Development of a mobile, high-throughput, and low-cost image-based plant growth phenotyping system.

Nondestructive plant phenotyping forms a key technique for unraveling molecular processes underlying plant development and response to the environment. While the emergence of high-throughput phenotyping facilities can further our understanding of plant development and stress responses, their high costs greatly hinder scientific progress. To democratize high-throughput plant phenotyping, we developed sets of low-cost image- and weight-based devices to monitor plant shoot growth and evapotranspiration. We paired these devices to a suite of computational pipelines for integrated and straightforward data analysis. The developed tools were validated for their suitability for large genetic screens by evaluating a cowpea (Vigna unguiculata) diversity panel for responses to drought stress. The observed natural variation was used as an input for a genome-wide association study, from which we identified nine genetic loci that might contribute to cowpea drought resilience during early vegetative development. The homologs of the candidate genes were identified in Arabidopsis (Arabidopsis thaliana) and subsequently evaluated for their involvement in drought stress by using available T-DNA insertion mutant lines. These results demonstrate the varied applicability of this low-cost phenotyping system. In the future, we foresee these setups facilitating the identification of genetic components of growth, plant architecture, and stress tolerance across a wide variety of plant species.

Numerical investigation of flow characteristics in the front and rear chambers of centrifugal pump and pump as turbine.

To investigate the flow characteristics in front chamber and rear chamber in pump mode and pump as turbine mode, a 3D computational model of a centrifugal pump was established, including the front and rear chamber. Based on Realizable k-ε turbulence model, numerical calculations of incompressible flow were carried out for internal viscous flow in two operating modes. Further analysis was conducted on the flow stability and hydraulic losses under two modes using energy gradient theory and entropy production theory. The numerical simulation results are within reasonable error compared to the experimental results in pump operation mode, which ensures the reliability of the numerical calculation method. The results indicate that the volumetric efficiency in both two modes is on an upward trend with increasing flow, but the volumetric efficiency of the pump mode is more significantly affected by changes in flow; the distribution patterns of dimensionless circumferential velocity and dimensionless radial velocity in the front and rear chambers under two operating modes are similar, but the distribution pattern of dimensionless radial velocity in the front chamber in turbine mode is significantly different from other operating conditions; flow instability is most likely to occur at the outlet of impeller, and the energy loss in clearance of wear-rings is greater than that in the pump chamber.

Friction-Wear and Noise Characteristics of Friction Disks with Circular Texture.

The reduction of friction-induced noise is a crucial research area for enhancing vehicle comfort, and this paper proposes a method based on circular pit texture to achieve this goal. We conducted a long-term sliding friction test using a pin-on-disc friction and a wear test bench to verify the validity of this method. To compare the friction noise of different surfaces, texture units with varying line densities were machined on the surface of friction disk samples. The resulting friction-wear and noise characteristics of the samples were analyzed in conjunction with the microscopic morphology of the worn surfaces. The results indicate that surfaces with textures can delay the onset of squeal noise, and the pattern of its development differs from that of smooth surfaces. The noise reduction effect is most evident due to the proper distribution of textures that can form furrow-like wear marks at the wear interface. The finite element results demonstrate that this morphology can improve pressure distribution at the leading point and reduce the tendency of system instability.

Hype or hope? Ketamine for the treatment of depression: results from the application of deep learning to Twitter posts from 2010 to 2023.

Objective: To investigate societal perceptions of ketamine's use in depression therapy by analysing Twitter posts from January 1, 2010 to April 1, 2023. Methods: Using Twitter as the social media platform of choice, and employing search terms based on (depression OR depressed OR depressive) AND (ketamine OR esketamine OR Spravato), we collected English-language tweets from January 1, 2010, to April 1, 2023. Using unsupervised machine learning and natural language processing (NLP) techniques, including Bidirectional Encoder Representations from Transformers (BERT) and BERTopic, the study identified prevalent topics surrounding public chatter around the use of ketamine in depression treatment. Manual thematic analyses further refined these topics into themes. Results: Out of an initial dataset of 99,405 tweets, after removing duplicate tweets, re-tweets and tweets posted by organizations over Twitter, 18,899 unique tweets from presumably individual users were analysed. Analysis of temporal trends revealed a shift in public attitudes, particularly after the United States Food and Drug Administration (FDA)'s 2019 approval of ketamine for depression. Three major themes emerged: a changing regulatory landscape, cautious optimism, and personal experiences with the drug. There was an initial spike in discussions post-FDA approval in 2019. Thereafter, cautious optimism (Theme 2) decreased among the general public, with more personal accounts (Theme 3) highlighting the potential benefits for some treatment-resistant patients. Limitations of the study include Twitter's inherent biases towards younger, English-speaking demographics. Conclusion: In summary, the public's multifaceted perception leans towards a hopeful stance on ketamine's therapeutic potential for depression.

