Stable O3 Decomposition by Layered Double Hydroxides: The Pivotal Role of NiOOH Transformation.

Because ozone (O3) is a significant air pollutant, advanced O3 elimination technologies, particularly those under high-humidity conditions, have become an essential research focus. In this study, a nickel-iron layered double hydroxide (NiFe-LDH) was modified via intercalation with octanoate to develop an effective hydrophobic catalyst (NiFe-OAa-LDH) for O3 decomposition. The NiFe-OAa-LDH catalyst sustained its O3 decomposition rate of >98% for 48 h under conditions of 90% relative humidity, 840 L/(g·h) space velocity, and 100 ppm inlet O3 concentration. Moreover, it maintained a decomposition rate of 90% even when tested at a higher airflow rate of 2500 L/(g·h). Based on the changes induced by the Ni-OII to Ni-OIII bonds in NiFe-OAa-LDH during O3 treatment, catalytic O3 decomposition was proposed to occur in two stages. The first stage involved the reaction between the hydroxyl groups and O3, leading to the breakage of the O-H bonds, formation of NiOOH, and structural changes in the catalyst. This transformation resulted in the formation of abundant and stable hydrogen vacancies. According to density functional theory calculations, O3 can be effectively decomposed at the hydrogen vacancies with a low energy barrier during the second stage. This study provides new insights into O3 decomposition.

Biomass-Based, Dual Enzyme-Responsive Nanopesticides: Eco-friendly and Efficient Control of Pine Wood Nematode Disease.

Pine wood nematode (PWN) disease is a globally devastating forest disease caused by infestation with PWN, Bursaphelenchus xylophilus, which mainly occurs through the vector insect Japanese pine sawyer (JPS), Monochamus alternatus. PWN disease is notoriously difficult to manage effectively and is known as the "cancer of pine trees." In this study, dual enzyme-responsive nanopesticides (AVM@EC@Pectin) were prepared using nanocoating avermectin (AVM) after modification with natural polymers. The proposed treatment can respond to the cell wall-degrading enzymes secreted by PWNs and vector insects during pine tree infestation to intelligently release pesticides to cut off the transmission and infestation pathways and realize the integrated control of PWN disease. The LC50 value of AVM@EC@Pectin was 11.19 mg/L for PWN and 26.31 mg/L for JPS. The insecticidal activity of AVM@EC@Pectin was higher than that of the commercial emulsifiable concentrate (AVM-EC), and the photostability, adhesion, and target penetration were improved. The half-life (t1/2) of AVM@EC@Pectin was 133.7 min, which is approximately twice that of AVM-EC (68.2 min). Sprayed and injected applications showed that nanopesticides had superior bidirectional transportation, with five-times higher AVM contents detected in the roots relative to those of AVM-EC when sprayed at the top. The safety experiment showed that the proposed treatment had lower toxicity and higher safety for nontarget organisms in the application environment and human cells. This study presents a green, safe, and effective strategy for the integrated management of PWN disease.

Stretchable Photonic Crystal-Assisted Glycoprotein Identification for Ovarian Cancer Diagnosis.

Photonic crystals with specific wavelengths can realize surface-enhanced excitation and emission intensities of fluorophores and enhance the fluorescence signals of fluorescent molecules. Herein, stretchable photonic crystals with good mechanochromic properties provide continuously adjustable forbidden wavelengths by stretching to change the lattice spacing, with reflectance peaks blue-shifted up to 110 nm to match indicators of different wavelengths and produce differentiated optical enhancement effects. Glycoproteins are significantly identified as clinical markers. However, the wide participation of glycoproteins in various life processes poses enormous complexity and critical challenges for rapid, facile, high-throughput, and accurate clinical analysis or health assessment. In this work, we proposed a stretchable photonic crystal-assisted glycoprotein identification approach for early ovarian cancer diagnosis. Stretchable photonic crystals can provide rich optical information to efficiently identify glycoproteins in complex matrices. A double-indicator fluorescence sensor was designed to respond to the protein trunk and oligosaccharide segment of glycoproteins separately for improved recognition accuracy. Seven typical glycoproteins could be discriminated from proteins, saccharides, or mixture interferents. Clinical ovarian cancer samples for early, intermediate, and advanced ovarian cancer and healthy subjects were verified with 100% accuracy. This strategy of stretchable photonic crystal-assisted glycoprotein identification provides an effective method for accurate, rapid ovarian cancer diagnosis and timely clinical treatment.

