Drug development encompasses multiple processes, wherein protein subcellular localization is essential. It promotes target identification, treatment development, and the design of drug delivery systems. In this research, a deep learning framework called LocPro is presented for predicting protein subcellular localization. Specifically, LocPro is unique in (a) combining protein representations from the pre-trained large language model (LLM) ESM2 and the expert-driven tool PROFEAT, (b) implementing a hybrid deep neural network architecture that integrates convolutional neural network (CNN), fully connected (FC) layer, and bidirectional long short-term memory (BiLSTM) blocks, and (c) developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels. Additionally, a dataset was curated and divided using a homology-based strategy for training and validation. Comparative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction. The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization. All in all, LocPro serves as a valuable complement to existing protein localization prediction tools. The web server is freely accessible at https://idrblab.org/LocPro/.

Lipopolysaccharides (LPS) are major outer membrane components of Gram-negative bacteria. Unlike most Gram-negative bacteria, Acinetobacter baumannii can still survive and acquire polymyxin resistance after complete loss of LPS. Previous studies of LPS-deficient Acinetobacter baumannii mostly focused on LPS-deficient strains induced by polymyxin, whose background was complex and unstable. To investigate LPS loss-mediated polymyxin resistant-Acinetobacter baumannii, this study constructed a stable and clear background LPS-deficient strain by knocking out lpxC gene in Acinetobacter baumannii ATCC 19606 with CIRSPR/Cas9, and then studied the phenotypic changes of the lpxC-deficient strain including morphology, growth rate, antibiotic susceptibility, virulence, membrane permeability, and membrane potential. Animal experiments were approved by the Animal Care and Welfare Committee Institute of Medicinal Biotechnology, CAMS and PUMC (approval number: IMB-20240119D₉). The results indicated that the lpxC gene of Acinetobacter baumannii ATCC 19606 was successfully knocked out. After losing the lpxC, the strain underwent the morphological change from rod-shaped to spherical. Furthermore, it leads to reduced growth rate, enhanced membrane permeability, decreased membrane potential, lower virulence, and increased antibiotic susceptibility to β-lactams, quinolones, aminoglycosides, macrolides, glycopeptides. The lpxC deletion results in significant changes in membrane homeostasis and adaptability of Acinetobacter baumannii. Understanding the phenotypic changes of colistin-resistant Acinetobacter baumannii mediated by LPS loss is useful for exploring the resistance mechanism of Acinetobacter baumannii and developing new therapeutic strategies.

The molecularly imprinted polymers membranes(MIPMs)were prepared for selective adsorption of lamotrigine(LTG)in plasma by surface molecular imprinting technology with polyvinylidenefluoride(PVDF)membranes as supporter,lamotrigine as template molecule,methyl methacrylate as functional monomer,ethylene glycol dimethacrylate as cross-linking agent,azodiisobutyronitrile as initiator and acetonitrile-dimethylformamide(1∶1.5,V/V)as pore-forming agent.The prepared MIPMs were characterized by scanning electron microscope,Fourier transform infrared spectroscopy,Brunaner-emmet-teller measurements,X-ray photoelectron spectroscopy,and thermogravimetric analysis.The adsorption properties of the materials were investigated by kinetic adsorption,isothermal adsorption,selective adsorption,adsorption-desorption and reusability experiments.The results showed that the imprinted layer of LTG was successfully coated on the surface of PVDF,and the materials had uniform particle size.The adsorption capacity and imprinting factor of the MIPMs towards LTG were 3.77 mg/g and 8.97,respectively.The nanomaterials showed fast mass transfer rate(30 min)and good reusability(the adsorption efficiency was 86.66%after 6 cycles),and could be used for the adsorption of LTG in plasma with low matrix interference,recoveries of 86.54%-90.48%and RSD of 1.51%-3.15%(n=5).The proposed LTG MIPMs were demonstrated to be simple and environment friendly,and had high selectivity in rapid separation and extraction of LTG in plasma.

