Complex Disease Research Articles

Multimorbidity clusters potentially superior to individual diseases for stratifying fracture risk in older people: a nationwide cohort study.

Comorbidities are common in fracture patients, but the interaction between fracture and comorbidities remains unclear. This study aimed to define specific multimorbidity clusters in older adults and quantify the association between the multimorbidity clusters and fracture risk. This nationwide cohort study includes 1.7 million adults in Denmark aged ≥50years who were followed from 2001 through 2014 for an incident low-trauma fracture. Chronic diseases and fractures were identified from the Danish National Hospital Discharge Register. Latent class analysis and Cox's regression were conducted to define the clusters and quantify fracture risk, respectively. The study included 793815 men (age: 64 ± 10) and 873524 women (65.5 ± 11), with a third having ≥1 chronic disease. The pre-existent chronic diseases grouped individuals into low-multimorbidity (80.3% in men, 83.6% in women), cardiovascular (12.5%, 10.6%), malignant (4.1%, 3.8%), diabetic (2.4%, 2.0%) and hepatic clusters (0.7%, men only). These clusters distinguished individuals with advanced, complex, or late-stage disease from those having earlier-stage disease. During a median follow-up of 14years (IQR: 6.5, 14), 95372 men and 212498 women sustained an incident fracture. The presence of multimorbidity was associated with a significantly greater risk of fracture, independent of age and sex. Importantly, the multimorbidity clusters had the highest discriminative performance in assessing fracture risk, whereas the strength of their association with fracture risk equalled or exceeded that of both the individual chronic diseases most prevalent in each cluster and of counts-based comorbidity indices. Future fracture prevention strategies should take comorbidities into account. Multimorbidity clusters may provide greater insight into fracture risk than individual diseases or counts-based comorbidity indices.

Aberrant N-glycosylation is a therapeutic target in carriers of a common and highly pleiotropic mutation in the manganese transporter ZIP8.

The treatment of defective glycosylation in clinical practice has been limited to patients with rare and severe phenotypes associated with congenital disorders of glycosylation (CDG). Carried by approximately 5% of the human population, the discovery of the highly pleiotropic, missense mutation in a manganese transporter ZIP8 has exposed under-appreciated roles for Mn homeostasis and aberrant Mn-dependent glycosyltransferases activity leading to defective N-glycosylation in complex human diseases. Here, we test the hypothesis that aberrant N-glycosylation contributes to disease pathogenesis of ZIP8 A391T-associated Crohn's disease. Analysis of N-glycan branching in intestinal biopsies demonstrates perturbation in active Crohn's disease and a genotype-dependent effect characterized by increased truncated N-glycans. A mouse model of ZIP8 391-Thr recapitulates the intestinal glycophenotype of patients carrying mutations in ZIP8. Borrowing from therapeutic strategies employed in the treatment of patients with CDGs, oral monosaccharide therapy with N-acetylglucosamine ameliorates the epithelial N-glycan defect, bile acid dyshomeostasis, intestinal permeability, and susceptibility to chemical-induced colitis in a mouse model of ZIP8 391-Thr. Together, these data support ZIP8 391-Thr alters N-glycosylation to contribute to disease pathogenesis, challenging the clinical paradigm that CDGs are limited to patients with rare diseases. Critically, the defect in glycosylation can be targeted with monosaccharide supplementation, providing an opportunity for genotype-driven, personalized medicine.

Exceptional Location of a Pleomorphic Leiosarcoma: Clinical Case

Pleomorphic leiomyosarcoma is a rare entity that is part of the pleomorphic sarcomas with a complex genome with a high metastatic capacity and a usually poor prognosis. The most common location remains the lower extremities but other sites have been reported in the literature, particularly in the chest wall. Leiomyosarcoma (LMS) is an exceptionally rare tumor in the chest wall. Classical LMS may exhibit focal areas of pleomorphic cells; however, the coexistence of a large pleomorphic component allows the tumor to be designated as pleomorphic leiomyosarcoma (PLMS). The first cases of pleomorphic leiomyosarcoma were reported in the literature by Brooks in 1985. The pleomorphic component of these tumors is often heterologous with either cartilaginous differentiation; bony or rhabdomyosarcomatous. Since pleomorphic myogenic sarcomas, including high-grade leiomyosarcomas and rhabdomyosarcomas, have a poorer prognosis hence the importance of an accurate and valid histological diagnosis. The thoracic location of a leiomyosarcoma remains exceptional or even extremely rare and management requires multidisciplinary consultation involving the surgeon; the oncologist and the radiotherapist with additional molecular study to properly detect genetic anomalies in order to consider possible targeted therapy.

