Targeting gut and intratumoral microbiota: a novel strategy to improve therapy resistance in cancer with a focus on urologic tumors.

INTRODUCTION: Growing attention has been drawn to urologic tumors due to their rising incidence and suboptimal clinical treatment outcomes. Cancer therapy resistance poses a significant challenge in clinical oncology, limiting the efficacy of conventional treatments and contributing to disease progression. Recent research has unveiled a complex interplay between the host microbiota and cancer cells, highlighting the role of the microbiota in modulating therapeutic responses. AREAS COVERED: We used the PubMed and Web of Science search engines to identify key publications in the fields of tumor progression and urologic tumor treatment, specifically focusing on the role of the microbiota. In this review, we summarize the current literature on how microbiota influence the tumor microenvironment and anti-tumor immunity, as well as their impact on treatments for urinary system malignancies, highlighting promising future applications. EXPERT OPINION: We explore how the composition and function of the gut microbiota influence the tumor microenvironment and immune response, ultimately impacting treatment outcomes. Additionally, we discuss emerging strategies targeting the microbiota to enhance therapeutic efficacy and overcome resistance. The application of antibiotics, fecal microbiota transplantation, and oncolytic bacteria has improved tumor treatment outcomes, which provides a novel insight into developing therapeutic strategies for urologic cancer.

Noncoding RNA Terc-53 and hyaluronan receptor Hmmr regulate ageing in mice.

One of the basic questions in the ageing field is whether there is fundamental difference between the ageing of lower invertebrates and mammals. A major difference between the lower invertebrates and mammals is the abundancy of noncoding RNAs, most of which are not conserved. We have previously identified a noncoding RNA Terc-53 that is derived from the RNA component of telomerase Terc. To study its physiological functions, we generated two transgenic mouse models overexpressing the RNA in wild-type and early-ageing Terc-/- backgrounds. Terc-53 mice showed age-related cognition decline and shortened life span, even though no developmental defects or physiological abnormality at early age was observed, indicating its involvement in normal ageing of mammals. Subsequent mechanistic study identified hyaluronan-mediated motility receptor (Hmmr) as the main effector of Terc-53. Terc-53 mediates the degradation of Hmmr, leading to an increase of inflammation in the affected tissues, accelerating organismal ageing. AAV-delivered supplementation of Hmmr in the hippocampus reversed the cognition decline in Terc-53 transgenic mice. Neither Terc-53 nor Hmmr has homologs in C. elegans. Neither do arthropods express hyaluronan (Stern 2017). These findings demonstrate the complexity of ageing in mammals, and open new paths for exploring noncoding RNA and Hmmr as means of treating age-related physical debilities and improving healthspan.

ANT2 functions as a translocon for mitochondrial cross-membrane translocation of RNAs.

Bidirectional transcription of mammalian mitochondrial DNA generates overlapping transcripts that are capable of forming double-stranded RNA (dsRNA) structures. Release of mitochondrial dsRNA into the cytosol activates the dsRNA-sensing immune signaling, which is a defense mechanism against microbial and viral attack and possibly cancer, but could cause autoimmune diseases when unchecked. A better understanding of the process is vital in therapeutic application of this defense mechanism and treatment of cognate human diseases. In addition to exporting dsRNAs, mitochondria also export and import a variety of non-coding RNAs. However, little is known about how these RNAs are transported across mitochondrial membranes. Here we provide direct evidence showing that adenine nucleotide translocase-2 (ANT2) functions as a mammalian RNA translocon in the mitochondrial inner membrane, independent of its ADP/ATP translocase activity. We also show that mitochondrial dsRNA efflux through ANT2 triggers innate immunity. Inhibiting this process alleviates inflammation in vivo, providing a potential therapeutic approach for treating autoimmune diseases.

How much nutrient reaches a stream: Insights from a hybrid model and implications for watershed nitrogen export and removal.