To explore the characteristics of big data of patients with allergic rhinitis, including the time, population and spatial distribution of allergic rhinitis in Beijing from 2016 to 2021, so as to provide reference for the prevention and treatment of this disease. Descriptive epidemiological methods were used to analyze the distribution (including gender, age and location)and trend of allergic rhinitis patients in 30 pilot hospitals from January 2016 to December 2021, T test and Kruskal-Wallis rank sum test were used to test the statistical differences. The results showed that the number of patients with allergic rhinitis in 30 hospitals increased year by year from 2016 to 2019, with an increase of 97.9%. In 2020, the number of patients decreased. In 2021, the number of visits returned to the pre-epidemic level (461 332); The number of patients with allergic rhinitis was the highest in September, with a seasonal index of 177.6%, while the lowest number was in February, accounting for only 47.2%; a significant difference was observed in the number of patients in different age groups(H=45 319.48, P<0.05), and patients under 15 years old accounted for the highest proportion(819 284 visits); There were significant differences between patients of different genders in the 45-59 year old group (t=-4.26, P<0.05).There were relatively more patients with allergic rhinitis in Dongcheng District(31.1%) than in Huairou District and Miyun District (0.4%). In conclusion, since 2016, the number of patients increased significantly, with a varied trend in different seasons. Most patients were children. There were more patients in the central urban area than in the outer suburbs.
Child ; Humans ; Female ; Male ; Adolescent ; Middle Aged ; Beijing/epidemiology* ; Big Data ; Epidemics ; Hospitals ; Rhinitis, Allergic/epidemiology*

To explore the characteristics of big data of patients with allergic rhinitis, including the time, population and spatial distribution of allergic rhinitis in Beijing from 2016 to 2021, so as to provide reference for the prevention and treatment of this disease. Descriptive epidemiological methods were used to analyze the distribution (including gender, age and location)and trend of allergic rhinitis patients in 30 pilot hospitals from January 2016 to December 2021, T test and Kruskal-Wallis rank sum test were used to test the statistical differences. The results showed that the number of patients with allergic rhinitis in 30 hospitals increased year by year from 2016 to 2019, with an increase of 97.9%. In 2020, the number of patients decreased. In 2021, the number of visits returned to the pre-epidemic level (461 332); The number of patients with allergic rhinitis was the highest in September, with a seasonal index of 177.6%, while the lowest number was in February, accounting for only 47.2%; a significant difference was observed in the number of patients in different age groups(H=45 319.48, P<0.05), and patients under 15 years old accounted for the highest proportion(819 284 visits); There were significant differences between patients of different genders in the 45-59 year old group (t=-4.26, P<0.05).There were relatively more patients with allergic rhinitis in Dongcheng District(31.1%) than in Huairou District and Miyun District (0.4%). In conclusion, since 2016, the number of patients increased significantly, with a varied trend in different seasons. Most patients were children. There were more patients in the central urban area than in the outer suburbs.
Child ; Humans ; Female ; Male ; Adolescent ; Middle Aged ; Beijing/epidemiology* ; Big Data ; Epidemics ; Hospitals ; Rhinitis, Allergic/epidemiology*

Objective:To investigate the construction and application value of a nomogram predictive model for the prognosis of rectal cancer liver metastases based on Surveillance, Epidemio-logy, and End Results (SEER) database.Methods:The retrospective cohort study was conducted. The clinicopathological data of 6 192 patients with rectal cancer liver metastases in the SEER database ( http://seer.cancer.gov/) and 312 patients who were admitted to The Second Affiliated Hospital of Naval Medical University January 2010 to December 2016 were collected. Of 6 192 patients, there were 3 592 males and 2 600 cases. There were 1 076 cases with age lower than 50 years, 2 862 cases with age as 50-69 years, 2 254 cases with age equal to or more than 70 years, respectively. Of 312 pati-ents, there were 177 males and 135 cases. There were 51 cases with age lower than 50 years, 155 cases with age as 50-69 years, 109 cases with age equal to or more than 70 years, respectively. Patients of the SEER database were set as the training set, and patients in The Second Affiliated Hospital of Naval Medical University were set as the validation set. Univariate and multivariate COX proportional hazards regression models were used to analyze risk factors associated with prognosis, and construct and verify the accuracy of nomogram predictive model for the prognosis of rectal cancer liver metas-tasis. The training set were used to construct the nomogram prediction model, and the validation set were used to verify its performance. Observation indicators: (1) prognostic factors analysis in patients with rectal cancer liver metastases; (2) construction and verificative of the predictive model for the prognosis of rectal cancer liver metastasis. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Count data were described as absolute numbers or percentages, and comparison between groups was conducted using the chi-square test. Comparison of ordinal data was analyzed using the rank sum test. The COX regression model was used for univariate and multivariate analyses. Kaplan-Meier method was used to calculate survival rates, and Log-Rank test was used for survival analysis. Results:(1) Prognostic factors analysis in patients with rectal cancer liver metastases. Results of multivariate analysis showed that age >50 years, TNM Ⅱ-Ⅳ stage, stage T3-T4, stage N1-N2, the number of lymph nodes dissected <12, tumor diameter >5.1 cm, positive carcinoembryonic antigen, peripheral nerve infiltration, radiotherapy and adjuvant chemotherapy, poorly differentiated or undifferented tumor were independent prognostic factors of patients ( P<0.05). (2) Construction and verification of the predictive model for the prognosis of rectal cancer liver metastasis. A nomogram predictive model for the prognosis of rectal cancer liver metastasis was constructed based in the multivariate analysis. The C-index of the nomogram predictive model was 0.91, with area under the curve as 0.726, indicating a good discriminant ability. Results of the calibration curve in validation dataset showed that the colorectal cancer survival rate predicted by the nomogram predictive model was consistent with the actual survival rate. Conclusion:The nomogram predictive model can accurately predict the survival probability of patients with rectal cancer liver metastases.

