Comparative Probiogenomics Analysis of Limosilactobacillus fermentum 3872.

Limosilactobacillus fermentum is an important member of the lactic acid bacteria group and holds immense potential for probiotic properties in human health and relevant industries. In this study, a comparative probiogenomic approach was applied to analyze the genome sequence of L. fermentum 3872, which was extracted from a commercially available yogurt sample, along with 20 different publicly available strains. Results indicate that the genome size of the characterized L. fermentum 3892 strain is 2,057,839 bp, with a single- and circular-type chromosome possessing a G + C content of 51.69%. The genome of L. fermentum 3892 strain comprises a total of 2120 open reading frames (ORFs), two genes encoding rRNAs, and 53 genes encoding tRNAs. Upon comparative probiogenomic analysis, two plasmid sequences were detected among the study strains, including one for the L. fermentum 3872 genome, which was found between position 1,288,203 and 1,289,237 with an identity of 80.98. The whole-genome alignment revealed 2223 identical sites and a pairwise identity of 98.9%, indicating a significant difference of 1.1% among genome strains. Comparison of amino acid encoding genes among strains included in this study suggests that the strain 3872 exhibited the highest degree of amino acids present, including glutamine, glutamate, aspartate, asparagine, lysine, threonine, methionine, and cysteine. The comparative antibiotic resistome profiling revealed that strain 3872 exhibited a high resistant capacity only to ciprofloxacin antibiotics as compared to other strains. This study provides a genomic-based evaluation approach for comparative probiotic strain analysis in commercial foods and their significance to human health.

Molecular functions of microRNAs in colorectal cancer: recent roles in proliferation, angiogenesis, apoptosis, and chemoresistance.

MiRNAs (microRNAs) constitute a group of diminutive molecules of non-coding RNA intricately involved in regulating gene expression. This regulation is primarily accomplished through the binding of miRNAs to complementary sequences situated in the 3'-UTR of the messenger RNA (mRNA) target; as a result, they are degraded or repressed. The multifaceted biogenesis of miRNAs is characterized by a meticulously orchestrated sequence of events encompassing transcription, processing, transportation, and decay. Colorectal cancer stands as a pervasive and formidable ailment, afflicting millions across the globe. Colorectal cancer is not well diagnosed early, and metastasis rates are high, which results in low survival rates in advanced stages. The genesis and progression of colorectal cancer are subject to the influence of genetic and epigenetic factors, among which miRNAs play a pivotal role. When it comes to colorectal cancer, miRNAs have a dual character, depending on the genes they target, functioning as either tumor suppressors or oncogenes and the prevailing cellular milieu. Their impact extends to modulating critical facets of colorectal cancer pathogenesis, including proliferation, angiogenesis, apoptosis, chemoresistance, and radiotherapy response. The discernible potential of miRNAs which are used as biomarkers to diagnose colorectal cancer, prognosis, and treatment response has come to the forefront. Notably, miRNAs are easily found and detected readily in a variety of biological fluids, including saliva, blood, urine, and feces. This prominence is attributed to the inherent advantages of miRNAs over conventional biomarkers, including heightened stability, specificity, sensitivity, and accessibility. Various investigations have pinpointed miRNA signatures or panels capable of differentiating colorectal cancer patients from their healthy counterparts, predicting colorectal cancer stage and survival, and monitoring colorectal cancer recurrence and therapy response. Although there has been research on miRNAs in various diseases, there has been less research on miRNAs in cancer. Moreover, updated results of preclinical and clinical studies on miRNA biomarkers and drugs are required. Nevertheless, the integration of miRNAs as biomarkers for colorectal cancer is not devoid of challenges and limitations. These encompass the heterogeneity prevalent among colorectal cancer subtypes and stages, the variability in miRNA expression across different tissues and individuals, the absence of standardized methodologies for miRNA detection and quantification, and the imperative for validation through extensive clinical trials. Consequently, further research is imperative to conclusively establish the clinical utility and reliability of miRNAs as colorectal cancer biomarkers. MiR-21 demonstrates carcinogenic characteristics by targeting several tumor suppressor genes, which encourages cell division, invasion, and metastasis. On the other hand, by controlling the Wnt/ß-catenin pathway, the tumor suppressor miRNA miR-34a prevents CRC cell proliferation, migration, and invasion. Furthermore, in colorectal cancer, the miR-200 family increases chemotherapy sensitivity while suppressing epithelial-mesenchymal transition (EMT). As an oncogene, the miR-17-92 cluster targets elements of the TGF-ß signaling pathway to encourage the growth of CRC cells. Finally, miR-143/145, which is downregulated in CRC, influences apoptosis and the progression of the cell cycle. These miRNAs affect pathways like Wnt, TGF-ß, PI3K-AKT, MAPK, and EMT, making them potential clinical biomarkers and therapeutic targets. This review summarizes recent research related to miRNAs, their role in tumor progression and metastasis, and their potential as biomarkers and therapeutic targets in colorectal cancer. In addition, we combined miRNAs' roles in tumorigenesis and development with the therapy of CRC patients, leading to novel perspectives on colorectal cancer diagnosis and treatment.

