Abstract: Background: Portal venous gas (PVG) is a recognized radiologic finding in necrotizing enterocolitis (NEC), but its value as a prognostic marker and indicator for surgical intervention remains controversial. Methods: This retrospective study analyzed data from infants with Bell stage II/III NEC admitted to “G. Salesi” Children’s Hospital NICU between 2013 and 2023. Patients were grouped by presence or absence of PVG on abdominal X-rays at diagnosis. Results: Among 57 infants, 25 (44%) had PVG. Gestational age and birth weight were comparable between groups. Bell stage III NEC was more frequent in PVG infants (64% vs 34%, P = 0.026). Surgery was performed in 56% of cases, more often in PVG patients (72% vs 44%, P = 0.033), who also had longer bowel resections (P = 0.039). Mortality was higher in the PVG group (32% vs 13%), with a significant difference in non-operated infants (43% vs 6%, P = 0.022). Postoperative short bowel syndrome was more frequent with PVG (22% vs 7%). Multivariate analysis identified Bell stage III NEC, not PVG, as significantly associated with surgery and mortality (P = 0.001). Conclusion: PVG in NEC is associated with more severe disease, higher surgical rates, and extensive intestinal resection.

Abstract: Punjab’s rice transplantation regulation seeks to reduce groundwater demand by moving cultivation closer to monsoon rainfall. This study examines how the hydroclimatic conditions supporting that rationale have changed over time. Using CHIRPS v2.0 rainfall and ERA5-Land temperature data for 2000–2024, we compare rainfall magnitude, interannual rainfall variability, temperature, and Hargreaves reference evapotranspiration between 2000–2008 and 2009–2024 for May–July. The district groupings assigned to Punjab’s three transplantation zones in 2025 provide the spatial units for this retrospective analysis. June conditions changed differently across zones. In Zone 1, mean rainfall declined by 9.55%, rainfall variability increased, and temperature and reference evapotranspiration rose, indicating less favourable conditions within the hydroclimatic alignment framework. In Zones 2 and 3, June rainfall increased by 173.19% and 63.19%, respectively, alongside higher temperature and evaporative demand. Rainfall variability increased in Zone 2 but remained broadly stable in Zone 3, producing mixed patterns of alignment. July accounted for a larger share of May–July rainfall across all three zones. These findings suggest that the environmental basis of transplantation regulation requires spatially differentiated reassessment. They do not establish changes in groundwater extraction or the suitability of individual prescribed dates. Adaptive crop-calendar governance could retain the conservation rationale of regulation while periodically reviewing timing against changing conditions. Its feasibility depends on coordination with labour, electricity, inputs, and procurement, linking cultivation timing to both immediate production needs and longer-term groundwater conservation.

Abstract: Cuproptosis is a novel form of regulated cell death, discovered in 2022, that occurs due to excessive copper accumulation in mitochondria. Unlike apoptosis, ferroptosis, pyroptosis, and necroptosis, cuproptosis depends on lipoylation of TCA cycle proteins, particularly DLAT, mediated by FDX1, and is accompanied by aggregation of lipoylated proteins and loss of Fe-S cluster proteins. This essay critically reviews the biochemical mechanisms of cuproptosis, its dual role in carcinogenesis (cuproplasia vs. cuproptosis), as well as its involvement in the pathogenesis of cardiovascular, neurodegenerative, metabolic, and musculoskeletal diseases. Therapeutic strategies are considered: copper ionophores (elesclomol, disulfiram), chelators (TTM, D-penicillamine), and nanotechnological delivery systems. Despite its substantial therapeutic potential, the clinical translation of cuproptosis-targeted strategies remains constrained by the lack of specific biomarkers, the complexity of selectivity control, and contradictory results of clinical trials. The need for biomarker-guided stratification of patients (e.g., by LDH level, FDX1 expression, ARID1A mutation status) and the development of tumor-specific nanosystems to minimize systemic toxicity are substantiated. The central thesis posits that cuproptosis is not merely a novel form of cell death, but a fundamental biochemical switch revealing the dual nature of copper; however, its clinical translation hinges on overcoming key limitations (Figure 1).

