Identification and assessment of new PIM2 inhibitors for treating hematologic cancers: A combined approach of energy-based virtual screening and machine learning evaluation.

PIM2, part of the PIM kinase family along with PIM1 and PIM3, is often overexpressed in hematologic cancers, fueling tumor growth. Despite its significance, there are no approved drugs targeting it. In response to this challenge, we devised a thorough virtual screening workflow for discovering novel PIM2 inhibitors. Our process includes molecular docking and diverse scoring methods like molecular mechanics generalized born surface area, XGBOOST, and DeepDock to rank potential inhibitors by binding affinities and interaction potential. Ten compounds were selected and subjected to an adequate evaluation of their biological activity. Compound 2 emerged as the most potent inhibitor with an IC50 of approximately 135.7 nM. It also displayed significant activity against various hematological cancers, including acute myeloid leukemia, mantle cell lymphoma, and anaplastic large cell lymphoma (ALCL). Molecular dynamics simulations elucidated the binding mode of compound 2 with PIM2, offering insights for drug development. These results highlight the reliability and efficacy of our virtual screening workflow, promising new drugs for hematologic cancers, notably ALCL.

Epidemiological characteristics and dynamic transmissions of COVID-19 pandemics in Chinese mainland: A trajectory clustering perspective analysis.

BACKGROUND: The corona virus disease 2019 (COVID-19) pandemic has spread to more than 210 countries and regions around the world, with different characteristics recorded depending on the location. A systematic summarization of COVID-19 outbreaks that occurred during the "dynamic zero-COVID" policy period in Chinese mainland had not been previously conducted. In-depth mining of the big data from the past two years of the COVID-19 pandemics must be performed to clarify their epidemiological characteristics and dynamic transmissions. METHODS: Trajectory clustering was used to group epidemic and time-varying reproduction number (Rt) curves of mass outbreaks into different models and reveal the epidemiological characteristics and dynamic transmissions of COVID-19. For the selected single-peak epidemic curves, we constructed a peak-point judgment model based on the dynamic slope and adopted a single-peak fitting model to identify the key time points and peak parameters. Finally, we developed an extreme gradient boosting-based prediction model for peak infection cases based on the total number of infections on the first 3, 5, and 7 days of the initial average incubation period. RESULTS: (1) A total of 7 52298 cases, including 587 outbreaks in 251 cities in Chinese mainland between June 11, 2020, and June 29, 2022, were collected, and the first wave of COVID-19 outbreaks was excluded. Excluding the Shanghai outbreak in 2022, the 586 remaining outbreaks resulted in 1 25425 infections, with an infection rate of 4.21 per 1 00000 individuals. The number of outbreaks varied based on location, season, and temperature. (2) Trajectory clustering analysis showed that 77 epidemic curves were divided into four patterns, which were dominated by two single-peak clustering patterns (63.3%). A total of 77 Rt curves were grouped into seven patterns, with the leading patterns including four downward dynamic transmission patterns (74.03%). These curves revealed that the interval from peak to the point where the Rt value dropped below 1 was approximately 5 days. (3) The peak-point judgment model achieved a better result in the area under the curve (0.96, 95% confidence interval = 0.90-1.00). The single-peak fitting results on the epidemic curves indicated that the interval from the slow-growth point to the sharp-decline point was approximately 4-6 days in more than 50% of mass outbreaks. (4) The peak-infection-case prediction model exhibited the superior clustering results of epidemic and Rt curves compared with the findings without grouping. CONCLUSION: Overall, our findings suggest the variation in the infection rates during the "dynamic zero-COVID" policy period based on the geographic division, level of economic development, seasonal division, and temperature. Trajectory clustering can be a useful tool for discovering epidemiological characteristics and dynamic transmissions, judging peak points, and predicting peak infection cases using different patterns.

Environmental Healthcare Assessment via Daily-Scale Drought Monitoring.

