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The B-box (BBX) family, which is a class of zinc finger transcription factors, exhibits special roles in plant growth and development as well as in plants’ ability to cope with various stresses. Even though Rubus chingii is an important traditional medicinally edible plant in east Asia, there are no comprehensive studies of BBX members in R. chingii. In this study, 32 RcBBX members were identified, and these were divided into five groups. A collinearity analysis showed that gene duplication events were common, and when combined with a motif analysis of the RcBBX genes, it was concluded that group V genes might have undergone deletion of gene fragments or mutations. Analysis of cis-acting elements revealed that each RcBBX gene contained hormone-, light-, and stress-related elements. Expression patterns of the 32 RcBBX genes during fruit ripening revealed that highest expression occurred at the small green fruit stage. Of note, the expression of several RcBBX genes increased rapidly as fruit developed. These findings, combined with the expression profiles of anthocyanin biosynthetic genes during fruit ripening, allowed us to identify the nuclear-targeted RcBBX26, which positively promoted anthocyanin production in R. chingii. The collective findings of this study shed light on the function of RcBBX genes in different tissues, developmental stages, and in response to two abiotic stresses.

Drought stress (DS) is one of the important abiotic stresses facing cash crops today. Drought can reduce plant growth and development, inhibit photosynthesis, and thus reduce plant yield. In this experiment, we investigated the protective mechanism of AMF on plant photosynthetic system by inoculating Paris polyphylla var. yunnanensis(P.py) with a clumping mycorrhizal fungus (AMF) under drought conditions. The drought environment was maintained by weighing AMF plants and non-AMF plants. The relative water content (RWC) of plant leaves was measured to determine its drought effect. DS decreased the RWC of plants, but AMF was able to increase the RWC of plants. chlorophyll a fluorescence curve measurements revealed that DS increased the OKJIP curve of plants, but AMF was able to reduce this trend, indicating that AMF increased the light absorption capacity of plants. DS also caused a decrease in plant Y(I) and Y(II). ETRI and ETRII, and increased Y(NO) and Y(NA) in plants, indicating that DS caused photosystem damage in plants. For the same host, different AMFs did not help to the same extent, but all AMFs were able to help plants reduce this damage and contribute to the increase of plant photosynthesis under normal water conditions.

Abstract A strong correlation between NOS2 and COX2 tumor expression and poor clinical outcomes in ER breast cancer has been established. However, the mechanisms of tumor induction of these enzymes are unclear. Analysis of The Cancer Genome Atlas (TCGA) revealed correlations between NOS2 and COX2 expression and Th1 cytokines. Herein, single-cell RNAseq analysis of TNBC cells shows potent NOS2 and COX2 induction by IFNγ combined with IL1β or TNFα. Given that IFNγ is secreted by cytolytic lymphocytes, which improve clinical outcomes, this role of IFNγ presents a dichotomy. To explore this conundrum, tumor NOS2, COX2, and CD8+ T cells were spatially analyzed in aggressive ER–, TNBC, and HER2 + breast tumors. High expression and clustering of NOS2-expressing tumor cells occurred at the tumor/stroma interface in the presence of stroma-restricted CD8+ T cells. High expression and clustering of COX2-expressing tumor cells extended into immune desert regions in the tumor core where CD8+ T cell penetration was limited or absent. Moreover, high NOS2-expressing tumor cells were proximal to areas with increased satellitosis, suggestive of cell clusters with a higher metastatic potential. Further in vitro experiments revealed that IFNγ + IL1β/TNFα increased the elongation and migration of treated tumor cells. This spatial analysis of the tumor microenvironment provides important insight into distinct neighborhoods where stroma-restricted CD8+ T cells exist proximal to NOS2-expressing tumor niches that could have increased metastatic potential.

