Synergism of salvianolic acid B and ginsenoside Rg1 magnifies the therapeutic potency against ischemic stroke.

Even though considerable progress has been made to reduce insult, ischemic stroke is still a significant cause of mortality and morbidity in the world, and new therapeutic strategies are urgently needed. In the present study, the magnesium salt of salvianolic acid B (SalB) and ginsenoside Rg1 (Rg1) combination as a multicomponent strategy against stroke was evaluated. The synergistic effect of Sa1B and Rg1 was evaluated by Bliss independence analysis on the middle cerebral artery occlusion model. The infarct volume, neuroethology, cerebral structure, and neurocyte number were evaluated by 3,5-triphenyltetrazolium chloride staining, Longa score, Garcia score, hematoxylin-eosin staining, and Nissl staining, respectively. Metabolomics was used to search for potential biomarkers and explore the mechanism of Sa1B/Rg1. First, the superior effects of SalB/Rg1 than SalB or Rg1 at the same dose were evaluated. Compared with SalB ( P  < 0.001) or Rg1 ( P  < 0.01), SalB/Rg1 significantly decreased infarct volume through 3,5-triphenyltetrazolium chloride staining and protected the structural integrity of cortex and striatum. The superior effect of SalB/Rg1 on neurological behavior was also detected compared with SalB or Rg1 significantly. Accompanying behavioral improvement, a considerable increase of SalB/Rg1 on neurons detected by Nissl staining was found on the cortex compared with SalB ( P  < 0.05) or Rg1 ( P  < 0.01). Second, the synergistic effect between SalB and Rg1 was strictly verified by Bliss independence analysis ( P  < 0.01) based on infarct volume. Finally, alleviation of cerebral metabolic disorders may be the possible mechanism of SalB/Rg1. Our study provided a multicomponent strategy against ischemic stroke, with not only dose reduction but also improved efficacy relative to single agents.

Comparative study on the anti-inflammatory and protective effects of different oxygen therapy regimens on lipopolysaccharide-induced acute lung injury in mice.

Oxygen therapy after acute lung injury can regulate the inflammatory response and reduce lung tissue injury. However, the optimal exposure pressure, duration, and frequency of oxygen therapy for acute lung injury remain unclear. In the present study, after intraperitoneal injection of lipopolysaccharide in ICR mice, 1.0 atmosphere absolute (ATA) pure oxygen and 2.0 ATA hyperbaric oxygen treatment for 1 hour decreased the levels of proinflammatory factors (interleukin-1beta and interleukin-6) in peripheral blood and lung tissues. However, only 2.0 ATA hyperbaric oxygen increased the mRNA levels of anti-inflammatory factors (interleukin-10 and arginase-1) in lung tissue; 3.0 ATA hyperbaric oxygen treatment had no significant effect. We also observed that at 2.0 ATA, the anti-inflammatory effect of a single exposure to hyperbaric oxygen for 3 hours was greater than that of a single exposure to hyperbaric oxygen for 1 hour. The protective effect of two exposures for 1.5 hours was similar to that of a single exposure for 3 hours. These results suggest that hyperbaric oxygen alleviates lipopolysaccharide-induced acute lung injury by regulating the expression of inflammatory factors in an acute lung injury model and that appropriately increasing the duration and frequency of hyperbaric oxygen exposure has a better tissue-protective effect on lipopolysaccharide-induced acute lung injury. These results could guide the development of more effective oxygen therapy regimens for acute lung injury patients.

Degradation of emerging contaminants in synthetic hydrolyzed urine by UV/peracetic acid: Free radical chemistry, and toxicity analysis.

The ecological impact of emerging contaminants (ECs) in aquatic environments has raised concerns, particularly with regards to urine as a significant source of such contaminants in wastewater. The current investigation used the UV/Peracetic Acid (UV/PAA) processes, an innovative advanced oxidation technology, to effectively separate two emerging pollutants from urine at its source, namely, ciprofloxacin (CIP) and bisphenol A(BPA). The research findings demonstrate that the presence of the majority of characteristic ions has minimal impact on the degradation of ECs. However, in synthetic hydrolyzed urine, only NH4+ inhibits the degradation of two types of ECs, with a more pronounced effect observed on CIP degradation compared to BPA.The impact of halogen ions, specifically Cl- and I-, on the degradation of CIP in synthetic hydrolyzed urine was a complex phenomenon. When these two halogen ions are present individually, the generation of reactive halogen species (RHS) within the system enhances the degradation of CIP. However, when both types of ions coexist, the formation of diatomic radical species partially inhibits degradation. In terms of BPA degradation, while the production of reactive chlorine species (RCS) to some extent hinders the reaction rate, the generation of reactive iodine species (RIS) promotes the overall process. CIP undergoes fragmentation of the piperazine and quinoline rings, decarboxylation, defluorination reactions, as well as substitution reactions, leading to the formation of products with simplified structures. The degradation of BPA occurs gradually through hydroxyl and halogen substitution as well as isopropyl cleavage. The preliminary toxicity analysis confirmed that the presence of halogen ions in urine resulted in the formation of halogenated products in two types of ECs, albeit with an overall reduction in toxicity. The UV/PAA processes was considered to be an effective and relatively safe approach for the separation of ECs in urine.

