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Spectroscopy and X-ray diffraction techniques encode ample information on investigated samples. The ability of rapidly and accurately extracting these enhances the means to steer the experiment, as well as the understanding of the underlying processes governing the experiment. It improves the efficiency of the experiment, and maximizes the scientific outcome. To address this, we introduce and validate three frameworks based on self-supervised learning which are capable of classifying 1D spectral curves using data transformations preserving the scientific content and only a small amount of data labeled by domain experts. In particular, in this work we focus on the identification of phase transitions in samples investigated by x-ray powder diffraction. We demonstrate that the three frameworks, based either on relational reasoning, contrastive learning, or a combination of the two, are capable of accurately identifying phase transitions. Furthermore, we discuss in detail the selection of data augmentation techniques, crucial to ensure that scientifically meaningful information is retained. [ABSTRACT FROM AUTHOR]

Renal replacement therapy (RRT) is a crucial treatment for sepsis-associated acute kidney injury (S-AKI), but it is uncertain which S-AKI patients should receive immediate RRT. Identifying the characteristics of patients who may benefit the most from RRT is an important task. This retrospective study utilized a public database and enrolled S-AKI patients, who were divided into RRT and non-RRT groups. Uplift modeling was used to estimate the individual treatment effect (ITE) of RRT. The validity of different models was compared using a qini curve. After labeling the patients in the validation cohort, we characterized the patients who would benefit the most from RRT and created a nomogram. A total of 8289 patients were assessed, among whom 591 received RRT, and 7698 did not receive RRT. The RRT group had a higher severity of illness than the non-RRT group, with a Sequential Organ Failure Assessment (SOFA) score of 9 (IQR 6,11) vs. 5 (IQR 3,7). The 28-day mortality rate was higher in the RRT group than the non-RRT group (34.83% vs. 14.61%, p < 0.0001). Propensity score matching (PSM) was used to balance baseline characteristics, 458 RRT patients and an equal number of non-RRT patients were enrolled for further research. After PSM, 28-day mortality of RRT and non-RRT groups were 32.3% vs. 39.3%, P = 0.033. Using uplift modeling, we found that urine output, fluid input, mean blood pressure, body temperature, and lactate were the top 5 factors that had the most influence on RRT effect. The area under the uplift curve (AUUC) of the class transformation model was 0.068, the AUUC of SOFA was 0.018, and the AUUC of Kdigo-stage was 0.050. The class transformation model was more efficient in predicting individual treatment effect. A logistic regression model was developed, and a nomogram was drawn to predict whether an S-AKI patient can benefit from RRT. Six factors were taken into account (urine output, creatinine, lactate, white blood cell count, glucose, respiratory rate). Uplift modeling can better predict the ITE of RRT on S-AKI patients than conventional score systems such as Kdigo and SOFA. We also found that white blood cell count is related to the benefits of RRT, suggesting that changes in inflammation levels may be associated with the effects of RRT on S-AKI patients. [ABSTRACT FROM AUTHOR]

Mitochondrial diseases (MDs) were a large group multisystem disorders, attributable in part to the dual genomic control. The advent of massively sequencing has improved diagnostic rates and speed, and was increasingly being used as a first-line diagnostic test. Paediatric patients (aged < 18 years) who underwent dual genomic sequencing were enrolled in this retrospective multicentre study. We evaluated the mitochondrial disease criteria (MDC) and molecular diagnostic yield of dual genomic sequencing. Causative variants were identified in 177 out of 503 (35.2%) patients using dual genomic sequencing. Forty-six patients (9.1%) had mitochondria-related variants, including 25 patients with nuclear DNA (nDNA) variants, 15 with mitochondrial DNA (mtDNA) variants, and six with dual genomic variants (MT-ND6 and POLG; MT-ND5 and RARS2; MT-TL1 and NARS2; MT-CO2 and NDUFS1; MT-CYB and SMARCA2; and CHRNA4 and MT-CO3). Based on the MDC, 15.2% of the patients with mitochondria-related variants were classified as "unlikely to have mitochondrial disorder". Moreover, 4.5% of the patients with non-mitochondria-related variants and 1.43% with negative genetic tests, were classified as "probably having mitochondrial disorder". Dual genomic sequencing in suspected MDs provided a more comprehensive and accurate diagnosis for pediatric patients, especially for patients with dual genomic variants. [ABSTRACT FROM AUTHOR]