Integrated Electrochemical Aptasensor Array toward Monitoring Anticancer Drugs in Sweat.

In the realm of clinical practice, the concurrent utilization of anticancer medications can enhance their overall therapeutic efficacy. However, it is crucial to acknowledge that the interactions among these anticancer drugs can potentially yield detrimental consequences on their intended outcomes. Consequently, the assessment of both anticancer potency and potential toxic side effects is greatly refined when multiple anticancer drugs are simultaneously detected and evaluated. Here, we designed a wearable electrochemical aptasensor array for monitoring multiple anticancer drugs in sweat. The integrated sensor array consists of three working electrodes modified with three different aptamers (Apt1, Apt2, and Apt3), a Au counter electrode, and a Ag/AgCl reference electrode. Molecular docking simulations were performed to show the binding affinities between three anticancer drugs and their corresponding aptamers. Various eigenvalues were derived from the square-wave voltammetry electrochemical signals, and these data sets were subjected to rigorous analysis through multivariate data analysis techniques. This analytical approach demonstrated exceptional performance by achieving flawless 100% accuracy in the precise identification of nine anticancer drugs consistently at uniform concentrations. Furthermore, the integrated wearable sensor array exhibited impressive capabilities, correctly recognizing all nine anticancer drugs with 100% accuracy and successfully distinguishing between these drugs in artificial sweat samples. The proposed sensor array presents good stability for 15 days. Flexibility tests showed stable device performance after 500 twisting cycles. This innovative wearable sensing array represents a novel approach for achieving real-time monitoring and precise adjustment of drug dosages. It offers invaluable insights for tailoring the treatment of anticancer drugs to individual patients, predicting both drug efficacy and potential adverse reactions within the field of clinical medicine.

Visual Gustation via Regulable Elastic Photonic Crystals.

The unique structural sensitivity of photonic crystals (PCs) endows them with stretchable or elastic tunability for light propagation and spontaneous emission modulation. Hydrogel PCs have been demonstrated to have biocompatibility and flexibility for potential human health detection and environmental security monitoring. However, current elastic PCs still possess a fixed elastic modulus and uncontrollable structural colors based on a tunable elastic modulus, posing considerable challenges for in situ detection, particularly in wearable or portable sensing devices. In this work, we introduced a novel chemo-mechanical transduction mechanism embedded within a photonic crystal nanomatrix, leading to the creation of structural colors and giving rise to a visual gustation sensing experience. By utilizing the captivating structural colors generated by the hydrogel PC, we employ abundant optical information to identify various analytes. The finite element analysis proved the electric field distribution in the PC matrix during stretch operations. The elastic-optical behaviors with various chemical cosolvents, including cations, anions, saccharides, or organic acids, were investigated. The mechanism of the Hofmeister effect regulating the elasticity of hydrogels was demonstrated with the network nanostructure of the hydrogels. The hydrogel PC matrix demonstrates remarkable capability in efficiently distinguishing a wide range of cations, anions, saccharides, and organic acids across various concentrations, mixtures, and even real food samples, such as tastes and soups. Through comprehensive research, a precise relationship between the structural colors and the elastic modulus of hydrogel PCs has been established, contributing to the biomatching elastic-optics platform for wearable devices, a dynamic environment, and clinical or health monitoring auxiliary.

Fluorescent Selectivity-Enhanced FRET Based on 3D Photonic Crystals for Multianalyte Sensing.

