Remarkable Second Harmonic Generation Response in (C5H6NO)+(CH3SO3)-: Unraveling the Role of Hydrogen Bond in Thermal Driven Nonlinear Optical Switch.

Heat-activated second harmonic generation (SHG) switching materials are gaining interest for their ability to switch between SHG on and off states, offering potential in optoelectronic applications. The novel nonlinear optical (NLO) switch, (C5H6NO)+(CH3SO3)- (4-hydroxypyridinium methylsulfonate, 4HPMS), is a near-room-temperature thermal driven material with a strong SHG response (3.3 × KDP), making it one of the most potent heat-stimulated NLO switches. It offers excellent contrast of 13 and a high laser-induced damage threshold (2.5 × KDP), with reversibility > 5 cycles. At 73 °C, 4HPMS transitions from the noncentrosymmetric Pna21 room temperature phase (RTP) to the centrosymmetric P21/c phase, caused by the rotation of the (C5H6NO)+ and (CH3SO3)- due to partially thermal breaking of intermolecular hydrogen bonds. The reverse phase change exhibits a large 50 °C thermal hysteresis. Density functional theory (DFT) calculations show that (C5H6NO)+ primarily dictates both the SHG coefficient (dij) and birefringence (∆n(Zeiss) = 0.216 vs ∆n(cal.) = 0.202 at 546 nm; Δn(Immersion) = 0.210 vs ∆n(cal.) = 0.198 at 589.3 nm), while the band gap (Eg) is influenced synergistically by (C5H6NO)+ and (CH3SO3)-. Additionally, 4HPMS-RTP also exhibits mechanochromism upon grinding as well as an aggregation-enhanced emission in a mixture of acetone and water.

Predictive ability of multi-population genomic prediction methods of phenotypes for reproduction traits in Chinese and Austrian pigs.

BACKGROUND: Multi-population genomic prediction can rapidly expand the size of the reference population and improve genomic prediction ability. Machine learning (ML) algorithms have shown advantages in single-population genomic prediction of phenotypes. However, few studies have explored the effectiveness of ML methods for multi-population genomic prediction. RESULTS: In this study, 3720 Yorkshire pigs from Austria and four breeding farms in China were used, and single-trait genomic best linear unbiased prediction (ST-GBLUP), multitrait GBLUP (MT-GBLUP), Bayesian Horseshoe (BayesHE), and three ML methods (support vector regression (SVR), kernel ridge regression (KRR) and AdaBoost.R2) were compared to explore the optimal method for joint genomic prediction of phenotypes of Chinese and Austrian pigs through 10 replicates of fivefold cross-validation. In this study, we tested the performance of different methods in two scenarios: (i) including only one Austrian population and one Chinese pig population that were genetically linked based on principal component analysis (PCA) (designated as the "two-population scenario") and (ii) adding reference populations that are unrelated based on PCA to the above two populations (designated as the "multi-population scenario"). Our results show that, the use of MT-GBLUP in the two-population scenario resulted in an improvement of 7.1% in predictive ability compared to ST-GBLUP, while the use of SVR and KKR yielded improvements in predictive ability of 4.5 and 5.3%, respectively, compared to MT-GBLUP. SVR and KRR also yielded lower mean square errors (MSE) in most population and trait combinations. In the multi-population scenario, improvements in predictive ability of 29.7, 24.4 and 11.1% were obtained compared to ST-GBLUP when using, respectively, SVR, KRR, and AdaBoost.R2. However, compared to MT-GBLUP, the potential of ML methods to improve predictive ability was not demonstrated. CONCLUSIONS: Our study demonstrates that ML algorithms can achieve better prediction performance than multitrait GBLUP models in multi-population genomic prediction of phenotypes when the populations have similar genetic backgrounds; however, when reference populations that are unrelated based on PCA are added, the ML methods did not show a benefit. When the number of populations increased, only MT-GBLUP improved predictive ability in both validation populations, while the other methods showed improvement in only one population.

