Effects of different precursors on the structure of lignin-based biochar and its ability to adsorb benzopyrene from sesame oil.

Agricultural by-products of sesame are promising bioresources in food processing. This study extracted lignin from the by-products of sesame oil production, namely, the capsules and straw of black and white sesame. Using acid, alkali, and ethanol methods, 12 distinct lignins were obtained to prepare biochar, aiming to investigate both the structural characteristics of lignin-based biochar (LBB) and its ability to remove benzo[a]pyrene (BaP) from sesame oil. The results showed that white sesame straw was the most suitable raw material for preparing biochar. In terms of the preparation method, acid-extracted lignin biochar was more effective in removing BaP than alkaline or ethanol methods. Notably, WS-1LB (white sesame straw acid-extracted lignin biochar) exhibited the highest BaP adsorption efficiency (91.44 %) and the maximum specific surface area (1065.8187 m2/g), characterized by porous structures. The pseudo 2nd and Freundlich models were found to be the best fit for the adsorption kinetics and isotherms of BaP on LBB, respectively, suggesting that a multilayer adsorption process was dominant. The high adsorption of LBB mainly resulted from pore filling. This study provides an economical and highly efficient biochar adsorbent for the removal of BaP in oil.

AZD1390, an ataxia telangiectasia mutated inhibitor, attenuates microglia-mediated neuroinflammation and ischemic brain injury.

AIMS: Excessive neuroinflammation mediated mainly by microglia plays a crucial role in ischemic stroke. AZD1390, an ataxia telangiectasia mutated (ATM) specific inhibitor, has been shown to promote radio-sensitization and survival in central nervous system malignancies, while the role of AZD1390 in ischemic stroke remains unknown. METHODS: Real-time PCR, western blot, immunofluorescence staining, flow cytometry and enzyme-linked immunosorbent assays were used to assess the activation of microglia and the release of inflammatory cytokines. Behavioral tests were performed to measure neurological deficits. 2,3,5-Triphenyltetrazolium chloride staining was conducted to assess the infarct volume. The activation of NF-κB signaling pathway was explored through immunofluorescence staining, western blot, co-immunoprecipitation and proximity ligation assay. RESULTS: The level of pro-inflammation cytokines and activation of NF-κB signaling pathway was suppressed by AZD1390 in vitro and in vivo. The behavior deficits and infarct size were partially restored with AZD1390 treatment in experimental stroke. AZD1390 restrict ubiquitylation and sumoylation of the essential regulatory subunit of NF-κB (NEMO) in an ATM-dependent and ATM-independent way respectively, which reduced the activation of the NF-κB pathway. CONCLUSION: AZD1390 suppressed NF-κB signaling pathway to alleviate ischemic brain injury in experimental stroke, and attenuated microglia activation and neuroinflammation, which indicated that AZD1390 might be an attractive agent for the treatment of ischemic stroke.

A Novel Method for Tracking Neck Motions Using a Skin-Conformable Wireless Accelerometer: A Pilot Study.

Introduction: Cervical spine disease is a leading cause of pain and disability. Degenerative conditions of the spine can result in neurologic compression of the cervical spinal cord or nerve roots and may be surgically treated with an anterior cervical discectomy and fusion (ACDF) in up to 137,000 people per year in the United States. A common sequelae of ACDF is reduced cervical range of motion (CROM) with patient-based complaints of stiffness and neck pain. Currently, tools for assessment of CROM are manual, subjective, and only intermittently utilized during doctor or physical therapy visits. We propose a skin-mountable acousto-mechanic sensor (ADvanced Acousto-Mechanic sensor; ADAM) as a tool for continuous neck motion monitoring in postoperative ACDF patients. We have developed and validated a machine learning neck motion classification algorithm to differentiate between eight neck motions (right/left rotation, right/left lateral bending, flexion, extension, retraction, protraction) in healthy normal subjects and patients. Methods: Sensor data from 12 healthy normal subjects and 5 patients were used to develop and validate a Convolutional Neural Network (CNN). Results: An average algorithm accuracy of 80.0 ± 3.8% was obtained for healthy normal subjects (94% for right rotation, 98% for left rotation, 65% for right lateral bending, 87% for left lateral bending, 89% for flexion, 77% for extension, 50% for retraction, 84% for protraction). An average accuracy of 67.5 ± 5.8% was obtained for patients. Discussion: ADAM, with our algorithm, may serve as a rehabilitation tool for neck motion monitoring in postoperative ACDF patients. Sensor-captured vital signs and other events (extubation, vocalization, physical therapy, walking) are potential metrics to be incorporated into our algorithm to offer more holistic monitoring of patients after cervical spine surgery.

