How sediment dredging alters phosphorus dynamics in a lowland rural river?

China's lowland rural rivers are facing severe eutrophication problems due to excessive phosphorus (P) from anthropogenic activities. However, quantifying P dynamics in a lowland rural river is challenging due to its complex interaction with surrounding areas. A P dynamic model (River-P) was specifically designed for lowland rural rivers to address this challenge. This model was coupled with the Environmental Fluid Dynamics Code (EFDC) and the Phosphorus Dynamic Model for lowland Polder systems (PDP) to characterize P dynamics under the impact of dredging in a lowland rural river. Based on a two-year (2020-2021) dataset from a representative lowland rural river in the Lake Taihu Basin, China, the coupled model was calibrated and achieved a model performance (R2>0.59, RMSE<0.04 mg/L) for total P (TP) concentrations. Our research in the study river revealed that (1) the time scale for the effectiveness of sediment dredging for P control was ∼300 days, with an increase in P retention capacity by 74.8 kg/year and a decrease in TP concentrations of 23% after dredging. (2) Dredging significantly reduced P release from sediment by 98%, while increased P resuspension and settling capacities by 16% and 46%, respectively. (3) The sediment-water interface (SWI) plays a critical role in P transfer within the river, as resuspension accounts for 16% of TP imports, and settling accounts for 47% of TP exports. Given the large P retention capacity of lowland rural rivers, drainage ditches and ponds with macrophytes are promising approaches to enhance P retention capacity. Our study provides valuable insights for local environmental departments, allowing a comprehensive understanding of P dynamics in lowland rural rivers. This enable the evaluation of the efficacy of sediment dredging in P control and the implementation of corresponding P control measures.

GDF11 protects against mitochondrial-dysfunction-dependent NLRP3 inflammasome activation to attenuate osteoarthritis.

INTRODUCTION: Osteoarthritis (OA) is a highly prevalent degenerative disease worldwide, and tumor necrosis factor (TNF-α) is closely associated with its development. Growth differentiation factor 11 (GDF11) has demonstrated anti-injury and anti-aging abilities in certain tissues; however, its regulatory role in OA remains unclear and requires further investigation. OBJECTIVES: To identify whether GDF11 can attenuate osteoarthritis. To exploring the the potential mechanism of GDF11 in alleviating osteoarthritis. METHODS: In this study, we cultured and stimulated mouse primary chondrocytes with or without TNF-α, analyzing the resulting damage phenotype through microarray analysis. Additionally, we employed GDF11 conditional knockout mice OA model to examine the relationship between GDF11 and OA. To investigate the target of GDF11's function, we utilized NLRP3 knockout mice and its inhibitor to verify the potential involvement of the NLRP3 inflammasome. RESULTS: Our in vitro experiments demonstrated that endogenous overexpression of GDF11 significantly inhibited TNF-α-induced cartilage matrix degradation and inflammatory expression in chondrocytes. Furthermore, loss of GDF11 led to NLRP3 inflammasome activation, inflammation, and metabolic dysfunction. In an in vivo surgically induced mouse model, intraarticular administration of recombinant human GDF11 alleviated OA pathogenesis, whereas GDF11 conditional knockout reversed this effect. Additionally, findings from the NLRP3-knockout DMM mouse model revealed that GDF11 exerted its protective effect by inhibiting NLRP3. CONCLUSION: These findings demonstrate the ability of GDF11 to suppress TNF-α-induced inflammation and cartilage degeneration by preventing mitochondrial dysfunction and inhibiting NLRP3 inflammasome activation, suggesting its potential as a promising therapeutic drug for osteoarthritis.

Lanthanide-Induced Ligand Effect to Regulate the Electronic Structure of Platinum-Lanthanide Nanoalloys for Efficient Methanol Oxidation.

The ligand effect in alloy catalysts is one of the decisive parameters of the catalytic performance. However, the strong interrelation between the ligand effect and the geometric effect of the active atom and its neighbors as well as the systematic alteration of the microenvironment of the active site makes the active mechanism unclear. Herein, Pt3Tm, Pt3Yb, and Pt3Lu with a cubic crystal system (Pm-3m) were selected. With the difference of Pt-Pt interatomic distance within 0.02 Å, we minimize the geometric effect to realize the disentanglement of the system. Through precise characterization, due to the low electronegativity of Ln (Ln = Tm, Yb, and Lu) and the ligand effect in the alloy, the electronic structure of Pt is continuously optimized, which improves the electrochemical methanol oxidation reaction (MOR) performance. The Ln electronegativity has a linear relationship with the MOR performance, and Pt3Yb/C achieves a high mass activity of up to 11.61 A mgPt-1, which is the highest value reported so far in Pt-based electrocatalysts. The results obtained in this study provide fundamental insights into the mechanism of ligand effects on the enhancement of electrochemical activity in rare-earth nanoalloys.

