Pharmacological treatment is not very effective for neuropathic pain (NP). A progressive decrease in the estimated effect of NP drugs has been reported, giving rise to an increase in the use of the multimodal analgesic approach. We performed a new, independent review to assess whether more evidence and of better-quality has become available since the last systematic review. We evaluated the efficacy, tolerability, and safety of double-blinded, randomized, controlled trials involving only adult participants and comparing combination therapy (CT: ≥ 2 drugs) to a placebo and/or at least one other comparator with an NP indication. The primary outcome assessed was the proportion of participants reporting ≥50% pain reductions from baseline. The secondary outcome assessed was the proportion of drop-outs due to treatment-emergent adverse events. After removing duplicates, 2323 citations were screened, with 164 articles assessed for eligibility, from which 16 were included for qualitative analysis. From the latter, only five lasted for at least 12 weeks and only six complied with the required data for complete analysis. CT has been adopted for years without robust evidence. Efforts have been made to achieve better-quality evidence, but the quality has not improved over the years. In this regard, guidelines for NP should attempt to make recommendations about CT research, prioritizing which combinations to analyze.

Colorectal cancer (CRC) is considered as one of the leading types of cancer in the world. CD133, as a cancer stem cell marker, has a pivotal role in the development of drug resistance, migration, and stemness properties of CRC cells. This study designed to check the combined effect of CD133siRNA and Oxaliplatin on proliferation, migration, apoptosis, and stemness properties of CRC cells in HT-29 cell line.MTT assay was performed to define the combined effect of CD133siRNA and Oxaliplatin on the viability of HT-29 cells. In order to figure out the effect of this combination therapy on CD133 expression at the gene and protein level, qRT-PCR and western blot were exploited, respectively. The ability of cell migration was tested by wound healing assay as well. Also, colony formation and sphere formation were conducted to assess the stemness properties in the combination group. Flow cytometry was conducted to investigate the apoptosis, cell cycle, and surface expression of CD133 in different groups. Finally, the expression of migration-, and stemness-associated genes were measured by qRT-PCR. We indicated that silencing of CD133 reduces the migration and stemness properties of colorectal cancerous cells. This suppression makes HT-29 cells more sensitive to Oxaliplatin and reduces the effective dose of this chemical drug. Therefore, the suppression of CD133 in combination with Oxaliplatin treatment might be a promising therapeutic approach in the treatment of colorectal cancer.

Phenotypic switching in cancer cells has been found to be present across tumor types. Recent studies on Glioblastoma report a remarkably common architecture of four well-defined phenotypes coexisting within high levels of intra-tumour genetic heterogeneity. Tumours grown from any cell type recapitulate the original phenotypic composition. Similar dynamics have been shown to occur in breast cancer, melanoma and likely across further cancer types. Given the adaptive potential of phenotypic switching (PHS) strategies, understanding how it drives tumour evolution and how to break down these architectures is a major priority. Here we model the ecological dynamics behind PHS. The model is able to reproduce experimental results, and specific conditions for cancer progression and clearance reveal novel features of plastic tumours and its direct consequences on therapy resistance. Following our results we discuss \textit{transition} therapy as a novel scheme to target not only combined cytotoxicity but also the rates of phenotypic switching.

For monitoring of chimeric antigen receptor (CAR) T-cell therapies antigen-based CAR detection methods are usually applied. However, for each target-antigen a separate detection system is required. Furthermore, when monitoring CAR T-cells in the blood of patients treated with bispecific antibodies or T-cell engagers (bsAbs/BiTEs) recognize the same antigen, these methods producing false-positive results in clinical diagnostics. Anti-CAR-linker monoclonal antibodies (mAbs) targeting the linker sequence between the variable domains of the antigen binding CAR fragment, promise an universal and unbiased CAR detection. To test this, we analyzed clinical specimens of all BCMA- and CD19 targeting CAR T-cell products currently approved for clinical use. We found a highly specific and sensitive CAR detection by using anti-CAR-linker mAb in blood cells from patients treated with Ide-cel, Tisa-cel, Axi-cel, Brexu-cel, and Liso-cel. For Ide-cel and Tisa-cel the sensitivity was significant lower compared to antigen-based CAR detection assays. Strikingly, the specificity of anti-CAR linker mAb was not affected by the simultaneous presence of bispecific blinatumomab or teclistamab for Axi-cel, Brexu-cel, Liso-cel or Ide-cel, respectively. Cilta-cel (containing an monomeric G4S-CAR linker) could not be detected by anti-CAR linker mAb. In conclusion, anti-CAR-linker mAbs are highly specific and useful for CAR T-cell monitoring but not universal applicable.

Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related mortality worldwide and a major global health burden. The treatment of HCC has experienced a paradigm shift in the last few years, following the discovery of immunotherapy. However, despite the profound success of immunotherapy in other cancer types, their response in HCC remains unsatisfactory. Some of the reasons that can explain this poor response include the immunosuppressive microenvironment of HCC, the absence of reliable biomarkers for response, and drug resistance. Previous preclinical and clinical studies have highlighted the role of combination therapy in overcoming some of these hurdles. In this article, we discuss the benefit of combining immune checkpoint inhibitors (ICIs) with stereotactic body radiation therapy (SBRT) in HCC and shed light on promising clinical trials.

Cell death resistance is a key feature of tumor cells. One of the main anti-cancer therapies is increasing the susceptibility of cells to death. Cancer cells have developed a capability of tumor immune escape. Hence, restoring the immunogenicity of cancer cells can be suggested as an effective approach against cancer. Accumulating evidence proposes that several anticancer agents provoke the release of danger-associated molecular patterns (DAMPs) that are determinants of immunogenicity and stimulate immunogenic cell death (ICD). It has been suggested that ICD inducers are two different types according to their various activities. Here, we review the well-characterized DAMPs and focus on the different types of ICD inducers and recent combination therapies that can augment the immunogenicity of cancer cells.

As cancer remains resistant to several modes of treatment, novel therapeutics are still under active investigation to overcome treatment inefficacy in cancer. Given the high attrition rate of de novo drug discovery, drug screening, and drug repurposing have offered time- and cost-effective alternative strategies for the identification of potentially effective therapeutics. In contrast to large-scale drug screens, computational approaches for drug repurposing leverage the increasing amounts of biomedical data to predict candidate therapeutic agents prior to testing in biological models. Current studies in drug repurposing for cancer therapy prediction have increasingly focused on the prediction of combination therapies, as combination therapies have numerous advantages over monotherapies. These include increased effect from synergistic interactions, reduced toxicity from lowered drug doses, and a reduced risk of resistance due to multiple non-overlapping mechanisms of action. This review provides a summary of several classes of computational methods used for drug combination therapy prediction in cancer research, including networks, regression-based machine learning, classifier machine learning models, and deep learning approaches, with the goal of presenting current progress in the field, particularly to non-computational cancer biologists. We conclude by discussing the need for further advancements in technologies that incorporate disease mechanisms, drug characteristics, multi-omics data, and clinical considerations to generate effective patient-specific drug combinations, as holistic data integration will inevitably result in optimal targeted therapeutics for cancer.

Background: At present, the treatments for patients with advanced lung cancer focus on chemotherapy, targeted therapy, immunotherapy, or a combination of multiple treatments. Purpose: The main purpose of this study is to compare the various chemotherapy-based combination therapies and find the best one for patients with advanced lung cancer. Methods: Based on database (PubMed, EMBASE and Medline) for randomized controlled trials of advanced lung cancer with combination therapy from 2008 to 2020, we searched literatures with overall survival (OS), progression-free survival (PFS), objective response rate (ORR) and adverse as outcome indicators and established a Bayesian mesh meta-analysis for multiple treatment strategies. Then, we combined the results of four outcome indicators to find out the best chemotherapy-based combination therapy strategy for patients with advanced lung cancer, further, we tried to screen out the best drugs of which were commonly used now. Results: It contained a total of 51 studies, including five combination therapies: Chemotherapy/Chemotherapy plus placebo (CT), chemotherapy plus one targeted therapy drug (CT+T), chemotherapy plus two targeted therapy drugs (CT+T+T), chemotherapy combined with immunotherapy (CT+I) or chemotherapy combined with biotherapy (CT+B). In terms of four outcome indicators, CT+I showed the best therapeutic benefits. In the comparison of immunotherapy drugs, pembrolizumab showed the best effect. Conclusion: Our results showed that, among the multiple chemotherapy-based combination therapy strategies, chemotherapy combined with immunotherapy is the best choice for patients with advanced lung cancer, and pembrolizumab combined with chemotherapy has the best effect.

Feline sporotrichosis is an endemic disease with high occurrence in Brazil. Itraconazole (ITZ), remains the drug of choice for treating this disease in cats, despite the increasing reports of therapeutic failure. A controlled, randomized clinical trial was performed on 166 naive cats with sporotrichosis to assess the effectiveness and safety of the combination therapy (ITZ+KI) com-pared with ITZ monotherapy. Cats were randomly allocated in two treatment groups: G1 - ITZ 100 mg/cat/day and G2 - ITZ 100mg/cat/day + KI 2.5-20 mg/kg/day. Cats treated in G2 presented 77% more risk of reaching clinical cure (a positive effect) than those treated in G1, even when controlled by negative predictors. The survival curves of the two treatment protocols indicates that clinical cure was achieved faster in G2. An increase in the KI dose was necessary in 28 cats due to persistence of clinical signs. Adverse reactions were equally frequent in both groups and manageable with a temporary drug suspension and/or a hepatoprotective therapy. The combination therapy was associated with a higher cure rate and a shorter treatment time, suggesting that ITZ+KI arises as a better option for treating feline sporotrichosis and should be considered as the first-line treatment in the presence of negative predictors.

Abstract: Background: In 2021, two randomized controlled trials (RCTs), TheraP and VISION, demonstrated that 177Lu-PSMA-617 as monotherapy was more effective for enhancing the decline of PSA than the comparator third-line treatments. Methods: Our review summarizes new RCTs that add to the use of radioligand therapy (RLT) for patients with high-risk prostate cancer (PCa). Results: Five past and present RCTs include 1139 patients. A RCT, ENZA-p, studied first-line treatment of patients with metastatic castration-resistant PCa (mCRPC). A combination of enzalutamide (ENZA) and 177Lu-PSMA-617 gave longer progression-free survival than ENZA as monotherapy. Other RCTs of patients with mCRPC, including the PSMAfore, and SPLASH trials, showed 177Lu-PSMA-617 as second-line treatment gave better progression-free survival than androgen receptor pathway inhibitors (combined p value 6 x 10-8). Conclusion: Patients with PCa may gain if they are given PSMA-RLT early in the treatment of PCa and as part of combination therapies.

Hypertension is a frequent risk factor for cardiovascular diseases and the prevalence rate is continuously rising. Multiple pathophysiological mechanisms are responsible for hypertension, necessitating a combination of drugs from different classes for best management. Combination therapy is five times more effective in decreasing blood pressure compared to escalating the dose of a single agent. As per the ACCOMPLISH trial analysis, coupling a renin-angiotensin system inhibitor with a calcium channel blocker is more effective than the combination of a renin-angiotensin system inhibitor with diuretics in reducing major cardiovascular events, cardiovascular-related mortality, and the progression of chronic kidney disease. The renin-angiotensin system can be suppressed by inhibiting the angiotensin-converting enzyme or angiotensin type 1 receptor (AT1R), resulting, in decreased vascular smooth muscle contraction, heart performance, and reduced aldosterone synthesis. Calcium channel blockers work by inhibiting L-type calcium channels, reducing heart performance via negative inotropic, chronotropic, and bathmotropic effects, along with reducing vascular smooth muscle contraction. Diuretics exert their antihypertensive impact by changing body fluid volume and electrolytes. Initially, hypertension treatment commences with a single medication but often, different classes of two or more antihypertensive medications are necessary for achieving the target blood pressure goal. Sometimes, for Resistant hypertension four different classes of antihypertensive medications are necessary to reach the target blood pressure goal.

The current study aimed to investigate the antitumor effects and potent mechanism of cytokine-induced killer (CIK) cells combined with irreversible electroporation (IRE) via an in vitro function assay in an in vivo Panc02 cell–bearing mouse model. We established an in vitro culture assay for CIK cells and determined the proportions of different peripheral lymphocytes. The antitumor effect of the combination of IRE and CIK cells in a Panc02 pancreatic-cancer (PC) subcutaneous-xenograft model was investigated; tumor size and mouse survival rates were recorded. We used flow cytometry (FCM) to analyze the proportion of intratumoral lymphocytes, the expression of chemokine receptors, and the proliferative activity of CIK cells. The proportion of cells that were positive for clusters of differentiation 3 and 8 (CD3+CD8+) and the proportion of CD3+CD56+ cells were both significantly increased after 21 days of in vitro culture. Combined IRE/CIK cell treatment significantly inhibited tumor growth and increased the survival rate of Panc02 cell–bearing mice. Furthermore, infiltration of lymphocytes into tumor tissue was significantly increased by this combination therapy compared with the untreated group or monotherapy group. In addition, IRE significantly enhanced the expression of chemokine receptors elicited by, and the proliferative activity of, CIK cells. In conclusion, IRE combined with CIK cells showed superior antitumor efficacy in a PC subcutaneous-xenograft model, which we attributed to the promotion of lymphocytic infiltration, as well as to upregulation of chemokine receptor expression and of regulators of CIK cell proliferation.

The proliferation of SARS-COV-2 through enhanced viral replication and its subsequent triggering of cytokine storm, are some of the hallmark phenotypes in severe COVID-19 patient cases. Cyclosporine, an immunosuppressant drug and Selinexor, an inhibitor of nuclear transporter protein, both have been successfully demonstrated to be effective against SARS-COV-2 infection by targeting those functions individually. However, the highly multifactorial pathology of SARS-COV-2 infection hinders any mono-therapeutic strategy to become an optimal option. In this study, we assess the potential efficacy of the Cyclosporine-Selinexor combination on an integrated interactome by adopting a network-medicine-based repositioning technique, where disease proximity, functional proximity and their topological separation are evaluated, followed by a robust statistical significance test. Results have shown that both drug target modules are highly proximal to the SARS-COV-2 disease modules in terms of network topology and functional associations, in a statistically significant manner, individually. Functional enrichment of both drug modules and SARS-COV-2 infected modules has shown that two drugs target the functions related to viral replication and cytokine storm during infection. Moreover, a high degree of network separation been those two drug target modules has been observed, revealing ``complementary exposure`` patterns, rendering this drug combination as an effective one against SARS-COV-2 infection. We hope that our results will encourage researchers to further investigate the potency of Cyclosporine and Selinexor combination in vivo or in vitro, and ultimately lead that up to clinical trials to treat SARS-COV-2 patients.

