Effect of Recycled Fine Aggregates on the Mechanical and Drying Shrinkage Properties of Alkali-Activated Recycled Concrete.

In this paper, the workability, mechanical, ion leaching, and drying shrinkage properties of alkali-activated concrete with recycled coarse and fine aggregates were studied, and the pore structure and micro-morphology of different alkali-activated recycled aggregate concretes (AARACs) were characterized by using the mercury intrusion method and scanning electron microscopy, respectively. The experimental results showed that with the increase in the replacement rate of the recycled fine aggregate (RFA), the flowability showed a decreasing trend. Adding a certain amount of RFA improves the mechanical properties of the AARAC. The compressive strength at a curing age of 28 days was 65.3 MPa with 70 wt% RFA replacement. When the replacement rate of the RFA was 100 wt%, the maximum splitting tensile strength (4.5 MPa) was obtained at a curing age of 7 days. However, the addition of the RFA had little effect on the flexural strength of the AARAC. As an extension of the curing age, the splitting tensile strength, flexural strength, tension-to-compression ratio, and flexure-to-compression ratio all showed an increasing trend at first and then a decreasing trend. At a curing age of 7 days, the tension-to-compression ratio and flexure-to-compression ratio were both high (except for those of R100), indicating that the ductility and toughness of the specimen were improved. The addition of the RFA increased the drying shrinkage of the AARAC. At a curing age of 120 days, compared to the specimen without the RFA, the drying shrinkage rate of the specimen with the addition of 70 wt% RFA increased by 34.15%. As the curing age increased, the microstructure of the reaction products became denser, but the proportion of large-diameter pores increased. This study evaluated the application of RFA in AARAC. The experimental results showed that the RFA-based AARAC had acceptable mechanical and durability properties.

Bayesian network analysis of factors influencing type 2 diabetes, coronary heart disease, and their comorbidities.

OBJECTIVE: Bayesian network (BN) models were developed to explore the specific relationships between influencing factors and type 2 diabetes mellitus (T2DM), coronary heart disease (CAD), and their comorbidities. The aim was to predict disease occurrence and diagnose etiology using these models, thereby informing the development of effective prevention and control strategies for T2DM, CAD, and their comorbidities. METHOD: Employing a case-control design, the study compared individuals with T2DM, CAD, and their comorbidities (case group) with healthy counterparts (control group). Univariate and multivariate Logistic regression analyses were conducted to identify disease-influencing factors. The BN structure was learned using the Tabu search algorithm, with parameter estimation achieved through maximum likelihood estimation. The predictive performance of the BN model was assessed using the confusion matrix, and Netica software was utilized for visual prediction and diagnosis. RESULT: The study involved 3,824 participants, including 1,175 controls, 1,163 T2DM cases, 982 CAD cases, and 504 comorbidity cases. The BN model unveiled factors directly and indirectly impacting T2DM, such as age, region, education level, and family history (FH). Variables like exercise, LDL-C, TC, fruit, and sweet food intake exhibited direct effects, while smoking, alcohol consumption, occupation, heart rate, HDL-C, meat, and staple food intake had indirect effects. Similarly, for CAD, factors with direct and indirect effects included age, smoking, SBP, exercise, meat, and fruit intake, while sleeping time and heart rate showed direct effects. Regarding T2DM and CAD comorbidities, age, FBG, SBP, fruit, and sweet intake demonstrated both direct and indirect effects, whereas exercise and HDL-C exhibited direct effects, and region, education level, DBP, and TC showed indirect effects. CONCLUSION: The BN model constructed using the Tabu search algorithm showcased robust predictive performance, reliability, and applicability in forecasting disease probabilities for T2DM, CAD, and their comorbidities. These findings offer valuable insights for enhancing prevention and control strategies and exploring the application of BN in predicting and diagnosing chronic diseases.

Research on mix design and mechanical performances of MK-GGBFS based geopolymer pastes using central composite design method.

