Advanced Multifunctional Hydrogels for Enhanced Wound Healing through Ultra-Fast Selenol-SNAr Chemistry.

Fabrication of versatile hydrogels in a facile and effective manner represents a pivotal challenge in the field of biomaterials. Herein, a novel strategy is presented for preparing on-demand degradable hydrogels with multilevel responsiveness. By employing selenol-dichlorotetrazine nucleophilic aromatic substitution (SNAr) to synthesize hydrogels under mild conditions in a buffer solution, the necessity of additives or posttreatments can be obviated. The nucleophilic and redox reactions between selenol and tetrazine culminate in the formation of three degradable chemical bonds-diselenide, aryl selenide, and dearomatized selenide-in a single, expeditious step. The resultant hydrogel manifests exceptional adaptability to intricate environments in conjunction with self-healing and on-demand degradation properties. Furthermore, the resulting material demonstrated light-triggered antibacterial activity. Animal studies further underscore the potential of integrating metformin into Se-Tz hydrogels under green light irradiation, as it effectively stimulates angiogenesis and collagen deposition, thereby fostering efficient wound healing. In comparison to previously documented hydrogels, Se-Tz hydrogels exhibit controlled degradation and drug release, outstanding antibacterial activity, mechanical robustness, and bioactivity, all without the need for costly and intricate preparation procedures. These findings underscore Se-Tz hydrogels as a safe and effective therapeutic option for diabetic wound dressings.

Innovative Biomaterials for Bone Tumor Treatment and Regeneration: Tackling Postoperative Challenges and Charting the Path Forward.

Surgical resection of bone tumors is the primary approach employed in the treatment of bone cancer. Simultaneously, perioperative interventions, particularly postoperative adjuvant anticancer strategies, play a crucial role in achieving satisfactory therapeutic outcomes. However, the occurrence of postoperative bone tumor recurrence, metastasis, extensive bone defects, and infection are significant risks that can result in unfavorable prognoses or even treatment failure. In recent years, there has been significant progress in the development of biomaterials, leading to the emergence of new treatment options for bone tumor therapy and bone regeneration. This progress report aims to comprehensively analyze the strategic development of unique therapeutic biomaterials with inherent healing properties and bioactive capabilities for bone tissue regeneration. These composite biomaterials, classified into metallic, inorganic non-metallic, and organic types, are thoroughly investigated for their responses to external stimuli such as light or magnetic fields, internal interventions including chemotherapy or catalytic therapy, and combination therapy, as well as their role in bone regeneration. Additionally, an overview of self-healing materials for osteogenesis is provided and their potential applications in combating osteosarcoma and promoting bone formation are explored. Furthermore, the safety concerns of integrated materials and current limitations are addressed, while also discussing the challenges and future prospects.

A Promising Application of Injectable Hydrogels in Nerve Repair and Regeneration for Ischemic Stroke.

Ischemic stroke, a condition that often leads to severe nerve damage, induces complex pathological and physiological changes in nerve tissue. The mature central nervous system (CNS) lacks intrinsic regenerative capacity, resulting in a poor prognosis and long-term neurological impairments. There is no available therapy that can fully restore CNS functionality. However, the utilization of injectable hydrogels has emerged as a promising strategy for nerve repair and regeneration. Injectable hydrogels possess exceptional properties, such as biocompatibility, tunable mechanical properties, and the ability to provide a supportive environment for cell growth and tissue regeneration. Recently, various hydrogel-based tissue engineering approaches, including cell encapsulation, controlled release of therapeutic factors, and incorporation of bioactive molecules, have demonstrated great potential in the treatment of CNS injuries caused by ischemic stroke. This article aims to provide a comprehensive review of the application and development of injectable hydrogels for the treatment of ischemic stroke-induced CNS injuries, shedding light on their therapeutic prospects, challenges, recent advancements, and future directions. Additionally, it will discuss the underlying mechanisms involved in hydrogel-mediated nerve repair and regeneration, as well as the need for further preclinical and clinical studies to validate their efficacy and safety.

Autophagy-modulating biomembrane nanostructures: A robust anticancer weapon by modulating the inner and outer cancer environment.

