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Abstract In oncology anti—PD1 / PDL1 therapy development for solid tumors, objective response rate (ORR) is commonly used clinical endpoint for early phase study decision making, while progression free survival (PFS) and overall survival (OS) are widely used for late phase study decision making. Developing predictive models to late phase outcomes such as median PFS (mPFS) and median OS (mOS) based on early phase clinical outcome ORR could inform late phase study design optimization and probability of success (POS) evaluation. In existing literature, there are ORR / mPFS / mOS association and surrogacy investigations with limited number of included clinical trials. In this paper, without establishing surrogacy, we attempt to predict late phase survival (mPFS and mOS) based on early efficacy ORR and optimize late phase trial design for anti—PD1 / PDL1 therapy development. In order to include adequate number of eligible clinical trials, we built a comprehensive quantitative clinical trial landscape database (QLD) by combining information from different sources such as clinicaltrial.gov, publications, company press releases for relevant indications and therapies. We developed a generalizable algorithm to systematically extract structured data for scientific accuracy and completeness. Finally, more than 150 late phase clinical trials were identified for ORR / mPFS (ORR / mOS) predictive model development while existing literature included at most 50 trials. A tree-based machine learning regression model has been derived to account for ORR / mPFS (ORR / mOS) relationship heterogeneity across tumor type, stage, line of therapy, treatment class and borrow strength simultaneously when homogeneity persists. The proposed method ensures that the predictive model is robust and have explicit structure for clinical interpretation. Through cross validation, the average predictive mean square error of the proposed model is competitive to random forest and extreme gradient boosting methods and outperforms commonly used additive or interaction linear regression models. An example application of the proposed ORR / mPFS (ORR / mOS) predictive model on late phase trial POS evaluation for anti—PD1 / PDL1 combination therapy was illustrated.

Objectives: To assess the effects of timing of maternal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination status on placental transfer of antibodies to neonates. Methods: In this cross-sectional study, chemiluminescence was employed to measure SARS-CoV-2 IgG antibody titers in paired maternal-infant samples from women infected during pregnancy who were vaccinated or unvaccinated. Generalized linear regression assessed factors affecting antibody transfer in infected pregnant women and neonatal titers. Results: The group with ≥90 days between infection and delivery showed a higher antibody transfer rate than the

【Objective】 Garlic is a cash crop in Dali, but its irrigation with livestock wastewater risks environmental pollution. This paper studies the combined effect of livestock wastewater irrigation and nitrogen fertilization on growth, yield, water and nitrogen utilization efficiency of garlic, as well as soil nitrogen in attempts to screen a sustainable livestock wastewater irrigation schedule for garlic production in this region. 【Method】 The experiment was conducted at the National Agricultural Environmental Dali Observation and Experimental Station. There were five treatments: freshwater irrigation without nitrogen application (CK), freshwater irrigation with 390 kg/hm2 of nitrogen application (C1), freshwater irrigation with 312 kg/hm2 of nitrogen application (C2), livestock wastewater irrigation without nitrogen application (R1), livestock wastewater irrigation with 150 kg/hm2 of nitrogen application (R2). In each treatment, we measured the growth indexes, including dry weight, height, stem diameter and leaf area index of the garlic at different growing stages, as well as yield, and water and nitrogen use efficiency of the garlic and soil nitrogen content. 【Result】 The growth of the garlic was the best in R2, but was comparable with that in R1 and C1; R2 gave the highest yield. Compared to CK, C1, C2, R1 and R2 increased the bulb yield by 111.30%, 81.23%, 98.19%, and 142.01%, respectively. The nitrogen absorption and use efficiency of R1 and R2 was 154.71% and 92.25% higher than that of C1, respectively; the nitrogen partial factor productivity of R1 and R2 was 110.75% and 47.63% higher than that of C1, respectively. Compared to C1, R1 reduced the irrigation water productivity and soil nitrogen in the 0-40 cm of soil layer by 29.19%, while R2 increased the irrigation water productivity by 2.34% and reduced soil nitrogen in the 0-40 cm of soil by 3.89%, respectively. Compared to C1, R1 and R2 increased nitrogen in the 0-20 cm of soil layer by 170.90% and 255.93% respectively. 【Conclusion】 Livestock wastewater irrigation combined with appropriate base nitrogen fertilization can sustain garlic growth and yield. Livestock wastewater irrigation improved the nitrogen use efficiency and nitrogen partial factor productivity, with limited effect on average soil total nitrogen.

Abstract Bietti crystalline corneoretinal dystrophy (BCD) is an autosomal recessive chorioretinal degenerative disease without approved therapeutic drugs. It is caused by mutations in CYP4V2 gene, and about 80% of BCD patients carry mutations in exon 7 to 11. Here, we apply CRISPR/Cas9 mediated homology-independent targeted integration (HITI)-based gene editing therapy in HEK293T cells, BCD patient derived iPSCs, and humanized Cyp4v3 mouse model (h-Cyp4v3 mut/mut ) using two rAAV2/8 vectors via sub-retinal administration. We find that sgRNA-guided Cas9 generates double-strand cleavage on intron 6 of the CYP4V2 gene, and the HITI donor inserts the carried sequence, part of intron 6, exon 7-11, and a stop codon into the DNA break, achieving precise integration, effective transcription and translation both in vitro and in vivo. HITI-based editing restores the viability of iPSC-RPE cells from BCD patient, improves the morphology, number and metabolism of RPE and photoreceptors in h-Cyp4v3 mut/mut mice. These results suggest that HITI-based editing could be a promising therapeutic strategy for those BCD patients carrying mutations in exon 7 to 11, and one injection will achieve lifelong effectiveness.

The compound AgBiS2, a ternary sulfide, has gained significant attention in the field of photovoltaics due to its characteristic properties of being non-toxic, low-cost, and highly efficient. However, due to the instability of its grain boundaries, the structure of the AgBiS2 may be transformed at high temperatures, consequently influencing the lifetime of devices utilizing this material. In this study, the mechanism of interfacial structural transition and the factors affecting the stability of AgBiS2 were investigated by in-situ transmission electron microscopy. Our observations revealed that, under high-temperature conditions, the structure of the material changes with the formation of triangular hole-like defects at the AgBiS2 interface, which is directly related to the movement of defects. Furthermore, the surface energy of the AgBiS2 crystal planes is different due to different atomic arrangements. Combining the experiments with theoretical calculations, we found that the defects such as dislocations tend to cluster on the high-energy plane (111), thereby leading to localized stress and strain concentration. Then, the structure transforms by reconstructing its interfacial atoms to reduce the local stress. Of note, this reconstruction leads to the formation of triangular hole-like defects, consequently reducing the overall energy of the system.

Although the growing literature on coronavirus disease 2019 (COVID-19) conspiracy theories has highlighted the role of digital media in fomenting beliefs, few studies have examined the influence of the fast-rising far-right media platforms. This study examines and compares the role of conservative media and far-right websites in propagating COVID-19 conspiracy theories and explores an underlying sociopsychological mechanism of political identity. The results of an online survey ( N = 702) in the United States indicated that people exposed to conservative media and far-right websites were more likely to endorse COVID-19 conspiracy theories, but the impact of conservative media exposure was more prominent. Additionally, the positive relations between conservative media/far-right websites exposure and conspiracy beliefs were stronger among liberal-leaning individuals than conservative-leaning individuals. Counter-attitudinal exposure is often regarded as a crucial element of political deliberation and a solution to opinion polarization. Our findings cautioned, however, that counter-attitudinal exposure would also help propagate conspiracy theories.