Summary: Thyroid nodules are a common disease, and fine needle aspiration cytology (FNAC) is the primary method to assess their malignancy. For the diagnosis of follicular thyroid nodules, however, FNAC has limitations. FNAC can classify them only as Bethesda IV nodules, leaving their exact malignant status and pathological type undetermined. This imprecise diagnosis creates difficulties in selecting the follow-up treatment. In this retrospective study, we collected ultrasound (US) image data of Bethesda IV thyroid nodules from 2006 to 2022 from five hospitals. Then, US image-based artificial intelligence (AI) models were trained to identify the specific category of Bethesda IV thyroid nodules. We tested the models using two independent datasets, and the best AI model achieved an area under the curve (AUC) between 0.90 and 0.95, demonstrating its potential value for clinical application. Our research findings indicate that AI could change the diagnosis and management process of Bethesda IV thyroid nodules.

Abstract Protein diversity due to alternative mRNA splicing or post-translational modifications (PTMs) plays a vital role in various cellular functions. The mitotic kinases polo-like kinase 1 (PLK1) and Aurora B (AURKB) phosphorylate survivin, an inhibitor of apoptosis (IAP) family member, thereby regulating cell proliferation. PLK1, AURKB, and survivin are overexpressed in triple-negative breast cancer (TNBC), an aggressive breast cancer subtype. TNBC is associated with high proliferative capacity, high rates of distant metastasis, and treatment resistance. The proliferation-promoting protein survivin and its activating kinases, PLK1 and AURKB, are overexpressed in TNBC. In this study, we investigated the role of survivin phosphorylation in racial disparities in TNBC cell proliferation. Analysis of TCGA TNBC data revealed higher expression levels of PLK1 (P = 0.026) and AURKB (P = 0.045) in African Americans (AAs; n = 41) than in European Americans (EAs; n = 86). In contrast, no significant racial differences in survivin mRNA or protein levels were observed. AA TNBC cells exhibited higher p-survivin levels than EA TNBC cells. Survivin silencing using small interfering RNAs significantly attenuated cell proliferation and cell cycle progression in AA TNBC cells, but not in EA TNBC cells. In addition, PLK1 and AURKB inhibition with volasertib and barasertib significantly inhibited the growth of AA TNBC xenografts, but not of EA TNBC tumors. These data suggest that inhibition of PLK1 and AURKB suppresses cell proliferation and tumor growth, specifically in AA TNBC. These findings suggest that targeting survivin phosphorylation may be a viable therapeutic option for AA patients with TNBC.

Mandarin is vulnerable to a range of external loads during processing and shipping, which can cause interior mechanical damage that can happen right away or over time and cause serious rotting when kept in storage. In this study, mandarin was treated to a certain quantity of compression load that did not result in a noticeable rupture of the peel. The interior pulp structure of mandarin was examined for damage prior to peel damage using CT scanning and image reconstruction. An image segmentation method based on mask processing was then used to calculate the pulp damage rate. We examined the variations in physiological activities and internal components between the test group that underwent compression load and the control group that did not undergo this type of stress during storage. The aim was to investigate the factors that contributed to the faster decay of mandarin following mechanical damage. Regression analysis was also used to establish a quantifiable relationship between the amount of compression deformation and the rates of damage and decay of mandarin during storage. The findings demonstrated that mandarin pulp exhibited visible mechanical damage when compression deformation exceeded 8 mm. This led to the disruption of physiological processes like respiration and polysaccharide breakdown, which in turn decreased the hardness of the fruit and sped up its rotting. This study identifies the critical range of compression deformation that leads to the beginning of pulp damage in mandarins. Additionally, it clarifies the quality deterioration mechanism of mandarins that have been subjected to compression damage during the storage period. Therefore, in practical production, various methods of picking, sorting, and collecting mandarins can be optimized to control the amount of compression deformation within a suitable range. This will reduce the probability of pulp damage. According to the study’s conclusions, storage conditions can be optimized to regulate the physiological activities of mandarins in a targeted manner. This can minimize the probability of fruit decay and reduce economic losses.

