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Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Conventional treatment options for TNBC often have limited efficacy and significant side effects. In recent years, traditional Chinese medicine (TCM) has shown promising results in the treatment of TNBC. TCMs include herb combinations that have synergistic effects to regulate homeostasis in the body, reduce tumor resistance, and improve patient quality of life. At present, three main TCM methods are used to treat TNBC in the clinic: strengthening the body's resistance, dispelling phlegm, and removing cancer toxins. This paper reviews the theories and mechanisms of each in TNBC treatment. The method of strengthening the body's resistance emphasizes enhancing the body's original Qi to fight against pathogenic factors; the method of dispelling phlegm seeks to eliminate phlegm stagnation and alleviate the burden on affected organs; the method of removing cancer toxins focuses on detoxification and detumescence to remove the toxic elements associated with TNBC. Although these methods treat TNBC from different etiologies, they have achieved good therapeutic effects and represent an important academic approach: That is, to cure the disease with a comprehensive view of the body and restore the balance of Yin and Yang. This knowledge lays a foundation for the future development and reasonable application of TCM in the clinic. [ABSTRACT FROM AUTHOR]

Simple Summary: The disialoganglioside GD2 is a molecule found in certain tumors, like neuroblastoma, but rarely in normal tissues. The main aim of this study was to understand if hu14.18K322A, an antibody targeting GD2, causes direct cell death in high-risk neuroblastoma and to delineate the pathways involved. Our results demonstrate that hu14.18K322A activates apoptosis and necroptosis but affects no other cell-death pathways. Hu14.18K322A synergistically increased cell death by induction chemotherapy drugs. We found an alteration in GD2 surface expression after chemotherapy treatment, emphasizing the complex interplay between them. These results highlight the multifaceted role of hu14.18K322A in high-risk neuroblastoma and suggest pathways that may be targeted to increase treatment efficacy. The disialoganglioside, GD2, is a promising therapeutic target due to its overexpression in certain tumors, particularly neuroblastoma (NB), with limited expression in normal tissues. Despite progress, the intricate mechanisms of action and the full spectrum of the direct cellular responses to anti-GD2 antibodies remain incompletely understood. In this study, we examined the direct cytotoxic effects of the humanized anti-GD2 antibody hu14.18K322A (hu14) on NB cell lines, by exploring the associated cell-death pathways. Additionally, we assessed the synergy between hu14 and conventional induction chemotherapy drugs. Our results revealed that hu14 treatment induced direct cytotoxic effects in CHLA15 and SK-N-BE1 cell lines, with a pronounced impact on proliferation and colony formation. Apoptosis emerged as the predominant cell-death pathway triggered by hu14. Furthermore, we saw a reduction in GD2 surface expression in response to hu14 treatment. Hu14 demonstrated synergy with induction chemotherapy drugs with alterations in GD2 expression. Our comprehensive investigation provides valuable insights into the multifaceted effects of hu14 on NB cells, shedding light on its direct cytotoxicity, cell-death pathways, and interactions with induction chemotherapy drugs. This study contributes to the evolving understanding of anti-GD2 antibody therapy and its potential synergies with conventional treatments in the context of NB. [ABSTRACT FROM AUTHOR]

Simple Summary: Mutation of the SMARCB1 gene can cause one of the most aggressive and lethal cancers of early childhood and infancy, malignant rhabdoid tumor (MRT). Despite the standard multimodal therapy (resection, conventional chemotherapy, and radiotherapy), the outlook for young children with MRT is poor. For infants, the disease can also preclude the use of radiotherapy. Numerous experimental treatments explore epigenetic mechanisms, but the DNA damage response has not yet been extensively evaluated as a therapeutic approach for MRT. We report a new therapeutic strategy for SMARCB1-deficient MRTs, combining PARP1 inhibition and DNA damage induction. The observed synergy between the PEGylated PARP1 inhibitor talazoparib (PEG~TLZ) and the DNA alkylating agent temozolomide (TMZ) may lead to improved therapeutic strategies for patients with this challenging cancer. We identified a new potential biomarker of response to PEG~TLZ+TMZ, O6-methylguanine methyltransferase (MGMT), and uncovered dysregulated signaling pathways involved in the response. Additionally, we elucidated the pro-survival role of SMARCB1 loss in MRT cells. Malignant rhabdoid tumors (MRTs) are among the most aggressive and treatment-resistant malignancies affecting infants, originating in the kidney, brain, liver, and soft tissues. The 5-year event-free survival rate for these cancers is a mere 20%. In nearly all cases of MRT, the SMARCB1 gene (occasionally SMARCA4)—a pivotal component of the SWI/SNF chromatin remodeling complex—is homozygously deleted, although the precise etiology of these tumors remains unknown. While young patients with localized MRT generally show improved outcomes, especially those who are older and have early-stage disease, the overall prognosis remains poor despite optimal standard treatments. This highlights the urgent need for more effective treatment strategies. We investigated the antitumor activity of a PARP1 inhibitor (talazoparib, TLZ) combined with a DNA alkylating agent (temozolomide, TMZ) in MRT xenograft models. PARP1 is a widely targeted molecule in cancer treatment and, beyond its role in DNA repair, it participates in transcriptional regulation by recruiting chromatin remodeling complexes to modulate DNA accessibility for RNA polymerases. To widen the therapeutic window of the drug combination, we employed PEGylated TLZ (PEG~TLZ), which has been reported to reduce systemic toxicity through slow drug release. Remarkably, our findings indicate that five out of six MRT xenografts exhibited an objective response to PEG~TLZ+TMZ therapy. Significantly, the loss of SMARCB1 was found to confer a protective effect, correlating with higher expression levels of DNA damage and repair proteins in SMARCB1-deficient MRT cells. Additionally, we identified MGMT as a potential biomarker indicative of in vivo MRT response to PEG~TLZ+TMZ therapy. Moreover, our analysis revealed alterations in signaling pathways associated with the observed antitumor efficacy. This study presents a novel and efficacious therapeutic approach for MRT, along with a promising candidate biomarker for predicting tumor response. [ABSTRACT FROM AUTHOR]

Simple Summary: Colorectal cancer (CRC) has become one of the leading causes of cancer-related morbidity and mortality worldwide. Immune checkpoint inhibitors (ICIs) and adoptive cell therapy (ACT) have been recently added to the clinical armamentarium of stage II/III diseases. Moreover, the improvement of a patient's telomere status may have a synergistic effect along with ICIs/ACT. This can be achieved either via lifestyle modifications with increased physical activity or with new promising treatments such as those acting on telomerase. Therefore, this review aims to comprehensively summarize the current data on immunotherapy in order to facilitate clinicians' familiarity with this relatively new therapeutic approach. Cancer of the colon and rectum (CRC) has been identified among the three most prevalent types of cancer and cancer-related deaths for both sexes. Even though significant progress in surgical and chemotherapeutic techniques has markedly improved disease-free and overall survival rates in contrast to those three decades ago, recent years have seen a stagnation in these improvements. This underscores the need for new therapies aiming to augment patient outcomes. A number of emerging strategies, such as immune checkpoint inhibitors (ICIs) and adoptive cell therapy (ACT), have exhibited promising outcomes not only in preclinical but also in clinical settings. Additionally, a thorough appreciation of the underlying biology has expanded the scope of research into potential therapeutic interventions. For instance, the pivotal role of altered telomere length in early CRC carcinogenesis, leading to chromosomal instability and telomere dysfunction, presents a promising avenue for future treatments. Thus, this review explores the advancements in CRC immunotherapy and telomere-targeted therapies, examining potential synergies and how these novel treatment modalities intersect to potentially enhance each other's efficacy, paving the way for promising future therapeutic advancements. [ABSTRACT FROM AUTHOR]

Background: Lung tumors are prevalent malignancies associated with a high mortality rate, imposing significant medical and societal burdens. Although immunotherapy shows promise in improving survival, response rates are relatively modest. Thermal ablation can not only eliminate tumor cells directly but also enhance antitumor immunity response, thus manifesting a remarkable propensity to synergize with immunotherapy. Summary: In this review, we provided a brief overview of the application of thermal ablation in peripheral lung tumors. We summarized the patient selection of thermal ablation. We highlighted the potential of thermal ablation to augment the antitumor immune response, offering a promising avenue for combined therapies. We summarized studies assessing the synergistic effects of thermal ablation and immunotherapy in preclinical and clinical settings. Lastly, we underscored the urgent issues that warrant in-depth exploration when applying thermal ablation and immunotherapy to lung tumor patients. Key Messages: This review emphasized the prospects of using thermal ablation combined with immunotherapy in patients with peripheral lung tumors. However, further research is needed to enhance and optimize this treatment strategy. [ABSTRACT FROM AUTHOR]