Abstract Immune checkpoint blockade (ICB) has shown considerable promise for treating various malignancies, but only a subset of cancer patients benefit from immune checkpoint inhibitor therapy because of immune evasion and immune-related adverse events (irAEs). The mechanisms underlying how tumor cells regulate immune cell response remain largely unknown. Here we show that hexokinase domain component 1 (HKDC1) promotes tumor immune evasion in a CD8+ T cell-dependent manner by activating STAT1/PD-L1 in tumor cells. Mechanistically, HKDC1 binds to and presents cytosolic STAT1 to IFNGR1 on the plasma membrane following IFNγ-stimulation by associating with cytoskeleton protein ACTA2, resulting in STAT1 phosphorylation and nuclear translocation. HKDC1 inhibition in combination with anti-PD-1/PD-L1 enhances in vivo T cell antitumor response in liver cancer models in male mice. Clinical sample analysis indicates a correlation among HKDC1 expression, STAT1 phosphorylation, and survival in patients with hepatocellular carcinoma treated with atezolizumab (anti-PD-L1). These findings reveal a role for HKDC1 in regulating immune evasion by coupling cytoskeleton with STAT1 activation, providing a potential combination strategy to enhance antitumor immune responses.

People Identification is a critical aspect in developing modern vehicles, aimed at enhancing safety and comfort levels. Most traditional methods of people identification in vehicles use RGB images or videos. In this study, we introduce a novel methodology for identifying individuals in private car scenarios, utilizing 3D Light Detection and Ranging (LiDAR) technology, generative image inpainting based on Contextual Attention, and the YOLOv5 model. Initially, we gather data utilizing a 3D-LiDAR instrument and subsequently convert the acquired depth data into depth images. Following this, the depth images are annotated manually to indicate the positions and identifiers of various individuals occupying distinct seats. This annotated data serves as the training material for the YOLOv5 model, facilitating the recognition and categorization of subjects. However, given that individuals seated in the back often have parts of their bodies occluded by the front seats and the passengers in them, we employ generative image inpainting techniques to reveal the occluded portions. This step significantly enhances the precision in detecting and identifying individuals situated in the back seats. We implemented our strategy on a restricted group of four participants, conducting training and testing phases within identical environments. Prior to the inpainting process, the classification’s F1 score stood at 66.5%. After inpainting, we observed a notable surge in the F1 score for the rear-seat passengers increased by 17.1%.

Abstract The users of the Dark Web require a secure and highly anonymous environment to exchange information while protecting their online privacy, which presents a privacy dilemma. This paper examines the digital footprints of user behavior on the three most popular cryptomarket forums on the Dark Web, namely Silk Road 1, Silk Road 2, and Agora. The results indicate that users who engage in more conversations and employ a wider range of vocabulary are more likely to discontinue their participation on the forum. Intriguingly, no significant relationship is found between network characteristics and user engagement. These findings emphasize that the risk of exposure within anonymous communities primarily stems from the potency of information rather than social connections, which sheds light on the privacy dilemma inherent in the Dark Web and provides deeper insights into the online user behavior surrounding anonymity-granting technologies on the Internet.

The SWAT model primarily investigates sources of water pollution and conducts ecological assessments of surface water in contemporary hydrology and water resources research. To date, there have been limited accomplishments in the study of groundwater resources in China. The MODFLOW model currently primarily simulates groundwater levels and the migration of water quality, depending on the hydrological surface water data in the relevant area. This study aims to investigate the groundwater distribution characteristics of the middle and lower reaches of the Songhua River, a significant agricultural and grain production region in China. The research focuses on the middle and lower reaches of the Songhua River basin in Northeast China and employed the SWAT distributed hydrological model to simulate runoff. The monthly recorded runoff at Tongjiang Station in Jiamusi City was utilized to calibrate the model parameters. Consequently, the MODFLOW model was introduced to compare and assess the simulation outcomes of the SWAT model, ultimately ascertaining the distribution characteristics of shallow groundwater, groundwater recharge, recoverable volume, and groundwater levels in the Songhua River Basin. The findings indicate that: (1) The SWAT model demonstrates efficacy in the study region, achieving R2 and NS values of 0.81 and 0.76, respectively, thereby fulfilling the fundamental criteria for scientific research. The MODFLOW model exhibits strong performance in the study region, achieving a periodic R2 of 0.98 and a verification R2 of 0.97, with the discrepancy between simulated and actual groundwater levels confined to 0.6 m, thereby satisfying the criteria for scientific research. (2) In 2011, 2014, and 2016, the groundwater recharge in the middle and lower sections of the Songhua River was 24.33 × 108 m3, 30.79 × 108 m3, and 32.25 × 108 m3, respectively, aligning closely with the SWAT simulation results, while the average annual groundwater level depth was 8.17 m. (3) In the research area, groundwater recharging occurs primarily by atmospheric precipitation, while drainage predominantly transpires via groundwater as base flow, constituting 81.46%. Secondly, the recharge of shallow groundwater to deep aquifers is around 7.14%, with a minimal share attributed to vadose zone loss, constituting merely 2.1%. (4) From 2010 to 2016, the average groundwater runoff modulus of the middle and lower reaches of the Songhua River basin was 1.005 L/(s·km²), with a total recharge of 216.58 × 108 m3 and a total recoverable amount of 105.11 × 108 m3. The mean yearly supply was 25.11 × 108 m3. The total groundwater recharge was 26.54 × 108 m3 in the driest year (2011) and 33.25 × 108 m3 in the year of most ample water (2016).

Assessing the quality of corn seeds necessitates evaluating their water, fat, protein, and starch content. This study integrates hyperspectral imaging technology with chemometric analysis techniques to achieve non-invasive and rapid detection of multiple key components in corn seeds. Hyperspectral images of the embryo surface of maize seeds were collected within the wavelength range of 1100~2498 nm. Subsequently, image segmentation techniques were applied to extract the germ structure of the corn seeds as the region of interest. Seven spectral data preprocessing algorithms were employed, and the Detrending Transformation (DT) algorithm was identified as the optimal preprocessing method through comparative analysis using the Partial Least Squares Regression (PLSR) model. To reduce spectral redundancy and streamline the prediction model, three algorithms were employed for characteristic wavelength extraction: Successive Projections Algorithm (SPA), Competitive Adaptive Reweighted Sampling (CARS), and Uninformative Variable Elimination (UVE). Using the original spectra and extracted characteristic wavelengths, PLSR, BP, RBF, and LSSVM models were constructed to detect the content of four components. The analysis indicated that the CARS-LSSVM algorithm had the best prediction performance. The PSO algorithm was employed to further optimize the parameters of the LSSVM model, thereby improving the model’s prediction performance. The R values for the four components in the test set were 0.9884, 0.9490, 0.9864, and 0.9687, respectively. This indicates that hyperspectral technology combined with the DT-CARS-PSO-LSSVM algorithm can effectively detect the main component content of corn seeds. This study not only provides a scientific basis for the evaluation of corn seed quality but also opens up new avenues for the development of non-destructive testing technology in related fields.

