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Background Ulcerative colitis (UC) is a persistent immune-mediated inflammatory bowel disease characterized by chronic relapses and remissions. The management of UC remains a subject of contention, particularly as approximately half of the patients experience a complex disease progression marked by chronic activity or frequent recurrence of common UC symptoms, significantly impacting their quality of life. Objective The current landscape presents a growing array of treatment modalities for UC. This study aims to systematically compare the relative efficacy and safety of biologics and small molecule drugs in treating patients with UC. Methods Two independent researchers meticulously conducted a search for randomized controlled trials involving biologics and small molecule drugs for UC. The search encompassed PubMed, Embase, Web of Science, Cochrane Library, CNKI, Wanfang Data, and VIP. The intervention group involved either biologics or small molecule drugs, while the control group received a placebo. The quality of the included studies was assessed using the Cochrane Risk of Bias tool and RevMan 5.4. Paired analyses and network meta-analyses were conducted using R Studio. The surface under the cumulative ranking curve (SUCRA) was employed to rank the included drugs based on each outcome indicator, providing a comparative assessment of the clinical efficacy of diverse treatments for UC. Results A total of 25 studies including 9 546 patients with ulcerative colitis and 10 intervention regimens (Filgotinib 100 mg, Filgotinib 200 mg, Upadacitinib, Tofacitinib, Etrolizumab, Adalimumab, Vedolizumab, Golimumab 50 mg, Golimumab 100 mg, Infliximab). The results of SUCRA probability ranking of clinical remission effect of each drug showed that Upadacitinib (94.1%) >Vedolizumab (85.1%) >Tofacitinib (74.3%) >Infliximab (72.7%) >Filgotinib 200 mg (51.5%) >Golimumab 100 mg (44.3%) >Golimumab 50 mg (39.3%) >Etrolizumab (38.9%) >Adalimumab (29.8%) >Filgotinib 100 mg (18.7%) >Placebo (0.7%). The results of SUCRA probability ranking of the effect of each drug on clinical response showed that Upadacitinib (98.4%) >Infliximab (84.4%) >Tofacitinib (67.2%) >Vedolizumab (58.4%) >Golimumab 50 mg (53.3%) >Adalimumab (34.6%) >Golimumab 100 mg (30.1%) >Placebo (0.4%). The results of SUCRA probability ranking of the effect of each drug on endoscopic remission showed that Upadacitinib (98.7%) >Tofacitinib (68.6%) >Filgotinib 200 mg (59.6%) >Adalimumab (55.2%) >Etrolizumab (46.0%) >Vedolizumab (45.9%) >Filgotinib 100 mg (23.4%) >Placebo (2.2%). The results of SUCRA probability ranking of the effect of each drug on mucosal healing showed that Upadacitinib (99.7%) >Tofacitinib (77.2%) >Infliximab (65.2%) >Golimumab 50 mg (46.4%) >Vedolizumab (44.4%) >Adalimumab (33.8%) >Golimumab 100 mg (31.9%) >Placebo (1.0%). The results of the SUCRA probability ranking of the risk of adverse events for each drug showed that Golimumab 100 mg (96.7%) >Golimumab 50 mg (92.1%) >Placebo (68.7%) >Tofacitinib (60.8%) >Adalimumab (60.7%) >Etrolizumab (47.2%) >Upadacitinib (42.2%) >Vedolizumab (41.3%) >Infliximab (27.0%) >Filgotinib 200 mg (6.6%) >Filgotinib 100 mg (6.2%) . Conclusion Upadacitinib demonstrated optimal efficacy in clinical response, clinical remission, mucosal healing, and endoscopic remission, and Filgotinib 100 mg demonstrating safer outcomes in terms of adverse events.

To address the issues of corrosion weakening of solid-waste-based backfill material caused by mine water, a novel hydrophobic solid waste backfill (HSBF) material was developed using polydimethylsiloxane (PDMS) and a silane coupling agent (SCA) as hydrophobic modification additives, and NaOH (SH) and sodium silicate (SS) as alkali activators. Fly ash and slag were chosen as the primary raw solid waste materials. The rheological properties of the hydrophobic-treated backfill slurries were measured, and the resulting physicochemical properties were compared with the unmodified reference group. This study reveals that the fresh HSBF slurry follows a Modified Bingham (M-B) model with shear-thinning characteristics. The addition of PDMS causes an increase in the water contact angle of the hardened HSBF material with F8S2 to up to 134.9°, indicating high hydrophobicity. Morphological observations indicated that PDMS mainly attaches to the inorganic particles' surface through the bridging action of SCA for the hydrophobic modification of the backfill material. The overall strength of the HSBF materials was further ensured via fly ash–slag ratio optimization, and was found to be enhanced up to 98% by increasing slag content from 20% to 50%. This is mainly attributed to the hydration of slag, forming C-S(A)-H gel, which contributes to the increased strength. The novel HSBF material enables the elimination of cement in mine backfilling applications, demonstrating good economic benefits. Its excellent mechanical and hydrophobic properties can not only prevent overburden displacement in goaf areas, but can also mitigate water resource loss from overlying strata and simultaneously reduce the safety risks associated with long-term mine water deterioration. [ABSTRACT FROM AUTHOR]