Salinity is a serious environmental problem following a worsening trend. This study investigates the role of 24-epibrassinolide(EBR) in regulating plant growth and physiological performances, particularly in alleviating the negative effects of salt stress. Melia azedarach L. seedlings from two seed sources, Sheyang (SY) and Xiashu (XS), were exposed to sea salt and treated with different concentrations of EBR within a 60-day period. The results demonstrate that appropriate EBR application improved the seedlings’ stress tolerance by promoting growth and physiological systems. In terms of the relative increment, it showed that a difference of 1.45% and 1.13% in the SY and XS groups was the positive effect of the highest EBR treatment concentration. As for diameter growth, the difference observed was 2.51% and 1.80% for the SY and XS groups, respectively. In all physiological measurements, including the content of photosynthetic pigments, water relations, membrane stability, osmolytes and antioxidant enzymes, significant changes generally observed between salt stress alone and the highest EBR treatment concentration. A better performance was observed in the SY seed source, which is of a coastal nature. These findings contribute to our understanding of Melia azedarach’s adaptation to changing environments and provide potential for further molecular studies as well as valuable insights for forestry, agricultural and ecological research.

As an MFI-type zeolite, ZSM-5 zeolite has wide applications in industry, such as in the fine chemical, petrochemical, and coal chemical industries. However, shape control of ZSM-5 nanocrystals constitutes one of the major challenges of current nanotechnology. Here, the MFI framework structure was used as the theoretical model of pure silicon ZSM-5 to investigate the surface energy and Wulff shape. The models with different crystal surfaces were simulated by molecular dynamics (MD) with the assistance of machine learning potentials (MLPs). The factors influencing the crystal surface energy, such as temperature, pH, and ionic concentration, have been studied in detail. Depending on the calculated surface energies, the crystal surface morphology and its ratio were obtained by means of the Wulff theorem. The results show that the area in the equilibrium shape of the (110) surface is usually the largest, and its proportion varies with external conditions. A high temperature and high concentration of the aluminum source promoted the growth of the (110) crystal surface, and the theoretical value of the crystal surface ratio was as high as 90%. This study provides theoretical insight into the synthesis of zeolites with different morphologies of all-silicon or low-aluminum.

Abstract We present a multiscale agent-based model of ductal carcinoma in situ (DCIS) to study how key phenotypic and signaling pathways are involved in the early stages of disease progression. The model includes a phenotypic hierarchy, and key endocrine and paracrine signaling pathways, and simulates cancer ductal growth in a 3D lattice-free domain. In particular, by considering stochastic cell dedifferentiation plasticity, the model allows for study of how dedifferentiation to a more stem-like phenotype plays key roles in the maintenance of cancer stem cell populations and disease progression. Through extensive parameter perturbation studies, we have quantified and ranked how DCIS is sensitive to perturbations in several key mechanisms that are instrumental to early disease development. Our studies reveal that long-term maintenance of multipotent stem-like cell niches within the tumor are dependent on cell dedifferentiation plasticity, and that disease progression will become arrested due to dilution of the multipotent stem-like population in the absence of dedifferentiation. We have identified dedifferentiation rates necessary to maintain biologically relevant multipotent cell populations, and also explored quantitative relationships between dedifferentiation rates and disease progression rates, which may potentially help to optimize the efficacy of emerging anti-cancer stem cell therapeutics.