A comprehensive study of the colloidal properties, biocompatibility, and synergistic antioxidant actions of Antarctic krill phospholipids.

Excipient selection is crucial to address the oxidation and solubility challenges of bioactive substances, impacting their safety and efficacy. AKPL, a novel ω-3 polyunsaturated fatty acids (PUFAs) esterified phospholipid derived from Antarctic krill, demonstrates unique antioxidant capabilities and synergistic effects. It exhibits pronounced surface activity and electronegativity at physiological pH, as evidenced by a critical micelle concentration (CMC) of 0.15 g/L and ζ-potential of -49.9 mV. In aqueous environments, AKPL self-assembles into liposomal structures, offering high biocompatibility and promoting cell proliferation. Its polyunsaturated bond-rich structure provides additional oxidation sites, imparting antioxidant properties superior to other phospholipids like DSPC and DOPC. Additionally, AKPL augments the efficacy of lipophilic antioxidants, such as alpha-tocopherol and curcumin, in aqueous media through both intermolecular and intramolecular interactions. In sum, AKPL emerges as an innovative unsaturated phospholipid, offering new strategies for encapsulating and delivering oxygen-sensitive agents.

Pushing the Limit of Photo-Controlled Polymerization: Hyperchromic and Bathochromic Effects.

The photocatalyst (PC) zinc tetraphenylporphyrin (ZnTPP) is highly efficient for photoinduced electron/energy transfer reversible addition-fragmentation chain transfer (PET-RAFT) polymerization. However, ZnTPP suffers from poor absorbance of orange light by the so-called Q-band of the absorption spectrum (maximum absorption wavelength λmax = 600 nm, at which molar extinction coefficient εmax = 1.0×104 L/(mol·cm)), hindering photo-curing applications that entail long light penetration paths. Over the past decade, there has not been any competing candidate in terms of efficiency, despite a myriad of efforts in PC design. By theoretical evaluation, here we rationally introduce a peripheral benzo moiety on each of the pyrrole rings of ZnTPP, giving zinc tetraphenyl tetrabenzoporphyrin (ZnTPTBP). This modification not only enlarges the conjugation length of the system, but also alters the a1u occupied π molecular orbital energy level and breaks the accidental degeneracy between the a1u and a2u orbitals, which is responsible for the low absorption intensity of the Q-band. As a consequence, not only is there a pronounced hyperchromic and bathochromic effect (λmax = 655 nm and εmax = 5.2×104 L/(mol·cm)) of the Q-band, but the hyperchromic effect is achieved without increasing the intensity of the less useful, low wavelength absorption peaks of the PC. Remarkably, this strong 655 nm absorption takes advantage of deep-red (650-700 nm) light, a major component of solar light exhibiting good atmosphere penetration, exploited by the natural PC chlorophyll a as well. Compared with ZnTPP, ZnTPTBP displayed a 49% increase in PET-RAFT polymerization rate with good control, marking a significant leap in the area of photo-controlled polymerization.

Zirconium-Catalyzed Synthesis of 6-(Trifluoromethyl)-2H-pyran-2-ones via C-C Bond Cleavage.

A strategy for the annulation reaction of alkynones with ethyl 4,4,4-trifluoro-3-oxobutanoate through C-C bond cleavage is described. The zirconium-catalyzed transformation provides access to a wide range of structurally diverse 6-(trifluoromethyl)-2H-pyran-2-ones in moderate to good yields, utilizing Na2CO3 as a base. Further transformations into trifluoromethylated arene derivatives have been demonstrated as well. Furthermore, plausible reaction pathways are proposed by conducting various control experiments and isolating a ß-diketone intermediate (X-ray) containing an intramolecular hydrogen bond.

Influence of surface water and groundwater on functional traits and trade-off strategies of oasis communities at the end of the Keriya River, China.