In order to alleviate environmental problems and reduce CO2 emissions, geopolymers had drew attention as a kind of alkali-activated materials. Geopolymers are easier access to raw materials, green and environment friendly than traditional cement industry. Its special reaction mechanism and gel structure show excellent characteristics such as quick hardening, high strength, acid and alkali resistance. In this paper, geopolymer pastes were made with metakaolin (MK) and ground granulated blast furnace slag (GGBFS) as precursors. The effects of liquid-solid ratio (L/S) and modulus of sodium silicate (Ms) on the performances of MK-GGBFS based geopolymer paste (MSGP) were characterized by workability, strength and microstructural tests. The regression equations were obtained by central composite design method to optimize the mix design of MSGP. The goodness of fit of all the equations were more than 98%. Based on the results of experiments, the optimum mix design was found to have L/S of 0.75 and Ms of 1.55. The workability of MSGP was significantly improved while maintaining the strength under the optimum mix design. The initial setting time of MSGP decreased by 71.8%, while both of the fluidity and 28-d compressive strength increased by 15.3%, compared with ordinary Portland cement pastes. Therefore, geopolymers are promising alternative cementitious material, which can consume a large amount of MK and GGBFS and promote green and clean production.

PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge.

PubTator 3.0 (https://www.ncbi.nlm.nih.gov/research/pubtator3/) is a biomedical literature resource using state-of-the-art AI techniques to offer semantic and relation searches for key concepts like proteins, genetic variants, diseases and chemicals. It currently provides over one billion entity and relation annotations across approximately 36 million PubMed abstracts and 6 million full-text articles from the PMC open access subset, updated weekly. PubTator 3.0's online interface and API utilize these precomputed entity relations and synonyms to provide advanced search capabilities and enable large-scale analyses, streamlining many complex information needs. We showcase the retrieval quality of PubTator 3.0 using a series of entity pair queries, demonstrating that PubTator 3.0 retrieves a greater number of articles than either PubMed or Google Scholar, with higher precision in the top 20 results. We further show that integrating ChatGPT (GPT-4) with PubTator APIs dramatically improves the factuality and verifiability of its responses. In summary, PubTator 3.0 offers a comprehensive set of features and tools that allow researchers to navigate the ever-expanding wealth of biomedical literature, expediting research and unlocking valuable insights for scientific discovery.

Bayesian network-based survival prediction model for patients having undergone post-transjugular intrahepatic portosystemic shunt for portal hypertension.

BACKGROUND: Portal hypertension (PHT), primarily induced by cirrhosis, manifests severe symptoms impacting patient survival. Although transjugular intrahepatic portosystemic shunt (TIPS) is a critical intervention for managing PHT, it carries risks like hepatic encephalopathy, thus affecting patient survival prognosis. To our knowledge, existing prognostic models for post-TIPS survival in patients with PHT fail to account for the interplay among and collective impact of various prognostic factors on outcomes. Consequently, the development of an innovative modeling approach is essential to address this limitation. AIM: To develop and validate a Bayesian network (BN)-based survival prediction model for patients with cirrhosis-induced PHT having undergone TIPS. METHODS: The clinical data of 393 patients with cirrhosis-induced PHT who underwent TIPS surgery at the Second Affiliated Hospital of Chongqing Medical University between January 2015 and May 2022 were retrospectively analyzed. Variables were selected using Cox and least absolute shrinkage and selection operator regression methods, and a BN-based model was established and evaluated to predict survival in patients having undergone TIPS surgery for PHT. RESULTS: Variable selection revealed the following as key factors impacting survival: age, ascites, hypertension, indications for TIPS, postoperative portal vein pressure (post-PVP), aspartate aminotransferase, alkaline phosphatase, total bilirubin, prealbumin, the Child-Pugh grade, and the model for end-stage liver disease (MELD) score. Based on the above-mentioned variables, a BN-based 2-year survival prognostic prediction model was constructed, which identified the following factors to be directly linked to the survival time: age, ascites, indications for TIPS, concurrent hypertension, post-PVP, the Child-Pugh grade, and the MELD score. The Bayesian information criterion was 3589.04, and 10-fold cross-validation indicated an average log-likelihood loss of 5.55 with a standard deviation of 0.16. The model's accuracy, precision, recall, and F1 score were 0.90, 0.92, 0.97, and 0.95 respectively, with the area under the receiver operating characteristic curve being 0.72. CONCLUSION: This study successfully developed a BN-based survival prediction model with good predictive capabilities. It offers valuable insights for treatment strategies and prognostic evaluations in patients having undergone TIPS surgery for PHT.

