Analysis of Key Genes Related to Systemic Lupus Erythematosus and COVID-19.

BACKGROUND: Systemic Lupus Erythematosus (SLE) is a multifactorial and complex immune disease; however, the relevance of COVID-19 infection in SLE patients remains uncertain. AIM: This study aims to explore the key candidate genes and pathways in patients with SLE. It also seeks to employ bioinformatics analysis to unravel the molecular signatures inherent in both SLE and COVID-19 patients. The ultimate aim is to identify potential targets and markers specifically relevant to SLE patients who contract SARS-CoV-2. METHODS: Datasets (GSE12374, GSE20864, GSE61635, GSE81622, and GSE144390) from the Gene Expression Omnibus (GEO) database were analyzed using Robust Rank Aggregation (RRA) method to identify differential expression genes (DEGs) in SLE patients compared to healthy individuals. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, tissue-specific gene analysis, and Protein-protein interaction (PPI) network were performed. Finally, the Venn diagram was employed to identify the intersections of COVID-19 genes, serving as potential targets for SLE patients with COVID-19 infection. RESULTS: A total of 154 DEGs were discovered, with GO enrichment indicating a predominant involvement in the defense response against the virus (P<0.001). KEGG pathway analysis showed enrichment in the NOD-like receptor signaling pathway and coronavirus disease, specifically COVID-19 (P<0.001). Tissue-specific genes related to the hematological and immune systems were emphasized (74%). The PPI network highlighted 22 genes, and 5 key genes, namely, IFIT1, IFIT3, MX1, MX2, and OAS3, which were identified after intersecting with COVID-19 patients' data. CONCLUSION: IFIT1, IFIT3, MX1, MX2, and OAS3 exhibiting differential expression, as well as the pathways associated with COVID-19, could potentially function as biomarkers and therapeutic targets for individuals with SLE infected with COVID-19.

Biochar with enhanced performance prepared based on "graphite-structure regulation" conjecture designed to effectively control water pollution.

In this work, corn straw was used as raw material, Hummers method and activation were used to adjust the graphite structure in biochar, and preparing straw based biochar (H-BCS) with ultra-high specific surface area (3441.80 m2/g), highly total pore volume (1.9859 cm3/g), and further enhanced physicochemical properties. Compared with untreated straw biochar (BCS), the specific surface area and total pore volume of H-BCS were increased by 47.24 % and 55.85 %, respectively. H-BCS showed good removal ability in subsequent experiments by using chloramphenicol (CP), hexavalent chromium (Cr6+), and crystal violet (CV) as adsorption models. In addition, the adsorption capacities of H-BCS (CP: 1396.30 mg/g, Cr6+: 218.40 mg/g, and CV: 1246.24 mg/g) are not only higher than most adsorbents, even after undergoing 5 cycles of regeneration, its adsorption capacity remains above 80 %, indicating significant potential for practical applications. In addition, we also speculated and analyzed the conjecture about the "graphite-structure regulation" during the preparation process, and finally discussed the possible mechanism during the adsorption processes. We hope this work could provide a new strategy to solve the restriction of biochar performance by further exploring the regulation of graphite structure in carbon materials.

DGPRI, a new liver fibrosis assessment index, predicts recurrence of AFP-negative hepatocellular carcinoma after hepatic resection: a single-center retrospective study.

Although patients with alpha-fetoprotein-negative hepatocellular carcinoma (AFPNHCC) have a favorable prognosis, a high risk of postoperative recurrence remains. We developed and validated a novel liver fibrosis assessment index, the direct bilirubin-gamma-glutamyl transpeptidase-to-platelet ratio (DGPRI). DGPRI was calculated for each of the 378 patients with AFPNHCC who underwent hepatic resection. The patients were divided into high- and low-score groups using the optimal cutoff value. The Lasso-Cox method was used to identify the characteristics of postoperative recurrence, followed by multivariate Cox regression analysis to determine the independent risk factors associated with recurrence. A nomogram model incorporating the DGPRI was developed and validated. High DGPRI was identified as an independent risk factor (hazard ratio = 2.086) for postoperative recurrence in patients with AFPNHCC. DGPRI exhibited better predictive ability for recurrence 1-5 years after surgery than direct bilirubin and the gamma-glutamyl transpeptidase-to-platelet ratio. The DGPRI-nomogram model demonstrated good predictive ability, with a C-index of 0.674 (95% CI 0.621-0.727). The calibration curves and clinical decision analysis demonstrated its clinical utility. The DGPRI nomogram model performed better than the TNM and BCLC staging systems for predicting recurrence-free survival. DGPRI is a novel and effective predictor of postoperative recurrence in patients with AFPNHCC and provides a superior assessment of preoperative liver fibrosis.

