Efficacy and safety of targeted therapy plus immunotherapy combined with hepatic artery infusion chemotherapy (FOLFOX) for unresectable hepatocarcinoma.

BACKGROUND: The advent of cutting-edge systemic therapies has driven advances in the treatment of hepatocellular carcinoma (HCC), and therapeutic strategies with multiple modes of delivery have been shown to be more efficacious than monotherapy. However, the mechanisms underlying this innovative treatment modality have not been elucidated. AIM: To evaluate the clinical efficacy of targeted therapy plus immunotherapy combined with hepatic arterial infusion chemotherapy (HAIC) of FOLFOX in patients with unresectable HCC. METHODS: We enrolled 53 patients with unresectable HCC who received a combination of targeted therapy, immunotherapy, and HAIC of FOLFOX between December 2020 and June 2021 and assessed the efficacy and safety of the treatment regimen. RESULTS: The objective response rate was 60.4% (32/53), complete response was 24.5% (13/53), partial response was 35.9% (19/53), and stable disease was 39.6% (21/53). The median duration of response and median progression-free survival were 9.1 and 13.9 months, respectively. The surgical conversion rate was 34.0% (18/53), and 1-year overall survival was 83.0% without critical complicating diseases or adverse events (AEs). CONCLUSION: The regimen of HAIC of FOLFOX, targeted therapy, and immunotherapy was curative for patients with unresectable HCC, with no serious AEs and a high rate of surgical conversion.

Validating core therapeutic targets for osteoporosis treatment based on integrating network pharmacology and informatics.

OBJECTIVE: Our goal was to find metabolism-related lncRNAs that were associated with osteoporosis (OP) and construct a model for predicting OP progression using these lncRNAs. METHODS: The GEO database was employed to obtain gene expression profiles. The WGCNA technique and differential expression analysis were used to identify hypoxia-related lncRNAs. A Lasso regression model was applied to select 25 hypoxia-related genes, from which a classification model was created. Its robust classification performance was confirmed with an area under the ROC curve close to 1, as verified on the validation set. Concurrently, we constructed a ceRNA network based on these genes to unveil potential regulatory processes. Biologically active compounds of STZYD were identified using the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP) database. BATMAN was used to identify its targets, and we obtained OP-related genes from Malacards and DisGeNET, followed by identifying intersection genes with metabolism-related genes. A pharmacological network was then constructed based on the intersecting genes. The pharmacological network was further integrated with the ceRNA network, resulting in the creation of a comprehensive network that encompasses herb-active components, pathways, lncRNAs, miRNAs, and targets. Expression levels of hypoxia-related lncRNAs in mononuclear cells isolated from peripheral blood of OP and normal patients were subsequently validated using quantitative real-time PCR (qRT-PCR). Protein levels of RUNX2 were determined through a western blot assay. RESULTS: CBFB, GLO1, NFKB2 and PIK3CA were identified as central therapeutic targets, and ADD3-AS1, DTX2P1-UPK3BP1-PMS2P11, TTTY1B, ZNNT1 and LINC00623 were identified as core lncRNAs. CONCLUSIONS: Our work uncovers a possible therapeutic mechanism for STZYD, providing a potential therapeutic target for OP. In addition, a prediction model of metabolism-related lncRNAs of OP progression was constructed to provide a reference for the diagnosis of OP patients.

Derivation and comprehensive analysis of ageing-related genes in intervertebral disc degeneration for prediction and immunology.

