Search Results (86)

Background/Objectives: The heterogeneity of cancer disease and the frequent ineffectiveness and resistance observed with currently available treatments highlight the importance of developing new antitumor therapies. The properties of gold nanoparticles, such as their photon-energy heating, are attractive for oncology therapy; this can be effective and localized. The combination of chemotherapy and hyperthermia is promising. Our aim was to evaluate the combination therapy of photon hyperthermia with 5-fluorouracil (5-FU) both in vitro and in vivo. Methods: This study evaluated the antitumor efficacy of a combined chemo-photothermal therapy using 5-fluorouracil (5-FU) and branched gold nanoshells (BGNSs) in a colorectal cancer model. BGNSs were synthesized via a seed-mediated method and characterized by electron microscopy and UV–vis spectroscopy, revealing an average diameter of 126.3 nm and a plasmon resonance peak at 800 nm, suitable for near-infrared (NIR) photothermal applications. In vitro assays using SW620-GFP colon cancer cells demonstrated a ≥90% reduction in cell viability after 24 h of combined treatment with 5-FU and BGNS under NIR irradiation. In vivo, xenograft-bearing nude mice received weekly intratumoral administrations of the combined therapy for four weeks. The group treated with 5-FU + BGNS + NIR exhibited a final tumor volume of 0.4 mm³ on day 28, compared to 1010 mm³ in the control group, corresponding to a tumor growth inhibition (TGI) of 100.74% (p < 0.001), which indicates not only complete inhibition of tumor growth but also regression below the initial tumor volume. Thermographic imaging confirmed that localized hyperthermia reached 45 ± 0.5 °C at the tumor site. Results: These findings suggest that the combination of 5-FU and BGNS-mediated hyperthermia may offer a promising strategy for enhancing therapeutic outcomes in patients with colorectal cancer while potentially minimizing systemic toxicity. Conclusions: This study highlights the potential of integrating nanotechnology with conventional chemotherapy for more effective and targeted cancer treatment. Full article

Introduction: The introduction of the transdiagnostic approach in psychiatry shifts the focus from discrete diagnoses to shared symptoms across various disorders. The Transdiagnostic Global Impression—Psychopathology (TGI-P) scale is a newly developed tool designed to assess psychiatric symptoms across diagnostic boundaries. It evaluates ten core symptom domains—positive, negative, cognitive, manic, depressive, addiction, anxiety, sleep, hostility, and self-harm—regardless of specific diagnoses. Objective: This study aims to evaluate the efficacy of cariprazine across these ten transdiagnostic symptom domains. Methods: A systematic literature review and meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Searches were performed on EMBASE and clinicaltrials.gov. Efficacy measures such as the Positive and Negative Syndrome Scale (PANSS), Montgomery–Åsberg Depression Rating Scale (MADRS), Young Mania Rating Scale (YMRS), Hamilton Anxiety Rating Scale (HAM-A), and Columbia-Suicide Severity Rating Scale (C-SSRS) were used to assess cariprazine’s effect on the ten transdiagnostic symptoms. Multilevel random-effects meta-analyses were conducted to evaluate the efficacy of cariprazine versus placebo in alleviating depressive and anxiety symptoms across clinical trials. Results: A total of 30 studies were included in the review. Cariprazine showed therapeutic benefits on positive, negative, manic, and depressive symptoms in specifically designed trials. Preliminary positive effects were seen on anxiety, hostility, and cognitive symptoms across disorders. However, specific trials have not been conducted for anxiety disorders or cognitive impairment. Meta-analyses demonstrated that cariprazine significantly reduces both depressive and anxiety symptoms compared to placebo. Cariprazine significantly improved sleep-related symptoms in both mania and depression trials. Suicidality was evaluated in non-suicidal populations, and no increase was observed. Addiction symptoms were part of the exclusion criteria in the RCTs, so they could not be assessed. Previous reports of cariprazine’s anti-craving and anti-abuse effects come from real-world evidence rather than RCT data. Conclusions: Cariprazine appears to be promising in addressing a broad range of symptom domains across psychiatric conditions. Full article

