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The purpose of the study is to propose a framework that summarizes the processing of existing and incoming sources about the life of the overseas Chinese, their historical heritage, and documents. The study addresses the significant problem of fragmentation and relatively poor accessibility of individual collections or sets of documents to interested researchers, who may not even know about the existence of the documents they are looking for. As an approach to solving this problem, it is proposed to use end-to-end processing of cached data, which is a description of digitized or material sources of artifacts already created by researchers. Cached data stores information about the use of a service, program, or data to structure and facilitate future individual use of that data. This is, in particular, the data about the structure of catalog or directory topics, keywords, and database indexes. With the help of AI, human resources, and already existing approaches to the algorithmizing of various types of digital data (for example, images of artifacts or documents), the created descriptions of sources are gradually being universalized and unified through the practice of database queries, and access to them is simplified using tags and ‘cloud’ data storages. This approach has great practical value because it does not require the use of special agreements, data formats, or complex digital tools that would be difficult to implement in international research practice.

Flexible, stretchable and sensitive textile-based sensors play important roles in a wide variety of artificial intelligence because of its seamless integration with clothing and good comfort. Herein, MXene sensing layer is deposited on the surface of springlike helical core-sheath polyester yarns thanks to the capillarity effect and its intrinsic hydrophilic ability, and the resultant strain sensor and humidity sensor exhibit wide detection range from 0.3 to 120% strain and 30–100% relative humidity (RH) detection, owing to elastic core-sheath structures. The strain sensor shows excellent reproducibility (over 10000 cycles) and fast response time (120 ms). The core-sheath yarn sensor can detect various human motions such as walking, bending and twisting as well as physiological signal (pulse), which have great potential in real-time precise medicine and health care. The yarn sensor could also be an excellent humidity sensor because of the high specific area structure of yarn and intrinsic hydrophilic properties of MXene sensing layer.

HighlightsMXene sediments is innovatively used as photothermal material for seawater desalination.Inspired by the natural wood transpiration process, a 3D MXene sediment-based aerogel with vertically aligned channels is innovatively prepared as solar evaporator.With unique structure and composition, excellent photothermal conversion efficiency, evaporation rate, salt resistance, and resistance to biological/oil/special environments are achieved in practical desalination.Solar-driven interfacial evaporation from seawater is considered an effective way to alleviate the emerging freshwater crisis because of its green and environmentally friendly characteristics. However, developing an evaporator with high efficiency, stability, and salt resistance remains a key challenge. MXene, with an internal photothermal conversion efficiency of 100%, has received tremendous research interest as a photothermal material. However, the process to prepare the MXene with monolayer is inefficient and generates a large amount of “waste” MXene sediments (MS). Here, MXene sediments is selected as the photothermal material, and a three-dimensional MXene sediments/poly(vinyl alcohol)/sodium alginate aerogel evaporator with vertically aligned pores by directional freezing method is innovatively designed. The vertical porous structure enables the evaporator to improve water transport, light capture, and high evaporation rate. Cotton swabs and polypropylene are used as the water channel and support, respectively, thus fabricating a self-floating evaporator. The evaporator exhibits an evaporation rate of 3.6 kg m−2 h−1 under one-sun illumination, and 18.37 kg m−2 of freshwater is collected in the condensation collection device after 7 h of outdoor sun irradiation. The evaporator also displays excellent oil and salt resistance. This research fully utilizes “waste” MS, enabling a self-floating evaporation device for freshwater collection.