Exceptional Location of a Pleomorphic Leiosarcoma: Clinical Case

Pleomorphic leiomyosarcoma is a rare entity that is part of the pleomorphic sarcomas with a complex genome with a high metastatic capacity and a usually poor prognosis. The most common location remains the lower extremities but other sites have been reported in the literature, particularly in the chest wall. Leiomyosarcoma (LMS) is an exceptionally rare tumor in the chest wall. Classical LMS may exhibit focal areas of pleomorphic cells; however, the coexistence of a large pleomorphic component allows the tumor to be designated as pleomorphic leiomyosarcoma (PLMS). The first cases of pleomorphic leiomyosarcoma were reported in the literature by Brooks in 1985. The pleomorphic component of these tumors is often heterologous with either cartilaginous differentiation; bony or rhabdomyosarcomatous. Since pleomorphic myogenic sarcomas, including high-grade leiomyosarcomas and rhabdomyosarcomas, have a poorer prognosis hence the importance of an accurate and valid histological diagnosis. The thoracic location of a leiomyosarcoma remains exceptional or even extremely rare and management requires multidisciplinary consultation involving the surgeon; the oncologist and the radiotherapist with additional molecular study to properly detect genetic anomalies in order to consider possible targeted therapy.

A Novel Detection Method for High-Order SNP Epistatic Interactions Based on Explicit-Encoding-Based Multitasking Harmony Search.

To elucidate the genetic basis of complex diseases, it is crucial to discover the single-nucleotide polymorphisms (SNPs) contributing to disease susceptibility. This is particularly challenging for high-order SNP epistatic interactions (HEIs), which exhibit small individual effects but potentially large joint effects. These interactions are difficult to detect due to the vast search space, encompassing billions of possible combinations, and the computational complexity of evaluating them. This study proposes a novel explicit-encoding-based multitasking harmony search algorithm (MTHS-EE-DHEI) specifically designed to address this challenge. The algorithm operates in three stages. First, a harmony search algorithm is employed, utilizing four lightweight evaluation functions, such as Bayesian network and entropy, to efficiently explore potential SNP combinations related to disease status. Second, a G-test statistical method is applied to filter out insignificant SNP combinations. Finally, two machine learning-based methods, multifactor dimensionality reduction (MDR) as well as random forest (RF), are employed to validate the classification performance of the remaining significant SNP combinations. This research aims to demonstrate the effectiveness of MTHS-EE-DHEI in identifying HEIs compared to existing methods, potentially providing valuable insights into the genetic architecture of complex diseases. The performance of MTHS-EE-DHEI was evaluated on twenty simulated disease datasets and three real-world datasets encompassing age-related macular degeneration (AMD), rheumatoid arthritis (RA), and breast cancer (BC). The results demonstrably indicate that MTHS-EE-DHEI outperforms four state-of-the-art algorithms in terms of both detection power and computational efficiency. The source code is available at https://github.com/shouhengtuo/MTHS-EE-DHEI.git .

