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Diffusive topology preserving manifold distances for single-cell data analysis

Manifold learning techniques have emerged as crucial tools for uncovering latent patterns in high-dimensional single-cell data. However, most existing dimensionality reduction methods primarily rely on 2D visualization, which can distort true data relationships and fail to extract reliable biological information. Here, we present DTNE (diffusive topology neighbor embedding), a dimensionality reduction framework that faithfully approximates manifold distance to enhance cellular relationships and dynamics. DTNE constructs a manifold distance matrix using a modified personalized PageRank algorithm, thereby preserving topological structure while enabling diverse single-cell analyses. This approach facilitates distribution-based cellular relationship analysis, pseudotime inference, and clustering within a unified framework. Extensive benchmarking against mainstream algorithms on diverse datasets demonstrates DTNE’s superior performance in maintaining geodesic distances and revealing significant biological patterns. Our results establish DTNE as a powerful tool for high-dimensional data analysis in uncovering meaningful biological insights.

Impact of media coverage on the transmission dynamics of TB with vaccines and treatment

Tuberculosis (TB) is one of the deadly infectious diseases affecting millions of individuals throughout the world. The main objective of this study is to investigate the impact of media coverage on the transmission dynamics of TB with vaccine and treatment strategy using mathematical model analysis. In the qualitative analysis of the proposed model we proved the existence, uniqueness, positivity, and boundedness of the model solutions, investigated both the disease-free and endemic equilibrium points, computed the basic and effective reproduction numbers using next generation matrix approach, analyzed the stability analysis of the equilibrium points, the backward bifurcation using the Castillo-Chavez and Song theorem and we re-formulated the corresponding optimal control problem and analyzed by applying the Pontryagin’s Minimum Principle. In the model quantitative (numerical) analysis part, we performed the model parameters sensitivity analysis and carried out numerical simulation to verify the qualitative analysis results. The findings of the study indicate that if the reproduction number is less than one, the solution converges to the disease-free state, signifying the asymptotic stability of the TB-free steady state. Moreover, the existence of a backward bifurcation shows that the disease-free equilibrium coexists with one or more endemic equilibria, even when the basic reproduction number is less than 1. Furthermore, it is found that as media efficacy increases, the disease infection rate decreases, which consequently leads to an increase in prevention and treatment control strategies.

Representational geometry explains puzzling error distributions in behavioral tasks

Measuring and interpreting errors in behavioral tasks is critical for understanding cognition. Conventional wisdom assumes that encoding/decoding errors for continuous variables in behavioral tasks should naturally have Gaussian distributions, so that deviations from normality in the empirical data indicate the presence of more complex sources of noise. This line of reasoning has been central for prior research on working memory. Here, we reassess this assumption and find that even in ideal observer models with Gaussian encoding noise, the error distribution is generally non-Gaussian, contrary to the commonly held belief. Critically, we find that the shape of the error distribution is determined by the geometrical structure of the encoding manifold via a simple rule. In the case of a high-dimensional geometry, the error distributions naturally exhibit flat tails. Using this insight, we apply our theory to visual short-term memory tasks, and find that it can account for a large array of experimental data with only two free parameters. Our results challenge the dominant view in the mechanisms and capacity constraints of working memory systems. They instead suggest that the Bayesian framework, which explains various aspects of perceptual behavior, also provides an excellent account of working memory. Overall, our results establish a direct connection between neural manifold geometry and behavior, and call attention to the geometry of the representation as a critically important, yet underappreciated factor in determining the character of errors in human behavior.