Recently, biomembrane nanostructures, such as liposomes, cell membrane-coated nanostructures, and exosomes, have demonstrated promising anticancer therapeutic effects. These nanostructures possess remarkable biocompatibility, multifunctionality, and low toxicity. However, their therapeutic efficacy is impeded by chemoresistance and radiotherapy resistance, which are closely associated with autophagy. Modulating autophagy could enhance the therapeutic sensitivity and effectiveness of these biomembrane nanostructures by influencing the immune system and the cancer microenvironment. For instance, autophagy can regulate the immunogenic cell death of cancer cells, antigen presentation of dendritic cells, and macrophage polarization, thereby activating the inflammatory response in the cancer microenvironment. Furthermore, combining autophagy-regulating drugs or genes with biomembrane nanostructures can exploit the targeting and long-term circulation properties of these nanostructures, leading to increased drug accumulation in cancer cells. This review explores the role of autophagy in carcinogenesis, cancer progression, metastasis, cancer immune responses, and resistance to treatment. Additionally, it highlights recent research advancements in the synergistic anticancer effects achieved through autophagy regulation by biomembrane nanostructures. The review also discusses the prospects and challenges associated with the future clinical translation of these innovative treatment strategies. In summary, these findings provide valuable insights into autophagy, autophagy-modulating biomembrane-based nanostructures, and the underlying molecular mechanisms, thereby facilitating the development of promising cancer therapeutics.

Biomembrane-Derived Nanoparticles in Alzheimer's Disease Therapy: A Comprehensive Review of Synthetic Lipid Nanoparticles and Natural Cell-Derived Vesicles.

Current therapies for Alzheimer's disease used in the clinic predominantly focus on reducing symptoms with limited capability to control disease progression; thus, novel drugs are urgently needed. While nanoparticles (liposomes, high-density lipoprotein-based nanoparticles) constructed with synthetic biomembranes have shown great potential in AD therapy due to their excellent biocompatibility, multifunctionality and ability to penetrate the BBB, nanoparticles derived from natural biomembranes (extracellular vesicles, cell membrane-based nanoparticles) display inherent biocompatibility, stability, homing ability and ability to penetrate the BBB, which may present a safer and more effective treatment for AD. In this paper, we reviewed the synthetic and natural biomembrane-derived nanoparticles that are used in AD therapy. The challenges associated with the clinical translation of biomembrane-derived nanoparticles and future perspectives are also discussed.

Extracellular vesicle biopotentiated hydrogels for diabetic wound healing: The art of living nanomaterials combined with soft scaffolds.

Diabetic wounds (DWs) pose a major challenge for the public health system owing to their high incidence, complex pathogenesis, and long recovery time; thus, there is an urgent need to develop innovative therapies to accelerate the healing process of diabetic wounds. As natural nanovesicles, extracellular vesicles (EVs) are rich in sources with low immunogenicity and abundant nutritive molecules and exert potent therapeutic effects on diabetic wound healing. To avoid the rapid removal of EVs, a suitable delivery system is required for their controlled release. Owing to the advantages of high porosity, good biocompatibility, and adjustable physical and chemical properties of hydrogels, EV biopotentiated hydrogels can aid in achieving precise and favorable therapy against diabetic wounds. This review highlights the different design strategies, therapeutic effects, and mechanisms of EV biopotentiated hydrogels. We also discussed the future challenges and opportunities of using EV biopotentiated hydrogels for diabetic wound healing.

Algae: A Robust Living Material Against Cancer.

Cancer is the second leading cause of death worldwide. Its incidence has been increasing in recent years, and it is becoming a major threat to human health. Conventional cancer treatment strategies, including surgery, chemotherapy, and radiotherapy, have faced problems such as drug resistance, toxic side effects and unsatisfactory therapeutic efficacy. Therefore, better development and utilization of biomaterials can improve the specificity and efficacy of tumor therapy. Algae, as a novel living material, possesses good biocompatibility. Although some reviews have elucidated several algae-based biomaterials for cancer treatment, the majority of the literature has focused on a limited number of algae. As a result, there is currently a lack of comprehensive reviews on the subject of anticancer algae. This review aims to address this gap by conducting a thorough examination of algal species that show potential for anticancer activity. Furthermore, our review will also elucidate the engineering strategies of algae and discuss the challenges and prospects associated with their implementation.

Biomembrane nanostructures: Multifunctional platform to enhance tumor chemoimmunotherapy via effective drug delivery.

