Theoretical comparison of fructose with methylglucoside for the production of formate and levulinate catalyzed by Brønsted acids in a methanol solution.

For the conversion of fructose/methylglucoside (MG) into both methyl formate (MF) and methyl levulinate (MLev), the C-source of formate [HCOO]- remains unclear at the molecular level. Herein, reaction mechanisms catalyzed by [CH3OH2]+ in a methanol solution were theoretically investigated at the PBE0/6-311++G(d,p) level. For the conversion of fructose into MF and MLev, the formate [HCOO]- comes from the C1-atom of fructose, in which the rate-determining step lies in the reaction of 5-hydroxymethylfurfural (HMF) with CH3OH to yield MF and MLev. The reaction of fructose with CH3OH kinetically tends to generate HMF intermediates rather than yield (MF + MLev). When MG is dissolved in a methanol solution, its O2, O3, and O4 atoms are closer to the first layer of the solvent than O1, O5, and O6 atoms. For the dehydration of MG with methanol into MF and MLev, the formate [HCOO]- stems from the dominant C1- and secondary C3-atoms of MG. Kinetically, MG is ready to yield (MF + MLev), whereas fructose can induce the reaction to remain at the HMF intermediate, inhibiting the further conversion of HMF with CH3OH into MF and MLev. If MG isomerizes into fructose, the reaction will be more preferable for yielding HMF rather than (MF + MLev).

Machine learning-assisted matrix-assisted laser desorption/ionization time-of-flight mass spectrometry toward rapid classification of milk products.

This study established a method for rapid classification of milk products by combining MALDI-TOF MS analysis with machine learning techniques. The analysis of 2 different types of milk products was used as an example. To select key variables as potential markers, integrated machine learning strategies based on 6 feature selection techniques combined with support vector machine (SVM) classifier were implemented to screen the informative features and classify the milk samples. The models were evaluated and compared by accuracy, Akaike information criterion (AIC), and Bayesian information criterion (BIC). The results showed the least absolute shrinkage and selection operator (LASSO) combined with SVM performs best, with prediction accuracy of 100% ± 0%, AIC of -360 ± 22, and BIC of -345 ± 22. Six features were selected by LASSO and identified based on the available protein molecular mass data. These results indicate that MALDI-TOF MS coupled with machine learning technique could be used to search for potential key targets for authentication and quality control of food products.

Machine learning-based analysis of heavy metal contamination in Chinese lake basin sediments: Assessing influencing factors and policy implications.

Sediments are important heavy metal sinks in lakes, crucial for ensuring water environment safety. Existing studies mainly focused on well-studied lakes, leaving gaps in understanding pollution patterns in specific basins and influencing factors.We compiled comprehensive sediment contamination data from literature and public datasets, including hydro-geomorphological, climatic, soil, landscape, and anthropogenic factors. Using advanced machine learning, we analyzed typical pollution factors to infer potential sources and migration pathways of pollutants and predicted pollution levels in basins with limited data availability. Our analysis of pollutant distribution data revealed that Cd had the most extensive pollution range, with the most severe pollution occurring in the Huaihe and Yangtze River basins. Furthermore, we identified distinct groups of driving factors influencing various heavy metals. Cd, Cr, and Pb were primarily influenced by human activities, while Cu and Ni were affected by both anthropogenic and natural factors, and Zn tended more towards natural sources. Our predictions indicated that, in addition to the typical highly polluted areas, the potential risk of Cd, Cu and Ni is higher in Xinjiang, and in Tibet and Qinghai, the potential risk of Cd, Cr, Cu and Ni is higher. Pb and Zn presented lower risks, except in the Huaihe and Yangtze River Basins. Temperature, wind, precipitation, precipitation rate, and the cation exchange capacity of soil significantly impacted the predictions of heavy metal pollution in sediments, suggesting that particulate migration, rainfall runoff, and soil erosion are likely the main pathways for pollutant migration into sediments. Considering the migration, pathways, and sources of pollutants, we propose strategies such as low-impact development and promoting sustainable transportation to mitigate pollution. This study provides the latest insights into heavy metal pollution in Chinese lake sediments, offering references for policy-making and water resource management.

Matrix Factorization-Based Dimensionality Reduction Algorithms─A Comparative Study on Spectroscopic Profiling Data.

