Influence of AngioJet Thrombectomy Combined with Catheter-Contact Thrombolysis on the Therapeutic Effect and Safety of Patients with Lower Extremity Deep Vein Thrombosis.

Objective: To investigate the effect of AngioJet thrombectomy combined with catheter-contact thrombolysis on the therapeutic effect and safety of patients with lower extremity deep vein thrombosis (LEDVT). Methods: 48 patients with LEDVT admitted to our hospital from February 2020 to January 2022 were selected as the study objects and were divided into a control group (n = 24) and research group (n = 24) by random number table method. The control group was treated with catheter-directed thrombolysis (CDT) while the research group was treated with a combination of CDT and AngioJet thrombectomy. The perioperative indicators, symptom improvement, thrombolytic indicators, coagulation function, and the incidence of complications were compared. Results: After treatment, the time of thrombectomy, the total dosage of urokinase, and the length of hospital stay in the research group were all lower than those in the control group (P < .05). After treatment, the peripheral diameter differences of large contralateral crus and calf of the two groups were lower than those before treatment; these peripheral diameter differences of the research group were significantly lower than those of the control group, and the differences were statistically significant (P < .05). After treatment, the venous patency rate, thrombus clearance rate, detumescence rate of the affected limb, and the proportion of grade III in the thrombolysis grade in the research group were all higher than those in the control group. The incidence of complications in the research group after treatment (8.33%) was significantly lower than in the control group (20.83%), with P < .05. Conclusion: AngioJet thrombectomy combined with catheter-contact thrombolysis in the treatment of patients with LEDVT can significantly improve the venous patency rate and thrombolysis rate, regulate the level of coagulation factors, and achieve good thrombolytic effect and safety.

Enhancing C and N turnover, functional bacteria abundance, and the efficiency of biowaste conversion using Streptomyces-Bacillus inoculation.

Microbial inoculation plays a significant role in promoting the efficiency of biowaste conversion. This study investigates the function of Streptomyces-Bacillus Inoculants (SBI) on carbon (C) and nitrogen (N) conversion, and microbial dynamics, during cow manure (10% and 20% addition) and corn straw co-composting. Compared to inoculant-free controls, inoculant application accelerated the compost's thermophilic stage (8 vs 15 days), and significantly increased compost total N contents (+47%) and N-reductase activities (nitrate reductase: +60%; nitrite reductase: +219%). Both bacterial and fungal community succession were significantly affected by DOC, urease, and NH4+-N, while the fungal community was also significantly affected by cellulase. The contribution rate of Cupriavidus to the physicochemical factors of compost was as high as 83.40%, but by contrast there were no significantly different contributions (∼60%) among the top 20 fungal genera. Application of SBI induced significant correlations between bacteria, compost C/N ratio, and catalase enzymes, indicative of compost maturation. We recommend SBI as a promising bio-composting additive to accelerate C and N turnover and high-quality biowaste maturation. SBI boosts organic cycling by transforming biowastes into bio-fertilizers efficiently. This highlights the potential for SBI application to improve plant growth and soil quality in multiple contexts.

Using unsupervised learning to classify inlet water for more stable design of water reuse in industrial parks.

The water reuse facilities of industrial parks face the challenge of managing a growing variety of wastewater sources as their inlet water. Typically, this clustering outcome is designed by engineers with extensive expertise. This paper presents an innovative application of unsupervised learning methods to classify inlet water in Chinese water reuse stations, aiming to reduce reliance on engineer experience. The concept of 'water quality distance' was incorporated into three unsupervised learning clustering algorithms (K-means, DBSCAN, and AGNES), which were validated through six case studies. Of the six cases, three were employed to illustrate the feasibility of the unsupervised learning clustering algorithm. The results indicated that the clustering algorithm exhibited greater stability and excellence compared to both artificial clustering and ChatGPT-based clustering. The remaining three cases were utilized to showcase the reliability of the three clustering algorithms. The findings revealed that the AGNES algorithm demonstrated superior potential application ability. The average purity in six cases of K-means, DBSCAN, and AGNES were 0.947, 0.852, and 0.955, respectively.

Ordered Macro-Microporous Single Crystals of Covalent Organic Frameworks with Efficient Sorption of Iodine.