Plant functional traits reflect the capacity of plants to adapt to their environment and the underlying optimization mechanisms. However, few studies have investigated trade-off strategies for functional traits in desert-wetland ecosystems, the mechanisms by which surface water disturbance and groundwater depth drive functional trait variation at the community scale, and the roles of intraspecific and interspecific variation. Therefore, this study analyzed specific differences in community-weighted mean traits among habitat types and obtained the relative contribution of intraspecific and interspecific variation by decomposing community-weighted mean traits, focusing on the Daliyabuyi Oasis in the hinterland of the Taklamakan Desert. We also explored the mechanisms by which surface water and groundwater influence different sources of variability specifically. The results showed that plant height, relative chlorophyll content, leaf thickness, leaf nitrogen content, and nitrogen-phosphorus ratio were the key traits reflecting habitat differences. As the groundwater depth becomes shallower and surface water disturbance intensifies, plant communities tend to have higher leaf nitrogen content, nitrogen-phosphorus ratio, and relative chlorophyll content and lower height. Surface water, groundwater, soil water content, and total soil nitrogen can influence interspecific and intraspecific variation in these traits through direct and indirect effects. As arid to wet habitats change, plant trade-off strategies for resources will shift from conservative to acquisitive. The study concluded that community functional traits are mainly contributed by interspecific variation, but consideration of intraspecific variation and the covariation effects that exist between it and interspecific variation can help to further enhance the understanding of the response of community traits in desert-wetland ecosystems to environmental change. Surface water disturbance has a non-negligible contribution to this adaptation process and plays a higher role than groundwater depth.

Self-delivery photothermal-boosted-nanobike multi-overcoming immune escape by photothermal/chemical/immune synergistic therapy against HCC.

Immune checkpoint inhibitors (ICIs) combined with antiangiogenic therapy have shown encouraging clinical benefits for the treatment of unresectable or metastatic hepatocellular carcinoma (HCC). Nevertheless, therapeutic efficacy and wide clinical applicability remain a challenge due to "cold" tumors' immunological characteristics. Tumor immunosuppressive microenvironment (TIME) continuously natural force for immune escape by extracellular matrix (ECM) infiltration, tumor angiogenesis, and tumor cell proliferation. Herein, we proposed a novel concept by multi-overcoming immune escape to maximize the ICIs combined with antiangiogenic therapy efficacy against HCC. A self-delivery photothermal-boosted-NanoBike (BPSP) composed of black phosphorus (BP) tandem-augmented anti-PD-L1 mAb plus sorafenib (SF) is meticulously constructed as a triple combination therapy strategy. The simplicity of BPSP's composition, with no additional ingredients added, makes it easy to prepare and presents promising marketing opportunities. (1) NIR-II-activated BPSP performs photothermal therapy (PTT) and remodels ECM by depleting collagen I, promoting deep penetration of therapeutics and immune cells. (2) PTT promotes SF release and SF exerts anti-vascular effects and down-regulates PD-L1 via RAS/RAF/ERK pathway inhibition, enhancing the efficacy of anti-PD-L1 mAb in overcoming immune evasion. (3) Anti-PD-L1 mAb block PD1/PD-L1 recognition and PTT-induced ICD initiates effector T cells and increases response rates of PD-L1 mAb. Highly-encapsulated BPSP converted 'cold' tumors into 'hot' ones, improved CTL/Treg ratio, and cured orthotopic HCC tumors in mice. Thus, multi-overcoming immune escape offers new possibilities for advancing immunotherapies, and photothermal/chemical/immune synergistic therapy shows promise in the clinical development of HCC.

Distribution characteristics of perioperative deep vein thrombosis (DVT) and risk factors of postoperative DVT exacerbation in patients with thoracolumbar fractures caused by high-energy injuries.

