Petrocodonliboensis (Gesneriaceae), a new species from Guizhou, China.

Petrocodonliboensis Sheng H.Tang & Jia W.Yang is a new species of Gesneriaceae from Guizhou, southwestern China. The new taxon has a pale-yellow corolla and is most similar to P.luteoflorus. However, it differs from the latter by having a urceolate (vs. cannulate) corolla tube, an abaxial corolla lip 0.8-1.1 mm (vs. 2-2.2 mm) long, and filaments 1.5-1.7 mm (vs. ca. 7 mm) long that are straight (vs. S-shaped or geniculate near the middle). The new taxon is assessed as "Data Deficient" (DD) according to the IUCN standards.

A novel insight of degradation ibuprofen in aqueous by catalytic ozonation with supported catalyst: Supports effect on ozone mass transfer.

Catalytic ozonation is an effective wastewater purification process. However, the low ozone mass transfer in packed bubble columns leads to low ozone utilization efficiency (OUE), poor organic degradation performance, and high energy consumption. Therefore, there is an urgent need to develop efficient supported catalysts that can enhance mass transfer and performance. However, the reaction mechanism of the support on ozone mass transfer remains unclear, which hinders the development of catalytic ozonation applications. In this study, lava rocks (LR)-supported catalysts, specifically CuMn2O4@LR and MnO2Co3O4@LR, were proposed for catalytic ozonation of IBP degradation due to their superior catalytic activity, stability, and high OUE. Addition of CuMn2O4@LR or MnO2Co3O4@LR increased IBP removal efficiency from 85% to 91% or 88%, and reduced energy consumption from 2.86 to 2.14 kWh/m3 or 2.60 kWh/m3, respectively. This improvement was attributed to LR-supported catalysts enhancing mass transfer and promoting O3 decomposition to generate •OH and •O2-, leading to IBP degradation. Furthermore, this study investigated the effects of ozone dose, supporter sizes, and catalyst components on ozone-liquid mass transfer. The results revealed that the size of the supporter influenced stacked porosity and consequently affected ozone mass transfer. Larger-sized LR (kLa= 0.172 min-1) exhibited better mass transfer compared to smaller-sized supports. Based on these findings, it was concluded that both CuMn2O4@LR and MnO2Co3O4@LR are potential catalysts for catalytic ozonation in residual IBP degradation of pharmaceutical wastewater, and LR showed good credibility as a catalyst supporter. Understanding the effects of supporters and active components on ozone mass transfer provides a fundamental principle for designing supported catalysts in catalytic ozonation applications.

Combined clinical significance of MRI and serum mannose-binding lectin in the prediction of spinal tuberculosis.

BACKGROUND: Spinal tuberculosis (STB) is a local manifestation of systemic infection caused by Mycobacterium tuberculosis, accounting for a significant proportion of joint tuberculosis cases. This study aimed to explore the diagnostic value of MRI combined with mannose-binding lectin (MBL) for STB. METHODS: 124 patients suspected of having STB were collected and divided into STB and non-STB groups according to their pathological diagnosis. Serum MBL levels were measured using ELISA and a Pearson analysis was constructed to determine the correlation between MBL and STB. ROC was plotted to analyze their diagnostic value for STB. All the subjects included in the study underwent an MRI. RESULTS: The sensitivity of MRI for the diagnosis of STB was 84.38% and specificity was 86.67%. The serum MBL levels of the patients in the STB group were significantly lower than the levels in the non-STB group. ROC analysis results indicated that serum MBL's area under the curve (AUC) for diagnosis of STB was 0.836, with a sensitivity of 82.3% and a specificity was 77.4%. The sensitivity of MRI combined with MBL diagnosis was 96.61%, and the specificity was 92.31%, indicating that combining the two diagnostic methods was more effective than using either one alone. CONCLUSIONS: Both MRI and MBL had certain diagnostic values for STB, but their combined use resulted in a diagnostic accuracy than either one alone.

Online Compositional Analysis of Complex Oligomers in Biomass Degradation by High-Pressure Flow-Through Reactor Coupled with High-Resolution Mass Spectrometry.