Human Umbilical Cord Mesenchymal Stem Cells Derived Exosomes Improved The Aged Mouse IVM Oocytes Quality.

During assisted reproductive technology (ART) treatment, the aged women, especially those over 35 years old, have fewer mature oocytes and poorer quality of the oocytes comparing with the young women. In vitro maturation (IVM) technology facilitates the usage of immature oocytes, which is clinically important for the aged women. However, the maturation rate is low for the oocytes from the aged women. Human umbilical cord mesenchymal stem cells derived exosomes (HUCMSCs-exosomes), as important mediators of intercellular communication, have been widely used to restore ovarian function and improve female fertility. In this study, we isolated HUCMSCs-exosomes and collected the immature germinal vesicle oocytes from the naturally aged mouse model. And we added these HUCMSCs-exosomes to the conventional IVM culture system. The effects of HUCMSCs-exosomes on IVM oocytes were observed and analyzed from multiple aspects including maturation rate, spindle morphology, mitochondria function, and development potential. We found the quality of oocytes was improved by HUCMSCs-exosomes. Based on the results, we propose that HUCMSCs-exosomes may provide a novel and cell free strategy in the improvement of the IVM in elderly infertile women in the future.

BMS-794833 reduces anlotinib resistance in osteosarcoma by targeting the VEGFR/Ras/CDK2 pathway.

Background: Osteosarcoma, a tumor that originates from bone cells, has a poor prognosis and a high degree of malignancy. Anlotinib, a small-molecule multi-target tyrosine kinase inhibitor (TKI), is the first-line drug in treating osteosarcoma, especially in late-stage osteosarcoma. However, patients often develop resistance after using anlotinib for a certain period, which poses a challenge to its further clinical application. Recently, several TKIs, for instance regorafenib and cabozantinib, have showed clinical interest in treating osteosarcoma and target both vascular endothelial growth factor receptor (VEGFR) and mesenchymal epithelial transition factor (c-MET). Therefore, the identification of new TKI warrants further investigation. Methods: We performed CCK8 aasays to confirm that BMS-794833 sensitization osteosarcoma cells to anlotinib. Bioinformatics analysis and rescue experiments showed that the reduce of resistance were dependent on the VEGFR/Ras/CDK2 pathway. Cell line based xenograft model were used to demonstrate that BMS-794833 and anlotinib could synergistically treat OS. Results: Here, we found that BMS-794833 reduced anlotinib resistance in osteosarcoma by targeting the VEGFR/Ras/CDK2 pathway. CCK8 assay showed that BMS-794833 significantly improved the resistance of osteosarcoma cells to anlotinib. The results of rescue experiments showed that the regulatory effects of BMS-794833 on the proliferation and drug resistance of osteosarcoma cells were dependent on the VEGFR/Ras/CDK2 pathway. In addition, BMS-794833 affected the resistance of osteosarcoma cells to anlotinib through epithelial-mesenchymal transition (EMT) and apoptosis pathways. More importantly, BMS-794833 and anlotinib exerted synergistic therapeutic effects against osteosarcoma in vivo. Conclusion: Altogether, this study reveals a new (VEGFR)-targeting drug that can be combined with anlotinib for the treatment of osteosarcoma, which provides an important theoretical basis for overcoming anlotinib resistance.

