Predicting photosynthetic bacteria-derived protein synthesis from wastewater using machine learning and causal inference.

Causal inference-assisted machine learning was used to predict photosynthetic bacterial (PSB) protein production capacity and identify key factors. The extreme gradient boosting algorithm effectively predicted protein content, while the gradient boosting decision tree algorithm excelled in predicting protein production, protein productivity, and protein energy yields. Driving factors were identified, with suitable ranges: protein content (pH 6.0-7.5, hydraulic retention time (HRT) < 3.8 d), protein production (biomass > 1.7 g, organic loading rate (OLR) > 9.2 gL-1d-1, temperature 26.7-35.0 °C), protein productivity (HRT < 3.5 d, biomass > 1.6 g, OLR > 10.0 gL-1d-1), and protein energy yields (light energy 0.1-4.4 kWh, biomass 1.7-65.0 g, chemical oxygen demand (COD) 0.1-2.5 gL-1). Illuminance, dissolved oxygen, COD, and COD/total nitrogen ratio were causal factors influencing protein production. Two-dimensional partial dependence plot revealed the interaction between two driving factors. This study enhances information on PSB protein production and offers insights for wastewater treatment and sustainable resource development.

Integrating UPLC-Q-Exactive Orbitrap/MS, Network pharmacology and experimental validation to reveal the potential mechanism of Kadsuracoccinea roots in Colon Cancer.

ETHNOPHARMACOLOGICAL RELEVANCE: Kadsura coccinea roots are a traditional folk medicine used to treat gastrointestinal diseases. In recent years, research on K. coccinea has predominantly focused on the analysis of chemical composition and screening for activity, but there is a scarcity of studies that employ mass spectrometry to analyze Kadsura coccinea roots. AIM OF THE STUDY: This study aimed to characterize the chemical composition of K. coccinea roots and explore the pharmacological mechanisms with network pharmacology. Cell assay and Western blot analysis were used to verify the pharmacological mechanism of the main compounds in K. coccinea roots. MATERIALS AND METHODS: UPLC-Q-Exactive Orbitrap/MS was used for chemical analysis of K. coccinea roots, and the compounds were identified by employing diagnostic product ions, fragmentation patterns, ChemSpider, and in-house databases. Network pharmacology was employed to estimate the pathways related to pharmacological mechanisms. In addition, MTT assay was conducted to determine the inhibitory activity of colon cancer cell lines, and their apoptotic abilities were evaluated by flow cytometry and Western blot. RESULTS: The UPLC-Q-Exactive Orbitrap/MS identified a total of 54 compounds in K. coccinea roots. The 54 compounds were subjected to network pharmacology analysis, exploring the pharmacological action of the main components of K. coccinea roots. The common targets between the compounds and colon cancer comprised 2009 GO biological process items and 186 KEGG signal pathways. Flow cytometry indicated that treatments with 20 µM of the above-named compounds resulted in an apoptosis rate of 16.6%, 79.7%, and 22.2% in HCT-116 cells, respectively. Meanwhile, Western blot analysis confirmed that the compounds promoted the expression of Bax and Caspase-3 level expression. CONCLUSION: The findings demonstrated that K. coccinea roots can treat colon cancer through multiple components, targets, and pathways. This study revealed the effective components and molecular mechanisms of K. coccinea, which were preliminarily verified using in vitro experiments.

Global patterns of lake microplastic pollution: Insights from regional human development levels.

Microplastics have emerged as a pervasive pollutant across various environmental media. Nevertheless, our understanding of their occurrence, sources, and drivers in global lakes still needs to be completed due to limited data. This study compiled data from 117 studies (2016-May 2024) on microplastic contamination in lake surface water and sediment, encompassing surface water samples in 351 lakes and lake sediment samples in 200 lakes across 43 countries. Using meta-analysis and statistical methods, the study reveals significant regional variability in microplastic pollution, with concentrations ranging from 0.09 to 207,500 items/m3 in surface water and from 5.41 to 18,100 items/kg in sediment. Most microplastics were under 1 mm in particle size, accounting for approximately 79 % of lake surface water and 76 % of sediment. Transparent and blue microplastics were the most common, constituting 34 % and 21 % of lake surface water and 28 % and 18 % of sediment, respectively. Fibers were the dominant shape, representing 47 % of lake surface water and 48 % of sediment. The primary identified polymer types were polyethylene (PE), polypropylene (PP), and polyethylene terephthalate (PET). Countries like India, Pakistan, and China had higher contamination levels. Positive correlations were found between microplastic abundance in surface water and factors like human footprint index (r = 0.29, p < 0.01), precipitation (r = 0.21, p < 0.05), and net surface solar radiation (r = 0.43, p < 0.001). In contrast, negative correlations were observed with the human development index (r = -0.61, p < 0.01) and wind speed (r = -0.42, p < 0.001). In sediment, microplastics abundance correlated positively with the human footprint index (r = 0.45, p < 0.001). This study underscores the variability in microplastic pollution in global lakes and the role of human activities and environmental factors, offering a valuable reference for future research.