Extracorporeal Shockwave for Intermittent Claudication and Quality of Life: A Randomized Clinical Trial.

Importance: Intermittent lower limb claudication limits function and quality of life. Supervised exercise programs are not readily available, and a noninvasive alternative is needed. Objective: To assess extracorporeal corporeal shockwave therapy in improving quality of life in patients with claudication. Design, Setting, and Participants: In this double-blind, placebo-controlled randomized clinical trial, patients in the outpatient setting at a single tertiary center for vascular surgery were randomized in a 1:1 ratio to extracorporeal shockwave therapy or placebo therapy with no shockwaves delivered. Recruitment was between June 2015 and January 2020, with 12-week follow-up ending in March 2020. A convenience sample of patients with claudication and conservative treatment requirements who refused or were unable to participate in supervised exercise were eligible. Patients receiving anticoagulation therapy or with an active cancer were excluded. Of 522 patients screened, 389 were eligible, 138 were enrolled, and 110 completed follow-up and were included in the primary analysis. Statistical analysis was completed by May 2021. Intervention: In the intervention group, patients received 100 impulses of 0.1mJ/mm/cm2 in an area of the gastrocnemius muscle 3 times weekly for 3 weeks. The steps for treatment were replicated for the control group without delivering the treatment. Main Outcomes and Measures: The primary outcome was the Physical Functioning domain of the 36-item Short-Form Quality of Life Questionnaire at 12-week follow-up. Secondary outcomes included walking distances, ankle brachial pressure index, and other quality-of-life measures. Results: Of 138 patients recruited and randomized, 92 (67%) were male, and the mean (SD) age of the study population was 67 (9.6) years. The intervention group had a significantly higher physical function score at 12 weeks (estimated median difference 3.8; 95% CI, 0.0-7.7; P = .03). However, this significance did not remain when adjusting for covariates. At 12 weeks, the intervention group had significantly longer pain-free and maximum walking distances (pain-free estimated median difference, 34.1, 95% CI, 11.4-56.8; P = .004; maximum estimated median difference, 51.4; 95% CI, 10.7-86.5; P = .01). Conclusions and Relevance: To our knowledge, this is the first double-blind, placebo-controlled, randomized clinical trial to consider extracorporeal shockwave therapy for the management of intermittent claudication. It demonstrated efficacy for walking distances, may have a positive effect on quality of life, and may provide a safe, noninvasive alternative therapy for patients with intermittent claudication. Trial Registration: ClinicalTrials.gov Identifier: NCT02652078.

Macrophage-enriched novel functional long noncoding RNAs LRRC75A-AS1 and GAPLINC regulate polarization and innate immune responses.

INTRODUCTION: Macrophages (Mφs) are functionally dynamic immune cells that bridge innate and adaptive immune responses; however, the underlying epigenetic mechanisms that control Mφ plasticity and innate immune functions are not well elucidated. OBJECTIVE: To identify novel functions of macrophage-enriched lncRNAs in regulating polarization and innate immune responses. METHODS: Total RNA isolated from differentiating monocyte-derived M1 and M2 Mφs was profiled for lncRNAs expression using RNAseq. Impact of LRRC75A-AS1, GAPLINC and AL139099.5 knockdown was examined on macrophage differentiation, polarization markers, phagocytosis, and antigen processing by flow cytometry and florescence microscopy. Cytokine profiles were examined by multiplex bead array and cytoskeletal signaling pathway genes were quantified by PCR-based array. Gingival biopsies were collected from periodontally healthy and diseased subjects to examine lncRNAs, M1/M2 marker expression. RESULTS: Transcriptome profiling of M1 and M2 Mφs identified thousands of differentially expressed known and novel lncRNAs. We characterized three Mφ-enriched lncRNAs LRRC75A-AS1, GAPLINC and AL139099.5 in polarization and innate immunity. Knockdown of LRRC75A-AS1 and GAPLINC downregulated the Mφ differentiation markers and skewed Mφ polarization by decreasing M1 markers without a significant impact on M2 markers. LRRC75A-AS1 and GAPLINC knockdown also attenuated bacterial phagocytosis, antigen processing and inflammatory cytokine secretion in Mφs, supporting their functional role in potentiating innate immune functions. Mechanistically, LRRC75A-AS1 and GAPLINC knockdown impaired Mφ migration by downregulating the expression of multiple cytoskeletal signaling pathways suggesting their critical role in regulating Mφ migration. Finally, we showed that LRRC75A-AS1 and GAPLINC were upregulated in periodontitis and their expression correlates with higher M1 markers suggesting their role in macrophage polarization in vivo. CONCLUSION: Our results show that polarized Mφs acquire a unique lncRNA repertoire and identified many previously unknown lncRNA sequences. LRRC75A-AS1 and GAPLINC, which are induced in periodontitis, regulate Mφ polarization and innate immune functions supporting their critical role in inflammation.

iAFPs-Mv-BiTCN: Predicting antifungal peptides using self-attention transformer embedding and transform evolutionary based multi-view features with bidirectional temporal convolutional networks.