Bacterial infection is the most common complication in wound healing, highlighting an urgent need for the development of innovative antibacterial technologies and treatments to address the growing threats posed by bacterial infections. Black phosphorus nanosheets (BPNSs), as a promising two‐dimensional nanomaterial, have been utilized in treating infected wounds. However, BP's limited stability restricts its application. In this study, we enhance BP's stability and its antibacterial properties by anchoring gallium ions (Ga3+) onto BP's surface, creating a novel antibacterial platform. This modification reduces BP's electron density and enhances its antibacterial capabilities through a synergistic effect. Under near‐infrared (NIR) irradiation, the BP/Ga3+ combination exerts antibacterial effects via photothermal therapy (PTT) and photodynamic therapy (PDT), while also releasing Ga3+. The Ga3+ employ a 'Trojan horse strategy' to disrupt iron metabolism, significantly boosting the antibacterial efficacy of the complex. This innovative material offers a viable alternative to antibiotics and holds significant promise for treating infected wounds and aiding skin reconstruction. [ABSTRACT FROM AUTHOR]

To enhance the clinical effect of antifungal medications for treating deadly fungal infections there is an increasing demand for novel treatments. Exploration of multiple-drug targeting in antifungal therapeutics is the need of the present era. In this pursuit, we identified potent antifungal compounds that were directed towards the multiple virulent targets in Rhizopus arrhizus. Quinoxaline di-N-oxide and piperazine derivatives were identified to exhibit antifungal activities. 03 bioactive compounds were identified from the docking results and antifungal activity. Furthermore, these compounds which were combined with the alkaline extract of M. olifera to make the aqueous phase, an oil phase containing cinnamon oil or clove oil and a combination of surfactants was made to prepare a bioactive composite emulsion. A significant antimycotic activity was seen for the bioactive composite emulsion when compared with the clinically used antifungal drugs. Our results indicate the synergy and potentiation of antimycotic drugs based on integrative medicine. [ABSTRACT FROM AUTHOR]

Purpose: Prolonged shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been observed in immunocompromised hosts. Early monotherapy with direct-acting antivirals or monoclonal antibodies, as recommended by the international guidelines, does not prevent this with certainty. Dual therapies may therefore have a synergistic effect. Methods: This retrospective, multicentre study compared treatment strategies for corona virus disease-19 (COVID-19) with combinations of nirmatrelvir/ritonavir, remdesivir, molnupiravir, and/ or mABs during the Omicron surge. Co-primary endpoints were prolonged viral shedding (≥ 106 copies/ml at day 21 after treatment initiation) and days with SARS-CoV-2 viral load ≥ 106 copies/ml. Therapeutic strategies and risk groups were compared using odds ratios and Fisher's tests or Kaplan−Meier analysis and long-rank tests. Multivariable regression analysis was performed. Results: 144 patients were included with a median duration of SARS-CoV-2 viral load ≥ 106 copies/ml of 8.0 days (IQR 6.0–15.3). Underlying haematological malignancies (HM) (p = 0.03) and treatment initiation later than five days after diagnosis (p < 0.01) were significantly associated with longer viral shedding. Prolonged viral shedding was observed in 14.6% (n = 21/144), particularly in patients with underlying HM (OR 3.5; 95% CI 1.2–9.9; p = 0.02). Clinical courses of COVID-19 were mild to moderate with only few adverse effects potentially related to combination treatment. Conclusion: Early combination treatment of COVID-19 effectively prevented prolonged viral shedding in 85.6% of cases. Considering the rapid viral clearance rates and low toxicity, individualized dual therapy approaches may be beneficial in high-risk patients. [ABSTRACT FROM AUTHOR]

Genomic rearrangements of the neurotrophic receptor tyrosine kinase genes (NTRK1, NTRK2, and NTRK3) are the most common mechanism of oncogenic activation for this family of receptors, resulting in sustained cancer cell proliferation. Several targeted therapies have been approved for tumours harbouring NTRK fusions and a new generation of TRK inhibitors has already been developed due to acquired resistance. We established a patient‐derived LMNA::NTRK1‐rearranged soft‐tissue sarcoma cell model ex vivo with an acquired resistance to targeted TRK inhibition. Molecular profiling of the resistant clones revealed an acquired NF2 loss of function mutation that was absent in the parental cell model. Parental cells showed continuous sensitivity to TRK‐targeted treatment, whereas the resistant clones were insensitive. Furthermore, resistant clones showed upregulation of the MAPK and mTOR/AKT pathways in the gene expression based on RNA sequencing data and increased sensitivity to MEK and mTOR inhibitor therapy. Drug synergy was seen using trametinib and rapamycin in combination with entrectinib. Medium‐throughput drug screening further identified small compounds as potential drug candidates to overcome resistance as monotherapy or in combination with entrectinib. In summary, we developed a comprehensive model of drug resistance in an LMNA::NTRK1‐rearranged soft‐tissue sarcoma and have broadened the understanding of acquired drug resistance to targeted TRK therapy. Furthermore, we identified drug combinations and small compounds to overcome acquired drug resistance and potentially guide patient care in a functional precision oncology setting. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

Objective. The aim of the study was to develop gradient diffusion strips with substances capable of potentiating the action of antibiotics for the treatment of infections caused by multidrug-resistant strains of K. pneumoniae. Materials and Methods. The substances azidothymidine and baicalin were used to evaluate the joint action of combinations of antibiotics with substances that potentiate their action. Determination of susceptibility to combinations of antibiotics (gentamicin, cefotaxime, ciprofloxacin and chloramphenicol) with the listed substances was carried out by a modified gradient-diffusion method (cross-test). We used gradient diffusion strips, which was made in the Saint-Petersburg Pasteur Institute. We investigated clinical multidrug-resistant K. pneumoniae strains (n = 20). The result of the joint action of a combination of two compounds was assessed by calculating the fractional inhibitory concentrations ΣFIC. Results. The values of MIC decreased eightfold when azidothymidine was combined with gentamicin and two times when combined with ciprofloxacin. MIC values were not reduced by the combination of azidothymidine with cefotaxime or chloramphenicol. It has been established that azidothymidine has antibacterial activity against strains of K. pneumoniae: MIC50 – 1 μg/ml and MIC90 – 2 μg/ml. The MIC50 and MIC90 values for baicalin were > 256 μg/ml. A synergistic antibacterial effect was detected when azidothymidine was combined with gentamicin (ΣFIC 0.33–0.50). An additive effect (ΣFIC 0.65–0.84) was detected when azidothymidine was combined with ciprofloxacin. Baikalin reduced the MIC value of cefotaxime by half, and the MIC50 values for gentamicin also decreased by half. Baicalin did not affect the susceptibility of multidrug-resistant K. pneumoniae strains to ciprofloxacin and chloramphenicol. Synergism was detected in the combination of baicalin and cefotaxime (ΣFIC 0.52 – 0.75 – additive effect). Conclusions. The development of gradient diffusion strips with azidothymidine and baicalin makes it possible to simplify methods for assessing the joint action of combinations of these substances with antibiotics and to avoid time-consuming preparatory steps. Our study demonstrated that azidothymidine exhibits synergistic activity in combination with gentamicin and ciprofloxacin and baicalin – in combination with cefotaxime. Further studies are needed to evaluate the potential use of these combinations in practical healthcare.

