Browse Articles

Emerging quality-by-design optimized HPLC method for the concurrent determination of cefixime and ornidazole: a multi-criteria green and blue environmental footprinting

Abstract Design of experiments has emerged as an influential and proactive approach that demonstrated favored applicability in optimizing chromatographic procedures. Quality-by-design guarantees the long-standing efficiency of the developed HPLC method reducing the need for costly and resource-intensive univariate approach. A low environmental footprint, sensitive, fast, and simple HPLC method was developed for concurrent estimation of cefixime (CFX) and ornidazole (ORN) in their raw materials, laboratory-prepared tablets, and pharmaceutical formulations using 2 3 full factorial design. The separation was performed on a cyano column through UV detection at 300 nm in less than 4 min. The elution was achieved using a mobile phase (pH = 6.0) composed of methanol and 0.3% triethylamine in ratio of (85%: 15%, v/v), respectively with a flow rate of 1 mL/min. The method’s validity was established with ICH $$\:{\text{Q}}_{2}{\text{R}}_{1}$$ regulations. Excellent linear correlation ( r  = 0.9999) was established within concentration ranges lies between 1 and 50 µg/mL and 0.5–50 µg/mL with high percent found of 100.04 ± 0.82 and 99.99 ± 1.01 for CFX and ORN, respectively. The approach exhibited high precision (% RDS < 2) and sensitivity with detection limits of 0.07 and 0.09 µg/mL and quantification limits of 0.21 and 0.28 µg/mL for CFX and ORN, respectively. Several metrics evidenced the method’s greenness and sustainability profile.

A method for improving winter wheat mapping accuracy based on multi-temporal feature fusion and stacking ensemble learning

Discovering novel multi-target compounds against aspartyl viral polymerases via ligand-based pharmacophore and structure-based screening

Melatonin–selenium nanoformulation: a promising therapeutic strategy against Ehrlich ascites carcinoma

Abstract Combination therapy has emerged as a standard strategy for enhancing the efficacy of anticancer treatments. The purpose of our study was to assess the melatonin-selenium nanoparticles’ anticancer potential (MSeNPs) in a murine model of Ehrlich ascites carcinoma (EAC). Assessments included cell viability, hematological parameters, oxidative stress markers, apoptosis, cell cycle dynamics, and pro-inflammatory cytokines. Our findings demonstrate that MSeNPs inhibit tumor growth and enhance antioxidant defenses. MSeNPs significantly reduce IL-6 levels, alleviating EAC-associated inflammation. Furthermore, MSeNPs induced apoptosis through caspase-3 activation and Ki-67 downregulation, resulting in decreased cell proliferation and significant G0/G1 cell cycle arrest, accompanied by marked suppression of the S phase. In conclusion, these results highlight the synergistic therapeutic advantage of MSeNPs, indicating greater efficacy than monotherapies with melatonin, selenium, or selenium nanoparticles alone. MSeNPs hold promise as a potent, multi-targeted agent for future cancer therapies.

A refined chronology of the Naumann’s elephant (Palaeoloxodon naumanni) provides a new insight on factors of their extinction

Assessment of community pharmacists’ knowledge on rivaroxaban drug and food interactions in Sudan

Daily briefing: Why it’s hard to show insight under pressure

Explainable machine learning-driven identification of heart failure biomarkers: a multi-model feature selection approach with SHAP-based interpretability

A novel intrusion detection system for IIoT in 5G networks using attention-augmented federated learning and lightweight transformer architectures

Age-based approach to characterize the dynamics of cellular processes

Cells continuously produce and degrade molecules, essential for maintaining homeostasis. The study of these dynamics has gained momentum since the development of pulse–chase methods, utilizing fluorescent or isotopic labeling to assess properties such as turnover rates or half-lives. However, standard analyses of these experiments often depend on assumptions such as the homogeneity of analyzed molecules or their immediate labeling, which do not always hold. Here, we show that the readouts of steady-state dynamic labeling experiments can be interpreted as the distribution of metabolic ages, defined as the time since each molecule entered the metabolic system, and that metabolic ages can be quantified with minimal assumptions. Using this age-based interpretation, we demonstrate how the experimentally observed labeling dynamics is connected to a variety of dynamic parameters including half-lives, decay rates, and residence times and how these interpretations are affected by the conditions of delayed input, cell growth, or complex degradation patterns. To aid in the experimental quantification of dynamic parameters, we introduce a compartmental model framework as well as an open-source software package. We illustrate the framework’s practical utility by quantifying dynamic parameters and determining the kinetic pool structure of budding yeast proteins at optimal and suboptimal growth temperatures.

