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Abstract Polyhydroxybutyrate (PHB) is a class of biodegradable polymers generally used by prokaryotes as carbon sources and for energy storage. This study explored the feasibility of repurposing used soybean oil (USO) as a cost-effective carbon substrate for the production of PHB by the strain Gordonia terrae S-LD, marking the first report on PHB biosynthesis by this rare actinomycete species. This strain can grow under a broad range of temperatures (25–40 ℃), initial pH values (4–10), and salt concentrations (0–7%). The findings indicate that this strain can synthesize PHB at a level of 2.63 ± 0.6 g/L in a waste-containing medium containing 3% NaCl within a 3 L triangular flask, accounting for 66.97% of the cell dry weight. Furthermore, 1H NMR, 13C NMR, and GC–MS results confirmed that the polymer was PHB. The thermal properties of PHB, including its melting (Tm) and crystallization (Tc) temperatures of 176.34 °C and 56.12 °C respectively, were determined via differential scanning calorimetry analysis. The produced PHB was characterized by a weight-average molecular weight (Mw) of 5.43 × 105 g/mol, a number-average molecular weight (Mn) of 4.00 × 105 g/mol, and a polydispersity index (PDI) of 1.36. In addition, the whole genome was sequenced, and the PHB biosynthetic pathway and quantitative expression of key genes were delineated in the novel isolated strain. In conclusion, this research introduces the first instance of polyhydroxyalkanoate (PHA) production by Gordonia terrae using used soybean oil as the exclusive carbon source, which will enrich strain resources for future PHB biosynthesis.

Propellant is a core fuel in defense and aerospace applications. However, conventional hydrazine fuel is highly volatile, toxic, and carcinogenic, resulting in huge threats to the human body and environment. N,N-dimethylethanamine (DMAZ) is a green, high-energy fuel with a low freezing point, high density, high specific impulse, and high combustion rate, and it is a promising substitute of conventional hydrazine fuel. Nevertheless, the industrial application of DMAZ is limited by long ignition delay. In this study, the mechanism of ignition of DMAZ was explored by summarizing current methods to reduce the ignition delay of DMAZ, including the addition of catalyst, fuel formulation, and tuning molecular structure. This study provides references for applications of amine azide.

Abstract Despite a lot of efforts devoted to construct efficient microbiomes, there are still major obstacles to moving from the lab to industrial applications due to the inapplicability of existing technologies or limited understanding of microbiome variation regularity. Here we show a domestication strategy to cultivate an effciient and resilient functional microbiome for addressing phenolic wastewater challenges, which involves directional domestication in shaker, laboratory water test in small-scale, gas test in pilot scale, water test in pilot scale, and engineering application in industrial scale. The domestication process includes the transition from water to gas, which provided complex transient environment for screening of a more adaptable and robust microbiome, thereby mitigating the performance disparities encountered when transitioning from laboratory experimentation to industrial engineering applications. Within the domestication and application processes for treating phenolic resin wastewater, a powerful functional microbiome was built by self-assembly. This leads to an augmented biodiversity and the development of more intricate phenol and formaldehyde metabolic pathways. The incorporation of increased stochastic processes and random network characteristics further suggested the stability of the microbial community during the application phase. This study elucidates the self-assembly process of microbial communities during the artificial construction process, showcasing their adaptive evolution under different adverse conditions. It serves as a noteworthy case study for the artificial construction of a microbiome for the engineering application of treating industrial wastewater.

Abstract Purpose The objective of this retrospective cohort study was to investigate the predictive value of stress-induced hyperglycemia parameters for delayed healing after tibial fracture post-surgery. Methods A cohort of 108 participants who underwent surgical intervention for tibial fractures caused by trauma was included in this retrospective study. Data collected from electronic medical records encompassed demographic characteristics, bone healing assessments, stress-induced hyperglycemia parameters, inflammatory markers, and stress-related hormones. Comparative analyses, correlation analyses, univariate logistic regression analyses, and receiver operating characteristic (ROC) curve analyses were conducted to assess the predictive value of the studied parameters. Results The delayed healing group exhibited higher levels of fasting blood glucose, postprandial glucose, and HbA1c, as well as elevated levels of inflammatory markers and stress-related hormones compared to the normal healing group. Correlation analysis and logistic regression demonstrated positive associations between stress-induced hyperglycemia parameters, inflammatory markers, stress-related hormones, and delayed union of tibial fractures (R2: 0.183 ~ 0.403;OR: 1.091 ~ 16.332). ROC curve analysis revealed high area under the curve (AUC = 0.911) values for stress-induced hyperglycemia parameters, indicating their potential as predictive markers for delayed healing. Multivariate regression analysis further substantiated the predictive capability of stress-induced hyperglycemia parameters. Conclusion The study findings highlight the complex interplay between stress-induced hyperglycemia, inflammatory response, and bone healing outcomes in patients undergoing surgical intervention for tibial fractures. The identification of stress-induced hyperglycemia parameters as potential predictive markers for delayed healing after tibial fracture surgery offers insights for risk assessment and patient management, emphasizing the need for comprehensive understanding of these factors to optimize postoperative recovery in orthopedic patients.