Background: Propofol is effective and used as a kind of routine anesthetics in procedure sedative anesthesia (PSA) for ureteroscopy. However, respiratory depression and unconscious physical activity always occur during propofol-based PSA, especially in elderly patients. Esketamine has sedative and analgesic effects but without risk of cardiorespiratory depression. The purpose of this study is to investigate whether esketamine can reduce the propofol median effective dose (ED50) for successful ureteroscope insertion in elderly male patients. Materials and methods: 49 elderly male patients undergoing elective rigid ureteroscopy were randomly divided into two groups: SK Group (0.25 mg/kg esketamine+propofol) and SF Group (0.1 µg/kg sufentanil+propofol). Patients in both two groups received propofol with initial bolus dose of 1.5 mg/kg after sufentanil or esketamine was administered intravenously. The effective dose of propofol was assessed by a modified Dixon's up-and-down method and then was adjusted with 0.1 mg/kg according to the previous patient response. Patients' response to ureteroscope insertion was classified as "movement" or "no movement". The primary outcome was the ED50 of propofol for successful ureteroscope insertion with esketamine or sufentanil. The secondary outcomes were the induction time, adverse events such as hemodynamic changes, hypoxemia and body movement were also measured. Result: 49 patients were enrolled and completed this study. The ED50 of propofol for successful ureteroscope insertion in SK Group was 1.356 ± 0.11 mg/kg, which was decreased compared with that in SF Group, 1.442 ± 0.08 mg/kg (P = 0.003). The induction time in SK Group was significantly shorter than in SF Group (P = 0.001). In SK Group, more stable hemodynamic variables were observed than in SF Group. The incidence of AEs between the two groups was not significantly different. Conclusion: The ED50 of propofol with esketamine administration for ureteroscope insertion in elderly male patients is 1.356 ± 0.11 mg/kg, significantly decreased in comparsion with sufentanil. Trial registration: Chinese Clinical Trial Registry, No: ChiCTR2300077170. Registered on 1 November 2023. Prospective registration. http://www.chictr.org.cn. [ABSTRACT FROM AUTHOR]

Antibiotic drug combination therapy is critical for the successful treatment of infections caused by multidrug resistant pathogens. We investigated the efficacy of β-lactam and β-lactam/β-lactamase inhibitor combinations with other antibiotics, against the hypervirulent, ceftazidime/avibactam resistant Pseudomonas aeruginosa Liverpool epidemic strain (LES) B58. Although minimum inhibitory concentrations in vitro differed by up to eighty-fold between standard and hostmimicking media, combinatorial effects only marginally changed between conditions for some combinations. Effective combinations in vitro were further tested in a chronic, high-densitymurine infectionmodel. Colistin and azithromycin demonstrated combinatorial effects with ceftazidime and ceftazidime/avibactam both in vitro and in vivo. Conversely, while tobramycin and tigecycline exhibited strong synergy in vitro, this effect was not observed in vivo. Our approach of using host-mimicking conditions and a sophisticated animal model to evaluate drug synergy against bacterial pathogens represents a promising approach. This methodology may offer insights into the prediction of combination therapy outcomes and the identification of potential treatment failures. [ABSTRACT FROM AUTHOR]

Combination therapy is one of the promising approaches in developing therapeutics to cure complex diseases, such as Alzheimer's disease (AD). In Thai traditional medicines, the clinical application often comprises multiple botanical drugs as a formulation. The synergistic interactions between botanical drugs in combination therapies are proposed to have several advantages, including increased therapeutic efficacy, and decreased toxicity and/or adverse effects. This study aimed to explore the therapeutic functions of a botanical hybrid preparation (BHP) of two botanical drugs within a traditional multi-herbal formulation. The synergistic actions of BHP of Dracaena cochinchinensis stemwood (DCS) and Ardisia elliptica fruit (AEF) at a specific ratio of 1:9 w/w were illustrated in neuroprotection and anti-inflammation. In cultured PC12 cells, BHP of DCS and AEF showed synergistic functions in inducing neuronal differentiation, characterized by neurofilament expression and neurite outgrowth. In addition, BHP of DCS and AEF exhibited a synergistic effect in inhibiting the aggregation of Aβ, a hallmark of AD pathology. The activated BV2 microglial cells induced by LPS were synergistically suppressed by the BHP of DCS and AEF, as evaluated by the expression of pro-inflammatory markers, including TNF-α, IL-1β, and iNOS, as well as the morphological change of microglial cells. The findings suggested that the effects of BHP of DCS and AEF were greater than individual botanical drugs in a specific ratio of 1:9 w/w to enhance neuroprotective and antiinflammatory functions. [ABSTRACT FROM AUTHOR]

Background: Cepharanthin® alone or in combination with glucocorticoid (GC) has been used to treat chronic immune thrombocytopenia (ITP) since the 1990s. Cepharanthine (CEP) is one of the main active components of Cepharanthin®. The purpose of this study was to investigate the effects of CEP on GC pharmacodynamics on immune cells and analyse the possible action mechanism of their interactions. Methods: Peripheral blood mononuclear cells (PBMCs), T lymphocytic leukemia MOLT-4 cells and daunorubicin resistant MOLT-4 cells (MOLT-4/DNR) were used to evaluate the pharmacodynamics and molecular mechanisms. Drug pharmacodynamics was evaluated by WST-8 assay. P-glycoprotein function was examined by rhodamine 123 assay. CD4+CD25+Foxp3+ regulatory T cells and Th1/Th2/Th17 cytokines were detected by flow cytometry. P-glycoprotein expression and GC receptor translocation were examined by Western blot. Results: CEP synergistically increased methylprednisolone (MP) efficacy with the suppressive effect on the cell viability of PBMCs. 0.3 and 1 μM of CEP significantly inhibited P-glycoprotein efflux function of CD4+ cells, CD8+ cells, and lymphocytes (P<0.05). 0.03~3 μM of CEP also inhibited the P-glycoprotein efflux function in MOLT-4/DNR cells in a concentration-dependent manner (P<0.001). However, 0.03~3 μM of CEP did not influence P-glycoprotein expression. 0.03~0.3 μM of CEP significantly increased the GC receptor distribution from the cytoplasm to the nucleus in a concentration-dependent manner in MOLT-4/DNR cells. The combination did not influence the frequency of CD4+, CD4+CD25+ and CD4+CD25+Foxp3+ T cells or the secretion of Th1/Th2/Th17 cytokines from PBMCs. In contrast, CEP alone at 1 μM decreased the percentage of CD4+ T cell significantly (P<0.01). It also inhibited the secretion of IL-6, IL-10, IL-17, TNF-α, and IFN-γ. Conclusions: CEP synergistically promoted MP pharmacodynamics to decrease the cell viability of the mitogen-activated PBMCs, possibly via inhibiting P-glycoprotein function and potentiating GC receptor translocation. The present study provides new evidence of the therapeutic effect of Cepharanthin® alone or in combination with GC for the management of chronic ITP. [ABSTRACT FROM AUTHOR]

Motivation Combination drug therapies are effective treatments for cancer. However, the genetic heterogeneity of the patients and exponentially large space of drug pairings pose significant challenges for finding the right combination for a specific patient. Current in silico prediction methods can be instrumental in reducing the vast number of candidate drug combinations. However, existing powerful methods are trained with cancer cell line gene expression data, which limits their applicability in clinical settings. While synergy measurements on cell line models are available at large scale, patient-derived samples are too few to train a complex model. On the other hand, patient-specific single-drug response data are relatively more available. Results In this work, we propose a deep learning framework, P ersonalized D eep S ynergy P redictor (PDSP), that enables us to use the patient-specific single drug response data for customizing patient drug synergy predictions. PDSP is first trained to learn synergy scores of drug pairs and their single drug responses for a given cell line using drug structures and large scale cell line gene expression data. Then, the model is fine-tuned for patients with their patient gene expression data and associated single drug response measured on the patient ex vivo samples. In this study, we evaluate PDSP on data from three leukemia patients and observe that it improves the prediction accuracy by 27% compared to models trained on cancer cell line data. Availability and implementation PDSP is available at https://github.com/hikuru/PDSP. [ABSTRACT FROM AUTHOR]