Associations between immune cell phenotypes and lung cancer subtypes: insights from mendelian randomization analysis.

INTRODUCTION: Lung cancer is a common malignant tumor, and different types of immune cells may have different effects on the occurrence and development of lung cancer subtypes, including lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). However, the causal relationship between immune phenotype and lung cancer is still unclear. METHODS: This study utilized a comprehensive dataset containing 731 immune phenotypes from the European Bioinformatics Institute (EBI) to evaluate the potential causal relationship between immune phenotypes and LUSC and LUAD using the inverse variance weighted (IVW) method in Mendelian randomization (MR). Sensitivity analyses, including MR-Egger intercept, Cochran Q test, and others, were conducted for the robustness of the results. The study results were further validated through meta-analysis using data from the Transdisciplinary Research Into Cancer of the Lung (TRICL) data. Additionally, confounding factors were excluded to ensure the robustness of the findings. RESULTS: Among the final selection of 729 immune cell phenotypes, three immune phenotypes exhibited statistically significant effects with LUSC. CD28 expression on resting CD4 regulatory T cells (OR 1.0980, 95% CI: 1.0627-1.1344, p < 0.0001) and CD45RA + CD28- CD8 + T cell %T cell (OR 1.0011, 95% CI: 1.0007; 1.0015, p < 0.0001) were associated with increased susceptibility to LUSC. Conversely, CCR2 expression on monocytes (OR 0.9399, 95% CI: 0.9177-0.9625, p < 0.0001) was correlated with a decreased risk of LUSC. However, no significant causal relationships were established between any immune cell phenotypes and LUAD. CONCLUSION: This study demonstrates that specific immune cell types are associated with the risk of LUSC but not with LUAD. While these findings are derived solely from European populations, they still provide clues for a deeper understanding of the immunological mechanisms underlying lung cancer and may offer new directions for future therapeutic strategies and preventive measures.

The role of the microscopic world: Exploring the role and potential of intratumoral microbiota in cancer immunotherapy.

Microorganisms, including bacteria, viruses, and fungi, coexist in the human body, forming a symbiotic microbiota that plays a vital role in human health and disease. Intratumoral microbial components have been discovered in various tumor tissues and are closely linked to the occurrence, progression, and treatment results of cancer. The intratumoral microbiota can enhance antitumor immunity through mechanisms such as activating the stimulator of interferon genes signaling pathway, stimulating T and NK cells, promoting the formation of TLS, and facilitating antigen presentation. Conversely, the intratumoral microbiota might suppress antitumor immune responses by increasing reactive oxygen species levels, creating an anti-inflammatory environment, inducing T cell inactivation, and enhancing immune suppression, thereby promoting cancer progression. The impact of intratumoral microbiota on antitumor immunity varies based on microbial composition, interactions with cancer cells, and the cancer's current state. A deep understanding of the complex interactions between intratumoral microbiota and antitumor immunity holds the potential to bring new therapeutic strategies and targets to cancer immunotherapy.

Prognostic impact of sodium fluorescein-guided microsurgery on cognitive function, neuropeptide dynamics, and short-term outcomes in brain glioma patients.