When the grid can’t keep up: how South African laboratories handle power outages

Folic acid attenuates maternal sertraline-induced hepatic injury in rat offspring

Collective motion in bacterial suspensions is scale-free

In suspensions of swimming bacteria, individual cells interact via long-range hydrodynamic forces and self-organize into collective states that drive large-scale chaotic flows, commonly referred to as “bacterial turbulence.” Despite extensive experimental and theoretical work, it remains unclear whether an intrinsic length scale underlies the observed patterns. To directly address this question and shed light on the mechanisms driving active turbulence, we investigate the emergence of large-scale flows in E. coli suspensions confined within flat cylindrical chambers, systematically varying the confinement height over more than two orders of magnitude. We first demonstrate that the critical density for the onset of collective motion scales inversely with the confinement height without saturation. Near the onset, both the observed length and time scales increase sharply, with the length scale limited only by the vertical confinement. Importantly, both scales exhibit clear power-law dependence on the confinement height, demonstrating the absence of an intrinsic length scale in bacterial collective motion. Close to the instability onset, we observed transient coherent vortices, reaching up to 4,000 times the size of a single bacterium and spanning the full chamber width, further reinforcing the conclusion that bacterial turbulence is scale-free. Our experimental results, which characterize the onset of collective motion and demonstrate that bacterial turbulence is scale-free, discriminate between competing theoretical models and provide essential input for theories seeking to capture the dynamics and constitutive relations of wet active matter.

Should there be a national museum of chemicals?

Research on a long-haul transmission-line distributed vibration signal denoising method based on dual-fiber sensing and weakly supervised learning

A reinforcement learning-enhanced discrete zebra optimization algorithm for solving the traveling salesman problem

Forbidden Sidon subsets of perfect difference sets, featuring a human-assisted proof

We resolve a $1,000 Erdős prize problem, complete with formal verification generated by a large language model. In over a dozen papers, beginning in 1976 and spanning two decades, Paul Erdős repeatedly posed one of his “favorite” conjectures: every finite Sidon set can be extended to a finite perfect difference set. We establish that {1, 2, 4, 8, 13} is a counterexample to this conjecture. During the preparation of this paper, we found that although this problem was presumed to be open for half a century, Marshall Hall, Jr. published a different counterexample three decades before Erdős first posed the problem. With a healthy skepticism of this apparent oversight, and out of an abundance of caution, we used ChatGPT to vibe prove both Hall’s and our counterexamples in Lean.

Nitric oxide dual-enhanced nanosystem boosts ferroptosis-chemotherapy synergy for tumor therapy

Indoor thermoregulatory homeostasis using hydrodynamic instability

Branching patterns can emerge when one fluid is injected into a more viscous one within a quasi-two-dimensional cavity. While these patterns have dazzled physicists for decades, modern engineering efforts have focused on suppressing, rather than leveraging, these flow instabilities. Here, by designing fluidic devices with calibrated geometries, liquid absorptivities, and rheology, we exploit the thermal sensitivity of the Saffman–Taylor instability to achieve thermoregulatory shading systems with self-adjustment capabilities. Our devices produce negative feedback branching patterns that reduce indoor solar heating when warm but increase it when cool. Moreover, compared to existing temperature-responsive shading approaches with fixed thermal behaviors, our system can switch its thermal sensitivity and indoor temperature setpoints on-demand by adjusting the rate that patterns are grown. Experiments and models reveal the energy savings and indoor climate control capabilities enabled by this thermoregulatory framework. Overall, our work provides a blueprint for designing materials with self-regulatory behaviors based on flow instabilities.

Chemical and mechanical extraction for egyptian safflower bio-oil with a performance and economic analysis for renewable fuel applications

Abstract The growing demand for sustainable biofuels has increased interest in efficient methods for extracting oil from non-edible feedstocks such as safflower. This study compares chemical and mechanical extraction techniques, including Soxhlet extraction, maceration, hydraulic pressing, and screw pressing, for biodiesel feedstock production. A Box–Behnken response surface methodology was applied to optimize screw press operating conditions. The optimal parameters were identified at 172.5 °C and a screw press speed of 1400 rpm, with an energy consumption of 3.86 W-hour and a yield of approximately 19% in 29.8 s. The oils extracted using four extraction techniques were characterized using gas chromatography-mass spectrometry and Fourier-transform infrared spectroscopy, confirming their suitability for biodiesel applications. Among the evaluated methods, a screw press proved to be the most energy-efficient and time-saving method, owing to the elimination of solvent use and its lower operational costs compared to conventional chemical methods. These findings highlight the potential of mechanical extraction as a cost-effective and environmentally sustainable approach for biodiesel production. Overall, this study provides a comparative and optimized framework for safflower oil extraction, supporting the transition toward greener and scalable biofuel production technologies.