Immune landscape in molecular subtypes of human papillomavirus-negative head and neck cancer.

Head and neck squamous cell carcinomas (HNSCC) remain a poorly understood disease clinically and immunologically. HPV is a known risk factor of HNSCC associated with better outcome, whereas HPV-negative HNSCC are more heterogeneous in outcome. Gene expression signatures have been developed to classify HNSCC into four molecular subtypes (classical, basal, mesenchymal, and atypical). However, the molecular underpinnings of treatment response and the immune landscape for these molecular subtypes are largely unknown. Herein, we described a comprehensive immune landscape analysis in three independent HNSCC cohorts (>700 patients) using transcriptomics data. We assigned the HPV- HNSCC patients into these four molecular subtypes and characterized the tumor microenvironment using deconvolution method. We determined that atypical and mesenchymal subtypes have greater immune enrichment and exhibit a T-cell exhaustion phenotype, compared to classical and basal subtypes. Further analyses revealed different B cell maturation and antibody isotypes enrichment patterns, and distinct immune microenvironment crosstalk in the atypical and mesenchymal subtypes. Taken together, our study suggests that treatments that enhances B cell activity may benefit patients with HNSCC of the atypical subtypes. The rationale can be utilized in the design of future precision immunotherapy trials based on the molecular subtypes of HPV- HNSCC.

Systematic evaluation of the predictive gene expression signatures of immune checkpoint inhibitors in metastatic melanoma.

Advances in immunotherapy, including immune checkpoint inhibitors (ICIs), have transformed the standard of care for many types of cancer including melanoma. ICIs have improved the overall outcome of melanoma patients; however, a significant proportion of patients suffer from primary or secondary tumor resistance. Therefore, there is an urgent need to develop predictive biomarkers to better select patients for ICI therapy. Numerous biomarkers that predict the response of melanoma to ICIs have been investigated, including biomarker signatures based on genomics or transcriptomics. Most of these predictive biomarkers have not been systematically evaluated across different cohorts to determine the reproducibility of these signatures in metastatic melanoma. We evaluated 28 previously published predictive biomarkers of ICIs based on gene expression signatures in eight previously published studies with available RNA-sequencing data in public repositories. We found that signatures related to IFN-γ-responsive genes, T and B cell markers, and chemokines in the tumor immune microenvironment are generally predictive of response to ICIs in these patients. In addition, we identified that these predictive biomarkers have higher predictive values in on-treatment samples as compared to pretreatment samples in metastatic melanoma. The most frequently overlapping genes among the top 18 predictive signatures were CXCL10, CXCL9, PRF1, RANTES, IFNG, HLA-DRA, GZMB, and CD8A. From gene set enrichment analysis and cell type deconvolution, we estimated that the tumors of responders were enriched with infiltrating cytotoxic T-cells and other immune cells and the upregulation of genes related to interferon-γ signaling. Conversely, the tumors of non-responders were enriched with stromal-related cell types such as fibroblasts and myofibroblasts, as well as enrichment with T helper 17 cell types across all cohorts. In summary, our approach of validating and integrating multi-omics data can help guide future biomarker development in the field of ICIs and serve the quest for a more personalized therapeutic approach for melanoma patients.

LncPSCA in the 8q24.3 risk locus drives gastric cancer through destabilizing DDX5.

Genome-wide association studies (GWAS) have identified multiple gastric cancer risk loci and several protein-coding susceptibility genes. However, the role of long-noncoding RNAs (lncRNAs) transcribed from these risk loci in gastric cancer development and progression remains to be explored. Here, we functionally characterize a lncRNA, lncPSCA, as a novel tumor suppressor whose expression is fine-regulated by a gastric cancer risk-associated genetic variant. The rs2978980 T > G change in an intronic enhancer of lncPSCA interrupts binding of transcription factor RORA, which down-regulates lncPSCA expression in an allele-specific manner. LncPSCA interacts with DDX5 and promotes DDX5 degradation through ubiquitination. Increased expression of lncPSCA results in low levels of DDX5, less RNA polymerase II (Pol II) binding with DDX5 in the nucleus, thus activating transcription of multiple p53 signaling genes by Pol II. These findings highlight the importance of functionally annotating lncRNAs in GWAS risk loci and the great potential of modulating lncRNAs as innovative cancer therapy.

