Pan-cancer analysis of the prognostic and immunological roles of SHP-1/ptpn6.

SHP-1, a nonreceptor protein tyrosine phosphatase encoded by ptpn6, has been regarded as a regulatory protein of hematopoietic cell biology for years. However, there is now increasing evidence to support its role in tumors. Thus, the role of ptpn6 for prognosis and immune regulation across 33 tumors was investigated, aiming to explore its functional heterogeneity and clinical significance in pan-cancer. Differential expression of ptpn6 was found between cancer and adjacent normal tissues, and its expression was significantly correlated with the prognosis of tumor patients. In most cancers, ptpn6 expression was significantly associated with immune infiltration. This was further confirmed by ptpn6-related genes/proteins enrichment analysis. Additionally, genetic alterations in ptpn6 was observed in most cancers. As for epigenetic changes, it's phosphorylation levels significantly altered in 6 tumors, while methylation levels significantly altered in 12 tumors. Notably, the methylation levels of ptpn6 were significantly decreased in 11 tumors, accompanied by its increased expression in 8 of them, suggesting that the hypomethylation may be related to its increased expression. Our results show that ptpn6 plays a specific role in tumor immunity and exerts a pleiotropic effect in a variety of tumors. It can serve as a prognostic factor for some cancers. Especially in LGG, KIRC, UCS and TGCT, the increased expression of ptpn6 is associated with poor prognosis and high immune infiltration. This aids in understanding the role of ptpn6 in tumor biology, and can provide insight into presenting a potential biomarker for poor prognosis and immune infiltration in cancers.

Sociological-Theory-Based Multitopic Self-Supervised Recommendation.

Social relationships offer crucial supplementary information for recommendations by leveraging users' social connections to gain insights into their preferences. However, prevalent social recommendation methods often grapple with the issues of sparsity and noise, which curtail their effectiveness. In addition, these methods overlook the intricacies of user interactions within social networks, which could provide invaluable information. Addressing their deficiencies, this article introduces a novel sociological-theory-based multitopic self-supervised recommendation method (SMSR). This method integrates user attitude information into the construction of social relationships and utilizes dynamic routing to identify and categorize topics, thereby mitigating the impact of social noise on recommendation accuracy. Furthermore, we reveal sophisticated higher order user relations within these topics by using motifs. By combining the light graph convolutional network with balance theory, SMSR efficiently aggregates information from diverse social relations to gain its outstanding performance. Moreover, we have devised and integrated four self-supervised signals, inspired by social theory and derived from heterogeneous graph analysis, to more effectively exploit the rich structural and semantic information inherent in social relationship graphs. Empirical results from extensive experiments on publicly available datasets underscore SMSR's superiority over the state of the art.

A Cross-Layer Game-Theoretic Approach to Resilient Control of Networked Switched Systems Against DoS Attacks.

This article investigates the resilient control strategies of networked switched systems (NSSs) against denial-of-service (DoS) attacks and external disturbance. In the network layer, both the defender and the attacker allocate energy over multiple channels. Considering the impact of switching characteristic in the physical layer on the network layer, a dynamic regulating factor is proposed to adjust the total energy of the defender. To optimize the signal-to-interference-noise ratio and energy consumption simultaneously at each player's side, a multiobjective game problem is formulated. Furthermore, a nondominated sorting genetic algorithm framework is employed, incorporating the knee point selection mechanism to attain the Pareto-Nash equilibrium, based on which the optimal defense strategy can be derived to achieve resilience against DoS attacks. In the physical-layer, taking the dynamic packet loss caused by DoS attacks and external disturbance into account, an H∞ minimax controller containing control inputs and the switching signal is designed to guarantee the optimal performance for NSSs through the dynamic game-theoretic approach. Finally, the networked continuous stirred tank reactor system is provided to verify the effectiveness of the proposed method.

UNeXt: An Efficient Network for the Semantic Segmentation of High-Resolution Remote Sensing Images.