Engineering of the Lrp/AsnC-type transcriptional regulator DecR as a genetically encoded biosensor for multilevel optimization of L-cysteine biosynthesis pathway in Escherichia coli.

L-cysteine is an important sulfur-containing amino acid being difficult to produce by microbial fermentation. Due to the lack of high-throughput screening methods, existing genetically engineered bacteria have been developed by simply optimizing the expression of L-cysteine-related genes one by one. To overcome this limitation, in this study, a biosensor-based approach for multilevel biosynthetic pathway optimization of L-cysteine from the DecR regulator variant of Escherichia coli was applied. Through protein engineering, we obtained the DecRN29Y/C81E/M90Q/M99E variant-based biosensor with improved specificity and an 8.71-fold increase in dynamic range. Using the developed biosensor, we performed high-throughput screening of the constructed promoter and RBS combination library, and successfully obtained the optimized strain, which resulted in a 6.29-fold increase in L-cysteine production. Molecular dynamics (MD) simulations and electrophoretic mobility shift analysis (EMSA) showed that the N29Y/C81E/M90Q/M99E variant had enhanced induction activity. This enhancement may be due to the increased binding of the variant to DNA in the presence of L-cysteine, which enhances transcriptional activation. Overall, our biosensor-based strategy provides a promising approach for optimizing biosynthetic pathways at multiple levels. The successful implementation of this strategy demonstrates its potential for screening improved recombinant strains.

A near-infrared fluorescence probe with large Stokes shift for selectively monitoring nitroreductase in living cells and mouse tumor models.

Hypoxia is commonly regarded as a typical feature of solid tumors, which originates from the insufficient supply of oxygen. Herein, the development of an efficient method for assessing hypoxia levels in tumors is strongly desirable. Nitroreductase (NTR) is an overexpressed reductase in the solid tumors, has been served as a potential biomarker to evaluate the degrees of hypoxia. In this work, we elaborately synthesized a new near-infrared (NIR) fluorescence probe (MR) to monitor NTR activity for assessment of hypoxia levels in living cells and in tumors. Upon exposure of NTR, the nitro-unit of MR could be selectively reduced to amino-moiety with the help of nicotinamide adenine dinucleotide. Moreover, the obtained fluorophore emitted a prominent NIR fluorescence, because it possessed a classical "push-pull" structure. The MR displayed several distinguished characters toward NTR, including intense NIR fluorescent signals, large Stokes shift, high selectivity and low limit of detection (46 ng/mL). Furthermore, cellular confocal fluorescence imaging results validated that the MR had potential of detecting NTR levels in hypoxic cells. Significantly, using the MR, the elevated of NTR levels were successfully visualized in the tumor-bearing mouse models. Therefore, this detecting platform based on this probe may be tactfully constructed for monitoring the variations of NTR and estimating the degrees of hypoxia in tumors.

A biomimetic camouflaged metal organic framework for enhanced siRNA delivery in the tumor environment.