This study conducted a retrospective analysis on 107 brain glioma patients treated from January 2018 to February 2020 to assess the impact of sodium fluorescein-guided microsurgery on postoperative cognitive function and short-term outcomes. Patients were divided into two groups: a control group (n=50 patients) undergoing routine surgery and a research group (n=57 patients) receiving sodium fluorescein-guided microsurgery. The study compared postoperative total resection rates, changes in cognitive scores, and neuropeptide levels in cerebrospinal fluid between the groups. The findings revealed that the research group experienced shorter surgical time and hospitalization duration, reduced blood loss, and higher total resection rates compared to the control group. Furthermore, the research group demonstrated improvements in cognitive scores and an increase in neuropeptide levels after surgery. There was no significant difference in the comparison of the incidence of postoperative complications between the two groups. The WHO classification and preoperative performance scores were independent prognostic factors for the evaluation of 3-year survival, highlighting the clinical significance of sodium fluorescein-guided microsurgery in improving quality of life and cognitive functions of patients without compromising their long-term survival outcomes.

Three-Dimensional-Printed Template-Guided Radioactive Seed Brachytherapy via a Submental Approach for Recurrent Base of Tongue and Floor of Mouth Cancer.

Background: This study assessed clinical outcomes of three-dimensional-printed template (3DPT)-guided radioactive seed brachytherapy (RSBT) via a submental approach for recurrent base of tongue and floor of mouth cancer. Methods: Thirty-one patients with recurrent lingual and floor of mouth squamous cell carcinoma after surgery and radiotherapy were treated with 3DPT-guided RSBT from 2015 to 2022. Seeds were implanted through a submental approach guided by 3DPTs. Local control (LC), overall survival (OS), disease control (DC) and quality of life (QOL) were evaluated. Results: The median follow-up was 13.7 months. The 1-, 3- and 5-year LC rates were 66.1%, 66.1%, and 55.1% respectively. The 1-, 3- and 5-year OS rates were 63.4%, 33.4%, and 8.3%. The 1-, 3- and 5-year DC rates were 37.8%, 26.5%, and 21.2%. Univariate analysis showed tumor size significantly affected LC (P = 0.031). The presence of extraterritorial lesions affected DC and OS on multivariate analysis (P < 0.01). QOL improved significantly in domains of pain, swallowing, chewing, taste, and emotion after treatment compared to baseline. Four patients (13%) developed necrosis and osteoradionecrosis. Conclusions: 3DPT-guided submental RSBT provided favorable LC and QOL for recurrent tongue/floor of mouth cancer with minimal toxicity; moreover, severe toxicity should be noted.

Short-Term Outcomes of Transcatheter Aortic Valve Replacement in Low-Risk Patients With Pure Severe Aortic Regurgitation.

Transcatheter aortic valve replacement (TAVR) has emerged as an alternative treatment for patients with pure severe aortic regurgitation (PSAR) who are contraindicated for surgery or have a high surgical risk. However, the therapeutic efficacy and safety of TAVR in low Society of Thoracic Surgeons (STS) score risk patients remain to be clarified. This study aimed to explore the feasibility of TAVR treatment in different STS-risk patients and to compare the adverse events between the groups. In this study, patients with PSAR who underwent TAVR at Zhongshan Hospital, Fudan University, China, during the inclusion period were included and categorized into 3 groups based on STS scores. The baseline data, imaging results, and follow-up data of the patients were documented. Therefore, of 75 TAVR patients, 38 (50.7%) were categorized as low risk (STS <4), and 37 (49.3%) patients were categorized as intermediate and high risk (STS ≥4). Compared with patients at intermediate and high risk, those in the low-risk group were younger, had a lower body mass index, had a lower prevalence of hypertension, chronic obstructive pulmonary disease, and previous percutaneous coronary intervention, and had better cardiac function (p all <0.05). In the hospital and at the 1-month follow-up, the degree of aortic regurgitation and cardiac function were significantly improved. No significant difference was found between the 2 groups in the hospital or during the 30-day follow-up. In conclusion, TAVR for PSAR in low-STS-risk patients is safe and efficient during 30 days of follow-up compared with intermediate- and high-STS-risk groups. TAVR for PSAR should not be limited to inoperable or STS-defined high-risk patients. Long-term follow-up is needed for further investigation.

Immunomodulation of adipose-derived mesenchymal stem cells on peripheral blood mononuclear cells in colorectal cancer patients with COVID-19.

