A Novel Cellular Senescence-related lncRNA Signature for Predicting the Prognosis of Breast Cancer Patients.

Background: Long non-coding RNA (lncRNA), a crucial regulator in breast cancer (BC) development, is intricately linked with cellular senescence. However, there is a lack of cellular senescence-related lncRNAs (CSRLs) signature to evaluate the prognosis of BC patients. Methods: Correlation analysis was conducted to identify lncRNAs associated with cellular senescence. Subsequently, a CSRL signature was crafted in the training cohort. The model's accuracy was evaluated through survival analysis and receiver operating characteristic curves. Furthermore, prognostic nomograms amalgamating cellular senescence and clinical characteristics were devised. Tumor microenvironment and checkpoint disparities were compared between low-risk and high-risk groups. The correlation between these signatures and treatment response in BC patients was also investigated. Finally, functional experiments were conducted for validation. Results: A signature comprising nine CSRLs was devised, which demonstrated adept prognostic capability in BC patients. Functional enrichment analysis revealed that tumor and immune-related pathways were predominantly enriched. Compared to the low-risk group, the high-risk group could benefit more from immunotherapy and certain chemotherapeutic agents. The expression of the 9 CSRLs was validated through in vitro experiments in different subtypes of BC cell lines and tissues. AC098484.1 was specifically verified for its association with senescence-associated secretory phenotypes. Conclusion: The CSRLs signature emerges as a promising prognostic biomarker for BC, with implications for immunological studies and treatment strategies. AC098484.1 has potential relevance in the treatment of BC cell senescence, and these findings improve the clinical treatment levels for BC patients.

Comparing overall survival between pediatric and adult retinoblastoma with the construction of nomogram for adult retinoblastoma: A SEER population-based analysis.

BACKGROUND: Retinoblastoma (RB) is a rare primary malignant tumor primarily affecting children. Our study aims to compare the overall survival (OS) between pediatric and adult RB patients and establish a predictive model for adult RB patients' OS to assist clinical decision-making. METHODS: This study retrospectively analyzed data from 1938 RB patients in the Surveillance, Epidemiology, and End Results (SEER) database, covering the period from 2000 to 2015. Propensity score matching (PSM) ensured balanced characteristics between pediatric and adult groups. A Cox proportional hazards regression model was used to assess prognostic factors, and selected variables were utilized to construct a predictive survival model. The Nomogram model's performance was evaluated through the C-index, time-dependent ROC curves, calibration curves, and decision curve analysis (DCA). RESULTS: Following PSM, adult RB patients had lower OS compared to pediatric RB patients. Independent prognostic factors for adult RB OS included age, gender, disease stage, radiation therapy, income, and diagnosis confirmation. In the training cohort, the Nomogram achieved a C-index for OS of 0.686 and accurately predicted 2-year, 3-year, and 5-year OS with AUC values of 0.672, 0.680, and 0.660, respectively. The C-index, time-dependent ROC curves, calibration curves, and DCA in both training and validation cohorts confirmed the Nomogram's excellent performance. CONCLUSION: In this study, adult RB patients have worse OS than pediatric RB patients. Consequently, we constructed a Nomogram to predict the risk for adult RB patients. The Nomogram demonstrated good accuracy and reliability, making it suitable for widespread application in clinical practice to assist healthcare professionals in assessing patients' prognoses.

Intelligent health and sport: An interplay between flexible sensors and basketball.

Basketball, as one of the most popular sports in the world, has millions of followers and massive economic value. Basketball evolves so fast that it requires teams with smarter strategies, better skills, and stronger players. However, the competition strategies and training methods in basketball are still experience-based, lacking precise data to drive for more efficient training and strategies. On the other hand, flexible sensors, as a new class of sensors, have been a hotspot for scientific research and widely applied in various fields. Due to their excellent characteristics of flexibility, wearing comfort, convenience, and response speed, integrating flexible sensors into basketball has the potential to greatly promote all aspects of the sport. This paper aims to bring more fusion between basketball and flexible sensors. In this perspective, we first perform a review of the history of sensing technologies in the basketball sport and discuss mechanisms of flexible sensors applied on basketball players. Then specific scenarios for flexible sensors applied in basketball were elaborated on in detail. Finally, we envision the potential applications of flexible sensors in basketball and present our views on future development directions. We hope this paper can depict how flexible sensing technology is integrated into basketball systems and point out the future development of basketball with the help of flexible sensors.