Construction and Validation of a Novel Nomogram Predicting Recurrence in Alpha-Fetoprotein-Negative Hepatocellular Carcinoma Post-Surgery Using an Innovative Liver Function-Nutrition-Inflammation-Immune (LFNII) Score: A Bicentric Investigation.

Purpose: We developed a nomogram based on the liver function, nutrition, inflammation, and immunity (LFNII) score to predict recurrence-free survival (RFS) post-resection in patients with hepatocellular carcinoma (HCC) exhibiting alpha-fetoprotein (AFP) negativity (AFP ≤20 ng/mL). Patients and Methods: Clinical data of 661 patients diagnosed with alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) who underwent surgical resection at two medical centers between 2012 and 2021 were collected. A total of 462 and 199 patients served as the training and validation sets, respectively. Pre-operative blood markers were collected and analyzed for LFNII. The LFNII score was formulated using the least absolute shrinkage and selection operator Cox regression model. A nomogram model was developed using the training set to incorporate other relevant clinicopathological indicators and predict postoperative recurrence. Model discrimination was assessed using the receiver operating characteristic curve, calibration was evaluated using a calibration curve, and clinical applicability was assessed using clinical decision curve analysis. A comparison with liver cancer staging was performed using the nomogram model. Finally, a cohort study was conducted to validate our findings. Results: We derived the LFNII scores from nine indicators. Elevated LFNII scores correlated with unfavorable clinicopathological features. The LFNII score area under the curve revealed superior predictive efficacy at 1-, 2-, and 5-year RFS intervals, with values of 0.675, 0.658, and 0.633, respectively. Multivariate Cox analysis revealed that a high LFNII score independently increased RFS risk in patients with AFP-NHCC. The C-index of the LFNII-nomogram model was 0.686 (95% confidence interval [CI], 0.651-0.721). The nomogram model's clinical application value surpassed that of standard HCC staging systems. Conclusion: The LFNII score-derived nomogram effectively predicted the RFS of patients with AFP-NHCC after curative resection.

Elderly users' perceptions of signage systems from tertiary hospitals in Guangzhou.

Wayfinding in hospitals today is a significant challenge for urban residents, especially for the elderly. This study investigated the perceptions and attitudes of the elderly toward existing hospital signage systems to identify the wayfinding needs in the healthcare environment. This study collected 762 elderly participants' perceptions and personal preferences regarding 12 features of the existing signage systems in three hospitals in the Yuexiu, Haizhu, and Liwan districts of Guangzhou using a questionnaire methodology. The study further explored the differences in perceptions and preferences for signage based on the gender, age, and educational level of the elderly participants. The findings indicate that most of the elderly participants experienced becoming lost in the hospital; they typically chose to ask others for directions first, followed by using the signage system. Most of the elderly participants had positive attitudes toward the current hospital signage system. Furthermore, they emphasized the importance of the signage system's graphics, texts, colors, and updates, which directly affects the readability and comprehensibility of signs. We found gender differences in perceptions and attitudes toward signage; male participants had more positive attitudes toward the hospital signage systems than female participants. Additionally, consistent with previous findings, the older the age of participants, the less comprehension they had regarding signage graphic symbols. We also found that the more educated elderly participants were, the more understanding of signage they had. At the same time, however, they were less satisfied, which is possibly because the more educated they were, the more aware they were of signage issues.

Lattice oxygen activation of MnO2 by CeO2 for the improved degradation of bisphenol A in the peroxymonosulfate-based oxidation.

The structure of MnO2 was modified by constructing the composites CeO2/ MnO2 via a facile hydrothermal method. The catalytic performance of optimal composite (Mn-Ce10) in peroxymonosulfate (PMS) activation for the degradation of bisphenol A (BPA) is approximately three times higher than that of MnO2 alone. The average valence of manganese in CeO2/MnO2 is lowered compared to MnO2, which induces the generation of more free radicals, such as OH and SO4•-. In addition, the composite exhibits a higher concentration of oxygen vacancies than MnO2, facilitating bondingwith PMS to produce more singlet oxygen (1O2). Moreover, the incorporation of CeO2 activates the lattice oxygen of MnO2, improving its oxidative ability. Consequently, approximately 48% of BPA decomposition in 10min is attributed to direct oxidation in the Mn-Ce10/PMS system, whereas only 36% occurs in 30min for the MnO2/PMS system. Simulation results confirm weakened Mn-O covalency and elongated Mn-O bonds due to the activation of lattice oxygen in CeO2/MnO2, demonstrating that PMS tends to be adsorbed on the composite rather than on MnO2. This work establishes a relationship between lattice oxygen and the degradation pathway, offering a novel approach for the targeted regulation of catalytic oxidation.