Chemotherapeutic drugs have been found to activate the immune response against tumors by inducing immunogenic cell death, in addition to their direct cytotoxic effects toward tumors, therefore broadening the application of chemotherapy in tumor immunotherapy. The combination of other therapeutic strategies, such as phototherapy or radiotherapy, could further strengthen the therapeutic effects of immunotherapy. Nanostructures can facilitate multimodal tumor therapy by integrating various active agents and combining multiple types of therapeutics in a single nanostructure. Biomembrane nanostructures (e.g., exosomes and cell membrane-derived nanostructures), characterized by superior biocompatibility, intrinsic targeting ability, intelligent responsiveness and immune-modulating properties, could realize superior chemoimmunotherapy and represent next-generation nanostructures for tumor immunotherapy. This review summarizes recent advances in biomembrane nanostructures in tumor chemoimmunotherapy and highlights different types of engineering approaches and therapeutic mechanisms. A series of engineering strategies for combining different biomembrane nanostructures, including liposomes, exosomes, cell membranes and bacterial membranes, are summarized. The combination strategy can greatly enhance the targeting, intelligence and functionality of biomembrane nanostructures for chemoimmunotherapy, thereby serving as a stronger tumor therapeutic method. The challenges associated with the clinical translation of biomembrane nanostructures for chemoimmunotherapy and their future perspectives are also discussed.

Microwave-activated Cu-doped zirconium metal-organic framework for a highly effective combination of microwave dynamic and thermal therapy.

Percutaneous microwave ablation (PMA) is a thermoablative method used as a minimally invasive treatment for liver cancer. However, the application of PMA is limited by its insufficient ROS generation efficiency and thermal effects. Herein, a new microwave-activated Cu-doped zirconium metal-organic framework (MOF) (CuZr MOF) used for enhanced PMA has a significantly improved microwave sensitizing effect. Owing to the strong inelastic collisions between ions confined in numerous micropores, CuZr MOF has strong microwave sensitivity and high thermal conversion efficiency, which can significantly improve microwave thermal therapy (MTT). Moreover, because of the existence of Cu2+ ions, a further benefit of CuZr MOF is their Fenton-like activity, in particular, microwaves used as an excitation source for microwave dynamic therapy (MDT) can improve the Fenton-like reaction to maximize the synergistic effectiveness of cancer therapy. Importantly, CuZr MOF can inhibit the production of heat shock proteins (HSPs) by producing abundant ROS to enhance tumor destruction. Mechanistically, we found that CuZr MOF + MW treatment modulates ferroptosis-mediated tumor cell death by targeting the HMOX1/GPX4 axis. In summary, this study develops a novel CuZr MOF microwave sensitizer with great potential for synergistic treatment of liver cancer by MTT and MDT.

An end-to-end seizure prediction approach using long short-term memory network.

There are increasing epilepsy patients suffering from the pain of seizure onsets, and effective prediction of seizures could improve their quality of life. To obtain high sensitivity for epileptic seizure prediction, current studies generally need complex feature extraction operations, which heavily depends on the artificial experience (or domain knowledge) and is highly subjective. To address these issues, in this paper we propose an end-to-end epileptic seizure prediction approach based on the long short-term memory network (LSTM). In the new method, only the gamma band of raw electroencephalography (EEG) signals is extracted as network input directly for seizure prediction, thus avoiding subjective and expensive feature design process. Despite its simplicity, the proposed method achieves the mean sensitivity of 91.76% and false prediction rate (FPR) of 0.29/h on Children's Hospital Boston-MIT (CHB-MIT) scalp EEG Database, respectively, when identifying the preictal stage from the EEG signals. Furthermore, different from traditional methods that only consider the classification of preictal and interictal EEG, we introduce the postictal stage as an extra class in the proposed method. As a result, the performance of seizure prediction is further improved, obtaining a higher sensitivity of 92.17% and a low FPR of 0.27/h. The mean warning time is 44.46 min, which suggests that sufficient time is reserved for patients to take intervention measures by this prediction method.

Metal-Based Nanoparticles: A Prospective Strategy for Helicobacter pylori Treatment.