An Antibacterial Bionic Periosteum with Angiogenesis-Neurogenesis Coupling Effect for Bone Regeneration.

The periosteum, rich in neurovascular networks, bone progenitor cells, and stem cells, is vital for bone repair. Current artificial periosteal materials face challenges in mechanical strength, bacterial infection, and promoting osteogenic differentiation and angiogenesis. To address these issues, we adjusted the electrospinning ratio of poly-ε-caprolactone and chitosan and incorporated Zn doping whitlockite with polydopamine coating into a nanofiber membrane. After a series of characterizations, optimal results were achieved with a poly-ε-caprolactone: chitosan ratio of 8:1 and 5% nanoparticle content. In vitro cell experiments and in vivo calvarial defect models, the sustained release of Mg2+ and Ca2+ promoted vascularization and new bone formation, respectively, while the release of Zn2+ was conducive to antibacterial and cooperated with Mg2+ to promote neurovascularization. Consequently, this antibacterial bionic periosteum with an angiogenesis-neurogenesis coupling effect demonstrates a promising potential for bone repair applications.

P2X7 receptor is essential for ST36-attenuated cardiac fibrosis upon beta-adrenergic insult.

P2X7 receptor (P2X7R) plays an important role in modulating inflammation and fibrosis, but information is limited whether Zusanli (ST36) can inhibit inflammation and fibrosis by regulating P2X7R. Isoprenaline at 5 mg/kg was subcutaneously injected to wild-type and P2X7R knockout mice for 7 days, while treatment groups received electroacupuncture (EA) stimulation at ST36 for 7 sessions. Following 7-session treatment, Masson's trichrome staining was performed to assess the fibrosis. Morphology, electrocardiogram, and echocardiography were carried out to evaluate the cardiac function and structure. Western blotting, hematoxylin and eosin staining, immunohistochemistry, and biochemical analysis of inflammatory cytokine and transmission electron microscopy were carried out to characterize the effect of ST36 on inflammation. P2X7R was overexpressed in ISO-treated mice. EA at ST36, but not at non-points, reduced ISO-induced cardiac fibrosis, increases in HW/BW, R+S wave relative to mice in ISO groups. In addition, EA at ST36 downregulated ISO-upregulated P2X7R and NLRP3 in ventricle. Moreover, EA reduced cytokines of IL-1ß, IL-6, and IL-18 in serum, and inhibited foam cell gathering, inflammatory cell infiltration, and autophagy. However, EA at ST36 failed to attenuate the cardiac fibrosis and hypertrophy in P2X7R knockout mice. In conclusion, EA at ST36 attenuated ISO-induced fibrosis possibly via P2X7R.

Optimized strategy among diet, exercise, and pharmacological interventions for nonalcoholic fatty liver disease: A network meta-analysis of randomized controlled trials.

