Controlling glass forming kinetics in 2D perovskites using organic cation isomers.

The recent discovery of glass-forming metal halide perovskites (MHPs) provides opportunities to broaden the application domain beyond traditionally celebrated optoelectronic research fueled by associated crystalline counterparts. In this regard, it is crucial to diversify the compositional space of glass-forming MHPs and introduce varied crystallization kinetics via synthetic structural engineering. Here, we compare two MHPs with slightly varying structural attributes, utilizing isomer organic cations with the same elemental composition, and demonstrate how this change in functional group position impacts the kinetics of glass formation and subsequent crystallization by multiple orders of magnitude. (S)-(-)-1-(1-Naphthyl)ethylammonium lead bromide (S(1-1)NPB) exhibits a lower melting point (Tm) of 175 °C and the melt readily vitrifies under a critical cooling rate (CCR) of 0.3 °C s-1. In contrast, (S)-(-)-1-(2-naphthyl)ethylammonium lead bromide (S(1-2)NPB) displays a Tm ∼193 °C and requires a CCR of 2500 °C s-1, necessitating the use of ultrafast calorimetry for glass formation and study of the underlying kinetics. The distinct Tm and glass-formation kinetics of the isomer MHPs are further understood through a combination of calorimetric and single-crystal X-ray diffraction studies on their crystalline counterparts, highlighting the influence of altered organic-inorganic hydrogen bonding interactions and entropic changes around melting, providing insights into the factors driving their divergent behaviors.

Activator of KAT3 histone acetyltransferase family ameliorates a neurodevelopmental disorder phenotype in the syntaxin 1A ablated mouse model.

Syntaxin-1A (stx1a) repression causes a neurodevelopmental disorder phenotype, low latent inhibition (LI) behavior, by disrupting 5-hydroxytryptaminergic (5-HTergic) systems. Herein, we discovered that lysine acetyltransferase (KAT) 3B increases stx1a neuronal transcription and TTK21, a KAT3 activator, induces stx1a transcription and 5-HT release in vitro. Furthermore, glucose-derived CSP-TTK21 could restore decreased stx1a expression, 5-HTergic systems in the brain, and low LI in stx1a (+/-) mice by crossing the blood-brain barrier, whereas the KAT3 inhibitor suppresses stx1a expression, 5-HTergic systems, and LI behaviors in wild-type mice. Finally, in wild-type and stx1a (-/-) mice treated with IKK inhibitors and CSP-TTK21, respectively, we show that KAT3 activator-induced LI improvement is a direct consequence of KAT3B-stx1a pathway, not a side effect. In conclusion, KAT3B can positively regulate stx1a transcription in neurons, and increasing neuronal stx1a expression and 5-HTergic systems by a KAT3 activator consequently improves the low LI behavior in the stx1a ablation mouse model.

Gallic Acid Derived 1, 2-Diarylindole as a Potential Antifungal Agent against Candida Strain.

BACKGROUND: In recent decades, Candida albicans has become a serious issue for public health. The worldwide rapid rise in drug resistance to conventional therapies is the main contributing reason. Moreover, because of their potent activity at low concentrations and apparent lack of toxicity, compounds originating from plants are used in therapeutic treatments because of their potent activity at low concentrations and apparent lack of toxicity. Particularly in immunocompromised people, Candida species can result in a wide range of ailments. OBJECTIVES: Present manuscript describes antifungal activity of an indole derivative 1-(4-((5- methoxy-2-(3,4,5-trimethoxyphenyl)-1H-indol-1-yl) methyl) phenoxy)-N,N-dimethylethan-1- amine (7, 100DL-6) by using an in-silico and in-vitro anti-candidal activity against two Candida strains; Candida kefyr-DS-02 (ATCC-204093) and Candida albicans (AI-clinical isolate, AIIMS- Delhi). METHODS: The synthetic strategy for the preparation of indole derivatives was modified through Fischer indole reaction. Antifungal activity of an indole derivative 1-(4-((5-methoxy-2-(3,4,5- trimethoxyphenyl)-1H-indol-1-yl) methyl) phenoxy)-N,N-dimethylethan-1-amine (7, 100DL-6) was done by using an in-silico and in-vitro anti-candidal activity against two Candida strains; Candida kefyr-DS-02 (ATCC-204093) and Candida albicans (AI-clinical isolate, AIIMS-Delhi). Compound 100DL-6 efficacy was determined by Combination synergy study, ergosterol binding assay, MTT toxicity study and Mutagenicity. RESULTS: Compound 100DL-6 was obtained in 65% yield on desired motifs. Docking scores found were 100DL-6 (-8.7 kcal/mol) and Fluconazole (-7.6 kcal/mol). Further, RMSD were shown for 100DL6 (0.26 ± 0.23 nm) and fluconazole (1.2 ± 0.62 nm). Indole derivative 100DL-6 was active against the tested fungal pathogens and the total zone of inhibition was measured between 13-14 mm in diameter and MIC values between 31.25 µg/mL to 250 µg/mL and MFC values between 62.5 µg/mL to 500 µg/mL. In checkerboard assay synergistic mode of interaction of 100DL-6 with known antifungal drugs was observed. In the presence of ergosterol 100DL-6 and standard drug (s) increased their MIC values, demonstrating a considerable affinity for ergosterol. Compound 100DL-6 was considered to be less-cytotoxic to the cells as determined by MTT assay. Lead compound 100DL-6 was found to be non-mutagenic. CONCLUSION: In the present study, 100DL6 (indole derivatives) significantly abrupted the ergosterol biosynthetic pathway and showed moderate anti-candidal effects. These studies suggest that 100DL6 significantly enhances antifungal effect of clinical drug fluconazole synergistically and may be considered as in clinical trial prior to some extensive in-vivo validations.

