Machine learning-based models for advanced fibrosis and cirrhosis diagnosis in chronic hepatitis B patients with hepatic steatosis.

BACKGROUND AND AIMS: The global rise of chronic hepatitis B (CHB) superimposed on hepatic steatosis (HS) warrants non-invasive, precise tools for assessing fibrosis progression. This study leveraged machine learning (ML) to develop diagnostic models for advanced fibrosis and cirrhosis in this patient population. METHODS: Treatment-naive CHB patients with concurrent HS who underwent liver biopsy in ten medical centers were enrolled as a training cohort and an independent external validation cohort (NCT05766449). Six ML models were implemented to predict advanced fibrosis and cirrhosis. The final models, derived from Shapley Additive exPlanations, were compared to Fibrosis-4 Index (FIB-4), Nonalcoholic fatty liver disease Fibrosis Score (NFS), and Aspartate transaminase to platelet ratio index (APRI) using the area under receiver operating characteristic curve (AUROC), and decision curve analysis (DCA). RESULTS: Of 1,198 eligible patients, the random forest (RF) model achieved AUROCs of 0.778 [95% confidence interval (CI) 0.749-0.807] for diagnosing advanced fibrosis (RF-AF model) and 0.777 (95%CI 0.748-0.806) for diagnosing cirrhosis (RF-C model) in the training cohort, and maintained high AUROCs in the validation cohort. In the training cohort, the RF-AF model obtained an AUROC of 0.825 (95% CI 0.787-0.862) in patients with HBV DNA ≥105 IU/ml, and RF-C model had an AUROC of 0.828 (95% CI 0.774-0.883) in female patients. The two models outperformed FIB-4, NFS, and APRI in the training cohort, and also performed well in the validation cohort. CONCLUSION: The RF models provide reliable, non-invasive tools for identifying advanced fibrosis and cirrhosis in CHB patients with concurrent HS, offering a significant advancement in the co-management of the two diseases.

Development of a machine learning-based model to predict hepatic inflammation in chronic hepatitis B patients with concurrent hepatic steatosis: a cohort study.

Background: With increasingly prevalent coexistence of chronic hepatitis B (CHB) and hepatic steatosis (HS), simple, non-invasive diagnostic methods to accurately assess the severity of hepatic inflammation are needed. We aimed to build a machine learning (ML) based model to detect hepatic inflammation in patients with CHB and concurrent HS. Methods: We conducted a multicenter, retrospective cohort study in China. Treatment-naive CHB patients with biopsy-proven HS between April 2004 and September 2022 were included. The optimal features for model development were selected by SHapley Additive explanations, and an ML algorithm with the best accuracy to diagnose moderate to severe hepatic inflammation (Scheuer's system ≥ G3) was determined and assessed by decision curve analysis (DCA) and calibration curve. This study is registered with ClinicalTrials.gov (NCT05766449). Findings: From a pool of 1,787 treatment-naive patients with CHB and HS across eleven hospitals, 689 patients from nine of these hospitals were chosen for the development of the diagnostic model. The remaining two hospitals contributed to two independent external validation cohorts, comprising 509 patients in validation cohort 1 and 589 in validation cohort 2. Eleven features regarding inflammation, hepatic and metabolic functions were identified. The gradient boosting classifier (GBC) model showed the best performance in predicting moderate to severe hepatic inflammation, with an area under the receiver operating characteristic curve (AUROC) of 0.86 (95% CI 0.83-0.88) in the training cohort, and 0.89 (95% CI 0.86-0.92), 0.76 (95% CI 0.73-0.80) in the first and second external validation cohorts, respectively. A publicly accessible web tool was generated for the model. Interpretation: Using simple parameters, the GBC model predicted hepatic inflammation in CHB patients with concurrent HS. It holds promise for guiding clinical management and improving patient outcomes. Funding: This research was supported by the National Natural Science Foundation of China (No. 82170609, 81970545), Natural Science Foundation of Shandong Province (Major Project) (No. ZR2020KH006), Natural Science Foundation of Jiangsu Province (No.BK20231118), Tianjin Key Medical Discipline (Specialty), Construction Project, TJYXZDXK-059B, Tianjin Health Science and Technology Project key discipline special, TJWJ2022XK034, and Research project of Chinese traditional medicine and Chinese traditional medicine combined with Western medicine of Tianjin municipal health and Family Planning Commission (2021022).