BACKGROUND: Emerging treatment methods, including exercise, diet, and drugs, for nonalcoholic fatty liver disease have been proposed. However, the differences in their efficacy have not been determined. We aimed to compare the effects of these treatments excluding surgery via a systematic review and network meta-analysis of randomized controlled trials. DATA SOURCE: The data sources included PubMed, Embase, Web of Science and Cochrane up to February 1st, 2023. The endpoints consisted of body mass index (BMI), serum markers of metabolism and liver injury markers, liver fat content, and stiffness. RESULTS: A total of 174 studies with 10,183 patients were included in this meta-analysis. In terms of improving BMI, Pan-agonist of peroxisome proliferator-activated receptors (PPAR) is the best treatment with the highest SUCRA (surface under the cumulative ranking) of 84.8% (mean = -3.40, 95% CI -5.55, -1.24) by the comparative effectiveness ranking. GLP-1 (glucagon-like peptide-1) has the best effect in improving the liver fat content based on the MRI-PDFF, steatosis score (SUCRA 99.7%, mean = -2.19, 95% CI -2.90, -1.48) and ballooning score (SUCRA 61.2%, mean = -0.82, 95% CI -4.46, 2.83). CONCLUSIONS: Pan-agonist of PPAR was the most efficacious regimen in lowering BMIs, whereas GLP-1R agonists achieved the highest efficacy of steatosis improvement in this network meta-analysis.

Role of remnant cholesterol in the relationship between physical activity and diabetes mellitus: an intermediary analysis.

Objective: The purpose of this investigation was to evaluate the potential link between physical activity (PA) and the heightened susceptibility to diabetes mellitus (DM), by examining whether remnant cholesterol (RC) might act as a mediator in this correlation. Methods: The research utilized data from the National Health and Nutrition Examination Survey, spanning from 2005 to 2018. Various statistical analyses were conducted for continuous and categorical variables, including the t-test, ANOVA, and χ2 test. Logistic regression was employed to analyze the association between PA and DM across three distinct models. Mediation analysis was also conducted to assess the potential mediation effects of RC. Results: The study encompassed a total of 9,149 participants, and it was observed that individuals with DM exhibited lower levels of PA. Furthermore, PA levels were found to be associated with all participant characteristics except poverty income ratio, fasting blood glucose, and HOMA-IR (p < 0.05). After adjusting for covariates (Model 3), individuals with high PA levels demonstrated a decreased likelihood of developing DM compared to those in the low PA group (OR: 0.73, 95%CI: 0.54-0.99). A significant dose-response relationship was identified (p < 0.05). No interaction between PA and RC in relation to DM risk was detected, and RC was found to serve as a mediator in the connection between PA and DM. After considering covariates, the mediating effect of RC between PA and DM weakens. Discussion: Our findings suggest that higher levels of PA are linked to a reduced risk of DM in U.S. adults, with RC likely playing a mediating role.

Bezafibrate alleviates diabetes-induced spermatogenesis dysfunction by inhibiting inflammation and oxidative stress.

The metabolic disorders caused by diabetes can lead to various complications, including male spermatogenesis dysfunction. Exploring effective therapeutics that attenuate diabetes mellitus (DM)-induced male subfertility is of great importance. Pharmaceuticals targeting PPARα activation such as bezafibrate have been regarded as an important strategy for patients with diabetes. In this study, we use streptozocin (STZ) injection to establish a type 1 DM mice model and use bezafibrate to treat DM mice and evaluate the effects of bezafibrate on the spermatogenic function of the DM male mice. Bezafibrate treatment exhibited protective effects on DM-induced spermatogenesis deficiency, as reflected by increased testis weight, improved histological morphology of testis, elevated sperm parameters, increased serum testosterone concentration as well as increased mRNA levels of steroidogenesis enzymes. Meanwhile, testicular cell apoptosis, inflammation accumulation and oxidative stress status were also shown to be alleviated by bezafibrate compared with the DM group. In vivo and in vitro studies, PPARα specific inhibitor and PPARα knockout mice were further used to investigate the role of PPARα in the protective effects of bezafibrate on DM-induced spermatogenesis dysfunction. Our results indicated that the protection of bezafibrate on DM-induced spermatogenesis deficiency was abrogated by PPARα inhibition or deletion. Our study suggested that bezafibrate administration could ameliorate DM-induced spermatogenesis dysfunction and may represent a novel practical strategy for male infertility.

The mediating effect of self-directed learning ability between professional identity and burnout among nursing students.