Obstacles to Early Diagnosis of Acute Hepatic Porphyria: Current Perspectives on Improving Early Diagnosis and Clinical Management.

Porphyrias are, for the most part, inherited disorders of the heme biosynthetic pathway which lead to accumulation of specific intermediates responsible for most of the symptoms and signs of biochemically active disease. Acute hepatic porphyrias usually come to clinical attention primarily in women in their reproductive years who present with episodic, severe, generalized abdominal pain. Such acute attacks may also be associated with tachycardia, systemic arterial hypertension, hyponatremia, recent history of dark reddish to brownish urine, and anxiety, delirium, and sensory or motor neuropathies. Diagnosing AHPs is often challenging, requiring a high index of suspicion and the appropriate testing showing elevated ALA and/or PBG in a random urine specimen. Obstacles to diagnosis include inappropriate testing for porphyrins only, inadequate sample handling, and ordering genetic testing as the initial diagnostic test. While some of these pitfalls in diagnosis are surmountable with current knowledge, others are in need of more research.

When online citizen science meets teaching: Storyfication of a science discovery game to teach, learn, and contribute to genomic research.

In the last decade, video games became a common vehicle for citizen science initiatives in life science, allowing participants to contribute to real scientific data analysis while learning about it. Since 2010, our scientific discovery game (SDG) Phylo enlists participants in comparative genomic data analysis. It is frequently used as a learning tool, but the activities were difficult to aggregate to build a coherent teaching activity. Here, we describe a strategy and series of recipes to facilitate the integration of SDGs in courses and implement this approach in Phylo. We developed new roles and functionalities enabling instructors to create assignments and monitor the progress of students. A story mode progressively introduces comparative genomics concepts, allowing users to learn and contribute to the analysis of real genomic sequences. Preliminary results from a user study suggest this framework may help to boost user motivation and clarify pedagogical objectives.

scTopoGAN: unsupervised manifold alignment of single-cell data.

Motivation: Single-cell technologies allow deep characterization of different molecular aspects of cells. Integrating these modalities provides a comprehensive view of cellular identity. Current integration methods rely on overlapping features or cells to link datasets measuring different modalities, limiting their application to experiments where different molecular layers are profiled in different subsets of cells. Results: We present scTopoGAN, a method for unsupervised manifold alignment of single-cell datasets with non-overlapping cells or features. We use topological autoencoders (topoAE) to obtain latent representations of each modality separately. A topology-guided Generative Adversarial Network then aligns these latent representations into a common space. We show that scTopoGAN outperforms state-of-the-art manifold alignment methods in complete unsupervised settings. Interestingly, the topoAE for individual modalities also showed better performance in preserving the original structure of the data in the low-dimensional representations when compared to other manifold projection methods. Taken together, we show that the concept of topology preservation might be a powerful tool to align multiple single modality datasets, unleashing the potential of multi-omic interpretations of cells. Availability and implementation: Implementation available on GitHub (https://github.com/AkashCiel/scTopoGAN). All datasets used in this study are publicly available.