Abstract: Games on knot and link diagrams provide a combinatorial setting in which topological invariants can be used to certify terminal outcomes and to guide winning strategies. Separately, bitopological game theory studies situations in which two topologies are relevant to the same underlying set or function space. This paper formulates a bitopological extension of finite knot-diagram games. A bitopological knot game consists of a finite diagram-state space, two topologies, player-dependent admissibility neighborhoods subordinate to those topologies, a turn rule, a terminal payoff, and a knot or link invariant used to evaluate terminal states. We prove a strategic quotient theorem: when a quotient map preserves terminal payoffs and the sets of successor classes available to each player, the quotient game has exactly the same minimax value and winning regions. We then give a two-topology version and explain how invariant-valued terminal payoffs can reduce a diagram game to a finite invariant game. A finite example shows that changing one player's admissibility system can change the value even when the terminal invariant is unchanged. Applications to the Knotting--Unknotting Game and the KnotLink Game are discussed as extensions, not as claims that the published winning-strategy results for those games have been reproved or superseded. The main contribution is a precise framework and a theorem that can be applied once the admissibility systems and quotient hypotheses are verified for a concrete family of knot or link shadows.

Abstract: The structural regime framework introduced in the preceding stages of the Universal Collapse program requires a stronger question than the construction of a regime classifier alone: whether the proposed structural representation contains sufficient information to distinguish configurations that are physically or structurally inequivalent within the admissible domain. In the present work, this question is investigated constructively. We consider the candidate local structural signature\( \Sigma^{*} = \left( C,X^{2},\operatorname{type}(X),I_{2},J \right) \), where \( X_{\mu}=\nabla_{\mu}C \), \( \qquad X^{2}=X_{\mu}X^{\mu} \), and \( Q_{\mu\nu} = \nabla_{\mu}\nabla_{\nu}C -\frac{1}{4}g_{\mu\nu}\Box C \), with \( I_{2} = Q_{\mu\nu}Q^{\mu\nu} = \operatorname{Tr}\!\left(Q\eta Q\eta\right) \) and \( \qquad J=X^{\mu}Q_{\mu\nu}X^{\nu} \), where the index contraction is performed with the background metric used in the computational construction. In the matrix representation adopted in the numerical tests, this contraction is represented by \( \operatorname{Tr}(Q\eta Q\eta) \). Rather than searching only for accidental collisions among independently generated configurations, we construct and analyze fibers of fixed \( \Sigma^{*} \). This reverses the usual classification procedure: instead of asking whether different configurations happen to share a signature, we fix the signature and actively search for structurally distinct configurations inside the corresponding fiber. The resulting computational campaign shows that configurations sharing \( \Sigma^{*} \) can nevertheless differ in tensorial rank, kernel structure, inertia class, spectral information, and local response. These distinctions persist under the admissibility and compatibility tests implemented in the study, including Hessian realizability, local scalar dynamics, conformal metric construction, representative gravitational constraints, and selected higher-jet consistency conditions. Population-level tests further show that the same \( \Sigma^{*}\ \)-fiber can contain multiple operationally separated classes. We then investigate a minimal extension of the candidate signature through higher spectral moments of the trace-free Hessian. In the tested extension sequence, the cubic spectral moment \( K_{3}=\operatorname{Tr} \left[ \left(Q^{\mu}{}_{\nu}\right)^{3} \right] \ \) is the first additional quantity found to separate the previously indistinguishable configurations. This motivates the tested extension \( \Sigma_{\min} = \left( C,X^{2},\operatorname{type}(X),I_{2},J,K_{3} \right) \). A subsequent constructive attack on this extended signature involved 22.5 million random deformation attempts distributed equally among timelike, spacelike, and non-null sectors. No collision of \( \Sigma^{*}+K_{3} \) was found in that population. These results do not establish global or universal sufficiency of \( \Sigma_{\min}\ \). The final collision search is a finite sampling procedure and does not constitute an exhaustive parametrization of the corresponding fiber. The principal result of this work is therefore more restricted: \( \Sigma^{*}\ \) is insufficient within the tested domain, while \( \Sigma^{*}+K_{3}\ \) survives the strongest constructive attack performed in the present computational campaign. The unresolved question of whether this extension is globally sufficient, and how its fibers should be characterized constructively, is left for subsequent work.