Objectives: Burnout influences students' academic performance and mental health. This study analyzed the relationship between professional identity, self-directed learning ability, and burnout, and examined the mediating effect of self-directed learning ability between professional identity and burnout among nursing students. Methods: 884 nursing students were recruited at two medical universities in China. Demographic information, Academic Burnout Scale, Professional Identity Questionnaire for Nursing Students, and Self-directed Learning Instrument were distributed to collect data. Results: Both professional identity (ß = -0.17) and self-directed learning ability (ß = -0.43) showed negative associations with students' burnout. Meanwhile, there was a partial mediating effect of self-directed learning ability between professional identity and burnout (-0.24, 95% CI = -0.30, -0.20). Conclusions: Nursing educators should emphasize on developing effective strategies to improve nursing students' professional identity and self-directed learning ability to prevent or reduce their burnout.

The fate of antibiotic resistance genes in wastewater containing microalgae treated by chlorination, ultra-violet, and Fenton reaction.

Antibiotic resistance genes (ARGs) and bacteria (ARBs) in the effluent of wastewater treatment plants (WWTPs) are of utmost importance for the dissemination of ARGs in natural aquatic environments. Therefore, there is an urgent need for effective technologies to eliminate WWTP ARGs/ARBs and mitigate the associated risks posed by the discharged ARG in aquatic environments. To test the effective technology for eliminating ARGs/ARBs, we compared the removal of ARGs and ARBs by three different tertiary treatments, namely ultra-violet (UV) disinfection, chlorination disinfection, and Fenton oxidation. Then, the treated wastewater was co-cultured with Chlorella vulgaris (representative of aquatic biota) to investigate the fate of discharged ARGs into the aquatic environment. The results demonstrated that chlorination (at a chlorine concentration of 15 mg/L) and Fenton (at pH 2.73, with 0.005 mol/L Fe2+ and 0.0025 mol/L H2O2) treatment showed higher efficacy in ARG removal (1.8 - 4.17 logs) than UV treatment (15 min) (1.29 - 3.87 logs). Moreover, chlorine at 15 mg/L and Fenton treatment effectively suppressed ARB regeneration while UV treatment for 15 min could not. Regardless of treatments tested in this study, the input of treated wastewater to the Chlorella system increased the number of ARGs and mobile genetic elements (MGEs), indicating the potential risk of ARG dissemination associated with WWTP discharge. Among the wastewater-Chlorella co-culture systems, chlorination resulted in less of an increase in the number of ARGs and MGEs compared to Fenton and UV treatment. When comparing the wastewater systems to the co-culture systems, it was observed that Chlorella vulgaris reduced the number of ARGs and MGEs in chlorination and UV-treated wastewater; however, Chlorella vulgaris promoted ARG survival in Fenton-treated water, suggesting that aquatic microalgae might act as a barrier to ARG dissemination. Overall, chlorination treatment not only effectively removes ARGs and inhibits ARB regeneration but also shows a lower risk of ARG dissemination. Therefore, chlorination is recommended for practical application in controlling the spread of discharged ARGs from WWTP effluent in natural aquatic environments.

PubTator 3.0: an AI-powered Literature Resource for Unlocking Biomedical Knowledge.

PubTator 3.0 (https://www.ncbi.nlm.nih.gov/research/pubtator3/) is a biomedical literature resource using state-of-the-art AI techniques to offer semantic and relation searches for key concepts like proteins, genetic variants, diseases, and chemicals. It currently provides over one billion entity and relation annotations across approximately 36 million PubMed abstracts and 6 million full-text articles from the PMC open access subset, updated weekly. PubTator 3.0's online interface and API utilize these precomputed entity relations and synonyms to provide advanced search capabilities and enable large-scale analyses, streamlining many complex information needs. We showcase the retrieval quality of PubTator 3.0 using a series of entity pair queries, demonstrating that PubTator 3.0 retrieves a greater number of articles than either PubMed or Google Scholar, with higher precision in the top 20 results. We further show that integrating ChatGPT (GPT-4) with PubTator APIs dramatically improves the factuality and verifiability of its responses. In summary, PubTator 3.0 offers a comprehensive set of features and tools that allow researchers to navigate the ever-expanding wealth of biomedical literature, expediting research and unlocking valuable insights for scientific discovery.