Meltable Hybrid Antimony and Bismuth Iodide One-Dimensional Perovskites.

Hybrid lead-halide perovskites have been studied extensively for their promising optoelectronic properties and prospective applications, including photovoltaics, solid-state lighting, and radiation detection. Research into these materials has also been aided by the simple and low-temperature synthetic conditions involved in solution-state deposition/crystallization or melt-processing techniques. However, concern over lead toxicity has plagued the field since its infancy. One of the most promising routes to mitigating toxicity in hybrid perovskite materials is substituting isoelectronic Bi(III) for Pb(II). Various methods have been developed to allow pnictide-based systems to capture properties of the Pb(II) analogues, but the ability to melt extended hybrid pnictide-halide materials has not been investigated. In this work, we prepare a series of one-dimensional antimony- and bismuth-iodide hybrid materials employing tetramethylpiperazinium (TMPZ)-related cations. We observe, for the first time, the ability to melt extended hybrid pnictide-halide materials for both the Sb(III) and Bi(III) systems. Additionally, we find that Sb(III) analogues melt at lower temperatures and attribute this observation to structural changes induced by the increased stereochemical activity of the Sb(III) lone pair coupled with the reduction in effective dimensionality due to steric interactions with the organic cations. Finally, we demonstrate the ability to melt process phase pure thin films of (S-MeTMPZ)SbI5.

Computational screening and MM/GBSA-based MD simulation studies reveal the high binding potential of FDA-approved drugs against Cutibacterium acnes sialidase.

Cutibacterium acnes is an opportunistic pathogen linked with acne vulgaris, affecting 80-90% of teenagers globally. On the leukocyte (WBCs) cell surface, the cell wall anchored sialidase in C. acnes virulence factor, catalysing the sialoconjugates into sialic acids and nutrients for C. acnes resulting in human skin inflammation. The clinical use of antibiotics for acne treatments has severe adverse effects, including microbial dysbiosis and resistance. Therefore, identifying inhibitors for primary virulence factors (Sialidase) was done using molecular docking of 1030 FDA-approved drugs. Initially, based on binding energies (ΔG), Naloxone (ZINC000000389747), Fenoldopam (ZINC000022116608), Labetalol (ZINC000000403010) and Thalitone (ZINC000000057255) were identified that showed high binding energies as -10.2, -10.1, -9.9 and -9.8 kcal/mol, respectively. In 2D analysis, these drugs also showed considerable structural conformer of hydrogen and hydrophobic interactions. Further, a 100 ns MD simulation study found the lowest deviation and fluctuations with various intermolecular interactions to stabilise the complexes. Out of 4, the Naloxone molecule showed robust, steady, and stable RMSD 0.23 ± 0.18 nm. Further, MMGBSA analysis supports MD results and found strong binding energy (ΔG) -29.71 ± 4.97 kcal/mol. In Comparative studies with Neu5Ac2en (native substrate) revealed naloxone has a higher affinity for sialidase. The PCA analysis showed that Naloxone and Thalitone were actively located on the active site, and other compounds were flickered. Our extensive computational and statistical report demonstrates that these FDA drugs can be validated as potential sialidase inhibitors.Communicated by Ramaswamy H. Sarma.

Study of Glass Formation and Crystallization Kinetics in a 2D Metal Halide Perovskite Using Ultrafast Calorimetry.

While crystalline 2D metal halide perovskites (MHPs) represent a well-celebrated semiconductor class, supporting applications in the fields of photovoltaics, emitters, and sensors, the recent discovery of glass formation in an MHP opens many new opportunities associated with reversible glass-crystalline switching, with each state offering distinct optoelectronic properties. However, the previously reported [S-(-)-1-(1-naphthyl)ethylammonium]2PbBr4 perovskite is a strong glass former with sluggish glass-crystal transformation time scales, pointing to a need for glassy MHPs with a broader range of compositions and crystallization kinetics. Herein we report glass formation for low-melting-temperature 1-MeHa2PbI4 (1-MeHa = 1-methyl-hexylammonium) using ultrafast calorimetry, thereby extending the range of MHP glass formation across a broader range of organic (fused ring to branched aliphatic) and halide (bromide to iodide) compositions. The importance of a slight loss of organic and hydrogen iodide components from the MHP in stabilizing the glassy state is elucidated. Furthermore, the underlying kinetics of glass-crystal transformation, including activation energies, crystal growth rate, Angell plot, and fragility index, is studied using a combination of kinetic, thermodynamic, and rheological modeling techniques. An inferred fast crystal growth rate of 0.21 m/s for 1-MeHa2PbI4 shows promise toward suitability in extended application spaces, for example, in metamaterials, nonvolatile memory, and optical and neuromorphic computing devices.