Dihydroartemisinin restores the immunogenicity and enhances the anticancer immunosurveillance of cisplatin by activating the PERK/eIF2α pathway.

BACKGROUND: Immunosurveillance is pivotal in the effectiveness of anticancer therapies and tumor control. The ineffectiveness of cisplatin in activating the immunosurveillance is attributed to its lack of adjuvanticity resulting from its inability to stimulate endoplasmic reticulum stress. Dihydroartemisinin demonstrates the anti-tumor effects through various mechanisms, including the activation of the endoplasmic reticulum stress. This study aimed to develop a novel strategy to enhance the immunogenicity of dying tumor cells by combining cisplatin with dihydroartemisinin, thereby triggering effective anti-tumor immunosurveillance and improving the efficacy of cisplatin in clinical practice. METHODS: Lewis lung carcinoma (LLC) and CT26 colon cancer cell lines and subcutaneous tumor models were used in this study. The importance of immunosurveillance was validated in both immunocompetent and immunodeficient mouse models. The ability of dihydroartemisinin and cisplatin therapy to induce immunogenic cell death and tumor growth control in vivo was validated by prophylactic tumor vaccination and therapeutic tumor models. The underlying mechanism was elucidated through the pharmaceutical or genetic intervention of the PERK/eIF2α pathway in vitro and in vivo. RESULTS: Dihydroartemisinin enhanced the generation of reactive oxygen species in cisplatin-treated LLC and CT26 cancer cells. The combination treatment of dihydroartemisinin with cisplatin promoted cell death and ensured an optimal release of damage-associated molecular patterns from dying cancer cells, promoting the phagocytosis of dendritic cells. In the tumor vaccination model, we confirmed that dihydroartemisinin plus cisplatin treatment induced immunogenic cell death. Utilizing immunocompetent and immunodeficient mouse models, we further demonstrated that the combination treatment suppressed the tumor growth of CT26 colon cancer and LLC lung cancer, leading to an improved prognosis through the restoration of cytotoxic T lymphocyte responses and reinstatement of anti-cancer immunosurveillance in vivo. Mechanistically, dihydroartemisinin restored the immunogenicity of cisplatin by activating the adjuvanticity of damage-associated molecular patterns, such as calreticulin exposure, through the PERK/eIF2α pathway. Additionally, the inhibition of eIF2α phosphorylation attenuated the anti-tumor efficiency of C + D in vivo. CONCLUSIONS: We highlighted that dihydroartemisinin acts as an immunogenic cell death rescuer for cisplatin, activating anticancer immunosurveillance in a PERK/eIF2α-dependent manner and offering a strategy to enhance the anti-tumor efficacy of cisplatin in clinical practice.

Effects of long-time and short-time heat stress on the meat quality of geese.

This investigation sought to reveal the effects of heat stress on the meat quality of geese. Wuzong geese were subjected to heat stress at 35°C for 25 d or 4 h to examine different heat stress time on meat quality. Short-time heat stress reduced muscle drip loss and meat color L* value while increasing pH value and meat color a* and b* values. Long-time heat stress decreased body weight and increased leg muscle pH value and meat color b* value. Amino acid profile of geese breast muscle revealed that both LHS and SHS can induce L-Cystine but reduced L-Cystathionine, which were positive correlated with cooking loss and meat color lightness, respectively. Lipidome analysis indicated that heat stress would alter the synthesis of unsaturated fatty acids, and the difference between LHS and SHS on lipids mainly focused on Hex1Cer and TG. Non-target metabolome analysis indicated effects of heat stress on Glycerolipid metabolism, Arachidonic acid metabolism, and Pyrimidine metabolism. Proteome analysis showed that heat stress mainly affects cellular respiration metabolism and immune response. These findings highlight the diverse effects of heat stress on meat quality, amino acid composition, lipidome, metabolome, and proteome in geese.

Is it feasible to develop a supervised learning algorithm incorporating spinopelvic mobility to predict impingement in patients undergoing total hip arthroplasty?