Investigating the dynamic mechanical behavior of single-crystal aluminum oxynitride (AlON) is fascinating and crucial for understanding material performance in relevant applications. Nevertheless, few studies have explored the dynamic mechanical properties of AlON single crystals. In this study, a series of nanoimpact experiments (representative strain rate ε˙r≈102s−1) were performed on three principal orientations ((010), (101), and (111)) of grains to extract the dynamic mechanical responses of AlON single crystals. Our results reveal that the dynamic plasticity of an AlON single crystal is governed by a combination of mechanisms, including dislocation motion and amorphization. Significantly, the localized amorphization induced by mechanical deformation has a softening effect (a lower dynamic hardness). The crystallographic orientation affects the dynamic hardness similarly to the static hardness. In particular, the (111) orientation results in the highest hardness, whereas the (010) orientation is the softest among the three principal orientations. This dependency aligns with the expectations derived from applying Schmid law. Furthermore, both the dynamic and static hardnesses exhibit typical indentation size effects (ISEs), which can be effectively described via the strain gradient theory associated with the geometrically necessary dislocations. In addition, the size and rate dependencies of the dynamic hardness can be decoupled into two independent terms.

Micro accelerometers are crucial tools for monitoring and providing early warning of geological disasters. This study focuses on the potential debris flow in Wangjiayuan, Fang County, Hubei Province, aiming to explore the relationship between clay content and debris flow motion characteristics. Physical model experiments were designed with varying clay content to simulate debris flow motion, and micro accelerometers were employed to monitor and record vibration acceleration changes during debris flow initiation and motion. Frequency spectra were generated using Fourier transform to analyze the motion characteristics in the frequency domain. The results showed that the predominant period of debris flow initiation ranged from 15 Hz to 29 Hz, while the period during motion in the middle section of the flow area ranged from 36 Hz to 54 Hz. Higher clay particle content was associated with a decrease in both the frequency range and mean of the predominant period, as well as a reduction in the Fourier amplitude extremum. These findings provide a foundation for monitoring and predicting debris flows, and the vibration signal characteristics of debris flow initiation and motion can be used to infer the clay content, offering insights into early warning systems for such geological hazards.

Abstract A high baseline NLR is associated with a poor prognosis of immunotherapy in patients with advanced HCC. As anti-tumour immune activation takes time, early dynamic changes in NLR may serve as a biomarker for predicting immunotherapy response. We conducted a retrospective study in which we enrolled 209 patients with aHCC who received ICIs (training cohort: N = 121, validation cohort: N = 88). In the training cohort, we categorized the patients based on the early changes in their NLR. Specifically, we defined patients as NLR Stable-Responder, NLR Responder and NLR Non-Responder. We compared the outcomes of these three patient groups using survival analysis. Additionally, we shortened the observation period to 6 weeks and validated the findings in the validation cohort. In the training cohort, early dynamic changes in NLR (HR 0.14, 95%CI 0.03–0.65, p = 0.012, HR 0.19, 95%CI 0.07–0.54, p = 0.002; HR 0.21, 95%CI 0.10–0.42, p