Abstract: We develop a groupoid-based framework for gerbes on orbifolds equipped with two compatible topologies. The smooth topology determines the underlying orbifold, whereas a second topology records additional topological structure on the levels of its presenting groupoid. We define paired banded gerbes, formulate their Dixmier–Douady invariants, and establish classification and Morita-invariance results under explicit descent and coefficient hypotheses. In particular, we prove that decorated pairs of circle-banded gerbes are classified by a product of two groupoid-cohomology groups. We then formulate a relative classification for compatible pairs using a homotopy fibre product of gerbe-classification groupoids. We prove that both constructions are invariant under Morita equivalences that preserve the two topological sites and their coefficient systems. A finite-quotient example demonstrates why orbifold isotropy cannot in general be discarded in favor of the coarse orbit space. The example also provides a test that any proposed bitopological Dixmier–Douady theory must satisfy. The standard orbifold-gerbe theory is distinguished throughout from the additional paired structure introduced here. The classification statements are conditional on explicitly stated descent hypotheses; no automatic equivalence between arbitrary pairs of topologies is assumed.

Abstract: The increasing reliance on cloud storage across sectors has made the protection of sensitive data a critical concern especially as advances in quantum computing threaten to break traditional public-key cryptographic systems. This growing vulnerability raises urgent questions about how to secure digital assets in a post-quantum future. To address this challenge, this study aims to design, implement, and evaluate a hybrid encryption framework that combines symmetric encryption for data confidentiality with quantum-resistant public-key algorithms for key management and digital signatures. The objective was to develop a secure and practical solution that can be readily adopted using open-source tools. The system was built in a Linux-based virtual environment using an S3-compatible object storage platform, integrated with quantum-safe cryptographic libraries, and automated through scripting. Performance testing was conducted using files ranging from 100 MB to 1 GB, with metrics such as encryption and decryption time, CPU usage, upload/download latency, and internet throughput analyzed. The results showed that while quantum-safe operations added some overhead, even large files could be securely processed in under two minutes with stable system performance and no data corruption. These findings confirm that hybrid encryption models can be deployed today without specialized hardware, offering a forward-compatible and robust approach to cloud security. This work contributes a tested and reproducible framework for early adoption of quantum-safe cryptography in real-world cloud environments.

Abstract: In daytime workers/learners, the reduction of sleep duration on weekdays can be partially compensated by an advance of circadian sleep phase caused by an advance of the 24-h cycle of exposure to light. Since health effects of these sleep reduction and phase advance cannot be easily separated in human studies, Drosophila melanogaster was used to compare health consequences of 1) shaking or heating between 3:00 to 7:00 during 5 weekdays applied to produce the 4-h sleep deprivation on weekday mornings and 2) shifting the 12-h interval of light exposure applied to produce the 4-h advance in weekday circadian timing. Flies showed a gradual restoration of the circadian phase on weekends after the 4-h weekday advance of the 24-h light-dark cycle. However, their reproduction and survival remained uncompromised. Shaking was associated with drastic negative consequences for reproduction and survival. Only survival was compromised by heating. Despite this, sleep loss caused by morning shaking or heating was compensated by its rebound during several following hours, and, on weekends, the 24-h sleep-wake pattern was already fully restored. While humans fail homeostatically compensate their monophasic sleep after its loss in the morning hours, polyphasic Drosophila sleep can be fully compensated during the same weekday.

Abstract: Small open language models that run on an ordinary office computer are an attractive basis for a security awareness assistant, and platforms such as SentinelSphere ship one in a compressed quantised form, that stores the numbers inside the model with fewer bits. This study asks how much cybersecurity knowledge this compression costs, and whether the cost is larger in Greek than in English. A sample of questions from the CyberMetric benchmark was translated into Greek with an open translation model that was not itself tested, the translation was checked by translating it back, and the same questions were put in both languages to Phi-4-mini at three levels of compression, to the general model Qwen2.5-3B and to the Greek adapted model Krikri-8B, all on a two core processor. Phi-4-mini answers Greek questions clearly worse than English ones even with light compression. The four bit compression that platforms ship costs almost nothing in English but a clear share of accuracy in Greek, and the strongest compression brings Greek close to guessing while English stays usable. The general model is the most accurate in English but among the weakest in Greek, where it needs about four times as many text pieces per question, while the Greek adapted model keeps the gap smallest at the price of a larger and slower file. Files made without the calibration step that relies on mostly English text, including the file the platform publishes, lose the same Greek accuracy at four bits. A compression level found acceptable in English should therefore not be assumed acceptable in Greek.