Aims: Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. Methods: This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy. Results: We identified nine predictors from an analysis of baseline spinopelvic characteristics and surgical planning parameters. Using fivefold cross-validation, the LGBM achieved 70.2% impingement prediction accuracy. With impingement data, the LGBM estimated direction with 85% accuracy, while the support vector machine (SVM) determined impingement type with 72.9% accuracy. After integrating imaging data with a multilayer perceptron (tabular) and a convolutional neural network (radiograph), the LGBM's prediction was 68.1%. Both combined and LGBM-only had similar impingement direction prediction rates (around 84.5%). Conclusion: This study is a pioneering effort in leveraging AI for impingement prediction in THA, utilizing a comprehensive, real-world clinical dataset. Our machine-learning algorithm demonstrated promising accuracy in predicting impingement, its type, and direction. While the addition of imaging data to our deep-learning algorithm did not boost accuracy, the potential for refined annotations, such as landmark markings, offers avenues for future enhancement. Prior to clinical integration, external validation and larger-scale testing of this algorithm are essential.

Balloon Pulmonary Angioplasty for Chronic Thromboembolic Pulmonary Disease: success rate and Complications among Different Patient Populations.

INTRODUCTION: Balloon pulmonary angioplasty (BPA) is an effective intervention for patients with chronic thromboembolic pulmonary disease (CTEPD). We aim to identify the patient group with a low success rate or high complication rate of BPA, which is still unclear. METHODS: Both CTEPD patients with or without pulmonary hypertension (CTEPH and NoPH-CTEPD) were included. CTEPH patients were divided into groups with or without pulmonary endarterectomy (PEA-CTEPH and NoPEA-CTEPH). The efficacy and safety of BPA were compared among the groups. RESULTS: There were 450, 66, and 41 sessions in the NoPEA-CTEPH, PEA-CTEPH, and NoPH-CTEPD groups, respectively. The success rate (≥ 1 degree improvement in flow grade) in the PEA-CTEPH group was 94.5%, significantly lower than that in the NoPEA-CTEPH (97.1%) and NoPH-CTEPD (98.4%) groups (P=0.014). The percentage of complete flow recovery in treated vessels was also lower in PEA-CTEPH group. BPA-related complication rate in NoPEA-CTEPH, PEA-CTEPH, and NoPH-CTEPD patients was 6.1%, 6.0%, and 0.0%, respectively (P=0.309). One BPA-related death occurred (solely in NoPEA-CTEPH). Mean pulmonary artery pressure ≥ 41.5 mmHg was a predictor of BPA-related complications. NoPEA-CTEPH patients had more improvement in 6-minute-walk-distance (6MWD, 87±93 m -NoPEA-CTEPH vs 40±43 m -PEA-CTEPH vs 18±20 m -NoPH-CTEPD, P=0.012). CONCLUSIONS: BPA was safe and effective for all CTEPD groups with less improvement for the PEA-CTEPH and NoPH-CTEPD groups. The success rate of BPA was lower in the PEA-CTEPH group and the complication rate was lower in the NoPH-CTEPD group. Pre-BPA treatment to lower pulmonary artery pressure should not be overlooked in CTEPD patients.

The total biosynthesis route of rosmarinic acid in Sarcandra glabra based on transcriptome sequencing.

Sarcandra glabra is a widely distributed and valuable plant in food and daily chemical industries, and is also a common-used medicinal plant for treating inflammatory diseases and tumors. Rosmarinic acid (RA) with significant pharmacological activity is an abundant and important constituent in S. glabra, however, little information about key enzymes involving the biosynthesis of RA in S. glabra is available and the underlying biosynthesis mechanisms of RA in S. glabra remain undeciphered. Therefore, in this study, by full-length transcriptome sequencing analyses of S. glabra, we screened the RA biosynthesis candidate genes based on sequence similarity and conducted enzymatic function characterization in vitro and in vivo. As a result, a complete set of 7 kinds of enzymes (SgPALs, SgC4H, Sg4CL, SgTATs, SgHPPRs, SgRAS and SgC3H) involving the biosynthesis route of RA from phenylalanine and tyrosine, were identified and fully characterized. This research systematically revealed the complete biosynthesis route of RA in S. glabra, which helps us better understand the process of RA synthesis and accumulation, especially the substrate promiscuities of SgRAS and SgC3H provide the molecular biological basis for the efficient biosynthesis of specific and abundant RA in S. glabra. The 7 kinds of key enzymes revealed in this study can be utilized as tool enzymes for production of RA by synthetic biology methods.