BackgroundOncotype DX Recurrence Score (RS) has been widely used to predict chemotherapy benefits in patients with estrogen receptor-positive breast cancer. Studies showed that the features used in Magee equations correlate with RS. We aimed to examine whether deep learning (DL)-based histology image analyses can enhance such correlations.MethodsWe retrieved 382 cases with RS diagnosed between 2011 and 2015 from the Emory University and the Ohio State University. All patients received surgery. DL models were developed to detect nuclei of tumor cells and tumor-infiltrating lymphocytes (TILs) and segment tumor cell nuclei in hematoxylin and eosin (H&E) stained histopathology whole slide images (WSIs). Based on the DL-based analysis, we derived image features from WSIs, such as tumor cell number, TIL number variance, and nuclear grades. The entire patient cohorts were divided into one training set (125 cases) and two validation sets (82 and 175 cases) based on the data sources and WSI resolutions. The training set was used to train the linear regression models to predict RS. For prediction performance comparison, we used independent variables from Magee features alone or the combination of WSI-derived image and Magee features.ResultsThe Pearson’s correlation coefficients between the actual RS and predicted RS by DL-based analysis were 0.7058 (p-value = 1.32 × 10–13) and 0.5041 (p-value = 1.15 × 10–12) for the validation sets 1 and 2, respectively. The adjusted R2 values using Magee features alone are 0.3442 and 0.2167 in the two validation sets, respectively. In contrast, the adjusted R2 values were enhanced to 0.4431 and 0.2182 when WSI-derived imaging features were jointly used with Magee features.ConclusionOur results suggest that DL-based digital pathological features can enhance Magee feature correlation with RS.

Abstract Metaplastic breast cancer (MpBC) is an exceedingly rare breast cancer variant that is therapeutically challenging and aggressive. MpBC is defined by the histological presence of at least two cellular types, typically epithelial and mesenchymal components. This variant harbors a triple-negative breast cancer (TNBC) phenotype, yet has a worse prognosis and decreased survival compared to TNBC. There are currently no standardized treatment guidelines specifically for MpBC. However, prior studies have found that MpBC typically has molecular alterations in epithelial-to-mesenchymal transition, amplification of epidermal growth factor receptor, PI3K/Akt signaling, nitric oxide signaling, Wnt/β-catenin signaling, altered immune response, and cell cycle dysregulation. Some of these molecular alterations have been studied as therapeutic targets, in both the preclinical and clinical setting. This current review discusses the histological organization and cellular origins of MpBC, molecular alterations, the role of radiation therapy, and current clinical trials for MpBC.

Malignant adenomyoepithelioma is a rare mammary malignancy that arises from malignant transformation of adenomyoepithelioma. Due to the rarity of this entity, the diagnostic criteria are vague and knowledge about this entity mainly comes from case reports and small case series studies. In this review, we will summarize its clinicopathologic features, pathogenesis, prognosis, and treatment based on published literature.

Summary: Identifying biomarkers to predict the clinical outcomes of individual patients is a fundamental problem in clinical oncology. Multiple single-gene biomarkers have already been identified and used in clinics. However, multiple oncogenes or tumor-suppressor genes are involved during the process of tumorigenesis. Additionally, the efficacy of single-gene biomarkers is limited by the extensively variable expression levels measured by high-throughput assays. In this study, we hypothesize that in individual tumor samples, the disruption of transcription homeostasis in key pathways or gene sets plays an important role in tumorigenesis and has profound implications for the patient's clinical outcome. We devised a computational method named iPath to identify, at the individual-sample level, which pathways or gene sets significantly deviate from their norms. We conducted a pan-cancer analysis and demonstrated that iPath is capable of identifying highly predictive biomarkers for clinical outcomes, including overall survival, tumor subtypes, and tumor-stage classifications. Motivation: Abundant single-gene biomarkers have been identified and used in clinics. However, hundreds of oncogenes or tumor-suppressor genes are involved during the process of tumorigenesis, and the efficacy of single-gene biomarkers might be hampered by the extensively variable expression levels measured by high-throughput assays. In this study, we devised a computational method named iPath to identify prognostic biomarker pathways, one sample at a time. To test its utility, we conducted a pan-cancer analysis across 14 cancer types from The Cancer Genome Atlas and demonstrated that iPath is capable of identifying highly predictive biomarkers for clinical outcomes, including overall survival, tumor subtypes, and tumor-stage classifications. We found that pathway-based biomarkers are more robust and effective than single genes.