The Tumorigenicity of Breast Cancer Cells Is Reduced upon Treatment with Small Extracellular Vesicles Isolated from Heparin Treated Cell Cultures.

As a member of the HPSG family, heparin is often used as a specific probe of their role in cell physiology; indeed, we have previously shown a reduction in the tumorigenicity of breast cancer cells when cultured in its presence. However, a partial reversal of the anti-tumorigenic effect occurred when the treated cells were cultured in fresh medium without heparin, which led us to consider whether a more persistent effect could be achieved by treatment of the cells with small extracellular vesicles (sEV) from heparin-treated cells. The tumorigenicity was analyzed using sEV isolated from the culture medium of heparin-treated MCF-7 and MDA-MB231 breast cancer cells (sEV-HT) or from conditioned medium following the termination of treatment (heparin discontinued, sEV-HD). Tumorigenicity was reduced in cells cultured in the presence of sEV-HT compared to that of cells cultured in the presence of sEV from untreated cells (sEV-Ctrl). sEV-HD were also observed to exert an anti-tumorigenic effect on the expression of pro-tumorigenic and cell cycle regulatory proteins, as well as signaling activities when added to fresh cultures of MCF-7 and MDA-MB231 cells. The anti-tumorigenic activity of the heparin-derived sEV may arise from observed changes in the miRNA content or from heparin, which was observed to be bound to the sEV. sEV may constitute a relatively stable reservoir of circulating heparin, allowing heparin activity to persist in the circulation even after therapy has been discontinued. These findings can be considered as a special additional pharmacological characteristic of heparin clinical therapy.

Paeonol alleviates ulcerative colitis in mice by increasing short-chain fatty acids derived from Clostridium butyricum.

BACKGROUND: Increasing evidence suggests that repairing the damaged intestinal epithelial barrier and restoring its function is the key to solving the problem of prolonged ulcerative colitis. Previous studies have shown that paeonol (pae) can alleviate colitis by down-regulating inflammatory pathways. In addition, pae also has a certain effect on regulating intestinal flora. However, it remains unclear whether pae can play a role in repairing the intestinal barrier and whether there is a relationship between the therapeutic effect and the gut microbiota. PURPOSES: The aim of this study is to investigate the effect of pae on intestinal barrier repair in UC mice and how the gut microbiota plays a part in it. STUDY DESIGN AND METHODS: The therapeutic effect of pae was evaluated in a 3% DSS-induced UC mouse model. The role of pae in repairing the intestinal barrier was evaluated by detecting colonic cupped cells by Alcian blue staining, the expression of colonic epithelial tight junction protein by immunofluorescence and western blot, and the proportion of IL-22+ILC3 cells in the lamina propria lymphocytes by flow cytometry. Subsequently, 16S rRNA sequencing was used to observe the changes in intestinal flora, GC-MS was used to detect the level of SCFAs, and qPCR was used to identify the abundance of Clostridium butyricum in the intestine to evaluate the effect of pae on the gut microbiota. The antibiotic-mediated depletion of the gut flora was then used to verify that pae depends on C. butyricum to play a healing role. Finally, non-targeted metabolomics was employed to investigate the potential pathways of pae regulating C. butyricum. RESULTS: Pae could improve intestinal microecological imbalance and promote the production of short-chain fatty acids (SCFAs). Most importantly, we identified C. butyricum as a key bacterium responsible for the intestinal barrier repair effect of pae in UC mice. Eradication of intestinal flora by antibiotics abolished the repair of the intestinal barrier and the promotion of SCFAs production by pae, while C. butyricum colonization could restore the therapeutic effects of pae in UC mice, which further confirmed that C. butyricum was indeed the "driver bacterium" of pae in UC treatment. Untargeted metabolomics showed that pae regulated some amino acid metabolism and 2-Oxocarboxylic acid metabolism in C. butyricum. CONCLUSIONS: Our study showed that the restoration of the impaired intestinal barrier by pae to alleviate colitis is associated with increased C. butyricum and SCFAs production, which may be a promising strategy for the treatment of UC.

Astragaloside IV inhibits AOM/DSS-induced colitis-associated tumorigenesis via activation of PPARγ signaling in mice.