Association between parental decisions regarding abortion and severity of fetal heart disease

The prenatal diagnosis of fetal heart disease potentially influences parental decision-making regarding pregnancy termination. Existing literature indicates that the severity, whether in complexity or lethality, significantly influences parental decisions concerning abortion. However, questions remain as to how fetal heart disease severity impacts parental decisions, given recent advancements in postsurgical outcomes. Therefore, we investigated risk factors associated with parents’ decision-making regarding abortion following a prenatal diagnosis of fetal heart disease. Our analysis included 73 (terminated: n = 37; continued: n = 36) pregnancies with a fetal heart disease diagnosed before 22 weeks of gestation. Increased gestational age at diagnosis reduced the likelihood of parents’ decision on termination (Model 1: adjusted odds ratio, 0.94; 95% confidence interval 0.89–0.99; Model 2: 0.95 0.90–0.997). Critical disease (5.25; 1.09–25.19) and concurrent extracardiac or genetic abnormalities (Model 1: 4.19, 1.21–14.53; Model 2: 5.47, 1.50–19.96) increased the likelihood of choosing abortion. Notably, complex disease did not significantly influence parental decisions (0.56; 0.14–2.20). These results suggest that parental decision-making regarding abortion may be influenced by earlier gestational age at diagnosis, the lethality of heart disease, and extracardiac or genetic abnormalities, but not its complexity if prenatal diagnosis and parental counseling are provided at a cardiovascular-specialized facility.

Challenges and opportunities in access to care for systemic lupus erythematosus patients across Europe and worldwide.

SLE presents significant challenges for patients and health-care professionals (HCPs), both across Europe and worldwide. Improving health-care outcomes for patients with SLE requires a comprehensive understanding of patient disease pathways. In particular, the geographical distance between SLE patients and specialized care centres, combined with the scarcity of rheumatologists, exacerbates delays in diagnosis and management. Also, the initial SLE symptoms can often be non-specific, and providing guidelines for primary HCPs and other non-specialists is extremely important. Improvement in access to treatment is also important, with several recently approved therapies for SLE not being available in several European countries and many low- and middle-income countries (LMICs). Furthermore, in the LMICs in which these treatments are available, they are not always covered by the health-care system, making their access almost impossible for those of lower socio-economic status. A number of provisions are already in place within the European Union, to improve access to care for patients with rare and complex diseases, including those with SLE. In particular, European Reference Networks (ERNs), such the ERN for Autoimmune Diseases ReCONNET, are virtual networks involving HCPs across Europe with the aim of improving the care of patients with rare and complex diseases that require highly specialized treatment and a concentration of knowledge and resources. In addition, lupus patient organizations such as Lupus Europe play a crucial role in raising awareness of SLE and advocating for improved access to care. Together, we can work towards a future where all people living with lupus receive the comprehensive and timely care they deserve.

Genetics in relation to cardiac diseases: Implications for general practitioners.

Cardiovascular diseases (CVDs) pose significant global health challenges, with genetics increasingly recognised as a key factor alongside traditional risk factors. This presents an opportunity for general practitioners (GPs) to refine their approaches. This article explores the impact of genetics on CVDs and its implications for GPs. It discusses monogenic disorders like inherited cardiomyopathies and polygenic risks, as well as pharmacogenetics, aiming to enhance risk assessment and personalised care. Monogenic disorders, driven by single gene mutations, exhibit predictable inheritance patterns, including inherited cardiomyopathies and channelopathies such as Long QT syndrome. Polygenic risks involve multiple genetic variants influencing CVD susceptibility, addressed through polygenic risk scores for precise risk assessment. Pharmacogenetics tailor drug interventions based on genetic profiles, though challenges like accessibility and ethical considerations persist. Integrating genetics into cardiovascular care holds promise for alleviating the global CVD burden and improving patient outcomes.

The Yield of Genetic Testing in Management of Nephrolithiasis

ObjectiveTo describe the yield and indications for performing genetic testing in patients with nephrolithiasis. Genetic testing for nephrolithiasis is becoming more accessible and rapid due to technologic advances. This study aimed to determine the diagnostic yield of genetic testing in a cohort of high-risk stone formers and to identify 24-hour urine characteristics to prompt genetic screening. Materials and MethodsWe retrospectively identified patients who underwent genetic testing for nephrolithiasis from 2020-22 at a single institution using a custom PerkinElmer™ genomics panel for nephrolithiasis. We compared characteristics of patients with and without genetic abnormalities. We used receiver operator characteristic (ROC) analysis to identify candidate thresholds for genetic testing. ResultsFourteen of 36 patients (39%) who underwent genetic testing had identifiable mutations. Five patients (14%) had known pathogenic mutations, including genes for primary hyperoxaluria (PH2 and PH3), cystinuria, and enamel renal syndrome. The remaining mutations were variants of uncertain significance. Of the 14 patients with identified mutations, only 6 had concordant 24-hour urine abnormalities, including 3/5 with known pathogenic mutations. In patients with urine oxalate ≥40mg/day, 3/29 (10.3%) had PH2 or PH3. ROC analysis showed that an oxalate threshold of ≥80mg/day may have promising screening characteristics. ConclusionsGenetic testing for nephrolithiasis remains controversial due to unknown yield and the time and energy required to discuss results with patients. This preliminary report describes the yield and identifies clinical factors and a potential cut-off that may assist clinicians in deciding when genetic profiling should be pursued.