Objective:To analyze influencing factors of coronary heart disease(CHD)in advanced aged population and the therapeutic effect of percutaneous coronary intervention(PCI).Methods:According to diagnosed as CHD or not,a total of 209 aged patients underwent cardio-and cerebrovascular examination in our hospital were divided into CHD group(n=104)and no CHD group(n=105),and general clinical data were compared between two groups.According to treatment method,CHD group was divided into routine treatment group(received routine medication)and PCI group;and recovery time,hospital stay,incidence rate of adverse events during admission and prognosis within one-year follow-up were compared between two groups.Influencing factors of CHD in aged population was analyzed.Results:Compared with no CHD group,there were significant rise in percentages of age＞80 years,smoking,diabetes mellitus,hypertension,total cholesterol＞5.17mmol/L,triglyceride＞1.7mmol/L,high density lipoprotein cholesterol(HDL-C)＜0.96mmol/L,low density lipoprotein cholesterol＞3.37mmol/L,uric acid＞420μmol/L and fibrinogen＞4 g/L in CHD group(P＜0.05 or＜0.01).Compared with routine treat-ment group,there were significant reductions in recovery time,hospital stay,incidence rates of adverse events,lu-men loss/restenosis,primary and secondary endpoint events within one-year follow-up in PCI group(P＜0.05 or＜0.01).Binary Logistic regression analysis indicated that age＞80 years,uric acid＞420μmol/L and HDL-C＜0.96mmol/L were independent risk factors for CHD in advanced aged population(OR=1.755～6.103,P＜0.05 or＜0.01).Conclusion:Age＞80 years,uric acid＞420μmol/L and HDL-C＜0.96 mmol/L are independent risk fac-tors for coronary heart disease in advanced aged population.PCI can significantly shorten recovery time and treat-ment time in advanced aged patients with coronary heart disease with good safety.

Objective To explore the risk factors for intracranial infection in patients after neurosurgery,con-struct and validate a Nomogram prediction model.Methods Data of 978 patients who underwent neurosurgery in a hospital in Nanjing from January 1,2019 to December 31,2022 were retrospectively analyzed.Independent risk fac-tors were screened through logistic univariate and multivariate analyses.Modeling variables were screened through Lasso regression.A Nomogram model was constructed and internally validated by logistic regression.Effectiveness of the model was evaluated with receiver operating characteristic(ROC)curve,calibration curve and decision curve.Results Among 978 patients underwent neurosurgery,293 had postoperative intracranial infection,with an inci-dence of healthcare-associated infection of 29.96％.There was no significant difference in age,gender,proportion of coronary heart disease,cerebral infarction,diabetes and hypertension between the infected group and the non-in-fected group(all P＞0.05).Multivariate logistic analysis showed that postoperative intracranial hypertension,fe-ver,increased neutrophil percentage in blood routine examination,turbid cerebrospinal fluid,positive Pan's test,decreased glucose concentration,abnormal ratio of cerebrospinal fluid/serum glucose,positive microbial culture,absence of indwelling external ventricular drainage tubes,presence of indwelling lumbar cistern drainage tubes,use of immunosuppressive agents,and long duration of surgery were independent risk factors for postoperative intracra-nial infection in patients who underwent neurosurgery(all P＜0.05).Fifteen variables were screened out through Lasso regression.Fourteen variables were finally included for modeling after collinear screening,missing data impu-tation(random forest method)and checking pairwise interaction items.A Nomogram prediction model was con-structed,with the area under ROC curve,sensitivity,specificity,and accuracy of 0.885,0.578,0.896,and 0.704,respectively.Internal validation of the model was conducted.The modeling and validation groups presented similar effects.The calibration curve and decision curve also indicated that the model had good predictive efficacy.Conclusion The constructed Nomogram prediction model for postoperative intracranial infection after neurosurgery is scientific,and the prediction indicators are easy to obtain.The model presents with high stability,reliability,and application value,thus can provide reference for the assessment of postoperative intracranial infection after neuro-surgery.