Globally, fungal infections have become a major health concern in humans. Fungal diseases generally occur due to the invading fungus appearing on a specific portion of the body and becoming hard for the human immune system to resist. The recent emergence of COVID-19 has intensely increased different nosocomial fungal infections. The existing wet-laboratory-based medications are expensive, time-consuming, and may have adverse side effects on normal cells. In the last decade, peptide therapeutics have gained significant attention due to their high specificity in targeting affected cells without affecting healthy cells. Motivated by the significance of peptide-based therapies, we developed a highly discriminative prediction scheme called iAFPs-Mv-BiTCN to predict antifungal peptides correctly. The training peptides are encoded using word embedding methods such as skip-gram and attention mechanism-based bidirectional encoder representation using transformer. Additionally, transform-based evolutionary features are generated using the Pseduo position-specific scoring matrix using discrete wavelet transform (PsePSSM-DWT). The fused vector of word embedding and evolutionary descriptors is formed to compensate for the limitations of single encoding methods. A Shapley Additive exPlanations (SHAP) based global interpolation approach is applied to reduce training costs by choosing the optimal feature set. The selected feature set is trained using a bi-directional temporal convolutional network (BiTCN). The proposed iAFPs-Mv-BiTCN model achieved a predictive accuracy of 98.15 % and an AUC of 0.99 using training samples. In the case of the independent samples, our model obtained an accuracy of 94.11 % and an AUC of 0.98. Our iAFPs-Mv-BiTCN model outperformed existing models with a ~4 % and ~5 % higher accuracy using training and independent samples, respectively. The reliability and efficacy of the proposed iAFPs-Mv-BiTCN model make it a valuable tool for scientists and may perform a beneficial role in pharmaceutical design and research academia.

Surgical Interventions in Chronic Pancreatitis: A Systematic Review of Their Impact on Quality of Life.

This systematic review evaluates the efficacy of surgical interventions in improving the quality of life for patients with chronic pancreatitis (CP). A thorough literature search, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, identified 11 studies that focused on patient-reported outcomes after surgical treatments, including pancreatic resections, drainage procedures, and duodenum-preserving head resections. The findings indicate that organ-preserving procedures, notably the Frey and Beger operations, significantly enhance pain control and overall quality of life while reducing analgesic dependency. This review provides crucial insights into the long-term efficacy and comparative benefits of different surgical approaches, highlighting the need for personalized surgical strategies in CP management. It emphasizes the necessity for standardized outcome measures and further comparative research to refine CP treatment protocols.

Deepstacked-AVPs: predicting antiviral peptides using tri-segment evolutionary profile and word embedding based multi-perspective features with deep stacking model.

BACKGROUND: Viral infections have been the main health issue in the last decade. Antiviral peptides (AVPs) are a subclass of antimicrobial peptides (AMPs) with substantial potential to protect the human body against various viral diseases. However, there has been significant production of antiviral vaccines and medications. Recently, the development of AVPs as an antiviral agent suggests an effective way to treat virus-affected cells. Recently, the involvement of intelligent machine learning techniques for developing peptide-based therapeutic agents is becoming an increasing interest due to its significant outcomes. The existing wet-laboratory-based drugs are expensive, time-consuming, and cannot effectively perform in screening and predicting the targeted motif of antiviral peptides. METHODS: In this paper, we proposed a novel computational model called Deepstacked-AVPs to discriminate AVPs accurately. The training sequences are numerically encoded using a novel Tri-segmentation-based position-specific scoring matrix (PSSM-TS) and word2vec-based semantic features. Composition/Transition/Distribution-Transition (CTDT) is also employed to represent the physiochemical properties based on structural features. Apart from these, the fused vector is formed using PSSM-TS features, semantic information, and CTDT descriptors to compensate for the limitations of single encoding methods. Information gain (IG) is applied to choose the optimal feature set. The selected features are trained using a stacked-ensemble classifier. RESULTS: The proposed Deepstacked-AVPs model achieved a predictive accuracy of 96.60%%, an area under the curve (AUC) of 0.98, and a precision-recall (PR) value of 0.97 using training samples. In the case of the independent samples, our model obtained an accuracy of 95.15%, an AUC of 0.97, and a PR value of 0.97. CONCLUSION: Our Deepstacked-AVPs model outperformed existing models with a ~ 4% and ~ 2% higher accuracy using training and independent samples, respectively. The reliability and efficacy of the proposed Deepstacked-AVPs model make it a valuable tool for scientists and may perform a beneficial role in pharmaceutical design and research academia.