OBJECTIVE: To investigate the distribution characteristics of perioperative deep venous thrombosis (DVT) in patients with thoracolumbar fractures caused by high-energy injuries and analyze the risk factors of postoperative DVT exacerbation. METHODS: From October 2016 to July 2021, a total of 550 patients with thoracolumbar fractures due to high-energy injuries in our hospital were retrospectively analyzed. Both lower limbs were examined by ultrasound before and after operation. Depending on whether the postoperative DVT was exacerbating, the group was divided into a DVT exacerbation group and a non-DVT exacerbation group. Clinical data were used to study the characteristics of perioperative DVT. Logistic regression analysis and receiver operating characteristic (ROC) curve were used to explore the risk factors of postoperative DVT exacerbation. RESULTS: DVT was found in 97 patients before operation, including 78 cases of distal thrombus, 6 cases of proximal thrombus, and 13 cases of mixed thrombus. Postoperative DVT increased to 116, including 87 distal thrombus, 10 proximal thrombus, and 19 mixed thrombus. The intermuscular vein was the most easily involved vein. Compared with lumbar fractures, thoracic fractures were more likely to have postoperative proximal thrombus (P=0.014). There were 48 cases of thrombus exacerbation after operation. Logistic regression analysis revealed that age, lower extremity muscle strength, time from injury to operation, and blood loss were risk factors for postoperative DVT exacerbation. CONCLUSIONS: The intermuscular vein is the most easily involved vein. The anatomical distribution of DVT at different fracture sites is different, and patients with thoracic fractures are more likely to have proximal DVT after operation. Age, lower extremity muscle strength, time from injury to operation, and blood loss were risk factors for postoperative DVT exacerbation.

A Polymer Nanocomposite with Strong Full-Spectrum Solar Absorption and Infrared Emission for All-Day Thermal Energy Management and Conversion.

Realizing efficient energy utilization from the heat source of the sun and the cold source of outer space is of great significance for addressing the global energy and environmental crisis. Materials with ideal full-spectrum solar absorption and infrared emission are highly desirable for adapting to the continuous weather dynamic throughout the day, nonetheless, their development remains challenging. Here, a polymer nanocomposite with full-spectrum strong solar (280-2500 nm) absorption ranging from 88.8% to 94.8% with an average value of 93.2% and full-spectrum high infrared (8-13 µm) emission ranging from 81.3% to 90.0% with an average value of 84.2%, is reported by melt-processing polypropylene and uniformly dispersed low-loading MXene nanosheets (1.9 vol%). The nanocomposite can achieve daytime photothermal enhancement of ≈50 °C and nighttime radiative cooling of 8 °C. The temperature difference throughout the day ensures all-day uninterrupted thermoelectric generation, yielding a power density output of 1.5 W m-2 (daytime) and 7.9 mW m-2 (nighttime) in real outdoor environment without any additional energy consumption. This work provides an impressive polymer nanocomposite with ideal full-spectrum solar absorption and infrared emission for all-day uninterrupted thermal energy management and conversion.

Nomogram for predicting postoperative deep vein thrombosis in patients with spinal fractures caused by high-energy injuries.

OBJECTIVE: Deep venous thrombosis (DVT) is a common complication in patients with spinal fractures caused by high-energy injuries. Early identification of patients at high risk of postoperative DVT is essential for the prevention of thrombosis. This study aimed to develop and validate a prediction model based on a nomogram to predict DVT in patients with spinal fractures caused by high-energy injuries. METHODS: Clinical data were collected from 936 patients admitted to our hospital between January 2016 and December 2021 with spinal fractures caused by high-energy injuries. Multivariate logistic regression analysis was used to identify the risk factors for postoperative DVT and to develop a nomogram. The predictive performance of the nomogram was evaluated by the receiver operating characteristic (ROC) curve and calibration curve. RESULTS: The incidence of preoperative DVT was 15.38% (144/936). The postoperative incidence of DVT was 20.5% (192/936). The multivariate analysis revealed that age, operation time, blood transfusion, duration of bed rest, American Spinal Injury Association (ASIA) score and D-dimer were risk factors for postoperative DVT. The area under the ROC curve of the nomogram was 0.835 and the calibration curve showed good calibration. CONCLUSIONS: The nomogram showed a good ability to predict postoperative DVT in patients with spinal fractures caused by high-energy injuries, which may benefit pre- and postoperative DVT prophylaxis strategy development.