Aim To explore the mechanism by which total coumarins in Pileostegia tomentella (TCPT) inhibits the proliferation of small cell lung cancer (SCLC) H1688 cells via inducing ferroptosis. Methods The gradient concentrations of TCPT were used to treat H1688 cells. CCK-8 assay was applied for detection of proliferative inhibition of H1688 cells. Transmission electron microscopy was used to approach the morphological changes of H1688 cells under the treatment of TCPT. Additionally, dichlorofluorescein (DCFH-DA) probe was used to detect the intracellular reactive oxygen species (ROS) level. BODIPY 581/ 589 Cll probe was applied to examine the intracellular lipid peroxide formation. Western blotting was employed to detect the expression levels of glutathione peroxidase 4 (GPX4), kelch-like ECH-associated protein (KEAP1), nuclear factor E2 related factor 2 (NRF2), ferritin heavy chain 1 (FTH1) proteins in HI688 cells. Results The proliferation of small cell lung cancer cell H1688 was dramatically inhibited after TCPT intervention (P < 0. 05, P < 0. 01). The morphological characteristics of ferroptosis induced by TCPT were observed by transmission electron microscope. TCPT could also effectively elevate intracellular level of ROS and lipid peroxide. In HI688 cells the expression of ferroptosis markers GPX4, NRF2, and FTH1 was down-regulated, while the expression of KEAP1 was up-regulated, and there were statistically significant differences among the markers mentioned a-bove (P<0. 01). Conclusions Total coumarins in TCPT can significantly inhibit the proliferation of H1688 cells, possibly through increasing ROS and intracellular lipid peroxide levels and eventually inducing ferroptosis.

Objective:To investigate the influencing factors of anastomotic leakage after laparoscopic intersphincter resection (ISR) for extremely low rectal cancer and construction of nomogram prediction model.Methods:The retrospective case-control study was conducted. The clinicopathological data of 812 patients who underwent laparoscopic ISR for extremely low rectal cancer in the Second Affiliated Hospital of Naval Medical University (Shanghai Changzheng Hospital) from February 2012 to February 2022 were collected. There were 459 males and 353 females, aged (51±11)years. Observation indicators: (1) surgical situations; (2) follow-up; (3) influencing factors of postoperative anastomotic leakage; (4) construction and evaluation of nomogram prediction model for postoperative anastomotic leakage. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M(range). Count data were described as absolute numbers. The COX proportional hazard model was used for univariate and multivariate analyses. The R software(3.5.1 version) was used to construct nomogram prediction model. The receiver operating characteristic (ROC) curve was drawn and the area under curve (AUC) was used to evaluate the efficacy of the nomogram prediction model. The Bootstrap method was used for internal verification and to calculate the average consistency index (C-index). Results:(1) Surgical situations. All 812 patients underwent laparoscopic ISR for extremely low rectal cancer, including 388 cases undergoing partial ISR, 218 cases undergoing subtotal ISR and 206 cases undergoing complete ISR. All 812 patients underwent ileal protective ostomy, and there were 306 cases with double anastomosis and 203 cases with left colic artery preserved, respectively. The operation time and volume of intraoperative blood loss of 812 patients was (179±33)minutes and (33±13)mL, respectively. (2) Follow-up. All 812 patients were followed up for (13.5±0.9)months. Of the 812 patients, there were 62 cases with postoperative anastomotic leakage and the healing time of these cases was (33±6)days. (3) Influencing factors of postoperative anastomotic leakage. Results of multivariate analysis showed that male, neoadjuvant chemoradiotherapy, failure of reser-ving left colic artery were independent risk factors of anastomotic leakage after laparoscopic ISR for extremely low rectal cancer ( hazard ratio=5.98, 4.00, 16.26, 95% confidence interval as 1.66-24.12, 1.30-12.42, 3.00-90.89, P<0.05). (4) Construction and evaluation of nomogram prediction model for postoperative anastomotic leakage. According to the results of multivariate analysis, male, neoadju-vant chemoradiotherapy and failure of reserving left colic artery were used to construct the nomogram prediction model for anastomotic leakage after laparoscopic ISR for extremely low rectal cancer, and the score of these indexes in the nomogram prediction model was 50, 49, 93, respectively. The total score of these index corresponded to the incidence rate of anastomotic leakage. Results of ROC curve showed that the AUC of nomogram prediction model of anastomotic leakage after laparoscopic ISR for extremely low rectal cancer was 0.87 (95% confidence interval as 0.80-0.93, P<0.05), with sensi-tivity and specificity 0.96 and 0.60, respectively. Results of internal verification showed that the C-index of nomogram prediction model was 0.87. Conclusion:Male, neoadjuvant chemoradiotherapy, failure of reserving left colic artery are independent risk factors of anastomotic leakage after laparo-scopic ISR for extremely low rectal cancer, and the nomogram prediction model based on these indexes can predict the incidence rate of postoperative anastomotic leakage.