In vivo single-molecule RNA structural profiling.

Cellular RNAs exhibit substantial heterogeneity in structure and function. Recently, Yang et al. developed an in vivo single-molecule RNA structure profiling methodology and revealed that individual isoforms of noncoding transcripts adopt multiple diverse and functionally relevant structural conformations, which change in abundance and structure in response to temperature conditions.

ARPC5 is transcriptionally activated by KLF4, and promotes cell migration and invasion in prostate cancer via up-regulating ADAM17 : ARPC5 serves as an oncogene in prostate cancer.

BACKGROUND: Prostate cancer (PCa) is one of the most common cancers in men worldwide. Actin-related protein 2/3 complex subunit 5 (ARPC5) has been validated as a critical regulator in several kinds of human tumors. However, whether ARPC5 is implicated in PCa progression remains largely unknown. METHODS: PCa specimens and PCa cell lines were obtained for detecting gene expressions using western blot and quantitative reverse transcriptase PCR (qRT-PCR). PCa cells transfected with ARPC5 shRNA or a disintegrin and metalloprotease 17 (ADAM17) overexpressed plasmids were harvested for assessing cell proliferation, migration and invasion by using cell counting kit-8 (CCK-8), colony formation and transwell assays, respectively. The interaction relationship between molecules was testified with chromatin immunoprecipitation and luciferase reporter assay. Xenograft mice model was conducted for confirming the role of ARPC5/ADAM17 axis in vivo. RESULTS: Upregulated ARPC5 was observed in PCa tissues and cells, as well as forecasted poor prognosis of PCa patients. Depletion of ARPC5 inhibited PCa cell proliferation, migration and invasion. Krüppel-like factor 4 (KLF4) was identified to be a transcriptional activator of ARPC5 via binding with its promoter region. Furthermore, ADAM17 served as a downstream effector of ARPC5. ADAM17 overexpression overturned ARPC5 knockdown-induced repressive impacts on PCa progression in vitro and in vivo. CONCLUSION: Collectively, ARPC5 was activated by KLF4 and upregulated ADAM17 to promote PCa progression, which might act as a promising therapeutic target and prognostic biomarker for PCa.

Deep learning-based multifeature integration robustly predicts central lymph node metastasis in papillary thyroid cancer.

BACKGROUND: Few highly accurate tests can diagnose central lymph node metastasis (CLNM) of papillary thyroid cancer (PTC). Genetic sequencing of tumor tissue has allowed the targeting of certain genetic variants for personalized cancer therapy development. METHODS: This study included 488 patients diagnosed with PTC by ultrasound-guided fine-needle aspiration biopsy, collected clinicopathological data, analyzed the correlation between CLNM and clinicopathological features using univariate analysis and binary logistic regression, and constructed prediction models. RESULTS: Binary logistic regression analysis showed that age, maximum diameter of thyroid nodules, capsular invasion, and BRAF V600E gene mutation were independent risk factors for CLNM, and statistically significant indicators were included to construct a nomogram prediction model, which had an area under the curve (AUC) of 0.778. A convolutional neural network (CNN) prediction model built with an artificial intelligence (AI) deep learning algorithm achieved AUCs of 0.89 in the training set and 0.78 in the test set, which indicated a high prediction efficacy for CLNM. In addition, the prediction models were validated in the subclinical metastasis and clinical metastasis groups with high sensitivity and specificity, suggesting the broad applicability of the models. Furthermore, CNN prediction models were constructed for patients with nodule diameters less than 1 cm. The AUCs in the training set and test set were 0.87 and 0.76, respectively, indicating high prediction efficacy. CONCLUSIONS: The deep learning-based multifeature integration prediction model provides a reference for the clinical diagnosis and treatment of PTC.

Quantification of Diffusive Methane Emissions from a Large Eutrophic Lake with Satellite Imagery.