Neoadjuvant endocrine therapy expands stromal populations that predict poor prognosis in estrogen receptor-positive breast cancer.

The tumor microenvironment (TME) is an important modulator of response and resistance to endocrine therapy in estrogen receptor alpha (ER) positive breast cancer. Endocrine therapy is highly effective at reducing tumor burden and preventing recurrence in most estrogen receptor alpha (ER) positive breast cancers. Existing drugs work either directly by targeting tumor-cell ER or indirectly by inhibiting estrogen production in stromal cells with aromatase inhibitors (AI). However, many stromal cells also express ER and the direct impact of endocrine therapies on ER + stromal cells remain unclear. In this study, we investigated how neoadjuvant endocrine therapy (NET) directly effects stromal cells by measuring changes in stomal components of the TME that favor tumor progression. We previously defined two major subsets of tumor-associated stromal cells (TASCs): CD146 positive/CDCP1 negative (TASCCD146 ), CD146 negative/CDCP1 positive (TASCCDCP1 ), and generated a differentially expressed genes list associated with each type. Here, we applied the TASC gene list for classification and an algorithm that estimates immune cell abundance (TIMEx) to METABRIC transcriptomic data for ER + breast cancer patients coupled with multiplex imaging and analysis of paired tissue samples pre- and post- NET with the AI exemestane. TASCCDCP1 composition predicted for decreased patient survival in the METABRIC cohort. Exemestane treatment significantly increased expression of TASCCDCP1 and decreased expression of TASCCD146 . The posttreatment shift toward TASCCDCP1 composition correlated with increased macrophage infiltration and increased CD8+ T-cell, B cell, and general stromal components. The effectiveness of NET is currently based solely on the reduction of ER+ breast cancer cells. Here, we show NET displays clear TME effects that promote the expansion of the less favorable TASCCDCP1 population which are correlated with TME remodeling and reshaping immune infiltration supportive of tumor progression. Our findings highlight the need to further understand the role of endocrine therapy on TME remodeling, tumor progression, and patient outcomes.

TIMEx: tumor-immune microenvironment deconvolution web-portal for bulk transcriptomics using pan-cancer scRNA-seq signatures.

SUMMARY: The heterogeneous cell types of the tumor-immune microenvironment (TIME) play key roles in determining cancer progression, metastasis and response to treatment. We report the development of TIMEx, a novel TIME deconvolution method emphasizing on estimating infiltrating immune cells for bulk transcriptomics using pan-cancer single-cell RNA-seq signatures. We also implemented a comprehensive, user-friendly web-portal for users to evaluate TIMEx and other deconvolution methods with bulk transcriptomic profiles. AVAILABILITY AND IMPLEMENTATION: TIMEx web-portal is freely accessible at http://timex.moffitt.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Abortion occurs during double fertilization and ovule development in Paeonia ludlowii.

Paeonia ludlowii (Stern & Taylor) D.Y.Hong, an endangered species, is indigenous to Tibet, China and propagated only by seed under natural conditions. Its natural reproduction is constrained by low fecundity. Excess seed abortion is a key factor restricting its natural reproduction, cultivation, introduction, and protection. Understanding the specific origin and occurrence of aborted ovules is important for the protection of offspring. Using serial sectioning analysis, we studied the process of pollination and fertilization of P. ludlowii and examined the characteristics of aborted ovules, developmental differences after flowering of normal and aborted ovules, and their ratios at different positions in P. ludlowii ovaries. During pollination, fertilization, and seed development, ovule abortion was frequent, with a random abortion position. There were three types of abortion, namely, abnormal pistil, sterile ovules, and embryo and endosperm abortions. Of these, embryo and endosperm abortions could be divided into early abortion and middle abortion. The early aborted ovules stopped growing on day 12, the endoblast and endosperm in the embryo sac aborted gradually. Furthermore, the shape of the embryo sac cavity changed. The volume of aborted ovules was significantly different from that of fertile ovules. At ripening, the external morphology of different types of aborted seeds was significantly different. The possible reasons for the abortion of the ovules are also discussed.

Implementation of a twin-beam state-based clock synchronization system with dispersion-free HOM feedback.

