Interactions between Organic Model Compounds and Ion Exchange Resins.

Ion exchange (IEX) can successfully remove natural organic matter (NOM) from surface water. However, the removal mechanism is not well understood due to the complexity and variability of NOM in real source waters as well as the influence of multiple parameters on the removal behavior. For example, this includes the physicochemical properties of the NOM and IEX resin, and the presence of competing anions. Model compounds with a range of physical and chemical characteristics were therefore used to determine the mechanisms of NOM removal by IEX resins. Fifteen model compounds were selected to evaluate the influence of hydrophobicity, size, and charge of organic molecules on the removal by ion exchange, both individually and in mixtures. Three different resins, comprising polystyrene and polyacrylic resin of macroporous and gellular structure, showed that charge density (CD) was the most important characteristic that controlled the removal, with CD of >5 mequiv mgDOC-1 resulting in high removal (≥89%). Size exclusion of compounds with high MW (≥8 kDa) was evident. The hydrophobicity of the resin and model compound was particularly important for removal of neutral molecules such as resorcinol, which was best removed by the more hydrophobic polystyrene resin. Relationships were identified that provided explanations of the interactions observed between NOM and IEX resin in real waters.

Role of filtration in managing the risk from Cryptosporidium in commercial swimming pools - a review.

Most commercial swimming pools use pressurised filters, typically containing sand media, to remove suspended solids as part of the water treatment process designed to keep water attractive, clean and safe. The accidental release of faecal material by bathers presents a poorly quantified risk to the safety of swimmers using the pool. The water treatment process usually includes a combination of maintaining a residual concentration of an appropriate biocide in the pool together with filtration to physically remove particles, including microbial pathogens, from the water. However, there is uncertainty about the effectiveness of treatment processes in removing all pathogens, and there has been growing concern about the number of reported outbreaks of the gastrointestinal disease cryptosporidiosis, caused by the chlorine-resistant protozoan parasite Cryptosporidium. A number of interacting issues influence the effectiveness of filtration for the removal of Cryptosporidium oocysts from swimming pools. This review explains the mechanisms by which filters remove particles of different sizes (including oocyst-sized particles, typically 4-6 µm), factors that affect the efficiency of particle removal (such as filtration velocity), current recommended management practices, and identifies further work to support the development of a risk-based management approach for the management of waterborne disease outbreaks from swimming pools.

Fluoride contamination in groundwater sources in Southwestern Nigeria: Assessment using multivariate statistical approach and human health risk.

The present study investigated the ionic and fluoride concentrations in tap water and its associated health risk to local dwellers of Ogun State (Abeokuta south), Nigeria. 63 samples were collected from twenty-one different locations. Results obtained revealed the mean concentration of fluoride (F-) as 1.23 mg/L. Other water quality parameters such as total dissolved solids (TDS), electrical conductivity (EC), F-, Fe2+, and SO42- surpassed the WHO guidance for drinking water. Strong positive correlation was observed between F- and TDS; F- and pH; TDS and EC; TDS and Mg2+; TDS and SO42-; TDS and HCO3-; EC and HCO3-; EC and SO42-; Na+ and Cl-; SO42- and Cl-. In addition, Empirical Bayesian Kriging (EBK) model was employed to spatially distribute the concentration of the analyzed elements within the study region. The chronic daily dose (CDD) and hazard quotient (HQ) were also used to evaluate the health risk associated with F-, considering dermal and ingestion as pathways. The results revealed that the associated HQ for infants between the age range of 6-12months within about 91% of the study region surpassed the accepted HQ limit. However, the HQ for age categories 11-16years; >65years; 18-21years; 21years; 16-18years within 95.2%, 90.5%, 80.95% and 100% of the study location were less than 1. Conclusively, the HQ values obtained in this study should serve as a baseline information for water management authorities, policymakers and the society at large towards addressing these pollution issues.

Maximum likelihood estimates of pairwise rearrangement distances.