Prostate Cancer Risk Stratification by Digital Histopathology and Deep Learning.

PURPOSE: Prostate cancer (PCa) represents a highly heterogeneous disease that requires tools to assess oncologic risk and guide patient management and treatment planning. Current models are based on various clinical and pathologic parameters including Gleason grading, which suffers from a high interobserver variability. In this study, we determine whether objective machine learning (ML)-driven histopathology image analysis would aid us in better risk stratification of PCa. MATERIALS AND METHODS: We propose a deep learning, histopathology image-based risk stratification model that combines clinicopathologic data along with hematoxylin and eosin- and Ki-67-stained histopathology images. We train and test our model, using a five-fold cross-validation strategy, on a data set from 502 treatment-naïve PCa patients who underwent radical prostatectomy (RP) between 2000 and 2012. RESULTS: We used the concordance index as a measure to evaluate the performance of various risk stratification models. Our risk stratification model on the basis of convolutional neural networks demonstrated superior performance compared with Gleason grading and the Cancer of the Prostate Risk Assessment Post-Surgical risk stratification models. Using our model, 3.9% of the low-risk patients were correctly reclassified to be high-risk and 21.3% of the high-risk patients were correctly reclassified as low-risk. CONCLUSION: These findings highlight the importance of ML as an objective tool for histopathology image assessment and patient risk stratification. With further validation on large cohorts, the digital pathology risk classification we propose may be helpful in guiding administration of adjuvant therapy including radiotherapy after RP.

Migration characteristics and risk assessment of chemical hazardous substances in infant teether toys.

Teether is a special toy used for infants oral contact. In this paper, a residual and migration detection method was developed using gas chromatography-tandem mass spectrometry for 20 screened hazardous substances in teethers. Fifteen substances were detected in 59 samples, with residual amounts and detection rates ranging from 0.01 mg⋅kg-1 to 106.15 mg⋅kg-1 and from 3.39 % to 84.7 % respectively. Then, 12 substances were detected in simulated saliva at migration levels ranging from 0.0143 mg⋅kg-1 to 20.03 mg⋅kg-1, with detection rates ranging from 1.69 % to 76.3 %. Statistically, the average migration rate of each substance ranged from 8.18 % to 53.28 % depending on the properties of the substance and the sample. The exposure risk of infants to teethers was evaluated separately for two age groups. The hazard quotient (HQ) and hazard index (HI) values for the analytes were higher in the 3-12-month age group than in the 12-24-month age group. The HQ values of triphenylphosphine oxide, benzocaine, and N-methylformanilide were relatively high, with averages of 1.2 × 10-2, 2.5 × 10-3, and 1.6 × 10-3, respectively, and the max HI of the 12 substances was 0.04. The HI and HQ values of the analytes were all below 1, indicating that the non-carcinogenic risks of analytes in teethers are at an acceptable level.

Toward Low-Carbon Rice Production in China: Historical Changes, Driving Factors, and Mitigation Potential.

Under the "Double Carbon" target, the development of low-carbon agriculture requires a holistic comprehension of spatially and temporally explicit greenhouse gas (GHG) emissions associated with agricultural products. However, the lack of systematic evaluation at a fine scale presents considerable challenges in guiding localized strategies for mitigating GHG emissions from crop production. Here, we analyzed the county-level carbon footprint (CF) of China's rice production from 2007 to 2018 by coupling life cycle assessment and the DNDC model. Results revealed a significant annual increase of 74.3 kg CO2-eq ha-1 in the average farm-based CF (FCF), while it remained stable for the product-based CF (PCF). The CF exhibited considerable variations among counties, ranging from 2324 to 20,768 kg CO2-eq ha-1 for FCF and from 0.36 to 3.81 kg CO2-eq kg-1 for PCF in 2018. The spatiotemporal heterogeneities of FCF were predominantly influenced by field CH4 emissions, followed by diesel consumption and soil organic carbon sequestration. Scenario analysis elucidates that the national total GHG emissions from rice production could be significantly reduced through optimized irrigation (48.5%) and straw-based biogas production (18.0%). Moreover, integrating additional strategies (e.g., advanced crop management, optimized fertilization, and biodiesel application) could amplify the overall emission reduction to 76.7% while concurrently boosting the rice yield by 11.8%. Our county-level research provides valuable insights for the formulation of targeted GHG mitigation policies in rice production, thereby advancing the pursuit of carbon-neutral agricultural practices.