Abstract Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality worldwide. Understanding the dysregulated epigenetics governing LUAD progression is pivotal for identifying therapeutic targets. CBX4, a chromobox protein, is reported to be upregulated in LUAD. This study highlights the dual impact of CBX4 on LUAD proliferation and metastasis through a series of rigorous in vitro and in vivo experiments. Further investigation into the underlying mechanism through high-throughput ChIP-seq and RNA-seq reveals that CBX4 functions in promoting LUAD proliferation via upregulating PHGDH expression and subsequent serine biosynthesis, while concurrently suppressing LUAD metastasis by inhibiting ZEB2 transcription. CBX4 facilitates PHGDH transcription through the interaction with GCN5, inducing heightened histone acetylation on the PHGDH promoter. Simultaneously, the inhibition of ZEB2 transcription involves CBX4-mediated recruitment of canonical PRC1 (cPRC1), establishing H2K119ub on the ZEB2 promoter. These findings underscore CBX4’s pivotal role as a regulator of LUAD progression, emphasizing its diverse transcriptional regulatory functions contingent upon interactions with specific epigenetic partners. Understanding the nuanced interplay between CBX4 and epigenetic factors sheds light on potential therapeutic avenues in LUAD.

A ratiometric fluorescent probe for hypoxanthine (Hx) detection was established based on the mimic enzyme and fluorescence characteristics of cobalt-doped graphite-phase carbon nitride (Co doped g-C3N4). In addition to emitting strong fluorescence, the peroxidase activity of Co doped g-C3N4 can catalyze the reaction of O-phenylenediamine and H2O2 to produce diallyl phthalate which can emit yellow fluorescence at 570 nm. Through the decomposition of Hx by xanthine oxidase, Hx can be indirectly detected by the generating hydrogen peroxide based on the measurement of fluorescent ratio I (F570/F370). The linear range was 1.7–272.2 mg/kg (R2 = 0.997), and the detection limit was 1.52 mg/kg (3σ/K, n = 9). The established method was applied to Hx detection in bass, grass carp, and shrimp, and the data were verifi ed by HPLC. The result shows that the established probe is sensitive, accurate, and reliable, and can be used for Hx detection in aquatic products.

To accurately predict the relative permittivity of cement-stabilized base materials, a study on the dielectric mixing model for cracked base materials was conducted. Based on the electromagnetic mixing theory of multiphase composites, a comprehensive dielectric mixing model of cement-stabilized base materials was derived. The volume ratios and relative permittivity values of the specimen constituents in different cracking states of the cement-stabilized base were determined using industrial CT and a Percometer relative permittivity meter, with comprehensive consideration given to the effects of different initial porosities and crack widths on the dielectric properties. Based on the volumetric and dielectric properties of the base material specimens in both intact and cracked states, as well as the error analysis between the predicted and measured values of the relative permittivity constant, the u-optimal solution of the dielectric mixing model for cement-stabilized base material was determined to be 1. Consequently, an optimization dielectric mixing model for semi-rigid base course materials in a cracked state was developed. The optimization model proposed is suitable for predicting the dielectric properties of cement-stabilized base material with crack widths generally greater than 3 mm during the service life of semi-rigid base course in engineering practice.

Accurate Digital Elevation Models (DEMs) are essential for precise terrain gravity field calculations, which are critical in gravity field modeling, airborne gravimeter and gradiometer calibration, and geophysical inversion. This study evaluates the accuracy of various satellite DEMs by comparing them with a LiDAR DEM at the Wudalianchi test site, a location requiring ultra-accurate terrain gravity fields. Major DEM error sources, particularly those related to vegetation, were identified and corrected using a least squares method that integrates canopy height, vegetation cover, NDVI, and airborne LiDAR DEM data. The impact of DEM vegetation errors on terrain gravity anomalies and gravity gradients was quantified using a partitioned adaptive gravity forward-modeling method at different measurement heights. The results indicate that the TanDEM-X DEM and AW3D30 DEM exhibit the highest vertical accuracy among the satellite DEMs evaluated in the Wudalianchi area. Vegetation significantly affects DEM accuracy, with vegetation-related errors causing an impact of approximately 0.17 mGal (RMS) on surface gravity anomalies. This effect is more pronounced in densely vegetated and volcanic regions. At 100 m above the surface and at an altitude of 1 km, vegetation height affects gravity anomalies by approximately 0.12 mGal and 0.07 mGal, respectively. Additionally, vegetation height impacts the vertical gravity gradient at 100 m above the surface by approximately 4.20 E (RMS), with errors up to 48.84 E over vegetation covered areas. The findings underscore the critical importance of using DEMs with vegetation errors removed for high-precision terrain gravity and gravity gradient modeling, particularly in applications such as airborne gravimeter and gradiometer calibration.

