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Abstract Background 2-oxoglutarate-dependent dioxygenase (2ODD) superfamily is the second largest enzyme family in the plant genome and plays diverse roles in secondary metabolic pathways. The medicinal plant Scutellaria baicalensis Georgi contains various flavonoids, which have the potential to treat coronavirus disease 2019 (COVID-19), such as baicalein and myricetin. Flavone synthase I (FNSI) and flavanone 3-hydroxylase (F3H) from the 2ODDs of DOXC subfamily have been reported to participate in flavonoids biosynthesis. It is certainly interesting to study the 2ODD members involved in the biosynthesis of flavonoids in S. baicalensis. Results We provided a genome-wide analysis of the 2ODDs of DOXC subfamily in S. baicalensis, a total of 88 2ODD genes were identified, 82 of which were grouped into 25 distinct clades based on phylogenetic analysis of At2ODDs. We then performed a functional analysis of Sb2ODDs involved in the biosynthesis of flavones and dihydroflavonols. Sb2ODD1 and Sb2ODD2 from DOXC38 clade exhibit the activity of FNSI (Flavone synthase I), which exclusively converts pinocembrin to chrysin. Sb2ODD1 has significantly higher transcription levels in the root. While Sb2ODD7 from DOXC28 clade exhibits high expression in flowers, it encodes a F3H (flavanone 3-hydroxylase). This enzyme is responsible for catalyzing the conversion of both naringenin and pinocembrin into dihydrokaempferol and pinobanksin, kinetic analysis showed that Sb2ODD7 exhibited high catalytic efficiency towards naringenin. Conclusions Our experiment suggests that Sb2ODD1 may serve as a supplementary factor to SbFNSII-2 and play a role in flavone biosynthesis specifically in the roots of S. baicalensis. Sb2ODD7 is mainly responsible for dihydrokaempferol biosynthesis in flowers, which can be further directed into the metabolic pathways of flavonols and anthocyanins.

Abstract Objective The purpose of this study was to translate and validate the reliability and validity of the Falls Health Literacy Scale (FHLS). Methods A total of 509 elderly hospitalized patients were recruited from Wuhan, China. The reliability of the scale was validated using internal consistency, split-half reliability and retest reliability. The validity of the scale with content validity index, exploratory factor analysis and validation factor analysis. Results The Chinese version of the FHLS consists of 3 dimensions, falls prevention experience, general health and staying active, and seeking health advice and services, with a total of 25 entries. The Cronbach’s α coefficient of the scale was 0.949, the range of Cronbach’s α values for each dimension was 0.911 to 0.927, the split-half reliability was 0.800, and the retest reliability was 0.801. The I-CVI of the scale ranged from 0.833 to 1.000, and the S-CVI was 0.973. The KMO value was 0.925, and the χ2 value of Bartlett’s sphericity test was 5,784.223 (P

Dockless bicycle-sharing system substantially impacts the present docked bicycle-sharing usage in the urban transportation system. This study explores such effects using usage data of docked bicycle-sharing systems in Xi’an before and after launching the dockless bicycle-sharing system. The influence period is divided into the no-influence stage, transition stage, and stabilization stage. The hotspot analysis method is employed to identify the most influenced areas. The geographically weighted regression model is then revised to determine the response of socioeconomic factors considering the launches of the dockless bicycle-sharing system. The results reveal that the critical impact of the dockless bicycle-sharing system on the docked system. Specifically, the weekly usage share of docked bicycle-sharing declined ranged from 0.51 % to 41.4 % in transition stage. Furthermore, population density, job density, per capita income, and per capita GDP are identified as the key contributing factors based on spatial analysis, where for each 1 % increase in the four indicators, docked bicycle-sharing system’s usage decreases by 1.014 %, 1.182 %, 2.021 %, and 0.904 %, respectively.