Genome-wide identification of GATA transcription factor family and the effect of different light quality on the accumulation of terpenoid indole alkaloids in Uncaria rhynchophylla.

Uncaria rhynchophylla is an evergreen vine plant, belonging to the Rubiaceae family, that is rich in terpenoid indole alkaloids (TIAs) that have therapeutic effects on hypertension and Alzheimer's disease. GATA transcription factors (TF) are a class of transcription regulators that participate in the light response regulation, chlorophyll synthesis, and metabolism, with the capability to bind to GATA cis-acting elements in the promoter region of target genes. Currently the charactertics of GATA TFs in U. rhynchophylla and how different light qualities affect the expression of GATA and key enzyme genes, thereby affecting the changes in U. rhynchophylla alkaloids have not been investigated. In this study, 25 UrGATA genes belonging to four subgroups were identified based on genome-wide analysis. Intraspecific collinearity analysis revealed that only segmental duplications were identified among the UrGATA gene family. Collinearity analysis of GATA genes between U. rhynchophylla and four representative plant species, Arabidopsis thaliana, Oryza sativa, Coffea Canephora, and Catharanthus roseus was also performed. U. rhynchophylla seedlings grown in either red lights or under reduced light intensity had altered TIAs content after 21 days. Gene expression analysis reveal a complex pattern of expression from the 25 UrGATA genes as well as a number of key TIA enzyme genes. UrGATA7 and UrGATA8 were found to have similar expression profiles to key enzyme TIA genes in response to altered light treatments, implying that they may be involved in the regulation TIA content. In this research, we comprehensively analyzed the UrGATA TFs, and offered insight into the involvement of UrGATA TFs from U. rhynchophylla in TIAs biosynthesis.

A comprehensive review of the literature on CD10: its function, clinical application, and prospects.

CD10, a zinc-dependent metalloprotease found on the cell surface, plays a pivotal role in an array of physiological and pathological processes including cardiovascular regulation, immune function, fetal development, pain response, oncogenesis, and aging. Recognized as a biomarker for hematopoietic and tissue stem cells, CD10 has garnered attention for its prognostic potential in the progression of leukemia and various solid tumors. Recent studies underscore its regulatory significance and therapeutic promise in combating Alzheimer's disease (AD), and it is noted for its protective role in preventing heart failure (HF), obesity, and type-2 diabetes. Furthermore, CD10/substance P interaction has also been shown to contribute to the pain signaling regulation and immunomodulation in diseases such as complex regional pain syndrome (CRPS) and osteoarthritis (OA). The emergence of COVID-19 has sparked interest in CD10's involvement in the disease's pathogenesis. Given its association with multiple disease states, CD10 is a prime therapeutic target; inhibitors targeting CD10 are now being advanced as therapeutic agents. This review compiles recent and earlier literature on CD10, elucidating its physicochemical attributes, tissue-specific expression, and molecular functions. Furthermore, it details the association of CD10 with various diseases and the clinical advancements of its inhibitors, providing a comprehensive overview of its growing significance in medical research.

Taiyi: a bilingual fine-tuned large language model for diverse biomedical tasks.