Gene silencing through RNA interference (RNAi), particularly using small double-stranded RNA (siRNA), has been identified as a potent strategy for targeted cancer treatment. Yet, its application faces challenges such as nuclease degradation, inefficient cellular uptake, endosomal entrapment, off-target effects, and immune responses, which have hindered its effective delivery. In the past few years, these challenges have been addressed significantly by using camouflaged metal-organic framework (MOF) nanocarriers. These nanocarriers protect siRNA from degradation, enhance cellular uptake, and reduce unintended side effects by effectively targeting desired cells while evading immune detection. By combining the properties of biomimetic membranes and MOFs, these nanocarriers offer superior benefits such as extended circulation times, enhanced stability, and reduced immune responses. Moreover, through ligand-receptor interactions, biomimetic membrane-coated MOFs achieve homologous targeting, minimizing off-target adverse effects. The MOFs, acting as the core, efficiently encapsulate and protect siRNA molecules, while the biomimetic membrane-coated surface provides homologous targeting, further increasing the precision of siRNA delivery to cancer cells. In particular, the biomimetic membranes help to shield the MOFs from the immune system, avoiding unwanted immune responses and improving their biocompatibility. The combination of siRNA with innovative nanocarriers, such as camouflaged-MOFs, presents a significant advancement in cancer therapy. The ability to deliver siRNA with precision and effectiveness using these camouflaged nanocarriers holds great promise for achieving more personalized and efficient cancer treatments in the future. This review article discusses the significant progress made in the development of siRNA therapeutics for cancer, focusing on their effective delivery through novel nanocarriers, with a particular emphasis on the role of metal-organic frameworks (MOFs) as camouflaged nanocarriers.

International consensus guidelines on robotic pancreatic surgery in 2023.

Background: With the rapid development of robotic surgery, especially for the abdominal surgery, robotic pancreatic surgery (RPS) has been applied increasingly around the world. However, evidence-based guidelines regarding its application, safety, and efficacy are still lacking. To harvest robust evidence and comprehensive clinical practice, this study aims to develop international guidelines on the use of RPS. Methods: World Health Organization (WHO) Handbook for Guideline Development, GRADE Grid method, Delphi vote, and the AGREE-II instrument were used to establish the Guideline Steering Group, Guideline Development Group, and Guideline Secretary Group, formulate 19 clinical questions, develop the recommendations, and draft the guidelines. Three online meetings were held on 04/12/2020, 30/11/2021, and 25/01/2022 to vote on the recommendations and get advice and suggestions from all involved experts. All the experts focusing on minimally invasive surgery from America, Europe and Oceania made great contributions to this consensus guideline. Results: After a systematic literature review 176 studies were included, 19 questions were addressed and 14 recommendations were developed through the expert assessment and comprehensive judgment of the quality and credibility of the evidence. Conclusions: The international RPS guidelines can guide current practice for surgeons, patients, medical societies, hospital administrators, and related social communities. Further randomized trials are required to determine the added value of RPS as compared to open and laparoscopic surgery.

FXR overexpression prevents hepatic steatosis through inhibiting AIM2 inflammasome activation in alcoholic liver disease.

BACKGROUND AND PURPOSE: Alcoholic liver disease (ALD), a metabolic liver disease caused by excessive alcohol consumption, has attracted increasing attention due to its high prevalence and mortality. Up to date, there is no effective and feasible treatment method for ALD. This study was to investigate whether Farnesoid X receptor (FXR, NR1H4) can alleviate ALD and whether this effect is mediated by inhibiting absent in melanoma 2 (AIM2) inflammasome activation. METHODS: The difference in FXR expression between normal subjects and ALD patients was analyzed using the Gene Expression Omnibus (GEO) database. Lieber-DeCarli liquid diet with 5% ethanol (v/v) (EtOH) was adopted to establish the mouse ALD model. Liver histopathological changes and the accumulation of lipid droplets were assessed by H&E and Oil Red O staining. Quantitative real-time PCR, Western blotting analysis and immunofluorescence staining were utilized to evaluate the expression levels of related genes and proteins. DCFH-DA staining was adopted to visualize reactive oxidative species (ROS). RESULTS: FXR was distinctly downregulated in liver tissues of patients with steatosis compared to normal livers using the GEO database, and in ethanol-induced AML-12 cellular steatosis model. FXR overexpression ameliorated hepatic lipid metabolism disorder and steatosis induced by ethanol by inhibiting the expression of genes involved in lipid synthesis and inducing the expression of genes responsible for lipid metabolism. Besides, FXR overexpression inhibited ethanol-induced AIM2 inflammasome activation and alleviated oxidative stress and ROS production during ethanol-induced hepatic steatosis. However, when FXR was knocked down, the results were completely opposite. CONCLUSIONS: FXR attenuated lipid metabolism disorders and lipid degeneration in alcohol-caused liver injury and alleviated oxidative stress and inflammation by inhibiting AIM2 inflammasome activation.

