Reinforcing Protein Biochemistry: A Two-Week Experiment Studying Iron(III) Binding by the Transferrin Protein through Stoichiometric Determination, Stability Analysis, and Visualization of the Binding Site.

The two-week protein biochemistry experience described herein focuses on reinforcing key biochemical concepts and achieving significant learning domain accomplishments for students (Content Knowledge, Logical Mathematical Reasoning, Visualization, Information Literacy, and Knowledge Integration) and valuable teaching opportunities for instructors. The experience encompasses an exploration of the transport protein serum transferrin as an important regulator of Fe(III) biochemistry and incorporates techniques to assess protein-metal stoichiometry and protein stability and to perform molecular visualization. Students gain practical experience in utilizing spectrophotometric analysis for constructing stoichiometric curves, in performing urea-PAGE, and in applying the PyMOL program to evaluate metal coordination at a protein binding site and the associated protein structural change. The learning and teaching accomplishments provide valuable skills that can be extended into research and translated to other teaching formats.

Enhancing IoT Network Security: Unveiling the Power of Self-Supervised Learning against DDoS Attacks.

The Internet of Things (IoT), projected to exceed 30 billion active device connections globally by 2025, presents an expansive attack surface. The frequent collection and dissemination of confidential data on these devices exposes them to significant security risks, including user information theft and denial-of-service attacks. This paper introduces a smart, network-based Intrusion Detection System (IDS) designed to protect IoT networks from distributed denial-of-service attacks. Our methodology involves generating synthetic images from flow-level traffic data of the Bot-IoT and the LATAM-DDoS-IoT datasets and conducting experiments within both supervised and self-supervised learning paradigms. Self-supervised learning is identified in the state of the art as a promising solution to replace the need for massive amounts of manually labeled data, as well as providing robust generalization. Our results showcase that self-supervised learning surpassed supervised learning in terms of classification performance for certain tests. Specifically, it exceeded the F1 score of supervised learning for attack detection by 4.83% and by 14.61% in accuracy for the multiclass task of protocol classification. Drawing from extensive ablation studies presented in our research, we recommend an optimal training framework for upcoming contrastive learning experiments that emphasize visual representations in the cybersecurity realm. This training approach has enabled us to highlight the broader applicability of self-supervised learning, which, in some instances, outperformed supervised learning transferability by over 5% in precision and nearly 1% in F1 score.

Transport and Application Layer DDoS Attacks Detection to IoT Devices by Using Machine Learning and Deep Learning Models.

From smart homes to industrial environments, the IoT is an ally to easing daily activities, where some of them are critical. More and more devices are connected to and through the Internet, which, given the large amount of different manufacturers, may lead to a lack of security standards. Denial of service attacks (DDoS, DoS) represent the most common and critical attack against and from these networks, and in the third quarter of 2021, there was an increase of 31% (compared to the same period of 2020) in the total number of advanced DDoS targeted attacks. This work uses the Bot-IoT dataset, addressing its class imbalance problem, to build a novel Intrusion Detection System based on Machine Learning and Deep Learning models. In order to evaluate how the records timestamps affect the predictions, we used three different feature sets for binary and multiclass classifications; this helped us avoid feature dependencies, as produced by the Argus flow data generator, whilst achieving an average accuracy >99%. Then, we conducted comprehensive experimentation, including time performance evaluation, matching and exceeding the results of the current state-of-the-art for identifying denial of service attacks, where the Decision Tree and Multi-layer Perceptron models were the best performing methods to identify DDoS and DoS attacks over IoT networks.

Iron Chelator Transmetalative Approach to Inhibit Human Ribonucleotide Reductase.