Modelling energy partition patterns of growing pigs fed diets with different net energy levels based on machine learning.

The objectives of this study were to evaluate the energy partition patterns of growing pigs fed diets with different net energy (NE) levels based on machine learning methods, and to develop prediction models for the NE requirement of growing pigs. Twenty-four Duroc × Landrace × Yorkshire crossbred barrows with an initial body weight of 24.90 ± 0.46 kg were randomly assigned to 3 dietary treatments, including the low NE group (2,325 kcal/kg), the medium NE group (2,475 kcal/kg), and the high NE group (2,625 kcal/kg). The total feces and urine produced from each pig during each period were collected, to calculate the NE intake, NE retained as protein (NEp), and NE retained as lipid (NEl). A total of 240 sets of data on the energy partition patterns of each pig were collected, 75% of the data in the dataset was randomly selected as the training dataset, and the remaining 25% was set as the testing dataset. Prediction models for the NE requirement of growing pigs were developed using algorithms including multiple linear regression (MR), artificial neural networks (ANN), k-nearest neighbor (K-NN), and random forest (RF), and the prediction performance of these models was compared on the testing dataset. The results showed pigs in the low NE group showed a lower average daily gain, lower average daily feed intake, lower NE intake, but greater feed conversion ratio compared to pigs in the high NE group in most growth stages. In addition, pigs in the three treatment groups did not show a significant difference in NEp in all growth stages, while pigs in the medium and high NE groups showed greater NEl compared to pig in the low NE group in growth stages from 25 to 55 kg (P < 0.05). Among the developed prediction models for NE intake, NEp, and NEl, the ANN models demonstrated the most optimal prediction performance with the smallest root mean square error (RMSE) and the largest R2, while the RF models had the worst prediction performance with the largest RMSE and the smallest R2. In conclusion, diets with varied NE concentrations within a certain range did not affect the NEp of growing pigs, and the models developed with the ANN algorithm could accurately achieve the NE requirement prediction in growing pigs.

Two-stage solid-state fermentation to increase the nutrient value of corn processing waste and explore its efficacy as a feed protein source.

Corn gluten meal-corn husk mixes (CCM) are an inexpensive and readily available agricultural by-product. This study explores a novel technique by converting CCM into high-value livestock feed protein sources through fermentation with Aspergillus niger AAX and Lactobacillus fermentum LLS, aiming to sustainably meet future global protein needs. The process of fermentation significantly altered the structural composition of high molecular weight proteins, zein, and dietary fibers. This transformation resulted in a marked elevation in the concentrations of peptides, free amino acids, and polyphenols. The acidic environment produced during fermentation prevented lipid oxidation in CCM, thereby extending its storability. After fermentation, the content of anti-nutritional factors decreased, while its antioxidant capacity increased. In vitro simulated digestion suggested that fermentation improved the digestibility of CCM protein. In vivo animal experiments showed that fermented CCM (FCCM) promoted growth and gut health in chicks. This study provides new insights into the utilization of CCM.

Smartphone as an alternative to measure chlorophyll-a concentration in small waterbodies.

Monitoring chlorophyll-a concentrations (Chl-a, µg·L-1) in aquatic ecosystems has attracted much attention due to its direct link to harmful algal blooms. However, there has been a lack of a cost-effective method for measuring Chl-a in small waterbodies. Inspired by the increase of smartphone photography, a Smartphone-based convolutional neural networks (CNN) framework (SCCA) was developed to estimate Chl-a in Aquatic ecosystem. To evaluate the performance of SCCA, 238 paired records (a smartphone image with a 12-color background and a measured Chl-a value) were collected from diverse aquatic ecosystems (e.g., rivers, lakes and ponds) across China in 2023. Our performance-evaluation results revealed a NS and R2 value of 0.90 and 0.94 in Chl-a estimation, demonstrating a satisfactory (NS = 0.84, R2 = 0.86) model fit in lower Chl-a (<30 µg L-1) conditions. SCCA had involved a realtime-update method with hyperparameter optimization technology. In comparison with the existing methods of measuring Chl-a, SCCA provides a useful screening tool for cost-effective measurement of Chl-a and has the potential for being an algal bloom screening means in small waterbodies, using Huajin River as a case study, especially under limited resources for water measurement. Overall, we highlight that the SCCA can be potentially integrated into a smartphone application in the future to diverse waterbodies in environmental management.