Blood analysis is regarded as the gold standard for monitoring analytes in clinical diagnostics. However, the time-consuming and site-limited nature often delays medical interventions that are crucial for patients in emergency scenarios. Herein, a weavable multi-biosensor array is developed through coaxial wet spinning for real-time multiplex detection of sweat biomarkers (pH, Na + , K + , and Ca 2+ ) and body temperature. The engineered microstructure of the multi-biosensor array exhibits a surface area that is around 200 times larger than that of conventional coated yarns, thereby facilitating directional sweat transport. The sensitivities of the pH, Na + , K + , Ca 2+ and temperature sensors have been determined to be 39.52 ± 0.5 mV pH −1 (3-7), 56.33 ± 1 mV dec −1 (10-160 mM), 34.13 ± 0.6 mV dec −1 (2-32 mM), 30.61 ± 0.8 mV dec −1 (0.5-2.53 mM), and 1.2 Ω ± 0.02 °C −1 (25-45 °C), respectively. It is noteworthy that the multi-biosensors exhibit consistent operational stability over 24 hours with minimal signal drift (pH: 0.13 ± 0.01 mV h −1 , Na + : 0.17 ± 0.02 mV h −1 , K + :0.1 ± 0.008 mV h −1 , Ca 2+ : 0.19 ± 0.01 mV h −1 , temperature: 0.05 ± 0.004 Ω h −1 ). By integrating the multi-biosensors and a circuit patch into the textile substrate, a wireless hairband system is constructed for tracking human physiological dynamics. Such significant technological advancement offers an innovative strategy for constructing real-time biosensing systems, which have the potential to revolutionize personalized healthcare and enable early diagnosis in emergency situations. The time-consuming and site-limited nature of blood analysis often delays medical interventions. Here, the authors developed a weaved multi-sensing hairband for real-time sweat biomarkers and body temperature monitoring.

Graphene has been highlighted in a variety of wearable electronics and smart textiles applications due to its unique properties such as high conductivity, transparency, flexibility and other excellent mechanical performance. Although there have been extensive efforts for graphene based conductive fibers/yarns, there are remaining challenges in terms of the seamless integration between 2D flakes, and reduced charge transport in a lower carrier concentration. Unstable resistance probably arises from the creation of gaps in the conductive parts of the smart textile. Also, regional temperatures can get too high, constituting a fire-safety hazard and endangering the wearer's safety. In this work, the synergistic effect of graphene and flame-retardant materials was investigated, and a conductive fabric was developed which is highly conductive and flame retardancy. Graphene has excellent electrical and thermal conductivity and acts synergistically with traditional flame-retardants on common fabrics. The electrical surface resistivity of hybrid material modified fabrics was as low as 0.54 kΩ/sq, so they could serve as safe and highly conductive conductor in a simple circuit and show excellent wash-ability. The limiting oxygen index of the fabric increased from 19 to 32 after modification in conjunction with the residue at 800 °C increased from 17.9 to 31%, which could be used as safe and highly conductive materials for smart textiles and wearable devices.

Background Breast cancer susceptibility gene (BRCA) mutation carriers are at an increased risk for breast, ovarian, prostate and pancreatic cancers. However, the role of BRCA is unclear in colorectal cancer; the results regarding the association between BRCA gene mutations and colorectal cancer risk are inconsistent and even controversial. This study aimed to investigate whether BRCA1 and BRCA2 gene mutations are associated with colorectal cancer risk. Methods In this systematic review, we searched PubMed/MEDLINE, Embase and Cochrane Library databases, adhering to PRISMA guidelines. Study quality was assessed using the Newcastle–Ottawa Scale (NOS). Unadjusted odds ratios (ORs) were used to estimate the probability of Breast Cancer Type 1 Susceptibility gene (BRCA1) and Breast Cancer Type 2 Susceptibility gene (BRCA2) mutations in colorectal cancer patients. The associations were evaluated using fixed effect models. Results Fourteen studies were included in the systematic review. Twelve studies, including seven case–control and five cohort studies, were included in the meta-analysis. A significant increase in the frequency of BRCA1 and BRCA2 mutations was observed in patients with colorectal cancer [OR = 1.34, 95% confidence interval (CI) = 1.02–1.76, P  = 0.04]. In subgroup analysis, colorectal cancer patients had an increased odds of BRCA1 (OR = 1.48, 95% CI = 1.10–2.01, P  = 0.01) and BRCA2 (OR = 1.56, 95% CI = 1.06–2.30, P  = 0.02) mutations. Conclusions BRCA genes are one of the genes that may increase the risk of developing colorectal cancer. Thus, BRCA genes could be potential candidates that may be included in the colorectal cancer genetic testing panel.