Abstract Anti-programmed death 1/programmed death ligand 1 (anti-PD-1/PD-L1) antibodies exert significant antitumor effects by overcoming tumor cell immune evasion and reversing T-cell exhaustion. However, the emergence of drug resistance causes most patients to respond poorly to these immune checkpoint inhibitors (ICIs). Studies have shown that insufficient T-cell infiltration, lack of PD-1 expression, deficient interferon signaling, loss of tumor antigen presentation, and abnormal lipid metabolism are all considered to be closely associated with immunotherapy resistance. To address drug resistance in tumor immunotherapy, a lot of research has concentrated on developing combination therapy strategies. Currently, ICIs such as anti-PD-1 /PD-L1 antibody combined with chemotherapy and targeted therapy have been approved for clinical treatment. In this review, we analyze the mechanisms of resistance to anti-PD-1/PD-L1 therapy in terms of the tumor microenvironment, gut microbiota, epigenetic regulation, and co-inhibitory immune checkpoint receptors. We also discuss various promising combination therapeutic strategies to address resistance to anti-PD-1/PD-L1 drugs, including combining these therapies with traditional Chinese medicine, non-coding RNAs, targeted therapy, other ICIs, and personalized cancer vaccines. Moreover, we focus on biomarkers that predict resistance to anti-PD-1/PD-L1 therapy as well as combination therapy efficacy. Finally, we suggest ways to further expand the application of immunotherapy through personalized combination strategies using biomarker systems.

The utilization of radiant floor systems is one effective method to address the increasing cooling demand. The radiant floor cooling system (RFCS) has self-regulating capabilities, which benefit grid stability and the use of renewable energy. The application performance of RFCS is based on system design and intelligent control, as systems with high thermal inertia make it difficult to provide ideal indoor response effects. Therefore, this review aims to summarize the current development status of RFCSs and evaluate future development directions based on relevant research trends. A comprehensive overview of the radiant floor structure and the composition of RFCS were provided. The type of radiant floor structures can bring greater possibilities for the application of RFCS. Then, system control and evaluation are analyzed, with research on anti-condensation of radiant floors mainly focused on system and environmental control. Based on application status of the RFCS, the impact of various factors is discussed, including condensation risks, and climate change. Resistance to disturbances not only requires implementing control measures but also integrating with the building environment. There is still great potential for the hardware design and multi-directional integration of RFCS. The results of this review help relevant researchers gain a comprehensive understanding of the current development status and prospects of RFCS contributing to the decarbonization of the construction industry.

Osteochondral lesions are common pathological alterations in synovial joints. Different techniques have been designed to achieve osteochondral repair, and tissue-engineered osteochondral grafts have shown the most promise. Histological assessments and related scoring systems are crucial for evaluating the quality of regenerated tissue, and the interpretation and comparison of various repair techniques require the establishment of a reliable and widely accepted histological method. To date, there is still no consensus on the type of histological assessment and scoring system that should be used for osteochondral repair. In this review, we summarize common osteochondral staining methods, discuss the criteria regarding high-quality histological images, and assess the current histological scoring systems for osteochondral regeneration. Safranin O/Fast green is the most widely used staining method for the cartilage layer, whereas Gomori and Van Gieson staining detect new bone formation. We suggest including the graft–host interface and more sections together with the basic histological information for images. An ideal scoring system should analyze both the cartilage and bone regions, especially for the subchondral bone plate. Furthermore, histological assessments should be performed over a longer period of time to minimize discrepancies caused by defect size and animal species.

The rise of e-commerce, bolstered by advancements in information and communication technology (ICT), has made it possible for consumers to shop online without the need to physically travel. The unexpected emergence of COVID-19 further accelerated this shift towards online shopping. This paper delves into the nuances of virtual versus physical access to goods, drawing from the dual access theory. It aims to offer a comprehensive understanding of the disparities in accessibility between digital and brick-and-mortar shopping experiences. Our results indicate that when considering the complete private costs—including the intrinsic costs of shopping and those incurred en route like travel and delivery fees—online shopping typically offers greater accessibility and is more cost-effective than its in-store counterpart. Interestingly, while physical access to shopping displays a pattern where the central city has a distinct advantage over the suburbs, virtual access presents a more uniform distribution throughout the city.