Wearable and interactive multicolored photochromic fiber display.

Endowing flexible and adaptable fiber devices with light-emitting capabilities has the potential to revolutionize the current design philosophy of intelligent, wearable interactive devices. However, significant challenges remain in developing fiber devices when it comes to achieving uniform and customizable light effects while utilizing lightweight hardware. Here, we introduce a mass-produced, wearable, and interactive photochromic fiber that provides uniform multicolored light control. We designed independent waveguides inside the fiber to maintain total internal reflection of light as it traverses the fiber. The impact of excessive light leakage on the overall illuminance can be reduced by utilizing the saturable absorption effect of fluorescent materials to ensure light emission uniformity along the transmission direction. In addition, we coupled various fluorescent composite materials inside the fiber to achieve artificially controllable spectral radiation of multiple color systems in a single fiber. We prepared fibers on mass-produced kilometer-long using the thermal drawing method. The fibers can be directly integrated into daily wearable devices or clothing in various patterns and combined with other signal input components to control and display patterns as needed. This work provides a new perspective and inspiration to the existing field of fiber display interaction, paving the way for future human-machine integration.

Controllable-morphology polymer blend photonic metafoam for radiative cooling.

Incorporating radiative cooling photonic structures into the cooling systems of buildings presents a novel strategy to mitigate global warming and boost global carbon neutrality. Photonic structures with excellent solar reflection and thermal emission can be obtained by a rational combination of different materials. The current preparation strategies of radiative cooling materials are dominated by doping inorganic micro-nano particles into polymers, which usually possess insufficient solar reflectance. Here, a porous polymer metafoam was prepared with polycarbonate (PC) and polydimethylsiloxane (PDMS) using a simple thermally induced phase separation method. The metafoam exhibits strong solar reflectivity (97%), superior thermal emissivity (91%), and low thermal conductivity (46 mW m-1 K-1) due to the controllable morphology of the randomly dispersed light-scattering air voids. Cooling tests demonstrate that the metafoam could reduce the average temperature by 5.2 °C and 10.2 °C during the daytime and nighttime, respectively. In addition, the simulation of a cooling energy system of buildings indicates that the metafoam can save 3.2-26.7 MJ m-2 per year in different cities, which is an energy-saving percentage of 14.7-41%. The excellent comprehensive performances, including the passive cooling property, thermal insulation and self-cleaning of the metafoam makes it appropriate for practical outdoor applications, exhibiting its great potential as an energy-saving building cooling material.

Preoperative low muscle mass and malnutrition affect the clinical prognosis of locally advanced gastric cancer patients undergoing radical surgery.

Background: Gastric cancer is a common and highly aggressive malignant tumor of the gastrointestinal tract that poses a serious threat to human life and health. As the clinical symptoms of early gastric carcinoma are not obvious, many patients are diagnosed in the middle or late stages. With the advancement of medical technology, gastrectomy has become a safer surgical procedure, but it still has a high recurrence and mortality rate after surgery. The prognosis of gastric cancer patients after surgery is not only related to tumor-related factors (i.e., tumor stage) but the patient's nutritional status. This study aimed to investigate the effect of preoperative muscle mass combined with the prognostic nutritional index (PNI) on clinical prognosis in locally advanced gastric carcinoma. Methods: The clinical data of 136 patients with locally advanced gastric carcinoma diagnosed by pathology and undergoing radical gastrectomy were retrospectively reviewed. To analyze the influencing factors of preoperative low muscle mass and its correlation with the prognostic nutritional index. Patients with both low muscle mass and low PNI (≤46.55) were assigned a score of 2, and those with only one or neither of these abnormalities were assigned a score of 1 or 0, respectively, according to the new prognostic score (PNIS). The relationship between PNIS and clinicopathological characteristics was analyzed. Univariate and multivariate analyses were performed to identify risk factors for overall survival (OS). Results: Low muscle mass was associated with a lower PNI (P < 0.01). The optimal cut-off value of PNI was 46.55, the sensitivity was 48%, and the specificity was 97.1%. There were 53 (38.97%), 59 (43.38%), and 24 patients (17.65%) in the PNIS 0, 1, and 2 groups, respectively. A higher PNIS and advanced age were independent risk factors for postoperative complications (P < 0.01). The overall survival rate in patients with PNIS 2 score was significantly poorer than in patients with scores of 1 or 0 (3-year OS: 45.8% vs 67.8% vs 92.4%, P < 0.001). A Multivariate Cox hazards analysis showed that PNIS 2, depth of tumor invasion, vascular invasion, and postoperative complications were independent predictors of the poor 3-year survival in patients with locally advanced gastric cancer. Conclusions: The combination of muscle mass and the PNI score system can be used to predict the survival outcome of patients with locally advanced gastric cancer.