Addressing recurrent cervical cancer poses a substantial challenge. Osimertinib, an FDA-approved EGFR inhibitor, has emerged as a promising option. Our study examined its potential to enhance paclitaxel's efficacy against cervical cancer. Osimertinib effectively hindered cancer cell growth and induced apoptosis across multiple cell lines. Combined with paclitaxel, it exhibited synergy in suppressing cervical cancer cells. Importantly, osimertinib's inhibitory effect was EGFR-independent; it targeted Mnk phosphorylation, reducing eIF4E activity. In mice, the combined osimertinib-paclitaxel treatment surpassed individual drugs in inhibiting cancer growth. These preclinical findings suggest osimertinib's repurposing as a means to improve paclitaxel's effectiveness in cervical cancer treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, we delve into a challenging aspect of breast cancer known as triple-negative breast cancer (TNBC), which lacks effective treatment options due to its unique characteristics. Our focus is on investigating a novel approach by combining Sorafenib, a drug that targets cancer in several ways, with Benzyl isothiocyanate, a compound with potential cancer-fighting properties. Through our research, we aim to understand how these two treatments work together against TNBC, especially before standard treatment methods are applied. By experimenting with TNBC cell lines and observing the effects of the combined treatment, we seek to uncover a more effective strategy for managing this aggressive form of cancer. Our findings hold the promise of not only enhancing treatment efficacy but also offering new hope for patients battling TNBC, potentially leading to better outcomes and a new direction in the fight against this formidable disease. Triple-negative breast cancer (TNBC) presents a therapeutic challenge due to its complex pathology and limited treatment options. Addressing this challenge, our study focuses on the effectiveness of combination therapy, which has recently become a critical strategy in cancer treatment, improving therapeutic outcomes and combating drug resistance and metastasis. We explored a novel combination therapy employing Benzyl isothiocyanate (BITC) and Sorafenib (SOR) and their nanoformulation, aiming to enhance therapeutic outcomes against TNBC. Through a series of in vitro assays, we assessed the cytotoxic effects of BITC and SOR, both free and encapsulated. The BITC–SOR-loaded nanoparticles (NPs) were synthesized using an amphiphilic copolymer, which demonstrated a uniform spherical morphology and favorable size distribution. The encapsulation efficiencies, as well as the sustained release profiles at varied pH levels, were quantified, revealing distinct kinetics that were well-modeled by the Korsmeyer–Peppas equation. The NP delivery system showed a marked dose-dependent cytotoxicity towards TNBC cells, with an IC50 of 7.8 μM for MDA-MB-231 cells, indicating improved efficacy over free drugs, while exhibiting minimal toxicity toward normal breast cells. Furthermore, the NPs significantly inhibited cell migration and invasion in TNBC models, surpassing the effects of free drugs. These findings underscore the potential of BITC–SOR-NPs as a promising therapeutic approach for TNBC, offering targeted delivery while minimizing systemic toxicity. [ABSTRACT FROM AUTHOR]

Background and Aims: Emergence of multidrug resistance in non‐fermenting Gram‐negative bacilli is a threat to public health. Combination therapy is a strategy for the treatment of antibiotic‐resistant infections. Methods: In this cross‐sectional study, a total of 63 nonduplicate clinical isolates of Acinetobacter baumannii and Pseudomonas aeruginosa were collected from various specimens. Identification of bacterial isolates was performed by phenotypic and molecular tests. Antibiotic susceptibility patterns and detection of β‐lactamase genes were determined using the broth microdilution and polymerase chain reaction (PCR) techniques, respectively. Then, the combined effects analysis was determined by the checkerboard method. Based on the status of resistance to carbapenems (imipenem and meropenem), 25 isolates of each genus were selected for further investigation. Results: For A. baumannii, blaOXA‐23, blaOXA‐58, and blaOXA‐48 genes were positive in 21 (84%), 17 (68%), and 11 (44%) of isolates, respectively. In P. aeruginosa isolates, blaVIM was the most common gene (44%) and other genes including blaIMP, blaNDM, and blaOXA‐23 were found in nine (36%), six (24%), and three (12%) isolates, respectively. Meropenem (MER)‐tigecycline (TIG) had a significant synergistic effect against 20 (80%) A. baumannii (p value < 0.001). This combination was also efficient against 5 (20%) P. aeruginosa isolates. Moreover, the other combination, tigecycline‐amikacin (TIG‐AMK) was effective against 10 (40%) A. baumannii isolates. The combination of colistin (COL) and MER showed a significant synergistic effect against 21 (84%) A. baumannii (p value < 0.001) and 17 (68%) P. aeruginosa isolates (p value < 0.001). Conclusion: The MER‐TIG and COL‐MER combinations are promising options against resistant bacteria. Our study could be helpful for the development of a new treatment recommendation. [ABSTRACT FROM AUTHOR]

Skin is the primary and largest protective organ of the human body. It produces a number of highly evolved arsenal of factors to counter the continuous assault of foreign materials and pathogens from the environment. One such potent factor is the repertoire of Antimicrobial Peptides (AMPs) that not only directly destroys invading pathogens, but also optimally modulate the immune functions of the body to counter the establishment and spread of infections. The canonical direct antimicrobial functions of these AMPs have been in focus for a long time to design principles for enhanced therapeutics, especially against the multi-drug resistant pathogens. However, in recent times the immunomodulatory functions performed by these peptides at sub-microbicidal concentrations have been a point of major focus in the field of host-directed therapeutics. Such strategies have the added benefit of not having the pathogens develop resistance against the immunomodulatory pathways, since the pathogens exploit these signaling pathways to obtain and survive within the host. Thus, this review summarizes the potent immunomodulatory effect of these AMPs on, specifically, the different host immune cells with the view of providing a platform of information that might help in designing studies to exploit and formulate effective host-directed adjunct therapeutic strategies that would synergies with drug regimens to counter the current diversity of drug-resistant skin opportunistic pathogens. [ABSTRACT FROM AUTHOR]

Motivation: Drug combination therapies have shown promise in clinical cancer treatments. However, it is hard to experimentally identify all drug combinations for synergistic interaction even with high-throughput screening due to the vast space of potential combinations. Although a number of computational methods for drug synergy prediction have proven successful in narrowing down this space, fusing drug pairs and cell line features effectively still lacks study, hindering current algorithms from understanding the complex interaction between drugs and cell lines. Results: In this paper, we proposed a Permutable feature fusion network for Drug-Drug Synergy prediction, named PermuteDDS. PermuteDDS takes multiple representations of drugs and cell lines as input and employs a permutable fusion mechanism to combine drug and cell line features. In experiments, PermuteDDS exhibits state-of-the-art performance on two benchmark data sets. Additionally, the results on independent test set grouped by different tissues reveal that PermuteDDS has good generalization performance. We believed that PermuteDDS is an effective and valuable tool for identifying synergistic drug combinations. It is publicly available at https://github.com/littlewei-lazy/PermuteDDS. Scientific contribution: First, this paper proposes a permutable feature fusion network for predicting drug synergy termed PermuteDDS, which extract diverse information from multiple drug representations and cell line representations. Second, the permutable fusion mechanism combine the drug and cell line features by integrating information of different channels, enabling the utilization of complex relationships between drugs and cell lines. Third, comparative and ablation experiments provide evidence of the efficacy of PermuteDDS in predicting drug-drug synergy. [ABSTRACT FROM AUTHOR]

Simple Summary: Radium-223 is used for the management of metastatic castration-resistant prostate cancer. However, the response to this treatment is poor. Targeting the DNA damage response pathway through pharmacological inhibition has the ability to enhance the radiation response. In this study, we investigated the radiosensitising effects of three different DNA damage response inhibitors targeting ATM, ATR, and PARP in combination with X-rays and radium-223 on human prostate cancer cell lines. Their effects on cell survival, DNA double-strand break repair, cell cycle distribution, and apoptosis were evaluated. We determined that these inhibitors increase the ability of X-rays and radium-223 to kill prostate cells to varying degrees. Moreover, inhibition of the DNA damage response pathways impeded the repair of radiation-induced DNA double-strand breaks and induced changes in cell cycle distribution. Altogether, our study determined DDR inhibition as a promising strategy to increase the effectiveness of treatments utilising X-rays and/or 223Ra for localised and metastatic castration-resistant prostate cancer. Radium-223 (223Ra) and Lutetium-177-labelled-PSMA-617 (177Lu-PSMA) are currently the only radiopharmaceutical treatments to prolong survival for patients with metastatic-castration-resistant prostate cancer (mCRPC); however, mCRPC remains an aggressive disease. Recent clinical evidence suggests patients with mutations in DNA repair genes associated with homologous recombination have a greater clinical benefit from 223Ra. In this study, we aimed to determine the utility of combining DNA damage response (DDR) inhibitors to increase the therapeutic efficacy of X-rays, or 223Ra. Radiobiological responses were characterised by in vitro assessment of clonogenic survival, repair of double strand breaks, cell cycle distribution, and apoptosis via PARP-1 cleavage. Here, we show that DDR inhibitors increase the therapeutic efficacy of both radiation qualities examined, which is associated with greater levels of residual DNA damage. Co-treatment of ATM or PARP inhibition with 223Ra increased cell cycle arrest in the G2/M phase. In comparison, combined ATR inhibition and radiation qualities caused G2/M checkpoint abrogation. Additionally, greater levels of apoptosis were observed after the combination of DDR inhibitors with 223Ra. This study identified the ATR inhibitor as the most synergistic inhibitor for both radiation qualities, supporting further pre-clinical evaluation of DDR inhibitors in combination with 223Ra for the treatment of prostate cancer. [ABSTRACT FROM AUTHOR]

