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Background Ovarian cancer (OvCa) is one of the most common malignant diseases of the female reproductive system in the world. The majority of OvCa is diagnosed with metastasis in the abdominal cavity. Epithelial-to-mesenchymal transition (EMT) plays a key role in tumor cell metastasis. However, it is still unclear whether long non-coding RNA (lncRNA) is implicated in EMT and influences cell invasion and metastasis in OvCa. Results In this study, using bioinformatcis analysis, we constructed a lncRNA-mediated competing endogenous RNA (ceRNA) network for mesenchymal OvCa and identified lncRNA AP000695.4, which we named pro-transition associated RNA (PTAR). PTAR was significantly up-regulated in the mesenchymal subtype samples compared with the epithelial subtype samples from the TCGA OvCa data sets. In addition, our study showed that PTAR expression was positively correlated with the expression level of ZEB1 in the mesenchymal OvCa samples. Meanwhile, we found that silencing miR-101 promoted cell migration, whereas the overexpression of miR-101 suppressed EMT and cell migration in OvCa cell lines through the regulation of ZEB1. Further analysis showed that enhanced expression of PTAR promoted EMT and metastasis through the regulation of miR-101, whereas silencing PTAR led to the attenuation of TGF-β1-induced tumorigenicity in ovarian cancer cells. Mechanistically, we found that PTAR acted as a ceRNA of miR-101, as forced expression of PTAR reduced the expression and activity of miR-101. More importantly, the knockdown of PTAR reduced tumorigenicity and metastasis in vivo. Conclusions Taken together, the results from our study highlight a role for the PTAR-miR-101-ZEB1 axis in OvCa, which offers novel strategies for the prevention of metastasis in OvCa.

Stretchable neuromorphic optoelectronics present tantalizing opportunities for intelligent vision applications that necessitate high spatial resolution and multimodal interaction. Existing neuromorphic devices are either stretchable but not reconcilable with multifunctionality, or discrete but with low-end neurological function and limited flexibility. Herein, we propose a defect-tunable viscoelastic perovskite film that is assembled into strain-insensitive quasi-continuous microsphere morphologies for intrinsically stretchable neuromorphic vision-adaptive transistors. The resulting device achieves trichromatic photoadaptation and a rapid adaptive speed (<150 s) beyond human eyes (3 ~ 30 min) even under 100% mechanical strain. When acted as an artificial synapse, the device can operate at an ultra-low energy consumption (15 aJ) (far below the human brain of 1 ~ 10 fJ) with a high paired-pulse facilitation index of 270% (one of the best figures of merit in stretchable synaptic phototransistors). Furthermore, adaptive optical imaging is achieved by the strain-insensitive perovskite films, accelerating the implementation of next-generation neuromorphic vision systems. Wearable neuromorphic optoelectronics require stretchable photosensitive materials and multifunctional integration. Here, authors develop intrinsically stretchable neuromorphic vision-adaptive transistors for skin-like neuromorphic vision systems.

Background Treatment-resistant depression (TRD) and pain frequently coexist clinically. Ketamine has analgesic and antidepressant effects, but few studies have evaluated individual differences in antidepressant outcomes to repeated ketamine in TRD patients with comorbid pain. Our aims were to determine the difference in ketamine’s antidepressant effects in TRD patients with or without pain and then to examine whether inflammatory cytokines might contribute to ketamine’s effect. Methods Sixty-six patients with TRD received six infusions of ketamine. Plasma levels of 19 inflammatory cytokines were assessed at baseline and post-infusion (day 13 and day 26) using the Luminex assay. Plasma inflammatory cytokines of sixty healthy controls (HCs) were also examined. Results TRD patients with pain had a higher antidepressant response rate ( χ 2 = 4.062, P = 0.044) and remission rate ( χ 2 = 4.062, P = 0.044) than patients without pain. Before ketamine treatment, GM-CSF and IL-6 levels were higher in the pain group than in the non-pain and HC groups. In the pain group, levels of TNF-α and IL-6 at day 13 and GM-CSF, fractalkine, IFN-γ, IL-10, MIP-3α, IL-12P70, IL-17α, IL-1β, IL-2, IL-4, IL-23, IL-5, IL-6, IL-7, MIP-1β, and TNF-α at day 26 were lower than those at baseline; in the non-pain group, TNF-α levels at day 13 and day 26 were lower than those at baseline. In the pain group, the changes of IL-6 were associated with improvement in pain intensity ( β = 0.333, P = 0.001) and depressive symptoms ( β = 0.478, P = 0.005) at day 13. Path analysis showed the direct ( β = 2.995, P = 0.028) and indirect ( β = 0.867, P = 0.042) effects of changes of IL-6 on improvement in depressive symptoms both were statistically significant. Conclusion This study suggested that an elevated inflammatory response plays a critical role in individual differences in TRD patients with or without pain. Ketamine showed great antidepressant and analgesic effects in TRD patients with pain, which may be related to its effects on modulating inflammation. Trial registration ChiCTR , ChiCTR-OOC-17012239. Registered on 26 May 2017