Conceptual frameworks for the integration of genetic and social epidemiology in complex diseases

Uncovering the root causes of complex diseases requires complex approaches, yet many studies continue to isolate the effects of genetic and social determinants of disease. Epidemiologic efforts that under-utilize genetic epidemiology methods and findings may lead to incomplete understanding of disease. Meanwhile, genetic epidemiology studies are often conducted without consideration of social and environmental context, limiting the public health impact of genomic discoveries. This divide endures despite shared goals and increases in interdisciplinary data due to a lack of shared theoretical frameworks and differing language. Here, we demonstrate that bridging epidemiological divides does not require entirely new ways of thinking. Existing social epidemiology frameworks including Ecosocial theory and Fundamental Cause Theory, can both be extended to incorporate principles from genetic epidemiology. We show that genetic epidemiology can strengthen, rather than detract from, efforts to understand the impact of social determinants of health. In addition to presenting theoretical synergies, we offer practical examples of how genetics can improve the public health impact of epidemiology studies across the field. Ultimately, we aim to provide a guiding framework for trainees and established epidemiologists to think about diseases and complex systems and foster more fruitful collaboration between genetic and traditional epidemiological disciplines.

Beyond PSA: a multi-modal pilot study identifying novel proteomic biomarkers in paraffin-embedded prostate cancer tissue

Abstract Background Prostate cancer (PCa) is a common and complex disease in men, often progressing from localized to aggressive meta-static stages requiring advanced therapies. Early detection of PCa relies primarily on multiparametric tests, with limitations, like over-diagnosis and lack of specificity. Advances in molecular profiling, particularly proteomics, could enhance patient stratification and personalized therapies. Methods We conducted an analysis using Formalin-Fixed Paraffin-Embedded (FFPE) samples from 23 patients diagnosed with prostatic adenocarcinoma. Proteins were extracted from tissues, followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. The data were processed to identify proteins and subsequent bioinformatics analysis was performed to uncover significant pathways and potential biomarkers panel. Validation of identified biomarkers was carried out through Western blotting (WB). Results Proteomic profiling identified 1,159 proteins, including 176 significantly elevated in tumor tissues. Enrichment analysis highlighted their involvement in stress response, protein metabolism, and signaling pathways associated with PCa progression. Key pathways included mTORC1 signaling, Myc signaling, and focal adhesion. A biomarker panel consisting of KLK3, GDF15, MIF, and AZGP1 was proposed based on their discriminatory power in distinguishing tumor from normal tissues. WB confirmed the tumor-specific expression of these candidates, particularly GDF15 and KLK3. Conclusions The present study shows for the first time a multi-modal approach that combines a panel of PCa tissue proteins, as a new tool of PCa in patients. The identified biomarker panel offers promise for improving detection and tailoring personalized treatment strategies in PCa management. Further validation in larger cohorts and clinical settings is warranted to establish these findings.