Non-coding RNA LINC01010 regulates macrophage polarization and innate immune functions by modulating NFκB signaling pathway.

Innate immune response is regulated by tissue resident or infiltrating immune cells such as macrophages (Mφ) that play critical role in tissue development, homeostasis, and repair of damaged tissue. However, the epigenetic mechanisms that regulate Mφ plasticity and innate immune functions are not well understood. Long non-coding RNA (lncRNA) are among the most abundant class of transcriptome but their function in myeloid cell biology is less explored. In this study, we deciphered the regulatory role of previously uncharacterized lncRNAs in Mφ polarization and innate immune responses. Two lncRNAs showed notable changes in their levels during M1 and M2 Mφ differentiation. Our findings indicate that LINC01010 expression increased and AC007032 expression decreased significantly. LINC01010 exhibit myeloid cell-specificity, while AC007032.1 is ubiquitous and expressed in both myeloid and lymphoid (T cells, B cells and NK cells) cells. Expression of these lncRNAs is dysregulated in periodontal disease (PD), a microbial biofilm-induced immune disease, and responsive to lipopolysaccharide (LPS) from different oral and non-oral bacteria. Knockdown of LINC01010 but not AC007032.1 reduced the surface expression of Mφ differentiation markers CD206 and CD68, and M1Mφ polarization markers MHCII and CD32. Furthermore, LINC01010 RNAi attenuated bacterial phagocytosis, antigen processing and cytokine secretion suggesting its key function in innate immunity. Mechanistically, LINC01010 knockdown Mφ treated with Escherichia coli LPS exhibit significantly reduced expression of multiple nuclear factor kappa B pathway genes. Together, our data highlight functional role of a PD-associated lncRNA LINC01010 in shaping macrophage differentiation, polarization, and innate immune activation.

Diet composition drives tissue-specific intensity of murine enteric infections.

Diet composition plays a large role in regulating gut health and enteric infection. In particular, synthetic "Western-style" diets may predispose to disease, while whole-grain diets containing high levels of crude fiber are thought to promote gut health. Here, we show that, in contrast to this paradigm, mice fed with unrefined chow are significantly more susceptible to infection with Trichuris muris, a caecum-dwelling nematode, than mice fed with refined, semi-synthetic diets (SSDs). Moreover, mice fed with SSD supplemented with inulin, a fermentable fiber, developed chronic T. muris burdens, whereas mice fed with SSD efficiently cleared the infection. Diet composition significantly impacted infection-induced changes in the host gut microbiome. Mice infected with the bacterium Citrobacter rodentium were also more susceptible to pathogen colonization when fed with either chow or inulin-enriched SSD. However, transcriptomic analysis of tissues from mice fed with either SSD or inulin-enriched SSD revealed that, in contrast to T. muris, increased C. rodentium infection appeared to be independent of the host immune response. Accordingly, exogenous treatment with interleukin (IL)-25 reduced T. muris burdens in inulin-fed mice, whereas IL-22 treatment was unable to restore resistance to C. rodentium colonization. Diet-mediated effects on pathogen burden were more pronounced for large intestine-dwelling pathogens, as effects on small the intestinal helminth (Heligmosomoides polygyrus) were less evident, and protozoan (Giardia muris) infection burdens were equivalent in mice fed with chow, inulin-enriched SSD, or SSD, despite higher cyst excretion in chow-fed mice. Collectively, our results point to a tissue- and pathogen-restricted effect of dietary fiber levels on enteric infection intensity.IMPORTANCEEnteric infections induce dysbiosis and inflammation and are a major public health burden. As the gut environment is strongly shaped by diet, the role of different dietary components in promoting resistance to infection is of interest. While diets rich in fiber or whole grain are normally associated with improved gut health, we show here that these components predispose the host to higher levels of pathogen infection. Thus, our results have significance for interpreting how different dietary interventions may impact on gastrointestinal infections. Moreover, our results may shed light on our understanding of how gut flora and mucosal immune function is influenced by the food that we eat.

Potential of UV-B radiation in drought stress resilience: A multidimensional approach to plant adaptation and future implications.