Lakes are major emitters of methane (CH4); however, a longstanding challenge with quantifying the magnitude of emissions remains as a result of large spatial and temporal variability. This study was designed to address the issue using satellite remote sensing with the advantages of spatial coverage and temporal resolution. Using Aqua/MODIS imagery (2003-2020) and in situ measured data (2011-2017) in eutrophic Lake Taihu, we compared the performance of eight machine learning models to predict diffusive CH4 emissions and found that the random forest (RF) model achieved the best fitting accuracy (R2 = 0.65 and mean relative error = 21%). On the basis of input satellite variables (chlorophyll a, water surface temperature, diffuse attenuation coefficient, and photosynthetically active radiation), we assessed how and why they help predict the CH4 emissions with the RF model. Overall, these variables mechanistically controlled the emissions, leading to the model capturing well the variability of diffusive CH4 emissions from the lake. Additionally, we found climate warming and associated algal blooms boosted the long-term increase in the emissions via reconstructing historical (2003-2020) daily time series of CH4 emissions. This study demonstrates the great potential of satellites to map lake CH4 emissions by providing spatiotemporal continuous data, with new and timely insights into accurately understanding the magnitude of aquatic greenhouse gas emissions.

Eutrophication and salinization elevate the dissolved organic matter content in arid lakes.

Dissolved organic matter (DOM) plays an essential role in the global lake carbon cycle. Understanding DOM composition and monitoring its spatiotemporal dynamics are of great significance for understanding the lake carbon cycle, controlling water pollution, and protecting water resources. However, previous studies have focused mainly on eutrophic freshwater lakes, with limited attention given to saline lakes. Based on in situ data collected in ten lakes in northwestern China, this study reported the changes in DOM components in different lake types. Parallel factor analysis (PARAFAC) was used to analyze the three-dimensional excitation emission matrix (EEMs) to obtain the DOM fluorescence components. The contributions of different environmental factors to the changes in DOM components were quantified by the generalized linear model (GLM). The results showed that the eutrophication index was significantly positively related to dissolved organic carbon (DOC) (R2 = 0.95, p < 0.01) and colored DOM (CDOM) (R2 = 0.96, p < 0.01) concentrations. Terrestrial humic-like and tryptophan-like components, which are highly correlated with human activities, explained 62% and 64% of the variations in DOC and CDOM, respectively. In sum, the contributions of human activities to the DOC and CDOM variations were 61% and 57%, respectively. Salinity also showed significant positive correlations with both DOC (R2 = 0.88, p < 0.01) and CDOM (R2 = 0.87, p < 0.01). Lake salinization led to increases in DOM concentration, and salinity contributed 20% and 16% to the DOC and CDOM variations, respectively. Therefore, human activities and salinity codetermined the DOM concentration and its composition in the western arid lakes. Based on these findings, this study proposed a feasible flowchart for remotely estimating DOM in saline lakes using satellite data. This study is significant for the long-term monitoring of the carbon cycle and the effective protection of lake water resources in saline lakes.

Computational biology-based study of the molecular mechanism of spermidine amelioration of acute pancreatitis.

Acute pancreatitis (AP) is an acute inflammatory gastrointestinal disease, the mortality and morbility of which has been on the increase in the past years. Spermidine, a natural polyamine, has a wide range of pharmacological effects including anti-inflammation, antioxidation, anti-aging, and anti-tumorigenic. This study aimed to investigate the reliable targets and molecular mechanisms of spermidine in treating AP. By employing computational biology methods including network pharmacology, molecular docking, and molecular dynamics (MD) simulations, we explored the potential targets of spermidine in improving AP with dietary supplementation. The computational biology results revealed that spermidine had high degrees (degree: 18, betweenness: 38.91; degree: 18, betweenness: 206.41) and stable binding free energy (ΔGbind: - 12.81 ± 0.55 kcal/mol, - 15.00 ± 1.00 kcal/mol) with acetylcholinesterase (AchE) and serotonin transporter (5-HTT). Experimental validation demonstrates that spermidine treatment could reduce the necrosis and AchE activity in pancreatic acinar cells. Cellular thermal shift assay (CETSA) results revealed that spermidine could bind to and stabilize the 5-HTT protein in acinar cells. Moreover, spermidine treatment impeded the rise of the expression of 5-HTT in pancreatic tissues of caerulein induced acute pancreatitis mice. In conclusion, serotonin transporter might be a reliable target of spermidine in treating AP. This study provides new idea for the exploration of potential targets of natural compounds.