BACKGROUND: Accumulating evidence has shown that adipose tissue-derived mesenchymal stem cells (ADSCs) are an effective therapeutic approach for managing coronavirus disease 2019 (COVID-19); however, further elucidation is required to determine their underlying immunomodulatory effect on the mRNA expression of T helper cell-related transcription factors (TFs) and cytokine release in peripheral blood mononuclear cells (PBMCs). AIM: To investigate the impact of ADSCs on the mRNA expression of TFs and cytokine release in PBMCs from colorectal cancer (CRC) patients with severe COVID-19 (CRC+ patients). METHODS: PBMCs from CRC+ patients (PBMCs-C+) and age-matched CRC patients (PBMCs-C) were stimulated and cultured in the presence/absence of ADSCs. The mRNA levels of T-box TF TBX21 (T-bet), GATA binding protein 3 (GATA-3), RAR-related orphan receptor C (RORC), and forkhead box P3 (FoxP3) in the PBMCs were determined by reverse transcriptase-polymerase chain reaction. Culture supernatants were evaluated for levels of interferon gamma (IFN-γ), interleukin 4 (IL-4), IL-17A, and transforming growth factor beta 1 (TGF-ß1) using an enzyme-linked immunosorbent assay. RESULTS: Compared with PBMCs-C, PBMCs-C+ exhibited higher mRNA levels of T-bet and RORC, and increased levels of IFN-γ and IL-17A. Additionally, a significant decrease in FoxP3 mRNA and TGF-ß1, as well as an increase in T-bet/GATA-3, RORC/FoxP3, IFN-γ/IL-4, and IL-17A/TGF-ß1 ratios were observed in PBMCs-C+. Furthermore, ADSCs significantly induced a functional regulatory T cell (Treg) subset, as evidenced by an increase in FoxP3 mRNA and TGF-ß1 release levels. This was accompanied by a significant decrease in the mRNA levels of T-bet and RORC, release of IFN-γ and IL-17A, and T-bet/GATA-3, RORC/FoxP3, IFN-γ/IL-4, and IL-17A/TGF-ß1 ratios, compared with the PBMCs-C+alone. CONCLUSION: The present in vitro studies showed that ADSCs contributed to the immunosuppressive effects on PBMCs-C+, favoring Treg responses. Thus, ADSC-based cell therapy could be a beneficial approach for patients with severe COVID-19 who fail to respond to conventional therapies.

Functional and mechanistic studies of a phytogenic formulation, Shrimp Best, in growth performance and vibriosis in whiteleg shrimp.

Climate change and disease threaten shrimp farming. Here, we studied the beneficial properties of a phytogenic formulation, Shrimp Best (SB), in whiteleg shrimp. Functional studies showed that SB dose-dependently increased shrimp body weight and decreased feed conversion ratio. We found that SB protected against Vibrio parahaemolyticus as evidenced by survival rate, bacterial load, and hepatopancreatic pathology in shrimp. Finally, we explored the likely mechanism by which SB affects growth performance and vibriosis in shrimp. The 16S rRNA sequencing data showed that SB increased 6 probiotic genera and decreased 6 genera of pathogenic bacteria in shrimp. Among these, SB increased the proportion of Lactobacillus johnsonii and decreased that of V. parahaemolyticus in shrimp guts. To dissect the relationship among SB, Lactobacillus and Vibrio, we investigated the in vitro regulation of Lactobacillus and Vibrio by SB. SB at ≥ 0.25 µg/mL promoted L. johnsonii growth. Additionally, L. johnsonii and its supernatant could inhibit V. parahaemolyticus. Furthermore, SB could up-regulate five anti-Vibrio metabolites of L. johnsonii, which caused bacterial membrane destruction. In parallel, we identified 3 fatty acids as active compounds from SB. Overall, this work demonstrated that SB improved growth performance and vibriosis protection in shrimp via the regulation of gut microbiota.

Predicting Alzheimer's progression in MCI: a DTI-based white matter network model.