Empty stomach together with menstrual bleeding as predictors of committed suicides among women of reproductive age: What a primary physician must know.

Background: Women of reproductive age group (WoRAG) are among the most vulnerable groups to suicide in India. The present study intended to develop a mathematical model to differentiate suicides from homicides among WoRAG. Methods: It was a cross-sectional study based on a record review of autopsy at Patna, India, from 2016 to 2021. The cause of deaths was ascertained by autopsies and other records independently by two investigators to reduce the interobserver bias. Independent variables were tested with confirmed suicides to calculate statistically significant association. These variables were further used for developing prediction models for the suicides by multivariate logistic regression analysis. Results: Out of total of 520 autopsies of WoRAG performed by investigators, the cause of death has been confirmed for 62. Of them, 30 were confirmed as suicides. In univariate analysis, suicides were associated with the menstrual bleed (OR 35 CI 6.9,179), gastric emptying (OR 3.9 CI 1.2,12.8), hanging, poisoning, and drowning as mode of death (OR 435 CI 37.4,5061.9). By logistic regression, three prediction models were built to predict suicide; Model I: gastric emptying, Model II: menstrual bleed, and Model III: including both. The area under the curve (AUC) for Models I, II, and III was 0.67 (95%CI 0.34,0.99), 0.92 (95%CI 0.75,1.00), and 0.94 (95%CI 0.82,1.00), respectively. The AUC of Model III differs significantly from that of Model I (P value 0.03) but not with Model II (P value 0.11). Conclusion: Menstrual bleed, gastric emptying, and mode of death may be used as a supplement tool in ascertaining the cause of death among WoRAG in medical and legal proceedings.

Does the Severity of Foraminal Stenosis Impact Outcomes of Lumbar Decompression Surgery?

OBJECTIVE: To establish the relationship between the magnitude of foraminal stenosis and 1) improvement in patient-reported outcomes, 2) improvement in motor function after lumbar decompression surgery, and 3) difference in surgical outcomes. METHODS: Patients who underwent one-level posterior lumbar decompression for radiculopathy were retrospectively identified. Patient demographics and surgical characteristics were collected through a query search and manual chart review of the electronic medical records. Foraminal stenosis was determined on magnetic resonance imaging and graded using Lee et al.'s validated methodology as none, mild, moderate, or severe. Surgical outcomes, motor function, and patient-reported outcome measures (PROMs) were compared based on the amount of stenosis (mild vs. moderate vs. severe). Bivariant and multivariant analyses were performed. RESULTS: Severe stenosis demonstrated more 90-day readmissions (0.00% vs. 0.00% vs. 8.57%, respectively, P = 0.019), though this effect did not remain significant on multivariate analysis (P = 0.068). There was no association between stenosis severity and the degree of functional impairment or PROMs preoperatively. Patients with moderate or severe preoperative foraminal stenosis showed improvement in all PROMs after surgery (P < 0.05) except the mental component of the Short Form 12 survey. Notably, central stenosis grade was insignificantly different between groups (P = 0.358). Multivariable logistic regression analysis did not identify any significant independent predictors of surgical outcomes or changes in PROMs. CONCLUSIONS: We demonstrated that regardless of foraminal stenosis severity preoperatively, patients have a similar improvement in PROMs, surgical outcomes, and restoration of motor function after lumbar decompression surgery for radiculopathy.

Recent trends and advances in type 1 diabetes therapeutics: A comprehensive review.

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by the destruction of pancreatic ß-cells, leading to insulin deficiency. Insulin replacement therapy is the current standard of care for T1D, but it has significant limitations. However, stem cell-based replacement therapy has the potential to restore ß-cell function and achieve glycaemic control eradicating the necessity for drugs or injecting insulin externally. While significant progress has been made in preclinical studies, the clinical translation of stem cell therapy for T1D is still in its early stages. In continuation, further research is essentially required to determine the safety and efficacy of stem cell therapies and to develop strategies to prevent immune rejection of stem cell-derived ß-cells. The current review highlights the current state of cellular therapies for T1D including, different types of stem cell therapies, gene therapy, immunotherapy, artificial pancreas, and cell encapsulation being investigated, and their potential for clinical translation.