Drug combination therapy is generally more effective than monotherapy in the field of cancer treatment. However, screening for effective synergistic combinations from a wide range of drug combinations is particularly important given the increase in the number of available drug classes and potential drug-drug interactions. Existing methods for predicting the synergistic effects of drug combinations primarily focus on extracting structural features of drug molecules and cell lines, but neglect the interaction mechanisms between cell lines and drug combinations. Consequently, there is a deficiency in comprehensive understanding of the synergistic effects of drug combinations. To address this issue, we propose a drug combination synergy prediction model based on multi-source feature interaction learning, named MFSynDCP, aiming to predict the synergistic effects of anti-tumor drug combinations. This model includes a graph aggregation module with an adaptive attention mechanism for learning drug interactions and a multi-source feature interaction learning controller for managing information transfer between different data sources, accommodating both drug and cell line features. Comparative studies with benchmark datasets demonstrate MFSynDCP's superiority over existing methods. Additionally, its adaptive attention mechanism graph aggregation module identifies drug chemical substructures crucial to the synergy mechanism. Overall, MFSynDCP is a robust tool for predicting synergistic drug combinations. The source code is available from GitHub at https://github.com/kkioplkg/MFSynDCP. [ABSTRACT FROM AUTHOR]

Background: The plasma cell malignancy, multiple myeloma (MM), remains incurable despite advanced treatment protocols. Overexpression of Bcl-2 (an anti-apoptotic protein), in MM harboring the translocation (11;14), contributes to resistance to prior therapy. Venetoclax, a selective oral inhibitor of BCL-2 is a novel agent that shows promise as a therapeutic agent. Aims: The objective of this systematic review is to address how the use of venetoclax, alone or as a combination regimen, contributed to the treatment of patients with t(11:14) positive relapsed/refractory multiple myeloma (RRMM). Data sources: This systematic review was conducted in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was done on 5th June 2022. A literature search was conducted on PubMed and Scopus, 145 articles were screened and 10 studies were included. Risk of bias assessment was performed using the Methodological Index for Non-Randomized Studies (MINORS) criteria. Data summary: Across the studies reviewed, a total of 311 patients were identified with t(11;14) positive RRMM. The overall response rate achieved ranged between 33% and 95.5%. Furthermore, the use of venetoclax has exhibited a favorable adverse effect profile. Side effects included hematological side effects, nausea, vomiting, and diarrhea. Conclusion: Venetoclax demonstrates promising results. When given with drugs like dexamethasone, daratumumab and carfilzomib, a synergistic effect is seen in treating translocation (11:14) positive relapsed/refractory MM. The use of venetoclax in clinical practice can potentially improve outcomes and quality of life in RRMM patients, and future research should continue to explore this promising treatment option. [ABSTRACT FROM AUTHOR]

Background: Glioblastoma (GBM) stands out as the most prevalent primary brain tumor characterized by its high aggressiveness. Numerous therapeutic approaches have been employed, and the utility of combination therapies has been substantiated, particularly in GBM treatment. Cisplatin, an anticancer chemotherapeutic agent, is employed for the management of various malignancies, including GBM; however, it is associated with significant systemic toxicity. In the realm of combination therapy, metformin, a biguanide drug conventionally used as a first-line treatment for type 2 diabetes, has recently emerged as a valuable adjunct in the treatment of a diverse spectrum of tumors. This study aimed to elucidate the impact of metformin on sensitizing the human cerebral GBM cancer cell line (AMGM) to cisplatin chemotherapy by employing the comet assay as a means to assess DNA damage, thereby advocating the potential of metformin as an adjuvant for cisplatin-based therapy. Method: In this experimental study, the AMGM cell line was cultured and subsequently treated with either single-agent cisplatin, metformin, or a combination of both drugs. Cell viability was assessed through growth inhibition calculations. The Chou--Talalay analysis was used to assess the cooperative effect of this drug combination. Furthermore, DNA fragmentation was quantified using the alkaline comet assay technique. Results: The findings demonstrate that metformin significantly potentiates the therapeutic efficacy of cisplatin by synergistically inhibiting the growth of AMGM cells and reducing DNA damage. Conclusion: These results underscore the potential utility of metformin as a valuable adjunct in enhancing the clinical effectiveness of chemotherapy regimens. [ABSTRACT FROM AUTHOR]

Background: Evidence suggests that statins can improve survival outcomes and ameliorate treatment-related side-effects in certain malignancies. Statins exhibit various mechanisms of action, including apoptosis induction, proliferation inhibition, tumor radiosensitization, lipid production suppression, and anti-inflammatory effects. This trial aimed to assess the impact of lovastatin on patients with locally advanced head and neck squamous cell carcinoma (HNSCC) undergoing definitive chemoradiation. Method: In this double-blinded randomized phase 2 clinical trial, 35 patients were randomly allocated to receive either 80 mg of lovastatin daily in conjunction with chemoradiotherapy (case group, n=18) or a placebo (control group). Primary outcomes included the response rate (RR) after three months, the occurrence of acute/late side-effects, median progression-free survival (PFS), and overall survival (OS). Results: The complete RR was slightly higher in the statin group (83.3% vs. 64.7%), although it did not reach statistical significance (P = 0.592). Acute adverse events did not significantly differ between the two groups. Grade 3 dermatitis occurred more frequently in the placebo group (35.3% vs. 11.1%), while grade 3 mucositis was more common in the statin group (38.9% vs. 11.8%). The median OS was 22 months (confidence interval (CI) 95% = 6.3-37.6) in the statin group and 17 months (CI 95% = 4.9-29.1) in the control group (P = 0.50). Median PFS was 20 months (CI 95% = 15.8-24.1) in the statin group and 15 months (CI 95% = 8.2-21.7) in the control group (P = 0.609). Conclusion: Combining lovastatin with chemoradiation augments the therapeutic effect in HNSCC. Larger-scale studies incorporating advanced radiotherapy techniques and baseline lipid profile assessments are necessary to investigate statins' efficacy in HNSCC further. [ABSTRACT FROM AUTHOR]

Over the last decades, low vitamin B12 status has been reported in individuals with type 2 diabetes mellitus (T2DM). Metformin, the first-line therapy for lowering blood glucose, is the main driving factor behind this association. Although the relationship between vitamin B12 deficiency and metformin is well established, results of studies on the exact effect of the dose and duration of the therapy remain inconsistent. Additionally, a lack of consensus on the definition of vitamin B12 deficiency adds to the conflicting literature. The objectives of this review were to analyze and synthesize the findings on the effects of metformin dose and duration on vitamin B12 status in patients with T2DM and to outline the potential mechanisms underlying metformin's effect on vitamin B12. Metformin therapy has adversely affected serum vitamin B12 concentrations, a marker of vitamin B12 status. The metformin usage index (a composite score of metformin dose and duration) might serve as a potential risk assessment tool for vitamin B12 screening in patients with T2DM. Considering the health implications of suboptimal vitamin B12 status, vitamin B12 concentrations should be monitored periodically in high-risk patients, such as vegans who are receiving metformin therapy for T2DM. Additionally, it is prudent to implement lifestyle strategies concurrent with metformin therapy in individuals with T2DM, promoting an overall synergistic effect on their glycemic control. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM), is a frequent class of malignant brain tumors. Epigenetic therapy, especially with synergistic combinations is highly paid attention for aggressive solid tumors like GBM. Here, RSM optimization has been used to increase the efficient arrest of U87 and U251 cell lines due to synergistic effects. Cell lines were treated with SAHA, 5-Azacytidine, GSK-126, and PTC-209 individually and then RSM was used to find most effective combinations. Results showed that optimized combinations significantly reduce cell survival and induce cell cycle arrest and apoptosis in both cell lines. Expression of cyclin B1 and cyclin D1 were decreased while caspase3 increased expression. [ABSTRACT FROM AUTHOR]