OBJECTIVE: This study aimed to identify features of white matter network attributes based on diffusion tensor imaging (DTI) that might lead to progression from mild cognitive impairment (MCI) and construct a comprehensive model based on these features for predicting the population at high risk of progression to Alzheimer's disease (AD) in MCI patients. METHODS: This study enrolled 121 MCI patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Among them, 36 progressed to AD after four years of follow-up. A brain network was constructed for each patient based on white matter fiber tracts, and network attribute features were extracted. White matter network features were downscaled, and white matter markers were constructed using an integrated downscaling approach, followed by forming an integrated model with clinical features and performance evaluation. RESULTS: APOE4 and ADAS scores were used as independent predictors and combined with white matter network markers to construct a comprehensive model. The diagnostic efficacy of the comprehensive model was 0.924 and 0.919, sensitivity was 0.864 and 0.900, and specificity was 0.871 and 0.815 in the training and test groups, respectively. The Delong test showed significant differences (P < 0.05) in the diagnostic efficacy of the combined model and APOE4 and ADAS scores, while there was no significant difference (P > 0.05) between the combined model and white matter network biomarkers. CONCLUSIONS: A comprehensive model constructed based on white matter network markers can identify MCI patients at high risk of progression to AD and provide an adjunct biomarker helpful in early AD detection.

Risk of cardiovascular death in patients with hepatocellular carcinoma based on the Fine-Gray model.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common types of cancers worldwide, ranking fifth among men and seventh among women, resulting in more than 7 million deaths annually. With the development of medical technology, the 5-year survival rate of HCC patients can be increased to 70%. However, HCC patients are often at increased risk of cardiovascular disease (CVD) death due to exposure to potentially cardiotoxic treatments compared with non-HCC patients. Moreover, CVD and cancer have become major disease burdens worldwide. Thus, further research is needed to lessen the risk of CVD death in HCC patient survivors. AIM: To determine the independent risk factors for CVD death in HCC patients and predict cardiovascular mortality (CVM) in HCC patients. METHODS: This study was conducted on the basis of the Surveillance, Epidemiology, and End Results database and included HCC patients with a diagnosis period from 2010 to 2015. The independent risk factors were identified using the Fine-Gray model. A nomograph was constructed to predict the CVM in HCC patients. The nomograph performance was measured using Harrell's concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) value. Moreover, the net benefit was estimated via decision curve analysis (DCA). RESULTS: The study included 21545 HCC patients, of whom 619 died of CVD. Age (< 60) [1.981 (1.573-2.496), P < 0.001], marital status (married) [unmarried: 1.370 (1.076-1.745), P = 0.011], alpha fetoprotein (normal) [0.778 (0.640-0.946), P = 0.012], tumor size (≤ 2 cm) [(2, 5] cm: 1.420 (1.060-1.903), P = 0.019; > 5 cm: 2.090 (1.543-2.830), P < 0.001], surgery (no) [0.376 (0.297-0.476), P < 0.001], and chemotherapy(none/unknown) [0.578 (0.472-0.709), P < 0.001] were independent risk factors for CVD death in HCC patients. The discrimination and calibration of the nomograph were better. The C-index values for the training and validation sets were 0.736 and 0.665, respectively. The AUC values of the ROC curves at 2, 4, and 6 years were 0.702, 0.725, 0.740 in the training set and 0.697, 0.710, 0.744 in the validation set, respectively. The calibration curves showed that the predicted probabilities of the CVM prediction model in the training set vs the validation set were largely consistent with the actual probabilities. DCA demonstrated that the prediction model has a high net benefit. CONCLUSION: Risk factors for CVD death in HCC patients were investigated for the first time. The nomograph served as an important reference tool for relevant clinical management decisions.

Effects of Aging Treatment on the Microstructures and Mechanical Properties of a TC18 Alloy.