Dynamic foraging strategy adaptation to heterogeneous environments contributes to social aggregation in snub-nosed monkeys.

The dynamics of animal social structures are heavily influenced by environmental patterns of competition and cooperation. In folivorous colobine primates, prevailing theories suggest that larger group sizes should be favored in rainforests with a year-round abundance of food, thereby reducing feeding competition. Yet, paradoxically, larger groups are frequently found in high-altitude or high-latitude montane ecosystems characterized by a seasonal scarcity of leaves. This contradiction is posited to arise from cooperative benefits in heterogeneous environments. To investigate this hypothesis, we carried out a six-year field study on two neighboring groups of golden snub-nosed monkey ( Rhinopithecus roxellana), a species representing the northernmost distribution of colobine primates. Results showed that the groups adjusted their movement and habitat selection in response to fluctuating climates and spatiotemporal variability of resources, indicative of a dynamic foraging strategy. Notably, during the cold, resource-scarce conditions in winter, the large group occupied food-rich habitats but did not exhibit significantly longer daily travel distances than the smaller neighboring group. Subsequently, we compiled an eco-behavioral dataset of 52 colobine species to explore their evolutionary trajectories. Analysis of this dataset suggested that the increase in group size may have evolved via home range expansion in response to the cold and heterogeneous climates found at higher altitudes or latitudes. Hence, we developed a multi-benefits framework to interpret the formation of larger groups by integrating environmental heterogeneity. In cold and diverse environments, even smaller groups require larger home ranges to meet their dynamic survival needs. The spatiotemporal distribution of high-quality resources within these expanded home ranges facilitates more frequent interactions between groups, thereby encouraging social aggregation into larger groups. This process enhances the benefits of collaborative actions and reproductive opportunities, while simultaneously optimizing travel costs through a dynamic foraging strategy.

Evaluation of the Current State of Chatbots for Digital Health: Scoping Review.

BACKGROUND: Chatbots have become ubiquitous in our daily lives, enabling natural language conversations with users through various modes of communication. Chatbots have the potential to play a significant role in promoting health and well-being. As the number of studies and available products related to chatbots continues to rise, there is a critical need to assess product features to enhance the design of chatbots that effectively promote health and behavioral change. OBJECTIVE: This scoping review aims to provide a comprehensive assessment of the current state of health-related chatbots, including the chatbots' characteristics and features, user backgrounds, communication models, relational building capacity, personalization, interaction, responses to suicidal thoughts, and users' in-app experiences during chatbot use. Through this analysis, we seek to identify gaps in the current research, guide future directions, and enhance the design of health-focused chatbots. METHODS: Following the scoping review methodology by Arksey and O'Malley and guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist, this study used a two-pronged approach to identify relevant chatbots: (1) searching the iOS and Android App Stores and (2) reviewing scientific literature through a search strategy designed by a librarian. Overall, 36 chatbots were selected based on predefined criteria from both sources. These chatbots were systematically evaluated using a comprehensive framework developed for this study, including chatbot characteristics, user backgrounds, building relational capacity, personalization, interaction models, responses to critical situations, and user experiences. Ten coauthors were responsible for downloading and testing the chatbots, coding their features, and evaluating their performance in simulated conversations. The testing of all chatbot apps was limited to their free-to-use features. RESULTS: This review provides an overview of the diversity of health-related chatbots, encompassing categories such as mental health support, physical activity promotion, and behavior change interventions. Chatbots use text, animations, speech, images, and emojis for communication. The findings highlight variations in conversational capabilities, including empathy, humor, and personalization. Notably, concerns regarding safety, particularly in addressing suicidal thoughts, were evident. Approximately 44% (16/36) of the chatbots effectively addressed suicidal thoughts. User experiences and behavioral outcomes demonstrated the potential of chatbots in health interventions, but evidence remains limited. CONCLUSIONS: This scoping review underscores the significance of chatbots in health-related applications and offers insights into their features, functionalities, and user experiences. This study contributes to advancing the understanding of chatbots' role in digital health interventions, thus paving the way for more effective and user-centric health promotion strategies. This study informs future research directions, emphasizing the need for rigorous randomized control trials, standardized evaluation metrics, and user-centered design to unlock the full potential of chatbots in enhancing health and well-being. Future research should focus on addressing limitations, exploring real-world user experiences, and implementing robust data security and privacy measures.