Determination of Ibuprofen Enantiomers in Mouse Blood Using Liquid Chromatography-Tandem Mass Spectrometry and Its Application to a Pharmacokinetic Study.

The aim of this study was to establish a simple, fast, and sensitive method with liquid chromatography-tandem mass spectrometry (LC-MS/MS) for simultaneously determining ibuprofen enantiomers using mouse blood in very small volumes. LC-MS/MS equipped with an electrospray ionization (ESI) source was used in negative ion mode and multiple-reaction monitoring mode. Enantiomer chromatographic separation was carried out on a Lux® 5 µm Cellulose-3 (250 × 4.6 mm, 5 µm) column at a flow rate of 0.6 mL/min. Samples were pretreated by extracting only 5 µL of blood with 40 µL of acetonitrile (containing 1.3% formic acid) so that a concentration-time profile could be completed using a single mouse. 2-(4-Propylphenyl) propanoic acid was used as an internal standard. Standard curves for each enantiomer were linear from 0.04 to 80.00 µg/mL, demonstrating a lower limit of quantitation (LLOQ) than all previously reported methods. This method was completely validated and successfully executed to investigate the pharmacokinetics of ibuprofen enantiomers after intravenous administration of racemic ibuprofen, (S)-(+)-ibuprofen, and (R)-(-)-ibuprofen in Kunming mice, respectively. The results showed that the pharmacokinetic profiles of the (R)-(-)-ibuprofen and (S)-(+)-ibuprofen were significantly different, indicating the unidirectional inversion of R-(-)-ibuprofen to (S)-(+)-ibuprofen.

Effective extraction of Xuetongsu and its role in preventing RA synovial hyperplasia by targeting synovial cell migration and apoptosis.

Kadsura heteroclita (Roxb) Craib also named Xuetong in Tujia ethnomedicine in China, has been traditionally employed in rheumatoid arthritis (RA) treatment. Our preceding investigations have elucidated that Xuetongsu (XTS), a triterpenoid compound predominant in Xuetong, showed excellent anti-RA-fibroblast-like synoviocytes (RAFLS) proliferation effect. However, XTS belongs to the trace components of the Xuetong plant, which poses certain limitations to the research. In this study, we designed a method that enhanced the extraction yield of XTS and explored the mechanism of its inhibition of RAFLS cell proliferation and migration in the treatment of RA. The results displayed that XTS reduced RAFLS cell proliferation, with an IC50 value of 4.68 ± 0.65 µM. A series of experimental techniques were utilized to show that XTS induce apoptosis in RAFLS cells at concentrations ranging from 4.5 to 18 µM, including wound healing assay, flow cytometry, and western blot analysis. Moreover, XTS at dosages of 0.42-0.84 mg/kg markedly attenuated paw swelling and synovial hyperplasia in arthritic rats, primarily through the inhibition of RAFLS migration and promotion of RAFLS apoptosis via High mobility group box 1 (HMGB-1)/Matrix metalloproteinase-9 (MMP-9)/MMP-13 signaling pathway and Bcl-2/Bax/Caspase-3 signaling pathway, respectively.

Learning Motor Cues in Brain-Muscle Modulation.