BACKGROUND: Colitis-associated colorectal cancer (CAC) is a severe complication of inflammatory bowel disease (IBD), resulting from long-term inflammation in the intestines. The primary cause of CAC is the imbalance of oxidative metabolism in intestinal cells, triggered by excessive reactive oxygen (ROS) and nitrogen (NO) species production due to prolonged intestinal inflammation. This imbalance leads to genomic instability caused by DNA damage, eventually resulting in the development of intestinal cancer. Previous studies have demonstrated that astragaloside IV is effective in treating dextran sulfate sodium salt (DSS)-induced colitis, but there is currently no relevant research on its efficacy in treating CAC. METHODS: To investigate the effect of astragaloside IV against CAC and the underlying mechanism, C57 mice were treated with (20, 40, 80 mg/kg) astragaloside IV while CAC was induced by intraperitoneal injection of 10 mg/kg azoxymethane (AOM) and ad libitum consumption of 2% dextran sulfate sodium salt (DSS). We re-verified the activating effects of astragaloside IV on PPARγ signaling in IEC-6 cells, which were reversed by GW9662 (the PPARγ inhibitor). RESULTS: Our results showed that astragaloside IV significantly improved AOM/DSS-induced CAC mice by inhibiting colonic shortening, preventing intestinal mucosal damage, reducing the number of tumors and, the expression of Ki67 protein. In addition, astragaloside IV could activate PPARγ signaling, which not only promoted the expression of Nrf2 and HO-1, restored the level of SOD, CAT and GSH, but also inhibited the expression of iNOS and reduced the production of NO in the intestine and IEC-6 cells. And this effect could be reversed by GW9662 in vitro. Astragaloside IV thus decreased the level of ROS and NO in the intestinal tract of mice, as well as reduced the damage of DNA, and therefore inhibited the occurrence of CAC. CONCLUSION: Astragaloside IV can activate PPARγ signaling in intestinal epithelial cells and reduces DNA damage caused by intestinal inflammation, thereby inhibiting colon tumourigenesis. The novelty of this study is to use PPARγ as the target to inhibit DNA damage to prevent the occurrence of CAC.

Corrigendum: Coexpression of HHLA2 and PD-L1 on tumor cells independently predicts the survival of spinal chordoma patients.

[This corrects the article DOI: 10.3389/fimmu.2021.797407.].

Structural diversity, biosynthesis, and biological functions of lipopeptides from Streptomyces.

Covering: up to 2022Streptomyces are ubiquitous in terrestrial and marine environments, where they display a fascinating metabolic diversity. As a result, these bacteria are a prolific source of active natural products. One important class of these natural products is the nonribosomal lipopeptides, which have diverse biological activities and play important roles in the lifestyle of Streptomyces. The importance of this class is highlighted by the use of related antibiotics in the clinic, such as daptomycin (tradename Cubicin). By virtue of recent advances spanning chemistry and biology, significant progress has been made in biosynthetic studies on the lipopeptide antibiotics produced by Streptomyces. This review will serve as a comprehensive guide for researchers working in this multidisciplinary field, providing a summary of recent progress regarding the investigation of lipopeptides from Streptomyces. In particular, we highlight the structures, properties, biosynthetic mechanisms, chemical and chemoenzymatic synthesis, and biological functions of lipopeptides. In addition, the application of genome mining techniques to Streptomyces that have led to the discovery of many novel lipopeptides is discussed, further demonstrating the potential of lipopeptides from Streptomyces for future development in modern medicine.

Huang Qin Decoction inhibits the initiation of experimental colitis associated carcinogenesis by controlling the PAD4 dependent NETs.

BACKGROUND: Colorectal cancer is associated with ulcerative colitis (UC). The infiltration of neutrophils is the main cause of DNA damage produced by inflammation in the intestinal epithelium. Under the action of peptidyl arginine deaminase 4 (PAD4), neutrophils dissociate chromatin and form neutrophil extracellular traps (NETs), which can aggravate tissue inflammation and encourage tumor development. Although Huang Qin Decoction (HQD) was found to be useful in treating UC and was used to gradually prevent and treat digestive tract cancers, the underlying reasons were unclear. METHODS: To demonstrate HQD could inhibits the initiation of colitis associated carcinogenesis by controlling NETs related inflammation, we first performed an AOM/DSS-generated colitis-associated carcinogenesis model to assess the efficacy of HQD in reducing neutrophil infiltration and anti-tumor activity. Then, using network pharmacology research, we investigated the potential mechanisms underlying those medicinal effects, as demonstrated by the detection of NETs aggregation and PAD4 expression changes in the colon. RESULTS: HQD substantially reduced the number of colon cancers and the expression of Ki67, restored the level of intestinal tight junction protein occludin and ZO-1, and relieved the intestinal inflammation caused by TNF-α, IL-1ß. At the same time, it inhibited neutrophil infiltration in the colon and improved the immunosurveillance of CD8+T cells. The potential mechanisms of HQD intervention against UC and UC with neoplasia (UCN) were studied using network pharmacology, and 156 conjunct genes as well as numerous inflammation-related pathways were identified. Protein-protein interaction (PPI) analysis indicated that HQD inhibition of intestinal tumors might be related to the deactivation of PAD4, which was verified by the down-regulation of NETs, MPO-DNA complex levels, and PAD4 expression after HQD treatment. CONCLUSION: Huang Qin Decoction inhibits the initiation of colitis associated carcinogenesis by controlling PAD4-dependent neutrophil extracellular traps.