Precipitation is the most important factor in determining the drought condition. In addition, the drought condition is also affected by the hydrological process such as evaporation, leakage, runoff, and groundwater. Based on a simple physical model of water income and recession, the effective precipitation index (WAP) can reflect the drought condition in a region on a short time scale. Using a water decline equation to describe the process of preliminary soil moisture, evaporation, runoff, and groundwater, the WAP can be used for the quantitative study of drought. This paper improves the calculation program of WAP with reference to the calculation model of the standardized index. The improved WAP (called SWAP) effectively solves the problem of seasonality in drought. The results showed that SWAP has the ability to capture the drought processes of occurrence, development, peak, and regression in a short time scale, and the SWAP can be used as an effective tool for drought identification, assessment, and prevention.

A Risk Assessment Tool for Identifying Osteoporosis in Older Women with Type 2 Diabetes Mellitus.

PURPOSE: To develop a simple and clinically useful assessment tool for osteoporosis in older women with type 2 diabetes mellitus (T2DM). METHODS: A total of 601 women over 60 years of age with T2DM were enrolled in this study. The levels of serum sex hormones and bone metabolism markers were compared between the osteoporosis and non-osteoporosis groups. The least absolute shrinkage and selection operator regularization (LASSO) model was applied to generate a risk assessment tool. The risk score formula was evaluated using receiver operating characteristic analysis and the relationship between the risk score and the bone mineral density (BMD) and T-value were investigated. RESULTS: Serum sex hormone-binding globulin (SHBG), cross-linked C-telopeptide of type 1 collagen (CTX), and osteocalcin (OC) were significantly higher in the osteoporosis group. After adjustment for age and body mass index (BMI), SHBG was found to be correlated with the T-value or BMD. Then, a risk score was specifically generated with age, BMI, SHBG, and CTX using the LASSO model. The risk score was significantly negatively correlated with the T-value and BMD of the lumbar spine, femoral neck, and total hip (all P<0.05). CONCLUSION: A risk score using age, BMI, SHBG, and CTX performs well for identifying osteoporosis in older women with T2DM.

Comprehensive evaluation of water resources carrying capacity and analysis of obstacle factors in Weifang City based on hierarchical cluster analysis-VIKOR method.

This study uses hierarchical cluster analysis (HCA) to screen the evaluation indexes and establishes a comprehensive evaluation index system for water resources carrying capacity (WRCC), based on the VIKOR method and the obstacle degree model for the identification of the main factors affecting the WRCC of Weifang City. The results show that the WRCC of Weifang City has steadily increased from 2008 to 2018. The subsystems referred to society and water environment are currently the main obstacles affecting Weifang's WRCC, but there is still space for improvement in the future. The areas with low WRCC was Kuiwen District in 2018, which was in a seriously overloaded state, mostly affected by the water resources subsystem. The implementation of measures such as efficiently improving the level of water resources management and the development of water conservancy projects is prominent in water resource planning in Kuiwen District. This study analyzes the current situation of water resources management in order to consider it in strategic decision-making in promoting the improvement of WRCC, which in turn may ensure the realization of a green and sustainable development strategy in the future for Weifang City.

Assessment of persistent fifth aortic arch by echocardiography and computed tomography angiography.

To evaluate the utility of echocardiography (echo) in the diagnosis of persistent fifth aortic arch (PFAA), a very rare congenital aortic arch anomaly, and to compare echo and computed tomography angiography (CTA) imaging findings to improve our understanding of this anomaly.Data on the clinical diagnosis, imaging findings, and clinical management of PFAA were retrospectively analyzed in 10 suspected cases of PFAA admitted to our hospital between January 2012 and February 2017. We compared echo as a first line examination modality, and CTA and surgery results as the gold standard. Weinberg's classification was used to classify the type of PFAA.All patients (100%) received echo examination, eight patients (80%) received CTA examination, and four patients (40%) received sternotomy surgery; all recovered well after surgery. According to Weinberg's classification, 2, 6, and 2 cases (20%, 60%, and 20%) were classified as Type A, B, and C, respectively. Echo was able to diagnose 5 cases of PFAA (1 Type A case and 4 Type B cases) in the first instance. The diagnostic conformance rate of echo was 62.5% after comparisons with CTA and surgery results.The clinical manifestation of PFAA was atypical, and its diagnosis depended primarily on medical imaging. Echo has a relatively high diagnostic accuracy for PFAA, which is very valuable for its early detection.

