Differentiation of Uc-MSCs into insulin secreting islet-like clusters by trypsin through TGF-beta signaling pathway.

Differentiation of human umbilical cord mesenchymal stem cells (Uc-MSCs) into islet-like clusters which are capable of synthesizing and secreting insulin can potentially serve as donors for islet transplantation in the patient deficiency in islet ß cell function both in type 1 or type 2 diabetic patients. Therefore, we developed an easy and higher efficacy approach by trypsinazing the Uc-MSCs and followed culture in differentiation medium to induce of Uc-MSCs differentiation into islet-like clusters, and the potential mechanism that in the early stage of differentiation was also investigated by using RNA-sequencing and bioinformatics. Results show that induction efficacy was reached to 98% and TGF-ß signaling pathway may play critical role in the early stage differentiation, it was further confirmed that the retardant effect of differentiation progress either in cell morphology or in islet specific genes expression can be observed upon blocking the activation of TGF-ß signaling pathway using specific inhibitor of LY2109761 (TßRI/II kinase inhibitor). Our current study, for the first time, development a protocol for differentiation of Uc-MSCs into islet-like clusters, and revealed the importance of TGF-ß signaling pathway in the early stage of differentiation of Uc-MSCs into islet-like clusters. Our study will provide alternative approach for clinical treatment of either type I or type II diabtes mellitus with dysfunctional pancreatic islets.

Drug repositioning based on residual attention network and free multiscale adversarial training.

BACKGROUND: Conducting traditional wet experiments to guide drug development is an expensive, time-consuming and risky process. Analyzing drug function and repositioning plays a key role in identifying new therapeutic potential of approved drugs and discovering therapeutic approaches for untreated diseases. Exploring drug-disease associations has far-reaching implications for identifying disease pathogenesis and treatment. However, reliable detection of drug-disease relationships via traditional methods is costly and slow. Therefore, investigations into computational methods for predicting drug-disease associations are currently needed. RESULTS: This paper presents a novel drug-disease association prediction method, RAFGAE. First, RAFGAE integrates known associations between diseases and drugs into a bipartite network. Second, RAFGAE designs the Re_GAT framework, which includes multilayer graph attention networks (GATs) and two residual networks. The multilayer GATs are utilized for learning the node embeddings, which is achieved by aggregating information from multihop neighbors. The two residual networks are used to alleviate the deep network oversmoothing problem, and an attention mechanism is introduced to combine the node embeddings from different attention layers. Third, two graph autoencoders (GAEs) with collaborative training are constructed to simulate label propagation to predict potential associations. On this basis, free multiscale adversarial training (FMAT) is introduced. FMAT enhances node feature quality through small gradient adversarial perturbation iterations, improving the prediction performance. Finally, tenfold cross-validations on two benchmark datasets show that RAFGAE outperforms current methods. In addition, case studies have confirmed that RAFGAE can detect novel drug-disease associations. CONCLUSIONS: The comprehensive experimental results validate the utility and accuracy of RAFGAE. We believe that this method may serve as an excellent predictor for identifying unobserved disease-drug associations.

Node-adaptive graph Transformer with structural encoding for accurate and robust lncRNA-disease association prediction.

BACKGROUND: Long noncoding RNAs (lncRNAs) are integral to a plethora of critical cellular biological processes, including the regulation of gene expression, cell differentiation, and the development of tumors and cancers. Predicting the relationships between lncRNAs and diseases can contribute to a better understanding of the pathogenic mechanisms of disease and provide strong support for the development of advanced treatment methods. RESULTS: Therefore, we present an innovative Node-Adaptive Graph Transformer model for predicting unknown LncRNA-Disease Associations, named NAGTLDA. First, we utilize the node-adaptive feature smoothing (NAFS) method to learn the local feature information of nodes and encode the structural information of the fusion similarity network of diseases and lncRNAs using Structural Deep Network Embedding (SDNE). Next, the Transformer module is used to capture potential association information between the network nodes. Finally, we employ a Transformer module with two multi-headed attention layers for learning global-level embedding fusion. Network structure coding is added as the structural inductive bias of the network to compensate for the missing message-passing mechanism in Transformer. NAGTLDA achieved an average AUC of 0.9531 and AUPR of 0.9537 significantly higher than state-of-the-art methods in 5-fold cross validation. We perform case studies on 4 diseases; 55 out of 60 associations between lncRNAs and diseases have been validated in the literatures. The results demonstrate the enormous potential of the graph Transformer structure to incorporate graph structural information for uncovering lncRNA-disease unknown correlations. CONCLUSIONS: Our proposed NAGTLDA model can serve as a highly efficient computational method for predicting biological information associations.