Spectroscopic profiling data used in analytical chemistry can be very high-dimensional. Dimensionality reduction (DR) is an effective way to handle the potential "curse of dimensionality" problem. Among the existing DR algorithms, many can be categorized as a matrix factorization (MF) problem, which decomposes the original data matrix X into the product of a low-dimensional matrix W and a dictionary matrix H. First, this paper provides a theoretical reformulation of relevant DR algorithms under a unified MF perspective, including PCA (principal component analysis), NMF (non-negative matrix factorization), LAE (linear autoencoder), RP (random projection), SRP (sparse random projection), VQ (vector quantization), AA (archetypical analysis), and ICA (independent component analysis). From this perspective, an open-sourced toolkit has been developed to integrate all of the above algorithms with a unified API. Second, we made a comparative study on MF-based DR algorithms. In a case study of TOF (time-of-flight) mass spectra, the eight algorithms extracted three components from the original 27,619 features. The results are compared by a set of DR quality metrics, e.g., reconstruction error, pairwise distance/ranking property, computational cost, local and global structure preservations, etc. Finally, based on the case study result, we summarized guidelines for DR algorithm selection. (1) For reconstruction quality, choose ICA. In the case study, ICA, PCA, and NMF have high reconstruction qualities (reconstruction error < 2%), ICA being the best. (2) To keep the pairwise topological structure, choose PCA. PCA best preserves the pairwise distance/ranking property. (3) For edge computing and IoT scenarios, choose RP or SRP if reconstruction is not required and the JL-lemma condition is met. The RP family has the best computational performance in the experiment, almost 10-100 times faster than its peers.

Design and synthesis of boron-containing ALK inhibitor with favorable in vivo efficacy.

ALK is an attractive therapeutic target for the treatment of non-small cell lung cancer. As an emerging element in medicinal chemistry, boron has achieved great success in the discovery of antitumor drugs and antibacterial agents. Through construction of a BCC (boron-containing compound) compound library and broad kinase screening, we found the ALK inhibitor hit compound 10a. Structural optimization by CADD and isosterism revealed that lead compound 10k has improved activity (ALKL1196M IC50 = 8.4 nM, NCI-H2228 cells IC50 = 520 nM) and better in vitro metabolic stability (human liver microsomes, T1/2 = 238 min). Compound 10k showed good in vivo efficacy in a nude mouse NCI-H2228 lung cancer xenograft model with a TGI of 52 %. Molecular simulation analysis results show that the hydroxyl group on the oxaborole forms a key hydrogen bond with Asn1254 or Asp1270, and this binding site provides a new idea for drug design. This is the first publicly reported lead compound for a boron-containing ALK inhibitor.

Improved YOLOX detection algorithm for contraband in X-ray images.

It is important to perform contraband inspections on items before they are taken into public places in order to ensure the safety of people and property. At present, the mainstream method of judging contraband is that security inspectors observe the X-ray image of objects and judge whether they belong to contraband. Unfortunately, contraband is often hidden under other normal objects. In a high-intensity working environment, security inspectors are very prone to missed detection and wrong detection. To this end, a detection framework based on computer vision technology is proposed, which is trained and improved on the basis of the current state-of-the-art YOLOX object detection network, and adopts strategies such as feature fusion, adding a double attention mechanism and classifying regression loss. Compared with the benchmark YOLOX-S model, the proposed method achieves a higher average accuracy, with an improvement of 5.0% on the public safety SIXray dataset, opening the way to large-scale automatic detection of contraband in public places.

Design and synthesis of boron-containing diphenylpyrimidines as potent BTK and JAK3 dual inhibitors.

Bruton's tyrosine kinase (BTK) and Janus kinase 3 (JAK3) are very promising targets for hematological malignancies and autoimmune diseases. In recent years, a few compounds have been approved as a marketed medicine, and several are undergoing clinical trials. By recombining the dominant backbone of known active compounds, constructing a foused library, and screening a broad panel of kinases, we found a class of compounds with dual activities of anti-BTK and anti-JAK3. Some of the compounds have shown 10-folds more active in the enzyme and cell-based assays than a known active compound. Furthermore, liver microsome stability experiments show that these compounds have better stability than ibrutinib. These explorations offered new clues to discover benzoxaborole fragment and pyrimidine scaffold as more effective BTK and JAK3 dual inhibitors.

IL-12/IL-18-preactivated donor NK cells enhance GVL effects and mitigate GvHD after allogeneic hematopoietic stem cell transplantation.