Protective effects of a novel chimeric virus-like particle vaccine against virulent NDV and IBDV challenge.

Newcastle disease (ND) and infectious bursal disease (IBD) pose significant threats to the chicken industry, causing substantial economic losses. Currently, immunization through vaccination is the most effective strategy to prevent ND and IBD but currently used traditional vaccines, including inactivated or attenuated vaccines, face challenges in achieving a balance between immunogenicity and safety. To develop a green and efficient novel vaccine for ND and IBD, we developed a bivalent chimeric virus-like particle vaccine (ND-IBD cVLPs) displaying the ND virus (NDV) HN protein and the IBD virus (IBDV) VP2 protein based on the ND VLPs carrier platform and insect baculovirus expression system. This study aimed to evaluate the immunogenicity and protective efficacy of ND-IBD cVLPs in specific pathogen-free chickens. Chickens were immunized with 50 µg of purified ND-IBD cVLPs at 7 days old, boosted at 21 days old, and challenged at 42 days old. The results demonstrated that ND-IBD cVLPs stimulated highly effective hemagglutination inhibition antibody levels against NDV HN protein and enzyme-linked immunosorbent assay antibody levels against the IBDV VP2 protein. Furthermore, ND-IBD cVLPs provided complete protection against virulent NDV and IBDV challenges and mitigated pathological damage to the lung caused by NDV infection and the bursa of Fabricius caused by IBDV infection. These findings suggest that ND-IBD cVLPs hold promise as a safe and efficient novel vaccine candidate for the effective prevention of ND and IBD, extending the development of a foreign protein delivery platform of ND VLPs.

The diverse roles of halide ions in the degradation of bisphenol A via UV/peracetic acid process at different pH values: Radical chemistry, and transformation pathways.

UV/Peracetic Acid (UV/PAA), as an innovative advanced oxidation process (AOP), is employed to treat bisphenol A (BPA) in water through the generation of hydroxyl radicals (•OH) and carbon-centered radicals (R-C•). The impact of halide ions (Cl-; Br-; I-) on the efficiency of UV/PAA was investigated for the first time under varying pH levels. The presence of halide ions exerted an influence on the reactivity of •OH and R-C•, exhibiting varying degrees of impact across different pH conditions. It was discovered that pH exerts a significant influence on its efficiency, with optimal removal performance observed at a pH 9. The degradation of BPA was inhibited by Cl- through the generation of reactive chlorine species (RCS), which triggers the interconversion between •OH and R-C•. Reactive bromine species (RBS) were produced in the presence of Br-, facilitating BPA degradation and generating HOBr as a supplementary source of •OH radicals. I- primarily generate reactive iodine species (RIS) through photolysis, which facilitates the degradation of BPA. The transformation of BPA involves hydroxylation, demethylation, halogenation, and cleavage reactions to form various products and pathways. The toxicity test demonstrates that the UV/PAA treatment of BPA exhibits lower toxicity, thereby indicating its environmentally friendly.

Effects of subcutaneous immunotherapy in allergic rhinitis children sensitive to dust mites.