Selective hydrogenations of lignin-derived phenolic compounds represent essential processes in the chemical industry, especially for production of a multitude of fine chemicals. However, selective hydrogenation of phenolic compounds in water phase suffers from low conversion. Here we report a catalyst of well-dispersed Ru clusters fixed in N-doped mesoporous hollow carbon spheres (Ru@N-CS) for enhanced cyclohexanol productivity in phenol hydrogenation at mild aqueous condition. This superhydrophobicity carbon spheres appear to selectively allow diffusion of phenol and hydrogen molecules to the electron-rich coordination unsaturated Ru active sites, while confining the reactants there to enhance its reaction probability. The Ru@N-CS catalyst can selectively hydrogenate phenol at 80 °C and 0.5 MPa of H2 in 30 min in aqueous medium with phenol conversions of 100% and ~100% cyclohexanol selectivity, corresponding to cyclohexanol productivity up to 471 per g of Ru per minute. The TOF value is up to 9980 h−1, which 14 times more than Ru nanoparticles supported on N-doped carbon hollow spheres (Ru/N-CS). This work provides an important catalytic system for upgrading of bio-oil into value-added chemicals under mild aqueous-phase.

Abstract Background Neoadjuvant dual human epidermal growth factor receptor (HER2) blockade with trastuzumab and pertuzumab plus paclitaxel leads to an overall pathologic complete response (pCR) rate of 46%. Dual HER2 blockade with ado-trastuzumab emtansine (T-DM1) and lapatinib plus nab-paclitaxel has shown efficacy in patients with metastatic HER2-positive breast cancer. To test neoadjuvant effectiveness of this regimen, an open-label, multicenter, randomized, phase II trial was conducted comparing T-DM1, lapatinib, and nab-paclitaxel with trastuzumab, pertuzumab, and paclitaxel in patients with early-stage HER2-positive breast cancer. Methods Stratification by estrogen receptor (ER) status occurred prior to randomization. Patients in the experimental arm received 6 weeks of targeted therapies (T-DM1 and lapatinib) followed by T-DM1 every 3 weeks, lapatinib daily, and nab-paclitaxel weekly for 12 weeks. In the standard arm, patients received 6 weeks of trastuzumab and pertuzumab followed by trastuzumab weekly, pertuzumab every 3 weeks, and paclitaxel weekly for 12 weeks. The primary objective was to evaluate the proportion of patients with residual cancer burden (RCB) 0 or I. Key secondary objectives included pCR rate, safety, and change in tumor size at 6 weeks. Hypothesis-generating correlative assessments were also performed. Results The 30 evaluable patients were well-balanced in patient and tumor characteristics. The proportion of patients with RCB 0 or I was higher in the experimental arm (100% vs. 62.5% in the standard arm, p = 0.0035). In the ER-positive subset, all patients in the experimental arm achieved RCB 0-I versus 25% in the standard arm (p = 0.0035). Adverse events were similar between the two arms. Conclusion In early-stage HER2-positive breast cancer, the neoadjuvant treatment with T-DM1, lapatinib, and nab-paclitaxel was more effective than the standard treatment, particularly in the ER-positive cohort. Trial registration Clinicaltrials.gov NCT02073487, February 27, 2014.

The High Throughput Truthing project aims to develop a dataset for validating artificial intelligence and machine learning models (AI/ML) fit for regulatory purposes. The context of this AI/ML validation dataset is the reporting of stromal tumor-infiltrating lymphocytes (sTILs) density evaluations in hematoxylin and eosin-stained invasive breast cancer biopsy specimens. After completing the pilot study, we found notable variability in the sTILs estimates as well as inconsistencies and gaps in the provided training to pathologists. Using the pilot study data and an expert panel, we created custom training materials to improve pathologist annotation quality for the pivotal study. We categorized regions of interest (ROIs) based on their mean sTILs density and selected ROIs with the highest and lowest sTILs variability. In a series of eight one-hour sessions, the expert panel reviewed each ROI and provided verbal density estimates and comments on features that confounded the sTILs evaluation. We aggregated and shaped the comments to identify pitfalls and instructions to improve our training materials. From these selected ROIs, we created a training set and proficiency test set to improve pathologist training with the goal to improve data collection for the pivotal study. We are not exploring AI/ML performance in this paper. Instead, we are creating materials that will train crowd-sourced pathologists to be the reference standard in a pivotal study to create an AI/ML model validation dataset. The issues discussed here are also important for clinicians to understand about the evaluation of sTILs in clinical practice and can provide insight to developers of AI/ML models.

