Elevation Influences Belowground Biomass Proportion in Forests by Affecting Climatic Factors, Soil Nutrients and Key Leaf Traits.

Forest biomass allocation is a direct manifestation of biological adaptation to environmental changes. Studying the distribution patterns of forest biomass along elevational gradients is ecologically significant for understanding the specific impacts of global change on plant resource allocation strategies. While aboveground biomass has been extensively studied, research on belowground biomass remains relatively limited. Furthermore, the patterns and driving factors of the belowground biomass proportion (BGBP) along elevational gradients are still unclear. In this study, we investigated the specific influences of climatic factors, soil nutrients, and key leaf traits on the elevational pattern of BGBP using data from 926 forests at 94 sites across China. In this study, BGBP data were calculated from the root biomass to the depth of 50 cm. Our findings indicate considerable variability in forest BGBP at a macro scale, showing a significant increasing trend along elevational gradients (p < 0.01). BGBP significantly decreases with increasing temperature and precipitation and increases with annual mean evapotranspiration (MAE) (p < 0.01). It decreases significantly with increasing soil phosphorus content and increases with soil pH (p < 0.01). Key leaf traits (leaf nitrogen (LN) and leaf phosphorus (LP)) are positively correlated with BGBP. Climatic factors (R2 = 0.46) have the strongest explanatory power for the variation in BGBP along elevations, while soil factors (R2 = 0.10) and key leaf traits (R2 = 0.08) also play significant roles. Elevation impacts BGBP directly and also indirectly through influencing such as climate conditions, soil nutrient availability, and key leaf traits, with direct effects being more pronounced than indirect effects. This study reveals the patterns and controlling factors of forests' BGBP along elevational gradients, providing vital ecological insights into the impact of global change on plant resource allocation strategies and offering scientific guidance for ecosystem management and conservation.

Climate Factors Influence Above- and Belowground Biomass Allocations in Alpine Meadows and Desert Steppes through Alterations in Soil Nutrient Availability.

Biomass is a direct reflection of community productivity, and the allocation of aboveground and belowground biomass is a survival strategy formed by the long-term adaptation of plants to environmental changes. However, under global changes, the patterns of aboveground-belowground biomass allocations and their controlling factors in different types of grasslands are still unclear. Based on the biomass data of 182 grasslands, including 17 alpine meadows (AMs) and 21 desert steppes (DSs), this study investigates the spatial distribution of the belowground biomass allocation proportion (BGBP) in different types of grasslands and their main controlling factors. The research results show that the BGBP of AMs is significantly higher than that of DSs (p < 0.05). The BGBP of AMs significantly decreases with increasing mean annual temperature (MAT) and mean annual precipitation (MAP) (p < 0.05), while it significantly increases with increasing soil nitrogen content (N), soil phosphorus content (P), and soil pH (p < 0.05). The BGBP of DSs significantly decreases with increasing MAP (p < 0.05), while it significantly increases with increasing soil phosphorus content (P) and soil pH (p < 0.05). The random forest model indicates that soil pH is the most important factor affecting the BGBP of both AMs and DSs. Climate-related factors were identified as key drivers shaping the spatial distribution patterns of BGBP by exerting an influence on soil nutrient availability. Climate and soil factors exert influences not only on grassland biomass allocation directly, but also indirectly by impacting the availability of soil nutrients.

Modeling and analyzing self-resistance of connected automated vehicular platoons under different cyberattack injection modes.