The utilization of CO2 mineralization fly ash (F) and coal gangue (G) technology is proposed in this research work to prepare underground backfilling materials. The test process can be divided into pre-treatment and post-treatment stages. In the pre-treatment stage, a sealed stirring vessel is used to conduct CO2 wet mineralization. The ratios of F and G were selected as follows: 20%:60% (F2G6), 30%:50% (F3G5), 40%:40% (F4G4), 50%:30% (F5G3), and 60%:20% (F6G2). The ratios were prepared into Φ50 mm × 100 mm cylindrical samples, with curing durations of 3 d, 7 d, 14 d, and 28 d. In the post-processing stage, the SANS microcomputer-controlled electronic universal testing machine and FLIR A615 infrared thermal imager were used to carry out uniaxial loading and temperature detection, respectively. The unconfined compressive strength (UCS), X-ray diffraction (XRD), average infrared radiation temperature (AIRT), variance of original infrared image temperature (VOIIT), and variance of successive minus infrared image temperature (VSMIT) of the samples were compared and analyzed. The results indicated that when curing reaches 14 d, the strength approaches its peak, with minimal changes in strength over a delayed period; furthermore, as the ratio of F to G continues to increase, the mineralization effect gradually strengthens, reaching its optimum level at a ratio of 5:3. However, when the ratio exceeds 5:3, signs of deteriorating mineralization effect start to appear. During the loading process, the AIRT of the mineralized samples showed a continuous increase, but the VOIIT and VSMIT of the mineralized sample both exhibited significant fluctuations or rapid increases during damage rupture. Moreover, the rise in the AIRT value was found to be linked to the increase in the ratio of F to G. This indicates that F has a higher thermal–mechanical conversion efficiency compared to G, so the temperature change will be greater during the loading process. The drastic changes in the VOIIT and VSMIT indicate that they can be used as sensitive response indicators for sample rupture, and can predict and warn of damage rupture in mineralized samples. Research work can provide practical guidance and reference for underground backfilling of CO2 mineralization industrial waste. [ABSTRACT FROM AUTHOR]

The brittleness index is one of the most integral parameters used in assessing rock bursts and catastrophic rock failures resulting from deep underground mining activities. Accurately predicting this parameter is crucial for effectively monitoring rock bursts, which can cause damage to miners and lead to the catastrophic failure of engineering structures. Therefore, developing a new brittleness index capable of effectively predicting rock bursts is essential for the safe and efficient execution of engineering projects. In this research study, a novel mathematical rock brittleness index is developed, utilizing factors such as crack initiation, crack damage, and peak stress for sandstones with varying water contents. Additionally, the brittleness index is compared with previous important brittleness indices (e.g., B1, B2, B3, and B4) predicted using infrared radiation (IR) characteristics, specifically the variance of infrared radiation temperature (VIRT), along with various artificial intelligent (AI) techniques such as k-nearest neighbor (KNN), extreme gradient boost (XGBoost), and random forest (RF), providing comprehensive insights for predicting rock bursts. The experimental and AI results revealed that: (1) crack initiation, elastic modulus, crack damage, and peak stress decrease with an increase in water content; (2) the brittleness indices such as B1, B3, and B4 show a positive linear exponential correlation, having a coefficient of determination of R2 = 0.88, while B2 shows a negative linear exponential correlation (R2 = 0.82) with water content. Furthermore, the proposed brittleness index shows a good linear correlation with B1, B3, and B4, with an R2 > 0.85, while it shows a poor negative linear correlation with B2, with an R2 = 0.61; (3) the RF model, developed for predicting the brittleness index, demonstrates superior performance when compared to other models, as indicated by the following performance parameters: R2 = 0.999, root mean square error (RMSE) = 0.383, mean square error (MSE) = 0.007, and mean absolute error (MAE) = 0.002. Consequently, RF stands as being recommended for accurate rock brittleness prediction. These research findings offer valuable insights and guidelines for effectively developing a brittleness index to assess the rock burst risks associated with rock engineering projects under water conditions. [ABSTRACT FROM AUTHOR]