Increasing global oceanic wind speed partly counteracted water clarity management effectiveness: A case study of Hainan Island coastal waters.

A sustainable coastal "blue economy" is one of the most significant opportunities and challenges in the new era. However, the management and conservation of marine ecosystems must recognize the interdependence in the coupled human and natural systems. In this study, we employed satellite remote sensing to map the spatial and temporal distribution of Secchi disk depth (SDD) in Hainan coastal waters, China for the first time, and quantitatively revealed the impacts of environmental investments on the coastal water environment in the context of global climate change. Based on the moderate resolution imaging spectroradiometer (MODIS) in situ concurrent matchups (N = 123), a simple green band (555 nm)-based quadratic algorithm was first developed to estimate the SDD for the coastal waters of Hainan Island in China (R2 = 0.70, root mean square error (RMSE) = 1.74 m). The long time-series SDD dataset (2001-2021) for Hainan coastal waters was reconstructed from MODIS observations. Spatially, SDD showed a pattern of high water clarity in eastern and southern coastal waters and low water clarity in the western and northern coastal areas. This pattern is attributed to unbalanced distributions of bathymetry and pollution from seagoing rivers. Seasonally, the humid tropical monsoon climate drove the SDD into a general pattern of high in the wet season and low in the dry season. Annually, the SDD in Hainan coastal waters improved significantly (p < 0.1), benefiting from environmental investments over the last 20 years. However, the increasing global oceanic wind speed in recent years has exacerbated sediment resuspension and deep ocean mixing, counteracting approximately 14.14% of the remedial management's effectiveness in protecting and restoring the coastal ecosystem. This study offers ways to improve the ecological and environmental regulations under global changes and to strengthen the public service capacity for aquatic management authorities with methods that support the sustainable development of coastal areas.

Management actions mitigate the risk of carbon dioxide emissions from urban lakes.

Lakes are recognized as important sources of carbon dioxide (CO2) emissions, which vary greatly across land use type. However, CO2 emissions from lakes in urban landscapes are generally overlooked despite their daily connections to human activity. Furthermore, the role of management actions in CO2 emissions remained unclear mostly because of the lack of long-term observations. Here, the CO2 partial pressure (pCO2) from two urban lakes (Lake Wuli and Lake Donghu) in eastern China were investigated based on 16-year (2002-2017) field measurements. This long-term measurements showed the annual mean pCO2 were 1150 ± 612 µatm for Lake Wuli and 1143 ± 887 µatm for Lake Donghu, with corresponding estimated flux of 21.12 ± 19.60 mmol m-2 d-1 and 16.42 ± 20.39 mmol m-2 d-1, respectively. This indicates significant CO2 evasion into the atmosphere. Strong links between CO2 and human-derived nutrients (e.g., ammonium) and dissolved organic carbon, dissolved oxygen, and trophic state index were found. Although pCO2 was relatively uniform across sites and seasons in each lake, substantial inter-annual variability with significant decreasing trends were found. The decrease in annual CO2 can be partly explained by the reduction of pollutant loadings with management actions, which held the hypotheses that management actions mitigated the CO2 emission risks. Overall, management actions (e.g., ecological restoration and municipal engineering) should be considered for better understanding the roles of anthropogenic aquatic ecosystems in carbon cycle.

Can the establishment of a protected area improve the lacustrine environment? A case study of Lake Chaohu, China.

Eutrophication of lacustrine environments with frequent cyanobacterial blooms has become a serious problem. Overpopulation and runoff into groundwater and lakes from fertilizers with too much nitrogen and phosphorous have caused most of the problems. Here, we first devised a land use and cover classification system based on the local characteristics of the first-level protected area of Lake Chaohu (FPALC). Lake Chaohu is the fifth largest freshwater lake in China. The land use and cover change (LUCC) products were produced using sub-meter resolution satellite data from 2019 to 2021 in the FPALC. This study presents an evaluation of the effectiveness of the established protected areas. The results show the most impactful type was the reduction in cropland with an area that declined from 7446.4 hm2 to 6433.3 hm2 from 2019 to 2021. Most of the reduced cropland was converted into wetlands, with 460.2 hm2 and 152.0 hm2 of cropland restored to wetlands from 2019 to 2020 and 2020-2021, respectively. The area of cyanobacterial blooms in Lake Chaohu showed a downward trend, and the lacustrine environment was greatly improved after the establishment of the FPALC. These quantified data can inform decision-making related to Lake Chaohu conservation and provide a reference for managing the aquatic environment in other watersheds.