The high-level integration and interaction between the information flow at the cyber layer and the physical subjects at the vehicular layer enables the connected automated vehicles (CAVs) to achieve rapid, cooperative and shared travel. However, the cyber layer is challenged by malicious attacks and the shortage of communication resources, which makes the vehicular layer suffer from system nonlinearity, disturbance randomness and behavior uncertainty, thus interfering with the stable operation of the platoon. So far, scholars usually adopt the method of assuming or improving the car-following model to explore the platoon behavior and the defense mechanism in cyberattacks, but they have not considered whether the model itself has disturbance and impact on cyberattack defenses. In other words, it is still being determined whether the car-following model designed can be fully applicable to such cyberattacks. To provide a theoretical basis for vehicular layer modeling, it is necessary to comprehend the self-resistance of different car-following models faced on various cyberattacks. First, we review the car-following models adopted on the vehicular layer in cyberattacks, involving traffic engineering, physical statistics, and platoon dynamics. Based on the review, we divide the malicious attacks faced by the cyber layer into explicit attacks and implicit attacks. Second, we develop a cooperative generalized force model (CGFM), which combines and unifies the r-predecessors following communication topology. The proposed models, labeled the vulnerable cooperative intelligent driver model (VCIDM), the vulnerable cooperative optimal velocity model (VCOVM), and the vulnerable cooperative platoon dynamics model (VCPDM), incorporate the CGFM model and assorted cyberattack injection modes to explain the cyberattack effects on the platoon self-resistance capability. Upon the described models, we provide six indicators in three dimensions from the basic traffic element, including drivers, vehicles, and environment. These indicators illustrate driver tolerance, vehicle adaptability, and environmental resistance when a platoon faces attacks such as bogus information, replay/delay, and communication interruption. We arrange and reorganize the car-following models and the cyberattack injection modes to complete the research on the self-resistance capability of the platoon, which has positive research value and practical significance for enhancing the endogenous security at the vehicular layer and improving the intrusion tolerability at the cyber layer.

Development of Megaselia scalaris at constant temperatures and its significance in estimating the time of death.

Megaselia scalaris (Schmitz, 1938) (Diptera: Phoridae) is a common insect in forensic science that is frequently found in indoor cases, particularly on corpses in closed environments. Although this species is useful for estimating the minimum postmortem interval (PMImin) in the absence of Calliphoridae, there is a lack of data on its development in China. Herein, we studied the development of M. scalaris exposed to seven constant temperatures ranging from 16 to 34 °C. The mean (± SD) developmental durations of M. scalaris from egg to adult stage at 16, 19, 22, 25, 28, 31, and 34 °C were 1486.9 ± 75.3, 823.7 ± 42.8, 448.2 ± 59.8, 417.7 ± 19.7, 297.2 ± 27.3, 272.9 ± 10.4, and 253.0 ± 5.0 h, respectively. The mean (± SE) lower developmental threshold temperature (TL) and the thermal summation constant (K) were determined by a linear model as 12.69 ± 0.3 °C and 4965.8 ± 227.9-degree hours, respectively. A nonlinear model estimated the lower developmental threshold temperature, intrinsic optimum temperature, and upper lethal developmental threshold temperature as 14.58, 21.00, and 34.15 °C, respectively. We established three development models to estimate the age of the immature insect, namely the isomegalen diagram, isomorphen diagram, and thermal summation model. In addition, a regression analysis of the relationship between body length and total development time from hatching to pupariation was performed. Our findings provide a basis for applications of M. scalaris in PMImin estimations.

A novel mathematical model and application software for estimating the age of necrophagous fly larvae.

The change in larval body length of necrophagous flies during their development is a key indicator for estimating larval age. However, existing forensic entomological models have limitations in this regard. In this study, a logistic algorithm was used to establish a general model for estimating the minimum postmortem interval (PMImin) using larval body length. The new model was used to simulate the relationship between larval body length and developmental time of eight species of necrophagous flies. The model parameters of body length variation with developmental time of the different species were calculated. Computer software was developed based on the established logistic model. The advantage of the new model is that each parameter has a biological meaning and can be used to estimate the age of larvae at any temperature and any larval body length. Cross-validation of the model showed that the overall mean accuracy of the fitted growth curves for the eight necrophagous fly larvae was 82.7%, the mean accuracy of age extrapolations for seven necrophagous fly species ranged from 76.8% to 92.9%, while the accuracy of age extrapolations for only one species was lower (i.e., 63.3%). This study provides a new method to estimate the PMImin based on larval body length, and the developed computer software will facilitate its application in forensic entomology.

Developmental Indicators of Chrysomya nigripes Aubertin under Different Constant Temperature Conditions and an Application Case for Estimating the PMImin.