Helicobacter pylori (H. pylori) is an infectious pathogen and the leading cause of gastrointestinal diseases, including gastric adenocarcinoma. Currently, bismuth quadruple therapy is the recommended first-line treatment, and it is reported to be highly effective, with >90% eradication rates on a consistent basis. However, the overuse of antibiotics causes H. pylori to become increasingly resistant to antibiotics, making its eradication unlikely in the foreseeable future. Besides, the effect of antibiotic treatments on the gut microbiota also needs to be considered. Therefore, effective, selective, antibiotic-free antibacterial strategies are urgently required. Due to their unique physiochemical properties, such as the release of metal ions, the generation of reactive oxygen species, and photothermal/photodynamic effects, metal-based nanoparticles have attracted a great deal of interest. In this article, we review recent advances in the design, antimicrobial mechanisms and applications of metal-based nanoparticles for the eradication of H. pylori. Additionally, we discuss current challenges in this field and future perspectives that may be used in anti-H. pylori strategies.

Selenide-linked polydopamine-reinforced hybrid hydrogels with on-demand degradation and light-triggered nanozyme release for diabetic wound healing.

BACKGROUND: Multifunctional hydrogels with controllable degradation and drug release have attracted extensive attention in diabetic wound healing. This study focused on the acceleration of diabetic wound healing with selenide-linked polydopamine-reinforced hybrid hydrogels with on-demand degradation and light-triggered nanozyme release. METHODS: Herein, selenium-containing hybrid hydrogels, defined as DSeP@PB, were fabricated via the reinforcement of selenol-end capping polyethylene glycol (PEG) hydrogels by polydopamine nanoparticles (PDANPs) and Prussian blue nanozymes in a one-pot approach in the absence of any other chemical additive or organic solvent based on diselenide and selenide bonding-guided crosslinking, making them accessible for large-scale mass production. RESULTS: Reinforcement by PDANPs greatly increases the mechanical properties of the hydrogels, realizing excellent injectability and flexible mechanical properties for DSeP@PB. Dynamic diselenide introduction endowed the hydrogels with on-demand degradation under reducing or oxidizing conditions and light-triggered nanozyme release. The bioactivity of Prussian blue nanozymes afforded the hydrogels with efficient antibacterial, ROS-scavenging and immunomodulatory effects, which protected cells from oxidative damage and reduced inflammation. Further animal studies indicated that DSeP@PB under red light irradiation showed the most efficient wound healing activity by stimulating angiogenesis and collagen deposition and inhibiting inflammation. CONCLUSION: The combined merits of DSeP@PB (on-demand degradation, light-triggered release, flexible mechanical robustness, antibacterial, ROS-scavenging and immunomodulatory capacities) enable its high potential as a new hydrogel dressing that can be harnessed for safe and efficient therapeutics for diabetic wound healing.

Treatment with Mesenchymal Stem Cell-Derived Nanovesicle-Containing Gelatin Methacryloyl Hydrogels Alleviates Osteoarthritis by Modulating Chondrogenesis and Macrophage Polarization.

Osteoarthritis is a degenerative disorder that can severely affect joints, and new treatment strategies are urgently needed. Administration of mesenchymal stem cell (MSC)-derived exosomes is a promising therapeutic strategy in osteoarthritis treatment. However, the poor yield of exosomes is an obstacle to the use of this modality in the clinic. Herein, a promising strategy is developed to fabricate high-yield exosome-mimicking MSC-derived nanovesicles (MSC-NVs) with enhanced regenerative and anti-inflammatory capabilities. MSC-NVs are prepared using an extrusion approach and are found to increase chondrocyte and human bone marrow MSC differentiation, proliferation, and migration, in addition to inducing M2 macrophage polarization. Furthermore, gelatin methacryloyl (GelMA) hydrogels loaded with MSC-NVs (GelMA-NVs) are formulated, which exhibit sustained release of MSC-NVs and are shown to be biocompatible with excellent mechanical properties. In a mouse osteoarthritis model constructed by surgical destabilization of the medial meniscus (DMM), GelMA-NVs effectively ameliorate osteoarthritis severity, reduce the secretion of catabolic factors, and enhance matrix synthesis. Furthermore, GelMA-NVs induce M2 macrophage polarization and inflammatory response inhibition in vivo. The findings demonstrate that GelMA-NVs hold promise for osteoarthritis treatment through modulation of chondrogenesis and macrophage polarization.

Epileptic seizure prediction using successive variational mode decomposition and transformers deep learning network.