Accurate estimation of evolutionary distances between taxa is important for many phylogenetic reconstruction methods. Distances can be estimated using a range of different evolutionary models, from single nucleotide polymorphisms to large-scale genome rearrangements. Corresponding corrections for genome rearrangement distances fall into 3 categories: Empirical computational studies, Bayesian/MCMC approaches, and combinatorial approaches. Here, we introduce a maximum likelihood estimator for the inversion distance between a pair of genomes, using a group-theoretic approach to modelling inversions introduced recently. This MLE functions as a corrected distance: in particular, we show that because of the way sequences of inversions interact with each other, it is quite possible for minimal distance and MLE distance to differently order the distances of two genomes from a third. The second aspect tackles the problem of accounting for the symmetries of circular arrangements. While, generally, a frame of reference is locked, and all computation made accordingly, this work incorporates the action of the dihedral group so that distance estimates are free from any a priori frame of reference. The philosophy of accounting for symmetries can be applied to any existing correction method, for which examples are offered.

Developing a statistically powerful measure for quartet tree inference using phylogenetic identities and Markov invariants.

Recently there has been renewed interest in phylogenetic inference methods based on phylogenetic invariants, alongside the related Markov invariants. Broadly speaking, both these approaches give rise to polynomial functions of sequence site patterns that, in expectation value, either vanish for particular evolutionary trees (in the case of phylogenetic invariants) or have well understood transformation properties (in the case of Markov invariants). While both approaches have been valued for their intrinsic mathematical interest, it is not clear how they relate to each other, and to what extent they can be used as practical tools for inference of phylogenetic trees. In this paper, by focusing on the special case of binary sequence data and quartets of taxa, we are able to view these two different polynomial-based approaches within a common framework. To motivate the discussion, we present three desirable statistical properties that we argue any invariant-based phylogenetic method should satisfy: (1) sensible behaviour under reordering of input sequences; (2) stability as the taxa evolve independently according to a Markov process; and (3) explicit dependence on the assumption of a continuous-time process. Motivated by these statistical properties, we develop and explore several new phylogenetic inference methods. In particular, we develop a statistically bias-corrected version of the Markov invariants approach which satisfies all three properties. We also extend previous work by showing that the phylogenetic invariants can be implemented in such a way as to satisfy property (3). A simulation study shows that, in comparison to other methods, our new proposed approach based on bias-corrected Markov invariants is extremely powerful for phylogenetic inference. The binary case is of particular theoretical interest as-in this case only-the Markov invariants can be expressed as linear combinations of the phylogenetic invariants. A wider implication of this is that, for models with more than two states-for example DNA sequence alignments with four-state models-we find that methods which rely on phylogenetic invariants are incapable of satisfying all three of the stated statistical properties. This is because in these cases the relevant Markov invariants belong to a class of polynomials independent from the phylogenetic invariants.

Matrix group structure and Markov invariants in the strand symmetric phylogenetic substitution model.

We consider the continuous-time presentation of the strand symmetric phylogenetic substitution model (in which rate parameters are unchanged under nucleotide permutations given by Watson-Crick base conjugation). Algebraic analysis of the model's underlying structure as a matrix group leads to a change of basis where the rate generator matrix is given by a two-part block decomposition. We apply representation theoretic techniques and, for any (fixed) number of phylogenetic taxa L and polynomial degree D of interest, provide the means to classify and enumerate the associated Markov invariants. In particular, in the quadratic and cubic cases we prove there are precisely [Formula: see text] and [Formula: see text] linearly independent Markov invariants, respectively. Additionally, we give the explicit polynomial forms of the Markov invariants for (i) the quadratic case with any number of taxa L, and (ii) the cubic case in the special case of a three-taxon phylogenetic tree. We close by showing our results are of practical interest since the quadratic Markov invariants provide independent estimates of phylogenetic distances based on (i) substitution rates within Watson-Crick conjugate pairs, and (ii) substitution rates across conjugate base pairs.

Lie Markov models with purine/pyrimidine symmetry.