Imaging techniques based on fluorescence and bioluminescence have been important tools in visualizing tumor progression and studying the effect of drugs and immunotherapies on tumor immune microenvironment in animal models of cancer. However, transgenic expression of foreign proteins may induce immune responses in immunocompetent syngeneic tumor transplant models and augment the efficacy of experimental drugs. In this study, we show that the growth rate of Lewis lung carcinoma (LL/2) tumors was reduced after transduction of tdTomato and luciferase (tdTomato/Luc) compared to the parental cell line. tdTomato/Luc expression by LL/2 cells altered the tumor microenvironment by increasing tumor-infiltrating lymphocytes (TILs) while inhibiting tumor-induced myeloid-derived suppressor cells (MDSCs). Interestingly, tdTomato/Luc expression did not alter the response of LL/2 tumors to anti-PD-1 and anti-CTLA-4 antibodies. These results suggest that the use of tdTomato/Luc-transduced cancer cells to conduct studies in immune competent mice may lead to cell-extrinsic tdTomato/Luc-induced alterations in tumor growth and tumor immune microenvironment that need to be taken into consideration when evaluating the efficacy of anti-cancer drugs and vaccines in immunocompetent animal models.

Background: The anti-programmed cell death protein-1 (PD-1) inhibitor is one of the second-line therapies for advanced hepatocellular carcinoma (HCC) after sorafenib failure. The goal of this study is to evaluate the feasibility and safety of ablation on the tumor in patients with advanced HCC who had stable disease or atypical response during single anti-PD-1 therapy after sorafenib failure. Atypical response defined as mixed responses in different lesions of the same individual (e.g., active or stable lesions mixed with progressive lesions).Patients and Methods: This proof-of-concept clinical trial enrolled 50 patients treated with an anti-PD-1 inhibitor of nivolumab or pembrolizumab monotherapy between July 2015 and Nov 2017. Thirty-three cases with stable disease or atypical response to anti-PD-1 inhibitor received subtotal thermal ablation. The safety and the response of ablation during anti-PD-1 therapy were evaluated. The survival was estimated by the Kaplan-Meier curve.Results: Of all 50 patients treated with anti-PD-1 therapy, the rate of response, stable disease, atypical and typical progression were 10% (n = 5), 42% (n = 21) 32% (n = 16), and 12% (n = 6), respectively. Additional ablation improved efficacy with tolerable toxicity, and the response rate was increased from 10 to 24% (12/50). The median time to progression, progression-free survival, and overall survival was 6.1 months (95%CI, 2.6–11.2), 5 months (95%CI, 2.9–7.1), and 16.9 months (95%CI, 7.7–26.1), respectively.Conclusions: This proof-of-concept trial suggested that additional ablation may increase the objective response rate with tolerated toxicity and achieved a relatively better median survival, in advanced HCC patients who had stable or atypical progressive diseases during anti-PD-1 therapy, which may provide a potentially promising strategy to treat advanced HCC.Trial registration number:ClinicalTrials.gov identifier: NCT03939975.