Conductive nanomaterials have recently gained a lot of interest due to their excellent physical, chemical, and electrical properties, as well as their numerous nanoscale morphologies, which enable them to be fabricated into a wide range of modern chemical and biological sensors. This study focuses mainly on current applications based on conductive nanostructured materials. They are the key elements in preparing wearable electrochemical Biosensors, including electrochemical immunosensors and DNA biosensors. Conductive nanomaterials such as carbon (Carbon Nanotubes, Graphene), metals and conductive polymers, which provide a large effective surface area, fast electron transfer rate and high electrical conductivity, are summarized in detail. Conductive polymer nanocomposites in combination with carbon and metal nanoparticles have also been addressed to increase sensor performance. In conclusion, a section on current challenges and opportunities in this growing field is forecasted at the end.

Highlights The iontronic meta-fabric exhibits a “hitting three birds with one stone” property, breaking through the bottleneck that traditional film materials (PDMS) cannot balance comfort and durability. The meta-fabrics can be integrated with garments and advanced data analysis systems to manufacture a series of large matrix structure (> 40 × 40, 1600 sensing units) rehabilitation training devices, overcoming the bottleneck of low matrix integration of traditional iontronic devices (< 10 × 10, 100 sensing units). Rehabilitation training is believed to be an effectual strategy that can reduce the risk of dysfunction caused by spasticity. However, achieving visualization rehabilitation training for patients remains clinically challenging. Herein, we propose visual rehabilitation training system including iontronic meta-fabrics with skin-friendly and large matrix features, as well as high-resolution image modules for distribution of human muscle tension. Attributed to the dynamic connection and dissociation of the meta-fabric, the fabric exhibits outstanding tactile sensing properties, such as wide tactile sensing range (0 ~ 300 kPa) and high-resolution tactile perception (50 Pa or 0.058%). Meanwhile, thanks to the differential capillary effect, the meta-fabric exhibits a “hitting three birds with one stone” property (dryness wearing experience, long working time and cooling sensing). Based on this, the fabrics can be integrated with garments and advanced data analysis systems to manufacture a series of large matrix structure (40 × 40, 1600 sensing units) training devices. Significantly, the tunability of piezo-ionic dynamics of the meta-fabric and the programmability of high-resolution imaging modules allow this visualization training strategy extendable to various common disease monitoring. Therefore, we believe that our study overcomes the constraint of standard spasticity rehabilitation training devices in terms of visual display and paves the way for future smart healthcare.

Owing to their excellent elasticities and adaptability as sensing materials, ionic hydrogels exhibit significant promise in the field of intelligent wearable devices. Nonetheless, molecular chains within the polymer network of hydrogels are susceptible to damage, leading to crack extension. Hence, we drew inspiration from the composite structure of the human dermis to engineer a composite hydrogel, incorporating dopamine-modified elastic fibers as a reinforcement. This approach mitigates crack expansion and augments sensor sensitivity by fostering intermolecular forces between the dopamine on the fibers, the hydrogel backbone, and water molecules. The design of this composite hydrogel elevates its breaking tensile capacity from 35 KJ to 203 KJ, significantly enhancing the fatigue resistance of the hydrogel. Remarkably, its electrical properties endure stability even after 2000 cycles of testing, and it manifests heightened sensitivity compared to conventional hydrogel configurations. This investigation unveils a novel method for crafting composite-structured hydrogels.

Fe3O4@C/Au nanoparticle (AuNP) nanocomposites were prepared through electrostatic adsorption of AuNPs onto PDDA-functionalized core/shell Fe3O4@C magnetic nanospheres, which had been synthesized by a facile solvothermal method. The morphology and composition of the nanocomposites were characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), Fourier transform infrared (FT-IR), etc. Moreover, highly electrocatalytic activity to the reduction of hydrogen peroxide (H2O2) was also exhibited on the Fe3O4@C/AuNP-modified indium tin oxide (ITO) electrode. The effect of solution pH and the modification amount of Fe3O4@C/AuNPs on the performance of electrocatalytic H2O2 reduction was investigated. Under the optimal conditions, the catalytic current showed a linear relationship with the increase of H2O2 concentration in the range of 0.007–15 mM and a detection limit of 5 μM. The H2O2 sensor showed high selectivity for H2O2 detection, which could effectively resist the interference of ascorbic acid (AA), uric acid (UA), and citric acid (CA). Finally, the H2O2 sensor was used in the real fetal bovine serum to detect H2O2 and obtained satisfactory results with the recovery values ranging from 95.14 to 103.6%.