To investigate the predictive value of serum lactate on neurological function impairment and the possible etiology. In this retrospective study, all the adult patients admitted to ICU more than 24 h after general anesthesia elective neurosurgery from January 2018 to January 2019 were recruited. The data of the serum lactate every 8 h during the 24 h of ICU admission were acquired and analyzed. 169 patients were included in the outcomes analysis. The average serum lactate after ICU admission was 3.7(3.4–4.1) mmol/L, higher than normal, and serum lactate elevated commonly after neurosurgery. The serum lactate at ICU admission (lactateserum0h) was not correlated with the outcomes, whereas the predictive value increased as the monitoring time was extended. The result indicated that lactateserum8h, the lactateserum16h, and the lactateserum24h were correlated with the primary outcome (difference of GCS scores before the surgery and after 24 h of ICU admission (ΔGCS24h) (p < 0.05). The lactateserum16h and the lactateserum 24 h were correlated with all the outcomes except for the hospital LOS. The ROC curve suggested that the lactateserum24h achieved the best predictive value. Patients with serum lactate non-recovered trend after 24 h of ICU stay had decreased GCS scores and vice versa, as indicated by the graph of the dynamic changes in the serum lactate. The predictive value of the serum glucose/serum lactate ratio at ICU admission (G/Lserum) was analyzed, and the result indicated that it was correlated with the ΔGCS24h (p < 0.05), the G/Lserum can predict neurological impairment earlier. Dynamic serum lactate monitoring and the G/Lserum at ICU admission have predict value on neurological function impairment after neurosurgery which might be attributed to ACMC. [ABSTRACT FROM AUTHOR]

Among seven species of the order Eulipotyphla (from southern Gansu and northern Sichuan Provinces, Central China) studied cytogenetically, karyotypes of one talpid species, Uropsilus aff. soricipes (2n = 36, NFa = 54), and three soricid species, Chodsigoa hypsibia (2n = 65, NFa = 66), Sorex cansulus (2n = 42, NFa = 64) and Sorex thibetanus (2n = 42, NFa = 60), are described cytogenetically for the first time. All four species are endemic to China with distribution ranges restricted to the Qinghai–Tibet Plateau and adjacent mountain ranges. The Ch. hypsibia karyotype consists of mostly acrocentric autosomes and one metacentric pair of autosomes; besides, a B chromosome was identified. No polymorphism was detected among karyotypes of other species, including shrews Sorex bedfordiae (2n = 26, NFa = 44), Anourosorex squamipes (2n = 48, NFa = 92) and Crocidura suaveolens (2n = 40, NFa = 44). The Chinese shrew mole U. aff. soricipes and three shrew species (S. bedfordiae, Ch. hypsibia and A. squamipes) represent autochthonous fauna of Central/Western China, whereas S. thibetanus, S. cansulus and C. suaveolens belong to phylogenetic groups occurring mostly to the north and west from China; therefore, they should be considered relatively recent colonisers. Thus, considering the relationships of the species within phylogenetic groups, our results on karyotypes are in good agreement with molecular genetic data. [ABSTRACT FROM AUTHOR]

A principle of choice in animal decision-making named probability matching (PM) has long been detected in animals, and can arise from different decision-making strategies. Little is known about how environmental stochasticity may influence the switching time of these different decision-making strategies. Here we address this problem using a combination of behavioral and theoretical approaches, and show, that although a simple Win-Stay-Loss-Shift (WSLS) strategy can generate PM in binary-choice tasks theoretically, budgerigars (Melopsittacus undulates) actually apply a range of sub-tactics more often when they are expected to make more accurate decisions. Surprisingly, budgerigars did not get more rewards than would be predicted when adopting a WSLS strategy, and their decisions also exhibited PM. Instead, budgerigars followed a learning strategy based on reward history, which potentially benefits individuals indirectly from paying lower switching costs. Furthermore, our data suggest that more stochastic environments may promote reward learning through significantly less switching. We suggest that switching costs driven by the stochasticity of an environmental niche can potentially represent an important selection pressure associated with decision-making that may play a key role in driving the evolution of complex cognition in animals. [ABSTRACT FROM AUTHOR]

Idiopathic pulmonary fibrosis (IPF) is a severe disorder leading to progressive and irreversible loss of pulmonary function. In this study we investigated the anti-fibrotic effect of vitamin D using a mouse model of IPF. Lung fibrosis was induced with bleomycin in vitamin D-sufficient and vitamin D-deficient C57BL/6 mice. We found that treatment with active vitamin D analog paricalcitol prevented mouse body weight loss and alleviated lung fibrosis, whereas vitamin D deficiency severely aggravated lung injury. At the molecular level, paricalcitol treatment suppressed the induction of fibrotic inducer TGF-β and extracellular matrix proteins α-SMA, collagen type I and fibronectin in the lung, whereas vitamin D deficiency exacerbated the induction of these proteins. Interestingly, bleomycin treatment activated the local renin–angiotensin system (RAS) in the lung, manifested by the induction of renin, angiotensinogen, angiotensin II and angiotensin receptor type 1 (AT1R). Paricalcitol treatment suppressed the induction of these RAS components, whereas vitamin D deficiency enhanced the activation of the lung RAS. We also showed that treatment of bleomycin-induced vitamin D-deficient mice with AT1R antagonist losartan relieved weight loss, substantially ameliorated lung fibrosis and markedly blocked TGF-β induction in the lung. Moreover, we demonstrated that in lung fibroblast cultures, TGF-β and angiotensin II synergistically induced TGF-β, AT1R, α-SMA, collagen type I and fibronectin, whereas 1,25-dihydroxyvitamin D markedly suppressed the induction of these fibrotic markers. Collectively, these observations strongly suggest that vitamin D mitigates lung fibrosis by blocking the activation of the lung RAS in this mouse model of IPF. [ABSTRACT FROM AUTHOR]