Fashioning microporous covalent organic frameworks (COFs) into single crystals with ordered macropores allows for an effective reduction of the mass transfer resistance and the maximum preservation of their intrinsic properties but remains unexplored. Here, we report the first synthesis of three-dimensional (3D) ordered macroporous single crystals of the imine-linked 3D microporous COFs (COF-300 and COF-303) via a template-assisted modulated strategy. In this strategy, COFs crystallized within the sacrificial colloidal crystal template, assembled from monodisperse polystyrene microspheres, and underwent an aniline-modulated amorphous-to-crystalline transformation to form large single crystals with 3D interconnected macropores. The effects of the introduced macroporous structure on the sorption performances of COF-300 single crystals were further probed by iodine. Our results indicate that iodine adsorption occurred in micropores of COF-300 but not in the introduced macropores. Accordingly, the iodine adsorption capacity of COF single crystals was governed by their micropore accessibility. The relatively long diffusion path in the non-macroporous COF-300 single crystals resulted in a limited micropore accessibility (48.4%) and thus a low capacity in iodine adsorption (1.48 g·g-1). The introduction of 3D ordered macropores can greatly shorten the microporous diffusion path in COF-300 single crystals and thus render all their micropores fully accessible in iodine adsorption with a capacity (3.15 g·g-1) that coincides well with the theoretical one.

Diagnostic markers and potential therapeutic agents for Sjögren's syndrome screened through multiple machine learning and molecular docking.

Primary Sjögren's syndrome (pSS) is a chronic inflammatory autoimmune disease, which mainly damages patients' exocrine glands. Sensitive early diagnostic indicators and effective treatments for pSS are lacking. Using machine learning methods to find diagnostic markers and effective therapeutic ways for pSS is of great significance. In our study, first, 1643 differentially expressed genes (DEGs; 737 were upregulated and 906 were downregulated) were ultimately screened out and analyzed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes based on the datasets from the Gene Expression Omnibus. Then, support vector machine, least absolute shrinkage and selection operator regression, random forest, and weighted correlation network analysis were used to screen out feature genes from DEGs. Subsequently, the intersection of the feature genes was taken to screen 10 genes as hub genes. Meanwhile, the analysis of the diagnostic efficiency of 10 hub genes showed their good diagnostic value for pSS, which was validated through immunohistochemistry on the paraffin sections of the labial gland. Subsequently, a multi-factor regulatory network and correlation analysis of hub genes were performed, and the results showed that ELAVL1 and IGF1R were positively correlated with each other but both negatively correlated with the other seven hub genes. Moreover, several meaningful results were detected through the immune infiltration landscape. Finally, we used molecular docking to screen potential therapeutic compounds of pSS based on the hub genes. We found that the small molecules DB08006, DB08036, and DB15308 had good docking scores with ELAVL1 and IGF1R simultaneously. Our study might provide effective diagnostic biomarkers and new therapeutic ideas for pSS.

The aryl hydrocarbon receptor in immune regulation and autoimmune pathogenesis.

As a ligand-activated transcription factor, the aryl hydrocarbon receptor (AhR) is activated by structurally diverse ligands derived from the environment, diet, microorganisms, and metabolic activity. Recent studies have demonstrated that AhR plays a key role in modulating both innate and adaptive immune responses. Moreover, AhR regulates innate immune and lymphoid cell differentiation and function, which is involved in autoimmune pathogenesis. In this review, we discuss recent advances in understanding the mechanism of activation of AhR and its mediated functional regulation in various innate immune and lymphoid cell populations, as well as the immune-regulatory effect of AhR in the development of autoimmune diseases. In addition, we highlight the identification of AhR agonists and antagonists that may serve as potential therapeutic targets for the treatment of autoimmune disorders.

Understanding the inter-city causality and regional transport of atmospheric PM2.5 pollution in winter in the Harbin-Changchun megalopolis in China: A perspective from local and regional.

Harbin-Changchun megalopolis (HCM) is the typical cold urban agglomeration in China, where PM2.5 pollution is still serious in winter against the backdrop of continuous improvement in annual air quality in China. To further understand interactions of atmospheric pollution among HCM cities, inter-city causality and regional transport of PM2.5 in the winter in the HCM were comprehensively investigated by using convergent cross mapping (CCM) and CMAQ-BFM methods. CCM analysis results suggest strong bidirectional causal relationships between cities in the HCM, and the causality during polluted episodes were significantly larger than that during clean period. In addition, the influence on local PM2.5 from the HCM western cities were larger than that from cities in the southeast. Inter-city and regional transport contributions results demonstrated that although local emission were the largest contributors among 14 sub-regions for most HCM cities, interactions among cities were strong. Regional transport (42.8%-77.4%) largely contributes to HCM cities' PM2.5 concentrations. Among three regions outside the HCM, NMG (including part of inner Mongolia and Baicheng city in Jilin, 9.1%) was the largest contributor to the PM2.5 concentration in the whole HCM, followed by JLS (including Liaoning Province, Tonghua and Baishan cities in Jilin province, 5.1%) and HLJ (including cities of Heihe, Yichun, Jiamusi, Hegang, Shuangyashan, Jixi, Qitaihe in the Heilongjiang province, 3.8%). Regional transport contribution to the most HCM cities increased significantly from excellent to heavily polluted days. Furthermore, close relationships between transport paths/intensity and wind direction/speed in studied region suggests that we can quantitatively guide the regional joint emergency prevention and control before and during heavily polluted events based on regional weather forecasts in the future.