CsSHMT3 gene enhances the growth and development in cucumber seedlings under salt stress.

Salt stress is one of the major factors limiting plant growth and productivity. Many studies have shown that serine hydroxymethyltransferase (SHMT) gene play an important role in growth, development and stress response in plants. However, to date, there have been few studies on whether SHMT3 can enhance salt tolerance in plants. Therefore, the effects of overexpression or silencing of CsSHMT3 gene on cucumber seedling growth under salt stress were investigated in this study. The results showed that overexpression of CsSHMT3 gene in cucumber seedlings resulted in a significant increase in chlorophyll content, photosynthetic rate and proline (Pro) content, and antioxidant enzyme activity under salt stress condition; whereas the content of malondialdehyde (MDA), superoxide anion (H2O2), hydrogen peroxide (O2·-) and relative conductivity were significantly decreased when CsSHMT3 gene was overexpressed. However, the content of chlorophyll and Pro, photosynthetic rate, and antioxidant enzyme activity of the silenced CsSHMT3 gene lines under salt stress were significantly reduced, while MDA, H2O2, O2·- content and relative conductivity showed higher level in the silenced CsSHMT3 gene lines. It was further found that the expression of stress-related genes SOD, CAT, SOS1, SOS2, NHX, and HKT was significantly up-regulated by overexpressing CsSHMT3 gene in cucumber seedlings; while stress-related gene expression showed significant decrease in silenced CsSHMT3 gene seedlings under salt stress. This suggests that overexpression of CsSHMT3 gene increased the salt tolerance of cucumber seedlings, while silencing of CsSHMT3 gene decreased the salt tolerance. In conclusion, CsSHMT3 gene might positively regulate salt stress tolerance in cucumber and be involved in regulating antioxidant activity, osmotic adjustment, and photosynthesis under salt stress. KEY MESSAGE: CsSHMT3 gene may positively regulate the expression of osmotic system, photosynthesis, antioxidant system and stress-related genes in cucumber.

Overexpression of COX7A1 Promotes the Resistance of Gastric Cancer to Oxaliplatin and Weakens the Efficacy of Immunotherapy.

Gastric cancer (GC) is one of the most common clinical malignant tumors worldwide, with high morbidity and mortality. Presently, the overall response rate to immunotherapy is low, and current methods for predicting the prognosis of GC are not optimal. Therefore, novel biomarkers with accuracy, efficiency, stability, performance ratio, and wide clinical application are needed. Based on public data sets, the chemotherapy cohort and immunotherapy cohort from Sun Yat-sen University Cancer Center, a series of bioinformatics analyses, such as differential expression analysis, survival analysis, drug sensitivity prediction, enrichment analysis, tumor immune dysfunction and exclusion analysis, single-sample gene set enrichment analysis, stemness index calculation, and immune cell infiltration analysis, were performed for screening and preliminary exploration. Immunohistochemical staining and in vitro experiments were performed for further verification. Overexpression of COX7A1 promoted the resistance of GC cells to Oxaliplatin. COX7A1 may induce immune escape by regulating the number of fibroblasts and their cellular communication with immune cells. In summary, measuring the expression levels of COX7A1 in the clinic may be useful in predicting the prognosis of GC patients, the degree of chemotherapy resistance, and the efficacy of immunotherapy.

Cyanopyridoimidazole/1,2-Aminothiol Click Reaction: A Novel Bioorthogonal Reaction for Synthesis of Radiotracers.

We herein described the design and synthesis of the cyanopyridoimidazoles (CPIs) as new bioorthogonal click reagents toward 1,2-aminothiol groups. Kinetic and density functional theory-based studies of the synthetic compounds revealed that incorporating an electron-withdrawing substituent into the CPI scaffold lowers its lowest unoccupied molecular orbital energy, consequently increasing reactivity. Optimized CPI 8a showed rapid reactivity and high stability in physiological conditions and has been demonstrated to be suitable for various radiotracer synthetic methods. Based on the new bioorthogonal reaction, a [67Ga]Ga-labeled prostate-specific membrane antigen-targeted probe was successfully prepared for in vivo imaging of prostate cancer in an animal model.