A series of biomass-derived platform molecules, such as glucose, furans, levulinic acid, 5-hydroxymethylfurfural, and acetic acids, can be converted into a variety of value-added chemicals through catalytic transformations that include dehydration, hydrogenation, oxidation, isomerization, reforming, ketonization, and aldol condensation over heterogeneous catalysts. Aqueous-phase processing is an important issue and a great challenge for the heterogeneous catalytic conversion of biobased chemicals due to the high water content of the biomass and the formation of water during the transformation process. In this paper, heterogeneous catalysts that are applicable to the aqueous-phase conversion process of biomass platform chemicals, including noble metal catalysts, non-noble metal catalysts, bimetallic catalysts, metal oxides, and zeolite, are introduced, and a comprehensive evaluation of the catalyst performance, including the catalytic activity, stability, and regeneration performance of different kinds of heterogeneous catalysts, are made. Besides, we highlighted the effect of water on heterogeneous catalysts and the deactivation mechanism in the aqueous phase. Beyond this, several catalytic mechanisms of aqueous-phase conversion over heterogeneous catalysts are summarized in order to help understand the reaction process on the surface of catalysts in the aqueous phase, so as to design targeted catalysts. At last, a prospect of biobased chemicals and fuels is forecasted.

Paris polyphylla Smith var. yunnanensis (Franch.) Hand.-Mazz. is a rhizomatous, herbaceous, perennial plant that has been used for more than a thousand years in traditional Chinese medicine. It is facing extinction due to overharvesting. Steroids are the major therapeutic components in Paris roots, the commercial value of which increases with age. To date, no genomic data on the species have been available. In this study, transcriptome analysis of an 8-year-old root and a 4-year-old root provided insight into the metabolic pathways that generate the steroids. Using Illumina sequencing technology, we generated a high-quality sequence and demonstrated de novo assembly and annotation of genes in the absence of prior genome information. Approximately 87,577 unique sequences, with an average length of 614 bases, were obtained from the root cells. Using bioinformatics methods, we annotated approximately 65.51% of the unique sequences by conducting a similarity search with known genes in the National Center for Biotechnology Information's non-redundant database. The unique transcripts were functionally classified using the Gene Ontology hierarchy and the Kyoto Encyclopedia of Genes and Genomes database. Of 3082 genes that were identified as significantly differentially expressed between roots of different ages, 1518 (49.25%) were upregulated and 1564 (50.75%) were downregulated in the older root. Metabolic pathway analysis predicted that 25 unigenes were responsible for the biosynthesis of the saponins steroids. These data represent a valuable resource for future genomic studies on this endangered species and will be valuable for efforts to genetically engineer P. polyphylla and facilitate saponin-rich plant development.

Failure to achieve pathologic complete response is associated with poor prognosis in breast cancer patients following neoadjuvant chemotherapy (NACT). However, prognostic biomarkers for clinical outcome are unclear in this patient population. Cyclin-dependent kinase 9 (CDK9) is often dysregulated in breast cancer, and its deficiency results in genomic instability. We reviewed the records of 84 breast cancer patients from Emory University’s Winship Cancer Institute who had undergone surgical resection after NACT and had tissue available for tissue microarray analysis (TMA). Data recorded included disease presentation, treatment, pathologic response, overall survival (OS), locoregional recurrence free survival (LRRFS), distant-failure free survival (DFFS), recurrence-free survival (RFS), and event-free survival (EFS). Immunohistochemistry was performed on patient samples to determine CDK9 expression levels after NACT. Protein expression was linked with clinical data to determine significance. In a Cox proportional hazards model, using a time-dependent covariate to evaluate the risk of death between groups beyond 3 years, high CDK9 expression was significantly associated with an increase in OS (HR: 0.26, 95% CI: 0.07-0.98, p=0.046). However, Kaplan-Meier curves for OS, LRRFS, DFFS, RFS, and EFS did not reach statistical significance. The results of this study indicate that CDK9 may have a potential role as a prognostic biomarker in patients with breast cancer following NACT. However, further validation studies with increased sample sizes are needed to help elucidate the prognostic role for CDK9 in the management of these patients.