Abstract How communities of living organisms assemble has long been a central question in ecology. The impact of habitat filtering and limiting similarity on plant community structures is well known, as both processes are influenced by individual responses to environmental fluctuations. Yet, the precise identifications and quantifications of the potential abiotic and biotic factors that shape community structures at a fine scale remains a challenge. Here, we applied null model approaches to assess the importance of habitat filtering and limiting similarity at two spatial scales. We used 63 natural vegetation plots, each measuring 5 × 5 m, with three nested subplots measuring 1 × 1 m, from the 2021 field survey, to examine the alpha diversity as well as beta diversity of plots and subplots. Linear mixed‐effects models were employed to determine the impact of environmental variables on assembly rules. Our results demonstrate that habitat filtering is the dominant assembly rules at both the plot and subplot levels, although limiting similarity assumes stronger at the subplot level. Plot‐level limiting similarity exhibited a positive association with fine‐scale partitioning, suggesting that trait divergence originated from a combination of limiting similarity and spatial partitioning. Our findings also reveal that the community assembly varies more strongly with the mean annual temperature gradient than the mean annual precipitation. This investigation provides a pertinent illustration of non‐random assembly rules from spatial scale and environmental factors in plant communities in the loess hilly region. It underscores the critical influence of spatial and environmental constraints in understanding the assembly of plant communities.

Abstract Background The organizational climate that fosters and supports the implementation of evidence is a key factor influencing the effective implementation of evidence-based practice (EBP). Nurses, being the largest group of medical staff, play a crucial role in EBP implementation. The perception of the climate for EBP implementation among nurses in their organizations is unknown, especially among Chinese nurses. Aims To clarify the implementation climate of EBP among Chinese nurses and identify the factors associated with the implementation and development of evidence-based nursing practices. Methods This study employed a descriptive cross-sectional study design. From March 2023 to April 2023, a sample of nurses (n = 1260) from two Tertiary care hospitals in central China were selected and surveyed by self-designed social-demographic questionnaire and Implementation Climate Scale. Multiple linear stepwise regression analysis was conducted to determine the predictors of implementation climate. Results The nurses achieved a mean ICS score of 59.10 ± 11.22, with mean scores exceeding 3 points for each sub-dimension and item. In the results of multiple linear regression, income satisfaction, implementation of evidence-based nursing practice project(s) within the unit, experience of evidence-based nursing practice during working life, and specific training or courses in evidence-based nursing practice were predictors of ICS. Of these, income satisfaction was the most significant predictor. These factors could explain 17.5% of the total variance in implementation climate. Conclusion The climate for implementing EBP in Chinese nursing organizations was relatively strong. Nursing managers can enhance the climate for implementing EBP in their organizations by actively improving salary and enhancing EBP-related trainings and practices. Relevance to clinical practice Understanding nurses’ perceptions of the EBP implementation climate in their organizations can help to identify specific barriers and facilitators to the development of EBP and facilitate its successful implementation. Patient or public contribution Clinical nurses were involved in data collection and completed the questionnaires on EBP implementation climate.

Abstract Background The status of anastomotic blood perfusion is associated with the occurrence of anastomotic leakage after intestinal anastomosis. Fluorescence angiography (FA) with indocyanine green (ICG) can objectively assess intestinal blood perfusion. This study aims to investigate whether anastomotic perfusion assessment with ICG influences surgical decision-making during laparoscopic intestinal resection and primary anastomosis for colonic stricture after necrotizing enterocolitis. Methods Patients who underwent laparoscopic intestinal resection and primary anastomosis between January 2022 and December 2022 were retrospectively analyzed. Before intestinal anastomosis, the ICG fluorescence technology was used to evaluate the blood perfusion of intestinal tubes on both sides of the anastomosis. After the completion of primary anastomosis, the anastomotic blood perfusion was assessed again. Results Of the 13 cases, laparoscopy was used to determine the extent of the diseased bowel to be excised, and the normal bowel was preserved for anastomosis. The anastomosis was established under the guidance of ICG fluorescence technology, and FA was performed after anastomosis to confirm good blood flow in the proximal bowel. The anastomotic intestinal tube was changed in one case because FA showed a difference between the normal range of intestinal blood flow and the macroscopic prediction. There was no evidence of ICG allergy, anastomotic leakage, anastomotic stricture, or other complications. The median follow-up was 6 months, and all patients recovered well. Conclusions The ICG fluorescence technology is helpful in precisely and efficiently determining the anastomotic intestinal blood flow during stricture resection and in avoiding anastomotic leakage caused by poor anastomotic intestinal blood flow to some extent, with satisfactory short-term efficacy.