Global divergent trends of algal blooms detected by satellite during 1982-2018.

Algal blooms (ABs) in inland lakes have caused adverse ecological effects, and health impairment of animals and humans. We used archived Landsat images to examine ABs in lakes (>1 km2 ) around the globe over a 37-year time span (1982-2018). Out of the 176032 lakes with area >1 km2 detected globally, 863 were impacted by ABs, 708 had sufficiently long records to define a trend, and 66% exhibited increasing trends in frequency ratio (FRQR, ratio of the number of ABs events observed in a year in a given lake to the number of available Landsat images for that lake) or area ratio (AR, ratio of annual maximum area covered by ABs observed in a lake to the surface area of that lake), while 34% showed a decreasing trend. Across North America, an intensification of ABs severity was observed for FRQR (p < .01) and AR (p < .01) before 1999, followed by a decrease in ABs FRQR (p < .01) and AR (p < .05) after the 2000s. The strongest intensification of ABs was observed in Asia, followed by South America, Africa, and Europe. No clear trend was detected for the Oceania. Across climatic zones, the contributions of anthropogenic factors to ABs intensification (16.5% for fertilizer, 19.4% for gross domestic product, and 18.7% for population) were slightly stronger than climatic drivers (10.1% for temperature, 11.7% for wind speed, 16.8% for pressure, and for 11.6% for rainfall). Collectively, these divergent trends indicate that consideration of anthropogenic factors as well as climate change should be at the forefront of management policies aimed at reducing the severity and frequency of ABs in inland waters.

Melatonin may suppress lung adenocarcinoma progression via regulation of the circular noncoding RNA hsa_circ_0017109/miR-135b-3p/TOX3 axis.

Melatonin is a hormone synthesized in the pineal gland and has widespread physiological and pharmacological functions. Moreover, it can activate protective receptor-dependent processes. These processes can prevent tissue carcinogenesis and inhibit malignant tumor progression and metastasis. Therefore, we investigated the regulatory effects of melatonin on dysregulated circular RNAs in human lung adenocarcinoma (LUAD) cells. In this study, we treated LUAD cells with melatonin and measured the expression of hsa_circ_0017109, miR-135b-3p, and TOX3 by quantitative reverse transcription polymerase chain reaction. Colony formation and cell counting kit-8 assays were used to determine cell proliferation. The wound-healing assay and Transwell experiment were carried out to evaluate the migration potential and invasive capacity of LUAD cells. Also, cell apoptosis was detected using a cell apoptosis kit, and protein production was identified by Western blot. It was suggested that melatonin could inhibit LUAD progression in vivo and in vitro, and the role of TOX3 in this process was explored. Additionally, hsa_circ_0017109 was found to sponge miR-135b-3p, a downstream factor of circ_0017109, which was demonstrated to target TOX3 in LUAD cells and could promote the Hippo pathway and epithelial-mesenchymal transition pathway. To summarize, we demonstrated that melatonin decreases the expression of circ_0017109 and suppresses the non-small-cell lung cancer cell migration, invasion, and proliferation through decreasing TOX3 expression via direct activation of miR-135b-3p.

Transport and fate of antibiotics in a typical aqua-agricultural catchment explained by rainfall events: Implications for catchment management.