The spatial pattern of Scirpus mariqueter expansion and the associated mechanism of self-organization using unmanned aerial vehicles and its significance for coastal wetland restoration.

Understanding the spatial expansion process of salt marshes and quantifying the factors driving this expansion are crucial for the management and restoration of coastal wetlands. In this study, we aimed to illustrate the expansion process of Scirpus mariqueter using drone remote sensing and quantify its relationship with habitat quality. Our hypothesis was that landscape metrics could serve as valuable indicators for prioritizing habitat restoration efforts along the coast. We utilized drone remote sensing and adopted the simple Greenness Index to reflect the growth status of S. mariqueter. Using this index, we computed the standard deviation ellipse and growth center. To evaluate habitat quality, we developed a method based on our previous research and other relevant reports. We then conducted a quantitative analysis of the expansion process of S. mariqueter in areas with varying habitat quality. We found that S. mariqueter's optimal elevation was 3.7 m, with a range of 2.5 to 4.3 m. The threshold value for soil total nitrogen was 0.3 g/kg, and the tolerance threshold for soil salinity was 2500 ppm. These three factors, elevation, soil total nitrogen, and soil salinity, collectively influenced habitat quality, with weights of 0.68, 0.23, and 0.09, respectively, as determined through geodetector analysis. During the summer, we observed a dominance of dispersal in S. mariqueter, with the species primarily spreading to areas with increased habitat quality. Patch shapes tended to be compact and regular in this season. In contrast, during the autumn, a dominance of decline was observed, with S. mariqueter mainly distributing to areas exhibiting decreased habitat quality. Patch shapes tended to be complex and irregular in the autumn season. Eventually micro-geomorphic modification and patch shape filling methods based on UAV observations are proposed to aid wetland restoration. These findings are of utmost importance for the restoration of coastal wetlands and the enhancement of ecosystem resilience.

Can AI-generated art stimulate the sustainability of intangible cultural heritage? A quantitative research on cultural and creative products of New Year Prints generated by AI.

The transformation of social development modes has led to profound changes in the pattern of intangible cultural heritage, while simultaneously posing significant challenges to its preservation. The rapid development of artificial intelligence (AI) technology has brought new development opportunities in various research fields. This study intends, by constructing and evaluating a theoretical model, to investigate whether AI-generated cultural and creative products can promote the sustainability of intangible cultural heritage. The central focus of this research is to measure the effectiveness of AI technologies in promoting the sustainability of intangible cultural heritage. The context of the research design is rooted in the attention, interest, search, action, and share (AISAS) model, incorporating theories of perceived value and cultural identity, to forecast the long-term viability of AI-generated cultural and creative products in the promotion of intangible cultural heritage. This research was conducted in Tianjin, China and carried out using quantitative methods, a questionnaire survey, and the accidental sampling method, taking a sample of 291 participants for analysis. The results show that 1) the attraction of and interest and participation in AI-generated Yangliuqing New Year Print cultural and creative products have a positive effect on perceived value; 2) the purchase and sharing of these products have a positive impact on cultural identity; 3) the perceived value has a positive impact on cultural identity; and 4) cultural identity has a positive impact on the sustainability of intangible cultural heritage. This study contributes to the theoretical development and practical application of the AISAS model and offers valuable insights into the future development trajectory of intangible cultural heritage, thereby promoting its sustainability. The limitations of this study are its small sample size and geographical restrictions. In future studies, the sample size will be expanded and will include more regions for data analysis.