Given the dominant failure mode of steel bridge deck pavement layers, which is flexural–tensile damage, the dynamic modulus parameters conventionally determined through uniaxial compression testing are found to be inadequate for the design or performance analysis of these layers. In order to simulate the actual stress of a pavement structure under wheel load, the four-point bending fatigue test method and uniaxial compression test method are used to measure the dynamic modulus of an epoxy asphalt mixture, and the differences between the two test methods are analyzed. Furthermore, the four-point bending fatigue test is employed to investigate the dynamic modulus and phase angle properties across varying temperatures and frequencies, facilitating the creation of master curves for these properties and utilizing Sigmoidal models to correlate dynamic modulus data at diverse temperature conditions. This study delves into the influence of epoxy resin content, mixture composition, and aging on the dynamic modulus. The experimental results show that the dynamic modulus measured by uniaxial compression exceeds that obtained from bending fatigue tests, with the difference initially increasing and then decreasing as temperature rises. This discrepancy significantly impacts the mechanical calculations of pavement layers, underscoring the importance of selecting the appropriate testing method. Temperature, frequency, and epoxy resin content have pronounced effects on the viscoelastic properties of the mixtures. Specifically, as temperature increases, the dynamic modulus undergoes a decrease, whereas the phase angle exhibits an increase. Additionally, the dynamic modulus augments with an increase in loading frequency, while the phase angle exhibits varied trends with frequency shifts across different temperatures. Both the WLF and Sigmoidal models are effective in constructing master curve representations for the dynamic flexural modulus and phase angle. The incorporation of epoxy resin transforms asphalt from a primarily viscous to a more elastic material, significantly enhancing the viscoelastic properties of the mixture. Notably, mixtures with 50% and 60% epoxy resin content exhibit comparable dynamic moduli and phase angles, while displaying notably superior performance compared to those with 40% epoxy resin content. For large-scale steel bridge deck pavement, 50% epoxy resin content is recommended. Moreover, epoxy asphalt mixtures demonstrate robust aging resistance, with minimal variations in the dynamic modulus and phase angle before and after aging. The research results can enable the acquisition of dynamic modulus and phase angle data in the whole temperature domain and the whole frequency domain, and provide reliable mixed performance parameters for the study of different application environmental performance of steel bridge deck pavement.

Abstract The high salt content of food waste (FW) severely limits microbial physiological activity and reduces its biodegradability. In this study, a salt‐tolerant thermophilic bacterial agent that consists of four different substrate degradation functional strains was evaluated for efficient high salt and oily FW in solid‐state aerobic biodegradation disposers. The phy‐chemical properties, enzyme activities, microbial community structure, and function during the biodegradation process were evaluated under high salt (5%) stress. The results showed that the agent promoted the degradation rate, increased the matrix temperature, decreased the moisture content (MC), and enhanced enzyme activities without putrid smell. High‐throughput sequencing indicated community structure succession between different groups and the positive contribution of the inoculated functional strains. During the FW biodegradation process, the Bacillus sp. inoculated was the dominant genus in the agent group. Furthermore, CCA further confirmed the positive effects of the four inoculated strains on high salt and oily FW aerobic biodegradation. Functional prediction and metabolite results both confirmed that the agent was more efficient in carbon, amino acid, and lipid metabolism, which demonstrated that the synthetic microbial consortium holds a potential advantage for efficiency and subsequent resource utilization for organic fertilizer.