Breast Cancer Incidence Among US Women Aged 20 to 49 Years by Race, Stage, and Hormone Receptor Status.

Importance: Breast cancer in young women has a less favorable prognosis compared with older women. Yet, comprehensive data on recent trends and how period and cohort effects may affect these trends among young women are not well-known. Objective: To evaluate breast cancer incidence among young women in the US over a 20-year period by race and ethnicity, hormone receptor status (estrogen receptor [ER] and progesterone receptor [PR]), tumor stage, and age at diagnosis, as well as how period and cohort effects may affect these trends. Design, Setting, and Participants: This cross-sectional study used data from Surveillance, Epidemiology, and End Results 17 registries (2000-2019). Women aged 20 to 49 years with a primary invasive breast cancer were included. Data were analyzed between February and June 2023. Main Outcomes and Measures: Age-standardized incidence rates (ASIR), incidence rate ratios (IRR), and average annual percent changes (AAPC) stratified by race and ethnicity, hormone receptor status, tumor stage, and age at diagnosis. Results: Out of 217 815 eligible women (1485 American Indian or Alaska Native [0.7%], 25 210 Asian or Pacific Islander [11.6%], 27 112 non-Hispanic Black [12.4%], 37 048 Hispanic [17.0%], 126 960 non-Hispanic White [58.3%]), the majority were diagnosed with an ER+/PR+ tumor (134 024 [61.5%]) and were diagnosed with a stage I tumor (81 793 [37.6%]). Overall, invasive breast cancer incidence increased (AAPC, 0.79; 95% CI, 0.42 to 1.15), with increasing trends across almost all racial and ethnic groups. ASIR increased for ER+/PR+ (AAPC, 2.72; 95% CI, 2.34 to 3.12) and ER+/PR- tumors (AAPC, 1.43; 95% CI, 1.00 to 1.87), and decreased for ER-/PR+ (AAPC, -3.25; 95% CI, -4.41 to -2.07) and ER-/PR- tumors (AAPC, -0.55; 95% CI, -1.68 to 0.60). For women aged 20 to 29 and 30 to 39 years, ASIRs were highest among non-Hispanic Black women (age 20-29 years: IRR, 1.53; 95% CI, 1.43 to 1.65; age 30-39 years: IRR, 1.15; 95% CI, 1.12 to 1.18). For women aged 40 to 49 years, ASIR was lower for non-Hispanic Black women (IRR, 0.96; 95% CI, 0.94 to 0.97) compared with non-Hispanic White women. Incidence rates increased for stages I and IV tumors but decreased for stage II and III tumors. Age-period-cohort analysis demonstrated both cohort and period effects on breast cancer incidence (P < .001). Conclusions and Relevance: In this population-based cross-sectional analysis, an increase in breast cancer incidence rates among young US women and age-related crossover between non-Hispanic White and Black women were observed. Prevention efforts in young women need to adopt a targeted approach to address racial disparities in incidence rates observed at different age phases.

Heparanase inhibitor OGT 2115 induces prostate cancer cell apoptosis via the downregulation of MCL­1.

Heparanase (HPSE), an endo-ß-D-glucuronidase, cleaves heparan sulfate and serves an important role in the tumor microenvironment and thus in tumorigenesis. HPSE is known to promote tumor cell evasion of apoptosis. However, the underlying mechanism of this requires further study. In the present study, the results demonstrated that myeloid cell leukemia-1 (MCL-1), an antiapoptotic protein, and HPSE were upregulated in prostate cancer tissues compared with adjacent normal tissues. In addition, the HPSE inhibitor, OGT 2115, inhibited PC-3 and DU-145 prostate cancer cell viability in a dose-dependent manner, with IC50 values of 20.2 and 97.2 µM, respectively. Furthermore, annexin V/PI double-staining assays demonstrated that OGT 2115 induced apoptosis in prostate cancer cells. OGT 2115 treatment markedly decreased MCL-1 protein expression levels, whereas RNA interference-mediated downregulation of MCL-1 and OGT 2115 drug treatment synergistically induced apoptosis in PC-3 and DU-145 cells. In vivo, OGT 2115 40 mg/kg (ig) significantly inhibited PC-3 cell xenograft growth in nude mice and increased the positive TUNEL staining rate of xenograft tissues. It was therefore hypothesized that MCL-1 was an important signaling molecule in OGT 2115-induced apoptosis. The results of the present study also demonstrated that the proteasome inhibitor, MG-132, markedly inhibited the downregulation of MCL-1 protein expression levels induced by OGT 2115. However, the protein synthesis inhibitor, cycloheximide, did not affect the role of OGT 2115 in regulating MCL-1. In summary, the results of the present study demonstrated that the proapoptotic activity of OGT 2115 was achieved by downregulating MCL-1.