Copper Loading-Controlled Selective Synthesis of 2,5-Bis(trifluoromethyl) and Monotrifluoromethyl-Substituted Oxazoles.

A general domino annulation reaction of sulfonylmethyl isocyanide with trifluoroacetic anhydride in the presence of copper chloride as an additive is developed. The reaction affords 2,5-bis(trifluoromethyl)oxazoles in modest to good yields under mild conditions. A wide variety of sulfonylmethyl isocyanide and perfluorocarboxylic anhydride substrates are amenable to this transformation. Under a higher copper salt loading conditions, the reaction led to the formation of monotrifluoromethyl-substituted oxazole product.

A Novel Approach for Apple Freshness Prediction Based on Gas Sensor Array and Optimized Neural Network.

Apple is an important cash crop in China, and the prediction of its freshness can effectively reduce its storage risk and avoid economic loss. The change in the concentration of odor information such as ethylene, carbon dioxide, and ethanol emitted during apple storage is an important feature to characterize the freshness of apples. In order to accurately predict the freshness level of apples, an electronic nose system based on a gas sensor array and wireless transmission module is designed, and a neural network prediction model using an improved Sparrow Search Algorithm (SSA) based on chaotic sequence (Tent) to optimize Back Propagation (BP) is proposed. The odor information emitted by apples is studied to complete an apple freshness prediction. Furthermore, by fitting the relationship between the prediction coefficient and the input vector, the accuracy benchmark of the prediction model is set, which further improves the prediction accuracy of apple odor information. Compared with the traditional prediction method, the system has the characteristics of simple operation, low cost, reliable results, mobile portability, and it avoids the damage to apples in the process of freshness prediction to realize non-destructive testing.

Biomimetic Superhydrophobic Materials through 3D Printing: Progress and Challenges.

Superhydrophobicity, a unique natural phenomenon observed in organisms such as lotus leaves and desert beetles, has inspired extensive research on biomimetic materials. Two main superhydrophobic effects have been identified: the "lotus leaf effect" and the "rose petal effect", both showing water contact angles larger than 150°, but with differing contact angle hysteresis values. In recent years, numerous strategies have been developed to fabricate superhydrophobic materials, among which 3D printing has garnered significant attention due to its rapid, low-cost, and precise construction of complex materials in a facile way. In this minireview, we provide a comprehensive overview of biomimetic superhydrophobic materials fabricated through 3D printing, focusing on wetting regimes, fabrication techniques, including printing of diverse micro/nanostructures, post-modification, and bulk material printing, and applications ranging from liquid manipulation and oil/water separation to drag reduction. Additionally, we discuss the challenges and future research directions in this burgeoning field.

Temperature sensitive liposome based cancer nanomedicine enables tumour lymph node immune microenvironment remodelling.

Targeting tumour immunosuppressive microenvironment is a crucial strategy in immunotherapy. However, the critical role of the tumour lymph node (LN) immune microenvironment (TLIME) in the tumour immune homoeostasis is often ignored. Here, we present a nanoinducer, NIL-IM-Lip, that remodels the suppressed TLIME via simultaneously mobilizing T and NK cells. The temperature-sensitive NIL-IM-Lip is firstly delivered to tumours, then directed to the LNs following pH-sensitive shedding of NGR motif and MMP2-responsive release of IL-15. IR780 and 1-MT induces immunogenic cell death and suppress regulatory T cells simultaneously during photo-thermal stimulation. We demonstrate that combining NIL-IM-Lip with anti-PD-1 significantly enhances the effectiveness of T and NK cells, leading to greatly suppressed tumour growth in both hot and cold tumour models, with complete response in some instances. Our work thus highlights the critical role of TLIME in immunotherapy and provides proof of principle to combine LN targeting with immune checkpoint blockade in cancer immunotherapy.

Improving Genomic Prediction Accuracy in the Chinese Holstein Population by Combining with the Nordic Holstein Reference Population.

