPRMT1, which potently inhibits PRMT1-mediated SRSF1 methylation, exon inclusion, and breast cancer cell growth. Combination treatment with iPRMT1 and inhibitors targeting SRSF1 phosphorylation exhibits an additive effect of suppressing breast cancer cell growth. In conclusion, our study dissects a mechanism underlying PRMT1-mediated RNA alternative splicing. Thus, PRMT1 has great potential as a therapeutic target in breast cancer treatment.

The pyrolysis parameter S1, which indicates the amount of free hydrocarbons present in shale, is often underestimated due to hydrocarbon loss during sample handling and measurement processes. To remedy this issue, we strongly recommend an immediate three-step hydrocarbon thermal desorption (HTD) approach to be conducted on oil shale at the drilling site. This approach measures Sg, S0, and S1*, which refer to gaseous, light, and free hydrocarbons, respectively. The new shale oil content value, calculated from the total of these three parameters, is far more precise and reliable than traditional pyrolysis S1. Moreover, we thoroughly investigated the components and microscopic occurrence features of hydrocarbons thermally desorbed at three temperature stages using gas chromatography (GC) and X-ray microcomputed tomography (CT). For example, we selected Chang 73 mud shale. Our experimental results irrefutably indicate that the ultimate shale oil content of poor resource rocks is significantly impacted by evaporative loss, with this effect being greater when the total organic carbon (TOC) is lower. Additionally, C1-5 and C1-7 hydrocarbons constitute almost all of Sg and S0, respectively. Sg and S0 are predominantly composed of C1-3 gaseous hydrocarbons, with a maximum proportion of 42.93%. In contrast, S1* contains a substantial amount of C16-31 hydrocarbons. A three-dimensional reconstruction model of an X-ray micro-CT scan shows that while the amount of shale organic matter greatly decreases from the frozen state to 300 °C, the pore volume significantly increases, particularly between 90 and 300 °C. The increased pore volume is mainly due to macropores and fractures. It is imperative to note that the shale oil triple-division boundaries must be adjusted based on more accurate oil content, although this would not affect the resource zones to which the samples already belong (ineffective, low-efficient, and enriched resources). In conclusion, we strongly advise conducting an immediate well-site analysis or utilizing preservation procedures, such as deep freezing or plastic film wrapping followed by core waxing, to minimize volatile loss.

The underground environment is complex and superimposed with the uncertainty and nonlinearity of the mine water disaster. The situation of water disaster inundation is changeable and difficult to predict. Regarding the difficulty of obtaining the inundation situation in the roadway at various time points during a flood and quickly determining the escape path based on the inundation situation, in this study, the “bucket principle” is used to construct the submergence path tree, determine the direction of the roadway flow bifurcation, analyze the progressive law of the mine water inrush submersion, simulate the water flow in the underground roadway, and visually display the real-time water flow change, water level height and escape path. The research shows that according to the constructed inundation path tree, the water level and other inundation parameters obtained by recursion are used as the basis for designing the escape path. The differential and integral progressive dynamic design of the escape path solves the problem that the optimal escape path cannot be planned in real time due to the complex underground environment and different water inrush conditions at different times.