Targeted radionuclide therapy (TRT) has recently seen a surge in popularity, with the use of radionuclides conjugated to small molecules and antibodies. Similarly, immunotherapy also has shown promising results – an example being chimeric antigen receptor (CAR) T-cells therapy in hematologic malignancies. Moreover, TRT and CAR T therapies possess unique features that require special consideration when determining how to dose, time, and sequence combination treatments, including the distribution of TRT dose in the body, the decay rate of the radionuclide, and the proliferation and persistence of the CAR-T cells. These characteristics complicate additive or synergistic effects of combination therapies and warrant a mathematical treatment which includes these dynamics in relation to the proliferation and clearance rates of the target tumor cells. Here we combine two previously published mathematical models in a multiple myeloma setting to explore the effects of dose, timing, and sequencing of TRT and CAR-T cell based therapies. We find that for a fixed TRT and CAR-T cell dose, the tumor proliferation rate is the most important parameter in determining the best timing of TRT and CAR T therapies.

Cancer cells display elevated reactive oxygen species (ROS) and altered redox status, Here based on these characteristics, we develop a multi-drug delivery platform AMB@PDAP-Fe (APPF), from magnetotactic bacterium AMB-1 and realize MRI-visualized tumor microenvironment-responsive photothermal-chemodynamic therapy. The Fe3+ in PDAP-Fe is reduced by the GSH at tumor site and is released in the form of highly active Fe2+, which catalyzes the generation of ROS through Fenton reaction and inhibits tumor growth. At the same time, the significant absorption of the mineralized magnetosomes in AMB-1 cells in the NIR region enable them to efficiently convert near-infrared light into heat energy for photothermal therapy (PTT), to which PDAP also contributes. The heat generated in the PTT process accelerates the process of Fe2+ release, thereby achieving an enhanced Fenton reaction in tumor microenvironment. In addition, the magnetosomes in AMB-1 are used as MRI contrast agent, and the curing process is visualized. This tumor microenvironment-responsive MTB-based multi-drug delivery platform displays a potency to combat tumor and demonstrates the utility and practicality of understanding the cooperative molecular mechanism when designing multi-drug combination therapies.

Nasal tumors are one of the most common tumors in aged golden retrievers. Adenocarcinomas or carcinomas are diagnosed in the majority of nasal tumors. Radiation therapy is the first option to decrease the size of tumor, and oral or intravenous chemotherapy is administered depending on the prognosis. Therefore, it is important to select the most appropriate drug for chemotherapy considering the price and the presence of concurrent disease. Anticancer drugs include first-generation chemotherapies, second-generation targeted anticancer drugs, and third-generation immunotherapy drugs. Considering their price and effectiveness, first- or second-generation anticancer drugs are mainly used.We report a first case in which a retriever with a nasal tumor was successfully treated and managed using a metronomic combination of chlorambucil (4mg/day, SID) and prednisolone (10mg/day) orally for 9 months at a general practice. A 35 kg spayed female golden retriever aged 8 years and 8 months visited the Bundang New York Animal Hospital in July 2023. A protocol of 4 weeks of chemotherapy followed by 1 week of rest was repeated, and the nasal exudate was significantly reduced. The size of the nasal tumor was monitored using Computed Tomography (CT) imaging at a referral hospital, and the images were taken in the following order: 1. before radiation therapy at the referral hospital and before chemotherapy; 2. after radiation therapy and before chemotherapy; and 3. after radiation therapy and after chemotherapy. Since the first occurrence of epistaxis, 12 months have passed (as of July 24). The nasal exudate is barely visible, and the retriever’s vital signs and weight remain stable. The size of the nasal tumor significantly decreased after 9 months of chemotherapy without moderate side effects. This study demonstrates that a prednisolone/chlorambucil metronomic combination can be an alternative to kinase inhibitor drugs as it is the cheapest and most effective way to manage tumors along with conventional radiation therapy.

Three patients with multi-year histories of relapsing and remitting Lyme disease and associated co-infections despite extended antibiotic therapy were each given double dose dapsone combination therapy (DDD CT) for a total of 7-8 weeks. At the completion of therapy, all three patients major Lyme symptoms remained in remission for a period of 25-30 months. In conclusion, Double dose dapsone therapy could represent a novel and effective anti-infective strategy in chronic Lyme disease/PTLDS, especially in those individuals who have failed regular dose dapsone combination therapy (DDS CT) or standard antibiotic protocols. A randomized, blinded, placebo-controlled trial is warranted to evaluate the efficacy of DDD CT in those individuals with chronic Lyme disease/PTLDS.

The contemporary treatment for metastatic castration-sensitive prostate cancer (mCSPC) has evolved significantly, building on successes in managing metastatic castration-resistant prostate cancer (mCRPC). Although androgen deprivation therapy (ADT) alone has long been the cornerstone of mCSPC treatment, combination therapies have emerged as the new standard of care based on recent advances, offering improved survival outcomes. Landmark phase 3 trials demonstrated that adding chemotherapy (docetaxel) and androgen receptor pathway inhibitors to ADT significantly enhances overall survival, particularly for patients with high-volume, high-risk, or de novo metastatic disease. Despite these advancements, a concerning gap between evidence-based guidelines and real-world practice remains, with many patients not receiving recommended combination therapies. The challenge in optimizing therapy sequences, considering both disease control and treatment burdens, and identifying clinical and biological subgroups that could benefit from personalized treatment strategies remains. The advent of triplet therapy has shown promise in extending survival, but the uro-oncology community must narrow the gap between evidence and practice to deliver the most effective care. Current research is focused on refining treatment approaches and utilizing biomarkers to guide therapy selection, aiming to offer more personalized and adaptive strategies for mCSPC management. Thus, aligning clinical practices with the evolving evidence is urgently needed to improve outcomes for patients facing this incurable disease.

Diarrhea remains one of the leading causes of mortality worldwide, especially among children. Recent epidemiological studies conducted in developing countries identified Shigella species as the most predominant pathogenic bacteria responsible for diarrhea. Antimicrobial therapy is necessary for Shigella infections; however, the rapid emergence of resistance against existing antimicrobials in Shigella spp. poses a serious global health problem. To identify alternative antimicrobial compounds with activity against Shigella species, the pathogens responsible for bacterial diarrhea. In this study, we have applied antibacterial phenotypic screening to identify potent anti-Shigella compounds across a broad chemical diversity, including selected acetaminophen derivatives containing benzothiazoles backbone, and their combination with certain antibiotics. In continuation to our effort in searching potent antimicrobial compounds, we have found this time around that two acetaminophen derivatives containing benzothiazoles backbone (4a and 4b) could inhibit the growth of Shigella flexneri with common MIC value of 12.5 µg/ml. These compounds were established through a time-kill kinetics’ study to be bactericidal. Meanwhile, the 2-aminobenzothiazoles (1a and 1b) used for the synthesis of compounds 4 (a & b) were found to be poorly active (MIC: 100 µg/ml) against this pathogen. Combination studies of 4a and 4b with the least susceptible antibiotics (ceftriaxone and cotrimoxazole) demonstrated synergistic anti-Shigella activity. The present study demonstrates that the azobenzothiazole dyes 4 (a & b) can be repurposed as potential anti-Shigella compounds, which can serve as scaffolds for the development of new agents against infectious diarrhea caused by Shigella and other enteric pathogens, especially in developing countries.

Due to slow progression and susceptibility to radical forms of treatment low-grade PC is associ-ated with high overall survival (OS). With the clinical progression of PC the therapy is getting more complex. The immunosuppressive tumor microenvironment (TME) makes PC a difficult target for most immunotherapeutics. Its general immune resistance is established by i.e. immune evasion through Treg cells, synthesis of immunosuppressive mediators, and defective expression of surface neoantigens. The success of sipuleucel-T in clinical trials initiated several other clinical studies that specifically target the immune escape of the tumor and eliminate the immunosuppres-sive properties of TME. In the settings of PC treatment, this can be commonly achieved with radi-ation therapy (RT). Also, focal therapies usually applied for localized PC, such as high-intensity focused ultrasound (HIFU) therapy, cryotherapy, photodynamic therapy (PDT), or irreversible electroporation (IRE) were shown to boost anti-cancer response. Nevertheless, the present guide-lines restrict their application to localized and low-grade PC. This review explains how RT and focal therapies enhance the immune response. We also provide data supporting the combination of RT and focal treatments with immune therapies.

HIV-associated cognitive dysfunction during combination antiretroviral therapy (cART) involves mitochondrial dysfunction, but the impact of contemporary cART on chronic metabolic changes in the brain and in latent HIV infection is unclear. We interrogated mitochondrial function in a human microglia (hμglia) cell line harboring inducible HIV provirus, and in SH-SY5Y cells, after exposure to individual antiretroviral drugs or cART, using the MitoStress assay. cART-induced changes in protein expression, reactive oxygen species (ROS) production, mitochondrial DNA copy number, and cellular iron were also explored. Finally, we evaluated the ability of ROS scavengers or plasmid-mediated overexpression of the antioxidant iron-binding protein, Fth1, to reverse mitochondrial defects. Contemporary antiretroviral drugs, particularly bictegravir, depressed multiple facets of mitochondrial function by 20-30%, with most pronounced effects in latently infected-HIV+ hμglia and SH-SY5Y cells. Latently HIV-infected hμglia exhibited upregulated glycolysis. Increases in total and/or mitochondrial ROS, mitochondrial DNA copy number, and cellular iron accompanied mitochondrial defects in hμglia and SH-SY5Y cells. In SH-SY5Y cells, cART reduced mitochondrial iron-sulfur-cluster-containing supercomplex and subunit expression and increased Nox2 expression. Fth1 overexpression or pre-treatment with N-acetylcysteine prevented cART-induced mitochondrial dysfunction. Contemporary cART impairs mitochondrial bioenergetics in hμglia and SH-SY5Y cells, partly through cellular iron accumulation; some effects differ by HIV latency.

The targeting-Her-2/neu therapy by passive application with trastuzumab is associated with acquired resistance and subsequent metastasis development, attributed to upregulation of tumoral PD-L1 expression and downregulation of Her-2/neu. We aimed to investigate this association, following active immunization with our recently constructed B cell–peptide based Her-2/neu vaccines in both preclinical and clinical settings. Immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), and combined positive score (CPS), were applied to evaluate Her-2/neu and PD-L1 expression using a murine syngeneic tumor model for Her-2/neu lung metastases, and tumor biopsies from a gastric cancer patient with disease progression. A significant and concomitant reduction of Her-2/neu and upregulation of PD-L1 expression was observed in the vaccinated mice, after 7 but not after 4 weeks of metastases development. A significant increase of tumor-infiltrating B lymphocytes was observed at both time points. Downregulation of Her-2/neu and upregulation of PD-L1 were observed in a patient’s primary tumor at the disease progression time point but not prior to vaccination (Her-2/neu IHC: 3 to 0, FISH: 4.98 to 1.63; PD-L1 CPS: 0% to 5%). Our results further underline the need for combination therapy by targeting PD-L1 to prevent metastasis formation and immune evasion of Her-2/neu positive and PD-L1 negative tumor cells.

In the face of persistent soil degradation in Benin due to poor agricultural practices, including excessive use of chemical fertilizers, there is an urgent need to seek solutions that integrate microorganisms of interest. The aim of the study was to assess the effect of combining three strains of indigenous arbuscular mycorrhizal fungi on maize production in northern Benin. The study involved 34 growers in Ouénou, Bagou, and Kokey. The experimental set-up consisted of three elementary plots with three treatments. Growth parameters were measured every 15 days, from the 15th to the 60th day after sowing, on ten plants per plot. Plant nutritional status, grain yield and mycorrhization were measured. Results showed that biostimulant + 50% NPK_Urea had similar positive effects on growth parameters to those induced by the application of 100% NPK_Urea. Gains of 30.25 to 36.35% were recorded in plant height at Kokey. On the other hand, biostimulant+ 50% NPK_Urea induced a better phosphorus uptake of 21.08 to 27.77%. In addition, the grain yield of mycorrhizal plants was 8.37% higher than that of plants receiving 100% NPK_Urea at Ouénou. These results show that this technology could be integrated into the agricultural system to promote sustainable maize growing in Benin.

High-precision dynamic positioning of highway vehicles is the foundation and prerequisite for achieving intelligent connected transportation. For the shortcomings of GNSS/INS combination and GNSS/INS/OD combination in tunnel vehicle positioning, this paper proposes a tunnel vehi-cle positioning method of GNSS/INS/OD combination based on lateral distance measurement and lane constraint. Firstly, lateral distance measurement of vehicles inside the tunnel is conducted based on laser radar point cloud data. Secondly, map matching positioning is performed based on lateral distance measurement, odometer, and lane markings. Experimental results demonstrate that for a 4.6 km tunnel, the average absolute error of lateral positioning is 0.294 meters, and the longitudinal positioning error is no more than 0.6 meters, which can effectively meet practical operational requirements.

Background/Objectives: Intervertebral disc degeneration is the most common cause of low back pain (LBP) and lumbosciatica is a major challenge to healthcare systems worldwide. ''For years, ozone therapy has been used with excellent results in intervertebral disc disease and in patients with LBP, thanks to its anti-inflammatory and pain-relieving action.'' At the other side, the repair effect fulfilled by porcine collagen, is a novelty to approach this pathology. In vitro studies have demonstrated the positive action of porcine collagen in extracellular matrix remodeling and homeostasis These tissue changes, associated with LBP, may suggest an indication for combined ozone/collagen treatment in patients with LBP. However, no studies have been reported regarding this combination of treatments. Methods: The present work compared two treatment groups (each of 10 LBP patients): A) Oxygen-Ozone Therapy (OOT) vs. B) OOT plus porcine collagen type 1 injections (COL I). Pain intensity and physiological function were assessed by the numerical rating scale (NSR) method. The Roland-Morrison questionnaire was used to assess disability. Patient data were acquired before, during and at six months of follow-up. Significant differences were assessed by ANOVA and T-Student test. Results: The analyses revealed significant statistical differences comparing the two arms, where, the OOT COL I treatment demonstrated a booster efficacy in pain, while the questionnaire revealed a reduction in disability. Conclusions:. The combination of these two therapies could be effective for the management of LBP. However no studies have been reported in literature regarding this therapeutic combination.