Chrysomya nigripes Aubertin, 1932, is a Calliphoridae species that colonize the carcass after the bloat phase and remains for long periods. Some early sarcosaprophagous insects complete one generation of development and are no longer associated with the corpse and surrounding environment, while C. nigripes larvae and pupae remain, providing a basis for the estimation of the minimum postmortem interval (PMImin) for highly decomposed or skeletonized carcasses. However, data on the growth and development of this species are not yet complete. As a result, we studied the developmental patterns of C. nigripes at eight constant temperatures ranging from 16-37 °C and constructed various developmental models, including the isomorphen diagram, isomegalen diagram, linear thermal summation model, nonlinear thermodynamic Optim SSI model, and logistic regression model. Chrysomya nigripes could not complete the entire developmental process at 16 °C, although it could be completed at other temperatures. The mean developmental times (±SD) of C. nigripes from egg to adult at 19 °C, 22 °C, 25 °C, 28 °C, 31 °C, 34 °C, and 37 °C were 644.9 ± 36.8 h, 422.9 ± 20.1 h, 323.1 ± 13.9 h, 246.6 ± 11.2 h, 202.5 ± 1.8 h, 191.5 ± 3.8 h, and 191.8 ± 2.0 h, respectively. The thermal summation constant (K) and lower critical thermal threshold (TL) derived from the linear thermal summation models were 4083.00 ± 293.39 degree hours and 12.52 ± 0.83 °C, respectively. In addition, TL, intrinsic optimum temperature (TΦ), and upper critical thermal threshold (TH) estimated by the optimized nonlinear thermodynamic Optim SSI model were 15.76 °C, 24.88 °C, and 38.15 °C, respectively. This study provides more comprehensive developmental data of C. nigripes for PMImin estimation.

A global perspective of forensic entomology case reports from 1935 to 2022.

Forensic entomology case reports are the product of rapid development in the field, the widespread acceptance of the science and the application of forensic entomological knowledge. In this study, we retrospectively summarized information derived from 307 forensic entomology case reports from 1935 to 2022 from a global perspective. Our checklist of relevant information included insect species, specific indoor or outdoor preferences, preferred temperatures, and stages of body decomposition. Finally, a concept and calculation method for postmortem interval (PMI) estimation accuracy was proposed. There were 232 cases using insect developmental data and 28 cases using succession patterns to estimate PMI. A total of 146 species of insects were involved in the cases, of which 62.3% were Diptera and 37.7% were Coleoptera. Postmortem intervals were estimated from eggs in 4 cases, larvae in 180 cases, pupae in 45 cases, and puparia in 38 cases. The majority of cases were from June to October, and the average number of species mentioned in the cases was more at 15-30 °C. Considering the standardization of application, in the majority of cases, insect evidence was collected by other personnel and sent to forensic entomologists, there was a delay in the sampling, and the scene or meteorological data were directly used without correcting. Our data shows that there are still many shortcomings in the universality and standardization of forensic entomology in its practical application.

Climate factors affect forest biomass allocation by altering soil nutrient availability and leaf traits.

Biomass in forests sequesters substantial amounts of carbon; although the contribution of aboveground biomass has been extensively studied, the contribution of belowground biomass remains understudied. Investigating the forest biomass allocation is crucial for understanding the impacts of global change on carbon allocation and cycling. Moreover, the question of how climate factors affect biomass allocation in natural and planted forests remains unresolved. Here, we addressed this question by collecting data from 384 planted forests and 541 natural forests in China. We evaluated the direct and indirect effects of climate factors on the belowground biomass proportion (BGBP). The average BGBP was 31.09% in natural forests and was significantly higher (38.75%) in planted forests. Furthermore, we observed a significant decrease in BGBP with increasing temperature and precipitation. Climate factors, particularly those affecting soil factors, such as pH, strongly affected the BGBP in natural and planted forests. Based on our results, we propose that future studies should consider the effects of forest type (natural or planted) and soil factors on BGBP.

Surgical selection and regional lymph node dissection for stage I second primary lung cancer patients following surgery for stage I first primary lung cancer.

Introduction: Studies investigating surgery for second primary non-small cell lung cancer (SP) patients are rare. The aim of this study was to explore the effects of surgical methods and regional lymph node (LN) dissection on lung cancer-specific mortality (LCSM) in stage I SP patients following surgery for stage I first primary non-small cell lung cancer (FP). Methods: Data on patients diagnosed with stage I SP after surgery for stage I FP were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Cumulative incidence function (CIF) curves, a competing risk model and propensity score matching (PSM) were adopted to compare the LCSM among different subgroups (including surgery and regional LN dissection). Results: A total of 238 stage I SP patients were extracted from the SEER database. Overall, the 5-year LCSM rate was 29.8% (CI: 23.1%-36.5%) for the whole cohort. Both before and after PSM, lobectomy had a similar LCSM incidence as sublobectomy, and ≥4 regional LN dissections had a significantly lower LCSM incidence than 1~3 regional LN dissections.In addition, patients who underwent 1~3 regional LN dissections had a comparable incidence of LCSM to those without LN dissections. Discussion: Stage I SP patients tended to gain more survival benefits when surgeons dissect ≥4 regional LNs. Allowing for the comparable LCSM incidence of sublobectomy to lobectomy, sublobectomy may be a reasonable choice for thoracic surgeons when performing surgery for these patients.