With the growth of the transportation industry, large volumes of waste tires are being generated, which necessitates the development of effective solutions for recycling waste tires. In this study, expansive clay was mixed with rubber fibers obtained from waste tires. Triaxial tests were conducted on the rubber fiber-reinforced expansive clay after freeze–thaw cycles. The experimental results of the unreinforced expansive clay from previous studies were used to evaluate the effect of mixing rubber fibers on the mechanical properties of rubber fiber-reinforced expansive clay under freeze–thaw cycles. The results demonstrate that the mixing of rubber fibers significantly reduces the effect of freeze–thaw cycles on the shear strength and elastic modulus of expansive clay. The shear strength and elastic modulus of the unreinforced expansive clay decrease markedly as the number of freeze–thaw cycles increases, while the shear strength and elastic modulus of the rubber fiber-reinforced expansive clay do not exhibit any remarkable change. A calculation model of the deviatoric stress–axial strain curves after freeze–thaw cycles was established. The model describes the deviatoric stress–axial strain behavior of rubber fiber-reinforced expansive clay and unreinforced expansive clay under different confining pressures and different numbers of freeze–thaw cycles.

The crack detection of concrete bridges is an important link in the safety evaluation of bridge structures, and the rapid and accurate identification and detection of bridge cracks is a prerequisite for ensuring the safety and long-term stable use of bridges. To solve the incomplete crack detection and segmentation caused by the complex background and small proportion in the actual bridge crack images, this paper proposes a coarse–fine combined bridge crack detection method of “double detection + single segmentation” based on deep learning. To validate the effect and practicality of fine crack detection, images of old civil bridges and viaduct bridges against a complex background and images of a bridge crack against a simple background are used as datasets. You Only Look Once V5(x) (YOLOV5(x)) was preferred as the object detection network model (ODNM) to perform initial and fine detection of bridge cracks, respectively. Using U-Net as the optimal semantic segmentation network model (SSNM), the crack detection results are accurately segmented for fine crack detection. The test results showed that the initial crack detection using YOLOV5(x) was more comprehensive and preserved the original shape of bridge cracks. Second, based on the initial detection, YOLOV5(x) was adopted for fine crack detection, which can determine the location and shape of cracks more carefully and accurately. Finally, the U-Net model was used to segment the accurately detected cracks and achieved a maximum accuracy (AC) value of 98.37%. The experiment verifies the effectiveness and accuracy of this method, which not only provides a faster and more accurate method for fine detection of bridge cracks but also provides technical support for future automated detection and preventive maintenance of bridge structures and has practical value for bridge crack detection engineering.

Abstract Organic electrochemical transistors (OECTs) have gained considerable attention due to their ability to simultaneously transduce and amplify ion‐based biological signals into electronic signals in bioelectronics. In this study, functionalized OECTs capable of detecting specific ion concentrations in aqueous solution and blood serum are investigated and described. Sodium, the most concentrated cation in the human body, is chosen as the target analyte due to its critical role in maintaining normal bodily functions such as blood pressure, nerve and muscle function, and fluid balance. These sodium ion sensors work at low source‐drain voltage, Vds = 0.4 V and gate voltage, Vg = 0 V, and demonstrate a high sensitivity of 126 μA dec−1 and a high selectivity over different cations. Furthermore, the OECT biosensors are employed to determine sodium concentration in more complex environments and demonstrated a log‐linear response within the physiological range of sodium in blood serum, ranging from 100 to 160 mm. In the final part of the study, the transistor‐based sensor is fabricated in a small‐footprint neural probe configuration and its sensing capability is investigated. These characteristics open up new opportunities for applications in wearable and implantable electronics.

Objective: This study aimed to investigate the infection status of Omicron in the population and the association between COVID-19 vaccination and infection with Omicron. Methods: We conducted a cross-sectional study to openly recruit participants for a survey of SARS-CoV-2 infection by convenience sampling from 1 January to 15 January 2023 after a COVID-19 pandemic swept across China. Additionally, the binary logistic regression model was adopted to evaluate the association between COVID-19 vaccination and the infection outcomes or symptom severity, respectively. Meanwhile, the relations between the vaccination and duration of the symptoms were estimated via ordinal logistic analysis. Results: Of the 2007 participants, the prevalence of infection with Omicron was 82.9%. Compared with unvaccinated individuals, inactivated COVID-19 vaccination could increase the risk of Omicron infection (OR = 1.942, 95% CI: 1.093–3.448), and the receipt of at least one dose of non-inactivated COVID-19 vaccines was a protective factor against infection (OR = 0.428, 95% CI: 0.226–0.812). By contrast, no relations were observed in COVID-19 vaccination with the symptoms of infection and duration of symptoms (p > 0.05). Conclusions: This cross-sectional study concluded that inactivated COVID-19 vaccination might increase the risk of Omicron infection, which should be a concern during COVID-19 vaccination and the treatment of variant infections in the future, and the receipt of at least one dose of non-inactivated COVID-19 vaccine was a protective factor against infection.

The separation of Li+ and [Bmim]+(1-Butyl-3-methylimidazolium) using a cation exchange membrane in an electric field is studied in this work. The effects of the type of cation exchange membrane, current density, total cation concentration, temperature, and anion types on the separation efficiency are investigated. The results indicate that it is feasible to achieve the efficient separation of Li+ and [Bmim]+ using the selectivity of cation exchange membranes under an electric field. The CIMS membrane (a type of cation exchange membrane produced by ASTOM Corporation) shows obvious selectivity of Li+ from [Bmim]+. When the current density is 5 mA/cm2 and the feed concentrations of Li+ and [Bmim]+ are 0.3 mol/L and 0.2 mol/L, respectively, the selective transport coefficient of CIMS can reach 5.9 in the first 120 min of the process. The separation efficiency can be effectively improved by reducing the current density and increasing the total cation concentration. Decreasing the feed temperature can slightly improve the separation efficiency. Changing the type of anion in the feed from chloride to acetate has no detectable effect on the separation.

Mutant RHO is the most frequent genetic cause of autosomal dominant retinitis pigmentosa (adRP). Here, we developed an allele-specific gene-editing therapeutic drug to selectively target the human T17M RHO mutant allele while leaving the wild-type RHO allele intact for the first time. We identified a Staphylococcus aureus Cas9 (SaCas9) guide RNA that was highly active and specific to the human T17M RHO allele. In vitro experiments using HEK293T cells and patient-specific induced pluripotent stem cells (iPSCs) demonstrated active nuclease activity and high specificity. Subretinal delivery of a single adeno-associated virus serotype 2/8 packaging SaCas9 and single guide RNA (sgRNA) to the retinas of the RHO humanized mice showed that this therapeutic drug targeted the mutant allele selectively, thereby downregulating the mutant RHO mRNA expression. Administration of this therapeutic drug resulted in a long-term (up to 11 months after treatment) improvement of retinal function and preservation of photoreceptors in the heterozygous mutant humanized mice. Our study demonstrated a dose-dependent therapeutic effect in vivo. Unwanted off-target effects were not observed at the whole-genome sequencing level. Our study provides strong support for the further development of this effective therapeutic drug to treat RHO-T17M-associated adRP, also offers a generalizable framework for developing gene-editing medicine. Furthermore, our success in restoring the vision loss in the suffering RHO humanized mice verifies the feasibility of allele-specific CRISPR/Cas9-based medicines for other autosomal dominant inherited retinal dystrophies.

The synthesis of polycyclic structures bearing partially saturated (hetero)arenes is important as many of these structures have biological relevance. Here the authors develop a one-step method for selective dearomative functionalization of feedstock (hetero)arenes via organophotocatalysis.

