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Background and Aims: Porto‐sinusoidal vascular disease (PSVD) is an under‐recognized and under‐diagnosed disease. The purpose of this study was to investigate the clinical features and prognosis of PSVD. Methods: The patients who underwent liver biopsies were analyzed retrospectively. The clinical and pathological data were reviewed and screened according to the latest diagnostic criteria of PSVD. Results: A total of 234 patients were diagnosed as PSVD, including 103 patients presented with portal hypertension (PH) and 131 patients without PH. At baseline, the alanine aminotransferase (ALT) and γ‐glutamyl transpeptidase (GGT) levels were higher in the no‐PH group. The liver stiffness increased in the PH group. In histological review, obliterative portal venopathy, sinusoidal dilatation and architectural disturbance were more common in the PH group, while portal tract abnormalities were more widely distributed in the no‐PH group. After a median follow‐up of 43.6 months, the survival rate of patients with baseline liver decompensation was 76.0%, and that of patients at a liver compensated stage in the PH group was 98.7%. First variceal bleeding occurred in 13.8% of patients with gastric‐oesophageal varices. None of the patients in the no‐PH group developed portal hypertension during follow‐up. Conclusions: PSVD can manifest as PH or mild liver enzyme abnormalities. There are significant differences in pathological features among patients with different clinical manifestations. Recurrent ascites are the main cause of death in PSVD patients. However, patients without PH have a slow disease progression, with recurrent elevated GGT levels being their main clinical feature. [ABSTRACT FROM AUTHOR]

To elucidate the brain‐wide information interactions that vary and contribute to individual differences in schizophrenia (SCZ), an information‐resolved method is employed to construct individual synergistic and redundant interaction matrices based on regional pairwise BOLD time‐series from 538 SCZ and 540 normal controls (NC). This analysis reveals a stable pattern of regionally‐specific synergy dysfunction in SCZ. Furthermore, a hierarchical Bayesian model is applied to deconstruct the patterns of whole‐brain synergy dysfunction into three latent factors that explain symptom heterogeneity in SCZ. Factor 1 exhibits a significant positive correlation with Positive and Negative Syndrome Scale (PANSS) positive scores, while factor 3 demonstrates significant negative correlations with PANSS negative and general scores. By integrating the neuroimaging data with normative gene expression information, this study identifies that each of these three factors corresponded to a subset of the SCZ risk gene set. Finally, by combining data from NeuroSynth and open molecular imaging sources, along with a spatially heterogeneous mean‐field model, this study delineates three SCZ synergy factors corresponding to distinct symptom profiles and implicating unique cognitive, neurodynamic, and neurobiological mechanisms. [ABSTRACT FROM AUTHOR]

BACKGROUND: Bacillus, as a plant–growth‐promoting rhizobacteria, can enhance the resistance of plants to phytopathogens. In our study, Bacillus strains showing excellent biocontrol were screened and used to control ginkgo leaf blight (Alternaria tenuissima). RESULTS: Four biocontrol Bacillus strains—Bsa537, Bam337, Bso544, and Bsu503—were selected from 286 isolates based on their capacity to inhibit pathogens and promote plant growth. The four Bacillus strains significantly improved the resistance of ginkgo to leaf blight. This was especially the case when the four strains were used as a mixture, which contributed to a decrease in lesion area of >40%. Hence, a mixture of Bacillus strains was used to control ginkgo leaf blight in the field. Treatment efficiency varied from 30% to 100% (average 81.5%) and was higher than that of the control (−2% to −18%, average − 8.5%); the antioxidant capacity of the treated ginkgo was also stronger. In addition, ginkgo biomass increased as a result of treatment with the Bacillus mixture, including leaf weight, area, thickness, number of lateral roots and root weight. Furthermore, the Bacillus mixture improved the ginkgo rhizosphere soil by boosting the number of beneficial microorganisms, lowering the number of pathogens and hastening soil catabolism. CONCLUSION: The Bacillus mixture improved the health status of ginkgo by protecting it from pathogen attack, promoting its growth and improving the microorganism community in the rhizosphere. This work closes a technological gap in the biological control of ginkgo leaf blight, investigates application methods for compound Bacillus biofertilizers and establishes a framework for the popularity and commercialization of these products. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The goal of this study was to exploit the excellent spatial resolution characteristics of a position-sensitive silicon photomultiplier (SiPM) and develop a high-resolution depth-of-interaction (DOI) encoding positron emission tomography (PET) detector module. The detector consists of a 30  ×  30 array of 0.445  ×  0.445  ×  20 mm3 polished LYSO crystals coupled to two 15.5  ×  15.5 mm2 linearly-graded SiPM (LG-SiPM) arrays at both ends. The flood histograms show that all the crystals in the LYSO array can be resolved. The energy resolution, the coincidence timing resolution and the DOI resolution were 21.8  ±  5.8%, 1.23  ±  0.10 ns and 3.8  ±  1.2 mm, respectively, at a temperature of -10 °C and a bias voltage of 35.0 V. The performance did not degrade significantly for event rates of up to 130 000 counts s-1. This detector represents an attractive option for small-bore PET scanner designs that simultaneously emphasize high spatial resolution and high detection efficiency, important, for example, in preclinical imaging of the rodent brain with neuroreceptor ligands.