The importance of method selection when estimating diet composition with quantitative fatty acid signature analysis

Quantitative fatty acid signature analysis (QFASA) is a common method of estimating the composition of prey species in the diets of consumers from polar and temperate ecosystems in which lipids are an important source of energy. A key characteristic of QFASA is that the large number of fatty acids that typically comprise lipids permits the dietary contributions of a correspondingly large number of prey types to be estimated. Several modifications to the original QFASA methods have been suggested in the literature and a significant extension of the original model published in 2017 allows simultaneous estimation of both diet proportions and calibration coefficients, which are metabolic constants in the model whose values must otherwise be estimated in independent feeding experiments. However, comparisons of diet estimates obtained using different estimation options have been limited. QFASA has been used to estimate the diet composition of several polar bear (Ursus maritimus) subpopulations, including the Southern Beaufort Sea (SBS) subpopulation. Prior QFASA estimates of SBS polar bear diet composition have most often been obtained using variations of the original QFASA model. We investigated the influence of variations in QFASA analytical methods on diet estimates by re-estimating the diet composition of polar bears from the Alaska portion of the SBS using three different methods and found that differences among the three sets of estimates were substantial. Our results illustrate how important the careful and deliberate selection of QFASA methods can be and we provide some guidance on techniques one might use to evaluate options.

The <i>Pseudomonas</i> ligninolytic catalytic network reveals the importance of auxiliary enzymes in lignin biocatalysts

Lignin degradation by biocatalysts is a key strategy to develop a plant-based sustainable carbon economy and thus alleviate global climate change. This process involves synergy between ligninases and auxiliary enzymes. However, auxiliary enzymes within secretomes, which are composed of thousands of enzymes, remain enigmatic, although several ligninolytic enzymes have been well characterized. Moreover, it is a challenge to understand synergistic lignin degradation via a diverse array of enzymes, especially in bacterial systems. In this study, the coexpression network of the periplasmic proteome uncovers potential accessory enzymes for B-type dye-decolorizing peroxidases (DypBs) in Pseudomonas putida A514. The catalytic network of the DypBs-based multienzyme complex is characterized. DypBs couple with quinone reductases and nitroreductase to participate in quinone redox cycling. They work with superoxide dismutase to induce Fenton reaction for lignin oxidation. A synthetic enzyme cocktail (SEC), recruiting 15 enzymes, was consequently designed with four functions. It overcomes the limitation of lignin repolymerization, exhibiting a capacity comparable to that of the native periplasmic secretome. Importantly, we reveal the synergistic mechanism of a SEC-A514 cell system, which incorporates the advantages of in vitro enzyme catalysis and in vivo microbial catabolism. Chemical analysis shows that this system significantly reduces the molecular weight of lignin, substantially extends the degradation spectra for lignin functional groups, and efficiently metabolizes lignin derivatives. As a result, 25% of lignin is utilized, and its average molecular weight is reduced by 27%. Our study advances the knowledge of bacterial lignin-degrading multienzymes and provides a viable lignin degradation strategy.

Association between chiropractic spinal manipulation for sciatica and opioid-related adverse events: A retrospective cohort study

Background Patients receiving chiropractic spinal manipulation (CSM) for spinal pain are less likely to be prescribed opioids, and some evidence suggests that these patients have a lower risk of any type of adverse drug event. We hypothesize that adults receiving CSM for sciatica will have a reduced risk of opioid-related adverse drug events (ORADEs) over a one-year follow-up compared to matched controls not receiving CSM. Methods We searched a United States (US) claims-based data resource (Diamond Network, TriNetX, Inc.) of more than 216 million patients, yielding data ranging from 2009 to 2024. We included patients aged ≥18 years with sciatica, excluding those post-spine surgery, prior anesthesia, serious pathology, high risk of ORADEs, and an ORADE ≤ 1-year prior. Patients were divided into two cohorts: (1) CSM and (2) usual medical care. We used propensity score matching to control for confounding variables associated with ORADEs. Comparative outcomes were analyzed by calculating risk ratios (RRs) and 95% confidence intervals (CIs) for the incidence of ORADEs and oral opioid prescription between cohorts. Results 372,471 patients per cohort remained after matching. The incidence of ORADEs over 1-year follow-up was less in the CSM cohort compared to the usual medical care cohort (CSM: 0.09%; usual medical care: 0.30%), yielding an RR of 0.29 (95% CI: 0.25–0.32; P &lt; .00001). CSM patients had a lower risk of receiving an oral opioid prescription (RR of 0.68 [95% CI: 0.68–0.69; P &lt; .00001]). Conclusions This study found that adults with sciatica who initially received CSM had a lower risk of an ORADE compared to matched controls not initially receiving CSM, likely explained by a lower probability of opioid prescription. These findings corroborate existing practice guidelines which recommend adding CSM to the management of sciatica when appropriately indicated.

