Harnessing potential role of gangliosides in immunomodulation and cancer therapeutics.

Gangliosides represent glycolipids containing sialic acid residues, present on the cell membrane with glycan residues exposed to the extracellular matrix (ECM), while the ceramides are anchored within the membrane. These molecules play a critical role in pathophysiological processes such as host-pathogen interactions, cell-cell recognition, signal transduction, cell adhesion, motility, and immunomodulation. Accumulated evidence suggests the overexpression of gangliosides on tumor tissues in comparison to healthy human tissues. These tumor-associated gangliosides have been implicated in various facets of tumor biology, including cell motility, differentiation, signaling, immunosuppression, angiogenesis, and metastasis. Consequently, these entities emerge as attractive targets for immunotherapeutic interventions. Notably, the administration of antibodies targeting gangliosides has demonstrated cytotoxic effects on cancer cells that exhibit an overexpression of these glycolipids. Passive immunotherapy approaches utilizing murine or murine/human chimeric anti-ganglioside antibodies have been explored as potential treatments for diverse cancer types. Additionally, vaccination strategies employing tumor-associated gangliosides in conjunction with adjuvants have entered the realm of promising techniques currently undergoing clinical trials. The present comprehensive review encapsulates the multifaceted roles of gangliosides in tumor initiation, progression, immunosuppression, and metastasis. Further, an overview is provided of the correlation between the expression status of gangliosides in normal and tumor cells and its impact on cancer patient survival. Furthermore, the discussion extends to ongoing and completed clinical trials employing diverse strategies to target gangliosides, elucidating their effectiveness in treating cancers. This emerging discipline is expected to supply substantial impetus for the establishment of novel therapeutic strategies.

The emerging role of human papillomavirus in lung cancer.

Lung cancer stands as one of the most lethal diseases and is the foremost cause of cancer-related mortalities worldwide. The pathophysiology of lung cancer is multifaceted, and it includes multiple cell signaling pathways and other complex factors such as oxidative stress and genetics. The association of HPV with lung carcinogenesis was first proposed in 1979, and since then, scientists worldwide have been putting forward several hypotheses to establish a relationship between this virus and lung cancer. Although studies have reported the presence of HPV in lung cancer, the exact mechanism of entry and the route of transmission have not been elucidated clearly till date. Numerous studies across the globe have detected differentially expressed HPV oncoproteins in lung cancer patients and found their association with the critical cell signaling pathways that leads to the development and progression of lung cancer. Many reports have also provided evidence stating the involvement of HPV in determining the survival status of lung cancer patients. The present review recapitulates the studies evincing the association of HPV and lung cancer, its route of transmission and mechanism of action; the detection of the virus and treatment opportunities for HPV-positive lung cancer; and the severity associated with this disease. Therefore, this will provide an explicit idea and would help to develop preventive measures and specific as well as effective treatment for HPV-associated lung carcinogenesis.

Unlocking the potential of Berberine: Advancing cancer therapy through chemosensitization and combination treatments.

Despite considerable progress in cancer treatment options, resistance to chemotherapeutic drugs remains a significant challenge. This review focuses on Berberine (BBR), an isoquinoline alkaloid found in various medicinal plants, which has garnered attention in the field of oncology for its anticancer potential either alone or in combination with other compounds and its ability to modulate chemoresistance, acting as a natural chemosensitizer. BBR's ability to modulate chemoresistance is attributed to its diverse mechanisms of action, including inducing DNA breaks, inhibition of drug efflux pumps, modulation of apoptosis and necroptosis, downregulating multidrug resistance genes, enhancing immune response, suppressing angiogenesis and targeting multiple pathways within cancer cells, including protein kinase B/mammalian target of rapamycin (Akt/mTOR), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase (MAPK), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), poly(ADP-ribose) polymerase (PARP1), janus kinase/signal transducers and activators of transcription (JAK-STAT), Wnt/ß-catenin etc. Moreover, BBR, in combination with other compounds, also offers a promising approach to cancer therapy, enforcing its broad-spectrum anticancer effects. Therefore, this review aims to elucidate the intricate mechanism of action of BBR in combinatorial therapy as a potential chemosensitizer to increase the efficiency of several drugs, including cisplatin, doxorubicin, lapatinib, tamoxifen, irinotecan, niraparib, etc. in various cancers. Additionally, this review briefly covers the origin and biological activities of BBR, exploring the specific actions underlying its anticancer effects. Further, pharmacokinetic properties of BBR are also discussed, providing insight into its therapeutic potential and optimization of its use in cancer treatment.