In the present work, the effects of aging treatment on the microstructures of a TC18 alloy are studied. The influence of aging treatment on the tensile properties and failure mechanisms is systematically analyzed. It is found that the size and morphology of the primary α (αp) phases are insensitive to aging temperature and time. Furthermore, the aging temperature and time dramatically influence the precipitation of the secondary α (αs) phases. Massive αs phases precipitate and gradually coarsen, and finally weave together by increasing the aging temperature or extending the aging time. The variations in αp and αs phases induced by aging parameters also affect the mechanical properties. Both yield strength (YS) and ultimate tensile strength (UTS) first increase and then decrease by increasing the aging temperature and time, while ductility first decreases and then increases. There is an excellent balance between the strengths and ductility. When the aging temperature is changed from 450 to 550 °C, YS varies from 1238.6 to 1381.6 MPa, UTS varies from 1363.2 to 1516.8 MPa, and the moderate elongation ranges from 9.0% to 10.3%. These results reveal that the thickness of αs phases is responsible for material strengths, while the content of α phases can enhance material ductility. The ductile characteristics of the alloy with coarser αs phases are more obvious than those with thinner αs phases. Therefore, the aging treatment is helpful for the precipitation and homogeneous distribution of αs phases, which are essential for balancing the strengths and ductility of the studied Ti alloy.

Fatigue Affects Body Acceleration During Vertical Jumping and Agility Tasks in Elite Young Badminton Players.

BACKGROUND: Badminton is a sport demanding both high aerobic and anaerobic fitness levels, and fatigue can significantly impact game performance. However, relevant studies are limited, and none have employed a wearable inertial measurement unit (IMU) to investigate the effects of fatigue on athletic performance in the field. HYPOTHESIS: Overall performance and body acceleration in both time and frequency domains during the fundamental badminton skills of vertical jumping and changes of direction will be affected by fatigue. STUDY DESIGN: Cross-sectional study. LEVEL OF EVIDENCE: Level 3. METHODS: A total of 38 young badminton players competing at the Division I level participated. Body accelerations while performing vertical jump and agility-T tests before and immediately after undergoing a fatigue protocol were measured by an IMU, positioned at the L4 to L5 level. RESULTS: Jumping height decreased significantly by 4 cm (P < 0.01) after fatigue with greater downward acceleration (1.03 m/s2, P < 0.05) during the squatting subphase. Finishing time increased significantly by 50 ms only during the 10-m side-shuffling of the agility-T test (P = 0.02) after fatigue with greater peak and mean accelerations (3.83 m/s2, P = 0.04; 0.43 m/s2, P < 0.01), and higher median and mean frequency (0.38 Hz, P = 0.04, 0.11 Hz, P = 0.01). CONCLUSION: This study using a wearable IMU demonstrates the effects of fatigue on body acceleration in badminton players. The frequency-domain analysis further indicated that fatigue might lead to loss of voluntary control of active muscles and increased impacts on the passive elastic elements. CLINICAL RELEVANCE: The findings imply that fatigue can lead to diminished athletic performance and highlight the potential for an increased risk of sports injuries. Consequently, maintaining precision in monitoring fatigue is crucial for elite young badminton players.

A comprehensive exploration of twist1 to identify a biomarker for tumor immunity and prognosis in pan-cancer.

Twist1 has been identified as a critical gene in tumor, but current study of this gene remains limitative. This study aims to investigate its roles and potential mechanisms across pan-cancer. The study used various databases and computational techniques to analyze twist's RNA expression, clinical data, gene mutations, tumor stemness, tumor microenvironment, immune regulation. Furthermore, the experimental method of fluorescence staining was carried out to identify twist1 expression in various tumor masses. After analyzing the protein-protein interaction of TWIST, enrichment analysis and predictive potential drugs were performed, and molecular docking was conducted to validate. We found that twist1 expression was significantly higher in various types of cancer and associated with tumor stage, grade, and poor prognosis in multiple cancers. Differential expression of twist1 was linked to gene mutation, RNA modifications, and tumor stemness. Additionally, twist1 expression was positively associated with tumor immunoregulation and immune checkpoint. Salinomycin, klugline, isocephaelince, manassantin B, and pimonidazole are predictive potential drugs targeting TWIST1. This study revealed that twist1 plays an important role in tumor, and might be a curial marker in tumor diagnose and prognosis. The study also highlighted twist1 as a promising therapeutic target for cancer treatment and provided a foundation for future research.

Activation of the Photosensitive Potential of 2D GaSe by Interfacial Engineering.