Present study on land use land cover analysis and taluka wise combination of cropped area, carried out in Beed district of Maharashtra state in India and studied 11 talukas of the district. Secondary data on land use land cover and area in various crops has been collected, compiled and analyzed from various secondary sources. Simple descriptive statistics used to examine the agricultural land use land cover and J.C. Weaver’s crop combination technique was used for taluka wise analysis of crop combinations and on the basis of highest to smallest area engaged in particular crop, crops have been ranked. The study showed that, in the district as a whole, percentage of uncultivated land other than fallow was about 46 percent as compare to net sown area is only 35 percent in total geographical area (1063855ha) of Beed district. The study further revealed that about 42 percent area engaged in food crops and about 58 percent area occupied by nonfood crops, which includes cereals (25%), cotton (19%), pulses (13%), oilseed (12%), sugarcane (5%) and fruits and vegetables (3%). Results of Weaver’s crop combination technique showed that the Wadwani taluka demarcated as most diversified taluka by means of maximum number (sixteen) of crops combinations with the lowest variance value (14) found in the present investigation. Further, the study revealed that the high crop diversity found in Dharur taluka with eighteen crop combinations and the taluka has given first rank amongst others. To derive the crop diversity ranking, taluka wise maximum to minimum number of crop combinations derived in different talukas and given ranks accordingly. The study concluded that, agricultural land use analysis is essential for solving and optimizing the land use problem, maintaining socio-ecological balance, best utilization of scarce resources. The authors enlightened that the rational use of agricultural land has important for food security and biodiversity which increase the productivity and profitability of the agriculture sector and it indicates the decision making ability of farmers in study area.

The flavonoid silymarin (SMN) has been widely used in preclinical and clinical studies to treat various types of cancer, either alone or in combination with chemotherapy agents. Herein, we investigated the therapeutic efficacy of SMN and its combination with capecitabine (CAP) and irinotecan (IRI) in a mouse model of colon cancer. A modified diet supplemented with SMN (2500 ppm) with mono- and combined therapy of CAP and IRI were used following 1, 2 dimethylhydrazine (DMH)-induced colon cancer. The lipid profile, liver function tests, and cytokine levels were measured. Additionally, the lipid peroxidation and inflammation indices as well as the antioxidant activities were examined. Eventually, western blotting analysis for colonic BAX and Bcl-2 levels and histopathological examination of colon sections were carried out. SMN alone and in combination with the chemotherapeutic agents could attenuate the DMH-induced hyperlipidemia and elevated liver function enzyme levels. SMN supplementation with chemotherapy agents could also improve antioxidant activity and reverse the elevated levels of lipid peroxidation and inflammatory markers. Furthermore, significant upregulation of BAX and downregulation of Bcl-2 were observed. Besides, carcinogen-induced polyp multiplicity, dysplastic, and inflammatory changes were ameliorated considerably by treatment regimens. Our results showed that the potential anticancer properties of SMN could enhance the therapeutic effects of chemotherapy agents and reduce hepatotoxicity.

Dermatophytes are the most common cause of fungal infections worldwide, affecting millions of people annually. The emergence of resistance among dermatophytes along with the availability of antifungal susceptibility procedures suitable for testing antifungal agents against this group of fungi make the combinatorial approach particularly interesting to be investigated. Therefore, we reviewed the scientific literature concerning the antifungal combinations in dermatophytes. A literature search on the subject performed in PubMed yielded 68 publications: 37 articles referring to in vitro studies, and 31 articles referring to case reports/clinical studies. In vitro studies involved over 400 clinical isolates of dermatophytes (69% Trichophyton spp., 29% Microsporum spp., and 2% Epidermophyton floccosum). Combinations included two antifungal agents or an antifungal agent plus another chemical compound including plant extracts/essential oils, calcineurin inhibitors, peptides, disinfectant agents and others. In general, drug combinations yielded variable results spanning from synergism to indifference. Antagonism was rarely seen. In over 700 patients with documented dermatophyte infections an antifungal combination approach could be evaluated. The most frequent combination included a systemic antifungal agent administered orally (i.e.: azole [mainly itraconazole], terbinafine or griseofulvin) plus a topical medication (i.e.: azole, terbinafine, ciclopirox, amorolfine) for several weeks. Clinical results indicate that association of antifungal agents is effective, and it might be useful in accelerate the clinical and microbiological healing of a superficial infection. Antifungal combinations in dermatophytes have gained considerable scientific interest over the years and, in consideration of the interesting results available as far, it is desirable to continue the research in this field.

This study measured the infrared spectra of secondary minerals in the oxidation zones of three types of copper ores: dioptase, malachite, and azurite, and detailedly assigned the peak positions of OH stretching vibrations and the origins of OH combination vibrations. Dioptase contains three types of water molecules with different orientations within its ring channels, which exhibit six kinds of OH stretching vibrations in the 3000-3600 cm-1 range, the bond length range is 2.652-2.887 Å. Among them, the 3443 cm-1 band shows strong near-infrared activity and combines with Si-O vibrations or OH bending vibrations in the structure, resulting in five combination vibration peaks in the 4000-5000 cm-1 range. Malachite contains two inequivalent hydroxyls in its structure, leading to two OH stretching vibrations in the high-frequency region, located at 3314 and 3402 cm-1, respectively. Azurite contains only one type of hydroxyl, thus only one characteristic OH stretching vibration is present, at 3424 cm-1. The OH stretching vibrations of malachite and azurite mainly combine with [CO3]2- vibrations or OH bending vibrations, leading to six and five combination peaks in the OH combination vibration region, respectively. By analyzing the combination of peak positions at 4341 cm-1 in the near-infrared spectrum, the merged OH bending vibration at 921 cm-1 in azurite was discovered. Spectroscopic research on secondary minerals can better provide a basis for ore exploration and geological remote sensing.

The oncologic disease is a big global health issue that causes thousands of deaths annually, and it has a significant impact in the life quality of patients. Prostate cancer (PCa) is the second most diagnosed cancer and the fourth leading cause of cancer-related death in men in the western world. Delineation of pathogenetic pathways and key driver molecular alterations involved in PCa development has provided a roadmap for the evaluation of biomarkers in predicting disease outcome and to identify potential therapeutic targets. Chemotherapeutic agents introduced from the 1990s include the taxanes (paclitaxel, docetaxel and cabazitaxel), which are the most anticancer drugs used for PCa treatment. This review presents the current knowledge about the onset and development of PCa, state-of-art on the use of taxane-based therapy, and their combination with targeting different transmembrane oncoproteins in PCa. The silencing of some transmembrane proteins can improve taxane sensitivity, and therefore, may be a mechanism to improve the ef-fectiveness of these drugs in PCa treatment. This combined therapy needs to be explored as po-tential therapeutic agent for reducing cell proliferation, migration, and invasiveness in PCa.

The aim of this study is to evaluate the optimal conditions of membrane filtration process. Both laboratory test and pilot-scale test were conducted to examine a treated water on blending water. The water sample were prepared by blending a raw water and the effluent water filtered through an organic membrane. The optimal efficiency in the treatment of water quality at the lab-scale test was generated under conditions of flux at 2.0 m³/m²∙day, the blending ratio of 4:1, and the optimal dosage of coagulant at 20 ppm. The pilot-scale test resulted in that the optimal efficiency was obtained under conditions of flux at 2.0 m³/m²∙day and the blending ratio of 6.0:1. However, the different results between lab-scale and pilot-scale tests on the optimal dosage of coagulant implied that it is difficult to achieve the stable condition of process operation at the low level of coagulant. In summary, the results indicated that, in the combination process of organic membrane and ceramic membrane, the recovery efficiency was achieved above the level of 98.4 %. Compared to 92.1 % in a single organic membrane process, the combination process is 6.3 % more efficient than the single one. This combination process of water treatment lead to stable recovery rates by the optimal input of dosage, less pollution load to water, and a stabilized filtration system.

The theoretical limit of link prediction is a fundamental problem in this field. Taking the network structure as object to research this problem is the mainstream method. This paper proposes a new viewpoint that link prediction methods can be divided into single or combination methods, based on the way they derive the similarity matrix, and investigates whether there a theoretical limit exists for combination methods. We propose and prove necessary and sufficient conditions for the combination method to reach the theoretical limit. The limit theorem reveals the essence of combination method that is to estimate probability density functions of existing links and nonexistent links. Based on limit theorem, a new combination method, theoretical limit fusion (TLF) method, is proposed. Simulations and experiments on real networks demonstrated that TLF method can achieve higher prediction accuracy.

Neuroblastoma (NB) is a childhood cancer with heterogeneous characteristics, posing challenges to effective treatment. NBs express somatostatin receptors that facilitates the use of somatostatin analogs (SSTAs) as tumor-seeking agents for diagnosis and therapy. High-risk (HR) NBs often have gain-of-function mutations in the receptor tyrosine kinase anaplastic lymphoma kinase (ALK). Despite intensive multimodal treatment, survival rates remain below 40% for children with HR-NB. The aim of this work was to investigate the combined effect of the SSTA 177Lu-octreotide with the ALK inhibitor lorlatinib. Mice bearing human HR-NB CLB-BAR tumors were treated with lorlatinib, 177Lu-octreotide, combination of these pharmaceuticals or saline (control). Tumor volume was monitored and tumor samples were evaluated for cleaved caspase-3 and expression of 84 human genes involved in apoptosis. Combination treatment with 177Lu-octreotide and lorlatinib demonstrated synergistic antitumor effects. Increased number of cleaved caspase 3-positive cells was observed in tumors from mice treated with 177Lu-octreotide alone and in combination with lorlatinib. Modulation of Bcl-2 family gene expression was observed only in the presence of both 177Lu-octreotide and lorlatinib, with BID downregulated and HRK upregulated on days 2 and 7, respectively. The data suggests that ALK signaling pathway inhibition may contribute to radiosensitization in radionuclide therapy with 177Lu-octreotide.

Pancreatic cancer is an intractable disease with the worst prognosis of all cancers. The currently used treatment regimens do not significantly impact patient survival, and therefore, effective treatment strategies are urgently needed. Drug repurposing, which identifies new indications for existing and approved drugs, has proven to be a promising approach to anti-cancer drug discovery. Indeed the antihelmintic drug, pyrvinium pamoate has shown promise as an anti-pancreatic cancer drug, but to date, the inhibition of mitochondrial function is the only mechanism of action described in pancreatic cancer. This study showed, using pancreatic cancer 2D cell cultures and 3D spheroids, that pyrvinium pamoate exhibited short- and long-term cytotoxicity, inhibited epithelial-to-mesenchymal transition and cell invasion and migration. Mechanistically, pyrvinium pamoate induced DNA damage, inhibited the PI3K/AKT cell survival pathway, and triggered cell cycle arrests, as well as apoptotic and autophagic cell death. Importantly, pyrvinium pamoate acted synergistically with the first-line drug, gemcitabine in 2D and 3D pancreatic cancer cell culture models. This study provided evidence that pyrvinium pamoate is effective as a single agent and in combination with gemcitabine for the treatment of pancreatic cancer.

Alveolar Rhabdomyosarcoma (ARMS), an invasive subtype of Rhabdomyosarcoma (RMS), is associated with chromosomal translocation events resulting in one of two oncogenic fusion genes PAX3-FOXO1 or PAX7-FOXO1. ARMS patients exhibit an overexpression of the pleiotropic cytokine Transforming growth factor beta (TGF-β). This overexpression of TGF-β1 causes an increased expression of a downstream transcription factor called SNAIL, which promotes Epithelial to Mesenchymal Transition (EMT). Overexpression of TGF-β also inhibits myogenic differentiation, making ARMS patients highly resistant to chemotherapy. In this review, we first describe different types of RMS and then focus on ARMS and the impact of TGF-β in this tumor type. We next highlight current chemotherapy strategies including a combination of FDA approved drugs vincristine, actinomycin D, and cyclophosphamide (VAC), Cabozantinib, Bortezomib, Vinorelbine, AZD 1775 and cisplatin. Lastly, we discuss chemotherapy agents that target the differentiation of tumor cells in ARMS which include all trans retinoic acid (ATRA) and 5-Azacytidine. Improving our understanding of the role of signaling pathways, such as TGF-β1, in the development of ARMS tumor cells differentiation will help inform more tailored drug administration in the future.

Lung cancer remains a formidable global health challenge that necessitates inventive strategies to improve therapeutic outcomes. Conventional treatments, including surgery, chemotherapy, and radiation, have demonstrated limitations in achieving sustained responses. Therefore, the explora-tion of novel approaches encompasses a range of interventions that show promise in enhancing outcomes for patients with lung cancer, particularly those facing advanced or refractory cases. These groundbreaking interventions hold the potential to overcome cancer resistance and offer personalized solutions. Despite the rapid evolution of emerging lung cancer therapies, persistent challenges such as resistance, toxicity, and patient selection underscore the need for continued development. Consequently, the landscape of lung cancer therapy is transforming with the in-troduction of precision medicine, immunotherapy, and innovative therapeutic modalities. Addi-tionally, a multifaceted approach involving combination therapies through the integration of tar-geted agents, immunotherapies, or traditional cytotoxic treatments addresses the heterogeneity of lung cancer while minimizing adverse effects. This review provides a brief overview of the latest emerging therapies that are reshaping the landscape of lung cancer treatment. As these novel treatments progress through clinical trials and integrate into standard care, the potential for more effective, targeted, and personalized lung cancer therapies comes into focus, instilling renewed hope for patients facing challenging diagnoses.