BackgroundTargeted and Immunotherapy has emerged as a new first-line treatment for advanced hepatocellular carcinoma (aHCC). To identify the appropriate targeted and immunotherapy, we implemented next generation sequencing (NGS) to provide predictive and prognostic values for aHCC patients.MethodsPretreatment samples from 127 HCC patients were examined for genomic changes using 680-gene NGS, and PD-L1 expression was detected by immunohistochemistry. Demographic and treatment data were included for analyses of links among treatment outcomes, drug responses, and genetic profiles. A prognostic index model for predicting benefit from treatment was constructed, taking into account of biomarkers, including TP53, TERT, PD-L1, and tumor mutation burden (TMB) as possible independent prognostic factors.ResultsThe multivariate Cox regression analyses showed that PD-L1≥1% (HR 25.07, 95%CI 1.56 - 403.29, p=0.023), TMB≥5Mb (HR 86.67, 95% CI 4.00 - 1876.48, p=0.004), TERT MU (HR 84.09, 95% CI 5.23 - 1352.70, p=0.002) and TP53 WT (HR 0.01, 95%CI 0.00 - 0.47, p=0.022) were independent risk factors for overall survival (OS), even after adjusting for various confounders. A prognostic nomogram for OS was developed, with an area under the ROC curve of 0.91, 0.85, and 0.98 at 1-, 2-, and 3- year, respectively, and a prognostic index cutoff of 1.2. According to the cutoff value, the patients were divided into the high-risk group (n=29) and low-risk group (n=98). The benefit of targeted and immunotherapy in the low-risk group was not distinguishable according to types of agents. However, treatment of Atezolizumab and Bevacizumab appeared to provide longer OS in the high-risk group (12 months vs 9.2, 9, or 5 months for other treatments, p

A 64-year-old woman was admitted to the hospital for sudden weakness in one of her left limbs. The patient was diagnosed with acute ischemic stroke (IS) of undetermined cause and received intravenous thrombolysis. Following thrombolysis, the patient’s left limb weakness improved, but she subsequently developed recurrent high fever and delirium. Further diagnostic tests revealed that she had been infected with Brucella melitensis. The patient showed significant improvement during anti-infection treatment for Brucellosis and secondary prevention treatment for IS. However, her condition unexpectedly worsened on the 44th day after admission due to a hemorrhagic stroke (HS), which required an urgent craniotomy. Immunohistochemical analysis of the hematoma sample collected during the operation showed the presence of CD4+ and CD8+ T lymphocytes surrounding the blood vessels. This case highlights the unique challenge of managing IS in brucellosis and sheds light on the potential role of T lymphocytes in the immune response related to stroke.

Background: Chukrasia tabularisis, a well-known tropical tree native to southeastern China, has anti-inflammatory and antioxidant activities, and contains large amounts of limonoids and triterpenoids. Objective: The aim of this study was to investigate the potential anti-inflammatory activity of limonoids from C. tabularis on lipopolysaccharide (LPS)-mediated RAW264.7 cells. Methods and results: Using a bioassay-guided approach, the chemical fraction with high anti-inflammatory activity was found and its chemical constituents were investigated. Phytochemical studies on active extracts resulted in the separation of three novel phragmalin limonoids (1–3), together with two known limonoids (4–5) and 11 tirucallane triterpenes (6–16). The activity of these isolated compounds in the production of nitric oxide (NO) on LPS-reated macrophages was evaluated. Limonoid 2 indicated significant anti-inflammatory activities with IC50 value of 4.58 μM. Limonoid 2 notably inhibited the production of NO, interleukin- 6 and tumor necrosis factor-α on macrophage. Signal transduction and activation of STAT and NF-κB activators were effectively blocked by limonoid 2. Conclusions: These results indicate that limonoid 2 has an anti-inflammatory effect by the inhibiting JAK2/STAT3, iNOS/eNOS, and NF-κB signaling pathways and regulating inflammatory mediators.

This paper presents a hermitic fiber sensor packaging technique that enables fiber sensors to be embedded in energy systems for performing multi-parameter measurements in high-temperature and strong radiation environments. A high-temperature stable Intrinsic Fabry–Perot interferometer (IFPI) array, inscribed by a femtosecond laser direct writing scheme, is used to measure both temperature and pressure induced strain changes. To address the large disparity in thermo-expansion coefficients (TECs) between silica fibers and metal parts, glass sealants with TEC between silica optical fibers and metals were used to hermetically seal optical fiber sensors inside stainless steel metal tubes. The hermetically sealed package is validated for helium leakages between 1 MPa and 10 MPa using a helium leak detector. An IFPI sensor embedded in glass sealant was used to measure pressure. The paper demonstrates an effective technique to deploy fiber sensors to perform multi-parameter measurements in a wide range of energy systems that utilize high temperatures and strong radiation environments to achieve efficient energy production.

