Predictive value of prognostic nutritional index as prognostic biomarkers in patients with lymphoma: a systematic review and meta-analysis.

BACKGROUND: Several research have indicated the significant potential of the Prognostic Nutritional Index (PNI) as a prognostic biomarker in lymphoma patients. However, there is some inconsistency in the findings of a few studies. Hence, to offer a thorough evaluation of the predictive significance of PNI in lymphoma patients, we performed a meta-analysis to examine the prognostic value of PNI for survival outcomes in lymphoma patients. METHODS: We conducted a comprehensive search for pertinent works published up until December 2023 in databases such as PubMed, EMBASE, Cochrane Library, and Web of Science. We obtained hazard ratio (HR) data related to survival outcomes and computed aggregated HRs with their corresponding 95% confidence intervals (CIs) to evaluate the correlation between PNI and both overall survival (OS) and progression-free survival (PFS) in lymphoma patients. RESULTS: By analyzing data from 1260 patients in 28 studies, we found that PNI levels were associated with prognosis in lymphoma patients. High PNI levels predicted that patients had longer OS (HR: 0.46, 95% CI 0.37-0.58, P < 0.05) and better PFS (HR: 0.56, 95% CI 0.45-0.70, P < 0.05). Subgroup analyses showed that the predictive ability of PNI for patient prognosis may differ depending on the type of lymphoma. In addition, we found that the critical PNI value had greater predictive potential at 40-45 and above 45. CONCLUSION: Our study suggests a strong association between PNI and prognostic outcomes in lymphoma patients, indicating that PNI holds substantial prognostic value in this population.

Interdependence of Support Wettability -Electrodeposition Rate - Sodium Metal Anode and SEI Microstructure.

This study examines how current collector support chemistry (sodiophilic intermetallic Na2Te vs. sodiophobic baseline Cu) and electrodeposition rate affect microstructure of sodium metal and its solid electrolyte interphase (SEI). Capacity and current (6 mAh cm-2, 0.5-3 mA cm-2) representative of commercially relevant mass loading in anode-free sodium metal battery (AF-SMBs) are analyzed. Synchrotron X-ray nanotomography and grazing-incidence wide-angle X-ray scattering (GIWAXS) are combined with cryogenic focused ion beam (cryo-FIB) microscopy. Highlighted are major differences in film morphology, internal porosity, and crystallographic preferred orientation e.g. (110) vs. (100) and (211) with support and deposition rate. Within the SEI, sodium fluoride (NaF) is more prevalent with Te-Cu versus sodium hydride (NaH) and sodium hydroxide (NaOH) with baseline Cu. Due to competitive grain growth the preferred orientation of sodium crystallites depends on film thickness. Mesoscale modelling delineates the role of SEI (ionic conductivity, morphology) on electrodeposit growth and onset of electrochemical instability.

Ex Situ Gaseous Reagent for Multicomponent Amine Bioconjugation.

We report a minimalist gaseous sulfonyl-chloride-derived reagent for multicomponent bioconjugation with amine, phenol, or aniline reagents to afford urea or carbamate products. With the utilization of a gas-phase reagent for a reaction mediated by metal ions, a variety of biologically relevant molecules, such as saccharide, poly(ethylene glycol), fluorophore, and affinity tag, can be efficiently cross-linked to the N terminus or lysine side-chain amines on natural polypeptides or proteins.

Light-emitting probes for in situ sensing of plant information.

Monitoring plant physiological information for gaining a comprehensive understanding of plant growth and stress responses contributes to safeguarding plant health. Light-emitting probes - in terms of small-molecule, nanomaterials-based, and genetically protein-based probes - can be introduced into plants through foliar and root treatment or genetic transformation. These probes offer exciting opportunities for sensitive and in situ monitoring of dynamic plant chemical information - for example, reactive oxygen species (ROS), calcium ions, phytohormones - with spatiotemporal resolution. In this review we explore the sensing mechanisms of these light-emitting probes and their applications in monitoring various chemical information in plants in situ. These probes can be used as part of a sentinel plant approach to provide stress warning in the field or to explore plant signaling pathways.

Dual-Function Alloying Nitrate Additives Stabilize Fast-Charging Lithium Metal Batteries.