Rivaroxaban and aspirin are commonly used antithrombotic agents that are used in combination for the prevention of coronary artery disease (CAD) and atherothrombotic events in adult patients after an acute coronary syndrome (ACS) with elevated cardiac biomarkers, or with coronary artery disease (CAD) or symptomatic peripheral artery disease (PAD) in high-risk patients. The recommended dosage is 2.5 mg Rivaroxaban twice daily with 75–100 mg aspirin daily. This study aimed to develop a fixed-dose combination tablet of rivaroxaban (2.5 mg) and aspirin (50 mg) to decrease the patient's pill burden and enhance medication adherence. The product formula was developed based on compatibility studies among the active ingredients and the active ingredients' compatibility studies. The formula and the manufacturing procedure were chosen based on the risk assessment for each active substance, wet granulation with both actives intragranular was found to have faster dissolution than direct mix formulae. Furthermore, a validated reverse-phase HPLC stability indicator method was developed to detect APIs and their possible degradants in the formula.

Rapid in vitro assessment of antimicrobial drug efficacy under clinically relevant pharmacokinetic conditions is an essential element of both drug development and clinical use. Here we present an overview of a novel integrated methodology for rapid assessment of such efficacy, particularly against emergence of resistant bacterial strains, as jointly researched by the authors in recent years. This methodology enables rapid in vitro assessment of antimicrobial efficacy of a single or multiple drugs in combination, following clinically relevant pharmacokinetics. The proposed methodology entails (a) automated collection of longitudinal time-kill data in an optical-density instrument; (b) processing of collected time-kill data with the aid of a mathematical model to de-termine optimal dosing regimens under clinically relevant pharmacokinetics for a single or mul-tiple drugs; and (c) in vitro validation of promising dosing regimens in a hollow fiber system. Proof-of-concept of this methodology through a number of in vitro studies is discussed. Future directions for refinement of optimal data collection and processing are discussed.

Combination treatment, i.e., the use of two or more drugs for the same condition, is frequent in medicine if monotherapy yields an insufficient therapeutic response. We here review and challenge clinical study designs and formats of reporting outcomes for the evaluation of the benefit/risk ratio of combination treatment over monotherapy. We demonstrate that benefits of combination treatment at the group level over-estimate the probability of benefit at the single patient level based on outcome simulations under almost any imaginable setting. Based on these findings we propose that studies testing combination treatment should always report on percentages of responders to monotherapy and combination treatment. We provide equations that allow calculation of the percentage of patients truly benefitting from combination (responders to both monotherapies) and that of patients exposed to risk of harm from adverse effects without a reasonable expectation of individual benefit. These considerations are explained based on real clinical data, mostly from the field of functional urology (male lower urinary tract symptoms).

The impact of financial risks extends beyond the normal operation and survival of industrial and commercial enterprises and financial institutions. They also have the potential to impede the stable development of a country's and even the world's financial economy. This is clearly demonstrated by the severe consequences of the frequent financial crises that have occurred in recent years. It thus follows that the prevention of financial risks has become one of the core tasks of the operation and management of industrial and commercial enterprises and financial institutions. Portfolio optimization techniques are employed in the construction of a variety of asset allocation models, with reinforcement learning algorithms used to dynamically adjust investment strategies with the objective of maximizing returns and minimizing risks. The preliminary construction of an asset allocation model is achieved through the utilization of a genetic algorithm. Genetic algorithms emulate the processes of natural selection and genetic variation to identify the optimal portfolio of assets that will yield the greatest returns at a pre-established level of risk. Subsequently, the Deep Q-Learning algorithm is introduced to facilitate dynamic adjustments and optimization of the asset allocation, based on the initial construction. Deep Q-learning employs deep neural networks to forecast the prospective returns of disparate investment strategies, thereby optimizing the decision-making process through continuous learning and updating. The combination of genetic algorithms and deep Q-learning enables the system to identify the optimal investment strategy under a diverse range of initial conditions and to adapt it in real-time to respond to market fluctuations and uncertainties. The experimental analysis demonstrates that the proposed method exhibits an exemplary capacity for risk control and a robust ability to generate stable income growth across diverse market environments. In simulation experiments, portfolios constructed using this method demonstrate lower volatility and higher average returns than those generated through traditional methods.

In recent years, bacterial resistance to conventional antibiotics has become a major concern in the medical field. The global misuse of antibiotics in clinics, personal use, and agriculture has accelerated this resistance, making infections increasingly difficult to treat and rendering new antibiotics ineffective more quickly. Finding new antibiotics is challenging due to the complexity of bacterial mechanisms, high costs and low financial incentives for the development of new molecular scaffolds, and stringent regulatory requirements. Additionally, innovation has slowed, with many new antibiotics being modifications of existing drugs rather than entirely new classes. Antimicrobial peptides (AMPs) are a valid alternative to small molecule antibiotics offering several advantages, including broad-spectrum activity and a lower likelihood of inducing resistance due to their multifaceted mechanisms of action. However, AMPs face challenges such as stability issues in physiological conditions, potential toxicity to human cells, high production costs, and difficulties in large-scale manufacturing. A reliable strategy to overcome the drawbacks associate with the use of small molecule antibiotics and AMPs is the combination therapy, namely the simultaneous co-administration of two or more antibiotics or the synthesis of covalently linked conjugates. This review is intended to cover and critically analyze the design, synthetic strategies, antibacterial activity and, when possible, the cytotoxicity of antibiotic-AMPs conjugates.

Non-polio enteroviruses (NPEVs), namely coxsackieviruses (CV), echoviruses (E), enteroviruses (EV), and rhinoviruses (RV), are responsible for a wide variety of illnesses. Some infections can progress to life-threatening complications in children or immunocompromised patients. To date, no treatments have been approved. Several molecules have been evaluated through clinical trials without success. To overcome these failures, the multi-target directed ligand (MTDL) strategy can be applied to tackle enterovirus infections. This work analyzes clinical trials to highlight the best candidates and develops filters to apply to a selection for MTDL synthesis. We explicitly stated the methods used to answer the question: Which solution can fight NPEVs effectively? We note the originality and relevance of this proposal in relation to the state of the art in the enterovirus-inhibitors field. Several combinations are possible to broaden the antiviral spectrum and potency. We discuss data related to the virus and data related to each LEAD compound identified. Overall, this study proposes a perspective on different strategies to overcome issues identified in clinical trials and evaluate the “MTDL” potential to improve the efficiency of drugs synergistically, broaden the targeted, and reduce the adverse effects and drug design cost as well as limit the opportunity of drug-resistant viruses.

Diarrhea-related mortality remains an important public health concern, particularly in developing countries, and has become difficult to treat because of antibacterial resistance. The development of synergistic antimicrobial agents appears to be a promising alternative treatment against diar-rheal infections. In this study, the combined effect of tetracycline together with either nitroxoline, sanguinarine, or zinc pyrithione (representing various classes of alkaloid-related compounds) was evaluated in vitro against selected diarrheagenic bacteria (Enterococcus faecalis, Escherichia coli, Listeria monocytogenes, Shigella flexneri, Vibrio parahaemolyticus, and Yersinia enterocolitica). The chequerboard method in 96-well microtiter plates was used to determine the sum of the fractional inhibitory concentration indices (FICIs). Three independent experiments were performed per combination, each in triplicate. It was observed that the combinations of tetracycline with either nitroxoline, sanguinarine, or zinc pyrithione produced synergistic effects against most of the pathogenic bacteria tested, with FICI values ranging from 0.086 to 0.5. Tetracycline-nitroxoline combinations produced the greatest synergistic action against S. flexneri at a FICI value of 0.086. Combinations of the agents tested in this study can thus be used for the development of new anti-diarrheal medications. However, studies focusing on their in vivo anti-diarrheal activity and safety are required before any consideration for utilization in human medicine.

Modern power system integrates more and more new energy and use a large number of power electronic equipment. This makes it face more challenges in online optimization and real-time control. Deep reinforcement learning(DRL) has the ability of processing big data and high-dimensional features, as well as the ability of independently learning and optimizing decision-making in complex environments. In this paper, we explore DRL based online combination optimization method of grid section for large complex power system. In our method, to improve the convergence speed of the model, we propose to discretize the output action of the unit and simplify the action space. We also design a reinforcement learning loss function with strong constraints to further improve the convergence speed of the model and facilitate the algorithm to obtain the stable solution. Moreover, to avoid the local optimal solution problem caused by the discretization of the output action, we propose to use the annealing optimization algorithm to make the granularity of the unit output finer. We verify our method on IEEE 118-bus system. The experimental results show that our model has fast convergence speed and better performance, and can obtain stable solutions.

Cross flow heat exchangers are commonly used in the thermal industry to transfer heat from hot tubes to cooling fluid. To protect the heat exchanger tubes from corrosion and dust accumulation, microscale coatings are often applied. In this study, we present machine-learning models for predicting heat transfer from hot tubes with different micro-sized coatings to cooling fluid in a turbulent flow using computational fluid dynamics simulations. A dataset of approximately 1000 cases was generated by varying the coating coverage thickness of each tube, the inlet Reynolds number, fluid flow inlet temperature, and wall temperature of tubes. The machine-learning models were generated to predict the overall heat flow rate in the heat exchanger, and it was found that combining the features based on their importance preserved the accuracy of the models while maintaining all the relevant information. The simulation results demonstrate that the proposed method increases the coefficient of determination (R2) for the models. The R2 values for unseen data for Random Forest, K-Nearest Neighbors, and Support Vector Regression were 0.9810, 0.9037, and 0.9754, respectively, indicating the usefulness of the proposed model for predicting heat transfer in various types of heat exchangers.

Chemotherapy is a standard therapeutic option for triple-negative breast cancer (TNBC); however, its effectiveness is often compromised by drug-related toxicity and resistance development. Herein, we aimed to evaluate whether an improved antineoplastic effect could be achieved in vitro and in vivo in TNBC by combining dovitinib, a multi-kinase inhibitor, with calcitriol, a natural anti-cancer hormone. In vitro, cell proliferation and cell-cycle distribution were studied by sulforhodamine B-assays and flow cytometry. In vivo, dovitinib/calcitriol effects on tumor growth, angiogenesis and endothelium activation were evaluated in xenografted mice by caliper measures, Itgb3-immunohistochemistry and 99mTc-RGD2-tumor uptake. The drug combination elicited a synergistically improved antiproliferative effect in TNBC-derived cells, which allowed a 7-fold dovitinib dose-reduction. Mechanistically, the co-treatment induced cell death and accumulation in S and G2/M phases, while inhibited tumor growth to a greater extent than each compound alone. Tumor uptake of 99mTc-RGD2 was reduced by dovitinib, suggesting angiogenesis inhibition, which was corroborated by decreased endothelial cell growth and tumor vessel density. In summary, calcitriol synergized dovitinib anticancer effects in vitro and in vivo, allowing for a significant dose-reduction of dovitinib, while maintaining its antiproliferative potency. Our results suggest the beneficial convergence of independent antitumor mechanisms of dovitinib and calcitriol to inhibit TNBC-tumor growth.

Due to an increase in the number of image achieves, Content-Based Image Retrieval (CBIR) has gained attention for research community of computer vision. The image visual contents are represented in a feature space in the form of numerical values that is considered as a feature vector of image. Images belonging to different classes may contain the common visuals and shapes that can result in the closeness of computed feature space of two different images belonging to separate classes. Due to this reason, feature extraction and image representation is selected with appropriate features as it directly affects the performance of image retrieval system. The commonly used visual features are image spatial layout, color, texture and shape. Image feature space is combined to achieve the discriminating ability that is not possible to achieve when the features are used separately. Due to this reason, in this paper, we aim to explore the low-level feature combination that are based on color and shape features. We selected color moments and color histogram to represent color while shape is represented by using invariant moments. We selected this combination, as these features are reported intuitive, compact and robust for image representation. We evaluated the performance of our proposed research by using the Corel, Coil and Ground Truth (GT) image datasets. We evaluated the proposed low-level feature fusion by calculating the precision, recall and time required for feature extraction. The precision, recall and feature extraction values obtained from the proposed low-level feature fusion outperforms the existing research of CBIR.

A series of novel sulfonylurea benzothiazoline were designed by splicing active groups and bioisosterism. A solvent-free synthetic route was developed for the sulfonylurea benzothiazoline derivatives via the cyclization and carbamylation. All the compounds were characterized by IR, 1H-NMR, 13C-NMR, HRMS. The biological activity tests indicated the compounds could protect maize against the injury caused by chlorsulfuron to some extent. The molecular docking result showed that the new compound competed with chlorosulfuron to bind with the herbicide target enzyme active site to attain detoxification.

After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex anti-tumor effects, such as innate and adaptive immune responses and the destruction of tumor vasculature. With the availability of different vector platforms and the potential of both genetic engineering and combination regimens to enhance particular aspects of safety and efficacy, the identification of optimal treatments for patient subpopulations or even individual patients becomes a top priority. Mathematical modeling can provide support in this arena by making use of experimental and clinical data to generate hypotheses about the mechanisms underlying complex biology and, ultimately, predict optimal treatment protocols. Increasingly complex models can be applied to account for therapeutically relevant parameters such as components of the immune system. In this review, we describe current developments in oncolytic virotherapy and mathematical modeling to discuss the benefit of integrating different modeling approaches into biological and clinical experimentation. Conclusively, we propose a mutual combination of these fields of research for more efficient development and effective treatments.

Currently, urban renewal activities in China are booming. And promoting the renovation of public buildings is the key due to its large scale, high cost and significant impact to the nature and social environment. To reduce the ambiguity and uncertainty in evaluating the potential for renewal of existing public buildings, a renewal potential evaluation model combining game theory combination weighting method and cloud model theory is proposed. The paper constructs a comprehensive evaluation index system based on relevant standards and literature. Game theory is used to optimize the weights obtained by AHP and entropy weight methods to obtain a combined weight. MATLAB programming is used to calculate the comprehensive cloud parameters of the evaluation index for the potential renewal of existing public buildings and therefore generate cloud Graphs. Through case study in Nanjing of China, it has been demonstrated that the combination empowerment cloud model can objectively reflect the relationship between the fuzziness and randomness of evaluation indicators for public building renewal potential. The expression of cloud Graphs can intuitively reflect the magnitude of renewal and renovation potential and the degree of uncertainty in evaluation results. The research result provides useful references for the sustainable utilization of building resources in the era of building.