Continuous-time Markov chains are a standard tool in phylogenetic inference. If homogeneity is assumed, the chain is formulated by specifying time-independent rates of substitutions between states in the chain. In applications, there are usually extra constraints on the rates, depending on the situation. If a model is formulated in this way, it is possible to generalise it and allow for an inhomogeneous process, with time-dependent rates satisfying the same constraints. It is then useful to require that, under some time restrictions, there exists a homogeneous average of this inhomogeneous process within the same model. This leads to the definition of "Lie Markov models" which, as we will show, are precisely the class of models where such an average exists. These models form Lie algebras and hence concepts from Lie group theory are central to their derivation. In this paper, we concentrate on applications to phylogenetics and nucleotide evolution, and derive the complete hierarchy of Lie Markov models that respect the grouping of nucleotides into purines and pyrimidines-that is, models with purine/pyrimidine symmetry. We also discuss how to handle the subtleties of applying Lie group methods, most naturally defined over the complex field, to the stochastic case of a Markov process, where parameter values are restricted to be real and positive. In particular, we explore the geometric embedding of the cone of stochastic rate matrices within the ambient space of the associated complex Lie algebra.

A tensorial approach to the inversion of group-based phylogenetic models.

BACKGROUND: Hadamard conjugation is part of the standard mathematical armoury in the analysis of molecular phylogenetic methods. For group-based models, the approach provides a one-to-one correspondence between the so-called "edge length" and "sequence" spectrum on a phylogenetic tree. The Hadamard conjugation has been used in diverse phylogenetic applications not only for inference but also as an important conceptual tool for thinking about molecular data leading to generalizations beyond strictly tree-like evolutionary modelling. RESULTS: For general group-based models of phylogenetic branching processes, we reformulate the problem of constructing a one-one correspondence between pattern probabilities and edge parameters. This takes a classic result previously shown through use of Fourier analysis and presents it in the language of tensors and group representation theory. This derivation makes it clear why the inversion is possible, because, under their usual definition, group-based models are defined for abelian groups only. CONCLUSION: We provide an inversion of group-based phylogenetic models that can implemented using matrix multiplication between rectangular matrices indexed by ordered-partitions of varying sizes. Our approach provides additional context for the construction of phylogenetic probability distributions on network structures, and highlights the potential limitations of restricting to group-based models in this setting.

Low-parameter phylogenetic inference under the general markov model.

In their 2008 and 2009 articles, Sumner and colleagues introduced the "squangles"-a small set of Markov invariants for phylogenetic quartets. The squangles are consistent with the general Markov (GM) model and can be used to infer quartets without the need to explicitly estimate all parameters. As the GM model is inhomogeneous and hence nonstationary, the squangles are expected to perform well compared with standard approaches when there are changes in base composition among species. However, the GM model assumes constant rates across sites, so the squangles should be confounded by data generated with invariant sites or other forms of rate-variation across sites. Here we implement the squangles in a least-squares setting that returns quartets weighted by either confidence or internal edge lengths, and we show how these weighted quartets can be used as input into a variety of supertree and supernetwork methods. For the first time, we quantitatively investigate the robustness of the squangles to breaking of the constant rates-across-sites assumption on both simulated and real data sets; and we suggest a modification that improves the performance of the squangles in the presence of invariant sites. Our conclusion is that the squangles provide a novel tool for phylogenetic estimation that is complementary to methods that explicitly account for rate-variation across sites, but rely on homogeneous-and hence stationary-models.

Unraveling the characteristics of dissolved organic matter removed by aluminum species based on FT-ICR MS analysis.

Given the complexity of dissolved organic matter (DOM) and its interactions with coagulant chemicals, the mechanisms of DOM removal by aluminum (Al) coagulants remains a significant unknown. In this study, six test waters containing DOM with molecular weight (MW, <1 kDa, 1-10 kDa and >10 kDa) and hydrophobicity (hydrophilic, transphilic and hydrophobic) were prepared and coagulated with Al0, Al13 and Al30. The molecular-level characteristics of DOM molecules that were removed or resistant to removal by Al species were analyzed using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The results showed that at the molecular level, saturated and reduced tannins and lignin-like compounds containing abundant carboxyl groups exhibited higher coagulation efficiency. Unsaturated and oxidized lipids, protein-like, and carbohydrates compounds were relatively resistant to Al coagulation due to their higher polarity and lower content of carboxyl groups. Al13 removed molecules across a wider range of molecular weights than Al0 and Al30, thus the DOC removal efficiency of Al13 was the highest. This study furthers the understanding of interactions between Al species and DOM, and provides scientific insights on the operation of water treatment plants to improve control of DOM.