Green solvents, materials, and lead-free semiconductors for sustainable fabrication of perovskite solar cells.

Perovskite materials research has received unprecedented recognition due to its applications in photovoltaics, LEDs, and other large area low-cost electronics. The exceptional improvement in the photovoltaic conversion efficiency of Perovskite solar cells (PSCs) achieved over the last decade has prompted efforts to develop and optimize device fabrication technologies for the industrial and commercial space. However, unstable operation in outdoor environments and toxicity of the employed materials and solvents have hindered this proposition. While their optoelectronic properties are extensively studied, the environmental impacts of the materials and manufacturing methods require further attention. This review summarizes and discusses green and environment-friendly methods for fabricating PSCs, particularly non-toxic solvents, and lead-free alternatives. Greener solvent choices are surveyed for all the solar cell films, (i.e. electron and hole transport, semiconductor, and electrode layers) and their impact on thin film quality, morphology and device performance is explored. We also discuss lead content in perovskites, its environmental impact and sequestration routes, and progress in replacing lead with greener alternatives. This review provides an analysis of sustainable green routes in perovskite solar cell fabrication, discussing the impact of each layer in the device stack, via life cycle analysis.

A two-dimensional lead-free hybrid perovskite semiconductor with reduced melting temperature.

1-Methylhexylammonium tin iodide yields the lowest reported melting temperature (Tm = 142 °C) to date among lead-free hybrid perovskite semiconductors. Molecular branching near the organic ammonium group coupled with tuning of metal/halogen character suppresses Tm and facilitates effective melt-based deposition of films with 568 nm absorption onset.

The Implication of Preoperative Central Stenosis on Patient-Reported Outcomes After Lumbar Decompression Surgery.

OBJECTIVE: To assess the impact of central stenosis severity on patient-reported outcomes after lumbar decompression. METHODS: Patient diagnosis, demographics, and surgical characteristics were collected via query search and manual chart review of electronic medical records. The inclusion criteria were posterior lumbar decompressions from 2014-2020, with accessible magnetic resonance imaging reports. As previously validated by Lee et al., central stenosis was determined on magnetic resonance imaging and graded as none, mild, moderate, or severe. Patients were dichotomized into 2 groups to improve statistical power for comparisons: none or mild central stenosis and moderate or severe central stenosis. Patient-reported outcome measures (PROMs) were compared between cohorts at 1 year postoperatively. Statistical significance was set at P < 0.05. RESULTS: On bivariate analysis, no significant differences were noted between cohorts with regard to preoperative, 1-year postoperative, and delta PROMs. In addition, no significant difference in the number of patients attaining minimal clinically important difference (MCID) for each PROM was noted between cohorts. With the exception of mental score of the Short Form-12 survey, all intragroup preoperative to postoperative PROMs indicated significant improvement (all P < 0.05) after lumbar decompression surgery. Multivariate regression identified moderate or severe central canal stenosis as a significant independent predictor of improvement in visual analog scale back (estimate = -1.464, P = 0.045). CONCLUSIONS: We demonstrate that patients with moderate or severe central spinal stenosis may have more improvement in back pain than those with mild or no central stenosis after lumbar spine decompression surgery.

Combination of terlipressin and noradrenaline versus terlipressin in hepatorenal syndrome with early non-response to terlipressin infusion: A randomized trial.

BACKGROUND: Terlipressin and noradrenaline are effective in the management of hepatorenal syndrome (HRS). There are no reports on the combination of these vasoconstrictors in type-1 HRS. AIM: To evaluate terlipressin with or without noradrenaline in type-1 HRS not responding to terlipressin at 48 hours. METHODS: Sixty patients were randomized to receive either terlipressin (group A; n = 30) or a combination of terlipressin and noradrenaline infusion (group B; n = 30). In group A, terlipressin infusion was started at 2 mg/day and increased by 1 mg/day (maximum 12 mg/day). In group B, terlipressin was given at a constant dose of 2 mg/day. Noradrenaline infusion was started at 0.5 mg/h at baseline and increased to 3 mg/h in a stepwise manner. The primary outcome was treatment response at 15 days. Secondary outcomes were 30-day survival, cost-benefit analysis and adverse events. RESULTS: There was no significant difference in the response rate between the groups (50% vs. 76.7%, p = 0.06) and 30-day survival was similar (36.7% vs. 53.3%, p = 0.13). Treatment was more expensive in group A (USD 750 vs. 350, p < 0.001). Adverse events were more frequent in group A (36.7% vs. 13.3%, p < 0.05). CONCLUSIONS: The combination of noradrenaline and terlipressin infusion results in a non-significantly higher rate of HRS resolution with significantly fewer adverse effects in HRS patients who do not respond to terlipressin within 48 hours. CLINICALTRIALS: gov (NCT03822091).