The antimicrobial resistance to clinically approved antibiotics is rapidly increasing worldwide. Staphylococcus aureus is a critical contributor to deaths associated with antibiotic resistance. In this regard, the search for natural compounds is quite active, that alone or in combination with other agents can be effective as new antibacterial agents. The antibacterial activity of essential oils has presented an increasing interest during the last years and was effective even on multidrug-resistant strains. The present study aims to investigate the interaction effects of oregano essential oil (OEO) with some conventional antibiotics against Staphylococcus aureus tested by agar methods. For this purpose, we selected S. aureus ATCC 29213 and five clinical isolates representative of the species. The essential oil was analyzed using gas chromatography coupled with mass spectrometry (GC-MS). The analysis of the Oregano essential oil revealed the main component to be carvacrol (81,20%). Concentration 2.5% (v/v) OEO was combined with drugs proposed by EUCAST, 2024, specifically penicillin, cefoxitin, erythromycin, gentamycin and tetracycline. The research results showed that the combination of OEO with penicillin, cefoxitin, erythromycin, and tetracycline enhanced the antimicrobial activity of the antibiotics against S. aureus in almost all cases. The area of suppression remained identical (but not smaller) in the unaffected cases. When comparing the effects of the GEN-OEO combination and GEN against most S. aureus strains, a decrease in antimicrobial activity was reported by the diffusion agar method.

Current antibiograms cannot discern the particular effect of a specific antibiotic when the bacteria are incubated with a mixture of antibiotics. To prove that this task is achievable, Escherichia coli strains were treated with ciprofloxacin for 45 min, immobilized on a slide and stained with SYBR Gold. In susceptible strains, the nucleoid relative surface started to decrease near the MIC, being progressively condensed as dose increased. The shrinkage level correlated with the DNA fragmentation degree. Ciprofloxacin-resistant bacilli showed no change. Additionally, E. coli strains were incubated with ampicillin for 45 min and processed similarly. The ampicillin-susceptible strain revealed intercellular DNA fragments that increased with dose, unlike the resistant strain. Co-incubation with both antibiotics revealed that ampicillin did not modify the nucleoid condensation effect of ciprofloxacin, whereas the quinolone partially decreased the background of DNA fragments induced by ampicillin. Sixty clinical isolates, with different combinations of susceptibility-resistance to each antibiotic, were co-incubated with the EUCAST breakpoints of susceptibility of ciprofloxacin and ampicillin. The morphological assay correctly categorized all the strains for each antibiotic in 60 min, demonstrating the feasible independent evaluation of a mixture of quinolone and beta-lactam. The rapid phenotypic assay may shorten the incubation times and necessary microbial mass currently required for evaluation.

This paper aims to investigate the coal thickness change area of the combined rock strata energy accumulation law. The method of connecting a uniaxial compression experiment with a theoret-ical analysis is used in this work. We employ a combination of coal and rock to carry out our studies. We investigate how different lithologies and ratios of coal-rock height affect the me-chanical properties of the mixture and the law governing energy accumulation. We have deter-mined the following facts: (1) The combination's peak strength and elastic modulus exceed that of coal and are inferior to that of rock but are nearer to that of coal. (2) When the coal-rock height ratios are dissimilar, the peak strength and modulus of elasticity of the combination show a negative correlation with the coal-thickness share, and the pre-peak energy accumulation and impact energy index of the combination shows a positive correlation with the coal-thickness share. (3) For the combination with the same coal-rock height ratio, the peak strength, elastic modulus, pre-peak energy accumulation, and impact energy index all increase with greater rock strength and elastic modulus. The presence of a hard rock layer affects the accumulation of pre-peak energy. ( 4 ) The stress in the surrounding rock gradually decreases as the coal thick-ness increases. In the area where coal thickness declines, the stress in surrounding rock is higher than that in the region where it thickens. The energy stored in the surrounding rock is directly proportional to the coal in the zone. Conversely, areas with thinner coal deposits exhibit a lower energy storage capacity in the surrounding rock than those with thicker coal deposits. The stress distribution of surrounding rock in coal thickness change is abnormal; substantial energy accu-mulation can swiftly initiate dynamic disasters, such as rock bursts. This study has important reference significance for preventing and controlling rock burst in coal thickness change areas.

The use of spherical radial basis functions (SRBFs) in regional gravity field modeling has become popular in recent years. However, to our knowledge, their potential for combining gravity data from multiple sources, particularly data with different spectrum information in the frequency domain, has not been extensively explored. Therefore, band-limited SRBFs, which have good lo-calization characteristics in the frequency domain, are the main tool in this study. We propose a residual and a-prior accuracy comparative analysis method to determine the optimal degree of expansion of SRBFs for gravity data. Using this methodology, we constructed a high-resolution geoid model called ColSRBF2023 in Colorado. The degrees of expansion for terrestrial and airborne data were set to 5200 and 1840, respectively. Results indicate that ColSRBF2023 has a standard deviation (STD) value of 2.3 cm compared to the GSVS17 validate data. This value is 2-6 mm lower than models obtained using different degrees of expansion for gravity data and models from other institutions considered in this study. Additionally, at the 1'×1' grid in the entire target area, ColSRBF2023 has an STD value of 2.4 cm when compared to the validation model. This value is also the best among the options examined in this study. These findings highlight the importance of determining the optimal expansion degree of gravity data, particularly when constructing high-resolution gravity field models in rugged mountainous regions.

The combination of non-steroidal anti-inflammatory drugs (NSAIDs) with non-opioid analgesics is common in clinical practice for the treatment of acute pain conditions like post-operative and post-traumatic pain. Besides that, and despite the very satisfactory results achieved by oral analgesics, parenteral analgesia is a key tool in the treatment of painful conditions when the enteral routes are not convenient. The parenteral ready-to-use fixed-dose combinations of NSAIDs with non-opioid analgesics like paracetamol or metamizole could play a central role in the treatment of painful conditions since they are able to gather into only one formulation the advantages of multimodal and parenteral analgesia. Surprisingly, only very recently a parenteral ready-to-use fixed-dose combination of Ibuprofen/Paracetamol was launched to the market. This review aims to review the current availability of NSAID-based Parenteral Fixed-dose combinations with paracetamol and metamizole in the European and American markets, and how the combination of such drugs could play a central role in a multimodal analgesia strategy. Also, it is explored how the parenteral formulations of NSAIDs, paracetamol, and metamizole could serve as starting elements for the development of new parenteral ready-to-use fixed-dose combinations. With this review, we concluded that, despite the well-recognized utility of combining NSAIDs with non-opioid analgesics, there are in the literature several randomized clinical trial studies unable to demonstrate clear advantages concerning their efficacy and safety. In the future, it is deemed necessary to perform clinical trials specifically designed to assess the efficacy and safety of these fixed-dose formulations to generate solid evidence of their clinical advantages.

Viral diseases represent a major public health concern and an ever-present risk for developing into a future pandemic. Antiviral antibody therapeutics, either alone or in combination with other therapies, have emerged as valuable preventative and treatment options, including during a global emergency. Here we will discuss polyclonal and monoclonal antiviral antibody therapies, focusing on the unique biochemical and physiological properties that make them well suited as therapeutic agents. We will describe the methods of antibody characterization and potency assessment throughout development, highlighting similarities and differences between polyclonal and monoclonal products as appropriate. In addition, we will consider the benefits and challenges of antiviral antibodies when used in combination with other antibodies or other types of antiviral therapeutics. Lastly, we will discuss novel approaches to the characterization and development of antiviral antibodies and identify areas that would benefit from additional research.

Background: Enterovirus infections affect people around the world, causing a range of illnesses, from mild fevers to severe, potentially fatal conditions. There are no approved vaccines or treatments for enterovirus infections. Methods: We have tested our library of broad-spectrum antiviral agents (BSAs) against echovirus 1 (EV1) in human adenocarcinoma alveolar basal epithelial A549 cells. We also tested combinations of the most active compounds against EV1 in A549 and human immortalized retinal pigment epithelium RPE cells. Results: We confirmed anti-enteroviral activities of pleconaril, rupintrivir, cycloheximide, vemurafenib, remdesivir, emetine, and anisomycin and identified novel synergistic rupintrivir-vemurafenib, vemurafenib-pleconaril and rupintrivir-pleconaril combinations against EV1 infection. Conclusions: Because rupintrivir, vemurafenib, and pleconaril require lower concentrations to inhibit enterovirus replication in vitro when combined, their combinations may have fewer side effects in vivo and therefore should be further studied in pre- and clinical trials.

In many image processing and computer vision applications, the main aim is to describe image contents. So, different visual properties such as color, texture and shape are extracted to make aim. In this respect, texture information play important role in image description and visual pattern classification. Texture is referred to a specific local distribution of intensities that is repeated throughout the image. Since now different operations or descriptors have been proposed to analysis texture characteristics. In the multi object images specific texture operators usually doesn’t provide accurate results. So, in many cases, combination of texture operators are used to achieve more discriminant features. In this paper, some combination methods are survived to analysis effect of combinational texture features in image content description. Also, in the result part, different related methods are compared in terms of accuracy and computational complexity.

Background: Three drug-combinations, ipilimumab-nivolumab (Ipi-Nivo), pembrolizumab-axitinib (Pembro-Axi) and avelumab-axitinib (Ave-Axi), have received regulatory approvals in USA and Europe for the treatment of metastatic renal cell carcinoma with clear cell component (mRCC). However, no head-to-head comparison data are available to identify the best option. Therefore, we aimed to compare these new treatments in the first-line setting. Methods: We conducted a systematic search in Pubmed, the Cochrane library and clinicaltri-al.gov website from January 2015 to October 2019, for any randomized controlled trials of treatment-naïve patients with mRCC. The process was performed according to PRISMA guide-lines. We performed a Bayesian network meta-analysis with two different approaches. The out-comes for analysis were overall survival, progression-free survival, and objective response rate. Results: Our search identified 3 published phase 3 randomized clinical trials (2835 patients). In the contrast-based model, Ave-Axi (SUCRA: 83%) and Pembro-Axi (SUCRA: 80%) exhibited the best ranking probabilities for PFS. For OS, Pembro-Axi (SUCRA: 96%) was the most pref-erable option against Ave-Axi and Ipi-Nivo. Objective response rate analysis showed Ave-Axi as the best (SUCRA= 94%) and Pembro-Axi as second best option. In the parametric models, risk of progression was comparable for Ave-Axi and Ipi-Nivo, whereas Pembro-Axi exhibited a lower risk during the first 6 months of treatment and a higher risk afterward. Furthermore, Pembro-Axi exhibited a net advantage in terms of OS over the two other regimens, while Ave-Axi was the least preferable option. Conclusions: Overall evidences suggested pembrolizumab plus axitinib may be the best option.

To determine the mode of action of the effects of phytoalexins in soybeans, we analyzed enzyme inhibition kinetics using Michaelis–Menten plots and the Lineweaver–Burk plots. The results showed that glyceollin showed competitive inhibition, genistein showed noncompetitive, daidzein was uncompetitive, and luteolin showed a mixed mode of action. The Ki values were determined using a Dixon plot as: glyceollin, 18.99; genistein, 15.42; luteolin, 16.81; and daidzein, 9.99 μM, respectively. Furthermore, potential synergistic effects between glyceollin and the three designated polyphenols were investigated. A combination of glyceollin and luteolin (the ratio of 3:7 of glyceollin and luteolin) had synergistic effects on α-glucosidase inhibition according to combination index (CI)-isobologram equation. Collectively, these results showed that a combination of glyceollin and luteolin has the potential to inhibit α-glucosidase activity via a synergistic mode of action.

Purpose: To compare the therapeutic efficacy and safety of dorzolamide/timolol fixed-combination in newly diagnosed primary open angle glaucoma patients. Methods: In this prospective, interventional case series, newly diagnosed primary open angle glaucoma (POAG) patients that had not been treated for glaucoma were included. Patients were started on Cosopt twice a day (BID) for 1 month and then switched to three times a day (TDS) for additional 1 month. Patients underwent comprehensive ophthalmic examination, diurnal intraocular pressure (IOP), blood pressure (BP) and 24-hours heart rate (HR) measurements at baseline, month 1( BID), and month 2( TDS). IOP, systolic and diastolic pressures were measured at 8:00 AM,12:00 AM, 4:00 PM, 8:00 PM and 12:00 PM. Throughout the study, all adverse events were recorded and monitored by the investigators. Results: In 31 POAG patients that completed the study ,mean baseline IOP was 23.1±3.15 mmHg . IOP was decreased significantly 16.5 ± 2.21 at 1 month (P < 0.0001) and 13.9 ± 2.23 mmHg at 1 and 2 month follow up. (P < 0.0001) IOP was significantly lower in month 2 compared to month 1 (P = 0.0004). While Cosopt BID significantly reduced the mean 24-hour systolic BP and mean 24-hour HR from baseline (P < 0.0001), the mean 24-hour systolic BP and HR remained unchanged 2ith Cosopt TDS compared to BID (P = 0.62). Conclusions: Cosopt TDS has a superior IOP-lowering effect than Cosopt BID in POAG patients with comparable safety profile.

Although new industrialized construction technologies have the potential to improve industry performance by optimizing work processes and improving the working environment, the application of these technologies in the construction industry is still in its infancy, and its technical direction is not yet set. This study aims to put forward a theoretical framework for evaluating the level of new-type building industrialization of construction engineering projects, conduct integrated research on the existing domestic and foreign literatures on new-type building industrialization and intelligent construction, preliminarily construct the index system, and determine the evaluation index system of new-type building industrialization projects through the Delphi method. The index weight is determined by the combination of order relation analysis and entropy weight method. The evaluation model is constructed by matter-element theory and cloud model, and the evaluation grade standard is proposed. The research results will help guide the evaluation of new building industrialization projects, and provide a judgment reference for determining the development trend and direction of new building industrialization technologies in the future, and help formulate data-driven industrial policies to promote the adoption of new industrialization technologies and promote the digital transformation of the construction industry.