Intervertebral disc degeneration (IDD) is triggered primarily by ageing, a process characterized by intrinsic, multifaceted and progressive characteristics. Regarding the crucial senescence genes and underlying regulatory mechanisms leading to the etiology of IDD, there is still some uncertainty. In this study, we used gene expression patterns from the GEO database to create a diagnostic model of IDD using differential ageing-related genes (DARG). We examine the relative dynamics of immune cells by single-sample gene set. On the basis of transcription factor (TF) miRNA and miRNA-mRNA pairs, the regulatory network for transcription and post-transcriptional processes was built. The active therapeutic components and Chinese herbal remedies of the main ageing genes were investigated using a network pharmacology approach. 20 DARGs were combined to create a diagnostic model, and both the training and validation sets had an area under the ROC curve of 1. We found alterations in many cell types in IDD tissue, but mainly in activated dendritic cells, type 17 T helper cells, and mast cells. We identified a regulatory axis for STAT1/miR-4306/PPARA based on the correlations between gene expression and targeting. Active substances (Naringenin and Quercetin) and herbs (Aurantii fructus and Eucommiae cortex) targeting PPARA for the treatment of IDD were discovered through network pharmacology. These results provide a theoretical framework for identifying and treating IDD. For the first time, we were able to diagnose IDD patients using 20 ageing-related indicators. At the same time, TF-miRNA-mRNA in conjunction with network pharmacology enabled the identification of prospective therapeutic targets and pharmacological processes.

Application Analysis of Multidisciplinary Diagnosis and Treatment Nursing Mode Based on Doctor-Nurse-Integration for Stroke Patients Undergoing Emergency Intervention Surgery.

Purpose: To analyze the application value of multidisciplinary diagnosis and treatment (MDT) nursing mode based on doctor-nurse-integration for stroke patients undergoing emergency intervention surgery. Methods: In this study, a historical comparative study method was adopted. 118 stroke patients and medical staff (9 doctors and 11 nurses) who met the diagnosis and inclusion criteria of emergency intervention surgery admitted from July 2021 to February 2022 were treated clinically according to the traditional medical care mode (TMC group), 87 stroke patients and medical staff (9 doctors and 11 nurses) who met the diagnosis and inclusion criteria of emergency intervention surgery admitted from February 2022 to June 2022 were treated and cared according to the MDT nursing mode based on medical integration (MDT group). Comparison of perioperative time indicators, postoperative outcome indicators, treatment compliance, secondary complications and visit satisfaction between the two groups of patients, and comparison of cooperation satisfaction between the two groups of medical staff. Results: The MDT group had shorter onset-emergency physician's reception time, arrival at CT room-completion time of CT/MR, notify intervention chamber-arrival time at catheter chamber, admission-femoral artery puncture time, admission-first vessel recanalization time, mean postural restraint time than the TMC group (P < 0.05). The postoperative mortality rate in the MDT group (5.75%) was comparable to that in the TMC group (8.47%) (P > 0.05); the postoperative disability rate in the MDT group (28.74%) was less than that in the TMC group (45.76%) (P < 0.05); the NIHSS score in the MDT group was lower than that in the TMC group, and the FMA score and BI score were both higher than those in the TMC group (P < 0.05). The MDT group had higher treatment compliance than the TMC group, fewer secondary complications than the TMC group, and higher patient visit satisfaction and medical staff cooperation satisfaction than the TMC group (P < 0.05). Conclusion: The implementation of the MDT nursing mode based on the doctor-nurse-integration for stroke patients undergoing emergency intervention surgery can improve the work efficiency of rescuing patients, improve the clinical treatment outcome of patients, and improve the satisfaction of doctors, nurses, and patients.

Soil mineral nitrogen regulation by a novel porous material in structurally degraded soils.

BACKGROUND: The availability of soil nitrogen (N) decreases as the structure of agricultural soils degrades. Traditional methods focus on organic amendments that indirectly affect the porosity and N content of soil. Due to the low efficiency of such amendments, new materials, particularly highly porous materials, are needed to improve the quality of soil, which has opened new directions. RESULTS: The addition of 2 to 7 mm of porous clay ceramic (PLC) significantly increased the fresh weight of Brassica chinensis. The soil aeration porosity (>50 µm) increased by 0.69% on average in response to 1% PLC application. Soil NO3 - -N, NH4 + -N and mineral N increased by 3.3, 1.3 and 4.6 mg kg-1 on average, respectively, following a 1% PLC application rate. The initial N content of the high PLC treatments was the lowest in the incubation experiment. The parameters of soil N mineralization, i.e. potentially mineralizable N (N0 ), the first-order rate constant (k) and the mineralization composite index (N0  × k), increased obviously as the amount of PLC increased. Porosities larger than 1000 µm were significantly more positively correlated with the parameters of soil N mineralization than those <500 µm. The Pearson correlation coefficients suggested that high porosity, mineral N and N0 values had significant positive relationships with the fresh weights in double seasons. CONCLUSION: The application of PLC increased soil aeration and enhanced the availability of soil N, which yielded large vegetable harvests in clayey soils in the short term. © 2022 Society of Chemical Industry.