Time Effects of Global Change on Forest Productivity in China from 2001 to 2017.

With global warming, the concentrations of fine particulate matter (PM2.5) and greenhouse gases, such as CO2, are increasing. However, it is still unknown whether these increases will affect vegetation productivity. Exploring the impacts of global warming on net primary productivity (NPP) will help us understand how ecosystem function responds to climate change in China. Using the Carnegie-Ames-Stanford Approach (CASA) ecosystem model based on remote sensing, we investigated the spatiotemporal changes in NPP across 1137 sites in China from 2001 to 2017. Our results revealed that: (1) Mean Annual Temperature (MAT) and Mean Annual Precipitation (MAP) were significantly positively correlated with NPP (p < 0.01), while PM2.5 concentration and CO2 emissions were significantly negatively correlated with NPP (p < 0.01). (2) The positive correlation between temperature, rainfall and NPP gradually weakened over time, while the negative correlation between PM2.5 concentration, CO2 emissions and NPP gradually strengthened over time. (3) High levels of PM2.5 concentration and CO2 emissions had negative effects on NPP, while high levels of MAT and MAP had positive effects on NPP.

Temperature-Dependent Development of Nitidula rufipes (Linnaeus, 1767) (Coleoptera: Nitidulidae) and Its Significance in Estimating Minimum Postmortem Interval.

Coleoptera, including the family Nitidulidae, are valuable for estimating long-term postmortem intervals in the late stage of body decomposition. This study showed that, under seven constant temperatures of 16, 19, 22, 25, 28, 31, and 34 °C, the developmental durations of Nitidula rufipes (Linnaeus, 1767) from oviposition to eclosion were 71.0 ± 4.4, 52.9 ± 4.1, 40.1 ± 3.4, 30.1 ± 2.1, 24.2 ± 2.0, 21.0 ±2.3, and 20.8 ± 2.4 days, respectively. The morphological indexes of body length, the widths of the head capsules, and the distance between the urogomphi of the larvae were measured in vivo. The regression model between larval body length and developmental durations was simulated for larval aging, and the head capsule width and the distance between the urogomphi at different instars were cluster-analyzed for instar discrimination. Based on the developmental durations, larval body length and thermal summation data were obtained, and the isomorphen diagram, isomegalen diagram, linear thermal summation models, and curvilinear Optim SSI models were established. The lower developmental threshold and thermal summation constant of N. rufipes evaluated by the linear thermal summation models were 9.65 ± 0.62 °C and 471.40 ± 25.46 degree days, respectively. The lower developmental thresholds, intrinsic optimum temperature, and upper lethal developmental threshold obtained by Optim SSI models were 10.12, 24.15, and 36.00 °C, respectively. The study of the immature stages of N. rufipes can provide preliminary basic developmental data for the estimation of minimum postmortem interval (PMImin). However, more extensive studies are needed on the effects of constant and fluctuating temperatures on the development of N. rufipes.

Estimating the intra-puparial period of Hydrotaea spinigera (Stein,1910) (Diptera: Muscidae) with morphological and gene expression changes.