Lithium metal is regarded as the "holy grail" of lithium-ion battery anodes due to its exceptionally high theoretical capacity (3800 mAh g-1) and lowest possible electrochemical potential (-3.04 V vs Li/Li+); however, lithium suffers from the dendritic formation that leads to parasitic reactions and cell failure. In this work, we stabilize fast-charging lithium metal plating/stripping with dual-function alloying M-nitrate additives (M: Ag, Bi, Ga, In, and Zn). First, lithium metal reduces M, forming lithiophilic alloys for dense Li nucleation. Additionally, nitrates form ionically conductive and mechanically stable Li3N and LiNxOy, enhancing Li-ion diffusion through the passivation layer. Notably, Zn-protected cells demonstrate electrochemically stable Li||Li cycling for 750+ cycles (2.0 mA cm-2) and 140 cycles (10.0 mA cm-2). Moreover, Zn-protected Li||Lithium Iron Phosphate full-cells achieve 134 mAh g-1 (89.2% capacity retention) after 400 cycles (C/2). This work investigates a promising solution to stabilize lithium metal plating/stripping for fast-charging lithium metal batteries.

Biosynthesis of Halogenated Tryptophans for Protein Engineering Using Genetic Code Expansion.

Genetic Code Expansion technology offers significant potential in incorporating noncanonical amino acids into proteins at precise locations, allowing for the modulation of protein structures and functions. However, this technology is often limited by the need for costly and challenging-to-synthesize external noncanonical amino acid sources. In this study, we address this limitation by developing autonomous cells capable of biosynthesizing halogenated tryptophan derivatives and introducing them into proteins using Genetic Code Expansion technology. By utilizing inexpensive halide salts and different halogenases, we successfully achieve the selective biosynthesis of 6-chloro-tryptophan, 7-chloro-tryptophan, 6-bromo-tryptophan, and 7-bromo-tryptophan. These derivatives are introduced at specific positions with corresponding bioorthogonal aminoacyl-tRNA synthetase/tRNA pairs in response to the amber codon. Following optimization, we demonstrate the robust expression of proteins containing halogenated tryptophan residues in cells with the ability to biosynthesize these tryptophan derivatives. This study establishes a versatile platform for engineering proteins with various halogenated tryptophans.

Pathomics and single-cell analysis of papillary thyroid carcinoma reveal the pro-metastatic influence of cancer-associated fibroblasts.

BACKGROUND: Papillary thyroid carcinoma (PTC) is globally prevalent and associated with an increased risk of lymph node metastasis (LNM). The role of cancer-associated fibroblasts (CAFs) in PTC remains unclear. METHODS: We collected postoperative pathological hematoxylin-eosin (HE) slides from 984 included patients with PTC to analyze the density of CAF infiltration at the invasive front of the tumor using QuPath software. The relationship between CAF density and LNM was assessed. Single-cell RNA sequencing (scRNA-seq) data from GSE193581 and GSE184362 datasets were integrated to analyze CAF infiltration in PTC. A comprehensive suite of in vitro experiments, encompassing EdU labeling, wound scratch assays, Transwell assays, and flow cytometry, were conducted to elucidate the regulatory role of CD36+CAF in two PTC cell lines, TPC1 and K1. RESULTS: A significant correlation was observed between high fibrosis density at the invasive front of the tumor and LNM. Analysis of scRNA-seq data revealed metastasis-associated myoCAFs with robust intercellular interactions. A diagnostic model based on metastasis-associated myoCAF genes was established and refined through deep learning methods. CD36 positive expression in CAFs can significantly promote the proliferation, migration, and invasion abilities of PTC cells, while inhibiting the apoptosis of PTC cells. CONCLUSION: This study addresses the significant issue of LNM risk in PTC. Analysis of postoperative HE pathological slides from a substantial patient cohort reveals a notable association between high fibrosis density at the invasive front of the tumor and LNM. Integration of scRNA-seq data comprehensively analyzes CAF infiltration in PTC, identifying metastasis-associated myoCAFs with strong intercellular interactions. In vitro experimental results indicate that CD36 positive expression in CAFs plays a promoting role in the progression of PTC. Overall, these findings provide crucial insights into the function of CAF subset in PTC metastasis.

Value of circulating tumor cell assisting low-dose computed tomography in screening pulmonary nodules based on existing liquid biopsy techniques: a systematic review with meta-analysis and trial sequential analysis.