An analytical model of label-free nanoscale chemical imaging reveals avenues toward improved spatial resolution and sensitivity

Atomic force microscopy–infrared spectroscopy (AFM-IR) is a photothermal scanning probe technique that combines nanoscale spatial resolution with the chemical analysis capability of mid-infrared spectroscopy. Using this hybrid technique, chemical identification down to the single molecule level has been demonstrated. However, the mechanism at the heart of AFM-IR, the transduction of local photothermal heating to cantilever deflection, is still not fully understood. Existing physical models only describe this process in few special cases but not in many of the types of sample geometries encountered in the practical use of AFM-IR. In this work, an analytical expression for modeling the temperature and photothermal expansion process is introduced, verified with finite element simulations, and validated with AFM-IR experiments. This method describes AFM-IR signal amplitudes in vertically and laterally heterogeneous samples and allows studying the effect of position and size of an absorber, pump laser repetition rate and pulse width on AFM-IR signal amplitudes and spatial resolution. The analytical model can be used to identify optimal AFM-IR experimental settings in conventional and advanced AFM-IR modes (e.g., tapping mode, surface-sensitive mode). The model also paves the way for signal inversion based superresolution AFM-IR.

Correction: Intersecting paths: Corporate and green innovation in Chinese firms—A penal cointegration analysis

Violence against women and girls research: Leveraging gains across disciplines

Violence against women and girls (VAWG) is a leading cause of mortality and morbidity worldwide, linked to numerous health, economic, and human rights outcomes. Target 5.2 of the Sustainable Development Goals calls for elimination of all forms of VAWG; however, progress toward achieving this goal has been inadequate. A lack of sufficient data and evidence has hindered global efforts to meet this target and hold governments accountable for action. While there have been substantial advancements in VAWG research methodology over the past three decades, researchers from diverse disciplines tend to work in silos, inhibiting progress in VAWG research. To address this challenge, we offer four key recommendations to support researchers in expanding transdisciplinary approaches: 1) leverage insights from a variety of VAWG data sources, 2) improve precision of VAWG definitions and outcomes, 3) create strategies to address underreporting, and 4) advance research ethics and equity. We conclude with a call to action for researchers, institutions, and donors to advance transdisciplinary research and foster collaboration, learning, and cross-fertilization across scientific fields to accelerate VAWG prevention efforts now and for future generations.

Correction: The moderating role of sociodemographic and work-related variables in burnout and mental health levels of Mexican medical residents

Molecular glue for phycobilisome attachment to photosystem II in <i>Synechococcus</i> sp. PCC 7002

Phycobilisomes (PBS) are the major photosynthetic light-harvesting complexes in cyanobacteria and red algae. While the structures of PBS have been determined in atomic resolutions, how PBS are attached to the reaction centers of photosystems remains less clear. Here, we report that a linker protein (LcpA) is required for the attachment of PBS to photosystem II (PSII) in the cyanobacterium Synechococcus sp. PCC 7002. We also report that the PB-loop of PBS, which is located within the α-APC domain of ApcE, is required for the attachment of PBS to PSII. Deletion of either PB-loop or the gene A0913 led to a decreased rate of photoautotrophic growth under illumination of green light, which is preferentially absorbed by PBS. A double mutant lacking the PB-loop and A0913 (ΔPBL-0913) showed a complete inhibition of O 2 evolution under the 590 nm light and could not grow under green light illumination. While assembled PBS could be isolated from ΔPBL-0913, the energy transfer from its PBS to PSII was blocked as measured by fluorescence induction. Photobleaching with intact cells showed that the PBS movement speed in ΔPBL-0913 was 2.5 times as fast as that of the wild type, suggesting that association of its PBS with thylakoids was weakened significantly. The pull-down and coimmunoprecipitation results showed that the LcpA interacts with the CP47 subunit of PSII through its N-terminal region and interacts with ApcB of PBS through its C-terminal α-helix motif. Our results provide insights into the molecular mechanism of PBS–PSII association and shed light on excitation energy transfer from PBS to PSII.