Fluorescence resonance energy transfer (FRET) finds widespread utility in biochemical sensing, single-molecule experiments, cell physiology, and various other domains due to its inherent simplicity and high sensitivity. Nevertheless, the efficiency of energy transfer between the FRET donor and acceptor is significantly contingent on the local photonic environment, a factor that limits its application in complex systems or multianalyte detections. Here, a fluorescent selectivity-enhanced acridine orange (AO)-aflatoxins (AFs) FRET system based on a range of 3D topological photonic crystals (PCs) was developed with the aim of enhancing the selectivity and discrimination capabilities of FRET. By exploring the angle-dependent characteristics of the photonic stopband, the stopband distribution across different 3D topological PCs pixels was investigated. This approach led to selective fluorescence enhancement in PCs that matched the stopbands, enabling the successful discrimination of six distinct aflatoxins and facilitating complex multianalysis of moldy food samples. In particular, the stopband, which was strategically positioned within the blue-purple structural color range, exhibited a strong alignment with the fluorescence peaks of both the FRET donor and acceptor. This alignment allowed the 3D three-pointed star PCs to be effectively employed for the identification of mixed samples containing six distinct aflatoxins as well as the detection of real aflatoxin samples present in moldy potatoes, bread, oats, and peanuts. Impressively, this approach achieved a remarkable accuracy rate of 100%. This innovative strategy not only presents a novel avenue for developing a multitarget discrimination analysis system but also offers a convenient pretreatment method for the quantitative detection of various aflatoxins.

Explainable Deep Learning-Assisted Self-Calibrating Colorimetric Patches for In Situ Sweat Analysis.

Sweat has emerged as a compelling analyte for noninvasive biosensing technology because it contains a wealth of important biomarkers in hormones, organic biomacromolecules, and various ionic mixtures. These components offer valuable insights and can reflect an individual's physiological conditions. Here, we introduced an explainable deep learning (DL)-assisted wearable self-calibrating colorimetric biosensing analysis platform to efficiently and precisely detect the biomarker's concentration in sweat. Specifically, we have integrated the advantages of the colorimetric sensing method, adsorbing-swelling hydrogel, and explainable DL algorithms to develop an enzyme/indicator-immobilized colorimetric patch, which has reliable colorimetric sensing ability and excellent adsorbing-swelling function. A total of 5625 colorimetric images were collected as the analysis data set and assessed two DL algorithms and seven machine learning (ML) algorithms. Zn2+, glucose, and Ca2+ in human sweats could be facilely classified and quantified with 100% accuracy via the convolutional neural network (CNN) model, and the testing results of actual sweats via the DL-assisted colorimetric approach are 91.7-97.2% matching with the classical UV-vis spectrum. Class activation mapping (CAM) was utilized to visualize the inner working mechanism of CNN operation, which contributes to verify and explicate the design rationality of the noninvasive biosensing technology. An "end-to-end" model was established to ascertain the black box of the DL algorithm, promoted software design or principium optimization, and contributed facile indicators for health monitoring, disease prevention, and clinical diagnosis.

Atomic Insights into the S Poisoning Effects of Single-Atom Catalysts in Li-S Batteries.

Here, we paved a new way to evaluate the susceptibility of M-N4-based single-atom catalysts (SACs) to sulfur poisoning in Li-S batteries. The strong binding strength of M-S in Ti-N4- and V-N4-based SACs is attributed to the high bond order, pronounced d-p hybridization, and differential charge density. However, overly strong binding strength of M-S can create a high energy barrier that prevents the detachment of covered S atoms and induces sulfur poisoning. This can significantly impede the exposure of catalysts to residual reactants during subsequent charge-discharge cycles. Moreover, the sulfur poisoning will dramatically depress the overall catalytic performance of the SACs during the subsequent charge-discharge process, indicating that some compromise should be made between the high catalytic performance and the sulfur poisoning in designing SACs for Li-S batteries.

Optical bistability modulation based on graphene sandwich structure with topological interface modes.