Long-term oncological outcomes of robotic versus laparoscopic gastrectomy for gastric cancer: multicentre cohort study.

BACKGROUND: The aim of this multicentre cohort study was to compare the long-term oncological outcomes of robotic gastrectomy (RG) and laparoscopic gastrectomy (LG) for patients with gastric cancer. METHODS: Patients with gastric cancer who underwent radical gastrectomy by robotic or laparoscopic approaches from 1 March 2010 to 31 December 2018 at 10 high-volume centres in China were selected from institutional databases. Patients receiving RG were matched 1 : 1 by propensity score with patients undergoing LG. The primary outcome was 3-year disease-free survival. Secondary outcomes were overall survival and disease recurrence. RESULTS: Some 2055 patients who underwent RG and 4309 patients who had LG were included. The propensity score-matched cohort comprised 2026 RGs and 2026 LGs. Median follow-up was 41 (i.q.r. 39-58) months for the RG group and 39 (38-56) months for the LG group. The 3-year disease-free survival rates were 80.8% in the RG group and 79.5% in the LG group (log rank P = 0.240; HR 0.92, 95% c.i. 0.80 to 1.06; P = 0.242). Three-year OS rates were 83.9 and 81.8% respectively (log rank P = 0.068; HR 0.87, 0.75 to 1.01; P = 0.068) and the cumulative incidence of recurrence over 3 years was 19.3% versus 20.8% (HR 0.95, 0.88 to 1.03; P = 0.219), with no difference between groups. CONCLUSION: RG and LG in patients with gastric cancer are associated with comparable disease-free and overall survival.

Predictors for new-onset conduction block in patients with pure native aortic regurgitation after transcatheter aortic valve replacement with a new-generation self-expanding valve (VitaFlow Liberty™): a retrospective cohort study.

BACKGROUND: New-generation self-expanding valves can improve the success rate of transcatheter aortic valve replacement (TAVR) for severe pure native aortic regurgitation (PNAR). However, predictors of new-onset conduction block post-TAVR using new-generation self-expanding valves in patients with PNAR remain to be established. Therefore, this study aimed to identify predictors of new-onset conduction block post-TAVR using new-generation self-expanding valves (VitaFlow Liberty™) in patients with PNAR. METHODS: In this retrospective cohort study, patients were categorized into pacemaker and non-pacemaker groups based on their need for new postoperative permanent pacemaker implantation (PPI). Based on the postoperative presence of either new-onset complete left bundle branch block (cLBBB) or high-grade atrioventricular block (AVB), patients were further classified into conduction disorder and non-conduction disorder groups. Laboratory, echocardiographic, computed tomography, preoperative and postoperative electrocardiography, and procedural and clinical data were collected immediately after TAVR and during hospitalization and compared between the groups. Multivariate logistic regression analysis was performed incorporating the significant variables from the univariate analyses. RESULTS: This study examined 68 consecutive patients with severe PNAR who underwent TAVR. In 20 patients, a permanent pacemaker was fitted postoperatively. Multivariate logistic regression analysis revealed an association between the need for postoperative PPI and preoperative complete right bundle branch block (cRBBB) or first-degree AVB, as well as a non-tubular left ventricular outflow tract (LVOT). In addition, valve implantation depth and angle of aortic root were independent predictors of new-onset cLBBB or high-grade AVB developing post-TAVR. The predictive value of valve implantation depth and angle of aortic root was further supported by receiver operating characteristic curve analysis results. CONCLUSIONS: In patients with PNAR undergoing TAVR using self-expanding valves, preoperative cRBBB or first-degree AVB and a non-tubular LVOT were indicators of a higher likelihood of PPI requirement. Moreover, deeper valve implantation depth and greater angle of aortic root may be independent risk factors for new-onset cLBBB or high-grade AVB post-TAVR. Valve implantation depth and angle of aortic root values may be used to predict the possibility of new cLBBB or high-grade AVB post-TAVR.

Intramuscular Pulsed Radiofrequency Upregulates BNDF-TrKB Expression in the Spinal Cord in Rats as an Alternative Treatment for Complicated Pain.