How bioaugmentation for pesticide removal influences the microbial community in biologically active sand filters.

Removing pesticides from biological drinking water filters is challenging due to the difficulty in activating pesticide-degrading bacteria within the filters. Bioaugmented bacteria can alter the filter's microbiome, affecting its performance either positively or negatively, depending on the bacteria used and their interaction with native microbes. We demonstrate that adding specific bacteria strains can effectively remove recalcitrant pesticides, like metaldehyde, yielding compliance to regulatory standards for an extended period. Our experiments revealed that the Sphingobium CMET-H strain was particularly effective, consistently reducing metaldehyde concentrations to levels within regulatory compliance, significantly outperforming Acinetobacter calcoaceticus E1. This success is attributed to the superior acclimation and distribution of the Sphingobium strain within the filter bed, facilitating more efficient interactions with and degradation of the pesticide, even when present at lower population densities compared to Acinetobacter calcoaceticus E1. Furthermore, our study demonstrates that the addition of pesticide-degrading strains significantly impacts the filter's microbiome at various depths, despite these strains making up less than 1% of the total microbial community. The sequence in which these bacteria are introduced influences the system's ability to degrade pesticides effectively. This research shows the potential of carefully selected and dosed bioaugmented bacteria to improve the pesticide removal capabilities of water filtration systems, while also highlighting the dynamics between bioaugmented and native microbial communities. Further investigation into optimizing bioaugmentation strategies is suggested to enhance the resilience and efficiency of drinking water treatment systems against pesticide contamination.

A modelling approach to explore the optimum bubble size for micro-nanobubble aeration.

Bubble aeration has been widely applied in water/wastewater treatment, however its low gas utilization rate results in high energy consumption. Application of micro-nanobubbles (MNB) has emerged as a process with the potential to significantly increase gas utilisation due to their high relative surface area and high gas-liquid mass transfer efficiency. In this study, we demonstrate through calibrated models that MNB of an optimum bubble size can shrink and burst at or below the water surface enabling (1) all encapsulated gas to thoroughly dissolve in water, and (2) the bursting of nanobubbles to potentially generate free radicals. Through the understanding of MNB dimensional characteristics and bubble behaviour in water, a dynamic model that integrated force balance (i.e. buoyancy force, gravity, drag force, Basset force and virtual mass force), and mass transfer was developed to describe the rising velocity and radius variation of MNB along its upward trajectory. Unlike for conventional millimetre-sized bubbles, intensive gas dissolution of MNBs led to radius reduction for small bubbles, while a large initial radius triggers bubble swelling. The initial water depth was also crucial, where greater depth could drive the potential for bubble shrinkage so that they were more liable to contract. For example, the optimum bubble size of air (42-194 µm) and oxygen (127-470 µm) MNB that could achieve complete gas transfer (100% gas utilisation) for a range of specific water depths (0.5-10 m) were calculated. The modelling results for microbubbles (10-530 µm) were well validated by the experimental data (R2>0.85). However, the validation of the modelling results for nanobubble (<1 µm) aeration requires further study due to a lack of available empirical data. In this study, the proposed model and analysis provided new insights into understanding bubble dynamics in water and offered fundamental guidance for practitioners looking to upgrade bubble aeration system.

Tumor-activated lymph node fibroblasts suppress T cell function in diffuse large B cell lymphoma.