AP003352.1/miR-141-3p axis enhances the proliferation of osteosarcoma by LPAR3.

Osteosarcoma (OS) is a highly malignant tumor with a poor prognosis and a growing incidence. LncRNAs and microRNAs control the occurrence and development process of osteosarcoma through ceRNA patterns. The LPAR3 gene is important in cancer cell proliferation, apoptosis and disease development. However, the regulatory mechanism of the ceRNA network through which LPAR3 participates in osteosarcoma has not been clarified. Herein, our study demonstrated that the AP003352.1/miR-141-3p axis drives LPAR3 expression to induce the malignant progression of osteosarcoma. First, the expression of LPAR3 is regulated by the changes in AP003352.1 and miR-141-3p. Similar to the ceRNA of miR-141-3p, AP003352.1 regulates the expression of LPAR3 through this mechanism. In addition, the regulation of AP003352.1 in malignant osteosarcoma progression depends to a certain degree on miR-141-3p. Importantly, the AP003352.1/miR-141-3p/LPAR3 axis can better serve as a multi-gene diagnostic marker for osteosarcoma. In conclusion, our research reveals a new ceRNA regulatory network, which provides a novel potential target for the diagnosis and treatment of osteosarcoma.

Efficient dynamic tunable metasurface based on Ge2Sb2Te5 in the near infrared band.

For effective wavefront management in the optical infrared range, dynamic all-dielectric metasurfaces, always based on phase transition materials, particularly G e 2 S b 2 T e 5 (GST), can be used. In this paper, we propose a GST-based tunable metasurface by structuring the phase-change material GST. We confirm that the nanopillar we designed has high transmittance in the wavelength band around 1550 nm and can fully cover the 0∼2π phase. Based on these characteristics, we can achieve beam steering and a focusing effect in amorphous phase by elaborately arranging GST nanopillars, while the aforementioned optical phenomena disappear in crystalline phase. Additionally, by arranging the array of vortex phases, we also realize switching the perfect composite vortex beam (PCVB) when changing the crystal state of GST, and simulate the generation of PCVB with different topological charges and sizes in amorphous phase. We believe that our research results can serve as a reference for multifunctional optical surfaces, dynamic optical control, optical communication, and information processing.

Controllable adhesion behavior in underwater environments.

Microstructure adhesive pads can effectively manipulate objects in underwater environments. Current adhesive pads can achieve adhesion and separation with rigid substrates underwater; however, challenges remain in the control of adhesion and detachment of flexible materials. Additionally, underwater object manipulation necessitates considerable pre-pressure and is sensitive to water temperature fluctuations, potentially causing object damage and complicating adhesion and detachment processes. Thus, we present a novel, controllable adhesive pad inspired by the functional attributes of microwedge adhesive pads, combined with a mussel-inspired copolymer (MAPMC). In the context of underwater applications for flexible materials, the use of a microstructure adhesion pad with microwedge characteristics (MAPMCs) is a proficient approach to adhesion and detachment operations. This innovative method relies on the precise manipulation of the microwedge structure's collapse and recovery during its operation, which serves as the foundation for its efficacy in such environments. MAPMCs exhibit self-recovering elasticity, water flow interaction, and tunable underwater adhesion and detachment. Numerical simulations elucidate the synergistic effects of MAPMCs, highlighting the advantages of the microwedge structure for controllable, non-damaging adhesion and separation processes. The integration of MAPMCs into a gripping mechanism allows for the handling of diverse objects in underwater environments. Furthermore, by merging MAPMCs and a gripper within a linked system, our approach enables automatic, non-damaging adhesion, manipulation, and release of a soft jellyfish model. The experimental results indicate the potential applicability of MACMPs in underwater operations.

Primary tumor resection improves survival benefit of stage IVB cervical carcinoma: a new perspective.