Abstract Cancer is a genetic disease caused by alterations in genome and epigenome and is one of the leading causes for death worldwide. The exploration of disease development and therapeutic strategies at the genetic level have become the key to the treatment of cancer and other genetic diseases. The functional analysis of genes and mutations has been slow and laborious. Therefore, there is an urgent need for alternative approaches to improve the current status of cancer research. Gene editing technologies provide technical support for efficient gene disruption and modification in vivo and in vitro, in particular the use of clustered regularly interspaced short palindromic repeats (CRISPR)–Cas systems. Currently, the applications of CRISPR–Cas systems in cancer rely on different Cas effector proteins and the design of guide RNAs. Furthermore, effective vector delivery must be met for the CRISPR–Cas systems to enter human clinical trials. In this review article, we describe the mechanism of the CRISPR–Cas systems and highlight the applications of class II Cas effector proteins. We also propose a synthetic biology approach to modify the CRISPR–Cas systems, and summarize various delivery approaches facilitating the clinical application of the CRISPR–Cas systems. By modifying the CRISPR–Cas system and optimizing its in vivo delivery, promising and effective treatments for cancers using the CRISPR–Cas system are emerging.

Albizia julibrissin saponin active fraction (AJSAF), is a prospective adjuvant with dual Th1/Th2 and Tc1/Tc2 potentiating activity. Its adjuvant activity has previously been proven to be strictly dependent on its spatial co-localization with antigens, highlighting the role of local innate immunity in its mechanisms. However, its potential targets and pathways remain unclear. Here, its intracellular molecular mechanisms of innate immune response were explored using mouse C2C12 myoblast by integrative analysis of the in vivo and in vitro transcriptome in combination with experimental validations. AJSAF elicited a temporary cytotoxicity and inflammation towards C2C12 cells. Gene set enrichment analysis demonstrated that AJSAF regulated similar cell death- and inflammatory response-related genes in vitro and in vivo through activating second messenger–MAPK–CREB pathways. AJSAF markedly enhanced the Ca2+, cAMP, and reactive oxygen species levels and accelerated MAPK and CREB phosphorylation in C2C12 cells. Furthermore, Ca2+ chelator, CREB inhibitor, and MAPK inhibitors dramatically blocked the up-regulation of IL-6, CXCL1, and COX2 in AJSAF-treated C2C12 cells. Collectively, these results demonstrated that AJSAF induced innate immunity via Ca2+–MAPK–CREB pathways. This study is beneficial for insights into the molecular mechanisms of saponin adjuvants.

3β-hydroxy-12-oleanen-27-oic acid (ATA), a cytotoxic oleanane triterpenoid with C14-COOH isolated from the rhizome of Astilbe chinensis, has been previously proven to possess antitumor activity and may be a promising antitumor agent. However, its molecular mechanisms of antitumor action were still unclear. This study explored the underlying mechanisms of cytotoxicity and potential target of ATA against human colorectal cancer HCT116 cells via integrative analysis of transcriptomics and network pharmacology in combination with in vitro and in vivo experimental validations. ATA significantly inhibited the proliferation of HCT116 cells in a concentration- and time-dependent manner and induced the cell cycle arrest at the G0/G1 phase, apoptosis, autophagy, and ferroptosis. Transcriptomic analysis manifested that ATA regulated mRNA expression of the genes related to cell proliferation, cell cycle, and cell death in HCT116 cells. The integrated analysis of transcriptomics, network pharmacology, and molecular docking revealed that ATA exerted cytotoxic activity via interactions with FDFT1, PPARA, and PPARG. Furthermore, FDFT1 was verified to be an upstream key target mediating the antiproliferative effect of ATA against HCT116 cells. Of note, ATA remarkably suppressed the growth of HCT116 xenografts in nude mice and displayed an apparent attenuation of FDFT1 in tumor tissues accompanied by the alteration of the biomarkers of autophagy, cell cycle, apoptosis, and ferroptosis. These results demonstrate that ATA exerted in vitro and in vivo antiproliferative effects against HCT116 cells through inducing cell apoptosis, autophagy, and ferroptosis via targeting FDFT1.

Assembling new van der Waals (vdW) materials is challenging for the development of two-dimensional (2D) function devices. The MoW3X8 membrane (X = Se, Te) is a new 2D TMDs membrane molecule composed of one WX2 monolayer and one WX2-MoX2-WX2 sandwich trilayer. The presence of Mo/W atoms endows the new structure with the bridges between X atoms that connect pairs of MoX2/WX2 monolayers and the terminal sites that produce the van der Waals gap in these layers. The mirror symmetry is broken and the phonon dispersion is suppressed by reducing the dimensionality of the MoW3X8 membrane. In this work, the phonon transport and thermoelectric properties of the MoW3X8 membrane are investigated using first-principles method combined with the semi-classical Boltzmann transport and relaxation time approximation (RTA) theories. It is found that the larger gap between low-frequency and high-frequency optical branches in the membrane prevents atomic vibrations and drastically reduces the phonon velocity in a mid-frequency range below the gap. The low-lying optical and acoustic phonon modes are closely linked in MoW3Te8 membranes, enhancing the phonon–phonon scattering and thereby shortening the phonon relaxation time. These characteristics allow the MoW3Te8 membrane to achieve an extremely low lattice thermal conductivity of 0.49 Wm-1K−1 relative to that of the MoW3Se8 membrane (3.25 Wm-1K−1), which also leads to the improvement in thermoelectric performance of the former one. Besides, the maximum ZT values of 4 (4.5) at 900 K and the carrier concentration of 4 × 1011 cm−2 in the n-type (p-type) MoW3Te8 membrane could be enriched because of the low lattice thermal conductivity.

A diphenyl prolinol TMS ether-catalyzed stereoselective reaction of 1-bromo-2-naphthols with enals has been developed. The organocatalyzed cross coupling-like reaction servers an efficient approach to sterically congested (E)-α-naphthyl enals. The formal C(sp2)-C(sp2) cross-coupling products are obtained in good yields and with excellent stereoselectivities in favor of E-isomers. A broad range of aromatic enals and 1-bromo-2-naphthols are tolerated. The synthetic strategy significantly expands the scope of the organocatalytic cross-coupling-like reactions by enabling sterically demanding 1-bromo-2-naphthols as viable substrates.

Abstract Oral squamous cell carcinoma (OSCC), the eighth most prevalent cancer in the world, arises from the interaction of multiple factors including tobacco, alcohol consumption, and betel quid. Chemotherapeutic agents such as cisplatin, 5‐fluorouracil, and paclitaxel have now become the first‐line options for OSCC patients. Nevertheless, most OSCC patients eventually acquire drug resistance, leading to poor prognosis. With the discovery and identification of non‐coding RNAs (ncRNAs), the functions of dysregulated ncRNAs in OSCC development and drug resistance are gradually being widely recognized. The mechanisms of drug resistance of OSCC are intricate and involve drug efflux, epithelial‐mesenchymal transition, DNA damage repair, and autophagy. At present, strategies to explore the reversal of drug resistance of OSCC need to be urgently developed. Nano‐delivery and self‐cellular drug delivery platforms are considered as effective strategies to overcome drug resistance due to their tumor targeting, controlled release, and consistent pharmacokinetic profiles. In particular, the combined application of new technologies (including CRISPR systems) opened up new horizons for the treatment of drug resistance of OSCC. Hence, this review explored emerging regulatory functions of ncRNAs in drug resistance of OSCC, elucidated multiple ncRNA‐meditated mechanisms of drug resistance of OSCC, and discussed the potential value of drug delivery platforms using nanoparticles and self‐cells as carriers in drug resistance of OSCC.