Machine learning algorithms have proven to be practical in a wide range of applications. Many studies have been conducted on the operational energy consumption and thermal comfort of radiant floor systems. This paper conducts a case study in a self-designed experimental setup that combines radiant floor and fan coil cooling (RFCFC) and develops a data monitoring system as a source of historical operational data. Seven machine learning algorithms (extreme learning machine (ELM), convolutional neural network (CNN), genetic algorithm-back propagation (GA-BP), radial basis function (RBF), random forest (RF), support vector machine (SVM), and long short-term memory (LSTM)) were employed to predict the behavior of the RFCFC system. Corresponding prediction models were then developed to evaluate operative temperature (Top) and energy consumption (Eh). The performance of the model was evaluated using five error metrics. The obtained results showed that the RF model had very high performance in predicting Top and Eh, with high correlation coefficients (>0.9915) and low error metrics. Compared with other models, it also demonstrated high accuracy in Eh prediction, yielding maximum reductions of 68.1, 82.4, and 43.2% in the mean absolute percentage error (MAPE), mean squared error (MSE), and mean absolute error (MAE), respectively. A sensitivity ranking algorithm analysis was also conducted. The obtained results demonstrated the importance of adjusting parameters, such as the radiant floor supply water temperature, to enhance the indoor comfort. This study provides a novel and effective method for evaluating the energy efficiency and thermal comfort of radiant cooling systems. It also provides insights for optimizing the efficiency and thermal comfort of RFCFC systems, and lays a theoretical foundation for future studies integrating machine learning algorithms in this field.

Single-cell sequencing (SCS) technology is changing our understanding of cellular components, functions, and interactions across organisms, because of its inherent advantage of avoiding noise resulting from genotypic and phenotypic heterogeneity across numerous samples. By directly and individually measuring multiple molecular characteristics of thousands to millions of single cells, SCS technology can characterize multiple cell types and uncover the mechanisms of gene regulatory networks, the dynamics of transcription, and the functional state of proteomic profiling. In this context, we conducted systematic research on SCS techniques, including the fundamental concepts, procedural steps, and applications of scDNA, scRNA, scATAC, scCITE, and scSNARE methods, focusing on the unique clinical advantages of SCS, particularly in cancer therapy. We have explored challenging but critical areas such as circulating tumor cells (CTCs), lineage tracing, tumor heterogeneity, drug resistance, and tumor immunotherapy. Despite challenges in managing and analyzing the large amounts of data that result from SCS, this technique is expected to reveal new horizons in cancer research. This review aims to emphasize the key role of SCS in cancer research and promote the application of single-cell technologies to cancer therapy.

Increased frequency and intensity of droughts under climate change will have a significant impact on land surface phenology, however, the drought-phenology interactions that are associated with complex temporal effects are not well understood. This study examined the response of land surface phenology to drought cumulative and time-lag effects by using the standardized precipitation and evapotranspiration index (SPEI) and explored the influence of hydrothermal and plant physiological factors on the phenology-drought relationship. We used the maximum correlation (rmax-cml) between phenology and cumulative SPEI (1- to 12-month) to determine the cumulative effect. The maximum correlation (rmax-lag) between phenology and lagged SPEI (1-month) was utilized to analyze the time-lag effect. Overall, the cumulative effect affected 25.36% of the vegetated area at the start of the growing season (SOS), 26.43% of the end of the growing season (EOS), and 26.57% of the length of the growing season (LOS). SOS was negatively affected by long-term SPEI, whereas EOS and LOS had positive correlations with short-term SPEI. The rmax-cml for shrubland was the largest, and the SOS and LOS response time scales of the forest were the shortest. The rmax-cml was larger in arid and semi-arid (AR and SAR) than in humid and semi-humid (HU and SHU). Meanwhile, the response time scales were longer in HU and SHU than in AR and SAR. The time-lag effect had a larger area of impact on land surface phenology than the cumulative effect, the areas were 46.12%, 47.93%, and 50.45% for SOS, EOS, and LOS, respectively, and the lagged time scales were longer. The phenology-SPEI correlation was dominantly driven by hydrological conditions, and the time scales were mainly affected by thermal factors. Moreover, the onset of phenology and the growth/senescence rate of plants influenced the relationship, suggesting that hydrothermal conditions may shift the time of phenology by regulating the growth/senescence rate and may thus modulate the phenology–drought interaction.