Incidence and Risk Factors for Cerebrovascular-Specific Mortality in Patients with Colorectal Cancer: A Registry-Based Cohort Study Involving 563,298 Patients.

BACKGROUND: Colorectal cancer (CRC) is one of the most prevalent diseases and the second leading cause of death worldwide. However, the relationship between CRC and cerebrovascular-specific mortality (CVSM) remains elusive, and less is known about the influencing factors associated with CVSM in CRC. Here, we aimed to analyze the incidence as well as the risk factors of CVSM in CRC. METHODS: Patients with a primary CRC diagnosed between 1973 and 2015 were identified from the Surveillance Epidemiology and End Results database, with follow-up data available until 31 December 2016. Conditional standardized mortality ratios were calculated to compare the incidence of CVSM between CRC patients and the general U.S. POPULATION: Univariate and multivariate survival analyses with a competing risk model were used to interrogate the risk factors for CVSM. RESULTS: A total of 563,298 CRC individuals were included. The CVSM in CRC patients was significantly higher than the general population in all age subgroups. Among the competing causes of death in patients, the cumulative mortality caused by cerebrovascular-specific diseases steadily increased during the study period. While age, surgery, other/unknown race and tumors located at the transverse colon positively influenced CVSM on both univariate and multivariate analyses, male patients and those who had radiotherapy, chemotherapy, a more recent year (2001-2015) of diagnosis, a grade II or III CRC, rectal cancer, or multiple primary or distant tumors experienced a lower risk of CVSM. INTERPRETATION: Our data suggest a potential role for CRC in the incidence of CVSM and also identify several significant predictors of CVSM that may be helpful for risk stratification and the therapeutic optimization of cerebrovascular-specific diseases in CRC patients.

Current Advancements in Sactipeptide Natural Products.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a growing class of natural products that benefited from genome sequencing technology in the past two decades. RiPPs are widely distributed in nature and show diverse chemical structures and rich biological activities. Despite the various structural characteristic of RiPPs, they follow a common biosynthetic logic: a precursor peptide containing an N-terminal leader peptide and a C-terminal core peptide; in some cases,a follower peptide is after the core peptide. The precursor peptide undergoes a series of modification, transport, and cleavage steps to form a mature natural product with specific activities. Sactipeptides (Sulfur-to-alpha carbon thioether cross-linked peptides) belong to RiPPs that show various biological activities such as antibacterial, spermicidal and hemolytic properties. Their common hallmark is an intramolecular thioether bond that crosslinks the sulfur atom of a cysteine residue to the α-carbon of an acceptor amino acid, which is catalyzed by a rSAM enzyme. This review summarizes recent achievements concerning the discovery, distribution, structural elucidation, biosynthesis and application prospects of sactipeptides.

Using Vinegar Residue-Based Carrier Materials to Improve the Biodegradation of Phenanthrene in Aqueous Solution.

A large amount of vinegar residue (VR) is generated every year in China, causing serious environmental pollutions. Meanwhile, as a kind of persistent organic pollutants, polycyclic aromatic hydrocarbons (PAHs) ubiquitously exist in environments. With a goal of reusing VR and reducing PAHs pollutions, we herein isolated one B. subtilis strain, ZL09-26, which can degrade phenanthrene and produce biosurfactants. Subsequently, raw VR was dried under different temperatures (50 °C, 80 °C, 100 °C and 120 °C) or pyrolyzed under 350 °C and 700 °C, respectively. After being characterized by various approaches, the treated VR were mixed with ZL09-26 as carriers to degrade phenanthrene. We found that VR dried at 50 °C (VR50) was the best in promoting the growth of ZL09-26 and the degradation of phenanthrene. This result may be attributed to the residual nutrients, suitable porosity and small surface charge of VR50. Our results demonstrate the potential of VR in the biodegradation of phenanthrene, which may be meaningful for developing new VR-based approaches to remove PAHs in aqueous environments.