BackgroundBone metastasis is a common adverse event in kidney cancer, often resulting in poor survival. However, tools for predicting KCBM and assessing survival after KCBM have not performed well.MethodsThe study uses machine learning to build models for assessing kidney cancer bone metastasis risk, prognosis, and performance evaluation. We selected 71,414 kidney cancer patients from SEER database between 2010 and 2016. Additionally, 963 patients with kidney cancer from an independent medical center were chosen to validate the performance. In the next step, eight different machine learning methods were applied to develop KCBM diagnosis and prognosis models while the risk factors were identified from univariate and multivariate logistic regression and the prognosis factors were analyzed through Kaplan-Meier survival curve and Cox proportional hazards regression. The performance of the models was compared with current models, including the logistic regression model and the AJCC TNM staging model, applying receiver operating characteristics, decision curve analysis, and the calculation of accuracy and sensitivity in both internal and independent external cohorts.ResultsOur prognosis model achieved an AUC of 0.8269 (95%CI: 0.8083–0.8425) in the internal validation cohort and 0.9123 (95%CI: 0.8979–0.9261) in the external validation cohort. In addition, we tested the performance of the extreme gradient boosting model through decision curve analysis curve, Precision-Recall curve, and Brier score and two models exhibited excellent performance.ConclusionOur developed models can accurately predict the risk and prognosis of KCBM and contribute to helping improve decision-making.

Polymeric nanoparticles (NPs) play an important role in controlled cancer drug delivery. Anticancer drugs can be conjugated or encapsulated by polymeric nanocarriers, which are known as polymeric nanomedicine. Polymeric nanomedicine has shown its potential in providing sustained release of drugs with reduced cytotoxicity and modified tumor retention, but until now, few delivery systems loading drugs have been able to meet clinical demands, so more efforts are needed. This research reviews the current state of the cancer drug-loading system by exhibiting a series of published articles that highlight the novelty and functions from a variety of different architectures including micelles, liposomes, dendrimers, polymersomes, hydrogels, and metal–organic frameworks. These may contribute to the development of useful polymeric NPs to achieve different therapeutic purposes.

Background: This study analyzed the phenotypes and genotypes of 41 Chinese families with inherited retinal dystrophy (IRD) and RPGR gene mutations.Methods: This retrospective analysis evaluated a cohort of 41 patients who were subjected to a specific Hereditary Eye Disease Enrichment Panel (HEDEP) analysis. All (likely) pathogenic variants were determined by Sanger sequencing, and co-segregation analyses were performed on the available family members. All cases were subjected to Sanger sequencing for RPGR open reading frame 15 (ORF15) mutations.Results: A total of 41 probands from different families with a clinical diagnosis of retinitis pigmentosa (RP; 34 cases) and cone-rod dystrophy (CORD; 7 cases) were included in this cohort. According to clinical information, 2, 18, and 21 cases were first assigned as autosomal dominant (AD), sporadic, and X-linked (XL) inheritance, respectively. Several cases of affected females who presented with a male phenotype have been described, posing challenges at diagnosis related to the apparent family history of AD. Mutations were located in RPGR exons or introns 1–14 and in ORF15 of 12 of 41 (29.3%) and 29 of 41 (70.7%) subjects, respectively. Thirty-four (likely) pathogenic mutations were identified. Frameshifts were the most frequently observed variants, followed by nonsense, splice, and missense mutations. Herein, a detailed description of four RP patients carrying RPGR intronic mutations is reported, and in vitro splice assays were performed to confirm the pathogenicity of these intronic mutations.Conclusion: Our findings provide useful insights for the genetic and clinical counseling of patients with XL IRD, which will be useful for ongoing and future gene therapy trials.

This study aims to evaluate the effectiveness of maternal inactivated COVID-19 vaccination before delivery for infants against Omicron infection in Guangzhou, China. A test-negative case-control design was conducted. This study selected infants born from 1 November 2021 to 23 November 2022 and tested for SARS-CoV-2 between 13 April 2022 and 30 November 2022 during outbreaks in Guangzhou. Multivariable logistic regression was performed to compare the maternal vaccination status of inactivated COVID-19 vaccines before delivery in cases and controls to estimate vaccine effectiveness (VE) for infants within 12 months. According to eligibility criteria, we finally selected 205 test-positive and 114 test-negative infants, as well as their mothers. The effectiveness of inactivated COVID-19 vaccines among fully vaccinated mothers was 48.4% (7.3% to 71.7%) for infants within 12 months, with the effectiveness of partial and booster vaccination showing no significant difference. Effectiveness for full vaccination presented a slight increase according to infants’ age at testing, with 49.6% (−12.3% to 78.4%) for 0–6 months and 59.9% (−0.6% to 84.4%) for over 6 months. A greater protective effect of two-dose vaccination was manifested in infants whose mother had received the second dose during the first trimester (65.9%, 95% CI: 7.7% to 87.9%) of pregnancy rather than preconception (43.5%, 95% CI: −8.7% to 71.1%). Moreover, VE could be improved to 77.1% (11.1% to 95.3%) when mothers received two doses both during pregnancy and 91.8% (41.1% to 99.6%) with receipt of a booster dose during pregnancy. Maternal vaccination with two doses of inactivated COVID-19 vaccines before delivery was moderately effective against Omicron infection in infants during the first 12 months of life. Full vaccination or a booster dose during pregnancy could confer better protection against Omicron for infants, although it might be overestimated due to the insufficient sample size in subgroups.

Bridge crack detection based on deep learning is a research area of great interest and difficulty in the field of bridge health detection. This study aimed to investigate the effectiveness of coupling a deep learning framework (DLF) with a convolutional neural network (CNN) for bridge crack detection. A dataset consisting of 2068 bridge crack images was randomly split into training, verification, and testing sets with a ratio of 8:1:1, respectively. Several CNN models, including Faster R-CNN, Single Shot MultiBox Detector (SSD), You Only Look Once (YOLO)-v5(x), U-Net, and Pyramid Scene Parsing Network (PSPNet), were used to conduct experiments using the PyTorch, TensorFlow2, and Keras frameworks. The experimental results show that the Harmonic Mean (F1) values of the detection results of the Faster R-CNN and SSD models under the Keras framework are relatively large (0.76 and 0.67, respectively, in the object detection model). The YOLO-v5(x) model of the TensorFlow2 framework achieved the highest F1 value of 0.67. In semantic segmentation models, the U-Net model achieved the highest detection result accuracy (AC) value of 98.37% under the PyTorch framework. The PSPNet model achieved the highest AC value of 97.86% under the TensorFlow2 framework. These experimental results provide optimal coupling efficiency parameters of a DLF and CNN for bridge crack detection. A more accurate and efficient DLF and CNN model for bridge crack detection has been obtained, which has significant practical application value.

Plants with the flower color phenotype of double-color flowers are very precious and attractive and can usually be regarded as valuable germplasm resources for studying and improving flower color. This paper summarizes the coloring mechanism of double-color flowers in plants from three aspects: the formation of double-color flowers, the physiological factors affecting the coloring difference of double-color flowers, and the molecular mechanism affecting the coloring difference of double-color flowers, to provide a theoretical reference for the in-depth study of the coloring mechanism and molecular breeding of double-color flowers in the future.