Online analysis of the composition and evolution of complex oligomeric intermediates in biomass degradation is highly desirable to elucidate the mechanism of bond cleavage and study the effect of conditions on the selective conversion of feedstocks. However, harsh reaction conditions and complicated conversion systems pose tremendous challenges for conventional, state-of-the-art analytical techniques. Herein, we introduce a continuous and rapid compositional analysis strategy coupling a high-pressure flow-through reactor with online high-resolution mass spectrometry, which enables the molecular-level characterization of most biomass-related products throughout the conversion for over 2 h. Catalytic depolymerization of one model compound was studied, and temperature-dependent data of over 50 intermediates as well as recondensation dimers and oligomers were obtained, which have rarely been reported in the literature. Thousands of products during the flow-through conversion of birch wood with molecular weights up to 1000 Da were presented, and 8 typical lignin dimers and oligomers with various interunit linkages were identified at the molecular level, demonstrating the potential to analyze more complicated systems far beyond conventional methods, especially for complex oligomers. The continuous evolutions of different components and typical products were unveiled for the first time, providing valuable insights into the investigation of the structure, composition, and decomposition mechanism of lignocellulose as well as the influence of reaction conditions. This method leads to the previously unattained ability to probe and reveal complicated chemical compositions in high-pressure reactions and can be applied to all other high-pressure heterogeneous aqueous reactions.

Anti-Interleukin 17A Biologic Therapy Attempts on Livedoid Vasculopathy: A Report of Case Series.

The application of biologics such as anti-tumor necrosis factor (TNF) has shown great efficacy in livedoid vasculopathy (LV). However, new biological options need to be identified for those with a high tuberculosis reactivation risk. In this study, we evaluated the efficacy of anti-17A biologics for LV therapy. Two patients with LV who were irresponsive to traditional anticoagulation therapy were studied at the outpatient dermatology clinic of Peking Union Medical College Hospital. All patients received anti-17A biological therapy for at least two-four weeks. Both patients reported an exacerbation of the skin lesions, which might indicate that the IL-17 pathway plays a critical role in LV pathogenesis.

Multiview Tensor Spectral Clustering via Co-regularization.

Graph-based multi-view clustering encodes multi-view data into sample affinities to find consensus representation, effectively overcoming heterogeneity across different views. However, traditional affinity measures tend to collapse as the feature dimension expands, posing challenges in estimating a unified alignment that reveals both crossview and inner relationships. To tackle this challenge, we propose to achieve multi-view uniform clustering via consensus representation coregularization. First, the sample affinities are encoded by both popular dyadic affinity and recent high-order affinities to comprehensively characterize spatial distributions of the HDLSS data. Second, a fused consensus representation is learned through aligning the multi-view lowdimensional representation by co-regularization. The learning of the fused representation is modeled by a high-order eigenvalue problem within manifold space to preserve the intrinsic connections and complementary correlations of original data. A numerical scheme via manifold minimization is designed to solve the high-order eigenvalue problem efficaciously. Experiments on eight HDLSS datasets demonstrate the effectiveness of our proposed method in comparison with the recent thirteen benchmark methods.

Risk factors and early detection of joint damage in patients with psoriasis: a case-control study.

BACKGROUND: Our aim was to target the unsatisfied need for early detection of the at-risk population and determine the subgroup of patients whose psoriasis (PsO) could transform into psoriatic arthritis (PsA). METHODS: A retrospective and longitudinal case-control study was conducted at Beijing Chao-yang Hospital. It included 75 patients who were clinically diagnosed with PsA in the case group and 345 who solely suffered from PsO without PsA in the control group. A variety of baseline covariates were gathered from every patient with PsO. Univariate and multivariate analyses and receiver operating characteristic (ROC) curves were used to identify underlying risk factors and determine whether it was necessary to examine the imaging of PsO patients. RESULTS: In multivariate logistic regression analysis, age ≥40 (odds ratio (OR): 1.04, 95% confidence interval (CI): 1.02-1.06, P < 0.01), nail involvement (OR: 1.17, 95% CI: 1.09-1.32, P < 0.01), erythrocyte sedimentation rate (ESR) (OR: 1.03, 95% CI: 1.01-1.06, P < 0.05) and elevated high-sensitivity C-reactive protein (hs-CRP) (OR: 1.31, 95% CI: 1.13-1.53, P < 0.01) were perceived to be risk factors for the transformation from PsO into clinical PsA. By combining magnetic resonance imaging (MRI)-detected enthesitis with tenosynovitis, combined predictors demonstrated better diagnostic efficacy, with an improvement in specificity (94.3% vs. 69%) and similarities in sensitivity (89% vs. 84.6%). The areas under the ROC curve (AUCs) amounted to 0.925 (95% CI: 0.882-0.967, P < 0.01) and 0.858 (95% CI: 0.814-0.903, P < 0.01). CONCLUSIONS: It was identified that age ≥40, nail involvement, as well as an elevated ESR, and hs-CRP served as independent risk factors for PsO transforming into PsA. Additionally, MRI provides additional value for the early recognition of PsA.