Chalcogenide glass nanospheres with tunable morphology by liquid-phase template approach.

Chalcogenide glass (ChG) with unique material properties has been widely used in mid-infrared. Traditional ChG microspheres/nanospheres preparation usually uses a high-temperature melting method, in which it is difficult to accurately control the size and the morphology of the nanospheres. Here, we produce nanoscale-uniform (200-500 nm), morphology-tunable, and arrangement-orderly ChG nanospheres from the inverse-opal photonic crystal (IOPC) template by the liquid-phase template (LPT) method. Moreover, we refer to the formation mechanism of nanosphere morphology as the evaporation-driven self-assembly of colloidal dispersion nanodroplets within the immobilized template and find that the concentration of ChG solution and the pore size of IOPC are the key to control the morphology of the nanospheres. The LPT method is also applied to the two-dimensional microstructure/nanostructure. This work provides an efficient and low-cost strategy for the preparation of multisize ChG nanospheres with tunable morphology and is expected to find various applications in mid-infrared, optoelectronic devices.

Dual-Mode Fiber Strain Sensor Based on Mechanochromic Photonic Crystal and Transparent Conductive Elastomer for Human Motion Detection.

As an important component of wearable and stretchable strain sensors, dual-mode strain sensors can respond to deformation via optical/electrical dual-signal changes, which have important applications in human motion monitoring. However, realizing a fiber-shaped dual-mode strain sensor that can work stably in real life remains a challenge. Here, we design an interactive dual-mode fiber strain sensor with both mechanochromic and mechanoelectrical functions that can be applied to a variety of different environments. The dual-mode fiber is produced by coating a transparent elastic conductive layer onto photonic fiber composed of silica particles and elastic rubber. The sensor has visualized dynamic color change, a large strain range (0-80%), and a high sensitivity (1.90). Compared to other dual-mode strain sensors based on the photonic elastomer, our sensor exhibits a significant advantage in strain range. Most importantly, it can achieve reversible and stable optical/electrical dual-signal outputs in response to strain under various environmental conditions. As a wearable portable device, the dual-mode fiber strain sensor can be used for real-time monitoring of human motion, realizing the direct interaction between users and devices, and is expected to be used in fields such as smart wearable, human-machine interactions, and health monitoring.

A nomogram for predicting overall survival in patients with parathyroid cancer: A novel web-based calculator.