In the field of clock synchronization, the application of frequency-entangled source is a promising direction to improve accuracy and security. In this paper, we analyze the performance of the twin-beam state and the difference-beam state using a practical second-order interference-based scheme. The advantages of the twin-beam state are pointed out especially for the dispersion-free property of HOM interference in a long-distance clock transfer. With the introduction of dispersion-compensated material, our experimental system based on a twin-beam state achieves a clock accuracy at 4 ps with a time offset precision of 1.8 ps over 10 s acquisition time while the time deviation is 0.15 ps over an averaging time of 5500 s in a 22 km-long transmission. These properties exhibit a leading position compared with the current clock synchronization system using the same theoretical scheme and also competitive among the implementations using other second-order interference-based schemes.

Roles of fiber birefringence and Raman scattering in the spontaneous four-wave mixing process through birefringent fibers.

We investigate the impact of fiber birefringence and spontaneous Raman scattering on the properties of photon pairs that are generated by the spontaneous four-wave mixing process in birefringent fibers. Starting from the formulation of the theory of four-wave mixing, we show a theoretical model for a generated optical field with the consideration of the Raman scattering and a Gaussian-distributed pump. The theoretical model is then applied for deriving the closed expressions of the photon-pair spectral properties as a function of the fiber birefringence. Also, with the modeled Raman gain, we evaluate the reduction of the pair production rate due to the presence of the Raman effect as well as the contributions of the Raman-scattered photons over a broad wavelength range. The predictions are experimentally verified with a commercial polarization-maintaining fiber.

Construction of an integrated multi-layer textile for solar-driven steam generation.

Solar steam generation has widespread application in wastewater treatment, seawater desalination, liquid-liquid separation, and other fields, providing potential opportunities for producing fresh water. Up until now, most researchers in this field focused on enhancing the evaporation rate of the solar steam generation device. However, problems in terms of its portability and flexibility still exist when it comes to real application scenarios. Herein, we propose a novel, to the best of our knowledge, integrated multi-layer textile composed of reduced graphene oxide/cotton (RGO/cotton) fabric, cotton yarn, and polypropylene (PP) fabric for solar-driven steam generation. The evaporation rate obtained by the integrated multi-layer textile as prepared is ${0.83}\;{{\rm kg\cdot m}^{- 2}}\cdot{{\rm h}^{- 1}}$ under one sun solar radiation, which is 3.16 times higher than that of blank experiment and is superior to many previously reported works. Its remarkable evaporation performance is mainly attributed to the inherent multi-layer structures, where porous RGO/cotton fabric exhibits ultra-water vapor permeability, hydrophilic cotton yarn supplies water continuously, and low-density hydrophobic PP fabric hinders heat sustainably. Based on the results of application performance evaluation, the integrated multi-layer textile with scalable manufacturability, portability, durability, and flexibility is expected to boost the development of solar-driven steam generation.

The emerging role of microRNAs and long noncoding RNAs in drug resistance of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the fifth most common malignancy worldwide and the second most lethal human cancer. A portion of patients with advanced HCC can significantly benefit from treatments with sorafenib, adriamycin, 5-fluorouracil and platinum drugs. However, most HCC patients eventually develop drug resistance, resulting in a poor prognosis. The mechanisms involved in HCC drug resistance are complex and inconclusive. Human transcripts without protein-coding potential are known as noncoding RNAs (ncRNAs), including microRNAs (miRNAs), small nucleolar RNAs (snoRNAs), long noncoding RNAs (lncRNAs) and circular RNA (circRNA). Accumulated evidences demonstrate that several deregulated miRNAs and lncRNAs are important regulators in the development of HCC drug resistance which elucidates their potential clinical implications. In this review, we summarized the detailed mechanisms by which miRNAs and lncRNAs affect HCC drug resistance. Multiple tumor-specific miRNAs and lncRNAs may serve as novel therapeutic targets and prognostic biomarkers for HCC.

Development and validation of a rapid, selective, and sensitive LC-MS/MS method for simultaneous determination of D- and L-amino acids in human serum: application to the study of hepatocellular carcinoma.