Adoptive transfer of donor NK cells has the potential of mediating graft-versus-leukemia (GVL) effect while suppressing acute graft-versus-host-disease (aGVHD) during allogeneic hematopoietic stem cell transplantation (allo-HSCT). However, these beneficial effects are limited by the transient function of adoptively transferred NK cells. Previous studies demonstrate that cytokine-induced memory-like NK cells that are preactivated by IL-12, IL-15, and IL-18 have enhanced effector functions and long life span in vivo. Here, we investigated the effects of IL-12/18-preactivated and IL-12/15/18-preactivated donor NK cells on GVL and aGVHD in a murine model of allo-HSCT. We found that both IL-12/18- and IL-12/15/18-preactivated NK cells mediated stronger GVL effect than control NK cells mainly due to their elevated activation/cytotoxicity and sustained proliferative potential. Interestingly, we observed that although both IL-12/18- and IL-12/15/18-preactivated NK cells significantly inhibited severe aGVHD, only the IL-12/18-preactivated NK cells maintained the beneficial effect of donor NK cells on mild aGVHD. The IL-12/15/18-preactivated NK cell infusion accelerated aGVHD in the fully-mismatched mild aGVHD model. Our results demonstrated that IL-12/18-preactivated NK cells displayed sustained and enhanced GVL functions, and could mitigate aGVHD despite the severity of the disease. IL-12/18-preactivated donor NK cell infusion may be an effective and safe adoptive therapy after allo-HSCT.

Identification of unexpected unlabeled N,N-dimethylamide formation in the synthesis of deuterated fragment of ribociclib by a HATU-mediated coupling reaction.

Starting from N,N-dimethylamine and D2 O, deuterated fragment of ribociclib was synthesized for use as a mass spectroscopy internal standard. Furthermore, systematic studies on D0 (unlabeled material) formation during the amidation reaction were performed, leading to the identification of a coupling reagent, HATU (O-(7-azabenzotriazol-1-yl)-N,N,N',N'-tetramethyluronium hexafluorophosphate), as main cause. Finally, an alternative route was designed using EDCI/HOBT as coupling reagents to produce the desired deuterated compound without D0 residue.

Synthesis and biological evaluation of deuterated sofosbuvir analogs as HCV NS5B inhibitors with enhanced pharmacokinetic properties.

A series of deuterated sofosbuvir analogs were designed and prepared with the aim of improving their pharmacokinetic properties. The devised synthetic routes allow for site-selective deuterium incorporation with high levels of isotopic purity. As expected, the deuterated analogs (37-44) are as efficacious as sofosbuvir when tested in vitro inhibition of viral replication (replicon) assays. Compared with sofosbuvir, deuterated analog 40 displays improved in vivo pharmacokinetics profiles in rats and dogs in terms of the metabolite and the prodrug. The Cmax and area under the curve (AUC) of 40 in dogs were increased by 3.4- and 2.7-fold, respectively. Due to the enhanced pharmacokinetic properties and the great synthetic advantage of an inexpensive deuterium source (D2 O) for 40, it was chosen for further investigation.

Synthesis of deuterium-labeled crizotinib, a potent and selective dual inhibitor of mesenchymal-epithelial transition factor (c-MET) kinase and anaplastic lymphoma kinase (ALK).

To more accurately and rapidly achieve quantitative detection of clinical crizotinib samples, stable isotope labeled crizotinib was required as an internal standard. We have developed a method to prepare racemic [D9 ] crizotinib using a base-catalyzed H/D exchange of both nitroso compound 2 and the acetophenone compound 6 with D2 O and NaBD4 reduction of 7 as the key steps to introduce the 9 deuterium atoms. Starting with 4-hydroxypiperidine, 14-step synthesis furnished the desired racemic [D9 ] crizotinib 18. The deuterium-labeled compound 18 with the chemical purity of 99.62% was applicable for use as internal standards in the drug clinical study.

An efficient and facile synthesis of deuterium-labeled anticancer agent bendamustine hydrochloride.

Bendamustine hydrochloride is an alkylating agent that was developed for the treatment of various human cancers. The stable isotope-labeled bendamustine was required to support clinic studies. An effective and operationally simple method for the synthesis of [D6 ] bendamustine hydrochloride was developed using DCl as a catalyst and D2 O as a deuterium source. Under the present condition, regioselectively deuterated bendamustine hydrochloride with high deuterium incorporation is achieved.

Synthesis of obeticholic acid, a farnesoid X receptor agonist, and its major metabolites labeled with deuterium.

Simple and facile methods for the synthesis of deuterium-labeled obeticholic acid and its 2 metabolites, glycine and taurine conjugates of obeticholic acid, are described herein. The 3 deuterated compounds were applicable for use as internal standards in drug development.