Why did air quality experience little improvement during the COVID-19 lockdown in megacities, northeast China?

To inhibit the COVID-19 (Coronavirus disease 2019) outbreak, unprecedented nationwide lockdowns were implemented in China in early 2020, resulting in a marked reduction of anthropogenic emissions. However, reasons for the insignificant improvement in air quality in megacities of northeast China, including Shenyang, Changchun, Jilin, Harbin, and Daqing, were scarcely reported. We assessed the influences of meteorological conditions and changes in emissions on air quality in the five megacities during the COVID-19 lockdown (February 2020) using the WRF-CMAQ model. Modeling results indicated that meteorology contributed a 14.7% increment in Air Quality Index (AQI) averaged over the five megacities, thus, the local unfavorable meteorology was one of the causes to yield little improved air quality. In terms of emission changes, the increase in residential emissions (+15%) accompanied by declining industry emissions (-15%) and transportation (-90%) emissions resulted in a slight AQI decrease of 3.1%, demonstrating the decrease in emissions associated with the lockdown were largely offset by the increment in residential emissions. Also, residential emissions contributed 42.3% to PM2.5 concentration on average based on the Integrated Source Apportionment tool. These results demonstrated the key role residential emissions played in determining air quality. The findings of this study provide a scenario that helps make appropriate emission mitigation measures for improving air quality in this part of China.

A study on the analysis of dynamical transmission behavior and mining key monitoring stations in PM and O3 networks in the Beijing-Tianjin-Hebei region of China.

To investigate the dynamical transmission behavior of pollutants and explore the roles played by monitoring stations in regional air pollutants transportation, we constructed a new model for the dynamical transmission index by adopting a statistics model that employs complex network analysis along with terrain data, meteorological variables, and air quality data. The study is conducted in Beijing-Tianjin-Hebei region with 70 stations in 13 cities. The findings indicated that the regional dynamical transmission networks were characterized by the participation of 67 out of 70 stations, as determined by node number. Among the model characteristics, the average path length and the average clustering coefficient, within the ranges of 2.08-2.32 and 0.26-0.51, respectively, maintained reasonable small-world characteristic. For the seasonal transmission features, the networks for PM2.5, PM10 in winter, and O3 in summer shared similar modeling characteristics with those of yearly networks. This suggested that the networks for these two seasons could represent the yearly transmission features. By employing the entropy weight method, the key monitoring stations numbered 1011 A, 1026 A, and 1010 A, which are located in Tianjin, Shijiazhuang, and Beijing, exerted significant impacts on air pollution transmission path in cities. The novel model has demonstrated its soundness and effectiveness in terms of capturing the behavior of transmission as well as the distinguishing roles of these crucial monitoring stations. This methodology could be employed for the construction of additional monitoring stations, identification of possible pollution sources, and prioritization of key pollution areas, thus providing valuable insights for environmental protection and management.

[Application and Progress of Intelligent Assistant Diagnosis in Mental Health Assessment System].

The establishment of mental health assessment system provides a new way for the early diagnosis of mental health problems, in view of the growing population of mental diseases and problems and the uneven distribution of mental health resources. In the mental health assessment system, intelligent assistant diagnosis can assist or help psychiatrists improve their work efficiency. Intelligent assistant diagnosis provides technical support for predictive screening and auxiliary diagnosis of mental health problems. It is an intelligent diagnosis research based on big data analysis and machine learning in mental health assessment system. This article mainly reviews the application methods, the application progress in the field of mental health, as well as related technical issues and safety issues, and prospects the future research development.

RuCoOx Nanofoam as a High-Performance Trifunctional Electrocatalyst for Rechargeable Zinc-Air Batteries and Water Splitting.