Excess nitrogen (N) discharged into streams and rivers degrades freshwater quality and threatens ecosystems worldwide. Land use patterns may influence riverine N export, yet the effect of location on N export and removal is not fully understood. We proposed a hybrid model to analyze N export and removal within the watersheds. The proposed model is satisfied for the riverine N modelling. The KGE and R2 are 0.75 and 0.72 in the calibration period which are 0.76 and 0.61 in the validation period. Human-impacted land use may modify the N yield in the watershed, and the net N export from built-up to the in-stream system was highest in the urbanized sub-watersheds (0.81), followed by the agricultural sub-watersheds (0.88), and forested sub-watersheds (0.96). Agricultural activities make a large contribution to the N exports in the watersheds, and the mean N input from the agricultural land use to in-stream were 2069-4353 kg km-2 yr-1. Besides, the excess inputs of N by overapplication of fertilizer and manure during the agricultural activities may increase legacy N in soil and groundwater. Biological processes for the riverine N removal may be controlled by the available substrate in the freshwater system, and temperature sensitivity of denitrification is highest in the flood seasons, especially for the human-impacted sub-watersheds. The riverine biological processes may be limited by other competitions. Our model results provide evidence that quantity and location of specific land use may control biogeochemistry within watersheds. We demonstrate the need to understand nutrient export and removal within watersheds by improving the representation of spatial patterns in existing watershed models, and we consider this study to be a new effort for the spatially explicit modeling to support land-use based N management in watersheds.

A new species of Populus and the extensive hybrid speciation arising from it on the Qinghai-Tibet Plateau.

While the diversity of species formation is broadly acknowledged, significant debate exists regarding the universal nature of hybrid species formation. Through an 18-year comprehensive study of all Populus species on the Qinghai-Tibet Plateau, 23 previously recorded species and 8 new species were identified. Based on morphological characteristics, these can be classified into three groups: species in section Leucoides, species with large leaves, and species with small leaves in section Tacamahaca. By conducting whole-genome re-sequencing of 150 genotypes from these 31 species, 2.28 million single nucleotide polymorphisms (SNPs) were identified. Phylogenetic analysis utilizing these SNPs not only revealed a highly intricate evolutionary network within the large-leaf species of section Tacamahaca but also confirmed that a new species, P. curviserrata, naturally hybridized with P. cathayana, P. szechuanica, and P. ciliata, resulting in 11 hybrid species. These findings indicate the widespread occurrence of hybrid species formation within this genus, with hybridization serving as a key evolutionary mechanism for Populus on the plateau. A novel hypothesis, "Hybrid Species Exterminating Their Ancestral Species (HSEAS)," is introduced to explain the mechanisms of hybrid species formation at three different scales: the entire plateau, the southeastern mountain region, and individual river valleys.

A bioengineered anti-VEGF protein with high affinity and high concentration for intravitreal treatment of wet age-related macular degeneration.

Intravitreal (IVT) injection of anti-vascular endothelial growth factor (anti-VEGF) has greatly improved the treatment of many retinal disorders, including wet age-related macular degeneration (wAMD), which is the third leading cause of blindness. However, frequent injections can be difficult for patients and may lead to various risks such as elevated intraocular pressure, infection, and retinal detachment. To address this issue, researchers have found that IVT injection of anti-VEGF proteins at their maximally viable concentration and dose can be an effective strategy. However, the intrinsic protein structure can limit the maximum concentration due to stability and solution viscosity. To overcome this challenge, we developed a novel anti-VEGF protein called nanoFc by fusing anti-VEGF nanobodies with a crystallizable fragment (Fc). NanoFc has demonstrated high binding affinity to VEGF165 through multivalency and potent bioactivity in various bioassays. Furthermore, nanoFc maintains satisfactory chemical and physical stability at 4°C over 1 month and is easily injectable at concentrations up to 200 mg/mL due to its unique architecture that yields a smaller shape factor. The design of nanoFc offers a bioengineering strategy to ensure both strong anti-VEGF binding affinity and high protein concentration, with the goal of reducing the frequency of IV injections.

Use of the improved tug-of-war acupuncture for promoting cartilage repair by inducing macrophage polarization in knee osteoarthritis.