Abstract Background Flavonoid glycosides extracted from roots of Scutellaria baicalensis exhibit strong pharmaceutical antitumor, antioxidative, anti-inflammatory, and antiviral activities. UDP glycosyltransferase (UGT) family members are responsible for the transfer of a glycosyl moiety from UDP sugars to a wide range of acceptor flavonoids. Baicalin is the major flavonoid glycoside found in S. baicalensis roots, and its aglycone baicalein is synthesized from a specially evolved pathway that has been elucidated. However, it is necessary to carry out a genome-wide study of genes involved in 7-O-glucuronidation, the final biosynthesis step of baicalin, which might elucidate the relationship between the enzymes and the metabolic accumulation patterns in this medicinal plant. Results We reported the phylogenetic analysis, tissue-specific expression, biochemical characterization and evolutionary analysis of glucosyltransferases (SbUGTs) and glucuronosyltransferases (SbUGATs) genes based on the recently released genome of S. baicalensis. A total of 124 UGTs were identified, and over one third of them were highly expressed in roots. In vitro enzyme assays showed that 6 SbUGTs could use UDP-glucose as a sugar donor and convert baicalein to oroxin A (baicalein 7-O-glucoside), while 4 SbUGATs used only UDP-glucuronic acid as the sugar donor and catalyzed baicalein to baicalin. SbUGAT4 and SbUGT2 are the most highly expressed SbUGAT and SbUGT genes in root tissues, respectively. Kinetic measurements revealed that SbUGAT4 had a lower Km value and higher Vmax/Km ratio to baicalein than those of SbUGT2. Furthermore, tandem duplication events were detected in SbUGTs and SbUGATs. Conclusions This study demonstrated that glucosylation and glucuronidation are two major glycosylated decorations in the roots of S. baicalensis. Higher expression level and affinity to substrate of SbUGAT4, and expansion of this gene family contribute high accumulation of baicalin in the root of S. baicalensis.

The station-level ridership during the peak hour is one of the key indicators for the design of station size and relevant facilities. However, with the operation of metro system, it cannot be ignored that, in many cities, the station peak and the city peak may not be simultaneously occurred. As the current ridership forecasting methods use the city peak as the point of reference, stations with wide differences of ridership in between would experience disorders due to serious underestimates of passenger demand during the actual peak. Accordingly, this study fully considers the phenomenon that the metro station peak is not identical to the city peak and focuses on the concept of the peak deviation coefficient (PDC), the ratio of the station peak ridership to the city peak ridership. It investigates how metro ridership determinants affects the PDC using the least square support vector machine (LSSVM) model. A land-use function complementarity index is employed as one of the independent variables, which is newly proposed in this study that describes the relationship of the commute land use around an individual station with that along the whole network. This method can help to resolve the ridership amplification indicator for a fine-grained station-level forecasting. The results for Xi'an metro indicate that the LSSVM is an effective method to scrutinize the nonlinear effects of e.g., land use attributes, on the temporal distribution features of the metro ridership. Compared to the ratio of commute land use measured for individual stations, the land-use function complementarity index can better explain and predict the severity of peak deviation phenomenon, controlling other independent variables in the model.

This paper investigates the spatial dependency of job and worker densities for the Minneapolis–St. Paul (Twin Cities) metropolitan area using census block level data from 2002 to 2017. A spatial weight matrix is proposed, considering the statistical expression of data, referred to as the correlation matrix, which detects the variations of dependencies among spatial units in both direction and level. The superior performance of the correlation matrix is demonstrated through a series of spatial regression models to predict land use patterns, in comparison with the conventionally used adjacency matrix as well as the accessibility matrix.