Background and Objectives: Military capability may be reduced in hot environments with individuals at risk of exertional heat stroke (EHS). Heat tolerance testing (HTT) can be used to indicate readiness to return to duty following EHS. HTT traditionally relies on rectal core temperature (T_re) assessment via a rectal probe. This study investigated the use of gastrointestinal core temperature (T_gi) as an alternative to T_re during HTT. A secondary aim was to compare physiological factors between heat-tolerant and heat-intolerant trials. Materials and Methods: Australian Defence Force personnel undergoing HTT following known or suspected heat stroke volunteered (n = 23 cases participating in 26 trials) along with 14 controls with no known heat illness history. Confusion matrices enabled comparison of HTT outcome based on T_gi and T_re. The validity of T_gi compared to T_re during HTT was assessed using correlation and bias. Comparisons between heat-tolerant and intolerant trials were performed using non-parametric tests. Results: Although T_gi correlated closely with T_re (Spearman’s rank correlation $\rho$ = 0.893; median bias 0.2 °C) there was no consistent pattern in the differences between measures. Importantly, the two measures only agreed on heat tolerance outcome in 80% of trials with T_gi failing to detect heat intolerance identified by T_re in 6 of 8 trials. If T_gi was relied upon for diagnostic outcome, return to duty may occur before full recovery. None of the assessed covariates were related to the difference between T_re and T_gi. In addition, resting heart rate and systolic blood pressure were significantly lower and body surface area to mass ratio significantly higher in heat-tolerant compared to intolerant trials. Conclusions: It is not recommended to rely on T_gi instead of T_re during HTT. Resting heart rate and systolic blood pressure findings point to the importance of aerobic exercise in conveying heat tolerance along with body composition. Full article

On the one hand, the dynamic characteristics of gas-heat flow in the IES (integrated energy system) are important in achieving multi-energy coupling, improving system scheduling flexibility, and increasing energy regulation potential. On the other hand, the uncertainty of new energy causes fluctuations in the interactive power between the upper TG (transmission grid) and the lower IES, and its coupling characteristics weaken the autonomy of each system. Therefore, this paper proposes a robust two-stage scheduling strategy for TG-IES, considering gas-heat dynamic characteristics. Firstly, according to the characteristic equation of gas-heat energy flow, the dynamic model of the gas-heat network is established and applied to system scheduling. Secondly, aiming at the uncertainty problem, a TG-IES two-stage robust model is constructed, and the ATC (analytical target cascading) method and the C&CG (column and constraint generation) algorithm are combined to realize the distributed solution of the non-convex coupling model. Finally, the effectiveness of the model and strategy is verified by using the IEEE-39 system as TG and the IEEE39 Grid-20 Gas Grid-6 Heat Network system as IES. The simulation results show that using a two-stage robust model and considering the dynamic characteristics of gas and heat can effectively reduce system operating costs and improve the environmental friendliness of system scheduling. Full article

The ripeness of tomatoes is a critical factor influencing both their quality and yield. Currently, the accurate and efficient detection of tomato ripeness in greenhouse environments, along with the implementation of selective harvesting, has become a topic of significant research interest. In response to the current challenges, including the unclear segmentation of tomato ripeness stages, low recognition accuracy, and the limited deployment of mobile applications, this study provided a detailed classification of tomato ripeness stages. Through image processing techniques, the issue of class imbalance was addressed. Based on this, a model named GCSS-YOLO was proposed. Feature extraction was refined by introducing the RepNCSPELAN module, which is a lightweight alternative that reduces model size. A multi-dimensional feature neck network was integrated to enhance feature fusion, and three Semantic Feature Learning modules (SGE) were added before the detection head to minimize environmental interference. Further, Shape_IoU replaced CIoU as the loss function, prioritizing bounding box shape and size for improved detection accuracy. Experiments demonstrated GCSS-YOLO’s superiority, achieving an average mean average precision mAP50 of 85.3% and F1 score of 82.4%, outperforming the SSD, RT-DETR, and YOLO variants and advanced models like YOLO-TGI and SAG-YOLO. For practical deployment, this study deployed a mobile application developed using the NCNN framework on the Android platform. Upon evaluation, the model achieved an RMSE of 0.9045, an MAE of 0.4545, and an R² value of 0.9426, indicating strong performance. Full article