Review: The application of source analysis methods in tracing urban non-point source pollution: categorization, hotspots, and future prospects.

The contribution of urban non-point source (NPS) pollution to surface water pollution has gradually increased, analyzing the sources of urban NPS pollution is of great significance for precisely controlling surface water pollution. A bibliometric analysis of relevant research literature from 2000 to 2021 reveals that the main methods used in the source analysis research of urban NPS pollution include the emission inventory approach, entry-exit mass balance approach, principal component analysis (PCA), positive matrix factorization (PMF) model, etc. These methods are primarily applied in three aspects: source analysis of rainfall-runoff pollution, source analysis of wet weather flow (WWF) pollution in combined sewers, and analysis of the contribution of urban NPS to the surface water pollution load. The application of source analysis methods in urban NPS pollution research has demonstrated an evolution from qualitative to quantitative, and further towards precise quantification. This progression has transitioned from predominantly relying on on-site monitoring to incorporating model simulations and employing mathematical statistical analyses for traceability. This paper reviews the principles, advantages, disadvantages, and the scope of application of these methods. It also aims to address existing problems and analyze potential future development directions, providing valuable references for subsequent related research.

Predictors of quitting support from nonsmoking mothers for smoking fathers: a cross-sectional study from Chinese pupils' families.

BACKGROUND: Quitting support from smokers' partners can predict quit attempts and smoking abstinence but research on factors that predict such support has been limited. To add more evidence for partner support and the improved interventions for smoking cessation, we analyzed some new potential predictors of quitting support from smokers' spouses. METHOD: This cross-sectional study was conducted in in 2022 and 2023, selecting the students' families in which fathers smoked and mothers didn't smoke from grade 1-5 of 13 primary schools in Qingdao, China. Parents who met the criteria completed the online questionnaires and 1018 families were included in the analysis. We measured personal information related to smokers and their spouses such as age, education and nicotine dependence, and variables related to family and marital relationship such as family functioning, perceived responsiveness and power in decision-making of quitting smoking. Quitting support from smokers' spouses was measured by Partner Interaction Questionnaire and generalized linear model was used to explore the potential predictors of partner support. RESULTS: In this study, the mean age of smokers was 39.97(SD = 5.57) and the mean age of smokers' spouses was 38.24(SD = 4.59). The regression analysis showed that for smokers and their spouses, the older age groups showed the lower ratio of positive/negative support(P < 0.05) and smokers with high education showed the less positive and negative partner support(P < 0.05). Nicotine dependence was positively associated with negative support (ß = 0.120, P < 0.01), and perceived responsiveness (ß = 0.124, P < 0.05) as well as family functioning (ß = 0.059, P < 0.05) was positively associated with positive support. These three factors were associated with ratio of positive/negative support(P < 0.05). In addition, power of smoker's spouse in decision-making of quitting smoking was positively associated with the positive (ß = 0.087, P < 0.001) and negative support (ß = 0.084, P < 0.001). CONCLUSIONS: Nicotine dependence, family functioning, power in decision-making of quitting smoking and perceived responsiveness were found to be the predictors of quitting support from smokers' spouses. By incorporating predictors of partner support and integrating some established theories that can improve family functioning and marital relationships, smoking cessation interventions can be further improved.