A novel approach for the router nodes placement in wireless mesh networks using phasing with approximation optimization algorithms

Optimal router node placement (RNP) is an effective method for improving the performance of wireless mesh networks (WMN). However, solving the RNP problem in WMN is difficult because it is NP-hard. As a result, this problem can only be solved using approximate optimization algorithms such as heuristics and meta-heuristics. In this study, we propose a new and effective method for solving the RNP problem. The idea behind this method is to solve the RNP problem in two stages using an optimal algorithm with fewer variables than the original RNP problem. In stage 1, we build an RNP sub problem using 15% to 20% of the number of routers, with the objective function of minimizing coverage overlap between routers to form a core network. Stage 2 is built into another RNP sub problem with the remaining number of routers, and the objective function is to maximize the network connectivity. Each sub problem was solved using an approximate optimal algorithm. The experimental results demonstrate that, in terms of client coverage and network connectivity, our proposed method outperforms widely used RNP problem-solving methods.

Complement C3 of tumor-derived extracellular vesicles promotes metastasis of RCC via recruitment of immunosuppressive myeloid cells

Heterogeneous roles of complement C3 have been implicated in tumor metastasis and are highly context dependent. However, the underlying mechanisms linking C3 to tumor metastasis remain elusive in renal cell carcinoma (RCC). Here, we demonstrate that C3 of RCC cell-derived extracellular vesicles (EVs) contributes to metastasis via polarizing tumor-associated macrophages (TAMs) into the immunosuppressive phenotype and recruiting polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs). Mechanistically, EV C3 induces the secretion of CCL2 and CXCL1 by lung macrophages and subsequently enhances TAM polarization and PMN-MDSC recruitment. Notably, targeting the CCL2/CCR2 or CXCL1/CXCR2 axis with the inhibitors RS504393 or Navarixin, respectively, effectively suppresses lung metastasis induced by RCC-derived C3 in a mouse model. Clinically, RCC patients with high expression of C3 demonstrate poor prognosis. Collectively, our findings reveal that tumor-derived EV C3 induces an immunosuppressive tumor microenvironment via TAMs, and thus promoting RCC metastasis.

Separation effectiveness of ideal ion exchange membranes: Application of the Gibbs-Donnan theory

Ion exchange membranes (IEMs) are permselective membranes that, in principle, only allow the flow of ions with a specific charge sign, opposite to that of the fixed membrane ionic groups (counter-ions). This charge-based selectivity, like the size-based selectivity of classic semipermeable membranes, leads to an uneven distribution of permeating ions on the two sides of the membrane, which allows for ion separation or recovery in various processes in industry or environmental protection. Here, we apply the principles of mass balance, charge neutrality, and equality of electrochemical potentials in the state of thermodynamic equilibrium to provide a simple method for estimating the Gibbs-Donnan factors and the equilibrium concentrations of permeating ions in two compartments separated by an ideal IEM, i.e. an IEM that is not permeable to co-ions. We present the method for the case when the equilibrium concentrations are known in one compartment and need to be estimated in the other compartment as well as for the case when the total masses of ions in both compartments are known and their equilibrium concentrations need to be predicted. For both cases, the presented nonlinear algebraic equations require in general the use of numerical methods to approximate their mathematical solutions, although we present as well some closed solutions for simple cases with ideal ionic mixtures. Based on the extended Debye–Hückel theory, we also provide analogous equations (general and for specific cases) for systems with non-ideal ionic mixtures. The presented method can provide the expected ideal separation effectiveness of an IEM, which can then be used to assess the relative separation effectiveness of a real membrane.