As integrated electronic microsystems advance, their internal components demonstrate increasing miniaturization, higher-density integration, and, consequently, significantly enhanced performance. This paper presents an on-chip transformer balun. The balun has a combination of planar coupled inductors and filtering capacitors using integrated passive device (IPD) technology, giving it the advantages of a more compact circuit size and lower cost to achieve single-ended to differential function on glass substrates. Moreover, it can be integrated in systems by flip-chip. The die has a size of 1.81 mm × 1.36 mm with a −15 dB single-ended return loss bandwidth of 2.07 GHz to 4.30 GHz. Within this bandwidth, the maximum insertion loss is 2.56 dB, and the amplitude imbalance is less than 2.04 dB. The phase difference between the differential signals is 180 ± 14.02° and the common mode rejection ratio (CMRR) is above 19.08 dB. The balun has the potential of miniaturization for integration on package or through-glass interposers (TGIs). Full article

In this study, we constructed a linear antibody–drug conjugate (ADC), 7300-LP1003, by coupling the camptothecin derivative 095 to a linker through an ether bond. In vitro enzyme experiments indicated that LP1003 releases 095 through the action of tissue cathepsin B. Therefore, we introduced lysine pairs with different water-soluble substituents to further modify the linker and synthesized side-chain ADCs 7300-LP3004 and 7300-LP2004, modified by polysarcosine and polyethylene glycol, respectively. In vitro experiments showed that, after incubation at 55 °C in phosphate-buffered saline for 48 h, 7300-LP3004 aggregation was 45.24%, which was significantly lower than that of 7300-LP1003 (77.14%). Cell cytotoxicity assays demonstrated that the side-chain ADCs, 7300-LP3004 and 7300-LP2004, exhibited significantly higher activity (IC50 values of 39.74 nM and 32.17 nM, respectively) compared to the linear ADC and 7300-Deruxtecan (IC50 of 186.5 nM and 124.5 nM, respectively). In the subcutaneous model of SHP-77 NOD scid gamma mice, when the ADC dose was 5 mg/kg, 7300-LP3004 showed the highest tumor inhibition rate with a tumor growth inhibition (TGI) of 106.09%, which was superior to that of the positive control 7300-Deruxtecan, which had a TGI of 103.95%. In conclusion, 7300-LP3004 demonstrated strong antitumor activity and high physicochemical stability, highlighting the need for further research and development of ADC drugs. Full article

The significantly rising incidence of oral cancer worldwide urgently requires the identification of novel, effective molecular targets to inhibit the progression of malignancy. DNA topoisomerase I (Topo I) is a well-established target for cancer treatment, and many studies have shown that different cancer cell genes could be targeted more selectively with one type of Topo I inhibitor. In this report, a new scaffold pyridothieno[3,2-c]isoquinoline 11,11-dioxide was designed via the combination of the key fragment or bioisoster of Topo I inhibitor azaindenoisoquinolines and G-quadruplex binder quindoline. Thirty-two target derivatives were synthesized, among which compounds 7be, with potent Topo I inhibition, exhibited effective antiproliferative activity against Cal27, one of the oral cancer cell lines highly expressing Topo I protein. Further studies indicated that 7be could also inhibit the activation of PI3K/AKT/NF-κB pathway and downregulate the level of c-MYC, repress the colony formation and the migration of Cal27 cells and trigger apoptosis and autophagy. Molecular docking indicated that 7be could interact with the complex of Topo I and DNA via a mode similar to the indenoisoquinolines. The results of the Cal27 xenograft model confirmed that 7be exhibited promising anticancer efficacy in vivo, with tumor growth inhibition (TGI) of 64.7% at 20 mg/kg. Full article