Recent transcriptomic-based analysis of diffuse large B cell lymphoma (DLBCL) has highlighted the clinical relevance of LN fibroblast and tumor-infiltrating lymphocyte (TIL) signatures within the tumor microenvironment (TME). However, the immunomodulatory role of fibroblasts in lymphoma remains unclear. Here, by studying human and mouse DLBCL-LNs, we identified the presence of an aberrantly remodeled fibroblastic reticular cell (FRC) network expressing elevated fibroblast-activated protein (FAP). RNA-Seq analyses revealed that exposure to DLBCL reprogrammed key immunoregulatory pathways in FRCs, including a switch from homeostatic to inflammatory chemokine expression and elevated antigen-presentation molecules. Functional assays showed that DLBCL-activated FRCs (DLBCL-FRCs) hindered optimal TIL and chimeric antigen receptor (CAR) T cell migration. Moreover, DLBCL-FRCs inhibited CD8+ TIL cytotoxicity in an antigen-specific manner. Notably, the interrogation of patient LNs with imaging mass cytometry identified distinct environments differing in their CD8+ TIL-FRC composition and spatial organization that associated with survival outcomes. We further demonstrated the potential to target inhibitory FRCs to rejuvenate interacting TILs. Cotreating organotypic cultures with FAP-targeted immunostimulatory drugs and a bispecific antibody (glofitamab) augmented antilymphoma TIL cytotoxicity. Our study reveals an immunosuppressive role of FRCs in DLBCL, with implications for immune evasion, disease pathogenesis, and optimizing immunotherapy for patients.

Brauer and partition diagram models for phylogenetic trees and forests.

We introduce a correspondence between phylogenetic trees and Brauer diagrams, inspired by links between binary trees and matchings described by Diaconis and Holmes (1998 Proc. Natl Acad. Sci. USA 95, 14 600-14 602. (doi:10.1073/pnas.95.25.14600)). This correspondence gives rise to a range of semigroup structures on the set of phylogenetic trees, and opens the prospect of many applications. We furthermore extend the Diaconis-Holmes correspondence from binary trees to non-binary trees and to forests, showing for instance that the set of all forests is in bijection with the set of partitions of finite sets.

Application of activated carbon fabric for the removal of a recalcitrant pesticide from agricultural run-off.

Removal of pesticides from agricultural run-off close to the point of application has the potential to prevent or reduce the pollution of water sources used for drinking. This research considered the novel application of activated carbon (AC) fabric as a sorbent material for removal of pesticides from field run-off. AC fabric was tested for the removal of the molluscicide pesticide metaldehyde under a range of flow rates at both laboratory and pilot scale. Metaldehyde at an initial concentration of 10 µg/L was removed effectively from deionised (DI) water and real source water by the AC cloth under all conditions tested, reaching removal of 1375 and 876 µg/g (equivalent to 169 and 264 mg/m2), respectively. The adsorption followed pseudo-second order kinetics (k2 of 29.9 and 34.8 g/µg min for the AC fabric and GAC), providing rapid removal of metaldehyde within the first 5 min of contact. In single pass and flow through conditions, stabilised removal of 46% metaldehyde was achieved by the AC fabric bundle for treatment of 700 L of real water in a pilot scale flume. This equated to removal of 454 µg/m2, although significantly more removal would be expected over longer duration testing given the stabilised removal and the equilibrium capacity of the fabric seen during the batch isotherm testing. The work provides evidence to show that AC fabric could be used in the catchment to reduce peak loads of pesticides in sources used for drinking water.

Exploring the use of flow cytometry for understanding the efficacy of disinfection in chlorine contact tanks.

A pilot scale chlorine contact tank (CCT) with flexible baffling was installed at an operational water treatment plant (WTP), taking a direct feed from the outlet of the rapid gravity filters (RGF). For the first time, disinfection efficacy was established by direct microbial monitoring in a continuous reactor using flow cytometry (FCM). Disinfection variables of dose, time, and hydraulic efficiency (short circuiting and dispersion) were explored following characterisation of the reactor's residence time distributions (RTD) by tracer testing. FCM enabled distinction to be made between changes in disinfection reactor design where standard culture-based methods could not. The product of chlorine concentration (C) and residence time (t) correlated well with inactivation of microbes, organisms, with the highest cell reductions (N/N0) reaching <0.025 at Ctx¯ of 20 mg.min/L and above. The influence of reactor geometry on disinfection was best shown from the Ct10. This identified that the initial level of microbial inactivation was higher in unbaffled reactors for low Ct10 values, although the highest levels of inactivation of 0.015 could only be achieved in the baffled reactors, because these conditions enabled the highest Ct10 values to be achieved. Increased levels of disinfection were closely associated with increased formation of the trihalomethane disinfection by-products. The results highlight the importance of well-designed and operated CCT. The improved resolution afforded by FCM provides a tool that can dynamically quantify disinfection processes, enabling options for much better process control.