BACKGROUND: Parathyroid carcinoma is a rare endocrine malignancy. Considering that clinicians develop appropriate treatment strategies based on patients' survival expectations. Therefore, the present study aimed to develop a survival prediction model to guide clinical decision-making. METHODS: We retrospectively analyzed 362 parathyroid carcinoma patients diaagnosed in the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. Correlations between outcome events and variables were analyzed using univariate and multifactorial Cox regression, and variables screened by the multifactorial Cox risk proportional model were used to construct a survival prediction model. The model was evaluated using Receiver Operating Characteristic (ROC) curves, decision curve analysis (DCA), and C-index and calibration curves. RESULTS: Univariate and multifactorial COX analyses revealed five independent prognostic factors for parathyroid carcinoma patients, which were subsequently used to develop the nomogram prediction model. In the training cohort, the C-index of the nomogram in predicting the overall survival (OS) was 0.747 (0.686-0.808), the area under the receiver operator characteristics curve(AUC)values of the nomogram in prediction of the 3, 5, and 10-year OS were 0.718 (0617-0.819), 0.711 (0.614-0.808) and 0.706 (0.610-0.803), respectively. In the validation cohort, the C-index was 0.740 (0.645-0.835), The AUC for 3, 5, and 10-years OS were 0.736 (0.584-0888), 0.698 (0.551-0.845) and 0.767 (0.647-0.887), respectively. The C-index, time-dependent ROC curve, calibration curve, and DCA showed that the Nomogram had a clear advantage. CONCLUSION: The developed nomogram can be applied in clinical practice to help clinicians to assess patient prognosis.

Advanced functional nanofibers: strategies to improve performance and expand functions.

Nanofibers have a wide range of applications in many fields such as energy generation and storage, environmental sensing and treatment, biomedical and health, thanks to their large specific surface area, excellent flexibility, and superior mechanical properties. With the expansion of application fields and the upgrade of application requirements, there is an inevitable trend of improving the performance and functions of nanofibers. Over the past few decades, numerous studies have demonstrated how nanofibers can be adapted to more complex needs through modifications of their structures, materials, and assembly. Thus, it is necessary to systematically review the field of nanofibers in which new ideas and technologies are emerging. Here we summarize the recent advanced strategies to improve the performances and expand the functions of nanofibers. We first introduce the common methods of preparing nanofibers, then summarize the advances in the field of nanofibers, especially up-to-date strategies for further enhancing their functionalities. We classify these strategies into three categories: design of nanofiber structures, tuning of nanofiber materials, and improvement of nanofibers assemblies. Finally, the optimization methods, materials, application areas, and fabrication methods are summarized, and existing challenges and future research directions are discussed. We hope this review can provide useful guidance for subsequent related work.

Developing and validating nomograms for predicting the survival in patients with clinical local-advanced gastric cancer.

Background: Many patients with gastric cancer are at a locally advanced stage during initial diagnosis. TNM staging is inaccurate in predicting survival. This study aims to develop two more accurate survival prediction models for patients with locally advanced gastric cancer (LAGC) and guide clinical decision-making. Methods: We recruited 2794 patients diagnosed with LAGC (2010-2015) from the Surveillance, Epidemiology, and End Results (SEER) database and performed external validation using data from 115 patients with LAGC at Yantai Affiliated Hospital of Binzhou Medical University. Univariate and multifactorial survival analyses were screened for meaningful independent prognostic factors and were used to build survival prediction models. Concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were evaluated for nomograms. Finally, the differences and relationships of survival and prognosis between the three different risk groups were described using the Kaplan-Meier method. Results: Cox proportional risk regression model analysis identified independent prognostic factors for patients with LAGC, and variables associated with overall survival (OS) included age, race, marital status, T-stage, N-stage, grade, histologic type, surgery, and chemotherapy. Variables associated with cancer-specific survival (CSS) included age, race, T-stage, N-stage, grade, histological type, surgery, and chemotherapy. In the training cohort, C-index of nomogram for predicting OS was 0.722 (95% confidence interval [95% CI]: 0.708-0.736] and CSS was 0.728 (95% CI: 0.713-0.743). In the external validation cohort, C-index of nomogram for predicted OS was 0.728 (95% CI:0.672-0.784) and CSS was 0.727 (95% CI:0.668-0.786). The calibration curves showed good concordance between the predicted and actual results. C-index, ROC, and DCA results indicated that our nomograms could more accurately predict OS and CSS than TNM staging and had a higher clinical benefit. Finally, to facilitate clinical use, we set up two web servers based on nomograms. Conclusion: The nomograms established in this study have better risk assessment ability than the clinical staging system, which can help clinicians predict the individual survival of LAGC patients more accurately and thus develop appropriate treatment strategies.