Efficient treatment of veterinary pharmaceutical industrial wastewater by catalytic ozonation process: degradation of enrofloxacin via molecular ozone reactions.

The study focused on the efficacious performance of bimetallic Fe-Zn loaded 3A zeolite in catalytic ozonation for the degradation of highly toxic veterinary antibiotic enrofloxacin in wastewater of the pharmaceutical industry. Batch experiments were conducted in a glass reactor containing a submerged pump holding catalyst pellets at suction. The submerged pump provided the agitation and recirculation across the solution for effective contact with the catalyst. The effect of ozone flow (0.8-1.55 mg/min) and catalyst dose (5-15 g/L) on the enrofloxacin degradation and removal of other conventional pollutants COD, BOD5, turbidity was studied. In batch experiments, 10 g of Fe-Zn 3A zeolite efficiently removed 92% of enrofloxacin, 77% of COD, 69% BOD5, and 61% turbidity in 1 L sample of pharmaceutical wastewater in 30 min at 1.1 mg/min of O3 flow. The catalytic performance of Fe-Zn 3A zeolite notably exceeded the removal efficiencies of 52%, 51%, 52%, and 59% for enrofloxacin, COD, BOD5, and turbidity, respectively, achieved with single ozonation process. Furthermore, an increase in the biodegradability of treated pharmaceutical industrial wastewater was observed and made biodegradable easily for subsequent treatment.

Continuous renal replacement therapy improves indicators and short-term survival in people with AIDS manifesting sepsis and acute kidney injury.

Acquired immune deficiency syndrome (AIDS) is susceptible to numerous complications such as sepsis and acute kidney injury (AKI), leading to adverse outcomes. Continuous renal replacement therapy (CRRT) is becoming increasingly popular in the treatment of sepsis and AKI. This study aimed to verify the effectiveness of CRRT in the treatment of AIDS with sepsis and AKI, to provide new directions for the treatment of severe AIDS. Data of 74 people with AIDS, sepsis and AKI were collected. They were divided into CRRT and non-CRRT groups. There was no difference in indicators between the two groups at admission. Vital signs, PH, serum potassium, renal function, blood lactate, APACHE II score, and SOFA score in CRRT group demonstrated significant improvements over those in the non-CRRT group both 24 and 72 hours after admission (P＜0.05). Level of Interleukin 6 and procalcitonin declined more significantly in CRRT group 72 hours after admission (P＜0.05). CRRT group had a higher 28-day survival rate (P＜0.05). CRRT improves the clinical indicators and increases the short-term survival rate of people with AIDS, sepsis and AKI.

A dual-modal dynamic contour-based method for cervical vascular ultrasound image instance segmentation.

OBJECTIVES: We intend to develop a dual-modal dynamic contour-based instance segmentation method that is based on carotid artery and jugular vein ultrasound and its optical flow image, then we evaluate its performance in comparison with the classic single-modal deep learning networks. METHOD: We collected 2432 carotid artery and jugular vein ultrasound images and divided them into training, validation and test dataset by the ratio of 8:1:1. We then used these ultrasound images to generate optical flow images with clearly defined contours. We also proposed a dual-stream information fusion module to fuse complementary features between different levels extracted from ultrasound and optical flow images. In addition, we proposed a learnable contour initialization method that eliminated the need for manual design of the initial contour, facilitating the rapid regression of nodes on the contour to the ground truth points. RESULTS: We verified our method by using a self-built dataset of carotid artery and jugular vein ultrasound images. The quantitative metrics demonstrated a bounding box detection mean average precision of 0.814 and a mask segmentation mean average precision of 0.842. Qualitative analysis of our results showed that our method achieved smoother segmentation boundaries for blood vessels. CONCLUSIONS: The dual-modal network we proposed effectively utilizes the complementary features of ultrasound and optical flow images. Compared to traditional single-modal instance segmentation methods, our approach more accurately segments the carotid artery and jugular vein in ultrasound images, demonstrating its potential for reliable and precise medical image analysis.

Computational simulation of multi-wavelength light-field thermometry based on a chromatic meta-lens.