BACKGROUND: Subcutaneous immunotherapy (SCIT) is now the only treatment that can modify the natural course of allergic rhinitis (AR). However, not all children with AR benefit from SCIT. OBJECTIVE: To evaluate the efficacy of SCIT in dust-mites-induced AR children and explore correlative factors predicting treatment response to SCIT. METHODS: 225 children aged 4-17 years old with AR were recruited from January 2016 to September 2019, and monitored at baseline, 4, 12, and 24 months after the start of SCIT treatment. The visual-analogue-score (VAS) was used to assess the clinical symptoms. Multivariate binary logistic regression analyses and receiver operating characteristic curves were used to explore correlative factors in predicting the efficacy of SCIT. RESULTS: The significant declines in VAS started after 4 months of SCIT and continued to improve throughout the study compared with baseline. An increase in children's age (OR=0.688, 95%CI: 0.479-0.988) and those with allergic history (OR=0.097, 95%CI: 0.009-1.095) were negatively associated with the risk of poor efficacy. Polysensitized children were more likely to suffer poor efficacy (OR=15.511 95%CI: 1.319-182.355). The clinical response at month 4 (r=0.707) and month 12 (r=0.925) was related to that at month 24. The area under the curve (AUC) for improvement at month 4 and month 12 was 0.746 and 0.860, respectively. CONCLUSION: Our study confirmed the clinical efficacy of SCIT in AR children. Children with younger age, negative allergic history, and multiple allergens may predict a worse efficacy. The onset of action and the clinical response to SCIT in the second year can be predicted as early as by month 4.

Transcriptional regulator Sar regulates the multiple secretion systems in Xanthomonas oryzae.

Xanthomonas oryzae pv. oryzae (Xoo) is a notorious plant pathogen that causes leaf blight of rice cultivars. The pathogenic bacteria possess numerous transcriptional regulators to regulate various biological processes, such as pathogenicity in the host plant. Our previous study identified a new master regulator PXO_RS20790 that is involved in pathogenicity for Xoo against the host rice. However, the molecular functions of PXO_RS20790 are still unclear. Here, we demonstrate that transcriptional regulator Sar (PXO_RS20790) regulates multiple secretion systems. The RNA-sequencing analysis, bacterial one-hybrid assay, and electrophoretic mobility shift assay revealed that Sar enables binding of the promoters of the T1SS-related genes, the avirulence gene, raxX, and positively regulates these genes' expression. Meanwhile, we found that Sar positively regulated the T6SS-1 clusters but did not regulate the T6SS-2 clusters. Furthermore, we revealed that only T6SS-2 is involved in interbacterial competition. We also indicated that Sar could bind the promoters of the T3SS regulators, hrpG and hrpX, to activate these two genes' transcription. Our findings revealed that Sar is a crucial regulator of multiple secretion systems and virulence.

Regulatory Mechanisms of Heat Stress Response and Thermomorphogenesis in Plants.

As worldwide warming intensifies, the average temperature of the earth continues to increase. Temperature is a key factor for the growth and development of all organisms and governs the distribution and seasonal behavior of plants. High temperatures lead to various biochemical, physiological, and morphological changes in plants and threaten plant productivity. As sessile organisms, plants are subjected to various hostile environmental factors and forced to change their cellular state and morphological architecture to successfully deal with the damage they suffer. Therefore, plants have evolved multiple strategies to cope with an abnormal rise in temperature. There are two main mechanisms by which plants respond to elevated environmental temperatures. One is the heat stress response, which is activated under extremely high temperatures; the other is the thermomorphogenesis response, which is activated under moderately elevated temperatures, below the heat-stress range. In this review, we summarize recent progress in the study of these two important heat-responsive molecular regulatory pathways mediated, respectively, by the Heat Shock Transcription Factor (HSF)-Heat Shock Protein (HSP) pathway and PHYTOCHROME INTER-ACTING FACTOR 4 (PIF4) pathways in plants and elucidate the regulatory mechanisms of the genes involved in these pathways to provide comprehensive data for researchers studying the heat response. We also discuss future perspectives in this field.

Ethylene Response Factor LlERF110 Mediates Heat Stress Response via Regulation of LlHsfA3A Expression and Interaction with LlHsfA2 in Lilies (Lilium longiflorum).

Heat stress seriously affects the quality of cut lily flowers. The ethylene response factors (ERFs) participate in heat stress response in many plants. In this study, heat treatment increased the production of ethylene in lily leaves, and exogenous ethylene treatment enhanced the heat resistance of lilies. LlERF110, an important transcription factor in the ethylene signaling pathway, was found in the high-temperature transcriptome. The coding region of LlERF110 (969 bp) encodes 322 amino acids and LlERF110 contains an AP2/ERF typical domain belonging to the ERF subfamily group X. LlERF110 was induced by ethylene and was expressed constitutively in all tissues. LlERF110 is localized in the nucleus and has transactivation activity. Virus-induced gene silencing of LlERF110 in lilies reduced the basal thermotolerance phenotypes and significantly decreased the expression of genes involved in the HSF-HSP pathway, such as LlHsfA2, LlHsfA3A, and LlHsfA5, which may activate other heat stress response genes; and LlHsp17.6 and LlHsp22, which may protect proteins under heat stress. LlERF110 could directly bind to the promoter of LlHsfA3A and activate its expression according to the yeast one hybrid and dual-luciferase reporter assays. LlERF110 interacts with LlHsfA2 in the nucleus according to BiFC and the yeast two-hybrid assays. In conclusion, these results indicate that LlERF110 plays an important role in the basal thermotolerance of lilies via regulation of the HSF-HSP pathway, which could be the junction of the heat stress response pathway and the ethylene signaling pathway.