The Achilles tendon (AT) is responsible for running, jumping, and standing. The AT injuries are very common in the population. In the adult population (21–60 years), the incidence of AT injuries is approximately 2.35 per 1,000 people. It negatively impacts people’s quality of life and increases the medical burden. Due to its low cellularity and vascular deficiency, AT has a poor healing ability. Therefore, AT injury healing has attracted a lot of attention from researchers. Current AT injury treatment options cannot effectively restore the mechanical structure and function of AT, which promotes the development of AT regenerative tissue engineering. Various nanofiber-based scaffolds are currently being explored due to their structural similarity to natural tendon and their ability to promote tissue regeneration. This review discusses current methods of AT regeneration, recent advances in the fabrication and enhancement of nanofiber-based scaffolds, and the development and use of multiscale nanofiber-based scaffolds for AT regeneration.

Abstract Background Total glucosides of paeony (TGP), an active compound extracted from the roots of Paeonia lactiflora Pallas, has been increasingly used as the adjunctive therapy for rheumatoid arthritis (RA) patients. Though TGP could mitigate the unanticipated adverse effects during the conventional treatment of RA, high-quality evidence-based meta-analysis data on this subject are still insufficient. The objective of this study is to evaluate the clinical safety of TGP adjuvant therapy in the RA treatment. Methods PubMed, EMBASE, Web of Science, China Network Knowledge Infrastructure (CNKI), SinoMed and WanFang Data were retrieved for randomized controlled trials (RCTs) and cohort study about TGP adjuvant therapy in patients with RA up to 28 January 2021. Literatures with eligibility criteria and information were screened and extracted by two researchers independently. The RevMan5.3 software was used for data analysis with effect estimates as risk ratio (RR) with 95% confidence interval (CI). Results A total of 39 studies involving 3680 RA participants were included. There were 8 comparisons: TGP plus methotrexate (MTX) therapy versus MTX therapy, TGP plus leflunomide (LEF) therapy versus LEF therapy, TGP plus MTX and LEF therapy versus MTX plus LEF therapy, TGP plus tripterygium glycosides (TG) therapy versus TG therapy, TGP plus meloxicam (MLX) therapy versus MLX therapy and TGP plus sulfasalazine (SSZ) therapy versus SSZ therapy, TGP plus iguratimod (IGU) therapy versus IGU therapy, TGP plus prednisone acetate tablets (PAT) therapy versus PAT therapy. The meta-analysis results showed that the occurrence of hepatic adverse effect (RR = 0.31, 95% CI = 0.23–0.41, P

Smooth state switching and accurate speed tracking are important for the stability and reactivity of bipedal robots when running. However, previous studies have rarely been able to synthesize these two capabilities online. In this paper, we present an online running-gait generator for bipedal robots that allows for smooth state switching and accurate speed tracking. Considering a fluctuating height nature and computational expediency, the robot is represented by a simplified variable-height inverted-pendulum (VHIP) model. In order to achieve smooth state switching at the beginning and end of running, a segmented zero moment point (ZMP) trajectory optimization is proposed to automatically provide a feasible and smooth center-of-mass (CoM) trajectory that enables the robot to stably start or stop running at the given speed. To accurately track online the desired speed during running, we propose an iterative algorithm to compute target footholds, which allows for the robot to follow the interactive desired speed after the next two steps. Lastly, a numerical experiment and the simulation of online variable speed running were performed with position-controlled bipedal robot BHR7P, and the results verified the effectiveness of the proposed methods.

To reduce the coding computational complexity of the rate and distortion calculations in HEVC, a fast TU level rate model with higher accuracy was proposed.The contribution percentages of different syntax elements in entropy coding were evaluated, and syntax element-wise accurate rate models were individually developed to construct the whole TU level model.In addition, coefficient levels were weighted adaptively to distinguish the nonuniform contributions of different coefficients in terms of rate profiling.Moreover, position-wise parameter was defined to depict the distribution patterns for possible non-zero coefficients within one block.The final linear rate model was developed by fine-tuning the model parameters from great amounts of samples in a statistical way.Finally, the transform domain distortion model was also established to bypass unnecessary reconstruction process.Experimental results show that the proposed algorithm can achieve 49.76% complexity reduction with 1.74% BD-BR increase for RA configuration.

Municipal solid waste management is an important component of urban services that is often handled by local governments. Addis Ababa, the capital city of Ethiopia faces rapid urbanization leading to overcrowding and the development of shantytowns and poor neighborhoods. The general aim of this study was to appraise the present dry waste service provision of Addis Ababa. This study used an integrative literature review method with critical analysis to investigate the current solid waste management status in Addis Ababa. The results of this study show that the delivery of the service does not keep pace with the city's solid waste generation and the city's municipal disposal of solid waste is found in actual, low status and spatial coverage. This humble status of city garbage management is also heightened by three critical factors, i.e. poor institutional structure, inadequate disposal site and transfer station, and poor households' solid waste handling practices. Besides, the city households dominantly created decomposable solid wastes (60%) through generation amount of 0.45 kg/person/day and the main source are residential wastes, which account for 76% of the total waste. The sudy concluded that, the main problem with the incompetence of this sector in the city was the lack of trained labor and inadequate service delivery. In order to improve the status, there should be awareness creation, improvement of the city government, and implementation of an incorporated method to the management of metropolitan solid waste that respects and involves all stakeholders in the metropolis.

Abstract Background Diabetic kidney disease (DKD) is the main cause of end-stage kidney disease and has become a heavy economic and social burden due to its high prevalence and morbidity. The most effective strategy is that patients with DKD should be diagnosed and treated early. Preliminary studies showed that the Chinese herbal Tangshen Formula (TSF) may delay the progression of DKD, reducing microalbuminuria and macroalbuminuria and improving renal function. We designed a randomized, double-blind, placebo-controlled trial to evaluate the efficacy of TSF in patients with DKD. Methods/design This trial is a 13-center, randomized, double-blind, placebo-controlled study. A total of 632 participants will be randomized in a 1:1 ratio to an experiment group (TSF plus losartan) and a control group (placebo plus losartan). The trial cycle will last 24 weeks. The primary outcome will be the change in the urine microalbumin–creatinine ratio from baseline to week 24. The secondary outcome will be the change in the rate of progression to the clinical proteinuria period after intervention, the rate of urine microalbumin negative conversion, the rate of normal urinary microalbumin, the doubling rate of the baseline creatinine value and the glomerular filtration rate between the two groups. Safety in medication will also be evaluated. Discussion We hypothesize that patients with type 2 diabetes in the early stage of DKD will benefit from TSF. If successful, this study will provide evidence-based recommendations for clinicians. Trial registration ClinicalTrials.gov, NCT03009864. Registered January 2017.

Periodontitis (PD) is a common chronic infectious disease. The local inflammatory response in the host may cause the destruction of supporting periodontal tissue. Macrophages play a variety of roles in PD, including regulatory and phagocytosis. Moreover, under the induction of different factors, macrophages polarize and form different functional phenotypes. Among them, M1-type macrophages with proinflammatory functions and M2-type macrophages with anti-inflammatory functions are the most representative, and both of them can regulate the tendency of the immune system to exert proinflammatory or anti-inflammatory functions. M1 and M2 macrophages are involved in the destructive and reparative stages of PD. Due to the complex microenvironment of PD, the dynamic development of PD, and various local mediators, increasing attention has been given to the study of macrophage polarization in PD. This review summarizes the role of macrophage polarization in the development of PD and its research progress.