The application of deep neural networks for the semantic segmentation of remote sensing images is a significant research area within the field of the intelligent interpretation of remote sensing data. The semantic segmentation of remote sensing images holds great practical value in urban planning, disaster assessment, the estimation of carbon sinks, and other related fields. With the continuous advancement of remote sensing technology, the spatial resolution of remote sensing images is gradually increasing. This increase in resolution brings about challenges such as significant changes in the scale of ground objects, redundant information, and irregular shapes within remote sensing images. Current methods leverage Transformers to capture global long-range dependencies. However, the use of Transformers introduces higher computational complexity and is prone to losing local details. In this paper, we propose UNeXt (UNet+ConvNeXt+Transformer), a real-time semantic segmentation model tailored for high-resolution remote sensing images. To achieve efficient segmentation, UNeXt uses the lightweight ConvNeXt-T as the encoder and a lightweight decoder, Transnext, which combines a Transformer and CNN (Convolutional Neural Networks) to capture global information while avoiding the loss of local details. Furthermore, in order to more effectively utilize spatial and channel information, we propose a SCFB (SC Feature Fuse Block) to reduce computational complexity while enhancing the model's recognition of complex scenes. A series of ablation experiments and comprehensive comparative experiments demonstrate that our method not only runs faster than state-of-the-art (SOTA) lightweight models but also achieves higher accuracy. Specifically, our proposed UNeXt achieves 85.2% and 82.9% mIoUs on the Vaihingen and Gaofen5 (GID5) datasets, respectively, while maintaining 97 fps for 512 × 512 inputs on a single NVIDIA GTX 4090 GPU, outperforming other SOTA methods.

Disruptive and complementary effects of depression symptoms on spontaneous brain activity in the subcortical vascular mild cognitive impairment.

Background: Although depression symptoms are commonly reported in patients with subcortical vascular mild cognitive impairment (svMCI), their impact on brain functions remains largely unknown, with diagnoses mainly dependent on behavioral assessments. Methods: In this study, we analyzed resting-state fMRI data from a cohort of 34 svMCI patients, comprising 18 patients with depression symptoms (svMCI+D) and 16 patients without (svMCI-D), along with 34 normal controls (NC). The study used the fraction of the amplitude of low-frequency fluctuations (fALFF), resting-state functional connectivity, correlation analyses, and support vector machine (SVM) techniques. Results: The fALFF of the right cerebellum (CERE.R) differed among the svMCI+D, svMCI-D, and NC groups. Specifically, the regional mean fALFF of CERE. R was lower in svMCI-D patients compared to NC but higher in svMCI+D patients compared to svMCI-D patients. Moreover, the adjusted fALFF of CERE. R showed a significant correlation with Montreal Cognitive Assessment (MOCA) scores in svMCI-D patients. The fALFF of the right orbital part of the superior frontal gyrus was significantly correlated with Hamilton Depression Scale scores in svMCI+D patients, whereas the fALFF of the right postcingulate cortex (PCC.R) showed a significant correlation with MOCA scores in svMCI-D patients. Furthermore, RSFC between PCC. R and right precuneus, as well as between CERE. R and the right lingual gyrus (LING.R), was significantly reduced in svMCI-D patients compared to NC. In regional analyses, the adjusted RSFC between PCC. R and PreCUN. R, as well as between CERE. R and LING. R, was decreased in svMCI-D patients compared to NC but increased in svMCI+D patients compared to svMCI-D. Further SVM analyses achieved good performances, with an area under the curve (AUC) of 0.82 for classifying svMCI+D, svMCI-D, and NC; 0.96 for classifying svMCI+D and svMCI-D; 0.82 for classifying svMCI+D and NC; and 0.92 for classifying svMCI-D and NC. Conclusion: The study revealed disruptive effects of cognitive impairment, along with both disruptive and complementary effects of depression symptoms on spontaneous brain activity in svMCI. Moreover, these findings suggest that the identified features might serve as potential biomarkers for distinguishing between svMCI+D, svMCI-D, and NC, thereby guiding clinical treatments such as transcranial magnetic stimulation for svMCI.

Tree species-dependent effects of afforestation on soil fungal diversity, functional guilds and co-occurrence networks in northern China.