Temporal convolutional networks and data rebalancing for clinical length of stay and mortality prediction.

It is critical for hospitals to accurately predict patient length of stay (LOS) and mortality in real-time. We evaluate temporal convolutional networks (TCNs) and data rebalancing methods to predict LOS and mortality. This is a retrospective cohort study utilizing the MIMIC-III database. The MIMIC-Extract pipeline processes 24 hour time-series clinical objective data for 23,944 unique patient records. TCN performance is compared to both baseline and state-of-the-art machine learning models including logistic regression, random forest, gated recurrent unit with decay (GRU-D). Models are evaluated for binary classification tasks (LOS > 3 days, LOS > 7 days, mortality in-hospital, and mortality in-ICU) with and without data rebalancing and analyzed for clinical runtime feasibility. Data is split temporally, and evaluations utilize tenfold cross-validation (stratified splits) followed by simulated prospective hold-out validation. In mortality tasks, TCN outperforms baselines in 6 of 8 metrics (area under receiver operating characteristic, area under precision-recall curve (AUPRC), and F-1 measure for in-hospital mortality; AUPRC, accuracy, and F-1 for in-ICU mortality). In LOS tasks, TCN performs competitively to the GRU-D (best in 6 of 8) and the random forest model (best in 2 of 8). Rebalancing improves predictive power across multiple methods and outcome ratios. The TCN offers strong performance in mortality classification and offers improved computational efficiency on GPU-enabled systems over popular RNN architectures. Dataset rebalancing can improve model predictive power in imbalanced learning. We conclude that temporal convolutional networks should be included in model searches for critical care outcome prediction systems.

Efficient catalyst screening using graph neural networks to predict strain effects on adsorption energy.

Small-molecule adsorption energies correlate with energy barriers of catalyzed intermediate reaction steps, determining the dominant microkinetic mechanism. Straining the catalyst can alter adsorption energies and break scaling relationships that inhibit reaction engineering, but identifying desirable strain patterns using density functional theory is intractable because of the high-dimensional search space. We train a graph neural network to predict the adsorption energy response of a catalyst/adsorbate system under a proposed surface strain pattern. The training data are generated by randomly straining and relaxing Cu-based binary alloy catalyst complexes taken from the Open Catalyst Project. The trained model successfully predicts the adsorption energy response for 85% of strains in unseen test data, outperforming ensemble linear baselines. Using ammonia synthesis as an example, we identify Cu-S alloy catalysts as promising candidates for strain engineering. Our approach can locate strain patterns that break adsorption energy scaling relations to improve catalyst performance.

Using plant data to estimate biodegradable COD fractions - case study kwaMashu WWTP.

A modelling study is under way in preparation for a planned upgrade of the capacity of the kwaMashu WWTP in eThekwini, South Africa, from 50 to 80 ML/d. When the configuration of an existing plant is to be changed, the most critical part of the model calibration is the influent wastewater fractionation. However, the constantly varying characteristics of wastewater make experimental determination of an adequately representative set of components difficult, time-consuming and expensive, which constitutes significant barriers to the adoption of modelling by many municipalities. Compliance and process monitoring generate large sets of influent measurements of chemical oxygen demand (COD), free and saline ammonia (FSA), total suspended solids (TSS), etc., but these are insufficient for modelling purposes. In particular, biodegradability is not routinely measured. However, since influent fractionation is designed to predict the fate of material in the wastewater treatment process, it should be possible to infer the fractionation from a combination of influent and plant measurements. This case study demonstrates the application of a pair of modelling tools, a probabilistic influent fractionator and a simplified steady­state plant­wide model, to estimate the influent fractionation, together with certain unmeasured or unreliable operational parameters.