Abstract: This paper examines when disclosure helps investors value intangible investments and what information is useful under different forms of uncertainty. We connect the disclosure literature with the theories of decision-making under ambiguity and real options. On this basis, we develop a conceptual framework that traces what has been invested, what value is expected, and what results have been achieved. We distinguish information asymmetry, where management knows more than the investor, from shared uncertainty about future outcomes. Shared uncertainty takes the form of risk when probabilities can be estimated, or ambiguity when there is no reliable basis for estimating them. Under shared ambiguity, information about management’s future decisions may be more useful than a detailed forecast of the final outcome. This information includes the project’s stages, the funding required, and the conditions for continuation or termination. Disclosing this information enables investors to account for opportunities to limit future losses. Its usefulness depends on how reliably the value and costs associated with termination can be assessed and whether management will follow the announced criteria. Subsequently comparing actual decisions with these criteria, including for unsuccessful projects, may reveal more about management’s reliability than the accuracy of a single forecast. The framework also explains why creditors and shareholders have different information needs. We formulate five propositions for future empirical testing and illustrate their conditions with numerical examples. The analysis offers guidance for disclosure on intangible investments in the context of the review of IAS 38.

Abstract: The multi-factorial origin of stress vulnerability remains incompletely understood, hampering the implementation of targeted prevention. As interplays between genes and environment lie at the basis of individual variability, epigenetic mechanisms are considered important mediators of adverse mental health trajectories following stressful experiences. We have previously demonstrated that the X-linked epigenetic factor Methyl-CpG binding protein 2 (MECP2) plays a role in stress susceptibility, with dysfunctional variants in transgenic mice and its downregulation in human populations being associated with a lower ability to cope with adverse events. By leveraging a study of the Italian Twin Registry on mental health during the COVID-19 pandemic, the present study explored whether a genetic component that accounts for individual variability in MECP2 expression may shape risk of developing stress-related mental health deterioration. We report an association between homozygosity for the minor allele of the rs2734647, a single nucleotide polymorphism (SNP) in the MECP2 3’-untranslated region (UTR) that has been linked to allele-specific MECP2 downregulation, and increased symptoms of COVID-19 pandemic-related depression, anxiety and distress in women. Our findings provide additional evidence to the emerging role of MECP2 in stress vulnerability, unveiling the contribution of genetic variation within the MECP2 locus to adverse mental health outcomes in women.

Abstract: Artificial intelligence (AI) and digital technologies can facilitate sport organizations’ forward-looking strategies, administration, accountability, and stakeholder communication. However, there is a need to consider leadership competencies, data utility, implementation infrastructure, and governance mechanisms. The purpose of this review article is to provide an Africa-centric analytical synthesis of AI-enabled leadership and digital governance in sport institutions. The review focuses on digital transformation, organizational dynamic capabilities, stakeholder governance, and responsible AI. Five conceptual areas were considered, including strategic leadership, data-driven decision-making, transparency and accountability, organizational readiness, and ethical and inclusive implementation. AI can enable financial audits, administrative reporting, resource allocation, performance evaluations, and stakeholder communications in sport organizations. However, there are risks associated with data privacy, algorithmic biases, cyber security, x- ai, digital divides, and reliance on external technologies. These factors could challenge the performance of sport organizations, particularly those with limited financial and infrastructural capabilities. The article provides a conceptual framework that connects institutional environments, AI-enabled leadership capabilities, digital governance mechanisms, and institutional transformation outcomes. Research gaps and implications were identified, including the need to study African sport-sponsoring entities, digital governance maturity models, financial accountability, and player data privacy. Since this is a review article, the proposed research strategy and thematic analysis need to go through a verifiable database search and screening process before the finalizing of the completed systematic review.

Abstract: This paper outlines the protocols, methods and technological steps used to manufacture perovskite semiconductor radiation detectors and compares them with those used in the manufacture of = more traditional semiconductor materials, such as Si, HPGe, CdZnTe, CdTe and TlBr. We analyze the problems and limitations arising when implementing these technologies at this early stage of perovskite detector development. We examine and critique the methods used in crystal growth and processing. Applying revised processes to CsPbBr₃ crystals with dimensions 5×5×3 mm³, we have manufactured a number of radiation detectors with different contact architectures – a planar contact structure, a planar structure with a guard ring and a ring-electrode type structure. In terms of energy resolution, the ring-drift detectors gave the best energy resolu-tion, followed by the planar with guard ring and the simple planar. Specifically, the ring-drift detectors provided FWHM energy resolutions of less than 1% at 662 and 1332 keV (0.79% and 0.86%, respectively) with a peak to Compton ratio of 11. The FWHM energy resolutions at 59.5 keV, 122 keV and 5.9 keV were 2.7 keV (4.5%), 3.4 keV (2.8 %) and ≤2.6 keV, respectively.

