Correlation Maps Research Articles

PREFUL MRI Depicts Dual Bronchodilator Changes in COPD: A Retrospective Analysis of a Randomized Controlled Trial.

PurposeTo assess whether dynamic ventilation and perfusion (Q) biomarkers derived by phase-resolved functional lung (PREFUL) MRI can measure treatment response to 14-day therapy with indacaterol-glycopyrronium (IND-GLY) and correlate to clinical outcomes including lung function, symptoms, and cardiac function in patients with chronic obstructive pulmonary disease (COPD), as determined by spirometry, body plethysmography, cardiac MRI, and dyspnea score measurements.Materials and MethodsThe cardiac left ventricular function in COPD (CLAIM) study enrolled patients aged 40 years or older with COPD, stable cardiovascular function, and hyperinflation (residual volume > 135% predicted). Dynamic MRI data of these patients were retrospectively analyzed using the PREFUL technique to assess the effect of 14-day IND-GLY treatment versus placebo on regional measurements of ventilation dynamics. After manual segmentation of the lung parenchyma, flow-volume loops of each voxel were correlated to an individualized reference flow-volume loop, creating a two-dimensional flow-volume loop correlation map (FVL-CM) as a measure of ventilation dynamics. Ventilation-perfusion match (VQM) was evaluated in combination with perfusion and regional ventilation (VQMRVent) and with perfusion and the FVL-CM measurement (VQMCM). For image and statistical analysis, the lung parenchyma was segmented as a region of interest by manually delineating the lung boundary and excluding the large (central) vessels for each section. Differences in ventilation, perfusion, and VQM between IND-GLY and placebo were compared using analysis of variance, with study treatment, patient, and period included as factors.ResultsFifty patients (mean age, 64.3 years ± 7.65 [SD]; 35 men) were included in this analysis. IND-GLY significantly increased mean correlation as measured with FVL-CM versus that of placebo (least squares [LS] means treatment difference: 0.05 [95% CI: 0.03, 0.07]; P < .0001). Compared with placebo, IND-GLY increased mean Q (LS means treatment difference: 9.27 mL/min/100 mL [95% CI: 0.05, 18.49]; P = .049) and improved both VQMCM and VQMRVent (LS means treatment difference: 0.06 [95% CI: 0.03, 0.08]; P < .0001 and 0.05 [95% CI: 0.02, 0.08]; P = .001, respectively).ConclusionRegional ventilation dynamics and VQM measured by PREFUL MRI show treatment response in COPD. Supplemental material is available for this article. Clinical trial registration no. NTR6831Keywords: MRI, COPD, Perfusion, Ventilation, Lung, PulmonaryPublished under a CC BY 4.0 license

Synthesis of Chiral Ionic Liquids from Natural Monosaccharides

AbstractThree series of new ionic liquids (ILs), namely imidazolium‐, pyrazolium‐, and bis‐benzimidazolium‐containing ILs, were prepared from low‐cost, unprotected carbohydrates. Information on anion‐cation interactions and solvation shell were obtained via diffusion NMR and heteronuclear Overhauser correlation maps (HOESY), respectively.

Site-selective dynamics of ligand-free and ligand-bound azidolysozyme.

Azido-modified alanine residues (AlaN3) are environment-sensitive, minimally invasive infrared probes for the site-specific investigation of protein structure and dynamics. Here, the capability of the label is investigated to query whether or not a ligand is bound to the active site of lysozyme and how the spectroscopy and dynamics change upon ligand binding. The results demonstrate specific differences for center frequencies of the asymmetric azide stretch vibration, the longtime decay, and the static offset of the frequency fluctuation correlation function (FFCF)-all of which are experimental observables-between the ligand-free and the ligand-bound N3-labeled protein. The center-frequency shifts range from 1 to 8 cm-1, which is detectable from state-of-the art experiments. Similarly, the nonvanishing static component Δ0 of the FFCF between ligand-free and ligand-bound protein can differ by up to a factor of 2.5. This makes the azide label a versatile and structurally sensitive probe to report on the dynamics of proteins in a variety of environments and for a range of different applications. Ligand-induced differences in the dynamics are also mapped onto changes in the local and through-space coupling between residues by virtue of dynamical cross correlation maps. This demonstrates that the position where the label is placed also influences the local and global protein motions.