OBJECTIVE: This study aims to assess the diagnostic utility of circulating tumor cells (CTCs) in conjunction with low-dose computed tomography (LDCT) for differentiating between benign and malignant pulmonary nodules and to substantiate the foundation for their integration into clinical practice. METHODS: A systematic literature review was performed independently by two researchers utilizing databases including PubMed, Web of Science, The Cochrane Library, Embase, and Medline, to collate studies up to September 15, 2023, that investigated the application of CTCs in diagnosing pulmonary nodules. A meta-analysis was executed employing Stata 15.0 and Revman 5.4 to calculate the pooled sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), and the area under the receiver operating characteristic curve (AUC). Additionally, trial sequential analysis was conducted using dedicated TSA software. RESULTS: The selection criteria identified 16 studies, encompassing a total of 3409 patients. The meta-analysis revealed that CTCs achieved a pooled sensitivity of 0.84 (95% CI 0.80 to 0.87), specificity of 0.80 (95% CI 0.73 to 0.86), PLR of 4.23 (95% CI 3.12 to 5.72), NLR of 0.20 (95% CI 0.16 to 0.25), DOR of 20.92 (95% CI 13.52 to 32.36), and AUC of 0.89 (95% CI 0.86 to 0.93). CONCLUSIONS: Circulating tumor cells demonstrate substantial diagnostic accuracy in distinguishing benign from malignant pulmonary nodules. The incorporation of CTCs into the diagnostic protocol can significantly augment the diagnostic efficacy of LDCT in screening for malignant lung diseases.

Sophisticated Structural Ceramics Shaped from 3D Printed Hydrogel Preceramic Skeleton.

Shaping ceramic materials into sophisticated architecture with 3D hierarchical structure is desirable in multiapplication yet remains challenge due to their brittle and stiff nature. Herein, a new method to achieve ceramic architectures with unsupported and large-spanning structure by shaping vat photopolymerization 3D printed hydrogel preceramic skeleton with unique flexible and deformable character is proposed. Specifically, the present photopolymerizable hydrogel preceramic achieves one stone, two birds: the photosensitive polymer matrix coupled with ceramic nanoparticles for the first shaping by vat photopolymerization 3D printing and the secondary plasticity of the 3D printed ceramic body through flexible shape deformation of hydrogel networks. Inorganic binder aluminum dihydrogen phosphate serves as hydrogel dispersion medium to achieve ultralow shrinkage photopolymerization ceramic. Compared with conventional polymer-derived photocuring ceramics, the linear shrinkage of lamina structure is solely 2%, and which of cubic ceramic structure is just 13.3%. More importantly, one 3D printed preceramic is conducted to reshape repeatedly myriad constructions, realizing reusability of intrinsic brittle ceramic, improving manufacturing fault tolerance rate. Finally, a variety of paradigms for ceramic structure applications are proposed toward stereo circuit, biomedicine, and catalytic applications, breaking the limitation of intrinsic brittleness of ceramic in high-precision manufacturing of complex ceramic devices.

Ab initio determination of melting and sound velocity of neon up to the deep interior of the Earth.

The thermophysical properties and elemental abundances of the noble gases in terrestrial materials can provide unique insights into the Earth's evolution and mantle dynamics. Here, we perform extensive ab initio molecular dynamics simulations to determine the melting temperature and sound velocity of neon up to 370 GPa and 7500 K to constrain its physical state and storage capacity, together with to reveal its implications for the deep interior of the Earth. It is found that solid neon can exist stably under the lower mantle and inner core conditions, and the abnormal melting of neon is not observed under the entire temperature (T) and pressure (P) region inside the Earth owing to its peculiar electronic structure, which is substantially distinct from other heavier noble gases. An inspection of the reduction for sound velocity along the Earth's geotherm evidences that neon can be used as a light element to account for the low-velocity anomaly and density deficit in the deep Earth. A comparison of the pair distribution functions and mean square displacements of MgSiO3-Ne and Fe-Ne alloys further reveals that MgSiO3 has a larger neon storage capacity than the liquid iron under the deep Earth condition, indicating that the lower mantle may be a natural deep noble gas storage reservoir. Our results provide valuable information for studying the fundamental behavior and phase transition of neon in a higher T-P regime, and further enhance our understanding for the interior structure and evolution processes inside the Earth.

Selective Macrocyclization of Unprotected Peptides with an Ex Situ Gaseous Linchpin Reagent.

Peptide cyclization has dramatic effects on a variety of important properties, enhancing metabolic stability, limiting conformational flexibility, and altering cellular entry and intracellular localization. The hydrophilic, polyfunctional nature of peptides creates chemoselectivity challenges in macrocyclization, especially for natural sequences without biorthogonal handles. Herein, we describe a gaseous sulfonyl chloride derived reagent that achieves amine-amine, amine-phenol, and amine-aniline crosslinking through a minimalist linchpin strategy that affords macrocyclic urea or carbamate products. The cyclization reaction is metal-mediated and involves a novel application of sulfine species that remains unexplored in aqueous or biological contexts. The aqueous method delivers unique cyclic or bicyclic topologies directly from a variety of natural bioactive peptides without the need for protecting-group strategies.