Use of nanotechnology-based nanomaterial as a substitute for antibiotics in monogastric animals.

Nanotechnology has emerged as a promising solution for tackling antibiotic resistance in monogastric animals, providing innovative methods to enhance animal health and well-being. This review explores the novel use of nanotechnology-based nanomaterials as substitutes for antibiotics in monogastric animals. With growing global concerns about antibiotic resistance and the need for sustainable practices in animal husbandry, nanotechnology offers a compelling avenue to address these challenges. The objectives of this review are to find out the potential of nanomaterials in improving animal health while reducing reliance on conventional antibiotics. We examine various forms of nanomaterials and their roles in promoting gut health and also emphasize fresh perspectives brought by integrating nanotechnology into animal healthcare. Additionally, we delve into the mechanisms underlying the antibacterial properties of nanomaterials and their effectiveness in combating microbial resistance. By shedding light on the transformative role of nanotechnology in animal production systems. This review contributes to our understanding of how nanotechnology can provide safer and more sustainable alternatives to antibiotics.

Detection of Marchiafava Bignami disease using distinct deep learning techniques in medical diagnostics.

PURPOSE: To detect the Marchiafava Bignami Disease (MBD) using a distinct deep learning technique. BACKGROUND: Advanced deep learning methods are becoming more crucial in contemporary medical diagnostics, particularly for detecting intricate and uncommon neurological illnesses such as MBD. This rare neurodegenerative disorder, sometimes associated with persistent alcoholism, is characterized by the loss of myelin or tissue death in the corpus callosum. It poses significant diagnostic difficulties owing to its infrequency and the subtle signs it exhibits in its first stages, both clinically and on radiological scans. METHODS: The novel method of Variational Autoencoders (VAEs) in conjunction with attention mechanisms is used to identify MBD peculiar diseases accurately. VAEs are well-known for their proficiency in unsupervised learning and anomaly detection. They excel at analyzing extensive brain imaging datasets to uncover subtle patterns and abnormalities that traditional diagnostic approaches may overlook, especially those related to specific diseases. The use of attention mechanisms enhances this technique, enabling the model to concentrate on the most crucial elements of the imaging data, similar to the discerning observation of a skilled radiologist. Thus, we utilized the VAE with attention mechanisms in this study to detect MBD. Such a combination enables the prompt identification of MBD and assists in formulating more customized and efficient treatment strategies. RESULTS: A significant breakthrough in this field is the creation of a VAE equipped with attention mechanisms, which has shown outstanding performance by achieving accuracy rates of over 90% in accurately differentiating MBD from other neurodegenerative disorders. CONCLUSION: This model, which underwent training using a diverse range of MRI images, has shown a notable level of sensitivity and specificity, significantly minimizing the frequency of false positive results and strengthening the confidence and dependability of these sophisticated automated diagnostic tools.

Deep transfer learning with fuzzy ensemble approach for the early detection of breast cancer.

Breast Cancer is a significant global health challenge, particularly affecting women with higher mortality compared with other cancer types. Timely detection of such cancer types is crucial, and recent research, employing deep learning techniques, shows promise in earlier detection. The research focuses on the early detection of such tumors using mammogram images with deep-learning models. The paper utilized four public databases where a similar amount of 986 mammograms each for three classes (normal, benign, malignant) are taken for evaluation. Herein, three deep CNN models such as VGG-11, Inception v3, and ResNet50 are employed as base classifiers. The research adopts an ensemble method where the proposed approach makes use of the modified Gompertz function for building a fuzzy ranking of the base classification models and their decision scores are integrated in an adaptive manner for constructing the final prediction of results. The classification results of the proposed fuzzy ensemble approach outperform transfer learning models and other ensemble approaches such as weighted average and Sugeno integral techniques. The proposed ResNet50 ensemble network using the modified Gompertz function-based fuzzy ranking approach provides a superior classification accuracy of 98.986%.

SKping cell cycle regulation: role of ubiquitin ligase SKP2 in hematological malignancies.