A deep-seated landslide could release numerous microseismic signals from creep-slip movement, which includes a rock-soil slip from the slope surface and a rock-soil shear rupture in the subsurface. Machine learning can effectively enhance the classification of microseismic signals in landslide seismic monitoring and interpret the mechanical processes of landslide motion. In this paper, eight sets of triaxial seismic sensors were deployed inside the deep-seated landslide, Jiuxianping, China, and a large number of microseismic signals related to the slope movement were obtained through 1-year-long continuous monitoring. All the data were passed through the seismic event identification mode, the ratio of the long-time average and short-time average. We selected 11 days of data, manually classified 4131 data into eight categories, and created a microseismic event database. Classical machine learning algorithms and ensemble learning algorithms were tested in this paper. In order to evaluate the seismic event classification performance of each algorithmic model, we evaluated the proposed algorithms through the dimensions of the accuracy, precision, and recall of each model. The validation results demonstrated that the best performing decision tree algorithm among the classical machine learning algorithms had an accuracy of 88.75%, while the ensemble algorithms, including random forest, Gradient Boosting Trees, Extreme Gradient Boosting, and Light Gradient Boosting Machine, had an accuracy range from 93.5% to 94.2% and also achieved better results in the combined evaluation of the precision, recall, and F1 score. The specific classification tests for each microseismic event category showed the same results. The results suggested that the ensemble learning algorithms show better results compared to the classical machine learning algorithms.

BackgroundImmunotherapy based on immune checkpoint inhibitors (ICIs) has become the first-line treatment for unresectable hepatocellular carcinoma (uHCC). However, only a small portion of patients are responsive to ICIs. It is important to identify the patients who are likely to benefit from ICIs in clinical practice. We aimed to examine the significance of serum IL-6 and CRP levels in predicting the effectiveness of ICIs for uHCC.MethodsWe retrospectively recruited 222 uHCC patients who received ICIs treatment (training cohort: 124 patients, validation cohort: 98 patients). In the training cohort, patients are categorized into the response group (R) and no-response group (NR). The levels of serum IL-6 and CRP were compared between the two groups. Internal validation was performed in the validation cohort. Survival analysis was carried out using the Kaplan-Meier method and Cox proportional hazard regression model. The nomograms were developed and assessed using the consistency index (C-index) and calibration curve.ResultsSerum levels of IL-6 and CRP were significantly lower in the R group than in the NR group (9.94 vs. 36.85 pg/ml, p< 0.001; 9.90 vs. 24.50 mg/L, p< 0.001, respectively). An ROC curve was employed to identify the optimal cut-off values for IL-6 and CRP in both groups, resulting in values of 19.82 pg/ml and 15.50 mg/L, respectively. Multivariate Cox regression analysis revealed that MVI (HR 1.751, 95%CI 1.059-2.894, p=0.029; HR 1.530, 95%CI 0.955-2.451, p=0.077), elevated IL-6 (HR 1.624, 95%CI 1.016-2.596, p=0.043; HR 2.146, 95%CI 1.361-3.383, p =0.001) and high CRP (HR 1.709, 95%CI 1.041-2.807, p=0.034; HR 1.846, 95%CI 1.128-3.022, p = 0.015) were independent risk factors for PFS and OS, even after various confounders adjustments. Nomograms are well-structured and validated prognostic maps constructed from three variables, as MVI, IL6 and CRP.ConclusionLow levels of IL-6 and CRP have a positive correlation with efficacy for uHCC patients receiving ICIs.

As agents in an emerging technology, Hermetia illucens (Linnaeus, 1758) (Diptera: Stratiomyidae) larvae, black soldier fly, have shown exciting potential for degrading antibiotics in organic solid waste, a process for which gut microorganisms play an important role. This study investigated the characteristics of larval gut bacterial communities effected by typical antibiotics. Initially, antibiotics significantly reduced the diversity of gut bacterial species. After 8 days, diversity recovered to similar to that of the control group in the chlortetracycline, tylosin, and sulfamethoxazole groups. Proteobacteria, Firmicutes, and Actinobacteriota were the dominant phyla at the initial BSFL gut. However, after 4 days treatment, the proportion of Actinobacteriota significantly decreased, but Bacteroidota notably increased. During the conversion process, 18, 18, 17, 21, and 19 core genera were present in the chlortetracycline, sulfamethoxazole, tylosin, norfloxacin, and gentamicin groups, respectively. Pseudomonas, Actinomyces, Morganella, Providencia and Klebsiella might be the important genera with extraordinary resistance and degradation to antibiotics. Statistical analyses of COGs showed that antibiotics changed the microbial community functions of BSFL gut. Compared with the control group, (i) the chlortetracycline, sulfamethoxazole, and tylosin groups showed significant increase in the classification functions of transcription, RNA processing and modification，and so on, (ii) the norfloxacin and gentamicin groups showed significant increase in defense mechanisms and other functions. Note that we categorized the response mechanisms of these classification functions to antibiotics into resistance and degradation. This provides a new perspective to deeply understand the joint biodegradation behavior of antibiotics in environments, and serves as an important reference for further development and utilization of microorganisms-assisted larvae for efficient degradation of antibiotics.