Two cases of complicated pain exist: posterior screw fixation and myofascial pain. Intramuscular pulsed radiofrequency (PRF) may be an alternative treatment for such patients. This is a two-stage animal study. In the first stage, two muscle groups and two nerve groups were subdivided into a high-temperature group with PRF at 58 °C and a regular temperature with PRF at 42 °C in rats. In the second stage, two nerve injury groups were subdivided into nerve injury with PRF 42 °C on the sciatic nerve and muscle. Blood and spinal cord samples were collected. In the first stage, the immunohistochemical analysis showed that PRF upregulated brain-derived neurotrophic factor (BDNF) in the spinal cord in both groups of rats. In the second stage, the immunohistochemical analysis showed significant BDNF and tropomyosin receptor kinase B (TrkB) expression within the spinal cord after PRF in muscles and nerves after nerve injury. The blood biomarkers showed a significant increase in BDNF levels. PRF in the muscle in rats could upregulate BDNF-TrkB in the spinal cord, similar to PRF on the sciatica nerve for pain relief in rats. PRF could be considered clinically for patients with complicated pain and this study also demonstrated the role of BDNF in pain modulation. The optimal temperature for PRF was 42 °C.

LDL Receptor-Related Protein 1B Polymorphisms Associated with Increased Risk of Lymph Node Metastasis in Oral Cancer Group with Diabetes Mellitus.

Oral cancer ranks fourth among malignancies among Taiwanese men and is the eighth most common cancer among men worldwide in terms of general diagnosis. The purpose of the current study was to investigate how low-density lipoprotein receptor-related protein 1B (LDL receptor related protein 1B; LRP1B) gene polymorphisms affect oral squamous cell carcinoma (OSCC) risk and progression in individuals with diabetes mellitus (DM). Three LRP1B single-nucleotide polymorphisms (SNPs), including rs10496915, rs431809, and rs6742944, were evaluated in 311 OSCC cases and 300 controls. Between the case and control groups, we found no evidence of a significant correlation between the risk of OSCC and any of the three specific SNPs. Nevertheless, in evaluating the clinicopathological criteria, individuals with DM who possess a minimum of one minor allele of rs10496915 (AC + CC; p = 0.046) were significantly associated with tumor size compared with those with homozygous major alleles (AA). Similarly, compared to genotypes homologous for the main allele (GG), rs6742944 genotypes (GA + AA; p = 0.010) were more likely to develop lymph node metastases. The tongue and the rs6742944 genotypes (GA + AA) exhibited higher rates of advanced clinical stages (p = 0.024) and lymph node metastases (p = 0.007) when compared to homozygous alleles (GG). LRP1B genetic polymorphisms appear to be prognostic and diagnostic markers for OSCC and DM, as well as contributing to genetic profiling research for personalized medicine.

The change of state-trait anxiety among patients undergoing orthognathic surgery: A longitudinal study.

INTRODUCTION: This study aimed to assess state-trait anxiety level changes in Chinese patients with dentofacial discrepancies before and after orthognathic surgery and to explore the feasibility of developing a reference index for the preoperative screening of postoperative patients with high anxiety. METHODS: A total of 96 Chinese patients with dentofacial discrepancies who underwent orthognathic surgery were included in this study. Data were collected before orthognathic surgery and at 2 weeks (T2), 3 months, and 6 months (T4) after surgery using the State-Trait Anxiety Inventory. Receiver operating characteristic and linear regression analyses were performed to screen for preoperative indicators of postoperative high-state anxiety. RESULTS: State-trait anxiety levels in patients with dentofacial discrepancies decreased after surgery (F = 18.95, P <0.01; F = 6.90, P <0.01). Trait Anxiety Inventory can be used to screen patients with high-state anxiety from T2 to T4 (area under cover 95% confidence interval: T2, 0.74 [0.62-0.86]; 3 months, 0.79 [0.69-0.90]; T4, 0.77 [0.66-0.87], P <0.01), corresponding to cutoff values of 48.5, 46.5, and 45.5, respectively. CONCLUSIONS: All participants' state-trait anxiety levels improved after surgery compared with their preoperative levels. Preoperative trait anxiety levels can be used as a reference indicator to screen patients who may have high-state anxiety levels after orthognathic surgery. The creation of a screening scale will assist health care professionals to more pertinently help patients with high anxiety.

MNCLCDA: predicting circRNA-drug sensitivity associations by using mixed neighbourhood information and contrastive learning.