Designing high-performance trifunctional electrocatalysts for ORR/OER/HER with outstanding activity and stability for each reaction is quite significant yet challenging for renewable energy technologies. Herein, a highly efficient and durable trifunctional electrocatalyst RuCoOx is prepared by a unique one-pot glucose-blowing approach. Remarkably, RuCoOx catalyst exhibits a small potential difference (ΔE) of 0.65 V and low HER overpotential of 37 mV (10 mA cm-2), as well as a negligible decay of overpotential after 200 000/10 000/10 000 CV cycles for ORR/OER/HER, all of which show overwhelming superiorities among the advanced trifunctional electrocatalysts. When used in liquid rechargeable Zn-air batteries and water splitting electrolyzer, RuCoOx exhibits high efficiency and outstanding durability even at quite large current density. Such excellent performance can be attributed to the rational combination of targeted ORR/OER/HER active sites into one electrocatalyst based on the double-phase coupling strategy, which induces sufficient electronic structure modulation and synergistic effect for enhanced trifunctional properties.

Characteristics of bacterial and fungal communities and their impact during cow manure and agroforestry biowaste co-composting.

Microbial communities and environmental conditions are both of great importance for efficient utilization of agroforestry resources. Nevertheless, knowledge about the role of soluble nutrients and enzymatic properties, and their inner links with microbial communities remain limited. This is especially the case for the co-composting of agricultural and forestry biowaste. Here, we investigate the succession of key microbes during co-composting (sawdust + cow manure, SA; straw + cow manure, ST), employing amplicon sequencing, enzyme assays, and physicochemical analyses. N-fixing bacteria (Pseudomonas) and C-degrading fungi (Acaulium) have been identified as dominant taxa during such co-composting. Although eight antibiotic resistance genes were found to persist during composting, pathogenic microbes declined with composting time. NO3--N content was screened as a determinant structuring the bacterial and fungal communities, with importance also shown for C-degrading enzymes such as cellulose, laccase, and peroxidase activity. These results identify the key microbial taxa and their main interactive environmental factors, which are potentially valuable for the development of a mixed microbial inoculant to accelerate the maturation of agroforestry biowastes composting.

Impact of land cover transformation on urban heat islands in Harbin, China.

At the local and regional climate scale, one of the most studied environmental issues is urban heat island (UHI). UHI is a thermal anomaly caused by temperature differences between urban and rural settings, which adds heat to the atmosphere and makes people feel uncomfortable. This study explores the influence of new land-cover data on UHI simulations using the high-resolution Weather Research and Forecasting (WRF) model coupled with the single-layer urban canopy model (SLUCM) in the city of Harbin. A comparison was performed between the new Tsinghua University (TU) land cover dataset with the default United States Geological Survey (USGS) and Moderate Resolution Imaging Spectroradiometer (MODIS) land cover datasets. The results of this study revealed that the new TU land cover data had better representation and more realistic land cover changes than the default datasets. The diurnal, seasonal, and long-term nighttime UHIs of air and surface temperatures were higher than the daytime UHIs for both downtown Harbin and the satellite towns. We discovered that coal-burning during winter had a significant influence on UHI in Harbin. Moreover, the results from our buffer revealed a rapid increase in the UHIs of satellite towns, thus revealing the need to focus on the effects of UHI in satellite towns in the future. Therefore, the timely updating of land cover datasets in the WRF model and implementing mitigation strategies will help improve the urban climatic comfort.

Assessing the emission sources and reduction potential of atmospheric ammonia at an urban site in Northeast China.

Atmospheric ammonium and ammonia have brought negative environmental impacts and adverse health effects. However, ammonia emissions are generally less regulated worldwide. This study analyzed ammonium pollution character, quantified the dominant ammonia emission sources, and assessed ammonia reduction potential in urban Harbin (China). The results showed that ammonium recorded low concentration in the non-heating season (1.34 ± 1.57 µg/m3), and recorded sharply increased concentration (6.50 ± 7.02 µg/m3) and relative abundance in the heating season. It was closely correlated with vehicle-related pollutants (CO) in non-heating season, while with biomass burning-related pollutants (K+, Cl-) in the heating season. Bayesian Mixing Model emphasized the increasing contribution of biomass burning and decreasing contribution of fertilizer as the pollution levels escalate. The results from the thermodynamic equilibrium model showed that a 50%-60% ammonium decrease could bring marketable decrements of the aerosol pH, aerosol water content, ammonium nitrate concentration, and inorganic ion mass. The results of this study would provide scientific bases for ammonia emission reduction and haze pollution control in urban Harbin.