Farnesoid X receptor overexpression prevents hepatic steatosis through inhibiting AIM2 inflammasome activation in nonalcoholic fatty liver disease.

Oxidative stress-mediated activation of inflammasome has a significant effect on the pathogenesis of nonalcoholic fatty liver disease (NAFLD). Farnesoid X receptor (NR1H4, FXR) has been implicated in biological function and many diseases, including NAFLD. The regulatory effect of FXR on oxidative stress and whether this process is related with the activation of absent melanoma 2 (AIM2) inflammasome in NAFLD remain unclear. In the present research, we confirmed that FXR in the livers of steatosis patients is significantly reduced compared with normal liver tissue by using the Gene Expression Omnibus (GEO) database and a palmitic acid (PA) - mediated steatosis model in AML-12 cells. Under the premise of ensuring the same food intake as the control group, overexpression of FXR in mice attenuated HFD-mediated weight gain and liver steatosis, facilitated lipid metabolism, improved fatty acid ß-oxidation, lipolysis, and reduced fatty acid synthesis and intake, which also inhibited the activation of AIM2 inflammasome. Overexpression of FXR alleviated PA-induced triglyceride (TG) accumulation, imbalance of lipid homeostasis, and the activation of AIM2 inflammasome in hepatic steatosis cells, while FXR knockdown appeared the opposite effects. FXR overexpression suppressed PA- and HFD-induced oxidative stress, but FXR siRNA demonstrated the opposite influence. The decreased ROS generation may be the reason why FXR weakens AIM2 activation when a fatty acid overload occurs. In conclusion, our results confirm that other than regulating lipid homeostasis and blocking NLRP3 inflammasome activation, FXR improves hepatic steatosis by a novel mechanism that inhibits oxidative stress and AIM2 inflammasome activation.

Enhanced thermophilic dark fermentation of hydrogen production from food waste by Fe-modified biochar.

The industrialization of hydrogen production through dark fermentation of food waste faces challenges, such as low yields and unpredictable fermentation processes. Biochar has emerged as a promising green additive to enhance hydrogen production in dark fermentation. Our study demonstrated that the introduction of Fe-modified biochar (Fe-L600) significantly boosted hydrogen production during thermophilic dark fermentation of food waste. The addition of Fe-L600 led to a remarkable 31.19% increase in hydrogen yield and shortened the time needed for achieving stabilization of hydrogen production from 18 h to 12 h. The metabolite analysis revealed an enhancement in the butyric acid pathway as the molar ratio of acetic acid to butyric acid decreased from 3.09 to 2.69 but hydrogen yield increased from 57.12 ± 1.48 to 76.78 ± 2.77 mL/g, indicating Fe-L600 improved hydrogen yield by regulating crucial metabolic pathways of hydrogen production. The addition of Fe-L600 also promoted the release of Fe2+ and Fe3+ and increased the concentrations of Fe2+ and Fe3+ in the fermentation system, which might promote the activity of hydrogenase and ferredoxin. Microbial community analysis indicated a substantial increase in the relative abundance of Thermoanaerobacterium after thermophilic dark fermentation. The relative abundances of microorganisms responsible for hydrolysis and acidogenesis were also observed to be improved in the system with Fe-L600 addition. This research provides a feasible strategy for improving hydrogen production of food waste and deepens the understanding of the mechanisms of biochar.

Outcomes of Robotic Versus Laparoscopic Pancreatoduodenectomy Following Learning Curves of Surgeons: A Multicenter Study on 2255 Patients.