The size of the reference population is critical in order to improve the accuracy of genomic prediction. Indeed, improving genomic prediction accuracy by combining multinational reference populations has proven to be effective. In this study, we investigated the improvement of genomic prediction accuracy in seven complex traits (i.e., milk yield; fat yield; protein yield; somatic cell count; body conformation; feet and legs; and mammary system conformation) by combining the Chinese and Nordic Holstein reference populations. The estimated genetic correlations between the Chinese and Nordic Holstein populations are high with respect to protein yield, fat yield, and milk yield-whereby these correlations range from 0.621 to 0.720-and are moderate with respect to somatic cell count (0.449), but low for the three conformation traits (which range from 0.144 to 0.236). When utilizing the joint reference data and a two-trait GBLUP model, the genomic prediction accuracy in the Chinese Holsteins improves considerably with respect to the traits with moderate-to-high genetic correlations, whereas the improvement in Nordic Holsteins is small. When compared with the single population analysis, using the joint reference population for genomic prediction in younger animals, results in a 2.3 to 8.1 percent improvement in accuracy. Meanwhile, 10 replications of five-fold cross-validation were also implemented in order to evaluate the performance of joint genomic prediction, thereby resulting in a 1.6 to 5.2 percent increase in accuracy. With respect to joint genomic prediction, the bias was found to be quite low. However, for traits with low genetic correlations, the joint reference data do not improve the prediction accuracy substantially for either population.

Patellar development after patella instability and early reduction in growing rabbits.

BACKGROUND: Patella-shaped disorder has been considered as a predisposing factor for patella instability. But the influence of early patella reduction for patellar development remains unclear. This study aimed to evaluate whether early operation in patella instability could improve patella morphology in growing rabbits. METHODS: Fifty rabbits (1-month-old) were included in the study. The control group underwent no surgical procedures. The two experimental groups (reduction group and non-reduced group), underwent medial soft tissue restraint release surgery. The reduction group, rabbits underwent the medial soft tissue sutura surgery in order to stabilize the patella 2 months after release surgery. The non-reduced group, rabbits did not undergo suture surgery. Computed Tomography (CT) scans analysis in two experimental endpoints (2, 5 months after release surgery) were selected to evaluate the transverse diameter, thickness, Wiberg index and Wiberg angle. Gross observation was conducted to assess morphological changes of the patella. RESULTS: CT scans showed significant difference in the mean transverse diameter, Wiberg angle between the two experimental groups and the control group 2 months after release surgery. 5 months after release surgery, the indices of patella were found no statistically difference in the reduction group versus the control group. However, the transverse diameter, Wiberg angle in the non-reduced group were significantly differences than that in the reduction group (P < 0.05). Gross observation showed a flattened articular surface of the patella in the non-reduced group. CONCLUSIONS: The results indicated that patella instability may lead to patella-shaped disorder, showing a flattened morphology. Early patella reduction can improve the patella morphology in growing rabbits.

Dynamic Changes and Relevant Factors of Perioperative Deep Vein Thrombosis in Patients with Thoracolumbar Fractures Caused by High-Energy Injuries.

OBJECTIVE: To investigate the dynamic changes and relevant factors of deep vein thrombosis (DVT) in patients with thoracolumbar fractures caused by high-energy injuries. METHODS: From January 2016 to June 2021, a total of 655 patients with thoracolumbar fractures who underwent surgical treatment in our hospital were retrospectively analyzed. The patients were examined by preoperative and postoperative ultrasonography, and divided into thrombus growth group, thrombus invariant group, and thrombus regression group according to the preoperative and postoperative ultrasonographic results. Medical record data, including demographic data, surgical data, and laboratory results, were collected and the differences in various factors among the groups were compared. RESULTS: DVT was found in 99 patients (15.1%, 99/655) before surgery, including 79 cases of distal thrombus, 7 cases of proximal thrombus, and 13 cases of mixed thrombus. The incidence of postoperative DVT increased to 20.6% (134/655), including 96 cases of distal thrombus, 15 cases of proximal thrombus, and 23 cases of mixed thrombus. Among them, 39.7% had thrombus growth, 49.3% had thrombus basically unchanged and 11.0% had thrombolysis. There were significant differences in age, lower extremity muscle strength, time from trauma to surgery, operation time, blood loss, blood transfusion, and post 3-D-dimer among the three groups. CONCLUSIONS: In patients with thoracolumbar fractures caused by high-energy injuries, the majority of patients with DVT do not change or grow after surgery, and only a few of them have thrombolysis. Younger age, lower extremity motor, and fewer blood transfusion contribute to thrombolysis. Delayed surgical intervention, longer operation time, and higher blood loss can lead to thrombosis growth. Post 3-D-dimer is closely related to the dynamic changes of thrombus.