Afforestation exerts a profound impact on soil fungal communities, with the nature and extent of these changes significantly influenced by the specific tree species selected. While extensive research has addressed the aboveground ecological outcomes of afforestation, the nuanced interactions between tree species and soil fungal dynamics remain underexplored. This study investigated the effects of afforestation with Caragana microphylla (CMI), Populus simonii (PSI), and Pinus sylvestris var. mongolica (PSY) on soil fungal diversity, functional guilds, and co-occurrence networks, drawing comparisons with neighboring grasslands. Our findings reveal a significant increase in soil fungal Chao1 richness following afforestation, though the degree of enhancement varied across tree species. Specifically, CMI and PSI forests showed notable increases in fungal richness, whereas the response in PSY forests was comparatively modest. Saprotrophic fungal groups, integral to organic matter decomposition, showed a substantial increase across all afforested sites, with CMI forests exhibiting an impressive 205.58% rise. Conversely, pathogenic fungi, which can negatively impact plant health, demonstrated a marked decrease within plantation forests. Symbiotic groups, particularly ectomycorrhizal fungi, were notably enriched solely in PSI forests. Co-occurrence network analysis further indicated that afforestation alters fungal network complexity: CMI forests displayed increased network interactions, while PSI and PSY forests exhibited a reduction in network connectivity. Soil bulk density and organic carbon content emerged as key factors influencing network complexity, whereas tree species identity played a crucial role in shaping soil fungal community composition. Collectively, these results emphasize the importance of adopting a species-specific strategy for afforestation to optimize soil fungal diversity and network structure, ultimately enhancing the ecological resilience and sustainability of forest plantation ecosystems.

Assessing the quality of breast cancer-related videos on TikTok: A cross-sectional study.

Purpose: Breast cancer, the most common cancer in women globally, highlights the need for patient education. Despite many breast cancer discussions on TikTok, their scientific evaluation is lacking. Our study seeks to assess the content quality and accuracy of popular TikTok videos on breast cancer, to improve the dissemination of health knowledge. Methods: On August 22, 2023, we collected the top 100 trending videos from TikTok's Chinese version using "breast cancer/breast nodule" as keywords. We noted their length, TikTok duration, likes, comments, favorites, reposts, uploader types, and topics. Four assessment tools were used: Goobie's six questions, the Patient Educational Material Assessment Tool (PEMAT), the Video Information and Quality Index (VIQI), and the Global Quality Score (GQS). These instruments evaluate videos based on content, informational integrity, and overall quality. Results: Among the 100 videos, content quality was low with Goobie's questions mostly scoring 0, except for management at 1.0 (QR 1.0). PEMAT scores were moderate: 54.1 (QR 1.6) for sum, 47.0 (QR 18.8) for PEMAT-A, and 52.3 (QR 11.7) for PEMAT-U. Regarding the quality of information, the VIQI (sum) median was 14.1 (QR 0.2). Additionally, the median GQS score was 3.5 (QR 0.1). Medical professionals' videos focused on breast cancer stages, while patient videos centered on personal experiences. Patient videos had lower content and overall quality compared to those by medical professionals (PEMAT, GQS: P < 0.001, P = 0.004) but received more comments, indicating higher engagement (all P < 0.05). Conclusion: TikTok's breast cancer content shows educational potential, but while informational quality is moderate, content quality needs improvement. Videos by medical professionals are of higher quality. We recommend increased involvement of healthcare professionals on TikTok to enhance content quality. Non-medical users should share verified information, and TikTok should strengthen its content vetting. Users must scrutinize the credibility of health information on social platforms.

Epidemiology, prognostic factors, and survival analysis in small cell esophageal carcinoma: A population-based study with external validation.

Small cell esophageal carcinoma (SCEC) is a poorly differentiated esophageal neuroendocrine neoplasm with a poor prognosis. This study aimed to explore the factors and treatment approaches influencing the prognosis of SCEC. In this retrospective study, we collected data from the 18 Surveillance, Epidemiology, and End Results (SEER) registries cohort between 2004 and 2019, as well as from a Chinese institutional registry covering the period from 2012 to 2022. We assessed the annual percentage change (APC) in incidence of SCEC. Kaplan-Meier and Cox regression analyses were conducted to evaluate survival outcomes. Additionally, nomograms were developed for overall survival (OS) and cancer-specific survival (CSS) in the SEER cohort for SCEC and validated in an independent Chinese cohort. This analysis included 299 SCEC patients from the SEER cohort and 66 cases from the Chinese cohort. During the period of 2004-2019, the incidence of SCEC reached a plateau, with an APC of -1.40 (95% confidence interval [CI]: -4.3 to 1.40, P > 0.05). Multivariable Cox regression analysis revealed that age, distant metastasis, and chemotherapy were independent factors for OS, while distant metastasis and chemotherapy were independent factors for CSS. The nomograms developed for OS and CSS in SCEC exhibited remarkable accuracy and reliable predictive capacity in estimating 1-year, 3-year, and 5-year OS and CSS. SCEC is a rare malignancy with aggressive behavior. Distant metastasis is significantly associated with worse OS and CSS in patients with SCEC. Currently, chemotherapy remains the primary treatment approach for SCEC.