Simple Summary: The heterogeneous response of cancer cells to targeted drugs is associated with the state transition dynamics of a molecular network. Identifying combinatorial drug targets to compensate for these heterogeneous responses can counteract adaptive resistance in cancer. To achieve this, we developed an algorithm called "merged transition map", which explores essential state transition dynamics to identify combinatorial drug targets. Our analysis showed that drug-induced state conflicts within the molecular regulatory motifs of a network can result in heterogeneous responses. Moreover, we found that addressing these conflicts with additional perturbations can synergistically improve drug efficacy. Compared to other network control algorithms, our approach showed higher performance in drug efficacy of the suggested combinatorial target pairs with reduced computational complexity. Furthermore, by applying the MTM on a Boolean network model, we identified a new target combination that induces apoptosis in gastric cancer, supported by previous experimental data. Inducing apoptosis in cancer cells is a primary goal in anti-cancer therapy, but curing cancer with a single drug is unattainable due to drug resistance. The complex molecular network in cancer cells causes heterogeneous responses to single-target drugs, thereby inducing an adaptive drug response. Here, we showed that targeted drug perturbations can trigger state conflicts between multi-stable motifs within a molecular regulatory network, resulting in heterogeneous drug responses. However, we revealed that properly regulating an interconnecting molecule between these motifs can synergistically minimize the heterogeneous responses and overcome drug resistance. We extracted the essential cellular response dynamics of the Boolean network driven by the target node perturbation and developed an algorithm to identify a synergistic combinatorial target that can reduce heterogeneous drug responses. We validated the proposed approach using exemplary network models and a gastric cancer model from a previous study by showing that the targets identified with our algorithm can better drive the networks to desired states than those with other control theories. Of note, our approach suggests a new synergistic pair of control targets that can increase cancer drug efficacy to overcome adaptive drug resistance. [ABSTRACT FROM AUTHOR]

The authors evaluated the synergistic analgesic effect of preemptive administration of 400 mg of ibuprofen (IBU) and potassium fluoride 2% (KF2), both in isolation or combination, on the painful perception of tooth sensitivity after tooth bleaching. Fifteen patients participated in this triple-blind, randomized, placebo-controlled clinical trial. The study used a crossover design for drug administration and a split-mouth design for desensitizer agent. Four paired groups were formed: IBU plus KF2 (IBU + KF2); IBU (IBU + placebo KF); KF2 (placebo IBU + KF2), and placebo (placebo IBU + placebo KF). The outcome measure was the perception of tooth sensitivity, assessed using a visual analog scale. Data were collected at 4 different times: immediately after tooth bleaching (baseline) and after 6, 30, and 54 hours. Statistical analysis was performed using the Friedman test and relative risk. IBU plus KF2 was found to be more effective in reducing tooth sensitivity immediately after bleaching (baseline) compared with the placebo group (P <.05). The risk of experiencing moderate or severe tooth sensitivity was approximately 4 times higher in the placebo group than in the IBU plus KF2 group (relative risk, 4.00; 95% CI, 1.01 to 15.81; P =.025). The combined use of 400 mg of IBU and KF2 appears to be beneficial in managing postbleaching tooth sensitivity. It provides a superior analgesic effect compared with placebo. The preemptive administration of IBU plus KF2 reduces tooth sensitivity after tooth whitening when compared with placebo. This clinical trial was registered in the Brazilian Clinical Trials Registry Platform. The registration number is U1111-1249-8191. [ABSTRACT FROM AUTHOR]

As cancer continues to rise globally, there is growing interest in discovering novel methods for prevention and treatment. Due to the limitations of traditional cancer therapies, there has been a growing emphasis on investigating herbal remedies and exploring their potential synergistic effects when combined with chemotherapy drugs. Cinnamaldehyde, derived from cinnamon, has gained significant attention for its potential role in cancer prevention and treatment. Extensive research has demonstrated that cinnamaldehyde exhibits promising anticancer properties by modulating various cellular processes involved in tumor growth and progression. However, challenges and unanswered questions remain regarding the precise mechanisms for its effective use as an anticancer agent. This article aims to explore the multifaceted effects of cinnamaldehyde on cancer cells and shed light on these existing issues. Cinnamaldehyde has diverse anti-cancer mechanisms, including inducing apoptosis by activating caspases and damaging mitochondrial function, inhibiting tumor angiogenesis, anti-proliferation, anti-inflammatory and antioxidant. In addition, cinnamaldehyde also acts as a reactive oxygen species scavenger, reducing oxidative stress and preventing DNA damage and genomic instability. This article emphasizes the promising therapeutic potential of cinnamaldehyde in cancer treatment and underscores the need for future research to unlock novel mechanisms and strategies for combating cancer. By providing valuable insights into the role and mechanism of cinnamaldehyde in cancer, this comprehensive understanding paves the way for its potential as a novel therapeutic agent. Overall, cinnamaldehyde holds great promise as an anticancer agent, and its comprehensive exploration in this article highlights its potential as a valuable addition to cancer treatment options. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Cancer Biotherapy is the property of Editorial Office of Chinese Journal of Cancer Biotherapy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: As interventional procedures become more common in clinical practice, sedatives are being increasingly used to enhance patient experience, overall safety, and procedural efficacy. An appropriate sedation depth, which is crucial for patient safety, is determined according to sedative dosage, procedural stimuli, and patient status. Thus, it is important that clinicians understand the continuous nature of sedation levels. Current Concepts: Although sedation offers benefits, it also carries risks. Thus, vigilant monitoring during and after a procedure is important for preventing excessive sedation depth and related complications. Combining sedatives with analgesics, including opioids, often has a synergistic effect that necessitates a dosage reduction. Interdisciplinary guidelines for moderate sedation were recently developed to address expanding procedural scopes and patient population diversity. Discussion and Conclusion: To ensure sedation safety and success in new procedures, healthcare providers should refer to relevant studies. In cases with limited evidence, sedative dosages should be determined based on their pharmacological characteristics. [ABSTRACT FROM AUTHOR]

The scientific and applied research leads day by day to achievements unbelievable some time ago. The results also mean spectacularity, often bordering on the imagination, but also a fast pace with a high speed of appearance of novelties. An enumeration of the results that "broke the incredible" must include Dolly (the sheep cloned in 1996), Eva (Adevarul, 2002) (Eve) the first cloned human being (USA in 2002, the year of the sheep's death!), the technological steps taken in terms of transhumanism (implants and improvements of trivial level (vaccine, contact lenses, etc.) or conventional (Alexander, 2015) (drugs for mental potentiation, bionic prostheses, more recently implants under the skin (Buhnici, 2017) or dedicated chip brains, etc.... (Neuralink, Neuravista, Second Sight (the bionic eyes). [ABSTRACT FROM AUTHOR]

The role of reactive oxygen species (ROS) in the killing exerted by antibiotics on bacteria is debated. Evidence attributes part of toxicity of many antibiotics to their ability to generate ROS by interfering with cellular metabolism, but some studies dismiss the role of ROS. Bicyclomycin (BCM) is a broad-spectrum antibiotic that is the only known compound to inhibit E. coli transcription terminator factor Rho with no known other cellular targets. In the present study, we addressed this question by checking whether the induction of oxidative stress could explain the increased sensitivity to Bicyclomycin in the hns deleted strain even in Δkil background in E. coli. BCM evoked the generation of ROS in E. coli cells. BCM is known to cause the cell filamentation phenotype in E. coli. Performing fluorescence microscopic analysis, we show that bicyclomycin-dependent cell filamentation is associated with SOS response. RecA-GFP filaments were found to colocalize with the damaged DNA sites in the cell. Further analysis revealed that the genomic DNA was partitioned but the cell septum formation was severely affected under BCM treatment. Furthermore, we observed biofilm formation by E. coli after BCM treatment. We hypothesize that ROS production after BCM treatment could lead to cell filamentation in bacteria. A better understanding of the mode of toxicity of BCM will help us design better antibiotic treatment regimes for clinical practices, including combinatorial drug therapies. The cell filamentation phenotype observed after BCM treatment makes this antibiotic a promising drug for phage-antibiotic synergy (PAS) therapy. [ABSTRACT FROM AUTHOR]