A validated liquid chromatography-tandem mass spectrometry method was developed for the simultaneous determination of D- and L-amino acids in human serum. Under the optimum conditions, except for DL-proline, L-glutamine, and D-lysine, the enantioseparation of the other 19 enantiomeric pairs of proteinogenic amino acids and nonchiral glycine was achieved with a CROWNPAK CR-I(+) chiral column within 13 min. The lower limits of quantitation for L-amino acids (including glycine) and D-amino acids were 5-56.25 µM and 0.625-500 nM, respectively, in human serum. The intraday precision and interday precision for all the analytes were less than 15%, and the accuracy ranged from -12.84% to 12.37% at three quality control levels. The proposed method, exhibiting high rapidity, enantioresolution, and sensitivity, was successfully applied to the quantification of D- and L-amino acid levels in serum from hepatocellular carcinoma patients and healthy individuals. The serum concentrations of L-arginine, L-isoleucine, L-aspartate, L-tryptophan, L-alanine, L-methionine, L-serine, glycine, L-valine, L-leucine, L-phenylalanine, L-threonine, D-isoleucine, D-alanine, D-glutamate, D-glutamine, D-methionine, and D-threonine were significantly reduced in the hepatocellular carcinoma patients compared with the healthy individuals (P < 0.01). D-Glutamate and D-glutamine were identified as the most downregulated serum markers (fold change greater than 1.5), which deserves further attention in hepatocellular carcinoma research. Graphical abstract Simultaneous determination of D- and L-amino acids in human serum from hepatocellular carcinoma patients and healthy individuals. AA amino acid, HCC hepatocellular carcinoma, LC liquid chromatography, MS/MS tandem mass spectrometry, NC normal control, TIC total ion chromatogram.

The gene pair PRR11 and SKA2 shares a NF-Y-regulated bidirectional promoter and contributes to lung cancer development.

Head-to-head gene pairs represent a unique feature of gene organization in eukaryotes, accounting for >10% of genes in the human genome. Identification and functional analysis of such gene pairs is only in its infancy. Recently, we identified PRR11 as a novel cancer-related gene that is implicated in cell cycle and lung cancer. Here we demonstrate that PRR11 is oriented in a head-to-head configuration with its neighboring gene, SKA2. 5'-RACE assay revealed that the intergenic spacer region between the two genes is <500 bp. Serial luciferase reporter assays demonstrated that a minimal 80-bp intergenic region functions as a core bidirectional promoter to drive basal transcription in both the PRR11 and SKA2 orientations. EMSA and ChIP assays demonstrated that NF-Y binds to and directly transactivates the PRR11-SKA2 bidirectional promoter. SiRNA-mediated NF-Y depletion significantly downregulated PRR11 and SKA2 expression. Expression of both PRR11 and SKA2 was significantly upregulated in lung cancer. Expression of the two genes was highly correlated with each other and with NF-Y expression. Remarkably, high expression of both PRR11 and SKA2 was associated with poorer prognosis in lung cancer patients compared with high expression of one gene or low expression of both genes. Knockdown of PRR11 and/or SKA2 remarkably reduced cell proliferation, migration, and invasion in lung cancer cells. Thus, the PRR11-SKA2 bidirectional transcription unit, which is a novel direct target of NF-Y, is essential for the accelerated proliferation and motility of lung cancer cells and may represent a potential target in the diagnosis and/or treatment of human lung cancer.

Differential requirement for the IKKß/NF-κB signaling module in regulating TLR- versus RLR-induced type 1 IFN expression in dendritic cells.

Host innate-immune responses are tailored by cell type to control and eradicate specific infectious agents. For example, an acute RNA virus infection can result in high-level expression of type 1 IFNs by both conventional dendritic cells (cDCs) and plasmacytoid dendritic cells (pDCs), but whereas cDCs preferentially use RIG-I-like receptor (RLR) signaling to produce type 1 IFNs, pDCs predominantly use TLRs to induce these cytokines. We previously found that the IκB kinase ß (IKKß)/NF-κB pathway regulates early IFN-ß expression, but not the magnitude of type 1 IFN expression following RLR engagement. In this study, we use IKKß inhibition and mice deficient in IKKß or canonical NF-κB subunits (p50, RelA/p65, and cRel) to demonstrate that the IKKß/NF-κB axis is critical for virus-induced type 1 IFN expression in pDCs, but not in cDCs. We also reveal a crucial and more general requirement for IKKß/NF-κB in TLR- but not RLR-induced expression of type 1 IFNs and inflammatory cytokines. Together, these findings reveal a previously unappreciated specificity of the IKKß/NF-κB signaling axis in regulation of antimicrobial responses by different classes of pattern recognition receptors, and therefore by individual cell types reliant on particular pattern recognition receptors for their innate-immune transcriptional responses.