Abstract: Conventional antibiotic and multidrug treatments become less and less effective and a discovery of new effective and safe antibacterial agents got a global priority. The returning to the natural antibacterial product is relatively new current trend. Terrestrial biota is a rich source of biologically active substances whose antibacterial potential was not fully utilized. Aim of this review is to present the current state-of-the art of terrestrial biota-derived antibacterial agents and inspired by nature treatments. It is a summary of the most important sources and new identified or modified antibacterial agents and treatments during the last 5 years. It focuses on the significance of plants- animals- and bacteria-derived biologically active agents as powerful alternatives to antibiotics as well as on the advantages of utilizing natural antibacterial molecules alone or in combinations with antibiotics. The main conclusion is that the terrestrial biota derived antibacterial products and substances open variety of new ways to modern improved therapeutic strategies. New terrestrial sources of known antibacterial agents and new antibacterial agents from terrestrial biota were discovered during the last 5 years, which are under investigation together with some long ago known but now surviving their renaissance for the development of new medical treatments. Use of natural antibacterial peptides as well as combinational therapy by commercial antibiotics and natural products outlines as the most promising for treating of bacterial infections. In vivo testing and clinical trials are necessary to reach clinical application.

This study examines the latest innovation in wooden pile foundation models using a combination of wood and concrete materials for house construction on swampy land. The focus of the research is on developing joints and materials that enhance the load-bearing capacity and stability of building structures on swampy terrain. The methods used include field observations, laboratory experiments, and descriptive analysis. The results show that the combination of wood and concrete in foundation piles can increase structural strength, reduce deformation, and extend the service life of buildings. The new joint techniques developed in this research are effective in improving structural integrity and minimizing the negative impacts of soft soil conditions. The conclusion emphasizes the importance of material innovation and joint techniques in construction on swampy land, providing practical guidance for construction practitioners and researchers in this field.

: Introduction: Discovering compounds with antibacterial activity is crucial in the current fight against antibiotic-resistance. Material and Methods: We generate two QSAR model to design six new heteroaryl drug candidates; we assessed the antibacterial properties of the compounds against nine ATCC strains, the majority being part of the ESKAPE group, that include Enterococcus faecalis, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and also Salmonella enterica and Escherichia coli. We performed a synergic assay in which we combined PB4, a compound that we have previously tested in published studies, with GC-VI-70, one of the new compounds with the best cytotoxicity/MIC profile. We tested sub-MIC concentrations of PB4 with five antibiotics (linezolid, gentamycin, ampicillin, erythromycin, rifampin and imipenem) to examine the synergic effect on the ATCC strains. To evaluate compounds’ cytotoxicity, we performed a 24-hour and 48-hour 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay on Colorectal Adenocarcinoma (CaCo-2) cells. The antibiotics were tested, alone and in combination with PB4. Results: PB4 lowered the MIC measured for GC-VI-70 and for the various antibiotics employed in clinical use, and all the compounds presented in this study have cytotoxic activity against cells. Conclusions: These compounds show promising use in combination with antibiotics to improve their effectiveness at low concentrations, to prevent unwanted cytotoxic effects.

Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. Despite extensive research efforts, the majority of trialed monotherapies to date have failed to demonstrate significant benefit. It has been suggested that this is due to the complex pathophysiology of TBI, which may possibly be addressed by a combination of therapeutic interventions. In this article, we have reviewed combinations of different pharmacologic treatments, combinations of non-pharmacologic interventions, and combined pharmacologic and non-pharmacologic interventions for TBI. Both preclinical and clinical studies have been included. While promising results have been found in animal models, clinical trials of combination therapies have not yet shown clear benefit. This may possibly be due to their application without consideration of the evolving pathophysiology of TBI. Improvements of this paradigm may come from novel interventions guided by multimodal neuromonitoring and multimodal imaging techniques, as well as the application of multi-targeted non-pharmacologic and endogenous therapies. There also needs to be a greater representation of female subjects in preclinical and clinical studies.

Objective: The combination of docetaxel (DTX) with Laser-Activated NanoTherapy (LANT), as a treatment for head and neck cancer (HNC) may enhance the therapeutic efficacy of lower doses of DTX, thereby minimizing the effective dosage, side effects and treatment times. Material and methods: Three HNSCC cell lines, Detroit 562, FaDu, and CAL 27, were treated with four combinations of DTX + LANT to evaluate DTX dose reduction and cell viability. Results: The 1 nM DTX + 5 nM LANT combination was the most effective treatment, increasing cell death over its corresponding DTX monotreatment with approximately 86.6%, 80.7%, and 92.1% cell death for Detroit 562, FaDu, and CAL 27, respectively. In Detroit 562, the 1 nM DTX + 5 nM LANT combination treatment resulted in the highest percentage of DTX dose reduction at 84.6%; in FaDu and CAL 27, the 0.5 nM DTX + 5 nM LANT combination treatment resulted in the highest percentage of DTX dose reduction at 78.2% and 82.4%, respectively. Conclusion: LANT may increase the therapeutic efficacy of DTX at significantly lower doses, which could improve patient outcomes.

The study of the area model of Pinus tabulaeformis forest provides an important reference for improving the management of Pinus tabulaeformis and revealing the growth law of Pinus tabulaeformis. According to the classification method proposed by Munro, stand growth and harvest prediction models are divided into three categories: full stand model, single wood model and diameter distribution model. Based on the fixed sample data of Shangluo Pinus tabulaeformis, the spatial instead of time method is used to process the data, and the weight coefficient of each model in the combined prediction model is calculated by using the optimal weighting method. The single wood model, the whole forest model and the diameter distribution model are combined by the combined prediction method to integrate the fault area prediction of Pinus tabulaeformis forest. The results show that the combined prediction method is more accurate than the single model (single wood model, whole forest model and diameter distribution model). At the same time, the method can improve the compatibility of the forest break area prediction model, ensure the consistency of the forest break area prediction, and provide a new direction for the research of forest resource monitoring and investigation.

As an important part of urban terminal delivery, automated guided vehicle (AGV) has been widely used in the field of takeout delivery. Due to the real-time generation of takeout orders, the delivery system is required to be extremely dynamic, so the AGV needs to be dynamically scheduled. At the same time, the uncertainty in the delivery process (such as the meal preparation time) further increases the complexity and difficulty of AGV scheduling. Considering the influence of these two factors, the method of embedding stochastic programming model into rolling mechanism is adopted to optimize the AGV delivery routing. Specifically, To handle real-time orders under dynamic demand, an optimization mechanism based on rolling scheduling framework is proposed, which allows the AGV route to be continuously updated. Different from most VRP models, open chain structure is used to describe the dynamic delivery path of AGV. In order to deal with the impact of uncertain meal preparation time on route planning, a stochastic programming model is formulated with the purpose of minimizing the expectation of order timeout rate and the total customer waiting time. In addition, an effective path merging strategy and after-effects strategy are also considered in the model. In order to solve the proposed mathematical programming model, a multi-objective optimization algorithm based on NSGA-III framework is developed. Finally, a series of experimental results demonstrate the effectiveness and superiority of the proposed model and algorithm.

Abstract: This study aimed at investigating the effects of Valencia KK4-type peanut skin ethanolic extract (KK4-PSE) in combination with cisplatin or 5-fluorouracil (5-FU) against HeLa cells in vitro and in xenograft models. MTT assay showed that KK4-PSE, cisplatin, and 5-FU suppressed proliferation of HeLa cells in a dose and time dependent manner. Drug interactions by Chou-Talalay method demonstrated that KK4-PSE enhanced antiproliferative activity of 5-FU against HeLa cells with combination index (CI) values of 0.49 (48 h) and 0.60 (72 h), indicating a synergistic effect, while KK4-PSE combined with cisplatin exhibited an additive effect (CI = 1.02) (72 h) and antagonistic effect at 24 and 48 h exposures (CI = 1.12 and 1.18, respectively). In nude mouse xenograft models, the combination of 5-FU and KK4-PSE markedly reduced HeLa tumor weights compared with control and single agent treatments. The combination of KK4-PSE and 5-FU achieved greater tumor growth inhibition than that of the KK4-PSE-cisplatin combination. KK4-PSE mitigated hepatotoxicity induced by both cisplatin and 5-FU in nude mice. The spleen hyaloserositis was significantly reduced in the combination treatment of 5-FU and KK4-PSE. These findings suggest a potential of KK4-PSE to inhibit cervical cancer cell growth while alleviating the toxicities of cisplatin and 5-FU.

In the context of the Korean building structure standard KDS2022, wind loads can be readily calculated in terms of the along-wind, across-wind, and torsional components, based on a single wind direction. However, this approach falls short in accurately and safely evaluating the impact of winds from various directions. Therefore, in this study, we developed a Wind Load Calculation Program (WCP) capable of predicting wind loads with relative precision during the preliminary design phase. First, wind tunnel tests were conducted to identify the essential factors necessary for calculating wind loads and the variables influencing these factors. The building shape considered was a square, and the wind force coefficients and power spectral density were measured by combining 4 ground roughness values, 11 side ratios (), 4 aspect ratios (), and wind directions ranging from 0° to 90°. Subsequently, a generalized formulation was devised to facilitate wind load calculations across diverse conditions and a method for calculating load combination coefficients, considering response correlation and load simultaneity, was presented. Finally, the wind loads obtained from the wind tunnel tests were compared with those predicted by the WCP using an actual project model.

Combination antiviral therapy may be helpful in the treatment of SARS-CoV-2 infection, however no clinical trial data are available and combined use of direct acting antivirals (DAA) and monoclonal antibodies (mAb) has been reported only anecdotally. To assess the cooperative effects of dual drug combinations in vitro, we used a VERO E6 cell based in vitro system with the ancestral B.1 or the highly divergent BQ.1.1 virus to test pairwise combinations of the licensed DAA, including nirmatrelvir (NRM), remdesivir (RDV) and the active metabolite of molnupiravir (EIDD-1931) as well the combination of RDV with four licensed mAbs (sotrovimab, bebtelovimab, cilgavimab, tixagevimab; tested only with the susceptible B.1 virus). According to SynergyFinder 3.0 summary and weighted scores, all the combinations had an additive effect. Within DAA/DAA combinations, paired scores with the B.1 and BQ.1.1 variants were comparable. In the post-hoc analysis weighting synergy by concentrations, several cases of highly synergistic scores were detected at specific drug concentrations, both for DAA/DAA and for RDV/mAb combinations. This was supported by in vitro confirmation experiments showing a more than linear shift of a drug effective concentration (IC50) at increasing concentrations of the companion drug, although the effect was prominent with DAA/DAA combinations but minimal or null with RDV/mAb combinations. These results support a cooperative effects of dual drug combinations in vitro, which should be further investigated in animal models before introduction into the clinic.

The rapid development of digital multimedia has resulted in a massive storm of large-scale data. The data compression method reduces data size and lowers transmission costs. As a result, data-hiding research in the compression domain poses significant challenges to researchers. This paper proposes a highly imperceptible data-hiding scheme for a compressed image of Absolute Moment Block Truncation Coding (AMBTC). The combination theory is implemented to ensure the high imperceptibility of the modified compressed images. By only modifying one pixel in a block to embed secret bits, the experimental results show that the proposed method achieved high imperceptibility and high hiding capacity.

In this study, we investigate the performance of the saddlepoint approximation of the probability mass function and the cumulative distribution function for the weighted sum of independent Poisson random variables. The goal is to approximate the hazard rate function for this complicated model. The better performance of this method is shown by numerical simulations and comparison with a performance of other approximation methods.

Aero-fuel centrifugal pumps are important power plants in aero-engines. Unlike most of the existing centrifugal pumps, a combination impeller is integrated with the pump to improve its performance. First, the critical geometrical parameters of combination impeller and volute are given. Then, the effects of combination impeller on flow characteristics inside the impeller and volute are clarified by comparing simulation results with that of the conventional impeller, where the effectiveness of selected numerical method is validated by an acceptable agreement between simulation and experiment. Finally, the experiment is performed to test the external performance of studied pump. A significant feature of this study is that the flow characteristics are significantly ameliorated by reducing the flow losses emerged in impeller inlet, impeller outlet and volute tongue. Correspondingly, the head and efficiency of combination impeller are higher with comparison to conventional impeller. Consequently, it is a promising approach in ameliorating flow field and improving external performance by applying a combination impeller to an aero-fuel centrifugal pump.

For a single exposure in radiography, a dual-layer flat-panel detector (DFD) can provide spectral images based on copper filtering or beam hardening, and efficiently utilize the transmitted x-ray photons to improve the detective quantum efficiency (DQE) performance. In this paper, we present a registration method for x-ray images acquired from DFD considering only spatial translations and scale factors. Note that the spatial translation difference between the upper and lower detector layers arises when attaching the layers, and the scale difference arises from the x-ray projection relative to the source and detector distances. The conventional registration methods have inconsistent estimate accuracies depending on the captured object scene even when using entire pixels, and have deteriorated frequency performance due to the interpolation method employed. The proposed method consists of two steps; the first step is conducting a spatial translation according to the Fourier shift theorem with a subpixel registration, and the second step is conducting a scale transformation using cubic interpolation to process the x-ray projections. To estimate the subpixel spatial translation, a maximum-amplitude method using a small portion of the slant-edge phantom is used. The performance of the proposed two-step method is first theoretically analyzed, and then observed by conducting extensive experiments and measuring the noise power spectrum and DQE. An example for registering chest images is also shown. For DFD, it is shown that the proposed method shows a better registration result than the conventional one-step registration.