PURPOSE: Recent studies have revealed that primary tumor resection (PTR) surgery could improve prognosis in some solid tumors. Thus, we aimed to investigate whether patients with stage IVB cervical carcinoma can benefit from PTR surgery and who can benefit. METHODS: We extracted and obtained data on patients with stage IVB cervical carcinoma from the SEER database from 2010 to 2017 and classified them into two groups: the surgery and the non-surgery group. The overall survival (OS) and cancer-specific survival (CSS) of the two groups were compared before and after propensity score matching (PSM). The independent prognostic variables were identified using univariate and multivariate Cox regression analyses. Then, the model was established to select the optimal patients to receive PTR surgery using multivariate logistic regression. RESULTS: After PSM, the study included 476 cervical carcinoma (stage IVB) patients, of whom 238 underwent PTR surgery. Compared to the non-surgery group, the surgery group's median OS and median CSS were both longer (median OS: 27 months vs. 13 months, P < 0.001; median CSS: 52 months vs. 21 months, P < 0.001). The model showed no organ metastasis, adenocarcinoma, G1/2, and chemotherapy were more supportive of performing PTR surgery. The calibration curves and DCA showed that the model had high predictive accuracy and excellent clinical applicability. Finally, the "surgery benefit" group had the OS that was approximately four times better than "surgery non-benefit" group. CONCLUSION: PTR surgery can potentially improve the prognosis of patients with cervical carcinoma at stage IVB. The model could probably select optimal candidates and provide a new perspective on individualized treatment.

Using Twitter-Based Data for Sexual Violence Research: Scoping Review.

BACKGROUND: Scholars have used data from in-person interviews, administrative systems, and surveys for sexual violence research. Using Twitter as a data source for examining the nature of sexual violence is a relatively new and underexplored area of study. OBJECTIVE: We aimed to perform a scoping review of the current literature on using Twitter data for researching sexual violence, elaborate on the validity of the methods, and discuss the implications and limitations of existing studies. METHODS: We performed a literature search in the following 6 databases: APA PsycInfo (Ovid), Scopus, PubMed, International Bibliography of Social Sciences (ProQuest), Criminal Justice Abstracts (EBSCO), and Communications Abstracts (EBSCO), in April 2022. The initial search identified 3759 articles that were imported into Covidence. Seven independent reviewers screened these articles following 2 steps: (1) title and abstract screening, and (2) full-text screening. The inclusion criteria were as follows: (1) empirical research, (2) focus on sexual violence, (3) analysis of Twitter data (ie, tweets or Twitter metadata), and (4) text in English. Finally, we selected 121 articles that met the inclusion criteria and coded these articles. RESULTS: We coded and presented the 121 articles using Twitter-based data for sexual violence research. About 70% (89/121, 73.6%) of the articles were published in peer-reviewed journals after 2018. The reviewed articles collectively analyzed about 79.6 million tweets. The primary approaches to using Twitter as a data source were content text analysis (112/121, 92.5%) and sentiment analysis (31/121, 25.6%). Hashtags (103/121, 85.1%) were the most prominent metadata feature, followed by tweet time and date, retweets, replies, URLs, and geotags. More than a third of the articles (51/121, 42.1%) used the application programming interface to collect Twitter data. Data analyses included qualitative thematic analysis, machine learning (eg, sentiment analysis, supervised machine learning, unsupervised machine learning, and social network analysis), and quantitative analysis. Only 10.7% (13/121) of the studies discussed ethical considerations. CONCLUSIONS: We described the current state of using Twitter data for sexual violence research, developed a new taxonomy describing Twitter as a data source, and evaluated the methodologies. Research recommendations include the following: development of methods for data collection and analysis, in-depth discussions about ethical norms, exploration of specific aspects of sexual violence on Twitter, examination of tweets in multiple languages, and decontextualization of Twitter data. This review demonstrates the potential of using Twitter data in sexual violence research.

Metasurface-based perfect vortex beams with trigonometric-function topological charge for OAM manipulation.