SKP2 (S-phase kinase-associated protein 2) is a member of the F-box family of substrate-recognition subunits in the SCF ubiquitin-protein ligase complexes. It is associated with ubiquitin-mediated degradation in the mammalian cell cycle components and other target proteins involved in cell cycle progression, signal transduction, and transcription. Being an oncogene in solid tumors and hematological malignancies, it is frequently associated with drug resistance and poor disease outcomes. In the current review, we discussed the novel role of SKP2 in different hematological malignancies. Further, we performed a limited in-silico analysis to establish the involvement of SKP2 in a few publicly available cancer datasets. Interestingly, our study identified Skp2 expression to be altered in a cancer-specific manner. While it was found to be overexpressed in several cancer types, few cancer showed a down-regulation in SKP2. Our review provides evidence for developing novel SKP2 inhibitors in hematological malignancies. We also investigated the effect of SKP2 status on survival and disease progression. In addition, the role of miRNA and its associated families in regulating Skp2 expression was explored. Subsequently, we predicted common miRNAs against Skp2 genes by using miRNA-predication tools. Finally, we discussed current approaches and future prospective approaches to target the Skp2 gene by using different drugs and miRNA-based therapeutics applications in translational research.

Natural compounds targeting YAP/TAZ axis in cancer: Current state of art and challenges.

Cancer has become a burgeoning global healthcare concern marked by its exponential growth and significant economic ramifications. Though advancements in the treatment modalities have increased the overall survival and quality of life, there are no definite treatments for the advanced stages of this malady. Hence, understanding the diseases etiologies and the underlying molecular complexities, will usher in the development of innovative therapeutics. Recently, YAP/TAZ transcriptional regulation has been of immense interest due to their role in development, tissue homeostasis and oncogenic transformations. YAP/TAZ axis functions as coactivators within the Hippo signaling cascade, exerting pivotal influence on processes such as proliferation, regeneration, development, and tissue renewal. In cancer, YAP is overexpressed in multiple tumor types and is associated with cancer stem cell attributes, chemoresistance, and metastasis. Activation of YAP/TAZ mirrors the cellular "social" behavior, encompassing factors such as cell adhesion and the mechanical signals transmitted to the cell from tissue structure and the surrounding extracellular matrix. Therefore, it presents a significant vulnerability in the clogs of tumors that could provide a wide window of therapeutic effectiveness. Natural compounds have been utilized extensively as successful interventions in the management of diverse chronic illnesses, including cancer. Owing to their capacity to influence multiple genes and pathways, natural compounds exhibit significant potential either as adjuvant therapy or in combination with conventional treatment options. In this review, we delineate the signaling nexus of YAP/TAZ axis, and present natural compounds as an alternate strategy to target cancer.

Lipid metabolism and its implications in tumor cell plasticity and drug resistance: what we learned thus far?

Metabolic reprogramming, a hallmark of cancer, allows cancer cells to adapt to their specific energy needs. The Warburg effect benefits cancer cells in both hypoxic and normoxic conditions and is a well-studied reprogramming of metabolism in cancer. Interestingly, the alteration of other metabolic pathways, especially lipid metabolism has also grabbed the attention of scientists worldwide. Lipids, primarily consisting of fatty acids, phospholipids and cholesterol, play essential roles as structural component of cell membrane, signalling molecule and energy reserves. This reprogramming primarily involves aberrations in the uptake, synthesis and breakdown of lipids, thereby contributing to the survival, proliferation, invasion, migration and metastasis of cancer cells. The development of resistance to the existing treatment modalities poses a major challenge in the field of cancer therapy. Also, the plasticity of tumor cells was reported to be a contributing factor for the development of resistance. A number of studies implicated that dysregulated lipid metabolism contributes to tumor cell plasticity and associated drug resistance. Therefore, it is important to understand the intricate reprogramming of lipid metabolism in cancer cells. In this review, we mainly focused on the implication of disturbed lipid metabolic events on inducing tumor cell plasticity-mediated drug resistance. In addition, we also discussed the concept of lipid peroxidation and its crucial role in phenotypic switching and resistance to ferroptosis in cancer cells. Elucidating the relationship between lipid metabolism, tumor cell plasticity and emergence of resistance will open new opportunities to develop innovative strategies and combinatorial approaches for the treatment of cancer.

Dynamic interplay of nuclear receptors in tumor cell plasticity and drug resistance: Shifting gears in malignant transformations and applications in cancer therapeutics.