Current studies for brain-muscle modulation often analyze selected properties in electrophysiological signals, leading to a partial understanding. This article proposes a cross-modal generative model that converts brain activities measured by electroencephalography (EEG) to corresponding muscular responses recorded by electromyography (EMG). Examining the generation process in the model highlights how the motor cue, representing implicit motor information hidden within brain activities, modulates the interaction between brain and muscle systems. The proposed model employs a two-stage generation process to bridge the semantic gap in cross-modal signals. Initially, the shared movement-related information between EEG and EMG signals is extracted using a contrastive learning framework. These shared representations act as conditional vectors in the subsequent EMG generation stage based on generative adversarial networks (GANs). Experiments on a self-collected multimodal electrophysiological signal data set show the algorithm's superiority over existing time series generative methods in cross-modal EMG generation. Further insights derived from the model's inference process underscore the brain's strategy for muscle control during movements. This research provides a data-driven approach for the neuroscience community, offering a comprehensive perspective of brain-muscular modulation.

Yeast culture enhances long-term fermentation of corn straw by ruminal microbes for volatile fatty acid production: Performance and mechanism.

Ruminal microbes can efficiently ferment biomass waste to produce volatile fatty acids (VFAs). However, keeping long-term efficient VFA production efficiency has become a bottleneck. In this study, yeast culture (YC) was used to enhance the VFA production in long-term fermentation. Results showed that YC group improved the volatile solid removal and VFA concentration to 47.8% and 7.82 g/L, respectively, 18.6% and 16.1% higher than the control, mainly enhancing the acetic, propionic, and butyric acid production. YC addition reduced the bacterial diversity, changed the bacterial composition, and improved interactions among bacteria. The regulation mechanism of YC was to increase the abundance and activity of hydrolytic and acidogenic bacteria such as Prevotella and Treponema, improve bacterial interactions, and further promote expression of functional genes. Ultimately, a long-term efficient ruminal fermentation of corn straw into VFAs was achieved.

Discovery of Potent and Selective Blockers Targeting the Epilepsy-Associated KNa1.1 Channel.

Gain-of-function (GOF) mutations of the sodium-activated potassium channel KNa1.1 (Slack, Slo2.2, or KCa4.1) induce severe, drug-resistant forms of epilepsy in infants and children. Although quinidine has shown promise in treating KCNT1-related epilepsies compared to other drugs, its limited efficacy and substantial side effects necessitate the development of new KNa1.1 channel inhibitors. In this study, we developed a novel class of KNa1.1 inhibitors using combined silico approaches and structural optimization. Among these inhibitors, compound Z05 was identified as a selective potential KNa1.1 inhibitor, especially against the hERG channel. Moreover, its binding site and potential counteraction to a GOF mutant Y796H were identified by the mutation studies. Our data also showed that Z05 had significant pharmacological profiles, including high brain penetration and moderate oral bioavailability, offering a valuable in vitro tool compound for further drug development in treating KCNT1-related epilepsies.

Long-Term Outcome of Low- and High-Dose Radioiodine for Thyroid Remnant Ablation.

OBJECTIVE: We conducted a prospective randomized clinical trial to compare the efficacy of low- and high-dose radioiodine for remnant ablation in patients with low-risk differentiated thyroid cancer (DTC) in China. The first-stage results showed equivalence was observed between the two groups. Here, we report recurrence and survival at 3-5 and 6-10 years and biochemical parameters. DESIGN, PATIENTS AND METHODS: Between January 2013 and December 2014, adult patients with DTC were enroled. Patients had undergone total or near-total thyroidectomy, with or without cervical lymph node dissection, with tumour stages T1-T3 with or without lymph node metastasis, but without distant metastasis. Patients were randomly assigned to the low-dose (1850 MBq) or high-dose (3700 MBq) radioiodine group. They were then followed up for 3-5 and 6-10 years. Data on biochemical abnormalities, recurrence and survival were analysed using Kolmogorov-Smirnov and χ2 tests. RESULTS: The data of 228 patients (mean age = 42 years; 70.6% women) were analysed, with 117 patients in the low-dose group and 111 in the high-dose group. There were no significant differences in biochemical abnormalities, recurrence, or survival rates at the 6-10-year follow-up (all p > .05). Nine patients experienced recurrence in the low-dose group (8.7%), while eight patients experienced recurrence in the high-dose group (8.2%). The survival rates were 100% and 98.2% in the low- and high-dose groups, respectively. CONCLUSIONS: The long-term effectiveness and safety of low-dose (1850 MBq) radioiodine are the same as those of high-dose (3700 MBq) radioiodine for thyroid remnant ablation in Chinese patients with low-risk DTC.