Efficient protein extraction for assessing food allergy risk in complex alternative protein matrices.

Allergy to novel food proteins, due to diverse ingredients and innovative food processing technologies employed to achieve desired functional properties, is a major safety concern. Current allergy testing methods (ELISA and mass spectrometry) depend on high-quality protein extracts, meaning existing methods are often tailored to specific matrices. Therefore, a more efficient and general protein extraction method is desirable for comprehensive allergy risk assessment. Here, we developed a highly efficient and reproducible protein extraction method which achieved at least 80 % efficiency across several food matrices. Proteomics analysis of a plant-based meat using our optimized extraction method showed that higher extraction efficiency improved reproducibility of identified proteins. Moreover, higher protein extraction efficiency resulted in increased abundances of individual allergenic proteins. This underscores the relevance of our method for more accurate measurements of allergenic protein concentrations in allergy risk assessments.

The Asymmetrical Fe-O-Se Bonds in Fe2O(SeO3)2 Boosting Bifunctional Oxygen Electrocatalytic Performance for Zinc-Air Battery.

Zinc-air batteries (ZABs) have the advantages of high energy density and rich zinc raw materials. It is a low-cost, green and sustainable energy storage device. At present, one of the key technologies that hinder the large-scale application of ZABs is the design and fabrication oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) bifunctional catalysts with excellent performance, especially the non-platinum-based catalysts. Here N-doped carbon-coated Fe-based selenium oxide catalyst Fe2O(SeO3)2/Fe3C@NC with high performance has been fabricated by a one-step pyrolysis and then the electrochemical oxidization. The experimental results confirmed that the existence of Fe-O-Se bonds in Fe2O(SeO3)2 crystal phase of Fe2O(SeO3)2/Fe3C@NC, and the Fe-O-Se bonds could obviously enhance ORR and OER catalytic performance of Fe2O(SeO3)2/Fe3C@NC. Density functional theoretical calculations (DFT) confirmed that the Fe2O(SeO3)2 in Fe2O(SeO3)2/Fe3C@NC had a higher d-band center of Fe atom and a lower p-orbital coupling degree with its own lattice O atom than Fe2O3, which leads to Fe site of Fe2O(SeO3)2 being more likely to adsorb external oxygen intermediates. The Fe-O-Se bonds in Fe2O(SeO3)2 results in the modification of coordination environment of Fe atoms and optimizes the adsorption energy of Fe site for oxygen intermediates. Compared with Fe2O3/Fe3C@NC, the Fe2O(SeO3)2/Fe3C@NC showed the obvious enhancements of ORR/OER catalytic activities with a half-wave potential of 0.91 V for ORR in 0.1 M KOH electrolyte and a low overpotential of 345 mV for OER at 10 mA cm-2 in a 1.0 M KOH electrolyte. The peak power density and specific capacity of Fe2O(SeO3)2/Fe3C@NC-based ZABs are higher than those of Pt/C+RuO2-ZABs. The above results demonstrate that the asymmetrical Fe-O-Se bonds in Fe2O(SeO3)2 plays a key role in improving the bifunctional catalytic activities of ORR/OER for ZABs.

Breast Modular Resection (BMR) in Nipple-Sparing Mastectomy (NSM) With Intraoperative Laser Speckle Contrast Imaging (LSCI) Monitoring Improved Surgical Training Outcome Among Fellows.