Modular pharmacology: research progress and development of analysis platform

Based on the systematic deconstruction of multi-dimensional and multi-target biological networks, modular pharmacology explains the complex mechanism of diseases and the interactions of multi-target drugs. It has made progress in the fields of pathogenesis of disease, biological basis of disease and traditional Chinese medicine(TCM) syndrome, pharmacological mechanism of multi-target herbs, compatibility of formulas, and discovery of new drug of TCM compound. However, the complexity of multi-omics data and biological networks brings challenges to the modular deconstruction and analysis of the drug networks. Here, we constructed the "Computing Platform for Modular Pharmacology" online analysis system, which can implement the function of network construction, module identification, module discriminant analysis, hub-module analysis, intra-module and inter-module relationship analysis, and topological visualization of network based on quantitative expression profiles and protein-protein interaction(PPI) data. This tool provides a powerful tool for the research on complex diseases and multi-target drug mechanisms by means of modular pharmacology. The platform may have broad range of application in disease modular identification and correlation mechanism, interpretation of scientific principles of TCM, analysis of complex mechanisms of TCM and formulas, and discovery of multi-target drugs.

The association between the size of adipocyte-derived extracellular vesicles and fasting serum triglyceride-glucose index as proxy measures of adipose tissue insulin resistance in a rat model of early-stage obesity.

Obesity is a complex disease that predisposes individuals to cardiometabolic alterations. It leads to adipose tissue (AT) dysfunction, which triggers insulin resistance (IR). This suggests that people with obesity develop local IR first and systemic IR later. AT secretes extracellular vesicles, which may be physiopathologically associated with the development of IR. Our aim was to evaluate the effect of a high-fat diet on different parameters of adiposity in a rat model of early-stage obesity and to determine if these parameters are associated with markers of systemic IR. In addition, we sought to explore the relationship between fasting blood measures of IR (Triglycerides/High Density Lipoprotein-cholesterol [TAG/HDL-c] and Triglycerides-Glucose Index [TyG Index]) with the size of adipocyte-derived extracellular vesicles (adEV). We used a model of diet-induced obesity for ten weeks in Wistar rats exposed to a high-fat diet. Final weight gain was analyzed by Dual X-ray absorptiometry. Visceral obesity was measured as epididymal AT weight. IR was evaluated with fasting TyG Index & TAG/HDL-c, and adEV were isolated from mature adipocytes on ceiling culture. In the high-fat diet group, glucose and triglyceride blood concentrations were higher in comparison to the control group (Log2FC, 0.5 and 1.5 times higher, respectively). The values for TyG Index and adEV size were different between the control animals and the high-fat diet group. Multiple linear regression analyses showed that adEV size can be significantly associated with the TyG Index value, when controlling for epididymal AT weight. Our results show that lipid and glucose metabolism, as well as the size and zeta potential of adEV are already altered in early-stage obesity and that adEV size can be significantly associated with liver and systemic IR, estimated by TyG Index.

Cystic fibrosis-related metabolic defects: crosstalk between ion channels and organs.

Cystic fibrosis is a debilitating disease characterized by a poor medical prognosis due to devastating lung injury. Recent medical advances targeting the major genetic mutation ΔF508 of the cystic fibrosis transmembrane conductance regulator (CFTR) protein have dramatically increased the lifespan of patients with this mutation. This development has led to major changes in the field and has pushed research beyond the ion transport nature of cystic fibrosis and toward multiorgan physiological reprogramming. In this issue of the JCI, Bae, Kim, and colleagues utilized a large animal pig model prior to the onset of disease. They revealed metabolic reprogramming and organ crosstalk that occurred prior to disease progression. These findings provide paradigm-shifting insight into this complex disease.

M6A mRNA methylation-mediated MAPK signaling modulates the nasal mucosa inflammatory response in allergic rhinitis.