This Letter proposes a light-field meta-lens multi-wavelength thermometry (MMT) system that is capable of modulating a full-spectrum incident radiation into four separate wavelength beams. The chromatic meta-lens is designed using finite-difference time-domain (FDTD) software to function as a filter, ensuring its ability to separate four wavelengths. The chromatic meta-lens is positioned on the back focus plane of the main lens to replace the microlens used in traditional light-field systems and simplify the overall system. After detecting the acquired wavelengths and intensities of the image on photodiodes, a raw multispectral image can be decoupled and processed using the Chameleon swarm algorithm (CSA). Four full-spectrum incident radiations corresponding to four temperature characteristic curves are detected. The high accuracy of the reverse temperature calculation enables the measurement of surface high-temperature distribution with precision.

Deep Tensor Spectral Clustering Network via Ensemble of Multiple Affinity Tensors.

Tensor spectral clustering (TSC) is an emerging approach that explores multi-wise similarities to boost learning. However, two key challenges have yet to be well addressed in the existing TSC methods: (1) The construction and storage of high-order affinity tensors to encode the multi-wise similarities are memory-intensive and hampers their applicability, and (2) they mostly employ a two-stage approach that integrates multiple affinity tensors of different orders to learn a consensus tensor spectral embedding, thus often leading to a suboptimal clustering result. To this end, this paper proposes a tensor spectral clustering network (TSC-Net) to achieve one-stage learning of a consensus tensor spectral embedding, while reducing the memory cost. TSC-Net employs a deep neural network that learns to map the input samples to the consensus tensor spectral embedding, guided by a TSC objective with multiple affinity tensors. It uses stochastic optimization to calculate a small part of the affinity tensors, thereby avoiding loading the whole affinity tensors for computation, thus significantly reducing the memory cost. Through using an ensemble of multiple affinity tensors, the TSC can dramatically improve clustering performance. Empirical studies on benchmark datasets demonstrate that TSC-Net outperforms the recent baseline methods.

Extracellular vesicles from keratinocytes and other skin-related cells in psoriasis: A review.

Psoriasis is a highly prevalent chronic inflammatory skin condition involving abnormal proliferation and differentiation of keratinocytes, together with substantial infiltration of immune cells. Extracellular vesicles (EVs), which are released spontaneously into the extracellular space by virtually all cell types, play a crucial role in cell-to-cell communication by delivering bioactive cargos such as mRNA nucleic acids and proteins to recipient cells. Numerous studies have highlighted the significant contributions of EVs to both the pathogenesis and treatment of psoriasis. This review provides a concise overview of skin-derived EVs and their involvement in the pathogenesis of psoriasis.

Immunotyping of peripheral blood lymphocytes by flow cytometry reveals Th cell as a potential prognostic biomarker for extranodal NK/T-cell lymphoma.

This study aimed to explore the distribution, characteristics and prognostic value of baseline peripheral blood lymphocyte subsets in patients with extranodal NK/T-cell lymphoma (NKTCL). We conducted this cross-sectional study of 205 newly-diagnosed NKTCL patients receiving first-line chemotherapy and radiation at our institute between 2010 and 2020. Baseline peripheral blood lymphocytes were detected using flow cytometry, and the clinical value was analyzed. Compared with healthy controls, patients with NKTCL presented with a distinct peripheral immunity with higher levels of cytotoxic CD8+ T cells (33.230 ± 12.090% vs. 27.060 ± 4.010%, p < 0.001) and NKT cells (7.697 ± 7.219% vs. 3.550 ± 2.088%, p < 0.001) but lower proportions of suppressive regulatory T cells (Treg, 2.999 ± 1.949% vs. 3.420 ± 1.051%, p = 0.003) and CD4+ helper T cells (Th, 33.084 ± 11.361% vs. 37.650 ± 3.153%, p < 0.001). Peripheral lymphocytes were differentially distributed according to age, stage, and primary site in patients with NKTCL. The proportion of Th cells/lymphocytes was associated with tumor burden reflected by stage (p = 0.037), serum lactate dehydrogenase (p = 0.0420), primary tumor invasion (p = 0.025), and prognostic index for NK/T-cell lymphoma (PINK) score (p = 0.041). Furthermore, elevated proportions of T cells (58.9% vs. 76.4%, p = 0.005), Th cells (56.3% vs. 68.8%, p = 0.047), or Treg cells (49.5% vs. 68.9%, p = 0.040) were associated with inferior 5-year progression-free survivals (PFS) via univariable survival analysis. Multivariate cox regression revealed elevated Th cells as an independent predictor for unfavorable PFS (HR = 2.333, 95% CI, 1.030-5.288, p = 0.042) in NKTCL. These results suggested the proportion of Th cells positively correlated with tumor burden and was a potential non-invasive biomarker for inferior survival for patients with NKTCL.