The escalating impact of climate change and ultraviolet (UV) radiation is subjecting plants to unique combinations of UV-B and drought stress. These combined stressors could have additive, synergistic, or antagonistic effects, but the precise nature of these impacts remains uncertain, hampering our ability to predict plant adaptations approach towards stressors. Our analysis of various studies shows that UV-B or drought conditions detrimentally influence plant growth and health metrics by the enhanced generation of reactive oxygen species causing damage to lipids, proteins, carbohydrates and DNA. Further reducing biomass accumulation, plant height, photosynthetic efficiency, leaf area, and water transpiration, while enhancing stress-related symptoms. In response to UV-B radiation and drought stress, plants exhibit a notable up-regulation of specific acclimation-associated metabolites, including proline, flavonoids, anthocyanins, unsaturated fatty acids, and antioxidants. These metabolites play a pivotal role in conferring protection against environmental stresses. Their biosynthesis and functional roles are potentially modulated by signalling molecules such as hydrogen peroxide, abscisic acid, jasmonic acid, salicylic acid, and ethylene, all of which have associated genetic markers that further elucidate their involvement in stress response pathways. In comparison to single stress, the combination of UV-B and drought induces the plant defence responses and growth retardation which are less-than-additive. This sub-additive response, consistent across different study environments, suggests the possibility of a cross-resistance mechanism. Our outlines imply that the adverse effects of increased drought and UV-B could potentially be mitigated by cross-talk between UV-B and drought regimes utilizing a multidimensional approach. This crucial insight could contribute significantly to refining our understanding of stress tolerance in the face of ongoing global climate change.

3D-QSAR, docking and molecular dynamics simulations of novel Pyrazolo-pyridazinone derivatives as covalent inhibitors of FGFR1: a scientific approach for possible anticancer agents.

Developing highly potent covalent inhibitors of Fibroblast growth factor receptors 1 (FGFR1) has always been a challenging task. In the current study, various computational techniques, such as 3D-QSAR, covalent docking, fingerprinting analysis, MD simulation followed by MMGB/PBSA, and per-residue energy decomposition analysis were used to explore the binding mechanism of pyrazolo[3,4-d]pyridazinone derivatives to FGFR1. The high q2 and r2 values for the CoMFA and CoMSIA models, suggest that the constructed 3D-QSAR models could reliably predict the bioactivities of FGFR1 inhibitors. The structural requirements revealed by the model's contour maps were strategically used to computationally create an in-house library of more than 100 new FGFR1 inhibitors using the R-group exploration technique implemented in the SparkTM software. The compounds from the in-house library were also mapped in the 3D-QSAR model that predicts comparable pIC50 values with the experimental values. A comparison between 3D-QSAR generated contours and molecular docking conformation of ligands was performed to reveal the fundamentals to design potent FGFR1 covalent inhibitors. The estimated binding free energies (MMGB/PBSA) for the selected compounds were in agreement with the experimental value ranking of their binding affinities towards FGFR1. Furthermore, per-residue energy decomposition analysis has identified Arg627 and Glu531 to contribute significantly in improved binding affinity of compound W16. During ADME analysis, the majority of in-house library compounds exhibited pharmacokinetic properties superior to those of experimentally produced compounds. These new compounds may help researchers better understand FGFR1 inhibition and lead to the creation of novel, potent FGFR1 inhibitors.Communicated by Ramaswamy H. Sarma.

Integrated computational approaches for designing potent pyrimidine-based CDK9 inhibitors: 3D-QSAR, docking, and molecular dynamics simulations.

CDK9 is an emerging target for the development of anticancer drugs. The development of CDK9 inhibitors with significant potency had consistently posed a formidable challenge. In the current research, a number of computational methodologies, such as, 3D-QSAR, molecular docking, fingerprint analysis, molecular dynamic (MD) simulations followed by MMGB/PBSA and ADMET studies were used systemically to uncover the binding mechanism of pyrimidine derivatives against CDK9. The CoMFA and CoMSIA models having high q2 (0.53, 0.54) and r2 values (0.96, 0.93) respectively indicating that model could accurately predict the bioactivities of CDK9 inhibitors. Using the R-group exploration technique implemented by the Spark™ by Cresset group, the structural requirements revealed by the contour maps of model were utilized strategically to create an in-house library of 100 new CDK9 inhibitors. Additionally, the compounds from the in-house library were mapped into 3D-QSAR model which predicted pIC50 values comparable to the experimental values. A comparison between 3D-QSAR generated contours and molecular docking conformation of ligands was performed to elucidate the essentials of CDK9 inhibitor design. MD simulations (100 ns) were performed on the selected docked complexes A21, A14 and D98 which contributed in validating the binding interactions. According to the findings of binding free energy analysis (MMGB/PBSA), It was observed that residues CYS106 and GLU107 had a considerable tendency to facilitate ligand-protein interactions via H-bond interactions. The aforementioned findings have the potential to enhance researchers comprehension of the mechanism underlying CDK9 inhibition and may be utilized in the development of innovative and efficacious CDK9 inhibitors.

Probing Baicalin as potential inhibitor of Aurora kinase B: A step towards lung cancer therapy.