Exploration of yellow-emitting phosphors for white LEDs from natural resources.

White light-emitting diodes (LEDs) are widely used in various lighting fields as a part of energy-efficient technology. However, some shortcomings of luminescent materials for white LEDs, such as complexity of synthesis, high cost, and harmful impact on the environment, limit their practical applications to a large extent. In this respect, the present work aims to study the ability of using Berberine (BBR) chloride extracted from Rhizoma coptidis and Phellodendron Chinese herbs as yellow phosphor for white LEDs. For this, white LEDs were successfully fabricated by applying 0.006 g of BBR chloride onto the blue LED chips (450 nm). The produced LEDs exhibited good luminescence properties at a voltage of 2.4 V along with eco-friendly characteristics and low cost. The Commission International de l'Eclairage chromaticity, the correlated color temperature, and the color rendering index were determined to be (${x} = {0.32}$, ${y} = {0.33}$), 5934 K, and 74, respectively. Therefore, BBR chloride is a suitable environmentally friendly and easily accessible yellow phosphor for white LEDs.

Integrating hyperspectral imaging with machine learning techniques for the high-resolution mapping of soil nitrogen fractions in soil profiles.

Soil nitrogen (N) plays a central role in soil quality and biogeochemical cycles. However, little is known about the distribution and spatial variability of the different fractions of soil N within entire soil profiles. This study aimed to investigate the potential of laboratory-based hyperspectral imaging (HSI) spectroscopy to retrieve and map total N (TN), available N (AvailN), ammonium N (NH4-N), nitrate N (NO3-N), and microbial biomass N (MBN) in soil profiles at a high resolution. HSI images of eleven intact soil profiles of 100 ± 5 cm depth from three typical soil types were recorded. A variety of nonlinear machine learning techniques, such as artificial neural networks (ANN), cubist regression tree (Cubist), k-nearest neighbour (KNN), support vector machine regression (SVMR) and extreme gradient boosting (XGBoost), were compared with a partial least squares regression (PLSR) to determine the most suitable model for the prediction of the various soil N fractions. Overall, the results showed that nonlinear techniques performed better than PLSR in most cases, with a high coefficient of determination (R2) and low root mean square error (RMSE). Among the models, SVMR was found to be superior to the other tested models for TN (R2P = 0.94, RMSEP = 0.17 g kg-1), AvailN (R2P = 0.94, RMSEP = 13.35 mg kg-1), NO3-N (R2P = 0.82, RMSEP = 7.31 mg kg-1), and NH4-N (R2P = 0.70, RMSEP = 1.51 mg kg-1) based on independent validation, whereas MBN (R2P = 0.63, RMSEP = 6.62 mg kg-1) was predicted best by KNN. In addition, SVMR required less computational time and was less sensitive to spectral noise. It can therefore be concluded that HSI spectroscopy combined with SVMR is suitable for the high-resolution mapping of various soil N fractions in soil profiles.

Atranones from Stachybotrys chartarum and their antitumor activities in MG-63 human osteosarcoma cells.