Colorectal cancer (CRC) remains a major global health issue. Although chemotherapy is the first-line treatment, its effectiveness is limited due to drug resistance developed in CRC. To overcome resistance and improve the prognosis of CRC patients, investigation for new therapeutic approaches is necessary. Using human colorectal adenocarcinoma (HT29) and metastatic CRC (SW620) cell lines, the potential anticancer properties of a newly synthesized compound 1-(Isobutyl)-3-(4-methylbenzyl) benzimidazolium chloride (IMBZC) were evaluated by performing MTT cytotoxicity, cell migration, and colony formation assays, as well as by monitoring apoptosis-related protein and gene expression using Western blot and reverse transcription-quantitative polymerase chain reaction technologies. Tested at various concentrations, the half-maximal inhibitory concentrations (IC50) of IMBZC on HT29 and SW620 cell growth were determined to be 6.97 μg/mL and 4.89 μg/mL, respectively. IMBZC did not alter cell growth of normal cells HEK293. In addition, IMBZC inhibited cell migration and significantly decreased colony formation, suggesting its promising role in suppressing cancer metastasis. Mechanistic analyzes revealed that IMBZC treatment increased the expression of pro-apoptotic proteins p53 and Bax, while decreasing the expression of anti-apoptotic proteins Bcl-2 and Bcl-xL, thus indicating the induction of apoptosis in IMBZC-treated CRC cells, compared to untreated cells. Additionally, the addition of IMBZC to conventional chemotherapeutic drugs (i.e., 5-fluorouracil, irinotecan, and oxaliplatin) resulted in an increase in the cytotoxic potential of the drugs. In conclusion, the study suggests that IMBZC has substantial anticancer effects against CRC cells through its ability to induce apoptosis, inhibit cancer cell migration and colony formation, and enhance the cytotoxic effects of conventional chemotherapeutic drugs. These findings indicate that IMBZC could be a promising chemotherapeutic drug for the treatment of CRC. Further research should be conducted using in vivo models to confirm the anti-CRC activities of IMBZC.

As an important support for power system with high penetration of renewable energy, energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption, and its installed capacity under the source-grid-load scenario is rising year by year, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under the source-grid-load scenarios, and proposes a comprehensive benefit evaluation method of energy storage projects based on fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super efficiency data envelopment analysis (DEA) model, which considers the perspective of economic and social environment. Firstly, the functional requirements of energy storage on the source-grid-load scenarios are explored respectively, and the characteristics of various functions are analyzed to form functional combination schemes. Secondly, index modeling is carried out from three aspects: the whole life cycle cost, functional combination benefit and social environmental benefit, and the comprehensive benefit evaluation index system of energy storage project is proposed, which includes both economic and social environment. Then, the intuitionistic trapezoidal fuzzy number is combined with DEMATEL to form an effective analysis method for the input-output relationship of the indexes, and the comprehensive evaluation is realized based on the super efficiency DEA model. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios respectively.

Two of the most common activation functions (AF) in deep neural networks (DNN) training are Sigmoid and ReLU. Sigmoid was tend to be more popular the previous decades, but it was suffering with the common vanishing gradient problems. ReLU has resolved these problems by using zero gradient and not tiny values for negative weights and the value “1” for all positives. Although it significant resolves the vanishing of the gradients, it poses new issues with dying neurons of the zero values. Recent approaches for improvements are in a similar direction by just proposing variations of the AF, such as Leaky ReLU (LReLU), while maintaining the solution within the same unresolved gradient problems. In this paper, the combining of the Sigmoid and ReLU in one single function is proposed, as a way to take the advantages of the two. The experimental results demonstrate that by using the ReLU’s gradient solution on positive weights, and Sigmoid’s gradient solution on negatives, has a significant improvement on performance of training Neural Networks on image classification of diseases such as COVID-19, text and tabular data classification tasks on five different datasets.

Background: In the present study, cisplatin, artemisinin and oleanolic acid were evaluated alone and in combination, on human ovarian A2780, A2780ZD0473R and A2780cisR cancer cell lines with aim of overcoming cisplatin resistance and side effects. Methods: Cytotoxicity was assessed by MTT reduction assay. CI values were used as a measure of combined drug effect. MALDI TOF/TOF MS/MS and 2-DE gel electrophoresis were used to identify protein biomarkers in ovarian cancer and to evaluate combination effects. Results: Synergism from combinations was dependent on concentration and sequence of administration. Generally, bolus was most synergistic. 49 proteins differently expressed by 2 ≥ fold were: CYPA, EIF5A1, Op18, p18, LDHB, P4HB, HSP7C, GRP94, ERp57, mortalin, IMMT, CLIC1, NM23, PSA3,1433Z, and HSP90B were down-regulated, whereas hnRNPA1, hnRNPA2/B1, EF2, GOT1, EF1A1, VIME, BIP, ATP5H, APG2, VINC, KPYM, RAN, PSA7, TPI, PGK1, ACTG and VDAC1 were up-regulated, while TCPA, TCPH, TCPB, PRDX6, EF1G, ATPA, ENOA, PRDX1, MCM7, GBLP, PSAT, Hop, EFTU, PGAM1, SERA and CAH2 were not-expressed in A2780cisR cells. The proteins were found to play critical roles in cell cycle regulation, metabolism and biosynthetic processes and drug resistance and detoxification. Conclusion: Results indicate that appropriately sequenced combinations of cisplatin with ART and OA may provide a means to reduce side effects and circumvent platinum resistance.

Input noise causes inescapable bias to the weight vectors of the adaptive filters during the adaptation processes. Moreover, the impulse noise at the output of the unknown systems can prevent bias compensation from converging. This paper presents a robust bias compensation method for a sparse normalized quasi-Newton least-mean (BC-SNQNLM) adaptive filtering algorithm to address this issue. We have mathematically derived the biased-compensation terms in an impulse noisy environment. Inspired by the convex combination of adaptive filters' step sizes, we propose a novel variable-mixing-norm method to accelerate the convergence for our BC-SNQNLM algorithm, which is referred to as BC-SNQNLM-VMN. Simulation results confirm that the proposed method significantly outperforms other comparative works regarding normalized mean-squared deviation (NMSD) in the steady state.

Infections caused by KPC-producing K. pneumoniae continue to pose a significant clinical challenge due to emerging resistance to new antimicrobials. We investigated the association between two drugs whose roles have been repurposed against multidrug-resistant bacteria: fosfomycin and temocillin. Temocillin exhibits unusual stability against KPC enzymes, while fosfomycin acts as a potent “synergizer”. We conducted in vitro antimicrobial activity studies on 100 clinical isolates of KPC-producing K. pneumoniae using a combination of fosfomycin and temocillin. The results demonstrated synergistic activity in 91% of the isolates. Subsequently, we assessed the effect on Galleria mellonella larvae using 5 different KPC-Kp isolates. The addition of fosfomycin to temocillin increased larvae survival from 73 to 97% (+Δ 32%; isolate 1), from 93 to 100% (+Δ 7%; isolate 2), from 63 to 86% (+Δ 36%; isolate 3), from 63 to 90% (+Δ 42%; isolate 4), and from 93 to 97% (+Δ 4%; isolate 10), respectively. Among the temocillin-resistant KPC-producing K. pneumoniae isolates (24 isolates), the addition of fosfomycin reduced temocillin MIC values below the resistance breakpoint in all isolated except one. Temocillin combined with fosfomycin emerges as a promising combination against KPC-producing K. pneumoniae, warranting further clinical evaluation.

The Savu Sea holds significant importance as a conservation area in Indonesia, providing sustenance and livelihoods for local communities. It is situated within the Coral Triangle, a critical hotspot for marine biodiversity worldwide. However, the Savu Sea is currently facing various threats, including overfishing, pollution, and the impacts of climate change. Effective management of this conservation area relies heavily on the active participation of local communities. Therefore, this study aims to address this issue by analyzing how factors within these communities, such as the socio-economic condition of coastal households, environmental awareness, the existence of community-based conservation areas, attitudes towards activities within the conservation area, and participation in multistakeholder institutions, contribute to a positive perception of the benefits provided by the Savu conservation area. To determine the complex causal conditions that influence the outcome of perception, the study employs the Qualitative Comparative Analysis (QCA) method, specifically using crisp set QCA (csQCA). A survey was conducted among 22 coastal villages surrounding the Savu Sea, resulting in the identification of 14 different combinations of pathways that contribute to varying levels of perception regarding conservation. Valuable lessons can be drawn from this study to enhance the design of policies aimed at effectively managing the Savu conservation area.

In a wide range of lymphoid neoplasms, the process of malignant transformation is associated to somatic mutations in B cells that affect the epigenetic machinery. Consequential alterations in histone modifications contribute to disease-specific changes in the transcriptional program. Affected genes commonly play important roles in cell cycle regulation, apoptosis-inducing signal transduction and DNA damage response, thus facilitating the emergence of malignant traits that impair immune surveillance and favor the emergence of different B-cell lymphoma subtypes. In the last two decades, the field has made a major effort to develop therapies that target these epigenetic alterations. In this review, we discuss which epigenetic alterations occur in non-Hodgkin B-cell lymphoma. Furthermore, we aim to present in close to comprehensive manner the current state-of-the-art in the preclinical and clinical development of epigenetic drugs. We focus on therapeutic strategies interfering with histone methylation and acetylation as these are most advanced in being deployed from the bench-to-bedside and have greatest potential to improve the prognosis of lymphoma patients.

Innovation is an essential key factor in the technology development history. Past research on innovation focused more on the innovation behavior of technology, but seldom described knowledge assets which also influence innovation behavior greatly. The effect of knowledge assets attribute and result on disruptive innovation is therefore regarded as the research topic in this study, where disruptive innovation is divided into outbound and inbound to combine combination-embeddednessandmajor business specificityof knowledge assets as the research model. Manufacturing enterprises in China are proceeded the questionnaire survey, and 173 valid copies are collected. The empirical analysis shows that combination-embeddedness of knowledge assets presents significantly positive effects on major business specificity and outbound innovationof an enterprise but reveals remarkably negative effects on inbound innovation. Enterprises are suggested to constantly accumulate knowledge assets with low major business specificity before disruptive innovation in order to reduce ineffective inbound innovation.

The construction of artificial grasslands using native species is an effective measure to restore degraded grassland. In this study, three native grass species, Elymus nutans, Elymus tangutorum and Poa litwinowiana, domesticated in the northern Tibetan Plateau, were used as test subjects. Three monocultures El. N, El. T and Po. L and four mixed combinations El. N+El. T, El. N+Po. L, El. T+Po. L and El. N + El. T + Po. L were set up, with 7 sowing combinations as the main zones, and nested fertilization and non-fertilization as the secondary zones. The optimal sowing combinations were selected to clarify the community growth dynamics of different grass pasture, and to investigate the transgressive overyielding and diversity effects of artificial grassland and the response of soil chemometrics to fertilizer application, with a view to providing a scientific basis for ecological restoration of degraded grassland in the northern Tibetan Plateau. The results show that the different sowing combinations of grassland all exhibit significant growth, with aboveground biomass peaking on 20 September. The type of El. N is the dominant community of the mixed combinations. The forage yield was highest in the combination, and the fertilization treatment significantly increased the forage yield. El. N + El. T + Po. L mixed sowing with fertilizer application is the recommended methodology to establish artificial grassland in the northern Tibetan Plateau. The relative yield totals of the mixed combinations were all greater than 1, and all were transgressive overyielding. Combined with the analysis of the distribution of soil ecological stoichiometric characteristics under fertilizer and non-fertilizer treatments, it was found that aboveground biomass and transgressive overyielding coefficients responded to soil ecological stoichiometry in completely different ways. Under the unfertilized treatment, soil C, N and P are regulated primarily through microbial stoichiometry under the resource dependence of soil dissolved nutrient stoichiometry, which affected aboveground of artificial grassland. Under the fertilizer treatment, microbially mediated extracellular enzyme stoichiometry was dynamically changing to regulate the new substrate environmental supply and demand balance derived from fertilizer application. Future research should further explore the long-term effects of these combinations under different environmental conditions and integrate other ecological restoration techniques to enhance the sustainability and ecological benefits of artificial grasslands. This will help achieve ecological balance and efficient utilization of forage resources in the Tibetan Plateau region, providing a more comprehensive scientific basis for regional environmental protection.

Antimicrobial peptides (AMPs) have emerged as a promising solution to tackle bacterial infections and combat antibiotic resistance. However, their clinical application has been hindered by their vulnerability to protease degradation and toxicity towards mammalian cells. To overcome these challenges, our study aims to develop a method to enhance the stability and safety of AMPs, applicable to effective drug-device combination products. KR12 antimicrobial peptide was chosen and in order to further enhance its delivery and efficacy, HIV TAT protein-derived cell-penetrating peptide (CPP) was fused to form CPP-KR12. A new product, CPP-KR12@Si, was developed by forming silica nanoparticles with self-entrapped CPP-KR12 peptide using the biomimetic silica precipitability due to its cationic nature. Peptide delivery from CPP-KR12@Si to bacteria and cells was delivered at a slightly delayed rate with improved stability against trypsin treatment and a reduction in cytotoxicity over CPP-KR12. Finally, the antimicrobial potential of CPP-KR12@Si/bone graft substitute (BGS) combination product was demonstrated, which is coated with CPP-KR12 in the form of nanoparticles on the surface of BGS. Self-entrapped AMP in silica nanoparticles is a safe and effective AMP delivery method that will be useful for developing a drug/device combination product for tissue regeneration.

To address the problem of limited fault diagnosis accuracy in oil-immersed on-load tap changers (OLTC), this paper introduces a novel fault diagnosis method that combines the analysis of mechanical vibration signals and high-frequency current signals. The proposed approach aims to enhance the accuracy of fault diagnosis. To begin, an experimental platform is constructed to simulate the OLTC contact. Mechanical vibration signals and high-frequency current signals are collected from the testing platform under various operating states. These signals are then subjected to wavelet packet transform for denoising, followed by correlation analysis to capture the relationship between signals in different states. Based on these preliminary steps, the features of the signals are extracted and analyzed using ensemble empirical mode decomposition and the Hilbert-Huang transform. Subsequently, a support vector machine (SVM) is employed to analyze both the mechanical vibration signal and high-frequency current signal, enabling the classification of the OLTC contact state. The results demonstrate that the combination of characteristic analysis of mechanical vibration signals and high-frequency current signals provides a more comprehensive reflection of the actual OLTC contact state under different conditions. Through the SVM classification, the error between the predicted values and real values of the two types of signals remains below 10%, validating the efficiency and feasibility of the proposed method for fault diagnosis of OLTC contacts. These research findings serve as a reliable foundation for the diagnosis of operational states of on-site oil-immersed on-load tap changers, offering valuable insights for practical applications.