Recent advances have brought forth the complex interplay between tumor cell plasticity and its consequential impact on drug resistance and tumor recurrence, both of which are critical determinants of neoplastic progression and therapeutic efficacy. Various forms of tumor cell plasticity, instrumental in facilitating neoplastic cells to develop drug resistance, include epithelial-mesenchymal transition (EMT) alternatively termed epithelial-mesenchymal plasticity, the acquisition of cancer stem cell (CSC) attributes, and transdifferentiation into diverse cell lineages. Nuclear receptors (NRs) are a superfamily of transcription factors (TFs) that play an essential role in regulating a multitude of cellular processes, including cell proliferation, differentiation, and apoptosis. NRs have been implicated to play a critical role in modulating gene expression associated with tumor cell plasticity and drug resistance. This review aims to provide a comprehensive overview of the current understanding of how NRs regulate these key aspects of cancer biology. We discuss the diverse mechanisms through which NRs influence tumor cell plasticity, including EMT, stemness, and metastasis. Further, we explore the intricate relationship between NRs and drug resistance, highlighting the impact of NR signaling on chemotherapy, radiotherapy and targeted therapies. We also discuss the emerging therapeutic strategies targeting NRs to overcome tumor cell plasticity and drug resistance. This review also provides valuable insights into the current clinical trials that involve agonists or antagonists of NRs modulating various aspects of tumor cell plasticity, thereby delineating the potential of NRs as therapeutic targets for improved cancer treatment outcomes.

Point biserial correlation symbiotic organism search nanoengineering based drug delivery for tumor diagnosis.

Nanoparticulate systems have the prospect of accounting for a new making of drug delivery systems. Nanotechnology is manifested to traverse the hurdle of both physical and biological sciences by implementing nanostructures indistinct fields of science, particularly in nano-based drug delivery. The low delivery efficiency of nanoparticles is a critical obstacle in the field of tumor diagnosis. Several nano-based drug delivery studies are focused on for tumor diagnosis. But, the nano-based drug delivery efficiency was not increased for tumor diagnosis. This work proposes a method called point biserial correlation symbiotic organism search nanoengineering-based drug delivery (PBC-SOSN). The objective and aim of the PBC-SOSN method is to achieve higher drug delivery efficiency and lesser drug delivery time for tumor diagnosis. The contribution of the PBC-SOSN is to optimized nanonengineering-based drug delivery with higher r drug delivery detection rate and smaller drug delivery error detection rate. Initially, raw data acquired from the nano-tumor dataset, and nano-drugs for glioblastoma dataset, overhead improved preprocessed samples are evolved using nano variational model decomposition-based preprocessing. After that, the preprocessed samples as input are subjected to variance analysis and point biserial correlation-based feature selection model. Finally, the preprocessed samples and features selected are subjected to symbiotic organism search nanoengineering (SOSN) to corroborate the objective. Based on these findings, point biserial correlation-based feature selection and a symbiotic organism search nanoengineering were tested for their modeling performance with a nano-tumor dataset and nano-drugs for glioblastoma dataset, finding the latter the better algorithm. Incorporated into the method is the potential to adjust the drug delivery detection rate and drug delivery error detection rate of the learned method based on selected features determined by nano variational model decomposition for efficient drug delivery.

Spinal Cord Termination and Lumbar Puncture Safety in Spinal Deformities.

Background Lumbar puncture, a common diagnostic and therapeutic procedure, is performed regardless of individual spinal alignment variations. However, the impact of kyphosis, scoliosis, and kyphoscoliosis on spinal cord termination level and lumbar puncture safety remains unclear. Objectives This study aimed to determine if the termination level of the spinal cord is different in individuals with spinal deformities and to assess the necessity of routine neuroimaging for safe lumbar puncture localization. Study design and settings This single-center retrospective study was conducted at a university hospital using patients' electronic medical records. The study was focused on patients diagnosed with kyphosis, scoliosis, or kyphoscoliosis using spinal magnetic resonance imaging from January 2010 to December 2022. Participants We evaluated 240 patients: 120 with diagnosed spinal deformities (kyphosis, scoliosis, or kyphoscoliosis) and 120 without deformities, categorized by sex (deformed: 92 females, 28 males; non-deformed: 72 females, 48 males). Patients with spinal trauma, bleeding, or tumors were excluded. Results No statistically significant correlation was found between spinal deformities and spinal cord termination, with L1 remaining the most common endpoint in all groups. Conclusion Routine neuroimaging prior to lumbar puncture in patients with spinal deformities was not associated with a safer procedure due to no observed impact on the termination level of the spinal cord.