BACKGROUND: Nipple-sparing mastectomy (NSM) and skin-sparing mastectomy (SSM) are challenging for surgical training among fellow trainees. We developed a surgical training course with novel concept of breast modular resection (BMR) for NSM/SSM procedure, and performed this study to investigate whether BMR could improve surgical outcomes compared to classical procedure resection (CPR). METHODS: The records of 105 breast cancer patients undergoing NSM/SSM with immediate reconstruction performed by fellow trainees were reviewed. Clinicopathological characteristics and surgical outcomes were compared between 2 groups. Laser speckle contrast imaging (LSCI) was performed to intraoperatively evaluate the blood supply of the NAC, and the absolute perfusion unit (PU) values and relative perfusion unit (rPU) values were further compared. RESULTS: Surgical training outcomes of BMR group (N = 52) were insignificantly improved compared to CPR group (N = 53). The rates of NAC necrosis, flap necrosis and implant removal all reduced respectively. Among the 60 NSM patients, the blood loss (P = .011) and surgery time (P < .001) was significantly reduced in BMR group (N = 30) and all the other outcomes were insignificantly improved. Both the absolute PU values and rPU values were significantly higher among patients without NAC necrosis (P < .001). The absolute PU values were significantly higher in BMR group (P = .002). CONCLUSION: Compared to CPR, the BMR-based surgical training course for NSM demonstrated the reduction in complications and operating time, offering a potential streamlined, efficient, and safe method for NSM procedure. LSCI was effective for intraoperative visualized evaluation of NAC blood supply and could provide effective real-time feedback for fellow trainees.

Caffeine and modafinil modulate the effects of sleep deprivation on thalamic resting-state functional connectivity: A double-blind pilot study.

BACKGROUND: Studies have found that the use of clinically approved caffeine and modafinil can alleviate cognitive impairment due to sleep deprivation (SD) to some extent. However, the neural mechanisms by which these two cognitive enhancers work to counteract the effects of SD on cognitive impairment remain unclear. METHODS: A double-blind within-subjects experiment using resting-state functional magnetic resonance imaging (rs-fMRI) was designed. Participants underwent three 36-h SD trials, each of which involved taking 200 mg of caffeine, modafinil, or placebo at the 28th and 32 nd h of SD. Sixteen subregions of the thalamus were selected as the regions of interest and changes in functional connectivity (FC) between the thalamus and the other brain regions were explored after the participants took caffeine or modafinil. RESULTS: The subjective sleepiness of the participants increased with the duration of SD. compared with placebo, modafinil and caffeine had insignificant effects on wakefulness or sleepiness. However, in terms of neural FC, we found varying degrees of attenuation or enhancement of the FC between the thalamus and other regions. Taking caffeine during SD weakened the FC between the right rostral temporal thalamus (rTtha) subregion and the left lingual gyrus compared with placebo. Caffeine enhanced the FC between three subregions of the thalamus, namely the left sensory thalamus, the left rTtha, and the right lateral pre-frontal thalamus, and the right inferior temporal, left orbitofrontal, and right superior occipital gyris. Modafinil weakened the FC between the right posterior parietal thalamus and left middle temporal gyrus, and enhanced the FC between the left medial pre-frontal thalamus, left rTtha, and right occipital thalamus and left middle frontal gyrus. CONCLUSIONS: After 36 h of total SD, modafinil and caffeine administration enhanced or attenuated the time-domain correlations between various subregions of the thalamus and brain regions of the frontal and temporal lobes in healthy adults, compared with placebo. These results provide valuable evidence for further unraveling the neuropharmacological mechanisms of caffeine and modafinil, as well as important insights for exploring effective pharmacological intervention strategies against SD.

Admission blood tests predicting survival of SARS-CoV-2 infected patients: a practical implementation of graph convolution network in imbalance dataset.