Quercetin, a flavonoid, has well-proven cytotoxicity potential, but its therapeutic efficacy is hampered by hydrophobicity, stability issues, and lower bioavailability. The present research aims to address these issues and formulation barriers by formulating a quercetin-loaded micellar nanogel. Quercetin was encapsulated in PF 68 micelles to enhance its solubility, loading, and stability to better its therapeutic potential. The nanogel was further characterized regarding for pH, spreadability, and in vitro cytotoxicity against human breast cancer cells (MCF-7). The resulting micelles exhibited a particle size of 180.26 ± 2.4 nm, surface charge of −13.5 mV, entrapment efficiency of 78.4 ± 1.2%, and in vitro release of 96.11 ± 0.75% up to 8 h. This in vitro cytotoxicity study on MCF-7 cell lines reveals the improved TGI and GI 50 values of micellar nanogel formulation compared to quercetin. The overall study results demonstrated that the developed micellar nanogel system might serve as a promising nanocarrier to enhance the cytotoxic potential of quercetin in cancer therapy. Full article

Background/Objectives: Cancer is a dynamic and complex disease that remains largely untreated despite major advances in oncology and treatment. In this context, we aimed here to investigate optimal control techniques in the management of tumor growth inhibition, with a particular focus on cancer chemotherapy treatment strategies. Methods: Using both linear autoregressive with exogenous inputs (ARX) and advanced non-linear tumor growth inhibition (TGI) modeling approaches, we investigated various single-agent treatment protocols, including continuous, periodic, and intermittent chemotherapy schedules. By integrating advanced mathematical modeling with optimal control theory and methods, namely the Linear Quadratic Regulator (LQR) and the “pseudo-linear” state-space equivalent representation and suboptimal control of a non-linear dynamic system known as the State-Dependent Riccati Equation (SDRE) approach, this work explores and evaluates successfully, more effective chemotherapy treatment strategies at the computer simulation level, using real preclinical data which increases the expectation to be applied in the clinical practice of oncology. Results: The integration of these methods provides insights into how different drug administration schedules may affect tumor response at the preclinical level. This work uses mathematical modeling to evaluate the efficacy of various periodic and intermittent chemotherapy treatment strategies, with a focus on optimizing drug doses while minimizing the potential side effects of chemotherapy due to the administration of less effective chemotherapeutic doses. Conclusions: The treatment scenarios tested in this study could effectively stop tumor growth or even lead to tumor regression to a negligible or near-zero size. This approach highlights the importance of computational tools for more effective treatment strategies in chemotherapy and offers a promising direction for future research and more efficient clinical applications in oncology as part of a more individualized approach. Full article

Efficient and reliable corn (Zea mays L.) yield prediction is important for varietal selection by plant breeders and management decision-making by growers. Unlike prior studies that focus mainly on county-level or controlled laboratory-scale areas, this study targets a production-scale area, better representing real-world agricultural conditions and offering more practical relevance for farmers. Therefore, the objective of our study was to determine the best combination of vegetation indices and abiotic factors for predicting corn yield in a rain-fed, production-scale area, identify the most suitable corn growth stage for yield estimation using machine learning, and identify the most effective machine learning model for corn yield estimation. Our study used high-resolution (6 cm) aerial multispectral imagery. Sixty-two different predictors, including soil properties (sand, silt, and clay percentages), slope, spectral bands (red, green, blue, red-edge, NIR), vegetation indices (GNDRE, NDRE, TGI), color-space indices, and wavelengths were derived from the multispectral data collected at the seven (V4, V5, V6, V7, V9, V12, and V14/VT) growth stages of corn. Four regression and machine learning algorithms were evaluated for yield prediction: linear regression, random forest, extreme gradient boosting, and gradient boosting regressor. A total of 6865 yield values were used for model training and 1716 for validation. Results show that, using random forest method, the V14/VT stage had the best yield predictions (RMSE of 0.52 Mg/ha for a mean yield of 10.19 Mg/ha), and yield estimation at V6 stage was still feasible. We concluded that integrating abiotic factors, such as slope and soil properties, significantly improved model accuracy. Among vegetation indices, TGI, HUE, and GNDRE performed better. Results from this study can help farmers or crop consultants plan ahead for future logistics through enhanced early-season yield predictions and support farm profitability and sustainability. Full article