Integrated analysis of gut microbiome and host immune responses in COVID-19

Emerging evidence indicates that the gut microbiome contributes to the host immune response to infectious diseases. Here, to explore the role of the gut microbiome in the host immune responses in COVID-19, we conducted shotgun metagenomic sequencing and immune profiling of 14 severe/critical and 24 mild/moderate COVID-19 cases as well as 31 healthy control samples. We found that the diversity of the gut microbiome was reduced in severe/critical COVID-19 cases compared to mild/moderate ones. We identified the abundance of some gut microbes altered post-SARS-CoV-2 infection and related to disease severity, such as Enterococcus faecium, Coprococcus comes, Roseburia intestinalis, Akkermansia muciniphila, Bacteroides cellulosilyticus and Blautia obeum. We further analyzed the correlation between the abundance of gut microbes and host responses, and obtained a correlation map between clinical features of COVID-19 and 16 severity-related gut microbe, including Coprococcus comes that was positively correlated with CD3+/CD4+/CD8+ lymphocyte counts. In addition, an integrative analysis of gut microbiome and the transcriptome of peripheral blood mononuclear cells (PBMCs) showed that genes related to viral transcription and apoptosis were up-regulated in Coprococcus comes low samples. Moreover, a number of metabolic pathways in gut microbes were also found to be differentially enriched in severe/critical or mild/moderate COVID-19 cases, including the superpathways of polyamine biosynthesis II and sulfur oxidation that were suppressed in severe/critical COVID-19. Together, our study highlighted a potential regulatory role of severity related gut microbes in the immune response of host.Electronic Supplementary MaterialSupplementary material is available in the online version of this article at 10.1007/s11684-022-0921-6 and is accessible for authorized users.

Some aspects of transition selective NMR involving rare spins

Satellite transition selective excitation/inversion of abundant spins across chemical shifts offers a robust opportunity for sensitivity enhancement of rare spins that are coupled to them. It is also well established that reconversion of rare spin double quantum coherence (DQC) to single quantum-single transitions (SQ-ST's) over a wide range of chemical shifts offers sensitivity enhancement in INADEQUATE-style experiments. The present contribution gives an overview of the latter category of experiments, including a brief summary of the literature, and the contributions from our Lab. In particular, the transition selective “composite refocusing” approach of Sørensen and his group is discussed for reconversion of DQC to SQ-ST's. A shorter transition selective DQC reconversion module introduced from our Lab is also described. A 2D rare spin correlation experiment introduced by us is then reviewed, in which we replace rare spin DQ evolution with immediate reconversion of DQC to SQ-ST's, followed by evolution of SQ-ST's, that is then terminated by a mixing period to deliver a diagonal-free COSY-like correlation map. Finally, our ‘indirect’, 1H detected version of this experiment is reviewed. Transition selective reconversion in ADEQUATE-style experiments was also introduced by us and is briefly mentioned. Interestingly, partial 1H transition selectivity is shown to result as a consequence of reconversion of rare spin DQC to SQ-ST's, followed by coherence order selective heteronuclear reverse transfer. The performance of these experiments when applied to small molecules is illustrated.

C-E (curtailment – Energy share) map: An objective and quantitative measure to evaluate wind and solar curtailment

As the share of VRE (variable renewable energy) has grown rapidly, curtailment issues have arisen worldwide. This paper evaluates and compares curtailment situations in selected countries using an objective and quantitative evaluation tool named the “C-E map” (curtailment-energy share map). The C-E map is a correlation map between curtailment ratios that mean curtailed wind (or solar) energy per available energy and energy shares of wind (or solar). The C-E map can draw a historical trend curve in a given country/area, as an at-a-glance tool to enable historical and/or international comparison. The C-E map also can classify the given countries/areas into several categories, according to the current levels of curtailment ratio and historical trends. The C-E map helps institutional and objective understanding of curtailment for non-experts including policy makers.