Background: Periodontitis is a chronic inflammatory disease that occurs in tooth-supporting tissues. Controlling inflammation and alleviating periodontal tissue destruction are key factors in periodontal therapy. This study aimed to develop an in situ curcumin/zinc oxide (Cur/ZNP) hydrogel and investigate its characteristics and effectiveness in the treatment of periodontitis. Methods: Antibacterial activity and cytotoxicity assays were performed in vitro. To evaluate the effect of the in situ Cur/ZNP hydrogel on periodontitis in vivo, an experimental periodontitis model was established in Sprague‒Dawley rats via silk ligature and inoculation of the maxillary first molar with Porphyromonas gingivalis. After one month of in situ treatment with the hydrogel, we examined the transcriptional responses of the gingiva to the Cur/ZNP hydrogel treatment and detected the alveolar bone level as well as the expression of osteocalcin (OCN) and osteoprotegerin (OPG) in the periodontal tissues of the rats. Results: Cur/ZNPs had synergistic inhibitory effects on P. gingivalis and good biocompatibility. RNA sequencing of the gingiva showed that immune effector process-related genes were significantly induced by experimental periodontitis. Carcinoembryonic antigen-related cell adhesion molecule 1 (Ceacam1), which is involved in the negative regulation of bone resorption, was differentially regulated by the Cur/ZNP hydrogel but not by the Cur hydrogel or ZNP hydrogel. The Cur/ZNP hydrogel also had a stronger protective effect on alveolar bone resorption than both the Cur hydrogel and the ZNP hydrogel. Conclusion: The Cur/ZNP hydrogel effectively inhibited periodontal pathogenic bacteria and alleviated alveolar bone destruction while exhibiting favorable biocompatibility. [ABSTRACT FROM AUTHOR]

Background: HBV infection can result in severe liver diseases and is one of the primary causes of liver cell carcinoma-related mortality. Liuwei Wuling tablet (LWWL) is a traditional Chinese medicine formula, with a protecting liver and decreasing enzyme activity, usually used to treat chronic hepatitis B with NAs in clinic. However, its main active ingredients and mechanism of action have not been fully investigated. Hence, we aimed to screen the active ingredient and effective ingredient combinations from Liuwei Wuling tablet to explore the anti-herpatitis B virus activity and mechanism. Methods: Analysis and screening of effective antiviral components in LWWL by network pharmacology, luteolin (Lut) may be a compound with significant antiviral activity. The mechanism of antiviral action of Lut was also found by real-time PCR detection and western blotting. Meanwhile, we established a co-culture model to investigate the antiviral mechanism of Schisandrin C (SC), one of the main active components of Schisandra chinensis fructus (the sovereign drug of LWWL). Next, HBV-infected mice were established by tail vein injection of pAAV-HBV1.2 plasmid and administered continuously for 20 days. And their antiviral capacity was evaluated by checking serum levels of HBsAg, HBeAg, levels of HBV DNA, and liver levels of HBcAg. Results: In this study, we conducted network pharmacology analysis on LWWL, and through in vitro experimental validation and data analysis, we found that luteolin (Lut) possessed obviously anti-HBV activity, inhibiting HBV replication by downregulating hepatocyte nuclear factor 4α (HNF4α) via the ERK pathway. Additionally, we established a co-culture system and proved that SC promoted activation of cGAS-STINIG pathway and IFN-β production in THP-1 cells to inhibit HBV replication in HepG2.2.15 cells. Moreover, we found the combination of SC and Lut shows a greater effect in inhibiting HBV compared to SC or Lut alone in HBV-infected mice. Conclusion: Taken together, our study suggests that combination of SC and Lut may be potential candidate drug for the prevention and treatment of chronic hepatitis B. [ABSTRACT FROM AUTHOR]

Nano-sized biomaterials are innovative drug carriers with nanometric dimensions. Designed with biocompatibility in mind, they enable precise drug delivery while minimizing side effects. Controlled release of therapeutic substances enhances efficacy, opening new possibilities for treating neurological and oncological diseases. Integrated diagnostic-therapeutic nanosystems allow real-time monitoring of treatment effectiveness, which is crucial for therapy personalization. Utilizing biomaterials as nano-sized carriers in conjunction with drugs represents a promising direction that could revolutionize the field of pharmaceutical therapy. Such carriers represent groundbreaking drug delivery systems on a nanometric scale, designed with biocompatibility in mind, enabling precise drug delivery while minimizing side effects. Using biomaterials in synergy with drugs demonstrates significant potential for a revolutionary impact on pharmaceutical therapy. Conclusions drawn from the review indicate that nano-sized biomaterials constitute an innovative tool that can significantly improve therapy effectiveness and safety, especially in treating neurological and oncological diseases. These findings should guide researchers towards further studies to refine nano-sized biomaterials, assess their effectiveness under various pathological conditions, and explore diagnostic-therapeutic applications. Ultimately, these results underscore the promising nature of nano-sized biomaterials as advanced drug carriers, ushering in a new era in nanomedical therapy. [ABSTRACT FROM AUTHOR]

Combinations of drugs have demonstrated potential therapeutic results in controlling the progression of cancer, with a possible decrease in toxicity and unfavorable side efects. Experimental screening is no longer feasible due to the vast number of possible medication combinations. As a result, the scientific community is becoming more and more interested in creating computational models that can quickly and precisely identify prospective drug combinations. Our methodology employs therapeutically significant drugs and cell line properties in machine learning techniques. Our suggested stacked machine learning model outperforms all other machine learning models taken into consideration. It employs Random Forest and XGBoost as base learners and Logistic Regression as a meta learner. The results of our research underscore the remarkable efficacy of our approach. Not only does it address the complexities of the task at hand, but it also showcases its potential to enhance predictive accuracy within this domain. The comparative analysis reveals that our model exhibits a noteworthy performance improvement across multiple evaluation metrics. Our findings represent a significant step forward in the quest for improved cancer treatment strategies. [ABSTRACT FROM AUTHOR]

Drug combination therapy shows promise in cancer treatment by addressing drug resistance, reducing toxicity, and enhancing therapeutic efficacy. However, the intricate and dynamic nature of biological systems makes identifying potential synergistic drugs a costly and time-consuming endeavor. To facilitate the development of combination therapy, techniques employing artificial intelligence have emerged as a transformative solution, providing a sophisticated avenue for advancing existing therapeutic approaches. In this study, we developed SynerGNet, a graph neural network model designed to accurately predict the synergistic effect of drug pairs against cancer cell lines. SynerGNet utilizes cancer-specific featured graphs created by integrating heterogeneous biological features into the human protein–protein interaction network, followed by a reduction process to enhance topological diversity. Leveraging synergy data provided by AZ-DREAM Challenges, the model yields a balanced accuracy of 0.68, significantly outperforming traditional machine learning. Encouragingly, augmenting the training data with carefully constructed synthetic instances improved the balanced accuracy of SynerGNet to 0.73. Finally, the results of an independent validation conducted against DrugCombDB demonstrated that it exhibits a strong performance when applied to unseen data. SynerGNet shows a great potential in detecting drug synergy, positioning itself as a valuable tool that could contribute to the advancement of combination therapy for cancer treatment. [ABSTRACT FROM AUTHOR]

Discovering effective anti-tumor drug combinations is crucial for advancing cancer therapy. Taking full account of intricate biological interactions is highly important in accurately predicting drug synergy. However, the extremely limited prior knowledge poses great challenges in developing current computational methods. To address this, we introduce SynergyX, a multi-modality mutual attention network to improve anti-tumor drug synergy prediction. It dynamically captures cross-modal interactions, allowing for the modeling of complex biological networks and drug interactions. A convolution-augmented attention structure is adopted to integrate multi-omic data in this framework effectively. Compared with other state-of-the-art models, SynergyX demonstrates superior predictive accuracy in both the General Test and Blind Test and cross-dataset validation. By exhaustively screening combinations of approved drugs, SynergyX reveals its ability to identify promising drug combination candidates for potential lung cancer treatment. Another notable advantage lies in its multidimensional interpretability. Taking Sorafenib and Vorinostat as an example, SynergyX serves as a powerful tool for uncovering drug-gene interactions and deciphering cell selectivity mechanisms. In summary, SynergyX provides an illuminating and interpretable framework, poised to catalyze the expedition of drug synergy discovery and deepen our comprehension of rational combination therapy. [ABSTRACT FROM AUTHOR]