Impact of climate change on snowmelt runoff in a Himalayan basin, Nepal.

The Hindu Kush Himalaya (HKH) is one of the major sources of fresh water on Earth and is currently under serious threat of climate change. This study investigates the future water availability in the Langtang basin, Central Himalayas, Nepal under climate change scenarios using state-of-the-art machine learning (ML) techniques. The daily snow area for the region was derived from MODIS images. The outputs of climate models were used to project the temperature and precipitation until 2100. Three ML models, including Gated recurrent unit (GRU), Long short-term memory (LSTM), and Recurrent neural network (RNN), were developed for snowmelt runoff prediction, and their performance was compared based on statistical indicators. The result suggests that the mean temperature of the basin could rise by 4.98 °C by the end of the century. The annual average precipitation in the basin is likely to increase in the future, especially due to high monsoon rainfall, but winter precipitation could decline. The annual river discharge is projected to upsurge significantly due to increased precipitation and snowmelt, and no shift in hydrograph is expected in the future. Among three ML models, the LSTM model performed better than GRU and RNN models. In summary, this study depicts severe future climate change in the region and quantifies its effect on river discharge. Furthermore, the study demonstrates the suitability of the LSTM model in streamflow prediction in the data-scarce HKH region. The outcomes of this study will be useful for water resource managers and planners in developing strategies to harness the positive impacts and offset the negative effects of climate change in the basin.

Metabolic signature of eyelid basal cell carcinoma.

PURPOSE: Eyelid basal cell carcinoma (BCC) is the most common eyelid malignancy. Metabolic reprogramming is critical in tumorigenesis, but the metabolic feature of eyelid BCC remains elusive. In this study, we aim to reveal the metabolic profile in eyelid BCC using targeted metabolomics. Eyelid samples were collected from patients who had removal of BCC and from control patients who underwent blepharoplasty. Multivariate analysis of metabolomics data distinguished the two groups, indicating that eyelid BCC has significantly different metabolome than the healthy tissue. We found 16 increased and 11 decreased metabolites in the BCC tissues. These metabolites were highly enriched in the metabolism of nicotinamide adenine dinucleotide (NAD), glutathione metabolism, polyamine metabolism, and the metabolism of glycine, serine, threonine, arginine and proline. amino acid metabolism. Metabolites from NAD metabolism (Nicotinamide; Nicotinamide riboside; N1-Methylnicotinamide) had the highest sensitivity, specificity, and prediction accuracy in a prediction model for eyelid BCC. In conclusion, eyelid BCC has a signature change of cell metabolome. Metabolites in NAD metabolic pathways could potentially be biomarkers or therapeutic targets for eyelid BCC.

Parameter Estimation Based on Sigmoid Transform in Wideband Bistatic MIMO Radar System under Impulsive Noise Environment.

Since second-order statistics-based methods rely heavily on Gaussianity assumption and fractional lower-order statistics-based methods depend on a priori knowledge of non-Gaussian noise, there remains a void in wideband bistatic multiple-input/multiple-output (MIMO) radar systems under impulsive noise. In this paper, a novel method based on Sigmoid transform was used to estimate target parameters, which do not need a priori knowledge of the noise in an impulsive noise environment. Firstly, a novel wideband ambiguity function, termed Sigmoid wideband ambiguity function (Sigmoid-WBAF), is proposed to estimate the Doppler stretch and time delay by searching the peak of the Sigmoid-WBAF. A novel Sigmoid correlation function is proposed. Furthermore, a new MUSIC algorithm based on the Sigmoid correlation function (Sigmoid-MUSIC) is proposed to estimate the direction-of-departure (DOD) and direction-of-arrival (DOA). Then, the boundness of the Sigmoid-WBAF to the symmetric alpha stable () noise, the feasibility analysis of the Sigmoid-WBAF, and complexity analysis of the Sigmoid-WBAF and Sigmoid-MUSIC are presented to evaluate the performance of the proposed method. In addition, the Cramér⁻Rao bound for parameter estimation was derived and computed in closed form, which shows that better performance was achieved. Simulation results and theoretical analyses are presented to verify the effectiveness of the proposed method.

Oxygen-Assisted Cathodic Deposition of Zeolitic Imidazolate Frameworks with Controlled Thickness.