Clinical studies have revealed a higher risk of breast tumor recurrence in African-American (AA) patients compared to European-American (EA) patients, contributing to the alarming inequality in clinical outcomes among the ethnic groups. However, distinctions in recurrence patterns upon receiving hormone, radiation, and/or chemotherapy between the races remain poorly characterized.We compared patterns and rates (per 1000 cancer patients per 1 year) of recurrence following each form of treatment between AA (n = 1850) and EA breast cancer patients (n = 7931) from a cohort of patients (n = 10504) treated between 2005-2015 at Northside Hospital in Atlanta, GA.Among patients who received any combination of adjuvant therapy, AA displayed higher overall rates of recurrence than EA (p = 0.015; HR: 1.699; CI: 1.108-2.606). Furthermore, recurrence rates were higher in AA than EA among stage I (p = 0.031; HR: 1.736; CI: 1.052-2.864) and T1 classified patients (p = 0.003; HR: 2.009; CI: 1.263-3.197). Interestingly, among patients who received neoadjuvant chemotherapy, AA displayed higher rates of local recurrence than EA (p = 0.024; HR: 7.134; CI: 1.295-39.313).Our analysis revealed higher incidence rates of recurrence in AA compared to EA among patients that received any combination of adjuvant therapy. Moreover, our data demonstrates an increased risk of tumor recurrence in AA than EA among patients diagnosed with minimally invasive disease. This is the first clinical study to suggest that neoadjuvant chemotherapy improves breast cancer recurrence rates and patterns in AA.

Context.--Inflammatory lesions of the breast are rare but not infrequently pose problems both clinically and morphologically, particularly on needle core biopsies. These lesions range from acute inflammatory conditions to chronic lymphoplasmacytic and lymphohistiocytic to granulomatous inflammatory diseases. Objective.--To provide a comprehensive overview of inflammatory lesions of the breast, with etiopathogenesis and clinical, radiologic, and pathologic features as well as differential diagnostic considerations, clinical management, and prognosis. Data Sources.--The existing literature in the English language, including original research articles and review articles describing inflammatory lesions of the breast. Conclusions.--Inflammatory lesions of the breast are characterized by a wide variety of clinical, radiologic, and morphologic features. The histopathologic differential diagnosis often includes a neoplastic process requiring ancillary studies and correlation with clinical and radiologic findings. Although most specimens display nonspecific findings precluding a definitive pathologic diagnosis, pathologists have a unique opportunity to play a crucial role in identifying key histologic features suggestive of certain entities, such as cystic neutrophilic granulomatous mastitis, immunoglobulin (Ig) G4 mastitis, or squamous metaplasia of lactiferous ducts, in the right clinical and radiologic context, and thereby guiding optimal and timely clinical management. The information presented herein will be helpful to practicing anatomic pathologists and pathology trainees in becoming more familiar with specific morphologic features and overcoming differential diagnostic challenges related to pathology reporting of inflammatory lesions of the breast. [ABSTRACT FROM AUTHOR]

Abstract Cutting-edge mid-wavelength infrared (MWIR) sensing technologies leverage infrared photodetectors, memory units, and computing units to enhance machine vision. Real-time processing and decision-making challenges emerge with the increasing number of intelligent pixels. However, current operations are limited to in-sensor computing capabilities for near-infrared technology, and high-performance MWIR detectors for multi-state switching functions are lacking. Here, we demonstrate a non-volatile MoS2/black phosphorus (BP) heterojunction MWIR photovoltaic detector featuring a semi-floating gate structure design, integrating near- to mid-infrared photodetection, memory and computing (PMC) functionalities. The PMC device exhibits the property of being able to store a stable responsivity, which varies linearly with the stored conductance state. Significantly, device weights (stable responsivity) can be programmed with power consumption as low as 1.8 fJ, and the blackbody peak responsivity can reach 1.68 A/W for the MWIR band. In the simulation of Faster Region with convolution neural network (CNN) based on the FLIR dataset, the PMC hardware responsivity weights can reach 89% mean Average Precision index of the feature extraction network software weights. This MWIR photovoltaic detector, with its versatile functionalities, holds significant promise for applications in advanced infrared object detection and recognition systems.