Efforts directed at curtailing the bioavailability of intracellular iron could lead to the development of broad-spectrum anticancer drugs given the metal's role in cancer proliferation and metastasis. Human ribonucleotide reductase (RNR), the key enzyme responsible for synthesizing the building blocks of DNA replication and repair, depends on Fe binding at its R2 subunit to activate the catalytic R1 subunit. This work explores an intracellular iron chelator transmetalative approach to inhibit RNR using the titanium(IV) chemical transferrin mimetic (cTfm) compounds Ti(HBED) and Ti(Deferasirox)2. Whole-cell EPR studies reveal that the compounds can effectively attenuate RNR activity though seemingly causing different changes to the labile iron pool that may account for differences in their potency against cells. Studies of Ti(IV) interactions with the adenosine nucleotide family at pH 7.4 reveal strong metal binding and extensive phosphate hydrolysis, which suggest the capacity of the metal to disturb the nucleotide substrate pool of the RNR enzyme. By decreasing intracellular Fe bioavailability and altering the nucleotide substrate pool, the Ti cTfm compounds could inhibit the activity of the R1 and R2 subunits of RNR. The compounds arrest the cell cycle in the S phase, indicating suppressed DNA replication, and induce apoptotic cell death. Cotreatment cell viability studies with cisplatin and Ti(Deferasirox)2 reveal a promising synergism between the compounds that is likely owed to their distinct but complementary effect on DNA replication.

Cytochrome c: Using Biological Insight toward Engineering an Optimized Anticancer Biodrug.

The heme protein cytochrome c (Cyt c) plays pivotal roles in cellular life and death processes. In the respiratory chain of mitochondria, it serves as an electron transfer protein, contributing to the proliferation of healthy cells. In the cell cytoplasm, it activates intrinsic apoptosis to terminate damaged cells. Insight into these mechanisms and the associated physicochemical properties and biomolecular interactions of Cyt c informs on the anticancer therapeutic potential of the protein, especially in its ability to subvert the current limitations of small molecule-based chemotherapy. In this review, we explore the development of Cyt c as an anticancer drug by identifying cancer types that would be receptive to the cytotoxicity of the protein and factors that can be finetuned to enhance its apoptotic potency. To this end, some information is obtained by characterizing known drugs that operate, in part, by triggering Cyt c induced apoptosis. The application of different smart drug delivery systems is surveyed to highlight important features for maintaining Cyt c stability and activity and improving its specificity for cancer cells and high drug payload release while recognizing the continuing limitations. This work serves to elucidate on the optimization of the strategies to translate Cyt c to the clinical market.

Exploring the pH dependent aqueous speciation of metal complexes through UV-Vis spectroscopy.

Coordination chemistry is a major component of the undergraduate inorganic chemistry curriculum and yet the presentation of the material can be cumbersome due to the limitations of the course typically being taught in one semester. Also, because of the large scope of this branch of chemistry encompassing all of the elements, the course design has not been standardized. These factors result in some important coordination chemistry themes being given insufficient development. Herein we propose a novel activity to formally introduce metal complex aqueous speciation in a holistic active-learning manner that includes a lecture component and hands-on experience. This topic has real world relevance and contextualizes many important coordination concepts. It would extend student comprehension about the intricate factors that affect metal complexation in an aqueous solution environment by focusing on the influence of pH. The activity explores the pH dependent speciation of the well-characterized interaction between Fe(III) and 2,3-dihydroxynapthalene-6-sulfonate and reveals the colorful changes in species throughout the pH range of 0 to 13. Students learn how to generate speciation plots and to understand the ultraviolet-visible (UV-Vis) electronic absorption spectroscopy of transition metal compounds to be able to analyze the source of color that they observe. Assessment of the activity was conducted with 24 students who completed a Likert scale survey and responded to open-ended questions. The activity was then applied in actual course settings in which student comprehension was quantitatively evaluated. The activity can be easily adapted to students of different stages of academic development from elementary to college students.

Exploring Serum Transferrin Regulation of Nonferric Metal Therapeutic Function and Toxicity.

Serum transferrin (sTf) plays a pivotal role in regulating iron biodistribution and homeostasis within the body. The molecular details of sTf Fe(III) binding blood transport, and cellular delivery through transferrin receptor-mediated endocytosis are generally well-understood. Emerging interest exists in exploring sTf complexation of nonferric metals as it facilitates the therapeutic potential and toxicity of several of them. This review explores recent X-ray structural and physiologically relevant metal speciation studies to understand how sTf partakes in the bioactivity of key non-redox active hard Lewis acidic metals. It challenges preconceived notions of sTf structure function correlations that were based exclusively on the Fe(III) model by revealing distinct coordination modalities that nonferric metal ions can adopt and different modes of binding to metal-free and Fe(III)-bound sTf that can directly influence how they enter into cells and, ultimately, how they may impact human health. This knowledge informs on biomedical strategies to engineer sTf as a delivery vehicle for metal-based diagnostic and therapeutic agents in the cancer field. It is the intention of this work to open new avenues for characterizing the functionality and medical utility of nonferric-bound sTf and to expand the significance of this protein in the context of bioinorganic chemistry.