A retrospective analysis was performed from May 2003 to October 2021 at our hospital. One hundred and eleven neonates diagnosed with gastric perforation were categorized into non-survivor and survivor groups based on prognosis. The mortality rate was 23.42%. Logistic regression was used to analyze the factors influencing the early neonatal death. The non-survivor groups showed more abdominal distension, vomiting, hypoxia, acidosis, hyperkalemia, and coagulation abnormalities. Serum potassium concentration (odds ratio [OR] 2.148, P =.043) was an independent risk factor; however, arterial partial pressure of oxygen (OR 0.977, P =.024), bicarbonate (OR 0.779, P =.023), and platelet count (OR 0.986, P =.014) had protective effects on neonatal death. Based on this, a visualized nomogram prediction model was constructed, patients who had a nomogram score of more than 163.787 was considered to have high risks of mortality, the area under the curve of this was up to 0.828 (95% confidence interval [0.733, 0.923]), the sensitivity was 80.0%, and the specificity was 76.9%. [ABSTRACT FROM AUTHOR]

Abstract Pancreatic cancer is one of the most malignant tumors worldwide, and pancreatic ductal adenocarcinoma is the most common type. In pancreatic cancer, glycolysis is the primary way energy is produced to maintain the proliferation, invasion, migration, and metastasis of cancer cells, even under normoxia. However, the potential molecular mechanism is still unknown. From this perspective, this review mainly aimed to summarize the current reasonable interpretation of aerobic glycolysis in pancreatic cancer and some of the newest methods for the detection and treatment of pancreatic cancer. More specifically, we reported some biochemical parameters, such as newly developed enzymes and transporters, and further explored their potential as diagnostic biomarkers and therapeutic targets.

Hepatocellular carcinoma (HCC) has a poor prognosis due to its high malignancy, rapid disease progression, and the presence of chemotherapy resistance. Long-stranded non-coding RNAs (lncRNAs) affect many malignant tumors, including HCC. However, their mechanism of action in HCC remains unclear. This study aimed to clarify the role of DUXAP8 in regulating the malignant phenotype and chemotherapy resistance in HCC. Using an in vivo xenograft tumor model, the regulatory functions and mechanisms of lncRNA DUXAP8 in the progression and response of HCC to chemotherapy were explored. It was found that DUXAP8 was significantly upregulated in a patient-derived xenograft tumor model based on sorafenib treatment, which is usually associated with a relatively poor prognosis in patients. In HCC, DUXAP8 maintained its upregulation in the expression by increasing the stability of m6A methylation-mediated RNA. DUXAP8 levels were positively correlated with the proliferation, migration, invasion, and chemotherapy resistance of HCC in vivo and in vitro. In the mechanistic study, it was found that DUXAP8 competitively binds to miR-584-5p through a competing endogenous RNA (ceRNA) mechanism, thus acting as a molecular sponge for miR-584-5p to regulate MAPK1 expression, which in turn activates the MAPK/ERK pathway. These findings can provide ideas for finding new prognostic indicators and therapeutic targets for patients with HCC.

Surgical treatment is the only possible cure for cholangiocarcinoma (CCA) at present. However, the high recurrence rate of postoperative CCA leads to a very poor prognosis for patients, effective postoperative chemotherapy is hence the key to preventing the recurrence of CCA. The sensitivity of CCA to cytotoxic chemotherapy drugs and targeted drugs varies from person to person, and therefore, the screening of sensitive drugs has become an important topic after CCA surgeries. Patient-Derived tumor Xenograft models (PDX) can stably retain the genetic and pathological characteristics of primary tumors, and better simulate the tumor microenvironment of CCA. The model is also of great significance in screening therapeutic targeted drugs after CCA, analyzing predictive biomarkers, and improving signal pathways in prognosis and basic research. This paper will review the current established methods and applications of the patient-derived tumor xenograft model of cholangiocarcinoma, aiming to provide new ideas for basic research and individualized treatment of cholangiocarcinoma after surgery.