Cell cycle regulators play pivotal roles as their dysregulation, leads to atypical proliferation and intrinsic genomic instability in cancer cells. Abnormal expression and functioning of Aurora kinase B (AURKB) are associated with cancer pathogenesis and thus exploited as a potential therapeutic target for the development of anti-cancer therapeutics. To identify effective AURKB inhibitors, a series of polyphenols was investigated to check their potential to inhibit recombinant AURKB. Their binding affinities were experimentally validated through fluorescence binding studies. Enzyme inhibition assay revealed that Mangiferin and Baicalin significantly inhibited AURKB activity with an IC50 values of 20.0 µM and 31.1 µM, respectively. To get atomistic insights into the binding mechanism, molecular docking and MD simulations of 100 ns were performed. Both compounds formed many non-covalent interactions with the residues of the active site pocket of AURKB. In addition, minimal conformational changes in the structure and formation of stable AURKB-ligand complex were observed during MD simulation analysis. Finally, cell-based studies suggested that Baicalin exhibited in-vitro cytotoxicity and anti-proliferative effects on lung cancer cell lines. Conclusively, Baicalin may be considered a promising therapeutic molecule against AURKB, adding an additional novel lead to the anti-cancer repertoire.

Recent Trends in Computer-aided Drug Design for Anti-cancer Drug Discovery.

Cancer is considered one of the deadliest diseases globally, and continuous research is being carried out to find novel potential therapies for myriad cancer types that affect the human body. Researchers are hunting for innovative remedies to minimize the toxic effects of conventional therapies being driven by cancer, which is emerging as pivotal causes of mortality worldwide. Cancer progression steers the formation of heterogeneous behavior, including self-sustaining proliferation, malignancy, and evasion of apoptosis, tissue invasion, and metastasis of cells inside the tumor with distinct molecular features. The complexity of cancer therapeutics demands advanced approaches to comprehend the underlying mechanisms and potential therapies. Precision medicine and cancer therapies both rely on drug discovery. In vitro drug screening and in vivo animal trials are the mainstays of traditional approaches for drug development; however, both techniques are laborious and expensive. Omics data explosion in the last decade has made it possible to discover efficient anti-cancer drugs via computational drug discovery approaches. Computational techniques such as computer-aided drug design have become an essential drug discovery tool and a keystone for novel drug development methods. In this review, we seek to provide an overview of computational drug discovery procedures comprising the target sites prediction, drug discovery based on structure and ligand-based design, quantitative structure-activity relationship (QSAR), molecular docking calculations, and molecular dynamics simulations with a focus on cancer therapeutics. The applications of artificial intelligence, databases, and computational tools in drug discovery procedures, as well as successfully computationally designed drugs, have been discussed to highlight the significance and recent trends in drug discovery against cancer. The current review describes the advanced computer-aided drug design methods that would be helpful in the designing of novel cancer therapies.

Novel echocardiographic markers for left ventricular filling pressure prediction in heart failure with preserved ejection fraction (ECHO-PREDICT): a prospective cross-sectional study.

Heart failure with preserved ejection fraction is a complex clinical syndrome associated with a high level of morbidity and mortality, constituting 56% of heart failure cases and showing an increasing prevalence. The E/Ea ratio, used for echocardiographic assessment of left ventricular (LV) filling pressure, has been commonly recommended as a noninvasive measure. However, its validity lacks robust prospective validation in patients with preserved LV ejection fraction, and its accuracy has been questioned in comparison to patients with reduced LV ejection fraction. The objective of this study was to evaluate the accuracy of novel echocardiographic markers incorporating peak E velocity, left atrial volume index (LAVi), and pulmonary artery systolic pressure (PAP) for noninvasive estimation of LV end-diastolic pressure (LVEDP) against invasive measurement. In this cross-sectional study conducted at a tertiary care hospital, a sample size of 122 participants was utilized. Statistical analyses including independent samples t-test, χ2 test, and linear regression analysis were employed to explore correlations and predict outcomes. The results indicated that Group 1 (LVEDP <20 mmHg) had a mean age of 59.25 years, while Group 2 (LVEDP >20 mmHg) had a mean age of 56.93 years. Mitral E velocity positively predicted LVEDP, while Mitral E/A ratio showed a negative association. Notably, (E+PAP)/2, (E+LAVi)/2, and Mitral E exhibited good discriminative ability, with respective area under the curve values of 0.840, 0.900, and 0.854. (E+LAVi)/2 demonstrated the highest discriminatory power, with a threshold of 40.100, yielding high sensitivity (0.971) but relatively low specificity (0.302) in predicting LVEDP greater than 20. These findings emphasize the accuracy and utility of combining diastolic variables and peak E velocity as markers for left ventricular filling pressure in patients with a high burden of cardiac disease. Additionally, the study highlights the importance of these parameters in assessing cardiac abnormalities and supports the potential of novel echocardiographic parameters, particularly (E+LAVi)/2, in predicting LVEDP greater than 20. Further research is warranted to validate and explore the prognostic implications of these parameters in larger patient populations, ultimately improving the diagnosis and management of cardiac disease and enhancing clinical outcomes.