Understanding electron structure of covalent triazine framework embraced with gold nanoparticles for nitrogen reduction to ammonia.

Regulating the electron structure and precise loading sites of metal-active sites within the highly conjugated and porous covalent-triazine frameworks (CTFs) is essential to promoting the nitrogen reduction reaction (NRR) performance for electrocatalytic ammonia (NH3) synthesis under ambient conditions. Herein, experimental method and density functional theory (DFT) calculations were conducted to deeply probe the effect on NRR of the modulation of modulating the electron structure and the loading site of gold nanoparticles (Au NPs) in a two-dimensional (2D) CTF. 2D CTF synthesized using melem and hexaketocyclohexane octahydrate as building blocks (denoted as M-HCO-CTF) served as a robust scaffold for loading Au NPs to form an M-HCO-CTF@AuNP hybrid. DFT results uncovered that well-defined Au sites with tunable local structure were the active site for driving the NRR, which can significantly suppress the conversion of H+ into *H adsorption and enhance the nitrogen (N2) adsorption/activation. The overlapped Au (3d) and *N2 (2p) orbitals lowered the free energy of the rate-determining step to form *NNH, thereby accelerating the NRR. The M-HCO-CTF@AuNPs electrocatalyst exhibited a large NH3 yield rate of 66.3 µg h-1 mg-1cat. and a high Faraday efficiency of 31.4 % at - 0.2 V versus reversible hydrogen electrode in 0.1 M HCl, superior to most reported CTF-based ones. This work can provide deep insights into the modulation of the electron structure of metal atoms within a porous organic framework for artificial NH3 synthesis through NRR.

Potential effects of Cu2+ stress on nitrogen removal performance, microbial characteristics, and metabolism pathways of biofilm reactor.

Sequencing batch biofilm reactors (SBBR) were utilized to investigate the impact of Cu2+ on nitrogen (N) removal and microbial characteristics. The result indicated that the low concentration of Cu2+ (0.5 mg L-1) facilitated the removal of ammonia nitrogen (NH4+-N), total nitrogen (TN), nitrate nitrogen (NO3--N), and chemical oxygen demand (COD). In comparison to the average effluent concentration of the control group, the average effluent concentrations of NH4+-N, NO3--N, COD, and TN were found to decrease by 40.53%, 17.02%, 10.73%, and 15.86%, respectively. Conversely, the high concentration of Cu2+ (5 mg L-1) resulted in an increase of 94.27%, 55.47%, 22.22%, and 14.23% in the aforementioned parameters, compared to the control group. Low concentrations of Cu2+ increased the abundance of nitrifying bacteria (Rhodanobacter, unclassified-o-Sacharimonadales), denitrifying bacteria (Thermomonas, Comamonas), denitrification-associated genes (hao, nosZ, norC, nffA, nirB, nick, and nifD), and heavy-metal-resistant genes related to Cu2+ (pcoB, cutM, cutC, pcoA, copZ) to promote nitrification and denitrification. Conversely, high concentration Cu2+ hindered the interspecies relationship among denitrifying bacteria genera, nitrifying bacteria genera, and other genera, reducing denitrification and nitrification efficiency. Cu2+ involved in the N and tricarboxylic acid (TCA) cycles, as evidenced by changes in the abundance of key enzymes, such as (EC:1.7.99.1), (EC:1.7.2.4), and (EC:1.1.1.42), which initially increased and then decreased with varying concentrations of Cu2+. Conversely, the abundance of EC1.7.2.1, associated with the accumulation of nitrite nitrogen (NO2--N), gradually declined. These findings provided insights into the impact of Cu2+ on biological N removal.

Expression and Function of Mammary Epithelial Cell-Derived Immunoglobulins.

Over the past 20 years, increasing evidence has demonstrated that immunoglobulins (Igs) can be widely generated from non B cells, including normal and malignant mammary epithelial cells. In normal breast tissue, the expression of IgG and IgA has been identified in epithelial cells of mammary glands during pregnancy and lactation, which can be secreted into milk, and might participate in neonatal immunity. On the other hand, non B-IgG is highly expressed in breast cancer cells, correlating with the poor prognosis of patients with breast cancer. Importantly, a specific group of IgG, bearing a unique N-linked glycan on the Asn162 site and aberrant sialylation modification at the end of the novel glycan (referred to as sialylated IgG (SIA-IgG)), has been found in breast cancer stem/progenitor-like cells. SIA-IgG can significantly promote the capacity of migration, invasiveness, and metastasis, as well as enhance self-renewal and tumorigenicity in vitro and in vivo. These findings suggest that breast epithelial cells can produce Igs with different biological activities under physiological and pathological conditions. During lactation, these Igs could be the main source of milk Igs to protect newborns from pathogenic infections, while under pathological conditions, they display oncogenic activity and promote the occurrence and progression of breast cancer.