Antibiotics receive many concerns since their negative environmental impacts are being revealed, especially in aqua-agricultural areas. Rainfall events are responsible for transferring excess contaminants to receiving waters. However, the understanding of antibiotics transport and fate responding to rainfall events was constrained by limited event-based data and lacking integrated consideration of dissolved and particulate forms. We developed an intensive monitoring strategy to capture responses of fourteen antibiotics to different types of rainfall events and inter-event low flow periods. Pollutant-rich suspended particles, as high as 1471 ng/g, were found in low flow periods while the very heavy rainfall events and consecutive rainfall events stimulated the release of antibiotics from eroded soil particles to river water. Therefore, these rainfall events drove radical increase of dissolved antibiotic concentration up to 592 ng/L and total flux up to 25.0 g/d. Sulfonamides were particularly sensitive to rainfall events because of their residues in manure-applied agricultural lands. Transport dynamics of most antibiotics were accretion whereas only clarithromycin exhibited a dilution pattern by concentration-discharge relationships. Aquaculture ponds were inferred to significantly contribute tetracycline, oxytetracycline, and clarithromycin. Conventional contaminants were compared to discriminate potential sources of antibiotics and imply effective catchment management. The results provided novel insights into event-based drivers and dynamics of antibiotics and could lead to appropriate management strategy.

Phosphorus alleviation of nitrogen-suppressed methane sink in global grasslands.

Grassland ecosystems account for more than 10% of the global CH4 sink in soils. A 4-year field experiment found that addition of P alone did not affect CH4 uptake and experimental addition of N alone significantly suppressed CH4 uptake, whereas concurrent N and P additions suppressed CH4 uptake to a lesser degree. A meta-analysis including 382 data points in global grasslands corroborated these findings. Global extrapolation with an empirical modelling approach estimated that contemporary N addition suppresses CH4 sink in global grassland by 11.4% and concurrent N and P deposition alleviates this suppression to 5.8%. The P alleviation of N-suppressed CH4 sink is primarily attributed to substrate competition, defined as the competition between ammonium and CH4 for the methane mono-oxygenase enzyme. The N and P impacts on CH4 uptake indicate that projected increases in N and P depositions might substantially affect CH4 uptake and alter the global CH4 cycle.

Satellite Estimation of Dissolved Carbon Dioxide Concentrations in China's Lake Taihu.

Lakes play an important role in the global carbon cycle; however, there are still large uncertainties in the estimation of global lake carbon emission due to the limitations in conducting field surveys at large geographic scales. Using long-term Moderate-Resolution Imaging Spectroradiometer (MODIS) imagery and field observation data in eutrophic Lake Taihu, we developed a novel approach to estimate the concentration of dissolved carbon dioxide (cCO2) in lakes. Based on the MODIS-derived chlorophyll-a concentration, lake surface temperature, diffuse attenuation coefficient of photosynthetically active radiation, and photosynthetically active radiation, a spatially explicit cCO2 model was developed using multivariate quadratic polynomial regression (coefficient of determination (R2) = 0.84, root-mean-square error (RMSE) = 11.81 µmol L-1, unbiased percent difference (UPD) = 22.46%). Monte Carlo simulations indicated that the model is stable with relatively small deviations in cCO2 estimates caused by input variables (UPD = 26.14%). MODIS data from 2003 to 2018 showed a significant declining trend (0.42 µmol L-1 yr-1, p < 0.05) in the annual mean cCO2. This was associated with a complex balance between the increasing algae biomass and decreasing external inputs of inorganic carbon, nutrients, and organic matter. The high spatiotemporal variabilities in cCO2 were attributed to river inputs and seasonal changes in temperature and algae biomass. The study shows that satellite remote sensing can play an important role in the field of inland water carbon cycling, providing timely much-needed insights into the drivers of the spatial and temporal changes in dissolved CO2 concentrations in inland waters.

Tanshinone IIA attenuates epithelial-mesenchymal transition to inhibit the tracheal narrowing.