OBJECTIVE: This study aimed to compare robotic pancreatoduodenectomy (RPD) with laparoscopic pancreatoduodenectomy (LPD) in operative and oncologic outcomes. BACKGROUND: Previous studies comparing RPD with LPD have only been carried out in small, single-center studies with variable quality. METHODS: Consecutive patients from nine centers in China who underwent RPD or LPD between 2015 and 2022 were included. A 1:1 propensity score matching (PSM) was used to minimize bias. RESULTS: Of the 2,255 patients, 1158 underwent RPD and 1097 underwent LPD. Following PSM, 1006 patients were enrolled in each group. The RPD group had significantly shorter operative time (270.0 vs. 305.0 minutes, P<0.001), lower intraoperative blood transfusion rate (5.9% vs. 12.0%, P<0.001), lower conversion rate (3.8% vs. 6.7%, P=0.004), and higher vascular reconstruction rate (7.9% vs. 5.6%, P=0.040) than the LPD group. There were no significant differences in estimated blood loss, postoperative length of stay, perioperative complications, and 90-day mortality. Patients who underwent vascular reconstruction had similar outcomes between the two groups, although they had significantly lower estimated blood loss (300.0 vs. 360.0 mL; P=0.021) in the RPD group. Subgroup analysis on pancreatic ductal adenocarcinoma (PDAC) found no significant differences between the two groups in median recurrence-free survival (14.3 vs. 15.3 mo, P=0.573) and overall survival (24.1 vs. 23.7 mo, P=0.710). CONCLUSIONS: In experienced hands, both RPD and LPD are safe and feasible procedures with similar surgical outcomes. RPD had the perioperative advantage over LPD especially in vascular reconstruction. For PDAC patients, RPD resulted in similar oncological and survival outcomes as LPD.

Survival outcomes of 2018 FIGO stage IIIC versus stages IIIA and IIIB in cervical cancer: A systematic review with meta-analysis.

OBJECTIVE: To assess the difference in survival outcomes between stage IIIC and stages IIIA and IIIB in the 2018 FIGO cervical cancer staging system. METHODS: The PubMed, EMBASE, MEDLINE and Web of Science were searched for articles published from November 1, 2018 to January 31, 2023. Articles published in English were considered. The included studies compared the survival outcomes of patients with cervical cancer in FIGO 2018 stage IIIC with those in stages IIIA and IIIB. Studies focused on rare histopathological types were excluded. The statistical analyses were performed using Stata 17 software. The endpoints were overall survival (OS) and progression-free survival (PFS). RESULTS: Ten retrospective cohort studies were eligible, involving 2113 (6.2%), 9812 (28.6%), 44 (0.1%), 10 171 (29.7%), 11 677 (34.1%) and 445 (1.3%) patients in stage IIIA, IIIB, IIIA&B, IIIC, IIIC1, and IIIC2, respectively. In the OS group, stage IIIC/C1 was significantly associated with superior survival compared with stage IIIA (hazard risk [HR] 0.62, 95% confidence interval [CI] 0.41-0.93, P = 0.022; I2 = 92.9%) and stage IIIB(A&B) (HR 0.56, 95% CI 0.44-0.71, P < 0.001; I2 = 94.0%). The FIGO 2018 stage IIIC2 was not associated with an increased mortality risk compared with stage IIIA and stage IIIB(A&B). In the PFS group, the outcome of FIGO 2018 stage IIIC/C1 was similar to stage IIIA (HR 0.66, 95% CI 0.27-1.64, P = 0.371; I2 = 65.6%), but better than stage IIIB(A&B) (HR 0.75, 95% CI 0.68-0.83, P < 0.001; I2 = 0.0%). The FIGO 2018 stage IIIC2 has similar PFS outcomes to stage IIIA and stage IIIB(A&B). CONCLUSION: Our findings demonstrate that survival outcomes of stage IIIC are no worse than those of stage IIIA and stage IIIB in the 2018 FIGO cervical cancer staging system. In cervical cancer, FIGO 2018 stage IIIC1 has significantly better OS outcomes than stage IIIA and stage IIIB.

Wireless broadband acousto-mechanical sensing system for continuous physiological monitoring.