Coexpression of HHLA2 and PD-L1 on Tumor Cells Independently Predicts the Survival of Spinal Chordoma Patients.

Background: Immunotherapy only achieves efficacy in some cancer patients, and less is known about other immune checkpoint molecules in chordoma. Here, we aimed to determine the expression of PD-L1, HHLA2, B7H3, IDO-1 and Galectin-9 in spinal chordoma and evaluated their association with tumor infiltrating lymphocytes (TILs), clinicopathological characteristics and survival of patients. Methods: Using multiplexed quantitative immunofluorescence (QIF), we simultaneously measured the levels of five different immune checkpoint molecules and major TIL subsets in 92 human spinal chordoma samples. Results: Tumor HHLA2 and PD-L1 were positive in 80.0% and 86.0% of cases, respectively. However, B7H3, IDO-1 and Galectin-9 positivity on tumor cells were only seen in 21.0% of cases, despite all showing predominantly stromal expression. Coexpression of these QIF markers in the tumor compartment was scarcely detected except for PD-L1 and HHLA2, which was observed in 69.6% of cases. While tumoral HHLA2 and stromal B7H3 expressions were associated with an aggressive tumor phenotype, suppressive immune response (specifically including elevated PD-1+ TILs level and decreased CD8+ TIL density) and poor prognosis, stromal levels of PD-L1 and Galectin-9 predicted the opposite outcomes. Importantly, HHLA2 and PD-L1 coexpression on tumor cells independently predicted both worse local recurrence-free survival and overall survival. Conclusion: These data provide a better understanding of the immunosuppressive mechanism in chordoma and may be useful for the development of combination or novel immunotherapy approaches aiming to improve therapeutic efficacy and survival.

The SCIFF-Derived Ranthipeptides Participate in Quorum Sensing in Solventogenic Clostridia.

Ranthipeptides, defined as radical non-α thioether-containing peptides, are a newly emerging class of natural products belonging to the ribosomally synthesized and post-translationally modified peptide (RiPP) superfamily. Ranthipeptides are shown to be widespread in the bacterial kingdom, whereas heretofore their biological functions remain completely elusive. In this work, putative ranthipeptides are investigated from two solventogenic clostridia, Clostridium beijerinckii and Clostridium ljungdahlii, which are derived from the so-called six Cys in forty-five residues (SCIFF) family of precursor peptides. A series of analysis show that these two ranthipeptides participate in quorum sensing and controlling cellular metabolism. These results highlight the diverse biological functions of the ever-increasing family of RiPP natural products and showcase the potential to engineer industrially interesting organisms by manipulating their RiPP biosynthetic pathways.

Progressive Metabolic Dysfunction and Nutritional Variability Precedes Necrotizing Enterocolitis.

Necrotizing Enterocolitis (NEC) is associated with prematurity, enteral feedings, and enteral dysbiosis. Accordingly, we hypothesized that along with nutritional variability, metabolic dysfunction would be associated with NEC onset. Methods: We queried a multicenter longitudinal database that included 995 preterm infants (<32 weeks gestation) and included 73 cases of NEC. Dried blood spot samples were obtained on day of life 1, 7, 28, and 42. Metabolite data from each time point included 72 amino acid (AA) and acylcarnitine (AC) measures. Nutrition data were averaged at each of the same time points. Odds ratios and 95% confidence intervals were calculated using samples obtained prior to NEC diagnosis and adjusted for potential confounding variables. Nutritional and metabolic data were plotted longitudinally to determine relationship to NEC onset. Results: Day 1 analyte levels of alanine, phenylalanine, free carnitine, C16, arginine, C14:1/C16, and citrulline/phenylalanine were associated with the subsequent development of NEC. Over time, differences in individual analyte levels associated with NEC onset shifted from predominantly AAs at birth to predominantly ACs by day 42. Subjects who developed NEC received significantly lower weight-adjusted total calories (p < 0.001) overall, a trend that emerged by day of life 7 (p = 0.020), and persisted until day of life 28 (p < 0.001) and 42 (p < 0.001). Conclusion: Premature infants demonstrate metabolic differences at birth. Metabolite abnormalities progress in parallel to significant differences in nutritional delivery signifying metabolic dysfunction in premature newborns prior to NEC onset. These observations provide new insights to potential contributing pathophysiology of NEC and opportunity for clinical care-based prevention.