Processing metal-organic frameworks (MOFs) as films with controllable thickness on a substrate is increasingly crucial for many applications to realize function integration and performance optimization. Herein, we report a facile cathodic deposition process that enables the large-area preparation of uniform films of zeolitic imidazolate frameworks (ZIF-8, ZIF-71, and ZIF-67) with highly tunable thickness ranging from approximately 24 nm to hundreds of nanometers. Importantly, this oxygen-reduction-triggered cathodic deposition does not lead to the plating of reduced metals (Zn and Co). It is also operable cost-effectively in the absence of supporting electrolyte and facilitates the construction of well-defined sub-micrometer-sized heterogeneous structures within ZIF films.

Chinese registry of rheumatoid arthritis (CREDIT): I. Introduction and prevalence of remission in Chinese patients with rheumatoid arthritis.

OBJECTIVES: To introduce the Chinese Registry of rhEumatoiD arthrITis (CREDIT), which is the first nationwide, multicentre, online rheumatoid arthritis (RA) registry in China, and to depict major cross-sectional data and treatment strategies of Chinese RA patients. METHODS: RA patients who fulfilled the 2010 ACR/EULAR classification criteria for rheumatoid arthritis were recruited into the registry by their rheumatologists from 144 clinical centres in China. Data, including demographics, disease characteristics, co-morbidities, treatment, and adverse reactions, were collected and documented through the predefined protocol. RESULTS: 8071 registered patients (F:M = 4.03:1) were registered up to May 2017. Mean age at symptom onset and at diagnosis was 46.15±14.72y and 48.68±14.54y, respectively. Point prevalence of remission (95% CIs) was 14.88% (14.10-15.66%), 4.23% (3.79-4.66%), 4.25% (3.81-4.69%), and 4.27% (3.83-4.72%) according to DAS28-CRP, CDAI, SDAI, and the 2011 ACR/EULAR remission criteria, respectively. 38.84% and 38.11% of treatment-naïve patients (n=3262) were in moderate (3.25.1) disease activity, respectively. Among treatment-naïve patients, those who were initiated on treatment with bDMARDs had higher disease activity than those who were treated with csDMARDs (p<0.05). Three months after initiating bDMARDs, 19.29% (n=38) of patients achieved remission (DAS28-CRP<2.6). CONCLUSIONS: The CREDIT registry is an effective tool for real-world study of RA patients in China. By providing information for diagnosis and treatment regimen, the CREDIT registry can enhance the application of treat-to-target (T2T) strategy and improve patient outcomes in China.

Crystal Structure of NaLuW2O8·2H2O and Down/Upconversion Luminescence of the Derived NaLu(WO4)2:Yb/Ln Phosphors (Ln = Ho, Er, Tm).

Hydrothermally reacting Lu(NO)3 and Na2WO4·2H2O at 200 °C and pH = 8 produced the new compound NaLuW2O8·2H2O, which was analyzed via the Rietveld technique to crystallize in the orthorhombic system (space group: Cmmm) with cell parameters a = 21.655(1), b = 5.1352(3), and c = 3.6320(2) Å and cell volume V = 403.87(4) Å3. The crystal structure presents -(NaO6)-(NaO6)- and -(LuO4(H2O)2WO5)-(LuO4(H2O)2WO5)- alternating layers linked together by the O2- ion common to NaO6 octahedron and WO5 triangle bipyramid. Tetragonal structured and phase-pure Na(Lu0.87Ln0.03Yb0.1)(WO4)2 phosphors (Ln = Ho, Er, and Tm) were directly produced by calcining their NaLuW2O8·2H2O analogous precursors at 600 °C for 2 h, followed by a detailed study of their downconversion/upconversion (DC/UC) photoluminescence. It was shown that the UC luminescence is dominated by a red band at ∼650 nm for Ho3+ (5F5 → 5I8 transition), green bands at ∼500-575 nm for Er3+ (2H11/2/4S3/2 → 4I15/2 transitions) and a blue band at ∼476 nm for Tm3+ (1G4 → 3H6 transition), all via a three-photon process. DC luminescence of the phosphors is characterized by a ∼545 nm green emission for Ho3+ (5F4/5S2 → 5I8 transition, λex = 453 nm), ∼500-575 nm green emissions for Er3+ (2H11/2/4S3/2 → 4I15/2 transitions, λex = 380 nm), and a ∼455 nm blue emission for Tm3+ (1D2 → 3F4 transition, λex = 360 nm), with CIE chromaticity coordinates of around (0.27, 0.71), (0.26, 0.72), and (0.15, 0.04), respectively.