Dibenzocyclooctyne-Branched Primer Assembled Gene Nanovector and Its Potential Applications in Genome Editing.

The CRISPR/Cas9 system has been widely used as an efficient genome editing toolkit for gene therapy. The delivery of vectors encoding the full CRISPR/Cas9 components including Cas9 gene and gRNA expression element into cells is the crucial step to effective genome editing. However, the cargo gene sequence for genome editing is usually large, which reduces the cargo encapsulation efficiency and affects the vector size. To obtain a nanovector with high cargo gene loading capacity and biocompatible size, we report the construction of a gene nanovector from branch-PCR with a dibenzocyclooctyne (DBCO)-branched primer and establish the correlation mapping between gene length and nanovector size. The results show that the size of nanovectors can be tuned according to the gene length. According to the findings, we constructed nanovectors carrying the full CRISPR/Cas9 components in 100-200 nm and validated their application in genome editing. The results show that this kind of nanovector exhibits higher serum stability than plasmids and can reach comparable genome editing efficiency with plasmids. Hence, this type of gene nanovector obtained through branch-PCR can carry large gene cargos and maintain a biocompatible nanoscale size, which we envisage will expand its medical applications in gene therapy.

Transferring Inter-Class Correlation for Teacher–Student frameworks with flexible models

The Teacher–Student (T–S) framework is widely utilized in classification tasks, through which the performance of one neural network (the student) can be improved by transferring knowledge from another trained neural network (the teacher). As the transferring knowledge is related to the network capacities and structures between the teacher and the student, how to define knowledge effectively remains an open question. To address this issue, we design a novel and flexible transferring knowledge, Self-Attention based Inter-Class Correlation (ICC) map, which reveals the correlation between every two classes in a mini-batch. Based on the ICC map, we propose a T–S framework, Inter-Class Correlation Transfer (ICCT), in which the knowledge from the teacher with a higher, equal, or lower capacity than the student can bring the benefit to the training process of the student. The ICCT can be applied flexibly on the heterogeneous network structures of the T–S pairs and exhibits excellent compatibility with existing frameworks with hidden-layers knowledge. Notably, the analysis of the ICCT demonstrates that students comprehensively learn the teacher’s knowledge in conjunction with their own understanding, rather than mimicking the teacher’s knowledge entirely. Extensive experiments are conducted in CIFAR-10, CIFAR-100, and ILSVRC2012 image classification datasets in different T–S application scenarios with different network structures. The results demonstrate that the ICCT can improve the student’s performance and outperform other state-of-the-art T–S frameworks.

Complex network-based pertussis and croup cough analysis: A machine learning approach

The paper proposes a novel approach to bring out the potential of complex networks based on graph theory to unwrap the hidden characteristics of cough signals, croup (BC), and pertussis (PS). The spectral and complex network analyses of 48 cough sounds are utilized for understanding the airflow through the infected respiratory tract. Among the different phases of the cough sound time-domain signals of BC and PS – expulsive (X), intermediate (I), and voiced (V) - the phase ‘I’ is noisy in BC due to improper glottal functioning. The spectral analyses reveal high-frequency components in both cough signals with an additional high-intense low-frequency spread in BC. The complex network features created by the correlation mapping approach, like number of edges (E), graph density (G), transitivity (Tr), degree centrality (D), average path length (L), and number of components (Nc) distinguishes BC and PS. The higher values of E, G, and Tr for BC indicate its musical nature through the strong correlation between the signal segments and the presence of high-intense low-frequency components in BC, unlike that in PS. The values of D, L, and Nc discriminate BC and PS in terms of the strength of the correlation between the nodes within them. The linear discriminant analysis (LDA) and quadratic support vector machine (QSVM) classifies BC and PS, with greater accuracy of 94.11% for LDA. The proposed work opens up the potentiality of employing complex networks for cough sound analysis, which is vital in the current scenario of COVID-19.