BACKGROUND: This study examines the effects of tanshinone IIA (TIIA) on epithelial-mesenchymal transition (EMT) in tracheal transplantation and the ability of TIIA to inhibit tracheal narrowing after tracheal transplantation. Mechanisms that may be involved in this process are also explored. METHODS: Human bronchial epithelial cells were treated in vitro with TGF-ß1 for 72 h. The cells were pretreated with TIIA (40 µg/mL) or DMSO for 2 h before TGF-ß1 stimulation. For the in vivo experiments, tracheas (5-6 rings) from Wistar rats were orthotopically transplanted into Sprague-Dawley rats. The experimental group received multiple infusions of sodium TIIA sulfonate (25 mg/kg, qd, intraperitoneally). The control group received infusions of the same volume of saline. Allografts were harvested at 3, 7, 10, 14, 35, and 90 d after transplantation and were examined for tracheal narrowing. Tracheal tissue samples and human bronchial epithelial cell were then subjected to further tests. RESULTS: In the in vitro assay, epithelial cadherin expression was decreased after TGF-ß1 stimulation, whereas α-smooth muscle actin and vimentin expression levels were increased. The expression levels of ZEB1 and Snail1 were also increased. These changes in expression were partially reversed by treatment with TIIA. In the in vivo assay, TIIA alleviated tracheal stenosis after tracheal allograft transplantation in rats and mitigated EMT by inhibiting the Smad signaling pathway and the expression of the transcription factors ZEB1 and Snail1. CONCLUSIONS: Our research suggests that TIIA reduces tracheal narrowing after tracheal transplantation by suppressing TGF-ß1-dependent EMT.

Atmospheric correction of HJ-1 CCD imagery over turbid lake waters.

We have presented an atmospheric correction algorithm for HJ-1 CCD imagery over Lakes Taihu and Chaohu with highly turbid waters. The Rayleigh scattering radiance (Lr) is calculated using the hyperspectral Lr with a wavelength interval 1nm. The hyperspectral Lr is interpolated from Lr in the central wavelengths of MODIS bands, which are converted from the band response-averaged Lr calculated using the Rayleigh look up tables (LUTs) in SeaDAS6.1. The scattering radiance due to aerosol (La) is interpolated from La at MODIS band 869nm, which is derived from MODIS imagery using a shortwave infrared atmospheric correction scheme. The accuracy of the atmospheric correction algorithm is firstly evaluated by comparing the CCD measured remote sensing reflectance (Rrs) with MODIS measurements, which are validated by the in situ data. The CCD measured Rrs is further validated by the in situ data for a total of 30 observation stations within ± 1h time window of satellite overpass and field measurements. The validation shows the mean relative errors about 0.341, 0.259, 0.293 and 0.803 at blue, green, red and near infrared bands.

Spatiotemporal heterogeneity of lake carbon dioxide flux leads to substantial uncertainties in regional upscaling estimates.

Limited field samplings result in significant uncertainties in regional and global estimates of lake carbon dioxide (CO2) emissions. However, quantitative analysis of uncertainty in regional lake CO2 emission estimates remains unclear. In this study, we utilized satellite data to estimate carbon dioxide flux from 113 eastern China lakes, revealing substantial spatial and temporal variations in flux, averaging 18.07 ± 81.83 mg m-2 d-1. Additionally, satellite-estimated total CO2 effluxes indicated previous upscaling studies had overestimated total CO2 effluxes from these studied lakes by approximately 3-11 times, primarily due to substantial variations in lake CO2 fluxes. Insufficient sampling resolution resulted in considerable uncertainty in upscaling estimations. Temporal variations in carbon dioxide contributed greater upscaling uncertainties than spatial variations in carbon dioxide. To capture the dynamics of lake CO2, increasing the number of sampling points and events is necessary as lake size decreases and trophic state increases. Finally, we propose a prediction for the optimal sampling resolution based on lake area and trophic state, recommending an average of 5 points per lake and bi-monthly sampling as the ideal resolution for similar shallow eutrophic lakes. This approach has been validated as effective in lakes across North America and Europe. We believe that future global-scale lake carbon budget estimates would benefit from field observations conducted at more reasonable sampling points and frequency.

A prospective single-center, single-arm, open-label, phase II study of sintilimab and anlotinib combined with chemotherapy in neoadjuvant treatment of resectable esophageal cancer.