Integration of multi-omics data for survival prediction of lung adenocarcinoma.

BACKGROUND AND OBJECTIVE: The morbidity of lung adenocarcinoma (LUAD) has been increasing year by year and the prognosis is poor. This has prompted researchers to study the survival of LUAD patients to ensure that patients can be cured in time or survive after appropriate treatment. There is still no fully valid model that can be applied to clinical practice. METHODS: We introduced struc2vec-based multi-omics data integration (SBMOI), which could integrate gene expression, somatic mutations and clinical data to construct mutation gene vectors representing LUAD patient features. Based on the patient features, the random survival forest (RSF) model was used to predict the long- and short-term survival of LUAD patients. To further demonstrate the superiority of SBMOI, we simultaneously replaced scale-free gene co-expression network (FCN) with a protein-protein interaction (PPI) network and a significant co-expression network (SCN) to compare accuracy in predicting LUAD patient survival under the same conditions. RESULTS: Our results suggested that compared with SCN and PPI network, the FCN based SBMOI combined with RSF model had better performance in long- and short-term survival prediction tasks for LUAD patients. The AUC of 1-year, 5-year, and 10-year survival in the validation dataset were 0.791, 0.825, and 0.917, respectively. CONCLUSIONS: This study provided a powerful network-based method to multi-omics data integration. SBMOI combined with RSF successfully predicted long- and short-term survival of LUAD patients, especially with high accuracy on long-term survival. Besides, SBMOI algorithm has the potential to combine with other machine learning models to complete clustering or stratificational tasks, and being applied to other diseases.

Bone morphogenetic protein 15 gene disruption affects the in vitro maturation of porcine oocytes by impairing spindle assembly and organelle function.

Bone morphogenetic protein 15 (BMP15) plays a crucial role in the porcine follicular development. However, its exact functions in the in vitro maturation (IVM) of porcine oocytes remain largely unknown. Here, through cytoplasmic injection of a preassembled crRNA-tracrRNA-Cas9 ribonucleoprotein complex, we achieved BMP15 disruption in approximately 54 % of the cultured porcine oocytes. Editing BMP15 impaired the IVM of porcine oocytes, as indicated by the significantly increased abnormal spindle assembly and reduced first polar body (PB1) extrusion. The editing also impaired cytoplasmic maturation of porcine oocytes, as reflected by reduced abundant of Golgi apparatus and impaired functions of mitochondria. The impaired IVM of porcine oocytes by editing BMP15 possibly was associated with the attenuated SMAD1/5 and EGFR-ERK1/2 signaling in the cumulus granulosa cells (CGCs) and the inhibited MOS/ERK1/2 signaling in oocytes. The attenuated MOS/ERK1/2 signaling may contribute to the inactivation of maturation promoting factor (MPF) and the increased abnormal spindle assembly, leading to reduced PB1 extrusion. It also may contribute to reduced Golgi apparatus formation, and impaired functions of mitochondria. These findings expand our understanding of the regulatory role of BMP15 in the IVM of porcine oocytes and provide a basis for manipulation of porcine reproductive performance.

Extrusion Printing of Surface-Functionalized Metal-Organic Framework Inks for a High-Performance Wearable Volatile Organic Compound Sensor.

Wearable sensors hold immense potential for real-time and non-destructive sensing of volatile organic compounds (VOCs), requiring both efficient sensing performance and robust mechanical properties. However, conventional colorimetric sensor arrays, acting as artificial olfactory systems for highly selective VOC profiling, often fail to meet these requirements simultaneously. Here, a high-performance wearable sensor array for VOC visual detection is proposed by extrusion printing of hybrid inks containing surface-functionalized sensing materials. Surface-modified hydrophobic polydimethylsiloxane (PDMS) improves the humidity resistance and VOC sensitivity of PDMS-coated dye/metal-organic frameworks (MOFs) composites. It also enhances their dispersion within liquid PDMS matrix, thereby promoting the hybrid liquid as high-quality extrusion-printing inks. The inks enable direct and precise printing on diverse substrates, forming a uniform and high particle-loading (70 wt%) film. The printed film on a flexible PDMS substrate demonstrates satisfactory flexibility and stretchability while retaining excellent sensing performance from dye/MOFs@PDMS particles. Further, the printed sensor array exhibits enhanced sensitivity to sub-ppm VOC levels, remarkable resistance to high relative humidity (RH) of 90%, and the differentiation ability for eight distinct VOCs. Finally, the wearable sensor proves practical by in situ monitoring of wheat scab-related VOC biomarkers. This study presents a versatile strategy for designing effective wearable gas sensors with widespread applications.