Synthesis of novel chiral imidazolium stationary phases and their enantioseparation evaluation by high-performance liquid chromatography.

Two novel chiral stationary phases (CSPs) were prepared by bonding chiral imidazoliums on the surface of silica gel. The chiral imidazoles were derivatized from chiral amines, 1-phenylethylamine and 1-(1-naphthyl)ethylamine. The obtained CSPs were characterized by Fourier Transform Infrared (FT-IR) spectroscopy and elemental analysis (EA), demonstrating the bonding densities of CSP 1 and CSP 2 were 0.43 mmol g-1 and 0.40 mmol g-1, respectively. These two CSPs could be used to availably separate 8 pharmaceuticals, 7 mandelic acid/its derivatives, 2 1-phenylethylamine derivatives, 1 1,1'-bi-2-naphthol, and 1 camphorsulfonic acid in high-performance liquid chromatography (HPLC). It is found that CSP 1 could effectively enantioseparate most chiral analytes, especially the acidic components, while CSP 2 could enantiorecognize all chiral analytes, although a number of components did not achieve baseline separation. Additionally, the effects of mobile phase composition, mobile phase pH and salt content, chiral selector structures, and analyte structures on the enantiorecognitions of the two CSPs were investigated. It is found that high acetonitrile content in mobile phases was conducive to enantiorecognition. Mobile phase pH and salt content could alter the retention behaviors of different enantiomers of the same chiral compound, resulting in better enantioresolution. Moreover, both chiral selector structures and substituted groups of analytes played a significant role in the separation of chiral solutes.

Updated assessment of the association of the XRCC1 Arg399Gln polymorphism with lung cancer risk in the Chinese population.

BACKGROUND: Published studies have reported relationships between X-ray repair cross-complementing group 1 (XRCC1) Arg399Gln polymorphism and lung cancer risk in Chinese population. However, the epidemiological results remained controversial. The objective of this study was to clarify the association of XRCC1 Arg399Gln polymorphism with lung cancer risk in the Chinese population. MATERIALS AND METHODS: Systematic searches were performed through the database of Medline/Pubmed, Web of Science, Embase, CNKI and WanFang Medical Online. Odds ratios (ORs) with 95% confidence interval (95%CI) were calculated to estimate the strength of the association. RESULTS: Overall, we observed an increased lung cancer risk among subjects carrying XRCC1 codon 399 Gln/Gln genotype (OR=1.36, 95%CI: 1.09-1.71) in the Chinese population on the basis of 19 studies with 5,416 cases and 5,782 controls. We did not observe any association between XRCC1 codon 399 Arg/Gln and Arg/Gln+Gln/Gln polymorphisms and lung cancer risk (OR=1.00, 95%CI: 0.92-1.08 and OR=1.05, 95%CI: 0.97- 1.13, respectively). Limiting the analysis to studies with controls in agreement with Hardy-Weinberg equilibrium (HWE), we observed an increased lung cancer risk among subjects carrying XRCC1 codon 399 Gln/Gln genotype (OR=1.18, 95%CI: 1.01-1.38). When stratified by source of control, we observed an increased lung cancer risk among subjects carrying XRCC1 codon 399 Arg/Gln+Gln/Gln genotype on the basis of hospitalized patient-based controls (OR=1.21, 95%CI: 1.04-1.42) and among subjects carrying XRCC1 codon 399 Gln/Gln genotype on the basis of healthy subject-based controls (OR=1.22, 95%CI: 1.04-1.43). CONCLUSIONS: Our findings indicated that certain XRCC1 Arg399Gln variants might affect the susceptibility of lung cancer in Chinese population. Larger sample size studies are required to confirm our findings.