Comparison of the properties of phenolic resin synthesized from different aldehydes and evaluation of the release and health risks of VOCs.

Different amounts of glyoxal and paraformaldehyde were used to synthesize phenol-glyoxal (PG) and phenol-paraformaldehyde (PPF) resins, which were compared with conventional phenol-formaldehyde (PF) resins. Glyoxal oxidation leads to a pH value of 9.83 for PG 2.2. With the addition of polyformaldehyde, PPF 2.2 exhibited the highest viscosity at 17333.33 mPa s. The PPF 2.0 plywood has a maximum bonding strength of 1.94 MPa. The formaldehyde emission of PG 1.8 plywood is found to have a minimum value of 0.025 mg/m3, reaching the ENF limit (≤0.025 mg/m3). Acetaldehyde is found only in volatile organic compound (VOC) emissions from PG plywood and is associated with increased glyoxal. PPF plywood emitted more aromatic and total VOC (TVOC) than the other two plywood types. The measured TVOC for PPF 2.2 is 196.07 µg/m3. The results showed that the total cancer risk (TCR) values of PPF 1.8, PPF 2.0, and PG 1.8 were above the threshold of 1.00E-4, indicating a definite carcinogenic risk. Acetaldehyde in the PG plywood exceeded the safety threshold for noncarcinogenic risk. The use of paraformaldehyde in the wood-based panel production is been considered a possible means of improving the bonding strength of plywood. Glyoxal has also been shown to be a viable method for lowering the formaldehyde emissions from plywood. The VOC emissions from plywood changed significantly depending on the aldehyde used. Limiting VOCs that present high health hazards is crucial for reducing the negative impact of plywood on both indoor environments and human health.

Genomic analysis reveals phylogeny of Zygophyllales and mechanism for water retention of a succulent xerophyte.

Revealing the genetic basis for stress-resistant traits in extremophile plants will yield important information for crop improvement. Zygophyllum xanthoxylum, an extant species of the ancient Mediterranean, is a succulent xerophyte that can maintain a favorable water status under desert habitats; however, the genetic basis of this adaptive trait is poorly understood. Furthermore, the phylogenetic position of Zygophyllales, to which Z. xanthoxylum belongs, remains controversial. In this study, we sequenced and assembled the chromosome-level genome of Z. xanthoxylum. Phylogenetic analysis showed that Zygophyllales and Myrtales form a separated taxon as a sister to the clade comprising fabids and malvids, clarifying the phylogenetic position of Zygophyllales at whole-genome scale. Analysis of genomic and transcriptomic data revealed multiple critical mechanisms underlying the efficient osmotic adjustment using Na+ and K+ as "cheap" osmolytes that Z. xanthoxylum has evolved through the expansion and synchronized expression of genes encoding key transporters/channels and their regulators involved in Na+/K+ uptake, transport, and compartmentation. It is worth noting that ZxCNGC1;1 (cyclic nucleotide-gated channels) and ZxCNGC1;2 constituted a previously undiscovered energy-saving pathway for Na+ uptake. Meanwhile, the core genes involved in biosynthesis of cuticular wax also featured an expansion and upregulated expression, contributing to the water retention capacity of Z. xanthoxylum under desert environments. Overall, these findings boost the understanding of evolutionary relationships of eudicots, illustrate the unique water retention mechanism in the succulent xerophyte that is distinct from glycophyte, and thus provide valuable genetic resources for the improvement of stress tolerance in crops and insights into the remediation of sodic lands.