AIPs-SnTCN: Predicting Anti-Inflammatory Peptides Using fastText and Transformer Encoder-Based Hybrid Word Embedding with Self-Normalized Temporal Convolutional Networks.

Inflammation is a biologically resistant response to harmful stimuli, such as infection, damaged cells, toxic chemicals, or tissue injuries. Its purpose is to eradicate pathogenic micro-organisms or irritants and facilitate tissue repair. Prolonged inflammation can result in chronic inflammatory diseases. However, wet-laboratory-based treatments are costly and time-consuming and may have adverse side effects on normal cells. In the past decade, peptide therapeutics have gained significant attention due to their high specificity in targeting affected cells without affecting healthy cells. Motivated by the significance of peptide-based therapies, we developed a highly discriminative prediction model called AIPs-SnTCN to predict anti-inflammatory peptides accurately. The peptide samples are encoded using word embedding techniques such as skip-gram and attention-based bidirectional encoder representation using a transformer (BERT). The conjoint triad feature (CTF) also collects structure-based cluster profile features. The fused vector of word embedding and sequential features is formed to compensate for the limitations of single encoding methods. Support vector machine-based recursive feature elimination (SVM-RFE) is applied to choose the ranking-based optimal space. The optimized feature space is trained by using an improved self-normalized temporal convolutional network (SnTCN). The AIPs-SnTCN model achieved a predictive accuracy of 95.86% and an AUC of 0.97 by using training samples. In the case of the alternate training data set, our model obtained an accuracy of 92.04% and an AUC of 0.96. The proposed AIPs-SnTCN model outperformed existing models with an ∼19% higher accuracy and an ∼14% higher AUC value. The reliability and efficacy of our AIPs-SnTCN model make it a valuable tool for scientists and may play a beneficial role in pharmaceutical design and research academia.

LncRNA MALAT1/microRNA-30b axis regulates macrophage polarization and function.

Macrophages (Mφ) are long-lived myeloid cells that can polarize towards the proinflammatory M1 or proresolving M2 phenotype to control diverse biological processes such as inflammation, tissue damage, and regeneration. Noncoding RNA are a class of nonprotein-coding transcriptome with numerous interdependent biological roles; however, their functional interaction in the regulation of Mφ polarization and immune responses remain unclear. Here, we show antagonistic relationship between lncRNA (MALAT1) and microRNA (miR-30b) in shaping macrophage polarization and immune functions. MALAT1 expression displays a time-dependent induction during Mφ differentiation and, upon challenge with TLR4 agonist (E. coli LPS). MALAT1 knockdown promoted the expression of M2Mφ markers without affecting M1Mφ markers, suggesting that MALAT1 favors the M1 phenotype by suppressing M2 differentiation. Compared to the control, MALAT1 knockdown resulted in reduced antigen uptake and processing, bacterial phagocytosis, and bactericidal activity, strongly supporting its critical role in regulating innate immune functions in Mφ. Consistent with this, MALAT1 knockdown showed impaired cytokine secretion upon challenge with LPS. Importantly, MALAT1 exhibit an antagonistic expression pattern with all five members of the miR-30 family during M2 Mφ differentiation. Dual-luciferase assays validated a novel sequence on MALAT1 that interacts with miR-30b, a microRNA that promotes the M2 phenotype. Phagocytosis and antigen processing assays unequivocally demonstrated that MALAT1 and miR-30b are functionally antagonistic. Concurrent MALAT1 knockdown and miR-30b overexpression exhibited the most significant attenuation in both assays. In human subjects with periodontal disease and murine model of ligature-induced periodontitis, we observed higher levels of MALAT1, M1Mφ markers and downregulation of miR-30b expression in gingival tissues suggesting a pro-inflammatory function of MALAT1 in vivo. Overall, we unraveled the role of MALAT1 in Mφ polarization and delineated the underlying mechanism of its regulation by involving MALAT-1-driven miR-30b sequestration.

Exploring the Impact of Salicylic Acid and Farmyard Manure on Soil Rhizospheric Properties and Cadmium Stress Alleviation in Maize (Zea mays L.).