A new metal complex-templated silver iodobismuthate exhibiting photocurrent response and photocatalytic property.

An organic-inorganic hybrid silver iodobismuthate characteristic of the infrequent [Ag2BiI6L2] cluster (L = I or I3) and with a unique Ag/Bi molar ratio (2/1), namely, [Zn(bipy)3]2Ag2BiI6(I)1.355(I3)1.645 (bipy = 2,2'-bipyridine; 1), was solvothermally synthesized, and structurally, optically, and theoretically studied. Intriguingly, compound 1 exhibited semiconductor behavior with an optical band gap of 2.33 eV, which endowed it with excellent photoelectric and photocatalytic properties. Electronic structure calculations further revealed that the relative separate conduction band (CB) and valence band (VB) in compound 1 may be responsible for the good optical activity. This study also includes the Hirshfeld surface analyses, thermogravimetric measurements and X-ray photoelectron spectroscopy (XPS) characterization.

Precision Probiotics in Agroecosystems: Multiple Strategies of Native Soil Microbiotas for Conquering the Competitor Ralstonia solanacearum.

Ralstonia solanacearum (Rs), a soilborne phytopathogen, causes bacterial wilt disease in a broad range of hosts. Common approaches, for example, the direct reduction of the pathogen using classic single broad-spectrum probiotics, suffer from poor colonization efficiency, interference by resident microbiota, and nonnative-microorganism invasion. The soil microbiota plays an important role in plant health. Revealing the intrinsic linkage between the microbiome and the occurrence of disease and then applying it to agroecosystems for the precise control of soilborne diseases should be an effective strategy. Here, we surveyed the differences in the microbiome between healthy and diseased soils used for tomato planting across six climatic regions in China by using 16S rRNA amplicon and metagenomic sequencing. The roles of species associated with disease symptoms were further validated. Healthy soil possessed more diverse bacterial communities and more potential plant probiotics than diseased soil. Healthy soil simultaneously presented multiple strategies, including specifically antagonizing Rs, decreasing the gene expression of the type III secretion system of Rs, and competing for nutrition with Rs. Bacteria enriched in diseased samples promoted the progression of tomato bacterial wilt by strengthening the chemotaxis of pathogens. Therefore, Rs and its collaborators should be jointly combatted for disease suppression. Our research provides integrated insights into a multifaceted strategy for the biocontrol of tomato bacterial wilt based on the individual network of local microbiota. IMPORTANCE In the current work, the relationship between the soil microbiota and tomato bacterial wilt on a large scale offered us a comprehensive understanding of the disease. The delicate strategy of the microbiota in soil used for growing tomatoes to conquer the strong competitor, Rs, was revealed by microbiome research. The collaborators of Rs that coexist in a common niche with Rs strengthened our understanding of the pathogenesis of bacterial wilt. Bacteria enriched in healthy soil that antagonized pathogens with high specificity provide a novel view for ecofriendly probiotics mining. Our study offers new perspectives on soilborne-pathogen biocontrol in agroecosystems by decoding the rule of the natural ecosystem.

Price Prediction of Pu'er tea based on ARIMA and BP Models.

Pu'er tea is a Yunnan geographical indication product, and its brand value ranks first in China. At present, qualitative and quantitative methods with low prediction accuracy are used to predict price. In this paper, based on the current situation and industry characteristics, a differential autoregressive integrated moving average model (ARIMA) is used to predict the short-term price. From the perspective of macro and micro, back-propagation neural network model (BP) was established to predict the long-term price based on the weight ranking of 16 factors affecting the price by technique for order preference by similarity to ideal solution method (TOPSIS). The future price is predicted and analyzed, and then based on the empirical results, suggestions are put forward for the industry in terms of reducing production capacity, increasing consumer demand and combining with the publicity and promotion of Internet.

Chemical modification of bamboo activated carbon surface and its adsorption property of simultaneous removal of phosphate and nitrate.