In this paper, we have investigated optical bistability modulation of transmitted beam that can be achieved by graphene sandwich structure with topological interface modes at terahertz frequency. Graphene with strong nonlinear optical effect was combined with sandwich photonic crystal to form a new sandwich structure with topological interface modes. The light-limiting properties of the topological interface modes, as well as its high unidirectionality and high transmission efficiency, all contribute positively to the reduction of the optical bistability threshold. In addition, the topological interface modes can effectively ensure the stability of the two steady state switching in the case of external interference. Moreover, optical bistability is closely related to the incident angle, the Fermi energy, the relaxation time, and the number of layers of graphene. Through parameter optimization, optical bistability with threshold of 105 V/m can be obtained, which has reached or is close to the range of the weak field.

Si3C Monolayer as an Efficient Metal-Free Catalyst for Nitrate Electrochemical Reduction: A Computational Study.

Nitrate electroreduction reaction to ammonia (NO3ER) holds great promise for both nitrogen pollution removal and valuable ammonia synthesis, which are still dependent on transition-metal-based catalysts at present. However, metal-free catalysts with multiple advantages for such processes have been rarely reported. Herein, by means of density functional theory (DFT) computations, in which the Perdew-Burke-Ernzerhof (PBE) functional is obtained by considering the possible van der Waals (vdW) interaction using the DFT+D3 method, we explored the potential of several two-dimensional (2D) silicon carbide monolayers as metal-free NO3ER catalysts. Our results revealed that the excellent synergistic effect between the three Si active sites within the Si3C monolayer enables the sufficient activation of NO3- and promotes its further hydrogenation into NO2*, NO*, and NH3, making the Si3C monolayer exhibit high NO3ER activity with a low limiting potential of -0.43 V. In particular, such an electrochemical process is highly dependent on the pH value of the electrolytes, in which acidic conditions are more favorable for NO3ER. Moreover, ab initio molecular dynamics (AIMD) simulations demonstrated the high stability of the Si3C monolayer. In addition, the Si3C monolayer shows a low formation energy, excellent electronic properties, a superior suppression effect on competing reactions, and high stability, offering significant advantages for its experimental synthesis and practical applications in electrocatalysis. Thus, a Si3C monolayer can perform as a promising NO3ER catalyst, which would open a new avenue to further develop novel metal-free catalysts for NO3ER.

Multicenter evaluation of a simple and sensitive nucleic acid self-testing for SARS-CoV-2.

A rapid and accurate COVID-19 diagnosis is a prerequisite for blocking the source of infection as soon as possible and taking the appropriate medical action. Herein, we developed GeneClick, a device for nucleic acid self-testing of SARS-CoV-2, consisting of three modules: a sampling kit, a microfluidic chip-based disposable cartridge, and an amplification reader. In addition, we evaluated the clinical performance of GeneClick using 2162 nasal swabs collected at three medical institutions, using three commercial RT-qPCR kits and an antigen self-test as references. Compared to RT-qPCR, the sensitivity and specificity of the GeneClick assay were 97.93% and 99.72%, respectively, with a kappa value of 0.979 (P â€‹< â€‹0.01). Of the 2162 samples, 2076 were also tested for SARS-CoV-2 antigens. Among the 314 positive samples identified by GeneClick assay, 63 samples were undetected by antigen tests. Overall, the GeneClick nucleic acid self-test demonstrated higher accuracy than the antigen-based detection. Based on the additional features, including simple operation, affordable price, portable device, and reliability of smartphone APP-driven sampling and result reporting, GeneClick offers a powerful tool for field-based SARS-CoV-2 detection in primary healthcare institutions or at-home use.

Multi-Analyte Discriminated ECL via Photonic Crystal-Enhanced Selectivity.

Electrochemiluminescence (ECL) has numerous merits such as high sensitivity and specificity for the detection applications on pharmacy, food safety, immunoassay, disease diagnosis, environmental monitoring, nucleic acid assay, and clinical treatment. However, the insufficiency of ECL luminescent reagents is restricting their adoption on complex systems or multi-analyte detections. In this work, to improve the selectivity and discrimination of ECL detection with one or less luminescent reagent, we employed multi-stopband photonic crystals (PCs) to enhance assigned ECL. The discrimination of ECL was well investigated to establish the quantitative description with PC stopbands. The multi-stopband PC electrode can facilely achieve 10 antibiotics qualitative and quantitative analysis with 100% accuracy and 0.44 µM LOD in PBS buffer and human serum. The selectivity of ECL detection for multi-analytes can be improved via designed PC luminescence amplifications. The exploration on PC selectivity for ECL enhancement will promote the realistic application of the ECL technique and contribute to the facile and efficient optical platform for clinical or health monitoring.

