Towards Personalised Mood Prediction and Explanation for Depression from Biophysical Data.

Digital health applications using Artificial Intelligence (AI) are a promising opportunity to address the widening gap between available resources and mental health needs globally. Increasingly, passively acquired data from wearables are augmented with carefully selected active data from depressed individuals to develop Machine Learning (ML) models of depression based on mood scores. However, most ML models are black box in nature, and hence the outputs are not explainable. Depression is also multimodal, and the reasons for depression may vary significantly between individuals. Explainable and personalised models will thus be beneficial to clinicians to determine the main features that lead to a decline in the mood state of a depressed individual, thus enabling suitable personalised therapy. This is currently lacking. Therefore, this study presents a methodology for developing personalised and accurate Deep Learning (DL)-based predictive mood models for depression, along with novel methods for identifying the key facets that lead to the exacerbation of depressive symptoms. We illustrate our approach by using an existing multimodal dataset containing longitudinal Ecological Momentary Assessments of depression, lifestyle data from wearables and neurocognitive assessments for 14 mild to moderately depressed participants over one month. We develop classification- and regression-based DL models to predict participants' current mood scores-a discrete score given to a participant based on the severity of their depressive symptoms. The models are trained inside eight different evolutionary-algorithm-based optimisation schemes that optimise the model parameters for a maximum predictive performance. A five-fold cross-validation scheme is used to verify the DL model's predictive performance against 10 classical ML-based models, with a model error as low as 6% for some participants. We use the best model from the optimisation process to extract indicators, using SHAP, ALE and Anchors from explainable AI literature to explain why certain predictions are made and how they affect mood. These feature insights can assist health professionals in incorporating personalised interventions into a depressed individual's treatment regimen.

Current Perspective in Cancer Theranostics Based on Gold Nanoparticles.

The growth of nanotechnology has revolutionized the diagnosis and treatment of diseases with high precision and effectiveness. Nanoparticles (NPs) represent a major point of attention in the scientific field, with an increasing number of studies revealing promising results. The unique physicochemical properties, biocompatibility, and highly developed chemical properties of gold nanoparticles (AuNPs) have promoted breakthroughs in the cancer community, focusing on the therapeutic and diagnostic applications of cancer diagnosis and treatment. This perspective aims to summarize the latest research on multifunctional AuNPs as therapeutic, diagnostic agents in cancer diagnosis and treatment. Several nanostructured hybrid AuNPs have been reviewed, and their applications in imaging, targeting, therapy, and delivery have been discussed.

Safranin O-functionalized cuboid mesoporous silica material for fluorescent sensing and adsorption of permanganate.

Incorporation of dual functions, i.e., sensing and adsorption, into one single organic-inorganic hybrid material for the detection and removal of toxic permanganate (MnO4-) ions is of great importance, representing a challenging and new task in the design and application of new functional materials. However, most of the reported materials display only one function as either sensing probes or adsorbents. In this work, a fluorescent cuboid mesoporous silica-based hybrid material (SiO2@SFNO) is first prepared by the covalent coupling of a new safranin O-based fluorophore (2,8-dimethyl-5-phenyl-3,7-bis(3-(3-(triethoxysilyl)propyl)ureido)phenazin-5-ium chloride) (SFNO) and newly-made cuboid mesoporous silica, which showed selective dual-functional activities towards MnO4- and green emission at 575 nm with a long-range excitation wavelength that is suitable for bio-imaging application. The design of this SiO2@SFNO material is based on the position of -NHCONH- groups, which are mainly responsible for the strong and selective coordination with MnO4-. SiO2@SFNO is responsive to MnO4- at parts per billion (67 ppb) level; it also displays high adsorption ability (292 mg g-1) to MnO4- in aqueous solutions. The fluorescence responses of MnO4-in vivo (limnodrilus claparedianus and zebrafish) demonstrate the possibility of further application in biology. Interestingly, this SiO2@SFNO material is also capable of monitoring trace amounts of Hg2+ and Cu2+ in living organisms, holding great potential in bio-related applications.

Selective and Recyclable Congo Red Dye Adsorption by Spherical Fe3O4 Nanoparticles Functionalized with 1,2,4,5-Benzenetetracarboxylic Acid.

In this study, the new material Fe3O4@BTCA has been synthesized by immobilization of 1,2,4,5-Benzenetetracarboxylic acid (BTCA) on the surface of Fe3O4 NPs, obtained by co-precipitation of FeCl3.6H2O and FeCl2.4H2O in the basic conditions. Characterization by P-XRD, FE-SEM, and TEM confirm Fe3O4 has a spherical crystalline structure with an average diameter of 15 nm, which after functionalization with BTCA, increases to 20 nm. Functionalization also enhances the surface area and surface charge of the material, confirmed by BET and zeta potential analyses, respectively. The dye adsorption capacity of Fe3O4@BTCA has been investigated for three common dyes; Congo red (C.R), Methylene blue (M.B), and Crystal violet (C.V). The adsorption studies show that the material rapidly and selectively adsorbs C.R dye with very high adsorption capacity (630 mg/g), which is attributed to strong H-bonding ability of BTCA with C.R dye as indicated by adsorption mechanism study. The material also shows excellent recyclability without any considerable loss of adsorption capacity. Adsorption isotherm and kinetic studies suggest that the adsorption occurs by the Langmuir adsorption model following pseudo-second-order adsorption kinetics.

One-Pot Hydrothermal Synthesis of Carbon Quantum Dots with Excellent Photoluminescent Properties and Catalytic Activity from Coke Powders.