The extensive use of carrier-aided smoothing code (CSC) filter has led to reduce the noise level of raw code measurements in GNSS positioning and navigation applications. However, the existing CSC technique is sensitive to the changes of the integer ambiguity and then the smoothing proce-dure needs to be restarted in the presence of cycle-slips. As the Doppler shift is instantaneous ob-servation and immune to cycle-slips, Doppler-aided smoothing code (DSC) algorithm would be more promising in challenged environment. Based on the Hatch-filter, an optimal DSC approach is proposed with the principle of minimum variance. Meanwhile, to inhibit the effect of integral cumulative error of Doppler, a balance factor is adopted to adjust the contributions of raw code and DSC. The noise level of code observable is not only affected by thermal noise, but also limited by systematic bias. Satellite code bias (SCB) has been identified in the raw code observable on each frequency for each BDS-2 satellite. By minimizing the sum of absolute value of residuals, polyno-mial segment fitting algorithm as a function of elevation-angles is applied to establish the SCB cor-rection model based on epoch-differenced Multipath (MP) deviations. Finally, numerical experi-ments demonstrate the validity and efficiency of the refined DSC filter with SCB corrections on each available frequency for BDS-2 un-GEO satellites.

Coinfection of B virus (HBV) and hepatitis Delta virus (HDV) lead to severe forms of progressive liver diseases. However, commercially available antiviral drugs have shown considerable adverse effects and low efficacy in managing these patients. Thus, there is a pressing need to develop new, innovative, and evidence-based therapies for these pathological entities. In line with this, some investigators have attempted to develop anti-viral drugs targeting HBV/HDV coinfection. In another development, investigators have also attempted to establish immune therapy targeting for HBV infection as recovery or effective control of HBV infection also lead to efficient control of HDV infection. This review has discussed an account of the evolving antiviral and immune therapeutic drugs for HBV/HDV infection. Also, based on current scientific knowledge how we have described the pros and cons of these drugs as no suitable drug has been developed during the last forty years for treating HBV infection except the availability of two” repurposed drugs”; interferons and its derivatives and nucleoside analogs, for managing HBV or HBV/HDV coinfection. It seems that an evolving and innovative therapeutic regimen that combines both antiviral drugs and immune modulators may be the best and realistic option for management of HBV/HDV coinfection.

This paper presents a computational approach designed to construct and query a literature-based knowledge graph for predicting novel drug therapeutics. The main objective is to offer a platform that discovers drug combinations from FDA-approved drugs and accelerates their investigations by domain scientists. Specifically, the paper introduced the following algorithms: (1) an algorithm for constructing the knowledge graph from drug, gene, and disease mentions in the biomedical literature; (2) an algorithm for vetting the knowledge graph from drug combinations that may pose a risk of drug interaction; (3) and two querying algorithms for searching the knowledge graph by a single drug or a combination of drugs. The resulting knowledge graph had 844 drugs, 306 gene/protein features, and 19 disease mentions. The original number of drug combinations generated was 2,001. We queried the knowledge graph to eliminate noise generated from chemicals that are not drugs. This step resulted in 614 drug combinations. When vetting the knowledge graph to eliminate the potentially risky drug combinations, it resulted in predicting 200 combinations. Our domain expert manually eliminated extra 54 combinations which left only 146 combination candidates. Our three-layered knowledge graph, empowered by our algorithms, offered a tool that predicted drug combination therapeutics for scientists who can further investigate from the viewpoint of drug targets and side effects.

Human infections caused by the H5 highly pathogenic avian influenza virus (HPAIV) sporadically threaten public health. The susceptibility of HPAIVs to baloxavir acid (BXA), a new class of inhibitors for the influenza virus cap-dependent endonuclease, has been confirmed in vitro, but it has not yet been fully characterized. Here, the efficacy of BXA against HPAIVs, including recent H5N8 variants, was assessed in vitro. The antiviral efficacy of baloxavir marboxil (BXM) in H5N1 virus-infected mice was also investigated. BXA exhibited similar in vitro activities against H5N1, H5N6, and H5N8 variants tested in comparison with seasonal and other zoonotic strains. Compared with oseltamivir phosphate (OSP), BXM monotherapy in mice infected with the H5N1 HPAIV clinical isolate, the A/Hong Kong/483/1997 strain, also caused a significant reduction in viral titers in the lungs, brains, and kidneys, thereby preventing acute lung inflammation and reducing mortality. Furthermore, compared with BXM or OSP monotherapy, combination treatments with BXM and OSP using a 48-hour delayed treatment model showed a more potent effect on viral replication in the organs, accompanied by improved survival. In conclusion, BXM has a potent antiviral efficacy against H5 HPAIV infections.

Immunotherapy has been considered for years as a viable and attractive treatment option for patients with cancer. Among immunotherapy arsenal, the targeting of intratumoral immune cells by immune-checkpoint inhibitory agents has recently revolutionized the treatment of several subtypes of tumours. These approaches aimed at restoring an effective anti-tumour immunity, rapidly reached the market thanks to the simultaneous identification of inhibitory signals that dampen an effective antitumor response in a large variety of neoplastic cells, and the clinical development of monoclonal antibodies targeting checkpoint receptors. Leading therapies in solid tumours are mainly focused on the cytotoxic T-lymphocyte–associated antigen 4 (CTLA-4) and programmed-death 1 (PD-1) pathways. These approaches have found a promising testing ground in both Hodgkin lymphoma and non-Hodgkin lymphoma, mainly because in these diseases the malignant cells interact with the immune system and commonly provide signals that regulate immune function. Although several trials have already demonstrated evidence of therapeutic activity with some checkpoint inhibitors in lymphoma, many of the immunologic lessons learned from solid tumours may not directly translate to lymphoid malignancies. In this sense, the mechanisms of effective antitumor responses are different between the different lymphoma subtypes, while the reasons for this substantial difference remain partially unknown. This review will discuss the current advances of immune-checkpoint blockade therapies in B-cell lymphoma and will build a projection of how the field may evolve in the near future. In particular, we will analyze the current strategies being evaluated both preclinically and clinically with the aim to foster the use of immune-checkpoint inhibitors in non-Hodgkin lymphoma, including combination approaches with chemotherapeutics, biological agents and/or different immunologic therapies.

Despite all scientific efforts and many protracted and expensive clinical trials, no new drug has been approved by FDA for treatment of Alzheimer disease (AD) since 2003. Indeed, more than 200 investigational programs have failed or have been abandoned in the last decade. The most probable explanations for failures of disease-modifying treatments (DMTs) for AD may include late initiation of treatments during the course of AD development, inappropriate drug dosages, erroneous selection of treatment targets, and mainly an inadequate understanding of the complex pathophysiology of AD, which may necessitate combination treatments rather than monotherapy. Clinical trials’ methodological issues have also been criticized. Current drug-development research for AD is aimed to overcome these drawbacks. Preclinical and prodromal AD populations, as well as traditionally investigated populations representing all the clinical stages of AD, are included in recent trials. Systematic use of biomarkers in staging preclinical and prodromal AD and of a single primary outcome in trials of prodromal AD are regularly integrated. The application of amyloid, tau, and neurodegeneration biomarkers, including new biomarkers—such as Tau positron emission tomography, neurofilament light chain (blood and CSF biomarker of axonal degeneration) and neurogranin (CSF biomarker of synaptic functioning)—to clinical trials allows more precise staging of AD. Additionally, use of the Bayesian statistics, modifiable clinical trial designs, and clinical trial simulators enrich the trial methodology. Besides, combination therapy regimens are currently assessed in clinical trials. The abovementioned diagnostic and statistical advances, which have been recently integrated in clinical trials, are consequential to the recent failures of studies of disease-modifying treatments. Their experiential rather than theoretical origins may better equip potentially successful drug-development strategies.

Gastric cancer is the fifth most common and fourth deadliest cancer worldwide, with a bleak 5-year survival rate of about 20%. Despite significant research into its pathobiology, prognostic predictability remains insufficient due to pathologists’ heavy workloads and the potential for diagnostic errors. Consequently, there is a pressing need for automated and precise histopathological diagnostic tools. This study leverages Machine Learning and Deep Learning techniques to classify histopathological images into healthy and cancerous categories. By utilizing both handcrafted and deep features and shallow learning classifiers on the GasHisSDB dataset, we conduct a comparative analysis to identify the most effective combinations of features and classifiers for differentiating normal from abnormal histopathological images without employing fine-tuning strategies. Our methodology achieves an accuracy of 95% with the SVM classifier, underscoring the effectiveness of feature fusion strategies. Additionally, cross-magnification experiments produced promising results with accuracies close to 80% and 90% when testing the models on unseen testing images with different resolutions.

The DNA Damage Response (DDR) network and the mitogen-activated protein kinase (MAPK) signaling pathway are crucial mechanisms for the survival of all living beings. An accumulating body of evidence suggests that there is a crosstalk between these two systems, thus favoring the appropriate functioning of multi-cellular organisms. On the other hand, aberrations within these mechanisms are thought to play a vital role in the onset and progression of several diseases, including cancer, as well as in the emergence of drug resistance. Here, we provide an overview of the current knowledge regarding alterations in the DDR machinery and the MAPK signaling pathway, as well as abnormalities in the DDR-MAPK functional crosstalk in multiple myeloma, the second most common hematologic malignancy. We also present the latest advances in the development of anti-myeloma drugs targeting crucial DDR- and MAPK-associated molecular components. These data could potentially be exploited to discover new therapeutic targets and effective biomarkers, as well as for the design of novel clinical trials. Interestingly, they might provide a new approach to increase the efficacy of anti-myeloma therapy by combining drugs targeting the DDR network and the MAPK signaling pathway.

Globally, we are undergoing compelling changes in virtually every branch of the society and every aspect of our daily lives over the last couple of years due to the COVID-19 pandemic. In the words of Melinda Gates, the famous American Philanthropist, the pandemic has literally “magnified every existing inequality”. There has been much talk and an ongoing debate on the origin of SARS-CoV-2 (or, the novel coronavirus) as to whether have evolved purely naturally or has the contaminating element of human intervention somewhere in its trajectory. Proponents of the pure ‘natural evolution theory’, some of whom are bigshots in the field of virology have seem to take up great effort to stamp their authority right from the very early days of the pandemic on the slow natural evolution of the virus from its ancestrors by several publications in high-profile journals. These well-cited papers however provide rationals that are somewhat contradictory and are backed up with data which maybe argued as far from being complete and/or all-inclusive. As time progressed, alternative theories to that of the pure natural evolution of the virus emerged with strong counter-logics and gradually compiling genomic and epidemiological data along with detailed structural studies of relevant molecular interactions. All said and done, till date, compelling evidences lack on either end of the spectrum making the COVID origin debate still very mucg wide open. Regardless of whether purely natural or human-intervented the damage caused by the virus is unmistakable and has been an alarming concern to medical science lately. To that end, a section of the scientific community is devoting committed efforts using immuno-informatics to design and develop possible multi-epitope combination vaccines to cover a plethora of viral antigens and their plausible future mutations, alongside with the vaccines that are currently available.

Acute low back pain (LBP) stands as a leading cause of activity limitation and work absenteeism, and its associated healthcare expenditures are expected to become substantial when acute LBP develops into a chronic and even refractory condition. Therefore, early intervention is crucial to prevent progression to chronic pain whose management is particularly challenging and for which the most effective pharmacological therapy is still controversial. Current guideline treatment recommendations vary and are mostly driven by expertise with opinion differing across different interventions. Thus, it is difficult to formulate evidence-based guidance when relatively few randomized clinical trials did explore the diagnosis and management of LBP while employing different selection criteria, statistical analyses, and outcome measurements. This narrative review aims to provide a critical appraisal of current acute LBP management by discussing the unmet needs and areas of improvement from bench-to-bedside and proposes multimodal analgesia as the way forward to attain an effective and prolonged pain relief and functional recovery in patients with acute LBP.

Despite numerous studies in statistical downscaling methodology, there remains a lack of methods that can downscale from precipitation modeled in global climate models to regional level high resolution gridded precipitation. This paper reports a novel downscaling method using a Generative Adversarial Network (GAN), CliGAN, which can downscale large-scale annual maximum precipitation given by simulation of multiple atmosphere-ocean global climate models (AOGCM) from Coupled Model Inter-comparison Project 6 (CMIP6) to regional-level gridded annual maximum precipitation data. This framework utilizes a convolution encoder-dense decoder network to create a generative network and a similar network to create a critic network. The model is trained using an adversarial training approach. The critic uses the Wasserstein distance loss function and the generator is trained using a combination of adversarial loss Wasserstein distance, structural loss with the multi-scale structural similarity index (MSSIM), and content loss with the Nash-Sutcliff Model Efficiency (NS). The MSSIM index allowed us to gain insight into the model’s regional characteristics and shows that relying exclusively on point-based error functions, widely used in statistical downscaling, may not be enough to reliably simulate regional precipitation characteristics. Further use of structural loss functions within CNN-based downscaling methods may lead to higher quality downscaled climate model products.

Abiotic stress in plants is an increasingly common problem in agriculture, and thus, studies on plant treatments with specific certain compounds that may help to mitigate these effects have increased in recent years Melatonin (MET) application and its role in mitigating the negative effects of abiotic stress in plants have become important in the last few years. MET, a derivative of tryptophan, is an important plant-related response molecule involved in the growth, development, and reproduction of plants, and the induction of different stress factors. In addition, MET plays a protective role against different abiotic stresses such as salinity, high/low temperature, high light, waterlogging, nutrient deficiency and stress combination by regulating both the enzymatic and non-enzymatic antioxidant defense systems. Also, MET interacts with many signaling molecules, among these, reactive oxygen species (ROS) and nitric oxide (NO), and participates in a wide variety of physiological reactions. It is well known that NO produces S-nitrosylation and NO2-Tyr of important antioxidant-related proteins, being this an important mechanism for maintaining the antioxidant capacity of the AsA/GSH cycle under nitro-oxidative conditions, being extensively reviewed here under different abiotic stress conditions. Lastly, in this review, we show the coordination between NO and MET as a long-range signaling molecule, regulating many responses in plants, including plant growth and abiotic stress tolerance. Despite all the knowledge acquired over the years, there is still more to know about how MET and NO act on tolerance to abiotic stresses.