Molecular mechanism of ligand recognition and activation of lysophosphatidic acid receptor LPAR6

Lysophosphatidic acid (LPA) exerts its physiological roles through the endothelialdifferentiation gene (EDG) family LPA receptors (LPAR1-3) or the non-EDG family LPA receptors (LPAR4-6). LPAR6 plays crucial roles in hair loss and cancer progression, yet its structural information is very limited. Here, we report the cryoelectron microscopy structure of LPA-bound human LPAR6 in complex with a mini G 13 or G q protein. These structures reveal a distinct ligand binding and recognition mode that differs significantly from that of LPAR1. Specifically, LPA uses its charged head to form an extensive polar interaction network with key polar residues on the extracellular side of transmembrane helix 5-6 and the extracellular loop 2. Structural comparisons and homology analysis suggest that the EDG and non-EDG families use two distinct modes for LPA binding. The structural observations are validated through functional mutagenesis studies. We further uncover the mechanisms of LPAR6 activation and principles of G-protein coupling. The structural information revealed by our study lays the groundwork for understanding LPAR6 signaling and provides a rational basis for designing compounds targeting LPAR6.

Pre-treatment subjective sleep quality as a predictive biomarker of tDCS effects in preclinical Alzheimer’s disease patients: Secondary analysis of a randomised clinical trial

Background Despite transcranial direct current stimulation (tDCS) has demonstrated encouraging potential for modulating the circadian rhythm, little is known about how well and sustainably tDCS might improve the subjective sleep quality in older adults. This study sought to determine how tDCS affected sleep quality and cognition, as well as how well pre-treatment sleep quality predicted tDCS effects on domain-specific cognitive functions in patients with mild neurocognitive disorder due to Alzheimer’s disease (NCD-AD). Methods This clinical trial aimed to compare the effectiveness of tDCS and cognitive training in mild NCD-AD patients (n =  201). Over the course of four weeks, patients were randomized to receive either tDCS plus working memory training, or sham tDCS plus working memory training, or tDCS plus controlled cognitive training. The Pittsburgh Sleep Quality Index (PSQI) was used to measured subjective sleep quality. The Alzheimer’s disease assessment scale-cognitive subscale (ADAS-Cog) was used to evaluate domain-specific cognitive functions. Results Recurrent tDCS treatments enhanced subjective sleep quality and cognition considerably. The poor sleepers (i.e., PSQI &gt;  5) who received tDCS treatment had more cognitive benefits (p =  0.031, Cohen’s d =  0.605) and sleep improvements (p &lt;  0.001, Cohen’s d =  1.209) in comparison to cognitive training. Pre-treatment subjective sleep quality was linked to tDCS-induced improvement in memory function. Conclusion During the course of two months, repeated tDCS could considerably enhance subjective sleep quality. For the cognitive benefits of the treatments, the status of pre-treatment subjective sleep quality is crucial. More thorough research is necessary to explore an efficient approach to managing comorbidities for preclinical AD patients.

Microfluidic purification of genomic DNA

We describe a microfluidic device to extract DNA from a cell lysate, without the need for centrifuges, magnetic beads, or gels. Instead, separation is driven by transverse migration of DNA, which occurs when a polyelectrolyte solution flowing through a microfluidic channel is subjected to an electric field. The coupling of the weak shearing with the axial electric field is highly selective for long, flexible, charged molecules, of which DNA is the sole example in a typical cell lysate. As a result of migration to the walls, DNA is held near the channel inlet by electrophoresis (there is no flow near the channel walls), while the remaining components are eluted by the much larger (at least 10-fold) convective flow. We have demonstrated the feasibility of the device by recovering up to 40 ng of purified DNA in less than 30 min from 10 μ L of Escherichia coli lysate. Gel electrophoresis indicates minimal additional fragmentation during purification, up to the maximum length recorded by the gel (60 kbp). Electropherograms were also obtained for purified mammalian DNA, using a Femto Pulse system (fragment lengths up to 165 kbp). Extracted samples show strong amplification by PCR, while the original lysate does not. Mixtures of λ -DNA and BSA were used to determine the extent of the separation of DNA from a physiological concentration of proteins (30 mg/mL). The protein concentration in the extract (0.3 to 0.5 ng/µL) was reduced by five orders of magnitude from the initial mixture.