Therapeutic potential of tocotrienols as chemosensitizers in cancer therapy.

Chemoresistance is the adaptation of cancer cells against therapeutic agents. When exhibited by cancer cells, chemoresistance helps them to avoid apoptosis, cause relapse, and metastasize, making it challenging for chemotherapeutic agents to treat cancer. Various strategies like dosage modification of drugs, nanoparticle-based delivery of chemotherapeutics, antibody-drug conjugates, and so on are being used to target and reverse chemoresistance, one among such is combination therapy. It uses the combination of two or more therapeutic agents to reverse multidrug resistance and improve the effects of chemotherapy. Phytochemicals are known to exhibit chemosensitizing properties and are found to be effective against various cancers. Tocotrienols (T3) and tocopherols (T) are natural bioactive analogs of vitamin E, which exhibit important medicinal value and potential curative properties apart from serving as an antioxidant and nutrient supplement. Notably, T3 exhibits a variety of pharmacological activities like anticancer, anti-inflammatory, antiproliferative, and so on. The chemosensitizing property of tocotrienol is exhibited by modulating several signaling pathways and molecular targets involved in cancer cell survival, proliferation, invasion, migration, and metastasis like NF-κB, STATs, Akt/mTOR, Bax/Bcl-2, Wnt/ß-catenin, and many more. T3 sensitizes cancer cells to chemotherapeutic drugs including cisplatin, doxorubicin, and paclitaxel increasing drug concentration and cytotoxicity. Discussed herewith are the chemosensitizing properties of tocotrienols on various cancer cell types when combined with various drugs and biological molecules.

Delineating the role of nuclear receptors in colorectal cancer, a focused review.

Colorectal cancer (CRC) stands as one of the most prevalent form of cancer globally, causing a significant number of deaths, surpassing 0.9 million in the year 2020. According to GLOBOCAN 2020, CRC ranks third in incidence and second in mortality in both males and females. Despite extensive studies over the years, there is still a need to establish novel therapeutic targets to enhance the patients' survival rate in CRC. Nuclear receptors (NRs) are ligand-activated transcription factors (TFs) that regulate numerous essential biological processes such as differentiation, development, physiology, reproduction, and cellular metabolism. Dysregulation and anomalous expression of different NRs has led to multiple alterations, such as impaired signaling cascades, mutations, and epigenetic changes, leading to various diseases, including cancer. It has been observed that differential expression of various NRs might lead to the initiation and progression of CRC, and are correlated with poor survival outcomes in CRC patients. Despite numerous studies on the mechanism and role of NRs in this cancer, it remains of significant scientific interest primarily due to the diverse functions that various NRs exhibit in regulating key hallmarks of this cancer. Thus, modulating the expression of NRs with their agonists and antagonists, based on their expression levels, holds an immense prospect in the diagnosis, prognosis, and therapeutical modalities of CRC. In this review, we primarily focus on the role and mechanism of NRs in the pathogenesis of CRC and emphasized the significance of targeting these NRs using a variety of agents, which may represent a novel and effective strategy for the prevention and treatment of this cancer.

Exploring the nexus of nuclear receptors in hematological malignancies.

Hematological malignancies (HM) represent a subset of neoplasms affecting the blood, bone marrow, and lymphatic systems, categorized primarily into leukemia, lymphoma, and multiple myeloma. Their prognosis varies considerably, with a frequent risk of relapse despite ongoing treatments. While contemporary therapeutic strategies have extended overall patient survival, they do not offer cures for advanced stages and often lead to challenges such as acquisition of drug resistance, recurrence, and severe side effects. The need for innovative therapeutic targets is vital to elevate both survival rates and patients' quality of life. Recent research has pivoted towards nuclear receptors (NRs) due to their role in modulating tumor cell characteristics including uncontrolled proliferation, differentiation, apoptosis evasion, invasion and migration. Existing evidence emphasizes NRs' critical role in HM. The regulation of NR expression through agonists, antagonists, or selective modulators, contingent upon their levels, offers promising clinical implications in HM management. Moreover, several anticancer agents targeting NRs have been approved by the Food and Drug Administration (FDA). This review highlights the integral function of NRs in HM's pathophysiology and the potential benefits of therapeutically targeting these receptors, suggesting a prospective avenue for more efficient therapeutic interventions against HM.

Peristaltic transport of Sutterby nanofluid flow in an inclined tapered channel with an artificial neural network model and biomedical engineering application.