Metabolic network connectivity disturbances in Parkinson's disease: a novel imaging biomarker.

The diagnosis of Parkinson's Disease (PD) presents ongoing challenges. Advances in imaging techniques like 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) have highlighted metabolic alterations in PD, yet the dynamic network interactions within the metabolic connectome remain elusive. To this end, we examined a dataset comprising 49 PD patients and 49 healthy controls. By employing a personalized metabolic connectome approach, we assessed both within- and between-network connectivities using Standard Uptake Value (SUV) and Jensen-Shannon Divergence Similarity Estimation (JSSE). A random forest algorithm was utilized to pinpoint key neuroimaging features differentiating PD from healthy states. Specifically, the results revealed heightened internetwork connectivity in PD, specifically within the somatomotor (SMN) and frontoparietal (FPN) networks, persisting after multiple comparison corrections (P < 0.05, Bonferroni adjusted for 10% and 20% sparsity). This altered connectivity effectively distinguished PD patients from healthy individuals. Notably, this study utilizes 18F-FDG PET imaging to map individual metabolic networks, revealing enhanced connectivity in the SMN and FPN among PD patients. This enhanced connectivity may serve as a promising imaging biomarker, offering a valuable asset for early PD detection.

Assessing exit screening of SARS-CoV-2 in Japan: an analysis of the airport screening data of passengers from the United Kingdom, 2020-2022.

BACKGROUND: Japan implemented strict border control measures and all incoming passengers were subject to entry screening with reverse transcription-polymerase chain reaction or antigen testing. From late 2020, exit screening within 72 h of departure to Japan also became mandatory. In this study, we evaluated the effectiveness of the exit screening policy in Japan by analyzing airport screening data from October 2020 to April 2022. METHODS: In addition to assessing entry screening data over time of passengers from the United Kingdom, we examined the prevalence of coronavirus disease 2019 (COVID-19) in the United Kingdom based on the Office of National Statistics infection survey. We constructed a statistical model that described entry screening positivity over time using Office of National Statistics prevalence data as the explanatory variable. Ideally, the time-dependent patterns of entry screening and Office of National Statistics prevalence data should resemble each other; however, we found that, sometimes, they were different and regarded the difference to statistically partly reflect the effectiveness of exit screening. RESULTS: The average proportion positive in one month before mandatory exit screening was implemented among Japanese passengers was 0.67% (95% confidence interval [CI]: 0.45, 0.98), whereas the proportion positive decreased to 0.49% (95% CI: 0.21, 1.15) in the first month of exit screening. Adjusting for time-dependent prevalence at the origin, we concluded that exit screening contributed to reducing passenger positivity by 59.3% (95% CI: 19.6, 81.3). The overall positivity values among passengers during the Delta and Omicron variant periods were 3.46 times and 1.46 times that during the pre-Delta variant period, respectively. CONCLUSIONS: We used a simplistic statistical model and empirical data from passengers arriving in Japan from the United Kingdom to support that exit screening helped to reduce the proportion positive by 59%. Although the proportion positive later increased considerably and precluded preventing the introduction of imported cases, submitting a certificate for a negative test result contributed to reducing the positivity among travelers.

Electrical Contacts in Monolayer MoSi2N4 Transistors.

The latest synthesized monolayer (ML) MoSi2N4 material exhibits stability in ambient conditions, suitable bandgap, and high mobilities. Its potential as a next-generation transistor channel material has been demonstrated through quantum transport simulations. However, in practical two-dimensional (2D) material transistors, the electrical contacts formed by the channel and the electrode must be optimized, as they are crucial for determining the efficiency of carrier injection. We employed the density functional theory (DFT) combined with the nonequilibrium Green's function (NEGF) method to systematically explore the vertical and horizontal interfaces between the typical metal electrodes and the ML MoSi2N4. The DFT+NEGF method incorporates the coupling between the electrode and the channel, which is crucial for quantum transport. Among these metals, Sc and Ti form n-type Ohmic contacts with zero tunneling barriers at both vertical and horizontal interfaces with ML MoSi2N4, making them optimal for contact metals. In-ML MoSi2N4 contacts display zero Schottky barriers but a 3.11 eV tunneling barrier. Cu and Au establish n-type Schottky contacts, while Pt forms a p-type contact. The Fermi pinning factors of the metal-ML MoSi2N4 contacts for both electrons and holes are above 0.51, much higher than the typical 2D semiconductors. Moreover, there is a strong positive correlation between the Fermi pinning factor and the band gap, with a Spearman rank correlation coefficient of 0.897 and a p-value below 0.001. Our work provides insight into the contact optimization for the ML MoSi2N4 transistors and highlights the promising potential of ML MoSi2N4 as the channel material for the next-generation FETs.