The human body generates various forms of subtle, broadband acousto-mechanical signals that contain information on cardiorespiratory and gastrointestinal health with potential application for continuous physiological monitoring. Existing device options, ranging from digital stethoscopes to inertial measurement units, offer useful capabilities but have disadvantages such as restricted measurement locations that prevent continuous, longitudinal tracking and that constrain their use to controlled environments. Here we present a wireless, broadband acousto-mechanical sensing network that circumvents these limitations and provides information on processes including slow movements within the body, digestive activity, respiratory sounds and cardiac cycles, all with clinical grade accuracy and independent of artifacts from ambient sounds. This system can also perform spatiotemporal mapping of the dynamics of gastrointestinal processes and airflow into and out of the lungs. To demonstrate the capabilities of this system we used it to monitor constrained respiratory airflow and intestinal motility in neonates in the neonatal intensive care unit (n = 15), and to assess regional lung function in patients undergoing thoracic surgery (n = 55). This broadband acousto-mechanical sensing system holds the potential to help mitigate cardiorespiratory instability and manage disease progression in patients through continuous monitoring of physiological signals, in both the clinical and nonclinical setting.

Lasso Analysis of Gait Characteristics and Correlation with Spinopelvic Parameters in Patients with Degenerative Lumbar Scoliosis.

PURPOSE: This study quantifies the gait characteristics of patients with degenerative lumbar scoliosis (DLS) and patients with simple lumbar spinal stenosis (LSS) by means of a three-dimensional gait analysis system, aiming to determine the image of spinal deformity on gait and the correlation between spinal-pelvic parameters and gait characteristics in patients with DLS to assist clinical work. METHODS: From June 2020 to December 2021, a total of 50 subjects were enrolled in this study, of whom 20 patients with DLS served as the case group and 30 middle-aged and elderly patients with LSS were selected as the control group according to the general conditions (sex, age, and BMI) of the case group. Spinal-pelvic parameters were measured by full-length frontal and lateral spine films one week before surgery, and kinematics were recorded on the same day using a gait analysis system. RESULTS: Compared to the control group, DLS patients exhibited significantly reduced velocity and cadence; gait variability and symmetry of both lower limbs were notably better in the LSS group than in the DLS group; joint ROM (range of motion) across multiple dimensions was also lower in the DLS group; and correlation analysis revealed that patients with a larger Cobb angle, T1PA, and higher CSVA tended to walk more slowly, and those with a larger PI, PT, and LL usually had smaller stride lengths. The greater the PI-SS mismatch, the longer the patient stayed in the support phase. Furthermore, a larger Cobb angle correlated with worse coronal hip mobility. CONCLUSIONS: DLS patients demonstrate distinctive gait abnormalities and reduced hip mobility compared to LSS patients. Significant correlations between crucial spinopelvic parameters and these gait changes underline their potential influence on gait disturbances in DLS. Our study identifies a Cobb angle cut-off of 16.1 as a key predictor for gait abnormalities. These insights can guide personalized treatment and intervention strategies, ultimately improving the quality of life for DLS patients.

Development and validation of web calculators to predict early recurrence and long-term survival in patients with duodenal papilla carcinoma after pancreaticoduodenectomy.

BACKGROUND: Duodenal papilla carcinoma (DPC) is prone to relapse even after radical pancreaticoduodenectomy (PD) (including robotic, laparoscopic and open approach). This study aimed to develop web calculators to predict early recurrence (ER) (within two years after surgery) and long-term survival in patients with DPC after PD. METHODS: Patients with DPC after radical PD were included. Univariate and multivariate logistic regression analyses were used to identify independent risk factors. Two web calculators were developed based on independent risk factors in the training cohort and then tested in the validation cohort. RESULTS: Of the 251 patients who met the inclusion criteria, 180 and 71 patients were enrolled in the training and validation cohorts, respectively. Multivariate logistic regression analysis revealed that tumor size [Odds Ratio (OR) 1.386; 95% confidence interval (CI) 1070-1.797; P = 0.014]; number of lymph node metastasis (OR 2.535; 95% CI 1.114-5.769; P = 0.027), perineural invasion (OR 3.078; 95% CI 1.147-8.257; P = 0.026), and tumor differentiation (OR 3.552; 95% CI 1.132-11.152; P = 0.030) were independent risk factors for ER. Nomogram based on the above four factors achieved good C-statistics of 0.759 and 0.729 in predicting ER in the training and the validation cohorts, respectively. Time-dependent ROC analysis (timeROC) and decision curve analysis (DCA) revealed that the nomogram provided superior diagnostic capacity and net benefit compared with single variable. CONCLUSIONS: This study developed and validated two web calculators that can predict ER and long-term survival in patients with DPC with high degree of stability and accuracy.