Impact of resin loading on ion exchange equilibrium for removal of organic matter and inorganic ions.

Ion Exchange (IEX) applications for drinking water can be limited due to high volumes of brine, brine waste and treated water corrosivity. Reusing the resin by operating at reduced regeneration frequency can overcome this. However, assessing changes on the resin loading over reuse cycles is complex because multiple presaturant ions participate in the exchange and existing models only account for the exchange with one presaturant ion. This study developed a theoretical multicomponent model for the determination of IEX equilibria when the resin loading increases due to reuse. The model suggested that both electrostatic interactions and admicelle formation were the separation mechanisms. The model revealed that under reduced regeneration frequencies, brine use and waste generation can be reduced by more than 90%, where the bicarbonate-form resin offered the potential for lower corrosivity. However, changes in resin loading after 5 reuse cycles showed that the risk of corrosion increased. For the tested source water, reusing the bicarbonate-form resin every 5 cycles would achieve the most sustainable option with 41% NOM removal and 79% brine and waste reduction. Under these conditions, almost 100% of exchange capacity is recovered after regeneration.

SU(2/1) superchiral self-duality: a new quantum, algebraic and geometric paradigm to describe the electroweak interactions.

We propose an extension of the Yang-Mills paradigm from Lie algebras to internal chiral superalgebras. We replace the Lie algebra-valued connection one-form A, by a superalgebra-valued polyform A ˜ mixing exterior-forms of all degrees and satisfying the chiral self-duality condition A ˜ = * A ˜ χ , where χ denotes the superalgebra grading operator. This superconnection contains Yang-Mills vectors valued in the even Lie subalgebra, together with scalars and self-dual tensors valued in the odd module, all coupling only to the charge parity CP-positive Fermions. The Fermion quantum loops then induce the usual Yang-Mills-scalar Lagrangian, the self-dual Avdeev-Chizhov propagator of the tensors, plus a new vector-scalar-tensor vertex and several quartic terms which match the geometric definition of the supercurvature. Applied to the SU(2/1) Lie-Kac simple superalgebra, which naturally classifies all the elementary particles, the resulting quantum field theory is anomaly-free and the interactions are governed by the super-Killing metric and by the structure constants of the superalgebra.

Radium-223 therapy for metastatic castration-resistant prostate cancer: survival benefit when used earlier in the treatment pathway.

BACKGROUND: Radium-223 dichloride (Ra-223) therapy improves overall survival in bony metastatic castration-resistant prostate cancer (mCRPC) patients. Recent guidance change recommends Ra-223 following at least two prior therapies for mCRPC. We evaluated how this change affects overall survival and the optimal timing of Ra-223 in the mCRPC treatment pathway. METHODS: Retrospective analysis of all mCRPC patients receiving Ra-223 therapy at a single UK centre over a 70-month period. Overall survival, number of prior lines of therapy commenced before Ra-223 initiation and number of Ra-223 therapy cycles completed were identified. RESULTS: One hundred ninety-one mCRPC patients received Ra-223 therapy during the study period. One hundred twenty-one (63%) received one prior therapy (group 1) and 70 (37%) received two prior therapies (group 2). Median survival in group 1 was significantly improved, compared to group 2 (448 days vs. 341 days (P = 0.03). Subgroup analysis of 111/191 (58%) patients that completed the recommended six Ra-223 therapy cycles showed additional improved survival. Median survival in group 1 was incrementally significantly improved, compared to group 2 within these patients (665 days vs. 552 days; P = 0.05). There was no difference in the number of patients completing the recommenced six cycles of therapy between the groups [72/121 (59%) vs. 39/70 (56%); P = 0.61]. CONCLUSION: We found a significant survival benefit when Ra-223 was used earlier in the mCRPC treatment pathway, with additional survival advantage seen in those patients completing all six Ra-223 cycles. Our results support the use of Ra-223 earlier in the treatment pathway.