Constructing Orbital Coupling-Modulated Homogeneous Dual-Atom Fe-Fe Sites for Boosting Bidirectional Conversion of Polysulfides.

Homogeneous dual-atom catalysts (HDACs) have garnered significant attention for their potential to overcome the shuttling effect and sluggish reaction kinetics in lithium-sulfur (Li-S) batteries. However, modulating the electron structure of metal atomic orbitals for HDACs to dictate the catalytic activity toward polysulfides has remained meaningful but unexplored so far. Herein, an interfacial cladding strategy is developed to obtain a new type of dual-atom iron matrix with a unique FeN2P1-FeN2P1 coordination structure (Fe2@NCP). The 3d orbital electrons of the Fe centers are redistributed by incorporating phosphorus atoms into the first coordination sphere. The theoretical calculations disclose that the strong coupling between the Fe d orbital and the S p orbital exhibits an enhanced Fe-S bond and improved reactivity toward polysulfides. Moreover, the Fe2@NCP catalyst achieves robust adsorption ability toward Li2Sn (1 ≤ n ≤ 8) and significantly boosts bidirectional sulfur redox reaction kinetics by lowering the Li2S deposition/decomposition energy barriers. Consequently, the assembled Li-S batteries present a high retention ratio of 77.3% after 500 cycles at 1C. Furthermore, the Li-S pouch cell also exhibits good performance at 0.1C (80.2% retention over 100 cycles) for practical application with a sulfur loading of 4.0 mg/cm2. The outcome of this study will facilitate the design of homogeneous dual-atom catalysts for Li-S batteries.

Optimizing Crystal Orientation and Defect Mitigation in Antimony Selenide Thin-Film Solar Cells through Buffer Layer Energy Band Adjustment.

Antimony selenide (Sb2Se3) has sparked significant interest in high-efficiency photovoltaic applications due to its advantageous material and optoelectronic properties. In recent years, there has been considerable development in this area. Nonetheless, defects and suboptimal [hk0] crystal orientation expressively limit further device efficiency enhancement. This study used Zinc (Zn) to adjust the interfacial energy band and strengthen carrier transport. For the first time, it is discovered that the diffusion of Zn in the cadmium sulfide (CdS) buffer layer can affect the crystalline orientation of the Sb2Se3 thin films in the superstrate structure. The effect of Zn diffusion on the morphology of Sb2Se3 thin films with CdxZn1-xS buffer layer has been investigated in detail. Additionally, Zn doping promotes forming Sb2Se3 thin films with the desired [hk1] orientation, resulting in denser and larger grain sizes which will eventually regulate the defect density. Finally, based on the energy band structure and high-quality Sb2Se3 thin films, this study achieves a champion power conversion efficiency (PCE) of 8.76%, with a VOC of 458 mV, a JSC of 28.13 mA cm-2, and an FF of 67.85%. Overall, this study explores the growth mechanism of Sb2Se3 thin films, which can lead to further improvements in the efficiency of Sb2Se3 solar cells.

The cross-cultural adaptation of Chinese international students: an empirical study on sequential-mediated effects.

Using convenience sampling and snowball sampling methods, data from 432 Chinese international students in 10 countries, including the United Kingdom, South Korea, and the United States, were collected to construct a multivariate sequential-mediated mixed model for cross-cultural adaptation. SPSS 23.0 and AMOS 23.0 were employed for aggregated validity, discriminant validity, and sequential-mediated effects analysis. The study found that: Cultural adaptation stress is negatively correlated with positive coping and positively correlated with negative coping, with negative coping having a significant negative impact during the cross-cultural adaptation process. Positive coping is positively correlated with sports participation, while negative coping is negatively correlated with sports participation. Sports participation is positively associated with in-group identification and negatively associated with out-group bias. In-group identification has a positive impact on cross-cultural adaptation, whereas out-group bias cannot effectively predict cross-cultural adaptation.