An efficient synthesis of deuterium-labeled degarelix acetate, a third-generation gonadotropin-releasing hormone receptor antagonist.

Degarelix acetate, a third-generation gonadotropin-releasing hormone receptor antagonist, shows great potential in the treatment of many androgen-related diseases. To support clinical studies of degarelix acetate, deuterium-labeled degarelix is highly desired for use as an internal standard. Using D2 O/D3 PO4 as a deuterium source, 2-amino-3-(naphthalen-2-yl)propanoic acid was converted to deuterated degarelix acetate in 13 steps and in 14% overall yield.

Augmented anti-tumor activity of NK-92 cells expressing chimeric receptors of TGF-ßR II and NKG2D.

The capacity of natural killer (NK) cells to kill tumor cells without specific antigen recognition provides an advantage over T cells and makes them potential effectors for tumor immunotherapy. However, the efficacy of NK cell adoptive therapy can be limited by the immunosuppressive tumor microenvironment. Transforming growth factor-ß (TGF-ß) is a potent immunosuppressive cytokine that can suppress NK cell function. To convert the suppressive signal induced by TGF-ß to an activating signal, we genetically modified NK-92 cells to express a chimeric receptor with TGF-ß type II receptor extracellular and transmembrane domains and the intracellular domain of NK cell-activating receptor NKG2D (TN chimeric receptor). NK-92 cells expressing TN receptors were resistant to TGF-ß-induced suppressive signaling and did not down-regulate NKG2D. These modified NK-92 cells had higher killing capacity and interferon γ (IFN-γ) production against tumor cells compared with the control cells and their cytotoxicity could be further enhanced by TGF-ß. More interestingly, the NK-92 cells expressing TN receptors were better chemo-attracted to the tumor cells expressing TGF-ß. The presence of these modified NK-92 cells significantly inhibited the differentiation of human naïve CD4+ T cells to regulatory T cells. NK-92-TN cells could also inhibit tumor growth in vivo in a hepatocellular carcinoma xenograft tumor model. Therefore, TN chimeric receptors can be a novel strategy to augment anti-tumor efficacy in NK cell adoptive therapy.

Preparation of tritium-labeled PF-622, a novel fatty acid amide hydrolase inhibitor.

To make a detailed characterization of the mechanism of inhibition and selectivity of a novel fatty acid amide hydrolase inhibitor PF-622, 3 tritium isotopomers were prepared. [3 H]PF-622a labeled at the piperazine ring B and [3 H]PF-622b labeled at both the ring B and phenyl ring A were synthesized via catalytic H(hydrogen)-T(tritium) exchange, utilizing 1 equiv and excess of Crabtree's catalyst, respectively. The preparation of [3 H]PF-622c labeled only at the phenyl ring A was achieved via tritiodebromination of the bromide precursor, using Pd(PPh3 )4 as a catalyst. The observations from these tritiation reactions might open a new perspective in the labeling for the targets having a similar moiety.

Secreted IL-1α promotes T-cell activation and expansion of CD11b(+) Gr1(+) cells in carbon tetrachloride-induced liver injury in mice.

Interleukin-1α is mainly expressed on the cell membrane, but can also be secreted during inflammation. The roles of secreted and membrane IL-1α in acute liver inflammation are still not known. Here, we examined the functions of secreted and membrane IL-1α in a mouse model of carbon tetrachloride-induced acute liver injury. We show that secreted IL-1α aggravates liver damage and membrane IL-1α slightly protects mice from liver injury. Further studies showed that secreted IL-1α promotes T-cell activation. It also increased the expansion of CD11b(+) Gr1(+) myeloid cells, which may serve as a negative regulator of acute liver inflammation. Moreover, secreted IL-1α induced IL-6 production from hepatocytes. IL-6 neutralization reduced the proliferation of CD11b(+) Gr1(+) myeloid cells in vivo. CCL2 and CXCL5 expression was increased by secreted IL-1α in vitro and in vivo. Antagonists of the chemokine receptors for CCL2 and CXCL5 significantly reduced the migration of CD11b(+) Gr1(+) myeloid cells. These results demonstrate that secreted and membrane IL-1α play different roles in acute liver injury. Secreted IL-1α could promote T-cell activation and the recruitment and expansion of CD11b(+) Gr1(+) myeloid cells through induction of CCL2, CXCL5, and IL-6. The controlled release of IL-1α could be a critical regulator during acute liver inflammation.