As one of the most common neurological disorders, epilepsy causes great physical and psychological damage to the patients. The long-term recurrent and unprovoked seizures make the prediction necessary. In this paper, a novel approach for epileptic seizure prediction based on successive variational mode decomposition (SVMD) and transformers is proposed. SVMD is extended to multidimensional form for time-frequency analysis of multi-channel signals. It could adaptively extract common band-limited intrinsic modes among all channels on different time scales by solving a variational optimization problem. In the proposed seizure prediction method, data are first decomposed into multiple modes on different time scales by multivariate SVMD, and then, irrelevant modes are removed for preprocessing. Finally, power spectrum of denoised data is input to a pre-trained bidirectional encoder representations from transformers (BERTs) for prediction. The BERT could identify the mode information related to epileptic seizures in time-frequency domain. It shows fair prediction performance on an intracranial EEG dataset with the average sensitivity of 0.86 and FPR of 0.18/h.

Nanosized concave pit/convex dot microarray for immunomodulatory osteogenesis and angiogenesis.

The immunomodulatory capability of biomaterials is of paramount importance for successful material-mediated bone regeneration. Particularly, the design of surface nano-topography can be leveraged to instruct immune reactions, yet the understanding of such "nano-morphology effect" is still very limited. Herein, highly ordered nano-concave pit (denoted as NCPit) and nano-convex dot (denoted as NCDot) microarrays with two different sizes were successfully constructed on a 316LSS surface via anodization and subsequently immersion-coating treatment, respectively. We, for the first time, comparatively investigated the interactions of NCPit and NCDot microarrays with RAW264.7 macrophages and their immunomodulatory impacts on osteogenesis and angiogenesis of human bone mesenchymal stem cells (hBMSCs) and human umbilical vein endothelial cells (HUVECs). NCDot microarrays induced macrophages towards M2 polarization with the higher expression level of anti-inflammatory markers (IL-10 and CD 206) and the lower level of pro-inflammatory markers (TNF-α, IL-1ß, IL-6 and CD 86) than those of the corresponding NCPit microarrays. During the process, the expressions of osteogenesis-related genes (Runx2, OPN and OCN) of hBMSCs, and angiogenesis-related genes (eNOS, HIF-1α, KDR and VEGF) of HUVECs were significantly upregulated by the NCDot microarray-modulating immune microenvironment of macrophages, and finally stimulated osteogenesis and angiogenesis. Thus, the prepared NCDot arrays were able to significantly promote osteo-/angiogenic activity by generating a more suitable immune microenvironment than NCPit arrays, offering substantial evidence for designing immunomodulatory biomaterials with specific microstructures and optimal bioactivity.

Effect of intermittent hypoxic training on hypoxia tolerance based on brain functional connectivity.

The difference of brain functional connectivity between hypoxic and normal states was studied. The impact of intermittent hypoxic training on the hypoxia tolerance of the brain was explored. Multivariable empirical mode decomposition was applied to extract common inherent modes of multichannel EEG adaptively instead of a priori selection of filter bandwidth, and the first two scales of intrinsic mode functions expressed the differences in brain connectivity. To quantify synchronization and search for consistent performance, coherence, phase locking value and synchronization likelihood were all utilized. Brain networks extracted from these synchronization measures all displayed that both local and global functional connectivity declined with increasing time in a hypoxic state. Furthermore, early hypoxia of the brain was represented on brain connectivity before mental fatigue was detected by conventional neurobehavioral evaluation. The decrease of connectivity tended to slow down in hypoxic conditions after training, which indicated that hypoxia tolerance strengthened because of the hypoxic training.

Identification of a stable major-effect QTL (Parth 2.1) controlling parthenocarpy in cucumber and associated candidate gene analysis via whole genome re-sequencing.