Introduction: Knee osteoarthritis (KOA) is a type of joint disease causing degenerative changes that are challenging to treat. The improved tug-of-war acupuncture (BHZF) can improve joint pain in KOA. However, the associated mechanism has not been validated. Methods: The KOA rabbit model was established. After the surgery, the improved BHZF was provided as an intervention, and the animals were euthanized after 2 weeks. Histopathological changes in the synovium and cartilage were observed on hematoxylin & eosin staining and Safranin O-Fast Green staining. Synovial fluid and serum samples were collected to assess the presence of cytokines using the enzyme-linked immunosorbent assay. The expression of M1 macrophage (CD86) and M2 macrophage (ARG1) markers in the cartilage and synovium was detected via immunohistochemistry and immunofluorescence assays. Results: The improved BHZF could reduce KOA-related pain and inhibit joint swelling. Further, it significantly maintained the morphology of articular chondrocytes in KOA and reduced the decomposition of the cartilage matrix. Then, it significantly reduced the expression of CD86-positive cells (P < 0.05), and increased the expression of ARG1-positive cells in the cartilage and synovium (P < 0.05). Moreover, it significantly decreased the expression of inflammatory factors interleukin (IL)-1 beta and tumor necrosis factor-alpha in the serum and synovial fluid (P < 0.05), and significantly increased the expression levels of anti-inflammatory cytokines IL-4 and IL-10 (P < 0.05). Conclusions: The improved BHZF can relieve pain and improve cartilage damage by regulating macrophage polarization in KOA.

The effect of morphology and crystal structure on the photocatalytic and photoelectrochemical performances of WO3.

A template-based solvothermal method was successfully developed for the controlled synthesis of two-dimensional (2D) monoclinic WO3 nanoplate/nanosheet arrays and three-dimensional (3D) hexagonal WO3 nanosphere/nanocage structures with single crystal petals. The structure-directing agents played an important role in controlling the morphology and phase of WO3 samples. The results showed that the WO3 nanospheres exhibited the highest visible light absorption capacity and a photocurrent density of 0.37 mA cm-2 at 1.23 V vs. RHE under simulated sunlight. Moreover, the photocatalytic dye results displayed 83.2% methylene blue degradation and 87.9% rhodamine B degradation within 120 min under visible light irradiation. The high performance of the WO3 nanospheres, resulted from the hierarchical structure, increased surface area and enhanced light absorption, which improved the photogenerated charge carrier transfer and separation capability.

A model of hybrid speciation process drawn from three new poplar species originating from distant hybridization between sections.

Although numerous studies have been conducted on hybrid speciation, our understanding of this process remains limited. Through an 18-year systematic investigation of all taxa of Populus on the Qinghai-Tibet Plateau, we discovered three new taxa with clear characteristics of sect. Leucoides. Further evidence was gathered from morphology, whole-genome bioinformatics, biogeography, and breeding to demonstrate synthetically that they all originated from distant hybridization between sect. Leucoides and sect. Tacamahaca. P. gonggaensis originated from the hybridization of P. lasiocarpa with P. cathayana, P. butuoensis from the hybridization of P. wilsonii with P. szechuanica, and P. dafengensis from the hybridization of P. lasiocarpa with P. szechuanica. Due to heterosis, the three hybrid taxa possess greater ecological adaptability than their ancestral species. We propose a hybrid speciation process model that incorporates orthogonal, reverse, and backcrossing events. This model can adequately explain some crucial evolutionary concerns, such as the nuclear-cytoplasmic conflict on phylogeny and the extinction of ancestral species within the distribution range of hybrid species.

Genome-wide identification and characterization of the RZFP gene family and analysis of its expression pattern under stress in Populus trichocarpa.

Forest trees face many abiotic stressors during their lifetime, including drought, heavy metals, high salinity, and chills, affecting their quality and yield. The RING-type ubiquitin ligase E3 is an invaluable component of the ubiquitin-proteasome system (UPS) and participates in plant growth and environmental interactions. Interestingly, only a few studies have explored the RING ZINC FINGER PROTEIN (RZFP) gene family. This study identified eight PtrRZFPs genes in the Populus genome, and their molecular features were analyzed. Gene structure analysis revealed that all PtrRZFPs genes contained >10 introns. Evolutionarily, the RZFPs were separated into four categories, and segmental replication events facilitated their amplification. Notably, many stress-related elements have been identified in the promoters of PtrRZFPs using Cis-acting element analysis. Moreover, some PtrRZFPs were significantly induced by drought and sorbitol, revealing their potential roles in regulating stress responses. Particularly, overexpression of the PtrRZFP1 gene in poplars conferred excellent drought tolerance; however, PtrRZFP1 knockdown plants were drought-sensitive. We identified the potential upstream transcription factors of PtrRZFPs and revealed the possible biological functions of RZFP1/4/7 in resisting osmotic and salt stress, laying the foundation for subsequent biological function studies and providing genetic resources for genetic engineering breeding for drought resistance in forest trees. This study offers crucial information for the further exploration of the functions of RZFPs in poplars.