Lycium barbarum, known as goji berry or wolfberry, is a fruit long associated with health benefits, showing a plethora of effects ranging from antioxidant, anticancer, anti-inflammatory, and immunomodulatory effects. Its potential is attributed to the significant presence of polysaccharides, glycopeptides, polyphenols, flavonoids, carotenoids, and their derivatives. These compounds effectively counteract the action of free radicals, positively influencing cellular balance and intracellular signaling, contributing to overall cell health and function acting on multiple molecular pathways. Several fractions extracted from goji berries demonstrate antitumor properties, particularly effective against breast cancer, without showing cytotoxic effects on normal human cells. Hence, the review explored the fundamental traits of bioactive elements in Lycium barbarum and their potential in cancer treatment and, specifically, breast cancer. It focused on elucidating wolfberry's influenced biochemical pathways, its synergism with anticancer drugs, and its potential to alleviate the side effects associated with existing cancer treatments. [ABSTRACT FROM AUTHOR]

Copyright of Namık Kemal Tıp Dergisi is the property of Galenos Yayinevi Tic. LTD. STI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Cancer Biotherapy is the property of Editorial Office of Chinese Journal of Cancer Biotherapy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: Antimalarial drug resistance is a global public health problem that leads to treatment failure. Synergistic drug combinations can improve treatment outcomes and delay the development of drug resistance. Here, we describe the implementation of a freely available computational tool, Machine Learning Synergy Predictor (MLSyPred©), to predict potential synergy in antimalarial drug combinations. Methods: The MLSyPred© synergy prediction method extracts molecular fingerprints from the drugs' biochemical structures to use as features and also cleans and prepares the raw data. Five machine learning algorithms (Logistic Regression, Random Forest, Support vector machine, Ada Boost, and Gradient Boost) were implemented to build prediction models. Implementation and application of the MLSyPred© tool were tested using datasets from 1540 combinations of 79 drugs and compounds biologically evaluated in pairs for three strains of Plasmodium falciparum (3D7, HB3, and Dd2). Results: The best prediction models were obtained using Logistic Regression for antimalarials with the strains Dd2 and HB3 (0.81 and 0.70 AUC, respectively) and Random Forest for antimalarials with 3D7 (0.69 AUC). The MLSyPred© tool yielded 45% precision for synergistically predicted antimalarial drug combinations that were annotated and biologically validated, thus confirming the functionality and applicability of the tool. Conclusion: The MLSyPred© tool is freely available and represents a promising strategy for discovering potential synergistic drug combinations for further development as novel antimalarial therapies. [ABSTRACT FROM AUTHOR]

The SS18-SSX fusion protein is an oncogenic driver in synovial sarcoma. At the molecular level, SS18-SSX functions as both an activator and a repressor to coordinate transcription of different genes responsible for tumorigenesis. Here, we identify the proto-oncogene FYN as a new SS18-SSX target gene and examine its relation to synovial sarcoma therapy. FYN is a tyrosine kinase that promotes cancer growth, metastasis and therapeutic resistance, but SS18-SSX appears to negatively regulate FYN expression in synovial sarcoma cells. Using both genetic and histone deacetylase inhibitor (HDACi)-based pharmacologic approaches, we show that suppression of SS18-SSX leads to FYN reactivation. In support of this notion, we find that blockade of FYN activity synergistically enhances HDACi action to reduce synovial sarcoma cell proliferation and migration. Our results support a role for FYN in attenuation of anti-cancer activity upon inhibition of SS18-SSX function and demonstrate the feasibility of targeting FYN to improve the effectiveness of HDACi treatment against synovial sarcoma.

There is some controversy regarding the interactions between creatine (CRE) and caffeine (CAF) supplements. The aim of this systematic review was to study whether such ergogenic interaction occurs and to analyze the protocol to optimize their synchronous use. The PubMed, Web of Science, MEDLINE, CINAHL, and SPORTDiscus databases were searched until November 2021 following the PRISMA guidelines. Ten studies were included. Three studies observed that CRE loading before an acute dose of CAF before exercise did not interfere in the beneficial effect of CAF, whereas one study reported that only an acute supplementation (SUP) of CAF was beneficial but not the acute SUP of both. When chronic SUP with CRE + CAF was used, two studies reported that CAF interfered in the beneficial effect of CRE, whereas three studies did not report interaction between concurrent SUP, and one study reported synergy. Possible mechanisms of interaction are opposite effects on relaxation time and gastrointestinal distress derived from concurrent SUP. CRE loading does not seem to interfere in the acute effect of CAF. However, chronic SUP of CAF during CRE loading could interfere in the beneficial effect of CRE. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is the most common malignancy among women worldwide. Despite advances in treating breast cancer over the past decades, drug resistance and adverse effects remain challenging. Recent therapeutic progress has shifted toward using drug combinations for better treatment efficiency. However, with a growing number of potential small-molecule cancer inhibitors, in silico strategies to predict pharmacological synergy before experimental trials are required to compensate for time and cost restrictions. Many deep learning models have been previously proposed to predict the synergistic effects of drug combinations with high performance. However, these models heavily relied on a large number of drug chemical structural fingerprints as their main features, which made model interpretation a challenge. Results: This study developed a deep neural network model that predicts synergy between small-molecule pairs based on their inhibitory activities against 13 selected key proteins. The synergy prediction model achieved a Pearson correlation coefficient between model predictions and experimental data of 0.63 across five breast cancer cell lines. BT-549 and MCF-7 achieved the highest correlation of 0.67 when considering individual cell lines. Despite achieving a moderate correlation compared to previous deep learning models, our model offers a distinctive advantage in terms of interpretability. Using the inhibitory activities against key protein targets as the main features allowed a straightforward interpretation of the model since the individual features had direct biological meaning. By tracing the synergistic interactions of compounds through their target proteins, we gained insights into the patterns our model recognized as indicative of synergistic effects. Conclusions: The framework employed in the present study lays the groundwork for future advancements, especially in model interpretation. By combining deep learning techniques and target-specific models, this study shed light on potential patterns of target-protein inhibition profiles that could be exploited in breast cancer treatment. [ABSTRACT FROM AUTHOR]

Breast cancer is one of the most common types of cancer in females. While drug combinations have shown potential in breast cancer treatments, identifying new effective drug pairs is challenging due to the vast number of possible combinations among available compounds. Efforts have been made to accelerate the process with in silico predictions. Here, we developed a Boolean model of signaling pathways in breast cancer. The model was tailored to represent five breast cancer cell lines by integrating information about cell-line specific mutations, gene expression, and drug treatments. The models reproduced cell-line specific protein activities and drug-response behaviors in agreement with experimental data. Next, we proposed a calculation of protein synergy scores (PSSs), determining the effect of drug combinations on individual proteins' activities. The PSSs of selected proteins were used to investigate the synergistic effects of 150 drug combinations across five cancer cell lines. The comparison of the highest single agent (HSA) synergy scores between experiments and model predictions from the MDA-MB-231 cell line achieved the highest Pearson's correlation coefficient of 0.58 with a great balance among the classification metrics (AUC = 0.74, sensitivity = 0.63, and specificity = 0.64). Finally, we clustered drug pairs into groups based on the selected PSSs to gain further insights into the mechanisms underlying the observed synergistic effects of drug pairs. Clustering analysis allowed us to identify distinct patterns in the protein activities that correspond to five different modes of synergy: 1) synergistic activation of FADD and BID (extrinsic apoptosis pathway), 2) synergistic inhibition of BCL2 (intrinsic apoptosis pathway), 3) synergistic inhibition of MTORC1, 4) synergistic inhibition of ESR1, and 5) synergistic inhibition of CYCLIN D. Our approach offers a mechanistic understanding of the efficacy of drug combinations and provides direction for selecting potential drug pairs worthy of further laboratory investigation. [ABSTRACT FROM AUTHOR]

Large language models (LLMs) have been shown to have significant potential in few-shot learning across various fields, even with minimal training data. However, their ability to generalize to unseen tasks in more complex fields, such as biology and medicine has yet to be fully evaluated. LLMs can offer a promising alternative approach for biological inference, particularly in cases where structured data and sample size are limited, by extracting prior knowledge from text corpora. Here we report our proposed few-shot learning approach, which uses LLMs to predict the synergy of drug pairs in rare tissues that lack structured data and features. Our experiments, which involved seven rare tissues from different cancer types, demonstrate that the LLM-based prediction model achieves significant accuracy with very few or zero samples. Our proposed model, the CancerGPT (with ~ 124M parameters), is comparable to the larger fine-tuned GPT-3 model (with ~ 175B parameters). Our research contributes to tackling drug pair synergy prediction in rare tissues with limited data, and also advancing the use of LLMs for biological and medical inference tasks. [ABSTRACT FROM AUTHOR]