Two new atranones T and U (1 and 2), and three known analogues atranone B (3), atranone Q (4), and stachatranone C (5) were isolated from the toxigenic fungus Stachybotrys chartarum. Their structures and absolute configurations were elucidated by spectroscopic data and calculated ECD analyses. The cytotoxicities of all the atranones (1-5) were evaluated against MG-63 human osteosarcoma cell lines. Compound 4 exhibited significant cytotoxic effect against MG-63 with IC50 value of 8.6 µM, being more active than the positive control, 5-FU (IC50 10.4 µM). Morphological features of apoptosis activities were evaluated in 4-treated MG-63 cells. Compound 4 effectively induced apoptosis of MG-63, which was associated with G0/G1-phase cell cycle arrest. Flow cytometric analysis showed that the treatment by 4 significantly induced MG-63 cell apoptosis in a dose-dependent manner.

White light emission from a single plant source extract with tunable photoluminescence.

Blue, yellow and red emissions from the extract of a single plant source (pomegranate), under NUV light excitation have been reported. The blue emission (450 nm) was attributed to baicalin and protein, whereas the yellow (550 nm) and red (665 nm) emissions were due to two kinds of anthocyanin components (A1 and A2, respectively). Both the green-to-white and yellow-to-white photoluminescences were tuned by variation of excitation wavelengths (350-400 nm). This change in photoluminescence was due to the occurrence of Forster resonance energy transfer from baicalin to A1. White light emission with good CIE color coordinates (0.34, 0.33) was obtained from the pomegranate pulp extract solution (12% w/v) at excitation of 350 nm. The results demonstrated that white light emission could be achieved from a single plant source, which would provide a new method for the design and fabrication of WLE with simple, green, and low-cost materials.

Single-phased emission-tunable Mg and Ce co-doped ZnO quantum dots for white LEDs.

In this study, a simple low-temperature route is presented for the synthesis of Mg and Ce co-doped ZnO quantum dots (QDs). X-ray diffraction, transmission electron microscopy, electron paramagnetic resonance, X-ray photoelectron spectroscopy, UV-vis absorption spectra, and fluorescence measurements were used to characterize the synthesized QDs. The results indicate that the oxygen vacancy concentration could be tuned via Mg and Ce ions doping, which leads to the regulation of luminescence. The visible emission was directly associated with oxygen vacancies, and a blue shift of the visible emission with increasing Ce doping concentration was due to the quantum confinement effect. Finally, we explored the application of Mg and Ce co-doped ZnO QDs by fabricating a white LED device. Notably, the white LED device presents good luminescence properties under a voltage of 3 V and a driven current of 200 mA. The Commission International de l'Eclairage chromaticity, the correlated color temperature, and the color rendering index were determined to be (x = 0.32, y = 0.30), 5733 K, and 81, respectively, which make them potential candidates as single-phased QDs for white light-emitting diodes.

Economics- and policy-driven organic carbon input enhancement dominates soil organic carbon accumulation in Chinese croplands.

China's croplands have experienced drastic changes in management practices, such as fertilization, tillage, and residue treatments, since the 1980s. There is an ongoing debate about the impact of these changes on soil organic carbon (SOC) and its implications. Here we report results from an extensive study that provided direct evidence of cropland SOC sequestration in China. Based on the soil sampling locations recorded by the Second National Soil Survey of China in 1980, we collected 4,060 soil samples in 2011 from 58 counties that represent the typical cropping systems across China. Our results showed that across the country, the average SOC stock in the topsoil (0-20 cm) increased from 28.6 Mg C ha-1 in 1980 to 32.9 Mg C ha-1 in 2011, representing a net increase of 140 kg C ha-1 year-1 However, the SOC change differed among the major agricultural regions: SOC increased in all major agronomic regions except in Northeast China. The SOC sequestration was largely attributed to increased organic inputs driven by economics and policy: while higher root biomass resulting from enhanced crop productivity by chemical fertilizers predominated before 2000, higher residue inputs following the large-scale implementation of crop straw/stover return policy took over thereafter. The SOC change was negatively related to N inputs in East China, suggesting that the excessive N inputs, plus the shallowness of plow layers, may constrain the future C sequestration in Chinese croplands. Our results indicate that cropland SOC sequestration can be achieved through effectively manipulating economic and policy incentives to farmers.