Imperceptible, designable, and scalable braided electronic cord.

Flexible sensors, friendly interfaces, and intelligent recognition are important in the research of novel human-computer interaction and the development of smart devices. However, major challenges are still encountered in designing user-centered smart devices with natural, convenient, and efficient interfaces. Inspired by the characteristics of textile-based flexible electronic sensors, in this article, we report a braided electronic cord with a low-cost, and automated fabrication to realize imperceptible, designable, and scalable user interfaces. The braided electronic cord is in a miniaturized form, which is suitable for being integrated with various occasions in life. To achieve high-precision interaction, a multi-feature fusion algorithm is designed to recognize gestures of different positions, different contact areas, and different movements performed on a single braided electronic cord. The recognized action results are fed back to varieties of interactive terminals, which show the diversity of cord forms and applications. Our braided electronic cord with the features of user friendliness, excellent durability and rich interaction mode will greatly promote the development of human-machine integration in the future.

Fabric computing: Concepts, opportunities, and challenges.

With the advent of the Internet of Everything, people can easily interact with their environments immersively. The idea of pervasive computing is becoming a reality, but due to the inconvenience of carrying silicon-based entities and a lack of fine-grained sensing capabilities for human-computer interaction, it is difficult to ensure comfort, esthetics, and privacy in smart spaces. Motivated by the rapid developments in intelligent fabric technology in the post-Moore era, we propose a novel computing approach that creates a paradigm shift driven by fabric computing and advocate a new concept of non-chip sensing in living spaces. We discuss the core notion and benefits of fabric computing, including its implementation, challenges, and future research opportunities.

Flexible and robust low-loss selenium-based multimaterial infrared fibers towards CO2 laser ablation.

A small-scale delivery medium for CO2 laser energy with stable performance, flexibility, and high-strength is crucial in extreme laser processing environments, especially for minimally invasive surgery in high-humidity, twisty and narrow channels. Here, flexible and robust multimaterial infrared fibers made of selenium-based chalcogenide glasses and thermoplastic polymer were developed with a low loss of 7.18 dB/m at 10.6 µm. The resulting fibers were capable of stably delivering single-mode CO2 laser with 0.42 W average power. Moreover, to achieve precise control over the fibers in the practical clinical environment, customized co-polymers of polyphenylene sulfone resin and polyvinylidene fluoride were used as the fiber built-in jackets. Consequently, the fibers exhibited hydrophobicity, thermostability, high tensile strength, and low bending stiffness. The results demonstrated that the fibers can be used to deliver CO2 laser energy for fabric cutting and bio-tissues ablation, making them attractive for CO2 laser material processing and minimally invasive laser surgery.

Development and validation of nomograms for predicting overall survival and cancer specific survival in locally advanced breast cancer patients: A SEER population-based study.

Background: For patients with locally advanced breast cancer (LABC), conventional TNM staging is not accurate in predicting survival outcomes. The aim of this study was to develop two accurate survival prediction models to guide clinical decision making. Methods: A retrospective analysis of 22,842 LABC patients was performed from 2010 to 2015 using the Surveillance, Epidemiology and End Results (SEER) database. An additional cohort of 200 patients from the Binzhou Medical University Hospital (BMUH) was analyzed. The least absolute shrinkage and selection operator (LASSO) regression was used to screen for variables. The identified variables were used to build a survival prediction model. The performance of the nomogram models was assessed based on the concordance index (C-index), calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Results: The LASSO analysis identified 9 variables in patients with LABC, including age, marital status, Grade, histological type, T-stage, N-stage, surgery, radiotherapy, and chemotherapy. In the training cohort, the C-index of the nomogram in predicting the overall survival (OS) was 0.767 [95% confidence intervals (95% CI): 0.751-0.775], cancer specific survival (CSS) was 0.765 (95% CI: 0.756-0.774). In the external validation cohort, the C-index of the nomogram in predicting the OS was 0.858 (95% CI: 0.812-0.904), the CSS was 0.866 (95% CI: 0.817-0.915). In the training cohort, the area under the receiver operator characteristics curve (AUC) values of the nomogram in prediction of the 1, 3, and 5-year OS were 0.836 (95% CI: 0.821-0.851), 0.769 (95% CI: 0.759-0.780), and 0.750 (95% CI: 0.738-0.762), respectively. The AUC values for prediction of the 1, 3, and 5-year CSS were 0.829 (95% CI: 0.811-0.847), 0.769 (95% CI: 0.757-0.780), and 0.745 (95% CI: 0.732-0.758), respectively. Results of the C-index, ROC curve, and DCA demonstrated that the nomogram was more accurate in predicting the OS and CSS of patients compared with conventional TNM staging. Conclusion: Two prediction models were developed and validated in this study which provided more accurate prediction of the OS and CSS in LABC patients than the TNM staging. The constructed models can be used for predicting survival outcomes and guide treatment plans for LABC patients.