Multiomics dynamic learning enables personalized diagnosis and prognosis for pancancer and cancer subtypes.

Artificial intelligence (AI) approaches in cancer analysis typically utilize a 'one-size-fits-all' methodology characterizing average patient responses. This manner neglects the diverse conditions in the pancancer and cancer subtypes of individual patients, resulting in suboptimal outcomes in diagnosis and treatment. To overcome this limitation, we shift from a blanket application of statistics to a focus on the explicit recognition of patient-specific abnormalities. Our objective is to use multiomics data to empower clinicians with personalized molecular descriptions that allow for customized diagnosis and interventions. Here, we propose a highly trustworthy multiomics learning (HTML) framework that employs multiomics self-adaptive dynamic learning to process each sample with data-dependent architectures and computational flows, ensuring personalized and trustworthy patient-centering of cancer diagnosis and prognosis. Extensive testing on a 33-type pancancer dataset and 12 cancer subtype datasets underscored the superior performance of HTML compared with static-architecture-based methods. Our findings also highlighting the potential of HTML in elucidating complex biological pathogenesis and paving the way for improved patient-specific care in cancer treatment.

Anesthesia methods for full-endoscopic lumbar discectomy: a review.

Full-endoscopic lumbar discectomy under local anesthesia is major trends for the treatment of lumbar disc herniation in spine minimally invasive surgery. However, sometimes local anesthesia is not enough for analgesic in surgery especially in interlaminar approach. This study summarizes the current study of anesthesia methods in full-endoscopic lumbar discectomy. Local anesthesia is still the most common anesthesia method in full-endoscopic lumbar discectomy and the comparison group for other anesthesia methods due to high safety. Compared to local anesthesia, Epidural anesthesia is less applied in full-endoscopic lumbar discectomy but reports better intraoperative pain control and equivalent safety due to the motor preservation and pain block characteristic of ropivacaine. General anesthesia can achieve totally pain block during surgery but nerve injury can not be ignored, and intraoperative neuromonitoring can assist. Regional anesthesia application is rare but also reports better anesthesia effects during surgery and equivalent safety. Anesthesia methods for full-endoscopic lumbar discectomy should be based on patient factors, surgical factors, and anesthesiologist factors to achieve satisfactory anesthesia experience and successful surgery.

Integrating genomics and proteomics data to identify candidate plasma biomarkers for lung cancer risk among European descendants.

BACKGROUND: Plasma proteins are potential biomarkers for complex diseases. We aimed to identify plasma protein biomarkers for lung cancer. METHODS: We investigated genetically predicted plasma levels of 1130 proteins in association with lung cancer risk among 29,266 cases and 56,450 controls of European descent. For proteins significantly associated with lung cancer risk, we evaluated associations of genetically predicted expression of their coding genes with the risk of lung cancer. RESULTS: Nine proteins were identified with genetically predicted plasma levels significantly associated with overall lung cancer risk at a false discovery rate (FDR) of <0.05. Proteins C2, MICA, AIF1, and CTSH were associated with increased lung cancer risk, while proteins SFTPB, HLA-DQA2, MICB, NRP1, and GMFG were associated with decreased lung cancer risk. Stratified analyses by histological types revealed the cross-subtype consistency of these nine associations and identified an additional protein, ICAM5, significantly associated with lung adenocarcinoma risk (FDR < 0.05). Coding genes of NRP1 and ICAM5 proteins are located at two loci that have never been reported by previous GWAS. Genetically predicted blood levels of genes C2, AIF1, and CTSH were associated with lung cancer risk, in directions consistent with those shown in protein-level analyses. CONCLUSION: Identification of novel plasma protein biomarkers provided new insights into the biology of lung cancer.