Tripterygium wilfordii is a vine from the Celastraceae family that is used in traditional Chinese medicine (TCM). The active ingredient, celastrol, is a friedelane-type pentacyclic triterpenoid with putative roles as an antitumor, immunosuppressive, and anti-obesity agent. Here, we report a reference genome assembly of T. wilfordii with high-quality annotation using a hybrid sequencing strategy. The total genome size obtained is 340.12 Mb, with a contig N50 value of 3.09 Mb. We successfully anchored 91.02% of sequences into 23 pseudochromosomes using high-throughput chromosome conformation capture (Hi–C) technology. The super-scaffold N50 value was 13.03 Mb. We also annotated 31,593 structural genes, with a repeat percentage of 44.31%. These data demonstrate that T. wilfordii diverged from Malpighiales species approximately 102.4 million years ago. By integrating genome, transcriptome and metabolite analyses, as well as in vivo and in vitro enzyme assays of two cytochrome P450 (CYP450) genes, TwCYP712K1 and TwCYP712K2, it is possible to investigate the second biosynthesis step of celastrol and demonstrate that this was derived from a common ancestor. These data provide insights and resources for further investigation of pathways related to celastrol, and valuable information to aid the conservation of resources, as well as understand the evolution of Celastrales.

The water components affecting turbidity are complex and changeable, and the spectral response mechanism of each water quality parameter is different. Therefore, this study mainly aimed at the turbidity monitoring by unmanned aerial vehicle (UAV) hyperspectral technology, and establishes a set of turbidity retrieval models through the artificial control experiment, and verifies the model’s accuracy through UAV flight and water sample data in the same period. The results of this experiment can also be extended to different inland waters for turbidity retrieval. Retrieval of turbidity values of small inland water bodies can provide support for the study of the degree of water pollution. We collected the images and data of aquaculture ponds and irrigation ditches in Dawa District, Panjin City, Liaoning Province. Twenty-nine standard turbidity solutions with different concentration gradients (concentration from 0 to 360 NTU—the abbreviation of Nephelometric Turbidity Unit, which stands for scattered turbidity.) were established through manual control and we simultaneously collected hyperspectral data from the spectral values of standard solutions. The sensitive band to turbidity was obtained after analyzing the spectral information. We established four kinds of retrieval, including the single band, band ratio, normalized ratio, and the partial least squares (PLS) models. We selected the two models with the highest R2 for accuracy verification. The band ratio model and PLS model had the highest accuracy, and R2 was, respectively, 0.65 and 0.72. The hyperspectral image data obtained by UAV were combined with the PLS model, which had the highest R2 to estimate the spatial distribution of water turbidity. The turbidity of the water areas in the study area was 5–300 NTU, and most of which are 5–80 NTU. It shows that the PLS models can retrieve the turbidity with high accuracy of aquaculture ponds, irrigation canals, and reservoirs in Dawa District of Panjin City, Liaoning Province. The experimental results are consistent with the conclusions of the field investigation.

Mitochondrial and lysosomal functions are intimately linked and are critical for cellular homeostasis, as evidenced by the fact that cellular senescence, aging, and multiple prominent diseases are associated with concomitant dysfunction of both organelles. However, it is not well understood how the two important organelles are regulated. Transcription factor EB (TFEB) is the master regulator of lysosomal function and is also implicated in regulating mitochondrial function; however, the mechanism underlying the maintenance of both organelles remains to be fully elucidated. Here, by comprehensive transcriptome analysis and subsequent chromatin immunoprecipitation-qPCR, we identified hexokinase domain containing 1 (HKDC1), which is known to function in the glycolysis pathway as a direct TFEB target. Moreover, HKDC1 was upregulated in both mitochondrial and lysosomal stress in a TFEB-dependent manner, and its function was critical for the maintenance of both organelles under stress conditions. Mechanistically, the TFEB–HKDC1 axis was essential for PINK1 (PTEN-induced kinase 1)/Parkin-dependent mitophagy via its initial step, PINK1 stabilization. In addition, the functions of HKDC1 and voltage-dependent anion channels, with which HKDC1 interacts, were essential for the clearance of damaged lysosomes and maintaining mitochondria–lysosome contact. Interestingly, HKDC1 regulated mitophagy and lysosomal repair independently of its prospective function in glycolysis. Furthermore, loss function of HKDC1 accelerated DNA damage–induced cellular senescence with the accumulation of hyperfused mitochondria and damaged lysosomes. Our results show that HKDC1, a factor downstream of TFEB, maintains both mitochondrial and lysosomal homeostasis, which is critical to prevent cellular senescence. [ABSTRACT FROM AUTHOR]