Objectives: This study aimed to investigate the impact of the RDW–albumin ratio (RAR), Triglyceride–glucose index (TGI), and pan-immune-inflammation value (PIV) on predicting prognosis in patients with coronary artery disease (CAD) and to assess the potential use of these biomarkers in clinical decision-making. Materials and Methods: This retrospective study involved patients diagnosed and treated from 2020 to 2024. The study population included individuals diagnosed with CAD (n = 450) as well as a control group without CAD (n = 150). Results: The RAR, TGI, and PIV were significantly higher in the CAD group (p < 0.01 for all). Furthermore, a high RAR was found to be a risk factor for CAD (OR = 1.4, 95% CI: 1.2–1.7, p < 0.01), while elevated TGI was also linked to an increased risk of CAD (OR = 1.5, 95% CI: 1.3–1.8, p < 0.01). Similarly, a high PIV was strongly associated with CAD risk (OR = 2.0, 95% CI: 1.7–2.4, p < 0.01). The combined analysis of RAR, TGI, and PIV yielded an AUC value of 0.78 (0.75–0.81), indicating that these biomarkers collectively provide high diagnostic accuracy for CAD, with a sensitivity of 74% and specificity of 77% (p < 0.01). Conclusions: In conclusion, our study not only emphasizes the significance of traditional risk factors in CAD, but also highlights new biomarkers that could improve predictive accuracy. The combined use of biomarkers such as the RAR, TGI, and PIV offers greater accuracy in diagnosing CAD. Thus, our research presents an innovative approach with the potential to enhance the prediction and management of CAD risk. Full article

Objectives: We aimed to investigate the association between the triglyceride glucose index (TGI) and mortality in patients with ST-elevation myocardial infarction (STEMI). Methods: This retrospective study utilized data from the records of patients diagnosed with STEMI who underwent primary percutaneous coronary intervention (PCI) at the Cardiology Department of Private Aktif International Hospital between 2020 and 2023. Demographic data, medical history, laboratory results, and treatment processes of the patients were obtained from retrospective records. Patients were divided into low (TGI ≤ 8.6)-, medium (TGI = 8.6–9.2)-, and high (TGI ≥ 9.2)-TGI groups according to their TGI levels. Results: The average age of the patients was 62 ± 10 years, and 65% were men. The intracoronary thrombus burden of patients in the high-TGI group was found to be significantly higher compared to the low- and medium-TGI groups (p = 0.01). While the rate of patients with a thrombolysis in myocardial infarction (TIMI) thrombosis score of 3 or above was 45% in the high-TGI group, this rate was observed to be 20% in the low-TGI group. The short-term (30-day) mortality rate was found to be 15% in the high-TGI group, 8% in the medium-TGI group, and 5% in the low-TGI group (p = 0.02). Long-term (after 30 days) mortality rates were determined as 25% in the high-TGI group, 15% in the medium-TGI group, and 10% in the low-TGI group (p = 0.01). TGI was an independent risk factor for both short-term and long-term mortality. The hazard ratio (HR) of high TGI levels for short-term mortality was found to be 2.5 (95% CI: 1.5–4.1, p = 0.01), and the HR for long-term mortality was 2.0 (95% CI: 1.3–3.2, p < 0.02). Conclusions: Our results show that high TGI levels are associated with increased thrombus burden and high mortality rates in STEMI. TGI can be used not only in predicting STEMI but also in early risk stratification and treatment planning for STEMI patients. Full article