OBJECTIVE: Most existing fine-tuned biomedical large language models (LLMs) focus on enhancing performance in monolingual biomedical question answering and conversation tasks. To investigate the effectiveness of the fine-tuned LLMs on diverse biomedical natural language processing (NLP) tasks in different languages, we present Taiyi, a bilingual fine-tuned LLM for diverse biomedical NLP tasks. MATERIALS AND METHODS: We first curated a comprehensive collection of 140 existing biomedical text mining datasets (102 English and 38 Chinese datasets) across over 10 task types. Subsequently, these corpora were converted to the instruction data used to fine-tune the general LLM. During the supervised fine-tuning phase, a 2-stage strategy is proposed to optimize the model performance across various tasks. RESULTS: Experimental results on 13 test sets, which include named entity recognition, relation extraction, text classification, and question answering tasks, demonstrate that Taiyi achieves superior performance compared to general LLMs. The case study involving additional biomedical NLP tasks further shows Taiyi's considerable potential for bilingual biomedical multitasking. CONCLUSION: Leveraging rich high-quality biomedical corpora and developing effective fine-tuning strategies can significantly improve the performance of LLMs within the biomedical domain. Taiyi shows the bilingual multitasking capability through supervised fine-tuning. However, those tasks such as information extraction that are not generation tasks in nature remain challenging for LLM-based generative approaches, and they still underperform the conventional discriminative approaches using smaller language models.

Replantation of digit-tip amputation caused by crush injuries with supermicrosurgery technique.

PURPOSE: Digit-tip amputation caused by crush injury is a common emergency scenario, and the management is full of challenges. The objective of this study was to demonstrate the application of the supermicrosurgery technique in replantation procedures for complex digit-tip amputations resulting from crush injuries, while also assessing functional and aesthetic outcomes. METHODS: We conducted a retrospective analysis of the data from 12 patients who underwent replantation of 15 digits in our department between July 2022 and June 2023. The outcomes of replantation, functional recovery (including return to work, cold tolerance, bone union, DASH score, VAS score, and two-point discrimination test), aesthetic results (including digit appearance, nail deformity, and pulp atrophy), and patient satisfaction were assessed. RESULTS: The amputation of 7 digits occurred within Tamai zone I level, 8 digits within Tamai zone II level, while 4 digits occurred within Ishikawa zone I level, 3 digits within Ishikawa zone II level, 7 digits within Ishikawa zone III level, and 1 digit within Ishikawa zone IV level. The replanted digits all survived (100%) without any indications of arterial insufficiency or venous congestion. The follow-up procedures were conducted on all 12 patients, with an average duration of 9.6 months (range, 6 to 18 months). The fracture successfully underwent healing at 9.2 weeks (range, 8 to 13 weeks). The mean VAS score was 1.75 points (range 0 to 4 points), the mean two-point discrimination test result was 5.72 mm (range 4.0 to 7.0 mm), and the mean DASH score was 9.78 points (range 3.33 to 22.5 points). All patients demonstrated cold tolerance and successfully resumed their pre-injury occupational activities. The nail deformity was observed in one digit following replantation within Tamai zone I, and in three digits following replantation within Tamai zone II; moreover, eight digits exhibited varying degrees of pulp atrophy. All patients expressed satisfaction with both functional and aesthetic outcomes. CONCLUSION: The successful replantation of digit-tip amputation caused by crush injury can be achieved through the application of supermicrosurgery technique, resulting in improved functional and aesthetic outcomes. Digit-tip replantation is a favorable and meaningful procedure with high patient satisfaction.

Cu-Catalyzed Direct Enantioselective Vinylogous Mannich Reaction between ß,γ-Unsaturated Pyrazoleamides and Ketimines.

A catalytic asymmetric vinylogous Mannich-type reaction between ß,γ-unsaturated amides and ketimines has been developed in excellent regio-, diastereo-, and enantioselectivities. The methodology provides an efficient approach to construct chiral homoallylic amines with a 3-amino-2-oxindole scaffold. Moreover, the transformations of the chiral products, including the removal of the pyrazole group or Boc group, the reduction of the C-C double bond, and Suzuki coupling, have been investigated.

Prognostic significance and relationship of SMAD3 phospho-isoforms and VEGFR-1 in gastric cancer: A clinicopathological study.