Hyphantria cunea Drury (Lepidoptera: Arctiidae) is a worldwide quarantine pest that has a wide range of host plants. Quercetin is a secondary metabolite involved in chemical defense processes in plants. To understand how H. cunea adapt to quercetin in its host plants, we determined the effects of quercetin on larval mortality, growth, nutritional indices, and the activity or content of detoxification enzymes in H. cunea larvae by feeding them an artificial diet containing different concentrations of quercetin. Our results showed that 0.50% quercetin treatment significantly prolonged the development duration of H. cunea larvae and inhibited growth of H. cunea. Nutritional indices analysis indicated that quercetin significantly affected nutrient use, including effects on the approximate digestibility, consumption index, relative growth rate, and efficiency of conversion of ingested food to body substance. Furthermore, our results revealed that quercetin reduced the content of carboxylesterases, and increased the activity or content of glutathione S-transferases, UDP-glucuronosyltransferases, and ATP-binding cassette transporters in H. cunea larvae. These results provide a foundation for revealing the adaptation that H. cunea use to adapt to quercetin in host plants.

The Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera: Liviidae) is the most widespread and devastating pest species in citrus orchards and is the natural vector of the phloem-limited bacterium that causes Huanglongbing (HLB) disease. Thus, reducing the population of D. citri is an important means to prevent the spread of HLB disease. Due to the long-term use of chemical control, biological control has become the most promising strategy. In this study, a novel highly pathogenic fungal strain was isolated from naturally infected cadavers of adult D. citri. The species was identified as Aspergillus fijiensis using morphological identification and phylogenetic analysis and assigned the strain name GDIZM-1. Tests to detect aflatoxin B1 demonstrated that A. fijiensis GDIZM-1 is a non-aflatoxin B1 producer. The pathogenicity of the strain against D. citri was determined under laboratory and greenhouse conditions. The results of the laboratory study indicated that nymphs from the 1st to 5th instar and adults of D. citri were infected by A. fijiensis GDIZM-1. The mortality of nymphs and adults of D. citri caused by infection with A. fijiensis increased with the concentration of the conidial suspension and exposure time, and the median lethal concentration (LC50) and median lethal time (LT50) values gradually decreased. The mortality of D. citri for all instars was higher than 70%, with high pathogenicity at the 7th day post treatment with 1 × 108 conidia/mL. The results of the greenhouse pathogenicity tests showed that the survival of D. citri adults was 3.33% on the 14th day post-treatment with 1 × 108 conidia/mL, which was significantly lower than that after treatment with the Metarhizium anisopliae GDIZMMa-3 strain and sterile water. The results of the present study revealed that the isolate of A. fijiensis GDIZM-1 was effective against D. citri and it provides a basis for the development of a new microbial pesticide against D. citri after validation of these results in the field.

Knee-stretched walking is considered to be a human-like and energy-efficient gait. The strategy of extending legs to obtain vertical center of mass trajectory is commonly used to avoid the problem of singularities in knee-stretched gait generation. However, knee-stretched gait generation utilizing this strategy with toe-off and heel-strike has kinematics conflicts at transition moments between single support and double support phases. In this article, a knee-stretched walking generation with toe-off and heel-strike for the position-controlled humanoid robot has been proposed. The position constraints of center of mass have been considered in the gait generation to avoid the kinematics conflicts based on model predictive control. The method has been verified in simulation and validated in experiment.

Background: The role of vitamin B12 and folate levels with risk of gestational diabetes mellitus (GDM) is unclear. The purpose of the current study was to conduct a systematic review and meta-analysis for assessing the relationship between vitamin B12 and folate concentrations during pregnancy and the risk of GDM.Methods: PubMed, Embase, CENTRAL, and Ovid databases were searched up to 10th December, 2020 for all types of studies assessing the relationship. Qualitative and quantitative analysis of data was carried out.Results: Twelve studies were included. Pooled serum vitamin B12 concentrations were found to be significantly lower in the GDM group as compared to the non-GDM group. No such difference was noted in serum folate levels. On pooled analysis of adjusted odds ratio's for risk of GDM with red blood cell (RBC) folate, serum folate, and vitamin B12 as continuous variables, no significant relationship was seen. On qualitative analysis, studies reported higher RBC folate levels with a significantly increased risk of GDM. Majority studies reported no relationship between serum folate and risk of GDM. Four of six studies reported a lowered risk of GDM with higher or normal vitamin B12 levels.Conclusion: The association between vitamin B12 and folate levels during pregnancy and the risk of GDM is unclear. Limited number of studies indicate increased risk of GDM with higher RBC folate levels, but majority studies found no association between serum folate and risk of GDM. Based on available studies, the association between the risk of GDM with vitamin B12 deficiency is conflicting. There is a need for further large-scale studies from different regions worldwide to strengthen current evidence.

Periodontitis is a type of systemic immune inflammation that is caused by the complex infection of a variety of microorganisms in the subgingival plaque and the imbalance of the microbial ecological environment in the mouth. Periodontitis and chronic kidney disease (CKD) share many risk factors, such as obesity, smoking, and age. A growing body of data supports a strong correlation between periodontitis and kidney disease. Evidence supports the role of periodontal inflammation and elevated serum inflammatory mediators in renal atherosclerosis, renal deterioration, and end-stage renal disease (ESRD) development. Periodontitis is a risk factor for kidney disease. However, to our knowledge, there are few studies detailing the possible link between periodontitis and CKD. This review summarizes the possible mechanisms underlying periodontitis and CKD. More importantly, it highlights novel and potential pathogenic factors for CKD, including bacteria, pro-inflammatory mediators and oxidative stress. However, most research on the relationship between periodontitis and systemic disease has not determined causality, and these diseases are largely linked by bidirectional associations. Future research will focus on exploring these links to contribute to new treatments for CKD.

Abstract There is growing evidence that regions of the genome that cannot encode proteins play an important role in diseases. These regions are usually transcribed into long non-coding RNAs (lncRNAs). LncRNAs, little or no coding potential, are defined as capped transcripts longer than 200 nucleotides. New sequencing technologies have shown that a large number of aberrantly expressed lncRNAs are associated with multiple cancer types and indicated they have emerged as an important class of pervasive genes during the development and progression of cancer. However, the underlying mechanism in cancer is still unknown. Therefore, it is necessary to elucidate the lncRNA function. Notably, many lncRNAs dysregulation are associated with Oral squamous cell carcinoma (OSCC) and affect various aspects of cellular homeostasis, including proliferation, survival, migration or genomic stability. This review expounds the up- or down-regulation of lncRNAs in OSCC and the molecular mechanisms by which lncRNAs perform their function in the malignant cell. Finally, the potential of lncRNAs as non-invasive biomarkers for OSCC diagnosis are also described. LncRNAs hold promise as prospective novel therapeutic targets, but more research is needed to gain a better understanding of their biologic function.