Topological charge (TC) is generally acknowledged as an important attribute of an optical vortex (OV), which indicates the twisted characterization of the wavefront. In most circumstances, the TC remains constant as an integer or fraction along the azimuthal direction. Herein, by transforming the TCs into the trigonometric functions of the azimuthal angle to tailor the spiral phase distributions, we numerically demonstrate generating perfect vortex beams (PVBs) with sine-function TC based on the all-dielectric geometric metasurfaces, whose unit structure is optimized to an ideal half-wave plate. To seek the intrinsic advancements of the proposed PVBs, their orbital angular momentum (OAM) as well as optical gradient force distributions are calculated for diverse particle manipulation. We believe our proposed scheme is desired to provide an original thought for OAM manipulation, information storage, and optical communication.

Preimplantation genetic testing for aneuploidy helps to achieve a live birth with fewer transfer cycles for the blastocyst FET patients with unexplained recurrent implantation failure.

PURPOSE: This retrospective cohort study aimed to investigate the value of preimplantation genetic testing for aneuploidy (PGT-A) as a screening test for patients suffering from unexplained recurrent implantation failure (RIF). METHODS: After screening patients in one reproductive medicine center, twenty-nine, forty-nine and thirty-eight women (< 40 years old) who had suffered unexplained RIF with PGT-A, or RIF without PGT-A, or no RIF with PGT-A were included. The clinical pregnancy rate and live birth rate per transfer, the conservative and optimal cumulative clinical pregnancy rates (CCPR) and live birth rates (CLBR) after three blastocyst FETs were analyzed. RESULTS: The live birth rate per transfer was significantly higher in the RIF + PGT-A group than that in the RIF + NO PGT-A group (47.6% vs. 24.6%, p = 0.014). After 3 cycles of FET, RIF + PGT-A group had significantly higher conservative CLBR and optimal CLBR compared to the RIF + NO PGT-A group (69.0% vs. 32.7%, p = 0.002 and 73.7% vs. 57.5%, p = 0.016), but had similar conservative and optimal CLBRs compared to the NO RIF + PGT-A group. The number of FET cycles required when half women achieved a live birth was 1 in the PGT-A group and 3 in RIF + NO PGT-A group. The miscarriage rates were not different between the RIF + PGT-A and RIF + NO PGT-A, RIF + PGT-A and NO RIF + PGT-A groups. CONCLUSION: PGT-A did be superior in reducing the number of transfer cycles required to achieve a similar live birth rate. Further studies to identify the RIF patients who would benefit most from PGT-A are necessary.

Estimation of heavy metal soil contamination distribution, hazard probability, and population at risk by machine learning prediction modeling in Guangxi, China.

Due to superposition of diverse pollution sources, soil heavy metal concentrations have been detected to exceed the recommended maximum permissible levels in many areas of Guangxi province, China. However, the heavy metal contamination distribution, hazard probability, and population at risk of heavy metals in the entire Guangxi province remain largely unclear. In this study, machine learning prediction models with different standard risk values determined according to land use types were used to identify high-risk areas and estimate populations at risk of Cr and Ni based on 658 topsoil samples from Guangxi province, China. Our results showed that soil Cr and Ni contamination derived from carbonate rocks was relatively serious in Guangxi province, and that their co-enrichment during soil formation was associated with Fe and Mn oxides and alkaline soil environment. Our established model exhibited excellent performance in predicting contamination distribution (R2 > 0.85) and hazard probability (AUC>0.85). Pollution of Cr and Ni exhibited a pattern of decreasing gradually from the central-west areas to the surrounding areas with the polluted area (Igeo>0) of Cr and Ni accounting for approximately 24.46% and 29.24% of total area in Guangxi province, respectively, but only 10.4% and 8.51% of total area was classified as Cr and Ni high-risk regions. We estimated approximately 1.44 and 1.47 million people were potentially exposed to the risk of Cr and Ni contamination, which were mainly concentrated in the Nanning, Laibin, and Guigang. These regions are main heavily-populated agricultural regions in Guangxi, and thus heavy metal contamination localization and risk control in these regions are urgent and essential from the perspective of food safety.