Objectives: We aimed to evaluate the importance of metabolic and inflammatory markers, specifically the Triglyceride–Glucose Index (TGI) and pan-immune inflammation value (PIV), in predicting mortality among patients diagnosed with pulmonary thromboembolism (PTE). Materials and Methods: A total of 450 patients diagnosed with PTE between December 2018 and December 2023 were included in his study. The diagnosis of PTE was confirmed by clinical presentation, laboratory tests, and imaging studies such as computed tomography pulmonary angiography (CTPA). Data were obtained from medical records, including demographic information, medical history, laboratory results, and clinical outcomes. Results: In terms of age, non-survivors were older on average (66.1 ± 11.8 years) compared to survivors (58.3 ± 12.4 years) (p = 0.03). In terms of gender, 55% of non-survivors and 45% of survivors were male (p = 0.111). Non-survivors had higher BMIs (28.3 ± 5.1) than survivors (25.7 ± 4.5) (p = 0.04). In terms of hypertension, 40% of non-survivors and 30% of survivors had hypertension (p = 0.041). In terms of diabetes, 35% of those who did not survive and 20% of those who survived had diabetes (p = 0.001). In terms of smoking, 25% of non-survivors and 15% of survivors smoke (p = 0.022). In terms of TGI, non-survivors had higher TGI values (12.1 ± 1.5) than survivors (5.9 ± 1.2) (p < 0.001). In terms of PIV, non-survivors had significantly higher PIV (878.2 ± 85.4) than survivors (254.5 ± 61.1) (p < 0.001). The risk factors found to be significantly associated with differentiation in the multiple logistic regression analysis included age, BMI, TGI, and PIV (p = 0.005, p = 0.002, p = 0.013, and 0.022, respectively). As a result, according to ROC analysis for patients who are non-survivors, age, BMI, TGI, and PIV were significant prognostic factors. The cut-off points for these values were >60, >27, >10, and >500, respectively. Conclusions: the TGI and PIV are strong markers for predicting mortality in PTE patients. The independent predictive value of age and BMI further demonstrates their role in risk stratification. We think that high TGI values and PIVs reflect underlying metabolic and inflammatory disorders that may contribute to worse outcomes in these patients. Full article

Background: Although immunotherapy has shown potential in cancer treatment, current immunotherapeutics for bladder cancer are limited by a low response rate. Therefore, it is necessary to investigate other suitable immunotherapeutic targets and strategies for bladder cancer. Methods: To evaluate whether CD47 could be a suitable target for bladder cancer immunotherapy, CD47 protein expression levels in 116 bladder cancer tissue samples were assessed by IHC staining. In vitro anti-tumor effect of blocking CD47 was examined by phagocytosis assays. In vivo anti-tumor effects of targeting CD47 and angiogenesis were experimented in the HSPCs-CDX model. Results: We find that CD47 is highly expressed in bladder cancer samples and is associated with poor prognosis. Blocking CD47 could enhance the human PBMC-derived macrophages’ phagocytosis of T24 (from 10.40% to 29.70%) and 5637 (from 5.31% to 33.52%) human bladder cancer cells, as well as demonstrate anti-tumor effects in the HSPCs-CDX model (tumor growth inhibition rate, TGI: 33.05%). During CD47 treatment, we observed that the level of angiogenesis increased after CD47 blockade, and it might undermine the effect of CD47 immunotherapy. We then combined CD47 blockade with anti-angiogenic drugs to treat bladder cancer and discovered that inhibiting angiogenesis could further improve the anti-tumor effect of CD47 blockade (TGI: 76.39%). Finally, we tested the anti-tumor effect of co-targeting CD47 and angiogenesis using a bispecific fusion protein, SIRPα-VEGFR1, which successfully inhibited tumor growth to a similar extent as a combination therapy. Conclusions: Our study suggests that targeting CD47 could inhibit the growth of bladder cancer by promoting macrophage-mediated anti-tumor immunity. Moreover, blocking CD47 and angiogenesis could achieve a potent anti-tumor effect and could be an effective immunotherapy strategy for bladder cancer. Full article