A Review on Cementitious and Geopolymer Composites with Lithium Slag Incorporation.

This study critically reviews lithium slag (LS) as a supplementary cementitious material (SCM), thereby examining its physiochemical characteristics, mechanical properties, and durability within cementitious and geopolymer composites. The review reveals that LS's particle size distribution is comparable to fly ash (FA) and ground granulated blast furnace slag (GGBS), which suggests it can enhance densification and nucleation in concrete. The mechanical treatment of LS promotes early hydration by increasing the solubility of aluminum, lithium, and silicon. LS's compositional similarity to FA endows it with low-calcium, high-reactivity properties that are suitable for cementitious and geopolymeric applications. Increasing the LS content reduces setting times and flowability while initially enhancing mechanical properties, albeit with diminishing returns beyond a 30% threshold. LS significantly improves chloride ion resistance and impacts drying shrinkage variably. This study categorizes LS's role in concrete as a filler, pozzolan, and nucleation agent, thereby contributing to the material's overall reduced porosity and increased durability. Economically, LS's cost is substantially lower than FA's; meanwhile, its environmental footprint is comparable to GGBS, thereby making it a sustainable and cost-effective alternative. Notwithstanding, there is a necessity for further research on LS's fine-tuning through grinding, its tensile properties, its performance under environmental duress, and its pozzolanic reactivity to maximize its utility in concrete technologies. This study comprehensively discusses the current strengths and weaknesses of LS in the field of building materials, thereby offering fresh perspectives and methodologies to enhance its performance, improve its application efficiency, and broaden its scope. These efforts are driving the sustainable and green development of LS in waste utilization and advanced concrete technology.

Multi-therapies Based on PARP Inhibition: Potential Therapeutic Approaches for Cancer Treatment.

The nuclear enzymes called poly(ADP-ribose)polymerases (PARPs) are known to catalyze the process of PARylation, which plays a vital role in various cellular functions. They have become important targets for the discovery of novel antitumor drugs since their inhibition can induce significant lethality in tumor cells. Therefore, researchers all over the world have been focusing on developing novel and potent PARP inhibitors for cancer therapy. Studies have shown that PARP inhibitors and other antitumor agents, such as EZH2 and EGFR inhibitors, play a synergistic role in cancer cells. The combined inhibition of PARP and the targets with synergistic effects may provide a rational strategy to improve the effectiveness of current anticancer regimens. In this Perspective, we sum up the recent advance of PARP-targeted agents, including single-target inhibitors/degraders and dual-target inhibitors/degraders, discuss the fundamental theory of developing these dual-target agents, and give insight into the corresponding structure-activity relationships of these agents.

Regioselective Synthesis of 5-Trifluoromethyl 1,2,4-Triazoles via [3 + 2]-Cycloaddition of Nitrile Imines with CF3CN.

We herein describe a general approach to 5-trifluoromethyl 1,2,4-triazoles via the [3 + 2]-cycloaddition of nitrile imines generated in situ from hydrazonyl chloride with CF3CN, utilizing 2,2,2-trifluoroacetaldehyde O-(aryl)oxime as the precursor of trifluoroacetonitrile. Various functional groups, including alkyl-substituted hydrazonyl chloride, were tolerated during cycloaddition. Furthermore, the gram-scale synthesis and common downstream transformations proved the potential synthetic relevance of this developed methodology.