The energy management strategy is the key to achieve fuel cell hybrid system operation with high-efficiency and low-energy cost. The widely used energy management strategies are established based on the fixed models of power sources energy consumption and efficiency. However, due to the gradual performance degradation of the fuel cell during the service period, some model parameters will change significantly and the fixed models will become increasingly inaccurate over time. Therefore, this paper established time-varying models of power sources energy consumption and efficiency by introducing the fuel cell degradation rate. On this basis, in order to reduce the energy consumption of the system, improve the fuel cell efficiency and relatively maintain the SOC level, a novel dual-mode energy management strategy, DMDEE, for hybrid vehicles was proposed. In order to improve the online operation speed of proposed energy management strategy, the optimal control rules were obtained by offline calculation first. Then through comparison experiments with other two energy management strategies, PMP and PF, it was verified that the proposed strategy can effectively reduce the system energy consumption and improve the efficiency of the fuel cell system, meanwhile could make the SOC regress after its deviating from ideal working area. In addition, the mode switching hysteresis control was also validated. Therefore, the effectiveness and superiority of the proposed energy management strategy in this paper has been verified.

Fractional vegetation cover (FVC) is an important indicator of ecosystem changes. Both satellite remote sensing and ground measurements are common methods for estimating FVC. However, desert vegetation grows sparsely and scantly and spreads widely in desert regions, making it challenging to accurately estimate its vegetation cover using satellite data. In this study, we used RGB images from two periods: images from 2006 captured with a small, light manned aircraft with a resolution of 0.1 m and images from 2019 captured with an unmanned aerial vehicle (UAV) with a resolution of 0.02 m. Three pixel-based machine learning algorithms, namely gradient enhancement decision tree (GBDT), k-nearest neighbor (KNN) and random forest (RF), were used to classify the main vegetation (woody and grass species) and calculate the coverage. An independent data set was used to evaluate the accuracy of the algorithms. Overall accuracies of GBDT, KNN and RF for 2006 image classification were 0.9140, 0.9190 and 0.9478, respectively, with RF achieving the best classification results. Overall accuracies of GBDT, KNN and RF for 2019 images were 0.8466, 0.8627 and 0.8569, respectively, with the KNN algorithm achieving the best results for vegetation cover classification. The vegetation coverage in the study area changed significantly from 2006 to 2019, with an increase in grass coverage from 15.47 ± 1.49% to 27.90 ± 2.79%. The results show that RGB images are suitable for mapping FVC. Determining the best spatial resolution for different vegetation features may make estimation of desert vegetation coverage more accurate. Vegetation cover changes are also important in terms of understanding the evolution of desert ecosystems.

From the perspective of treating wastes with wastes, bamboo sawdust was integrated with a hydroxyapatite (HAP) precursor to create engineered nano-HAP/micro-biochar composites (HBCs) by optimizing the co-precipitated precursor contents and co-pyrolysis temperature (300, 450, 600 °C). The physicochemical properties of HBCs, including morphologies, porosities, component ratios, crystalline structures, surface elemental chemical states, surface functional groups, and zeta potentials as a function of carbonization temperatures and components of precursors, were studied. Biochar matrix as an efficient carrier with enhanced specific surface area to prevent HAP from aggregation was desired. The sorption behavior of heavy metal (Cu(II), Cd(II), and Pb(II)) and pharmaceuticals (carbamazepine and tetracycline) on HBCs were analyzed given various geochemical conditions, including contact time, pH value, ionic strength, inferencing cations and anions, coexisting humic acid, and ambient temperature. HBCs could capture these pollutants efficiently from both simulated wastewaters and real waters. Combined with spectroscopic techniques, proper multiple dominant sorption mechanisms for each sorbate were elucidated separately. HBCs presented excellent reusability for the removal of these pollutants through six recycles, except for tetracycline. The results of this study provide meaningful insight into the proper integration of biochar–mineral composites for the management of aquatic heavy metals and pharmaceuticals.

Background: Diabetic retinopathy (DR) is one of the most common and severe microvascular complications of diabetes mellitus (DM), which results in blindness among adults worldwide. Presently, the efficacy of drug treatments for diabetic retinopathy (DR) is not satisfactory, thus urgently necessitating effective drug treatment measures. TangWang prescription (TWP) has been found to have retinal protection effects in previous clinical and basic research. However, there is a lack of rigorous, randomized, and controlled studies. This study aims to evaluate the efficacy and safety of TWP in delaying the development of DR.Methods: This study is a randomized, double-blind, placebo-controlled, parallel-group, multicenter clinical trial, consisting of 384 participants to be randomized in a 1:1 ratio in the treatment and control groups. Furthermore, the treatment and control groups will be administered the TangWang prescription and the placebo, respectively, each at a dose of one bag twice a day. The study period will last for 48 weeks. The primary outcome measure will be the changes in the degree of retinal microvascular lesions before and after treatment. The secondary outcome will be changes in the degree of hemangioma, microvascular bleeding, microvascular leakage, macular edema, and vision. All statistical tests will be two-sided, and a p < 0.05 will be considered statistically significant.Discussion: We hypothesize that the patients with DR will benefit from TangWang prescription, and in addition to the central random system and platform of dynamic information collection, the patients’ conditions will be monitored, and the data collected for analysis. If successful, this study will provide evidence that the TWP formulation delays in the progression of DR.Trial registration: The design of this trial has been registered with the ClinicalTrials.gov (NCT03025399).

Studying the high-temperature mechanical properties of rocks is of great significance to engineering disasters caused by deep rock mining and underground protection projects. In view of insufficient research on the high-temperature mechanical properties of deep rocks in southwestern China, we used high-temperature heating devices and statics equipment to conduct static tests on Skarn. XW7L-12 box-type resistance furnace was adopted to heat Skarn (25°C, 200°C, 400°C, 600°C, and 800°C), and the temperature effect of its basic physical parameters (density and wave velocity) was measured and analyzed. Uniaxial compression experiments were performed on two cooling methods of Skarn (natural cooling and water cooling) by a constant stress pressure testing machine to obtain a stress-strain curve and analyze its statics index (peak strength, tensile strength, elastic modulus, and peak strain) and the change rule of failure mode with temperature rise and different cooling methods. With the temperature increasing, various static mechanical indexes of Skarn will be greatly affected. Meanwhile, the different cooling methods are not related to the change trend of the mechanical properties of Skarn under high temperature.

The rapid settlement of tailings is an important technical guarantee for the continuous production of downhole filling. The selection of a reasonable flocculant is essential for accelerating the settlement speed of classified fine tailings. The present paper conducts indoor static sedimentation experiments, NMR observation, electron microscope scanning, and other methods to analyze the porosity and pore-size distribution characteristics of floc solution for classified fine tailing under four flocculants, namely, ZYZ, ZYD, JYC-1, and JYC-2. The dimension, spatial distribution characteristics, particle size characteristics, and morphological characteristics of the scanning electron microscope images of floc were studied. Results show that the unit consumption of flocculant at 30 g/t is the critical value for increasing the flocculation and sedimentation effect of the classified fine tailings solution. The highest distribution percentage of small-sized classified fine tailings and the lowest average pore size was observed under the ZYZ-type flocculant. This flocculant also obtained the lowest porosity, largest average floc size, largest area occupied by the floc, lowest pore percentage, and the densest floc structure. Thus, this flocculant showed the best flocculation effect. A negative correlation was observed between the equivalent diameter of floc with varying settlement heights. The dimension of floc increased with the decrease in bed settlement height, and the overall structure of the floc gradually transitioned from loose to dense from top to bottom. The present paper characterizes the microscopic morphology and spatial structure characteristics of floc under different flocculants from a microscopic point of view. The present paper also provides a scientific basis for the selection of the optimal flocculant.