Potential application of natural compounds in ischaemic stroke: Focusing on the mechanisms underlying "lysosomocentric" dysfunction of the autophagy-lysosomal pathway.

Ischaemic stroke (IS) is the second leading cause of death and a major cause of disability worldwide. Currently, the clinical management of IS still depends on restoring blood flow via pharmacological thrombolysis or mechanical thrombectomy, with accompanying disadvantages of narrow therapeutic time window and risk of haemorrhagic transformation. Thus, novel pathophysiological mechanisms and targeted therapeutic candidates are urgently needed. The autophagy-lysosomal pathway (ALP), as a dynamic cellular lysosome-based degradative process, has been comprehensively studied in recent decades, including its upstream regulatory mechanisms and its role in mediating neuronal fate after IS. Importantly, increasing evidence has shown that IS can lead to lysosomal dysfunction, such as lysosomal membrane permeabilization, impaired lysosomal acidity, lysosomal storage disorder, and dysfunctional lysosomal ion homeostasis, which are involved in the IS-mediated defects in ALP function. There is tightly regulated crosstalk between transcription factor EB (TFEB), mammalian target of rapamycin (mTOR) and lysosomal function, but their relationship remains to be systematically summarized. Notably, a growing body of evidence emphasizes the benefits of naturally derived compounds in the treatment of IS via modulation of ALP function. However, little is known about the roles of natural compounds as modulators of lysosomes in the treatment of IS. Therefore, in this context, we provide an overview of the current understanding of the mechanisms underlying IS-mediated ALP dysfunction, from a lysosomal perspective. We also provide an update on the effect of natural compounds on IS, according to their chemical structural types, in different experimental stroke models, cerebral regions and cell types, with a primary focus on lysosomes and autophagy initiation. This review aims to highlight the therapeutic potential of natural compounds that target lysosomal and ALP function for IS treatment.

Microbial carbon metabolism patterns of microplastic biofilm in the vertical profile of urban rivers.

Microplastics (MPs) can provide a unique niche for microbiota in waters, thus regulating the nutrients and carbon cycling. Following the vertical transport of MPs in waters, the compositions of attached biofilm may be dramatically changed. However, few studies have focused on the related ecological function response, including the carbon metabolism. In this study, we investigated the microbial carbon metabolism patterns of attached biofilm on different MPs in the vertical profile of urban rivers. The results showed that the carbon metabolism capacity of biofilm on the degradable polylactic acid (PLA) MPs was higher than that in the non-degradable polyethylene terephthalate (PET) MPs. In the vertical profile, the carbon metabolism rates of biofilm on two MPs both decreased with water depth, being 0.74 and 0.91 folds in bottom waters of that in surface waters. Specifically, the utilization of polymers, carbohydrate, and amine of PLA biofilm was significantly inhibited in the bottom waters, which were not altered on the PET. Compared with surface waters, the microbial metabolism function index of PLA biofilm was inhibited in deep waters, but elevated in the PET biofilm. In addition, the water quality parameters (e.g., nutrients) in the vertical profile largely shaped carbon metabolism patterns. These findings highlight the distinct carbon metabolism patterns in aquatic environments in the vertical profile, providing new insights into the effects of MPs on global carbon cycle.

Recent advances in methane and hydrogen production from lignocellulosic degradation with anaerobic fungi.

Anaerobic fungi (AF) efficiently degrade lignocellulosic biomass with unique pseudoroot system and enzymatic properties that can remove polysaccharides and some lignified components from plant cell walls, further releasing acetate, lactate, ethanol, hydrogen (H2), etc. As research on AF for bioengineering has become a hot topic, a review of lignocellulosic conversion with AF for methane (CH4) and H2 production is needed. Efficient degradation of lignocellulose with AF mainly relies on multiple free carbohydrate-active enzymes and cellulosomes in the free and bound state. Meanwhile, co-cultivation of AF and methanogens significantly improves the lignocellulose degradation and CH4 production, and the maximum CH4 yield reached 315 mL/g. Bioaugmentation of AF in anaerobic digestion increases the maximum CH4 yield by 330 %. Also, AF show H2 production potential, however, H2 yield from anaerobic fungal fermentation of lignocellulose remains low. Therefore, anaerobic fungi have great potential in the conversion of lignocellulosic biomass to CH4 and H2.