BACKGROUND: circRNAs play an important role in drug resistance and cancer development. Recently, many studies have shown that the expressions of circRNAs in human cells can affect the sensitivity of cells to therapeutic drugs, thus significantly influencing the therapeutic effects of these drugs. Traditional biomedical experiments required to verify this sensitivity relationship are not only time-consuming but also expensive. Hence, the development of an efficient computational approach that can accurately predict the novel associations between drug sensitivities and circRNAs is a crucial and pressing need. METHODS: In this research, we present a novel computational framework called MNCLCDA, which aims to predict the potential associations between drug sensitivities and circRNAs to assist with medical research. First, MNCLCDA quantifies the similarity between the given drug and circRNA using drug structure information, circRNA gene sequence information, and GIP kernel information. Due to the existence of noise in similarity information, we employ a preprocessing approach based on random walk with restart for similarity networks to efficiently capture the useful features of circRNAs and drugs. Second, we use a mixed neighbourhood graph convolutional network to obtain the neighbourhood information of nodes. Then, a graph-based contrastive learning method is used to enhance the robustness of the model, and finally, a double Laplace-regularized least-squares method is used to predict potential circRNA-drug associations through the kernel matrices in the circRNA and drug spaces. RESULTS: Numerous experimental results show that MNCLCDA outperforms six other advanced methods. In addition, the excellent performance of our proposed model in case studies illustrates that MNCLCDA also has the ability to predict the associations between drug sensitivity and circRNA in practical situations. CONCLUSIONS: After a large number of experiments, it is illustrated that MNCLCDA is an efficient tool for predicting the potential associations between drug sensitivities and circRNAs, thereby can provide some guidance for clinical trials.

Evaluation of Chelator-to-Antibody Ratio on Development of 89Zr-iPET Tracer for Imaging of PD-L1 Expression on Tumor.

89Zr-iPET has been widely used for preclinical and clinical immunotherapy studies to predict patient stratification or evaluate therapeutic efficacy. In this study, we prepared and evaluated 89Zr-DFO-anti-PD-L1-mAb tracers with varying chelator-to-antibody ratios (CARs), including 89Zr-DFO-anti-PD-L1-mAb_3X (tracer_3X), 89Zr-DFO-anti-PD-L1-mAb_10X (tracer_10X), and 89Zr-DFO-anti-PD-L1-mAb_20X (tracer_20X). The DFO-anti-PD-L1-mAb conjugates with varying CARs were prepared using a random conjugation method and then subjected to quality control. The conjugates were radiolabeled with 89Zr and evaluated in a PD-L1-expressing CT26 tumor-bearing mouse model. Next, iPET imaging, biodistribution, pharmacokinetics, and ex vivo pathological and immunohistochemical examinations were conducted. LC-MS analysis revealed that DFO-anti-PD-L1-mAb conjugates were prepared with CARs ranging from 0.4 to 2.0. Radiochemical purity for all tracer groups was >99% after purification. The specific activity levels of tracer_3X, tracer_10X, and tracer_20X were 2.2 ± 0.6, 8.2 ± 0.6, and 10.5 ± 1.6 µCi/µg, respectively. 89Zr-iPET imaging showed evident tumor uptake in all tracer groups and reached the maximum uptake value at 24 h postinjection (p.i.). Biodistribution data at 168 h p.i. revealed that the tumor-to-liver, tumor-to-muscle, and tumor-to-blood uptake ratios for tracer_3X, tracer_10X, and tracer_20X were 0.46 ± 0.14, 0.58 ± 0.33, and 1.54 ± 0.51; 4.7 ± 1.3, 7.1 ± 3.9, and 14.7 ± 1.1; and 13.1 ± 5.8, 19.4 ± 13.8, and 41.3 ± 10.6, respectively. Significant differences were observed between tracer_3X and tracer_20X in the aforementioned uptake ratios at 168 h p.i. The mean residence time and elimination half-life for tracer_3X, tracer_10X, and tracer_20X were 25.4 ± 4.9, 24.2 ± 6.1, and 25.8 ± 3.3 h and 11.8 ± 0.5, 11.1 ± 0.7, and 11.7 ± 0.6 h, respectively. No statistical differences were found between-tracer in the aforementioned pharmacokinetic parameters. In conclusion, 89Zr-DFO-anti-PD-L1-mAb tracers with a CAR of 1.4-2.0 may be better at imaging PD-L1 expression in tumors than are traditional low-CAR 89Zr-iPET tracers.