Aerial detection of beached marine plastic using a novel, hyperspectral short-wave infrared (SWIR) camera

Abstract Plastic pollution in the marine environment is a pervasive, global problem that threatens wildlife and human health. Routine monitoring is required to determine pollution hotspots, focus clean-up efforts, and assess the efficacy of legislation implemented to reduce environmental contamination. The shoreline represents an accessible area, relative to open water, from which to monitor this. Unmanned aerial vehicles (UAVs) offer a low-cost platform for remote sensing that operates below cloud coverage, which can interfere with satellite imagery. Detection of plastic using visible light is limited however, and results may be improved by using short-wave infrared (SWIR) imagery to collect chemical information. Within the commercial recycling industry, plastic items are sorted successfully based on their composition using SWIR instrumentation that measures the chemical spectra of waste items under controlled illumination. Here, proof of concept is established for aerial detection of domestic and shoreline-harvested plastic items on a beach under natural sunlight with a lightweight (800 g), hyperspectral SWIR camera deployed at an altitude of ∼ 5 m over ∼ 30-m transects. The results of spectral correlation mapping to compare imagery spectra to polyethylene and polypropylene reference spectra demonstrate that these two polymers can be successfully detected with this novel method.

Amplitude modulation of relative humidity by wind in Northeast China: the formation of variance annual cycle in relative humidity

Relative humidity has an important impact not only on climate change and ecosystems but also on human life. The intensity of high-frequency fluctuations in surface relative humidity over Northeast China shows a predominant seasonally dependent structure, which may be closely related to regional monsoon activities. However, the factors responsible for this phenomenon remain unknown. This study defines the variance annual cycle (VAC) to describe this seasonally dependent intensity structure of high-frequency relative humidity fluctuations. Relative humidity VAC shows a high correlation with low-frequency oscillations of surface wind speed. We examine the instantaneous amplitude-phase correlation map and amplitude modulation (AM) index between surface relative humidity and surface wind speed. We find that the surface wind speed with a period around 140–420 days has a significant amplitude modulation effect on the surface relative humidity with a period of around 2–90 days over most regions in Northeast China, which reveals that the low-frequency oscillations of surface wind speed amplitude modulate on the high-frequency fluctuations of surface relative humidity. To explore the physical mechanism behind this modulation, we examine the monthly mean patterns of the surface wind and sea level pressure fields. The patterns indicate that this amplitude modulation is induced by the evolution and transition of East Asian winter monsoon and summer monsoon.

Label-free photoacoustic computed tomography of mouse cortical responses to retinal photostimulation using a pair-wise correlation map.

The lack of a non-invasive or minimally invasive imaging technique has long been a challenge to investigating brain activities in mice. Functional magnetic resonance imaging and the more recently developed diffuse optical imaging both suffer from limited spatial resolution. Photoacoustic (PA) imaging combines the sensitivity of optical excitation to hemodynamic changes and ultrasound detection's relatively high spatial resolution. In this study, we evaluated the feasibility of using a label-free, real-time PA computed tomography (PACT) system to measure visually evoked hemodynamic responses within the primary visual cortex (V1) in mice. Photostimulation of the retinas evoked significantly faster and stronger V1 responses in wild-type mice than in age-matched rod/cone-degenerate mice, consistent with known differences between rod/cone- vs. melanopsin-mediated photoreception. In conclusion, the PACT system in this study has sufficient sensitivity and spatial resolution to resolve visual cortical hemodynamics during retinal photostimulation, and PACT is a potential tool for investigating visually evoked brain activities in mouse models of retinal diseases.