Growth inhibitory effect of KYKZL-1 on Hep G2 cells via inhibition of AA metabolites and caspase-3 pathway and cell cycle arrest.

KYKZL-1, a newly synthesized compound with COX/5-LOX dual inhibition, was subjected to the inhibitory activity test on Hep G2 growth. We found that KYKZL-1 inhibited the growth of Hep G2 cells via inducing apoptosis. Further studies showed that KYKZL-1 activated caspase-3 through cytochrome c release from mitochondria and down regulation of Bcl-2/Bax ratio and reduced the high level of COX-2 and 5-LOX. As shown in its anti-inflammatory effect, KYKZL-1 also exhibited inhibitory effect on the PGE2 and LTB4 production in Hep G2 cells. Accordingly, exogenous addition of PGE2 or LTB4 reversed the decreases in cell viability. In addition, KYKZL-1 caused cell cycle arrest at the S-G2 checkpoint via the activation of p21(CIP1) protein and down-regulation of cyclin A expression. These data indicate that the growth inhibitory effect of KYKZL-1 is associated with inhibition of AA metabolites and caspase-3 pathway and cell cycle arrest. Combined with our previous findings, KYKZL-1 exhibiting COX/5-LOX inhibition may be a promising potential agent not only for inflammation control but also for cancer prevention/therapy with an enhanced gastric safety profile.

Gene expression profiling analysis reveals that DLG3 is down-regulated in glioblastoma.

Glioblastoma multiforme (GBM) is the most malignant glioma. In the current study, 149 astrocytoma gene expression datasets were classified by prediction analysis of microarray. Strikingly, disks large homolog 3 (DLG3), a membrane-associated guanylate kinase-family gene, had the highest score in the GBM subset. DLG3 mRNA expression is significantly down-regulated in GBM relative to normal tissue and grade II or grade III astrocytoma according to the results of real-time polymerase chain reaction, and its protein expression shows an obvious difference by immunohistochemistry. Further assays show that DLG3 over-expression induces mitotic cell cycle arrest and apoptosis, and it inhibits proliferation and migration. However, DLG3 over-expression has almost no affect on invasion. The DLG3 protein expression in human brain GBM tissue and its effects on GBM cell invasion were not expected. Our data suggest that DLG3 is down-regulated in this cancer type. To our knowledge, this is the first report to clearly demonstrate the possible involvement of DLG3 in GBM.

The agreement of low lean mass with obesity using different definitions and its correlation with hyperuricemia.

Background: The agreement on the identification of sarcopenic obesity remains elusive, and its association with hyperuricemia remains unestablished. This study sought to evaluate the agreement of low lean mass (LLM) with obesity and its correlation with hyperuricemia. Methods: A total of 25,252 study participants, comprising 4,597 individuals with hyperuricemia, were obtained from the National Health and Nutrition Examination Survey spanning the years 1999-2006 and 2011-2018. LLM with obesity was characterized by the coexistence of LLM, determined by the ratio of appendicular lean mass to body mass index (BMI), and three categories of obesity including BMI, body fat percentage (BF%), and waist circumference (WC). We employed Cohen's kappa to evaluate the agreement among the different diagnostic criteria and implemented survey multiple logistic regression and stratified analyses to explicate the connection between LLM with obesity and the risk of hyperuricemia. Results: When defining obesity using BF%, BMI, and WC, the prevalence of LLM with obesity varied from 6.6 to 10.1%, with moderate-to-strong agreement. In the fully adjusted model, individuals with LLM or any of the three types of obesity exhibited notably elevated odds of developing hyperuricemia. Likewise, participants with LLM and obesity had 2.70 (LLM + BMI), 2.44 (LLM + BF%), and 3.12 (LLM + WC) times the risk of hyperuricemia, respectively, compared with healthy individuals. The association between LLM with obesity and hyperuricemia remained stable and significant across different age and sex subgroups. Conclusion: When employing the three definitions of obesity, the incidence of LLM with obesity was not high, and the diagnostic agreement was relatively good. The participants with LLM and obesity exhibited an increased risk of hyperuricemia.