Hydrotaea spinigera (Stein, 1910) (Diptera: Muscidae) is a forensically important sarcosaprophagous species widely distributed throughout the Oriental and Australasian regions. At the advanced decomposition stage or the skeletonize stage, the immature stages of H. spinigera, especially the pupae, can still be found in large quantities and could be used as important indicators to estimate the minimum postmortem interval (PMImin). However, there have been no studies on the intra-puparial period of this species. Herein, we studied morphological and differential gene expression changes during the intra-puparial development of H. spinigera, aiming to accurately estimate the intra-puparial age of H. spinigera. The intra-puparial morphological changes of H. spinigera were observed at seven constant temperatures ranging from 16 °C to 34 °C and divided into 12 sub-stages. Structures that could be used to estimate the intra-puparial age, such as compound eyes, mouthparts, antennae, thorax, legs, wings, and abdomen, were observed in detail, and the developmental process of each structure was divided into 5 to 10 stages. The time range of each sub-stage, or when a structure appeared, was recorded. For the gene expression section, the most suitable reference genes were screened by geNorm, NormFinder, BestKeeper, and ΔCt methods. Based on the selected reference genes, real-time quantitative PCR (RT qPCR) was used to detect the expression changes of the white and hsp90 genes with developmental time at 19 °C, 25 °C, and 31 °C. Results showed that the trend of hsp90 gene expression under different temperatures was not consistent, while white genes exhibited regular changes during development, and could thus be used for age estimation of H. spinigera. This study provides an important basis for forensic entomology to use morphological and differential gene expression for estimating the age of H. spinigera during the intra-puparial period. Moreover, the combination of the two methods can produce a more accurate minimum postmortem interval (PMImin) estimate compared to when each method is used separately.

Deep learning method for risk identification of autonomous bus operation considering image data augmentation strategies.

OBJECTIVE: The autonomous bus is a key application scenario for autonomous driving technology. Identifying the risk of autonomous bus operation is of great significant to improve road traffic safety and promote the large-scale application of autonomous driving technology. METHODS: For the purpose of risk identification, the actual operation data for autonomous buses in Shanghai were converted into 3 kinds of grayscale images and 1 kind of radar image from a temporal-spatial perspective, and a deep learning convolutional neural network, AlexNet, was applied for image recognition. This article uses several image data augmentation strategies to address the problem of uneven distribution of samples and compares the effectiveness of different strategies. RESULTS: The optimal accuracy (ACC) of the risk identification was 90.4%, the optimal true positive rate (TPR) was 83.7%, and the optimal false negative rate (FPR) was 94.58%. The accuracy of risk identification using AlexNet was higher based on the sample containing Fourier images. In addition, risk identification accuracy based on grayscale images was higher than that based on radar images. CONCLUSIONS: Autonomous buses were found to be vulnerable to risks in areas such as turning sections and intersections. In addition, the results show that the Fourier transform, an image augmentation strategy, can effectively solve the uneven sample distribution problem, and the length of the input time series has an impact on the accuracy of the risk identification.

Effects of Soil Nutrients on Plant Nutrient Traits in Natural Pinus tabuliformis Forests.

In light of global warming, the interaction between plant nutrient traits and soil nutrients is still unclear. Plant nutrient traits (e.g., N and P) and their stoichiometric relationships (N/P ratio) are essential for plant growth and reproduction. However, the specific role of soil nutrients in driving variation in plant nutrient traits remains poorly understood. Fifty natural Pinus tabuliformis forests were used as the research object to clarify the interaction between plant nutrient traits and soil nutrients. We show that: (1) The Nmass, Pmass and N/P ratios of leaves were significantly higher than those of roots. The N/P ratio of both leaves and roots was less than 14. (2) Leaf nutrient traits showed diverse relationship patterns with root nutrient traits throughout the growing period. Significant changes were found in root nutrient PC2 (the second principal component of root nutrient traits) and leaf nutrient PC1 (the first principal component of leaf traits), and non-significant changes were found in other relationships between leaf and root traits (p > 0.05). Root nutrient traits explained 36.4% of the variance in leaf nutrient traits. (3) With the increase in soil nutrient PC2 (related to N), leaf PC2 (related to N) showed a significant trend of first decreasing and then increasing (p < 0.05). Only the soil Nmass was significantly correlated with the leaf Nmass (p < 0.05), which demonstrated that the growth and survival of Pinus tabuliformis forests were mainly affected by N-limitation.

Thick quilt may severely impact the estimation of postmortem interval using forensic entomology-based methods -two case reports.

This paper introduces two indoor cases in China, characterized by bodies lying on a mattress, covered with thick quilts and wearing clothes. There were obvious deviation in the estimated minimum postmortem interval (PMImin) of the corpses using entomological methods. Based on the forensic entomology evidence from the scene, the PMImin estimated using temperature data from the nearest weather station was longer than the actual postmortem interval (PMI) based on the police investigation and the security camera footage. The most probable cause of the errors in PMImin estimation was the hindrance in heat dissipation since the corpses were covered with thick quilts while lying on the mattress. Therefore, the heat generated by the decomposition process and larval activity was hard to lose, resulting in the rapid development of insects. These case reports emphasize the importance of temperature collection in forensic entomological investigations. Our findings call for standardized temperature acquisition procedures, including which temperature measurements (body, microenvironment or ambient temperature) should be used in forensic entomological investigations when handling similar cases.