Using polyaspartic acid (PAsp) and bentonite (BT) as the main raw materials, a new type of degradable soil water retaining agent (PAsp-AA/BT) was synthesized by microwave radiation. The optimum synthesis conditions and comprehensive properties of PAsp-AA/BT were discussed and the structure and surface characteristics of PAspsp-AA/BT were characterized by FTIR, SEM, XRD and TGA in the paper. The results showed that the optimum synthesis conditions of PAsp-AA/BT were as follows: the dosages of polyaspartic acid (PAsp), bentonite (BT), initiator potassium persulfate, crosslinking agent N , N ′-methylene bisacrylamide was 5, 3, 0.3, 0.03%, respectively, the neutralization degree of acrylic acid was 75%, and the microwave power was 490W. Under this condition, the absorption ratio of the synthesized PAspsp-AA/BT in deionized water and 0.9% NaCl solution was 953 and 164 g/g, respectively. The synthesized PAsp-AA/BT had a high water absorption rate, good water retention and repeated water absorption, and the degradation rate in soil within 30 days reached 32.75%, with good degradation effect. The analysis of SEM, FT-IR, XRD and TGA showed that: the surface of PAsp-AA/BT was rough and had obvious pore structure, which was conducive to the diffusion of water molecules; polyaspartic acid, bentonite and acrylic acid were polymerized; the cross-linking structure was formed between polyaspartic acid, bentonite and acrylic acid; the product of PASP-AA/BT had good thermal stability. This study provides a new soil water retaining agent, which is helpful for the better development of soil water retaining agent research.

To investigate the characteristics of soil heavy metal pollution in the Manghe River watershed, a typical industrial and mining complex area in the Yellow River Basin, concentrations of Hg, Cr, Cu, Ni, Pb, Zn, Cd, and pH were measured in 121 topsoil samples (0–20 cm) collected from the study area. Geostatistical methods were employed to analyze the spatial distribution patterns of heavy metals. The pollution status was assessed using the pollution load index (PLI), while correlation analysis, principal component analysis (PCA), and a positive matrix factorization (PMF) model were applied to identify the sources of heavy metals. The results indicated that: (1) The concentrations of Hg, As, Ni, Cu, Pb, Zn, and Cd exceeded their respective background values, with Hg, Pb and Cd reaching 3.52, 4.85, and 46.4 times of the background levels, respectively.(2) Different elements exhibited distinct spatial distribution and diffusion patterns, revealing their respective sources and influencing factors. (3) The overall PLI was 0.785, reflecting a mild pollution level across the region, while industrial and mining lands exhibited severe pollution (PLI = 4.3). The relative contribution of each heavy metal to the pollution load was ranked as follows: Cd (30.35)> Pb (4.76)> Hg (3.62)> Zn (2.18)> As (1.77)> Cu (1.53). (4) Principal component analysis categorized the sources of heavy metals into anthropogenic activities and natural origins. Further analysis using the PMF model delineated four specific sources: coal combustion (10.87%), natural and agricultural contributions (27.37%), transportation and agricultural actives (26.81%), and industrial emissions (34.95%). Finally, the study identified the following feasible strategies for controlling heavy metal pollution: blocking and remediating industrial pollution sources; treating agricultural non-point source pollution through biological methods; and substituting traditional transportation sources with new energy alternatives. This research could support decision-making processes related to the prevention and control of heavy metal pollution in the study area, as well as regional sustainable development.

Fish species substitution and fraud has become a worldwide economic issue in the seafood industry. In this study, an ultraviolet-visible (UV-Vis) spectroscopy-based method was developed for the identification of fish samples. Sixty fish samples from twelve commonly consumed fish species in China were analyzed as models to testify the protocol. The obtained results show that UV-Vis spectroscopy combined with chemometric analysis, such as principal component analysis (PCA), can accurately distinguish two fish species by boiling fish tissue sample in trifluoroacetic acid (TFA) solution for 2 min and analyzing the resultant samples using a UV-Vis spectrometer. The developed strategy was successfully applied to the classification and identification of fish samples on the market. It is a promising strategy that can be applied to the classification and authenticity testing of closely related fish species in order to detect and recognize fish substitution.