Development of multiscale ultra-coarse-grained models for the SARS-CoV-2 virion from cryo-electron microscopy data.

The global spread of the new coronavirus COVID-19 has seriously affected human health and has caused a large number of deaths. Using molecular dynamics (MD) simulations to study the microscopic dynamic behavior of the virion provides an important means to study the pathogenic mechanism. In this work, we develop an ultra-coarse-grained (UCG) model of the SARS-CoV-2 virion from the authentic cryo-electron microscopy data, which enables MD simulation of the entire virion within microseconds. In addition, a hybrid all-atom and UCG (AA/UCG) virion model involving an all-atom spike protein is developed for the investigation of the spike protein interactions. A comparison of the conformational changes for the spike proteins as simulated in the hybrid model and that isolated in solution as in the free form reveals that the former is completely different from the latter. The simulation results demonstrate the necessity for the development of multiscale models to study the functions of proteins in the biomolecular complexes.

A rapid and highly sensitive multiple detection of human adenovirus type 3, type 7 and respiratory syncytial virus by recombinase-aided reverse transcription PCR.

BACKGROUND: Polymerase chain reaction (PCR) has been widely used for many pathogen detection. However, PCR technology still suffers from long detection time and insufficient sensitivity. Recombinase-aided amplification (RAA) is a powerful nucleic acid detection tool with high sensitivity and amplification efficiency, but its complex probes and inability of multiplex detection hinder the further application of this technology. METHODS: In this study, we developed and validated the multiplex reverse transcription recombinase-aided PCR (multiplex RT-RAP) assay for human adenovirus 3 (HADV3), human adenovirus 7 (HADV7), and human respiratory syncytial virus (HRSV) within 1 h with Human RNaseP protein as a reference gene to monitor the whole process. RESULTS: Using recombinant plasmids, the sensitivity of multiplex RT-RAP for the detection of HADV3, HADV7, and HRSV was 18, 3, and 18 copies per reaction, respectively. The multiplex RT-RAP showed no cross-reactivity with other respiratory viruses, demonstrating its good specificity. A total of 252 clinical specimens were tested by multiplex RT-RAP and the results were found to be consistent with those of corresponding RT-qPCR assays. After testing serial dilutions of selected positive specimens, the detection sensitivity of multiplex RT-RAP was two to eightfold higher than that of corresponding RT-qPCR. CONCLUSION: We conclude the multiplex RT-RAP is a robust, rapid, highly sensitive, and specific assay with the potential to be used in the screening of clinical samples with low viral load.

Multiplex LNA probe-based RAP assay for rapid and highly sensitive detection of rifampicin-resistant Mycobacterium tuberculosis.

Objectives: The World Health Organization (WHO) Global tuberculosis Report 2021 stated that rifampicin-resistant tuberculosis (RR-TB) remains a major public health threat. However, the in-practice diagnostic techniques for RR-TB have a variety of limitations including longer time, lack of sensitivity, and undetectable low proportion of heterogeneous drug resistance. Methods: Here we developed a multiplex LNA probe-based RAP method (MLP-RAP) for more sensitive detection of multiple point mutations of the RR-TB and its heteroresistance. A total of 126 clinical isolates and 78 sputum samples collected from the National Tuberculosis Reference Laboratory, China CDC, were tested by MLP-RAP assay. In parallel, qPCR and Sanger sequencing of nested PCR product assay were also performed for comparison. Results: The sensitivity of the MLP-RAP assay could reach 5 copies/µl using recombinant plasmids, which is 20 times more sensitive than qPCR (100 copies/µl). In addition, the detection ability of rifampicin heteroresistance was 5%. The MLP-RAP assay had low requirements (boiling method) for nucleic acid extraction and the reaction could be completed within 1 h when placed in a fluorescent qPCR instrument. The result of the clinical evaluation showed that the MLP-RAP method could cover codons 516, 526, 531, and 533 with good specificity. 41 out of 78 boiled sputum samples were detected positive by MLP-RAP assay, which was further confirmed by Sanger sequencing of nested PCR product assay, on the contrary, qPCR was able to detect 32 samples only. Compared with Sanger sequencing of nested PCR product assay, both the specificity and sensitivity of the MLP-RAP assay were 100%. Conclusion: MLP-RAP assay can detect RR-TB infection with high sensitivity and specificity, indicating that this assay has the prospect of being applied for rapid and sensitive RR-TB detection in general laboratories where fluorescent qPCR instrument is available.