BACKGROUND: Antiangiogenic treatment and immunochemotherapy effectively treat patients with advanced esophageal cancer. However, there remains a dearth of studies concerning neoadjuvant therapy for resectable esophageal cancer. METHODS: The study focused on patients with T2-4NxM0 resectable esophageal carcinoma. Neoadjuvant treatment involved administering anlotinib (10 mg orally, once a day, 2 weeks on and 1 week off) for antiangiogenesis and sintilimab (200 mg) and chemotherapy for three cycles. Surgical treatment was performed 4-6 weeks after the last chemotherapy cycle was completed. The primary endpoints assessed were pathological complete response (pCR) and safety. RESULTS: Out of the 34 screened patients, 17 were successfully enrolled in the study, and 14 completed the entire treatment process. The pCR was 35.3% (6/17). However, two patients experienced mortality. The occurring rate of grade 3 or higher complications after the surgery was 78.6% (11/14) according to Clavien-Dindo classification. Specifically, anastomotic leakage was observed in 57.1% (8/14) of the patients. CONCLUSION: Compared to neoadjuvant chemotherapy, the current regimen demonstrated improved pCR. However, it did not show significant improvement compared to immunochemotherapy. It is essential to exercise caution when using this treatment approach in patients with esophageal cancer as it might increase postoperative complications, especially anastomotic leakage.

Prognostic Model Construction of Disulfidptosis-Related Genes and Targeted Anticancer Drug Research in Pancreatic Cancer.

Pancreatic cancer stands as one of the most lethal malignancies, characterized by delayed diagnosis, high mortality rates, limited treatment efficacy, and poor prognosis. Disulfidptosis, a recently unveiled modality of cell demise induced by disulfide stress, has emerged as a critical player intricately associated with the onset and progression of various cancer types. It has emerged as a promising candidate biomarker for cancer diagnosis, prognosis assessment, and treatment strategies. In this study, we have effectively established a prognostic risk model for pancreatic cancer by incorporating multiple differentially expressed long non-coding RNAs (DElncRNAs) closely linked to disulfide-driven cell death. Our investigation delved into the nuanced relationship between the DElncRNA-based predictive model for disulfide-driven cell death and the therapeutic responses to anticancer agents. Our findings illuminate that the high-risk subgroup exhibits heightened susceptibility to the small molecule compound AZD1208, positioning it as a prospective therapeutic agent for pancreatic cancer. Finally, we have elucidated the underlying mechanistic potential of AZD1208 in ameliorating pancreatic cancer through its targeted inhibition of the peroxisome proliferator-activated receptor-γ (PPARG) protein, employing an array of comprehensive analytical methods, including molecular docking and molecular dynamics (MD) simulations. This study explores disulfidptosis-related genes, paving the way for the development of targeted therapies for pancreatic cancer and emphasizing their significance in the field of oncology. Furthermore, through computational biology approaches, the drug AZD1208 was identified as a potential treatment targeting the PPARG protein for pancreatic cancer. This discovery opens new avenues for exploring targets and screening drugs for pancreatic cancer.

Influence of climate extremes on long-term changes in cyanobacterial blooms in a eutrophic and shallow lake.

Climate change and human activities have crucial effects on the variations in phytoplankton blooms in lakes worldwide. A record-breaking heatwave and drought event was reported in the middle and lower reaches of the Yangtze River during the summer of 2022, but only little is known about how cyanobacterial blooms in lakes respond to such climate extremes. Here, we utilized MODIS images to generate the area, occurrence, and initial blooming date (IBD) of cyanobacterial blooms in Lake Chaohu from 2000 to 2022. We found that the area and occurrence of cyanobacterial blooms were largely reduced. At the same time, the IBD was delayed in 2022 compared with the previous 20 years. The annual occurrence and mean area of cyanobacterial blooms in 2022 were 17 % and 23.1 km2, respectively, which were the lowest reported levels since the 21st century. The IBD in 2022 was four months late compared with the IBD in 2020. The high wind speed in spring delayed the spring blooms in 2022. The record-breaking heatwaves and drought from June to August reduced the blooms by influencing the growth of cyanobacteria and reducing the flow of nutrients from the watershed into the lake. This study highlights the compound impact of heatwave and drought climate events on reducing cyanobacterial blooms in a long-term period, enhancing additional understanding of the changes in phytoplankton blooms in lakes.