A data-driven framework to assess population dynamics during novel coronavirus outbreaks: A case study on Xiamen Island, China.

The outbreak of the Coronavirus Disease 2019 (COVID-19) has profoundly influenced daily life, necessitating the understanding of the relationship between the epidemic's progression and population dynamics. In this study, we present a data-driven framework that integrates GIS-based data mining technology and a Susceptible, Exposed, Infected and Recovered (SEIR) model. This approach helps delineate population dynamics at the grid and community scales and analyze the impacts of government policies, urban functional areas, and intercity flows on population dynamics during the pandemic. Xiamen Island was selected as a case study to validate the effectiveness of the data-driven framework. The results of the high/low cluster analysis provide 99% certainty (P < 0.01) that the population distribution between January 23 and March 16, 2020, was not random, a phenomenon referred to as high-value clustering. The SEIR model predicts that a ten-day delay in implementing a lockdown policy during an epidemic can lead to a significant increase in the number of individuals infected by the virus. Throughout the epidemic prevention and control period (January 23 to February 21, 2020), residential and transportation areas housed more residents. After the resumption of regular activities, the population was mainly concentrated in residential, industrial, and transportation, as well as road facility areas. Notably, the migration patterns into and out of Xiamen were primarily centered on neighboring cities both before and after the outbreak. However, migration indices from cities outside the affected province drastically decreased and approached zero following the COVID-19 outbreak. Our findings offer new insights into the interplay between the epidemic's development and population dynamics, which enhances the prevention and control of the coronavirus epidemic.

Development of a Sandwiched Piezoelectric Accelerometer for Low-Frequency and Wide-Band Seismic Exploration.

A sandwiched piezoelectric accelerometer is developed and optimized for acquiring low-frequency, wide-band seismic data. The proposed accelerometer addresses the challenges of capturing seismic signals in the low-frequency range while maintaining a broad frequency response through the design of multi-stage charge amplifiers and a sandwiched structure. The device's design, fabrication process, and performance evaluation are discussed in detail. Experimental results demonstrate its performance in amplitude and phase response characteristics.

Polymorphic nanobody crystals as long-acting intravitreal therapy for wet age-related macular degeneration.

Wet age-related macular degeneration (wet AMD) is the most common cause of blindness, and chronic intravitreal injection of anti-vascular endothelial growth factor (VEGF) proteins has been the dominant therapeutic approach. Less intravitreal injection and a prolonged inter-injection interval are the main drivers behind new wet AMD drug innovations. By rationally engineering the surface residues of a model anti-VEGF nanobody, we obtained a series of anti-VEGF nanobodies with identical protein structures and VEGF binding affinities, while drastically different crystallization propensities and crystal lattice structures. Among these nanobody crystals, the P212121 lattice appeared to be denser and released protein slower than the P1 lattice, while nanobody crystals embedding zinc coordination further slowed the protein release rate. The polymorphic protein crystals could be a potentially breakthrough strategy for chronic intravitreal administration of anti-VEGF proteins.

Linking ecosystem service flow to water-related ecological security pattern: A methodological approach applied to a coastal province of China.