Molecular dissemination of emerging antibiotic, biocide, and metal co-resistomes in the Himalayan hot springs

Growing resistance among microbial communities against antimicrobial compounds, especially antibiotics, is a significant threat to living beings. With increasing antibiotic resistance in human pathogens, it is necessary to examine the habitats having community interests. In the present study, a metagenomic approach has been employed to understand the causes, dissemination, and effects of antibiotic, metal, and biocide resistomes on the microbial ecology of three hot springs, Borong, Lingdem, and Yumthang, located at different altitudes of the Sikkim Himalaya. The taxonomic assessment of these hot springs depicted the predominance of mesophilic organisms, mainly belonging to the phylum Proteobacteria. The enriched microbial metabolism assosiated with energy, cellular processes, adaptation to diverse environments, and defence were deciphered in the metagenomes. The genes representing resistance to semisynthetic antibiotics, e.g., aminoglycosides, fluoroquinolones, fosfomycin, vancomycin, trimethoprim, tetracycline, streptomycin, beta-lactams, multidrug resistance, and biocides such as triclosan, hydrogen peroxide, acriflavin, were abundantly present. Various genes attributing resistance to copper, arsenic, iron, and mercury in metal resistome were detected. Relative abundance, correlation, and genome mapping of metagenome-assembled genomes indicated the co-evolution of antibiotic and metal resistance in predicted novel species belonging to Vogesella, Thiobacillus, and Tepidimona genera. The metagenomic findings were further validated with isolation of microbial cultures, exhibiting resistance against antibiotics and heavy metals, from the hot spring water samples. The study furthers our understanding about the molecular basis of co-resistomes in the ceological niches and their possible impact on the environment.

The molecular docking and molecular dynamics study of flavonol synthase and flavonoid 3’-monooxygenase enzymes involved for the enrichment of kaempferol

Kaempferol is a natural flavonol that shows many pharmacological properties including anti-inflammatory, antioxidant, anticancer, antidiabetic activities etc. It has been reported in many vegetables, fruits, herbs and medicinal plants. The enzyme flavonol synthase (FLS, EC 1.14.20.6) catalyses the conversion of dihydroflavonols to flavonols. Whereas flavonoid 3’-monooxygenase (F3’H, EC 1.14.14.82) catalyses the hydroxylation of dihydroflavonol, and flavonol. FLS is involved in the synthesis of the kaempferol whereas F3’H causes degradation of kaempferol. The present study aimed to analyse the binding affinity, stability and activating activity of enzyme FLS as well as inhibitory activity of enzyme F3’H involved in the enrichment of the kaempferol using the in-silico approaches. Computational study for physico-chemical properties, conserved domain identification, 3-D structure prediction and its validation, conservation analysis, molecular docking followed by molecular dynamics analysis of FLS and F3’H, protein-activator (FLS-LIG Complex) and protein-inhibitor (F3’H-LIG Complex) complexes have been performed. Other structural analyses like root mean square fluctuation (RMSF), root mean square deviation (RMSD), surface area solvent accessibility (SASA), radius of gyration (Rg), hydrogen bond analysis, principal component analysis (PCA), Poisson-Boltzmann analysis (MM_PBSA) and the dynamic cross correlation map (DCCM) analysis to explore the structural, functional and thermodynamic stability of the proteins and the complexes were also studied. The molecular docking result showed that FLS binds strongly with the activator ascorbate (CID _54670067) while F3’H binds with the inhibitor ketoconazole (CID_456201). The most powerful inhibitor (ketoconazole for F3’H) and activator (ascorbate for FLS) is determined by computing the thermodynamic binding free energy through MM_PBSA analysis. The current work provides wide-ranging structural and functional information about FLS and F3’H enzymes showing detailed molecular mechanism of kaempferol biosynthesis and its degradation and hence kaempferol enrichment. Finding of the present work opens up new possibilities for future research towards enrichment of kaempferol by using activator (ascorbate) for FLS and inhibitor (ketoconazole) for F3’H as well as for its large-scale production using in vitro approaches. Communicated by Ramaswamy H. Sarma

Identification of Orthotropic Elastic Properties of Wood by a Synthetic Image Approach Based on Digital Image Correlation.