Effects of Subsetting by Parent Materials on Prediction of Soil Organic Matter Content in a Hilly Area Using Vis-NIR Spectroscopy.

Assessment and monitoring of soil organic matter (SOM) quality are important for understanding SOM dynamics and developing management practices that will enhance and maintain the productivity of agricultural soils. Visible and near-infrared (Vis-NIR) diffuse reflectance spectroscopy (350-2500 nm) has received increasing attention over the recent decades as a promising technique for SOM analysis. While heterogeneity of sample sets is one critical factor that complicates the prediction of soil properties from Vis-NIR spectra, a spectral library representing the local soil diversity needs to be constructed. The study area, covering a surface of 927 km2 and located in Yujiang County of Jiangsu Province, is characterized by a hilly area with different soil parent materials (e.g., red sandstone, shale, Quaternary red clay, and river alluvium). In total, 232 topsoil (0-20 cm) samples were collected for SOM analysis and scanned with a Vis-NIR spectrometer in the laboratory. Reflectance data were related to surface SOM content by means of a partial least square regression (PLSR) method and several data pre-processing techniques, such as first and second derivatives with a smoothing filter. The performance of the PLSR model was tested under different combinations of calibration/validation sets (global and local calibrations stratified according to parent materials). The results showed that the models based on the global calibrations can only make approximate predictions for SOM content (RMSE (root mean squared error) = 4.23-4.69 g kg-1; R2 (coefficient of determination) = 0.80-0.84; RPD (ratio of standard deviation to RMSE) = 2.19-2.44; RPIQ (ratio of performance to inter-quartile distance) = 2.88-3.08). Under the local calibrations, the individual PLSR models for each parent material improved SOM predictions (RMSE = 2.55-3.49 g kg-1; R2 = 0.87-0.93; RPD = 2.67-3.12; RPIQ = 3.15-4.02). Among the four different parent materials, the largest R2 and the smallest RMSE were observed for the shale soils, which had the lowest coefficient of variation (CV) values for clay (18.95%), free iron oxides (15.93%), and pH (1.04%). This demonstrates the importance of a practical subsetting strategy for the continued improvement of SOM prediction with Vis-NIR spectroscopy.

Effects of soil data and simulation unit resolution on quantifying changes of soil organic carbon at regional scale with a biogeochemical process model.

Soil organic carbon (SOC) models were often applied to regions with high heterogeneity, but limited spatially differentiated soil information and simulation unit resolution. This study, carried out in the Tai-Lake region of China, defined the uncertainty derived from application of the DeNitrification-DeComposition (DNDC) biogeochemical model in an area with heterogeneous soil properties and different simulation units. Three different resolution soil attribute databases, a polygonal capture of mapping units at 1:50,000 (P5), a county-based database of 1:50,000 (C5) and county-based database of 1:14,000,000 (C14), were used as inputs for regional DNDC simulation. The P5 and C5 databases were combined with the 1:50,000 digital soil map, which is the most detailed soil database for the Tai-Lake region. The C14 database was combined with 1:14,000,000 digital soil map, which is a coarse database and is often used for modeling at a national or regional scale in China. The soil polygons of P5 database and county boundaries of C5 and C14 databases were used as basic simulation units. Results project that from 1982 to 2000, total SOC change in the top layer (0-30 cm) of the 2.3 M ha of paddy soil in the Tai-Lake region was +1.48 Tg C, -3.99 Tg C and -15.38 Tg C based on P5, C5 and C14 databases, respectively. With the total SOC change as modeled with P5 inputs as the baseline, which is the advantages of using detailed, polygon-based soil dataset, the relative deviation of C5 and C14 were 368% and 1126%, respectively. The comparison illustrates that DNDC simulation is strongly influenced by choice of fundamental geographic resolution as well as input soil attribute detail. The results also indicate that improving the framework of DNDC is essential in creating accurate models of the soil carbon cycle.