Touchable Gustation via a Hoffmeister Gel Iontronic Sensor.

A particular sense, touchable gustation, was achieved. We proposed a chemical-mechanical interface strategy with an iontronic sensor device. A conductive hydrogel, amino trimethylene phosphonic acid (ATMP) assisted poly(vinyl alcohol) (PVA), was employed as the dielectric layer of the gel iontronic sensor. The Hofmeister effect of the ATMP-PVA hydrogel was well investigated to establish the quantitative description of the gel elasticity modulus to chemical cosolvents. The mechanical properties of hydrogels can be transduced extensively and reversibly by regulating the aggregation state of polymer chains with hydrated ions or cosolvents. Scanning electron microscopy (SEM) images of ATMP-PVA hydrogel microstructures stained with different soaked cosolvents present different networks. The information on different chemical components will be stored in the ATMP-PVA gels. The flexible gel iontronic sensor with a hierarchical pyramid structure performed high linear sensitivity of 3224.2 kPa-1 and wide pressure response in the range of 0-100 kPa. The finite element analysis proved the pressure distribution at the gel interface of the gel iontronic sensor and the capacitation-stress response relation. Various cations, anions, amino acids, and saccharides can be discriminated, classified, and quantified with the gel iontronic sensor. The Hofmeister effect regulated chemical-mechanical interface performs the response and conversion of biological/chemical signals into electrical output in real time. The particular function to tactile with gustation percept will contribute promising applications in the human-machine interaction, humanoid robot, clinic treatment, or athletic training optimization.

Rapid two-stage amplification in a single tube for simultaneous detection of norovirus GII and group a rotavirus.

The most prevalent viruses currently causing diarrhea are norovirus and rotavirus, and rapid and sensitive detection methods are essential for the early diagnosis of disease. The purpose of this study was to establish a sensitive single-tube two-stage nucleic acid amplification method-reverse transcription recombinase-assisted PCR (RT-RAP)-for simultaneous detection of norovirus GII and group A Rotavirus, with the first stage consisting of isothermal reverse transcription recombinase-aided amplification (RT-RAA) and the second stage consisting of qPCR (quantitative PCR). RT-RAP is more sensitive than either RT-RAA or qRT-PCR (quantitative RT-PCR) alone. And the addition of a barrier that can be disassembled after heating enabled the detection of samples within 1 h in a single closed tube. Sensitivity was 10 copies/reaction of norovirus (Novs) GII and group A rotavirus (RVA). In parallel, two hundred fecal specimens were used to evaluate the method and compare it with a commercial fluorescent quantitative RT-PCR. The data showed kappa values of 0.957 and 0.98 (p < 0.05) for detecting Novs GII and RVA by the two methods, indicating the potential of the newly established assay to be applied to clinical and laboratory testing.

Cactus-Inspired Photonic Crystal Chip for Attomolar Fluorescence Multi-analysis.