Prediction of Aureococcus anophageffens using machine learning and deep learning.

The recurrent brown tide phenomenon, attributed to Aureococcus anophagefferens (A. anophagefferens), constitutes a significant threat to the Qinhuangdao sea area in China, leading to pronounced ecological degradation and substantial economic losses. This study utilized machine learning and deep learning techniques to predict A. anophagefferens population density, aiming to elucidate the occurrence mechanism and influencing factors of brown tide. Specifically, Random Forest (RF) algorithm was utilized to impute missing water quality data, facilitating its direct application in subsequent algal population prediction models. The results revealed that all four models-RF, Support Vector Regression (SVR), Multilayer Perceptron (MLP), and Convolutional Neural Network (CNN)-exhibited high accuracy in predicting A. anophagefferens population densities, with R2 values exceeding 0.75. RF, in particular, showed exceptional accuracy and reliability, with an R2 value surpassing 0.8. Additionally, the study ascertained five critical factors influencing A. anophagefferens population density: ammonia nitrogen, pH, total nitrogen, temperature, and silicate.

Quantum entanglement and interference at 3 µm.

Given the important advantages of the mid-infrared optical range (2.5 to 25 µm) for biomedical sensing, optical communications, and molecular spectroscopy, extending quantum information technology to this region is highly attractive. However, the development of mid-infrared quantum information technology is still in its infancy. Here, we report on the generation of a time-energy entangled photon pair in the mid-infrared wavelength band. By using frequency upconversion detection technology, we observe the two-photon Hong-Ou-Mandel interference and demonstrate the time-energy entanglement between twin photons at 3082 nm via the Franson-type interferometer, verifying the indistinguishability and nonlocality of the photons. This work is very promising for future applications of optical quantum technology in the mid-infrared band, which will bring more opportunities in the fields of quantum communication, precision sensing, and imaging.

The ASH1L-AS1-ASH1L axis controls NME1-mediated activation of the RAS signaling in gastric cancer.

Gastric cancer (GC) is one of the most leading cause of malignancies. However, the molecular mechanisms underlying stomach carcinogenesis remain incompletely understood. Dysregulated genetic and epigenetic alternations significantly contribute to GC development. Here, we report that ASH1L and its antisense lncRNA ASH1L-AS1, which are transcribed from the most significant GC-risk signal at 1q22, act as novel oncogenes. The high levels of ASH1L or lncRNA ASH1L-AS1 expression in GC specimens are associated with worse prognosis of patients. In line with this, ASH1L and ASH1L-AS1 are functionally important in promoting GC disease progression. LncRNA ASH1L-AS1 up-regulates ASH1L transcription, increases histone methyltransferase ASH1L expression and elevates genome-wide H3K4me3 modification levels in GC cells. Furthermore, ASH1L-AS1 directly interacts with transcription factor NME1 protein to form the ASH1L-AS1-NME1 ribonucleoprotein, which transcriptionally promotes expression of ASH1L, ASH1L-AS1, KRAS and RAF1, and activates the RAS signaling pathway in GC cells. Taken together, our data demonstrated that the ASH1L-AS1-ASH1L regulatory axis controls histone modification reprogram and activation of the RAS signaling in cancers. Thus, ASH1L-AS1 might be a novel targets of GC therapeutics and diagnosis in the clinic.

Incorporating marine particulate carbon into machine learning for accurate estimation of coastal chlorophyll-a.

Accurate predictions of coastal ocean chlorophyll-a (Chl-a) concentrations are necessary for dynamic water quality monitoring, with eutrophication as a critical factor. Prior studies that used the driven-data method have typically overlooked the relationship between Chl-a and marine particulate carbon. To address this gap, marine particulate carbon was incorporated into machine learning (ML) and deep learning (DL) models to estimate Chl-a concentrations in the Yang Jiang coastal ocean of China. Incorporating particulate organic carbon (POC) and particulate inorganic carbon (PIC) as predictors can lead to successful Chl-a estimation. The Gaussian process regression (GPR) model significantly outperforming the DL model in terms of stability and robustness. A lower POC/Chl-a ratio was observed in coastal areas, in contrast to the higher ratios detected in the southern regions of the study area. This study highlights the efficacy of the GPR model for estimating Chl-a and the importance of considering POC in modeling Chl-a concentrations.