Zr/CTAB/BAC was prepared by bamboo activated carbon (BAC) functionalised by zirconia chloride octahydrate (ZrOCl2·8H2O) and Cetyltrimethylammonium bromide (CTAB). The effects of temperature, time, Zr dosage and CTAB concentration on removing phosphate and nitrate (H2PO4- and NO3-) in wastewater were investigated. The structure of Zr/CTAB/BAC was characterized by SEM, BET, FTIR, XRD and TG, and the kinetics and thermodynamics of adsorption were discussed. The optimum preparation conditions were as follows: the modification temperature was 25 °C, the modification time was 4 h, the mass of the modifier Zr added was 0.40 g, and the concentration of the modifier CTAB was 0.6 mM. When the dosage of Zr/CTAB/BAC was in the range of 0.1 g-1.0 g, the removal efficiency of phosphate in simulated wastewater was between 59.32% and 99.42%, and the removal efficiency of nitrate was between 34.08% and 93.70%. Using NaOH as a regenerant, after four times adsorption and desorption experiments, the removal efficiency of phosphate and nitrate by Zr/CTAB/BAC can still reach more than 70%. The chemical adsorption was the primary cause of the adsorption, and the adsorption process was endothermic. Zr/CTAB/BAC had an obvious removal effect on phosphate and nitrate in water, which could be promoted to treat other anionic salts in sewage.

Patient-Generated Subjective Global Assessment (PG-SGA) predicts length of hospital stay in lung adenocarcinoma patients.

The prevalence of malnutrition is high among oncology patients in Northern China. Malnutrition is related to the longer hospital stay, and it can be used to predict the prognostic outcome of patients. This work focused on investigating the relationship of nutritional condition with the length of hospital stay (LOS) in Northern Chinese patients with lung adenocarcinoma (LUAD). The Patient-Generated Subjective Global Assessment (PG-SGA), Nutritional Risk Screening 2002 (NRS 2002) score, recent weight loss and BMI were assessed in a probabilistic sample of 389 LUAD patients without epidermal growth factor receptor (EGFR) mutations. This study collected the demographic and clinical features of patients in a prospective manner. Then, we examined the association of nutritional status with LOS among the population developing LUAD. According to the PG-SGA, 63 (16·3 %), 174 (44·7 %) and 78 (20·1 %) patients were at risk for undernutrition, moderate undernutrition and severe undernutrition, respectively. Nutritional risk was found in 141 (36·2 %) patients based on the NRS 2002. The average LOS for tumour patients in Northern China was 12·5 d. At admission, a risk of undernutrition or undernutrition according to the PG-SGA (P < 0·001), NRS 2002 (P < 0·001) and latest weight loss (P < 0·001) predicted the longer LOS. LOS was related to nutritional status and hospitalisation expenses (P < 0·001). LUAD patients who stayed in the ICU had a poorer nutritional status and a longer LOS (P < 0·001). In Northern Chinese patients with LUAD, a risk for undernutrition evaluated by the PG-SGA, the NRS 2002 and recent weight loss, but not BMI, could predict a longer LOS.

Breast Cancer Detection Using Multimodal Time Series Features From Ultrasound Shear Wave Absolute Vibro-Elastography.

In shear wave absolute vibro-elastography (S-WAVE), a steady-state multi-frequency external mechanical excitation is applied to tissue, while a time-series of ultrasound radio-frequency (RF) data are acquired. Our objective is to determine the potential of S-WAVE to classify breast tissue lesions as malignant or benign. We present a new processing pipeline for feature-based classification of breast cancer using S-WAVE data, and we evaluate it on a new data set collected from 40 patients. Novel bi-spectral and Wigner spectrum features are computed directly from the RF time series and are combined with textural and spectral features from B-mode and elasticity images. The Random Forest permutation importance ranking and the Quadratic Mutual Information methods are used to reduce the number of features from 377 to 20. Support Vector Machines and Random Forest classifiers are used with leave-one-patient-out and Monte Carlo cross-validations. Classification results obtained for different feature sets are presented. Our best results (95% confidence interval, Area Under Curve = 95%±1.45%, sensitivity = 95%, and specificity = 93%) outperform the state-of-the-art reported S-WAVE breast cancer classification performance. The effect of feature selection and the sensitivity of the above classification results to changes in breast lesion contours is also studied. We demonstrate that time-series analysis of externally vibrated tissue as an elastography technique, even if the elasticity is not explicitly computed, has promise and should be pursued with larger patient datasets. Our study proposes novel directions in the field of elasticity imaging for tissue classification.