Modern energy systems are finding new applications for magnetohydrodynamic rheological bio-inspired pumping systems. The incorporation of the electrically conductive qualities of flowing liquids into the biological geometries, rheological behavior, and propulsion processes of these systems was a significant effort. Additional enhancements to transport properties are possible with the use of nanofluids. Due to their several applications in physiology and industry, including urine dynamics, chyme migration in the gastrointestinal system, and the hemodynamics of tiny blood arteries. Peristaltic processes also move spermatozoa in the human reproductive system and embryos in the uterus. The present research examines heat transport in a two-dimensional deformable channel containing magnetic viscoelastic nanofluids by considering all of these factors concurrently, which is vulnerable to peristaltic waves and hall current under ion slip and other situations. Nanofluid rheology makes use of the Sutterby fluid model, while nanoscale effects are modeled using the Buongiorno model. The current study introduces an innovative numerical computing solver utilizing a Multilayer Perceptron feed-forward back-propagation artificial neural network (ANN) with the Levenberg-Marquardt algorithm. Data were collected for testing, certifying, and training the ANN model. In order to make the dimensional PDEs dimensionless, the non-similar variables are employed and calculated by the Homotopy perturbation technique. The effects of developing parameters such as Sutterby fluid parameter, Froude number, thermophoresis, ion-slip parameter, Brownian motion, radiation, Eckert number, and Hall parameter on velocity, temperature, and concentration are demonstrated. The machine learning model chooses data, builds and trains a network, and subsequently assesses its performance using the mean square error metric. Current results declare that the improving Reynolds number tends to increase the pressure rise. Improving the Hall parameter is shown to result in a decrease in velocity. When raising a fluid's parameter, the temperature profile rises.

Harnessing Sulforaphane Potential as a Chemosensitizing Agent: A Comprehensive Review.

Recent advances in oncological research have highlighted the potential of naturally derived compounds in cancer prevention and treatment. Notably, sulforaphane (SFN), an isothiocyanate derived from cruciferous vegetables including broccoli and cabbage, has exhibited potent chemosensitizing capabilities across diverse cancer types of bone, brain, breast, lung, skin, etc. Chemosensitization refers to the enhancement of cancer cell sensitivity to chemotherapy agents, counteracting the chemoresistance often developed by tumor cells. Mechanistically, SFN orchestrates this sensitization by modulating an array of cellular signaling pathways (e.g., Akt/mTOR, NF-κB, Wnt/ß-catenin), and regulating the expression and activity of pivotal genes, proteins, and enzymes (e.g., p53, p21, survivin, Bcl-2, caspases). When combined with conventional chemotherapeutic agents, SFN synergistically inhibits cancer cell proliferation, invasion, migration, and metastasis while potentiating drug-induced apoptosis. This positions SFN as a potential adjunct in cancer therapy to augment the efficacy of standard treatments. Ongoing preclinical and clinical investigations aim to further delineate the therapeutic potential of SFN in oncology. This review illuminates the multifaceted role of this phytochemical, emphasizing its potential to enhance the therapeutic efficacy of anti-cancer agents, suggesting its prospective contributions to cancer chemosensitization and management.

Modeling of two-stage anaerobic onsite wastewater sanitation system to predict effluent soluble chemical oxygen demand through machine learning.

The present research aims to predict effluent soluble chemical oxygen demand (SCOD) in anaerobic digestion (AD) process using machine-learning based approach. Anaerobic digestion is a highly sensitive process and depends upon several environmental and operational factors, such as temperature, flow, and load. Therefore, predicting output characteristics using modeling is important not only for process monitoring and control, but also to reduce the operating cost of the treatment plant. It is difficult to predict COD in a real time mode, so it is better to use Complex Mathematical Modeling (CMM) for simulating AD process and forecasting output parameters. Therefore, different Machine Learning algorithms, such as Linear Regression, Decision Tree, Random Forest and Artificial Neural Networks, have been used for predicting effluent SCOD using data acquired from in situ anaerobic wastewater treatment system. The result of the predicted data using different algorithms were compared with experimental data of anaerobic system. It was observed that the Artificial Neural Networks is the most effective simulation technique that correlated with the experimental data with the mean absolute percentage error of 10.63 and R2 score of 0.96. This research proposes an efficient and reliable integrated modeling method for early prediction of the water quality in wastewater treatment.