Abstract: Large Language Model (LLM)-based multi-agent systems have demonstrated strong capabilities in complex task automation. However, these systems suffer from a critical vulnerability: hallucination cascade, where erroneous information generated by one agent propagates through the system and is amplified by downstream agents. We propose Dynamic Consensus Auditing (DCA), a novel framework that introduces a lightweight audit agent to monitor inter-agent message flows. DCA combines Retrieval-Augmented Generation (RAG) with uncertainty quantification based on semantic entropy to detect potentially hallucinated content. When high-uncertainty messages are detected, DCA triggers a peer review mechanism where multiple agents vote on the validity of the information. Experiments on HotpotQA, TriviaQA, and MuSiQue benchmarks demonstrate that DCA reduces error propagation rates by 42.5% (relative reduction) on average compared to baseline multi-agent systems, with a token overhead of 15.3% (averaged across datasets). Our results suggest that, in the context of multi-hop question answering with three-agent pipelines, consensus-aware verification provides a practical balance between reliability and computational efficiency in multi-agent collaboration.

Abstract: Background: N6-methyladenosine (m6A) is the most abundant internal modification of eukaryotic mRNA. Writers deposit it, erasers remove it, and readers interpret it. In the central nervous system (CNS), this system regulates local translation, synaptic plasticity, neurodevelopment, glial function, and behavioral adaptations relevant to addiction, stress, and cognitive disorders. Methods: Literature was identified through PubMed, Scopus, and Web of Science searches up to March 2026. We reviewed primary literature on the m6A enzymatic machinery, its roles in neuronal and glial function, its involvement in CNS disorders, and the current state of m6A-targeted pharmacology. Results: The m6A machinery concentrates in the brain and regulates transcripts encoding synaptic proteins, ion channels, and neurotrophic factors. Manipulating the pathway alters learning, memory, stress responses, and drug-related behaviors in rodents. In glial cells, m6A regulates microglial polarization, astrocyte reactivity, and oligodendrocyte differentiation, though this literature is less mature and replication is limited. Inhibitors of METTL3 and FTO exist, as do early-stage reader ligands; none has demonstrated the selectivity, brain penetration, or kinetic compatibility required for a CNS therapeutic. A METTL3 inhibitor (STC-15) has entered Phase 1 oncology trials, confirming druggability in principle but not CNS applicability. Conclusions: The m6A epitranscriptome is mechanistically compelling but pharmacologically immature for CNS application. Realizing its potential requires brain-penetrant, isoform-selective probes; relapse-relevant behavioral models with replication across drug classes; and circuit-level data on m6A dynamics relative to protein half-lives. Human data remain sparse, limited by postmortem RNA stability and the absence of validated m6A biomarkers.

Abstract: This paper investigates the causal relationship between trading volume and stock price around stock splits in African stock markets, which are characterized by low liquidity. The sample comprises 223 split stocks listed on seven exchanges (BRVM, Egypt, Morocco, Mauritius, Nigeria, South Africa, Tunisia) over the 2014–2024 period. We combine linear Granger (1969) causality tests with the nonlinear causality test of Diks & Panchenko (2006), after a BDS test confirming nonlinear dependence. Before the split, volume predicts price: linearly in the BRVM and Tunisia, and nonlinearly in Egypt, Tunisia and South Africa (at the 5% significance level). After the split, the relationship is reconfigured: price becomes predictive of volume, particularly in the BRVM, Tunisia, South Africa and Mauritius, while Morocco displays bidirectional causality (at the 5% significance level). These findings suggest that, once a stock is split, investors become sensitive to price levels, which affects the tradability of the security. Managers should therefore use stock splits carefully and target an optimal price range.

Abstract: Internet of Things (IoT), artificial intelligence (AI), and digital connectivity offer potential opportunities to improve dairy production and resource management, but their application in developing countries remains constrained by infrastructure, cost, and technical limitations. This study develops an integrated System Dynamics model to examine the potential effects of digital technology adoption on dairy production, livestock development, resource recovery, and economic activities in Bangladesh. Drawing on a systematic literature review and secondary evidence, the model represents technology-related improvements through scenario-dependent efficiency coefficients rather than physically implemented IoT systems or trained AI algorithms. The study examined baseline and technology adoption scenarios over 60 months, supported by parameter sensitivity analysis. The simulations show higher milk production, livestock development, and resource recovery outputs under the technology adoption assumptions. Sensitivity analysis, configured for 200 simulations across three technology-related parameters, indicates increasing variation in selected outputs over time. The findings demonstrate how digital technology assumptions can influence interconnected production and resource flows, while highlighting the importance of connectivity, affordability, and institutional support. The framework supports exploratory scenario assessment rather than empirical prediction of individual dairy farms.