The Prognostic Value and Potential Immune Mechanisms of lncRNAs Related to Immunogenic Cell Death in Papillary Thyroid Carcinoma.

Background: Long non-coding RNAs (lncRNAs) associated with immunogenic cell death (ICD) play a pivotal role in tumorigenesis and offer prognostic insights for papillary thyroid carcinoma (PTC) patients. This study delves into the impact of ICD-related lncRNAs on the prognosis of PTC. Methods: PTC samples were accessed from The Cancer Genome Atlas-Thyroid carcinoma database (TCGA-THCA) and consensus cluster analysis to elucidate the influence of ICD-related lncRNA expression. To gauge the prognostic significance of these lncRNAs, we developed a prognostic model. Additionally, we conducted GO and KEGG enrichment analyses, assessed immune cell infiltration (ICI) using CIBERSORT and ssGSEA, examined immune checkpoint expression, tumor mutation burden (TMB), tumor microenvironment (TME), T-cell dysfunction and exclusion (TIDE), TCIA, and drug sensitivity across various groups. A comprehensive suite of in vitro experiments, encompassing EdU labeling, wound scratch assays, Transwell assays, and flow cytometry, were conducted to elucidate the regulatory role of LINC00924 in two PTC cell lines, BCPAP and TPC1, transfected with LINC00924 overexpression plasmids. Results: Two distinct clusters demonstrated varying TME, BRAF, NRAS, and ICI characteristics, suggesting potential immune mechanisms in PTC. Our prognostic model identified seven lncRNAs: SRRM2-AS1, AC008556.1, BHLHE40-AS1, EGOT, AL39066.1, LINC00924, and PICART1. The expression of ICD-related lncRNAs correlated with progression-free interval (PFI) in PTC patients. Overexpression of LINC00924 significantly reduced cell proliferation, migration, and invasion, while augmenting apoptosis in PTC cells. Conclusion: Our findings highlight the potential of ICD-related lncRNAs as prognostic biomarkers for PFI in PTC. In vitro experiments suggest a protective role of LINC00924 in PTC progression.

Eye-Readable and Wearable Colorimetric Sensor Arrays for In Situ Monitoring of Volatile Organic Compounds.

Wearable sensors utilize changes in color as a response to physiological stimuli, making them easily recognizable by the naked eye. These colorimetric wearable sensors offer benefits such as easy readability, rapid responsiveness, cost-effectiveness, and straightforward manufacturing techniques. However, their applications in detecting volatile organic compounds (VOCs) in situ have been limited due to the low concentration of complex VOCs and complicated external interferences. Aiming to address these challenges, we introduced readable and wearable colorimetric sensing arrays with a microchannel structure and highly gas-sensitive materials for in situ detection of complex VOCs. The highly gas-sensitive materials were designed by loading gas-sensitive dyes into the porous metal-organic frameworks and further depositing the composites on the electrospun nanofiber membrane. The colorimetric sensor arrays were fabricated using various gas-sensitive composites, including eight dye/MOF composites that respond to various VOCs and two Pd2+/dye/MOF composites that respond to ethylene. This enables the specific recognition of multiple characteristic VOCs. A microfluidic channel made of polydimethylsiloxane (PDMS) was integrated with different colorimetric elements to create a wearable sensor array. It was attached to the surface of fruits to collect and monitor VOCs using the DenseNet classification method. As a proof of concept, we demonstrated the feasibility of the wearable sensing system in monitoring the ripening process of fruits by continuously measuring the VOC emissions from the skin of the fruit.

Binary Solvent Induced Stable Interphase Layer for Ultra-Long Life Sodium Metal Batteries.