Allergic rhinitis (AR) is a complex disease in which gene-environment interactions contribute to its pathogenesis. Epigenetic modifications, such as N6-methyladenosine (m6A) modification of mRNA, play important roles in regulating gene expression in multiple physiological and pathological processes. However, the function of m6A modification in AR and the inflammatory response is poorly understood. We used the ovalbumin (OVA) and aluminum hydroxide to induce an AR mouse model. Nasal symptoms, histopathology, and serum cytokines were examined. We performed combined m6A and RNA sequencing to analyze changes in m6A modification profiles. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and methylated RNA immunoprecipitation sequencing qPCR (MeRIP-qPCR) were used to verify differential methylation of mRNAs and the m6A methylation level. Knockdown or inhibition of Alkbh5 in nasal mucosa of mice was mediated by lentiviral infection or IOX1 treatment. We showed that m6A was enriched in a group of genes involved in MAPK signaling pathway. Moreover, we identified a MAPK pathway involving Map3k8, Erk2, and Nfκb1 that may play a role in the disrupted inflammatory response associated with nasal inflammation. The m6A eraser, Alkbh5, was highly expressed in the nasal mucosa of AR model mice. Furthermore, knockdown of Alkbh5 expression by lentiviral infection resulted in high MAPK pathway activity and a significant nasal mucosa inflammatory response. Our findings indicate that ALKBH5-mediated m6A dysregulation likely contributes to a nasal inflammatory response via the MAPK pathway. Together, our data show that m6A dysregulation mediated by ALKBH5, is likely to contribute to inflammation of the nasal mucosa via the MAPK signaling pathway, suggesting that ALKBH5 is a potential biomarker for AR treatment.

Translating “AI for omics” into precision therapy

Precision medicine aims to empower clinicians to predict the most appropriate course of action for patients with complex diseases like cancer and others.1 With an efficient interrogation of the omics, molecular, and clinical data at play in diseases, effective, personalized, and precise medical treatment strategies are expected for many disorders. In addition, the treatment modality of precision medicine is increasingly diversified, spanning from mainstream drug and antibody treatment to newly developed gene and cell therapy, etc. In various treatment modalities including the treatment by Chinese medicine, precision is the highest demand, and the underlying patterns and rationales across various factors to uncover the biological mechanism and actionable information that support early detection, prevention and therapy of complex disorders can be identified by the omics data.1,2 Therefore, the omics sequencing technology and accumulated omics data serve as the core technology and resources that can have huge impact on such a course of action. Accordingly, the integrative analysis of such omics data provides a great opportunity to support precision medicine studies. However, facing the unique features of the omics data, like the dominant characteristics of “high dimension and small sample”, traditional data analysis strategies are likely unsuitable, and data-driven artificial intelligence (AI) technology is emerging as an effective paradigm for precision medicine study. To this end, this study aims to present a concise and overview perspective of the characteristics and the emerging directions of omics sequencing data, as well as the related AI analysis schema in handling such data, together with the summarized precision therapy cases based on the integration of AI and omics.

Clinical efficacy of the bared external anal sphincter (BEAS) in high horseshoe-shaped anal fistulas: Protocol for a real-world, prospective cohort study

BackgroundHigh horseshoe-shaped anal fistula (HHAF) is a complex disease that manifests in the perianal region and typically requires surgical intervention for treatment. However, the current therapeutic approaches are limited by the high rates of postoperative recurrence and anal incontinence. To overcome the limitations of traditional surgical approaches, we introduce the bared external anal sphincter (BEAS) technique. Our study aims to compare the clinical efficacy of BEAS surgery with that of the modified Hanley procedure in a real-world setting. Materials and methodsThis single-centre, prospective cohort study will be conducted in a tertiary hospital in China and aims to evaluate the short-term clinical efficacy and safety of BEAS surgery and modified Hanley surgery in HHAF patients from March 2024 to March 2026. Data from the prospective database of this tertiary referral hospital will be used to obtain insights into the clinical outcomes of these surgical treatments. The primary outcome of this study will be the wound healing rate within six months, while the secondary outcomes will include the time to return to work, the maximum visual analogue scale pain score (VAS-PS) within 1 to 5 days postsurgery, and the Cleveland Clinic Florida Incontinence Score (CCF-IS) and Quality of Life in Anal Fistula Questionnaire Score (QoLAF-QS) at 1, 3, and 6 months postsurgery. Moreover, logistic regression analysis will be used to explore the risk factors for anal fistula recurrence after the BEAS procedure. DiscussionThis will be the first cohort study to evaluate the differences in therapeutic outcomes between patients who undergo BEAS surgery and patients who undergo surgery via the modified Hanley procedure. By conducting a detailed observation of the efficacy and treatment results of these two surgical methods, this study aims to reveal the differences the clinical effectiveness of these approaches and to provide evidence-based support for future randomized controlled trials (RCTs).