Water security is a critical concern due to intensifying anthropogenic activities and climate change. Delineating a water-related ecological security pattern can help to optimize spatial configuration, which in turn can inform sustainable water management. However, the methodology remains unclear. In this study, we developed a framework linking ecosystem service flow to water-related ecological security pattern; hence, we identified the sources, sinks, key corridors, and vulnerable nodes in Fujian Province, China. Our results revealed that the sources were located inland at high altitudes with a decreasing area trend in the south and an increasing area trend in the north, whereas the sinks were spread in coastal areas and exhibited a decreasing trend with relatively stable spatial distribution. The water-related ecological security has degraded as represented by a decreasing ecological supply-demand ratio over the last 30 years. Key corridors were identified in 17.12% of the rivers, and 22.5% of the vulnerable nodes were recognized as early warning nodes. Climate variability affected source distribution, while anthropogenic activities drove sink dynamics. These findings have important implications including landscape pattern planning and sustainable water management in the context of accelerated land use/cover and climate changes.

Gut Microbiota and Tumor Immune Escape: A New Perspective for Improving Tumor Immunotherapy.

The gut microbiota is a large symbiotic community of anaerobic and facultative aerobic bacteria inhabiting the human intestinal tract, and its activities significantly affect human health. Increasing evidence has suggested that the gut microbiome plays an important role in tumor-related immune regulation. In the tumor microenvironment (TME), the gut microbiome and its metabolites affect the differentiation and function of immune cells regulating the immune evasion of tumors. The gut microbiome can indirectly influence individual responses to various classical tumor immunotherapies, including immune checkpoint inhibitor therapy and adoptive immunotherapy. Microbial regulation through antibiotics, prebiotics, and fecal microbiota transplantation (FMT) optimize the composition of the gut microbiome, improving the efficacy of immunotherapy and bringing a new perspective and hope for tumor treatment.

Spatial distribution and potential ecological risk of metal(loid)s in cultivated land from Xianjia Town in Fujian, Southeast China.

Metal(loid)s in cultivated land become an important issue with respect to human health and food security. However, it remains challenging to identify metal(loid) pollution characteristics due to varying environmental settings at the local scale. In this study, the geographic information system and categorical regression model were applied to analyze the spatial distribution and influencing factors of metal(loid)s in cultivated land using 90 sampling sites in Xianjia Town, Southeast China. The pollution levels and ecological risks of five metal(loid)s-Cd, Pb, Cr, Hg, and As-were further investigated using the single pollution index (PI), Nemerow comprehensive pollution index (PN), and potential ecological risk index (RI). The results indicate that the cultivated soils were affected by Cd and Pb pollution, with 3.06 and 6.30 times higher average concentrations than the soil environment background values (SEBV) of Fujian Province, respectively. Based on the CATREG model, crop type had a great impact on Pb and Hg contents. Cr contents were higher in rice fields, while Hg and As concentrations were higher in turmeric fields. Cr and Hg contents under five crop types did not exceed the SEBV of Fujian Province. The average Pb contents in rice fields were 1.25 and the Cd contents in vegetable fields 1.09 times higher than the average value in sampled soils. According to the RI, 63.66% of the sampling points were at medium to high risk. These findings enhance our understanding of the metal(loid)s pollution characteristics and their ecological risks in cultivated land at the local scale.

A method for detecting the non-stationarity during high flows under global change.

The sustainability of existing water resources is influenced by extreme streamflow, and climate variability and human activities are generally the major factors controlling these dynamics. However, most of previously proposed methods to determine the effects of these factors have only been developed under the assumption of stationarity. Therefore, to overcome the existing research gap, an innovative method was proposed in this study to analyze and distinguish the effects of climate variability and human activities on extreme streamflow based on the non-stationarity theory. Accordingly, a rainfall-runoff model was developed using long-term hydrological data in the watersheds of Southeast China, which cover >75,000 km2. The model proposed in this study showed an acceptable performance, as indicated by the Nash-Sutcliffe efficiency coefficient (NSE), the Kling-Gupta efficiency (KGE), and percent bias (PBIAS). The NSE, KGE, and |PBIAS| were 0.67-0.75, 0.57-0.74, and 1.22-16.79 during the calibration periods, respectively. And the NSE, KGE, and |PBIAS| were 0.69-0.77, 0.65-0.76, and 0.98-17.51 during the calibration periods, respectively. The trends of the extreme streamflow were analyzed for these watersheds at different time scales. The streamflow extremes at short time scales were found to be more sensitive to changing environment than those at longer time scales. The major factor controlling streamflow extremes at short time scales was human activities and climate change may be the dominant factor influencing streamflow extremes at long time scales. The findings of this study could provide useful insights into water management under global change conditions.