BACKGROUND: Predicting an individual's risk of death from COVID-19 is essential for planning and optimising resources. However, since the real-world mortality rate is relatively low, particularly in places like Hong Kong, this makes building an accurate prediction model difficult due to the imbalanced nature of the dataset. This study introduces an innovative application of graph convolutional networks (GCNs) to predict COVID-19 patient survival using a highly imbalanced dataset. Unlike traditional models, GCNs leverage structural relationships within the data, enhancing predictive accuracy and robustness. By integrating demographic and laboratory data into a GCN framework, our approach addresses class imbalance and demonstrates significant improvements in prediction accuracy. METHODS: The cohort included all consecutive positive COVID-19 patients fulfilling study criteria admitted to 42 public hospitals in Hong Kong between January 23 and December 31, 2020 (n = 7,606). We proposed the population-based graph convolutional neural network (GCN) model which took blood test results, age and sex as inputs to predict the survival outcomes. Furthermore, we compared our proposed model to the Cox Proportional Hazard (CPH) model, conventional machine learning models, and oversampling machine learning models. Additionally, a subgroup analysis was performed on the test set in order to acquire a deeper understanding of the relationship between each patient node and its neighbours, revealing possible underlying causes of the inaccurate predictions. RESULTS: The GCN model was the top-performing model, with an AUC of 0.944, considerably outperforming all other models (p < 0.05), including the oversampled CPH model (0.708), linear regression (0.877), Linear Discriminant Analysis (0.860), K-nearest neighbours (0.834), Gaussian predictor (0.745) and support vector machine (0.847). With Kaplan-Meier estimates, the GCN model demonstrated good discriminability between low- and high-risk individuals (p < 0.0001). Based on subanalysis using the weighted-in score, although the GCN model was able to discriminate well between different predicted groups, the separation was inadequate between false negative (FN) and true negative (TN) groups. CONCLUSION: The GCN model considerably outperformed all other machine learning methods and baseline CPH models. Thus, when applied to this imbalanced COVID survival dataset, adopting a population graph representation may be an approach to achieving good prediction.

Irinotecan plus raltitrexed as second­line chemotherapy for metastatic colorectal cancer: A retrospective study.

The present study evaluated the efficiency, prognostic factors for and the safety of irinotecan combined with raltitrexed (TOMIRI) in patients with metastatic colorectal cancer (CRC). Outcome data of patients who received TOMIRI as first-, second- and third- or later-line treatment regimens were assessed to compare the efficacy of this regimen. Progression-free survival (PFS), overall survival (OS), objective response rate (ORR) and disease control rate (DCR) were evaluated for each group. Kaplan-Meier curves and univariate and multivariate analyses were performed to evaluate efficacy. From January 2017 to December 2019, TOMIRI was administered as a first-line treatment in 23 patients, second-line treatment in 164 patients and third- or later-line treatment in 18 patients. Irinotecan and 5-fluorouracil (FOLFIRI) was administered to another 50 patients, who served as the control group. The median PFS was 9, 7 and 6 months and the median OS was 37, 21 and 17 months for first-, second- and third- or later-line treatments, respectively. The ORRs of the included patients were 21.7, 13.4 and 11.1%, respectively, and the DCRs were 91.3, 81.7 and 66.7%, respectively. Compared with FOLFIRI, TOMIRI as a second-line chemotherapy treatment was associated with longer survival of the patients with CRC. Further analysis demonstrated that pathologic tumor-node-metastasis category, carcinoembryonic antigen, carbohydrate antigen 19-9, treatment cycles, targeted therapy, treatment of local metastases and first-line PFS were prognostic factors for second-line treatment. Among these, the number of treatment cycles was of vital importance. Hepatic dysfunction was the most commonly reported grade 1-2 (55.1%) and grade 3-4 (7.3%) adverse event. Neutropenia (12.2%), thrombocytopenia (10.2%), anemia (27.3%), proteinuria (38.1%) and hematuria (21.0%) were also common grade 1-2 adverse events. In conclusion, TOMIRI may be recommended as an effective and safe second-line treatment for metastatic CRC in the clinic.

Pristine MOF Materials for Separator Application in Lithium-Sulfur Battery.

Lithium-sulfur (Li-S) batteries have attracted significant attention in the realm of electronic energy storage and conversion owing to their remarkable theoretical energy density and cost-effectiveness. However, Li-S batteries continue to face significant challenges, primarily the severe polysulfides shuttle effect and sluggish sulfur redox kinetics, which are inherent obstacles to their practical application. Metal-organic frameworks (MOFs), known for their porous structure, high adsorption capacity, structural flexibility, and easy synthesis, have emerged as ideal materials for separator modification. Efficient polysulfides interception/conversion ability and rapid lithium-ion conduction enabled by MOFs modified layers are demonstrated in Li-S batteries. In this perspective, the objective is to present an overview of recent advancements in utilizing pristine MOF materials as modification layers for separators in Li-S batteries. The mechanisms behind the enhanced electrochemical performance resulting from each design strategy are explained. The viewpoints and crucial challenges requiring resolution are also concluded for pristine MOFs separator in Li-S batteries. Moreover, some promising materials and concepts based on MOFs are proposed to enhance electrochemical performance and investigate polysulfides adsorption/conversion mechanisms. These efforts are expected to contribute to the future advancement of MOFs in advanced Li-S batteries.