An accurate system matrix is essential in positron emission tomography (PET) for reconstructing high quality images. To reduce storage size and image reconstruction time, we factor the system matrix into a product of a geometry projection matrix and a sinogram blurring matrix. The geometric projection matrix is computed analytically and the sinogram blurring matrix is estimated from point source measurements. Previously, we have estimated a 2-D blurring matrix for a preclinical PET scanner. The 2-D blurring matrix only considers blurring effects within a transaxial sinogram and does not compensate for inter-sinogram blurring effects. For PET scanners with a long axial field of view, inter-sinogram blurring can be a major problem influencing the image quality in the axial direction. Hence, the estimation of a 4-D blurring matrix is desirable to further improve the image quality. The 4-D blurring matrix estimation is an ill-conditioned problem due to the large number of unknowns. Here, we propose a rank-one approximation for each blurring kernel image formed by a row vector of the sinogram blurring matrix to improve the stability of the 4-D blurring matrix estimation. The proposed method is applied to the simulated data as well as the real data obtained from an Inveon microPET scanner. The results show that the newly estimated 4-D blurring matrix can improve the image quality over those obtained with a 2-D blurring matrix and requires less point source scans to achieve similar image quality compared with an unconstrained 4-D blurring matrix estimation.

The leading edge timing pick-off technique is the simplest timing extraction method for PET detectors. Due to the inherent time-walk of the leading edge technique, corrections should be made to improve timing resolution, especially for time-of-flight PET. Time-walk correction can be done by utilizing the relationship between the threshold crossing time and the event energy on an event by event basis. In this paper, a time-walk correction method is proposed and evaluated using timing information from two identical detectors both using leading edge discriminators. This differs from other techniques that use an external dedicated reference detector, such as a fast PMT-based detector using constant fraction techniques to pick-off timing information. In our proposed method, one detector was used as reference detector to correct the time-walk of the other detector. Time-walk in the reference detector was minimized by using events within a small energy window (508.5 - 513.5 keV). To validate this method, a coincidence detector pair was assembled using two SensL MicroFB SiPMs and two 2.5 mm × 2.5 mm × 20 mm polished LYSO crystals. Coincidence timing resolutions using different time pick-off techniques were obtained at a bias voltage of 27.5 V and a fixed temperature of 20 °C. The coincidence timing resolution without time-walk correction were 389.0 ± 12.0 ps (425 -650 keV energy window) and 670.2 ± 16.2 ps (250-750 keV energy window). The timing resolution with time-walk correction improved to 367.3 ± 0.5 ps (425 - 650 keV) and 413.7 ± 0.9 ps (250 - 750 keV). For comparison, timing resolutions were 442.8 ± 12.8 ps (425 - 650 keV) and 476.0 ± 13.0 ps (250 - 750 keV) using constant fraction techniques, and 367.3 ± 0.4 ps (425 - 650 keV) and 413.4 ± 0.9 ps (250 - 750 keV) using a reference detector based on the constant fraction technique. These results show that the proposed leading edge based time-walk correction method works well. Timing resolution obtained using this method was equivalent to that obtained using a reference detector and was better than that obtained using constant fraction discriminators.