Sodium foil, promising for high-energy-density batteries, faces reversibility challenges due to its inherent reactivity and unstable solid electrolyte interphase (SEI) layer. In this study, a stable sodium metal battery (SMB) is achieved by tuning the electrolyte solvation structure through the addition of co-solvent 2-methyl tetrahydrofuran (MTHF) to diglyme (Dig). The introduction of cyclic ether-based MTHF results in increased anion incorporation in the solvation structure, even at lower salt concentrations. Specifically, the anion stabilization capabilities of the environmentally sustainable MTHF co-solvent lead to a contact-ion pair-based solvation structure. Time-of-flight mass spectroscopy analysis reveals that a shift toward an anion-dominated solvation structure promotes the formation of a thin and uniform SEI layer. Consequently, employing a NaPF6-based electrolyte with a Dig:MTHF ratio of 50% (v/v) binary solvent yields an average Coulombic efficiency of 99.72% for 300 cycles in Cu||Na cell cycling. Remarkably, at a C/2 cycling rate, Na||Na symmetric cell cycling demonstrates ultra-long-term stability exceeding 7000 h, and full cells with Na0.44MnO2 as a cathode retain 80% of their capacity after 500 cycles. This study systematically examines solvation structure, SEI layer composition, and electrochemical cycling, emphasizing the significance of MTHF-based binary solvent mixtures for high-performance SMBs.

Engineering small-molecule and protein drugs for targeting bone tumors.

Bone cancer is common and severe. Both primary (e.g., osteosarcoma, Ewing sarcoma) and secondary (e.g., metastatic) bone cancers lead to significant health problems and death. Currently, treatments such as chemotherapy, hormone therapy, and radiation therapy are used to treat bone cancer, but they often only shrink or slow tumor growth and do not eliminate cancer completely. The bone microenvironment contributes unique signals that influence cancer growth, immunogenicity, and metastasis. Traditional cancer therapies have limited effectiveness due to off-target effects and poor distribution on bones. As a result, therapies with improved specificity and efficacy for treating bone tumors are highly needed. One of the most promising strategies involves the targeted delivery of pharmaceutical agents to the site of bone cancer by introduction of bone-targeting moieties, such as bisphosphonates or oligopeptides. These moieties have high affinities to the bone hydroxyapatite matrix, a structure found exclusively in skeletal tissue, and can enhance the targeting ability and efficacy of anticancer drugs when combating bone tumors. This review focuses on the engineering of small molecules and proteins with bone-targeting moieties for the treatment of bone tumors.

50-nm Gas-Filled Protein Nanostructures to Enable the Access of Lymphatic Cells by Ultrasound Technologies.

Ultrasound imaging and ultrasound-mediated gene and drug delivery are rapidly advancing diagnostic and therapeutic methods; however, their use is often limited by the need for microbubbles, which cannot transverse many biological barriers due to their large size. Here, the authors introduce 50-nm gas-filled protein nanostructures derived from genetically engineered gas vesicles(GVs) that are referred to as 50 nmGVs. These diamond-shaped nanostructures have hydrodynamic diameters smaller than commercially available 50-nm gold nanoparticles and are, to the authors' knowledge, the smallest stable, free-floating bubbles made to date. 50 nmGVs can be produced in bacteria, purified through centrifugation, and remain stable for months. Interstitially injected 50 nmGVs can extravasate into lymphatic tissues and gain access to critical immune cell populations, and electron microscopy images of lymph node tissues reveal their subcellular location in antigen-presenting cells adjacent to lymphocytes. The authors anticipate that 50 nmGVs can substantially broaden the range of cells accessible to current ultrasound technologies and may generate applications beyond biomedicine as ultrasmall stable gas-filled nanomaterials.

Integrated Fruit Ripeness Assessment System Based on an Artificial Olfactory Sensor and Deep Learning.

Artificial scent screening systems, inspired by the mammalian olfactory system, hold promise for fruit ripeness detection, but their commercialization is limited by low sensitivity or pattern recognition inaccuracy. This study presents a portable fruit ripeness prediction system based on colorimetric sensing combinatorics and deep convolutional neural networks (DCNN) to accurately identify fruit ripeness. Using the gas chromatography-mass spectrometry (GC-MS) method, the study discerned the distinctive gases emitted by mango, peach, and banana across various ripening stages. The colorimetric sensing combinatorics utilized 25 dyes sensitive to fruit volatile gases, generating a distinct scent fingerprint through cross-reactivity to diverse concentrations and varieties of gases. The unique scent fingerprints can be identified using DCNN. After capturing colorimetric sensor image data, the densely connected convolutional network (DenseNet) was employed, achieving an impressive accuracy rate of 97.39% on the validation set and 82.20% on the test set in assessing fruit ripeness. This fruit ripeness prediction system, coupled with a DCNN, successfully addresses the issues of complex pattern recognition and low identification accuracy. Overall, this innovative tool exhibits high accuracy, non-destructiveness, practical applicability, convenience, and low cost, making it worth considering and developing for fruit ripeness detection.