Identifying virulence factors using graph transformer autoencoder with ESMFold-predicted structures.

With the increasing resistance of bacterial pathogens to conventional antibiotics, antivirulence strategies targeting virulence factors (VFs) have become an effective new therapy for the treatment of pathogenic bacterial infections. Therefore, the identification and prediction of VFs can provide ideal candidate targets for the implementation of antivirulence strategies in treating infections caused by pathogenic bacteria. Currently, the existing computational models predominantly rely on the amino acid sequences of virulence proteins while overlooking structural information. Here, we propose a novel graph transformer autoencoder for VF identification (GTAE-VF), which utilizes ESMFold-predicted 3D structures and converts the VF identification problem into a graph-level prediction task. In an encoder-decoder framework, GTAE-VF adaptively learns both local and global information by integrating a graph convolutional network and a transformer to implement all-pair message passing, which can better capture long-range correlations and potential relationships. Extensive experiments on an independent test dataset demonstrate that GTAE-VF achieves reliable and robust prediction accuracy with an AUC of 0.963, which is consistently better than that of other structure-based and sequence-based approaches. We believe that GTAE-VF has the potential to emerge as a valuable tool for assessing VFs and devising antivirulence strategies.

Comparative efficacy of different types of exercise modalities on psychiatric symptomatology in patients with schizophrenia: a systematic review with network meta-analysis.

This network meta-analysis investigated the effects of 8 types of physical exercises on treating positive symptoms, negative symptoms, general psychopathology, and the Positive And Negative Syndrome Scale (PANSS) total score in patients with schizophrenia. The methods adhered to PRISMA guidelines and used the Cochrane risk of bias tool for quality assessment, and Stata software for data analysis. Data were sourced from PubMed, Embase, Web of Science, and the Cochrane database up to August 15, 2023, following PICOS principles. A total of 25 studies including 1441 participants were analyzed. Results showed that resistance exercise seems to be effective for improving positive symptoms, while Yoga was more effective for negative symptoms. Low-intensity aerobic exercise was optimal for general psychopathology, and Yoga was effective in improving the PANSS total score. The study concluded that yoga and aerobic exercise demonstrated superior performance, but the impact of exercise on patients with schizophrenia is also influenced by individual factors and intervention dosages. Therefore, a pre-assessment of patients considering factors such as interests, hobbies, and physical capabilities is crucial for selecting appropriate exercise modalities.

A Spherical Cap Model of Epidural Hematomas.

Background Epidural hematomas (EDHs), which have a characteristic biconvex shape, are a type of post-traumatic intracranial mass. EDHs and other types of intracranial hematomas are often diagnosed with computed tomography (CT). The volumes of EDHs are important in treatment decisions and prognosis. Their volumes are usually estimated on CT using the "ABC" method, which is based on the ellipsoid shape rather than their biconvex shape. Objective To simulate the biconvex shape, we modeled the geometry of EDHs with two spherical caps. We aim to provide simpler estimation of EDH volumes in clinical settings, and eventually recommend a threshold for surgical evacuation. Methods Applying the relationship between the sphere radius, spherical cap height, and base circle radius, we derived formulas for the shape of an EDH, relating its largest diameter and location to the other two diameters. We also estimated EDH volumes using the spherical cap volume and conventional ABC formulas and then constructed a lookup table accordingly. Results Validation of the model was performed using 14 CT image sets from previously reported patients with EDHs. Our geometric model demonstrated accurate predictions. The model also allows reducing the number of parameters to be measured in the ABC method from three to one, the hematoma length, showcasing its potential as a reliable tool for clinical decision-making. Based on our model, an EDH longer than 7 cm would occupy more than 30 mL of the intracranial volume. Conclusion The proposed model offers a streamlined approach to estimating EDH volumes, reducing the complexity of parameters required for clinical assessments. We recommend a length of 7 cm as a threshold for surgical evacuation of EDHs. This acceleration in decision-making is crucial for managing critically injured patients with traumatic brain injuries. Further validation across diverse patient populations will enhance the generalizability and utility of this geometric modeling approach in clinical settings.

Anti-cancer mechanisms of natural isoflavones against melanoma.