Two-dimensional (2D) gallium selenide (GaSe) holds great promise for pioneering advancements in photodetection due to its exceptional electronic and optoelectronic properties. However, in conventional photodetectors, 2D GaSe only functions as a photosensitive layer, failing to fully exploit its inherent photosensitive potential. Herein, we propose an ultrasensitive photodetector based on out-of-plane 2D GaSe/MoSe2 heterostructure. Through interfacial engineering, 2D GaSe serves not only as the photosensitive layer but also as the photoconductive gain and passivation layer, introducing a photogating effect and extending the lifetime of photocarriers. Capitalizing on these features, the device exhibits exceptional photodetection performance, including a responsivity of 28 800 A/W, specific detectivity of 7.1 × 1014 Jones, light on/off ratio of 1.2 × 106, and rise/fall time of 112.4/426.8 µs. Moreover, high-resolution imaging under various wavelengths is successfully demonstrated using this device. Additionally, we showcase the generality of this device design by activating the photosensitive potential of 2D GaSe with other transition metal dichalcogenides (TMDCs) such as WSe2, WS2, and MoS2. This work provides inspiration for future development in high-performance photodetectors, shining a spotlight on the potential of 2D GaSe and its heterostructure.

Co-doped NiFe carbonate hydroxide hydrate nanosheets with edge effect constructed from spent lithium-ion battery ternary cathodes for oxygen evolution reaction.

The recycling of spent lithium-ion batteries (LIBs) has received increasing attention for environment and resource reclamation. Converting LIBs wastes into high-efficiency catalysts is a win-win strategy for realizing resource reclamation and addressing sustainable energy challenges. Herein, we developed a simple method to upcycle spent-LIBs cathode powder into Co-doped NiFe carbonate hydroxide hydrate (Co/NFCH-FF) as a low-cost and efficient oxygen evolution reaction (OER) electrocatalyst. The optimized Co/NFCH-FF electrode appears very competitive OER performances with low overpotentials of 201 and 249 mV at 10 and 100 mA cm-2, respectively, a small Tafel slope of 48.4 mV dec-1, and a high long-term stability. Moreover, we reveal that the existence of Co atoms leads to the formation of a crystalline/amorphous (c/a) interface at the Co/NFCH nanosheet edge, inducing the nanosheets possess a unique edge effect to enhance electric fields and accumulate hydroxide ions (OH-) at the edge during the OER process. Benefiting from edge effect, Co/NFCH-FF shows outstanding intrinsic activity. Furthermore, Co atoms as dopants stabilize the electronic structure of Co/NFCH-FF, enabling Co/NFCH-FF to exhibit excellent catalytic stability. This work provides an effective strategy for converting the end-life LIBs to high-performance multicomponent OER electrocatalysts and proposes new insights into the mechanism of enhanced catalytic activity of Co/NFCH.

MulStack: An ensemble learning prediction model of multilabel mRNA subcellular localization.

Subcellular localization of mRNA is related to protein synthesis, cell polarity, cell movement and other biological regulation mechanisms. The distribution of mRNAs in subcellulars is similar to that of proteins, and most mRNAs are distributed in multiple subcellulars. Recently, some computational methods have been designed to predict the subcellular localization of mRNA. However, these methods only employed a sin-gle level of mRNA features and did not employ the position encoding of nucleotides in mRNA. In this paper, an ensemble learning prediction model is proposed, named MulStack, which is based on random forest and deep learning for multilabel mRNA subcellular localization. The proposed method employs two levels of mRNA features, including sequence-level and residue-level features, and position encoding is employed for the first time in the field of subcellular localization of mRNA. Random forest is employed to learn mRNA sequence-level feature, deep learning is employed to learn mRNA sequence-level feature and mRNA residue-level combined with position encoding. And the outputs of random forest and deep learning model will be weighted sum as the prediction probability. Compared with existing methods, the results show that MulStack is the best in the localization of the nucleus, cytosol and exosome. In addition, position weight matrices (PWMs) are extracted by convolutional neural networks (CNNs) that can be matched with known RNA binding protein motifs. Gene ontology (GO) enrichment analysis shows biological processes, molecular functions and cellular components of mRNA genes. The prediction web server of MulStack is freely accessible at http://bliulab.net/MulStack.