Inflammatory Gene Panel Guiding the Study of Genetics in Inflammatory Bowel Disease.

Inflammatory bowel disease (IBD) is a complex disease that develops through a sequence of molecular events that are still poorly defined. This process is driven by a multitude of context-dependent genes that play different roles based on their environment. The complexity and multi-faceted nature of these genes make it difficult to study the genetic basis of IBD. The goal of this article is to review the key genes in the pathophysiology of IBD and highlight new technology that can be used in further research. This paper examines Nanostring RNA probe technology, which uses tissue analyzed without the use of enzymes, transcription, or amplification. Nanostring offers several panels of genes to test, including an inflammation panel of 234 genes. This article analyzes this panel and reviews the literature for each gene's effect in IBD for use as a framework to review the pathophysiology of the disease. The panel was narrowed to 26 genes with significant evidence of mechanistic potential in IBD, which were then categorized into specific areas of pathogenesis. These include gut barrier breakdown, inappropriate recognition of commensal bacteria, immune cell activation, proinflammatory cytokine release, and subsequent impairment of the anti-inflammatory response. The eventual goal of this paper is the creation of a customized panel of IBD genes that can be used to better understand the genetic mechanism of IBD and aid in the development of future therapies in IBD.

Functional studies of McSTE24, McCYP305a1, and McJHEH, three essential genes act in cantharidin biosynthesis in the blister beetle (Coleoptera: Meloidae).

Cantharidin is a toxic defensive substance secreted by most blister beetles when attacked. It has been used to treat many complex diseases since ancient times and has recently regained popularity as an anticancer agent. However, the detailed mechanism of the cantharidin biosynthesis has not been completely addressed. In this study, we cloned McSTE24 (encoding STE24 endopeptidase) from terpenoid backbone pathway, McCYP305a1 (encoding cytochrome P450, family 305) and McJHEH [encoding subfamily A, polypeptide 1 and juvenile hormone (JH) epoxide hydrolase] associated to JH synthesis/degradation in the blister beetle Mylabris cichorii (Linnaeus, 1758, Coleoptera: Meloidae). Expression pattern analyses across developmental stages in adult males revealed that the expressions of 3 transcripts were closely linked to cantharidin titer exclusively during the peak period of cantharidin synthesis (20-25 days old). In contrast, at other stages, these genes may primarily regulate different biological processes. When RNA interference with double-stranded RNA suppressed the expressions of the 3 genes individually, significant reductions in cantharidin production were observed in males and also in females following McJHEH knockdown, indicating that these 3 genes might primarily contribute to cantharidin biosynthesis in males, but not in females, while females could self-synthesis a small amount of cantharidin. These findings support the previously hypothesized sexual dimorphism in cantharidin biosynthesis during the adult phase. McCYP305a1 collaborates with its upstream gene McSTE24 in cantharidin biosynthesis, while McJHEH independently regulates cantharidin biosynthesis in males.

Integrating molecular docking and molecular dynamics simulation approaches for investigation of the affinity and interactions of the Curcumin with phosphatase and tensin homolog (PTEN) and mutated PTEN

Cancer is a complex disease that imposes a significant economic burden on populations globally. Curcumin, the active ingredient in turmeric, has anti-cancer properties that hold promise for preventing cancer. By affecting key intracellular signalling pathways and proteins like NF-κB and STAT3, curcumin shows potential for thwarting cancer growth.Our research utilizes molecular docking and dynamics simulations to investigate how curcumin interacts with Phosphatase and tensin homolog (PTEN) and mutated PTEN. PTEN, a tumor suppressor protein containing 403 amino acids, plays a vital role in various cancers due to its enzymatic activities. Our results suggest that curcumin binds more strongly to mutated PTEN, indicating its potential to target cancer cells with mutated PTEN.Additionally, molecular dynamics simulations demonstrate that curcumin effectively interacts with mutated PTEN, forming stable hydrogen bonds and van der Waals interactions. These findings suggest that curcumin could serve as a safe and efficient natural compound for exploring as a therapeutic agent to reactivate mutated PTEN in cancer treatment.