The incidence of skin-related neoplasms has generally increased in recent years. Melanoma arises from malignant mutations in melanocytes in the basal layer of the epidermis and is a fatal skin cancer that seriously threatens human health. Isoflavones are polyphenolic compounds widely present in legumes and have drawn scientists' attention, because they have good efficacy against a variety of cancers, including melanoma, without significant toxic side effects and resistance. In this review article, we summarize the research progress of isoflavones in melanoma, including anti-melanoma roles and mechanisms of isoflavones via inhibition of tyrosinase activity, melanogenesis, melanoma cell growth, invasion of melanoma cells, and induction of apoptosis in melanoma cells. This information is important for the prevention, clinical treatment, and prognosis and survival of melanoma.

Acetylcholinesterase inhibitory phloroglucinols from tropic Rhodomyrtus tomentosa.

Four previously undescribed phloroglucinols, including three pairs of enantiomers, (±)-rhodotomentodimer F, (±)-rhodotomentodimer G, and (±)-rhodotomentomonomer E, and one phloroglucinol-sesquiterpene meroterpenoid, rhodotomentodione E, together with one previously reported congener, (±)-rhodomyrtosone A, were obtained from the leaves of Rhodomyrtus tomentosa. The structures including absolute configurations of previously undescribed isolates were elucidated by extensive spectroscopic analysis (HRESIMS and NMR), ECD calculations, and single-crystal X-ray diffraction. (±)-Rhodotomentodimer F is a rare phloroglucinol dimer conjugated by a ß-triketone moiety and an unprecedented resorcinol unit via the formation of a rare bis-furan ring system, whereas (±)-rhodotomentomonomer E share a rearranged pentacyclic scaffold. Pharmacologically, (±)-rhodotomentomonomer E showed the strongest human acetylcholinesterase (hAChE) inhibitory effect with an IC50 value of 1.04 ± 0.05 µM. Molecular formula studies revealed that hydrogen bonds formed between hAChE residues Glu202, Ser203, Ala204, Gly121, Gly122, Tyr337, and His447 and (±)-rhodotomentomonomer E played crucial roles in its observed activity. These findings indicated that the leaves of Rhodomyrtus tomentosa can supply a rich source of hAChE inhibitors. These inhibitors might potentially be utilized in the therapeutic strategy for Alzheimer's disease, offering promising candidates for further research and development.

Doping with KBr to Achieve High-Performance CsPbBr3 Semitransparent Perovskite Solar Cells.

Wide-bandgap semitransparent perovskite photovoltaics are emerging as one of the ideal candidates for building-integrated photovoltaics (BIPV). However, surface defects in inorganic CsPbBr3 perovskite prepared by vapor deposition severely limit the optoelectronic performance of perovskite solar cells. To address this issue, a strategy of doping a trace amount of KBr into perovskite by vapor deposition is adopted, effectively improving the quality of the film, reducing surface defect concentration, and enhancing the transportation and extraction of charge carriers. Simultaneously, fully physical vapor deposition technology is employed to fabricate perovskite solar cells with an average visible light transmittance of 44%. These devices exhibited an ultrahigh open-circuit voltage of 1.55 V and a superior power conversion efficiency (PCE) of 7.28%, demonstrating excellent moisture and heat resistance. Moreover, the corresponding 5 cm × 5 cm modules achieve a PCE of 5.35% with great thermal insulation capability. This work provides an approach for fabricating highly efficient all-inorganic perovskite solar cells with high average visible light transmittance, demonstrating new insights into their application in building-integrated photovoltaics.

Antitumor effects of Cypaliuruside F from Cyclocarya paliurus on HepG2 cells.

An undescribed dammarane triterpenoid saponin Cypaliuruside F was isolated from the leaves of Cyclocarya paliurus in our preliminary study. The MTT assay, flow cytometry, cell scratch, and DAPI staining were used to detect the antitumor effects of Cypaliuruside F on HepG2 cells. Subsequently, network pharmacology and molecular docking analysis were used to analyse the key targets of Cypaliuruside F against HCC. In addition, a Western blot was performed to determine the effects of Cypaliuruside F on the expression of key proteins in HepG2 cells. The experimental results indicated that the damarane triterpenoid saponin Cypaliuruside F from Cyclocarya paliurus inhibits the proliferation of HepG2 cells by inducing apoptosis and cell cycle arrest. These changes may promote the apoptosis of HepG2 cells by inhibiting the expression of mTOR, STAT3, and Bcl-2 while activating Bax.