The Impact of Thermal Treatment Intensity on Proteins, Fatty Acids, Macro/Micro-Nutrients, Flavor, and Heating Markers of Milk-A Comprehensive Review.

Milk thermal treatment, such as pasteurization, high-temperature short-time processing, and the emerging ultra-short-time processing (<0.5 s), are crucial for ensuring milk safety and extending its shelf life. Milk is a nutritive food matrix with various macro/micro-nutrients and other constituents that are possibly affected by thermal treatment for reasons associated with processing strength. Therefore, understanding the relationship between heating strength and milk quality is vital for the dairy industry. This review summarizes the impact of thermal treatment strength on milk's nutritional and sensory properties, the synthesizing of the structural integrity and bioavailability of milk proteins, the profile and stability of fatty acids, the retention of macro/micro-nutrients, as well as the overall flavor profile. Additionally, it examines the formation of heat-induced markers, such as Maillard reaction products, lactulose, furosine, and alkaline phosphatase activity, which serve as indicators of heating intensity. Flavor and heating markers are commonly used to assess the quality of pasteurized milk. By examining former studies, we conclude that ultra-short-time-processing-treated milk is comparable to pasteurized milk in terms of specific parameters (such as whey protein behavior, furosine, and ALP contents). This review aims to better summarize how thermal treatments influence the milk matrix, guiding the dairy industry's development and balancing milk products' safety and nutritional value.

Efficacy and risk factors of stent placement in the treatment of malignant tracheoesophageal fistula.

Background: Due to the low incidence of malignant tracheoesophageal fistula and the paucity of relevant clinical studies, the benefits of stent implantation have not been well documented. It remains unclear which factors may affect fistula closure. Methods: Between January 2015 and January 2021, 344 patients who were diagnosed with malignant tracheoesophageal fistula at Zhongda Hospital, Southeast University, were retrospectively enrolled. Demographic and clinical data were collected. Risk factors for fistula closure identified by univariate analysis were further analyzed using multivariable logistic regression. Results: A total of 288 patients were analyzed in this study, of which 94 were treated conservatively, 170 were treated with an esophageal stent, and 24 were treated with a tracheal stent. Among them, the delta Karnofsky's performance status score values (after 2 weeks/before treatment [p = 0.0028], after 1 month/before treatment [p = 0.0103]) were significantly different between conservative and stent treatment. There was a significant reduction of pneumonia incidence in the stenting group (33.53%) compared to the conservative treatment group (77.05%) after one month (p <0.0001). In addition, the closure of fistulas was influenced by four independent risk factors: 1) treatment methods (p < 0.0001), 2) fistula size (p = 0.0003), 3) preoperative white blood cell count (p = 0.0042), and 4) preoperative Karnofsky's performance status score (p = 0.0001). Conclusions: Stent implantation has become an effective method for treating malignant tracheoesophageal fistula compared to conservative treatment. Additionally, stent implantation, smaller fistula size, lower preoperative white blood cell count, and higher preoperative Karnofsky's performance status score suggest a better outcome.

Multiplex influences on vigilance and biochemical variables induced by sleep deprivation.