Iron and Copper Intracellular Chelation as an Anticancer Drug Strategy.

A very promising direction in the development of anticancer drugs is inhibiting the molecular pathways that keep cancer cells alive and able to metastasize. Copper and iron are two essential metals that play significant roles in the rapid proliferation of cancer cells and several chelators have been studied to suppress the bioavailability of these metals in the cells. This review discusses the major contributions that Cu and Fe play in the progression and spreading of cancer and evaluates select Cu and Fe chelators that demonstrate great promise as anticancer drugs. Efforts to improve the cellular delivery, efficacy, and tumor responsiveness of these chelators are also presented including a transmetallation strategy for dual targeting of Cu and Fe. To elucidate the effectiveness and specificity of Cu and Fe chelators for treating cancer, analytical tools are described for measuring Cu and Fe levels and for tracking the metals in cells, tissue, and the body.

Expanding the Therapeutic Potential of the Iron Chelator Deferasirox in the Development of Aqueous Stable Ti(IV) Anticancer Complexes.

The recent X-ray structure of titanium(IV)-bound human serum transferrin (STf) exhibiting citrate as a synergistic anion reveals a difference in Ti(IV) coordination versus iron(III), the metal endogenously delivered by the protein to cells. This finding enriches our bioinspired drug design strategy for Ti(IV)-based anticancer therapeutics, which applies a family of Fe(III) chelators termed chemical transferrin mimetic (cTfm) ligands to inhibit Fe bioavailability in cancer cells. Deferasirox, a drug used for iron overload disease, is a cTfm ligand that models STf coordination to Fe(III), favoring Fe(III) binding versus Ti(IV). This metal affinity preference drives deferasirox to facilitate the release of cytotoxic Ti(IV) intracellularly in exchange for Fe(III). An aqueous speciation study performed by potentiometric titration from pH 4 to 8 with micromolar levels of Ti(IV) deferasirox at a 1:2 ratio reveals exclusively Ti(deferasirox)2 in solution. The predominant complex at pH 7.4, [Ti(deferasirox)2]2-, exhibits the one of the highest aqueous stabilities observed for a potent cytotoxic Ti(IV) species, demonstrating little dissociation even after 1 month in cell culture media. UV-vis and 1H NMR studies show that the stability is unaffected by the presence of biomolecular Ti(IV) binders such as citrate, STf, and albumin, which have been shown to induce dissociation or regulate cellular uptake and can alter the activity of other antiproliferative Ti(IV) complexes. Kinetic studies on [Ti(deferasirox)2]2- transmetalation with Fe(III) show that a labile Fe(III) source is required to induce this process. The initial step of this process occurs on the time scale of minutes, and equilibrium for the complete transmetalation is reached on a time scale of hours to a day. This work reveals a mechanism to deliver Ti(IV) compounds into cells and trigger Ti(IV) release by a labile Fe(III) species. Cellular studies including other cTfm ligands confirm the Fe(III) depletion mechanism of these compounds and show their ability to induce early and late apoptosis.

Intrauterine growth restriction with abnormal umbilical artery Dopplers: a harbinger for preeclampsia?

OBJECTIVE: To determine whether abnormal umbilical artery Doppler velocimetry in the setting of unexplained intrauterine growth restriction (IUGR) is predictive of preeclampsia. METHODS: This was a retrospective cohort study of singleton pregnancies diagnosed with unexplained IUGR between 2005 and 2008. Subjects were classified based on the presence or absence of abnormal Dopplers. The proportions of preeclampsia in the two groups were compared. RESULTS: A total of 268 cases were included in the study. There were 57 cases with abnormal umbilical artery Dopplers. Of those, preeclampsia was diagnosed in 8 (14.0%) cases. In turn, there were 211 cases with normal Dopplers. Of those, preeclampsia was diagnosed in 9 (4.3%) cases. After controlling for age and parity, patients with abnormal Dopplers were 2.9 times more likely to be diagnosed with preeclampsia. CONCLUSIONS: Cases of unexplained IUGR with abnormal umbilical artery Dopplers appear to be at increased risk of preeclampsia compared to those with normal Dopplers.