bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.03.17.643612

Anaerobic co-digestion of sewage sludge and food waste: staging and carriers enhance system performance and process stability

Ali, M.·Pena, C. B.·De Vrieze, J.
View original source ↗Export metadata ↓

Abstract

Sewage sludge generated during biological wastewater treatment requires adequate treatment. Anaerobic digestion of sewage sludge is preferred, yet, it is often characterized by low biogas production rates. Co-digestion of sewage sludge with food waste could improve the hydrolysis rate and nutrients balance, resulting in higher biogas production rates. In this study, single- and two-stage anaerobic reactors were operated, with and without carriers in semi-continuous mode for 205 days for assessing the expected improved biogas production rates of sewage sludge and food waste co-digestion. Mono-digestion of sewage sludge resulted in average biogas production rates of 230{+/-}31 and 538{+/-}40 mLbiogas L-1 d-1 for single- and two-stage systems with carriers, respectively. Co-digestion of sewage sludge with food waste resulted in an improved biogas production rates in both systems. Average biogas production rates of 868{+/-}114 and 1507{+/-}174 mLbiogas L-1 d-1 were measured in single- and two-stage systems, respectively, with carriers during co-digestion of food waste (30%) and sewage sludge (70%). In all cases, the addition of carriers improved biogas production, and reduced volatile fatty acid accumulation. In conclusion, two-stage co-digestion of sewage sludge and food waste with carriers achieved the highest biogas production and long-term stability.

Source connections

Explore related subjects

bioengineeringPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ali, M., Pena, C. B., De Vrieze, J.. 2025-03-17. Anaerobic co-digestion of sewage sludge and food waste: staging and carriers enhance system performance and process stability. https://doi.org/10.1101/2025.03.17.643612

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

SpiraMed: A Stereotactic Helix-based Therapy Delivery system for the Human Brain

Stereotactic needle-based delivery remains the standard for local administration of Advanced Therapy Medicinal Products (ATMPs) to the human brain. ATMP administration typically involves multiple trajectories, presenting cumulative risks and prolonging surgery. Reflux-prone, patchy therapy coverage compromises clinical results. We demonstrate a novel approach, deploying a helical delivery catheter via a single access trajectory per target, referred to as SpiraMed. Helix retraction is synchronised with therapy delivery, enabling comprehensive target coverage in seconds. Helix pitch and diameter can be precisely tailored to patient-specific target volume and vascular anatomy, as part of the preoperative stereotactic surgical planning process. Testing in agarose phantoms, live sheep and cadaveric human brain confirms enhanced therapy delivery volume, delivery speed and target coverage, with reductions in reflux and predicted risk of bleeding complication. SpiraMed represents a new paradigm, promising to help deliver on the transformative potential of cell and gene therapies across the spectrum of human CNS disease.

bioengineering↗
bioRxiv2026

AtomWeaver: Multi-Component Flow Matching with a Structured Geometric Prior Facilitates Non-Canonical Peptide Design

Fixed-backbone sequence discovery, or inverse folding, is a critical recurring task in the development of new polypeptide therapeutics. Once promising backbones are established for a target pocket, computational inverse folding methods greatly help accelerate generation of candidate sequences. Such methods are mature for the traditional case of limiting to the fixed twenty-letter canonical vocabulary; however, they cannot access the broader space of non-canonical amino acids (NCAAs). This design constraint is exacerbated for peptide binders, a fast-growing modality that readily incorporates NCAAs, though in practice non-canonical design frequently depends on laborious medicinal-chemistry campaigns. An extension of inverse folding to NCAAs is thus critical to accelerating design of novel therapeutic peptides. AtomWeaver uses a joint all-site, atom-level generative scheme that does not restrict side-chain categorical assignment by either predetermined or co-resolving residue identity. Conditioned only on a fixed peptide backbone and its target protein, its multi-component flow guides side-chain atoms as unlabeled points in R3 from a nested shell prior to a variable-count final atom cloud. Identity is then read by matching each predicted cloud against a reference library of canonical and non-canonical templates. Since identity is decided only at decode time, the addressable vocabulary is a property of the library rather than of the trained weights: a new NCAA costs one reference structure and no retraining, and the model can select residues it was never prompted for and never saw in training. On a deep mutational scan of two peptide-target systems, AtomWeaver's canonical readout shows high observed mean agreement with experimental values among the compared inverse-folding methods. In the mixed canonical-noncanonical setting that canonical-only baselines cannot support at all, it likewise retains ranking signal across both systems. AtomWeaver also displayed self-consistent designs on de novo binder backbones, with the highest interface confidence among compared methods. Notably, it reached these metrics while achieving broad empirical coverage of our 300-residue vocabulary, including four non-canonical types never visible in training. AtomWeaver thus serves canonical and non-canonical peptide design alike, while transforming residue vocabulary to an expandable inference-time choice.

bioengineering↗
bioRxiv2026

The Influence of Obesity and Body Shape on Sagittal Plane Knee Kinematics and Kinetics during Obstacle Crossing

Altered walking mechanics in individuals with obesity can contribute to knee osteoarthritis. The gait deviations may become more pronounced during obstacle crossing. In women, body fat distribution may further influence knee load, especially when excess fat accumulates in the thighs and hips. However, relatively little is known about how regional fat distribution affects gait in women with obesity. This study investigated how obesity and, among women, different fat distributions (Apple: more abdominal fat; Pear: more lower-limb fat) influence knee biomechanics during walking with and without obstacle crossing. Participants were 15 controls without obesity (NB) and 27 with obesity (OB). Within female participants, 10 without obesity (fNB) were compared with 20 with obesity, stratified by waist-hip ratio (Apple:10, Pear:10). Speed-adjusted statistical parametric mapping applied a general linear model (NB vs. OB) and an analysis of covariance (fNB vs. Apple vs. Pear). OB exhibited a significantly greater late-stance knee extension moment than NB across all tasks, and this difference persisted among fNB, Apple, and Pear in obstacle tasks (p<0.05). OB walked with reduced knee flexion during the early-stance leading limb after crossing a medium-height obstacle (p=0.048) and a high-height obstacle (p=0.008) compared to NB. There were significant body-shape effects (p<0.05), and post-hoc comparisons confirmed that Pear had lower knee angles than fNB in both leading-limb conditions after crossing medium- and high-height obstacles (p=0.008 and p=0.001, respectively). These findings suggest that obstacle crossing helps illuminate how excess weight influences knee biomechanics, and how regional fat distribution modulates the degree of this alteration.

bioengineering↗