Donor NK Cells and IL-15 promoted engraftment in nonmyeloablative allogeneic bone marrow transplantation.

Donor NK cells could promote engraftment by suppressing host alloreactive responses during allogeneic bone marrow transplantation (allo-BMT). The biological activity of NK cells could be significantly enhanced by IL-15. The current study attempted to evaluate the effect of donor NK cells and IL-15 administration on engraftment and immune reconstitution in a murine nonmyeloablative allo-BMT model. Mice infused with donor NK cells and treated with IL-15 during nonmyeloablative allo-BMT resulted in increased donor engraftment compared with either treatment alone. The number of donor-derived cell subsets also increased in the spleen of the recipient mice with combination treatment. The alloreactivity to donor type Ags was significantly reduced in the recipient mice with donor NK cell infusion and IL-15 treatment, which was manifested by decreased proliferation and IL-2 secretion of splenocytes from recipient mice in response to donor type Ags in MLR and decreased capacity of the splenocytes killing donor type tumor targets. We subsequently exposed recipient mice to reduced irradiation conditioning and showed that donor NK cell infusion and hydrodynamic injection-mediated IL-15 expression could synergistically promote donor engraftment and suppress alloreactivity during nonmyeloablative allo-BMT. Infusion of CFSE-labeled donor CD45.1(+) NK cells demonstrated that IL-15 could enhance the infused donor NK cell proliferation and function in vivo. IL-15 treatment also promoted donor bone marrow-derived NK cell development and function. Thus, donor NK cell infusion and IL-15 treatment could synergistically promote the engraftment and the development of donor-derived cell subsets and suppress the host alloresponse in a murine nonmyeloablative allo-BMT model.

An Updated Review on the Spatial Distribution of Borrelia burgdorferi Sensu Lato Across Ticks, Animals and Humans in Northeastern China and Adjacent Regions.

BACKGROUND: Lyme disease is a tick-borne zoonotic disease caused by Borrelia burgdorferi sensu lato and is prevalent in northeastern Asia, particularly in the forested area of Northeastern China. However, a lack of systematic data on the spatial distribution of B. burgdorferi in this region hinders the prediction of its transmission risk across the landscape. METHODS: To provide an updated overview and establish a comprehensive spatial distribution database, we conducted a systematic review of literature published between 2000 and 2022. We collected and compiled relevant data on B. burgdorferi in Northeastern China and its neighbouring regions, outlining its distribution in ticks, wild animals, livestock and humans. Spatial analysis was performed to identify spatial clusters of tick positivity and host infection rates. RESULTS: From a total of 1823 literature, we selected 110 references to compile 626 detection records of B. burgdorferi, including 288 in ticks, 109 in wildlife, 111 in livestock and domestic animals and 100 in humans. The average detection rate of B. burgdorferi in ticks was approximately 20%, with wildlife, livestock and domestic animal host positivity rates below 50% and human seroprevalence rates varying from 0.94% to 44.18%. CONCLUSIONS: The study identified the presence of 17 tick species and ten genotypes of B. burgdorferi in the region, indicating a broad distribution. Notably, B. burgdorferi exhibited notable clustering, particularly in the central and eastern areas of Jilin Province, warranting further investigation.

Enhanced data preprocessing with novel window function in Raman spectroscopy: Leveraging feature selection and machine learning for raspberry origin identification.

In this study, a simple and accurate approach is proposed for enhancing the origin identification of raspberry samples using a combination of innovative Raman spectral preprocessing techniques, feature selection, and machine learning algorithms. Window function was creatively introduced and combined with baseline removal technique to preprocess the Raman spectral data, reducing the dimensionality of the raw data and ensuring the quality of the processed data. An optimization process was conducted to determine the optimal parameter for the window function, resulting in a binning window width of 5 that yielded the highest accuracy. After applying three feature selection techniques, it was found that the information gain model had the best performance in extracting discriminative spectral features. Finally, ten different machine learning algorithms were employed to construct predictive models, and the optimal models were selected. Linear Support Vector Classifier (LinearSVC), Multi-Layer Perceptron Classifier (MLPClassifier), and Linear Discriminant Analysis (LDA) achieve accuracy, precision, recall, and F1 values above 0.96, while the Random Vector Functional Link Network Classifier (RVFLClassifier) surpasses 0.93 for these performance metrics. These results demonstrate the effectiveness of the proposed approach in identifying the origin of raspberry samples with high accuracy and robustness, providing a valuable tool for agricultural product authentication and quality control.