This work aims to determine the orthotropic linear elastic constitutive parameters of Pinus pinaster Ait. wood from a single uniaxial compressive experimental test, under quasi-static loading conditions, based on two different specimen configurations: (a) on-axis rectangular specimens oriented on the radial-tangential plane, (b) off-axis specimens with a grain angle of about 60° (radial-tangential plane). Using digital image correlation (DIC), full-field displacement and strain maps are obtained and used to identify the four orthotropic elastic parameters using the finite element model updating (FEMU) technique. Based on the FE data, a synthetic image reconstruction approach is proposed by coupling the inverse identification method with synthetically deformed images, which are then processed by DIC and compared with the experimental results. The proposed methodology is first validated by employing a DIC-levelled FEA reference in the identification procedure. The impact of the DIC setting parameters on the identification results is systematically investigated. This influence appears to be stronger when the parameter is less sensitive to the experimental setup used. When using on-axis specimen configuration, three orthotropic parameters of Pinus pinaster (, and ) are correctly identified, while the shear modulus () is robustly identified when using off-axis specimen configuration.

Molecular-scale deformation of glass-fiber-reinforced polypropylene probed by rheo-optical Fourier transform infrared imaging combined with a two-trace two-dimensional correlation technique

The molecular-scale deformation behavior of glass-fiber-reinforced polypropylene was probed by a newly developed rheo-optical Fourier transform infrared (FTIR) imaging technique combined with two-trace two-dimensional correlation mapping. This technique, based on an in situ polarized FTIR microscopic analysis, revealed variations in the polymer orientation during tensile deformation. The analyses of composites containing single fibers aligned parallel and perpendicular to the elongation direction clearly revealed that the addition of maleic anhydride-grafted polypropylene (MAPP) restricts the polymer mobility at the matrix–fiber interface and inhibits interfacial debonding during the elongation process. Namely, matrix–fiber adhesion was improved by the compatibilizing effects of MAPP, which in turn contributed to enhanced mechanical properties resulting from the efficient stress transfer and reduction in fracture formation at the matrix–fiber interface. This study demonstrates that the rheo-optical technique can provide a better understanding of the reinforcement mechanism of glass-fiber-reinforced thermoplastics related to interfacial states.

Characterization of porous media by nuclear magnetic resonance beyond fast diffusion limit with numerical simulation

Nuclear magnetic resonance logging is an important formation detection technique in the petroleum industry, which is always used to detect formation pore structure and fluid identification. However, conventional nuclear magnetic resonance characterization methods assume that the formation pore medium are in fast diffusion regime. In complex formations, non-fast diffusion regimes (intermediate diffusion and slow diffusion) are also present. In the previous paper [13], a new method for characterizing porous media with non-fast diffusion regime and uniform pore size distribution by T2-T2 pulse sequence is proposed. In this research, the T2-T2 signals of periodic stacked pore models beyond fast diffusion regime are numerically simulated by the random walk algorithm, and the pore size - surface relaxivity maps are respectively inverted, the relationship between pore structure and correlation maps are discussed. The results provide theoretical foundation for characterizing pore structure beyond fast diffusion limit.