Astilbin Attenuates Cadmium-Induced Adipose Tissue Damage by Inhibiting NF-κB Pathways and Regulating the Expression of HSPs in Chicken.

Cadmium (Cd) can damage tissues by inducing oxidative stress, lymphocyte infiltration, and inflammation in these sites. Meanwhile, astilbin (Ast) is an antioxidant agent. At present, only a few mechanisms of Cd-induced adipose tissue damage have been described. Herein, we assessed the potential protective effects and the molecular mechanism underlying the antioxidant properly of Ast after Cd intake in chicken adipose tissue. In this study, a total of 160 7-day-old roosters were randomly divided into four groups. Roosters were fed with a basic diet (C group), Ast 40 mg/kg (Ast group), CdCl2 150 mg/kg + Ast 40 mg/kg (Cd/Ast group), and CdCl2 150 mg/kg (Cd group) for 60 days. We found that Cd intake changed the morphology and structure of adipose tissues and decreased the expression of several antioxidants, including total superoxide dismutase (T-SOD), glutathione peroxidase (GSH-Px), catalase (CAT), and total antioxidant capacity (T-AOC), but increased those of oxidative stress markers including malondialdehyde (MDA), inducible nitric oxide synthase (iNOS), NO, and H2O2. Cd further activated the nuclear factor kappa B (NF-κB) signaling pathway and increased the expression of the inflammation-related mediators, interleukin 1beta (IL-1ß), interleukin 6 (IL-6), interleukin 8 (IL-8), interleukin 10 (IL-10), cyclooxygenase-2 (COX-2), iNOS, prostaglandin E synthase (PTGES), tumor necrosis factor-alpha (TNF-α), and interferon-gamma (IFN-γ). Cd-induced oxidative stress upregulated the expression of three heat shock proteins (HSPs), including HSP27, HSP70, and HSP90. Summarily, Cd causes oxidative stress-mediated tissue damage by activating the NF-κB pathway, promoting inflammation and upregulating the expression of HSPs. However, Ast supplementation modulates oxidative stress in adipose tissue by inhibiting inflammation mediated by the NF-κB pathway and regulating the expression of HSPs.

A Preliminary Study of Body Decomposition and Arthropod Succession in an Arid Area in Northwest China During Summer.

The study of insect fauna and their development and succession patterns on decaying cadavers is crucial to promoting insect evidence as a useful tool in forensic science, particularly for estimating the postmortem interval (PMI). Body decomposition and arthropod succession are affected by many factors and exhibit substantial regional variations; therefore, detailed succession studies in different biogeographic regions are required for understanding the successional patterns of insects in various environments. This study was conducted in the summer of 2021 using three domestic pig carcasses (Sus scrofa domestica L., 1758) in the field of Shizuishan City, Ningxia, Northwest China. A total of 40 species of necrophagous insects belonging to three orders and 16 families were collected. Among Diptera, Lucilia sericata (Meigen,1826), Chrysomya megacephala (Fabricius,1794), and Phormia regina (Meigen,1826) (Diptera: Calliphoridae) were the dominant species. As for Coleoptera, the dominant species changed throughout the process of carcass decomposition from Saprinus semipunctatus (Fabricius,1792) (Coleoptera: Histeridae) to Dermestes maculatus DeGeer,1774 and Dermestes frischii Kugelann,1792 (Coleoptera: Dermestidae). The carcasses desiccated rapidly and reached the remains stage under extreme conditions of high temperatures and low humidity, after which a large amount of dried tissue of the carcasses attracted populations of Coleoptera, particularly Dermstidae, which were abundant and remained until the end of the experiment on day 50. The current study is the first forensic entomological investigation of succession in Northwest China and provides basic data for the estimation of PMI during summer in this region.

Emodin reverses resistance to gemcitabine in pancreatic cancer by suppressing stemness through regulation of the epithelial­mesenchymal transition.