Machine learning-based estimation of riverine nutrient concentrations and associated uncertainties caused by sampling frequencies.

Accurate and sufficient water quality data is essential for watershed management and sustainability. Machine learning models have shown great potentials for estimating water quality with the development of online sensors. However, accurate estimation is challenging because of uncertainties related to models used and data input. In this study, random forest (RF), support vector machine (SVM), and back-propagation neural network (BPNN) models are developed with three sampling frequency datasets (i.e., 4-hourly, daily, and weekly) and five conventional indicators (i.e., water temperature (WT), hydrogen ion concentration (pH), electrical conductivity (EC), dissolved oxygen (DO), and turbidity (TUR)) as surrogates to individually estimate riverine total phosphorus (TP), total nitrogen (TN), and ammonia nitrogen (NH4+-N) in a small-scale coastal watershed. The results show that the RF model outperforms the SVM and BPNN machine learning models in terms of estimative performance, which explains much of the variation in TP (79 ± 1.3%), TN (84 ± 0.9%), and NH4+-N (75 ± 1.3%), when using the 4-hourly sampling frequency dataset. The higher sampling frequency would help the RF obtain a significantly better performance for the three nutrient estimation measures (4-hourly > daily > weekly) for R2 and NSE values. WT, EC, and TUR were the three key input indicators for nutrient estimations in RF. Our study highlights the importance of high-frequency data as input to machine learning model development. The RF model is shown to be viable for riverine nutrient estimation in small-scale watersheds of important local water security.

Genome-wide analysis and expression profiling of Cation/H+ exchanger (CAX) family genes reveal likely functions in cadmium stress responses in poplar.

Cadmium, a toxic heavy metal, seriously affects human health and ecological security. The cation/H+ exchanger (CAX) family is a unique metal transporter that plays a crucial role in Cd acquisition, transfer, and remission in plants. Although there are many studies related to the genome-wide analysis of Populus trichocarpa, little research has been done on the CAX family genes, especially concerning Cd stress. In this study, genome-wide analysis of the Populus CAX family identified seven stress-related CAX genes. The evolutionary tree indicated that the CaCA family genes were grouped into four clusters. Moreover, seven pairs of genes were derived by segmental duplication in poplars. Cis-acting element analysis identified numerous stress-related elements in the promoters of diverse PtrCAXs. Furthermore, some PtrCAXs were up-regulated by drought, beetle, and mechanical damage, indicating their possible function in regulating stress response. Under cadmium stress, all CAX genes in the roots were up-regulated. Our findings suggest that plants may regulate their response to Cd stress through the TF-CAXs module. Comprehensively investigating the CAX family provides a scientific basis for the phytoremediation of heavy metal pollution by Populus.

Impact analysis of environmental and social factors on early-stage COVID-19 transmission in China by machine learning.

As a highly contagious disease, COVID-19 caused a worldwide pandemic and it is still ongoing. However, the infection in China has been successfully controlled although its initial transmission was also nationwide and has caused a serious public health crisis. The analysis on the early-stage COVID-19 transmission in China is worth investigating for its guiding significance on prevention to other countries and regions. In this study, we conducted the experiments from the perspectives of COVID-19 occurrence and intensity. We eliminated unimportant factors from 113 variables and applied four machine learning-based classification and regression models to predict COVID-19 occurrence and intensity, respectively. The influence of each important factor was analysed when applicable. Our optimal model on COVID-19 occurrence prediction presented an accuracy of 91.91% and the best R2 of intensity prediction reached 0.778. Linear regression-based model was identified as unable to fit and predict the intensity, and thus only the variable influence on COVID-19 occurrence can be explained. We found that (1) CO VID-19 was more likely to occur in prosperous cities closer to the epicentre and located on higher altitudes, (2) and the occurrence was higher under extreme weather and high minimum relative humidity. (3) Most air pollutants increased the risk of COVID-19 occurrence except NO2 and O3, and there existed a lag effect of 6-7 days. (4) NPIs (non-pharmaceutical interventions) did not show apparent effect until two weeks after.