BACKGROUND: The TGF-ß/SMAD3 and VEGFR-1 signaling pathways play important roles in gastric cancer metastasis. SMAD3 phosphorylation is a crucial prognostic marker in gastric cancer. AIM: To determine the prognostic value and relationship of SMAD3 phospho-isoforms and VEGFR-1 in gastric cancer. METHODS: This was a single-center observational study which enrolled 98 gastric cancer patients and 82 adjacent normal gastric tissues from patients aged 32-84 years (median age 65) between July 2006 and April 2007. Patients were followed up until death or the study ended (median follow-up duration of 28.5 mo). The samples were used to generate tissue microarrays (TMAs) for immunohistochemical (IHC) staining. The expressions of TGF-ß1, pSMAD3C(S423/425), pSMAD3L(S204), and VEGFR-1 in gastric cancer (GC) tumor tissue and normal tissue were measured by IHC staining using TMAs obtained from 98 GC patients. Prognosis and survival information of the patients was recorded by Outdo Biotech from May 2007 to July 2015. The relationship between TGF-ß1, pSMAD3C(S423/425), pSMAD3L(S204), and VEGFR-1 protein expression levels was analyzed using Pearson's correlation coefficient. The relationship between protein expression levels and clinicopathological parameters was analyzed using the Chi-squared test. A survival curve was generated using the Kaplan-Meier survival analysis. RESULTS: TGFß-1 and VEGFR-1 expression was significantly upregulated in gastric cancer tissue compared to adjacent non-cancerous tissue. The positive expression of phosphorylated isoforms of Smad3 varied depending on the phosphorylation site [pSMAD3C(S423/425): 51.0% and pSMAD3L(S204): 31.6%]. High expression of pSMAD3L(S204) was significantly correlated with larger tumors (P = 0.038) and later N stages (P = 0.035). Additionally, high expression of VEGFR-1 was closely correlated with tumor size (P = 0.015) and pathological grading (P = 0.013). High expression of both pSMAD3L(S204) and VEGFR-1 was associated with unfavorable outcomes in terms of overall survival (OS). Multivariate analysis indicated that high expression of pSMAD3L(S204) and VEGFR-1 were independent risk factors for prognosis in GC patients. VEGFR-1 protein expression was correlated with TGF-ß1 (r = 0.220, P = 0.029), pSMAD3C(S423/425) (r = 0.302, P = 0.002), and pSMAD3L(S204) (r = 0.201, P = 0.047), respectively. Simultaneous overexpression of pSMAD3L(S204) and VEGFR-1 was associated with poor OS in gastric cancer patients. CONCLUSION: Co-upregulation of pSMAD3L(S204) and VEGFR-1 can serve as a predictive marker for poor gastric cancer prognosis, and pSMAD3L(204) may be involved in enhanced gastric cancer metastasis in a VEGFR-1-dependent manner.

A bibliometric analysis of global research hotspots and progress on microplastics in soil‒plant systems.

Plastic pollution has become a global and persistent challenge, posing threats to ecosystems and organisms. In recent years, there has been a rapid increase in scientific research focused on understanding microplastics in the soil‒plant system. This surge is primarily driven by the direct impact of microplastics on agricultural productivity and their association with human activities. In this study, we conducted a comprehensive bibliometric analysis to provide an overview of the current research on microplastics in soil‒plant systems. We systematically analysed 192 articles and observed a significant rise in research interests since 2017. Notably, China has emerged as a leading contributor in terms of published papers, closely followed by Germany and the Netherlands. Through co-authorship network analysis, we identified 634 different institutions that participated in publishing papers in this field, with the Chinese Academy of Sciences having the most collaborations. In the co-occurrence keyword network, we identified four clusters focusing on the diversity of microplastics within the agroecosystem, transportation, and quantification of microplastics in soil, analysis of plastic contamination type and impact, and investigation of microplastic phytotoxicity. Furthermore, we identified ten research priorities, categorized into the effects of microplastics in "soil" and "plant". The research hotspots were found to be the effect of microplastics on soil physicochemical properties and the synergistic phytotoxicity of microplastics with other pollutants. Overall, this bibliometric analysis holds significant value, serving as an important reference point and offering valuable suggestions for future researchers in this rapidly advancing field.