BACKGROUND: Parthenocarpy is an important trait for yield and quality in many plants. But due to its complex interactions with genetic and physiological factors, it has not been adequately understood and applied to breeding and production. Finding novel and effective quantitative trait loci (QTLs) is a critical step towards understanding its genetic mechanism. Cucumber (Cucumis sativus L.) is a typical parthenocarpic plant but the QTLs controlling parthenocarpy in cucumber were not mapped on chromosomes, and the linked markers were neither user-friendly nor confirmed by previous studies. Hence, we conducted a two-season QTL study of parthenocarpy based on the cucumber genome with 145 F2:3 families derived from a cross between EC1 (a parthenocarpic inbred line) and 8419 s-1 (a non-parthenocarpic inbred line) in order to map novel QTLs. Whole genome re-sequencing was also performed both to develop effective linked markers and to predict candidate genes. RESULTS: A genetic linkage map, employing 133 Simple Sequence Repeats (SSR) markers and nine Insertion/Deletion (InDel) markers spanning 808.1 cM on seven chromosomes, was constructed from an F2 population. Seven novel QTLs were identified on chromosomes 1, 2, 3, 5 and 7. Parthenocarpy 2.1 (Parth2.1), a QTL on chromosome 2, was a major-effect QTL with a logarithm of odds (LOD) score of 9.0 and phenotypic variance explained (PVE) of 17.0 % in the spring season and with a LOD score of 6.2 and PVE of 10.2 % in the fall season. We confirmed this QTL using a residual heterozygous line97-5 (RHL97-5). Effectiveness of linked markers of the Parth2.1 was validated in F3:4 population and in 21 inbred lines. Within this region, there were 57 genes with nonsynonymous SNPs/InDels in the coding sequence. Based on further combined analysis with transcriptome data between two parents, CsARF19, CsWD40, CsEIN1, CsPPR, CsHEXO3, CsMDL, CsDJC77 and CsSMAX1 were predicted as potential candidate genes controlling parthenocarpy. CONCLUSIONS: A major-effect QTL Parth2.1 and six minor-effect QTLs mainly contribute to the genetic architecture of parthenocarpy in cucumber. SSR16226 and Indel-T-39 can be used in marker-assisted selection (MAS) of cucumber breeding. Whole genome re-sequencing enhances the efficiency of polymorphic marker development and prediction of candidate genes.

Effect of intermittent hypoxic training on hypoxia tolerance based on single-channel EEG.

A single-channel algorithm was proposed in order to study effect of intermittent hypoxic training on hypoxia tolerance based on EEG pattern. EEG was decomposed by ensemble empirical mode decomposition into a finite number of intrinsic mode functions (IMFs) based on the intrinsic local characteristic time scale. Analytic amplitude, analytic frequency, and recurrence property quantified by recurrence quantification analysis were explored on IMFs, and the first two scales revealed difference between normal EEG and hypoxia EEG. Classification accuracy of hypoxia EEG and normal EEG could reach 67.8% before decline of neurobehavioral ability, which represented that hypoxia EEG pattern could be detected at an early stage. Classification accuracy of hypoxia EEG and normal EEG increased with time and deepened intensity of hypoxia was observed by regular shift of hypoxia EEG pattern with time in a three dimensional subspace. The reduced shift and classification accuracy after intermittent hypoxic training represented that hypoxia tolerance enhanced.

Noninvasive Blood Glucose Analysis Based on Near-Infrared Reflectance Spectroscopy.

Noninvasive glucose detection is highly required for more convenient and less pain glycaemic monitoring. Most of currently used methods are invasive. In this paper, a near-infrared reflectance spectroscopy (NIRS) is proposed to detect blood glucose to protect patient absent of pain. NIRS is a safe, simple and efficient technology applied in many fields. Experiments, based on Oral Glucose Tolerance Test (OGTT), were conducted to collect data modeling with partial least squares (PLS) regression. 42 samples of fingertip blood and palm were measured by commercially available blood glucose meter and NIRS separately at the same time. The glucose concentration range is between 5 and 12 mmol·L-1. With leave-one-out cross-validation, we obtained a result of root mean square error of cross-validation (RMSECV) of 1.16 mmol·L-1 for all the data. With the pre-processing methods of normalization and un-informative variables elimination reducing noise and eliminating some additional effects, we get a better result of 0.79 mmol·L-1. A RMSECV of 0.41 mmol·L-1 for individual modeling is much less than the total modeling. It has a broad application prospect in individual customization.

Optimal Sensor Selection for Classifying a Set of Ginsengs Using Metal-Oxide Sensors.

The sensor selection problem was investigated for the application of classification of a set of ginsengs using a metal-oxide sensor-based homemade electronic nose with linear discriminant analysis. Samples (315) were measured for nine kinds of ginsengs using 12 sensors. We investigated the classification performances of combinations of 12 sensors for the overall discrimination of combinations of nine ginsengs. The minimum numbers of sensors for discriminating each sample set to obtain an optimal classification performance were defined. The relation of the minimum numbers of sensors with number of samples in the sample set was revealed. The results showed that as the number of samples increased, the average minimum number of sensors increased, while the increment decreased gradually and the average optimal classification rate decreased gradually. Moreover, a new approach of sensor selection was proposed to estimate and compare the effective information capacity of each sensor.