Water-soluble, high quantum yield, green color carbon quantum dots (CQDs) are prepared by acid reflux with the use of coke powders as a carbon source. The CQDs are characterized by UV-Vis absorption spectroscopy, fluorescence spectroscopy, transmission electron microscope, fourier transform infrared spectrophotometer and x-ray diffraction. The analysis includes the evaluation of key variables with effect in the synthetic process of the quantum yield (QY) of CQDs: the reaction temperature and time, the volume of mixed acid (concentrated H2SO4 and HNO3) and the pH value on the structure and properties of as-prepared CQDs. The results revealed that the optimal hydrothermal synthesis conditions for obtaining CQDs are reaction at 100 °C for 8 h, with the volume of mixed acid is 16 mL, at pH value 9. The prepared CQDs have the activity of peroxidase-like and that quantum yield(QY)reached 34.27%.

Design of Multifunctional Fluorescent Hybrid Materials Based on SiO2 Materials and Core-Shell Fe3 O4 @SiO2 Nanoparticles for Metal Ion Sensing.

Hybrid fluorescent materials constructed from organic chelating fluorescent probes and inorganic solid supports by covalent interactions are a special type of hybrid sensing platform that has gained much interest in the context of metal ion sensing applications owing to their excellent advantages, recyclability, and solubility/dispersibility in particular, as compared with single organic fluorescent molecules. In recent decades, SiO2 materials and core-shell Fe3 O4 @SiO2 nanoparticles have become important inorganic solid materials and have been used as inorganic solid supports to hybridize with organic fluorescent receptors, resulting in multifunctional fluorescent hybrid systems for potential applications in sensing and related research fields. Therefore, recent progress in various fluorescent-group-functionalized SiO2 materials is reviewed, with a focus on mesoporous silica nanoparticles and core-shell Fe3 O4 @SiO2 nanoparticles, as interesting fluorescent organic-inorganic hybrid materials for sensing applications toward essential and toxic metal ions. Selective examples of other types of silica/silicon materials, such as periodic mesoporous organosilicas, solid SiO2 nanoparticles, fibrous silica spheres, silica nanowires, silica nanotubes, and silica hollow microspheres, are also mentioned. Finally, relevant perspectives of metal-ion-sensing-oriented silica-fluorescent probe hybrid materials are provided.

An Ionophore for High Lithium Loading and Selective Capture from Brine.

The continuous demand and uneven dispersal of natural mineral resources of lithium with a low recycling rate of lithium commodities have forced researchers to look for alternative resources like geothermal brine, brackish brines, and sea brines. But selective lithium-ion extraction and even lithium-ion binding from these aqueous systems is a recognized challenge due to very high hydration energy and the coexistence of other like metal ions but appealing due to economic benefits. Therefore, the designed synthesis of synthetic ionophores with high lithium selectivity is crucial as they can work on dilute conditions without removal of interfering metal ions. However, most of the lithium selective ionophores known in the literature are mononucleated, and no emphasis is given on designing multinucleating ionophore systems to improve the lithium loading capacity which will open up unexplored paths toward the development of a more sustainable and economical extraction process. Herein, we describe a rare fluorogenic macrocyclic ionophore with two binding pockets for selective lithium recognition and extraction among various major alkali and alkaline earth metal ions of oceanic presence through both solid-state and solution studies. Under solid-liquid extraction conditions, this receptor shows a high lithium loading capacity of 135% with LiClO4 and 69.16% with LiCl salt with exclusive selectivity. Under liquid-liquid extraction conditions, this ionophore shows a loading capacity of 27% with 1 M LiCl and 48.57% with 1 M LiClO4 source phase concentration. This new ionophore, therefore, inspiring further to modify and develop a better multinucleating extractant with high lithium loading capacity which is rare in the literature.

An Anthracene Excimer Fluorescence Probe on Mesoporous Silica for Dual Functions of Detection and Adsorption of Mercury (II) and Copper (II) with Biological In Vivo Applications.

Dual functional activity by the same organic-inorganic hybrid material toward selective metal ion detection and its adsorption has drawn more attraction in the field of sensing. However, most of the hybrid materials in the literature are either for sensing studies or adsorption studies. In this manuscript, a fluorescent active hybrid material SiO2 @PBATPA is synthesized by covalent coupling of anthracene-based chelating ligand N,N'-(propane-1,3-diyl) bis(N-(anthracen-9-ylmethyl)-2-((3-(triethoxysilyl)propyl) amino) acetamide) (PBATPA) within the mesopores of newly synthesized cubic mesoporous silica. The synthetic strategy is designed to form an exclusively intramolecular excimer on a solid surface, which is then used as a sensory tool for selective detection of metal ions through fluorescence quenching by the destruction of excimer upon metal ion binding. The dual functions of sensing and adsorption studies show selectivity toward Hg2+ and Cu2+ among various metal ions with detection limits of 37 and 6 ppb, respectively, and adsorption capacities of 482 and 246 mg g-1 , respectively. This material can be used as a sensory cum adsorbent material in real food samples and living organisms such as the brine shrimp Artemia salina without any toxic effects from the material.

Copper(II)-Specific Fluorogenic Task-Specific Ionic Liquids as Selective Fluorescence Probes and Recyclable Extractants.

The designed synthesis of a series of copper(II) specific fluorogenic hydrophobic task-specific ionic liquids (TSILs) from a new naphthalene-based tetradentate ligand is reported. Absorption and fluorescence spectral studies reveal both the ligand and its derivative TSILs show exclusive selectivity towards copper(II) ions. The Stern-Volmer method for calculation of the detection limit for ligand and TSIL1-3 shows values of 0.12, 20, 17, and 15 µM, respectively. Extraction and striping studies by doping these TSILs in [bmim][NTf2] demonstrated that these TSILs are recyclable extractants for the selective recovery of Cu(II) ions from a mixture of 14 relevant metal chloride aqueous solutions in biphasic liquid-liquid extraction with approximately 95% recovery.