Abstract: Dairy whey is an agro-industrial by-product with potential for agricultural nutrient recycling. This study evaluated fermented whey-based biofertilizers containing cattle manure, alfalfa, and baker’s yeast for lettuce (Lactuca sativa L.) production under semiarid conditions in Mexico. Three formulations containing 2.5, 5.0, or 7.5 L of whey were characterized and assessed through a germination bioassay and two 35-day field cultivation cycles. Increasing whey incorporation was associated with higher organic matter and nutrient concentrations, as well as greater electrical conductivity. Seed germination remained high (93.33–96.00%), without significant treatment differences; however, root and shoot lengths were lower than in the water control. Under field conditions, the intermediate formulation (T2; 5.0 L whey) supported strong vegetative development and produced fresh biomass statistically comparable to T3 in both cycles. T2 also showed the highest phosphorus concentration in plant tissue. Soil responses varied by property, with significant treatment effects on changes in pH, electrical conductivity, available phosphorus, and exchangeable potassium, but not on organic matter, total nitrogen, or moisture. These findings identify T2 as a promising formulation for further evaluation, while highlighting the need to monitor seedling growth and soil salinity during repeated applications.

Abstract: Scalp itch and beard irritation are multifactorial neurocutaneous disorders associated with microbial dysbiosis, impaired skin barrier function, inflammation, and activation of the transient receptor potential vanilloid 1 (TRPV1) ion channel, a key mediator of itch signalling and neurogenic inflammation. Although conventional therapies such as ketoconazole, zinc pyrithione, and hydrocortisone provide symptomatic relief, their long-term use is limited by adverse effects, irritation, and regulatory concerns, highlighting the need for safer steroid-free alternatives. In the present study, the molecular mechanism underlying the antipruritic potential of FERMENZA, a natural postbiotic formulation, was investigated using an integrated computational approach. LC-MS metabolite profiling identified major phytochemicals, which were subjected to molecular docking against the TRPV1 vanilloid-binding pocket, followed by 40 ns molecular dynamics simulations in a POPC lipid bilayer under physiological conditions. Among the identified metabolites, rutin exhibited the highest binding affinity (-12.76 kcal mol^-1), followed by ellagic acid (-11.83 kcal mol^-1), outperforming the reference antagonist capsazepine (-8.96 kcal mol^-1) as well as hydrocortisone (-8.06 kcal mol^-1), ketoconazole (-6.56 kcal mol^-1), and zinc pyrithione (-6.06 kcal mol^-1). Both phytochemicals formed stable hydrogen bonds and hydrophobic interactions with key residues in the TRPV1 binding pocket. Molecular dynamics simulations confirmed stable protein-ligand complexes without ligand dissociation throughout the simulation. Rutin showed the highest structural stability, reflected by the lowest backbone RMSD (3.72 ± 0.37 Å), stable radius of gyration, minimal solvent-accessible surface area fluctuations, and negligible perturbation of the surrounding POPC membrane. Overall, the findings identify rutin, followed by ellagic acid, as promising natural TRPV1 modulators and provide a molecular basis for the antipruritic activity of FERMENZA, supporting its potential as a safe, drug-free and steroid-free natural formulation for managing scalp itch and beard hypersensitivity.

Abstract: Accumulating evidence indicates that the main adaptive function of meiosis is the repair of damage in germ line DNA, transmitted from parent to progeny. This view contrasts with the alternative view that meiosis is primarily an adaptation for generating new genetic variation that might provide a competitive advantage. Meiosis occurs in forms of reproduction that produce little or no genetic variation among progeny, such as parthenogenesis, selfing (self-fertilization), and close inbreeding. Such forms of reproduction in fungi, protozoa, insects, plants and animals are reviewed here, and some of the benefits of these forms of reproduction are described. These benefits are evidence consistent with the concept that the main adaptive benefit of meiosis is the repair of damage in germ-line DNA.