Challenges and Advances in Genome Editing Technologies in Streptomyces.

The genome of Streptomyces encodes a high number of natural product (NP) biosynthetic gene clusters (BGCs). Most of these BGCs are not expressed or are poorly expressed (commonly called silent BGCs) under traditional laboratory experimental conditions. These NP BGCs represent an unexplored rich reservoir of natural compounds, which can be used to discover novel chemical compounds. To activate silent BGCs for NP discovery, two main strategies, including the induction of BGCs expression in native hosts and heterologous expression of BGCs in surrogate Streptomyces hosts, have been adopted, which normally requires genetic manipulation. So far, various genome editing technologies have been developed, which has markedly facilitated the activation of BGCs and NP overproduction in their native hosts, as well as in heterologous Streptomyces hosts. In this review, we summarize the challenges and recent advances in genome editing tools for Streptomyces genetic manipulation with a focus on editing tools based on clustered regularly interspaced short palindrome repeat (CRISPR)/CRISPR-associated protein (Cas) systems. Additionally, we discuss the future research focus, especially the development of endogenous CRISPR/Cas-based genome editing technologies in Streptomyces.

A Method for the Quantitative Analysis of a Key Component in Complex Mixtures Using Raman Spectroscopy Based on Peak Decomposition.

Raman spectroscopy has been increasingly used in industrial production processes for analytical purposes. However, the quantitative analysis of complex mixtures based on their Raman spectra remains a problem, especially when not all of the spectra of pure components in the mixture are available. In this work, a method for the quantitative analysis of a key component in complex mixtures based on peak decomposition is introduced. The proposed method only requires the spectrum of the main component in the mixture before analysis. The spectra of the mixture are decomposed to the contributions of the main component and a group of parametric Lorentzian functions. Then, the representative peaks of the key component are extracted. Finally, a calibration model is established. This method is applied to a complex mixture containing m-xylene, o-xylene, p-xylene, ethylbenzene, methylbenzene, three trimethylbenzenes, non-aromatic hydrocarbons, etc. to determine the concentration of o-xylene in the mixture. Experiments demonstrate that the proposed method performs better than the commonly-used partial least squares (PLS), especially when the number of training samples is very small.

An Automated Baseline Correction Method Based on Iterative Morphological Operations.

Raman spectra usually suffer from baseline drift caused by fluorescence or other reasons. Therefore, baseline correction is a necessary and crucial step that must be performed before subsequent processing and analysis of Raman spectra. An automated baseline correction method based on iterative morphological operations is proposed in this work. The method can adaptively determine the structuring element first and then gradually remove the spectral peaks during iteration to get an estimated baseline. Experiments on simulated data and real-world Raman data show that the proposed method is accurate, fast, and flexible for handling different kinds of baselines in various practical situations. The comparison of the proposed method with some state-of-the-art baseline correction methods demonstrates its advantages over the existing methods in terms of accuracy, adaptability, and flexibility. Although only Raman spectra are investigated in this paper, the proposed method is hopefully to be used for the baseline correction of other analytical instrumental signals, such as IR spectra and chromatograms.

Automated decomposition algorithm for Raman spectra based on a Voigt line profile model.

Raman spectra measured by spectrometers usually suffer from band overlap and random noise. In this paper, an automated decomposition algorithm based on a Voigt line profile model for Raman spectra is proposed to solve this problem. To decompose a measured Raman spectrum, a Voigt line profile model is introduced to parameterize the measured spectrum, and a Gaussian function is used as the instrumental broadening function. Hence, the issue of spectral decomposition is transformed into a multiparameter optimization problem of the Voigt line profile model parameters. The algorithm can eliminate instrumental broadening, obtain a recovered Raman spectrum, resolve overlapping bands, and suppress random noise simultaneously. Moreover, the recovered spectrum can be decomposed to a group of Lorentzian functions. Experimental results on simulated Raman spectra show that the performance of this algorithm is much better than a commonly used blind deconvolution method. The algorithm has also been tested on the industrial Raman spectra of ortho-xylene and proved to be effective.