Severe adverse drug reactions (SADRs) pose significant challenges to pharmacotherapy. Machine learning (ML) models hold promise in providing reliable solutions for predicting SADRs. This study is designed to pinpoint the independent risk factors contributing to SADRs through the application of ML techniques, thus constructing a predictive model for SADRs applicable in real-world clinical settings. This retrospective dual-center cohort study analyzed adverse drug reaction (ADR) cases reported in two Chinese tertiary medical centers from 2014 to 2022. Per the World Health Organization - Uppsala Monitoring Centre severity criteria, cases were classified as SADRs or common ADRs. Independent predictors were identified via univariate and multivariate logistic regression (LR). A random partitioning of the data set resulted in a 75% training set and a 25% test set. The performance of three ML algorithms, including LR, Random Forest and Gradient Boosting Machine, was compared. A nomogram was constructed, model performance was measured by the area under the receiver operating characteristic curve (AUC), concordance index (C index), Hosmer-Lemeshow test (H-L test), Decision Curve Analysis (DCA), and Clinical Impact Curve (CIC). A total of 508 SADRs were identified. The AUC values of LR model demonstrates the highest predictability among the three ML models. The AUC was 0.707 in the test set and the AUC in the training set was 0.689. A nomogram was established based on the LR model and evaluated. The C-index was 0.714 in the test set and the AUC in the training set was 0.713; The H-L test produced a chi-square value of 9.769 ( = 0.369), indicating good calibration. The DCA and CIC verify that the LR model possesses significant predictive value. According to the LR model, there were 20 predictors, including age ≥54 years, concurrent diseases ≥3, cardiac insufficiency, hemorrhagic disorders, active malignancies, cerebral infarction, bone fractures, anti-infectives, cytotoxic antineoplastics, proton pump inhibitors, antiepileptics, anticoagulants, diagnostic agents, arterial administration. This study established a predictive nomogram for SADRs based on LR through comparative analysis of three ML approaches. The developed nomogram enables clinically meaningful risk stratification for SADRs, facilitating prophylactic surveillance of high-risk populations.

This study investigates the use of hydrochars derived from sweet potato residue ( Ipomoea batatas ), Indian mallow ( Abutilon theophrasti Medicus ), and Nan bamboo ( Phyllostachys edulis ) for diesel adsorption in oily wastewater treatment. Hydrochars were prepared via hydrothermal carbonization, and their adsorption kinetics and thermodynamics were evaluated. The optimal adsorption conditions for sweet potato residue hydrochar (SPRH) were: 1.8 g·L − 1 dosage, 479 mg·L − 1 diesel concentration, pH 4-, and 120-min adsorption time, with a capacity of 165.52 mg·g − 1 . Kinetic studies revealed that adsorption followed a pseudo-second-order model, and the isotherm fitted the Langmuir model. For Indian mallow hydrochar (IMH), optimal conditions were: 1.4 g·L − 1 dosage, 398 mg·L − 1 diesel concentration, pH 3.18, and 100 min, achieving 157.41 mg·g − 1 capacity. IMH adsorption also followed the pseudo-second-order model, driven by chemical adsorption. Nan bamboo hydrochar (NBH) showed optimal conditions at 1.8 g·L − 1 dosage, 502 mg·L − 1 diesel concentration, pH 3.92, and 120 min, with a diesel adsorption capacity of 193.75 mg·g − 1 . Chemical modification of NBH with KMnO 4 , H 2 O 2 , H 3 PO 4 , and HNO 3 improved adsorption by 12.38–21.25%. After four adsorption-desorption cycles, modified NBH retained 63.24% of its initial capacity, indicating good stability and regeneration potential. These findings suggest that modified NBH offers a cost-effective, efficient solution for oily wastewater treatment.

The research on rapid and efficient detection of microplastics in water is still in its early stages. Fluorescence feature recognition represents an important and innovative approach to microplastic detection. While carbon quantum dots have been widely used in various environmental detection methods, their use for detecting microplastics in water environments has been rarely reported. In this study, N and Cl co-doped carbon quantum dots were synthesized via a hydrothermal method. The heteroatom doping process endowed them with blue luminescence properties, and their adsorption for microplastics was improved through the introduction of positive and negative charges and intermolecular forces. By utilizing a combined mechanism of fluorescence and Rayleigh scattering, the detection of polystyrene microplastics with three different particle sizes was achieved. In the detection process, it exhibits excellent light stability. Notably, the nano-polystyrene exhibited a good nonlinear relationship within the range of 0.01 g/L to 0.001 g/L, with R2 values of 0.923 and 0.980 and a detection limit of 0.4 mg/L. These findings provide a novel approach for the detection of nano microplastics.

Challenges associated with stretchable optoelectronic devices, such as pixel size, power consumption and stability, severely brock their realization in high-resolution digital imaging. Herein, we develop a universal detachable interface technique that allows uniform, damage-free and reproducible integration of micropatterned stretchable electrodes for pixel-dense intrinsically stretchable organic transistor arrays. Benefiting from the ideal heterocontact and short channel length (2 μm) in our transistors, switching current ratio exceeding 10 6 , device density of 41,000 transistors/cm 2 , operational voltage down to 5 V and excellent stability are simultaneously achieved. The resultant stretchable transistor-based image sensors exhibit ultrasensitive X-ray detection and high-resolution imaging capability. A megapixel image is demonstrated, which is unprecedented for stretchable direct-conversion X-ray detectors. These results forge a bright future for the stretchable photonic integration toward next-generation visualization equipment. Pixel size, power consumption, and stability of stretchable optoelectronic devices limit their application in digital imaging. Bian et al. developed a universal detachable interface technique for damage-free micropattern, reproducible transfer and ideal heterocontact of intrinsically stretchable electrodes.