The present study aimed to explore the effects and underlying mechanisms of emodin (Emo) on gemcitabine (GEM)-resistant pancreatic cancer. GEM-resistant SW1990 cells (SW1990/GZ) were established by successively doubling the concentration of GEM. Cell viability was measured using the CCK-8 assay and flow cytometry was used to measure cell apoptosis. Cell migration was assessed using a Transwell assay. Sphere and colony-formation assays were used to evaluate cell self-renewal. The expression levels of epithelial-mesenchymal transition (EMT) and stem cell biomarkers were determined using western blotting. Snail family transcriptional repressor 1 gene (Snail) was overexpressed by transfecting cells with pcDNA3.1-Snail plasmids. A xenograft model was established in nude mice by using SW1990/GZ and Snail-overexpressing SW1990/GZ cells. Proliferation, migration, self-renewal and EMT progression of GEM-treated SW1990/GZ cells were significantly suppressed in vitro by Emo treatment, whereas the overexpression of Snail abolished the aforementioned effects. In in vivo, the antitumor activity of GEM and the inhibitory effect of GEM against EMT progression and stem-like characteristics were enhanced by treatment with Emo, whilst overexpression of Snail reversed these effects. In conclusion, Emo reversed GEM resistance in pancreatic cancer by suppressing stemness and regulating EMT progression.

Development of a Risk Classifier to Predict Tumor Recurrence and Lenvatinib Benefits in Hepatocellular Carcinoma After Liver Transplantation.

BACKGROUND: Current selection tools were not precise enough to predict recurrence of hepatocellular carcinoma (HCC) and benefit of adjuvant lenvatinib for patients who received liver transplant (LT) for HCC. Thus, we aim at developing a risk classifier to predict recurrence of HCC and benefit of adjuvant Lenvatinib for those who underwent LT for HCC. METHODS: Cox regression model was applied to selected predictors and created the final model in a training cohort of 287 patients who underwent LT for HCC, which was tested in an internal validation cohort of 72 patients by using C-statistic and net classification index (NRI) compared with the following HCC selection criteria: the Milan criteria, the Up-to-7 criteria, and the University of California, San Francisco criteria. RESULTS: We built a Risk Classifier of South China Cohort (RCOSC) based on 4 variables: the maximum diameter plus number of viable tumors, alpha-fetoprotein, microvascular invasion, and highest alanine aminotransferase in 7 days after LT. In validation analyses, our RCOSC showed good predictive performance (C-statistic, 0.866; 95% confidence interval [CI], 0.833-0.899) and had better prognostic value than Milan criteria (NRI, 0.406; P < .001), University of California, San Francisco (NRI, 0.497; P < .001), and Up-to-7 (NRI, 0.527; P < .001). By applying the RCOSC, we were able to accurately categorize patients into high-risk and low-risk groups. Further survival analysis revealed that the patients in the high-risk group might have a better therapeutic response to preventive regimen of lenvatinib after LT for HCC (hazard ratio, 0.38; 95% CI, 0.161-0.871, P = .018). CONCLUSIONS: Our RCOSC presented favorable predictive performance for HCC recurrence. It might be capable of sifting out patients who benefit from adjuvant therapy after LT for HCC, providing a reliable tool for precise clinical decision-making of patients with HCC with LT.

Regional green total factor performance analysis of China's construction industry based on a unified framework combining static and dynamic indexes.

It has an important meaning to improve green total factor performance in the construction industry for China's green and high-quality development. In addition to the traditional desirable economic output and undesirable CO2 emission output, the indicators representing social welfare of China's construction industry were incorporated into the total factor framework. On this basis, a global non-radial DEA approach was employed to explore the sources and the key factors leading to changes in regional green total factor performance of China's construction industry from both static and dynamic perspectives. The results were concluded as follows: (1) The lower energy efficiency and CO2 emission efficiency were the main reasons for low level of green total factor efficiency. During the sample period, energy efficiency increased rapidly while capital efficiency remained almost unchanged. (2) The green total factor productivity demonstrated an increasing trend, which was driven by technological progress rather than technical efficiency. An in-depth decomposition revealed that the deterioration of technical efficiency was mainly caused by the negative effect of CO2 emissions. (3) Regional green total factor performance of China's construction industry demonstrated obvious spatial heterogeneity. Each province should comprehensively consider its own characteristics of green development in the construction industry to formulate the corresponding optimization strategy. These findings can help decision makers design specific policies on regional-oriented green development of China's construction industry.