Eutrophication is considered to be a significant threat to estuaries and coastal waters. Various localized studies on the world’s oceans have recognized and confirmed that the Forel-Ule Color Index (FUI) or optical measurements are proportional to several water quality variables based on the relatively clear Chl-a-based waters. However, the application potential of FUI in the turbid estuary with complex optics has not been explored. In this study, we selected the coastal waters in the northern Liaodong Bay as the study area, using the field hyperspectral reflectances (Rrs) collected in 2018 to correct the hue angle and verify the Sentinel-2 images algorithm of FUI by in situ FUI in 2019–2020. The results show that there is a good agreement (R2 = 0.81, RMSE = 1.32, MAPE = 1.25%). Trophic Level Index (TLI) was used to evaluate the eutrophication status. The relationship between the in situ FUI and TLI collected in 2018 was discussed based on the difference in the dominant components of waters, while a number of non-algae suspended solids in the estuaries and coastal waters led to the overestimation of eutrophication based on FUI. The R(560)–R(704) (when FUI is between 11 and 15) and R(665)/R(704) (when FUI is between 19 and 21) was employed to distinguish total suspended matter (TSM)-dominated systems in the FUI-based eutrophication assessment. Based on the analysis, a new approach to assessing the eutrophication of coastal waters in Liaodong Bay was developed, which proved to have good accuracy by the field data in 2019 and 2020 (accuracy is 79%). Finally, we used Sentinel-2 images from Google Earth from 2019 to 2020 and locally processed data from 2018 to analyze the FUI spatial distribution and spatial and temporal statistics of the trophic status in the northern Liaodong Bay. The results show that the northern Liaodong Bay always presented the distribution characteristics of high inshore and low outside, high in the southeast and low in the northwest. The nutrient status is the worst in spring and summer.

Traditionally accessibility has been analyzed from the perspective of the mean or expected travel time, which fails to capture the full cost, especially the external cost, of travel. The full cost accessibility (FCA) framework, proposed by Cui and Levinson (2018), provides a theoretical basis to fill the gap. It combines temporal, monetary, and non-monetary internal and external travel costs into accessibility evaluations, considering the time cost, crash cost, emission cost, and monetary cost. This paper extends the FCA framework and measures the full cost accessibility by auto for the Minneapolis - St. Paul Metropolitan area, demonstrating the practicality of the FCA framework on real networks.

MicroRNAs (miRNAs) are endogenous non-coding small RNA molecules that can be secreted into the circulation and exist in remarkably stable forms. Like intercellular miRNAs, circulating miRNAs participate in numerous regulations of biological process and expressed aberrantly under abnormal or pathological status. The quality and quantity changes of circulating miRNAs are associated with the initiation and progression of cancer and can be easily detected by basic molecular biology techniques. Consequently, considerable effort has been devoted to identify suitable extracellular miRNAs for noninvasive biomarkers in cancer. However, several challenges need to be overcome before the practical application. In this review, we discuss several issues of circulating miRNAs: biological function and basic transport carriers; extracellular cell communication process; roles as reliable cancer biomarkers and usage in targeted cancer therapy; and challenges for clinical application.

Traditional accessibility evaluation fails to fully capture the travel costs, especially the external costs, of travel. This study develops a full cost accessibility (FCA) framework by combining the internal and external cost components of travel time, safety, emissions, and money. The example illustrated compares FCA by automobile and bicycle on a toy network to demonstrate the potential and practicality of applying the FCA framework on real networks. This method provides an efficient evaluation tool for transport planning projects.