Correction: The shadow of the family: Historical roots of social trust in Europe

Metabolic activity controls the emergence of coherent flows in microbial suspensions

Photosynthetic microbes have evolved and successfully adapted to the ever-changing environmental conditions in complex microhabitats throughout almost all ecosystems on Earth. In the absence of light, they can sustain their biological functionalities through aerobic respiration, and even in anoxic conditions through anaerobic metabolic activity. For a suspension of photosynthetic microbes in an anaerobic environment, individual cellular motility is directly controlled by its photosynthetic activity, i.e. the intensity of the incident light absorbed by chlorophyll. The effects of the metabolic activity on the collective motility on the population level, however, remain elusive so far. Here, we demonstrate that at high light intensities, a suspension of photosynthetically active microbes exhibits a stable reverse sedimentation profile of the cell density due to the microbes’ natural bias to move against gravity. With decreasing photosynthetic activity, and therefore suppressed individual motility, the living suspension becomes unstable giving rise to coherent bioconvective flows. The collective motility is fully reversible and manifests as regular, three-dimensional plume structures, in which flow rates and cell distributions are directly controlled via the light intensity. The coherent flows emerge in the highly unfavorable condition of lacking both light and oxygen and, thus, might help the microbial collective to expand the exploration of their natural habitat in search for better survival conditions.

Mental health challenges and perceptions of stigma among youth living with HIV in Tanzania

Youth living with HIV (YLWH) face psychosocial challenges and HIV-related stigma, which impact adherence to antiretroviral therapy (ART). This study was designed to understand better the change in mental health symptoms and experiences with stigma among YLWH in Tanzania who completed the original pilot Sauti ya Vijana (SYV), a mental health and life skills group intervention. YLWH who completed SYV and demonstrated a change of ≥2 points in either direction on their Patient Health Questionnaire PHQ-9 (depression screener) from baseline to 18 months were purposively sampled. HIV Stigma was measured using 10-questions from the Berger HIV Stigma Scale, and findings ranged from 4–16 for internal stigma and 6–24 for external stigma. In-depth interviews (IDI) were conducted in Kiswahili and included topics such as history of mental health challenges, perceptions of stigma, and experiences with the SYV intervention. Interviews were transcribed, translated to English, and analyzed for emergent themes. Ten youth, 18–25 years of age, were interviewed; 70% were male. Mean (SD) PHQ-9 scores were 7.3 (SD = 3.5) at baseline and 5.6 (SD = 5.0) at 18 months. All participants reported experiencing intermittent episodes of mental health challenges due to difficult interpersonal relationships and fear of stigma. Youth relied on peer support and skills from the SYV intervention to cope with mental health challenges and stigma. Participants reported fear of being stigmatized by others, which led to behaviors such as skipping medication or avoiding situations for worry about unintentional disclosure. All participants endorsed experiencing external stigma on the HIV stigma scale; however, only 3 of 10 participants reported experiencing enacted stigma when directly asked to describe an experience during in-depth interviews. Participants described how SYV helped them have “more confidence”, accept themselves, and incorporate positive coping skills such as relaxation (deep breathing) when they felt stressed. The findings suggest SYV helped YLWH accept themselves, develop positive coping methods, and identify and form peer social support; but stigma remains common. Descriptions of stigma were not recognized as such; experiences of enacted stigma were acknowledged by some participants. More research is needed to understand and measure mental distress and wellness as well as stigma in this population so that interventions may more accurately detect change in key outcomes.