Cadmium (Cd) pollution is a growing environmental problem that negatively impacts plant growth and development, particularly in maize. In this research, the impact of farmyard manure (FYM) and salicylic acid (SA) on rhizospheric characteristics and the reduction of Cd stress in maize was examined at Government College (GC) University, Lahore, in 2022. The experiment was arranged with a randomized design, including three replications of 12 treatments (T1 = Control; T2 = Farmyard manure; T3 = Salicylic Acid; T4 = 100 mg/kg of soil Cd; T5 = 200 mg/kg of soil Cd; T6 = Farmyard manure + Salicylic acid; T7 = FYM + 100 mg/kg soil Cd; T8 = FYM + 200 mg/kg soil Cd; T9 = SA + 100 mg/kg soil Cd; T10 = SA + 200 mg/kg soil Cd; T11 = FYM + SA + 100 mg/kg soil Cd; T12 = FYM + SA + 200 mg/kg soil Cd). Results demonstrated that Cd stress negatively affected the maize plant and soil properties, but the application of SA and FYM was effective to mitigate the Cd stress up to a certain level. A reduction of 41.52%, 39.14%, and 39.94% in root length, length of the leaf, and crop growth rate was noticed, due to the Cd stress at 200 mg/kg soil, but this reduction was reduced to 18.83%, 10.35%, and 12.26%, respectively, when FYM and salicylic acid were applied as a combined application under the same stress level of Cd. The root biomass, leaf surface area, and length were all improved by SA and FYM, which enhanced the plant's capacity to absorb nutrients and improve growth under Cd stress. In conclusion, the use of salicylic acid together with farm manure can be an effective approach to mitigate Cd stress in maize crops.

A Case of Locally Advanced Fibrosarcoma in a Young Male.

Fibrosarcoma is a rare, highly malignant tumor that develops from uncontrolled overgrowth of fibroblastic cells. It may start as a painless lump or swelling under the skin. But as it grows, it can push surrounding structures - organs, muscles, nerves, or blood vessels - and lead to pain and tenderness. The treatment of fibrosarcoma depends on several factors such as size, grade, location of primary tumor, extent of spread, age, and general health condition of the patient. The main treatment is surgical removal of the primary tumor with wide-margin excision and amputation if localized in the limb. Prior to surgical intervention, radiotherapy can be applied to reduce the tumor size or following surgery to lower the risk of recurrence. Chemotherapy is indicated in cases of metastasis. Unfortunately, the prognosis of fibrosarcoma is not favorable. For high-grade fibrosarcoma, the five-year survival rate is around 30% and for low-grade fibrosarcoma, it is 50-80%, with recurrence in the first two to five years post-surgery. We encountered a case of high-grade fibrosarcoma with aggressive growth in a 36-year-old male, requiring above-knee amputation.

Comparison of Postoperative Complications of Open Versus Laparoscopic Cholecystectomy According to the Modified Clavien-Dindo Classification System.

BACKGROUND: Though laparoscopic cholecystectomy has become a gold standard management technique for gallbladder diseases, an open approach can also be used for patients having complicated gallbladder disease. Post-cholecystectomy complications are well-documented in existing English scientific literature but are not well understood according to the grade of intervention required to treat those complications. OBJECTIVE: To compare the postoperative complications of laparoscopic versus open cholecystectomy according to the modified Clavien-Dindo classification (MCDC) system. MATERIALS AND METHODS:  A retrospective study was conducted at the Department of General Surgery, Unit - III, Lahore General Hospital, Lahore, comprising the data of patients operated between July 01, 2021, and December 31, 2021, after departmental approval # SU-III/73/LGH, dated April 1, 2022. Patients with the definitive diagnosis of acute cholecystitis, chronic cholecystitis, cholelithiasis, and cholecysto-duodenal fistula were included, while cases of choledocholithiasis and, gall bladder carcinoma were excluded from this study. Eighty patients met the inclusion criteria, with 40 patients in each group of open and laparoscopic cholecystectomy. Information for the data set of age, gender, history of surgical procedure, immediate and late outcome, length of surgery, and MCDC grade were collected. Low-grade complications were Grade I and Grade II, while Grades III to V were high-grade. RESULTS: The mean age of included patients was 42.52 ± 8.76 and 40.025 ± 8.12 years, in the open and laparoscopic group, with 80% and 90% female preponderance, respectively. Grade I and Grade II complications occurred in both groups of patients, with Grade III only in patients who underwent open cholecystectomy. None of the patients from each group developed Grade IV or Grade V complications. Among 40 patients who underwent laparoscopic cholecystectomy, 35% of the patients developed low-grade complications, whereas 40% of the patients developed low-grade complications after open cholecystectomy, with respiratory complications being the most common. High-grade complications after open cholecystectomy were found among 2.5% of patients, whereas no patients developed high-grade complications following the laparoscopic approach. CONCLUSION: Patients who underwent laparoscopic cholecystectomy are less prone to develop complications than patients undergoing open cholecystectomy, hence requiring low-grade interventions of surgical and non-surgical types. MCDC is a valuable tool for assessing surgical complications and can help improve patient outcomes by providing a standardized method for reporting and comparing complication rates.