Multifunctional Fiber-Enabled Intelligent Health Agents.

The application of wearable devices is promoting the development toward digitization and intelligence in the field of health. However, the current smart devices centered on human health have disadvantages such as weak perception, high interference degree, and unfriendly interaction. Here, an intelligent health agent based on multifunctional fibers, with the characteristics of autonomy, activeness, intelligence, and perceptibility enabling health services, is proposed. According to the requirements for healthcare in the medical field and daily life, four major aspects driven by intelligent agents, including health monitoring, therapy, protection, and minimally invasive surgery, are summarized from the perspectives of materials science, medicine, and computer science. The function of intelligent health agents is realized through multifunctional fibers as sensing units and artificial intelligence technology as a cognitive engine. The structure, characteristics, and performance of fibers and analysis systems and algorithms are reviewed, while discussing future challenges and opportunities in healthcare and medicine. Finally, based on the above four aspects, future scenarios related to health protection of a person's life are presented. Intelligent health agents will have the potential to accelerate the realization of precision medicine and active health.

Helicobacter pylori Biofilm-Related Drug Resistance and New Developments in Its Anti-Biofilm Agents.

Helicobacter pylori is one of the most common pathogenic bacterium worldwide, infecting about 50% of the world's population. It is a major cause of several upper gastrointestinal diseases, including peptic ulcers and gastric cancer. The emergence of H. pylori resistance to antibiotics has been a major clinical challenge in the field of gastroenterology. In the course of H. pylori infection, some bacteria invade the gastric epithelium and are encapsulated into a self-produced matrix to form biofilms that protect the bacteria from external threats. Bacteria with biofilm structures can be up to 1000 times more resistant to antibiotics than planktonic bacteria. This implies that targeting biofilms might be an effective strategy to alleviate H. pylori drug resistance. Therefore, it is important to develop drugs that can eliminate or disperse biofilms. In recent years, anti-biofilm agents have been investigated as alternative or complementary therapies to antibiotics to reduce the rate of drug resistance. This article discusses the formation of H. pylori biofilms, the relationship between biofilms and drug resistance in H. pylori, and the recent developments in the research of anti-biofilm agents targeting H. pylori drug resistance.

Flexible thermochromic fabrics enabling dynamic colored display.

Color-changeable fibers can provide diverse functions for intelligent wearable devices such as novel information displays and human-machine interfaces when woven into fabric. This work develops a low-cost, effective, and scalable strategy to produce thermochromic fibers by wet spinning. Through a combination of different thermochromic microcapsules, flexible fibers with abundant and reversible color changes are obtained. These color changes can be clearly observed by the naked eye. It is also found that the fibers exhibit excellent color-changing stability even after 8000 thermal cycles. Moreover, the thermochromic fibers can be fabricated on a large scale and easily woven or implanted into various fabrics with good mechanical performance. Driven by their good mechanical and physical characteristics, applications of thermochromic fibers in dynamic colored display are demonstrated. Dynamic quick response (QR) code display and recognition are successfully realized with thermochromic fabrics. This work well confirms the potential applications of thermochromic fibers in smart textiles, wearable devices, flexible displays, and human-machine interfaces.