This paper presents the design and construction of the facade renovation project ("Bamboo Cubic" project) of Huangqiao Square in Shaowu City, Fujian Province, China. In this project, the structural form and cross-sectional dimensions were determined using a combination of manual and finite element analysis to meet relevant regulations. Once the structural form was confirmed, primary structural components such as the foundation, the column base, and the connection between frame elements were designed to comply with design requirements. Innovative connections were used to install a unique curved design, which required curved LBL members to be prefabricated with precision. The total height of the LBL bamboo frame part is 16.86 m. This project clearly showed that engineered bamboo can be used both as a structural primary member as well as for aesthetic purpose. Use of steel and LBL frames in the "Bamboo Cubic" facade project highlighted the prospect of future hybrid construction.

Based on the hail data of the China Meteorological Administration, the spatial and temporal distributions of hail disaster eents in China during 2010-2020 are studied by using the statistical method and GIS technology. The result is shown below. (1) The number of stations and the days of hails in China increase, while the number of severe hails decreases during 2010-2020. (2) The seasonal change is significant for the number of stations and the days of hails with the maximum in summer and the minimum in winter. In terms of monthly variation, hail occurs most often in June and least often in November. In southwest and central China, the monthly variation of the number of stations and the days of hails is bimodal. The monthly distribution of severe hail is similar to that of hail, but it occurs least often in December. The severe hail occurs most frequently in southwest China. (3) For diurnal variation, hail or severe hail mainly occurrs from afternoon to evening. The peak appears 1-hour later in northwest China than in other areas. (4) In terms of spatial distribution, the number of stations and the days of hail or severe disaster in Northwest, Southwest, and North China are significantly higher than those in the other regions, and the proportion of severe hail in Northeast and South China is higher than that in the other regions. The annual average days of hail or severe hail are distributed in multi-zone bands, and the multi-hail area extends along the mountains, with the largest value located in the Yunnan-Guizhou Plateau, followed by the mountains of Qinling, Yinshan, Daxing 'anling, and Tianshan. In addition, the low-incidence area of eastern China in spring has become a high-incidence area of hail. (5)From the elevation distribution, hail is most likely to occur at the altitude of 1.5-2 km, and severe hail is most likely to occur at the altitude of 1-1.5 km. In winter, hail is mainly below 2 km. With the rise of temperature, hail gradually increases in the high-altitude areas, and the proportion of hailstones in the high-altitude areas reaches the maximum in September.

Some long non-coding RNAs (lncRNAs) have been documented to be involved in cancer progression and anticancer drug resistance in hepatocellular carcinoma (HCC). Thus, approaches designed to target these genes may facilitate the development of promising strategies for treating HCC. Previously, we showed that lncRNA BBOX1-AS1 was highly expressed and played an oncogenic role in HCC. However, the potential functions and mechanisms through which BBOX1-AS1 regulates HCC progression and drug resistance remain unclear. This study revealed that BBOX1-AS1 could promote tumor progression, autophagy, and drug resistance by upregulating PHF8 in HCC cells. Mechanistically, BBOX1-AS1 enhanced the stability of PHF8 mRNA by targeting the PHF8 inhibitor miR-361-3p to regulate tumor progression and autophagy in HCC. The functional rescue experiments showed that PHF8 acted as a key factor in regulating the biological effects induced by BBOX1-AS1 and miR-361-3p in HCC, indicating that BBOX1-AS1 promotes tumor progression and sorafenib resistance by regulating miR-361-3p/PHF8. Finally, mouse tumor models and patient-derived organoid models were established to further confirm these findings. Taken together, the results demonstrate that BBOX1-AS1 promotes HCC progression and sorafenib resistance via the miR-361-3p/PHF8 axis.