Introduction: Sleep loss and sleep deprivation (SD) cause deleterious influences on health, cognition, mood and behaviour. Nevertheless, insufficient sleep and SD are prevalent across many industries and occur in various emergencies. The deleterious consequences of SD have yet to be fully elucidated. This study aimed to assess the extensive influences of SD on physiology, vigilance, and plasma biochemical variables. Methods: Seventeen volunteers were recruited to participate in a 32.5-h SD experiment. Multiple physiological and cognitive variables, including tympanic temperature, blood oxygen saturation (SaO2), and vigilance were recorded. Urinal/salivary samples were collected and subjected to cortisol or cortisone analysis, and plasma samples were subjected to transcriptomic analysis of circular RNA (circRNA) expression using microarray. Plasma neurotransmitters were measured by targeted metabolic analysis, and the levels of inflammatory factors were assessed by antibody microarray. Results: The volunteers showed significantly increased sleepiness and decreased vigilance during SD, and the changes in circadian rhythm and plasma biochemistry were observed. The plasma calcium (p = 0.0007) was induced by SD, while ischaemia-modified albumin (IMA, p = 0.0030) and total bile acid (TBA, p = 0.0157) decreased. Differentially expressed circRNAs in plasma were identified, which are involved in multiple signaling pathways including neuronal regulation and immunity. Accordingly, SD induced a decrease in 3-hydroxybutyric acid (3OBH, p = 0.0002) and an increase in thyroxine (T4, p < 0.0001) in plasma. The plasma anti-inflammatory cytokine IL-10 was downregulated while other ten inflammatory factors were upregulated. Conclusion: This study demonstrates that SD influences biochemical, physiological, cognitive variables, and the significantly changed variables may serve as candidates of SD markers. These findings may further our understanding of the detrimental consequence of sleep disturbance at multiple levels.

Cervical cancer segmentation based on medical images: a literature review.

Background and Objective: Cervical cancer clinical target volume (CTV) outlining and organs at risk segmentation are crucial steps in the diagnosis and treatment of cervical cancer. Manual segmentation is inefficient and subjective, leading to the development of automated or semi-automated methods. However, limitation of image quality, organ motion, and individual differences still pose significant challenges. Apart from numbers of studies on the medical images' segmentation, a comprehensive review within the field is lacking. The purpose of this paper is to comprehensively review the literatures on different types of medical image segmentation regarding cervical cancer and discuss the current level and challenges in segmentation process. Methods: As of May 31, 2023, we conducted a comprehensive literature search on Google Scholar, PubMed, and Web of Science using the following term combinations: "cervical cancer images", "segmentation", and "outline". The included studies focused on the segmentation of cervical cancer utilizing computed tomography (CT), magnetic resonance (MR), and positron emission tomography (PET) images, with screening for eligibility by two independent investigators. Key Content and Findings: This paper reviews representative papers on CTV and organs at risk segmentation in cervical cancer and classifies the methods into three categories based on image modalities. The traditional or deep learning methods are comprehensively described. The similarities and differences of related methods are analyzed, and their advantages and limitations are discussed in-depth. We have also included experimental results by using our private datasets to verify the performance of selected methods. The results indicate that the residual module and squeeze-and-excitation blocks module can significantly improve the performance of the model. Additionally, the segmentation method based on improved level set demonstrates better segmentation accuracy than other methods. Conclusions: The paper provides valuable insights into the current state-of-the-art in cervical cancer CTV outlining and organs at risk segmentation, highlighting areas for future research.

Flexocatalysis Enhances Tumor Photodynamic Therapy.

Photodynamic therapy (PDT) is long-standing suffered from elevated tumor interstitial fluid pressure (TIFP) and prevalent hypoxic microenvironment within the solid malignancies. Herein, sound-activated flexocatalysis is developed to overcome the dilemma of PDT through both enhancing tumor penetration of photosensitizers by reducing TIFP and establishing an oxygen-rich microenvironment. In detail, a Schottky junction is constructed by flexocatalyst MoSe2 nanoflowers and Pt. Subsequently, the Schottky junction is loaded with the photosensitizer indocyanine green (ICG) and encapsulated within tumor cytomembrane to constitute a bionic-flexocatalytic nanomedicine (MPI@M). After targeting the tumor, MPI@M orchestrates flexocatalytic water splitting in tumor interstitial fluid under acoustic stimulation to lower TIFP, which boosted the tumor penetration of ICG. Concurrently, the oxygen released from the flexocatalytic water splitting overcomes the limitation of hypoxia against PDT. Furthermore, superfluous singlet oxygen generated by PDT can induce mitochondrial dysfunction for further tumor cell apoptosis. After 60 min of flexocatalysis, both the 30% decrease of TIFP and the relieved tumor hypoxia are observed, significantly promoting the therapeutic effect of PDT. Consequently, MoSe2/Pt junction nanoflowers, with the excellent flexocatalytic performance, hold significant potential for future applications in biocatalytic cancer therapies.