Single-nucleus RNA-seq identifies one galanin neuronal subtype in mouse preoptic hypothalamus activated during recovery from sleep deprivation.

The preoptic area of the hypothalamus (POA) is essential for sleep regulation. However, the cellular makeup of the POA is heterogeneous, and the molecular identities of the sleep-promoting cells remain elusive. To address this question, this study compares mice during recovery sleep following sleep deprivation to mice allowed extended sleep. Single-nucleus RNA sequencing (single-nucleus RNA-seq) identifies one galanin inhibitory neuronal subtype that shows upregulation of rapid and delayed activity-regulated genes during recovery sleep. This cell type expresses higher levels of growth hormone receptor and lower levels of estrogen receptor compared to other galanin subtypes. single-nucleus RNA-seq also reveals cell-type-specific upregulation of purinergic receptor (P2ry14) and serotonin receptor (Htr2a) during recovery sleep in this neuronal subtype, suggesting possible mechanisms for sleep regulation. Studies with RNAscope validate the single-nucleus RNA-seq findings. Thus, the combined use of single-nucleus RNA-seq and activity-regulated genes identifies a neuronal subtype functionally involved in sleep regulation.

Recovery of nutrients from fish sludge to enhance the growth of microalga Chlorella sorokiniana CMBB276.

Intensive aquaculture production generates large amounts of sludge. This waste could be considered as a potential source of nutrients that can be recovered and utilized. Little attention has been paid to nutrient recovery from fish sludge. In this study, bioconversion of sludge was evaluated in lab scale under anaerobic (AN), facultative anaerobic (FA) and aerobic (AE) conditions. After 40 days of fermentation, AN recovered the highest values of dissolved total nitrogen (82.7 mg L-1), while AE showed the highest dissolved total phosphorus (11.8 mg L-1) and the highest reduction of total suspended solids (36.0 %). Microbial analysis showed that AN exhibited a distinct bacterial community than that of FA and AE. Furthermore, C. sorokiniana grown in AN effluents collected after 12 days of fermentation achieved the highest biomass production (1.96 g L-1). These results suggest that AN has the best potential to recover nutrients from sludge for production of C. sorokiniana.

Genetic Evidence for a Causal Relationship Between Innate Leukocytes and the Risk of Digestive System Cancers in East Asians and Europeans.

Background: Peripheral traditional immune cell disorder plays an important role in cancer onset and development. The causal relationships between leukocytes prior to cancer and the risk of digestive system cancer remain unknown. This study assesses the causal correlations between leukocytes and digestive system cancer risk in East Asians and Europeans. Methods: Summary-level data on leukocyte-related genetic variation were extracted from Biobank Japan (107,964 participants) and a recent large-scale meta-analysis (563,946 participants). Summary-level data for the cancers were obtained from Biobank Japan (212,978 individuals) and the FinnGen consortium (178,802 participants). Univariable and multivariable Mendelian randomization (MR) analyses were performed on East Asians and Europeans separately. Results: Univariable MR analysis demonstrated the significant association between circulating eosinophil counts and risk of colorectal cancer (CRC) in East Asians (odds ratio (OR) = 0.80, 95% confidence interval (CI): 0.69 - 0.92, P = 0.002) and a suggestive relationship in the European population (OR = 0.86, 95% CI: 0.77 - 0.97, P = 0.013). An inverse suggestive association was observed between levels of basophils and the risk of gastric cancer (GC) in East Asians (OR = 0.83, 95% CI: 0.72 - 0.97, P = 0.019). The multivariable MR analysis showed the independent causal effect of eosinophil count on CRC risk in East Asians (OR = 0.72, 95% CI: 0.57 - 0.92, P = 0.009) and Europeans (OR = 0.80, 95% CI: 0.70 - 0.92, P = 0.002). Circulating basophils served as the negative causal factor in GC risk in East Asians (OR = 0.80, 95% CI: 0.67 - 0.94, P = 0.007). Conclusions: Our MR analyses revealed a genetic causal relationship between reduced blood eosinophils and an increased CRC risk in both Europeans and East Asians. Furthermore, our results suggested a causal association between decreased basophils and an elevated GC risk specifically in East Asians.