Peritoneal fluid indocyanine green test for diagnosis of gut leakage in anastomotic leakage rats and colorectal surgery patients.

BACKGROUND: Application of indocyanine green (ICG) fluorescence has led to new developments in gastrointestinal surgery. However, little is known about the use of ICG for the diagnosis of postoperative gut leakage (GL). In addition, there is a lack of rapid and intuitive methods to definitively diagnose postoperative GL. AIM: To investigate the effect of ICG in the diagnosis of anastomotic leakage in a surgical rat GL model and evaluate its diagnostic value in colorectal surgery patients. METHODS: Sixteen rats were divided into two groups: GL group (n = 8) and sham group (n = 8). Approximately 0.5 mL of ICG (2.5 mg/mL) was intravenously injected postoperatively. The peritoneal fluid was collected for the fluorescence test at 24 and 48 h. Six patients with rectal cancer who had undergone laparoscopic rectal cancer resection plus enterostomies were injected with 10 mL of ICG (2.5 mg/mL) on postoperative day 1. Their ostomy fluids were collected 24 h after ICG injection to identify the possibility of the ICG excreting from the peripheral veins to the enterostomy stoma. Participants who had undergone colectomy or rectal cancer resection were enrolled in the diagnostic test. The peritoneal fluids from drainage were collected 24 h after ICG injection. The ICG fluorescence test was conducted using OptoMedic endoscopy along with a near-infrared fluorescent imaging system. RESULTS: The peritoneal fluids from the GL group showed ICG-dependent green fluorescence in contrast to the sham group. Six samples of ostomy fluids showed green fluorescence, indicating the possibility of ICG excreting from the peripheral veins to the enterostomy stoma in patients. The peritoneal fluid ICG test exhibited a sensitivity of 100% and a specificity of 83.3% for the diagnosis of GL. The positive predictive value was 71.4%, while the negative predictive value was 100%. The likelihood ratios were 6.0 for a positive test result and 0 for a negative result. CONCLUSION: The postoperative ICG test in a drainage tube is a valuable and simple technique for the diagnosis of GL. Hence, it should be employed in clinical settings in patients with suspected GL.

Electrochemical oxidative thioetherification of aldehyde hydrazones with thiophenols.

An electrochemically promoted oxidative dehydrogenation cross-coupling reaction between aldehyde hydrazones and thiophenols is demonstrated for the first time, which resulted in a variety of (Z)-thioetherified products in moderate to excellent yields. This strategy can be carried out under an air atmosphere, featuring scalability and excellent stereoselectivity. In addition, the transformation efficiently produces readily recyclable disulfide as a by-product with high yields, which significantly reduces the environmental pollution caused by thioetherification.

Identification of the M2 Macrophage-associated Gene THBS2 as a Predictive Marker for Inflammatory Cancer Transformation.

Ulcerative colitis (UC)-induced colitis-associated colorectal cancer (CAC) has a worse prognosis than sporadic colorectal cancer. And with the incidence of ulcerative colitis on the rise, it is critical to identify new therapeutic targets in time to stop the progression of inflammation to cancer. Through immunohistochemistry (IHC) and Gene Expression Omnibus (GEO) database analysis, we acquired the gene M2DEG, which is differentially expressed in M2 macrophages. The impact of M2DEG on the immune environment and clinical variables was confirmed through various data sets and actual tissue samples. Our findings indicate that patients with UC exhibiting reduced M2 macrophage infiltration tend to have more widespread disease, elevated endoscopic Mayo scores, and a higher probability of developing CAC. Through examining the string of M2DEG between UC and CAC, THBS2 emerged as a key marker. Elevated levels of THBS2 were notably linked to reduced overall survival (OS) and progression-free survival (RFS), and this heightened THBS2 expression played a crucial role in the spread of tumors, as verified by immunohistochemical studies. To sum up, patients with UC exhibiting reduced M2 macrophage infiltration have a higher propensity for CAC development, making THBS2 a crucial focus for converting UC into CAC. Furthermore, identifying antibody analogues targeting THBS2 could potentially lower the likelihood of CAC transformation in patients with UC.

Ulcerative colitis patients with low M2DEG expression have more extensive lesions, poorer immune responses, and higher Mayo endoscopic scores, implying a poorer prognosis and a greater likelihood of transformation from UC to CAC. THBS2 is M2DEG's core gene; the search for an antibody targeting THBS2 may help lower the risk of CAC transformation in patients with UC.