Spatiotemporal Reflectance Fusion via Tensor Sparse Representation

Tradeoffs between the spatial and temporal resolutions of current satellite instruments limit our ability to conduct high-quality and continuous monitoring of the earth’s surface dynamics. Spatiotemporal image fusion has become increasingly necessary to obtain remote sensing images with high spatiotemporal resolution. However, current learning-based methods concentrate on predicting images only from spatial similarity and neglect spectral correlations of remote sensing images, leading to significant spectral information loss. In this article, we develop a novel nonlocal tensor sparse representation-based semicoupled dictionary learning approach (SCDNTSR) for spatiotemporal fusion. In the SCDNTSR method, the spectral correlation and the spatial similarity of the nonlocal similar cubes are simultaneously exploited through the tensor–tensor product-based tensor sparse representation. Furthermore, the semicoupled mapping prior knowledge of sparse coefficients across the high- and low-spatial resolution (HSR\LSR) image spaces is exploited with the coupled dictionary to constrain the similarity of sparse coefficients to improve the prediction performance. In addition, to capture additional prior spatial information, the SCDNTSR provides a new method to determine the degradation relationship between the target HSR and LSR difference images with the help of the known HSR and LSR difference images. The proposed SCDNTSR method was tested on real datasets at both the Coleambally Irrigation Area study site and the Lower Gwydir Catchment study site. Results show that the proposed method outperforms five state-of-the-art methods, especially in maintaining the spectral information, proving the feasibility of integrating the degradation relationship, spatio-spectral-nonlocal correlation, and semicoupled mapping priors of the multisource data into the proposed model.

Wavelet-Based Texture Reformation Network for Image Super-Resolution.

Most reference-based image super-resolution (RefSR) methods directly leverage the raw features extracted from a pretrained VGG encoder to transfer the matched texture information from a reference image to a low-resolution image. We argue that simply operating on these raw features neglects the influence of irrelevant and redundant information and the importance of abundant high-frequency representations, leading to undesirable texture matching and transfer results. Taking the advantages of wavelet transformation, which represents the contextual and textural information of features at different scales, we propose a Wavelet-based Texture Reformation Network (WTRN) for RefSR. We first decompose the extracted texture features into low-frequency and high-frequency sub-bands and conduct feature matching on the low-frequency component. Based on the correlation map obtained from the feature matching process, we then separately swap and transfer wavelet-domain features at different stages of the network. Furthermore, a wavelet-based texture adversarial loss is proposed to make the network generate more visually plausible textures. Experiments on four benchmark datasets demonstrate that our proposed method outperforms previous RefSR methods both quantitatively and qualitatively. The source code is available at https://github.com/zskuang58/WTRN-TIP.

Magnetic coupling and spin ordering in bisdithiazolyl, thiaselenazolyl, and bisdiselenazolyl molecular materials.

The use of purely organic materials is a promising approach for the miniaturization of devices due to their interesting optical, electronic and magnetic properties. Bisdithiazolyl-based bisDTA compounds have emerged as promising candidates for radical-based single component conductors exhibiting simultaneously magnetic properties. Our computational work focuses on the intriguing magnetism of 4 isostructural pyridine-bridged bisDTA-multifunctional materials triggered by their magnetic and conducting properties being strongly dependent on the different S/Se ratios in the neutral radical skeleton: specifically, bisdithiazolyl (S,S) displays no magnetic order at low temperatures, thiaselenazolyl (Se,S) exhibits spin-canted antiferromagnetism (AFM), and both (S,Se) and bisdiselenazolyl (Se,Se) behave as bulk ferromagnets (FM). Our results reveal that (1) the magnetic response depends on the existence of an intricate network of both AFM and FM spin exchange JAB couplings between neighbouring radicals; and (2) the structural arrangement of π-stacked pairs of radicals sits on a point in the configurational space that is very close to a crossover region where JAB switches from AFM to FM. Indeed, for bulk FM, the experimental response is only accounted for when considering an ab initio optimised crystal structure able to portray adequately the electronic structure of bisDTAs in the region close to the temperature at which magnetic ordering emerges. Magneto-structural correlation maps show the large sensitivity of JAB to very small structural changes with temperature along the π-stacks that lead to drastic changes in the magnetic properties. Clearly, the understanding of magnetism in the title bisDTA compounds is decisive to rationally tailor the properties of multifunctional materials by subtle structural modifications of their crystal packing.