Automation and efficiency requirements of environmental monitoring are the pursuit of spontaneous sampling and ultrasensitivity for current sensory systems or detection apparatuses. In this work, inspired by cactus hierarchical structures, we develop a cactus-inspired photonic crystal chip to integrate spontaneous droplet sampling and fluorescence enhancement for sensitive multi-analyte detection. A conical hydrophilic pattern on hydrophobic surfaces can give rise to unidirectional Laplace pressure, which drives droplet transport to the assigned photonic crystal site. The nanostructure of photonic crystals has bigger capillarity to drive the droplet wetting uniformly into the photonic crystal matrix while performing prominent fluorescence enhancement by their photonic bandgap. A low to attomolar (2.24 × 10-19 M) fluorescence limit of detection (LOD) sensitivity can be achieved by the synergy of spontaneous droplet sampling and fluorescence enhancement. Focused on eutrophic water problems and algae pollution monitoring, a femtomolar (1.83 × 10-15 M) LOD and identification of various microcystins in urban environmental water can be achieved. The suitable integration of the unidirectional droplet transport by Laplace pressure and fluorescence enhancement by photonic crystals can achieve the spontaneous sampling and signal enhancement for ultratrace detections and sample survey of environmental monitoring and disease diagnosis.

Explainable Deep Learning-Assisted Photochromic Sensor for ß-Lactam Antibiotic Identification.

Photochromic sensors have the advantages of diverse isomers for multi-analysis, providing more sensing information and possessing more recognition units and more sensitivity to external stimulations, but they present enormous complexity with various stimulations as well. Deep learning (DL) algorithms contribute a huge advantage at analyzing nonlinear and multidimensional data, but they suffer from nontransparent inner networks, "black-boxes". In this work, we employed the explainable DL approach to process and explicate photochromic sensing. Spirooxazine metallic complexes were adopted to prepare a multi-state analysis array for ß-Lactams identification and quantitation. A dataset of 2520 unduplicated fluorescence intensity images was collected for convolutional neural network (CNN) operation. The method clearly discriminated six ß-Lactams with 97.98% prediction accuracy and allowed rapid quantification with a concentration range from 1 to 100 mg/L. The photochromic sensing mechanism was verified via molecular simulation and class activation mapping, which explicated how the CNN model assesses the importance of photochromic sensor states and makes a discrimination decision. The explainable DL-assisted analysis method establishes an end-to-end strategy to ascertain and verify the complicated sensing mechanism for device optimization and even new scientific discovery.

Clinical characteristics of second primary malignancies among first primary malignancy survivors: A single-center study, 2005-2020.

The cancer survivor population is growing due to advances in detection and treatment. For improved long-term patient management, it is critical to examine the clinical characteristics and outcomes of second primary malignancies (SPMs). An SPM is defined as a second distinct pathological diagnosis, with the same or different origin as the first primary malignancy (FPM). In the present retrospective study, categorical clinical variables were compared between subgroups and the impact on overall survival was evaluated. A total of 1,188 patients with an FPM were included, of which 102 experienced an SPM (8.59%). When compared with the patients who did not develop an SPM, patients with an SPM were significantly older at first diagnosis, had a higher pathological stage and higher rates of biliary tract disease and thyroid disease. In addition, patients with an SPM were more likely to have received postoperative chemotherapy (28.43 vs. 12.16%, P<0.0001) and to be long-term consumers of cigarettes and alcohol (25.00 vs. 8.95%, P<0.05). In addition, an increase in the number of regimens received but not in the number of courses of chemotherapy was associated with a reduction in the time interval to SPM development. Non-small cell lung cancer (NSCLC) was the most common type of FPM (18.27%). In patients with NSCLC the occurrence of SPMs was relatively low (5.07%) and the SPM-associated mortality rate was 2.30%. Breast cancer was the second common type of FPM (12.09%). Patients with breast cancer had a relatively high likelihood of developing an SPM (9.30%), for which family history of malignancy and postoperative chemotherapy were identified as potential risk factors. Patients with stomach cancer were the most vulnerable to SPM (17.95%) and patients with digestive tract cancer had the longest time interval between the FPM and SPM development. In addition, thyroid adenoma was identified as a potential risk factor for SCLC. The findings of the present study may provide valuable guidance for the short- and long-term monitoring of FPM survivors.